An introduction to latent variable growth curve modeling concepts, issues, and application
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...
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.
Levi, M. [=Marcel M.; Biemond, B. J.; Sturk, A.; Hoek, J.; ten Cate, J. W.
1991-01-01
We studied the effect of an ionic high osmolar contrast medium (Ioxitalamate), an ionic low osmolar contrast medium (Ioxaglate) and various nonionic low osmolar contrast media (Iopamidol, Iopromide and Iohexol) on thrombus growth in a rabbit jugular vein thrombosis model. Thrombus growth was
International Nuclear Information System (INIS)
Brianzoni, Serena; Mammana, Cristiana; Michetti, Elisabetta
2012-01-01
Highlights: ► One dimensional piecewise smooth map: border collision bifurcations. ► Numerical simulations: complex dynamics. ► Ves production function in the solow–swan growth model and comparison with the ces production function. - Abstract: We study the dynamics shown by the discrete time neoclassical one-sector growth model with differential savings as in Bohm and Kaas while assuming VES production function in the form given by Revankar . It is shown that the model can exhibit unbounded endogenous growth despite the absence of exogenous technical change and the presence of non-reproducible factors if the elasticity of substitution is greater than one. We then consider parameters range related to non-trivial dynamics (i.e. the elasticity of substitution in less than one and shareholders save more than workers) and we focus on local and global bifurcations causing the transition to more and more complex asymptotic dynamics. In particular, as our map is non-differentiable in a subset of the states space, we show that border collision bifurcations occur. Several numerical simulations support the analysis.
Thomas, Yoann; Mazurié, Joseph; Alunno-Bruscia, Marianne; Bacher, Cédric; Bouget, Jean-François; Gohin, Francis; Pouvreau, Stéphane; Struski, Caroline
2011-11-01
In order to assess the potential of various marine ecosystems for shellfish aquaculture and to evaluate their carrying capacities, there is a need to clarify the response of exploited species to environmental variations using robust ecophysiological models and available environmental data. For a large range of applications and comparison purposes, a non-specific approach based on 'generic' individual growth models offers many advantages. In this context, we simulated the response of blue mussel ( Mytilus edulis L.) to the spatio-temporal fluctuations of the environment in Mont Saint-Michel Bay (North Brittany) by forcing a generic growth model based on Dynamic Energy Budgets with satellite-derived environmental data (i.e. temperature and food). After a calibration step based on data from mussel growth surveys, the model was applied over nine years on a large area covering the entire bay. These simulations provide an evaluation of the spatio-temporal variability in mussel growth and also show the ability of the DEB model to integrate satellite-derived data and to predict spatial and temporal growth variability of mussels. Observed seasonal, inter-annual and spatial growth variations are well simulated. The large-scale application highlights the strong link between food and mussel growth. The methodology described in this study may be considered as a suitable approach to account for environmental effects (food and temperature variations) on physiological responses (growth and reproduction) of filter feeders in varying environments. Such physiological responses may then be useful for evaluating the suitability of coastal ecosystems for shellfish aquaculture.
A Variable Input-Output Model for Inflation, Growth, and Energy for the Korean Economy.
1983-12-01
and the sales price of cukput as determinan -s of the technical coefficients were suggested by Walras [Ref. 4] and many other eco.cmis.s. (Ref. 5] Arrow...34included in manufacturing and construction secter. The other industries include the social and government services. 32 Ii. * 1.’ *. - .-- :~ ~~\\ ~~ v...e3lectricity, government enterprise, and other social commercial industries. The rate of growth of the money suiply and interest ratqs on loans are the key
Román-Román, Patricia; Román-Román, Sergio; Serrano-Pérez, Juan José; Torres-Ruiz, Francisco
2016-10-21
In experimental studies on tumor growth, whenever the time evolution of the relative volume of a tumor in an untreated (control) group can be fitted by a Gompertz diffusion process there is a possibility that an antiproliferative therapy, which modifies the growth rate of the process that fits the treated group, may also affect its variability. The present paper proposes several procedures for the estimation of the time function included in the infinitesimal variance of the new process, as well as the time function affecting the growth rate (which is included in the infinitesimal mean). Also, a hypothesis testing is designed to confirm or refute the need for including such a time-dependent function in the infinitesimal variance. In order to validate and compare the proposed procedures a simulation study has been carried out. In addition, a proposal is made for a strategy aimed at finding the optimal combination of procedures for each case. A real data application concerning the effects of cisplatin on a patient-derived xenograft (PDX) tumor model showcases the advantages of this model over others that have been used in the past. Copyright © 2016 Elsevier Ltd. All rights reserved.
Jaskierniak, D.; Kuczera, G.; Benyon, R.
2016-04-01
A major challenge in surface hydrology involves predicting streamflow in ungauged catchments with heterogeneous vegetation and spatiotemporally varying evapotranspiration (ET) rates. We present a top-down approach for quantifying the influence of broad-scale changes in forest structure on ET and hence streamflow. Across three catchments between 18 and 100 km2 in size and with regenerating Eucalyptus regnans and E. delegatensis forest, we demonstrate how variation in ET can be mapped in space and over time using LiDAR data and commonly available forest inventory data. The model scales plot-level sapwood area (SA) to the catchment-level using basal area (BA) and tree stocking density (N) estimates in forest growth models. The SA estimates over a 69 year regeneration period are used in a relationship between SA and vegetation induced streamflow loss (L) to predict annual streamflow (Q) with annual rainfall (P) estimates. Without calibrating P, BA, N, SA, and L to Q data, we predict annual Q with R2 between 0.68 and 0.75 and Nash Sutcliffe efficiency (NSE) between 0.44 and 0.48. To remove bias, the model was extended to allow for runoff carry-over into the following year as well as minor correction to rainfall bias, which produced R2 values between 0.72 and 0.79, and NSE between 0.70 and 0.79. The model under-predicts streamflow during drought periods as it lacks representation of ecohydrological processes that reduce L with either reduced growth rates or rainfall interception during drought. Refining the relationship between sapwood thickness and forest inventory variables is likely to further improve results.
Directory of Open Access Journals (Sweden)
Dario Constantinescu
2016-12-01
Full Text Available Drought stress is a major abiotic stres threatening plant and crop productivity. In case of fleshy fruits, understanding Drought stress is a major abiotic stress threatening plant and crop productivity. In case of fleshy fruits, understanding mechanisms governing water and carbon accumulations and identifying genes, QTLs and phenotypes, that will enable trade-offs between fruit growth and quality under Water Deficit (WD condition is a crucial challenge for breeders and growers. In the present work, 117 recombinant inbred lines of a population of Solanum lycopersicum were phenotyped under control and WD conditions. Plant water status, fruit growth and composition were measured and data were used to calibrate a process-based model describing water and carbon fluxes in a growing fruit as a function of plant and environment. Eight genotype-dependent model parameters were estimated using a multiobjective evolutionary algorithm in order to minimize the prediction errors of fruit dry and fresh mass throughout fruit development. WD increased the fruit dry matter content (up to 85 % and decreased its fresh weight (up to 60 %, big fruit size genotypes being the most sensitive. The mean normalized root mean squared errors of the predictions ranged between 16-18 % in the population. Variability in model genotypic parameters allowed us to explore diverse genetic strategies in response to WD. An interesting group of genotypes could be discriminated in which i the low loss of fresh mass under WD was associated with high active uptake of sugars and low value of the maximum cell wall extensibility, and ii the high dry matter content in control treatment (C was associated with a slow decrease of mass flow. Using 501 SNP markers genotyped across the genome, a QTL analysis of model parameters allowed to detect three main QTLs related to xylem and phloem conductivities, on chromosomes 2, 4 and 8. The model was then applied to design ideotypes with high dry matter
Directory of Open Access Journals (Sweden)
Fahad Ali
2018-02-01
Full Text Available The paper empirically investigates three different methods to construct factors and identifies some pitfalls that arise in the application of Fama-French’s three-factor model to the Pakistani stock returns. We find that the special features in Pakistan significantly affect size and value factors and also influence the explanatory power of the three-factor model. Additionally, the paper examines the ability of the three factors to predict the future growth of Pakistan’s economy. Using monthly data of both financial and non-financial companies between 2002 and 2016, the article empirically investigates and finds that: (1 size and book-to-market factors exist in the Pakistani stock market, two mimic portfolios SMB and HML generate a return of 9.15% and 12.27% per annum, respectively; (2 adding SMB and HML factors into the model meaningfully increases the explanatory power of the model; and (3 the model’s factors, except for value factor, predict future gross domestic product (GDP growth of Pakistan and remain robust. Our results are robust across sub-periods, risk regimes, and under three different methods of constructing the factors.
Variable importance in latent variable regression models
Kvalheim, O.M.; Arneberg, R.; Bleie, O.; Rajalahti, T.; Smilde, A.K.; Westerhuis, J.A.
2014-01-01
The quality and practical usefulness of a regression model are a function of both interpretability and prediction performance. This work presents some new graphical tools for improved interpretation of latent variable regression models that can also assist in improved algorithms for variable
E. Gregory McPherson; Paula J. Peper
2012-01-01
This paper describes three long-term tree growth studies conducted to evaluate tree performance because repeated measurements of the same trees produce critical data for growth model calibration and validation. Several empirical and process-based approaches to modeling tree growth are reviewed. Modeling is more advanced in the fields of forestry and...
Accounting for inherent variability of growth in microbial risk assessment.
Marks, H M; Coleman, M E
2005-04-15
Risk assessments of pathogens need to account for the growth of small number of cells under varying conditions. In order to determine the possible risks that occur when there are small numbers of cells, stochastic models of growth are needed that would capture the distribution of the number of cells over replicate trials of the same scenario or environmental conditions. This paper provides a simple stochastic growth model, accounting only for inherent cell-growth variability, assuming constant growth kinetic parameters, for an initial, small, numbers of cells assumed to be transforming from a stationary to an exponential phase. Two, basic, microbial sets of assumptions are considered: serial, where it is assume that cells transform through a lag phase before entering the exponential phase of growth; and parallel, where it is assumed that lag and exponential phases develop in parallel. The model is based on, first determining the distribution of the time when growth commences, and then modelling the conditional distribution of the number of cells. For the latter distribution, it is found that a Weibull distribution provides a simple approximation to the conditional distribution of the relative growth, so that the model developed in this paper can be easily implemented in risk assessments using commercial software packages.
Stochastic models for tumoral growth
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.
DEFF Research Database (Denmark)
Palosuo, Taru; Kersebaum, Kurt Christian; Angulo, Carlos
2011-01-01
observations at all sites and in all years, and none could unequivocally be labelled robust and accurate in terms of yield prediction across different environments and crop cultivars with only minimum calibration. The best performance regarding yield estimation was for DAISY and DSSAT, for which the RMSE...... and WOFOST furnished high total above-ground biomass estimates, whereas CROPSYST, DSSAT and FASSET provided low total above-ground estimates. Consequently, DSSAT and FASSET produced very high harvest index values, followed by HERMES and WOFOST. APES and DAISY, on the other hand, returned low harvest index...... of grain yield estimates provided by the models for all sites and years reflects substantial uncertainties in model estimates achieved with only minimum calibration. Mean predictions from the eight models, on the other hand, were in good agreement with measured data. This applies to both results across all...
Variable amplitude fatigue crack growth behavior - a short overview
International Nuclear Information System (INIS)
Singh, Konjengbam Darunkumar; Parry, Matthew Roger; Sinclair, Ian
2011-01-01
A short overview concerning variable amplitude (VA) fatigue crack growth behavior is presented in this paper. The topics covered in this review encompass important issues pertaining to both single and repeated overload transients. Reviews on transient post overload effects such as plasticity induced crack closure, crack tip blunting, residual stresses, crack deflection and branching, activation of near threshold mechanisms, strain hardening are highlighted. A brief summary on experimental trends and finite element modelling of overload induced crack closure is also presented
Variable amplitude fatigue crack growth behavior - a short overview
Energy Technology Data Exchange (ETDEWEB)
Singh, Konjengbam Darunkumar [Indian Institute of Technology, Guwahati (India); Parry, Matthew Roger [Airbus Operations Ltd, Bristol (United Kingdom); Sinclair, Ian [University of Southampton, Southampton (United Kingdom)
2011-03-15
A short overview concerning variable amplitude (VA) fatigue crack growth behavior is presented in this paper. The topics covered in this review encompass important issues pertaining to both single and repeated overload transients. Reviews on transient post overload effects such as plasticity induced crack closure, crack tip blunting, residual stresses, crack deflection and branching, activation of near threshold mechanisms, strain hardening are highlighted. A brief summary on experimental trends and finite element modelling of overload induced crack closure is also presented.
Vogeler, Iris; Mackay, Alec; Vibart, Ronaldo; Rendel, John; Beautrais, Josef; Dennis, Samuel
2016-09-15
Farm system and nutrient budget models are increasingly being used in analysis to inform on farm decision making and evaluate land use policy options at regional scales. These analyses are generally based on the use of average annual pasture yields. In New Zealand (NZ), like in many countries, there is considerable inter-annual variation in pasture growth rates, due to climate. In this study a modelling approach was used to (i) include inter-annual variability as an integral part of the analysis and (ii) test the approach in an economic analysis of irrigation in a case study within the Hawkes Bay Region of New Zealand. The Agricultural Production Systems Simulator (APSIM) was used to generate pasture dry matter yields (DMY) for 20 different years and under both dryland and irrigation. The generated DMY were linked to outputs from farm-scale modelling for both Sheep and Beef Systems (Farmaxx Pro) and Dairy Systems (Farmax® Dairy Pro) to calculate farm production over 20 different years. Variation in DMY and associated livestock production due to inter-annual variation in climate was large, with a coefficient of variations up to 20%. Irrigation decreased this inter-annual variation. On average irrigation, with unlimited available water, increased income by $831 to 1195/ha, but when irrigation was limited to 250mm/ha/year income only increased by $525 to 883/ha. Using pasture responses in individual years to capturing the inter-annual variation, rather than the pasture response averaged over 20years resulted in lower financial benefits. In the case study income from irrigation based on an average year were 10 to >20% higher compared with those obtained from individual years. Copyright © 2016 Elsevier B.V. All rights reserved.
Stochastic ontogenetic growth model
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.
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
Pauli-Bruns, Anette; Knop, Klaus; Lippold, Bernhard C
2010-03-01
The one-step preparation of sustained release matrix pellets, using a melting procedure in a fluidized bed apparatus, was tested in a 2(3) full factorial design of experiments, using microcrystalline wax as lipophilic binder, theophylline as model drug and talc as additional matrix forming agent. The three influence parameters were (A) size of binder particles, (B) fraction of theophylline in solid particles and (C) fraction of microcrystalline wax in formulation. The response variables were agglomerate size and size distribution, dissolution time, agglomerate crush resistance, sphericity, yield and porosity. Nearly spherical pellets comprising a smooth, closed surface could be obtained with the used method, exhibiting the hollow core typical for the immersion and layering mechanism. The reproducibility was very good concerning all responses. The size of agglomerates is proportional to the size of the binder particles, which serve as cores for pellet formation in the molten state in the fluidized bed. Additionally, the agglomerate size is influenced by the volume of the solid particles in relation to the binder particles, with more solid particles leading to larger agglomerates and vice versa. Dissolution times vary in a very wide range, resulting from the interplay between amount of drug in relation to the meltable matrix substance microcrystalline wax and the non-meltable matrix substance talc. The change of binder particle size does not lead to a structural change of the matrix; both dissolution times and porosity are not significantly altered. Agglomerate crush resistance is low due to the hollow core of the pellets. However, it is significantly increased if the volume fraction of microcrystalline wax in the matrix is high, which means that the matrix is mechanically better stabilized. A theoretical model has been established to quantitatively explain agglomerate growth and very good accordance of the full particle size distributions between predicted and
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.
Nonconvex Model of Material Growth: Mathematical Theory
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.
Pradip Saud; Thomas B. Lynch; Duncan S. Wilson; John Stewart; James M. Guldin; Bob Heinemann; Randy Holeman; Dennis Wilson; Keith Anderson
2015-01-01
An individual-tree basal area growth model previously developed for even-aged naturally occurring shortleaf pine trees (Pinus echinata Mill.) in western Arkansas and southeastern Oklahoma did not include weather variables. Individual-tree growth and yield modeling of shortleaf pine has been carried out using the remeasurements of over 200 plots...
Using structural equation modeling to investigate relationships among ecological variables
Malaeb, Z.A.; Kevin, Summers J.; Pugesek, B.H.
2000-01-01
Structural equation modeling is an advanced multivariate statistical process with which a researcher can construct theoretical concepts, test their measurement reliability, hypothesize and test a theory about their relationships, take into account measurement errors, and consider both direct and indirect effects of variables on one another. Latent variables are theoretical concepts that unite phenomena under a single term, e.g., ecosystem health, environmental condition, and pollution (Bollen, 1989). Latent variables are not measured directly but can be expressed in terms of one or more directly measurable variables called indicators. For some researchers, defining, constructing, and examining the validity of latent variables may be the end task of itself. For others, testing hypothesized relationships of latent variables may be of interest. We analyzed the correlation matrix of eleven environmental variables from the U.S. Environmental Protection Agency's (USEPA) Environmental Monitoring and Assessment Program for Estuaries (EMAP-E) using methods of structural equation modeling. We hypothesized and tested a conceptual model to characterize the interdependencies between four latent variables-sediment contamination, natural variability, biodiversity, and growth potential. In particular, we were interested in measuring the direct, indirect, and total effects of sediment contamination and natural variability on biodiversity and growth potential. The model fit the data well and accounted for 81% of the variability in biodiversity and 69% of the variability in growth potential. It revealed a positive total effect of natural variability on growth potential that otherwise would have been judged negative had we not considered indirect effects. That is, natural variability had a negative direct effect on growth potential of magnitude -0.3251 and a positive indirect effect mediated through biodiversity of magnitude 0.4509, yielding a net positive total effect of 0
Modeling Exponential Population Growth
McCormick, Bonnie
2009-01-01
The concept of population growth patterns is a key component of understanding evolution by natural selection and population dynamics in ecosystems. The National Science Education Standards (NSES) include standards related to population growth in sections on biological evolution, interdependence of organisms, and science in personal and social…
Hulshof, Catherine M; Stegen, James C; Swenson, Nathan G; Enquist, Carolyn A F; Enquist, Brian J
2012-01-01
Plants are expected to differentially allocate resources to reproduction, growth, and survival in order to maximize overall fitness. Life history theory predicts that the allocation of resources to reproduction should occur at the expense of vegetative growth. Although it is known that both organism size and resource availability can influence life history traits, few studies have addressed how size dependencies of growth and reproduction and variation in resource supply jointly affect the coupling between growth and reproduction. In order to understand the relationship between growth and reproduction in the context of resource variability, we utilize a long-term observational data set consisting of 670 individual trees over a 10-year period within a local population of Bursera simaruba (L.) Sarg. We (1) quantify the functional form and variability in the growth-reproduction relationship at the population and individual-tree level and (2) develop a theoretical framework to understand the allometric dependence of growth and reproduction. Our findings suggest that the differential responses of allometric growth and reproduction to resource availability, both between years and between microsites, underlie the apparent relationship between growth and reproduction. Finally, we offer an alternative approach for quantifying the relationship between growth and reproduction that accounts for variation in allometries.
A new population growth map with variable coefficients
International Nuclear Information System (INIS)
Jannussis, A.
1986-01-01
In the present paper it is investigated a simple population growth map with variable coefficients. Moreover, it is studied the new population map of the form xsub(j+1) = axsub(j) (1/(1 + bxsub(j)) -1/(1 + cxsub(j))), c not= b, j = 0, 1,..., which is transformed in an equivalent logistic map
Modeling Population Growth and Extinction
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,…
Modeling the Variable Heliopause Location
Hensley, Kerry
2018-03-01
In 2012, Voyager 1 zipped across the heliopause. Five and a half years later, Voyager 2 still hasnt followed its twin into interstellar space. Can models of the heliopause location help determine why?How Far to the Heliopause?Artists conception of the heliosphere with the important structures and boundaries labeled. [NASA/Goddard/Walt Feimer]As our solar system travels through the galaxy, the solar outflow pushes against the surrounding interstellar medium, forming a bubble called the heliosphere. The edge of this bubble, the heliopause, is the outermost boundary of our solar system, where the solar wind and the interstellar medium meet. Since the solar outflow is highly variable, the heliopause is constantly moving with the motion driven by changes inthe Sun.NASAs twin Voyager spacecraft were poisedto cross the heliopause after completingtheir tour of the outer planets in the 1980s. In 2012, Voyager 1 registered a sharp increase in the density of interstellar particles, indicating that the spacecraft had passed out of the heliosphere and into the interstellar medium. The slower-moving Voyager 2 was set to pierce the heliopause along a different trajectory, but so far no measurements have shown that the spacecraft has bid farewell to oursolar system.In a recent study, ateam of scientists led by Haruichi Washimi (Kyushu University, Japan and CSPAR, University of Alabama-Huntsville) argues that models of the heliosphere can help explain this behavior. Because the heliopause location is controlled by factors that vary on many spatial and temporal scales, Washimiand collaborators turn to three-dimensional, time-dependent magnetohydrodynamics simulations of the heliosphere. In particular, they investigate how the position of the heliopause along the trajectories of Voyager 1 and Voyager 2 changes over time.Modeled location of the heliopause along the paths of Voyagers 1 (blue) and 2 (orange). Click for a closer look. The red star indicates the location at which Voyager
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.
Massie, Danielle L.; Smith, Geoffrey; Bonvechio, Timothy F.; Bunch, Aaron J.; Lucchesi, David O.; Wagner, Tyler
2018-01-01
Quantifying spatial variability in fish growth and identifying large‐scale drivers of growth are fundamental to many conservation and management decisions. Although fish growth studies often focus on a single population, it is becoming increasingly clear that large‐scale studies are likely needed for addressing transboundary management needs. This is particularly true for species with high recreational value and for those with negative ecological consequences when introduced outside of their native range, such as the Flathead Catfish Pylodictis olivaris. This study quantified growth variability of the Flathead Catfish across a large portion of its contemporary range to determine whether growth differences existed between habitat types (i.e., reservoirs and rivers) and between native and introduced populations. Additionally, we investigated whether growth parameters varied as a function of latitude and time since introduction (for introduced populations). Length‐at‐age data from 26 populations across 11 states in the USA were modeled using a Bayesian hierarchical von Bertalanffy growth model. Population‐specific growth trajectories revealed large variation in Flathead Catfish growth and relatively high uncertainty in growth parameters for some populations. Relatively high uncertainty was also evident when comparing populations and when quantifying large‐scale patterns. Growth parameters (Brody growth coefficient [K] and theoretical maximum average length [L∞]) were not different (based on overlapping 90% credible intervals) between habitat types or between native and introduced populations. For populations within the introduced range of Flathead Catfish, latitude was negatively correlated with K. For native populations, we estimated an 85% probability that L∞ estimates were negatively correlated with latitude. Contrary to predictions, time since introduction was not correlated with growth parameters in introduced populations of Flathead Catfish
Growth models and analysis of development
Energy Technology Data Exchange (ETDEWEB)
Mathur, G
1979-10-01
This paper deals with remnants of neoclassical elements in Keynesian and post-Keynesian thought, and attempts to demonstrate that the elimination of these elements from our modes of thinking would not impoverish economic analysis as a means of solving real problems. In the Keynesian analysis the causation from investment to savings is exhibited in terms of income determination. When put in terms of a capital-theory model, the vector of savings is represented in two ways: real savings and counterpart real savings. The former coincides with the investment vector and the latter with the vector of consumption goods foregone for diverting resources towards equipment making. Thus the Keynesian causation in capital theory terms makes the concept of national savings as an independent variable redudant. The Robinsonian causation in a golden age with full employment and its reversal of direction in a steady state with non-employment are then considered. But in each of these, variables like rate of savings and output/capital ratio are found to be dormant variables. They are termed as null variables which, being of no account in both full-employment and unemployment situations, could, without loss, be deleted from the repertory of analytical tools. The Harrod formula of warranted rate of growth, when put in causal form, thus becomes a redundant portion of economics of growth. The real determinants of the growth rate and real wage rate on which the analysis of growth or of development should be based, are also depicted.
Handbook of latent variable and related models
Lee, Sik-Yum
2011-01-01
This Handbook covers latent variable models, which are a flexible class of models for modeling multivariate data to explore relationships among observed and latent variables.- Covers a wide class of important models- Models and statistical methods described provide tools for analyzing a wide spectrum of complicated data- Includes illustrative examples with real data sets from business, education, medicine, public health and sociology.- Demonstrates the use of a wide variety of statistical, computational, and mathematical techniques.
Key variables influencing patterns of lava dome growth and collapse
Husain, T.; Elsworth, D.; Voight, B.; Mattioli, G. S.; Jansma, P. E.
2013-12-01
Lava domes are conical structures that grow by the infusion of viscous silicic or intermediate composition magma from a central volcanic conduit. Dome growth can be characterized by repeated cycles of growth punctuated by collapse, as the structure becomes oversized for its composite strength. Within these cycles, deformation ranges from slow long term deformation to sudden deep-seated collapses. Collapses may range from small raveling failures to voluminous and fast-moving pyroclastic flows with rapid and long-downslope-reach from the edifice. Infusion rate and magma rheology together with crystallization temperature and volatile content govern the spatial distribution of strength in the structure. Solidification, driven by degassing-induced crystallization of magma leads to the formation of a continuously evolving frictional talus as a hard outer shell. This shell encapsulates the cohesion-dominated soft ductile core. Here we explore the mechanics of lava dome growth and failure using a two-dimensional particle-dynamics model. This meshless model follows the natural evolution of a brittle carapace formed by loss of volatiles and rheological stiffening and avoids difficulties of hour-glassing and mesh-entangelment typical in meshed models. We test the fidelity of the model against existing experimental and observational models of lava dome growth. The particle-dynamics model follows the natural development of dome growth and collapse which is infeasible using simple analytical models. The model provides insight into the triggers that lead to the transition in collapse mechasnism from shallow flank collapse to deep seated sector collapse. Increase in material stiffness due to decrease in infusion rate results in the transition of growth pattern from endogenous to exogenous. The material stiffness and strength are strongly controlled by the magma infusion rate. Increase in infusion rate decreases the time available for degassing induced crystallization leading to a
Generalized latent variable modeling multilevel, longitudinal, and structural equation models
Skrondal, Anders; Rabe-Hesketh, Sophia
2004-01-01
This book unifies and extends latent variable models, including multilevel or generalized linear mixed models, longitudinal or panel models, item response or factor models, latent class or finite mixture models, and structural equation models.
A Core Language for Separate Variability Modeling
DEFF Research Database (Denmark)
Iosif-Lazăr, Alexandru Florin; Wasowski, Andrzej; Schaefer, Ina
2014-01-01
Separate variability modeling adds variability to a modeling language without requiring modifications of the language or the supporting tools. We define a core language for separate variability modeling using a single kind of variation point to define transformations of software artifacts in object...... hierarchical dependencies between variation points via copying and flattening. Thus, we reduce a model with intricate dependencies to a flat executable model transformation consisting of simple unconditional local variation points. The core semantics is extremely concise: it boils down to two operational rules...
Latent variable models are network models.
Molenaar, Peter C M
2010-06-01
Cramer et al. present an original and interesting network perspective on comorbidity and contrast this perspective with a more traditional interpretation of comorbidity in terms of latent variable theory. My commentary focuses on the relationship between the two perspectives; that is, it aims to qualify the presumed contrast between interpretations in terms of networks and latent variables.
Model uncertainty in growth empirics
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
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.
In silico modeling for tumor growth visualization.
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.
Dynamic of vapor bubble growth in fields of variable pressure
International Nuclear Information System (INIS)
Pedroso, H.K.
1982-01-01
A mathematical model for the description of the growth from an initial nucleus of a vapor bubble imersed in liquid, subjected to a loss of pressure is presented. The model is important for analysing LOCA (Loss of Coolant Acident) in P.W.R. type reactors. Several simplifications were made in the phenomenum governing equations. With such simplifications the heat diffusion equation became the determining factor for the bubble growth, and the problem was reduced to solve the heat diffusion equation for semi infinite solid whose surface temperature is a well known function of time (it is supposed that the surface temperature is equal to the saturation temperature of the liquid at the system pressure at a given moment). The model results in an analytical expression for the bubble radius as a function of time. Comparisons with experimental data and previous models were made, with reasonable agreement. (author) [pt
Li, Yan; Wagner, Tyler; Jiao, Yan; Lorantas, Robert M.; Murphy, Cheryl
2018-01-01
Understanding the spatial and temporal variability in life-history traits among populations is essential for the management of recreational fisheries. However, valuable freshwater recreational fish species often suffer from a lack of catch information. In this study, we demonstrated the use of an approach to estimate the spatial and temporal variability in growth and mortality in the absence of catch data and apply the method to riverine smallmouth bass (Micropterus dolomieu) populations in Pennsylvania, USA. Our approach included a growth analysis and a length-based analysis that estimates mortality. Using a hierarchical Bayesian approach, we examined spatial variability in growth and mortality by assuming parameters vary spatially but remain constant over time and temporal variability by assuming parameters vary spatially and temporally. The estimated growth and mortality of smallmouth bass showed substantial variability over time and across rivers. We explored the relationships of the estimated growth and mortality with spring water temperature and spring flow. Growth rate was likely to be positively correlated with these two factors, while young mortality was likely to be positively correlated with spring flow. The spatially and temporally varying growth and mortality suggest that smallmouth bass populations across rivers may respond differently to management plans and disturbance such as environmental contamination and land-use change. The analytical approach can be extended to other freshwater recreational species that also lack of catch data. The approach could also be useful in developing population assessments with erroneous catch data or be used as a model sensitivity scenario to verify traditional models even when catch data are available.
Winter Arctic sea ice growth: current variability and projections for the coming decades
Petty, A.; Boisvert, L.; Webster, M.; Holland, M. M.; Bailey, D. A.; Kurtz, N. T.; Markus, T.
2017-12-01
Arctic sea ice increases in both extent and thickness during the cold winter months ( October to May). Winter sea ice growth is an important factor controlling ocean ventilation and winter water/deep water formation, as well as determining the state and vulnerability of the sea ice pack before the melt season begins. Key questions for the Arctic community thus include: (i) what is the current magnitude and variability of winter Arctic sea ice growth and (ii) how might this change in a warming Arctic climate? To address (i), our current best guess of pan-Arctic sea ice thickness, and thus volume, comes from satellite altimetry observations, e.g. from ESA's CryoSat-2 satellite. A significant source of uncertainty in these data come from poor knowledge of the overlying snow depth. Here we present new estimates of winter sea ice thickness from CryoSat-2 using snow depths from a simple snow model forced by reanalyses and satellite-derived ice drift estimates, combined with snow depth estimates from NASA's Operation IceBridge. To address (ii), we use data from the Community Earth System Model's Large Ensemble Project, to explore sea ice volume and growth variability, and how this variability might change over the coming decades. We compare and contrast the model simulations to observations and the PIOMAS ice-ocean model (over recent years/decades). The combination of model and observational analysis provide novel insight into Arctic sea ice volume variability.
Directory of Open Access Journals (Sweden)
Corey Sparks
2009-07-01
Full Text Available This paper presents an analysis of the differential growth rates of the farming and non-farming segments of a rural Scottish community during the 19th and early 20th centuries using the variable-r method allowing for net migration. Using this method, I find that the farming population of Orkney, Scotland, showed less variability in their reproduction and growth rates than the non-farming population during a period of net population decline. I conclude by suggesting that the variable-r method can be used in general cases where the relative growth of subpopulations or subpopulation reproduction is of interest.
National Research Council Canada - National Science Library
Chan, Kwai
2004-01-01
... of aerospace structural alloys. In this three-year program, physics-based fatigue crack initiation and growth models were developed and integrated into a probabilistic micromechanical code for treating fatigue life variability...
Population growth is a variable open to change
Potts, M.
2016-12-01
The absolute number of people and the rate of population growth have an impact on climate mitigation, adaptation and possible conflict. Half the pregnancies in the US are unintended. Robust quantitative evidence from California demonstrates that improving access to family planning is the single most cost-effective way of mitigating our carbon footprint. Globally, there are 80 million unintended pregnancies annually. Many non-evidence barriers deprive women of the information and means required to separate sex from childbearing. Between 1960 and 1990, meeting the need for family planning led to a rapid fall in family size in much of Asia. Since 1990, funding for family planning has collapsed and fertility decline has stalled. The UN projects that by 2100 global population will increase by 3.8 billion (equal to world population in 1975). 80% of this growth will be in Africa. Studies project that climate change will undermine crop yields in parts of Africa, especially the Sahel. A high ratio of young males to the rest of the population is a risk factor in conflict. Today, only 1% of overseas assistance is allocated to family planning. Based on analysis of the past, doubling that investment would accelerate fertility decline, facilitating climate mitigation and adaptation, and possibly reducing conflict. Population and family planning were pushed off the international agenda by unacceptably and tragic episodes of coercion in China and India. However, there is compelling data that when voluntary family planning is widely available then family size can fall rapidly, as occurred in the Islamic Republic of Iran, where fertility fell more rapidly than in any other country in history. Family planning is listening to what women want not telling people want to do. Population growth is a variable open to change in a human rights framework. Population and family planning are variables relevant to the scientific agenda of the AGU.
Mudcake growth: Model and implications
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
Eutrophication Modeling Using Variable Chlorophyll Approach
International Nuclear Information System (INIS)
Abdolabadi, H.; Sarang, A.; Ardestani, M.; Mahjoobi, E.
2016-01-01
In this study, eutrophication was investigated in Lake Ontario to identify the interactions among effective drivers. The complexity of such phenomenon was modeled using a system dynamics approach based on a consideration of constant and variable stoichiometric ratios. The system dynamics approach is a powerful tool for developing object-oriented models to simulate complex phenomena that involve feedback effects. Utilizing stoichiometric ratios is a method for converting the concentrations of state variables. During the physical segmentation of the model, Lake Ontario was divided into two layers, i.e., the epilimnion and hypolimnion, and differential equations were developed for each layer. The model structure included 16 state variables related to phytoplankton, herbivorous zooplankton, carnivorous zooplankton, ammonium, nitrate, dissolved phosphorus, and particulate and dissolved carbon in the epilimnion and hypolimnion during a time horizon of one year. The results of several tests to verify the model, close to 1 Nash-Sutcliff coefficient (0.98), the data correlation coefficient (0.98), and lower standard errors (0.96), have indicated well-suited model’s efficiency. The results revealed that there were significant differences in the concentrations of the state variables in constant and variable stoichiometry simulations. Consequently, the consideration of variable stoichiometric ratios in algae and nutrient concentration simulations may be applied in future modeling studies to enhance the accuracy of the results and reduce the likelihood of inefficient control policies.
Cárdenas-Castro, Manuel; Faúndez-Abarca, Ximena; Arancibia-Martini, Héctor; Ceruti-Mahn, Cristián
2017-08-01
The present study explores reports of growth in survivors and family members of victims of state terrorism ( N = 254) in Chile from 1973 to 1990. The results indicate the presence of reports of posttraumatic growth ( M = 4.69) and a positive and statistically significant correlation with variables related to the life impact of the stressful events ( r = .46), social sharing of emotions ( r = .32), deliberate rumination ( r = .37), positive reappraisal ( r = .35), reconciliation ( r = .39), spiritual practices ( r = .33), and meaning in life ( r = .51). The relationship between growth and forgiveness is not statistically significant. The variables that best predict posttraumatic growth are positive reappraisal (β = .28), life impact (β = .24), meaning in life β = .23), and reconciliation (β = .20). The forward-method hierarchical model indicates that these variables are significant predictors of growth levels, R 2 = .53, F(8, 210) = 30.08, p state terrorism manage to grow after these experiences, and the redefinition of meaning in life and the positive reappraisal of the traumatic experiences are the elements that make it possible to create a new narrative about the past.
Galactic models with variable spiral structure
International Nuclear Information System (INIS)
James, R.A.; Sellwood, J.A.
1978-01-01
A series of three-dimensional computer simulations of disc galaxies has been run in which the self-consistent potential of the disc stars is supplemented by that arising from a small uniform Population II sphere. The models show variable spiral structure, which is more pronounced for thin discs. In addition, the thin discs form weak bars. In one case variable spiral structure associated with this bar has been seen. The relaxed discs are cool outside resonance regions. (author)
A model for AGN variability on multiple time-scales
Sartori, Lia F.; Schawinski, Kevin; Trakhtenbrot, Benny; Caplar, Neven; Treister, Ezequiel; Koss, Michael J.; Urry, C. Megan; Zhang, C. E.
2018-05-01
We present a framework to link and describe active galactic nuclei (AGN) variability on a wide range of time-scales, from days to billions of years. In particular, we concentrate on the AGN variability features related to changes in black hole fuelling and accretion rate. In our framework, the variability features observed in different AGN at different time-scales may be explained as realisations of the same underlying statistical properties. In this context, we propose a model to simulate the evolution of AGN light curves with time based on the probability density function (PDF) and power spectral density (PSD) of the Eddington ratio (L/LEdd) distribution. Motivated by general galaxy population properties, we propose that the PDF may be inspired by the L/LEdd distribution function (ERDF), and that a single (or limited number of) ERDF+PSD set may explain all observed variability features. After outlining the framework and the model, we compile a set of variability measurements in terms of structure function (SF) and magnitude difference. We then combine the variability measurements on a SF plot ranging from days to Gyr. The proposed framework enables constraints on the underlying PSD and the ability to link AGN variability on different time-scales, therefore providing new insights into AGN variability and black hole growth phenomena.
Modeling and control of greenhouse crop growth
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...
Gait variability: methods, modeling and meaning
Directory of Open Access Journals (Sweden)
Hausdorff Jeffrey M
2005-07-01
Full Text Available Abstract The study of gait variability, the stride-to-stride fluctuations in walking, offers a complementary way of quantifying locomotion and its changes with aging and disease as well as a means of monitoring the effects of therapeutic interventions and rehabilitation. Previous work has suggested that measures of gait variability may be more closely related to falls, a serious consequence of many gait disorders, than are measures based on the mean values of other walking parameters. The Current JNER series presents nine reports on the results of recent investigations into gait variability. One novel method for collecting unconstrained, ambulatory data is reviewed, and a primer on analysis methods is presented along with a heuristic approach to summarizing variability measures. In addition, the first studies of gait variability in animal models of neurodegenerative disease are described, as is a mathematical model of human walking that characterizes certain complex (multifractal features of the motor control's pattern generator. Another investigation demonstrates that, whereas both healthy older controls and patients with a higher-level gait disorder walk more slowly in reduced lighting, only the latter's stride variability increases. Studies of the effects of dual tasks suggest that the regulation of the stride-to-stride fluctuations in stride width and stride time may be influenced by attention loading and may require cognitive input. Finally, a report of gait variability in over 500 subjects, probably the largest study of this kind, suggests how step width variability may relate to fall risk. Together, these studies provide new insights into the factors that regulate the stride-to-stride fluctuations in walking and pave the way for expanded research into the control of gait and the practical application of measures of gait variability in the clinical setting.
Gentilesca, Tiziana; Rita, Angelo; Brunetti, Michele; Giammarchi, Francesco; Leonardi, Stefano; Magnani, Federico; van Noije, Twan; Tonon, Giustino; Borghetti, Marco
2018-07-01
In this study, we investigated the role of climatic variability and atmospheric nitrogen deposition in driving long-term tree growth in canopy beech trees along a geographic gradient in the montane belt of the Italian peninsula, from the Alps to the southern Apennines. We sampled dominant trees at different developmental stages (from young to mature tree cohorts, with tree ages spanning from 35 to 160 years) and used stem analysis to infer historic reconstruction of tree volume and dominant height. Annual growth volume (G V ) and height (G H ) variability were related to annual variability in model simulated atmospheric nitrogen deposition and site-specific climatic variables, (i.e. mean annual temperature, total annual precipitation, mean growing period temperature, total growing period precipitation, and standard precipitation evapotranspiration index) and atmospheric CO 2 concentration, including tree cambial age among growth predictors. Generalized additive models (GAM), linear mixed-effects models (LMM), and Bayesian regression models (BRM) were independently employed to assess explanatory variables. The main results from our study were as follows: (i) tree age was the main explanatory variable for long-term growth variability; (ii) GAM, LMM, and BRM results consistently indicated climatic variables and CO 2 effects on G V and G H were weak, therefore evidence of recent climatic variability influence on beech annual growth rates was limited in the montane belt of the Italian peninsula; (iii) instead, significant positive nitrogen deposition (N dep ) effects were repeatedly observed in G V and G H ; the positive effects of N dep on canopy height growth rates, which tended to level off at N dep values greater than approximately 1.0 g m -2 y -1 , were interpreted as positive impacts on forest stand above-ground net productivity at the selected study sites. © 2018 John Wiley & Sons Ltd.
Gaussian Mixture Model of Heart Rate Variability
Costa, Tommaso; Boccignone, Giuseppe; Ferraro, Mario
2012-01-01
Heart rate variability (HRV) is an important measure of sympathetic and parasympathetic functions of the autonomic nervous system and a key indicator of cardiovascular condition. This paper proposes a novel method to investigate HRV, namely by modelling it as a linear combination of Gaussians. Results show that three Gaussians are enough to describe the stationary statistics of heart variability and to provide a straightforward interpretation of the HRV power spectrum. Comparisons have been made also with synthetic data generated from different physiologically based models showing the plausibility of the Gaussian mixture parameters. PMID:22666386
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
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.
Confounding of three binary-variables counterfactual model
Liu, Jingwei; Hu, Shuang
2011-01-01
Confounding of three binary-variables counterfactual model is discussed in this paper. According to the effect between the control variable and the covariate variable, we investigate three counterfactual models: the control variable is independent of the covariate variable, the control variable has the effect on the covariate variable and the covariate variable affects the control variable. Using the ancillary information based on conditional independence hypotheses, the sufficient conditions...
Effects of Population Growth and Climate Variability on Sustainable Groundwater in Mali, West Africa
Directory of Open Access Journals (Sweden)
Alexandra Lutz
2010-12-01
Full Text Available Groundwater is increasingly relied on as a source of potable water in developing countries, but factors such as population growth, development, and climate variability, pose potential challenges for ongoing sustainable supply. The effect of these factors on the groundwater system was considered in four scenarios using a numerical model to represent the Bani area of Mali, West Africa. By 2040, population growth, climate variability, and development as urbanization, agriculture, and industry creates scenarios in which groundwater extraction is an increasingly larger percentage of the groundwater system. Consumption from agriculture and industry increases extraction rates from less than 1 to 3.8% of mean annual precipitation, which will likely affect the groundwater system. For instance, concentrated pumping in local areas may result in water level declines. The results of this study contribute to an ongoing evaluation of sustainable groundwater resources in West Africa.
Mudcake growth: Model and implications
Liu, Q.
2017-12-15
Oil and gas account for 60% of the world\\'s energy consumption. Drilling muds that are used to advance oil and gas wells must be engineered to avoid wellbore integrity problems associated with mud cake formation, to favor cake erosion during 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. The comprehensive mud cake growth model readily accommodates environmental factors (e.g., temperature, pH, and ionic concentration) and defines the yield stress distribution for displacement-erosion analyses. Results show that the mud cake thickness is more sensitive to time than to filtration pressure, therefore, time controls the non-uniform distribution of mudcake thickness during drilling. Long filtration time, high permeability, high salinity, high in-situ temperature and low viscosity exacerbate fluid loss and give rise to thick filter cakes. The analysis of residual cake thickness during cement displacement must take into account the effective stress dependent mudcake formation and the time-dependent mud thixotropy. Thixotropy dominates the mud yield stress at high void ratios, e.g. e > 20. The offsetting force that causes differential pressure sticking increases sub-linearly as a power function of the still-time.
The growth of optically variable features on banknotes
Lancaster, Ian M.; Mitchell, Astrid
2004-06-01
Public verification features are part of a matrix of security features on banknotes which allow the authenticity of legitimate banknotes to be established. They are characterised by being overt and easy to verify -- no examination tool or equipment is required even though the devices themselves are invariably highly sophisticated. Recent developments, though, combine overt and covert elements which may reqire inspection tools. Traditionally, banknote issuers were reluctant to involve the general public in the checking of banknotes, preferring to rely on those employed to handle them, experts and machinery to authenticate the various (normally undisclosed) features. This has now changed as the ability to counterfeit has moved from those highly skilled in printing to anyone with a scanner and computer -- the incidence of counterfeiting has grown exponentially in the last decade. Three techniques for what can be categorized as public verification features have been used for banknotes for many decades and continue to provide a barrier to counterfeiting: (1) the optical effects of watermarks; (2) the appearance and tactile characteristics of cylinder mould-made paper; (3) the tactile characteristics of intaglio print. Since the 1980s the emergence of threads and optically variable features have added to the available features which can be utilized on banknotes for public verification purposes. OVDs fall broadly into the two categories of diffraction and color shift. Products which utilize the former include holograms, kinegrams and other devices originated with similar techniques and bearing a variety of proprietary names, but collectively known as diffractive optically variable image devices (DOVIDs). All share the fundamental characteristic of changing in appearance according to the viewing angle, providing an effective barrier to the increasingly common use of digital reprographic technology as a counterfeiting tool as well as a simple means for verification by the
Directory of Open Access Journals (Sweden)
Iman Dadashi
2013-04-01
Full Text Available The primary objective of this study is to investigate the effect of growth and financial strength variables on the financial leverage for some listed companies in the Tehran Stock Exchange. For this purpose, a sample of 700 firm-years among listed companies in the Tehran Stock Exchange over the period 2006-2010 was examined. In the present study, the growth variables, including asset growth, profit growth and sales growth; and financial strength calculated by the Altman Z-bankruptcy model have been considered as independent variables. In addition, the ratios of long-term debt to total assets, long-term debt to fixed assets, total long-term debt and short-term receivable facilities to equity capital and total long-term debt and short-term receivable facilities to total assets are used as measures of financial leverage and dependent variables. The results indicate that there is a negative and significant relationship between assets growth and some indexes of financial leverage. There is also a positive and significant relationship between the variables of profit growth, sales growth and financial strength with financial leverage measures.
Variable selection and model choice in geoadditive regression models.
Kneib, Thomas; Hothorn, Torsten; Tutz, Gerhard
2009-06-01
Model choice and variable selection are issues of major concern in practical regression analyses, arising in many biometric applications such as habitat suitability analyses, where the aim is to identify the influence of potentially many environmental conditions on certain species. We describe regression models for breeding bird communities that facilitate both model choice and variable selection, by a boosting algorithm that works within a class of geoadditive regression models comprising spatial effects, nonparametric effects of continuous covariates, interaction surfaces, and varying coefficients. The major modeling components are penalized splines and their bivariate tensor product extensions. All smooth model terms are represented as the sum of a parametric component and a smooth component with one degree of freedom to obtain a fair comparison between the model terms. A generic representation of the geoadditive model allows us to devise a general boosting algorithm that automatically performs model choice and variable selection.
Natural climate variability in a coupled model
International Nuclear Information System (INIS)
Zebiak, S.E.; Cane, M.A.
1990-01-01
Multi-century simulations with a simplified coupled ocean-atmosphere model are described. These simulations reveal an impressive range of variability on decadal and longer time scales, in addition to the dominant interannual el Nino/Southern Oscillation signal that the model originally was designed to simulate. Based on a very large sample of century-long simulations, it is nonetheless possible to identify distinct model parameter sensitivities that are described here in terms of selected indices. Preliminary experiments motivated by general circulation model results for increasing greenhouse gases suggest a definite sensitivity to model global warming. While these results are not definitive, they strongly suggest that coupled air-sea dynamics figure prominently in global change and must be included in models for reliable predictions
Bubenheim, David L.; Schlick, Greg; Genovese, Vanessa; Wilson, Kenneth D.
2018-01-01
Management of aquatic weeds in complex watersheds and river systems present many challenges to assessment, planning and implementation of management practices for floating and submerged aquatic invasive plants. The Delta Region Areawide Aquatic Weed Project (DRAAWP), a USDA sponsored area-wide project, is working to enhance planning, decision-making and operational efficiency in the California Sacramento-San Joaquin Delta. Satellite and airborne remote sensing are used map (area coverage and biomass density), direct operations, and assess management impacts on plant communities. Archived satellite records enable review of results following previous climate and management events and aide in developing long-term strategies. Examples of remote sensing aiding effectiveness of aquatic weed management will be discussed as well as areas for potential technological improvement. Modeling at local and watershed scales using the SWAT modeling tool provides insight into land-use effects on water quality (described by Zhang in same Symposium). Controlled environment growth studies have been conducted to quantify the growth response of invasive aquatic plants to water quality and other environmental factors. Environmental variability occurs across a range of time scales from long-term climate and seasonal trends to short-term water flow mediated variations. Response time for invasive species response are examined at time scales of weeks, day, and hours using a combination of study duration and growth assessment techniques to assess water quality, temperature (air and water), nitrogen, phosphorus, and light effects. These provide response parameters for plant growth models in response to the variation and interact with management and economic models associated with aquatic weed management. Plant growth models are to be informed by remote sensing and applied spatially across the Delta to balance location and type of aquatic plant, growth response to altered environments and
Human Capital Variables and Economic Growth in Nigeria: An Interactive Effect
Directory of Open Access Journals (Sweden)
Adenike Mosunmola Osoba
2017-05-01
Full Text Available Various studies have focused on the relationship between human capital and economic growth all over the world. However, there is still a missing gap on the joint influence of human capital investment components on economic growth particularly in Nigeria. This study therefore examines the interactive effects of the relationship between human capital investment components and economic growth in Nigeria for the period of 1986 – 2014. The study employed secondary annual data on education expenditure, health expenditure, real gross domestic product and gross capital formation obtained from the Central Bank Statistical bulletin, 2014. The data were analyzed using Fully Modified Ordinary Least Squares (FMOLS technique. The results of the study showed that there was positive and significant relationship between the interactive effects of human capital components and growth in Nigeria. The study concluded that the interactive effect of the human capital variables was also in conformity with the theoretical proposition that increase in human capital will enhance growth as stipulated in the modified Solow growth model by Mankiw, Romer & Weil (1992.
Jauch, Edward C; Lindsell, Christopher J; Adeoye, Opeolu; Khoury, Jane; Barsan, William; Broderick, Joseph; Pancioli, Arthur; Brott, Thomas
2006-08-01
Early hematoma expansion in spontaneous intracerebral hemorrhage (ICH) is associated with worse clinical outcome. We hypothesized that hemodynamic parameters are associated with the increase in hematoma volume owing to their relationship to blood vessel wall stresses. We performed a post hoc analysis of clinical and computed tomography (CT) data from patients enrolled in a prospective observational study of ICH patients presenting within 3 hours from symptom onset. Hematoma volumes were measured at hospital arrival and at 1 and 20 hours from presentation. Blood pressure and heart rate, recorded at 19 time points between presentation and 20 hours, were used to derive hemodynamic variables. Multivariable logistic-regression models were constructed to assess the relation between hemodynamic parameters and hematoma growth, adjusted for clinical covariates. From the original study, 98 patients underwent baseline and 1-hour CT scans; of these, 65 had 20-hour CT scans. Substantial hematoma growth was observed in 28% within the first hour. Of the 65 patients not undergoing surgery within 20 hours, 37% experienced hematoma growth by 20 hours. Neither baseline or peak hemodynamic parameters nor changes in hemodynamic parameters were significantly associated with hematoma growth at either 1 or 20 hours. We found no blood pressure or heart rate parameters, individually or in combination, that were associated with hematoma growth. Our data suggest the influence of hemodynamic parameters on vessel wall stress to be an unlikely target for intervention in reducing the risk of early hematoma growth in ICH.
On Latent Growth Models for Composites and Their Constituents.
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.
A Model for Positively Correlated Count Variables
DEFF Research Database (Denmark)
Møller, Jesper; Rubak, Ege Holger
2010-01-01
An α-permanental random field is briefly speaking a model for a collection of non-negative integer valued random variables with positive associations. Though such models possess many appealing probabilistic properties, many statisticians seem unaware of α-permanental random fields...... and their potential applications. The purpose of this paper is to summarize useful probabilistic results, study stochastic constructions and simulation techniques, and discuss some examples of α-permanental random fields. This should provide a useful basis for discussing the statistical aspects in future work....
Mathematical modeling of microbial growth in milk
Directory of Open Access Journals (Sweden)
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.
Itter, Malcolm S.; Finley, Andrew O.; D'Amato, Anthony W.; Foster, Jane R.; Bradford, John B.
2017-01-01
Changes in the frequency, duration, and severity of climate extremes are forecast to occur under global climate change. The impacts of climate extremes on forest productivity and health remain difficult to predict due to potential interactions with disturbance events and forest dynamics—changes in forest stand composition, density, size and age structure over time. Such interactions may lead to non-linear forest growth responses to climate involving thresholds and lag effects. Understanding how forest dynamics influence growth responses to climate is particularly important given stand structure and composition can be modified through management to increase forest resistance and resilience to climate change. To inform such adaptive management, we develop a hierarchical Bayesian state space model in which climate effects on tree growth are allowed to vary over time and in relation to past climate extremes, disturbance events, and forest dynamics. The model is an important step toward integrating disturbance and forest dynamics into predictions of forest growth responses to climate extremes. We apply the model to a dendrochronology data set from forest stands of varying composition, structure, and development stage in northeastern Minnesota that have experienced extreme climate years and forest tent caterpillar defoliation events. Mean forest growth was most sensitive to water balance variables representing climatic water deficit. Forest growth responses to water deficit were partitioned into responses driven by climatic threshold exceedances and interactions with insect defoliation. Forest growth was both resistant and resilient to climate extremes with the majority of forest growth responses occurring after multiple climatic threshold exceedances across seasons and years. Interactions between climate and disturbance were observed in a subset of years with insect defoliation increasing forest growth sensitivity to water availability. Forest growth was particularly
Itter, Malcolm S; Finley, Andrew O; D'Amato, Anthony W; Foster, Jane R; Bradford, John B
2017-06-01
Changes in the frequency, duration, and severity of climate extremes are forecast to occur under global climate change. The impacts of climate extremes on forest productivity and health remain difficult to predict due to potential interactions with disturbance events and forest dynamics-changes in forest stand composition, density, size and age structure over time. Such interactions may lead to non-linear forest growth responses to climate involving thresholds and lag effects. Understanding how forest dynamics influence growth responses to climate is particularly important given stand structure and composition can be modified through management to increase forest resistance and resilience to climate change. To inform such adaptive management, we develop a hierarchical Bayesian state space model in which climate effects on tree growth are allowed to vary over time and in relation to past climate extremes, disturbance events, and forest dynamics. The model is an important step toward integrating disturbance and forest dynamics into predictions of forest growth responses to climate extremes. We apply the model to a dendrochronology data set from forest stands of varying composition, structure, and development stage in northeastern Minnesota that have experienced extreme climate years and forest tent caterpillar defoliation events. Mean forest growth was most sensitive to water balance variables representing climatic water deficit. Forest growth responses to water deficit were partitioned into responses driven by climatic threshold exceedances and interactions with insect defoliation. Forest growth was both resistant and resilient to climate extremes with the majority of forest growth responses occurring after multiple climatic threshold exceedances across seasons and years. Interactions between climate and disturbance were observed in a subset of years with insect defoliation increasing forest growth sensitivity to water availability. Forest growth was particularly
Latent Growth and Dynamic Structural Equation Models.
Grimm, Kevin J; Ram, Nilam
2018-05-07
Latent growth models make up a class of methods to study within-person change-how it progresses, how it differs across individuals, what are its determinants, and what are its consequences. Latent growth methods have been applied in many domains to examine average and differential responses to interventions and treatments. In this review, we introduce the growth modeling approach to studying change by presenting different models of change and interpretations of their model parameters. We then apply these methods to examining sex differences in the development of binge drinking behavior through adolescence and into adulthood. Advances in growth modeling methods are then discussed and include inherently nonlinear growth models, derivative specification of growth models, and latent change score models to study stochastic change processes. We conclude with relevant design issues of longitudinal studies and considerations for the analysis of longitudinal data.
Provenance variability in nursery growth of subalpine fir
Charlie Cartwright; Cheng Ying
2011-01-01
Subalpine fir (Abies lasiocarpa [Hook] Nutt.) is a wide-ranging, high-elevation species in the interior of British Columbia. It is commonly harvested for lumber, but replanting of it is limited. Some reticence is based upon wood quality and rate of growth, but there are also seed and nursery culturing difficulties. This study investigated seedling growth traits of 111...
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.
DEFF Research Database (Denmark)
Jónsdóttir, Kristjana Ýr; Schmiegel, Jürgen; Jensen, Eva Bjørn Vedel
2008-01-01
In the present paper, we give a condensed review, for the nonspecialist reader, of a new modelling framework for spatio-temporal processes, based on Lévy theory. We show the potential of the approach in stochastic geometry and spatial statistics by studying Lévy-based growth modelling of planar o...... objects. The growth models considered are spatio-temporal stochastic processes on the circle. As a by product, flexible new models for space–time covariance functions on the circle are provided. An application of the Lévy-based growth models to tumour growth is discussed....
Modeling the variability of shapes of a human placenta.
Yampolsky, M; Salafia, C M; Shlakhter, O; Haas, D; Eucker, B; Thorp, J
2008-09-01
Placentas are generally round/oval in shape, but "irregular" shapes are common. In the Collaborative Perinatal Project data, irregular shapes were associated with lower birth weight for placental weight, suggesting variably shaped placentas have altered function. (I) Using a 3D one-parameter model of placental vascular growth based on Diffusion Limited Aggregation (an accepted model for generating highly branched fractals), models were run with a branching density growth parameter either fixed or perturbed at either 5-7% or 50% of model growth. (II) In a data set with detailed measures of 1207 placental perimeters, radial standard deviations of placental shapes were calculated from the umbilical cord insertion, and from the centroid of the shape (a biologically arbitrary point). These two were compared to the difference between the observed scaling exponent and the Kleiber scaling exponent (0.75), considered optimal for vascular fractal transport systems. Spearman's rank correlation considered pcentroid) was associated with differences from the Kleiber exponent (p=0.006). A dynamical DLA model recapitulates multilobate and "star" placental shapes via changing fractal branching density. We suggest that (1) irregular placental outlines reflect deformation of the underlying placental fractal vascular network, (2) such irregularities in placental outline indicate sub-optimal branching structure of the vascular tree, and (3) this accounts for the lower birth weight observed in non-round/oval placentas in the Collaborative Perinatal Project.
Stochastic models for tumoral growth
Escudero, Carlos
2006-01-01
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 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 stoch...
The Biasing Effects of Unmodeled ARMA Time Series Processes on Latent Growth Curve Model Estimates
Sivo, Stephen; Fan, Xitao; Witta, Lea
2005-01-01
The purpose of this study was to evaluate the robustness of estimated growth curve models when there is stationary autocorrelation among manifest variable errors. The results suggest that when, in practice, growth curve models are fitted to longitudinal data, alternative rival hypotheses to consider would include growth models that also specify…
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.
Frost Growth and Densification on a Flat Surface in Laminar Flow with Variable Humidity
Kandula, M.
2012-01-01
Experiments are performed concerning frost growth and densification in laminar flow over a flat surface under conditions of constant and variable humidity. The flat plate test specimen is made of aluminum-6031, and has dimensions of 0.3 mx0.3 mx6.35 mm. Results for the first variable humidity case are obtained for a plate temperature of 255.4 K, air velocity of 1.77 m/s, air temperature of 295.1 K, and a relative humidity continuously ranging from 81 to 54%. The second variable humidity test case corresponds to plate temperature of 255.4 K, air velocity of 2.44 m/s, air temperature of 291.8 K, and a relative humidity ranging from 66 to 59%. Results for the constant humidity case are obtained for a plate temperature of 263.7 K, air velocity of 1.7 m/s, air temperature of 295 K, and a relative humidity of 71.6 %. Comparisons of the data with the author's frost model extended to accommodate variable humidity suggest satisfactory agreement between the theory and the data for both constant and variable humidity.
Entanglement Growth in Quench Dynamics with Variable Range Interactions
Directory of Open Access Journals (Sweden)
J. Schachenmayer
2013-09-01
Full Text Available Studying entanglement growth in quantum dynamics provides both insight into the underlying microscopic processes and information about the complexity of the quantum states, which is related to the efficiency of simulations on classical computers. Recently, experiments with trapped ions, polar molecules, and Rydberg excitations have provided new opportunities to observe dynamics with long-range interactions. We explore nonequilibrium coherent dynamics after a quantum quench in such systems, identifying qualitatively different behavior as the exponent of algebraically decaying spin-spin interactions in a transverse Ising chain is varied. Computing the buildup of bipartite entanglement as well as mutual information between distant spins, we identify linear growth of entanglement entropy corresponding to propagation of quasiparticles for shorter-range interactions, with the maximum rate of growth occurring when the Hamiltonian parameters match those for the quantum phase transition. Counterintuitively, the growth of bipartite entanglement for long-range interactions is only logarithmic for most regimes, i.e., substantially slower than for shorter-range interactions. Experiments with trapped ions allow for the realization of this system with a tunable interaction range, and we show that the different phenomena are robust for finite system sizes and in the presence of noise. These results can act as a direct guide for the generation of large-scale entanglement in such experiments, towards a regime where the entanglement growth can render existing classical simulations inefficient.
Directory of Open Access Journals (Sweden)
Nicolas Latte
2016-08-01
Full Text Available Global change—particularly climate change, forest management, and atmospheric deposition—has significantly altered forest growing conditions in Europe. The influences of these changes on beech growth (Fagus sylvatica L. were investigated for the past 80 years in Belgium, using non-linear mixed effects models on ring-width chronologies of 149 mature and dominant beech trees (87–186 years old. The effects of the developmental stage (i.e., increasing tree size were filtered out in order to focus on time-dependent growth changes. Beech radial growth was divided into a low-frequency signal (=growth rate, mainly influenced by forest management and atmospheric deposition, and into a high-frequency variability (≈mean sensitivity, mainly influenced by climate change. Between 1930 and 2008, major long-term and time-dependent changes were highlighted. The beech growth rate has decreased by about 38% since the 1950–1960s, and growth variability has increased by about 45% since the 1970–1980s. Our results indicate that (1 before the 1980s, beech growth rate was not predominantly impacted by climate change but rather by soil alteration (i.e., soil compaction and/or nitrogen deposition; and (2 since the 1980s, climate change induced more frequent and intense yearly growth reductions that amplified the growth rate decrease. The highlighted changes were similar in the two ecoregions of Belgium, although more pronounced in the lowlands than in the uplands.
On the growth estimates of entire functions of double complex variables
Directory of Open Access Journals (Sweden)
Sanjib Datta
2017-08-01
Full Text Available Recently Datta et al. (2016 introduced the idea of relative type and relative weak type of entire functions of two complex variables with respect to another entire function of two complex variables and prove some related growth properties of it. In this paper, further we study some growth properties of entire functions of two complex variables on the basis of their relative types and relative weak types as introduced by Datta et al (2016.
Testing mechanistic models of growth in insects.
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).
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.
Theoretical growth rates, periods, and pulsation constants for long-period variables
International Nuclear Information System (INIS)
Fox, M.W.; Wood, P.R.
1982-01-01
Theoretical values of the growth rate, period, and pulsation constant for the first three radial pulsation modes in red giants (Population II and galactic disk) and supergiants have been derived in the linear, nonadiabatic approximation. The effects of altering the surface boundary conditions, the effective temperature (or mixing length), and the opacity in the outer layers have been explored. In the standard models, the Q-value for the first overtone can be much larger (Q 1 1 roughly-equal0.04); in addition, the Q-value for the fundamental mode is reduced from previous values, as is the period ratio P 0 /P 1 . The growth rate for the fundamental mode is found to increase with luminosity on the giant branch while the growth rate for the first overtone decreases. Dynamical instabilities found in previous adiabatic models of extreme red giants do not occur when nonadiabatic effects are included in the models. In some massive, luminous models, period ratios P 0 /P 1 approx.7 occur when P 0 approx.2000--5000 days; it is suggested that the massive galactic supergiants and carbon stars which have secondary periods Papprox.2000--7000 days and primary periods Papprox.300--700 days are first-overtone pulsators in which the long secondary periods are due to excitation of the fundamental mode. Some other consequences of the present results are briefly discussed, with particular emphasis on the mode of pulsation of the Mira variables. Subject headings: stars: long-period variables: stars: pulsation: stars: supergiants
A mean-field game economic growth model
Gomes, Diogo A.; Lafleche, Laurent; Nurbekyan, Levon
2016-01-01
Here, we examine a mean-field game (MFG) that models the economic growth of a population of non-cooperative, rational agents. In this MFG, agents are described by two state variables - the capital and consumer goods they own. Each agent seeks
Error-in-variables models in calibration
Lira, I.; Grientschnig, D.
2017-12-01
In many calibration operations, the stimuli applied to the measuring system or instrument under test are derived from measurement standards whose values may be considered to be perfectly known. In that case, it is assumed that calibration uncertainty arises solely from inexact measurement of the responses, from imperfect control of the calibration process and from the possible inaccuracy of the calibration model. However, the premise that the stimuli are completely known is never strictly fulfilled and in some instances it may be grossly inadequate. Then, error-in-variables (EIV) regression models have to be employed. In metrology, these models have been approached mostly from the frequentist perspective. In contrast, not much guidance is available on their Bayesian analysis. In this paper, we first present a brief summary of the conventional statistical techniques that have been developed to deal with EIV models in calibration. We then proceed to discuss the alternative Bayesian framework under some simplifying assumptions. Through a detailed example about the calibration of an instrument for measuring flow rates, we provide advice on how the user of the calibration function should employ the latter framework for inferring the stimulus acting on the calibrated device when, in use, a certain response is measured.
Pollution externalities in a Schumpeterian growth model
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...
Preliminary Multi-Variable Parametric Cost Model for Space Telescopes
Stahl, H. Philip; Hendrichs, Todd
2010-01-01
This slide presentation reviews creating a preliminary multi-variable cost model for the contract costs of making a space telescope. There is discussion of the methodology for collecting the data, definition of the statistical analysis methodology, single variable model results, testing of historical models and an introduction of the multi variable models.
Modeling variability in porescale multiphase flow experiments
Ling, Bowen; Bao, Jie; Oostrom, Mart; Battiato, Ilenia; Tartakovsky, Alexandre M.
2017-07-01
Microfluidic devices and porescale numerical models are commonly used to study multiphase flow in biological, geological, and engineered porous materials. In this work, we perform a set of drainage and imbibition experiments in six identical microfluidic cells to study the reproducibility of multiphase flow experiments. We observe significant variations in the experimental results, which are smaller during the drainage stage and larger during the imbibition stage. We demonstrate that these variations are due to sub-porescale geometry differences in microcells (because of manufacturing defects) and variations in the boundary condition (i.e., fluctuations in the injection rate inherent to syringe pumps). Computational simulations are conducted using commercial software STAR-CCM+, both with constant and randomly varying injection rates. Stochastic simulations are able to capture variability in the experiments associated with the varying pump injection rate.
Growth Curve Models and Applications : Indian Statistical Institute
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...
How to get rid of W: a latent variables approach to modelling spatially lagged variables
Folmer, H.; Oud, J.
2008-01-01
In this paper we propose a structural equation model (SEM) with latent variables to model spatial dependence. Rather than using the spatial weights matrix W, we propose to use latent variables to represent spatial dependence and spillover effects, of which the observed spatially lagged variables are
How to get rid of W : a latent variables approach to modelling spatially lagged variables
Folmer, Henk; Oud, Johan
2008-01-01
In this paper we propose a structural equation model (SEM) with latent variables to model spatial dependence. Rather than using the spatial weights matrix W, we propose to use latent variables to represent spatial dependence and spillover effects, of which the observed spatially lagged variables are
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....
Quantifying Variability in Growth and Thermal Inactivation Kinetics of Lactobacillus plantarum.
Aryani, D C; den Besten, H M W; Zwietering, M H
2016-08-15
The presence and growth of spoilage organisms in food might affect the shelf life. In this study, the effects of experimental, reproduction, and strain variabilities were quantified with respect to growth and thermal inactivation using 20 Lactobacillus plantarum strains. Also, the effect of growth history on thermal resistance was quantified. The strain variability in μmax was similar (P > 0.05) to reproduction variability as a function of pH, aw, and temperature, while being around half of the reproduction variability (P plantarum strains, and the pHmin was between 3.2 and 3.5, the aw,min was between 0.936 and 0.953, the [HLamax], at pH 4.5, was between 29 and 38 mM, and the Tmin was between 3.4 and 8.3°C. The average D values ranged from 0.80 min to 19 min at 55°C, 0.22 to 3.9 min at 58°C, 3.1 to 45 s at 60°C, and 1.8 to 19 s at 63°C. In contrast to growth, the strain variability in thermal resistance was on average six times higher than the reproduction variability and more than ten times higher than the experimental variability. The strain variability was also 1.8 times higher (P 10-log10 differences after thermal treatment. Accurate control and realistic prediction of shelf life is complicated by the natural diversity among microbial strains, and limited information on microbiological variability is available for spoilage microorganisms. Therefore, the objectives of the present study were to quantify strain variability, reproduction (biological) variability, and experimental variability with respect to the growth and thermal inactivation kinetics of Lactobacillus plantarum and to quantify the variability in thermal resistance attributed to growth history. The quantitative knowledge obtained on experimental, reproduction, and strain variabilities can be used to improve experimental designs and to adequately select strains for challenge growth and inactivation tests. Moreover, the integration of strain variability in prediction of microbial growth and
Stochastic modeling of thermal fatigue crack growth
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...
Severe linear growth retardation in rural Zambian children: the influence of biological variables.
Hautvast, J.L.A.; Tolboom, J.J.M.; Kaftwembe, E.M.; Musonda, R.M.; Mwanakasale, V.; Staveren, W.A. van; Hof, M.A. van 't; Sauerwein, R.W.; Willems, J.L.; Monnens, L.A.H.
2000-01-01
BACKGROUND: The prevalence of stunting in preschool children in Zambia is high; stunting has detrimental effects on concurrent psychomotor development and later working capacity. OBJECTIVE: Our objective was to investigate biological variables that may contribute to linear growth retardation in
Growth curve models and statistical diagnostics
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.
Bayesian modeling of measurement error in predictor variables
Fox, Gerardus J.A.; Glas, Cornelis A.W.
2003-01-01
It is shown that measurement error in predictor variables can be modeled using item response theory (IRT). The predictor variables, that may be defined at any level of an hierarchical regression model, are treated as latent variables. The normal ogive model is used to describe the relation between
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.
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
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.
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.
Institution, Financial Sector, and Economic Growth: Use The Institutions As An Instrument Variable
Directory of Open Access Journals (Sweden)
Albertus Girik Allo
2016-06-01
Full Text Available Institution has been investigated having indirect role on economic growth. This paper aims to evaluate whether the quality of institution matters for economic growth. By applying institution as instrumental variable at Foreign Direct Investment (FDI, quality of institution significantly influence economic growth. This study applies two set of data period, namely 1985-2013 and 2000-2013, available online in the World Bank (WB. The first data set, 1985-2013 is used to estimate the role of financial sector on economic growth, focuses on 67 countries. The second data set, 2000-2013 determine the role of institution on financial sector and economic growth by applying 2SLS estimation method. We define institutional variables as set of indicators: Control of Corruption, Political Stability and Absence of Violence, and Voice and Accountability provide declining impact of FDI to economic growth.
Variability in urban soils influences the health and growth of native tree seedlings
Clara C. Pregitzer; Nancy F. Sonti; Richard A. Hallett
2016-01-01
Reforesting degraded urban landscapes is important due to the many benefits urban forests provide. Urban soils are highly variable, yet little is known about how this variability in urban soils influences tree seedling performance and survival. We conducted a greenhouse study to assess health, growth, and survival of four native tree species growing in native glacial...
Institution, Financial Sector, and Economic Growth: Use The Institutions As An Instrument Variable
Albertus Girik Allo
2016-01-01
Institution has been investigated having indirect role on economic growth. This paper aims to evaluate whether the quality of institution matters for economic growth. By applying institution as instrumental variable at Foreign Direct Investment (FDI), quality of institution significantly influence economic growth. This study applies two set of data period, namely 1985-2013 and 2000-2013, available online in the World Bank (WB). The first data set, 1985-2013 is used to estimate the role of fin...
Legros, S; Mialet-Serra, I; Caliman, J-P; Siregar, F A; Clément-Vidal, A; Dingkuhn, M
2009-11-01
Oil palm flowering and fruit production show seasonal maxima whose causes are unknown. Drought periods confound these rhythms, making it difficult to analyse or predict dynamics of production. The present work aims to analyse phenological and growth responses of adult oil palms to seasonal and inter-annual climatic variability. Two oil palm genotypes planted in a replicated design at two sites in Indonesia underwent monthly observations during 22 months in 2006-2008. Measurements included growth of vegetative and reproductive organs, morphology and phenology. Drought was estimated from climatic water balance (rainfall - potential evapotranspiration) and simulated fraction of transpirable soil water. Production history of the same plants for 2001-2005 was used for inter-annual analyses. Drought was absent at the equatorial Kandista site (0 degrees 55'N) but the Batu Mulia site (3 degrees 12'S) had a dry season with variable severity. Vegetative growth and leaf appearance rate fluctuated with drought level. Yield of fruit, a function of the number of female inflorescences produced, was negatively correlated with photoperiod at Kandista. Dual annual maxima were observed supporting a recent theory of circadian control. The photoperiod-sensitive phases were estimated at 9 (or 9 + 12 x n) months before bunch maturity for a given phytomer. The main sensitive phase for drought effects was estimated at 29 months before bunch maturity, presumably associated with inflorescence sex determination. It is assumed that seasonal peaks of flowering in oil palm are controlled even near the equator by photoperiod response within a phytomer. These patterns are confounded with drought effects that affect flowering (yield) with long time-lag. Resulting dynamics are complex, but if the present results are confirmed it will be possible to predict them with models.
Kinetic Model of Growth of Arthropoda Populations
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.
Compatible growth models and stand density diagrams
International Nuclear Information System (INIS)
Smith, N.J.; Brand, D.G.
1988-01-01
This paper discusses a stand average growth model based on the self-thinning rule developed and used to generate stand density diagrams. Procedures involved in testing are described and results are included
Drag coefficient Variability and Thermospheric models
Moe, Kenneth
Satellite drag coefficients depend upon a variety of factors: The shape of the satellite, its altitude, the eccentricity of its orbit, the temperature and mean molecular mass of the ambient atmosphere, and the time in the sunspot cycle. At altitudes where the mean free path of the atmospheric molecules is large compared to the dimensions of the satellite, the drag coefficients can be determined from the theory of free-molecule flow. The dependence on altitude is caused by the concentration of atomic oxygen which plays an important role by its ability to adsorb on the satellite surface and thereby affect the energy loss of molecules striking the surface. The eccentricity of the orbit determines the satellite velocity at perigee, and therefore the energy of the incident molecules relative to the energy of adsorption of atomic oxygen atoms on the surface. The temperature of the ambient atmosphere determines the extent to which the random thermal motion of the molecules influences the momentum transfer to the satellite. The time in the sunspot cycle affects the ambient temperature as well as the concentration of atomic oxygen at a particular altitude. Tables and graphs will be used to illustrate the variability of drag coefficients. Before there were any measurements of gas-surface interactions in orbit, Izakov and Cook independently made an excellent estimate that the drag coefficient of satellites of compact shape would be 2.2. That numerical value, independent of altitude, was used by Jacchia to construct his model from the early measurements of satellite drag. Consequently, there is an altitude dependent bias in the model. From the sparce orbital experiments that have been done, we know that the molecules which strike satellite surfaces rebound in a diffuse angular distribution with an energy loss given by the energy accommodation coefficient. As more evidence accumulates on the energy loss, more realistic drag coefficients are being calculated. These improved drag
Ringeval, B.; de Noblet-Ducoudre, N.; Prigent, C.; Bousquet, P.
2006-12-01
The atmospheric methane growth rate presents lots of seasonal and year-to-year variations. Large uncertainties still exist in the relative part of differents sources and sinks on these variations. We have considered, in this study, the main natural sources of methane and the supposed main variable source, i.e. wetlands, and tried to simulate the variations of their emissions considering the variability of the wetland extent and of the climate. For this study, we use the methane emission model of Walter et al. (2001) and the quantification of the flooded areas for the years 1993-2000 obtained with a suite of satellite observations by Prigent et al. (2001). The data necessary to the Walter's model are obtained with simulation of a dynamic global vegetation model ORCHIDEE (Krinner et al. (2005)) constrained by the NCC climate data (Ngo-Duc et al. (2005)) and after imposing a water-saturated soil to approach productivity of wetlands. We calculate global annual methane emissions from wetlands to be 400 Tg per year, that is higher than previous results obtained with fixed wetland extent. Simulations are realised to estimate the part of variability in the emissions explained by the variability of the wetland extent. It seems that the year-to-year emission variability is mainly explained by the interannual variability of wetland extent. The seasonnal variability is explained for 75% in the tropics and only for 40% in the north of 30°N by variability of wetlands extend. Finally, we compare results with a top-down approach of Bousquet et al.(2006).
Value function in economic growth model
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.
Reactive burn models and ignition & growth concept
Directory of Open Access Journals (Sweden)
Shaw M.S.
2011-01-01
Full Text Available Plastic-bonded explosives are heterogeneous materials. Experimentally, shock initiation is sensitive to small amounts of porosity, due to the formation of hot spots (small localized regions of high temperature. This leads to the Ignition & Growth concept, introduced by LeeTarver in 1980, as the basis for reactive burn models. A homo- genized burn rate needs to account for three meso-scale physical effects: (i the density of active hot spots or burn centers; (ii the growth of the burn fronts triggered by the burn centers; (iii a geometric factor that accounts for the overlap of deflagration wavelets from adjacent burn centers. These effects can be combined and the burn model defined by specifying the reaction progress variable λ = g(s as a function of a dimensionless reaction length s(t = rbc/ℓbc, rather than by specifying an explicit burn rate. The length scale ℓbc(Ps = [Nbc(Ps]−1/3 is the average distance between burn centers, where Nbc is the number density of burn centers activated by the lead shock. The reaction length rbc(t = ∫t0 D(P(t′dt′ is the distance the burn front propagates from a single burn center, where D(P is the deflagration speed as a function of the local pressure and t is the time since the shock arrival. A key implementation issue is how to determine the lead shock strength in conjunction with a shock capturing scheme. We have developed a robust algorithm for this purpose based on the Hugoniot jump condition for the energy. The algorithm utilizes the time dependence of density, pressure and energy within each cell. The method is independent of the numerical dissipation used for shock capturing. It is local and can be used in one or more space dimensions. The burn model has a small number of parameters which can be calibrated to fit velocity gauge data from shock initiation experiments.
Tax Evasion and Economic Growth in an Endogenous Growth Model
加藤, 秀弥; KATO, Hideya
2004-01-01
This paper presents an endogenous growth model with tax evasion where government expenditures affect production. An individual evades a tax so as to maximize his or her utility, the tax authority controls the detection probability to maximize net tax revenue, and the government chooses the income tax rate to maximize individuals’ utility. The main conclusions are as follows. First, the optical income tax rate with tax evasion is higher than that without tax evasion. Second, the rise in a ...
Resolving structural variability in network models and the brain.
Directory of Open Access Journals (Sweden)
Florian Klimm
2014-03-01
Full Text Available Large-scale white matter pathways crisscrossing the cortex create a complex pattern of connectivity that underlies human cognitive function. Generative mechanisms for this architecture have been difficult to identify in part because little is known in general about mechanistic drivers of structured networks. Here we contrast network properties derived from diffusion spectrum imaging data of the human brain with 13 synthetic network models chosen to probe the roles of physical network embedding and temporal network growth. We characterize both the empirical and synthetic networks using familiar graph metrics, but presented here in a more complete statistical form, as scatter plots and distributions, to reveal the full range of variability of each measure across scales in the network. We focus specifically on the degree distribution, degree assortativity, hierarchy, topological Rentian scaling, and topological fractal scaling--in addition to several summary statistics, including the mean clustering coefficient, the shortest path-length, and the network diameter. The models are investigated in a progressive, branching sequence, aimed at capturing different elements thought to be important in the brain, and range from simple random and regular networks, to models that incorporate specific growth rules and constraints. We find that synthetic models that constrain the network nodes to be physically embedded in anatomical brain regions tend to produce distributions that are most similar to the corresponding measurements for the brain. We also find that network models hardcoded to display one network property (e.g., assortativity do not in general simultaneously display a second (e.g., hierarchy. This relative independence of network properties suggests that multiple neurobiological mechanisms might be at play in the development of human brain network architecture. Together, the network models that we develop and employ provide a potentially useful
Piecewise Linear-Linear Latent Growth Mixture Models with Unknown Knots
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…
Walenga, Ross L; Longest, P Worth; Kaviratna, Anubhav; Hindle, Michael
2017-06-01
Nebulized aerosol drug delivery during the administration of noninvasive positive pressure ventilation (NPPV) is commonly implemented. While studies have shown improved patient outcomes for this therapeutic approach, aerosol delivery efficiency is reported to be low with high variability in lung-deposited dose. Excipient enhanced growth (EEG) aerosol delivery is a newly proposed technique that may improve drug delivery efficiency and reduce intersubject aerosol delivery variability when coupled with NPPV. A combined approach using in vitro experiments and computational fluid dynamics (CFD) was used to characterize aerosol delivery efficiency during NPPV in two new nasal cavity models that include face mask interfaces. Mesh nebulizer and in-line dry powder inhaler (DPI) sources of conventional and EEG aerosols were both considered. Based on validated steady-state CFD predictions, EEG aerosol delivery improved lung penetration fraction (PF) values by factors ranging from 1.3 to 6.4 compared with conventional-sized aerosols. Furthermore, intersubject variability in lung PF was very high for conventional aerosol sizes (relative differences between subjects in the range of 54.5%-134.3%) and was reduced by an order of magnitude with the EEG approach (relative differences between subjects in the range of 5.5%-17.4%). Realistic in vitro experiments of cyclic NPPV demonstrated similar trends in lung delivery to those observed with the steady-state simulations, but with lower lung delivery efficiencies. Reaching the lung delivery efficiencies reported with the steady-state simulations of 80%-90% will require synchronization of aerosol administration during inspiration and reducing the size of the EEG aerosol delivery unit. The EEG approach enabled high-efficiency lung delivery of aerosols administered during NPPV and reduced intersubject aerosol delivery variability by an order of magnitude. Use of an in-line DPI device that connects to the NPPV mask appears to be a
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…
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
Reactor scale modeling of multi-walled carbon nanotube growth
International Nuclear Information System (INIS)
Lombardo, Jeffrey J.; Chiu, Wilson K.S.
2011-01-01
As the mechanisms of carbon nanotube (CNT) growth becomes known, it becomes important to understand how to implement this knowledge into reactor scale models to optimize CNT growth. In past work, we have reported fundamental mechanisms and competing deposition regimes that dictate single wall carbon nanotube growth. In this study, we will further explore the growth of carbon nanotubes with multiple walls. A tube flow chemical vapor deposition reactor is simulated using the commercial software package COMSOL, and considered the growth of single- and multi-walled carbon nanotubes. It was found that the limiting reaction processes for multi-walled carbon nanotubes change at different temperatures than the single walled carbon nanotubes and it was shown that the reactions directly governing CNT growth are a limiting process over certain parameters. This work shows that the optimum conditions for CNT growth are dependent on temperature, chemical concentration, and the number of nanotube walls. Optimal reactor conditions have been identified as defined by (1) a critical inlet methane concentration that results in hydrogen abstraction limited versus hydrocarbon adsorption limited reaction kinetic regime, and (2) activation energy of reaction for a given reactor temperature and inlet methane concentration. Successful optimization of a CNT growth processes requires taking all of those variables into account.
Generalized Network Psychometrics : Combining Network and Latent Variable Models
Epskamp, S.; Rhemtulla, M.; Borsboom, D.
2017-01-01
We introduce the network model as a formal psychometric model, conceptualizing the covariance between psychometric indicators as resulting from pairwise interactions between observable variables in a network structure. This contrasts with standard psychometric models, in which the covariance between
McNeish, Daniel; Dumas, Denis
2017-01-01
Recent methodological work has highlighted the promise of nonlinear growth models for addressing substantive questions in the behavioral sciences. In this article, we outline a second-order nonlinear growth model in order to measure a critical notion in development and education: potential. Here, potential is conceptualized as having three components-ability, capacity, and availability-where ability is the amount of skill a student is estimated to have at a given timepoint, capacity is the maximum amount of ability a student is predicted to be able to develop asymptotically, and availability is the difference between capacity and ability at any particular timepoint. We argue that single timepoint measures are typically insufficient for discerning information about potential, and we therefore describe a general framework that incorporates a growth model into the measurement model to capture these three components. Then, we provide an illustrative example using the public-use Early Childhood Longitudinal Study-Kindergarten data set using a Michaelis-Menten growth function (reparameterized from its common application in biochemistry) to demonstrate our proposed model as applied to measuring potential within an educational context. The advantage of this approach compared to currently utilized methods is discussed as are future directions and limitations.
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
Localisation in a Growth Model with Interaction
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.
Residual Structures in Latent Growth Curve Modeling
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…
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
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.
Predictor variable resolution governs modeled soil types
Soil mapping identifies different soil types by compressing a unique suite of spatial patterns and processes across multiple spatial scales. It can be quite difficult to quantify spatial patterns of soil properties with remotely sensed predictor variables. More specifically, matching the right scale...
Modeling Coast Redwood Variable Retention Management Regimes
John-Pascal Berrill; Kevin O' Hara
2007-01-01
Variable retention is a flexible silvicultural system that provides forest managers with an alternative to clearcutting. While much of the standing volume is removed in one harvesting operation, residual stems are retained to provide structural complexity and wildlife habitat functions, or to accrue volume before removal during subsequent stand entries. The residual...
Variable Fidelity Aeroelastic Toolkit - Structural Model, Phase I
National Aeronautics and Space Administration — The proposed innovation is a methodology to incorporate variable fidelity structural models into steady and unsteady aeroelastic and aeroservoelastic analyses in...
Multi-wheat-model ensemble responses to interannual climatic variability
DEFF Research Database (Denmark)
Ruane, A C; Hudson, N I; Asseng, S
2016-01-01
We compare 27 wheat models' yield responses to interannual climate variability, analyzed at locations in Argentina, Australia, India, and The Netherlands as part of the Agricultural Model Intercomparison and Improvement Project (AgMIP) Wheat Pilot. Each model simulated 1981–2010 grain yield, and ......-term warming, suggesting that additional processes differentiate climate change impacts from observed climate variability analogs and motivating continuing analysis and model development efforts.......We compare 27 wheat models' yield responses to interannual climate variability, analyzed at locations in Argentina, Australia, India, and The Netherlands as part of the Agricultural Model Intercomparison and Improvement Project (AgMIP) Wheat Pilot. Each model simulated 1981–2010 grain yield, and we...... evaluate results against the interannual variability of growing season temperature, precipitation, and solar radiation. The amount of information used for calibration has only a minor effect on most models' climate response, and even small multi-model ensembles prove beneficial. Wheat model clusters reveal...
ABOUT PSYCHOLOGICAL VARIABLES IN APPLICATION SCORING MODELS
Directory of Open Access Journals (Sweden)
Pablo Rogers
2015-01-01
Full Text Available The purpose of this study is to investigate the contribution of psychological variables and scales suggested by Economic Psychology in predicting individuals’ default. Therefore, a sample of 555 individuals completed a self-completion questionnaire, which was composed of psychological variables and scales. By adopting the methodology of the logistic regression, the following psychological and behavioral characteristics were found associated with the group of individuals in default: a negative dimensions related to money (suffering, inequality and conflict; b high scores on the self-efficacy scale, probably indicating a greater degree of optimism and over-confidence; c buyers classified as compulsive; d individuals who consider it necessary to give gifts to children and friends on special dates, even though many people consider this a luxury; e problems of self-control identified by individuals who drink an average of more than four glasses of alcoholic beverage a day.
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.
Beauregard, Frieda; de Blois, Sylvie
2014-01-01
Both climatic and edaphic conditions determine plant distribution, however many species distribution models do not include edaphic variables especially over large geographical extent. Using an exceptional database of vegetation plots (n = 4839) covering an extent of ∼55,000 km2, we tested whether the inclusion of fine scale edaphic variables would improve model predictions of plant distribution compared to models using only climate predictors. We also tested how well these edaphic variables could predict distribution on their own, to evaluate the assumption that at large extents, distribution is governed largely by climate. We also hypothesized that the relative contribution of edaphic and climatic data would vary among species depending on their growth forms and biogeographical attributes within the study area. We modelled 128 native plant species from diverse taxa using four statistical model types and three sets of abiotic predictors: climate, edaphic, and edaphic-climate. Model predictive accuracy and variable importance were compared among these models and for species' characteristics describing growth form, range boundaries within the study area, and prevalence. For many species both the climate-only and edaphic-only models performed well, however the edaphic-climate models generally performed best. The three sets of predictors differed in the spatial information provided about habitat suitability, with climate models able to distinguish range edges, but edaphic models able to better distinguish within-range variation. Model predictive accuracy was generally lower for species without a range boundary within the study area and for common species, but these effects were buffered by including both edaphic and climatic predictors. The relative importance of edaphic and climatic variables varied with growth forms, with trees being more related to climate whereas lower growth forms were more related to edaphic conditions. Our study identifies the potential
Directory of Open Access Journals (Sweden)
Frieda Beauregard
Full Text Available Both climatic and edaphic conditions determine plant distribution, however many species distribution models do not include edaphic variables especially over large geographical extent. Using an exceptional database of vegetation plots (n = 4839 covering an extent of ∼55,000 km2, we tested whether the inclusion of fine scale edaphic variables would improve model predictions of plant distribution compared to models using only climate predictors. We also tested how well these edaphic variables could predict distribution on their own, to evaluate the assumption that at large extents, distribution is governed largely by climate. We also hypothesized that the relative contribution of edaphic and climatic data would vary among species depending on their growth forms and biogeographical attributes within the study area. We modelled 128 native plant species from diverse taxa using four statistical model types and three sets of abiotic predictors: climate, edaphic, and edaphic-climate. Model predictive accuracy and variable importance were compared among these models and for species' characteristics describing growth form, range boundaries within the study area, and prevalence. For many species both the climate-only and edaphic-only models performed well, however the edaphic-climate models generally performed best. The three sets of predictors differed in the spatial information provided about habitat suitability, with climate models able to distinguish range edges, but edaphic models able to better distinguish within-range variation. Model predictive accuracy was generally lower for species without a range boundary within the study area and for common species, but these effects were buffered by including both edaphic and climatic predictors. The relative importance of edaphic and climatic variables varied with growth forms, with trees being more related to climate whereas lower growth forms were more related to edaphic conditions. Our study
Multi-Wheat-Model Ensemble Responses to Interannual Climate Variability
Ruane, Alex C.; Hudson, Nicholas I.; Asseng, Senthold; Camarrano, Davide; Ewert, Frank; Martre, Pierre; Boote, Kenneth J.; Thorburn, Peter J.; Aggarwal, Pramod K.; Angulo, Carlos
2016-01-01
We compare 27 wheat models' yield responses to interannual climate variability, analyzed at locations in Argentina, Australia, India, and The Netherlands as part of the Agricultural Model Intercomparison and Improvement Project (AgMIP) Wheat Pilot. Each model simulated 1981e2010 grain yield, and we evaluate results against the interannual variability of growing season temperature, precipitation, and solar radiation. The amount of information used for calibration has only a minor effect on most models' climate response, and even small multi-model ensembles prove beneficial. Wheat model clusters reveal common characteristics of yield response to climate; however models rarely share the same cluster at all four sites indicating substantial independence. Only a weak relationship (R2 0.24) was found between the models' sensitivities to interannual temperature variability and their response to long-termwarming, suggesting that additional processes differentiate climate change impacts from observed climate variability analogs and motivating continuing analysis and model development efforts.
Investigation of Mediational Processes Using Parallel Process Latent Growth Curve Modeling
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
Variable selection in Logistic regression model with genetic algorithm.
Zhang, Zhongheng; Trevino, Victor; Hoseini, Sayed Shahabuddin; Belciug, Smaranda; Boopathi, Arumugam Manivanna; Zhang, Ping; Gorunescu, Florin; Subha, Velappan; Dai, Songshi
2018-02-01
Variable or feature selection is one of the most important steps in model specification. Especially in the case of medical-decision making, the direct use of a medical database, without a previous analysis and preprocessing step, is often counterproductive. In this way, the variable selection represents the method of choosing the most relevant attributes from the database in order to build a robust learning models and, thus, to improve the performance of the models used in the decision process. In biomedical research, the purpose of variable selection is to select clinically important and statistically significant variables, while excluding unrelated or noise variables. A variety of methods exist for variable selection, but none of them is without limitations. For example, the stepwise approach, which is highly used, adds the best variable in each cycle generally producing an acceptable set of variables. Nevertheless, it is limited by the fact that it commonly trapped in local optima. The best subset approach can systematically search the entire covariate pattern space, but the solution pool can be extremely large with tens to hundreds of variables, which is the case in nowadays clinical data. Genetic algorithms (GA) are heuristic optimization approaches and can be used for variable selection in multivariable regression models. This tutorial paper aims to provide a step-by-step approach to the use of GA in variable selection. The R code provided in the text can be extended and adapted to other data analysis needs.
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.
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 ...
Fixed transaction costs and modelling limited dependent variables
Hempenius, A.L.
1994-01-01
As an alternative to the Tobit model, for vectors of limited dependent variables, I suggest a model, which follows from explicitly using fixed costs, if appropriate of course, in the utility function of the decision-maker.
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....
Black, Bryan A.; Dunham, Jason B.; Blundon, Brett W.; Raggon, Mark F.; Zima, Daniela
2010-01-01
Estimates of historical variability in river ecosystems are often lacking, but long-lived freshwater mussels could provide unique opportunities to understand past conditions in these environments. We applied dendrochronology techniques to quantify historical variability in growth-increment widths in valves (shells) of western pearlshell freshwater mussels (Margaritifera falcata). A total of 3 growth-increment chronologies, spanning 19 to 26 y in length, were developed. Growth was highly synchronous among individuals within each site, and to a lesser extent, chronologies were synchronous among sites. All 3 chronologies negatively related to instrumental records of stream discharge, while correlations with measures of water temperature were consistently positive but weaker. A reconstruction of stream discharge was performed using linear regressions based on a mussel growth chronology and the regional Palmer Drought Severity Index (PDSI). Models based on mussel growth and PDSI yielded similar coefficients of prediction (R2Pred) of 0.73 and 0.77, respectively, for predicting out-ofsample observations. From an ecological perspective, we found that mussel chronologies provided a rich source of information for understanding climate impacts. Responses of mussels to changes in climate and stream ecosystems can be very site- and process-specific, underscoring the complex nature of biotic responses to climate change and the need to understand both regional and local processes in projecting climate impacts on freshwater species.
Coevolution of variability models and related software artifacts
DEFF Research Database (Denmark)
Passos, Leonardo; Teixeira, Leopoldo; Dinztner, Nicolas
2015-01-01
models coevolve with other artifact types, we study a large and complex real-world variant-rich software system: the Linux kernel. Specifically, we extract variability-coevolution patterns capturing changes in the variability model of the Linux kernel with subsequent changes in Makefiles and C source...
Fatigue Crack and Delamination Growth in Fibre Metal Laminates under Variable Amplitude Loading
Khan, S.
2013-01-01
This thesis presents the investigation into the fatigue propagation and delamination growth of Fibre Metal Laminates under variable amplitude loading. As explained in the first chapter, the motivation of the research is twofold: first, to obtain a clear understanding and detailed characterization of
Contributions of cell growth and biochemical reactions to nongenetic variability of cells.
Schwabe, A.; Bruggeman, F.J.
2014-01-01
Cell-to-cell variability in the molecular composition of isogenic, steady-state growing cells arises spontaneously from the inherent stochasticity of intracellular biochemical reactions and cell growth. Here, we present a general decomposition of the total variance in the copy number per cell of a
Defining a Family of Cognitive Diagnosis Models Using Log-Linear Models with Latent Variables
Henson, Robert A.; Templin, Jonathan L.; Willse, John T.
2009-01-01
This paper uses log-linear models with latent variables (Hagenaars, in "Loglinear Models with Latent Variables," 1993) to define a family of cognitive diagnosis models. In doing so, the relationship between many common models is explicitly defined and discussed. In addition, because the log-linear model with latent variables is a general model for…
Modeling Fish Growth in Low Dissolved Oxygen
Neilan, Rachael Miller
2013-01-01
This article describes a computational project designed for undergraduate students as an introduction to mathematical modeling. Students use an ordinary differential equation to describe fish weight and assume the instantaneous growth rate depends on the concentration of dissolved oxygen. Published laboratory experiments suggest that continuous…
Stochastic Growth Models with No Discounting
Czech Academy of Sciences Publication Activity Database
Sladký, Karel
2007-01-01
Roč. 15, č. 4 (2007), s. 88-98 ISSN 0572-3043 R&D Projects: GA ČR(CZ) GA402/06/0990; GA ČR GA402/05/0115 Institutional research plan: CEZ:AV0Z10750506 Keywords : economic dynamics * stochastic version of the Ramsey growth model * Markov decision processes Subject RIV: AH - Economics
Nationwide Macroeconomic Variables and the Growth Rate of Bariatric Surgeries in Brazil.
Cazzo, Everton; Ramos, Almino Cardoso; Pareja, José Carlos; Chaim, Elinton Adami
2018-06-06
The effect of nationwide economic issues on the necessary expansion in the number of bariatric procedures remains unclear. This study aims to determine whether there are correlations between the growth rate in the number of bariatric surgeries and the major macroeconomic variables over time in Brazil. It is a nationwide analysis regarding the number of bariatric surgeries in Brazil and the main national macroeconomic variables from 2003 through 2016: gross domestic product (GDP), inflation rate, and the unemployment rate, as well as the evolution in the number of registered bariatric surgeons. There were significant positive correlations of the growth rate of surgeries with the early variations of the GDP (R = 0.5558; p = 0.04863) and of the overall health expenditure per capita (R = 0.78322; p = 0.00259). The growth rate of the number of bariatric surgeries was not correlated with the unemployment and inflation rates, as well as with the growth rate of available bariatric surgeons. There were direct relationships between the growth rate of bariatric surgeries and the evolutions of the GDP and health care expenditure per capita. These variables appear to influence the nationwide offer of bariatric surgery.
Variable Selection for Regression Models of Percentile Flows
Fouad, G.
2017-12-01
Percentile flows describe the flow magnitude equaled or exceeded for a given percent of time, and are widely used in water resource management. However, these statistics are normally unavailable since most basins are ungauged. Percentile flows of ungauged basins are often predicted using regression models based on readily observable basin characteristics, such as mean elevation. The number of these independent variables is too large to evaluate all possible models. A subset of models is typically evaluated using automatic procedures, like stepwise regression. This ignores a large variety of methods from the field of feature (variable) selection and physical understanding of percentile flows. A study of 918 basins in the United States was conducted to compare an automatic regression procedure to the following variable selection methods: (1) principal component analysis, (2) correlation analysis, (3) random forests, (4) genetic programming, (5) Bayesian networks, and (6) physical understanding. The automatic regression procedure only performed better than principal component analysis. Poor performance of the regression procedure was due to a commonly used filter for multicollinearity, which rejected the strongest models because they had cross-correlated independent variables. Multicollinearity did not decrease model performance in validation because of a representative set of calibration basins. Variable selection methods based strictly on predictive power (numbers 2-5 from above) performed similarly, likely indicating a limit to the predictive power of the variables. Similar performance was also reached using variables selected based on physical understanding, a finding that substantiates recent calls to emphasize physical understanding in modeling for predictions in ungauged basins. The strongest variables highlighted the importance of geology and land cover, whereas widely used topographic variables were the weakest predictors. Variables suffered from a high
Variability aware compact model characterization for statistical circuit design optimization
Qiao, Ying; Qian, Kun; Spanos, Costas J.
2012-03-01
Variability modeling at the compact transistor model level can enable statistically optimized designs in view of limitations imposed by the fabrication technology. In this work we propose an efficient variabilityaware compact model characterization methodology based on the linear propagation of variance. Hierarchical spatial variability patterns of selected compact model parameters are directly calculated from transistor array test structures. This methodology has been implemented and tested using transistor I-V measurements and the EKV-EPFL compact model. Calculation results compare well to full-wafer direct model parameter extractions. Further studies are done on the proper selection of both compact model parameters and electrical measurement metrics used in the method.
Walenga, Ross L.; Kaviratna, Anubhav; Hindle, Michael
2017-01-01
Abstract Background: Nebulized aerosol drug delivery during the administration of noninvasive positive pressure ventilation (NPPV) is commonly implemented. While studies have shown improved patient outcomes for this therapeutic approach, aerosol delivery efficiency is reported to be low with high variability in lung-deposited dose. Excipient enhanced growth (EEG) aerosol delivery is a newly proposed technique that may improve drug delivery efficiency and reduce intersubject aerosol delivery variability when coupled with NPPV. Materials and Methods: A combined approach using in vitro experiments and computational fluid dynamics (CFD) was used to characterize aerosol delivery efficiency during NPPV in two new nasal cavity models that include face mask interfaces. Mesh nebulizer and in-line dry powder inhaler (DPI) sources of conventional and EEG aerosols were both considered. Results: Based on validated steady-state CFD predictions, EEG aerosol delivery improved lung penetration fraction (PF) values by factors ranging from 1.3 to 6.4 compared with conventional-sized aerosols. Furthermore, intersubject variability in lung PF was very high for conventional aerosol sizes (relative differences between subjects in the range of 54.5%–134.3%) and was reduced by an order of magnitude with the EEG approach (relative differences between subjects in the range of 5.5%–17.4%). Realistic in vitro experiments of cyclic NPPV demonstrated similar trends in lung delivery to those observed with the steady-state simulations, but with lower lung delivery efficiencies. Reaching the lung delivery efficiencies reported with the steady-state simulations of 80%–90% will require synchronization of aerosol administration during inspiration and reducing the size of the EEG aerosol delivery unit. Conclusions: The EEG approach enabled high-efficiency lung delivery of aerosols administered during NPPV and reduced intersubject aerosol delivery variability by an order of magnitude. Use of an in
Variable amplitude fatigue, modelling and testing
International Nuclear Information System (INIS)
Svensson, Thomas.
1993-01-01
Problems related to metal fatigue modelling and testing are here treated in four different papers. In the first paper different views of the subject are summarised in a literature survey. In the second paper a new model for fatigue life is investigated. Experimental results are established which are promising for further development of the mode. In the third paper a method is presented that generates a stochastic process, suitable to fatigue testing. The process is designed in order to resemble certain fatigue related features in service life processes. In the fourth paper fatigue problems in transport vibrations are treated
Trape, S.; Durand, J.-D.; Vigliola, L.; Panfili, J.
2017-11-01
With the persistence of a drought since the late 1960s, some West African estuaries became permanently reversed in term of salinity gradient and hypersaline waters are present in their upstream part (salinity >60). To understand the mechanisms regulating fish recruitment intensity in these estuaries and evaluate the consequences of freshwater shortages on juvenile habitat quality, a growth study was conducted in the Saloum hypersaline estuary (Senegal). The Mugilidae fish family, highly representative of estuarine environments, was targeted and several species sampled (Chelon dumerili, Mugil bananensis and M. cf. curema sp. M). Juveniles were sampled monthly all the year round in three areas of the estuary exhibiting strongly contrasted habitat conditions. Otolith sections were used to estimate the ages, reconstruct growth trajectories, estimate the duration of the oceanic larval phase, and evaluate juvenile growth variability along the salinity gradient. Analyses revealed that the temporal recruitment variability of C. dumerili, with 2 annual cohorts, was not mainly induced by growth-selection mechanisms, but probably more by predation pressures. Juveniles exhibited significantly faster growth rates in the lower salinity suggesting that benthic food availability was a strong factor controlling habitat quality of early juveniles. Salinity had also a clear impact when reducing the growth in hypersaline conditions and/or selecting slower growing individuals. Moderate freshwater inputs positively affected the nursery function of the estuary for mugilids by enhancing the productivity of the first trophic levels. In a long term, the global change could have an impact of the mugilid fishery and its management.
modelling relationship between rainfall variability and yields
African Journals Online (AJOL)
, S. and ... factors to rice yield. Adebayo and Adebayo (1997) developed double log multiple regression model to predict rice yield in Adamawa State, Nigeria. The general form of .... the second are the crop yield/values for millet and sorghum ...
Mathematical foundations of the dendritic growth models.
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.
Linear latent variable models: the lava-package
DEFF Research Database (Denmark)
Holst, Klaus Kähler; Budtz-Jørgensen, Esben
2013-01-01
are implemented including robust standard errors for clustered correlated data, multigroup analyses, non-linear parameter constraints, inference with incomplete data, maximum likelihood estimation with censored and binary observations, and instrumental variable estimators. In addition an extensive simulation......An R package for specifying and estimating linear latent variable models is presented. The philosophy of the implementation is to separate the model specification from the actual data, which leads to a dynamic and easy way of modeling complex hierarchical structures. Several advanced features...
Variability in growth rates of larval haddock in the northern North Sea
DEFF Research Database (Denmark)
Gallego, A.; Heath, M.R.; Basford, D.J.
1999-01-01
of the spring plankton production bloom, and a likely explanation for the absence of environmental effects on larval growth was high food availability and larval feeding rates. Nevertheless, differences in growth were observed between cohorts, with larvae hatched later in the spring displaying higher growth...... at age than those hatched earlier. Particle-tracking modelling suggested that differences in temperature history between cohorts, on their own or compounded by a potential interaction between temperature and the development of plankton production, may explain the higher growth rate of the larvae hatched...
Modeling error distributions of growth curve models through Bayesian methods.
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.
Metabolic enzyme cost explains variable trade-offs between microbial growth rate and yield.
Directory of Open Access Journals (Sweden)
Meike T Wortel
2018-02-01
Full Text Available Microbes may maximize the number of daughter cells per time or per amount of nutrients consumed. These two strategies correspond, respectively, to the use of enzyme-efficient or substrate-efficient metabolic pathways. In reality, fast growth is often associated with wasteful, yield-inefficient metabolism, and a general thermodynamic trade-off between growth rate and biomass yield has been proposed to explain this. We studied growth rate/yield trade-offs by using a novel modeling framework, Enzyme-Flux Cost Minimization (EFCM and by assuming that the growth rate depends directly on the enzyme investment per rate of biomass production. In a comprehensive mathematical model of core metabolism in E. coli, we screened all elementary flux modes leading to cell synthesis, characterized them by the growth rates and yields they provide, and studied the shape of the resulting rate/yield Pareto front. By varying the model parameters, we found that the rate/yield trade-off is not universal, but depends on metabolic kinetics and environmental conditions. A prominent trade-off emerges under oxygen-limited growth, where yield-inefficient pathways support a 2-to-3 times higher growth rate than yield-efficient pathways. EFCM can be widely used to predict optimal metabolic states and growth rates under varying nutrient levels, perturbations of enzyme parameters, and single or multiple gene knockouts.
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...
The Impact of Key Monetary Variables on the Economic Growth of the CEMAC Zone
Directory of Open Access Journals (Sweden)
Forgha Godfrey NJIMANTED
2016-09-01
Full Text Available This study seeks to empirically explore the impact of key monetary policy variables on the economic growth in the CEMAC zone from the period of 1981 to 2015. Carried out using the Ex post facto research design based on the principal components selection approach, the study interacts money supply, interest rate, economic growth, and inflation rate, among themselves and their lagged values using the Vector Auto-regressive (VAR analytical technique. The Classical quantity theory of money, the Cambridge Cash Balanced, the liquidity preference theory and the Monetarists as theoretical frameworks were explored to appreciate the time trends of the selected variables on the economic growth of the CEMAC zone. Based on the (VAR methodology, the study reveals that key monetary policy variables influence economic growth of the CEMAC zone in different ways with inflation rate as the impact factor. On the basis of the above findings and the evidence from other studies, lending and inflation rate generated substantial destabilizing impacts on the economic growth, suggesting that the monetary authorities should play a critical role in creating an enabling environment for growth. The determination of the optimal lending rate should reflect the overall internal rate of returns in the productive sectors with due attention to market fundamentals. In line with this, the Central Bank of CEMAC should be given complete instrumental autonomy to operate depending on a set of in-built targets by the individual countries of the zone. Effective monetary targeting and accommodating monetary policies should be designed and implemented as the need arises with little or no political motives.
Predicting Madura cattle growth curve using non-linear model
Widyas, N.; Prastowo, S.; Widi, T. S. M.; Baliarti, E.
2018-03-01
Madura cattle is Indonesian native. It is a composite breed that has undergone hundreds of years of selection and domestication to reach nowadays remarkable uniformity. Crossbreeding has reached the isle of Madura and the Madrasin, a cross between Madura cows and Limousine semen emerged. This paper aimed to compare the growth curve between Madrasin and one type of pure Madura cows, the common Madura cattle (Madura) using non-linear models. Madura cattles are kept traditionally thus reliable records are hardly available. Data were collected from small holder farmers in Madura. Cows from different age classes (5years) were observed, and body measurements (chest girth, body length and wither height) were taken. In total 63 Madura and 120 Madrasin records obtained. Linear model was built with cattle sub-populations and age as explanatory variables. Body weights were estimated based on the chest girth. Growth curves were built using logistic regression. Results showed that within the same age, Madrasin has significantly larger body compared to Madura (plogistic models fit better for Madura and Madrasin cattle data; with the estimated MSE for these models were 39.09 and 759.28 with prediction accuracy of 99 and 92% for Madura and Madrasin, respectively. Prediction of growth curve using logistic regression model performed well in both types of Madura cattle. However, attempts to administer accurate data on Madura cattle are necessary to better characterize and study these cattle.
A geometric model for magnetizable bodies with internal variables
Directory of Open Access Journals (Sweden)
Restuccia, L
2005-11-01
Full Text Available In a geometrical framework for thermo-elasticity of continua with internal variables we consider a model of magnetizable media previously discussed and investigated by Maugin. We assume as state variables the magnetization together with its space gradient, subjected to evolution equations depending on both internal and external magnetic fields. We calculate the entropy function and necessary conditions for its existence.
Variable-Structure Control of a Model Glider Airplane
Waszak, Martin R.; Anderson, Mark R.
2008-01-01
A variable-structure control system designed to enable a fuselage-heavy airplane to recover from spin has been demonstrated in a hand-launched, instrumented model glider airplane. Variable-structure control is a high-speed switching feedback control technique that has been developed for control of nonlinear dynamic systems.
Verification of models for ballistic movement time and endpoint variability.
Lin, Ray F; Drury, Colin G
2013-01-01
A hand control movement is composed of several ballistic movements. The time required in performing a ballistic movement and its endpoint variability are two important properties in developing movement models. The purpose of this study was to test potential models for predicting these two properties. Twelve participants conducted ballistic movements of specific amplitudes using a drawing tablet. The measured data of movement time and endpoint variability were then used to verify the models. This study was successful with Hoffmann and Gan's movement time model (Hoffmann, 1981; Gan and Hoffmann 1988) predicting more than 90.7% data variance for 84 individual measurements. A new theoretically developed ballistic movement variability model, proved to be better than Howarth, Beggs, and Bowden's (1971) model, predicting on average 84.8% of stopping-variable error and 88.3% of aiming-variable errors. These two validated models will help build solid theoretical movement models and evaluate input devices. This article provides better models for predicting end accuracy and movement time of ballistic movements that are desirable in rapid aiming tasks, such as keying in numbers on a smart phone. The models allow better design of aiming tasks, for example button sizes on mobile phones for different user populations.
Interdecadal variability in a global coupled model
International Nuclear Information System (INIS)
Storch, J.S. von.
1994-01-01
Interdecadal variations are studied in a 325-year simulation performed by a coupled atmosphere - ocean general circulation model. The patterns obtained in this study may be considered as characteristic patterns for interdecadal variations. 1. The atmosphere: Interdecadal variations have no preferred time scales, but reveal well-organized spatial structures. They appear as two modes, one is related with variations of the tropical easterlies and the other with the Southern Hemisphere westerlies. Both have red spectra. The amplitude of the associated wind anomalies is largest in the upper troposphere. The associated temperature anomalies are in thermal-wind balance with the zonal winds and are out-of-phase between the troposphere and the lower stratosphere. 2. The Pacific Ocean: The dominant mode in the Pacific appears to be wind-driven in the midlatitudes and is related to air-sea interaction processes during one stage of the oscillation in the tropics. Anomalies of this mode propagate westward in the tropics and the northward (southwestward) in the North (South) Pacific on a time scale of about 10 to 20 years. (orig.)
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.
Spatial variability and parametric uncertainty in performance assessment models
International Nuclear Information System (INIS)
Pensado, Osvaldo; Mancillas, James; Painter, Scott; Tomishima, Yasuo
2011-01-01
The problem of defining an appropriate treatment of distribution functions (which could represent spatial variability or parametric uncertainty) is examined based on a generic performance assessment model for a high-level waste repository. The generic model incorporated source term models available in GoldSim ® , the TDRW code for contaminant transport in sparse fracture networks with a complex fracture-matrix interaction process, and a biosphere dose model known as BDOSE TM . Using the GoldSim framework, several Monte Carlo sampling approaches and transport conceptualizations were evaluated to explore the effect of various treatments of spatial variability and parametric uncertainty on dose estimates. Results from a model employing a representative source and ensemble-averaged pathway properties were compared to results from a model allowing for stochastic variation of transport properties along streamline segments (i.e., explicit representation of spatial variability within a Monte Carlo realization). We concluded that the sampling approach and the definition of an ensemble representative do influence consequence estimates. In the examples analyzed in this paper, approaches considering limited variability of a transport resistance parameter along a streamline increased the frequency of fast pathways resulting in relatively high dose estimates, while those allowing for broad variability along streamlines increased the frequency of 'bottlenecks' reducing dose estimates. On this basis, simplified approaches with limited consideration of variability may suffice for intended uses of the performance assessment model, such as evaluation of site safety. (author)
Resolving the Complex Genetic Basis of Phenotypic Variation and Variability of Cellular Growth.
Ziv, Naomi; Shuster, Bentley M; Siegal, Mark L; Gresham, David
2017-07-01
In all organisms, the majority of traits vary continuously between individuals. Explaining the genetic basis of quantitative trait variation requires comprehensively accounting for genetic and nongenetic factors as well as their interactions. The growth of microbial cells can be characterized by a lag duration, an exponential growth phase, and a stationary phase. Parameters that characterize these growth phases can vary among genotypes (phenotypic variation), environmental conditions (phenotypic plasticity), and among isogenic cells in a given environment (phenotypic variability). We used a high-throughput microscopy assay to map genetic loci determining variation in lag duration and exponential growth rate in growth rate-limiting and nonlimiting glucose concentrations, using segregants from a cross of two natural isolates of the budding yeast, Saccharomyces cerevisiae We find that some quantitative trait loci (QTL) are common between traits and environments whereas some are unique, exhibiting gene-by-environment interactions. Furthermore, whereas variation in the central tendency of growth rate or lag duration is explained by many additive loci, differences in phenotypic variability are primarily the result of genetic interactions. We used bulk segregant mapping to increase QTL resolution by performing whole-genome sequencing of complex mixtures of an advanced intercross mapping population grown in selective conditions using glucose-limited chemostats. We find that sequence variation in the high-affinity glucose transporter HXT7 contributes to variation in growth rate and lag duration. Allele replacements of the entire locus, as well as of a single polymorphic amino acid, reveal that the effect of variation in HXT7 depends on genetic, and allelic, background. Amplifications of HXT7 are frequently selected in experimental evolution in glucose-limited environments, but we find that HXT7 amplifications result in antagonistic pleiotropy that is absent in naturally
Multiple Imputation of Predictor Variables Using Generalized Additive Models
de Jong, Roel; van Buuren, Stef; Spiess, Martin
2016-01-01
The sensitivity of multiple imputation methods to deviations from their distributional assumptions is investigated using simulations, where the parameters of scientific interest are the coefficients of a linear regression model, and values in predictor variables are missing at random. The
Shafizadeh-Moghadam, Hossein; Helbich, Marco
2015-03-01
The rapid growth of megacities requires special attention among urban planners worldwide, and particularly in Mumbai, India, where growth is very pronounced. To cope with the planning challenges this will bring, developing a retrospective understanding of urban land-use dynamics and the underlying driving-forces behind urban growth is a key prerequisite. This research uses regression-based land-use change models - and in particular non-spatial logistic regression models (LR) and auto-logistic regression models (ALR) - for the Mumbai region over the period 1973-2010, in order to determine the drivers behind spatiotemporal urban expansion. Both global models are complemented by a local, spatial model, the so-called geographically weighted logistic regression (GWLR) model, one that explicitly permits variations in driving-forces across space. The study comes to two main conclusions. First, both global models suggest similar driving-forces behind urban growth over time, revealing that LRs and ALRs result in estimated coefficients with comparable magnitudes. Second, all the local coefficients show distinctive temporal and spatial variations. It is therefore concluded that GWLR aids our understanding of urban growth processes, and so can assist context-related planning and policymaking activities when seeking to secure a sustainable urban future.
Higher-dimensional cosmological model with variable gravitational ...
Indian Academy of Sciences (India)
We have studied five-dimensional homogeneous cosmological models with variable and bulk viscosity in Lyra geometry. Exact solutions for the field equations have been obtained and physical properties of the models are discussed. It has been observed that the results of new models are well within the observational ...
Inventory implications of using sampling variances in estimation of growth model coefficients
Albert R. Stage; William R. Wykoff
2000-01-01
Variables based on stand densities or stocking have sampling errors that depend on the relation of tree size to plot size and on the spatial structure of the population, ignoring the sampling errors of such variables, which include most measures of competition used in both distance-dependent and distance-independent growth models, can bias the predictions obtained from...
A variable-order fractal derivative model for anomalous diffusion
Directory of Open Access Journals (Sweden)
Liu Xiaoting
2017-01-01
Full Text Available This paper pays attention to develop a variable-order fractal derivative model for anomalous diffusion. Previous investigations have indicated that the medium structure, fractal dimension or porosity may change with time or space during solute transport processes, results in time or spatial dependent anomalous diffusion phenomena. Hereby, this study makes an attempt to introduce a variable-order fractal derivative diffusion model, in which the index of fractal derivative depends on temporal moment or spatial position, to characterize the above mentioned anomalous diffusion (or transport processes. Compared with other models, the main advantages in description and the physical explanation of new model are explored by numerical simulation. Further discussions on the dissimilitude such as computational efficiency, diffusion behavior and heavy tail phenomena of the new model and variable-order fractional derivative model are also offered.
A mean-field game economic growth model
Gomes, Diogo A.
2016-08-05
Here, we examine a mean-field game (MFG) that models the economic growth of a population of non-cooperative, rational agents. In this MFG, agents are described by two state variables - the capital and consumer goods they own. Each agent seeks to maximize his/her utility by taking into account statistical data about the whole population. The individual actions drive the evolution of the players, and a market-clearing condition determines the relative price of capital and consumer goods. We study the existence and uniqueness of optimal strategies of the agents and develop numerical methods to compute these strategies and the equilibrium price.
A Non-Gaussian Spatial Generalized Linear Latent Variable Model
Irincheeva, Irina
2012-08-03
We consider a spatial generalized linear latent variable model with and without normality distributional assumption on the latent variables. When the latent variables are assumed to be multivariate normal, we apply a Laplace approximation. To relax the assumption of marginal normality in favor of a mixture of normals, we construct a multivariate density with Gaussian spatial dependence and given multivariate margins. We use the pairwise likelihood to estimate the corresponding spatial generalized linear latent variable model. The properties of the resulting estimators are explored by simulations. In the analysis of an air pollution data set the proposed methodology uncovers weather conditions to be a more important source of variability than air pollution in explaining all the causes of non-accidental mortality excluding accidents. © 2012 International Biometric Society.
A Non-Gaussian Spatial Generalized Linear Latent Variable Model
Irincheeva, Irina; Cantoni, Eva; Genton, Marc G.
2012-01-01
We consider a spatial generalized linear latent variable model with and without normality distributional assumption on the latent variables. When the latent variables are assumed to be multivariate normal, we apply a Laplace approximation. To relax the assumption of marginal normality in favor of a mixture of normals, we construct a multivariate density with Gaussian spatial dependence and given multivariate margins. We use the pairwise likelihood to estimate the corresponding spatial generalized linear latent variable model. The properties of the resulting estimators are explored by simulations. In the analysis of an air pollution data set the proposed methodology uncovers weather conditions to be a more important source of variability than air pollution in explaining all the causes of non-accidental mortality excluding accidents. © 2012 International Biometric Society.
Modelling the co-evolution of indirect genetic effects and inherited variability.
Marjanovic, Jovana; Mulder, Han A; Rönnegård, Lars; Bijma, Piter
2018-03-28
When individuals interact, their phenotypes may be affected not only by their own genes but also by genes in their social partners. This phenomenon is known as Indirect Genetic Effects (IGEs). In aquaculture species and some plants, however, competition not only affects trait levels of individuals, but also inflates variability of trait values among individuals. In the field of quantitative genetics, the variability of trait values has been studied as a quantitative trait in itself, and is often referred to as inherited variability. Such studies, however, consider only the genetic effect of the focal individual on trait variability and do not make a connection to competition. Although the observed phenotypic relationship between competition and variability suggests an underlying genetic relationship, the current quantitative genetic models of IGE and inherited variability do not allow for such a relationship. The lack of quantitative genetic models that connect IGEs to inherited variability limits our understanding of the potential of variability to respond to selection, both in nature and agriculture. Models of trait levels, for example, show that IGEs may considerably change heritable variation in trait values. Currently, we lack the tools to investigate whether this result extends to variability of trait values. Here we present a model that integrates IGEs and inherited variability. In this model, the target phenotype, say growth rate, is a function of the genetic and environmental effects of the focal individual and of the difference in trait value between the social partner and the focal individual, multiplied by a regression coefficient. The regression coefficient is a genetic trait, which is a measure of cooperation; a negative value indicates competition, a positive value cooperation, and an increasing value due to selection indicates the evolution of cooperation. In contrast to the existing quantitative genetic models, our model allows for co-evolution of
Influence of Environmental Variables on Gambierdiscus spp. (Dinophyceae Growth and Distribution.
Directory of Open Access Journals (Sweden)
Yixiao Xu
Full Text Available Benthic dinoflagellates in the genus Gambierdiscus produce the ciguatoxin precursors responsible for the occurrence of ciguatera toxicity. The prevalence of ciguatera toxins in fish has been linked to the presence and distribution of toxin-producing species in coral reef ecosystems, which is largely determined by the presence of suitable benthic habitat and environmental conditions favorable for growth. Here using single factor experiments, we examined the effects of salinity, irradiance, and temperature on growth of 17 strains of Gambierdiscus representing eight species/phylotypes (G. belizeanus, G. caribaeus, G. carolinianus, G. carpenteri, G. pacificus, G. silvae, Gambierdiscus sp. type 4-5, most of which were established from either Marakei Island, Republic of Kiribati, or St. Thomas, United States Virgin Island (USVI. Comparable to prior studies, growth rates fell within the range of 0-0.48 divisions day(-1. In the salinity and temperature studies, Gambierdiscus responded in a near Gaussian, non-linear manner typical for such studies, with optimal and suboptimal growth occurring in the range of salinities of 25 and 45 and 21.0 and 32.5°C. In the irradiance experiment, no mortality was observed; however, growth rates at 55 μmol photons · m(-2 · s(-1 were lower than those at 110-400 μmol photons · m(-2 · s(-1. At the extremes of the environmental conditions tested, growth rates were highly variable, evidenced by large coefficients of variability. However, significant differences in intraspecific growth rates were typically found only at optimal or near-optimal growth conditions. Polynomial regression analyses showed that maximum growth occurred at salinity and temperature levels of 30.1-38.5 and 23.8-29.2°C, respectively. Gambierdiscus growth patterns varied among species, and within individual species: G. belizeanus, G. caribaeus, G. carpenteri, and G. pacificus generally exhibited a wider range of tolerance to environmental
Moore, Wayne V; Dana, Ken; Frane, James; Lippe, Barbara
2008-09-01
In children with idiopathic short stature (ISS), growth hormone (GH) response to a provocative test will be inversely related to the first year response to hGH and be a variable accounting for a degree of responsiveness. Because high levels of GH are a characteristic of GH insensitivity, such as in Laron syndrome, it is possible that a high stimulated GH is associated with a lower first year height velocity among children diagnosed as having ISS. We examined the relationship between the peak stimulated GH levels in 3 ISS groups; GH >10 -40 ng/mL and the first year growth response to rhGH therapy. We also looked at 8 other predictor variables (age, sex, height SDS, height age, body mass index (BMI), bone age, dose, and SDS deficit from target parental height. Multiple regression analysis with the first year height as the dependent variable and peak stimulated GH was the primary endpoint. The predictive value of adding each of the other variables was then assessed. Mean change in height velocity was similar among the three groups, with a maximum difference among the groups of 0.6 cm/yr. There was a small but statistically significant correlation (r=-0.12) between the stimulated GH and first year height velocity. The small correlation between first year growth response and peak GH is not clinically relevant in defining GH resistance. No cut off level by peak GH could be determined to enhance the usefulness of this measure to predict response. Baseline age was the only clinically significant predictor, R-squared, 6.4%. All other variables contributed less than an additional 2% to the R-squared.
Transitions in a probabilistic interface growth model
International Nuclear Information System (INIS)
Alves, S G; Moreira, J G
2011-01-01
We study a generalization of the Wolf–Villain (WV) interface growth model based on a probabilistic growth rule. In the WV model, particles are randomly deposited onto a substrate and subsequently move to a position nearby where the binding is strongest. We introduce a growth probability which is proportional to a power of the number n i of bindings of the site i: p i ∝n i ν . Through extensive simulations, in (1 + 1) dimensions, we find three behaviors depending on the ν value: (i) if ν is small, a crossover from the Mullins–Herring to the Edwards–Wilkinson (EW) universality class; (ii) for intermediate values of ν, a crossover from the EW to the Kardar–Parisi–Zhang (KPZ) universality class; and, finally, (iii) for large ν values, the system is always in the KPZ class. In (2 + 1) dimensions, we obtain three different behaviors: (i) a crossover from the Villain–Lai–Das Sarma to the EW universality class for small ν values; (ii) the EW class is always present for intermediate ν values; and (iii) a deviation from the EW class is observed for large ν values
Preliminary Multi-Variable Cost Model for Space Telescopes
Stahl, H. Philip; Hendrichs, Todd
2010-01-01
Parametric cost models are routinely used to plan missions, compare concepts and justify technology investments. This paper reviews the methodology used to develop space telescope cost models; summarizes recently published single variable models; and presents preliminary results for two and three variable cost models. Some of the findings are that increasing mass reduces cost; it costs less per square meter of collecting aperture to build a large telescope than a small telescope; and technology development as a function of time reduces cost at the rate of 50% per 17 years.
Hopf Bifurcation of a Delayed Epidemic Model with Information Variable and Limited Medical Resources
Directory of Open Access Journals (Sweden)
Caijuan Yan
2014-01-01
Full Text Available We consider SIR epidemic model in which population growth is subject to logistic growth in absence of disease. We get the condition for Hopf bifurcation of a delayed epidemic model with information variable and limited medical resources. By analyzing the corresponding characteristic equations, the local stability of an endemic equilibrium and a disease-free equilibrium is discussed. If the basic reproduction ratio ℛ01, we obtain sufficient conditions under which the endemic equilibrium E* of system is locally asymptotically stable. And we also have discussed the stability and direction of Hopf bifurcations. Numerical simulations are carried out to explain the mathematical conclusions.
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
Bayesian approach to errors-in-variables in regression models
Rozliman, Nur Aainaa; Ibrahim, Adriana Irawati Nur; Yunus, Rossita Mohammad
2017-05-01
In many applications and experiments, data sets are often contaminated with error or mismeasured covariates. When at least one of the covariates in a model is measured with error, Errors-in-Variables (EIV) model can be used. Measurement error, when not corrected, would cause misleading statistical inferences and analysis. Therefore, our goal is to examine the relationship of the outcome variable and the unobserved exposure variable given the observed mismeasured surrogate by applying the Bayesian formulation to the EIV model. We shall extend the flexible parametric method proposed by Hossain and Gustafson (2009) to another nonlinear regression model which is the Poisson regression model. We shall then illustrate the application of this approach via a simulation study using Markov chain Monte Carlo sampling methods.
A Probit Model for the State of the Greek GDP Growth
Directory of Open Access Journals (Sweden)
Stavros Degiannakis
2015-08-01
Full Text Available The paper provides probability estimates of the state of the GDP growth. A regime-switching model defines the probability of the Greek GDP being in boom or recession. Then probit models extract the predictive information of a set of explanatory (economic and financial variables regarding the state of the GDP growth. A contemporaneous, as well as a lagged, relationship between the explanatory variables and the state of the GDP growth is conducted. The mean absolute distance (MAD between the probability of not being in recession and the probability estimated by the probit model is the function that evaluates the performance of the models. The probit model with the industrial production index and the realized volatility as the explanatory variables has the lowest MAD value of 6.43% (7.94% in the contemporaneous (lagged relationship.
Loss given default models incorporating macroeconomic variables for credit cards
Crook, J.; Bellotti, T.
2012-01-01
Based on UK data for major retail credit cards, we build several models of Loss Given Default based on account level data, including Tobit, a decision tree model, a Beta and fractional logit transformation. We find that Ordinary Least Squares models with macroeconomic variables perform best for forecasting Loss Given Default at the account and portfolio levels on independent hold-out data sets. The inclusion of macroeconomic conditions in the model is important, since it provides a means to m...
Growth and energy nexus in Europe revisited: Evidence from a fixed effects political economy model
International Nuclear Information System (INIS)
Menegaki, Angeliki N.; Ozturk, Ilhan
2013-01-01
This is an empirical study on the causal relationship between economic growth and energy for 26 European countries in a multivariate panel framework over the period 1975–2009 using a two-way fixed effects model and including greenhouse gas emissions, capital, fossil energy consumption, Herfindahl index (political competition) and number of years the government chief executive stays in office (political stability) as independent variables in the model. Empirical results confirm bidirectional causality between growth and political stability, capital and political stability, capital and fossil energy consumption. Whether political stability favors the implementation of growth or leads to corruption demands further research. - Highlights: • Economic growth and energy for 26 European countries is examined. • Two-way fixed effects model with political economy variables is employed. • Bidirectional causality is observed between growth and political stability
Energy Technology Data Exchange (ETDEWEB)
Rollin, Bertrand [Los Alamos National Laboratory; Andrews, Malcolm J [Los Alamos National Laboratory
2010-01-01
We present our progress toward setting initial conditions in variable density turbulence models. In particular, we concentrate our efforts on the BHR turbulence model for turbulent Rayleigh-Taylor instability. Our approach is to predict profiles of relevant variables before fully turbulent regime and use them as initial conditions for the turbulence model. We use an idealized model of mixing between two interpenetrating fluids to define the initial profiles for the turbulence model variables. Velocities and volume fractions used in the idealized mixing model are obtained respectively from a set of ordinary differential equations modeling the growth of the Rayleigh-Taylor instability and from an idealization of the density profile in the mixing layer. A comparison between predicted profiles for the turbulence model variables and profiles of the variables obtained from low Atwood number three dimensional simulations show reasonable agreement.
Araucaria growth response to solar and climate variability in South Brazil
Prestes, Alan; Klausner, Virginia; Rojahn da Silva, Iuri; Ojeda-González, Arian; Lorensi, Caren
2018-05-01
In this work, the Sun-Earth-climate relationship is studied using tree growth rings of Araucaria angustifolia (Bertol.) O. Kuntze collected in the city of Passo Fundo, located in the state of Rio Grande do Sul (RS), Brazil. These samples were previously studied by Rigozo et al. (2008); however, their main interest was to search for the solar periodicities in the tree-ring width mean time series without interpreting the rest of the periodicities found. The question arises as to what are the drivers related to those periodicities. For this reason, the classical method of spectral analysis by iterative regression and wavelet methods are applied to find periodicities and trends present in each tree-ring growth, in Southern Oscillation Index (SOI), and in annual mean temperature anomaly between the 24 and 44° S. In order to address the aforementioned question, this paper discusses the correlation between the growth rate of the tree rings with temperature and SOI. In each tree-ring growth series, periods between 2 and 7 years were found, possibly related to the El Niño/La Niña phenomena, and a ˜ 23-year period was found, which may be related to temperature variation. These novel results might represent the tree-ring growth response to local climate conditions during its lifetime, and to nonlinear coupling between the Sun and the local climate variability responsible to the regional climate variations.
Interacting ghost dark energy models with variable G and Λ
Sadeghi, J.; Khurshudyan, M.; Movsisyan, A.; Farahani, H.
2013-12-01
In this paper we consider several phenomenological models of variable Λ. Model of a flat Universe with variable Λ and G is accepted. It is well known, that varying G and Λ gives rise to modified field equations and modified conservation laws, which gives rise to many different manipulations and assumptions in literature. We will consider two component fluid, which parameters will enter to Λ. Interaction between fluids with energy densities ρ1 and ρ2 assumed as Q = 3Hb(ρ1+ρ2). We have numerical analyze of important cosmological parameters like EoS parameter of the composed fluid and deceleration parameter q of the model.
Variable selection for mixture and promotion time cure rate models.
Masud, Abdullah; Tu, Wanzhu; Yu, Zhangsheng
2016-11-16
Failure-time data with cured patients are common in clinical studies. Data from these studies are typically analyzed with cure rate models. Variable selection methods have not been well developed for cure rate models. In this research, we propose two least absolute shrinkage and selection operators based methods, for variable selection in mixture and promotion time cure models with parametric or nonparametric baseline hazards. We conduct an extensive simulation study to assess the operating characteristics of the proposed methods. We illustrate the use of the methods using data from a study of childhood wheezing. © The Author(s) 2016.
A predictability study of Lorenz's 28-variable model as a dynamical system
Krishnamurthy, V.
1993-01-01
The dynamics of error growth in a two-layer nonlinear quasi-geostrophic model has been studied to gain an understanding of the mathematical theory of atmospheric predictability. The growth of random errors of varying initial magnitudes has been studied, and the relation between this classical approach and the concepts of the nonlinear dynamical systems theory has been explored. The local and global growths of random errors have been expressed partly in terms of the properties of an error ellipsoid and the Liapunov exponents determined by linear error dynamics. The local growth of small errors is initially governed by several modes of the evolving error ellipsoid but soon becomes dominated by the longest axis. The average global growth of small errors is exponential with a growth rate consistent with the largest Liapunov exponent. The duration of the exponential growth phase depends on the initial magnitude of the errors. The subsequent large errors undergo a nonlinear growth with a steadily decreasing growth rate and attain saturation that defines the limit of predictability. The degree of chaos and the largest Liapunov exponent show considerable variation with change in the forcing, which implies that the time variation in the external forcing can introduce variable character to the predictability.
a modified intervention model for gross domestic product variable
African Journals Online (AJOL)
observations on a variable that have been measured at ... assumption that successive values in the data file ... these interventions, one may try to evaluate the effect of ... generalized series by comparing the distinct periods. A ... the process of checking for adequacy of the model based .... As a result, the model's forecast will.
Simple model for crop photosynthesis in terms of weather variables ...
African Journals Online (AJOL)
A theoretical mathematical model for describing crop photosynthetic rate in terms of the weather variables and crop characteristics is proposed. The model utilizes a series of efficiency parameters, each of which reflect the fraction of possible photosynthetic rate permitted by the different weather elements or crop architecture.
Model for expressing leaf photosynthesis in terms of weather variables
African Journals Online (AJOL)
A theoretical mathematical model for describing photosynthesis in individual leaves in terms of weather variables is proposed. The model utilizes a series of efficiency parameters, each of which reflect the fraction of potential photosynthetic rate permitted by the different environmental elements. These parameters are useful ...
Efficient Business Service Consumption by Customization with Variability Modelling
Directory of Open Access Journals (Sweden)
Michael Stollberg
2010-07-01
Full Text Available The establishment of service orientation in industry determines the need for efficient engineering technologies that properly support the whole life cycle of service provision and consumption. A central challenge is adequate support for the efficient employment of komplex services in their individual application context. This becomes particularly important for large-scale enterprise technologies where generic services are designed for reuse in several business scenarios. In this article we complement our work regarding Service Variability Modelling presented in a previous publication. There we presented an approach for the customization of services for individual application contexts by creating simplified variants, based on model-driven variability management. That work presents our revised service variability metamodel, new features of the variability tools and an applicability study, which reveals that substantial improvements on the efficiency of standard business service consumption under both usability and economic aspects can be achieved.
Modelling the effects of spatial variability on radionuclide migration
International Nuclear Information System (INIS)
1998-01-01
The NEA workshop reflect the present status in national waste management program, specifically in spatial variability and performance assessment of geologic disposal sites for deed repository system the four sessions were: Spatial Variability: Its Definition and Significance to Performance Assessment and Site Characterisation; Experience with the Modelling of Radionuclide Migration in the Presence of Spatial Variability in Various Geological Environments; New Areas for Investigation: Two Personal Views; What is Wanted and What is Feasible: Views and Future Plans in Selected Waste Management Organisations. The 26 papers presented on the four oral sessions and on the poster session have been abstracted and indexed individually for the INIS database. (R.P.)
From Transition Systems to Variability Models and from Lifted Model Checking Back to UPPAAL
DEFF Research Database (Denmark)
Dimovski, Aleksandar; Wasowski, Andrzej
2017-01-01
efficient lifted (family-based) model checking for real-time variability models. This reduces the cost of maintaining specialized family-based real-time model checkers. Real-time variability models can be model checked using the standard UPPAAL. We have implemented abstractions as syntactic source...
Internal variability of a 3-D ocean model
Directory of Open Access Journals (Sweden)
Bjarne Büchmann
2016-11-01
Full Text Available The Defence Centre for Operational Oceanography runs operational forecasts for the Danish waters. The core setup is a 60-layer baroclinic circulation model based on the General Estuarine Transport Model code. At intervals, the model setup is tuned to improve ‘model skill’ and overall performance. It has been an area of concern that the uncertainty inherent to the stochastical/chaotic nature of the model is unknown. Thus, it is difficult to state with certainty that a particular setup is improved, even if the computed model skill increases. This issue also extends to the cases, where the model is tuned during an iterative process, where model results are fed back to improve model parameters, such as bathymetry.An ensemble of identical model setups with slightly perturbed initial conditions is examined. It is found that the initial perturbation causes the models to deviate from each other exponentially fast, causing differences of several PSUs and several kelvin within a few days of simulation. The ensemble is run for a full year, and the long-term variability of salinity and temperature is found for different regions within the modelled area. Further, the developing time scale is estimated for each region, and great regional differences are found – in both variability and time scale. It is observed that periods with very high ensemble variability are typically short-term and spatially limited events.A particular event is examined in detail to shed light on how the ensemble ‘behaves’ in periods with large internal model variability. It is found that the ensemble does not seem to follow any particular stochastic distribution: both the ensemble variability (standard deviation or range as well as the ensemble distribution within that range seem to vary with time and place. Further, it is observed that a large spatial variability due to mesoscale features does not necessarily correlate to large ensemble variability. These findings bear
Understanding and forecasting polar stratospheric variability with statistical models
Directory of Open Access Journals (Sweden)
C. Blume
2012-07-01
Full Text Available The variability of the north-polar stratospheric vortex is a prominent aspect of the middle atmosphere. This work investigates a wide class of statistical models with respect to their ability to model geopotential and temperature anomalies, representing variability in the polar stratosphere. Four partly nonstationary, nonlinear models are assessed: linear discriminant analysis (LDA; a cluster method based on finite elements (FEM-VARX; a neural network, namely the multi-layer perceptron (MLP; and support vector regression (SVR. These methods model time series by incorporating all significant external factors simultaneously, including ENSO, QBO, the solar cycle, volcanoes, to then quantify their statistical importance. We show that variability in reanalysis data from 1980 to 2005 is successfully modeled. The period from 2005 to 2011 can be hindcasted to a certain extent, where MLP performs significantly better than the remaining models. However, variability remains that cannot be statistically hindcasted within the current framework, such as the unexpected major warming in January 2009. Finally, the statistical model with the best generalization performance is used to predict a winter 2011/12 with warm and weak vortex conditions. A vortex breakdown is predicted for late January, early February 2012.
Effect of specimen geometry on the variability in fatigue crack growth rate
International Nuclear Information System (INIS)
Tsuji, Hirokazu; Nakajima, Hajime; Kondo, Tatsuo
1982-02-01
Fatigue crack growth tests on SA 533 grade B class 1 steel were conducted in air with both contoured double cantilever beam (CDCB) specimens and compact-tension (CT) specimens for comparison, which corresponded to the ΔK constant and ΔK increasing fatigue tests respectively. The variability of the measured values was examined statistically, and possible sources of the determined variability were discussed. The variability in the ΔK increasing fatigue tests with the CT specimens was found to be substantially greater than that in the ΔK constant fatigue tests with the CDCB specimens employed in the present study. In addition, the width of the scatter as well as in the degree of deviation from the expected linearity in da/dN versus ΔK plots were found to be varied depending on the level of ΔK in the CT specimen. Based on the results, a conclusion was drawn that constant ΔK type tests should be preferred in the tests where accuracy and reproducibility of crack growth rate measurement was of particular importance. (author)
Spatial and temporal variability in growth of southern flounder (Paralichthys lethostigma)
Midway, Stephen R.; Wagner, Tyler; Arnott, Stephen A.; Biondo, Patrick; Martinez-Andrade, Fernando; Wadsworth, Thomas F.
2015-01-01
Delineation of stock structure is important for understanding the ecology and management of many fish populations, particularly those with wide-ranging distributions and high levels of harvest. Southern flounder (Paralichthys lethostigma) is a popular commercial and recreational species along the southeast Atlantic coast and Gulf of Mexico, USA. Recent studies have provided genetic and otolith morphology evidence that the Gulf of Mexico and Atlantic Ocean stocks differ. Using age and growth data from four states (Texas, Alabama, South Carolina, and North Carolina) we expanded upon the traditional von Bertalanffy model in order to compare growth rates of putative geographic stocks of southern flounder. We improved the model fitting process by adding a hierarchical Bayesian framework to allow each parameter to vary spatially or temporally as a random effect, as well as log transforming the three model parameters (L∞, K, andt0). Multiple comparisons of parameters showed that growth rates varied (even within states) for females, but less for males. Growth rates were also consistent through time, when long-term data were available. Since within-basin populations are thought to be genetically well-mixed, our results suggest that consistent small-scale environmental conditions (i.e., within estuaries) likely drive growth rates and should be considered when developing broader scale management plans.
Directory of Open Access Journals (Sweden)
Maria Estela de León
2005-09-01
Full Text Available Annual von Bertalanffy growth parameters of the Caribbean spiny lobster (Panulirus argus in Cuban waters were estimated from a long term study (40 years by length-based methods ELEFAN and the new version of SLCA. Data of around 800 000 lobsters (with carapace length ranging 14 to 199mm were randomly sampled in artificial shelters (a non selective fishing gear very common in the lobster fishery, through the field monitory program established for this species since 1963 in 14 localities of southwestern Cuban shelf. The software ELEFAN showed problems to converge in an optimal combination of the instantaneous growth coefficient (K and the asymptotic length (L8 of the von Bertalanffy equation, whereas the new SLCA software produced value estimates of K between 0.20 and 0.27 year-1 and values of L8 between 177 and 190 mm carapace length, all within the range reported in the literature. The standardized anomalies of both parameters showed the presence of cycles along the analyzed time series. Decadal variability in growth parameters was revealed through the spectral analysis indicating cycles of 16 and 20 years for K and of 16 years for L8. The incidence of some factors such as biomass and temperature that modulate growth in this crustacean was explored, using a nonlinear multiple regression model. These combined factors explained 33% and 69% of the variability of K and L8 respectively. The growth coefficient appeared to be maximum with annual mean sea surface temperature of 28.1º C and the largest L 8is reached at a annual men biomass level of 23 000 t. These results should be the basis to understand the Cuban lobster population dynamics. Rev. Biol. Trop. 53(3-4: 475-486. Epub 2005 Oct 3.Los parámetros de crecimiento anuales para la langosta espinosa del Caribe (Panulirus argus en aguas cubanas se estimaron para una serie de 40 años de datos de composición por longitud, a través de los métodos indirectos basados en la talla ELEFAN y el nuevo
Kinetic Modeling of Corn Fermentation with S. cerevisiae Using a Variable Temperature Strategy
Directory of Open Access Journals (Sweden)
Augusto C. M. Souza
2018-04-01
Full Text Available While fermentation is usually done at a fixed temperature, in this study, the effect of having a controlled variable temperature was analyzed. A nonlinear system was used to model batch ethanol fermentation, using corn as substrate and the yeast Saccharomyces cerevisiae, at five different fixed and controlled variable temperatures. The lower temperatures presented higher ethanol yields but took a longer time to reach equilibrium. Higher temperatures had higher initial growth rates, but the decay of yeast cells was faster compared to the lower temperatures. However, in a controlled variable temperature model, the temperature decreased with time with the initial value of 40 ∘ C. When analyzing a time window of 60 h, the ethanol production increased 20% compared to the batch with the highest temperature; however, the yield was still 12% lower compared to the 20 ∘ C batch. When the 24 h’ simulation was analyzed, the controlled model had a higher ethanol concentration compared to both fixed temperature batches.
Kinetic Modeling of Corn Fermentation with S. cerevisiae Using a Variable Temperature Strategy.
Souza, Augusto C M; Mousaviraad, Mohammad; Mapoka, Kenneth O M; Rosentrater, Kurt A
2018-04-24
While fermentation is usually done at a fixed temperature, in this study, the effect of having a controlled variable temperature was analyzed. A nonlinear system was used to model batch ethanol fermentation, using corn as substrate and the yeast Saccharomyces cerevisiae , at five different fixed and controlled variable temperatures. The lower temperatures presented higher ethanol yields but took a longer time to reach equilibrium. Higher temperatures had higher initial growth rates, but the decay of yeast cells was faster compared to the lower temperatures. However, in a controlled variable temperature model, the temperature decreased with time with the initial value of 40 ∘ C. When analyzing a time window of 60 h, the ethanol production increased 20% compared to the batch with the highest temperature; however, the yield was still 12% lower compared to the 20 ∘ C batch. When the 24 h’ simulation was analyzed, the controlled model had a higher ethanol concentration compared to both fixed temperature batches.
Energy Technology Data Exchange (ETDEWEB)
Eugène, Sarah, E-mail: Sarah.Eugene@inria.fr; Doumic, Marie, E-mail: Philippe.Robert@inria.fr, E-mail: Marie.Doumic@inria.fr [INRIA de Paris, 2 Rue Simone Iff, CS 42112, 75589 Paris Cedex 12 (France); Sorbonne Universités, UPMC Université Pierre et Marie Curie, UMR 7598, Laboratoire Jacques-Louis Lions, F-75005 Paris (France); Xue, Wei-Feng, E-mail: W.F.Xue@kent.ac.uk [School of Biosciences, University of Kent, Canterbury, Kent CT2 7NJ (United Kingdom); Robert, Philippe, E-mail: Philippe.Robert@inria.fr [INRIA de Paris, 2 Rue Simone Iff, CS 42112, 75589 Paris Cedex 12 (France)
2016-05-07
Self-assembly of proteins into amyloid aggregates is an important biological phenomenon associated with human diseases such as Alzheimer’s disease. Amyloid fibrils also have potential applications in nano-engineering of biomaterials. The kinetics of amyloid assembly show an exponential growth phase preceded by a lag phase, variable in duration as seen in bulk experiments and experiments that mimic the small volumes of cells. Here, to investigate the origins and the properties of the observed variability in the lag phase of amyloid assembly currently not accounted for by deterministic nucleation dependent mechanisms, we formulate a new stochastic minimal model that is capable of describing the characteristics of amyloid growth curves despite its simplicity. We then solve the stochastic differential equations of our model and give mathematical proof of a central limit theorem for the sample growth trajectories of the nucleated aggregation process. These results give an asymptotic description for our simple model, from which closed form analytical results capable of describing and predicting the variability of nucleated amyloid assembly were derived. We also demonstrate the application of our results to inform experiments in a conceptually friendly and clear fashion. Our model offers a new perspective and paves the way for a new and efficient approach on extracting vital information regarding the key initial events of amyloid formation.
Mediterranean climate modelling: variability and climate change scenarios
International Nuclear Information System (INIS)
Somot, S.
2005-12-01
Air-sea fluxes, open-sea deep convection and cyclo-genesis are studied in the Mediterranean with the development of a regional coupled model (AORCM). It accurately simulates these processes and their climate variabilities are quantified and studied. The regional coupling shows a significant impact on the number of winter intense cyclo-genesis as well as on associated air-sea fluxes and precipitation. A lower inter-annual variability than in non-coupled models is simulated for fluxes and deep convection. The feedbacks driving this variability are understood. The climate change response is then analysed for the 21. century with the non-coupled models: cyclo-genesis decreases, associated precipitation increases in spring and autumn and decreases in summer. Moreover, a warming and salting of the Mediterranean as well as a strong weakening of its thermohaline circulation occur. This study also concludes with the necessity of using AORCMs to assess climate change impacts on the Mediterranean. (author)
Plasticity models of material variability based on uncertainty quantification techniques
Energy Technology Data Exchange (ETDEWEB)
Jones, Reese E. [Sandia National Lab. (SNL-CA), Livermore, CA (United States); Rizzi, Francesco [Sandia National Lab. (SNL-CA), Livermore, CA (United States); Boyce, Brad [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Templeton, Jeremy Alan [Sandia National Lab. (SNL-CA), Livermore, CA (United States); Ostien, Jakob [Sandia National Lab. (SNL-CA), Livermore, CA (United States)
2017-11-01
The advent of fabrication techniques like additive manufacturing has focused attention on the considerable variability of material response due to defects and other micro-structural aspects. This variability motivates the development of an enhanced design methodology that incorporates inherent material variability to provide robust predictions of performance. In this work, we develop plasticity models capable of representing the distribution of mechanical responses observed in experiments using traditional plasticity models of the mean response and recently developed uncertainty quantification (UQ) techniques. Lastly, we demonstrate that the new method provides predictive realizations that are superior to more traditional ones, and how these UQ techniques can be used in model selection and assessing the quality of calibrated physical parameters.
Precipitation variability inferred from the annual growth and isotopic composition of tropical trees
Ballantyne, A. P.; Baker, P. A.; Chambers, J. Q.; Villalba, R.
2005-12-01
Here we demonstrate that annual growth and isotopic ratios in tropical trees are responsive to seasonal and annual precipitation variability. We identify several regions of tropical South America characterized by significant relationships between oxygen isotopic ratios (δ 18O) in precipitation and precipitation amount (r = -0.82). Many of these regions are also sensitive to inter-annual variability in the South American Monsoon modulated by the El Niño Southern Oscillation (ENSO). The effectiveness of δ 18O and annual growth of tropical trees as a precipitation proxy is validated by high-resolution sampling of a Tachigali vermelho tree growing near Manaus, Brazil (3.1° S, 60.0° S). Growth in Tachigali spp. was highly correlated with both precipitation and cellulose δ 18O (r = 0.60) and precipitation amount was significantly correlated with δ 18O at a lag of approximately one month (r = 0.56). We also report a multi-proxy record spanning 180 years from Cedrela odorata growing in the Peruvian Amazon near Puerto Maldonado (12.6° S, 69.2° W) revealing a significant relationship between cellulose and monsoon precipitation over the region (r = -0.33). A 150-year record obtained from Polylepis tarapacana growing at Volcan Granada in Northern Argentina (22.0° S, 66.0° W) is also reported with a significant relationship between local monsoon precipitation and a regionally derived ring width index (r = 0.38). Although no significant relationship was revealed between cellulose δ 18O and precipitation in this taxa at this location, separate radii within the same tree revealed a significantly coherent δ 18O signal (r = 0.38). We compared our proxy chronologies with monsoon precipitation reanalysis data for tropical South America, which revealed key features of the South American Monsoon and their sensitivity to ENSO variability.
Local variability in growth and reproduction of Salix arctica in the High Arctic
Directory of Open Access Journals (Sweden)
Noémie Boulanger-Lapointe
2016-06-01
Full Text Available Arctic terrestrial ecosystems are heterogeneous because of the strong influences of microtopography, soil moisture and snow accumulation on vegetation distribution. The interaction between local biotic and abiotic factors and global climate patterns will influence species responses to climate change. Salix arctica (Arctic willow is a structuring species, ubiquitous and widespread, and as such is one of the most important shrub species in the High Arctic. In this study, we measured S. arctica reproductive effort, early establishment, survival and growth in the Zackenberg valley, north-east Greenland. We sampled four plant communities that varied with respect to snow conditions, soil moisture, nutrient content and plant composition. We found large variability in reproductive effort and success with total catkin density ranging from 0.6 to 66 catkins/m2 and seedling density from <1 to 101 seedlings/m2. There were also major differences in crown area increment (4–23 cm2/year and stem radial growth (40–74 µm/year. The snowbed community, which experienced a recent reduction in snow cover, supported young populations with high reproductive effort, establishment and growth. Soil nutrient content and herbivore activity apparently did not strongly constrain plant reproduction and growth, but competition by Cassiope tetragona and low soil moisture may inhibit performance. Our results show that local environmental factors, such as snow accumulation, have a significant impact on tundra plant response to climate change and will affect the understanding of regional vegetation response to climate change.
Modeling Turbulent Combustion for Variable Prandtl and Schmidt Number
Hassan, H. A.
2004-01-01
This report consists of two abstracts submitted for possible presentation at the AIAA Aerospace Science Meeting to be held in January 2005. Since the submittal of these abstracts we are continuing refinement of the model coefficients derived for the case of a variable Turbulent Prandtl number. The test cases being investigated are a Mach 9.2 flow over a degree ramp and a Mach 8.2 3-D calculation of crossing shocks. We have developed an axisymmetric code for treating axisymmetric flows. In addition the variable Schmidt number formulation was incorporated in the code and we are in the process of determining the model constants.
The Properties of Model Selection when Retaining Theory Variables
DEFF Research Database (Denmark)
Hendry, David F.; Johansen, Søren
Economic theories are often fitted directly to data to avoid possible model selection biases. We show that embedding a theory model that specifies the correct set of m relevant exogenous variables, x{t}, within the larger set of m+k candidate variables, (x{t},w{t}), then selection over the second...... set by their statistical significance can be undertaken without affecting the estimator distribution of the theory parameters. This strategy returns the theory-parameter estimates when the theory is correct, yet protects against the theory being under-specified because some w{t} are relevant....
Modelling the Growth and Volatility in Daily International Mass Tourism to Peru
Jose Angelo Divino; Michael McAleer
2009-01-01
Peru is a South American country that is divided into two parts by the Andes Mountains. The rich historical, cultural and geographic diversity has led to the inclusion of ten Peruvian sites on UNESCO’s World Heritage List. For the potential negative impacts of mass tourism on the environment, and hence on future international tourism demand, to be managed appropriately require modelling growth rates and volatility adequately. The paper models the growth rate and volatility (or the variability...
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.
Flower Power: Sunflowers as a Model for Logistic Growth
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,…
Ocean carbon and heat variability in an Earth System Model
Thomas, J. L.; Waugh, D.; Gnanadesikan, A.
2016-12-01
Ocean carbon and heat content are very important for regulating global climate. Furthermore, due to lack of observations and dependence on parameterizations, there has been little consensus in the modeling community on the magnitude of realistic ocean carbon and heat content variability, particularly in the Southern Ocean. We assess the differences between global oceanic heat and carbon content variability in GFDL ESM2Mc using a 500-year, pre-industrial control simulation. The global carbon and heat content are directly out of phase with each other; however, in the Southern Ocean the heat and carbon content are in phase. The global heat mutli-decadal variability is primarily explained by variability in the tropics and mid-latitudes, while the variability in global carbon content is primarily explained by Southern Ocean variability. In order to test the robustness of this relationship, we use three additional pre-industrial control simulations using different mesoscale mixing parameterizations. Three pre-industrial control simulations are conducted with the along-isopycnal diffusion coefficient (Aredi) set to constant values of 400, 800 (control) and 2400 m2 s-1. These values for Aredi are within the range of parameter settings commonly used in modeling groups. Finally, one pre-industrial control simulation is conducted where the minimum in the Gent-McWilliams parameterization closure scheme (AGM) increased to 600 m2 s-1. We find that the different simulations have very different multi-decadal variability, especially in the Weddell Sea where the characteristics of deep convection are drastically changed. While the temporal frequency and amplitude global heat and carbon content changes significantly, the overall spatial pattern of variability remains unchanged between the simulations.
Robin J. Tausch
2015-01-01
A theoretically based analytic model of plant growth in single species conifer communities based on the species fully occupying a site and fully using the site resources is introduced. Model derivations result in a single equation simultaneously describes changes over both, different site conditions (or resources available), and over time for each variable for each...
Model for analyzing growth kinetics of a slowly growing Mycobacterium sp
International Nuclear Information System (INIS)
Lambrecht, R.S.; Carriere, J.F.; Collins, M.T.
1988-01-01
This report describes a simple method for quantifying viable mycobacteria and for determining generation time. We used statistical models and computer analysis of growth curves generated for the slowly growing mycobacterium Mycobacterium paratuberculosis under controlled conditions to derive a mathematical formula relating the dependent variable, growth, to the independent variables, log10 number of organisms in the inoculum (inoculum size) and incubation time. Growth was measured by a radiometric method which detects 14 CO 2 release during metabolism of a 14 C-labeled substrate. The radiometric method allowed for early detection of growth and detected as few as three viable bacteria. The coefficient of variation between culture vials inoculated with the same number of M. paratuberculosis was 0.083. Radiometric measurements were highly correlated to spectrophotometric and plate count methods for measuring growth (r = 0.962 and 0.992, respectively). The proportion of the total variability explained by the model in a goodness of fit test was 0.9994. Application of the model to broth cultures provided accurate estimates of the number of M. paratuberculosis (standard error = 0.21, log10 scale) and the growth rate (coefficient of variation, 0.03). Generation time was observed to be dependent upon the number of organisms in the inoculum. The model accurately described all phases of growth of M. paratuberculosis and can likely be applied to other slowly growing microorganisms
Tao, F.; Rötter, R.
2013-12-01
Many studies on global climate report that climate variability is increasing with more frequent and intense extreme events1. There are quite large uncertainties from both the plot- and regional-scale models in simulating impacts of climate variability and extremes on crop development, growth and productivity2,3. One key to reducing the uncertainties is better exploitation of experimental data to eliminate crop model deficiencies and develop better algorithms that more adequately capture the impacts of extreme events, such as high temperature and drought, on crop performance4,5. In the present study, in a first step, the inter-annual variability in wheat yield and climate from 1971 to 2012 in Finland was investigated. Using statistical approaches the impacts of climate variability and extremes on wheat growth and productivity were quantified. In a second step, a plot-scale model, WOFOST6, and a regional-scale crop model, MCWLA7, were calibrated and validated, and applied to simulate wheat growth and yield variability from 1971-2012. Next, the estimated impacts of high temperature stress, cold damage, and drought stress on crop growth and productivity based on the statistical approaches, and on crop simulation models WOFOST and MCWLA were compared. Then, the impact mechanisms of climate extremes on crop growth and productivity in the WOFOST model and MCWLA model were identified, and subsequently, the various algorithm and impact functions were fitted against the long-term crop trial data. Finally, the impact mechanisms, algorithms and functions in WOFOST model and MCWLA model were improved to better simulate the impacts of climate variability and extremes, particularly high temperature stress, cold damage and drought stress for location-specific and large area climate impact assessments. Our studies provide a good example of how to improve, in parallel, the plot- and regional-scale models for simulating impacts of climate variability and extremes, as needed for
Classification criteria of syndromes by latent variable models
DEFF Research Database (Denmark)
Petersen, Janne
2010-01-01
patient's characteristics. These methods may erroneously reduce multiplicity either by combining markers of different phenotypes or by mixing HALS with other processes such as aging. Latent class models identify homogenous groups of patients based on sets of variables, for example symptoms. As no gold......The thesis has two parts; one clinical part: studying the dimensions of human immunodeficiency virus associated lipodystrophy syndrome (HALS) by latent class models, and a more statistical part: investigating how to predict scores of latent variables so these can be used in subsequent regression...... standard exists for diagnosing HALS the normally applied diagnostic models cannot be used. Latent class models, which have never before been used to diagnose HALS, make it possible, under certain assumptions, to: statistically evaluate the number of phenotypes, test for mixing of HALS with other processes...
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).
Internal variability in a regional climate model over West Africa
Energy Technology Data Exchange (ETDEWEB)
Vanvyve, Emilie; Ypersele, Jean-Pascal van [Universite catholique de Louvain, Institut d' astronomie et de geophysique Georges Lemaitre, Louvain-la-Neuve (Belgium); Hall, Nicholas [Laboratoire d' Etudes en Geophysique et Oceanographie Spatiales/Centre National d' Etudes Spatiales, Toulouse Cedex 9 (France); Messager, Christophe [University of Leeds, Institute for Atmospheric Science, Environment, School of Earth and Environment, Leeds (United Kingdom); Leroux, Stephanie [Universite Joseph Fourier, Laboratoire d' etude des Transferts en Hydrologie et Environnement, BP53, Grenoble Cedex 9 (France)
2008-02-15
Sensitivity studies with regional climate models are often performed on the basis of a few simulations for which the difference is analysed and the statistical significance is often taken for granted. In this study we present some simple measures of the confidence limits for these types of experiments by analysing the internal variability of a regional climate model run over West Africa. Two 1-year long simulations, differing only in their initial conditions, are compared. The difference between the two runs gives a measure of the internal variability of the model and an indication of which timescales are reliable for analysis. The results are analysed for a range of timescales and spatial scales, and quantitative measures of the confidence limits for regional model simulations are diagnosed for a selection of study areas for rainfall, low level temperature and wind. As the averaging period or spatial scale is increased, the signal due to internal variability gets smaller and confidence in the simulations increases. This occurs more rapidly for variations in precipitation, which appear essentially random, than for dynamical variables, which show some organisation on larger scales. (orig.)
Automatic Welding Control Using a State Variable Model.
1979-06-01
A-A10 610 NAVEAL POSTGRADUATE SCH4O.M CEAY CA0/ 13/ SAUTOMATIC WELDING CONTROL USING A STATE VARIABLE MODEL.W()JUN 79 W V "my UNCLASSIFIED...taverse Drive Unit // Jbint Path /Fixed Track 34 (servomotor positioning). Additional controls of heave (vertical), roll (angular rotation about the
Viscous cosmological models with a variable cosmological term ...
African Journals Online (AJOL)
Einstein's field equations for a Friedmann-Lamaitre Robertson-Walker universe filled with a dissipative fluid with a variable cosmological term L described by full Israel-Stewart theory are considered. General solutions to the field equations for the flat case have been obtained. The solution corresponds to the dust free model ...
Appraisal and Reliability of Variable Engagement Model Prediction ...
African Journals Online (AJOL)
The variable engagement model based on the stress - crack opening displacement relationship and, which describes the behaviour of randomly oriented steel fibres composite subjected to uniaxial tension has been evaluated so as to determine the safety indices associated when the fibres are subjected to pullout and with ...
Higher-dimensional cosmological model with variable gravitational ...
Indian Academy of Sciences (India)
variable G and bulk viscosity in Lyra geometry. Exact solutions for ... a comparative study of Robertson–Walker models with a constant deceleration .... where H is defined as H =(˙A/A)+(1/3)( ˙B/B) and β0,H0 are representing present values of β ...
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
Oscillating shells: A model for a variable cosmic object
Nunez, Dario
1997-01-01
A model for a possible variable cosmic object is presented. The model consists of a massive shell surrounding a compact object. The gravitational and self-gravitational forces tend to collapse the shell, but the internal tangential stresses oppose the collapse. The combined action of the two types of forces is studied and several cases are presented. In particular, we investigate the spherically symmetric case in which the shell oscillates radially around a central compact object.
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
Sparse modeling of spatial environmental variables associated with asthma.
Chang, Timothy S; Gangnon, Ronald E; David Page, C; Buckingham, William R; Tandias, Aman; Cowan, Kelly J; Tomasallo, Carrie D; Arndt, Brian G; Hanrahan, Lawrence P; Guilbert, Theresa W
2015-02-01
Geographically distributed environmental factors influence the burden of diseases such as asthma. Our objective was to identify sparse environmental variables associated with asthma diagnosis gathered from a large electronic health record (EHR) dataset while controlling for spatial variation. An EHR dataset from the University of Wisconsin's Family Medicine, Internal Medicine and Pediatrics Departments was obtained for 199,220 patients aged 5-50years over a three-year period. Each patient's home address was geocoded to one of 3456 geographic census block groups. Over one thousand block group variables were obtained from a commercial database. We developed a Sparse Spatial Environmental Analysis (SASEA). Using this method, the environmental variables were first dimensionally reduced with sparse principal component analysis. Logistic thin plate regression spline modeling was then used to identify block group variables associated with asthma from sparse principal components. The addresses of patients from the EHR dataset were distributed throughout the majority of Wisconsin's geography. Logistic thin plate regression spline modeling captured spatial variation of asthma. Four sparse principal components identified via model selection consisted of food at home, dog ownership, household size, and disposable income variables. In rural areas, dog ownership and renter occupied housing units from significant sparse principal components were associated with asthma. Our main contribution is the incorporation of sparsity in spatial modeling. SASEA sequentially added sparse principal components to Logistic thin plate regression spline modeling. This method allowed association of geographically distributed environmental factors with asthma using EHR and environmental datasets. SASEA can be applied to other diseases with environmental risk factors. Copyright © 2014 Elsevier Inc. All rights reserved.
REFERENCE MODELS OF ENDOGENOUS ECONOMIC GROWTH
GEAMĂNU MARINELA
2012-01-01
The new endogenous growth theories are a very important research area for shaping the most effective policies and long term sustainable development strategies. Endogenous growth theory has emerged as a reaction to the imperfections of neoclassical theory, by the fact that the economic growth is the endogenous product of an economical system.
Modeling urban growth in Kigali city Rwanda
Nduwayezu, G.; Sliuzas, R.V.; Kuffer, M.
2017-01-01
The uncontrolled urban growth is the key characteristics in most cities in less developed countries. However, having a good understanding of the key drivers of the city's growth dynamism has proven to be a key instrument to manage urban growth. This paper investigates the main determinants of Kigali
Analysis models for variables associated with breastfeeding duration
Directory of Open Access Journals (Sweden)
Edson Theodoro dos S. Neto
2013-09-01
Full Text Available OBJECTIVE To analyze the factors associated with breastfeeding duration by two statistical models. METHODS A population-based cohort study was conducted with 86 mothers and newborns from two areas primary covered by the National Health System, with high rates of infant mortality in Vitória, Espírito Santo, Brazil. During 30 months, 67 (78% children and mothers were visited seven times at home by trained interviewers, who filled out survey forms. Data on food and sucking habits, socioeconomic and maternal characteristics were collected. Variables were analyzed by Cox regression models, considering duration of breastfeeding as the dependent variable, and logistic regression (dependent variables, was the presence of a breastfeeding child in different post-natal ages. RESULTS In the logistic regression model, the pacifier sucking (adjusted Odds Ratio: 3.4; 95%CI 1.2-9.55 and bottle feeding (adjusted Odds Ratio: 4.4; 95%CI 1.6-12.1 increased the chance of weaning a child before one year of age. Variables associated to breastfeeding duration in the Cox regression model were: pacifier sucking (adjusted Hazard Ratio 2.0; 95%CI 1.2-3.3 and bottle feeding (adjusted Hazard Ratio 2.0; 95%CI 1.2-3.5. However, protective factors (maternal age and family income differed between both models. CONCLUSIONS Risk and protective factors associated with cessation of breastfeeding may be analyzed by different models of statistical regression. Cox Regression Models are adequate to analyze such factors in longitudinal studies.
Study of growth kinetic and modeling of ethanol production by ...
African Journals Online (AJOL)
... coefficient (0.96299). Based on Leudking-Piret model, it could be concluded that ethanol batch fermentation is a non-growth associated process. Key words: Kinetic parameters, simulation, cell growth, ethanol, Saccharomyces cerevisiae.
Two-step variable selection in quantile regression models
Directory of Open Access Journals (Sweden)
FAN Yali
2015-06-01
Full Text Available We propose a two-step variable selection procedure for high dimensional quantile regressions, in which the dimension of the covariates, pn is much larger than the sample size n. In the first step, we perform ℓ1 penalty, and we demonstrate that the first step penalized estimator with the LASSO penalty can reduce the model from an ultra-high dimensional to a model whose size has the same order as that of the true model, and the selected model can cover the true model. The second step excludes the remained irrelevant covariates by applying the adaptive LASSO penalty to the reduced model obtained from the first step. Under some regularity conditions, we show that our procedure enjoys the model selection consistency. We conduct a simulation study and a real data analysis to evaluate the finite sample performance of the proposed approach.
Oscillations in a Growth Model with Capital, Technology and Environment with Exogenous Shocks
Directory of Open Access Journals (Sweden)
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.
Ensembling Variable Selectors by Stability Selection for the Cox Model
Directory of Open Access Journals (Sweden)
Qing-Yan Yin
2017-01-01
Full Text Available As a pivotal tool to build interpretive models, variable selection plays an increasingly important role in high-dimensional data analysis. In recent years, variable selection ensembles (VSEs have gained much interest due to their many advantages. Stability selection (Meinshausen and Bühlmann, 2010, a VSE technique based on subsampling in combination with a base algorithm like lasso, is an effective method to control false discovery rate (FDR and to improve selection accuracy in linear regression models. By adopting lasso as a base learner, we attempt to extend stability selection to handle variable selection problems in a Cox model. According to our experience, it is crucial to set the regularization region Λ in lasso and the parameter λmin properly so that stability selection can work well. To the best of our knowledge, however, there is no literature addressing this problem in an explicit way. Therefore, we first provide a detailed procedure to specify Λ and λmin. Then, some simulated and real-world data with various censoring rates are used to examine how well stability selection performs. It is also compared with several other variable selection approaches. Experimental results demonstrate that it achieves better or competitive performance in comparison with several other popular techniques.
DEFF Research Database (Denmark)
Panduro, Toke Emil; Thorsen, Bo Jellesmark
2014-01-01
Hedonic models in environmental valuation studies have grown in terms of number of transactions and number of explanatory variables. We focus on the practical challenge of model reduction, when aiming for reliable parsimonious models, sensitive to omitted variable bias and multicollinearity. We...
Hidden Markov latent variable models with multivariate longitudinal data.
Song, Xinyuan; Xia, Yemao; Zhu, Hongtu
2017-03-01
Cocaine addiction is chronic and persistent, and has become a major social and health problem in many countries. Existing studies have shown that cocaine addicts often undergo episodic periods of addiction to, moderate dependence on, or swearing off cocaine. Given its reversible feature, cocaine use can be formulated as a stochastic process that transits from one state to another, while the impacts of various factors, such as treatment received and individuals' psychological problems on cocaine use, may vary across states. This article develops a hidden Markov latent variable model to study multivariate longitudinal data concerning cocaine use from a California Civil Addict Program. The proposed model generalizes conventional latent variable models to allow bidirectional transition between cocaine-addiction states and conventional hidden Markov models to allow latent variables and their dynamic interrelationship. We develop a maximum-likelihood approach, along with a Monte Carlo expectation conditional maximization (MCECM) algorithm, to conduct parameter estimation. The asymptotic properties of the parameter estimates and statistics for testing the heterogeneity of model parameters are investigated. The finite sample performance of the proposed methodology is demonstrated by simulation studies. The application to cocaine use study provides insights into the prevention of cocaine use. © 2016, The International Biometric Society.
Neo-logistic model for the growth of bacteria
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...
A.D. McGuire; R.W. Ruess; A. Lloyd; J. Yarie; J.S. Clein; G.P. Juday
2010-01-01
This paper integrates dendrochronological, demographic, and experimental perspectives to improve understanding of the response of white spruce (Picea glauca (Moench) Voss) tree growth to climatic variability in interior Alaska. The dendrochronological analyses indicate that climate warming has led to widespread declines in white spruce growth...
Rodgveller, Cara J; Hutchinson, Charles E; Harris, Jeremy P; Vulstek, Scott C; Guthrie, Charles M
2017-01-01
Fish stocks can be defined by differences in their distribution, life history, and genetics. Managing fish based on stock structure is integral to successful management of a species because fishing may affect stocks disproportionately. Genetic and environmental differences can affect the shape and growth of otoliths and these differences may be indicative of stock structure. To investigate the potential for speciation or stock structure in giant grenadier, Albatrossia pectoralis, we quantified the shape of female giant grenadier otoliths and compared body growth rates for fish with three otolith shapes; shape types were classified visually by an experienced giant grenadier age reader, and were not defined by known distribution or life history differences. We found extreme variation in otolith shape among individuals; however, the shapes were a gradation and not clearly defined into three groups. The two more extreme shapes, visually defined as "hatchet" and "comb", were discernable based on principal component analyses of elliptical Fourier descriptors, and the "mixed" shape overlapped both of the extreme shapes. Fish with hatchet-shaped otoliths grew faster than fish with comb-shaped otoliths. A genetic test (cytochrome c oxidase 1 used by the Fish Barcode of Life Initiative) showed almost no variability among samples, indicating that the samples were all from one species. The lack of young specimens makes it difficult to link otolith shape and growth difference to life history. In addition, shape could not be correlated with adult movement patterns because giant grenadiers experience 100% mortality after capture and, therefore, cannot be tagged and released. Despite these limitations, the link between body growth and otolith shape indicates measurable differences that deserve more study.
Gillman, Max; Otto, Glen
2006-01-01
The paper presents and tests a theory of the demand for money that is derived from a general equilibrium, endogenous growth economy, which in effect combines a special case of the shopping time exchange economy with the cash-in-advance framework. The model predicts that both higher inflation and financial innovation - that reduces the cost of credit - induce agents to substitute away from money towards exchange credit. The implied interest elasticity of money demand rises with the inflation r...
Environmental versus demographic variability in stochastic predator–prey models
International Nuclear Information System (INIS)
Dobramysl, U; Täuber, U C
2013-01-01
In contrast to the neutral population cycles of the deterministic mean-field Lotka–Volterra rate equations, including spatial structure and stochastic noise in models for predator–prey interactions yields complex spatio-temporal structures associated with long-lived erratic population oscillations. Environmental variability in the form of quenched spatial randomness in the predation rates results in more localized activity patches. Our previous study showed that population fluctuations in rare favorable regions in turn cause a remarkable increase in the asymptotic densities of both predators and prey. Very intriguing features are found when variable interaction rates are affixed to individual particles rather than lattice sites. Stochastic dynamics with demographic variability in conjunction with inheritable predation efficiencies generate non-trivial time evolution for the predation rate distributions, yet with overall essentially neutral optimization. (paper)
Testing linear growth rate formulas of non-scale endogenous growth models
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
Modeling biological tissue growth: discrete to continuum representations.
Hywood, Jack D; Hackett-Jones, Emily J; Landman, Kerry A
2013-09-01
There is much interest in building deterministic continuum models from discrete agent-based models governed by local stochastic rules where an agent represents a biological cell. In developmental biology, cells are able to move and undergo cell division on and within growing tissues. A growing tissue is itself made up of cells which undergo cell division, thereby providing a significant transport mechanism for other cells within it. We develop a discrete agent-based model where domain agents represent tissue cells. Each agent has the ability to undergo a proliferation event whereby an additional domain agent is incorporated into the lattice. If a probability distribution describes the waiting times between proliferation events for an individual agent, then the total length of the domain is a random variable. The average behavior of these stochastically proliferating agents defining the growing lattice is determined in terms of a Fokker-Planck equation, with an advection and diffusion term. The diffusion term differs from the one obtained Landman and Binder [J. Theor. Biol. 259, 541 (2009)] when the rate of growth of the domain is specified, but the choice of agents is random. This discrepancy is reconciled by determining a discrete-time master equation for this process and an associated asymmetric nonexclusion random walk, together with consideration of synchronous and asynchronous updating schemes. All theoretical results are confirmed with numerical simulations. This study furthers our understanding of the relationship between agent-based rules, their implementation, and their associated partial differential equations. Since tissue growth is a significant cellular transport mechanism during embryonic growth, it is important to use the correct partial differential equation description when combining with other cellular functions.
Pre-quantum mechanics. Introduction to models with hidden variables
International Nuclear Information System (INIS)
Grea, J.
1976-01-01
Within the context of formalism of hidden variable type, the author considers the models used to describe mechanical systems before the introduction of the quantum model. An account is given of the characteristics of the theoretical models and their relationships with experimental methodology. The models of analytical, pre-ergodic, stochastic and thermodynamic mechanics are studied in succession. At each stage the physical hypothesis is enunciated by postulate corresponding to the type of description of the reality of the model. Starting from this postulate, the physical propositions which are meaningful for the model under consideration are defined and their logical structure is indicated. It is then found that on passing from one level of description to another, one can obtain successively Boolean lattices embedded in lattices of continuous geometric type, which are themselves embedded in Boolean lattices. It is therefore possible to envisage a more detailed description than that given by the quantum lattice and to construct it by analogy. (Auth.)
An Atmospheric Variability Model for Venus Aerobraking Missions
Tolson, Robert T.; Prince, Jill L. H.; Konopliv, Alexander A.
2013-01-01
Aerobraking has proven to be an enabling technology for planetary missions to Mars and has been proposed to enable low cost missions to Venus. Aerobraking saves a significant amount of propulsion fuel mass by exploiting atmospheric drag to reduce the eccentricity of the initial orbit. The solar arrays have been used as the primary drag surface and only minor modifications have been made in the vehicle design to accommodate the relatively modest aerothermal loads. However, if atmospheric density is highly variable from orbit to orbit, the mission must either accept higher aerothermal risk, a slower pace for aerobraking, or a tighter corridor likely with increased propulsive cost. Hence, knowledge of atmospheric variability is of great interest for the design of aerobraking missions. The first planetary aerobraking was at Venus during the Magellan mission. After the primary Magellan science mission was completed, aerobraking was used to provide a more circular orbit to enhance gravity field recovery. Magellan aerobraking took place between local solar times of 1100 and 1800 hrs, and it was found that the Venusian atmospheric density during the aerobraking phase had less than 10% 1 sigma orbit to orbit variability. On the other hand, at some latitudes and seasons, Martian variability can be as high as 40% 1 sigmaFrom both the MGN and PVO mission it was known that the atmosphere, above aerobraking altitudes, showed greater variability at night, but this variability was never quantified in a systematic manner. This paper proposes a model for atmospheric variability that can be used for aerobraking mission design until more complete data sets become available.
Directory of Open Access Journals (Sweden)
Carlos Roberto Sette Jr
2016-04-01
Full Text Available ABSTRACT Climatic conditions stimulates the cambial activity of plants, and cause significant changes in trunk diameter growth and wood characteristics. The objective of this study was to evaluate the influence of climate variables in the diameter growth rate of the stem and the wood density of Eucalyptus grandis trees in different classes of the basal area. A total of 25 Eucalyptus trees at 22 months of age were selected according to the basal area distribution. Dendrometer bands were installed at the height of 1.30 meters (DBH to monitor the diameter growth every 14 days, for 26 months. After measuring growth, the trees were felled and wood discs were removed at the DBH level to determine the radial density profile through x-ray microdensitometry and then re-scale the average values every 14 days. Climatic variables for the monitoring period were obtained and grouped every 14 days. The effect of the climate variables was determined by maximum and minimum growth periods in assessing trunk growth. These growth periods were related with precipitation, average temperature and relative air humidity. The re-scaled wood density values, calculated using the radial growth of the tree trunks measured accurately with steel dendrometers, enabled the determination of the relationship of small changes in wood density and the effect of the climatic variations and growth rate of eucalyptus tree trunks. A high sensitivity of the wood density to variation in precipitation levels was found.
A new approach for modelling variability in residential construction projects
Directory of Open Access Journals (Sweden)
Mehrdad Arashpour
2013-06-01
Full Text Available The construction industry is plagued by long cycle times caused by variability in the supply chain. Variations or undesirable situations are the result of factors such as non-standard practices, work site accidents, inclement weather conditions and faults in design. This paper uses a new approach for modelling variability in construction by linking relative variability indicators to processes. Mass homebuilding sector was chosen as the scope of the analysis because data is readily available. Numerous simulation experiments were designed by varying size of capacity buffers in front of trade contractors, availability of trade contractors, and level of variability in homebuilding processes. The measurements were shown to lead to an accurate determination of relationships between these factors and production parameters. The variability indicator was found to dramatically affect the tangible performance measures such as home completion rates. This study provides for future analysis of the production homebuilding sector, which may lead to improvements in performance and a faster product delivery to homebuyers.
A new approach for modelling variability in residential construction projects
Directory of Open Access Journals (Sweden)
Mehrdad Arashpour
2013-06-01
Full Text Available The construction industry is plagued by long cycle times caused by variability in the supply chain. Variations or undesirable situations are the result of factors such as non-standard practices, work site accidents, inclement weather conditions and faults in design. This paper uses a new approach for modelling variability in construction by linking relative variability indicators to processes. Mass homebuilding sector was chosen as the scope of the analysis because data is readily available. Numerous simulation experiments were designed by varying size of capacity buffers in front of trade contractors, availability of trade contractors, and level of variability in homebuilding processes. The measurements were shown to lead to an accurate determination of relationships between these factors and production parameters. The variability indicator was found to dramatically affect the tangible performance measures such as home completion rates. This study provides for future analysis of the production homebuilding sector, which may lead to improvements in performance and a faster product delivery to homebuyers.
DEFF Research Database (Denmark)
Nielsen, Cecilie Lykke Marvig; Kristiansen, Rikke M.; Nielsen, Dennis Sandris
2015-01-01
sugar and fat and a traditionally long self-life of sweet IMFs, the presence of Z. rouxii in the raw materials for IMFs has made assessment of the microbiological stability a significant hurdle in product development. Therefore, knowledge on growth/no growth boundaries of Z. rouxii in sweet IMFs...... is important to ensure microbiological stability and aid product development. Several models have been developed for fat based, sweet IMFs. However, fruit/sugar based IMFs, such as fruit based chocolate fillings and jams, have lower pH and aw than what is accounted for in previously developed models....... In the present study growth/no growth models for acidified sweet IMFs were developed with the variables aw (0.65-0.80), pH (2.5-4.0), ethanol (0-14.5% (w/w) in water phase) and time (0-90 days). Two different strains of Z. rouxii previously found to show pronounced resistance to the investigated variables were...
Design of Plant Gas Exchange Experiments in a Variable Pressure Growth Chamber
Corey, Kenneth A.
1996-01-01
Sustainable human presence in extreme environments such as lunar and martian bases will require bioregenerative components to human life support systems where plants are used for generation of oxygen, food, and water. Reduced atmospheric pressures will be used to minimize mass and engineering requirements. Few studies have assessed the metabolic and developmental responses of plants to reduced pressure and varied oxygen atmospheres. The first tests of hypobaric pressures on plant gas exchange and biomass production at the Johnson Space Center will be initiated in January 1996 in the Variable Pressure Growth Chamber (VPGC), a large, closed plant growth chamber rated for 10.2 psi. Experiments were designed and protocols detailed for two complete growouts each of lettuce and wheat to generate a general database for human life support requirements and to answer questions about plant growth processes in reduced pressure and varied oxygen environments. The central objective of crop growth studies in the VPGC is to determine the influence of reduced pressure and reduced oxygen on the rates of photosynthesis, dark respiration, evapotranspiration and biomass production of lettuce and wheat. Due to the constraint of one experimental unit, internal controls, called pressure transients, will be used to evaluate rates of CO2 uptake, O2 evolution, and H2O generation. Pressure transients will give interpretive power to the results of repeated growouts at both reduced and ambient pressures. Other experiments involve the generation of response functions to partial pressures of O2 and CO2 and to light intensity. Protocol for determining and calculating rates of gas exchange have been detailed. In order to build these databases and implement the necessary treatment combinations in short time periods, specific requirements for gas injections and removals have been defined. A set of system capability checks will include determination of leakage rates conducted prior to the actual crop
Multiscale thermohydrologic model: addressing variability and uncertainty at Yucca Mountain
International Nuclear Information System (INIS)
Buscheck, T; Rosenberg, N D; Gansemer, J D; Sun, Y
2000-01-01
Performance assessment and design evaluation require a modeling tool that simultaneously accounts for processes occurring at a scale of a few tens of centimeters around individual waste packages and emplacement drifts, and also on behavior at the scale of the mountain. Many processes and features must be considered, including non-isothermal, multiphase-flow in rock of variable saturation and thermal radiation in open cavities. Also, given the nature of the fractured rock at Yucca Mountain, a dual-permeability approach is needed to represent permeability. A monolithic numerical model with all these features requires too large a computational cost to be an effective simulation tool, one that is used to examine sensitivity to key model assumptions and parameters. We have developed a multi-scale modeling approach that effectively simulates 3D discrete-heat-source, mountain-scale thermohydrologic behavior at Yucca Mountain and captures the natural variability of the site consistent with what we know from site characterization and waste-package-to-waste-package variability in heat output. We describe this approach and present results examining the role of infiltration flux, the most important natural-system parameter with respect to how thermohydrologic behavior influences the performance of the repository
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.
Response of wheat restricted-tillering and vigorous growth traits to variables of climate change.
Dias de Oliveira, Eduardo A; Siddique, Kadambot H M; Bramley, Helen; Stefanova, Katia; Palta, Jairo A
2015-02-01
The response of wheat to the variables of climate change includes elevated CO2, high temperature, and drought which vary according to the levels of each variable and genotype. Independently, elevated CO2, high temperature, and terminal drought affect wheat biomass and grain yield, but the interactive effects of these three variables are not well known. The aim of this study was to determine the effects of elevated CO2 when combined with high temperature and terminal drought on the high-yielding traits of restricted-tillering and vigorous growth. It was hypothesized that elevated CO2 alone, rather than combined with high temperature, ameliorates the effects of terminal drought on wheat biomass and grain yield. It was also hypothesized that wheat genotypes with more sink capacity (e.g. high-tillering capacity and leaf area) have more grain yield under combined elevated CO2, high temperature, and terminal drought. Two pairs of sister lines with contrasting tillering and vigorous growth were grown in poly-tunnels in a four-factor completely randomized split-plot design with elevated CO2 (700 µL L(-1)), high day time temperature (3 °C above ambient), and drought (induced from anthesis) in all combinations to test whether elevated CO2 ameliorates the effects of high temperature and terminal drought on biomass accumulation and grain yield. For biomass and grain yield, only main effects for climate change variables were significant. Elevated CO2 significantly increased grain yield by 24-35% in all four lines and terminal drought significantly reduced grain yield by 16-17% in all four lines, while high temperature (3 °C above the ambient) had no significant effect. A trade-off between yield components limited grain yield in lines with greater sink capacity (free-tillering lines). This response suggests that any positive response to predicted changes in climate will not overcome the limitations imposed by the trade-off in yield components. © 2014 Commonwealth 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.
Explicit estimating equations for semiparametric generalized linear latent variable models
Ma, Yanyuan
2010-07-05
We study generalized linear latent variable models without requiring a distributional assumption of the latent variables. Using a geometric approach, we derive consistent semiparametric estimators. We demonstrate that these models have a property which is similar to that of a sufficient complete statistic, which enables us to simplify the estimating procedure and explicitly to formulate the semiparametric estimating equations. We further show that the explicit estimators have the usual root n consistency and asymptotic normality. We explain the computational implementation of our method and illustrate the numerical performance of the estimators in finite sample situations via extensive simulation studies. The advantage of our estimators over the existing likelihood approach is also shown via numerical comparison. We employ the method to analyse a real data example from economics. © 2010 Royal Statistical Society.
Speech-discrimination scores modeled as a binomial variable.
Thornton, A R; Raffin, M J
1978-09-01
Many studies have reported variability data for tests of speech discrimination, and the disparate results of these studies have not been given a simple explanation. Arguments over the relative merits of 25- vs 50-word tests have ignored the basic mathematical properties inherent in the use of percentage scores. The present study models performance on clinical tests of speech discrimination as a binomial variable. A binomial model was developed, and some of its characteristics were tested against data from 4120 scores obtained on the CID Auditory Test W-22. A table for determining significant deviations between scores was generated and compared to observed differences in half-list scores for the W-22 tests. Good agreement was found between predicted and observed values. Implications of the binomial characteristics of speech-discrimination scores are discussed.
Delpierre, Nicolas; Berveiller, Daniel; Granda, Elena; Dufrêne, Eric
2016-04-01
Although the analysis of flux data has increased our understanding of the interannual variability of carbon inputs into forest ecosystems, we still know little about the determinants of wood growth. Here, we aimed to identify which drivers control the interannual variability of wood growth in a mesic temperate deciduous forest. We analysed a 9-yr time series of carbon fluxes and aboveground wood growth (AWG), reconstructed at a weekly time-scale through the combination of dendrometer and wood density data. Carbon inputs and AWG anomalies appeared to be uncorrelated from the seasonal to interannual scales. More than 90% of the interannual variability of AWG was explained by a combination of the growth intensity during a first 'critical period' of the wood growing season, occurring close to the seasonal maximum, and the timing of the first summer growth halt. Both atmospheric and soil water stress exerted a strong control on the interannual variability of AWG at the study site, despite its mesic conditions, whilst not affecting carbon inputs. Carbon sink activity, not carbon inputs, determined the interannual variations in wood growth at the study site. Our results provide a functional understanding of the dependence of radial growth on precipitation observed in dendrological studies. © 2015 The Authors. New Phytologist © 2015 New Phytologist Trust.
Efficient family-based model checking via variability abstractions
DEFF Research Database (Denmark)
Dimovski, Aleksandar; Al-Sibahi, Ahmad Salim; Brabrand, Claus
2016-01-01
with the abstract model checking of the concrete high-level variational model. This allows the use of Spin with all its accumulated optimizations for efficient verification of variational models without any knowledge about variability. We have implemented the transformations in a prototype tool, and we illustrate......Many software systems are variational: they can be configured to meet diverse sets of requirements. They can produce a (potentially huge) number of related systems, known as products or variants, by systematically reusing common parts. For variational models (variational systems or families...... of related systems), specialized family-based model checking algorithms allow efficient verification of multiple variants, simultaneously, in a single run. These algorithms, implemented in a tool Snip, scale much better than ``the brute force'' approach, where all individual systems are verified using...
Forest Growth and Yield Models Viewed From a Different Perspective
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...
Parameter Estimates in Differential Equation Models for Population Growth
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,…
Predictive modeling and reducing cyclic variability in autoignition engines
Hellstrom, Erik; Stefanopoulou, Anna; Jiang, Li; Larimore, Jacob
2016-08-30
Methods and systems are provided for controlling a vehicle engine to reduce cycle-to-cycle combustion variation. A predictive model is applied to predict cycle-to-cycle combustion behavior of an engine based on observed engine performance variables. Conditions are identified, based on the predicted cycle-to-cycle combustion behavior, that indicate high cycle-to-cycle combustion variation. Corrective measures are then applied to prevent the predicted high cycle-to-cycle combustion variation.
United States geological survey's reserve-growth models and their implementation
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.
Spiral Growth in Plants: Models and Simulations
Allen, Bradford D.
2004-01-01
The analysis and simulation of spiral growth in plants integrates algebra and trigonometry in a botanical setting. When the ideas presented here are used in a mathematics classroom/computer lab, students can better understand how basic assumptions about plant growth lead to the golden ratio and how the use of circular functions leads to accurate…
Genetic Variability on Growth, Phenological and Seed Characteristics of Jatropha curcas L.
Directory of Open Access Journals (Sweden)
Sagar MOHAPATRA
2010-06-01
Full Text Available Twenty randomly selected seeds of Jatropha curcas collected from different agroclimatic zones of India were studied for variability on growth, phenology and seed characteristics in a progeny trial under tropical monsoon climatic conditions of Bhubaneswar (200 14�N/850 50� E, India. Correlation studies revealed that length and number of branches were positively correlated with the number of inflorescence (P<1% and number of fruits per plant (P<5%. A positive correlation between fruit diameter and oil content and also, between seed length and test weight was observed. Number of fruits per plant showed almost 100% heritability followed by the number of inflorescence (88.79%. Non hierarchical Euclidean cluster analysis resulted in six clusters with highest number of six accessions namely, �Chandaka�, �PKVJ-AKT-1�, �TNMC-4�, �PKVJ-MKU-1�, �TFRI-1� and Indore falling under cluster II. Maximum and minimum intra-cluster distances were observed for cluster II (2.929 and cluster III (0.000, respectively. Maximum inter-cluster distance (7.195 was found between cluster III and VI followed by Cluster III and IV (7.074. Analysis of the results of the present study clearly indicate that crossing between the accessions of cluster III and VI would be useful in developing variable genotypes in the subsequent generations.
Are revised models better models? A skill score assessment of regional interannual variability
Sperber, Kenneth R.; Participating AMIP Modelling Groups
1999-05-01
Various skill scores are used to assess the performance of revised models relative to their original configurations. The interannual variability of all-India, Sahel and Nordeste rainfall and summer monsoon windshear is examined in integrations performed under the experimental design of the Atmospheric Model Intercomparison Project. For the indices considered, the revised models exhibit greater fidelity at simulating the observed interannual variability. Interannual variability of all-India rainfall is better simulated by models that have a more realistic rainfall climatology in the vicinity of India, indicating the beneficial effect of reducing systematic model error.
gamboostLSS: An R Package for Model Building and Variable Selection in the GAMLSS Framework
Directory of Open Access Journals (Sweden)
Benjamin Hofner
2016-10-01
Full Text Available Generalized additive models for location, scale and shape are a flexible class of regression models that allow to model multiple parameters of a distribution function, such as the mean and the standard deviation, simultaneously. With the R package gamboostLSS, we provide a boosting method to fit these models. Variable selection and model choice are naturally available within this regularized regression framework. To introduce and illustrate the R package gamboostLSS and its infrastructure, we use a data set on stunted growth in India. In addition to the specification and application of the model itself, we present a variety of convenience functions, including methods for tuning parameter selection, prediction and visualization of results. The package gamboostLSS is available from the Comprehensive R Archive Network (CRAN at https://CRAN.R-project.org/package=gamboostLSS.
A Variable Flow Modelling Approach To Military End Strength Planning
2016-12-01
function. The MLRPS is more complex than the variable flow model as it has to cater for a force structure that is much larger than just the MT branch...essential positions in a Ship’s complement, or by the biggest current deficit in forecast end strength. The model can be adjusted to cater for any of these...is unlikely that the RAN will be able to cater for such an increase in hires, so this scenario is not likely to solve their problem. Each transition
Variable sound speed in interacting dark energy models
Linton, Mark S.; Pourtsidou, Alkistis; Crittenden, Robert; Maartens, Roy
2018-04-01
We consider a self-consistent and physical approach to interacting dark energy models described by a Lagrangian, and identify a new class of models with variable dark energy sound speed. We show that if the interaction between dark energy in the form of quintessence and cold dark matter is purely momentum exchange this generally leads to a dark energy sound speed that deviates from unity. Choosing a specific sub-case, we study its phenomenology by investigating the effects of the interaction on the cosmic microwave background and linear matter power spectrum. We also perform a global fitting of cosmological parameters using CMB data, and compare our findings to ΛCDM.
Connolly, Joseph W.; Friedlander, David; Kopasakis, George
2015-01-01
This paper covers the development of an integrated nonlinear dynamic simulation for a variable cycle turbofan engine and nozzle that can be integrated with an overall vehicle Aero-Propulso-Servo-Elastic (APSE) model. A previously developed variable cycle turbofan engine model is used for this study and is enhanced here to include variable guide vanes allowing for operation across the supersonic flight regime. The primary focus of this study is to improve the fidelity of the model's thrust response by replacing the simple choked flow equation convergent-divergent nozzle model with a MacCormack method based quasi-1D model. The dynamic response of the nozzle model using the MacCormack method is verified by comparing it against a model of the nozzle using the conservation element/solution element method. A methodology is also presented for the integration of the MacCormack nozzle model with the variable cycle engine.
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-O_{2} 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.
Detecting Growth Shape Misspecifications in Latent Growth Models: An Evaluation of Fit Indexes
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…
Grassland Growth in Response to Climate Variability in the Upper Indus Basin, Pakistan
Directory of Open Access Journals (Sweden)
Sawaid Abbas
2015-08-01
Full Text Available Grasslands in the upper Indus basin provide a resource base for nomadic livestock grazing which is one of the major traditional livelihood practices in the area. The study presents climate patterns, grassland phenology, productivity and spatio-temporal climate controls on grassland growth using satellite data over the upper Indus basin of the Himalayan region, Pakistan. Phenology and productivity metrics of the grasses were estimated using a combination of derivative and threshold methods applied on fitted seasonal vegetation indices data over the period of 2001–2011. Satellite based rainfall and land surface temperature data are considered as representative explanatory variables to climate variability. The results showed distinct phenology and productivity patterns across four bioclimatic regions: (i humid subtropical region (HSR—late start and early end of season with short length of season and low productivity (ii temperate region (TR—early start and late end of season with higher length of season and moderate productivity (iii sub alpine region (SAR—late start and late end of season with very high length of season and the most productive grasses, and (iv alpine region (AR—late start and early end of season with small length of season and least productive grasses. Grassland productivity is constrained by temperature in the alpine region and by rainfall in the humid sub-tropical region. Spring temperature, winter and summer rainfall has shown significant and varied impact on phenology across different altitudes. The productivity is being influenced by summer and annual rainfall in humid subtropical regions, spring temperature in alpine and sub-alpine regions and both temperature and rainfall are contributing in temperate regions. The results revealing a strong relationship between grassland dynamics and climate variability put forth strong signals for drawing more scientific management of rangelands in the area.
Directory of Open Access Journals (Sweden)
Ubaid Yaqoob
2017-01-01
Full Text Available Ferula jaeschkeana Vatke is an important threatened medicinal plant of the Himalayan region. The present study was carried out to determine the impact of the habitat variability and altitudinal gradient on the morphological and reproductive features of the species under study. The species exhibited great variability in its morphological traits under different environmental conditions. The plants were more vigorous and taller at a low altitude site, Kashmir University Botanical Garden (KUBG while the plants of a high altitude site, Gulmarg were shorter. With increased altitude, a significant reduction in the number of umbels per flowering stem, umbellules per umbel and flowers per umbellule occurred. An increase in the number of stigma and anthers was also observed in some plants at higher altitudes. Principal component analysis (PCA revealed that the habitat of KUBG and Dachigam proved relatively better for the growth of F. jaeschkeana. Maximum resources were allocated to the growth and development of the stem followed by root tubers, leaves and inflorescence. Reproductive success of the plant species varied along the altitudinal gradient and ranged from 64% to 72%. Increasing altitude resulted in a decrease in the allocation of biomass to reproductive structures in the form of decreasing dry weight. The total resource budget per plant was maximum in low altitude Drang (572.6 ± 158.36 g and Dachigam (568.4 ± 133.42 g populations and was least in the Gulmarg population (333.4 ± 82.89 g. The reproductive effort was higher (50.83% for the high altitude Gulmarg population. The regression analysis revealed a positive correlation and predicts that plant height has a direct impact on the umbel diameter and leaf length. Our results present a detailed account on the variation of growth characteristics, reproductive success and changes in allocation patterns in relation to the environmental conditions of this valuable medicinal plant species
Quantifying intrinsic and extrinsic variability in stochastic gene expression models.
Singh, Abhyudai; Soltani, Mohammad
2013-01-01
Genetically identical cell populations exhibit considerable intercellular variation in the level of a given protein or mRNA. Both intrinsic and extrinsic sources of noise drive this variability in gene expression. More specifically, extrinsic noise is the expression variability that arises from cell-to-cell differences in cell-specific factors such as enzyme levels, cell size and cell cycle stage. In contrast, intrinsic noise is the expression variability that is not accounted for by extrinsic noise, and typically arises from the inherent stochastic nature of biochemical processes. Two-color reporter experiments are employed to decompose expression variability into its intrinsic and extrinsic noise components. Analytical formulas for intrinsic and extrinsic noise are derived for a class of stochastic gene expression models, where variations in cell-specific factors cause fluctuations in model parameters, in particular, transcription and/or translation rate fluctuations. Assuming mRNA production occurs in random bursts, transcription rate is represented by either the burst frequency (how often the bursts occur) or the burst size (number of mRNAs produced in each burst). Our analysis shows that fluctuations in the transcription burst frequency enhance extrinsic noise but do not affect the intrinsic noise. On the contrary, fluctuations in the transcription burst size or mRNA translation rate dramatically increase both intrinsic and extrinsic noise components. Interestingly, simultaneous fluctuations in transcription and translation rates arising from randomness in ATP abundance can decrease intrinsic noise measured in a two-color reporter assay. Finally, we discuss how these formulas can be combined with single-cell gene expression data from two-color reporter experiments for estimating model parameters.
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.
Modeling key processes causing climate change and variability
Energy Technology Data Exchange (ETDEWEB)
Henriksson, S.
2013-09-01
Greenhouse gas warming, internal climate variability and aerosol climate effects are studied and the importance to understand these key processes and being able to separate their influence on the climate is discussed. Aerosol-climate model ECHAM5-HAM and the COSMOS millennium model consisting of atmospheric, ocean and carbon cycle and land-use models are applied and results compared to measurements. Topics at focus are climate sensitivity, quasiperiodic variability with a period of 50-80 years and variability at other timescales, climate effects due to aerosols over India and climate effects of northern hemisphere mid- and high-latitude volcanic eruptions. The main findings of this work are (1) pointing out the remaining challenges in reducing climate sensitivity uncertainty from observational evidence, (2) estimates for the amplitude of a 50-80 year quasiperiodic oscillation in global mean temperature ranging from 0.03 K to 0.17 K and for its phase progression as well as the synchronising effect of external forcing, (3) identifying a power law shape S(f) {proportional_to} f-{alpha} for the spectrum of global mean temperature with {alpha} {approx} 0.8 between multidecadal and El Nino timescales with a smaller exponent in modelled climate without external forcing, (4) separating aerosol properties and climate effects in India by season and location (5) the more efficient dispersion of secondary sulfate aerosols than primary carbonaceous aerosols in the simulations, (6) an increase in monsoon rainfall in northern India due to aerosol light absorption and a probably larger decrease due to aerosol dimming effects and (7) an estimate of mean maximum cooling of 0.19 K due to larger northern hemisphere mid- and high-latitude volcanic eruptions. The results could be applied or useful in better isolating the human-caused climate change signal, in studying the processes further and in more detail, in decadal climate prediction, in model evaluation and in emission policy
Simulation modeling on the growth of firm's safety management capability
Institute of Scientific and Technical Information of China (English)
LIU Tie-zhong; LI Zhi-xiang
2008-01-01
Aiming to the deficiency of safety management measure, established simulation model about firm's safety management capability(FSMC) based on organizational learning theory. The system dynamics(SD) method was used, in which level and rate system, variable equation and system structure flow diagram was concluded. Simulation model was verified from two aspects: first, model's sensitivity to variable was tested from the gross of safety investment and the proportion of safety investment; second, variables dependency was checked up from the correlative variable of FSMC and organizational learning. The feasibility of simulation model is verified though these processes.
Shiyko, Mariya P.; Li, Yuelin; Rindskopf, David
2012-01-01
Intensive longitudinal data (ILD) have become increasingly common in the social and behavioral sciences; count variables, such as the number of daily smoked cigarettes, are frequently used outcomes in many ILD studies. We demonstrate a generalized extension of growth mixture modeling (GMM) to Poisson-distributed ILD for identifying qualitatively…
Differential model of macroeconomic growth with endogenic cyclicity
Directory of Open Access Journals (Sweden)
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
Episodic swell growth inferred from variable uplift of the Cape Verde hotspot islands
Ramalho, R.; Helffrich, G.; Cosca, M.; Vance, D.; Hoffmann, D.; Schmidt, D.N.
2010-01-01
On the Beagle voyage, Charles Darwin first noted the creation and subsidence of ocean islands, establishing in geology's infancy that island freeboard changes with time. Hotspot ocean islands have an obvious mechanism for freeboard change through the growth of the bathymetric anomaly, or swell, on which the islands rest. Models for swell development indicate that flexural, thermal or dynamic pressure contributions, as well as spreading of melt residue from the hotspot, can all contribute to island uplift. Here we test various models for swell development using the uplift histories for the islands of the Cape Verde hotspot, derived from isotopic dating of marine terraces and subaerial to submarine lava-flow morphologies. The island uplift histories, in conjunction with inter-island spacing, uplift rate and timing differences, rule out flexural, thermal or dynamic pressure contributions. We also find that uplift cannot be reconciled with models that advocate the spreading of melt residue in swell development unless swell growth is episodic. Instead, we infer from the uplift histories that two processes have acted to raise the islands during the past 6 Myr. During an initial phase, mantle processes acted to build the swell. Subsequently, magmatic intrusions at the island edifice caused 350 m of local uplift at the scale of individual islands. Finally, swell-wide uplift contributed a further 100 m of surface rise.
Product unit neural network models for predicting the growth limits of Listeria monocytogenes.
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.
Geochemical Modeling Of F Area Seepage Basin Composition And Variability
International Nuclear Information System (INIS)
Millings, M.; Denham, M.; Looney, B.
2012-01-01
From the 1950s through 1989, the F Area Seepage Basins at the Savannah River Site (SRS) received low level radioactive wastes resulting from processing nuclear materials. Discharges of process wastes to the F Area Seepage Basins followed by subsequent mixing processes within the basins and eventual infiltration into the subsurface resulted in contamination of the underlying vadose zone and downgradient groundwater. For simulating contaminant behavior and subsurface transport, a quantitative understanding of the interrelated discharge-mixing-infiltration system along with the resulting chemistry of fluids entering the subsurface is needed. An example of this need emerged as the F Area Seepage Basins was selected as a key case study demonstration site for the Advanced Simulation Capability for Environmental Management (ASCEM) Program. This modeling evaluation explored the importance of the wide variability in bulk wastewater chemistry as it propagated through the basins. The results are intended to generally improve and refine the conceptualization of infiltration of chemical wastes from seepage basins receiving variable waste streams and to specifically support the ASCEM case study model for the F Area Seepage Basins. Specific goals of this work included: (1) develop a technically-based 'charge-balanced' nominal source term chemistry for water infiltrating into the subsurface during basin operations, (2) estimate the nature of short term and long term variability in infiltrating water to support scenario development for uncertainty quantification (i.e., UQ analysis), (3) identify key geochemical factors that control overall basin water chemistry and the projected variability/stability, and (4) link wastewater chemistry to the subsurface based on monitoring well data. Results from this study provide data and understanding that can be used in further modeling efforts of the F Area groundwater plume. As identified in this study, key geochemical factors affecting basin
Modeling urban growth in Kigali city Rwanda
African Journals Online (AJOL)
kagoyire
industrialization, land consumption and infrastructural development, have impacted ..... urban growth (reference image) and urban development predicted to the ..... neighboring characteristics (regular water and electricity provision) were not ...
Bayesian modeling of Clostridium perfringens growth in beef-in-sauce products.
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 the Spatial Isotope Variability of Precipitation in Syria
Energy Technology Data Exchange (ETDEWEB)
Kattan, Z.; Kattaa, B. [Department of Geology, Atomic Energy Commission of Syria (AECS), Damascus (Syrian Arab Republic)
2013-07-15
Attempts were made to model the spatial variability of environmental isotope ({sup 18}O, {sup 2}H and {sup 3}H) compositions of precipitation in syria. Rainfall samples periodically collected on a monthly basis from 16 different stations were used for processing and demonstrating the spatial distributions of these isotopes, together with those of deuterium excess (d) values. Mathematically, the modelling process was based on applying simple polynomial models that take into consideration the effects of major geographic factors (Lon.E., Lat.N., and altitude). The modelling results of spatial distribution of stable isotopes ({sup 18}O and {sup 2}H) were generally good, as shown from the high correlation coefficients (R{sup 2} = 0.7-0.8), calculated between the observed and predicted values. In the case of deuterium excess and tritium distributions, the results were most likely approximates (R{sup 2} = 0.5-0.6). Improving the simulation of spatial isotope variability probably requires the incorporation of other local meteorological factors, such as relative air humidity, precipitation amount and vapour pressure, which are supposed to play an important role in such an arid country. (author)
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
Seychelles Dome variability in a high resolution ocean model
Nyadjro, E. S.; Jensen, T.; Richman, J. G.; Shriver, J. F.
2016-02-01
The Seychelles-Chagos Thermocline Ridge (SCTR; 5ºS-10ºS, 50ºE-80ºE) in the tropical Southwest Indian Ocean (SWIO) has been recognized as a region of prominence with regards to climate variability in the Indian Ocean. Convective activities in this region have regional consequences as it affect socio-economic livelihood of the people especially in the countries along the Indian Ocean rim. The SCTR is characterized by a quasi-permanent upwelling that is often associated with thermocline shoaling. This upwelling affects sea surface temperature (SST) variability. We present results on the variability and dynamics of the SCTR as simulated by the 1/12º high resolution HYbrid Coordinate Ocean Model (HYCOM). It is observed that locally, wind stress affects SST via Ekman pumping of cooler subsurface waters, mixing and anomalous zonal advection. Remotely, wind stress curl in the eastern equatorial Indian Ocean generates westward-propagating Rossby waves that impacts the depth of the thermocline which in turn impacts SST variability in the SCTR region. The variability of the contributions of these processes, especially with regard to the Indian Ocean Dipole (IOD) are further examined. In a typical positive IOD (PIOD) year, the net vertical velocity in the SCTR is negative year-round as easterlies along the region are intensified leading to a strong positive curl. This vertical velocity is caused mainly by anomalous local Ekman downwelling (with peak during September-November), a direct opposite to the climatology scenario when local Ekman pumping is positive (upwelling favorable) year-round. The anomalous remote contribution to the vertical velocity changes is minimal especially during the developing and peak stages of PIOD events. In a typical negative IOD (NIOD) year, anomalous vertical velocity is positive almost year-round with peaks in May and October. The remote contribution is positive, in contrast to the climatology and most of the PIOD years.
Shared Variable Oriented Parallel Precompiler for SPMD Model
Institute of Scientific and Technical Information of China (English)
无
1995-01-01
For the moment,commercial parallel computer systems with distributed memory architecture are usually provided with parallel FORTRAN or parallel C compliers,which are just traditional sequential FORTRAN or C compilers expanded with communication statements.Programmers suffer from writing parallel programs with communication statements. The Shared Variable Oriented Parallel Precompiler (SVOPP) proposed in this paper can automatically generate appropriate communication statements based on shared variables for SPMD(Single Program Multiple Data) computation model and greatly ease the parallel programming with high communication efficiency.The core function of parallel C precompiler has been successfully verified on a transputer-based parallel computer.Its prominent performance shows that SVOPP is probably a break-through in parallel programming technique.
Geospatial models of climatological variables distribution over Colombian territory
International Nuclear Information System (INIS)
Baron Leguizamon, Alicia
2003-01-01
Diverse studies have dealt on the existing relation between the variables temperature about the air and precipitation with the altitude; nevertheless they have been precise analyses or by regions, but no of them has gotten to constitute itself in a tool that reproduces the space distribution, of the temperature or the precipitation, taking into account orography and allowing to obtain from her data on these variables in a certain place. Cradle in the raised relation and from the multi-annual monthly information of the temperature of the air and the precipitation, it was calculated the vertical gradients of temperature and the related the precipitation to the altitude. After it, with base in the data of altitude provided by the DEM, one calculated the values of temperature and precipitation, and those values were interpolated to generate geospatial models monthly
Modeling the effects of ozone on soybean growth and yield.
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.
Lv, Qiming; Schneider, Manuel K; Pitchford, Jonathan W
2008-08-01
We study individual plant growth and size hierarchy formation in an experimental population of Arabidopsis thaliana, within an integrated analysis that explicitly accounts for size-dependent growth, size- and space-dependent competition, and environmental stochasticity. It is shown that a Gompertz-type stochastic differential equation (SDE) model, involving asymmetric competition kernels and a stochastic term which decreases with the logarithm of plant weight, efficiently describes individual plant growth, competition, and variability in the studied population. The model is evaluated within a Bayesian framework and compared to its deterministic counterpart, and to several simplified stochastic models, using distributional validation. We show that stochasticity is an important determinant of size hierarchy and that SDE models outperform the deterministic model if and only if structural components of competition (asymmetry; size- and space-dependence) are accounted for. Implications of these results are discussed in the context of plant ecology and in more general modelling situations.
Tax Evasion in a Model of Endogenous Growth
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...
Multimodel Ensembles of Wheat Growth: Many Models are Better than One
Martre, Pierre; Wallach, Daniel; Asseng, Senthold; Ewert, Frank; Jones, James W.; Rotter, Reimund P.; Boote, Kenneth J.; Ruane, Alexander C.; Thorburn, Peter J.; Cammarano, Davide;
2015-01-01
Crop models of crop growth are increasingly used to quantify the impact of global changes due to climate or crop management. Therefore, accuracy of simulation results is a major concern. Studies with ensembles of crop model scan give valuable information about model accuracy and uncertainty, but such studies are difficult to organize and have only recently begun. We report on the largest ensemble study to date, of 27 wheat models tested in four contrasting locations for their accuracy in simulating multiple crop growth and yield variables. The relative error averaged over models was 2438 for the different end-of-season variables including grain yield (GY) and grain protein concentration (GPC). There was little relation between error of a model for GY or GPC and error for in-season variables. Thus, most models did not arrive at accurate simulations of GY and GPC by accurately simulating preceding growth dynamics. Ensemble simulations, taking either the mean (e-mean) or median (e-median) of simulated values, gave better estimates than any individual model when all variables were considered. Compared to individual models, e-median ranked first in simulating measured GY and third in GPC. The error of e-mean and e-median declined with an increasing number of ensemble members, with little decrease beyond 10 models. We conclude that multimodel ensembles can be used to create new estimators with improved accuracy and consistency in simulating growth dynamics. We argue that these results are applicable to other crop species, and hypothesize that they apply more generally to ecological system models.
Multimodel Ensembles of Wheat Growth: More Models are Better than One
Martre, Pierre; Wallach, Daniel; Asseng, Senthold; Ewert, Frank; Jones, James W.; Rotter, Reimund P.; Boote, Kenneth J.; Ruane, Alex C.; Thorburn, Peter J.; Cammarano, Davide;
2015-01-01
Crop models of crop growth are increasingly used to quantify the impact of global changes due to climate or crop management. Therefore, accuracy of simulation results is a major concern. Studies with ensembles of crop models can give valuable information about model accuracy and uncertainty, but such studies are difficult to organize and have only recently begun. We report on the largest ensemble study to date, of 27 wheat models tested in four contrasting locations for their accuracy in simulating multiple crop growth and yield variables. The relative error averaged over models was 24-38% for the different end-of-season variables including grain yield (GY) and grain protein concentration (GPC). There was little relation between error of a model for GY or GPC and error for in-season variables. Thus, most models did not arrive at accurate simulations of GY and GPC by accurately simulating preceding growth dynamics. Ensemble simulations, taking either the mean (e-mean) or median (e-median) of simulated values, gave better estimates than any individual model when all variables were considered. Compared to individual models, e-median ranked first in simulating measured GY and third in GPC. The error of e-mean and e-median declined with an increasing number of ensemble members, with little decrease beyond 10 models. We conclude that multimodel ensembles can be used to create new estimators with improved accuracy and consistency in simulating growth dynamics. We argue that these results are applicable to other crop species, and hypothesize that they apply more generally to ecological system models.
Stochastic growth logistic model with aftereffect for batch fermentation process
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
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.
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...
A MODEL OF ECONOMIC GROWTH WITH PUBLIC FINANCE: DYNAMICS AND ANALYTIC SOLUTION
Directory of Open Access Journals (Sweden)
Oliviero Antonio Carboni
2013-01-01
Full Text Available This paper studies the equilibrium dynamics of a growth model with public finance where two different allocations of public resources are considered. The model simultaneously determines the optimal shares of consumption, capital accumulation, taxes and composition of the two different public expenditures which maximize a representative household's lifetime utilities in a centralized economy. The analysis supplies a closed form solution. Moreover, with one restriction on the parameters ( we fully determine the solutions path for all variables of the model and determine the conditions for balanced growth.
Initial CGE Model Results Summary Exogenous and Endogenous Variables Tests
Energy Technology Data Exchange (ETDEWEB)
Edwards, Brian Keith [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Boero, Riccardo [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Rivera, Michael Kelly [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
2017-08-07
The following discussion presents initial results of tests of the most recent version of the National Infrastructure Simulation and Analysis Center Dynamic Computable General Equilibrium (CGE) model developed by Los Alamos National Laboratory (LANL). The intent of this is to test and assess the model’s behavioral properties. The test evaluated whether the predicted impacts are reasonable from a qualitative perspective. This issue is whether the predicted change, be it an increase or decrease in other model variables, is consistent with prior economic intuition and expectations about the predicted change. One of the purposes of this effort is to determine whether model changes are needed in order to improve its behavior qualitatively and quantitatively.
Kinetic models of cell growth, substrate utilization and bio ...
African Journals Online (AJOL)
STORAGESEVER
2008-05-02
May 2, 2008 ... Aspergillus fumigatus. A simple model was proposed using the Logistic Equation for the growth, ... costs and also involved in less sophisticated fermentation ... apply and they are accurately proved that the model can express ...
A fuzzy mathematical model of West Java population with logistic growth model
Nurkholipah, N. S.; Amarti, Z.; Anggriani, N.; Supriatna, A. K.
2018-03-01
In this paper we develop a mathematics model of population growth in the West Java Province Indonesia. The model takes the form as a logistic differential equation. We parameterize the model using several triples of data, and choose the best triple which has the smallest Mean Absolute Percentage Error (MAPE). The resulting model is able to predict the historical data with a high accuracy and it also able to predict the future of population number. Predicting the future population is among the important factors that affect the consideration is preparing a good management for the population. Several experiment are done to look at the effect of impreciseness in the data. This is done by considering a fuzzy initial value to the crisp model assuming that the model propagates the fuzziness of the independent variable to the dependent variable. We assume here a triangle fuzzy number representing the impreciseness in the data. We found that the fuzziness may disappear in the long-term. Other scenarios also investigated, such as the effect of fuzzy parameters to the crisp initial value of the population. The solution of the model is obtained numerically using the fourth-order Runge-Kutta scheme.
Nonlinear Growth Models in M"plus" and SAS
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…
Singular vector decomposition of the internal variability of the Canadian Regional Climate Model
Energy Technology Data Exchange (ETDEWEB)
Diaconescu, Emilia Paula; Laprise, Rene [University of Quebec at Montreal (UQAM), Department of Earth and Atmospheric Sciences, Canadian Network for Regional Climate Modelling and Diagnostics, P.O. Box 8888, Montreal, QC (Canada); Centre ESCER (Etude et Simulation du Climat a l' Echelle Regionale), Montreal, QC (Canada); Zadra, Ayrton [University of Quebec at Montreal (UQAM), Department of Earth and Atmospheric Sciences, Canadian Network for Regional Climate Modelling and Diagnostics, P.O. Box 8888, Montreal, QC (Canada); Environment Canada, Meteorological Research Division, Montreal, QC (Canada); Centre ESCER (Etude et Simulation du Climat a l' Echelle Regionale), Montreal, QC (Canada)
2012-03-15
Previous studies have shown that Regional Climate Models (RCM) internal variability (IV) fluctuates in time depending on synoptic events. This study focuses on the physical understanding of episodes with rapid growth of IV. An ensemble of 21 simulations, differing only in their initial conditions, was run over North America using version 5 of the Canadian RCM (CRCM). The IV is quantified in terms of energy of CRCM perturbations with respect to a reference simulation. The working hypothesis is that IV is arising through rapidly growing perturbations developed in dynamically unstable regions. If indeed IV is triggered by the growth of unstable perturbations, a large proportion of the CRCM perturbations must project onto the most unstable singular vectors (SVs). A set of ten SVs was computed to identify the orthogonal set of perturbations that provide the maximum growth with respect to the dry total-energy norm during the course of the CRCM ensemble of simulations. CRCM perturbations were then projected onto the subspace of SVs. The analysis of one episode of rapid growth of IV is presented in detail. It is shown that a large part of the IV growth is explained by initially small-amplitude unstable perturbations represented by the ten leading SVs, the SV subspace accounting for over 70% of the CRCM IV growth in 36 h. The projection on the leading SV at final time is greater than the projection on the remaining SVs and there is a high similarity between the CRCM perturbations and the leading SV after 24-36 h tangent-linear model integration. The vertical structure of perturbations revealed that the baroclinic conversion is the dominant process in IV growth for this particular episode. (orig.)
TAX COMPOSITION AND ECONOMIC GROWTH. A PANEL-MODEL APPROACH FOR EASTERN EUROPE
Directory of Open Access Journals (Sweden)
MURA PETRU-OVIDIU
2015-03-01
Full Text Available In this paper, we investigate the impact of tax composition on economic growth, based on a panel-model approach. The dataset includes six East-European countries and covers the period 1995-2012. Specifically, the study explores the relative impact of different components of tax revenue (direct and indirect tax revenue, as percentage of total tax revenue on economic growth. The paper adds marginally to the empirical literature, showing how the two types of tax revenue influence economic growth in Eastern Europe, under an extended set of economic and sociopolitical control variables. The most important empirical output, for the 6 investigated East-European countries during 1995-2012, suggests that direct taxes are significant and negatively correlated with economic growth, while indirect taxes exert a positive influence on the dependent variable, though insignificant. As for the control variables, it seems that only freedom from corruption and political stability have a significant impact on economic growth. The study suggests that the design of tax systems in Eastern European countries is in accordance with the Commission’s priorities regarding its growth-friendliness. As for policy implications, governments should continue shifting the tax burden away from labour on to tax bases linked to consumption, property, and combating pollution, with potential positive effects both for growth and for fighting against tax evasion.
Modelling the growth of Populus species using Ecosystem Demography (ED) model
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.
Variable slip wind generator modeling for real-time simulation
Energy Technology Data Exchange (ETDEWEB)
Gagnon, R.; Brochu, J.; Turmel, G. [Hydro-Quebec, Varennes, PQ (Canada). IREQ
2006-07-01
A model of a wind turbine using a variable slip wound-rotor induction machine was presented. The model was created as part of a library of generic wind generator models intended for wind integration studies. The stator winding of the wind generator was connected directly to the grid and the rotor was driven by the turbine through a drive train. The variable resistors was synthesized by an external resistor in parallel with a diode rectifier. A forced-commutated power electronic device (IGBT) was connected to the wound rotor by slip rings and brushes. Simulations were conducted in a Matlab/Simulink environment using SimPowerSystems blocks to model power systems elements and Simulink blocks to model the turbine, control system and drive train. Detailed descriptions of the turbine, the drive train and the control system were provided. The model's implementation in the simulator was also described. A case study demonstrating the real-time simulation of a wind generator connected at the distribution level of a power system was presented. Results of the case study were then compared with results obtained from the SimPowerSystems off-line simulation. Results showed good agreement between the waveforms, demonstrating the conformity of the real-time and the off-line simulations. The capability of Hypersim for real-time simulation of wind turbines with power electronic converters in a distribution network was demonstrated. It was concluded that hardware-in-the-loop (HIL) simulation of wind turbine controllers for wind integration studies in power systems is now feasible. 5 refs., 1 tab., 6 figs.
Directory of Open Access Journals (Sweden)
Vojinovič Borut
2005-01-01
Full Text Available Financial development is correlated with several underlying regulatory variables (such as indicators of investor protection, market transparency variables for corporate governance growth and rules for capital market development, which are under the control of national legislators and EU directives. This paper provides estimates of the relationship between financial market development and corporate growth and assesses the impact of financial market integration on this relationship with reference to European Union (EU countries. The regression results obtained using this panel support the hypothesis that financial development promotes growth particularly in industries that are more financially dependent on external finance. For policy purposes, analyzing changes in these regulatory variables may be a more interesting exercise than analyzing integration of the financial systems themselves. Since assuming that EU countries will raise its regulatory and legal standards to the U.S. standards appears unrealistic, in this case we examine a scenario where EU countries raise their standards to the highest current EU standard.
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.
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.
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
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.
Pal, Probir Kumar; Kumar, Rajender; Guleria, Vipan; Mahajan, Mitali; Prasad, Ramdeen; Pathania, Vijaylata; Gill, Baljinder Singh; Singh, Devinder; Chand, Gopi; Singh, Bikram; Singh, Rakesh Deosharan; Ahuja, Paramvir Singh
2015-02-27
Plant nutrition and climatic conditions play important roles on the growth and secondary metabolites of stevia (Stevia rebaudiana Bertoni); however, the nutritional dose is strongly governed by the soil properties and climatic conditions of the growing region. In northern India, the interactive effects of crop ecology and plant nutrition on yield and secondary metabolites of stevia are not yet properly understood. Thus, a field experiment comprising three levels of nitrogen, two levels of phosphorus and three levels of potassium was conducted at three locations to ascertain whether the spatial and nutritional variability would dominate the leaf yield and secondary metabolites profile of stevia. Principal component analysis (PCA) indicates that the applications of 90 kg N, 40 kg P2O5 and 40 kg K2O ha-1 are the best nutritional conditions in terms of dry leaf yield for CSIR-IHBT (Council of Scientific and Industrial Research- Institute Himalayan Bioresource Technology) and RHRS (Regional Horticultural Research Station) conditions. The spatial variability also exerted considerable effect on the leaf yield and stevioside content in leaves. Among the three locations, CSIR-IHBT was found most suitable in case of dry leaf yield and secondary metabolites accumulation in leaves. The results suggest that dry leaf yield and accumulation of stevioside are controlled by the environmental factors and agronomic management; however, the accumulation of rebaudioside-A (Reb-A) is not much influenced by these two factors. Thus, leaf yield and secondary metabolite profiles of stevia can be improved through the selection of appropriate growing locations and proper nutrient management.
Energy Technology Data Exchange (ETDEWEB)
Fedorov, Alexey V. [Yale Univ., New Haven, CT (United States)
2015-01-14
The central goal of this research project was to understand the mechanisms of decadal and multi-decadal variability of the Atlantic Meridional Overturning Circulation (AMOC) as related to climate variability and abrupt climate change within a hierarchy of climate models ranging from realistic ocean models to comprehensive Earth system models. Generalized Stability Analysis, a method that quantifies the transient and asymptotic growth of perturbations in the system, is one of the main approaches used throughout this project. The topics we have explored range from physical mechanisms that control AMOC variability to the factors that determine AMOC predictability in the Earth system models, to the stability and variability of the AMOC in past climates.
Estimation and variable selection for generalized additive partial linear models
Wang, Li
2011-08-01
We study generalized additive partial linear models, proposing the use of polynomial spline smoothing for estimation of nonparametric functions, and deriving quasi-likelihood based estimators for the linear parameters. We establish asymptotic normality for the estimators of the parametric components. The procedure avoids solving large systems of equations as in kernel-based procedures and thus results in gains in computational simplicity. We further develop a class of variable selection procedures for the linear parameters by employing a nonconcave penalized quasi-likelihood, which is shown to have an asymptotic oracle property. Monte Carlo simulations and an empirical example are presented for illustration. © Institute of Mathematical Statistics, 2011.
Context Tree Estimation in Variable Length Hidden Markov Models
Dumont, Thierry
2011-01-01
We address the issue of context tree estimation in variable length hidden Markov models. We propose an estimator of the context tree of the hidden Markov process which needs no prior upper bound on the depth of the context tree. We prove that the estimator is strongly consistent. This uses information-theoretic mixture inequalities in the spirit of Finesso and Lorenzo(Consistent estimation of the order for Markov and hidden Markov chains(1990)) and E.Gassiat and S.Boucheron (Optimal error exp...
Remote sensing of the Canadian Arctic: Modelling biophysical variables
Liu, Nanfeng
It is anticipated that Arctic vegetation will respond in a variety of ways to altered temperature and precipitation patterns expected with climate change, including changes in phenology, productivity, biomass, cover and net ecosystem exchange. Remote sensing provides data and data processing methodologies for monitoring and assessing Arctic vegetation over large areas. The goal of this research was to explore the potential of hyperspectral and high spatial resolution multispectral remote sensing data for modelling two important Arctic biophysical variables: Percent Vegetation Cover (PVC) and the fraction of Absorbed Photosynthetically Active Radiation (fAPAR). A series of field experiments were conducted to collect PVC and fAPAR at three Canadian Arctic sites: (1) Sabine Peninsula, Melville Island, NU; (2) Cape Bounty Arctic Watershed Observatory (CBAWO), Melville Island, NU; and (3) Apex River Watershed (ARW), Baffin Island, NU. Linear relationships between biophysical variables and Vegetation Indices (VIs) were examined at different spatial scales using field spectra (for the Sabine Peninsula site) and high spatial resolution satellite data (for the CBAWO and ARW sites). At the Sabine Peninsula site, hyperspectral VIs exhibited a better performance for modelling PVC than multispectral VIs due to their capacity for sampling fine spectral features. The optimal hyperspectral bands were located at important spectral features observed in Arctic vegetation spectra, including leaf pigment absorption in the red wavelengths and at the red-edge, leaf water absorption in the near infrared, and leaf cellulose and lignin absorption in the shortwave infrared. At the CBAWO and ARW sites, field PVC and fAPAR exhibited strong correlations (R2 > 0.70) with the NDVI (Normalized Difference Vegetation Index) derived from high-resolution WorldView-2 data. Similarly, high spatial resolution satellite-derived fAPAR was correlated to MODIS fAPAR (R2 = 0.68), with a systematic
Classification criteria of syndromes by latent variable models
DEFF Research Database (Denmark)
Petersen, Janne
2010-01-01
, although this is often desired. I have proposed a new method for predicting class membership that, in contrast to methods based on posterior probabilities of class membership, yields consistent estimates when regressed on explanatory variables in a subsequent analysis. There are four different basic models...... analyses. Part 1: HALS engages different phenotypic changes of peripheral lipoatrophy and central lipohypertrophy. There are several different definitions of HALS and no consensus on the number of phenotypes. Many of the definitions consist of counting fulfilled criteria on markers and do not include...
Modeling intraindividual variability with repeated measures data methods and applications
Hershberger, Scott L
2013-01-01
This book examines how individuals behave across time and to what degree that behavior changes, fluctuates, or remains stable.It features the most current methods on modeling repeated measures data as reported by a distinguished group of experts in the field. The goal is to make the latest techniques used to assess intraindividual variability accessible to a wide range of researchers. Each chapter is written in a ""user-friendly"" style such that even the ""novice"" data analyst can easily apply the techniques.Each chapter features:a minimum discussion of mathematical detail;an empirical examp
Variable recruitment fluidic artificial muscles: modeling and experiments
International Nuclear Information System (INIS)
Bryant, Matthew; Meller, Michael A; Garcia, Ephrahim
2014-01-01
We investigate taking advantage of the lightweight, compliant nature of fluidic artificial muscles to create variable recruitment actuators in the form of artificial muscle bundles. Several actuator elements at different diameter scales are packaged to act as a single actuator device. The actuator elements of the bundle can be connected to the fluidic control circuit so that different groups of actuator elements, much like individual muscle fibers, can be activated independently depending on the required force output and motion. This novel actuation concept allows us to save energy by effectively impedance matching the active size of the actuators on the fly based on the instantaneous required load. This design also allows a single bundled actuator to operate in substantially different force regimes, which could be valuable for robots that need to perform a wide variety of tasks and interact safely with humans. This paper proposes, models and analyzes the actuation efficiency of this actuator concept. The analysis shows that variable recruitment operation can create an actuator that reduces throttling valve losses to operate more efficiently over a broader range of its force–strain operating space. We also present preliminary results of the design, fabrication and experimental characterization of three such bioinspired variable recruitment actuator prototypes. (paper)
Quantifying uncertainty, variability and likelihood for ordinary differential equation models
LENUS (Irish Health Repository)
Weisse, Andrea Y
2010-10-28
Abstract Background In many applications, ordinary differential equation (ODE) models are subject to uncertainty or variability in initial conditions and parameters. Both, uncertainty and variability can be quantified in terms of a probability density function on the state and parameter space. Results The partial differential equation that describes the evolution of this probability density function has a form that is particularly amenable to application of the well-known method of characteristics. The value of the density at some point in time is directly accessible by the solution of the original ODE extended by a single extra dimension (for the value of the density). This leads to simple methods for studying uncertainty, variability and likelihood, with significant advantages over more traditional Monte Carlo and related approaches especially when studying regions with low probability. Conclusions While such approaches based on the method of characteristics are common practice in other disciplines, their advantages for the study of biological systems have so far remained unrecognized. Several examples illustrate performance and accuracy of the approach and its limitations.
Uncertainty importance measure for models with correlated normal variables
International Nuclear Information System (INIS)
Hao, Wenrui; Lu, Zhenzhou; Wei, Pengfei
2013-01-01
In order to explore the contributions by correlated input variables to the variance of the model output, the contribution decomposition of the correlated input variables based on Mara's definition is investigated in detail. By taking the quadratic polynomial output without cross term as an illustration, the solution of the contribution decomposition is derived analytically using the statistical inference theory. After the correction of the analytical solution is validated by the numerical examples, they are employed to two engineering examples to show their wide application. The derived analytical solutions can directly be used to recognize the contributions by the correlated input variables in case of the quadratic or linear polynomial output without cross term, and the analytical inference method can be extended to the case of higher order polynomial output. Additionally, the origins of the interaction contribution of the correlated inputs are analyzed, and the comparisons of the existing contribution indices are completed, on which the engineer can select the suitable indices to know the necessary information. At last, the degeneration of the correlated inputs to the uncorrelated ones and some computational issues are discussed in concept
Graphene growth process modeling: a physical-statistical approach
Wu, Jian; Huang, Qiang
2014-09-01
As a zero-band semiconductor, graphene is an attractive material for a wide variety of applications such as optoelectronics. Among various techniques developed for graphene synthesis, chemical vapor deposition on copper foils shows high potential for producing few-layer and large-area graphene. Since fabrication of high-quality graphene sheets requires the understanding of growth mechanisms, and methods of characterization and control of grain size of graphene flakes, analytical modeling of graphene growth process is therefore essential for controlled fabrication. The graphene growth process starts with randomly nucleated islands that gradually develop into complex shapes, grow in size, and eventually connect together to cover the copper foil. To model this complex process, we develop a physical-statistical approach under the assumption of self-similarity during graphene growth. The growth kinetics is uncovered by separating island shapes from area growth rate. We propose to characterize the area growth velocity using a confined exponential model, which not only has clear physical explanation, but also fits the real data well. For the shape modeling, we develop a parametric shape model which can be well explained by the angular-dependent growth rate. This work can provide useful information for the control and optimization of graphene growth process on Cu foil.
DEFF Research Database (Denmark)
Høst-Madsen, Anders; Shah, Peter Jivan; Hansen, Torben
1987-01-01
Computer-simulation techniques are used to study the domain-growth kinetics of (2×1) ordering in a two-dimensional Ising model with nonconserved order parameter and with variable ratio α of next-nearest- and nearest-neighbor interactions. At zero temperature, persistent growth characterized...
Mechanical model for filament buckling and growth by phase ordering.
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.
Modeling and optimization of algae growth
Thornton, Anthony Richard; Weinhart, Thomas; Bokhove, Onno; Zhang, Bowen; van der Sar, Dick M.; Kumar, Kundan; Pisarenco, Maxim; Rudnaya, Maria; Savcenco, Valeriu; Rademacher, Jens; Zijlstra, Julia; Szabelska, Alicja; Zyprych, Joanna; van der Schans, Martin; Timperio, Vincent; Veerman, Frits
2010-01-01
The wastewater from greenhouses has a high amount of mineral contamination and an environmentally-friendly method of removal is to use algae to clean this runoff water. The algae consume the minerals as part of their growth process. In addition to cleaning the water, the created algal bio-mass has a
Viscous dark energy models with variable G and Λ
International Nuclear Information System (INIS)
Arbab, Arbab I.
2008-01-01
We consider a cosmological model with bulk viscosity η and variable cosmological A ∝ ρ -α , alpha = const and gravitational G constants. The model exhibits many interesting cosmological features. Inflation proceeds due to the presence of bulk viscosity and dark energy without requiring the equation of state p=-ρ. During the inflationary era the energy density ρ does not remain constant, as in the de-Sitter type. Moreover, the cosmological and gravitational constants increase exponentially with time, whereas the energy density and viscosity decrease exponentially with time. The rate of mass creation during inflation is found to be very huge suggesting that all matter in the universe is created during inflation. (author)
Age structure and capital dilution effects in neo-classical growth models.
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.
Wibowo, Wahyu; Wene, Chatrien; Budiantara, I. Nyoman; Permatasari, Erma Oktania
2017-03-01
Multiresponse semiparametric regression is simultaneous equation regression model and fusion of parametric and nonparametric model. The regression model comprise several models and each model has two components, parametric and nonparametric. The used model has linear function as parametric and polynomial truncated spline as nonparametric component. The model can handle both linearity and nonlinearity relationship between response and the sets of predictor variables. The aim of this paper is to demonstrate the application of the regression model for modeling of effect of regional socio-economic on use of information technology. More specific, the response variables are percentage of households has access to internet and percentage of households has personal computer. Then, predictor variables are percentage of literacy people, percentage of electrification and percentage of economic growth. Based on identification of the relationship between response and predictor variable, economic growth is treated as nonparametric predictor and the others are parametric predictors. The result shows that the multiresponse semiparametric regression can be applied well as indicate by the high coefficient determination, 90 percent.
Constrained variability of modeled T:ET ratio across biomes
Fatichi, Simone; Pappas, Christoforos
2017-07-01
A large variability (35-90%) in the ratio of transpiration to total evapotranspiration (referred here as T:ET) across biomes or even at the global scale has been documented by a number of studies carried out with different methodologies. Previous empirical results also suggest that T:ET does not covary with mean precipitation and has a positive dependence on leaf area index (LAI). Here we use a mechanistic ecohydrological model, with a refined process-based description of evaporation from the soil surface, to investigate the variability of T:ET across biomes. Numerical results reveal a more constrained range and higher mean of T:ET (70 ± 9%, mean ± standard deviation) when compared to observation-based estimates. T:ET is confirmed to be independent from mean precipitation, while it is found to be correlated with LAI seasonally but uncorrelated across multiple sites. Larger LAI increases evaporation from interception but diminishes ground evaporation with the two effects largely compensating each other. These results offer mechanistic model-based evidence to the ongoing research about the patterns of T:ET and the factors influencing its magnitude across biomes.
Stochastic Individual-Based Modeling of Bacterial Growth and Division Using Flow Cytometry
Directory of Open Access Journals (Sweden)
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.
Multi-scale climate modelling over Southern Africa using a variable-resolution global model
CSIR Research Space (South Africa)
Engelbrecht, FA
2011-12-01
Full Text Available -mail: fengelbrecht@csir.co.za Multi-scale climate modelling over Southern Africa using a variable-resolution global model FA Engelbrecht1, 2*, WA Landman1, 3, CJ Engelbrecht4, S Landman5, MM Bopape1, B Roux6, JL McGregor7 and M Thatcher7 1 CSIR Natural... improvement. Keywords: multi-scale climate modelling, variable-resolution atmospheric model Introduction Dynamic climate models have become the primary tools for the projection of future climate change, at both the global and regional scales. Dynamic...
Optimal Patent Life in a Variety-Expansion Growth Model
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...
Transient modelling of a natural circulation loop under variable pressure
International Nuclear Information System (INIS)
Vianna, Andre L.B.; Faccini, Jose L.H.; Su, Jian; Instituto de Engenharia Nuclear
2017-01-01
The objective of the present work is to model the transient operation of a natural circulation loop, which is one-tenth scale in height to a typical Passive Residual Heat Removal system (PRHR) of an Advanced Pressurized Water Nuclear Reactor and was designed to meet the single and two-phase flow similarity criteria to it. The loop consists of a core barrel with electrically heated rods, upper and lower plena interconnected by hot and cold pipe legs to a seven-tube shell heat exchanger of countercurrent design, and an expansion tank with a descending tube. A long transient characterized the loop operation, during which a phenomenon of self-pressurization, without self-regulation of the pressure, was experimentally observed. This represented a unique situation, named natural circulation under variable pressure (NCVP). The self-pressurization was originated in the air trapped in the expansion tank and compressed by the loop water dilatation, as it heated up during each experiment. The mathematical model, initially oriented to the single-phase flow, included the heat capacity of the structure and employed a cubic polynomial approximation for the density, in the buoyancy term calculation. The heater was modelled taking into account the different heat capacities of the heating elements and the heater walls. The heat exchanger was modelled considering the coolant heating, during the heat exchanging process. The self-pressurization was modelled as an isentropic compression of a perfect gas. The whole model was computationally implemented via a set of finite difference equations. The corresponding computational algorithm of solution was of the explicit, marching type, as for the time discretization, in an upwind scheme, regarding the space discretization. The computational program was implemented in MATLAB. Several experiments were carried out in the natural circulation loop, having the coolant flow rate and the heating power as control parameters. The variables used in the
Transient modelling of a natural circulation loop under variable pressure
Energy Technology Data Exchange (ETDEWEB)
Vianna, Andre L.B.; Faccini, Jose L.H.; Su, Jian, E-mail: avianna@nuclear.ufrj.br, E-mail: sujian@nuclear.ufrj.br, E-mail: faccini@ien.gov.br [Coordenacao de Pos-Graduacao e Pesquisa de Engenharia (COPPE/UFRJ), Rio de Janeiro, RJ (Brazil). Programa de Engenharia Nuclear; Instituto de Engenharia Nuclear (IEN/CNEN-RJ), Rio de Janeiro, RJ (Brazil). Lab. de Termo-Hidraulica Experimental
2017-07-01
The objective of the present work is to model the transient operation of a natural circulation loop, which is one-tenth scale in height to a typical Passive Residual Heat Removal system (PRHR) of an Advanced Pressurized Water Nuclear Reactor and was designed to meet the single and two-phase flow similarity criteria to it. The loop consists of a core barrel with electrically heated rods, upper and lower plena interconnected by hot and cold pipe legs to a seven-tube shell heat exchanger of countercurrent design, and an expansion tank with a descending tube. A long transient characterized the loop operation, during which a phenomenon of self-pressurization, without self-regulation of the pressure, was experimentally observed. This represented a unique situation, named natural circulation under variable pressure (NCVP). The self-pressurization was originated in the air trapped in the expansion tank and compressed by the loop water dilatation, as it heated up during each experiment. The mathematical model, initially oriented to the single-phase flow, included the heat capacity of the structure and employed a cubic polynomial approximation for the density, in the buoyancy term calculation. The heater was modelled taking into account the different heat capacities of the heating elements and the heater walls. The heat exchanger was modelled considering the coolant heating, during the heat exchanging process. The self-pressurization was modelled as an isentropic compression of a perfect gas. The whole model was computationally implemented via a set of finite difference equations. The corresponding computational algorithm of solution was of the explicit, marching type, as for the time discretization, in an upwind scheme, regarding the space discretization. The computational program was implemented in MATLAB. Several experiments were carried out in the natural circulation loop, having the coolant flow rate and the heating power as control parameters. The variables used in the
Modeling of Craniofacial Anatomy, Variation, and Growth
DEFF Research Database (Denmark)
Thorup, Signe Strann
The topic of this thesis is automatic analysis of craniofacial images with respect to changes due to growth and surgery, inter-subject variation and intracranial volume estimation. The methods proposed contribute to the knowledge about specific craniofacial anomalies, as well as provide a tool...... for detailed analyses for clinical and research purposes. Most of the applications in this thesis rely on non-rigid image registration by the means of warping one image into the coordinate system of another image. This warping results in a deformation field that describes the anatomical correspondence between......, thus creating a personalized atlas. The knowledge built into the atlas is e.g. location of anatomical regions and landmarks of importance to surgery planning and evaluation or population studies. With these correspondences, various analyses could be carried out e.g. quantification of growth, inter...
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...
Modelling the Growth of Swine Flu
Thomson, Ian
2010-01-01
The spread of swine flu has been a cause of great concern globally. With no vaccine developed as yet, (at time of writing in July 2009) and given the fact that modern-day humans can travel speedily across the world, there are fears that this disease may spread out of control. The worst-case scenario would be one of unfettered exponential growth.…
International Nuclear Information System (INIS)
Paraventi, D.J.; Moshier, W.C.
2007-01-01
SCC testing of Alloy 600 and its weld metals has demonstrated that temperature, stress intensity factor (K), dissolved hydrogen, and yield strength all play a role on crack growth in deaerated, hydrogenated water. Typically, each variable has been modeled independently. However, some of these variables interact, which can affect crack growth predictions. In particular, testing has demonstrated several important interactions, including final annealing temperature and K, cold work and dissolved hydrogen, and orientation and cold work. The annealing temperature influences the K dependence of Alloy 600, with lower temperature anneals decreasing the influence of stress on growth. The response to cold work varies as a function of processing method and orientation, with crack growth in the processing direction having a stronger yield strength dependence than crack growth perpendicular to the processing direction. The effect of hydrogen has been found to be related to electrochemical potential, with the most susceptible condition occurring near the Ni/NiO phase transition. However, cold worked Alloy 600 maintains the peak susceptibility at low hydrogen conditions. (author)
Directory of Open Access Journals (Sweden)
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.
Applied model for the growth of the daytime mixed layer
DEFF Research Database (Denmark)
Batchvarova, E.; Gryning, Sven-Erik
1991-01-01
numerically. When the mixed layer is shallow or the atmosphere nearly neutrally stratified, the growth is controlled mainly by mechanical turbulence. When the layer is deep, its growth is controlled mainly by convective turbulence. The model is applied on a data set of the evolution of the height of the mixed...... layer in the morning hours, when both mechanical and convective turbulence contribute to the growth process. Realistic mixed-layer developments are obtained....
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...
Goshe, Lisa R.; Coggins, Lewis; Shaver, Donna J.; Higgins, Ben; Landry, Andre M.; Bailey, Rhonda
2017-01-01
Effective management of protected sea turtle populations requires knowledge not only of mean values for demographic and life-history parameters, but also temporal and spatial trends, variability, and underlying causes. For endangered Kemp’s ridley sea turtles (Lepidochelys kempii), the need for baseline information of this type has been emphasized during attempts to understand causes underlying the recent truncation in the recovery trajectory for nesting females. To provide insight into variability in age and size at sexual maturation (ASM and SSM) and long-term growth patterns likely to influence population trends, we conducted skeletochronological analysis of humerus bones from 333 Kemp’s ridleys stranded throughout the Gulf of Mexico (GOM) from 1993 to 2010. Ranges of possible ASMs (6.8 to 21.8 yr) and SSMs (53.3 to 68.3 cm straightline carapace length (SCL)) estimated using the “rapprochement” skeletal growth mark associated with maturation were broad, supporting incorporation of a maturation schedule in Kemp’s ridley population models. Mean ASMs estimated from rapprochement and by fitting logistic, generalized additive mixed, and von Bertalanffy growth models to age and growth data ranged from 11 to 13 yr; confidence intervals for the logistic model predicted maturation of 95% of the population between 11.9 and 14.8 yr. Early juvenile somatic growth rates in the GOM were greater than those previously reported for the Atlantic, indicating potential for differences in maturation trajectories between regions. Finally, long-term, significant decreases in somatic growth response were found for both juveniles and adults, which could influence recruitment to the reproductive population and observed nesting population trends. PMID:28333937
Directory of Open Access Journals (Sweden)
Larisa Avens
Full Text Available Effective management of protected sea turtle populations requires knowledge not only of mean values for demographic and life-history parameters, but also temporal and spatial trends, variability, and underlying causes. For endangered Kemp's ridley sea turtles (Lepidochelys kempii, the need for baseline information of this type has been emphasized during attempts to understand causes underlying the recent truncation in the recovery trajectory for nesting females. To provide insight into variability in age and size at sexual maturation (ASM and SSM and long-term growth patterns likely to influence population trends, we conducted skeletochronological analysis of humerus bones from 333 Kemp's ridleys stranded throughout the Gulf of Mexico (GOM from 1993 to 2010. Ranges of possible ASMs (6.8 to 21.8 yr and SSMs (53.3 to 68.3 cm straightline carapace length (SCL estimated using the "rapprochement" skeletal growth mark associated with maturation were broad, supporting incorporation of a maturation schedule in Kemp's ridley population models. Mean ASMs estimated from rapprochement and by fitting logistic, generalized additive mixed, and von Bertalanffy growth models to age and growth data ranged from 11 to 13 yr; confidence intervals for the logistic model predicted maturation of 95% of the population between 11.9 and 14.8 yr. Early juvenile somatic growth rates in the GOM were greater than those previously reported for the Atlantic, indicating potential for differences in maturation trajectories between regions. Finally, long-term, significant decreases in somatic growth response were found for both juveniles and adults, which could influence recruitment to the reproductive population and observed nesting population trends.
Phase-field model of eutectic growth
International Nuclear Information System (INIS)
Karma, A.
1994-01-01
A phase-field model which describes the solidification of a binary eutectic alloy with a simple symmetric phase diagram is introduced and the sharp-interface limit of this model is explored both analytically and numerically
Balanced growth path solutions of a Boltzmann mean field game model for knowledge growth
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.
A smart growth evaluation model based on data envelopment analysis
Zhang, Xiaokun; Guan, Yongyi
2018-04-01
With the rapid spread of urbanization, smart growth (SG) has attracted plenty of attention from all over the world. In this paper, by the establishment of index system for smart growth, data envelopment analysis (DEA) model was suggested to evaluate the SG level of the current growth situation in cities. In order to further improve the information of both radial direction and non-radial detection, we introduced the non-Archimedean infinitesimal to form C2GS2 control model. Finally, we evaluated the SG level in Canberra and identified a series of problems, which can verify the applicability of the model and provide us more improvement information.
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.
On the explaining-away phenomenon in multivariate latent variable models.
van Rijn, Peter; Rijmen, Frank
2015-02-01
Many probabilistic models for psychological and educational measurements contain latent variables. Well-known examples are factor analysis, item response theory, and latent class model families. We discuss what is referred to as the 'explaining-away' phenomenon in the context of such latent variable models. This phenomenon can occur when multiple latent variables are related to the same observed variable, and can elicit seemingly counterintuitive conditional dependencies between latent variables given observed variables. We illustrate the implications of explaining away for a number of well-known latent variable models by using both theoretical and real data examples. © 2014 The British Psychological Society.
Modeling growth from weaning to maturity in beef cattle breeds
To better understand growth trajectory and maturity differences between beef breeds, three models – Brody, spline, and quadratic – were fit to cow growth data, and resulting parameter estimates were evaluated for 3 breed categories – British, continental, and Brahman-influenced. The data were weight...
Modeling growth of Clostridium perfringens in pea soup during cooling
Jong, de A.E.I.; Beumer, R.R.; Zwietering, M.H.
2005-01-01
Clostridium perfringens is a pathogen that mainly causes food poisoning outbreaks when large quantities of food are prepared. Therefore, a model was developed to predict the effect of different cooling procedures on the growth of this pathogen during cooling of food: Dutch pea soup. First, a growth
Evaluating the Predictive Value of Growth Prediction Models
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…
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 Schumpeterian Model of Entrepreneurship, Innovation, and Regional Economic Growth
Batabyal, A.; Nijkamp, P.
2012-01-01
The authors provide the first theoretical analysis of a one-sector, discrete-time, Schumpeterian model of growth in a regional economy in which consumers are risk neutral, there is no population growth, monopolistic entrepreneurs produce intermediate goods, and a single consumption good is produced
A grain boundary sliding model for cavitation, crack growth and ...
African Journals Online (AJOL)
A model is presented for cavity growth, crack propagation and fracture resulting from grain boundary sliding (GBS) during high temperature creep deformation. The theory of cavity growth by GBS was based on energy balance criteria on the assumption that the matrix is sufficiently plastic to accommodate misfit strains ...
Effect of milk proteins on linear growth and IGF variables in overweight adolescents
DEFF Research Database (Denmark)
Larnkjær, Anni; Arnberg, Karina; Michaelsen, Kim F
2014-01-01
Milk may stimulate growth acting via insulin-like growth factor-I (IGF-I) secretion but the effect in adolescents is less examined. This study investigates the effect of milk proteins on linear growth, IGF-I, IGF binding protein-3 (IGFBP-3) and IGF-I/IGFBP-3 ratio in overweight adolescents....
Directory of Open Access Journals (Sweden)
Ruth Durán
2018-05-01
Full Text Available Clinoform depositional features along the Iberian Mediterranean margin are investigated in this study, with the aim of establishing the causes of their varied shapes and other characteristics. We have analyzed the broad-scale margin physiography and seismic stratigraphic patterns based on high-resolution bathymetric data and previously interpreted seismic data. In addition, we have evaluated regional supply conditions and the uplift-subsidence regime of the different shelf sectors. The upper Quaternary record is strongly dominated by shelf-margin regressive wedges affected by the prevailing 100 ka cyclicity. However, the margins exhibit considerable lateral variability, as the result of the balance between the amount of sediment supply and the uplift-subsidence relationship. Three major shelf sectors with distinct morpho-sedimentary features have been defined. The relatively narrow northern shelves (Roses, La Planassa and Barcelona are supplied by discrete river outlets that collectively constitute a linear source and are mainly affected by tectonic tilting. The wide middle shelves (Ebro Shelf, the Gulf of Valencia, and the Northern Arc receive the sediment supply from the large Ebro River and other medium rivers. Although the tectonic regime changes laterally (strong subsidence in the north and uplift in the south, shelf growth is maintained by lateral advection of sediments. The southern shelves (the Southern Arc and the northern Alboran Shelf are very abrupt and narrow because of the uplifting Betic Cordillera, and the torrential fluvial regimes that determine a very efficient sediment by-pass toward the deep basin. Submarine canyons deeply incised in the continental margin constitute a key physiographic feature that may enhance the transport of sediment to the deep sea or individualize shelf sectors with specific sedimentation patterns, as occurs in the Catalan margin.
Total Variability Modeling using Source-specific Priors
DEFF Research Database (Denmark)
Shepstone, Sven Ewan; Lee, Kong Aik; Li, Haizhou
2016-01-01
sequence of an utterance. In both cases the prior for the latent variable is assumed to be non-informative, since for homogeneous datasets there is no gain in generality in using an informative prior. This work shows in the heterogeneous case, that using informative priors for com- puting the posterior......, can lead to favorable results. We focus on modeling the priors using minimum divergence criterion or fac- tor analysis techniques. Tests on the NIST 2008 and 2010 Speaker Recognition Evaluation (SRE) dataset show that our proposed method beats four baselines: For i-vector extraction using an already...... trained matrix, for the short2-short3 task in SRE’08, five out of eight female and four out of eight male common conditions, were improved. For the core-extended task in SRE’10, four out of nine female and six out of nine male common conditions were improved. When incorporating prior information...
A size-structured model of bacterial growth and reproduction.
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.
Selection, calibration, and validation of models of tumor growth.
Lima, E A B F; Oden, J T; Hormuth, D A; Yankeelov, T E; Almeida, R C
2016-11-01
This paper presents general approaches for addressing some of the most important issues in predictive computational oncology concerned with developing classes of predictive models of tumor growth. First, the process of developing mathematical models of vascular tumors evolving in the complex, heterogeneous, macroenvironment of living tissue; second, the selection of the most plausible models among these classes, given relevant observational data; third, the statistical calibration and validation of models in these classes, and finally, the prediction of key Quantities of Interest (QOIs) relevant to patient survival and the effect of various therapies. The most challenging aspects of this endeavor is that all of these issues often involve confounding uncertainties: in observational data, in model parameters, in model selection, and in the features targeted in the prediction. Our approach can be referred to as "model agnostic" in that no single model is advocated; rather, a general approach that explores powerful mixture-theory representations of tissue behavior while accounting for a range of relevant biological factors is presented, which leads to many potentially predictive models. Then representative classes are identified which provide a starting point for the implementation of OPAL, the Occam Plausibility Algorithm (OPAL) which enables the modeler to select the most plausible models (for given data) and to determine if the model is a valid tool for predicting tumor growth and morphology ( in vivo ). All of these approaches account for uncertainties in the model, the observational data, the model parameters, and the target QOI. We demonstrate these processes by comparing a list of models for tumor growth, including reaction-diffusion models, phase-fields models, and models with and without mechanical deformation effects, for glioma growth measured in murine experiments. Examples are provided that exhibit quite acceptable predictions of tumor growth in laboratory
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.
Fracture Mechanical Markov Chain Crack Growth Model
DEFF Research Database (Denmark)
Gansted, L.; Brincker, Rune; Hansen, Lars Pilegaard
1991-01-01
propagation process can be described by a discrete space Markov theory. The model is applicable to deterministic as well as to random loading. Once the model parameters for a given material have been determined, the results can be used for any structure as soon as the geometrical function is known....
Jochner, Matthias; Bugmann, Harald; Nötzli, Magdalena; Bigler, Christof
2017-10-01
Upper treeline ecotones are important life form boundaries and particularly sensitive to a warming climate. Changes in growth conditions at these ecotones have wide-ranging implications for the provision of ecosystem services in densely populated mountain regions like the European Alps. We quantify climate effects on short- and long-term tree growth responses, focusing on among-tree variability and potential feedback effects. Although among-tree variability is thought to be substantial, it has not been considered systematically yet in studies on growth-climate relationships. We compiled tree-ring data including almost 600 trees of major treeline species ( Larix decidua , Picea abies , Pinus cembra , and Pinus mugo ) from three climate regions of the Swiss Alps. We further acquired tree size distribution data using unmanned aerial vehicles. To account for among-tree variability, we employed information-theoretic model selections based on linear mixed-effects models (LMMs) with flexible choice of monthly temperature effects on growth. We isolated long-term trends in ring-width indices (RWI) in interaction with elevation. The LMMs revealed substantial amounts of previously unquantified among-tree variability, indicating different strategies of single trees regarding when and to what extent to invest assimilates into growth. Furthermore, the LMMs indicated strongly positive temperature effects on growth during short summer periods across all species, and significant contributions of fall ( L. decidua ) and current year's spring ( L. decidua , P. abies ). In the longer term, all species showed consistently positive RWI trends at highest elevations, but different patterns with decreasing elevation. L. decidua exhibited even negative RWI trends compared to the highest treeline sites, whereas P. abies , P. cembra , and P. mugo showed steeper or flatter trends with decreasing elevation. This does not only reflect effects of ameliorated climate conditions on tree
A conjugate of an anti-midkine single-chain variable fragment to doxorubicin inhibits tumor growth
Energy Technology Data Exchange (ETDEWEB)
Zhao, Shuli [Immunology and Reproductive Biology Laboratory, Medical School & State Key Laboratory of Pharmaceutical Biotechnology, Nanjing University, Nanjing (China); Nanjing Affiliated First Hospital, Nanjing Medical University, Nanjing (China); Zhao, Guangfeng; Xie, Hao; Huang, Yahong [Immunology and Reproductive Biology Laboratory, Medical School & State Key Laboratory of Pharmaceutical Biotechnology, Nanjing University, Nanjing (China); Hou, Yayi [Immunology and Reproductive Biology Laboratory, Medical School & State Key Laboratory of Pharmaceutical Biotechnology, Nanjing University, Nanjing (China); Jiangsu Key Laboratory of Molecular Medicine, Nanjing University, Nanjing (China)
2012-01-27
Doxorubicin (DOX) was conjugated to a single-chain variable fragment (scFv) against human midkine (MK), and the conjugate (scFv-DOX) was used to target the chemotherapeutic agent to a mouse solid tumor model in which the tumor cells expressed high levels of human MK. The His-tagged recombinant scFv was expressed in bacteria, purified by metal affinity chromatography, and then conjugated to DOX using oxidative dextran (Dex) as a linker. The molecular formula of this immunoconjugate was scFv(Dex){sub 1.3}(DOX){sub 20}. In vitro apoptosis assays showed that the scFv-DOX conjugate was more cytotoxic against MK-transfected human adenocarcinoma cells (BGC823-MK) than untransfected cells (55.3 ± 2.4 vs 22.4 ± 3.8%) for three independent experiments. Nude mice bearing BGC823-MK solid tumors received scFv-DOX or equivalent doses of scFv + DOX for 2 weeks and tumor growth was more effectively inhibited by the scFv-DOX conjugate than by scFv + DOX (51.83% inhibition vs 40.81%). Histological analysis of the tumor tissues revealed that the highest levels of DOX accumulated in tumors from mice treated with scFv-DOX and this resulted in more extensive tumor cell death than in animals treated with the equivalent dose of scFv + DOX. These results show that the scFv-DOX conjugate effectively inhibited tumor growth in vivo and suggest that antigen-specific scFv may be competent drug-carriers.
A conjugate of an anti-midkine single-chain variable fragment to doxorubicin inhibits tumor growth
International Nuclear Information System (INIS)
Zhao, Shuli; Zhao, Guangfeng; Xie, Hao; Huang, Yahong; Hou, Yayi
2012-01-01
Doxorubicin (DOX) was conjugated to a single-chain variable fragment (scFv) against human midkine (MK), and the conjugate (scFv-DOX) was used to target the chemotherapeutic agent to a mouse solid tumor model in which the tumor cells expressed high levels of human MK. The His-tagged recombinant scFv was expressed in bacteria, purified by metal affinity chromatography, and then conjugated to DOX using oxidative dextran (Dex) as a linker. The molecular formula of this immunoconjugate was scFv(Dex) 1.3 (DOX) 20 . In vitro apoptosis assays showed that the scFv-DOX conjugate was more cytotoxic against MK-transfected human adenocarcinoma cells (BGC823-MK) than untransfected cells (55.3 ± 2.4 vs 22.4 ± 3.8%) for three independent experiments. Nude mice bearing BGC823-MK solid tumors received scFv-DOX or equivalent doses of scFv + DOX for 2 weeks and tumor growth was more effectively inhibited by the scFv-DOX conjugate than by scFv + DOX (51.83% inhibition vs 40.81%). Histological analysis of the tumor tissues revealed that the highest levels of DOX accumulated in tumors from mice treated with scFv-DOX and this resulted in more extensive tumor cell death than in animals treated with the equivalent dose of scFv + DOX. These results show that the scFv-DOX conjugate effectively inhibited tumor growth in vivo and suggest that antigen-specific scFv may be competent drug-carriers
Mediation Analysis in a Latent Growth Curve Modeling Framework
von Soest, Tilmann; Hagtvet, Knut A.
2011-01-01
This article presents several longitudinal mediation models in the framework of latent growth curve modeling and provides a detailed account of how such models can be constructed. Logical and statistical challenges that might arise when such analyses are conducted are also discussed. Specifically, we discuss how the initial status (intercept) and…
Growth models for Pinus patula in Angola | Delgado-Matas ...
African Journals Online (AJOL)
This study developed growth models for Pinus patula Schiede ex Schltdl. et Cham. for the Central Highlands of Angola for simulating the development of stand characteristics. The model set included dominant height, individual-tree diameter increment, individual-tree height and self-thinning models. The study was based ...
Directory of Open Access Journals (Sweden)
BUDIMAN
2012-01-01
Full Text Available Budiman, Arisoesilaningsih E. 2012. Predictive model of Amorphophallus muelleri growth in some agroforestry in East Java by multiple regression analysis. Biodiversitas 13: 18-22. The aims of this research was to determine the multiple regression models of vegetative and corm growth of Amorphophallus muelleri Blume in some age variations and habitat conditions of agroforestry in East Java. Descriptive exploratory research method was conducted by systematic random sampling at five agroforestries on four plantations in East Java: Saradan, Bojonegoro, Nganjuk and Blitar. In each agroforestry, we observed A. muelleri vegetative and corm growth on four growing age (1, 2, 3 and 4 years old respectively as well as environmental variables such as altitude, vegetation, climate and soil conditions. Data were analyzed using descriptive statistics to compare A. muelleri habitat in five agroforestries. Meanwhile, the influence and contribution of each environmental variable to the growth of A. muelleri vegetative and corm were determined using multiple regression analysis of SPSS 17.0. The multiple regression models of A. muelleri vegetative and corm growth were generated based on some characteristics of agroforestries and age showed high validity with R2 = 88-99%. Regression model showed that age, monthly temperatures, percentage of radiation and soil calcium (Ca content either simultaneously or partially determined the growth of A. muelleri vegetative and corm. Based on these models, the A. muelleri corm reached the optimal growth after four years of cultivation and they will be ready to be harvested. Additionally, the soil Ca content should reach 25.3 me.hg-1 as Sugihwaras agroforestry, with the maximal radiation of 60%.
Andries, Jan P M; Vander Heyden, Yvan; Buydens, Lutgarde M C
2017-08-22
The calibration performance of Partial Least Squares regression (PLS) can be improved by eliminating uninformative variables. For PLS, many variable elimination methods have been developed. One is the Uninformative-Variable Elimination for PLS (UVE-PLS). However, the number of variables retained by UVE-PLS is usually still large. In UVE-PLS, variable elimination is repeated as long as the root mean squared error of cross validation (RMSECV) is decreasing. The set of variables in this first local minimum is retained. In this paper, a modification of UVE-PLS is proposed and investigated, in which UVE is repeated until no further reduction in variables is possible, followed by a search for the global RMSECV minimum. The method is called Global-Minimum Error Uninformative-Variable Elimination for PLS, denoted as GME-UVE-PLS or simply GME-UVE. After each iteration, the predictive ability of the PLS model, built with the remaining variable set, is assessed by RMSECV. The variable set with the global RMSECV minimum is then finally selected. The goal is to obtain smaller sets of variables with similar or improved predictability than those from the classical UVE-PLS method. The performance of the GME-UVE-PLS method is investigated using four data sets, i.e. a simulated set, NIR and NMR spectra, and a theoretical molecular descriptors set, resulting in twelve profile-response (X-y) calibrations. The selective and predictive performances of the models resulting from GME-UVE-PLS are statistically compared to those from UVE-PLS and 1-step UVE, one-sided paired t-tests. The results demonstrate that variable reduction with the proposed GME-UVE-PLS method, usually eliminates significantly more variables than the classical UVE-PLS, while the predictive abilities of the resulting models are better. With GME-UVE-PLS, a lower number of uninformative variables, without a chemical meaning for the response, may be retained than with UVE-PLS. The selectivity of the classical UVE method
Liu, Bingxuan; Liu, Haiquan; Pan, Yingjie; Xie, Jing; Zhao, Yong
2016-01-01
Microbial growth variability plays an important role on food safety risk assessment. In this study, the growth kinetic characteristics corresponding to maximum specific growth rate (μmax) of 50 V. parahaemolyticus isolates from different sources and genotypes were evaluated at different temperatures (10, 20, 30, and 37°C) and salinity (0.5, 3, 5, 7, and 9%) using the automated turbidimetric system Bioscreen C. The results demonstrated that strain growth variability increased as the growth conditions became more stressful both in terms of temperature and salinity. The coefficient of variation (CV) of μmax for temperature was larger than that for salinity, indicating that the impact of temperature on strain growth variability was greater than that of salinity. The strains isolated from freshwater aquatic products had more conspicuous growth variations than those from seawater. Moreover, the strains with tlh (+) /tdh (+) /trh (-) exhibited higher growth variability than tlh (+) /tdh (-) /trh (-) or tlh (+) /tdh (-) /trh (+), revealing that gene heterogeneity might have possible relations with the growth variability. This research illustrates that the growth environments, strain sources as well as genotypes have impacts on strain growth variability of V. parahaemolyticus, which can be helpful for incorporating strain variability in predictive microbiology and microbial risk assessment.
A Novel Modelling Approach for Predicting Forest Growth and Yield under Climate Change.
Directory of Open Access Journals (Sweden)
M Irfan Ashraf
Full Text Available Global climate is changing due to increasing anthropogenic emissions of greenhouse gases. Forest managers need growth and yield models that can be used to predict future forest dynamics during the transition period of present-day forests under a changing climatic regime. In this study, we developed a forest growth and yield model that can be used to predict individual-tree growth under current and projected future climatic conditions. The model was constructed by integrating historical tree growth records with predictions from an ecological process-based model using neural networks. The new model predicts basal area (BA and volume growth for individual trees in pure or mixed species forests. For model development, tree-growth data under current climatic conditions were obtained using over 3000 permanent sample plots from the Province of Nova Scotia, Canada. Data to reflect tree growth under a changing climatic regime were projected with JABOWA-3 (an ecological process-based model. Model validation with designated data produced model efficiencies of 0.82 and 0.89 in predicting individual-tree BA and volume growth. Model efficiency is a relative index of model performance, where 1 indicates an ideal fit, while values lower than zero means the predictions are no better than the average of the observations. Overall mean prediction error (BIAS of basal area and volume growth predictions was nominal (i.e., for BA: -0.0177 cm(2 5-year(-1 and volume: 0.0008 m(3 5-year(-1. Model variability described by root mean squared error (RMSE in basal area prediction was 40.53 cm(2 5-year(-1 and 0.0393 m(3 5-year(-1 in volume prediction. The new modelling approach has potential to reduce uncertainties in growth and yield predictions under different climate change scenarios. This novel approach provides an avenue for forest managers to generate required information for the management of forests in transitional periods of climate change. Artificial intelligence
Modelling carbon and nitrogen turnover in variably saturated soils
Batlle-Aguilar, J.; Brovelli, A.; Porporato, A.; Barry, D. A.
2009-04-01
Natural ecosystems provide services such as ameliorating the impacts of deleterious human activities on both surface and groundwater. For example, several studies have shown that a healthy riparian ecosystem can reduce the nutrient loading of agricultural wastewater, thus protecting the receiving surface water body. As a result, in order to develop better protection strategies and/or restore natural conditions, there is a growing interest in understanding ecosystem functioning, including feedbacks and nonlinearities. Biogeochemical transformations in soils are heavily influenced by microbial decomposition of soil organic matter. Carbon and nutrient cycles are in turn strongly sensitive to environmental conditions, and primarily to soil moisture and temperature. These two physical variables affect the reaction rates of almost all soil biogeochemical transformations, including microbial and fungal activity, nutrient uptake and release from plants, etc. Soil water saturation and temperature are not constants, but vary both in space and time, thus further complicating the picture. In order to interpret field experiments and elucidate the different mechanisms taking place, numerical tools are beneficial. In this work we developed a 3D numerical reactive-transport model as an aid in the investigation the complex physical, chemical and biological interactions occurring in soils. The new code couples the USGS models (MODFLOW 2000-VSF, MT3DMS and PHREEQC) using an operator-splitting algorithm, and is a further development an existing reactive/density-dependent flow model PHWAT. The model was tested using simplified test cases. Following verification, a process-based biogeochemical reaction network describing the turnover of carbon and nitrogen in soils was implemented. Using this tool, we investigated the coupled effect of moisture content and temperature fluctuations on nitrogen and organic matter cycling in the riparian zone, in order to help understand the relative
Examples of EOS Variables as compared to the UMM-Var Data Model
Cantrell, Simon; Lynnes, Chris
2016-01-01
In effort to provide EOSDIS clients a way to discover and use variable data from different providers, a Unified Metadata Model for Variables is being created. This presentation gives an overview of the model and use cases we are handling.
Global terrestrial isoprene emission models: sensitivity to variability in climate and vegetation
Directory of Open Access Journals (Sweden)
A. Arneth
2011-08-01
Full Text Available Due to its effects on the atmospheric lifetime of methane, the burdens of tropospheric ozone and growth of secondary organic aerosol, isoprene is central among the biogenic compounds that need to be taken into account for assessment of anthropogenic air pollution-climate change interactions. Lack of process-understanding regarding leaf isoprene production as well as of suitable observations to constrain and evaluate regional or global simulation results add large uncertainties to past, present and future emissions estimates. Focusing on contemporary climate conditions, we compare three global isoprene models that differ in their representation of vegetation and isoprene emission algorithm. We specifically aim to investigate the between- and within model variation that is introduced by varying some of the models' main features, and to determine which spatial and/or temporal features are robust between models and different experimental set-ups. In their individual standard configurations, the models broadly agree with respect to the chief isoprene sources and emission seasonality, with maximum monthly emission rates around 20–25 Tg C, when averaged by 30-degree latitudinal bands. They also indicate relatively small (approximately 5 to 10 % around the mean interannual variability of total global emissions. The models are sensitive to changes in one or more of their main model components and drivers (e.g., underlying vegetation fields, climate input which can yield increases or decreases in total annual emissions of cumulatively by more than 30 %. Varying drivers also strongly alters the seasonal emission pattern. The variable response needs to be interpreted in view of the vegetation emission capacities, as well as diverging absolute and regional distribution of light, radiation and temperature, but the direction of the simulated emission changes was not as uniform as anticipated. Our results highlight the need for modellers to evaluate their
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.
Modeling truck traffic volume growth congestion.
2009-05-01
Modeling of the statewide transportation system is an important element in understanding issues and programming of funds to thwart potential congestion. As Alabama grows its manufacturing economy, the number of heavy vehicles traversing its highways ...
Unified models of interactions with gauge-invariant variables
International Nuclear Information System (INIS)
Zet, Gheorghe
2000-01-01
A model of gauge theory is formulated in terms of gauge-invariant variables over a 4-dimensional space-time. Namely, we define a metric tensor g μν ( μ , ν = 0,1,2,3) starting with the components F μν a and F μν a tilde of the tensor associated to the Yang-Mills fields and its dual: g μν = 1/(3Δ 1/3 ) (ε abc F μα a F αβ b tilde F βν c ). Here Δ is a scale factor which can be chosen of a convenient form so that the theory may be self-dual or not. The components g μν are interpreted as new gauge-invariant variables. The model is applied to the case when the gauge group is SU(2). For the space-time we choose two different manifolds: (i) the space-time is R x S 3 , where R is the real line and S 3 is the three-dimensional sphere; (ii) the space-time is endowed with axial symmetry. We calculate the components g μν of the new metric for the two cases in terms of SU(2) gauge potentials. Imposing the supplementary condition that the new metric coincides with the initial metric of the space-time, we obtain the field equations (of the first order in derivatives) for the gauge fields. In addition, we determine the scale factor Δ which is introduced in the definition of g μν to ensure the property of self-duality for our SU(2) gauge theory, namely, 1/(2√g)(ε αβστ g μα g νβ F στ a = F μν a , g = det (g μν ). In the case (i) we show that the space-time R x S 3 is not compatible with a self-dual SU(2) gauge theory, but in the case (ii) the condition of self-duality is satisfied. The model developed in our work can be considered as a possible way to unification of general relativity and Yang-Mills theories. This means that the gauge theory can be formulated in the close analogy with the general relativity, i.e. the Yang-Mills equations are equivalent to Einstein equations with the right-hand side of a simple form. (authors)
White dwarf models of supernovae and cataclysmic variables
International Nuclear Information System (INIS)
Nomoto, K.; Hashimoto, M.
1986-01-01
If the accreting white dwarf increases its mass to the Chandrasekhar mass, it will either explode as a Type I supernova or collapse to form a neutron star. In fact, there is a good agreement between the exploding white dwarf model for Type I supernovae and observations. We describe various types of evolution of accreting white dwarfs as a function of binary parameters (i.e,. composition, mass, and age of the white dwarf, its companion star, and mass accretion rate), and discuss the conditions for the precursors of exploding or collapsing white dwarfs, and their relevance to cataclysmic variables. Particular attention is given to helium star cataclysmics which might be the precursors of some Type I supernovae or ultrashort period x-ray binaries. Finally we present new evolutionary calculations using the updated nuclear reaction rates for the formation of O+Ne+Mg white dwarfs, and discuss the composition structure and their relevance to the model for neon novae. 61 refs., 14 figs
Multidecadal Variability in Surface Albedo Feedback Across CMIP5 Models
Schneider, Adam; Flanner, Mark; Perket, Justin
2018-02-01
Previous studies quantify surface albedo feedback (SAF) in climate change, but few assess its variability on decadal time scales. Using the Coupled Model Intercomparison Project Version 5 (CMIP5) multimodel ensemble data set, we calculate time evolving SAF in multiple decades from surface albedo and temperature linear regressions. Results are meaningful when temperature change exceeds 0.5 K. Decadal-scale SAF is strongly correlated with century-scale SAF during the 21st century. Throughout the 21st century, multimodel ensemble mean SAF increases from 0.37 to 0.42 W m-2 K-1. These results suggest that models' mean decadal-scale SAFs are good estimates of their century-scale SAFs if there is at least 0.5 K temperature change. Persistent SAF into the late 21st century indicates ongoing capacity for Arctic albedo decline despite there being less sea ice. If the CMIP5 multimodel ensemble results are representative of the Earth, we cannot expect decreasing Arctic sea ice extent to suppress SAF in the 21st century.
Directory of Open Access Journals (Sweden)
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.
Djerrad, Zineb; Djouahri, Abderrahmane; Kadik, Leila
2017-04-01
The impact of growth stages during vegetative cycle (B 0 - B 5 ) on chemical composition and antioxidant activities of Pinus halepensis Mill. needles essential oils was investigated for the first time. GC and GC/MS analyses pointed to a quantitative variability of components; terpene hydrocarbons derivatives, represented by α-pinene (8.5 - 12.9%), myrcene (17.5 - 21.6%), p-cymene (7.9 - 11.9%) and (Z)-β-caryophyllene (17.3 - 21.2%) as major components, decreased from 88.9% at B 0 growth stage to 66.9% at B 5 growth stage, whereas oxygenated derivatives, represented by caryophyllene oxide (5.4 - 12.6%) and terpinen-4-ol (0.4 - 3.3%) as major components, increased from 7% at B 0 growth stage to 28.4% at B 5 growth stage. Furthermore, our findings showed that essential oil of P. halepensis needles collected at B 5 growth stage possess higher antioxidant activities by four different testing systems than those collected at B 0 - B 4 growth stages. This highlighted variability led to conclude that we should select essential oils to be investigated carefully depending on growth stage, in order to have the highest effectiveness of essential oil in terms of biological activities for human health purposes. © 2017 Wiley-VHCA AG, Zurich, Switzerland.
Quadratic tracer dynamical models tobacco growth
International Nuclear Information System (INIS)
Qiang Jiyi; Hua Cuncai; Wang Shaohua
2011-01-01
In order to study the non-uniformly transferring process of some tracer dosages, we assume that the absorption of some tracer by tobacco is a quadratic function of the tracer quantity of the tracer in the case of fast absorption, whereas the exclusion of the tracer from tobacco is a linear function of the tracer quantity in the case of slow exclusion, after the tracer is introduced into tobacco once at zero time. A single-compartment quadratic dynamical model of Logistic type is established for the leaves of tobacco. Then, a two-compartment quadratic dynamical model is established for leaves and calms of the tobacco. Qualitative analysis of the models shows that the tracer applied to the leaves of the tobacco is excluded finally; however, the tracer stays at the tobacco for finite time. Two methods are also given for computing the parameters in the models. Finally, the results of the models are verified by the 32 P experiment for the absorption of tobacco. (authors)
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.)
Directory of Open Access Journals (Sweden)
Elvis Felipe Elli
2015-12-01
Full Text Available ABSTRACT The objective of this study was to evaluate the effect of growth reducer and nitrogen fertilization on morphological variables, SPAD index, radiation interception, and grain yield of three cultivars of wheat. The experimental design was a randomized block in factorial scheme 3x5x2, with three cultivars (Mestre, Iguaçú and Itaipú, five nitrogen doses (0, 40, 80, 120, 160 Kg ha-1, and application or no application of a growth reducer, with three replications. The following characteristics were evaluated: plant height, SPAD index, leaf area index (LAI, Global Radiation Interception (GRI and grain yield. The Tukey test (p < 0.05 was used for the comparison between the means of cultivar and growth reducer factors, and for a regression analysis to evaluate N levels. Increasing the dose of nitrogen promotes an increase in LAI of plants of wheat crops differently among cultivars, which leads to a greater degree of global radiation interception. At doses higher or equal to 120 Kg ha-1 of nitrogen, there are significant differences in grain yield between treatments with and without the application of the growth reducer. The significant interaction between growth reducer and nitrogen dose, showed that applications of growth reducer increase the GRI at doses above and below 80 Kg ha-1 of nitrogen. Nitrogen rates of 138 and 109 Kg ha-1 are responsible for maximum grain yields of wheat, which is 4235 and 3787 Kg ha-1 with and without the use of growth reducer, respectively.
Modeling and Simulation of Variable Mass, Flexible Structures
Tobbe, Patrick A.; Matras, Alex L.; Wilson, Heath E.
2009-01-01
The advent of the new Ares I launch vehicle has highlighted the need for advanced dynamic analysis tools for variable mass, flexible structures. This system is composed of interconnected flexible stages or components undergoing rapid mass depletion through the consumption of solid or liquid propellant. In addition to large rigid body configuration changes, the system simultaneously experiences elastic deformations. In most applications, the elastic deformations are compatible with linear strain-displacement relationships and are typically modeled using the assumed modes technique. The deformation of the system is approximated through the linear combination of the products of spatial shape functions and generalized time coordinates. Spatial shape functions are traditionally composed of normal mode shapes of the system or even constraint modes and static deformations derived from finite element models of the system. Equations of motion for systems undergoing coupled large rigid body motion and elastic deformation have previously been derived through a number of techniques [1]. However, in these derivations, the mode shapes or spatial shape functions of the system components were considered constant. But with the Ares I vehicle, the structural characteristics of the system are changing with the mass of the system. Previous approaches to solving this problem involve periodic updates to the spatial shape functions or interpolation between shape functions based on system mass or elapsed mission time. These solutions often introduce misleading or even unstable numerical transients into the system. Plus, interpolation on a shape function is not intuitive. This paper presents an approach in which the shape functions are held constant and operate on the changing mass and stiffness matrices of the vehicle components. Each vehicle stage or component finite element model is broken into dry structure and propellant models. A library of propellant models is used to describe the
Benchmark data set for wheat growth models
DEFF Research Database (Denmark)
Asseng, S; Ewert, F.; Martre, P
2015-01-01
The data set includes a current representative management treatment from detailed, quality-tested sentinel field experiments with wheat from four contrasting environments including Australia, The Netherlands, India and Argentina. Measurements include local daily climate data (solar radiation, max...... analysis with 26 models and 30 years (1981-2010) for each location, for elevated atmospheric CO2 and temperature changes, a heat stress sensitivity analysis at anthesis, and a sensitivity analysis with soil and crop management variations and a Global Climate Model end-century scenario....
A mathematical model of microalgae growth in cylindrical photobioreactor
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.
Modelling breast cancer tumour growth for a stable disease population.
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.
A mathematical model of the growth of uterine myomas.
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.
Non-linear Growth Models in Mplus and SAS
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
Small Business Training Models for Community Growth.
Jellison, Holly M., Ed.
Nine successful community college programs for small business management training are described in this report in terms of their college and economic context, purpose, offerings, delivery modes, operating and marketing strategies, community outreach, support services, faculty and staff, evaluation, and future directions. The model programs are…
Variability in growth of Vachellia nilotica provenances tested in the Sudano-Sahelian zone of Niger
DEFF Research Database (Denmark)
Larwanou, Mahamane; Issa, Rabiou; Saadou, Mahamane
2014-01-01
A provenance trial of Vachellia nilotica (Acacia nilotica) was conducted in Niger in order to assess variability in growth among 10 provenances from Africa (subsp. adstringens from Niger, Senegal and Cameroun) and outside the continent (subsp. indica from Pakistan and Yemen). Tree height, diameter...... at breast height and crown diameter were measured 15 years after trial establishment. Comparison of blocks located at slightly different elevation showed that trees had better survival and growth at the lower sites. The African provenances had better survival and total basal area than provenances from Yemen...
Elvis Felipe Elli; Braulio Otomar Caron; Sandro Luis Petter Medeiros; Elder Eloy; Gean Charles Monteiro; Denise Schmidt
2015-01-01
ABSTRACT The objective of this study was to evaluate the effect of growth reducer and nitrogen fertilization on morphological variables, SPAD index, radiation interception, and grain yield of three cultivars of wheat. The experimental design was a randomized block in factorial scheme 3x5x2, with three cultivars (Mestre, Iguaçú and Itaipú), five nitrogen doses (0, 40, 80, 120, 160 Kg ha-1), and application or no application of a growth reducer, with three replications. The following characteri...
Patterns of tree growth in relation to environmental variability in the ...
Indian Academy of Sciences (India)
Tree diameter growth is sensitive to environmental fluctuations and tropical dry forests experience high seasonal and inter-annual environmental variation. Tree growth rates in a large permanent plot at Mudumalai, southern India, were examined for the influences of rainfall and three intrinsic factors (size, species and ...
Hanson, Janet; Bangert, Arthur; Ruff, William
2016-01-01
According to school growth mindset theory a school's organizational structure influences teachers' beliefs in their collective ability to help all students grow and learn; including those from diverse cultural, religious, identity, and socioeconomic demographics. The implicit theory of growth mindset has been quantified for a school's culture on…
Reserve growth in oil pools of Alberta : model and forecast
Energy Technology Data Exchange (ETDEWEB)
Verma, M.; Cook, T. [United States Geological Survey, Denver, CO (United States). Central Region
2010-09-15
This paper presented a reserve growth study that was conducted on oil pools in Alberta, Canada. Historical oil reserve data were evaluated to assess the potential for future reserve growth in both pools and fields, and reserve growth models and functions were developed to better forecast hydrocarbon volumes. The study also considered the sensitivity of reserve growth to such factors as pool size, porosity, and oil gravity. From 1960 to 2005, the reported known recoverable oil in Alberta, excluding the Athabasca oil sands and including only pools with adequate data, increased from 4.2 to 13.9 billion barrels of oil (BBO). New discoveries contributed 3.7 BBO and reserve growth added 6 BBO. Most reserve growth occurred in pools with more than 125,000 barrels of oil. Light-oil pools account for most of the total known oil volume and consequently showed the lowest growth. Pools with greater than 30 percent porosity grew more than pools with lower porosity reservoirs. Oil field growth was found to be almost twice that of pool growth, possibly because the analysis evaluated fields with two or more pools discovered in different years. The growth in oil volumes in Alberta pools is projected to be about 454 million barrels of oil in the period from 2006 to 2010. Over a 25-year period, the cumulative reserve growth in Alberta oil pools was substantially lower than other major petroleum-producing regions, but the growth at the field level compares well. 8 refs., 2 tabs., 9 figs.
Populational Growth Models Proportional to Beta Densities with Allee Effect
Aleixo, Sandra M.; Rocha, J. Leonel; Pestana, Dinis D.
2009-05-01
We consider populations growth models with Allee effect, proportional to beta densities with shape parameters p and 2, where the dynamical complexity is related with the Malthusian parameter r. For p>2, these models exhibit a population dynamics with natural Allee effect. However, in the case of 1
models do not include this effect. In order to inforce it, we present some alternative models and investigate their dynamics, presenting some important results.
VAM2D: Variably saturated analysis model in two dimensions
International Nuclear Information System (INIS)
Huyakorn, P.S.; Kool, J.B.; Wu, Y.S.
1991-10-01
This report documents a two-dimensional finite element model, VAM2D, developed to simulate water flow and solute transport in variably saturated porous media. Both flow and transport simulation can be handled concurrently or sequentially. The formulation of the governing equations and the numerical procedures used in the code are presented. The flow equation is approximated using the Galerkin finite element method. Nonlinear soil moisture characteristics and atmospheric boundary conditions (e.g., infiltration, evaporation and seepage face), are treated using Picard and Newton-Raphson iterations. Hysteresis effects and anisotropy in the unsaturated hydraulic conductivity can be taken into account if needed. The contaminant transport simulation can account for advection, hydrodynamic dispersion, linear equilibrium sorption, and first-order degradation. Transport of a single component or a multi-component decay chain can be handled. The transport equation is approximated using an upstream weighted residual method. Several test problems are presented to verify the code and demonstrate its utility. These problems range from simple one-dimensional to complex two-dimensional and axisymmetric problems. This document has been produced as a user's manual. It contains detailed information on the code structure along with instructions for input data preparation and sample input and printed output for selected test problems. Also included are instructions for job set up and restarting procedures. 44 refs., 54 figs., 24 tabs
Modeling Variable Phanerozoic Oxygen Effects on Physiology and Evolution.
Graham, Jeffrey B; Jew, Corey J; Wegner, Nicholas C
2016-01-01
Geochemical approximation of Earth's atmospheric O2 level over geologic time prompts hypotheses linking hyper- and hypoxic atmospheres to transformative events in the evolutionary history of the biosphere. Such correlations, however, remain problematic due to the relative imprecision of the timing and scope of oxygen change and the looseness of its overlay on the chronology of key biotic events such as radiations, evolutionary innovation, and extinctions. There are nevertheless general attributions of atmospheric oxygen concentration to key evolutionary changes among groups having a primary dependence upon oxygen diffusion for respiration. These include the occurrence of Devonian hypoxia and the accentuation of air-breathing dependence leading to the origin of vertebrate terrestriality, the occurrence of Carboniferous-Permian hyperoxia and the major radiation of early tetrapods and the origins of insect flight and gigantism, and the Mid-Late Permian oxygen decline accompanying the Permian extinction. However, because of variability between and error within different atmospheric models, there is little basis for postulating correlations outside the Late Paleozoic. Other problems arising in the correlation of paleo-oxygen with significant biological events include tendencies to ignore the role of blood pigment affinity modulation in maintaining homeostasis, the slow rates of O2 change that would have allowed for adaptation, and significant respiratory and circulatory modifications that can and do occur without changes in atmospheric oxygen. The purpose of this paper is thus to refocus thinking about basic questions central to the biological and physiological implications of O2 change over geological time.
Stochastic transport models for mixing in variable-density turbulence
Bakosi, J.; Ristorcelli, J. R.
2011-11-01
In variable-density (VD) turbulent mixing, where very-different- density materials coexist, the density fluctuations can be an order of magnitude larger than their mean. Density fluctuations are non-negligible in the inertia terms of the Navier-Stokes equation which has both quadratic and cubic nonlinearities. Very different mixing rates of different materials give rise to large differential accelerations and some fundamentally new physics that is not seen in constant-density turbulence. In VD flows material mixing is active in a sense far stronger than that applied in the Boussinesq approximation of buoyantly-driven flows: the mass fraction fluctuations are coupled to each other and to the fluid momentum. Statistical modeling of VD mixing requires accounting for basic constraints that are not important in the small-density-fluctuation passive-scalar-mixing approximation: the unit-sum of mass fractions, bounded sample space, and the highly skewed nature of the probability densities become essential. We derive a transport equation for the joint probability of mass fractions, equivalent to a system of stochastic differential equations, that is consistent with VD mixing in multi-component turbulence and consistently reduces to passive scalar mixing in constant-density flows.
Variable Width Riparian Model Enhances Landscape and Watershed Condition
Abood, S. A.; Spencer, L.
2017-12-01
Riparian areas are ecotones that represent about 1% of USFS administered landscape and contribute to numerous valuable ecosystem functions such as wildlife habitat, stream water quality and flows, bank stability and protection against erosion, and values related to diversity, aesthetics and recreation. Riparian zones capture the transitional area between terrestrial and aquatic ecosystems with specific vegetation and soil characteristics which provide critical values/functions and are very responsive to changes in land management activities and uses. Two staff areas at the US Forest Service have coordinated on a two phase project to support the National Forests in their planning revision efforts and to address rangeland riparian business needs at the Forest Plan and Allotment Management Plan levels. The first part of the project will include a national fine scale (USGS HUC-12 digits watersheds) inventory of riparian areas on National Forest Service lands in western United States with riparian land cover, utilizing GIS capabilities and open source geospatial data. The second part of the project will include the application of riparian land cover change and assessment based on selected indicators to assess and monitor riparian areas on annual/5-year cycle basis.This approach recognizes the dynamic and transitional nature of riparian areas by accounting for hydrologic, geomorphic and vegetation data as inputs into the delineation process. The results suggest that incorporating functional variable width riparian mapping within watershed management planning can improve riparian protection and restoration. The application of Riparian Buffer Delineation Model (RBDM) approach can provide the agency Watershed Condition Framework (WCF) with observed riparian area condition on an annual basis and on multiple scales. The use of this model to map moderate to low gradient systems of sufficient width in conjunction with an understanding of the influence of distinctive landscape
Gruber, Jonathan
2014-06-01
Before we can evaluate the impact of the Affordable Care Act on health insurance premiums in the individual market, it is critical to understand the pricing trends of these premiums before the implementation of the law. Using rates of increase in the individual insurance market collected from state regulators, this issue brief documents trends in premium growth in the pre-ACA period. From 2008 to 2010, premiums grew by 10 percent or more per year. This growth was also highly variable across states, and even more variable across insurance plans within states. The study suggests that evaluating trends in premiums requires looking across a broad array of states and plans, and that policymakers must examine how present and future changes in premium rates compare with the more than 10 percent per year premium increases in the years preceding health reform.
Model for the growth of the world airline network
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.
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....
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.
An evolving network model with modular growth
International Nuclear Information System (INIS)
Zou Zhi-Yun; Liu Peng; Lei Li; Gao Jian-Zhi
2012-01-01
In this paper, we propose an evolving network model growing fast in units of module, according to the analysis of the evolution characteristics in real complex networks. Each module is a small-world network containing several interconnected nodes and the nodes between the modules are linked by preferential attachment on degree of nodes. We study the modularity measure of the proposed model, which can be adjusted by changing the ratio of the number of inner-module edges and the number of inter-module edges. In view of the mean-field theory, we develop an analytical function of the degree distribution, which is verified by a numerical example and indicates that the degree distribution shows characteristics of the small-world network and the scale-free network distinctly at different segments. The clustering coefficient and the average path length of the network are simulated numerically, indicating that the network shows the small-world property and is affected little by the randomness of the new module. (interdisciplinary physics and related areas of science and technology)
Sensitivity of Fit Indices to Misspecification in Growth Curve Models
Wu, Wei; West, Stephen G.
2010-01-01
This study investigated the sensitivity of fit indices to model misspecification in within-individual covariance structure, between-individual covariance structure, and marginal mean structure in growth curve models. Five commonly used fit indices were examined, including the likelihood ratio test statistic, root mean square error of…
Modelling primary branch growth based on a multilevel nonlinear ...
African Journals Online (AJOL)
In addition to random effects, various time series correlation structures were evaluated to account for residual autocorrelation, and the AR(1) and ARMA(1,1) structures were selected for the branch diameter and length growth models, respectively. Model validation results using an independent data set confirmed that ...
Modeling and forecasting mortality with economic growth : a multipopulation approach
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
Growth models for six Eucalyptus species in Angola | Delgado ...
African Journals Online (AJOL)
This study developed growth models for Eucalyptus saligna Sm., E. camaldulensis Dehnh., E. macarthurii H.Deane & Maiden, E. resinifera Sm., E. siderophloia Benth. and E. grandis Hill ex. Maiden, for the central highlands of Angola, and used these models to simulate the development of stand characteristics.
Kinetic models of cell growth, substrate utilization and bio ...
African Journals Online (AJOL)
Bio-decolorization kinetic studies of distillery effluent in a batch culture were conducted using Aspergillus fumigatus. A simple model was proposed using the Logistic Equation for the growth, Leudeking-Piret kinetics for bio-decolorization, and also for substrate utilization. The proposed models appeared to provide a suitable ...
Stratified flows with variable density: mathematical modelling and numerical challenges.
Murillo, Javier; Navas-Montilla, Adrian
2017-04-01
Stratified flows appear in a wide variety of fundamental problems in hydrological and geophysical sciences. They may involve from hyperconcentrated floods carrying sediment causing collapse, landslides and debris flows, to suspended material in turbidity currents where turbulence is a key process. Also, in stratified flows variable horizontal density is present. Depending on the case, density varies according to the volumetric concentration of different components or species that can represent transported or suspended materials or soluble substances. Multilayer approaches based on the shallow water equations provide suitable models but are not free from difficulties when moving to the numerical resolution of the governing equations. Considering the variety of temporal and spatial scales, transfer of mass and energy among layers may strongly differ from one case to another. As a consequence, in order to provide accurate solutions, very high order methods of proved quality are demanded. Under these complex scenarios it is necessary to observe that the numerical solution provides the expected order of accuracy but also converges to the physically based solution, which is not an easy task. To this purpose, this work will focus in the use of Energy balanced augmented solvers, in particular, the Augmented Roe Flux ADER scheme. References: J. Murillo , P. García-Navarro, Wave Riemann description of friction terms in unsteady shallow flows: Application to water and mud/debris floods. J. Comput. Phys. 231 (2012) 1963-2001. J. Murillo B. Latorre, P. García-Navarro. A Riemann solver for unsteady computation of 2D shallow flows with variable density. J. Comput. Phys.231 (2012) 4775-4807. A. Navas-Montilla, J. Murillo, Energy balanced numerical schemes with very high order. The Augmented Roe Flux ADER scheme. Application to the shallow water equations, J. Comput. Phys. 290 (2015) 188-218. A. Navas-Montilla, J. Murillo, Asymptotically and exactly energy balanced augmented flux
Variable Renewable Energy in Long-Term Planning Models: A Multi-Model Perspective
Energy Technology Data Exchange (ETDEWEB)
Cole, Wesley [National Renewable Energy Lab. (NREL), Golden, CO (United States); Frew, Bethany [National Renewable Energy Lab. (NREL), Golden, CO (United States); Mai, Trieu [National Renewable Energy Lab. (NREL), Golden, CO (United States); Sun, Yinong [National Renewable Energy Lab. (NREL), Golden, CO (United States); Bistline, John [Electric Power Research Inst. (EPRI), Knoxville, TN (United States); Blanford, Geoffrey [Electric Power Research Inst. (EPRI), Knoxville, TN (United States); Young, David [Electric Power Research Inst. (EPRI), Knoxville, TN (United States); Marcy, Cara [U.S. Energy Information Administration, Washington, DC (United States); Namovicz, Chris [U.S. Energy Information Administration, Washington, DC (United States); Edelman, Risa [US Environmental Protection Agency (EPA), Washington, DC (United States); Meroney, Bill [US Environmental Protection Agency (EPA), Washington, DC (United States); Sims, Ryan [US Environmental Protection Agency (EPA), Washington, DC (United States); Stenhouse, Jeb [US Environmental Protection Agency (EPA), Washington, DC (United States); Donohoo-Vallett, Paul [Dept. of Energy (DOE), Washington DC (United States)
2017-11-01
Long-term capacity expansion models of the U.S. electricity sector have long been used to inform electric sector stakeholders and decision-makers. With the recent surge in variable renewable energy (VRE) generators — primarily wind and solar photovoltaics — the need to appropriately represent VRE generators in these long-term models has increased. VRE generators are especially difficult to represent for a variety of reasons, including their variability, uncertainty, and spatial diversity. This report summarizes the analyses and model experiments that were conducted as part of two workshops on modeling VRE for national-scale capacity expansion models. It discusses the various methods for treating VRE among four modeling teams from the Electric Power Research Institute (EPRI), the U.S. Energy Information Administration (EIA), the U.S. Environmental Protection Agency (EPA), and the National Renewable Energy Laboratory (NREL). The report reviews the findings from the two workshops and emphasizes the areas where there is still need for additional research and development on analysis tools to incorporate VRE into long-term planning and decision-making. This research is intended to inform the energy modeling community on the modeling of variable renewable resources, and is not intended to advocate for or against any particular energy technologies, resources, or policies.
A thermodynamic model for growth mechanisms of multiwall carbon nanotubes.
Energy Technology Data Exchange (ETDEWEB)
Kaatz, Forrest H.; Overmyer, Donald L.; Siegal, Michael P.
2006-02-01
Multiwall carbon nanotubes are grown via thermal chemical vapor deposition between temperatures of 630 and 830 C using acetylene in nitrogen as the carbon source. This process is modeled using classical thermodynamics to explain the total carbon deposition as a function of time and temperature. An activation energy of 1.60 eV is inferred for nanotube growth after considering the carbon solubility term. Scanning electron microscopy shows growth with diameters increasing linearly with time. Transmission electron microscopy and Raman spectroscopy show multiwall nanotubes surrounded by a glassy-carbon sheath, which grows with increasing wall thickness as growth temperatures and times rise.
Thermodynamic model for growth mechanisms of multiwall carbon nanotubes
Kaatz, F. H.; Siegal, M. P.; Overmyer, D. L.; Provencio, P. P.; Tallant, D. R.
2006-12-01
Multiwall carbon nanotubes are grown via thermal chemical vapor deposition between temperatures of 630 and 830°C using acetylene in nitrogen as the carbon source. This process is modeled using classical thermodynamics to explain the total carbon deposition as a function of time and temperature. An activation energy of 1.60eV is inferred for nanotube growth after considering the carbon solubility term. Scanning electron microscopy shows growth with diameters increasing linearly with time. Transmission electron microscopy and Raman spectroscopy show multiwall nanotubes surrounded by a glassy-carbon sheath, which grows with increasing wall thickness as growth temperatures and times rise.
Spending Natural Resource Revenues in an Altruistic Growth Model
DEFF Research Database (Denmark)
Frederiksen, Elisabeth Hermann
This paper examines how revenues from a natural resource interact with growth and welfare in an overlapping generations model with altruism. The revenues are allocated between public productive services and direct transfers to members of society by spending policies. We analyze how these policies...... influence the dynamics, and how the dynamics are influenced by the abundance of the revenue. Abundant revenues may harm growth, but growth and welfare can be oppositely affected. We also provide the socially optimal policy. Overall, the analysis suggests that variation in the strength of altruism...
Estimating net present value variability for deterministic models
van Groenendaal, W.J.H.
1995-01-01
For decision makers the variability in the net present value (NPV) of an investment project is an indication of the project's risk. So-called risk analysis is one way to estimate this variability. However, risk analysis requires knowledge about the stochastic character of the inputs. For large,
Directory of Open Access Journals (Sweden)
E. Pishbahar
2015-05-01
Full Text Available There are different ideas and opinions about the effects of macroeconomic variables on real and nominal variables. To answer the question of whether changes in macroeconomic variables as a political tool is useful over a business cycle, understanding the effect of macroeconomic variables on economic growth is important. In the present study, the Bayesian Vector autoregresive model and seasonality data for the years between 1991 and 2013 was used to determine the impact of monetary policy on value-added agriculture. Predicts of Vector autoregresive model are usually divertaed due to a lot of parameters in the model. Bayesian vector autoregresive model estimates more reliable predictions due to reducing the number of included parametrs and considering the former models. Compared to the Vector Autoregressive model, the coefficients are estimated more accurately. Based on the results of RMSE in this study, previous function Nrmal-Vyshart was identified as a suitable previous disteribution. According to the results of the impulse response function, the sudden effects of shocks in macroeconomic variables on the value added in agriculture and domestic venture capital are stable. The effects on the exchange rates, tax revenues and monetary will bemoderated after 7, 5 and 4periods. Monetary policy shocks ,in the first half of the year, increased the value added of agriculture, while in the second half of the year had a depressing effect on the value added.
Government technology push in agribusiness: a model of endogenous growth
Directory of Open Access Journals (Sweden)
Francisco Venegas Martínez
2008-10-01
Full Text Available This paper develops a model of endogenous growth where the government acts as a promoting agent to boost technology in agribusiness. In the framework of a monetary economy, the optimal level of government spending to enhance technology in the agricultural industry is characterized. Moreover the impact of such a spending on economic welfare is assessed. Finally, a number of agro-oriented policies to increase growth in the sector are established.
Alexandrium minutum growth controlled by phosphorus An applied model
Chapelle, Annie; Labry, Claire; Sourisseau, Marc; Lebreton, Carole; Youenou, Agnes; Crassous, Marie-pierre
2010-01-01
Toxic algae are a worldwide problem threatening aquaculture public health and tourism Alexandrium a toxic dinoflagellate proliferates in Northwest France estuaries (i e the Penze estuary) causing Paralytic Shellfish Poisoning events Vegetative growth and in particular the role of nutrient uptake and growth rate are crucial parameters to understand toxic blooms With the goal of modelling in situ Alexandrium blooms related to environmental parameters we first try to calibrate a zero-dimensional...
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
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.
Test Method Variability in Slow Crack Growth Properties of Sealing Glasses
Salem, J. A.; Tandon, R.
2010-01-01
The crack growth properties of several sealing glasses were measured by using constant stress rate testing in 2 and 95 percent RH (relative humidity). Crack growth parameters measured in high humidity are systematically smaller (n and B) than those measured in low humidity, and crack velocities for dry environments are 100x lower than for wet environments. The crack velocity is very sensitive to small changes in RH at low RH. Biaxial and uniaxial stress states produced similar parameters. Confidence intervals on crack growth parameters that were estimated from propagation of errors solutions were comparable to those from Monte Carlo simulation. Use of scratch-like and indentation flaws produced similar crack growth parameters when residual stresses were considered.
Forster, R.M.; Martin-Jézéquel, V.R.
2005-01-01
Microphytobenthic diatoms have great ecological importance in estuarine and coastal marine ecosystenis, yet many aspects of their physiology have not been investigated under controlled conditions. This work describes patterns in growth rates and photosynthesis in different types of culture for
Directory of Open Access Journals (Sweden)
V. MADERICH
2015-07-01
Full Text Available A chain of simple linked models is used to simulate the seasonal and interannual variability of the Turkish Straits System. This chain includes two-layer hydraulic models of the Bosphorus and Dardanelles straits simulating the exchange in terms of level and density difference along each strait, and a one-dimensional area averaged layered model of the Marmara Sea. The chain of models is complemented also by the similar layered model of the Black Sea proper and by a one-layer Azov Sea model with the Kerch Strait. This linked chain of models is used to study the seasonal and interannual variability of the system in the period 1970-2009. The salinity of the Black Sea water flowing into the Aegean Sea increases by approximately 1.7 times through entrainment from the lower layer. The flow entering into the lower layer of the Dardanelles Strait from the Aegean Sea is reduced by nearly 80% when it reaches the Black Sea. In the seasonal scale, a maximal transport in the upper layer and minimal transport in the bottom layer are during winter/spring for the Bosphorus and in spring for the Dardanelles Strait, whereas minimal transport in upper layer and maximal undercurrent are during the summer for the Bosphorus Strait and autumn for the Dardanelles Strait. The increase of freshwater flux into the Black Sea in interannual time scales (41 m3s-1 per year is accompanied by a more than twofold growth of the Dardanelles outflow to the North Aegean (102 m3s-1 per year.
The Aspergillus niger growth on the treated concrete substrate using variable antifungals
Parjo, U. K.; Sunar, N. M.; Leman, A. M.; Gani, P.; Embong, Z.; Tajudin, S. A. A.
2016-11-01
The aim of this study was to evaluate the Aspergillus niger (A. niger) growth on substrates after incorporates with different compounds of antifungals which is normally used in food industry. The antifungals named as potassium sorbate (PS), calcium benzoate (CB) and zinc salicylate (ZS) were applied on concrete substrate covered with different wall finishing such as acrylic paint (AP), glycerol based paint (GBP), thin wallpaper (THIN) and thick wallpaper (THICK). The concrete substrate were inoculated with spore suspension, incubated at selected temperature (30oC) and relative humidity (90%)in plant growth chamber. The observations were done from the Day 3 until Day 27. The results showed that the growth of the A. niger for concrete treated by PS for AP, GBP, THIN, and THICK were 64%, 32%, 11% and 100%, respectively. Meanwhile for CB, the growth of A. niger on AP, GBP, THIN, and THICK were 100%, 12%, 41%, and 13%, respectively. Similarly, treated concrete by ZS revealed that the growth of A. niger on the same substrate cover were 33%, 47%, 40%, and 39%, respectively. The results obtained in this study provide a valuable knowledge on the abilities of antifungals to remediate A. niger that inoculated on the concrete substrate. Consequently, this study proved that the PS covering with THIN more efficiency compares CB and ZS to prevent A. niger growth.
Solar Cycle Variability Induced by Tilt Angle Scatter in a Babcock-Leighton Solar Dynamo Model
Karak, Bidya Binay; Miesch, Mark
2017-09-01
We present results from a three-dimensional Babcock-Leighton (BL) dynamo model that is sustained by the emergence and dispersal of bipolar magnetic regions (BMRs). On average, each BMR has a systematic tilt given by Joy’s law. Randomness and nonlinearity in the BMR emergence of our model produce variable magnetic cycles. However, when we allow for a random scatter in the tilt angle to mimic the observed departures from Joy’s law, we find more variability in the magnetic cycles. We find that the observed standard deviation in Joy’s law of {σ }δ =15^\\circ produces a variability comparable to the observed solar cycle variability of ˜32%, as quantified by the sunspot number maxima between 1755 and 2008. We also find that tilt angle scatter can promote grand minima and grand maxima. The time spent in grand minima for {σ }δ =15^\\circ is somewhat less than that inferred for the Sun from cosmogenic isotopes (about 9% compared to 17%). However, when we double the tilt scatter to {σ }δ =30^\\circ , the simulation statistics are comparable to the Sun (˜18% of the time in grand minima and ˜10% in grand maxima). Though the BL mechanism is the only source of poloidal field, we find that our simulations always maintain magnetic cycles even at large fluctuations in the tilt angle. We also demonstrate that tilt quenching is a viable and efficient mechanism for dynamo saturation; a suppression of the tilt by only 1°-2° is sufficient to limit the dynamo growth. Thus, any potential observational signatures of tilt quenching in the Sun may be subtle.
Fahimi, Farzad; Yaseen, Zaher Mundher; El-shafie, Ahmed
2017-05-01
Since the middle of the twentieth century, artificial intelligence (AI) models have been used widely in engineering and science problems. Water resource variable modeling and prediction are the most challenging issues in water engineering. Artificial neural network (ANN) is a common approach used to tackle this problem by using viable and efficient models. Numerous ANN models have been successfully developed to achieve more accurate results. In the current review, different ANN models in water resource applications and hydrological variable predictions are reviewed and outlined. In addition, recent hybrid models and their structures, input preprocessing, and optimization techniques are discussed and the results are compared with similar previous studies. Moreover, to achieve a comprehensive view of the literature, many articles that applied ANN models together with other techniques are included. Consequently, coupling procedure, model evaluation, and performance comparison of hybrid models with conventional ANN models are assessed, as well as, taxonomy and hybrid ANN models structures. Finally, current challenges and recommendations for future researches are indicated and new hybrid approaches are proposed.
Alonso, Santos; Armour, John A. L.
2001-01-01
We have sequenced a highly polymorphic subterminal noncoding region from human chromosome 16p13.3, flanking the 5′ end of the hypervariable minisatellite MS205, in 100 chromosomes sampled from different African and Euroasiatic populations. Coalescence analysis indicates that the time to the most recent common ancestor (approximately 1 million years) predates the appearance of anatomically modern human forms. The root of the network describing this variability lies in Africa. African populations show a greater level of diversity and deeper branches. Most Euroasiatic variability seems to have been generated after a recent out-of-Africa range expansion. A history of population growth is the most likely scenario for the Euroasiatic populations. This pattern of nuclear variability can be reconciled with inferences based on mitochondrial DNA. PMID:11158547
Growth Modeling with Non-Ignorable Dropout: Alternative Analyses of the STAR*D Antidepressant Trial
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
Some Limits Using Random Slope Models to Measure Academic Growth
Directory of Open Access Journals (Sweden)
Daniel B. Wright
2017-11-01
Full Text Available Academic growth is often estimated using a random slope multilevel model with several years of data. However, if there are few time points, the estimates can be unreliable. While using random slope multilevel models can lower the variance of the estimates, these procedures can produce more highly erroneous estimates—zero and negative correlations with the true underlying growth—than using ordinary least squares estimates calculated for each student or school individually. An example is provided where schools with increasing graduation rates are estimated to have negative growth and vice versa. The estimation is worse when the underlying data are skewed. It is recommended that there are at least six time points for estimating growth if using a random slope model. A combination of methods can be used to avoid some of the aberrant results if it is not possible to have six or more time points.
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...
Aurensanz Clemente, Esther; Samper Villagrasa, Pilar; Ayerza Casas, Ariadna; Ruiz Frontera, Pablo; Bueno Lozano, Olga; Moreno Aznar, Luis Alberto; Bueno Lozano, Gloria
2017-05-01
Small for gestational age (SGA) children without catch-up growth can benefit from treatment with growth hormone (rhGH). However, they should be monitored very closely because they are at increased risk of metabolic syndrome. A group of 28 SGA children with a mean age of 8.79 years and undergoing treatment with rhGH were selected for evaluation. Over the course of 4 years, an annual evaluation was performed on the anthropometric variables (weight, height, body mass index [BMI], growth rate, blood pressure and waist perimeter), metabolic risk variables (glycaemia, glycosylated haemoglobin, cholesterol ratio, insulinaemia, insulin-like growth factor 1[IGF1], IGF binding protein-3 [IGFBP-3], IGF1/IGFBP3 ratio, and HOMA index), and body composition variables. Treatment with rhGH was associated with a significant increase in height (-2.76±.11 SD to -1.53±.17 SD, P=.000), weight (-1.50±.09 SD to -1.21±.13 SD; P=.016), and growth rate (-1.43±.35 SD to .41±.41 SD; P=.009), without a corresponding change in the BMI. Insulinaemia (9.33±1.93mU/ml to 16.55±1.72mU/ml; P=.044) and the HOMA index (3.63±.76 to 6.43±.67; P=.042) increased, approaching insulin resistance levels. No changes were observed in the lipid profile. Body composition changes were observed, with a significant increase in lean mass (73.19±1.26 to 78.74±1.31; P=.037), and a reduction of fat mass (26.81±1.26 to 21.26±1.31; P=.021). Treatment with rhGH is effective for improving anthropometric variables in SGA patients who have not experienced a catch-up growth. It also produces changes in body composition, which may lead to a reduction in risk of metabolic syndrome. However, some insulin resistance was observed. It is important to follow up this patient group in order to find out whether these changes persist into adulthood. Copyright © 2016 Asociación Española de Pediatría. Publicado por Elsevier España, S.L.U. All rights reserved.
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
Sperber, K. R.; Palmer, T. N.
1996-11-01
The interannual variability of rainfall over the Indian subcontinent, the African Sahel, and the Nordeste region of Brazil have been evaluated in 32 models for the period 1979-88 as part of the Atmospheric Model Intercomparison Project (AMIP). The interannual variations of Nordeste rainfall are the most readily captured, owing to the intimate link with Pacific and Atlantic sea surface temperatures. The precipitation variations over India and the Sahel are less well simulated. Additionally, an Indian monsoon wind shear index was calculated for each model. Evaluation of the interannual variability of a wind shear index over the summer monsoon region indicates that the models exhibit greater fidelity in capturing the large-scale dynamic fluctuations than the regional-scale rainfall variations. A rainfall/SST teleconnection quality control was used to objectively stratify model performance. Skill scores improved for those models that qualitatively simulated the observed rainfall/El Niño- Southern Oscillation SST correlation pattern. This subset of models also had a rainfall climatology that was in better agreement with observations, indicating a link between systematic model error and the ability to simulate interannual variations.A suite of six European Centre for Medium-Range Weather Forecasts (ECMWF) AMIP runs (differing only in their initial conditions) have also been examined. As observed, all-India rainfall was enhanced in 1988 relative to 1987 in each of these realizations. All-India rainfall variability during other years showed little or no predictability, possibly due to internal chaotic dynamics associated with intraseasonal monsoon fluctuations and/or unpredictable land surface process interactions. The interannual variations of Nordeste rainfall were best represented. The State University of New York at Albany/National Center for Atmospheric Research Genesis model was run in five initial condition realizations. In this model, the Nordeste rainfall
NONLINEAR MODELS FOR DESCRIPTION OF CACAO FRUIT GROWTH WITH ASSUMPTION VIOLATIONS
Directory of Open Access Journals (Sweden)
JOEL AUGUSTO MUNIZ
2017-01-01
Full Text Available Cacao (Theobroma cacao L. is an important fruit in the Brazilian economy, which is mainly cultivated in the southern State of Bahia. The optimal stage for harvesting is a major factor for fruit quality and the knowledge on its growth curves can help, especially in identifying the ideal maturation stage for harvesting. Nonlinear regression models have been widely used for description of growth curves. However, several studies in this subject do not consider the residual analysis, the existence of a possible dependence between longitudinal observations, or the sample variance heterogeneity, compromising the modeling quality. The objective of this work was to compare the fit of nonlinear regression models, considering residual analysis and assumption violations, in the description of the cacao (clone Sial-105 fruit growth. The data evaluated were extracted from Brito and Silva (1983, who conducted the experiment in the Cacao Research Center, Ilheus, State of Bahia. The variables fruit length, diameter and volume as a function of fruit age were studied. The use of weighting and incorporation of residual dependencies was efficient, since the modeling became more consistent, improving the model fit. Considering the first-order autoregressive structure, when needed, leads to significant reduction in the residual standard deviation, making the estimates more reliable. The Logistic model was the most efficient for the description of the cacao fruit growth.
Bauer, Daniel J.; Curran, Patrick J.
2004-01-01
Structural equation mixture modeling (SEMM) integrates continuous and discrete latent variable models. Drawing on prior research on the relationships between continuous and discrete latent variable models, the authors identify 3 conditions that may lead to the estimation of spurious latent classes in SEMM: misspecification of the structural model,…
Selecting candidate predictor variables for the modelling of post ...
African Journals Online (AJOL)
Objectives: The objective of this project was to determine the variables most likely to be associated with post- .... (as defined subjectively by the research team) in global .... ed on their lack of knowledge of wealth scoring tools. ... HIV serology.
Deng, Chenhui; Plan, Elodie L; Karlsson, Mats O
2016-06-01
Parameter variation in pharmacometric analysis studies can be characterized as within subject parameter variability (WSV) in pharmacometric models. WSV has previously been successfully modeled using inter-occasion variability (IOV), but also stochastic differential equations (SDEs). In this study, two approaches, dynamic inter-occasion variability (dIOV) and adapted stochastic differential equations, were proposed to investigate WSV in pharmacometric count data analysis. These approaches were applied to published count models for seizure counts and Likert pain scores. Both approaches improved the model fits significantly. In addition, stochastic simulation and estimation were used to explore further the capability of the two approaches to diagnose and improve models where existing WSV is not recognized. The results of simulations confirmed the gain in introducing WSV as dIOV and SDEs when parameters vary randomly over time. Further, the approaches were also informative as diagnostics of model misspecification, when parameters changed systematically over time but this was not recognized in the structural model. The proposed approaches in this study offer strategies to characterize WSV and are not restricted to count data.
Modelling for Fuel Optimal Control of a Variable Compression Engine
Nilsson, Ylva
2007-01-01
Variable compression engines are a mean to meet the demand on lower fuel consumption. A high compression ratio results in high engine efficiency, but also increases the knock tendency. On conventional engines with fixed compression ratio, knock is avoided by retarding the ignition angle. The variable compression engine offers an extra dimension in knock control, since both ignition angle and compression ratio can be adjusted. The central question is thus for what combination of compression ra...
Exact solutions to a nonlinear dispersive model with variable coefficients
International Nuclear Information System (INIS)
Yin Jun; Lai Shaoyong; Qing Yin
2009-01-01
A mathematical technique based on an auxiliary differential equation and the symbolic computation system Maple is employed to investigate a prototypical and nonlinear K(n, n) equation with variable coefficients. The exact solutions to the equation are constructed analytically under various circumstances. It is shown that the variable coefficients and the exponent appearing in the equation determine the quantitative change in the physical structures of the solutions.
Vallot, Dorothée; Applegate, Patrick; Pettersson, Rickard
2013-04-01
Projecting future climate and ice sheet development requires sophisticated models and extensive field observations. Given the present state of our knowledge, it is very difficult to say what will happen with certainty. Despite the ongoing increase in atmospheric greenhouse gas concentrations, the possibility that a new ice sheet might form over Scandinavia in the far distant future cannot be excluded. The growth of a new Scandinavian Ice Sheet would have important consequences for buried nuclear waste repositories. The Greenland Analogue Project, initiated by the Swedish Nuclear Fuel and Waste Management Company (SKB), is working to assess the effects of a possible future ice sheet on groundwater flow by studying a constrained domain in Western Greenland by field measurements (including deep bedrock drilling in front of the ice sheet) combined with numerical modeling. To address the needs of the GAP project, we interpolated results from an ensemble of ice sheet model runs to the smaller and more finely resolved modeling domain used in the GAP project's hydrologic modeling. Three runs have been chosen with three fairly different positive degree-day factors among those that reproduced the modern ice margin at the borehole position. The interpolated results describe changes in hydrologically-relevant variables over two time periods, 115 ka to 80 ka, and 20 ka to 1 ka. In the first of these time periods, the ice margin advances over the model domain; in the second time period, the ice margin retreats over the model domain. The spatially-and temporally dependent variables that we treated include the ice thickness, basal melting rate, surface mass balance, basal temperature, basal thermal regime (frozen or thawed), surface temperature, and basal water pressure. The melt flux is also calculated.
Modeling and designing of variable-period and variable-pole-number undulator
Directory of Open Access Journals (Sweden)
I. Davidyuk
2016-02-01
Full Text Available The concept of permanent-magnet variable-period undulator (VPU was proposed several years ago and has found few implementations so far. The VPUs have some advantages as compared with conventional undulators, e.g., a wider range of radiation wavelength tuning and the option to increase the number of poles for shorter periods. Both these advantages will be realized in the VPU under development now at Budker INP. In this paper, we present the results of 2D and 3D magnetic field simulations and discuss some design features of this VPU.
Using Enthalpy as a Prognostic Variable in Atmospheric Modelling with Variable Composition
2016-04-14
Sela, personal communication, 2005). These terms are also routinely neglected in models. In models with a limited number of gaseous tracers, such as...so-called energy- exchange term (second term on the left- hand side) in Equation (5). The finite-difference schemes in existing atmospheric models have...equation for the sum of enthalpy and kinetic energy of horizontal motion is solved. This eliminates the energy- exchange term and automatically
Alternative models developed for estimating acute systemic toxicity are generally evaluated using in vivo LD50 values. However, in vivo acute systemic toxicity studies can produce variable results, even when conducted according to accepted test guidelines. This variability can ma...
3D Multiscale Modelling of Angiogenesis and Vascular Tumour Growth
Perfahl, H.
2012-11-01
We present a three-dimensional, multiscale model of vascular tumour growth, which couples nutrient/growth factor transport, blood flow, angiogenesis, vascular remodelling, movement of and interactions between normal and tumour cells, and nutrient-dependent cell cycle dynamics within each cell. We present computational simulations which show how a vascular network may evolve and interact with tumour and healthy cells. We also demonstrate how our model may be combined with experimental data, to predict the spatio-temporal evolution of a vascular tumour.
3D Multiscale Modelling of Angiogenesis and Vascular Tumour Growth
Perfahl, H.; Byrne, H. M.; Chen, T.; Estrella, V.; Alarcó n, T.; Lapin, A.; Gatenby, R. A.; Gillies, R. J.; Lloyd, M. C.; Maini, P. K.; Reuss, M.; Owen, M. R.
2012-01-01
We present a three-dimensional, multiscale model of vascular tumour growth, which couples nutrient/growth factor transport, blood flow, angiogenesis, vascular remodelling, movement of and interactions between normal and tumour cells, and nutrient-dependent cell cycle dynamics within each cell. We present computational simulations which show how a vascular network may evolve and interact with tumour and healthy cells. We also demonstrate how our model may be combined with experimental data, to predict the spatio-temporal evolution of a vascular tumour.
Research & development and growth: A Bayesian model averaging analysis
Czech Academy of Sciences Publication Activity Database
Horváth, Roman
2011-01-01
Roč. 28, č. 6 (2011), s. 2669-2673 ISSN 0264-9993. [Society for Non-linear Dynamics and Econometrics Annual Conferencen. Washington DC, 16.03.2011-18.03.2011] R&D Projects: GA ČR GA402/09/0965 Institutional research plan: CEZ:AV0Z10750506 Keywords : Research and development * Growth * Bayesian model averaging Subject RIV: AH - Economic s Impact factor: 0.701, year: 2011 http://library.utia.cas.cz/separaty/2011/E/horvath-research & development and growth a bayesian model averaging analysis.pdf
Some Remarks on Stochastic Versions of the Ramsey Growth Model
Czech Academy of Sciences Publication Activity Database
Sladký, Karel
2012-01-01
Roč. 19, č. 29 (2012), s. 139-152 ISSN 1212-074X R&D Projects: GA ČR GAP402/10/1610; GA ČR GAP402/10/0956; GA ČR GAP402/11/0150 Institutional support: RVO:67985556 Keywords : Economic dynamics * Ramsey growth model with disturbance * stochastic dynamic programming * multistage stochastic programs Subject RIV: BB - Applied Statistics, Operational Research http://library.utia.cas.cz/separaty/2013/E/sladky-some remarks on stochastic versions of the ramsey growth model.pdf
Jump, Alistair S.; Ruiz-Benito, Paloma; Greenwood, Sarah; Allen, Craig D.; Kitzberger, Thomas; Fensham, Rod; Martínez-Vilalta, Jordi; Lloret, Francisco
2017-01-01
Ongoing climate change poses significant threats to plant function and distribution. Increased temperatures and altered precipitation regimes amplify drought frequency and intensity, elevating plant stress and mortality. Large-scale forest mortality events will have far-reaching impacts on carbon and hydrological cycling, biodiversity, and ecosystem services. However, biogeographical theory and global vegetation models poorly represent recent forest die-off patterns. Furthermore, as trees are sessile and long-lived, their responses to climate extremes are substantially dependent on historical factors. We show that periods of favourable climatic and management conditions that facilitate abundant tree growth can lead to structural overshoot of aboveground tree biomass due to a subsequent temporal mismatch between water demand and availability. When environmental favourability declines, increases in water and temperature stress that are protracted, rapid, or both, drive a gradient of tree structural responses that can modify forest self-thinning relationships. Responses ranging from premature leaf senescence and partial canopy dieback to whole-tree mortality reduce canopy leaf area during the stress period and for a lagged recovery window thereafter. Such temporal mismatches of water requirements from availability can occur at local to regional scales throughout a species geographical range. As climate change projections predict large future fluctuations in both wet and dry conditions, we expect forests to become increasingly structurally mismatched to water availability and thus overbuilt during more stressful episodes. By accounting for the historical context of biomass development, our approach can explain previously problematic aspects of large-scale forest mortality, such as why it can occur throughout the range of a species and yet still be locally highly variable, and why some events seem readily attributable to an ongoing drought while others do not. This
Jump, Alistair S; Ruiz-Benito, Paloma; Greenwood, Sarah; Allen, Craig D; Kitzberger, Thomas; Fensham, Rod; Martínez-Vilalta, Jordi; Lloret, Francisco
2017-09-01
Ongoing climate change poses significant threats to plant function and distribution. Increased temperatures and altered precipitation regimes amplify drought frequency and intensity, elevating plant stress and mortality. Large-scale forest mortality events will have far-reaching impacts on carbon and hydrological cycling, biodiversity, and ecosystem services. However, biogeographical theory and global vegetation models poorly represent recent forest die-off patterns. Furthermore, as trees are sessile and long-lived, their responses to climate extremes are substantially dependent on historical factors. We show that periods of favourable climatic and management conditions that facilitate abundant tree growth can lead to structural overshoot of aboveground tree biomass due to a subsequent temporal mismatch between water demand and availability. When environmental favourability declines, increases in water and temperature stress that are protracted, rapid, or both, drive a gradient of tree structural responses that can modify forest self-thinning relationships. Responses ranging from premature leaf senescence and partial canopy dieback to whole-tree mortality reduce canopy leaf area during the stress period and for a lagged recovery window thereafter. Such temporal mismatches of water requirements from availability can occur at local to regional scales throughout a species geographical range. As climate change projections predict large future fluctuations in both wet and dry conditions, we expect forests to become increasingly structurally mismatched to water availability and thus overbuilt during more stressful episodes. By accounting for the historical context of biomass development, our approach can explain previously problematic aspects of large-scale forest mortality, such as why it can occur throughout the range of a species and yet still be locally highly variable, and why some events seem readily attributable to an ongoing drought while others do not. This
Pollution and economic growth in a model of overlapping generations
Energy Technology Data Exchange (ETDEWEB)
Fisher, Eric O`N. [Department of Economics, The Ohio State University, Columbus, OH (United States); Van Marrewijk, Charles [Department of Economics, Erasmus University, Rotterdam (Netherlands)
1994-01-22
We analyze a model of overlapping generations in which clean air, a pure public consumption good, is used as a private input into production. Although production exhibits constant returns to scale, endogenous growth can occur because the economy has tWO sectors. In a laissez-faire equilibrium, there is no market for pollution rights, and firms appropriate clean air in an arbitrary manner. Growth occurs only if the marginal propensity to save is high enough and the asymptotic share of pollution in the investment sector is zero. Firms generate quasi-rents that are the value of pollution rights. These quasi-rents crowd out investment and slow economic growth. A laissez- faire equilibrium may not support Pareto optimal allocations, but a Pigouvian tax with lump-sum distribution of the resulting revenues does. Hence, a pollution lax yields a double dividend because it can increase both the static efficiency of the economy and its growth rate. 1 fig., 20 refs.
Growth model of Au films on Ru(001)
International Nuclear Information System (INIS)
Canessa, E.; Calmetta, A.
1992-06-01
In an attempt to find generic features on the fractal growth of Au films deposited on Ru(001), a simple simulation model based on irreversible diffusion-limited aggregation (DLA) is discussed. Highly irregular two-dimensional dentritic islands of Au particles that gradually grow on a larger host lattice of Ru particles and have fractal dimension d f approx. 1.70 each, are generated via a multiple had-hoc version of the DLA algorithm for single aggregates. Annealing effects on the islands morphology are reproduced assuming different sticking probabilities at nearest-neighbour lattice sites of Au films on Ru(001). Using simulation data, islands growth are described in analogy to diffusion-limited, precipitate growth with soft impingement of precipities. This leads to analyse thin film island growth kinetics in such fractal systems and to predict a main peak in scattering intensity patterns due to interisland interference. (author). 12 refs, 4 figs
Pollution and economic growth in a model of overlapping generations
International Nuclear Information System (INIS)
Fisher, Eric O'N.; Van Marrewijk, Charles
1994-01-01
We analyze a model of overlapping generations in which clean air, a pure public consumption good, is used as a private input into production. Although production exhibits constant returns to scale, endogenous growth can occur because the economy has tWO sectors. In a laissez-faire equilibrium, there is no market for pollution rights, and firms appropriate clean air in an arbitrary manner. Growth occurs only if the marginal propensity to save is high enough and the asymptotic share of pollution in the investment sector is zero. Firms generate quasi-rents that are the value of pollution rights. These quasi-rents crowd out investment and slow economic growth. A laissez- faire equilibrium may not support Pareto optimal allocations, but a Pigouvian tax with lump-sum distribution of the resulting revenues does. Hence, a pollution lax yields a double dividend because it can increase both the static efficiency of the economy and its growth rate. 1 fig., 20 refs
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.
Modeling and Forecasting Mortality With Economic Growth: A Multipopulation Approach.
Boonen, Tim J; Li, Hong
2017-10-01
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 particular, we extend the Li and Lee model (Li and Lee 2005) by including economic growth, represented by the real gross domestic product (GDP) per capita, to capture the common mortality trend for a group of populations with similar socioeconomic conditions. We find that our proposed model provides a better in-sample fit and an out-of-sample forecast performance. Moreover, it generates lower (higher) forecasted period life expectancy for countries with high (low) GDP per capita than the Li and Lee model.
A Discrete Monetary Economic Growth Model with the MIU Approach
Directory of Open Access Journals (Sweden)
Wei-Bin Zhang
2008-01-01
Full Text Available This paper proposes an alternative approach to economic growth with money. The production side is the same as the Solow model, the Ramsey model, and the Tobin model. But we deal with behavior of consumers differently from the traditional approaches. The model is influenced by the money-in-the-utility (MIU approach in monetary economics. It provides a mechanism of endogenous saving which the Solow model lacks and avoids the assumption of adding up utility over a period of time upon which the Ramsey approach is based.
Eye growth and myopia development: Unifying theory and Matlab model.
Hung, George K; Mahadas, Kausalendra; Mohammad, Faisal
2016-03-01
The aim of this article is to present an updated unifying theory of the mechanisms underlying eye growth and myopia development. A series of model simulation programs were developed to illustrate the mechanism of eye growth regulation and myopia development. Two fundamental processes are presumed to govern the relationship between physiological optics and eye growth: genetically pre-programmed signaling and blur feedback. Cornea/lens is considered to have only a genetically pre-programmed component, whereas eye growth is considered to have both a genetically pre-programmed and a blur feedback component. Moreover, based on the Incremental Retinal-Defocus Theory (IRDT), the rate of change of blur size provides the direction for blur-driven regulation. The various factors affecting eye growth are shown in 5 simulations: (1 - unregulated eye growth): blur feedback is rendered ineffective, as in the case of form deprivation, so there is only genetically pre-programmed eye growth, generally resulting in myopia; (2 - regulated eye growth): blur feedback regulation demonstrates the emmetropization process, with abnormally excessive or reduced eye growth leading to myopia and hyperopia, respectively; (3 - repeated near-far viewing): simulation of large-to-small change in blur size as seen in the accommodative stimulus/response function, and via IRDT as well as nearwork-induced transient myopia (NITM), leading to the development of myopia; (4 - neurochemical bulk flow and diffusion): release of dopamine from the inner plexiform layer of the retina, and the subsequent diffusion and relay of neurochemical cascade show that a decrease in dopamine results in a reduction of proteoglycan synthesis rate, which leads to myopia; (5 - Simulink model): model of genetically pre-programmed signaling and blur feedback components that allows for different input functions to simulate experimental manipulations that result in hyperopia, emmetropia, and myopia. These model simulation programs
Long-term relationships of major macro-variables in a resource-related economic model of Australia
International Nuclear Information System (INIS)
Harvie, Charles; Hoa, T. van
1993-01-01
The paper reports the results of a simple cointegration analysis applied to bivariate causality models using data on resource output, oil prices, terms of trade, current account and output growth to investigate the long-term relationships among these major macroeconomic aggregates in a resource-related economic model of Australia. For the period 1960-1990, the empirical evidence indicates that these five macro-variables, as formulated in our model, are not random walks. In addition, resource production and oil prices are significantly cointegrated, and they are also significantly cointegrated with the current account, terms of trade and economic growth. These findings provide support to the long-term adjustments foundation of our resource-related model. (author)
Directory of Open Access Journals (Sweden)
Darjat Sudrajat
2015-05-01
Full Text Available Indonesian logistics companies needed performance improvement (particularly in organic growth for increasing their competitiveness. Based on previous researches that in order to increase organic growth, it could be conducted through developing corporate entrepreneurship, namely the activities that enhance company’s ability to innovate, take risk and seize market opportunities. The purpose of this paper tried to explore the relationships among variables, namely organic growth (OG, corporate entrepreneurship (CE, transformational leadership (TL, knowledge management (KM, and strategic management (SM. Therefore, this research used causal-explanatory study to explain relationships among the variables. The results of this research were concluded that TL, KM, and SM have contributions to corporate entrepreneurship and organicgrowth. The relationships could be constructed in a conceptual model that could be verified through further research.
Mathematical analysis of a model for the growth of the bovine corpus luteum
Prokopiou, Sotiris A.
2013-12-13
The corpus luteum (CL) is an ovarian tissue that grows in the wound space created by follicular rupture. It produces the progesterone needed in the uterus to maintain pregnancy. Rapid growth of the CL and progesterone transport to the uterus require angiogenesis, the creation of new blood vessels from pre-existing ones, a process which is regulated by proteins that include fibroblast growth factor 2 (FGF2). In this paper we develop a system of time-dependent ordinary differential equations to model CL growth. The dependent variables represent FGF2, endothelial cells (ECs), luteal cells, and stromal cells (like pericytes), by assuming that the CL volume is a continuum of the three cell types. We assume that if the CL volume exceeds that of the ovulated follicle, then growth is inhibited. This threshold volume partitions the system dynamics into two regimes, so that the model may be classified as a Filippov (piecewise smooth) system. We show that normal CL growth requires an appropriate balance between the growth rates of luteal and stromal cells. We investigate how angiogenesis influences CL growth by considering how the system dynamics depend on the dimensionless EC proliferation rate, {Mathematical expression}. We find that weak (low {Mathematical expression}) or strong (high {Mathematical expression}) angiogenesis leads to \\'pathological\\' CL growth, since the loss of CL constituents compromises progesterone production or delivery. However, for intermediate values of {Mathematical expression}, normal CL growth is predicted. The implications of these results for cow fertility are also discussed. For example, inadequate angiogenesis has been linked to infertility in dairy cows. © 2013 Springer-Verlag Berlin Heidelberg.
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.
Effects of loading variables on fatigue-crack growth in liquid-metal environments
CSIR Research Space (South Africa)
Fernandes, PJL
1995-10-01
Full Text Available Liquid-metal-induced embrittlement (LMIE) refers to the loss of ductility in normally ductile metals and alloys when stressed while in contact with a liquid metal. In this study, the fatigue crack growth behaviour of brass in molten gallium...
Czech Academy of Sciences Publication Activity Database
Natalini, F.; Alejano, R.; Vazquez-Pique, J.; Pardos, M.; Calama, R.; Büntgen, Ulf
2016-01-01
Roč. 40, dec (2016), s. 72-84 ISSN 1125-7865 Institutional support: RVO:67179843 Keywords : tree-rings * genetically depauperate * mediterranean climate * phenotypic plasticity * cambial activity * fagus-sylvatica * spain * drought * widespread * halepensis * Climate change * Dendroecology * Growth plasticity * Mediterranean * Tree rings * Drought Subject RIV: EH - Ecology, Behaviour Impact factor: 2.259, year: 2016
Intra-annual variability in skeletal growth of the Devonian tabulate coral Scoliopora
Czech Academy of Sciences Publication Activity Database
Hladil, Jindřich
2002-01-01
Roč. 68, - (2002), s. 77-78 ISSN 0729-011X. [International Palaeontological Congress Australia /1./. 06.07.2002-10.07.2002, Sydney] R&D Projects: GA AV ČR IAA3013209 Keywords : sclerochronology * skeletal growth * ocean and marine basins Subject RIV: DB - Geology ; Mineralogy
Directory of Open Access Journals (Sweden)
David Shilane
2013-01-01
Full Text Available The negative binomial distribution becomes highly skewed under extreme dispersion. Even at moderately large sample sizes, the sample mean exhibits a heavy right tail. The standard normal approximation often does not provide adequate inferences about the data's expected value in this setting. In previous work, we have examined alternative methods of generating confidence intervals for the expected value. These methods were based upon Gamma and Chi Square approximations or tail probability bounds such as Bernstein's inequality. We now propose growth estimators of the negative binomial mean. Under high dispersion, zero values are likely to be overrepresented in the data. A growth estimator constructs a normal-style confidence interval by effectively removing a small, predetermined number of zeros from the data. We propose growth estimators based upon multiplicative adjustments of the sample mean and direct removal of zeros from the sample. These methods do not require estimating the nuisance dispersion parameter. We will demonstrate that the growth estimators' confidence intervals provide improved coverage over a wide range of parameter values and asymptotically converge to the sample mean. Interestingly, the proposed methods succeed despite adding both bias and variance to the normal approximation.
Energy Technology Data Exchange (ETDEWEB)
Rollin, Bertrand [Los Alamos National Laboratory; Andrews, Malcolm J [Los Alamos National Laboratory
2010-01-01
We present our progress toward setting initial conditions in variable density turbulence models. In particular, we concentrate our efforts on the BHR turbulence model for turbulent Rayleigh-Taylor instability. Our approach is to predict profiles of relevant parameters before the fully turbulent regime and use them as initial conditions for the turbulence model. We use an idealized model of the mixing between two interpenetrating fluids to define the initial profiles for the turbulence model parameters. Velocities and volume fractions used in the idealized mixing model are obtained respectively from a set of ordinary differential equations modeling the growth of the Rayleigh-Taylor instability and from an idealization of the density profile in the mixing layer. A comparison between predicted initial profiles for the turbulence model parameters and initial profiles of the parameters obtained from low Atwood number three dimensional simulations show reasonable agreement.
Application of a Snow Growth Model to Radar Remote Sensing
Erfani, E.; Mitchell, D. L.
2014-12-01
Microphysical growth processes of diffusion, aggregation and riming are incorporated analytically in a steady-state snow growth model (SGM) to solve the zeroth- and second- moment conservation equations with respect to mass. The SGM is initiated by radar reflectivity (Zw), supersaturation, temperature, and a vertical profile of the liquid water content (LWC), and it uses a gamma size distribution (SD) to predict the vertical evolution of size spectra. Aggregation seems to play an important role in the evolution of snowfall rates and the snowfall rates produced by aggregation, diffusion and riming are considerably greater than those produced by diffusion and riming alone, demonstrating the strong interaction between aggregation and riming. The impact of ice particle shape on particle growth rates and fall speeds is represented in the SGM in terms of ice particle mass-dimension (m-D) power laws (m = αDβ). These growth rates are qualitatively consistent with empirical growth rates, with slower (faster) growth rates predicted for higher (lower) β values. In most models, β is treated constant for a given ice particle habit, but it is well known that β is larger for the smaller crystals. Our recent work quantitatively calculates β and α for cirrus clouds as a function of D where the m-D expression is a second-order polynomial in log-log space. By adapting this method to the SGM, the ice particle growth rates and fall speeds are predicted more accurately. Moreover, the size spectra predicted by the SGM are in good agreement with those from aircraft measurements during Lagrangian spiral descents through frontal clouds, indicating the successful modeling of microphysical processes. Since the lowest Zw over complex topography is often significantly above cloud base, the precipitation is often underestimated by radar quantitative precipitation estimates (QPE). Our SGM is capable of being initialized with Zw at the lowest reliable radar echo and consequently improves
National Research Council Canada - National Science Library
Abate, Christopher
2004-01-01
...) data with a hybrid adjusted cost growth (ACG) model. In addition, an analysis of acquisition reform initiatives during the treatment period was conducted to determine if reform efforts impacted missile system cost growth. A pre-reform...
Modeling of dislocation dynamics in germanium Czochralski growth
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.
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.
Meeuwig, M.H.; Dunham, J.B.; Hayes, J.P.; Vinyard, G.L.
2004-01-01
The effects of constant (12, 18, and 24 A?C) and cyclical (daily variation of 15a??21 and 12a??24 A?C) thermal regimes on the growth and feeding of Lahontan cutthroat trout (Oncorhynchus clarki henshawi) of variable sizes were examined. Higher constant temperatures (i.e., 24 A?C) and more variable daily temperatures (i.e., 12a??24 A?C daily cycle) negatively affected growth rates. As fish mass increased (from 0.24 to 15.52 g) the effects of different thermal regimes on mass growth became more pronounced. Following 14 days exposure to the thermal regimes, feeding rates of individual fish were assessed during acute exposure (40 min) to test temperatures of 12, 18, and 24 A?C. Feeding rate was depressed during acute exposure to 24 A?C, but was not significantly affected by the preceding thermal regime. Our results indicate that even brief daily exposure to higher temperatures (e.g., 24 A?C) can have considerable sublethal effects on cutthroat trout, and that fish size should be considered when examining the effects of temperature.
Directory of Open Access Journals (Sweden)
Rasiukevičiūtė Neringa
2017-06-01
Full Text Available Botrytis cinerea Pers.:Fr. is a widespread necrotrophic pathogen causing grey mould on many economically important horticultural crops. The variability in various B. cinerea populations is known to be very high. Despite the economic importance, the variability of B. cinerea has not been investigated previously on fruit crops in Lithuania. The aim of the study was to characterise the variability of B. cinerea strains isolated from strawberry and apple in different growth conditions on various agar media and to assess mycelial compatibility among the isolates. Larger colony diameter after four days of incubation was observed for isolates from strawberry on potato dextrose and beer universal agars in 24 h dark or light regime, followed by pectin agar in 24 h light. Similarly, the maximum radial growth of the isolates from apple was on potato dextrose agar (dark, followed by beer universal agar (dark and light, after four days of incubation at 20 °C. In the mycelial compatibility tests, barrage formation was evident in mycelial contacts between several isolates, indicating their vegetative incompatibility. The tests revealed that 76% were compatible and 24% were incompatible among investigated strains.
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.
Random-growth urban model with geographical fitness
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.
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.
Cumulative growth of minor hysteresis loops in the Kolmogorov model
International Nuclear Information System (INIS)
Meilikhov, E. Z.; Farzetdinova, R. M.
2013-01-01
The phenomenon of nonrepeatability of successive remagnetization cycles in Co/M (M = Pt, Pd, Au) multilayer film structures is explained in the framework of the Kolmogorov crystallization model. It is shown that this model of phase transitions can be adapted so as to adequately describe the process of magnetic relaxation in the indicated systems with “memory.” For this purpose, it is necessary to introduce some additional elements into the model, in particular, (i) to take into account the fact that every cycle starts from a state “inherited” from the preceding cycle and (ii) to assume that the rate of growth of a new magnetic phase depends on the cycle number. This modified model provides a quite satisfactory qualitative and quantitative description of all features of successive magnetic relaxation cycles in the system under consideration, including the surprising phenomenon of cumulative growth of minor hysteresis loops.
Forecasting Costa Rican Quarterly Growth with Mixed-frequency Models
Directory of Open Access Journals (Sweden)
Adolfo Rodríguez Vargas
2014-11-01
Full Text Available We assess the utility of mixed-frequency models to forecast the quarterly growth rate of Costa Rican real GDP: we estimate bridge and MiDaS models with several lag lengths using information of the IMAE and compute forecasts (horizons of 0-4 quarters which are compared between themselves, with those of ARIMA models and with those resulting from forecast combinations. Combining the most accurate forecasts is most useful when forecasting in real time, whereas MiDaS forecasts are the best-performing overall: as the forecasting horizon increases, their precisionis affected relatively little; their success rates in predicting the direction of changes in the growth rate are stable, and several forecastsremain unbiased. In particular, forecasts computed from simple MiDaS with 9 and 12 lags are unbiased at all horizons and information sets assessed, and show the highest number of significant differences in forecasting ability in comparison with all other models.
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.
Microstructural modelling of creep crack growth from a blunted crack
Onck, P.R.; Giessen, E. van der
1998-01-01
The effect of crack tip blunting on the initial stages of creep crack growth is investigated by means of a planar microstructural model in which grains are represented discretely. The actual linking-up process of discrete microcracks with the macroscopic crack is simulated, with full account of the
Escherichia coli growth modeling using neural network | Shamsudin ...
African Journals Online (AJOL)
technique that has the ability to predict with efficient and good performance. Using NARX, a highly accurate model was developed to predict the growth of Escherichia coli (E. coli) based on pH water parameter. The multiparameter portable sensor and spectrophotometer data were used to build and train the neural network.
Building Context with Tumor Growth Modeling Projects in Differential Equations
Beier, Julie C.; Gevertz, Jana L.; Howard, Keith E.
2015-01-01
The use of modeling projects serves to integrate, reinforce, and extend student knowledge. Here we present two projects related to tumor growth appropriate for a first course in differential equations. They illustrate the use of problem-based learning to reinforce and extend course content via a writing or research experience. Here we discuss…
A Role for M-Matrices in Modelling Population Growth
James, Glyn; Rumchev, Ventsi
2006-01-01
Adopting a discrete-time cohort-type model to represent the dynamics of a population, the problem of achieving a desired total size of the population under a balanced growth (contraction) and the problem of maintaining the desired size, once achieved, are studied. Properties of positive-time systems and M-matrices are used to develop the results,…
Models of Economic Growth and Development in the Context of ...
African Journals Online (AJOL)
The better-known models of economic growth such as the Lewis, Rostow,. Harrod-Domar ... produce highly educated populaces usually reap the benefits of such in terms of high per capita ..... The Russian revolution of 1917 led by Lenin proposed in theory a .... This was about government intervention into the economy to ...
Developmental trajectories of adolescent popularity: a growth curve modelling analysis.
Cillessen, Antonius H N; Borch, Casey
2006-12-01
Growth curve modelling was used to examine developmental trajectories of sociometric and perceived popularity across eight years in adolescence, and the effects of gender, overt aggression, and relational aggression on these trajectories. Participants were 303 initially popular students (167 girls, 136 boys) for whom sociometric data were available in Grades 5-12. The popularity and aggression constructs were stable but non-overlapping developmental dimensions. Growth curve models were run with SAS MIXED in the framework of the multilevel model for change [Singer, J. D., & Willett, J. B. (2003). Applied longitudinal data analysis. Oxford, UK: Oxford University Press]. Sociometric popularity showed a linear change trajectory; perceived popularity showed nonlinear change. Overt aggression predicted low sociometric popularity but an increase in perceived popularity in the second half of the study. Relational aggression predicted a decrease in sociometric popularity, especially for girls, and continued high-perceived popularity for both genders. The effect of relational aggression on perceived popularity was the strongest around the transition from middle to high school. The importance of growth curve models for understanding adolescent social development was discussed, as well as specific issues and challenges of growth curve analyses with sociometric data.
Hybrid discrete dislocation models for fatigue crack growth
Curtin, W. A.; Deshpande, V. S.; Needleman, A.; Van der Giessen, E.; Wallin, M.
A framework for accurately modeling fatigue crack growth in ductile crystalline solids is necessarily multiscale The creation of new free surface occurs at the atomistic scale, where the material's cohesive strength is controlled by the local chemistry On the other hand, significant dissipation
Growth and yield models for Eucalyptus grandis grown in Swaziland ...
African Journals Online (AJOL)
The aim of this study was to develop a stand-level growth and yield model for short-rotationEucalyptus grandis grown for pulp wood production at Piggs Peak in Swaziland. The data were derived from a Nelder 1a spacing trial established with E. grandis clonal cuttings in 1998 and terminated in 2005. Planting density ...
Modeling growth of specific spoilage organisms in tilapia ...
African Journals Online (AJOL)
Tilapia is an important aquatic fish, but severe spoilage of tilapia is most likely related to the global aquaculture. The spoilage is mostly caused by specific spoilage organisms (SSO). Therefore, it is very important to use microbial models to predict the growth of SSO in tilapia. This study firstly verified Pseudomonas and Vibrio ...
Studying historical occupational careers with multilevel growth models
Schulz, W.; Maas, I.
2010-01-01
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.