Adjusting the Stems Regional Forest Growth Model to Improve Local Predictions
W. Brad Smith
1983-01-01
A simple procedure using double sampling is described for adjusting growth in the STEMS regional forest growth model to compensate for subregional variations. Predictive accuracy of the STEMS model (a distance-independent, individual tree growth model for Lake States forests) was improved by using this procedure
A Vernacular for Linear Latent Growth Models
ERIC Educational Resources Information Center
Hancock, Gregory R.; Choi, Jaehwa
2006-01-01
In its most basic form, latent growth modeling (latent curve analysis) allows an assessment of individuals' change in a measured variable X over time. For simple linear models, as with other growth models, parameter estimates associated with the a construct (amount of X at a chosen temporal reference point) and b construct (growth in X per unit…
Gurien, Lori A; Wyrick, Deidre L; Smith, Samuel D; Maxson, R Todd
2016-05-01
Although this issue remains unexamined, pediatric surgeons commonly use simple interrupted suture for bowel anastomosis, as it is thought to improve intestinal growth postoperatively compared to continuous running suture. However, effects on intestinal growth are unclear. We compared intestinal growth using different anastomotic techniques during the postoperative period in young rats. Young, growing rats underwent small bowel transection and anastomosis using either simple interrupted or continuous running technique. At 7-weeks postoperatively after a four-fold growth, the anastomotic site was resected. Diameters and burst pressures were measured. Thirteen rats underwent anastomosis with simple interrupted technique and sixteen with continuous running method. No differences were found in body weight at first (102.46 vs 109.75g) or second operations (413.85 vs 430.63g). Neither the diameters (0.69 vs 0.79cm) nor burst pressures were statistically different, although the calculated circumference was smaller in the simple interrupted group (2.18 vs 2.59cm; p=0.03). No ruptures occurred at the anastomotic line. This pilot study is the first to compare continuous running to simple interrupted intestinal anastomosis in a pediatric model and showed no difference in growth. Adopting continuous running techniques for bowel anastomosis in young children may lead to faster operative time without affecting intestinal growth. Copyright © 2016 Elsevier Inc. All rights reserved.
The use of models to predict potential contamination aboard orbital vehicles
NASA Technical Reports Server (NTRS)
Boraas, Martin E.; Seale, Dianne B.
1989-01-01
A model of fungal growth on air-exposed, nonnutritive solid surfaces, developed for utilization aboard orbital vehicles is presented. A unique feature of this testable model is that the development of a fungal mycelium can facilitate its own growth by condensation of water vapor from its environment directly onto fungal hyphae. The fungal growth rate is limited by the rate of supply of volatile nutrients and fungal biomass is limited by either the supply of nonvolatile nutrients or by metabolic loss processes. The model discussed is structurally simple, but its dynamics can be quite complex. Biofilm accumulation can vary from a simple linear increase to sustained exponential growth, depending on the values of the environmental variable and model parameters. The results of the model are consistent with data from aquatic biofilm studies, insofar as the two types of systems are comparable. It is shown that the model presented is experimentally testable and provides a platform for the interpretation of observational data that may be directly relevant to the question of growth of organisms aboard the proposed Space Station.
A Simple Model of Hox Genes: Bone Morphology Demonstration
ERIC Educational Resources Information Center
Shmaefsky, Brian
2008-01-01
Visual demonstrations of abstract scientific concepts are effective strategies for enhancing content retention (Shmaefsky 2004). The concepts associated with gene regulation of growth and development are particularly complex and are well suited for teaching with visual models. This demonstration provides a simple and accurate model of Hox gene…
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.
Quality and Growth Implications of Incremental Costing Models for Distance Education Units
ERIC Educational Resources Information Center
Crawford, C. B.; Gould, Lawrence V.; King, Dennis; Parker, Carl
2010-01-01
The purpose of this article is to explore quality and growth implications emergent from various incremental costing models applied to distance education units. Prior research relative to costing models and three competing costing models useful in the current distance education environment are discussed. Specifically, the simple costing model, unit…
Adjusting STEMS growth model for Wisconsin forests.
Margaret R. Holdaway
1985-01-01
Describes a simple procedure for adjusting growth in the STEMS regional tree growth model to compensate for subregional differences. Coefficients are reported to adjust Lake States STEMS to the forests of Northern and Central Wisconsin--an area of essentially uniform climate and similar broad physiographic features. Errors are presented for various combinations of...
ZIMOD: A Simple Computer Model of the Zimbabwean Economy.
ERIC Educational Resources Information Center
Knox, Jon; And Others
1988-01-01
This paper describes a rationale for the construction and use of a simple consistency model of the Zimbabwean economy that incorporates an input-output matrix. The model is designed to investigate alternative industrial strategies and their consequences for the balance of payments, consumption, and overall gross domestic product growth for a…
Modeling the growth and branching of plants: A simple rod-based model
NASA Astrophysics Data System (ADS)
Faruk Senan, Nur Adila; O'Reilly, Oliver M.; Tresierras, Timothy N.
A rod-based model for plant growth and branching is developed in this paper. Specifically, Euler's theory of the elastica is modified to accommodate growth and remodeling. In addition, branching is characterized using a configuration force and evolution equations are postulated for the flexural stiffness and intrinsic curvature. The theory is illustrated with examples of multiple static equilibria of a branched plant and the remodeling and tip growth of a plant stem under gravitational loading.
Setaria viridis floral-dip: A simple and rapid Agrobacterium-medicated transformation method
USDA-ARS?s Scientific Manuscript database
Setaria viridis was recently described as a new monocotyledonous model species for C4 photosynthesis research and genetic transformation. It has biological attributes (rapid life cycle, small genome, diploid, short stature and simple growth requirements) that make it suitable for use as a model plan...
Analytic derivation of bacterial growth laws from a simple model of intracellular chemical dynamics.
Pandey, Parth Pratim; Jain, Sanjay
2016-09-01
Experiments have found that the growth rate and certain other macroscopic properties of bacterial cells in steady-state cultures depend upon the medium in a surprisingly simple manner; these dependencies are referred to as 'growth laws'. Here we construct a dynamical model of interacting intracellular populations to understand some of the growth laws. The model has only three population variables: an amino acid pool, a pool of enzymes that transport an external nutrient and produce the amino acids, and ribosomes that catalyze their own and the enzymes' production from the amino acids. We assume that the cell allocates its resources between the enzyme sector and the ribosomal sector to maximize its growth rate. We show that the empirical growth laws follow from this assumption and derive analytic expressions for the phenomenological parameters in terms of the more basic model parameters. Interestingly, the maximization of the growth rate of the cell as a whole implies that the cell allocates resources to the enzyme and ribosomal sectors in inverse proportion to their respective 'efficiencies'. The work introduces a mathematical scheme in which the cellular growth rate can be explicitly determined and shows that two large parameters, the number of amino acid residues per enzyme and per ribosome, are useful for making approximations.
Bayesian Analysis of Longitudinal Data Using Growth Curve Models
ERIC Educational Resources Information Center
Zhang, Zhiyong; Hamagami, Fumiaki; Wang, Lijuan Lijuan; Nesselroade, John R.; Grimm, Kevin J.
2007-01-01
Bayesian methods for analyzing longitudinal data in social and behavioral research are recommended for their ability to incorporate prior information in estimating simple and complex models. We first summarize the basics of Bayesian methods before presenting an empirical example in which we fit a latent basis growth curve model to achievement data…
Exponential growth kinetics for Polyporus versicolor and Pleurotus ostreatus in submerged culture
DOE Office of Scientific and Technical Information (OSTI.GOV)
Carroad, P.A.; Wilke, C.R.
1977-04-01
Simple mathematical models for a batch culture of pellet-forming fungi in submerged culture were tested on growth data for Polyporus versicolor (ATCC 12679) and Pleurotus ostreatus (ATCC 9415). A kinetic model based on a growth rate proportional to the two-thirds power of the cell mass was shown to be satisfactory. A model based on a growth rate directly proportional to the cell mass fitted the data equally well, however, and may be preferable because of mathematical simplicity.
van Mantgem, P.J.; Stephenson, N.L.
2005-01-01
1 We assess the use of simple, size-based matrix population models for projecting population trends for six coniferous tree species in the Sierra Nevada, California. We used demographic data from 16 673 trees in 15 permanent plots to create 17 separate time-invariant, density-independent population projection models, and determined differences between trends projected from initial surveys with a 5-year interval and observed data during two subsequent 5-year time steps. 2 We detected departures from the assumptions of the matrix modelling approach in terms of strong growth autocorrelations. We also found evidence of observation errors for measurements of tree growth and, to a more limited degree, recruitment. Loglinear analysis provided evidence of significant temporal variation in demographic rates for only two of the 17 populations. 3 Total population sizes were strongly predicted by model projections, although population dynamics were dominated by carryover from the previous 5-year time step (i.e. there were few cases of recruitment or death). Fractional changes to overall population sizes were less well predicted. Compared with a null model and a simple demographic model lacking size structure, matrix model projections were better able to predict total population sizes, although the differences were not statistically significant. Matrix model projections were also able to predict short-term rates of survival, growth and recruitment. Mortality frequencies were not well predicted. 4 Our results suggest that simple size-structured models can accurately project future short-term changes for some tree populations. However, not all populations were well predicted and these simple models would probably become more inaccurate over longer projection intervals. The predictive ability of these models would also be limited by disturbance or other events that destabilize demographic rates. ?? 2005 British Ecological Society.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Zhang, Damao; Wang, Zhien; Heymsfield, Andrew J.
Measurement of ice number concentration in clouds is important but still challenging. Stratiform mixed-phase clouds (SMCs) provide a simple scenario for retrieving ice number concentration from remote sensing measurements. The simple ice generation and growth pattern in SMCs offers opportunities to use cloud radar reflectivity (Ze) measurements and other cloud properties to infer ice number concentration quantitatively. To understand the strong temperature dependency of ice habit and growth rate quantitatively, we develop a 1-D ice growth model to calculate the ice diffusional growth along its falling trajectory in SMCs. The radar reflectivity and fall velocity profiles of ice crystals calculatedmore » from the 1-D ice growth model are evaluated with the Atmospheric Radiation Measurements (ARM) Climate Research Facility (ACRF) ground-based high vertical resolution radar measurements. Combining Ze measurements and 1-D ice growth model simulations, we develop a method to retrieve the ice number concentrations in SMCs at given cloud top temperature (CTT) and liquid water path (LWP). The retrieved ice concentrations in SMCs are evaluated with in situ measurements and with a three-dimensional cloud-resolving model simulation with a bin microphysical scheme. These comparisons show that the retrieved ice number concentrations are within an uncertainty of a factor of 2, statistically.« less
Growth and yield models for central hardwoods
Martin E. Dale; Donald E. Hilt
1989-01-01
Over the last 20 years computers have become an efficient tool to estimate growth and yield. Computerized yield estimates vary from simple approximation or interpolation of traditional normal yield tables to highly sophisticated programs that simulate the growth and yield of each individual tree.
Simulations of Quantum Dot Growth on Semiconductor Surfaces: Morphological Design of Sensor Concepts
2008-12-01
size equalization can be clearly illustrated during the growth process. In this work we develop a fast multiscale 3D kinetic Monte Carlo ( KMC ) QD...model will provide an attractive means for producing predictably ordered nanostructures. MODEL DESCRIPTION The 3D layer-by-layer KMC growth model...Voter, 2001) and KMC simulation experience (Pan et al., 2004; Pan et al., 2006; Meixner et al, 2003) in 2D, we therefore propose the following simple
Cylindrically symmetric Green's function approach for modeling the crystal growth morphology of ice.
Libbrecht, K G
1999-08-01
We describe a front-tracking Green's function approach to modeling cylindrically symmetric crystal growth. This method is simple to implement, and with little computer power can adequately model a wide range of physical situations. We apply the method to modeling the hexagonal prism growth of ice crystals, which is governed primarily by diffusion along with anisotropic surface kinetic processes. From ice crystal growth observations in air, we derive measurements of the kinetic growth coefficients for the basal and prism faces as a function of temperature, for supersaturations near the water saturation level. These measurements are interpreted in the context of a model for the nucleation and growth of ice, in which the growth dynamics are dominated by the structure of a disordered layer on the ice surfaces.
Using Simple and Complex Growth Models to Articulate Developmental Change: Matching Theory to Method
ERIC Educational Resources Information Center
Ram, Nilam; Grimm, Kevin
2007-01-01
Growth curve modeling has become a mainstay in the study of development. In this article we review some of the flexibility provided by this technique for describing and testing hypotheses about: (1) intraindividual change across multiple occasions of measurement, and (2) interindividual differences in intraindividual change. Through empirical…
Glycolysis Is Governed by Growth Regime and Simple Enzyme Regulation in Adherent MDCK Cells
Rehberg, Markus; Ritter, Joachim B.; Reichl, Udo
2014-01-01
Due to its vital importance in the supply of cellular pathways with energy and precursors, glycolysis has been studied for several decades regarding its capacity and regulation. For a systems-level understanding of the Madin-Darby canine kidney (MDCK) cell metabolism, we couple a segregated cell growth model published earlier with a structured model of glycolysis, which is based on relatively simple kinetics for enzymatic reactions of glycolysis, to explain the pathway dynamics under various cultivation conditions. The structured model takes into account in vitro enzyme activities, and links glycolysis with pentose phosphate pathway and glycogenesis. Using a single parameterization, metabolite pool dynamics during cell cultivation, glucose limitation and glucose pulse experiments can be consistently reproduced by considering the cultivation history of the cells. Growth phase-dependent glucose uptake together with cell-specific volume changes generate high intracellular metabolite pools and flux rates to satisfy the cellular demand during growth. Under glucose limitation, the coordinated control of glycolytic enzymes re-adjusts the glycolytic flux to prevent the depletion of glycolytic intermediates. Finally, the model's predictive power supports the design of more efficient bioprocesses. PMID:25329309
Glycolysis is governed by growth regime and simple enzyme regulation in adherent MDCK cells.
Rehberg, Markus; Ritter, Joachim B; Reichl, Udo
2014-10-01
Due to its vital importance in the supply of cellular pathways with energy and precursors, glycolysis has been studied for several decades regarding its capacity and regulation. For a systems-level understanding of the Madin-Darby canine kidney (MDCK) cell metabolism, we couple a segregated cell growth model published earlier with a structured model of glycolysis, which is based on relatively simple kinetics for enzymatic reactions of glycolysis, to explain the pathway dynamics under various cultivation conditions. The structured model takes into account in vitro enzyme activities, and links glycolysis with pentose phosphate pathway and glycogenesis. Using a single parameterization, metabolite pool dynamics during cell cultivation, glucose limitation and glucose pulse experiments can be consistently reproduced by considering the cultivation history of the cells. Growth phase-dependent glucose uptake together with cell-specific volume changes generate high intracellular metabolite pools and flux rates to satisfy the cellular demand during growth. Under glucose limitation, the coordinated control of glycolytic enzymes re-adjusts the glycolytic flux to prevent the depletion of glycolytic intermediates. Finally, the model's predictive power supports the design of more efficient bioprocesses.
A simple 2D biofilm model yields a variety of morphological features.
Hermanowicz, S W
2001-01-01
A two-dimensional biofilm model was developed based on the concept of cellular automata. Three simple, generic processes were included in the model: cell growth, internal and external mass transport and cell detachment (erosion). The model generated a diverse range of biofilm morphologies (from dense layers to open, mushroom-like forms) similar to those observed in real biofilm systems. Bulk nutrient concentration and external mass transfer resistance had a large influence on the biofilm structure.
Brain tumor modeling: glioma growth and interaction with chemotherapy
NASA Astrophysics Data System (ADS)
Banaem, Hossein Y.; Ahmadian, Alireza; Saberi, Hooshangh; Daneshmehr, Alireza; Khodadad, Davood
2011-10-01
In last decade increasingly mathematical models of tumor growths have been studied, particularly on solid tumors which growth mainly caused by cellular proliferation. In this paper we propose a modified model to simulate the growth of gliomas in different stages. Glioma growth is modeled by a reaction-advection-diffusion. We begin with a model of untreated gliomas and continue with models of polyclonal glioma following chemotherapy. From relatively simple assumptions involving homogeneous brain tissue bounded by a few gross anatomical landmarks (ventricles and skull) the models have been expanded to include heterogeneous brain tissue with different motilities of glioma cells in grey and white matter. Tumor growth is characterized by a dangerous change in the control mechanisms, which normally maintain a balance between the rate of proliferation and the rate of apoptosis (controlled cell death). Result shows that this model closes to clinical finding and can simulate brain tumor behavior properly.
Paul, Nicholas A; Svensson, Carl Johan; de Nys, Rocky; Steinberg, Peter D
2014-01-01
All of the theory and most of the data on the ecology and evolution of chemical defences derive from terrestrial plants, which have considerable capacity for internal movement of resources. In contrast, most macroalgae--seaweeds--have no or very limited capacity for resource translocation, meaning that trade-offs between growth and defence, for example, should be localised rather than systemic. This may change the predictions of chemical defence theories for seaweeds. We developed a model that mimicked the simple growth pattern of the red seaweed Asparagopsis armata which is composed of repeating clusters of somatic cells and cells which contain deterrent secondary chemicals (gland cells). To do this we created a distinct growth curve for the somatic cells and another for the gland cells using empirical data. The somatic growth function was linked to the growth function for defence via differential equations modelling, which effectively generated a trade-off between growth and defence as these neighbouring cells develop. By treating growth and defence as separate functions we were also able to model a trade-off in growth of 2-3% under most circumstances. However, we found contrasting evidence for this trade-off in the empirical relationships between growth and defence, depending on the light level under which the alga was cultured. After developing a model that incorporated both branching and cell division rates, we formally demonstrated that positive correlations between growth and defence are predicted in many circumstances and also that allocation costs, if they exist, will be constrained by the intrinsic growth patterns of the seaweed. Growth patterns could therefore explain contrasting evidence for cost of constitutive chemical defence in many studies, highlighting the need to consider the fundamental biology and ontogeny of organisms when assessing the allocation theories for defence.
Phase-field crystal modeling of heteroepitaxy and exotic modes of crystal nucleation
NASA Astrophysics Data System (ADS)
Podmaniczky, Frigyes; Tóth, Gyula I.; Tegze, György; Pusztai, Tamás; Gránásy, László
2017-01-01
We review recent advances made in modeling heteroepitaxy, two-step nucleation, and nucleation at the growth front within the framework of a simple dynamical density functional theory, the Phase-Field Crystal (PFC) model. The crystalline substrate is represented by spatially confined periodic potentials. We investigate the misfit dependence of the critical thickness in the StranskiKrastanov growth mode in isothermal studies. Apparently, the simulation results for stress release via the misfit dislocations fit better to the PeopleBean model than to the one by Matthews and Blakeslee. Next, we investigate structural aspects of two-step crystal nucleation at high undercoolings, where an amorphous precursor forms in the first stage. Finally, we present results for the formation of new grains at the solid-liquid interface at high supersaturations/supercoolings, a phenomenon termed Growth Front Nucleation (GFN). Results obtained with diffusive dynamics (applicable to colloids) and with a hydrodynamic extension of the PFC theory (HPFC, developed for simple liquids) will be compared. The HPFC simulations indicate two possible mechanisms for GFN.
ERIC Educational Resources Information Center
Chou, Yuan K.
2007-01-01
The author devises a simple way of incorporating the financial sector into a growth model that is pedagogically useful. Financial innovation raises the efficiency of financial intermediation by increasing the variety of financial products and services, resulting in improved matching of the needs of individual savers with those of firms raising…
Social Trust and the Growth of Schooling
ERIC Educational Resources Information Center
Bjornskov, Christian
2009-01-01
The paper develops a simple model to examine how social trust might affect the growth of schooling through lowering transaction costs associated with employing educated individuals. In a sample of 52 countries, the paper thereafter provides empirical evidence that trust has led to faster growth of schooling in the period 1960-2000. The findings…
Fun Microbiology: How To Measure Growth of a Fungus.
ERIC Educational Resources Information Center
Mitchell, James K.; And Others
1997-01-01
Describes an experiment to demonstrate a simple method for measuring fungus growth by monitoring the effect of temperature on the growth of Trichoderma viride. Among the advantages that this experimental model provides is introducing students to the importance of using the computer as a scientific tool for analyzing and presenting data. (AIM)
DOE Office of Scientific and Technical Information (OSTI.GOV)
Pinches, A.; Pallent, L.J.
1986-10-01
Rate and yield information relating to biomass and product formation and to nitrogen, glucose and oxygen consumption are described for xanthan gum batch fermentations in which both chemically defined (glutamate nitrogen) and complex (peptone nitrogen) media are employed. Simple growth and product models are used for data interpretation. For both nitrogen sources, rate and yield parameter estimates are shown to be independent of initial nitrogen concentrations. For stationary phases, specific rates of gum production are shown to be independent of nitrogen source but dependent on initial nitrogen concentration. The latter is modeled empirically and suggests caution in applying simple productmore » models to xanthan gum fermentations. 13 references.« less
Population Genetics of Three Dimensional Range Expansions
NASA Astrophysics Data System (ADS)
Lavrentovich, Maxim; Nelson, David
2014-03-01
We develop a simple model of genetic diversity in growing spherical cell clusters, where the growth is confined to the cluster surface. This kind of growth occurs in cells growing in soft agar, and can also serve as a simple model of avascular tumors. Mutation-selection balance in these radial expansions is strongly influenced by scaling near a neutral, voter model critical point and by the inflating frontier. We develop a scaling theory to describe how the dynamics of mutation-selection balance is cut off by inflation. Genetic drift, i.e., local fluctuations in the genetic diversity, also plays an important role, and can lead to the extinction even of selectively advantageous strains. We calculate this extinction probability, taking into account the effect of rough population frontiers.
Two Growth Modes of Graphitic Carbon Nanofibers with Herring-Bone Structure
DOE Office of Scientific and Technical Information (OSTI.GOV)
Merkulov, Igor A; Melechko, Anatoli Vasilievich; Wells, Jack C
2005-01-01
A simple mathematical model of the carbon nanofiber catalytic growth process is presented. Two major types of the fiber-catalyst interface shapes have been identified and described having qualitatively different structure in the center of a nanofiber. Presently, we discuss that the appearance of the irregular structure in the nanofiber central area is a result of curved-interface-growth kinematics. We suggest the method to determine the phenomenological parameters of the developed model from experimental data.
Two growth modes of graphitic carbon nanofibers with herring-bone structure
NASA Astrophysics Data System (ADS)
Merkulov, I. A.; Meleshko, A. V.; Wells, J. C.; Cui, H.; Merkulov, V. I.; Simpson, M. L.; Lowndes, D. H.
2005-07-01
A simple mathematical model of the carbon nanofiber catalytic growth process is presented. Two major types of the fiber-catalyst interface shapes have been identified and described having qualitatively different structure in the center of a nanofiber. Presently, we discuss that the appearance of the irregular structure in the nanofiber central area is a result of curved-interface-growth kinematics. We suggest the method to determine the phenomenological parameters of the developed model from experimental data.
NASA Astrophysics Data System (ADS)
Jaiswal, D.; Long, S.; Parton, W. J.; Hartman, M.
2012-12-01
A coupled modeling system of crop growth model (BioCro) and biogeochemical model (DayCent) has been developed to assess the two-way interactions between plant growth and biogeochemistry. Crop growth in BioCro is simulated using a detailed mechanistic biochemical and biophysical multi-layer canopy model and partitioning of dry biomass into different plant organs according to phenological stages. Using hourly weather records, the model partitions light between dynamically changing sunlit and shaded portions of the canopy and computes carbon and water exchange with the atmosphere and through the canopy for each hour of the day, each day of the year. The model has been parameterized for the bioenergy crops sugarcane, Miscanthus and switchgrass, and validation has shown it to predict growth cycles and partitioning of biomass to a high degree of accuracy. As such it provides an ideal input for a soil biogeochemical model. DayCent is an established model for predicting long-term changes in soil C & N and soil-atmosphere exchanges of greenhouse gases. At present, DayCent uses a relatively simple productivity model. In this project BioCro has replaced this simple model to provide DayCent with a productivity and growth model equal in detail to its biogeochemistry. Dynamic coupling of these two models to produce CroCent allows for differential C: N ratios of litter fall (based on rates of senescence of different plant organs) and calibration of the model for realistic plant productivity in a mechanistic way. A process-based approach to modeling plant growth is needed for bioenergy crops because research on these crops (especially second generation feedstocks) has started only recently, and detailed agronomic information for growth, yield and management is too limited for effective empirical models. The coupled model provides means to test and improve the model against high resolution data, such as that obtained by eddy covariance and explore yield implications of different crop and soil management.
Is Decoupling GDP Growth from Environmental Impact Possible?
Ward, James D; Sutton, Paul C; Werner, Adrian D; Costanza, Robert; Mohr, Steve H; Simmons, Craig T
2016-01-01
The argument that human society can decouple economic growth-defined as growth in Gross Domestic Product (GDP)-from growth in environmental impacts is appealing. If such decoupling is possible, it means that GDP growth is a sustainable societal goal. Here we show that the decoupling concept can be interpreted using an easily understood model of economic growth and environmental impact. The simple model is compared to historical data and modelled projections to demonstrate that growth in GDP ultimately cannot be decoupled from growth in material and energy use. It is therefore misleading to develop growth-oriented policy around the expectation that decoupling is possible. We also note that GDP is increasingly seen as a poor proxy for societal wellbeing. GDP growth is therefore a questionable societal goal. Society can sustainably improve wellbeing, including the wellbeing of its natural assets, but only by discarding GDP growth as the goal in favor of more comprehensive measures of societal wellbeing.
A monomer-trimer model supports intermittent glucagon fibril growth
NASA Astrophysics Data System (ADS)
Košmrlj, Andrej; Cordsen, Pia; Kyrsting, Anders; Otzen, Daniel E.; Oddershede, Lene B.; Jensen, Mogens H.
2015-03-01
We investigate in vitro fibrillation kinetics of the hormone peptide glucagon at various concentrations using confocal microscopy and determine the glucagon fibril persistence length 60μm. At all concentrations we observe that periods of individual fibril growth are interrupted by periods of stasis. The growth probability is large at high and low concentrations and is reduced for intermediate glucagon concentrations. To explain this behavior we propose a simple model, where fibrils come in two forms, one built entirely from glucagon monomers and one entirely from glucagon trimers. The opposite building blocks act as fibril growth blockers, and this generic model reproduces experimental behavior well.
A new computational growth model for sea urchin skeletons.
Zachos, Louis G
2009-08-07
A new computational model has been developed to simulate growth of regular sea urchin skeletons. The model incorporates the processes of plate addition and individual plate growth into a composite model of whole-body (somatic) growth. A simple developmental model based on hypothetical morphogens underlies the assumptions used to define the simulated growth processes. The data model is based on a Delaunay triangulation of plate growth center points, using the dual Voronoi polygons to define plate topologies. A spherical frame of reference is used for growth calculations, with affine deformation of the sphere (based on a Young-Laplace membrane model) to result in an urchin-like three-dimensional form. The model verifies that the patterns of coronal plates in general meet the criteria of Voronoi polygonalization, that a morphogen/threshold inhibition model for plate addition results in the alternating plate addition pattern characteristic of sea urchins, and that application of the Bertalanffy growth model to individual plates results in simulated somatic growth that approximates that seen in living urchins. The model suggests avenues of research that could explain some of the distinctions between modern sea urchins and the much more disparate groups of forms that characterized the Paleozoic Era.
Two Sides of the Same Coin: U. S. "Residual" Inequality and the Gender Gap
ERIC Educational Resources Information Center
Bacolod, Marigee P.; Blum, Bernardo S.
2010-01-01
We show that the narrowing gender gap and the growth in earnings inequality are consistent with a simple model in which skills are heterogeneous, and the growth in skill prices has been particularly strong for skills with which women are well endowed. Empirical analysis of DOT, CPS, and NLSY79 data finds evidence to support this model. A large…
A simple marriage model for the power-law behaviour in the frequency distributions of family names
NASA Astrophysics Data System (ADS)
Wu, Hao-Yun; Chou, Chung-I.; Tseng, Jie-Jun
2011-01-01
In many countries, the frequency distributions of family names are found to decay as a power law with an exponent ranging from 1.0 to 2.2. In this work, we propose a simple marriage model which can reproduce this power-law behaviour. Our model, based on the evolution of families, consists of the growth of big families and the formation of new families. Preliminary results from the model show that the name distributions are in good agreement with empirical data from Taiwan and Norway.
FARSITE: Fire Area Simulator-model development and evaluation
Mark A. Finney
1998-01-01
A computer simulation model, FARSITE, includes existing fire behavior models for surface, crown, spotting, point-source fire acceleration, and fuel moisture. The model's components and assumptions are documented. Simulations were run for simple conditions that illustrate the effect of individual fire behavior models on two-dimensional fire growth.
Complex Autocatalysis in Simple Chemistries.
Virgo, Nathaniel; Ikegami, Takashi; McGregor, Simon
2016-01-01
Life on Earth must originally have arisen from abiotic chemistry. Since the details of this chemistry are unknown, we wish to understand, in general, which types of chemistry can lead to complex, lifelike behavior. Here we show that even very simple chemistries in the thermodynamically reversible regime can self-organize to form complex autocatalytic cycles, with the catalytic effects emerging from the network structure. We demonstrate this with a very simple but thermodynamically reasonable artificial chemistry model. By suppressing the direct reaction from reactants to products, we obtain the simplest kind of autocatalytic cycle, resulting in exponential growth. When these simple first-order cycles are prevented from forming, the system achieves superexponential growth through more complex, higher-order autocatalytic cycles. This leads to nonlinear phenomena such as oscillations and bistability, the latter of which is of particular interest regarding the origins of life.
A computational method for optimizing fuel treatment locations
Mark A. Finney
2006-01-01
Modeling and experiments have suggested that spatial fuel treatment patterns can influence the movement of large fires. On simple theoretical landscapes consisting of two fuel types (treated and untreated) optimal patterns can be analytically derived that disrupt fire growth efficiently (i.e. with less area treated than random patterns). Although conceptually simple,...
Promoting Teacher Growth through Lesson Study: A Culturally Embedded Approach
ERIC Educational Resources Information Center
Ebaeguin, Marlon
2015-01-01
Lesson Study has captured the attention of many international educators with its promise of improved student learning and sustained teacher growth. Lesson Study, however, has cultural underpinnings that a simple transference model overlooks. A culturally embedded approach attends to the existing cultural orientations and values of host schools.…
Functional and Structural Optimality in Plant Growth: A Crop Modelling Case Study
NASA Astrophysics Data System (ADS)
Caldararu, S.; Purves, D. W.; Smith, M. J.
2014-12-01
Simple mechanistic models of vegetation processes are essential both to our understanding of plant behaviour and to our ability to predict future changes in vegetation. One concept that can take us closer to such models is that of plant optimality, the hypothesis that plants aim to achieve an optimal state. Conceptually, plant optimality can be either structural or functional optimality. A structural constraint would mean that plants aim to achieve a certain structural characteristic such as an allometric relationship or nutrient content that allows optimal function. A functional condition refers to plants achieving optimal functionality, in most cases by maximising carbon gain. Functional optimality conditions are applied on shorter time scales and lead to higher plasticity, making plants more adaptable to changes in their environment. In contrast, structural constraints are optimal given the specific environmental conditions that plants are adapted to and offer less flexibility. We exemplify these concepts using a simple model of crop growth. The model represents annual cycles of growth from sowing date to harvest, including both vegetative and reproductive growth and phenology. Structural constraints to growth are represented as an optimal C:N ratio in all plant organs, which drives allocation throughout the vegetative growing stage. Reproductive phenology - i.e. the onset of flowering and grain filling - is determined by a functional optimality condition in the form of maximising final seed mass, so that vegetative growth stops when the plant reaches maximum nitrogen or carbon uptake. We investigate the plants' response to variations in environmental conditions within these two optimality constraints and show that final yield is most affected by changes during vegetative growth which affect the structural constraint.
Implications of Biospheric Energization
NASA Astrophysics Data System (ADS)
Budding, Edd; Demircan, Osman; Gündüz, Güngör; Emin Özel, Mehmet
2016-07-01
Our physical model relating to the origin and development of lifelike processes from very simple beginnings is reviewed. This molecular ('ABC') process is compared with the chemoton model, noting the role of the autocatalytic tuning to the time-dependent source of energy. This substantiates a Darwinian character to evolution. The system evolves from very simple beginnings to a progressively more highly tuned, energized and complex responding biosphere, that grows exponentially; albeit with a very low net growth factor. Rates of growth and complexity in the evolution raise disturbing issues of inherent stability. Autocatalytic processes can include a fractal character to their development allowing recapitulative effects to be observed. This property, in allowing similarities of pattern to be recognized, can be useful in interpreting complex (lifelike) systems.
NASA Astrophysics Data System (ADS)
Valencia, Hubert; Kangawa, Yoshihiro; Kakimoto, Koichi
2015-12-01
GaAs(100) c(4×4) surfaces were examined by ab initio calculations, under As2, H2 and N2 gas mixed conditions as a model for GaAs1-xNx vapor-phase epitaxy (VPE) on GaAs(100). Using a simple model consisting of As2 and H2 molecules adsorptions and As/N atom substitutions, it was shown to be possible to examine the crystal growth behavior considering the relative stability of the resulting surfaces against the chemical potential of As2, H2 and N2 gases. Such simple model allows us to draw a picture of the temperature and pressure stability domains for each surfaces that can be linked to specific growth conditions, directly. We found that, using this simple model, it is possible to explain the different N-incorporation regimes observed experimentally at different temperatures, and to predict the transition temperature between these regimes. Additionally, a rational explanation of N-incorporation ratio for each of these regimes is provided. Our model should then lead to a better comprehension and control of the experimental conditions needed to realize a high quality VPE of GaAs1-xNx.
Phase transition in tumor growth: I avascular development
NASA Astrophysics Data System (ADS)
Izquierdo-Kulich, E.; Rebelo, I.; Tejera, E.; Nieto-Villar, J. M.
2013-12-01
We propose a mechanism for avascular tumor growth based on a simple chemical network. This model presents a logistic behavior and shows a “second order” phase transition. We prove the fractal origin of the empirical logistics and Gompertz constant and its relation to mitosis and apoptosis rate. Finally, the thermodynamics framework developed demonstrates the entropy production rate as a Lyapunov function during avascular tumor growth.
Concepts in solid tumor evolution.
Sidow, Arend; Spies, Noah
2015-04-01
Evolutionary mechanisms in cancer progression give tumors their individuality. Cancer evolution is different from organismal evolution, however, and we discuss where concepts from evolutionary genetics are useful or limited in facilitating an understanding of cancer. Based on these concepts we construct and apply the simplest plausible model of tumor growth and progression. Simulations using this simple model illustrate the importance of stochastic events early in tumorigenesis, highlight the dominance of exponential growth over linear growth and differentiation, and explain the clonal substructure of tumors. Copyright © 2015 Elsevier Ltd. All rights reserved.
Tubular growth and bead formation in the lyotropic lamellar phase of a lipid.
Bhatia, Tripta; Hatwalne, Yashodhan; Madhusudana, N V
2015-07-28
We use fluorescence confocal polarised microscopy (FCPM) to study tubular growth upon hydration of dry DOPC (1,2-dioleoyl-sn-glycero-3-phosphocholine) in water and water-glycerol mixtures. We have developed a model to relate the FCPM intensity profiles to the multilamellar structures of the tubules. Insertion of an additional patch inside a tubule produces a beaded structure, while a straight configuration is retained if the growth is on the outside. We use a simple model to suggest that reduction in overall curvature energy drives bead formation.
Predicting the cover-up of dead branches using a simple single regressor equation
Christopher M. Oswalt; Wayne K. Clatterbuck; E.C. Burkhardt
2007-01-01
Information on the effects of branch diameter on branch occlusion is necessary for building models capable of forecasting the effect of management decisions on tree or log grade. We investigated the relationship between branch size and subsequent branch occlusion through diameter growth with special attention toward the development of a simple single regressor equation...
USDA-ARS?s Scientific Manuscript database
Predicting impacts of the magnitude and seasonal timing of rainfall pulses in water-limited grassland ecosystems concerns ecologists, climate scientists, hydrologists, and a variety of stakeholders. This report describes a simple, effective procedure to emulate the seasonal response of grassland bio...
Growth of semimetallic ErAs films epitaxially embedded in GaAs
NASA Astrophysics Data System (ADS)
Crook, Adam M.; Nair, Hari P.; Lee, Jong H.; Ferrer, Domingo A.; Akinwande, Deji; Bank, Seth R.
2011-10-01
We present models for the growth and electrical conductivity of ErAs films grown with the nanoparticle-seeded film growth technique. This growth mode overcomes the mismatch in rotational symmetry between the rocksalt ErAs crystal structure and the zincblende GaAs crystal structure. This results in films of ErAs grown through a thin film of GaAs that preserves the symmetry of the substrate. The conductivity of the films, as a function of film thickness, are investigated and a surface roughness model is used to explain observed trends. Transmission electron micrographs confirm the suppression of anti-phase domains. A simple diffusion model is developed to describe the diffusion and incorporation of surface erbium into subsurface ErAs layers and predict potential failure mechanisms of the growth method.
Is Decoupling GDP Growth from Environmental Impact Possible?
Sutton, Paul C.; Werner, Adrian D.; Costanza, Robert; Mohr, Steve H.; Simmons, Craig T.
2016-01-01
The argument that human society can decouple economic growth—defined as growth in Gross Domestic Product (GDP)—from growth in environmental impacts is appealing. If such decoupling is possible, it means that GDP growth is a sustainable societal goal. Here we show that the decoupling concept can be interpreted using an easily understood model of economic growth and environmental impact. The simple model is compared to historical data and modelled projections to demonstrate that growth in GDP ultimately cannot be decoupled from growth in material and energy use. It is therefore misleading to develop growth-oriented policy around the expectation that decoupling is possible. We also note that GDP is increasingly seen as a poor proxy for societal wellbeing. GDP growth is therefore a questionable societal goal. Society can sustainably improve wellbeing, including the wellbeing of its natural assets, but only by discarding GDP growth as the goal in favor of more comprehensive measures of societal wellbeing. PMID:27741300
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.
Measuring and Modeling the Growth Dynamics of Self-Catalyzed GaP Nanowire Arrays.
Oehler, Fabrice; Cattoni, Andrea; Scaccabarozzi, Andrea; Patriarche, Gilles; Glas, Frank; Harmand, Jean-Christophe
2018-02-14
The bottom-up fabrication of regular nanowire (NW) arrays on a masked substrate is technologically relevant, but the growth dynamic is rather complex due to the superposition of severe shadowing effects that vary with array pitch, NW diameter, NW height, and growth duration. By inserting GaAsP marker layers at a regular time interval during the growth of a self-catalyzed GaP NW array, we are able to retrieve precisely the time evolution of the diameter and height of a single NW. We then propose a simple numerical scheme which fully computes shadowing effects at play in infinite arrays of NWs. By confronting the simulated and experimental results, we infer that re-emission of Ga from the mask is necessary to sustain the NW growth while Ga migration on the mask must be negligible. When compared to random cosine or random uniform re-emission from the mask, the simple case of specular reflection on the mask gives the most accurate account of the Ga balance during the growth.
A dynamic model for tumour growth and metastasis formation.
Haustein, Volker; Schumacher, Udo
2012-07-05
A simple and fast computational model to describe the dynamics of tumour growth and metastasis formation is presented. The model is based on the calculation of successive generations of tumour cells and enables one to describe biologically important entities like tumour volume, time point of 1st metastatic growth or number of metastatic colonies at a given time. The model entirely relies on the chronology of these successive events of the metastatic cascade. The simulation calculations were performed for two embedded growth models to describe the Gompertzian like growth behaviour of tumours. The initial training of the models was carried out using an analytical solution for the size distribution of metastases of a hepatocellular carcinoma. We then show the applicability of our models to clinical data from the Munich Cancer Registry. Growth and dissemination characteristics of metastatic cells originating from cells in the primary breast cancer can be modelled thus showing its ability to perform systematic analyses relevant for clinical breast cancer research and treatment. In particular, our calculations show that generally metastases formation has already been initiated before the primary can be detected clinically.
A dynamic model for tumour growth and metastasis formation
2012-01-01
A simple and fast computational model to describe the dynamics of tumour growth and metastasis formation is presented. The model is based on the calculation of successive generations of tumour cells and enables one to describe biologically important entities like tumour volume, time point of 1st metastatic growth or number of metastatic colonies at a given time. The model entirely relies on the chronology of these successive events of the metastatic cascade. The simulation calculations were performed for two embedded growth models to describe the Gompertzian like growth behaviour of tumours. The initial training of the models was carried out using an analytical solution for the size distribution of metastases of a hepatocellular carcinoma. We then show the applicability of our models to clinical data from the Munich Cancer Registry. Growth and dissemination characteristics of metastatic cells originating from cells in the primary breast cancer can be modelled thus showing its ability to perform systematic analyses relevant for clinical breast cancer research and treatment. In particular, our calculations show that generally metastases formation has already been initiated before the primary can be detected clinically. PMID:22548735
Growth and instability of a phospholipid vesicle in a bath of fatty acids
NASA Astrophysics Data System (ADS)
Dervaux, J.; Noireaux, V.; Libchaber, A. J.
2017-06-01
Using a microfluidic trap, we study the behavior of individual phospholipid vesicles in contact with fatty acids. We show that spontaneous fatty acids insertion inside the bilayer is controlled by the vesicle size, osmotic pressure difference across the membrane and fatty acids concentration in the external bath. Depending on these parameters, vesicles can grow spherically or become unstable and fragment into several daughter vesicles. We establish the phase diagram for vesicle growth and we derive a simple thermodynamic model that reproduces the time evolution of the vesicle volume. Finally, we show that stable growth can be achieved on an artificial cell expressing a simple set of bacterial cytoskeletal proteins, paving the way toward artificial cell reproduction.
Fatigue crack growth with single overload - Measurement and modeling
NASA Technical Reports Server (NTRS)
Davidson, D. L.; Hudak, S. J., Jr.; Dexter, R. J.
1987-01-01
This paper compares experiments with an analytical model of fatigue crack growth under variable amplitude. The stereoimaging technique was used to measure displacements near the tips of fatigue cracks undergoing simple variations in load amplitude-single overloads and overload/underload combinations. Measured displacements were used to compute strains, and stresses were determined from the strains. Local values of crack driving force (Delta-K effective) were determined using both locally measured opening loads and crack tip opening displacements. Experimental results were compared with simulations made for the same load variation conditions using Newman's FAST-2 model. Residual stresses caused by overloads, crack opening loads, and growth retardation periods were compared.
A Numerical and Experimental Study of Damage Growth in a Composite Laminate
NASA Technical Reports Server (NTRS)
McElroy, Mark; Ratcliffe, James; Czabaj, Michael; Wang, John; Yuan, Fuh-Gwo
2014-01-01
The present study has three goals: (1) perform an experiment where a simple laminate damage process can be characterized in high detail; (2) evaluate the performance of existing commercially available laminate damage simulation tools by modeling the experiment; (3) observe and understand the underlying physics of damage in a composite honeycomb sandwich structure subjected to low-velocity impact. A quasi-static indentation experiment has been devised to provide detailed information about a simple mixed-mode damage growth process. The test specimens consist of an aluminum honeycomb core with a cross-ply laminate facesheet supported on a stiff uniform surface. When the sample is subjected to an indentation load, the honeycomb core provides support to the facesheet resulting in a gradual and stable damage growth process in the skin. This enables real time observation as a matrix crack forms, propagates through a ply, and then causes a delamination. Finite element analyses were conducted in ABAQUS/Explicit(TradeMark) 6.13 that used continuum and cohesive modeling techniques to simulate facesheet damage and a geometric and material nonlinear model to simulate core crushing. The high fidelity of the experimental data allows a detailed investigation and discussion of the accuracy of each numerical modeling approach.
Using energy budgets to combine ecology and toxicology in a mammalian sentinel species
NASA Astrophysics Data System (ADS)
Desforges, Jean-Pierre W.; Sonne, Christian; Dietz, Rune
2017-04-01
Process-driven modelling approaches can resolve many of the shortcomings of traditional descriptive and non-mechanistic toxicology. We developed a simple dynamic energy budget (DEB) model for the mink (Mustela vison), a sentinel species in mammalian toxicology, which coupled animal physiology, ecology and toxicology, in order to mechanistically investigate the accumulation and adverse effects of lifelong dietary exposure to persistent environmental toxicants, most notably polychlorinated biphenyls (PCBs). Our novel mammalian DEB model accurately predicted, based on energy allocations to the interconnected metabolic processes of growth, development, maintenance and reproduction, lifelong patterns in mink growth, reproductive performance and dietary accumulation of PCBs as reported in the literature. Our model results were consistent with empirical data from captive and free-ranging studies in mink and other wildlife and suggest that PCB exposure can have significant population-level impacts resulting from targeted effects on fetal toxicity, kit mortality and growth and development. Our approach provides a simple and cross-species framework to explore the mechanistic interactions of physiological processes and ecotoxicology, thus allowing for a deeper understanding and interpretation of stressor-induced adverse effects at all levels of biological organization.
Growth factors, nutrient signaling, and cardiovascular aging.
Fontana, Luigi; Vinciguerra, Manlio; Longo, Valter D
2012-04-13
Growth factors regulated by specific macronutrients have been shown to promote aging and accelerate mortality in the majority of the organisms studied. In particular, the enzymes activated by growth hormone, insulin, and insulin-like growth factor-1 in mammals and their orthologs in simple model organisms represent perhaps the best-understood proteins involved in the aging process. Dietary restriction, which reduces the level of insulin-like growth factor-1 and of other growth factors, has been associated with protection from diabetes, cancer, and cardiovascular diseases, and deficiencies in growth hormone signaling and insulin-like growth factor-1 are strongly associated with protection from cancer and diabetes in both mice and humans; however, their role in cardiac function and cardiovascular diseases is controversial. Here, we review the link between growth factors, cardiac function, and heart disease with focus on the cardioprotective and sensitizing effect of growth factors in both model organisms and humans.
The penny pusher: a cellular model of lens growth.
Shi, Yanrong; De Maria, Alicia; Lubura, Snježana; Šikić, Hrvoje; Bassnett, Steven
2014-12-16
The mechanisms that regulate the number of cells in the lens and, therefore, its size and shape are unknown. We examined the dynamic relationship between proliferative behavior in the epithelial layer and macroscopic lens growth. The distribution of S-phase cells across the epithelium was visualized by confocal microscopy and cell populations were determined from orthographic projections of the lens surface. The number of S-phase cells in the mouse lens epithelium fell exponentially, to an asymptotic value of approximately 200 cells by 6 months. Mitosis became increasingly restricted to a 300-μm-wide swath of equatorial epithelium, the germinative zone (GZ), within which two peaks in labeling index were detected. Postnatally, the cell population increased to approximately 50,000 cells at 4 weeks of age. Thereafter, the number of cells declined, despite continued growth in lens dimensions. This apparently paradoxical observation was explained by a time-dependent increase in the surface area of cells at all locations. The cell biological measurements were incorporated into a physical model, the Penny Pusher. In this simple model, cells were considered to be of a single type, the proliferative behavior of which depended solely on latitude. Simulations using the Penny Pusher predicted the emergence of cell clones and were in good agreement with data obtained from earlier lineage-tracing studies. The Penny Pusher, a simple stochastic model, offers a useful conceptual framework for the investigation of lens growth mechanisms and provides a plausible alternative to growth models that postulate the existence of lens stem cells. Copyright 2015 The Association for Research in Vision and Ophthalmology, Inc.
Direct identification of predator-prey dynamics in gyrokinetic simulations
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kobayashi, Sumire, E-mail: sumire.kobayashi@lpp.polytechnique.fr; Gürcan, Özgür D; Diamond, Patrick H.
2015-09-15
The interaction between spontaneously formed zonal flows and small-scale turbulence in nonlinear gyrokinetic simulations is explored in a shearless closed field line geometry. It is found that when clear limit cycle oscillations prevail, the observed turbulent dynamics can be quantitatively captured by a simple Lotka-Volterra type predator-prey model. Fitting the time traces of full gyrokinetic simulations by such a reduced model allows extraction of the model coefficients. Scanning physical plasma parameters, such as collisionality and density gradient, it was observed that the effective growth rates of turbulence (i.e., the prey) remain roughly constant, in spite of the higher and varyingmore » level of primary mode linear growth rates. The effective growth rate that was extracted corresponds roughly to the zonal-flow-modified primary mode growth rate. It was also observed that the effective damping of zonal flows (i.e., the predator) in the parameter range, where clear predator-prey dynamics is observed, (i.e., near marginal stability) agrees with the collisional damping expected in these simulations. This implies that the Kelvin-Helmholtz-like instability may be negligible in this range. The results imply that when the tertiary instability plays a role, the dynamics becomes more complex than a simple Lotka-Volterra predator prey.« less
Raymer, James; Abel, Guy J.; Rogers, Andrei
2012-01-01
Population projection models that introduce uncertainty are a growing subset of projection models in general. In this paper, we focus on the importance of decisions made with regard to the model specifications adopted. We compare the forecasts and prediction intervals associated with four simple regional population projection models: an overall growth rate model, a component model with net migration, a component model with in-migration and out-migration rates, and a multiregional model with destination-specific out-migration rates. Vector autoregressive models are used to forecast future rates of growth, birth, death, net migration, in-migration and out-migration, and destination-specific out-migration for the North, Midlands and South regions in England. They are also used to forecast different international migration measures. The base data represent a time series of annual data provided by the Office for National Statistics from 1976 to 2008. The results illustrate how both the forecasted subpopulation totals and the corresponding prediction intervals differ for the multiregional model in comparison to other simpler models, as well as for different assumptions about international migration. The paper ends end with a discussion of our results and possible directions for future research. PMID:23236221
Accumulated distribution of material gain at dislocation crystal growth
DOE Office of Scientific and Technical Information (OSTI.GOV)
Rakin, V. I., E-mail: rakin@geo.komisc.ru
2016-05-15
A model for slowing down the tangential growth rate of an elementary step at dislocation crystal growth is proposed based on the exponential law of impurity particle distribution over adsorption energy. It is established that the statistical distribution of material gain on structurally equivalent faces obeys the Erlang law. The Erlang distribution is proposed to be used to calculate the occurrence rates of morphological combinatorial types of polyhedra, presenting real simple crystallographic forms.
A Simple Model for Estimating Total and Merchantable Tree Heights
Alan R. Ek; Earl T. Birdsall; Rebecca J. Spears
1984-01-01
A model is described for estimating total and merchantable tree heights for Lake States tree species. It is intended to be used for compiling forest survey data and in conjunction with growth models for developing projections of tree product yield. Model coefficients are given for 25 species along with fit statistics. Supporting data sets are also described.
Estillore, Armando D; Morris, Holly S; Or, Victor W; Lee, Hansol D; Alves, Michael R; Marciano, Meagan A; Laskina, Olga; Qin, Zhen; Tivanski, Alexei V; Grassian, Vicki H
2017-08-09
Individual airborne sea spray aerosol (SSA) particles show diversity in their morphologies and water uptake properties that are highly dependent on the biological, chemical, and physical processes within the sea subsurface and the sea surface microlayer. In this study, hygroscopicity data for model systems of organic compounds of marine origin mixed with NaCl are compared to data for authentic SSA samples collected in an ocean-atmosphere facility providing insights into the SSA particle growth, phase transitions and interactions with water vapor in the atmosphere. In particular, we combine single particle morphology analyses using atomic force microscopy (AFM) with hygroscopic growth measurements in order to provide important insights into particle hygroscopicity and the surface microstructure. For model systems, a range of simple and complex carbohydrates were studied including glucose, maltose, sucrose, laminarin, sodium alginate, and lipopolysaccharides. The measured hygroscopic growth was compared with predictions from the Extended-Aerosol Inorganics Model (E-AIM). It is shown here that the E-AIM model describes well the deliquescence transition and hygroscopic growth at low mass ratios but not as well for high ratios, most likely due to a high organic volume fraction. AFM imaging reveals that the equilibrium morphology of these single-component organic particles is amorphous. When NaCl is mixed with the organics, the particles adopt a core-shell morphology with a cubic NaCl core and the organics forming a shell similar to what is observed for the authentic SSA samples. The observation of such core-shell morphologies is found to be highly dependent on the salt to organic ratio and varies depending on the nature and solubility of the organic component. Additionally, single particle organic volume fraction AFM analysis of NaCl : glucose and NaCl : laminarin mixtures shows that the ratio of salt to organics in solution does not correspond exactly for individual particles - showing diversity within the ensemble of particles produced even for a simple two component system.
ERIC Educational Resources Information Center
Street, Garrett M.; Laubach, Timothy A.
2013-01-01
We provide a 5E structured-inquiry lesson so that students can learn more of the mathematics behind the logistic model of population biology. By using models and mathematics, students understand how population dynamics can be influenced by relatively simple changes in the environment.
NASA Astrophysics Data System (ADS)
Kozhevnikov, I. V.; Buzmakov, A. V.; Siewert, F.; Tiedtke, K.; Störmer, M.; Samoylova, L.; Sinn, H.
2017-05-01
Simple analytic equation is deduced to explain new physical phenomenon detected experimentally: growth of nano-dots (40-55 nm diameter, 8-13 nm height, 9.4 dots/μm2 surface density) on the grazing incidence mirror surface under the three years irradiation by the free electron laser FLASH (5-45 nm wavelength, 3 degrees grazing incidence angle). The growth model is based on the assumption that the growth of nano-dots is caused by polymerization of incoming hydrocarbon molecules under the action of incident photons directly or photoelectrons knocked out from a mirror surface. The key feature of our approach consists in that we take into account the radiation intensity variation nearby a mirror surface in an explicit form, because the polymerization probability is proportional to it. We demonstrate that the simple analytic approach allows to explain all phenomena observed in experiment and to predict new effects. In particular, we show that the nano-dots growth depends crucially on the grazing angle of incoming beam and its intensity: growth of nano-dots is observed in the limited from above and below intervals of the grazing angle and the radiation intensity. Decrease in the grazing angle by 1 degree only (from 3 to 2 degree) may result in a strong suppression of nanodots growth and their total disappearing. Similarly, decrease in the radiation intensity by several times (replacement of free electron laser by synchrotron) results also in disappearing of nano-dots growth.
Fractal dimension and universality in avascular tumor growth
NASA Astrophysics Data System (ADS)
Ribeiro, Fabiano L.; dos Santos, Renato Vieira; Mata, Angélica S.
2017-04-01
For years, the comprehension of the tumor growth process has been intriguing scientists. New research has been constantly required to better understand the complexity of this phenomenon. In this paper, we propose a mathematical model that describes the properties, already known empirically, of avascular tumor growth. We present, from an individual-level (microscopic) framework, an explanation of some phenomenological (macroscopic) aspects of tumors, such as their spatial form and the way they develop. Our approach is based on competitive interaction between the cells. This simple rule makes the model able to reproduce evidence observed in real tumors, such as exponential growth in their early stage followed by power-law growth. The model also reproduces (i) the fractal-space distribution of tumor cells and (ii) the universal growth behavior observed in both animals and tumors. Our analyses suggest that the universal similarity between tumor and animal growth comes from the fact that both can be described by the same dynamic equation—the Bertalanffy-Richards model—even if they do not necessarily share the same biological properties.
NASA Astrophysics Data System (ADS)
Shiau, Lie-Ding; Wang, Hsu-Pei
2016-05-01
A model is developed in this work to calculate the interfacial energy and growth activation energy of a crystallized substance from induction time data without the knowledge of the actual growth rate. Induction time data for αL-glutamic acid measured with a turbidity probe for various supersaturations at temperatures from 293 to 313 K are employed to verify the developed model. In the model a simple empirical growth rate with growth order 2 is assumed because experiments are conducted at low supersaturation. The results indicate for αL-glutamic acid that the growth activation energy is 39 kJ/mol, which suggests that the growth rate of small nuclei in the agitated induction time experiments is integration controlled. The interfacial energy obtained from the current model is in the range of 5.2-7.4 mJ/m2, which is slightly greater than that obtained from the traditional method (ti-1∝J) for which the value is in the range 4.1-5.7 mJ/m2.
USDA-ARS?s Scientific Manuscript database
Improving process-based crop models is needed to achieve high fidelity forecasts of regional energy, water, and carbon exchange. However, most state-of-the-art Land Surface Models (LSMs) assessed in the fifth phase of the Coupled Model Inter-comparison project (CMIP5) simulated crops as simple C3 or...
Wang, Y; Xu, J; Wang, R M; Yu, D P
2004-01-01
Large-scale micro/nanosized Ga(2)O(3) structures were synthesized via a simple vapor p9hase growth method. The morphology of the as-grown structures varied from aligned arrays of smooth nano/microscale wires to composite and complex microdendrites. We present evidence that the formation of the observed structure depends strongly on its position relative to the source materials (the concentration distribution) and on the growth temperature. A growth model is proposed, based on the vapor-solid (VS) mechanism, which can explain the observed morphologies.
NASA Astrophysics Data System (ADS)
Baird, M. E.; Walker, S. J.; Wallace, B. B.; Webster, I. T.; Parslow, J. S.
2003-03-01
A simple model of estuarine eutrophication is built on biomechanical (or mechanistic) descriptions of a number of the key ecological processes in estuaries. Mechanistically described processes include the nutrient uptake and light capture of planktonic and benthic autotrophs, and the encounter rates of planktonic predators and prey. Other more complex processes, such as sediment biogeochemistry, detrital processes and phosphate dynamics, are modelled using empirical descriptions from the Port Phillip Bay Environmental Study (PPBES) ecological model. A comparison is made between the mechanistically determined rates of ecological processes and the analogous empirically determined rates in the PPBES ecological model. The rates generally agree, with a few significant exceptions. Model simulations were run at a range of estuarine depths and nutrient loads, with outputs presented as the annually averaged biomass of autotrophs. The simulations followed a simple conceptual model of eutrophication, suggesting a simple biomechanical understanding of estuarine processes can provide a predictive tool for ecological processes in a wide range of estuarine ecosystems.
Growth factors, nutrient signaling, and cardiovascular aging
Fontana, Luigi; Vinciguerra, Manlio; Longo, Valter D.
2012-01-01
Growth factors regulated by specific macronutrients have been shown to promote aging and accelerate mortality in the great majority of the organisms studied. In particular, the enzymes activated by growth hormone (GH), insulin and insulin-like growth factor 1 (IGF-I) in mammals and their orthologs in simple model organisms represent perhaps the best-understood proteins involved in the aging process. Dietary restriction (DR), which reduces the level of IGF-I and of other growth factors, has been associated with protection from diabetes, cancer, and cardiovascular diseases and deficiencies in GH signaling and IGF-I are strongly associated with protection from cancer and diabetes in both mice and humans, but their role in cardiac function and cardiovascular diseases is controversial. Here we review the link between growth factors, cardiac function and heart disease with focus on the cardioprotective and sensitizing effect of growth factors in both model organisms and humans. PMID:22499903
Lester, Nigel P; Shuter, Brian J; Venturelli, Paul; Nadeau, Daniel
2014-01-01
A simple population model was developed to evaluate the role of plastic and evolutionary life-history changes on sustainable exploitation rates. Plastic changes are embodied in density-dependent compensatory adjustments to somatic growth rate and larval/juvenile survival, which can compensate for the reductions in reproductive lifetime and mean population fecundity that accompany the higher adult mortality imposed by exploitation. Evolutionary changes are embodied in the selective pressures that higher adult mortality imposes on age at maturity, length at maturity, and reproductive investment. Analytical development, based on a biphasic growth model, led to simple equations that show explicitly how sustainable exploitation rates are bounded by each of these effects. We show that density-dependent growth combined with a fixed length at maturity and fixed reproductive investment can support exploitation-driven mortality that is 80% of the level supported by evolutionary changes in maturation and reproductive investment. Sustainable fishing mortality is proportional to natural mortality (M) times the degree of density-dependent growth, as modified by both the degree of density-dependent early survival and the minimum harvestable length. We applied this model to estimate sustainable exploitation rates for North American walleye populations (Sander vitreus). Our analysis of demographic data from walleye populations spread across a broad latitudinal range indicates that density-dependent variation in growth rate can vary by a factor of 2. Implications of this growth response are generally consistent with empirical studies suggesting that optimal fishing mortality is approximately 0.75M for teleosts. This approach can be adapted to the management of other species, particularly when significant exploitation is imposed on many, widely distributed, but geographically isolated populations.
Bastien, Renaud; Meroz, Yasmine
2016-12-01
Nutation is an oscillatory movement that plants display during their development. Despite its ubiquity among plants movements, the relation between the observed movement and the underlying biological mechanisms remains unclear. Here we show that the kinematics of the full organ in 3D give a simple picture of plant nutation, where the orientation of the curvature along the main axis of the organ aligns with the direction of maximal differential growth. Within this framework we reexamine the validity of widely used experimental measurements of the apical tip as markers of growth dynamics. We show that though this relation is correct under certain conditions, it does not generally hold, and is not sufficient to uncover the specific role of each mechanism. As an example we re-interpret previously measured experimental observations using our model.
NASA Astrophysics Data System (ADS)
Yin, Yip Chee; Hock-Eam, Lim
2012-09-01
Our empirical results show that we can predict GDP growth rate more accurately in continent with fewer large economies, compared to smaller economies like Malaysia. This difficulty is very likely positively correlated with subsidy or social security policies. The stage of economic development and level of competiveness also appears to have interactive effects on this forecast stability. These results are generally independent of the forecasting procedures. Countries with high stability in their economic growth, forecasting by model selection is better than model averaging. Overall forecast weight averaging (FWA) is a better forecasting procedure in most countries. FWA also outperforms simple model averaging (SMA) and has the same forecasting ability as Bayesian model averaging (BMA) in almost all countries.
NASA Technical Reports Server (NTRS)
Smialek, James L.
2002-01-01
An equation has been developed to model the iterative scale growth and spalling process that occurs during cyclic oxidation of high temperature materials. Parabolic scale growth and spalling of a constant surface area fraction have been assumed. Interfacial spallation of the only the thickest segments was also postulated. This simplicity allowed for representation by a simple deterministic summation series. Inputs are the parabolic growth rate constant, the spall area fraction, oxide stoichiometry, and cycle duration. Outputs include the net weight change behavior, as well as the total amount of oxygen and metal consumed, the total amount of oxide spalled, and the mass fraction of oxide spalled. The outputs all follow typical well-behaved trends with the inputs and are in good agreement with previous interfacial models.
Akimoto, Yuki; Yugi, Katsuyuki; Uda, Shinsuke; Kudo, Takamasa; Komori, Yasunori; Kubota, Hiroyuki; Kuroda, Shinya
2013-01-01
Cells use common signaling molecules for the selective control of downstream gene expression and cell-fate decisions. The relationship between signaling molecules and downstream gene expression and cellular phenotypes is a multiple-input and multiple-output (MIMO) system and is difficult to understand due to its complexity. For example, it has been reported that, in PC12 cells, different types of growth factors activate MAP kinases (MAPKs) including ERK, JNK, and p38, and CREB, for selective protein expression of immediate early genes (IEGs) such as c-FOS, c-JUN, EGR1, JUNB, and FOSB, leading to cell differentiation, proliferation and cell death; however, how multiple-inputs such as MAPKs and CREB regulate multiple-outputs such as expression of the IEGs and cellular phenotypes remains unclear. To address this issue, we employed a statistical method called partial least squares (PLS) regression, which involves a reduction of the dimensionality of the inputs and outputs into latent variables and a linear regression between these latent variables. We measured 1,200 data points for MAPKs and CREB as the inputs and 1,900 data points for IEGs and cellular phenotypes as the outputs, and we constructed the PLS model from these data. The PLS model highlighted the complexity of the MIMO system and growth factor-specific input-output relationships of cell-fate decisions in PC12 cells. Furthermore, to reduce the complexity, we applied a backward elimination method to the PLS regression, in which 60 input variables were reduced to 5 variables, including the phosphorylation of ERK at 10 min, CREB at 5 min and 60 min, AKT at 5 min and JNK at 30 min. The simple PLS model with only 5 input variables demonstrated a predictive ability comparable to that of the full PLS model. The 5 input variables effectively extracted the growth factor-specific simple relationships within the MIMO system in cell-fate decisions in PC12 cells.
Numerical model of solar dynamic radiator for parametric analysis
NASA Technical Reports Server (NTRS)
Rhatigan, Jennifer L.
1989-01-01
Growth power requirements for Space Station Freedom will be met through addition of 25 kW solar dynamic (SD) power modules. Extensive thermal and power cycle modeling capabilities have been developed which are powerful tools in Station design and analysis, but which prove cumbersome and costly for simple component preliminary design studies. In order to aid in refining the SD radiator to the mature design stage, a simple and flexible numerical model was developed. The model simulates heat transfer and fluid flow performance of the radiator and calculates area mass and impact survivability for many combinations of flow tube and panel configurations, fluid and material properties, and environmental and cycle variations.
NASA Astrophysics Data System (ADS)
Voloshin, A. E.
2013-11-01
The well-known one-dimensional Burton-Prim-Slichter and Ostrogorsky-Müller analytical models obtained for the stationary mass transfer regime describe in a simple form the dependence of the effective impurity segregation coefficient on the ratio of the crystal growth and convective flow rates. Solutions for the initial transient regime are found in both models. It is shown that the formulas obtained make it possible to determine both the crystal growth rate and the convective mixing intensity on the basis of the analysis of impurity segregation in crystal.
Castorina, P; Delsanto, P P; Guiot, C
2006-05-12
A classification in universality classes of broad categories of phenomenologies, belonging to physics and other disciplines, may be very useful for a cross fertilization among them and for the purpose of pattern recognition and interpretation of experimental data. We present here a simple scheme for the classification of nonlinear growth problems. The success of the scheme in predicting and characterizing the well known Gompertz, West, and logistic models, suggests to us the study of a hitherto unexplored class of nonlinear growth problems.
Fatigue and damage tolerance scatter models
NASA Astrophysics Data System (ADS)
Raikher, Veniamin L.
1994-09-01
Effective Total Fatigue Life and Crack Growth Scatter Models are proposed. The first of them is based on the power form of the Wohler curve, fatigue scatter dependence on mean life value, cycle stress ratio influence on fatigue scatter, and validated description of the mean stress influence on the mean fatigue life. The second uses in addition are fracture mechanics approach, assumption of initial damage existence, and Paris equation. Simple formulas are derived for configurations of models. A preliminary identification of the parameters of the models is fulfilled on the basis of experimental data. Some new and important results for fatigue and crack growth scatter characteristics are obtained.
Mathematical Modeling the Geometric Regularity in Proteus Mirabilis Colonies
NASA Astrophysics Data System (ADS)
Zhang, Bin; Jiang, Yi; Minsu Kim Collaboration
Proteus Mirabilis colony exhibits striking spatiotemporal regularity, with concentric ring patterns with alternative high and low bacteria density in space, and periodicity for repetition process of growth and swarm in time. We present a simple mathematical model to explain the spatiotemporal regularity of P. Mirabilis colonies. We study a one-dimensional system. Using a reaction-diffusion model with thresholds in cell density and nutrient concentration, we recreated periodic growth and spread patterns, suggesting that the nutrient constraint and cell density regulation might be sufficient to explain the spatiotemporal periodicity in P. Mirabilis colonies. We further verify this result using a cell based model.
Higher plant modelling for life support applications: first results of a simple mechanistic model
NASA Astrophysics Data System (ADS)
Hezard, Pauline; Dussap, Claude-Gilles; Sasidharan L, Swathy
2012-07-01
In the case of closed ecological life support systems, the air and water regeneration and food production are performed using microorganisms and higher plants. Wheat, rice, soybean, lettuce, tomato or other types of eatable annual plants produce fresh food while recycling CO2 into breathable oxygen. Additionally, they evaporate a large quantity of water, which can be condensed and used as potable water. This shows that recycling functions of air revitalization and food production are completely linked. Consequently, the control of a growth chamber for higher plant production has to be performed with efficient mechanistic models, in order to ensure a realistic prediction of plant behaviour, water and gas recycling whatever the environmental conditions. Purely mechanistic models of plant production in controlled environments are not available yet. This is the reason why new models must be developed and validated. This work concerns the design and test of a simplified version of a mathematical model coupling plant architecture and mass balance purposes in order to compare its results with available data of lettuce grown in closed and controlled chambers. The carbon exchange rate, water absorption and evaporation rate, biomass fresh weight as well as leaf surface are modelled and compared with available data. The model consists of four modules. The first one evaluates plant architecture, like total leaf surface, leaf area index and stem length data. The second one calculates the rate of matter and energy exchange depending on architectural and environmental data: light absorption in the canopy, CO2 uptake or release, water uptake and evapotranspiration. The third module evaluates which of the previous rates is limiting overall biomass growth; and the last one calculates biomass growth rate depending on matter exchange rates, using a global stoichiometric equation. All these rates are a set of differential equations, which are integrated with time in order to provide total biomass fresh weight during the full growth duration. The model predicts a growth with exponential rate at the beginning and then it becomes linear for the end of the growth; this follows rather accurately the experimental data. Even if this model is too simple to be realistic for more complex plants in changing environments, this is the first step for an integrated approach of plant growth accounting of architectural and mass transfer limitations.
Kwok, Oi-Man; Underhill, Andrea T.; Berry, Jack W.; Luo, Wen; Elliott, Timothy R.; Yoon, Myeongsun
2008-01-01
The use and quality of longitudinal research designs has increased over the past two decades, and new approaches for analyzing longitudinal data, including multi-level modeling (MLM) and latent growth modeling (LGM), have been developed. The purpose of this paper is to demonstrate the use of MLM and its advantages in analyzing longitudinal data. Data from a sample of individuals with intra-articular fractures of the lower extremity from the University of Alabama at Birmingham’s Injury Control Research Center is analyzed using both SAS PROC MIXED and SPSS MIXED. We start our presentation with a discussion of data preparation for MLM analyses. We then provide example analyses of different growth models, including a simple linear growth model and a model with a time-invariant covariate, with interpretation for all the parameters in the models. More complicated growth models with different between- and within-individual covariance structures and nonlinear models are discussed. Finally, information related to MLM analysis such as online resources is provided at the end of the paper. PMID:19649151
NASA Technical Reports Server (NTRS)
Miller, R. D.; Rogers, J. T.
1975-01-01
General requirements for dynamic loads analyses are described. The indicial lift growth function unsteady subsonic aerodynamic representation is reviewed, and the FLEXSTAB CPS is evaluated with respect to these general requirements. The effects of residual flexibility techniques on dynamic loads analyses are also evaluated using a simple dynamic model.
J.M. Warren; F.C. Meinzer; J.R. Brooks; J.-C. Domec; R. Coulombe
2006-01-01
We incorporated soil/plant biophysical properties into a simple model to predict seasonal trajectories of hydraulic redistribution (HR). We measured soil water content, water potential root conductivity, and climate across multiple years in two old-growth coniferous forests. The HR variability within sites (0 to 0.5 mm/d) was linked to spatial patterns of roots, soil...
Emergence of robust growth laws from optimal regulation of ribosome synthesis.
Scott, Matthew; Klumpp, Stefan; Mateescu, Eduard M; Hwa, Terence
2014-08-22
Bacteria must constantly adapt their growth to changes in nutrient availability; yet despite large-scale changes in protein expression associated with sensing, adaptation, and processing different environmental nutrients, simple growth laws connect the ribosome abundance and the growth rate. Here, we investigate the origin of these growth laws by analyzing the features of ribosomal regulation that coordinate proteome-wide expression changes with cell growth in a variety of nutrient conditions in the model organism Escherichia coli. We identify supply-driven feedforward activation of ribosomal protein synthesis as the key regulatory motif maximizing amino acid flux, and autonomously guiding a cell to achieve optimal growth in different environments. The growth laws emerge naturally from the robust regulatory strategy underlying growth rate control, irrespective of the details of the molecular implementation. The study highlights the interplay between phenomenological modeling and molecular mechanisms in uncovering fundamental operating constraints, with implications for endogenous and synthetic design of microorganisms. © 2014 The Authors. Published under the terms of the CC BY 4.0 license.
Growth of Ni nanoclusters on irradiated graphene: a molecular dynamics study.
Valencia, F J; Hernandez-Vazquez, E E; Bringa, E M; Moran-Lopez, J L; Rogan, J; Gonzalez, R I; Munoz, F
2018-04-23
We studied the soft landing of Ni atoms on a previously damaged graphene sheet by means of molecular dynamics simulations. We found a monotonic decrease of the cluster frequency as a function of its size, but few big clusters comprise an appreciable fraction of the total number of Ni atoms. The aggregation of Ni atoms is also modeled by means of a simple phenomenological model. The results are in clear contrast with the case of hard or energetic landing of metal atoms, where there is a tendency to form mono-disperse metal clusters. This behavior is attributed to the high diffusion of unattached Ni atoms, together with vacancies acting as capture centers. The findings of this work show that a simple study of the energetics of the system is not enough in the soft landing regime, where it is unavoidable to also consider the growth process of metal clusters.
Predator-prey modeling of the coupling of co-propagating CAE to kink modes
NASA Astrophysics Data System (ADS)
Fredrickson, Eric
2012-10-01
Co-propagating Compressional Alfven eigenmodes (CAE) with shorter wavelength and higher frequency than the counter-propagating CAE and Global Alfven eigenmodes (GAE) often accompany a low frequency n=1 kink. The lower frequency CAE and GAE are excited through a Doppler-shifted cyclotron resonance; the high frequency CAE (hfCAE) through a simple parallel resonance. We present measurements of the mode structure and spectrum of the hfCAE, and compare those measurements to predictions of a simple model for CAE. The modes are bursting with a typical burst frequency on the order of a few kHz. The n=1 kink frequency is usually higher than this, but when the kink frequency does drop towards the hfCAE burst frequency, the hfCAE burst frequency can become locked with the kink frequency. A simple predator-prey model to simulate the hfCAE bursting demonstrates that a modulation of the growth or damping rate by a few percent, at a frequency near the natural burst frequency, can lock the burst frequency to the modulation frequency. The modulation of the damping rate is postulated to be through a coupling of the kink with a symmetry-breaking error field. The deeper question is how the kink interaction with a locked mode can affect the damping/growth rates of the CAE.
Sayers, A; Heron, J; Smith, Adac; Macdonald-Wallis, C; Gilthorpe, M S; Steele, F; Tilling, K
2017-02-01
There is a growing debate with regards to the appropriate methods of analysis of growth trajectories and their association with prospective dependent outcomes. Using the example of childhood growth and adult BP, we conducted an extensive simulation study to explore four two-stage and two joint modelling methods, and compared their bias and coverage in estimation of the (unconditional) association between birth length and later BP, and the association between growth rate and later BP (conditional on birth length). We show that the two-stage method of using multilevel models to estimate growth parameters and relating these to outcome gives unbiased estimates of the conditional associations between growth and outcome. Using simulations, we demonstrate that the simple methods resulted in bias in the presence of measurement error, as did the two-stage multilevel method when looking at the total (unconditional) association of birth length with outcome. The two joint modelling methods gave unbiased results, but using the re-inflated residuals led to undercoverage of the confidence intervals. We conclude that either joint modelling or the simpler two-stage multilevel approach can be used to estimate conditional associations between growth and later outcomes, but that only joint modelling is unbiased with nominal coverage for unconditional associations.
Szilágyi, N; Kovács, R; Kenyeres, I; Csikor, Zs
2013-01-01
Biofilm development in a fixed bed biofilm reactor system performing municipal wastewater treatment was monitored aiming at accumulating colonization and maximum biofilm mass data usable in engineering practice for process design purposes. Initially a 6 month experimental period was selected for investigations where the biofilm formation and the performance of the reactors were monitored. The results were analyzed by two methods: for simple, steady-state process design purposes the maximum biofilm mass on carriers versus influent load and a time constant of the biofilm growth were determined, whereas for design approaches using dynamic models a simple biofilm mass prediction model including attachment and detachment mechanisms was selected and fitted to the experimental data. According to a detailed statistical analysis, the collected data have not allowed us to determine both the time constant of biofilm growth and the maximum biofilm mass on carriers at the same time. The observed maximum biofilm mass could be determined with a reasonable error and ranged between 438 gTS/m(2) carrier surface and 843 gTS/m(2), depending on influent load, and hydrodynamic conditions. The parallel analysis of the attachment-detachment model showed that the experimental data set allowed us to determine the attachment rate coefficient which was in the range of 0.05-0.4 m d(-1) depending on influent load and hydrodynamic conditions.
Zhang, Ziyu; Yuan, Lang; Lee, Peter D; Jones, Eric; Jones, Julian R
2014-01-01
Bone augmentation implants are porous to allow cellular growth, bone formation and fixation. However, the design of the pores is currently based on simple empirical rules, such as minimum pore and interconnects sizes. We present a three-dimensional (3D) transient model of cellular growth based on the Navier–Stokes equations that simulates the body fluid flow and stimulation of bone precursor cellular growth, attachment, and proliferation as a function of local flow shear stress. The model's effectiveness is demonstrated for two additive manufactured (AM) titanium scaffold architectures. The results demonstrate that there is a complex interaction of flow rate and strut architecture, resulting in partially randomized structures having a preferential impact on stimulating cell migration in 3D porous structures for higher flow rates. This novel result demonstrates the potential new insights that can be gained via the modeling tool developed, and how the model can be used to perform what-if simulations to design AM structures to specific functional requirements. PMID:24664988
VLF wave growth and discrete emission triggering in the magnetosphere - A feedback model
NASA Technical Reports Server (NTRS)
Helliwell, R. A.; Inan, U. S.
1982-01-01
A simple nonlinear feedback model is presented to explain VLF wave growth and emission triggering observed in VLF transmission experiments. The model is formulated in terms of the interaction of electrons with a slowly varying wave in an inhomogeneous medium as in an unstable feedback amplifier with a delay line; constant frequency oscillations are generated on the magnetic equator, while risers and fallers are generated on the downstream and upstream sides of the equator, respectively. Quantitative expressions are obtained for the stimulated radiation produced by energy exchanged between energetic electrons and waves by Doppler-shifted cyclotron resonance, and feedback between the stimulated radiation and the phase bunched currents is incorporated in terms of a two-port discrete time model. The resulting model is capable of explaining the observed temporal growth and saturation effects, phase advance, retardation or frequency shift during growth in the context of a single parameter depending on the energetic particle distribution function, as well as pretermination triggering.
When growth models are not universal: evidence from marine invertebrates
Hirst, Andrew G.; Forster, Jack
2013-01-01
The accumulation of body mass, as growth, is fundamental to all organisms. Being able to understand which model(s) best describe this growth trajectory, both empirically and ultimately mechanistically, is an important challenge. A variety of equations have been proposed to describe growth during ontogeny. Recently, the West Brown Enquist (WBE) equation, formulated as part of the metabolic theory of ecology, has been proposed as a universal model of growth. This equation has the advantage of having a biological basis, but its ability to describe invertebrate growth patterns has not been well tested against other, more simple models. In this study, we collected data for 58 species of marine invertebrate from 15 different taxa. The data were fitted to three growth models (power, exponential and WBE), and their abilities were examined using an information theoretic approach. Using Akaike information criteria, we found changes in mass through time to fit an exponential equation form best (in approx. 73% of cases). The WBE model predominantly overestimates body size in early ontogeny and underestimates it in later ontogeny; it was the best fit in approximately 14% of cases. The exponential model described growth well in nine taxa, whereas the WBE described growth well in one of the 15 taxa, the Amphipoda. Although the WBE has the advantage of being developed with an underlying proximate mechanism, it provides a poor fit to the majority of marine invertebrates examined here, including species with determinate and indeterminate growth types. In the original formulation of the WBE model, it was tested almost exclusively against vertebrates, to which it fitted well; the model does not however appear to be universal given its poor ability to describe growth in benthic or pelagic marine invertebrates. PMID:23945691
Pozzobon, Victor; Perre, Patrick
2018-01-21
This work provides a model and the associated set of parameters allowing for microalgae population growth computation under intermittent lightning. Han's model is coupled with a simple microalgae growth model to yield a relationship between illumination and population growth. The model parameters were obtained by fitting a dataset available in literature using Particle Swarm Optimization method. In their work, authors grew microalgae in excess of nutrients under flashing conditions. Light/dark cycles used for these experimentations are quite close to those found in photobioreactor, i.e. ranging from several seconds to one minute. In this work, in addition to producing the set of parameters, Particle Swarm Optimization robustness was assessed. To do so, two different swarm initialization techniques were used, i.e. uniform and random distribution throughout the search-space. Both yielded the same results. In addition, swarm distribution analysis reveals that the swarm converges to a unique minimum. Thus, the produced set of parameters can be trustfully used to link light intensity to population growth rate. Furthermore, the set is capable to describe photodamages effects on population growth. Hence, accounting for light overexposure effect on algal growth. Copyright © 2017 Elsevier Ltd. All rights reserved.
Mathematical models to characterize early epidemic growth: A Review
Chowell, Gerardo; Sattenspiel, Lisa; Bansal, Shweta; Viboud, Cécile
2016-01-01
There is a long tradition of using mathematical models to generate insights into the transmission dynamics of infectious diseases and assess the potential impact of different intervention strategies. The increasing use of mathematical models for epidemic forecasting has highlighted the importance of designing reliable models that capture the baseline transmission characteristics of specific pathogens and social contexts. More refined models are needed however, in particular to account for variation in the early growth dynamics of real epidemics and to gain a better understanding of the mechanisms at play. Here, we review recent progress on modeling and characterizing early epidemic growth patterns from infectious disease outbreak data, and survey the types of mathematical formulations that are most useful for capturing a diversity of early epidemic growth profiles, ranging from sub-exponential to exponential growth dynamics. Specifically, we review mathematical models that incorporate spatial details or realistic population mixing structures, including meta-population models, individual-based network models, and simple SIR-type models that incorporate the effects of reactive behavior changes or inhomogeneous mixing. In this process, we also analyze simulation data stemming from detailed large-scale agent-based models previously designed and calibrated to study how realistic social networks and disease transmission characteristics shape early epidemic growth patterns, general transmission dynamics, and control of international disease emergencies such as the 2009 A/H1N1 influenza pandemic and the 2014-15 Ebola epidemic in West Africa. PMID:27451336
Mathematical models to characterize early epidemic growth: A review
NASA Astrophysics Data System (ADS)
Chowell, Gerardo; Sattenspiel, Lisa; Bansal, Shweta; Viboud, Cécile
2016-09-01
There is a long tradition of using mathematical models to generate insights into the transmission dynamics of infectious diseases and assess the potential impact of different intervention strategies. The increasing use of mathematical models for epidemic forecasting has highlighted the importance of designing reliable models that capture the baseline transmission characteristics of specific pathogens and social contexts. More refined models are needed however, in particular to account for variation in the early growth dynamics of real epidemics and to gain a better understanding of the mechanisms at play. Here, we review recent progress on modeling and characterizing early epidemic growth patterns from infectious disease outbreak data, and survey the types of mathematical formulations that are most useful for capturing a diversity of early epidemic growth profiles, ranging from sub-exponential to exponential growth dynamics. Specifically, we review mathematical models that incorporate spatial details or realistic population mixing structures, including meta-population models, individual-based network models, and simple SIR-type models that incorporate the effects of reactive behavior changes or inhomogeneous mixing. In this process, we also analyze simulation data stemming from detailed large-scale agent-based models previously designed and calibrated to study how realistic social networks and disease transmission characteristics shape early epidemic growth patterns, general transmission dynamics, and control of international disease emergencies such as the 2009 A/H1N1 influenza pandemic and the 2014-2015 Ebola epidemic in West Africa.
L3.PHI.CTF.P10.02-rev2 Coupling of Subchannel T/H (CTF) and CRUD Chemistry (MAMBA1D)
DOE Office of Scientific and Technical Information (OSTI.GOV)
Salko, Robert K.; Palmtag, Scott; Collins, Benjamin S.
2015-05-15
The purpose of this milestone is to create a preliminary capability for modeling light water reactor (LWR) thermal-hydraulic (T/H) and CRUD growth using the CTF subchannel code and the subgrid version of the MAMBA CRUD chemistry code, MAMBA1D. In part, this is a follow-on to Milestone L3.PHI.VCS.P9.01, which is documented in Report CASL-U-2014-0188-000, titled "Development of CTF Capability for Modeling Reactor Operating Cycles with Crud Growth". As the title suggests, the previous milestone set up a framework for modeling reactor operation cycles with CTF. The framework also facilitated coupling to a CRUD chemistry capability for modeling CRUD growth throughout themore » reactor operating cycle. To demonstrate the capability, a simple CRUD \\surrogate" tool was developed and coupled to CTF; however, it was noted that CRUD growth predictions by the surrogate were not considered realistic. This milestone builds on L3.PHI.VCS.P9.01 by replacing this simple surrogate tool with the more advanced MAMBA1D CRUD chemistry code. Completing this task involves addressing unresolved tasks from Milestone L3.PHI.VCS.P9.01, setting up an interface to MAMBA1D, and extracting new T/H information from CTF that was not previously required in the simple surrogate tool. Speci c challenges encountered during this milestone include (1) treatment of the CRUD erosion model, which requires local turbulent kinetic energy (TKE) (a value that CTF does not calculate) and (2) treatment of the MAMBA1D CRUD chimney boiling model in the CTF rod heat transfer solution. To demonstrate this new T/H, CRUD modeling capability, two sets of simulations were performed: (1) an 18 month cycle simulation of a quarter symmetry model of Watts Bar and (2) a simulation of Assemblies G69 and G70 from Seabrook Cycle 5. The Watts Bar simulation is merely a demonstration of the capability. The simulation of the Seabrook cycle, which had experienced CRUD-related fuel rod failures, had actual CRUD-scrape data to compare with results. As results show, the initial CTF/MAMBA1D-predicted CRUD thicknesses were about half of their expected values, so further investigation will be required for this simulation.« less
Monte Carlo grain growth modeling with local temperature gradients
NASA Astrophysics Data System (ADS)
Tan, Y.; Maniatty, A. M.; Zheng, C.; Wen, J. T.
2017-09-01
This work investigated the development of a Monte Carlo (MC) simulation approach to modeling grain growth in the presence of non-uniform temperature field that may vary with time. We first scale the MC model to physical growth processes by fitting experimental data. Based on the scaling relationship, we derive a grid site selection probability (SSP) function to consider the effect of a spatially varying temperature field. The SSP function is based on the differential MC step, which allows it to naturally consider time varying temperature fields too. We verify the model and compare the predictions to other existing formulations (Godfrey and Martin 1995 Phil. Mag. A 72 737-49 Radhakrishnan and Zacharia 1995 Metall. Mater. Trans. A 26 2123-30) in simple two-dimensional cases with only spatially varying temperature fields, where the predicted grain growth in regions of constant temperature are expected to be the same as for the isothermal case. We also test the model in a more realistic three-dimensional case with a temperature field varying in both space and time, modeling grain growth in the heat affected zone of a weld. We believe the newly proposed approach is promising for modeling grain growth in material manufacturing processes that involves time-dependent local temperature gradient.
Does faint galaxy clustering contradict gravitational instability?
NASA Technical Reports Server (NTRS)
Melott, Adrian L.
1992-01-01
It has been argued, based on the weakness of clustering of faint galaxies, that these objects cannot be the precursors of present galaxies in a simple Einstein-de Sitter model universe with clustering driven by gravitational instability. It is shown that the assumptions made about the growth of clustering were too restrictive. In such a universe, the growth of clustering can easily be fast enough to match the data.
A partial Hamiltonian approach for current value Hamiltonian systems
NASA Astrophysics Data System (ADS)
Naz, R.; Mahomed, F. M.; Chaudhry, Azam
2014-10-01
We develop a partial Hamiltonian framework to obtain reductions and closed-form solutions via first integrals of current value Hamiltonian systems of ordinary differential equations (ODEs). The approach is algorithmic and applies to many state and costate variables of the current value Hamiltonian. However, we apply the method to models with one control, one state and one costate variable to illustrate its effectiveness. The current value Hamiltonian systems arise in economic growth theory and other economic models. We explain our approach with the help of a simple illustrative example and then apply it to two widely used economic growth models: the Ramsey model with a constant relative risk aversion (CRRA) utility function and Cobb Douglas technology and a one-sector AK model of endogenous growth are considered. We show that our newly developed systematic approach can be used to deduce results given in the literature and also to find new solutions.
Consequences of increased longevity for wealth, fertility, and population growth
NASA Astrophysics Data System (ADS)
Bogojević, A.; Balaž, A.; Karapandža, R.
2008-01-01
We present, solve and numerically simulate a simple model that describes the consequences of increased longevity for fertility rates, population growth and the distribution of wealth in developed societies. We look at the consequences of the repeated use of life extension techniques and show that they represent a novel commodity whose introduction will profoundly influence key aspects of the economy and society in general. In particular, we uncover two phases within our simplified model, labeled as ‘mortal’ and ‘immortal’. Within the life extension scenario it is possible to have sustainable economic growth in a population of stable size, as a result of dynamical equilibrium between the two phases.
Dynamics and forecast in a simple model of sustainable development for rural populations.
Angulo, David; Angulo, Fabiola; Olivar, Gerard
2015-02-01
Society is becoming more conscious on the need to preserve the environment. Sustainable development schemes have grown rapidly as a tool for managing, predicting and improving the growth path in different regions and economy sectors. We introduce a novel and simple mathematical model of ordinary differential equations (ODEs) in order to obtain a dynamical description for each one of the sustainability components (economy, social development and environment conservation), together with their dependence with demographic dynamics. The main part in the modeling task is inspired by the works by Cobb, Douglas, Brander and Taylor. This is completed through some new insights by the authors. A model application is presented for three specific geographical rural regions in Caldas (Colombia).
Applications of Perron-Frobenius theory to population dynamics.
Li, Chi-Kwong; Schneider, Hans
2002-05-01
By the use of Perron-Frobenius theory, simple proofs are given of the Fundamental Theorem of Demography and of a theorem of Cushing and Yicang on the net reproductive rate occurring in matrix models of population dynamics. The latter result, which is closely related to the Stein-Rosenberg theorem in numerical linear algebra, is further refined with some additional nonnegative matrix theory. When the fertility matrix is scaled by the net reproductive rate, the growth rate of the model is $1$. More generally, we show how to achieve a given growth rate for the model by scaling the fertility matrix. Demographic interpretations of the results are given.
Simulating initial attack with two fire containment models
Romain M. Mees
1985-01-01
Given a variable rate of fireline construction and an elliptical fire growth model, two methods for estimating the required number of resources, time to containment, and the resulting fire area were compared. Five examples illustrate some of the computational differences between the simple and the complex methods. The equations for the two methods can be used and...
Quantitative model of the growth of floodplains by vertical accretion
Moody, J.A.; Troutman, B.M.
2000-01-01
A simple one-dimensional model is developed to quantitatively predict the change in elevation, over a period of decades, for vertically accreting floodplains. This unsteady model approximates the monotonic growth of a floodplain as an incremental but constant increase of net sediment deposition per flood for those floods of a partial duration series that exceed a threshold discharge corresponding to the elevation of the floodplain. Sediment deposition from each flood increases the elevation of the floodplain and consequently the magnitude of the threshold discharge resulting in a decrease in the number of floods and growth rate of the floodplain. Floodplain growth curves predicted by this model are compared to empirical growth curves based on dendrochronology and to direct field measurements at five floodplain sites. The model was used to predict the value of net sediment deposition per flood which best fits (in a least squares sense) the empirical and field measurements; these values fall within the range of independent estimates of the net sediment deposition per flood based on empirical equations. These empirical equations permit the application of the model to estimate of floodplain growth for other floodplains throughout the world which do not have detailed data of sediment deposition during individual floods. Copyright (C) 2000 John Wiley and Sons, Ltd.
Origin of Complexity in Multicellular Organisms
NASA Astrophysics Data System (ADS)
Furusawa, Chikara; Kaneko, Kunihiko
2000-06-01
Through extensive studies of dynamical system modeling cellular growth and reproduction, we find evidence that complexity arises in multicellular organisms naturally through evolution. Without any elaborate control mechanism, these systems can exhibit complex pattern formation with spontaneous cell differentiation. Such systems employ a ``cooperative'' use of resources and maintain a larger growth speed than simple cell systems, which exist in a homogeneous state and behave ``selfishly.'' The relevance of the diversity of chemicals and reaction dynamics to the growth of a multicellular organism is demonstrated. Chaotic biochemical dynamics are found to provide the multipotency of stem cells.
Revisiting a model of ontogenetic growth: estimating model parameters from theory and data.
Moses, Melanie E; Hou, Chen; Woodruff, William H; West, Geoffrey B; Nekola, Jeffery C; Zuo, Wenyun; Brown, James H
2008-05-01
The ontogenetic growth model (OGM) of West et al. provides a general description of how metabolic energy is allocated between production of new biomass and maintenance of existing biomass during ontogeny. Here, we reexamine the OGM, make some minor modifications and corrections, and further evaluate its ability to account for empirical variation on rates of metabolism and biomass in vertebrates both during ontogeny and across species of varying adult body size. We show that the updated version of the model is internally consistent and is consistent with other predictions of metabolic scaling theory and empirical data. The OGM predicts not only the near universal sigmoidal form of growth curves but also the M(1/4) scaling of the characteristic times of ontogenetic stages in addition to the curvilinear decline in growth efficiency described by Brody. Additionally, the OGM relates the M(3/4) scaling across adults of different species to the scaling of metabolic rate across ontogeny within species. In providing a simple, quantitative description of how energy is allocated to growth, the OGM calls attention to unexplained variation, unanswered questions, and opportunities for future research.
Prey-producing predators: the ecology of human intensification.
Efferson, Charles
2008-01-01
Economic growth theory and theoretical ecology represent independent traditions of modeling aggregate consumer-resource systems. Both focus on different but equally important forces underlying the dynamics of human societies. Though the two traditions have unknowingly converged in some ways, they each have curious conventions from the perspective of the other. These conventions are reviewed, and two separate modeling frameworks that integrate the two traditions in a simple and straightforward fashion are developed and analyzed. The resulting models represent a consumer species (e.g. humans) that both produces and consumes its resources and then reproduces biologically according to the consumption of its resources. Depending on the balance between production, consumption, and reproduction, the models can exhibit stagnant behavior, like some predator-prey models, or growth, like many mutualism and economic growth models. When growth occurs, in the long term it takes one of two forms. Either resources per capita grow and the human population size converges to a constant, which may be zero, or resources per capita converge to a constant and the human population grows. The difference depends on initial conditions and the particular mix of biological conditions and human technology.
Growth Scenarios for the City of Guangzhou, China: Transferability and Confirmability
NASA Astrophysics Data System (ADS)
Lehner, A.; Kraus, V.; Wei, C.; Steinnocher, K.
2016-09-01
This work deals with the development of urban growth scenarios and the prevision of the spatial distribution of built-up area and population for the urban area of the city of Guangzhou in China. Using freely-available data, including remotely sensed data as well as census data from the ground, expenditure of time and costs shall remain low. Guangzhou, one of the biggest cities within the Pearl River Delta, has faced an enormous economic and urban growth during the last three decades. Due to its economical and spatial characteristics it is a promising candidate for urban growth scenarios. The monitoring and prediction of urban growth comprises data of population and give them a spatial representation. The model, originally applied for the Indian city Ahmedabad, is used for urban growth scenarios. Therefore, transferability and confirmability of the model are evaluated. Challenges that may occur by transferring a model for urban growth from one region to another are discussed. With proposing the use of urban remote sensing and freely available data, urban planners shall be fitted with a comprehensible and simple tool to be able to contribute to the future challenge Smart Growth.
Leroy, Frédéric; De Vuyst, Luc
2001-01-01
Although commercial MRS broth has been designed to allow excellent growth of lactobacilli, most of these bacteria are still subjected to a self-inhibiting process. The most likely explanation is the accumulation of lactic acid or other toxic end products and the depletion of nutrients. In this study, the self-inhibition of Lactobacillus sakei CTC 494 was analyzed in a kinetic way, and a nutrient depletion model was set up to describe the growth inhibition process. This simple model has considerable advantages compared to commonly used descriptive models such as the logistic growth equation. It offers a better fit and a more realistic description of the growth data by taking into account both growth inhibition due to lactic acid production and changes in growth rates due to nutrient depletion. Depending on the fermentation conditions, in MRS broth there appears to be a strong decrease of the specific growth rate over time. Some undefined compounds present in the complex nitrogen source of MRS broth appear to be of crucial importance because of their limited availability. Moreover, nutrient availability affects bacteriocin production through its effect on cell growth as well as on the bacteriocin production per cell. A plateau value for the bacteriocin production by L. sakei CTC 494 was observed. PMID:11571136
Growth morphologies of wax in the presence of kinetic inhibitors
NASA Astrophysics Data System (ADS)
Tetervak, Alexander A.
Driven by the need to prevent crystallization of normal alkanes from diesel fuels in cold climates, the petroleum industry has developed additives to slow the growth of these crystals and alter their morphologies. Although the utility of these kinetic inhibitors has been well demonstrated in the field, few studies have directly monitored their effect at microscopic morphology, and the mechanisms by which they act remain poorly understood. Here we present a study of the effects of such additives on the crystallization of long-chain n-alkanes from solution. The additives change the growth morphology from plate-like crystals to a microcrystalline mesh. When we impose a front velocity by moving the sample through a temperature gradient, the mesh growth may form a macroscopic banded pattern and also exhibit a burst-crystallization behavior. In this study, we characterize these crystallization phenomena and also two growth models: a continuum model that demonstrates the essential behavior of the banded crystallization, and a simple qualitative cellular automata model that captures basics of the burst-crystallization process. Keywords: solidification; mesh crystallization; kinetic inhibitor; burst growth.
A simple microbial fuel cell model for improvement of biomedical device powering times.
Roxby, Daniel N; Tran, Nham; Nguyen, Hung T
2014-01-01
This study describes a Matlab based Microbial Fuel Cell (MFC) model for a suspended microbial population, in the anode chamber for the use of the MFC in powering biomedical devices. The model contains three main sections including microbial growth, microbial chemical uptake and secretion and electrochemical modeling. The microbial growth portion is based on a Continuously Stirred Tank Reactor (CSTR) model for the microbial growth with substrate and electron acceptors. Microbial stoichiometry is used to determine chemical concentrations and their rates of change and transfer within the MFC. These parameters are then used in the electrochemical modeling for calculating current, voltage and power. The model was tested for typically exhibited MFC characteristics including increased electrode distances and surface areas, overpotentials and operating temperatures. Implantable biomedical devices require long term powering which is the main objective for MFCs. Towards this end, our model was tested with different initial substrate and electron acceptor concentrations, revealing a four-fold increase in concentrations decreased the power output time by 50%. Additionally, the model also predicts that for a 35.7% decrease in specific growth rate, a 50% increase in power longevity is possible.
Density-dependence as a size-independent regulatory mechanism.
de Vladar, Harold P
2006-01-21
The growth function of populations is central in biomathematics. The main dogma is the existence of density-dependence mechanisms, which can be modelled with distinct functional forms that depend on the size of the population. One important class of regulatory functions is the theta-logistic, which generalizes the logistic equation. Using this model as a motivation, this paper introduces a simple dynamical reformulation that generalizes many growth functions. The reformulation consists of two equations, one for population size, and one for the growth rate. Furthermore, the model shows that although population is density-dependent, the dynamics of the growth rate does not depend either on population size, nor on the carrying capacity. Actually, the growth equation is uncoupled from the population size equation, and the model has only two parameters, a Malthusian parameter rho and a competition coefficient theta. Distinct sign combinations of these parameters reproduce not only the family of theta-logistics, but also the van Bertalanffy, Gompertz and Potential Growth equations, among other possibilities. It is also shown that, except for two critical points, there is a general size-scaling relation that includes those appearing in the most important allometric theories, including the recently proposed Metabolic Theory of Ecology. With this model, several issues of general interest are discussed such as the growth of animal population, extinctions, cell growth and allometry, and the effect of environment over a population.
No way out? The double-bind in seeking global prosperity alongside mitigated climate change
NASA Astrophysics Data System (ADS)
Garrett, T. J.
2012-01-01
In a prior study (Garrett, 2011), I introduced a simple economic growth model designed to be consistent with general thermodynamic laws. Unlike traditional economic models, civilization is viewed only as a well-mixed global whole with no distinction made between individual nations, economic sectors, labor, or capital investments. At the model core is a hypothesis that the global economy's current rate of primary energy consumption is tied through a constant to a very general representation of its historically accumulated wealth. Observations support this hypothesis, and indicate that the constant's value is λ = 9.7 ± 0.3 milliwatts per 1990 US dollar. It is this link that allows for treatment of seemingly complex economic systems as simple physical systems. Here, this growth model is coupled to a linear formulation for the evolution of globally well-mixed atmospheric CO2 concentrations. While very simple, the coupled model provides faithful multi-decadal hindcasts of trajectories in gross world product (GWP) and CO2. Extending the model to the future, the model suggests that the well-known IPCC SRES scenarios substantially underestimate how much CO2 levels will rise for a given level of future economic prosperity. For one, global CO2 emission rates cannot be decoupled from wealth through efficiency gains. For another, like a long-term natural disaster, future greenhouse warming can be expected to act as an inflationary drag on the real growth of global wealth. For atmospheric CO2 concentrations to remain below a "dangerous" level of 450 ppmv (Hansen et al., 2007), model forecasts suggest that there will have to be some combination of an unrealistically rapid rate of energy decarbonization and nearly immediate reductions in global civilization wealth. Effectively, it appears that civilization may be in a double-bind. If civilization does not collapse quickly this century, then CO2 levels will likely end up exceeding 1000 ppmv; but, if CO2 levels rise by this much, then the risk is that civilization will gradually tend towards collapse.
Unidirectional random growth with resetting
NASA Astrophysics Data System (ADS)
Biró, T. S.; Néda, Z.
2018-06-01
We review stochastic processes without detailed balance condition and derive their H-theorem. We obtain stationary distributions and investigate their stability in terms of generalized entropic distances beyond the Kullback-Leibler formula. A simple stochastic model with local growth rates and direct resetting to the ground state is investigated and applied to various networks, scientific citations and Facebook popularity, hadronic yields in high energy particle reactions, income and wealth distributions, biodiversity and settlement size distributions.
Temperature Compensated Piezoelectric Materials
1982-09-01
modeling of the dielectric, elas- tic, piezoelectric and thermoelectric properties of a simple proper ferroelec- tric. In the thermodynamic...COMPOSITIONS 61 5.1 Growth of Sro.sBao.sNbaOe Thin Films 61 5.2 Growth of SraKNbsOis Thin Films 63 6.0 STRUCTURAL.AND FERROELECTRIC PROPERTIES OF...Transitions 75 6.4 Ferroelectric Data 77 6.5 Concl usi ons 82 7.0 PHOTOREFRACTIVE PROPERTIES OF SBN SINGLE CRYSTALS 85 8.0 PUBLICATIONS AND
Quantitative proteomic analysis reveals a simple strategy of global resource allocation in bacteria
Hui, Sheng; Silverman, Josh M; Chen, Stephen S; Erickson, David W; Basan, Markus; Wang, Jilong; Hwa, Terence; Williamson, James R
2015-01-01
A central aim of cell biology was to understand the strategy of gene expression in response to the environment. Here, we study gene expression response to metabolic challenges in exponentially growing Escherichia coli using mass spectrometry. Despite enormous complexity in the details of the underlying regulatory network, we find that the proteome partitions into several coarse-grained sectors, with each sector's total mass abundance exhibiting positive or negative linear relations with the growth rate. The growth rate-dependent components of the proteome fractions comprise about half of the proteome by mass, and their mutual dependencies can be characterized by a simple flux model involving only two effective parameters. The success and apparent generality of this model arises from tight coordination between proteome partition and metabolism, suggesting a principle for resource allocation in proteome economy of the cell. This strategy of global gene regulation should serve as a basis for future studies on gene expression and constructing synthetic biological circuits. Coarse graining may be an effective approach to derive predictive phenomenological models for other ‘omics’ studies. PMID:25678603
Fadel, Ali; Lemaire, Bruno J; Vinçon-Leite, Brigitte; Atoui, Ali; Slim, Kamal; Tassin, Bruno
2017-09-01
Many freshwater bodies worldwide that suffer from harmful algal blooms would benefit for their management from a simple ecological model that requires few field data, e.g. for early warning systems. Beyond a certain degree, adding processes to ecological models can reduce model predictive capabilities. In this work, we assess whether a simple ecological model without nutrients is able to describe the succession of cyanobacterial blooms of different species in a hypereutrophic reservoir and help understand the factors that determine these blooms. In our study site, Karaoun Reservoir, Lebanon, cyanobacteria Aphanizomenon ovalisporum and Microcystis aeruginosa alternatively bloom. A simple configuration of the model DYRESM-CAEDYM was used; both cyanobacteria were simulated, with constant vertical migration velocity for A. ovalisporum, with vertical migration velocity dependent on light for M. aeruginosa and with growth limited by light and temperature and not by nutrients for both species. The model was calibrated on two successive years with contrasted bloom patterns and high variations in water level. It was able to reproduce the measurements; it showed a good performance for the water level (root-mean-square error (RMSE) lower than 1 m, annual variation of 25 m), water temperature profiles (RMSE of 0.22-1.41 °C, range 13-28 °C) and cyanobacteria biomass (RMSE of 1-57 μg Chl a L -1 , range 0-206 μg Chl a L -1 ). The model also helped understand the succession of blooms in both years. The model results suggest that the higher growth rate of M. aeruginosa during favourable temperature and light conditions allowed it to outgrow A. ovalisporum. Our results show that simple model configurations can be sufficient not only for theoretical works when few major processes can be identified but also for operational applications. This approach could be transposed on other hypereutrophic lakes and reservoirs to describe the competition between dominant phytoplankton species, contribute to early warning systems or be used for management scenarios.
Animal spirits, competitive markets, and endogenous growth
NASA Astrophysics Data System (ADS)
Miyazaki, Kenji
2013-10-01
This paper uses a simple model with an endogenous discount rate and linear technology to investigate whether a competitive equilibrium has a higher balanced growth path (BGP) than the social planning solution and whether the BGP is determinate or indeterminate. The implications are as follows. To start with, people with an instinct to compare themselves with others possess an endogenous discount rate. In turn, this instinct affects the economic growth rate in a competitive market economy. The competitive market economy also sometimes achieves higher economic growth than a social planning economy. However, the outcomes of market economy occasionally fluctuate because of the presence of the self-fulfilling prophecy or animal spirits.
Did the ever dead outnumber the living and when? A birth-and-death approach
NASA Astrophysics Data System (ADS)
Avan, Jean; Grosjean, Nicolas; Huillet, Thierry
2015-02-01
This paper is an attempt to formalize analytically the question raised in 'World Population Explained: Do Dead People Outnumber Living, Or Vice Versa?' Huffington Post, Howard (2012). We start developing simple deterministic Malthusian growth models of the problem (with birth and death rates either constant or time-dependent) before running into both linear birth and death Markov chain models and age-structured models.
A necessary condition for dispersal driven growth of populations with discrete patch dynamics.
Guiver, Chris; Packman, David; Townley, Stuart
2017-07-07
We revisit the question of when can dispersal-induced coupling between discrete sink populations cause overall population growth? Such a phenomenon is called dispersal driven growth and provides a simple explanation of how dispersal can allow populations to persist across discrete, spatially heterogeneous, environments even when individual patches are adverse or unfavourable. For two classes of mathematical models, one linear and one non-linear, we provide necessary conditions for dispersal driven growth in terms of the non-existence of a common linear Lyapunov function, which we describe. Our approach draws heavily upon the underlying positive dynamical systems structure. Our results apply to both discrete- and continuous-time models. The theory is illustrated with examples and both biological and mathematical conclusions are drawn. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.
Island growth as a growth mode in atomic layer deposition: A phenomenological model
NASA Astrophysics Data System (ADS)
Puurunen, Riikka L.; Vandervorst, Wilfried
2004-12-01
Atomic layer deposition (ALD) has recently gained world-wide attention because of its suitability for the fabrication of conformal material layers with thickness in the nanometer range. Although the principles of ALD were realized about 40 years ago, the description of many physicochemical processes that occur during ALD growth is still under development. A constant amount of material deposited in an ALD reaction cycle, that is, growth-per-cycle (GPC), has been a paradigm in ALD through decades. The GPC may vary, however, especially in the beginning of the ALD growth. In this work, a division of ALD processes to four classes is proposed, on the basis of how the GPC varies with the number of ALD reaction cycles: linear growth, substrate-enhanced growth, and substrate-inhibited growth of type 1 and type 2. Island growth is identified as a likely origin for type 2 substrate-inhibited growth, where the GPC increases and goes through a maximum before it settles to a constant value characteristic of a steady growth. A simple phenomenological model is developed to describe island growth in ALD. The model assumes that the substrate is unreactive with the ALD reactants, except for reactive defects. ALD growth is assumed to proceed symmetrically from the defects, resulting islands of a conical shape. Random deposition is the growth mode on the islands. The model allows the simulation of GPC curves, surface fraction curves, and surface roughness, with physically significant parameters. When the model is applied to the zirconium tetrachloride/water and the trimethylaluminum/water ALD processes on hydrogen-terminated silicon, the calculated GPC curves and surface fractions agree with the experiments. The island growth model can be used to assess the occurrence of island growth, the size of islands formed, and point of formation of a continuous ALD-grown film. The benefits and limitations of the model and the general characteristics of type 2 substrate-inhibited ALD are discussed.
Zhang, Ziyu; Yuan, Lang; Lee, Peter D; Jones, Eric; Jones, Julian R
2014-11-01
Bone augmentation implants are porous to allow cellular growth, bone formation and fixation. However, the design of the pores is currently based on simple empirical rules, such as minimum pore and interconnects sizes. We present a three-dimensional (3D) transient model of cellular growth based on the Navier-Stokes equations that simulates the body fluid flow and stimulation of bone precursor cellular growth, attachment, and proliferation as a function of local flow shear stress. The model's effectiveness is demonstrated for two additive manufactured (AM) titanium scaffold architectures. The results demonstrate that there is a complex interaction of flow rate and strut architecture, resulting in partially randomized structures having a preferential impact on stimulating cell migration in 3D porous structures for higher flow rates. This novel result demonstrates the potential new insights that can be gained via the modeling tool developed, and how the model can be used to perform what-if simulations to design AM structures to specific functional requirements. © 2014 Wiley Periodicals, Inc.
Physical root-soil interactions
NASA Astrophysics Data System (ADS)
Kolb, Evelyne; Legué, Valérie; Bogeat-Triboulot, Marie-Béatrice
2017-12-01
Plant root system development is highly modulated by the physical properties of the soil and especially by its mechanical resistance to penetration. The interplay between the mechanical stresses exerted by the soil and root growth is of particular interest for many communities, in agronomy and soil science as well as in biomechanics and plant morphogenesis. In contrast to aerial organs, roots apices must exert a growth pressure to penetrate strong soils and reorient their growth trajectory to cope with obstacles like stones or hardpans or to follow the tortuous paths of the soil porosity. In this review, we present the main macroscopic investigations of soil-root physical interactions in the field and combine them with simple mechanistic modeling derived from model experiments at the scale of the individual root apex.
Physical root-soil interactions.
Kolb, Evelyne; Legué, Valérie; Bogeat-Triboulot, Marie-Béatrice
2017-11-16
Plant root system development is highly modulated by the physical properties of the soil and especially by its mechanical resistance to penetration. The interplay between the mechanical stresses exerted by the soil and root growth is of particular interest for many communities, in agronomy and soil science as well as in biomechanics and plant morphogenesis. In contrast to aerial organs, roots apices must exert a growth pressure to penetrate strong soils and reorient their growth trajectory to cope with obstacles like stones or hardpans or to follow the tortuous paths of the soil porosity. In this review, we present the main macroscopic investigations of soil-root physical interactions in the field and combine them with simple mechanistic modeling derived from model experiments at the scale of the individual root apex.
Application of balancing methods in modeling the penicillin fermentation.
Heijnen, J J; Roels, J A; Stouthamer, A H
1979-12-01
This paper shows the application of elementary balancing methods in combination with simple kinetic equations in the formulation of an unstructured model for the fed-batch process for the production of penicillin. The rate of substrate uptake is modeled with a Monod-type relationship. The specific penicillin production rate is assumed to be a function of growth rate. Hydrolysis of penicillin to penicilloic acid is assumed to be first order in penicillin. In simulations with the present model it is shown that the model, although assuming a strict relationship between specific growth rate and penicillin productivity, allows for the commonly observed lag phase in the penicillin concentration curve and the apparent separation between growth and production phase (idiophase-trophophase concept). Furthermore it is shown that the feed rate profile during fermentation is of vital importance in the realization of a high production rate throughout the duration of the fermentation. It is emphasized that the method of modeling presented may also prove rewarding for an analysis of fermentation processes other than the penicillin fermentation.
Internalizing Trajectories in Young Boys and Girls: The Whole Is Not a Simple Sum of Its Parts
ERIC Educational Resources Information Center
Carter, Alice S.; Godoy, Leandra; Wagmiller, Robert L.; Veliz, Philip; Marakovitz, Susan; Briggs-Gowan, Margaret J.
2010-01-01
There is support for a differentiated model of early internalizing emotions and behaviors, yet researchers have not examined the course of multiple components of an internalizing domain across early childhood. In this paper we present growth models for the Internalizing domain of the Infant-Toddler Social and Emotional Assessment and its component…
Establishment of an orthotopic lung cancer model in nude mice and its evaluation by spiral CT.
Liu, Xiang; Liu, Jun; Guan, Yubao; Li, Huiling; Huang, Liyan; Tang, Hailing; He, Jianxing
2012-04-01
To establish a simple and highly efficient orthotopic animal model of lung cancer cell line A549 and evaluate the growth pattern of intrathoracic tumors by spiral CT. A549 cells (5×10(6) mL(-1)) were suspended and inoculated into the right lung of BALB/c nude mice via intrathoracic injection. Nude mice were scanned three times each week by spiral CT after inoculation of lung cancer cell line A549. The survival time and body weight of nude mice as well as tumor invasion and metastasis were examined. Tissue was collected for subsequent histological assay after autopsia of mice. The tumor-forming rate of the orthotopic lung cancer model was 90%. The median survival time was 30.7 (range, 20-41) days. The incidence of tumor metastasis was 100%. The mean tumor diameter and the average CT value gradually increased in a time-dependent manner. The method of establishing the orthotopic lung cancer model through transplanting A549 cells into the lung of nude mice is simple and highly successful. Spiral CT can be used to evaluate intrathoracic tumor growth in nude mice vividly and dynamically.
Establishment of an orthotopic lung cancer model in nude mice and its evaluation by spiral CT
Liu, Xiang; Liu, Jun; Guan, Yubao; Li, Huiling; Huang, Liyan; Tang, Hailing
2012-01-01
Objective To establish a simple and highly efficient orthotopic animal model of lung cancer cell line A549 and evaluate the growth pattern of intrathoracic tumors by spiral CT. Methods A549 cells (5×106 mL-1) were suspended and inoculated into the right lung of BALB/c nude mice via intrathoracic injection. Nude mice were scanned three times each week by spiral CT after inoculation of lung cancer cell line A549. The survival time and body weight of nude mice as well as tumor invasion and metastasis were examined. Tissue was collected for subsequent histological assay after autopsia of mice. Results The tumor-forming rate of the orthotopic lung cancer model was 90%. The median survival time was 30.7 (range, 20-41) days. The incidence of tumor metastasis was 100%. The mean tumor diameter and the average CT value gradually increased in a time-dependent manner. Conclusions The method of establishing the orthotopic lung cancer model through transplanting A549 cells into the lung of nude mice is simple and highly successful. Spiral CT can be used to evaluate intrathoracic tumor growth in nude mice vividly and dynamically. PMID:22833819
Biomat development in soil treatment units for on-site wastewater treatment.
Winstanley, H F; Fowler, A C
2013-10-01
We provide a simple mathematical model of the bioremediation of contaminated wastewater leaching into the subsoil below a septic tank percolation system. The model comprises a description of the percolation system's flows, together with equations describing the growth of biomass and the uptake of an organic contaminant concentration. By first rendering the model dimensionless, it can be partially solved, to provide simple insights into the processes which control the efficacy of the system. In particular, we provide quantitative insight into the effect of a near surface biomat on subsoil permeability; this can lead to trench ponding, and thus propagation of effluent further down the trench. Using the computed vadose zone flow field, the model can be simply extended to include reactive transport of other contaminants of interest.
Data-driven outbreak forecasting with a simple nonlinear growth model
Lega, Joceline; Brown, Heidi E.
2016-01-01
Recent events have thrown the spotlight on infectious disease outbreak response. We developed a data-driven method, EpiGro, which can be applied to cumulative case reports to estimate the order of magnitude of the duration, peak and ultimate size of an ongoing outbreak. It is based on a surprisingly simple mathematical property of many epidemiological data sets, does not require knowledge or estimation of disease transmission parameters, is robust to noise and to small data sets, and runs quickly due to its mathematical simplicity. Using data from historic and ongoing epidemics, we present the model. We also provide modeling considerations that justify this approach and discuss its limitations. In the absence of other information or in conjunction with other models, EpiGro may be useful to public health responders. PMID:27770752
Numerical modeling of the traction process in the treatment for Pierre-Robin Sequence.
Słowiński, Jakub J; Czarnecka, Aleksandra
2016-10-01
The goal of this numerical study was to identify the results of modulated growth simulation of the mandibular bone during traction in Pierre-Robin Sequence (PRS) treatment. Numerical simulation was conducted in the Ansys 16.2 environment. Two FEM (finite elements method) models of a newborn's mandible (a spatial and a flat model) were developed. The procedure simulated a 20-week traction period. The adopted growth measure was mandibular length increase, defined as the distance between the Co-Pog anatomic points used in cephalometric analysis. The simulation calculations conducted on the developed models showed that modulation had a significant influence on the pace of bone growth. In each of the analyzed cases, growth modulation resulted in an increase in pace. The largest value of increase was 6.91 mm. The modulated growth with the most beneficial load variant increased the basic value of the growth by as much as 24.6%, and growth with the least beneficial variant increased by 7.4%. Traction is a simple, minimally invasive and inexpensive procedure. The proposed algorithm may enable the development of a helpful forecasting tool, which could be of real use to doctors working on Pierre-Robin Sequence and other mandibular deformations in children. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.
The Interrelationship between Promoter Strength, Gene Expression, and Growth Rate
Klesmith, Justin R.; Detwiler, Emily E.; Tomek, Kyle J.; Whitehead, Timothy A.
2014-01-01
In exponentially growing bacteria, expression of heterologous protein impedes cellular growth rates. Quantitative understanding of the relationship between expression and growth rate will advance our ability to forward engineer bacteria, important for metabolic engineering and synthetic biology applications. Recently, a work described a scaling model based on optimal allocation of ribosomes for protein translation. This model quantitatively predicts a linear relationship between microbial growth rate and heterologous protein expression with no free parameters. With the aim of validating this model, we have rigorously quantified the fitness cost of gene expression by using a library of synthetic constitutive promoters to drive expression of two separate proteins (eGFP and amiE) in E. coli in different strains and growth media. In all cases, we demonstrate that the fitness cost is consistent with the previous findings. We expand upon the previous theory by introducing a simple promoter activity model to quantitatively predict how basal promoter strength relates to growth rate and protein expression. We then estimate the amount of protein expression needed to support high flux through a heterologous metabolic pathway and predict the sizable fitness cost associated with enzyme production. This work has broad implications across applied biological sciences because it allows for prediction of the interplay between promoter strength, protein expression, and the resulting cost to microbial growth rates. PMID:25286161
Influence of flooding duration on the biomass growth of alder and willow.
Lewis F. Ohmann; M. Dean Knighton; Ronald McRoberts
1990-01-01
Simple second-order (quadratic) polynomials were used to model the relationship between 3-year biomass increase (net ovendry weight in grams) and flooding duration (days) for four combinations of shrub type (alder, willow) and soils type (fine-sand, clay-loam).
[General growth patterns and simple mathematic models of height and weight of Chinese children].
Zong, Xin-nan; Li, Hui
2009-05-01
To explore the growth patterns and simple mathematic models of height and weight of Chinese children. The original data had been obtained from two national representative cross-sectional surveys which were 2005 National Survey of Physical Development of Children (under 7 years of age) and 2005 Chinese National Survey on Students Constitution and Health (6 - 18 years). Reference curves of height and weight of children under 7 years of age was constructed by LMS method, and data of children from 6 to 18 years of age were smoothed by cubic spline function and transformed by modified LMS procedure. Growth velocity was calculated by smoothed values of height and weight. Simple linear model was fitted for children 1 to 10 years of age, for which smoothed height and weight values were used. (1) Birth length of Chinese children was about 50 cm, average length 61 cm, 67 cm, 76 cm and 88 cm at the 3rd, 6th, 12th and 24th month. Height gain was stable from 2 to 10 years of age, average 6 - 7 cm each year. Birth length doubles by 3.5 years, and triples by 12 years. The formula estimating average height of normal children aged 2 - 10 years was, height (cm) = age (yr) x 6.5 + 76 (cm). (2) Birth weight was about 3.3 kg. Growth velocity was at peak about 1.0 - 1.1 kg/mon in the first 3 months, decreased by half and was about 0.5 - 0.6 kg/mon in the second 3 months, and was reduced by a quarter, which was about 0.25 - 0.30 kg/mon, in the last 6 months of the first year. Body mass was up to doubles, triples and quadruple of birth weight at about the 3rd, 12th and 24th month. Average annual gain was about 2 kg and 3 kg from 1 - 6 years and 7 - 10 years, respectively. The estimated formula for children 1 to 6 years of age was weight (kg) = age (yr) x 2 + 8 (kg), but for those 7 - 10 years old, weight (kg) = age (yr) x 3 + 2 (kg). Growth patterns of height and weight at the different age stages were summarized for Chinese children, and simple reference data of height and weight velocity from 0 to 18 years and approximate estimation formula from 1 - 10 years was presented for clinical practice.
NASA Astrophysics Data System (ADS)
Booth, Richard A.; Meru, Farzana; Lee, Man Hoi; Clarke, Cathie J.
2018-03-01
For grain growth to proceed effectively and lead to planet formation, a number of barriers to growth must be overcome. One such barrier, relevant for compact grains in the inner regions of the disc, is the `bouncing barrier' in which large grains (˜mm size) tend to bounce off each other rather than sticking. However, by maintaining a population of small grains, it has been suggested that cm-size particles may grow rapidly by sweeping up these small grains. We present the first numerically resolved investigation into the conditions under which grains may be lucky enough to grow beyond the bouncing barrier by a series of rare collisions leading to growth (so-called `breakthrough'). Our models support previous results, and show that in simple models breakthrough requires the mass ratio at which high-velocity collisions transition to growth instead of causing fragmentation to be low, ϕ ≲ 50. However, in models that take into account the dependence of the fragmentation threshold on mass ratio, we find that breakthrough occurs more readily, even if mass transfer is relatively inefficient. This suggests that bouncing may only slow down growth, rather than preventing growth beyond a threshold barrier. However, even when growth beyond the bouncing barrier is possible, radial drift will usually prevent growth to arbitrarily large sizes.
Modeling Impact of Urbanization in US Cities Using Simple Biosphere Model SiB2
NASA Technical Reports Server (NTRS)
Zhang, Ping; Bounoua, Lahouari; Thome, Kurtis; Wolfe, Robert
2016-01-01
We combine Landsat- and the Moderate Resolution Imaging Spectroradiometer (MODIS)-based products, as well as climate drivers from Phase 2 of the North American Land Data Assimilation System (NLDAS-2) in a Simple Biosphere land surface model (SiB2) to assess the impact of urbanization in continental USA (excluding Alaska and Hawaii). More than 300 cities and their surrounding suburban and rural areas are defined in this study to characterize the impact of urbanization on surface climate including surface energy, carbon budget, and water balance. These analyses reveal an uneven impact of urbanization across the continent that should inform upon policy options for improving urban growth including heat mitigation and energy use, carbon sequestration and flood prevention.
A simple nonlocal damage model for predicting failure of notched laminates
NASA Technical Reports Server (NTRS)
Kennedy, T. C.; Nahan, M. F.
1995-01-01
The ability to predict failure loads in notched composite laminates is a requirement in a variety of structural design circumstances. A complicating factor is the development of a zone of damaged material around the notch tip. The objective of this study was to develop a computational technique that simulates progressive damage growth around a notch in a manner that allows the prediction of failure over a wide range of notch sizes. This was accomplished through the use of a relatively simple, nonlocal damage model that incorporates strain-softening. This model was implemented in a two-dimensional finite element program. Calculations were performed for two different laminates with various notch sizes under tensile loading, and the calculations were found to correlate well with experimental results.
NASA Astrophysics Data System (ADS)
Minton, Allen
2014-08-01
A linear increase in the concentration of "inert" macromolecules with time is incorporated into simple excluded volume models for protein condensation or fibrillation. Such models predict a long latent period during which no significant amount of protein aggregates, followed by a steep increase in the total amount of aggregate. The elapsed time at which these models predict half-conversion of model protein to aggregate varies by less than a factor of two when the intrinsic rate constant for condensation or fibril growth of the protein is varied over many orders of magnitude. It is suggested that this concept can explain why the symptoms of neurodegenerative diseases associated with the aggregation of very different proteins and peptides appear at approximately the same advanced age in humans.
Keren, Leeat; Segal, Eran; Milo, Ron
2016-01-01
Most proteins show changes in level across growth conditions. Many of these changes seem to be coordinated with the specific growth rate rather than the growth environment or the protein function. Although cellular growth rates, gene expression levels and gene regulation have been at the center of biological research for decades, there are only a few models giving a base line prediction of the dependence of the proteome fraction occupied by a gene with the specific growth rate. We present a simple model that predicts a widely coordinated increase in the fraction of many proteins out of the proteome, proportionally with the growth rate. The model reveals how passive redistribution of resources, due to active regulation of only a few proteins, can have proteome wide effects that are quantitatively predictable. Our model provides a potential explanation for why and how such a coordinated response of a large fraction of the proteome to the specific growth rate arises under different environmental conditions. The simplicity of our model can also be useful by serving as a baseline null hypothesis in the search for active regulation. We exemplify the usage of the model by analyzing the relationship between growth rate and proteome composition for the model microorganism E.coli as reflected in recent proteomics data sets spanning various growth conditions. We find that the fraction out of the proteome of a large number of proteins, and from different cellular processes, increases proportionally with the growth rate. Notably, ribosomal proteins, which have been previously reported to increase in fraction with growth rate, are only a small part of this group of proteins. We suggest that, although the fractions of many proteins change with the growth rate, such changes may be partially driven by a global effect, not necessarily requiring specific cellular control mechanisms. PMID:27073913
Threshold for extinction and survival in stochastic tumor immune system
NASA Astrophysics Data System (ADS)
Li, Dongxi; Cheng, Fangjuan
2017-10-01
This paper mainly investigates the stochastic character of tumor growth and extinction in the presence of immune response of a host organism. Firstly, the mathematical model describing the interaction and competition between the tumor cells and immune system is established based on the Michaelis-Menten enzyme kinetics. Then, the threshold conditions for extinction, weak persistence and stochastic persistence of tumor cells are derived by the rigorous theoretical proofs. Finally, stochastic simulation are taken to substantiate and illustrate the conclusion we have derived. The modeling results will be beneficial to understand to concept of immunoediting, and develop the cancer immunotherapy. Besides, our simple theoretical model can help to obtain new insight into the complexity of tumor growth.
A Simple Device to Measure Root Growth Rates
ERIC Educational Resources Information Center
Rauser, Wilfried E.; Horton, Roger F.
1975-01-01
Describes construction and use of a simple auxanometer which students can use to accurately measure root growth rates of intact seedlings. Typical time course data are presented for the effect of ethylene and indole acetic acid on pea root growth. (Author/BR)
Overman, Allen R.; Scholtz, Richard V.
2011-01-01
The expanded growth model is developed to describe accumulation of plant biomass (Mg ha−1) and mineral elements (kg ha−1) in with calendar time (wk). Accumulation of plant biomass with calendar time occurs as a result of photosynthesis for green land-based plants. A corresponding accumulation of mineral elements such as nitrogen, phosphorus, and potassium occurs from the soil through plant roots. In this analysis, the expanded growth model is tested against high quality, published data on corn (Zea mays L.) growth. Data from a field study in South Carolina was used to evaluate the application of the model, where the planting time of April 2 in the field study maximized the capture of solar energy for biomass production. The growth model predicts a simple linear relationship between biomass yield and the growth quantifier, which is confirmed with the data. The growth quantifier incorporates the unit processes of distribution of solar energy which drives biomass accumulation by photosynthesis, partitioning of biomass between light-gathering and structural components of the plants, and an aging function. A hyperbolic relationship between plant nutrient uptake and biomass yield is assumed, and is confirmed for the mineral elements nitrogen (N), phosphorus (P), and potassium (K). It is concluded that the rate limiting process in the system is biomass accumulation by photosynthesis and that nutrient accumulation occurs in virtual equilibrium with biomass accumulation. PMID:22194842
Murray, Kris A; Skerratt, Lee F; Garland, Stephen; Kriticos, Darren; McCallum, Hamish
2013-01-01
The pandemic amphibian disease chytridiomycosis often exhibits strong seasonality in both prevalence and disease-associated mortality once it becomes endemic. One hypothesis that could explain this temporal pattern is that simple weather-driven pathogen proliferation (population growth) is a major driver of chytridiomycosis disease dynamics. Despite various elaborations of this hypothesis in the literature for explaining amphibian declines (e.g., the chytrid thermal-optimum hypothesis) it has not been formally tested on infection patterns in the wild. In this study we developed a simple process-based model to simulate the growth of the pathogen Batrachochytrium dendrobatidis (Bd) under varying weather conditions to provide an a priori test of a weather-linked pathogen proliferation hypothesis for endemic chytridiomycosis. We found strong support for several predictions of the proliferation hypothesis when applied to our model species, Litoria pearsoniana, sampled across multiple sites and years: the weather-driven simulations of pathogen growth potential (represented as a growth index in the 30 days prior to sampling; GI30) were positively related to both the prevalence and intensity of Bd infections, which were themselves strongly and positively correlated. In addition, a machine-learning classifier achieved ~72% success in classifying positive qPCR results when utilising just three informative predictors 1) GI30, 2) frog body size and 3) rain on the day of sampling. Hence, while intrinsic traits of the individuals sampled (species, size, sex) and nuisance sampling variables (rainfall when sampling) influenced infection patterns obtained when sampling via qPCR, our results also strongly suggest that weather-linked pathogen proliferation plays a key role in the infection dynamics of endemic chytridiomycosis in our study system. Predictive applications of the model include surveillance design, outbreak preparedness and response, climate change scenario modelling and the interpretation of historical patterns of amphibian decline.
NASA Astrophysics Data System (ADS)
Talghader, J. J.; Hadley, M. A.; Smith, J. S.
1995-12-01
A molecular beam epitaxy growth monitoring method is developed for distributed Bragg reflectors and vertical-cavity surface-emitting laser (VCSEL) resonators. The wavelength of the substrate thermal emission that corresponds to the optical cavity resonant wavelength is selected by a monochromator and monitored during growth. This method allows VCSEL cavities of arbitrary design wavelength to be grown with a single control program. This letter also presents a theoretical model for the technique which is based on transmission matrices and simple thermal emission properties. Demonstrated reproducibility of the method is well within 0.1%.
A review of some fish nutrition methodologies.
Belal, Ibrahim E H
2005-03-01
Several classical warm blooded animal (poultry, sheep, cows, etc.) methods for dietary nutrients evaluation (digestibility, metabolizablity, and energy budget) are applied to fish, even though fish live in a different environment in addition to being cold blooded animals. These applications have caused significant errors that have made these methods non-additive and meaningless, as is explained in the text. In other words, dietary digestion and absorption could not adequately be measured due to the aquatic environment fish live in. Therefore, net nutrient deposition and/or growth are the only accurate measurement left to evaluate dietary nutrients intake in fish. In order to understand and predict dietary nutrient intake-growth response relationship, several mathematical models; (1) the simple linear equation, (2) the logarithmic equation, and (3) the quadratic equation are generally used. These models however, do not describe a full range of growth and have no biological meaning as explained in the text. On the other hand, a model called the saturation kinetic model. It has biological basis (the law of mass action and the enzyme kinetic) and it describes the full range of growth curve. Additionally, it has four parameters that summarize the growth curve and could also be used in comparing diets or nutrients effect on fish growth and/or net nutrient deposition. The saturation kinetic model is proposed to be adequate for dietary nutrient evaluation for fish. The theoretical derivation of this model is illustrated in the text.
Preneoplastic lesion growth driven by the death of adjacent normal stem cells
Chao, Dennis L.; Eck, J. Thomas; Brash, Douglas E.; Maley, Carlo C.; Luebeck, E. Georg
2008-01-01
Clonal expansion of premalignant lesions is an important step in the progression to cancer. This process is commonly considered to be a consequence of sustaining a proliferative mutation. Here, we investigate whether the growth trajectory of clones can be better described by a model in which clone growth does not depend on a proliferative advantage. We developed a simple computer model of clonal expansion in an epithelium in which mutant clones can only colonize space left unoccupied by the death of adjacent normal stem cells. In this model, competition for space occurs along the frontier between mutant and normal territories, and both the shapes and the growth rates of lesions are governed by the differences between mutant and normal cells' replication or apoptosis rates. The behavior of this model of clonal expansion along a mutant clone's frontier, when apoptosis of both normal and mutant cells is included, matches the growth of UVB-induced p53-mutant clones in mouse dorsal epidermis better than a standard exponential growth model that does not include tissue architecture. The model predicts precancer cell mutation and death rates that agree with biological observations. These results support the hypothesis that clonal expansion of premalignant lesions can be driven by agents, such as ionizing or nonionizing radiation, that cause cell killing but do not directly stimulate cell replication. PMID:18815380
Parametrizing growth in dark energy and modified gravity models
NASA Astrophysics Data System (ADS)
Resco, Miguel Aparicio; Maroto, Antonio L.
2018-02-01
It is well known that an extremely accurate parametrization of the growth function of matter density perturbations in Λ CDM cosmology, with errors below 0.25%, is given by f (a )=Ωmγ(a ) with γ ≃0.55 . In this work, we show that a simple modification of this expression also provides a good description of growth in modified gravity theories. We consider the model-independent approach to modified gravity in terms of an effective Newton constant written as μ (a ,k )=Geff/G and show that f (a )=β (a )Ωmγ(a ) provides fits to the numerical solutions with similar accuracy to that of Λ CDM . In the time-independent case with μ =μ (k ), simple analytic expressions for β (μ ) and γ (μ ) are presented. In the time-dependent (but scale-independent) case μ =μ (a ), we show that β (a ) has the same time dependence as μ (a ). As an example, explicit formulas are provided in the Dvali-Gabadadze-Porrati (DGP) model. In the general case, for theories with μ (a ,k ), we obtain a perturbative expansion for β (μ ) around the general relativity case μ =1 which, for f (R ) theories, reaches an accuracy below 1%. Finally, as an example we apply the obtained fitting functions in order to forecast the precision with which future galaxy surveys will be able to measure the μ parameter.
A Simple Plant Growth Analysis.
ERIC Educational Resources Information Center
Oxlade, E.
1985-01-01
Describes the analysis of dandelion peduncle growth based on peduncle length, epidermal cell dimensions, and fresh/dry mass. Methods are simple and require no special apparatus or materials. Suggests that limited practical work in this area may contribute to students' lack of knowledge on plant growth. (Author/DH)
Biased growth processes and the ``rich-get-richer'' principle
NASA Astrophysics Data System (ADS)
de Moura, Alessandro P.
2004-05-01
We study a simple stochastic system with a “rich-get-richer” behavior, in which there are 2 states, and N particles that are successively assigned to one of the states, with a probability pi that depends on the states’ occupation ni as pi = nγi /( nγ1 + nγ2 ) . We show that there is a phase transition as γ crosses the critical value γc =1 . For γ<1 , in the thermodynamic limit the occupations are approximately the same, n1 ≈ n2 . For γ>1 , however, a spontaneous symmetry breaking occurs, and the system goes to a highly clustered configuration, in which one of the states has almost all the particles. These results also hold for any finite number of states (not only two). We show that this “rich-get-richer” principle governs the growth dynamics in a simple model of gravitational aggregation, and we argue that the same is true in all growth processes mediated by long-range forces like gravity.
Cellular and dendritic growth in a binary melt - A marginal stability approach
NASA Technical Reports Server (NTRS)
Laxmanan, V.
1986-01-01
A simple model for the constrained growth of an array of cells or dendrites in a binary alloy in the presence of an imposed positive temperature gradient in the liquid is proposed, with the dendritic or cell tip radius calculated using the marginal stability criterion of Langer and Muller-Krumbhaar (1977). This approach, an approach adopting the ad hoc assumption of minimum undercooling at the cell or dendrite tip, and an approach based on the stability criterion of Trivedi (1980) all predict tip radii to within 30 percent of each other, and yield a simple relationship between the tip radius and the growth conditions. Good agreement is found between predictions and data obtained in a succinonitrile-acetone system, and under the present experimental conditions, the dendritic tip stability parameter value is found to be twice that obtained previously, possibly due to a transition in morphology from a cellular structure with just a few side branches, to a more fully developed dendritic structure.
Growth-rate dependent global effects on gene expression in bacteria
Klumpp, Stefan; Zhang, Zhongge; Hwa, Terence
2010-01-01
Summary Bacterial gene expression depends not only on specific regulations but also directly on bacterial growth, because important global parameters such as the abundance of RNA polymerases and ribosomes are all growth-rate dependent. Understanding these global effects is necessary for a quantitative understanding of gene regulation and for the robust design of synthetic genetic circuits. The observed growth-rate dependence of constitutive gene expression can be explained by a simple model using the measured growth-rate dependence of the relevant cellular parameters. More complex growth dependences for genetic circuits involving activators, repressors and feedback control were analyzed, and salient features were verified experimentally using synthetic circuits. The results suggest a novel feedback mechanism mediated by general growth-dependent effects and not requiring explicit gene regulation, if the expressed protein affects cell growth. This mechanism can lead to growth bistability and promote the acquisition of important physiological functions such as antibiotic resistance and tolerance (persistence). PMID:20064380
Growth rate predicts mortality of Abies concolor in both burned and unburned stands
van Mantgem, Phillip J.; Stephenson, Nathan L.; Mutch, Linda S.; Johnson, Veronica G.; Esperanza, Annie M.; Parsons, David J.
2003-01-01
Tree mortality is often the result of both long-term and short-term stress. Growth rate, an indicator of long-term stress, is often used to estimate probability of death in unburned stands. In contrast, probability of death in burned stands is modeled as a function of short-term disturbance severity. We sought to narrow this conceptual gap by determining (i) whether growth rate, in addition to crown scorch, is a predictor of mortality in burned stands and (ii) whether a single, simple model could predict tree death in both burned and unburned stands. Observations of 2622 unburned and 688 burned Abies concolor (Gord. & Glend.) Lindl. (white fir) in the Sierra Nevada of California, U.S.A., indicated that growth rate was a significant predictor of mortality in the unburned stands, while both crown scorch and radial growth were significant predictors of mortality in the burned stands. Applying the burned stand model to unburned stands resulted in an overestimation of the unburned stand mortality rate. While failing to create a general model of tree death for A. concolor, our findings underscore the idea that similar processes may affect mortality in disturbed and undisturbed stands.
1992-01-14
modes. Nonlinearity 4, 697-726. Campbell, S. A . 1991. The Effects of Symmetry on Low Dimensional Modal Interactions. Ph. D. Thesis. (Theoretical and...et aL; they have a ready for submission entitled " Bifurcation from symmetric heteroclinic cycles with three interacting modes". The purpose of this...simple model for the effects of riblets on the growth and form of eigenstructures is under investigation. This model is a straight-forward extension of
How did the swiss cheese plant get its holes?
Muir, Christopher D
2013-02-01
Adult leaf fenestration in "Swiss cheese" plants (Monstera Adans.) is an unusual leaf shape trait lacking a convincing evolutionary explanation. Monstera are secondary hemiepiphytes that inhabit the understory of tropical rainforests, where photosynthesis from sunflecks often makes up a large proportion of daily carbon assimilation. Here I present a simple model of leaf-level photosynthesis and whole-plant canopy dynamics in a stochastic light environment. The model demonstrates that leaf fenestration can reduce the variance in plant growth and thereby increase geometric mean fitness. This growth-variance hypothesis also suggests explanations for conspicuous ontogenetic changes in leaf morphology (heteroblasty) in Monstera, as well as the absence of leaf fenestration in co-occurring juvenile tree species. The model provides a testable hypothesis of the adaptive significance of a unique leaf shape and illustrates how variance in growth rate could be an important factor shaping plant morphology and physiology.
A fiber-reinforced-fluid model of anisotropic plant root cell growth
NASA Astrophysics Data System (ADS)
Jensen, Oliver E.; Dyson, Rosemary J.
2009-11-01
We present a theoretical model of a single cell in the expansion zone of the primary root of the plant Arabidopsis thaliana. The cell undergoes rapid elongation with approximately constant radius. Growth is driven by high internal turgor pressure causing viscous stretching of the cell wall, with embedded cellulose microfibrils providing the wall with strongly anisotropic properties. We represent the cell as a thin cylindrical fiber-reinforced viscous sheet between rigid end plates. Asymptotic reduction of the governing equations, under simple sets of assumptions about fiber and wall properties, yields variants of the traditional Lockhart equation that relates the axial cell growth rate to the internal pressure. The model provides insights into the geometric and biomechanical parameters underlying bulk quantities such as wall extensibility and shows how either dynamical changes in wall material properties or passive fibre reorientation may suppress cell elongation.
Although hydraulic redistribution of soil water (HR) by roots is a widespread phenomenon, the processes governing spatial and temporal patterns of HR are not well understood. We incorporated soil/plant biophysical properties into a simple model based on Darcy's law to predict sea...
Using a Simple Parcel Model to Investigate the Haines Index
Mary Ann Jenkins; Steven K. Krueger; Ruiyu Sun
2003-01-01
The Haines Index (Haines 1988) ia fire-weather index based on stability and moisture conditions of the lower atmosphere that rates the potential for large fire growth or extreme fire behavior. The Hained Index is calculated by adding a temperature term a to a moisture term b.
Drosophila as a genetic and cellular model for studies on axonal growth
Sánchez-Soriano, Natalia; Tear, Guy; Whitington, Paul; Prokop, Andreas
2007-01-01
One of the most fascinating processes during nervous system development is the establishment of stereotypic neuronal networks. An essential step in this process is the outgrowth and precise navigation (pathfinding) of axons and dendrites towards their synaptic partner cells. This phenomenon was first described more than a century ago and, over the past decades, increasing insights have been gained into the cellular and molecular mechanisms regulating neuronal growth and navigation. Progress in this area has been greatly assisted by the use of simple and genetically tractable invertebrate model systems, such as the fruit fly Drosophila melanogaster. This review is dedicated to Drosophila as a genetic and cellular model to study axonal growth and demonstrates how it can and has been used for this research. We describe the various cellular systems of Drosophila used for such studies, insights into axonal growth cones and their cytoskeletal dynamics, and summarise identified molecular signalling pathways required for growth cone navigation, with particular focus on pathfinding decisions in the ventral nerve cord of Drosophila embryos. These Drosophila-specific aspects are viewed in the general context of our current knowledge about neuronal growth. PMID:17475018
Precipitation growth in convective clouds. [hail
NASA Technical Reports Server (NTRS)
Srivastava, R. C.
1981-01-01
Analytical solutions to the equations of both the growth and motion of hailstones in updrafts and of cloud water contents which vary linearly with height were used to investigate hail growth in a model cloud. A strong correlation was found between the hail embyro starting position and its trajectory and final size. A simple model of the evolution of particle size distribution by coalescence and spontaneous and binary disintegrations was formulated. Solutions for the mean mass of the distribution and the equilibrium size distribution were obtained for the case of constant collection kernel and disintegration parameters. Azimuthal scans of Doppler velocity at a number of elevation angles were used to calculate high resolution vertical profiles of particle speed and horizontal divergence (the vertical air velocity) in a region of widespread precipitation trailing a mid-latitude squall line.
NASA Technical Reports Server (NTRS)
Curreri, Peter A.
2010-01-01
Two contemporary issues foretell a shift from our historical Earth based industrial economy and habitation to a solar system based society. The first is the limits to Earth's carrying capacity, that is the maximum number of people that the Earth can support before a catastrophic impact to the health of the planet and human species occurs. The simple example of carrying capacity is that of a bacterial colony in a Petri dish with a limited amount of nutrient. The colony experiences exponential population growth until the carrying capacity is reached after which catastrophic depopulation often results. Estimates of the Earth s carrying capacity vary between 14 and 40 billion people. Although at current population growth rates we may have over a century before we reach Earth s carrying limit our influence on climate and resources on the planetary scale is becoming scientifically established. The second issue is the exponential growth of knowledge and technological power. The exponential growth of technology interacts with the exponential growth of population in a manner that is unique to a highly intelligent species. Thus, the predicted consequences (world famines etc.) of the limits to growth have been largely avoided due to technological advances. However, at the mid twentieth century a critical coincidence occurred in these two trends humanity obtained the technological ability to extinguish life on the planetary scale (by nuclear, chemical, biological means) and attained the ability to expand human life beyond Earth. This paper examines an optimized O Neill/Glaser model (O Neill 1975; Curreri 2007; Detweiler and Curreri 2008) for the economic human population of space. Critical to this model is the utilization of extraterrestrial resources, solar power and spaced based labor. A simple statistical analysis is then performed which predicts the robustness of a single planet based technological society versus that of multiple world (independent habitats) society.
NASA Technical Reports Server (NTRS)
Curreri, Peter A.
2010-01-01
Two contemporary issues foretell a shift from our historical Earth based industrial economy and habitation to a solar system based society. The first is the limits to Earth s carrying capacity, that is the maximum number of people that the Earth can support before a catastrophic impact to the health of the planet and human species occurs. The simple example of carrying capacity is that of a bacterial colony in a Petri dish with a limited amount of nutrient. The colony experiences exponential population growth until the carrying capacity is reached after which catastrophic depopulation often results. Estimates of the Earth s carrying capacity vary between 14 and 40 billion people. Although at current population growth rates we may have over a century before we reach Earth s carrying limit our influence on climate and resources on the planetary scale is becoming scientifically established. The second issue is the exponential growth of knowledge and technological power. The exponential growth of technology interacts with the exponential growth of population in a manner that is unique to a highly intelligent species. Thus, the predicted consequences (world famines etc.) of the limits to growth have been largely avoided due to technological advances. However, at the mid twentieth century a critical coincidence occurred in these two trends humanity obtained the technological ability to extinguish life on the planetary scale (by nuclear, chemical, biological means) and attained the ability to expand human life beyond Earth. This paper examines an optimized O Neill/Glaser model (O Neill 1975; Curreri 2007; Detweiler and Curreri 2008) for the economic human population of space. Critical to this model is the utilization of extraterrestrial resources, solar power and spaced based labor. A simple statistical analysis is then performed which predicts the robustness of a single planet based technological society versus that of multiple world (independent habitats) society.
NASA Technical Reports Server (NTRS)
Curreri, Peter A.
2010-01-01
Two contemporary issues foretell a shift from our historical Earth based industrial economy and habitation to a solar system based society. The first is the limits to Earth s carrying capacity, that is the maximum number of people that the Earth can support before a catastrophic impact to the health of the planet and human species occurs. The simple example of carrying capacity is that of a bacterial colony in a Petri dish with a limited amount of nutrient. The colony experiences exponential population growth until the carrying capacity is reached after which catastrophic depopulation often results. Estimates of the Earth s carrying capacity vary between 14 and 40 billion people. Although at current population growth rates we may have over a century before we reach Earth s carrying limit our influence on climate and resources on the planetary scale is becoming scientifically established. The second issue is the exponential growth of knowledge and technological power. The exponential growth of technology interacts with the exponential growth of population in a manner that is unique to a highly intelligent species. Thus, the predicted consequences (world famines etc.) of the limits to growth have been largely avoided due to technological advances. However, at the mid twentieth century a critical coincidence occurred in these two trends humanity obtained the technological ability to extinguish life on the planetary scale (by nuclear, chemical, biological means) and attained the ability to expand human life beyond Earth. This paper examines an optimized O'Neill/Glaser model (O Neill 1975; Curreri 2007; Detweiler and Curreri 2008) for the economic human population of space. Critical to this model is the utilization of extraterrestrial resources, solar power and spaced based labor. A simple statistical analysis is then performed which predicts the robustness of a single planet based technological society versus that of multiple world (independent habitats) society.
NASA Astrophysics Data System (ADS)
Durang, Xavier; Henkel, Malte
2017-12-01
Motivated by an analogy with the spherical model of a ferromagnet, the three Arcetri models are defined. They present new universality classes, either for the growth of interfaces, or else for lattice gases. They are distinct from the common Edwards-Wilkinson and Kardar-Parisi-Zhang universality classes. Their non-equilibrium evolution can be studied by the exact computation of their two-time correlators and responses. In both interpretations, the first model has a critical point in any dimension and shows simple ageing at and below criticality. The exact universal exponents are found. The second and third model are solved at zero temperature, in one dimension, where both show logarithmic sub-ageing, of which several distinct types are identified. Physically, the second model describes a lattice gas and the third model describes interface growth. A clear physical picture on the subsequent time and length scales of the sub-ageing process emerges.
Bhaumik, Basabi; Mathur, Mona
2003-01-01
We present a model for development of orientation selectivity in layer IV simple cells. Receptive field (RF) development in the model, is determined by diffusive cooperation and resource limited competition guided axonal growth and retraction in geniculocortical pathway. The simulated cortical RFs resemble experimental RFs. The receptive field model is incorporated in a three-layer visual pathway model consisting of retina, LGN and cortex. We have studied the effect of activity dependent synaptic scaling on orientation tuning of cortical cells. The mean value of hwhh (half width at half the height of maximum response) in simulated cortical cells is 58 degrees when we consider only the linear excitatory contribution from LGN. We observe a mean improvement of 22.8 degrees in tuning response due to the non-linear spiking mechanisms that include effects of threshold voltage and synaptic scaling factor.
Poverty trap formed by the ecology of infectious diseases
Bonds, Matthew H.; Keenan, Donald C.; Rohani, Pejman; Sachs, Jeffrey D.
2010-01-01
While most of the world has enjoyed exponential economic growth, more than one-sixth of the world is today roughly as poor as their ancestors were many generations ago. Widely accepted general explanations for the persistence of such poverty have been elusive and are needed by the international development community. Building on a well-established model of human infectious diseases, we show how formally integrating simple economic and disease ecology models can naturally give rise to poverty traps, where initial economic and epidemiological conditions determine the long-term trajectory of the health and economic development of a society. This poverty trap may therefore be broken by improving health conditions of the population. More generally, we demonstrate that simple human ecological models can help explain broad patterns of modern economic organization. PMID:20007179
A nonlinear competitive model of the prostate tumor growth under intermittent androgen suppression.
Yang, Jing; Zhao, Tong-Jun; Yuan, Chang-Qing; Xie, Jing-Hui; Hao, Fang-Fang
2016-09-07
Hormone suppression has been the primary modality of treatment for prostate cancer. However long-term androgen deprivation may induce androgen-independent (AI) recurrence. Intermittent androgen suppression (IAS) is a potential way to delay or avoid the AI relapse. Mathematical models of tumor growth and treatment are simple while they are capable of capturing the essence of complicated interactions. Game theory models have analyzed that tumor cells can enhance their fitness by adopting genetically determined survival strategies. In this paper, we consider the survival strategies as the competitive advantage of tumor cells and propose a new model to mimic the prostate tumor growth in IAS therapy. Then we investigate the competition effect in tumor development by numerical simulations. The results indicate that successfully IAS-controlled states can be achieved even though the net growth rate of AI cells is positive for any androgen level. There is crucial difference between the previous models and the new one in the phase diagram of successful and unsuccessful tumor control by IAS administration, which means that the suggestions from the models for medication can be different. Furthermore we introduce quadratic logistic terms to the competition model to simulate the tumor growth in the environment with a finite carrying capacity considering the nutrients or inhibitors. The simulations show that the tumor growth can reach an equilibrium state or an oscillatory state with the net growth rate of AI cells being androgen independent. Our results suggest that the competition and the restraint of a limited environment can enhance the possibility of relapse prevention. Copyright © 2016 Elsevier Ltd. All rights reserved.
Chemical consequences of the initial diffusional growth of cloud droplets - A clean marine case
NASA Technical Reports Server (NTRS)
Twohy, C. H.; Charlson, R. J.; Austin, P. H.
1989-01-01
A simple microphysical cloud parcel model and a simple representation of the background marine aerosol are used to predict the concentrations and compositions of droplets of various sizes near cloud base. The aerosol consists of an externally-mixed ammonium bisulfate accumulation mode and a sea-salt coarse particle mode. The difference in diffusional growth rates between the small and large droplets as well as the differences in composition between the two aerosol modes result in substantial differences in solute concentration and composition with size of droplets in the parcel. The chemistry of individual droplets is not, in general, representative of the bulk (volume-weighted mean) cloud water sample. These differences, calculated to occur early in the parcel's lifetime, should have important consequences for chemical reactions such as aqueous phase sulfate production.
Theoretical size controls of the giant Phaeocystis globosa colonies
NASA Astrophysics Data System (ADS)
Liu, Xiao; Smith, Walker O.; Tang, Kam W.; Doan, Nhu Hai; Nguyen, Ngoc Lam
2015-06-01
An unusual characteristic of the cosmopolitan haptophyte Phaeocystis globosa is its ability to form colonies of strikingly large size-up to 3 cm in diameter. The large size and the presence of a mucoid envelope are believed to contribute to the formation of dense blooms in Southeast Asia. We collected colonies of different sizes in shallow coastal waters of Viet Nam and conducted a series of measurements and experiments on individual colonies. Using these empirical data, we developed a simple carbon-based model to predict the growth and maximal size of P. globosa colonies. Our model suggests that growth of a colony from 0.2 cm to 1.4 cm (the maximal size in our samples) would take 16 days. This number, however, is strongly influenced by the maximal photosynthetic rate and other physiological parameters used in the model. The model also returns a specific growth rate of 0.30 d-1 for colonial cells, comparable to satellite estimates, but lower than have been measured for unicellular P. globosa in batch culture at similar temperatures. We attribute this low growth rate to not only the model uncertainties, but factors such as self-shading and diffusive limitation of nutrient uptake.
Kinetic model for dependence of thin film stress on growth rate, temperature, and microstructure
NASA Astrophysics Data System (ADS)
Chason, E.; Shin, J. W.; Hearne, S. J.; Freund, L. B.
2012-04-01
During deposition, many thin films go through a range of stress states, changing from compressive to tensile and back again. In addition, the stress depends strongly on the processing and material parameters. We have developed a simple analytical model to describe the stress evolution in terms of a kinetic competition between different mechanisms of stress generation and relaxation at the triple junction where the surface and grain boundary intersect. The model describes how the steady state stress scales with the dimensionless parameter D/LR where D is the diffusivity, R is the growth rate, and L is the grain size. It also explains the transition from tensile to compressive stress as the microstructure evolves from isolated islands to a continuous film. We compare calculations from the model with measurements of the stress dependence on grain size and growth rate in the steady state regime and of the evolution of stress with thickness for different temperatures.
Global dynamics in a stoichiometric food chain model with two limiting nutrients.
Chen, Ming; Fan, Meng; Kuang, Yang
2017-07-01
Ecological stoichiometry studies the balance of energy and multiple chemical elements in ecological interactions to establish how the nutrient content affect food-web dynamics and nutrient cycling in ecosystems. In this study, we formulate a food chain with two limiting nutrients in the form of a stoichiometric population model. A comprehensive global analysis of the rich dynamics of the targeted model is explored both analytically and numerically. Chaotic dynamic is observed in this simple stoichiometric food chain model and is compared with traditional model without stoichiometry. The detailed comparison reveals that stoichiometry can reduce the parameter space for chaotic dynamics. Our findings also show that decreasing producer production efficiency may have only a small effect on the consumer growth but a more profound impact on the top predator growth. Copyright © 2017 Elsevier Inc. All rights reserved.
Liew, Lawrence J; Day, Richard M; Dilley, Rodney J
2017-03-01
Tissue engineering approaches using growth factors and various materials for repairing chronic perforations of the tympanic membrane are being developed, but there are surprisingly few relevant tissue culture models available to test new treatments. Here, we present a simple three-dimensional model system based on micro-dissecting the rat tympanic membrane umbo and grafting it into the membrane of a cell culture well insert. Cell outgrowth from the graft produced sufficient cells to populate a membrane of similar surface area to the human tympanic membrane within 2 weeks. Tissue grafts from the annulus region also showed cell outgrowth but were not as productive. The umbo organoid supported substantial cell proliferation and migration under the influence of keratinocyte growth medium. Cells from umbo grafts were enzymatically harvested from the polyethylene terephthalate (PET) membrane for expansion in routine culture and cells could be harvested consecutively from the same graft over multiple cycles. We used harvested cells to test cell migration properties and to engraft a porous silk scaffold material as proof-of-principle for tissue engineering applications. This model is simple enough to be widely adopted for tympanic membrane regeneration studies and has promise as a tissue-equivalent model alternative to animal testing.
Torrents, Genís; Illa, Xavier; Vives, Eduard; Planes, Antoni
2017-01-01
A simple model for the growth of elongated domains (needle-like) during a martensitic phase transition is presented. The model is purely geometric and the only interactions are due to the sequentiality of the kinetic problem and to the excluded volume, since domains cannot retransform back to the original phase. Despite this very simple interaction, numerical simulations show that the final observed microstructure can be described as being a consequence of dipolar-like interactions. The model is analytically solved in 2D for the case in which two symmetry related domains can grow in the horizontal and vertical directions. It is remarkable that the solution is analytic both for a finite system of size L×L and in the thermodynamic limit L→∞, where the elongated domains become lines. Results prove the existence of criticality, i.e., that the domain sizes observed in the final microstructure show a power-law distribution characterized by a critical exponent. The exponent, nevertheless, depends on the relative probabilities of the different equivalent variants. The results provide a plausible explanation of the weak universality of the critical exponents measured during martensitic transformations in metallic alloys. Experimental exponents show a monotonous dependence with the number of equivalent variants that grow during the transition.
Wiechers, Dirk; Kahlen, Katrin; Stützel, Hartmut
2011-01-01
Background and Aims Growth imbalances between individual fruits are common in indeterminate plants such as cucumber (Cucumis sativus). In this species, these imbalances can be related to differences in two growth characteristics, fruit growth duration until reaching a given size and fruit abortion. Both are related to distribution, and environmental factors as well as canopy architecture play a key role in their differentiation. Furthermore, events leading to a fruit reaching its harvestable size before or simultaneously with a prior fruit can be observed. Functional–structural plant models (FSPMs) allow for interactions between environmental factors, canopy architecture and physiological processes. Here, we tested hypotheses which account for these interactions by introducing dominance and abortion thresholds for the partitioning of assimilates between growing fruits. Methods Using the L-System formalism, an FSPM was developed which combined a model for architectural development, a biochemical model of photosynthesis and a model for assimilate partitioning, the last including a fruit growth model based on a size-related potential growth rate (RP). Starting from a distribution proportional to RP, the model was extended by including abortion and dominance. Abortion was related to source strength and dominance to sink strength. Both thresholds were varied to test their influence on fruit growth characteristics. Simulations were conducted for a dense row and a sparse isometric canopy. Key Results The simple partitioning models failed to simulate individual fruit growth realistically. The introduction of abortion and dominance thresholds gave the best results. Simulations of fruit growth durations and abortion rates were in line with measurements, and events in which a fruit was harvestable earlier than an older fruit were reproduced. Conclusions Dominance and abortion events need to be considered when simulating typical fruit growth traits. By integrating environmental factors, the FSPM can be a valuable tool to analyse and improve existing knowledge about the dynamics of assimilates partitioning. PMID:21715366
A creep cavity growth model for creep-fatigue life prediction of a unidirectional W/Cu composite
NASA Astrophysics Data System (ADS)
Kim, Young-Suk; Verrilli, Michael J.; Halford, Gary R.
1992-05-01
A microstructural model was developed to predict creep-fatigue life in a (0)(sub 4), 9 volume percent tungsten fiber-reinforced copper matrix composite at the temperature of 833 K. The mechanism of failure of the composite is assumed to be governed by the growth of quasi-equilibrium cavities in the copper matrix of the composite, based on the microscopically observed failure mechanisms. The methodology uses a cavity growth model developed for prediction of creep fracture. Instantaneous values of strain rate and stress in the copper matrix during fatigue cycles were calculated and incorporated in the model to predict cyclic life. The stress in the copper matrix was determined by use of a simple two-bar model for the fiber and matrix during cyclic loading. The model successfully predicted the composite creep-fatigue life under tension-tension cyclic loading through the use of this instantaneous matrix stress level. Inclusion of additional mechanisms such as cavity nucleation, grain boundary sliding, and the effect of fibers on matrix-stress level would result in more generalized predictions of creep-fatigue life.
A creep cavity growth model for creep-fatigue life prediction of a unidirectional W/Cu composite
NASA Technical Reports Server (NTRS)
Kim, Young-Suk; Verrilli, Michael J.; Halford, Gary R.
1992-01-01
A microstructural model was developed to predict creep-fatigue life in a (0)(sub 4), 9 volume percent tungsten fiber-reinforced copper matrix composite at the temperature of 833 K. The mechanism of failure of the composite is assumed to be governed by the growth of quasi-equilibrium cavities in the copper matrix of the composite, based on the microscopically observed failure mechanisms. The methodology uses a cavity growth model developed for prediction of creep fracture. Instantaneous values of strain rate and stress in the copper matrix during fatigue cycles were calculated and incorporated in the model to predict cyclic life. The stress in the copper matrix was determined by use of a simple two-bar model for the fiber and matrix during cyclic loading. The model successfully predicted the composite creep-fatigue life under tension-tension cyclic loading through the use of this instantaneous matrix stress level. Inclusion of additional mechanisms such as cavity nucleation, grain boundary sliding, and the effect of fibers on matrix-stress level would result in more generalized predictions of creep-fatigue life.
Tissue-scale, personalized modeling and simulation of prostate cancer growth
NASA Astrophysics Data System (ADS)
Lorenzo, Guillermo; Scott, Michael A.; Tew, Kevin; Hughes, Thomas J. R.; Zhang, Yongjie Jessica; Liu, Lei; Vilanova, Guillermo; Gomez, Hector
2016-11-01
Recently, mathematical modeling and simulation of diseases and their treatments have enabled the prediction of clinical outcomes and the design of optimal therapies on a personalized (i.e., patient-specific) basis. This new trend in medical research has been termed “predictive medicine.” Prostate cancer (PCa) is a major health problem and an ideal candidate to explore tissue-scale, personalized modeling of cancer growth for two main reasons: First, it is a small organ, and, second, tumor growth can be estimated by measuring serum prostate-specific antigen (PSA, a PCa biomarker in blood), which may enable in vivo validation. In this paper, we present a simple continuous model that reproduces the growth patterns of PCa. We use the phase-field method to account for the transformation of healthy cells to cancer cells and use diffusion-reaction equations to compute nutrient consumption and PSA production. To accurately and efficiently compute tumor growth, our simulations leverage isogeometric analysis (IGA). Our model is shown to reproduce a known shape instability from a spheroidal pattern to fingered growth. Results of our computations indicate that such shift is a tumor response to escape starvation, hypoxia, and, eventually, necrosis. Thus, branching enables the tumor to minimize the distance from inner cells to external nutrients, contributing to cancer survival and further development. We have also used our model to perform tissue-scale, personalized simulation of a PCa patient, based on prostatic anatomy extracted from computed tomography images. This simulation shows tumor progression similar to that seen in clinical practice.
NASA Astrophysics Data System (ADS)
Rienow, Andreas; Stenger, Dirk
2014-07-01
The Ruhr is an "old acquaintance" in the discourse of urban decline in old industrialized cities. The agglomeration has to struggle with archetypical problems of former monofunctional manufacturing cities. Surprisingly, the image of a shrinking city has to be refuted if you shift the focus from socioeconomic wealth to its morphological extension. Thus, it is the objective of this study to meet the challenge of modeling urban sprawl and demographic decline by combining two artificial intelligent solutions: The popular urban cellular automaton SLEUTH simulates urban growth using four simple but effective growth rules. In order to improve its performance, SLEUTH has been modified among others by combining it with a robust probability map based on support vector machines. Additionally, a complex multi-agent system is developed to simulate residential mobility in a shrinking city agglomeration: residential mobility and the housing market of shrinking city systems focuses on the dynamic of interregional housing markets implying the development of potential dwelling areas. The multi-agent system comprises the simulation of population patterns, housing prices, and housing demand in shrinking city agglomerations. Both models are calibrated and validated regarding their localization and quantification performance. Subsequently, the urban landscape configuration and composition of the Ruhr 2025 are simulated. A simple spatial join is used to combine the results serving as valuable inputs for future regional planning in the context of multifarious demographic change and preceding urban growth.
Kumar, Rakesh; Maurya, Ranjana; Saran, Shweta
2018-02-23
Prostate cancer (PC) is one of the leading cancers in men, raising a serious health issue worldwide. Due to lack of suitable biomarker, their inhibitors and the platform for testing those inhibitors result in poor prognosis of PC. AMP-activated protein kinase (AMPK) is a highly conserved protein kinase found in eukaryotes that is involved in growth and development, and also acts as a therapeutic target for PC. The aim of the present study is to identify novel potent inhibitors of AMPK and propose a simple cellular model system for understanding its biology. Structural modelling and MD simulations were performed to construct and refine the 3D models of Dictyostelium and human AMPK. Binding mechanisms of different drug compounds were studied by performing molecular docking, molecular dynamics and MM-PBSA methods. Two novel drugs were isolated having higher binding affinity over the known drugs and hydrophobic forces that played a key role during protein-ligand interactions. The study also explored the simple cellular model system for drug screening and understanding the biology of a therapeutic target by performing in vitro experiments.
Dynamical patterns and regime shifts in the nonlinear model of soil microorganisms growth
NASA Astrophysics Data System (ADS)
Zaitseva, Maria; Vladimirov, Artem; Winter, Anna-Marie; Vasilyeva, Nadezda
2017-04-01
Dynamical model of soil microorganisms growth and turnover is formulated as a system of nonlinear partial differential equations of reaction-diffusion type. We consider spatial distributions of concentrations of several substrates and microorganisms. Biochemical reactions are modelled by chemical kinetic equations. Transport is modelled by simple linear diffusion for all chemical substances, while for microorganisms we use different transport functions, e.g. some of them can actively move along gradient of substrate concentration, while others cannot move. We solve our model in two dimensions, starting from uniform state with small initial perturbations for various parameters and find parameter range, where small initial perturbations grow and evolve. We search for bifurcation points and critical regime shifts in our model and analyze time-space profile and phase portraits of these solutions approaching critical regime shifts in the system, exploring possibility to detect such shifts in advance. This work is supported by NordForsk, project #81513.
Exploring the patterns and evolution of self-organized urban street networks through modeling
NASA Astrophysics Data System (ADS)
Rui, Yikang; Ban, Yifang; Wang, Jiechen; Haas, Jan
2013-03-01
As one of the most important subsystems in cities, urban street networks have recently been well studied by using the approach of complex networks. This paper proposes a growing model for self-organized urban street networks. The model involves a competition among new centers with different values of attraction radius and a local optimal principle of both geometrical and topological factors. We find that with the model growth, the local optimization in the connection process and appropriate probability for the loop construction well reflect the evolution strategy in real-world cities. Moreover, different values of attraction radius in centers competition process lead to morphological change in patterns including urban network, polycentric and monocentric structures. The model succeeds in reproducing a large diversity of road network patterns by varying parameters. The similarity between the properties of our model and empirical results implies that a simple universal growth mechanism exists in self-organized cities.
A Simple Model of Entrepreneurship for Principles of Economics Courses
ERIC Educational Resources Information Center
Gunter, Frank R.
2012-01-01
The critical roles of entrepreneurs in creating, operating, and destroying markets, as well as their importance in driving long-term economic growth are still generally either absent from principles of economics texts or relegated to later chapters. The primary difficulties in explaining entrepreneurship at the principles level are the lack of a…
Overload retardation due to plasticity-induced crack closure
NASA Technical Reports Server (NTRS)
Fleck, N. A.; Shercliff, H. R.
1989-01-01
Experiments are reported which show that plasticity-induced crack closure can account for crack growth retardation following an overload. The finite element method is used to provide evidence which supports the experimental observations of crack closure. Finally, a simple model is presented which predicts with limited success the retardation transient following an overload.
Due to complex population dynamics and source-sink metapopulation processes, animal fitness sometimes varies across landscapes in ways that cannot be deduced from simple density patterns. In this study, we examine spatial patterns in fitness using a combination of intensive fiel...
Estimating annual bole biomass production using uncertainty analysis
Travis J. Woolley; Mark E. Harmon; Kari B. O' Connell
2007-01-01
Two common sampling methodologies coupled with a simple statistical model were evaluated to determine the accuracy and precision of annual bole biomass production (BBP) and inter-annual variability estimates using this type of approach. We performed an uncertainty analysis using Monte Carlo methods in conjunction with radial growth core data from trees in three Douglas...
Filopodial dynamics and growth cone stabilization in Drosophila visual circuit development
Özel, Mehmet Neset; Langen, Marion; Hassan, Bassem A; Hiesinger, P Robin
2015-01-01
Filopodial dynamics are thought to control growth cone guidance, but the types and roles of growth cone dynamics underlying neural circuit assembly in a living brain are largely unknown. To address this issue, we have developed long-term, continuous, fast and high-resolution imaging of growth cone dynamics from axon growth to synapse formation in cultured Drosophila brains. Using R7 photoreceptor neurons as a model we show that >90% of the growth cone filopodia exhibit fast, stochastic dynamics that persist despite ongoing stepwise layer formation. Correspondingly, R7 growth cones stabilize early and change their final position by passive dislocation. N-Cadherin controls both fast filopodial dynamics and growth cone stabilization. Surprisingly, loss of N-Cadherin causes no primary targeting defects, but destabilizes R7 growth cones to jump between correct and incorrect layers. Hence, growth cone dynamics can influence wiring specificity without a direct role in target recognition and implement simple rules during circuit assembly. DOI: http://dx.doi.org/10.7554/eLife.10721.001 PMID:26512889
Using phenomenological models for forecasting the 2015 Ebola challenge.
Pell, Bruce; Kuang, Yang; Viboud, Cecile; Chowell, Gerardo
2018-03-01
The rising number of novel pathogens threatening the human population has motivated the application of mathematical modeling for forecasting the trajectory and size of epidemics. We summarize the real-time forecasting results of the logistic equation during the 2015 Ebola challenge focused on predicting synthetic data derived from a detailed individual-based model of Ebola transmission dynamics and control. We also carry out a post-challenge comparison of two simple phenomenological models. In particular, we systematically compare the logistic growth model and a recently introduced generalized Richards model (GRM) that captures a range of early epidemic growth profiles ranging from sub-exponential to exponential growth. Specifically, we assess the performance of each model for estimating the reproduction number, generate short-term forecasts of the epidemic trajectory, and predict the final epidemic size. During the challenge the logistic equation consistently underestimated the final epidemic size, peak timing and the number of cases at peak timing with an average mean absolute percentage error (MAPE) of 0.49, 0.36 and 0.40, respectively. Post-challenge, the GRM which has the flexibility to reproduce a range of epidemic growth profiles ranging from early sub-exponential to exponential growth dynamics outperformed the logistic growth model in ascertaining the final epidemic size as more incidence data was made available, while the logistic model underestimated the final epidemic even with an increasing amount of data of the evolving epidemic. Incidence forecasts provided by the generalized Richards model performed better across all scenarios and time points than the logistic growth model with mean RMS decreasing from 78.00 (logistic) to 60.80 (GRM). Both models provided reasonable predictions of the effective reproduction number, but the GRM slightly outperformed the logistic growth model with a MAPE of 0.08 compared to 0.10, averaged across all scenarios and time points. Our findings further support the consideration of transmission models that incorporate flexible early epidemic growth profiles in the forecasting toolkit. Such models are particularly useful for quickly evaluating a developing infectious disease outbreak using only case incidence time series of the early phase of an infectious disease outbreak. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.
In Search of a Better Bean: A Simple Activity to Introduce Plant Biology
ERIC Educational Resources Information Center
Spaccarotella, Kim; James, Roxie
2014-01-01
Measuring plant stem growth over time is a simple activity commonly used to introduce concepts in growth and development in plant biology (Reid & Pu, 2007). This Quick Fix updates the activity and incorporates a real-world application: students consider possible effects of soil substrate and sunlight conditions on plant growth without needing…
Data-driven outbreak forecasting with a simple nonlinear growth model.
Lega, Joceline; Brown, Heidi E
2016-12-01
Recent events have thrown the spotlight on infectious disease outbreak response. We developed a data-driven method, EpiGro, which can be applied to cumulative case reports to estimate the order of magnitude of the duration, peak and ultimate size of an ongoing outbreak. It is based on a surprisingly simple mathematical property of many epidemiological data sets, does not require knowledge or estimation of disease transmission parameters, is robust to noise and to small data sets, and runs quickly due to its mathematical simplicity. Using data from historic and ongoing epidemics, we present the model. We also provide modeling considerations that justify this approach and discuss its limitations. In the absence of other information or in conjunction with other models, EpiGro may be useful to public health responders. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.
NASA Astrophysics Data System (ADS)
Yang, Pu
Since the application of nanowires may lead to a new generation of electronic, optoelectronic and magnetic devices, there is much research on understanding the growth mechanism of various "self assembled" nanowires on semiconductor surfaces. The motivation of the present work is to use theoretical modeling to study the conditions required to form and grow elongated islands and nanowires. In this work, a modeling method is developed to study the time-dependent anisotropic diffusion and growth in two dimensions for an array of rectangular islands. This method uses discrete Fast Fourier Transformation (FFT) to solve the time-dependent diffusion equation on the surface. The ad-particles are captured and incorporated to the island edge to simulate island growth. Implemented in MATLABRTM programs, this model produces expected faceted shapes; the calculation runs very fast on a common personal computer. Time-dependent island growth and the evolving diffusion field have been visualized using simple MATLABRTM functions and can be made into MATLABRTM movies. This modeling method is applied to simulate elongated island and nanowire growth by incorporating anisotropic bonding at the island edge. When there is a full sink in one direction and partial sink in the other direction at the island edge, the model results in the growth of an elongated island with an aspect ratio that stabilizes after it reaches a certain value. This result agrees with experimental data on "endotaxial" nanowire growth. For the island edge with a full sink in one direction and no sink in the other direction, the island grows in length with constant width, which is comparable to experimental data on Bi nanoline and rare-earth metal nanowire growth.
Scaling behavior in corrosion and growth of a passive film.
Aarão Reis, F D A; Stafiej, Janusz
2007-07-01
We study a simple model for metal corrosion controlled by the reaction rate of the metal with an anionic species and the diffusion of that species in the growing passive film between the solution and the metal. A crossover from the reaction-controlled to the diffusion-controlled growth regime with different roughening properties is observed. Scaling arguments provide estimates of the crossover time and film thickness as functions of the reaction and diffusion rates and the concentration of anionic species in the film-solution interface, including a nontrivial square-root dependence on that concentration. At short times, the metal-film interface exhibits Kardar-Parisi-Zhang (KPZ) scaling, which crosses over to a diffusion-limited erosion (Laplacian growth) regime at long times. The roughness of the metal-film interface at long times is obtained as a function of the rates of reaction and diffusion and of the KPZ growth exponent. The predictions have been confirmed by simulations of a lattice version of the model in two dimensions. Relations with other erosion and corrosion models and possible applications are discussed.
Estimation of the curvature of the solid liquid interface during Bridgman crystal growth
NASA Astrophysics Data System (ADS)
Barat, Catherine; Duffar, Thierry; Garandet, Jean-Paul
1998-11-01
An approximate solution for the solid/liquid interface curvature due to the crucible effect in crystal growth is derived from simple heat flux considerations. The numerical modelling of the problem carried out with the help of the finite element code FIDAP supports the predictions of our analytical expression and allows to identify its range of validity. Experimental interface curvatures, measured in gallium antimonide samples grown by the vertical Bridgman method, are seen to compare satisfactorily to analytical and numerical results. Other literature data are also in fair agreement with the predictions of our models in the case where the amount of heat carried by the crucible is small compared to the overall heat flux.
Random functions via Dyson Brownian Motion: progress and problems
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wang, Gaoyuan; Battefeld, Thorsten
2016-09-05
We develope a computationally efficient extension of the Dyson Brownian Motion (DBM) algorithm to generate random function in C{sup 2} locally. We further explain that random functions generated via DBM show an unstable growth as the traversed distance increases. This feature restricts the use of such functions considerably if they are to be used to model globally defined ones. The latter is the case if one uses random functions to model landscapes in string theory. We provide a concrete example, based on a simple axionic potential often used in cosmology, to highlight this problem and also offer an ad hocmore » modification of DBM that suppresses this growth to some degree.« less
An overview of longitudinal data analysis methods for neurological research.
Locascio, Joseph J; Atri, Alireza
2011-01-01
The purpose of this article is to provide a concise, broad and readily accessible overview of longitudinal data analysis methods, aimed to be a practical guide for clinical investigators in neurology. In general, we advise that older, traditional methods, including (1) simple regression of the dependent variable on a time measure, (2) analyzing a single summary subject level number that indexes changes for each subject and (3) a general linear model approach with a fixed-subject effect, should be reserved for quick, simple or preliminary analyses. We advocate the general use of mixed-random and fixed-effect regression models for analyses of most longitudinal clinical studies. Under restrictive situations or to provide validation, we recommend: (1) repeated-measure analysis of covariance (ANCOVA), (2) ANCOVA for two time points, (3) generalized estimating equations and (4) latent growth curve/structural equation models.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Klein, William
Over the 21 years of funding we have pursued several projects related to earthquakes, damage and nucleation. We developed simple models of earthquake faults which we studied to understand Gutenburg-Richter scaling, foreshocks and aftershocks, the effect of spatial structure of the faults and its interaction with underlying self organization and phase transitions. In addition we studied the formation of amorphous solids via the glass transition. We have also studied nucleation with a particular concentration on transitions in systems with a spatial symmetry change. In addition we investigated the nucleation process in models that mimic rock masses. We obtained the structuremore » of the droplet in both homogeneous and heterogeneous nucleation. We also investigated the effect of defects or asperities on the nucleation of failure in simple models of earthquake faults.« less
Damage and strength of composite materials: Trends, predictions, and challenges
NASA Technical Reports Server (NTRS)
Obrien, T. Kevin
1994-01-01
Research on damage mechanisms and ultimate strength of composite materials relevant to scaling issues will be addressed in this viewgraph presentation. The use of fracture mechanics and Weibull statistics to predict scaling effects for the onset of isolated damage mechanisms will be highlighted. The ability of simple fracture mechanics models to predict trends that are useful in parametric or preliminary designs studies will be reviewed. The limitations of these simple models for complex loading conditions will also be noted. The difficulty in developing generic criteria for the growth of these mechanisms needed in progressive damage models to predict strength will be addressed. A specific example for a problem where failure is a direct consequence of progressive delamination will be explored. A damage threshold/fail-safety concept for addressing composite damage tolerance will be discussed.
Theory for Transitions Between Exponential and Stationary Phases: Universal Laws for Lag Time
NASA Astrophysics Data System (ADS)
Himeoka, Yusuke; Kaneko, Kunihiko
2017-04-01
The quantitative characterization of bacterial growth has attracted substantial attention since Monod's pioneering study. Theoretical and experimental works have uncovered several laws for describing the exponential growth phase, in which the number of cells grows exponentially. However, microorganism growth also exhibits lag, stationary, and death phases under starvation conditions, in which cell growth is highly suppressed, for which quantitative laws or theories are markedly underdeveloped. In fact, the models commonly adopted for the exponential phase that consist of autocatalytic chemical components, including ribosomes, can only show exponential growth or decay in a population; thus, phases that halt growth are not realized. Here, we propose a simple, coarse-grained cell model that includes an extra class of macromolecular components in addition to the autocatalytic active components that facilitate cellular growth. These extra components form a complex with the active components to inhibit the catalytic process. Depending on the nutrient condition, the model exhibits typical transitions among the lag, exponential, stationary, and death phases. Furthermore, the lag time needed for growth recovery after starvation follows the square root of the starvation time and is inversely related to the maximal growth rate. This is in agreement with experimental observations, in which the length of time of cell starvation is memorized in the slow accumulation of molecules. Moreover, the lag time distributed among cells is skewed with a long time tail. If the starvation time is longer, an exponential tail appears, which is also consistent with experimental data. Our theory further predicts a strong dependence of lag time on the speed of substrate depletion, which can be tested experimentally. The present model and theoretical analysis provide universal growth laws beyond the exponential phase, offering insight into how cells halt growth without entering the death phase.
Analysis of the vapor-liquid-solid mechanism for nanowire growth and a model for this mechanism.
Mohammad, S Noor
2008-05-01
The vapor-liquid-solid (VLS) mechanism is most widely employed to grow nanowires (NWs). The mechanism uses foreign element catalytic agent (FECA) to mediate the growth. Because of this, it is believed to be very stable with the FECA-mediated droplets not consumed even when reaction conditions change. Recent experiments however differ, which suggest that even under cleanest growth conditions, VLS mechanism may not produce long, thin, uniform, single-crystal nanowires of high purity. The present investigation has addressed various issues involving fundamentals of VLS growth. While addressing these issues, it has taken into consideration the influence of the electrical, hydrodynamic, thermodynamic, and surface tension effects on NW growth. It has found that parameters such as mesoscopic effects on nanoparticle seeds, charge distribution in FECA-induced droplets, electronegativity of the droplet with respect to those of reactive nanowire vapor species, growth temperature, and chamber pressure play important role in the VLS growth. On the basis of an in-depth analysis of various issues, a simple, novel, malleable (SNM) model has been presented for the VLS mechanism. The model appears to explain the formation and observed characteristics of a wide variety of nanowires, including elemental and compound semiconductor nanowires. Also it provides an understanding of the influence of the dynamic behavior of the droplets on the NW growth. This study finds that increase in diameter with time of the droplet of tapered nanowires results primarily from gradual incorporation of oversupplied nanowire species into the FECA-mediated droplet, which is supported by experiments. It finds also that optimum compositions of the droplet constituents are crucial for VLS nanowire growth. An approximate model presented to exemplify the parametric dependency of VLS growth provides good description of NW growth rate as a function of temperature.
Predicting overload-affected fatigue crack growth in steels
DOE Office of Scientific and Technical Information (OSTI.GOV)
Skorupa, M.; Skorupa, A.; Ladecki, B.
1996-12-01
The ability of semi-empirical crack closure models to predict the effect of overloads on fatigue crack growth in low-alloy steels has been investigated. With this purpose, the CORPUS model developed for aircraft metals and spectra has been checked first through comparisons between the simulated and observed results for a low-alloy steel. The CORPUS predictions of crack growth under several types of simple load histories containing overloads appeared generally unconservative which prompted the authors to formulate a new model, more suitable for steels. With the latter approach, the assumed evolution of the crack opening stress during the delayed retardation stage hasmore » been based on experimental results reported for various steels. For all the load sequences considered, the predictions from the proposed model appeared to be by far more accurate than those from CORPUS. Based on the analysis results, the capability of semi-empirical prediction concepts to cover experimentally observed trends that have been reported for sequences with overloads is discussed. Finally, possibilities of improving the model performance are considered.« less
Simple Models for Nanocrystal Growth
NASA Astrophysics Data System (ADS)
Jensen, Pablo
Growth of new materials with tailored properties is one of the most active research directions for physicists. As pointed out by Silvan Schweber in his brilliant analysis of the evolution of physics after World War II [1] "An important transformation has taken place in physics: As had previously happened in chemistry, an ever larger fraction of the efforts in the field were being devoted to the study of novelty rather than to the elucidation of fundamental laws and interactions […] The successes of quantum mechanics at the atomic level immediately made it clear to the more perspicacious physicists that the laws behind the phenomena had been apprehended, that they could therefore control the behavior of simple macroscopic systems and, more importantly, that they could create new structures, new objects and new phenomena […] Condensed matter physics has indeed become the study of systems that have never before existed. Phenomena such as superconductivity are genuine novelties in the universe."
Uchimura, Tomoya; Hollander, Judith M; Nakamura, Daisy S; Liu, Zhiyi; Rosen, Clifford J; Georgakoudi, Irene; Zeng, Li
2017-10-01
Postnatal bone growth involves a dramatic increase in length and girth. Intriguingly, this period of growth is independent of growth hormone and the underlying mechanism is poorly understood. Recently, an IGF2 mutation was identified in humans with early postnatal growth restriction. Here, we show that IGF2 is essential for longitudinal and appositional murine postnatal bone development, which involves proper timing of chondrocyte maturation and perichondrial cell differentiation and survival. Importantly, the Igf2 null mouse model does not represent a simple delay of growth but instead uncoordinated growth plate development. Furthermore, biochemical and two-photon imaging analyses identified elevated and imbalanced glucose metabolism in the Igf2 null mouse. Attenuation of glycolysis rescued the mutant phenotype of premature cartilage maturation, thereby indicating that IGF2 controls bone growth by regulating glucose metabolism in chondrocytes. This work links glucose metabolism with cartilage development and provides insight into the fundamental understanding of human growth abnormalities. © 2017. Published by The Company of Biologists Ltd.
Validating a model that predicts daily growth and feed quality of New Zealand dairy pastures.
Woodward, S J
2001-09-01
The Pasture Quality (PQ) model is a simple, mechanistic, dynamical system model that was designed to capture the essential biological processes in grazed grass-clover pasture, and to be optimised to derive improved grazing strategies for New Zealand dairy farms. While the individual processes represented in the model (photosynthesis, tissue growth, flowering, leaf death, decomposition, worms) were based on experimental data, this did not guarantee that the assembled model would accurately predict the behaviour of the system as a whole (i.e., pasture growth and quality). Validation of the whole model was thus a priority, since any strategy derived from the model could impact a farm business in the order of thousands of dollars per annum if adopted. This paper describes the process of defining performance criteria for the model, obtaining suitable data to test the model, and carrying out the validation analysis. The validation process highlighted a number of weaknesses in the model, which will lead to the model being improved. As a result, the model's utility will be enhanced. Furthermore, validation was found to have an unexpected additional benefit, in that despite the model's poor initial performance, support was generated for the model among field scientists involved in the wider project.
Toward an Ising Model of Cancer and Beyond
Torquato, Salvatore
2011-01-01
The holy grail of tumor modeling is to formulate theoretical and computational tools that can be utilized in the clinic to predict neoplastic progression and propose individualized optimal treatment strategies to control cancer growth. In order to develop such a predictive model, one must account for the numerous complex mechanisms involved in tumor growth. Here we review resarch work that we have done toward the development of an “Ising model” of cancer. The Ising model is an idealized statistical-mechanical model of ferromagnetism that is based on simple local-interaction rules, but nonetheless leads to basic insights and features of real magnets, such as phase transitions with a critical point. The review begins with a description of a minimalist four-dimensional (three dimensions in space and one in time) cellular automaton (CA) model of cancer in which healthy cells transition between states (proliferative, hypoxic, and necrotic) according to simple local rules and their present states, which can viewed as a stripped-down Ising model of cancer. This model is applied to model the growth of glioblastoma multiforme, the most malignant of brain cancers. This is followed by a discussion of the extension of the model to study the effect on the tumor dynamics and geometry of a mutated subpopulation. A discussion of how tumor growth is affected by chemotherapeutic treatment, including induced resistance, is then described. How angiogenesis as well as the heterogeneous and confined environment in which a tumor grows is incorporated in the CA model is discussed. The characterization of the level of organization of the invasive network around a solid tumor using spanning trees is subsequently described. Then, we describe open problems and future promising avenues for future research, including the need to develop better molecular-based models that incorporate the true heterogeneous environment over wide range of length and time scales (via imaging data), cell motility, oncogenes, tumor suppressor genes and cell-cell communication. A discussion about the need to bring to bear the powerful machinery of the theory of heterogeneous media to better understand the behavior of cancer in its microenvironment is presented. Finally, we propose the possibility of using optimization techniques, which have been used profitably to understand physical phenomena, in order to devise therapeutic (chemotherapy/radiation) strategies and to understand tumorigenesis itself. PMID:21301063
Diverging patterns with endogenous labor migration.
Reichlin, P; Rustichini, A
1998-05-05
"The standard neoclassical model cannot explain persistent migration flows and lack of cross-country convergence when capital and labor are mobile. Here we present a model where both phenomena may take place.... Our model is based on the Arrow-Romer approach to endogenous growth theory. We single out the importance of a (however weak) scale effect from the size of the workforce.... The main conclusion of this simple model is that lack of convergence, or even divergence, among countries is possible, even with perfect capital mobility and labor mobility." excerpt
Simulation of fatigue crack growth under large scale yielding conditions
NASA Astrophysics Data System (ADS)
Schweizer, Christoph; Seifert, Thomas; Riedel, Hermann
2010-07-01
A simple mechanism based model for fatigue crack growth assumes a linear correlation between the cyclic crack-tip opening displacement (ΔCTOD) and the crack growth increment (da/dN). The objective of this work is to compare analytical estimates of ΔCTOD with results of numerical calculations under large scale yielding conditions and to verify the physical basis of the model by comparing the predicted and the measured evolution of the crack length in a 10%-chromium-steel. The material is described by a rate independent cyclic plasticity model with power-law hardening and Masing behavior. During the tension-going part of the cycle, nodes at the crack-tip are released such that the crack growth increment corresponds approximately to the crack-tip opening. The finite element analysis performed in ABAQUS is continued for so many cycles until a stabilized value of ΔCTOD is reached. The analytical model contains an interpolation formula for the J-integral, which is generalized to account for cyclic loading and crack closure. Both simulated and estimated ΔCTOD are reasonably consistent. The predicted crack length evolution is found to be in good agreement with the behavior of microcracks observed in a 10%-chromium steel.
G-Jitter Effects in Protein Crystal Growth - A Numerical Study
NASA Technical Reports Server (NTRS)
Ramachandran, N.; Baugher, C. R.
1995-01-01
The impact of spacecraft acceleration environment on Protein Crystal Growth (PCG) is studied. A brief overview of the Space Shuttle acceleration environment is provided followed by a simple scaling procedure used to obtain estimates of the flow and concentration field characteristics in PCG. A detailed two-dimensional numerical model is then used to simulate the PCG system response to different disturbance scenarios; viz. residual g effects, impulse type disturbances and oscillatory inputs. The results show that PCG is susceptible to g-jitter and is a good candidate for vibration isolation.
Taguchi method for partial differential equations with application in tumor growth.
Ilea, M; Turnea, M; Rotariu, M; Arotăriţei, D; Popescu, Marilena
2014-01-01
The growth of tumors is a highly complex process. To describe this process, mathematical models are needed. A variety of partial differential mathematical models for tumor growth have been developed and studied. Most of those models are based on the reaction-diffusion equations and mass conservation law. A variety of modeling strategies have been developed, each focusing on tumor growth. Systems of time-dependent partial differential equations occur in many branches of applied mathematics. The vast majority of mathematical models in tumor growth are formulated in terms of partial differential equations. We propose a mathematical model for the interactions between these three cancer cell populations. The Taguchi methods are widely used by quality engineering scientists to compare the effects of multiple variables, together with their interactions, with a simple and manageable experimental design. In Taguchi's design of experiments, variation is more interesting to study than the average. First, Taguchi methods are utilized to search for the significant factors and the optimal level combination of parameters. Except the three parameters levels, other factors levels other factors levels would not be considered. Second, cutting parameters namely, cutting speed, depth of cut, and feed rate are designed using the Taguchi method. Finally, the adequacy of the developed mathematical model is proved by ANOVA. According to the results of ANOVA, since the percentage contribution of the combined error is as small. Many mathematical models can be quantitatively characterized by partial differential equations. The use of MATLAB and Taguchi method in this article illustrates the important role of informatics in research in mathematical modeling. The study of tumor growth cells is an exciting and important topic in cancer research and will profit considerably from theoretical input. Interpret these results to be a permanent collaboration between math's and medical oncologists.
Pattern formation with proportionate growth
NASA Astrophysics Data System (ADS)
Dhar, Deepak
It is a common observation that as baby animals grow, different body parts grow approximately at same rate. This property, called proportionate growth is remarkable in that it is not encountered easily outside biology. The models of growth that have been studied in Physics so far, e.g diffusion -limited aggregation, surface deposition, growth of crystals from melt etc. involve only growth at the surface, with the inner structure remaining frozen. Interestingly, patterns formed in growing sandpiles provide a very wide variety of patterns that show proportionate growth. One finds patterns with different features, with sharply defined boundaries. In particular, even with very simple rules, one can produce patterns that show striking resemblance to those seen in nature. We can characterize the asymptotic pattern exactly in some special cases. I will discuss in particular the patterns grown on noisy backgrounds. Supported by J. C. Bose fellowship from DST (India).
An ordinary differential equation model for full thickness wounds and the effects of diabetes.
Bowden, L G; Maini, P K; Moulton, D E; Tang, J B; Wang, X T; Liu, P Y; Byrne, H M
2014-11-21
Wound healing is a complex process in which a sequence of interrelated phases contributes to a reduction in wound size. For diabetic patients, many of these processes are compromised, so that wound healing slows down. In this paper we present a simple ordinary differential equation model for wound healing in which attention focusses on the dominant processes that contribute to closure of a full thickness wound. Asymptotic analysis of the resulting model reveals that normal healing occurs in stages: the initial and rapid elastic recoil of the wound is followed by a longer proliferative phase during which growth in the dermis dominates healing. At longer times, fibroblasts exert contractile forces on the dermal tissue, the resulting tension stimulating further dermal tissue growth and enhancing wound closure. By fitting the model to experimental data we find that the major difference between normal and diabetic healing is a marked reduction in the rate of dermal tissue growth for diabetic patients. The model is used to estimate the breakdown of dermal healing into two processes: tissue growth and contraction, the proportions of which provide information about the quality of the healed wound. We show further that increasing dermal tissue growth in the diabetic wound produces closure times similar to those associated with normal healing and we discuss the clinical implications of this hypothesised treatment. Copyright © 2014 Elsevier Ltd. All rights reserved.
Random-growth urban model with geographical fitness
NASA Astrophysics Data System (ADS)
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.
Johnston, A.S.A.; Hodson, M.E.; Thorbek, P.; Alvarez, T.; Sibly, R.M.
2014-01-01
Earthworms are important organisms in soil communities and so are used as model organisms in environmental risk assessments of chemicals. However current risk assessments of soil invertebrates are based on short-term laboratory studies, of limited ecological relevance, supplemented if necessary by site-specific field trials, which sometimes are challenging to apply across the whole agricultural landscape. Here, we investigate whether population responses to environmental stressors and pesticide exposure can be accurately predicted by combining energy budget and agent-based models (ABMs), based on knowledge of how individuals respond to their local circumstances. A simple energy budget model was implemented within each earthworm Eisenia fetida in the ABM, based on a priori parameter estimates. From broadly accepted physiological principles, simple algorithms specify how energy acquisition and expenditure drive life cycle processes. Each individual allocates energy between maintenance, growth and/or reproduction under varying conditions of food density, soil temperature and soil moisture. When simulating published experiments, good model fits were obtained to experimental data on individual growth, reproduction and starvation. Using the energy budget model as a platform we developed methods to identify which of the physiological parameters in the energy budget model (rates of ingestion, maintenance, growth or reproduction) are primarily affected by pesticide applications, producing four hypotheses about how toxicity acts. We tested these hypotheses by comparing model outputs with published toxicity data on the effects of copper oxychloride and chlorpyrifos on E. fetida. Both growth and reproduction were directly affected in experiments in which sufficient food was provided, whilst maintenance was targeted under food limitation. Although we only incorporate toxic effects at the individual level we show how ABMs can readily extrapolate to larger scales by providing good model fits to field population data. The ability of the presented model to fit the available field and laboratory data for E. fetida demonstrates the promise of the agent-based approach in ecology, by showing how biological knowledge can be used to make ecological inferences. Further work is required to extend the approach to populations of more ecologically relevant species studied at the field scale. Such a model could help extrapolate from laboratory to field conditions and from one set of field conditions to another or from species to species. PMID:25844009
NASA Astrophysics Data System (ADS)
Laura, P.; Probert, I.; Langer, G.; Aloisi, G.
2016-02-01
Coccolithophores are unicellular, calcifying marine algae that play a fundamental role in the oceanic carbon cycle. Recent research has focused on investigating the effect of ocean acidification on cellular calcification. However, the success of this important phytoplankton group in the future ocean will depend on how cellular growth reacts to changes in a combination of environmental variables. We carried out batch culture experiments in conditions of light- and nutrient- (nitrate and phosphate) limitation that reproduce the in situ conditions of a deep ecological niche of coccolithophores in the South Pacific Gyre (BIOSOPE cruise, 2004). We modelled nutrient acquisition and cellular growth in our batch experiments using a Droop internal-stores model. We show that nutrient acquisition and growth are decoupled in coccolithophores; this ability may be key in making life possible in oligotrophic conditions such as the deep BIOSOPE biological niche. Combining the results of our culture experiments with those of Langer et al. (2013), we used the model to obtain estimates of fundamental physiological parameters such as the Monod constant for nutrient uptake, the maximum growth rate and the minimum cellular nutrient quota. These parameters are characteristic of different phytoplankton groups and are needed to simulate phytoplankton growth in biogeochemical models. Our results suggest that growth of coccolithophores in the BIOSOPE deep ecological niche is light-limited rather than nutrient-limited. Our work also shows that simple batch experiments and straightforward numerical modelling are capable of providing estimates of physiological parameters usually obtained in more costly and complicated chemostat experiments.
Emergent dynamics of the climate-economy system in the Anthropocene.
Kellie-Smith, Owen; Cox, Peter M
2011-03-13
Global CO(2) emissions are understood to be the largest contributor to anthropogenic climate change, and have, to date, been highly correlated with economic output. However, there is likely to be a negative feedback between climate change and human wealth: economic growth is typically associated with an increase in CO(2) emissions and global warming, but the resulting climate change may lead to damages that suppress economic growth. This climate-economy feedback is assumed to be weak in standard climate change assessments. When the feedback is incorporated in a transparently simple model it reveals possible emergent behaviour in the coupled climate-economy system. Formulae are derived for the critical rates of growth of global CO(2) emissions that cause damped or long-term boom-bust oscillations in human wealth, thereby preventing a soft landing of the climate-economy system. On the basis of this model, historical rates of economic growth and decarbonization appear to put the climate-economy system in a potentially damaging oscillatory regime.
NASA Technical Reports Server (NTRS)
Carsey, Frank D.; Garwood, Ronald W.; Roach, Andrew T.
1993-01-01
In this paper we present an interpretation of coarse resolution passive microwave data for 1989 and 1992 in the context of a simple model of ice-edge retreat to obtain the Nordbukta emayment growth and the formation and migration of an Odden polynya.
Three Cs in Measurement Models: Causal Indicators, Composite Indicators, and Covariates
ERIC Educational Resources Information Center
Bollen, Kenneth A.; Bauldry, Shawn
2011-01-01
In the last 2 decades attention to causal (and formative) indicators has grown. Accompanying this growth has been the belief that one can classify indicators into 2 categories: effect (reflective) indicators and causal (formative) indicators. We argue that the dichotomous view is too simple. Instead, there are effect indicators and 3 types of…
Using a Simple "Escherichia Coli" Growth Curve Model to Teach the Scientific Method
ERIC Educational Resources Information Center
McKernan, Lisa N.
2015-01-01
The challenge of teaching in the sciences is not only conveying knowledge in the discipline, but also developing essential critical thinking, data analysis, and scientific writing skills. I outline an exercise that can be done easily as part of a microbiology laboratory course. It teaches the nature of the research process, from asking questions…
Cable logging production rate equations for thinning young-growth Douglas-fir
Chris B. LeDoux; Lawson W. Starnes
1986-01-01
A cable logging thinning simulation model and field study data from cable thinning production studies have been assembled and converted into a set of simple equations. These equations can be used to estimate the hourly production rates of various cable thinning machines operating in the mountainous terrain of western Oregon and western Washington. The equations include...
A Constitutive Relationship between Crack Propagation and Specific Damping Capacity in Steel
1990-10-01
diagnostic tool for detecting crack growth in structures. The model must be simple to act as a tool, but it must be comprehensive to provide accuracy...strain for static fracture u ECritical strain above which plastic strain occursP EAverage value of the cyclic plastic-strain rangeP E t ln(Ao/AI), true
NASA Astrophysics Data System (ADS)
Rendel, Pedro M.; Gavrieli, Ittai; Wolff-Boenisch, Domenik; Ganor, Jiwchar
2018-03-01
The main obstacle in the formulation of a quantitative rate-model for mineral precipitation is the absence of a rigorous method for coupling nucleation and growth processes. In order to link both processes, we conducted a series of batch experiments in which gypsum nucleation was followed by crystal growth. Experiments were carried out using various stirring methods in several batch vessels made of different materials. In the experiments, the initial degree of supersaturation of the solution with respect to gypsum (Ωgyp) was set between 1.58 and 1.82. Under these conditions, heterogeneous nucleation is the dominant nucleation mode. Based on changes in SO42- concentration with time, the induction time of gypsum nucleation and the following rate of crystal growth were calculated for each experiment. The induction time (6-104 h) was found to be a function of the vessel material, while the rates of crystal growth, which varied over three orders of magnitude, were strongly affected by the stirring speed and its mode (i.e. rocking, shaking, magnetic stirrer, and magnetic impeller). The SO42- concentration data were then used to formulate a forward model that couples the simple rate laws for nucleation and crystal growth of gypsum into a single kinetic model. Accordingly, the obtained rate law is based on classical nucleation theory and heterogeneous crystal growth.
NASA Technical Reports Server (NTRS)
Naumann, R. J.
1982-01-01
A relatively simple one-dimensional thermal model of the Bridgman growth process has been developed which is applicable to the growth of small diameter samples with conductivities similar to those of metallic alloys. The heat flow in a translating rod is analyzed in a way that is applicable to Biot numbers less than unity. The model accommodates an adiabatic zone, different heat transfer coefficients in the hot and cold zones, and changes in sample material properties associated with phase change. The analysis is applied to several simplified cases. The effect of the rod's motion is studied in a three-zone furnace for a rod sufficiently long that end effects can be neglected; end effects are then investigated for a motionless rod. Finally, the addition of a fourth zone, an independently controlled booster heater between the main heater and the adiabatic zone, is evaluated for its ability to increase the gradient in the sample at the melt interface and to control the position of the interface.
NASA Astrophysics Data System (ADS)
Hsu, Sze-Bi; Mei, Linfeng; Wang, Feng-Bin
2015-11-01
Phytoplankton species in a water column compete for mineral nutrients and light, and the existing models usually neglect differences in the nutrient content and the amount of light absorbed of individuals. In this current paper, we examine a size-structured and nonlocal reaction-diffusion-advection system which describes the dynamics of a single phytoplankton species in a water column where the species depends simply on light for its growth. Our model is under the assumption that the amount of light absorbed by individuals is proportional to cell size, which varies for populations that reproduce by simple division into two equally-sized daughters. We first establish the existence of a critical death rate and our analysis indicates that the phytoplankton survives if and only if its death rate is less than the critical death rate. The critical death rate depends on a general reproductive rate, the characteristics of the water column (e.g., turbulent diffusion rate, sinking, depth), cell growth, cell division, and cell size.
Yurk, Brian P
2018-07-01
Animal movement behaviors vary spatially in response to environmental heterogeneity. An important problem in spatial ecology is to determine how large-scale population growth and dispersal patterns emerge within highly variable landscapes. We apply the method of homogenization to study the large-scale behavior of a reaction-diffusion-advection model of population growth and dispersal. Our model includes small-scale variation in the directed and random components of movement and growth rates, as well as large-scale drift. Using the homogenized model we derive simple approximate formulas for persistence conditions and asymptotic invasion speeds, which are interpreted in terms of residence index. The homogenization results show good agreement with numerical solutions for environments with a high degree of fragmentation, both with and without periodicity at the fast scale. The simplicity of the formulas, and their connection to residence index make them appealing for studying the large-scale effects of a variety of small-scale movement behaviors.
[Radiotherapy and chaos theory: the tit bird and the butterfly...].
Denis, F; Letellier, C
2012-09-01
Although the same simple laws govern cancer outcome (cell division repeated again and again), each tumour has a different outcome before as well as after irradiation therapy. The linear-quadratic radiosensitivity model allows an assessment of tumor sensitivity to radiotherapy. This model presents some limitations in clinical practice because it does not take into account the interactions between tumour cells and non-tumoral bystander cells (such as endothelial cells, fibroblasts, immune cells...) that modulate radiosensitivity and tumor growth dynamics. These interactions can lead to non-linear and complex tumor growth which appears to be random but that is not since there is not so many tumors spontaneously regressing. In this paper we propose to develop a deterministic approach for tumour growth dynamics using chaos theory. Various characteristics of cancer dynamics and tumor radiosensitivity can be explained using mathematical models of competing cell species. Copyright © 2012 Société française de radiothérapie oncologique (SFRO). Published by Elsevier SAS. All rights reserved.
Takamatsu, Atsuko; Takaba, Eri; Takizawa, Ginjiro
2009-01-07
Branching network growth patterns, depending on environmental conditions, in plasmodium of true slime mold Physarum polycephalum were investigated. Surprisingly, the patterns resemble those in bacterial colonies even though the biological mechanisms differ greatly. Bacterial colonies are collectives of microorganisms in which individual organisms have motility and interact through nutritious and chemical fields. In contrast, the plasmodium is a giant amoeba-like multinucleated unicellular organism that forms a network of tubular structures through which protoplasm streams. The cell motility of the plasmodium is generated by oscillation phenomena observed in the partial bodies, which interact through the tubular structures. First, we analyze characteristics of the morphology quantitatively, then we abstract local rules governing the growing process to construct a simple network growth model. This model is independent of specific systems, in which only two rules are applied. Finally, we discuss the mechanism of commonly observed biological pattern formations through comparison with the system of bacterial colonies.
Temporal asymmetries in Interbank Market: an empirically grounded Agent-Based Model
NASA Astrophysics Data System (ADS)
Zlatic, Vinko; Popovic, Marko; Abraham, Hrvoje; Caldarelli, Guido; Iori, Giulia
2014-03-01
We analyse the changes in the topology of the structure of the E-mid interbank market in the period from September 1st 1999 to September 1st 2009. We uncover a type of temporal irreversibility in the growth of the largest component of the interbank trading network, which is not common to any of the usual network growth models. Such asymmetry, which is also detected on the growth of the clustering and reciprocity coefficient, reveals that the trading mechanism is driven by different dynamics at the beginning and at the end of the day. We are able to recover the complexity of the system by means of a simple Agent Based Model in which the probability of matching between counter parties depends on a time varying vertex fitness (or attractiveness) describing banks liquidity needs. We show that temporal irreversibility is associated with heterogeneity in the banking system and emerges when the distribution of liquidity shocks across banks is broad. We acknowledge support from FET project FOC-II.
Coupling Climate Models and Forward-Looking Economic Models
NASA Astrophysics Data System (ADS)
Judd, K.; Brock, W. A.
2010-12-01
Authors: Dr. Kenneth L. Judd, Hoover Institution, and Prof. William A. Brock, University of Wisconsin Current climate models range from General Circulation Models (GCM’s) with millions of degrees of freedom to models with few degrees of freedom. Simple Energy Balance Climate Models (EBCM’s) help us understand the dynamics of GCM’s. The same is true in economics with Computable General Equilibrium Models (CGE’s) where some models are infinite-dimensional multidimensional differential equations but some are simple models. Nordhaus (2007, 2010) couples a simple EBCM with a simple economic model. One- and two- dimensional ECBM’s do better at approximating damages across the globe and positive and negative feedbacks from anthroprogenic forcing (North etal. (1981), Wu and North (2007)). A proper coupling of climate and economic systems is crucial for arriving at effective policies. Brock and Xepapadeas (2010) have used Fourier/Legendre based expansions to study the shape of socially optimal carbon taxes over time at the planetary level in the face of damages caused by polar ice cap melt (as discussed by Oppenheimer, 2005) but in only a “one dimensional” EBCM. Economists have used orthogonal polynomial expansions to solve dynamic, forward-looking economic models (Judd, 1992, 1998). This presentation will couple EBCM climate models with basic forward-looking economic models, and examine the effectiveness and scaling properties of alternative solution methods. We will use a two dimensional EBCM model on the sphere (Wu and North, 2007) and a multicountry, multisector regional model of the economic system. Our aim will be to gain insights into intertemporal shape of the optimal carbon tax schedule, and its impact on global food production, as modeled by Golub and Hertel (2009). We will initially have limited computing resources and will need to focus on highly aggregated models. However, this will be more complex than existing models with forward-looking economic modules, and the initial models will help guide the construction of more refined models that can effectively use more powerful computational environments to analyze economic policies related to climate change. REFERENCES Brock, W., Xepapadeas, A., 2010, “An Integration of Simple Dynamic Energy Balance Climate Models and Ramsey Growth Models,” Department of Economics, University of Wisconsin, Madison, and University of Athens. Golub, A., Hertel, T., etal., 2009, “The opportunity cost of land use and the global potential for greenhouse gas mitigation in agriculture and forestry,” RESOURCE AND ENERGY ECONOMICS, 31, 299-319. Judd, K., 1992, “Projection methods for solving aggregate growth models,” JOURNAL OF ECONOMIC THEORY, 58: 410-52. Judd, K., 1998, NUMERICAL METHODS IN ECONOMICS, MIT Press, Cambridge, Mass. Nordhaus, W., 2007, A QUESTION OF BALANCE: ECONOMIC MODELS OF CLIMATE CHANGE, Yale University Press, New Haven, CT. North, G., R., Cahalan, R., Coakely, J., 1981, “Energy balance climate models,” REVIEWS OF GEOPHYSICS AND SPACE PHYSICS, Vol. 19, No. 1, 91-121, February Wu, W., North, G. R., 2007, “Thermal decay modes of a 2-D energy balance climate model,” TELLUS, 59A, 618-626.
Borchers, Steffen; Freund, Susann; Rath, Alexander; Streif, Stefan; Reichl, Udo; Findeisen, Rolf
2013-01-01
Production of bio-pharmaceuticals in cell culture, such as mammalian cells, is challenging. Mathematical models can provide support to the analysis, optimization, and the operation of production processes. In particular, unstructured models are suited for these purposes, since they can be tailored to particular process conditions. To this end, growth phases and the most relevant factors influencing cell growth and product formation have to be identified. Due to noisy and erroneous experimental data, unknown kinetic parameters, and the large number of combinations of influencing factors, currently there are only limited structured approaches to tackle these issues. We outline a structured set-based approach to identify different growth phases and the factors influencing cell growth and metabolism. To this end, measurement uncertainties are taken explicitly into account to bound the time-dependent specific growth rate based on the observed increase of the cell concentration. Based on the bounds on the specific growth rate, we can identify qualitatively different growth phases and (in-)validate hypotheses on the factors influencing cell growth and metabolism. We apply the approach to a mammalian suspension cell line (AGE1.HN). We show that growth in batch culture can be divided into two main growth phases. The initial phase is characterized by exponential growth dynamics, which can be described consistently by a relatively simple unstructured and segregated model. The subsequent phase is characterized by a decrease in the specific growth rate, which, as shown, results from substrate limitation and the pH of the medium. An extended model is provided which describes the observed dynamics of cell growth and main metabolites, and the corresponding kinetic parameters as well as their confidence intervals are estimated. The study is complemented by an uncertainty and outlier analysis. Overall, we demonstrate utility of set-based methods for analyzing cell growth and metabolism under conditions of uncertainty.
Borchers, Steffen; Freund, Susann; Rath, Alexander; Streif, Stefan; Reichl, Udo; Findeisen, Rolf
2013-01-01
Production of bio-pharmaceuticals in cell culture, such as mammalian cells, is challenging. Mathematical models can provide support to the analysis, optimization, and the operation of production processes. In particular, unstructured models are suited for these purposes, since they can be tailored to particular process conditions. To this end, growth phases and the most relevant factors influencing cell growth and product formation have to be identified. Due to noisy and erroneous experimental data, unknown kinetic parameters, and the large number of combinations of influencing factors, currently there are only limited structured approaches to tackle these issues. We outline a structured set-based approach to identify different growth phases and the factors influencing cell growth and metabolism. To this end, measurement uncertainties are taken explicitly into account to bound the time-dependent specific growth rate based on the observed increase of the cell concentration. Based on the bounds on the specific growth rate, we can identify qualitatively different growth phases and (in-)validate hypotheses on the factors influencing cell growth and metabolism. We apply the approach to a mammalian suspension cell line (AGE1.HN). We show that growth in batch culture can be divided into two main growth phases. The initial phase is characterized by exponential growth dynamics, which can be described consistently by a relatively simple unstructured and segregated model. The subsequent phase is characterized by a decrease in the specific growth rate, which, as shown, results from substrate limitation and the pH of the medium. An extended model is provided which describes the observed dynamics of cell growth and main metabolites, and the corresponding kinetic parameters as well as their confidence intervals are estimated. The study is complemented by an uncertainty and outlier analysis. Overall, we demonstrate utility of set-based methods for analyzing cell growth and metabolism under conditions of uncertainty. PMID:23936299
Murray, Kris A.; Skerratt, Lee F.; Garland, Stephen; Kriticos, Darren; McCallum, Hamish
2013-01-01
The pandemic amphibian disease chytridiomycosis often exhibits strong seasonality in both prevalence and disease-associated mortality once it becomes endemic. One hypothesis that could explain this temporal pattern is that simple weather-driven pathogen proliferation (population growth) is a major driver of chytridiomycosis disease dynamics. Despite various elaborations of this hypothesis in the literature for explaining amphibian declines (e.g., the chytrid thermal-optimum hypothesis) it has not been formally tested on infection patterns in the wild. In this study we developed a simple process-based model to simulate the growth of the pathogen Batrachochytrium dendrobatidis (Bd) under varying weather conditions to provide an a priori test of a weather-linked pathogen proliferation hypothesis for endemic chytridiomycosis. We found strong support for several predictions of the proliferation hypothesis when applied to our model species, Litoria pearsoniana, sampled across multiple sites and years: the weather-driven simulations of pathogen growth potential (represented as a growth index in the 30 days prior to sampling; GI30) were positively related to both the prevalence and intensity of Bd infections, which were themselves strongly and positively correlated. In addition, a machine-learning classifier achieved ∼72% success in classifying positive qPCR results when utilising just three informative predictors 1) GI30, 2) frog body size and 3) rain on the day of sampling. Hence, while intrinsic traits of the individuals sampled (species, size, sex) and nuisance sampling variables (rainfall when sampling) influenced infection patterns obtained when sampling via qPCR, our results also strongly suggest that weather-linked pathogen proliferation plays a key role in the infection dynamics of endemic chytridiomycosis in our study system. Predictive applications of the model include surveillance design, outbreak preparedness and response, climate change scenario modelling and the interpretation of historical patterns of amphibian decline. PMID:23613783
Cirrus cloud model parameterizations: Incorporating realistic ice particle generation
NASA Technical Reports Server (NTRS)
Sassen, Kenneth; Dodd, G. C.; Starr, David OC.
1990-01-01
Recent cirrus cloud modeling studies have involved the application of a time-dependent, two dimensional Eulerian model, with generalized cloud microphysical parameterizations drawn from experimental findings. For computing the ice versus vapor phase changes, the ice mass content is linked to the maintenance of a relative humidity with respect to ice (RHI) of 105 percent; ice growth occurs both with regard to the introduction of new particles and the growth of existing particles. In a simplified cloud model designed to investigate the basic role of various physical processes in the growth and maintenance of cirrus clouds, these parametric relations are justifiable. In comparison, the one dimensional cloud microphysical model recently applied to evaluating the nucleation and growth of ice crystals in cirrus clouds explicitly treated populations of haze and cloud droplets, and ice crystals. Although these two modeling approaches are clearly incompatible, the goal of the present numerical study is to develop a parametric treatment of new ice particle generation, on the basis of detailed microphysical model findings, for incorporation into improved cirrus growth models. For example, the relation between temperature and the relative humidity required to generate ice crystals from ammonium sulfate haze droplets, whose probability of freezing through the homogeneous nucleation mode are a combined function of time and droplet molality, volume, and temperature. As an example of this approach, the results of cloud microphysical simulations are presented showing the rather narrow domain in the temperature/humidity field where new ice crystals can be generated. The microphysical simulations point out the need for detailed CCN studies at cirrus altitudes and haze droplet measurements within cirrus clouds, but also suggest that a relatively simple treatment of ice particle generation, which includes cloud chemistry, can be incorporated into cirrus cloud growth.
On the botanic model of plant growth with intermediate vegetative-reproductive stage.
Ioslovich, Ilya; Gutman, Per-Olof
2005-11-01
The application of dynamic optimization to mathematical models of ontogenic biological growth has been the subject of much research [see e.g. . J. Theor. Biol. 33, 299-307]. Kozłowsky and Ziółko [1988. Thor. Popul. Biol. 34, 118-129] and Ziółko and Kozłowski [1995. IEEE Trans. Automat. Contr. 40(10), 1779-1783] presented a model with gradual transition from vegetative to reproductive growth. The central point of their model is a mixed state-control constraint on the rate of reproductive growth, which leads to a mixed vegetative-reproductive growth period. Their model is modified here in order to take into account the difference of photosynthesis use efficiency when energy is accumulated in the vegetative and in the reproductive organs of a plant, respectively. The simple assumption on correlation between photosynthesis and temperature permits us to modify the model in a form that is useful for changing climate. Unfortunately, the mathematical solution of the optimal control problem in Kozłowsky and Ziółko (1988) and Ziółko and Kozłowski (1995) is incorrect. The strict mathematical solution is presented here, the numerical example from is solved, and the results are compared. The influence of the length of the season and the relative photosynthesis use efficiency, as well as of the potential sink demand of the reproductive organs, on the location and duration of the mixed vegetative-reproduction period of growth is investigated numerically. The results show that the mixed growth period is increased and shifted toward the end of the season when the lengths of the season is increased. Additional details of the sensitivity analysis are also presented.
Cloud fluid models of gas dynamics and star formation in galaxies
NASA Technical Reports Server (NTRS)
Struck-Marcell, Curtis; Scalo, John M.; Appleton, P. N.
1987-01-01
The large dynamic range of star formation in galaxies, and the apparently complex environmental influences involved in triggering or suppressing star formation, challenges the understanding. The key to this understanding may be the detailed study of simple physical models for the dominant nonlinear interactions in interstellar cloud systems. One such model is described, a generalized Oort model cloud fluid, and two simple applications of it are explored. The first of these is the relaxation of an isolated volume of cloud fluid following a disturbance. Though very idealized, this closed box study suggests a physical mechanism for starbursts, which is based on the approximate commensurability of massive cloud lifetimes and cloud collisional growth times. The second application is to the modeling of colliding ring galaxies. In this case, the driving processes operating on a dynamical timescale interact with the local cloud processes operating on the above timescale. The results is a variety of interesting nonequilibrium behaviors, including spatial variations of star formation that do not depend monotonically on gas density.
Slow crack growth in glass in combined mode I and mode II loading
NASA Technical Reports Server (NTRS)
Shetty, D. K.; Rosenfield, A. R.
1991-01-01
Slow crack growth in soda-lime glass under combined mode I and mode II loading was investigated in precracked disk specimens in which pure mode I, pure mode II, and various combinations of mode I and mode II were achieved by loading in diametral compression at selected angles with respect to symmetric radial cracks. It is shown that slow crack growth under these conditions can be described by a simple exponential relationship with elastic strain energy release rate as the effective crack-driving force parameter. It is possible to interpret this equation in terms of theoretical models that treat subcritical crack growth as a thermally activated bond-rupture process with an activation energy dependent on the environment, and the elastic energy release rate as the crack-driving force parameter.
Effect of Time-Dependent Pinning Pressure on Abnormal Grain Growth: Phase Field Simulation
NASA Astrophysics Data System (ADS)
Kim, Jeong Min; Min, Guensik; Shim, Jae-Hyeok; Lee, Kyung Jong
2018-05-01
The effect of the time-dependent pinning pressure of precipitates on abnormal grain growth has been investigated by multiphase field simulation with a simple precipitation model. The application of constant pinning pressure is problematic because it always induces abnormal grain growth or no grain growth, which is not reasonable considering the real situation. To produce time-dependent pinning pressure, both precipitation kinetics and precipitate coarsening kinetics have been considered with two rates: slow and fast. The results show that abnormal grain growth is suppressed at the slow precipitation rate. At the slow precipitation rate, the overall grain growth caused by the low pinning pressure in the early stage indeed plays a role in preventing abnormal grain growth by reducing the mobility advantage of abnormal grains. In addition, the fast precipitate coarsening rate tends to more quickly transform abnormal grain growth into normal grain growth by inducing the active growth of grains adjacent to the abnormal grains in the early stage. Therefore, the present study demonstrates that the time dependence of the pinning pressure of precipitates is a critical factor that determines the grain growth mode.
Effect of Time-Dependent Pinning Pressure on Abnormal Grain Growth: Phase Field Simulation
NASA Astrophysics Data System (ADS)
Kim, Jeong Min; Min, Guensik; Shim, Jae-Hyeok; Lee, Kyung Jong
2018-03-01
The effect of the time-dependent pinning pressure of precipitates on abnormal grain growth has been investigated by multiphase field simulation with a simple precipitation model. The application of constant pinning pressure is problematic because it always induces abnormal grain growth or no grain growth, which is not reasonable considering the real situation. To produce time-dependent pinning pressure, both precipitation kinetics and precipitate coarsening kinetics have been considered with two rates: slow and fast. The results show that abnormal grain growth is suppressed at the slow precipitation rate. At the slow precipitation rate, the overall grain growth caused by the low pinning pressure in the early stage indeed plays a role in preventing abnormal grain growth by reducing the mobility advantage of abnormal grains. In addition, the fast precipitate coarsening rate tends to more quickly transform abnormal grain growth into normal grain growth by inducing the active growth of grains adjacent to the abnormal grains in the early stage. Therefore, the present study demonstrates that the time dependence of the pinning pressure of precipitates is a critical factor that determines the grain growth mode.
NASA Technical Reports Server (NTRS)
Bakuckas, J. G., Jr.; Johnson, W. S.
1992-01-01
Several fiber bridging models were reviewed and applied to study the matrix fatigue crack growth behavior in center notched (0)(sub 8) SCS-6/Ti-15-3 and (0)(sub 4) SCS-6/Ti-6Al-4V laminates. Observations revealed that fatigue damage consisted primarily of matrix cracks and fiber matrix interfacial failure in the (0)(sub 8) SCS-6/Ti-15-3 laminates. Fiber-matrix interface failure included fracture of the brittle reaction zone and cracking between the two carbon rich fiber coatings. Intact fibers in the wake of the matrix cracks reduce the stress intensity factor range. Thus, an applied stress intensity factor range is inappropriate to characterize matrix crack growth behavior. Fiber bridging models were used to determine the matrix stress intensity factor range in titanium metal matrix composites. In these models, the fibers in the wake of the crack are idealized as a closure pressure. An unknown constant frictional shear stress is assumed to act along the debond or slip length of the bridging fibers. The frictional shear stress was used as a curve fitting parameter to available data (crack growth data, crack opening displacement data, and debond length data). Large variations in the frictional shear stress required to fit the experimental data indicate that the fiber bridging models in their present form lack predictive capabilities. However, these models provide an efficient and relatively simple engineering method for conducting parametric studies of the matrix growth behavior based on constituent properties.
Caballero-Lima, David; Kaneva, Iliyana N.; Watton, Simon P.
2013-01-01
In the hyphal tip of Candida albicans we have made detailed quantitative measurements of (i) exocyst components, (ii) Rho1, the regulatory subunit of (1,3)-β-glucan synthase, (iii) Rom2, the specialized guanine-nucleotide exchange factor (GEF) of Rho1, and (iv) actin cortical patches, the sites of endocytosis. We use the resulting data to construct and test a quantitative 3-dimensional model of fungal hyphal growth based on the proposition that vesicles fuse with the hyphal tip at a rate determined by the local density of exocyst components. Enzymes such as (1,3)-β-glucan synthase thus embedded in the plasma membrane continue to synthesize the cell wall until they are removed by endocytosis. The model successfully predicts the shape and dimensions of the hyphae, provided that endocytosis acts to remove cell wall-synthesizing enzymes at the subapical bands of actin patches. Moreover, a key prediction of the model is that the distribution of the synthase is substantially broader than the area occupied by the exocyst. This prediction is borne out by our quantitative measurements. Thus, although the model highlights detailed issues that require further investigation, in general terms the pattern of tip growth of fungal hyphae can be satisfactorily explained by a simple but quantitative model rooted within the known molecular processes of polarized growth. Moreover, the methodology can be readily adapted to model other forms of polarized growth, such as that which occurs in plant pollen tubes. PMID:23666623
Petersen, J.H.; DeAngelis, D.L.; Paukert, C.P.
2008-01-01
Many fish species are at risk to some degree, and conservation efforts are planned or underway to preserve sensitive populations. For many imperiled species, models could serve as useful tools for researchers and managers as they seek to understand individual growth, quantify predator-prey dynamics, and identify critical sources of mortality. Development and application of models for rare species however, has been constrained by small population sizes, difficulty in obtaining sampling permits, limited opportunities for funding, and regulations on how endangered species can be used in laboratory studies. Bioenergetic and life history models should help with endangered species-recovery planning since these types of models have been used successfully in the last 25 years to address management problems for many commercially and recreationally important fish species. In this paper we discuss five approaches to developing models and parameters for rare species. Borrowing model functions and parameters from related species is simple, but uncorroborated results can be misleading. Directly estimating parameters with laboratory studies may be possible for rare species that have locally abundant populations. Monte Carlo filtering can be used to estimate several parameters by means of performing simple laboratory growth experiments to first determine test criteria. Pattern-oriented modeling (POM) is a new and developing field of research that uses field-observed patterns to build, test, and parameterize models. Models developed using the POM approach are closely linked to field data, produce testable hypotheses, and require a close working relationship between modelers and empiricists. Artificial evolution in individual-based models can be used to gain insight into adaptive behaviors for poorly understood species and thus can fill in knowledge gaps. ?? Copyright by the American Fisheries Society 2008.
An avian model for the reversal of neurobehavioral teratogenicity with neural stem cells
Dotan, Sharon; Pinkas, Adi; Slotkin, Theodore A.; Yanai, Joseph
2010-01-01
A fast and simple model which uses lower animals on the evolutionary scale is beneficial for developing procedures for the reversal of neurobehavioral teratogenicity with neural stem cells. Here, we established a procedure for the derivation of chick neural stem cells, establishing embryonic day (E) 10 as optimal for progression to neuronal phenotypes. Cells were obtained from the embryonic cerebral hemispheres and incubated for 5–7 days in enriched medium containing epidermal growth factor (EGF) and basic fibroblast growth factor (FGF2) according to a procedure originally developed for mice. A small percentage of the cells survived, proliferated and formed nestin-positive neurospheres. After removal of the growth factors to allow differentiation (5 days), 74% of the cells differentiated into all major lineages of the nervous system, including neurons (Beta III tubulin-positive, 54% of the total number of differentiated cells), astrocytes (GFAP-positive, 26%), and oligodendrocytes (O4-positive, 20%). These findings demonstrate that the cells were indeed neural stem cells. Next, the cells were transplanted in two allograft chick models; (1) direct cerebral transplantation to 24-hours-old chicks, followed by post-transplantation cell tracking at 24 hours, 6 days and 14 days, and (2) intravenous transplantation to chick embryos on E13, followed by cell tracking on E19. With both methods, transplanted cells were found in the brain. The chick embryo provides a convenient, precisely-timed and unlimited supply of neural progenitors for therapy by transplantation, as well as constituting a fast and simple model in which to evaluate the ability of neural stem cell transplantation to repair neural damage, steps that are critical for progress toward therapeutic applications. PMID:20211723
Teaching Population Growth Using Cultures of Vinegar Eels, "Turbatrix aceti" (Nematoda)
ERIC Educational Resources Information Center
Wallace, Robert L.
2005-01-01
A simple laboratory exercise is presented that follows the population growth of the common vinegar eel, "Turbatrix aceti" (Nematoda), in a microcosm using a simple culture medium. It lends itself to an exercise in a single semester course. (Contains 4 figures.)
Understanding Exponential Growth: As Simple as a Drop in a Bucket.
ERIC Educational Resources Information Center
Goldberg, Fred; Shuman, James
1984-01-01
Provides procedures for a simple laboratory activity on exponential growth and its characteristic doubling time. The equipment needed consists of a large plastic bucket, an eyedropper, a stopwatch, an assortment of containers and graduated cylinders, and a supply of water. (JN)
Fujarewicz, Krzysztof; Lakomiec, Krzysztof
2016-12-01
We investigate a spatial model of growth of a tumor and its sensitivity to radiotherapy. It is assumed that the radiation dose may vary in time and space, like in intensity modulated radiotherapy (IMRT). The change of the final state of the tumor depends on local differences in the radiation dose and varies with the time and the place of these local changes. This leads to the concept of a tumor's spatiotemporal sensitivity to radiation, which is a function of time and space. We show how adjoint sensitivity analysis may be applied to calculate the spatiotemporal sensitivity of the finite difference scheme resulting from the partial differential equation describing the tumor growth. We demonstrate results of this approach to the tumor proliferation, invasion and response to radiotherapy (PIRT) model and we compare the accuracy and the computational effort of the method to the simple forward finite difference sensitivity analysis. Furthermore, we use the spatiotemporal sensitivity during the gradient-based optimization of the spatiotemporal radiation protocol and present results for different parameters of the model.
Greedy algorithms and Zipf laws
NASA Astrophysics Data System (ADS)
Moran, José; Bouchaud, Jean-Philippe
2018-04-01
We consider a simple model of firm/city/etc growth based on a multi-item criterion: whenever entity B fares better than entity A on a subset of M items out of K, the agent originally in A moves to B. We solve the model analytically in the cases K = 1 and . The resulting stationary distribution of sizes is generically a Zipf-law provided M > K/2. When , no selection occurs and the size distribution remains thin-tailed. In the special case M = K, one needs to regularize the problem by introducing a small ‘default’ probability ϕ. We find that the stationary distribution has a power-law tail that becomes a Zipf-law when . The approach to the stationary state can also be characterized, with strong similarities with a simple ‘aging’ model considered by Barrat and Mézard.
An Overview of Longitudinal Data Analysis Methods for Neurological Research
Locascio, Joseph J.; Atri, Alireza
2011-01-01
The purpose of this article is to provide a concise, broad and readily accessible overview of longitudinal data analysis methods, aimed to be a practical guide for clinical investigators in neurology. In general, we advise that older, traditional methods, including (1) simple regression of the dependent variable on a time measure, (2) analyzing a single summary subject level number that indexes changes for each subject and (3) a general linear model approach with a fixed-subject effect, should be reserved for quick, simple or preliminary analyses. We advocate the general use of mixed-random and fixed-effect regression models for analyses of most longitudinal clinical studies. Under restrictive situations or to provide validation, we recommend: (1) repeated-measure analysis of covariance (ANCOVA), (2) ANCOVA for two time points, (3) generalized estimating equations and (4) latent growth curve/structural equation models. PMID:22203825
Asumadu-Sarkodie, Samuel; Owusu, Phebe Asantewaa
2017-03-01
In this study, the impact of energy, agriculture, macroeconomic and human-induced indicators on environmental pollution from 1971 to 2011 is investigated using the statistically inspired modification of partial least squares (SIMPLS) regression model. There was evidence of a linear relationship between energy, agriculture, macroeconomic and human-induced indicators and carbon dioxide emissions. Evidence from the SIMPLS regression shows that a 1% increase in crop production index will reduce carbon dioxide emissions by 0.71%. Economic growth increased by 1% will reduce carbon dioxide emissions by 0.46%, which means that an increase in Ghana's economic growth may lead to a reduction in environmental pollution. The increase in electricity production from hydroelectric sources by 1% will reduce carbon dioxide emissions by 0.30%; thus, increasing renewable energy sources in Ghana's energy portfolio will help mitigate carbon dioxide emissions. Increasing enteric emissions by 1% will increase carbon dioxide emissions by 4.22%, and a 1% increase in the nitrogen content of manure management will increase carbon dioxide emissions by 6.69%. The SIMPLS regression forecasting exhibited a 5% MAPE from the prediction of carbon dioxide emissions.
Key variables influencing patterns of lava dome growth and collapse
NASA Astrophysics Data System (ADS)
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 transition in the growth pattern, while a decrease in infusion rate results in larger crystals causing the material to stiffen leading to formation of spines. Material stiffness controls the growth direction of the viscous plug in the lava dome interior. Material strength and stiffness controled by rate of infusion influence lava dome growth more significantly than coefficient of frictional of the talus.
Growth of Pt/Cu(100): An Atomistic Modeling Comparison with the Pd/Cu(100) Surface Alloy
NASA Technical Reports Server (NTRS)
Demarco, Gustavo; Garces, Jorge E.; Bozzolo, Guillermo
2002-01-01
The Bozzolo, Ferrante, and Smith (BFS) method for alloys is applied to the study of Pt deposition on Cu(100). The formation of a Cu-Pt surface alloy is discussed within the framework of previous results for Pd/Cu(100). In spite of the fact that both Pd and Pt share the same basic behavior when deposited on Cu, it is seen that subtle differences become responsible for the differences in growth observed at higher cover-ages. In agreement with experiment, all the main features of Pt/Cu(100) and Pd/Cu(100) are obtained by means of a simple modeling scheme, and explained in terms of a few basic ingredients that emerge from the BFS analysis.
Inferring mixed-culture growth from total biomass data in a wavelet approach
NASA Astrophysics Data System (ADS)
Ibarra-Junquera, V.; Escalante-Minakata, P.; Murguía, J. S.; Rosu, H. C.
2006-10-01
It is shown that the presence of mixed-culture growth in batch fermentation processes can be very accurately inferred from total biomass data by means of the wavelet analysis for singularity detection. This is accomplished by considering simple phenomenological models for the mixed growth and the more complicated case of mixed growth on a mixture of substrates. The main quantity provided by the wavelet analysis is the Hölder exponent of the singularity that we determine for our illustrative examples. The numerical results point to the possibility that Hölder exponents can be used to characterize the nature of the mixed-culture growth in batch fermentation processes with potential industrial applications. Moreover, the analysis of the same data affected by the common additive Gaussian noise still lead to the wavelet detection of the singularities although the Hölder exponent is no longer a useful parameter.
ERIC Educational Resources Information Center
Shen, Linjun
As part of a longitudinal study of the growth of general medical knowledge among osteopathic medical students, a simple, convenient, and accurate vertical equating method was developed for constructing a scale for medical achievement. It was believed that Parts 1, 2, and 3 of the National Board of Osteopathic Medical Examiners' (NBOME) examination…
Improving Estimation of Ground Casualty Risk From Reentering Space Objects
NASA Technical Reports Server (NTRS)
Ostrom, Chris L.
2017-01-01
A recent improvement to the long-term estimation of ground casualties from reentering space debris is the further refinement and update to the human population distribution. Previous human population distributions were based on global totals with simple scaling factors for future years, or a coarse grid of population counts in a subset of the world's countries, each cell having its own projected growth rate. The newest population model includes a 5-fold refinement in both latitude and longitude resolution. All areas along a single latitude are combined to form a global population distribution as a function of latitude, creating a more accurate population estimation based on non-uniform growth at the country and area levels. Previous risk probability calculations used simplifying assumptions that did not account for the ellipsoidal nature of the Earth. The new method uses first, a simple analytical method to estimate the amount of time spent above each latitude band for a debris object with a given orbit inclination and second, a more complex numerical method that incorporates the effects of a non-spherical Earth. These new results are compared with the prior models to assess the magnitude of the effects on reentry casualty risk.
Variations in planetary convection via the effect of climate on damage
NASA Astrophysics Data System (ADS)
Landuyt, W.; Bercovici, D.
2008-12-01
The generation of plate tectonics on Earth and its absence on the other terrestrial planets (especially Venus) remains a significant conundrum in geophysics. We propose a model for the generation of plate tectonics that suggests an important interaction between a planet's climate and its lithospheric damage behavior; and thus provides a simple explanation for the tectonic difference between Earth and Venus. We propose that high surface temperatures will lead to higher healing rates (e.g. grain growth) in the lithosphere that will act to suppress localization, plate boundary formation, and subduction. This leads to episodic or stagnant lid convection on Venus because of its hotter climate. In contrast, Earth's cooler climate promotes damage and plate boundary formation. The damage rheology presented in this paper attempts to describe the evolution of grain size by allowing for grain reduction via deformational work input and grain growth via surface tension- driven coarsening. We present results from convection simulations and a simple "drip-instability" model to test our hypothesis. The results suggest the feasibility of our proposed hypothesis that the influence of climate on damage may control the mode of tectonics on a planet.
Improving Estimation of Ground Casualty Risk from Reentering Space Objects
NASA Technical Reports Server (NTRS)
Ostrom, C.
2017-01-01
A recent improvement to the long-term estimation of ground casualties from reentering space debris is the further refinement and update to the human population distribution. Previous human population distributions were based on global totals with simple scaling factors for future years, or a coarse grid of population counts in a subset of the world's countries, each cell having its own projected growth rate. The newest population model includes a 5-fold refinement in both latitude and longitude resolution. All areas along a single latitude are combined to form a global population distribution as a function of latitude, creating a more accurate population estimation based on non-uniform growth at the country and area levels. Previous risk probability calculations used simplifying assumptions that did not account for the ellipsoidal nature of the earth. The new method uses first, a simple analytical method to estimate the amount of time spent above each latitude band for a debris object with a given orbit inclination, and second, a more complex numerical method that incorporates the effects of a non-spherical Earth. These new results are compared with the prior models to assess the magnitude of the effects on reentry casualty risk.
Nonlocal Models of Cosmic Acceleration
NASA Astrophysics Data System (ADS)
Woodard, R. P.
2014-02-01
I review a class of nonlocally modified gravity models which were proposed to explain the current phase of cosmic acceleration without dark energy. Among the topics considered are deriving causal and conserved field equations, adjusting the model to make it support a given expansion history, why these models do not require an elaborate screening mechanism to evade solar system tests, degrees of freedom and kinetic stability, and the negative verdict of structure formation. Although these simple models are not consistent with data on the growth of cosmic structures many of their features are likely to carry over to more complicated models which are in better agreement with the data.
Kirk, Devin; Jones, Natalie; Peacock, Stephanie; Phillips, Jessica; Molnár, Péter K; Krkošek, Martin; Luijckx, Pepijn
2018-02-01
The complexity of host-parasite interactions makes it difficult to predict how host-parasite systems will respond to climate change. In particular, host and parasite traits such as survival and virulence may have distinct temperature dependencies that must be integrated into models of disease dynamics. Using experimental data from Daphnia magna and a microsporidian parasite, we fitted a mechanistic model of the within-host parasite population dynamics. Model parameters comprising host aging and mortality, as well as parasite growth, virulence, and equilibrium abundance, were specified by relationships arising from the metabolic theory of ecology. The model effectively predicts host survival, parasite growth, and the cost of infection across temperature while using less than half the parameters compared to modeling temperatures discretely. Our results serve as a proof of concept that linking simple metabolic models with a mechanistic host-parasite framework can be used to predict temperature responses of parasite population dynamics at the within-host level.
Jones, Natalie; Peacock, Stephanie; Phillips, Jessica; Molnár, Péter K.; Krkošek, Martin; Luijckx, Pepijn
2018-01-01
The complexity of host–parasite interactions makes it difficult to predict how host–parasite systems will respond to climate change. In particular, host and parasite traits such as survival and virulence may have distinct temperature dependencies that must be integrated into models of disease dynamics. Using experimental data from Daphnia magna and a microsporidian parasite, we fitted a mechanistic model of the within-host parasite population dynamics. Model parameters comprising host aging and mortality, as well as parasite growth, virulence, and equilibrium abundance, were specified by relationships arising from the metabolic theory of ecology. The model effectively predicts host survival, parasite growth, and the cost of infection across temperature while using less than half the parameters compared to modeling temperatures discretely. Our results serve as a proof of concept that linking simple metabolic models with a mechanistic host–parasite framework can be used to predict temperature responses of parasite population dynamics at the within-host level. PMID:29415043
Short-ranged memory model with preferential growth
NASA Astrophysics Data System (ADS)
Schaigorodsky, Ana L.; Perotti, Juan I.; Almeira, Nahuel; Billoni, Orlando V.
2018-02-01
In this work we introduce a variant of the Yule-Simon model for preferential growth by incorporating a finite kernel to model the effects of bounded memory. We characterize the properties of the model combining analytical arguments with extensive numerical simulations. In particular, we analyze the lifetime and popularity distributions by mapping the model dynamics to corresponding Markov chains and branching processes, respectively. These distributions follow power laws with well-defined exponents that are within the range of the empirical data reported in ecologies. Interestingly, by varying the innovation rate, this simple out-of-equilibrium model exhibits many of the characteristics of a continuous phase transition and, around the critical point, it generates time series with power-law popularity, lifetime and interevent time distributions, and nontrivial temporal correlations, such as a bursty dynamics in analogy with the activity of solar flares. Our results suggest that an appropriate balance between innovation and oblivion rates could provide an explanatory framework for many of the properties commonly observed in many complex systems.
Short-ranged memory model with preferential growth.
Schaigorodsky, Ana L; Perotti, Juan I; Almeira, Nahuel; Billoni, Orlando V
2018-02-01
In this work we introduce a variant of the Yule-Simon model for preferential growth by incorporating a finite kernel to model the effects of bounded memory. We characterize the properties of the model combining analytical arguments with extensive numerical simulations. In particular, we analyze the lifetime and popularity distributions by mapping the model dynamics to corresponding Markov chains and branching processes, respectively. These distributions follow power laws with well-defined exponents that are within the range of the empirical data reported in ecologies. Interestingly, by varying the innovation rate, this simple out-of-equilibrium model exhibits many of the characteristics of a continuous phase transition and, around the critical point, it generates time series with power-law popularity, lifetime and interevent time distributions, and nontrivial temporal correlations, such as a bursty dynamics in analogy with the activity of solar flares. Our results suggest that an appropriate balance between innovation and oblivion rates could provide an explanatory framework for many of the properties commonly observed in many complex systems.
NASA Astrophysics Data System (ADS)
Chan, Kwai S.; Enright, Michael P.; Moody, Jonathan; Fitch, Simeon H. K.
2014-01-01
The objective of this investigation was to develop an innovative methodology for life and reliability prediction of hot-section components in advanced turbopropulsion systems. A set of generic microstructure-based time-dependent crack growth (TDCG) models was developed and used to assess the sources of material variability due to microstructure and material parameters such as grain size, activation energy, and crack growth threshold for TDCG. A comparison of model predictions and experimental data obtained in air and in vacuum suggests that oxidation is responsible for higher crack growth rates at high temperatures, low frequencies, and long dwell times, but oxidation can also induce higher crack growth thresholds (Δ K th or K th) under certain conditions. Using the enhanced risk analysis tool and material constants calibrated to IN 718 data, the effect of TDCG on the risk of fracture in turboengine components was demonstrated for a generic rotor design and a realistic mission profile using the DARWIN® probabilistic life-prediction code. The results of this investigation confirmed that TDCG and cycle-dependent crack growth in IN 718 can be treated by a simple summation of the crack increments over a mission. For the temperatures considered, TDCG in IN 718 can be considered as a K-controlled or a diffusion-controlled oxidation-induced degradation process. This methodology provides a pathway for evaluating microstructural effects on multiple damage modes in hot-section components.
Reeves, Gregory T; Narang, Atul; Pilyugin, Sergei S
2004-01-21
The growth of mixed microbial cultures on mixtures of substrates is a problem of fundamental biological interest. In the last two decades, several unstructured models of mixed-substrate growth have been studied. It is well known, however, that the growth patterns in mixed-substrate environments are dictated by the enzymes that catalyse the transport of substrates into the cell. We have shown previously that a model taking due account of transport enzymes captures and explains all the observed patterns of growth of a single species on two substitutable substrates (J. Theor. Biol. 190 (1998) 241). Here, we extend the model to study the steady states of growth of two species on two substitutable substrates. The model is analysed to determine the conditions for existence and stability of the various steady states. Simulations are performed to determine the flow rates and feed concentrations at which both species coexist. We show that if the interaction between the two species is purely competitive, then at any given flow rate, coexistence is possible only if the ratio of the two feed concentrations lies within a certain interval; excessive supply of either one of the two substrates leads to annihilation of one of the species. This result simplifies the construction of the operating diagram for purely competing species. This is because the two-dimensional surface that bounds the flow rates and feed concentrations at which both species coexist has a particularly simple geometry: It is completely determined by only two coordinates, the flow rate and the ratio of the two feed concentrations. We also study commensalistic interactions between the two species by assuming that one of the species excretes a product that can support the growth of the other species. We show that such interactions enhance the coexistence region.
Contrail Formation in Aircraft Wakes Using Large-Eddy Simulations
NASA Technical Reports Server (NTRS)
Paoli, R.; Helie, J.; Poinsot, T. J.; Ghosal, S.
2002-01-01
In this work we analyze the issue of the formation of condensation trails ("contrails") in the near-field of an aircraft wake. The basic configuration consists in an exhaust engine jet interacting with a wing-tip training vortex. The procedure adopted relies on a mixed Eulerian/Lagrangian two-phase flow approach; a simple micro-physics model for ice growth has been used to couple ice and vapor phases. Large eddy simulations have carried out at a realistic flight Reynolds number to evaluate the effects of turbulent mixing and wake vortex dynamics on ice-growth characteristics and vapor thermodynamic properties.
Skylab M518 multipurpose furnace convection analysis
NASA Technical Reports Server (NTRS)
Bourgeois, S. V.; Spradley, L. W.
1975-01-01
An analysis was performed of the convection which existed on ground tests and during skylab processing of two experiments: vapor growth of IV-VI compounds growth of spherical crystals. A parallel analysis was also performed on Skylab experiment indium antimonide crystals because indium antimonide (InSb) was used and a free surface existed in the tellurium-doped Skylab III sample. In addition, brief analyses were also performed of the microsegregation in germanium experiment because the Skylab crystals indicated turbulent convection effects. Simple dimensional analysis calculations and a more accurate, but complex, convection computer model, were used in the analysis.
The molecular basis of ethylene signalling in Arabidopsis
NASA Technical Reports Server (NTRS)
Woeste, K.; Kieber, J. J.; Evans, M. L. (Principal Investigator)
1998-01-01
The simple gas ethylene profoundly influences plants at nearly every stage of growth and development. In the past ten years, the use of a genetic approach, based on the triple response phenotype, has been a powerful tool for investigating the molecular events that underlie these effects. Several fundamental elements of the pathway have been described: a receptor with homology to bacterial two-component histidine kinases (ETR1), elements of a MAP kinase cascade (CTR1) and a putative transcription factor (EIN3). Taken together, these elements can be assembled into a simple, linear model for ethylene signalling that accounts for most of the well-characterized ethylene mediated responses.
Numerical modeling study on the epitaxial growth of silicon from dichlorosilane
NASA Astrophysics Data System (ADS)
Zaidi, Imama; Jang, Yeon-Ho; Ko, Dong Guk; Im, Ik-Tae
2018-02-01
Computer simulations play an important role in determining the optimal design parameters for chemical vapor deposition (CVD) reactors, such as flow rates, positions of the inlet and outlet orifices, and rotational rates, etc. Reliability of the results of these simulations depends on the set of chemical reaction used to represent the process of deposition in the reactor. Aim of the present work is to validate the simple empirical reaction to model the epitaxial growth of silicon for a Dichlorosilane-H2 (DCS)-H2 system. Governing equations for continuity, momentum, energy, and reacting species are solved numerically using the finite volume method. The agreement between experimental and predicted growth rates for various DCS flow rates is shown to be satisfactory. The increase in growth rate with the increase in pressure is in accordance with the available data. Based on the validated chemical reaction model, a study was carried out to analyze the uniformity of the silicon layer thickness for two different flow rates in a planetary reactor. It was concluded that, based on the operating conditions, the uniformity of the silicon layer over the wafer is independent of the satellite rotational rate in the reactor.
A non-modal analytical method to predict turbulent properties applied to the Hasegawa-Wakatani model
DOE Office of Scientific and Technical Information (OSTI.GOV)
Friedman, B., E-mail: friedman11@llnl.gov; Lawrence Livermore National Laboratory, Livermore, California 94550; Carter, T. A.
2015-01-15
Linear eigenmode analysis often fails to describe turbulence in model systems that have non-normal linear operators and thus nonorthogonal eigenmodes, which can cause fluctuations to transiently grow faster than expected from eigenmode analysis. When combined with energetically conservative nonlinear mode mixing, transient growth can lead to sustained turbulence even in the absence of eigenmode instability. Since linear operators ultimately provide the turbulent fluctuations with energy, it is useful to define a growth rate that takes into account non-modal effects, allowing for prediction of energy injection, transport levels, and possibly even turbulent onset in the subcritical regime. We define such amore » non-modal growth rate using a relatively simple model of the statistical effect that the nonlinearities have on cross-phases and amplitude ratios of the system state variables. In particular, we model the nonlinearities as delta-function-like, periodic forces that randomize the state variables once every eddy turnover time. Furthermore, we estimate the eddy turnover time to be the inverse of the least stable eigenmode frequency or growth rate, which allows for prediction without nonlinear numerical simulation. We test this procedure on the 2D and 3D Hasegawa-Wakatani model [A. Hasegawa and M. Wakatani, Phys. Rev. Lett. 50, 682 (1983)] and find that the non-modal growth rate is a good predictor of energy injection rates, especially in the strongly non-normal, fully developed turbulence regime.« less
A non-modal analytical method to predict turbulent properties applied to the Hasegawa-Wakatani model
DOE Office of Scientific and Technical Information (OSTI.GOV)
Friedman, B.; Carter, T. A.
2015-01-15
Linear eigenmode analysis often fails to describe turbulence in model systems that have non-normal linear operators and thus nonorthogonal eigenmodes, which can cause fluctuations to transiently grow faster than expected from eigenmode analysis. When combined with energetically conservative nonlinear mode mixing, transient growth can lead to sustained turbulence even in the absence of eigenmode instability. Since linear operators ultimately provide the turbulent fluctuations with energy, it is useful to define a growth rate that takes into account non-modal effects, allowing for prediction of energy injection, transport levels, and possibly even turbulent onset in the subcritical regime. Here, we define suchmore » a non-modal growth rate using a relatively simple model of the statistical effect that the nonlinearities have on cross-phases and amplitude ratios of the system state variables. In particular, we model the nonlinearities as delta-function-like, periodic forces that randomize the state variables once every eddy turnover time. Furthermore, we estimate the eddy turnover time to be the inverse of the least stable eigenmode frequency or growth rate, which allows for prediction without nonlinear numerical simulation. Also, we test this procedure on the 2D and 3D Hasegawa-Wakatani model [A. Hasegawa and M. Wakatani, Phys. Rev. Lett. 50, 682 (1983)] and find that the non-modal growth rate is a good predictor of energy injection rates, especially in the strongly non-normal, fully developed turbulence regime.« less
A model for predicting high-temperature fatigue failure of a W/Cu composite
NASA Technical Reports Server (NTRS)
Verrilli, M. J.; Kim, Y.-S.; Gabb, T. P.
1991-01-01
The material studied, a tungsten-fiber-reinforced, copper-matrix composite, is a candidate material for rocket nozzle liner applications. It was shown that at high temperatures, fatigue cracks initiate and propagate inside the copper matrix through a process of initiation, growth, and coalescence of grain boundary cavities. The ductile tungsten fibers neck and rupture locally after the surrounding matrix fails, and complete failure of the composite then ensues. A simple fatigue life prediction model is presented for the tungsten/copper composite system.
Regulation of planar growth by the Arabidopsis AGC protein kinase UNICORN.
Enugutti, Balaji; Kirchhelle, Charlotte; Oelschner, Maxi; Torres Ruiz, Ramón Angel; Schliebner, Ivo; Leister, Dario; Schneitz, Kay
2012-09-11
The spatial coordination of growth is of central importance for the regulation of plant tissue architecture. Individual layers, such as the epidermis, are clonally propagated and structurally maintained by symmetric cell divisions that are oriented along the plane of the layer. The developmental control of this process is poorly understood. The simple cellular basis and sheet-like structure of Arabidopsis integuments make them an attractive model system to address planar growth. Here we report on the characterization of the Arabidopsis UNICORN (UCN) gene. Analysis of ucn integuments reveals localized distortion of planar growth, eventually resulting in an ectopic multicellular protrusion. In addition, ucn mutants exhibit ectopic growth in filaments and petals, as well as aberrant embryogenesis. We further show that UCN encodes an active AGC VIII kinase. Genetic, biochemical, and cell biological data suggest that UCN suppresses ectopic growth in integuments by directly repressing the KANADI transcription factor ABERRANT TESTA SHAPE. Our findings indicate that UCN represents a unique plant growth regulator that maintains planar growth of integuments by repressing a developmental regulator involved in the control of early integument growth and polarity.
Constrained Allocation Flux Balance Analysis
Mori, Matteo; Hwa, Terence; Martin, Olivier C.
2016-01-01
New experimental results on bacterial growth inspire a novel top-down approach to study cell metabolism, combining mass balance and proteomic constraints to extend and complement Flux Balance Analysis. We introduce here Constrained Allocation Flux Balance Analysis, CAFBA, in which the biosynthetic costs associated to growth are accounted for in an effective way through a single additional genome-wide constraint. Its roots lie in the experimentally observed pattern of proteome allocation for metabolic functions, allowing to bridge regulation and metabolism in a transparent way under the principle of growth-rate maximization. We provide a simple method to solve CAFBA efficiently and propose an “ensemble averaging” procedure to account for unknown protein costs. Applying this approach to modeling E. coli metabolism, we find that, as the growth rate increases, CAFBA solutions cross over from respiratory, growth-yield maximizing states (preferred at slow growth) to fermentative states with carbon overflow (preferred at fast growth). In addition, CAFBA allows for quantitatively accurate predictions on the rate of acetate excretion and growth yield based on only 3 parameters determined by empirical growth laws. PMID:27355325
A new simple /spl infin/OH neuron model as a biologically plausible principal component analyzer.
Jankovic, M V
2003-01-01
A new approach to unsupervised learning in a single-layer neural network is discussed. An algorithm for unsupervised learning based upon the Hebbian learning rule is presented. A simple neuron model is analyzed. A dynamic neural model, which contains both feed-forward and feedback connections between the input and the output, has been adopted. The, proposed learning algorithm could be more correctly named self-supervised rather than unsupervised. The solution proposed here is a modified Hebbian rule, in which the modification of the synaptic strength is proportional not to pre- and postsynaptic activity, but instead to the presynaptic and averaged value of postsynaptic activity. It is shown that the model neuron tends to extract the principal component from a stationary input vector sequence. Usually accepted additional decaying terms for the stabilization of the original Hebbian rule are avoided. Implementation of the basic Hebbian scheme would not lead to unrealistic growth of the synaptic strengths, thanks to the adopted network structure.
Modelling morphology evolution during solidification of IPP in processing conditions
DOE Office of Scientific and Technical Information (OSTI.GOV)
Pantani, R., E-mail: rpantani@unisa.it, E-mail: fedesantis@unisa.it, E-mail: vsperanza@unisa.it, E-mail: gtitomanlio@unisa.it; De Santis, F., E-mail: rpantani@unisa.it, E-mail: fedesantis@unisa.it, E-mail: vsperanza@unisa.it, E-mail: gtitomanlio@unisa.it; Speranza, V., E-mail: rpantani@unisa.it, E-mail: fedesantis@unisa.it, E-mail: vsperanza@unisa.it, E-mail: gtitomanlio@unisa.it
During polymer processing, crystallization takes place during or soon after flow. In most of cases, the flow field dramatically influences both the crystallization kinetics and the crystal morphology. On their turn, crystallinity and morphology affect product properties. Consequently, in the last decade, researchers tried to identify the main parameters determining crystallinity and morphology evolution during solidification In processing conditions. In this work, we present an approach to model flow-induced crystallization with the aim of predicting the morphology after processing. The approach is based on: interpretation of the FIC as the effect of molecular stretch on the thermodynamic crystallization temperature; modelingmore » the molecular stretch evolution by means of a model simple and easy to be implemented in polymer processing simulation codes; identification of the effect of flow on nucleation density and spherulites growth rate by means of simple experiments; determination of the condition under which fibers form instead of spherulites. Model predictions reproduce most of the features of final morphology observed in the samples after solidification.« less
Discrete and continuous models for tissue growth and shrinkage.
Yates, Christian A
2014-06-07
The incorporation of domain growth into stochastic models of biological processes is of increasing interest to mathematical modellers and biologists alike. In many situations, especially in developmental biology, the growth of the underlying tissue domain plays an important role in the redistribution of particles (be they cells or molecules) which may move and react atop the domain. Although such processes have largely been modelled using deterministic, continuum models there is an increasing appetite for individual-based stochastic models which can capture the fine details of the biological movement processes which are being elucidated by modern experimental techniques, and also incorporate the inherent stochasticity of such systems. In this work we study a simple stochastic model of domain growth. From a basic version of this model, Hywood et al. (2013) were able to derive a Fokker-Plank equation (FPE) (in this case an advection-diffusion partial differential equation on a growing domain) which describes the evolution of the probability density of some tracer particles on the domain. We extend their work so that a variety of different domain growth mechanisms can be incorporated and demonstrate a good agreement between the mean tracer density and the solution of the FPE in each case. In addition we incorporate domain shrinkage (via element death) into our individual-level model and demonstrate that we are able to derive coefficients for the FPE in this case as well. For situations in which the drift and diffusion coefficients are not readily available we introduce a numerical coefficient estimation approach and demonstrate the accuracy of this approach by comparing it with situations in which an analytical solution is obtainable. Copyright © 2014 Elsevier Ltd. All rights reserved.
Growth of wormlike micelles in nonionic surfactant solutions: Quantitative theory vs. experiment.
Danov, Krassimir D; Kralchevsky, Peter A; Stoyanov, Simeon D; Cook, Joanne L; Stott, Ian P; Pelan, Eddie G
2018-06-01
Despite the considerable advances of molecular-thermodynamic theory of micelle growth, agreement between theory and experiment has been achieved only in isolated cases. A general theory that can provide self-consistent quantitative description of the growth of wormlike micelles in mixed surfactant solutions, including the experimentally observed high peaks in viscosity and aggregation number, is still missing. As a step toward the creation of such theory, here we consider the simplest system - nonionic wormlike surfactant micelles from polyoxyethylene alkyl ethers, C i E j . Our goal is to construct a molecular-thermodynamic model that is in agreement with the available experimental data. For this goal, we systematized data for the micelle mean mass aggregation number, from which the micelle growth parameter was determined at various temperatures. None of the available models can give a quantitative description of these data. We constructed a new model, which is based on theoretical expressions for the interfacial-tension, headgroup-steric and chain-conformation components of micelle free energy, along with appropriate expressions for the parameters of the model, including their temperature and curvature dependencies. Special attention was paid to the surfactant chain-conformation free energy, for which a new more general formula was derived. As a result, relatively simple theoretical expressions are obtained. All parameters that enter these expressions are known, which facilitates the theoretical modeling of micelle growth for various nonionic surfactants in excellent agreement with the experiment. The constructed model can serve as a basis that can be further upgraded to obtain quantitative description of micelle growth in more complicated systems, including binary and ternary mixtures of nonionic, ionic and zwitterionic surfactants, which determines the viscosity and stability of various formulations in personal-care and house-hold detergency. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.
NASA Astrophysics Data System (ADS)
Danner, Travis W.
Developing technology systems requires all manner of investment---engineering talent, prototypes, test facilities, and more. Even for simple design problems the investment can be substantial; for complex technology systems, the development costs can be staggering. The profitability of a corporation in a technology-driven industry is crucially dependent on maximizing the effectiveness of research and development investment. Decision-makers charged with allocation of this investment are forced to choose between the further evolution of existing technologies and the pursuit of revolutionary technologies. At risk on the one hand is excessive investment in an evolutionary technology which has only limited availability for further improvement. On the other hand, the pursuit of a revolutionary technology may mean abandoning momentum and the potential for substantial evolutionary improvement resulting from the years of accumulated knowledge. The informed answer to this question, evolutionary or revolutionary, requires knowledge of the expected rate of improvement and the potential a technology offers for further improvement. This research is dedicated to formulating the assessment and forecasting tools necessary to acquire this knowledge. The same physical laws and principles that enable the development and improvement of specific technologies also limit the ultimate capability of those technologies. Researchers have long used this concept as the foundation for modeling technological advancement through extrapolation by analogy to biological growth models. These models are employed to depict technology development as it asymptotically approaches limits established by the fundamental principles on which the technological approach is based. This has proven an effective and accurate approach to modeling and forecasting simple single-attribute technologies. With increased system complexity and the introduction of multiple system objectives, however, the usefulness of this modeling technique begins to diminish. With the introduction of multiple objectives, researchers often abandon technology growth models for scoring models and technology frontiers. While both approaches possess advantages over current growth models for the assessment of multi-objective technologies, each lacks a necessary dimension for comprehensive technology assessment. By collapsing multiple system metrics into a single, non-intuitive technology measure, scoring models provide a succinct framework for multi-objective technology assessment and forecasting. Yet, with no consideration of physical limits, scoring models provide no insight as to the feasibility of a particular combination of system capabilities. They only indicate that a given combination of system capabilities yields a particular score. Conversely, technology frontiers are constructed with the distinct objective of providing insight into the feasibility of system capability combinations. Yet again, upper limits to overall system performance are ignored. Furthermore, the data required to forecast subsequent technology frontiers is often inhibitive. In an attempt to reincorporate the fundamental nature of technology advancement as bound by physical principles, researchers have sought to normalize multi-objective systems whereby the variability of a single system objective is eliminated as a result of changes in the remaining objectives. This drastically limits the applicability of the resulting technology model because it is only applicable for a single setting of all other system attributes. Attempts to maintain the interaction between the growth curves of each technical objective of a complex system have thus far been limited to qualitative and subjective consideration. This research proposes the formulation of multidimensional growth models as an approach to simulating the advancement of multi-objective technologies towards their upper limits. Multidimensional growth models were formulated by noticing and exploiting the correlation between technology growth models and technology frontiers. Both are frontiers in actuality. The technology growth curve is a frontier between capability levels of a single attribute and time, while a technology frontier is a frontier between the capability levels of two or more attributes. Multidimensional growth models are formulated by exploiting the mathematical significance of this correlation. The result is a model that can capture both the interaction between multiple system attributes and their expected rates of improvement over time. The fundamental nature of technology development is maintained, and interdependent growth curves are generated for each system metric with minimal data requirements. Being founded on the basic nature of technology advancement, relative to physical limits, the availability for further improvement can be determined for a single metric relative to other system measures of merit. A by-product of this modeling approach is a single n-dimensional technology frontier linking all n system attributes with time. This provides an environment capable of forecasting future system capability in the form of advancing technology frontiers. The ability of a multidimensional growth model to capture the expected improvement of a specific technological approach is dependent on accurately identifying the physical limitations to each pertinent attribute. This research investigates two potential approaches to identifying those physical limits, a physics-based approach and a regression-based approach. The regression-based approach has found limited acceptance among forecasters, although it does show potential for estimating upper limits with a specified degree of uncertainty. Forecasters have long favored physics-based approaches for establishing the upper limit to unidimensional growth models. The task of accurately identifying upper limits has become increasingly difficult with the extension of growth models into multiple dimensions. A lone researcher may be able to identify the physical limitation to a single attribute of a simple system; however, as system complexity and the number of attributes increases, the attention of researchers from multiple fields of study is required. Thus, limit identification is itself an area of research and development requiring some level of investment. Whether estimated by physics or regression-based approaches, predicted limits will always have some degree of uncertainty. This research takes the approach of quantifying the impact of that uncertainty on model forecasts rather than heavily endorsing a single technique to limit identification. In addition to formulating the multidimensional growth model, this research provides a systematic procedure for applying that model to specific technology architectures. Researchers and decision-makers are able to investigate the potential for additional improvement within that technology architecture and to estimate the expected cost of each incremental improvement relative to the cost of past improvements. In this manner, multidimensional growth models provide the necessary information to set reasonable program goals for the further evolution of a particular technological approach or to establish the need for revolutionary approaches in light of the constraining limits of conventional approaches.
NASA Astrophysics Data System (ADS)
Plegnière, Sabrina; Casper, Markus; Hecker, Benjamin; Müller-Fürstenberger, Georg
2014-05-01
The basis of many models to calculate and assess climate change and its consequences are annual means of temperature and precipitation. This method leads to many uncertainties especially at the regional or local level: the results are not realistic or too coarse. Particularly in agriculture, single events and the distribution of precipitation and temperature during the growing season have enormous influences on plant growth. Therefore, the temporal distribution of climate variables should not be ignored. To reach this goal, a high-resolution ecological-economic model was developed which combines a complex plant growth model (STICS) and an economic model. In this context, input data of the plant growth model are daily climate values for a specific climate station calculated by the statistical climate model (WETTREG). The economic model is deduced from the results of the plant growth model STICS. The chosen plant is corn because corn is often cultivated and used in many different ways. First of all, a sensitivity analysis showed that the plant growth model STICS is suitable to calculate the influences of different cultivation methods and climate on plant growth or yield as well as on soil fertility, e.g. by nitrate leaching, in a realistic way. Additional simulations helped to assess a production function that is the key element of the economic model. Thereby the problems when using mean values of temperature and precipitation in order to compute a production function by linear regression are pointed out. Several examples show why a linear regression to assess a production function based on mean climate values or smoothed natural distribution leads to imperfect results and why it is not possible to deduce a unique climate factor in the production function. One solution for this problem is the additional consideration of stress indices that show the impairment of plants by water or nitrate shortage. Thus, the resulting model takes into account not only the ecological factors (e.g. the plant growth) or the economical factors as a simple monetary calculation, but also their mutual influences. Finally, the ecological-economic model enables us to make a risk assessment or evaluate adaptation strategies.
NASA Astrophysics Data System (ADS)
Caldararu, S.; Smith, M. J.; Purves, D.; Emmott, S.
2013-12-01
Global agriculture will, in the future, be faced with two main challenges: climate change and an increase in global food demand driven by an increase in population and changes in consumption habits. To be able to predict both the impacts of changes in climate on crop yields and the changes in agricultural practices necessary to respond to such impacts we currently need to improve our understanding of crop responses to climate and the predictive capability of our models. Ideally, what we would have at our disposal is a modelling tool which, given certain climatic conditions and agricultural practices, can predict the growth pattern and final yield of any of the major crops across the globe. We present a simple, process-based crop growth model based on the assumption that plants allocate above- and below-ground biomass to maintain overall carbon optimality and that, to maintain this optimality, the reproductive stage begins at peak nitrogen uptake. The model includes responses to available light, water, temperature and carbon dioxide concentration as well as nitrogen fertilisation and irrigation. The model is data constrained at two sites, the Yaqui Valley, Mexico for wheat and the Southern Great Plains flux site for maize and soybean, using a robust combination of space-based vegetation data (including data from the MODIS and Landsat TM and ETM+ instruments), as well as ground-based biomass and yield measurements. We show a number of climate response scenarios, including increases in temperature and carbon dioxide concentrations as well as responses to irrigation and fertiliser application.
Xu, Li-Jian; Liu, Yuan-Shuai; Zhou, Li-Gang; Wu, Jian-Yong
2011-09-01
Beauvericin (BEA) is a cyclic hexadepsipeptide mycotoxin with notable phytotoxic and insecticidal activities. Fusarium redolens Dzf2 is a highly BEA-producing fungus isolated from a medicinal plant. The aim of the current study was to develop a simple and valid kinetic model for F. redolens Dzf2 mycelial growth and the optimal fed-batch operation for efficient BEA production. A modified Monod model with substrate (glucose) and product (BEA) inhibition was constructed based on the culture characteristics of F. redolens Dzf2 mycelia in a liquid medium. Model parameters were derived by simulation of the experimental data from batch culture. The model fitted closely with the experimental data over 20-50 g l(-1) glucose concentration range in batch fermentation. The kinetic model together with the stoichiometric relationships for biomass, substrate and product was applied to predict the optimal feeding scheme for fed-batch fermentation, leading to 54% higher BEA yield (299 mg l(-1)) than in the batch culture (194 mg l(-1)). The modified Monod model incorporating substrate and product inhibition was proven adequate for describing the growth kinetics of F. redolens Dzf2 mycelial culture at suitable but not excessive initial glucose levels in batch and fed-batch cultures.
Mathematical modelling of cell layer growth in a hollow fibre bioreactor.
Chapman, Lloyd A C; Whiteley, Jonathan P; Byrne, Helen M; Waters, Sarah L; Shipley, Rebecca J
2017-04-07
Generating autologous tissue grafts of a clinically useful volume requires efficient and controlled expansion of cell populations harvested from patients. Hollow fibre bioreactors show promise as cell expansion devices, owing to their potential for scale-up. However, further research is required to establish how to specify appropriate hollow fibre bioreactor operating conditions for expanding different cell types. In this study we develop a simple model for the growth of a cell layer seeded on the outer surface of a single fibre in a perfused hollow fibre bioreactor. Nutrient-rich culture medium is pumped through the fibre lumen and leaves the bioreactor via the lumen outlet or passes through the porous fibre walls and cell layer, and out via ports on the outer wall of the extra-capillary space. Stokes and Darcy equations for fluid flow in the fibre lumen, fibre wall, cell layer and extra-capillary space are coupled to reaction-advection-diffusion equations for oxygen and lactate transport through the bioreactor, and to a simple growth law for the evolution of the free boundary of the cell layer. Cells at the free boundary are assumed to proliferate at a rate that increases with the local oxygen concentration, and to die and detach from the layer if the local fluid shear stress or lactate concentration exceed critical thresholds. We use the model to predict operating conditions that maximise the cell layer growth for different cell types. In particular, we predict the optimal flow rate of culture medium into the fibre lumen and fluid pressure imposed at the lumen outlet for cell types with different oxygen demands and fluid shear stress tolerances, and compare the growth of the cell layer when the exit ports on the outside of the bioreactor are open with that when they are closed. Model simulations reveal that increasing the inlet flow rate and outlet fluid pressure increases oxygen delivery to the cell layer and, therefore, the growth rate of cells that are tolerant to high shear stresses, but may be detrimental for shear-sensitive cells. The cell layer growth rate is predicted to increase, and be less sensitive to the lactate tolerance of the cells, when the exit ports are opened, as the radial flow through the bioreactor is enhanced and the lactate produced by the cells cleared more rapidly from the cell layer. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.
Local pH oscillations witness autocatalytic self-organization of biomorphic nanostructures
NASA Astrophysics Data System (ADS)
Montalti, M.; Zhang, G.; Genovese, D.; Morales, J.; Kellermeier, M.; García-Ruiz, J. M.
2017-02-01
Bottom-up self-assembly of simple molecular compounds is a prime pathway to complex materials with interesting structures and functions. Coupled reaction systems are known to spontaneously produce highly ordered patterns, so far observed in soft matter. Here we show that similar phenomena can occur during silica-carbonate crystallization, the emerging order being preserved. The resulting materials, called silica biomorphs, exhibit non-crystallographic curved morphologies and hierarchical textures, much reminiscent of structural principles found in natural biominerals. We have used a fluorescent chemosensor to probe local conditions during the growth of such self-organized nanostructures. We demonstrate that the pH oscillates in the local microenvironment near the growth front due to chemical coupling, which becomes manifest in the final mineralized architectures as intrinsic banding patterns with the same periodicity. A better understanding of dynamic autocatalytic crystallization processes in such simple model systems is key to the rational development of advanced materials and to unravel the mechanisms of biomineralization.
The role of model dynamics in ensemble Kalman filter performance for chaotic systems
Ng, G.-H.C.; McLaughlin, D.; Entekhabi, D.; Ahanin, A.
2011-01-01
The ensemble Kalman filter (EnKF) is susceptible to losing track of observations, or 'diverging', when applied to large chaotic systems such as atmospheric and ocean models. Past studies have demonstrated the adverse impact of sampling error during the filter's update step. We examine how system dynamics affect EnKF performance, and whether the absence of certain dynamic features in the ensemble may lead to divergence. The EnKF is applied to a simple chaotic model, and ensembles are checked against singular vectors of the tangent linear model, corresponding to short-term growth and Lyapunov vectors, corresponding to long-term growth. Results show that the ensemble strongly aligns itself with the subspace spanned by unstable Lyapunov vectors. Furthermore, the filter avoids divergence only if the full linearized long-term unstable subspace is spanned. However, short-term dynamics also become important as non-linearity in the system increases. Non-linear movement prevents errors in the long-term stable subspace from decaying indefinitely. If these errors then undergo linear intermittent growth, a small ensemble may fail to properly represent all important modes, causing filter divergence. A combination of long and short-term growth dynamics are thus critical to EnKF performance. These findings can help in developing practical robust filters based on model dynamics. ?? 2011 The Authors Tellus A ?? 2011 John Wiley & Sons A/S.
Diffusion of a new intermediate product in a simple 'classical-Schumpeterian' model.
Haas, David
2018-05-01
This paper deals with the problem of new intermediate products within a simple model, where production is circular and goods enter into the production of other goods. It studies the process by which the new good is absorbed into the economy and the structural transformation that goes with it. By means of a long-period method the forces of structural transformation are examined, in particular the shift of existing means of production towards the innovation and the mechanism of differential growth in terms of alternative techniques and their associated systems of production. We treat two important Schumpeterian topics: the question of technological unemployment and the problem of 'forced saving' and the related problem of an involuntary reduction of real consumption per capita. It is shown that both phenomena are potential by-products of the transformation process.
NASA Astrophysics Data System (ADS)
Houska, T.; Multsch, S.; Kraft, P.; Frede, H.-G.; Breuer, L.
2014-04-01
Computer simulations are widely used to support decision making and planning in the agriculture sector. On the one hand, many plant growth models use simplified hydrological processes and structures - for example, by the use of a small number of soil layers or by the application of simple water flow approaches. On the other hand, in many hydrological models plant growth processes are poorly represented. Hence, fully coupled models with a high degree of process representation would allow for a more detailed analysis of the dynamic behaviour of the soil-plant interface. We coupled two of such high-process-oriented independent models and calibrated both models simultaneously. The catchment modelling framework (CMF) simulated soil hydrology based on the Richards equation and the van Genuchten-Mualem model of the soil hydraulic properties. CMF was coupled with the plant growth modelling framework (PMF), which predicts plant growth on the basis of radiation use efficiency, degree days, water shortage and dynamic root biomass allocation. The Monte Carlo-based generalized likelihood uncertainty estimation (GLUE) method was applied to parameterize the coupled model and to investigate the related uncertainty of model predictions. Overall, 19 model parameters (4 for CMF and 15 for PMF) were analysed through 2 × 106 model runs randomly drawn from a uniform distribution. The model was applied to three sites with different management in Müncheberg (Germany) for the simulation of winter wheat (Triticum aestivum L.) in a cross-validation experiment. Field observations for model evaluation included soil water content and the dry matter of roots, storages, stems and leaves. The shape parameter of the retention curve n was highly constrained, whereas other parameters of the retention curve showed a large equifinality. We attribute this slightly poorer model performance to missing leaf senescence, which is currently not implemented in PMF. The most constrained parameters for the plant growth model were the radiation-use efficiency and the base temperature. Cross validation helped to identify deficits in the model structure, pointing out the need for including agricultural management options in the coupled model.
Halsteinli, Vidar; Kittelsen, Sverre A; Magnussen, Jon
2010-02-01
The performance of health service providers may be monitored by measuring productivity. However, the policy value of such measures may depend crucially on the accuracy of input and output measures. In particular, an important question is how to adjust adequately for case-mix in the production of health care. In this study, we assess productivity growth in Norwegian outpatient child and adolescent mental health service units (CAMHS) over a period characterized by governmental utilization of simple productivity indices, a substantial increase in capacity and a concurrent change in case-mix. We analyze the sensitivity of the productivity growth estimates using different specifications of output to adjust for case-mix differences. Case-mix adjustment is achieved by distributing patients into eight groups depending on reason for referral, age and gender, as well as correcting for the number of consultations. We utilize the nonparametric Data Envelopment Analysis (DEA) method to implicitly calculate weights that maximize each unit's efficiency. Malmquist indices of technical productivity growth are estimated and bootstrap procedures are performed to calculate confidence intervals and to test alternative specifications of outputs. The dataset consist of an unbalanced panel of 48-60 CAMHS in the period 1998-2006. The mean productivity growth estimate from a simple unadjusted patient model (one single output) is 35%; adjusting for case-mix (eight outputs) reduces the growth estimate to 15%. Adding consultations increases the estimate to 28%. The latter reflects an increase in number of consultations per patient. We find that the governmental productivity indices strongly tend to overestimate productivity growth. Case-mix adjustment is of major importance and governmental utilization of performance indicators necessitates careful considerations of output specifications. Copyright 2009 Elsevier Ltd. All rights reserved.
Modeling the growth of Listeria monocytogenes in mold-ripened cheeses.
Lobacz, Adriana; Kowalik, Jaroslaw; Tarczynska, Anna
2013-06-01
This study presents possible applications of predictive microbiology to model the safety of mold-ripened cheeses with respect to bacteria of the species Listeria monocytogenes during (1) the ripening of Camembert cheese, (2) cold storage of Camembert cheese at temperatures ranging from 3 to 15°C, and (3) cold storage of blue cheese at temperatures ranging from 3 to 15°C. The primary models used in this study, such as the Baranyi model and modified Gompertz function, were fitted to growth curves. The Baranyi model yielded the most accurate goodness of fit and the growth rates generated by this model were used for secondary modeling (Ratkowsky simple square root and polynomial models). The polynomial model more accurately predicted the influence of temperature on the growth rate, reaching the adjusted coefficients of multiple determination 0.97 and 0.92 for Camembert and blue cheese, respectively. The observed growth rates of L. monocytogenes in mold-ripened cheeses were compared with simulations run with the Pathogen Modeling Program (PMP 7.0, USDA, Wyndmoor, PA) and ComBase Predictor (Institute of Food Research, Norwich, UK). However, the latter predictions proved to be consistently overestimated and contained a significant error level. In addition, a validation process using independent data generated in dairy products from the ComBase database (www.combase.cc) was performed. In conclusion, it was found that L. monocytogenes grows much faster in Camembert than in blue cheese. Both the Baranyi and Gompertz models described this phenomenon accurately, although the Baranyi model contained a smaller error. Secondary modeling and further validation of the generated models highlighted the issue of usability and applicability of predictive models in the food processing industry by elaborating models targeted at a specific product or a group of similar products. Copyright © 2013 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.
The Nucleation and Growth of Protein Crystals
NASA Technical Reports Server (NTRS)
Pusey, Marc
2004-01-01
Obtaining crystals of suitable size and high quality continues to be a major bottleneck in macromolecular crystallography. Currently, structural genomics efforts are achieving on average about a 10% success rate in going from purified protein to a deposited crystal structure. Growth of crystals in microgravity was proposed as a means of overcoming size and quality problems, which subsequently led to a major NASA effort in microgravity crystal growth, with the agency also funding research into understanding the process. Studies of the macromolecule crystal nucleation and growth process were carried out in a number of labs in an effort to understand what affected the resultant crystal quality on Earth, and how microgravity improved the process. Based upon experimental evidence, as well as simple starting assumptions, we have proposed that crystal nucleation occurs by a series of discrete self assembly steps, which 'set' the underlying crystal symmetry. This talk will review the model developed, and its origins, in our laboratory for how crystals nucleate and grow, and will then present, along with preliminary data, how we propose to use this model to improve the success rate for obtaining crystals from a given protein.
Bacterial finite-size effects for population expansion under flow
NASA Astrophysics Data System (ADS)
Toschi, Federico; Tesser, Francesca; Zeegers, Jos C. H.; Clercx, Herman J. H.; Brunsveld, Luc
2016-11-01
For organisms living in a liquid ecosystem, flow and flow gradients have a dual role as they transport nutrient while, at the same time, dispersing the individuals. In absence of flow and under homogeneous conditions, the growth of a population towards an empty region is usually described by a reaction-diffusion equation. The effect of fluid flow is not yet well understood and the interplay between transport of individuals and growth opens a wide scenario of possible behaviors. In this work, we study experimentally the dynamics of non-motile E. coli bacteria colonies spreading inside rectangular channels, in PDMS microfluidic devices. By use of a fluorescent microscope we analyze the dynamics of the population density subjected to different co- and counter-flow conditions and shear rates. A simple model incorporating growth, dispersion and drift of finite size beads is able to explain the experimental findings. This indicates that models based on the Fisher-Kolmogorov-Petrovsky-Piscounov equation (FKPP) may have to be supplemented with bacterial finite-size effects in order to be able to accurately reproduce experimental results for population spatial growth.
Frazil-ice growth rate and dynamics in mixed layers and sub-ice-shelf plumes
NASA Astrophysics Data System (ADS)
Rees Jones, David W.; Wells, Andrew J.
2018-01-01
The growth of frazil or granular ice is an important mode of ice formation in the cryosphere. Recent advances have improved our understanding of the microphysical processes that control the rate of ice-crystal growth when water is cooled beneath its freezing temperature. These advances suggest that crystals grow much faster than previously thought. In this paper, we consider models of a population of ice crystals with different sizes to provide insight into the treatment of frazil ice in large-scale models. We consider the role of crystal growth alongside the other physical processes that determine the dynamics of frazil ice. We apply our model to a simple mixed layer (such as at the surface of the ocean) and to a buoyant plume under a floating ice shelf. We provide numerical calculations and scaling arguments to predict the occurrence of frazil-ice explosions, which we show are controlled by crystal growth, nucleation, and gravitational removal. Faster crystal growth, higher secondary nucleation, and slower gravitational removal make frazil-ice explosions more likely. We identify steady-state crystal size distributions, which are largely insensitive to crystal growth rate but are affected by the relative importance of secondary nucleation to gravitational removal. Finally, we show that the fate of plumes underneath ice shelves is dramatically affected by frazil-ice dynamics. Differences in the parameterization of crystal growth and nucleation give rise to radically different predictions of basal accretion and plume dynamics, and can even impact whether a plume reaches the end of the ice shelf or intrudes at depth.
Noise in gene expression is coupled to growth rate.
Keren, Leeat; van Dijk, David; Weingarten-Gabbay, Shira; Davidi, Dan; Jona, Ghil; Weinberger, Adina; Milo, Ron; Segal, Eran
2015-12-01
Genetically identical cells exposed to the same environment display variability in gene expression (noise), with important consequences for the fidelity of cellular regulation and biological function. Although population average gene expression is tightly coupled to growth rate, the effects of changes in environmental conditions on expression variability are not known. Here, we measure the single-cell expression distributions of approximately 900 Saccharomyces cerevisiae promoters across four environmental conditions using flow cytometry, and find that gene expression noise is tightly coupled to the environment and is generally higher at lower growth rates. Nutrient-poor conditions, which support lower growth rates, display elevated levels of noise for most promoters, regardless of their specific expression values. We present a simple model of noise in expression that results from having an asynchronous population, with cells at different cell-cycle stages, and with different partitioning of the cells between the stages at different growth rates. This model predicts non-monotonic global changes in noise at different growth rates as well as overall higher variability in expression for cell-cycle-regulated genes in all conditions. The consistency between this model and our data, as well as with noise measurements of cells growing in a chemostat at well-defined growth rates, suggests that cell-cycle heterogeneity is a major contributor to gene expression noise. Finally, we identify gene and promoter features that play a role in gene expression noise across conditions. Our results show the existence of growth-related global changes in gene expression noise and suggest their potential phenotypic implications. © 2015 Keren et al.; Published by Cold Spring Harbor Laboratory Press.
Noise in gene expression is coupled to growth rate
Keren, Leeat; van Dijk, David; Weingarten-Gabbay, Shira; Davidi, Dan; Jona, Ghil; Weinberger, Adina; Milo, Ron; Segal, Eran
2015-01-01
Genetically identical cells exposed to the same environment display variability in gene expression (noise), with important consequences for the fidelity of cellular regulation and biological function. Although population average gene expression is tightly coupled to growth rate, the effects of changes in environmental conditions on expression variability are not known. Here, we measure the single-cell expression distributions of approximately 900 Saccharomyces cerevisiae promoters across four environmental conditions using flow cytometry, and find that gene expression noise is tightly coupled to the environment and is generally higher at lower growth rates. Nutrient-poor conditions, which support lower growth rates, display elevated levels of noise for most promoters, regardless of their specific expression values. We present a simple model of noise in expression that results from having an asynchronous population, with cells at different cell-cycle stages, and with different partitioning of the cells between the stages at different growth rates. This model predicts non-monotonic global changes in noise at different growth rates as well as overall higher variability in expression for cell-cycle–regulated genes in all conditions. The consistency between this model and our data, as well as with noise measurements of cells growing in a chemostat at well-defined growth rates, suggests that cell-cycle heterogeneity is a major contributor to gene expression noise. Finally, we identify gene and promoter features that play a role in gene expression noise across conditions. Our results show the existence of growth-related global changes in gene expression noise and suggest their potential phenotypic implications. PMID:26355006
Major galaxy mergers and the growth of supermassive black holes in quasars.
Treister, Ezequiel; Natarajan, Priyamvada; Sanders, David B; Urry, C Megan; Schawinski, Kevin; Kartaltepe, Jeyhan
2010-04-30
Despite observed strong correlations between central supermassive black holes (SMBHs) and star formation in galactic nuclei, uncertainties exist in our understanding of their coupling. We present observations of the ratio of heavily obscured to unobscured quasars as a function of cosmic epoch up to z congruent with 3 and show that a simple physical model describing mergers of massive, gas-rich galaxies matches these observations. In the context of this model, every obscured and unobscured quasar represents two distinct phases that result from a massive galaxy merger event. Much of the mass growth of the SMBH occurs during the heavily obscured phase. These observations provide additional evidence for a causal link between gas-rich galaxy mergers, accretion onto the nuclear SMBH, and coeval star formation.
Network-based model of the growth of termite nests
NASA Astrophysics Data System (ADS)
Eom, Young-Ho; Perna, Andrea; Fortunato, Santo; Darrouzet, Eric; Theraulaz, Guy; Jost, Christian
2015-12-01
We present a model for the growth of the transportation network inside nests of the social insect subfamily Termitinae (Isoptera, termitidae). These nests consist of large chambers (nodes) connected by tunnels (edges). The model based on the empirical analysis of the real nest networks combined with pruning (edge removal, either random or weighted by betweenness centrality) and a memory effect (preferential growth from the latest added chambers) successfully predicts emergent nest properties (degree distribution, size of the largest connected component, average path lengths, backbone link ratios, and local graph redundancy). The two pruning alternatives can be associated with different genuses in the subfamily. A sensitivity analysis on the pruning and memory parameters indicates that Termitinae networks favor fast internal transportation over efficient defense strategies against ant predators. Our results provide an example of how complex network organization and efficient network properties can be generated from simple building rules based on local interactions and contribute to our understanding of the mechanisms that come into play for the formation of termite networks and of biological transportation networks in general.
Fatigue damage mechanics of notched graphite-epoxy laminates
NASA Astrophysics Data System (ADS)
Spearing, Mark; Beaumont, Peter W. R.; Ashby, Michael F.
A modeling approach is presented that recognizes that the residual properties of composite laminates after any form of loading depend on the damage state. Therefore, in the case of cyclic loading, it is necessary to first derive a damage growth law and then relate the residual properties to the accumulated damage. The propagation of fatigue damage in notched laminates is investigated. A power law relationship between damage growth and the strain energy release rate is developed. The material constants used in the model have been determined in independent experiments and are invariant for all the layups investigated. The strain energy release rates are calculated using a simple finite element representation of the damaged specimen. The model is used to predict the effect of tension-tension cyclic loading on laminates of the T300/914C carbon-fiber epoxy system. The extent of damage propagation is successfully predicted in a number of cross-ply laminates.
The growth of aspherical structure in the universe - Is the Local Supercluster an unusual system
NASA Technical Reports Server (NTRS)
White, S. D. M.; Silk, J.
1979-01-01
The growth and subsequent collapse of homogeneous ellipsoidal perturbations in a uniform expanding background is considered as a simple model for the formation of large-scale aspherical structures in the observed universe. Numerical calculations of the evolution of such perturbations turn out to be well described by an approximate analytic solution of the equations of motion, and simple relationships are found between the initial shape of a perturbation and its shape and kinematic properties at the time of collapse. Perturbations do not change their shape significantly until they reach a density contrast of order unity. As a result, structures with the kinematic properties of the Local Supercluster should form much more commonly in a low-density universe than in a flat universe. The homogeneity of the local Hubble flow, the motion of the Milky Way with respect to the microwave background, and the flattening of the Local Supercluster can be successfully accounted for by these models, provided that the initial perturbation is sufficiently flattened. Viable models are obtained only if the ratio of the lengths of the two smaller axes of the initial perturbation is at least 3:1 in an Einstein-de Sitter universe or at least 1.8:1 in a universe for which the density parameter (Omega) is of order 0.1, when the protocluster pancakes.
Cloern, J.E.
1999-01-01
Anthropogenic nutrient enrichment of the coastal zone is now a well-established fact. However, there is still uncertainty about the mechanisms through which nutrient enrichment can disrupt biological communities and ecosystem processes in the coastal zone. For example, while some estuaries exhibit classic symptoms of acute eutrophication, including enhanced production of algal biomass, other nutrient-rich estuaries maintain low algal biomass and primary production. This implies that large differences exist among coastal ecosystems in the rates and patterns of nutrient assimilation and cycling. Part of this variability comes from differences among ecosystems in the other resource that can limit algal growth and production - the light energy required for photosynthesis. Complete understanding of the eutrophication process requires consideration of the interacting effects of light and nutrients, including the role of light availability as a regulator of the expression of eutrophication. A simple index of the relative strength of light and nutrient limitation of algal growth can be derived from models that describe growth rate as a function of these resources. This index can then be used as one diagnostic to classify the sensitivity of coastal ecosystems to the harmful effects of eutrophication. Here I illustrate the application of this diagnostic with light and nutrient measurements made in three California estuaries and two Dutch estuaries.
NASA Astrophysics Data System (ADS)
Cremer, Jonas; Segota, Igor; Yang, Chih-Yu; Arnoldini, Markus; Groisman, Alex; Hwa, Terence
2016-11-01
More than half of fecal dry weight is bacterial mass with bacterial densities reaching up to 1012 cells per gram. Mostly, these bacteria grow in the proximal large intestine where lateral flow along the intestine is strong: flow can in principal lead to a washout of bacteria from the proximal large intestine. Active mixing by contractions of the intestinal wall together with bacterial growth might counteract such a washout and allow high bacterial densities to occur. As a step towards understanding bacterial growth in the presence of mixing and flow, we constructed an in-vitro setup where controlled wall-deformations of a channel emulate contractions. We investigate growth along the channel under a steady nutrient inflow. Depending on mixing and flow, we observe varying spatial gradients in bacterial density along the channel. Active mixing by deformations of the channel wall is shown to be crucial in maintaining a steady-state bacterial population in the presence of flow. The growth-dynamics is quantitatively captured by a simple mathematical model, with the effect of mixing described by an effective diffusion term. Based on this model, we discuss bacterial growth dynamics in the human large intestine using flow- and mixing-behavior having been observed for humans.
Cadell, Susan; Hemsworth, David; Smit Quosai, Trudy; Steele, Rose; Davies, Elizabeth; Liben, Stephen; Straatman, Lynn; Siden, Harold
2014-03-01
When parents first meet their child, they take on the entwined joys and burdens of caring for another person. Providing care for their child becomes the basic expectation, during health and illness, through the developmental milestones, into adulthood and beyond. For those parents who have a child who is born with or is later diagnosed with a life-limiting illness, parents also become caregivers in ways that parents of predominantly well children do not. While the circumstances are undisputedly stressful, for some parents benefits can co-occur along with the negative outcomes. This article tests two structural equation models of possible factors that allow these parent caregivers to experience growth in the circumstances. The diagnosis and illness of a child in the context of pediatric palliative care is a very complex experience for parents. The stresses are numerous and life-changing and yet the parents in this research demonstrated growth as measured by the Post Traumatic Growth Inventory. It appears that particular personal resources reflected in personal well-being are a precursor to the process of positive meaning making, which then, in turn, contributes to growth. The path to posttraumatic growth is not a simple one, but this research contributes to further elucidating it.
Regulatory design governing progression of population growth phases in bacteria.
Martínez-Antonio, Agustino; Lomnitz, Jason G; Sandoval, Santiago; Aldana, Maximino; Savageau, Michael A
2012-01-01
It has long been noted that batch cultures inoculated with resting bacteria exhibit a progression of growth phases traditionally labeled lag, exponential, pre-stationary and stationary. However, a detailed molecular description of the mechanisms controlling the transitions between these phases is lacking. A core circuit, formed by a subset of regulatory interactions involving five global transcription factors (FIS, HNS, IHF, RpoS and GadX), has been identified by correlating information from the well- established transcriptional regulatory network of Escherichia coli and genome-wide expression data from cultures in these different growth phases. We propose a functional role for this circuit in controlling progression through these phases. Two alternative hypotheses for controlling the transition between the growth phases are first, a continuous graded adjustment to changing environmental conditions, and second, a discontinuous hysteretic switch at critical thresholds between growth phases. We formulate a simple mathematical model of the core circuit, consisting of differential equations based on the power-law formalism, and show by mathematical and computer-assisted analysis that there are critical conditions among the parameters of the model that can lead to hysteretic switch behavior, which--if validated experimentally--would suggest that the transitions between different growth phases might be analogous to cellular differentiation. Based on these provocative results, we propose experiments to test the alternative hypotheses.
Classical Mathematical Models for Description and Prediction of Experimental Tumor Growth
Benzekry, Sébastien; Lamont, Clare; Beheshti, Afshin; Tracz, Amanda; Ebos, John M. L.; Hlatky, Lynn; Hahnfeldt, Philip
2014-01-01
Despite internal complexity, tumor growth kinetics follow relatively simple laws that can be expressed as mathematical models. To explore this further, quantitative analysis of the most classical of these were performed. The models were assessed against data from two in vivo experimental systems: an ectopic syngeneic tumor (Lewis lung carcinoma) and an orthotopically xenografted human breast carcinoma. The goals were threefold: 1) to determine a statistical model for description of the measurement error, 2) to establish the descriptive power of each model, using several goodness-of-fit metrics and a study of parametric identifiability, and 3) to assess the models' ability to forecast future tumor growth. The models included in the study comprised the exponential, exponential-linear, power law, Gompertz, logistic, generalized logistic, von Bertalanffy and a model with dynamic carrying capacity. For the breast data, the dynamics were best captured by the Gompertz and exponential-linear models. The latter also exhibited the highest predictive power, with excellent prediction scores (≥80%) extending out as far as 12 days in the future. For the lung data, the Gompertz and power law models provided the most parsimonious and parametrically identifiable description. However, not one of the models was able to achieve a substantial prediction rate (≥70%) beyond the next day data point. In this context, adjunction of a priori information on the parameter distribution led to considerable improvement. For instance, forecast success rates went from 14.9% to 62.7% when using the power law model to predict the full future tumor growth curves, using just three data points. These results not only have important implications for biological theories of tumor growth and the use of mathematical modeling in preclinical anti-cancer drug investigations, but also may assist in defining how mathematical models could serve as potential prognostic tools in the clinic. PMID:25167199
Classical mathematical models for description and prediction of experimental tumor growth.
Benzekry, Sébastien; Lamont, Clare; Beheshti, Afshin; Tracz, Amanda; Ebos, John M L; Hlatky, Lynn; Hahnfeldt, Philip
2014-08-01
Despite internal complexity, tumor growth kinetics follow relatively simple laws that can be expressed as mathematical models. To explore this further, quantitative analysis of the most classical of these were performed. The models were assessed against data from two in vivo experimental systems: an ectopic syngeneic tumor (Lewis lung carcinoma) and an orthotopically xenografted human breast carcinoma. The goals were threefold: 1) to determine a statistical model for description of the measurement error, 2) to establish the descriptive power of each model, using several goodness-of-fit metrics and a study of parametric identifiability, and 3) to assess the models' ability to forecast future tumor growth. The models included in the study comprised the exponential, exponential-linear, power law, Gompertz, logistic, generalized logistic, von Bertalanffy and a model with dynamic carrying capacity. For the breast data, the dynamics were best captured by the Gompertz and exponential-linear models. The latter also exhibited the highest predictive power, with excellent prediction scores (≥80%) extending out as far as 12 days in the future. For the lung data, the Gompertz and power law models provided the most parsimonious and parametrically identifiable description. However, not one of the models was able to achieve a substantial prediction rate (≥70%) beyond the next day data point. In this context, adjunction of a priori information on the parameter distribution led to considerable improvement. For instance, forecast success rates went from 14.9% to 62.7% when using the power law model to predict the full future tumor growth curves, using just three data points. These results not only have important implications for biological theories of tumor growth and the use of mathematical modeling in preclinical anti-cancer drug investigations, but also may assist in defining how mathematical models could serve as potential prognostic tools in the clinic.
A simple apparatus for controlling nucleation and size in protein crystal growth
NASA Technical Reports Server (NTRS)
Gernert, Kim M.; Smith, Robert; Carter, Daniel C.
1988-01-01
A simple device is described for controlling vapor equilibrium in macromolecular crystallization as applied to the protein crystal growth technique commonly referred to as the 'hanging drop' method. Crystal growth experiments with hen egg white lysozyme have demonstrated control of the nucleation rate. Nucleation rate and final crystal size have been found to be highly dependent upon the rate at which critical supersaturation is approached. Slower approaches show a marked decrease in the nucleation rate and an increase in crystal size.
Halbach, Udo; Burkhardt, Heinz Jürgen
1972-09-01
Laboratory populations of the rotifer Brachionus calyciflorus were cultured at different temperatures (25, 20, 15°C) but otherwise at constant conditions. The population densities showed relatively constant oscillations (Figs. 1 to 3A-C). Amplitudes and frequencies of the oscillations were positively correlated with temperature (Table 1). A test was made, whether the logistic growth function with simple time lag is able to describe the population curves. There are strong similarities between the simulations (Figs. 1-3E) and the real population dynamics if minor adjustments of the empirically determined parameters are made. There-fore it is suggested that time lags are responsible for the observed oscillations. However, the actual time lags probably do not act in the simple manner of the model, because birth and death rates react with different time lags, and both parameters are dependent on individual age and population density. A more complex model, which incorporates these modifications, should lead to a more realistic description of the observed oscillations.
A Simple Inexpensive Bridgman-Stockbarger Crystal Growth System for Organic Materials
NASA Technical Reports Server (NTRS)
Choi, J.; Aggarwal, M. D.; Wang, W. S.; Metzl, R.; Bhat, K.; Penn, Benjamin G.; Frazier, Donald O.
1996-01-01
Direct observation of solid-liquid interface is important for the directional solidification to determine the desired interface shape by controlling the growth parameters. To grow good quality single crystals of novel organic nonlinear optical materials, a simple inexpensive Bridgman-Stockbarger (BS) crystal growth system has been designed and fabricated. Two immiscible liquids have been utilized to create two zones for this crystal growth system. Bulk single crystals of benzil derivative and n-salicylidene-aniline have been successfully grown in this system. The optimum lowering rate has been found to be 0.1 mm/h for the flat interface. Results on the crystal growth and other parameters of the grown crystals are presented.
Modeling the plant-soil interaction in presence of heavy metal pollution and acidity variations.
Guala, Sebastián; Vega, Flora A; Covelo, Emma F
2013-01-01
On a mathematical interaction model, developed to model metal uptake by plants and the effects on their growth, we introduce a modification which considers also effects on variations of acidity in soil. The model relates the dynamics of the uptake of metals from soil to plants and also variations of uptake according to the acidity level. Two types of relationships are considered: total and available metal content. We suppose simple mathematical assumptions in order to get as simple as possible expressions with the aim of being easily tested in experimental problems. This work introduces modifications to two versions of the model: on the one hand, the expression of the relationship between the metal in soil and the concentration of the metal in plants and, on the other hand, the relationship between the metal in the soil and total amount of the metal in plants. The fine difference of both versions is fundamental at the moment to consider the tolerance and capacity of accumulation of pollutants in the biomass from the soil.
Data and methodological problems in establishing state gasoline-conservation targets
DOE Office of Scientific and Technical Information (OSTI.GOV)
Greene, D.L.; Walton, G.H.
The Emergency Energy Conservation Act of 1979 gives the President the authority to set gasoline-conservation targets for states in the event of a supply shortage. This paper examines data and methodological problems associated with setting state gasoline-conservation targets. The target-setting method currently used is examined and found to have some flaws. Ways of correcting these deficiencies through the use of Box-Jenkins time-series analysis are investigated. A successful estimation of Box-Jenkins models for all states included the estimation of the magnitude of the supply shortages of 1979 in each state and a preliminary estimation of state short-run price elasticities, which weremore » found to vary about a median value of -0.16. The time-series models identified were very simple in structure and lent support to the simple consumption growth model assumed by the current target method. The authors conclude that the flaws in the current method can be remedied either by replacing the current procedures with time-series models or by using the models in conjunction with minor modifications of the current method.« less
Barczi, Jean-François; Rey, Hervé; Caraglio, Yves; de Reffye, Philippe; Barthélémy, Daniel; Dong, Qiao Xue; Fourcaud, Thierry
2008-05-01
AmapSim is a tool that implements a structural plant growth model based on a botanical theory and simulates plant morphogenesis to produce accurate, complex and detailed plant architectures. This software is the result of more than a decade of research and development devoted to plant architecture. New advances in the software development have yielded plug-in external functions that open up the simulator to functional processes. The simulation of plant topology is based on the growth of a set of virtual buds whose activity is modelled using stochastic processes. The geometry of the resulting axes is modelled by simple descriptive functions. The potential growth of each bud is represented by means of a numerical value called physiological age, which controls the value for each parameter in the model. The set of possible values for physiological ages is called the reference axis. In order to mimic morphological and architectural metamorphosis, the value allocated for the physiological age of buds evolves along this reference axis according to an oriented finite state automaton whose occupation and transition law follows a semi-Markovian function. Simulations were performed on tomato plants to demonstrate how the AmapSim simulator can interface external modules, e.g. a GREENLAB growth model and a radiosity model. The algorithmic ability provided by AmapSim, e.g. the reference axis, enables unified control to be exercised over plant development parameter values, depending on the biological process target: how to affect the local pertinent process, i.e. the pertinent parameter(s), while keeping the rest unchanged. This opening up to external functions also offers a broadened field of applications and thus allows feedback between plant growth and the physical environment.
Barczi, Jean-François; Rey, Hervé; Caraglio, Yves; de Reffye, Philippe; Barthélémy, Daniel; Dong, Qiao Xue; Fourcaud, Thierry
2008-01-01
Background and Aims AmapSim is a tool that implements a structural plant growth model based on a botanical theory and simulates plant morphogenesis to produce accurate, complex and detailed plant architectures. This software is the result of more than a decade of research and development devoted to plant architecture. New advances in the software development have yielded plug-in external functions that open up the simulator to functional processes. Methods The simulation of plant topology is based on the growth of a set of virtual buds whose activity is modelled using stochastic processes. The geometry of the resulting axes is modelled by simple descriptive functions. The potential growth of each bud is represented by means of a numerical value called physiological age, which controls the value for each parameter in the model. The set of possible values for physiological ages is called the reference axis. In order to mimic morphological and architectural metamorphosis, the value allocated for the physiological age of buds evolves along this reference axis according to an oriented finite state automaton whose occupation and transition law follows a semi-Markovian function. Key Results Simulations were performed on tomato plants to demostrate how the AmapSim simulator can interface external modules, e.g. a GREENLAB growth model and a radiosity model. Conclusions The algorithmic ability provided by AmapSim, e.g. the reference axis, enables unified control to be exercised over plant development parameter values, depending on the biological process target: how to affect the local pertinent process, i.e. the pertinent parameter(s), while keeping the rest unchanged. This opening up to external functions also offers a broadened field of applications and thus allows feedback between plant growth and the physical environment. PMID:17766310
Mathematical modelling of tissue formation in chondrocyte filter cultures.
Catt, C J; Schuurman, W; Sengers, B G; van Weeren, P R; Dhert, W J A; Please, C P; Malda, J
2011-12-17
In the field of cartilage tissue engineering, filter cultures are a frequently used three-dimensional differentiation model. However, understanding of the governing processes of in vitro growth and development of tissue in these models is limited. Therefore, this study aimed to further characterise these processes by means of an approach combining both experimental and applied mathematical methods. A mathematical model was constructed, consisting of partial differential equations predicting the distribution of cells and glycosaminoglycans (GAGs), as well as the overall thickness of the tissue. Experimental data was collected to allow comparison with the predictions of the simulation and refinement of the initial models. Healthy mature equine chondrocytes were expanded and subsequently seeded on collagen-coated filters and cultured for up to 7 weeks. Resulting samples were characterised biochemically, as well as histologically. The simulations showed a good representation of the experimentally obtained cell and matrix distribution within the cultures. The mathematical results indicate that the experimental GAG and cell distribution is critically dependent on the rate at which the cell differentiation process takes place, which has important implications for interpreting experimental results. This study demonstrates that large regions of the tissue are inactive in terms of proliferation and growth of the layer. In particular, this would imply that higher seeding densities will not significantly affect the growth rate. A simple mathematical model was developed to predict the observed experimental data and enable interpretation of the principal underlying mechanisms controlling growth-related changes in tissue composition.
Guevara, J M; Moncayo, M A; Vaca-González, J J; Gutiérrez, M L; Barrera, L A; Garzón-Alvarado, D A
2015-01-01
Mechanical stimuli play a significant role in the process of long bone development as evidenced by clinical observations and in vivo studies. Up to now approaches to understand stimuli characteristics have been limited to the first stages of epiphyseal development. Furthermore, growth plate mechanical behavior has not been widely studied. In order to better understand mechanical influences on bone growth, we used Carter and Wong biomechanical approximation to analyze growth plate mechanical behavior, and explore stress patterns for different morphological stages of the growth plate. To the best of our knowledge this work is the first attempt to study stress distribution on growth plate during different possible stages of bone development, from gestation to adolescence. Stress distribution analysis on the epiphysis and growth plate was performed using axisymmetric (3D) finite element analysis in a simplified generic epiphyseal geometry using a linear elastic model as the first approximation. We took into account different growth plate locations, morphologies and widths, as well as different epiphyseal developmental stages. We found stress distribution during bone development established osteogenic index patterns that seem to influence locally epiphyseal structures growth and coincide with growth plate histological arrangement. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.
Vermeulen, A; Devlieghere, F; De Loy-Hendrickx, A; Uyttendaele, M
2011-01-31
In November 2008, a technical guidance document on the challenge test protocol was published by the EU CRL (Community of Reference Laboratory) for L. monocytogenes. This document describes the practical aspects on the execution of a challenge test in order to comply to the EU Commission regulation N° 2073/2005 on microbiological criteria for foodstuff. In this guideline two approaches are specified. On the one hand challenge tests, based on actual data measurements at the beginning and end of the shelf-life of products stored under reasonably foreseen T-profile, are described. On the other hand, growth potential is calculated by predictive models using a validated maximum specific growth rate. The present study evaluates the two above mentioned approaches on cold smoked salmon, a typical risk product for L. monocytogenes. The focus is on: (i) the relative importance of intrabatch versus interbatch variability, (ii) the concept of a simple challenge test based on actual data at start and end of shelf life versus a modelling approach and (iii) the interpretation of challenge tests. Next to this, available tertiary models were used to estimate the growth potential of these products based on their initial physicochemical characteristics. From the results it could be concluded that in some batches considerable intrabatch variability was obtained. In general, however, the interbatch variability was significantly higher than intrabatch variability. Concerning the two above mentioned methods for challenge tests, it can be stated that the first approach (simple challenge test) can be set up rather rapidly and is cost-effective for SMEs (small and medium enterprises) but provides only a single isolated outcome. This implies that challenge tests should be redone if changes occur in composition or production process. The second (modelling) approach, using extended challenge tests to establish growth parameters needs larger set ups and more complicated data analysis, which makes them more expensive. Using available tertiary models has the major advantage that the most important intrinsic and extrinsic factors can be included for the prediction of the growth parameter. It was clear that product specific models, taking into account the interaction effects with background flora, performed the best. Regarding the challenge tests, it can be concluded that the best approach to choose will depend on the particular context as in the end both approaches will lead to the same conclusion. Copyright © 2010 Elsevier B.V. All rights reserved.
Optimal quality control of bakers' yeast fed-batch culture using population dynamics.
Dairaku, K; Izumoto, E; Morikawa, H; Shioya, S; Takamatsu, T
1982-12-01
An optimal quality control policy for the overall specific growth rate of bakers' yeast, which maximizes the fermentative activity in the making of bread, was obtained by direct searching based on the mathematical model proposed previously. The mathematical model had described the age distribution of bakers' yeast which had an essential relationship to the ability of fermentation in the making of bread. The mathematical model is a simple aging model with two periods: Nonbudding and budding. Based on the result obtained by direct searching, the quality control of bakers' yeast fed-batch culture was performed and confirmed to be experimentally valid.
Tipping Points, Great and Small
NASA Astrophysics Data System (ADS)
Morrison, Foster
2010-12-01
The Forum by Jordan et al. [2010] addressed environmental problems of various scales in great detail, but getting the critical message through to the formulators of public policies requires going back to basics, namely, that exponential growth (of a population, an economy, or most anything else) is not sustainable. When have you heard any politician or economist from anywhere across the ideological spectrum say anything other than that more growth is essential? There is no need for computer models to demonstrate “limits to growth,” as was done in the 1960s. Of course, as one seeks more details, the complexity of modeling will rapidly outstrip the capabilities of both observation and computing. This is common with nonlinear systems, even simple ones. Thus, identifying all possible “tipping points,” as suggested by Jordan et al. [2010], and then stopping just short of them, is impractical if not impossible. The main thing needed to avoid environmental disasters is a bit of common sense.
Simulating the growth of an charge cloud for a microchannel plate detector
NASA Astrophysics Data System (ADS)
Siwal, Davinder; Wiggins, Blake; Desouza, Romualdo
2015-10-01
Position sensitive microchannel plate (MCP) detectors have a variety of applications in the fields of astronomy, medical imaging, neutron imaging, and ion beam tracking. Recently, a novel approach has been implemented to detect the position of an incident particle. The charge cloud produced by the MCP induces a signal on a wire harp placed between the MCP and an anode. On qualitative grounds it is clear that in this detector the induced signal shape depends on the size of the electron cloud. A detailed study has therefore been performed to investigate the size of the charge cloud within the MCP and its growth as it propagates from the MCP to the anode. A simple model has been developed to calculate the impact of charge repulsion on the growth of the electron cloud. Both the details of the model and its predictions will be presented. Supported by the US DOE NNSA under Award No. DE-NA0002012.
NASA Astrophysics Data System (ADS)
Saurez-Gonzalez, Darilis
The work presented in this document, focused on the development and characterization of mineral coatings on scaffold materials to serve as templates for growth factor binding and release. Mineral coatings were formed using a biomimetic approach that consisted in the incubation of scaffolds in modified simulated body fluids (mSBF). To modulate the properties of the mineral coating, which we hypothesized would dictate growth factor release, we used carbonate (HCO3) concentration in mSBF of 4.2 mM, 25mM, and 100mM. Analysis of the mineral coatings formed using scanning electron microscopy indicated growth of a continuous layer of mineral with different morphologies. X-ray diffraction analysis showed peaks associated with hydroxyapatite. FTIR data confirmed the substitution of HCO3 in the mineral. As the extent of HCO3 substitution increased, the coating exhibited more rapid dissolution kinetics in an environment deficient in calcium and phosphate. The mineral coatings provided an effective mechanism for bioactive growth factor binding and release. Peptide versions of vascular endothelial growth factor (VEGF) and bone morphogenetic protein 2 (BMP2) were bound with efficiencies up to 90% to mineral-coated PCL scaffolds. Recombinant human vascular endothelial growth factor (rhVEGF) also bound to mineral coated scaffolds with lower efficiency (20%) and released with faster release kinetics compared to peptides growth factor. Released rhVEGF induced human umbilical vein endothelial cell (HUVEC) proliferation in vitro and enhanced blood vessel formation in vivo in an intramuscular sheep model. In addition to the use the mineral coatings for single growth factor release, we expanded the concept and bound both an angiogenic (rhVEGF) and osteogenic (mBMP2) growth factor by a simple double dipping process. Sustained release of both growth factors was demonstrated for over 60 days. Released rhVEGF enhanced blood vessel formation in vivo in sheep and its biological activity was not affected by the presence of mBMP2. The approach for growth factor binding and release from mineral coatings can be adapted to different materials and medical devices and provide a simple and adaptable mechanism for sustained release of single or dual growth factors.
Forward modeling of tree-ring data: a case study with a global network
NASA Astrophysics Data System (ADS)
Breitenmoser, P. D.; Frank, D.; Brönnimann, S.
2012-04-01
Information derived from tree-rings is one of the most powerful tools presently available for studying past climatic variability as well as identifying fundamental relationships between tree-growth and climate. Climate reconstructions are typically performed by extending linear relationships, established during the overlapping period of instrumental and climate proxy archives into the past. Such analyses, however, are limited by methodological assumptions, including stationarity and linearity of the climate-proxy relationship. We investigate climate and tree-ring data using the Vaganov-Shashkin-Lite (VS-Lite) forward model of tree-ring width formation to examine the relations among actual tree growth and climate (as inferred from the simulated chronologies) to reconstruct past climate variability. The VS-lite model has been shown to produce skill comparable to that achieved using classical dendrochronological statistical modeling techniques when applied on simulations of a network of North American tree-ring chronologies. Although the detailed mechanistic processes such as photosynthesis, storage, or cell processes are not modeled directly, the net effect of the dominating nonlinear climatic controls on tree-growth are implemented into the model by the principle of limiting factors and threshold growth response functions. The VS-lite model requires as inputs only latitude, monthly mean temperature and monthly accumulated precipitation. Hence, this simple, process-based model enables ring-width simulation at any location where monthly climate records exist. In this study, we analyse the growth response of simulated tree-rings to monthly climate conditions obtained from the 20th century reanalysis project back to 1871. These simulated tree-ring chronologies are compared to the climate-driven variability in worldwide observed tree-ring chronologies from the International Tree Ring Database. Results point toward the suitability of the relationship among actual tree growth and climate (as inferred from the simulated chronologies) for use in global palaeoclimate reconstructions.
Experimental simulation and morphological quantification of volcano growth
NASA Astrophysics Data System (ADS)
Grosse, Pablo; Kervyn, Matthieu; Gallland, Olivier; Delcamp, Audray; Poppe, Sam
2016-04-01
Volcanoes display very diverse morphologies as a result of a complex interplay of several constructive and destructive processes. Here the role played by the spatial distribution of eruption centre and by an underlying strike-slip fault in controlling the long term growth of volcanoes is investigated with analogue models. Volcano growth was simulated by depositing loads of granular material (sand-kaolin mixtures) from a point source. An individual load deposited at a fixed location produces a simple symmetrical cone with flank slopes at the angle of repose of the granular material (~33°) that can be considered as the building-block for the experiments. Two sets of experiments were undertaken: (1) the location of deposition of the granular material (i.e. the volcano growth location) was shifted with time following specific probability density functions simulating shifts or migrations in vent location; (2) the location of deposition was kept fixed, but the deposition rate (i.e. the volcano growth rate) was varied coupled with the movement of a basal plate attached to a step-motor simulating a strike-slip displacement under the growing cone (and hence deformation of the cone). During the progression of the experiments, the models were photographed at regular time intervals using four digital cameras positioned at slightly different angles over the models. The photographs were used to generate synthetic digital elevation models (DEMs) with 0.2 mm spatial resolution of each step of the models by applying the MICMAC digital stereo-photogrammetry software. Morphometric data were extracted from the DEMs by applying two IDL-language algorithms: NETVOLC, used to automatically calculate the volcano edifice basal outline, and MORVOLC, used to extract a set of morphometric parameters that characterize the volcano edifice in terms of size, plan shape, profile shape and slopes. Analysis of the DEM-derived morphometric parameters allows to quantitatively characterize the growth evolution of the volcano models in terms of vent distribution and growth rate-deformation rate ratios.
NASA Astrophysics Data System (ADS)
Zhou, Tihe; Zhang, Peng; O'Malley, Ronald J.; Zurob, Hatem S.; Subramanian, Mani
2015-01-01
In order to achieve a fine uniform grain-size distribution using the process of thin slab casting and directing rolling (TSCDR), it is necessary to control the grain-size prior to the onset of thermomechanical processing. In the companion paper, Model Fe- Al Steel with Exceptional Resistance to High Temperature Coarsening. Part I: Coarsening Mechanism and Particle Pinning Effects, a new steel composition which uses a small volume fraction of austenite particles to pin the growth of delta-ferrite grains at high temperature was proposed and grain growth was studied in reheated samples. This paper will focus on the development of a simple laboratory-scale setup to simulate thin-slab casting of the newly developed steel and demonstrate the potential for grain size control under industrial conditions. Steel bars with different diameters are briefly dipped into the molten steel to create a shell of solidified material. These are then cooled down to room temperature at different cooling rates. During cooling, the austenite particles nucleate along the delta-ferrite grain boundaries and greatly retard grain growth. With decreasing temperature, more austenite particles precipitate, and grain growth can be completely arrested in the holding furnace. Additional applications of the model alloy are discussed including grain-size control in the heat affected zone in welds and grain-growth resistance at high temperature.
Crack deflection: Implications for the growth of long and short fatigue cracks
NASA Astrophysics Data System (ADS)
Suresh, S.
1983-11-01
The influences of crack deflection on the growth rates of nominally Mode I fatigue cracks are examined. Previous theoretical analyses of stress intensity solutions for kinked elastic cracks are reviewed. Simple elastic deflection models are developed to estimate the growth rates of nonlinear fatigue cracks subjected to various degrees of deflection, by incorporating changes in the effective driving force and in the apparent propagation rates. Experimental data are presented for intermediate-quenched and step-quenched conditions of Fe/2Si/0.1C ferrite-martensite dual phase steel, where variations in crack morphology alone influence considerably the fatigue crack propagation rates and threshold stress intensity range values. Such results are found to be in good quantitative agreement with the deflection model predictions of propagation rates for nonlinear cracks. Experimental information on crack deflection, induced by variable amplitude loading, is also provided for 2020-T651 aluminum alloy. It is demonstrated with the aid of elastic analyses and experiments that crack deflection models offer a physically-appealing rationale for the apparently slower growth rates of long fatigue cracks subjected to constant and variable amplitude loading and for the apparent deceleration and/or arrest of short cracks. The changes in the propagation rates of deflected fatigue cracks are discussed in terms of the local mode of crack advance, microstructure, effective driving force, growth mechanisms, mean stress, slip characteristics, and crack closure.
NASA Astrophysics Data System (ADS)
Durand-Smet, P.; Gauquelin, E.; Chastrette, N.; Boudaoud, A.; Asnacios, A.
2017-10-01
While plant growth is well known to rely on turgor pressure, it is challenging to quantify the contribution of turgor pressure to plant cell rheology. Here we used a custom-made micro-rheometer to quantify the viscoelastic behavior of isolated plant cells while varying their internal turgor pressure. To get insight into how plant cells adapt their internal pressure to the osmolarity of their medium, we compared the mechanical behavior of single plant cells to that of a simple, passive, pressurized shell: a soccer ball. While both systems exhibited the same qualitative behavior, a simple mechanical model allowed us to quantify turgor pressure regulation at the single cell scale.
A size threshold governs Caenorhabditis elegans developmental progression
Uppaluri, Sravanti; Brangwynne, Clifford P.
2015-01-01
The growth of organisms from humans to bacteria is affected by environmental conditions. However, mechanisms governing growth and size control are not well understood, particularly in the context of changes in food availability in developing multicellular organisms. Here, we use a novel microfluidic platform to study the impact of diet on the growth and development of the nematode Caenorhabditis elegans. This device allows us to observe individual worms throughout larval development, quantify their growth as well as pinpoint the moulting transitions marking successive developmental stages. Under conditions of low food availability, worms grow very slowly, but do not moult until they have achieved a threshold size. The time spent in larval stages can be extended by over an order of magnitude, in agreement with a simple threshold size model. Thus, a critical worm size appears to trigger developmental progression, and may contribute to prolonged lifespan under dietary restriction. PMID:26290076
Measurement and analysis of critical crack tip processes during fatigue crack growth
NASA Technical Reports Server (NTRS)
Davidson, D. L.; Hudak, S. J.; Dexter, R. J.
1985-01-01
The mechanics of fatigue crack growth under constant-amplitudes and variable-amplitude loading were examined. Critical loading histories involving relatively simple overload and overload/underload cycles were studied to provide a basic understanding of the underlying physical processes controlling crack growth. The material used for this study was 7091-T7E69, a powder metallurgy aluminum alloy. Local crack-tip parameters were measured at various times before, during, and after the overloads, these include crack-tip opening loads and displacements, and crack-tip strain fields. The latter were useed, in combination with the materials cyclic and monotonic stress-strain properties, to compute crack-tip residual stresses. The experimental results are also compared with analytical predictions obtained using the FAST-2 computer code. The sensitivity of the analytical model to constant-amplitude fatigue crack growth rate properties and to through-thickness constrain are studied.
Garg, Suruchi; Manchanda, Shweta
2017-01-01
Platelet-rich plasma (PRP) has emerged as a new treatment modality in regenerative plastic surgery and dermatology. PRP is a simple, cost-effective and feasible treatment option with high patient satisfaction for hair loss and can be regarded as a valuable adjuvant treatment modality for androgenic alopecia and other types of non-scarring alopecias. Authors have proposed a hair model termed "Golden anchorage with 'molecular locking' of ectodermal and mesenchymal components for survival and integrity of hair follicle (HF)" in this article. Golden anchorage comprises of bulge stem cells, ectodermal basement membrane and bulge portion of APM. PRP with its autologous supply of millions of growth factors works on 'Golden anchorage' along with keratinocytes (PDGF), dermal papilla (IGF and fibroblast growth factor), vasculature (VEGF and PDGF) and neural cells (Nerve Growth Factor) in a multipronged manner serving as an 'elixir' for hair growth and improving overall environment.
Directional stability of crack propagation
DOE Office of Scientific and Technical Information (OSTI.GOV)
Streit, R.D.; Finnie, I.
Despite many alternative models, the original Erdogan and Sih (1963) hypothesis that a crack will grow in the direction perpendicular to the maximum circumferential stress sigma/sub theta/ is seen to be adequate for predicting the angle of crack growth under the condition of mixed mode loading. Their predictions, which were based on the singularity terms in the series expansion for the Mode I and Mode II stress fields, can be improved if the second term in the series is also included. Although conceptually simple, their predictions of the crack growth direction fit very closely to the data obtained from manymore » sources.« less
Diffusion Dynamics and Creative Destruction in a Simple Classical Model
2015-01-01
ABSTRACT The article explores the impact of the diffusion of new methods of production on output and employment growth and income distribution within a Classical one‐sector framework. Disequilibrium paths are studied analytically and in terms of simulations. Diffusion by differential growth affects aggregate dynamics through several channels. The analysis reveals the non‐steady nature of economic change and shows that the adaptation pattern depends both on the innovation's factor‐saving bias and on the extent of the bias, which determines the strength of the selection pressure on non‐innovators. The typology of different cases developed shows various aspects of Schumpeter's concept of creative destruction. PMID:27642192
NASA Technical Reports Server (NTRS)
Cox, Matthew C.; Anilkumar, Amrutur V.; Grugel, RIchard N.; Lee, Chun P.
2008-01-01
Directional solidification experiments were performed, using succinonitrile saturated with nitrogen gas, to examine the effects of in-situ processing pressure changes on the formation growth, and evolution of an isolated, cylindrical gaseous pore. A novel solidification facility, capable of processing thin cylindrical samples (I.D. < 1.0 mm), under controlled pressure conditions, was used for the experiments. A new experimental method for growing the isolated pore from a seed bubble is introduced. The experimental results indicate that an in-situ processing pressure change will result in either a transient change in pore diameter or a complete termination of pore growth, indicating that pressure changes can be used as a control parameter to terminate bubble growth. A simple analytical model has been introduced to explain the experimental observations.
When growth and photosynthesis don't match: implications for carbon balance models
NASA Astrophysics Data System (ADS)
Medlyn, B.; Mahmud, K.; Duursma, R.; Pfautsch, S.; Campany, C.
2017-12-01
Most models of terrestrial plant growth are based on the principle of carbon balance: that growth can be predicted from net uptake of carbon via photosynthesis. A key criticism leveled at these models by plant physiologists is that there are many circumstances in which plant growth appears to be independent of photosynthesis: for example, during the onset of drought, or with rising atmospheric CO2 concentration. A crucial problem for terrestrial carbon cycle models is to develop better representations of plant carbon balance when there is a mismatch between growth and photosynthesis. Here we present two studies providing insight into this mismatch. In the first, effects of root restriction on plant growth were examined by comparing Eucalyptus tereticornis seedlings growing in containers of varying sizes with freely-rooted seedlings. Root restriction caused a reduction in photosynthesis, but this reduction was insufficient to explain the even larger reduction observed in growth. We applied data assimilation to a simple carbon balance model to quantify the response of carbon balance as a whole in this experiment. We inferred that, in addition to photosynthesis, there are significant effects of root restriction on growth respiration, carbon allocation, and carbohydrate utilization. The second study was carried out at the EucFACE Free-Air CO2 Enrichment experiment. At this experiment, photosynthesis of the overstorey trees is increased with enriched CO2, but there is no significant effect on above-ground productivity. These mature trees have reached their maximum height but are at significant risk of canopy loss through disturbance, and we hypothesized that additional carbon taken up through photosynthesis is preferentially allocated to storage rather than growth. We tested this hypothesis by measuring stemwood non-structural carbohydrates (NSC) during a psyllid outbreak that completely defoliated the canopy in 2015. There was a significant drawdown of NSC during canopy re-flushing but no effect of CO2 enrichment on NSC storage nor the rate of canopy renewal. Our studies highlight an important uncertainty in current carbon balance models and demonstrate quantitative approaches than can be used to address this uncertainty.
Crack Growth Modeling in an Advanced Powder Metallurgy Alloy
1980-07-01
Figure ~ ~ ~ ~ ~ 1 90. SpcmnCniuain CorMtra ulfcto Experiments. .= is5.9 mm__ C ,, . 625 inch) , so t’ 0 1 ".6 12.7 mm (0.50 inch) Figure 5. Configuration...best simple correlation of hold time and stress ratio (R = 0.05 through 0.8) effects on Inconel 718 at 650* C (1200" F) was by the maximum stress...in the work done in another studyt22) on Inconel 718. Based on these room-temperature studies, the interpolative model was ex- pected to have a
On the improbability of intelligent extraterrestrials
NASA Astrophysics Data System (ADS)
Bond, A.
1982-05-01
Discussions relating to the prevalence of extraterrestrial life generally remain ambiguous due to the lack of a suitable model for the development of biology. In this paper a simple model is proposed based on neutral evolution theory which leads to quantitative values for the genome growth rate within a biosphere. It is hypothesised that the genome size is a measure of organism complexity and hence an indicator of the likelihood of intelligence. The calculations suggest that organisms with the complexity of human beings may be rare and only occur with a probability below once per galaxy.
NASA Astrophysics Data System (ADS)
Basu, A.; Das, B.; Middya, T. R.; Bhattacharya, D. P.
2017-01-01
The phonon growth characteristic in a degenerate semiconductor has been calculated under the condition of low temperature. If the lattice temperature is high, the energy of the intravalley acoustic phonon is negligibly small compared to the average thermal energy of the electrons. Hence one can traditionally assume the electron-phonon collisions to be elastic and approximate the Bose-Einstein (B.E.) distribution for the phonons by the simple equipartition law. However, in the present analysis at the low lattice temperatures, the interaction of the non equilibrium electrons with the acoustic phonons becomes inelastic and the simple equipartition law for the phonon distribution is not valid. Hence the analysis is made taking into account the inelastic collisions and the complete form of the B.E. distribution. The high-field distribution function of the carriers given by Fermi-Dirac (F.D.) function at the field dependent carrier temperature, has been approximated by a well tested model that apparently overcomes the intrinsic problem of correct evaluation of the integrals involving the product and powers of the Fermi function. Hence the results thus obtained are more reliable compared to the rough estimation that one may obtain from using the exact F.D. function, but taking recourse to some over simplified approximations.
Putting Theory to the Test: Which Regulatory Mechanisms Can Drive Realistic Growth of a Root?
De Vos, Dirk; Vissenberg, Kris; Broeckhove, Jan; Beemster, Gerrit T. S.
2014-01-01
In recent years there has been a strong development of computational approaches to mechanistically understand organ growth regulation in plants. In this study, simulation methods were used to explore which regulatory mechanisms can lead to realistic output at the cell and whole organ scale and which other possibilities must be discarded as they result in cellular patterns and kinematic characteristics that are not consistent with experimental observations for the Arabidopsis thaliana primary root. To aid in this analysis, a ‘Uniform Longitudinal Strain Rule’ (ULSR) was formulated as a necessary condition for stable, unidirectional, symplastic growth. Our simulations indicate that symplastic structures are robust to differences in longitudinal strain rates along the growth axis only if these differences are small and short-lived. Whereas simple cell-autonomous regulatory rules based on counters and timers can produce stable growth, it was found that steady developmental zones and smooth transitions in cell lengths are not feasible. By introducing spatial cues into growth regulation, those inadequacies could be avoided and experimental data could be faithfully reproduced. Nevertheless, a root growth model based on previous polar auxin-transport mechanisms violates the proposed ULSR due to the presence of lateral gradients. Models with layer-specific regulation or layer-driven growth offer potential solutions. Alternatively, a model representing the known cross-talk between auxin, as the cell proliferation promoting factor, and cytokinin, as the cell differentiation promoting factor, predicts the effect of hormone-perturbations on meristem size. By down-regulating PIN-mediated transport through the transcription factor SHY2, cytokinin effectively flattens the lateral auxin gradient, at the basal boundary of the division zone, (thereby imposing the ULSR) to signal the exit of proliferation and start of elongation. This model exploration underlines the value of generating virtual root growth kinematics to dissect and understand the mechanisms controlling this biological system. PMID:25358093
Putting theory to the test: which regulatory mechanisms can drive realistic growth of a root?
De Vos, Dirk; Vissenberg, Kris; Broeckhove, Jan; Beemster, Gerrit T S
2014-10-01
In recent years there has been a strong development of computational approaches to mechanistically understand organ growth regulation in plants. In this study, simulation methods were used to explore which regulatory mechanisms can lead to realistic output at the cell and whole organ scale and which other possibilities must be discarded as they result in cellular patterns and kinematic characteristics that are not consistent with experimental observations for the Arabidopsis thaliana primary root. To aid in this analysis, a 'Uniform Longitudinal Strain Rule' (ULSR) was formulated as a necessary condition for stable, unidirectional, symplastic growth. Our simulations indicate that symplastic structures are robust to differences in longitudinal strain rates along the growth axis only if these differences are small and short-lived. Whereas simple cell-autonomous regulatory rules based on counters and timers can produce stable growth, it was found that steady developmental zones and smooth transitions in cell lengths are not feasible. By introducing spatial cues into growth regulation, those inadequacies could be avoided and experimental data could be faithfully reproduced. Nevertheless, a root growth model based on previous polar auxin-transport mechanisms violates the proposed ULSR due to the presence of lateral gradients. Models with layer-specific regulation or layer-driven growth offer potential solutions. Alternatively, a model representing the known cross-talk between auxin, as the cell proliferation promoting factor, and cytokinin, as the cell differentiation promoting factor, predicts the effect of hormone-perturbations on meristem size. By down-regulating PIN-mediated transport through the transcription factor SHY2, cytokinin effectively flattens the lateral auxin gradient, at the basal boundary of the division zone, (thereby imposing the ULSR) to signal the exit of proliferation and start of elongation. This model exploration underlines the value of generating virtual root growth kinematics to dissect and understand the mechanisms controlling this biological system.
Simple spatial scaling rules behind complex cities.
Li, Ruiqi; Dong, Lei; Zhang, Jiang; Wang, Xinran; Wang, Wen-Xu; Di, Zengru; Stanley, H Eugene
2017-11-28
Although most of wealth and innovation have been the result of human interaction and cooperation, we are not yet able to quantitatively predict the spatial distributions of three main elements of cities: population, roads, and socioeconomic interactions. By a simple model mainly based on spatial attraction and matching growth mechanisms, we reveal that the spatial scaling rules of these three elements are in a consistent framework, which allows us to use any single observation to infer the others. All numerical and theoretical results are consistent with empirical data from ten representative cities. In addition, our model can also provide a general explanation of the origins of the universal super- and sub-linear aggregate scaling laws and accurately predict kilometre-level socioeconomic activity. Our work opens a new avenue for uncovering the evolution of cities in terms of the interplay among urban elements, and it has a broad range of applications.
Diffusion of a new intermediate product in a simple ‘classical‐Schumpeterian’ model
2017-01-01
Abstract This paper deals with the problem of new intermediate products within a simple model, where production is circular and goods enter into the production of other goods. It studies the process by which the new good is absorbed into the economy and the structural transformation that goes with it. By means of a long‐period method the forces of structural transformation are examined, in particular the shift of existing means of production towards the innovation and the mechanism of differential growth in terms of alternative techniques and their associated systems of production. We treat two important Schumpeterian topics: the question of technological unemployment and the problem of ‘forced saving’ and the related problem of an involuntary reduction of real consumption per capita. It is shown that both phenomena are potential by‐products of the transformation process. PMID:29695874
NASA Astrophysics Data System (ADS)
Zhang, A.; Guo, Z.; Xiong, S.-M.
2018-05-01
The influence of natural convection on lamellar eutectic growth was determined by a comprehensive phase-field lattice-Boltzmann study for Al-Cu and CB r4-C2C l6 eutectic alloys. The mass differences resulting from concentration differences led to the fluid flow and a robust parallel and adaptive mesh refinement algorithm was employed to improve the computational efficiency. By means of carefully designed "numerical experiments", the eutectic growth under natural convection was explored and a simple analytical model was proposed to predict the adjustment of the lamellar spacing. Furthermore, by alternating the solute expansion coefficient, initial lamellar spacing, and undercooling, the microstructure evolution was presented and compared with the classical eutectic growth theory. Results showed that both interfacial solute distribution and average curvature were affected by the natural convection, the effect of which could be further quantified by adding a constant into the growth rule proposed by Jackson and Hunt [Jackson and Hunt, Trans. Metall. Soc. AIME 236, 1129 (1966)].
Baroukh, Caroline; Muñoz-Tamayo, Rafael; Steyer, Jean-Philippe; Bernard, Olivier
2014-01-01
Metabolic modeling is a powerful tool to understand, predict and optimize bioprocesses, particularly when they imply intracellular molecules of interest. Unfortunately, the use of metabolic models for time varying metabolic fluxes is hampered by the lack of experimental data required to define and calibrate the kinetic reaction rates of the metabolic pathways. For this reason, metabolic models are often used under the balanced growth hypothesis. However, for some processes such as the photoautotrophic metabolism of microalgae, the balanced-growth assumption appears to be unreasonable because of the synchronization of their circadian cycle on the daily light. Yet, understanding microalgae metabolism is necessary to optimize the production yield of bioprocesses based on this microorganism, as for example production of third-generation biofuels. In this paper, we propose DRUM, a new dynamic metabolic modeling framework that handles the non-balanced growth condition and hence accumulation of intracellular metabolites. The first stage of the approach consists in splitting the metabolic network into sub-networks describing reactions which are spatially close, and which are assumed to satisfy balanced growth condition. The left metabolites interconnecting the sub-networks behave dynamically. Then, thanks to Elementary Flux Mode analysis, each sub-network is reduced to macroscopic reactions, for which simple kinetics are assumed. Finally, an Ordinary Differential Equation system is obtained to describe substrate consumption, biomass production, products excretion and accumulation of some internal metabolites. DRUM was applied to the accumulation of lipids and carbohydrates of the microalgae Tisochrysis lutea under day/night cycles. The resulting model describes accurately experimental data obtained in day/night conditions. It efficiently predicts the accumulation and consumption of lipids and carbohydrates. PMID:25105494
The life of a meander bend: Connecting shape and dynamics via analysis of a numerical model
NASA Astrophysics Data System (ADS)
Schwenk, Jon; Lanzoni, Stefano; Foufoula-Georgiou, Efi
2015-04-01
Analysis of bend-scale meandering river dynamics is a problem of theoretical and practical interest. This work introduces a method for extracting and analyzing the history of individual meander bends from inception until cutoff (called "atoms") by tracking backward through time the set of two cutoff nodes in numerical meander migration models. Application of this method to a simplified yet physically based model provides access to previously unavailable bend-scale meander dynamics over long times and at high temporal resolutions. We find that before cutoffs, the intrinsic model dynamics invariably simulate a prototypical cutoff atom shape we dub simple. Once perturbations from cutoffs occur, two other archetypal cutoff planform shapes emerge called long and round that are distinguished by a stretching along their long and perpendicular axes, respectively. Three measures of meander migration—growth rate, average migration rate, and centroid migration rate—are introduced to capture the dynamic lives of individual bends and reveal that similar cutoff atom geometries share similar dynamic histories. Specifically, through the lens of the three shape types, simples are seen to have the highest growth and average migration rates, followed by rounds, and finally longs. Using the maximum average migration rate as a metric describing an atom's dynamic past, we show a strong connection between it and two metrics of cutoff geometry. This result suggests both that early formative dynamics may be inferred from static cutoff planforms and that there exists a critical period early in a meander bend's life when its dynamic trajectory is most sensitive to cutoff perturbations. An example of how these results could be applied to Mississippi River oxbow lakes with unknown historic dynamics is shown. The results characterize the underlying model and provide a framework for comparisons against more complex models and observed dynamics.
Local rules simulation of the kinetics of virus capsid self-assembly.
Schwartz, R; Shor, P W; Prevelige, P E; Berger, B
1998-12-01
A computer model is described for studying the kinetics of the self-assembly of icosahedral viral capsids. Solution of this problem is crucial to an understanding of the viral life cycle, which currently cannot be adequately addressed through laboratory techniques. The abstract simulation model employed to address this is based on the local rules theory of. Proc. Natl. Acad. Sci. USA. 91:7732-7736). It is shown that the principle of local rules, generalized with a model of kinetics and other extensions, can be used to simulate complicated problems in self-assembly. This approach allows for a computationally tractable molecular dynamics-like simulation of coat protein interactions while retaining many relevant features of capsid self-assembly. Three simple simulation experiments are presented to illustrate the use of this model. These show the dependence of growth and malformation rates on the energetics of binding interactions, the tolerance of errors in binding positions, and the concentration of subunits in the examples. These experiments demonstrate a tradeoff within the model between growth rate and fidelity of assembly for the three parameters. A detailed discussion of the computational model is also provided.
Quantum Entanglement Growth under Random Unitary Dynamics
NASA Astrophysics Data System (ADS)
Nahum, Adam; Ruhman, Jonathan; Vijay, Sagar; Haah, Jeongwan
2017-07-01
Characterizing how entanglement grows with time in a many-body system, for example, after a quantum quench, is a key problem in nonequilibrium quantum physics. We study this problem for the case of random unitary dynamics, representing either Hamiltonian evolution with time-dependent noise or evolution by a random quantum circuit. Our results reveal a universal structure behind noisy entanglement growth, and also provide simple new heuristics for the "entanglement tsunami" in Hamiltonian systems without noise. In 1D, we show that noise causes the entanglement entropy across a cut to grow according to the celebrated Kardar-Parisi-Zhang (KPZ) equation. The mean entanglement grows linearly in time, while fluctuations grow like (time )1/3 and are spatially correlated over a distance ∝(time )2/3. We derive KPZ universal behavior in three complementary ways, by mapping random entanglement growth to (i) a stochastic model of a growing surface, (ii) a "minimal cut" picture, reminiscent of the Ryu-Takayanagi formula in holography, and (iii) a hydrodynamic problem involving the dynamical spreading of operators. We demonstrate KPZ universality in 1D numerically using simulations of random unitary circuits. Importantly, the leading-order time dependence of the entropy is deterministic even in the presence of noise, allowing us to propose a simple coarse grained minimal cut picture for the entanglement growth of generic Hamiltonians, even without noise, in arbitrary dimensionality. We clarify the meaning of the "velocity" of entanglement growth in the 1D entanglement tsunami. We show that in higher dimensions, noisy entanglement evolution maps to the well-studied problem of pinning of a membrane or domain wall by disorder.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Chakraborty, S.; Izaguirre, I.; Raffelt, G.G.
Neutrino-neutrino refraction in dense media can cause self-induced flavor conversion triggered by collective run-away modes of the interacting flavor oscillators. The growth rates were usually found to be of order a typical vacuum oscillation frequency Δ m{sup 2}/2E. However, even in the simple case of a ν{sub e} beam interacting with an opposite-moving ν-bar {sub e} beam, and allowing for spatial inhomogeneities, the growth rate of the fastest-growing Fourier mode is of order μ=√2 G{sub F} n{sub ν}, a typical ν–ν interaction energy. This growth rate is much larger than the vacuum oscillation frequency and gives rise to flavor conversion on a muchmore » shorter time scale. This phenomenon of 'fast flavor conversion' occurs even for vanishing Δ m{sup 2}/2E and thus does not depend on energy, but only on the angle distributions. Moreover, it does not require neutrinos to mix or to have masses, except perhaps for providing seed disturbances. We also construct a simple homogeneous example consisting of intersecting beams and study a schematic supernova model proposed by Ray Sawyer, where ν{sub e} and ν-bar {sub e} emerge with different zenith-angle distributions, the key ingredient for fast flavor conversion. What happens in realistic astrophysical scenarios remains to be understood.« less
Model of Fission Yeast Cell Shape Driven by Membrane-Bound Growth Factors and the Cytoskeleton
Drake, Tyler; Vavylonis, Dimitrios
2013-01-01
Fission yeast serves as a model for how cellular polarization machinery consisting of signaling molecules and the actin and microtubule cytoskeleton regulates cell shape. In this work, we develop mathematical models to investigate how these cells maintain a tubular shape of approximately constant diameter. Many studies identify active Cdc42, found in a cap at the inner membrane of growing cell tips, as an important regulator of local cell wall remodeling, likely through control of exocyst tethering and the targeting of other polarity-enhancing structures. First, we show that a computational model with Cdc42-dependent local cell wall remodeling under turgor pressure predicts a relationship between spatial extent of growth signal and cell diameter that is in agreement with prior experiments. Second, we model the consequences of feedback between cell shape and distribution of Cdc42 growth signal at cell tips. We show that stability of cell diameter over successive cell divisions places restrictions on their mutual dependence. We argue that simple models where the spatial extent of the tip growth signal relies solely on geometrical alignment of confined microtubules might lead to unstable width regulation. Third, we study a computational model that combines a growth signal distributed over a characteristic length scale (as, for example, by a reaction-diffusion mechanism) with an axis-sensing microtubules system that places landmarks at positions where microtubule tips touch the cortex. A two-dimensional implementation of this model leads to stable cell diameter for a wide range of parameters. Changes to the parameters of this model reproduce straight, bent, and bulged cell shapes, and we discuss how this model is consistent with other observed cell shapes in mutants. Our work provides an initial quantitative framework for understanding the regulation of cell shape in fission yeast, and a scaffold for understanding this process on a more molecular level in the future. PMID:24146607
Jones, Zack W; Leander, Rachel; Quaranta, Vito; Harris, Leonard A; Tyson, Darren R
2018-01-01
Even among isogenic cells, the time to progress through the cell cycle, or the intermitotic time (IMT), is highly variable. This variability has been a topic of research for several decades and numerous mathematical models have been proposed to explain it. Previously, we developed a top-down, stochastic drift-diffusion+threshold (DDT) model of a cell cycle checkpoint and showed that it can accurately describe experimentally-derived IMT distributions [Leander R, Allen EJ, Garbett SP, Tyson DR, Quaranta V. Derivation and experimental comparison of cell-division probability densities. J. Theor. Biol. 2014;358:129-135]. Here, we use the DDT modeling approach for both descriptive and predictive data analysis. We develop a custom numerical method for the reliable maximum likelihood estimation of model parameters in the absence of a priori knowledge about the number of detectable checkpoints. We employ this method to fit different variants of the DDT model (with one, two, and three checkpoints) to IMT data from multiple cell lines under different growth conditions and drug treatments. We find that a two-checkpoint model best describes the data, consistent with the notion that the cell cycle can be broadly separated into two steps: the commitment to divide and the process of cell division. The model predicts one part of the cell cycle to be highly variable and growth factor sensitive while the other is less variable and relatively refractory to growth factor signaling. Using experimental data that separates IMT into G1 vs. S, G2, and M phases, we show that the model-predicted growth-factor-sensitive part of the cell cycle corresponds to a portion of G1, consistent with previous studies suggesting that the commitment step is the primary source of IMT variability. These results demonstrate that a simple stochastic model, with just a handful of parameters, can provide fundamental insights into the biological underpinnings of cell cycle progression.
Mechanism-based model for tumor drug resistance.
Kuczek, T; Chan, T C
1992-01-01
The development of tumor resistance to cytotoxic agents has important implications in the treatment of cancer. If supported by experimental data, mathematical models of resistance can provide useful information on the underlying mechanisms and aid in the design of therapeutic regimens. We report on the development of a model of tumor-growth kinetics based on the assumption that the rates of cell growth in a tumor are normally distributed. We further assumed that the growth rate of each cell is proportional to its rate of total pyrimidine synthesis (de novo plus salvage). Using an ovarian carcinoma cell line (2008) and resistant variants selected for chronic exposure to a pyrimidine antimetabolite, N-phosphonacetyl-L-aspartate (PALA), we derived a simple and specific analytical form describing the growth curves generated in 72 h growth assays. The model assumes that the rate of de novo pyrimidine synthesis, denoted alpha, is shifted down by an amount proportional to the log10 PALA concentration and that cells whose rate of pyrimidine synthesis falls below a critical level, denoted alpha 0, can no longer grow. This is described by the equation: Probability (growth) = probability (alpha 0 less than alpha-constant x log10 [PALA]). This model predicts that when growth curves are plotted on probit paper, they will produce straight lines. This prediction is in agreement with the data we obtained for the 2008 cells. Another prediction of this model is that the same probit plots for the resistant variants should shift to the right in a parallel fashion. Probit plots of the dose-response data obtained for each resistant 2008 line following chronic exposure to PALA again confirmed this prediction. Correlation of the rightward shift of dose responses to uridine transport (r = 0.99) also suggests that salvage metabolism plays a key role in tumor-cell resistance to PALA. Furthermore, the slope of the regression lines enables the detection of synergy such as that observed between dipyridamole and PALA. Although the rate-normal model was used to study the rate of salvage metabolism in PALA resistance in the present study, it may be widely applicable to modeling of other resistance mechanisms such as gene amplification of target enzymes.
A Simple Model for the Cloud Adjacency Effect and the Apparent Bluing of Aerosols Near Clouds
NASA Technical Reports Server (NTRS)
Marshak, Alexander; Wen, Guoyong; Coakley, James A., Jr.; Remer, Lorraine A.; Loeb,Norman G.; Cahalan, Robert F.
2008-01-01
In determining aerosol-cloud interactions, the properties of aerosols must be characterized in the vicinity of clouds. Numerous studies based on satellite observations have reported that aerosol optical depths increase with increasing cloud cover. Part of the increase comes from the humidification and consequent growth of aerosol particles in the moist cloud environment, but part comes from 3D cloud-radiative transfer effects on the retrieved aerosol properties. Often, discerning whether the observed increases in aerosol optical depths are artifacts or real proves difficult. The paper provides a simple model that quantifies the enhanced illumination of cloud-free columns in the vicinity of clouds that are used in the aerosol retrievals. This model is based on the assumption that the enhancement in the cloud-free column radiance comes from enhanced Rayleigh scattering that results from the presence of the nearby clouds. The enhancement in Rayleigh scattering is estimated using a stochastic cloud model to obtain the radiative flux reflected by broken clouds and comparing this flux with that obtained with the molecules in the atmosphere causing extinction, but no scattering.
Iwai, Sosuke; Fujiwara, Kenji; Tamura, Takuro
2016-09-01
Algal endosymbiosis is widely distributed in eukaryotes including many protists and metazoans, and plays important roles in aquatic ecosystems, combining phagotrophy and phototrophy. To maintain a stable symbiotic relationship, endosymbiont population size in the host must be properly regulated and maintained at a constant level; however, the mechanisms underlying the maintenance of algal endosymbionts are still largely unknown. Here we investigate the population dynamics of the unicellular ciliate Paramecium bursaria and its Chlorella-like algal endosymbiont under various experimental conditions in a simple culture system. Our results suggest that endosymbiont population size in P. bursaria was not regulated by active processes such as cell division coupling between the two organisms, or partitioning of the endosymbionts at host cell division. Regardless, endosymbiont population size was eventually adjusted to a nearly constant level once cells were grown with light and nutrients. To explain this apparent regulation of population size, we propose a simple mechanism based on the different growth properties (specifically the nutrient requirements) of the two organisms, and based from this develop a mathematical model to describe the population dynamics of host and endosymbiont. The proposed mechanism and model may provide a basis for understanding the maintenance of algal endosymbionts. © 2015 Society for Applied Microbiology and John Wiley & Sons Ltd.
A simple integrated assessment approach to global change simulation and evaluation
NASA Astrophysics Data System (ADS)
Ogutu, Keroboto; D'Andrea, Fabio; Ghil, Michael
2016-04-01
We formulate and study the Coupled Climate-Economy-Biosphere (CoCEB) model, which constitutes the basis of our idealized integrated assessment approach to simulating and evaluating global change. CoCEB is composed of a physical climate module, based on Earth's energy balance, and an economy module that uses endogenous economic growth with physical and human capital accumulation. A biosphere model is likewise under study and will be coupled to the existing two modules. We concentrate on the interactions between the two subsystems: the effect of climate on the economy, via damage functions, and the effect of the economy on climate, via a control of the greenhouse gas emissions. Simple functional forms of the relation between the two subsystems permit simple interpretations of the coupled effects. The CoCEB model is used to make hypotheses on the long-term effect of investment in emission abatement, and on the comparative efficacy of different approaches to abatement, in particular by investing in low carbon technology, in deforestation reduction or in carbon capture and storage (CCS). The CoCEB model is very flexible and transparent, and it allows one to easily formulate and compare different functional representations of climate change mitigation policies. Using different mitigation measures and their cost estimates, as found in the literature, one is able to compare these measures in a coherent way.
The Effects of Impurities on Protein Crystal Growth and Nucleation: A Preliminary Study
NASA Technical Reports Server (NTRS)
Schall, Constance A.
1998-01-01
Kubota and Mullin (1995) devised a simple model to account for the effects of impurities on crystal growth of small inorganic and organic molecules in aqueous solutions. Experimentally, the relative step velocity and crystal growth of these molecules asymptotically approach zero or non-zero values with increasing concentrations of impurities. Alternatively, the step velocity and crystal growth can linearly approach zero as the impurity concentration increases. The Kubota-Mullin model assumes that the impurity exhibits Langmuirian adsorption onto the crystal surface. Decreases in step velocities and subsequent growth rates are related to the fractional coverage (theta) of the crystal surface by adsorbed impurities; theta = Kx / (I +Kx), x = mole fraction of impurity in solution. In the presence of impurities, the relative step velocity, V/Vo, and the relative growth rate of a crystal face, G/Go, are proposed to conform to the following equations: V/Vo approx. = G/Go = 1 - (alpha)(theta). The adsorption of impurity is assumed to be rapid and in quasi-equilibrium with the crystal surface sites available. When the value of alpha, an effectiveness factor, is one the growth will asymptotically approach zero with increasing concentrations of impurity. At values less than one, growth approaches a non-zero value asymptotically. When alpha is much greater than one, there will be a linear relationship between impurity concentration and growth rates. Kubota and Mullin expect alpha to decrease with increasing supersaturation and shrinking size of a two dimensional nucleus. It is expected that impurity effects on protein crystal growth will exhibit behavior similar to that of impurities in small molecule growth. A number of proteins were added to purified chicken egg white lysozyme, the effect on crystal nucleation and growth assessed.
The Isothermal Dendritic Growth Experiment Archive
NASA Astrophysics Data System (ADS)
Koss, Matthew
2009-03-01
The growth of dendrites is governed by the interplay between two simple and familiar processes---the irreversible diffusion of energy, and the reversible work done in the formation of new surface area. To advance our understanding of these processes, NASA sponsored a project that flew on the Space Shuttle Columbia is 1994, 1996, and 1997 to record and analyze benchmark data in an apparent-microgravity ``laboratory.'' In this laboratory, energy transfer by gravity driven convection was essentially eliminated and one could test independently, for the first time, both components of dendritic growth theory. The analysis of this data shows that although the diffusion of energy can be properly accounted for, the results from interfacial physics appear to be in disagreement and alternate models should receive increased attention. Unfortunately, currently and for the foreseeable future, there is no access or financial support to develop and conduct additional experiments of this type. However, the benchmark data of 35mm photonegatives, video, and all supporting instrument data are now available at the IDGE Archive at the College of the Holy Cross. This data may still have considerable relevance to researchers working specifically with dendritic growth, and more generally those working in the synthesis, growth & processing of materials, multiscale computational modeling, pattern formation, and systems far from equilibrium.
Materials processing in a centrifuge - Numerical modeling of macrogravity effects
NASA Technical Reports Server (NTRS)
Ramachandran, N.; Downey, J. P.; Jones, J. C.; Curreri, P. A.
1992-01-01
The fluid mechanics associated with crystal growth processes on a centrifuge is investigated. A simple scaling analysis is used to examine the relative magnitudes of the forces acting on the system and good agreement is obtained with previous studies. A two-dimensional model of crystal growth on a centrifuge is proposed and calculations are undertaken to help in understanding the fundamental transport processes within the crystal growth cell. Results from three-dimensional calculations of actual centrifuge-based crystal growth systems are presented both for the thermodynamically stable and unstable configurations. The calculations show the existence of flow bifurcations in certain configurations but not in all instances. The numerical simulations also show that the centrifugal force is the dominant stabilizing force on fluid convection in the stable configuration. The stabilizing influence of the Coriolis force is found to be only secondary in nature. No significant impact of gravity gradient is found in the calculations. Simulations of unstable configurations show that the Coriolis force has a stabilizing influence on fluid motion by delaying the onset of unsteady convection. Detailed flow and thermal field characteristics are presented for all the different cases that are simulated.
Water security, risk and economic growth: lessons from a dynamical systems model
NASA Astrophysics Data System (ADS)
Dadson, Simon; Hall, Jim; Garrick, Dustin; Sadoff, Claudia; Grey, David; Whittington, Dale
2016-04-01
Investments in the physical infrastructure, human capital, and institutions needed for water resources management have been a noteworthy feature in the development of most civilisations. These investments affect the economy in two distinct ways: (i) by improving the factor productivity of water in multiple sectors of the economy, especially those that are water intensive such as agriculture and energy; and (ii) by reducing the acute and chronic harmful effects of water-related hazards like floods, droughts, and water-related diseases. The need for capital investment to mitigate these risks in order to promote economic growth is widely acknowledged, but prior work to conceptualise the relationship between water-related risks and economic growth has focused on the productive and harmful roles of water in the economy independently. Here the two influences are combined using a simple, dynamical model of water-related investment, risk, and growth at the national level. The model suggests the existence of a context-specific threshold above which growth proceeds along an 'S'-curve. In many cases there is a requirement for initial investment in water-related assets to enable growth. Below the threshold it is possible for a poverty trap to arise. The presence and location of the poverty trap is context-specific and depends on the relative exposure of productive water-related assets to risk, compared with risks faced by assets in the wider economy. Exogenous changes in the level of water-related risk (through, for example, climate and land cover change) can potentially push an economy away from a growth path towards a poverty trap. These results illustrate the value of accounting for environmental risk in models of economic growth and may offer guidance in the design of robust policies for investment in water-related productive assets to manage risk, particularly in the face of global and regional environmental change.
Mathematical modeling of solid cancer growth with angiogenesis
2012-01-01
Background Cancer arises when within a single cell multiple malfunctions of control systems occur, which are, broadly, the system that promote cell growth and the system that protect against erratic growth. Additional systems within the cell must be corrupted so that a cancer cell, to form a mass of any real size, produces substances that promote the growth of new blood vessels. Multiple mutations are required before a normal cell can become a cancer cell by corruption of multiple growth-promoting systems. Methods We develop a simple mathematical model to describe the solid cancer growth dynamics inducing angiogenesis in the absence of cancer controlling mechanisms. Results The initial conditions supplied to the dynamical system consist of a perturbation in form of pulse: The origin of cancer cells from normal cells of an organ of human body. Thresholds of interacting parameters were obtained from the steady states analysis. The existence of two equilibrium points determine the strong dependency of dynamical trajectories on the initial conditions. The thresholds can be used to control cancer. Conclusions Cancer can be settled in an organ if the following combination matches: better fitness of cancer cells, decrease in the efficiency of the repairing systems, increase in the capacity of sprouting from existing vascularization, and higher capacity of mounting up new vascularization. However, we show that cancer is rarely induced in organs (or tissues) displaying an efficient (numerically and functionally) reparative or regenerative mechanism. PMID:22300422
Modeling the cost and benefit of proteome regulation in a growing bacterial cell
NASA Astrophysics Data System (ADS)
Sharma, Pooja; Pratim Pandey, Parth; Jain, Sanjay
2018-07-01
Escherichia coli cells differentially regulate the production of metabolic and ribosomal proteins in order to stay close to an optimal growth rate in different environments, and exhibit the bacterial growth laws as a consequence. We present a simple mathematical model of a growing-dividing cell in which an internal dynamical mechanism regulates the allocation of proteomic resources between different protein sectors. The model allows an endogenous determination of the growth rate of the cell as a function of cellular and environmental parameters, and reproduces the bacterial growth laws. We use the model and its variants to study the balance between the cost and benefit of regulation. A cost is incurred because cellular resources are diverted to produce the regulatory apparatus. We show that there is a window of environments or a ‘niche’ in which the unregulated cell has a higher fitness than the regulated cell. Outside this niche there is a large space of constant and time varying environments in which regulation is an advantage. A knowledge of the ‘niche boundaries’ allows one to gain an intuitive understanding of the class of environments in which regulation is an advantage for the organism and which would therefore favour the evolution of regulation. The model allows us to determine the ‘niche boundaries’ as a function of cellular parameters such as the size of the burden of the regulatory apparatus. This class of models may be useful in elucidating various tradeoffs in cells and in making in-silico predictions relevant for synthetic biology.
Mechanistic Understanding of Microbial Plugging for Improved Sweep Efficiency
DOE Office of Scientific and Technical Information (OSTI.GOV)
Steven Bryant; Larry Britton
2008-09-30
Microbial plugging has been proposed as an effective low cost method of permeability reduction. Yet there is a dearth of information on the fundamental processes of microbial growth in porous media, and there are no suitable data to model the process of microbial plugging as it relates to sweep efficiency. To optimize the field implementation, better mechanistic and volumetric understanding of biofilm growth within a porous medium is needed. In particular, the engineering design hinges upon a quantitative relationship between amount of nutrient consumption, amount of growth, and degree of permeability reduction. In this project experiments were conducted to obtainmore » new data to elucidate this relationship. Experiments in heterogeneous (layered) beadpacks showed that microbes could grow preferentially in the high permeability layer. Ultimately this caused flow to be equally divided between high and low permeability layers, precisely the behavior needed for MEOR. Remarkably, classical models of microbial nutrient uptake in batch experiments do not explain the nutrient consumption by the same microbes in flow experiments. We propose a simple extension of classical kinetics to account for the self-limiting consumption of nutrient observed in our experiments, and we outline a modeling approach based on architecture and behavior of biofilms. Such a model would account for the changing trend of nutrient consumption by bacteria with the increasing biomass and the onset of biofilm formation. However no existing model can explain the microbial preference for growth in high permeability regions, nor is there any obvious extension of the model for this observation. An attractive conjecture is that quorum sensing is involved in the heterogeneous bead packs.« less
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 < 0.001) when using a linear mixed-effect models with random slopes and a first order continuous autoregressive error term. There was substantial heterogeneity in both the intercept (p < 0.001) and slopes (p < 0.001) of the individual growth trajectories. We also identified important serial correlation within the structure of the data (ρ = 0.66; 95 % CI 0.64 to 0.68; p < 0.001), which we 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. 19,598, respectively). While the regression parameters are more complex to interpret in the former, we argue that inference for any problem depends more on the estimated curve or differences in curves rather than the coefficients. Moreover, use of cubic regression splines provides biological meaningful growth velocity and acceleration curves despite increased complexity in coefficient interpretation. Through this stepwise approach, we provide a set of tools to model longitudinal childhood data for non-statisticians using linear mixed-effect models.
Online automatic tuning and control for fed-batch cultivation
van Straten, Gerrit; van der Pol, Leo A.; van Boxtel, Anton J. B.
2007-01-01
Performance of controllers applied in biotechnological production is often below expectation. Online automatic tuning has the capability to improve control performance by adjusting control parameters. This work presents automatic tuning approaches for model reference specific growth rate control during fed-batch cultivation. The approaches are direct methods that use the error between observed specific growth rate and its set point; systematic perturbations of the cultivation are not necessary. Two automatic tuning methods proved to be efficient, in which the adaptation rate is based on a combination of the error, squared error and integral error. These methods are relatively simple and robust against disturbances, parameter uncertainties, and initialization errors. Application of the specific growth rate controller yields a stable system. The controller and automatic tuning methods are qualified by simulations and laboratory experiments with Bordetella pertussis. PMID:18157554
NASA Astrophysics Data System (ADS)
Gadag, Shiva P.; Patra, Susant
2000-12-01
Solder joint interconnects are mechanical means of structural support for bridging the various electronic components and providing electrical contacts and a thermal path for heat dissipation. The functionality of the electronic device often relies on the structural integrity of the solder. The dimensional stability of solder joints is numerically predicted based on their mechanical properties. Algorithms to model the kinetics of dissolution and subsequent growth of intermetallic from the complete knowledge of a single history of time-temperature-reflow profile, by considering equivalent isothermal time intervals, have been developed. The information for dissolution is derived during the heating cycle of reflow and for the growth process from cooling curve of reflow profile. A simple and quick analysis tool to derive tensile stress-strain maps as a function of the reflow temperature of solder and strain rate has been developed by numerical program. The tensile properties are used in modeling thermal strain, thermal fatigue and to predict the overall fatigue life of solder joints. The numerical analysis of the tensile properties as affected by their composition and rate of testing, has been compiled in this paper. A numerical model using constitutive equation has been developed to evaluate the interfacial fatigue crack growth rate. The model can assess the effect of cooling rate, which depends on the level of strain energy release rate. Increasing cooling rate from normalizing to water-quenching, enhanced the fatigue resistance to interfacial crack growth by up to 50% at low strain energy release rate. The increased cooling rates enhanced the fatigue crack growth resistance by surface roughening at the interface of solder joint. This paper highlights salient features of process modeling. Interfacial intermetallic microstructure is affected by cooling rate and thereby affects the mechanical properties.
Organelle Size Scaling of the Budding Yeast Vacuole by Relative Growth and Inheritance.
Chan, Yee-Hung M; Reyes, Lorena; Sohail, Saba M; Tran, Nancy K; Marshall, Wallace F
2016-05-09
It has long been noted that larger animals have larger organs compared to smaller animals of the same species, a phenomenon termed scaling [1]. Julian Huxley proposed an appealingly simple model of "relative growth"-in which an organ and the whole body grow with their own intrinsic rates [2]-that was invoked to explain scaling in organs from fiddler crab claws to human brains. Because organ size is regulated by complex, unpredictable pathways [3], it remains unclear whether scaling requires feedback mechanisms to regulate organ growth in response to organ or body size. The molecular pathways governing organelle biogenesis are simpler than organogenesis, and therefore organelle size scaling in the cell provides a more tractable case for testing Huxley's model. We ask the question: is it possible for organelle size scaling to arise if organelle growth is independent of organelle or cell size? Using the yeast vacuole as a model, we tested whether mutants defective in vacuole inheritance, vac8Δ and vac17Δ, tune vacuole biogenesis in response to perturbations in vacuole size. In vac8Δ/vac17Δ, vacuole scaling increases with the replicative age of the cell. Furthermore, vac8Δ/vac17Δ cells continued generating vacuole at roughly constant rates even when they had significantly larger vacuoles compared to wild-type. With support from computational modeling, these results suggest there is no feedback between vacuole biogenesis rates and vacuole or cell size. Rather, size scaling is determined by the relative growth rates of the vacuole and the cell, thus representing a cellular version of Huxley's model. Copyright © 2016 Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Hufnagl, Marc; Peck, Myron A.; Nash, Richard D. M.; Dickey-Collas, Mark
2015-11-01
Unraveling the key processes affecting marine fish recruitment will ultimately require a combination of field, laboratory and modelling studies. We combined analyzes of long-term (30-year) field data on larval fish abundance, distribution and length, and biophysical model simulations of different levels of complexity to identify processes impacting the survival and growth of autumn- and winter-spawned Atlantic herring (Clupea harengus) larvae. Field survey data revealed interannual changes in intensity of utilization of the five major spawning grounds (Orkney/Shetland, Buchan, Banks north, Banks south, and Downs) as well as spatio-temporal variability in the length and abundance of overwintered larvae. The mean length of larvae captured in post-winter surveys was negatively correlated to the proportion of larvae from the southern-most (Downs) winter-spawning component. Furthermore, the mean length of larvae originating from all spawning components has decreased since 1990 suggesting ecosystem-wide changes impacting larval growth potential, most likely due to changes in prey fields. A simple biophysical model assuming temperature-dependent growth and constant mortality underestimated larval growth rates suggesting that larval mortality rates steeply declined with increasing size and/or age during winter as no match with field data could be obtained. In contrast better agreement was found between observed and modelled post-winter abundance for larvae originating from four spawning components when a more complex, physiological-based foraging and growth model was employed using a suite of potential prey field and size-based mortality scenarios. Nonetheless, agreement between field and model-derived estimates was poor for larvae originating from the winter-spawned Downs component. In North Sea herring, the dominant processes impacting larval growth and survival appear to have shifted in time and space highlighting how environmental forcing, ecosystem state and other factors can form a Gordian knot of marine fish recruitment processes. We highlight gaps in process knowledge and recommend specific field, laboratory and modelling studies which, in our opinion, are most likely to unravel the dominant processes and advance predictive capacity of the environmental regulation of recruitment in autumn and winter-spawned fishes in temperate areas such as herring in the North Sea.
Niklas, Karl J
2006-02-01
Life forms as diverse as unicellular algae, zooplankton, vascular plants, and mammals appear to obey quarter-power scaling rules. Among the most famous of these rules is Kleiber's (i.e. basal metabolic rates scale as the three-quarters power of body mass), which has a botanical analogue (i.e. annual plant growth rates scale as the three-quarters power of total body mass). Numerous theories have tried to explain why these rules exist, but each has been heavily criticized either on conceptual or empirical grounds. N,P-STOICHIOMETRY: Recent models predicting growth rates on the basis of how total cell, tissue, or organism nitrogen and phosphorus are allocated, respectively, to protein and rRNA contents may provide the answer, particularly in light of the observation that annual plant growth rates scale linearly with respect to standing leaf mass and that total leaf mass scales isometrically with respect to nitrogen but as the three-quarters power of leaf phosphorus. For example, when these relationships are juxtaposed with other allometric trends, a simple N,P-stoichiometric model successfully predicts the relative growth rates of 131 diverse C3 and C4 species. The melding of allometric and N,P-stoichiometric theoretical insights provides a robust modelling approach that conceptually links the subcellular 'machinery' of protein/ribosomal metabolism to observed growth rates of uni- and multicellular organisms. Because the operation of this 'machinery' is basic to the biology of all life forms, its allometry may provide a mechanistic explanation for the apparent ubiquity of quarter-power scaling rules.
Kelly, B.G.; Loether, A.; DiChiara, A. D.; ...
2017-04-20
An in-situ optical pump/x-ray probe technique has been used to study the size dependent lattice parameter of Pt nanoparticles subjected to picosecond duration optical laser pulses. The as-prepared Pt nanoparticles exhibited a contracted lattice parameter consistent with the response of an isolated elastic sphere to a compressive surface stress. During photo-thermally induced sintering and grain growth, however, the Pt lattice parameter did not evolve with the inverse particle size dependence predicted by simple surface stress models. Lastly, the observed behavior could be attributed to the combined effects of a compressive surface/interface stress and a tensile stress arising from intergranular material.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kelly, B.G.; Loether, A.; DiChiara, A. D.
An in-situ optical pump/x-ray probe technique has been used to study the size dependent lattice parameter of Pt nanoparticles subjected to picosecond duration optical laser pulses. The as-prepared Pt nanoparticles exhibited a contracted lattice parameter consistent with the response of an isolated elastic sphere to a compressive surface stress. During photo-thermally induced sintering and grain growth, however, the Pt lattice parameter did not evolve with the inverse particle size dependence predicted by simple surface stress models. Lastly, the observed behavior could be attributed to the combined effects of a compressive surface/interface stress and a tensile stress arising from intergranular material.
Noack, Stephan; Voges, Raphael; Gätgens, Jochem; Wiechert, Wolfgang
2017-09-20
Corynebacterium glutamicum serves as important production host for small molecular compounds that are derived from precursor molecules of the central carbon metabolism. It is therefore a well-studied model organism of industrial biotechnology. However, a deeper understanding of the regulatory principles underlying the synthesis of central metabolic enzymes under different environmental conditions as well as its impact on cell growth is still missing. We studied enzyme abundances in C. glutamicum in response to growth on: (i) one limiting carbon source by sampling chemostat and fed-batch cultivations and (ii) changing carbon sources provided in excess by sampling batch cultivations. The targeted quantification of 20 central metabolic enzymes by isotope dilution mass spectrometry revealed that cells maintain stable enzyme concentrations when grown on d-glucose as single carbon and energy source and, most importantly, independent of its availability. By contrast, switching from d-glucose to d-fructose, d-mannose, d-arabitol, acetate, l-lactate or l-glutamate results in highly specific enzyme regulation patterns that can partly be explained by the activity of known transcriptional regulators. Based on these experimental results we propose a simple framework for modeling cell population growth as a nested function of nutrient supply and intracellular enzyme abundances. In summary, our study extends the basis for the formulation of predictive mechanistic models of bacterial growth, applicable in industrial bioprocess development. Copyright © 2017 Elsevier B.V. All rights reserved.
Ford, R M; Lauffenburger, D A
1992-05-01
An individual cell-based mathematical model of Rivero et al. provides a framework for determining values of the chemotactic sensitivity coefficient chi 0, an intrinsic cell population parameter that characterizes the chemotactic response of bacterial populations. This coefficient can theoretically relate the swimming behavior of individual cells to the resulting migration of a bacterial population. When this model is applied to the commonly used capillary assay, an approximate solution can be obtained for a particular range of chemotactic strengths yielding a very simple analytical expression for estimating the value of chi 0, [formula: see text] from measurements of cell accumulation in the capillary, N, when attractant uptake is negligible. A0 and A infinity are the dimensionless attractant concentrations initially present at the mouth of the capillary and far into the capillary, respectively, which are scaled by Kd, the effective dissociation constant for receptor-attractant binding. D is the attractant diffusivity, and mu is the cell random motility coefficient. NRM is the cell accumulation in the capillary in the absence of an attractant gradient, from which mu can be determined independently as mu = (pi/4t)(NRM/pi r2bc)2, with r the capillary tube radius and bc the bacterial density initially in the chamber. When attractant uptake is significant, a slightly more involved procedure requiring a simple numerical integration becomes necessary. As an example, we apply this approach to quantitatively characterize, in terms of the chemotactic sensitivity coefficient chi 0, data from Terracciano indicating enhanced chemotactic responses of Escherichia coli to galactose when cultured under growth-limiting galactose levels in a chemostat.
Bagnara, Davide; Kaufman, Matthew S.; Calissano, Carlo; Marsilio, Sonia; Patten, Piers E. M.; Simone, Rita; Chum, Philip; Yan, Xiao-Jie; Allen, Steven L.; Kolitz, Jonathan E.; Baskar, Sivasubramanian; Rader, Christoph; Mellstedt, Hakan; Rabbani, Hodjattallah; Lee, Annette; Gregersen, Peter K.; Rai, Kanti R.
2011-01-01
Chronic lymphocytic leukemia (CLL) is an incurable adult disease of unknown etiology. Understanding the biology of CLL cells, particularly cell maturation and growth in vivo, has been impeded by lack of a reproducible adoptive transfer model. We report a simple, reproducible system in which primary CLL cells proliferate in nonobese diabetes/severe combined immunodeficiency/γcnull mice under the influence of activated CLL-derived T lymphocytes. By cotransferring autologous T lymphocytes, activated in vivo by alloantigens, the survival and growth of primary CFSE-labeled CLL cells in vivo is achieved and quantified. Using this approach, we have identified key roles for CD4+ T cells in CLL expansion, a direct link between CD38 expression by leukemic B cells and their activation, and support for CLL cells preferentially proliferating in secondary lymphoid tissues. The model should simplify analyzing kinetics of CLL cells in vivo, deciphering involvement of nonleukemic elements and nongenetic factors promoting CLL cell growth, identifying and characterizing potential leukemic stem cells, and permitting preclinical studies of novel therapeutics. Because autologous activated T lymphocytes are 2-edged swords, generating unwanted graph-versus-host and possibly autologous antitumor reactions, the model may also facilitate analyses of T-cell populations involved in immune surveillance relevant to hematopoietic transplantation and tumor cytoxicity. PMID:21385850
NASA Astrophysics Data System (ADS)
Tsujimoto, Kumiko; Homma, Koki; Koike, Toshio; Ohta, Tetsu
2013-04-01
A coupled model of a distributed hydrological model and a rice growth model was developed in this study. The distributed hydrological model used in this study is the Water and Energy Budget-based Distributed Hydrological Model (WEB-DHM) developed by Wang et al. (2009). This model includes a modified SiB2 (Simple Biosphere Model, Sellers et al., 1996) and the Geomorphology-Based Hydrological Model (GBHM) and thus it can physically calculate both water and energy fluxes. The rice growth model used in this study is the Simulation Model for Rice-Weather relations (SIMRIW) - rainfed developed by Homma et al. (2009). This is an updated version of the original SIMRIW (Horie et al., 1987) and can calculate rice growth by considering the yield reduction due to water stress. The purpose of the coupling is the integration of hydrology and crop science to develop a tool to support decision making 1) for determining the necessary agricultural water resources and 2) for allocating limited water resources to various sectors. The efficient water use and optimal water allocation in the agricultural sector are necessary to balance supply and demand of limited water resources. In addition, variations in available soil moisture are the main reasons of variations in rice yield. In our model, soil moisture and the Leaf Area Index (LAI) are calculated inside SIMRIW-rainfed so that these variables can be simulated dynamically and more precisely based on the rice than the more general calculations is the original WEB-DHM. At the same time by coupling SIMRIW-rainfed with WEB-DHM, lateral flow of soil water, increases in soil moisture and reduction of river discharge due to the irrigation, and its effects on the rice growth can be calculated. Agricultural information such as planting date, rice cultivar, fertilization amount are given in a fully distributed manner. The coupled model was validated using LAI and soil moisture in a small basin in western Cambodia (Sangker River Basin). This basin is mostly rainfed paddy so that irrigation scheme was firstly switched off. Several simulations with varying irrigation scheme were performed to determine the optimal irrigation schedule in this basin.
NASA Astrophysics Data System (ADS)
Kumari, S.; Sharma, P.; Srivastava, A.; Rastogi, D.; Sehgal, V. K.; Dhakar, R.; Roy, S. B.
2017-12-01
Vegetation dynamics and surface meteorology are tightly coupled through the exchange of momentum, moisture and heat between the land surface and the atmosphere. In this study, we use a recently developed coupled atmosphere-crop growth dynamics model to study these exchanges and their effects in a spring wheat cropland in northern India. In particular, we investigate the role of irrigation in controlling crop growth rates, surface meteorology, and sensible and latent heat fluxes. The model is developed by implementing a crop growth module based on the Simple and Universal Crop growth Simulator (SUCROS) model in the Weather Research Forecasting (WRF) mesoscale atmospheric model. The crop module calculates photosynthesis rates, carbon assimilation, and biomass partitioning as a function of environmental factors and crop development stage. The leaf area index (LAI) and root depth calculated by the crop module is then fed to the Noah-MP land module of WRF to calculate land-atmosphere fluxes. The crop model is calibrated using data from an experimental spring wheat crop site in the Indian Agriculture Research Institute. The coupled model is capable of simulating the observed spring wheat phenology. Irrigation is simulated by changing the soil moisture levels from 50% - 100% of field capacity. Results show that the yield first increases with increasing soil moisture and then starts decreasing as we further increase the soil moisture. Yield attains its maximum value with soil moisture at the level of 60% water of FC. At this level, high LAI values lead to a decrease in the Bowen Ratio because more energy is transferred to the atmosphere as latent heat rather than sensible heat resulting in a cooling effect on near-surface air temperatures. Apart from improving simulation of land-atmosphere interactions, this coupled modeling approach can form the basis for the seamless crop yield and seasonal scale weather outlook prediction system.
Structure of S-shaped growth in innovation diffusion
NASA Astrophysics Data System (ADS)
Shimogawa, Shinsuke; Shinno, Miyuki; Saito, Hiroshi
2012-05-01
A basic question on innovation diffusion is why the growth curve of the adopter population in a large society is often S shaped. From macroscopic, microscopic, and mesoscopic viewpoints, the growth of the adopter population is observed as the growth curve, individual adoptions, and differences among individual adoptions, respectively. The S shape can be explained if an empirical model of the growth curve can be deduced from models of microscopic and mesoscopic structures. However, even the structure of growth curve has not been revealed yet because long-term extrapolations by proposed models of S-shaped curves are unstable and it has been very difficult to predict the long-term growth and final adopter population. This paper studies the S-shaped growth from the viewpoint of social regularities. Simple methods to analyze power laws enable us to extract the structure of the growth curve directly from the growth data of recent basic telecommunication services. This empirical model of growth curve is singular at the inflection point and a logarithmic function of time after this point, which explains the unstable extrapolations obtained using previously proposed models and the difficulty in predicting the final adopter population. Because the empirical S curve can be expressed in terms of two power laws of the regularity found in social performances of individuals, we propose the hypothesis that the S shape represents the heterogeneity of the adopter population, and the heterogeneity parameter is distributed under the regularity in social performances of individuals. This hypothesis is so powerful as to yield models of microscopic and mesoscopic structures. In the microscopic model, each potential adopter adopts the innovation when the information accumulated by the learning about the innovation exceeds a threshold. The accumulation rate of information is heterogeneous among the adopter population, whereas the threshold is a constant, which is the opposite of previously proposed models. In the mesoscopic model, flows of innovation information incoming to individuals are organized as dimorphic and partially clustered. These microscopic and mesoscopic models yield the empirical model of the S curve and explain the S shape as representing the regularities of information flows generated through a social self-organization. To demonstrate the validity and importance of the hypothesis, the models of three level structures are applied to reveal the mechanism determining and differentiating diffusion speeds. The empirical model of S curves implies that the coefficient of variation of the flow rates determines the diffusion speed for later adopters. Based on this property, a model describing the inside of information flow clusters can be given, which provides a formula interconnecting the diffusion speed, cluster populations, and a network topological parameter of the flow clusters. For two recent basic telecommunication services in Japan, the formula represents the variety of speeds in different areas and enables us to explain speed gaps between urban and rural areas and between the two services. Furthermore, the formula provides a method to estimate the final adopter population.
Controlled recovery of phylogenetic communities from an evolutionary model using a network approach
NASA Astrophysics Data System (ADS)
Sousa, Arthur M. Y. R.; Vieira, André P.; Prado, Carmen P. C.; Andrade, Roberto F. S.
2016-04-01
This works reports the use of a complex network approach to produce a phylogenetic classification tree of a simple evolutionary model. This approach has already been used to treat proteomic data of actual extant organisms, but an investigation of its reliability to retrieve a traceable evolutionary history is missing. The used evolutionary model includes key ingredients for the emergence of groups of related organisms by differentiation through random mutations and population growth, but purposefully omits other realistic ingredients that are not strictly necessary to originate an evolutionary history. This choice causes the model to depend only on a small set of parameters, controlling the mutation probability and the population of different species. Our results indicate that for a set of parameter values, the phylogenetic classification produced by the used framework reproduces the actual evolutionary history with a very high average degree of accuracy. This includes parameter values where the species originated by the evolutionary dynamics have modular structures. In the more general context of community identification in complex networks, our model offers a simple setting for evaluating the effects, on the efficiency of community formation and identification, of the underlying dynamics generating the network itself.
Efficient embedding of complex networks to hyperbolic space via their Laplacian
Alanis-Lobato, Gregorio; Mier, Pablo; Andrade-Navarro, Miguel A.
2016-01-01
The different factors involved in the growth process of complex networks imprint valuable information in their observable topologies. How to exploit this information to accurately predict structural network changes is the subject of active research. A recent model of network growth sustains that the emergence of properties common to most complex systems is the result of certain trade-offs between node birth-time and similarity. This model has a geometric interpretation in hyperbolic space, where distances between nodes abstract this optimisation process. Current methods for network hyperbolic embedding search for node coordinates that maximise the likelihood that the network was produced by the afore-mentioned model. Here, a different strategy is followed in the form of the Laplacian-based Network Embedding, a simple yet accurate, efficient and data driven manifold learning approach, which allows for the quick geometric analysis of big networks. Comparisons against existing embedding and prediction techniques highlight its applicability to network evolution and link prediction. PMID:27445157
Efficient embedding of complex networks to hyperbolic space via their Laplacian
NASA Astrophysics Data System (ADS)
Alanis-Lobato, Gregorio; Mier, Pablo; Andrade-Navarro, Miguel A.
2016-07-01
The different factors involved in the growth process of complex networks imprint valuable information in their observable topologies. How to exploit this information to accurately predict structural network changes is the subject of active research. A recent model of network growth sustains that the emergence of properties common to most complex systems is the result of certain trade-offs between node birth-time and similarity. This model has a geometric interpretation in hyperbolic space, where distances between nodes abstract this optimisation process. Current methods for network hyperbolic embedding search for node coordinates that maximise the likelihood that the network was produced by the afore-mentioned model. Here, a different strategy is followed in the form of the Laplacian-based Network Embedding, a simple yet accurate, efficient and data driven manifold learning approach, which allows for the quick geometric analysis of big networks. Comparisons against existing embedding and prediction techniques highlight its applicability to network evolution and link prediction.
Adaptation, Growth, and Resilience in Biological Distribution Networks
NASA Astrophysics Data System (ADS)
Ronellenfitsch, Henrik; Katifori, Eleni
Highly optimized complex transport networks serve crucial functions in many man-made and natural systems such as power grids and plant or animal vasculature. Often, the relevant optimization functional is nonconvex and characterized by many local extrema. In general, finding the global, or nearly global optimum is difficult. In biological systems, it is believed that such an optimal state is slowly achieved through natural selection. However, general coarse grained models for flow networks with local positive feedback rules for the vessel conductivity typically get trapped in low efficiency, local minima. We show how the growth of the underlying tissue, coupled to the dynamical equations for network development, can drive the system to a dramatically improved optimal state. This general model provides a surprisingly simple explanation for the appearance of highly optimized transport networks in biology such as plant and animal vasculature. In addition, we show how the incorporation of spatially collective fluctuating sources yields a minimal model of realistic reticulation in distribution networks and thus resilience against damage.
NASA Technical Reports Server (NTRS)
Grugel, Richard N,; Tewari, Surendra; Rajamure, R. S.; Erdman, Robert; Poirier, David
2012-01-01
Primary dendrite arm spacings of Al-7 wt% Si alloy directionally solidified in low gravity environment of space (MICAST-6 and MICAST-7: Thermal gradient approx. 19 to 26 K/cm, Growth speeds varying from 5 to 50 microns/s show good agreement with the Hunt-Lu model. Primary dendrite trunk diameters of the ISS processed samples show a good fit with a simple analytical model based on Kirkwood s approach, proposed here. Natural convection, a) decreases primary dendrite arm spacing. b) appears to increase primary dendrite trunk diameter.
How high energy fluxes may affect Rayleigh–Taylor instability growth in young supernova remnants
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kuranz, Carolyn C.; Park, Hye -Sook; Huntington, Channing M.
Here, energy-transport effects can alter the structure that develops as a supernova evolves into a supernova remnant. The Rayleigh–Taylor instability is thought to produce structure at the interface between the stellar ejecta and the circumstellar matter, based on simple models and hydrodynamic simulations. Here we report experimental results from the National Ignition Facility to explore how large energy fluxes, which are present in supernovae, affect this structure. We observed a reduction in Rayleigh–Taylor growth. In analyzing the comparison with supernova SN1993J, a Type II supernova, we found that the energy fluxes produced by heat conduction appear to be larger thanmore » the radiative energy fluxes, and large enough to have dramatic consequences. No reported astrophysical simulations have included radiation and heat conduction self-consistently in modeling supernova remnants and these dynamics should be noted in the understanding of young supernova remnants.« less
The economics of bootstrapping space industries - Development of an analytic computer model
NASA Technical Reports Server (NTRS)
Goldberg, A. H.; Criswell, D. R.
1982-01-01
A simple economic model of 'bootstrapping' industrial growth in space and on the Moon is presented. An initial space manufacturing facility (SMF) is assumed to consume lunar materials to enlarge the productive capacity in space. After reaching a predetermined throughput, the enlarged SMF is devoted to products which generate revenue continuously in proportion to the accumulated output mass (such as space solar power stations). Present discounted value and physical estimates for the general factors of production (transport, capital efficiency, labor, etc.) are combined to explore optimum growth in terms of maximized discounted revenues. It is found that 'bootstrapping' reduces the fractional cost to a space industry of transport off-Earth, permits more efficient use of a given transport fleet. It is concluded that more attention should be given to structuring 'bootstrapping' scenarios in which 'learning while doing' can be more fully incorporated in program analysis.
How high energy fluxes may affect Rayleigh–Taylor instability growth in young supernova remnants
Kuranz, Carolyn C.; Park, Hye -Sook; Huntington, Channing M.; ...
2018-04-19
Here, energy-transport effects can alter the structure that develops as a supernova evolves into a supernova remnant. The Rayleigh–Taylor instability is thought to produce structure at the interface between the stellar ejecta and the circumstellar matter, based on simple models and hydrodynamic simulations. Here we report experimental results from the National Ignition Facility to explore how large energy fluxes, which are present in supernovae, affect this structure. We observed a reduction in Rayleigh–Taylor growth. In analyzing the comparison with supernova SN1993J, a Type II supernova, we found that the energy fluxes produced by heat conduction appear to be larger thanmore » the radiative energy fluxes, and large enough to have dramatic consequences. No reported astrophysical simulations have included radiation and heat conduction self-consistently in modeling supernova remnants and these dynamics should be noted in the understanding of young supernova remnants.« less
Market penetration of energy supply technologies
NASA Astrophysics Data System (ADS)
Condap, R. J.
1980-03-01
Techniques to incorporate the concepts of profit-induced growth and risk aversion into policy-oriented optimization models of the domestic energy sector are examined. After reviewing the pertinent market penetration literature, simple mathematical programs in which the introduction of new energy technologies is constrained primarily by the reinvestment of profits are formulated. The main results involve the convergence behavior of technology production levels under various assumptions about the form of the energy demand function. Next, profitability growth constraints are embedded in a full-scale model of U.S. energy-economy interactions. A rapidly convergent algorithm is developed to utilize optimal shadow prices in the computation of profitability for individual technologies. Allowance is made for additional policy variables such as government funding and taxation. The result is an optimal deployment schedule for current and future energy technologies which is consistent with the sector's ability to finance capacity expansion.
Quasar evolution and the growth of black holes
NASA Technical Reports Server (NTRS)
Small, Todd A.; Blandford, Roger D.
1992-01-01
A 'minimalist' model of AGN evolution is analyzed that links the measured luminosity function to an elementary description of black hole accretion. The observed luminosity function of bright AGN is extrapolated and simple prescriptions for the growth and luminosity of black holes are introduced to infer quasar birth rates, mean fueling rates, and relict black hole distribution functions. It is deduced that the mean accretion rate scales as (M exp -1./5)(t exp -6.7) and that, for the most conservative model used, the number of relict black holes per decade declines only as M exp -0.4 for black hole masses between 3 x 10 exp 7 and 3 x 10 exp 9 solar masses. If all sufficiently massive galaxies pass through a quasar phase with asymptotic black hole mass a monotonic function of the galaxy mass, then it is possible to compare the space density of galaxies with estimated central masses to that of distant quasars.
Spatial variability of chlorophyll and nitrogen content of rice from hyperspectral imagery
NASA Astrophysics Data System (ADS)
Moharana, Shreedevi; Dutta, Subashisa
2016-12-01
Chlorophyll and nitrogen are the most essential parameters for paddy crop growth. Spectroradiometric measurements were collected at canopy level during critical growth period of rice. Chemical analysis was performed to quantify the total leaf content. By exploiting the ground based measurements, regression models were established for chlorophyll and nitrogen aimed indices with their corresponding crop growth variables. Vegetation index models were developed for mapping these parameters from Hyperion imagery in an agriculture system. It was inferred that the present Simple Ratio (SR) and Leaf Nitrogen Concentration (LNC) indices, which followed a linear and nonlinear relationship respectively, were completely different from published Tian et al. (2011). The nitrogen content varied widely from 1 to 4% and only 2 to 3% for paddy crop using present modified index models and Tian et al. (2011) respectively. The modified LNC index model performed better than the established Tian et al. (2011) model as far as estimated nitrogen content from Hyperion imagery was concerned. Furthermore, within the observed chlorophyll range obtained from the studied rice varieties grown in the rice agriculture system, the index models (LNC, OASVI, Gitelson, mSR and MTCI) performed well in the spatial distribution of rice chlorophyll content from Hyperion imagery. Spatial distribution of total chlorophyll content varied widely from 1.77 to 5.81 mg/g (LNC), 3.0 to 13 mg/g (OASVI), 0.5 to 10.43 mg/g (Gitelson), 2.18 to 10.61 mg/g (mSR) and 2.90 to 5.40 mg/g (MTCI). The spatial information of these parameters will help in proper nutrient management, yield forecasting, and will serve as inputs for crop growth and forecasting models for a precision rice agriculture system.
Tague, Christina L; McDowell, Nathan G; Allen, Craig D
2013-01-01
Climate-induced tree mortality is an increasing concern for forest managers around the world. We used a coupled hydrologic and ecosystem carbon cycling model to assess temperature and precipitation impacts on productivity and survival of ponderosa pine (Pinus ponderosa). Model predictions were evaluated using observations of productivity and survival for three ponderosa pine stands located across an 800 m elevation gradient in the southern Rocky Mountains, USA, during a 10-year period that ended in a severe drought and extensive tree mortality at the lowest elevation site. We demonstrate the utility of a relatively simple representation of declines in non-structural carbohydrate (NSC) as an approach for estimating patterns of ponderosa pine vulnerability to drought and the likelihood of survival along an elevation gradient. We assess the sensitivity of simulated net primary production, NSC storage dynamics, and mortality to site climate and soil characteristics as well as uncertainty in the allocation of carbon to the NSC pool. For a fairly wide set of assumptions, the model estimates captured elevational gradients and temporal patterns in growth and biomass. Model results that best predict mortality risk also yield productivity, leaf area, and biomass estimates that are qualitatively consistent with observations across the sites. Using this constrained set of parameters, we found that productivity and likelihood of survival were equally dependent on elevation-driven variation in temperature and precipitation. Our results demonstrate the potential for a coupled hydrology-ecosystem carbon cycling model that includes a simple model of NSC dynamics to predict drought-related mortality. Given that increases in temperature and in the frequency and severity of drought are predicted for a broad range of ponderosa pine and other western North America conifer forest habitats, the model potentially has broad utility for assessing ecosystem vulnerabilities.
Tague, Christina L.; McDowell, Nathan G.; Allen, Craig D.
2013-01-01
Climate-induced tree mortality is an increasing concern for forest managers around the world. We used a coupled hydrologic and ecosystem carbon cycling model to assess temperature and precipitation impacts on productivity and survival of ponderosa pine (Pinus ponderosa). Model predictions were evaluated using observations of productivity and survival for three ponderosa pine stands located across an 800 m elevation gradient in the southern Rocky Mountains, USA, during a 10-year period that ended in a severe drought and extensive tree mortality at the lowest elevation site. We demonstrate the utility of a relatively simple representation of declines in non-structural carbohydrate (NSC) as an approach for estimating patterns of ponderosa pine vulnerability to drought and the likelihood of survival along an elevation gradient. We assess the sensitivity of simulated net primary production, NSC storage dynamics, and mortality to site climate and soil characteristics as well as uncertainty in the allocation of carbon to the NSC pool. For a fairly wide set of assumptions, the model estimates captured elevational gradients and temporal patterns in growth and biomass. Model results that best predict mortality risk also yield productivity, leaf area, and biomass estimates that are qualitatively consistent with observations across the sites. Using this constrained set of parameters, we found that productivity and likelihood of survival were equally dependent on elevation-driven variation in temperature and precipitation. Our results demonstrate the potential for a coupled hydrology-ecosystem carbon cycling model that includes a simple model of NSC dynamics to predict drought-related mortality. Given that increases in temperature and in the frequency and severity of drought are predicted for a broad range of ponderosa pine and other western North America conifer forest habitats, the model potentially has broad utility for assessing ecosystem vulnerabilities.
Tague, Christina L.; McDowell, Nathan G.; Allen, Craig D.
2013-01-01
Climate-induced tree mortality is an increasing concern for forest managers around the world. We used a coupled hydrologic and ecosystem carbon cycling model to assess temperature and precipitation impacts on productivity and survival of ponderosa pine (Pinus ponderosa). Model predictions were evaluated using observations of productivity and survival for three ponderosa pine stands located across an 800 m elevation gradient in the southern Rocky Mountains, USA, during a 10-year period that ended in a severe drought and extensive tree mortality at the lowest elevation site. We demonstrate the utility of a relatively simple representation of declines in non-structural carbohydrate (NSC) as an approach for estimating patterns of ponderosa pine vulnerability to drought and the likelihood of survival along an elevation gradient. We assess the sensitivity of simulated net primary production, NSC storage dynamics, and mortality to site climate and soil characteristics as well as uncertainty in the allocation of carbon to the NSC pool. For a fairly wide set of assumptions, the model estimates captured elevational gradients and temporal patterns in growth and biomass. Model results that best predict mortality risk also yield productivity, leaf area, and biomass estimates that are qualitatively consistent with observations across the sites. Using this constrained set of parameters, we found that productivity and likelihood of survival were equally dependent on elevation-driven variation in temperature and precipitation. Our results demonstrate the potential for a coupled hydrology-ecosystem carbon cycling model that includes a simple model of NSC dynamics to predict drought-related mortality. Given that increases in temperature and in the frequency and severity of drought are predicted for a broad range of ponderosa pine and other western North America conifer forest habitats, the model potentially has broad utility for assessing ecosystem vulnerabilities. PMID:24282532
Finite-size effects on bacterial population expansion under controlled flow conditions
NASA Astrophysics Data System (ADS)
Tesser, Francesca; Zeegers, Jos C. H.; Clercx, Herman J. H.; Brunsveld, Luc; Toschi, Federico
2017-03-01
The expansion of biological species in natural environments is usually described as the combined effect of individual spatial dispersal and growth. In the case of aquatic ecosystems flow transport can also be extremely relevant as an extra, advection induced, dispersal factor. We designed and assembled a dedicated microfluidic device to control and quantify the expansion of populations of E. coli bacteria under both co-flowing and counter-flowing conditions, measuring the front speed at varying intensity of the imposed flow. At variance with respect to the case of classic advective-reactive-diffusive chemical fronts, we measure that almost irrespective of the counter-flow velocity, the front speed remains finite at a constant positive value. A simple model incorporating growth, dispersion and drift on finite-size hard beads allows to explain this finding as due to a finite volume effect of the bacteria. This indicates that models based on the Fisher-Kolmogorov-Petrovsky-Piscounov equation (FKPP) that ignore the finite size of organisms may be inaccurate to describe the physics of spatial growth dynamics of bacteria.
Deadly competition between sibling bacterial colonies
Be'er, Avraham; Zhang, H. P.; Florin, E.-L.; Payne, Shelley M.; Ben-Jacob, Eshel; Swinney, Harry L.
2009-01-01
Bacteria can secrete a wide array of antibacterial compounds when competing with other bacteria for the same resources. Some of these compounds, such as bacteriocins, can affect bacteria of similar or closely related strains. In some cases, these secretions have been found to kill sibling cells that belong to the same colony. Here, we present experimental observations of competition between 2 sibling colonies of Paenibacillus dendritiformis grown on a low-nutrient agar gel. We find that neighboring colonies (growing from droplet inoculation) mutually inhibit growth through secretions that become lethal if the level exceeds a well-defined threshold. In contrast, within a single colony developing from a droplet inoculation, no growth inhibition is observed. However, growth inhibition and cell death are observed if material extracted from the agar between 2 growing colonies is introduced outside a growing single colony. To interpret the observations, we devised a simple mathematical model for the secretion of an antibacterial compound. Simulations of this model illustrate how secretions from neighboring colonies can be deadly, whereas secretions from a single colony growing from a droplet are not. PMID:19129489
NASA Astrophysics Data System (ADS)
Costa, José C. S.; Coelho, Ana F. S. M. G.; Mendes, Adélio; Santos, Luís M. N. B. F.
2018-01-01
Nanoscience and technology has generated an important area of research in the field of properties and functionality of ionic liquids (ILs) based materials and their thin films. This work explores the deposition process of ILs droplets as precursors for the fabrication of thin films, by means of physical vapor deposition (PVD). It was found that the deposition (by PVD on glass, indium tin oxide, graphene/nickel and gold-coated quartz crystal surfaces) of imidazolium [C4mim][NTf2] and pyrrolidinium [C4C1Pyrr][NTf2] based ILs generates micro/nanodroplets with a shape, size distribution and surface coverage that could be controlled by the evaporation flow rate and deposition time. No indication of the formation of a wetting-layer prior to the island growth was found. Based on the time-dependent morphological analysis of the micro/nanodroplets, a simple model for the description of the nucleation process and growth of ILs droplets is presented. The proposed model is based on three main steps: minimum free area to promote nucleation; first order coalescence; second order coalescence.
Changes of scaling relationships in an evolving population: The example of "sedimentary" stylolites
NASA Astrophysics Data System (ADS)
Peacock, D. C. P.; Korneva, I.; Nixon, C. W.; Rotevatn, A.
2017-03-01
Bed-parallel (;sedimentary;) stylolites are used as an example of a population that evolves by the addition of new components, their growth and their merger. It is shown that this style of growth controls the changes in the scaling relationships of the population. Stylolites tend to evolve in carbonate rocks through time, for example by compaction during progressive burial. The evolution of a population of stylolites, and their likely effects on porosity, are demonstrated using simple numerical models. Starting with a power-law distribution, the adding of new stylolites, the increase in their amplitudes and their merger decrease the slope of magnitude versus cumulative frequency of the population. The population changes to a non-power-law distribution as smaller stylolites merge to form larger stylolites. The results suggest that other populations can be forward- or backward-modelled, such as fault lengths, which also evolve by the addition of components, their growth and merger. Consideration of the ways in which populations change improves understanding of scaling relationships and vice versa, and would assist in the management of geofluid reservoirs.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Höcker, Jan; Duchoň, Tomáš; Veltruská, Kateřina
2016-01-06
We present a novel and simple method for the preparation of a well-defined CeO 2(100) model system on Cu(111) based on the adjustment of the Ce/O ratio during growth. The method yields micrometer-sized, several nanometers high, single-phase CeO 2(100) islands with controllable size and surface termination that can be benchmarked against the known (111) nanostructured islands on Cu(111). We also demonstrate the ability to adjust the Ce to O stoichiometry from CeO 2(100) (100% Ce 4+) to c-Ce 2O 3(100) (100% Ce 3+), which can be readily recognized by characteristic surface reconstructions observed by low-energy electron diffraction. Finally, the discoverymore » of the highly stable CeO x(100) phase on a hexagonally close packed metal surface represents an unexpected growth mechanism of ceria on Cu(111), and it provides novel opportunities to prepare more elaborate models, benchmark surface chemical reactivity, and thus gain valuable insights into the redox chemistry of ceria in catalytic processes.« less
Baeumer, Christoph; Xu, Chencheng; Gunkel, Felix; Raab, Nicolas; Heinen, Ronja Anika; Koehl, Annemarie; Dittmann, Regina
2015-01-01
Emerging electrical and magnetic properties of oxide interfaces are often dominated by the termination and stoichiometry of substrates and thin films, which depend critically on the growth conditions. Currently, these quantities have to be measured separately with different sophisticated techniques. This report will demonstrate that the analysis of angle dependent X-ray photoelectron intensity ratios provides a unique tool to determine both termination and stoichiometry simultaneously in a straightforward experiment. Fitting the experimental angle dependence with a simple analytical model directly yields both values. The model is calibrated through the determination of the termination of SrTiO3 single crystals after systematic pulsed laser deposition of sub-monolayer thin films of SrO. We then use the model to demonstrate that during homoepitaxial SrTiO3 growth, excess Sr cations are consumed in a self-organized surface termination conversion before cation defects are incorporated into the film. We show that this termination conversion results in insulating properties of interfaces between polar perovskites and SrTiO3 thin films. These insights about oxide thin film growth can be utilized for interface engineering of oxide heterostructures. In particular, they suggest a recipe for obtaining two-dimensional electron gases at thin film interfaces: SrTiO3 should be deposited slightly Ti-rich to conserve the TiO2-termination. PMID:26189436
An eco-hydrologic model of malaria outbreaks
NASA Astrophysics Data System (ADS)
Montosi, E.; Manzoni, S.; Porporato, A.; Montanari, A.
2012-03-01
Malaria is a geographically widespread infectious disease that is well known to be affected by climate variability at both seasonal and interannual timescales. In an effort to identify climatic factors that impact malaria dynamics, there has been considerable research focused on the development of appropriate disease models for malaria transmission and their consideration alongside climatic datasets. These analyses have focused largely on variation in temperature and rainfall as direct climatic drivers of malaria dynamics. Here, we further these efforts by considering additionally the role that soil water content may play in driving malaria incidence. Specifically, we hypothesize that hydro-climatic variability should be an important factor in controlling the availability of mosquito habitats, thereby governing mosquito growth rates. To test this hypothesis, we reduce a nonlinear eco-hydrologic model to a simple linear model through a series of consecutive assumptions and apply this model to malaria incidence data from three South African provinces. Despite the assumptions made in the reduction of the model, we show that soil water content can account for a significant portion of malaria's case variability beyond its seasonal patterns, whereas neither temperature nor rainfall alone can do so. Future work should therefore consider soil water content as a simple and computable variable for incorporation into climate-driven disease models of malaria and other vector-borne infectious diseases.
An ecohydrological model of malaria outbreaks
NASA Astrophysics Data System (ADS)
Montosi, E.; Manzoni, S.; Porporato, A.; Montanari, A.
2012-08-01
Malaria is a geographically widespread infectious disease that is well known to be affected by climate variability at both seasonal and interannual timescales. In an effort to identify climatic factors that impact malaria dynamics, there has been considerable research focused on the development of appropriate disease models for malaria transmission driven by climatic time series. These analyses have focused largely on variation in temperature and rainfall as direct climatic drivers of malaria dynamics. Here, we further these efforts by considering additionally the role that soil water content may play in driving malaria incidence. Specifically, we hypothesize that hydro-climatic variability should be an important factor in controlling the availability of mosquito habitats, thereby governing mosquito growth rates. To test this hypothesis, we reduce a nonlinear ecohydrological model to a simple linear model through a series of consecutive assumptions and apply this model to malaria incidence data from three South African provinces. Despite the assumptions made in the reduction of the model, we show that soil water content can account for a significant portion of malaria's case variability beyond its seasonal patterns, whereas neither temperature nor rainfall alone can do so. Future work should therefore consider soil water content as a simple and computable variable for incorporation into climate-driven disease models of malaria and other vector-borne infectious diseases.
A new method for evaluating forest thinning: growth dominance in managed Pinus resinosa stands
John B. Bradford; Anthony W. D' Amato; Brian J. Palik; Shawn Fraver
2010-01-01
Growth dominance is a relatively new, simple, quantitative metric of within-stand individual tree growth patterns, and is defined as positive when larger trees in the stand display proportionally greater growth than smaller trees, and negative when smaller trees display proportionally greater growth than larger trees. We examined long-term silvicultural experiments in...
Evaluating growth performance of young stands
A. L. Roe; R. E. Benson
1966-01-01
A simple procedure for evaluating the diameter growth of young stands in relation to potential growth is described. A comparison technique is developed which contrasts relative diameter of crop trees to the relative diameter growth of the last decade to show the condition and trend of growth in the stand. The method is objective, easy to use, and has several...
Quantum Entanglement Growth under Random Unitary Dynamics
DOE Office of Scientific and Technical Information (OSTI.GOV)
Nahum, Adam; Ruhman, Jonathan; Vijay, Sagar
Characterizing how entanglement grows with time in a many-body system, for example, after a quantum quench, is a key problem in nonequilibrium quantum physics. We study this problem for the case of random unitary dynamics, representing either Hamiltonian evolution with time-dependent noise or evolution by a random quantum circuit. Our results reveal a universal structure behind noisy entanglement growth, and also provide simple new heuristics for the “entanglement tsunami” in Hamiltonian systems without noise. In 1D, we show that noise causes the entanglement entropy across a cut to grow according to the celebrated Kardar-Parisi-Zhang (KPZ) equation. The mean entanglement growsmore » linearly in time, while fluctuations grow like (time) 1/3 and are spatially correlated over a distance ∝(time) 2/3. We derive KPZ universal behavior in three complementary ways, by mapping random entanglement growth to (i) a stochastic model of a growing surface, (ii) a “minimal cut” picture, reminiscent of the Ryu-Takayanagi formula in holography, and (iii) a hydrodynamic problem involving the dynamical spreading of operators. We demonstrate KPZ universality in 1D numerically using simulations of random unitary circuits. Importantly, the leading-order time dependence of the entropy is deterministic even in the presence of noise, allowing us to propose a simple coarse grained minimal cut picture for the entanglement growth of generic Hamiltonians, even without noise, in arbitrary dimensionality. We clarify the meaning of the “velocity” of entanglement growth in the 1D entanglement tsunami. We show that in higher dimensions, noisy entanglement evolution maps to the well-studied problem of pinning of a membrane or domain wall by disorder.« less
Quantum Entanglement Growth under Random Unitary Dynamics
Nahum, Adam; Ruhman, Jonathan; Vijay, Sagar; ...
2017-07-24
Characterizing how entanglement grows with time in a many-body system, for example, after a quantum quench, is a key problem in nonequilibrium quantum physics. We study this problem for the case of random unitary dynamics, representing either Hamiltonian evolution with time-dependent noise or evolution by a random quantum circuit. Our results reveal a universal structure behind noisy entanglement growth, and also provide simple new heuristics for the “entanglement tsunami” in Hamiltonian systems without noise. In 1D, we show that noise causes the entanglement entropy across a cut to grow according to the celebrated Kardar-Parisi-Zhang (KPZ) equation. The mean entanglement growsmore » linearly in time, while fluctuations grow like (time) 1/3 and are spatially correlated over a distance ∝(time) 2/3. We derive KPZ universal behavior in three complementary ways, by mapping random entanglement growth to (i) a stochastic model of a growing surface, (ii) a “minimal cut” picture, reminiscent of the Ryu-Takayanagi formula in holography, and (iii) a hydrodynamic problem involving the dynamical spreading of operators. We demonstrate KPZ universality in 1D numerically using simulations of random unitary circuits. Importantly, the leading-order time dependence of the entropy is deterministic even in the presence of noise, allowing us to propose a simple coarse grained minimal cut picture for the entanglement growth of generic Hamiltonians, even without noise, in arbitrary dimensionality. We clarify the meaning of the “velocity” of entanglement growth in the 1D entanglement tsunami. We show that in higher dimensions, noisy entanglement evolution maps to the well-studied problem of pinning of a membrane or domain wall by disorder.« less
NASA Astrophysics Data System (ADS)
Eugène, Sarah; Xue, Wei-Feng; Robert, Philippe; Doumic, Marie
2016-05-01
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.
Lee, G H; Hur, W; Bremmon, C E; Flickinger, M C
1996-03-20
A simulation was developed based on experimental data obtained in a 14-L reactor to predict the growth and L-lysine accumulation kinetics, and change in volume of a large-scale (250-m(3)) Bacillus methanolicus methanol-based process. Homoserine auxotrophs of B. methanolicus MGA3 are unique methylotrophs because of the ability to secrete lysine during aerobic growth and threonine starvation at 50 degrees C. Dissolved methanol (100 mM), pH, dissolved oxygen tension (0.063 atm), and threonine levels were controlled to obtain threonine-limited conditions and high-cell density (25 g dry cell weight/L) in a 14-L reactor. As a fed-batch process, the additions of neat methanol (fed on demand), threonine, and other nutrients cause the volume of the fermentation to increase and the final lysine concentration to decrease. In addition, water produced as a result of methanol metabolism contributes to the increase in the volume of the reactor. A three-phase approach was used to predict the rate of change of culture volume based on carbon dioxide production and methanol consumption. This model was used for the evaluation of volume control strategies to optimize lysine productivity. A constant volume reactor process with variable feeding and continuous removal of broth and cells (VF(cstr)) resulted in higher lysine productivity than a fed-batch process without volume control. This model predicts the variation in productivity of lysine with changes in growth and in specific lysine productivity. Simple modifications of the model allows one to investigate other high-lysine-secreting strains with different growth and lysine productivity characteristics. Strain NOA2#13A5-2 which secretes lysine and other end-products were modeled using both growth and non-growth-associated lysine productivity. A modified version of this model was used to simulate the change in culture volume of another L-lysine producing mutant (NOA2#13A52-8A66) with reduced secretion of end-products. The modified simulation indicated that growth-associated production dominates in strain NOA2#13A52-8A66. (c) 1996 John Wiley & Sons, Inc.
NASA Astrophysics Data System (ADS)
Curtarolo, Stefano; Awasthy, Neha; Setyawan, Wahyu; Mora, Elena; Tokune, Toshio; Bolton, Kim; Harutyunyan, Avetik
2008-03-01
Various diameters of alumina-supported Fe catalysts are used to grow single-walled carbon nanotubes (SWCNTs) with chemical vapor decomposition. We find that the reduction of the catalyst size requires an increase of the minimum temperature necessary for the growth. We address this phenomenon in terms of solubility of C in Fe nanoclusters and, by using first principles calculations, we devise a simple model to predict the behavior of the phases competing for stability in Fe-C nanoclusters at low temperature. We show that, as a function particles size, there are three scenarios compatible with steady state-, limited- and no-growth of SWCNTs, corresponding to unaffected, reduced and no solubility of C in the particles. The result raises previously unknown concerns about the growth feasibility of small and very-long SWCNTs within the current Fe CVD technology, and suggests new strategies in the search of better catalysts. Research supported by Honda R.I. and NSF.
Manchanda, Shweta
2017-01-01
Platelet-rich plasma (PRP) has emerged as a new treatment modality in regenerative plastic surgery and dermatology. PRP is a simple, cost-effective and feasible treatment option with high patient satisfaction for hair loss and can be regarded as a valuable adjuvant treatment modality for androgenic alopecia and other types of non-scarring alopecias. Authors have proposed a hair model termed “Golden anchorage with ‘molecular locking’ of ectodermal and mesenchymal components for survival and integrity of hair follicle (HF)” in this article. Golden anchorage comprises of bulge stem cells, ectodermal basement membrane and bulge portion of APM. PRP with its autologous supply of millions of growth factors works on ‘Golden anchorage’ along with keratinocytes (PDGF), dermal papilla (IGF and fibroblast growth factor), vasculature (VEGF and PDGF) and neural cells (Nerve Growth Factor) in a multipronged manner serving as an ‘elixir’ for hair growth and improving overall environment. PMID:28815175
Parnell, S; Gottwald, T R; Cunniffe, N J; Alonso Chavez, V; van den Bosch, F
2015-09-07
Emerging plant pathogens are a significant problem for conservation and food security. Surveillance is often instigated in an attempt to detect an invading epidemic before it gets out of control. Yet in practice many epidemics are not discovered until already at a high prevalence, partly due to a lack of quantitative understanding of how surveillance effort and the dynamics of an invading epidemic relate. We test a simple rule of thumb to determine, for a surveillance programme taking a fixed number of samples at regular intervals, the distribution of the prevalence an epidemic will have reached on first discovery (discovery-prevalence) and its expectation E(q*). We show that E(q*) = r/(N/Δ), i.e. simply the rate of epidemic growth divided by the rate of sampling; where r is the epidemic growth rate, N is the sample size and Δ is the time between sampling rounds. We demonstrate the robustness of this rule of thumb using spatio-temporal epidemic models as well as data from real epidemics. Our work supports the view that, for the purposes of early detection surveillance, simple models can provide useful insights in apparently complex systems. The insight can inform decisions on surveillance resource allocation in plant health and has potential applicability to invasive species generally. © 2015 The Author(s).
Parnell, S.; Gottwald, T. R.; Cunniffe, N. J.; Alonso Chavez, V.; van den Bosch, F.
2015-01-01
Emerging plant pathogens are a significant problem for conservation and food security. Surveillance is often instigated in an attempt to detect an invading epidemic before it gets out of control. Yet in practice many epidemics are not discovered until already at a high prevalence, partly due to a lack of quantitative understanding of how surveillance effort and the dynamics of an invading epidemic relate. We test a simple rule of thumb to determine, for a surveillance programme taking a fixed number of samples at regular intervals, the distribution of the prevalence an epidemic will have reached on first discovery (discovery-prevalence) and its expectation E(q*). We show that E(q*) = r/(N/Δ), i.e. simply the rate of epidemic growth divided by the rate of sampling; where r is the epidemic growth rate, N is the sample size and Δ is the time between sampling rounds. We demonstrate the robustness of this rule of thumb using spatio-temporal epidemic models as well as data from real epidemics. Our work supports the view that, for the purposes of early detection surveillance, simple models can provide useful insights in apparently complex systems. The insight can inform decisions on surveillance resource allocation in plant health and has potential applicability to invasive species generally. PMID:26336177
A STING-activating nanovaccine for cancer immunotherapy
NASA Astrophysics Data System (ADS)
Luo, Min; Wang, Hua; Wang, Zhaohui; Cai, Haocheng; Lu, Zhigang; Li, Yang; Du, Mingjian; Huang, Gang; Wang, Chensu; Chen, Xiang; Porembka, Matthew R.; Lea, Jayanthi; Frankel, Arthur E.; Fu, Yang-Xin; Chen, Zhijian J.; Gao, Jinming
2017-07-01
The generation of tumour-specific T cells is critically important for cancer immunotherapy. A major challenge in achieving a robust T-cell response is the spatiotemporal orchestration of antigen cross-presentation in antigen-presenting cells with innate stimulation. Here, we report a minimalist nanovaccine, comprising a simple physical mixture of an antigen and a synthetic polymeric nanoparticle, PC7A NP, which generates a strong cytotoxic T-cell response with low systemic cytokine expression. Mechanistically, the PC7A NP achieves efficient cytosolic delivery of tumour antigens to antigen-presenting cells in draining lymph nodes, leading to increased surface presentation while simultaneously activating type I interferon-stimulated genes. This effect is dependent on stimulator of interferon genes (STING), but not the Toll-like receptor or the mitochondrial antiviral-signalling protein (MAVS) pathway. The nanovaccine led to potent tumour growth inhibition in melanoma, colon cancer and human papilloma virus-E6/E7 tumour models. The combination of the PC7A nanovaccine and an anti-PD-1 antibody showed great synergy, with 100% survival over 60 days in a TC-1 tumour model. Rechallenging of these tumour-free animals with TC-1 cells led to complete inhibition of tumour growth, suggesting the generation of long-term antitumour memory. The STING-activating nanovaccine offers a simple, safe and robust strategy in boosting anti-tumour immunity for cancer immunotherapy.
Predator prey oscillations in a simple cascade model of drift wave turbulence
DOE Office of Scientific and Technical Information (OSTI.GOV)
Berionni, V.; Guercan, Oe. D.
2011-11-15
A reduced three shell limit of a simple cascade model of drift wave turbulence, which emphasizes nonlocal interactions with a large scale mode, is considered. It is shown to describe both the well known predator prey dynamics between the drift waves and zonal flows and to reduce to the standard three wave interaction equations. Here, this model is considered as a dynamical system whose characteristics are investigated. The analytical solutions for the purely nonlinear limit are given in terms of the Jacobi elliptic functions. An approximate analytical solution involving Jacobi elliptic functions and exponential growth is computed using scale separationmore » for the case of unstable solutions that are observed when the energy injection rate is high. The fixed points of the system are determined, and the behavior around these fixed points is studied. The system is shown to display periodic solutions corresponding to limit cycle oscillations, apparently chaotic phase space orbits, as well as unstable solutions that grow slowly while oscillating rapidly. The period doubling route to transition to chaos is examined.« less
Rotation and plasma stability in the Fitzpatrick-Aydemir model
DOE Office of Scientific and Technical Information (OSTI.GOV)
Pustovitov, V. D.
2007-08-15
The rotational stabilization of the resistive wall modes (RWMs) is analyzed within the single-mode cylindrical Fitzpatrick-Aydemir model [R. Fitzpatrick, Phys. Plasmas 9, 3459 (2002)]. Here, the consequences of the Fitzpatrick-Aydemir dispersion relation are derived in terms of the observable growth rate and toroidal rotation frequency of the mode, which allows easy interpretation of the results and comparison with experimental observations. It is shown that this model, developed for the plasma with weak dissipation, predicts the rotational destabilization of RWM in the typical range of the RWM rotation. The model predictions are compared with those obtained in a similar model, butmore » with the Boozer boundary conditions at the plasma surface [A. H. Boozer, Phys. Plasmas 11, 110 (2004)]. Simple experimental tests of the model are proposed.« less
NASA Astrophysics Data System (ADS)
Parekh, Bharat; Joshi, Mihir; Vaidya, Ashok
2008-04-01
Hydroxyapatite is very useful for various biomedical applications, due to its chemical similarity with mineralized bone of human. Hydroxyapatite is also responsible for arthropathy (joint disease). In the present study, the growth of hydroxyapatite crystals was carried out by using single-diffusion gel growth technique in silica hydro gel media, at physiological temperature. The growth of hydroxyapatite crystals under slow and controlled environment in gel medium can be simulated in a simple manner to the growth in human body. The crystals, formed in the Liesegang rings, were characterized by powder XRD, FTIR and dielectric study. The diffusion study is also carried out for the hydroxyapatite crystals using the moving boundary model. The inhibitive influence of various Ayurvedic medicinal plant extracts such as Boswellia serrata gum resin , Tribulus terrestris fruits, Rotula aquatica roots, Boerhaavia diffusa roots and Commiphora wightii, on the growth of hydroxyapatite was studied. Roots of R. aquatica and B. diffusa show some inhibition of the hydroxyapatite crystals in vitro. This preclinical study will be helpful to design the therapy for prevention of hydroxyapatite-based ailments.
Liang, Haiyi; Mahadevan, L.
2009-01-01
Long leaves in terrestrial plants and their submarine counterparts, algal blades, have a typical, saddle-like midsurface and rippled edges. To understand the origin of these morphologies, we dissect leaves and differentially stretch foam ribbons to show that these shapes arise from a simple cause, the elastic relaxation via bending that follows either differential growth (in leaves) or differential stretching past the yield point (in ribbons). We quantify these different modalities in terms of a mathematical model for the shape of an initially flat elastic sheet with lateral gradients in longitudinal growth. By using a combination of scaling concepts, stability analysis, and numerical simulations, we map out the shape space for these growing ribbons and find that as the relative growth strain is increased, a long flat lamina deforms to a saddle shape and/or develops undulations that may lead to strongly localized ripples as the growth strain is localized to the edge of the leaf. Our theory delineates the geometric and growth control parameters that determine the shape space of finite laminae and thus allows for a comparative study of elongated leaf morphology. PMID:19966215
When water meets behavioral economics (or: it is not all about money!)
NASA Astrophysics Data System (ADS)
Escriva-Bou, A.
2014-12-01
Water engineers do not like people; we are better with numbers, equations and models where people behavior is only a variable, usually constant, or in the best case a probabilistic approximation. On the other side, most economic studies relate to people's behavior, and when economists develop engineering-based models, engineers usually think that econometric approaches are too simple to represent complex systems that engineers like to work with. Besides this simple-minded cliche, there is a lot of field to explore in the intersections of both disciplines. Even though the development of infrastructure cost-benefit analyses after Dupuit's work, or the more recent growth of hydroeconomic modeling, we are still missing a lot of potential synergic benefits from integrating behavioral economics and water infrastructure design and management. To present a simple example: urban water infrastructure design is based on water peaks, so reservoirs, pump stations and pipe dimensions have to be built to serve these peaks; water-related energy assessment studies have shown that there is a lot of energy used for every drop of water used in our houses, farms, and industries, and energy peaks are even larger that water peaks, creating expensive troubles for energy supply; and all this energy consumption means greenhouse gas emissions. Therefore we agree that reducing water peaks might create a lot of benefits, but could water customers change their behavior? Which incentives do they need? It is only about money, or it may be managed with better information? Beyond this example there are many other promising economic topics that could help in our daily water problems, such as: game theoretic approaches to understand decisions; science-based agent models that help us to understand the performance of a system as the sum of agents' actions and interactions; or the analysis of institutional-driven management to avoid the tragedy of the commons that depletes groundwater resources globally. And no need to remind that all resource scarcity problems will increase with population growth, so it would be better to begin work sooner on these problems.
Can simple rules control development of a pioneer vertebrate neuronal network generating behavior?
Roberts, Alan; Conte, Deborah; Hull, Mike; Merrison-Hort, Robert; al Azad, Abul Kalam; Buhl, Edgar; Borisyuk, Roman; Soffe, Stephen R
2014-01-08
How do the pioneer networks in the axial core of the vertebrate nervous system first develop? Fundamental to understanding any full-scale neuronal network is knowledge of the constituent neurons, their properties, synaptic interconnections, and normal activity. Our novel strategy uses basic developmental rules to generate model networks that retain individual neuron and synapse resolution and are capable of reproducing correct, whole animal responses. We apply our developmental strategy to young Xenopus tadpoles, whose brainstem and spinal cord share a core vertebrate plan, but at a tractable complexity. Following detailed anatomical and physiological measurements to complete a descriptive library of each type of spinal neuron, we build models of their axon growth controlled by simple chemical gradients and physical barriers. By adding dendrites and allowing probabilistic formation of synaptic connections, we reconstruct network connectivity among up to 2000 neurons. When the resulting "network" is populated by model neurons and synapses, with properties based on physiology, it can respond to sensory stimulation by mimicking tadpole swimming behavior. This functioning model represents the most complete reconstruction of a vertebrate neuronal network that can reproduce the complex, rhythmic behavior of a whole animal. The findings validate our novel developmental strategy for generating realistic networks with individual neuron- and synapse-level resolution. We use it to demonstrate how early functional neuronal connectivity and behavior may in life result from simple developmental "rules," which lay out a scaffold for the vertebrate CNS without specific neuron-to-neuron recognition.
Quist, M.C.; Guy, C.S.; Schultz, R.D.; Stephen, J.L.
2003-01-01
We compared the growth of walleyes Stizostedion vitreum in Kansas to that of other populations throughout North America and determined the effects of the abundance of gizzard shad Dorosoma cepedianum and temperature on the growth of walleyes in Kansas reservoirs. Age was estimated from scales and otoliths collected from walleyes (N = 2,072) sampled with gill nets from eight Kansas reservoirs during fall in 1991-1999. Age-0 gizzard shad abundance was indexed based on summer seining information, and temperature data were obtained from the National Oceanic and Atmospheric Administration. Parameter estimates of von Bertalanffy growth models indicated that the growth of walleyes in Kansas was more similar to that of southern latitude populations (e.g., Mississippi and Texas) than to that of northern (e.g., Manitoba, Minnesota and South Dakota) or middle latitude (e.g., Colorado and Iowa) populations. Northern and middle latitude populations had lower mean back-calculated lengths at age 1, lower growth coefficients, and greater longevity than southern and Kansas populations. A relative growth index (RGI; [Lt/Ls ] ?? 100, where Lt is the observed length at age and Ls is the age-specific standard length derived from a pooled von Bertalanffy growth model) and standardized percentile values (percentile values of mean back-calculated lengths at age) indicated that the growth of walleyes in Kansas was above average compared with that of other populations in North America. The annual growth increments of Kansas walleyes were more variable among years than among reservoirs. The growth increments of age-0 and age-1 walleyes were positively related to the catch rates of gizzard shad smaller than 80 mm, whereas the growth of age-2 and age-3 walleyes was inversely related to mean summer air temperature. Our results provide a framework for comparing North American walleye populations, and our proposed RGI provides a simple, easily interpreted index of growth.
Growth dynamics and the evolution of cooperation in microbial populations
NASA Astrophysics Data System (ADS)
Cremer, Jonas; Melbinger, Anna; Frey, Erwin
2012-02-01
Microbes providing public goods are widespread in nature despite running the risk of being exploited by free-riders. However, the precise ecological factors supporting cooperation are still puzzling. Following recent experiments, we consider the role of population growth and the repetitive fragmentation of populations into new colonies mimicking simple microbial life-cycles. Individual-based modeling reveals that demographic fluctuations, which lead to a large variance in the composition of colonies, promote cooperation. Biased by population dynamics these fluctuations result in two qualitatively distinct regimes of robust cooperation under repetitive fragmentation into groups. First, if the level of cooperation exceeds a threshold, cooperators will take over the whole population. Second, cooperators can also emerge from a single mutant leading to a robust coexistence between cooperators and free-riders. We find frequency and size of population bottlenecks, and growth dynamics to be the major ecological factors determining the regimes and thereby the evolutionary pathway towards cooperation.
Zhong, Nianbing; Liao, Qiang; Zhu, Xun; Chen, Rong
2014-04-15
A new simple fiber-optic evanescent wave sensor was created to accurately monitor the growth and hydrogen production performance of biofilms. The proposed sensor consists of two probes (i.e., a sensor and reference probe), using the etched fibers with an appropriate surface roughness to improve its sensitivity. The sensor probe measures the biofilm growth and change of liquid-phase concentration inside the biofilm. The reference probe is coated with a hydrophilic polytetrafluoroethylene membrane to separate the liquids from photosynthetic bacteria Rhodopseudomonas palustris CQK 01 and to measure the liquid concentration. We also developed a model to demonstrate the accuracy of the measurement. The biofilm measurement was calibrated using an Olympus microscope. A linear relationship was obtained for the biofilm thickness range from 0 to 120 μm with a synthetic medium under continuous supply to the bioreactor. The highest level of hydrogen production rate occurred at a thickness of 115 μm.
Effect of deposition rate and NNN interactions on adatoms mobility in epitaxial growth
NASA Astrophysics Data System (ADS)
Hamouda, Ajmi B. H.; Mahjoub, B.; Blel, S.
2017-07-01
This paper provides a detailed analysis of the surface diffusion problem during epitaxial step-flow growth using a simple theoretical model for the diffusion equation of adatoms concentration. Within this framework, an analytical expression for the adatom mobility as a function of the deposition rate and the Next-Nearest-Neighbor (NNN) interactions is derived and compared with the effective mobility computed from kinetic Monte Carlo (kMC) simulations. As far as the 'small' step velocity or relatively weak deposition rate commonly used for copper growth is concerned, an excellent quantitative agreement with the theoretical prediction is found. The effective adatoms mobility is shown to exhibit an exponential decrease with NNN interactions strength and increases in roughly linear behavior versus deposition rate F. The effective step stiffness and the adatoms mobility are also shown to be closely related to the concentration of kinks.
NASA Astrophysics Data System (ADS)
Foley, B. J.
2017-12-01
Grain-size reduction is thought to play an important role in shear localization within the lithosphere, as mylonites are commonly seen in regions that have undergone intense deformation. However, flow in lithospheric shear zones can also cause heating due to the energy dissipated by deformation. As grain growth is strongly enhanced by warmer temperatures, shear heating may impede grainsize reduction and the formation of mylonite zones. I use models of simple shear, with length-scales representative of lithospheric shear zones and plate boundaries, including shear heating and grainsize evolution. Grain-damage theory is used to represent the evolution of grainsize. The models are used to determine conditions where grainsize reduction dominates versus those where shear heating dominates; if grainsize reduction dominates, then heating is held in check by the drop in viscosity brought about by small grains. On the other hand, if heating dominates then grain-reduction is prevented by fast grain-growth rates. From the numerical models, simple scaling laws are developed that give the stready-state grainsize and temperature rise as a function of strain-rate, background temperature, and parameters for grain-growth and grain-reduction. I find that for parameter ranges constrained by field observations of shear zones and rock deformation experiments, grainsize reduction dominated over shear heating. Very high strain-rates or driving stresses, above what is typically expected in natural shear zones, are needed for shear heating to dominate over grainsize reduction. Also explored is the timescale to reach steady-state grainsize and temperature conditions in a shear zone. For realistic driving stress or strain-rate, timescales to reach steady-state are often very long, on the order of hundreds of millions of years or longer. This might indicate that natural shear zones do not reach steady-state, or that additional processes are important in initiating lithospheric shear localization.
A first step to compare geodynamical models and seismic observations of the inner core
NASA Astrophysics Data System (ADS)
Lasbleis, M.; Waszek, L.; Day, E. A.
2016-12-01
Seismic observations have revealed a complex inner core, with lateral and radial heterogeneities at all observable scales. The dominant feature is the east-west hemispherical dichotomy in seismic velocity and attenuation. Several geodynamical models have been proposed to explain the observed structure: convective instabilities, external forces, crystallisation processes or influence of outer core convection. However, interpreting such geodynamical models in terms of the seismic observations is difficult, and has been performed only for very specific models (Geballe 2013, Lincot 2014, 2016). Here, we propose a common framework to make such comparisons. We have developed a Python code that propagates seismic ray paths through kinematic geodynamical models for the inner core, computing a synthetic seismic data set that can be compared to seismic observations. Following the method of Geballe 2013, we start with the simple model of translation. For this, the seismic velocity is proposed to be function of the age or initial growth rate of the material (since there is no deformation included in our models); the assumption is reasonable when considering translation, growth and super rotation of the inner core. Using both artificial (random) seismic ray data sets and a real inner core data set (from Waszek et al. 2011), we compare these different models. Our goal is to determine the model which best matches the seismic observations. Preliminary results show that super rotation successfully creates an eastward shift in properties with depth, as has been observed seismically. Neither the growth rate of inner core material nor the relationship between crystal size and seismic velocity are well constrained. Consequently our method does not directly compute the seismic travel times. Instead, here we use age, growth rate and other parameters as proxies for the seismic properties, which represent a good first step to compare geodynamical and seismic observations.Ultimately we aim to release our codes to broader scientific community, allowing researchers from all disciplines to test their models of inner core growth against seismic observations or create a kinematic model for the evolution of the inner core which matches new geophysical observations.
A simple model for the evolution of melt pond coverage on permeable Arctic sea ice
NASA Astrophysics Data System (ADS)
Popović, Predrag; Abbot, Dorian
2017-05-01
As the melt season progresses, sea ice in the Arctic often becomes permeable enough to allow for nearly complete drainage of meltwater that has collected on the ice surface. Melt ponds that remain after drainage are hydraulically connected to the ocean and correspond to regions of sea ice whose surface is below sea level. We present a simple model for the evolution of melt pond coverage on such permeable sea ice floes in which we allow for spatially varying ice melt rates and assume the whole floe is in hydrostatic balance. The model is represented by two simple ordinary differential equations, where the rate of change of pond coverage depends on the pond coverage. All the physical parameters of the system are summarized by four strengths that control the relative importance of the terms in the equations. The model both fits observations and allows us to understand the behavior of melt ponds in a way that is often not possible with more complex models. Examples of insights we can gain from the model are that (1) the pond growth rate is more sensitive to changes in bare sea ice albedo than changes in pond albedo, (2) ponds grow slower on smoother ice, and (3) ponds respond strongest to freeboard sinking on first-year ice and sidewall melting on multiyear ice. We also show that under a global warming scenario, pond coverage would increase, decreasing the overall ice albedo and leading to ice thinning that is likely comparable to thinning due to direct forcing. Since melt pond coverage is one of the key parameters controlling the albedo of sea ice, understanding the mechanisms that control the distribution of pond coverage will help improve large-scale model parameterizations and sea ice forecasts in a warming climate.
A simple rule based model for scheduling farm management operations in SWAT
NASA Astrophysics Data System (ADS)
Schürz, Christoph; Mehdi, Bano; Schulz, Karsten
2016-04-01
For many interdisciplinary questions at the watershed scale, the Soil and Water Assessment Tool (SWAT; Arnold et al., 1998) has become an accepted and widely used tool. Despite its flexibility, the model is highly demanding when it comes to input data. At SWAT's core the water balance and the modeled nutrient cycles are plant growth driven (implemented with the EPIC crop growth model). Therefore, land use and crop data with high spatial and thematic resolution, as well as detailed information on cultivation and farm management practices are required. For many applications of the model however, these data are unavailable. In order to meet these requirements, SWAT offers the option to trigger scheduled farm management operations by applying the Potential Heat Unit (PHU) concept. The PHU concept solely takes into account the accumulation of daily mean temperature for management scheduling. Hence, it contradicts several farming strategies that take place in reality; such as: i) Planting and harvesting dates are set much too early or too late, as the PHU concept is strongly sensitivity to inter-annual temperature fluctuations; ii) The timing of fertilizer application, in SWAT this often occurs simultaneously on the same date in in each field; iii) and can also coincide with precipitation events. Particularly, the latter two can lead to strong peaks in modeled nutrient loads. To cope with these shortcomings we propose a simple rule based model (RBM) to schedule management operations according to realistic farmer management practices in SWAT. The RBM involves simple strategies requiring only data that are input into the SWAT model initially, such as temperature and precipitation data. The user provides boundaries of time periods for operation schedules to take place for all crops in the model. These data are readily available from the literature or from crop variety trials. The RBM applies the dates by complying with the following rules: i) Operations scheduled in the spring planting season and fall harvesting season are temperature dependent. Warmer than usual conditions trigger the setting of respective operations earlier in spring and later in fall to prolong the cropping season. ii) Operations are randomized within a time span ± 5 days around the calculated dates and iii) are only set on days where no rainfall occurs. Advantages offered by the RBM framework are the implementation of farmers undertaking different farming strategies, such as conventional or conservative farming, and the consideration of the prevailing weather conditions on the planting periods, thus the shifting management operations due to climate change will also be considered over the long term. By applying these rules to the available data we were able to establish a simple framework developing more realistic crop management schedules for SWAT which are an improvement over the current PHU concept implemented in SWAT. The outlined framework is easily extendible and adaptable to many other applications in SWAT. Case studies have yet to demonstrate the applicability and the validity of the proposed RBM.
Human population and atmospheric carbon dioxide growth dynamics: Diagnostics for the future
NASA Astrophysics Data System (ADS)
Hüsler, A. D.; Sornette, D.
2014-10-01
We analyze the growth rates of human population and of atmospheric carbon dioxide by comparing the relative merits of two benchmark models, the exponential law and the finite-time-singular (FTS) power law. The later results from positive feedbacks, either direct or mediated by other dynamical variables, as shown in our presentation of a simple endogenous macroeconomic dynamical growth model describing the growth dynamics of coupled processes involving human population (labor in economic terms), capital and technology (proxies by CO2 emissions). Human population in the context of our energy intensive economies constitutes arguably the most important underlying driving variable of the content of carbon dioxide in the atmosphere. Using some of the best databases available, we perform empirical analyses confirming that the human population on Earth has been growing super-exponentially until the mid-1960s, followed by a decelerated sub-exponential growth, with a tendency to plateau at just an exponential growth in the last decade with an average growth rate of 1.0% per year. In contrast, we find that the content of carbon dioxide in the atmosphere has continued to accelerate super-exponentially until 1990, with a transition to a progressive deceleration since then, with an average growth rate of approximately 2% per year in the last decade. To go back to CO2 atmosphere contents equal to or smaller than the level of 1990 as has been the broadly advertised goals of international treaties since 1990 requires herculean changes: from a dynamical point of view, the approximately exponential growth must not only turn to negative acceleration but also negative velocity to reverse the trend.
NASA Astrophysics Data System (ADS)
Louna, Zineeddine; Goda, Ibrahim; Ganghoffer, Jean-François
2018-01-01
We construct in the present paper constitutive models for bone remodeling based on micromechanical analyses at the scale of a representative unit cell (RUC) including a porous trabecular microstructure. The time evolution of the microstructure is simulated as a surface remodeling process by relating the surface growth remodeling velocity to a surface driving force incorporating a (surface) Eshelby tensor. Adopting the framework of irreversible thermodynamics, a 2D constitutive model based on the setting up of the free energy density and a dissipation potential is identified from FE simulations performed over a unit cell representative of the trabecular architecture obtained from real bone microstructures. The static and evolutive effective properties of bone at the scale of the RUC are obtained by combining a methodology for the evaluation of the average kinematic and static variables over a prototype unit cell and numerical simulations with controlled imposed first gradient rates. The formulated effective growth constitutive law at the scale of the homogenized set of trabeculae within the RUC is of viscoplastic type and relates the average growth strain rate to the homogenized stress tensor. The postulated model includes a power law function of an effective stress chosen to depend on the first and second stress invariants. The model coefficients are calibrated from a set of virtual testing performed over the RUC subjected to a sequence of loadings. Numerical simulations show that overall bone growth does not show any growth kinematic hardening. The obtained results quantify the strength and importance of different types of external loads (uniaxial tension, simple shear, and biaxial loading) on the overall remodeling process and the development of elastic deformations within the RUC.
Energy Balance Models and Planetary Dynamics
NASA Technical Reports Server (NTRS)
Domagal-Goldman, Shawn
2012-01-01
We know that planetary dynamics can have a significant affect on the climate of planets. Planetary dynamics dominate the glacial-interglacial periods on Earth, leaving a significant imprint on the geological record. They have also been demonstrated to have a driving influence on the climates of other planets in our solar system. We should therefore expect th.ere to be similar relationships on extrasolar planets. Here we describe a simple energy balance model that can predict the growth and thickness of glaciers, and their feedbacks on climate. We will also describe model changes that we have made to include planetary dynamics effects. This is the model we will use at the start of our collaboration to handle the influence of dynamics on climate.
Stock, Kristin; Estrada, Marta F; Vidic, Suzana; Gjerde, Kjersti; Rudisch, Albin; Santo, Vítor E; Barbier, Michaël; Blom, Sami; Arundkar, Sharath C; Selvam, Irwin; Osswald, Annika; Stein, Yan; Gruenewald, Sylvia; Brito, Catarina; van Weerden, Wytske; Rotter, Varda; Boghaert, Erwin; Oren, Moshe; Sommergruber, Wolfgang; Chong, Yolanda; de Hoogt, Ronald; Graeser, Ralph
2016-07-01
Two-dimensional (2D) cell cultures growing on plastic do not recapitulate the three dimensional (3D) architecture and complexity of human tumors. More representative models are required for drug discovery and validation. Here, 2D culture and 3D mono- and stromal co-culture models of increasing complexity have been established and cross-comparisons made using three standard cell carcinoma lines: MCF7, LNCaP, NCI-H1437. Fluorescence-based growth curves, 3D image analysis, immunohistochemistry and treatment responses showed that end points differed according to cell type, stromal co-culture and culture format. The adaptable methodologies described here should guide the choice of appropriate simple and complex in vitro models.
Stock, Kristin; Estrada, Marta F.; Vidic, Suzana; Gjerde, Kjersti; Rudisch, Albin; Santo, Vítor E.; Barbier, Michaël; Blom, Sami; Arundkar, Sharath C.; Selvam, Irwin; Osswald, Annika; Stein, Yan; Gruenewald, Sylvia; Brito, Catarina; van Weerden, Wytske; Rotter, Varda; Boghaert, Erwin; Oren, Moshe; Sommergruber, Wolfgang; Chong, Yolanda; de Hoogt, Ronald; Graeser, Ralph
2016-01-01
Two-dimensional (2D) cell cultures growing on plastic do not recapitulate the three dimensional (3D) architecture and complexity of human tumors. More representative models are required for drug discovery and validation. Here, 2D culture and 3D mono- and stromal co-culture models of increasing complexity have been established and cross-comparisons made using three standard cell carcinoma lines: MCF7, LNCaP, NCI-H1437. Fluorescence-based growth curves, 3D image analysis, immunohistochemistry and treatment responses showed that end points differed according to cell type, stromal co-culture and culture format. The adaptable methodologies described here should guide the choice of appropriate simple and complex in vitro models. PMID:27364600
A predictive model for the tokamak density limit
Teng, Q.; Brennan, D. P.; Delgado-Aparicio, L.; ...
2016-07-28
We reproduce the Greenwald density limit, in all tokamak experiments by using a phenomenologically correct model with parameters in the range of experiments. A simple model of equilibrium evolution and local power balance inside the island has been implemented to calculate the radiation-driven thermo-resistive tearing mode growth and explain the density limit. Strong destabilization of the tearing mode due to an imbalance of local Ohmic heating and radiative cooling in the island predicts the density limit within a few percent. Furthermore, we found the density limit and it is a local edge limit and weakly dependent on impurity densities. Ourmore » results are robust to a substantial variation in model parameters within the range of experiments.« less
Modeling Thin Film Oxide Growth
NASA Astrophysics Data System (ADS)
Sherman, Quentin
Thin film oxidation is investigated using two modeling techniques in the interest of better understanding the roles of space charge and non-equilibrium effects. An electrochemical phase-field model of an oxide-metal interface is formulated in one dimension and studied at equilibrium and during growth. An analogous sharp interface model is developed to validate the phase-field model in the thick film limit. Electrochemical profiles across the oxide are shown to deviate from the sharp interface prediction when the oxide film is thin compared to the Debye length, however no effect on the oxidation kinetics is found. This is attributed to the simple thermodynamic and kinetic models used therein. The phase-field model provides a framework onto to which additional physics can be added to better model thin film oxidation. A model for solute trapping during the oxidation of binary alloys is developed to study non-equilibrium effects during the early stages of oxide growth. The model is applied to NiCr alloys, and steady-state interfacial composition maps are presented for the growth of an oxide with the rock salt structure. No detailed experimental data is available to verify the predictions of the solute trapping model, however it is shown to be consistent with the trends observed during the early stages of NiCr oxidation. Lastly, experimental studies of the wet infiltration technique for decorating solid oxide fuel cell anodes with nickel nanoparticles are presented. The effect of nickel nitrate calcination parameters on the resulting nickel oxide microstructures are studied on both porous and planar substrates. Decreasing the calcination temperature and dwell time, as well as a dehydration step after nickel nitrate infiltration, are all shown to decrease the initial nickel oxide particle size, but other factors such as geometry and nickel loading per unit area also affected the final nickel particle size and morphology upon reduction.
NASA Astrophysics Data System (ADS)
Wegehenkel, M.
In this paper, long-term effects of different afforestation scenarios on landscape wa- ter balance will be analyzed taking into account the results of a regional case study. This analysis is based on using a GIS-coupled simulation model for the the spatially distributed calculation of water balance.For this purpose, the modelling system THE- SEUS with a simple GIS-interface will be used. To take into account the special case of change in forest cover proportion, THESEUS was enhanced with a simple for- est growth model. In the regional case study, model runs will be performed using a detailed spatial data set from North-East Germany. This data set covers a mesoscale catchment located at the moraine landscape of North-East Germany. Based on this data set, the influence of the actual landuse and of different landuse change scenarios on water balance dynamics will be investigated taking into account the spatial distributed modelling results from THESEUS. The model was tested using different experimen- tal data sets from field plots as well as obsverded catchment discharge. Additionally to such convential validation techniques, remote sensing data were used to check the simulated regional distribution of water balance components like evapotranspiration in the catchment.
A simple and complete model for wind turbine wakes over complex terrain
NASA Astrophysics Data System (ADS)
Rommelfanger, Nick; Rajborirug, Mai; Luzzatto-Fegiz, Paolo
2017-11-01
Simple models for turbine wakes have been used extensively in the wind energy community, both as independent tools, as well as to complement more refined and computationally-intensive techniques. These models typically prescribe empirical relations for how the wake radius grows with downstream distance x and obtain the wake velocity at each x through the application of either mass conservation, or of both mass and momentum conservation (e.g. Katić et al. 1986; Frandsen et al. 2006; Bastankhah & Porté-Agel 2014). Since these models assume a global behavior of the wake (for example, linear spreading with x) they cannot respond to local changes in background flow, as may occur over complex terrain. Instead of assuming a global wake shape, we develop a model by relying on a local assumption for the growth of the turbulent interface. To this end, we introduce to wind turbine wakes the use of the entrainment hypothesis, which has been used extensively in other areas of geophysical fluid dynamics. We obtain two coupled ordinary differential equations for mass and momentum conservation, which can be readily solved with a prescribed background pressure gradient. Our model is in good agreement with published data for the development of wakes over complex terrain.
NASA Astrophysics Data System (ADS)
Valencia, Hubert; Kangawa, Yoshihiro; Kakimoto, Koichi
2017-06-01
Using ab initio calculations, a simple model for GaAs1-xNx vapor-phase epitaxy on (100) surface of GaAs was created. By studying As2 and H2 molecules adsorptions and As/N atom substitutions on (100) GaAs surfaces, we obtain a relative stability diagram of all stable surfaces under varying As2, H2, and N2 conditions. We previously proved that this model could describe the vapor-phase epitaxy of GaAs1-x Nx with simple, fully decomposed, precursors. In this paper, we show that in more complex reaction conditions using monomethylhydrazine (MMHy), and dimethylhydrazine (DMHy), it is still possible to use our model to obtain an accurate description of the temperature and pressure stability domains for each surfaces, linked to chemical beam epitaxy (CBE) growth conditions. Moreover, the different N-incorporation regimes observed experimentally at different temperature can be explain and predict by our model. The use of MMHy and DMHy precursors can also be rationalized. Our model should then help to better understand the conditions needed to obtain an high quality GaAs1-xNx using vapor-phase epitaxy.
Assessment of Fungal Growth in Liquid Cultures and Bioassay of Toxic Products.
ERIC Educational Resources Information Center
Isaac, Susan; And Others
1988-01-01
Outlined is a procedure for the assessment of fungal growth under different cultural conditions, together with a demonstration of the toxic nature of exudates released from a fungal pathogen during growth in culture, using a simple bioassay. (Author/CW)
A statistical mechanical model of economics
NASA Astrophysics Data System (ADS)
Lubbers, Nicholas Edward Williams
Statistical mechanics pursues low-dimensional descriptions of systems with a very large number of degrees of freedom. I explore this theme in two contexts. The main body of this dissertation explores and extends the Yard Sale Model (YSM) of economic transactions using a combination of simulations and theory. The YSM is a simple interacting model for wealth distributions which has the potential to explain the empirical observation of Pareto distributions of wealth. I develop the link between wealth condensation and the breakdown of ergodicity due to nonlinear diffusion effects which are analogous to the geometric random walk. Using this, I develop a deterministic effective theory of wealth transfer in the YSM that is useful for explaining many quantitative results. I introduce various forms of growth to the model, paying attention to the effect of growth on wealth condensation, inequality, and ergodicity. Arithmetic growth is found to partially break condensation, and geometric growth is found to completely break condensation. Further generalizations of geometric growth with growth in- equality show that the system is divided into two phases by a tipping point in the inequality parameter. The tipping point marks the line between systems which are ergodic and systems which exhibit wealth condensation. I explore generalizations of the YSM transaction scheme to arbitrary betting functions to develop notions of universality in YSM-like models. I find that wealth vi condensation is universal to a large class of models which can be divided into two phases. The first exhibits slow, power-law condensation dynamics, and the second exhibits fast, finite-time condensation dynamics. I find that the YSM, which exhibits exponential dynamics, is the critical, self-similar model which marks the dividing line between the two phases. The final chapter develops a low-dimensional approach to materials microstructure quantification. Modern materials design harnesses complex microstructure effects to develop high-performance materials, but general microstructure quantification is an unsolved problem. Motivated by statistical physics, I envision microstructure as a low-dimensional manifold, and construct this manifold by leveraging multiple machine learning approaches including transfer learning, dimensionality reduction, and computer vision breakthroughs with convolutional neural networks.
Butterworth, Alice S; Robertson, Alan J; Ho, Mei-Fong; Gatton, Michelle L; McCarthy, James S; Trenholme, Katharine R
2011-04-18
Obtaining single parasite clones is required for many techniques in malaria research. Cloning by limiting dilution using microscopy-based assessment for parasite growth is an arduous and labor-intensive process. An alternative method for the detection of parasite growth in limiting dilution assays is using a commercial ELISA histidine-rich protein II (HRP2) detection kit. Detection of parasite growth was undertaken using HRP2 ELISA and compared to thick film microscopy. An HRP2 protein standard was used to determine the detection threshold of the HRP2 ELISA assay, and a HRP2 release model was used to extrapolate the amount of parasite growth required for a positive result. The HRP2 ELISA was more sensitive than microscopy for detecting parasite growth. The minimum level of HRP2 protein detection of the ELISA was 0.11 ng/ml. Modeling of HRP2 release determined that 2,116 parasites are required to complete a full erythrocytic cycle to produce sufficient HRP2 to be detected by the ELISA. Under standard culture conditions this number of parasites is likely to be reached between 8 to 14 days of culture. This method provides an accurate and simple way for the detection of parasite growth in limiting dilution assays, reducing time and resources required in traditional methods. Furthermore the method uses spent culture media instead of the parasite-infected red blood cells, enabling culture to continue. © 2011 Butterworth et al; licensee BioMed Central Ltd.
NASA Technical Reports Server (NTRS)
Carlson, Frederick
1990-01-01
The objective of this theoretical research effort was to improve the understanding of the growth of Pb(x)Sn(1-x)Te and especially how crystal quality could be improved utilizing the microgravity environment of space. All theoretical growths are done using the vertical Bridgman method. It is believed that improved single crystal yields can be achieved by systematically identifying and studying system parameters both theoretically and experimentally. A computational model was developed to study and eventually optimize the growth process. The model is primarily concerned with the prediction of the thermal field, although mass transfer in the melt and the state of stress in the crystal were of considerable interest. The evolution is presented of the computer simulation and some of the important results obtained. Diffusion controlled growth was first studied since it represented a relatively simple, but nontheless realistic situation. In fact, results from this analysis prompted a study of the triple junction region where the melt, crystal, and ampoule wall meet. Since microgravity applications were sought because of the low level of fluid movement, the effect of gravitational field strength on the thermal and concentration field was also of interest. A study of the strength of coriolis acceleration on the growth process during space flight was deemed necessary since it would surely produce asymmetries in the flow field if strong enough. Finally, thermosolutal convection in a steady microgravity field for thermally stable conditions and both stable and unstable solutal conditions was simulated.
Brenner, M H
1983-01-01
This paper discusses a first-stage analysis of the link of unemployment rates, as well as other economic, social and environmental health risk factors, to mortality rates in postwar Britain. The results presented represent part of an international study of the impact of economic change on mortality patterns in industrialized countries. The mortality patterns examined include total and infant mortality and (by cause) cardiovascular (total), cerebrovascular and heart disease, cirrhosis of the liver, and suicide, homicide and motor vehicle accidents. Among the most prominent factors that beneficially influence postwar mortality patterns in England/Wales and Scotland are economic growth and stability and health service availability. A principal detrimental factor to health is a high rate of unemployment. Additional factors that have an adverse influence on mortality rates are cigarette consumption and heavy alcohol use and unusually cold winter temperatures (especially in Scotland). The model of mortality that includes both economic changes and behavioral and environmental risk factors was successfully applied to infant mortality rates in the interwar period. In addition, the "simple" economic change model of mortality (using only economic indicators) was applied to other industrialized countries. In Canada, the United States, the United Kingdom, and Sweden, the simple version of the economic change model could be successfully applied only if the analysis was begun before World War II; for analysis beginning in the postwar era, the more sophisticated economic change model, including behavioral and environmental risk factors, was required. In France, West Germany, Italy, and Spain, by contrast, some success was achieved using the simple economic change model.
A Discrete Fracture Network Model with Stress-Driven Nucleation and Growth
NASA Astrophysics Data System (ADS)
Lavoine, E.; Darcel, C.; Munier, R.; Davy, P.
2017-12-01
The realism of Discrete Fracture Network (DFN) models, beyond the bulk statistical properties, relies on the spatial organization of fractures, which is not issued by purely stochastic DFN models. The realism can be improved by injecting prior information in DFN from a better knowledge of the geological fracturing processes. We first develop a model using simple kinematic rules for mimicking the growth of fractures from nucleation to arrest, in order to evaluate the consequences of the DFN structure on the network connectivity and flow properties. The model generates fracture networks with power-law scaling distributions and a percentage of T-intersections that are consistent with field observations. Nevertheless, a larger complexity relying on the spatial variability of natural fractures positions cannot be explained by the random nucleation process. We propose to introduce a stress-driven nucleation in the timewise process of this kinematic model to study the correlations between nucleation, growth and existing fracture patterns. The method uses the stress field generated by existing fractures and remote stress as an input for a Monte-Carlo sampling of nuclei centers at each time step. Networks so generated are found to have correlations over a large range of scales, with a correlation dimension that varies with time and with the function that relates the nucleation probability to stress. A sensibility analysis of input parameters has been performed in 3D to quantify the influence of fractures and remote stress field orientations.
Simulation Studies of the Effect of Forest Spatial Structure on InSAR Signature
NASA Technical Reports Server (NTRS)
Sun, Guoqing; Liu, Dawei; Ranson, K. Jon; Koetz, Benjamin
2007-01-01
The height of scattering phase retrieved from InSAR data is considered being correlated with the tree height and the spatial structure of the forest stand. Though some researchers have used simple backscattering models to estimate tree height from the height of scattering center, the effect of forest spatial structure on InSAR data is not well understood yet. A three-dimensional coherent radar backscattering model for forest canopies based on realistic three-dimensional scene was used to investigate the effect in this paper. The realistic spatial structure of forest canopies was established either by field measurements (stem map) or through use of forest growth model. Field measurements or a forest growth model parameterized using local environmental parameters provides information of forest species composition and tree sizes in certain growth phases. A fractal tree model (L-system) was used to simulate individual 3- D tree structure of different ages or heights. Trees were positioned in a stand in certain patterns resulting in a 3-D medium of discrete scatterers. The radar coherent backscatter model took the 3-D forest scene as input and simulates the coherent radar backscattering signature. Interferometric SAR images of 3D scenes were simulated and heights of scattering phase centers were estimated from the simulated InSAR data. The effects of tree height, crown cover, crown depth, and the spatial distribution patterns of trees on the scattering phase center were analyzed. The results will be presented in the paper.
Black Hole Safari: Tracking Populations and Hunting Big Game
NASA Astrophysics Data System (ADS)
McConnell, N. J.
2013-10-01
Understanding the physical connection, or lack thereof, between the growth of galaxies and supermassive black holes is a key challenge in extragalactic astronomy. Dynamical studies of nearby galaxies are building a census of black hole masses across a broad range of galaxy types and uncovering statistical correlations between galaxy bulge properties and black hole masses. These local correlations provide a baseline for studying galaxies and black holes at higher redshifts. Recent measurements have probed the extremes of the supermassive black hole population and introduced surprises that challenge simple models of black hole and galaxy co-evolution. Future advances in the quality and quantity of dynamical black hole mass measurements will shed light upon the growth of massive galaxies and black holes in different cosmic environments.
Effect of flow and active mixing on bacterial growth in a colon-like geometry
NASA Astrophysics Data System (ADS)
Cremer, Jonas; Segota, Igor; Arnoldini, Markus; Groisman, Alex; Hwa, Terence
The large intestine harbors bacteria from hundreds of species, with bacterial densities reaching up to 1012 cells per gram. Many different factors influence bacterial growth dynamics and thus bacterial density and microbiota composition. One dominant force is flow which can in principle lead to a washout of bacteria from the proximal colon. Active mixing by Contractions of the colonic wall together with bacterial growth might counteract such flow-forces and allow high bacterial densities to occur. As a step towards understanding bacterial growth in the presence of mixing and flow, we constructed an in-vitro setup where controlled wall-deformations of a channel emulate Contractions. We investigate growth along the channel under a steady nutrient inflow. In the limits of no or very frequent Contractions, the device behaves like a plug-flow reactor and a chemostat respectively. Depending on mixing and flow, we observe varying spatial gradients in bacterial density along the channel. Active mixing by deformations of the channel wall is shown to be crucial in maintaining a steady-state bacterial population in the presence of flow. The growth-dynamics is quantitatively captured by a simple mathematical model, with the effect of mixing described by an effective diffusion term.
Assessing the impact of nutrient enrichment in estuaries: susceptibility to eutrophication.
Painting, S J; Devlin, M J; Malcolm, S J; Parker, E R; Mills, D K; Mills, C; Tett, P; Wither, A; Burt, J; Jones, R; Winpenny, K
2007-01-01
The main aim of this study was to develop a generic tool for assessing risks and impacts of nutrient enrichment in estuaries. A simple model was developed to predict the magnitude of primary production by phytoplankton in different estuaries from nutrient input (total available nitrogen and/or phosphorus) and to determine likely trophic status. In the model, primary production is strongly influenced by water residence times and relative light regimes. The model indicates that estuaries with low and moderate light levels are the least likely to show a biological response to nutrient inputs. Estuaries with a good light regime are likely to be sensitive to nutrient enrichment, and to show similar responses, mediated only by site-specific geomorphological features. Nixon's scale was used to describe the relative trophic status of estuaries, and to set nutrient and chlorophyll thresholds for assessing trophic status. Estuaries identified as being eutrophic may not show any signs of eutrophication. Additional attributes need to be considered to assess negative impacts. Here, likely detriment to the oxygen regime was considered, but is most applicable to areas of restricted exchange. Factors which limit phytoplankton growth under high nutrient conditions (water residence times and/or light availability) may favour the growth of other primary producers, such as macrophytes, which may have a negative impact on other biological communities. The assessment tool was developed for estuaries in England and Wales, based on a simple 3-category typology determined by geomorphology and relative light levels. Nixon's scale needs to be validated for estuaries in England and Wales, once more data are available on light levels and primary production.
NASA Astrophysics Data System (ADS)
Xue, Yan
The optimal growth and its relationship with the forecast skill of the Zebiak and Cane model are studied using a simple statistical model best fit to the original nonlinear model and local linear tangent models about idealized climatic states (the mean background and ENSO cycles in a long model run), and the actual forecast states, including two sets of runs using two different initialization procedures. The seasonally varying Markov model best fit to a suite of 3-year forecasts in a reduced EOF space (18 EOFs) fits the original nonlinear model reasonably well and has comparable or better forecast skill. The initial error growth in a linear evolution operator A is governed by the eigenvalues of A^{T}A, and the square roots of eigenvalues and eigenvectors of A^{T}A are named singular values and singular vectors. One dominant growing singular vector is found, and the optimal 6 month growth rate is largest for a (boreal) spring start and smallest for a fall start. Most of the variation in the optimal growth rate of the two forecasts is seasonal, attributable to the seasonal variations in the mean background, except that in the cold events it is substantially suppressed. It is found that the mean background (zero anomaly) is the most unstable state, and the "forecast IC states" are more unstable than the "coupled model states". One dominant growing singular vector is found, characterized by north-south and east -west dipoles, convergent winds on the equator in the eastern Pacific and a deepened thermocline in the whole equatorial belt. This singular vector is insensitive to initial time and optimization time, but its final pattern is a strong function of initial states. The ENSO system is inherently unpredictable for the dominant singular vector can amplify 5-fold to 24-fold in 6 months and evolve into the large scales characteristic of ENSO. However, the inherent ENSO predictability is only a secondary factor, while the mismatches between the model and data is a primary factor controlling the current forecast skill.
Models of cooperative dynamics from biomolecules to magnets
NASA Astrophysics Data System (ADS)
Mobley, David Lowell
This work details application of computer models to several biological systems (prion diseases and Alzheimer's disease) and a magnetic system. These share some common themes, which are discussed. Here, simple lattice-based models are applied to aggregation of misfolded protein in prion diseases like Mad Cow disease. These can explain key features of the diseases. The modeling is based on aggregation being essential in establishing the time-course of infectivity. Growth of initial aggregates is assumed to dominate the experimentally observed lag phase. Subsequent fission, regrowth, and fission set apart the exponential doubling phase in disease progression. We explore several possible modes of growth for 2-D aggregates and suggest the model providing the best explanation for the experimental data. We develop testable predictions from this model. Like prion disease, Alzheimer's disease (AD) is an amyloid disease characterized by large aggregates in the brain. However, evidence increasingly points away from these as the toxic agent and towards oligomers of the Abeta peptide. We explore one possible toxicity mechanism---insertion of Abeta into cell membranes and formation of harmful ion channels. We find that mutations in this peptide which cause familial Alzheimer's disease (FAD) also affect the insertion of this peptide into membranes in a fairly consistent way, suggesting that this toxicity mechanism may be relevant biologically. We find a particular inserted configuration which may be especially harmful and develop testable predictions to verify whether or not this is the case. Nucleation is an essential feature of our models for prion disease, in that it protects normal, healthy individuals from getting prion disease. Nucleation is important in many other areas, and we modify our lattice-based nucleation model to apply to a hysteretic magnetic system where nucleation has been suggested to be important. From a simple model, we find qualitative agreement with experiment, and make testable experimental predictions concerning time-dependence and temperature-dependence of the major hysteresis loop and reversal curves which have been experimentally verified. We argue why this model may be suitable for systems like these and explain implications for Ising-like models. We suggest implications for future modeling work. Finally, we present suggestions for future work in all three areas.
NASA Astrophysics Data System (ADS)
Butler, S. L.
2010-09-01
A porosity localizing instability occurs in compacting porous media that are subjected to shear if the viscosity of the solid matrix decreases with porosity ( Stevenson, 1989). This instability may have significant consequences for melt transport in regions of partial melt in the mantle and may significantly modify the effective viscosity of the asthenosphere ( Kohlstedt and Holtzman, 2009). Most analyses of this instability have been carried out assuming an imposed simple shear flow (e.g., Spiegelman, 2003; Katz et al., 2006; Butler, 2009). Pure shear can be realized in laboratory experiments and studying the instability in a pure shear flow allows us to test the generality of some of the results derived for simple shear and the flow pattern for pure shear more easily separates the effects of deformation from rotation. Pure shear flows may approximate flows near the tops of mantle plumes near earth's surface and in magma chambers. In this study, we present linear theory and nonlinear numerical model results for a porosity and strain-rate weakening compacting porous layer subjected to pure shear and we investigate the effects of buoyancy-induced oscillations. The linear theory and numerical model will be shown to be in excellent agreement. We will show that melt bands grow at the same angles to the direction of maximum compression as in simple shear and that buoyancy-induced oscillations do not significantly inhibit the porosity localizing instability. In a pure shear flow, bands parallel to the direction of maximum compression increase exponentially in wavelength with time. However, buoyancy-induced oscillations are shown to inhibit this increase in wavelength. In a simple shear flow, bands increase in wavelength when they are in the orientation for growth of the porosity localizing instability. Because the amplitude spectrum is always dominated by bands in this orientation, band wavelengths increase with time throughout simple shear simulations until the wavelength becomes similar to one compaction length. Once the wavelength becomes similar to one compaction length, the growth of the amplitude of the band slows and shorter wavelength bands that are increasing in amplitude at a greater rate take over. This may provide a mechanism to explain the experimental observation that band spacing is controlled by the compaction length ( Kohlstedt and Holtzman, 2009).
Crack Growth of a Titanium-Aluminide Alloy under Thermal-Mechanical Fatigue
1988-12-01
the elastic-plastic fracture mechanics ( EPFM ) relations such as the J-integral or crack tip opening displacement (CTOD) must be used. Much more work...has been done in the area of LEFM, using stress intensity factor range AK as a correlating factor, than in EPFM . No matter which type of analysis is...thus obvious that a simple linear summation model such as Heil’s might not be applicable to this material. Other damage mechanisms were then investigated
Water security, risk, and economic growth: Insights from a dynamical systems model
NASA Astrophysics Data System (ADS)
Dadson, Simon; Hall, Jim W.; Garrick, Dustin; Sadoff, Claudia; Grey, David; Whittington, Dale
2017-08-01
Investments in the physical infrastructure, human capital, and institutions needed for water resources management have been noteworthy in the development of most civilizations. These investments affect the economy in two distinct ways: (i) by improving the factor productivity of water in multiple economic sectors, especially those that are water intensive such as agriculture and energy and (ii) by reducing acute and chronic harmful effects of water-related hazards like floods, droughts, and water-related diseases. The need for capital investment to mitigate risks and promote economic growth is widely acknowledged, but prior conceptual work on the relationship between water-related investments and economic growth has focused on the productive and harmful roles of water in the economy independently. Here the two influences are combined using a simple, dynamical systems model of water-related investment, risk, and growth. In cases where initial water security is low, initial investment in water-related assets enables growth. Without such investment, losses due to water-related hazards exert a drag on economic growth and may create a poverty trap. The presence and location of the poverty trap is context-specific and depends on the exposure of productive water-related assets to water-related risk. Exogenous changes in water-related risk can potentially push an economy away from a growth path toward a poverty trap. Our investigation shows that an inverted-U-shaped investment relation between the level of investment in water security and the current level of water security leads to faster rates of growth than the alternatives that we consider here, and that this relation is responsible for the "S"-curve that is posited in the literature. These results illustrate the importance of accounting for environmental and health risks in economic models and offer insights for the design of robust policies for investment in water-related productive assets to manage risk, in the face of environmental change.
3D fold growth rates in transpressional tectonic settings
NASA Astrophysics Data System (ADS)
Frehner, Marcel
2015-04-01
Geological folds are inherently three-dimensional (3D) structures; hence, they also grow in 3D. In this study, fold growth in all three dimensions is quantified numerically using a finite-element algorithm for simulating deformation of Newtonian media in 3D. The presented study is an extension and generalization of the work presented in Frehner (2014), which only considered unidirectional layer-parallel compression. In contrast, the full range from strike slip settings (i.e., simple shear) to unidirectional layer-parallel compression is considered here by varying the convergence angle of the boundary conditions; hence the results are applicable to general transpressional tectonic settings. Only upright symmetrical single-layer fold structures are considered. The horizontal higher-viscous layer exhibits an initial point-like perturbation. Due to the mixed pure- and simple shear boundary conditions a mechanical buckling instability grows from this perturbation in all three dimensions, described by: Fold amplification (vertical growth): Fold amplification describes the growth from a fold shape with low limb-dip angle to a shape with higher limb-dip angle. Fold elongation (growth parallel to fold axis): Fold elongation describes the growth from a dome-shaped (3D) structure to a more cylindrical fold (2D). Sequential fold growth (growth perpendicular to fold axial plane): Sequential fold growth describes the growth of secondary (and further) folds adjacent to the initial isolated fold. The term 'lateral fold growth' is used as an umbrella term for both fold elongation and sequential fold growth. In addition, the orientation of the fold axis is tracked as a function of the convergence angle. Even though the absolute values of all three growth rates are markedly reduced with increasing simple-shear component at the boundaries, the general pattern of the quantified fold growth under the studied general-shear boundary conditions is surprisingly similar to the end-member case of unidirectional layer-parallel compression (Frehner, 2014). Fold growth rates in the two lateral directions are almost identical resulting in bulk fold structures with aspect ratios in map view close to 1. Fold elongation is continuous with increasing bulk deformation, while sequential fold growth exhibits jumps whenever a new sequential fold appears. Compared with the two lateral growth directions, fold amplification exhibits a slightly higher growth rate. The orientation of the fold axis has an angle equal to 1 2 of 90° minus the convergence angle; and this orientation is stable with increasing bulk deformation, i.e. the fold axis does not rotate with increasing general-shear deformation. For example, for simple-shear boundary conditions (convergence angle 0°) the fold axis is stable at an angle of 45° to the boundaries; for a convergence angle of 45° the fold axis is stable at an angle of 22.5° to the boundaries. REFERENCE: Frehner M., 2014: 3D fold growth rates, Terra Nova 26, 417-424, doi:10.1111/ter.12116.
A simple technique for correction of relapsed overjet.
Kakkirala, Neelima; Saxena, Ruchi
2014-01-01
Class III malocclusions are usually growth related discrepancies, which often become more severe when growth is completed Orthognathic surgery can be a part of the treatment plan, although a good number of cases can be treated non-surgically by camouflage treatment. The purpose of this report is to review the relapse tendency in patients treated non-surgically. A simple technique is described to combat one such post-treatment relapse condition in an adult patient who had undergone orthodontic treatment by extraction of a single lower incisor.
Multiscale simulation of xenon diffusion and grain boundary segregation in UO₂
Andersson, David A.; Tonks, Michael R.; Casillas, Luis; ...
2015-07-01
In light water reactor fuel, gaseous fission products segregate to grain boundaries, resulting in the nucleation and growth of large intergranular fission gas bubbles. The segregation rate is controlled by diffusion of fission gas atoms through the grains and interaction with the boundaries. Based on the mechanisms established from earlier density functional theory (DFT) and empirical potential calculations, diffusion models for xenon (Xe), uranium (U) vacancies and U interstitials in UO₂ have been derived for both intrinsic (no irradiation) and irradiation conditions. Segregation of Xe to grain boundaries is described by combining the bulk diffusion model with a model formore » the interaction between Xe atoms and three different grain boundaries in UO₂ (Σ5 tilt, Σ5 twist and a high angle random boundary), as derived from atomistic calculations. The present model does not attempt to capture nucleation or growth of fission gas bubbles at the grain boundaries. The point defect and Xe diffusion and segregation models are implemented in the MARMOT phase field code, which is used to calculate effective Xe and U diffusivities as well as to simulate Xe redistribution for a few simple microstructures.« less
Mathematical Modelling of the Infusion Test
NASA Astrophysics Data System (ADS)
Cieslicki, Krzysztof
2007-01-01
The objective of this paper was to improve the well established in clinical practice Marmarou model for intracranial volume-pressure compensation by adding the pulsatile components. It was demonstrated that complicated pulsation and growth in intracranial pressure during infusion test could be successfully modeled by the relatively simple analytical expression derived in this paper. The CSF dynamics were tested in 25 patients with clinical symptoms of hydrocephalus. Basing on the frequency spectrum of the patient's baseline pressure and identified parameters of CSF dynamic, for each patient an "ideal" infusion test curve free from artefacts and slow waves was simulated. The degree of correlation between simulated and real curves obtained from clinical observations gave insight into the adequacy of assumptions of Marmarou model. The proposed method of infusion tests analysis designates more exactly the value of the reference pressure, which is usually treated as a secondary and of uncertain significance. The properly identified value of the reference pressure decides on the degree of pulsation amplitude growth during IT, as well as on the value of elastance coefficient. The artificially generated tests with various pulsation components were also applied to examine the correctness of the used algorithm of identification of the original Marmarou model parameters.
Oscillations in a simple climate-vegetation model
NASA Astrophysics Data System (ADS)
Rombouts, J.; Ghil, M.
2015-05-01
We formulate and analyze a simple dynamical systems model for climate-vegetation interaction. The planet we consider consists of a large ocean and a land surface on which vegetation can grow. The temperature affects vegetation growth on land and the amount of sea ice on the ocean. Conversely, vegetation and sea ice change the albedo of the planet, which in turn changes its energy balance and hence the temperature evolution. Our highly idealized, conceptual model is governed by two nonlinear, coupled ordinary differential equations, one for global temperature, the other for vegetation cover. The model exhibits either bistability between a vegetated and a desert state or oscillatory behavior. The oscillations arise through a Hopf bifurcation off the vegetated state, when the death rate of vegetation is low enough. These oscillations are anharmonic and exhibit a sawtooth shape that is characteristic of relaxation oscillations, as well as suggestive of the sharp deglaciations of the Quaternary. Our model's behavior can be compared, on the one hand, with the bistability of even simpler, Daisyworld-style climate-vegetation models. On the other hand, it can be integrated into the hierarchy of models trying to simulate and explain oscillatory behavior in the climate system. Rigorous mathematical results are obtained that link the nature of the feedbacks with the nature and the stability of the solutions. The relevance of model results to climate variability on various timescales is discussed.
Oscillations in a simple climate-vegetation model
NASA Astrophysics Data System (ADS)
Rombouts, J.; Ghil, M.
2015-02-01
We formulate and analyze a simple dynamical systems model for climate-vegetation interaction. The planet we consider consists of a large ocean and a land surface on which vegetation can grow. The temperature affects vegetation growth on land and the amount of sea ice on the ocean. Conversely, vegetation and sea ice change the albedo of the planet, which in turn changes its energy balance and hence the temperature evolution. Our highly idealized, conceptual model is governed by two nonlinear, coupled ordinary differential equations, one for global temperature, the other for vegetation cover. The model exhibits either bistability between a vegetated and a desert state or oscillatory behavior. The oscillations arise through a Hopf bifurcation off the vegetated state, when the death rate of vegetation is low enough. These oscillations are anharmonic and exhibit a sawtooth shape that is characteristic of relaxation oscillations, as well as suggestive of the sharp deglaciations of the Quaternary. Our model's behavior can be compared, on the one hand, with the bistability of even simpler, Daisyworld-style climate-vegetation models. On the other hand, it can be integrated into the hierarchy of models trying to simulate and explain oscillatory behavior in the climate system. Rigorous mathematical results are obtained that link the nature of the feedbacks with the nature and the stability of the solutions. The relevance of model results to climate variability on various time scales is discussed.
Atuegwu, Nkiruka C; Arlinghaus, Lori R; Li, Xia; Chakravarthy, A Bapsi; Abramson, Vandana G; Sanders, Melinda E; Yankeelov, Thomas E
2013-01-01
Diffusion-weighted and dynamic contrast-enhanced magnetic resonance imaging (MRI) data of 28 patients were obtained pretreatment, after one cycle, and after completion of all cycles of neoadjuvant chemotherapy (NAC). For each patient at each time point, the tumor cell number was estimated using the apparent diffusion coefficient and the extravascular extracellular (ve) and plasma volume (vp) fractions. The proliferation/death rate was obtained using the number of tumor cells from the first two time points in conjunction with the logistic model of tumor growth, which was then used to predict tumor cellularity at the conclusion of NAC. The Pearson correlation coefficient between the predicted and the experimental number of tumor cells measured at the end of NAC was 0.81 (P = .0043). The proliferation rate estimated after the first cycle of therapy was able to separate patients who went on to achieve pathologic complete response from those who did not (P = .021) with a sensitivity and specificity of 82.4% and 72.7%, respectively. These data provide preliminary results indicating that incorporating readily available quantitative MRI data into a simple model of tumor growth can lead to potentially clinically relevant information for predicting an individual patient's response to NAC. PMID:23730404
Modeling the Effects of HER/ErbB1-3 Coexpression on Receptor Dimerization and Biological Response
Shankaran, Harish; Wiley, H. Steven; Resat, Haluk
2006-01-01
The human epidermal growth factor receptor (HER/ErbB) system comprises the epidermal growth factor receptor (EGFR/HER1) and three other homologs, namely HERs 2–4. This receptor system plays a critical role in cell proliferation and differentiation and receptor overexpression has been associated with poor prognosis in cancers of the epithelium. Here, we examine the effect of coexpressing varying levels of HERs 1–3 on the receptor dimerization patterns using a detailed kinetic model for HER/ErbB dimerization and trafficking. Our results indicate that coexpression of EGFR with HER2 or HER3 biases signaling to the cell surface and retards signal downregulation. In addition, simultaneous coexpression of HERs 1–3 leads to an abundance of HER2-HER3 heterodimers, which are known to be potent inducers of cell growth and transformation. Our new approach to use parameter dependence analysis in experimental design reveals that measurements of HER3 phosphorylation and HER2 internalization ratio may prove to be especially useful for the estimation of critical model parameters. Further, we examine the effect of receptor dimerization patterns on biological response using a simple phenomenological model. Results indicate that coexpression of EGFR with HER2 and HER3 at low to moderate levels may enable cells to match the response of a high HER2 expresser. PMID:16533841
Simple Signaling Molecules for Inductive Bone Regenerative Engineering
Nelson, Stephen J.; Deng, Meng; Sethuraman, Swaminathan; Doty, Stephen B.; Lo, Kevin W. H.; Khan, Yusuf M.; Laurencin, Cato T.
2014-01-01
With greater than 500,000 orthopaedic procedures performed in the United States each year requiring a bone graft, the development of novel graft materials is necessary. We report that some porous polymer/ceramic composite scaffolds possess intrinsic osteoinductivity as shown through their capacity to induce in vivo host osteoid mineralization and in vitro stem cell osteogenesis making them attractive synthetic bone graft substitutes. It was discovered that certain low crystallinity ceramics partially dissociate into simple signaling molecules (i.e., calcium and phosphate ions) that induce stem cells to endogenously produce their own osteoinductive proteins. Review of the literature has uncovered a variety of simple signaling molecules (i.e., gases, ions, and redox reagents) capable of inducing other desirable stem cell differentiation through endogenous growth factor production. Inductive simple signaling molecules, which we have termed inducerons, represent a paradigm shift in the field of regenerative engineering where they can be utilized in place of recombinant protein growth factors. PMID:25019622
A Simple and Robust Statistical Test for Detecting the Presence of Recombination
Bruen, Trevor C.; Philippe, Hervé; Bryant, David
2006-01-01
Recombination is a powerful evolutionary force that merges historically distinct genotypes. But the extent of recombination within many organisms is unknown, and even determining its presence within a set of homologous sequences is a difficult question. Here we develop a new statistic, Φw, that can be used to test for recombination. We show through simulation that our test can discriminate effectively between the presence and absence of recombination, even in diverse situations such as exponential growth (star-like topologies) and patterns of substitution rate correlation. A number of other tests, Max χ2, NSS, a coalescent-based likelihood permutation test (from LDHat), and correlation of linkage disequilibrium (both r2 and |D′|) with distance, all tend to underestimate the presence of recombination under strong population growth. Moreover, both Max χ2 and NSS falsely infer the presence of recombination under a simple model of mutation rate correlation. Results on empirical data show that our test can be used to detect recombination between closely as well as distantly related samples, regardless of the suspected rate of recombination. The results suggest that Φw is one of the best approaches to distinguish recurrent mutation from recombination in a wide variety of circumstances. PMID:16489234
Enhancing dendritic cell immunotherapy for melanoma using a simple mathematical model.
Castillo-Montiel, E; Chimal-Eguía, J C; Tello, J Ignacio; Piñon-Zaráte, G; Herrera-Enríquez, M; Castell-Rodríguez, A E
2015-06-09
The immunotherapy using dendritic cells (DCs) against different varieties of cancer is an approach that has been previously explored which induces a specific immune response. This work presents a mathematical model of DCs immunotherapy for melanoma in mice based on work by Experimental Immunotherapy Laboratory of the Medicine Faculty in the Universidad Autonoma de Mexico (UNAM). The model is a five delay differential equation (DDEs) which represents a simplified view of the immunotherapy mechanisms. The mathematical model takes into account the interactions between tumor cells, dendritic cells, naive cytotoxic T lymphocytes cells (inactivated cytotoxic cells), effector cells (cytotoxic T activated cytotoxic cells) and transforming growth factor β cytokine (T G F-β). The model is validated comparing the computer simulation results with biological trial results of the immunotherapy developed by the research group of UNAM. The results of the growth of tumor cells obtained by the control immunotherapy simulation show a similar amount of tumor cell population than the biological data of the control immunotherapy. Moreover, comparing the increase of tumor cells obtained from the immunotherapy simulation and the biological data of the immunotherapy applied by the UNAM researchers obtained errors of approximately 10 %. This allowed us to use the model as a framework to test hypothetical treatments. The numerical simulations suggest that by using more doses of DCs and changing the infusion time, the tumor growth decays compared with the current immunotherapy. In addition, a local sensitivity analysis is performed; the results show that the delay in time " τ", the maximal growth rate of tumor "r" and the maximal efficiency of tumor cytotoxic cells rate "aT" are the most sensitive model parameters. By using this mathematical model it is possible to simulate the growth of the tumor cells with or without immunotherapy using the infusion protocol of the UNAM researchers, to obtain a good approximation of the biological trials data. It is worth mentioning that by manipulating the different parameters of the model the effectiveness of the immunotherapy may increase. This last suggests that different protocols could be implemented by the Immunotherapy Laboratory of UNAM in order to improve their results.
Natural entropy production in an inflationary model for a polarized vacuum
NASA Astrophysics Data System (ADS)
Berman, Marcelo Samuel; Som, Murari M.
2007-08-01
Though entropy production is forbidden in standard FRW Cosmology, Berman and Som presented a simple inflationary model where entropy production by bulk viscosity, during standard inflation without ad hoc pressure terms can be accommodated with Robertson Walker’s metric, so the requirement that the early Universe be anisotropic is not essential in order to have entropy growth during inflationary phase, as we show. Entropy also grows due to shear viscosity, for the anisotropic case. The intrinsically inflationary metric that we propose can be thought of as defining a polarized vacuum, and leads directly to the desired effects without the need of introducing extra pressure terms.
Radiation pressure injection in laser-wakefield acceleration
NASA Astrophysics Data System (ADS)
Liu, Y. L.; Kuramitsu, Y.; Isayama, S.; Chen, S. H.
2018-01-01
We investigated the injection of electrons in laser-wakefield acceleration induced by a self-modulated laser pulse by a two dimensional particle-in-cell simulation. The localized electric fields and magnetic fields are excited by the counter-streaming flows on the surface of the ion bubble, owing to the Weibel or two stream like instability. The electrons are injected into the ion bubble from the sides of it and then accelerated by the wakefield. Contrary to the conventional wave breaking model, the injection of monoenergetic electrons are mainly caused by the electromagnetic process. A simple model was proposed to address the instability, and the growth rate was verified numerically and theoretically.
Farley, Jennifer R.; Sterritt, Jeffrey R.; Crane, Andrés B.; Wallace, Christopher S.
2017-01-01
Astroglia play key roles in the development of neurons, ranging from regulating neuron survival to promoting synapse formation, yet basic questions remain about whether astrocytes might be involved in forming the dendritic arbor. Here, we used cultured hippocampal neurons as a simple in vitro model that allowed dendritic growth and geometry to be analyzed quantitatively under conditions where the extent of interactions between neurons and astrocytes varied. When astroglia were proximal to neurons, dendrites and dendritic filopodia oriented toward them, but the general presence of astroglia significantly reduced overall dendrite growth. Further, dendritic arbors in partial physical contact with astroglia developed a pronounced pattern of asymmetrical growth, because the dendrites in direct contact were significantly smaller than the portion of the arbor not in contact. Notably, thrombospondin, the astroglial factor shown previously to promote synapse formation, did not inhibit dendritic growth. Thus, while astroglia promoted the formation of presynaptic contacts onto dendrites, dendritic growth was constrained locally within a developing arbor at sites where dendrites contacted astroglia. Taken together, these observations reveal influences on spatial orientation of growth as well as influences on morphogenesis of the dendritic arbor that have not been previously identified. PMID:28081563
Spatial elements of mortality risk in old-growth forests
Das, Adrian; Battles, John; van Mantgem, Phillip J.; Stephenson, Nathan L.
2008-01-01
For many species of long-lived organisms, such as trees, survival appears to be the most critical vital rate affecting population persistence. However, methods commonly used to quantify tree death, such as relating tree mortality risk solely to diameter growth, almost certainly do not account for important spatial processes. Our goal in this study was to detect and, if present, to quantify the relevance of such processes. For this purpose, we examined purely spatial aspects of mortality for four species, Abies concolor, Abies magnifica, Calocedrus decurrens, and Pinus lambertiana, in an old-growth conifer forest in the Sierra Nevada of California, USA. The analysis was performed using data from nine fully mapped long-term monitoring plots.In three cases, the results unequivocally supported the inclusion of spatial information in models used to predict mortality. For Abies concolor, our results suggested that growth rate may not always adequately capture increased mortality risk due to competition. We also found evidence of a facilitative effect for this species, with mortality risk decreasing with proximity to conspecific neighbors. For Pinus lambertiana, mortality risk increased with density of conspecific neighbors, in keeping with a mechanism of increased pathogen or insect pressure (i.e., a Janzen-Connell type effect). Finally, we found that models estimating risk of being crushed were strongly improved by the inclusion of a simple index of spatial proximity.Not only did spatial indices improve models, those improvements were relevant for mortality prediction. For P. lambertiana, spatial factors were important for estimation of mortality risk regardless of growth rate. For A. concolor, although most of the population fell within spatial conditions in which mortality risk was well described by growth, trees that died occurred outside those conditions in a disproportionate fashion. Furthermore, as stands of A. concolor become increasingly dense, such spatial factors are likely to become increasingly important. In general, models that fail to account for spatial pattern are at risk of failure as conditions change.
Pagès, Loïc; Picon-Cochard, Catherine
2014-10-01
Our objective was to calibrate a model of the root system architecture on several Poaceae species and to assess its value to simulate several 'integrated' traits measured at the root system level: specific root length (SRL), maximum root depth and root mass. We used the model ArchiSimple, made up of sub-models that represent and combine the basic developmental processes, and an experiment on 13 perennial grassland Poaceae species grown in 1.5-m-deep containers and sampled at two different dates after planting (80 and 120 d). Model parameters were estimated almost independently using small samples of the root systems taken at both dates. The relationships obtained for calibration validated the sub-models, and showed species effects on the parameter values. The simulations of integrated traits were relatively correct for SRL and were good for root depth and root mass at the two dates. We obtained some systematic discrepancies that were related to the slight decline of root growth in the last period of the experiment. Because the model allowed correct predictions on a large set of Poaceae species without global fitting, we consider that it is a suitable tool for linking root traits at different organisation levels. © 2014 INRA. New Phytologist © 2014 New Phytologist Trust.
A general model for the scaling of offspring size and adult size.
Falster, Daniel S; Moles, Angela T; Westoby, Mark
2008-09-01
Understanding evolutionary coordination among different life-history traits is a key challenge for ecology and evolution. Here we develop a general quantitative model predicting how offspring size should scale with adult size by combining a simple model for life-history evolution with a frequency-dependent survivorship model. The key innovation is that larger offspring are afforded three different advantages during ontogeny: higher survivorship per time, a shortened juvenile phase, and advantage during size-competitive growth. In this model, it turns out that size-asymmetric advantage during competition is the factor driving evolution toward larger offspring sizes. For simplified and limiting cases, the model is shown to produce the same predictions as the previously existing theory on which it is founded. The explicit treatment of different survival advantages has biologically important new effects, mainly through an interaction between total maternal investment in reproduction and the duration of competitive growth. This goes on to explain alternative allometries between log offspring size and log adult size, as observed in mammals (slope = 0.95) and plants (slope = 0.54). Further, it suggests how these differences relate quantitatively to specific biological processes during recruitment. In these ways, the model generalizes across previous theory and provides explanations for some differences between major taxa.
Universe without dark energy: Cosmic acceleration from dark matter-baryon interactions
NASA Astrophysics Data System (ADS)
Berezhiani, Lasha; Khoury, Justin; Wang, Junpu
2017-06-01
Cosmic acceleration is widely believed to require either a source of negative pressure (i.e., dark energy), or a modification of gravity, which necessarily implies new degrees of freedom beyond those of Einstein gravity. In this paper we present a third possibility, using only dark matter (DM) and ordinary matter. The mechanism relies on the coupling between dark matter and ordinary matter through an effective metric. Dark matter couples to an Einstein-frame metric, and experiences a matter-dominated, decelerating cosmology up to the present time. Ordinary matter couples to an effective metric that depends also on the DM density, in such a way that it experiences late-time acceleration. Linear density perturbations are stable and propagate with arbitrarily small sound speed, at least in the case of "pressure" coupling. Assuming a simple parametrization of the effective metric, we show that our model can successfully match a set of basic cosmological observables, including luminosity distance, baryon acoustic oscillation measurements, angular-diameter distance to last scattering, etc. For the growth history of density perturbations, we find an intriguing connection between the growth factor and the Hubble constant. To get a growth history similar to the Λ CDM prediction, our model predicts a higher H0, closer to the value preferred by direct estimates. On the flip side, we tend to overpredict the growth of structures whenever H0 is comparable to the Planck preferred value. The model also tends to predict larger redshift-space distortions at low redshift than Λ CDM .
A Simple Experimental Demonstration of Microbial Growth and Interaction.
ERIC Educational Resources Information Center
Wainwright, Milton
1988-01-01
Described is a simple, safe, and inexpensive experiment which allows secondary school pupils to observe how fungi and bacteria grow and interact with each other. Included are discussions of materials, methods, observations, and a historical comment. (Author/CW)
Is Climate Simulation in Growth Chambers Necessary?
Z.M. Wang; K.H. Johnsen; M.J. Lechowicz
1999-01-01
In the expression of their genetic potential as phenotypes, trees respond to environmental cues such as photoperiod, temperature and soil and atmospheric water. However, growth chamber experiments often utilize simple and standard environmental conditions that might not provide these important environmental signals. We conducted a study to compare seedling growth in...
Regulation of nitrogen metabolism by GATA zinc finger transcription factors in Yarrowia lipolytica
Pomraning, Kyle R.; Bredeweg, Erin L.; Baker, Scott E.; ...
2017-02-15
Here, fungi accumulate lipids in a manner dependent on the quantity and quality of the nitrogen source on which they are growing. In the oleaginous yeast Yarrowia lipolytica, growth on a complex source of nitrogen enables rapid growth and limited accumulation of neutral lipids, while growth on a simple nitrogen source promotes lipid accumulation in large lipid droplets. Here we examined the roles of nitrogen catabolite repression and its regulation by GATA zinc finger transcription factors on lipid metabolism in Y. lipolytica. Deletion of the GATA transcription factor genes gzf3 and gzf2 resulted in nitrogen source-specific growth defects and greatermore » accumulation of lipids when the cells were growing on a simple nitrogen source. Deletion of gzf1, which is most similar to activators of genes repressed by nitrogen catabolite repression in filamentous ascomycetes, did not affect growth on the nitrogen sources tested. We examined gene expression of wild-type and GATA transcription factor mutants on simple and complex nitrogen sources and found that expression of enzymes involved in malate metabolism, beta-oxidation, and ammonia utilization are strongly upregulated on a simple nitrogen source. Deletion of gzf3 results in overexpression of genes with GATAA sites in their promoters, suggesting that it acts as a repressor, while gzf2 is required for expression of ammonia utilization genes but does not grossly affect the transcription level of genes predicted to be controlled by nitrogen catabolite repression. Both GATA transcription factor mutants exhibit decreased expression of genes controlled by carbon catabolite repression via the repressor mig1, including genes for beta-oxidation, highlighting the complex interplay between regulation of carbon, nitrogen, and lipid metabolism.« less
Regulation of nitrogen metabolism by GATA zinc finger transcription factors in Yarrowia lipolytica
DOE Office of Scientific and Technical Information (OSTI.GOV)
Pomraning, Kyle R.; Bredeweg, Erin L.; Baker, Scott E.
Here, fungi accumulate lipids in a manner dependent on the quantity and quality of the nitrogen source on which they are growing. In the oleaginous yeast Yarrowia lipolytica, growth on a complex source of nitrogen enables rapid growth and limited accumulation of neutral lipids, while growth on a simple nitrogen source promotes lipid accumulation in large lipid droplets. Here we examined the roles of nitrogen catabolite repression and its regulation by GATA zinc finger transcription factors on lipid metabolism in Y. lipolytica. Deletion of the GATA transcription factor genes gzf3 and gzf2 resulted in nitrogen source-specific growth defects and greatermore » accumulation of lipids when the cells were growing on a simple nitrogen source. Deletion of gzf1, which is most similar to activators of genes repressed by nitrogen catabolite repression in filamentous ascomycetes, did not affect growth on the nitrogen sources tested. We examined gene expression of wild-type and GATA transcription factor mutants on simple and complex nitrogen sources and found that expression of enzymes involved in malate metabolism, beta-oxidation, and ammonia utilization are strongly upregulated on a simple nitrogen source. Deletion of gzf3 results in overexpression of genes with GATAA sites in their promoters, suggesting that it acts as a repressor, while gzf2 is required for expression of ammonia utilization genes but does not grossly affect the transcription level of genes predicted to be controlled by nitrogen catabolite repression. Both GATA transcription factor mutants exhibit decreased expression of genes controlled by carbon catabolite repression via the repressor mig1, including genes for beta-oxidation, highlighting the complex interplay between regulation of carbon, nitrogen, and lipid metabolism.« less
NASA Astrophysics Data System (ADS)
Multsch, Sebastian; Kraft, Philipp; Frede, Hans-Georg; Breuer, Lutz
2010-05-01
Today, crop models have a widespread application in natural sciences, because plant growth interacts and modifies the environment. Transport processes involve water and nutrient uptake from the saturated and unsaturated zone in the pedosphere. Turnover processes include the conversion of dead root biomass into organic matter. Transpiration and the interception of radiation influence the energy exchange between atmosphere and biosphere. But many more feedback mechanisms might be of interest, including erosion, soil compaction or trace gas exchanges. Most of the existing crop models have a closed structure and do not provide interfaces or code design elements for easy data transfer or process exchange with other models during runtime. Changes in the model structure, the inclusion of alternative process descriptions or the implementation of additional functionalities requires a lot of coding. The same is true if models are being upscaled from field to landscape or catchment scale. We therefore conclude that future integrated model developments would benefit from a model structure that has the following requirements: replaceability, expandability and independency. In addition to these requirements we also propose the interactivity of models, which means that models that are being coupled are highly interacting and depending on each other, i.e. the model should be open for influences from other independent models and react on influences directly. Hence, a model which consists of building blocks seems to be reasonable. The aim of the study is the presentation of the new crop model type, the plant growth model framework, PMF. The software concept refers to an object-oriented approach, which is developed with the Unified Modeling Language (UML). The model is implemented with Python, a high level object-oriented programming language. The integration of the models with a setup code enables the data transfer on the computer memory level and direct exchange of information about changing boundary conditions. The crop model concept refers to two main elements. A plant model, which represents an abstract network of plant organs and processes and a process library, which holds mathematical solutions for the growth processes. Growth processes were mainly taken from existing, well known crop models such as SUCROS and CERES. The crop specific properties of root architecture are described based on a maximum rooting depth and a vertical growth rate. The biomass distribution depends on an interactive allocation process due to the soil layers with a daily time step. In order to show the performance and capabilities of PMF, the model is coupled with the Catchment Modeling Framework (CMF) and the simple nitrogen mineralization model DeComp. The main feature of the integrated model set up is the interaction between root growth, water uptake and nitrogen supply of the soil. We show a virtual case study on the hillslope scale and spatially dependence of water and nitrogen stress based on topographic position and seasonal development.
Relaxation processes in a low-order three-dimensional magnetohydrodynamics model
NASA Technical Reports Server (NTRS)
Stribling, Troy; Matthaeus, William H.
1991-01-01
The time asymptotic behavior of a Galerkin model of 3D magnetohydrodynamics (MHD) has been interpreted using the selective decay and dynamic alignment relaxation theories. A large number of simulations has been performed that scan a parameter space defined by the rugged ideal invariants, including energy, cross helicity, and magnetic helicity. It is concluded that time asymptotic state can be interpreted as a relaxation to minimum energy. A simple decay model, based on absolute equilibrium theory, is found to predict a mapping of initial onto time asymptotic states, and to accurately describe the long time behavior of the runs when magnetic helicity is present. Attention is also given to two processes, operating on time scales shorter than selective decay and dynamic alignment, in which the ratio of kinetic to magnetic energy relaxes to values 0(1). The faster of the two processes takes states initially dominant in magnetic energy to a state of near-equipartition between kinetic and magnetic energy through power law growth of kinetic energy. The other process takes states initially dominant in kinetic energy to the near-equipartitioned state through exponential growth of magnetic energy.
Christiansson, Anders
2017-08-01
This Research Communication explores the usefulness of predictive modelling to explain bacterial behaviour during cooling. A simple dynamic lag phase model was developed and validated. The model takes into account the effect of the cooling profile on the lag phase and growth in bulk tank milk. The time before the start of cooling was the most critical and should not exceed 1 h. The cooling rate between 30 and approximately 10 °C was the second most critical period. Cooling from 30 to 10 °C within 2 h ensured minimal growth of psychrotrophic bacteria in the milk. The cooling rate between 10 and 4 °C (the slowest phase of cooling) was of surprisingly little importance. Given a normal cooling profile to 10 °C, several hours of prolonged cooling time made practically no difference in psychrotrophic counts. This behaviour can be explained by the time/temperature dependence of the work needed by the bacteria to complete the lag phase at low temperature. For milk quality advisors, it is important to know that slow cooling below 10 °C does not result in high total counts of bacteria. In practice, slow cooling is occasionally found at farms with robotic milking. However, when comparing psychrotrophic growth in bulk milk tanks designed for robotic milking or conventional milking, the model predicted less growth for robotic milking for identical cooling profiles. It is proposed that due to the different rates of milk entering the tank, fewer bacteria will exit the lag phase during robotic milking and they will be more diluted than in conventional milking systems. At present, there is no international standard that specifies the cooling profile in robotic systems. The information on the insignificant effect of the cooling rate below 10 °C may be useful in the development of a standard.
Value of the distant future: Model-independent results
NASA Astrophysics Data System (ADS)
Katz, Yuri A.
2017-01-01
This paper shows that the model-independent account of correlations in an interest rate process or a log-consumption growth process leads to declining long-term tails of discount curves. Under the assumption of an exponentially decaying memory in fluctuations of risk-free real interest rates, I derive the analytical expression for an apt value of the long run discount factor and provide a detailed comparison of the obtained result with the outcome of the benchmark risk-free interest rate models. Utilizing the standard consumption-based model with an isoelastic power utility of the representative economic agent, I derive the non-Markovian generalization of the Ramsey discounting formula. Obtained analytical results allowing simple calibration, may augment the rigorous cost-benefit and regulatory impact analysis of long-term environmental and infrastructure projects.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ribas, Álvaro; Espaillat, Catherine C.; Macías, Enrique
Far-infrared and (sub)millimeter fluxes can be used to study dust in protoplanetary disks, the building blocks of planets. Here, we combine observations from the Herschel Space Observatory with ancillary data of 284 protoplanetary disks in the Taurus, Chamaeleon I, and Ophiuchus star-forming regions, covering from the optical to mm/cm wavelengths. We analyze their spectral indices as a function of wavelength and determine their (sub)millimeter slopes when possible. Most disks display observational evidence of grain growth, in agreement with previous studies. No correlation is found between other tracers of disk evolution and the millimeter spectral indices. A simple disk model ismore » used to fit these sources, and we derive posterior distributions for the optical depth at 1.3 mm and 10 au, the disk temperature at this same radius, and the dust opacity spectral index β . We find the fluxes at 70 μ m to correlate strongly with disk temperatures at 10 au, as derived from these simple models. We find tentative evidence for spectral indices in Chamaeleon I being steeper than those of disks in Taurus/Ophiuchus, although more millimeter observations are needed to confirm this trend and identify its possible origin. Additionally, we determine the median spectral energy distribution of each region and find them to be similar across the entire wavelength range studied, possibly due to the large scatter in disk properties and morphologies.« less
Light quality and temperature effects on antirrhinum growth and development
Khattak, Abdul Mateen; Pearson, Simon
2005-01-01
An experiment was carried out to examine the effects of light quality on the growth and development of antirrhinum under three different temperatures 19 °C, 24 °C and 27 °C in glasshouses. Five different colour filters (i.e. ‘Red absorbing’, ‘Blue absorbing’, ‘Blue and Red absorbing’ and two ‘partially Blue absorbing’ materials) were tested, with one clear polythene as a control. Plant height, internode length and leaf area were significantly affected by the spectral filters as well as the temperature. Analysis of color filter’s effect on presumed photoreceptors to exist indicated that antirrhinum plant height was regulated by the action of a blue acting photoreceptor (BAP) and not the phytochrome. There was no evidence for an effect of phytochrome or BAP on time to flowering, however, increasing temperature levels effectively decreased the time to flowering. To predict the effects of different spectral qualities and temperature, simple models were created from data on plant height, internode length and time to flowering. These models were then applied to simulate the potential benefits of spectral filters and temperature in manipulation of growth control and flowering in antirrhinum. PMID:15633247
Income distribution trends and future food demand.
Cirera, Xavier; Masset, Edoardo
2010-09-27
This paper surveys the theoretical literature on the relationship between income distribution and food demand, and identifies main gaps of current food modelling techniques that affect the accuracy of food demand projections. At the heart of the relationship between income distribution and food demand is Engel's law. Engel's law establishes that as income increases, households' demand for food increases less than proportionally. A consequence of this law is that the particular shape of the distribution of income across individuals and countries affects the rate of growth of food demand. Our review of the literature suggests that existing models of food demand fail to incorporate the required Engel flexibility when (i) aggregating different food budget shares among households; and (ii) changing budget shares as income grows. We perform simple simulations to predict growth in food demand under alternative income distribution scenarios taking into account nonlinearity of food demand. Results suggest that (i) distributional effects are to be expected from changes in between-countries inequality, rather than within-country inequality; and (ii) simulations of an optimistic and a pessimistic scenario of income inequality suggest that world food demand in 2050 would be 2.7 per cent higher and 5.4 per cent lower than distributional-neutral growth, respectively.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Dornstetter, Jean-Christophe; LPICM-CNRS, Ecole Polytechnique, 91128 Palaiseau; Bruneau, Bastien
2014-06-21
We report on the growth of microcrystalline silicon films from the dissociation of SiF{sub 4}/H{sub 2}/Ar gas mixtures. For this growth chemistry, the formation of HF molecules provides a clear signature of the amorphous to microcrystalline growth transition. Depositing films from silicon tetrafluoride requires the removal of F produced by SiF{sub 4} dissociation, and this removal is promoted by the addition of H{sub 2} which strongly reacts with F to form HF molecules. At low H{sub 2} flow rates, the films grow amorphous as all the available hydrogen is consumed to form HF. Above a critical flow rate, corresponding tomore » the full removal of F, microcrystalline films are produced as there is an excess of atomic hydrogen in the plasma. A simple yet accurate phenomenological model is proposed to explain the SiF{sub 4}/H{sub 2} plasma chemistry in accordance with experimental data. This model provides some rules of thumb to achieve high deposition rates for microcrystalline silicon, namely, that increased RF power must be balanced by an increased H{sub 2} flow rate.« less
Neuritogenesis: A model for space radiation effects on the central nervous system
NASA Technical Reports Server (NTRS)
Vazquez, M. E.; Broglio, T. M.; Worgul, B. V.; Benton, E. V.
1994-01-01
Pivotal to the astronauts' functional integrity and survival during long space flights are the strategies to deal with space radiations. The majority of the cellular studies in this area emphasize simple endpoints such as growth related events which, although useful to understand the nature of primary cell injury, have poor predictive value for extrapolation to more complex tissues such as the central nervous system (CNS). In order to assess the radiation damage on neural cell populations, we developed an in vitro model in which neuronal differentiation, neurite extension, and synaptogenesis occur under controlled conditions. The model exploits chick embryo neural explants to study the effects of radiations on neuritogenesis. In addition, neurobiological problems associated with long-term space flights are discussed.
NASA Astrophysics Data System (ADS)
Heumann, B. W.; Guichard, F.; Seaquist, J. W.
2005-05-01
The HABSEED model uses remote sensing derived NPP as a surrogate for habitat quality as the driving mechanism for population growth and local seed dispersal. The model has been applied to the Sahel region of Africa. Results show that the functional response of plants to habitat quality alters population distribution. Plants more tolerant of medium quality habitat have greater distributions to the North while plants requiring only the best habitat are limited to the South. For all functional response types, increased seed production results in diminishing returns. Functional response types have been related to life history tradeoffs and r-K strategies based on the results. Results are compared to remote sensing derived vegetation land cover.
ERIC Educational Resources Information Center
Metz, James
2001-01-01
Describes an activity designed to help students connect the ideas of linear growth and exponential growth through graphs of the future value of accounts that earn simple interest and accounts that earn compound interest. Includes worksheets and solutions. (KHR)
Expression of and secretion through the Aeromonas salmonicida type III secretion system.
Ebanks, Roger O; Knickle, Leah C; Goguen, Michel; Boyd, Jessica M; Pinto, Devanand M; Reith, Michael; Ross, Neil W
2006-05-01
Aeromonas salmonicida subsp. salmonicida is the aetiological agent of furunculosis, a disease of farmed and wild salmonids. The type III secretion system (TTSS) is one of the primary virulence factors in A. salmonicida. Using a combination of differential proteomic analysis and reverse transcriptase (RT)-PCR, it is shown that A. salmonicida A449 induces the expression of TTSS proteins at 28 degrees C, but not at its more natural growth temperature of 17 degrees C. More modest increases in expression occur at 24 degrees C. This temperature-induced up-regulation of the TTSS in A. salmonicida A449 occurs within 30 min of a growth temperature increase from 16 to 28 degrees C. Growth conditions such as low-iron, low pH, low calcium, growth within the peritoneal cavity of salmon and growth to high cell densities do not induce the expression of the TTSS in A. salmonicida A449. The only other known growth condition that induces expression of the TTSS is growth of the bacterium at 16 degrees C in salt concentrations ranging from 0.19 to 0.38 M NaCl. It is also shown that growth at 28 degrees C followed by exposure to low calcium results in the secretion of one of the TTSS effector proteins. This study presents a simple in vitro model for the expression of TTSS proteins in A. salmonicida.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Yang, Jianming; Yin, Liang; Lessner, Faith H.
Anoxygenic purple phototrophic bacteria have served as important models for studies of photophosphorylation. The pigment-protein complexes responsible for converting light energy to ATP are relatively simple and these bacteria can grow heterotrophically under aerobic conditions, thus allowing for the study of mutants defective in photophosphorylation. In the past, genes responsible for anoxygenic phototrophic growth have been identified in a number of different bacterial species. Here we systematically studied the genetic basis for this metabolism by using Tn-seq to identify genes essential for the anaerobic growth of the purple bacterium Rhodopseudomonas palustris on acetate in light. We identified 171 genes requiredmore » for growth in this condition, 35 of which are annotated as photosynthesis genes. Among these are a few new genes not previously shown to be essential for phototrophic growth. We verified the essentiality of many of the genes we identified by analyzing the phenotypes of mutants we generated by Tn mutagenesis that had altered pigmentation. We used directed mutagenesis to verify that the R. palustris NADH:quinone oxidoreductase complex IE is essential for phototrophic growth. As a complement to the genetic data, we carried out proteomics experiments in which we found that 429 proteins were present in significantly higher amounts in cells grown anaerobically in light compared to aerobically. Among these were proteins encoded by subset of the phototrophic growth-essential genes.« less
Side, Domenico Delle; Nassisi, Vincenzo; Pennetta, Cecilia; Alifano, Pietro; Di Salvo, Marco; Talà, Adelfia; Chechkin, Aleksei; Seno, Flavio
2017-01-01
We present an effective dynamical model for the onset of bacterial bioluminescence, one of the most studied quorum sensing-mediated traits. Our model is built upon simple equations that describe the growth of the bacterial colony, the production and accumulation of autoinducer signal molecules, their sensing within bacterial cells, and the ensuing quorum activation mechanism that triggers bioluminescent emission. The model is directly tested to quantitatively reproduce the experimental distributions of photon emission times, previously measured for bacterial colonies of Vibrio jasicida, a luminescent bacterium belonging to the Harveyi clade, growing in a highly drying environment. A distinctive and novel feature of the proposed model is bioluminescence ‘quenching’ after a given time elapsed from activation. Using an advanced fitting procedure based on the simulated annealing algorithm, we are able to infer from the experimental observations the biochemical parameters used in the model. Such parameters are in good agreement with the literature data. As a further result, we find that, at least in our experimental conditions, light emission in bioluminescent bacteria appears to originate from a subtle balance between colony growth and quorum activation due to autoinducers diffusion, with the two phenomena occurring on the same time scale. This finding is consistent with a negative feedback mechanism previously reported for Vibrio harveyi. PMID:29308273
NASA Astrophysics Data System (ADS)
Anderson, Thomas R.; Hessen, Dag O.; Mitra, Aditee; Mayor, Daniel J.; Yool, Andrew
2013-09-01
The performance of four contemporary formulations describing trophic transfer, which have strongly contrasting assumptions as regards the way that consumer growth is calculated as a function of food C:N ratio and in the fate of non-limiting substrates, was compared in two settings: a simple steady-state ecosystem model and a 3D biogeochemical general circulation model. Considerable variation was seen in predictions for primary production, transfer to higher trophic levels and export to the ocean interior. The physiological basis of the various assumptions underpinning the chosen formulations is open to question. Assumptions include Liebig-style limitation of growth, strict homeostasis in zooplankton biomass, and whether excess C and N are released by voiding in faecal pellets or via respiration/excretion post-absorption by the gut. Deciding upon the most appropriate means of formulating trophic transfer is not straightforward because, despite advances in ecological stoichiometry, the physiological mechanisms underlying these phenomena remain incompletely understood. Nevertheless, worrying inconsistencies are evident in the way in which fundamental transfer processes are justified and parameterised in the current generation of marine ecosystem models, manifested in the resulting simulations of ocean biogeochemistry. Our work highlights the need for modellers to revisit and appraise the equations and parameter values used to describe trophic transfer in marine ecosystem models.
Mathematical Modeling of Allelopathy. III. A Model for Curve-Fitting Allelochemical Dose Responses
Liu, De Li; An, Min; Johnson, Ian R.; Lovett, John V.
2003-01-01
Bioassay techniques are often used to study the effects of allelochemicals on plant processes, and it is generally observed that the processes are stimulated at low allelochemical concentrations and inhibited as the concentrations increase. A simple empirical model is presented to analyze this type of response. The stimulation-inhibition properties of allelochemical-dose responses can be described by the parameters in the model. The indices, p% reductions, are calculated to assess the allelochemical effects. The model is compared with experimental data for the response of lettuce seedling growth to Centaurepensin, the olfactory response of weevil larvae to α-terpineol, and the responses of annual ryegrass (Lolium multiflorum Lam.), creeping red fescue (Festuca rubra L., cv. Ensylva), Kentucky bluegrass (Poa pratensis L., cv. Kenblue), perennial ryegrass (L. perenne L., cv. Manhattan), and Rebel tall fescue (F. arundinacea Schreb) seedling growth to leachates of Rebel and Kentucky 31 tall fescue. The results show that the model gives a good description to observations and can be used to fit a wide range of dose responses. Assessments of the effects of leachates of Rebel and Kentucky 31 tall fescue clearly differentiate the properties of the allelopathic sources and the relative sensitivities of indicators such as the length of root and leaf. PMID:19330111
Side, Domenico Delle; Nassisi, Vincenzo; Pennetta, Cecilia; Alifano, Pietro; Di Salvo, Marco; Talà, Adelfia; Chechkin, Aleksei; Seno, Flavio; Trovato, Antonio
2017-12-01
We present an effective dynamical model for the onset of bacterial bioluminescence, one of the most studied quorum sensing-mediated traits. Our model is built upon simple equations that describe the growth of the bacterial colony, the production and accumulation of autoinducer signal molecules, their sensing within bacterial cells, and the ensuing quorum activation mechanism that triggers bioluminescent emission. The model is directly tested to quantitatively reproduce the experimental distributions of photon emission times, previously measured for bacterial colonies of Vibrio jasicida , a luminescent bacterium belonging to the Harveyi clade, growing in a highly drying environment. A distinctive and novel feature of the proposed model is bioluminescence 'quenching' after a given time elapsed from activation. Using an advanced fitting procedure based on the simulated annealing algorithm, we are able to infer from the experimental observations the biochemical parameters used in the model. Such parameters are in good agreement with the literature data. As a further result, we find that, at least in our experimental conditions, light emission in bioluminescent bacteria appears to originate from a subtle balance between colony growth and quorum activation due to autoinducers diffusion, with the two phenomena occurring on the same time scale. This finding is consistent with a negative feedback mechanism previously reported for Vibrio harveyi .
A simple phenomenological model for grain clustering in turbulence
NASA Astrophysics Data System (ADS)
Hopkins, Philip F.
2016-01-01
We propose a simple model for density fluctuations of aerodynamic grains, embedded in a turbulent, gravitating gas disc. The model combines a calculation for the behaviour of a group of grains encountering a single turbulent eddy, with a hierarchical approximation of the eddy statistics. This makes analytic predictions for a range of quantities including: distributions of grain densities, power spectra and correlation functions of fluctuations, and maximum grain densities reached. We predict how these scale as a function of grain drag time ts, spatial scale, grain-to-gas mass ratio tilde{ρ }, strength of turbulence α, and detailed disc properties. We test these against numerical simulations with various turbulence-driving mechanisms. The simulations agree well with the predictions, spanning ts Ω ˜ 10-4-10, tilde{ρ }˜ 0{-}3, α ˜ 10-10-10-2. Results from `turbulent concentration' simulations and laboratory experiments are also predicted as a special case. Vortices on a wide range of scales disperse and concentrate grains hierarchically. For small grains this is most efficient in eddies with turnover time comparable to the stopping time, but fluctuations are also damped by local gas-grain drift. For large grains, shear and gravity lead to a much broader range of eddy scales driving fluctuations, with most power on the largest scales. The grain density distribution has a log-Poisson shape, with fluctuations for large grains up to factors ≳1000. We provide simple analytic expressions for the predictions, and discuss implications for planetesimal formation, grain growth, and the structure of turbulence.
Island dynamics and anisotropy during vapor phase epitaxy of m-plane GaN
Perret, Edith; Xu, Dongwei; Highland, M. J.; ...
2017-12-04
Using in situ grazing-incidence x-ray scattering, we have measured the diffuse scattering from islands that form during layer-by-layer growth of GaN by metal-organic vapor phase epitaxy on the (10more » $$\\bar{1}$$0) m-plane surface. The diffuse scattering is extended in the (0001) in-plane direction in reciprocal space, indicating a strong anisotropy with islands elongated along [1$$\\bar{2}$$10] and closely spaced along [0001]. This is confirmed by atomic force microscopy of a quenched sample. Islands were characterized as a function of growth rate F and temperature. Furthermore, the island spacing along [0001] observed during the growth of the first monolayer obeys a power-law dependence on growth rate F -n, with an exponent n=0.25±0.02. Our results are in agreement with recent kinetic Monte Carlo simulations, indicating that elongated islands result from the dominant anisotropy in step edge energy and not from surface diffusion anisotropy. The observed power-law exponent can be explained using a simple steady-state model, which gives n = 1/4.« less
Mitra, Aditee; Flynn, Kevin J
2007-05-01
Ingestion kinetics of animals are controlled by both external food availability and feedback from the quantity of material already within the gut. The latter varies with gut transit time (GTT) and digestion of the food. Ingestion, assimilation efficiency, and thus, growth dynamics are not related in a simple fashion. For the first time, the important linkage between these processes and GTT is demonstrated; this is achieved using a biomass-based, mechanistic multinutrient model fitted to experimental data for zooplankton growth dynamics when presented with food items of varying quality (stoichiometric composition) or quantity. The results show that trophic transfer dynamics will vary greatly between the extremes of feeding on low-quantity/high-quality versus high-quantity/low-quality food; these conditions are likely to occur in nature. Descriptions of consumer behavior that assume a constant relationship between the kinetics of grazing and growth irrespective of food quality and/or quantity, with little or no recognition of the combined importance of these factors on consumer behavior, may seriously misrepresent consumer activity in dynamic situations.
Influence of lattice orientation on growth and structure of graphene on Cu(001)
Wofford, Joseph M.; Nie, Shu; Thürmer, Konrad; ...
2015-03-31
We have used low-energy electron microscopy (LEEM) and diffraction (LEED) to examine the significance of lattice orientation in graphene growth on Cu(0 0 1). Individual graphene domains undergo anisotropic growth on the Cu surface, and develop into lens shapes with their long axes roughly aligned with Cu <1 0 0> in-plane directions. Furthermore, the long axis of a lens-shaped domain is only rarely oriented along a C <1 1> direction, suggesting that carbon attachment at “zigzag” graphene island edges is unfavorable. A kink-mediated adatom attachment process is consistent with the behavior observed here and reported in the literature. Likewise, themore » details of the ridged moiré pattern formed by the superposition of the graphene lattice on the (0 0 1) Cu surface also evolve with the graphene lattice orientation, and are predicted well by a simple geometric model. Managing the kink-mediated growth mode of graphene on Cu(0 0 1) will be necessary for the continued improvement of this graphene synthesis technique.« less
Ethanol inhibition kinetics of Kluyveromyces marxianus grown on Jerusalem artichoke juice
DOE Office of Scientific and Technical Information (OSTI.GOV)
Bajpai, P.; Margaritis, A.
1982-12-01
The kinetics of ethanol inhibition on cell growth and ethanol production by Kluyveromyces marxianus UCD (FST) 55-82 were studied during batch growth. The liquid medium contained 10% (weight/volume) inulin-type sugars derived from an extract of Jerusalem artichoke (Helianthus tuberosus) tubers, supplemented with small amounts of Tween 80, oleic acid, and corn steep liquor. Initial ethanol concentrations ranging from 0 to 80 g/liter in the liquid medium were used to study the inhibitory effect of ethanol on the following parameters: maximum specific growth rate (mu max), cell and ethanol yields, and sugar utilization. It was found that as the initial ethanolmore » concentration increased from 0 to 80 g/liter, and maximum specific growth rate of K. marxianus cells decreased from 0.42 to 0.09/hour, whereas the ethanol and cell yields and sugar utilization remained almost constant. A simple kinetic model was used to correlate the mu max results and the rates of cell and ethanol production, and the appropriate constants were evaluated. (Refs. 22).« less
Hydro-Thermal Fatigue Resistance Measurements on Polymer Interfaces
NASA Astrophysics Data System (ADS)
Gurumurthy, Charan K.; Kramer, Edward J.; Hui, Chung-Yuen
1998-03-01
We have developed a new technique based on a fiber optic displacement sensor for rapid determination of hydro-thermal fatigue crack growth rate per cycle (da/dN) of an epoxy/polyimide interface used in flip chip attach microelectronic assembly. The sample is prepared as a trilayered cantilever beam by capillary flow of the epoxy underfill over a polyimide coated metallic beam. During hydro-thermal cycling the crack growth along the interface (from the free end) changes the displacement of this end of the beam and we measure the free end displacement at the lowest temperature in each hydro-thermal cycle. The change in beam displacement is then converted into crack growth rate (da/dN). da/dN depends on the maximum change in the strain energy release rate of the crack and the phase angle in each cycle. The relation between da/dN and maximum strain energy release rate characterizes the fatigue crack growth resistance of the interface. We have developed and used a simple model anhydride cured and a commercially available PMDA/ODA passivation for this study.
Island dynamics and anisotropy during vapor phase epitaxy of m-plane GaN
DOE Office of Scientific and Technical Information (OSTI.GOV)
Perret, Edith; Xu, Dongwei; Highland, M. J.
Using in situ grazing-incidence x-ray scattering, we have measured the diffuse scattering from islands that form during layer-by-layer growth of GaN by metal-organic vapor phase epitaxy on the (10more » $$\\bar{1}$$0) m-plane surface. The diffuse scattering is extended in the (0001) in-plane direction in reciprocal space, indicating a strong anisotropy with islands elongated along [1$$\\bar{2}$$10] and closely spaced along [0001]. This is confirmed by atomic force microscopy of a quenched sample. Islands were characterized as a function of growth rate F and temperature. Furthermore, the island spacing along [0001] observed during the growth of the first monolayer obeys a power-law dependence on growth rate F -n, with an exponent n=0.25±0.02. Our results are in agreement with recent kinetic Monte Carlo simulations, indicating that elongated islands result from the dominant anisotropy in step edge energy and not from surface diffusion anisotropy. The observed power-law exponent can be explained using a simple steady-state model, which gives n = 1/4.« less
NASA Technical Reports Server (NTRS)
Tarney, J.; Wyborn, L. E. A.; Sheraton, J. W.; Wyborn, D.
1988-01-01
Critical to models for continental crust growth and recycling are the processes through which crustal growth takes place. In particular, it is important to know whether these processes have changed fundamentally with time in response to the earth's thermal evolution, and whether the crustal compositions generated are compatible with crustal remobilization, crustal recycling, or represent primary additions. There are some significant and consistent differences in the major and trace element compositions of crustal components with time which have important implications for crustal growth processes. These will be illustrated with reference to Archean rocks from a number of shield areas, Proterozoic granitoids from Australia and elsewhere, Palaeozoic granitoids from Australia and Scotland, and Mesozoic - recent granitoids from present continental margin belts. Surprisingly some rather simple and consistent patterns energy using this technique. There are then significant differences in compositions of granitoid crustal additions throughout geological time, with a particular type of granitoid apparently dominating a particular time period. This implies that the tectonic processes giving rise to granite generation have changed in response to the earth's thermal evolution.
Mesoscopic model for binary fluids
NASA Astrophysics Data System (ADS)
Echeverria, C.; Tucci, K.; Alvarez-Llamoza, O.; Orozco-Guillén, E. E.; Morales, M.; Cosenza, M. G.
2017-10-01
We propose a model for studying binary fluids based on the mesoscopic molecular simulation technique known as multiparticle collision, where the space and state variables are continuous, and time is discrete. We include a repulsion rule to simulate segregation processes that does not require calculation of the interaction forces between particles, so binary fluids can be described on a mesoscopic scale. The model is conceptually simple and computationally efficient; it maintains Galilean invariance and conserves the mass and energy in the system at the micro- and macro-scale, whereas momentum is conserved globally. For a wide range of temperatures and densities, the model yields results in good agreement with the known properties of binary fluids, such as the density profile, interface width, phase separation, and phase growth. We also apply the model to the study of binary fluids in crowded environments with consistent results.
Pattern formation in individual-based systems with time-varying parameters
NASA Astrophysics Data System (ADS)
Ashcroft, Peter; Galla, Tobias
2013-12-01
We study the patterns generated in finite-time sweeps across symmetry-breaking bifurcations in individual-based models. Similar to the well-known Kibble-Zurek scenario of defect formation, large-scale patterns are generated when model parameters are varied slowly, whereas fast sweeps produce a large number of small domains. The symmetry breaking is triggered by intrinsic noise, originating from the discrete dynamics at the microlevel. Based on a linear-noise approximation, we calculate the characteristic length scale of these patterns. We demonstrate the applicability of this approach in a simple model of opinion dynamics, a model in evolutionary game theory with a time-dependent fitness structure, and a model of cell differentiation. Our theoretical estimates are confirmed in simulations. In further numerical work, we observe a similar phenomenon when the symmetry-breaking bifurcation is triggered by population growth.
Topological structure of dictionary graphs
NASA Astrophysics Data System (ADS)
Fukś, Henryk; Krzemiński, Mark
2009-09-01
We investigate the topological structure of the subgraphs of dictionary graphs constructed from WordNet and Moby thesaurus data. In the process of learning a foreign language, the learner knows only a subset of all words of the language, corresponding to a subgraph of a dictionary graph. When this subgraph grows with time, its topological properties change. We introduce the notion of the pseudocore and argue that the growth of the vocabulary roughly follows decreasing pseudocore numbers—that is, one first learns words with a high pseudocore number followed by smaller pseudocores. We also propose an alternative strategy for vocabulary growth, involving decreasing core numbers as opposed to pseudocore numbers. We find that as the core or pseudocore grows in size, the clustering coefficient first decreases, then reaches a minimum and starts increasing again. The minimum occurs when the vocabulary reaches a size between 103 and 104. A simple model exhibiting similar behavior is proposed. The model is based on a generalized geometric random graph. Possible implications for language learning are discussed.
A new approach for development of kinetics of wastewater treatment in aerobic biofilm reactor
NASA Astrophysics Data System (ADS)
Goswami, S.; Sarkar, S.; Mazumder, D.
2017-09-01
Biofilm process is widely used for the treatment of a variety of wastewater especially containing slowly biodegradable substances. It provides resistance against toxic environment and is capable of retaining biomass under continuous operation. Development of kinetics is very much pertinent for rational design of a biofilm process for the treatment of wastewater with or without inhibitory substances. A simple approach for development of such kinetics for an aerobic biofilm reactor has been presented using a novel biofilm model. The said biofilm model is formulated from the correlations between substrate concentrations in the influent/effluent and at biofilm liquid interface along with substrate flux and biofilm thickness complying Monod's growth kinetics. The methodology for determining the kinetic coefficients for substrate removal and biomass growth has been demonstrated stepwise along with graphical representations. Kinetic coefficients like K, k, Y, b t, b s, and b d are determined either from the intercepts of X- and Y-axis or from the slope of the graphical plots.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Boscá, A., E-mail: alberto.bosca@upm.es; Dpto. de Ingeniería Electrónica, E.T.S.I. de Telecomunicación, Universidad Politécnica de Madrid, Madrid 28040; Pedrós, J.
2015-01-28
Due to its intrinsic high mobility, graphene has proved to be a suitable material for high-speed electronics, where graphene field-effect transistor (GFET) has shown excellent properties. In this work, we present a method for extracting relevant electrical parameters from GFET devices using a simple electrical characterization and a model fitting. With experimental data from the device output characteristics, the method allows to calculate parameters such as the mobility, the contact resistance, and the fixed charge. Differentiated electron and hole mobilities and direct connection with intrinsic material properties are some of the key aspects of this method. Moreover, the method outputmore » values can be correlated with several issues during key fabrication steps such as the graphene growth and transfer, the lithographic steps, or the metalization processes, providing a flexible tool for quality control in GFET fabrication, as well as a valuable feedback for improving the material-growth process.« less
Exploring the evolution of London's street network in the information space: A dual approach
NASA Astrophysics Data System (ADS)
Masucci, A. Paolo; Stanilov, Kiril; Batty, Michael
2014-01-01
We study the growth of London's street network in its dual representation, as the city has evolved over the past 224 years. The dual representation of a planar graph is a content-based network, where each node is a set of edges of the planar graph and represents a transportation unit in the so-called information space, i.e., the space where information is handled in order to navigate through the city. First, we discuss a novel hybrid technique to extract dual graphs from planar graphs, called the hierarchical intersection continuity negotiation principle. Then we show that the growth of the network can be analytically described by logistic laws and that the topological properties of the network are governed by robust log-normal distributions characterizing the network's connectivity and small-world properties that are consistent over time. Moreover, we find that the double-Pareto-like distributions for the connectivity emerge for major roads and can be modeled via a stochastic content-based network model using simple space-filling principles.
Paths to future growth in photovoltaics manufacturing
Basore, Paul A.
2016-03-01
The past decade has seen rapid growth in the photovoltaics industry, followed in the past few years by a period of much slower growth. A simple model that is consistent with this historical record can be used to predict the future evolution of the industry. Two key parameters are identified that determine the outcome. One is the annual global investment in manufacturing capacity normalized to the manufacturing capacity for the previous year (capacity-normalized capital investment rate, CapIR, units dollar/W). The other is how much capital investment is required for each watt of annual manufacturing capacity, normalized to the service lifemore » of the assets (capacity-normalized capital demand rate, CapDR, units dollar/W). If these two parameters remain unchanged from the values they have held for the past few years, global manufacturing capacity will peak in the next few years and then decline. However, it only takes a modest improvement in CapIR to ensure future growth in photovoltaics. Here, several approaches are presented that can enable the required improvement in CapIR. If, in addition, there is an accompanying improvement in CapDR, the rate of growth can be substantially accelerated.« less
Dijkstra, Camelia E.; Larkin, Oliver J.; Anthony, Paul; Davey, Michael R.; Eaves, Laurence; Rees, Catherine E. D.; Hill, Richard J. A.
2011-01-01
Diamagnetic levitation is a technique that uses a strong, spatially varying magnetic field to reproduce aspects of weightlessness, on the Earth. We used a superconducting magnet to levitate growing bacterial cultures for up to 18 h, to determine the effect of diamagnetic levitation on all phases of the bacterial growth cycle. We find that diamagnetic levitation increases the rate of population growth in a liquid culture and reduces the sedimentation rate of the cells. Further experiments and microarray gene analysis show that the increase in growth rate is owing to enhanced oxygen availability. We also demonstrate that the magnetic field that levitates the cells also induces convective stirring in the liquid. We present a simple theoretical model, showing how the paramagnetic force on dissolved oxygen can cause convection during the aerobic phases of bacterial growth. We propose that this convection enhances oxygen availability by transporting oxygen around the liquid culture. Since this process results from the strong magnetic field, it is not present in other weightless environments, e.g. in Earth orbit. Hence, these results are of significance and timely to researchers considering the use of diamagnetic levitation to explore effects of weightlessness on living organisms and on physical phenomena. PMID:20667843
Dijkstra, Camelia E; Larkin, Oliver J; Anthony, Paul; Davey, Michael R; Eaves, Laurence; Rees, Catherine E D; Hill, Richard J A
2011-03-06
Diamagnetic levitation is a technique that uses a strong, spatially varying magnetic field to reproduce aspects of weightlessness, on the Earth. We used a superconducting magnet to levitate growing bacterial cultures for up to 18 h, to determine the effect of diamagnetic levitation on all phases of the bacterial growth cycle. We find that diamagnetic levitation increases the rate of population growth in a liquid culture and reduces the sedimentation rate of the cells. Further experiments and microarray gene analysis show that the increase in growth rate is owing to enhanced oxygen availability. We also demonstrate that the magnetic field that levitates the cells also induces convective stirring in the liquid. We present a simple theoretical model, showing how the paramagnetic force on dissolved oxygen can cause convection during the aerobic phases of bacterial growth. We propose that this convection enhances oxygen availability by transporting oxygen around the liquid culture. Since this process results from the strong magnetic field, it is not present in other weightless environments, e.g. in Earth orbit. Hence, these results are of significance and timely to researchers considering the use of diamagnetic levitation to explore effects of weightlessness on living organisms and on physical phenomena.
Thermal stability of static coronal loops: Part 1: Effects of boundary conditions
NASA Technical Reports Server (NTRS)
Antiochos, S. K.; Shoub, E. C.; An, C. H.; Emslie, A. G.
1985-01-01
The linear stability of static coronal-loop models undergoing thermal perturbations was investigated. The effect of conditions at the loop base on the stability properties of the models was considered in detail. The question of appropriate boundary conditions at the loop base was considered and it was concluded that the most physical assumptions are that the temperature and density (or pressure) perturbations vanish there. However, if the base is taken to be sufficiently deep in the chromosphere, either several chromospheric scale heights or several coronal loop lengths in depth, then the effect of the boundary conditions on loop stability becomes negligible so that all physically acceptable conditions are equally appropriate. For example, one could as well assume that the velocity vanishes at the base. The growth rates and eigenmodes of static models in which gravity is neglected and in which the coronal heating is a relatively simple function, either constant per-unit mass or per-unit volume were calculated. It was found that all such models are unstable with a growth rate of the order of the coronal cooling time. The physical implications of these results for the solar corona and transition region are discussed.
NASA Astrophysics Data System (ADS)
Purewal, Justin; Wang, John; Graetz, Jason; Soukiazian, Souren; Tataria, Harshad; Verbrugge, Mark W.
2014-12-01
Capacity fade is reported for 1.5 Ah Li-ion batteries containing a mixture of Li-Ni-Co-Mn oxide (NCM) + Li-Mn oxide spinel (LMO) as positive electrode material and a graphite negative electrode. The batteries were cycled at a wide range of temperatures (10 °C-46 °C) and discharge currents (0.5C-6.5C). The measured capacity losses were fit to a simple physics-based model which calculates lithium inventory loss from two related mechanisms: (1) mechanical degradation at the graphite anode particle surface caused by diffusion-induced stresses (DIS) and (2) chemical degradation caused by lithium loss to continued growth of the solid-electrolyte interphase (SEI). These two mechanisms are coupled because lithium is consumed through SEI formation on newly exposed crack surfaces. The growth of crack surface area is modeled as a fatigue phenomenon due to the cyclic stresses generated by repeated lithium insertion and de-insertion of graphite particles. This coupled chemical-mechanical degradation model is consistent with the observed capacity loss features for the NCM + LMO/graphite cells.
NASA Technical Reports Server (NTRS)
Lee, Tze-San
1992-01-01
A model of three-stage nested experimental design was applied to analyze the lettuce data obtained from the variable pressure growth chamber test bed at NASA-Johnson Space Center. From the results of an application of the analysis of variance and covariance on the data set, it was noted that all of the (uncontrollable) factors, Side, Zone, Height and (controllable) PAR (photosynthetically active radiation), had nonhomogeneous effects on the dry weight of the edible biomass of lettuce per pot. Incidentally, the variations accountable to the (uncontrollable) factorial heterogeneities are merely 9 percent and 17 percent of the total variation for both the first and second crop test, respectively. After adjusting for the PAR as a covariate in the no-intercept model, the accountable variations to all the four factors are 94 percent and 92 percent for the first and the second crop test, respectively. With the use of a no-intercept simple linear regression model, the accountable variations to the factor PAR are 92 percent and 90 percent for the first and the second crop test, respectively. Evidently, the (controllable) factor PAR is the dominating one.