Linking genes to microbial growth kinetics: an integrated biochemical systems engineering approach

NARCIS (Netherlands)

Koutinas, M.; Kiparissides, A.; Silva-Rocha, R.; Lam, M.C.; Martins Dos Santos, V.A.P.; Lorenzo, de V.; Pistikopoulos, E.N.; Mantalaris, A.

2011-01-01

The majority of models describing the kinetic properties of a microorganism for a given substrate are unstructured and empirical. They are formulated in this manner so that the complex mechanism of cell growth is simplified. Herein, a novel approach for modelling microbial growth kinetics is

Modeling and forecasting mortality with economic growth : a multipopulation approach

NARCIS (Netherlands)

Boonen, T.J.; Li, H.

2017-01-01

Research on mortality modeling of multiple populations focuses mainly on extrapolating past mortality trends and summarizing these trends by one or more common latent factors. This article proposes a multipopulation stochastic mortality model that uses the explanatory power of economic growth. In

Modelling planktic foraminifer growth and distribution using an ecophysiological multi-species approach

Directory of Open Access Journals (Sweden)

F. Lombard

2011-04-01

Full Text Available We present an eco-physiological model reproducing the growth of eight foraminifer species (Neogloboquadrina pachyderma, Neogloboquadrina incompta, Neogloboquadrina dutertrei, Globigerina bulloides, Globigerinoides ruber, Globigerinoides sacculifer, Globigerinella siphonifera and Orbulina universa. By using the main physiological rates of foraminifers (nutrition, respiration, symbiotic photosynthesis, this model estimates their growth as a function of temperature, light availability, and food concentration. Model parameters are directly derived or calibrated from experimental observations and only the influence of food concentration (estimated via Chlorophyll-a concentration was calibrated against field observations. Growth rates estimated from the model show positive correlation with observed abundance from plankton net data suggesting close coupling between individual growth and population abundance. This observation was used to directly estimate potential abundance from the model-derived growth. Using satellite data, the model simulate the dominant foraminifer species with a 70.5% efficiency when compared to a data set of 576 field observations worldwide. Using outputs of a biogeochemical model of the global ocean (PISCES instead of satellite images as forcing variables gives also good results, but with lower efficiency (58.9%. Compared to core tops observations, the model also correctly reproduces the relative worldwide abundance and the diversity of the eight species when using either satellite data either PISCES results. This model allows prediction of the season and water depth at which each species has its maximum abundance potential. This offers promising perspectives for both an improved quantification of paleoceanographic reconstructions and for a better understanding of the foraminiferal role in the marine carbon cycle.

Parameter Estimates in Differential Equation Models for Population Growth

Science.gov (United States)

Winkel, Brian J.

2011-01-01

We estimate the parameters present in several differential equation models of population growth, specifically logistic growth models and two-species competition models. We discuss student-evolved strategies and offer "Mathematica" code for a gradient search approach. We use historical (1930s) data from microbial studies of the Russian biologist,…

Structural modelling of economic growth: Technological changes

Directory of Open Access Journals (Sweden)

Sukharev Oleg

2016-01-01

Full Text Available Neoclassical and Keynesian theories of economic growth assume the use of Cobb-Douglas modified functions and other aggregate econometric approaches to growth dynamics modelling. In that case explanations of economic growth are based on the logic of the used mathematical ratios often including the ideas about aggregated values change and factors change a priori. The idea of assessment of factor productivity is the fundamental one among modern theories of economic growth. Nevertheless, structural parameters of economic system, institutions and technological changes are practically not considered within known approaches, though the latter is reflected in the changing parameters of production function. At the same time, on the one hand, the ratio of structural elements determines the future value of the total productivity of the factors and, on the other hand, strongly influences the rate of economic growth and its mode of innovative dynamics. To put structural parameters of economic system into growth models with the possibility of assessment of such modes under conditions of interaction of new and old combinations is an essential step in the development of the theory of economic growth/development. It allows forming stimulation policy of economic growth proceeding from the structural ratios and relations recognized for this economic system. It is most convenient in such models to use logistic functions demonstrating the resource change for old and new combination within the economic system. The result of economy development depends on starting conditions, and on institutional parameters of velocity change of resource borrowing in favour of a new combination and creation of its own resource. Model registration of the resource is carried out through the idea of investments into new and old combinations.

Education, Endogenous Human Capital, and Monetary Economic Growth with MIU Approach

OpenAIRE

Zhang, Wei-Bin

2013-01-01

This study builds a monetary growth model with inflation policy and education. The model is a synthesis of the Uzawa-Lucas two-sector growth model and traditional monetary model with the money-in-utility (MIU) approach. We show how money, physical capital and human capital interact over time under exogenous inflation policy in a free market economy. The dynamics of the economy is described by three differential equations. We show that the monetary economic system has a saddle equilibrium poin...

Modeling of multibranched crosslike crack growth

International Nuclear Information System (INIS)

Canessa, E.; Tanatar, B.

1991-06-01

Multibranched crosslike crack patterns formed in concentrically loaded square plates are studied in terms of fractal geometry, where the associated fractal dimension d f is calculated for their characterization. We apply simplest deterministic and stochastic approaches at a phenomenological level in an attempt to find generic features as guidelines for future experimental and theoretical work. The deterministic model for fracture propagation we apply, which is a variant of the discretized Laplace approach for randomly ramified fractal cracks proposed by Takayasu, reproduces the basic ingredients of observed complex fracture patters. The stochastic model, although is not strictly a model for crack propagation, is based on diffusion-limited aggregation (DLA) for fractal growth and produces slightly more realistic assessment of the crosslike growth of the cracks in asymmetric multibranches. Nevertheless, this simple ad-hoc DLA-version for modeling the present phenomena as well as the deterministic approach for fracture propagation give fractal dimensionality for the fracture pattern in accord with our estimations made from recent experimental data. It is found that there is a crossover of two fractal dimensions, corresponding to the core (higher d f ) and multibranched crosslike (lower D f ) regions, that contains loops, that are interpreted as representing different symmetry regions within the square plates of finite size. (author). 26 refs, 5 figs

Random-growth urban model with geographical fitness

Science.gov (United States)

Kii, Masanobu; Akimoto, Keigo; Doi, Kenji

2012-12-01

This paper formulates a random-growth urban model with a notion of geographical fitness. Using techniques of complex-network theory, we study our system as a type of preferential-attachment model with fitness, and we analyze its macro behavior to clarify the properties of the city-size distributions it predicts. First, restricting the geographical fitness to take positive values and using a continuum approach, we show that the city-size distributions predicted by our model asymptotically approach Pareto distributions with coefficients greater than unity. Then, allowing the geographical fitness to take negative values, we perform local coefficient analysis to show that the predicted city-size distributions can deviate from Pareto distributions, as is often observed in actual city-size distributions. As a result, the model we propose can generate a generic class of city-size distributions, including but not limited to Pareto distributions. For applications to city-population projections, our simple model requires randomness only when new cities are created, not during their subsequent growth. This property leads to smooth trajectories of city population growth, in contrast to other models using Gibrat’s law. In addition, a discrete form of our dynamical equations can be used to estimate past city populations based on present-day data; this fact allows quantitative assessment of the performance of our model. Further study is needed to determine appropriate formulas for the geographical fitness.

Modeling of Hybrid Growth Wastewater Bio-reactor

International Nuclear Information System (INIS)

EI Nashaei, S.; Garhyan, P.; Prasad, P.; Abdel Halim, H.S.; Ibrahim, G.

2004-01-01

The attached/suspended growth mixed reactors are considered one of the recently tried approaches to improve the performance of the biological treatment by increasing the volume of the accumulated biomass in terms of attached growth as well as suspended growth. Moreover, the domestic WW can be easily mixed with a high strength non-hazardous industrial wastewater and treated together in these bio-reactors if the need arises. Modeling of Hybrid hybrid growth wastewater reactor addresses the need of understanding the rational of such system in order to achieve better design and operation parameters. This paper aims at developing a heterogeneous mathematical model for hybrid growth system considering the effect of diffusion, external mass transfer, and power input to the system in a rational manner. The model will be based on distinguishing between liquid/solid phase (bio-film and bio-floc). This model would be a step ahead to the fine tuning the design of hybrid systems based on the experimental data of a pilot plant to be implemented in near future

Integrated Intelligent Modeling, Design and Control of Crystal Growth Processes

National Research Council Canada - National Science Library

Prasad, V

2000-01-01

.... This MURI program took an integrated approach towards modeling, design and control of crystal growth processes and in conjunction with growth and characterization experiments developed much better...

A multilevel nonlinear mixed-effects approach to model growth in pigs

DEFF Research Database (Denmark)

Strathe, Anders Bjerring; Danfær, Allan Christian; Sørensen, H.

2010-01-01

Growth functions have been used to predict market weight of pigs and maximize return over feed costs. This study was undertaken to compare 4 growth functions and methods of analyzing data, particularly one that considers nonlinear repeated measures. Data were collected from an experiment with 40...... pigs maintained from birth to maturity and their BW measured weekly or every 2 wk up to 1,007 d. Gompertz, logistic, Bridges, and Lopez functions were fitted to the data and compared using information criteria. For each function, a multilevel nonlinear mixed effects model was employed because....... Furthermore, studies should consider adding continuous autoregressive process when analyzing nonlinear mixed models with repeated measures....

Regression models for linking patterns of growth to a later outcome: infant growth and childhood overweight

Directory of Open Access Journals (Sweden)

Andrew K. Wills

2016-04-01

Full Text Available Abstract Background Regression models are widely used to link serial measures of anthropometric size or changes in size to a later outcome. Different parameterisations of these models enable one to target different questions about the effect of growth, however, their interpretation can be challenging. Our objective was to formulate and classify several sets of parameterisations by their underlying growth pattern contrast, and to discuss their utility using an expository example. Methods We describe and classify five sets of model parameterisations in accordance with their underlying growth pattern contrast (conditional growth; being bigger v being smaller; becoming bigger and staying bigger; growing faster v being bigger; becoming and staying bigger versus being bigger. The contrasts are estimated by including different sets of repeated measures of size and changes in size in a regression model. We illustrate these models in the setting of linking infant growth (measured on 6 occasions: birth, 6 weeks, 3, 6, 12 and 24 months in weight-for-height-for-age z-scores to later childhood overweight at 8y using complete cases from the Norwegian Childhood Growth study (n = 900. Results In our expository example, conditional growth during all periods, becoming bigger in any interval and staying bigger through infancy, and being bigger from birth were all associated with higher odds of later overweight. The highest odds of later overweight occurred for individuals who experienced high conditional growth or became bigger in the 3 to 6 month period and stayed bigger, and those who were bigger from birth to 24 months. Comparisons between periods and between growth patterns require large sample sizes and need to consider how to scale associations to make comparisons fair; with respect to the latter, we show one approach. Conclusion Studies interested in detrimental growth patterns may gain extra insight from reporting several sets of growth pattern

Machine Learning Approach for Software Reliability Growth Modeling with Infinite Testing Effort Function

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Subburaj Ramasamy

2017-01-01

Full Text Available Reliability is one of the quantifiable software quality attributes. Software Reliability Growth Models (SRGMs are used to assess the reliability achieved at different times of testing. Traditional time-based SRGMs may not be accurate enough in all situations where test effort varies with time. To overcome this lacuna, test effort was used instead of time in SRGMs. In the past, finite test effort functions were proposed, which may not be realistic as, at infinite testing time, test effort will be infinite. Hence in this paper, we propose an infinite test effort function in conjunction with a classical Nonhomogeneous Poisson Process (NHPP model. We use Artificial Neural Network (ANN for training the proposed model with software failure data. Here it is possible to get a large set of weights for the same model to describe the past failure data equally well. We use machine learning approach to select the appropriate set of weights for the model which will describe both the past and the future data well. We compare the performance of the proposed model with existing model using practical software failure data sets. The proposed log-power TEF based SRGM describes all types of failure data equally well and also improves the accuracy of parameter estimation more than existing TEF and can be used for software release time determination as well.

Modeling Math Growth Trajectory--An Application of Conventional Growth Curve Model and Growth Mixture Model to ECLS K-5 Data

Science.gov (United States)

Lu, Yi

2016-01-01

To model students' math growth trajectory, three conventional growth curve models and three growth mixture models are applied to the Early Childhood Longitudinal Study Kindergarten-Fifth grade (ECLS K-5) dataset in this study. The results of conventional growth curve model show gender differences on math IRT scores. When holding socio-economic…

GROWTH REGIMES IN SUB-SAHARAN AFRICA: A MIXTUREMODEL APPROACH

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Emmanuel Igbinoba

2016-07-01

Full Text Available This paper employs a generalized mixture model approach to empiricallydetermine if Sub-Saharan African countries henceforth (SSA follow ahomogenous growth pattern based on the conditional distribution of their growthrates. Latent effects are employed to determine the growth experience of SSAcountries and to examine the structural characteristics of the clusters if any exist.Affirmation of clusters might imply significant productivity divergence amongSub-Saharan economies, helping explaining the structural imbalances in theregion. Results strongly buttress the existence of clusters and little evidence of acommon growth path, implying divergence among Sub-Saharan economies andspecific economic reforms are required in the identified clusters to guaranteesustainability and equality of growth in the SSA region. We also observed apositive and significant effect of investment even though the estimated long runeffects of investment on economic growth are smaller than expected

Geometrical approach to tumor growth.

Science.gov (United States)

Escudero, Carlos

2006-08-01

Tumor growth has a number of features in common with a physical process known as molecular beam epitaxy. Both growth processes are characterized by the constraint of growth development to the body border, and surface diffusion of cells and particles at the growing edge. However, tumor growth implies an approximate spherical symmetry that makes necessary a geometrical treatment of the growth equations. The basic model was introduced in a former paper [C. Escudero, Phys. Rev. E 73, 020902(R) (2006)], and in the present work we extend our analysis and try to shed light on the possible geometrical principles that drive tumor growth. We present two-dimensional models that reproduce the experimental observations, and analyze the unexplored three-dimensional case, for which interesting conclusions on tumor growth are derived.

Modelling grain growth in the framework of Rational Extended Thermodynamics

International Nuclear Information System (INIS)

Kertsch, Lukas; Helm, Dirk

2016-01-01

Grain growth is a significant phenomenon for the thermomechanical processing of metals. Since the mobility of the grain boundaries is thermally activated and energy stored in the grain boundaries is released during their motion, a mutual interaction with the process conditions occurs. To model such phenomena, a thermodynamic framework for the representation of thermomechanical coupling phenomena in metals including a microstructure description is required. For this purpose, Rational Extended Thermodynamics appears to be a useful tool. We apply an entropy principle to derive a thermodynamically consistent model for grain coarsening due to the growth and shrinkage of individual grains. Despite the rather different approaches applied, we obtain a grain growth model which is similar to existing ones and can be regarded as a thermodynamic extension of that by Hillert (1965) to more general systems. To demonstrate the applicability of the model, we compare our simulation results to grain growth experiments in pure copper by different authors, which we are able to reproduce very accurately. Finally, we study the implications of the energy release due to grain growth on the energy balance. The present unified approach combining a microstructure description and continuum mechanics is ready to be further used to develop more elaborate material models for complex thermo-chemo-mechanical coupling phenomena. (paper)

Modelling grain growth in the framework of Rational Extended Thermodynamics

Science.gov (United States)

Kertsch, Lukas; Helm, Dirk

2016-05-01

Grain growth is a significant phenomenon for the thermomechanical processing of metals. Since the mobility of the grain boundaries is thermally activated and energy stored in the grain boundaries is released during their motion, a mutual interaction with the process conditions occurs. To model such phenomena, a thermodynamic framework for the representation of thermomechanical coupling phenomena in metals including a microstructure description is required. For this purpose, Rational Extended Thermodynamics appears to be a useful tool. We apply an entropy principle to derive a thermodynamically consistent model for grain coarsening due to the growth and shrinkage of individual grains. Despite the rather different approaches applied, we obtain a grain growth model which is similar to existing ones and can be regarded as a thermodynamic extension of that by Hillert (1965) to more general systems. To demonstrate the applicability of the model, we compare our simulation results to grain growth experiments in pure copper by different authors, which we are able to reproduce very accurately. Finally, we study the implications of the energy release due to grain growth on the energy balance. The present unified approach combining a microstructure description and continuum mechanics is ready to be further used to develop more elaborate material models for complex thermo-chemo-mechanical coupling phenomena.

A risk modelling approach for setting microbiological limits using enterococci as indicator for growth potential of Salmonella in pork.

Science.gov (United States)

Bollerslev, Anne Mette; Nauta, Maarten; Hansen, Tina Beck; Aabo, Søren

2017-01-02

Microbiological limits are widely used in food processing as an aid to reduce the exposure to hazardous microorganisms for the consumers. However, in pork, the prevalence and concentrations of Salmonella are generally low and microbiological limits are not considered an efficient tool to support hygiene interventions. The objective of the present study was to develop an approach which could make it possible to define potential risk-based microbiological limits for an indicator, enterococci, in order to evaluate the risk from potential growth of Salmonella. A positive correlation between the concentration of enterococci and the prevalence and concentration of Salmonella was shown for 6640 pork samples taken at Danish cutting plants and retail butchers. The samples were collected in five different studies in 2001, 2002, 2010, 2011 and 2013. The observations that both Salmonella and enterococci are carried in the intestinal tract, contaminate pork by the same mechanisms and share similar growth characteristics (lag phase and maximum specific growth rate) at temperatures around 5-10°C, suggest a potential of enterococci to be used as an indicator of potential growth of Salmonella in pork. Elevated temperatures during processing will lead to growth of both enterococci and, if present, also Salmonella. By combining the correlation between enterococci and Salmonella with risk modelling, it is possible to predict the risk of salmonellosis based on the level of enterococci. The risk model used for this purpose includes the dose-response relationship for Salmonella and a reduction factor to account for preparation of the fresh pork. By use of the risk model, it was estimated that the majority of salmonellosis cases, caused by the consumption of pork in Denmark, is caused by the small fraction of pork products that has enterococci concentrations above 5logCFU/g. This illustrates that our approach can be used to evaluate the potential effect of different microbiological

Proces-based modeling of the overflow induced growth of erosional channels

NARCIS (Netherlands)

Tuan, T.Q.; Stive, M.J.F.; Verhagen, H.J.; Visser, P.J.

2008-01-01

A new process-based approach is introduced for a more efficient computation of the overflow-induced growth of an erosional channel in a noncohesive homogeneous narrow landmass such as the breach growth in a sand-dike. The approach is easy to incorporate in a 1D/2DV morphodynamic model to compute the

Orchestrated structure evolution: modeling growth-regulated nanomanufacturing

Energy Technology Data Exchange (ETDEWEB)

Abbasi, Shaghayegh; Boehringer, Karl F [Department of Electrical Engineering, University of Washington, Seattle, WA 98195-2500 (United States); Kitayaporn, Sathana; Schwartz, Daniel T, E-mail: karlb@washington.edu [Department of Chemical Engineering, University of Washington, Seattle, WA 98195-2500 (United States)

2011-04-22

Orchestrated structure evolution (OSE) is a scalable manufacturing method that combines the advantages of top-down (tool-directed) and bottom-up (self-propagating) approaches. The method consists of a seed patterning step that defines where material nucleates, followed by a growth step that merges seeded islands into the final patterned thin film. We develop a model to predict the completed pattern based on a computationally efficient approximate Green's function solution of the diffusion equation plus a Voronoi diagram based approach that defines the final grain boundary structure. Experimental results rely on electron beam lithography to pattern the seeds, followed by the mass transfer limited growth of copper via electrodeposition. The seed growth model is compared with experimental results to quantify nearest neighbor seed-to-seed interactions as well as how seeds interact with the pattern boundary to impact the local growth rate. Seed-to-seed and seed-to-pattern interactions are shown to result in overgrowth of seeds on edges and corners of the shape, where seeds have fewer neighbors. We explore how local changes to the seed location can be used to improve the patterning quality without increasing the manufacturing cost. OSE is shown to enable a unique set of trade-offs between the cost, time, and quality of thin film patterning.

IMPACT OF TRADE OPENNESS ON OUTPUT GROWTH: CO INTEGRATION AND ERROR CORRECTION MODEL APPROACH

Directory of Open Access Journals (Sweden)

Asma Arif

2012-01-01

Full Text Available This study analyzed the long run relationship between trade openness and output growth for Pakistan using annual time series data for 1972-2010. This study follows the Engle and Granger co integration analysis and error correction approach to analyze the long run relationship between the two variables. The Error Correction Term (ECT for output growth and trade openness is significant at 5% level of significance and indicates a positive long run relation between the variables. This study has also analyzed the causality between trade openness and output growth by using granger causality test. The results of granger causality show that there is a bi-directional significant relationship between trade openness and economic growth.

Modeling lodgepole pine radial growth relative to climate and genetics using universal growth-trend response functions.

Science.gov (United States)

McLane, Sierra C; LeMay, Valerie M; Aitken, Sally N

2011-04-01

Forests strongly affect Earth's carbon cycles, making our ability to forecast forest-productivity changes associated with rising temperatures and changes in precipitation increasingly critical. In this study, we model the influence of climate on annual radial growth using lodgepole pine (Pinus contorta) trees grown for 34 years in a large provenance experiment in western Canada. We use a random-coefficient modeling approach to build universal growth-trend response functions that simultaneously incorporate the impacts of different provenance and site climates on radial growth trends under present and future annual (growth-year), summer, and winter climate regimes. This approach provides new depth to traditional quantitative genetics population response functions by illustrating potential changes in population dominance over time, as well as indicating the age and size at which annual growth begins declining for any population growing in any location under any present or future climate scenario within reason, given the ages and climatic conditions sampled. Our models indicate that lodgepole pine radial-growth levels maximize between 3.9 degrees and 5.1 degrees C mean growth-year temperature. This translates to productivity declining by the mid-21st century in southern and central British Columbia (BC), while increasing beyond the 2080s in northern BC and Yukon, as temperatures rise. Relative to summer climate indices, productivity is predicted to decline continuously through the 2080s in all locations, while relative to winter climate variables, the opposite trend occurs, with the growth increases caused by warmer winters potentially offsetting the summer losses. Trees from warmer provenances, i.e., from the center of the species range, perform best in nearly all of our present and future climate-scenario models. We recommend that similar models be used to analyze population growth trends relative to annual and intra-annual climate in other large-scale provenance

Comprehensive computational model for combining fluid hydrodynamics, light transport and biomass growth in a Taylor vortex algal photobioreactor: Lagrangian approach.

Science.gov (United States)

Gao, Xi; Kong, Bo; Vigil, R Dennis

2017-01-01

A comprehensive quantitative model incorporating the effects of fluid flow patterns, light distribution, and algal growth kinetics on biomass growth rate is developed in order to predict the performance of a Taylor vortex algal photobioreactor for culturing Chlorella vulgaris. A commonly used Lagrangian strategy for coupling the various factors influencing algal growth was employed whereby results from computational fluid dynamics and radiation transport simulations were used to compute numerous microorganism light exposure histories, and this information in turn was used to estimate the global biomass specific growth rate. The simulations provide good quantitative agreement with experimental data and correctly predict the trend in reactor performance as a key reactor operating parameter is varied (inner cylinder rotation speed). However, biomass growth curves are consistently over-predicted and potential causes for these over-predictions and drawbacks of the Lagrangian approach are addressed. Copyright © 2016 Elsevier Ltd. All rights reserved.

Growth Curve Models and Applications : Indian Statistical Institute

CERN Document Server

2017-01-01

Growth curve models in longitudinal studies are widely used to model population size, body height, biomass, fungal growth, and other variables in the biological sciences, but these statistical methods for modeling growth curves and analyzing longitudinal data also extend to general statistics, economics, public health, demographics, epidemiology, SQC, sociology, nano-biotechnology, fluid mechanics, and other applied areas.   There is no one-size-fits-all approach to growth measurement. The selected papers in this volume build on presentations from the GCM workshop held at the Indian Statistical Institute, Giridih, on March 28-29, 2016. They represent recent trends in GCM research on different subject areas, both theoretical and applied. This book includes tools and possibilities for further work through new techniques and modification of existing ones. The volume includes original studies, theoretical findings and case studies from a wide range of app lied work, and these contributions have been externally r...

A new model for simulating growth in fish

Directory of Open Access Journals (Sweden)

Johannes Hamre

2014-01-01

Full Text Available A real dynamic population model calculates change in population sizes independent of time. The Beverton & Holt (B&H model commonly used in fish assessment includes the von Bertalanffy growth function which has age or accumulated time as an independent variable. As a result the B&H model has to assume constant fish growth. However, growth in fish is highly variable depending on food availability and environmental conditions. We propose a new growth model where the length increment of fish living under constant conditions and unlimited food supply, decreases linearly with increasing fish length until it reaches zero at a maximal fish length. The model is independent of time and includes a term which accounts for the environmental variation. In the present study, the model was validated in zebrafish held at constant conditions. There was a good fit of the model to data on observed growth in Norwegian spring spawning herring, capelin from the Barents Sea, North Sea herring and in farmed coastal cod. Growth data from Walleye Pollock from the Eastern Bering Sea and blue whiting from the Norwegian Sea also fitted reasonably well to the model, whereas data from cod from the North Sea showed a good fit to the model only above a length of 70 cm. Cod from the Barents Sea did not grow according to the model. The last results can be explained by environmental factors and variable food availability in the time under study. The model implicates that the efficiency of energy conversion from food decreases as the individual animal approaches its maximal length and is postulated to represent a natural law of fish growth.

Brexit and the Politics of UK Growth Models

DEFF Research Database (Denmark)

Rosamond, Ben

2018-01-01

Brexit has reopened and repoliticized the debate about future growth models for the UK economy. This contribution argues that this debate is built around historically specific path dependencies that reflect the particular character of public debate about British political economy, while also...... particular attention to the importance of the politics of support. It suggests that recent debate about growth models has been largely subsumed within the politics of Brexit, which has politicized that debate, albeit through the emergent political economy frames that Brexit has provoked. The paper explores...... suggesting that the debate around Brexit takes place at a very distinctive moment in the history of democratic capitalism in Europe. This combination gives the renewed politicization a specific and perhaps perverse character. The paper considers how we should approach debates about growth models, paying...

Cellular Automaton Modeling of Dendritic Growth Using a Multi-grid Method

International Nuclear Information System (INIS)

Natsume, Y; Ohsasa, K

2015-01-01

A two-dimensional cellular automaton model with a multi-grid method was developed to simulate dendritic growth. In the present model, we used a triple-grid system for temperature, solute concentration and solid fraction fields as a new approach of the multi-grid method. In order to evaluate the validity of the present model, we carried out simulations of single dendritic growth, secondary dendrite arm growth, multi-columnar dendritic growth and multi-equiaxed dendritic growth. From the results of the grid dependency from the simulation of single dendritic growth, we confirmed that the larger grid can be used in the simulation and that the computational time can be reduced dramatically. In the simulation of secondary dendrite arm growth, the results from the present model were in good agreement with the experimental data and the simulated results from a phase-field model. Thus, the present model can quantitatively simulate dendritic growth. From the simulated results of multi-columnar and multi-equiaxed dendrites, we confirmed that the present model can perform simulations under practical solidification conditions. (paper)

An Evolutionary Robotics Approach to the Control of Plant Growth and Motion: Modeling Plants and Crossing the Reality Gap

DEFF Research Database (Denmark)

Wahby, Mostafa; Hofstadler, Daniel Nicolas; Heinrich, Mary Katherine

2016-01-01

The self-organizing bio-hybrid collaboration of robots and natural plants allows for a variety of interesting applications. As an example we investigate how robots can be used to control the growth and motion of a natural plant, using LEDs to provide stimuli. We follow an evolutionary robotics...... approach where task performance is determined by monitoring the plant's reaction. First, we do initial plant experiments with simple, predetermined controllers. Then we use image sampling data as a model of the dynamics of the plant tip xy position. Second, we use this approach to evolve robot controllers...

Post-Keynesyen Talep Yönelimli Büyüme Modelleri(Post-Keynesian Demand Oriented Growth Models

Directory of Open Access Journals (Sweden)

Yelda Bugay TEKGÜL

2013-12-01

Full Text Available Economic literature generally contains growth models dominated by classical/neo-classical approach. These models focused on the differences in the growth rates among countries in terms of supply of factors of production. Wheras capital accumulation and technical progress are viewed as the main determinant of the growth, increase in per-capita income is only determined by supply-side factors. Should the economy is in the position of under-employment and under-capacity, then these approaches are not capable of satisfactory explanation for the economic growth. Assumptions of supply-side approach are endogenous regarding the economic system and restricted by the demand. In an open economy, growth can be defined as a component of a Keynesian demand-oriented economic system and it is genarally called as Post-Keynesian growth models. These models have been developed on two main axes: “Export-led growth model”, introduced by N. Kaldor and “balance-of-payment constrained growth model”introduced by A.P.Thirwall in 1979. Export-led growth model is based on the assumption that internally determined productivity increases generate a virtous circle economy. Balance-of-payment constrained growth model, on the other hand, is based on the assumption that foreign trade deficit cannot continue forever and that long-run growth rate is a function of the export and elasticity of demand for import of the country. The objective of this paper is to discuss and critisize export-led growth and balance-of-payment constrained growth model.

Geometrical approach to tumor growth

OpenAIRE

Escudero, Carlos

2006-01-01

Tumor growth has a number of features in common with a physical process known as molecular beam epitaxy. Both growth processes are characterized by the constraint of growth development to the body border, and surface diffusion of cells/particles at the growing edge. However, tumor growth implies an approximate spherical symmetry that makes necessary a geometrical treatment of the growth equations. The basic model was introduced in a former article [C. Escudero, Phys. Rev. E 73, 020902(R) (200...

In silico modeling for tumor growth visualization.

Science.gov (United States)

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.

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

Science.gov (United States)

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.

Analytical prediction model for non-symmetric fatigue crack growth in Fibre Metal Laminates

NARCIS (Netherlands)

Wang, W.; Rans, C.D.; Benedictus, R.

2017-01-01

This paper proposes an analytical model for predicting the non-symmetric crack growth and accompanying delamination growth in FMLs. The general approach of this model applies Linear Elastic Fracture Mechanics, the principle of superposition, and displacement compatibility based on the

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

Science.gov (United States)

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

Modelling subject-specific childhood growth using linear mixed-effect models with cubic regression splines.

Science.gov (United States)

Grajeda, Laura M; Ivanescu, Andrada; Saito, Mayuko; Crainiceanu, Ciprian; Jaganath, Devan; Gilman, Robert H; Crabtree, Jean E; Kelleher, Dermott; Cabrera, Lilia; Cama, Vitaliano; Checkley, William

2016-01-01

Childhood growth is a cornerstone of pediatric research. Statistical models need to consider individual trajectories to adequately describe growth outcomes. Specifically, well-defined longitudinal models are essential to characterize both population and subject-specific growth. Linear mixed-effect models with cubic regression splines can account for the nonlinearity of growth curves and provide reasonable estimators of population and subject-specific growth, velocity and acceleration. We provide a stepwise approach that builds from simple to complex models, and account for the intrinsic complexity of the data. We start with standard cubic splines regression models and build up to a model that includes subject-specific random intercepts and slopes and residual autocorrelation. We then compared cubic regression splines vis-à-vis linear piecewise splines, and with varying number of knots and positions. Statistical code is provided to ensure reproducibility and improve dissemination of methods. Models are applied to longitudinal height measurements in a cohort of 215 Peruvian children followed from birth until their fourth year of life. Unexplained variability, as measured by the variance of the regression model, was reduced from 7.34 when using ordinary least squares to 0.81 (p linear mixed-effect models with random slopes and a first order continuous autoregressive error term. There was substantial heterogeneity in both the intercept (p modeled with a first order continuous autoregressive error term as evidenced by the variogram of the residuals and by a lack of association among residuals. The final model provides a parametric linear regression equation for both estimation and prediction of population- and individual-level growth in height. We show that cubic regression splines are superior to linear regression splines for the case of a small number of knots in both estimation and prediction with the full linear mixed effect model (AIC 19,352 vs. 19

Linking genes to microbial growth kinetics: an integrated biochemical systems engineering approach.

Science.gov (United States)

Koutinas, Michalis; Kiparissides, Alexandros; Silva-Rocha, Rafael; Lam, Ming-Chi; Martins Dos Santos, Vitor A P; de Lorenzo, Victor; Pistikopoulos, Efstratios N; Mantalaris, Athanasios

2011-07-01

The majority of models describing the kinetic properties of a microorganism for a given substrate are unstructured and empirical. They are formulated in this manner so that the complex mechanism of cell growth is simplified. Herein, a novel approach for modelling microbial growth kinetics is proposed, linking biomass growth and substrate consumption rates to the gene regulatory programmes that control these processes. A dynamic model of the TOL (pWW0) plasmid of Pseudomonas putida mt-2 has been developed, describing the molecular interactions that lead to the transcription of the upper and meta operons, known to produce the enzymes for the oxidative catabolism of m-xylene. The genetic circuit model was combined with a growth kinetic model decoupling biomass growth and substrate consumption rates, which are expressed as independent functions of the rate-limiting enzymes produced by the operons. Estimation of model parameters and validation of the model's predictive capability were successfully performed in batch cultures of mt-2 fed with different concentrations of m-xylene, as confirmed by relative mRNA concentration measurements of the promoters encoded in TOL. The growth formation and substrate utilisation patterns could not be accurately described by traditional Monod-type models for a wide range of conditions, demonstrating the critical importance of gene regulation for the development of advanced models closely predicting complex bioprocesses. In contrast, the proposed strategy, which utilises quantitative information pertaining to upstream molecular events that control the production of rate-limiting enzymes, predicts the catabolism of a substrate and biomass formation and could be of central importance for the design of optimal bioprocesses. Copyright © 2011 Elsevier Inc. All rights reserved.

Modeling pitting growth data and predicting degradation trend

International Nuclear Information System (INIS)

Viglasky, T.; Awad, R.; Zeng, Z.; Riznic, J.

2007-01-01

A non-statistical modeling approach to predict material degradation is presented in this paper. In this approach, the original data series is processed using Accumulated Generating Operation (AGO). With the aid of the AGO which weakens the random fluctuation embedded in the data series, an approximately exponential curve is established. The generated data series described by the exponential curve is then modeled by a differential equation. The coefficients of the differential equation can be deduced by approximate difference formula based on least-squares algorithm. By solving the differential equation and processing an inverse AGO, a predictive model can be obtained. As this approach is not established on the basis of statistics, the prediction can be performed with a limited amount of data. Implementation of this approach is demonstrated by predicting the pitting growth rate in specimens and wear trend in steam generator tubes. The analysis results indicate that this approach provides a powerful tool with reasonable precision to predict material degradation. (author)

Conditional random slope: A new approach for estimating individual child growth velocity in epidemiological research.

Science.gov (United States)

Leung, Michael; Bassani, Diego G; Racine-Poon, Amy; Goldenberg, Anna; Ali, Syed Asad; Kang, Gagandeep; Premkumar, Prasanna S; Roth, Daniel E

2017-09-10

Conditioning child growth measures on baseline accounts for regression to the mean (RTM). Here, we present the "conditional random slope" (CRS) model, based on a linear-mixed effects model that incorporates a baseline-time interaction term that can accommodate multiple data points for a child while also directly accounting for RTM. In two birth cohorts, we applied five approaches to estimate child growth velocities from 0 to 12 months to assess the effect of increasing data density (number of measures per child) on the magnitude of RTM of unconditional estimates, and the correlation and concordance between the CRS and four alternative metrics. Further, we demonstrated the differential effect of the choice of velocity metric on the magnitude of the association between infant growth and stunting at 2 years. RTM was minimally attenuated by increasing data density for unconditional growth modeling approaches. CRS and classical conditional models gave nearly identical estimates with two measures per child. Compared to the CRS estimates, unconditional metrics had moderate correlation (r = 0.65-0.91), but poor agreement in the classification of infants with relatively slow growth (kappa = 0.38-0.78). Estimates of the velocity-stunting association were the same for CRS and classical conditional models but differed substantially between conditional versus unconditional metrics. The CRS can leverage the flexibility of linear mixed models while addressing RTM in longitudinal analyses. © 2017 The Authors American Journal of Human Biology Published by Wiley Periodicals, Inc.

Modeling individual differences in randomized experiments using growth models: Recommendations for design, statistical analysis and reporting of results of internet interventions

Directory of Open Access Journals (Sweden)

Hugo Hesser

2015-05-01

Full Text Available Growth models (also known as linear mixed effects models, multilevel models, and random coefficients models have the capability of studying change at the group as well as the individual level. In addition, these methods have documented advantages over traditional data analytic approaches in the analysis of repeated-measures data. These advantages include, but are not limited to, the ability to incorporate time-varying predictors, handle dependence among repeated observations in a very flexible manner, and to provide accurate estimates with missing data under fairly unrestrictive missing data assumptions. The flexibility of the growth curve modeling approach to the analysis of change makes it the preferred choice in the evaluation of direct, indirect and moderated intervention effects. Although offering many benefits, growth models present challenges in terms of design, analysis and reporting of results. This paper provides a nontechnical overview of growth models in the analysis of change in randomized experiments and advocates for their use in the field of internet interventions. Practical recommendations for design, analysis and reporting of results from growth models are provided.

Process-based modelling of tree and stand growth: towards a hierarchical treatment of multiscale processes

International Nuclear Information System (INIS)

Makela, A.

2003-01-01

A generally accepted method has not emerged for managing the different temporal and spatial scales in a forest ecosystem. This paper reviews a hierarchical-modular modelling tradition, with the main focus on individual tree growth throughout the rotation. At this scale, model performance requires (i) realistic long-term dynamic properties, (ii) realistic responses of growth and mortality of competing individuals, and (iii) realistic responses to ecophysio-logical inputs. Model development and validation are illustrated through allocation patterns, height growth, and size-related feedbacks. Empirical work to test the approach is reviewed. In this approach, finer scale effects are embedded in parameters calculated using more detailed, interacting modules. This is exemplified by (i) the within-year effect of weather on annual photosynthesis, (ii) the effects of fast soil processes on carbon allocation and photosynthesis, and (iii) the utilization of detailed stem structure to predict wood quality. Prevailing management paradigms are reflected in growth modelling. A shift of emphasis has occurred from productivity in homogeneous canopies towards, e.g., wood quality versus total yield, spatially more explicit models, and growth decline in old-growth forests. The new problems emphasize the hierarchy of the system and interscale interactions, suggesting that the hierarchical-modular approach could prove constructive. (author)

A website evaluation model by integration of previous evaluation models using a quantitative approach

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Ali Moeini

2015-01-01

Full Text Available Regarding the ecommerce growth, websites play an essential role in business success. Therefore, many authors have offered website evaluation models since 1995. Although, the multiplicity and diversity of evaluation models make it difficult to integrate them into a single comprehensive model. In this paper a quantitative method has been used to integrate previous models into a comprehensive model that is compatible with them. In this approach the researcher judgment has no role in integration of models and the new model takes its validity from 93 previous models and systematic quantitative approach.

Towards a capability approach to child growth: A theoretical framework.

Science.gov (United States)

Haisma, Hinke; Yousefzadeh, Sepideh; Boele Van Hensbroek, Pieter

2018-04-01

Child malnutrition is an important cause of under-5 mortality and morbidity around the globe. Despite the partial success of (inter)national efforts to reduce child mortality, under-5 mortality rates continue to be high. The multidimensional approaches of the Sustainable Development Goals may suggest new directions for rethinking strategies for reducing child mortality and malnutrition. We propose a theoretical framework for developing a "capability" approach to child growth. The current child growth monitoring practices are based on 2 assumptions: (a) that anthropometric and motor development measures are the appropriate indicators; and (b) that child growth can be assessed using a single universal standard that is applicable around the world. These practices may be further advanced by applying a capability approach to child growth, whereby growth is redefined as the achievement of certain capabilities (of society, parents, and children). This framework is similar to the multidimensional approach to societal development presented in the seminal work of Amartya Sen. To identify the dimensions of healthy child growth, we draw upon theories from the social sciences and evolutionary biology. Conceptually, we consider growth as a plural space and propose assessing growth by means of a child growth matrix in which the context is embedded in the assessment. This approach will better address the diversities and the inequalities in child growth. Such a multidimensional measure will have implications for interventions and policy, including prevention and counselling, and could have an impact on child malnutrition and mortality. © 2017 The Authors. Maternal and Child Nutrition Published by John Wiley & Sons, Ltd.

A Systematic Approach for Identifying Level-1 Error Covariance Structures in Latent Growth Modeling

Science.gov (United States)

Ding, Cherng G.; Jane, Ten-Der; Wu, Chiu-Hui; Lin, Hang-Rung; Shen, Chih-Kang

2017-01-01

It has been pointed out in the literature that misspecification of the level-1 error covariance structure in latent growth modeling (LGM) has detrimental impacts on the inferences about growth parameters. Since correct covariance structure is difficult to specify by theory, the identification needs to rely on a specification search, which,…

Accounting for household heterogeneity in general equilibrium economic growth models

International Nuclear Information System (INIS)

Melnikov, N.B.; O'Neill, B.C.; Dalton, M.G.

2012-01-01

We describe and evaluate a new method of aggregating heterogeneous households that allows for the representation of changing demographic composition in a multi-sector economic growth model. The method is based on a utility and labor supply calibration that takes into account time variations in demographic characteristics of the population. We test the method using the Population-Environment-Technology (PET) model by comparing energy and emissions projections employing the aggregate representation of households to projections representing different household types explicitly. Results show that the difference between the two approaches in terms of total demand for energy and consumption goods is negligible for a wide range of model parameters. Our approach allows the effects of population aging, urbanization, and other forms of compositional change on energy demand and CO 2 emissions to be estimated and compared in a computationally manageable manner using a representative household under assumptions and functional forms that are standard in economic growth models.

An approach to the broadband effect on Latin American growth: A structural model

Directory of Open Access Journals (Sweden)

María Verónica Alderete

2017-07-01

Full Text Available This paper analyses the fixed broadband penetration effect on Latin American economic growth. The methodology employed consists of using a simultaneous equation model based on Koutroumpis (2009 and Katz and Callorda (2013. To aid this process, we use country level data from the World Bank and the Regional Dialogue about the Information Society-DIRSI for the 2010-2014 period. The results obtained stress the importance of broadband penetration for economic growth in Latin America.

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

Directory of Open Access Journals (Sweden)

Michelle Hine Armstrong

Full Text Available 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.

Science.gov (United States)

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 mathematical model of the growth of uterine myomas.

Science.gov (United States)

Chen, C Y; Ward, J P

2014-12-01

Uterine myomas or fibroids are common, benign smooth muscle tumours that can grow to 10  cm or more in diameter and are routinely removed surgically. They are typically slow- growing, well-vascularised, spherical tumours that, on a macro-scale, are a structurally uniform, hard elastic material. We present a multi-phase mathematical model of a fully vascularised myoma growing within a surrounding elastic tissue. Adopting a continuum approach, the model assumes the conservation of mass and momentum of four phases, namely cells/collagen, extracellular fluid, arterial and venous phases. The cell/collagen phase is treated as a poro-elastic material, based on a linear stress-strain relationship, and Darcy's law is applied to describe flow in the extracellular fluid and the two vascular phases. The supply of extracellular fluid is dependent on the capillary flow rate and mean capillary pressure expressed in terms of the arterial and venous pressures. Cell growth and division is limited to the myoma domain and dependent on the local stress in the material. The resulting model consists of a system of nonlinear partial differential equations with two moving boundaries. Numerical solutions of the model successfully reproduce qualitatively the clinically observed three-phase "fast-slow-fast" growth profile that is typical for myomas. The results suggest that this growth profile requires stress-induced resistance to growth by the surrounding tissue and a switch-like cell growth response to stress. Analysis of large-time solutions reveal that while there is a functioning vasculature throughout the myoma, exponential growth results, otherwise power-law growth is predicted. An extensive survey of the effect of parameters on model solutions is also presented, and in particular, the enhanced growth caused by factors such as oestrogen is predicted by the model.

Simulating Spatial Growth Patterns in Developing Countries: an Agent Based Modelling Approach. A Case of Shama in the Western Region of Ghana

Science.gov (United States)

Inkoom, J. N.

2011-12-01

In Sub-Saharan Africa, rapid urban growth is characterized by prolific expansion of unplanned (informal) structures, and unguided spatial expansion. These unguided expansions by human agents have outstripped the regulatory capacities of Central and Local government. Governmental institutions in finding solutions to the unguided expansion in unplanned use of land have to call for the modelling of what influences the spatial decision and role of human agents in the growth of informal settlement. The objective of the study is to simulate spatial growth pattern of settlements in the Shama district using an agent based model. The study was conducted within a framework of NetLogo. The NetLogo assisted to incorporate and simulate driving forces that affect location decision-making by households and the growth of informal settlement. A survey was conducted to obtain household location decision preferences. The development of unplanned settlement has been a function of land price, proximity to economic centre's, household economic potential, and the location decision-making patterns of households. The exploratory analysis found particularly that majority of spontaneous development took place on areas liable to floods suggesting that some structures fall outside the required building regulations. The application of the proposed model indicates its potential to improve urban planning policies and decision-making processes in emerging cities of developing countries. Also, the result of the simulation suggests potential preferential location for residential development. The research justifies an approach in the area of simulating urban dynamics with agent-based models.

Modelling breast cancer tumour growth for a stable disease population.

Science.gov (United States)

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.

Practice-oriented optical thin film growth simulation via multiple scale approach

Energy Technology Data Exchange (ETDEWEB)

Turowski, Marcus, E-mail: m.turowski@lzh.de [Laser Zentrum Hannover e.V., Hollerithallee 8, Hannover 30419 (Germany); Jupé, Marco [Laser Zentrum Hannover e.V., Hollerithallee 8, Hannover 30419 (Germany); QUEST: Centre of Quantum Engineering and Space-Time Research, Leibniz Universität Hannover (Germany); Melzig, Thomas [Fraunhofer Institute for Surface Engineering and Thin Films IST, Bienroder Weg 54e, Braunschweig 30108 (Germany); Moskovkin, Pavel [Research Centre for Physics of Matter and Radiation (PMR-LARN), University of Namur (FUNDP), 61 rue de Bruxelles, Namur 5000 (Belgium); Daniel, Alain [Centre for Research in Metallurgy, CRM, 21 Avenue du bois Saint Jean, Liège 4000 (Belgium); Pflug, Andreas [Fraunhofer Institute for Surface Engineering and Thin Films IST, Bienroder Weg 54e, Braunschweig 30108 (Germany); Lucas, Stéphane [Research Centre for Physics of Matter and Radiation (PMR-LARN), University of Namur (FUNDP), 61 rue de Bruxelles, Namur 5000 (Belgium); Ristau, Detlev [Laser Zentrum Hannover e.V., Hollerithallee 8, Hannover 30419 (Germany); QUEST: Centre of Quantum Engineering and Space-Time Research, Leibniz Universität Hannover (Germany)

2015-10-01

Simulation of the coating process is a very promising approach for the understanding of thin film formation. Nevertheless, this complex matter cannot be covered by a single simulation technique. To consider all mechanisms and processes influencing the optical properties of the growing thin films, various common theoretical methods have been combined to a multi-scale model approach. The simulation techniques have been selected in order to describe all processes in the coating chamber, especially the various mechanisms of thin film growth, and to enable the analysis of the resulting structural as well as optical and electronic layer properties. All methods are merged with adapted communication interfaces to achieve optimum compatibility of the different approaches and to generate physically meaningful results. The present contribution offers an approach for the full simulation of an Ion Beam Sputtering (IBS) coating process combining direct simulation Monte Carlo, classical molecular dynamics, kinetic Monte Carlo, and density functional theory. The simulation is performed exemplary for an existing IBS-coating plant to achieve a validation of the developed multi-scale approach. Finally, the modeled results are compared to experimental data. - Highlights: • A model approach for simulating an Ion Beam Sputtering (IBS) process is presented. • In order to combine the different techniques, optimized interfaces are developed. • The transport of atomic species in the coating chamber is calculated. • We modeled structural and optical film properties based on simulated IBS parameter. • The modeled and the experimental refractive index data fit very well.

Modelling planktic foraminifer growth and distribution using an ecophysiological multi-species approach

DEFF Research Database (Denmark)

Lombard, Fabien; Labeyrie, L.; Michel, E.

2011-01-01

We present an eco-physiological model reproducing the growth of eight foraminifer species (Neogloboquadrina pachyderma, Neogloboquadrina incompta, Neogloboquadrina dutertrei, Globigerina bulloides, Globigerinoides ruber, Globigerinoides sacculifer, Globigerinella siphonifera and Orbulina universa...... in the marine carbon cycle....... ocean (PISCES) instead of satellite images as forcing variables gives also good results, but with lower efficiency (58.9%). Compared to core tops observations, the model also correctly reproduces the relative worldwide abundance and the diversity of the eight species when using either satellite data...

Towards Sustainable Growth Business Models

Energy Technology Data Exchange (ETDEWEB)

Kamp-Roelands, N.; Balkenende, J.P.; Van Ommen, P.

2012-03-15

The Dutch Sustainable Growth Coalition (DSGC) has the following objectives: The DSGC aims to pro-actively drive sustainable growth business models along three lines: (1) Shape. DSGC member companies aim to connect economic profitability with environmental and social progress on the basis of integrated sustainable growth business models; (2) Share. DSGC member companies aim for joint advocacy of sustainable growth business models both internationally and nationally; and (3) Stimulate. DSGC member companies aim to stimulate and influence the policy debate on enabling sustainable growth - with a view to finding solutions to the environmental and social challenges we are facing. This is their first report. The vision, actions and mission of DSGC are documented in the Manifesto in Chapter 2 of this publication. Chapter 3 contains an overview of key features of an integrated sustainable growth business model and the roadmap towards such a model. In Chapter 4, project examples of DSGC members are presented, providing insight into the hands-on reality of implementing the good practices. Chapter 5 offers an overview of how the Netherlands provides an enabling environment for sustainable growth business models. Chapter 6 offers the key conclusions.

Robust Determinants of Growth in Asian Developing Economies: A Bayesian Panel Data Model Averaging Approach

OpenAIRE

LEON-GONZALEZ, Roberto; VINAYAGATHASAN, Thanabalasingam

2013-01-01

This paper investigates the determinants of growth in the Asian developing economies. We use Bayesian model averaging (BMA) in the context of a dynamic panel data growth regression to overcome the uncertainty over the choice of control variables. In addition, we use a Bayesian algorithm to analyze a large number of competing models. Among the explanatory variables, we include a non-linear function of inflation that allows for threshold effects. We use an unbalanced panel data set of 27 Asian ...

Modelling the interaction between flooding events and economic growth

Directory of Open Access Journals (Sweden)

J. Grames

2015-06-01

Full Text Available Socio-hydrology describes the interaction between the socio-economy and water. Recent models analyze the interplay of community risk-coping culture, flooding damage and economic growth (Di Baldassarre et al., 2013; Viglione et al., 2014. These models descriptively explain the feedbacks between socio-economic development and natural disasters like floods. Contrary to these descriptive models, our approach develops an optimization model, where the intertemporal decision of an economic agent interacts with the hydrological system. In order to build this first economic growth model describing the interaction between the consumption and investment decisions of an economic agent and the occurrence of flooding events, we transform an existing descriptive stochastic model into an optimal deterministic model. The intermediate step is to formulate and simulate a descriptive deterministic model. We develop a periodic water function to approximate the former discrete stochastic time series of rainfall events. Due to the non-autonomous exogenous periodic rainfall function the long-term path of consumption and investment will be periodic.

Econometric modelling of Serbian current account determinants: Jackknife Model Averaging approach

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Petrović Predrag

2014-01-01

Full Text Available This research aims to model Serbian current account determinants for the period Q1 2002 - Q4 2012. Taking into account the majority of relevant determinants, using the Jackknife Model Averaging approach, 48 different models have been estimated, where 1254 equations needed to be estimated and averaged for each of the models. The results of selected representative models indicate moderate persistence of the CA and positive influence of: fiscal balance, oil trade balance, terms of trade, relative income and real effective exchange rates, where we should emphasise: (i a rather strong influence of relative income, (ii the fact that the worsening of oil trade balance results in worsening of other components (probably non-oil trade balance of CA and (iii that the positive influence of terms of trade reveals functionality of the Harberger-Laursen-Metzler effect in Serbia. On the other hand, negative influence is evident in case of: relative economic growth, gross fixed capital formation, net foreign assets and trade openness. What particularly stands out is the strong effect of relative economic growth that, most likely, reveals high citizens' future income growth expectations, which has negative impact on the CA.

Heterogeneity of growth in the west Balkans and emerging Europe: A dynamic panel data model approach

Directory of Open Access Journals (Sweden)

Josifidis Kosta

2012-01-01

Full Text Available This paper explores the heterogeneity of growth in the Western Balkan and Emerging European economies. For that purpose, growth determinants are estimated in the period 1997-2009 by dynamic panel data models. The chosen period provides a comparison for the model results with those estimated for the period up to 2007 in order to analyze changes caused by the global instability. According to the main findings of the paper, macroeconomic stabilization and structural reforms still matter in determining economic growth, but foreign direct investments and economic integrations seem to have the most important role in stimulating growth in the observed countries. Moreover, significant positive effects of foreign direct investments and economic integrations produce differences in growth paths between Emerging European and Western Balkan economies. Sharp decrease of foreign inflows in 2008 determined contractions of growth rates firstly in Emerging European economies with subsequent spill-over on the Western Balkan economies during 2009. Consequently, in the period of global instability, differences between two groups of economies become even more obvious.

Fractal approach to computer-analytical modelling of tree crown

International Nuclear Information System (INIS)

Berezovskaya, F.S.; Karev, G.P.; Kisliuk, O.F.; Khlebopros, R.G.; Tcelniker, Yu.L.

1993-09-01

In this paper we discuss three approaches to the modeling of a tree crown development. These approaches are experimental (i.e. regressive), theoretical (i.e. analytical) and simulation (i.e. computer) modeling. The common assumption of these is that a tree can be regarded as one of the fractal objects which is the collection of semi-similar objects and combines the properties of two- and three-dimensional bodies. We show that a fractal measure of crown can be used as the link between the mathematical models of crown growth and light propagation through canopy. The computer approach gives the possibility to visualize a crown development and to calibrate the model on experimental data. In the paper different stages of the above-mentioned approaches are described. The experimental data for spruce, the description of computer system for modeling and the variant of computer model are presented. (author). 9 refs, 4 figs

Quantitative Phase-Field Approach for Simulating Grain Growth in Anisotropic Systems with Arbitrary Inclination and Misorientation Dependence

International Nuclear Information System (INIS)

Moelans, N.; Blanpain, B.; Wollants, P.

2008-01-01

A phase-field approach for quantitative simulations of grain growth in anisotropic systems is introduced, together with a new methodology to derive appropriate model parameters that reproduce given misorientation and inclination dependent grain boundary energy and mobility in the simulations. The proposed model formulation and parameter choice guarantee a constant diffuse interface width and consequently give high controllability of the accuracy in grain growth simulations

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

Science.gov (United States)

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...

Generic global regression models for growth prediction of Salmonella in ground pork and pork cuts

DEFF Research Database (Denmark)

Buschhardt, Tasja; Hansen, Tina Beck; Bahl, Martin Iain

2017-01-01

Introduction and Objectives Models for the prediction of bacterial growth in fresh pork are primarily developed using two-step regression (i.e. primary models followed by secondary models). These models are also generally based on experiments in liquids or ground meat and neglect surface growth....... It has been shown that one-step global regressions can result in more accurate models and that bacterial growth on intact surfaces can substantially differ from growth in liquid culture. Material and Methods We used a global-regression approach to develop predictive models for the growth of Salmonella....... One part of obtained logtransformed cell counts was used for model development and another for model validation. The Ratkowsky square root model and the relative lag time (RLT) model were integrated into the logistic model with delay. Fitted parameter estimates were compared to investigate the effect...

A coupled model approach to reduce nonpoint-source pollution resulting from predicted urban growth: A case study in the Ambos Nogales watershed

Science.gov (United States)

Norman, L.M.; Guertin, D.P.; Feller, M.

2008-01-01

The development of new approaches for understanding processes of urban development and their environmental effects, as well as strategies for sustainable management, is essential in expanding metropolitan areas. This study illustrates the potential of linking urban growth and watershed models to identify problem areas and support long-term watershed planning. Sediment is a primary source of nonpoint-source pollution in surface waters. In urban areas, sediment is intermingled with other surface debris in transport. In an effort to forecast the effects of development on surface-water quality, changes predicted in urban areas by the SLEUTH urban growth model were applied in the context of erosion-sedimentation models (Universal Soil Loss Equation and Spatially Explicit Delivery Models). The models are used to simulate the effect of excluding hot-spot areas of erosion and sedimentation from future urban growth and to predict the impacts of alternative erosion-control scenarios. Ambos Nogales, meaning 'both Nogaleses,' is a name commonly used for the twin border cities of Nogales, Arizona and Nogales, Sonora, Mexico. The Ambos Nogales watershed has experienced a decrease in water quality as a result of urban development in the twin-city area. Population growth rates in Ambos Nogales are high and the resources set in place to accommodate the rapid population influx will soon become overburdened. Because of its remote location and binational governance, monitoring and planning across the border is compromised. One scenario described in this research portrays an improvement in water quality through the identification of high-risk areas using models that simulate their protection from development and replanting with native grasses, while permitting the predicted and inevitable growth elsewhere. This is meant to add to the body of knowledge about forecasting the impact potential of urbanization on sediment delivery to streams for sustainable development, which can be

A 2-D nucleation-growth model of spheroidal graphite

International Nuclear Information System (INIS)

Lacaze, Jacques; Bourdie, Jacques; Castro-Román, Manuel Jesus

2017-01-01

Analysis of recent experimental investigations, in particular by transmission electron microscopy, suggests spheroidal graphite grows by 2-D nucleation of new graphite layers at the outer surface of the nodules. These layers spread over the surface along the prismatic direction of graphite which is the energetically preferred growth direction of graphite when the apparent growth direction of the nodules is along the basal direction of graphite. 2-D nucleation-growth models first developed for precipitation of pure substances are then adapted to graphite growth from the liquid in spheroidal graphite cast irons. Lateral extension of the new graphite layers is controlled by carbon diffusion in the liquid. This allows describing quantitatively previous experimental results giving strong support to this approach.

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

Science.gov (United States)

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.

Explaining African Growth Performance: A Production-Frontier Approach

OpenAIRE

Romain Houssa; Oleg Badunenko; Daniel J. Henderson

2010-01-01

This paper employs a production frontier approach that allows distinguishing technologic progress from efficiency development. Data on 35 African countries in 1970-2007 show that efficiency losses have constrained growth in Africa while technology progress has played a marginal growth enhancing role in the region. Moreover, physical and human capital accumulation are the main factors that drive productivity growth at the country level. Examining the outcomes of successful countries suggests t...

EVOLUTION OF THEORIES AND EMPIRICAL MODELS OF A RELATIONSHIP BETWEEN ECONOMIC GROWTH, SCIENCE AND INNOVATIONS (PART I

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Kaneva M. A.

2017-12-01

Full Text Available This article is a first chapter of an analytical review of existing theoretical models of a relationship between economic growth / GRP and indicators of scientific development and innovation activities, as well as empirical approaches to testing this relationship. Aim of the paper is a systematization of existing approaches to modeling of economic growth geared by science and innovations. The novelty of the current review lies in the authors’ criteria of interconnectedness of theoretical and empirical studies in the systematization of a wide range of publications presented in a final table-scheme. In the first part of the article the authors discuss evolution of theoretical approaches, while the second chapter presents a time gap between theories and their empirical verification caused by the level of development of quantitative instruments such as econometric models. The results of this study can be used by researchers and graduate students for familiarization with current scientific approaches that manifest progress from theory to empirical verification of a relationship «economic growth-innovations» for improvement of different types of models in spatial econometrics. To apply these models to management practices the presented review could be supplemented with new criteria for classification of knowledge production functions and other theories about effect of science on economic growth.

A comparison of scope for growth (SFG) and dynamic energy budget (DEB) models applied to the blue mussel ( Mytilus edulis)

Science.gov (United States)

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.

Bayesian modeling of Clostridium perfringens growth in beef-in-sauce products.

Science.gov (United States)

Jaloustre, S; Cornu, M; Morelli, E; Noël, V; Delignette-Muller, M L

2011-04-01

Models on Clostridium perfringens growth which have been published to date have all been deterministic. A probabilistic model describing growth under non-isothermal conditions was thus proposed for predicting C. perfringens growth in beef-in-sauce products cooked and distributed in a French hospital. Model parameters were estimated from different types of data from various studies. A Bayesian approach was proposed to model the overall uncertainty regarding parameters and potential variability on the 'work to be done' (h(0)) during the germination, outgrowth and lag phase. Three models which differed according to their description of this parameter h(0) were tested. The model with inter-curve variability on h(0) was found to be the best one, on the basis of goodness-of-fit assessment and validation with literature data on results obtained under non-isothermal conditions. This model was used in two-dimensional Monte Carlo simulations to predict C. perfringens growth throughout the preparation of beef-in-sauce products, using temperature profiles recorded in a hospital kitchen. The median predicted growth was 7.8×10(-2) log(10) cfu·g(-1) (95% credibility interval [2.4×10(-2), 0.8]) despite the fact that for more than 50% of the registered temperature profiles cooling steps were longer than those required by French regulations. Copyright © 2010 Elsevier Ltd. All rights reserved.

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

Science.gov (United States)

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.

The Effects of Unemployment on Economic Growth in Greece. An ARDL Bound Test Approach.

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Nikolaos Dritsakis

2016-12-01

Full Text Available The aim of this paper is to investigate the relationship between unemployment rate, economic growth and inflation rate in Greece, using annual data covering the period 1995-2015. The unit root tests results indicated that the variables have different integration order. Subsequently, the bounds testing (ARDL approach and ECM-ARDL model are applied in order to examine the long-run and the causal relationship between the variables. The empirical results of the study revealed, both in the short and long-run, that there is a unidirectional causal relationship between unemployment and economic growth with direction from unemployment to economic growth, as well as a unidirectional causality running from inflation to economic growth.

Developing a dynamic growth model for teak plantations in India

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Vindhya Prasad Tewari

2014-05-01

Full Text Available Background Tectona grandis (teak is one of the most important tropical timber speciesoccurring naturally in India. Appropriate growth models, based on advanced modeling techniques,are not available but are necessary for the successful management of teak stands in the country.Long-term forest planning requires mathematical models, and the principles of Dynamical SystemTheory provide a solid foundation for these. Methods The state-space approach makes it possible to accommodate disturbances and avarying environment. In this paper, an attempt has been made to develop a dynamic growthmodel based on the limited data, consisting of three annual measurements, collected from 22 teak sample plots in Karnataka, Southern India. Results A biologically consistent whole-stand growth model has been presented which uses thestate-space approach for modelling rates of change of three state-variables viz., dominant height,stems per hectare and stand basal area. Moreover, the model includes a stand volume equationas an output function to estimate this variable at any point in time. Transition functions werefitted separately and simultaneously. Moreover, a continuous autoregressive error structure isalso included in the modelling process. For fitting volume equation, generalized method of moments was used to get efficient parameter estimates under heteroscedastic conditions. Conclusions A simple model containing few free parameters performed well and is particularlywell suited to situations where available data is scarce.

A multi-sectoral version of the Post-Keynesian growth model

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Ricardo Azevedo Araujo

2015-03-01

Full Text Available Abstract With this inquiry, we seek to develop a disaggregated version of the post-Keynesian approach to economic growth, by showing that indeed it can be treated as a particular case of the Pasinettian model of structural change and economic expansion. By relying upon vertical integration it becomes possible to carry out the analysis initiated by Kaldor (1956 and Robinson (1956, 1962, and followed by Dutt (1984, Rowthorn (1982 and later Bhaduri and Marglin (1990 in a multi-sectoral model in which demand and productivity increase at different paces in each sector. By adopting this approach it is possible to show that the structural economic dynamics is conditioned not only to patterns of evolving demand and diffusion of technological progress but also to the distributive features of the economy, which can give rise to different regimes of economic growth. Besides, we find it possible to determine the natural rate of profit that makes the mark-up rate to be constant over time.

Technical note: Comparison of methane ebullition modelling approaches used in terrestrial wetland models

Science.gov (United States)

Peltola, Olli; Raivonen, Maarit; Li, Xuefei; Vesala, Timo

2018-02-01

Emission via bubbling, i.e. ebullition, is one of the main methane (CH4) emission pathways from wetlands to the atmosphere. Direct measurement of gas bubble formation, growth and release in the peat-water matrix is challenging and in consequence these processes are relatively unknown and are coarsely represented in current wetland CH4 emission models. In this study we aimed to evaluate three ebullition modelling approaches and their effect on model performance. This was achieved by implementing the three approaches in one process-based CH4 emission model. All the approaches were based on some kind of threshold: either on CH4 pore water concentration (ECT), pressure (EPT) or free-phase gas volume (EBG) threshold. The model was run using 4 years of data from a boreal sedge fen and the results were compared with eddy covariance measurements of CH4 fluxes.Modelled annual CH4 emissions were largely unaffected by the different ebullition modelling approaches; however, temporal variability in CH4 emissions varied an order of magnitude between the approaches. Hence the ebullition modelling approach drives the temporal variability in modelled CH4 emissions and therefore significantly impacts, for instance, high-frequency (daily scale) model comparison and calibration against measurements. The modelling approach based on the most recent knowledge of the ebullition process (volume threshold, EBG) agreed the best with the measured fluxes (R2 = 0.63) and hence produced the most reasonable results, although there was a scale mismatch between the measurements (ecosystem scale with heterogeneous ebullition locations) and model results (single horizontally homogeneous peat column). The approach should be favoured over the two other more widely used ebullition modelling approaches and researchers are encouraged to implement it into their CH4 emission models.

PWSCC Growth Assessment Model Considering Stress Triaxiality Factor for Primary Alloy 600 Components

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Jong-Sung Kim

2016-08-01

Full Text Available We propose a primary water stress corrosion cracking (PWSCC initiation model of Alloy 600 that considers the stress triaxiality factor to apply to finite element analysis. We investigated the correlation between stress triaxiality effects and PWSCC growth behavior in cold-worked Alloy 600 stream generator tubes, and identified an additional stress triaxiality factor that can be added to Garud's PWSCC initiation model. By applying the proposed PWSCC initiation model considering the stress triaxiality factor, PWSCC growth simulations based on the macroscopic phenomenological damage mechanics approach were carried out on the PWSCC growth tests of various cold-worked Alloy 600 steam generator tubes and compact tension specimens. As a result, PWSCC growth behavior results from the finite element prediction are in good agreement with the experimental results.

Growth hormone insensitivity syndrome: A sensitive approach

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Soumik Goswami

2012-01-01

Full Text Available Patients with Growth Hormone Insensitivity have characteristic phenotypic features and severe short stature. The underlying basis are mutations in the growth hormone receptor gene which gives rise to a characteristic hormonal profile. Although a scoring system has been devised for the diagnosis of this disorder, it has not been indisputably validated. The massive expense incurred in the diagnosis and treatment of this condition with suboptimal therapeutic response necessitates a judicious approach in this regard in our country.

Business Model Innovation Portfolio Strategy for Growth Under Product-Market Configurations

OpenAIRE

Bert Verhoeven; Lester W. Johnson

2017-01-01

Purpose: The research links three concepts: product market growth strategy, the magnitude of innovation and Business Model Innovation, merging them together into a dynamic Business Model Innovation strategy framework. Design/Methodology/Approach: The paper is conceptual and exploratory in nature and builds on existing literature and the author’s experience with developing business models. Findings: The BMI strategy framework can help managers establish a BMI portfolio strategy followi...

Stochastic models for tumoral growth

Science.gov (United States)

Escudero, Carlos

2006-02-01

Strong experimental evidence has indicated that tumor growth belongs to the molecular beam epitaxy universality class. This type of growth is characterized by the constraint of cell proliferation to the tumor border and the surface diffusion of cells at the growing edge. Tumor growth is thus conceived as a competition for space between the tumor and the host, and cell diffusion at the tumor border is an optimal strategy adopted for minimizing the pressure and helping tumor development. Two stochastic partial differential equations are reported in this paper in order to correctly model the physical properties of tumoral growth in (1+1) and (2+1) dimensions. The advantage of these models is that they reproduce the correct geometry of the tumor and are defined in terms of polar variables. An analysis of these models allows us to quantitatively estimate the response of the tumor to an unfavorable perturbation during growth.

Electricity consumption and economic growth nexus in Portugal using cointegration and causality approaches

International Nuclear Information System (INIS)

Shahbaz, Muhammad; Tang, Chor Foon; Shahbaz Shabbir, Muhammad

2011-01-01

The aim of this paper is to re-examine the relationship between electricity consumption, economic growth, and employment in Portugal using the cointegration and Granger causality frameworks. This study covers the sample period from 1971 to 2009. We examine the presence of a long-run equilibrium relationship using the bounds testing approach to cointegration within the Unrestricted Error-Correction Model (UECM). Moreover, we examine the direction of causality between electricity consumption, economic growth, and employment in Portugal using the Granger causality test within the Vector Error-Correction Model (VECM). As a summary of the empirical findings, we find that electricity consumption, economic growth, and employment in Portugal are cointegrated and there is bi-directional Granger causality between the three variables in the long-run. With the exception of the Granger causality between electricity consumption and economic growth, the rest of the variables are also bi-directional Granger causality in the short-run. Furthermore, we find that there is unidirectional Granger causality running from economic growth to electricity consumption, but no evidence of reversal causality. - Highlights: → We re-examine the relationship between electricity consumption, economic growth, and employment in Portugal. → The electricity consumption and economic growth is causing each other in the long-run. → In the short-run, economic growth Granger-cause electricity consumption, but no evidence of reversal causality. → Energy conservation policy will deteriorate the process of economic growth in the long-run. → Portugal should increase investment on R and D to design new energy savings technology.

Testing mechanistic models of growth in insects.

Science.gov (United States)

Maino, James L; Kearney, Michael R

2015-11-22

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

Oscillations in a Growth Model with Capital, Technology and Environment with Exogenous Shocks

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Wei-Bin Zhang

2015-07-01

Full Text Available This paper generalizes the dynamic growth model with wealth accumulation, technological change and environmental change by Zhang (2012 by making all the parameters as time-dependent parameters. The model treats physical capital accumulation, knowledge creation and utilization, and environmental change as endogenous variables. It synthesizes the basic ideas of the neoclassical growth theory, Arrow’s learning-by-doing model and the traditional dynamic models of environmental change within a comprehensive framework. The behavior of the household is described with an alternative approach to household behavior. We simulated the model to demonstrate existence of equilibrium points, motion of the dynamic system, and oscillations due to different exogenous shocks.

Translational mixed-effects PKPD modelling of recombinant human growth hormone - from hypophysectomized rat to patients

DEFF Research Database (Denmark)

Thorsted, A; Thygesen, P; Agersø, H

2016-01-01

BACKGROUND AND PURPOSE: We aimed to develop a mechanistic mixed-effects pharmacokinetic (PK)-pharmacodynamic (PD) (PKPD) model for recombinant human growth hormone (rhGH) in hypophysectomized rats and to predict the human PKPD relationship. EXPERIMENTAL APPROACH: A non-linear mixed-effects model...... was developed from experimental PKPD studies of rhGH and effects of long-term treatment as measured by insulin-like growth factor 1 (IGF-1) and bodyweight gain in rats. Modelled parameter values were scaled to human values using the allometric approach with fixed exponents for PKs and unscaled for PDs...... s.c. administration was over predicted. After correction of the human s.c. absorption model, the induction model for IGF-1 well described the human PKPD data. CONCLUSIONS: A translational mechanistic PKPD model for rhGH was successfully developed from experimental rat data. The model links...

Urban Growth Modelling with Artificial Neural Network and Logistic Regression. Case Study: Sanandaj City, Iran

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SASSAN MOHAMMADY

2013-01-01

Full Text Available Cities have shown remarkable growth due to attraction, economic, social and facilities centralization in the past few decades. Population and urban expansion especially in developing countries, led to lack of resources, land use change from appropriate agricultural land to urban land use and marginalization. Under these circumstances, land use activity is a major issue and challenge for town and country planners. Different approaches have been attempted in urban expansion modelling. Artificial Neural network (ANN models are among knowledge-based models which have been used for urban growth modelling. ANNs are powerful tools that use a machine learning approach to quantify and model complex behaviour and patterns. In this research, ANN and logistic regression have been employed for interpreting urban growth modelling. Our case study is Sanandaj city and we used Landsat TM and ETM+ imageries acquired at 2000 and 2006. The dataset used includes distance to main roads, distance to the residence region, elevation, slope, and distance to green space. Percent Area Match (PAM obtained from modelling of these changes with ANN is equal to 90.47% and the accuracy achieved for urban growth modelling with Logistic Regression (LR is equal to 88.91%. Percent Correct Match (PCM and Figure of Merit for ANN method were 91.33% and 59.07% and then for LR were 90.84% and 57.07%, respectively.

Stochastic Individual-Based Modeling of Bacterial Growth and Division Using Flow Cytometry

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Míriam R. García

2018-01-01

Full Text Available A realistic description of the variability in bacterial growth and division is critical to produce reliable predictions of safety risks along the food chain. Individual-based modeling of bacteria provides the theoretical framework to deal with this variability, but it requires information about the individual behavior of bacteria inside populations. In this work, we overcome this problem by estimating the individual behavior of bacteria from population statistics obtained with flow cytometry. For this objective, a stochastic individual-based modeling framework is defined based on standard assumptions during division and exponential growth. The unknown single-cell parameters required for running the individual-based modeling simulations, such as cell size growth rate, are estimated from the flow cytometry data. Instead of using directly the individual-based model, we make use of a modified Fokker-Plank equation. This only equation simulates the population statistics in function of the unknown single-cell parameters. We test the validity of the approach by modeling the growth and division of Pediococcus acidilactici within the exponential phase. Estimations reveal the statistics of cell growth and division using only data from flow cytometry at a given time. From the relationship between the mother and daughter volumes, we also predict that P. acidilactici divide into two successive parallel planes.

Modeling Alaska boreal forests with a controlled trend surface approach

Science.gov (United States)

Mo Zhou; Jingjing Liang

2012-01-01

An approach of Controlled Trend Surface was proposed to simultaneously take into consideration large-scale spatial trends and nonspatial effects. A geospatial model of the Alaska boreal forest was developed from 446 permanent sample plots, which addressed large-scale spatial trends in recruitment, diameter growth, and mortality. The model was tested on two sets of...

Layered growth model and epitaxial growth structures for SiCAlN alloys

International Nuclear Information System (INIS)

Liu Zhaoqing; Ni Jun; Su Xiaoao; Dai Zhenhong

2009-01-01

Epitaxial growth structures for (SiC) 1-x (AlN) x alloys are studied using a layered growth model. First-principle calculations are used to determine the parameters in the layered growth model. The phase diagrams of epitaxial growth are given. There is a rich variety of the new metastable polytype structures at x=1/6 ,1/5 ,1/4 ,1/3 , and 1/2 in the layered growth phase diagrams. We have also calculated the electronic properties of the short periodical SiCAlN alloys predicted by our layered growth model. The results show that various ordered structures of (SiC) 1-x (AlN) x alloys with the band gaps over a wide range are possible to be synthesized by epitaxial growth.

Stochastic ontogenetic growth model

Science.gov (United States)

West, B. J.; West, D.

2012-02-01

An ontogenetic growth model (OGM) for a thermodynamically closed system is generalized to satisfy both the first and second law of thermodynamics. The hypothesized stochastic ontogenetic growth model (SOGM) is shown to entail the interspecies allometry relation by explicitly averaging the basal metabolic rate and the total body mass over the steady-state probability density for the total body mass (TBM). This is the first derivation of the interspecies metabolic allometric relation from a dynamical model and the asymptotic steady-state distribution of the TBM is fit to data and shown to be inverse power law.

Accounting for age uncertainty in growth modeling, the case study of yellowfin tuna (Thunnus albacares of the Indian Ocean.

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Emmanuelle Dortel

Full Text Available Age estimates, typically determined by counting periodic growth increments in calcified structures of vertebrates, are the basis of population dynamics models used for managing exploited or threatened species. In fisheries research, the use of otolith growth rings as an indicator of fish age has increased considerably in recent decades. However, otolith readings include various sources of uncertainty. Current ageing methods, which converts an average count of rings into age, only provide periodic age estimates in which the range of uncertainty is fully ignored. In this study, we describe a hierarchical model for estimating individual ages from repeated otolith readings. The model was developed within a Bayesian framework to explicitly represent the sources of uncertainty associated with age estimation, to allow for individual variations and to include knowledge on parameters from expertise. The performance of the proposed model was examined through simulations, and then it was coupled to a two-stanza somatic growth model to evaluate the impact of the age estimation method on the age composition of commercial fisheries catches. We illustrate our approach using the sagittal otoliths of yellowfin tuna of the Indian Ocean collected through large-scale mark-recapture experiments. The simulation performance suggested that the ageing error model was able to estimate the ageing biases and provide accurate age estimates, regardless of the age of the fish. Coupled with the growth model, this approach appeared suitable for modeling the growth of Indian Ocean yellowfin and is consistent with findings of previous studies. The simulations showed that the choice of the ageing method can strongly affect growth estimates with subsequent implications for age-structured data used as inputs for population models. Finally, our modeling approach revealed particularly useful to reflect uncertainty around age estimates into the process of growth estimation and it can

An introduction to latent variable growth curve modeling concepts, issues, and application

CERN Document Server

Duncan, Terry E; Strycker, Lisa A

2013-01-01

This book provides a comprehensive introduction to latent variable growth curve modeling (LGM) for analyzing repeated measures. It presents the statistical basis for LGM and its various methodological extensions, including a number of practical examples of its use. It is designed to take advantage of the reader's familiarity with analysis of variance and structural equation modeling (SEM) in introducing LGM techniques. Sample data, syntax, input and output, are provided for EQS, Amos, LISREL, and Mplus on the book's CD. Throughout the book, the authors present a variety of LGM techniques that are useful for many different research designs, and numerous figures provide helpful diagrams of the examples.Updated throughout, the second edition features three new chapters-growth modeling with ordered categorical variables, growth mixture modeling, and pooled interrupted time series LGM approaches. Following a new organization, the book now covers the development of the LGM, followed by chapters on multiple-group is...

Population Modeling Approach to Optimize Crop Harvest Strategy. The Case of Field Tomato.

Science.gov (United States)

Tran, Dinh T; Hertog, Maarten L A T M; Tran, Thi L H; Quyen, Nguyen T; Van de Poel, Bram; Mata, Clara I; Nicolaï, Bart M

2017-01-01

In this study, the aim is to develop a population model based approach to optimize fruit harvesting strategies with regard to fruit quality and its derived economic value. This approach was applied to the case of tomato fruit harvesting under Vietnamese conditions. Fruit growth and development of tomato (cv. "Savior") was monitored in terms of fruit size and color during both the Vietnamese winter and summer growing seasons. A kinetic tomato fruit growth model was applied to quantify biological fruit-to-fruit variation in terms of their physiological maturation. This model was successfully calibrated. Finally, the model was extended to translate the fruit-to-fruit variation at harvest into the economic value of the harvested crop. It can be concluded that a model based approach to the optimization of harvest date and harvest frequency with regard to economic value of the crop as such is feasible. This approach allows growers to optimize their harvesting strategy by harvesting the crop at more uniform maturity stages meeting the stringent retail demands for homogeneous high quality product. The total farm profit would still depend on the impact a change in harvesting strategy might have on related expenditures. This model based harvest optimisation approach can be easily transferred to other fruit and vegetable crops improving homogeneity of the postharvest product streams.

Modeling and control of greenhouse crop growth

CERN Document Server

Rodríguez, Francisco; Guzmán, José Luis; Ramírez-Arias, Armando

2015-01-01

A discussion of challenges related to the modeling and control of greenhouse crop growth, this book presents state-of-the-art answers to those challenges. The authors model the subsystems involved in successful greenhouse control using different techniques and show how the models obtained can be exploited for simulation or control design; they suggest ideas for the development of physical and/or black-box models for this purpose. Strategies for the control of climate- and irrigation-related variables are brought forward. The uses of PID control and feedforward compensators, both widely used in commercial tools, are summarized. The benefits of advanced control techniques—event-based, robust, and predictive control, for example—are used to improve on the performance of those basic methods. A hierarchical control architecture is developed governed by a high-level multiobjective optimization approach rather than traditional constrained optimization and artificial intelligence techniques.  Reference trajector...

Using Multiscale Modeling to Study Coupled Flow, Transport, Reaction and Biofilm Growth Processes in Porous Media

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Valocchi, A. J.; Laleian, A.; Werth, C. J.

2017-12-01

Perturbation of natural subsurface systems by fluid inputs may induce geochemical or microbiological reactions that change porosity and permeability, leading to complex coupled feedbacks between reaction and transport processes. Some examples are precipitation/dissolution processes associated with carbon capture and storage and biofilm growth associated with contaminant transport and remediation. We study biofilm growth due to mixing controlled reaction of multiple substrates. As biofilms grow, pore clogging occurs which alters pore-scale flow paths thus changing the mixing and reaction. These interactions are challenging to quantify using conventional continuum-scale porosity-permeability relations. Pore-scale models can accurately resolve coupled reaction, biofilm growth and transport processes, but modeling at this scale is not feasible for practical applications. There are two approaches to address this challenge. Results from pore-scale models in generic pore structures can be used to develop empirical relations between porosity and continuum-scale parameters, such as permeability and dispersion coefficients. The other approach is to develop a multiscale model of biofilm growth in which non-overlapping regions at pore and continuum spatial scales are coupled by a suitable method that ensures continuity of flux across the interface. Thus, regions of high reactivity where flow alteration occurs are resolved at the pore scale for accuracy while regions of low reactivity are resolved at the continuum scale for efficiency. This approach thus avoids the need for empirical upscaling relations in regions with strong feedbacks between reaction and porosity change. We explore and compare these approaches for several two-dimensional cases.

Integrated healthcare networks' performance: a growth curve modeling approach.

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Wan, Thomas T H; Wang, Bill B L

2003-05-01

This study examines the effects of integration on the performance ratings of the top 100 integrated healthcare networks (IHNs) in the United States. A strategic-contingency theory is used to identify the relationship of IHNs' performance to their structural and operational characteristics and integration strategies. To create a database for the panel study, the top 100 IHNs selected by the SMG Marketing Group in 1998 were followed up in 1999 and 2000. The data were merged with the Dorenfest data on information system integration. A growth curve model was developed and validated by the Mplus statistical program. Factors influencing the top 100 IHNs' performance in 1998 and their subsequent rankings in the consecutive years were analyzed. IHNs' initial performance scores were positively influenced by network size, number of affiliated physicians and profit margin, and were negatively associated with average length of stay and technical efficiency. The continuing high performance, judged by maintaining higher performance scores, tended to be enhanced by the use of more managerial or executive decision-support systems. Future studies should include time-varying operational indicators to serve as predictors of network performance.

Modelling the interaction between flooding events and economic growth

Science.gov (United States)

Grames, Johanna; Fürnkranz-Prskawetz, Alexia; Grass, Dieter; Viglione, Alberto; Blöschl, Günter

2016-04-01

Recently socio-hydrology models have been proposed to analyze the interplay of community risk-coping culture, flooding damage and economic growth. These models descriptively explain the feedbacks between socio-economic development and natural disasters such as floods. Complementary to these descriptive models, we develop a dynamic optimization model, where the inter-temporal decision of an economic agent interacts with the hydrological system. This interdisciplinary approach matches with the goals of Panta Rhei i.e. to understand feedbacks between hydrology and society. It enables new perspectives but also shows limitations of each discipline. Young scientists need mentors from various scientific backgrounds to learn their different research approaches and how to best combine them such that interdisciplinary scientific work is also accepted by different science communities. In our socio-hydrology model we apply a macro-economic decision framework to a long-term flood-scenario. We assume a standard macro-economic growth model where agents derive utility from consumption and output depends on physical capital that can be accumulated through investment. To this framework we add the occurrence of flooding events which will destroy part of the capital. We identify two specific periodic long term solutions and denote them rich and poor economies. Whereas rich economies can afford to invest in flood defense and therefore avoid flood damage and develop high living standards, poor economies prefer consumption instead of investing in flood defense capital and end up facing flood damages every time the water level rises. Nevertheless, they manage to sustain at least a low level of physical capital. We identify optimal investment strategies and compare simulations with more frequent and more intense high water level events.

Robust Growth Determinants

OpenAIRE

Doppelhofer, Gernot; Weeks, Melvyn

2011-01-01

This paper investigates the robustness of determinants of economic growth in the presence of model uncertainty, parameter heterogeneity and outliers. The robust model averaging approach introduced in the paper uses a flexible and parsi- monious mixture modeling that allows for fat-tailed errors compared to the normal benchmark case. Applying robust model averaging to growth determinants, the paper finds that eight out of eighteen variables found to be significantly related to economic growth ...

On a Versatile Stochastic Growth Model

Directory of Open Access Journals (Sweden)

Samiur Arif

2012-06-01

Full Text Available Growth phenomena are ubiquitous and pervasive not only in biology and the medical sciences, but also in economics, marketing and the computer and social sciences. We introduce a three-parameter version of the classic pure-birth process growth model when suitably instantiated, can be used to model growth phenomena in many seemingly unrelated application domains. We point out that the model is computationally attractive since it admits of conceptually simple, closed form solutions for the time-dependent probabilities.

Modeling Forest Biomass and Growth: Coupling Long-Term Inventory and Lidar Data

Science.gov (United States)

Babcock, Chad; Finley, Andrew O.; Cook, Bruce D.; Weiskittel, Andrew; Woodall, Christopher W.

2016-01-01

Combining spatially-explicit long-term forest inventory and remotely sensed information from Light Detection and Ranging (LiDAR) datasets through statistical models can be a powerful tool for predicting and mapping above-ground biomass (AGB) at a range of geographic scales. We present and examine a novel modeling approach to improve prediction of AGB and estimate AGB growth using LiDAR data. The proposed model accommodates temporal misalignment between field measurements and remotely sensed data-a problem pervasive in such settings-by including multiple time-indexed measurements at plot locations to estimate AGB growth. We pursue a Bayesian modeling framework that allows for appropriately complex parameter associations and uncertainty propagation through to prediction. Specifically, we identify a space-varying coefficients model to predict and map AGB and its associated growth simultaneously. The proposed model is assessed using LiDAR data acquired from NASA Goddard's LiDAR, Hyper-spectral & Thermal imager and field inventory data from the Penobscot Experimental Forest in Bradley, Maine. The proposed model outperformed the time-invariant counterpart models in predictive performance as indicated by a substantial reduction in root mean squared error. The proposed model adequately accounts for temporal misalignment through the estimation of forest AGB growth and accommodates residual spatial dependence. Results from this analysis suggest that future AGB models informed using remotely sensed data, such as LiDAR, may be improved by adapting traditional modeling frameworks to account for temporal misalignment and spatial dependence using random effects.

Viscoelastic model of tungsten 'fuzz' growth

International Nuclear Information System (INIS)

Krasheninnikov, S I

2011-01-01

A viscoelastic model of fuzz growth is presented. The model describes the main features of tungsten fuzz observed in experiments. It gives estimates of fuzz growth rate and temperature range close to experimental ones.

Values of Land and Renewable Resources in a Three-Sector Economic Growth Model

Directory of Open Access Journals (Sweden)

Zhang Wei-Bin

2015-04-01

Full Text Available This paper studies dynamic interdependence of capital, land and resource values in a three sector growth model with endogenous wealth and renewable resources. The model is based on the neoclassical growth theory, Ricardian theory and growth theory with renewable resources. The household’s decision is modeled with an alternative approach proposed by Zhang two decades ago. The economic system consists of the households, industrial, agricultural, and resource sectors. The model describes a dynamic interdependence between wealth accumulation, resource change, and division of labor under perfect competition. We simulate the model to demonstrate the existence of a unique stable equilibrium point and plot the motion of the dynamic system. The study conducts comparative dynamic analysis with regard to changes in the propensity to consume resources, the propensity to consume housing, the propensity to consume agricultural goods, the propensity to consume industrial goods, the propensity to save, the population, and the output elasticity of capital of the resource sector.

Mathematical modeling of microbial growth in milk

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Jhony Tiago Teleken

2011-12-01

Full Text Available A mathematical model to predict microbial growth in milk was developed and analyzed. The model consists of a system of two differential equations of first order. The equations are based on physical hypotheses of population growth. The model was applied to five different sets of data of microbial growth in dairy products selected from Combase, which is the most important database in the area with thousands of datasets from around the world, and the results showed a good fit. In addition, the model provides equations for the evaluation of the maximum specific growth rate and the duration of the lag phase which may provide useful information about microbial growth.

Cognitive predictors of children's development in mathematics achievement: A latent growth modeling approach.

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Xenidou-Dervou, Iro; Van Luit, Johannes E H; Kroesbergen, Evelyn H; Friso-van den Bos, Ilona; Jonkman, Lisa M; van der Schoot, Menno; van Lieshout, Ernest C D M

2018-04-24

Research has identified various domain-general and domain-specific cognitive abilities as predictors of children's individual differences in mathematics achievement. However, research into the predictors of children's individual growth rates, namely between-person differences in within-person change in mathematics achievement is scarce. We assessed 334 children's domain-general and mathematics-specific early cognitive abilities and their general mathematics achievement longitudinally across four time-points within the first and second grades of primary school. As expected, a constellation of multiple cognitive abilities contributed to the children's starting level of mathematical success. Specifically, latent growth modeling revealed that WM abilities, IQ, counting skills, nonsymbolic and symbolic approximate arithmetic and comparison skills explained individual differences in the children's initial status on a curriculum-based general mathematics achievement test. Surprisingly, however, only one out of all the assessed cognitive abilities was a unique predictor of the children's individual growth rates in mathematics achievement: their performance in the symbolic approximate addition task. In this task, children were asked to estimate the sum of two large numbers and decide if this estimated sum was smaller or larger compared to a third number. Our findings demonstrate the importance of multiple domain-general and mathematics-specific cognitive skills for identifying children at risk of struggling with mathematics and highlight the significance of early approximate arithmetic skills for the development of one's mathematical success. We argue the need for more research focus on explaining children's individual growth rates in mathematics achievement. © 2018 John Wiley & Sons Ltd.

Estimation of winter wheat canopy nitrogen density at different growth stages based on Multi-LUT approach

Science.gov (United States)

Li, Zhenhai; Li, Na; Li, Zhenhong; Wang, Jianwen; Liu, Chang

2017-10-01

Rapid real-time monitoring of wheat nitrogen (N) status is crucial for precision N management during wheat growth. In this study, Multi Lookup Table (Multi-LUT) approach based on the N-PROSAIL model parameters setting at different growth stages was constructed to estimating canopy N density (CND) in winter wheat. The results showed that the estimated CND was in line with with measured CND, with the determination coefficient (R2) and the corresponding root mean square error (RMSE) values of 0.80 and 1.16 g m-2, respectively. Time-consuming of one sample estimation was only 6 ms under the test machine with CPU configuration of Intel(R) Core(TM) i5-2430 @2.40GHz quad-core. These results confirmed the potential of using Multi-LUT approach for CND retrieval in winter wheat at different growth stages and under variables climatic conditions.

Multi-omics approach to study the growth efficiency and amino acid metabolism in Lactococcus lactis at various specific growth rates

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Arike Liisa

2011-02-01

Full Text Available Abstract Background Lactococcus lactis is recognised as a safe (GRAS microorganism and has hence gained interest in numerous biotechnological approaches. As it is fastidious for several amino acids, optimization of processes which involve this organism requires a thorough understanding of its metabolic regulations during multisubstrate growth. Results Using glucose limited continuous cultivations, specific growth rate dependent metabolism of L. lactis including utilization of amino acids was studied based on extracellular metabolome, global transcriptome and proteome analysis. A new growth medium was designed with reduced amino acid concentrations to increase precision of measurements of consumption of amino acids. Consumption patterns were calculated for all 20 amino acids and measured carbon balance showed good fit of the data at all growth rates studied. It was observed that metabolism of L. lactis became more efficient with rising specific growth rate in the range 0.10 - 0.60 h-1, indicated by 30% increase in biomass yield based on glucose consumption, 50% increase in efficiency of nitrogen use for biomass synthesis, and 40% reduction in energy spilling. The latter was realized by decrease in the overall product formation and higher efficiency of incorporation of amino acids into biomass. L. lactis global transcriptome and proteome profiles showed good correlation supporting the general idea of transcription level control of bacterial metabolism, but the data indicated that substrate transport systems together with lower part of glycolysis in L. lactis were presumably under allosteric control. Conclusions The current study demonstrates advantages of the usage of strictly controlled continuous cultivation methods combined with multi-omics approach for quantitative understanding of amino acid and energy metabolism of L. lactis which is a valuable new knowledge for development of balanced growth media, gene manipulations for desired product

BUILDING NEW BUSINESS MODELS FOR SUSTAINABLE GROWTH AND DEVELOPMENT

OpenAIRE

Taco C. R. van Someren; Shuhua van Someren-Wang

2011-01-01

Considered are issues of methodology and methods, as well as ideology of strategic innovation. Using the tools of this approach is offered as mechanisms to develop and build business models for sustainable socio-economic economic growth and development of different regions. The connection between key problems of sustainable development and management policy of different economic entities is studied. The consultancy company Ynnovate’s experience in addressing these issues in the EU and China i...

A Multilevel Latent Growth Curve Approach to Predicting Student Proficiency

Science.gov (United States)

Choi, Kilchan; Goldschmidt, Pete

2012-01-01

Value-added models and growth-based accountability aim to evaluate school's performance based on student growth in learning. The current focus is on linking the results from value-added models to the ones from growth-based accountability systems including Adequate Yearly Progress decisions mandated by No Child Left Behind. We present a new…

Stochastic process corrosion growth models for pipeline reliability

International Nuclear Information System (INIS)

Bazán, Felipe Alexander Vargas; Beck, André Teófilo

2013-01-01

Highlights: •Novel non-linear stochastic process corrosion growth model is proposed. •Corrosion rate modeled as random Poisson pulses. •Time to corrosion initiation and inherent time-variability properly represented. •Continuous corrosion growth histories obtained. •Model is shown to precisely fit actual corrosion data at two time points. -- Abstract: Linear random variable corrosion models are extensively employed in reliability analysis of pipelines. However, linear models grossly neglect well-known characteristics of the corrosion process. Herein, a non-linear model is proposed, where corrosion rate is represented as a Poisson square wave process. The resulting model represents inherent time-variability of corrosion growth, produces continuous growth and leads to mean growth at less-than-one power of time. Different corrosion models are adjusted to the same set of actual corrosion data for two inspections. The proposed non-linear random process corrosion growth model leads to the best fit to the data, while better representing problem physics

Product unit neural network models for predicting the growth limits of Listeria monocytogenes.

Science.gov (United States)

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.

Modeling growth and dissemination of lymphoma in a co-evolving lymph node: a diffuse-domain approach

Science.gov (United States)

Chuang, Yao-Li; Cristini, Vittorio; Chen, Ying; Li, Xiangrong; Frieboes, Hermann; Lowengrub, John

2013-03-01

While partial differential equation models of tumor growth have successfully described various spatiotemporal phenomena observed for in-vitro tumor spheroid experiments, one challenge towards taking these models to further study in-vivo tumors is that instead of relatively static tissue culture with regular boundary conditions, in-vivo tumors are often confined in organ tissues that co-evolve with the tumor growth. Here we adopt a recently developed diffuse-domain method to account for the co-evolving domain boundaries, adapting our previous in-vitro tumor model for the development of lymphoma encapsulated in a lymph node, which may swell or shrink due to proliferation and dissemination of lymphoma cells and treatment by chemotherapy. We use the model to study the induced spatial heterogeneity, which may arise as an emerging phenomenon in experimental observations and model analysis. Spatial heterogeneity is believed to lead to tumor infiltration patterns and reduce the efficacy of chemotherapy, leaving residuals that cause cancer relapse after the treatment. Understanding the spatiotemporal evolution of in-vivo tumors can be an essential step towards more effective strategies of curing cancer. Supported by NIH-PSOC grant 1U54CA143907-01.

Nonconvex Model of Material Growth: Mathematical Theory

Science.gov (United States)

Ganghoffer, J. F.; Plotnikov, P. I.; Sokolowski, J.

2018-06-01

The model of volumetric material growth is introduced in the framework of finite elasticity. The new results obtained for the model are presented with complete proofs. The state variables include the deformations, temperature and the growth factor matrix function. The existence of global in time solutions for the quasistatic deformations boundary value problem coupled with the energy balance and the evolution of the growth factor is shown. The mathematical results can be applied to a wide class of growth models in mechanics and biology.

Modeling dust growth in protoplanetary disks: The breakthrough case

Science.gov (United States)

Drążkowska, J.; Windmark, F.; Dullemond, C. P.

2014-07-01

Context. Dust coagulation in protoplanetary disks is one of the initial steps toward planet formation. Simple toy models are often not sufficient to cover the complexity of the coagulation process, and a number of numerical approaches are therefore used, among which integration of the Smoluchowski equation and various versions of the Monte Carlo algorithm are the most popular. Aims: Recent progress in understanding the processes involved in dust coagulation have caused a need for benchmarking and comparison of various physical aspects of the coagulation process. In this paper, we directly compare the Smoluchowski and Monte Carlo approaches to show their advantages and disadvantages. Methods: We focus on the mechanism of planetesimal formation via sweep-up growth, which is a new and important aspect of the current planet formation theory. We use realistic test cases that implement a distribution in dust collision velocities. This allows a single collision between two grains to have a wide range of possible outcomes but also requires a very high numerical accuracy. Results: For most coagulation problems, we find a general agreement between the two approaches. However, for the sweep-up growth driven by the "lucky" breakthrough mechanism, the methods exhibit very different resolution dependencies. With too few mass bins, the Smoluchowski algorithm tends to overestimate the growth rate and the probability of breakthrough. The Monte Carlo method is less dependent on the number of particles in the growth timescale aspect but tends to underestimate the breakthrough chance due to its limited dynamic mass range. Conclusions: We find that the Smoluchowski approach, which is generally better for the breakthrough studies, is sensitive to low mass resolutions in the high-mass, low-number tail that is important in this scenario. To study the low number density features, a new modulation function has to be introduced to the interaction probabilities. As the minimum resolution

A Systems Model to Make, Market, and Lead Your Way towards Sustained Growth

Directory of Open Access Journals (Sweden)

Raman Kumar Agrawalla

2017-06-01

Full Text Available Business enterprises exist in a world that is fiercely competitive, tied with huge global uncertainties. They always encounter increasing pressure on prices and margins. Hence, irrespective of their domain of operations and industry, businesses are naturally concerned about their growth, specifically sustained profitable growth, in today’s world. Marketing is a key business function to market and lead a business towards sustained profitable growth but the problem is it lacks a systems perspective in its operations, strategy, and practice. Further, given the confluence and systemic interactions of various economic, digital, and competitive forces; the challenge for different business functions—including marketing—increases tremendously. In this context, it is important for business enterprises to have a systems perspective to find their ways to growth that will be sustained. This calls for a holistic approach to assimilate and steer the business functions in any enterprise. The present conceptual paper focuses on an important business function for sustained growth in a holistic way and presents a systems model, called ‘Value Based Business Approach (VBBA-marketing’, which has potential to guide and steer companies and business enterprises to create a path for their sustained profitable growth.

Statistical prediction of AVB wear growth and initiation in model F steam generator tubes using Monte Carlo method

International Nuclear Information System (INIS)

Lee, Jae Bong; Park, Jae Hak; Kim, Hong Deok; Chung, Han Sub; Kim, Tae Ryong

2005-01-01

The growth of AVB wear in Model F steam generator tubes is predicted using the Monte Carlo Method and statistical approaches. The statistical parameters that represent the characteristics of wear growth and wear initiation are derived from In-Service Inspection (ISI) Non-Destructive Evaluation (NDE) data. Based on the statistical approaches, wear growth model are proposed and applied to predict wear distribution at the End Of Cycle (EOC). Probabilistic distributions of the number of wear flaws and maximum wear depth at EOC are obtained from the analysis. Comparing the predicted EOC wear flaw data with the known EOC data the usefulness of the proposed method is examined and satisfactory results are obtained

Statistical prediction of AVB wear growth and initiation in model F steam generator tubes using Monte Carlo method

Energy Technology Data Exchange (ETDEWEB)

Lee, Jae Bong; Park, Jae Hak [Chungbuk National Univ., Cheongju (Korea, Republic of); Kim, Hong Deok; Chung, Han Sub; Kim, Tae Ryong [Korea Electtric Power Research Institute, Daejeon (Korea, Republic of)

2005-07-01

The growth of AVB wear in Model F steam generator tubes is predicted using the Monte Carlo Method and statistical approaches. The statistical parameters that represent the characteristics of wear growth and wear initiation are derived from In-Service Inspection (ISI) Non-Destructive Evaluation (NDE) data. Based on the statistical approaches, wear growth model are proposed and applied to predict wear distribution at the End Of Cycle (EOC). Probabilistic distributions of the number of wear flaws and maximum wear depth at EOC are obtained from the analysis. Comparing the predicted EOC wear flaw data with the known EOC data the usefulness of the proposed method is examined and satisfactory results are obtained.

Modeling Root Growth, Crop Growth and N Uptake of Winter Wheat Based on SWMS_2D: Model and Validation

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Dejun Yang

Full Text Available ABSTRACT Simulations for root growth, crop growth, and N uptake in agro-hydrological models are of significant concern to researchers. SWMS_2D is one of the most widely used physical hydrologically related models. This model solves equations that govern soil-water movement by the finite element method, and has a public access source code. Incorporating key agricultural components into the SWMS_2D model is of practical importance, especially for modeling some critical cereal crops such as winter wheat. We added root growth, crop growth, and N uptake modules into SWMS_2D. The root growth model had two sub-models, one for root penetration and the other for root length distribution. The crop growth model used was adapted from EU-ROTATE_N, linked to the N uptake model. Soil-water limitation, nitrogen limitation, and temperature effects were all considered in dry-weight modeling. Field experiments for winter wheat in Bouwing, the Netherlands, in 1983-1984 were selected for validation. Good agreements were achieved between simulations and measurements, including soil water content at different depths, normalized root length distribution, dry weight and nitrogen uptake. This indicated that the proposed new modules used in the SWMS_2D model are robust and reliable. In the future, more rigorous validation should be carried out, ideally under 2D situations, and attention should be paid to improve some modules, including the module simulating soil N mineralization.

Testing R&D-Based Endogenous Growth Models

DEFF Research Database (Denmark)

Kruse-Andersen, Peter Kjær

2017-01-01

R&D-based growth models are tested using US data for the period 1953-2014. A general growth model is developed which nests the model varieties of interest. The model implies a cointegrating relationship between multifactor productivity, research intensity, and employment. This relationship...... is estimated using cointegrated VAR models. The results provide evidence against the widely used fully endogenous variety and in favor of the semi-endogenous variety. Forecasts based on the empirical estimates suggest that the slowdown in US productivity growth will continue. Particularly, the annual long...

Bayesian Calibration, Validation and Uncertainty Quantification for Predictive Modelling of Tumour Growth: A Tutorial.

Science.gov (United States)

Collis, Joe; Connor, Anthony J; Paczkowski, Marcin; Kannan, Pavitra; Pitt-Francis, Joe; Byrne, Helen M; Hubbard, Matthew E

2017-04-01

In this work, we present a pedagogical tumour growth example, in which we apply calibration and validation techniques to an uncertain, Gompertzian model of tumour spheroid growth. The key contribution of this article is the discussion and application of these methods (that are not commonly employed in the field of cancer modelling) in the context of a simple model, whose deterministic analogue is widely known within the community. In the course of the example, we calibrate the model against experimental data that are subject to measurement errors, and then validate the resulting uncertain model predictions. We then analyse the sensitivity of the model predictions to the underlying measurement model. Finally, we propose an elementary learning approach for tuning a threshold parameter in the validation procedure in order to maximize predictive accuracy of our validated model.

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

Science.gov (United States)

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.

Kinetic Model of Growth of Arthropoda Populations

Science.gov (United States)

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

2018-05-01

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

Numeric, Agent-based or System dynamics model? Which modeling approach is the best for vast population simulation?

Science.gov (United States)

Cimler, Richard; Tomaskova, Hana; Kuhnova, Jitka; Dolezal, Ondrej; Pscheidl, Pavel; Kuca, Kamil

2018-02-01

Alzheimer's disease is one of the most common mental illnesses. It is posited that more than 25 % of the population is affected by some mental disease during their lifetime. Treatment of each patient draws resources from the economy concerned. Therefore, it is important to quantify the potential economic impact. Agent-based, system dynamics and numerical approaches to dynamic modeling of the population of the European Union and its patients with Alzheimer's disease are presented in this article. Simulations, their characteristics, and the results from different modeling tools are compared. The results of these approaches are compared with EU population growth predictions from the statistical office of the EU by Eurostat. The methodology of a creation of the models is described and all three modeling approaches are compared. The suitability of each modeling approach for the population modeling is discussed. In this case study, all three approaches gave us the results corresponding with the EU population prediction. Moreover, we were able to predict the number of patients with AD and, based on the modeling method, we were also able to monitor different characteristics of the population. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Differential model of macroeconomic growth with endogenic cyclicity

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Mikhail I. Geraskin

2017-09-01

Full Text Available Objective to elaborate a mathematical model of economic growth taking into account the cyclical nature of macroeconomic dynamics with the model parameters based on the Russian economy statistics. Methods economic and mathematical modeling system analysis regression factor analysis econometric time series analysis. Results the article states that under unstable economic growth in Russia forecasting of strategic prospects of the Russian economy is one of the topical directions of scientific studies. Furthermore construction of predictive models should be based on multiple factors taking into account such basic concepts as the neoKeynesian HarrodDomar model Ramsey ndash Cass ndash Koopmans model S. V. Dubovskiyrsquos concept as well as the neoclassical growth model by R. Solow. They served as the basis for developing a multifactor differential economic growth model which is a modification of the neoclassical growth model by R. Solow taking into account the laborsaving and capitalsaving forms of scientifictechnical progress and the Keynesian concept of investment. The model parameters are determined based on the dynamics of actual GDP employment fixed assets and investments in fixed assets for 19652016 in Russia on the basis of official statistics. The generalized model showed the presence of longwave fluctuations that are not detected during the individual periods modeling. The cyclical nature of macroeconomic dynamics with a period of 54 years was found which corresponds to the parameters of long waves by N. D. Kondratiev. Basing on the model the macroeconomic growth forecast was generated which shows that after 2020 the increase of scientifictechnical progress will be negative. Scientific novelty a model is proposed of the scientifictechnical progress indicator showing the growth rate of the capital productivity ratio to the saving rate a differential model of macroeconomic growth is obtained which endogenously takes cyclicity into account

Modelling the growth of Populus species using Ecosystem Demography (ED) model

Science.gov (United States)

Wang, D.; Lebauer, D. S.; Feng, X.; Dietze, M. C.

2010-12-01

Hybrid poplar plantations are an important source being evaluated for biomass production. Effective management of such plantations requires adequate growth and yield models. The Ecosystem Demography model (ED) makes predictions about the large scales of interest in above- and belowground ecosystem structure and the fluxes of carbon and water from a description of the fine-scale physiological processes. In this study, we used a workflow management tool, the Predictive Ecophysiological Carbon flux Analyzer (PECAn), to integrate literature data, field measurement and the ED model to provide predictions of ecosystem functioning. Parameters for the ED ensemble runs were sampled from the posterior distribution of ecophysiological traits of Populus species compiled from the literature using a Bayesian meta-analysis approach. Sensitivity analysis was performed to identify the parameters which contribute the most to the uncertainties of the ED model output. Model emulation techniques were used to update parameter posterior distributions using field-observed data in northern Wisconsin hybrid poplar plantations. Model results were evaluated with 5-year field-observed data in a hybrid poplar plantation at New Franklin, MO. ED was then used to predict the spatial variability of poplar yield in the coterminous United States (United States minus Alaska and Hawaii). Sensitivity analysis showed that root respiration, dark respiration, growth respiration, stomatal slope and specific leaf area contribute the most to the uncertainty, which suggests that our field measurements and data collection should focus on these parameters. The ED model successfully captured the inter-annual and spatial variability of the yield of poplar. Analyses in progress with the ED model focus on evaluating the ecosystem services of short-rotation woody plantations, such as impacts on soil carbon storage, water use, and nutrient retention.

An engineering thermodynamic approach to select the electromagnetic wave effective on cell growth.

Science.gov (United States)

Lucia, Umberto; Grisolia, Giulia; Ponzetto, Antonio; Silvagno, Francesca

2017-09-21

To date, the choice of the characteristics of the extremely low-frequency electromagnetic field beneficial in proliferative disorders is still empirical. In order to make the ELF interaction selective, we applied the thermodynamic and biochemical principles to the analysis of the thermo-chemical output generated by the cell in the environment. The theoretical approach applied an engineering bio-thermodynamic approach recently developed in order to obtain a physical-mathematical model that calculated the frequency of the field able to maximize the mean entropy changes as a function of cellular parameters. The combined biochemical approach envisioned the changes of entropy as a metabolic shift leading to a reduction of cell growth. The proliferation of six human cancer cell lines was evaluated as the output signal able to confirm the correctness of the mathematical model. By considering the cell as a reactive system able to respond to the unbalancing external stimuli, for the first time we could calculate and validate the frequencies of the field specifically effective on distinct cells. Copyright © 2017 Elsevier Ltd. All rights reserved.

Estimating Potential GDP for the Romanian Economy and Assessing the Sustainability of Economic Growth: A Multivariate Filter Approach

Directory of Open Access Journals (Sweden)

Dan Armeanu

2015-03-01

Full Text Available In the current context of economic recovery and rebalancing, the necessity of modelling and estimating the potential output and output gap emerges in order to assess the quality and sustainability of economic growth, the monetary and fiscal policies, as well as the impact of business cycles. Despite the importance of potential GDP and the output gap, there are difficulties in reliably estimating them, as many of the models proposed in the economic literature are calibrated for developed economies and are based on complex macroeconomic relationships and a long history of robust data, while emerging economies exhibit high volatility. The object of this study is to develop a model in order to estimate the potential GDP and output gap and to assess the sustainability of projected growth using a multivariate filter approach. This trend estimation technique is the newest approach proposed by the economic literature and has gained wide acceptance with researchers and practitioners alike, while also being used by the IMF for Romania. The paper will be structured as follows. We first discuss the theoretical background of the model. The second section focuses on an analysis of the Romanian economy for the 1995–2013 time frame, while also providing a forecast for 2014–2017 and an assessment of the sustainability of Romania’s economic growth. The third section sums up the results and concludes.

Testing linear growth rate formulas of non-scale endogenous growth models

NARCIS (Netherlands)

Ziesemer, Thomas

2017-01-01

Endogenous growth theory has produced formulas for steady-state growth rates of income per capita which are linear in the growth rate of the population. Depending on the details of the models, slopes and intercepts are positive, zero or negative. Empirical tests have taken over the assumption of

An Approach of Estimating Individual Growth Curves for Young Thoroughbred Horses Based on Their Birthdays

Science.gov (United States)

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

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

Science.gov (United States)

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.

Elastic Labour Supply and Home Production in a Monetary Growth Model

Directory of Open Access Journals (Sweden)

Wei-Bin Zhang

2011-10-01

Full Text Available This study constructs a monetary gender growth model with capital accumulation and endogenous labour supply. The real aspects of the model are based on the neoclassical growth theory and monetary aspects of the model are based on the cash-in-advance (CIA approach. We show that the dynamics of the economy can be described by 2-dimensional differential equations. We simulate equilibrium and motion of the economy with specified monetary policies, household preference and technology. As the monetary economic system is unstable, the economy may either experience unlimited growth or economic crisis. We also study effects of changes in some parameters on the economic equilibrium. For instance, as the woman raises her propensity to stay at home, the capital intensity is not affected, which results in that the wage rates, the rate and output level per unit of labour input are not affected. Nevertheless, the man increases his work time and the woman reduces her work time, resulting in the fall of the labour supply. The money holing, durable goods used at home and consumption level per household are reduced; also the total wealth, total capital inputs, total durable goods and total output levels are reduced.

Trajectories of adolescent substance use development and the influence of healthy leisure: A growth mixture modeling approach.

Science.gov (United States)

Weybright, Elizabeth H; Caldwell, Linda L; Ram, Nilam; Smith, Edward A; Wegner, Lisa

2016-06-01

Considerable heterogeneity exists in adolescent substance use development. To most effectively prevent use, distinct trajectories of use must be identified as well as differential associations with predictors of use, such as leisure experience. The current study used a person-centered approach to identify distinct substance use trajectories and how leisure is associated with trajectory classes. Data came from a larger efficacy trial of 2.249 South African high school students who reported substance use at any time across 8 waves. Growth mixture modeling was used to identify developmental trajectories of substance use and the influence of healthy leisure. Results identified three increasing and one stable substance use trajectory and subjective healthy leisure served to protect against use. This study is the first of its kind to focus on a sample of South African adolescents and serves to develop a richer understanding of substance use development and the role of healthy leisure. Copyright © 2016 The Foundation for Professionals in Services for Adolescents. Published by Elsevier Ltd. All rights reserved.

Dynamic density functional theory of solid tumor growth: Preliminary models

Directory of Open Access Journals (Sweden)

Arnaud Chauviere

2012-03-01

Full Text Available Cancer is a disease that can be seen as a complex system whose dynamics and growth result from nonlinear processes coupled across wide ranges of spatio-temporal scales. The current mathematical modeling literature addresses issues at various scales but the development of theoretical methodologies capable of bridging gaps across scales needs further study. We present a new theoretical framework based on Dynamic Density Functional Theory (DDFT extended, for the first time, to the dynamics of living tissues by accounting for cell density correlations, different cell types, phenotypes and cell birth/death processes, in order to provide a biophysically consistent description of processes across the scales. We present an application of this approach to tumor growth.

Pre-treatment growth and IGF-I deficiency as main predictors of response to growth hormone therapy in neural models

Directory of Open Access Journals (Sweden)

Urszula Smyczyn´ska

2018-01-01

Full Text Available Mathematical models have been applied in prediction of growth hormone treatment effectiveness in children since the end of 1990s. Usually they were multiple linear regression models; however, there are also examples derived by empirical non-linear methods. Proposed solution consists in application of machine learning technique – artificial neural networks – to analyse this problem. This new methodology, contrary to previous ones, allows detection of both linear and non-linear dependencies without assuming their character a priori. The aims of this work included: development of models predicting separately growth during 1st year of treatment and final height as well as identification of important predictors and in-depth analysis of their influence on treatment’s effectiveness. The models were derived on the basis of clinical data of 272 patients treated for at least 1 year, 133 of whom have already attained final height. Starting from models containing 17 and 20 potential predictors, respectively for 1st year and final height model, we were able to reduce their number to 9 and 10. Basing on the final models, IGF-I concentration and earlier growth were indicated as belonging to most important predictors of response to GH therapy, while results of GH secretion tests were automatically excluded as insignificant. Moreover, majority of the dependencies were observed to be non-linear, thus using neural networks seems to be reasonable approach despite it being more complex than previously applied methods.

Catalyst design for carbon nanotube growth using atomistic modeling

International Nuclear Information System (INIS)

Pint, Cary L; Bozzolo, Guillermo; Hauge, Robert

2008-01-01

The formation and stability of bimetallic catalyst particles, in the framework of carbon nanotube growth, is studied using the Bozzolo-Ferrante-Smith (BFS) method for alloys. Monte Carlo-Metropolis simulations with the BFS method are utilized in order to predict and study equilibrium configurations for nanoscale catalyst particles which are directly relevant to the catalyst state prior to growth of carbon nanotubes. At the forefront of possible catalyst combinations is the popular Fe-Mo bimetallic catalyst, which we have recently studied experimentally. We explain our experimental results, which indicate that the growth observed is dependent on the order of co-catalyst deposition, in the straightforward interpretation of BFS strain and chemical energy contributions toward the formation of Fe-Mo catalyst prior to growth. We find that the competition between the formation of metastable inner Mo cores and clusters of surface-segregated Mo atoms in Fe-Mo catalyst particles influences catalyst formation, and we investigate the role of Mo concentration and catalyst particle size in this process. Finally, we apply the same modeling approach to other prominent bimetallic catalysts and suggest that this technique can be a powerful tool to understand and manipulate catalyst design for highly efficient carbon nanotube growth

The amazing growth of the early church

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Wim A. Dreyer

2012-11-01

Full Text Available The church grew rapidly during the first centuries. The question is: Why? Generations of scholars approached this question from different perspectives and with different methods. Historical research, analysis of early Christian texts and theological reflection were the most common methods used to shed light on the growth of the church. In this contribution five different models of growth were discussed, using the approach of A.M. Schor as a point of departure. These models of church growth were put under the headings of an apostolic mission model, values reproduction model, social reaction model, network model with an institutional model added.

When growth and photosynthesis don't match: implications for carbon balance models

Science.gov (United States)

Medlyn, B.; Mahmud, K.; Duursma, R.; Pfautsch, S.; Campany, C.

2017-12-01

Most models of terrestrial plant growth are based on the principle of carbon balance: that growth can be predicted from net uptake of carbon via photosynthesis. A key criticism leveled at these models by plant physiologists is that there are many circumstances in which plant growth appears to be independent of photosynthesis: for example, during the onset of drought, or with rising atmospheric CO2 concentration. A crucial problem for terrestrial carbon cycle models is to develop better representations of plant carbon balance when there is a mismatch between growth and photosynthesis. Here we present two studies providing insight into this mismatch. In the first, effects of root restriction on plant growth were examined by comparing Eucalyptus tereticornis seedlings growing in containers of varying sizes with freely-rooted seedlings. Root restriction caused a reduction in photosynthesis, but this reduction was insufficient to explain the even larger reduction observed in growth. We applied data assimilation to a simple carbon balance model to quantify the response of carbon balance as a whole in this experiment. We inferred that, in addition to photosynthesis, there are significant effects of root restriction on growth respiration, carbon allocation, and carbohydrate utilization. The second study was carried out at the EucFACE Free-Air CO2 Enrichment experiment. At this experiment, photosynthesis of the overstorey trees is increased with enriched CO2, but there is no significant effect on above-ground productivity. These mature trees have reached their maximum height but are at significant risk of canopy loss through disturbance, and we hypothesized that additional carbon taken up through photosynthesis is preferentially allocated to storage rather than growth. We tested this hypothesis by measuring stemwood non-structural carbohydrates (NSC) during a psyllid outbreak that completely defoliated the canopy in 2015. There was a significant drawdown of NSC during

Quantitative Analysis of Intra Urban Growth Modeling using socio economic agents by combining cellular automata model with agent based model

Science.gov (United States)

Singh, V. K.; Jha, A. K.; Gupta, K.; Srivastav, S. K.

2017-12-01

Recent studies indicate that there is a significant improvement in the urban land use dynamics through modeling at finer spatial resolutions. Geo-computational models such as cellular automata and agent based model have given evident proof regarding the quantification of the urban growth pattern with urban boundary. In recent studies, socio- economic factors such as demography, education rate, household density, parcel price of the current year, distance to road, school, hospital, commercial centers and police station are considered to the major factors influencing the Land Use Land Cover (LULC) pattern of the city. These factors have unidirectional approach to land use pattern which makes it difficult to analyze the spatial aspects of model results both quantitatively and qualitatively. In this study, cellular automata model is combined with generic model known as Agent Based Model to evaluate the impact of socio economic factors on land use pattern. For this purpose, Dehradun an Indian city is selected as a case study. Socio economic factors were collected from field survey, Census of India, Directorate of economic census, Uttarakhand, India. A 3X3 simulating window is used to consider the impact on LULC. Cellular automata model results are examined for the identification of hot spot areas within the urban area and agent based model will be using logistic based regression approach where it will identify the correlation between each factor on LULC and classify the available area into low density, medium density, high density residential or commercial area. In the modeling phase, transition rule, neighborhood effect, cell change factors are used to improve the representation of built-up classes. Significant improvement is observed in the built-up classes from 84 % to 89 %. However after incorporating agent based model with cellular automata model the accuracy improved from 89 % to 94 % in 3 classes of urban i.e. low density, medium density and commercial classes

Growth curve models and statistical diagnostics

CERN Document Server

Pan, Jian-Xin

2002-01-01

Growth-curve models are generalized multivariate analysis-of-variance models. These models are especially useful for investigating growth problems on short times in economics, biology, medical research, and epidemiology. This book systematically introduces the theory of the GCM with particular emphasis on their multivariate statistical diagnostics, which are based mainly on recent developments made by the authors and their collaborators. The authors provide complete proofs of theorems as well as practical data sets and MATLAB code.

An imputation/copula-based stochastic individual tree growth model for mixed species Acadian forests: a case study using the Nova Scotia permanent sample plot network

Directory of Open Access Journals (Sweden)

John A. KershawJr

2017-09-01

Full Text Available Background A novel approach to modelling individual tree growth dynamics is proposed. The approach combines multiple imputation and copula sampling to produce a stochastic individual tree growth and yield projection system. Methods The Nova Scotia, Canada permanent sample plot network is used as a case study to develop and test the modelling approach. Predictions from this model are compared to predictions from the Acadian variant of the Forest Vegetation Simulator, a widely used statistical individual tree growth and yield model. Results Diameter and height growth rates were predicted with error rates consistent with those produced using statistical models. Mortality and ingrowth error rates were higher than those observed for diameter and height, but also were within the bounds produced by traditional approaches for predicting these rates. Ingrowth species composition was very poorly predicted. The model was capable of reproducing a wide range of stand dynamic trajectories and in some cases reproduced trajectories that the statistical model was incapable of reproducing. Conclusions The model has potential to be used as a benchmarking tool for evaluating statistical and process models and may provide a mechanism to separate signal from noise and improve our ability to analyze and learn from large regional datasets that often have underlying flaws in sample design.

Modeling Growth and Yield of Schizolobium amazonicum under Different Spacings

Directory of Open Access Journals (Sweden)

Gilson Fernandes da Silva

2013-01-01

Full Text Available This study aimed to present an approach to model the growth and yield of the species Schizolobium amazonicum (Paricá based on a study of different spacings located in Pará, Brazil. Whole-stand models were employed, and two modeling strategies (Strategies A and B were tested. Moreover, the following three scenarios were evaluated to assess the accuracy of the model in estimating total and commercial volumes at five years of age: complete absence of data (S1; available information about the variables basal area, site index, dominant height, and number of trees at two years of age (S2; and this information available at five years of age (S3. The results indicated that the 3 × 2 spacing has a higher mortality rate than normal, and, in general, greater spacing corresponds to larger diameter and average height and smaller basal area and volume per hectare. In estimating the total and commercial volumes for the three scenarios tested, Strategy B seems to be the most appropriate method to estimate the growth and yield of Paricá plantations in the study region, particularly because Strategy A showed a significant bias in its estimates.

Modelling the effects of lactic acid, sodium benzoate and temperature on the growth of Candida maltosa.

Science.gov (United States)

Valík, Ľ; Ačai, P; Liptáková, D

2017-11-01

The growth of the oxidatively imperfect yeast Candida maltosa Komagata, Nakase et Katsuya was studied experimentally and modelled mathematically in relation to sodium benzoate and lactic acid concentrations at different temperatures. Application of gamma models for the growth rate resulted in determination of cardinal temperature parameters for the growth environment containing lactic acid or sodium benzoate (T min  = 0·7/1·3°C, T max  = 45·3/45·0°C, T opt  = 36·1/37·0°C, μ opt  = 0·88/0·96 h -1 ) as well as the maximal lactic acid concentration for growth (1·9%) or sodium benzoate (1397 mg kg -1 ). Based on the model, the times to reach the density of C. maltosa at the level of 10 5  CFU per ml can be determined at each combination of storage temperature and preservative concentration. The approach used in this study can broaden knowledge of the microbiological quality of fermented milk products during storage as well as the preservation efficacy of mayonnaise dressing for storage and consumption. The strain of Candida maltosaYP1 was originally isolated from air filters that ensured clean air overpressure in yoghurt fermentation tanks. Its growth in contaminated yoghurts manifested outwardly through surface growth, assimilation lactic acid and slight production of carbon dioxide. This was the opportunity to model the effects of lactic acid and sodium benzoate on growth and predict its behaviour in foods. The approach used in this study provides knowledge about microbiological quality development during storage of the fermented milk products as well as some preserved foods for storage and consumption. © 2017 The Society for Applied Microbiology.

Modelling asymmetric growth in crowded plant communities

DEFF Research Database (Denmark)

Damgaard, Christian

2010-01-01

A class of models that may be used to quantify the effect of size-asymmetric competition in crowded plant communities by estimating a community specific degree of size-asymmetric growth for each species in the community is suggested. The model consists of two parts: an individual size......-asymmetric growth part, where growth is assumed to be proportional to a power function of the size of the individual, and a term that reduces the relative growth rate as a decreasing function of the individual plant size and the competitive interactions from other plants in the neighbourhood....

Modeling Population Growth and Extinction

Science.gov (United States)

Gordon, Sheldon P.

2009-01-01

The exponential growth model and the logistic model typically introduced in the mathematics curriculum presume that a population grows exclusively. In reality, species can also die out and more sophisticated models that take the possibility of extinction into account are needed. In this article, two extensions of the logistic model are considered,…

Evaluating predictive models for solar energy growth in the US states and identifying the key drivers

Science.gov (United States)

Chakraborty, Joheen; Banerji, Sugata

2018-03-01

Driven by a desire to control climate change and reduce the dependence on fossil fuels, governments around the world are increasing the adoption of renewable energy sources. However, among the US states, we observe a wide disparity in renewable penetration. In this study, we have identified and cleaned over a dozen datasets representing solar energy penetration in each US state, and the potentially relevant socioeconomic and other factors that may be driving the growth in solar. We have applied a number of predictive modeling approaches - including machine learning and regression - on these datasets over a 17-year period and evaluated the relative performance of the models. Our goals were: (1) identify the most important factors that are driving the growth in solar, (2) choose the most effective predictive modeling technique for solar growth, and (3) develop a model for predicting next year’s solar growth using this year’s data. We obtained very promising results with random forests (about 90% efficacy) and varying degrees of success with support vector machines and regression techniques (linear, polynomial, ridge). We also identified states with solar growth slower than expected and representing a potential for stronger growth in future.

Economic Growth Models Transition

Directory of Open Access Journals (Sweden)

Coralia Angelescu

2006-03-01

Full Text Available The transitional recession in countries of Eastern Europe has been much longer than expected. The legacy and recent policy mistakes have both contributed to the slow progress. As structural reforms and gradual institution building have taken hold, the post-socialist economics have started to recover, with some leading countries building momentum toward faster growth. There is a possibility that in wider context of globalization several of these emerging market economies will be able to catch up with the more advanced industrial economies in a matter of one or two generations. Over the past few years, most candidate countries have made progress in the transition to a competitive market economy, macroeconomic stabilization and structural reform. However their income levels have remained far below those in the Member States. Measured by per capita income in purchasing power standards, there has been a very limited amount of catching up over the past fourteen years. Prior, the distinctions between Solow-Swan model and endogenous growth model. The interdependence between transition and integration are stated in this study. Finally, some measures of macroeconomic policy for sustainable growth are proposed in correlation with real macroeconomic situation of the Romanian economy. Our study would be considered the real convergence for the Romanian economy and the recommendations for the adequate policies to achieve a fast real convergence and sustainable growth.

Economic Growth Models Transition

Directory of Open Access Journals (Sweden)

Coralia Angelescu

2006-01-01

Full Text Available The transitional recession in countries of Eastern Europe has been much longer than expected. The legacy and recent policy mistakes have both contributed to the slow progress. As structural reforms and gradual institution building have taken hold, the post-socialist economics have started to recover, with some leading countries building momentum toward faster growth. There is a possibility that in wider context of globalization several of these emerging market economies will be able to catch up with the more advanced industrial economies in a matter of one or two generations. Over the past few years, most candidate countries have made progress in the transition to a competitive market economy, macroeconomic stabilization and structural reform. However their income levels have remained far below those in the Member States. Measured by per capita income in purchasing power standards, there has been a very limited amount of catching up over the past fourteen years. Prior, the distinctions between Solow-Swan model and endogenous growth model. The interdependence between transition and integration are stated in this study. Finally, some measures of macroeconomic policy for sustainable growth are proposed in correlation with real macroeconomic situation of the Romanian economy. Our study would be considered the real convergence for the Romanian economy and the recommendations for the adequate policies to achieve a fast real convergence and sustainable growth.

Recent advances in modelling creep crack growth

International Nuclear Information System (INIS)

Riedel, H.

1988-08-01

At the time of the previous International Conference on Fracture, the C* integral had long been recognized as a promising load parameter for correlating crack growth rates in creep-ductile materials. The measured crack growth rates as a function of C* and of the temperature could be understood on the basis of micromechanical models. The distinction between C*-controlled and K I -controlled creep crack growth had been clarified and first attempts had been made to describe creep crack growth in the transient regime between elastic behavior and steady-state creep. This paper describes the progress in describing transient crack growth including the effect of primary creep. The effect of crack-tip geometry changes by blunting and by crack growth on the crack-tip fields and on the validity of C* is analyzed by idealizing the growing-crack geometry by a sharp notch and using recent solutions for the notch-tip fields. A few new three-dimensional calculations of C* are cited and important theoretical points are emphasized regarding the three-dimensional fields at crack tips. Finally, creep crack growth is described by continuum-damage models for which similarity solutions can be obtained. Crack growth under small-scale creep conditions turns out to be difficult to understand. Slightly different models yield very different crack growth rates. (orig.) With 4 figs

A VECM approach to detangling growth, exports, imports and FDI knot in selected CEE countries

Directory of Open Access Journals (Sweden)

Saša Žiković

2014-12-01

Full Text Available The authors analyze the relationship between GDP, imports-coverage ratio (NEX, FDI and gross fixed capital formation (GFC in selected CEE countries by using an error correction model. The empirical results confirm a positive long-run influence of the imports coverage ratio, FDI and GFC on GDP growth for all of the countries, except Croatia. In the case of Croatia, there is a significant negative feedback between FDI and GDP growth in the long run and a positive one in the short run. By using B. Horvat’s research on this subject, a logical explanation of this sort of paradoxical behavior is suggested. The second uncommon result is the long-run positive relationship between GDP and the imports-coverage ratio. The obtained result speaks in favor of a conservative approach to running a national economy, where the current account and the imports-coverage ratio are taken into account and the economic growth is achieved through slower but stable, internally driven growth.

Linear spline multilevel models for summarising childhood growth trajectories: A guide to their application using examples from five birth cohorts.

Science.gov (United States)

Howe, Laura D; Tilling, Kate; Matijasevich, Alicia; Petherick, Emily S; Santos, Ana Cristina; Fairley, Lesley; Wright, John; Santos, Iná S; Barros, Aluísio Jd; Martin, Richard M; Kramer, Michael S; Bogdanovich, Natalia; Matush, Lidia; Barros, Henrique; Lawlor, Debbie A

2016-10-01

Childhood growth is of interest in medical research concerned with determinants and consequences of variation from healthy growth and development. Linear spline multilevel modelling is a useful approach for deriving individual summary measures of growth, which overcomes several data issues (co-linearity of repeat measures, the requirement for all individuals to be measured at the same ages and bias due to missing data). Here, we outline the application of this methodology to model individual trajectories of length/height and weight, drawing on examples from five cohorts from different generations and different geographical regions with varying levels of economic development. We describe the unique features of the data within each cohort that have implications for the application of linear spline multilevel models, for example, differences in the density and inter-individual variation in measurement occasions, and multiple sources of measurement with varying measurement error. After providing example Stata syntax and a suggested workflow for the implementation of linear spline multilevel models, we conclude with a discussion of the advantages and disadvantages of the linear spline approach compared with other growth modelling methods such as fractional polynomials, more complex spline functions and other non-linear models. © The Author(s) 2013.

Pollution externalities in a Schumpeterian growth model

OpenAIRE

Koesler, Simon

2010-01-01

This paper extends a standard Schumpeterian growth model to include an environmental dimension. Thereby, it explicitly links the pollution intensity of economic activity to technological progress. In a second step, it investigates the effect of pollution on economic growth under the assumption that pollution intensities are related to technological progress. Several conclusions emerge from the model. In equilibrium, the economy follows a balanced growth path. The effect of pollution on the ec...

Domain growth in weakly disordered magnets: A coupled map lattice approach

International Nuclear Information System (INIS)

Biswal, B.; Puri, S.; Chowdhury, D.

1994-06-01

We developed a novel numerical method of studying domain growth in the Ising-type models. Using this method we investigate the laws of domain growth in random-exchange Ising model. (author). 23 refs, 5 figs

Generalized Models from Beta(p, 2) Densities with Strong Allee Effect: Dynamical Approach

OpenAIRE

Aleixo, Sandra M.; Rocha, J. Leonel

2012-01-01

A dynamical approach to study the behaviour of generalized populational growth models from Beta(p, 2) densities, with strong Allee effect, is presented. The dynamical analysis of the respective unimodal maps is performed using symbolic dynamics techniques. The complexity of the correspondent discrete dynamical systems is measured in terms of topological entropy. Different populational dynamics regimes are obtained when the intrinsic growth rates are modified: extinction, bistability, chaotic ...

Exploring Bioeconomy Growth through the Public Release of the Biomass Scenario Model

Energy Technology Data Exchange (ETDEWEB)

Newes, Emily K [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Biddy, Mary J [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Bush, Brian W [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Inman, Daniel J [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Vimmerstedt, Laura J [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Peterson, Steve [Lexidyne, LLC

2017-08-02

The Biomass Scenario Model (BSM) is an important tool for exploring vibrant future bioeconomy scenarios that leverage domestic resources. Developed by NREL and BETO, this model of the domestic biofuels supply chain has been used to explore success strategies for BETO's activities towards bioeconomy growth. The BSM offers a robust test bed for detailed exploration of effects of BETO activities within the complex context of resource availability; physical, technological, and economic constraints; behavior; and policy. The public release of the model in 2017 will allow broad engagement with the theme of the conference as model users can analyze bioeconomy growth, domestic biomass resource use, and associated effects. The BSM is a carefully validated, state-of-the-art, dynamic model of the biomass to biofuels supply chain. Using a system dynamics simulation modeling approach, the model tracks long-term deployment of biofuels given technology development and investment, considering land availability, the competing oil market, consumer demand, and government policies over time. Sample outputs include biofuels production, feedstock use, capital investment, incentives, and costs of feedstocks and fuels. BSM scenarios reveal technological, economic, and policy challenges, as well as opportunities for dynamic growth of the bioeconomy with strategic public and private investment at key points in the system. The model logic and results have been reviewed extensively, through collaborative analysis, expert reviews and external publications (https://www.zotero.org/groups/bsm_publications/).

Mechanistic model for microbial growth on hydrocarbons

Energy Technology Data Exchange (ETDEWEB)

Mallee, F M; Blanch, H W

1977-12-01

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

Value function in economic growth model

Science.gov (United States)

Bagno, Alexander; Tarasyev, Alexandr A.; Tarasyev, Alexander M.

2017-11-01

Properties of the value function are examined in an infinite horizon optimal control problem with an unlimited integrand index appearing in the quality functional with a discount factor. Optimal control problems of such type describe solutions in models of economic growth. Necessary and sufficient conditions are derived to ensure that the value function satisfies the infinitesimal stability properties. It is proved that value function coincides with the minimax solution of the Hamilton-Jacobi equation. Description of the growth asymptotic behavior for the value function is provided for the logarithmic, power and exponential quality functionals and an example is given to illustrate construction of the value function in economic growth models.

A Model of Controlled Growth

Science.gov (United States)

Bressan, Alberto; Lewicka, Marta

2018-03-01

We consider a free boundary problem for a system of PDEs, modeling the growth of a biological tissue. A morphogen, controlling volume growth, is produced by specific cells and then diffused and absorbed throughout the domain. The geometric shape of the growing tissue is determined by the instantaneous minimization of an elastic deformation energy, subject to a constraint on the volumetric growth. For an initial domain with C}^{2,α boundary, our main result establishes the local existence and uniqueness of a classical solution, up to a rigid motion.

Trajectories and models of individual growth

Directory of Open Access Journals (Sweden)

Arseniy Karkach

2006-11-01

Full Text Available It has long been recognized that the patterns of growth play an important role in the evolution of age trajectories of fertility and mortality (Williams, 1957. Life history studies would benefit from a better understanding of strategies and mechanisms of growth, but still no comparative research on individual growth strategies has been conducted. Growth patterns and methods have been shaped by evolution and a great variety of them are observed. Two distinct patterns - determinate and indeterminate growth - are of a special interest for these studies since they present qualitatively different outcomes of evolution. We attempt to draw together studies covering growth in plant and animal species across a wide range of phyla focusing primarily on the noted qualitative features. We also review mathematical descriptions of growth, namely empirical growth curves and growth models, and discuss the directions of future research.

A nonparametric random coefficient approach for life expectancy growth using a hierarchical mixture likelihood model with application to regional data from North Rhine-Westphalia (Germany).

Science.gov (United States)

Böhning, Dankmar; Karasek, Sarah; Terschüren, Claudia; Annuß, Rolf; Fehr, Rainer

2013-03-09

Life expectancy is of increasing prime interest for a variety of reasons. In many countries, life expectancy is growing linearly, without any indication of reaching a limit. The state of North Rhine-Westphalia (NRW) in Germany with its 54 districts is considered here where the above mentioned growth in life expectancy is occurring as well. However, there is also empirical evidence that life expectancy is not growing linearly at the same level for different regions. To explore this situation further a likelihood-based cluster analysis is suggested and performed. The modelling uses a nonparametric mixture approach for the latent random effect. Maximum likelihood estimates are determined by means of the EM algorithm and the number of components in the mixture model are found on the basis of the Bayesian Information Criterion. Regions are classified into the mixture components (clusters) using the maximum posterior allocation rule. For the data analyzed here, 7 components are found with a spatial concentration of lower life expectancy levels in a centre of NRW, formerly an enormous conglomerate of heavy industry, still the most densely populated area with Gelsenkirchen having the lowest level of life expectancy growth for both genders. The paper offers some explanations for this fact including demographic and socio-economic sources. This case study shows that life expectancy growth is widely linear, but it might occur on different levels.

Modeling error distributions of growth curve models through Bayesian methods.

Science.gov (United States)

Zhang, Zhiyong

2016-06-01

Growth curve models are widely used in social and behavioral sciences. However, typical growth curve models often assume that the errors are normally distributed although non-normal data may be even more common than normal data. In order to avoid possible statistical inference problems in blindly assuming normality, a general Bayesian framework is proposed to flexibly model normal and non-normal data through the explicit specification of the error distributions. A simulation study shows when the distribution of the error is correctly specified, one can avoid the loss in the efficiency of standard error estimates. A real example on the analysis of mathematical ability growth data from the Early Childhood Longitudinal Study, Kindergarten Class of 1998-99 is used to show the application of the proposed methods. Instructions and code on how to conduct growth curve analysis with both normal and non-normal error distributions using the the MCMC procedure of SAS are provided.

Modelling of the acid base properties of two thermophilic bacteria at different growth times

Science.gov (United States)

Heinrich, Hannah T. M.; Bremer, Phil J.; McQuillan, A. James; Daughney, Christopher J.

2008-09-01

Acid-base titrations and electrophoretic mobility measurements were conducted on the thermophilic bacteria Anoxybacillus flavithermus and Geobacillus stearothermophilus at two different growth times corresponding to exponential and stationary/death phase. The data showed significant differences between the two investigated growth times for both bacterial species. In stationary/death phase samples, cells were disrupted and their buffering capacity was lower than that of exponential phase cells. For G. stearothermophilus the electrophoretic mobility profiles changed dramatically. Chemical equilibrium models were developed to simultaneously describe the data from the titrations and the electrophoretic mobility measurements. A simple approach was developed to determine confidence intervals for the overall variance between the model and the experimental data, in order to identify statistically significant changes in model fit and thereby select the simplest model that was able to adequately describe each data set. Exponential phase cells of the investigated thermophiles had a higher total site concentration than the average found for mesophilic bacteria (based on a previously published generalised model for the acid-base behaviour of mesophiles), whereas the opposite was true for cells in stationary/death phase. The results of this study indicate that growth phase is an important parameter that can affect ion binding by bacteria, that growth phase should be considered when developing or employing chemical models for bacteria-bearing systems.

A multilevel approach to examining cephalopod growth using Octopus pallidus as a model.

Science.gov (United States)

Semmens, Jayson; Doubleday, Zoë; Hoyle, Kate; Pecl, Gretta

2011-08-15

Many aspects of octopus growth dynamics are poorly understood, particularly in relation to sub-adult or adult growth, muscle fibre dynamics and repro-somatic investment. The growth of 5 month old Octopus pallidus cultured in the laboratory was investigated under three temperature regimes over a 12 week period: seasonally increasing temperatures (14-18°C); seasonally decreasing temperatures (18-14°C); and a constant temperature mid-way between seasonal peaks (16°C). Differences in somatic growth at the whole-animal level, muscle tissue structure and rate of gonad development were investigated. Continuous exponential growth was observed, both at a group and at an individual level, and there was no detectable effect of temperature on whole-animal growth rate. Juvenile growth rate (from 1 to 156 days) was also monitored prior to the controlled experiment; exponential growth was observed, but at a significantly faster rate than in the older experimental animals, suggesting that O. pallidus exhibit a double-exponential two-phase growth pattern. There was considerable variability in size-at-age even between individuals growing under identical thermal regimes. Animals exposed to seasonally decreasing temperatures exhibited a higher rate of gonad development compared with animals exposed to increasing temperatures; however, this did not coincide with a detectable decline in somatic growth rate or mantle condition. The ongoing production of new mitochondria-poor and mitochondria-rich muscle fibres (hyperplasia) was observed, indicated by a decreased or stable mean muscle fibre diameter concurrent with an increase in whole-body size. Animals from both seasonal temperature regimes demonstrated higher rates of new mitochondria-rich fibre generation relative to those from the constant temperature regime, but this difference was not reflected in a difference in growth rate at the whole-body level. This is the first study to record ongoing hyperplasia in the muscle tissue of an

On Latent Growth Models for Composites and Their Constituents.

Science.gov (United States)

Hancock, Gregory R; Mao, Xiulin; Kher, Hemant

2013-09-01

Over the last decade and a half, latent growth modeling has become an extremely popular and versatile technique for evaluating longitudinal change and its determinants. Most common among the models applied are those for a single measured variable over time. This model has been extended in a variety of ways, most relevant for the current work being the multidomain and the second-order latent growth models. Whereas the former allows for growth function characteristics to be modeled for multiple outcomes simultaneously, with the degree of growth characteristics' relations assessed within the model (e.g., cross-domain slope factor correlations), the latter models growth in latent outcomes, each of which has effect indicators repeated over time. But what if one has an outcome that is believed to be formative relative to its indicator variables rather than latent? In this case, where the outcome is a composite of multiple constituents, modeling change over time is less straightforward. This article provides analytical and applied details for simultaneously modeling growth in composites and their constituent elements, including a real data example using a general computer self-efficacy questionnaire.

Root-shoot growth responses during interspecific competition quantified using allometric modelling.

Science.gov (United States)

Robinson, David; Davidson, Hazel; Trinder, Clare; Brooker, Rob

2010-12-01

Plant competition studies are restricted by the difficulty of quantifying root systems of competitors. Analyses are usually limited to above-ground traits. Here, a new approach to address this issue is reported. Root system weights of competing plants can be estimated from: shoot weights of competitors; combined root weights of competitors; and slopes (scaling exponents, α) and intercepts (allometric coefficients, β) of ln-regressions of root weight on shoot weight of isolated plants. If competition induces no change in root : shoot growth, α and β values of competing and isolated plants will be equal. Measured combined root weight of competitors will equal that estimated allometrically from measured shoot weights of each competing plant. Combined root weights can be partitioned directly among competitors. If, as will be more usual, competition changes relative root and shoot growth, the competitors' combined root weight will not equal that estimated allometrically and cannot be partitioned directly. However, if the isolated-plant α and β values are adjusted until the estimated combined root weight of competitors matches the measured combined root weight, the latter can be partitioned among competitors using their new α and β values. The approach is illustrated using two herbaceous species, Dactylis glomerata and Plantago lanceolata. Allometric modelling revealed a large and continuous increase in the root : shoot ratio by Dactylis, but not Plantago, during competition. This was associated with a superior whole-plant dry weight increase in Dactylis, which was ultimately 2·5-fold greater than that of Plantago. Whole-plant growth dominance of Dactylis over Plantago, as deduced from allometric modelling, occurred 14-24 d earlier than suggested by shoot data alone. Given reasonable assumptions, allometric modelling can analyse competitive interactions in any species mixture, and overcomes a long-standing problem in studies of competition.

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

Science.gov (United States)

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…

Stochastic modeling of thermal fatigue crack growth

CERN Document Server

Radu, Vasile

2015-01-01

The book describes a systematic stochastic modeling approach for assessing thermal-fatigue crack-growth in mixing tees, based on the power spectral density of temperature fluctuation at the inner pipe surface. It shows the development of a frequency-temperature response function in the framework of single-input, single-output (SISO) methodology from random noise/signal theory under sinusoidal input. The frequency response of stress intensity factor (SIF) is obtained by a polynomial fitting procedure of thermal stress profiles at various instants of time. The method, which takes into account the variability of material properties, and has been implemented in a real-world application, estimates the probabilities of failure by considering a limit state function and Monte Carlo analysis, which are based on the proposed stochastic model. Written in a comprehensive and accessible style, this book presents a new and effective method for assessing thermal fatigue crack, and it is intended as a concise and practice-or...

The dynamic relationship between health expenditure and economic growth: is the health-led growth hypothesis valid for Turkey?

Science.gov (United States)

Atilgan, Emre; Kilic, Dilek; Ertugrul, Hasan Murat

2017-06-01

The well-known health-led growth hypothesis claims a positive correlation between health expenditure and economic growth. The aim of this paper is to empirically investigate the health-led growth hypothesis for the Turkish economy. The bound test approach, autoregressive-distributed lag approach (ARDL) and Kalman filter modeling are employed for the 1975-2013 period to examine the co-integration relationship between economic growth and health expenditure. The ARDL model is employed in order to investigate the long-term and short-term static relationship between health expenditure and economic growth. The results show that a 1 % increase in per-capita health expenditure will lead to a 0.434 % increase in per-capita gross domestic product. These findings are also supported by the Kalman filter model's results. Our findings show that the health-led growth hypothesis is supported for Turkey.

POPULATION GROWTH AND PREFERENCE CHANGE IN A GENERALIZED SOLOW GROWTH MODEL WITH GENDER TIME DISTRIBUTIONS

Directory of Open Access Journals (Sweden)

Wei-Bin Zhang

2016-09-01

Full Text Available The study builds a model of dynamic interactions between the birth rate, the mortality rate, the population, wealth accumulation, time distribution between work, leisure and children caring, habit formation and preference change. The production technology and markets are built on the Solow growth model. We base our modeling the population dynamics on the Haavelmo population model and the Barro-Becker fertility choice model. This study takes account of habit formation and preference change. Although it is influenced by the Ramsey growth theory with time preference and habit formation, it uses Zhang’s approach to the household with habit formation and preference change. We synthesize different dynamic forces in a compact framework, using the utility function proposed by Zhang. Analytically, we focus on transitional processes as well as economic equilibrium. As the economic system is given by autonomous nonlinear differential equations, it is not easy to analyze its behavior. We simulate the model to demonstrate the existence of an equilibrium point and plot the motion of the dynamic system. We examine the effects of changes in weights given to the habit stock of children, the wife’s wage rate having negative impact on the propensity to have children, the wife weighing less the habit stock of leisure time, the wife’s habit stock of leisure time having negative impact on the husband’s propensity to use leisure time, the wife’s wage rate having negative impact on the husband’s propensity to use leisure time, woman’s human capital being improved, a rise in the total factor productivity, and the mother spending more time on each child fostering.

Model uncertainty in growth empirics

NARCIS (Netherlands)

Prüfer, P.

2008-01-01

This thesis applies so-called Bayesian model averaging (BMA) to three different economic questions substantially exposed to model uncertainty. Chapter 2 addresses a major issue of modern development economics: the analysis of the determinants of pro-poor growth (PPG), which seeks to combine high

Mechanics of quasi-static crack growth

Energy Technology Data Exchange (ETDEWEB)

Rice, J R

1978-10-01

Results on the mechanics of quasi-static crack growth are reviewed. These include recent studies on the geometry and stability of crack paths in elastic-brittle solids, and on the thermodynamics of Griffith cracking, including environmental effects. The relation of crack growth criteria to non-elastic rheological models is considered and paradoxes with energy balance approaches, based on singular crack models, are discussed for visco-elastic, diffuso-elastic, and elastic-plastic materials. Also, recent approaches to prediction of stable crack growth in ductile, elastic-plastic solids are discussed.

A Discrete Heterogeneous-Group Economic Growth Model with Endogenous Leisure Time

Directory of Open Access Journals (Sweden)

Wei-Bin Zhang

2009-01-01

Full Text Available This paper proposes a one-sector multigroup growth model with endogenous labor supply in discrete time. Proposing an alternative approach to behavior of households, we examine the dynamics of wealth and income distribution in a competitive economy with capital accumulation as the main engine of economic growth. We show how human capital levels, preferences, and labor force of heterogeneous households determine the national economic growth, wealth, and income distribution and time allocation of the groups. By simulation we demonstrate, for instance, that in the three-group economy when the rich group's human capital is improved, all the groups will economically benefit, and the leisure times of all the groups are reduced but when any other group's human capital is improved, the group will economically benefit, the other two groups economically lose, and the leisure times of all the groups are increased.

Modeling Urban Collaborative Growth Dynamics Using a Multiscale Simulation Model for the Wuhan Urban Agglomeration Area, China

Directory of Open Access Journals (Sweden)

Yan Yu

2018-05-01

Full Text Available Urban agglomeration has become the predominant form of urbanization in China. In this process, spatial interaction evidently played a significant role in promoting the collaborative development of these correlated cities. The traditional urban model’s focus on individual cities should be transformed to an urban system model. In this study, a multi-scale simulation model has been proposed to simulate the agglomeration development process of the Wuhan urban agglomeration area by embedding the multi-scale spatial interaction into the transition rule system of cellular automata (CA. A system dynamic model was used to predict the demand for new urban land at an aggregated urban agglomeration area scale. A data field approach was adopted to measuring the interaction of intercity at city scale. Neighborhood interaction was interpreted with a logistic regression method at the land parcel scale. Land use data from 1995, 2005, and 2015 were used to calibrate and evaluate the model. The simulation results show that there has been continuing urban growth in the Wuhan urban agglomeration area from 1995 to 2020. Although extension-sprawl was the predominant pattern of urban spatial expansion, the trend of extensive growth to intensive growth is clear during the entire period. The spatial interaction among these cities has been reinforced, which guided the collaborative development and formed the regional urban system network.

Detecting Growth Shape Misspecifications in Latent Growth Models: An Evaluation of Fit Indexes

Science.gov (United States)

Leite, Walter L.; Stapleton, Laura M.

2011-01-01

In this study, the authors compared the likelihood ratio test and fit indexes for detection of misspecifications of growth shape in latent growth models through a simulation study and a graphical analysis. They found that the likelihood ratio test, MFI, and root mean square error of approximation performed best for detecting model misspecification…

Forest evaporation models: Relationships between stand growth and evaporation

CSIR Research Space (South Africa)

Le Maitre, David C

1997-06-01

Full Text Available The relationships between forest stand structure, growth and evaporation were analysed to determine whether forest evaporation can be estimated from stand growth data. This approach permits rapid assessment of the potential impacts of afforestation...

Modeling urban fire growth

International Nuclear Information System (INIS)

Waterman, T.E.; Takata, A.N.

1983-01-01

The IITRI Urban Fire Spread Model as well as others of similar vintage were constrained by computer size and running costs such that many approximations/generalizations were introduced to reduce program complexity and data storage requirements. Simplifications were introduced both in input data and in fire growth and spread calculations. Modern computational capabilities offer the means to introduce greater detail and to examine its practical significance on urban fire predictions. Selected portions of the model are described as presently configured, and potential modifications are discussed. A single tract model is hypothesized which permits the importance of various model details to be assessed, and, other model applications are identified

Solvability conditions for dendritic growth in the boundary-layer model with capillary anisotropy

Science.gov (United States)

Langer, J. S.; Hong, D. C.

1986-01-01

This paper is concerned primarily with the development of an analytic approach to the theory of steady-state velocity selection in the boundary-layer model of dendritic solidification. The two-dimensional version of this model with a fourfold crystalline anisotropy alpha in the surface tension is considered. By extending a WKB method introduced in an earlier paper, the alpha dependence of the selected growth rate is determined in the limit of small alpha; and this rate is studied for large alphas in the limit in which the dimensionless undercooling approaches unity. Portions of the paper are devoted to a reinterpretation of the mathematical structure of the solvability condition in problems of this kind.

Multiscale Simulation and Modeling of Multilayer Heteroepitactic Growth of C60 on Pentacene.

Science.gov (United States)

Acevedo, Yaset M; Cantrell, Rebecca A; Berard, Philip G; Koch, Donald L; Clancy, Paulette

2016-03-29

We apply multiscale methods to describe the strained growth of multiple layers of C60 on a thin film of pentacene. We study this growth in the presence of a monolayer pentacene step to compare our simulations to recent experimental studies by Breuer and Witte of submonolayer growth in the presence of monolayer steps. The molecular-level details of this organic semiconductor interface have ramifications on the macroscale structural and electronic behavior of this system and allow us to describe several unexplained experimental observations for this system. The growth of a C60 thin film on a pentacene surface is complicated by the differing crystal habits of the two component species, leading to heteroepitactical growth. In order to probe this growth, we use three computational methods that offer different approaches to coarse-graining the system and differing degrees of computational efficiency. We present a new, efficient reaction-diffusion continuum model for 2D systems whose results compare well with mesoscale kinetic Monte Carlo (KMC) results for submonolayer growth. KMC extends our ability to simulate multiple layers but requires a library of predefined rates for event transitions. Coarse-grained molecular dynamics (CGMD) circumvents KMC's need for predefined lattices, allowing defects and grain boundaries to provide a more realistic thin film morphology. For multilayer growth, in this particularly suitable candidate for coarse-graining, CGMD is a preferable approach to KMC. Combining the results from these three methods, we show that the lattice strain induced by heteroepitactical growth promotes 3D growth and the creation of defects in the first monolayer. The CGMD results are consistent with experimental results on the same system by Conrad et al. and by Breuer and Witte in which C60 aggregates change from a 2D structure at low temperature to 3D clusters along the pentacene step edges at higher temperatures.

Neo-logistic model for the growth of bacteria

OpenAIRE

Tashiro, Tohru; Yoshimura, Fujiko

2017-01-01

We propose a neo-logistic model that can describe bacterial growth data precisely. This model is not derived by modifying the logistic model formally, but by incorporating the synthesis of inducible enzymes into the logistic model indirectly. Therefore, the meaning of the parameters of the neo-logistic model becomes physically clear. The neo-logistic model can approximate bacterial growth better than models previously presented, and predict the order of the saturated number of bacteria in the...

Modeling of metal thin film growth: Linking angstrom-scale molecular dynamics results to micron-scale film topographies

Science.gov (United States)

Hansen, U.; Rodgers, S.; Jensen, K. F.

2000-07-01

A general method for modeling ionized physical vapor deposition is presented. As an example, the method is applied to growth of an aluminum film in the presence of an ionized argon flux. Molecular dynamics techniques are used to examine the surface adsorption, reflection, and sputter reactions taking place during ionized physical vapor deposition. We predict their relative probabilities and discuss their dependence on energy and incident angle. Subsequently, we combine the information obtained from molecular dynamics with a line of sight transport model in a two-dimensional feature, incorporating all effects of reemission and resputtering. This provides a complete growth rate model that allows inclusion of energy- and angular-dependent reaction rates. Finally, a level-set approach is used to describe the morphology of the growing film. We thus arrive at a computationally highly efficient and accurate scheme to model the growth of thin films. We demonstrate the capabilities of the model predicting the major differences on Al film topographies between conventional and ionized sputter deposition techniques studying thin film growth under ionized physical vapor deposition conditions with different Ar fluxes.

Repeated Microneedle Stimulation Induces Enhanced Hair Growth in a Murine Model.

Science.gov (United States)

Kim, Yoon Seob; Jeong, Kwan Ho; Kim, Jung Eun; Woo, Young Jun; Kim, Beom Joon; Kang, Hoon

2016-10-01

Microneedle is a method that creates transdermal microchannels across the stratum corneum barrier layer of skin. No previous study showed a therapeutic effect of microneedle itself on hair growth by wounding. The aim of this study is to investigate the effect of repeated microwound formed by microneedle on hair growth and hair growth-related genes in a murine model. A disk microneedle roller was applied to each group of mice five times a week for three weeks. First, to identify the optimal length and cycle, microneedles of lengths of 0.15 mm, 0.25 mm, 0.5 mm, and 1 mm and cycles of 3, 6, 10, and 13 cycles were applied. Second, the effect of hair growth and hair-growth-related genes such as Wnt3a, β-catenin, vascular endothelial growth factor (VEGF), and Wnt10b was observed using optimized microneedle. Outcomes were observed using visual inspection, real-time polymerase chain reaction, and immunohistochemistry. We found that the optimal length and cycle of microneedle treatment on hair growth was 0.25 mm/10 cycles and 0.5 mm/10 cycles. Repeated microneedle stimulation promoted hair growth, and it also induced the enhanced expression of Wnt3a, β-catenin, VEGF, and Wnt10b. Our study provides evidence that microneedle stimulation can induce hair growth via activation of the Wnt/β-catenin pathway and VEGF. Combined with the drug delivery effect, we believe that microneedle stimulation could lead to new approaches for alopecia.

Energy consumption and economic growth nexus in Tanzania: An ARDL bounds testing approach

International Nuclear Information System (INIS)

Odhiambo, Nicholas M.

2009-01-01

In this paper, we examine the intertemporal causal relationship between energy consumption and economic growth in Tanzania during the period of 1971-2006. Unlike the majority of the previous studies, we employ the newly developed autoregressive distributed lag (ARDL)-bounds testing approach by Pesaran et al. [2001. Bounds testing approaches to the analysis of level relationships. Journal of Applied Econometrics 16, 289-326] to examine this linkage. We also use two proxies of energy consumption, namely total energy consumption per capita and electricity consumption per capita. The results of the bounds test show that there is a stable long-run relationship between each of the proxies of energy consumption and economic growth. The results of the causality test, on the other hand, show that there is a unidirectional causal flow from total energy consumption to economic growth and a prima-facie causal flow from electricity consumption to economic growth. Overall, the study finds that energy consumption spurs economic growth in Tanzania

Energy consumption and economic growth nexus in Tanzania. An ARDL bounds testing approach

Energy Technology Data Exchange (ETDEWEB)

Odhiambo, Nicholas M. [Economics Department, University of South Africa (UNISA), P.O. Box 392, UNISA, 0003, Pretoria (South Africa)

2009-02-15

In this paper, we examine the intertemporal causal relationship between energy consumption and economic growth in Tanzania during the period of 1971-2006. Unlike the majority of the previous studies, we employ the newly developed autoregressive distributed lag (ARDL)-bounds testing approach by Pesaran et al. [2001. Bounds testing approaches to the analysis of level relationships. Journal of Applied Econometrics 16, 289-326] to examine this linkage. We also use two proxies of energy consumption, namely total energy consumption per capita and electricity consumption per capita. The results of the bounds test show that there is a stable long-run relationship between each of the proxies of energy consumption and economic growth. The results of the causality test, on the other hand, show that there is a unidirectional causal flow from total energy consumption to economic growth and a prima-facie causal flow from electricity consumption to economic growth. Overall, the study finds that energy consumption spurs economic growth in Tanzania. (author)

Energy consumption and economic growth nexus in Tanzania: An ARDL bounds testing approach

Energy Technology Data Exchange (ETDEWEB)

Odhiambo, Nicholas M. [Economics Department, University of South Africa (UNISA), P.O. Box 392, UNISA, 0003, Pretoria (South Africa)], E-mail: nmbaya99@yahoo.com

2009-02-15

In this paper, we examine the intertemporal causal relationship between energy consumption and economic growth in Tanzania during the period of 1971-2006. Unlike the majority of the previous studies, we employ the newly developed autoregressive distributed lag (ARDL)-bounds testing approach by Pesaran et al. [2001. Bounds testing approaches to the analysis of level relationships. Journal of Applied Econometrics 16, 289-326] to examine this linkage. We also use two proxies of energy consumption, namely total energy consumption per capita and electricity consumption per capita. The results of the bounds test show that there is a stable long-run relationship between each of the proxies of energy consumption and economic growth. The results of the causality test, on the other hand, show that there is a unidirectional causal flow from total energy consumption to economic growth and a prima-facie causal flow from electricity consumption to economic growth. Overall, the study finds that energy consumption spurs economic growth in Tanzania.

Non-linear Growth Models in Mplus and SAS

Science.gov (United States)

Grimm, Kevin J.; Ram, Nilam

2013-01-01

Non-linear growth curves or growth curves that follow a specified non-linear function in time enable researchers to model complex developmental patterns with parameters that are easily interpretable. In this paper we describe how a variety of sigmoid curves can be fit using the Mplus structural modeling program and the non-linear mixed-effects modeling procedure NLMIXED in SAS. Using longitudinal achievement data collected as part of a study examining the effects of preschool instruction on academic gain we illustrate the procedures for fitting growth models of logistic, Gompertz, and Richards functions. Brief notes regarding the practical benefits, limitations, and choices faced in the fitting and estimation of such models are included. PMID:23882134

Modeling of Particle Engulfment during the Growth of Crystalline Silicon for Solar Cells

Science.gov (United States)

Tao, Yutao

A major challenge for the growth of multi-crystalline silicon is the formation of carbide and nitride precipitates in the melt that are engulfed by the solidification front to form inclusions. These lower cell efficiency and can lead to wafer breakage and sawing defects. Minimizing the number of these engulfed particles will promote lower cost and higher quality silicon and will advance progress in commercial solar cell production. To better understand the physical mechanisms responsible for such inclusions during crystal growth, we have developed finite-element, moving-boundary analyses to assess particle dynamics during engulfment via solidification fronts. Two-dimensional, steady-state and dynamic models are developed using the Galerkin finite element method and elliptic mesh generation techniques in an arbitrary Eulerian-Lagrangian (ALE) implementation. This numerical approach allows for an accurate representation of forces and dynamics previously inaccessible by approaches using analytical approximations. We reinterpret the significance of premelting via the definition of an unambiguous critical velocity for engulfment from steady-state analysis and bifurcation theory. Parametric studies are then performed to uncover the dependence of critical growth velocity upon some important physical properties. We also explore the complicated transient behaviors due to oscillating crystal growth conditions as well as the nonlinear nature related with temperature gradients and solute effects in the system. When compared with results for the SiC-Si system measured during ParSiWal experiments conducted by our collaborators, our model predicts a more realistic scaling of critical velocity with particle size than that predicted by prior theories. However, the engulfment growth velocity observed in the subsequent experiment onboard the TEXUS sounding rocket mission turned out to be unexpectedly higher. To explain this model discrepancy, a macroscopic model is developed in order

Modelling diameter growth, mortality and recruitment of trees in ...

African Journals Online (AJOL)

Modelling diameter growth, mortality and recruitment of trees in miombo woodlands of Tanzania. ... Individual tree diameter growth and mortality models, and area-based recruitment models were developed. ... AJOL African Journals Online.

Forest growth modeling in the Southern Region, National Forest System

International Nuclear Information System (INIS)

Belcher, D.M.

1988-01-01

This paper discusses an attempt to combine individual tree growth models and stand level growth models currently available for the Region into one computer program. Operation of the program is explained and growth models are included

Interleukin-12 Inhibits Tumor Growth in a Novel Angiogenesis Canine Hemangiosarcoma Xenograft Model

Directory of Open Access Journals (Sweden)

Nasim Akhtar

2004-03-01

Full Text Available We established a canine hemangiosarcoma cell line derived from malignant endothelial cells comprising a spontaneous tumor in a dog to provide a renewable source of endothelial cells for studies of angiogenesis in malignancy. Pieces of the hemangiosarcoma biopsy were engrafted subcutaneously in a bg/nu/XID mouse allowing the tumor cells to expand in vivo. A cell line, SB-HSA, was derived from the xenograft. SB-HSA cells expressed vascular endothelial growth factor (VEGF receptors 1 and 2, CD31, CD146, and αvβ3 integrin, and produced several growth factors and cytokines, including VEGF, basic fibroblast growth factor, and interleukin (IL-8 that are stimulatory to endothelial cell growth. These results indicated that the cells recapitulated features of mitotically activated endothelia. In vivo, SB-HSA cells stimulated robust angiogenic responses in mice and formed tumor masses composed of aberrant vascular channels in immunocompromised mice providing novel opportunities for investigating the effectiveness of antiangiogenic agents. Using this model, we determined that IL-12, a cytokine with both immunostimulatory and antiangiogenic effects, suppressed angiogenesis induced by, and tumor growth of, SB-HSA cells. The endothelial cell model we have described offers unique opportunities to pursue further investigations with IL-12, as well as other antiangiogenic approaches in cancer therapy.

Estimating the Relationship between Economic Growth and Health Expenditures in ECO Countries Using Panel Cointegration Approach

Directory of Open Access Journals (Sweden)

Nahid Hatam

2016-03-01

Full Text Available Increasing knowledge of people about health leads to raising the share of health expenditures in government budget continuously; although governors do not like this rise because of budget limitations. This study aimed to find the association between health expenditures and economic growth in ECO countries. We added health capital in Solow model and used the panel cointegration approach to show the importance of health expenditures in economic growth. For estimating the model, first we used Pesaran cross-sectional dependency test, after that we used Pesaran CADF unit root test, and then we used Westerlund panel cointegration test to show if there is a long-term association between variables or not. After that, we used chaw test, Breusch-Pagan test and Hausman test to find the form of the model. Finally, we used OLS estimator for panel data. Findings showed that there is a positive, strong association between health expenditures and economic growth in ECO countries. If governments increase investing in health, the total production of the country will be increased, so health expenditures are considered as an investing good. The effects of health expenditures in developing countries must be higher than those in developed countries. Such studies can help policy makers to make long-term decisions.

Estimating the Relationship between Economic Growth and Health Expenditures in ECO Countries Using Panel Cointegration Approach.

Science.gov (United States)

Hatam, Nahid; Tourani, Sogand; Homaie Rad, Enayatollah; Bastani, Peivand

2016-02-01

Increasing knowledge of people about health leads to raising the share of health expenditures in government budget continuously; although governors do not like this rise because of budget limitations. This study aimed to find the association between health expenditures and economic growth in ECO countries. We added health capital in Solow model and used the panel cointegration approach to show the importance of health expenditures in economic growth. For estimating the model, first we used Pesaran cross-sectional dependency test, after that we used Pesaran CADF unit root test, and then we used Westerlund panel cointegration test to show if there is a long-term association between variables or not. After that, we used chaw test, Breusch-Pagan test and Hausman test to find the form of the model. Finally, we used OLS estimator for panel data. Findings showed that there is a positive, strong association between health expenditures and economic growth in ECO countries. If governments increase investing in health, the total production of the country will be increased, so health expenditures are considered as an investing good. The effects of health expenditures in developing countries must be higher than those in developed countries. Such studies can help policy makers to make long-term decisions.

Bounds test approach to cointegration and causality between nuclear energy consumption and economic growth in India

International Nuclear Information System (INIS)

Wolde-Rufael, Yemane

2010-01-01

This paper attempts to examine the dynamic relationship between economic growth, nuclear energy consumption, labor and capital for India for the period 1969-2006. Applying the bounds test approach to cointegration developed by we find that there was a short- and a long-run relationship between nuclear energy consumption and economic growth. Using four long-run estimators we also found that nuclear energy consumption has a positive and a statistically significant impact on India's economic growth. Further, applying the approach to Granger causality and the variance decomposition approach developed by , we found a positive and a significant uni-directional causality running from nuclear energy consumption to economic growth without feedback. This implies that economic growth in India is dependent on nuclear energy consumption where a decrease in nuclear energy consumption may lead to a decrease in real income. For a fast growing energy-dependent economy this may have far-reaching implications for economic growth. India's economic growth can be frustrated if energy conservation measures are undertaken without due regard to the negative impact they have on economic growth.

On valuing patches: estimating contributions to metapopulation growth with reverse-time capture-recapture modeling

Science.gov (United States)

Jamie S. Sanderlin; Peter M. Waser; James E. Hines; James D. Nichols

2012-01-01

Metapopulation ecology has historically been rich in theory, yet analytical approaches for inferring demographic relationships among local populations have been few. We show how reverse-time multi-state capture­recapture models can be used to estimate the importance of local recruitment and interpopulation dispersal to metapopulation growth. We use 'contribution...

Determining of migraine prognosis using latent growth mixture models.

Science.gov (United States)

Tasdelen, Bahar; Ozge, Aynur; Kaleagasi, Hakan; Erdogan, Semra; Mengi, Tufan

2011-04-01

This paper presents a retrospective study to classify patients into subtypes of the treatment according to baseline and longitudinally observed values considering heterogenity in migraine prognosis. In the classical prospective clinical studies, participants are classified with respect to baseline status and followed within a certain time period. However, latent growth mixture model is the most suitable method, which considers the population heterogenity and is not affected drop-outs if they are missing at random. Hence, we planned this comprehensive study to identify prognostic factors in migraine. The study data have been based on a 10-year computer-based follow-up data of Mersin University Headache Outpatient Department. The developmental trajectories within subgroups were described for the severity, frequency, and duration of headache separately and the probabilities of each subgroup were estimated by using latent growth mixture models. SAS PROC TRAJ procedures, semiparametric and group-based mixture modeling approach, were applied to define the developmental trajectories. While the three-group model for the severity (mild, moderate, severe) and frequency (low, medium, high) of headache appeared to be appropriate, the four-group model for the duration (low, medium, high, extremely high) was more suitable. The severity of headache increased in the patients with nausea, vomiting, photophobia and phonophobia. The frequency of headache was especially related with increasing age and unilateral pain. Nausea and photophobia were also related with headache duration. Nausea, vomiting and photophobia were the most significant factors to identify developmental trajectories. The remission time was not the same for the severity, frequency, and duration of headache.

Modeling the growth dynamics of multiple Escherichia coli strains in the pig intestine following intramuscular ampicillin treatment

DEFF Research Database (Denmark)

Ahmad, Amais; Zachariasen, Camilla; Christiansen, Lasse Engbo

2016-01-01

using a mathematical model to simulate the competitive growth of E. coli strains in a pig intestine under specified plasma concentration profiles of ampicillin. Results : In vitro growth results demonstrated that the resistant strains did not carry a fitness cost for their resistance, and that the most...... susceptible strains were more affected by increasing concentrations of antibiotics that the rest of the strains. The modeling revealed that short treatment duration resulted in lower levels of resistance and that dosing frequency did not substantially influence the growth of resistant strains. Resistance...... with ampicillin resistance in E. coli. Besides dosing factors, epidemiological factors (such as number of competing strains and bacterial excretion) influenced resistance development and need to be considered further in relation to optimal treatment strategies. The modeling approach used in the study is generic...

Gaussian radial growth

DEFF Research Database (Denmark)

Jónsdóttir, Kristjana Ýr; Jensen, Eva B. Vedel

The growth of planar and spatial objects is often modelled using one-dimensional size parameters, e.g. volume, area or average radius. We take a more detailed approach and model how the boundary of a growing object expands in time. We mainly consider star-shaped planar objects. The model can...... be regarded as a dynamic deformable template model. The limiting shape of the object may be circular but this is only one possibility among a range of limiting shapes. An application to tumour growth is presented. Two extensions of the model, involving time series and Lévy bases, respectively, are briefly...

Growth of cortical neuronal network in vitro: Modeling and analysis

International Nuclear Information System (INIS)

Lai, P.-Y.; Jia, L. C.; Chan, C. K.

2006-01-01

We present a detailed analysis and theoretical growth models to account for recent experimental data on the growth of cortical neuronal networks in vitro [Phys. Rev. Lett. 93, 088101 (2004)]. The experimentally observed synchronized firing frequency of a well-connected neuronal network is shown to be proportional to the mean network connectivity. The growth of the network is consistent with the model of an early enhanced growth of connection, but followed by a retarded growth once the synchronized cluster is formed. Microscopic models with dominant excluded volume interactions are consistent with the observed exponential decay of the mean connection probability as a function of the mean network connectivity. The biological implications of the growth model are also discussed

Seasonal patterns in growth, blood consumption, and effects on hosts by parasitic-phase sea lampreys in the Great Lakes: an individual-based model approach

Science.gov (United States)

Madenjian, Charles P.; Cochran, Philip A.; Bergstedt, Roger A.

2003-01-01

An individual-based model (IBM) was developed for sea lamprey (Petromyzon marinus) populations in the Laurentian Great Lakes. The IBM was then calibrated to observed growth, by season, for sea lampreys in northern Lake Huron under two different water temperature regimes: a regime experienced by Seneca-strain lake trout (Salvelinus namaycush) and a regime experienced by Marquettestrain lake trout. Modeling results indicated that seasonal blood consumption under the Seneca regime was very similar to that under the Marquette regime. Simulated mortality of lake trout directly due to blood removal by sea lampreys occurred at nearly twice the rate during August and September under the Marquette regime than under the Seneca regime. However, cumulative sea lamprey-induced mortality on lake trout over the entire duration of the sea lamprey's parasitic phase was only 7% higher for the Marquette regime compared with the Seneca regime. Thus, these modeling results indicated that the strain composition of the host (lake trout) population was not important in determining total number of lake trout deaths or total blood consumption attributable to the sea lamprey population, given the sea lamprey growth pattern. Regardless of water temperature regime, both blood consumption rate by sea lampreys and rate of sea lamprey-induced mortality on lake trout peaked in late October. Elevated blood consumption in late October appeared to be unrelated to changes in water temperature. The IBM approach should prove useful in optimizing control of sea lampreys in the Laurentian Great Lakes.

Balanced growth path solutions of a Boltzmann mean field game model for knowledge growth

KAUST Repository

Burger, Martin

2016-11-18

In this paper we study balanced growth path solutions of a Boltzmann mean field game model proposed by Lucas and Moll [15] to model knowledge growth in an economy. Agents can either increase their knowledge level by exchanging ideas in learning events or by producing goods with the knowledge they already have. The existence of balanced growth path solutions implies exponential growth of the overall production in time. We prove existence of balanced growth path solutions if the initial distribution of individuals with respect to their knowledge level satisfies a Pareto-tail condition. Furthermore we give first insights into the existence of such solutions if in addition to production and knowledge exchange the knowledge level evolves by geometric Brownian motion.

Modeling the effects of ozone on soybean growth and yield.

Science.gov (United States)

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.

A Comparison of Jungian, Person-Centered, and Gestalt Approaches to Personal Growth Groups.

Science.gov (United States)

Day, Bryon; Matthes, William

1992-01-01

Compares Jungian approach to personal growth groups to Person-centered and Gestalt approaches. Notes similarities, though Jungian approach adds dimension of "cognitive map" not found in other two. Notes that cognitive map uses constructs from Jung's theory of individuation process, hypothesizing that integration of these constructs into…

The need for data science in epidemic modelling. Comment on: "Mathematical models to characterize early epidemic growth: A review" by Gerardo Chowell et al.

Science.gov (United States)

Danon, Leon; Brooks-Pollock, Ellen

2016-09-01

In their review, Chowell et al. consider the ability of mathematical models to predict early epidemic growth [1]. In particular, they question the central prediction of classical differential equation models that the number of cases grows exponentially during the early stages of an epidemic. Using examples including HIV and Ebola, they argue that classical models fail to capture key qualitative features of early growth and describe a selection of models that do capture non-exponential epidemic growth. An implication of this failure is that predictions may be inaccurate and unusable, highlighting the need for care when embarking upon modelling using classical methodology. There remains a lack of understanding of the mechanisms driving many observed epidemic patterns; we argue that data science should form a fundamental component of epidemic modelling, providing a rigorous methodology for data-driven approaches, rather than trying to enforce established frameworks. The need for refinement of classical models provides a strong argument for the use of data science, to identify qualitative characteristics and pinpoint the mechanisms responsible for the observed epidemic patterns.

An approach to multiscale modelling with graph grammars.

Science.gov (United States)

Ong, Yongzhi; Streit, Katarína; Henke, Michael; Kurth, Winfried

2014-09-01

Functional-structural plant models (FSPMs) simulate biological processes at different spatial scales. Methods exist for multiscale data representation and modification, but the advantages of using multiple scales in the dynamic aspects of FSPMs remain unclear. Results from multiscale models in various other areas of science that share fundamental modelling issues with FSPMs suggest that potential advantages do exist, and this study therefore aims to introduce an approach to multiscale modelling in FSPMs. A three-part graph data structure and grammar is revisited, and presented with a conceptual framework for multiscale modelling. The framework is used for identifying roles, categorizing and describing scale-to-scale interactions, thus allowing alternative approaches to model development as opposed to correlation-based modelling at a single scale. Reverse information flow (from macro- to micro-scale) is catered for in the framework. The methods are implemented within the programming language XL. Three example models are implemented using the proposed multiscale graph model and framework. The first illustrates the fundamental usage of the graph data structure and grammar, the second uses probabilistic modelling for organs at the fine scale in order to derive crown growth, and the third combines multiscale plant topology with ozone trends and metabolic network simulations in order to model juvenile beech stands under exposure to a toxic trace gas. The graph data structure supports data representation and grammar operations at multiple scales. The results demonstrate that multiscale modelling is a viable method in FSPM and an alternative to correlation-based modelling. Advantages and disadvantages of multiscale modelling are illustrated by comparisons with single-scale implementations, leading to motivations for further research in sensitivity analysis and run-time efficiency for these models.

A stochastic model of solid state thin film deposition: Application to chalcopyrite growth

Directory of Open Access Journals (Sweden)

Robert J. Lovelett

2016-04-01

Full Text Available Developing high fidelity quantitative models of solid state reaction systems can be challenging, especially in deposition systems where, in addition to the multiple competing processes occurring simultaneously, the solid interacts with its atmosphere. In this work, we develop a model for the growth of a thin solid film where species from the atmosphere adsorb, diffuse, and react with the film. The model is mesoscale and describes an entire film with thickness on the order of microns. Because it is stochastic, the model allows us to examine inhomogeneities and agglomerations that would be impossible to characterize with deterministic methods. We demonstrate the modeling approach with the example of chalcopyrite Cu(InGa(SeS2 thin film growth via precursor reaction, which is a common industrial method for fabricating thin film photovoltaic modules. The model is used to understand how and why through-film variation in the composition of Cu(InGa(SeS2 thin films arises and persists. We believe that the model will be valuable as an effective quantitative description of many other materials systems used in semiconductors, energy storage, and other fast-growing industries.

Modelling growth-competition relationships in trembling aspen and white spruce mixed boreal forests of Western Canada.

Science.gov (United States)

Huang, Jian-Guo; Stadt, Kenneth J; Dawson, Andria; Comeau, Philip G

2013-01-01

We examined the effect of competition on stem growth of Picea glauca and Populus tremuloides in boreal mixedwood stands during the stem exclusion stage. We combined traditional approaches of collecting competition data with dendrochronology to provide retrospective measurements of stem diameter growth. Several competition indices including stand basal area (BA), the sum of stem diameter at breast height (SDBH), and density (N) for the broadleaf and coniferous species, as well as similar indices considering only trees with diameters greater than each subject (BAGR, SDBHGR, and NGR), were evaluated. We used a nonlinear mixed model to characterize the basal area increment over the past 5, 10, 15, 20, 25, 30, and 35 years as a function of growth of nearby dominant trees, the size of the subject trees, deciduous and coniferous competition indices, and ecoregions. SDBHGR and BAGR were better predictors for spruce, and SDBHGR and NGR were better for aspen, respectively, than other indices. Results showed strongest correlations with long-term stem growth, as the best models integrated growth for 10-25 years for aspen and ≥ 25 for spruce. Our model demonstrated a remarkable capability (adjusted R(2)>0.67) to represent this complex variation in growth as a function of site, size and competition.

Modelling growth-competition relationships in trembling aspen and white spruce mixed boreal forests of Western Canada.

Directory of Open Access Journals (Sweden)

Jian-Guo Huang

Full Text Available We examined the effect of competition on stem growth of Picea glauca and Populus tremuloides in boreal mixedwood stands during the stem exclusion stage. We combined traditional approaches of collecting competition data with dendrochronology to provide retrospective measurements of stem diameter growth. Several competition indices including stand basal area (BA, the sum of stem diameter at breast height (SDBH, and density (N for the broadleaf and coniferous species, as well as similar indices considering only trees with diameters greater than each subject (BAGR, SDBHGR, and NGR, were evaluated. We used a nonlinear mixed model to characterize the basal area increment over the past 5, 10, 15, 20, 25, 30, and 35 years as a function of growth of nearby dominant trees, the size of the subject trees, deciduous and coniferous competition indices, and ecoregions. SDBHGR and BAGR were better predictors for spruce, and SDBHGR and NGR were better for aspen, respectively, than other indices. Results showed strongest correlations with long-term stem growth, as the best models integrated growth for 10-25 years for aspen and ≥ 25 for spruce. Our model demonstrated a remarkable capability (adjusted R(2>0.67 to represent this complex variation in growth as a function of site, size and competition.

The Spatio-Temporal Modeling of Urban Growth Using Remote Sensing and Intelligent Algorithms, Case of Mahabad, Iran

Directory of Open Access Journals (Sweden)

Alì Soltani

2013-06-01

Full Text Available The simulation of urban growth can be considered as a useful way for analyzing the complex process of urban physical evolution. The aim of this study is to model and simulate the complex patterns of land use change by utilizing remote sensing and artificial intelligence techniques in the fast growing city of Mahabad, north-west of Iran which encountered with several environmental subsequences. The key subject is how to allocate optimized weight into effective parameters upon urban growth and subsequently achieving an improved simulation. Artificial Neural Networks (ANN algorithm was used to allocate the weight via an iteration approach. In this way, weight allocation was carried out by the ANN training accomplishing through time-series satellite images representing urban growth process. Cellular Automata (CA was used as the principal motor of the model and then ANN applied to find suitable scale of parameters and relations between potential factors affecting urban growth. The general accuracy of the suggested model and obtained Fuzzy Kappa Coefficient confirms achieving better results than classic CA models in simulating nonlinear urban evolution process.

Non-rigid image registration using bone growth model

DEFF Research Database (Denmark)

Bro-Nielsen, Morten; Gramkow, Claus; Kreiborg, Sven

1997-01-01

Non-rigid registration has traditionally used physical models like elasticity and fluids. These models are very seldom valid models of the difference between the registered images. This paper presents a non-rigid registration algorithm, which uses a model of bone growth as a model of the change...... between time sequence images of the human mandible. By being able to register the images, this paper at the same time contributes to the validation of the growth model, which is based on the currently available medical theories and knowledge...

Growth and Poverty

DEFF Research Database (Denmark)

Arndt, Channing; Leyaro, Vincent; Mahrt, Kristi

2017-01-01

This chapter considers the evolution of welfare of the Tanzanian population using a multi-dimensional approach. It also employs a detailed economy-wide model of the Tanzanian economy to explore growth and monetary poverty reduction scenarios from 2007 to 2015. This approach permits assessment...... of the coherence of observed trends in macroeconomic variables and projects consumption poverty outcomes to 2015. In the multi-dimensional approach, we find that real gains have been achieved. On monetary poverty, our model broadly reproduces key macroeconomic features of the past eight years. We find...... that published consumption poverty reductions for 2007 to 2011/12 from the most recent assessment fall within a reasonable to optimistic range. And, the simulations generate broader based growth across the income distribution compared with the recent assessment. Looking forward, the simulations from 2012 to 2105...

A mathematical model of microalgae growth in cylindrical photobioreactor

Science.gov (United States)

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.

Modeling of metal nanocluster growth on patterned substrates and surface pattern formation under ion bombardment

Energy Technology Data Exchange (ETDEWEB)

Numazawa, Satoshi

2012-11-01

This work addresses the metal nanocluster growth process on prepatterned substrates, the development of atomistic simulation method with respect to an acceleration of the atomistic transition states, and the continuum model of the ion-beam inducing semiconductor surface pattern formation mechanism. Experimentally, highly ordered Ag nanocluster structures have been grown on pre-patterned amorphous SiO{sub 2} surfaces by oblique angle physical vapor deposition at room temperature. Despite the small undulation of the rippled surface, the stripe-like Ag nanoclusters are very pronounced, reproducible and well-separated. The first topic is the investigation of this growth process with a continuum theoretical approach to the surface gas condensation as well as an atomistic cluster growth model. The atomistic simulation model is a lattice-based kinetic Monte-Carlo (KMC) method using a combination of a simplified inter-atomic potential and experimental transition barriers taken from the literature. An effective transition event classification method is introduced which allows a boost factor of several thousand compared to a traditional KMC approach, thus allowing experimental time scales to be modeled. The simulation predicts a low sticking probability for the arriving atoms, millisecond order lifetimes for single Ag monomers and {approx}1 nm square surface migration ranges of Ag monomers. The simulations give excellent reproduction of the experimentally observed nanocluster growth patterns. The second topic specifies the acceleration scheme utilized in the metallic cluster growth model. Concerning the atomistic movements, a classical harmonic transition state theory is considered and applied in discrete lattice cells with hierarchical transition levels. The model results in an effective reduction of KMC simulation steps by utilizing a classification scheme of transition levels for thermally activated atomistic diffusion processes. Thermally activated atomistic movements

Modeling of metal nanocluster growth on patterned substrates and surface pattern formation under ion bombardment

Energy Technology Data Exchange (ETDEWEB)

Numazawa, Satoshi

2012-11-01

This work addresses the metal nanocluster growth process on prepatterned substrates, the development of atomistic simulation method with respect to an acceleration of the atomistic transition states, and the continuum model of the ion-beam inducing semiconductor surface pattern formation mechanism. Experimentally, highly ordered Ag nanocluster structures have been grown on pre-patterned amorphous SiO{sub 2} surfaces by oblique angle physical vapor deposition at room temperature. Despite the small undulation of the rippled surface, the stripe-like Ag nanoclusters are very pronounced, reproducible and well-separated. The first topic is the investigation of this growth process with a continuum theoretical approach to the surface gas condensation as well as an atomistic cluster growth model. The atomistic simulation model is a lattice-based kinetic Monte-Carlo (KMC) method using a combination of a simplified inter-atomic potential and experimental transition barriers taken from the literature. An effective transition event classification method is introduced which allows a boost factor of several thousand compared to a traditional KMC approach, thus allowing experimental time scales to be modeled. The simulation predicts a low sticking probability for the arriving atoms, millisecond order lifetimes for single Ag monomers and {approx}1 nm square surface migration ranges of Ag monomers. The simulations give excellent reproduction of the experimentally observed nanocluster growth patterns. The second topic specifies the acceleration scheme utilized in the metallic cluster growth model. Concerning the atomistic movements, a classical harmonic transition state theory is considered and applied in discrete lattice cells with hierarchical transition levels. The model results in an effective reduction of KMC simulation steps by utilizing a classification scheme of transition levels for thermally activated atomistic diffusion processes. Thermally activated atomistic movements

BUILDING NEW BUSINESS MODELS FOR SUSTAINABLE GROWTH AND DEVELOPMENT

Directory of Open Access Journals (Sweden)

Taco C. R. van Someren

2011-06-01

Full Text Available Considered are issues of methodology and methods, as well as ideology of strategic innovation. Using the tools of this approach is offered as mechanisms to develop and build business models for sustainable socio-economic economic growth and development of different regions. The connection between key problems of sustainable development and management policy of different economic entities is studied. The consultancy company Ynnovate’s experience in addressing these issues in the EU and China is shown. It is offered to the use its experience and tools in exploring the areas of cross-border economic cooperation between territories of the Russian Far East and China

Localisation in a Growth Model with Interaction

Science.gov (United States)

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.

Temperature and precipitation records from stalagmites grown under disequilibrium conditions: A model approach.

Science.gov (United States)

Mühlinghaus, C.; Scholz, D.; Mangini, A.

2009-04-01

records of the stalagmites, which were obtained by three independent model runs, follow a general trend over the whole growth period and reveal good correlations within certain time-frames. This is a promising first result of the model. In addition the calculated temperatures are robust to small variations of the input variables, giving confidence in the algorithm of the model and for further temperature reconstructions from kinetically grown stalagmites. Literature Dreybrodt, W., 1999. Chemical kinetics, speleothem growth and climate. Boreas 28, 347 -356. Kaufmann, G., Dreybrodt, W. , 2004. Stalagmite growth and palaeo-climate: an inverse approach. Earth and Planetary Science Letters 224, 529 - 545. Kilian, R., Biester, H., Behrmann, J., Baeza, O., Fesq-Martin, M., Hohner, M., Schimpf, D., Friedmann, A., Mangini, A., 2006: Millennium-scale volcanic impact on a superhumid and pristine ecosystem, Geology, 34: 609 - 612. Mühlinghaus, C., Scholz, D., Mangini, A., 2007. Modelling stalagmite growth and ^13C as a function of drip interval and temperature. Geochimica et Cosmochimica Acta 71, 2780 - 2790. Mühlinghaus, C.; Scholz, D., Mangini, A., 2008a. Temperature and precipitation records from stalagmites grown under disequilibrium conditions: A first approach. Advances in speleothem research, PAGES News, 16 Mühlinghaus, C., Scholz, D., Mangini, A., 2008b. Fractionation of stable isotopes in stalagmites under disequilibrium conditions. Geochimica et Cosmochimica Acta, Submitted. Schimpf, D., 2005. Datierung und Interpretation der Kohlenstoff- und Sauerstoffsotopie zweier holozäner Stalagmiten aus dem Süden Chiles (Patagonien). Master's thesis, Ruprecht-Karls- University, Heidelberg. Schimpf, D., Kilian, R., Mangini, A., Spötl, C., Kronz, A., in prep. Evaluation of chemical, isotopic and detrital proxies of a high-resolution stalagmite record from the southernmost Chilean Andes (53˚ S) Scholz, D., Mühlinghaus, C., Mangini, A., 2008. Modelling the evolution of ^13C and

Growth rate in the dynamical dark energy models

International Nuclear Information System (INIS)

Avsajanishvili, Olga; Arkhipova, Natalia A.; Samushia, Lado; Kahniashvili, Tina

2014-01-01

Dark energy models with a slowly rolling cosmological scalar field provide a popular alternative to the standard, time-independent cosmological constant model. We study the simultaneous evolution of background expansion and growth in the scalar field model with the Ratra-Peebles self-interaction potential. We use recent measurements of the linear growth rate and the baryon acoustic oscillation peak positions to constrain the model parameter α that describes the steepness of the scalar field potential. (orig.)

Growth rate in the dynamical dark energy models.

Science.gov (United States)

Avsajanishvili, Olga; Arkhipova, Natalia A; Samushia, Lado; Kahniashvili, Tina

Dark energy models with a slowly rolling cosmological scalar field provide a popular alternative to the standard, time-independent cosmological constant model. We study the simultaneous evolution of background expansion and growth in the scalar field model with the Ratra-Peebles self-interaction potential. We use recent measurements of the linear growth rate and the baryon acoustic oscillation peak positions to constrain the model parameter [Formula: see text] that describes the steepness of the scalar field potential.

Investigation of Mediational Processes Using Parallel Process Latent Growth Curve Modeling

Science.gov (United States)

Cheong, JeeWon; MacKinnon, David P.; Khoo, Siek Toon

2010-01-01

This study investigated a method to evaluate mediational processes using latent growth curve modeling. The mediator and the outcome measured across multiple time points were viewed as 2 separate parallel processes. The mediational process was defined as the independent variable influencing the growth of the mediator, which, in turn, affected the growth of the outcome. To illustrate modeling procedures, empirical data from a longitudinal drug prevention program, Adolescents Training and Learning to Avoid Steroids, were used. The program effects on the growth of the mediator and the growth of the outcome were examined first in a 2-group structural equation model. The mediational process was then modeled and tested in a parallel process latent growth curve model by relating the prevention program condition, the growth rate factor of the mediator, and the growth rate factor of the outcome. PMID:20157639

Studying historical occupational careers with multilevel growth models

Directory of Open Access Journals (Sweden)

Wiebke Schulz

2010-10-01

Full Text Available In this article we propose to study occupational careers with historical data by using multilevel growth models. Historical career data are often characterized by a lack of information on the timing of occupational changes and by different numbers of observations of occupations per individual. Growth models can handle these specificities, whereas standard methods, such as event history analyses can't. We illustrate the use of growth models by studying career success of men and women, using data from the Historical Sample of the Netherlands. The results show that the method is applicable to male careers, but causes trouble when analyzing female careers.

Tax Evasion in a Model of Endogenous Growth

OpenAIRE

Been-Lon Chen

2003-01-01

This paper integrates tax evasion into a standard AK growth model with public capital. In the model, the government optimizes the tax rate, while individuals optimize tax evasion. It studies tax rate, tax evasion and economic growth, and compares them with otherwise identical economies except those without tax evasion. It inquires into the effects of three government policies on tax rate, tax evasion, and economic growth. It finds that an increase in both unit cost of tax evasion and punishme...

An immunologic approach to induction of epidermal growth factor deficiency

DEFF Research Database (Denmark)

Raaberg, Lasse; Nexø, Ebba; Poulsen, Steen Seier

1995-01-01

Epidermal growth factor (EGF) in pharmacologic doses is able to induce growth and development in the fetus and the newborn. To investigate the opposite situation, the effects of insufficient amounts of EGF during development, we wanted to establish an in vivo model with a state of EGF deficiency....

Nonlinear Growth Models in M"plus" and SAS

Science.gov (United States)

Grimm, Kevin J.; Ram, Nilam

2009-01-01

Nonlinear growth curves or growth curves that follow a specified nonlinear function in time enable researchers to model complex developmental patterns with parameters that are easily interpretable. In this article we describe how a variety of sigmoid curves can be fit using the M"plus" structural modeling program and the nonlinear…

Insurance-growth nexus in Ghana: An autoregressive distributed lag bounds cointegration approach

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Abdul Latif Alhassan

2014-12-01

Full Text Available This paper examines the long-run causal relationship between insurance penetration and economic growth in Ghana from 1990 to 2010. Using the autoregressive distributed lag (ARDL bounds approach to cointegration by Pesaran et al. (1996, 2001, the study finds a long-run positive relationship between insurance penetration and economic growth which implies that funds mobilized from insurance business have a long run impact on economic growth. A unidirectional causality was found to run from aggregate insurance penetration, life and non-life insurance penetration to economic growth to support the ‘supply-leading’ hypothesis. The findings have implications for insurance market development in Ghana.

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

Science.gov (United States)

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.

Mathematical models of tumor growth: translating absorbed dose to tumor control probability

International Nuclear Information System (INIS)

Sgouros, G.

1996-01-01

Full text: The dose-rate in internal emitter therapy is low and time-dependent as compared to external beam radiotherapy. Once the total absorbed dose delivered to a target tissue is calculated, however, most dosimetric analyses of radiopharmaceuticals are considered complete. To translate absorbed dose estimates obtained for internal emitter therapy to biologic effect, the growth characteristics, repair capacity, and radiosensitivity of the tumor must be considered. Tumor growth may be represented by the Gompertz equation in which tumor cells increase at an exponential growth rate that is itself decreasing at an exponential rate; as the tumor increases in size, the growth rate diminishes. The empirical Gompertz expression for tumor growth may be derived from a mechanistic model in which growth is represented by a balance between tumor-cell birth and loss. The birth rate is assumed to be fixed, while the cell loss rate is time-dependent and increases with tumor size. The birth rate of the tumors may be related to their potential doubling time. Multiple biopsies of individual tumors have demonstrated a heterogeneity in the potential doubling time of tumors. By extending the mechanistic model described above to allow for sub-populations of tumor cells with different birth rates, the effect of kinetic heterogeneity within a tumor may be examined. Model simulations demonstrate that the cell kinetic parameters of a tumor are predicted to change over time and measurements obtained using a biopsy are unlikely to reflect the kinetics of the tumor throughout its growth history. A decrease in overall tumor mass, in which each sub-population is reduced in proportion to its cell number, i.e., the log-kill assumption, leads to re-growth of a tumor that has a greater proliferation rate. Therapy that is linked to the potential doubling time or to the effective proliferation rate of the tumor may lead to re-growth of a tumor that is kinetically unchanged. The simplest model of

SUSTAINABLE GROWTH OF THE COMMERCIAL AVIATION INDUSTRY IN MALAYSIA USING A SYSTEM DYNAMICS APPROACH

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B. S. TAN

2015-09-01

Full Text Available The environmental impact of the commercial aviation industry for an emerging economy like Malaysia is under-studied. The focus on the subject has thus far concentrated either on non geographical performance of the aviation industry or technical performance of aircrafts and that leaves the sustainability of the commercial aviation industry for an economy, or more specifically, an emerging economy least understood. Hence, this paper aims to investigate the sustainability of the growth of the commercial aviation industry in Malaysia and its impact upon the environment using a system dynamics approach. VENSIM is employed to model the commercial aviation industry in Malaysia as a dynamic system to evaluate the CO2 emitted from each component within the industry in order to forecast its overall CO2 emission. Results from the analysis show that sustainable growth can be affected by adopting short and long term strategies identified in this study.

Ensembles modeling approach to study Climate Change impacts on Wheat

Science.gov (United States)

Ahmed, Mukhtar; Claudio, Stöckle O.; Nelson, Roger; Higgins, Stewart

2017-04-01

Simulations of crop yield under climate variability are subject to uncertainties, and quantification of such uncertainties is essential for effective use of projected results in adaptation and mitigation strategies. In this study we evaluated the uncertainties related to crop-climate models using five crop growth simulation models (CropSyst, APSIM, DSSAT, STICS and EPIC) and 14 general circulation models (GCMs) for 2 representative concentration pathways (RCP) of atmospheric CO2 (4.5 and 8.5 W m-2) in the Pacific Northwest (PNW), USA. The aim was to assess how different process-based crop models could be used accurately for estimation of winter wheat growth, development and yield. Firstly, all models were calibrated for high rainfall, medium rainfall, low rainfall and irrigated sites in the PNW using 1979-2010 as the baseline period. Response variables were related to farm management and soil properties, and included crop phenology, leaf area index (LAI), biomass and grain yield of winter wheat. All five models were run from 2000 to 2100 using the 14 GCMs and 2 RCPs to evaluate the effect of future climate (rainfall, temperature and CO2) on winter wheat phenology, LAI, biomass, grain yield and harvest index. Simulated time to flowering and maturity was reduced in all models except EPIC with some level of uncertainty. All models generally predicted an increase in biomass and grain yield under elevated CO2 but this effect was more prominent under rainfed conditions than irrigation. However, there was uncertainty in the simulation of crop phenology, biomass and grain yield under 14 GCMs during three prediction periods (2030, 2050 and 2070). We concluded that to improve accuracy and consistency in simulating wheat growth dynamics and yield under a changing climate, a multimodel ensemble approach should be used.

Energy Production and Regional Economic Growth in China: A More Comprehensive Analysis Using a Panel Model

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Yaobin Liu

2013-03-01

Full Text Available China has witnessed a fast economic growth in the recent two decades. However, the heavy energy exploitation seems to show a negative relation to regional economic growth. Thus, the issue is whether the energy production is a curse or blessing for the regional economic growth in China. The present study deploys a comprehensive approach to rigorously prove the validity of a proposed panel data model that includes a second generation panel unit root test and panel cointegration and a spatial panel model. The results from the second generation panel unit root test and panel cointegration allowing for cross-sectional dependences show the differenced series are stationary and there exists a cointegration relationship among these variables for all sub-regions. The results from the spatial panel data model support the conjecture of the spatial dependent and show that there is a “resource curse” only for the Western region and Central region in China.

Population models for Greater Snow Geese: a comparison of different approaches to assess potential impacts of harvest

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Gauthier, G.

2004-06-01

Full Text Available Demographic models, which are a natural extension of capture-recapture (CR methodology, are a powerful tool to guide decisions when managing wildlife populations. We compare three different modelling approaches to evaluate the effect of increased harvest on the population growth of Greater Snow Geese (Chen caerulescens atlantica. Our first approach is a traditional matrix model where survival was reduced to simulate increased harvest. We included environmental stochasticity in the matrix projection model by simulating good, average, and bad years to account for the large inter-annual variation in fecundity and first-year survival, a common feature of birds nesting in the Arctic. Our second approach is based on the elasticity (or relative sensitivity of population growth rate (lambda to changes in survival as simple functions of generation time. Generation time was obtained from the mean transition matrix based on the observed proportion of good, average and bad years between 1985 and 1998. If we assume that hunting mortality is additive to natural mortality, then a simple formula predicts changes in lambda as a function of changes in harvest rate. This second approach can be viewed as a simplification of the matrix model because it uses formal sensitivity results derived from population projection. Our third, and potentially more powerful approach, uses the Kalman Filter to combine information on demographic parameters, i.e. the population mechanisms summarized in a transition matrix model, and the census information (i.e. annual survey within an overall Gaussian likelihood. The advantage of this approach is that it minimizes process and measured uncertainties associated with both the census and demographic parameters based on the variance of each estimate. This third approach, in contrast to the second, can be viewed as an extension of the matrix model, by combining its results with the independent census information.

Stochastic modelling of avascular tumour growth and therapy

International Nuclear Information System (INIS)

Sahoo, S; Sahoo, A; Shearer, S F C

2011-01-01

In this paper, a generalized stochastic model for the growth of avascular tumours is presented. This model captures the dynamical evolution of avascular tumour cell subpopulations by incorporating Gaussian white noise into the growth rate of the mitotic function. This work generalizes the deterministic model proposed by Sherratt and Chaplain (2001 J. Math. Biol. 43 291) where they formulated a tumour model in an in vivo setting, in terms of continuum densities of proliferating, quiescent and necrotic cells. Detailed simulations of our model show that the inclusion of Gaussian noise in the original model of Sherratt and Chaplain substantially distorts the overall structure of the density profiles in addition to reducing the speed of tumour growth. Within this stochastic carcinogenesis framework the action of therapy is also investigated by replacing Gaussian white noise with a therapy term. We compare a constant therapy protocol with a logarithmic time-dependent protocol. Our results predict that a logarithmic therapy is more effective than the constant therapy protocol.

Surface-bounded growth modeling applied to human mandibles

DEFF Research Database (Denmark)

Andresen, Per Rønsholt

1999-01-01

This thesis presents mathematical and computational techniques for three dimensional growth modeling applied to human mandibles. The longitudinal shape changes make the mandible a complex bone. The teeth erupt and the condylar processes change direction, from pointing predominantly backward...... of the common features. 3.model the process that moves the matched points (growth modeling). A local shape feature called crest line has shown itself to be structurally stable on mandibles. Registration of crest lines (from different mandibles) results in a sparse deformation field, which must be interpolated...... old mandible based on the 3 month old scan. When using successively more recent scans as basis for the model the error drops to 2.0 mm for the 11 years old scan. Thus, it seems reasonable to assume that the mandibular growth is linear....

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

Science.gov (United States)

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.

Growth Kinetics and Modeling of Direct Oxynitride Growth with NO-O2 Gas Mixtures

Energy Technology Data Exchange (ETDEWEB)

Everist, Sarah; Nelson, Jerry; Sharangpani, Rahul; Smith, Paul Martin; Tay, Sing-Pin; Thakur, Randhir

1999-05-03

We have modeled growth kinetics of oxynitrides grown in NO-O₂ gas mixtures from first principles using modified Deal-Grove equations. Retardation of oxygen diffusion through the nitrided dielectric was assumed to be the dominant growth-limiting step. The model was validated against experimentally obtained curves with good agreement. Excellent uniformity, which exceeded expected walues, was observed.

Modelling growth of Penicillium expansum and Aspergillus niger at constant and fluctuating temperature conditions.

Science.gov (United States)

Gougouli, Maria; Koutsoumanis, Konstantinos P

2010-06-15

The growth of Penicillium expansum and Aspergillus niger, isolated from yogurt production environment, was investigated on malt extract agar with pH=4.2 and a(w)=0.997, simulating yogurt, at isothermal conditions ranging from -1.3 to 35 degrees C and from 5 to 42.3 degrees C, respectively. The growth rate (mu) and (apparent) lag time (lambda) of the mycelium growth were modelled as a function of temperature using a Cardinal Model with Inflection (CMI). The results showed that the CMI can describe successfully the effect of temperature on fungal growth within the entire biokinetic range for both isolates. The estimated values of the CMI for mu were T(min)=-5.74 degrees C, T(max)=30.97 degrees C, T(opt)=22.08 degrees C and mu(opt)=0.221 mm/h for P. expansum and T(min)=10.13 degrees C, T(max)=43.13 degrees C, T(opt)=31.44 degrees C, and mu(opt)=0.840 mm/h for A. niger. The cardinal values for lambda were very close to the respective values for mu indicating similar temperature dependence of the growth rate and the lag time of the mycelium growth. The developed models were further validated under fluctuating temperature conditions using various dynamic temperature scenarios. The time-temperature conditions studied included single temperature shifts before or after the end of the lag time and continuous periodic temperature fluctuations. The prediction of growth at changing temperature was based on the assumption that after a temperature shift the growth rate is adopted instantaneously to the new temperature, while the lag time was predicted using a cumulative lag approach. The results showed that when the temperature shifts occurred before the end of the lag, they did not cause any significant additional lag and the observed total lag was very close to the cumulative lag predicted by the model. In experiments with temperature shifts after the end of the lag time, accurate predictions were obtained when the temperature profile included temperatures which were inside the

Mudcake growth: Model and implications

KAUST Repository

Liu, Q.; Santamarina, Carlos

2017-01-01

cementing, and to prevent partial differential sticking. We developed a robust mud cake growth model for water-based mud based on wide stress-range constitutive equations within a Lagrangian reference system to avoid non-natural moving boundary solutions

Approaches to modeling landscape-scale drought-induced forest mortality

Science.gov (United States)

Gustafson, Eric J.; Shinneman, Douglas

2015-01-01

Drought stress is an important cause of tree mortality in forests, and drought-induced disturbance events are projected to become more common in the future due to climate change. Landscape Disturbance and Succession Models (LDSM) are becoming widely used to project climate change impacts on forests, including potential interactions with natural and anthropogenic disturbances, and to explore the efficacy of alternative management actions to mitigate negative consequences of global changes on forests and ecosystem services. Recent studies incorporating drought-mortality effects into LDSMs have projected significant potential changes in forest composition and carbon storage, largely due to differential impacts of drought on tree species and interactions with other disturbance agents. In this chapter, we review how drought affects forest ecosystems and the different ways drought effects have been modeled (both spatially and aspatially) in the past. Building on those efforts, we describe several approaches to modeling drought effects in LDSMs, discuss advantages and shortcomings of each, and include two case studies for illustration. The first approach features the use of empirically derived relationships between measures of drought and the loss of tree biomass to drought-induced mortality. The second uses deterministic rules of species mortality for given drought events to project changes in species composition and forest distribution. A third approach is more mechanistic, simulating growth reductions and death caused by water stress. Because modeling of drought effects in LDSMs is still in its infancy, and because drought is expected to play an increasingly important role in forest health, further development of modeling drought-forest dynamics is urgently needed.

A Latent Growth Mixture Modeling Approach to PTSD Symptoms in Rape Victims.

Science.gov (United States)

Armour, Cherie; Shevlin, Mark; Elklit, Ask; Mroczek, Dan

2012-03-01

The research literature has suggested that longitudinal changes in posttraumatic stress disorder (PTSD) could be adequately described in terms of one universal trajectory, with individual differences in baseline levels (intercept) and rate of change (slope) being negligible. However, not everyone who has experienced a trauma is diagnosed with PTSD, and symptom severity levels differ between individuals exposed to similar traumas. The current study employed the latent growth mixture modeling technique to test for multiple trajectories using data from a sample of Danish rape victims (N = 255). In addition, the analysis aimed to determine whether a number of explanatory variables could differentiate between the trajectories (age, acute stress disorder [ASD], and perceived social support). Results concluded the existence of two PTSD trajectories. ASD was found to be the only significant predictor of one trajectory characterized by high initial levels of PTSD symptomatology. The present findings confirmed the existence of multiple trajectories with regard to PTSD symptomatology in a way that may be useful to clinicians working with this population.

A Latent Growth Mixture Modeling Approach to PTSD Symptoms in Rape Victims

Science.gov (United States)

Armour, Cherie; Shevlin, Mark; Elklit, Ask; Mroczek, Dan

2012-01-01

The research literature has suggested that longitudinal changes in posttraumatic stress disorder (PTSD) could be adequately described in terms of one universal trajectory, with individual differences in baseline levels (intercept) and rate of change (slope) being negligible. However, not everyone who has experienced a trauma is diagnosed with PTSD, and symptom severity levels differ between individuals exposed to similar traumas. The current study employed the latent growth mixture modeling technique to test for multiple trajectories using data from a sample of Danish rape victims (N = 255). In addition, the analysis aimed to determine whether a number of explanatory variables could differentiate between the trajectories (age, acute stress disorder [ASD], and perceived social support). Results concluded the existence of two PTSD trajectories. ASD was found to be the only significant predictor of one trajectory characterized by high initial levels of PTSD symptomatology. The present findings confirmed the existence of multiple trajectories with regard to PTSD symptomatology in a way that may be useful to clinicians working with this population. PMID:22661909

Establishing a cause and effect relationship for ambient ozone exposure and tree growth in the forest: Progress and an experimental approach

International Nuclear Information System (INIS)

Manning, William J.

2005-01-01

Much has been written about the effects of ambient ozone on tree growth. Cause and effect has been established with seedlings in chambers. Results from multi-year studies with older tree seedlings, in open-top chambers, have been inconclusive, due to chamber effects. Extrapolation of results from chambers to trees in the forest is not possible. Predictive models for forest tree growth reductions caused by ozone have been developed, but not verified. Dendrochronological methods have been used to establish correlations between radial growth reductions in forest trees and ambient ozone exposure. The protective chemical ethylenediurea (EDU) has been used to protect tree seedlings from ozone injury. An experimental approach is advocated here that utilizes forest trees selected for sensitivity and non-sensitivity to ozone, dendrochronological methods, the protective chemical EDU, and monitoring data for ambient ozone, stomatal conductance, soil moisture potential, air temperature, PAR, etc. in long-term investigations to establish cause and effect relationships. - Progress is reviewed and an experimental approach is proposed to demonstrate a cause and effect relationship for ambient ozone and forest tree growth

A day in the life of fish larvae: modeling foraging and growth using quirks.

Directory of Open Access Journals (Sweden)

Klaus B Huebert

Full Text Available This article introduces "Quirks," a generic, individual-based model synthesizing over 40 years of empirical and theoretical insights into the foraging behavior and growth physiology of marine fish larvae. In Quirks, different types of larvae are defined by a short list of their biological traits, and all foraging and growth processes (including the effects of key environmental factors are modeled following one unified set of mechanistic rules. This approach facilitates ecologically meaningful comparisons between different species and environments. We applied Quirks to model young exogenously feeding larvae of four species: 5.5-mm European anchovy (Engraulis encrasicolus, 7-mm Atlantic cod (Gadus morhua, 13-mm Atlantic herring (Clupea harengus, and 7-mm European sprat (Sprattus sprattus. Modeled growth estimates explained the majority of variability among 53 published empirical growth estimates, and displayed very little bias: 0.65% ± 1.2% d(-1 (mean ± standard error. Prey organisms of ∼ 67% the maximum ingestible prey length were optimal for all larval types, in terms of the expected ingestion per encounter. Nevertheless, the foraging rate integrated over all favorable prey sizes was highest when smaller organisms made up >95% of the prey biomass under the assumption of constant normalized size spectrum slopes. The overall effect of turbulence was consistently negative, because its detrimental influence on prey pursuit success exceeded its beneficial influence on prey encounter rate. Model sensitivity to endogenous traits and exogenous environmental factors was measured and is discussed in depth. Quirks is free software and open source code is provided.

Analysing and modelling the growth behaviour of Listeria monocytogenes on RTE cooked meat products after a high pressure treatment at 400 MPa.

Science.gov (United States)

Hereu, A; Dalgaard, P; Garriga, M; Aymerich, T; Bover-Cid, S

2014-09-01

Various predictive models are available for high pressure inactivation of Listeria monocytogenes in food, but currently available models do not consider the growth kinetics of surviving cells during the subsequent storage of products. Therefore, we characterised the growth of L. monocytogenes in sliced cooked meat products after a pressurization treatment. Two inoculum levels (10(7) or 10(4) CFU/g) and two physiological states before pressurization (freeze-stressed or cold-adapted) were evaluated. Samples of cooked ham and mortadella were inoculated, high pressure processed (400 MPa, 5 min) and subsequently stored at 4, 8 and 12 °C. The Logistic model with delay was used to estimate lag phase (λ) and maximum specific growth rate (μmax) values from the obtained growth curves. The effect of storage temperature on μmax and λ was modelled using the Ratkowsky square root model and the relative lag time (RLT) concept. Compared with cold-adapted cells the freeze-stressed cells were more pressure-resistant and showed a much longer lag phase during growth after the pressure treatment. Interestingly, for high-pressure inactivation and subsequent growth, the time to achieve a concentration of L. monocytogenes 100-fold (2-log) higher than the cell concentration prior to the pressure treatment was similar for the two studied physiological states of the inoculum. Two secondary models were necessary to describe the different growth behaviour of L. monocytogenes on ready-to-eat cooked ham (lean product) and mortadella (fatty product). This supported the need of a product-oriented approach to assess growth after high pressure processing. The performance of the developed predictive models for the growth of L. monocytogenes in high-pressure processed cooked ham and mortadella was evaluated by comparison with available data from the literature and by using the Acceptable Simulation Zone approach. Overall, 91% of the relative errors fell into the Acceptable Simulation Zone

R.M. Solow Adjusted Model of Economic Growth

Directory of Open Access Journals (Sweden)

Ion Gh. Rosca

2007-05-01

Full Text Available Besides the models of M. Keynes, R.F. Harrod, E. Domar, D. Romer, Ramsey-Cass-Koopmans etc., the R.M. Solow model is part of the category which characterizes the economic growth. The paper proposes the study of the R.M. Solow adjusted model of economic growth, while the adjustment consisting in the model adaptation to the Romanian economic characteristics. The article is the first one from a three paper series dedicated to the macroeconomic modelling theme, using the R.M. Solow model, such as: “Measurement of the economic growth and extensions of the R.M. Solow adjusted model” and “Evolution scenarios at the Romanian economy level using the R.M. Solow adjusted model”. The analysis part of the model is based on the study of the equilibrium to the continuous case with some interpretations of the discreet one, by using the state diagram. The optimization problem at the economic level is also used; it is built up of a specified number of representative consumers and firms in order to reveal the interaction between these elements.

Modeling change in learning strategies throughout higher education: a multi-indicator latent growth perspective.

Science.gov (United States)

Coertjens, Liesje; Donche, Vincent; De Maeyer, Sven; Vanthournout, Gert; Van Petegem, Peter

2013-01-01

The change in learning strategies during higher education is an important topic of research in the Student Approaches to Learning field. Although the studies on this topic are increasingly longitudinal, analyses have continued to rely primarily on traditional statistical methods. The present research is innovative in the way it uses a multi-indicator latent growth analysis in order to more accurately estimate the general and differential development in learning strategy scales. Moreover, the predictive strength of the latent growth models are estimated. The sample consists of one cohort of Flemish University College students, 245 of whom participated in the three measurement waves by filling out the processing and regulation strategies scales of the Inventory of Learning Styles--Short Versions. Independent-samples t-tests revealed that the longitudinal group is a non-random subset of students starting University College. For each scale, a multi-indicator latent growth model is estimated using Mplus 6.1. Results suggest that, on average, during higher education, students persisting in their studies in a non-delayed manner seem to shift towards high-quality learning and away from undirected and surface-oriented learning. Moreover, students from the longitudinal group are found to vary in their initial levels, while, unexpectedly, not in their change over time. Although the growth models fit the data well, significant residual variances in the latent factors remain.

Modeling change in learning strategies throughout higher education: a multi-indicator latent growth perspective.

Directory of Open Access Journals (Sweden)

Liesje Coertjens

Full Text Available The change in learning strategies during higher education is an important topic of research in the Student Approaches to Learning field. Although the studies on this topic are increasingly longitudinal, analyses have continued to rely primarily on traditional statistical methods. The present research is innovative in the way it uses a multi-indicator latent growth analysis in order to more accurately estimate the general and differential development in learning strategy scales. Moreover, the predictive strength of the latent growth models are estimated. The sample consists of one cohort of Flemish University College students, 245 of whom participated in the three measurement waves by filling out the processing and regulation strategies scales of the Inventory of Learning Styles--Short Versions. Independent-samples t-tests revealed that the longitudinal group is a non-random subset of students starting University College. For each scale, a multi-indicator latent growth model is estimated using Mplus 6.1. Results suggest that, on average, during higher education, students persisting in their studies in a non-delayed manner seem to shift towards high-quality learning and away from undirected and surface-oriented learning. Moreover, students from the longitudinal group are found to vary in their initial levels, while, unexpectedly, not in their change over time. Although the growth models fit the data well, significant residual variances in the latent factors remain.

Coupling biomechanics to a cellular level model: an approach to patient-specific image driven multi-scale and multi-physics tumor simulation.

Science.gov (United States)

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.

Modelling the growth of a methanotrophic biofilm

DEFF Research Database (Denmark)

Arcangeli, J.-P.; Arvin, E.

1999-01-01

This article discusses the growth of methanotrophic biofilms. Several independent biofilm growths scenarios involving different inocula were examined. Biofilm growth, substrate removal and product formation were monitored throughout the experiments. Based on the oxygen consumption it was concluded...... that heterotrophs and nitrifiers co-existed with methanotrophs in the biofilm. Heterotrophic biomass grew on soluble polymers formed by the hydrolysis of dead biomass entrapped in the biofilm. Nitrifier populations developed because of the presence of ammonia in the mineral medium. Based on these experimental...... was performed on this model. It indicated that the most influential parameters were those related to the biofilm (i.e. density; solid-volume fraction; thickness). This suggests that in order to improve the model, further research regarding the biofilm structure and composition is needed....

Modelling of tomato stem diameter growth rate based on physiological responses

International Nuclear Information System (INIS)

Li, L.; Tan, J.; Lv, T.

2017-01-01

The stem diameter is an important parameter describing the growth of tomato plant during vegetative growth stage. A stem diameter growth model was developed to predict the response of plant growth under different conditions. By analyzing the diurnal variations of stem diameter in tomato (Solanum lycopersicum L.), it was found that the stem diameter measured at 3:00 am was the representative value as the daily basis of tomato stem diameter. Based on the responses of growth rate in stem diameter to light and temperature, a linear regression relationship was applied to establish the stem diameter growth rate prediction model for the vegetative growth stage in tomato and which was further validated by experiment. The root mean square error (RMSE) and relative error (RE) were used to test the correlation between measured and modeled stem diameter variations. Results showed that the model can be used in prediction for stem diameter growth rate at vegetative growth stage in tomato. (author)

A literature review on growth models and strategies: The missing link in entrepreneurial growth

Directory of Open Access Journals (Sweden)

Syed Fida Hussain Shah

2013-08-01

Full Text Available This study focuses on the importance of growth models, growth strategies, role of knowledge management system in the formulation of effective strategy for the enterprises following growth. Choice of an appropriate growth strategy is at the heart of any successful entrepreneurial venture. Selection of a strategy may be effective for one entrepreneur while it is not for other. Choice of Growth Strategy depends on various different factors, organisational context and environment which may vary from enterprise to enterprise. Resource based view is very important consideration for the entrepreneurs on the path of growth. Evaluation of all kind of resources helps them to grow their enterprises successfully. Selection of an appropriate growth strategy allows the entrepreneurs in overcoming growth challenges and avoiding the growth reversals and setbacks.

An adaptive ARX model to estimate the RUL of aluminum plates based on its crack growth

Science.gov (United States)

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.

Modelling the interaction between flooding events and economic growth

Science.gov (United States)

Grames, Johanna; Grass, Dieter; Prskawetz, Alexia; Blöschl, Günther

2015-04-01

Socio-hydrology describes the interaction between the socio-economy, water and population dynamics. Recent models analyze the interplay of community risk-coping culture, flooding damage and economic growth (Di Baldassarre, 2013, Viglione, 2014). These models descriptively explain the feedbacks between socio-economic development and natural disasters like floods. Contrary to these descriptive models, our approach develops an optimization model, where the intertemporal decision of an economic agent interacts with the hydrological system. This is the first economic growth model describing the interaction between the consumption and investment decisions of an economic agent and the occurrence of flooding events: Investments in defense capital can avoid floods even when the water level is high, but on the other hand such investment competes with investment in productive capital and hence may reduce the level of consumption. When floods occur, the flood damage therefore depends on the existing defense capital. The aim is to find an optimal tradeoff between investments in productive versus defense capital such as to optimize the stream of consumption in the long-term. We assume a non-autonomous exogenous periodic rainfall function (Yevjevich et.al. 1990, Zakaria 2001) which implies that the long-term equilibrium will be periodic . With our model we aim to derive mechanisms that allow consumption smoothing in the long term, and at the same time allow for optimal investment in flood defense to maximize economic output. We choose an aggregate welfare function that depends on the consumption level of the society as the objective function. I.e. we assume a social planer with perfect foresight that maximizes the aggregate welfare function. Within our model framework we can also study whether the path and level of defense capital (that protects people from floods) is related to the time preference rate of the social planner. Our model also allows to investigate how the frequency

Education-growth dynamics for Australia: A case study approach

Directory of Open Access Journals (Sweden)

Kunofiwa Tsaurai

2015-04-01

Full Text Available The main focus of this research is to establish the relevancy of the Keynesian theory in explaining education expenditure on the economy of Austria using a case study approach. Wagner (1890 and Keynes (1936 have been for a long time been the two major theorists on the relationship between education expenditure and economic growth. Both theoretical and empirical literature review concludes that the two variables relate to each other in two distinct ways, the popular one being that education boost the economy (Keynes view followed by the Wagner view that says it is the economy that is doing well that pushes investment in education. A case study review for Austria clearly shows that an increase in education expenditure does not only constitute a significant portion of the GDP per capita in Austria but also provided a positive influence on economic growth and development. The author recommends Austria policymakers and responsible authorities to up their education development programmes and budgets in order to lay a strong foundation for sustainable economic growth and prosperity.

Electricity supply industry modelling for multiple objectives under demand growth uncertainty

International Nuclear Information System (INIS)

Heinrich, G.; Basson, L.; Howells, M.; Petrie, J.

2007-01-01

Appropriate energy-environment-economic (E3) modelling provides key information for policy makers in the electricity supply industry (ESI) faced with navigating a sustainable development path. Key challenges include engaging with stakeholder values and preferences, and exploring trade-offs between competing objectives in the face of underlying uncertainty. As a case study we represent the South African ESI using a partial equilibrium E3 modelling approach, and extend the approach to include multiple objectives under selected future uncertainties. This extension is achieved by assigning cost penalties to non-cost attributes to force the model's least-cost objective function to better satisfy non-cost criteria. This paper incorporates aspects of flexibility to demand growth uncertainty into each future expansion alternative by introducing stochastic programming with recourse into the model. Technology lead times are taken into account by the inclusion of a decision node along the time horizon where aspects of real options theory are considered within the planning process. Hedging in the recourse programming is automatically translated from being purely financial, to include the other attributes that the cost penalties represent. From a retrospective analysis of the cost penalties, the correct market signals, can be derived to meet policy goal, with due regard to demand uncertainty. (author)

Adjusting the Stems Regional Forest Growth Model to Improve Local Predictions

Science.gov (United States)

W. Brad Smith

1983-01-01

A simple procedure using double sampling is described for adjusting growth in the STEMS regional forest growth model to compensate for subregional variations. Predictive accuracy of the STEMS model (a distance-independent, individual tree growth model for Lake States forests) was improved by using this procedure

Individual-Tree Diameter Growth Models for Mixed Nothofagus Second Growth Forests in Southern Chile

Directory of Open Access Journals (Sweden)

Paulo C. Moreno

2017-12-01

Full Text Available Second growth forests of Nothofagus obliqua (roble, N. alpina (raulí, and N. dombeyi (coihue, known locally as RORACO, are among the most important native mixed forests in Chile. To improve the sustainable management of these forests, managers need adequate information and models regarding not only existing forest conditions, but their future states with varying alternative silvicultural activities. In this study, an individual-tree diameter growth model was developed for the full geographical distribution of the RORACO forest type. This was achieved by fitting a complete model by comparing two variable selection procedures: cross-validation (CV, and least absolute shrinkage and selection operator (LASSO regression. A small set of predictors successfully explained a large portion of the annual increment in diameter at breast height (DBH growth, particularly variables associated with competition at both the tree- and stand-level. Goodness-of-fit statistics for this final model showed an empirical coefficient of correlation (R2emp of 0.56, relative root mean square error of 44.49% and relative bias of −1.96% for annual DBH growth predictions, and R2emp of 0.98 and 0.97 for DBH projection at 6 and 12 years, respectively. This model constitutes a simple and useful tool to support management plans for these forest ecosystems.

Continuum and discrete approach in modeling biofilm development and structure: a review.

Science.gov (United States)

Mattei, M R; Frunzo, L; D'Acunto, B; Pechaud, Y; Pirozzi, F; Esposito, G

2018-03-01

The scientific community has recognized that almost 99% of the microbial life on earth is represented by biofilms. Considering the impacts of their sessile lifestyle on both natural and human activities, extensive experimental activity has been carried out to understand how biofilms grow and interact with the environment. Many mathematical models have also been developed to simulate and elucidate the main processes characterizing the biofilm growth. Two main mathematical approaches for biomass representation can be distinguished: continuum and discrete. This review is aimed at exploring the main characteristics of each approach. Continuum models can simulate the biofilm processes in a quantitative and deterministic way. However, they require a multidimensional formulation to take into account the biofilm spatial heterogeneity, which makes the models quite complicated, requiring significant computational effort. Discrete models are more recent and can represent the typical multidimensional structural heterogeneity of biofilm reflecting the experimental expectations, but they generate computational results including elements of randomness and introduce stochastic effects into the solutions.

An engineering approach for examining crack growth and stability in flawed structures

International Nuclear Information System (INIS)

Shih, C.F.; German, M.D.; Kumar, V.

1981-01-01

Progress made in two research programmes, sponsored by the Electric Power Research Institute (EPRI), to identify viable parameters for characterising crack initiation and continued extension are summarised. An engineering/design methodology, based on these parameters, for the assessment of crack growth and instability in engineering structures which are stressed beyond the regime of applicability of linear elastic fracture mechanics is developed. The ultimate goal in the development of such a methodology is to establish an improved basis for analysing the effect of flaws (postulated or detected) on the safety margins of pressure boundary components of light water-cooled type nuclear steam supply systems. The methodology can also be employed for structural integrity analyses of other engineering components. Extensive experimental and analytical investigations undertaken to evaluate potential criteria for crack initiation and growth and the selection of the final criteria for analysing crack growth and stability in flawed structures are summarised. The experimental and analytical results obtained to date suggest that parameters based on the J-integral and the crack tip opening displacement, delta, are the most promising. This is not surprising since, from a theoretical basis, the two approaches are similar if certain conditions are met. An engineering/design approach for the assessment of crack growth and instability in flawed structures is outlined. (author)

Energy demand projections based on an uncertain dynamic system modeling approach

International Nuclear Information System (INIS)

Dong, S.

2000-01-01

Today, China has become the world's second largest pollution source of CO 2 . Owing to coal-based energy consumption, it is estimated that 85--90% of the SO 2 and CO 2 emission of China results from coal use. With high economic growth and increasing environmental concerns, China's energy consumption in the next few decades has become an issue of active concern. Forecasting of energy demand over long periods, however, is getting more complex and uncertain. It is believed that the economic and energy systems are chaotic and nonlinear. Traditional linear system modeling, used mostly in energy demand forecasts, therefore, is not a useful approach. In view of uncertainty and imperfect information about future economic growth and energy development, an uncertain dynamic system model, which has the ability to incorporate and absorb the nature of an uncertain system with imperfect or incomplete information, is developed. Using the model, the forecasting of energy demand in the next 25 years is provided. The model predicts that China's energy demand in 2020 will be about 2,700--3,000 Mtce, coal demand 3,500 Mt, increasing by 128% and 154%, respectively, compared with that of 1995

Growth Modeling with Non-Ignorable Dropout: Alternative Analyses of the STAR*D Antidepressant Trial

Science.gov (United States)

Muthén, Bengt; Asparouhov, Tihomir; Hunter, Aimee; Leuchter, Andrew

2011-01-01

This paper uses a general latent variable framework to study a series of models for non-ignorable missingness due to dropout. Non-ignorable missing data modeling acknowledges that missingness may depend on not only covariates and observed outcomes at previous time points as with the standard missing at random (MAR) assumption, but also on latent variables such as values that would have been observed (missing outcomes), developmental trends (growth factors), and qualitatively different types of development (latent trajectory classes). These alternative predictors of missing data can be explored in a general latent variable framework using the Mplus program. A flexible new model uses an extended pattern-mixture approach where missingness is a function of latent dropout classes in combination with growth mixture modeling using latent trajectory classes. A new selection model allows not only an influence of the outcomes on missingness, but allows this influence to vary across latent trajectory classes. Recommendations are given for choosing models. The missing data models are applied to longitudinal data from STAR*D, the largest antidepressant clinical trial in the U.S. to date. Despite the importance of this trial, STAR*D growth model analyses using non-ignorable missing data techniques have not been explored until now. The STAR*D data are shown to feature distinct trajectory classes, including a low class corresponding to substantial improvement in depression, a minority class with a U-shaped curve corresponding to transient improvement, and a high class corresponding to no improvement. The analyses provide a new way to assess drug efficiency in the presence of dropout. PMID:21381817

Modelling of ductile and cleavage fracture by local approach

International Nuclear Information System (INIS)

Samal, M.K.; Dutta, B.K.; Kushwaha, H.S.

2000-08-01

This report describes the modelling of ductile and cleavage fracture processes by local approach. It is now well known that the conventional fracture mechanics method based on single parameter criteria is not adequate to model the fracture processes. It is because of the existence of effect of size and geometry of flaw, loading type and rate on the fracture resistance behaviour of any structure. Hence, it is questionable to use same fracture resistance curves as determined from standard tests in the analysis of real life components because of existence of all the above effects. So, there is need to have a method in which the parameters used for the analysis will be true material properties, i.e. independent of geometry and size. One of the solutions to the above problem is the use of local approaches. These approaches have been extensively studied and applied to different materials (including SA33 Gr.6) in this report. Each method has been studied and reported in a separate section. This report has been divided into five sections. Section-I gives a brief review of the fundamentals of fracture process. Section-II deals with modelling of ductile fracture by locally uncoupled type of models. In this section, the critical cavity growth parameters of the different models have been determined for the primary heat transport (PHT) piping material of Indian pressurised heavy water reactor (PHWR). A comparative study has been done among different models. The dependency of the critical parameters on stress triaxiality factor has also been studied. It is observed that Rice and Tracey's model is the most suitable one. But, its parameters are not fully independent of triaxiality factor. For this purpose, a modification to Rice and Tracery's model is suggested in Section-III. Section-IV deals with modelling of ductile fracture process by locally coupled type of models. Section-V deals with the modelling of cleavage fracture process by Beremins model, which is based on Weibulls

Export and Economic Growth Nexus in the GCC Countries: A panel Data Approach

Directory of Open Access Journals (Sweden)

hatem Hatef abdulkadhim

2017-12-01

Full Text Available The export and economic growth nexus, which is called Balassa’s Export-Led Growth Hypothesis (ELGH  in the literature, is still an unstill issue in both the theoretical and empirical literature. In the present study, the effect of export on economic growth in  oil exporting developing countries, namely, Bahrain, Saudi Arabia, Qatar,  Kuwait, UAE, and Oman in the 1990–2014 period was tested based on three models, pooled ordinary least squares (POLS, fixed effects model (FEM, and random effects model (REM  via panel data analysis . The findings revealed strong support for the “export-led growth” hypothesis. In addition, our results show that apart from growth in the labor force, investments in capital formation are necessary for economic growth. According to the obtained results, the ability to adopt technological changes in order to increase efficiency, and sustain economic development is also important.

A size-structured model of bacterial growth and reproduction.

Science.gov (United States)

Ellermeyer, S F; Pilyugin, S S

2012-01-01

We consider a size-structured bacterial population model in which the rate of cell growth is both size- and time-dependent and the average per capita reproduction rate is specified as a model parameter. It is shown that the model admits classical solutions. The population-level and distribution-level behaviours of these solutions are then determined in terms of the model parameters. The distribution-level behaviour is found to be different from that found in similar models of bacterial population dynamics. Rather than convergence to a stable size distribution, we find that size distributions repeat in cycles. This phenomenon is observed in similar models only under special assumptions on the functional form of the size-dependent growth rate factor. Our main results are illustrated with examples, and we also provide an introductory study of the bacterial growth in a chemostat within the framework of our model.

Modeling Urban Spatial Growth in Mountainous Regions of Western China

Directory of Open Access Journals (Sweden)

Guoping Huang

2017-08-01

Full Text Available The scale and speed of urbanization in the mountainous regions of western China have received little attention from researchers. These cities are facing rapid population growth and severe environmental degradation. This study analyzed historical urban growth trends in this mountainous region to better understand the interaction between the spatial growth pattern and the mountainous topography. Three major factors—slope, accessibility, and land use type—were studied in light of their relationships with urban spatial growth. With the analysis of historical data as the basis, a conceptual urban spatial growth model was devised. In this model, slope, accessibility, and land use type together create resistance to urban growth, while accessibility controls the sequence of urban development. The model was tested and evaluated using historical data. It serves as a potential tool for planners to envision and assess future urban growth scenarios and their potential environmental impacts to make informed decisions.

Stochastic growth logistic model with aftereffect for batch fermentation process

Energy Technology Data Exchange (ETDEWEB)

Rosli, Norhayati; Ayoubi, Tawfiqullah [Faculty of Industrial Sciences and Technology, Universiti Malaysia Pahang, Lebuhraya Tun Razak, 26300 Gambang, Pahang (Malaysia); Bahar, Arifah; Rahman, Haliza Abdul [Department of Mathematical Sciences, Faculty of Science, Universiti Teknologi Malaysia, 81310 Johor Bahru, Johor (Malaysia); Salleh, Madihah Md [Department of Biotechnology Industry, Faculty of Biosciences and Bioengineering, Universiti Teknologi Malaysia, 81310 Johor Bahru, Johor (Malaysia)

2014-06-19

In this paper, the stochastic growth logistic model with aftereffect for the cell growth of C. acetobutylicum P262 and Luedeking-Piret equations for solvent production in batch fermentation system is introduced. The parameters values of the mathematical models are estimated via Levenberg-Marquardt optimization method of non-linear least squares. We apply Milstein scheme for solving the stochastic models numerically. The effciency of mathematical models is measured by comparing the simulated result and the experimental data of the microbial growth and solvent production in batch system. Low values of Root Mean-Square Error (RMSE) of stochastic models with aftereffect indicate good fits.

Stochastic growth logistic model with aftereffect for batch fermentation process

Science.gov (United States)

Rosli, Norhayati; Ayoubi, Tawfiqullah; Bahar, Arifah; Rahman, Haliza Abdul; Salleh, Madihah Md

2014-06-01

In this paper, the stochastic growth logistic model with aftereffect for the cell growth of C. acetobutylicum P262 and Luedeking-Piret equations for solvent production in batch fermentation system is introduced. The parameters values of the mathematical models are estimated via Levenberg-Marquardt optimization method of non-linear least squares. We apply Milstein scheme for solving the stochastic models numerically. The effciency of mathematical models is measured by comparing the simulated result and the experimental data of the microbial growth and solvent production in batch system. Low values of Root Mean-Square Error (RMSE) of stochastic models with aftereffect indicate good fits.

Stochastic growth logistic model with aftereffect for batch fermentation process

International Nuclear Information System (INIS)

Rosli, Norhayati; Ayoubi, Tawfiqullah; Bahar, Arifah; Rahman, Haliza Abdul; Salleh, Madihah Md

2014-01-01

In this paper, the stochastic growth logistic model with aftereffect for the cell growth of C. acetobutylicum P262 and Luedeking-Piret equations for solvent production in batch fermentation system is introduced. The parameters values of the mathematical models are estimated via Levenberg-Marquardt optimization method of non-linear least squares. We apply Milstein scheme for solving the stochastic models numerically. The effciency of mathematical models is measured by comparing the simulated result and the experimental data of the microbial growth and solvent production in batch system. Low values of Root Mean-Square Error (RMSE) of stochastic models with aftereffect indicate good fits

Modelling and predicting growth of psychrotolerant pseudomonads in milk and cottage cheese

DEFF Research Database (Denmark)

Martinez Rios, Veronica; Østergaard, Nina Bjerre; Rosshaug, Per Sand

.43. The acceptable simulation zone method showed the new model for cottage cheese to successfully predict growth of psychrotolerant pseudomonads at both constant and dynamic temperature storage conditions. The new models can be used together with the Food Spoilage and Safety Predictor (FSSP) software to predict......Mathematical models were developed and evaluated for growth of psychrotolerant pseudomonads in chilled milk and cottage cheese with cultured cream dressing. The mathematical models include the effect of temperature, pH, NaCl, lactic acid and sorbic acid. A simplified cardinal parameter growth model...... was developed based on growth in broth. Subsequently, the reference growth rate parameter (μref at 25 °C) was fitted to a total of 35 growth rates from cottage cheese with cultured cream dressing. Growth rate models for milk and cottage cheese were evaluated by comparison with data from literature and new...

Flower Power: Sunflowers as a Model for Logistic Growth

Science.gov (United States)

Fernandez, Eileen; Geist, Kristi A.

2011-01-01

Logistic growth displays an interesting pattern: It starts fast, exhibiting the rapid growth characteristic of exponential models. As time passes, it slows in response to constraints such as limited resources or reallocation of energy. The growth continues to slow until it reaches a limit, called capacity. When the growth describes a population,…

Dynamic metabolic modeling of heterotrophic and mixotrophic microalgal growth on fermentative wastes.

Directory of Open Access Journals (Sweden)

Caroline Baroukh

2017-06-01

Full Text Available Microalgae are promising microorganisms for the production of numerous molecules of interest, such as pigments, proteins or triglycerides that can be turned into biofuels. Heterotrophic or mixotrophic growth on fermentative wastes represents an interesting approach to achieving higher biomass concentrations, while reducing cost and improving the environmental footprint. Fermentative wastes generally consist of a blend of diverse molecules and it is thus crucial to understand microalgal metabolism in such conditions, where switching between substrates might occur. Metabolic modeling has proven to be an efficient tool for understanding metabolism and guiding the optimization of biomass or target molecule production. Here, we focused on the metabolism of Chlorella sorokiniana growing heterotrophically and mixotrophically on acetate and butyrate. The metabolism was represented by 172 metabolic reactions. The DRUM modeling framework with a mildly relaxed quasi-steady-state assumption was used to account for the switching between substrates and the presence of light. Nine experiments were used to calibrate the model and nine experiments for the validation. The model efficiently predicted the experimental data, including the transient behavior during heterotrophic, autotrophic, mixotrophic and diauxic growth. It shows that an accurate model of metabolism can now be constructed, even in dynamic conditions, with the presence of several carbon substrates. It also opens new perspectives for the heterotrophic and mixotrophic use of microalgae, especially for biofuel production from wastes.

Evaluating Non-Linear Regression Models in Analysis of Persian Walnut Fruit Growth

Directory of Open Access Journals (Sweden)

I. Karamatlou

2016-02-01

Full Text Available Introduction: Persian walnut (Juglans regia L. is a large, wind-pollinated, monoecious, dichogamous, long lived, perennial tree cultivated for its high quality wood and nuts throughout the temperate regions of the world. Growth model methodology has been widely used in the modeling of plant growth. Mathematical models are important tools to study the plant growth and agricultural systems. These models can be applied for decision-making anddesigning management procedures in horticulture. Through growth analysis, planning for planting systems, fertilization, pruning operations, harvest time as well as obtaining economical yield can be more accessible.Non-linear models are more difficult to specify and estimate than linear models. This research was aimed to studynon-linear regression models based on data obtained from fruit weight, length and width. Selecting the best models which explain that fruit inherent growth pattern of Persian walnut was a further goal of this study. Materials and Methods: The experimental material comprising 14 Persian walnut genotypes propagated by seed collected from a walnut orchard in Golestan province, Minoudasht region, Iran, at latitude 37◦04’N; longitude 55◦32’E; altitude 1060 m, in a silt loam soil type. These genotypes were selected as a representative sampling of the many walnut genotypes available throughout the Northeastern Iran. The age range of walnut trees was 30 to 50 years. The annual mean temperature at the location is16.3◦C, with annual mean rainfall of 690 mm.The data used here is the average of walnut fresh fruit and measured withgram/millimeter/day in2011.According to the data distribution pattern, several equations have been proposed to describesigmoidal growth patterns. Here, we used double-sigmoid and logistic–monomolecular models to evaluate fruit growth based on fruit weight and4different regression models in cluding Richards, Gompertz, Logistic and Exponential growth for evaluation

A Comparison of Modeling Approaches in Simulating Chlorinated Ethene Removal in a Constructed Wetland by a Microbial Consortia

National Research Council Canada - National Science Library

Campbell, Jason

2002-01-01

... of the modeling approaches affect simulation results. Concepts like microbial growth in the form of a biofilm and spatially varying contaminant concentrations bring the validity of the CSTR assumption into question...

Modelling of strongly coupled particle growth and aggregation

International Nuclear Information System (INIS)

Gruy, F; Touboul, E

2013-01-01

The mathematical modelling of the dynamics of particle suspension is based on the population balance equation (PBE). PBE is an integro-differential equation for the population density that is a function of time t, space coordinates and internal parameters. Usually, the particle is characterized by a unique parameter, e.g. the matter volume v. PBE consists of several terms: for instance, the growth rate and the aggregation rate. So, the growth rate is a function of v and t. In classical modelling, the growth and the aggregation are independently considered, i.e. they are not coupled. However, current applications occur where the growth and the aggregation are coupled, i.e. the change of the particle volume with time is depending on its initial value v 0 , that in turn is related to an aggregation event. As a consequence, the dynamics of the suspension does not obey the classical Von Smoluchowski equation. This paper revisits this problem by proposing a new modelling by using a bivariate PBE (with two internal variables: v and v 0 ) and by solving the PBE by means of a numerical method and Monte Carlo simulations. This is applied to a physicochemical system with a simple growth law and a constant aggregation kernel.

Thermal models pertaining to continental growth

International Nuclear Information System (INIS)

Morgan, P.; Ashwal, L.

1988-01-01

Thermal models are important to understanding continental growth as the genesis, stabilization, and possible recycling of continental crust are closely related to the tectonic processes of the earth which are driven primarily by heat. The thermal energy budget of the earth was slowly decreasing since core formation, and thus the energy driving the terrestrial tectonic engine was decreasing. This fundamental observation was used to develop a logic tree defining the options for continental growth throughout earth history

Models of the Economic Growth and their Relevance

Directory of Open Access Journals (Sweden)

Nicolae MOROIANU

2012-06-01

Full Text Available Until few years ago, the economic growth was something perfect normal, part of an era marked by the transformation speed. Normality itself has been transformed and we currently are influenced by other rules, unknown yet, which should answer the question: “How do we return to the economic growth?” The economic growth and the models aiming to solve this problem concern the economic history even since its beginnings. In this paper we would like to find out what is the relevance that the well-known macroeconomic models still have and which might be their applicability level in a framework created by a black swan event type.

Do persistently fast-growing juveniles contribute disproportionately to population growth? A new analysis tool for matrix models and its application to rainforest trees.

Science.gov (United States)

Zuidema, Pieter A; Brienen, Roel J W; During, Heinjo J; Güneralp, Burak

2009-11-01

Plants and animals often exhibit strong and persistent growth variation among individuals within a species. Persistently fast-growing individuals have a higher chance of reaching reproductive size, do so at a younger age, and therefore contribute disproportionately to population growth (lambda). Here we introduce a new approach to quantify this "fast-growth effect." We propose using age-size-structured matrix models in which persistently fast and slow growers are distinguished as they occur in relatively young and old age classes for a given size category. Life-cycle pathways involving fast growth can then be identified, and their contribution to lambda is quantified through loop analysis. We applied this approach to an example species, the tropical rainforest tree Cedrela odorata, that shows persistent growth variation among individuals. Loop analysis showed that juvenile trees reaching the 10-cm diameter class at below-median age contributed twice as much to lambda as slow juvenile growers. Fast growth to larger-diameter categories also contributed disproportionately to lambda. The results were robust to changes in parameter values and life-history trade-offs. These results show that the fast-growth effect can be strong in long-lived species. Persistent growth differences among individuals should therefore be accommodated for in demographic models and life-history studies.

Stochastic Differential Equation-Based Flexible Software Reliability Growth Model

Directory of Open Access Journals (Sweden)

P. K. Kapur

2009-01-01

Full Text Available Several software reliability growth models (SRGMs have been developed by software developers in tracking and measuring the growth of reliability. As the size of software system is large and the number of faults detected during the testing phase becomes large, so the change of the number of faults that are detected and removed through each debugging becomes sufficiently small compared with the initial fault content at the beginning of the testing phase. In such a situation, we can model the software fault detection process as a stochastic process with continuous state space. In this paper, we propose a new software reliability growth model based on Itô type of stochastic differential equation. We consider an SDE-based generalized Erlang model with logistic error detection function. The model is estimated and validated on real-life data sets cited in literature to show its flexibility. The proposed model integrated with the concept of stochastic differential equation performs comparatively better than the existing NHPP-based models.

Investigation of various growth mechanisms of solid tumour growth within the linear-quadratic model for radiotherapy

International Nuclear Information System (INIS)

McAneney, H; O'Rourke, S F C

2007-01-01

The standard linear-quadratic survival model for radiotherapy is used to investigate different schedules of radiation treatment planning to study how these may be affected by different tumour repopulation kinetics between treatments. The laws for tumour cell repopulation include the logistic and Gompertz models and this extends the work of Wheldon et al (1977 Br. J. Radiol. 50 681), which was concerned with the case of exponential re-growth between treatments. Here we also consider the restricted exponential model. This has been successfully used by Panetta and Adam (1995 Math. Comput. Modelling 22 67) in the case of chemotherapy treatment planning.Treatment schedules investigated include standard fractionation of daily treatments, weekday treatments, accelerated fractionation, optimized uniform schedules and variation of the dosage and α/β ratio, where α and β are radiobiological parameters for the tumour tissue concerned. Parameters for these treatment strategies are extracted from the literature on advanced head and neck cancer, prostate cancer, as well as radiosensitive parameters. Standardized treatment protocols are also considered. Calculations based on the present analysis indicate that even with growth laws scaled to mimic initial growth, such that growth mechanisms are comparable, variation in survival fraction to orders of magnitude emerged. Calculations show that the logistic and exponential models yield similar results in tumour eradication. By comparison the Gompertz model calculations indicate that tumours described by this law result in a significantly poorer prognosis for tumour eradication than either the exponential or logistic models. The present study also shows that the faster the tumour growth rate and the higher the repair capacity of the cell line, the greater the variation in outcome of the survival fraction. Gaps in treatment, planned or unplanned, also accentuate the differences of the survival fraction given alternative growth

A joint individual-based model coupling growth and mortality reveals that tree vigor is a key component of tropical forest dynamics.

Science.gov (United States)

Aubry-Kientz, Mélaine; Rossi, Vivien; Boreux, Jean-Jacques; Hérault, Bruno

2015-06-01

Tree vigor is often used as a covariate when tree mortality is predicted from tree growth in tropical forest dynamic models, but it is rarely explicitly accounted for in a coherent modeling framework. We quantify tree vigor at the individual tree level, based on the difference between expected and observed growth. The available methods to join nonlinear tree growth and mortality processes are not commonly used by forest ecologists so that we develop an inference methodology based on an MCMC approach, allowing us to sample the parameters of the growth and mortality model according to their posterior distribution using the joint model likelihood. We apply our framework to a set of data on the 20-year dynamics of a forest in Paracou, French Guiana, taking advantage of functional trait-based growth and mortality models already developed independently. Our results showed that growth and mortality are intimately linked and that the vigor estimator is an essential predictor of mortality, highlighting that trees growing more than expected have a far lower probability of dying. Our joint model methodology is sufficiently generic to be used to join two longitudinal and punctual linked processes and thus may be applied to a wide range of growth and mortality models. In the context of global changes, such joint models are urgently needed in tropical forests to analyze, and then predict, the effects of the ongoing changes on the tree dynamics in hyperdiverse tropical forests.

Mathematical foundations of the dendritic growth models.

Science.gov (United States)

Villacorta, José A; Castro, Jorge; Negredo, Pilar; Avendaño, Carlos

2007-11-01

At present two growth models describe successfully the distribution of size and topological complexity in populations of dendritic trees with considerable accuracy and simplicity, the BE model (Van Pelt et al. in J. Comp. Neurol. 387:325-340, 1997) and the S model (Van Pelt and Verwer in Bull. Math. Biol. 48:197-211, 1986). This paper discusses the mathematical basis of these models and analyzes quantitatively the relationship between the BE model and the S model assumed in the literature by developing a new explicit equation describing the BES model (a dendritic growth model integrating the features of both preceding models; Van Pelt et al. in J. Comp. Neurol. 387:325-340, 1997). In numerous studies it is implicitly presupposed that the S model is conditionally linked to the BE model (Granato and Van Pelt in Brain Res. Dev. Brain Res. 142:223-227, 2003; Uylings and Van Pelt in Network 13:397-414, 2002; Van Pelt, Dityatev and Uylings in J. Comp. Neurol. 387:325-340, 1997; Van Pelt and Schierwagen in Math. Biosci. 188:147-155, 2004; Van Pelt and Uylings in Network. 13:261-281, 2002; Van Pelt, Van Ooyen and Uylings in Modeling Dendritic Geometry and the Development of Nerve Connections, pp 179, 2000). In this paper we prove the non-exactness of this assumption, quantify involved errors and determine the conditions under which the BE and S models can be separately used instead of the BES model, which is more exact but considerably more difficult to apply. This study leads to a novel expression describing the BE model in an analytical closed form, much more efficient than the traditional iterative equation (Van Pelt et al. in J. Comp. Neurol. 387:325-340, 1997) in many neuronal classes. Finally we propose a new algorithm in order to obtain the values of the parameters of the BE model when this growth model is matched to experimental data, and discuss its advantages and improvements over the more commonly used procedures.

Latent Growth Modeling of nursing care dependency of acute neurological inpatients.

Science.gov (United States)

Piredda, M; Ghezzi, V; De Marinis, M G; Palese, A

2015-01-01

Longitudinal three-time point study, addressing how neurological adult patient care dependency varies from the admission time to the 3rd day of acute hospitalization. Nursing care dependency was measured with the Care Dependency Scale (CDS) and a Latent Growth Modeling approach was used to analyse the CDS trend in 124 neurosurgical and stroke inpatients. Care dependence followed a decreasing linear trend. Results can help nurse-managers planning an appropriate amount of nursing care for acute neurological patients during their initial stage of hospitalization. Further studies are needed aimed at investigating the determinants of nursing care dependence during the entire in-hospital stay.

Predicting growth of the healthy infant using a genome scale metabolic model.

Science.gov (United States)

Nilsson, Avlant; Mardinoglu, Adil; Nielsen, Jens

2017-01-01

An estimated 165 million children globally have stunted growth, and extensive growth data are available. Genome scale metabolic models allow the simulation of molecular flux over each metabolic enzyme, and are well adapted to analyze biological systems. We used a human genome scale metabolic model to simulate the mechanisms of growth and integrate data about breast-milk intake and composition with the infant's biomass and energy expenditure of major organs. The model predicted daily metabolic fluxes from birth to age 6 months, and accurately reproduced standard growth curves and changes in body composition. The model corroborates the finding that essential amino and fatty acids do not limit growth, but that energy is the main growth limiting factor. Disruptions to the supply and demand of energy markedly affected the predicted growth, indicating that elevated energy expenditure may be detrimental. The model was used to simulate the metabolic effect of mineral deficiencies, and showed the greatest growth reduction for deficiencies in copper, iron, and magnesium ions which affect energy production through oxidative phosphorylation. The model and simulation method were integrated to a platform and shared with the research community. The growth model constitutes another step towards the complete representation of human metabolism, and may further help improve the understanding of the mechanisms underlying stunting.

Implicit Theories about Intelligence and Growth (Personal Best) Goals: Exploring Reciprocal Relationships

Science.gov (United States)

Martin, Andrew J.

2015-01-01

Background: There has been increasing interest in growth approaches to students' academic development, including value-added models, modelling of academic trajectories, growth motivation orientations, growth mindsets, and growth goals. Aims: This study sought to investigate the relationships between implicit theories about intelligence…

Another brick in the cell wall: biosynthesis dependent growth model.

Directory of Open Access Journals (Sweden)

Adelin Barbacci

Full Text Available Expansive growth of plant cell is conditioned by the cell wall ability to extend irreversibly. This process is possible if (i a tensile stress is developed in the cell wall due to the coupling effect between turgor pressure and the modulation of its mechanical properties through enzymatic and physicochemical reactions and if (ii new cell wall elements can be synthesized and assembled to the existing wall. In other words, expansive growth is the result of coupling effects between mechanical, thermal and chemical energy. To have a better understanding of this process, models must describe the interplay between physical or mechanical variable with biological events. In this paper we propose a general unified and theoretical framework to model growth in function of energy forms and their coupling. This framework is based on irreversible thermodynamics. It is then applied to model growth of the internodal cell of Chara corallina modulated by changes in pressure and temperature. The results describe accurately cell growth in term of length increment but also in term of cell pectate biosynthesis and incorporation to the expanding wall. Moreover, the classical growth model based on Lockhart's equation such as the one proposed by Ortega, appears as a particular and restrictive case of the more general growth equation developed in this paper.

A Modelling Approach for Integrated Planning of Port Capacity- Trade-Offs in Rotterdam Investment Planning

Directory of Open Access Journals (Sweden)

Sander Dekker

2006-03-01

Full Text Available This paper presents a modelling approach for planning ofport capacity. The approach integrates port commercial andpublic interests. It further incorporates route competition andautonomous demand growth. It is applied to port expansion,which can be considered as a strategy for an individual port todeal with route competition. The basis for solving this planningproblem comprises an analysis of port demand and supply in apartial equilibrium model. With such an approach, the reactionof a single port on the change in a transport network comprisingalternative routes to a hinterland destination can be simulated.To establish the optimal expansion strategy, port expansion iscombined with congestion pricing. This is used for the simultaneousdetermination of 1 optimal expansion size, and 2 investmentrecovery period. The modelling approach will be appliedto Rotterdam port focusing on port expansion by means ofland reclamation. The scenmio of the entry of a new competingroute via the Italian port Gioia Tauro is used to address sometrade-offs in Rotterdam investment planning.

Piecewise Linear-Linear Latent Growth Mixture Models with Unknown Knots

Science.gov (United States)

Kohli, Nidhi; Harring, Jeffrey R.; Hancock, Gregory R.

2013-01-01

Latent growth curve models with piecewise functions are flexible and useful analytic models for investigating individual behaviors that exhibit distinct phases of development in observed variables. As an extension of this framework, this study considers a piecewise linear-linear latent growth mixture model (LGMM) for describing segmented change of…

Mechanical model for filament buckling and growth by phase ordering.

Science.gov (United States)

Rey, Alejandro D; Abukhdeir, Nasser M

2008-02-05

A mechanical model of open filament shape and growth driven by phase ordering is formulated. For a given phase-ordering driving force, the model output is the filament shape evolution and the filament end-point kinematics. The linearized model for the slope of the filament is the Cahn-Hilliard model of spinodal decomposition, where the buckling corresponds to concentration fluctuations. Two modes are predicted: (i) sequential growth and buckling and (ii) simultaneous buckling and growth. The relation among the maximum buckling rate, filament tension, and matrix viscosity is given. These results contribute to ongoing work in smectic A filament buckling.

Force-induced bone growth and adaptation: A system theoretical approach to understanding bone mechanotransduction

International Nuclear Information System (INIS)

Maldonado, Solvey; Findeisen, Rolf

2010-01-01

The modeling, analysis, and design of treatment therapies for bone disorders based on the paradigm of force-induced bone growth and adaptation is a challenging task. Mathematical models provide, in comparison to clinical, medical and biological approaches an structured alternative framework to understand the concurrent effects of the multiple factors involved in bone remodeling. By now, there are few mathematical models describing the appearing complex interactions. However, the resulting models are complex and difficult to analyze, due to the strong nonlinearities appearing in the equations, the wide range of variability of the states, and the uncertainties in parameters. In this work, we focus on analyzing the effects of changes in model structure and parameters/inputs variations on the overall steady state behavior using systems theoretical methods. Based on an briefly reviewed existing model that describes force-induced bone adaptation, the main objective of this work is to analyze the stationary behavior and to identify plausible treatment targets for remodeling related bone disorders. Identifying plausible targets can help in the development of optimal treatments combining both physical activity and drug-medication. Such treatments help to improve/maintain/restore bone strength, which deteriorates under bone disorder conditions, such as estrogen deficiency.

Hyperbolastic modeling of tumor growth with a combined treatment of iodoacetate and dimethylsulphoxide

International Nuclear Information System (INIS)

Eby, Wayne M; Tabatabai, Mohammad A; Bursac, Zoran

2010-01-01

An understanding of growth dynamics of tumors is important in understanding progression of cancer and designing appropriate treatment strategies. We perform a comparative study of the hyperbolastic growth models with the Weibull and Gompertz models, which are prevalently used in the field of tumor growth. The hyperbolastic growth models H1, H2, and H3 are applied to growth of solid Ehrlich carcinoma under several different treatments. These are compared with results from Gompertz and Weibull models for the combined treatment. The growth dynamics of the solid Ehrlich carcinoma with the combined treatment are studied using models H1, H2, and H3, and the models are highly accurate in representing the growth. The growth dynamics are also compared with the untreated tumor, the tumor treated with only iodoacetate, and the tumor treated with only dimethylsulfoxide, and the combined treatment. The hyperbolastic models prove to be effective in representing and analyzing the growth dynamics of the solid Ehrlich carcinoma. These models are more precise than Gompertz and Weibull and show less error for this data set. The precision of H3 allows for its use in a comparative analysis of tumor growth rates between the various treatments

Development and validation of an extensive growth and growth boundary model for psychrotolerant Lactobacillus spp. in seafood and meat products

DEFF Research Database (Denmark)

Mejlholm, Ole; Dalgaard, Paw

2013-01-01

A new and extensive growth and growth boundary model for psychrotolerant Lactobacillus spp. was developed and validated for processed and unprocessed products of seafood and meat. The new model was developed by refitting and expanding an existing cardinal parameter model for growth and the growth...... of psychrotolerant Lactobacillus spp. was clearly demonstrated. The new model can be used to predict growth of psychrotolerant Lactobacillus spp. in seafood and meat products e.g. prediction of the time to a critical cell concentration of bacteria is considered useful for establishing the shelf life. In addition...... boundary of lactic acid bacteria (LAB) in processed seafood (O. Mejlholm and P. Dalgaard, J. Food Prot. 70. 2485–2497, 2007). Initially, to estimate values for the maximum specific growth rate at the reference temperature of 25°C (μref) and the theoretical minimum temperature that prevents growth...

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

Science.gov (United States)

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

2014-09-01

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

A DYNAMICAL SYSTEM APPROACH IN MODELING TECHNOLOGY TRANSFER

Directory of Open Access Journals (Sweden)

Hennie Husniah

2016-05-01

Full Text Available In this paper we discuss a mathematical model of two parties technology transfer from a leader to a follower. The model is reconstructed via dynamical system approach from a known standard Raz and Assa model and we found some important conclusion which have not been discussed in the original model. The model assumes that in the absence of technology transfer from a leader to a follower, both the leader and the follower have a capability to grow independently with a known upper limit of the development. We obtain a rich mathematical structure of the steady state solution of the model. We discuss a special situation in which the upper limit of the technological development of the follower is higher than that of the leader, but the leader has started earlier than the follower in implementing the technology. In this case we show a paradox stating that the follower is unable to reach its original upper limit of the technological development could appear whenever the transfer rate is sufficiently high.  We propose a new model to increase realism so that any technological transfer rate could only has a positive effect in accelerating the rate of growth of the follower in reaching its original upper limit of the development.

Self-similar measures in multi-sector endogenous growth models

International Nuclear Information System (INIS)

La Torre, Davide; Marsiglio, Simone; Mendivil, Franklin; Privileggi, Fabio

2015-01-01

We analyze two types of stochastic discrete time multi-sector endogenous growth models, namely a basic Uzawa–Lucas (1965, 1988) model and an extended three-sector version as in La Torre and Marsiglio (2010). As in the case of sustained growth the optimal dynamics of the state variables are not stationary, we focus on the dynamics of the capital ratio variables, and we show that, through appropriate log-transformations, they can be converted into affine iterated function systems converging to an invariant distribution supported on some (possibly fractal) compact set. This proves that also the steady state of endogenous growth models—i.e., the stochastic balanced growth path equilibrium—might have a fractal nature. We also provide some sufficient conditions under which the associated self-similar measures turn out to be either singular or absolutely continuous (for the three-sector model we only consider the singularity).

Modeling and simulation of Si crystal growth from melt

Energy Technology Data Exchange (ETDEWEB)

Liu, Lijun; Liu, Xin; Li, Zaoyang [National Engineering Research Center for Fluid Machinery and Compressors, School of Energy and Power Engineering, Xi' an Jiaotong University, Xi' an, Shaanxi 710049 (China); Miyazawa, Hiroaki; Nakano, Satoshi; Kakimoto, Koichi [Research Institute for Applied Mechanics, Kyushu University, Kasuga 816-8580 (Japan)

2009-07-01

A numerical simulator was developed with a global model of heat transfer for any crystal growth taking place at high temperature. Convective, conductive and radiative heat transfers in the furnace are solved together in a conjugated way by a finite volume method. A three-dimensional (3D) global model was especially developed for simulation of heat transfer in any crystal growth with 3D features. The model enables 3D global simulation be conducted with moderate requirement of computer resources. The application of this numerical simulator to a CZ growth and a directional solidification process for Si crystals, the two major production methods for crystalline Si for solar cells, was introduced. Some typical results were presented, showing the importance and effectiveness of numerical simulation in analyzing and improving these kinds of Si crystal growth processes from melt. (copyright 2009 WILEY-VCH Verlag GmbH and Co. KGaA, Weinheim) (orig.)

Leptin administration affects growth and skeletal development in a rat intrauterine growth restriction model: preliminary study.

Science.gov (United States)

Bar-El Dadon, Shimrit; Shahar, Ron; Katalan, Vered; Monsonego-Ornan, Efrat; Reifen, Ram

2011-09-01

Skeletal abnormalities are one of the hallmarks of growth delay during gestation. The aim of this study was to determine changes induced by leptin in skeletal growth and development in a rat model of intrauterine growth retardation (IUGR) and to elucidate the possible underlying mechanisms. Intrauterine growth retardation was induced prepartum and the effects of leptin to mothers prenatally or to offspring postnatally were studied. Radii were harvested and tested mechanically and structurally. Tibias were evaluated for growth-plate morphometry. On day 40 postpartum, total bone length and mineral density and tibial growth-plate width and numbers of cells within its zones of offspring treated with leptin were significantly greater than in the control group. Postnatal leptin administration in an IUGR model improves the structural properties and elongation rate of bone. These findings could pave the way to preventing some phenotypic presentations of IUGR. Copyright © 2011 Elsevier Inc. All rights reserved.

Neutral endopeptidase-resistant C-type natriuretic peptide variant represents a new therapeutic approach for treatment of fibroblast growth factor receptor 3-related dwarfism.

Science.gov (United States)

Wendt, Daniel J; Dvorak-Ewell, Melita; Bullens, Sherry; Lorget, Florence; Bell, Sean M; Peng, Jeff; Castillo, Sianna; Aoyagi-Scharber, Mika; O'Neill, Charles A; Krejci, Pavel; Wilcox, William R; Rimoin, David L; Bunting, Stuart

2015-04-01

Achondroplasia (ACH), the most common form of human dwarfism, is caused by an activating autosomal dominant mutation in the fibroblast growth factor receptor-3 gene. Genetic overexpression of C-type natriuretic peptide (CNP), a positive regulator of endochondral bone growth, prevents dwarfism in mouse models of ACH. However, administration of exogenous CNP is compromised by its rapid clearance in vivo through receptor-mediated and proteolytic pathways. Using in vitro approaches, we developed modified variants of human CNP, resistant to proteolytic degradation by neutral endopeptidase, that retain the ability to stimulate signaling downstream of the CNP receptor, natriuretic peptide receptor B. The variants tested in vivo demonstrated significantly longer serum half-lives than native CNP. Subcutaneous administration of one of these CNP variants (BMN 111) resulted in correction of the dwarfism phenotype in a mouse model of ACH and overgrowth of the axial and appendicular skeletons in wild-type mice without observable changes in trabecular and cortical bone architecture. Moreover, significant growth plate widening that translated into accelerated bone growth, at hemodynamically tolerable doses, was observed in juvenile cynomolgus monkeys that had received daily subcutaneous administrations of BMN 111. BMN 111 was well tolerated and represents a promising new approach for treatment of patients with ACH. Copyright © 2015 by The American Society for Pharmacology and Experimental Therapeutics.

The relationship between CO2 emission, energy consumption and economic growth in Malaysia: a three-way linkage approach.

Science.gov (United States)

Sulaiman, Chindo; Abdul-Rahim, A S

2017-11-01

This study examines the three-way linkage relationships between CO 2 emission, energy consumption and economic growth in Malaysia, covering the 1975-2015 period. An autoregressive distributed lag approach was employed to achieve the objective of the study and gauged by dynamic ordinary least squares. Additionally, vector error correction model, variance decompositions and impulse response functions were employed to further examine the relationship between the interest variables. The findings show that economic growth is neither influenced by energy consumption nor by CO 2 emission. Energy consumption is revealed to be an increasing function of CO 2 emission. Whereas, CO 2 emission positively and significantly depends on energy consumption and economic growth. This implies that CO 2 emission increases with an increase in both energy consumption and economic growth. Conclusively, the main drivers of CO 2 emission in Malaysia are proven to be energy consumption and economic growth. Therefore, renewable energy sources ought to be considered by policy makers to curb emission from the current non-renewable sources. Wind and biomass can be explored as they are viable sources. Energy efficiency and savings should equally be emphasised and encouraged by policy makers. Lastly, growth-related policies that target emission reduction are also recommended.

A Proposed Model for Protein Crystal Nucleation and Growth

Science.gov (United States)

Pusey, Marc; Curreri, Peter A. (Technical Monitor)

2002-01-01

How does one take a molecule, strongly asymmetric in both shape and charge distribution, and assemble it into a crystal? We propose a model for the nucleation and crystal growth process for tetragonal lysozyme, based upon fluorescence, light, neutron, and X-ray scattering data, size exclusion chromatography experiments, dialysis kinetics, AFM, and modeling of growth rate data, from this and other laboratories. The first species formed is postulated to be a 'head to side' dimer. Through repeating associations involving the same intermolecular interactions this grows to a 4(sub 3) helix structure, that in turn serves as the basic unit for nucleation and subsequent crystal growth. High salt attenuates surface charges while promoting hydrophobic interactions. Symmetry facilitates subsequent helix-helix self-association. Assembly stability is enhanced when a four helix structure is obtained, with each bound to two neighbors. Only two unique interactions are required. The first are those for helix formation, where the dominant interaction is the intermolecular bridging anion. The second is the anti-parallel side-by-side helix-helix interaction, guided by alternating pairs of symmetry related salt bridges along each side. At this stage all eight unique positions of the P4(sub3)2(sub 1),2(sub 1) unit cell are filled. The process is one of a) attenuating the most strongly interacting groups, such that b) the molecules begin to self-associate in defined patterns, so that c) symmetry is obtained, which d) propagates as a growing crystal. Simple and conceptually obvious in hindsight, this tells much about what we are empirically doing when we crystallize macromolecules. By adjusting the growth parameters we are empirically balancing the intermolecular interactions, preferentially attenuating the dominant strong (for lysozyme the charged groups) while strengthening the lesser strong (hydrophobic) interactions. In the general case for proteins the lack of a singularly defined

Markov and semi-Markov switching linear mixed models used to identify forest tree growth components.

Science.gov (United States)

Chaubert-Pereira, Florence; Guédon, Yann; Lavergne, Christian; Trottier, Catherine

2010-09-01

Tree growth is assumed to be mainly the result of three components: (i) an endogenous component assumed to be structured as a succession of roughly stationary phases separated by marked change points that are asynchronous among individuals, (ii) a time-varying environmental component assumed to take the form of synchronous fluctuations among individuals, and (iii) an individual component corresponding mainly to the local environment of each tree. To identify and characterize these three components, we propose to use semi-Markov switching linear mixed models, i.e., models that combine linear mixed models in a semi-Markovian manner. The underlying semi-Markov chain represents the succession of growth phases and their lengths (endogenous component) whereas the linear mixed models attached to each state of the underlying semi-Markov chain represent-in the corresponding growth phase-both the influence of time-varying climatic covariates (environmental component) as fixed effects, and interindividual heterogeneity (individual component) as random effects. In this article, we address the estimation of Markov and semi-Markov switching linear mixed models in a general framework. We propose a Monte Carlo expectation-maximization like algorithm whose iterations decompose into three steps: (i) sampling of state sequences given random effects, (ii) prediction of random effects given state sequences, and (iii) maximization. The proposed statistical modeling approach is illustrated by the analysis of successive annual shoots along Corsican pine trunks influenced by climatic covariates. © 2009, The International Biometric Society.

Evaluating the Predictive Value of Growth Prediction Models

Science.gov (United States)

Murphy, Daniel L.; Gaertner, Matthew N.

2014-01-01

This study evaluates four growth prediction models--projection, student growth percentile, trajectory, and transition table--commonly used to forecast (and give schools credit for) middle school students' future proficiency. Analyses focused on vertically scaled summative mathematics assessments, and two performance standards conditions (high…

Crossover from Nonequilibrium Fractal Growth to Equilibrium Compact Growth

DEFF Research Database (Denmark)

Sørensen, Erik Schwartz; Fogedby, Hans C.; Mouritsen, Ole G.

1988-01-01

Solidification controlled by vacancy diffusion is studied by Monte Carlo simulations of a two-dimensional Ising model defined by a Hamiltonian which models a thermally driven fluid-solid phase transition. The nonequilibrium morphology of the growing solid is studied as a function of time as the s...... as the system relaxes into equilibrium described by a temperature. At low temperatures the model exhibits fractal growth at early times and crossover to compact solidification as equilibrium is approached....

Crack initiation and growth in welded structures

International Nuclear Information System (INIS)

Assire, A.

2000-01-01

This work concerns the remaining life assessment of a structure containing initial defects of manufacturing. High temperature crack initiation and growth are studied for austenitic stainless steels, and defect assessment methods are improved in order to take into account welded structures. For these one, the probability to have a defect is significant. Two kinds of approaches are commonly used for defect assessment analysis. Fracture mechanics global approach with an energetic criterion, and local approach with a model taking into account the physical damage mechanism. For both approaches mechanical fields (stress and strain) have to be computed everywhere within the structure. Then, Finite Element computation is needed. The first part of the thesis concerns the identification of non linear kinematic and isotropic constitutive models. A pseudo-analytical method is proposed for a 'Two Inelastic Strain' model. This method provides a strategy of identification with a mechanical meaning, and this enables to associate each parameter to a physical phenomenon. Existing identifications are improved for cyclic plasticity and creep on a large range of stress levels. The second part concerns high temperature crack initiation and growth in welded structures. Finite Element analysis on plate and tube experimental configuration enable to understand the phenomenons of interaction between base metal and weld metal under mechanical and thermal loading. Concerning global approach, criteria based on C* parameter (Rice integral for visco-plasticity) are used. Finite Element computations underline the fact that for a defect located in the weld metal, C* values strongly depend on the base metal creep strain rate, because widespread visco-plasticity is located in both metals. A simplified method, based on the reference stress approach, is proposed and validated with Finite Element results. Creep crack growth simplified assessment is a quite good validation of the experimental results

A spatial error model with continuous random effects and an application to growth convergence

Science.gov (United States)

Laurini, Márcio Poletti

2017-10-01

We propose a spatial error model with continuous random effects based on Matérn covariance functions and apply this model for the analysis of income convergence processes (β -convergence). The use of a model with continuous random effects permits a clearer visualization and interpretation of the spatial dependency patterns, avoids the problems of defining neighborhoods in spatial econometrics models, and allows projecting the spatial effects for every possible location in the continuous space, circumventing the existing aggregations in discrete lattice representations. We apply this model approach to analyze the economic growth of Brazilian municipalities between 1991 and 2010 using unconditional and conditional formulations and a spatiotemporal model of convergence. The results indicate that the estimated spatial random effects are consistent with the existence of income convergence clubs for Brazilian municipalities in this period.

Optimal Patent Life in a Variety-Expansion Growth Model

OpenAIRE

Lin, Hwan C.

2013-01-01

This paper presents more channels through which the optimal patent life is determined in a R&D-based endogenous growth model that permits growth of new varieties of consumer goods over time. Its modeling features include an endogenous hazard rate facing incumbent monopolists, the prevalence of research congestion, and the aggregate welfare importance of product differentiation. As a result, a patent’s effective life is endogenized and less than its legal life. The model is calibrated to a glo...

Residual Structures in Latent Growth Curve Modeling

Science.gov (United States)

Grimm, Kevin J.; Widaman, Keith F.

2010-01-01

Several alternatives are available for specifying the residual structure in latent growth curve modeling. Two specifications involve uncorrelated residuals and represent the most commonly used residual structures. The first, building on repeated measures analysis of variance and common specifications in multilevel models, forces residual variances…

A Bayesian approach to identifying and compensating for model misspecification in population models.

Science.gov (United States)

Thorson, James T; Ono, Kotaro; Munch, Stephan B

2014-02-01

State-space estimation methods are increasingly used in ecology to estimate productivity and abundance of natural populations while accounting for variability in both population dynamics and measurement processes. However, functional forms for population dynamics and density dependence often will not match the true biological process, and this may degrade the performance of state-space methods. We therefore developed a Bayesian semiparametric state-space model, which uses a Gaussian process (GP) to approximate the population growth function. This offers two benefits for population modeling. First, it allows data to update a specified "prior" on the population growth function, while reverting to this prior when data are uninformative. Second, it allows variability in population dynamics to be decomposed into random errors around the population growth function ("process error") and errors due to the mismatch between the specified prior and estimated growth function ("model error"). We used simulation modeling to illustrate the utility of GP methods in state-space population dynamics models. Results confirmed that the GP model performs similarly to a conventional state-space model when either (1) the prior matches the true process or (2) data are relatively uninformative. However, GP methods improve estimates of the population growth function when the function is misspecified. Results also demonstrated that the estimated magnitude of "model error" can be used to distinguish cases of model misspecification. We conclude with a discussion of the prospects for GP methods in other state-space models, including age and length-structured, meta-analytic, and individual-movement models.

Tourism and Economic Growth in Sri Lanka: An ARDL Bounds Testing Approach

OpenAIRE

P. Srinivasan; Santhosh Kumar P. K; L. Ganesh

2012-01-01

The purpose of the study is to examine the impact of tourism on economic growth in Sri Lanka through the Autoregressive Distributed Lag (ARDL) bounds testing approach. The analysis was carried out for the period from 1969 to 2009. By and large, our analysis reveals that the tourism has a positive impact on economic growth in Sri Lanka both in the short-run and long-run. Hence, it is crucial for the Sri Lankan government to achieve unification and stability by focusing on political solutions t...

A placenta clinic approach to the diagnosis and management of fetal growth restriction.

Science.gov (United States)

Kingdom, John C; Audette, Melanie C; Hobson, Sebastian R; Windrim, Rory C; Morgen, Eric

2018-02-01

Effective detection and management of fetal growth restriction is relevant to all obstetric care providers. Models of best practice to care for these patients and their families continue to evolve. Since much of the disease burden in fetal growth restriction originates in the placenta, the concept of a multidisciplinary placenta clinic program, managed primarily within a maternal-fetal medicine division, has gained popularity. In this context, fetal growth restriction is merely one of many placenta-related disorders that can benefit from an interdisciplinary approach, incorporating expertise from specialist perinatal ultrasound and magnetic resonance imaging, reproductive genetics, neonatal pediatrics, internal medicine subspecialties, perinatal pathology, and nursing. The accurate diagnosis and prognosis for women with fetal growth restriction is established by comprehensive clinical review and detailed sonographic evaluation of the fetus, combined with uterine artery Doppler and morphologic assessment of the placenta. Diagnostic accuracy for placenta-mediated fetal growth restriction may be enhanced by quantification of maternal serum biomarkers including placenta growth factor alone or combined with soluble fms-like tyrosine kinase-1. Uterine artery Doppler is typically abnormal in most instances of early-onset fetal growth restriction and is associated with coexistent preeclampsia and underlying maternal vascular malperfusion pathology of the placenta. By contrast, rare but potentially more serious underlying placental diagnoses, such as massive perivillous fibrinoid deposition, chronic histiocytic intervillositis, or fetal thrombotic vasculopathy, may be associated with normal uterine artery Doppler waveforms. Despite minor variations in placental size, shape, and cord insertion, placental function remains, largely normal in the general population. Consequently, morphologic assessment of the placenta is not currently incorporated into current screening

Forest Growth and Yield Models Viewed From a Different Perspective

Science.gov (United States)

Jeffery C. Goelz

2002-01-01

Typically, when different forms of growth and yield models are considered, they are grouped into convenient discrete classes. As a heuristic device, I chose to use a contrasting perspective, that all growth and yield models are diameter distribution models that merely differ in regard to which diameter distribution is employed and how the distribution is projected to...

A generalized diffusion model for growth of nanoparticles synthesized by colloidal methods.

Science.gov (United States)

Wen, Tianlong; Brush, Lucien N; Krishnan, Kannan M

2014-04-01

A nanoparticle growth model is developed to predict and guide the syntheses of monodisperse colloidal nanoparticles in the liquid phase. The model, without any a priori assumptions, is based on the Fick's law of diffusion, conservation of mass and the Gibbs-Thomson equation for crystal growth. In the limiting case, this model reduces to the same expression as the currently accepted model that requires the assumption of a diffusion layer around each nanoparticle. The present growth model bridges the two limiting cases of the previous model i.e. complete diffusion controlled and adsorption controlled growth of nanoparticles. Specifically, the results show that a monodispersion of nanoparticles can be obtained both with fast monomer diffusion and with surface reaction under conditions of small diffusivity to surface reaction constant ratio that results is growth 'focusing'. This comprehensive description of nanoparticle growth provides new insights and establishes the required conditions for fabricating monodisperse nanoparticles critical for a wide range of applications. Copyright © 2013 Elsevier Inc. All rights reserved.

Using time-dependent models to investigate body condition and growth rate of the giant gartersnake

Science.gov (United States)

Coates, P.S.; Wylie, G.D.; Halstead, B.J.; Casazza, Michael L.

2009-01-01

Identifying links between phenotypic attributes and fitness is a primary goal of reproductive ecology. Differences in within-year patterns of body condition between sexes of gartersnakes in relation to reproduction and growth are not fully understood. We conducted an 11-year field study of body condition and growth rate of the giant gartersnake Thamnophis gigas across 13 study areas in the Central Valley of California, USA. We developed a priori mixed effects models of body condition index (BCI), which included covariates of time, sex and snout-vent length and reported the best-approximating models using an information theoretic approach. Also, we developed models of growth rate index (GRI) using covariates of sex and periods based on reproductive behavior. The largest difference in BCI between sexes, as predicted by a non-linear (cubic) time model, occurred during the mating period when female body condition (0.014??0.001 se) was substantially greater than males (-0.027??0.002 se). Males likely allocated energy to search for mates, while females likely stored energy for embryonic development. We also provided evidence that males use more body energy reserves than females during hibernation, perhaps because of different body temperatures between sexes. We found GRI of male snakes was substantially lower during the mating period than during a non-mating period, which indicated that a trade-off existed between searching for mates and growth. These findings contribute to our understanding of snake ecology in a Mediterranean climate. ?? 2009 The Zoological Society of London.

Economic consequences of population size, structure and growth.

Science.gov (United States)

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

Overview: early history of crop growth and photosynthesis modeling.

Science.gov (United States)

El-Sharkawy, Mabrouk A

2011-02-01

As in industrial and engineering systems, there is a need to quantitatively study and analyze the many constituents of complex natural biological systems as well as agro-ecosystems via research-based mechanistic modeling. This objective is normally addressed by developing mathematically built descriptions of multilevel biological processes to provide biologists a means to integrate quantitatively experimental research findings that might lead to a better understanding of the whole systems and their interactions with surrounding environments. Aided with the power of computational capacities associated with computer technology then available, pioneering cropping systems simulations took place in the second half of the 20th century by several research groups across continents. This overview summarizes that initial pioneering effort made to simulate plant growth and photosynthesis of crop canopies, focusing on the discovery of gaps that exist in the current scientific knowledge. Examples are given for those gaps where experimental research was needed to improve the validity and application of the constructed models, so that their benefit to mankind was enhanced. Such research necessitates close collaboration among experimentalists and model builders while adopting a multidisciplinary/inter-institutional approach. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

Using plant growth modeling to analyse C source-sink relations under drought: inter and intra specific comparison

Directory of Open Access Journals (Sweden)

Benoit ePallas

2013-11-01

Full Text Available The ability to assimilate C and allocate NSC (non structural carbohydrates to the most appropriate organs is crucial to maximize plant ecological or agronomic performance. Such C source and sink activities are differentially affected by environmental constraints. Under drought, plant growth is generally more sink than source limited as organ expansion or appearance rate is earlier and stronger affected than C assimilation. This favors plant survival and recovery but not always agronomic performance as NSC are stored rather than used for growth due to a modified metabolism in source and sink leaves. Such interactions between plant C and water balance are complex and plant modeling can help analyzing their impact on plant phenotype. This paper addresses the impact of trade-offs between C sink and source activities and plant production under drought, combining experimental and modeling approaches. Two contrasted monocotyledonous species (rice, oil palm were studied. Experimentally, the sink limitation of plant growth under moderate drought was confirmed as well as the modifications in NSC metabolism in source and sink organs. Under severe stress, when C source became limiting, plant NSC concentration decreased. Two plant models dedicated to oil palm and rice morphogenesis were used to perform a sensitivity analysis and further explore how to optimize C sink and source drought sensitivity to maximize plant growth. Modeling results highlighted that optimal drought sensitivity depends both on drought type and species and that modeling is a great opportunity to analyse such complex processes. Further modeling needs and more generally the challenge of using models to support complex trait breeding are discussed.

Model for the growth of the world airline network

Science.gov (United States)

Verma, T.; Araújo, N. A. M.; Nagler, J.; Andrade, J. S.; Herrmann, H. J.

2016-06-01

We propose a probabilistic growth model for transport networks which employs a balance between popularity of nodes and the physical distance between nodes. By comparing the degree of each node in the model network and the World Airline Network (WAN), we observe that the difference between the two is minimized for α≈2. Interestingly, this is the value obtained for the node-node correlation function in the WAN. This suggests that our model explains quite well the growth of airline networks.

Size and temperature consideration in the liquid layer growth from nanovoids and the melting model construction

International Nuclear Information System (INIS)

Li, H.; Liang, X.H.; Li, M.

2014-01-01

A new model for the solid melting point T m (D) from nanovoids is proposed through considering the liquid layer growth behavior. This model, which does not have any adjustable parameter, introduces the classical thermodynamic treatment, i.e., the liquid nucleation and growth theory, for nanoparticle melting. With increased void diameter D, T m (D) approaches to T m0 . Moreover, T m (D) > T m0 for a small void (T m0 is the bulk melting point). In other words, the solid can be significantly superheated especially when D decreases, even if the difference of interface energy is larger than zero. This finding can be expected from the negatively curved surface of the void. The model predictions are consistent with the molecular dynamic (MD) simulation results for argon solids. Moreover, the growth of liquid layer from void surface relies on both size and temperature, which directly determine liquid layer thickness, and only when liquid layer thickness reaches to a critical value, can void become instable. - Highlights: • A united model for the crystal melting point from nanovoids is established. • Melting point increases with decreased void size. • The result is expected from the negatively curved surface of the void. • The prediction is agreed well with the MD simulation results

An endogenous growth model with embodied energy-saving technical change

International Nuclear Information System (INIS)

Van Zon, A.; Yetkiner, I. H.

2003-01-01

In this paper, we extend the Romer [Journal of Political Economy 98 (Part 2) (1990) S271] model in two ways. First we include energy consumption of intermediates. Second, intermediates become heterogeneous due to endogenous energy-saving technical change. We show that the resulting model can still generate steady state growth, but the growth rate depends negatively on the growth of real energy prices. The reason is that real energy price rises will lower the profitability of using new intermediate goods, and hence, the profitability of doing research, and therefore have a negative impact on growth. We also show that the introduction of an energy tax that is recycled in the form of an R and D subsidy may increase growth. We conclude that in order to have energy efficiency growth and output growth under rising real energy prices, a combination of R and D and energy policy is called for

Fetal, neonatal, infant, and child international growth standards: an unprecedented opportunity for an integrated approach to assess growth and development.

Science.gov (United States)

Garza, Cutberto

2015-07-01

The recent publication of fetal growth and gestational age-specific growth standards by the International Fetal and Newborn Growth Consortium for the 21st Century Project and the previous publication by the WHO of infant and young child growth standards based on the WHO Multicentre Growth Reference Study enable evaluations of growth from ∼9 wk gestation to 5 y. The most important features of these projects are the prescriptive approach used for subject selection and the rigorous testing of the assertion that growth is very similar among geographically and ethnically diverse nonisolated populations when health, nutrition, and other care needs are met and the environment imposes minimal constraints on growth. Both studies documented that with adequate controls, the principal source of variability in growth during gestation and early childhood resides among individuals. Study sites contributed much less to observed variability. The agreement between anthropometric measurements common to both studies also is noteworthy. Jointly, these studies provide for the first time, to my knowledge, a conceptually consistent basis for worldwide and localized assessments and comparisons of growth performance in early life. This is an important contribution to improving the health care of children across key periods of growth and development, especially given the appropriate interest in pursuing "optimal" health in the "first 1000 d," i.e., the period covering fertilization/implantation, gestation, and postnatal life to 2 y of age. © 2015 American Society for Nutrition.

Theory and modeling of microstructural evolution in polycrystalline materials: Solute segregation, grain growth and phase transformations

Science.gov (United States)

Ma, Ning

2005-11-01

To accurately predict microstructure evolution and, hence, to synthesis metal and ceramic alloys with desirable properties involves many fundamental as well as practical issues. In the present study, novel theoretical and phase field approaches have been developed to address some of these issues including solute drag and segregation transition at grain boundaries and dislocations, grain growth in systems of anisotropic boundary properties, and precipitate microstructure development in polycrystalline materials. The segregation model has allowed for the prediction of a first-order segregation transition, which could be related to the sharp transition of solute concentration of grain boundary as a function of temperature. The incorporating of interfacial energy and mobility as functions of misorientation and inclination in the phase field model has allowed for the study of concurrent grain growth and texture evolution. The simulation results were analyzed using the concept of local grain boundary energy density, which simplified significantly the development of governing equations for texture controlled grain growth in Ti-6Al-4V. Quantitative phase field modeling techniques have been developed by incorporating thermodynamic and diffusivity databases. The models have been validated against DICTRA simulations in simple 1D problems and applied to simulate realistic microstructural evolutions in Ti-6Al-4V, including grain boundary a and globular a growth and sideplate development under both isothermal aging and continuous cooling conditions. The simulation predictions agree well with experimental observations.

Examining carbon emissions economic growth nexus for India: A multivariate cointegration approach

International Nuclear Information System (INIS)

Ghosh, Sajal

2010-01-01

The study probes cointegration and causality between carbon emissions and economic growth for India using ARDL bounds testing approach complemented by Johansen-Juselius maximum likelihood procedure in a multivariate framework by incorporating energy supply, investment and employment for time span 1971-2006. The study fails to establish long-run equilibrium relationship and long term causality between carbon emissions and economic growth; however, there exists a bi-directional short-run causality between the two. Hence, in the short-run, any effort to reduce carbon emissions could lead to a fall in the national income. This study also establishes unidirectional short-run causality running from economic growth to energy supply and energy supply to carbon emissions. The absence of causality running from energy supply to economic growth implies that in India, energy conservation and energy efficiency measures can be implemented to minimize the wastage of energy across value chain. Such measures would narrow energy demand-supply gap. Absence of long-run causality between carbon emissions and economic growth implies that in the long-run, focus should be given on harnessing energy from clean sources to curb carbon emissions, which would not affect the country's economic growth.

Using Calculus to Model the Growth of L. Plantarum Bacteria

Directory of Open Access Journals (Sweden)

Erin Carey

2009-01-01

Full Text Available Experimental data for the growth of Lactobacillus plantarum bacteria have been obtained over time, creating the need for mathematical means to model this data. We use the Gompertz model because it is a sigmoid function for a time series, where growth is slowest at the start and end of a time period. The Gompertz model is especially useful because it defines specific parameters that characterize the S-shaped curve. In addition, the Gompertz model uses relative growth, which is the logarithm of the given population compared to the initial population. This reflects the fact that bacteria grow exponentially. The important parameters that were found were the lag time and the asymptote.

The Balance-of-Payments-Constrained Growth Model and the Limits to Export-Led Growth

Directory of Open Access Journals (Sweden)

Robert A. Blecker

2000-12-01

Full Text Available This paper discusses how A. P. Thirlwall's model of balance-of-payments-constrained growth can be adapted to analyze the idea of a "fallacy of composition" in the export-led growth strategy of many developing countries. The Deaton-Muellbauer model of the Almost Ideal Demand System (AIDS is used to represent the adding-up constraints on individual countries' exports, when they are all trying to export competing products to the same foreign markets (i.e. newly industrializing countries are exporting similar types of manufactured goods to the OECD countries. The relevance of the model to the recent financial crises in developing countries and policy alternatives for redirecting development strategies are also discussed.

Modeling plasma-assisted growth of graphene-carbon nanotube hybrid

International Nuclear Information System (INIS)

Tewari, Aarti

2016-01-01

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. 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.

Modeling plasma-assisted growth of graphene-carbon nanotube hybrid

Energy Technology Data Exchange (ETDEWEB)

Tewari, Aarti [Department of Applied Physics, Delhi Technological University, Shahbad Daulatpur, Bawana Road, Delhi 110 042 (India)

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. 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.

Development and validation of extensive growth and growth boundary models for psychrotolerant pseudomonads in seafood, meat and vegetable products

DEFF Research Database (Denmark)

Martinez Rios, Veronica; Dalgaard, Paw

Extensive growth and growth boundary models were developed and validated for psychrotolerant pseudomonads growing in seafood, meat and vegetable products. The new models were developed by expanding anexisting cardinal parameter-type model for growth of pseudomonads in milk (Martinez-Rios et al......, when observed and predicted μmax -values were compared. Thus, on average μmax -values for seafood and meat products were overestimated by 14%. Additionally, the reference growth rate parameter μref25˚C was calibrated by fitting the model to 21 μmax -values in vegetable products. This resulted in a μref......25˚C -value of 0.54 1/h. The calibrated vegetable model wassuccessfully validated using 51 μmax -values for psychrotolerant pseudomonads in vegetables. Average bias and accuracy factor values of 1.24 and 1.38 were obtained, respectively. Lag time models were developed by using relative lag times from...

Modelling growth curves of Nigerian indigenous normal feather ...

African Journals Online (AJOL)

This study was conducted to predict the growth curve parameters using Bayesian Gompertz and logistic models and also to compare the two growth function in describing the body weight changes across age in Nigerian indigenous normal feather chicken. Each chick was wing-tagged at day old and body weights were ...

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

Science.gov (United States)

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.

Mathematical model for predicting molecular-beam epitaxy growth rates for wafer production

International Nuclear Information System (INIS)

Shi, B.Q.

2003-01-01

An analytical mathematical model for predicting molecular-beam epitaxy (MBE) growth rates is reported. The mathematical model solves the mass-conservation equation for liquid sources in conical crucibles and predicts the growth rate by taking into account the effect of growth source depletion on the growth rate. Assumptions made for deducing the analytical model are discussed. The model derived contains only one unknown parameter, the value of which can be determined by using data readily available to MBE growers. Procedures are outlined for implementing the model in MBE production of III-V compound semiconductor device wafers. Results from use of the model to obtain targeted layer compositions and thickness of InP-based heterojunction bipolar transistor wafers are presented

A high precision extrapolation method in multiphase-field model for simulating dendrite growth

Science.gov (United States)

Yang, Cong; Xu, Qingyan; Liu, Baicheng

2018-05-01

The phase-field method coupling with thermodynamic data has become a trend for predicting the microstructure formation in technical alloys. Nevertheless, the frequent access to thermodynamic database and calculation of local equilibrium conditions can be time intensive. The extrapolation methods, which are derived based on Taylor expansion, can provide approximation results with a high computational efficiency, and have been proven successful in applications. This paper presents a high precision second order extrapolation method for calculating the driving force in phase transformation. To obtain the phase compositions, different methods in solving the quasi-equilibrium condition are tested, and the M-slope approach is chosen for its best accuracy. The developed second order extrapolation method along with the M-slope approach and the first order extrapolation method are applied to simulate dendrite growth in a Ni-Al-Cr ternary alloy. The results of the extrapolation methods are compared with the exact solution with respect to the composition profile and dendrite tip position, which demonstrate the high precision and efficiency of the newly developed algorithm. To accelerate the phase-field and extrapolation computation, the graphic processing unit (GPU) based parallel computing scheme is developed. The application to large-scale simulation of multi-dendrite growth in an isothermal cross-section has demonstrated the ability of the developed GPU-accelerated second order extrapolation approach for multiphase-field model.

Modeling of dislocation dynamics in germanium Czochralski growth

Science.gov (United States)

Artemyev, V. V.; Smirnov, A. D.; Kalaev, V. V.; Mamedov, V. M.; Sidko, A. P.; Podkopaev, O. I.; Kravtsova, E. D.; Shimansky, A. F.

2017-06-01

Obtaining very high-purity germanium crystals with low dislocation density is a practically difficult problem, which requires knowledge and experience in growth processes. Dislocation density is one of the most important parameters defining the quality of germanium crystal. In this paper, we have performed experimental study of dislocation density during 4-in. germanium crystal growth using the Czochralski method and comprehensive unsteady modeling of the same crystal growth processes, taking into account global heat transfer, melt flow and melt/crystal interface shape evolution. Thermal stresses in the crystal and their relaxation with generation of dislocations within the Alexander-Haasen model have been calculated simultaneously with crystallization dynamics. Comparison to experimental data showed reasonable agreement for the temperature, interface shape and dislocation density in the crystal between calculation and experiment.

Bayesian Model on Fatigue Crack Growth Rate of Type 304 Stainless Steel

Energy Technology Data Exchange (ETDEWEB)

Choi, Sanhae; Yoon, Jae Young; Hwang, Il Soon [Nuclear Materials Laboratory, Seoul National University, Seoul (Korea, Republic of)

2015-10-15

The fatigue crack growth rate curve is typically estimated by deterministic methods in accordance with the ASME Boiler and Pressure Vessel Code Sec. XI. The reliability of nuclear materials must also consider the environmental effect. This can be overcome by probabilistic methods that estimate the degradation of materials. In this study, fatigue tests were carried out on Type 304 stainless steel (STS 304) to obtain a fatigue crack growth rate curve and Paris' law constants. Tests were conducted on a constant load and a constant delta K, respectively. The unknown constants of Paris' law were updated probabilistically by Bayesian inference and the method can be used for the probabilistic structural integrity assessment of other nuclear materials. In this paper, Paris' law constants including C and m for Type 304 stainless steel were determined by probabilistic approach with Bayesian Inference. The Bayesian update process is limited in accuracy, because this method should assume initial data distribution. If we select an appropriate distribution, this updating method is powerful enough to get data results considering the environment and materials. Until now, remaining lives of NPPs are estimated by deterministic methods using a priori model to finally assess structural integrity. Bayesian approach can utilize in-service inspection data derived from aged properties.

Bayesian Model on Fatigue Crack Growth Rate of Type 304 Stainless Steel

International Nuclear Information System (INIS)

Choi, Sanhae; Yoon, Jae Young; Hwang, Il Soon

2015-01-01

The fatigue crack growth rate curve is typically estimated by deterministic methods in accordance with the ASME Boiler and Pressure Vessel Code Sec. XI. The reliability of nuclear materials must also consider the environmental effect. This can be overcome by probabilistic methods that estimate the degradation of materials. In this study, fatigue tests were carried out on Type 304 stainless steel (STS 304) to obtain a fatigue crack growth rate curve and Paris' law constants. Tests were conducted on a constant load and a constant delta K, respectively. The unknown constants of Paris' law were updated probabilistically by Bayesian inference and the method can be used for the probabilistic structural integrity assessment of other nuclear materials. In this paper, Paris' law constants including C and m for Type 304 stainless steel were determined by probabilistic approach with Bayesian Inference. The Bayesian update process is limited in accuracy, because this method should assume initial data distribution. If we select an appropriate distribution, this updating method is powerful enough to get data results considering the environment and materials. Until now, remaining lives of NPPs are estimated by deterministic methods using a priori model to finally assess structural integrity. Bayesian approach can utilize in-service inspection data derived from aged properties

Modeling water scarcity over south Asia: Incorporating crop growth and irrigation models into the Variable Infiltration Capacity (VIC) model

Science.gov (United States)

Troy, Tara J.; Ines, Amor V. M.; Lall, Upmanu; Robertson, Andrew W.

2013-04-01

Large-scale hydrologic models, such as the Variable Infiltration Capacity (VIC) model, are used for a variety of studies, from drought monitoring to projecting the potential impact of climate change on the hydrologic cycle decades in advance. The majority of these models simulates the natural hydrological cycle and neglects the effects of human activities such as irrigation, which can result in streamflow withdrawals and increased evapotranspiration. In some parts of the world, these activities do not significantly affect the hydrologic cycle, but this is not the case in south Asia where irrigated agriculture has a large water footprint. To address this gap, we incorporate a crop growth model and irrigation model into the VIC model in order to simulate the impacts of irrigated and rainfed agriculture on the hydrologic cycle over south Asia (Indus, Ganges, and Brahmaputra basin and peninsular India). The crop growth model responds to climate signals, including temperature and water stress, to simulate the growth of maize, wheat, rice, and millet. For the primarily rainfed maize crop, the crop growth model shows good correlation with observed All-India yields (0.7) with lower correlations for the irrigated wheat and rice crops (0.4). The difference in correlation is because irrigation provides a buffer against climate conditions, so that rainfed crop growth is more tied to climate than irrigated crop growth. The irrigation water demands induce hydrologic water stress in significant parts of the region, particularly in the Indus, with the streamflow unable to meet the irrigation demands. Although rainfall can vary significantly in south Asia, we find that water scarcity is largely chronic due to the irrigation demands rather than being intermittent due to climate variability.

Phase-field model of vapor-liquid-solid nanowire growth

Science.gov (United States)

Wang, Nan; Upmanyu, Moneesh; Karma, Alain

2018-03-01

We present a multiphase-field model to describe quantitatively nanowire growth by the vapor-liquid-solid (VLS) process. The free-energy functional of this model depends on three nonconserved order parameters that distinguish the vapor, liquid, and solid phases and describe the energetic properties of various interfaces, including arbitrary forms of anisotropic γ plots for the solid-vapor and solid-liquid interfaces. The evolution equations for those order parameters describe basic kinetic processes including the rapid (quasi-instantaneous) equilibration of the liquid catalyst to a droplet shape with constant mean curvature, the slow incorporation of growth atoms at the droplet surface, and crystallization within the droplet. The standard constraint that the sum of the phase fields equals unity and the conservation of the number of catalyst atoms, which relates the catalyst volume to the concentration of growth atoms inside the droplet, are handled via separate Lagrange multipliers. An analysis of the model is presented that rigorously maps the phase-field equations to a desired set of sharp-interface equations for the evolution of the phase boundaries under the constraint of force balance at three-phase junctions (triple points) given by the Young-Herring relation that includes torque term related to the anisotropy of the solid-liquid and solid-vapor interface excess free energies. Numerical examples of growth in two dimensions are presented for the simplest case of vanishing crystalline anisotropy and the more realistic case of a solid-liquid γ plot with cusped minima corresponding to two sets of (10 ) and (11 ) facets. The simulations reproduce many of the salient features of nanowire growth observed experimentally, including growth normal to the substrate with tapering of the side walls, transitions between different growth orientations, and crawling growth along the substrate. They also reproduce different observed relationships between the nanowire growth

Mathematical modeling of Kluyveromyces marxianus growth in solid-state fermentation using a packed-bed bioreactor.

Science.gov (United States)

Mazutti, Marcio A; Zabot, Giovani; Boni, Gabriela; Skovronski, Aline; de Oliveira, Débora; Di Luccio, Marco; Rodrigues, Maria Isabel; Maugeri, Francisco; Treichel, Helen

2010-04-01

This work investigated the growth of Kluyveromyces marxianus NRRL Y-7571 in solid-state fermentation in a medium composed of sugarcane bagasse, molasses, corn steep liquor and soybean meal within a packed-bed bioreactor. Seven experimental runs were carried out to evaluate the effects of flow rate and inlet air temperature on the following microbial rates: cell mass production, total reducing sugar and oxygen consumption, carbon dioxide and ethanol production, metabolic heat and water generation. A mathematical model based on an artificial neural network was developed to predict the above-mentioned microbial rates as a function of the fermentation time, initial total reducing sugar concentration, inlet and outlet air temperatures. The results showed that the microbial rates were temperature dependent for the range 27-50 degrees C. The proposed model efficiently predicted the microbial rates, indicating that the neural network approach could be used to simulate the microbial growth in SSF.

Modelling an industrial anaerobic granular reactor using a multi-scale approach

DEFF Research Database (Denmark)

Feldman, Hannah; Flores Alsina, Xavier; Ramin, Pedram

2017-01-01

The objective of this paper is to show the results of an industrial project dealing with modelling of anaerobic digesters. A multi-scale mathematical approach is developed to describe reactor hydrodynamics, granule growth/distribution and microbial competition/inhibition for substrate/space within...... the biofilm. The main biochemical and physico-chemical processes in the model are based on the Anaerobic Digestion Model No 1 (ADM1) extended with the fate of phosphorus (P), sulfur (S) and ethanol (Et-OH). Wastewater dynamic conditions are reproduced and data frequency increased using the Benchmark...... simulations show the effects on the overall process performance when operational (pH) and loading (S:COD) conditions are modified. Lastly, the effect of intra-granular precipitation on the overall organic/inorganic distribution is assessed at: 1) different times; and, 2) reactor heights. Finally...

Gompertzian stochastic model with delay effect to cervical cancer growth

International Nuclear Information System (INIS)

Mazlan, Mazma Syahidatul Ayuni binti; Rosli, Norhayati binti; Bahar, Arifah

2015-01-01

In this paper, a Gompertzian stochastic model with time delay is introduced to describe the cervical cancer growth. The parameters values of the mathematical model are estimated via Levenberg-Marquardt optimization method of non-linear least squares. We apply Milstein scheme for solving the stochastic model numerically. The efficiency of mathematical model is measured by comparing the simulated result and the clinical data of cervical cancer growth. Low values of Mean-Square Error (MSE) of Gompertzian stochastic model with delay effect indicate good fits

Gompertzian stochastic model with delay effect to cervical cancer growth

Energy Technology Data Exchange (ETDEWEB)

Mazlan, Mazma Syahidatul Ayuni binti; Rosli, Norhayati binti [Faculty of Industrial Sciences and Technology, Universiti Malaysia Pahang, Lebuhraya Tun Razak, 26300 Gambang, Pahang (Malaysia); Bahar, Arifah [Department of Mathematical Sciences, Faculty of Science, Universiti Teknologi Malaysia, 81310 Johor Bahru, Johor and UTM Centre for Industrial and Applied Mathematics (UTM-CIAM), Universiti Teknologi Malaysia, 81310 Johor Bahru, Johor (Malaysia)

2015-02-03

In this paper, a Gompertzian stochastic model with time delay is introduced to describe the cervical cancer growth. The parameters values of the mathematical model are estimated via Levenberg-Marquardt optimization method of non-linear least squares. We apply Milstein scheme for solving the stochastic model numerically. The efficiency of mathematical model is measured by comparing the simulated result and the clinical data of cervical cancer growth. Low values of Mean-Square Error (MSE) of Gompertzian stochastic model with delay effect indicate good fits.

Which factors make the difference for explaining growth in newcomer organizational commitment? A latent growth modeling approach

NARCIS (Netherlands)

Maia, L. G.; Bastos, A. V. B.; Solinger, O.N.

2016-01-01

Previous studies on newcomer socialization have evidenced quite consistently that newcomers' affective commitment tends to decline in the first years of employment. In this paper, we attempt to explain why a minority of Brazilian newcomers in a governmental organization (N=194) display growth in

Analisis Hubungan antara Berbagai Model Gabungan Proksi Investment Opportunity Set dan Real Growth dengan Menggunakan Pendekatan Confirmatory Factor Analysis”

Directory of Open Access Journals (Sweden)

Muhammad Yusuf

2016-02-01

Full Text Available This study develops and makes composite observed variables from individual Investment Opportunity Set (IOS proxies into one latent variable using structural equation models with a confirmatory factor analysis approach. Six composite investment opportunity set proxies are then created based on some individual proxies, namely price related IOS and investment related IOS. These composite IOS proxies are correlated with the real growth to prove that the model has consistency and ability to predict the real growth. A confirmatory factor analysis results in all observed variables that make latent variables for each model show different result in every model. At model 1, the CFA result show   that every price related IOS proxies at model 1 have significant measurement model fit. At model 2, the Confirmatory Factor Analysis (CFA result show that every price related IOS proxies at model 2 have significant measurement model fit, except for one proxies named Rasio Capital Expenditure to Total Book Asset (RACTE. At model 3, the CFA result show that every price related IOS proxies at model 2 have significant measurement model fit, except for one proxies named Book Value of Property, Plant and Equipment to Book Value of Asset(BVPPEBVA. At model 4, the CFA result show   that every price related IOS proxies at model 1 have significant measurement model fit. At model 5, the CFA result show   that every price related IOS proxies at model 1 have significant measurement model fit. At model 6, the CFA result show that there is no significant measurement model fit for every investment related IOS proxies. Correlation test for all models show almost different result in every models. At model 1, the correlation test show that there is a weak, not significant-positive correlation between price related IOS proxies as latent variable, and real growth proxies. At model 2, the correlation test shows that there is a weak, significant negative correlation between price

A stress driven growth model for soft tissue considering biological availability

International Nuclear Information System (INIS)

Oller, S; Bellomo, F J; Nallim, L G; Armero, F

2010-01-01

Some of the key factors that regulate growth and remodeling of tissues are fundamentally mechanical. However, it is important to take into account the role of bioavailability together with the stresses and strains in the processes of normal or pathological growth. In this sense, the model presented in this work is oriented to describe the growth of soft biological tissue under 'stress driven growth' and depending on the biological availability of the organism. The general theoretical framework is given by a kinematic formulation in large strain combined with the thermodynamic basis of open systems. The formulation uses a multiplicative decomposition of deformation gradient, splitting it in a growth part and visco-elastic part. The strains due to growth are incompatible and are controlled by an unbalanced stresses related to a homeostatic state. Growth implies a volume change with an increase of mass maintaining constant the density. One of the most interesting features of the proposed model is the generation of new tissue taking into account the contribution of mass to the system controlled through biological availability. Because soft biological tissues in general have a hierarchical structure with several components (usually a soft matrix reinforced with collagen fibers), the developed growth model is suitable for the characterization of the growth of each component. This allows considering a different behavior for each of them in the context of a generalized theory of mixtures. Finally, we illustrate the response of the model in case of growth and atrophy with an application example.

OPEN SOURCE APPROACH TO URBAN GROWTH SIMULATION

Directory of Open Access Journals (Sweden)

A. Petrasova

2016-06-01

Full Text Available Spatial patterns of land use change due to urbanization and its impact on the landscape are the subject of ongoing research. Urban growth scenario simulation is a powerful tool for exploring these impacts and empowering planners to make informed decisions. We present FUTURES (FUTure Urban – Regional Environment Simulation – a patch-based, stochastic, multi-level land change modeling framework as a case showing how what was once a closed and inaccessible model benefited from integration with open source GIS.We will describe our motivation for releasing this project as open source and the advantages of integrating it with GRASS GIS, a free, libre and open source GIS and research platform for the geospatial domain. GRASS GIS provides efficient libraries for FUTURES model development as well as standard GIS tools and graphical user interface for model users. Releasing FUTURES as a GRASS GIS add-on simplifies the distribution of FUTURES across all main operating systems and ensures the maintainability of our project in the future. We will describe FUTURES integration into GRASS GIS and demonstrate its usage on a case study in Asheville, North Carolina. The developed dataset and tutorial for this case study enable researchers to experiment with the model, explore its potential or even modify the model for their applications.

Age structure and capital dilution effects in neo-classical growth models.

Science.gov (United States)

Blanchet, D

1988-01-01

Economists often over estimate capital dilution effects when applying neoclassical growth models which use age structured population and depreciation of capital stock. This occurs because capital stock is improperly characterized. A standard model which assumes a constant depreciation of capital intimates that a population growth rate equal to a negative constant savings ratio is preferable to any higher growth rate. Growth rates which are lower than a negative constant savings ratio suggest an ever growing capital/labor ratio and an ever growing standard of living, even if people do not save. This is suggested because the natural reduction of the capital stock through depreciation is slower than the population decrease which is simply unrealistic. This model overlooks the fact that low or negative growth rates result in an ageing of the capital stock, and this ageing subsequently results in an increase of the overall rate of capital depreciation. In that overly simplistic model, depreciation was assumed independent of the age of the captial stock. Incorporating depreciation as a variable into a model allows a more symmetric treatment of capital. Using models with heterogenous capital, this article explores what occurs when more than 1 kind of capital good is involved in production and when these various captial goods have different lengths of life. Applying economic models, it also examines what occurs when the length of life of capital may vary. These variations correct the negative impact that population growth can have on per capital production and consumption.