The importance of expressing antimicrobial agents on water basis in growth/no growth interface models: a case study for Zygosaccharomyces bailii.

PubMed

Dang, T D T; Vermeulen, A; Mertens, L; Geeraerd, A H; Van Impe, J F; Devlieghere, F

2011-01-31

In a previous study on Zygosaccharomyces bailii, three growth/no growth models have been developed, predicting growth probability of the yeast at different conditions typical for acidified foods (Dang, T.D.T., Mertens, L., Vermeulen, A., Geeraerd, A.H., Van Impe, J.F., Debevere, J., Devlieghere, F., 2010. Modeling the growth/no growth boundary of Z. bailii in acidic conditions: A contribution to the alternative method to preserve foods without using chemical preservatives. International Journal of Food Microbiology 137, 1-12). In these broth-based models, the variables were pH, water activity and acetic acid, with acetic acid concentration expressed in volume % on the total culture medium (i.e., broth). To continue the previous study, validation experiments were performed for 15 selected combinations of intrinsic factors to assess the performance of the model at 22°C (60days) in a real food product (ketchup). Although the majority of experimental results were consistent, some remarkable deviations between prediction and validation were observed, e.g., Z. bailii growth occurred in conditions where almost no growth had been predicted. A thorough investigation revealed that the difference between two ways of expressing acetic acid concentration (i.e., on broth basis and on water basis) is rather significant, particularly for media containing high amounts of dry matter. Consequently, the use of broth-based concentrations in the models was not appropriate. Three models with acetic acid concentration expressed on water basis were established and it was observed that predictions by these models well matched the validation results; therefore a "systematic error" in broth-based models was recognized. In practice, quantities of antimicrobial agents are often calculated based on the water content of food products. Hence, to assure reliable predictions and facilitate the application of models (developed from lab media with high dry matter contents), it is important to express antimicrobial agents' concentrations on a common basis-the water content. Reviews over other published growth/no growth models in literature are carried out and expressions of the stress factors' concentrations (on broth basis) found in these models confirm this finding. Copyright © 2010 Elsevier B.V. All rights reserved.

The AFIS tree growth model for updating annual forest inventories in Minnesota

Treesearch

Margaret R. Holdaway

2000-01-01

As the Forest Service moves towards annual inventories, states may use model predictions of growth to update unmeasured plots. A tree growth model (AFIS) based on the scaled Weibull function and using the average-adjusted model form is presented. Annual diameter growth for four species was modeled using undisturbed plots from Minnesota's Aspen-Birch and Northern...

Discrete statistical model of fatigue crack growth in a Ni-base superalloy, capable of life prediction

NASA Astrophysics Data System (ADS)

Boyd-Lee, Ashley; King, Julia

1992-07-01

A discrete statistical model of fatigue crack growth in a nickel base superalloy Waspaloy, which is quantitative from the start of the short crack regime to failure, is presented. Instantaneous crack growth rate distributions and persistence of arrest distributions are used to compute fatigue lives and worst case scenarios without extrapolation. The basis of the model is non-material specific, it provides an improved method of analyzing crack growth rate data. For Waspaloy, the model shows the importance of good bulk fatigue crack growth resistance to resist early short fatigue crack growth and the importance of maximizing crack arrest both by the presence of a proportion of small grains and by maximizing grain boundary corrugation.

Exponential growth kinetics for Polyporus versicolor and Pleurotus ostreatus in submerged culture

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

Carroad, P.A.; Wilke, C.R.

1977-04-01

Simple mathematical models for a batch culture of pellet-forming fungi in submerged culture were tested on growth data for Polyporus versicolor (ATCC 12679) and Pleurotus ostreatus (ATCC 9415). A kinetic model based on a growth rate proportional to the two-thirds power of the cell mass was shown to be satisfactory. A model based on a growth rate directly proportional to the cell mass fitted the data equally well, however, and may be preferable because of mathematical simplicity.

A structure-based extracellular matrix expansion mechanism of fibrous tissue growth

PubMed Central

Kalson, Nicholas S; Lu, Yinhui; Taylor, Susan H; Starborg, Tobias; Holmes, David F; Kadler, Karl E

2015-01-01

Embryonic growth occurs predominately by an increase in cell number; little is known about growth mechanisms later in development when fibrous tissues account for the bulk of adult vertebrate mass. We present a model for fibrous tissue growth based on 3D-electron microscopy of mouse tendon. We show that the number of collagen fibrils increases during embryonic development and then remains constant during postnatal growth. Embryonic growth was explained predominately by increases in fibril number and length. Postnatal growth arose predominately from increases in fibril length and diameter. A helical crimp structure was established in embryogenesis, and persisted postnatally. The data support a model where the shape and size of tendon is determined by the number and position of embryonic fibroblasts. The collagen fibrils that these cells synthesise provide a template for postnatal growth by structure-based matrix expansion. The model has important implications for growth of other fibrous tissues and fibrosis. DOI: http://dx.doi.org/10.7554/eLife.05958.001 PMID:25992598

Development and corroboration of a bioenergetics model for northern pikeminnow (Ptychocheilus oregonensis) feeding on juvenile salmonids in the Columbia River

USGS Publications Warehouse

Petersen, J.H.; Ward, D.L.

1999-01-01

A bioenergetics model was developed and corroborated for northern pikeminnow Ptychocheilus oregonensis, an important predator on juvenile salmonids in the Pacific Northwest. Predictions of modeled predation rate on salmonids were compared with field data from three areas of John Day Reservoir (Columbia River). To make bioenergetics model estimates of predation rate, three methods were used to approximate the change in mass of average predators during 30-d growth periods: observed change in mass between the first and the second month, predicted change in mass calculated with seasonal growth rates, and predicted change in mass based on an annual growth model. For all reservoir areas combined, bioenergetics model predictions of predation on salmon were 19% lower than field estimates based on observed masses, 45% lower than estimates based on seasonal growth rates, and 15% lower than estimates based on the annual growth model. For each growth approach, the largest differences in field-versus-model predation occurred at the midreservoir area (-84% to -67% difference). Model predictions of the rate of predation on salmonids were examined for sensitivity to parameter variation, swimming speed, sampling bias caused by gear selectivity, and asymmetric size distributions of predators. The specific daily growth rate of northern pikeminnow predicted by the model was highest in July and October and decreased during August. The bioenergetics model for northern pikeminnow performed well compared with models for other fish species that have been tested with field data. This model should be a useful tool for evaluating management actions such as predator removal, examining the influence of temperature on predation rates, and exploring interactions between predators in the Columbia River basin.

A nonparametric analysis of plot basal area growth using tree based models

Treesearch

G. L. Gadbury; H. K. lyer; H. T. Schreuder; C. Y. Ueng

1997-01-01

Tree based statistical models can be used to investigate data structure and predict future observations. We used nonparametric and nonlinear models to reexamine the data sets on tree growth used by Bechtold et al. (1991) and Ruark et al. (1991). The growth data were collected by Forest Inventory and Analysis (FIA) teams from 1962 to 1972 (4th cycle) and 1972 to 1982 (...

Coupling urban growth scenarios with nearshore biophysical change models to inform coastal restoration planning in Puget Sound, Washington

NASA Astrophysics Data System (ADS)

Byrd, K. B.; Kreitler, J.; Labiosa, W.

2010-12-01

A scenario represents an account of a plausible future given logical assumptions about how conditions change over discrete bounds of space and time. Development of multiple scenarios provides a means to identify alternative directions of urban growth that account for a range of uncertainty in human behavior. Interactions between human and natural processes may be studied by coupling urban growth scenario outputs with biophysical change models; if growth scenarios encompass a sufficient range of alternative futures, scenario assumptions serve to constrain the uncertainty of biophysical models. Spatially explicit urban growth models (map-based) produce output such as distributions and densities of residential or commercial development in a GIS format that can serve as input to other models. Successful fusion of growth model outputs with other model inputs requires that both models strategically address questions of interest, incorporate ecological feedbacks, and minimize error. The U.S. Geological Survey (USGS) Puget Sound Ecosystem Portfolio Model (PSEPM) is a decision-support tool that supports land use and restoration planning in Puget Sound, Washington, a 35,500 sq. km region. The PSEPM couples future scenarios of urban growth with statistical, process-based and rule-based models of nearshore biophysical changes and ecosystem services. By using a multi-criteria approach, the PSEPM identifies cross-system and cumulative threats to the nearshore environment plus opportunities for conservation and restoration. Sub-models that predict changes in nearshore biophysical condition were developed and existing models were integrated to evaluate three growth scenarios: 1) Status Quo, 2) Managed Growth, and 3) Unconstrained Growth. These decadal scenarios were developed and projected out to 2060 at Oregon State University using the GIS-based ENVISION model. Given land management decisions and policies under each growth scenario, the sub-models predicted changes in 1) fecal coliform in shellfish growing areas, 2) sediment supply to beaches, 3) State beach recreational visits, 4) eelgrass habitat suitability, 5) forage fish habitat suitability, and 6) nutrient loadings. In some cases thousands of shoreline units were evaluated with multiple predictive models, creating a need for streamlined and consistent database development and data processing. Model development over multiple disciplines demonstrated the challenge of merging data types from multiple sources that were inconsistent in spatial and temporal resolution, classification schemes, and topology. Misalignment of data in space and time created potential for error and misinterpretation of results. This effort revealed that the fusion of growth scenarios and biophysical models requires an up-front iterative adjustment of both scenarios and models so that growth model outputs provide the needed input data in the correct format. Successful design of data flow across models that includes feedbacks between human and ecological systems was found to enhance the use of the final data product for decision making.

HUMAN BODY SHAPE INDEX BASED ON AN EXPERIMENTALLY DERIVED MODEL OF HUMAN GROWTH

PubMed Central

Lebiedowska, Maria K.; Alter, Katharine E.; Stanhope, Steven J.

2009-01-01

Objectives To test the assumption of geometrically similar growth by developing experimentally derived models of human body growth during the age interval of 5–18 years; to use the derived growth models to establish a new Human Body Shape Index (HBSI) based on natural age related changes in HBS; and to compare various metrics of relative body weight (body mass index, ponderal index, HBSI) in a sample of 5–18 year old children. Study design Non-disabled Polish children (N=847) participated in this descriptive study. To model growth, the best fit between body height (H) and body mass (M) was calculated for each sex with the allometric equation M= miHχ. HBSI and HBSI were calculated separately for girls and boys, using sex-specific values for χ and a general HBSI from combined data. The customary body mass and ponderal indices were calculated and compared to HBSI values. Results The models of growth were M=13.11H2.84 (R2=.90) and M=13.64H2.68 (R2=.91) for girls and boys respectively. HBSI values contained less inherent variability and were influenced least by growth (age and height) than customary indices. Conclusion Age-related growth during childhood is sex-specific and not geometrically similar. Therefore, indices of human body shape formulated from experimentally derived models of human growth are superior to customary geometric similarity-based indices for the characterization of human body shape in children during the formative growth years. PMID:18154897

Human body shape index based on an experimentally derived model of human growth.

PubMed

Lebiedowska, Maria K; Alter, Katharine E; Stanhope, Steven J

2008-01-01

To test the assumption of geometrically similar growth by developing experimentally derived models of human body growth during the age interval of 5 to 18 years; to use these derived growth models to establish a new human body shape index (HBSI) based on natural age-related changes in human body shape (HBS); and to compare various metrics of relative body weight (body mass index [BMI], ponderal index [PI], and HBSI) in a sample of 5- to 18-year-old children. Nondisabled Polish children (n = 847) participated in this descriptive study. To model growth, the best fit between body height (H) and body mass (M) was calculated for each sex using the allometric equation M = m(i) H(chi). HBSI was calculated separately for girls and boys, using sex-specific values for chi and a general HBSI from combined data. The customary BMI and PI were calculated and compared with HBSI values. The models of growth were M = 13.11H(2.84) (R2 = 0.90) for girls and M = 13.64H(2.68) (R2 = 0.91) for boys. HBSI values contained less inherent variability and were less influenced by growth (age and height) compared with BMI and PI. Age-related growth during childhood is sex-specific and not geometrically similar. Therefore, indices of HBS formulated from experimentally derived models of human growth are superior to customary geometric similarity-based indices for characterizing HBS in children during the formative growth years.

The review of dynamic monitoring technology for crop growth

NASA Astrophysics Data System (ADS)

Zhang, Hong-wei; Chen, Huai-liang; Zou, Chun-hui; Yu, Wei-dong

2010-10-01

In this paper, crop growth monitoring methods are described elaborately. The crop growth models, Netherlands-Wageningen model system, the United States-GOSSYM model and CERES models, Australia APSIM model and CCSODS model system in China, are introduced here more focus on the theories of mechanism, applications, etc. The methods and application of remote sensing monitoring methods, which based on leaf area index (LAI) and biomass were proposed by different scholars at home and abroad, are highly stressed in the paper. The monitoring methods of remote sensing coupling with crop growth models are talked out at large, including the method of "forced law" which using remote sensing retrieval state parameters as the crop growth model parameters input, and then to enhance the dynamic simulation accuracy of crop growth model and the method of "assimilation of Law" which by reducing the gap difference between the value of remote sensing retrieval and the simulated values of crop growth model and thus to estimate the initial value or parameter values to increasing the simulation accuracy. At last, the developing trend of monitoring methods are proposed based on the advantages and shortcomings in previous studies, it is assured that the combination of remote sensing with moderate resolution data of FY-3A, MODIS, etc., crop growth model, "3S" system and observation in situ are the main methods in refinement of dynamic monitoring and quantitative assessment techniques for crop growth in future.

An individual-based simulation model for mottled sculpin (Cottus bairdi) in a southern Appalachian stream

Treesearch

Brenda Rashleigh; Gary D. Grossman

2005-01-01

We describe and analyze a spatially explicit, individual-based model for the local population dynamics of mottled sculpin (Cottus bairdi). The model simulated daily growth, mortality, movement and spawning of individuals within a reach of stream. Juvenile and adult growth was based on consumption bioenergetics of benthic macroinvertebrate prey;...

Unified Plant Growth Model (UPGM). 1. Background, objectives, and vision.

USDA-ARS?s Scientific Manuscript database

Since the development of the Environmental Policy Integrated Climate (EPIC) model in 1988, the EPIC-based plant growth code has been incorporated and modified into many agro-ecosystem models. The goals of the Unified Plant Growth Model (UPGM) project are: 1) integrating into one platform the enhance...

Identification of growth phases and influencing factors in cultivations with AGE1.HN cells using set-based methods.

PubMed

Borchers, Steffen; Freund, Susann; Rath, Alexander; Streif, Stefan; Reichl, Udo; Findeisen, Rolf

2013-01-01

Production of bio-pharmaceuticals in cell culture, such as mammalian cells, is challenging. Mathematical models can provide support to the analysis, optimization, and the operation of production processes. In particular, unstructured models are suited for these purposes, since they can be tailored to particular process conditions. To this end, growth phases and the most relevant factors influencing cell growth and product formation have to be identified. Due to noisy and erroneous experimental data, unknown kinetic parameters, and the large number of combinations of influencing factors, currently there are only limited structured approaches to tackle these issues. We outline a structured set-based approach to identify different growth phases and the factors influencing cell growth and metabolism. To this end, measurement uncertainties are taken explicitly into account to bound the time-dependent specific growth rate based on the observed increase of the cell concentration. Based on the bounds on the specific growth rate, we can identify qualitatively different growth phases and (in-)validate hypotheses on the factors influencing cell growth and metabolism. We apply the approach to a mammalian suspension cell line (AGE1.HN). We show that growth in batch culture can be divided into two main growth phases. The initial phase is characterized by exponential growth dynamics, which can be described consistently by a relatively simple unstructured and segregated model. The subsequent phase is characterized by a decrease in the specific growth rate, which, as shown, results from substrate limitation and the pH of the medium. An extended model is provided which describes the observed dynamics of cell growth and main metabolites, and the corresponding kinetic parameters as well as their confidence intervals are estimated. The study is complemented by an uncertainty and outlier analysis. Overall, we demonstrate utility of set-based methods for analyzing cell growth and metabolism under conditions of uncertainty.

Identification of Growth Phases and Influencing Factors in Cultivations with AGE1.HN Cells Using Set-Based Methods

PubMed Central

Borchers, Steffen; Freund, Susann; Rath, Alexander; Streif, Stefan; Reichl, Udo; Findeisen, Rolf

2013-01-01

Production of bio-pharmaceuticals in cell culture, such as mammalian cells, is challenging. Mathematical models can provide support to the analysis, optimization, and the operation of production processes. In particular, unstructured models are suited for these purposes, since they can be tailored to particular process conditions. To this end, growth phases and the most relevant factors influencing cell growth and product formation have to be identified. Due to noisy and erroneous experimental data, unknown kinetic parameters, and the large number of combinations of influencing factors, currently there are only limited structured approaches to tackle these issues. We outline a structured set-based approach to identify different growth phases and the factors influencing cell growth and metabolism. To this end, measurement uncertainties are taken explicitly into account to bound the time-dependent specific growth rate based on the observed increase of the cell concentration. Based on the bounds on the specific growth rate, we can identify qualitatively different growth phases and (in-)validate hypotheses on the factors influencing cell growth and metabolism. We apply the approach to a mammalian suspension cell line (AGE1.HN). We show that growth in batch culture can be divided into two main growth phases. The initial phase is characterized by exponential growth dynamics, which can be described consistently by a relatively simple unstructured and segregated model. The subsequent phase is characterized by a decrease in the specific growth rate, which, as shown, results from substrate limitation and the pH of the medium. An extended model is provided which describes the observed dynamics of cell growth and main metabolites, and the corresponding kinetic parameters as well as their confidence intervals are estimated. The study is complemented by an uncertainty and outlier analysis. Overall, we demonstrate utility of set-based methods for analyzing cell growth and metabolism under conditions of uncertainty. PMID:23936299

A brief dataset on the model-based evaluation of the growth performance of Bacillus coagulans and l-lactic acid production in a lignin-supplemented medium.

PubMed

Glaser, Robert; Venus, Joachim

2017-04-01

The data presented in this article are related to the research article entitled "Model-based characterization of growth performance and l-lactic acid production with high optical purity by thermophilic Bacillus coagulans in a lignin-supplemented mixed substrate medium (R. Glaser and J. Venus, 2016) [1]". This data survey provides the information on characterization of three Bacillus coagulans strains. Information on cofermentation of lignocellulose-related sugars in lignin-containing media is given. Basic characterization data are supported by optical-density high-throughput screening and parameter adjustment to logistic growth models. Lab scale fermentation procedures are examined by model adjustment of a Monod kinetics-based growth model. Lignin consumption is analyzed using the data on decolorization of a lignin-supplemented minimal medium.

Constraints based analysis of extended cybernetic models.

PubMed

Mandli, Aravinda R; Venkatesh, Kareenhalli V; Modak, Jayant M

2015-11-01

The cybernetic modeling framework provides an interesting approach to model the regulatory phenomena occurring in microorganisms. In the present work, we adopt a constraints based approach to analyze the nonlinear behavior of the extended equations of the cybernetic model. We first show that the cybernetic model exhibits linear growth behavior under the constraint of no resource allocation for the induction of the key enzyme. We then quantify the maximum achievable specific growth rate of microorganisms on mixtures of substitutable substrates under various kinds of regulation and show its use in gaining an understanding of the regulatory strategies of microorganisms. Finally, we show that Saccharomyces cerevisiae exhibits suboptimal dynamic growth with a long diauxic lag phase when growing on a mixture of glucose and galactose and discuss on its potential to achieve optimal growth with a significantly reduced diauxic lag period. The analysis carried out in the present study illustrates the utility of adopting a constraints based approach to understand the dynamic growth strategies of microorganisms. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

A structurally based analytic model of growth and biomass dynamics in single species stands of conifers

Treesearch

Robin J. Tausch

2015-01-01

A theoretically based analytic model of plant growth in single species conifer communities based on the species fully occupying a site and fully using the site resources is introduced. Model derivations result in a single equation simultaneously describes changes over both, different site conditions (or resources available), and over time for each variable for each...

Kinetic modelling of starch and lipid formation during mixotrophic, nutrient-limited microalgal growth.

PubMed

Figueroa-Torres, Gonzalo M; Pittman, Jon K; Theodoropoulos, Constantinos

2017-10-01

Microalgal starch and lipids, carbon-based storage molecules, are useful as potential biofuel feedstocks. In this work, cultivation strategies maximising starch and lipid formation were established by developing a multi-parameter kinetic model describing microalgal growth as well as starch and lipid formation, in conjunction with laboratory-scale experiments. Growth dynamics are driven by nitrogen-limited mixotrophic conditions, known to increase cellular starch and lipid contents whilst enhancing biomass growth. Model parameters were computed by fitting model outputs to a range of experimental datasets from batch cultures of Chlamydomonas reinhardtii. Predictive capabilities of the model were established against different experimental data. The model was subsequently used to compute optimal nutrient-based cultivation strategies in terms of initial nitrogen and carbon concentrations. Model-based optimal strategies yielded a significant increase of 261% for starch (0.065gCL -1 ) and 66% for lipid (0.08gCL -1 ) production compared to base-case conditions (0.018gCL -1 starch, 0.048gCL -1 lipids). Copyright © 2017 Elsevier Ltd. All rights reserved.

AN INDIVIDUAL-BASED SIMULATION MODEL FOR MOTTLED SCULPIN (COTTUS BAIRDI) IN A SOUTHERN APPALACHIAN STREAM

EPA Science Inventory

We describe and analyze a spatially explicit, individual-based model for the local population dynamics of mottled sculpin (Cottus bairdi). The model simulated daily growth, mortality, movement and spawning of individuals within a reach of stream. Juvenile and adult growth was bas...

United States geological survey's reserve-growth models and their implementation

USGS Publications Warehouse

Klett, T.R.

2005-01-01

The USGS has developed several mathematical models to forecast reserve growth of fields both in the United States (U.S.) and the world. The models are based on historical reserve growth patterns of fields in the U.S. The patterns of past reserve growth are extrapolated to forecast future reserve growth. Changes of individual field sizes through time are extremely variable, therefore, the reserve growth models take on a statistical approach whereby volumetric changes for populations of fields are used in the models. Field age serves as a measure of the field-development effort that is applied to promote reserve growth. At the time of the USGS World Petroleum Assessment 2000, a reserve growth model for discovered fields of the world was not available. Reserve growth forecasts, therefore, were made based on a model of historical reserve growth of fields of the U.S. To test the feasibility of such an application, reserve growth forecasts were made of 186 giant oil fields of the world (excluding the U.S. and Canada). In addition, forecasts were made for these giant oil fields subdivided into those located in and outside of Organization of Petroleum Exporting Countries (OPEC). The model provided a reserve-growth forecast that closely matched the actual reserve growth that occurred from 1981 through 1996 for the 186 fields as a whole, as well as for both OPEC and non-OPEC subdivisions, despite the differences in reserves definition among the fields of the U.S. and the rest of the world. ?? 2005 International Association for Mathematical Geology.

Modelling spatio-temporal variability of Mytilus edulis (L.) growth by forcing a dynamic energy budget model with satellite-derived environmental data

NASA Astrophysics Data System (ADS)

Thomas, Yoann; Mazurié, Joseph; Alunno-Bruscia, Marianne; Bacher, Cédric; Bouget, Jean-François; Gohin, Francis; Pouvreau, Stéphane; Struski, Caroline

2011-11-01

In order to assess the potential of various marine ecosystems for shellfish aquaculture and to evaluate their carrying capacities, there is a need to clarify the response of exploited species to environmental variations using robust ecophysiological models and available environmental data. For a large range of applications and comparison purposes, a non-specific approach based on 'generic' individual growth models offers many advantages. In this context, we simulated the response of blue mussel ( Mytilus edulis L.) to the spatio-temporal fluctuations of the environment in Mont Saint-Michel Bay (North Brittany) by forcing a generic growth model based on Dynamic Energy Budgets with satellite-derived environmental data (i.e. temperature and food). After a calibration step based on data from mussel growth surveys, the model was applied over nine years on a large area covering the entire bay. These simulations provide an evaluation of the spatio-temporal variability in mussel growth and also show the ability of the DEB model to integrate satellite-derived data and to predict spatial and temporal growth variability of mussels. Observed seasonal, inter-annual and spatial growth variations are well simulated. The large-scale application highlights the strong link between food and mussel growth. The methodology described in this study may be considered as a suitable approach to account for environmental effects (food and temperature variations) on physiological responses (growth and reproduction) of filter feeders in varying environments. Such physiological responses may then be useful for evaluating the suitability of coastal ecosystems for shellfish aquaculture.

A mathematical model of microalgae growth in cylindrical photobioreactor

NASA Astrophysics Data System (ADS)

Bakeri, Noorhadila Mohd; Jamaian, Siti Suhana

2017-08-01

Microalgae are unicellular organisms, which exist individually or in chains or groups but can be utilized in many applications. Researchers have done various efforts in order to increase the growth rate of microalgae. Microalgae have a potential as an effective tool for wastewater treatment, besides as a replacement for natural fuel such as coal and biodiesel. The growth of microalgae can be estimated by using Geider model, which this model is based on photosynthesis irradiance curve (PI-curve) and focused on flat panel photobioreactor. Therefore, in this study a mathematical model for microalgae growth in cylindrical photobioreactor is proposed based on the Geider model. The light irradiance is the crucial part that affects the growth rate of microalgae. The absorbed photon flux will be determined by calculating the average light irradiance in a cylindrical system illuminated by unidirectional parallel flux and considering the cylinder as a collection of differential parallelepipeds. Results from this study showed that the specific growth rate of microalgae increases until the constant level is achieved. Therefore, the proposed mathematical model can be used to estimate the rate of microalgae growth in cylindrical photobioreactor.

Unified risk analysis of fatigue failure in ductile alloy components during all three stages of fatigue crack evolution process.

PubMed

Patankar, Ravindra

2003-10-01

Statistical fatigue life of a ductile alloy specimen is traditionally divided into three stages, namely, crack nucleation, small crack growth, and large crack growth. Crack nucleation and small crack growth show a wide variation and hence a big spread on cycles versus crack length graph. Relatively, large crack growth shows a lesser variation. Therefore, different models are fitted to the different stages of the fatigue evolution process, thus treating different stages as different phenomena. With these independent models, it is impossible to predict one phenomenon based on the information available about the other phenomenon. Experimentally, it is easier to carry out crack length measurements of large cracks compared to nucleating cracks and small cracks. Thus, it is easier to collect statistical data for large crack growth compared to the painstaking effort it would take to collect statistical data for crack nucleation and small crack growth. This article presents a fracture mechanics-based stochastic model of fatigue crack growth in ductile alloys that are commonly encountered in mechanical structures and machine components. The model has been validated by Ray (1998) for crack propagation by various statistical fatigue data. Based on the model, this article proposes a technique to predict statistical information of fatigue crack nucleation and small crack growth properties that uses the statistical properties of large crack growth under constant amplitude stress excitation. The statistical properties of large crack growth under constant amplitude stress excitation can be obtained via experiments.

Partitioning the Uncertainty in Estimates of Mean Basal Area Obtained from 10-year Diameter Growth Model Predictions

Treesearch

Ronald E. McRoberts

2005-01-01

Uncertainty in model-based predictions of individual tree diameter growth is attributed to three sources: measurement error for predictor variables, residual variability around model predictions, and uncertainty in model parameter estimates. Monte Carlo simulations are used to propagate the uncertainty from the three sources through a set of diameter growth models to...

Modelling the role of surface stress on the kinetics of tissue growth in confined geometries.

PubMed

Gamsjäger, E; Bidan, C M; Fischer, F D; Fratzl, P; Dunlop, J W C

2013-03-01

In a previous paper we presented a theoretical framework to describe tissue growth in confined geometries based on the work of Ambrosi and Guillou [Ambrosi D, Guillou A. Growth and dissipation in biological tissues. Cont Mech Thermodyn 2007;19:245-51]. A thermodynamically consistent eigenstrain rate for growth was derived using the concept of configurational forces and used to investigate growth in holes of cylindrical geometries. Tissue growing from concave surfaces can be described by a model based on this theory. However, an apparently asymmetric behaviour between growth from convex and concave surfaces has been observed experimentally, but is not predicted by this model. This contradiction is likely to be due to the presence of contractile tensile stresses produced by cells near the tissue surface. In this contribution we extend the model in order to couple tissue growth to the presence of a surface stress. This refined growth model is solved for two geometries, within a cylindrical hole and on the outer surface of a cylinder, thus demonstrating how surface stress may indeed inhibit growth on convex substrates. Copyright © 2012 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Growth response of conifers in Adirondack plantations to changing environment: Model approaches based on stem-analysis

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

Pan, Y.

1993-01-01

Based on model approaches, three conifer species, red pine, Norway spruce and Scots pine grown in plantations at Pack Demonstration Forest, in the southeastern Adirondack mountains of New York, were chosen to study growth response to different environmental changes, including silvicultural treatments and changes in climate and chemical environment. Detailed stem analysis data provided a basis for constructing tree growth models. These models were organized into three groups: morphological, dynamic and predictive. The morphological model was designed to evaluate relationship between tree attributes and interactive influences of intrinsic and extrinsic factors on the annual increments. Three types of morphological patternsmore » have been characterized: space-time patterns of whole-stem rings, intrinsic wood deposition pattern along the tree-stem, and bolewood allocation ratio patterns along the tree-stem. The dynamic model reflects the growth process as a system which responds to extrinsic signal inputs, including fertilization pulses, spacing effects and climatic disturbance, as well as intrinsic feedback. Growth signals indicative of climatic effects were used to construct growth-climate models using both multivariate analysis and Kalman filter methods. The predictive model utilized GCMs and growth-climate relationships to forecast tree growth responses in relation to future scenarios of CO[sub 2]-induced climate change. Prediction results indicate that different conifer species have individualistic growth response to future climatic change and suggest possible changes in future growth and distribution of naturally occurring conifers in this region.« less

An individual-based growth and competition model for coastal redwood forest restoration

USGS Publications Warehouse

van Mantgem, Phillip J.; Das, Adrian J.

2014-01-01

Thinning treatments to accelerate coastal redwood forest stand development are in wide application, but managers have yet to identify prescriptions that might best promote Sequoia sempervirens (Lamb. ex D. Don) Endl. (redwood) growth. The creation of successful thinning prescriptions would be aided by identifying the underlying mechanisms governing how individual tree growth responds to competitive environments in coastal redwood forests. We created a spatially explicit individual-based model of tree competition and growth parameterized using surveys of upland redwood forests at Redwood National Park, California. We modeled competition for overstory trees (stems ≥ 20 cm stem diameter at breast height, 1.37 m (dbh)) as growth reductions arising from sizes, distances, and species identity of competitor trees. Our model explained up to half of the variation in individual tree growth, suggesting that neighborhood crowding is an important determinant of growth in this forest type. We used our model to simulate the effects of novel thinning prescriptions (e.g., 40% stand basal area removal) for redwood forest restoration, concluding that these treatments could lead to substantial growth releases, particularly for S. sempervirens. The results of this study, along with continued improvements to our model, will help to determine spacing and species composition that best encourage growth.

Transition index maps for urban growth simulation: application of artificial neural networks, weight of evidence and fuzzy multi-criteria evaluation.

PubMed

Shafizadeh-Moghadam, Hossein; Tayyebi, Amin; Helbich, Marco

2017-06-01

Transition index maps (TIMs) are key products in urban growth simulation models. However, their operationalization is still conflicting. Our aim was to compare the prediction accuracy of three TIM-based spatially explicit land cover change (LCC) models in the mega city of Mumbai, India. These LCC models include two data-driven approaches, namely artificial neural networks (ANNs) and weight of evidence (WOE), and one knowledge-based approach which integrates an analytical hierarchical process with fuzzy membership functions (FAHP). Using the relative operating characteristics (ROC), the performance of these three LCC models were evaluated. The results showed 85%, 75%, and 73% accuracy for the ANN, FAHP, and WOE. The ANN was clearly superior compared to the other LCC models when simulating urban growth for the year 2010; hence, ANN was used to predict urban growth for 2020 and 2030. Projected urban growth maps were assessed using statistical measures, including figure of merit, average spatial distance deviation, producer accuracy, and overall accuracy. Based on our findings, we recomend ANNs as an and accurate method for simulating future patterns of urban growth.

Effects of microscale inertia on dynamic ductile crack growth

NASA Astrophysics Data System (ADS)

Jacques, N.; Mercier, S.; Molinari, A.

2012-04-01

The aim of this paper is to investigate the role of microscale inertia in dynamic ductile crack growth. A constitutive model for porous solids that accounts for dynamic effects due to void growth is proposed. The model has been implemented in a finite element code and simulations of crack growth in a notched bar and in an edge cracked specimen have been performed. Results are compared to predictions obtained via the Gurson-Tvergaard-Needleman (GTN) model where micro-inertia effects are not accounted for. It is found that microscale inertia has a significant influence on the crack growth. In particular, it is shown that micro-inertia plays an important role during the strain localisation process by impeding void growth. Therefore, the resulting damage accumulation occurs in a more progressive manner. For this reason, simulations based on the proposed modelling exhibit much less mesh sensitivity than those based on the viscoplastic GTN model. Microscale inertia is also found to lead to lower crack speeds. Effects of micro-inertia on fracture toughness are evaluated.

The NLS-Based Nonlinear Grey Multivariate Model for Forecasting Pollutant Emissions in China.

PubMed

Pei, Ling-Ling; Li, Qin; Wang, Zheng-Xin

2018-03-08

The relationship between pollutant discharge and economic growth has been a major research focus in environmental economics. To accurately estimate the nonlinear change law of China's pollutant discharge with economic growth, this study establishes a transformed nonlinear grey multivariable (TNGM (1, N )) model based on the nonlinear least square (NLS) method. The Gauss-Seidel iterative algorithm was used to solve the parameters of the TNGM (1, N ) model based on the NLS basic principle. This algorithm improves the precision of the model by continuous iteration and constantly approximating the optimal regression coefficient of the nonlinear model. In our empirical analysis, the traditional grey multivariate model GM (1, N ) and the NLS-based TNGM (1, N ) models were respectively adopted to forecast and analyze the relationship among wastewater discharge per capita (WDPC), and per capita emissions of SO₂ and dust, alongside GDP per capita in China during the period 1996-2015. Results indicated that the NLS algorithm is able to effectively help the grey multivariable model identify the nonlinear relationship between pollutant discharge and economic growth. The results show that the NLS-based TNGM (1, N ) model presents greater precision when forecasting WDPC, SO₂ emissions and dust emissions per capita, compared to the traditional GM (1, N ) model; WDPC indicates a growing tendency aligned with the growth of GDP, while the per capita emissions of SO₂ and dust reduce accordingly.

The evaluation system of city's smart growth success rates

NASA Astrophysics Data System (ADS)

Huang, Yifan

2018-04-01

"Smart growth" is to pursue the best integrated perform+-ance of the Economically prosperous, socially Equitable, and Environmentally Sustainable(3E). Firstly, we establish the smart growth evaluation system(SGI) and the sustainable development evaluation system(SDI). Based on the ten principles and the definition of three E's of sustainability. B y using the Z-score method and the principal component analysis method, we evaluate and quantify indexes synthetically. Then we define the success of smart growth as the ratio of the SDI to the SGI composite score growth rate (SSG). After that we select two cities — Canberra and Durres as the objects of our model in view of the model. Based on the development plans and key data of these two cities, we can figure out the success of smart growth. And according to our model, we adjust some of the growth indicators for both cities. Then observe the results before and after adjustment, and finally verify the accuracy of the model.

Dynamic metabolic modeling for a MAB bioprocess.

PubMed

Gao, Jianying; Gorenflo, Volker M; Scharer, Jeno M; Budman, Hector M

2007-01-01

Production of monoclonal antibodies (MAb) for diagnostic or therapeutic applications has become an important task in the pharmaceutical industry. The efficiency of high-density reactor systems can be potentially increased by model-based design and control strategies. Therefore, a reliable kinetic model for cell metabolism is required. A systematic procedure based on metabolic modeling is used to model nutrient uptake and key product formation in a MAb bioprocess during both the growth and post-growth phases. The approach combines the key advantages of stoichiometric and kinetic models into a complete metabolic network while integrating the regulation and control of cellular activity. This modeling procedure can be easily applied to any cell line during both the cell growth and post-growth phases. Quadratic programming (QP) has been identified as a suitable method to solve the underdetermined constrained problem related to model parameter identification. The approach is illustrated for the case of murine hybridoma cells cultivated in stirred spinners.

Development of the AFRL Aircrew Perfomance and Protection Data Bank

DTIC Science & Technology

2007-12-01

Growth model and statistical model of hypobaric chamber simulations. It offers a quick and readily accessible online DCS risk assessment tool for...are used for the DCS prediction instead of the original model. ADRAC is based on more than 20 years of hypobaric chamber studies using human...prediction based on the combined Bubble Growth model and statistical model of hypobaric chamber simulations was integrated into the Data Bank. It

A Novel Modelling Approach for Predicting Forest Growth and Yield under Climate Change.

PubMed

Ashraf, M Irfan; Meng, Fan-Rui; Bourque, Charles P-A; MacLean, David A

2015-01-01

Global climate is changing due to increasing anthropogenic emissions of greenhouse gases. Forest managers need growth and yield models that can be used to predict future forest dynamics during the transition period of present-day forests under a changing climatic regime. In this study, we developed a forest growth and yield model that can be used to predict individual-tree growth under current and projected future climatic conditions. The model was constructed by integrating historical tree growth records with predictions from an ecological process-based model using neural networks. The new model predicts basal area (BA) and volume growth for individual trees in pure or mixed species forests. For model development, tree-growth data under current climatic conditions were obtained using over 3000 permanent sample plots from the Province of Nova Scotia, Canada. Data to reflect tree growth under a changing climatic regime were projected with JABOWA-3 (an ecological process-based model). Model validation with designated data produced model efficiencies of 0.82 and 0.89 in predicting individual-tree BA and volume growth. Model efficiency is a relative index of model performance, where 1 indicates an ideal fit, while values lower than zero means the predictions are no better than the average of the observations. Overall mean prediction error (BIAS) of basal area and volume growth predictions was nominal (i.e., for BA: -0.0177 cm(2) 5-year(-1) and volume: 0.0008 m(3) 5-year(-1)). Model variability described by root mean squared error (RMSE) in basal area prediction was 40.53 cm(2) 5-year(-1) and 0.0393 m(3) 5-year(-1) in volume prediction. The new modelling approach has potential to reduce uncertainties in growth and yield predictions under different climate change scenarios. This novel approach provides an avenue for forest managers to generate required information for the management of forests in transitional periods of climate change. Artificial intelligence technology has substantial potential in forest modelling.

A Novel Modelling Approach for Predicting Forest Growth and Yield under Climate Change

PubMed Central

Ashraf, M. Irfan; Meng, Fan-Rui; Bourque, Charles P.-A.; MacLean, David A.

2015-01-01

Global climate is changing due to increasing anthropogenic emissions of greenhouse gases. Forest managers need growth and yield models that can be used to predict future forest dynamics during the transition period of present-day forests under a changing climatic regime. In this study, we developed a forest growth and yield model that can be used to predict individual-tree growth under current and projected future climatic conditions. The model was constructed by integrating historical tree growth records with predictions from an ecological process-based model using neural networks. The new model predicts basal area (BA) and volume growth for individual trees in pure or mixed species forests. For model development, tree-growth data under current climatic conditions were obtained using over 3000 permanent sample plots from the Province of Nova Scotia, Canada. Data to reflect tree growth under a changing climatic regime were projected with JABOWA-3 (an ecological process-based model). Model validation with designated data produced model efficiencies of 0.82 and 0.89 in predicting individual-tree BA and volume growth. Model efficiency is a relative index of model performance, where 1 indicates an ideal fit, while values lower than zero means the predictions are no better than the average of the observations. Overall mean prediction error (BIAS) of basal area and volume growth predictions was nominal (i.e., for BA: -0.0177 cm2 5-year-1 and volume: 0.0008 m3 5-year-1). Model variability described by root mean squared error (RMSE) in basal area prediction was 40.53 cm2 5-year-1 and 0.0393 m3 5-year-1 in volume prediction. The new modelling approach has potential to reduce uncertainties in growth and yield predictions under different climate change scenarios. This novel approach provides an avenue for forest managers to generate required information for the management of forests in transitional periods of climate change. Artificial intelligence technology has substantial potential in forest modelling. PMID:26173081

Exploring Latent Class Based on Growth Rates in Number Sense Ability

ERIC Educational Resources Information Center

Kim, Dongil; Shin, Jaehyun; Lee, Kijyung

2013-01-01

The purpose of this study was to explore latent class based on growth rates in number sense ability by using latent growth class modeling (LGCM). LGCM is one of the noteworthy methods for identifying growth patterns of the progress monitoring within the response to intervention framework in that it enables us to analyze latent sub-groups based not…

Growth potential and habitat requirements of endangered age-0 pallid sturgeon (Scaphirhynchus albus) in the Missouri River, USA, determined using a individual-based model framework

USGS Publications Warehouse

Deslauriers, David; Heironimus, Laura B.; Rapp, Tobias; Graeb, Brian D. S.; Klumb, Robert A.; Chipps, Steven R.

2018-01-01

An individual-based model framework was used to evaluate growth potential of the federally endangered pallid sturgeon (Scaphirhynchus albus) in the Missouri River. The model, developed for age-0 sturgeon, combines information on functional feeding response, bioenergetics and swimming ability to regulate consumption and growth within a virtual foraging arena. Empirical data on water temperature, water velocity and prey density were obtained from three sites in the Missouri River and used as inputs in the model to evaluate hypotheses concerning factors affecting pallid sturgeon growth. The model was also used to evaluate the impacts of environmental heterogeneity and water velocity on individual growth variability, foraging success and dispersal ability. Growth was simulated for a period of 100 days using 100 individuals (first feeding; 19 mm and 0.035 g) per scenario. Higher growth was shown to occur at sites where high densities of Ephemeroptera and Chironomidae larvae occurred throughout the growing season. Highly heterogeneous habitats (i.e., wide range of environmental conditions) and moderate water velocities (0.3 m/s) were also found to positively affect growth rates. The model developed here provides an important management and conservation tool for evaluating growth hypotheses and(or) identifying habitats in the Missouri River that are favourable to age-0 pallid sturgeon growth.

Crop monitoring & yield forecasting system based on Synthetic Aperture Radar (SAR) and process-based crop growth model: Development and validation in South and South East Asian Countries

NASA Astrophysics Data System (ADS)

Setiyono, T. D.

2014-12-01

Accurate and timely information on rice crop growth and yield helps governments and other stakeholders adapting their economic policies and enables relief organizations to better anticipate and coordinate relief efforts in the wake of a natural catastrophe. Such delivery of rice growth and yield information is made possible by regular earth observation using space-born Synthetic Aperture Radar (SAR) technology combined with crop modeling approach to estimate yield. Radar-based remote sensing is capable of observing rice vegetation growth irrespective of cloud coverage, an important feature given that in incidences of flooding the sky is often cloud-covered. The system allows rapid damage assessment over the area of interest. Rice yield monitoring is based on a crop growth simulation and SAR-derived key information, particularly start of season and leaf growth rate. Results from pilot study sites in South and South East Asian countries suggest that incorporation of SAR data into crop model improves yield estimation for actual yields. Remote-sensing data assimilation into crop model effectively capture responses of rice crops to environmental conditions over large spatial coverage, which otherwise is practically impossible to achieve. Such improvement of actual yield estimates offers practical application such as in a crop insurance program. Process-based crop simulation model is used in the system to ensure climate information is adequately captured and to enable mid-season yield forecast.

Lattice Gas Model Based Optimization of Plasma-Surface Processes for GaN-Based Compound Growth

NASA Astrophysics Data System (ADS)

Nonokawa, Kiyohide; Suzuki, Takuma; Kitamori, Kazutaka; Sawada, Takayuki

2001-10-01

Progress of the epitaxial growth technique for GaN-based compounds makes these materials attractive for applications in high temperature/high-power electronic devices as well as in short-wavelength optoelectronic devices. For MBE growth of GaN epilayer, atomic nitrogen is usually supplied from ECR-plasma while atomic Ga is supplied from conventional K-cell. To grow high-quality epilayer, fundamental knowledge of the detailed atomic process, such as adsorption, surface migration, incorporation, desorption and so forth, is required. We have studied the influence of growth conditions on the flatness of the growth front surface and the growth rate using Monte Carlo simulation based on the lattice gas model. Under the fixed Ga flux condition, the lower the nitrogen flux and/or the higher the growth temperature, the better the flatness of the front surface at the sacrifice of the growth rate of the epilayer. When the nitrogen flux is increased, the growth rate reaches saturation value determined from the Ga flux. At a fixed growth temperature, increasing of nitrogen to Ga flux ratio results in rough surface owing to 3-dimensional island formation. Other characteristics of MBE-GaN growth using ECR-plasma can be well reproduced.

Equine Assisted Psychotherapy: The Equine Assisted Growth and Learning Association's Model Overview of Equine-Based Modalities

ERIC Educational Resources Information Center

Notgrass, Clayton G.; Pettinelli, J. Douglas

2015-01-01

This article describes the Equine Assisted Growth and Learning Association's (EAGALA) experiential model called "Equine Assisted Psychotherapy" (EAP). EAGALA's model is based on the Association for Experiential Education's (AEE) tenets and is focused on the learner's experience with horses. Drawing on the historical use of equines in the…

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

USGS Publications Warehouse

Klett, T.R.

2003-01-01

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

A generalized system of models forecasting Central States tree growth.

Treesearch

Stephen R. Shifley

1987-01-01

Describes the development and testing of a system of individual tree-based growth projection models applicable to species in Indiana, Missouri, and Ohio. Annual tree basal area growth is estimated as a function of tree size, crown ratio, stand density, and site index. Models are compatible with the STEMS and TWIGS Projection System.

Hydrothermal time models for conidial germination and mycelial growth of the seed pathogen Pyrenophora semeniperda

Treesearch

Connor W. Barth; Susan E. Meyer; Julie Beckstead; Phil S. Allen

2015-01-01

Population-based threshold models using hydrothermal time (HTT) have been widely used to model seed germination. We used HTT to model conidial germination and mycelial growth for the seed pathogen Pyrenophora semeniperda in a novel approach to understanding its interactions with host seeds. Germination time courses and mycelial growth rates for P.semeniperda were...

Explaining the trade-growth link: Assessing diffusion-based and structure-based models of exchange.

PubMed

Clark, Rob; Mahutga, Matthew C

2013-03-01

International development scholars advance contrasting theoretical explanations for the hypothesized link between trade and growth. Diffusion-based models suggest that trade with integrated partners provides states with greater access to technical knowledge. Structure-based models propose that trading with isolated partners produces a bargaining advantage. In this study, we adjudicate between these competing visions by applying Bonacich's (1987) measure of power centrality to the international trade network. We manipulate the procedure's "attenuation factor" (β) such that a state's trade centrality can be enhanced when a state is connected to either central or isolated partners. Drawing from a sample of 101 states during the 1980-2000 period, we use difference-of-logs models to assess the impact of trade centrality on economic growth net of controls. We find that the positive relationship between trade centrality and growth peaks when states trade with isolated partners in the periphery. Copyright © 2012 Elsevier Inc. All rights reserved.

Two-way Coupling of a Process-Based Crop Growth Model (BioCro) and a Biogeochemistry Model (DayCent) and its Application to an Energy Crop Site in the mid-west USA

NASA Astrophysics Data System (ADS)

Jaiswal, D.; Long, S.; Parton, W. J.; Hartman, M.

2012-12-01

A coupled modeling system of crop growth model (BioCro) and biogeochemical model (DayCent) has been developed to assess the two-way interactions between plant growth and biogeochemistry. Crop growth in BioCro is simulated using a detailed mechanistic biochemical and biophysical multi-layer canopy model and partitioning of dry biomass into different plant organs according to phenological stages. Using hourly weather records, the model partitions light between dynamically changing sunlit and shaded portions of the canopy and computes carbon and water exchange with the atmosphere and through the canopy for each hour of the day, each day of the year. The model has been parameterized for the bioenergy crops sugarcane, Miscanthus and switchgrass, and validation has shown it to predict growth cycles and partitioning of biomass to a high degree of accuracy. As such it provides an ideal input for a soil biogeochemical model. DayCent is an established model for predicting long-term changes in soil C & N and soil-atmosphere exchanges of greenhouse gases. At present, DayCent uses a relatively simple productivity model. In this project BioCro has replaced this simple model to provide DayCent with a productivity and growth model equal in detail to its biogeochemistry. Dynamic coupling of these two models to produce CroCent allows for differential C: N ratios of litter fall (based on rates of senescence of different plant organs) and calibration of the model for realistic plant productivity in a mechanistic way. A process-based approach to modeling plant growth is needed for bioenergy crops because research on these crops (especially second generation feedstocks) has started only recently, and detailed agronomic information for growth, yield and management is too limited for effective empirical models. The coupled model provides means to test and improve the model against high resolution data, such as that obtained by eddy covariance and explore yield implications of different crop and soil management.

A model of urban rational growth based on grey prediction

NASA Astrophysics Data System (ADS)

Xiao, Wenjing

2017-04-01

Smart growth focuses on building sustainable cities, using compact development to prevent urban sprawl. This paper establishes a series of models to implement smart growth theories into city design. Besides two specific city design cases are shown. Firstly, We establishes Smart Growth Measure Model to measure the success of smart growth of a city. And we use Full Permutation Polygon Synthetic Indicator Method to calculate the Comprehensive Indicator (CI) which is used to measure the success of smart growth. Secondly, this paper uses the principle of smart growth to develop a new growth plan for two cities. We establish an optimization model to maximum CI value. The Particle Swarm Optimization (PSO) algorithm is used to solve the model. Combined with the calculation results and the specific circumstances of cities, we make their the smart growth plan respectively.

A 3-dimensional DTI MRI-based model of GBM growth and response to radiation therapy.

PubMed

Hathout, Leith; Patel, Vishal; Wen, Patrick

2016-09-01

Glioblastoma (GBM) is both the most common and the most aggressive intra-axial brain tumor, with a notoriously poor prognosis. To improve this prognosis, it is necessary to understand the dynamics of GBM growth, response to treatment and recurrence. The present study presents a mathematical diffusion-proliferation model of GBM growth and response to radiation therapy based on diffusion tensor (DTI) MRI imaging. This represents an important advance because it allows 3-dimensional tumor modeling in the anatomical context of the brain. Specifically, tumor infiltration is guided by the direction of the white matter tracts along which glioma cells infiltrate. This provides the potential to model different tumor growth patterns based on location within the brain, and to simulate the tumor's response to different radiation therapy regimens. Tumor infiltration across the corpus callosum is simulated in biologically accurate time frames. The response to radiation therapy, including changes in cell density gradients and how these compare across different radiation fractionation protocols, can be rendered. Also, the model can estimate the amount of subthreshold tumor which has extended beyond the visible MR imaging margins. When combined with the ability of being able to estimate the biological parameters of invasiveness and proliferation of a particular GBM from serial MRI scans, it is shown that the model has potential to simulate realistic tumor growth, response and recurrence patterns in individual patients. To the best of our knowledge, this is the first presentation of a DTI-based GBM growth and radiation therapy treatment model.

Cotton growth modeling and assessment using unmanned aircraft system visual-band imagery

NASA Astrophysics Data System (ADS)

Chu, Tianxing; Chen, Ruizhi; Landivar, Juan A.; Maeda, Murilo M.; Yang, Chenghai; Starek, Michael J.

2016-07-01

This paper explores the potential of using unmanned aircraft system (UAS)-based visible-band images to assess cotton growth. By applying the structure-from-motion algorithm, the cotton plant height (ph) and canopy cover (cc) information were retrieved from the point cloud-based digital surface models (DSMs) and orthomosaic images. Both UAS-based ph and cc follow a sigmoid growth pattern as confirmed by ground-based studies. By applying an empirical model that converts the cotton ph to cc, the estimated cc shows strong correlation (R2=0.990) with the observed cc. An attempt for modeling cotton yield was carried out using the ph and cc information obtained on June 26, 2015, the date when sigmoid growth curves for both ph and cc tended to decline in slope. In a cross-validation test, the correlation between the ground-measured yield and the estimated equivalent derived from the ph and/or cc was compared. Generally, combining ph and cc, the performance of the yield estimation is most comparable against the observed yield. On the other hand, the observed yield and cc-based estimation produce the second strongest correlation, regardless of the complexity of the models.

Estimation and application of a growth and yield model for uneven-aged mixed conifer stands in California.

Treesearch

Jingjing Liang; J. Buongiorno; R.A. Monserud

2005-01-01

A growth model for uneven-aged mixed-conifer stands in California was developed with data from 205 permanent plots. The model predicts the number of softwood and hardwood trees in nineteen diameter classes, based on equations for diameter growth rates, mortality arid recruitment. The model gave unbiased predictions of the expected number of trees by diameter class and...

Estimation of median growth curves for children up two years old based on biresponse local linear estimator

NASA Astrophysics Data System (ADS)

Chamidah, Nur; Rifada, Marisa

2016-03-01

There is significant of the coeficient correlation between weight and height of the children. Therefore, the simultaneous model estimation is better than partial single response approach. In this study we investigate the pattern of sex difference in growth curve of children from birth up to two years of age in Surabaya, Indonesia based on biresponse model. The data was collected in a longitudinal representative sample of the Surabaya population of healthy children that consists of two response variables i.e. weight (kg) and height (cm). While a predictor variable is age (month). Based on generalized cross validation criterion, the modeling result based on biresponse model by using local linear estimator for boy and girl growth curve gives optimal bandwidth i.e 1.41 and 1.56 and the determination coefficient (R2) i.e. 99.99% and 99.98%,.respectively. Both boy and girl curves satisfy the goodness of fit criterion i.e..the determination coefficient tends to one. Also, there is difference pattern of growth curve between boy and girl. The boy median growth curves is higher than those of girl curve.

Towards a consensus-based biokinetic model for green microalgae - The ASM-A.

PubMed

Wágner, Dorottya S; Valverde-Pérez, Borja; Sæbø, Mariann; Bregua de la Sotilla, Marta; Van Wagenen, Jonathan; Smets, Barth F; Plósz, Benedek Gy

2016-10-15

Cultivation of microalgae in open ponds and closed photobioreactors (PBRs) using wastewater resources offers an opportunity for biochemical nutrient recovery. Effective reactor system design and process control of PBRs requires process models. Several models with different complexities have been developed to predict microalgal growth. However, none of these models can effectively describe all the relevant processes when microalgal growth is coupled with nutrient removal and recovery from wastewaters. Here, we present a mathematical model developed to simulate green microalgal growth (ASM-A) using the systematic approach of the activated sludge modelling (ASM) framework. The process model - identified based on a literature review and using new experimental data - accounts for factors influencing photoautotrophic and heterotrophic microalgal growth, nutrient uptake and storage (i.e. Droop model) and decay of microalgae. Model parameters were estimated using laboratory-scale batch and sequenced batch experiments using the novel Latin Hypercube Sampling based Simplex (LHSS) method. The model was evaluated using independent data obtained in a 24-L PBR operated in sequenced batch mode. Identifiability of the model was assessed. The model can effectively describe microalgal biomass growth, ammonia and phosphate concentrations as well as the phosphorus storage using a set of average parameter values estimated with the experimental data. A statistical analysis of simulation and measured data suggests that culture history and substrate availability can introduce significant variability on parameter values for predicting the reaction rates for bulk nitrate and the intracellularly stored nitrogen state-variables, thereby requiring scenario specific model calibration. ASM-A was identified using standard cultivation medium and it can provide a platform for extensions accounting for factors influencing algal growth and nutrient storage using wastewater resources. Copyright © 2016 Elsevier Ltd. All rights reserved.

Predicting the Effects of Water Quality on the Growth of Thalassia testudinum in Tampa Bay with a Dynamic Simile-Based Model Tool

EPA Science Inventory

We describe a seagrass growth (SGG) model that is coupled to a water quality (WQ) model that includes the effects of phytoplankton (chlorophyll), colored dissolved organic matter (CDOM) and suspended solids (TSS) on water clarity. Phytoplankton growth was adjusted daily for PAR (...

The NLS-Based Nonlinear Grey Multivariate Model for Forecasting Pollutant Emissions in China

PubMed Central

Pei, Ling-Ling; Li, Qin

2018-01-01

The relationship between pollutant discharge and economic growth has been a major research focus in environmental economics. To accurately estimate the nonlinear change law of China’s pollutant discharge with economic growth, this study establishes a transformed nonlinear grey multivariable (TNGM (1, N)) model based on the nonlinear least square (NLS) method. The Gauss–Seidel iterative algorithm was used to solve the parameters of the TNGM (1, N) model based on the NLS basic principle. This algorithm improves the precision of the model by continuous iteration and constantly approximating the optimal regression coefficient of the nonlinear model. In our empirical analysis, the traditional grey multivariate model GM (1, N) and the NLS-based TNGM (1, N) models were respectively adopted to forecast and analyze the relationship among wastewater discharge per capita (WDPC), and per capita emissions of SO2 and dust, alongside GDP per capita in China during the period 1996–2015. Results indicated that the NLS algorithm is able to effectively help the grey multivariable model identify the nonlinear relationship between pollutant discharge and economic growth. The results show that the NLS-based TNGM (1, N) model presents greater precision when forecasting WDPC, SO2 emissions and dust emissions per capita, compared to the traditional GM (1, N) model; WDPC indicates a growing tendency aligned with the growth of GDP, while the per capita emissions of SO2 and dust reduce accordingly. PMID:29517985

Cotton growth modeling and assessment using UAS visual-band imagery

USDA-ARS?s Scientific Manuscript database

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

Serum-free keloid fibroblast cell culture: an in vitro model for the study of aberrant wound healing.

PubMed

Koch, R J; Goode, R L; Simpson, G T

1997-04-01

The purpose of this study was to develop an in vitro serum-free keloid fibroblast model. Keloid formation remains a problem for every surgeon. Prior evaluations of fibroblast characteristics in vitro, especially those of growth factor measurement, have been confounded by the presence of serum-containing tissue culture media. The serum itself contains growth factors, yet has been a "necessary evil" to sustain cell growth. The design of this study is laboratory-based and uses keloid fibroblasts obtained from five patients undergoing facial (ear lobule) keloid removal in a university-affiliated clinic. Keloid fibroblasts were established in primary cell culture and then propagated in a serum-free environment. The main outcome measures included sustained keloid fibroblast growth and viability, which was comparable to serum-based models. The keloid fibroblast cell cultures exhibited logarithmic growth, sustained a high cellular viability, maintained a monolayer, and displayed contact inhibition. Demonstrating model consistency, there was no statistically significant difference between the mean cell counts of the five keloid fibroblast cell lines at each experimental time point. The in vitro growth of keloid fibroblasts in a serum-free model has not been done previous to this study. The results of this study indicate that the proliferative characteristics described are comparable to those of serum-based models. The described model will facilitate the evaluation of potential wound healing modulators, and cellular effects and collagen modifications of laser resurfacing techniques, and may serve as a harvest source for contaminant-free fibroblast autoimplants. Perhaps its greatest utility will be in the evaluation of endogenous and exogenous growth factors.

Comparison between two meshless methods based on collocation technique for the numerical solution of four-species tumor growth model

NASA Astrophysics Data System (ADS)

Dehghan, Mehdi; Mohammadi, Vahid

2017-03-01

As is said in [27], the tumor-growth model is the incorporation of nutrient within the mixture as opposed to being modeled with an auxiliary reaction-diffusion equation. The formulation involves systems of highly nonlinear partial differential equations of surface effects through diffuse-interface models [27]. Simulations of this practical model using numerical methods can be applied for evaluating it. The present paper investigates the solution of the tumor growth model with meshless techniques. Meshless methods are applied based on the collocation technique which employ multiquadrics (MQ) radial basis function (RBFs) and generalized moving least squares (GMLS) procedures. The main advantages of these choices come back to the natural behavior of meshless approaches. As well as, a method based on meshless approach can be applied easily for finding the solution of partial differential equations in high-dimension using any distributions of points on regular and irregular domains. The present paper involves a time-dependent system of partial differential equations that describes four-species tumor growth model. To overcome the time variable, two procedures will be used. One of them is a semi-implicit finite difference method based on Crank-Nicolson scheme and another one is based on explicit Runge-Kutta time integration. The first case gives a linear system of algebraic equations which will be solved at each time-step. The second case will be efficient but conditionally stable. The obtained numerical results are reported to confirm the ability of these techniques for solving the two and three-dimensional tumor-growth equations.

From Experiment to Theory: What Can We Learn from Growth Curves?

PubMed

Kareva, Irina; Karev, Georgy

2018-01-01

Finding an appropriate functional form to describe population growth based on key properties of a described system allows making justified predictions about future population development. This information can be of vital importance in all areas of research, ranging from cell growth to global demography. Here, we use this connection between theory and observation to pose the following question: what can we infer about intrinsic properties of a population (i.e., degree of heterogeneity, or dependence on external resources) based on which growth function best fits its growth dynamics? We investigate several nonstandard classes of multi-phase growth curves that capture different stages of population growth; these models include hyperbolic-exponential, exponential-linear, exponential-linear-saturation growth patterns. The constructed models account explicitly for the process of natural selection within inhomogeneous populations. Based on the underlying hypotheses for each of the models, we identify whether the population that it best fits by a particular curve is more likely to be homogeneous or heterogeneous, grow in a density-dependent or frequency-dependent manner, and whether it depends on external resources during any or all stages of its development. We apply these predictions to cancer cell growth and demographic data obtained from the literature. Our theory, if confirmed, can provide an additional biomarker and a predictive tool to complement experimental research.

Simulating Spatial Growth Patterns in Developing Countries: A Case of Shama in the Western Region of Ghana.

NASA Astrophysics Data System (ADS)

Inkoom, J. N.; Nyarko, B. K.

2014-12-01

The integration of geographic information systems (GIS) and agent-based modelling (ABM) can be an efficient tool to improve spatial planning practices. This paper utilizes GIS and ABM approaches to simulate spatial growth patterns of settlement structures in Shama. A preliminary household survey on residential location decision-making choice served as the behavioural rule for household agents in the model. Physical environment properties of the model were extracted from a 2005 image implemented in NetLogo. The resulting growth pattern model was compared with empirical growth patterns to ascertain the model's accuracy. The paper establishes that the development of unplanned structures and its evolving structural pattern are a function of land price, proximity to economic centres, household economic status and location decision-making patterns. The application of the proposed model underlines its potential for integration into urban planning policies and practices, and for understanding residential decision-making processes in emerging cities in developing countries. Key Words: GIS; Agent-based modelling; Growth patterns; NetLogo; Location decision making; Computational Intelligence.

A Comparison Study of Machine Learning Based Algorithms for Fatigue Crack Growth Calculation.

PubMed

Wang, Hongxun; Zhang, Weifang; Sun, Fuqiang; Zhang, Wei

2017-05-18

The relationships between the fatigue crack growth rate ( d a / d N ) and stress intensity factor range ( Δ K ) are not always linear even in the Paris region. The stress ratio effects on fatigue crack growth rate are diverse in different materials. However, most existing fatigue crack growth models cannot handle these nonlinearities appropriately. The machine learning method provides a flexible approach to the modeling of fatigue crack growth because of its excellent nonlinear approximation and multivariable learning ability. In this paper, a fatigue crack growth calculation method is proposed based on three different machine learning algorithms (MLAs): extreme learning machine (ELM), radial basis function network (RBFN) and genetic algorithms optimized back propagation network (GABP). The MLA based method is validated using testing data of different materials. The three MLAs are compared with each other as well as the classical two-parameter model ( K * approach). The results show that the predictions of MLAs are superior to those of K * approach in accuracy and effectiveness, and the ELM based algorithms show overall the best agreement with the experimental data out of the three MLAs, for its global optimization and extrapolation ability.

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

Hodshire, Anna L.; Lawler, Michael J.; Zhao, Jun

New-particle formation (NPF) is a significant source of aerosol particles into the atmosphere. However, these particles are initially too small to have climatic importance and must grow, primarily through net uptake of low-volatility species, from diameters  ∼  1 to 30–100 nm in order to potentially impact climate. There are currently uncertainties in the physical and chemical processes associated with the growth of these freshly formed particles that lead to uncertainties in aerosol-climate modeling. Four main pathways for new-particle growth have been identified: condensation of sulfuric-acid vapor (and associated bases when available), condensation of organic vapors, uptake of organic acids through acid–base chemistrymore » in the particle phase, and accretion of organic molecules in the particle phase to create a lower-volatility compound that then contributes to the aerosol mass. The relative importance of each pathway is uncertain and is the focus of this work. The 2013 New Particle Formation Study (NPFS) measurement campaign took place at the DOE Southern Great Plains (SGP) facility in Lamont, Oklahoma, during spring 2013. Measured gas- and particle-phase compositions during these new-particle growth events suggest three distinct growth pathways: (1) growth by primarily organics, (2) growth by primarily sulfuric acid and ammonia, and (3) growth by primarily sulfuric acid and associated bases and organics. To supplement the measurements, we used the particle growth model MABNAG (Model for Acid–Base chemistry in NAnoparticle Growth) to gain further insight into the growth processes on these 3 days at SGP. MABNAG simulates growth from (1) sulfuric-acid condensation (and subsequent salt formation with ammonia or amines), (2) near-irreversible condensation from nonreactive extremely low-volatility organic compounds (ELVOCs), and (3) organic-acid condensation and subsequent salt formation with ammonia or amines. MABNAG is able to corroborate the observed differing growth pathways, while also predicting that ELVOCs contribute more to growth than organic salt formation. However, most MABNAG model simulations tend to underpredict the observed growth rates between 10 and 20 nm in diameter; this underprediction may come from neglecting the contributions to growth from semi-to-low-volatility species or accretion reactions. Our results suggest that in addition to sulfuric acid, ELVOCs are also very important for growth in this rural setting. We discuss the limitations of our study that arise from not accounting for semi- and low-volatility organics, as well as nitrogen-containing species beyond ammonia and amines in the model. Quantitatively understanding the overall budget, evolution, and thermodynamic properties of lower-volatility organics in the atmosphere will be essential for improving global aerosol models.« less

A novel process-based model of microbial growth: self-inhibition in Saccharomyces cerevisiae aerobic fed-batch cultures.

PubMed

Mazzoleni, Stefano; Landi, Carmine; Cartenì, Fabrizio; de Alteriis, Elisabetta; Giannino, Francesco; Paciello, Lucia; Parascandola, Palma

2015-07-30

Microbial population dynamics in bioreactors depend on both nutrients availability and changes in the growth environment. Research is still ongoing on the optimization of bioreactor yields focusing on the increase of the maximum achievable cell density. A new process-based model is proposed to describe the aerobic growth of Saccharomyces cerevisiae cultured on glucose as carbon and energy source. The model considers the main metabolic routes of glucose assimilation (fermentation to ethanol and respiration) and the occurrence of inhibition due to the accumulation of both ethanol and other self-produced toxic compounds in the medium. Model simulations reproduced data from classic and new experiments of yeast growth in batch and fed-batch cultures. Model and experimental results showed that the growth decline observed in prolonged fed-batch cultures had to be ascribed to self-produced inhibitory compounds other than ethanol. The presented results clarify the dynamics of microbial growth under different feeding conditions and highlight the relevance of the negative feedback by self-produced inhibitory compounds on the maximum cell densities achieved in a bioreactor.

Forest canopy growth dynamic modeling based on remote sensing prodcuts and meteorological data in Daxing'anling of Northeast China

NASA Astrophysics Data System (ADS)

Wu, Qiaoli; Song, Jinling; Wang, Jindi; Xiao, Zhiqiang

2014-11-01

Leaf Area Index (LAI) is an important biophysical variable for vegetation. Compared with vegetation indexes like NDVI and EVI, LAI is more capable of monitoring forest canopy growth quantitatively. GLASS LAI is a spatially complete and temporally continuous product derived from AVHRR and MODIS reflectance data. In this paper, we present the approach to build dynamic LAI growth models for young and mature Larix gmelinii forest in north Daxing'anling in Inner Mongolia of China using the Dynamic Harmonic Regression (DHR) model and Double Logistic (D-L) model respectively, based on the time series extracted from multi-temporal GLASS LAI data. Meanwhile we used the dynamic threshold method to attract the key phenological phases of Larix gmelinii forest from the simulated time series. Then, through the relationship analysis between phenological phases and the meteorological factors, we found that the annual peak LAI and the annual maximum temperature have a good correlation coefficient. The results indicate this forest canopy growth dynamic model to be very effective in predicting forest canopy LAI growth and extracting forest canopy LAI growth dynamic.

Monte Carlo-based calibration and uncertainty analysis of a coupled plant growth and hydrological model

NASA Astrophysics Data System (ADS)

Houska, T.; Multsch, S.; Kraft, P.; Frede, H.-G.; Breuer, L.

2014-04-01

Computer simulations are widely used to support decision making and planning in the agriculture sector. On the one hand, many plant growth models use simplified hydrological processes and structures - for example, by the use of a small number of soil layers or by the application of simple water flow approaches. On the other hand, in many hydrological models plant growth processes are poorly represented. Hence, fully coupled models with a high degree of process representation would allow for a more detailed analysis of the dynamic behaviour of the soil-plant interface. We coupled two of such high-process-oriented independent models and calibrated both models simultaneously. The catchment modelling framework (CMF) simulated soil hydrology based on the Richards equation and the van Genuchten-Mualem model of the soil hydraulic properties. CMF was coupled with the plant growth modelling framework (PMF), which predicts plant growth on the basis of radiation use efficiency, degree days, water shortage and dynamic root biomass allocation. The Monte Carlo-based generalized likelihood uncertainty estimation (GLUE) method was applied to parameterize the coupled model and to investigate the related uncertainty of model predictions. Overall, 19 model parameters (4 for CMF and 15 for PMF) were analysed through 2 × 106 model runs randomly drawn from a uniform distribution. The model was applied to three sites with different management in Müncheberg (Germany) for the simulation of winter wheat (Triticum aestivum L.) in a cross-validation experiment. Field observations for model evaluation included soil water content and the dry matter of roots, storages, stems and leaves. The shape parameter of the retention curve n was highly constrained, whereas other parameters of the retention curve showed a large equifinality. We attribute this slightly poorer model performance to missing leaf senescence, which is currently not implemented in PMF. The most constrained parameters for the plant growth model were the radiation-use efficiency and the base temperature. Cross validation helped to identify deficits in the model structure, pointing out the need for including agricultural management options in the coupled model.

Growth and food consumption by tiger muskellunge: Effects of temperature and ration level on bioenergetic model predictions

USGS Publications Warehouse

Chipps, S.R.; Einfalt, L.M.; Wahl, David H.

2000-01-01

We measured growth of age-0 tiger muskellunge as a function of ration size (25, 50, 75, and 100% C(max))and water temperature (7.5-25??C) and compared experimental results with those predicted from a bioenergetic model. Discrepancies between actual and predicted values varied appreciably with water temperature and growth rate. On average, model output overestimated winter consumption rates at 10 and 7.5??C by 113 to 328%, respectively, whereas model predictions in summer and autumn (20-25??C) were in better agreement with actual values (4 to 58%). We postulate that variation in model performance was related to seasonal changes in esocid metabolic rate, which were not accounted for in the bioenergetic model. Moreover, accuracy of model output varied with feeding and growth rate of tiger muskellunge. The model performed poorly for fish fed low rations compared with estimates based on fish fed ad libitum rations and was attributed, in part, to the influence of growth rate on the accuracy of bioenergetic predictions. Based on modeling simulations, we found that errors associated with bioenergetic parameters had more influence on model output when growth rate was low, which is consistent with our observations. In addition, reduced conversion efficiency at high ration levels may contribute to variable model performance, thereby implying that waste losses should be modeled as a function of ration size for esocids. Our findings support earlier field tests of the esocid bioenergetic model and indicate that food consumption is generally overestimated by the model, particularly in winter months and for fish exhibiting low feeding and growth rates.

BUDEM: an urban growth simulation model using CA for Beijing metropolitan area

NASA Astrophysics Data System (ADS)

Long, Ying; Shen, Zhenjiang; Du, Liqun; Mao, Qizhi; Gao, Zhanping

2008-10-01

It is in great need of identifying the future urban form of Beijing, which faces challenges of rapid growth in urban development projects implemented in Beijing. We develop Beijing Urban Developing Model (BUDEM in short) to support urban planning and corresponding policies evaluation. BUDEM is the spatio-temporal dynamic model for simulating urban growth in Beijing metropolitan area, using cellular automata (CA) and Multi-agent system (MAS) approaches. In this phase, the computer simulation using CA in Beijing metropolitan area is conducted, which attempts to provide a premise of urban activities including different kinds of urban development projects for industrial plants, shopping facilities, houses. In the paper, concept model of BUDEM is introduced, which is established basing on prevalent urban growth theories. The method integrating logistic regression and MonoLoop is used to retrieve weights in the transition rule by MCE. After model sensibility analysis, we apply BUDEM into three aspects of urban planning practices: (1) Identifying urban growth mechanism in various historical phases since 1986; (2) Identifying urban growth policies needed to implement desired urban form (BEIJING2020), namely planned urban form; (3) Simulating urban growth scenarios of 2049 (BEIJING2049) basing on the urban form and parameter set of BEIJING2020.

A unified theory for ice vapor growth suitable for cloud models: Testing and implications for cold cloud evolution

NASA Astrophysics Data System (ADS)

Zhang, Chengzhu

A new microphysical model for the vapor growth and aspect ratio evolution of atmospheric ice crystals is presented. The method is based on the adaptive habit model of Chen and Lamb (1994), but is modified to include surface kinetic processes for crystal growth. Inclusion of surface kinetic effects is accomplished with a new theory that accounts for axis dependent growth. Deposition coefficients (growth efficiencies) are predicted for two axis directions based on laboratory-determined parameters for growth initiation (critical supersaturations) on each face. In essence, the new theory extends the adaptive habit approach of Chen and Lamb (1994) to ice saturation states below that of liquid saturation, where Chen and Lamb (1994) is likely most valid. The new model is used to simulate changes in crystal primary habit as a function of temperature and ice supersaturation. Predictions are compared with a detailed hexagonal growth model both in a single particle framework and in a Lagrangian parcel model to indicate the accuracy of the new method. Moreover, predictions of the ratio of the axis deposition coefficients match laboratory-generated data. A parameterization for predicting deposition coefficients is developed for the bulk microphysics frame work in Regional Atmospheric Modeling System (RAMS). Initial eddy-resolving model simulation is conducted to study the effect of surface kinetics on microphysical and dynamical processes in cold cloud development.

Mistletoe-induced growth reductions at the forest stand scale.

PubMed

Kollas, Chris; Gutsch, Martin; Hommel, Robert; Lasch-Born, Petra; Suckow, Felicitas

2018-05-01

The hemiparasite European mistletoe (Viscum album L.) adversely affects growth and reproduction of the host Scots pine (Pinus sylvestris L.) and in consequence may lead to tree death. Here, we aimed to estimate mistletoe-induced losses in timber yield applying the process-based forest growth model 4C. The parasite was implemented into the eco-physiological forest growth model 4C using (literature-derived) established impacts of the parasite on the tree's water and carbon cycle. The amended model was validated simulating a sample forest stand in the Berlin area (Germany) comprising trees with and without mistletoe infection. At the same forest stand, tree core measurements were taken to evaluate simulated and observed growth. A subsample of trees were harvested to quantify biomass compartments of the tree canopy and to derive a growth function of the mistletoe population. The process-based simulations of the forest stand revealed 27% reduction in basal area increment (BAI) during the last 9 years of heavy infection, which was confirmed by the measurements (29% mean growth reduction). The long-term simulations of the forest stand before and during the parasite infection showed that the amended forest growth model 4C depicts well the BAI growth pattern during >100 years and also quantifies well the mistletoe-induced growth reductions in Scots pine stands.

Mathematical models to characterize early epidemic growth: A Review

PubMed Central

Chowell, Gerardo; Sattenspiel, Lisa; Bansal, Shweta; Viboud, Cécile

2016-01-01

There is a long tradition of using mathematical models to generate insights into the transmission dynamics of infectious diseases and assess the potential impact of different intervention strategies. The increasing use of mathematical models for epidemic forecasting has highlighted the importance of designing reliable models that capture the baseline transmission characteristics of specific pathogens and social contexts. More refined models are needed however, in particular to account for variation in the early growth dynamics of real epidemics and to gain a better understanding of the mechanisms at play. Here, we review recent progress on modeling and characterizing early epidemic growth patterns from infectious disease outbreak data, and survey the types of mathematical formulations that are most useful for capturing a diversity of early epidemic growth profiles, ranging from sub-exponential to exponential growth dynamics. Specifically, we review mathematical models that incorporate spatial details or realistic population mixing structures, including meta-population models, individual-based network models, and simple SIR-type models that incorporate the effects of reactive behavior changes or inhomogeneous mixing. In this process, we also analyze simulation data stemming from detailed large-scale agent-based models previously designed and calibrated to study how realistic social networks and disease transmission characteristics shape early epidemic growth patterns, general transmission dynamics, and control of international disease emergencies such as the 2009 A/H1N1 influenza pandemic and the 2014-15 Ebola epidemic in West Africa. PMID:27451336

Mathematical models to characterize early epidemic growth: A review

NASA Astrophysics Data System (ADS)

Chowell, Gerardo; Sattenspiel, Lisa; Bansal, Shweta; Viboud, Cécile

2016-09-01

There is a long tradition of using mathematical models to generate insights into the transmission dynamics of infectious diseases and assess the potential impact of different intervention strategies. The increasing use of mathematical models for epidemic forecasting has highlighted the importance of designing reliable models that capture the baseline transmission characteristics of specific pathogens and social contexts. More refined models are needed however, in particular to account for variation in the early growth dynamics of real epidemics and to gain a better understanding of the mechanisms at play. Here, we review recent progress on modeling and characterizing early epidemic growth patterns from infectious disease outbreak data, and survey the types of mathematical formulations that are most useful for capturing a diversity of early epidemic growth profiles, ranging from sub-exponential to exponential growth dynamics. Specifically, we review mathematical models that incorporate spatial details or realistic population mixing structures, including meta-population models, individual-based network models, and simple SIR-type models that incorporate the effects of reactive behavior changes or inhomogeneous mixing. In this process, we also analyze simulation data stemming from detailed large-scale agent-based models previously designed and calibrated to study how realistic social networks and disease transmission characteristics shape early epidemic growth patterns, general transmission dynamics, and control of international disease emergencies such as the 2009 A/H1N1 influenza pandemic and the 2014-2015 Ebola epidemic in West Africa.

Czochralski crystal growth: Modeling study

NASA Technical Reports Server (NTRS)

Dudukovic, M. P.; Ramachandran, P. A.; Srivastava, R. K.; Dorsey, D.

1986-01-01

The modeling study of Czochralski (Cz) crystal growth is reported. The approach was to relate in a quantitative manner, using models based on first priniciples, crystal quality to operating conditions and geometric variables. The finite element method is used for all calculations.

Numerical simulation of dendrite growth in nickel-based superalloy and validated by in-situ observation using high temperature confocal laser scanning microscopy

NASA Astrophysics Data System (ADS)

Yan, Xuewei; Xu, Qingyan; Liu, Baicheng

2017-12-01

Dendritic structures are the predominant microstructural constituents of nickel-based superalloys, an understanding of the dendrite growth is required in order to obtain the desirable microstructure and improve the performance of castings. For this reason, numerical simulation method and an in-situ observation technology by employing high temperature confocal laser scanning microscopy (HT-CLSM) were used to investigate dendrite growth during solidification process. A combined cellular automaton-finite difference (CA-FD) model allowing for the prediction of dendrite growth of binary alloys was developed. The algorithm of cells capture was modified, and a deterministic cellular automaton (DCA) model was proposed to describe neighborhood tracking. The dendrite and detail morphology, especially hundreds of dendrites distribution at a large scale and three-dimensional (3-D) polycrystalline growth, were successfully simulated based on this model. The dendritic morphologies of samples before and after HT-CLSM were both observed by optical microscope (OM) and scanning electron microscope (SEM). The experimental observations presented a reasonable agreement with the simulation results. It was also found that primary or secondary dendrite arm spacing, and segregation pattern were significantly influenced by dendrite growth. Furthermore, the directional solidification (DS) dendritic evolution behavior and detail morphology were also simulated based on the proposed model, and the simulation results also agree well with experimental results.

Three-Dimension Visualization for Primary Wheat Diseases Based on Simulation Model

NASA Astrophysics Data System (ADS)

Shijuan, Li; Yeping, Zhu

Crop simulation model has been becoming the core of agricultural production management and resource optimization management. Displaying crop growth process makes user observe the crop growth and development intuitionisticly. On the basis of understanding and grasping the occurrence condition, popularity season, key impact factors for main wheat diseases of stripe rust, leaf rust, stem rust, head blight and powdery mildew from research material and literature, we designed 3D visualization model for wheat growth and diseases occurrence. The model system will help farmer, technician and decision-maker to use crop growth simulation model better and provide decision-making support. Now 3D visualization model for wheat growth on the basis of simulation model has been developed, and the visualization model for primary wheat diseases is in the process of development.

Probabilistic Prognosis of Non-Planar Fatigue Crack Growth

NASA Technical Reports Server (NTRS)

Leser, Patrick E.; Newman, John A.; Warner, James E.; Leser, William P.; Hochhalter, Jacob D.; Yuan, Fuh-Gwo

2016-01-01

Quantifying the uncertainty in model parameters for the purpose of damage prognosis can be accomplished utilizing Bayesian inference and damage diagnosis data from sources such as non-destructive evaluation or structural health monitoring. The number of samples required to solve the Bayesian inverse problem through common sampling techniques (e.g., Markov chain Monte Carlo) renders high-fidelity finite element-based damage growth models unusable due to prohibitive computation times. However, these types of models are often the only option when attempting to model complex damage growth in real-world structures. Here, a recently developed high-fidelity crack growth model is used which, when compared to finite element-based modeling, has demonstrated reductions in computation times of three orders of magnitude through the use of surrogate models and machine learning. The model is flexible in that only the expensive computation of the crack driving forces is replaced by the surrogate models, leaving the remaining parameters accessible for uncertainty quantification. A probabilistic prognosis framework incorporating this model is developed and demonstrated for non-planar crack growth in a modified, edge-notched, aluminum tensile specimen. Predictions of remaining useful life are made over time for five updates of the damage diagnosis data, and prognostic metrics are utilized to evaluate the performance of the prognostic framework. Challenges specific to the probabilistic prognosis of non-planar fatigue crack growth are highlighted and discussed in the context of the experimental results.

Measuring crown dynamics of longleaf pine in the sandhills of Eglin Air Force Base

Treesearch

Matt Anderson; Greg L. Somers; W. Rick Smith; Mickey Freeland; Donna Ruth

1998-01-01

The USDA Forest Service SRS, in cooperation with Auburn University, is developing an individual tree, spatially explicit, and btoiogicaily based growth model for natural iongieaf pine sands at Eglin Air Force Base in Florida. The goal of the growth model is to provide a tool for the land managers to compare silvicultural practices effects on the light and water...

A Power-Law Growth and Decay Model with Autocorrelation for Posting Data to Social Networking Services.

PubMed

Fujiyama, Toshifumi; Matsui, Chihiro; Takemura, Akimichi

2016-01-01

We propose a power-law growth and decay model for posting data to social networking services before and after social events. We model the time series structure of deviations from the power-law growth and decay with a conditional Poisson autoregressive (AR) model. Online postings related to social events are described by five parameters in the power-law growth and decay model, each of which characterizes different aspects of interest in the event. We assess the validity of parameter estimates in terms of confidence intervals, and compare various submodels based on likelihoods and information criteria.

A laboratory-calibrated model of coho salmon growth with utility for ecological analyses

USGS Publications Warehouse

Manhard, Christopher V.; Som, Nicholas A.; Perry, Russell W.; Plumb, John M.

2018-01-01

We conducted a meta-analysis of laboratory- and hatchery-based growth data to estimate broadly applicable parameters of mass- and temperature-dependent growth of juvenile coho salmon (Oncorhynchus kisutch). Following studies of other salmonid species, we incorporated the Ratkowsky growth model into an allometric model and fit this model to growth observations from eight studies spanning ten different populations. To account for changes in growth patterns with food availability, we reparameterized the Ratkowsky model to scale several of its parameters relative to ration. The resulting model was robust across a wide range of ration allocations and experimental conditions, accounting for 99% of the variation in final body mass. We fit this model to growth data from coho salmon inhabiting tributaries and constructed ponds in the Klamath Basin by estimating habitat-specific indices of food availability. The model produced evidence that constructed ponds provided higher food availability than natural tributaries. Because of their simplicity (only mass and temperature are required as inputs) and robustness, ration-varying Ratkowsky models have utility as an ecological tool for capturing growth in freshwater fish populations.

Kinetic Model of Growth of Arthropoda Populations

NASA Astrophysics Data System (ADS)

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

2018-05-01

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

Praedicere Possumus: An Italian web-based application for predictive microbiology to ensure food safety.

PubMed

Polese, Pierluigi; Torre, Manuela Del; Stecchini, Mara Lucia

2018-03-31

The use of predictive modelling tools, which mainly describe the response of microorganisms to a particular set of environmental conditions, may contribute to a better understanding of microbial behaviour in foods. In this paper, a tertiary model, in the form of a readily available and userfriendly web-based application Praedicere Possumus (PP) is presented with research examples from our laboratories. Through the PP application, users have access to different modules, which apply a set of published models considered reliable for determining the compliance of a food product with EU safety criteria and for optimising processing throughout the identification of critical control points. The application pivots around a growth/no-growth boundary model, coupled with a growth model, and includes thermal and non-thermal inactivation models. Integrated functionalities, such as the fractional contribution of each inhibitory factor to growth probability (f) and the time evolution of the growth probability (P t ), have also been included. The PP application is expected to assist food industry and food safety authorities in their common commitment towards the improvement of food safety.

A white-box model of S-shaped and double S-shaped single-species population growth

PubMed Central

Kalmykov, Lev V.

2015-01-01

Complex systems may be mechanistically modelled by white-box modeling with using logical deterministic individual-based cellular automata. Mathematical models of complex systems are of three types: black-box (phenomenological), white-box (mechanistic, based on the first principles) and grey-box (mixtures of phenomenological and mechanistic models). Most basic ecological models are of black-box type, including Malthusian, Verhulst, Lotka–Volterra models. In black-box models, the individual-based (mechanistic) mechanisms of population dynamics remain hidden. Here we mechanistically model the S-shaped and double S-shaped population growth of vegetatively propagated rhizomatous lawn grasses. Using purely logical deterministic individual-based cellular automata we create a white-box model. From a general physical standpoint, the vegetative propagation of plants is an analogue of excitation propagation in excitable media. Using the Monte Carlo method, we investigate a role of different initial positioning of an individual in the habitat. We have investigated mechanisms of the single-species population growth limited by habitat size, intraspecific competition, regeneration time and fecundity of individuals in two types of boundary conditions and at two types of fecundity. Besides that, we have compared the S-shaped and J-shaped population growth. We consider this white-box modeling approach as a method of artificial intelligence which works as automatic hyper-logical inference from the first principles of the studied subject. This approach is perspective for direct mechanistic insights into nature of any complex systems. PMID:26038717

Modeling the temporal periodicity of growth increments based on harmonic functions

PubMed Central

Morales-Bojórquez, Enrique; González-Peláez, Sergio Scarry; Bautista-Romero, J. Jesús; Lluch-Cota, Daniel Bernardo

2018-01-01

Age estimation methods based on hard structures require a process of validation to confirm the periodical pattern of growth marks. Among such processes, one of the most used is the marginal increment ratio (MIR), which was stated to follow a sinusoidal cycle in a population. Despite its utility, in most cases, its implementation has lacked robust statistical analysis. Accordingly, we propose a modeling approach for the temporal periodicity of growth increments based on single and second order harmonic functions. For illustrative purposes, the MIR periodicities for two geoduck species (Panopea generosa and Panopea globosa) were modeled to identify the periodical pattern of growth increments in the shell. This model identified an annual periodicity for both species but described different temporal patterns. The proposed procedure can be broadly used to objectively define the timing of the peak, the degree of symmetry, and therefore, the synchrony of band deposition of different species on the basis of MIR data. PMID:29694381

Population balance modeling: current status and future prospects.

PubMed

Ramkrishna, Doraiswami; Singh, Meenesh R

2014-01-01

Population balance modeling is undergoing phenomenal growth in its applications, and this growth is accompanied by multifarious reviews. This review aims to fortify the model's fundamental base, as well as point to a variety of new applications, including modeling of crystal morphology, cell growth and differentiation, gene regulatory processes, and transfer of drug resistance. This is accomplished by presenting the many faces of population balance equations that arise in the foregoing applications.

Monte Carlo grain growth modeling with local temperature gradients

NASA Astrophysics Data System (ADS)

Tan, Y.; Maniatty, A. M.; Zheng, C.; Wen, J. T.

2017-09-01

This work investigated the development of a Monte Carlo (MC) simulation approach to modeling grain growth in the presence of non-uniform temperature field that may vary with time. We first scale the MC model to physical growth processes by fitting experimental data. Based on the scaling relationship, we derive a grid site selection probability (SSP) function to consider the effect of a spatially varying temperature field. The SSP function is based on the differential MC step, which allows it to naturally consider time varying temperature fields too. We verify the model and compare the predictions to other existing formulations (Godfrey and Martin 1995 Phil. Mag. A 72 737-49 Radhakrishnan and Zacharia 1995 Metall. Mater. Trans. A 26 2123-30) in simple two-dimensional cases with only spatially varying temperature fields, where the predicted grain growth in regions of constant temperature are expected to be the same as for the isothermal case. We also test the model in a more realistic three-dimensional case with a temperature field varying in both space and time, modeling grain growth in the heat affected zone of a weld. We believe the newly proposed approach is promising for modeling grain growth in material manufacturing processes that involves time-dependent local temperature gradient.

Multiple new-particle growth pathways observed at the US DOE Southern Great Plains field site

DOE PAGES

Hodshire, Anna L.; Lawler, Michael J.; Zhao, Jun; ...

2016-07-28

New-particle formation (NPF) is a significant source of aerosol particles into the atmosphere. However, these particles are initially too small to have climatic importance and must grow, primarily through net uptake of low-volatility species, from diameters  ∼  1 to 30–100 nm in order to potentially impact climate. There are currently uncertainties in the physical and chemical processes associated with the growth of these freshly formed particles that lead to uncertainties in aerosol-climate modeling. Four main pathways for new-particle growth have been identified: condensation of sulfuric-acid vapor (and associated bases when available), condensation of organic vapors, uptake of organic acids through acid–base chemistrymore » in the particle phase, and accretion of organic molecules in the particle phase to create a lower-volatility compound that then contributes to the aerosol mass. The relative importance of each pathway is uncertain and is the focus of this work. The 2013 New Particle Formation Study (NPFS) measurement campaign took place at the DOE Southern Great Plains (SGP) facility in Lamont, Oklahoma, during spring 2013. Measured gas- and particle-phase compositions during these new-particle growth events suggest three distinct growth pathways: (1) growth by primarily organics, (2) growth by primarily sulfuric acid and ammonia, and (3) growth by primarily sulfuric acid and associated bases and organics. To supplement the measurements, we used the particle growth model MABNAG (Model for Acid–Base chemistry in NAnoparticle Growth) to gain further insight into the growth processes on these 3 days at SGP. MABNAG simulates growth from (1) sulfuric-acid condensation (and subsequent salt formation with ammonia or amines), (2) near-irreversible condensation from nonreactive extremely low-volatility organic compounds (ELVOCs), and (3) organic-acid condensation and subsequent salt formation with ammonia or amines. MABNAG is able to corroborate the observed differing growth pathways, while also predicting that ELVOCs contribute more to growth than organic salt formation. However, most MABNAG model simulations tend to underpredict the observed growth rates between 10 and 20 nm in diameter; this underprediction may come from neglecting the contributions to growth from semi-to-low-volatility species or accretion reactions. Our results suggest that in addition to sulfuric acid, ELVOCs are also very important for growth in this rural setting. We discuss the limitations of our study that arise from not accounting for semi- and low-volatility organics, as well as nitrogen-containing species beyond ammonia and amines in the model. Quantitatively understanding the overall budget, evolution, and thermodynamic properties of lower-volatility organics in the atmosphere will be essential for improving global aerosol models.« less

Growth model for uneven-aged loblolly pine stands : simulations and management implications

Treesearch

C.-R. Lin; J. Buongiorno; Jeffrey P. Prestemon; K. E. Skog

1998-01-01

A density-dependent matrix growth model of uneven-aged loblolly pine stands was developed with data from 991 permanent plots in the southern United States. The model predicts the number of pine, soft hardwood, and hard hardwood trees in 13 diameter classes, based on equations for ingrowth, upgrowth, and mortality. Projections of 6 to 10 years agreed with the growth...

Analytical modeling of fire growth on fire-resistive wood-based materials with changing conditions

Treesearch

Mark A. Dietenberger

2006-01-01

Our analytical model of fire growth for the ASTM E 84 tunnel, which simultaneously predicts heat release rate, flame-over area, and pyrolysis area as functions of time for constant conditions, was documented in the 2001 BCC Symposium for different treated wood materials. The model was extended to predict ignition and fire growth on exterior fire-resistive structures...

User's guide: RPGrow$: a red pine growth and analysis spreadsheet for the Lake States.

Treesearch

Carol A. Hyldahl; Gerald H. Grossman

1993-01-01

Describes RPGrow$, a stand-level, interactive spreadsheet for projecting growth and yield and estimating financial returns of red pine plantations in the Lake States. This spreadsheet is based on published growth models for red pine. Financial analyses are based on discounted cash flow methods.

Dendritic growth shapes in kinetic Monte Carlo models

NASA Astrophysics Data System (ADS)

Krumwiede, Tim R.; Schulze, Tim P.

2017-02-01

For the most part, the study of dendritic crystal growth has focused on continuum models featuring surface energies that yield six pointed dendrites. In such models, the growth shape is a function of the surface energy anisotropy, and recent work has shown that considering a broader class of anisotropies yields a correspondingly richer set of growth morphologies. Motivated by this work, we generalize nanoscale models of dendritic growth based on kinetic Monte Carlo simulation. In particular, we examine the effects of extending the truncation radius for atomic interactions in a bond-counting model. This is done by calculating the model’s corresponding surface energy and equilibrium shape, as well as by running KMC simulations to obtain nanodendritic growth shapes. Additionally, we compare the effects of extending the interaction radius in bond-counting models to that of extending the number of terms retained in the cubic harmonic expansion of surface energy anisotropy in the context of continuum models.

Simultaneous construction of PCR-DGGE-based predictive models of Listeria monocytogenes and Vibrio parahaemolyticus on cooked shrimps.

PubMed

Liao, C; Peng, Z Y; Li, J B; Cui, X W; Zhang, Z H; Malakar, P K; Zhang, W J; Pan, Y J; Zhao, Y

2015-03-01

The aim of this study was to simultaneously construct PCR-DGGE-based predictive models of Listeria monocytogenes and Vibrio parahaemolyticus on cooked shrimps at 4 and 10°C. Calibration curves were established to correlate peak density of DGGE bands with microbial counts. Microbial counts derived from PCR-DGGE and plate methods were fitted by Baranyi model to obtain molecular and traditional predictive models. For L. monocytogenes, growing at 4 and 10°C, molecular predictive models were constructed. It showed good evaluations of correlation coefficients (R(2) > 0.92), bias factors (Bf ) and accuracy factors (Af ) (1.0 ≤ Bf ≤ Af ≤ 1.1). Moreover, no significant difference was found between molecular and traditional predictive models when analysed on lag phase (λ), maximum growth rate (μmax ) and growth data (P > 0.05). But for V. parahaemolyticus, inactivated at 4 and 10°C, molecular models show significant difference when compared with traditional models. Taken together, these results suggest that PCR-DGGE based on DNA can be used to construct growth models, but it is inappropriate for inactivation models yet. This is the first report of developing PCR-DGGE to simultaneously construct multiple molecular models. It has been known for a long time that microbial predictive models based on traditional plate methods are time-consuming and labour-intensive. Denaturing gradient gel electrophoresis (DGGE) has been widely used as a semiquantitative method to describe complex microbial community. In our study, we developed DGGE to quantify bacterial counts and simultaneously established two molecular predictive models to describe the growth and survival of two bacteria (Listeria monocytogenes and Vibrio parahaemolyticus) at 4 and 10°C. We demonstrated that PCR-DGGE could be used to construct growth models. This work provides a new approach to construct molecular predictive models and thereby facilitates predictive microbiology and QMRA (Quantitative Microbial Risk Assessment). © 2014 The Society for Applied Microbiology.

Evaluating land-use change scenarios for the Puget Sound Basin, Washington, within the ecosystem recovery target model-based framework

USGS Publications Warehouse

Villarreal, Miguel; Labiosa, Bill; Aiello, Danielle

2017-05-23

The Puget Sound Basin, Washington, has experienced rapid urban growth in recent decades, with varying impacts to local ecosystems and natural resources. To plan for future growth, land managers often use scenarios to assess how the pattern and volume of growth may affect natural resources. Using three different land-management scenarios for the years 2000–2060, we assessed various spatial patterns of urban growth relative to maps depicting a model-based characterization of the ecological integrity and recent development pressure of individual land parcels. The three scenarios depict future trajectories of land-use change under alternative management strategies—status quo, managed growth, and unconstrained growth. The resulting analysis offers a preliminary assessment of how future growth patterns in the Puget Sound Basin may impact land targeted for conservation and how short-term metrics of land-development pressure compare to longer term growth projections.

An empirical model of the phytoplankton chlorophyll : carbon ratio-the conversion factor between productivity and growth rate

USGS Publications Warehouse

Cloern, James E.; Grenz, Christian; Vidergar-Lucas, Lisa

1995-01-01

We present an empirical model that describes the ratio of phytoplankton chlorophyll a to carbon, Chl: C, as a function of temperature, daily irradiance, and nutrient-limited growth rate. Our model is based on 219 published measurements of algal cultures exposed to light-limited or nutrient-limited growth conditions. We illustrate an approach for using this estimator of Chl: C to calculate phytoplankton population growth rate from measured primary productivity. This adaptive Chl: C model gives rise to interactive light-nutrient effects in which growth efficiency increases with nutrient availability under low-light conditions. One implication of this interaction is the enhancement of phytoplankton growth efficiency, in addition to enhancement of biomass yield, as a response to eutrophication.

The microcomputer scientific software series 6: ECOPHYS user's manual.

Treesearch

George E. Host; H. Michael Rauscher; J. G. Isebrands; Donald I. Dickmann; Richard E. Dickson; Thomas R. Crow; D.A. Michael

1990-01-01

ECOPHYS is an ecophysiological whole-tree growth process model designed to simulate the growth of poplar in the establishment year. This microcomputer-based model may be used to test the influence of genetically determined physiological or morphological attributes on plant growth. This manual describes the installation, file structures, and operational procedures for...

Growth in Mathematical Understanding: How Can We Characterise It and How Can We Represent It?

ERIC Educational Resources Information Center

Pirie, Susan; Kieren, Thomas

1994-01-01

Proposes a model for the growth of mathematical understanding based on the consideration of understanding as a whole, dynamic, leveled but nonlinear process. Illustrates the model using the concept of fractions. How to map the growth of understanding is explained in detail. (Contains 26 references.) (MKR)

Assessing the Reliability of Curriculum-Based Measurement: An Application of Latent Growth Modeling

ERIC Educational Resources Information Center

Yeo, Seungsoo; Kim, Dong-Il; Branum-Martin, Lee; Wayman, Miya Miura; Espin, Christine A.

2012-01-01

The purpose of this study was to demonstrate the use of Latent Growth Modeling (LGM) as a method for estimating reliability of Curriculum-Based Measurement (CBM) progress-monitoring data. The LGM approach permits the error associated with each measure to differ at each time point, thus providing an alternative method for examining of the…

Strategies for Balanced Rural-Urban Growth. Agricultural Information Bulletin No. 392.

ERIC Educational Resources Information Center

Edwards, Clark

Summarizing an Economic Research Service (ERS) publication, this guide to a balanced rural-urban growth describes the results of a computer based ERS model which examined seven strategies to improve rural economic development. Based on 1960-70 trends, the model is described as asking how much would be required of each of the following strategies…

Measurement of the volume growth rate of single budding yeast with the MOSFET-based microfluidic Coulter counter

PubMed Central

Sun, Jiashu; Stowers, Chris C.; Boczko, Erik M.

2012-01-01

We report on measurements of the volume growth rate of ten individual budding yeast cells using a recently developed MOSFET-based microfluidic Coulter counter. The MOSFET-based microfluidic Coulter counter is very sensitive, provides signals that are immune from the baseline drift, and can work with cell culture media of complex composition. These desirable features allow us to directly measure the volume growth rate of single cells of Saccharomyces cerevisiae LYH3865 strain budding yeast in YNB culture media over a whole cell cycle. Results indicate that all budding yeast follow a sigmoid volume growth profile with reduced growth rates at the initial stage before the bud emerges and the final stage after the daughter gets mature. Analysis of the data indicates that even though all piecewise linear, Gomperitz, and Hill’s function models can fit the global growth profile equally well, the data strongly support local exponential growth phenomenon. Accurate volume growth measurements are important for applications in systems biology where quantitative parameters are required for modeling and simulation. PMID:20717618

Measurement of the volume growth rate of single budding yeast with the MOSFET-based microfluidic Coulter counter.

PubMed

Sun, Jiashu; Stowers, Chris C; Boczko, Erik M; Li, Deyu

2010-11-07

We report on measurements of the volume growth rate of ten individual budding yeast cells using a recently developed MOSFET-based microfluidic Coulter counter. The MOSFET-based microfluidic Coulter counter is very sensitive, provides signals that are immune from the baseline drift, and can work with cell culture media of complex composition. These desirable features allow us to directly measure the volume growth rate of single cells of Saccharomyces cerevisiae LYH3865 strain budding yeast in YNB culture media over a whole cell cycle. Results indicate that all budding yeast follow a sigmoid volume growth profile with reduced growth rates at the initial stage before the bud emerges and the final stage after the daughter gets mature. Analysis of the data indicates that even though all piecewise linear, Gomperitz, and Hill's function models can fit the global growth profile equally well, the data strongly support local exponential growth phenomenon. Accurate volume growth measurements are important for applications in systems biology where quantitative parameters are required for modeling and simulation.

Development and validation of a mathematical model for growth of pathogens in cut melons.

PubMed

Li, Di; Friedrich, Loretta M; Danyluk, Michelle D; Harris, Linda J; Schaffner, Donald W

2013-06-01

Many outbreaks of foodborne illness associated with the consumption of fresh-cut melons have been reported. The objective of our research was to develop a mathematical model that predicts the growth rate of Salmonella on fresh-cut cantaloupe over a range of storage temperatures and to validate that model by using Salmonella and Escherichia coli O157:H7 on cantaloupe, honeydew, and watermelon, using both new data and data from the published studies. The growth of Salmonella on honeydew and watermelon and E. coli O157:H7 on cantaloupe, honeydew, and watermelon was monitored at temperatures of 4 to 25°C. The Ratkowsky (or square-root model) was used to describe Salmonella growth on cantaloupe as a function of storage temperature. Our results show that the levels of Salmonella on fresh-cut cantaloupe with an initial load of 3 log CFU/g can reach over 7 log CFU/g at 25°C within 24 h. No growth was observed at 4°C. A linear correlation was observed between the square root of Salmonella growth rate and temperature, such that √growth rate = 0.026 × (T - 5.613), R(2) = 0.9779. The model was generally suitable for predicting the growth of both Salmonella and E. coli O157:H7 on cantaloupe, honeydew, and watermelon, for both new data and data from the published literature. When compared with existing models for growth of Salmonella, the new model predicts a theoretic minimum growth temperature similar to the ComBase Predictive Models and Pathogen Modeling Program models but lower than other food-specific models. The ComBase Prediction Models results are very similar to the model developed in this study. Our research confirms that Salmonella can grow quickly and reach high concentrations when cut cantaloupe is stored at ambient temperatures, without visual signs of spoilage. Our model provides a fast and cost-effective method to estimate the effects of storage temperature on fresh-cut melon safety and could also be used in subsequent quantitative microbial risk assessments.

Evaluation of a lake whitefish bioenergetics model

USGS Publications Warehouse

Madenjian, Charles P.; O'Connor, Daniel V.; Pothoven, Steven A.; Schneeberger, Philip J.; Rediske, Richard R.; O'Keefe, James P.; Bergstedt, Roger A.; Argyle, Ray L.; Brandt, Stephen B.

2006-01-01

We evaluated the Wisconsin bioenergetics model for lake whitefish Coregonus clupeaformis in the laboratory and in the field. For the laboratory evaluation, lake whitefish were fed rainbow smelt Osmerus mordax in four laboratory tanks during a 133-d experiment. Based on a comparison of bioenergetics model predictions of lake whitefish food consumption and growth with observed consumption and growth, we concluded that the bioenergetics model furnished significantly biased estimates of both food consumption and growth. On average, the model overestimated consumption by 61% and underestimated growth by 16%. The source of the bias was probably an overestimation of the respiration rate. We therefore adjusted the respiration component of the bioenergetics model to obtain a good fit of the model to the observed consumption and growth in our laboratory tanks. Based on the adjusted model, predictions of food consumption over the 133-d period fell within 5% of observed consumption in three of the four tanks and within 9% of observed consumption in the remaining tank. We used polychlorinated biphenyls (PCBs) as a tracer to evaluate model performance in the field. Based on our laboratory experiment, the efficiency with which lake whitefish retained PCBs from their food (I?) was estimated at 0.45. We applied the bioenergetics model to Lake Michigan lake whitefish and then used PCB determinations of both lake whitefish and their prey from Lake Michigan to estimate p in the field. Application of the original model to Lake Michigan lake whitefish yielded a field estimate of 0.28, implying that the original formulation of the model overestimated consumption in Lake Michigan by 61%. Application of the bioenergetics model with the adjusted respiration component resulted in a field I? estimate of 0.56, implying that this revised model underestimated consumption by 20%.

Use of an uncertainty analysis for genome-scale models as a prediction tool for microbial growth processes in subsurface environments.

PubMed

Klier, Christine

2012-03-06

The integration of genome-scale, constraint-based models of microbial cell function into simulations of contaminant transport and fate in complex groundwater systems is a promising approach to help characterize the metabolic activities of microorganisms in natural environments. In constraint-based modeling, the specific uptake flux rates of external metabolites are usually determined by Michaelis-Menten kinetic theory. However, extensive data sets based on experimentally measured values are not always available. In this study, a genome-scale model of Pseudomonas putida was used to study the key issue of uncertainty arising from the parametrization of the influx of two growth-limiting substrates: oxygen and toluene. The results showed that simulated growth rates are highly sensitive to substrate affinity constants and that uncertainties in specific substrate uptake rates have a significant influence on the variability of simulated microbial growth. Michaelis-Menten kinetic theory does not, therefore, seem to be appropriate for descriptions of substrate uptake processes in the genome-scale model of P. putida. Microbial growth rates of P. putida in subsurface environments can only be accurately predicted if the processes of complex substrate transport and microbial uptake regulation are sufficiently understood in natural environments and if data-driven uptake flux constraints can be applied.

On the use and the performance of software reliability growth models

NASA Technical Reports Server (NTRS)

Keiller, Peter A.; Miller, Douglas R.

1991-01-01

We address the problem of predicting future failures for a piece of software. The number of failures occurring during a finite future time interval is predicted from the number failures observed during an initial period of usage by using software reliability growth models. Two different methods for using the models are considered: straightforward use of individual models, and dynamic selection among models based on goodness-of-fit and quality-of-prediction criteria. Performance is judged by the relative error of the predicted number of failures over future finite time intervals relative to the number of failures eventually observed during the intervals. Six of the former models and eight of the latter are evaluated, based on their performance on twenty data sets. Many open questions remain regarding the use and the performance of software reliability growth models.

Implementation of the dynamical system of the deposit and loan growth based on the Lotka-Volterra model and the improved model

NASA Astrophysics Data System (ADS)

Fadhlurrahman, Akmal; Sumarti, Novriana

2016-04-01

The Lotka-Volterra model is a very popular mathematical model based on the relationship in Ecology between predator, which is an organism that eats another organism, and prey, which is the organism which the predator eats. Predator and prey evolve together. The prey is part of the predator's environment, and the existence of the predator depends on the existence of the prey. As a dynamical system, this model could generate limit cycles, which is an interesting type of equilibrium sometime in the system of two or more dimensions. In [1,2], the dynamical system of the the Deposit and Loan Volumes based on the Lotka-Volterra Model had been developed. In this paper, we improve the definition of parameters in the model and then implement the model on the data of banking from January 2003 to December 2014 which consist of 4 (four) types of banks. The data is represented into the form of return in order to have data in a periodical-like form. The results show the periodicity in the deposit and loan growth data which is in line with paper in [3] that suggest the positive correlation between loan growth and deposit growth, and vice-versa.

A Power-Law Growth and Decay Model with Autocorrelation for Posting Data to Social Networking Services

PubMed Central

Fujiyama, Toshifumi; Matsui, Chihiro; Takemura, Akimichi

2016-01-01

We propose a power-law growth and decay model for posting data to social networking services before and after social events. We model the time series structure of deviations from the power-law growth and decay with a conditional Poisson autoregressive (AR) model. Online postings related to social events are described by five parameters in the power-law growth and decay model, each of which characterizes different aspects of interest in the event. We assess the validity of parameter estimates in terms of confidence intervals, and compare various submodels based on likelihoods and information criteria. PMID:27505155

Residual stresses in high temperature corrosion of pure zirconium using elasto-viscoplastic model: Application to the deflection test in monofacial oxidation

NASA Astrophysics Data System (ADS)

Fettré, D.; Bouvier, S.; Favergeon, J.; Kurpaska, L.

2015-12-01

The paper is devoted to modeling residual stresses and strains in an oxide film formed during high temperature oxidation. It describes the deflection test in isothermal high-temperature monofacial oxidation (DTMO) of pure zirconium. The model incorporates kinetics and mechanism of oxidation and takes into account elastic, viscoplastic, growth and chemical strains. Different growth strains models are considered, namely, isotropic growth strains given by Pilling-Bedworth ratio, anisotropic growth strains defined by Parise and co-authors and physically based model for growth strain proposed by Clarke. Creep mechanisms based on dislocation slip and core diffusion, are used. A mechanism responsible for through thickness normal stress gradient in the oxide film is proposed. The material parameters are identified using deflection tests under 400 °C, 500 °C and 600 °C. The effect of temperature on creep and stress relaxation is analyzed. Numerical sensitivity study of the DTMO experiment is proposed in order to investigate the effects of the initial foil thickness and platinum coating on the deflection curves.

[Employment and urban growth; an application of Czamanski's model to the Mexican case].

PubMed

Verduzco Chavez, B

1991-01-01

The author applies the 1964 model developed by Stanislaw Czamanski, based on theories of urban growth and industrial localization, to the analysis of urban growth in Mexico. "The advantages of this model in its application as a support instrument in the process of urban planning when the information available is incomplete are...discussed...." Census data for 44 cities in Mexico are used. (SUMMARY IN ENG) excerpt

Developing Inventory Projection Models Using Empirical Net Forest Growth and Growing-Stock Density Relationships Across U.S. Regions and Species Group

Treesearch

Prakash Nepal; Peter J. Ince; Kenneth E. Skog; Sun J. Chang

2012-01-01

This paper describes a set of empirical net forest growth models based on forest growing-stock density relationships for three U.S. regions (North, South, and West) and two species groups (softwoods and hardwoods) at the regional aggregate level. The growth models accurately predict historical U.S. timber inventory trends when we incorporate historical timber harvests...

Quantitative model of the growth of floodplains by vertical accretion

USGS Publications Warehouse

Moody, J.A.; Troutman, B.M.

2000-01-01

A simple one-dimensional model is developed to quantitatively predict the change in elevation, over a period of decades, for vertically accreting floodplains. This unsteady model approximates the monotonic growth of a floodplain as an incremental but constant increase of net sediment deposition per flood for those floods of a partial duration series that exceed a threshold discharge corresponding to the elevation of the floodplain. Sediment deposition from each flood increases the elevation of the floodplain and consequently the magnitude of the threshold discharge resulting in a decrease in the number of floods and growth rate of the floodplain. Floodplain growth curves predicted by this model are compared to empirical growth curves based on dendrochronology and to direct field measurements at five floodplain sites. The model was used to predict the value of net sediment deposition per flood which best fits (in a least squares sense) the empirical and field measurements; these values fall within the range of independent estimates of the net sediment deposition per flood based on empirical equations. These empirical equations permit the application of the model to estimate of floodplain growth for other floodplains throughout the world which do not have detailed data of sediment deposition during individual floods. Copyright (C) 2000 John Wiley and Sons, Ltd.

Storage and growth of denitrifiers in aerobic granules: part I. model development.

PubMed

Ni, Bing-Jie; Yu, Han-Qing

2008-02-01

A mathematical model, based on the Activated Sludge Model No.3 (ASM3), is developed to describe the storage and growth activities of denitrifiers in aerobic granules under anoxic conditions. In this model, mass transfer, hydrolysis, simultaneous anoxic storage and growth, anoxic maintenance, and endogenous decay are all taken into account. The model established is implemented in the well-established AQUASIM simulation software. A combination of completely mixed reactor and biofilm reactor compartments provided by AQUASIM is used to simulate the mass transport and conversion processes occurring in both bulk liquid and granules. The modeling results explicitly show that the external substrate is immediately utilized for storage and growth at feast phase. More external substrates are diverted to storage process than the primary biomass production process. The model simulation indicates that the nitrate utilization rate (NUR) of granules-based denitrification process includes four linear phases of nitrate reduction. Furthermore, the methodology for determining the most important parameter in this model, that is, anoxic reduction factor, is established. (c) 2007 Wiley Periodicals, Inc.

Dendritic solidification. I - Analysis of current theories and models. II - A model for dendritic growth under an imposed thermal gradient

NASA Technical Reports Server (NTRS)

Laxmanan, V.

1985-01-01

A critical review of the present dendritic growth theories and models is presented. Mathematically rigorous solutions to dendritic growth are found to rely on an ad hoc assumption that dendrites grow at the maximum possible growth rate. This hypothesis is found to be in error and is replaced by stability criteria which consider the conditions under which a dendrite tip advances in a stable fashion in a liquid. The important elements of a satisfactory model for dendritic solidification are summarized and a theoretically consistent model for dendritic growth under an imposed thermal gradient is proposed and described. The model is based on the modification of an analysis due to Burden and Hunt (1974) and predicts correctly in all respects, the transition from a dendritic to a planar interface at both very low and very large growth rates.

Large historical growth in global terrestrial gross primary production

DOE PAGES

Campbell, J. E.; Berry, J. A.; Seibt, U.; ...

2017-04-05

Growth in terrestrial gross primary production (GPP) may provide a negative feedback for climate change. It remains uncertain, however, to what extent biogeochemical processes can suppress global GPP growth. In consequence, model estimates of terrestrial carbon storage and carbon cycle –climate feedbacks remain poorly constrained. Here we present a global, measurement-based estimate of GPP growth during the twentieth century based on long-term atmospheric carbonyl sulphide (COS) records derived from ice core, firn, and ambient air samples. Here, we interpret these records using a model that simulates changes in COS concentration due to changes in its sources and sinks, including amore » large sink that is related to GPP. We find that the COS record is most consistent with climate-carbon cycle model simulations that assume large GPP growth during the twentieth century (31% ± 5%; mean ± 95% confidence interval). Finally, while this COS analysis does not directly constrain estimates of future GPP growth it provides a global-scale benchmark for historical carbon cycle simulations.« less

Large historical growth in global terrestrial gross primary production

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

Campbell, J. E.; Berry, J. A.; Seibt, U.

Growth in terrestrial gross primary production (GPP) may provide a negative feedback for climate change. It remains uncertain, however, to what extent biogeochemical processes can suppress global GPP growth. In consequence, model estimates of terrestrial carbon storage and carbon cycle –climate feedbacks remain poorly constrained. Here we present a global, measurement-based estimate of GPP growth during the twentieth century based on long-term atmospheric carbonyl sulphide (COS) records derived from ice core, firn, and ambient air samples. Here, we interpret these records using a model that simulates changes in COS concentration due to changes in its sources and sinks, including amore » large sink that is related to GPP. We find that the COS record is most consistent with climate-carbon cycle model simulations that assume large GPP growth during the twentieth century (31% ± 5%; mean ± 95% confidence interval). Finally, while this COS analysis does not directly constrain estimates of future GPP growth it provides a global-scale benchmark for historical carbon cycle simulations.« less

A Finite Element Model for Mixed Porohyperelasticity with Transport, Swelling, and Growth.

PubMed

Armstrong, Michelle Hine; Buganza Tepole, Adrián; Kuhl, Ellen; Simon, Bruce R; Vande Geest, Jonathan P

2016-01-01

The purpose of this manuscript is to establish a unified theory of porohyperelasticity with transport and growth and to demonstrate the capability of this theory using a finite element model developed in MATLAB. We combine the theories of volumetric growth and mixed porohyperelasticity with transport and swelling (MPHETS) to derive a new method that models growth of biological soft tissues. The conservation equations and constitutive equations are developed for both solid-only growth and solid/fluid growth. An axisymmetric finite element framework is introduced for the new theory of growing MPHETS (GMPHETS). To illustrate the capabilities of this model, several example finite element test problems are considered using model geometry and material parameters based on experimental data from a porcine coronary artery. Multiple growth laws are considered, including time-driven, concentration-driven, and stress-driven growth. Time-driven growth is compared against an exact analytical solution to validate the model. For concentration-dependent growth, changing the diffusivity (representing a change in drug) fundamentally changes growth behavior. We further demonstrate that for stress-dependent, solid-only growth of an artery, growth of an MPHETS model results in a more uniform hoop stress than growth in a hyperelastic model for the same amount of growth time using the same growth law. This may have implications in the context of developing residual stresses in soft tissues under intraluminal pressure. To our knowledge, this manuscript provides the first full description of an MPHETS model with growth. The developed computational framework can be used in concert with novel in-vitro and in-vivo experimental approaches to identify the governing growth laws for various soft tissues.

A Finite Element Model for Mixed Porohyperelasticity with Transport, Swelling, and Growth

PubMed Central

Armstrong, Michelle Hine; Buganza Tepole, Adrián; Kuhl, Ellen; Simon, Bruce R.; Vande Geest, Jonathan P.

2016-01-01

The purpose of this manuscript is to establish a unified theory of porohyperelasticity with transport and growth and to demonstrate the capability of this theory using a finite element model developed in MATLAB. We combine the theories of volumetric growth and mixed porohyperelasticity with transport and swelling (MPHETS) to derive a new method that models growth of biological soft tissues. The conservation equations and constitutive equations are developed for both solid-only growth and solid/fluid growth. An axisymmetric finite element framework is introduced for the new theory of growing MPHETS (GMPHETS). To illustrate the capabilities of this model, several example finite element test problems are considered using model geometry and material parameters based on experimental data from a porcine coronary artery. Multiple growth laws are considered, including time-driven, concentration-driven, and stress-driven growth. Time-driven growth is compared against an exact analytical solution to validate the model. For concentration-dependent growth, changing the diffusivity (representing a change in drug) fundamentally changes growth behavior. We further demonstrate that for stress-dependent, solid-only growth of an artery, growth of an MPHETS model results in a more uniform hoop stress than growth in a hyperelastic model for the same amount of growth time using the same growth law. This may have implications in the context of developing residual stresses in soft tissues under intraluminal pressure. To our knowledge, this manuscript provides the first full description of an MPHETS model with growth. The developed computational framework can be used in concert with novel in-vitro and in-vivo experimental approaches to identify the governing growth laws for various soft tissues. PMID:27078495

Dynamic Predictive Model for Growth of Bacillus cereus from Spores in Cooked Beans.

PubMed

Juneja, Vijay K; Mishra, Abhinav; Pradhan, Abani K

2018-02-01

Kinetic growth data for Bacillus cereus grown from spores were collected in cooked beans under several isothermal conditions (10 to 49°C). Samples were inoculated with approximately 2 log CFU/g heat-shocked (80°C for 10 min) spores and stored at isothermal temperatures. B. cereus populations were determined at appropriate intervals by plating on mannitol-egg yolk-polymyxin agar and incubating at 30°C for 24 h. Data were fitted into Baranyi, Huang, modified Gompertz, and three-phase linear primary growth models. All four models were fitted to the experimental growth data collected at 13 to 46°C. Performances of these models were evaluated based on accuracy and bias factors, the coefficient of determination ( R 2 ), and the root mean square error. Based on these criteria, the Baranyi model best described the growth data, followed by the Huang, modified Gompertz, and three-phase linear models. The maximum growth rates of each primary model were fitted as a function of temperature using the modified Ratkowsky model. The high R 2 values (0.95 to 0.98) indicate that the modified Ratkowsky model can be used to describe the effect of temperature on the growth rates for all four primary models. The acceptable prediction zone (APZ) approach also was used for validation of the model with observed data collected during single and two-step dynamic cooling temperature protocols. When the predictions using the Baranyi model were compared with the observed data using the APZ analysis, all 24 observations for the exponential single rate cooling were within the APZ, which was set between -0.5 and 1 log CFU/g; 26 of 28 predictions for the two-step cooling profiles also were within the APZ limits. The developed dynamic model can be used to predict potential B. cereus growth from spores in beans under various temperature conditions or during extended chilling of cooked beans.

Simulating Cancer Growth with Multiscale Agent-Based Modeling

PubMed Central

Wang, Zhihui; Butner, Joseph D.; Kerketta, Romica; Cristini, Vittorio; Deisboeck, Thomas S.

2014-01-01

There have been many techniques developed in recent years to in silico model a variety of cancer behaviors. Agent-based modeling is a specific discrete-based hybrid modeling approach that allows simulating the role of diversity in cell populations as well as within each individual cell; it has therefore become a powerful modeling method widely used by computational cancer researchers. Many aspects of tumor morphology including phenotype-changing mutations, the adaptation to microenvironment, the process of angiogenesis, the influence of extracellular matrix, reactions to chemotherapy or surgical intervention, the effects of oxygen and nutrient availability, and metastasis and invasion of healthy tissues have been incorporated and investigated in agent-based models. In this review, we introduce some of the most recent agent-based models that have provided insight into the understanding of cancer growth and invasion, spanning multiple biological scales in time and space, and we further describe several experimentally testable hypotheses generated by those models. We also discuss some of the current challenges of multiscale agent-based cancer models. PMID:24793698

Modeling the effects of ozone on soybean growth and yield.

PubMed

Kobayashi, K; Miller, J E; Flagler, R B; Heck, W W

1990-01-01

A simple mechanistic model was developed based on an existing growth model in order to address the mechanisms of the effects of ozone on growth and yield of soybean [Glycine max. (L.) Merr. 'Davis'] and interacting effects of other environmental stresses. The model simulates daily growth of soybean plants using environmental data including shortwave radiation, temperature, precipitation, irrigation and ozone concentration. Leaf growth, dry matter accumulation, water budget, nitrogen input and seed growth linked to senescence and abscission of leaves are described in the model. The effects of ozone are modeled as reduced photosynthate production and accelerated senescence. The model was applied to the open-top chamber experiments in which soybean plants were exposed to ozone under two levels of soil moisture regimes. After calibrating the model to the growth data and seed yield, goodness-of-fit of the model was tested. The model fitted well for top dry weight in the vegetative growth phase and also at maturity. The effect of ozone on seen yield was also described satisfactorily by the model. The simulation showed apparent interaction between the effect of ozone and soil moisture stress on the seed yield. The model revealed that further work is needed concerning the effect of ozone on the senescence process and the consequences of alteration of canopy microclimate by the open-top chambers.

On the evolution of developmental mechanisms: Divergent polarities in leaf growth as a case study.

PubMed

Gupta, Mainak Das; Nath, Utpal

2016-01-01

Most model plants used to study leaf growth share a common developmental mechanism, namely basipetal growth polarity, wherein the distal end differentiates first with progressively more proliferative cells toward the base. Therefore, this base-to-tip growth pattern has served as a paradigm to explain leaf growth and also formed the basis for several computational models. However, our recent report in The Plant Cell on the investigation of leaf growth in 75 eudicot species covering a wide range of eudicot families showed that leaves grow with divergent polarities in the proximo-distal axis or without any obvious polarity. This divergence in growth polarity is linked to the expression divergence of a conserved microRNA-transcription factor module. This study raises several questions on the evolutionary origin of leaf growth pattern, such as 'when and why in evolution did the divergent growth polarities arise?' and 'what were the molecular changes that led to this divergence?'. Here, we discuss a few of these questions in some detail.

Statistical Test for Latent Growth Nonlinearity with Three Time Points. Research Brief 8

ERIC Educational Resources Information Center

Nese, Joseph F. T.

2013-01-01

Curriculum-based measurement (CBM) is a system of assessment used to screen for students at risk for poor learning. CBM benchmark screening assessments are typically administered to all students in the fall, winter, and spring, and these data are frequently used by researchers to model and perhaps explain within-year growth. Modeling growth with…

3-PG simulations of young ponderosa pine plantations under varied management intensity: why do they grow so differently?

Treesearch

Liang Wei; Marshall John; Jianwei Zhang; Hang Zhou; Robert Powers

2014-01-01

Models can be powerful tools for estimating forest productivity and guiding forest management, but their credibility and complexity are often an issue for forest managers. We parameterized a process-based forest growth model, 3-PG (Physiological Principles Predicting Growth), to simulate growth of ponderosa pine (Pinus ponderosa) plantations in...

Modeling the population dynamics of Pacific yew.

Treesearch

Richard T. Busing; Thomas A. Spies

1995-01-01

A study of Pacific yew (Taxus brevifolia Nutt.) population dynamics in the mountains of western Oregon and Washington was based on a combination of long-term population data and computer modeling. Rates of growth and mortality were low in mature and old-growth forest stands. Diameter growth at breast height ranged from 0 to 3 centimeters per decade...

NASA Experimental Program to Stimulate Competitive Research: South Carolina

NASA Technical Reports Server (NTRS)

Sutton, Michael A.

2004-01-01

The use of an appropriate relationship model is critical for reliable prediction of future urban growth. Identification of proper variables and mathematic functions and determination of the weights or coefficients are the key tasks for building such a model. Although the conventional logistic regression model is appropriate for handing land use problems, it appears insufficient to address the issue of interdependency of the predictor variables. This study used an alternative approach to simulation and modeling urban growth using artificial neural networks. It developed an operational neural network model trained using a robust backpropagation method. The model was applied in the Myrtle Beach region of South Carolina, and tested with both global datasets and areal datasets to examine the strength of both regional models and areal models. The results indicate that the neural network model not only has many theoretic advantages over other conventional mathematic models in representing the complex urban systems, but also is practically superior to the logistic model in its capability to predict urban growth with better - accuracy and less variation. The neural network model is particularly effective in terms of successfully identifying urban patterns in the rural areas where the logistic model often falls short. It was also found from the area-based tests that there are significant intra-regional differentiations in urban growth with different rules and rates. This suggests that the global modeling approach, or one model for the entire region, may not be adequate for simulation of a urban growth at the regional scale. Future research should develop methods for identification and subdivision of these areas and use a set of area-based models to address the issues of multi-centered, intra- regionally differentiated urban growth.

Development of a hybrid modeling approach for predicting intensively managed Douglas-fir growth at multiple scales.

Treesearch

A. Weiskittel; D. Maguire; R. Monserud

2007-01-01

Hybrid models offer the opportunity to improve future growth projections by combining advantages of both empirical and process-based modeling approaches. Hybrid models have been constructed in several regions and their performance relative to a purely empirical approach has varied. A hybrid model was constructed for intensively managed Douglas-fir plantations in the...

Mechanistic modelling of the inhibitory effect of pH on microbial growth.

PubMed

Akkermans, Simen; Van Impe, Jan F

2018-06-01

Modelling and simulation of microbial dynamics as a function of processing, transportation and storage conditions is a useful tool to improve microbial food safety and quality. The goal of this research is to improve an existing methodology for building mechanistic predictive models based on the environmental conditions. The effect of environmental conditions on microbial dynamics is often described by combining the separate effects in a multiplicative way (gamma concept). This idea was extended further in this work by including the effects of the lag and stationary growth phases on microbial growth rate as independent gamma factors. A mechanistic description of the stationary phase as a function of pH was included, based on a novel class of models that consider product inhibition. Experimental results on Escherichia coli growth dynamics indicated that also the parameters of the product inhibition equations can be modelled with the gamma approach. This work has extended a modelling methodology, resulting in predictive models that are (i) mechanistically inspired, (ii) easily identifiable with a limited work load and (iii) easily extended to additional environmental conditions. Copyright © 2017. Published by Elsevier Ltd.

A nonlinear CDM based damage growth law for ductile materials

NASA Astrophysics Data System (ADS)

Gautam, Abhinav; Priya Ajit, K.; Sarkar, Prabir Kumar

2018-02-01

A nonlinear ductile damage growth criterion is proposed based on continuum damage mechanics (CDM) approach. The model is derived in the framework of thermodynamically consistent CDM assuming damage to be isotropic. In this study, the damage dissipation potential is also derived to be a function of varying strain hardening exponent in addition to damage strain energy release rate density. Uniaxial tensile tests and load-unload-cyclic tensile tests for AISI 1020 steel, AISI 1030 steel and Al 2024 aluminum alloy are considered for the determination of their respective damage variable D and other parameters required for the model(s). The experimental results are very closely predicted, with a deviation of 0%-3%, by the proposed model for each of the materials. The model is also tested with predictabilities of damage growth by other models in the literature. Present model detects the state of damage quantitatively at any level of plastic strain and uses simpler material tests to find the parameters of the model. So, it should be useful in metal forming industries to assess the damage growth for the desired deformation level a priori. The superiority of the new model is clarified by the deviations in the predictability of test results by other models.

Stabilizing detached Bridgman melt crystal growth: Model-based nonlinear feedback control

NASA Astrophysics Data System (ADS)

Yeckel, Andrew; Daoutidis, Prodromos; Derby, Jeffrey J.

2012-12-01

The dynamics and operability limits of a nonlinear-proportional-integral controller designed to stabilize detached vertical Bridgman crystal growth are studied. The manipulated variable is the pressure difference between upper and lower vapor spaces, and the controlled variable is the gap width at the triple-phase line. The controller consists of a model-based nonlinear component coupled with a standard proportional-integral controller. The nonlinear component is based on a capillary model of shape stability. Perturbations to gap width, pressure difference, wetting angle, and growth angle are studied under both shape stable and shape unstable conditions. The nonlinear-PI controller allows a wider operating range of gain than a standard PI controller used alone, is easier to tune, and eliminates solution multiplicity from closed-loop operation.

Monitoring growth condition of spring maize in Northeast China using a process-based model

NASA Astrophysics Data System (ADS)

Wang, Peijuan; Zhou, Yuyu; Huo, Zhiguo; Han, Lijuan; Qiu, Jianxiu; Tan, Yanjng; Liu, Dan

2018-04-01

Early and accurate assessment of the growth condition of spring maize, a major crop in China, is important for the national food security. This study used a process-based Remote-Sensing-Photosynthesis-Yield Estimation for Crops (RS-P-YEC) model, driven by satellite-derived leaf area index and ground-based meteorological observations, to simulate net primary productivity (NPP) of spring maize in Northeast China from the first ten-day (FTD) of May to the second ten-day (STD) of August during 2001-2014. The growth condition of spring maize in 2014 in Northeast China was monitored and evaluated spatially and temporally by comparison with 5- and 13-year averages, as well as 2009 and 2013. Results showed that NPP simulated by the RS-P-YEC model, with consideration of multi-scattered radiation inside the crop canopy, could reveal the growth condition of spring maize more reasonably than the Boreal Ecosystem Productivity Simulator. Moreover, NPP outperformed other commonly used vegetation indices (e.g., Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI)) for monitoring and evaluating the growth condition of spring maize. Compared with the 5- and 13-year averages, the growth condition of spring maize in 2014 was worse before the STD of June and after the FTD of August, and it was better from the third ten-day (TTD) of June to the TTD of July across Northeast China. Spatially, regions with slightly worse and worse growth conditions in the STD of August 2014 were concentrated mainly in central Northeast China, and they accounted for about half of the production area of spring maize in Northeast China. This study confirms that NPP is a good indicator for monitoring and evaluating growth condition because of its capacity to reflect the physiological characteristics of crops. Meanwhile, the RS-P-YEC model, driven by remote sensing and ground-based meteorological data, is effective for monitoring crop growth condition over large areas in a near real time.

Modeling of time dependent localized flow shear stress and its impact on cellular growth within additive manufactured titanium implants

PubMed Central

Zhang, Ziyu; Yuan, Lang; Lee, Peter D; Jones, Eric; Jones, Julian R

2014-01-01

Bone augmentation implants are porous to allow cellular growth, bone formation and fixation. However, the design of the pores is currently based on simple empirical rules, such as minimum pore and interconnects sizes. We present a three-dimensional (3D) transient model of cellular growth based on the Navier–Stokes equations that simulates the body fluid flow and stimulation of bone precursor cellular growth, attachment, and proliferation as a function of local flow shear stress. The model's effectiveness is demonstrated for two additive manufactured (AM) titanium scaffold architectures. The results demonstrate that there is a complex interaction of flow rate and strut architecture, resulting in partially randomized structures having a preferential impact on stimulating cell migration in 3D porous structures for higher flow rates. This novel result demonstrates the potential new insights that can be gained via the modeling tool developed, and how the model can be used to perform what-if simulations to design AM structures to specific functional requirements. PMID:24664988

Urban Growth Modeling Using Cellular Automata with Multi-Temporal Remote Sensing Images Calibrated by the Artificial Bee Colony Optimization Algorithm.

PubMed

Naghibi, Fereydoun; Delavar, Mahmoud Reza; Pijanowski, Bryan

2016-12-14

Cellular Automata (CA) is one of the most common techniques used to simulate the urbanization process. CA-based urban models use transition rules to deliver spatial patterns of urban growth and urban dynamics over time. Determining the optimum transition rules of the CA is a critical step because of the heterogeneity and nonlinearities existing among urban growth driving forces. Recently, new CA models integrated with optimization methods based on swarm intelligence algorithms were proposed to overcome this drawback. The Artificial Bee Colony (ABC) algorithm is an advanced meta-heuristic swarm intelligence-based algorithm. Here, we propose a novel CA-based urban change model that uses the ABC algorithm to extract optimum transition rules. We applied the proposed ABC-CA model to simulate future urban growth in Urmia (Iran) with multi-temporal Landsat images from 1997, 2006 and 2015. Validation of the simulation results was made through statistical methods such as overall accuracy, the figure of merit and total operating characteristics (TOC). Additionally, we calibrated the CA model by ant colony optimization (ACO) to assess the performance of our proposed model versus similar swarm intelligence algorithm methods. We showed that the overall accuracy and the figure of merit of the ABC-CA model are 90.1% and 51.7%, which are 2.9% and 8.8% higher than those of the ACO-CA model, respectively. Moreover, the allocation disagreement of the simulation results for the ABC-CA model is 9.9%, which is 2.9% less than that of the ACO-CA model. Finally, the ABC-CA model also outperforms the ACO-CA model with fewer quantity and allocation errors and slightly more hits.

Urban Growth Modeling Using Cellular Automata with Multi-Temporal Remote Sensing Images Calibrated by the Artificial Bee Colony Optimization Algorithm

PubMed Central

Naghibi, Fereydoun; Delavar, Mahmoud Reza; Pijanowski, Bryan

2016-01-01

Cellular Automata (CA) is one of the most common techniques used to simulate the urbanization process. CA-based urban models use transition rules to deliver spatial patterns of urban growth and urban dynamics over time. Determining the optimum transition rules of the CA is a critical step because of the heterogeneity and nonlinearities existing among urban growth driving forces. Recently, new CA models integrated with optimization methods based on swarm intelligence algorithms were proposed to overcome this drawback. The Artificial Bee Colony (ABC) algorithm is an advanced meta-heuristic swarm intelligence-based algorithm. Here, we propose a novel CA-based urban change model that uses the ABC algorithm to extract optimum transition rules. We applied the proposed ABC-CA model to simulate future urban growth in Urmia (Iran) with multi-temporal Landsat images from 1997, 2006 and 2015. Validation of the simulation results was made through statistical methods such as overall accuracy, the figure of merit and total operating characteristics (TOC). Additionally, we calibrated the CA model by ant colony optimization (ACO) to assess the performance of our proposed model versus similar swarm intelligence algorithm methods. We showed that the overall accuracy and the figure of merit of the ABC-CA model are 90.1% and 51.7%, which are 2.9% and 8.8% higher than those of the ACO-CA model, respectively. Moreover, the allocation disagreement of the simulation results for the ABC-CA model is 9.9%, which is 2.9% less than that of the ACO-CA model. Finally, the ABC-CA model also outperforms the ACO-CA model with fewer quantity and allocation errors and slightly more hits. PMID:27983633

A semi-empirical model for the complete orientation dependence of the growth rate for vapor phase epitaxy - Chloride VPE of GaAs

NASA Technical Reports Server (NTRS)

Seidel-Salinas, L. K.; Jones, S. H.; Duva, J. M.

1992-01-01

A semi-empirical model has been developed to determine the complete crystallographic orientation dependence of the growth rate for vapor phase epitaxy (VPE). Previous researchers have been able to determine this dependence for a limited range of orientations; however, our model yields relative growth rate information for any orientation. This model for diamond and zincblende structure materials is based on experimental growth rate data, gas phase diffusion, and surface reactions. Data for GaAs chloride VPE is used to illustrate the model. The resulting growth rate polar diagrams are used in conjunction with Wulff constructions to simulate epitaxial layer shapes as grown on patterned substrates. In general, this model can be applied to a variety of materials and vapor phase epitaxy systems.

Predicting the impact of combined therapies on myeloma cell growth using a hybrid multi-scale agent-based model.

PubMed

Ji, Zhiwei; Su, Jing; Wu, Dan; Peng, Huiming; Zhao, Weiling; Nlong Zhao, Brian; Zhou, Xiaobo

2017-01-31

Multiple myeloma is a malignant still incurable plasma cell disorder. This is due to refractory disease relapse, immune impairment, and development of multi-drug resistance. The growth of malignant plasma cells is dependent on the bone marrow (BM) microenvironment and evasion of the host's anti-tumor immune response. Hence, we hypothesized that targeting tumor-stromal cell interaction and endogenous immune system in BM will potentially improve the response of multiple myeloma (MM). Therefore, we proposed a computational simulation of the myeloma development in the complicated microenvironment which includes immune cell components and bone marrow stromal cells and predicted the effects of combined treatment with multi-drugs on myeloma cell growth. We constructed a hybrid multi-scale agent-based model (HABM) that combines an ODE system and Agent-based model (ABM). The ODEs was used for modeling the dynamic changes of intracellular signal transductions and ABM for modeling the cell-cell interactions between stromal cells, tumor, and immune components in the BM. This model simulated myeloma growth in the bone marrow microenvironment and revealed the important role of immune system in this process. The predicted outcomes were consistent with the experimental observations from previous studies. Moreover, we applied this model to predict the treatment effects of three key therapeutic drugs used for MM, and found that the combination of these three drugs potentially suppress the growth of myeloma cells and reactivate the immune response. In summary, the proposed model may serve as a novel computational platform for simulating the formation of MM and evaluating the treatment response of MM to multiple drugs.

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

Yang, Laurence; Yurkovich, James T.; Lloyd, Colton J.

Integrating omics data to refine or make context-specific models is an active field of constraint-based modeling. Proteomics now cover over 95% of the Escherichia coli proteome by mass. Genome-scale models of Metabolism and macromolecular Expression (ME) compute proteome allocation linked to metabolism and fitness. Using proteomics data, we formulated allocation constraints for key proteome sectors in the ME model. The resulting calibrated model effectively computed the “generalist” (wild-type) E. coli proteome and phenotype across diverse growth environments. Across 15 growth conditions, prediction errors for growth rate and metabolic fluxes were 69% and 14% lower, respectively. The sector-constrained ME model thusmore » represents a generalist ME model reflecting both growth rate maximization and “hedging” against uncertain environments and stresses, as indicated by significant enrichment of these sectors for the general stress response sigma factor σS. Finally, the sector constraints represent a general formalism for integrating omics data from any experimental condition into constraint-based ME models. The constraints can be fine-grained (individual proteins) or coarse-grained (functionally-related protein groups) as demonstrated here. Furthermore, this flexible formalism provides an accessible approach for narrowing the gap between the complexity captured by omics data and governing principles of proteome allocation described by systems-level models.« less

[Three-dimensional morphological modeling and visualization of wheat root system].

PubMed

Tan, Feng; Tang, Liang; Hu, Jun-Cheng; Jiang, Hai-Yan; Cao, Wei-Xing; Zhu, Yan

2011-01-01

Crop three-dimensional (3D) morphological modeling and visualization is an important part of digital plant study. This paper aimed to develop a 3D morphological model of wheat root system based on the parameters of wheat root morphological features, and to realize the visualization of wheat root growth. According to the framework of visualization technology for wheat root growth, a 3D visualization model of wheat root axis, including root axis growth model, branch geometric model, and root axis curve model, was developed firstly. Then, by integrating root topology, the corresponding pixel was determined, and the whole wheat root system was three-dimensionally re-constructed by using the morphological feature parameters in the root morphological model. Finally, based on the platform of OpenGL, and by integrating the technologies of texture mapping, lighting rendering, and collision detection, the 3D visualization of wheat root growth was realized. The 3D output of wheat root system from the model was vivid, which could realize the 3D root system visualization of different wheat cultivars under different water regimes and nitrogen application rates. This study could lay a technical foundation for further development of an integral visualization system of wheat plant.

A simple microbial fuel cell model for improvement of biomedical device powering times.

PubMed

Roxby, Daniel N; Tran, Nham; Nguyen, Hung T

2014-01-01

This study describes a Matlab based Microbial Fuel Cell (MFC) model for a suspended microbial population, in the anode chamber for the use of the MFC in powering biomedical devices. The model contains three main sections including microbial growth, microbial chemical uptake and secretion and electrochemical modeling. The microbial growth portion is based on a Continuously Stirred Tank Reactor (CSTR) model for the microbial growth with substrate and electron acceptors. Microbial stoichiometry is used to determine chemical concentrations and their rates of change and transfer within the MFC. These parameters are then used in the electrochemical modeling for calculating current, voltage and power. The model was tested for typically exhibited MFC characteristics including increased electrode distances and surface areas, overpotentials and operating temperatures. Implantable biomedical devices require long term powering which is the main objective for MFCs. Towards this end, our model was tested with different initial substrate and electron acceptor concentrations, revealing a four-fold increase in concentrations decreased the power output time by 50%. Additionally, the model also predicts that for a 35.7% decrease in specific growth rate, a 50% increase in power longevity is possible.

A smart growth evaluation model based on data envelopment analysis

NASA Astrophysics Data System (ADS)

Zhang, Xiaokun; Guan, Yongyi

2018-04-01

With the rapid spread of urbanization, smart growth (SG) has attracted plenty of attention from all over the world. In this paper, by the establishment of index system for smart growth, data envelopment analysis (DEA) model was suggested to evaluate the SG level of the current growth situation in cities. In order to further improve the information of both radial direction and non-radial detection, we introduced the non-Archimedean infinitesimal to form C2GS2 control model. Finally, we evaluated the SG level in Canberra and identified a series of problems, which can verify the applicability of the model and provide us more improvement information.

Gastrointestinal Spatiotemporal mRNA Expression of Ghrelin vs Growth Hormone Receptor and New Growth Yield Machine Learning Model Based on Perturbation Theory.

PubMed

Ran, Tao; Liu, Yong; Li, Hengzhi; Tang, Shaoxun; He, Zhixiong; Munteanu, Cristian R; González-Díaz, Humberto; Tan, Zhiliang; Zhou, Chuanshe

2016-07-27

The management of ruminant growth yield has economic importance. The current work presents a study of the spatiotemporal dynamic expression of Ghrelin and GHR at mRNA levels throughout the gastrointestinal tract (GIT) of kid goats under housing and grazing systems. The experiments show that the feeding system and age affected the expression of either Ghrelin or GHR with different mechanisms. Furthermore, the experimental data are used to build new Machine Learning models based on the Perturbation Theory, which can predict the effects of perturbations of Ghrelin and GHR mRNA expression on the growth yield. The models consider eight longitudinal GIT segments (rumen, abomasum, duodenum, jejunum, ileum, cecum, colon and rectum), seven time points (0, 7, 14, 28, 42, 56 and 70 d) and two feeding systems (Supplemental and Grazing feeding) as perturbations from the expected values of the growth yield. The best regression model was obtained using Random Forest, with the coefficient of determination R(2) of 0.781 for the test subset. The current results indicate that the non-linear regression model can accurately predict the growth yield and the key nodes during gastrointestinal development, which is helpful to optimize the feeding management strategies in ruminant production system.

Gastrointestinal Spatiotemporal mRNA Expression of Ghrelin vs Growth Hormone Receptor and New Growth Yield Machine Learning Model Based on Perturbation Theory

PubMed Central

Ran, Tao; Liu, Yong; Li, Hengzhi; Tang, Shaoxun; He, Zhixiong; Munteanu, Cristian R.; González-Díaz, Humberto; Tan, Zhiliang; Zhou, Chuanshe

2016-01-01

The management of ruminant growth yield has economic importance. The current work presents a study of the spatiotemporal dynamic expression of Ghrelin and GHR at mRNA levels throughout the gastrointestinal tract (GIT) of kid goats under housing and grazing systems. The experiments show that the feeding system and age affected the expression of either Ghrelin or GHR with different mechanisms. Furthermore, the experimental data are used to build new Machine Learning models based on the Perturbation Theory, which can predict the effects of perturbations of Ghrelin and GHR mRNA expression on the growth yield. The models consider eight longitudinal GIT segments (rumen, abomasum, duodenum, jejunum, ileum, cecum, colon and rectum), seven time points (0, 7, 14, 28, 42, 56 and 70 d) and two feeding systems (Supplemental and Grazing feeding) as perturbations from the expected values of the growth yield. The best regression model was obtained using Random Forest, with the coefficient of determination R2 of 0.781 for the test subset. The current results indicate that the non-linear regression model can accurately predict the growth yield and the key nodes during gastrointestinal development, which is helpful to optimize the feeding management strategies in ruminant production system. PMID:27460882

Improving the capability of an integrated CA-Markov model to simulate spatio-temporal urban growth trends using an Analytical Hierarchy Process and Frequency Ratio

NASA Astrophysics Data System (ADS)

Aburas, Maher Milad; Ho, Yuek Ming; Ramli, Mohammad Firuz; Ash'aari, Zulfa Hanan

2017-07-01

The creation of an accurate simulation of future urban growth is considered one of the most important challenges in urban studies that involve spatial modeling. The purpose of this study is to improve the simulation capability of an integrated CA-Markov Chain (CA-MC) model using CA-MC based on the Analytical Hierarchy Process (AHP) and CA-MC based on Frequency Ratio (FR), both applied in Seremban, Malaysia, as well as to compare the performance and accuracy between the traditional and hybrid models. Various physical, socio-economic, utilities, and environmental criteria were used as predictors, including elevation, slope, soil texture, population density, distance to commercial area, distance to educational area, distance to residential area, distance to industrial area, distance to roads, distance to highway, distance to railway, distance to power line, distance to stream, and land cover. For calibration, three models were applied to simulate urban growth trends in 2010; the actual data of 2010 were used for model validation utilizing the Relative Operating Characteristic (ROC) and Kappa coefficient methods Consequently, future urban growth maps of 2020 and 2030 were created. The validation findings confirm that the integration of the CA-MC model with the FR model and employing the significant driving force of urban growth in the simulation process have resulted in the improved simulation capability of the CA-MC model. This study has provided a novel approach for improving the CA-MC model based on FR, which will provide powerful support to planners and decision-makers in the development of future sustainable urban planning.

Response of branch growth and mortality to silvicultural treatments in coastal Douglas-fir plantations: implications for predicting tree growth.

Treesearch

A.R. Weiskittel; D. Maguire; R.A. Monserud

2007-01-01

Static models of individual tree crown attributes such as height to crown base and maximum branch diameter profile have been developed for several commercially important species. Dynamic models of individual branch growth and mortality have received less attention, but have generally been developed retrospectively by dissecting felled trees; however, this approach is...

Stand-level growth and yield component models for red oak-sweetgum forests on Mid-South minor stream bottoms

Treesearch

Emily B. Schultz; J. Clint Iles; Thomas G. Matney; Andrew W. Ezell; James S. Meadows; Theodor D. Leininger; al. et.

2010-01-01

Greater emphasis is being placed on Southern bottomland hardwood management, but relatively few growth and yield prediction systems exist that are based on sufficient measurements. We present the aggregate stand-level expected yield and structural component equations for a red oak (Quercus section Lobatae)-sweetgum (Liquidambar styraciflua L.) growth and yield model....

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

Srivastava, Himanshu; Ganguli, Tapas; Deb, S. K.

The in-situ growth of CuO nanowires was studied by Energy Dispersive X-ray Diffraction (EDXRD) to observe the mechanism of growth. The study was carried out for comparison at two temperatures—at 500 °C, the optimum temperature of the nanowires growth, and at 300 °C just below the temperature range of the growth. The in situ observation revealed the successive oxidation of Cu foil to Cu{sub 2}O layer and finally to CuO layer. Further analysis showed the presence of a compressive stress in CuO layer due to interface at CuO and Cu{sub 2}O layers. The compressive stress was found to increase withmore » the growth of the nanowires at 500 °C while it relaxed with the growth of CuO layer at 300 °C. The present results do not support the existing model of stress relaxation induced growth of nanowires. Based on the detailed Transmission Electron Microscope, Scanning Electron Microscope, and EDXRD results, a microstructure based growth model has been suggested.« less

Partial migration: growth varies between resident and migratory fish.

PubMed

Gillanders, Bronwyn M; Izzo, Christopher; Doubleday, Zoë A; Ye, Qifeng

2015-03-01

Partial migration occurs in many taxa and ecosystems and may confer survival benefits. Here, we use otolith chemistry data to determine whether fish from a large estuarine system were resident or migratory, and then examine whether contingents display differences in modelled growth based on changes in width of otolith growth increments. Sixty-three per cent of fish were resident based on Ba : Ca of otoliths, with the remainder categorized as migratory, with both contingents distributed across most age/size classes and both sexes, suggesting population-level bet hedging. Migrant fish were in slightly better condition than resident fish based on Fulton's K condition index. Migration type (resident versus migratory) was 56 times more likely to explain variation in growth than a model just incorporating year- and age-related growth trends. While average growth only varied slightly between resident and migratory fish, year-to-year variation was significant. Such dynamism in growth rates likely drives persistence of both life-history types. The complex relationships in growth between contingents suggest that management of species exhibiting partial migration is challenging, especially in a world subject to a changing climate. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

Assessing age- and silt index-independent diameter growth models of individual-tree Southern Appalachian hardwoods

Treesearch

Henry W. Mcnab; Thomas F. Lloyd

1999-01-01

Models of forest vegetation dynamics based on characteristics of individual trees are more suitable to predicting growth of multiple species and age classes than those based on stands. The objective of this study was to assess age- and site index-independent relationships between periodic diameter increment and tree and site effects for 11 major hardwood tree species....

Modeling and predicting urban growth pattern of the Tokyo metropolitan area based on cellular automata

NASA Astrophysics Data System (ADS)

Zhao, Yaolong; Zhao, Junsan; Murayama, Yuji

2008-10-01

The period of high economic growth in Japan which began in the latter half of the 1950s led to a massive migration of population from rural regions to the Tokyo metropolitan area. This phenomenon brought about rapid urban growth and urban structure changes in this area. Purpose of this study is to establish a constrained CA (Cellular Automata) model with GIS (Geographical Information Systems) to simulate urban growth pattern in the Tokyo metropolitan area towards predicting urban form and landscape for the near future. Urban land-use is classified into multi-categories for interpreting the effect of interaction among land-use categories in the spatial process of urban growth. Driving factors of urban growth pattern, such as land condition, railway network, land-use zoning, random perturbation, and neighborhood interaction and so forth, are explored and integrated into this model. These driving factors are calibrated based on exploratory spatial data analysis (ESDA), spatial statistics, logistic regression, and "trial and error" approach. The simulation is assessed at both macro and micro classification levels in three ways: visual approach; fractal dimension; and spatial metrics. Results indicate that this model provides an effective prototype to simulate and predict urban growth pattern of the Tokyo metropolitan area.

An individual-based model of the krill Euphausia pacifica in the California Current

NASA Astrophysics Data System (ADS)

Dorman, Jeffrey G.; Sydeman, William J.; Bograd, Steven J.; Powell, Thomas M.

2015-11-01

Euphausia pacifica is an abundant and important prey resource for numerous predators of the California Current and elsewhere in the North Pacific. We developed an individual-based model (IBM) for E. pacifica to study its bioenergetics (growth, stage development, reproduction, and mortality) under constant/ideal conditions as well as under varying ocean conditions and food resources. To model E. pacifica under varying conditions, we coupled the IBM to an oceanographic-ecosystem model over the period 2000-2008 (9 years). Model results under constant/ideal food conditions compare favorably with experimental studies conducted under food unlimited conditions. Under more realistic variable oceanographic conditions, mean growth rates over the continental shelf were positive only when individuals migrated diurnally to the depth of maximum phytoplankton layer during nighttime feeding. Our model only used phytoplankton as prey and coastal growth rates were lower than expected (0.01 mm d-1), suggesting that a diverse prey base (zooplankton, protists, marine snow) may be required to facilitate growth and survival of modeled E. pacifica in the coastal environment. This coupled IBM-ROMS modeling framework and its parameters provides a tool for understanding the biology and ecology of E. pacifica and could be developed to further the understanding of climatic effects on this key prey species and enhance an ecosystem approach to fisheries and wildlife management in this region.

A study of life prediction differences for a nickel-base Alloy 690 using a threshold and a non-threshold model

NASA Astrophysics Data System (ADS)

Young, B. A.; Gao, Xiaosheng; Srivatsan, T. S.

2009-10-01

In this paper we compare and contrast the crack growth rate of a nickel-base superalloy (Alloy 690) in the Pressurized Water Reactor (PWR) environment. Over the last few years, a preponderance of test data has been gathered on both Alloy 690 thick plate and Alloy 690 tubing. The original model, essentially based on a small data set for thick plate, compensated for temperature, load ratio and stress-intensity range but did not compensate for the fatigue threshold of the material. As additional test data on both plate and tube product became available the model was gradually revised to account for threshold properties. Both the original and revised models generated acceptable results for data that were above 1 × 10 -11 m/s. However, the test data at the lower growth rates were over-predicted by the non-threshold model. Since the original model did not take the fatigue threshold into account, this model predicted no operating stress below which the material would effectively undergo fatigue crack growth. Because of an over-prediction of the growth rate below 1 × 10 -11 m/s, due to a combination of low stress, small crack size and long rise-time, the model in general leads to an under-prediction of the total available life of the components.

Fractional differential equations based modeling of microbial survival and growth curves: model development and experimental validation.

PubMed

Kaur, A; Takhar, P S; Smith, D M; Mann, J E; Brashears, M M

2008-10-01

A fractional differential equations (FDEs)-based theory involving 1- and 2-term equations was developed to predict the nonlinear survival and growth curves of foodborne pathogens. It is interesting to note that the solution of 1-term FDE leads to the Weibull model. Nonlinear regression (Gauss-Newton method) was performed to calculate the parameters of the 1-term and 2-term FDEs. The experimental inactivation data of Salmonella cocktail in ground turkey breast, ground turkey thigh, and pork shoulder; and cocktail of Salmonella, E. coli, and Listeria monocytogenes in ground beef exposed at isothermal cooking conditions of 50 to 66 degrees C were used for validation. To evaluate the performance of 2-term FDE in predicting the growth curves-growth of Salmonella typhimurium, Salmonella Enteritidis, and background flora in ground pork and boneless pork chops; and E. coli O157:H7 in ground beef in the temperature range of 22.2 to 4.4 degrees C were chosen. A program was written in Matlab to predict the model parameters and survival and growth curves. Two-term FDE was more successful in describing the complex shapes of microbial survival and growth curves as compared to the linear and Weibull models. Predicted curves of 2-term FDE had higher magnitudes of R(2) (0.89 to 0.99) and lower magnitudes of root mean square error (0.0182 to 0.5461) for all experimental cases in comparison to the linear and Weibull models. This model was capable of predicting the tails in survival curves, which was not possible using Weibull and linear models. The developed model can be used for other foodborne pathogens in a variety of food products to study the destruction and growth behavior.

Using SAS PROC CALIS to fit Level-1 error covariance structures of latent growth models.

PubMed

Ding, Cherng G; Jane, Ten-Der

2012-09-01

In the present article, we demonstrates the use of SAS PROC CALIS to fit various types of Level-1 error covariance structures of latent growth models (LGM). Advantages of the SEM approach, on which PROC CALIS is based, include the capabilities of modeling the change over time for latent constructs, measured by multiple indicators; embedding LGM into a larger latent variable model; incorporating measurement models for latent predictors; and better assessing model fit and the flexibility in specifying error covariance structures. The strength of PROC CALIS is always accompanied with technical coding work, which needs to be specifically addressed. We provide a tutorial on the SAS syntax for modeling the growth of a manifest variable and the growth of a latent construct, focusing the documentation on the specification of Level-1 error covariance structures. Illustrations are conducted with the data generated from two given latent growth models. The coding provided is helpful when the growth model has been well determined and the Level-1 error covariance structure is to be identified.

Final Report for Project 13-4791: New Mechanistic Models of Creep-Fatigue Crack Growth Interactions for Advanced High Temperature Reactor Components

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

Kruzic, Jamie J; Siegmund, Thomas; Tomar, Vikas

This project developed and validated a novel, multi-scale, mechanism-based model to quantitatively predict creep-fatigue crack growth and failure for Ni-based Alloy 617 at 800°C. Alloy 617 is a target material for intermediate heat exchangers in Generation IV very high temperature reactor designs, and it is envisioned that this model will aid in the design of safe, long lasting nuclear power plants. The technical effectiveness of the model was shown by demonstrating that experimentally observed crack growth rates can be predicted under both steady state and overload crack growth conditions. Feasibility was considered by incorporating our model into a commercially availablemore » finite element method code, ABAQUS, that is commonly used by design engineers. While the focus of the project was specifically on an alloy targeted for Generation IV nuclear reactors, the benefits to the public are expected to be wide reaching. Indeed, creep-fatigue failure is a design consideration for a wide range of high temperature mechanical systems that rely on Ni-based alloys, including industrial gas power turbines, advanced ultra-super critical steam turbines, and aerospace turbine engines. It is envisioned that this new model can be adapted to a wide range of engineering applications.« less

Computational modeling of hypertensive growth in the human carotid artery

NASA Astrophysics Data System (ADS)

Sáez, Pablo; Peña, Estefania; Martínez, Miguel Angel; Kuhl, Ellen

2014-06-01

Arterial hypertension is a chronic medical condition associated with an elevated blood pressure. Chronic arterial hypertension initiates a series of events, which are known to collectively initiate arterial wall thickening. However, the correlation between macrostructural mechanical loading, microstructural cellular changes, and macrostructural adaptation remains unclear. Here, we present a microstructurally motivated computational model for chronic arterial hypertension through smooth muscle cell growth. To model growth, we adopt a classical concept based on the multiplicative decomposition of the deformation gradient into an elastic part and a growth part. Motivated by clinical observations, we assume that the driving force for growth is the stretch sensed by the smooth muscle cells. We embed our model into a finite element framework, where growth is stored locally as an internal variable. First, to demonstrate the features of our model, we investigate the effects of hypertensive growth in a real human carotid artery. Our results agree nicely with experimental data reported in the literature both qualitatively and quantitatively.

Analysis of the Sensitivity and Uncertainty in 2-Stage Clonal Growth Models for Formaldehyde with Relevance to Other Biologically-Based Dose Response (BBDR) Models

EPA Science Inventory

The National Center for Environmental Assessment (NCEA) has conducted and supported research addressing uncertainties in 2-stage clonal growth models for cancer as applied to formaldehyde. In this report, we summarized publications resulting from this research effort, discussed t...

Theoretical and Experimental Study of Bacterial Colony Growth in 3D

NASA Astrophysics Data System (ADS)

Shao, Xinxian; Mugler, Andrew; Nemenman, Ilya

2014-03-01

Bacterial cells growing in liquid culture have been well studied and modeled. However, in nature, bacteria often grow as biofilms or colonies in physically structured habitats. A comprehensive model for population growth in such conditions has not yet been developed. Based on the well-established theory for bacterial growth in liquid culture, we develop a model for colony growth in 3D in which a homogeneous colony of cells locally consume a diffusing nutrient. We predict that colony growth is initially exponential, as in liquid culture, but quickly slows to sub-exponential after nutrient is locally depleted. This prediction is consistent with our experiments performed with E. coli in soft agar. Our model provides a baseline to which studies of complex growth process, such as such as spatially and phenotypically heterogeneous colonies, must be compared.

A growth inhibitory model with SOx influenced effective growth rate for estimation of algal biomass concentration under flue gas atmosphere

USDA-ARS?s Scientific Manuscript database

A theoretical model for the prediction of biomass concentration under real flue gas emission has been developed. The model considers the CO2 mass transfer rate, the critical SOx concentration and its role on pH based inter-conversion of bicarbonate in model building. The calibration and subsequent v...

Ricinus communis-based biopolymer and epidermal growth factor regulations on bone defect repair: A rat tibia model

NASA Astrophysics Data System (ADS)

Mendoza-Barrera, C.; Meléndez-Lira, M.; Altuzar, V.; Tomás, S. A.

2003-01-01

We report the effect of the addition of an epidermal growth factor to a Ricinus communis-based biopolymer in the healing of a rat tibia model. Bone repair and osteointegration after a period of three weeks were evaluated employing photoacoustic spectroscopy and x-ray diffraction. A parallel study was performed at 1, 2, 3, 4, 5, 6, 7, and 8 weeks with energy dispersive x-ray spectroscopy. We conclude that the use of an epidermal growth factor (group EGF) in vivo accelerates the process of bony repair in comparison with other groups, and that the employment of the Ricinus communis-based biopolymer as a bone substitute decreases bone production.

Expanded Study on the accumulation effect of tourism under the constraint of structure

NASA Astrophysics Data System (ADS)

Wang, Qiang; Yang, Zhenzhi; Huang, Lu

2017-05-01

There is a mutual influence between departmental structure and accumulation and growth. Therefore, the accumulation and growth of the tourism industry will be subject to certain restrictions on the industrial structure, and, conversely, it will have an impact on the existing industrial structure. Li Jingyi reported special research in the paper called "Research on tourism growth based on structural constraints" about the relationship between the growth of tourism and the existing industrial structure. It pointed out the specific interdependence between tourism and other economic sectors in terms of accumulation and growth. However, the research of Li Jingyi is based on the trichotomy of social product value. It is too abstract, while the study is understandable in theory. In practice, it is difficult to use the model of the paper to deal with specific problems. Therefore, how to improve the industry association model in the paper of Li and make it more in line with the actual situation becomes our concern. In this paper, the author hopes to improve the model of Li's paper by simplifying the decomposition of social product value. At the same time, it makes a further study on accumulation elasticity and growth elasticity. On this basis, some suggestions are put forward to guide the development of other industries based on the tourism industry.

Transient Mobility on Submonolayer Island Growth: An Exploration of Asymptotic Effects in Modeling

NASA Astrophysics Data System (ADS)

Morales-Cifuentes, Josue; Einstein, Theodore L.; Pimpinelli, Alberto

In studies of epitaxial growth, modeling of the smallest stable cluster (i+1 monomers, with i the critical nucleus size), is paramount in understanding growth dynamics. Our previous work has tackled submonolayer growth by modeling the effect of ballistic monomers, hot-precursors, on diffusive dynamics. Different scaling regimes and energies were predicted, with initial confirmation by applying to para-hexaphenyl submonolayer studies. Lingering questions about the applicability and behavior of the model are addressed. First, we show how an asymptotic approximation based on the growth exponent, α (N Fα) allows for robustness of modeling to experimental data; second, we answer questions about non-monotonicity by exploring the behavior of the growth exponent across realizable parameter spaces; third, we revisit our previous para-hexaphenyl work and examine relevant physical parameters, namely the speed of the hot-monomers. We conclude with an exploration of how the new asymptotic approximation can be used to strengthen the application of our model to other physical systems.

A statistical approach to develop a detailed soot growth model using PAH characteristics

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

Raj, Abhijeet; Celnik, Matthew; Shirley, Raphael

A detailed PAH growth model is developed, which is solved using a kinetic Monte Carlo algorithm. The model describes the structure and growth of planar PAH molecules, and is referred to as the kinetic Monte Carlo-aromatic site (KMC-ARS) model. A detailed PAH growth mechanism based on reactions at radical sites available in the literature, and additional reactions obtained from quantum chemistry calculations are used to model the PAH growth processes. New rates for the reactions involved in the cyclodehydrogenation process for the formation of 6-member rings on PAHs are calculated in this work based on density functional theory simulations. Themore » KMC-ARS model is validated by comparing experimentally observed ensembles on PAHs with the computed ensembles for a C{sub 2}H{sub 2} and a C{sub 6}H{sub 6} flame at different heights above the burner. The motivation for this model is the development of a detailed soot particle population balance model which describes the evolution of an ensemble of soot particles based on their PAH structure. However, at present incorporating such a detailed model into a population balance is computationally unfeasible. Therefore, a simpler model referred to as the site-counting model has been developed, which replaces the structural information of the PAH molecules by their functional groups augmented with statistical closure expressions. This closure is obtained from the KMC-ARS model, which is used to develop correlations and statistics in different flame environments which describe such PAH structural information. These correlations and statistics are implemented in the site-counting model, and results from the site-counting model and the KMC-ARS model are in good agreement. Additionally the effect of steric hindrance in large PAH structures is investigated and correlations for sites unavailable for reaction are presented. (author)« less

Localisation in a Growth Model with Interaction

NASA Astrophysics Data System (ADS)

Costa, M.; Menshikov, M.; Shcherbakov, V.; Vachkovskaia, M.

2018-05-01

This paper concerns the long term behaviour of a growth model describing a random sequential allocation of particles on a finite cycle graph. The model can be regarded as a reinforced urn model with graph-based interaction. It is motivated by cooperative sequential adsorption, where adsorption rates at a site depend on the configuration of existing particles in the neighbourhood of that site. Our main result is that, with probability one, the growth process will eventually localise either at a single site, or at a pair of neighbouring sites.

Localisation in a Growth Model with Interaction

NASA Astrophysics Data System (ADS)

Costa, M.; Menshikov, M.; Shcherbakov, V.; Vachkovskaia, M.

2018-06-01

This paper concerns the long term behaviour of a growth model describing a random sequential allocation of particles on a finite cycle graph. The model can be regarded as a reinforced urn model with graph-based interaction. It is motivated by cooperative sequential adsorption, where adsorption rates at a site depend on the configuration of existing particles in the neighbourhood of that site. Our main result is that, with probability one, the growth process will eventually localise either at a single site, or at a pair of neighbouring sites.

Comparison of individual-based modeling and population approaches for prediction of foodborne pathogens growth.

PubMed

Augustin, Jean-Christophe; Ferrier, Rachel; Hezard, Bernard; Lintz, Adrienne; Stahl, Valérie

2015-02-01

Individual-based modeling (IBM) approach combined with the microenvironment modeling of vacuum-packed cold-smoked salmon was more effective to describe the variability of the growth of a few Listeria monocytogenes cells contaminating irradiated salmon slices than the traditional population models. The IBM approach was particularly relevant to predict the absence of growth in 25% (5 among 20) of artificially contaminated cold-smoked salmon samples stored at 8 °C. These results confirmed similar observations obtained with smear soft cheese (Ferrier et al., 2013). These two different food models were used to compare the IBM/microscale and population/macroscale modeling approaches in more global exposure and risk assessment frameworks taking into account the variability and/or the uncertainty of the factors influencing the growth of L. monocytogenes. We observed that the traditional population models significantly overestimate exposure and risk estimates in comparison to IBM approach when contamination of foods occurs with a low number of cells (<100 per serving). Moreover, the exposure estimates obtained with the population model were characterized by a great uncertainty. The overestimation was mainly linked to the ability of IBM to predict no growth situations rather than the consideration of microscale environment. On the other hand, when the aim of quantitative risk assessment studies is only to assess the relative impact of changes in control measures affecting the growth of foodborne bacteria, the two modeling approach gave similar results and the simplest population approach was suitable. Copyright © 2014 Elsevier Ltd. All rights reserved.

Translation elicits a growth rate-dependent, genome-wide, differential protein production in Bacillus subtilis.

PubMed

Borkowski, Olivier; Goelzer, Anne; Schaffer, Marc; Calabre, Magali; Mäder, Ulrike; Aymerich, Stéphane; Jules, Matthieu; Fromion, Vincent

2016-05-17

Complex regulatory programs control cell adaptation to environmental changes by setting condition-specific proteomes. In balanced growth, bacterial protein abundances depend on the dilution rate, transcript abundances and transcript-specific translation efficiencies. We revisited the current theory claiming the invariance of bacterial translation efficiency. By integrating genome-wide transcriptome datasets and datasets from a library of synthetic gfp-reporter fusions, we demonstrated that translation efficiencies in Bacillus subtilis decreased up to fourfold from slow to fast growth. The translation initiation regions elicited a growth rate-dependent, differential production of proteins without regulators, hence revealing a unique, hard-coded, growth rate-dependent mode of regulation. We combined model-based data analyses of transcript and protein abundances genome-wide and revealed that this global regulation is extensively used in B. subtilis We eventually developed a knowledge-based, three-step translation initiation model, experimentally challenged the model predictions and proposed that a growth rate-dependent drop in free ribosome abundance accounted for the differential protein production. © 2016 The Authors. Published under the terms of the CC BY 4.0 license.

A dynamic model for tumour growth and metastasis formation.

PubMed

Haustein, Volker; Schumacher, Udo

2012-07-05

A simple and fast computational model to describe the dynamics of tumour growth and metastasis formation is presented. The model is based on the calculation of successive generations of tumour cells and enables one to describe biologically important entities like tumour volume, time point of 1st metastatic growth or number of metastatic colonies at a given time. The model entirely relies on the chronology of these successive events of the metastatic cascade. The simulation calculations were performed for two embedded growth models to describe the Gompertzian like growth behaviour of tumours. The initial training of the models was carried out using an analytical solution for the size distribution of metastases of a hepatocellular carcinoma. We then show the applicability of our models to clinical data from the Munich Cancer Registry. Growth and dissemination characteristics of metastatic cells originating from cells in the primary breast cancer can be modelled thus showing its ability to perform systematic analyses relevant for clinical breast cancer research and treatment. In particular, our calculations show that generally metastases formation has already been initiated before the primary can be detected clinically.

A dynamic model for tumour growth and metastasis formation

PubMed Central

2012-01-01

A simple and fast computational model to describe the dynamics of tumour growth and metastasis formation is presented. The model is based on the calculation of successive generations of tumour cells and enables one to describe biologically important entities like tumour volume, time point of 1st metastatic growth or number of metastatic colonies at a given time. The model entirely relies on the chronology of these successive events of the metastatic cascade. The simulation calculations were performed for two embedded growth models to describe the Gompertzian like growth behaviour of tumours. The initial training of the models was carried out using an analytical solution for the size distribution of metastases of a hepatocellular carcinoma. We then show the applicability of our models to clinical data from the Munich Cancer Registry. Growth and dissemination characteristics of metastatic cells originating from cells in the primary breast cancer can be modelled thus showing its ability to perform systematic analyses relevant for clinical breast cancer research and treatment. In particular, our calculations show that generally metastases formation has already been initiated before the primary can be detected clinically. PMID:22548735

Mechanisms of complex network growth: Synthesis of the preferential attachment and fitness models

NASA Astrophysics Data System (ADS)

Golosovsky, Michael

2018-06-01

We analyze growth mechanisms of complex networks and focus on their validation by measurements. To this end we consider the equation Δ K =A (t ) (K +K0) Δ t , where K is the node's degree, Δ K is its increment, A (t ) is the aging constant, and K0 is the initial attractivity. This equation has been commonly used to validate the preferential attachment mechanism. We show that this equation is undiscriminating and holds for the fitness model [Caldarelli et al., Phys. Rev. Lett. 89, 258702 (2002), 10.1103/PhysRevLett.89.258702] as well. In other words, accepted method of the validation of the microscopic mechanism of network growth does not discriminate between "rich-gets-richer" and "good-gets-richer" scenarios. This means that the growth mechanism of many natural complex networks can be based on the fitness model rather than on the preferential attachment, as it was believed so far. The fitness model yields the long-sought explanation for the initial attractivity K0, an elusive parameter which was left unexplained within the framework of the preferential attachment model. We show that the initial attractivity is determined by the width of the fitness distribution. We also present the network growth model based on recursive search with memory and show that this model contains both the preferential attachment and the fitness models as extreme cases.

The impact of atmospheric deposition and climate on forest growth in Europe using two empirical modelling approaches

NASA Astrophysics Data System (ADS)

Dobbertin, M.; Solberg, S.; Laubhann, D.; Sterba, H.; Reinds, G. J.; de Vries, W.

2009-04-01

Most recent studies show increasing forest growth in central Europe, rather than a decline as was expected due to negative effects of air pollution. While nitrogen deposition, increasing temperature and change in forest management are discussed as possible causes, quantification of the various environmental factors has rarely been undertaken. In our study, we used data from several hundreds of intensive monitoring plots from the ICP Forests network in Europe, ranging from northern Finland to Spain and southern Italy. Five-year growth data for the period 1994-1999 were available from roughly 650 plots to examine the influence of environmental factors on forest growth. Evaluations focused on the influence of nitrogen, sulphur and acid deposition, temperature, precipitation and drought. Concerning the latter meteorological variables we used the deviation from the long-term (30 years) mean. The study included the main tree species common beech (Fagus sylvatica), sessile or pedunculate oak (Quercus petraea and Q. robur), Scots pine (Pinus sylvestris) and Norway spruce (Picea abies). Two very different approaches were used. In the first approach an individual tree-based regression model was applied (Laubhahn et al., 2009), while in the second approach a stand-based model was applied (Solberg et al., 2009). The individual tree-based model had measured basal area increment of each individual tree as a growth response variable and tree size (diameter at breast height), tree competition (basal area of larger trees and stand density index), site factors (e.g. soil C/N ratio, temperature), and environmental factors (e.g. temperature change compared to long-term average, nitrogen and sulphur deposition) as influencing parameters. In the stand-growth model, stem volume increment was used as the growth response variable, after filtering out the expected growth. Expected growth was modelled as a function of site productivity, stand age and a stand density index. Relative volume growth was then calculated as actual growth in % of expected growth. The site productivity was either taken from expert estimates or computed from for each species from three site index curves from northern, central and southern Europe. Requirements for plot selection were different for both methods, resulting in 382 plots selected for the tree-individual approach and 363 plots for the stand growth model approach. Using a mixed model approach, the individual tree-based models for all species showed a high goodness of fit with Pseudo-R2 between 0.33 and 0.44. Diameter at breast height and basal area of larger trees were highly influential variables in all models. Increasing temperature showed a positive effect on growth for all species except Norway spruce. Nitrogen deposition showed a positive impact on growth for all four species. This influence was significant with p < 0.05 for all species except common beech, where the effect was nearly significant (p = 0.077). An increase of 1 kg N ha-1 yr-1 corresponded to an increase in basal area increment between 1.20% and 1.49% depending on species. The stand-growth models explained between 18% and 40% of the variance in expected growth, mainly with a positive effect of site productivity and a negative effect of age. The various models and statistical approaches were fairly consistent, and indicated a fertilizing effect of nitrogen deposition on relative growth, with a slightly above 1 percent increase in volume increment per kg of nitrogen deposition per ha and year. This was most clear for spruce and pine, and most pronounced for plots having soil C/N ratios above 25 (i.e. low nitrogen availability). Also, we found a positive relationship between relative growth and summer temperature, i.e. May-August mean temperature deviation from the 1961-1990 means. Other influences were uncertain. Possibly, sulphur and acid deposition have effects on growth, but these effects are eventually outweighed by the positive effect of nitrogen deposition, because of co-linearity between these variables. Considering an average total stem carbon uptake for European forests near 1730 kg per hectare and year, the increase in growth in the individual tree-based models implied an estimated sequestration of approximately 21- 26 kg carbon per kg nitrogen deposition. Using the growth data and the relative stem growth predicted in the stand growth models, values for the various models ranged between 16 and 24 kg (mean 19 kg) carbon uptake per kg nitrogen deposition. Both approaches, although being very different and using a different set of plots and different methods to estimate the N induced carbon uptake in stem wood resulted in very similar results. In summary, our results indicate a clear fertilization effect of N deposition on European forests, mainly on sites with high C/N soil ratios. It is in line with approaches focused on the fate of N in forest ecosystems and with results of N fertilizer experiments but much smaller than had recently been reported in other field studies (De Vries et al., 2008). Increasing temperature was also found to have a positive influence on forest growth, but this effect seemed to be less clear. References: De Vries W., Solberg S., Dobbertin M., Sterba H., Laubhahn D., Reinds G.J., Nabuurs G.-J., Gundersen P. (2008) Ecologically implausible carbon response. Nature, 451, E1-E3. Laubhann, D., Sterba H., Reinds, G.J., de Vries, W. The impact of atmospheric deposition and climate on forest growth in European monitoring plots: An individual tree growth model. Forest Ecol. Manage. (2009) doi:10.1016/j.foreco.2008.09.050. Solberg, S., Dobbertin, M., Reinds, G.J., Lange, H., Andreassen, K., Garcia Fernandez, P., Hildingsson, A., de Vries, W. Analyses of the impact of changes in atmospheric deposition and climate on forest growth in European monitoring plots: A stand growth approach. For. Ecol. Manage. (2009) doi:10.1016/j.foreco.2008.09.057.

Salmonella Typhimurium and Staphylococcus aureus dynamics in/on variable (micro)structures of fish-based model systems at suboptimal temperatures.

PubMed

Baka, Maria; Verheyen, Davy; Cornette, Nicolas; Vercruyssen, Stijn; Van Impe, Jan F

2017-01-02

The limited knowledge concerning the influence of food (micro)structure on microbial dynamics decreases the accuracy of the developed predictive models, as most studies have mainly been based on experimental data obtained in liquid microbiological media or in/on real foods. The use of model systems has a great potential when studying this complex factor. Apart from the variability in (micro)structural properties, model systems vary in compositional aspects, as a consequence of their (micro)structural variation. In this study, different experimental food model systems, with compositional and physicochemical properties similar to fish patés, are developed to study the influence of food (micro)structure on microbial dynamics. The microbiological safety of fish products is of major importance given the numerous cases of salmonellosis and infections attributed to staphylococcus toxins. The model systems understudy represent food (micro)structures of liquids, aqueous gels, emulsions and gelled emulsions. The growth/inactivation dynamics and a modelling approach of combined growth and inactivation of Salmonella Typhimurium and Staphylococcus aureus, related to fish products, are investigated in/on these model systems at temperatures relevant to fish products' common storage (4°C) and to abuse storage temperatures (8 and 12°C). ComBase (http://www.combase.cc/) predictions compared with the maximum specific growth rate (μ max ) values estimated by the Baranyi and Roberts model in the current study indicated that the (micro)structure influences the microbial dynamics. Overall, ComBase overestimated microbial growth at the same pH, a w and storage temperature. Finally, the storage temperature had also an influence on how much each model system affected the microbial dynamics. Copyright © 2016. Published by Elsevier B.V.

Substrate and metabolite diffusion within model medium for soft cheese in relation to growth of Penicillium camembertii.

PubMed

Aldarf, Mazen; Fourcade, Florence; Amrane, Abdeltif; Prigent, Yves

2006-08-01

Penicillium camembertii was cultivated on a jellified peptone-lactate based medium to simulate the composition of Camembert cheese. Diffusional limitations due to substrate consumption were not involved in the linear growth recorded during culture, while nitrogen (peptone) limitation accounted for growth cessation. Examination of gradients confirmed that medium neutralization was the consequence of lactate consumption and ammonium production. The diffusion of the lactate assimilated from the core to the rind and that of the ammonium produced from the rind to the core was described by means of a diffusion/reaction model involving a partial linking of consumption or production to growth. The model matched experimental data throughout growth.

Stochastic von Bertalanffy models, with applications to fish recruitment.

PubMed

Lv, Qiming; Pitchford, Jonathan W

2007-02-21

We consider three individual-based models describing growth in stochastic environments. Stochastic differential equations (SDEs) with identical von Bertalanffy deterministic parts are formulated, with a stochastic term which decreases, remains constant, or increases with organism size, respectively. Probability density functions for hitting times are evaluated in the context of fish growth and mortality. Solving the hitting time problem analytically or numerically shows that stochasticity can have a large positive impact on fish recruitment probability. It is also demonstrated that the observed mean growth rate of surviving individuals always exceeds the mean population growth rate, which itself exceeds the growth rate of the equivalent deterministic model. The consequences of these results in more general biological situations are discussed.

Subcritical crack growth in fibrous materials

NASA Astrophysics Data System (ADS)

Santucci, S.; Cortet, P.-P.; Deschanel, S.; Vanel, L.; Ciliberto, S.

2006-05-01

We present experiments on the slow growth of a single crack in a fax paper sheet submitted to a constant force F. We find that statistically averaged crack growth curves can be described by only two parameters: the mean rupture time τ and a characteristic growth length ζ. We propose a model based on a thermally activated rupture process that takes into account the microstructure of cellulose fibers. The model is able to reproduce the shape of the growth curve, the dependence of ζ on F as well as the effect of temperature on the rupture time τ. We find that the length scale at which rupture occurs in this model is consistently close to the diameter of cellulose microfibrils.

Estimating parameters for tree basal area growth with a system of equations and seemingly unrelated regressions

Treesearch

Charles E. Rose; Thomas B. Lynch

2001-01-01

A method was developed for estimating parameters in an individual tree basal area growth model using a system of equations based on dbh rank classes. The estimation method developed is a compromise between an individual tree and a stand level basal area growth model that accounts for the correlation between trees within a plot by using seemingly unrelated regression (...

Simulating cancer growth with multiscale agent-based modeling.

PubMed

Wang, Zhihui; Butner, Joseph D; Kerketta, Romica; Cristini, Vittorio; Deisboeck, Thomas S

2015-02-01

There have been many techniques developed in recent years to in silico model a variety of cancer behaviors. Agent-based modeling is a specific discrete-based hybrid modeling approach that allows simulating the role of diversity in cell populations as well as within each individual cell; it has therefore become a powerful modeling method widely used by computational cancer researchers. Many aspects of tumor morphology including phenotype-changing mutations, the adaptation to microenvironment, the process of angiogenesis, the influence of extracellular matrix, reactions to chemotherapy or surgical intervention, the effects of oxygen and nutrient availability, and metastasis and invasion of healthy tissues have been incorporated and investigated in agent-based models. In this review, we introduce some of the most recent agent-based models that have provided insight into the understanding of cancer growth and invasion, spanning multiple biological scales in time and space, and we further describe several experimentally testable hypotheses generated by those models. We also discuss some of the current challenges of multiscale agent-based cancer models. Copyright © 2014 Elsevier Ltd. All rights reserved.

A review of the potential effects of climate change on quaking aspen (Populus tremuloides) in the Western United States and a new tool for surveying sudden aspen decline

Treesearch

Toni Lyn Morelli; Susan C. Carr

2011-01-01

We conducted a literature review of the effects of climate on the distribution and growth of quaking aspen (Populus tremuloides Michx.) in the Western United States. Based on our review, we summarize models of historical climate determinants of contemporary aspen distribution. Most quantitative climate-based models linked aspen presence and growth...

A model for predicting Xanthomonas arboricola pv. pruni growth as a function of temperature

PubMed Central

Llorente, Isidre; Montesinos, Emilio; Moragrega, Concepció

2017-01-01

A two-step modeling approach was used for predicting the effect of temperature on the growth of Xanthomonas arboricola pv. pruni, causal agent of bacterial spot disease of stone fruit. The in vitro growth of seven strains was monitored at temperatures from 5 to 35°C with a Bioscreen C system, and a calibrating equation was generated for converting optical densities to viable counts. In primary modeling, Baranyi, Buchanan, and modified Gompertz equations were fitted to viable count growth curves over the entire temperature range. The modified Gompertz model showed the best fit to the data, and it was selected to estimate the bacterial growth parameters at each temperature. Secondary modeling of maximum specific growth rate as a function of temperature was performed by using the Ratkowsky model and its variations. The modified Ratkowsky model showed the best goodness of fit to maximum specific growth rate estimates, and it was validated successfully for the seven strains at four additional temperatures. The model generated in this work will be used for predicting temperature-based Xanthomonas arboricola pv. pruni growth rate and derived potential daily doublings, and included as the inoculum potential component of a bacterial spot of stone fruit disease forecaster. PMID:28493954

Importance of aggregation and small ice crystals in cirrus clouds, based on observations and an ice particle growth model

NASA Technical Reports Server (NTRS)

Mitchell, David L.; Chai, Steven K.; Dong, Yayi; Arnott, W. Patrick; Hallett, John

1993-01-01

The 1 November 1986 FIRE I case study was used to test an ice particle growth model which predicts bimodal size spectra in cirrus clouds. The model was developed from an analytically based model which predicts the height evolution of monomodal ice particle size spectra from the measured ice water content (IWC). Size spectra from the monomodal model are represented by a gamma distribution, N(D) = N(sub o)D(exp nu)exp(-lambda D), where D = ice particle maximum dimension. The slope parameter, lambda, and the parameter N(sub o) are predicted from the IWC through the growth processes of vapor diffusion and aggregation. The model formulation is analytical, computationally efficient, and well suited for incorporation into larger models. The monomodal model has been validated against two other cirrus cloud case studies. From the monomodal size spectra, the size distributions which determine concentrations of ice particles less than about 150 mu m are predicted.

A frost formation model and its validation under various experimental conditions

NASA Technical Reports Server (NTRS)

Dietenberger, M. A.

1982-01-01

A numerical model that was used to calculate the frost properties for all regimes of frost growth is described. In the first regime of frost growth, the initial frost density and thickness was modeled from the theories of crystal growth. The 'frost point' temperature was modeled as a linear interpolation between the dew point temperature and the fog point temperature, based upon the nucleating capability of the particular condensing surfaces. For a second regime of frost growth, the diffusion model was adopted with the following enhancements: the generalized correlation of the water frost thermal conductivity was applied to practically all water frost layers being careful to ensure that the calculated heat and mass transfer coefficients agreed with experimental measurements of the same coefficients.

On a Nonlinear Model for Tumor Growth: Global in Time Weak Solutions

NASA Astrophysics Data System (ADS)

Donatelli, Donatella; Trivisa, Konstantina

2014-07-01

We investigate the dynamics of a class of tumor growth models known as mixed models. The key characteristic of these type of tumor growth models is that the different populations of cells are continuously present everywhere in the tumor at all times. In this work we focus on the evolution of tumor growth in the presence of proliferating, quiescent and dead cells as well as a nutrient. The system is given by a multi-phase flow model and the tumor is described as a growing continuum Ω with boundary ∂Ω both of which evolve in time. Global-in-time weak solutions are obtained using an approach based on penalization of the boundary behavior, diffusion and viscosity in the weak formulation.

AN INDIVIDUAL-BASED MODEL OF COTTUS POPULATION DYNAMICS

EPA Science Inventory

We explored population dynamics of a southern Appalachian population of Cottus bairdi using a spatially-explicit, individual-based model. The model follows daily growth, mortality, and spawning of individuals as a function of flow and temperature. We modeled movement of juveniles...

[Individual growth modeling of the penshell Atrina maura (Bivalvia: Pinnidae) using a multi model inference approach].

PubMed

Aragón-Noriega, Eugenio Alberto

2013-09-01

Growth models of marine animals, for fisheries and/or aquaculture purposes, are based on the popular von Bertalanffy model. This tool is mostly used because its parameters are used to evaluate other fisheries models, such as yield per recruit; nevertheless, there are other alternatives (such as Gompertz, Logistic, Schnute) not yet used by fishery scientists, that may result useful depending on the studied species. The penshell Atrina maura, has been studied for fisheries or aquaculture supplies, but its individual growth has not yet been studied before. The aim of this study was to model the absolute growth of the penshell A. maura using length-age data. For this, five models were assessed to obtain growth parameters: von Bertalanffy, Gompertz, Logistic, Schnute case 1 and Schnute and Richards. The criterion used to select the best models was the Akaike information criterion, as well as the residual squared sum and R2 adjusted. To get the average asymptotic length, the multi model inference approach was used. According to Akaike information criteria, the Gompertz model better described the absolute growth of A. maura. Following the multi model inference approach the average asymptotic shell length was 218.9 mm (IC 212.3-225.5) of shell length. I concluded that the use of the multi model approach and the Akaike information criteria represented the most robust method for growth parameter estimation of A. maura and the von Bertalanffy growth model should not be selected a priori as the true model to obtain the absolute growth in bivalve mollusks like in the studied species in this paper.

Novel Multiscale Modeling Tool Applied to Pseudomonas aeruginosa Biofilm Formation

PubMed Central

Biggs, Matthew B.; Papin, Jason A.

2013-01-01

Multiscale modeling is used to represent biological systems with increasing frequency and success. Multiscale models are often hybrids of different modeling frameworks and programming languages. We present the MATLAB-NetLogo extension (MatNet) as a novel tool for multiscale modeling. We demonstrate the utility of the tool with a multiscale model of Pseudomonas aeruginosa biofilm formation that incorporates both an agent-based model (ABM) and constraint-based metabolic modeling. The hybrid model correctly recapitulates oxygen-limited biofilm metabolic activity and predicts increased growth rate via anaerobic respiration with the addition of nitrate to the growth media. In addition, a genome-wide survey of metabolic mutants and biofilm formation exemplifies the powerful analyses that are enabled by this computational modeling tool. PMID:24147108

Novel multiscale modeling tool applied to Pseudomonas aeruginosa biofilm formation.

PubMed

Biggs, Matthew B; Papin, Jason A

2013-01-01

Multiscale modeling is used to represent biological systems with increasing frequency and success. Multiscale models are often hybrids of different modeling frameworks and programming languages. We present the MATLAB-NetLogo extension (MatNet) as a novel tool for multiscale modeling. We demonstrate the utility of the tool with a multiscale model of Pseudomonas aeruginosa biofilm formation that incorporates both an agent-based model (ABM) and constraint-based metabolic modeling. The hybrid model correctly recapitulates oxygen-limited biofilm metabolic activity and predicts increased growth rate via anaerobic respiration with the addition of nitrate to the growth media. In addition, a genome-wide survey of metabolic mutants and biofilm formation exemplifies the powerful analyses that are enabled by this computational modeling tool.

Wind growth and wave breaking in higher-order spectral phase resolved wave models

NASA Astrophysics Data System (ADS)

Leighton, R.; Walker, D. T.

2016-02-01

Wind growth and wave breaking are a integral parts of the wave evolution. Higher-OrderSpectral models (HoS) describing the non-linear evolution require empirical models for these effects. In particular, the assimilation of phase-resolved remotesensing data will require the prediction and modeling of wave breaking events.The HoS formulation used in this effort is based on fully nonlinear model of O. Nwogu (2009). The model for wave growth due to wind is based on the early normal and tangential stress model of Munk (1947). The model for wave breaking contains two parts. The first part initiates the breaking events based on the local wave geometry and the second part is a model for the pressure field, which acting against the surface normal velocity extracts energy from the wave. The models are tuned to balance the wind energy input with the breaking wave losses and to be similarfield observations of breaking wave coverage. The initial wave field, based on a Pierson-Moskowitz spectrum for 10 meter wind speed of 5-15 m/s, defined over a region of up to approximate 2.5 km on a side with the simulation running for several hundreds of peak wave periods. Results will be presented describing the evolution of the wave field.Sponsored by Office of Naval Research, Code 322

Principles of proteome allocation are revealed using proteomic data and genome-scale models

PubMed Central

Yang, Laurence; Yurkovich, James T.; Lloyd, Colton J.; Ebrahim, Ali; Saunders, Michael A.; Palsson, Bernhard O.

2016-01-01

Integrating omics data to refine or make context-specific models is an active field of constraint-based modeling. Proteomics now cover over 95% of the Escherichia coli proteome by mass. Genome-scale models of Metabolism and macromolecular Expression (ME) compute proteome allocation linked to metabolism and fitness. Using proteomics data, we formulated allocation constraints for key proteome sectors in the ME model. The resulting calibrated model effectively computed the “generalist” (wild-type) E. coli proteome and phenotype across diverse growth environments. Across 15 growth conditions, prediction errors for growth rate and metabolic fluxes were 69% and 14% lower, respectively. The sector-constrained ME model thus represents a generalist ME model reflecting both growth rate maximization and “hedging” against uncertain environments and stresses, as indicated by significant enrichment of these sectors for the general stress response sigma factor σS. Finally, the sector constraints represent a general formalism for integrating omics data from any experimental condition into constraint-based ME models. The constraints can be fine-grained (individual proteins) or coarse-grained (functionally-related protein groups) as demonstrated here. This flexible formalism provides an accessible approach for narrowing the gap between the complexity captured by omics data and governing principles of proteome allocation described by systems-level models. PMID:27857205

Principles of proteome allocation are revealed using proteomic data and genome-scale models

DOE PAGES

Yang, Laurence; Yurkovich, James T.; Lloyd, Colton J.; ...

2016-11-18

Integrating omics data to refine or make context-specific models is an active field of constraint-based modeling. Proteomics now cover over 95% of the Escherichia coli proteome by mass. Genome-scale models of Metabolism and macromolecular Expression (ME) compute proteome allocation linked to metabolism and fitness. Using proteomics data, we formulated allocation constraints for key proteome sectors in the ME model. The resulting calibrated model effectively computed the “generalist” (wild-type) E. coli proteome and phenotype across diverse growth environments. Across 15 growth conditions, prediction errors for growth rate and metabolic fluxes were 69% and 14% lower, respectively. The sector-constrained ME model thusmore » represents a generalist ME model reflecting both growth rate maximization and “hedging” against uncertain environments and stresses, as indicated by significant enrichment of these sectors for the general stress response sigma factor σS. Finally, the sector constraints represent a general formalism for integrating omics data from any experimental condition into constraint-based ME models. The constraints can be fine-grained (individual proteins) or coarse-grained (functionally-related protein groups) as demonstrated here. Furthermore, this flexible formalism provides an accessible approach for narrowing the gap between the complexity captured by omics data and governing principles of proteome allocation described by systems-level models.« less

The Modellers' Halting Foray into Ecological Theory: Or, What is This Thing Called 'Growth Rate'?

PubMed

Deveau, Michael; Karsten, Richard; Teismann, Holger

2015-06-01

This discussion paper describes the attempt of an imagined group of non-ecologists ("Modellers") to determine the population growth rate from field data. The Modellers wrestle with the multiple definitions of the growth rate available in the literature and the fact that, in their modelling, it appears to be drastically model-dependent, which seems to throw into question the very concept itself. Specifically, they observe that six representative models used to capture the data produce growth-rate values, which differ significantly. Almost ready to concede that the problem they set for themselves is ill-posed, they arrive at an alternative point of view that not only preserves the identity of the concept of the growth rate, but also helps discriminate between competing models for capturing the data. This is accomplished by assessing how robustly a given model is able to generate growth-rate values from randomized time-series data. This leads to the proposal of an iterative approach to ecological modelling in which the definition of theoretical concepts (such as the growth rate) and model selection complement each other. The paper is based on high-quality field data of mites on apple trees and may be called a "data-driven opinion piece".

New exposure-based metric approach for evaluating O3 risk to North American aspen forests

Treesearch

K.E. Percy; M. Nosal; W. Heilman; T. Dann; J. Sober; A.H. Legge; D.F. Karnosky

2007-01-01

The United States and Canada currently use exposure-based metrics to protect vegetation from O3. Using 5 years (1999-2003) of co-measured O3, meteorology and growth response, we have developed exposure-based regression models that predict Populus tremuloides growth change within the North American ambient...

Observing and modeling dynamics in terrestrial gross primary productivity and phenology from remote sensing: An assessment using in-situ measurements

NASA Astrophysics Data System (ADS)

Verma, Manish K.

Terrestrial gross primary productivity (GPP) is the largest and most variable component of the carbon cycle and is strongly influenced by phenology. Realistic characterization of spatio-temporal variation in GPP and phenology is therefore crucial for understanding dynamics in the global carbon cycle. In the last two decades, remote sensing has become a widely-used tool for this purpose. However, no study has comprehensively examined how well remote sensing models capture spatiotemporal patterns in GPP, and validation of remote sensing-based phenology models is limited. Using in-situ data from 144 eddy covariance towers located in all major biomes, I assessed the ability of 10 remote sensing-based methods to capture spatio-temporal variation in GPP at annual and seasonal scales. The models are based on different hypotheses regarding ecophysiological controls on GPP and span a range of structural and computational complexity. The results lead to four main conclusions: (i) at annual time scale, models were more successful capturing spatial variability than temporal variability; (ii) at seasonal scale, models were more successful in capturing average seasonal variability than interannual variability; (iii) simpler models performed as well or better than complex models; and (iv) models that were best at explaining seasonal variability in GPP were different from those that were best able to explain variability in annual scale GPP. Seasonal phenology of vegetation follows bounded growth and decay, and is widely modeled using growth functions. However, the specific form of the growth function affects how phenological dynamics are represented in ecosystem and remote sensing-base models. To examine this, four different growth functions (the logistic, Gompertz, Mirror-Gompertz and Richards function) were assessed using remotely sensed and in-situ data collected at several deciduous forest sites. All of the growth functions provided good statistical representation of in-situ and remote sensing time series. However, the Richards function captured observed asymmetric dynamics that were not captured by the other functions. The timing of key phenophase transitions derived using the Richards function therefore agreed best with observations. This suggests that ecosystem models and remote-sensing algorithms would benefit from using the Richards function to represent phenological dynamics.

Modeling Tree Growth Taking into Account Carbon Source and Sink Limitations.

PubMed

Hayat, Amaury; Hacket-Pain, Andrew J; Pretzsch, Hans; Rademacher, Tim T; Friend, Andrew D

2017-01-01

Increasing CO 2 concentrations are strongly controlled by the behavior of established forests, which are believed to be a major current sink of atmospheric CO 2 . There are many models which predict forest responses to environmental changes but they are almost exclusively carbon source (i.e., photosynthesis) driven. Here we present a model for an individual tree that takes into account the intrinsic limits of meristems and cellular growth rates, as well as control mechanisms within the tree that influence its diameter and height growth over time. This new framework is built on process-based understanding combined with differential equations solved by numerical method. Our aim is to construct a model framework of tree growth for replacing current formulations in Dynamic Global Vegetation Models, and so address the issue of the terrestrial carbon sink. Our approach was successfully tested for stands of beech trees in two different sites representing part of a long-term forest yield experiment in Germany. This model provides new insights into tree growth and limits to tree height, and addresses limitations of previous models with respect to sink-limited growth.

Growth models of Rhizophora mangle L. seedlings in tropical southwestern Atlantic

NASA Astrophysics Data System (ADS)

Lima, Karen Otoni de Oliveira; Tognella, Mônica Maria Pereira; Cunha, Simone Rabelo; Andrade, Humber Agrelli de

2018-07-01

The present study selected and compared regression models that best describe the growth curves of Rhizophora mangle seedlings based on the height (cm) and time (days) variables. The Linear, Exponential, Power Law, Monomolecular, Logistic, and Gompertz models were adjusted with non-linear formulations and minimization of the sum of the squares of the residues. The Akaike Information Criterion was used to select the best model for each seedling. After this selection, the determination coefficient, which evaluates how well a model describes height variation as a time function, was inspected. Differing from the classic population ecology studies, the Monomolecular, Three-parameter Logistic, and Gompertz models presented the best performance in describing growth, suggesting they are the most adequate options for long-term studies. The different growth curves reflect the complexity of stem growth at the seedling stage for R. mangle. The analysis of the joint distribution of the parameters initial height, growth rate, and, asymptotic size allowed the study of the species ecological attributes and to observe its intraspecific variability in each model. Our results provide a basis for interpretation of the dynamics of seedlings growth during their establishment in a mature forest, as well as its regeneration processes.

Biofilm growth in porous media: Experiments, computational modeling at the porescale, and upscaling

NASA Astrophysics Data System (ADS)

Peszynska, Malgorzata; Trykozko, Anna; Iltis, Gabriel; Schlueter, Steffen; Wildenschild, Dorthe

2016-09-01

Biofilm growth changes many physical properties of porous media such as porosity, permeability and mass transport parameters. The growth depends on various environmental conditions, and in particular, on flow rates. Modeling the evolution of such properties is difficult both at the porescale where the phase morphology can be distinguished, as well as during upscaling to the corescale effective properties. Experimental data on biofilm growth is also limited because its collection can interfere with the growth, while imaging itself presents challenges. In this paper we combine insight from imaging, experiments, and numerical simulations and visualization. The experimental dataset is based on glass beads domain inoculated by biomass which is subjected to various flow conditions promoting the growth of biomass and the appearance of a biofilm phase. The domain is imaged and the imaging data is used directly by a computational model for flow and transport. The results of the computational flow model are upscaled to produce conductivities which compare well with the experimentally obtained hydraulic properties of the medium. The flow model is also coupled to a newly developed biomass-nutrient growth model, and the model reproduces morphologies qualitatively similar to those observed in the experiment.

Investigation of the Factors Influencing Volatile Chemical Fate During Steady-state Accretion on Wet-growing Hail

NASA Astrophysics Data System (ADS)

Michael, R. A.; Stuart, A. L.

2007-12-01

Phase partitioning during freezing affects the transport and distribution of volatile chemical species in convective clouds. This consequently can have impacts on tropospheric chemistry, air quality, pollutant deposition, and climate change. Here, we discuss the development, evaluation, and application of a mechanistic model for the study and prediction of volatile chemical partitioning during steady-state hailstone growth. The model estimates the fraction of a chemical species retained in a two-phase freezing hailstone. It is based upon mass rate balances over water and solute for accretion under wet-growth conditions. Expressions for the calculation of model components, including the rates of super-cooled drop collection, shedding, evaporation, and hail growth were developed and implemented based on available cloud microphysics literature. Solute fate calculations assume equilibrium partitioning at air-liquid and liquid-ice interfaces. Currently, we are testing the model by performing mass balance calculations, sensitivity analyses, and comparison to available experimental data. Application of the model will improve understanding of the effects of cloud conditions and chemical properties on the fate of dissolved chemical species during hail growth.

Modeling of time dependent localized flow shear stress and its impact on cellular growth within additive manufactured titanium implants.

PubMed

Zhang, Ziyu; Yuan, Lang; Lee, Peter D; Jones, Eric; Jones, Julian R

2014-11-01

Bone augmentation implants are porous to allow cellular growth, bone formation and fixation. However, the design of the pores is currently based on simple empirical rules, such as minimum pore and interconnects sizes. We present a three-dimensional (3D) transient model of cellular growth based on the Navier-Stokes equations that simulates the body fluid flow and stimulation of bone precursor cellular growth, attachment, and proliferation as a function of local flow shear stress. The model's effectiveness is demonstrated for two additive manufactured (AM) titanium scaffold architectures. The results demonstrate that there is a complex interaction of flow rate and strut architecture, resulting in partially randomized structures having a preferential impact on stimulating cell migration in 3D porous structures for higher flow rates. This novel result demonstrates the potential new insights that can be gained via the modeling tool developed, and how the model can be used to perform what-if simulations to design AM structures to specific functional requirements. © 2014 Wiley Periodicals, Inc.

Modelling the growth of Listeria monocytogenes in Mediterranean fish species from aquaculture production.

PubMed

Bolívar, Araceli; Costa, Jean Carlos Correia Peres; Posada-Izquierdo, Guiomar D; Valero, Antonio; Zurera, Gonzalo; Pérez-Rodríguez, Fernando

2018-04-02

Over the last couple of decades, several studies have evaluated growth dynamics of L. monocytogenes in lightly processed and ready-to-eat (RTE) fishery products mostly consumed in Nordic European countries. Other fish species from aquaculture production are of special interest since their relevant consumption patterns and added value in Mediterranean countries, such as sea bream and sea bass. In the present study, the growth of L. monocytogenes was evaluated in fish-based juice (FBJ) by means of optical density (OD) measurements in a temperature range 2-20 °C under different atmosphere conditions (i.e. reduced oxygen and aerobic). The Baranyi and Roberts model was used to estimate the maximum growth rate (μ max ) from the observed growth curves. The effect of storage temperature on μ max was modelled using the Ratkowsky square root model. The developed models were validated using experimental growth data for L. monocytogenes in sea bream and sea bass fillets stored under static and dynamic temperature conditions. Overall, models developed in FBJ provided fail-safe predictions for L. monocytogenes growth. For the model generated under reduced oxygen conditions, bias and accuracy factor for growth rate predictions were 1.15 and 1.25, respectively, showing good performance to adequately predict L. monocytogenes growth in Mediterranean fish products. The present study provides validated predictive models for L. monocytogenes growth in Mediterranean fish species to be used in microbial risk assessment and shelf-life studies. Copyright © 2018 Elsevier B.V. All rights reserved.

Assessing forest vulnerability to climate warming using a process-based model of tree growth: bad prospects for rear-edges.

PubMed

Sánchez-Salguero, Raúl; Camarero, Jesus Julio; Gutiérrez, Emilia; González Rouco, Fidel; Gazol, Antonio; Sangüesa-Barreda, Gabriel; Andreu-Hayles, Laia; Linares, Juan Carlos; Seftigen, Kristina

2017-07-01

Growth models can be used to assess forest vulnerability to climate warming. If global warming amplifies water deficit in drought-prone areas, tree populations located at the driest and southernmost distribution limits (rear-edges) should be particularly threatened. Here, we address these statements by analyzing and projecting growth responses to climate of three major tree species (silver fir, Abies alba; Scots pine, Pinus sylvestris; and mountain pine, Pinus uncinata) in mountainous areas of NE Spain. This region is subjected to Mediterranean continental conditions, it encompasses wide climatic, topographic and environmental gradients, and, more importantly, it includes rear-edges of the continuous distributions of these tree species. We used tree-ring width data from a network of 110 forests in combination with the process-based Vaganov-Shashkin-Lite growth model and climate-growth analyses to forecast changes in tree growth during the 21st century. Climatic projections were based on four ensembles CO 2 emission scenarios. Warm and dry conditions during the growing season constrain silver fir and Scots pine growth, particularly at the species rear-edge. By contrast, growth of high-elevation mountain pine forests is enhanced by climate warming. The emission scenario (RCP 8.5) corresponding to the most pronounced warming (+1.4 to 4.8 °C) forecasted mean growth reductions of -10.7% and -16.4% in silver fir and Scots pine, respectively, after 2050. This indicates that rising temperatures could amplify drought stress and thus constrain the growth of silver fir and Scots pine rear-edge populations growing at xeric sites. Contrastingly, mountain pine growth is expected to increase by +12.5% due to a longer and warmer growing season. The projections of growth reduction in silver fir and Scots pine portend dieback and a contraction of their species distribution areas through potential local extinctions of the most vulnerable driest rear-edge stands. Our modeling approach provides accessible tools to evaluate forest vulnerability to warmer conditions. © 2016 John Wiley & Sons Ltd.

Effect of food microstructure on growth dynamics of Listeria monocytogenes in fish-based model systems.

PubMed

Verheyen, Davy; Bolívar, Araceli; Pérez-Rodríguez, Fernando; Baka, Maria; Skåra, Torstein; Van Impe, Jan F

2018-06-01

Traditionally, predictive growth models for food pathogens are developed based on experiments in broth media, resulting in models which do not incorporate the influence of food microstructure. The use of model systems with various microstructures is a promising concept to get more insight into the influence of food microstructure on microbial dynamics. By means of minimal variation of compositional and physicochemical factors, these model systems can be used to study the isolated effect of certain microstructural aspects on microbial growth, survival and inactivation. In this study, the isolated effect on microbial growth dynamics of Listeria monocytogenes of two food microstructural aspects and one aspect influenced by food microstructure were investigated, i.e., the nature of the food matrix, the presence of fat droplets, and microorganism growth morphology, respectively. To this extent, fish-based model systems with various microstructures were used, i.e., a liquid, a second more viscous liquid system containing xanthan gum, an emulsion, an aqueous gel, and a gelled emulsion. Growth experiments were conducted at 4 and 10 °C, both using homogeneous and surface inoculation (only for the gelled systems). Results regarding the influence of the growth morphology indicated that the lag phase of planktonic cells in the liquid system was similar to the lag phase of submerged colonies in the xanthan system. The lag phase of submerged colonies in each gelled system was considerably longer than the lag phase of surface colonies on these respective systems. The maximum specific growth rate of planktonic cells in the liquid system was significantly lower than for submerged colonies in the xanthan system at 10 °C, while no significant differences were observed at 4 °C. The maximum cell density was higher for submerged colonies than for surface colonies. The nature of the food matrix only exerted an influence on the maximum specific growth rate, which was significantly higher in the viscous systems than in the gelled systems. The presence of a small amount of fat droplets improved the growth of L. monocytogenes at 4 °C, resulting in a shorter lag phase and a higher maximum specific growth rate. The obtained results could be useful in the determination of a set of suitable microstructural parameters for future predictive models that incorporate the influence of food microstructure on microbial dynamics. Copyright © 2018. Published by Elsevier B.V.

Effects of local film properties on the nucleation and growth of tin whiskers and hillocks

NASA Astrophysics Data System (ADS)

Sarobol, Pylin

Whiskers and hillocks grow spontaneously on Pb-free Sn electrodeposited films as a response to thin film stresses. Stress relaxation occurs by atom deposition to specific grain boundaries in the plane of the film, with hillocks being formed when grain boundary migration accompanies growth out of the plane of the film. The implication for whisker formation in electronics is serious: whiskers can grow to be millimeters long, sometimes causing short circuiting between adjacent components and, thereby, posing serious electrical reliability risks. In order to develop more effective whisker mitigation strategies, a predictive physics-based model has been needed. A growth model is developed, based on grain boundary faceting, localized Coble creep, as well as grain boundary sliding for whiskers, and grain boundary sliding with shear induced grain boundary migration for hillocks. In this model of whisker formation, two mechanisms are important: accretion of atoms by Coble creep on grain boundary planes normal to the growth direction inducing a grain boundary shear and grain boundary sliding in the direction of whisker growth. The model accurately captures the importance of the geometry of "surface grains"---shallow grains on film surfaces whose depths are significantly less than their in-plane grain sizes. A critical factor in the analysis is the ratio of the grain boundary sliding coefficient to the in-plane film compressive stress. If the accretion-induced shear stresses are not coupled to grain boundary motion and sliding occurs, a whisker forms. If the shear stress is coupled to grain boundary migration, a hillock forms. Based on this model, long whiskers grow from shallow surface grains with easy grain boundary sliding in the direction of growth. Other observed growth morphologies will be discussed in light of our model. Additional insights into the preferred sites for whisker and hillock growth were developed based on elastic anisotropy, local film microstructure, grain misorientation, and elastic strain energy density (ESED) as the driving force for growth. Local grain orientations and strains measured by synchrotron micro-diffraction in regions containing whiskers or hillocks were compared with elastic finite element analysis simulations, including Sn elastic anisotropy. Whisker and hillock grains were observed to have higher crystallographic misorientations with neighboring grains than generally observed in the microstructure. While elastic simulations predicted higher local out-of-plane elastic strains and ESEDs for whisker and hillock grains, synchrotron measurements of out-of-plane strains of whisker and hillock grains after growth showed relaxation, with correspondingly low ESEDs calculated from measured strains. This suggests that, before whisker or hillock formation, highly misoriented grains with high out-of-plane elastic strains and ESEDs relative to their neighbors determined, at least in part, which grains became whiskers or hillocks. Based on the models and experiments in this thesis, a clearer picture emerges of the necessary and sufficient conditions for tin whisker and hillock formation in thin films.

Modelling urban growth in the Indo-Gangetic plain using nighttime OLS data and cellular automata

NASA Astrophysics Data System (ADS)

Roy Chowdhury, P. K.; Maithani, Sandeep

2014-12-01

The present study demonstrates the applicability of the Operational Linescan System (OLS) sensor in modelling urban growth at regional level. The nighttime OLS data provides an easy, inexpensive way to map urban areas at a regional scale, requiring a very small volume of data. A cellular automata (CA) model was developed for simulating urban growth in the Indo-Gangetic plain; using OLS data derived maps as input. In the proposed CA model, urban growth was expressed in terms of causative factors like economy, topography, accessibility and urban infrastructure. The model was calibrated and validated based on OLS data of year 2003 and 2008 respectively using spatial metrics measures and subsequently the urban growth was predicted for the year 2020. The model predicted high urban growth in North Western part of the study area, in south eastern part growth would be concentrated around two cities, Kolkata and Howrah. While in the middle portion of the study area, i.e., Jharkhand, Bihar and Eastern Uttar Pradesh, urban growth has been predicted in form of clusters, mostly around the present big cities. These results will not only provide an input to urban planning but can also be utilized in hydrological and ecological modelling which require an estimate of future built up areas especially at regional level.

Modeling Tetragonal Lysozyme Crystal Growth Rates

NASA Technical Reports Server (NTRS)

Gorti, Sridhar; Forsythe, Elizabeth L.; Pusey, Marc L.

2003-01-01

Tetragonal lysozyme 110 face crystal growth rates, measured over 5 orders of magnitude in range, can be described using a model where growth occurs by 2D nucleation on the crystal surface for solution supersaturations of c/c(sub eq) less than or equal to 7 +/- 2. Based upon the model, the step energy per unit length, beta was estimated to be approx. 5.3 +/- 0.4 x 10(exp -7) erg/mol-cm, which for a step height of 56 A corresponds to barrier of approx. 7 +/- 1 k(sub B)T at 300 K. For supersaturations of c/c(sub eq) > 8, the model emphasizing crystal growth by 2D nucleation not only could not predict, but also consistently overestimated, the highest observable crystal growth rates. Kinetic roughening is hypothesized to occur at a cross-over supersaturation of c/c(sub eq) > 8, where crystal growth is postulated to occur by a different process such as adsorption. Under this assumption, all growth rate data indicated that a kinetic roughening transition and subsequent crystal growth by adsorption for all solution conditions, varying in buffer pH, temperature and precipitant concentration, occurs for c/c(sub eq)(T, pH, NaCl) in the range between 5 and 10, with an energy barrier for adsorption estimated to be approx. 20 k(sub B)T at 300 K. Based upon these and other estimates, we determined the size of the critical surface nucleate, at the crossover supersaturation and higher concentrations, to range from 4 to 10 molecules.

Individual-based modelling of population growth and diffusion in discrete time.

PubMed

Tkachenko, Natalie; Weissmann, John D; Petersen, Wesley P; Lake, George; Zollikofer, Christoph P E; Callegari, Simone

2017-01-01

Individual-based models (IBMs) of human populations capture spatio-temporal dynamics using rules that govern the birth, behavior, and death of individuals. We explore a stochastic IBM of logistic growth-diffusion with constant time steps and independent, simultaneous actions of birth, death, and movement that approaches the Fisher-Kolmogorov model in the continuum limit. This model is well-suited to parallelization on high-performance computers. We explore its emergent properties with analytical approximations and numerical simulations in parameter ranges relevant to human population dynamics and ecology, and reproduce continuous-time results in the limit of small transition probabilities. Our model prediction indicates that the population density and dispersal speed are affected by fluctuations in the number of individuals. The discrete-time model displays novel properties owing to the binomial character of the fluctuations: in certain regimes of the growth model, a decrease in time step size drives the system away from the continuum limit. These effects are especially important at local population sizes of <50 individuals, which largely correspond to group sizes of hunter-gatherers. As an application scenario, we model the late Pleistocene dispersal of Homo sapiens into the Americas, and discuss the agreement of model-based estimates of first-arrival dates with archaeological dates in dependence of IBM model parameter settings.

Physiologically based pharmacokinetic and pharmacodynamic modeling of an antagonist (SM-406/AT-406) of multiple inhibitor of apoptosis proteins (IAPs) in a mouse xenograft model of human breast cancer.

PubMed

Zhang, Tao; Li, Yanyan; Zou, Peng; Yu, Jing-yu; McEachern, Donna; Wang, Shaomeng; Sun, Duxin

2013-09-01

The inhibitors of apoptosis proteins (IAPs) are a class of key apoptosis regulators overexpressed or dysregulated in cancer. SM-406/AT-406 is a potent and selective small molecule mimetic of Smac that antagonizes the inhibitor of apoptosis proteins (IAPs). A physiologically based pharmacokinetic and pharmacodynamic (PBPK-PD) model was developed to predict the tissue concentration-time profiles of SM-406, the related onco-protein levels in tumor, and the tumor growth inhibition in a mouse model bearing human breast cancer xenograft. In the whole body physiologically based pharmacokinetic (PBPK) model for pharmacokinetics characterization, a well stirred (perfusion rate-limited) model was used to describe SM-406 pharmacokinetics in the lung, heart, kidney, intestine, liver and spleen, and a diffusion rate-limited (permeability limited) model was used for tumor. Pharmacodynamic (PD) models were developed to correlate the SM-406 concentration in tumor to the cIAP1 degradation, pro-caspase 8 decrease, CL-PARP accumulation and tumor growth inhibition. The PBPK-PD model well described the experimental pharmacokinetic data, the pharmacodynamic biomarker responses and tumor growth. This model may be helpful to predict tumor and plasma SM-406 concentrations in the clinic. Copyright © 2013 John Wiley & Sons, Ltd.

Unequal Education, Poverty and Low Growth--A Theoretical Framework for Rural Education of China

ERIC Educational Resources Information Center

Wu, Fangwei; Zhang, Deyuan; Zhang, Jinghua

2008-01-01

This paper constructs an intertemporal substitution educational model based on endogenous growth theory and examines the rural education, farmer income and rural economic growth problems in China. It shows that the households originally with the same economic endowment but different education endowment take different growth routes, the income…

Pentastatin-1, a collagen IV derived 20-mer peptide, suppresses tumor growth in a small cell lung cancer xenograft model.

PubMed

Koskimaki, Jacob E; Karagiannis, Emmanouil D; Tang, Benjamin C; Hammers, Hans; Watkins, D Neil; Pili, Roberto; Popel, Aleksander S

2010-02-01

Angiogenesis is the formation of neovasculature from a pre-existing vascular network. Progression of solid tumors including lung cancer is angiogenesis-dependent. We previously introduced a bioinformatics-based methodology to identify endogenous anti-angiogenic peptide sequences, and validated these predictions in vitro in human umbilical vein endothelial cell (HUVEC) proliferation and migration assays. One family of peptides with high activity is derived from the alpha-fibrils of type IV collagen. Based on the results from the in vitro screening, we have evaluated the ability of a 20 amino acid peptide derived from the alpha5 fibril of type IV collagen, pentastatin-1, to suppress vessel growth in an angioreactor-based directed in vivo angiogenesis assay (DIVAA). In addition, pentastatin-1 suppressed tumor growth with intraperitoneal peptide administration in a small cell lung cancer (SCLC) xenograft model in nude mice using the NCI-H82 human cancer cell line. Pentastatin-1 decreased the invasion of vessels into angioreactors in vivo in a dose dependent manner. The peptide also decreased the rate of tumor growth and microvascular density in vivo in a small cell lung cancer xenograft model. The peptide treatment significantly decreased the invasion of microvessels in angioreactors and the rate of tumor growth in the xenograft model, indicating potential treatment for angiogenesis-dependent disease, and for translational development as a therapeutic agent for lung cancer.

Impact of computational structure-based methods on drug discovery.

PubMed

Reynolds, Charles H

2014-01-01

Structure-based drug design has become an indispensible tool in drug discovery. The emergence of structure-based design is due to gains in structural biology that have provided exponential growth in the number of protein crystal structures, new computational algorithms and approaches for modeling protein-ligand interactions, and the tremendous growth of raw computer power in the last 30 years. Computer modeling and simulation have made major contributions to the discovery of many groundbreaking drugs in recent years. Examples are presented that highlight the evolution of computational structure-based design methodology, and the impact of that methodology on drug discovery.

Using a laboratory-based growth model to estimate mass- and temperature-dependent growth parameters across populations of juvenile Chinook Salmon

USGS Publications Warehouse

Perry, Russell W.; Plumb, John M.; Huntington, Charles

2015-01-01

To estimate the parameters that govern mass- and temperature-dependent growth, we conducted a meta-analysis of existing growth data from juvenile Chinook Salmon Oncorhynchus tshawytscha that were fed an ad libitum ration of a pelleted diet. Although the growth of juvenile Chinook Salmon has been well studied, research has focused on a single population, a narrow range of fish sizes, or a narrow range of temperatures. Therefore, we incorporated the Ratkowsky model for temperature-dependent growth into an allometric growth model; this model was then fitted to growth data from 11 data sources representing nine populations of juvenile Chinook Salmon. The model fit the growth data well, explaining 98% of the variation in final mass. The estimated allometric mass exponent (b) was 0.338 (SE = 0.025), similar to estimates reported for other salmonids. This estimate of b will be particularly useful for estimating mass-standardized growth rates of juvenile Chinook Salmon. In addition, the lower thermal limit, optimal temperature, and upper thermal limit for growth were estimated to be 1.8°C (SE = 0.63°C), 19.0°C (SE = 0.27°C), and 24.9°C (SE = 0.02°C), respectively. By taking a meta-analytical approach, we were able to provide a growth model that is applicable across populations of juvenile Chinook Salmon receiving an ad libitum ration of a pelleted diet.

Predictive model for the growth of spoilage bacteria on modified atmosphere packaged Atlantic salmon produced in Australia.

PubMed

Powell, S M; Ratkowsky, D A; Tamplin, M L

2015-05-01

Most existing models for the spoilage of modified atmosphere packed Atlantic salmon are based on the growth of the spoilage organism Photobacterium phosphoreum. However, there is evidence that this organism is not the specific spoilage organism on salmon produced and packaged in Australia. We developed a predictive model for the growth of bacteria in Australian-produced Atlantic salmon stored under modified atmosphere conditions (30-98% carbon dioxide in nitrogen) at refrigeration temperatures (0-10 °C). As expected, both higher levels of carbon dioxide and lower temperatures decreased the observed growth rates of the total population. A Bělehrádek-type model for growth rate fitted the data best with an acceptably low root mean square error. At low temperatures (∼0 °C) the growth rates in this study were similar to those predicted by other models but at higher temperatures (∼10 °C) the growth rates were significantly lower in the current study. Crown Copyright © 2014. Published by Elsevier Ltd. All rights reserved.

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

USGS Publications Warehouse

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

2015-01-01

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

Tree-ring growth of Scots pine, Common beech and Pedunculate oak under future climate in northeastern Germany

NASA Astrophysics Data System (ADS)

Jurasinski, Gerald; Scharnweber, Tobias; Schröder, Christian; Lennartz, Bernd; Bauwe, Andreas

2017-04-01

Tree growth depends, among other factors, largely on the prevailing climatic conditions. Therefore, tree growth patterns are to be expected under climate change. Here, we analyze the tree-ring growth response of three major European tree species to projected future climate across a climatic (mostly precipitation) gradient in northeastern Germany. We used monthly data for temperature, precipitation, and the standardized precipitation evapotranspiration index (SPEI) over multiple time scales (1, 3, 6, 12, and 24 months) to construct models of tree-ring growth for Scots pine (Pinus syl- vestris L.) at three pure stands, and for Common beech (Fagus sylvatica L.) and Pedunculate oak (Quercus robur L.) at three mature mixed stands. The regression models were derived using a two-step approach based on partial least squares regression (PLSR) to extract potentially well explaining variables followed by ordinary least squares regression (OLSR) to consolidate the models to the least number of variables while retaining high explanatory power. The stability of the models was tested with a comprehensive calibration-verification scheme. All models were successfully verified with R2s ranging from 0.21 for the western pine stand to 0.62 for the beech stand in the east. For growth prediction, climate data forecasted until 2100 by the regional climate model WETTREG2010 based on the A1B Intergovernmental Panel on Climate Change (IPCC) emission scenario was used. For beech and oak, growth rates will likely decrease until the end of the 21st century. For pine, modeled growth trends vary and range from a slight growth increase to a weak decrease in growth rates depending on the position along the climatic gradient. The climatic gradient across the study area will possibly affect the future growth of oak with larger growth reductions towards the drier east. For beech, site-specific adaptations seem to override the influence of the climatic gradient. We conclude that in Northeastern Germany Scots pine has great potential to remain resilient to projected climate change without any greater impairment, whereas Common beech and Pedunculate oak will likely face lesser growth under the expected warmer and dryer climate conditions. The results call for an adaptation of forest management to mitigate the negative effects of climate change for beech and oak in the region.

The integration of geophysical and enhanced Moderate Resolution Imaging Spectroradiometer Normalized Difference Vegetation Index data into a rule-based, piecewise regression-tree model to estimate cheatgrass beginning of spring growth

USGS Publications Warehouse

Boyte, Stephen P.; Wylie, Bruce K.; Major, Donald J.; Brown, Jesslyn F.

2015-01-01

Cheatgrass exhibits spatial and temporal phenological variability across the Great Basin as described by ecological models formed using remote sensing and other spatial data-sets. We developed a rule-based, piecewise regression-tree model trained on 99 points that used three data-sets – latitude, elevation, and start of season time based on remote sensing input data – to estimate cheatgrass beginning of spring growth (BOSG) in the northern Great Basin. The model was then applied to map the location and timing of cheatgrass spring growth for the entire area. The model was strong (R2 = 0.85) and predicted an average cheatgrass BOSG across the study area of 29 March–4 April. Of early cheatgrass BOSG areas, 65% occurred at elevations below 1452 m. The highest proportion of cheatgrass BOSG occurred between mid-April and late May. Predicted cheatgrass BOSG in this study matched well with previous Great Basin cheatgrass green-up studies.

Evaluation of a kinetic model for computer simulation of growth and fermentation by Scheffersomyces (Pichia) stipitis fed D-xylose

USDA-ARS?s Scientific Manuscript database

Scheffersomyces (formly Pichia) stipitis is a potential biocatalyst for converting lignocelluloses to ethanol because the yeast natively ferments xylose. An unstructured kinetic model based upon a system of linear differential equations has been formulated that describes growth and ethanol productio...

Non-Linear Modeling of Growth Prerequisites in a Finnish Polytechnic Institution of Higher Education

ERIC Educational Resources Information Center

Nokelainen, Petri; Ruohotie, Pekka

2009-01-01

Purpose: This study aims to examine the factors of growth-oriented atmosphere in a Finnish polytechnic institution of higher education with categorical exploratory factor analysis, multidimensional scaling and Bayesian unsupervised model-based visualization. Design/methodology/approach: This study was designed to examine employee perceptions of…

Biophysical modelling of intra-ring variations in tracheid features and wood density of Pinus pinaster trees exposed to seasonal droughts

Treesearch

Sarah Wilkinson; Jerome Ogee; Jean-Christophe Domec; Mark Rayment; Lisa Wingate

2015-01-01

Process-based models that link seasonally varying environmental signals to morphological features within tree rings are essential tools to predict tree growth response and commercially important wood quality traits under future climate scenarios. This study evaluated model portrayal of radial growth and wood anatomy observations within a mature maritime pine (Pinus...

Using a GIS-based spot growth model and visual simulator to evaluate the effects of silvicultural treatments on southern pine beetle-infested stands

Treesearch

Chiao-Ying Chou; Roy L. Hedden; Bo Song; Thomas M. Williams

2013-01-01

Many models are available for simulating the probability of southern pine beetle (Dendroctonus frontalis Zimmermann) (SPB) infestation and outbreak dynamics. However, only a few models focused on the potential spatial SPB growth. Although the integrated pest management systems are currently adopted, SPB management is still challenging because of...

S-curve networks and an approximate method for estimating degree distributions of complex networks

NASA Astrophysics Data System (ADS)

Guo, Jin-Li

2010-12-01

In the study of complex networks almost all theoretical models have the property of infinite growth, but the size of actual networks is finite. According to statistics from the China Internet IPv4 (Internet Protocol version 4) addresses, this paper proposes a forecasting model by using S curve (logistic curve). The growing trend of IPv4 addresses in China is forecasted. There are some reference values for optimizing the distribution of IPv4 address resource and the development of IPv6. Based on the laws of IPv4 growth, that is, the bulk growth and the finitely growing limit, it proposes a finite network model with a bulk growth. The model is said to be an S-curve network. Analysis demonstrates that the analytic method based on uniform distributions (i.e., Barabási-Albert method) is not suitable for the network. It develops an approximate method to predict the growth dynamics of the individual nodes, and uses this to calculate analytically the degree distribution and the scaling exponents. The analytical result agrees with the simulation well, obeying an approximately power-law form. This method can overcome a shortcoming of Barabási-Albert method commonly used in current network research.

AmapSim: a structural whole-plant simulator based on botanical knowledge and designed to host external functional models.

PubMed

Barczi, Jean-François; Rey, Hervé; Caraglio, Yves; de Reffye, Philippe; Barthélémy, Daniel; Dong, Qiao Xue; Fourcaud, Thierry

2008-05-01

AmapSim is a tool that implements a structural plant growth model based on a botanical theory and simulates plant morphogenesis to produce accurate, complex and detailed plant architectures. This software is the result of more than a decade of research and development devoted to plant architecture. New advances in the software development have yielded plug-in external functions that open up the simulator to functional processes. The simulation of plant topology is based on the growth of a set of virtual buds whose activity is modelled using stochastic processes. The geometry of the resulting axes is modelled by simple descriptive functions. The potential growth of each bud is represented by means of a numerical value called physiological age, which controls the value for each parameter in the model. The set of possible values for physiological ages is called the reference axis. In order to mimic morphological and architectural metamorphosis, the value allocated for the physiological age of buds evolves along this reference axis according to an oriented finite state automaton whose occupation and transition law follows a semi-Markovian function. Simulations were performed on tomato plants to demonstrate how the AmapSim simulator can interface external modules, e.g. a GREENLAB growth model and a radiosity model. The algorithmic ability provided by AmapSim, e.g. the reference axis, enables unified control to be exercised over plant development parameter values, depending on the biological process target: how to affect the local pertinent process, i.e. the pertinent parameter(s), while keeping the rest unchanged. This opening up to external functions also offers a broadened field of applications and thus allows feedback between plant growth and the physical environment.

AmapSim: A Structural Whole-plant Simulator Based on Botanical Knowledge and Designed to Host External Functional Models

PubMed Central

Barczi, Jean-François; Rey, Hervé; Caraglio, Yves; de Reffye, Philippe; Barthélémy, Daniel; Dong, Qiao Xue; Fourcaud, Thierry

2008-01-01

Background and Aims AmapSim is a tool that implements a structural plant growth model based on a botanical theory and simulates plant morphogenesis to produce accurate, complex and detailed plant architectures. This software is the result of more than a decade of research and development devoted to plant architecture. New advances in the software development have yielded plug-in external functions that open up the simulator to functional processes. Methods The simulation of plant topology is based on the growth of a set of virtual buds whose activity is modelled using stochastic processes. The geometry of the resulting axes is modelled by simple descriptive functions. The potential growth of each bud is represented by means of a numerical value called physiological age, which controls the value for each parameter in the model. The set of possible values for physiological ages is called the reference axis. In order to mimic morphological and architectural metamorphosis, the value allocated for the physiological age of buds evolves along this reference axis according to an oriented finite state automaton whose occupation and transition law follows a semi-Markovian function. Key Results Simulations were performed on tomato plants to demostrate how the AmapSim simulator can interface external modules, e.g. a GREENLAB growth model and a radiosity model. Conclusions The algorithmic ability provided by AmapSim, e.g. the reference axis, enables unified control to be exercised over plant development parameter values, depending on the biological process target: how to affect the local pertinent process, i.e. the pertinent parameter(s), while keeping the rest unchanged. This opening up to external functions also offers a broadened field of applications and thus allows feedback between plant growth and the physical environment. PMID:17766310

Corruption and economic growth with non constant labor force growth

NASA Astrophysics Data System (ADS)

Brianzoni, Serena; Campisi, Giovanni; Russo, Alberto

2018-05-01

Based on Brianzoni et al. [1] in the present work we propose an economic model regarding the relationship between corruption in public procurement and economic growth. We extend the benchmark model by introducing endogenous labor force growth, described by the logistic equation. The results of previous studies, as Del Monte and Papagni [2] and Mauro [3], show that countries are stuck in one of the two equilibria (high corruption and low economic growth or low corruption and high economic growth). Brianzoni et al. [1] prove the existence of a further steady state characterized by intermediate levels of capital per capita and corruption. Our aim is to investigate the effects of the endogenous growth around such equilibrium. Moreover, due to the high number of parameters of the model, specific attention is given to the numerical simulations which highlight new policy measures that can be adopted by the government to fight corruption.

Numerical Estimation of the Curvature of Biological Surfaces

NASA Technical Reports Server (NTRS)

Todd, P. H.

1985-01-01

Many biological systems may profitably be studied as surface phenomena. A model consisting of isotropic growth of a curved surface from a flat sheet is assumed. With such a model, the Gaussian curvature of the final surface determines whether growth rate of the surface is subharmonic or superharmonic. These properties correspond to notions of convexity and concavity, and thus to local excess growth and local deficiency of growth. In biological models where the major factors controlling surface growth are intrinsic to the surface, researchers thus gained from geometrical study information on the differential growth undergone by the surface. These ideas were applied to an analysis of the folding of the cerebral cortex, a geometrically rather complex surface growth. A numerical surface curvature technique based on an approximation to the Dupin indicatrix of the surface was developed. A metric for comparing curvature estimates is introduced, and considerable numerical testing indicated the reliability of this technique.

Application of enthalpy model for floating zone silicon crystal growth

NASA Astrophysics Data System (ADS)

Krauze, A.; Bergfelds, K.; Virbulis, J.

2017-09-01

A 2D simplified crystal growth model based on the enthalpy method and coupled with a low-frequency harmonic electromagnetic model is developed to simulate the silicon crystal growth near the external triple point (ETP) and crystal melting on the open melting front of a polycrystalline feed rod in FZ crystal growth systems. Simulations of the crystal growth near the ETP show significant influence of the inhomogeneities of the EM power distribution on the crystal growth rate for a 4 in floating zone (FZ) system. The generated growth rate fluctuations are shown to be larger in the system with higher crystal pull rate. Simulations of crystal melting on the open melting front of the polycrystalline rod show the development of melt-filled grooves at the open melting front surface. The distance between the grooves is shown to grow with the increase of the skin-layer depth in the solid material.

A new reserve growth model for United States oil and gas fields

USGS Publications Warehouse

Verma, M.K.

2005-01-01

Reserve (or field) growth, which is an appreciation of total ultimate reserves through time, is a well-recognized phenomenon, particularly in mature petroleum provinces. The importance of forecasting reserve growth accurately in a mature petroleum province made it necessary to develop improved growth functions, and a critical review of the original Arrington method was undertaken. During a five-year (1992-1996), the original Arrington method gave 1.03% higher than the actual oil reserve growth, whereas the proposed modified method gave a value within 0.3% of the actual growth, and therefore it was accepted for the development for reserve growth models. During a five-year (1992-1996), the USGS 1995 National Assessment gave 39.3% higher oil and 33.6% lower gas than the actual growths, whereas the new model based on Modified Arrington method gave 11.9% higher oil and 29.8% lower gas than the actual growths. The new models forecast predict reserve growths of 4.2 billion barrels of oil (2.7%) and 30.2 trillion cubic feet of gas (5.4%) for the conterminous U.S. for the next five years (1997-2001). ?? 2005 International Association for Mathematical Geology.

In silico modeling for tumor growth visualization.

PubMed

Jeanquartier, Fleur; Jean-Quartier, Claire; Cemernek, David; Holzinger, Andreas

2016-08-08

Cancer is a complex disease. Fundamental cellular based studies as well as modeling provides insight into cancer biology and strategies to treatment of the disease. In silico models complement in vivo models. Research on tumor growth involves a plethora of models each emphasizing isolated aspects of benign and malignant neoplasms. Biologists and clinical scientists are often overwhelmed by the mathematical background knowledge necessary to grasp and to apply a model to their own research. We aim to provide a comprehensive and expandable simulation tool to visualizing tumor growth. This novel Web-based application offers the advantage of a user-friendly graphical interface with several manipulable input variables to correlate different aspects of tumor growth. By refining model parameters we highlight the significance of heterogeneous intercellular interactions on tumor progression. Within this paper we present the implementation of the Cellular Potts Model graphically presented through Cytoscape.js within a Web application. The tool is available under the MIT license at https://github.com/davcem/cpm-cytoscape and http://styx.cgv.tugraz.at:8080/cpm-cytoscape/ . In-silico methods overcome the lack of wet experimental possibilities and as dry method succeed in terms of reduction, refinement and replacement of animal experimentation, also known as the 3R principles. Our visualization approach to simulation allows for more flexible usage and easy extension to facilitate understanding and gain novel insight. We believe that biomedical research in general and research on tumor growth in particular will benefit from the systems biology perspective.

Cyclic plasticity models and application in fatigue analysis

NASA Technical Reports Server (NTRS)

Kalev, I.

1981-01-01

An analytical procedure for prediction of the cyclic plasticity effects on both the structural fatigue life to crack initiation and the rate of crack growth is presented. The crack initiation criterion is based on the Coffin-Manson formulae extended for multiaxial stress state and for inclusion of the mean stress effect. This criterion is also applied for the accumulated damage ahead of the existing crack tip which is assumed to be related to the crack growth rate. Three cyclic plasticity models, based on the concept of combination of several yield surfaces, are employed for computing the crack growth rate of a crack plane stress panel under several cyclic loading conditions.

Network growth models: A behavioural basis for attachment proportional to fitness

NASA Astrophysics Data System (ADS)

Bell, Michael; Perera, Supun; Piraveenan, Mahendrarajah; Bliemer, Michiel; Latty, Tanya; Reid, Chris

2017-02-01

Several growth models have been proposed in the literature for scale-free complex networks, with a range of fitness-based attachment models gaining prominence recently. However, the processes by which such fitness-based attachment behaviour can arise are less well understood, making it difficult to compare the relative merits of such models. This paper analyses an evolutionary mechanism that would give rise to a fitness-based attachment process. In particular, it is proven by analytical and numerical methods that in homogeneous networks, the minimisation of maximum exposure to node unfitness leads to attachment probabilities that are proportional to node fitness. This result is then extended to heterogeneous networks, with supply chain networks being used as an example.

On Fitting a Multivariate Two-Part Latent Growth Model

PubMed Central

Xu, Shu; Blozis, Shelley A.; Vandewater, Elizabeth A.

2017-01-01

A 2-part latent growth model can be used to analyze semicontinuous data to simultaneously study change in the probability that an individual engages in a behavior, and if engaged, change in the behavior. This article uses a Monte Carlo (MC) integration algorithm to study the interrelationships between the growth factors of 2 variables measured longitudinally where each variable can follow a 2-part latent growth model. A SAS macro implementing Mplus is developed to estimate the model to take into account the sampling uncertainty of this simulation-based computational approach. A sample of time-use data is used to show how maximum likelihood estimates can be obtained using a rectangular numerical integration method and an MC integration method. PMID:29333054

Evaluation of a kinetic model for computer simulation of growth and fermentation by Scheffersomyces (Pichia) stipitis fed D-xylose.

PubMed

Slininger, P J; Dien, B S; Lomont, J M; Bothast, R J; Ladisch, M R; Okos, M R

2014-08-01

Scheffersomyces (formerly Pichia) stipitis is a potential biocatalyst for converting lignocelluloses to ethanol because the yeast natively ferments xylose. An unstructured kinetic model based upon a system of linear differential equations has been formulated that describes growth and ethanol production as functions of ethanol, oxygen, and xylose concentrations for both growth and fermentation stages. The model was validated for various growth conditions including batch, cell recycle, batch with in situ ethanol removal and fed-batch. The model provides a summary of basic physiological yeast properties and is an important tool for simulating and optimizing various culture conditions and evaluating various bioreactor designs for ethanol production. © 2014 Wiley Periodicals, Inc.

Monte Carlo Based Calibration and Uncertainty Analysis of a Coupled Plant Growth and Hydrological Model

NASA Astrophysics Data System (ADS)

Houska, Tobias; Multsch, Sebastian; Kraft, Philipp; Frede, Hans-Georg; Breuer, Lutz

2014-05-01

Computer simulations are widely used to support decision making and planning in the agriculture sector. On the one hand, many plant growth models use simplified hydrological processes and structures, e.g. by the use of a small number of soil layers or by the application of simple water flow approaches. On the other hand, in many hydrological models plant growth processes are poorly represented. Hence, fully coupled models with a high degree of process representation would allow a more detailed analysis of the dynamic behaviour of the soil-plant interface. We used the Python programming language to couple two of such high process oriented independent models and to calibrate both models simultaneously. The Catchment Modelling Framework (CMF) simulated soil hydrology based on the Richards equation and the Van-Genuchten-Mualem retention curve. CMF was coupled with the Plant growth Modelling Framework (PMF), which predicts plant growth on the basis of radiation use efficiency, degree days, water shortage and dynamic root biomass allocation. The Monte Carlo based Generalised Likelihood Uncertainty Estimation (GLUE) method was applied to parameterize the coupled model and to investigate the related uncertainty of model predictions to it. Overall, 19 model parameters (4 for CMF and 15 for PMF) were analysed through 2 x 106 model runs randomly drawn from an equally distributed parameter space. Three objective functions were used to evaluate the model performance, i.e. coefficient of determination (R2), bias and model efficiency according to Nash Sutcliffe (NSE). The model was applied to three sites with different management in Muencheberg (Germany) for the simulation of winter wheat (Triticum aestivum L.) in a cross-validation experiment. Field observations for model evaluation included soil water content and the dry matters of roots, storages, stems and leaves. Best parameter sets resulted in NSE of 0.57 for the simulation of soil moisture across all three sites. The shape parameter of the retention curve n was highly constrained whilst other parameters of the retention curve showed a large equifinality. The root and storage dry matter observations were predicted with a NSE of 0.94, a low bias of 58.2 kg ha-1 and a high R2 of 0.98. Dry matters of stem and leaves were predicted with less, but still high accuracy (NSE=0.79, bias=221.7 kg ha-1, R2=0.87). We attribute this slightly poorer model performance to missing leaf senescence which is currently not implemented in PMF. The most constrained parameters for the plant growth model were the radiation-use-efficiency and the base temperature. Cross validation helped to identify deficits in the model structure, pointing out the need of including agricultural management options in the coupled model.

Monte Carlo based calibration and uncertainty analysis of a coupled plant growth and hydrological model

NASA Astrophysics Data System (ADS)

Houska, T.; Multsch, S.; Kraft, P.; Frede, H.-G.; Breuer, L.

2013-12-01

Computer simulations are widely used to support decision making and planning in the agriculture sector. On the one hand, many plant growth models use simplified hydrological processes and structures, e.g. by the use of a small number of soil layers or by the application of simple water flow approaches. On the other hand, in many hydrological models plant growth processes are poorly represented. Hence, fully coupled models with a high degree of process representation would allow a more detailed analysis of the dynamic behaviour of the soil-plant interface. We used the Python programming language to couple two of such high process oriented independent models and to calibrate both models simultaneously. The Catchment Modelling Framework (CMF) simulated soil hydrology based on the Richards equation and the van-Genuchten-Mualem retention curve. CMF was coupled with the Plant growth Modelling Framework (PMF), which predicts plant growth on the basis of radiation use efficiency, degree days, water shortage and dynamic root biomass allocation. The Monte Carlo based Generalised Likelihood Uncertainty Estimation (GLUE) method was applied to parameterize the coupled model and to investigate the related uncertainty of model predictions to it. Overall, 19 model parameters (4 for CMF and 15 for PMF) were analysed through 2 × 106 model runs randomly drawn from an equally distributed parameter space. Three objective functions were used to evaluate the model performance, i.e. coefficient of determination (R2), bias and model efficiency according to Nash Sutcliffe (NSE). The model was applied to three sites with different management in Muencheberg (Germany) for the simulation of winter wheat (Triticum aestivum L.) in a cross-validation experiment. Field observations for model evaluation included soil water content and the dry matters of roots, storages, stems and leaves. Best parameter sets resulted in NSE of 0.57 for the simulation of soil moisture across all three sites. The shape parameter of the retention curve n was highly constrained whilst other parameters of the retention curve showed a large equifinality. The root and storage dry matter observations were predicted with a NSE of 0.94, a low bias of -58.2 kg ha-1 and a high R2 of 0.98. Dry matters of stem and leaves were predicted with less, but still high accuracy (NSE = 0.79, bias = 221.7 kg ha-1, R2 = 0.87). We attribute this slightly poorer model performance to missing leaf senescence which is currently not implemented in PMF. The most constrained parameters for the plant growth model were the radiation-use-efficiency and the base temperature. Cross validation helped to identify deficits in the model structure, pointing out the need of including agricultural management options in the coupled model.

Predicting the combinatorial effects of water activity, pH and organic acids on Listeria growth in media and complex food matrices.

PubMed

Nyhan, L; Begley, M; Mutel, A; Qu, Y; Johnson, N; Callanan, M

2018-09-01

The aim of this study was to develop a model to predict growth of Listeria in complex food matrices as a function of pH, water activity and undissociated acetic and propionic acid concentration i.e. common food hurdles. Experimental growth curves of Listeria in food products and broth media were collected from ComBase, the literature and industry sources from which a bespoke secondary gamma model was constructed. Model performance was evaluated by comparing predictions to measured growth rates in growth media (BHI broth) and two adjusted food matrices (zucchini purée and béarnaise sauce). In general, observed growth rates were higher in broth than in the food matrices which resulted in the model over-estimating growth in the adjusted food matrices. In addition, model outputs were more accurate for conditions without acids, indicating that the organic acid component of the model was a source of inaccuracy. In summary, a new predictive growth model for innovating or renovating food products that rely on multi-hurdle technology was created. This study is the first to report on modelling of propionic acid as an inhibitor of Listeria in combination with other hurdles. Our findings provide valuable insights into predictive model design and performance and highlight the importance of experimental validation of models in real food matrices rather than laboratory media alone. Copyright © 2018 Elsevier Ltd. All rights reserved.

Modeling determinants of growth: evidence for a community-based target in height?

PubMed

Aßmann, Christian; Hermanussen, Michael

2013-07-01

Human growth is traditionally envisaged as a target-seeking process regulated by genes, nutrition, health, and the state of an individual's social and economic environment; it is believed that under optimal physical conditions, an individual will achieve his or her full genetic potential. Using a panel data set on individual height increments, we suggest a statistical modeling approach that characterizes growth as first-order trend stationary and allows for controlling individual growth tempo via observable measures of individual maturity. A Bayesian framework and corresponding Markov-chain Monte Carlo techniques allowing for a conceptually stringent treatment of missing values are adapted for parameter estimation. The model provides evidence for the adjustment of the individual growth rate toward average height of the population. The increase in adult body height during the past 150 y has been explained by the steady improvement of living conditions that are now being considered to have reached an optimum in Western societies. The current investigation questions the notion that the traditional concept in the understanding of this target-seeking process is sufficient. We consider an additional regulator that possibly points at community-based target seeking in growth.

Economic planning and equilibrium growth of human resources and capital in health-care sector: Case study of Iran.

PubMed

Mahboobi-Ardakan, Payman; Kazemian, Mahmood; Mehraban, Sattar

2017-01-01

During different planning periods, human resources factor has been considerably increased in the health-care sector. The main goal is to determine economic planning conditions and equilibrium growth for services level and specialized workforce resources in health-care sector and also to determine the gap between levels of health-care services and specialized workforce resources in the equilibrium growth conditions and their available levels during the periods of the first to fourth development plansin Iran. In the study after data collection, econometric methods and EViews version 8.0 were used for data processing. The used model was based on neoclassical economic growth model. The results indicated that during the former planning periods, although specialized workforce has been increased significantly in health-care sector, lack of attention to equilibrium growth conditions caused imbalance conditions for product level and specialized workforce in health-care sector. In the past development plans for health services, equilibrium conditions based on the full employment in the capital stock, and specialized labor are not considered. The government could act by choosing policies determined by the growth model to achieve equilibrium level in the field of human resources and services during the next planning periods.

IWR-MAIN Water Use Forecasting System. Version 5.1. User’s Manual and System Description

DTIC Science & Technology

1987-12-01

Crosschecks for Input Data 1-68 11-1 Organization of the IWR-MAIN System H-8 11-2 Example of Econometric Demand Model 11-9 11-3 Example of Unit Use Coefficient...Unaccounted (entry does not affect default Loss and free service calculations) Y Conservation Data City Name: Test City USA Fl-Hetp, F2-return to monu, F4...socioeconomic data. 1-11 (1) Internal Growth Models The IWR-MAIN program contains a subroutine called GROWTH which uses econometric growth models based on

Plant architecture, growth and radiative transfer for terrestrial and space environments

NASA Technical Reports Server (NTRS)

Norman, John M.; Goel, Narendra S.

1993-01-01

The overall objective of this research was to develop a hardware implemented model that would incorporate realistic and dynamic descriptions of canopy architecture in physiologically based models of plant growth and functioning, with an emphasis on radiative transfer while accommodating other environmental constraints. The general approach has five parts: a realistic mathematical treatment of canopy architecture, a methodology for combining this general canopy architectural description with a general radiative transfer model, the inclusion of physiological and environmental aspects of plant growth, inclusion of plant phenology, and integration.

Prediction of pathogen growth on iceberg lettuce under real temperature history during distribution from farm to table.

PubMed

Koseki, Shigenobu; Isobe, Seiichiro

2005-10-25

The growth of pathogenic bacteria Escherichia coli O157:H7, Salmonella spp., and Listeria monocytogenes on iceberg lettuce under constant and fluctuating temperatures was modelled in order to estimate the microbial safety of this vegetable during distribution from the farm to the table. Firstly, we examined pathogen growth on lettuce at constant temperatures, ranging from 5 to 25 degrees C, and then we obtained the growth kinetic parameters (lag time, maximum growth rate (micro(max)), and maximum population density (MPD)) using the Baranyi primary growth model. The parameters were similar to those predicted by the pathogen modelling program (PMP), with the exception of MPD. The MPD of each pathogen on lettuce was 2-4 log(10) CFU/g lower than that predicted by PMP. Furthermore, the MPD of pathogens decreased with decreasing temperature. The relationship between mu(max) and temperature was linear in accordance with Ratkowsky secondary model as was the relationship between the MPD and temperature. Predictions of pathogen growth under fluctuating temperature used the Baranyi primary microbial growth model along with the Ratkowsky secondary model and MPD equation. The fluctuating temperature profile used in this study was the real temperature history measured during distribution from the field at harvesting to the retail store. Overall predictions for each pathogen agreed well with observed viable counts in most cases. The bias and root mean square error (RMSE) of the prediction were small. The prediction in which mu(max) was based on PMP showed a trend of overestimation relative to prediction based on lettuce. However, the prediction concerning E. coli O157:H7 and Salmonella spp. on lettuce greatly overestimated growth in the case of a temperature history starting relatively high, such as 25 degrees C for 5 h. In contrast, the overall prediction of L. monocytogenes under the same circumstances agreed with the observed data.

The essential features and modes of bacterial polar growth.

PubMed

Cameron, Todd A; Zupan, John R; Zambryski, Patricia C

2015-06-01

Polar growth represents a surprising departure from the canonical dispersed cell growth model. However, we know relatively little of the underlying mechanisms governing polar growth or the requisite suite of factors that direct polar growth. Underscoring how classic doctrine can be turned on its head, the peptidoglycan layer of polar-growing bacteria features unusual crosslinks and in some species the quintessential cell division proteins FtsA and FtsZ are recruited to the growing poles. Remarkably, numerous medically important pathogens utilize polar growth, accentuating the need for intensive research in this area. Here we review models of polar growth in bacteria based on recent research in the Actinomycetales and Rhizobiales, with emphasis on Mycobacterium and Agrobacterium species. Copyright © 2015 Elsevier Ltd. All rights reserved.

Dietary change and stable isotopes: a model of growth and dormancy in cave bears.

PubMed Central

Lidén, K; Angerbjörn, A

1999-01-01

In order to discuss dietary change over time by the use of stable isotopes, it is necessary to sort out the underlying processes in isotopic variation. Together with the dietary signal other processes have been investigated, namely metabolic processes, collagen turnover and physical growth. However, growth and collagen turnover time have so far been neglected in dietary reconstruction based on stable isotopes. An earlier study suggested that cave bears (Ursus spelaeus) probably gave birth to cubs during dormancy. We provide an estimate of the effect on stable isotopes of growth and metabolism and discuss collagen turnover in a population of cave bears. Based on a quantitative model, we hypothesized that bear cubs lactated their mothers during their first and second winters, but were fed solid food together with lactation during their first summer. This demonstrates the need to include physical growth, metabolism and collagen turnover in dietary reconstruction. Whereas the effects of diet and metabolism are due to fractionation, growth and collagen turnover are dilution processes. PMID:10518325

Tribology. Mechanisms of antiwear tribofilm growth revealed in situ by single-asperity sliding contacts.

PubMed

Gosvami, N N; Bares, J A; Mangolini, F; Konicek, A R; Yablon, D G; Carpick, R W

2015-04-03

Zinc dialkyldithiophosphates (ZDDPs) form antiwear tribofilms at sliding interfaces and are widely used as additives in automotive lubricants. The mechanisms governing the tribofilm growth are not well understood, which limits the development of replacements that offer better performance and are less likely to degrade automobile catalytic converters over time. Using atomic force microscopy in ZDDP-containing lubricant base stock at elevated temperatures, we monitored the growth and properties of the tribofilms in situ in well-defined single-asperity sliding nanocontacts. Surface-based nucleation, growth, and thickness saturation of patchy tribofilms were observed. The growth rate increased exponentially with either applied compressive stress or temperature, consistent with a thermally activated, stress-assisted reaction rate model. Although some models rely on the presence of iron to catalyze tribofilm growth, the films grew regardless of the presence of iron on either the tip or substrate, highlighting the critical role of stress and thermal activation. Copyright © 2015, American Association for the Advancement of Science.

Effect of sodium accumulation on heterotrophic growth and polyhydroxybutyrate (PHB) production by Cupriavidus necator.

PubMed

Mozumder, Md Salatul Islam; Garcia-Gonzalez, Linsey; De Wever, Heleen; Volcke, Eveline I P

2015-09-01

This study evaluates the effect of sodium (Na(+)) concentration on the growth and PHB production by Cupriavidus necator. Both biomass growth and PHB production were inhibited by Na(+): biomass growth became zero at 8.9 g/L Na(+) concentration while PHB production was completely stopped at 10.5 g/L Na(+). A mathematical model for pure culture heterotrophic PHB production was set up to describe the Na(+) inhibition effect. The parameters related to Na(+) inhibition were estimated based on shake flask experiments. The accumulated Na(+) showed non-linear inhibition effect on biomass growth but linear inhibition effect on PHB production kinetics. Fed-batch experiments revealed that a high accumulation of Na(+) due to a prolonged growth phase, using NaOH for pH control, decreased the subsequent PHB production. The model was validated based on independent experimental data sets, showing a good agreement between experimental data and simulation results. Copyright © 2015 Elsevier Ltd. All rights reserved.

Modern Methods for Modeling Change in Obesity Research in Nursing.

PubMed

Sereika, Susan M; Zheng, Yaguang; Hu, Lu; Burke, Lora E

2017-08-01

Persons receiving treatment for weight loss often demonstrate heterogeneity in lifestyle behaviors and health outcomes over time. Traditional repeated measures approaches focus on the estimation and testing of an average temporal pattern, ignoring the interindividual variability about the trajectory. An alternate person-centered approach, group-based trajectory modeling, can be used to identify distinct latent classes of individuals following similar trajectories of behavior or outcome change as a function of age or time and can be expanded to include time-invariant and time-dependent covariates and outcomes. Another latent class method, growth mixture modeling, builds on group-based trajectory modeling to investigate heterogeneity within the distinct trajectory classes. In this applied methodologic study, group-based trajectory modeling for analyzing changes in behaviors or outcomes is described and contrasted with growth mixture modeling. An illustration of group-based trajectory modeling is provided using calorie intake data from a single-group, single-center prospective study for weight loss in adults who are either overweight or obese.

Age, growth and population structure of invasive lionfish (Pterois volitans/miles) in northeast Florida using a length-based, age-structured population model.

PubMed

Johnson, Eric G; Swenarton, Mary Katherine

2016-01-01

The effective management of invasive species requires detailed understanding of the invader's life history. This information is essential for modeling population growth and predicting rates of expansion, quantifying ecological impacts and assessing the efficacy of removal and control strategies. Indo-Pacific lionfish ( Pterois volitans/miles ) have rapidly invaded the western Atlantic, Gulf of Mexico and Caribbean Sea with documented negative impacts on native ecosystems. To better understand the life history of this species, we developed and validated a length-based, age-structured model to investigate age, growth and population structure in northeast Florida. The main findings of this study were: (1) lionfish exhibited rapid growth with seasonal variation in growth rates; (2) distinct cohorts were clearly identifiable in the length-frequency data, suggesting that lionfish are recruiting during a relatively short period in summer; and (3) the majority of lionfish were less than two years old with no lionfish older than three years of age, which may be the result of culling efforts as well as ontogenetic habitat shifts to deeper water.

Age, growth and population structure of invasive lionfish (Pterois volitans/miles) in northeast Florida using a length-based, age-structured population model

PubMed Central

2016-01-01

The effective management of invasive species requires detailed understanding of the invader’s life history. This information is essential for modeling population growth and predicting rates of expansion, quantifying ecological impacts and assessing the efficacy of removal and control strategies. Indo-Pacific lionfish (Pterois volitans/miles) have rapidly invaded the western Atlantic, Gulf of Mexico and Caribbean Sea with documented negative impacts on native ecosystems. To better understand the life history of this species, we developed and validated a length-based, age-structured model to investigate age, growth and population structure in northeast Florida. The main findings of this study were: (1) lionfish exhibited rapid growth with seasonal variation in growth rates; (2) distinct cohorts were clearly identifiable in the length-frequency data, suggesting that lionfish are recruiting during a relatively short period in summer; and (3) the majority of lionfish were less than two years old with no lionfish older than three years of age, which may be the result of culling efforts as well as ontogenetic habitat shifts to deeper water. PMID:27920953

Simulating crop growth with Expert-N-GECROS under different site conditions in Southwest Germany

NASA Astrophysics Data System (ADS)

Poyda, Arne; Ingwersen, Joachim; Demyan, Scott; Gayler, Sebastian; Streck, Thilo

2016-04-01

When feedbacks between the land surface and the atmosphere are investigated by Atmosphere-Land surface-Crop-Models (ALCM) it is fundamental to accurately simulate crop growth dynamics as plants directly influence the energy partitioning at the plant-atmosphere interface. To study both the response and the effect of intensive agricultural crop production systems on regional climate change in Southwest Germany, the crop growth model GECROS (YIN & VAN LAAR, 2005) was calibrated based on multi-year field data from typical crop rotations in the Kraichgau and Swabian Alb regions. Additionally, the SOC (soil organic carbon) model DAISY (MÜLLER et al., 1998) was implemented in the Expert-N model tool (ENGEL & PRIESACK, 1993) and combined with GECROS. The model was calibrated based on a set of plant (BBCH, LAI, plant height, aboveground biomass, N content of biomass) and weather data for the years 2010 - 2013 and validated with the data of 2014. As GECROS adjusts the root-shoot partitioning in response to external conditions (water, nitrogen, CO2), it is suitable to simulate crop growth dynamics under changing climate conditions and potentially more frequent stress situations. As C and N pools and turnover rates in soil as well as preceding crop effects were expected to considerably influence crop growth, the model was run in a multi-year, dynamic way. Crop residues and soil mineral N (nitrate, ammonium) available for the subsequent crop were accounted for. The model simulates growth dynamics of winter wheat, winter rape, silage maize and summer barley at the Kraichgau and Swabian Alb sites well. The Expert-N-GECROS model is currently parameterized for crops with potentially increasing shares in future crop rotations. First results will be shown.

Modelling Root Systems Using Oriented Density Distributions

NASA Astrophysics Data System (ADS)

Dupuy, Lionel X.

2011-09-01

Root architectural models are essential tools to understand how plants access and utilize soil resources during their development. However, root architectural models use complex geometrical descriptions of the root system and this has limitations to model interactions with the soil. This paper presents the development of continuous models based on the concept of oriented density distribution function. The growth of the root system is built as a hierarchical system of partial differential equations (PDEs) that incorporate single root growth parameters such as elongation rate, gravitropism and branching rate which appear explicitly as coefficients of the PDE. Acquisition and transport of nutrients are then modelled by extending Darcy's law to oriented density distribution functions. This framework was applied to build a model of the growth and water uptake of barley root system. This study shows that simplified and computer effective continuous models of the root system development can be constructed. Such models will allow application of root growth models at field scale.

"Peer Review: Nonroad (NR) Updates to Population Growth, Compression Ignition (CI) Criteria, Toxic Emission Factors and Speciation Profiles"

EPA Science Inventory

This report focuses on the methodology for estimating growth in NR engine populations as used in the MOVES201X-NONROAD emission inventory model. MOVES NR growth rates start with base year engine populations and estimate growth in the populations of NR engines, while applying cons...

Computational modelling of the scaffold-free chondrocyte regeneration: a two-way coupling between the cell growth and local fluid flow and nutrient concentration.

PubMed

Hossain, Md Shakhawath; Bergstrom, D J; Chen, X B

2015-11-01

The in vitro chondrocyte cell culture process in a perfusion bioreactor provides enhanced nutrient supply as well as the flow-induced shear stress that may have a positive influence on the cell growth. Mathematical and computational modelling of such a culture process, by solving the coupled flow, mass transfer and cell growth equations simultaneously, can provide important insight into the biomechanical environment of a bioreactor and the related cell growth process. To do this, a two-way coupling between the local flow field and cell growth is required. Notably, most of the computational and mathematical models to date have not taken into account the influence of the cell growth on the local flow field and nutrient concentration. The present research aimed at developing a mathematical model and performing a numerical simulation using the lattice Boltzmann method to predict the chondrocyte cell growth without a scaffold on a flat plate placed inside a perfusion bioreactor. The model considers the two-way coupling between the cell growth and local flow field, and the simulation has been performed for 174 culture days. To incorporate the cell growth into the model, a control-volume-based surface growth modelling approach has been adopted. The simulation results show the variation of local fluid velocity, shear stress and concentration distribution during the culture period due to the growth of the cell phase and also illustrate that the shear stress can increase the cell volume fraction to a certain extent.

Accounting for inherent variability of growth in microbial risk assessment.

PubMed

Marks, H M; Coleman, M E

2005-04-15

Risk assessments of pathogens need to account for the growth of small number of cells under varying conditions. In order to determine the possible risks that occur when there are small numbers of cells, stochastic models of growth are needed that would capture the distribution of the number of cells over replicate trials of the same scenario or environmental conditions. This paper provides a simple stochastic growth model, accounting only for inherent cell-growth variability, assuming constant growth kinetic parameters, for an initial, small, numbers of cells assumed to be transforming from a stationary to an exponential phase. Two, basic, microbial sets of assumptions are considered: serial, where it is assume that cells transform through a lag phase before entering the exponential phase of growth; and parallel, where it is assumed that lag and exponential phases develop in parallel. The model is based on, first determining the distribution of the time when growth commences, and then modelling the conditional distribution of the number of cells. For the latter distribution, it is found that a Weibull distribution provides a simple approximation to the conditional distribution of the relative growth, so that the model developed in this paper can be easily implemented in risk assessments using commercial software packages.

Importance of the habitat choice behavior assumed when modeling the effects of food and temperature on fish populations

USGS Publications Warehouse

Wildhaber, Mark L.; Lamberson, Peter J.

2004-01-01

Various mechanisms of habitat choice in fishes based on food and/or temperature have been proposed: optimal foraging for food alone; behavioral thermoregulation for temperature alone; and behavioral energetics and discounted matching for food and temperature combined. Along with development of habitat choice mechanisms, there has been a major push to develop and apply to fish populations individual-based models that incorporate various forms of these mechanisms. However, it is not known how the wide variation in observed and hypothesized mechanisms of fish habitat choice could alter fish population predictions (e.g. growth, size distributions, etc.). We used spatially explicit, individual-based modeling to compare predicted fish populations using different submodels of patch choice behavior under various food and temperature distributions. We compared predicted growth, temperature experience, food consumption, and final spatial distribution using the different models. Our results demonstrated that the habitat choice mechanism assumed in fish population modeling simulations was critical to predictions of fish distribution and growth rates. Hence, resource managers who use modeling results to predict fish population trends should be very aware of and understand the underlying patch choice mechanisms used in their models to assure that those mechanisms correctly represent the fish populations being modeled.

How TK-TD and population models for aquatic macrophytes could support the risk assessment for plant protection products.

PubMed

Hommen, Udo; Schmitt, Walter; Heine, Simon; Brock, Theo Cm; Duquesne, Sabine; Manson, Phil; Meregalli, Giovanna; Ochoa-Acuña, Hugo; van Vliet, Peter; Arts, Gertie

2016-01-01

This case study of the Society of Environmental Toxicology and Chemistry (SETAC) workshop MODELINK demonstrates the potential use of mechanistic effects models for macrophytes to extrapolate from effects of a plant protection product observed in laboratory tests to effects resulting from dynamic exposure on macrophyte populations in edge-of-field water bodies. A standard European Union (EU) risk assessment for an example herbicide based on macrophyte laboratory tests indicated risks for several exposure scenarios. Three of these scenarios are further analyzed using effect models for 2 aquatic macrophytes, the free-floating standard test species Lemna sp., and the sediment-rooted submerged additional standard test species Myriophyllum spicatum. Both models include a toxicokinetic (TK) part, describing uptake and elimination of the toxicant, a toxicodynamic (TD) part, describing the internal concentration-response function for growth inhibition, and a description of biomass growth as a function of environmental factors to allow simulating seasonal dynamics. The TK-TD models are calibrated and tested using laboratory tests, whereas the growth models were assumed to be fit for purpose based on comparisons of predictions with typical growth patterns observed in the field. For the risk assessment, biomass dynamics are predicted for the control situation and for several exposure levels. Based on specific protection goals for macrophytes, preliminary example decision criteria are suggested for evaluating the model outputs. The models refined the risk indicated by lower tier testing for 2 exposure scenarios, while confirming the risk associated for the third. Uncertainties related to the experimental and the modeling approaches and their application in the risk assessment are discussed. Based on this case study and the assumption that the models prove suitable for risk assessment once fully evaluated, we recommend that 1) ecological scenarios be developed that are also linked to the exposure scenarios, and 2) quantitative protection goals be set to facilitate the interpretation of model results for risk assessment. © 2015 SETAC.

Development of a coupled model of a distributed hydrological model and a rice growth model for optimizing irrigation schedule

NASA Astrophysics Data System (ADS)

Tsujimoto, Kumiko; Homma, Koki; Koike, Toshio; Ohta, Tetsu

2013-04-01

A coupled model of a distributed hydrological model and a rice growth model was developed in this study. The distributed hydrological model used in this study is the Water and Energy Budget-based Distributed Hydrological Model (WEB-DHM) developed by Wang et al. (2009). This model includes a modified SiB2 (Simple Biosphere Model, Sellers et al., 1996) and the Geomorphology-Based Hydrological Model (GBHM) and thus it can physically calculate both water and energy fluxes. The rice growth model used in this study is the Simulation Model for Rice-Weather relations (SIMRIW) - rainfed developed by Homma et al. (2009). This is an updated version of the original SIMRIW (Horie et al., 1987) and can calculate rice growth by considering the yield reduction due to water stress. The purpose of the coupling is the integration of hydrology and crop science to develop a tool to support decision making 1) for determining the necessary agricultural water resources and 2) for allocating limited water resources to various sectors. The efficient water use and optimal water allocation in the agricultural sector are necessary to balance supply and demand of limited water resources. In addition, variations in available soil moisture are the main reasons of variations in rice yield. In our model, soil moisture and the Leaf Area Index (LAI) are calculated inside SIMRIW-rainfed so that these variables can be simulated dynamically and more precisely based on the rice than the more general calculations is the original WEB-DHM. At the same time by coupling SIMRIW-rainfed with WEB-DHM, lateral flow of soil water, increases in soil moisture and reduction of river discharge due to the irrigation, and its effects on the rice growth can be calculated. Agricultural information such as planting date, rice cultivar, fertilization amount are given in a fully distributed manner. The coupled model was validated using LAI and soil moisture in a small basin in western Cambodia (Sangker River Basin). This basin is mostly rainfed paddy so that irrigation scheme was firstly switched off. Several simulations with varying irrigation scheme were performed to determine the optimal irrigation schedule in this basin.

A Physiologically Based Kinetic Model of Rat and Mouse Gestation: Disposition of a Weak Acid

EPA Science Inventory

A physiologically based toxicokinetic model of gestation in the rat mouse has been developed. The model is superimposed on the normal growth curve for nonpregnant females. It describes the entire gestation period including organogenesis. The model consists of uterus, mammary tiss...

A functional–structural model for radiata pine (Pinus radiata) focusing on tree architecture and wood quality

PubMed Central

Fernández, M. Paulina; Norero, Aldo; Vera, Jorge R.; Pérez, Eduardo

2011-01-01

Backgrounds and Aims Functional–structural models are interesting tools to relate environmental and management conditions with forest growth. Their three-dimensional images can reveal important characteristics of wood used for industrial products. Like virtual laboratories, they can be used to evaluate relationships among species, sites and management, and to support silvicultural design and decision processes. Our aim was to develop a functional–structural model for radiata pine (Pinus radiata) given its economic importance in many countries. Methods The plant model uses the L-system language. The structure of the model is based on operational units, which obey particular rules, and execute photosynthesis, respiration and morphogenesis, according to their particular characteristics. Plant allometry is adhered to so that harmonic growth and plant development are achieved. Environmental signals for morphogenesis are used. Dynamic turnover guides the normal evolution of the tree. Monthly steps allow for detailed information of wood characteristics. The model is independent of traditional forest inventory relationships and is conceived as a mechanistic model. For model parameterization, three databases which generated new information relating to P. radiata were analysed and incorporated. Key Results Simulations under different and contrasting environmental and management conditions were run and statistically tested. The model was validated against forest inventory data for the same sites and times and against true crown architectural data. The performance of the model for 6-year-old trees was encouraging. Total height, diameter and lengths of growth units were adequately estimated. Branch diameters were slightly overestimated. Wood density values were not satisfactory, but the cyclical pattern and increase of growth rings were reasonably well modelled. Conclusions The model was able to reproduce the development and growth of the species based on mechanistic formulations. It may be valuable in assessing stand behaviour under different environmental and management conditions, assisting in decision-making with regard to management, and as a research tool to formulate hypothesis regarding forest tree growth and development. PMID:21987452

Development of input data layers for the FARSITE fire growth model for the Selway-Bitterroot Wilderness Complex, USA

Treesearch

Robert E. Keane; Janice L. Garner; Kirsten M. Schmidt; Donald G. Long; James P. Menakis; Mark A. Finney

1998-01-01

Fuel and vegetation spatial data layers required by the spatially explicit fire growth model FARSITE were developed for all lands in and around the Selway-Bitterroot Wilderness Area in Idaho and Montana. Satellite imagery and terrain modeling were used to create the three base vegetation spatial data layers of potential vegetation, cover type, and structural stage....

Cybernetic modeling based on pathway analysis for Penicillium chrysogenum fed-batch fermentation.

PubMed

Geng, Jun; Yuan, Jingqi

2010-08-01

A macrokinetic model employing cybernetic methodology is proposed to describe mycelium growth and penicillin production. Based on the primordial and complete metabolic network of Penicillium chrysogenum found in the literature, the modeling procedure is guided by metabolic flux analysis and cybernetic modeling framework. The abstracted cybernetic model describes the transients of the consumption rates of the substrates, the assimilation rates of intermediates, the biomass growth rate, as well as the penicillin formation rate. Combined with the bioreactor model, these reaction rates are linked with the most important state variables, i.e., mycelium, substrate and product concentrations. Simplex method is used to estimate the sensitive parameters of the model. Finally, validation of the model is carried out with 20 batches of industrial-scale penicillin cultivation.

Optimization of space system development resources

NASA Astrophysics Data System (ADS)

Kosmann, William J.; Sarkani, Shahram; Mazzuchi, Thomas

2013-06-01

NASA has had a decades-long problem with cost growth during the development of space science missions. Numerous agency-sponsored studies have produced average mission level cost growths ranging from 23% to 77%. A new study of 26 historical NASA Science instrument set developments using expert judgment to reallocate key development resources has an average cost growth of 73.77%. Twice in history, a barter-based mechanism has been used to reallocate key development resources during instrument development. The mean instrument set development cost growth was -1.55%. Performing a bivariate inference on the means of these two distributions, there is statistical evidence to support the claim that using a barter-based mechanism to reallocate key instrument development resources will result in a lower expected cost growth than using the expert judgment approach. Agent-based discrete event simulation is the natural way to model a trade environment. A NetLogo agent-based barter-based simulation of science instrument development was created. The agent-based model was validated against the Cassini historical example, as the starting and ending instrument development conditions are available. The resulting validated agent-based barter-based science instrument resource reallocation simulation was used to perform 300 instrument development simulations, using barter to reallocate development resources. The mean cost growth was -3.365%. A bivariate inference on the means was performed to determine that additional significant statistical evidence exists to support a claim that using barter-based resource reallocation will result in lower expected cost growth, with respect to the historical expert judgment approach. Barter-based key development resource reallocation should work on spacecraft development as well as it has worked on instrument development. A new study of 28 historical NASA science spacecraft developments has an average cost growth of 46.04%. As barter-based key development resource reallocation has never been tried in a spacecraft development, no historical results exist, and a simulation of using that approach must be developed. The instrument development simulation should be modified to account for spacecraft development market participant differences. The resulting agent-based barter-based spacecraft resource reallocation simulation would then be used to determine if significant statistical evidence exists to prove a claim that using barter-based resource reallocation will result in lower expected cost growth.

Evolution of solidification texture during additive manufacturing.

PubMed

Wei, H L; Mazumder, J; DebRoy, T

2015-11-10

Striking differences in the solidification textures of a nickel based alloy owing to changes in laser scanning pattern during additive manufacturing are examined based on theory and experimental data. Understanding and controlling texture are important because it affects mechanical and chemical properties. Solidification texture depends on the local heat flow directions and competitive grain growth in one of the six <100> preferred growth directions in face centered cubic alloys. Therefore, the heat flow directions are examined for various laser beam scanning patterns based on numerical modeling of heat transfer and fluid flow in three dimensions. Here we show that numerical modeling can not only provide a deeper understanding of the solidification growth patterns during the additive manufacturing, it also serves as a basis for customizing solidification textures which are important for properties and performance of components.

Multiaxial Fatigue Life Prediction Based on Short Crack Propagation Model with Equivalent Strain Parameter

NASA Astrophysics Data System (ADS)

Zhao, Xiang-Feng; Shang, De-Guang; Sun, Yu-Juan; Song, Ming-Liang; Wang, Xiao-Wei

2018-01-01

The maximum shear strain and the normal strain excursion on the critical plane are regarded as the primary parameters of the crack driving force to establish a new short crack model in this paper. An equivalent strain-based intensity factor is proposed to correlate the short crack growth rate under multiaxial loading. According to the short crack model, a new method is proposed for multiaxial fatigue life prediction based on crack growth analysis. It is demonstrated that the method can be used under proportional and non-proportional loadings. The predicted results showed a good agreement with experimental lives in both high-cycle and low-cycle regions.

Spatiotemporal variability of urban growth factors: A global and local perspective on the megacity of Mumbai

NASA Astrophysics Data System (ADS)

Shafizadeh-Moghadam, Hossein; Helbich, Marco

2015-03-01

The rapid growth of megacities requires special attention among urban planners worldwide, and particularly in Mumbai, India, where growth is very pronounced. To cope with the planning challenges this will bring, developing a retrospective understanding of urban land-use dynamics and the underlying driving-forces behind urban growth is a key prerequisite. This research uses regression-based land-use change models - and in particular non-spatial logistic regression models (LR) and auto-logistic regression models (ALR) - for the Mumbai region over the period 1973-2010, in order to determine the drivers behind spatiotemporal urban expansion. Both global models are complemented by a local, spatial model, the so-called geographically weighted logistic regression (GWLR) model, one that explicitly permits variations in driving-forces across space. The study comes to two main conclusions. First, both global models suggest similar driving-forces behind urban growth over time, revealing that LRs and ALRs result in estimated coefficients with comparable magnitudes. Second, all the local coefficients show distinctive temporal and spatial variations. It is therefore concluded that GWLR aids our understanding of urban growth processes, and so can assist context-related planning and policymaking activities when seeking to secure a sustainable urban future.

General Training System; GENTRAS. Final Report.

ERIC Educational Resources Information Center

International Business Machines Corp., Gaithersburg, MD. Federal Systems Div.

GENTRAS (General Training System) is a computer-based training model for the Marine Corps which makes use of a systems approach. The model defines the skill levels applicable for career growth and classifies and defines the training needed for this growth. It also provides a training cost subsystem which will provide a more efficient means of…

Growth Models and Teacher Evaluation: What Teachers Need to Know and Do

ERIC Educational Resources Information Center

Katz, Daniel S.

2016-01-01

Including growth models based on student test scores in teacher evaluations effectively holds teachers individually accountable for students improving their test scores. While an attractive policy for state administrators and advocates of education reform, value-added measures have been fraught with problems, and their use in teacher evaluation is…

Assimilation of active and passive microwave observations for improved estimates of soil moisture and crop growth

USDA-ARS?s Scientific Manuscript database

An Ensemble Kalman Filter-based data assimilation framework that links a crop growth model with active and passive (AP) microwave models was developed to improve estimates of soil moisture (SM) and vegetation biomass over a growing season of soybean. Complementarities in AP observations were incorpo...

Defense Spending and Regional Growth: An Examination of an Export-Base Model and an Econometric Model.

DTIC Science & Technology

1987-06-01

consumer preferences provide influences that can stimulate the rate of growth of the endogenous and/or exogenous income industries. B. EXPORT INDUSTRIES...location quotient was selected to alleviate 12 some of the problems created by consumer preferences and expendi- ture patterns. This value was compared

A likelihood-based time series modeling approach for application in dendrochronology to examine the growth-climate relations and forest disturbance history

EPA Science Inventory

A time series intervention analysis (TSIA) of dendrochronological data to infer the tree growth-climate-disturbance relations and forest disturbance history is described. Maximum likelihood is used to estimate the parameters of a structural time series model with components for ...

Building Context with Tumor Growth Modeling Projects in Differential Equations

ERIC Educational Resources Information Center

Beier, Julie C.; Gevertz, Jana L.; Howard, Keith E.

2015-01-01

The use of modeling projects serves to integrate, reinforce, and extend student knowledge. Here we present two projects related to tumor growth appropriate for a first course in differential equations. They illustrate the use of problem-based learning to reinforce and extend course content via a writing or research experience. Here we discuss…

A Model Based on Environmental Factors for Diameter Distribution in Black Wattle in Brazil

PubMed Central

Sanquetta, Carlos Roberto; Behling, Alexandre; Dalla Corte, Ana Paula; Péllico Netto, Sylvio; Rodrigues, Aurelio Lourenço; Simon, Augusto Arlindo

2014-01-01

This article discusses the dynamics of a diameter distribution in stands of black wattle throughout its growth cycle using the Weibull probability density function. Moreover, the parameters of this distribution were related to environmental variables from meteorological data and surface soil horizon with the aim of finding a model for diameter distribution which their coefficients were related to the environmental variables. We found that the diameter distribution of the stand changes only slightly over time and that the estimators of the Weibull function are correlated with various environmental variables, with accumulated rainfall foremost among them. Thus, a model was obtained in which the estimators of the Weibull function are dependent on rainfall. Such a function can have important applications, such as in simulating growth potential in regions where historical growth data is lacking, as well as the behavior of the stand under different environmental conditions. The model can also be used to project growth in diameter, based on the rainfall affecting the forest over a certain time period. PMID:24932909

Modelling and Optimization of Nannochloropsis and Chlorella Growth for Various Locations and Seasons

NASA Astrophysics Data System (ADS)

Gharagozloo, P. E.

2014-12-01

Efficient production of algal biofuels could reduce dependence on foreign oil providing domestic renewable energy. Algae-based biofuels are attractive for their large oil yield potential despite decreased land use and natural-resource requirements compared to terrestrial energy crops. Important factors controlling algal-lipid productivity include temperature, nutrient availability, salinity, pH, and the light-to-biomass conversion rate. Computational approaches allow for inexpensive predictions of algae-growth kinetics for various bioreactor sizes and geometries without multiple, expensive measurement systems. In this work, we parameterize our physics-based computational algae growth model for the marine Nannochloropsis oceanica and freshwater Chlorella species. We then compare modelling results with experiments conducted in identical raceway ponds at six geographical locations in the United States (Hawaii, California, Arizona, Ohio, Georgia, and Florida) and three seasons through the Algae Testbed Public Private Partnership - Unified Field Studies. Results show that the computational model effectively predicts algae growth in systems across varying environments and identifies the causes for reductions in algal productivities. The model is then used to identify improvements to the cultivation system to produce higher biomass yields. This model could be used to study the effects of scale-up including the effects of predation, depth-decay of light (light extinction), and optimized nutrient and CO2 delivery. As more multifactorial data are accumulated for a variety of algal strains, the model could be used to select appropriate algal species for various geographic and climatic locations and seasons. Applying the model facilitates optimization of pond designs based on location and season.

Controlling Microbial Byproducts using Model-Based Substrate Monitoring and Control Strategies

NASA Technical Reports Server (NTRS)

Smernoff, David T.; Blackwell, Charles; Mancinelli, Rocco L.; DeVincenzi, Donald (Technical Monitor)

2000-01-01

We have developed a computer-controlled bioreactor system to study various aspects of microbially-mediated nitrogen cycling. The system has been used to investigate methods for controlling microbial denitrification (the dissimilatory reduction of nitrate to N2O and N2) in hydroponic plant growth chambers. Such chambers are key elements of advanced life support systems being designed for use on long duration space missions, but nitrogen use efficiency in them is reduced by denitrification. Control software architecture was designed which permits the heterogeneous control of system hardware using traditional feedback control, and quantitative and qualitative models of various system features. Model-based feed forward control entails prediction of future systems in states and automated regulation of system parameters to achieve desired and avoid undesirable system states. A bacterial growth rate model based on the classic Monod model of saturation kinetics was used to evaluate the response of several individual denitrifying species to varying environmental conditions. The system and models are now being applied to mixed microbial communities harvested from the root zone of a hydroponic growth chamber. The use of a modified Monod organism interaction model was evaluated as a means of achieving more accurate description of the dynamic behavior of the communities. A minimum variance parameter estimation routine was also' used to calibrate the constant parameters in the model by iterative evaluation of substrate (nitrate) uptake and growth kinetics. This representation of processes and interactions aids in the formulation of control laws. The feed forward control strategy being developed will increase system autonomy, reduce crew intervention and limit the accumulation of undesirable waste products (NOx).

Modeling of Austenite Grain Growth During Austenitization in a Low Alloy Steel

NASA Astrophysics Data System (ADS)

Dong, Dingqian; Chen, Fei; Cui, Zhenshan

2016-01-01

The main purpose of this work is to develop a pragmatic model to predict austenite grain growth in a nuclear reactor pressure vessel steel. Austenite grain growth kinetics has been investigated under different heating conditions, involving heating temperature, holding time, as well as heating rate. Based on the experimental results, the mathematical model was established by regression analysis. The model predictions present a good agreement with the experimental data. Meanwhile, grain boundary precipitates and pinning effects on grain growth were studied by transmission electron microscopy. It is found that with the increasing of the temperature, the second-phase particles tend to be dissolved and the pinning effects become smaller, which results in a rapid growth of certain large grains with favorable orientation. The results from this study provide the basis for the establishment of large-sized ingot heating specification for SA508-III steel.

Development of the vertical Bridgman technique for 6-inch diameter c-axis sapphire growth supported by numerical simulation

NASA Astrophysics Data System (ADS)

Miyagawa, Chihiro; Kobayashi, Takumi; Taishi, Toshinori; Hoshikawa, Keigo

2014-09-01

Based on the growth of 3-inch diameter c-axis sapphire using the vertical Bridgman (VB) technique, numerical simulations were made and used to guide the growth of a 6-inch diameter sapphire. A 2D model of the VB hot-zone was constructed, the seeding interface shape of the 3-inch diameter sapphire as revealed by green laser scattering was estimated numerically, and the temperature distributions of two VB hot-zone models designed for 6-inch diameter sapphire growth were numerically simulated to achieve the optimal growth of large crystals. The hot-zone model with one heater was selected and prepared, and 6-inch diameter c-axis sapphire boules were actually grown, as predicted by the numerical results.

GROWTH AND INEQUALITY: MODEL EVALUATION BASED ON AN ESTIMATION-CALIBRATION STRATEGY

PubMed Central

Jeong, Hyeok; Townsend, Robert

2010-01-01

This paper evaluates two well-known models of growth with inequality that have explicit micro underpinnings related to household choice. With incomplete markets or transactions costs, wealth can constrain investment in business and the choice of occupation and also constrain the timing of entry into the formal financial sector. Using the Thai Socio-Economic Survey (SES), we estimate the distribution of wealth and the key parameters that best fit cross-sectional data on household choices and wealth. We then simulate the model economies for two decades at the estimated initial wealth distribution and analyze whether the model economies at those micro-fit parameter estimates can explain the observed macro and sectoral aspects of income growth and inequality change. Both models capture important features of Thai reality. Anomalies and comparisons across the two distinct models yield specific suggestions for improved research on the micro foundations of growth and inequality. PMID:20448833

Leuconostoc mesenteroides growth in food products: prediction and sensitivity analysis by adaptive-network-based fuzzy inference systems.

PubMed

Wang, Hue-Yu; Wen, Ching-Feng; Chiu, Yu-Hsien; Lee, I-Nong; Kao, Hao-Yun; Lee, I-Chen; Ho, Wen-Hsien

2013-01-01

An adaptive-network-based fuzzy inference system (ANFIS) was compared with an artificial neural network (ANN) in terms of accuracy in predicting the combined effects of temperature (10.5 to 24.5°C), pH level (5.5 to 7.5), sodium chloride level (0.25% to 6.25%) and sodium nitrite level (0 to 200 ppm) on the growth rate of Leuconostoc mesenteroides under aerobic and anaerobic conditions. THE ANFIS AND ANN MODELS WERE COMPARED IN TERMS OF SIX STATISTICAL INDICES CALCULATED BY COMPARING THEIR PREDICTION RESULTS WITH ACTUAL DATA: mean absolute percentage error (MAPE), root mean square error (RMSE), standard error of prediction percentage (SEP), bias factor (Bf), accuracy factor (Af), and absolute fraction of variance (R (2)). Graphical plots were also used for model comparison. The learning-based systems obtained encouraging prediction results. Sensitivity analyses of the four environmental factors showed that temperature and, to a lesser extent, NaCl had the most influence on accuracy in predicting the growth rate of Leuconostoc mesenteroides under aerobic and anaerobic conditions. The observed effectiveness of ANFIS for modeling microbial kinetic parameters confirms its potential use as a supplemental tool in predictive mycology. Comparisons between growth rates predicted by ANFIS and actual experimental data also confirmed the high accuracy of the Gaussian membership function in ANFIS. Comparisons of the six statistical indices under both aerobic and anaerobic conditions also showed that the ANFIS model was better than all ANN models in predicting the four kinetic parameters. Therefore, the ANFIS model is a valuable tool for quickly predicting the growth rate of Leuconostoc mesenteroides under aerobic and anaerobic conditions.

Leuconostoc Mesenteroides Growth in Food Products: Prediction and Sensitivity Analysis by Adaptive-Network-Based Fuzzy Inference Systems

PubMed Central

Wang, Hue-Yu; Wen, Ching-Feng; Chiu, Yu-Hsien; Lee, I-Nong; Kao, Hao-Yun; Lee, I-Chen; Ho, Wen-Hsien

2013-01-01

Background An adaptive-network-based fuzzy inference system (ANFIS) was compared with an artificial neural network (ANN) in terms of accuracy in predicting the combined effects of temperature (10.5 to 24.5°C), pH level (5.5 to 7.5), sodium chloride level (0.25% to 6.25%) and sodium nitrite level (0 to 200 ppm) on the growth rate of Leuconostoc mesenteroides under aerobic and anaerobic conditions. Methods The ANFIS and ANN models were compared in terms of six statistical indices calculated by comparing their prediction results with actual data: mean absolute percentage error (MAPE), root mean square error (RMSE), standard error of prediction percentage (SEP), bias factor (Bf), accuracy factor (Af), and absolute fraction of variance (R 2). Graphical plots were also used for model comparison. Conclusions The learning-based systems obtained encouraging prediction results. Sensitivity analyses of the four environmental factors showed that temperature and, to a lesser extent, NaCl had the most influence on accuracy in predicting the growth rate of Leuconostoc mesenteroides under aerobic and anaerobic conditions. The observed effectiveness of ANFIS for modeling microbial kinetic parameters confirms its potential use as a supplemental tool in predictive mycology. Comparisons between growth rates predicted by ANFIS and actual experimental data also confirmed the high accuracy of the Gaussian membership function in ANFIS. Comparisons of the six statistical indices under both aerobic and anaerobic conditions also showed that the ANFIS model was better than all ANN models in predicting the four kinetic parameters. Therefore, the ANFIS model is a valuable tool for quickly predicting the growth rate of Leuconostoc mesenteroides under aerobic and anaerobic conditions. PMID:23705023

Predictive Model for Growth of Staphylococcus aureus on Raw Pork, Ham, and Sausage.

PubMed

Mansur, Ahmad Rois; Park, Joong-Hyun; Oh, Deog-Hwan

2016-01-01

Recent Staphylococcus aureus outbreaks linked to meat and poultry products underscore the importance of understanding the growth kinetics of S. aureus in these products at different temperatures. Raw pork, ham, and sausage (each 10 ± 0.3 g) were inoculated with a three-strain cocktail of S. aureus, resulting in an initial level of ca. 3 log CFU/g. Samples were stored isothermally at 10, 15, 20, 25, 30, 35, and 40°C, and S. aureus was enumerated at appropriate time intervals. The square root model was developed using experimental data collected from S. aureus grown on all samples (where data from raw pork, ham, and sausage were combined) so as to describe the growth rate of S. aureus as a function of temperature. The model was then compared with models for S. aureus growth on each individual sample in the experiments (raw pork, ham, or sausage) and the S. aureus ComBase models, as well as models for the growth of different types of pathogens (S. aureus, Escherichia coli O157:H7, Clostridium perfringens, Salmonella serovars, and Salmonella Typhimurium) on various types of meat and poultry products. The results show that the S. aureus model developed here based on the pooled data from all three pork products seems suitable for the prediction of S. aureus growth on different pork products under isothermal conditions from 10 to 25°C, as well as for S. aureus growth on different meat and poultry products at higher temperatures between 20 and 35°C. Regardless of some high deviations observed at temperatures between 25 and 40°C, the developed model still seems suitable to predict the growth of other pathogens on different types of meat and poultry products over the temperature ranges used here, especially for E. coli O157:H7 and Salmonella Typhimurium. The developed model, therefore, may be useful for estimating the effects of storage temperature on the behavior of pathogens in different meat and poultry products and for microbial risk assessments evaluating meat safety.

Microstructure-Based Fatigue Life Prediction Methods for Naval Steel Structures

DTIC Science & Technology

1993-01-30

approach is to work with the lognormal random variable model proposed by Yang et al . [2], which avoids these difficulties. The simplest form of the...I Al - I I 11. and Ti-alloys [ 10- 111 correlate with the elastic modulus only in the continuum growth regime. On the other hand. compilation of...growth. In fact, Eq. (5) implies that microstructure plays no role in the continuum growth regime. Theoretical models of Frost, et al . [35], and

A single strain-based growth law predicts concentric and eccentric cardiac growth during pressure and volume overload

PubMed Central

Kerckhoffs, Roy C.P.; Omens, Jeffrey; McCulloch, Andrew D.

2011-01-01

Adult cardiac muscle adapts to mechanical changes in the environment by growth and remodeling (G&R) via a variety of mechanisms. Hypertrophy develops when the heart is subjected to chronic mechanical overload. In ventricular pressure overload (e.g. due to aortic stenosis) the heart typically reacts by concentric hypertrophic growth, characterized by wall thickening due to myocyte radial growth when sarcomeres are added in parallel. In ventricular volume overload, an increase in filling pressure (e.g. due to mitral regurgitation) leads to eccentric hypertrophy as myocytes grow axially by adding sarcomeres in series leading to ventricular cavity enlargement that is typically accompanied by some wall thickening. The specific biomechanical stimuli that stimulate different modes of ventricular hypertrophy are still poorly understood. In a recent study, based on in-vitro studies in micropatterned myocyte cell cultures subjected to stretch, we proposed that cardiac myocytes grow longer to maintain a preferred sarcomere length in response to increased fiber strain and grow thicker to maintain interfilament lattice spacing in response to increased cross-fiber strain. Here, we test whether this growth law is able to predict concentric and eccentric hypertrophy in response to aortic stenosis and mitral valve regurgitation, respectively, in a computational model of the adult canine heart coupled to a closed loop model of circulatory hemodynamics. A non-linear finite element model of the beating canine ventricles coupled to the circulation was used. After inducing valve alterations, the ventricles were allowed to adapt in shape in response to mechanical stimuli over time. The proposed growth law was able to reproduce major acute and chronic physiological responses (structural and functional) when integrated with comprehensive models of the pressure-overloaded and volume-overloaded canine heart, coupled to a closed-loop circulation. We conclude that strain-based biomechanical stimuli can drive cardiac growth, including wall thickening during pressure overload. PMID:22639476

A methodology to predict damage initiation, damage growth and residual strength in titanium matrix composites

NASA Technical Reports Server (NTRS)

Bakuckas, J. G., Jr.; Johnson, W. S.

1994-01-01

In this research, a methodology to predict damage initiation, damage growth, fatigue life, and residual strength in titanium matrix composites (TMC) is outlined. Emphasis was placed on micromechanics-based engineering approaches. Damage initiation was predicted using a local effective strain approach. A finite element analysis verified the prevailing assumptions made in the formulation of this model. Damage growth, namely, fiber-bridged matrix crack growth, was evaluated using a fiber bridging (FB) model which accounts for thermal residual stresses. This model combines continuum fracture mechanics and micromechanics analyses yielding stress-intensity factor solutions for fiber-bridged matrix cracks. It is assumed in the FB model that fibers in the wake of the matrix crack are idealized as a closure pressure, and an unknown constant frictional shear stress is assumed to act along the debond length of the bridging fibers. This frictional shear stress was used as a curve fitting parameter to the available experimental data. Fatigue life and post-fatigue residual strength were predicted based on the axial stress in the first intact 0 degree fiber calculated using the FB model and a three-dimensional finite element analysis.

Early subtropical forest growth is driven by community mean trait values and functional diversity rather than the abiotic environment.

PubMed

Kröber, Wenzel; Li, Ying; Härdtle, Werner; Ma, Keping; Schmid, Bernhard; Schmidt, Karsten; Scholten, Thomas; Seidler, Gunnar; von Oheimb, Goddert; Welk, Erik; Wirth, Christian; Bruelheide, Helge

2015-09-01

While functional diversity (FD) has been shown to be positively related to a number of ecosystem functions including biomass production, it may have a much less pronounced effect than that of environmental factors or species-specific properties. Leaf and wood traits can be considered particularly relevant to tree growth, as they reflect a trade-off between resources invested into growth and persistence. Our study focussed on the degree to which early forest growth was driven by FD, the environment (11 variables characterizing abiotic habitat conditions), and community-weighted mean (CWM) values of species traits in the context of a large-scale tree diversity experiment (BEF-China). Growth rates of trees with respect to crown diameter were aggregated across 231 plots (hosting between one and 23 tree species) and related to environmental variables, FD, and CWM, the latter two of which were based on 41 plant functional traits. The effects of each of the three predictor groups were analyzed separately by mixed model optimization and jointly by variance partitioning. Numerous single traits predicted plot-level tree growth, both in the models based on CWMs and FD, but none of the environmental variables was able to predict tree growth. In the best models, environment and FD explained only 4 and 31% of variation in crown growth rates, respectively, while CWM trait values explained 42%. In total, the best models accounted for 51% of crown growth. The marginal role of the selected environmental variables was unexpected, given the high topographic heterogeneity and large size of the experiment, as was the significant impact of FD, demonstrating that positive diversity effects already occur during the early stages in tree plantations.

Early subtropical forest growth is driven by community mean trait values and functional diversity rather than the abiotic environment

PubMed Central

Kröber, Wenzel; Li, Ying; Härdtle, Werner; Ma, Keping; Schmid, Bernhard; Schmidt, Karsten; Scholten, Thomas; Seidler, Gunnar; von Oheimb, Goddert; Welk, Erik; Wirth, Christian; Bruelheide, Helge

2015-01-01

While functional diversity (FD) has been shown to be positively related to a number of ecosystem functions including biomass production, it may have a much less pronounced effect than that of environmental factors or species-specific properties. Leaf and wood traits can be considered particularly relevant to tree growth, as they reflect a trade-off between resources invested into growth and persistence. Our study focussed on the degree to which early forest growth was driven by FD, the environment (11 variables characterizing abiotic habitat conditions), and community-weighted mean (CWM) values of species traits in the context of a large-scale tree diversity experiment (BEF-China). Growth rates of trees with respect to crown diameter were aggregated across 231 plots (hosting between one and 23 tree species) and related to environmental variables, FD, and CWM, the latter two of which were based on 41 plant functional traits. The effects of each of the three predictor groups were analyzed separately by mixed model optimization and jointly by variance partitioning. Numerous single traits predicted plot-level tree growth, both in the models based on CWMs and FD, but none of the environmental variables was able to predict tree growth. In the best models, environment and FD explained only 4 and 31% of variation in crown growth rates, respectively, while CWM trait values explained 42%. In total, the best models accounted for 51% of crown growth. The marginal role of the selected environmental variables was unexpected, given the high topographic heterogeneity and large size of the experiment, as was the significant impact of FD, demonstrating that positive diversity effects already occur during the early stages in tree plantations. PMID:26380685

A comparison of three approaches for simulating fine-scale surface winds in support of wildland fire management. Part II. An exploratory study of the effect of simulated winds on fire growth simulations

Treesearch

Jason M. Forthofer; Bret W. Butler; Charles W. McHugh; Mark A. Finney; Larry S. Bradshaw; Richard D. Stratton; Kyle S. Shannon; Natalie S. Wagenbrenner

2014-01-01

The effect of fine-resolution wind simulations on fire growth simulations is explored. The wind models are (1) a wind field consisting of constant speed and direction applied everywhere over the area of interest; (2) a tool based on the solution of the conservation of mass only (termed mass-conserving model) and (3) a tool based on a solution of conservation of mass...

Methodology Developed for Modeling the Fatigue Crack Growth Behavior of Single-Crystal, Nickel-Base Superalloys

NASA Technical Reports Server (NTRS)

1996-01-01

Because of their superior high-temperature properties, gas generator turbine airfoils made of single-crystal, nickel-base superalloys are fast becoming the standard equipment on today's advanced, high-performance aerospace engines. The increased temperature capabilities of these airfoils has allowed for a significant increase in the operating temperatures in turbine sections, resulting in superior propulsion performance and greater efficiencies. However, the previously developed methodologies for life-prediction models are based on experience with polycrystalline alloys and may not be applicable to single-crystal alloys under certain operating conditions. One of the main areas where behavior differences between single-crystal and polycrystalline alloys are readily apparent is subcritical fatigue crack growth (FCG). The NASA Lewis Research Center's work in this area enables accurate prediction of the subcritical fatigue crack growth behavior in single-crystal, nickel-based superalloys at elevated temperatures.

Module-based multiscale simulation of angiogenesis in skeletal muscle

PubMed Central

2011-01-01

Background Mathematical modeling of angiogenesis has been gaining momentum as a means to shed new light on the biological complexity underlying blood vessel growth. A variety of computational models have been developed, each focusing on different aspects of the angiogenesis process and occurring at different biological scales, ranging from the molecular to the tissue levels. Integration of models at different scales is a challenging and currently unsolved problem. Results We present an object-oriented module-based computational integration strategy to build a multiscale model of angiogenesis that links currently available models. As an example case, we use this approach to integrate modules representing microvascular blood flow, oxygen transport, vascular endothelial growth factor transport and endothelial cell behavior (sensing, migration and proliferation). Modeling methodologies in these modules include algebraic equations, partial differential equations and agent-based models with complex logical rules. We apply this integrated model to simulate exercise-induced angiogenesis in skeletal muscle. The simulation results compare capillary growth patterns between different exercise conditions for a single bout of exercise. Results demonstrate how the computational infrastructure can effectively integrate multiple modules by coordinating their connectivity and data exchange. Model parameterization offers simulation flexibility and a platform for performing sensitivity analysis. Conclusions This systems biology strategy can be applied to larger scale integration of computational models of angiogenesis in skeletal muscle, or other complex processes in other tissues under physiological and pathological conditions. PMID:21463529

Modeling the Arrest of Tissue Growth in Epithelia

NASA Astrophysics Data System (ADS)

Golden, Alexander; Lubensky, David

The mechanisms of control and eventual arrest of growth of tissues is an area that has received considerable attention, both experimentally and in the development of quantitative models. In particular, the Drosophila wing disc epithelium appears to robustly arrive at a unique final size. One mechanism that has the potential to play a role in the eventual cessation of growth is mechanical feedback from stresses induced by nonuniform growth. There is experimental support for an effect on the tissue growth rate by such mechanical stresses, and a number of numerical or cell-based models have been proposed that show that the arrest of growth can be achieved by mechanical feedback. We introduce an analytic framework that allows us to understand different coarse-grained feedback mechanisms on the same terms. We use the framework to distinguish between families of models that do not have a unique final size and those that do and give rough estimates for how much variability in the eventual organ size can be expected in models that do not have a unique final size. NSF Grant DMR-1056456.

Improvement of specific growth rate of Pichia pastoris for effective porcine interferon-α production with an on-line model-based glycerol feeding strategy.

PubMed

Gao, Min-Jie; Zheng, Zhi-Yong; Wu, Jian-Rong; Dong, Shi-Juan; Li, Zhen; Jin, Hu; Zhan, Xiao-Bei; Lin, Chi-Chung

2012-02-01

Effective expression of porcine interferon-α (pIFN-α) with recombinant Pichia pastoris was conducted in a bench-scale fermentor. The influence of the glycerol feeding strategy on the specific growth rate and protein production was investigated. The traditional DO-stat feeding strategy led to very low cell growth rate resulting in low dry cell weight (DCW) of about 90 g/L during the subsequent induction phase. The previously reported Artificial Neural Network Pattern Recognition (ANNPR) model-based glycerol feeding strategy improved the cell density to 120 g DCW/L, while the specific growth rate decreased from 0.15 to 0.18 to 0.03-0.08 h(-1) during the last 10 h of the glycerol feeding stage leading to a variation of the porcine interferon-α production, as the glycerol feeding scheme had a significant effect on the induction phase. This problem was resolved by an improved ANNPR model-based feeding strategy to maintain the specific growth rate above 0.11 h(-1). With this feeding strategy, the pIFN-α concentration reached a level of 1.43 g/L, more than 1.5-fold higher than that obtained with the previously adopted feeding strategy. Our results showed that increasing the specific growth rate favored the target protein production and the glycerol feeding methods directly influenced the induction stage. Consequently, higher cell density and specific growth rate as well as effective porcine interferon-α production have been achieved by our novel glycerol feeding strategy.

[Construction of individual-based ecological model for Scomber japonicas at its early growth stages in East China Sea].

PubMed

Li, Yue-Song; Chen, Xin-Jun; Yang, Hong

2012-06-01

By adopting FVCOM-simulated 3-D physical field and based on the biological processes of chub mackerel (Scomber japonicas) in its early life history from the individual-based biological model, the individual-based ecological model for S. japonicas at its early growth stages in the East China Sea was constructed through coupling the physical field in March-July with the biological model by the method of Lagrange particle tracking. The model constructed could well simulate the transport process and abundance distribution of S. japonicas eggs and larvae. The Taiwan Warm Current, Kuroshio, and Tsushima Strait Warm Current directly affected the transport process and distribution of the eggs and larvae, and indirectly affected the growth and survive of the eggs and larvae through the transport to the nursery grounds with different water temperature and foods. The spawning grounds in southern East China Sea made more contributions to the recruitment to the fishing grounds in northeast East China Sea, but less to the Yangtze estuary and Zhoushan Island. The northwestern and southwestern parts of spawning grounds had strong connectivity with the nursery grounds of Cheju and Tsushima Straits, whereas the northeastern and southeastern parts of the spawning ground had strong connectivity with the nursery grounds of Kyushu and Pacific Ocean.

Numerical optimization of Ignition and Growth reactive flow modeling for PAX2A

NASA Astrophysics Data System (ADS)

Baker, E. L.; Schimel, B.; Grantham, W. J.

1996-05-01

Variable metric nonlinear optimization has been successfully applied to the parameterization of unreacted and reacted products thermodynamic equations of state and reactive flow modeling of the HMX based high explosive PAX2A. The NLQPEB nonlinear optimization program has been recently coupled to the LLNL developed two-dimensional high rate continuum modeling programs DYNA2D and CALE. The resulting program has the ability to optimize initial modeling parameters. This new optimization capability was used to optimally parameterize the Ignition and Growth reactive flow model to experimental manganin gauge records. The optimization varied the Ignition and Growth reaction rate model parameters in order to minimize the difference between the calculated pressure histories and the experimental pressure histories.

Exploring Reading Growth Profiles for Middle School Students with Significant Cognitive Disabilities

ERIC Educational Resources Information Center

Farley, Daniel Patrick

2017-01-01

Statewide accountability programs are incorporating academic growth estimates for general assessments. This transition focuses attention on modeling growth for students with significant cognitive disabilities (SWSCD) who take alternate assessments based on alternate achievement standards (AA-AAS), as most states attempt to structure their AA-AAS…

Transition between 'base' and 'tip' carbon nanofiber growth modes

NASA Astrophysics Data System (ADS)

Melechko, Anatoli V.; Merkulov, Vladimir I.; Lowndes, Douglas H.; Guillorn, Michael A.; Simpson, Michael L.

2002-04-01

Carbon nanofibers (CNFs) have been synthesized by catalytically controlled dc glow discharge plasma-enhanced chemical vapor deposition (PECVD). Both base-type and tip-type nanofibers have been produced on identical substrates. We have observed a sharp transition between these two growth modes by controlling the kinetics of the growth process without changing the substrate and catalyst materials. This transition is brought about by changing the parameters used in the deposition process such as the flow ratio of the carbonaceous and etchant gasses and others. This study of the initial growth stages as a function of time for both regimes provides a basis for a model of the growth mode transition.

The effect of growth temperature variation on partially bismuth filled carbon nanotubes synthesis using a soft semi-metallic template.

PubMed

Sahoo, R K; Jacob, C

2014-06-01

The dewetting of a low melting point metal thin film deposited on silicon substrates was studied. The experimental results suggest that the change in the growth temperature affects the nanostructures that form. Based on the experimental results, the temperature which yielded the smallest features for the growth of nanotubes is determined. The mechanism by which these nano-templates become an efficient seeds for the growth of the carbon nanotubes is discussed. The partial bismuth filling inside the CNTs was optimized. Based on the results, a schematic growth model for better understanding of the process parameters has also been proposed.

Use of nonlinear models for describing scrotal circumference growth in Guzerat bulls raised under grazing conditions.

PubMed

Loaiza-Echeverri, A M; Bergmann, J A G; Toral, F L B; Osorio, J P; Carmo, A S; Mendonça, L F; Moustacas, V S; Henry, M

2013-03-15

The objective was to use various nonlinear models to describe scrotal circumference (SC) growth in Guzerat bulls on three farms in the state of Minas Gerais, Brazil. The nonlinear models were: Brody, Logistic, Gompertz, Richards, Von Bertalanffy, and Tanaka, where parameter A is the estimated testis size at maturity, B is the integration constant, k is a maturating index and, for the Richards and Tanaka models, m determines the inflection point. In Tanaka, A is an indefinite size of the testis, and B and k adjust the shape and inclination of the curve. A total of 7410 SC records were obtained every 3 months from 1034 bulls with ages varying between 2 and 69 months (<240 days of age = 159; 241-365 days = 451; 366-550 days = 1443; 551-730 days = 1705; and >731 days = 3652 SC measurements). Goodness of fit was evaluated by coefficients of determination (R(2)), error sum of squares, average prediction error (APE), and mean absolute deviation. The Richards model did not reach the convergence criterion. The R(2) were similar for all models (0.68-0.69). The error sum of squares was lowest for the Tanaka model. All models fit the SC data poorly in the early and late periods. Logistic was the model which best estimated SC in the early phase (based on APE and mean absolute deviation). The Tanaka and Logistic models had the lowest APE between 300 and 1600 days of age. The Logistic model was chosen for analysis of the environmental influence on parameters A and k. Based on absolute growth rate, SC increased from 0.019 cm/d, peaking at 0.025 cm/d between 318 and 435 days of age. Farm, year, and season of birth significantly affected size of adult SC and SC growth rate. An increase in SC adult size (parameter A) was accompanied by decreased SC growth rate (parameter k). In conclusion, SC growth in Guzerat bulls was characterized by an accelerated growth phase, followed by decreased growth; this was best represented by the Logistic model. The inflection point occurred at approximately 376 days of age (mean SC of 17.9 cm). We inferred that early selection of testicular size might result in smaller testes at maturity. Copyright © 2013 Elsevier Inc. All rights reserved.

Economic consequences of population size, structure and growth.

PubMed

Lee, R

1983-01-01

There seems to be 4 major approaches to conceptualizing and modeling demographic influences on economic and social welfare. These approaches are combined in various ways to construct richer and more comprehensive models. The basic approaches are: demographic influences on household or family behavior; population growth and reproducible capital; population size and fixed factors; and population and advantages of scale. These 4 models emphasize the supply side effects of population. A few of the ways in which these theories have been combined are sketched. Neoclassical growth models often have been combined with age distributed populations of individuals (or households), assumed to pursue optimal life cycle consumption and saving. In some well known development models, neoclassical growth models for the modern sector are linked by labor markets and migration to fixed factor (land) models of the traditional (agricultural) sector. A whole series of macro simulation models for developed and developing countries was based on single sector neoclassical growth models with age distributed populations. Yet, typically the household level foundations of assumed age distribution effects were not worked out. Simon's (1977) simulation models are in a class by themselves, for they are the only models that attempt to incorporate all the kinds of effects discussed. The economic demography of the individual and family cycle, as it is affected by regimes of fertility, mortality, and nuptiality, taken as given, are considered. The examination touches on many of the purported consequences of aggregate population growth and age composition, since so many of these are based implicitly or explicitly on assertions about micro level behavior. Demographic influences on saving and consumption, on general labor supply and female labor supply, and on problems of youth and old age dependency frequently fall in this category. Finally, attention is focused specifically on macro economic issues in the consequences of population in both developed and developing countries. In general cross national studies have failed to provide rough and stylized depiction of the consequences of rapid population growth, unless the absence of significant results is itself the result.

Fatigue crack propagation behavior of stainless steel welds

NASA Astrophysics Data System (ADS)

Kusko, Chad S.

The fatigue crack propagation behavior of austenitic and duplex stainless steel base and weld metals has been investigated using various fatigue crack growth test procedures, ferrite measurement techniques, light optical microscopy, stereomicroscopy, scanning electron microscopy, and optical profilometry. The compliance offset method has been incorporated to measure crack closure during testing in order to determine a stress ratio at which such closure is overcome. Based on this method, an empirically determined stress ratio of 0.60 has been shown to be very successful in overcoming crack closure for all da/dN for gas metal arc and laser welds. This empirically-determined stress ratio of 0.60 has been applied to testing of stainless steel base metal and weld metal to understand the influence of microstructure. Regarding the base metal investigation, for 316L and AL6XN base metals, grain size and grain plus twin size have been shown to influence resulting crack growth behavior. The cyclic plastic zone size model has been applied to accurately model crack growth behavior for austenitic stainless steels when the average grain plus twin size is considered. Additionally, the effect of the tortuous crack paths observed for the larger grain size base metals can be explained by a literature model for crack deflection. Constant Delta K testing has been used to characterize the crack growth behavior across various regions of the gas metal arc and laser welds at the empirically determined stress ratio of 0.60. Despite an extensive range of stainless steel weld metal FN and delta-ferrite morphologies, neither delta-ferrite morphology significantly influence the room temperature crack growth behavior. However, variations in weld metal da/dN can be explained by local surface roughness resulting from large columnar grains and tortuous crack paths in the weld metal.

Modeling Physiological Processes That Relate Toxicant Exposure and Bacterial Population Dynamics

PubMed Central

Klanjscek, Tin; Nisbet, Roger M.; Priester, John H.; Holden, Patricia A.

2012-01-01

Quantifying effects of toxicant exposure on metabolic processes is crucial to predicting microbial growth patterns in different environments. Mechanistic models, such as those based on Dynamic Energy Budget (DEB) theory, can link physiological processes to microbial growth. Here we expand the DEB framework to include explicit consideration of the role of reactive oxygen species (ROS). Extensions considered are: (i) additional terms in the equation for the “hazard rate” that quantifies mortality risk; (ii) a variable representing environmental degradation; (iii) a mechanistic description of toxic effects linked to increase in ROS production and aging acceleration, and to non-competitive inhibition of transport channels; (iv) a new representation of the “lag time” based on energy required for acclimation. We estimate model parameters using calibrated Pseudomonas aeruginosa optical density growth data for seven levels of cadmium exposure. The model reproduces growth patterns for all treatments with a single common parameter set, and bacterial growth for treatments of up to 150 mg(Cd)/L can be predicted reasonably well using parameters estimated from cadmium treatments of 20 mg(Cd)/L and lower. Our approach is an important step towards connecting levels of biological organization in ecotoxicology. The presented model reveals possible connections between processes that are not obvious from purely empirical considerations, enables validation and hypothesis testing by creating testable predictions, and identifies research required to further develop the theory. PMID:22328915

The Evolving Urban Community and Military Installations: A Dynamic Spatial Decision Support System for Sustainable Military Communities

DTIC Science & Technology

2007-01-01

focus on identifying growth by income and housing costs. These, and other models are focused on the city itself and deal with growth over the course...2. This model employs a set of econometric models to project future population, household, and employment. The landscape is gridded into one... model in LEAM (LEAMecon) forecasts changes in output, employment and income over time based on changes in the market, technology, productivity and

A Minimalistic Resource Allocation Model to Explain Ubiquitous Increase in Protein Expression with Growth Rate

PubMed Central

Keren, Leeat; Segal, Eran; Milo, Ron

2016-01-01

Most proteins show changes in level across growth conditions. Many of these changes seem to be coordinated with the specific growth rate rather than the growth environment or the protein function. Although cellular growth rates, gene expression levels and gene regulation have been at the center of biological research for decades, there are only a few models giving a base line prediction of the dependence of the proteome fraction occupied by a gene with the specific growth rate. We present a simple model that predicts a widely coordinated increase in the fraction of many proteins out of the proteome, proportionally with the growth rate. The model reveals how passive redistribution of resources, due to active regulation of only a few proteins, can have proteome wide effects that are quantitatively predictable. Our model provides a potential explanation for why and how such a coordinated response of a large fraction of the proteome to the specific growth rate arises under different environmental conditions. The simplicity of our model can also be useful by serving as a baseline null hypothesis in the search for active regulation. We exemplify the usage of the model by analyzing the relationship between growth rate and proteome composition for the model microorganism E.coli as reflected in recent proteomics data sets spanning various growth conditions. We find that the fraction out of the proteome of a large number of proteins, and from different cellular processes, increases proportionally with the growth rate. Notably, ribosomal proteins, which have been previously reported to increase in fraction with growth rate, are only a small part of this group of proteins. We suggest that, although the fractions of many proteins change with the growth rate, such changes may be partially driven by a global effect, not necessarily requiring specific cellular control mechanisms. PMID:27073913

Lysine production from methanol at 50 degrees C using Bacillus methanolicus: Modeling volume control, lysine concentration, and productivity using a three-phase continuous simulation.

PubMed

Lee, G H; Hur, W; Bremmon, C E; Flickinger, M C

1996-03-20

A simulation was developed based on experimental data obtained in a 14-L reactor to predict the growth and L-lysine accumulation kinetics, and change in volume of a large-scale (250-m(3)) Bacillus methanolicus methanol-based process. Homoserine auxotrophs of B. methanolicus MGA3 are unique methylotrophs because of the ability to secrete lysine during aerobic growth and threonine starvation at 50 degrees C. Dissolved methanol (100 mM), pH, dissolved oxygen tension (0.063 atm), and threonine levels were controlled to obtain threonine-limited conditions and high-cell density (25 g dry cell weight/L) in a 14-L reactor. As a fed-batch process, the additions of neat methanol (fed on demand), threonine, and other nutrients cause the volume of the fermentation to increase and the final lysine concentration to decrease. In addition, water produced as a result of methanol metabolism contributes to the increase in the volume of the reactor. A three-phase approach was used to predict the rate of change of culture volume based on carbon dioxide production and methanol consumption. This model was used for the evaluation of volume control strategies to optimize lysine productivity. A constant volume reactor process with variable feeding and continuous removal of broth and cells (VF(cstr)) resulted in higher lysine productivity than a fed-batch process without volume control. This model predicts the variation in productivity of lysine with changes in growth and in specific lysine productivity. Simple modifications of the model allows one to investigate other high-lysine-secreting strains with different growth and lysine productivity characteristics. Strain NOA2#13A5-2 which secretes lysine and other end-products were modeled using both growth and non-growth-associated lysine productivity. A modified version of this model was used to simulate the change in culture volume of another L-lysine producing mutant (NOA2#13A52-8A66) with reduced secretion of end-products. The modified simulation indicated that growth-associated production dominates in strain NOA2#13A52-8A66. (c) 1996 John Wiley & Sons, Inc.

Executive functioning as a mediator of conduct problems prevention in children of homeless families residing in temporary supportive housing: a parallel process latent growth modeling approach.

PubMed

Piehler, Timothy F; Bloomquist, Michael L; August, Gerald J; Gewirtz, Abigail H; Lee, Susanne S; Lee, Wendy S C

2014-01-01

A culturally diverse sample of formerly homeless youth (ages 6-12) and their families (n = 223) participated in a cluster randomized controlled trial of the Early Risers conduct problems prevention program in a supportive housing setting. Parents provided 4 annual behaviorally-based ratings of executive functioning (EF) and conduct problems, including at baseline, over 2 years of intervention programming, and at a 1-year follow-up assessment. Using intent-to-treat analyses, a multilevel latent growth model revealed that the intervention group demonstrated reduced growth in conduct problems over the 4 assessment points. In order to examine mediation, a multilevel parallel process latent growth model was used to simultaneously model growth in EF and growth in conduct problems along with intervention status as a covariate. A significant mediational process emerged, with participation in the intervention promoting growth in EF, which predicted negative growth in conduct problems. The model was consistent with changes in EF fully mediating intervention-related changes in youth conduct problems over the course of the study. These findings highlight the critical role that EF plays in behavioral change and lends further support to its importance as a target in preventive interventions with populations at risk for conduct problems.

Posttraumatic growth in post-surgical coronary artery bypass graft patients

PubMed Central

Waight, Catherine A; Sheridan, Judith; Tesar, Peter

2015-01-01

Recent research in posttraumatic growth has been applied to people with life-threatening illnesses to optimise recovery. There is a lack of research exploring posttraumatic growth in coronary artery bypass graft patients. This article describes the recovery experience of 14 coronary artery bypass graft patients (13 males and 1 female) at their first outpatient review post-surgery. Grounded theory analysis was used to develop a model of distinct and shared pathways to growth depending on whether patients were symptomatic or asymptomatic pre-coronary artery bypass graft. Outcomes of posttraumatic growth in this sample included action-based healthy lifestyle growth and two forms of cognitive growth: appreciation of life and new possibilities. The model of posttraumatic growth developed in this study may be helpful in guiding future research into promoting posttraumatic growth and behaviour change in coronary artery bypass graft patients. PMID:28070351

Integration of Life-Stage Physiologically Based Pharmacokinetic Models with Adverse Outcome Pathways and Environmental Exposure Models to Screen for Environmental Hazards

EPA Science Inventory

A Life-stage Physiologically-Based Pharmacokinetic (PBPK) model was developed to include descriptions of several life-stage events such as pregnancy, fetal development, the neonate and child growth. The overall modeling strategy was used for in vitro to in vivo (IVIVE) extrapolat...

Biofilms promote altruism.

PubMed

Kreft, Jan-Ulrich

2004-08-01

The origin of altruism is a fundamental problem in evolution, and the maintenance of biodiversity is a fundamental problem in ecology. These two problems combine with the fundamental microbiological question of whether it is always advantageous for a unicellular organism to grow as fast as possible. The common basis for these three themes is a trade-off between growth rate and growth yield, which in turn is based on irreversible thermodynamics. The trade-off creates an evolutionary alternative between two strategies: high growth yield at low growth rate versus high growth rate at low growth yield. High growth yield at low growth rate is a case of an altruistic strategy because it increases the fitness of the group by using resources economically at the cost of decreased fitness, or growth rate, of the individual. The group-beneficial behaviour is advantageous in the long term, whereas the high growth rate strategy is advantageous in the short term. Coexistence of species requires differences between their niches, and niche space is typically divided into four 'axes' (time, space, resources, predators). This neglects survival strategies based on cooperation, which extend the possibilities of coexistence, arguing for the inclusion of cooperation as the fifth 'axis'. Here, individual-based model simulations show that spatial structure, as in, for example, biofilms, is necessary for the origin and maintenance of this 'primitive' altruistic strategy and that the common belief that growth rate but not yield decides the outcome of competition is based on chemostat models and experiments. This evolutionary perspective on life in biofilms can explain long-known biofilm characteristics, such as the structural organization into microcolonies, the often-observed lack of mixing among microcolonies, and the shedding of single cells, as promoting the origin and maintenance of the altruistic strategy. Whereas biofilms enrich altruists, enrichment cultures, microbiology's paradigm for isolating bacteria into pure culture, select for highest growth rate.

Right-Sizing Statistical Models for Longitudinal Data

PubMed Central

Wood, Phillip K.; Steinley, Douglas; Jackson, Kristina M.

2015-01-01

Arguments are proposed that researchers using longitudinal data should consider more and less complex statistical model alternatives to their initially chosen techniques in an effort to “right-size” the model to the data at hand. Such model comparisons may alert researchers who use poorly fitting overly parsimonious models to more complex better fitting alternatives, and, alternatively, may identify more parsimonious alternatives to overly complex (and perhaps empirically under-identified and/or less powerful) statistical models. A general framework is proposed for considering (often nested) relationships between a variety of psychometric and growth curve models. A three-step approach is proposed in which models are evaluated based on the number and patterning of variance components prior to selection of better-fitting growth models that explain both mean and variation/covariation patterns. The orthogonal, free-curve slope-intercept (FCSI) growth model is considered as a general model which includes, as special cases, many models including the Factor Mean model (FM, McArdle & Epstein, 1987), McDonald's (1967) linearly constrained factor model, Hierarchical Linear Models (HLM), Repeated Measures MANOVA, and the Linear Slope Intercept (LinearSI) Growth Model. The FCSI model, in turn, is nested within the Tuckerized factor model. The approach is illustrated by comparing alternative models in a longitudinal study of children's vocabulary and by comparison of several candidate parametric growth and chronometric models in a Monte Carlo study. PMID:26237507

Right-sizing statistical models for longitudinal data.

PubMed

Wood, Phillip K; Steinley, Douglas; Jackson, Kristina M

2015-12-01

Arguments are proposed that researchers using longitudinal data should consider more and less complex statistical model alternatives to their initially chosen techniques in an effort to "right-size" the model to the data at hand. Such model comparisons may alert researchers who use poorly fitting, overly parsimonious models to more complex, better-fitting alternatives and, alternatively, may identify more parsimonious alternatives to overly complex (and perhaps empirically underidentified and/or less powerful) statistical models. A general framework is proposed for considering (often nested) relationships between a variety of psychometric and growth curve models. A 3-step approach is proposed in which models are evaluated based on the number and patterning of variance components prior to selection of better-fitting growth models that explain both mean and variation-covariation patterns. The orthogonal free curve slope intercept (FCSI) growth model is considered a general model that includes, as special cases, many models, including the factor mean (FM) model (McArdle & Epstein, 1987), McDonald's (1967) linearly constrained factor model, hierarchical linear models (HLMs), repeated-measures multivariate analysis of variance (MANOVA), and the linear slope intercept (linearSI) growth model. The FCSI model, in turn, is nested within the Tuckerized factor model. The approach is illustrated by comparing alternative models in a longitudinal study of children's vocabulary and by comparing several candidate parametric growth and chronometric models in a Monte Carlo study. (c) 2015 APA, all rights reserved).

Human growth and body weight dynamics: an integrative systems model.

PubMed

Rahmandad, Hazhir

2014-01-01

Quantifying human weight and height dynamics due to growth, aging, and energy balance can inform clinical practice and policy analysis. This paper presents the first mechanism-based model spanning full individual life and capturing changes in body weight, composition and height. Integrating previous empirical and modeling findings and validated against several additional empirical studies, the model replicates key trends in human growth including A) Changes in energy requirements from birth to old ages. B) Short and long-term dynamics of body weight and composition. C) Stunted growth with chronic malnutrition and potential for catch up growth. From obesity policy analysis to treating malnutrition and tracking growth trajectories, the model can address diverse policy questions. For example I find that even without further rise in obesity, the gap between healthy and actual Body Mass Indexes (BMIs) has embedded, for different population groups, a surplus of 14%-24% in energy intake which will be a source of significant inertia in obesity trends. In another analysis, energy deficit percentage needed to reduce BMI by one unit is found to be relatively constant across ages. Accompanying documented and freely available simulation model facilitates diverse applications customized to different sub-populations.

Human Growth and Body Weight Dynamics: An Integrative Systems Model

PubMed Central

Rahmandad, Hazhir

2014-01-01

Quantifying human weight and height dynamics due to growth, aging, and energy balance can inform clinical practice and policy analysis. This paper presents the first mechanism-based model spanning full individual life and capturing changes in body weight, composition and height. Integrating previous empirical and modeling findings and validated against several additional empirical studies, the model replicates key trends in human growth including A) Changes in energy requirements from birth to old ages. B) Short and long-term dynamics of body weight and composition. C) Stunted growth with chronic malnutrition and potential for catch up growth. From obesity policy analysis to treating malnutrition and tracking growth trajectories, the model can address diverse policy questions. For example I find that even without further rise in obesity, the gap between healthy and actual Body Mass Indexes (BMIs) has embedded, for different population groups, a surplus of 14%–24% in energy intake which will be a source of significant inertia in obesity trends. In another analysis, energy deficit percentage needed to reduce BMI by one unit is found to be relatively constant across ages. Accompanying documented and freely available simulation model facilitates diverse applications customized to different sub-populations. PMID:25479101

How to make a tree ring: Coupling stem water flow and cambial activity in mature Alpine conifers

NASA Astrophysics Data System (ADS)

Peters, Richard L.; Frank, David C.; Treydte, Kerstin; Steppe, Kathy; Kahmen, Ansgar; Fonti, Patrick

2017-04-01

Inter-annual tree-ring measurements are used to understand tree-growth responses to climatic variability and reconstruct past climate conditions. In parallel, mechanistic models use experimentally defined plant-atmosphere interactions to explain past growth responses and predict future environmental impact on forest productivity. Yet, substantial inconsistencies within mechanistic model ensembles and mismatches with empirical data indicate that significant progress is still needed to understand the processes occurring at an intra-annual resolution that drive annual growth. However, challenges arise due to i) few datasets describing climatic responses of high-resolution physiological processes over longer time-scales, ii) uncertainties on the main mechanistic process limiting radial stem growth and iii) complex interactions between multiple environmental factors which obscure detection of the main stem growth driver, generating a gap between our understanding of intra- and inter-annual growth mechanisms. We attempt to bridge the gap between inter-annual tree-ring width and sub-daily radial stem-growth and provide a mechanistic perspective on how environmental conditions affect physiological processes that shape tree rings in conifers. We combine sub-hourly sap flow and point dendrometer measurements performed on mature Alpine conifers (Larix decidua) into an individual-based mechanistic tree-growth model to simulate sub-hourly cambial activity. The monitored trees are located along a high elevational transect in the Swiss Alps (Lötschental) to analyse the effect of increasing temperature. The model quantifies internal tree hydraulic pathways that regulate the turgidity within the cambial zone and induce cell enlargement for radial growth. The simulations are validated against intra-annual growth patterns derived from xylogenesis data and anatomical analyses. Our efforts advance the process-based understanding of how climate shapes the annual tree-ring structures and could potentially improve our ability to reconstruct the climate of the past and predict future growth under changing climate.

Global evaluation of biofuel potential from microalgae

PubMed Central

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

2014-01-01

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

Educational Investment, Family Context, and Children's Math and Reading Growth from Kindergarten through the Third Grade

ERIC Educational Resources Information Center

Cheadle, Jacob E.

2008-01-01

Drawing on longitudinal data from the Early Childhood Longitudinal Study, Kindergarten Class of 1998-1999, this study used IRT modeling to operationalize a measure of parental educational investments based on Lareau's notion of concerted cultivation. It used multilevel piece-wise growth models regressing children's math and reading achievement…

Reaction-to-fire testing and modeling for wood products

Treesearch

Mark A. Dietenberger; Robert H. White

2001-01-01

In this review we primarily discuss our use of the oxygen consumption calorimeter (ASTM E1354 for cone calorimeter and ISO9705 for room/corner tests) and fire growth modeling to evaluate treated wood products. With recent development towards performance-based building codes, new methodology requires engineering calculations of various fire growth scenarios. The initial...

Measurement Equivalence of Teachers' Sense of Efficacy Scale Using Latent Growth Methods

ERIC Educational Resources Information Center

Basokçu, T. Oguz; Ögretmen, T.

2016-01-01

This study is based on the application of latent growth modeling, which is one of structural equation models on real data. Teachers' Sense of Efficacy Scale (TSES), which was previously adapted into Turkish was administered to 200 preservice teachers at different time intervals for three times and study data was collected. Measurement equivalence…

Regenerative life support system research

NASA Technical Reports Server (NTRS)

1988-01-01

Sections on modeling, experimental activities during the grant period, and topics under consideration for the future are contained. The sessions contain discussions of: four concurrent modeling approaches that were being integrated near the end of the period (knowledge-based modeling support infrastructure and data base management, object-oriented steady state simulations for three concepts, steady state mass-balance engineering tradeoff studies, and object-oriented time-step, quasidynamic simulations of generic concepts); interdisciplinary research activities, beginning with a discussion of RECON lab development and use, and followed with discussions of waste processing research, algae studies and subsystem modeling, low pressure growth testing of plants, subsystem modeling of plants, control of plant growth using lighting and CO2 supply as variables, search for and development of lunar soil simulants, preliminary design parameters for a lunar base life support system, and research considerations for food processing in space; and appendix materials, including a discussion of the CELSS Conference, detailed analytical equations for mass-balance modeling, plant modeling equations, and parametric data on existing life support systems for use in modeling.

Modeling the population-level effects of hypoxia on a coastal fish: implications of a spatially-explicit individual-based model

NASA Astrophysics Data System (ADS)

Rose, K.; Creekmore, S.; Thomas, P.; Craig, K.; Neilan, R.; Rahman, S.; Wang, L.; Justic, D.

2016-02-01

The northwestern Gulf of Mexico (USA) currently experiences a large hypoxic area ("dead zone") during the summer. The population-level effects of hypoxia on coastal fish are largely unknown. We developed a spatially-explicit, individual-based model to analyze how hypoxia effects on reproduction, growth, and mortality of individual Atlantic croaker could lead to population-level responses. The model follows the hourly growth, mortality, reproduction, and movement of individuals on a 300 x 800 spatial grid of 1 km2 cells for 140 years. Chlorophyll-a concentration and water temperature were specified daily for each grid cell. Dissolved oxygen (DO) was obtained from a 3-D water quality model for four years that differed in their severity of hypoxia. A bioenergetics model was used to represent growth, mortality was assumed stage- and age-dependent, and movement behavior was based on temperature preferences and avoidance of low DO. Hypoxia effects were imposed using exposure-effects sub-models that converted time-varying exposure to DO to reductions in growth and fecundity, and increases in mortality. Using sequences of mild, intermediate, and severe hypoxia years, the model predicted a 20% decrease in population abundance. Additional simulations were performed under the assumption that river-based nutrients loadings that lead to more hypoxia also lead to higher primary production and more food for croaker. Twenty-five percent and 50% nutrient reduction scenarios were simulated by adjusting the cholorphyll-a concentrations used as food proxy for the croaker. We then incrementally increased the DO concentrations to determine how much hypoxia would need to be reduced to offset the lower food production resulting from reduced nutrients. We discuss the generality of our results, the hidden effects of hypoxia on fish, and our overall strategy of combining laboratory and field studies with modeling to produce robust predictions of population responses to stressors under dynamic and multi-stressor conditions.

Fractal dimension and universality in avascular tumor growth

NASA Astrophysics Data System (ADS)

Ribeiro, Fabiano L.; dos Santos, Renato Vieira; Mata, Angélica S.

2017-04-01

For years, the comprehension of the tumor growth process has been intriguing scientists. New research has been constantly required to better understand the complexity of this phenomenon. In this paper, we propose a mathematical model that describes the properties, already known empirically, of avascular tumor growth. We present, from an individual-level (microscopic) framework, an explanation of some phenomenological (macroscopic) aspects of tumors, such as their spatial form and the way they develop. Our approach is based on competitive interaction between the cells. This simple rule makes the model able to reproduce evidence observed in real tumors, such as exponential growth in their early stage followed by power-law growth. The model also reproduces (i) the fractal-space distribution of tumor cells and (ii) the universal growth behavior observed in both animals and tumors. Our analyses suggest that the universal similarity between tumor and animal growth comes from the fact that both can be described by the same dynamic equation—the Bertalanffy-Richards model—even if they do not necessarily share the same biological properties.

Impact of competitor species composition on predicting diameter growth and survival rates of Douglas-fir trees in southwestern Oregon

USGS Publications Warehouse

Bravo, Felipe; Hann, D.W.; Maguire, Douglas A.

2001-01-01

Mixed conifer and hardwood stands in southwestern Oregon were studied to explore the hypothesis that competition effects on individual-tree growth and survival will differ according to the species comprising the competition measure. Likewise, it was hypothesized that competition measures should extrapolate best if crown-based surrogates are given preference over diameter-based (basal area based) surrogates. Diameter growth and probability of survival were modeled for individual Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco) trees growing in pure stands. Alternative models expressing one-sided and two-sided competition as a function of either basal area or crown structure were then applied to other plots in which Douglas-fir was mixed with other conifers and (or) hardwood species. Crown-based variables outperformed basal area based variables as surrogates for one-sided competition in both diameter growth and survival probability, regardless of species composition. In contrast, two-sided competition was best represented by total basal area of competing trees. Surrogates reflecting differences in crown morphology among species relate more closely to the mechanics of competition for light and, hence, facilitate extrapolation to species combinations for which no observations are available.

Pore-scale simulation of microbial growth using a genome-scale metabolic model: Implications for Darcy-scale reactive transport

NASA Astrophysics Data System (ADS)

Tartakovsky, G. D.; Tartakovsky, A. M.; Scheibe, T. D.; Fang, Y.; Mahadevan, R.; Lovley, D. R.

2013-09-01

Recent advances in microbiology have enabled the quantitative simulation of microbial metabolism and growth based on genome-scale characterization of metabolic pathways and fluxes. We have incorporated a genome-scale metabolic model of the iron-reducing bacteria Geobacter sulfurreducens into a pore-scale simulation of microbial growth based on coupling of iron reduction to oxidation of a soluble electron donor (acetate). In our model, fluid flow and solute transport is governed by a combination of the Navier-Stokes and advection-diffusion-reaction equations. Microbial growth occurs only on the surface of soil grains where solid-phase mineral iron oxides are available. Mass fluxes of chemical species associated with microbial growth are described by the genome-scale microbial model, implemented using a constraint-based metabolic model, and provide the Robin-type boundary condition for the advection-diffusion equation at soil grain surfaces. Conventional models of microbially-mediated subsurface reactions use a lumped reaction model that does not consider individual microbial reaction pathways, and describe reactions rates using empirically-derived rate formulations such as the Monod-type kinetics. We have used our pore-scale model to explore the relationship between genome-scale metabolic models and Monod-type formulations, and to assess the manifestation of pore-scale variability (microenvironments) in terms of apparent Darcy-scale microbial reaction rates. The genome-scale model predicted lower biomass yield, and different stoichiometry for iron consumption, in comparison to prior Monod formulations based on energetics considerations. We were able to fit an equivalent Monod model, by modifying the reaction stoichiometry and biomass yield coefficient, that could effectively match results of the genome-scale simulation of microbial behaviors under excess nutrient conditions, but predictions of the fitted Monod model deviated from those of the genome-scale model under conditions in which one or more nutrients were limiting. The fitted Monod kinetic model was also applied at the Darcy scale; that is, to simulate average reaction processes at the scale of the entire pore-scale model domain. As we expected, even under excess nutrient conditions for which the Monod and genome-scale models predicted equal reaction rates at the pore scale, the Monod model over-predicted the rates of biomass growth and iron and acetate utilization when applied at the Darcy scale. This discrepancy is caused by an inherent assumption of perfect mixing over the Darcy-scale domain, which is clearly violated in the pore-scale models. These results help to explain the need to modify the flux constraint parameters in order to match observations in previous applications of the genome-scale model at larger scales. These results also motivate further investigation of quantitative multi-scale relationships between fundamental behavior at the pore scale (where genome-scale models are appropriately applied) and observed behavior at larger scales (where predictions of reactive transport phenomena are needed).

Pore-scale simulation of microbial growth using a genome-scale metabolic model: Implications for Darcy-scale reactive transport

NASA Astrophysics Data System (ADS)

Scheibe, T. D.; Tartakovsky, G.; Tartakovsky, A. M.; Fang, Y.; Mahadevan, R.; Lovley, D. R.

2012-12-01

Recent advances in microbiology have enabled the quantitative simulation of microbial metabolism and growth based on genome-scale characterization of metabolic pathways and fluxes. We have incorporated a genome-scale metabolic model of the iron-reducing bacteria Geobacter sulfurreducens into a pore-scale simulation of microbial growth based on coupling of iron reduction to oxidation of a soluble electron donor (acetate). In our model, fluid flow and solute transport is governed by a combination of the Navier-Stokes and advection-diffusion-reaction equations. Microbial growth occurs only on the surface of soil grains where solid-phase mineral iron oxides are available. Mass fluxes of chemical species associated with microbial growth are described by the genome-scale microbial model, implemented using a constraint-based metabolic model, and provide the Robin-type boundary condition for the advection-diffusion equation at soil grain surfaces. Conventional models of microbially-mediated subsurface reactions use a lumped reaction model that does not consider individual microbial reaction pathways, and describe reactions rates using empirically-derived rate formulations such as the Monod-type kinetics. We have used our pore-scale model to explore the relationship between genome-scale metabolic models and Monod-type formulations, and to assess the manifestation of pore-scale variability (microenvironments) in terms of apparent Darcy-scale microbial reaction rates. The genome-scale model predicted lower biomass yield, and different stoichiometry for iron consumption, in comparison to prior Monod formulations based on energetics considerations. We were able to fit an equivalent Monod model, by modifying the reaction stoichiometry and biomass yield coefficient, that could effectively match results of the genome-scale simulation of microbial behaviors under excess nutrient conditions, but predictions of the fitted Monod model deviated from those of the genome-scale model under conditions in which one or more nutrients were limiting. The fitted Monod kinetic model was also applied at the Darcy scale; that is, to simulate average reaction processes at the scale of the entire pore-scale model domain. As we expected, even under excess nutrient conditions for which the Monod and genome-scale models predicted equal reaction rates at the pore scale, the Monod model over-predicted the rates of biomass growth and iron and acetate utilization when applied at the Darcy scale. This discrepancy is caused by an inherent assumption of perfect mixing over the Darcy-scale domain, which is clearly violated in the pore-scale models. These results help to explain the need to modify the flux constraint parameters in order to match observations in previous applications of the genome-scale model at larger scales. These results also motivate further investigation of quantitative multi-scale relationships between fundamental behavior at the pore scale (where genome-scale models are appropriately applied) and observed behavior at larger scales (where predictions of reactive transport phenomena are needed).

Pore-scale simulation of microbial growth using a genome-scale metabolic model: Implications for Darcy-scale reactive transport

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

Tartakovsky, Guzel D.; Tartakovsky, Alexandre M.; Scheibe, Timothy D.

2013-09-07

Recent advances in microbiology have enabled the quantitative simulation of microbial metabolism and growth based on genome-scale characterization of metabolic pathways and fluxes. We have incorporated a genome-scale metabolic model of the iron-reducing bacteria Geobacter sulfurreducens into a pore-scale simulation of microbial growth based on coupling of iron reduction to oxidation of a soluble electron donor (acetate). In our model, fluid flow and solute transport is governed by a combination of the Navier-Stokes and advection-diffusion-reaction equations. Microbial growth occurs only on the surface of soil grains where solid-phase mineral iron oxides are available. Mass fluxes of chemical species associated withmore » microbial growth are described by the genome-scale microbial model, implemented using a constraint-based metabolic model, and provide the Robin-type boundary condition for the advection-diffusion equation at soil grain surfaces. Conventional models of microbially-mediated subsurface reactions use a lumped reaction model that does not consider individual microbial reaction pathways, and describe reactions rates using empirically-derived rate formulations such as the Monod-type kinetics. We have used our pore-scale model to explore the relationship between genome-scale metabolic models and Monod-type formulations, and to assess the manifestation of pore-scale variability (microenvironments) in terms of apparent Darcy-scale microbial reaction rates. The genome-scale model predicted lower biomass yield, and different stoichiometry for iron consumption, in comparisonto prior Monod formulations based on energetics considerations. We were able to fit an equivalent Monod model, by modifying the reaction stoichiometry and biomass yield coefficient, that could effectively match results of the genome-scale simulation of microbial behaviors under excess nutrient conditions, but predictions of the fitted Monod model deviated from those of the genome-scale model under conditions in which one or more nutrients were limiting. The fitted Monod kinetic model was also applied at the Darcy scale; that is, to simulate average reaction processes at the scale of the entire pore-scale model domain. As we expected, even under excess nutrient conditions for which the Monod and genome-scale models predicted equal reaction rates at the pore scale, the Monod model over-predicted the rates of biomass growth and iron and acetate utilization when applied at the Darcy scale. This discrepancy is caused by an inherent assumption of perfect mixing over the Darcy-scale domain, which is clearly violated in the pore-scale models. These results help to explain the need to modify the flux constraint parameters in order to match observations in previous applications of the genome-scale model at larger scales. These results also motivate further investigation of quantitative multi-scale relationships between fundamental behavior at the pore scale (where genome-scale models are appropriately applied) and observed behavior at larger scales (where predictions of reactive transport phenomena are needed).« less

Towards establishing a combined rate law of nucleation and crystal growth - The case study of gypsum precipitation

NASA Astrophysics Data System (ADS)

Rendel, Pedro M.; Gavrieli, Ittai; Wolff-Boenisch, Domenik; Ganor, Jiwchar

2018-03-01

The main obstacle in the formulation of a quantitative rate-model for mineral precipitation is the absence of a rigorous method for coupling nucleation and growth processes. In order to link both processes, we conducted a series of batch experiments in which gypsum nucleation was followed by crystal growth. Experiments were carried out using various stirring methods in several batch vessels made of different materials. In the experiments, the initial degree of supersaturation of the solution with respect to gypsum (Ωgyp) was set between 1.58 and 1.82. Under these conditions, heterogeneous nucleation is the dominant nucleation mode. Based on changes in SO42- concentration with time, the induction time of gypsum nucleation and the following rate of crystal growth were calculated for each experiment. The induction time (6-104 h) was found to be a function of the vessel material, while the rates of crystal growth, which varied over three orders of magnitude, were strongly affected by the stirring speed and its mode (i.e. rocking, shaking, magnetic stirrer, and magnetic impeller). The SO42- concentration data were then used to formulate a forward model that couples the simple rate laws for nucleation and crystal growth of gypsum into a single kinetic model. Accordingly, the obtained rate law is based on classical nucleation theory and heterogeneous crystal growth.

Economic planning and equilibrium growth of human resources and capital in health-care sector: Case study of Iran

PubMed Central

Mahboobi-Ardakan, Payman; Kazemian, Mahmood; Mehraban, Sattar

2017-01-01

CONTEXT: During different planning periods, human resources factor has been considerably increased in the health-care sector. AIMS: The main goal is to determine economic planning conditions and equilibrium growth for services level and specialized workforce resources in health-care sector and also to determine the gap between levels of health-care services and specialized workforce resources in the equilibrium growth conditions and their available levels during the periods of the first to fourth development plansin Iran. MATERIALS AND METHODS: In the study after data collection, econometric methods and EViews version 8.0 were used for data processing. The used model was based on neoclassical economic growth model. RESULTS: The results indicated that during the former planning periods, although specialized workforce has been increased significantly in health-care sector, lack of attention to equilibrium growth conditions caused imbalance conditions for product level and specialized workforce in health-care sector. CONCLUSIONS: In the past development plans for health services, equilibrium conditions based on the full employment in the capital stock, and specialized labor are not considered. The government could act by choosing policies determined by the growth model to achieve equilibrium level in the field of human resources and services during the next planning periods. PMID:28616419

Optimization of Phenotyping Assays for the Model Monocot Setaria viridis

PubMed Central

Acharya, Biswa R.; Roy Choudhury, Swarup; Estelle, Aiden B.; Vijayakumar, Anitha; Zhu, Chuanmei; Hovis, Laryssa; Pandey, Sona

2017-01-01

Setaria viridis (green foxtail) is an important model plant for the study of C4 photosynthesis in panicoid grasses, and is fast emerging as a system of choice for the study of plant development, domestication, abiotic stress responses and evolution. Basic research findings in Setaria are expected to advance research not only in this species and its close relative S. italica (foxtail millet), but also in other panicoid grasses, many of which are important food or bioenergy crops. Here we report on the standardization of multiple growth and development assays for S. viridis under controlled conditions, and in response to several phytohormones and abiotic stresses. We optimized these assays at three different stages of the plant’s life: seed germination and post-germination growth using agar plate-based assays, early seedling growth and development using germination pouch-based assays, and adult plant growth and development under environmentally controlled growth chambers and greenhouses. These assays will be useful for the community to perform large scale phenotyping analyses, mutant screens, comparative physiological analysis, and functional characterization of novel genes of Setaria or other related agricultural crops. Precise description of various growth conditions, effective treatment conditions and description of the resultant phenotypes will help expand the use of S. viridis as an effective model system. PMID:29312412

Optimization of Phenotyping Assays for the Model Monocot Setaria viridis.

PubMed

Acharya, Biswa R; Roy Choudhury, Swarup; Estelle, Aiden B; Vijayakumar, Anitha; Zhu, Chuanmei; Hovis, Laryssa; Pandey, Sona

2017-01-01

Setaria viridis (green foxtail) is an important model plant for the study of C4 photosynthesis in panicoid grasses, and is fast emerging as a system of choice for the study of plant development, domestication, abiotic stress responses and evolution. Basic research findings in Setaria are expected to advance research not only in this species and its close relative S. italica (foxtail millet), but also in other panicoid grasses, many of which are important food or bioenergy crops. Here we report on the standardization of multiple growth and development assays for S. viridis under controlled conditions, and in response to several phytohormones and abiotic stresses. We optimized these assays at three different stages of the plant's life: seed germination and post-germination growth using agar plate-based assays, early seedling growth and development using germination pouch-based assays, and adult plant growth and development under environmentally controlled growth chambers and greenhouses. These assays will be useful for the community to perform large scale phenotyping analyses, mutant screens, comparative physiological analysis, and functional characterization of novel genes of Setaria or other related agricultural crops. Precise description of various growth conditions, effective treatment conditions and description of the resultant phenotypes will help expand the use of S. viridis as an effective model system.

Evolution of solidification texture during additive manufacturing

PubMed Central

Wei, H. L.; Mazumder, J.; DebRoy, T.

2015-01-01

Striking differences in the solidification textures of a nickel based alloy owing to changes in laser scanning pattern during additive manufacturing are examined based on theory and experimental data. Understanding and controlling texture are important because it affects mechanical and chemical properties. Solidification texture depends on the local heat flow directions and competitive grain growth in one of the six <100> preferred growth directions in face centered cubic alloys. Therefore, the heat flow directions are examined for various laser beam scanning patterns based on numerical modeling of heat transfer and fluid flow in three dimensions. Here we show that numerical modeling can not only provide a deeper understanding of the solidification growth patterns during the additive manufacturing, it also serves as a basis for customizing solidification textures which are important for properties and performance of components. PMID:26553246

Evolution of solidification texture during additive manufacturing

DOE PAGES

Wei, H. L.; Mazumder, J.; DebRoy, T.

2015-11-10

Striking differences in the solidification textures of a nickel based alloy owing to changes in laser scanning pattern during additive manufacturing are examined based on theory and experimental data. Understanding and controlling texture are important because it affects mechanical and chemical properties. Solidification texture depends on the local heat flow directions and competitive grain growth in one of the six <100> preferred growth directions in face centered cubic alloys. Furthermore, the heat flow directions are examined for various laser beam scanning patterns based on numerical modeling of heat transfer and fluid flow in three dimensions. Here we show that numericalmore » modeling can not only provide a deeper understanding of the solidification growth patterns during the additive manufacturing, it also serves as a basis for customizing solidification textures which are important for properties and performance of components.« less

Modeling the growth of Listeria monocytogenes in mold-ripened cheeses.

PubMed

Lobacz, Adriana; Kowalik, Jaroslaw; Tarczynska, Anna

2013-06-01

This study presents possible applications of predictive microbiology to model the safety of mold-ripened cheeses with respect to bacteria of the species Listeria monocytogenes during (1) the ripening of Camembert cheese, (2) cold storage of Camembert cheese at temperatures ranging from 3 to 15°C, and (3) cold storage of blue cheese at temperatures ranging from 3 to 15°C. The primary models used in this study, such as the Baranyi model and modified Gompertz function, were fitted to growth curves. The Baranyi model yielded the most accurate goodness of fit and the growth rates generated by this model were used for secondary modeling (Ratkowsky simple square root and polynomial models). The polynomial model more accurately predicted the influence of temperature on the growth rate, reaching the adjusted coefficients of multiple determination 0.97 and 0.92 for Camembert and blue cheese, respectively. The observed growth rates of L. monocytogenes in mold-ripened cheeses were compared with simulations run with the Pathogen Modeling Program (PMP 7.0, USDA, Wyndmoor, PA) and ComBase Predictor (Institute of Food Research, Norwich, UK). However, the latter predictions proved to be consistently overestimated and contained a significant error level. In addition, a validation process using independent data generated in dairy products from the ComBase database (www.combase.cc) was performed. In conclusion, it was found that L. monocytogenes grows much faster in Camembert than in blue cheese. Both the Baranyi and Gompertz models described this phenomenon accurately, although the Baranyi model contained a smaller error. Secondary modeling and further validation of the generated models highlighted the issue of usability and applicability of predictive models in the food processing industry by elaborating models targeted at a specific product or a group of similar products. Copyright © 2013 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Modeling of scale-dependent bacterial growth by chemical kinetics approach.

PubMed

Martínez, Haydee; Sánchez, Joaquín; Cruz, José-Manuel; Ayala, Guadalupe; Rivera, Marco; Buhse, Thomas

2014-01-01

We applied the so-called chemical kinetics approach to complex bacterial growth patterns that were dependent on the liquid-surface-area-to-volume ratio (SA/V) of the bacterial cultures. The kinetic modeling was based on current experimental knowledge in terms of autocatalytic bacterial growth, its inhibition by the metabolite CO2, and the relief of inhibition through the physical escape of the inhibitor. The model quantitatively reproduces kinetic data of SA/V-dependent bacterial growth and can discriminate between differences in the growth dynamics of enteropathogenic E. coli, E. coli JM83, and Salmonella typhimurium on one hand and Vibrio cholerae on the other hand. Furthermore, the data fitting procedures allowed predictions about the velocities of the involved key processes and the potential behavior in an open-flow bacterial chemostat, revealing an oscillatory approach to the stationary states.

A film-rupture model of hydrogen-induced, slow crack growth in alpha-beta titanium

NASA Technical Reports Server (NTRS)

Nelson, H. G.

1975-01-01

The appearance of the terrace like fracture morphology of gaseous hydrogen induced crack growth in acicular alpha-beta titanium alloys is discussed as a function of specimen configuration, magnitude of applied stress intensity, test temperature, and hydrogen pressure. Although the overall appearance of the terrace structure remained essentially unchanged, a distinguishable variation is found in the size of the individual terrace steps, and step size is found to be inversely dependent upon the rate of hydrogen induced slow crack growth. Additionally, this inverse relationship is independent of all the variables investigated. These observations are quantitatively discussed in terms of the formation and growth of a thin hydride film along the alpha-beta boundaries and a qualitative model for hydrogen induced slow crack growth is presented, based on the film-rupture model of stress corrosion cracking.

Modeling of the Bacillus subtilis Bacterial Biofilm Growing on an Agar Substrate

PubMed Central

Wang, Xiaoling; Wang, Guoqing; Hao, Mudong

2015-01-01

Bacterial biofilms are organized communities composed of millions of microorganisms that accumulate on almost any kinds of surfaces. In this paper, a biofilm growth model on an agar substrate is developed based on mass conservation principles, Fick's first law, and Monod's kinetic reaction, by considering nutrient diffusion between biofilm and agar substrate. Our results show biofilm growth evolution characteristics such as biofilm thickness, active biomass, and nutrient concentration in the agar substrate. We quantitatively obtain biofilm growth dependence on different parameters. We provide an alternative mathematical method to describe other kinds of biofilm growth such as multiple bacterial species biofilm and also biofilm growth on various complex substrates. PMID:26355542

Modeling of the Bacillus subtilis Bacterial Biofilm Growing on an Agar Substrate.

PubMed

Wang, Xiaoling; Wang, Guoqing; Hao, Mudong

2015-01-01

Bacterial biofilms are organized communities composed of millions of microorganisms that accumulate on almost any kinds of surfaces. In this paper, a biofilm growth model on an agar substrate is developed based on mass conservation principles, Fick's first law, and Monod's kinetic reaction, by considering nutrient diffusion between biofilm and agar substrate. Our results show biofilm growth evolution characteristics such as biofilm thickness, active biomass, and nutrient concentration in the agar substrate. We quantitatively obtain biofilm growth dependence on different parameters. We provide an alternative mathematical method to describe other kinds of biofilm growth such as multiple bacterial species biofilm and also biofilm growth on various complex substrates.

NASA Software Cost Estimation Model: An Analogy Based Estimation Model

NASA Technical Reports Server (NTRS)

Hihn, Jairus; Juster, Leora; Menzies, Tim; Mathew, George; Johnson, James

2015-01-01

The cost estimation of software development activities is increasingly critical for large scale integrated projects such as those at DOD and NASA especially as the software systems become larger and more complex. As an example MSL (Mars Scientific Laboratory) developed at the Jet Propulsion Laboratory launched with over 2 million lines of code making it the largest robotic spacecraft ever flown (Based on the size of the software). Software development activities are also notorious for their cost growth, with NASA flight software averaging over 50% cost growth. All across the agency, estimators and analysts are increasingly being tasked to develop reliable cost estimates in support of program planning and execution. While there has been extensive work on improving parametric methods there is very little focus on the use of models based on analogy and clustering algorithms. In this paper we summarize our findings on effort/cost model estimation and model development based on ten years of software effort estimation research using data mining and machine learning methods to develop estimation models based on analogy and clustering. The NASA Software Cost Model performance is evaluated by comparing it to COCOMO II, linear regression, and K-­ nearest neighbor prediction model performance on the same data set.

Development and application of Geobacillus stearothermophilus growth model for predicting spoilage of evaporated milk.

PubMed

Kakagianni, Myrsini; Gougouli, Maria; Koutsoumanis, Konstantinos P

2016-08-01

The presence of Geobacillus stearothermophilus spores in evaporated milk constitutes an important quality problem for the milk industry. This study was undertaken to provide an approach in modelling the effect of temperature on G. stearothermophilus ATCC 7953 growth and in predicting spoilage of evaporated milk. The growth of G. stearothermophilus was monitored in tryptone soy broth at isothermal conditions (35-67 °C). The data derived were used to model the effect of temperature on G. stearothermophilus growth with a cardinal type model. The cardinal values of the model for the maximum specific growth rate were Tmin = 33.76 °C, Tmax = 68.14 °C, Topt = 61.82 °C and μopt = 2.068/h. The growth of G. stearothermophilus was assessed in evaporated milk at Topt in order to adjust the model to milk. The efficiency of the model in predicting G. stearothermophilus growth at non-isothermal conditions was evaluated by comparing predictions with observed growth under dynamic conditions and the results showed a good performance of the model. The model was further used to predict the time-to-spoilage (tts) of evaporated milk. The spoilage of this product caused by acid coagulation when the pH approached a level around 5.2, eight generations after G. stearothermophilus reached the maximum population density (Nmax). Based on the above, the tts was predicted from the growth model as the sum of the time required for the microorganism to multiply from the initial to the maximum level ( [Formula: see text] ), plus the time required after the [Formula: see text] to complete eight generations. The observed tts was very close to the predicted one indicating that the model is able to describe satisfactorily the growth of G. stearothermophilus and to provide realistic predictions for evaporated milk spoilage. Copyright © 2016 Elsevier Ltd. All rights reserved.

Somatic growth of mussels Mytilus edulis in field studies compared to predictions using BEG, DEB, and SFG models

NASA Astrophysics Data System (ADS)

Larsen, Poul S.; Filgueira, Ramón; Riisgård, Hans Ulrik

2014-04-01

Prediction of somatic growth of blue mussels, Mytilus edulis, based on the data from 2 field-growth studies of mussels in suspended net-bags in Danish waters was made by 3 models: the bioenergetic growth (BEG), the dynamic energy budget (DEB), and the scope for growth (SFG). Here, the standard BEG model has been expanded to include the temperature dependence of filtration rate and respiration and an ad hoc modification to ensure a smooth transition to zero ingestion as chlorophyll a (chl a) concentration approaches zero, both guided by published data. The first 21-day field study was conducted at nearly constant environmental conditions with a mean chl a concentration of C = 2.7 μg L- 1, and the observed monotonous growth in the dry weight of soft parts was best predicted by DEB while BEG and SFG models produced lower growth. The second 165-day field study was affected by large variations in chl a and temperature, and the observed growth varied accordingly, but nevertheless, DEB and SFG predicted monotonous growth in good agreement with the mean pattern while BEG mimicked the field data in response to observed changes in chl a concentration and temperature. The general features of the models were that DEB produced the best average predictions, SFG mostly underestimated growth, whereas only BEG was sensitive to variations in chl a concentration and temperature. DEB and SFG models rely on the calibration of the half-saturation coefficient to optimize the food ingestion function term to that of observed growth, and BEG is independent of observed actual growth as its predictions solely rely on the time history of the local chl a concentration and temperature.

On System Engineering a Barter-Based Re-allocation of Space System Key Development Resources

NASA Astrophysics Data System (ADS)

Kosmann, William J.

NASA has had a decades-long problem with cost growth during the development of space science missions. Numerous agency-sponsored studies have produced average mission level development cost growths ranging from 23 to 77%. A new study of 26 historical NASA science instrument set developments using expert judgment to re-allocate key development resources has an average cost growth of 73.77%. Twice in history, during the Cassini and EOS-Terra science instrument developments, a barter-based mechanism has been used to re-allocate key development resources. The mean instrument set development cost growth was -1.55%. Performing a bivariate inference on the means of these two distributions, there is statistical evidence to support the claim that using a barter-based mechanism to re-allocate key instrument development resources will result in a lower expected cost growth than using the expert judgment approach. Agent-based discrete event simulation is the natural way to model a trade environment. A NetLogo agent-based barter-based simulation of science instrument development was created. The agent-based model was validated against the Cassini historical example, as the starting and ending instrument development conditions are available. The resulting validated agent-based barter-based science instrument resource re-allocation simulation was used to perform 300 instrument development simulations, using barter to re-allocate development resources. The mean cost growth was -3.365%. A bivariate inference on the means was performed to determine that additional significant statistical evidence exists to support a claim that using barter-based resource re-allocation will result in lower expected cost growth, with respect to the historical expert judgment approach. Barter-based key development resource re-allocation should work on science spacecraft development as well as it has worked on science instrument development. A new study of 28 historical NASA science spacecraft developments has an average cost growth of 46.04%. As barter-based key development resource re-allocation has never been tried in a spacecraft development, no historical results exist, and an inference on the means test is not possible. A simulation of using barter-based resource re-allocation should be developed. The NetLogo instrument development simulation should be modified to account for spacecraft development market participant differences. The resulting agent-based barter-based spacecraft resource re-allocation simulation would then be used to determine if significant statistical evidence exists to prove a claim that using barter-based resource re-allocation will result in lower expected cost growth.

Growth and mortality of larval sunfish in backwaters of the upper Mississippi River

USGS Publications Warehouse

Zigler, S.J.; Jennings, C.A.

1993-01-01

The authors estimated the growth and mortality of larval sunfish Lepomis spp. in backwater habitats of the upper Mississippi River with an otolith-based method and a length-based method. Fish were sampled with plankton nets at one station in Navigation Pools 8 and 14 in 1989 and at two stations in Pool 8 in 1990. For both methods, growth was modeled with an exponential equation, and instantaneous mortality was estimated by regressing the natural logarithm of fish catch for each 1-mm size-group against the estimated age of the group, which was derived from the growth equations. At two of the stations, the otolith-based method provided more precise estimates of sunfish growth than the length-based method. We were able to compare length-based and otolith-based estimates of sunfish mortality only at the two stations where we caught the largest numbers of sunfish. Estimates of mortality were similar for both methods in Pool 14, where catches were higher, but the length-based method gave significantly higher estimates in Pool 8, where the catches were lower. The otolith- based method required more laboratory analysis, but provided better estimates of the growth and mortality than the length-based method when catches were low. However, the length-based method was more cost- effective for estimating growth and mortality when catches were large.

Crystal plasticity modeling of irradiation growth in Zircaloy-2

DOE PAGES

Patra, Anirban; Tome, Carlos; Golubov, Stanislav I.

2017-05-10

A reaction-diffusion based mean field rate theory model is implemented in the viscoplastic self-consistent (VPSC) crystal plasticity framework to simulate irradiation growth in hcp Zr and its alloys. A novel scheme is proposed to model the evolution (both number density and radius) of irradiation-induced dislocation loops that can be informed directly from experimental data of dislocation density evolution during irradiation. This framework is used to predict the irradiation growth behavior of cold-worked Zircaloy-2 and trends compared to available experimental data. The role of internal stresses in inducing irradiation creep is discussed. Effects of grain size, texture, and external stress onmore » the coupled irradiation growth and creep behavior are also studied.« less

Crystal plasticity modeling of irradiation growth in Zircaloy-2

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

Patra, Anirban; Tome, Carlos; Golubov, Stanislav I.

A reaction-diffusion based mean field rate theory model is implemented in the viscoplastic self-consistent (VPSC) crystal plasticity framework to simulate irradiation growth in hcp Zr and its alloys. A novel scheme is proposed to model the evolution (both number density and radius) of irradiation-induced dislocation loops that can be informed directly from experimental data of dislocation density evolution during irradiation. This framework is used to predict the irradiation growth behavior of cold-worked Zircaloy-2 and trends compared to available experimental data. The role of internal stresses in inducing irradiation creep is discussed. Effects of grain size, texture, and external stress onmore » the coupled irradiation growth and creep behavior are also studied.« less

Mathematical modeling of ethanol production in solid-state fermentation based on solid medium' dry weight variation.

PubMed

Mazaheri, Davood; Shojaosadati, Seyed Abbas; Zamir, Seyed Morteza; Mousavi, Seyyed Mohammad

2018-04-21

In this work, mathematical modeling of ethanol production in solid-state fermentation (SSF) has been done based on the variation in the dry weight of solid medium. This method was previously used for mathematical modeling of enzyme production; however, the model should be modified to predict the production of a volatile compound like ethanol. The experimental results of bioethanol production from the mixture of carob pods and wheat bran by Zymomonas mobilis in SSF were used for the model validation. Exponential and logistic kinetic models were used for modeling the growth of microorganism. In both cases, the model predictions matched well with the experimental results during the exponential growth phase, indicating the good ability of solid medium weight variation method for modeling a volatile product formation in solid-state fermentation. In addition, using logistic model, better predictions were obtained.

Visualized modeling platform for virtual plant growth and monitoring on the internet

NASA Astrophysics Data System (ADS)

Zhou, De-fu; Tian, Feng-qui; Ren, Ping

2009-07-01

Virtual plant growth is a key research topic in Agriculture Information Technique and Computer Graphics. It has been applied in botany, agronomy, environmental sciences, computre sciences and applied mathematics. Modeling leaf color dynamics in plant is of significant importance for realizing virtual plant growth. Using systematic analysis method and dynamic modeling technology, a SPAD-based leaf color dynamic model was developed to simulate time-course change characters of leaf SPAD on the plant. In addition, process of plant growth can be computer-stimulated using Virtual Reality Modeling Language (VRML) to establish a vivid and visible model, including shooting, rooting, blooming, as well as growth of the stems and leaves. In the resistance environment, e.g., lacking of water, air or nutrient substances, high salt or alkaline, freezing injury, high temperature, suffering from diseases and insect pests, the changes from the level of whole plant to organs, tissues and cells could be computer-stimulated. Changes from physiological and biochemistry could also be described. When a series of indexes were input by the costumers, direct view and microcosmic changes could be shown. Thus, the model has a good performance in predicting growth condition of the plant, laying a foundation for further constructing virtual plant growth system. The results revealed that realistic physiological and pathological processes of 3D virtual plants could be demonstrated by proper design and effectively realized in the internet.

A multiphysics 3D model of tissue growth under interstitial perfusion in a tissue-engineering bioreactor.

PubMed

Nava, Michele M; Raimondi, Manuela T; Pietrabissa, Riccardo

2013-11-01

The main challenge in engineered cartilage consists in understanding and controlling the growth process towards a functional tissue. Mathematical and computational modelling can help in the optimal design of the bioreactor configuration and in a quantitative understanding of important culture parameters. In this work, we present a multiphysics computational model for the prediction of cartilage tissue growth in an interstitial perfusion bioreactor. The model consists of two separate sub-models, one two-dimensional (2D) sub-model and one three-dimensional (3D) sub-model, which are coupled between each other. These sub-models account both for the hydrodynamic microenvironment imposed by the bioreactor, using a model based on the Navier-Stokes equation, the mass transport equation and the biomass growth. The biomass, assumed as a phase comprising cells and the synthesised extracellular matrix, has been modelled by using a moving boundary approach. In particular, the boundary at the fluid-biomass interface is moving with a velocity depending from the local oxygen concentration and viscous stress. In this work, we show that all parameters predicted, such as oxygen concentration and wall shear stress, by the 2D sub-model with respect to the ones predicted by the 3D sub-model are systematically overestimated and thus the tissue growth, which directly depends on these parameters. This implies that further predictive models for tissue growth should take into account of the three dimensionality of the problem for any scaffold microarchitecture.

An energy budget agent-based model of earthworm populations and its application to study the effects of pesticides

PubMed Central

Johnston, A.S.A.; Hodson, M.E.; Thorbek, P.; Alvarez, T.; Sibly, R.M.

2014-01-01

Earthworms are important organisms in soil communities and so are used as model organisms in environmental risk assessments of chemicals. However current risk assessments of soil invertebrates are based on short-term laboratory studies, of limited ecological relevance, supplemented if necessary by site-specific field trials, which sometimes are challenging to apply across the whole agricultural landscape. Here, we investigate whether population responses to environmental stressors and pesticide exposure can be accurately predicted by combining energy budget and agent-based models (ABMs), based on knowledge of how individuals respond to their local circumstances. A simple energy budget model was implemented within each earthworm Eisenia fetida in the ABM, based on a priori parameter estimates. From broadly accepted physiological principles, simple algorithms specify how energy acquisition and expenditure drive life cycle processes. Each individual allocates energy between maintenance, growth and/or reproduction under varying conditions of food density, soil temperature and soil moisture. When simulating published experiments, good model fits were obtained to experimental data on individual growth, reproduction and starvation. Using the energy budget model as a platform we developed methods to identify which of the physiological parameters in the energy budget model (rates of ingestion, maintenance, growth or reproduction) are primarily affected by pesticide applications, producing four hypotheses about how toxicity acts. We tested these hypotheses by comparing model outputs with published toxicity data on the effects of copper oxychloride and chlorpyrifos on E. fetida. Both growth and reproduction were directly affected in experiments in which sufficient food was provided, whilst maintenance was targeted under food limitation. Although we only incorporate toxic effects at the individual level we show how ABMs can readily extrapolate to larger scales by providing good model fits to field population data. The ability of the presented model to fit the available field and laboratory data for E. fetida demonstrates the promise of the agent-based approach in ecology, by showing how biological knowledge can be used to make ecological inferences. Further work is required to extend the approach to populations of more ecologically relevant species studied at the field scale. Such a model could help extrapolate from laboratory to field conditions and from one set of field conditions to another or from species to species. PMID:25844009

A formulation of multidimensional growth models for the assessment and forecast of technology attributes

NASA Astrophysics Data System (ADS)

Danner, Travis W.

Developing technology systems requires all manner of investment---engineering talent, prototypes, test facilities, and more. Even for simple design problems the investment can be substantial; for complex technology systems, the development costs can be staggering. The profitability of a corporation in a technology-driven industry is crucially dependent on maximizing the effectiveness of research and development investment. Decision-makers charged with allocation of this investment are forced to choose between the further evolution of existing technologies and the pursuit of revolutionary technologies. At risk on the one hand is excessive investment in an evolutionary technology which has only limited availability for further improvement. On the other hand, the pursuit of a revolutionary technology may mean abandoning momentum and the potential for substantial evolutionary improvement resulting from the years of accumulated knowledge. The informed answer to this question, evolutionary or revolutionary, requires knowledge of the expected rate of improvement and the potential a technology offers for further improvement. This research is dedicated to formulating the assessment and forecasting tools necessary to acquire this knowledge. The same physical laws and principles that enable the development and improvement of specific technologies also limit the ultimate capability of those technologies. Researchers have long used this concept as the foundation for modeling technological advancement through extrapolation by analogy to biological growth models. These models are employed to depict technology development as it asymptotically approaches limits established by the fundamental principles on which the technological approach is based. This has proven an effective and accurate approach to modeling and forecasting simple single-attribute technologies. With increased system complexity and the introduction of multiple system objectives, however, the usefulness of this modeling technique begins to diminish. With the introduction of multiple objectives, researchers often abandon technology growth models for scoring models and technology frontiers. While both approaches possess advantages over current growth models for the assessment of multi-objective technologies, each lacks a necessary dimension for comprehensive technology assessment. By collapsing multiple system metrics into a single, non-intuitive technology measure, scoring models provide a succinct framework for multi-objective technology assessment and forecasting. Yet, with no consideration of physical limits, scoring models provide no insight as to the feasibility of a particular combination of system capabilities. They only indicate that a given combination of system capabilities yields a particular score. Conversely, technology frontiers are constructed with the distinct objective of providing insight into the feasibility of system capability combinations. Yet again, upper limits to overall system performance are ignored. Furthermore, the data required to forecast subsequent technology frontiers is often inhibitive. In an attempt to reincorporate the fundamental nature of technology advancement as bound by physical principles, researchers have sought to normalize multi-objective systems whereby the variability of a single system objective is eliminated as a result of changes in the remaining objectives. This drastically limits the applicability of the resulting technology model because it is only applicable for a single setting of all other system attributes. Attempts to maintain the interaction between the growth curves of each technical objective of a complex system have thus far been limited to qualitative and subjective consideration. This research proposes the formulation of multidimensional growth models as an approach to simulating the advancement of multi-objective technologies towards their upper limits. Multidimensional growth models were formulated by noticing and exploiting the correlation between technology growth models and technology frontiers. Both are frontiers in actuality. The technology growth curve is a frontier between capability levels of a single attribute and time, while a technology frontier is a frontier between the capability levels of two or more attributes. Multidimensional growth models are formulated by exploiting the mathematical significance of this correlation. The result is a model that can capture both the interaction between multiple system attributes and their expected rates of improvement over time. The fundamental nature of technology development is maintained, and interdependent growth curves are generated for each system metric with minimal data requirements. Being founded on the basic nature of technology advancement, relative to physical limits, the availability for further improvement can be determined for a single metric relative to other system measures of merit. A by-product of this modeling approach is a single n-dimensional technology frontier linking all n system attributes with time. This provides an environment capable of forecasting future system capability in the form of advancing technology frontiers. The ability of a multidimensional growth model to capture the expected improvement of a specific technological approach is dependent on accurately identifying the physical limitations to each pertinent attribute. This research investigates two potential approaches to identifying those physical limits, a physics-based approach and a regression-based approach. The regression-based approach has found limited acceptance among forecasters, although it does show potential for estimating upper limits with a specified degree of uncertainty. Forecasters have long favored physics-based approaches for establishing the upper limit to unidimensional growth models. The task of accurately identifying upper limits has become increasingly difficult with the extension of growth models into multiple dimensions. A lone researcher may be able to identify the physical limitation to a single attribute of a simple system; however, as system complexity and the number of attributes increases, the attention of researchers from multiple fields of study is required. Thus, limit identification is itself an area of research and development requiring some level of investment. Whether estimated by physics or regression-based approaches, predicted limits will always have some degree of uncertainty. This research takes the approach of quantifying the impact of that uncertainty on model forecasts rather than heavily endorsing a single technique to limit identification. In addition to formulating the multidimensional growth model, this research provides a systematic procedure for applying that model to specific technology architectures. Researchers and decision-makers are able to investigate the potential for additional improvement within that technology architecture and to estimate the expected cost of each incremental improvement relative to the cost of past improvements. In this manner, multidimensional growth models provide the necessary information to set reasonable program goals for the further evolution of a particular technological approach or to establish the need for revolutionary approaches in light of the constraining limits of conventional approaches.

Measurements of Protein Crystal Face Growth Rates

NASA Technical Reports Server (NTRS)

Gorti, S.

2014-01-01

Protein crystal growth rates will be determined for several hyperthermophile proteins.; The growth rates will be assessed using available theoretical models, including kinetic roughening.; If/when kinetic roughening supersaturations are established, determinations of protein crystal quality over a range of supersaturations will also be assessed.; The results of our ground based effort may well address the existence of a correlation between fundamental growth mechanisms and protein crystal quality.

[Cultural regionalization for Notopterygium incisum based on 3S technology platform. I. Evaluation for growth suitability for N. incisum based on ecological factors analysis by Maxent and ArcGIS model].

PubMed

Sun, Hong-bing; Sun, Hui; Jiang, Shun-yuan; Zhou, Yi; Cao, Wen-long; Ji, Ming-chang; Zhy, Wen-tao; Yan, Han-jing

2015-03-01

Growth suitability as assessment indicators for medicinal plants cultivation was proposed based on chemical quality determination and ecological factors analysis by Maxent and ArcGIS model. Notopterygium incisum, an endangered Chinese medicinal plant, was analyzed as a case, its potential distribution areas at different suitability grade and regionalization map were formulated based on growth suitability theory. The results showed that the most suitable habitats is Sichuan province, and more than 60% of the most suitable areawas located in the western Sichuan such as Aba and Ganzi prefectures for N. incisum. The results indicated that habitat altitude, average air temperature in September, and vegetation types were the dominant factors contributing to the grade of plant growth, precipitation and slope were the major factors contributing to notopterol accumulation in its underground parts, while isoimperatorin in its underground parts was negatively corelated with precipitation and slope of its habitat. However, slope as a factor influencing chemical components seemed to be a pseudo corelationship. Therefore, there were distinguishing differences between growth suitability and quality suitability for medicinal plants, which was helpful to further research and practice of cultivation regionalization, wild resource monitoring and large-scale cultivation of traditional Chinese medicine plants.

Modelling breast cancer tumour growth for a stable disease population.

PubMed

Isheden, Gabriel; Humphreys, Keith

2017-01-01

Statistical models of breast cancer tumour progression have been used to further our knowledge of the natural history of breast cancer, to evaluate mammography screening in terms of mortality, to estimate overdiagnosis, and to estimate the impact of lead-time bias when comparing survival times between screen detected cancers and cancers found outside of screening programs. Multi-state Markov models have been widely used, but several research groups have proposed other modelling frameworks based on specifying an underlying biological continuous tumour growth process. These continuous models offer some advantages over multi-state models and have been used, for example, to quantify screening sensitivity in terms of mammographic density, and to quantify the effect of body size covariates on tumour growth and time to symptomatic detection. As of yet, however, the continuous tumour growth models are not sufficiently developed and require extensive computing to obtain parameter estimates. In this article, we provide a detailed description of the underlying assumptions of the continuous tumour growth model, derive new theoretical results for the model, and show how these results may help the development of this modelling framework. In illustrating the approach, we develop a model for mammography screening sensitivity, using a sample of 1901 post-menopausal women diagnosed with invasive breast cancer.

Dissecting a new connection between cytokinin and jasmonic acid in control of leaf growth

USDA-ARS?s Scientific Manuscript database

Plant growth is mediated by two cellular processes: division and elongation. The maize leaf is an excellent model to study plant growth since these processes are spatially separated into discreet zones - a division zone (DZ), transition zone (TZ), and elongation zone (EZ) - at the base of the leaf. ...

Empirically Derived Optimal Growth Equations For Hardwoods and Softwoods in Arkansas

Treesearch

Don C. Bragg

2002-01-01

Accurate growth projections are critical to reliable forest models, and ecologically based simulators can improve siivicultural predictions because of their sensitivity to change and their capacity to produce long-term forecasts. Potential relative increment (PRI) optimal diameter growth equations for loblolly pine, shortleaf pine, sweetgum, and white oak were fit to...

The Growth of Tense Productivity

ERIC Educational Resources Information Center

Rispoli, Matthew; Hadley, Pamela A.; Holt, Janet K.

2009-01-01

Purpose: This study tests empirical predictions of a maturational model for the growth of tense in children younger than 36 months using a type-based productivity measure. Method: Caregiver-child language samples were collected from 20 typically developing children every 3 months from 21 to 33 months of age. Growth in the productivity of tense…

Can Higher Education Foster Economic Growth? Chicago Fed Letter. Number 229

ERIC Educational Resources Information Center

Mattoon, Richard H.

2006-01-01

Not all observers agree that higher education and economic growth are obvious or necessary complements to each other. The controversy may be exacerbated because of the difficulty of measuring the exact contribution of colleges and universities to economic growth. Recognizing that a model based on local conditions and higher education's response…

2D Process-based Microbialite Growth Model

NASA Astrophysics Data System (ADS)

Airo, A.; Smith, A.

2007-12-01

A 2D process-based microbialite growth model (MGM) has been developed that integrates the coupled effects of the microbialite growth and sediment distribution within a two-dimensional cross-section of a subaqueous bedrock profile. Sediment transport is realized through particle erosion and deposition that are a function of local wave energy which is computed on the basis of linear wave theory. Surface-normal microbialite growth is directly correlated to light intensity, which is computed for every point of the microbialite surface by using a Henyey- Greenstein-type relation for scattering and the Beer's Law for absorption in the water column. Shadowing effects by surrounding obstacles and/or overlying sediment are also considered. Sediment particles can be incorporated into the microbialite framework if growth occurs in the presence of sediment. The resulting meter-size microbialite constructs develop morphologies that correspond well to natural microbialites. Furthermore, changes of environmental factors such as light intensity, wave energy, and bedrock profile result in morphological variations of the microbialites that would be expected on the basis of the current understanding of microbialite growth and development.

A Model of Differential Growth-Guided Apical Hook Formation in Plants

PubMed Central

Žádníková, Petra; Wabnik, Krzysztof; Abuzeineh, Anas; Prusinkiewicz, Przemysław

2016-01-01

Differential cell growth enables flexible organ bending in the presence of environmental signals such as light or gravity. A prominent example of the developmental processes based on differential cell growth is the formation of the apical hook that protects the fragile shoot apical meristem when it breaks through the soil during germination. Here, we combined in silico and in vivo approaches to identify a minimal mechanism producing auxin gradient-guided differential growth during the establishment of the apical hook in the model plant Arabidopsis thaliana. Computer simulation models based on experimental data demonstrate that asymmetric expression of the PIN-FORMED auxin efflux carrier at the concave (inner) versus convex (outer) side of the hook suffices to establish an auxin maximum in the epidermis at the concave side of the apical hook. Furthermore, we propose a mechanism that translates this maximum into differential growth, and thus curvature, of the apical hook. Through a combination of experimental and in silico computational approaches, we have identified the individual contributions of differential cell elongation and proliferation to defining the apical hook and reveal the role of auxin-ethylene crosstalk in balancing these two processes. PMID:27754878

Selecting Populations for Non-Analogous Climate Conditions Using Universal Response Functions: The Case of Douglas-Fir in Central Europe.

PubMed

Chakraborty, Debojyoti; Wang, Tongli; Andre, Konrad; Konnert, Monika; Lexer, Manfred J; Matulla, Christoph; Schueler, Silvio

2015-01-01

Identifying populations within tree species potentially adapted to future climatic conditions is an important requirement for reforestation and assisted migration programmes. Such populations can be identified either by empirical response functions based on correlations of quantitative traits with climate variables or by climate envelope models that compare the climate of seed sources and potential growing areas. In the present study, we analyzed the intraspecific variation in climate growth response of Douglas-fir planted within the non-analogous climate conditions of Central and continental Europe. With data from 50 common garden trials, we developed Universal Response Functions (URF) for tree height and mean basal area and compared the growth performance of the selected best performing populations with that of populations identified through a climate envelope approach. Climate variables of the trial location were found to be stronger predictors of growth performance than climate variables of the population origin. Although the precipitation regime of the population sources varied strongly none of the precipitation related climate variables of population origin was found to be significant within the models. Overall, the URFs explained more than 88% of variation in growth performance. Populations identified by the URF models originate from western Cascades and coastal areas of Washington and Oregon and show significantly higher growth performance than populations identified by the climate envelope approach under both current and climate change scenarios. The URFs predict decreasing growth performance at low and middle elevations of the case study area, but increasing growth performance on high elevation sites. Our analysis suggests that population recommendations based on empirical approaches should be preferred and population selections by climate envelope models without considering climatic constrains of growth performance should be carefully appraised before transferring populations to planting locations with novel or dissimilar climate.

A three-dimensional phase field model for nanowire growth by the vapor-liquid-solid mechanism

NASA Astrophysics Data System (ADS)

Wang, Yanming; Ryu, Seunghwa; McIntyre, Paul C.; Cai, Wei

2014-07-01

We present a three-dimensional multi-phase field model for catalyzed nanowire (NW) growth by the vapor-liquid-solid (VLS) mechanism. The equation of motion contains both a Ginzburg-Landau term for deposition and a diffusion (Cahn-Hilliard) term for interface relaxation without deposition. Direct deposition from vapor to solid, which competes with NW crystal growth through the molten catalyst droplet, is suppressed by assigning a very small kinetic coefficient at the solid-vapor interface. The thermodynamic self-consistency of the model is demonstrated by its ability to reproduce the equilibrium contact angles at the VLS junction. The incorporation of orientation dependent gradient energy leads to faceting of the solid-liquid and solid-vapor interfaces. The model successfully captures the curved shape of the NW base and the Gibbs-Thomson effect on growth velocity.

Dynamic energy budget model: a monitoring tool for growth and reproduction performance of Mytilus galloprovincialis in Bizerte Lagoon (Southwestern Mediterranean Sea).

PubMed

Béjaoui-Omri, Amel; Béjaoui, Béchir; Harzallah, Ali; Aloui-Béjaoui, Nejla; El Bour, Monia; Aleya, Lotfi

2014-11-01

Mussel farming is the main economic activity in Bizerte Lagoon, with a production that fluctuates depending on environmental factors. In the present study, we apply a bioenergetic growth model to the mussel Mytilus galloprovincialis, based on dynamic energy budget (DEB) theory which describes energy flux variation through the different compartments of the mussel body. Thus, the present model simulates both mussel growth and sexual cycle steps according to food availability and water temperature and also the effect of climate change on mussel behavior and reproduction. The results point to good concordance between simulations and growth parameters (metric length and weight) for mussels in the lagoon. A heat wave scenario was also simulated using the DEB model, which highlighted mussel mortality periods during a period of high temperature.

An unstructured mathematical model for growth of Pleurotus ostreatus on lignocellulosic material in solid-state fermentation systems

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

Sarikaya, A.; Ladisch, M.R.

1997-01-01

Inedible plant material, generated in a Controlled Ecological Life Support System (CELSS), should be recycled preferably by bioregenerative methods that utilize enzymes or micro-organisms. This material consists of hemicellulose, cellulose, and lignin with the lignin fraction representing a recalcitrant component that is not readily treated by enzymatic methods. Consequently, the white-rot fungus, Pleurotus ostreatus, is attractive since it effectively degrades lignin and produces edible mushrooms. This work describes an unstructured model for the growth of P. ostreatus in a solid-state fermentation system using lignocellulosic plant materials from Brassica napus (rapeseed) as a substrate at three different particle sizes. A logisticmore » function model based on area was found to fit the surface growth of the mycelium on the solid substrate with respect to time, whereas a model based on diameter, alone, did not fit the data as well. The difference between the two measures of growth was also evident for mycelial growth in a bioreactor designed to facilitate a slow flowrate of air through the 1.5 cm thick mat of lignocellulosic biomass particles. The result is consistent with the concept of competition of the mycelium for the substrate that surrounds it, rather than just substrate that is immediately available to single cells. This approach provides a quantitative measure of P. ostreatus growth on lignocellulosic biomass in a solid-state fermentation system. The experimental data show that the best growth is obtained for the largest particles (1 cm) of the lignocellulosic substrate. 13 refs., 6 figs., 2 tabs.« less

Hygroscopic aerosol deposition in the human upper respiratory tract under various thermo-humidity conditions.

PubMed

Xi, Jinxiang; Kim, Jongwon; Si, Xiuhua A; Zhou, Yue

2013-01-01

The deposition of hygroscopic aerosols is highly complex in nature, which results from a cumulative effect of dynamic particle growth and the real-time size-specific deposition mechanisms. The objective of this study is to evaluate hygroscopic effects on the particle growth, transport, and deposition of nasally inhaled aerosols across a range of 0.2-2.5 μm in an adult image-based nose-throat model. Temperature and relative humidity fields were simulated using the LRN k-ω turbulence model and species transport model under a spectrum of thermo-humidity conditions. Particle growth and transport were simulated using a well validated Lagrangian tracking model coupled with a user-defined hygroscopic growth module. Results of this study indicate that the saturation level and initial particle size are the two major factors that determine the particle growth rate (d/d0), while the effect of inhalation flow rate is found to be not significant. An empirical correlation of condensation growth of nasally inhaled hygroscopic aerosols in adults has been developed based on a variety of thermo-humidity inhalation conditions. Significant elevated nasal depositions of hygroscopic aerosols could be induced by condensation growth for both sub-micrometer and small micrometer particulates. In particular, the deposition of initially 2.5 μm hygroscopic aerosols was observed to be 5-8 times that of inert particles under warm to hot saturated conditions. Results of this study have important implications in exposure assessment in hot humid environments, where much higher risks may be expected compared to normal conditions.

Modelling foetal growth in a bi-ethnic sample: results from the Born in Bradford (BiB) birth cohort.

PubMed

Norris, Tom; Tuffnell, Derek; Wright, John; Cameron, Noël

2014-01-01

Attempts to explain the increased risk for metabolic disorders observed in South Asians have focused on the "South Asian" phenotype at birth and subsequent post-natal growth, with little research on pre-natal growth. To identify whether divergent growth patterns exist for foetal weight, head (HC) and abdominal circumferences (AC) in a sample of Pakistani and White British foetuses. Models were based on 5553 (weight), 5154 (HC) and 5099 (AC) foetuses from the Born in Bradford birth cohort. Fractional polynomials and mixed effects models were employed to determine growth patterns from ~15 weeks of gestation-birth. Pakistani foetuses were significantly smaller and lighter as early as 20 weeks. However, there was no ethnic difference in the growth patterns of weight and HC. For AC, Pakistani foetuses displayed a trend for reduced growth in the final trimester. As the pattern of weight and HC growth was not significantly different during the period under investigation, the mechanism culminating in the reduced Pakistani size at birth may act earlier in gestation. Reduced AC growth in Pakistanis may represent reduced growth of the visceral organs, with consequences for post-natal liver metabolism and renal function.

Determining individual variation in growth and its implication for life-history and population processes using the empirical Bayes method.

PubMed

Vincenzi, Simone; Mangel, Marc; Crivelli, Alain J; Munch, Stephan; Skaug, Hans J

2014-09-01

The differences in demographic and life-history processes between organisms living in the same population have important consequences for ecological and evolutionary dynamics. Modern statistical and computational methods allow the investigation of individual and shared (among homogeneous groups) determinants of the observed variation in growth. We use an Empirical Bayes approach to estimate individual and shared variation in somatic growth using a von Bertalanffy growth model with random effects. To illustrate the power and generality of the method, we consider two populations of marble trout Salmo marmoratus living in Slovenian streams, where individually tagged fish have been sampled for more than 15 years. We use year-of-birth cohort, population density during the first year of life, and individual random effects as potential predictors of the von Bertalanffy growth function's parameters k (rate of growth) and L∞ (asymptotic size). Our results showed that size ranks were largely maintained throughout marble trout lifetime in both populations. According to the Akaike Information Criterion (AIC), the best models showed different growth patterns for year-of-birth cohorts as well as the existence of substantial individual variation in growth trajectories after accounting for the cohort effect. For both populations, models including density during the first year of life showed that growth tended to decrease with increasing population density early in life. Model validation showed that predictions of individual growth trajectories using the random-effects model were more accurate than predictions based on mean size-at-age of fish.

A comparison of scope for growth (SFG) and dynamic energy budget (DEB) models applied to the blue mussel ( Mytilus edulis)

NASA Astrophysics Data System (ADS)

Filgueira, Ramón; Rosland, Rune; Grant, Jon

2011-11-01

Growth of Mytilus edulis was simulated using individual based models following both Scope For Growth (SFG) and Dynamic Energy Budget (DEB) approaches. These models were parameterized using independent studies and calibrated for each dataset by adjusting the half-saturation coefficient of the food ingestion function term, XK, a common parameter in both approaches related to feeding behavior. Auto-calibration was carried out using an optimization tool, which provides an objective way of tuning the model. Both approaches yielded similar performance, suggesting that although the basis for constructing the models is different, both can successfully reproduce M. edulis growth. The good performance of both models in different environments achieved by adjusting a single parameter, XK, highlights the potential of these models for (1) producing prospective analysis of mussel growth and (2) investigating mussel feeding response in different ecosystems. Finally, we emphasize that the convergence of two different modeling approaches via calibration of XK, indicates the importance of the feeding behavior and local trophic conditions for bivalve growth performance. Consequently, further investigations should be conducted to explore the relationship of XK to environmental variables and/or to the sophistication of the functional response to food availability with the final objective of creating a general model that can be applied to different ecosystems without the need for calibration.

BATTLE: Biomarker-Based Approaches of Targeted Therapy for Lung Cancer Elimination

DTIC Science & Technology

2007-04-01

localization, which • The combination of erlotinib and Ad-dnIGF-1R synergistically inhibits the growth of tumors in xenograft mouse models . able outcomes...of erlotinib and Ad-dnIGF-1R synergistically inhibits the growth of tumors in xenograft mouse models . Specific Aim 2.3: To investigate the...biomarkers and adaptive randomization via hierarchical Bayes modeling . 2) To study the molecular mechanisms of response and resistance to targeted

Examining the effect of down regulation under high [CO2] on the growth of soybean assimilating a semi process-based model and FACE data

NASA Astrophysics Data System (ADS)

Sakurai, G.; Iizumi, T.; Yokozawa, M.

2011-12-01

The actual impact of elevated [CO2] with the interaction of the other climatic factors on the crop growth is still debated. In many process-based crop models, the response of photosynthesis per single leaf to environmental factors is basically described using the biochemical model of Farquhar et al. (1980). However, the decline in photosynthetic enhancement known as down regulation has not been taken into account. On the other hand, the mechanisms causing photosynthetic down regulation is still unknown, which makes it difficult to include the effect of down regulation into process-based crop models. The current results of Free-air CO2 enrichment (FACE) experiments have reported the effect of down regulation under actual environments. One of the effective approaches to involve these results into future crop yield prediction is developing a semi process-based crop growth model, which includes the effect of photosynthetic down regulation as a statistical model, and assimilating the data obtained in FACE experiments. In this study, we statistically estimated the parameters of a semi process-based model for soybean growth ('SPM-soybean') using a hierarchical Baysian method with the FACE data on soybeans (Morgan et al. 2005). We also evaluated the effect of down regulation on the soybean yield in future climatic conditions. The model selection analysis showed that the effective correction to the overestimation of the Farquhar's biochemical C3 model was to reduce the maximum rate of carboxylation (Vcmax) under elevated [CO2]. However, interestingly, the difference in the estimated final crop yields between the corrected model and the non-corrected model was very slight (Fig.1a) for future projection under climate change scenario (Miroc-ESM). This was due to that the reduction in Vcmax also brought about the reduction of the base dark respiration rate of leaves. Because the dark respiration rate exponentially increases with temperature, the slight difference in base respiration rate becomes a large difference under high temperature under the future climate scenarios. In other words, if the temperature rise is very small or zero under elevated [CO2] condition, the effect of down regulation significantly appears (Fig.1b). This result suggest that further experimental data that considering high CO2 effect and high temperature effect in field conditions should be important and elaborate the model projection of the future crop yield through data assimilation method.

Cellular automata-based modelling and simulation of biofilm structure on multi-core computers.

PubMed

Skoneczny, Szymon

2015-01-01

The article presents a mathematical model of biofilm growth for aerobic biodegradation of a toxic carbonaceous substrate. Modelling of biofilm growth has fundamental significance in numerous processes of biotechnology and mathematical modelling of bioreactors. The process following double-substrate kinetics with substrate inhibition proceeding in a biofilm has not been modelled so far by means of cellular automata. Each process in the model proposed, i.e. diffusion of substrates, uptake of substrates, growth and decay of microorganisms and biofilm detachment, is simulated in a discrete manner. It was shown that for flat biofilm of constant thickness, the results of the presented model agree with those of a continuous model. The primary outcome of the study was to propose a mathematical model of biofilm growth; however a considerable amount of focus was also placed on the development of efficient algorithms for its solution. Two parallel algorithms were created, differing in the way computations are distributed. Computer programs were created using OpenMP Application Programming Interface for C++ programming language. Simulations of biofilm growth were performed on three high-performance computers. Speed-up coefficients of computer programs were compared. Both algorithms enabled a significant reduction of computation time. It is important, inter alia, in modelling and simulation of bioreactor dynamics.

Fatigue reliability of deck structures subjected to correlated crack growth

NASA Astrophysics Data System (ADS)

Feng, G. Q.; Garbatov, Y.; Guedes Soares, C.

2013-12-01

The objective of this work is to analyse fatigue reliability of deck structures subjected to correlated crack growth. The stress intensity factors of the correlated cracks are obtained by finite element analysis and based on which the geometry correction functions are derived. The Monte Carlo simulations are applied to predict the statistical descriptors of correlated cracks based on the Paris-Erdogan equation. A probabilistic model of crack growth as a function of time is used to analyse the fatigue reliability of deck structures accounting for the crack propagation correlation. A deck structure is modelled as a series system of stiffened panels, where a stiffened panel is regarded as a parallel system composed of plates and are longitudinal. It has been proven that the method developed here can be conveniently applied to perform the fatigue reliability assessment of structures subjected to correlated crack growth.

Linking stem cell function and growth pattern of intestinal organoids.

PubMed

Thalheim, Torsten; Quaas, Marianne; Herberg, Maria; Braumann, Ulf-Dietrich; Kerner, Christiane; Loeffler, Markus; Aust, Gabriela; Galle, Joerg

2018-01-15

Intestinal stem cells (ISCs) require well-defined signals from their environment in order to carry out their specific functions. Most of these signals are provided by neighboring cells that form a stem cell niche, whose shape and cellular composition self-organize. Major features of this self-organization can be studied in ISC-derived organoid culture. In this system, manipulation of essential pathways of stem cell maintenance and differentiation results in well-described growth phenotypes. We here provide an individual cell-based model of intestinal organoids that enables a mechanistic explanation of the observed growth phenotypes. In simulation studies of the 3D structure of expanding organoids, we investigate interdependences between Wnt- and Notch-signaling which control the shape of the stem cell niche and, thus, the growth pattern of the organoids. Similar to in vitro experiments, changes of pathway activities alter the cellular composition of the organoids and, thereby, affect their shape. Exogenous Wnt enforces transitions from branched into a cyst-like growth pattern; known to occur spontaneously during long term organoid expansion. Based on our simulation results, we predict that the cyst-like pattern is associated with biomechanical changes of the cells which assign them a growth advantage. The results suggest ongoing stem cell adaptation to in vitro conditions during long term expansion by stabilizing Wnt-activity. Our study exemplifies the potential of individual cell-based modeling in unraveling links between molecular stem cell regulation and 3D growth of tissues. This kind of modeling combines experimental results in the fields of stem cell biology and cell biomechanics constituting a prerequisite for a better understanding of tissue regeneration as well as developmental processes. Copyright © 2017 Elsevier Inc. All rights reserved.

Methods to determine the growth domain in a multidimensional environmental space.

PubMed

Le Marc, Yvan; Pin, Carmen; Baranyi, József

2005-04-15

Data from a database on microbial responses to the food environment (ComBase, see www.combase.cc) were used to study the boundary of growth several pathogens (Aeromonas hydrophila, Escherichia coli, Listeria monocytogenes, Yersinia enterocolitica). Two methods were used to evaluate the growth/no growth interface. The first one is an application of the Minimum Convex Polyhedron (MCP) introduced by Baranyi et al. [Baranyi, J., Ross, T., McMeekin, T., Roberts, T.A., 1996. The effect of parameterisation on the performance of empirical models used in Predictive Microbiology. Food Microbiol. 13, 83-91.]. The second method applies logistic regression to define the boundary of growth. The combination of these two different techniques can be a useful tool to handle the problem of extrapolation of predictive models at the growth limits.

Hormone-Mediated Pattern Formation in Seedling of Plants: a Competitive Growth Dynamics Model

NASA Astrophysics Data System (ADS)

Kawaguchi, Satoshi; Mimura, Masayasu; Ohya, Tomoyuki; Oikawa, Noriko; Okabe, Hirotaka; Kai, Shoichi

2001-10-01

An ecologically relevant pattern formation process mediated by hormonal interactions among growing seedlings is modeled based on the experimental observations on the effects of indole acetic acid, which can act as an inhibitor and activator of root growth depending on its concentration. In the absence of any lateral root with constant hormone-sensitivity, the edge effect phenomenon is obtained depending on the secretion rate of hormone from the main root. Introduction of growth-stage-dependent hormone-sensitivity drastically amplifies the initial randomness, resulting in spatially irregular macroscopic patterns. When the lateral root growth is introduced, periodic patterns are obtained whose periodicity depends on the length of lateral roots. The growth-stage-dependent hormone-sensitivity and the lateral root growth are crucial for macroscopic periodic-pattern formation.

Inventory implications of using sampling variances in estimation of growth model coefficients

Treesearch

Albert R. Stage; William R. Wykoff

2000-01-01

Variables based on stand densities or stocking have sampling errors that depend on the relation of tree size to plot size and on the spatial structure of the population, ignoring the sampling errors of such variables, which include most measures of competition used in both distance-dependent and distance-independent growth models, can bias the predictions obtained from...

Growth of Lactobacillus paracasei ATCC334 in a cheese model system: A biochemical approach

USDA-ARS?s Scientific Manuscript database

Growth of Lactobacillus paracasei ATCC 334, in a cheese-ripening model system based upon a medium prepared from ripening Cheddar cheese extract (CCE) was evaluated. Lactobacillus paracasei ATCC 334 grows in CCE made from cheese ripened for 2 (2mCCE), 6 (6mCCE), and 8 (8mCCE) mo, to final cell densit...

Literature-Based Scientific Learning: A Collaboration Model

ERIC Educational Resources Information Center

Elrod, Susan L.; Somerville, Mary M.

2007-01-01

Amidst exponential growth of knowledge, student insights into the knowledge creation practices of the scientific community can be furthered by science faculty collaborations with university librarians. The Literature-Based Scientific Learning model advances undergraduates' disciplinary mastery and information literacy through experience with…

Comparing root architectural models

NASA Astrophysics Data System (ADS)

Schnepf, Andrea; Javaux, Mathieu; Vanderborght, Jan

2017-04-01

Plant roots play an important role in several soil processes (Gregory 2006). Root architecture development determines the sites in soil where roots provide input of carbon and energy and take up water and solutes. However, root architecture is difficult to determine experimentally when grown in opaque soil. Thus, root architectural models have been widely used and been further developed into functional-structural models that are able to simulate the fate of water and solutes in the soil-root system (Dunbabin et al. 2013). Still, a systematic comparison of the different root architectural models is missing. In this work, we focus on discrete root architecture models where roots are described by connected line segments. These models differ (a) in their model concepts, such as the description of distance between branches based on a prescribed distance (inter-nodal distance) or based on a prescribed time interval. Furthermore, these models differ (b) in the implementation of the same concept, such as the time step size, the spatial discretization along the root axes or the way stochasticity of parameters such as root growth direction, growth rate, branch spacing, branching angles are treated. Based on the example of two such different root models, the root growth module of R-SWMS and RootBox, we show the impact of these differences on simulated root architecture and aggregated information computed from this detailed simulation results, taking into account the stochastic nature of those models. References Dunbabin, V.M., Postma, J.A., Schnepf, A., Pagès, L., Javaux, M., Wu, L., Leitner, D., Chen, Y.L., Rengel, Z., Diggle, A.J. Modelling root-soil interactions using three-dimensional models of root growth, architecture and function (2013) Plant and Soil, 372 (1-2), pp. 93 - 124. Gregory (2006) Roots, rhizosphere and soil: the route to a better understanding of soil science? European Journal of Soil Science 57: 2-12.

Kinetic characteristics and modeling of microalgae Chlorella vulgaris growth and CO2 biofixation considering the coupled effects of light intensity and dissolved inorganic carbon.

PubMed

Chang, Hai-Xing; Huang, Yun; Fu, Qian; Liao, Qiang; Zhu, Xun

2016-04-01

Understanding and optimizing the microalgae growth process is an essential prerequisite for effective CO2 capture using microalgae in photobioreactors. In this study, the kinetic characteristics of microalgae Chlorella vulgaris growth in response to light intensity and dissolved inorganic carbon (DIC) concentration were investigated. The greatest values of maximum biomass concentration (Xmax) and maximum specific growth rate (μmax) were obtained as 2.303 g L(-1) and 0.078 h(-1), respectively, at a light intensity of 120 μmol m(-2) s(-1) and DIC concentration of 17 mM. Based on the results, mathematical models describing the coupled effects of light intensity and DIC concentration on microalgae growth and CO2 biofixation are proposed. The models are able to predict the temporal evolution of C. vulgaris growth and CO2 biofixation rates from lag to stationary phases. Verification experiments confirmed that the model predictions agreed well with the experimental results. Copyright © 2016 Elsevier Ltd. All rights reserved.

Oxidation-Assisted Crack Growth in Single-Crystal Superalloys during Fatigue with Compressive Holds

NASA Astrophysics Data System (ADS)

Lafata, M. A.; Rettberg, L. H.; He, M. Y.; Pollock, T. M.

2018-01-01

The mechanism of oxidation-assisted growth of surface cracks during fatigue with compressive holds has been studied experimentally and via a model that describes the role of oxide and substrate properties. The creep-based finite element model has been employed to examine the role of material parameters in the damage evolution in a Ni-base single-crystal superalloy René N5. Low-cycle fatigue experiments with compressive holds were conducted at 1255 K and 1366 K (982 °C and 1093 °C). Interrupted and failed specimens were characterized for crack depth and spacing, oxide thickness, and microstructural evolution. Comparison of experimental to modeled hysteresis loops indicates that transient creep drives the macroscopic stress-strain response. Crack penetration rates are strongly influenced by growth stresses in the oxide, structural evolution in the substrate, and the development of γ ^' } denuded zones. Implications for design of alloys resistant to this mode of degradation are discussed.

On-lattice agent-based simulation of populations of cells within the open-source Chaste framework.

PubMed

Figueredo, Grazziela P; Joshi, Tanvi V; Osborne, James M; Byrne, Helen M; Owen, Markus R

2013-04-06

Over the years, agent-based models have been developed that combine cell division and reinforced random walks of cells on a regular lattice, reaction-diffusion equations for nutrients and growth factors; and ordinary differential equations for the subcellular networks regulating the cell cycle. When linked to a vascular layer, this multiple scale model framework has been applied to tumour growth and therapy. Here, we report on the creation of an agent-based multi-scale environment amalgamating the characteristics of these models within a Virtual Physiological Human (VPH) Exemplar Project. This project enables reuse, integration, expansion and sharing of the model and relevant data. The agent-based and reaction-diffusion parts of the multi-scale model have been implemented and are available for download as part of the latest public release of Chaste (Cancer, Heart and Soft Tissue Environment; http://www.cs.ox.ac.uk/chaste/), part of the VPH Toolkit (http://toolkit.vph-noe.eu/). The environment functionalities are verified against the original models, in addition to extra validation of all aspects of the code. In this work, we present the details of the implementation of the agent-based environment, including the system description, the conceptual model, the development of the simulation model and the processes of verification and validation of the simulation results. We explore the potential use of the environment by presenting exemplar applications of the 'what if' scenarios that can easily be studied in the environment. These examples relate to tumour growth, cellular competition for resources and tumour responses to hypoxia (low oxygen levels). We conclude our work by summarizing the future steps for the expansion of the current system.

Investigating calcite growth rates using a quartz crystal microbalance with dissipation (QCM-D)

NASA Astrophysics Data System (ADS)

Cao, Bo; Stack, Andrew G.; Steefel, Carl I.; DePaolo, Donald J.; Lammers, Laura N.; Hu, Yandi

2018-02-01

Calcite precipitation plays a significant role in processes such as geological carbon sequestration and toxic metal sequestration and, yet, the rates and mechanisms of calcite growth under close to equilibrium conditions are far from well understood. In this study, a quartz crystal microbalance with dissipation (QCM-D) was used for the first time to measure macroscopic calcite growth rates. Calcite seed crystals were first nucleated and grown on sensors, then growth rates of calcite seed crystals were measured in real-time under close to equilibrium conditions (saturation index, SI = log ({Ca2+}/{CO32-}/Ksp) = 0.01-0.7, where {i} represent ion activities and Ksp = 10-8.48 is the calcite thermodynamic solubility constant). At the end of the experiments, total masses of calcite crystals on sensors measured by QCM-D and inductively coupled plasma mass spectrometry (ICP-MS) were consistent, validating the QCM-D measurements. Calcite growth rates measured by QCM-D were compared with reported macroscopic growth rates measured with auto-titration, ICP-MS, and microbalance. Calcite growth rates measured by QCM-D were also compared with microscopic growth rates measured by atomic force microscopy (AFM) and with rates predicted by two process-based crystal growth models. The discrepancies in growth rates among AFM measurements and model predictions appear to mainly arise from differences in step densities, and the step velocities were consistent among the AFM measurements as well as with both model predictions. Using the predicted steady-state step velocity and the measured step densities, both models predict well the growth rates measured using QCM-D and AFM. This study provides valuable insights into the effects of reactive site densities on calcite growth rate, which may help design future growth models to predict transient-state step densities.

Counteracting structural errors in ensemble forecast of influenza outbreaks.

PubMed

Pei, Sen; Shaman, Jeffrey

2017-10-13

For influenza forecasts generated using dynamical models, forecast inaccuracy is partly attributable to the nonlinear growth of error. As a consequence, quantification of the nonlinear error structure in current forecast models is needed so that this growth can be corrected and forecast skill improved. Here, we inspect the error growth of a compartmental influenza model and find that a robust error structure arises naturally from the nonlinear model dynamics. By counteracting these structural errors, diagnosed using error breeding, we develop a new forecast approach that combines dynamical error correction and statistical filtering techniques. In retrospective forecasts of historical influenza outbreaks for 95 US cities from 2003 to 2014, overall forecast accuracy for outbreak peak timing, peak intensity and attack rate, are substantially improved for predicted lead times up to 10 weeks. This error growth correction method can be generalized to improve the forecast accuracy of other infectious disease dynamical models.Inaccuracy of influenza forecasts based on dynamical models is partly due to nonlinear error growth. Here the authors address the error structure of a compartmental influenza model, and develop a new improved forecast approach combining dynamical error correction and statistical filtering techniques.

Modelling cell wall growth using a fibre-reinforced hyperelastic-viscoplastic constitutive law

NASA Astrophysics Data System (ADS)

Huang, R.; Becker, A. A.; Jones, I. A.

2012-04-01

A fibre-reinforced hyperelastic-viscoplastic model using a finite strain Finite Element (FE) analysis is presented to study the expansive growth of cell walls. Based on the connections between biological concepts and plasticity theory, e.g. wall-loosening and plastic yield, wall-stiffening and plastic hardening, the modelling of cell wall growth is established within a framework of anisotropic viscoplasticity aiming to represent the corresponding biology-controlled behaviour of a cell wall. In order to model in vivo growth, special attention is paid to the differences between a living cell and an isolated wall. The proposed hyperelastic-viscoplastic theory provides a unique framework to clarify the interplay between cellulose microfibrils and cell wall matrix and how this interplay regulates sustainable growth in a particular direction while maintaining the mechanical strength of the cell walls by new material deposition. Moreover, the effect of temperature is taken into account. A numerical scheme is suggested and FE case studies are presented and compared with experimental data.

Application of dynamic flux balance analysis to an industrial Escherichia coli fermentation.

PubMed

Meadows, Adam L; Karnik, Rahi; Lam, Harry; Forestell, Sean; Snedecor, Brad

2010-03-01

We have developed a reactor-scale model of Escherichia coli metabolism and growth in a 1000 L process for the production of a recombinant therapeutic protein. The model consists of two distinct parts: (1) a dynamic, process specific portion that describes the time evolution of 37 process variables of relevance and (2) a flux balance based, 123-reaction metabolic model of E. coli metabolism. This model combines several previously reported modeling approaches including a growth rate-dependent biomass composition, maximum growth rate objective function, and dynamic flux balancing. In addition, we introduce concentration-dependent boundary conditions of transport fluxes, dynamic maintenance demands, and a state-dependent cellular objective. This formulation was able to describe specific runs with high-fidelity over process conditions including rich media, simultaneous acetate and glucose consumption, glucose minimal media, and phosphate depleted media. Furthermore, the model accurately describes the effect of process perturbations--such as glucose overbatching and insufficient aeration--on growth, metabolism, and titer. (c) 2009 Elsevier Inc. All rights reserved.

Assessing tropical rainforest growth traits: Data - Model fusion in the Congo basin and beyond

NASA Astrophysics Data System (ADS)

Pietsch, Stephan

2017-04-01

Virgin forest ecosystems resemble the key reference level for natural tree growth dynamics. The mosaic cycle concept describes such dynamics as local disequilibria driven by patch level succession cycles of breakdown, regeneration, juvenescence and old growth. These cycles, however, may involve different traits of light demanding and shade tolerant species assemblies. In this work a data model fusion concept will be introduced to assess the differences in growth dynamics of the mosaic cycle of the Western Congolian Lowland Rainforest ecosystem. Field data from 34 forest patches located in an ice age forest refuge, recently pinpointed to the ground and still devoid of direct human impact up to today - resemble the data base. A 3D error assessment procedure versus BGC model simulations for the 34 patches revealed two different growth dynamics, consistent with observed growth traits of pioneer and late succession species assemblies of the Western Congolian Lowland rainforest. An application of the same procedure to Central American Pacific rainforests confirms the strength of the 3D error field data model fusion concept to Central American Pacific rainforests confirms the strength of the 3D error field data model fusion concept to assess different growth traits of the mosaic cycle of natural forest dynamics.

Assessing tropical rainforest growth traits: Data - Model fusion in the Congo basin and beyond.

NASA Astrophysics Data System (ADS)

Pietsch, S.

2016-12-01

Virgin forest ecosystems resemble the key reference level for natural tree growth dynamics. The mosaic cycle concept describes such dynamics as local disequilibria driven by patch level succession cycles of breakdown, regeneration, juvenescence and old growth. These cycles, however, may involve different traits of light demanding and shade tolerant species assemblies. In this work a data model fusion concept will be introduced to assess the differences in growth dynamics of the mosaic cycle of the Western Congolian Lowland Rainforest ecosystem. Field data from 34 forest patches located in an ice age forest refuge, recently pinpointed to the ground and still devoid of direct human impact up to today - resemble the data base. A 3D error assessment procedure versus BGC model simulations for the 34 patches revealed two different growth dynamics, consistent with observed growth traits of pioneer and late succession species assemblies of the Western Congolian Lowland rainforest. An application of the same procedure to Central American Pacific rainforests confirms the strength of the 3D error field data model fusion concept to assess different growth traits of the mosaic cycle of natural forest dynamics.

NASA Earth Science Research Results for Improved Regional Crop Yield Prediction

NASA Astrophysics Data System (ADS)

Mali, P.; O'Hara, C. G.; Shrestha, B.; Sinclair, T. R.; G de Goncalves, L. G.; Salado Navarro, L. R.

2007-12-01

National agencies such as USDA Foreign Agricultural Service (FAS), Production Estimation and Crop Assessment Division (PECAD) work specifically to analyze and generate timely crop yield estimates that help define national as well as global food policies. The USDA/FAS/PECAD utilizes a Decision Support System (DSS) called CADRE (Crop Condition and Data Retrieval Evaluation) mainly through an automated database management system that integrates various meteorological datasets, crop and soil models, and remote sensing data; providing significant contribution to the national and international crop production estimates. The "Sinclair" soybean growth model has been used inside CADRE DSS as one of the crop models. This project uses Sinclair model (a semi-mechanistic crop growth model) for its potential to be effectively used in a geo-processing environment with remote-sensing-based inputs. The main objective of this proposed work is to verify, validate and benchmark current and future NASA earth science research results for the benefit in the operational decision making process of the PECAD/CADRE DSS. For this purpose, the NASA South American Land Data Assimilation System (SALDAS) meteorological dataset is tested for its applicability as a surrogate meteorological input in the Sinclair model meteorological input requirements. Similarly, NASA sensor MODIS products is tested for its applicability in the improvement of the crop yield prediction through improving precision of planting date estimation, plant vigor and growth monitoring. The project also analyzes simulated Visible/Infrared Imager/Radiometer Suite (VIIRS, a future NASA sensor) vegetation product for its applicability in crop growth prediction to accelerate the process of transition of VIIRS research results for the operational use of USDA/FAS/PECAD DSS. The research results will help in providing improved decision making capacity to the USDA/FAS/PECAD DSS through improved vegetation growth monitoring from high spatial and temporal resolution remote sensing datasets; improved time-series meteorological inputs required for crop growth models; and regional prediction capability through geo-processing-based yield modeling.

Variation in piñon pine growth responses to climate across gradients of environmental stress using an individual-based approach

NASA Astrophysics Data System (ADS)

Redmond, M. D.; Kelsey, K.; Urza, A.; Barger, N. N.

2015-12-01

Forest and woodland ecosystems play a crucial role in the global carbon cycle and may be strongly affected by changing climate. Here we use an individual-based approach to model piñon pine (Pinus edulis) radial growth responses to climate across gradients of environmental stress. We sampled piñon pine trees at 24 sites across southwestern Colorado that varied in soil available water capacity, elevation, and latitude, obtaining a total of 552 pinon pine tree ring series. We used linear mixed effect models to assess piñon pine growth responses to climate and site-level environmental stress (mean annual climatic water deficit and soil available water capacity). Using a similar modeling approach, we also determined long-term growth trends across our gradients of environmental stress. Piñon pine growth was strongly positively associated with winter precipitation and strongly negatively associated with summer vapor pressure deficit. However, the strength of the relationship between winter precipitation and piñon pine growth was affected by site-level environmental stress. Trees at sites with greater climatic water deficit (i.e. hotter, drier sites) were more sensitive to winter precipitation. Interestingly, trees at sites with greater soil available water capacity were also more sensitive to winter precipitation, as these trees had much higher growth rates during years of high precipitation. We found weak evidence of long-term declines in piñon growth rates over the past century within our study area. Growth trends overtime did vary across our soil available water capacity gradient: trees growing at sites with higher soil available water capacity responded more positively to the cool, wet climate conditions of the 1910s and 1980s, whereas tree growth rates at sites with lower soil available water capacity declined more linearly over the last century. Our findings suggest that the sensitivity of woodland ecosystems to changing climate will vary across the landscape due to differences in edaphic and physiographic factors. These results support recent dendroecology studies that emphasize the need to use a more individual-based approach to enhance our understanding of tree growth responses to climate.

Cellular trade-offs and optimal resource allocation during cyanobacterial diurnal growth

PubMed Central

Knoop, Henning; Bockmayr, Alexander; Steuer, Ralf

2017-01-01

Cyanobacteria are an integral part of Earth’s biogeochemical cycles and a promising resource for the synthesis of renewable bioproducts from atmospheric CO2. Growth and metabolism of cyanobacteria are inherently tied to the diurnal rhythm of light availability. As yet, however, insight into the stoichiometric and energetic constraints of cyanobacterial diurnal growth is limited. Here, we develop a computational framework to investigate the optimal allocation of cellular resources during diurnal phototrophic growth using a genome-scale metabolic reconstruction of the cyanobacterium Synechococcus elongatus PCC 7942. We formulate phototrophic growth as an autocatalytic process and solve the resulting time-dependent resource allocation problem using constraint-based analysis. Based on a narrow and well-defined set of parameters, our approach results in an ab initio prediction of growth properties over a full diurnal cycle. The computational model allows us to study the optimality of metabolite partitioning during diurnal growth. The cyclic pattern of glycogen accumulation, an emergent property of the model, has timing characteristics that are in qualitative agreement with experimental findings. The approach presented here provides insight into the time-dependent resource allocation problem of phototrophic diurnal growth and may serve as a general framework to assess the optimality of metabolic strategies that evolved in phototrophic organisms under diurnal conditions. PMID:28720699

An adaptive ARX model to estimate the RUL of aluminum plates based on its crack growth

NASA Astrophysics Data System (ADS)

Barraza-Barraza, Diana; Tercero-Gómez, Víctor G.; Beruvides, Mario G.; Limón-Robles, Jorge

2017-01-01

A wide variety of Condition-Based Maintenance (CBM) techniques deal with the problem of predicting the time for an asset fault. Most statistical approaches rely on historical failure data that might not be available in several practical situations. To address this issue, practitioners might require the use of self-starting approaches that consider only the available knowledge about the current degradation process and the asset operating context to update the prognostic model. Some authors use Autoregressive (AR) models for this purpose that are adequate when the asset operating context is constant, however, if it is variable, the accuracy of the models can be affected. In this paper, three autoregressive models with exogenous variables (ARX) were constructed, and their capability to estimate the remaining useful life (RUL) of a process was evaluated following the case of the aluminum crack growth problem. An existing stochastic model of aluminum crack growth was implemented and used to assess RUL estimation performance of the proposed ARX models through extensive Monte Carlo simulations. Point and interval estimations were made based only on individual history, behavior, operating conditions and failure thresholds. Both analytic and bootstrapping techniques were used in the estimation process. Finally, by including recursive parameter estimation and a forgetting factor, the ARX methodology adapts to changing operating conditions and maintain the focus on the current degradation level of an asset.

Treatment Analysis in a Cancer Stem Cell Context Using a Tumor Growth Model Based on Cellular Automata.

PubMed

Monteagudo, Ángel; Santos, José

2015-01-01

Cancer can be viewed as an emergent behavior in terms of complex system theory and artificial life, Cellular Automata (CA) being the tool most used for studying and characterizing the emergent behavior. Different approaches with CA models were used to model cancer growth. The use of the abstract model of acquired cancer hallmarks permits the direct modeling at cellular level, where a cellular automaton defines the mitotic and apoptotic behavior of cells, and allows for an analysis of different dynamics of the cellular system depending on the presence of the different hallmarks. A CA model based on the presence of hallmarks in the cells, which includes a simulation of the behavior of Cancer Stem Cells (CSC) and their implications for the resultant growth behavior of the multicellular system, was employed. This modeling of cancer growth, in the avascular phase, was employed to analyze the effect of cancer treatments in a cancer stem cell context. The model clearly explains why, after treatment against non-stem cancer cells, the regrowth capability of CSCs generates a faster regrowth of tumor behavior, and also shows that a continuous low-intensity treatment does not favor CSC proliferation and differentiation, thereby allowing an unproblematic control of future tumor regrowth. The analysis performed indicates that, contrary to the current attempts at CSC control, trying to make CSC proliferation more difficult is an important point to consider, especially in the immediate period after a standard treatment for controlling non-stem cancer cell proliferation.

A physically based analytical spatial air temperature and humidity model

Treesearch

Yang Yang; Theodore A. Endreny; David J. Nowak

2013-01-01

Spatial variation of urban surface air temperature and humidity influences human thermal comfort, the settling rate of atmospheric pollutants, and plant physiology and growth. Given the lack of observations, we developed a Physically based Analytical Spatial Air Temperature and Humidity (PASATH) model. The PASATH model calculates spatial solar radiation and heat...

Growth Dynamics of Information Search Services

ERIC Educational Resources Information Center

Lindquist, Mats G.

1978-01-01

An analysis of computer-based search services (ISSs) from a system's viewpoint, using a continuous simulation model to reveal growth and stagnation of a typical system is presented, as well as an analysis of decision making for an ISS. (Author/MBR)

Vertical Bridgman growth of Hg 1-xMn xTe with variational withdrawal rate

NASA Astrophysics Data System (ADS)

Zhi, Gu; Wan-Qi, Jie; Guo-Qiang, Li; Long, Zhang

2004-09-01

Based on the solute redistribution models, Vertical Bridgman growth of Hg1-xMnxTe with variational withdrawal rate is studied. Both theoretical analysis and experimental results show that the axial composition uniformity is improved and the crystal growth rate is also increased at the optimized variational method of withdrawal rate.

Monte Carlo simulation of ferroelectric domain growth

NASA Astrophysics Data System (ADS)

Li, B. L.; Liu, X. P.; Fang, F.; Zhu, J. L.; Liu, J.-M.

2006-01-01

The kinetics of two-dimensional isothermal domain growth in a quenched ferroelectric system is investigated using Monte Carlo simulation based on a realistic Ginzburg-Landau ferroelectric model with cubic-tetragonal (square-rectangle) phase transitions. The evolution of the domain pattern and domain size with annealing time is simulated, and the stability of trijunctions and tetrajunctions of domain walls is analyzed. It is found that in this much realistic model with strong dipole alignment anisotropy and long-range Coulomb interaction, the powerlaw for normal domain growth still stands applicable. Towards the late stage of domain growth, both the average domain area and reciprocal density of domain wall junctions increase linearly with time, and the one-parameter dynamic scaling of the domain growth is demonstrated.

Kinetic Model of the Initial Stage of the Nanowire Growth

NASA Astrophysics Data System (ADS)

Filimonov, S. N.; Hervieu, Yu. Yu.

2018-03-01

A kinetic model of the formation of pyramid-like bulges (pedestals) at the bases of vertical nanowires is proposed. The formation of the pedestals at the early stage of the nanowire growth is assumed to be induced by a higher nucleation rate of two-dimensional islands under the catalyst droplet, as compared to the nucleation rate at the non-activated surface areas. Kinetics of the nucleation and propagation of the steps in the pyramid is described with a model of the multilayer growth, taking into account that the catalyst droplet at the nanowire top is a strong sink for adatoms. It is shown that the transition from the growth of the pyramid to the axial growth of the nanowire is possible if the appearance of a nucleus of the new layer under the catalyst droplet results in a partial dissolution of the underlying layer. In this case a segment of the nanowire sidewall is formed, preventing the lateral growth of the layers generated by the droplet.

An integrated microalgal growth model and its application to optimize the biomass production of Scenedesmus sp. LX1 in open pond under the nutrient level of domestic secondary effluent.

PubMed

Wu, Yin-Hu; Li, Xin; Yu, Yin; Hu, Hong-Ying; Zhang, Tian-Yuan; Li, Feng-Min

2013-09-01

Microalgal growth is the key to the coupled system of wastewater treatment and microalgal biomass production. In this study, Monod model, Droop model and Steele model were incorporated to obtain an integrated growth model describing the combined effects of nitrogen, phosphorus and light intensity on the growth rate of Scenedesmus sp. LX1. The model parameters were obtained via fitting experimental data to these classical models. Furthermore, the biomass production of Scenedesmus sp. LX1 in open pond under nutrient level of secondary effluent was analyzed based on the integrated model, predicting a maximal microalgal biomass production rate about 20 g m(-2) d(-1). In order to optimize the biomass production of open pond the microalgal biomass concentration, light intensity on the surface of open pond, total depth of culture medium and hydraulic retention time should be 500 g m(-3), 16,000 lx, 0.2 m and 5.2 d in the conditions of this study, respectively. Copyright © 2013 Elsevier Ltd. All rights reserved.

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

Rongle Zhang; Jie Chang; Yuanyuan Xu

A new kinetic model of the Fischer-Tropsch synthesis (FTS) is proposed to describe the non-Anderson-Schulz-Flory (ASF) product distribution. The model is based on the double-polymerization monomers hypothesis, in which the surface C{sub 2}{asterisk} species acts as a chain-growth monomer in the light-product range, while C{sub 1}{asterisk} species acts as a chain-growth monomer in the heavy-product range. The detailed kinetic model in the Langmuir-Hinshelwood-Hougen-Watson type based on the elementary reactions is derived for FTS and the water-gas-shift reaction. Kinetic model candidates are evaluated by minimization of multiresponse objective functions with a genetic algorithm approach. The model of hydrocarbon product distribution ismore » consistent with experimental data (

An Agent-Based Model of New Venture Creation: Conceptual Design for Simulating Entrepreneurship

NASA Technical Reports Server (NTRS)

Provance, Mike; Collins, Andrew; Carayannis, Elias

2012-01-01

There is a growing debate over the means by which regions can foster the growth of entrepreneurial activity in order to stimulate recovery and growth of their economies. On one side, agglomeration theory suggests the regions grow because of strong clusters that foster knowledge spillover locally; on the other side, the entrepreneurial action camp argues that innovative business models are generated by entrepreneurs with unique market perspectives who draw on knowledge from more distant domains. We will show you the design for a novel agent-based model of new venture creation that will demonstrate the relationship between agglomeration and action. The primary focus of this model is information exchange as the medium for these agent interactions. Our modeling and simulation study proposes to reveal interesting relationships in these perspectives, offer a foundation on which these disparate theories from economics and sociology can find common ground, and expand the use of agent-based modeling into entrepreneurship research.

Fatigue crack growth model RANDOM2 user manual. Appendix 1: Development of advanced methodologies for probabilistic constitutive relationships of material strength models

NASA Technical Reports Server (NTRS)

Boyce, Lola; Lovelace, Thomas B.

1989-01-01

FORTRAN program RANDOM2 is presented in the form of a user's manual. RANDOM2 is based on fracture mechanics using a probabilistic fatigue crack growth model. It predicts the random lifetime of an engine component to reach a given crack size. Details of the theoretical background, input data instructions, and a sample problem illustrating the use of the program are included.

Model for growth of fractal solid state surface and possibility of its verification by means of atomic force microscopy

NASA Astrophysics Data System (ADS)

Kulikov, D. A.; Potapov, A. A.; Rassadin, A. E.; Stepanov, A. V.

2017-10-01

In the paper, methods of verification of models for growth of solid state surface by means of atomic force microscopy are suggested. Simulation of growth of fractals with cylindrical generatrix on the solid state surface is presented. Our mathematical model of this process is based on generalization of the Kardar-Parisi-Zhang equation. Corner stones of this generalization are both conjecture of anisotropy of growth of the surface and approximation of small angles. The method of characteristics has been applied to solve the Kardar-Parisi-Zhang equation. Its solution should be considered up to the gradient catastrophe. The difficulty of nondifferentiability of fractal initial generatrix has been overcome by transition from a mathematical fractal to a physical one.

Predicting overload-affected fatigue crack growth in steels

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

Skorupa, M.; Skorupa, A.; Ladecki, B.

1996-12-01

The ability of semi-empirical crack closure models to predict the effect of overloads on fatigue crack growth in low-alloy steels has been investigated. With this purpose, the CORPUS model developed for aircraft metals and spectra has been checked first through comparisons between the simulated and observed results for a low-alloy steel. The CORPUS predictions of crack growth under several types of simple load histories containing overloads appeared generally unconservative which prompted the authors to formulate a new model, more suitable for steels. With the latter approach, the assumed evolution of the crack opening stress during the delayed retardation stage hasmore » been based on experimental results reported for various steels. For all the load sequences considered, the predictions from the proposed model appeared to be by far more accurate than those from CORPUS. Based on the analysis results, the capability of semi-empirical prediction concepts to cover experimentally observed trends that have been reported for sequences with overloads is discussed. Finally, possibilities of improving the model performance are considered.« less

Computational Systems Biology in Cancer: Modeling Methods and Applications

PubMed Central

Materi, Wayne; Wishart, David S.

2007-01-01

In recent years it has become clear that carcinogenesis is a complex process, both at the molecular and cellular levels. Understanding the origins, growth and spread of cancer, therefore requires an integrated or system-wide approach. Computational systems biology is an emerging sub-discipline in systems biology that utilizes the wealth of data from genomic, proteomic and metabolomic studies to build computer simulations of intra and intercellular processes. Several useful descriptive and predictive models of the origin, growth and spread of cancers have been developed in an effort to better understand the disease and potential therapeutic approaches. In this review we describe and assess the practical and theoretical underpinnings of commonly-used modeling approaches, including ordinary and partial differential equations, petri nets, cellular automata, agent based models and hybrid systems. A number of computer-based formalisms have been implemented to improve the accessibility of the various approaches to researchers whose primary interest lies outside of model development. We discuss several of these and describe how they have led to novel insights into tumor genesis, growth, apoptosis, vascularization and therapy. PMID:19936081

[Cultural regionalization for Coptis chinensis based on 3S technology platform Ⅰ. Study on growth suitability for Coptis chinensis based on ecological factors analysis by Maxent and ArcGIS model].

PubMed

Liu, Xin; Yang, Yan-Fang; Song, Hong-Ping; Zhang, Xiao-Bo; Huang, Lu-Qi; Wu, He-Zhen

2016-09-01

At the urgent request of Coptis chinensis planting,growth suitability as assessment indicators for C. chinensis cultivation was proposed and analyzed in this paper , based on chemical quality determination and ecological fators analysis by Maxent and ArcGIS model. Its potential distribution areas at differernt suitability grade and regionalization map were formulated based on statistical theory and growth suitability theory. The results showed that the most suitable habitats is some parts of Chongqing and Hubei province, such as Shizhu, Lichuan, Wulong, Wuxi, Enshi. There are seven ecological factor is the main ecological factors affect the growth of Coptidis Rhizoma, including altitude, precipitation in February and September and the rise of precipitation and altitude is conducive to the accumulation of total alkaloid content in C. chinensis. Therefore, The results of the study not only illustrates the most suitable for the surroundings of Coptidis Rhizoma, also helpful to further research and practice of cultivation regionalization, wild resource monitoring and large-scale cultivation of traditional Chinese medicine plants. Copyright© by the Chinese Pharmaceutical Association.

Baseline projections for Latin America: base-year assumptions, key drivers and greenhouse emissions

DOE PAGES

van Ruijven, Bas J.; Daenzer, Katie; Fisher-Vanden, Karen; ...

2016-02-14

This article provides an overview of the base-year assumptions and core baseline projections for the set of models participating in the LAMP and CLIMACAP projects. Here we present the range in core baseline projections for Latin America, and identify key differences between model projections including how these projections compare to historic trends. We find relatively large differences across models in base year assumptions related to population, GDP, energy and CO 2 emissions due to the use of different data sources, but also conclude that this does not influence the range of projections. We find that population and GDP projections acrossmore » models span a broad range, comparable to the range represented by the set of Shared Socioeconomic Pathways (SSPs). Kaya-factor decomposition indicates that the set of core baseline scenarios mirrors trends experienced over the past decades. Emissions in Latin America are projected to rise as result of GDP and population growth and a minor shift in the energy mix toward fossil fuels. Most scenarios assume a somewhat higher GDP growth than historically observed and continued decline of population growth. Minor changes in energy intensity or energy mix are projected over the next few decades.« less

Concepts in solid tumor evolution.

PubMed

Sidow, Arend; Spies, Noah

2015-04-01

Evolutionary mechanisms in cancer progression give tumors their individuality. Cancer evolution is different from organismal evolution, however, and we discuss where concepts from evolutionary genetics are useful or limited in facilitating an understanding of cancer. Based on these concepts we construct and apply the simplest plausible model of tumor growth and progression. Simulations using this simple model illustrate the importance of stochastic events early in tumorigenesis, highlight the dominance of exponential growth over linear growth and differentiation, and explain the clonal substructure of tumors. Copyright © 2015 Elsevier Ltd. All rights reserved.

Structural Health Monitoring System Trade Space Analysis Tool with Consideration for Crack Growth, Sensor Degradation and a Variable Detection Threshold

DTIC Science & Technology

2014-09-18

Erdogan , 1963). 26 Paris’s Law Under a fatigue stress regime Paris’s Law relates sub-critical crack growth to stress intensity factor. The basic...Paris and Erdogan , 1963). After takeoff, the model generates a probability distribution for the crack length in that specific sortie based on the...Law is one of the most widely used fatigue crack growth models and was used in this research effort (Paris and Erdogan , 1963). Paris’s Law Under a

A self-modifying cellular automaton model of historical urbanization in the San Francisco Bay area

USGS Publications Warehouse

Clarke, K.C.; Hoppen, S.; Gaydos, L.

1997-01-01

In this paper we describe a cellular automaton (CA) simulation model developed to predict urban growth as part of a project for estimating the regional and broader impact of urbanization on the San Francisco Bay area's climate. The rules of the model are more complex than those of a typical CA and involve the use of multiple data sources, including topography, road networks, and existing settlement distributions, and their modification over time. In addition, the control parameters of the model are allowed to self-modify: that is, the CA adapts itself to the circumstances it generates, in particular, during periods of rapid growth or stagnation. In addition, the model was written to allow the accumulation of probabilistic estimates based on Monte Carlo methods. Calibration of the model has been accomplished by the use of historical maps to compare model predictions of urbanization, based solely upon the distribution in year 1900, with observed data for years 1940, 1954, 1962, 1974, and 1990. The complexity of this model has made calibration a particularly demanding step. Lessons learned about the methods, measures, and strategies developed to calibrate the model may be of use in other environmental modeling contexts. With the calibration complete, the model is being used to generate a set of future scenarios for the San Francisco Bay area along with their probabilities based on the Monte Carlo version of the model. Animated dynamic mapping of the simulations will be used to allow visualization of the impact of future urban growth.

Mechanism-based model for tumor drug resistance.

PubMed

Kuczek, T; Chan, T C

1992-01-01

The development of tumor resistance to cytotoxic agents has important implications in the treatment of cancer. If supported by experimental data, mathematical models of resistance can provide useful information on the underlying mechanisms and aid in the design of therapeutic regimens. We report on the development of a model of tumor-growth kinetics based on the assumption that the rates of cell growth in a tumor are normally distributed. We further assumed that the growth rate of each cell is proportional to its rate of total pyrimidine synthesis (de novo plus salvage). Using an ovarian carcinoma cell line (2008) and resistant variants selected for chronic exposure to a pyrimidine antimetabolite, N-phosphonacetyl-L-aspartate (PALA), we derived a simple and specific analytical form describing the growth curves generated in 72 h growth assays. The model assumes that the rate of de novo pyrimidine synthesis, denoted alpha, is shifted down by an amount proportional to the log10 PALA concentration and that cells whose rate of pyrimidine synthesis falls below a critical level, denoted alpha 0, can no longer grow. This is described by the equation: Probability (growth) = probability (alpha 0 less than alpha-constant x log10 [PALA]). This model predicts that when growth curves are plotted on probit paper, they will produce straight lines. This prediction is in agreement with the data we obtained for the 2008 cells. Another prediction of this model is that the same probit plots for the resistant variants should shift to the right in a parallel fashion. Probit plots of the dose-response data obtained for each resistant 2008 line following chronic exposure to PALA again confirmed this prediction. Correlation of the rightward shift of dose responses to uridine transport (r = 0.99) also suggests that salvage metabolism plays a key role in tumor-cell resistance to PALA. Furthermore, the slope of the regression lines enables the detection of synergy such as that observed between dipyridamole and PALA. Although the rate-normal model was used to study the rate of salvage metabolism in PALA resistance in the present study, it may be widely applicable to modeling of other resistance mechanisms such as gene amplification of target enzymes.

Improved brain tumor segmentation by utilizing tumor growth model in longitudinal brain MRI

NASA Astrophysics Data System (ADS)

Pei, Linmin; Reza, Syed M. S.; Li, Wei; Davatzikos, Christos; Iftekharuddin, Khan M.

2017-03-01

In this work, we propose a novel method to improve texture based tumor segmentation by fusing cell density patterns that are generated from tumor growth modeling. To model tumor growth, we solve the reaction-diffusion equation by using Lattice-Boltzmann method (LBM). Computational tumor growth modeling obtains the cell density distribution that potentially indicates the predicted tissue locations in the brain over time. The density patterns is then considered as novel features along with other texture (such as fractal, and multifractal Brownian motion (mBm)), and intensity features in MRI for improved brain tumor segmentation. We evaluate the proposed method with about one hundred longitudinal MRI scans from five patients obtained from public BRATS 2015 data set, validated by the ground truth. The result shows significant improvement of complete tumor segmentation using ANOVA analysis for five patients in longitudinal MR images.

Improved brain tumor segmentation by utilizing tumor growth model in longitudinal brain MRI.

PubMed

Pei, Linmin; Reza, Syed M S; Li, Wei; Davatzikos, Christos; Iftekharuddin, Khan M

2017-02-11

In this work, we propose a novel method to improve texture based tumor segmentation by fusing cell density patterns that are generated from tumor growth modeling. In order to model tumor growth, we solve the reaction-diffusion equation by using Lattice-Boltzmann method (LBM). Computational tumor growth modeling obtains the cell density distribution that potentially indicates the predicted tissue locations in the brain over time. The density patterns is then considered as novel features along with other texture (such as fractal, and multifractal Brownian motion (mBm)), and intensity features in MRI for improved brain tumor segmentation. We evaluate the proposed method with about one hundred longitudinal MRI scans from five patients obtained from public BRATS 2015 data set, validated by the ground truth. The result shows significant improvement of complete tumor segmentation using ANOVA analysis for five patients in longitudinal MR images.

Phytoplankton growth rate modelling: can spectroscopic cell chemotyping be superior to physiological predictors?

PubMed

Fanesi, Andrea; Wagner, Heiko; Wilhelm, Christian

2017-02-08

Climate change has a strong impact on phytoplankton communities and water quality. However, the development of robust techniques to assess phytoplankton growth is still in progress. In this study, the growth rate of phytoplankton cells grown at different temperatures was modelled based on conventional physiological traits (e.g. chlorophyll, carbon and photosynthetic parameters) using the partial least square regression (PLSR) algorithm and compared with a new approach combining Fourier transform infrared-spectroscopy and PLSR. In this second model, it is assumed that the macromolecular composition of phytoplankton cells represents an intracellular marker for growth. The models have comparable high predictive power (R 2 > 0.8) and low error in predicting new observations. Interestingly, not all of the predictors present the same weight in the modelling of growth rate. A set of specific parameters, such as non-photochemical fluorescence quenching (NPQ) and the quantum yield of carbon production in the first model, and lipid, protein and carbohydrate contents for the second one, strongly covary with cell growth rate regardless of the taxonomic position of the phytoplankton species investigated. This reflects a set of specific physiological adjustments covarying with growth rate, conserved among taxonomically distant algal species that might be used as guidelines for the improvement of modern primary production models. The high predictive power of both sets of cellular traits for growth rate is of great importance for applied phycological studies. Our approach may find application as a quality control tool for the monitoring of phytoplankton populations in natural communities or in photobioreactors. © 2017 The Author(s).

A Model of Silicate Grain Nucleation and Growth in Circumstellar Outflows

NASA Technical Reports Server (NTRS)

Paquette, John A.; Ferguson, Frank T.; Nuth, Joseph A., III

2011-01-01

Based on its abundance, high bond energy, and recent measurements of its vapor pressure SiO is a natural candidate for dust nucleation in circumstellar outflows around asymptotic giant branch stars. In this paper, we describe a model of the nucleation and growth of silicate dust in such outflows. The sensitivity of the model to varying choices of poorly constrained chemical parameters is explored, and the merits of using scaled rather than classical nucleation theory are briefly considered, An elaboration of the model that includes magnesium and iron as growth species is then presented and discussed. The composition of the bulk of the grains derived from the model is consistent with olivines and pyroxenes, but somewhat metal-rich grains and very small, nearly pure SiO grains are also produced,

Growth Kinetics and Morphology of Barite Crystals Derived from Face-Specific Growth Rates

DOE PAGES

Godinho, Jose R. A.; Stack, Andrew G.

2015-03-30

Here we investigate the growth kinetics and morphology of barite (BaSO 4) crystals by measuring the growth rates of the (001), (210), (010), and (100) surfaces using vertical scanning interferometry. Solutions with saturation indices 1.1, 2.1, and 3.0 without additional electrolyte, in 0.7 M NaCl, or in 1.3 mM SrCl2 are investigated. Face-specific growth rates are inhibited in the SrCl 2 solution relative to a solution without electrolyte, except for (100). Contrarily, growth of all faces is promoted in the NaCl solution. The variation of face-specific rates is solution-specific, which leads to a. change of the crystal morphology and overallmore » growth rate of crystals. The measured face-specific growth rates are used to model the growth of single crystals. Modeled crystals have a morphology and size similar to those grown from solution. Based on the model the time dependence of surface area and growth rates is analyzed. Growth rates change with time due to surface area normalization for small crystals and large growth intervals. By extrapolating rates to crystals with large surfaces areas, time-independent growth rates are 0.783, 2.96, and 0.513 mmol∙m -2∙h -1, for saturation index 2.1 solutions without additional electrolyte, NaCl, and SrCl 2, respectively.« less

Growth Kinetics and Morphology of Barite Crystals Derived from Face-Specific Growth Rates

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

Godinho, Jose R. A.; Stack, Andrew G.

Here we investigate the growth kinetics and morphology of barite (BaSO 4) crystals by measuring the growth rates of the (001), (210), (010), and (100) surfaces using vertical scanning interferometry. Solutions with saturation indices 1.1, 2.1, and 3.0 without additional electrolyte, in 0.7 M NaCl, or in 1.3 mM SrCl2 are investigated. Face-specific growth rates are inhibited in the SrCl 2 solution relative to a solution without electrolyte, except for (100). Contrarily, growth of all faces is promoted in the NaCl solution. The variation of face-specific rates is solution-specific, which leads to a. change of the crystal morphology and overallmore » growth rate of crystals. The measured face-specific growth rates are used to model the growth of single crystals. Modeled crystals have a morphology and size similar to those grown from solution. Based on the model the time dependence of surface area and growth rates is analyzed. Growth rates change with time due to surface area normalization for small crystals and large growth intervals. By extrapolating rates to crystals with large surfaces areas, time-independent growth rates are 0.783, 2.96, and 0.513 mmol∙m -2∙h -1, for saturation index 2.1 solutions without additional electrolyte, NaCl, and SrCl 2, respectively.« less

Metabolic modeling of energy balances in Mycoplasma hyopneumoniae shows that pyruvate addition increases growth rate.

PubMed

Kamminga, Tjerko; Slagman, Simen-Jan; Bijlsma, Jetta J E; Martins Dos Santos, Vitor A P; Suarez-Diez, Maria; Schaap, Peter J

2017-10-01

Mycoplasma hyopneumoniae is cultured on large-scale to produce antigen for inactivated whole-cell vaccines against respiratory disease in pigs. However, the fastidious nutrient requirements of this minimal bacterium and the low growth rate make it challenging to reach sufficient biomass yield for antigen production. In this study, we sequenced the genome of M. hyopneumoniae strain 11 and constructed a high quality constraint-based genome-scale metabolic model of 284 chemical reactions and 298 metabolites. We validated the model with time-series data of duplicate fermentation cultures to aim for an integrated model describing the dynamic profiles measured in fermentations. The model predicted that 84% of cellular energy in a standard M. hyopneumoniae cultivation was used for non-growth associated maintenance and only 16% of cellular energy was used for growth and growth associated maintenance. Following a cycle of model-driven experimentation in dedicated fermentation experiments, we were able to increase the fraction of cellular energy used for growth through pyruvate addition to the medium. This increase in turn led to an increase in growth rate and a 2.3 times increase in the total biomass concentration reached after 3-4 days of fermentation, enhancing the productivity of the overall process. The model presented provides a solid basis to understand and further improve M. hyopneumoniae fermentation processes. Biotechnol. Bioeng. 2017;114: 2339-2347. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Dimensional, Geometrical, and Physical Constraints in Skull Growth.

PubMed

Weickenmeier, Johannes; Fischer, Cedric; Carter, Dennis; Kuhl, Ellen; Goriely, Alain

2017-06-16

After birth, the skull grows and remodels in close synchrony with the brain to allow for an increase in intracranial volume. Increase in skull area is provided primarily by bone accretion at the sutures. Additional remodeling, to allow for a change in curvatures, occurs by resorption on the inner surface of the bone plates and accretion on their outer surfaces. When a suture fuses too early, normal skull growth is disrupted, leading to a deformed final skull shape. The leading theory assumes that the main stimulus for skull growth is provided by mechanical stresses. Based on these ideas, we first discuss the dimensional, geometrical, and kinematic synchrony between brain, skull, and suture growth. Second, we present two mechanical models for skull growth that account for growth at the sutures and explain the various observed dysmorphologies. These models demonstrate the particular role of physical and geometrical constraints taking place in skull growth.

Dimensional, Geometrical, and Physical Constraints in Skull Growth

NASA Astrophysics Data System (ADS)

Weickenmeier, Johannes; Fischer, Cedric; Carter, Dennis; Kuhl, Ellen; Goriely, Alain

2017-06-01

After birth, the skull grows and remodels in close synchrony with the brain to allow for an increase in intracranial volume. Increase in skull area is provided primarily by bone accretion at the sutures. Additional remodeling, to allow for a change in curvatures, occurs by resorption on the inner surface of the bone plates and accretion on their outer surfaces. When a suture fuses too early, normal skull growth is disrupted, leading to a deformed final skull shape. The leading theory assumes that the main stimulus for skull growth is provided by mechanical stresses. Based on these ideas, we first discuss the dimensional, geometrical, and kinematic synchrony between brain, skull, and suture growth. Second, we present two mechanical models for skull growth that account for growth at the sutures and explain the various observed dysmorphologies. These models demonstrate the particular role of physical and geometrical constraints taking place in skull growth.

Biochemomechanical poroelastic theory of avascular tumor growth

NASA Astrophysics Data System (ADS)

Xue, Shi-Lei; Li, Bo; Feng, Xi-Qiao; Gao, Huajian

2016-09-01

Tumor growth is a complex process involving genetic mutations, biochemical regulations, and mechanical deformations. In this paper, a thermodynamics-based nonlinear poroelastic theory is established to model the coupling among the mechanical, chemical, and biological mechanisms governing avascular tumor growth. A volumetric growth law accounting for mechano-chemo-biological coupled effects is proposed to describe the development of solid tumors. The regulating roles of stresses and nutrient transport in the tumor growth are revealed under different environmental constraints. We show that the mechano-chemo-biological coupling triggers anisotropic and heterogeneous growth, leading to the formation of layered structures in a growing tumor. There exists a steady state in which tumor growth is balanced by resorption. The influence of external confinements on tumor growth is also examined. A phase diagram is constructed to illustrate how the elastic modulus and thickness of the confinements jointly dictate the steady state of tumor volume. Qualitative and quantitative agreements with experimental observations indicate the developed model is capable of capturing the essential features of avascular tumor growth in various environments.

Biophysical modelling of intra-ring variations in tracheid features and wood density of Pinus pinaster trees exposed to seasonal droughts.

PubMed

Wilkinson, Sarah; Ogée, Jérôme; Domec, Jean-Christophe; Rayment, Mark; Wingate, Lisa

2015-03-01

Process-based models that link seasonally varying environmental signals to morphological features within tree rings are essential tools to predict tree growth response and commercially important wood quality traits under future climate scenarios. This study evaluated model portrayal of radial growth and wood anatomy observations within a mature maritime pine (Pinus pinaster (L.) Aït.) stand exposed to seasonal droughts. Intra-annual variations in tracheid anatomy and wood density were identified through image analysis and X-ray densitometry on stem cores covering the growth period 1999-2010. A cambial growth model was integrated with modelled plant water status and sugar availability from the soil-plant-atmosphere transfer model MuSICA to generate estimates of cell number, cell volume, cell mass and wood density on a weekly time step. The model successfully predicted inter-annual variations in cell number, ring width and maximum wood density. The model was also able to predict the occurrence of special anatomical features such as intra-annual density fluctuations (IADFs) in growth rings. Since cell wall thickness remained surprisingly constant within and between growth rings, variations in wood density were primarily the result of variations in lumen diameter, both in the model and anatomical data. In the model, changes in plant water status were identified as the main driver of the IADFs through a direct effect on cell volume. The anatomy data also revealed that a trade-off existed between hydraulic safety and hydraulic efficiency. Although a simplified description of cambial physiology is presented, this integrated modelling approach shows potential value for identifying universal patterns of tree-ring growth and anatomical features over a broad climatic gradient. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Using phenomenological models for forecasting the 2015 Ebola challenge.

PubMed

Pell, Bruce; Kuang, Yang; Viboud, Cecile; Chowell, Gerardo

2018-03-01

The rising number of novel pathogens threatening the human population has motivated the application of mathematical modeling for forecasting the trajectory and size of epidemics. We summarize the real-time forecasting results of the logistic equation during the 2015 Ebola challenge focused on predicting synthetic data derived from a detailed individual-based model of Ebola transmission dynamics and control. We also carry out a post-challenge comparison of two simple phenomenological models. In particular, we systematically compare the logistic growth model and a recently introduced generalized Richards model (GRM) that captures a range of early epidemic growth profiles ranging from sub-exponential to exponential growth. Specifically, we assess the performance of each model for estimating the reproduction number, generate short-term forecasts of the epidemic trajectory, and predict the final epidemic size. During the challenge the logistic equation consistently underestimated the final epidemic size, peak timing and the number of cases at peak timing with an average mean absolute percentage error (MAPE) of 0.49, 0.36 and 0.40, respectively. Post-challenge, the GRM which has the flexibility to reproduce a range of epidemic growth profiles ranging from early sub-exponential to exponential growth dynamics outperformed the logistic growth model in ascertaining the final epidemic size as more incidence data was made available, while the logistic model underestimated the final epidemic even with an increasing amount of data of the evolving epidemic. Incidence forecasts provided by the generalized Richards model performed better across all scenarios and time points than the logistic growth model with mean RMS decreasing from 78.00 (logistic) to 60.80 (GRM). Both models provided reasonable predictions of the effective reproduction number, but the GRM slightly outperformed the logistic growth model with a MAPE of 0.08 compared to 0.10, averaged across all scenarios and time points. Our findings further support the consideration of transmission models that incorporate flexible early epidemic growth profiles in the forecasting toolkit. Such models are particularly useful for quickly evaluating a developing infectious disease outbreak using only case incidence time series of the early phase of an infectious disease outbreak. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

Phase-Field Modeling of Polycrystalline Solidification: From Needle Crystals to Spherulites—A Review

NASA Astrophysics Data System (ADS)

Gránásy, László; Rátkai, László; Szállás, Attila; Korbuly, Bálint; Tóth, Gyula I.; Környei, László; Pusztai, Tamás

2014-04-01

Advances in the orientation-field-based phase-field (PF) models made in the past are reviewed. The models applied incorporate homogeneous and heterogeneous nucleation of growth centers and several mechanisms to form new grains at the perimeter of growing crystals, a phenomenon termed growth front nucleation. Examples for PF modeling of such complex polycrystalline structures are shown as impinging symmetric dendrites, polycrystalline growth forms (ranging from disordered dendrites to spherulitic patterns), and various eutectic structures, including spiraling two-phase dendrites. Simulations exploring possible control of solidification patterns in thin films via external fields, confined geometry, particle additives, scratching/piercing the films, etc. are also displayed. Advantages, problems, and possible solutions associated with quantitative PF simulations are discussed briefly.

Revisit of the Saito-Dresselhaus-Dresselhaus C2 ingestion model: on the mechanism of atomic-carbon-participated fullerene growth.

PubMed

Wang, Wei-Wei; Dang, Jing-Shuang; Zhao, Xiang; Nagase, Shigeru

2017-11-09

We introduce a mechanistic study based on a controversial fullerene bottom-up growth model proposed by R. Saito, G. Dresselhaus, and M. S. Dresselhaus. The so-called SDD C 2 addition model has been dismissed as chemically inadmissible but here we prove that it is feasible via successive atomic-carbon-participated addition and migration reactions. Kinetic calculations on the formation of isolated pentagon rule (IPR)-obeying C 70 and Y 3 N@C 80 are carried out by employing the SDD model for the first time. A stepwise mechanism is proposed with a considerably low barrier of ca. 2 eV which is about 3 eV lower than a conventional isomerization-containing fullerene growth pathway.

A Microstructure-Based Time-Dependent Crack Growth Model for Life and Reliability Prediction of Turbopropulsion Systems

NASA Astrophysics Data System (ADS)

Chan, Kwai S.; Enright, Michael P.; Moody, Jonathan; Fitch, Simeon H. K.

2014-01-01

The objective of this investigation was to develop an innovative methodology for life and reliability prediction of hot-section components in advanced turbopropulsion systems. A set of generic microstructure-based time-dependent crack growth (TDCG) models was developed and used to assess the sources of material variability due to microstructure and material parameters such as grain size, activation energy, and crack growth threshold for TDCG. A comparison of model predictions and experimental data obtained in air and in vacuum suggests that oxidation is responsible for higher crack growth rates at high temperatures, low frequencies, and long dwell times, but oxidation can also induce higher crack growth thresholds (Δ K th or K th) under certain conditions. Using the enhanced risk analysis tool and material constants calibrated to IN 718 data, the effect of TDCG on the risk of fracture in turboengine components was demonstrated for a generic rotor design and a realistic mission profile using the DARWIN® probabilistic life-prediction code. The results of this investigation confirmed that TDCG and cycle-dependent crack growth in IN 718 can be treated by a simple summation of the crack increments over a mission. For the temperatures considered, TDCG in IN 718 can be considered as a K-controlled or a diffusion-controlled oxidation-induced degradation process. This methodology provides a pathway for evaluating microstructural effects on multiple damage modes in hot-section components.

Trajectories of Heroin Addiction: Growth Mixture Modeling Results Based on a 33-Year Follow-Up Study

ERIC Educational Resources Information Center

Hser, Yih-Ing; Huang, David; Chou, Chih-Ping; Anglin, M. Douglas

2007-01-01

This study investigates trajectories of heroin use and subsequent consequences in a sample of 471 male heroin addicts who were admitted to the California Civil Addict Program in 1964-1965 and followed over 33 years. Applying a two-part growth mixture modeling strategy to heroin use level during the first 16 years of the addiction careers since…

Inventory-based sensitivity analysis of the Large Tree Diameter Growth Submodel of the Southern Variant of the FVS

Treesearch

Giorgio Vacchiano; John D. Shaw; R. Justin DeRose; James N. Long

2008-01-01

Diameter increment is an important variable in modeling tree growth. Most facets of predicted tree development are dependent in part on diameter or diameter increment, the most commonly measured stand variable. The behavior of the Forest Vegetation Simulator (FVS) largely relies on the performance of the diameter increment model and the subsequent use of predicted dbh...

Representing growth response to fertilization in the Prognosis Model for Stand Development

Treesearch

Albert R. Stage; Nicholas L. Crookston; Bahman Shafii; James A. Moore; John Olson

1990-01-01

Capability to represent effects of fertilization has been added to the Prognosis Model for Stand Development. As implemented in version 6, the extension is calibrated only for applications of 200 lb nitrogen applied in the form of urea. Direct and indirect effects are based on growth 10 years after treatment for diameter effects, and 6 years after treatment for height...

Modeling plasma-assisted growth of graphene-carbon nanotube hybrid

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

Tewari, Aarti

2016-08-15

A theoretical model describing the growth of graphene-CNT hybrid in a plasma medium is presented. Using the model, the growth of carbon nanotube (CNT) on a catalyst particle and thereafter the growth of the graphene on the CNT is studied under the purview of plasma sheath and number density kinetics of different plasma species. It is found that the plasma parameter such as ion density; gas ratios and process parameter such as source power affect the CNT and graphene dimensions. The variation in growth rates of graphene and CNT under different plasma power, gas ratios, and ion densities is analyzed.more » Based on the results obtained, it can be concluded that higher hydrocarbon ion densities and gas ratios of hydrocarbon to hydrogen favor the growth of taller CNTs and graphene, respectively. In addition, the CNT tip radius reduces with hydrogen ion density and higher plasma power favors graphene with lesser thickness. The present study can help in better understanding of the graphene-CNT hybrid growth in a plasma medium.« less

Digital Image Analysis of Yeast Single Cells Growing in Two Different Oxygen Concentrations to Analyze the Population Growth and to Assist Individual-Based Modeling.

PubMed

Ginovart, Marta; Carbó, Rosa; Blanco, Mónica; Portell, Xavier

2017-01-01

Nowadays control of the growth of Saccharomyces to obtain biomass or cellular wall components is crucial for specific industrial applications. The general aim of this contribution is to deal with experimental data obtained from yeast cells and from yeast cultures to attempt the integration of the two levels of information, individual and population, to progress in the control of yeast biotechnological processes by means of the overall analysis of this set of experimental data, and to assist in the improvement of an individual-based model, namely, INDISIM- Saccha . Populations of S. cerevisiae growing in liquid batch culture, in aerobic and microaerophilic conditions, were studied. A set of digital images was taken during the population growth, and a protocol for the treatment and analyses of the images obtained was established. The piecewise linear model of Buchanan was adjusted to the temporal evolutions of the yeast populations to determine the kinetic parameters and changes of growth phases. In parallel, for all the yeast cells analyzed, values of direct morphological parameters, such as area, perimeter, major diameter, minor diameter, and derived ones, such as circularity and elongation, were obtained. Graphical and numerical methods from descriptive statistics were applied to these data to characterize the growth phases and the budding state of the yeast cells in both experimental conditions, and inferential statistical methods were used to compare the diverse groups of data achieved. Oxidative metabolism of yeast in a medium with oxygen available and low initial sugar concentration can be taken into account in order to obtain a greater number of cells or larger cells. Morphological parameters were analyzed statistically to identify which were the most useful for the discrimination of the different states, according to budding and/or growth phase, in aerobic and microaerophilic conditions. The use of the experimental data for subsequent modeling work was then discussed and compared to simulation results generated with INDISIM- Saccha , which allowed us to advance in the development of this yeast model, and illustrated the utility of data at different levels of observation and the needs and logic behind the development of a microbial individual-based model.

Introducing a novel interaction model structure for the combined effect of temperature and pH on the microbial growth rate.

PubMed

Akkermans, Simen; Noriega Fernandez, Estefanía; Logist, Filip; Van Impe, Jan F

2017-01-02

Efficient modelling of the microbial growth rate can be performed by combining the effects of individual conditions in a multiplicative way, known as the gamma concept. However, several studies have illustrated that interactions between different effects should be taken into account at stressing environmental conditions to achieve a more accurate description of the growth rate. In this research, a novel approach for modeling the interactions between the effects of environmental conditions on the microbial growth rate is introduced. As a case study, the effect of temperature and pH on the growth rate of Escherichia coli K12 is modeled, based on a set of computer controlled bioreactor experiments performed under static environmental conditions. The models compared in this case study are the gamma model, the model of Augustin and Carlier (2000), the model of Le Marc et al. (2002) and the novel multiplicative interaction model, developed in this paper. This novel model enables the separate identification of interactions between the effects of two (or more) environmental conditions. The comparison of these models focuses on the accuracy, interpretability and compatibility with efficient modeling approaches. Moreover, for the separate effects of temperature and pH, new cardinal parameter model structures are proposed. The novel interaction model contributes to a generic modeling approach, resulting in predictive models that are (i) accurate, (ii) easily identifiable with a limited work load, (iii) modular, and (iv) biologically interpretable. Copyright © 2016. Published by Elsevier B.V.

A New Method for Non-destructive Measurement of Biomass, Growth Rates, Vertical Biomass Distribution and Dry Matter Content Based on Digital Image Analysis

PubMed Central

Tackenberg, Oliver

2007-01-01

Background and Aims Biomass is an important trait in functional ecology and growth analysis. The typical methods for measuring biomass are destructive. Thus, they do not allow the development of individual plants to be followed and they require many individuals to be cultivated for repeated measurements. Non-destructive methods do not have these limitations. Here, a non-destructive method based on digital image analysis is presented, addressing not only above-ground fresh biomass (FBM) and oven-dried biomass (DBM), but also vertical biomass distribution as well as dry matter content (DMC) and growth rates. Methods Scaled digital images of the plants silhouettes were taken for 582 individuals of 27 grass species (Poaceae). Above-ground biomass and DMC were measured using destructive methods. With image analysis software Zeiss KS 300, the projected area and the proportion of greenish pixels were calculated, and generalized linear models (GLMs) were developed with destructively measured parameters as dependent variables and parameters derived from image analysis as independent variables. A bootstrap analysis was performed to assess the number of individuals required for re-calibration of the models. Key Results The results of the developed models showed no systematic errors compared with traditionally measured values and explained most of their variance (R2 ≥ 0·85 for all models). The presented models can be directly applied to herbaceous grasses without further calibration. Applying the models to other growth forms might require a re-calibration which can be based on only 10–20 individuals for FBM or DMC and on 40–50 individuals for DBM. Conclusions The methods presented are time and cost effective compared with traditional methods, especially if development or growth rates are to be measured repeatedly. Hence, they offer an alternative way of determining biomass, especially as they are non-destructive and address not only FBM and DBM, but also vertical biomass distribution and DMC. PMID:17353204

Putting Theory to the Test: Which Regulatory Mechanisms Can Drive Realistic Growth of a Root?

PubMed Central

De Vos, Dirk; Vissenberg, Kris; Broeckhove, Jan; Beemster, Gerrit T. S.

2014-01-01

In recent years there has been a strong development of computational approaches to mechanistically understand organ growth regulation in plants. In this study, simulation methods were used to explore which regulatory mechanisms can lead to realistic output at the cell and whole organ scale and which other possibilities must be discarded as they result in cellular patterns and kinematic characteristics that are not consistent with experimental observations for the Arabidopsis thaliana primary root. To aid in this analysis, a ‘Uniform Longitudinal Strain Rule’ (ULSR) was formulated as a necessary condition for stable, unidirectional, symplastic growth. Our simulations indicate that symplastic structures are robust to differences in longitudinal strain rates along the growth axis only if these differences are small and short-lived. Whereas simple cell-autonomous regulatory rules based on counters and timers can produce stable growth, it was found that steady developmental zones and smooth transitions in cell lengths are not feasible. By introducing spatial cues into growth regulation, those inadequacies could be avoided and experimental data could be faithfully reproduced. Nevertheless, a root growth model based on previous polar auxin-transport mechanisms violates the proposed ULSR due to the presence of lateral gradients. Models with layer-specific regulation or layer-driven growth offer potential solutions. Alternatively, a model representing the known cross-talk between auxin, as the cell proliferation promoting factor, and cytokinin, as the cell differentiation promoting factor, predicts the effect of hormone-perturbations on meristem size. By down-regulating PIN-mediated transport through the transcription factor SHY2, cytokinin effectively flattens the lateral auxin gradient, at the basal boundary of the division zone, (thereby imposing the ULSR) to signal the exit of proliferation and start of elongation. This model exploration underlines the value of generating virtual root growth kinematics to dissect and understand the mechanisms controlling this biological system. PMID:25358093

Putting theory to the test: which regulatory mechanisms can drive realistic growth of a root?

PubMed

De Vos, Dirk; Vissenberg, Kris; Broeckhove, Jan; Beemster, Gerrit T S

2014-10-01

In recent years there has been a strong development of computational approaches to mechanistically understand organ growth regulation in plants. In this study, simulation methods were used to explore which regulatory mechanisms can lead to realistic output at the cell and whole organ scale and which other possibilities must be discarded as they result in cellular patterns and kinematic characteristics that are not consistent with experimental observations for the Arabidopsis thaliana primary root. To aid in this analysis, a 'Uniform Longitudinal Strain Rule' (ULSR) was formulated as a necessary condition for stable, unidirectional, symplastic growth. Our simulations indicate that symplastic structures are robust to differences in longitudinal strain rates along the growth axis only if these differences are small and short-lived. Whereas simple cell-autonomous regulatory rules based on counters and timers can produce stable growth, it was found that steady developmental zones and smooth transitions in cell lengths are not feasible. By introducing spatial cues into growth regulation, those inadequacies could be avoided and experimental data could be faithfully reproduced. Nevertheless, a root growth model based on previous polar auxin-transport mechanisms violates the proposed ULSR due to the presence of lateral gradients. Models with layer-specific regulation or layer-driven growth offer potential solutions. Alternatively, a model representing the known cross-talk between auxin, as the cell proliferation promoting factor, and cytokinin, as the cell differentiation promoting factor, predicts the effect of hormone-perturbations on meristem size. By down-regulating PIN-mediated transport through the transcription factor SHY2, cytokinin effectively flattens the lateral auxin gradient, at the basal boundary of the division zone, (thereby imposing the ULSR) to signal the exit of proliferation and start of elongation. This model exploration underlines the value of generating virtual root growth kinematics to dissect and understand the mechanisms controlling this biological system.

Three-dimensional kinetic Monte Carlo simulations of cubic transition metal nitride thin film growth

NASA Astrophysics Data System (ADS)

Nita, F.; Mastail, C.; Abadias, G.

2016-02-01

A three-dimensional kinetic Monte Carlo (KMC) model has been developed and used to simulate the microstructure and growth morphology of cubic transition metal nitride (TMN) thin films deposited by reactive magnetron sputtering. Results are presented for the case of stoichiometric TiN, chosen as a representative TMN prototype. The model is based on a NaCl-type rigid lattice and includes deposition and diffusion events for both N and Ti species. It is capable of reproducing voids and overhangs, as well as surface faceting. Simulations were carried out assuming a uniform flux of incoming particles approaching the surface at normal incidence. The ballistic deposition model is parametrized with an interaction parameter r0 that mimics the capture distance at which incoming particles may stick on the surface, equivalently to a surface trapping mechanism. Two diffusion models are implemented, based on the different ways to compute the site-dependent activation energy for hopping atoms. The influence of temperature (300-500 K), deposition flux (0.1-100 monolayers/s), and interaction parameter r0 (1.5-6.0 Å) on the obtained growth morphology are presented. Microstructures ranging from highly porous, [001]-oriented straight columns with smooth top surface to rough columns emerging with different crystallographic facets are reproduced, depending on kinetic restrictions, deposited energy (seemingly captured by r0), and shadowing effect. The development of facets is a direct consequence of the diffusion model which includes an intrinsic (minimum energy-based) diffusion anisotropy, although no crystallographic diffusion anisotropy was explicitly taken into account at this stage. The time-dependent morphological evolution is analyzed quantitatively to extract the growth exponent β and roughness exponent α , as indicators of kinetic roughening behavior. For dense TiN films, values of α ≈0.7 and β =0.24 are obtained in good agreement with existing experimental data. At this stage a single lattice is considered but the KMC model will be extended further to address more complex mechanisms, such as anisotropic surface diffusion and grain boundary migration at the origin of the competitive columnar growth observed in polycrystalline TiN-based films.

Coupling biomechanics to a cellular level model: an approach to patient-specific image driven multi-scale and multi-physics tumor simulation.

PubMed

May, Christian P; Kolokotroni, Eleni; Stamatakos, Georgios S; Büchler, Philippe

2011-10-01

Modeling of tumor growth has been performed according to various approaches addressing different biocomplexity levels and spatiotemporal scales. Mathematical treatments range from partial differential equation based diffusion models to rule-based cellular level simulators, aiming at both improving our quantitative understanding of the underlying biological processes and, in the mid- and long term, constructing reliable multi-scale predictive platforms to support patient-individualized treatment planning and optimization. The aim of this paper is to establish a multi-scale and multi-physics approach to tumor modeling taking into account both the cellular and the macroscopic mechanical level. Therefore, an already developed biomodel of clinical tumor growth and response to treatment is self-consistently coupled with a biomechanical model. Results are presented for the free growth case of the imageable component of an initially point-like glioblastoma multiforme tumor. The composite model leads to significant tumor shape corrections that are achieved through the utilization of environmental pressure information and the application of biomechanical principles. Using the ratio of smallest to largest moment of inertia of the tumor material to quantify the effect of our coupled approach, we have found a tumor shape correction of 20% by coupling biomechanics to the cellular simulator as compared to a cellular simulation without preferred growth directions. We conclude that the integration of the two models provides additional morphological insight into realistic tumor growth behavior. Therefore, it might be used for the development of an advanced oncosimulator focusing on tumor types for which morphology plays an important role in surgical and/or radio-therapeutic treatment planning. Copyright © 2011 Elsevier Ltd. All rights reserved.

TGFβ (Transforming Growth Factor-β) Blockade Induces a Human-Like Disease in a Nondissecting Mouse Model of Abdominal Aortic Aneurysm.

PubMed

Lareyre, Fabien; Clément, Marc; Raffort, Juliette; Pohlod, Stefanie; Patel, Meghana; Esposito, Bruno; Master, Leanne; Finigan, Alison; Vandestienne, Marie; Stergiopulos, Nikolaos; Taleb, Soraya; Trachet, Bram; Mallat, Ziad

2017-11-01

Current experimental models of abdominal aortic aneurysm (AAA) do not accurately reproduce the major features of human AAA. We hypothesized that blockade of TGFβ (transforming growth factor-β) activity-a guardian of vascular integrity and immune homeostasis-would impair vascular healing in models of nondissecting AAA and would lead to sustained aneurysmal growth until rupture. Here, we test this hypothesis in the elastase-induced AAA model in mice. We analyze AAA development and progression using ultrasound in vivo, synchrotron-based ultrahigh resolution imaging ex vivo, and a combination of biological, histological, and flow cytometry-based cellular and molecular approaches in vitro. Systemic blockade of TGFβ using a monoclonal antibody induces a transition from a self-contained aortic dilatation to a model of sustained aneurysmal growth, associated with the formation of an intraluminal thrombus. AAA growth is associated with wall disruption but no medial dissection and culminates in fatal transmural aortic wall rupture. TGFβ blockade enhances leukocyte infiltration both in the aortic wall and the intraluminal thrombus and aggravates extracellular matrix degradation. Early blockade of IL-1β or monocyte-dependent responses substantially limits AAA severity. However, blockade of IL-1β after disease initiation has no effect on AAA progression to rupture. Endogenous TGFβ activity is required for the healing of AAA. TGFβ blockade may be harnessed to generate new models of AAA with better relevance to the human disease. We expect that the new models will improve our understanding of the pathophysiology of AAA and will be useful in the identification of new therapeutic targets. © 2017 American Heart Association, Inc.

Product unit neural network models for predicting the growth limits of Listeria monocytogenes.

PubMed

Valero, A; Hervás, C; García-Gimeno, R M; Zurera, G

2007-08-01

A new approach to predict the growth/no growth interface of Listeria monocytogenes as a function of storage temperature, pH, citric acid (CA) and ascorbic acid (AA) is presented. A linear logistic regression procedure was performed and a non-linear model was obtained by adding new variables by means of a Neural Network model based on Product Units (PUNN). The classification efficiency of the training data set and the generalization data of the new Logistic Regression PUNN model (LRPU) were compared with Linear Logistic Regression (LLR) and Polynomial Logistic Regression (PLR) models. 92% of the total cases from the LRPU model were correctly classified, an improvement on the percentage obtained using the PLR model (90%) and significantly higher than the results obtained with the LLR model, 80%. On the other hand predictions of LRPU were closer to data observed which permits to design proper formulations in minimally processed foods. This novel methodology can be applied to predictive microbiology for describing growth/no growth interface of food-borne microorganisms such as L. monocytogenes. The optimal balance is trying to find models with an acceptable interpretation capacity and with good ability to fit the data on the boundaries of variable range. The results obtained conclude that these kinds of models might well be very a valuable tool for mathematical modeling.

Determining Individual Variation in Growth and Its Implication for Life-History and Population Processes Using the Empirical Bayes Method

PubMed Central

Vincenzi, Simone; Mangel, Marc; Crivelli, Alain J.; Munch, Stephan; Skaug, Hans J.

2014-01-01

The differences in demographic and life-history processes between organisms living in the same population have important consequences for ecological and evolutionary dynamics. Modern statistical and computational methods allow the investigation of individual and shared (among homogeneous groups) determinants of the observed variation in growth. We use an Empirical Bayes approach to estimate individual and shared variation in somatic growth using a von Bertalanffy growth model with random effects. To illustrate the power and generality of the method, we consider two populations of marble trout Salmo marmoratus living in Slovenian streams, where individually tagged fish have been sampled for more than 15 years. We use year-of-birth cohort, population density during the first year of life, and individual random effects as potential predictors of the von Bertalanffy growth function's parameters k (rate of growth) and (asymptotic size). Our results showed that size ranks were largely maintained throughout marble trout lifetime in both populations. According to the Akaike Information Criterion (AIC), the best models showed different growth patterns for year-of-birth cohorts as well as the existence of substantial individual variation in growth trajectories after accounting for the cohort effect. For both populations, models including density during the first year of life showed that growth tended to decrease with increasing population density early in life. Model validation showed that predictions of individual growth trajectories using the random-effects model were more accurate than predictions based on mean size-at-age of fish. PMID:25211603

Knowledge representation to support reasoning based on multiple models

NASA Technical Reports Server (NTRS)

Gillam, April; Seidel, Jorge P.; Parker, Alice C.

1990-01-01

Model Based Reasoning is a powerful tool used to design and analyze systems, which are often composed of numerous interactive, interrelated subsystems. Models of the subsystems are written independently and may be used together while they are still under development. Thus the models are not static. They evolve as information becomes obsolete, as improved artifact descriptions are developed, and as system capabilities change. Researchers are using three methods to support knowledge/data base growth, to track the model evolution, and to handle knowledge from diverse domains. First, the representation methodology is based on having pools, or types, of knowledge from which each model is constructed. In addition information is explicit. This includes the interactions between components, the description of the artifact structure, and the constraints and limitations of the models. The third principle we have followed is the separation of the data and knowledge from the inferencing and equation solving mechanisms. This methodology is used in two distinct knowledge-based systems: one for the design of space systems and another for the synthesis of VLSI circuits. It has facilitated the growth and evolution of our models, made accountability of results explicit, and provided credibility for the user community. These capabilities have been implemented and are being used in actual design projects.

Network-based model of the growth of termite nests

NASA Astrophysics Data System (ADS)

Eom, Young-Ho; Perna, Andrea; Fortunato, Santo; Darrouzet, Eric; Theraulaz, Guy; Jost, Christian

2015-12-01

We present a model for the growth of the transportation network inside nests of the social insect subfamily Termitinae (Isoptera, termitidae). These nests consist of large chambers (nodes) connected by tunnels (edges). The model based on the empirical analysis of the real nest networks combined with pruning (edge removal, either random or weighted by betweenness centrality) and a memory effect (preferential growth from the latest added chambers) successfully predicts emergent nest properties (degree distribution, size of the largest connected component, average path lengths, backbone link ratios, and local graph redundancy). The two pruning alternatives can be associated with different genuses in the subfamily. A sensitivity analysis on the pruning and memory parameters indicates that Termitinae networks favor fast internal transportation over efficient defense strategies against ant predators. Our results provide an example of how complex network organization and efficient network properties can be generated from simple building rules based on local interactions and contribute to our understanding of the mechanisms that come into play for the formation of termite networks and of biological transportation networks in general.

Shock Initiation Experiments with Ignition and Growth Modeling on the HMX-Based Explosive LX-14

NASA Astrophysics Data System (ADS)

Vandersall, Kevin S.; Dehaven, Martin R.; Strickland, Shawn L.; Tarver, Craig M.; Springer, H. Keo; Cowan, Matt R.

2017-06-01

Shock initiation experiments on the HMX-based explosive LX-14 were performed to obtain in-situ pressure gauge data, characterize the run-distance-to-detonation behavior, and provide a basis for Ignition and Growth reactive flow modeling. A 101 mm diameter gas gun was utilized to initiate the explosive charges with manganin piezoresistive pressure gauge packages placed between sample disks pressed to different densities ( 1.57 or 1.83 g/cm3 that corresponds to 85 or 99% of theoretical maximum density (TMD), respectively). The shock sensitivity was found to increase with decreasing density as expected. Ignition and Growth model parameters were derived that yielded reasonable agreement with the experimental data at both initial densities. The shock sensitivity at the tested densities will be compared to prior work published on other HMX-based formulations. This work performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344. This work was funded in part by the Joint DoD-DOE Munitions Program.

Limits to the Positive Effect of Ocean Acidification on Macroalgal Primary Production, Interactions with Light and Temperature

NASA Astrophysics Data System (ADS)

Kubler, J.; Dudgeon, S. R.; Nisumaa, A. M.

2016-02-01

About one third of macroalgal species lack any carbon concentrating mechanism (CCM), which prevents carbon limitation under air equilibrium in other seaweed species. It is predicted that those species lacking CCM's will benefit from ongoing ocean acidification in terms of primary productivity and growth. The absolute sizes and pattern of those benefits are not known. Here, we compare the results of a model based on composite data from the literature, with a growth experiment using Plocamium cartilagineum, a broadly distributed rhodophyte species lacking a carbon concentrating mechanism and hypothesized to be carbon limited under current conditions. We grew P. cartilagineum, at 15 and 20°C in seawater aerated with a total of 53 different pCO2s (from 344 to 1053µatm), in 8 multiweek trials over 12 months. We measured growth and photosynthetic rates. A linear mixed model analysis was used to partition the effect sizes of drivers of variation in the experiment. The growth rates and maximum photosynthetic rates responded nonlinearly to OA, increasing with elevated pCO2 from recent atmospheric level to up 450µatm and decreasing at higher pCO2. Light harvesting efficiency was unaffected by pCO2 and inversely related to temperature. We were able to compare the results of the growth experiment directly to the model based on the additive effects of temperature and pCO2 on photosynthetic rates, finding concordance of the pattern of response. The size of the effect of pCO2 on growth rate in the experiment was greater than the effect predicted by the model for net primary productivity. These results predict that the benefit of OA for macroalgal growth may disappear as ocean acidification continues through this century.

Estimating thermal performance curves from repeated field observations

USGS Publications Warehouse

Childress, Evan; Letcher, Benjamin H.

2017-01-01

Estimating thermal performance of organisms is critical for understanding population distributions and dynamics and predicting responses to climate change. Typically, performance curves are estimated using laboratory studies to isolate temperature effects, but other abiotic and biotic factors influence temperature-performance relationships in nature reducing these models' predictive ability. We present a model for estimating thermal performance curves from repeated field observations that includes environmental and individual variation. We fit the model in a Bayesian framework using MCMC sampling, which allowed for estimation of unobserved latent growth while propagating uncertainty. Fitting the model to simulated data varying in sampling design and parameter values demonstrated that the parameter estimates were accurate, precise, and unbiased. Fitting the model to individual growth data from wild trout revealed high out-of-sample predictive ability relative to laboratory-derived models, which produced more biased predictions for field performance. The field-based estimates of thermal maxima were lower than those based on laboratory studies. Under warming temperature scenarios, field-derived performance models predicted stronger declines in body size than laboratory-derived models, suggesting that laboratory-based models may underestimate climate change effects. The presented model estimates true, realized field performance, avoiding assumptions required for applying laboratory-based models to field performance, which should improve estimates of performance under climate change and advance thermal ecology.

Recruiting Conventional Tree Architecture Models into State-of-the-Art LiDAR Mapping for Investigating Tree Growth Habits in Structure.

PubMed

Lin, Yi; Jiang, Miao; Pellikka, Petri; Heiskanen, Janne

2018-01-01

Mensuration of tree growth habits is of considerable importance for understanding forest ecosystem processes and forest biophysical responses to climate changes. However, the complexity of tree crown morphology that is typically formed after many years of growth tends to render it a non-trivial task, even for the state-of-the-art 3D forest mapping technology-light detection and ranging (LiDAR). Fortunately, botanists have deduced the large structural diversity of tree forms into only a limited number of tree architecture models, which can present a-priori knowledge about tree structure, growth, and other attributes for different species. This study attempted to recruit Hallé architecture models (HAMs) into LiDAR mapping to investigate tree growth habits in structure. First, following the HAM-characterized tree structure organization rules, we run the kernel procedure of tree species classification based on the LiDAR-collected point clouds using a support vector machine classifier in the leave-one-out-for-cross-validation mode. Then, the HAM corresponding to each of the classified tree species was identified based on expert knowledge, assisted by the comparison of the LiDAR-derived feature parameters. Next, the tree growth habits in structure for each of the tree species were derived from the determined HAM. In the case of four tree species growing in the boreal environment, the tests indicated that the classification accuracy reached 85.0%, and their growth habits could be derived by qualitative and quantitative means. Overall, the strategy of recruiting conventional HAMs into LiDAR mapping for investigating tree growth habits in structure was validated, thereby paving a new way for efficiently reflecting tree growth habits and projecting forest structure dynamics.

Recruiting Conventional Tree Architecture Models into State-of-the-Art LiDAR Mapping for Investigating Tree Growth Habits in Structure

PubMed Central

Lin, Yi; Jiang, Miao; Pellikka, Petri; Heiskanen, Janne

2018-01-01

Mensuration of tree growth habits is of considerable importance for understanding forest ecosystem processes and forest biophysical responses to climate changes. However, the complexity of tree crown morphology that is typically formed after many years of growth tends to render it a non-trivial task, even for the state-of-the-art 3D forest mapping technology—light detection and ranging (LiDAR). Fortunately, botanists have deduced the large structural diversity of tree forms into only a limited number of tree architecture models, which can present a-priori knowledge about tree structure, growth, and other attributes for different species. This study attempted to recruit Hallé architecture models (HAMs) into LiDAR mapping to investigate tree growth habits in structure. First, following the HAM-characterized tree structure organization rules, we run the kernel procedure of tree species classification based on the LiDAR-collected point clouds using a support vector machine classifier in the leave-one-out-for-cross-validation mode. Then, the HAM corresponding to each of the classified tree species was identified based on expert knowledge, assisted by the comparison of the LiDAR-derived feature parameters. Next, the tree growth habits in structure for each of the tree species were derived from the determined HAM. In the case of four tree species growing in the boreal environment, the tests indicated that the classification accuracy reached 85.0%, and their growth habits could be derived by qualitative and quantitative means. Overall, the strategy of recruiting conventional HAMs into LiDAR mapping for investigating tree growth habits in structure was validated, thereby paving a new way for efficiently reflecting tree growth habits and projecting forest structure dynamics. PMID:29515616

GLISTRboost: Combining Multimodal MRI Segmentation, Registration, and Biophysical Tumor Growth Modeling with Gradient Boosting Machines for Glioma Segmentation.

PubMed

Bakas, Spyridon; Zeng, Ke; Sotiras, Aristeidis; Rathore, Saima; Akbari, Hamed; Gaonkar, Bilwaj; Rozycki, Martin; Pati, Sarthak; Davatzikos, Christos

2016-01-01

We present an approach for segmenting low- and high-grade gliomas in multimodal magnetic resonance imaging volumes. The proposed approach is based on a hybrid generative-discriminative model. Firstly, a generative approach based on an Expectation-Maximization framework that incorporates a glioma growth model is used to segment the brain scans into tumor, as well as healthy tissue labels. Secondly, a gradient boosting multi-class classification scheme is used to refine tumor labels based on information from multiple patients. Lastly, a probabilistic Bayesian strategy is employed to further refine and finalize the tumor segmentation based on patient-specific intensity statistics from the multiple modalities. We evaluated our approach in 186 cases during the training phase of the BRAin Tumor Segmentation (BRATS) 2015 challenge and report promising results. During the testing phase, the algorithm was additionally evaluated in 53 unseen cases, achieving the best performance among the competing methods.

Earth surface modeling for education: How effective is it? Latest classroom tests with Web-based Interactive Landform Simulation Model - Grand Canyon (WILSIM-GC)

NASA Astrophysics Data System (ADS)

Luo, W.; Pelletier, J. D.; Smith, T.; Whalley, K.; Shelhamer, A.; Darling, A.; Ormand, C. J.; Duffin, K.; Hung, W. C.; Iverson, E. A. R.; Shernoff, D.; Zhai, X.; Chiang, J. L.; Lotter, N.

2016-12-01

The Web-based Interactive Landform Simulation Model - Grand Canyon (WILSIM-GC, http://serc.carleton.edu/landform/) is a simplified version of a physically-based model that simulates bedrock channel erosion, cliff retreat, and base level change. Students can observe the landform evolution in animation under different scenarios by changing parameter values. In addition, cross-sections and profiles at different time intervals can be displayed and saved for further quantitative analysis. Students were randomly assigned to a treatment group (using WILSIM-GC simulation) or a control group (using traditional paper-based material). Pre- and post-tests were administered to measure students' understanding of the concepts and processes related to Grand Canyon formation and evolution. Results from the ANOVA showed that for both groups there were statistically significant growth in scores from pre-test to post-test [F(1, 47) = 25.82, p < .001], but the growth in scores between the two groups was not statistically significant [F(1, 47) = 0.08, p =.774]. In semester 1, the WILSIM-GC group showed greater growth, while in semester 2, the paper-based group showed greater growth. Additionally, a significant time × group × gender × semester interaction effect was observed [F(1, 47) = 4.76, p =.034]. Here, in semester 1 female students were more strongly advantaged by the WILSIM-GC intervention than male students, while in semester 2, female students were less strongly advantaged than male students. The new results are consistent with our initial findings (Luo et al., 2016) and others reported in the literature, i.e., simulation approach is at least equally effective as traditional paper-based method in teaching students about landform evolution. Survey data indicate that students favor the simulation approach. Further study is needed to investigate the reasons for the difference by gender.

Aging, Maturation and Growth of Sauropodomorph Dinosaurs as Deduced from Growth Curves Using Long Bone Histological Data: An Assessment of Methodological Constraints and Solutions

PubMed Central

Griebeler, Eva Maria; Klein, Nicole; Sander, P. Martin

2013-01-01

Information on aging, maturation, and growth is important for understanding life histories of organisms. In extinct dinosaurs, such information can be derived from the histological growth record preserved in the mid-shaft cortex of long bones. Here, we construct growth models to estimate ages at death, ages at sexual maturity, ages at which individuals were fully-grown, and maximum growth rates from the growth record preserved in long bones of six sauropod dinosaur individuals (one indeterminate mamenchisaurid, two Apatosaurus sp., two indeterminate diplodocids, and one Camarasaurus sp.) and one basal sauropodomorph dinosaur individual (Plateosaurus engelhardti). Using these estimates, we establish allometries between body mass and each of these traits and compare these to extant taxa. Growth models considered for each dinosaur individual were the von Bertalanffy model, the Gompertz model, and the logistic model (LGM), all of which have inherently fixed inflection points, and the Chapman-Richards model in which the point is not fixed. We use the arithmetic mean of the age at the inflection point and of the age at which 90% of asymptotic mass is reached to assess respectively the age at sexual maturity or the age at onset of reproduction, because unambiguous indicators of maturity in Sauropodomorpha are lacking. According to an AIC-based model selection process, the LGM was the best model for our sauropodomorph sample. Allometries established are consistent with literature data on other Sauropodomorpha. All Sauropodomorpha reached full size within a time span similar to scaled-up modern mammalian megaherbivores and had similar maximum growth rates to scaled-up modern megaherbivores and ratites, but growth rates of Sauropodomorpha were lower than of an average mammal. Sauropodomorph ages at death probably were lower than that of average scaled-up ratites and megaherbivores. Sauropodomorpha were older at maturation than scaled-up ratites and average mammals, but younger than scaled-up megaherbivores. PMID:23840575

Aging, Maturation and Growth of Sauropodomorph Dinosaurs as Deduced from Growth Curves Using Long Bone Histological Data: An Assessment of Methodological Constraints and Solutions.

PubMed

Griebeler, Eva Maria; Klein, Nicole; Sander, P Martin

2013-01-01

Information on aging, maturation, and growth is important for understanding life histories of organisms. In extinct dinosaurs, such information can be derived from the histological growth record preserved in the mid-shaft cortex of long bones. Here, we construct growth models to estimate ages at death, ages at sexual maturity, ages at which individuals were fully-grown, and maximum growth rates from the growth record preserved in long bones of six sauropod dinosaur individuals (one indeterminate mamenchisaurid, two Apatosaurus sp., two indeterminate diplodocids, and one Camarasaurus sp.) and one basal sauropodomorph dinosaur individual (Plateosaurus engelhardti). Using these estimates, we establish allometries between body mass and each of these traits and compare these to extant taxa. Growth models considered for each dinosaur individual were the von Bertalanffy model, the Gompertz model, and the logistic model (LGM), all of which have inherently fixed inflection points, and the Chapman-Richards model in which the point is not fixed. We use the arithmetic mean of the age at the inflection point and of the age at which 90% of asymptotic mass is reached to assess respectively the age at sexual maturity or the age at onset of reproduction, because unambiguous indicators of maturity in Sauropodomorpha are lacking. According to an AIC-based model selection process, the LGM was the best model for our sauropodomorph sample. Allometries established are consistent with literature data on other Sauropodomorpha. All Sauropodomorpha reached full size within a time span similar to scaled-up modern mammalian megaherbivores and had similar maximum growth rates to scaled-up modern megaherbivores and ratites, but growth rates of Sauropodomorpha were lower than of an average mammal. Sauropodomorph ages at death probably were lower than that of average scaled-up ratites and megaherbivores. Sauropodomorpha were older at maturation than scaled-up ratites and average mammals, but younger than scaled-up megaherbivores.

Dry matter partitioning models for the simulation of individual fruit growth in greenhouse cucumber canopies

PubMed Central

Wiechers, Dirk; Kahlen, Katrin; Stützel, Hartmut

2011-01-01

Background and Aims Growth imbalances between individual fruits are common in indeterminate plants such as cucumber (Cucumis sativus). In this species, these imbalances can be related to differences in two growth characteristics, fruit growth duration until reaching a given size and fruit abortion. Both are related to distribution, and environmental factors as well as canopy architecture play a key role in their differentiation. Furthermore, events leading to a fruit reaching its harvestable size before or simultaneously with a prior fruit can be observed. Functional–structural plant models (FSPMs) allow for interactions between environmental factors, canopy architecture and physiological processes. Here, we tested hypotheses which account for these interactions by introducing dominance and abortion thresholds for the partitioning of assimilates between growing fruits. Methods Using the L-System formalism, an FSPM was developed which combined a model for architectural development, a biochemical model of photosynthesis and a model for assimilate partitioning, the last including a fruit growth model based on a size-related potential growth rate (RP). Starting from a distribution proportional to RP, the model was extended by including abortion and dominance. Abortion was related to source strength and dominance to sink strength. Both thresholds were varied to test their influence on fruit growth characteristics. Simulations were conducted for a dense row and a sparse isometric canopy. Key Results The simple partitioning models failed to simulate individual fruit growth realistically. The introduction of abortion and dominance thresholds gave the best results. Simulations of fruit growth durations and abortion rates were in line with measurements, and events in which a fruit was harvestable earlier than an older fruit were reproduced. Conclusions Dominance and abortion events need to be considered when simulating typical fruit growth traits. By integrating environmental factors, the FSPM can be a valuable tool to analyse and improve existing knowledge about the dynamics of assimilates partitioning. PMID:21715366

Climate Change Implications to Irrigated Rice Production in Southern Brazil: A Modelling Approach

NASA Astrophysics Data System (ADS)

Dos Santos, Thiago

Rice is one of the staple foods for more than three billion people worldwide. When cultivated under irrigated conditions (i.e. lowland rice), rice is one of the most intensive water consumer crops globally. Therefore, representation of rice growth should be integrated into the latest land surface models to allow studies on food security and to ensure that accurate simulations of the bidirectional feedbacks between the land surface and atmosphere take place. In this study, I present a new process-based model for rice fields that includes rice growth and rice irrigation as modules within the Agro-IBIS dynamic agro-ecosystem model. The model includes a series of equations, agricultural management parameters and an irrigation scheme that are specifically tailored for rice crops. The model was evaluated against leaf area index and biomass observations, obtained for one growing season in Rio Grande do Sul state (southern Brazil), and in Los Banos, Philippines. The model accurately captured the temporal dynamics of leaf area index in both the Brazilian and the Philippine sites, and predicted end-of-season biomass with an error of between -9.5% and 11.3% depending on the location and the plant organ. Rice phenology is predicted by the model based on experimentally-derived growth rates, and was evaluated by comparing simulated and observed durations of the four growth phases considered by the model. Agro-IBIS showed a tendency to overestimate the duration of the growth stages between 3% and 16%, but underestimated by 8% the duration of the panicle formation phase in one growing season. The new irrigation model is based on the water balance at the surface and applies irrigation in order to keep the water layer at the paddy field always in the optimum level. A set of climate projections from global climate models under two emission scenarios, and excluding and considering CO2 fertilizations effects, was used to drive the updated Agro-IBIS to estimate the effects of climate change on rice phenology, productivity and irrigation demand in southern Brazil during the 21st century. The results suggest that rice yields in southern Brazil can increase in average by 10-30%, but by up to 80% in regions where the current temperature is below optimum for rice growth and therefore will be benefited by warming. However, the same region might experience higher water demand for rice irrigation, which might pose a challenge for rice production in that region.

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

PubMed

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

2017-10-11

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

solveME: fast and reliable solution of nonlinear ME models.

PubMed

Yang, Laurence; Ma, Ding; Ebrahim, Ali; Lloyd, Colton J; Saunders, Michael A; Palsson, Bernhard O

2016-09-22

Genome-scale models of metabolism and macromolecular expression (ME) significantly expand the scope and predictive capabilities of constraint-based modeling. ME models present considerable computational challenges: they are much (>30 times) larger than corresponding metabolic reconstructions (M models), are multiscale, and growth maximization is a nonlinear programming (NLP) problem, mainly due to macromolecule dilution constraints. Here, we address these computational challenges. We develop a fast and numerically reliable solution method for growth maximization in ME models using a quad-precision NLP solver (Quad MINOS). Our method was up to 45 % faster than binary search for six significant digits in growth rate. We also develop a fast, quad-precision flux variability analysis that is accelerated (up to 60× speedup) via solver warm-starts. Finally, we employ the tools developed to investigate growth-coupled succinate overproduction, accounting for proteome constraints. Just as genome-scale metabolic reconstructions have become an invaluable tool for computational and systems biologists, we anticipate that these fast and numerically reliable ME solution methods will accelerate the wide-spread adoption of ME models for researchers in these fields.

Modeling Calculation and Synthesis of Alumina Whiskers Based on the Vapor Deposition Process.

PubMed

Gong, Wei; Li, Xiangcheng; Zhu, Boquan

2017-10-17

This study simulated the bulk structure and surface energy of Al₂O₃ based on the density of states (DOS) and studied the synthesis and microstructure of one-dimensional Al₂O₃ whiskers. The simulation results indicate that the (001) surface has a higher surface energy than the others. The growth mechanism of Al₂O₃ whiskers follows vapor-solid (VS) growth. For the (001) surface with the higher surface energy, the driving force of crystal growth would be more intense in the (001) plane, and the alumina crystal would tend to grow preferentially along the direction of the (001) plane from the tip of the crystal. The Al₂O₃ grows to the shape of whisker with [001] orientation, which is proved both through modeling and experimentation.

dK/da effects on the SCC growth rates of nickel base alloys in high-temperature water

NASA Astrophysics Data System (ADS)

Chen, Kai; Wang, Jiamei; Du, Donghai; Andresen, Peter L.; Zhang, Lefu

2018-05-01

The effect of dK/da on crack growth behavior of nickel base alloys has been studied by conducting stress corrosion cracking tests under positive and negative dK/da loading conditions on Alloys 690, 600 and X-750 in high temperature water. Results indicate that positive dK/da accelerates the SCC growth rates, and the accelerating effect increases with dK/da and the initial CGR. The FRI model was found to underestimate the dK/da effect by ∼100X, especially for strain hardening materials, and this underscores the need for improved insight and models for crack tip strain rate. The effect of crack tip strain rate and dK/dt in particular can explain the dK/da accelerating effect.

Growth and mortality of larval Myctophum affine (Myctophidae, Teleostei).

PubMed

Namiki, C; Katsuragawa, M; Zani-Teixeira, M L

2015-04-01

The growth and mortality rates of Myctophum affine larvae were analysed based on samples collected during the austral summer and winter of 2002 from south-eastern Brazilian waters. The larvae ranged in size from 2·75 to 14·00 mm standard length (L(S)). Daily increment counts from 82 sagittal otoliths showed that the age of M. affine ranged from 2 to 28 days. Three models were applied to estimate the growth rate: linear regression, exponential model and Laird-Gompertz model. The exponential model best fitted the data, and L(0) values from exponential and Laird-Gompertz models were close to the smallest larva reported in the literature (c. 2·5 mm L(S)). The average growth rate (0·33 mm day(-1)) was intermediate among lanternfishes. The mortality rate (12%) during the larval period was below average compared with other marine fish species but similar to some epipelagic fishes that occur in the area. © 2015 The Fisheries Society of the British Isles.

Plant growth and respiration re-visited: maintenance respiration defined – it is an emergent property of, not a separate process within, the system – and why the respiration : photosynthesis ratio is conservative

PubMed Central

Thornley, John H. M.

2011-01-01

Background and Aims Plant growth and respiration still has unresolved issues, examined here using a model. The aims of this work are to compare the model's predictions with McCree's observation-based respiration equation which led to the ‘growth respiration/maintenance respiration paradigm’ (GMRP) – this is required to give the model credibility; to clarify the nature of maintenance respiration (MR) using a model which does not represent MR explicitly; and to examine algebraic and numerical predictions for the respiration:photosynthesis ratio. Methods A two-state variable growth model is constructed, with structure and substrate, applicable on plant to ecosystem scales. Four processes are represented: photosynthesis, growth with growth respiration (GR), senescence giving a flux towards litter, and a recycling of some of this flux. There are four significant parameters: growth efficiency, rate constants for substrate utilization and structure senescence, and fraction of structure returned to the substrate pool. Key Results The model can simulate McCree's data on respiration, providing an alternative interpretation to the GMRP. The model's parameters are related to parameters used in this paradigm. MR is defined and calculated in terms of the model's parameters in two ways: first during exponential growth at zero growth rate; and secondly at equilibrium. The approaches concur. The equilibrium respiration:photosynthesis ratio has the value of 0·4, depending only on growth efficiency and recycling fraction. Conclusions McCree's equation is an approximation that the model can describe; it is mistaken to interpret his second coefficient as a maintenance requirement. An MR rate is defined and extracted algebraically from the model. MR as a specific process is not required and may be replaced with an approach from which an MR rate emerges. The model suggests that the respiration:photosynthesis ratio is conservative because it depends on two parameters only whose values are likely to be similar across ecosystems. PMID:21948663

Estimation of Staphylococcus aureus growth parameters from turbidity data: characterization of strain variation and comparison of methods.

PubMed

Lindqvist, R

2006-07-01

Turbidity methods offer possibilities for generating data required for addressing microorganism variability in risk modeling given that the results of these methods correspond to those of viable count methods. The objectives of this study were to identify the best approach for determining growth parameters based on turbidity data and use of a Bioscreen instrument and to characterize variability in growth parameters of 34 Staphylococcus aureus strains of different biotypes isolated from broiler carcasses. Growth parameters were estimated by fitting primary growth models to turbidity growth curves or to detection times of serially diluted cultures either directly or by using an analysis of variance (ANOVA) approach. The maximum specific growth rates in chicken broth at 17 degrees C estimated by time to detection methods were in good agreement with viable count estimates, whereas growth models (exponential and Richards) underestimated growth rates. Time to detection methods were selected for strain characterization. The variation of growth parameters among strains was best described by either the logistic or lognormal distribution, but definitive conclusions require a larger data set. The distribution of the physiological state parameter ranged from 0.01 to 0.92 and was not significantly different from a normal distribution. Strain variability was important, and the coefficient of variation of growth parameters was up to six times larger among strains than within strains. It is suggested to apply a time to detection (ANOVA) approach using turbidity measurements for convenient and accurate estimation of growth parameters. The results emphasize the need to consider implications of strain variability for predictive modeling and risk assessment.

Synchrotron characterization of nanograined UO 2 grain growth

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

Mo, Kun; Miao, Yinbin; Yun, Di

2015-09-30

This activity is supported by the US Nuclear Energy Advanced Modeling and Simulation (NEAMS) Fuels Product Line (FPL) and aims at providing experimental data for the validation of the mesoscale simulation code MARMOT. MARMOT is a mesoscale multiphysics code that predicts the coevolution of microstructure and properties within reactor fuel during its lifetime in the reactor. It is an important component of the Moose-Bison-Marmot (MBM) code suite that has been developed by Idaho National Laboratory (INL) to enable next generation fuel performance modeling capability as part of the NEAMS Program FPL. In order to ensure the accuracy of the microstructuremore » based materials models being developed within the MARMOT code, extensive validation efforts must be carried out. In this report, we summarize our preliminary synchrotron radiation experiments at APS to determine the grain size of nanograin UO 2. The methodology and experimental setup developed in this experiment can directly apply to the proposed in-situ grain growth measurements. The investigation of the grain growth kinetics was conducted based on isothermal annealing and grain growth characterization as functions of duration and temperature. The kinetic parameters such as activation energy for grain growth for UO 2 with different stoichiometry are obtained and compared with molecular dynamics (MD) simulations.« less

Supplying materials needed for grain growth characterizations of nano-grained UO 2

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

Mo, Kun; Miao, Yinbin; Yun, Di

2015-09-30

This activity is supported by the US Nuclear Energy Advanced Modeling and Simulation (NEAMS) Fuels Product Line (FPL) and aims at providing experimental data for the validation of the mesoscale simulation code MARMOT. MARMOT is a mesoscale multiphysics code that predicts the coevolution of microstructure and properties within reactor fuel during its lifetime in the reactor. It is an important component of the Moose-Bison-Marmot (MBM) code suite that has been developed by Idaho National Laboratory (INL) to enable next generation fuel performance modeling capability as part of the NEAMS Program FPL. In order to ensure the accuracy of the microstructuremore » based materials models being developed within the MARMOT code, extensive validation efforts must be carried out. In this report, we summarize our preliminary synchrotron radiation experiments at APS to determine the grain size of nanograin UO 2. The methodology and experimental setup developed in this experiment can directly apply to the proposed in-situ grain growth measurements. The investigation of the grain growth kinetics was conducted based on isothermal annealing and grain growth characterization as functions of duration and temperature. The kinetic parameters such as activation energy for grain growth for UO 2 with different stoichiometry are obtained and compared with molecular dynamics (MD) simulations.« less

Academic Growth Expectations for Students with Emotional and Behavior Disorders

ERIC Educational Resources Information Center

Ysseldyke, Jim; Scerra, Carmine; Stickney, Eric; Beckler, Amanda; Dituri, Joan; Ellis, Karen

2017-01-01

Computer adaptive assessments were used to monitor the academic status and growth of students with emotional behavior disorders (EBD) in reading (N = 321) and math (N = 322) in a regional service center serving 56 school districts. A cohort sequential model was used to compare that performance to the status and growth of a national user base of…

Systems and Photosystems: Cellular Limits of Autotrophic Productivity in Cyanobacteria

PubMed Central

Burnap, Robert L.

2014-01-01

Recent advances in the modeling of microbial growth and metabolism have shown that growth rate critically depends upon the optimal allocation of finite proteomic resources among different cellular functions and that modeling growth rates becomes more realistic with the explicit accounting for the costs of macromolecular synthesis, most importantly, protein expression. The “proteomic constraint” is considered together with its application to understanding photosynthetic microbial growth. The central hypothesis is that physical limits of cellular space (and corresponding solvation capacity) in conjunction with cell surface-to-volume ratios represent the underlying constraints on the maximal rate of autotrophic microbial growth. The limitation of cellular space thus constrains the size the total complement of macromolecules, dissolved ions, and metabolites. To a first approximation, the upper limit in the cellular amount of the total proteome is bounded this space limit. This predicts that adaptation to osmotic stress will result in lower maximal growth rates due to decreased cellular concentrations of core metabolic proteins necessary for cell growth owing the accumulation of compatible osmolytes, as surmised previously. The finite capacity of membrane and cytoplasmic space also leads to the hypothesis that the species-specific differences in maximal growth rates likely reflect differences in the allocation of space to niche-specific proteins with the corresponding diminution of space devoted to other functions including proteins of core autotrophic metabolism, which drive cell reproduction. An optimization model for autotrophic microbial growth, the autotrophic replicator model, was developed based upon previous work investigating heterotrophic growth. The present model describes autotrophic growth in terms of the allocation protein resources among core functional groups including the photosynthetic electron transport chain, light-harvesting antennae, and the ribosome groups. PMID:25654078

Study on Spatial Spillover Effects of Logistics Industry Development for Economic Growth in the Yangtze River Delta City Cluster Based on Spatial Durbin Model

PubMed Central

Xu, Xinxing

2017-01-01

The overall entropy method is used to evaluate the development level of the logistics industry in the city based on a mechanism analysis of the spillover effect of the development of the logistics industry on economic growth, according to the panel data of 26 cities in the Yangtze River delta. On this basis, the paper uses the spatial durbin model to study the direct impact of the development of the logistics industry on economic growth and the spatial spillover effect. The results show that the direct impact coefficient of the development of the logistics industry in the Yangtze River Delta urban agglomeration on local economic growth is 0.092, and the significant spatial spillover effect on the economic growth in the surrounding area is 0.197. Compared with the labor force input, capital investment and the degree of opening to the world, and government functions, the logistics industry’s direct impact coefficient is the largest, other than capital investment; the coefficient of the spillover effect is higher than other control variables, making it a “strong engine” of the Yangtze River Delta urban agglomeration economic growth. PMID:29207555

Study on Spatial Spillover Effects of Logistics Industry Development for Economic Growth in the Yangtze River Delta City Cluster Based on Spatial Durbin Model.

PubMed

Xu, Xinxing; Wang, Yuhong

2017-12-04

The overall entropy method is used to evaluate the development level of the logistics industry in the city based on a mechanism analysis of the spillover effect of the development of the logistics industry on economic growth, according to the panel data of 26 cities in the Yangtze River delta. On this basis, the paper uses the spatial durbin model to study the direct impact of the development of the logistics industry on economic growth and the spatial spillover effect. The results show that the direct impact coefficient of the development of the logistics industry in the Yangtze River Delta urban agglomeration on local economic growth is 0.092, and the significant spatial spillover effect on the economic growth in the surrounding area is 0.197. Compared with the labor force input, capital investment and the degree of opening to the world, and government functions, the logistics industry's direct impact coefficient is the largest, other than capital investment; the coefficient of the spillover effect is higher than other control variables, making it a "strong engine" of the Yangtze River Delta urban agglomeration economic growth.

Modeling invasive breast cancer: growth factors propel progression of HER2-positive premalignant lesions

PubMed Central

Pradeep, C-R; Zeisel, A; Köstler, WJ; Lauriola, M; Jacob-Hirsch, J; Haibe-Kains, B; Amariglio, N; Ben-Chetrit, N; Emde, A; Solomonov, I; Neufeld, G; Piccart, M; Sagi, I; Sotiriou, C; Rechavi, G; Domany, E; Desmedt, C; Yarden, Y

2013-01-01

The HER2/neu oncogene encodes a receptor-like tyrosine kinase whose overexpression in breast cancer predicts poor prognosis and resistance to conventional therapies. However, the mechanisms underlying aggressiveness of HER2 (human epidermal growth factor receptor 2)-overexpressing tumors remain incompletely understood. Because it assists epidermal growth factor (EGF) and neuregulin receptors, we overexpressed HER2 in MCF10A mammary cells and applied growth factors. HER2-overexpressing cells grown in extracellular matrix formed filled spheroids, which protruded outgrowths upon growth factor stimulation. Our transcriptome analyses imply a two-hit model for invasive growth: HER2-induced proliferation and evasion from anoikis generate filled structures, which are morphologically and transcriptionally analogous to preinvasive patients’ lesions. In the second hit, EGF escalates signaling and transcriptional responses leading to invasive growth. Consistent with clinical relevance, a gene expression signature based on the HER2/EGF-activated transcriptional program can predict poorer prognosis of a subgroup of HER2-overexpressing patients. In conclusion, the integration of a three-dimensional cellular model and clinical data attributes progression of HER2-overexpressing lesions to EGF-like growth factors acting in the context of the tumor's microenvironment. PMID:22139081

Ontogenetic scaling of metabolism, growth, and assimilation: testing metabolic scaling theory with Manduca sexta larvae.

PubMed

Sears, Katie E; Kerkhoff, Andrew J; Messerman, Arianne; Itagaki, Haruhiko

2012-01-01

Metabolism, growth, and the assimilation of energy and materials are essential processes that are intricately related and depend heavily on animal size. However, models that relate the ontogenetic scaling of energy assimilation and metabolism to growth rely on assumptions that have yet to be rigorously tested. Based on detailed daily measurements of metabolism, growth, and assimilation in tobacco hornworms, Manduca sexta, we provide a first experimental test of the core assumptions of a metabolic scaling model of ontogenetic growth. Metabolic scaling parameters changed over development, in violation of the model assumptions. At the same time, the scaling of growth rate matches that of metabolic rate, with similar scaling exponents both across and within developmental instars. Rates of assimilation were much higher than expected during the first two instars and did not match the patterns of scaling of growth and metabolism, which suggests high costs of biosynthesis early in development. The rapid increase in size and discrete instars observed in larval insect development provide an ideal system for understanding how patterns of growth and metabolism emerge from fundamental cellular processes and the exchange of materials and energy between an organism and its environment.

Growth patterns and life-history strategies in Placodontia (Diapsida: Sauropterygia)

PubMed Central

Klein, Nicole; Neenan, James M.; Scheyer, Torsten M.; Griebeler, Eva Maria

2015-01-01

Placodontia is a clade of durophagous, near shore marine reptiles from Triassic sediments of modern-day Europe, Middle East and China. Although much is known about their primary anatomy and palaeoecology, relatively little has been published regarding their life history, i.e. ageing, maturation and growth. Here, growth records derived from long bone histological data of placodont individuals are described and modelled to assess placodont growth and life-history strategies. Growth modelling methods are used to confirm traits documented in the growth record (age at onset of sexual maturity, age when asymptotic length was achieved, age at death, maximum longevity) and also to estimate undocumented traits. Based on these growth models, generalized estimates of these traits are established for each taxon. Overall differences in bone tissue types and resulting growth curves indicate different growth patterns and life-history strategies between different taxa of Placodontia. Psephoderma and Paraplacodus grew with lamellar-zonal bone tissue type and show growth patterns as seen in modern reptiles. Placodontia indet. aff. Cyamodus and some Placodontia indet. show a unique combination of fibrolamellar bone tissue regularly stratified by growth marks, a pattern absent in modern sauropsids. The bone tissue type of Placodontia indet. aff. Cyamodus and Placodontia indet. indicates a significantly increased basal metabolic rate when compared with modern reptiles. Double lines of arrested growth, non-annual rest lines in annuli, and subcycles that stratify zones suggest high dependence of placodont growth on endogenous and exogenous factors. Histological and modelled differences within taxa point to high individual developmental plasticity but sexual dimorphism in growth patterns and the presence of different taxa in the sample cannot be ruled out. PMID:26587259

A combined model of human erythropoiesis and granulopoiesis under growth factor and chemotherapy treatment

PubMed Central

2014-01-01

Background Haematotoxicity of conventional chemotherapies often results in delays of treatment or reduction of chemotherapy dose. To ameliorate these side-effects, patients are routinely treated with blood transfusions or haematopoietic growth factors such as erythropoietin (EPO) or granulocyte colony-stimulating factor (G-CSF). For the latter ones, pharmaceutical derivatives are available, which differ in absorption kinetics, pharmacokinetic and -dynamic properties. Due to the complex interaction of cytotoxic effects of chemotherapy and the stimulating effects of different growth factor derivatives, optimal treatment is a non-trivial task. In the past, we developed mathematical models of thrombopoiesis, granulopoiesis and erythropoiesis under chemotherapy and growth-factor applications which can be used to perform clinically relevant predictions regarding the feasibility of chemotherapy schedules and cytopenia prophylaxis with haematopoietic growth factors. However, interactions of lineages and growth-factors were ignored so far. Results To close this gap, we constructed a hybrid model of human granulopoiesis and erythropoiesis under conventional chemotherapy, G-CSF and EPO applications. This was achieved by combining our single lineage models of human erythropoiesis and granulopoiesis with a common stem cell model. G-CSF effects on erythropoiesis were also implemented. Pharmacodynamic models are based on ordinary differential equations describing proliferation and maturation of haematopoietic cells. The system is regulated by feedback loops partly mediated by endogenous and exogenous EPO and G-CSF. Chemotherapy is modelled by depletion of cells. Unknown model parameters were determined by fitting the model predictions to time series data of blood counts and cytokine profiles. Data were extracted from literature or received from cooperating clinical study groups. Our model explains dynamics of mature blood cells and cytokines after growth-factor applications in healthy volunteers. Moreover, we modelled 15 different chemotherapeutic drugs by estimating their bone marrow toxicity. Taking into account different growth-factor schedules, this adds up to 33 different chemotherapy regimens explained by the model. Conclusions We conclude that we established a comprehensive biomathematical model to explain the dynamics of granulopoiesis and erythropoiesis under combined chemotherapy, G-CSF, and EPO applications. We demonstrate how it can be used to make predictions regarding haematotoxicity of yet untested chemotherapy and growth-factor schedules. PMID:24886056

Sizing the Jurassic theropod dinosaur Allosaurus: assessing growth strategy and evolution of ontogenetic scaling of limbs.

PubMed

Bybee, Paul J; Lee, Andrew H; Lamm, Ellen-Thérèse

2006-03-01

Allosaurus is one of the most common Mesozoic theropod dinosaurs. We present a histological analysis to assess its growth strategy and ontogenetic limb bone scaling. Based on an ontogenetic series of humeral, ulnar, femoral, and tibial sections of fibrolamellar bone, we estimate the ages of the largest individuals in the sample to be between 13-19 years. Growth curve reconstruction suggests that maximum growth occurred at 15 years, when body mass increased 148 kg/year. Based on larger bones of Allosaurus, we estimate an upper age limit of between 22-28 years of age, which is similar to preliminary data for other large theropods. Both Model I and Model II regression analyses suggest that relative to the length of the femur, the lengths of the humerus, ulna, and tibia increase in length more slowly than isometry predicts. That pattern of limb scaling in Allosaurus is similar to those in other large theropods such as the tyrannosaurids. Phylogenetic optimization suggests that large theropods independently evolved reduced humeral, ulnar, and tibial lengths by a phyletic reduction in longitudinal growth relative to the femur.

Front tracking based modeling of the solid grain growth on the adaptive control volume grid

NASA Astrophysics Data System (ADS)

Seredyński, Mirosław; Łapka, Piotr

2017-07-01

The paper presents the micro-scale model of unconstrained solidification of the grain immersed in under-cooled liquid, based on the front tracking approach. For this length scale, the interface tracked through the domain is meant as the solid-liquid boundary. To prevent generation of huge meshes the energy transport equation is discretized on the adaptive control volume (c.v.) mesh. The coupling of dynamically changing mesh and moving front position is addressed. Preliminary results of simulation of a test case, the growth of single grain, are presented and discussed.

An RBF-PSO based approach for modeling prostate cancer

NASA Astrophysics Data System (ADS)

Perracchione, Emma; Stura, Ilaria

2016-06-01

Prostate cancer is one of the most common cancers in men; it grows slowly and it could be diagnosed in an early stage by dosing the Prostate Specific Antigen (PSA). However, a relapse after the primary therapy could arise in 25 - 30% of cases and different growth characteristics of the new tumor are observed. In order to get a better understanding of the phenomenon, a two parameters growth model is considered. To estimate the parameters values identifying the disease risk level a novel approach, based on combining Particle Swarm Optimization (PSO) with meshfree interpolation methods, is proposed.

Numerical Parameter Optimization of the Ignition and Growth Model for HMX Based Plastic Bonded Explosives

NASA Astrophysics Data System (ADS)

Gambino, James; Tarver, Craig; Springer, H. Keo; White, Bradley; Fried, Laurence

2017-06-01

We present a novel method for optimizing parameters of the Ignition and Growth reactive flow (I&G) model for high explosives. The I&G model can yield accurate predictions of experimental observations. However, calibrating the model is a time-consuming task especially with multiple experiments. In this study, we couple the differential evolution global optimization algorithm to simulations of shock initiation experiments in the multi-physics code ALE3D. We develop parameter sets for HMX based explosives LX-07 and LX-10. The optimization finds the I&G model parameters that globally minimize the difference between calculated and experimental shock time of arrival at embedded pressure gauges. This work was performed under the auspices of the U.S. DOE by LLNL under contract DE-AC52-07NA27344. LLNS, LLC LLNL-ABS- 724898.

Evaluation of Proteus as a Tool for the Rapid Development of Models of Hydrologic Systems

NASA Astrophysics Data System (ADS)

Weigand, T. M.; Farthing, M. W.; Kees, C. E.; Miller, C. T.

2013-12-01

Models of modern hydrologic systems can be complex and involve a variety of operators with varying character. The goal is to implement approximations of such models that are both efficient for the developer and computationally efficient, which is a set of naturally competing objectives. Proteus is a Python-based toolbox that supports prototyping of model formulations as well as a wide variety of modern numerical methods and parallel computing. We used Proteus to develop numerical approximations for three models: Richards' equation, a brine flow model derived using the Thermodynamically Constrained Averaging Theory (TCAT), and a multiphase TCAT-based tumor growth model. For Richards' equation, we investigated discontinuous Galerkin solutions with higher order time integration based on the backward difference formulas. The TCAT brine flow model was implemented using Proteus and a variety of numerical methods were compared to hand coded solutions. Finally, an existing tumor growth model was implemented in Proteus to introduce more advanced numerics and allow the code to be run in parallel. From these three example models, Proteus was found to be an attractive open-source option for rapidly developing high quality code for solving existing and evolving computational science models.

An Approach of Estimating Individual Growth Curves for Young Thoroughbred Horses Based on Their Birthdays

PubMed Central

ONODA, Tomoaki; YAMAMOTO, Ryuta; SAWAMURA, Kyohei; MURASE, Harutaka; NAMBO, Yasuo; INOUE, Yoshinobu; MATSUI, Akira; MIYAKE, Takeshi; HIRAI, Nobuhiro

2014-01-01

ABSTRACT We propose an approach of estimating individual growth curves based on the birthday information of Japanese Thoroughbred horses, with considerations of the seasonal compensatory growth that is a typical characteristic of seasonal breeding animals. The compensatory growth patterns appear during only the winter and spring seasons in the life of growing horses, and the meeting point between winter and spring depends on the birthday of each horse. We previously developed new growth curve equations for Japanese Thoroughbreds adjusting for compensatory growth. Based on the equations, a parameter denoting the birthday information was added for the modeling of the individual growth curves for each horse by shifting the meeting points in the compensatory growth periods. A total of 5,594 and 5,680 body weight and age measurements of Thoroughbred colts and fillies, respectively, and 3,770 withers height and age measurements of both sexes were used in the analyses. The results of predicted error difference and Akaike Information Criterion showed that the individual growth curves using birthday information better fit to the body weight and withers height data than not using them. The individual growth curve for each horse would be a useful tool for the feeding managements of young Japanese Thoroughbreds in compensatory growth periods. PMID:25013356

Asymptotic analysis of noisy fitness maximization, applied to metabolism & growth

NASA Astrophysics Data System (ADS)

De Martino, Daniele; Masoero, Davide

2016-12-01

We consider a population dynamics model coupling cell growth to a diffusion in the space of metabolic phenotypes as it can be obtained from realistic constraints-based modeling. In the asymptotic regime of slow diffusion, that coincides with the relevant experimental range, the resulting non-linear Fokker-Planck equation is solved for the steady state in the WKB approximation that maps it into the ground state of a quantum particle in an Airy potential plus a centrifugal term. We retrieve scaling laws for growth rate fluctuations and time response with respect to the distance from the maximum growth rate suggesting that suboptimal populations can have a faster response to perturbations.

A novel growth mode of Physarum polycephalum during starvation

NASA Astrophysics Data System (ADS)

Lee, Jonghyun; Oettmeier, Christina; Döbereiner, Hans-Günther

2018-06-01

Organisms are constantly looking to forage and respond to various environmental queues to maximize their chance of survival. This is reflected in the unicellular organism Physarum polycephalum, which is known to grow as an optimized network. Here, we describe a new growth pattern of Physarum mesoplasmodium, where sheet-like motile bodies termed ‘satellites’ are formed. This non-network pattern formation is induced only when nutrients are scarce, suggesting that it is a type of emergency response. Our goal is to construct a model to describe the behaviour of satellites based on negative chemotaxis. We conjecture a diffusion-based model which implements detection of a signal molecule above a threshold concentration. Then we calculate how far the satellites must travel until the concentration signal falls below the threshold. These calculated distances are in good agreement with the distances where satellites stop. Based on the Akaike weight analysis, our threshold model is at least 2.3 times more likely to be the better model than the others we have considered. Based on the model, we estimate the diffusion coefficient of this molecule, which corresponds to typical signalling molecules.

Unravelling the Gordian knot! Key processes impacting overwintering larval survival and growth: A North Sea herring case study

NASA Astrophysics Data System (ADS)

Hufnagl, Marc; Peck, Myron A.; Nash, Richard D. M.; Dickey-Collas, Mark

2015-11-01

Unraveling the key processes affecting marine fish recruitment will ultimately require a combination of field, laboratory and modelling studies. We combined analyzes of long-term (30-year) field data on larval fish abundance, distribution and length, and biophysical model simulations of different levels of complexity to identify processes impacting the survival and growth of autumn- and winter-spawned Atlantic herring (Clupea harengus) larvae. Field survey data revealed interannual changes in intensity of utilization of the five major spawning grounds (Orkney/Shetland, Buchan, Banks north, Banks south, and Downs) as well as spatio-temporal variability in the length and abundance of overwintered larvae. The mean length of larvae captured in post-winter surveys was negatively correlated to the proportion of larvae from the southern-most (Downs) winter-spawning component. Furthermore, the mean length of larvae originating from all spawning components has decreased since 1990 suggesting ecosystem-wide changes impacting larval growth potential, most likely due to changes in prey fields. A simple biophysical model assuming temperature-dependent growth and constant mortality underestimated larval growth rates suggesting that larval mortality rates steeply declined with increasing size and/or age during winter as no match with field data could be obtained. In contrast better agreement was found between observed and modelled post-winter abundance for larvae originating from four spawning components when a more complex, physiological-based foraging and growth model was employed using a suite of potential prey field and size-based mortality scenarios. Nonetheless, agreement between field and model-derived estimates was poor for larvae originating from the winter-spawned Downs component. In North Sea herring, the dominant processes impacting larval growth and survival appear to have shifted in time and space highlighting how environmental forcing, ecosystem state and other factors can form a Gordian knot of marine fish recruitment processes. We highlight gaps in process knowledge and recommend specific field, laboratory and modelling studies which, in our opinion, are most likely to unravel the dominant processes and advance predictive capacity of the environmental regulation of recruitment in autumn and winter-spawned fishes in temperate areas such as herring in the North Sea.

What Do the Numbers Say? Clarifying Our Interpretation of Carbon Use Efficiency Data from Soil.

NASA Astrophysics Data System (ADS)

Geyer, K.; Dijkstra, P.; Sinsabaugh, R. L.; Frey, S. D.

2017-12-01

Carbon use efficiency (CUE) is the proportion of carbon resources that a microorganism commits towards cellular growth and thus affects the dynamics of soil organic matter pools. While numerous approaches exist for estimating CUE, no attempts have been made to simultaneously compare methods and reconcile their inherent biases. Such work is necessary to partition the observed variation in CUE estimates (commonly between 0.3 - 0.7) as biological or technical in origin. Here we review our results from experimental work aimed at comparing both traditional and emerging CUE techniques. Soil from the Harvard Forest Long Term Ecological Research site in Massachusetts, USA, was amended with 13C-glucose and 18O-water in laboratory mesocosms and monitored for changing rates of soil dissolved organic carbon (DOC) uptake, respiration (R), microbial biomass (MBC) production, DNA synthesis, and heat (Q) flux over 72 hrs. Three CUE estimates were generated from this data: 1) Δ13MBC/(Δ13MBC+ 13R), 2) Δ18DNA/(Δ18DNA + R), 3) Q/R. CUE was also measured via two indirect techniques: metabolic flux modeling and stoichiometric modeling. Results indicate that the 18O technique is able to discern gross growth of soil microbes while the 13C technique indicates net growth. As a result, 18O-based CUE remains unchanged ( 0.45) for the incubation duration at low amendment rates (0.0 and 0.05 mg glucose-C/g) while 13C-based CUE declines with time (0.75 to 0.5). The 13C technique likely overestimates CUE because the numerator (Δ13MBC) integrates any label (whether or not destined for growth) residing within the cell. High amendment rates (2.0 mg glucose-C/g) cause dramatic declines in 18O- and 13C-based CUE for the first 24 hr of incubation, but neither modeling approach was able to detect these dynamics. In summary, our results suggest that 13C-based estimates of CUE are best interpreted as net changes in the residence of labeled substrate within MBC pools while 18O-based estimates directly capture gross growth dynamics. Metabolic flux modeling and stoichiometric modeling appear to be suited for conditions of steady-state MBC only, where they approximate the CUE magnitude of the 13C- and 18O-based approaches, respectively.

Optimal bioprocess design through a gene regulatory network - growth kinetic hybrid model: Towards Replacing Monod kinetics.

PubMed

Tsipa, Argyro; Koutinas, Michalis; Usaku, Chonlatep; Mantalaris, Athanasios

2018-05-02

Currently, design and optimisation of biotechnological bioprocesses is performed either through exhaustive experimentation and/or with the use of empirical, unstructured growth kinetics models. Whereas, elaborate systems biology approaches have been recently explored, mixed-substrate utilisation is predominantly ignored despite its significance in enhancing bioprocess performance. Herein, bioprocess optimisation for an industrially-relevant bioremediation process involving a mixture of highly toxic substrates, m-xylene and toluene, was achieved through application of a novel experimental-modelling gene regulatory network - growth kinetic (GRN-GK) hybrid framework. The GRN model described the TOL and ortho-cleavage pathways in Pseudomonas putida mt-2 and captured the transcriptional kinetics expression patterns of the promoters. The GRN model informed the formulation of the growth kinetics model replacing the empirical and unstructured Monod kinetics. The GRN-GK framework's predictive capability and potential as a systematic optimal bioprocess design tool, was demonstrated by effectively predicting bioprocess performance, which was in agreement with experimental values, when compared to four commonly used models that deviated significantly from the experimental values. Significantly, a fed-batch biodegradation process was designed and optimised through the model-based control of TOL Pr promoter expression resulting in 61% and 60% enhanced pollutant removal and biomass formation, respectively, compared to the batch process. This provides strong evidence of model-based bioprocess optimisation at the gene level, rendering the GRN-GK framework as a novel and applicable approach to optimal bioprocess design. Finally, model analysis using global sensitivity analysis (GSA) suggests an alternative, systematic approach for model-driven strain modification for synthetic biology and metabolic engineering applications. Copyright © 2018. Published by Elsevier Inc.

Random regression analysis for body weights and main morphological traits in genetically improved farmed tilapia (Oreochromis niloticus).

PubMed

He, Jie; Zhao, Yunfeng; Zhao, Jingli; Gao, Jin; Xu, Pao; Yang, Runqing

2018-02-01

To genetically analyse growth traits in genetically improved farmed tilapia (GIFT), the body weight (BWE) and main morphological traits, including body length (BL), body depth (BD), body width (BWI), head length (HL) and length of the caudal peduncle (CPL), were measured six times in growth duration on 1451 fish from 45 mixed families of full and half sibs. A random regression model (RRM) was used to model genetic changes of the growth traits with days of age and estimate the heritability for any growth point and genetic correlations between pairwise growth points. Using the covariance function based on optimal RRMs, the heritabilities were estimated to be from 0.102 to 0.662 for BWE, 0.157 to 0.591 for BL, 0.047 to 0.621 for BD, 0.018 to 0.577 for BWI, 0.075 to 0.597 for HL and 0.032 to 0.610 for CPL between 60 and 140 days of age. All genetic correlations exceeded 0.5 between pairwise growth points. Moreover, the traits at initial days of age showed less correlation with those at later days of age. With phenotypes observed repeatedly, the model choice showed that the optimal RRMs could more precisely predict breeding values at a specific growth time than repeatability models or multiple trait animal models, which enhanced the efficiency of selection for the BWE and main morphological traits.

Accumulation of Biomass and Mineral Elements with Calendar Time by Corn: Application of the Expanded Growth Model

PubMed Central

Overman, Allen R.; Scholtz, Richard V.

2011-01-01

The expanded growth model is developed to describe accumulation of plant biomass (Mg ha−1) and mineral elements (kg ha−1) in with calendar time (wk). Accumulation of plant biomass with calendar time occurs as a result of photosynthesis for green land-based plants. A corresponding accumulation of mineral elements such as nitrogen, phosphorus, and potassium occurs from the soil through plant roots. In this analysis, the expanded growth model is tested against high quality, published data on corn (Zea mays L.) growth. Data from a field study in South Carolina was used to evaluate the application of the model, where the planting time of April 2 in the field study maximized the capture of solar energy for biomass production. The growth model predicts a simple linear relationship between biomass yield and the growth quantifier, which is confirmed with the data. The growth quantifier incorporates the unit processes of distribution of solar energy which drives biomass accumulation by photosynthesis, partitioning of biomass between light-gathering and structural components of the plants, and an aging function. A hyperbolic relationship between plant nutrient uptake and biomass yield is assumed, and is confirmed for the mineral elements nitrogen (N), phosphorus (P), and potassium (K). It is concluded that the rate limiting process in the system is biomass accumulation by photosynthesis and that nutrient accumulation occurs in virtual equilibrium with biomass accumulation. PMID:22194842

Phase field models for heterogeneous nucleation: Application to inoculation in alpha-solidifying Ti-Al-B alloys

NASA Astrophysics Data System (ADS)

Apel, M.; Eiken, J.; Hecht, U.

2014-02-01

This paper aims at briefly reviewing phase field models applied to the simulation of heterogeneous nucleation and subsequent growth, with special emphasis on grain refinement by inoculation. The spherical cap and free growth model (e.g. A.L. Greer, et al., Acta Mater. 48, 2823 (2000)) has proven its applicability for different metallic systems, e.g. Al or Mg based alloys, by computing the grain refinement effect achieved by inoculation of the melt with inert seeding particles. However, recent experiments with peritectic Ti-Al-B alloys revealed that the grain refinement by TiB2 is less effective than predicted by the model. Phase field simulations can be applied to validate the approximations of the spherical cap and free growth model, e.g. by computing explicitly the latent heat release associated with different nucleation and growth scenarios. Here, simulation results for point-shaped nucleation, as well as for partially and completely wetted plate-like seed particles will be discussed with respect to recalescence and impact on grain refinement. It will be shown that particularly for large seeding particles (up to 30 μm), the free growth morphology clearly deviates from the assumed spherical cap and the initial growth - until the free growth barrier is reached - significantly contributes to the latent heat release and determines the recalescence temperature.

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

ERIC Educational Resources Information Center

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

2017-01-01

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

Single Plant Root System Modeling under Soil Moisture Variation

NASA Astrophysics Data System (ADS)

Yabusaki, S.; Fang, Y.; Chen, X.; Scheibe, T. D.

2016-12-01

A prognostic Virtual Plant-Atmosphere-Soil System (vPASS) model is being developed that integrates comprehensively detailed mechanistic single plant modeling with microbial, atmospheric, and soil system processes in its immediate environment. Three broad areas of process module development are targeted: Incorporating models for root growth and function, rhizosphere interactions with bacteria and other organisms, litter decomposition and soil respiration into established porous media flow and reactive transport models Incorporating root/shoot transport, growth, photosynthesis and carbon allocation process models into an integrated plant physiology model Incorporating transpiration, Volatile Organic Compounds (VOC) emission, particulate deposition and local atmospheric processes into a coupled plant/atmosphere model. The integrated plant ecosystem simulation capability is being developed as open source process modules and associated interfaces under a modeling framework. The initial focus addresses the coupling of root growth, vascular transport system, and soil under drought scenarios. Two types of root water uptake modeling approaches are tested: continuous root distribution and constitutive root system architecture. The continuous root distribution models are based on spatially averaged root development process parameters, which are relatively straightforward to accommodate in the continuum soil flow and reactive transport module. Conversely, the constitutive root system architecture models use root growth rates, root growth direction, and root branching to evolve explicit root geometries. The branching topologies require more complex data structures and additional input parameters. Preliminary results are presented for root model development and the vascular response to temporal and spatial variations in soil conditions.

Mapping the environmental limitations to growth of coastal Douglas-fir stands on Vancouver Island, British Columbia.

PubMed

Coops, Nicholas C; Coggins, Sam B; Kurz, Werner A

2007-06-01

Coastal Douglas-fir (Pseudotsuga menziesii spp. menziesii (Mirb.) Franco) occurs over a wide range of environmental conditions on Vancouver Island, British Columbia. Although ecological zones have been drawn, no formal spatial analysis of environmental limitations on tree growth has been carried out. Such an exercise is desirable to identify areas that may warrant intensive management and to evaluate the impacts of predicted climate change this century. We applied a physiologically based forest growth model, 3-PG (Physiological Principles Predicting Growth), to interpret and map current limitations to Douglas-fir growth across Vancouver Island at 100-m cell resolution. We first calibrated the model to reproduce the regional productivity estimates reported in yield table growth curves. Further analyses indicated that slope exposure is important; southwest slopes of 30 degrees receive 40% more incident radiation than similarly inclined northeast slopes. When combined with other environmental differences associated with aspect, the model predicted 60% more growth on southwest exposures than on northeast exposures. The model simulations support field observations that drought is rare in the wetter zones, but common on the eastern side of Vancouver Island at lower elevations and on more exposed slopes. We illustrate the current limitations on growth caused by suboptimal temperature, high vapor pressure deficits and other factors. The modeling approach complements ecological classifications and offers the potential to identify the most favorable sites for management of other native tree species under current and future climatic conditions.

Implementation of Combined Feather and Surface-Normal Ice Growth Models in LEWICE/X

NASA Technical Reports Server (NTRS)

Velazquez, M. T.; Hansman, R. J., Jr.

1995-01-01

Experimental observations have shown that discrete rime ice growths called feathers, which grow in approximately the direction of water droplet impingement, play an important role in the growth of ice on accreting surfaces for some thermodynamic conditions. An improved physical model of ice accretion has been implemented in the LEWICE 2D panel-based ice accretion code maintained by the NASA Lewis Research Center. The LEWICE/X model of ice accretion explicitly simulates regions of feather growth within the framework of the LEWICE model. Water droplets impinging on an accreting surface are withheld from the normal LEWICE mass/energy balance and handled in a separate routine; ice growth resulting from these droplets is performed with enhanced convective heat transfer approximately along droplet impingement directions. An independent underlying ice shape is grown along surface normals using the unmodified LEWICE method. The resulting dual-surface ice shape models roughness-induced feather growth observed in icing wind tunnel tests. Experiments indicate that the exact direction of feather growth is dependent on external conditions. Data is presented to support a linear variation of growth direction with temperature and cloud water content. Test runs of LEWICE/X indicate that the sizes of surface regions containing feathers are influenced by initial roughness element height. This suggests that a previous argument that feather region size is determined by boundary layer transition may be incorrect. Simulation results for two typical test cases give improved shape agreement over unmodified LEWICE.

The fiber walk: a model of tip-driven growth with lateral expansion.

PubMed

Bucksch, Alexander; Turk, Greg; Weitz, Joshua S

2014-01-01

Tip-driven growth processes underlie the development of many plants. To date, tip-driven growth processes have been modeled as an elongating path or series of segments, without taking into account lateral expansion during elongation. Instead, models of growth often introduce an explicit thickness by expanding the area around the completed elongated path. Modeling expansion in this way can lead to contradictions in the physical plausibility of the resulting surface and to uncertainty about how the object reached certain regions of space. Here, we introduce fiber walks as a self-avoiding random walk model for tip-driven growth processes that includes lateral expansion. In 2D, the fiber walk takes place on a square lattice and the space occupied by the fiber is modeled as a lateral contraction of the lattice. This contraction influences the possible subsequent steps of the fiber walk. The boundary of the area consumed by the contraction is derived as the dual of the lattice faces adjacent to the fiber. We show that fiber walks generate fibers that have well-defined curvatures, and thus enable the identification of the process underlying the occupancy of physical space. Hence, fiber walks provide a base from which to model both the extension and expansion of physical biological objects with finite thickness.

Urban growth simulation from "first principles".

PubMed

Andersson, Claes; Lindgren, Kristian; Rasmussen, Steen; White, Roger

2002-08-01

General and mathematically transparent models of urban growth have so far suffered from a lack in microscopic realism. Physical models that have been used for this purpose, i.e., diffusion-limited aggregation, dielectric breakdown models, and correlated percolation all have microscopic dynamics for which analogies with urban growth appear stretched. Based on a Markov random field formulation we have developed a model that is capable of reproducing a variety of important characteristic urban morphologies and that has realistic microscopic dynamics. The results presented in this paper are particularly important in relation to "urban sprawl," an important aspect of which is aggressively spreading low-density land uses. This type of growth is increasingly causing environmental, social, and economical problems around the world. The microdynamics of our model, or its "first principles," can be mapped to human decisions and motivations and thus potentially also to policies and regulations. We measure statistical properties of macrostates generated by the urban growth mechanism that we propose, and we compare these to empirical measurements as well as to results from other models. To showcase the open-endedness of the model and to thereby relate our work to applied urban planning we have also included a simulated city consisting of a large number of land use classes in which also topographical data have been used.

Growing up and role modeling: a theory in Iranian nursing students' education.

PubMed

Mokhtari Nouri, Jamileh; Ebadi, Abbas; Alhani, Fatemeh; Rejeh, Nahid

2014-11-16

One of the key strategies in students' learning is being affected by models. Understanding the role-modeling process in education will help to make greater use of this training strategy. The aim of this grounded theory study was to explore Iranian nursing students and instructors' experiences about role modeling process. Data was analyzed by Glaserian's Grounded Theory methodology through semi-structured interviews with 7 faculty members, 2 nursing students; the three focus group discussions with 20 nursing students based on purposive and theoretical sampling was done for explaining role modeling process from four nursing faculties in Tehran. Through basic coding, an effort to comprehensive growth and excellence was made with the basic social process consisting the core category and through selective coding three phases were identified as: realizing and exposure to inadequate human and professional growth, facilitating human and professional growth and evolution. The role modeling process is taking place unconscious, involuntary, dynamic and with positive progressive process in order to facilitate overall growth in nursing student. Accordingly, the design and implementation of the designed model can be used to make this unconscious to conscious, active and voluntarily processes a process to help education administrators of nursing colleges and supra organization to prevent threats to human and professional in nursing students' education and promote nursing students' growth.

The Fiber Walk: A Model of Tip-Driven Growth with Lateral Expansion

PubMed Central

Bucksch, Alexander; Turk, Greg; Weitz, Joshua S.

2014-01-01

Tip-driven growth processes underlie the development of many plants. To date, tip-driven growth processes have been modeled as an elongating path or series of segments, without taking into account lateral expansion during elongation. Instead, models of growth often introduce an explicit thickness by expanding the area around the completed elongated path. Modeling expansion in this way can lead to contradictions in the physical plausibility of the resulting surface and to uncertainty about how the object reached certain regions of space. Here, we introduce fiber walks as a self-avoiding random walk model for tip-driven growth processes that includes lateral expansion. In 2D, the fiber walk takes place on a square lattice and the space occupied by the fiber is modeled as a lateral contraction of the lattice. This contraction influences the possible subsequent steps of the fiber walk. The boundary of the area consumed by the contraction is derived as the dual of the lattice faces adjacent to the fiber. We show that fiber walks generate fibers that have well-defined curvatures, and thus enable the identification of the process underlying the occupancy of physical space. Hence, fiber walks provide a base from which to model both the extension and expansion of physical biological objects with finite thickness. PMID:24465607

Temporal consistency of spatial pattern in growth of the mussel, Mytilus edulis: Implications for predictive modelling

NASA Astrophysics Data System (ADS)

Bergström, Per; Lindegarth, Susanne; Lindegarth, Mats

2013-10-01

Human pressures on coastal seas are increasing and methods for sustainable management, including spatial planning and mitigative actions, are therefore needed. In coastal areas worldwide, the development of mussel farming as an economically and ecologically sustainable industry requires geographic information on the growth and potential production capacity. In practice this means that coherent maps of temporally stable spatial patterns of growth need to be available in the planning process and that maps need to be based on mechanistic or empirical models. Therefore, as a first step towards development of models of growth, we assessed empirically the fundamental requirement that there are temporally consistent spatial patterns of growth in the blue mussel, Mytilus edulis. Using a pilot study we designed and dimensioned a transplant experiment, where the spatial consistency in the growth of mussels was evaluated at two resolutions. We found strong temporal and scale-dependent spatial variability in growth but patterns suggested that spatial patterns were uncoupled between growth of shell and that of soft tissue. Spatial patterns of shell growth were complex and largely inconsistent among years. Importantly, however, the growth of soft tissue was qualitatively consistent among years at the scale of km. The results suggest that processes affecting the whole coastal area cause substantial differences in growth of soft tissue among years but that factors varying at the scale of km create strong and persistent spatial patterns of growth, with a potential doubling of productivity by identifying the most suitable locations. We conclude that the observed spatial consistency provides a basis for further development of predictive modelling and mapping of soft tissue growth in these coastal areas. Potential causes of observed patterns, consequences for mussel-farming as a tool for mitigating eutrophication, aspects of precision of modelling and sampling of mussel growth as well as ecological functions in general are discussed.

Direct coupling of a genome-scale microbial in silico model and a groundwater reactive transport model.

PubMed

Fang, Yilin; Scheibe, Timothy D; Mahadevan, Radhakrishnan; Garg, Srinath; Long, Philip E; Lovley, Derek R

2011-03-25

The activity of microorganisms often plays an important role in dynamic natural attenuation or engineered bioremediation of subsurface contaminants, such as chlorinated solvents, metals, and radionuclides. To evaluate and/or design bioremediated systems, quantitative reactive transport models are needed. State-of-the-art reactive transport models often ignore the microbial effects or simulate the microbial effects with static growth yield and constant reaction rate parameters over simulated conditions, while in reality microorganisms can dynamically modify their functionality (such as utilization of alternative respiratory pathways) in response to spatial and temporal variations in environmental conditions. Constraint-based genome-scale microbial in silico models, using genomic data and multiple-pathway reaction networks, have been shown to be able to simulate transient metabolism of some well studied microorganisms and identify growth rate, substrate uptake rates, and byproduct rates under different growth conditions. These rates can be identified and used to replace specific microbially-mediated reaction rates in a reactive transport model using local geochemical conditions as constraints. We previously demonstrated the potential utility of integrating a constraint-based microbial metabolism model with a reactive transport simulator as applied to bioremediation of uranium in groundwater. However, that work relied on an indirect coupling approach that was effective for initial demonstration but may not be extensible to more complex problems that are of significant interest (e.g., communities of microbial species and multiple constraining variables). Here, we extend that work by presenting and demonstrating a method of directly integrating a reactive transport model (FORTRAN code) with constraint-based in silico models solved with IBM ILOG CPLEX linear optimizer base system (C library). The models were integrated with BABEL, a language interoperability tool. The modeling system is designed in such a way that constraint-based models targeting different microorganisms or competing organism communities can be easily plugged into the system. Constraint-based modeling is very costly given the size of a genome-scale reaction network. To save computation time, a binary tree is traversed to examine the concentration and solution pool generated during the simulation in order to decide whether the constraint-based model should be called. We also show preliminary results from the integrated model including a comparison of the direct and indirect coupling approaches and evaluated the ability of the approach to simulate field experiment. Published by Elsevier B.V.

Using Satellite Data for Environmental Impact Analysis in Economic Growth: the Case of Mongolia

NASA Astrophysics Data System (ADS)

Tungalag, A.; Tsolmon, R.; Ochirkhuyag, L.; Oyunjargal, J.

2016-06-01

The Mongolian economy is based on the primary and secondary economic sectors of agriculture and industry. In addition, minerals and mining become a key sector of its economy. The main mining resources are gold, copper, coal, fluorspar and steel. However, the environment and green economy is one of the big problems among most of the countries and especially for countries like Mongolia where the mining is major part of economy; it is a number one problem. The research of the work tested how environmental elements effect to current Mongolian economic growth, which is growing economy because of mining sector. The study of economic growth but the starting point for any study of economic growth is the neoclassical growth model emphasizing the role of capital accumulation. The growth is analysed either in terms of models with exogenous saving rates (the Solow-Swan model), or models where consumption and hence savings are determined by optimizing individuals. These are the so-called optimal growth or Ramsey-Cass-Koopmans. The study extends the Solow model and the Ramsey-Cass-Koopmans model, including environmental elements which are satellite data determine to degraded land and vegetation value from 1995 to 2013. In contrast, we can see the degraded land area increases from 1995 (4856 m2) to 2013 (10478 m2) and vegetation value decrease at same time. A description of the methodology of the study conducted follows together with the data collected and econometric estimations and calibration with environmental elements.

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

Zhang, Damao; Wang, Zhien; Heymsfield, Andrew J.

Measurement of ice number concentration in clouds is important but still challenging. Stratiform mixed-phase clouds (SMCs) provide a simple scenario for retrieving ice number concentration from remote sensing measurements. The simple ice generation and growth pattern in SMCs offers opportunities to use cloud radar reflectivity (Ze) measurements and other cloud properties to infer ice number concentration quantitatively. To understand the strong temperature dependency of ice habit and growth rate quantitatively, we develop a 1-D ice growth model to calculate the ice diffusional growth along its falling trajectory in SMCs. The radar reflectivity and fall velocity profiles of ice crystals calculatedmore » from the 1-D ice growth model are evaluated with the Atmospheric Radiation Measurements (ARM) Climate Research Facility (ACRF) ground-based high vertical resolution radar measurements. Combining Ze measurements and 1-D ice growth model simulations, we develop a method to retrieve the ice number concentrations in SMCs at given cloud top temperature (CTT) and liquid water path (LWP). The retrieved ice concentrations in SMCs are evaluated with in situ measurements and with a three-dimensional cloud-resolving model simulation with a bin microphysical scheme. These comparisons show that the retrieved ice number concentrations are within an uncertainty of a factor of 2, statistically.« less

Water Temperature, Invertebrate Drift, and the Scope for Growth for Juvenile Spring Chinook Salmon.

NASA Astrophysics Data System (ADS)

Lovtang, J. C.; Li, H. W.

2005-05-01

We present a bioenergetic assessment of habitat quality based on the concept of the scope for growth for juvenile Chinook salmon. Growth of juvenile salmonids during the freshwater phase of their life history depends on a balance between two main factors: energy intake and metabolic costs. The metabolic demands of temperature and the availability of food play integral roles in determining the scope for growth of juvenile salmonids in stream systems. We investigated differences in size of juvenile spring Chinook salmon in relation to water temperature and invertebrate drift density in six unique study reaches in the Metolius River Basin, a tributary of the Deschutes River in Central Oregon. This project was initiated to determine the relative quality and potential productivity of habitat in the Metolius Basin prior to the reintroduction of spring Chinook salmon, which were extirpated from the middle Deschutes basin in the early 1970's due to the construction of a hydroelectric dam. Variations in the growth of juvenile Chinook salmon can be described using a multiple regression model of water temperature and invertebrate drift density. We also discuss the relationships between our bioenergetic model, variations of the ideal free distribution model, and physiological growth models.