Generalised Central Limit Theorems for Growth Rate Distribution of Complex Systems

NASA Astrophysics Data System (ADS)

Takayasu, Misako; Watanabe, Hayafumi; Takayasu, Hideki

2014-04-01

We introduce a solvable model of randomly growing systems consisting of many independent subunits. Scaling relations and growth rate distributions in the limit of infinite subunits are analysed theoretically. Various types of scaling properties and distributions reported for growth rates of complex systems in a variety of fields can be derived from this basic physical model. Statistical data of growth rates for about 1 million business firms are analysed as a real-world example of randomly growing systems. Not only are the scaling relations consistent with the theoretical solution, but the entire functional form of the growth rate distribution is fitted with a theoretical distribution that has a power-law tail.

Class of self-limiting growth models in the presence of nonlinear diffusion

NASA Astrophysics Data System (ADS)

Kar, Sandip; Banik, Suman Kumar; Ray, Deb Shankar

2002-06-01

The source term in a reaction-diffusion system, in general, does not involve explicit time dependence. A class of self-limiting growth models dealing with animal and tumor growth and bacterial population in a culture, on the other hand, are described by kinetics with explicit functions of time. We analyze a reaction-diffusion system to study the propagation of spatial front for these models.

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

DTIC Science & Technology

1987-12-01

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

An evaluation of the STEMS tree growth projection system.

Treesearch

Margaret R. Holdaway; Gary J. Brand

1983-01-01

STEMS (Stand and Tree Evaluation and Modeling System) is a tree growth projection system. This paper (1) compares the performance of the current version of STEMS developed for the Lake States with that of the original model and (2) reports the results of an analysis of the current model over a wide range of conditions and identifies its main strengths and weaknesses...

Implementing a national process for estimating growth, removals, and mortality at the Pacific Northwest’s Forest Inventory and Analysis’s Region: modeling diameter growth

Treesearch

Olaf. Kuegler

2015-01-01

The Pacific Northwest Research Station’s Forest Inventory and Analysis Unit began remeasurement of permanently located FIA plots under the annualized design in 2011. With remeasurement has come the need to implement the national FIA system for compiling estimates of forest growth, removals, and mortality. The national system requires regional diameter-growth models to...

Thermal system design and modeling of meniscus controlled silicon growth process for solar applications

NASA Astrophysics Data System (ADS)

Wang, Chenlei

The direct conversion of solar radiation to electricity by photovoltaics has a number of significant advantages as an electricity generator. That is, solar photovoltaic conversion systems tap an inexhaustible resource which is free of charge and available anywhere in the world. Roofing tile photovoltaic generation, for example, saves excess thermal heat and preserves the local heat balance. This means that a considerable reduction of thermal pollution in densely populated city areas can be attained. A semiconductor can only convert photons with the energy of the band gap with good efficiency. It is known that silicon is not at the maximum efficiency but relatively close to it. There are several main parts for the photovoltaic materials, which include, single- and poly-crystalline silicon, ribbon silicon, crystalline thin-film silicon, amorphous silicon, copper indium diselenide and related compounds, cadmium telluride, et al. In this dissertation, we focus on melt growth of the single- and poly-crystalline silicon manufactured by Czochralski (Cz) crystal growth process, and ribbon silicon produced by the edge-defined film-fed growth (EFG) process. These two methods are the most commonly used techniques for growing photovoltaic semiconductors. For each crystal growth process, we introduce the growth mechanism, growth system design, general application, and progress in the numerical simulation. Simulation results are shown for both Czochralski and EFG systems including temperature distribution of the growth system, velocity field inside the silicon melt and electromagnetic field for the EFG growth system. Magnetic field is applied on Cz system to reduce the melt convection inside crucible and this has been simulated in our numerical model. Parametric studies are performed through numerical and analytical models to investigate the relationship between heater power levels and solidification interface movement and shape. An inverse problem control scheme is developed to control the solidification interface of Cz system by adjusting heater powers. For the EFG system, parametric studies are performed to discuss the effect of several growth parameters including window opening size, argon gas flow rate and growth thermal environment on the temperature distribution, silicon tube thickness and pulling rate. Two local models are developed and integrated with the global model to investigate the detailed transport phenomena in a small region around the solidification interface including silicon crystal, silicon melt, free surface, liquid-solid interface and graphite die design. Different convection forms are taken into consideration.

Comparing the STEMS and AFIS growth models with respect to the uncertainty of predictions

Treesearch

Ronald E. McRoberts; Margaret R. Holdaway; Veronica C. Lessard

2000-01-01

The uncertainty in 5-, 10-, and 20-year diameter growth predictions is estimated using Monte Carlo simulations for four Lake States tree species. Two sets of diameter growth models are used: recalibrations of the STEMS models using forest inventory and analysis data, and new growth models developed as a component of an annual forest inventory system for the North...

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

PubMed

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

2016-07-27

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

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

PubMed Central

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

2016-01-01

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

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

NASA Astrophysics Data System (ADS)

Danner, Travis W.

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

An Individual-Tree Growth and Yield Prediction System for Even-Aged Natural Shortleaf Pine Forests

Treesearch

Thomas B. Lynch; Kenneth L. Hitch; Michael M. Huebschmann; Paul A. Murphy

1999-01-01

The development of a system of equations that model the growth and development of even-aged natural shortleaf (Pinus echinata Mill.) pine forests is described. The growth prediction system is a distance-independent individual-tree simulator containing equations that predict basal-area growth, survival, total and merchantable heights, and total and...

Autoimmune control of lesion growth in CNS with minimal damage

NASA Astrophysics Data System (ADS)

Mathankumar, R.; Mohan, T. R. Krishna

2013-07-01

Lesions in central nervous system (CNS) and their growth leads to debilitating diseases like Multiple Sclerosis (MS), Alzheimer's etc. We developed a model earlier [1, 2] which shows how the lesion growth can be arrested through a beneficial auto-immune mechanism. We compared some of the dynamical patterns in the model with different facets of MS. The success of the approach depends on a set of control parameters and their phase space was shown to have a smooth manifold separating the uncontrolled lesion growth region from the controlled. Here we show that an optimal set of parameter values exist in the model which minimizes system damage while, at once, achieving control of lesion growth.

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

NASA Technical Reports Server (NTRS)

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

2000-01-01

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

Effective equations governing an active poroelastic medium

PubMed Central

2017-01-01

In this work, we consider the spatial homogenization of a coupled transport and fluid–structure interaction model, to the end of deriving a system of effective equations describing the flow, elastic deformation and transport in an active poroelastic medium. The ‘active’ nature of the material results from a morphoelastic response to a chemical stimulant, in which the growth time scale is strongly separated from other elastic time scales. The resulting effective model is broadly relevant to the study of biological tissue growth, geophysical flows (e.g. swelling in coals and clays) and a wide range of industrial applications (e.g. absorbant hygiene products). The key contribution of this work is the derivation of a system of homogenized partial differential equations describing macroscale growth, coupled to transport of solute, that explicitly incorporates details of the structure and dynamics of the microscopic system, and, moreover, admits finite growth and deformation at the pore scale. The resulting macroscale model comprises a Biot-type system, augmented with additional terms pertaining to growth, coupled to an advection–reaction–diffusion equation. The resultant system of effective equations is then compared with other recent models under a selection of appropriate simplifying asymptotic limits. PMID:28293138

General Training System; GENTRAS. Final Report.

ERIC Educational Resources Information Center

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

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

Modeling of the Competitive Growth of Listeria monocytogenes and Lactococcus lactis in Vegetable Broth

PubMed Central

Breidt, Frederick; Fleming, Henry P.

1998-01-01

Current mathematical models used by food microbiologists do not address the issue of competitive growth in mixed cultures of bacteria. We developed a mathematical model which consists of a system of nonlinear differential equations describing the growth of competing bacterial cell cultures. In this model, bacterial cell growth is limited by the accumulation of protonated lactic acid and decreasing pH. In our experimental system, pure and mixed cultures of Lactococcus lactis and Listeria monocytogenes were grown in a vegetable broth medium. Predictions of the model indicate that pH is the primary factor that limits the growth of L. monocytogenes in competition with a strain of L. lactis which does not produce the bacteriocin nisin. The model also predicts the values of parameters that affect the growth and death of the competing populations. Further development of this model will incorporate the effects of additional inhibitors, such as bacteriocins, and may aid in the selection of lactic acid bacterium cultures for use in competitive inhibition of pathogens in minimally processed foods. PMID:9726854

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

Treesearch

Charles E. Rose; Thomas B. Lynch

2001-01-01

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

A model of milk production in lactating dairy cows in relation to energy and nitrogen dynamics.

PubMed

Johnson, I R; France, J; Cullen, B R

2016-02-01

A generic daily time-step model of a dairy cow, designed to be included in whole-system pasture simulation models, is described that includes growth, milk production, and lactation in relation to energy and nitrogen dynamics. It is a development of a previously described animal growth and metabolism model that describes animal body composition in terms of protein, water, and fat, and energy dynamics in relation to growth requirements, resynthesis of degraded protein, and animal activity. This is further developed to include lactation and fetal growth. Intake is calculated in relation to stage of lactation, pasture availability, supplementary feed, and feed quality. Energy costs associated with urine N excretion and methane fermentation are accounted for. Milk production and fetal growth are then calculated in relation to the overall energy and nitrogen dynamics. The general behavior of the model is consistent with expected characteristics. Simulations using the model as part of a whole-system pasture simulation model (DairyMod) are compared with experimental data where good agreement between pasture, concentrate and forage intake, as well as milk production over 3 consecutive lactation cycles, is observed. The model is shown to be well suited for inclusion in large-scale system simulation models. Copyright © 2016 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

ECONOMIC GROWTH ANALYSIS SYSTEM: USER'S GUIDE VERSION 2.0

EPA Science Inventory

The two-volume report describes the development of and provides information needed to operate, the Economic Growth Analysis System (E-GAS) Version 2.0 model. The model will be used to project emissions inventories of volatile organic compounds (VOCs), oxides of nitrogen (NOx), a...

ECONOMIC GROWTH ANALYSIS SYSTEM: REFERENCE MANUAL VERSION 2.0

EPA Science Inventory

The two-volume report describes the development of and provides information needed to operate, the Economic Growth Analysis System (E-GAS) Version 2.0 model. The model will be used to project emissions inventories of volatile organic compounds (VOCs), oxides of nitrogen (NOx), a...

ECONOMIC GROWTH ANALYSIS SYSTEM: USER'S GUIDE - VERSION 3.0

EPA Science Inventory

The two-volume report describes the development of, and provides information needed to operate, the Economic Growth Analysis System (E-GAS) Version 3.0 model. The model will be used to project emissions inventories of volatile organic compounds, oxides of nitrogen, and carbon mon...

ECONOMIC GROWTH ANALYSIS SYSTEM: REFERENCE MANUAL VERSION 3.0

EPA Science Inventory

The two-volume report describes the development of, and provides information needed to operate, the Economic Growth Analysis System (E-GAS) Version 3.0 model. The model will be used to project emissions inventories of volatile organic compounds, oxides of nitrogen, and carbon mon...

A Multilevel Latent Growth Curve Approach to Predicting Student Proficiency

ERIC Educational Resources Information Center

Choi, Kilchan; Goldschmidt, Pete

2012-01-01

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

An Individual-Tree Growth and Yield Prediction System for Uneven-Aged Shortleaf Pine Stands

Treesearch

Michael M. Huebschmann; Lawrence R. Gering; Thomas B. Lynch; Onesphore Bitoki; Paul A. Murphy

2000-01-01

A system of equations modeling the growth and development of uneven-aged shortleaf pine (Pinus echinata Mill.) stands is described. The prediction system consists of two main components: (1) a distance-independent, individual-tree simulator containing equations that forecast ingrowth, basal-area growth, probability of survival, total and...

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

NASA Astrophysics Data System (ADS)

Fadhlurrahman, Akmal; Sumarti, Novriana

2016-04-01

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

Stress studies in EFG

NASA Technical Reports Server (NTRS)

1982-01-01

A program to study stress generation mechanisms in silicon sheet growth was started. The purpose of the research is to define post-growth temperature profiles for the sheet that can minimize its stress during growth at high speeds, e.g., greater than 3 cm/min. The initial tasks described concern work in progress toward the development of computing capabilities to (1) model stress-temperature relationships in steady-state ribbon growth, and (2) provide a means to calculate realistic temperature fields in ribbon, given growth system component temperatures as boundary conditions. If it is determined that low stress configurations can be achieved, the modeling is to be tested experimentally by constructing low-stress growth systems for EFG silicon ribbon.

Chaotic attractors in tumor growth and decay: a differential equation model.

PubMed

Harney, Michael; Yim, Wen-sau

2015-01-01

Tumorigenesis can be modeled as a system of chaotic nonlinear differential equations. A simulation of the system is realized by converting the differential equations to difference equations. The results of the simulation show that an increase in glucose in the presence of low oxygen levels decreases tumor growth.

Critical thickness of transition from 2D to 3D growth and peculiarities of quantum dots formation in GexSi1-x/Sn/Si and Ge1-ySny/Si systems

NASA Astrophysics Data System (ADS)

Lozovoy, Kirill A.; Kokhanenko, Andrey P.; Voitsekhovskii, Alexander V.

2018-03-01

Nowadays using of tin as one of the deposited materials in GeSi/Sn/Si, GeSn/Si and GeSiSn/Si material systems is one of the most topical problems. These materials are very promising for various applications in nanoelectronics and optoelectronics due to possibility of band gap management and synthesis of direct band semiconductors within these systems. However, there is a lack of theoretical investigations devoted to the peculiarities of germanium on silicon growth in the presence of tin. In this paper a new theoretical approach for modeling growth processes of binary and ternary semiconductor compounds during the molecular beam epitaxy in these systems is presented. The established kinetic model based on the general nucleation theory takes into account the change in physical and mechanical parameters, diffusion coefficient and surface energies in the presence of tin. With the help of the developed model the experimentally observed significant decrease in the 2D-3D transition temperatures for GeSiSn/Si system compared to GeSi/Si system is theoretically explained for the first time in the literature. Besides that, the derived expressions allow one to explain the experimentally observed temperature dependencies of the critical thickness, as well as to predict the average size and surface density of quantum dots for different contents and temperatures in growth experiment, that confirms applicability of the model proposed. Moreover, the established model can be easily applied to other material systems in which the Stranski-Krastanow growth mode occurs.

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

PubMed

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

2017-01-02

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

Numerical simulations of crystal growth in a transdermal drug delivery system

NASA Astrophysics Data System (ADS)

Zeng, Jianming; Jacob, Karl I.; Tikare, Veena

2004-02-01

Grain growth by precipitation and Ostwald ripening in an unstressed matrix of a dissolved crystallizable component was simulated using a kinetic Monte Carlo model. This model was used previously to study Ostwald ripening in the high crystallizable component regime and was shown to correctly simulate solution, diffusion and precipitation. In this study, the same model with modifications was applied to the low crystallizable regime of interest to the transdermal drug delivery system (TDS) community. We demonstrate the model's utility by simulating precipitation and grain growth during isothermal storage at different supersaturation conditions. The simulation results provide a first approximation for the crystallization occurring in TDS. It has been reported that for relatively higher temperature growth of drug crystals in TDS occurs only in the middle third of the polymer layer. The results from the simulations support these findings that crystal growth is limited to the middle third of the region, where the availability of crystallizable components is the highest, for cluster growth at relatively high temperature.

Mechanically induced alterations in cultured skeletal muscle growth

NASA Technical Reports Server (NTRS)

Vandenburgh, H. H.; Hatfaludy, S.; Karlisch, P.; Shansky, J.

1991-01-01

Model systems are available for mechanically stimulating cultured skeletal muscle cells by passive tensile forces which simulate those found in vivo. When applied to embryonic muscle cells in vitro these forces induce tissue organogenesis, metabolic adaptations, and muscle cell growth. The mechanical stimulation of muscle cell growth correlates with stretch-induced increases in the efflux of prostaglandins PGE2 and PGF2(alpha) in a time and frequency dependent manner. These prostaglandins act as mechanical 'second messengers' regulating skeletal muscle protein turnover rates. Since they also effect bone remodelling in response to tissue loading and unloading, secreted prostaglandins may serve as paracrine growth factors, coordinating the growth rates of muscle and bone in response to external mechanical forces. Cell culture model systems will supplement other models in understanding mechanical transduction processes at the molecular level.

A New Model for Root Growth in Soil with Macropores

NASA Astrophysics Data System (ADS)

Landl, M.; Huber, K.; Schnepf, A.; Vanderborght, J.; Javaux, M.; Bengough, G.; Vereecken, H.

2016-12-01

In order to study soil-root interaction processes, dynamic root architecture models which are linked to models that simulate water flow and nutrient transport in the soil-root system are needed. Such models can be used to predict the impact of soil structural features, e.g. the presence of macropores in dense subsoil, on water and nutrient uptake by plants. In dynamic root architecture models, root growth is represented by moving root tips whose growth trajectory results in the creation of linear root segments. Typically, the direction of each new root segment is calculated as the vector sum of various direction-affecting components. The use of these established methods to simulate root growth in soil containing macropores, however, failed to reproduce experimentally observed root growth patterns. We therefore developed an alternative modelling approach where we distinguish between, firstly, the driving force for root growth which is determined by the orientation of the previous root segment as well as the influence of gravitropism and, secondly, soil mechanical resistance to root growth. The latter is expressed by root conductance which represents the inverse of soil penetration resistance and is treated similarly to hydraulic conductivity in Darcy's law. At the presence of macropores, root conductance is anisotropic which leads to a difference between the direction of the driving force and the direction of the root tip movement. The model was tested using data from the literature, at pot scale, at macropore scale, and in a series of simulations where sensitivity to gravity and macropore orientation was evaluated. The model simulated root growth trajectories in structured soil at both single root and whole root-system scales, generating root systems that were similar to images from experiments. Its implementation in the three dimensional soil and root water uptake model R-SWMS enables the use of the model in the future to evaluate the effect of macropores on crop access to water and nutrients.

Transpiration during life cycle in controlled wheat growth

NASA Technical Reports Server (NTRS)

Volk, Tyler; Rummel, John D.

1990-01-01

A previously developed model of wheat growth, designed for convenient incorporation into system level models of advanced space life support systems is described. The model is applied to data from an experiment that grew wheat under controlled conditions and measured fresh biomass and cumulated transpiration as a function of time. The adequacy of modeling the transpiration as proportional to the inedible biomass and an age factor that varies during the life cycle are discussed.

Shifts in growth strategies reflect tradeoffs in cellular economics

PubMed Central

Molenaar, Douwe; van Berlo, Rogier; de Ridder, Dick; Teusink, Bas

2009-01-01

The growth rate-dependent regulation of cell size, ribosomal content, and metabolic efficiency follows a common pattern in unicellular organisms: with increasing growth rates, cell size and ribosomal content increase and a shift to energetically inefficient metabolism takes place. The latter two phenomena are also observed in fast growing tumour cells and cell lines. These patterns suggest a fundamental principle of design. In biology such designs can often be understood as the result of the optimization of fitness. Here we show that in basic models of self-replicating systems these patterns are the consequence of maximizing the growth rate. Whereas most models of cellular growth consider a part of physiology, for instance only metabolism, the approach presented here integrates several subsystems to a complete self-replicating system. Such models can yield fundamentally different optimal strategies. In particular, it is shown how the shift in metabolic efficiency originates from a tradeoff between investments in enzyme synthesis and metabolic yields for alternative catabolic pathways. The models elucidate how the optimization of growth by natural selection shapes growth strategies. PMID:19888218

Capital, population and urban patterns.

PubMed

Zhang, W

1994-04-01

The author develops an approach to urban dynamics with endogenous capital and population growth, synthesizing the Alonso location model, the two-sector neoclassical growth model, and endogenous population theory. A dynamic model for an isolated island economy with endogenous capital, population, and residential structure is developed on the basis of Alonso's residential model and the two-sector neoclassical growth model. The model describes the interdependence between residential structure, economic growth, population growth, and economic structure over time and space. It has a unique long-run equilibrium, which may be either stable or unstable, depending upon the population dynamics. Applying the Hopf theorem, the author also shows that when the system is unstable, the economic geography exhibits permanent endogenous oscillations.

Linking a modified EPIC-based growth model (UPGM) with a component-based watershed model (AGES-W)

USDA-ARS?s Scientific Manuscript database

Agricultural models and decision support systems (DSS) for assessing water use and management are increasingly being applied to diverse geographic regions at different scales. This requires models that can simulate different crops, however, very few plant growth models are available that “easily” ...

Disentangling early language development: modeling lexical and grammatical acquisition using an extension of case-study methodology.

PubMed

Robinson, B F; Mervis, C B

1998-03-01

The early lexical and grammatical development of 1 male child is examined with growth curves and dynamic-systems modeling procedures. Lexical-development described a pattern of logistic growth (R2 = .98). Lexical and plural development shared the following characteristics: Plural growth began only after a threshold was reached in vocabulary size; lexical growth slowed as plural growth increased. As plural use reached full mastery, lexical growth began again to increase. It was hypothesized that a precursor model (P. van Geert, 1991) would fit these data. Subsequent testing indicated that the precursor model, modified to incorporate brief yet intensive plural growth, provided a suitable fit. The value of the modified precursor model for the explication of processes implicated in language development is discussed.

Analyzing The Uncertainty Of Diameter Growth Model Predictions

Treesearch

Ronald E. McRoberts; Veronica C. Lessard; Margaret R. Holdaway

1999-01-01

The North Central Research Station of the USDA Forest Service is developing a new set of individual tree, diameter growth models to be used as a component of an annual forest inventory system. The criterion for selection of predictor variables for these models is the uncertainty in 5-, 10-, and 20-year diameter growth predictions estimated using Monte Carlo simulations...

Systems biology and mechanics of growth.

PubMed

Eskandari, Mona; Kuhl, Ellen

2015-01-01

In contrast to inert systems, living biological systems have the advantage to adapt to their environment through growth and evolution. This transfiguration is evident during embryonic development, when the predisposed need to grow allows form to follow function. Alterations in the equilibrium state of biological systems breed disease and mutation in response to environmental triggers. The need to characterize the growth of biological systems to better understand these phenomena has motivated the continuum theory of growth and stimulated the development of computational tools in systems biology. Biological growth in development and disease is increasingly studied using the framework of morphoelasticity. Here, we demonstrate the potential for morphoelastic simulations through examples of volume, area, and length growth, inspired by tumor expansion, chronic bronchitis, brain development, intestine formation, plant shape, and myopia. We review the systems biology of living systems in light of biochemical and optical stimuli and classify different types of growth to facilitate the design of growth models for various biological systems within this generic framework. Exploring the systems biology of growth introduces a new venue to control and manipulate embryonic development, disease progression, and clinical intervention. © 2015 Wiley Periodicals, Inc.

Growth trishear model and its application to the Gilbertown graben system, southwest Alabama

USGS Publications Warehouse

Jin, G.; Groshong, R.H.; Pashin, J.C.

2009-01-01

Fault-propagation folding associated with an upward propagating fault in the Gilbertown graben system is revealed by well-based 3-D subsurface mapping and dipmeter analysis. The fold is developed in the Selma chalk, which is an oil reservoir along the southern margin of the graben. Area-depth-strain analysis suggests that the Cretaceous strata were growth units, the Jurassic strata were pregrowth units, and the graben system is detached in the Louann Salt. The growth trishear model has been applied in this paper to study the evolution and kinematics of extensional fault-propagation folding. Models indicate that the propagation to slip (p/s) ratio of the underlying fault plays an important role in governing the geometry of the resulting extensional fault-propagation fold. With a greater p/s ratio, the fold is more localized in the vicinity of the propagating fault. The extensional fault-propagation fold in the Gilbertown graben is modeled by both a compactional and a non-compactional growth trishear model. Both models predict a similar geometry of the extensional fault-propagation fold. The trishear model with compaction best predicts the fold geometry. ?? 2008 Elsevier Ltd. All rights reserved.

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

NASA Astrophysics Data System (ADS)

Shijuan, Li; Yeping, Zhu

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

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.

On the definition of a Monte Carlo model for binary crystal growth.

PubMed

Los, J H; van Enckevort, W J P; Meekes, H; Vlieg, E

2007-02-01

We show that consistency of the transition probabilities in a lattice Monte Carlo (MC) model for binary crystal growth with the thermodynamic properties of a system does not guarantee the MC simulations near equilibrium to be in agreement with the thermodynamic equilibrium phase diagram for that system. The deviations remain small for systems with small bond energies, but they can increase significantly for systems with large melting entropy, typical for molecular systems. These deviations are attributed to the surface kinetics, which is responsible for a metastable zone below the liquidus line where no growth occurs, even in the absence of a 2D nucleation barrier. Here we propose an extension of the MC model that introduces a freedom of choice in the transition probabilities while staying within the thermodynamic constraints. This freedom can be used to eliminate the discrepancy between the MC simulations and the thermodynamic equilibrium phase diagram. Agreement is achieved for that choice of the transition probabilities yielding the fastest decrease of the free energy (i.e., largest growth rate) of the system at a temperature slightly below the equilibrium temperature. An analytical model is developed, which reproduces quite well the MC results, enabling a straightforward determination of the optimal set of transition probabilities. Application of both the MC and analytical model to conditions well away from equilibrium, giving rise to kinetic phase diagrams, shows that the effect of kinetics on segregation is even stronger than that predicted by previous models.

Retardation analytical model to extend service life

NASA Technical Reports Server (NTRS)

Matejczyk, D.

1984-01-01

A fatigue crack growth model that incorporates crack growth retardation effects and is applicable to the materials characteristics and service environments of high performance LH2/LO2 engine systems was developed and tested.

Computational Systems Biology in Cancer: Modeling Methods and Applications

PubMed Central

Materi, Wayne; Wishart, David S.

2007-01-01

In recent years it has become clear that carcinogenesis is a complex process, both at the molecular and cellular levels. Understanding the origins, growth and spread of cancer, therefore requires an integrated or system-wide approach. Computational systems biology is an emerging sub-discipline in systems biology that utilizes the wealth of data from genomic, proteomic and metabolomic studies to build computer simulations of intra and intercellular processes. Several useful descriptive and predictive models of the origin, growth and spread of cancers have been developed in an effort to better understand the disease and potential therapeutic approaches. In this review we describe and assess the practical and theoretical underpinnings of commonly-used modeling approaches, including ordinary and partial differential equations, petri nets, cellular automata, agent based models and hybrid systems. A number of computer-based formalisms have been implemented to improve the accessibility of the various approaches to researchers whose primary interest lies outside of model development. We discuss several of these and describe how they have led to novel insights into tumor genesis, growth, apoptosis, vascularization and therapy. PMID:19936081

An unstructured mathematical model for growth of Pleurotus ostreatus on lignocellulosic material in solid-state fermentation systems

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

Sarikaya, A.; Ladisch, M.R.

1997-01-01

Inedible plant material, generated in a Controlled Ecological Life Support System (CELSS), should be recycled preferably by bioregenerative methods that utilize enzymes or micro-organisms. This material consists of hemicellulose, cellulose, and lignin with the lignin fraction representing a recalcitrant component that is not readily treated by enzymatic methods. Consequently, the white-rot fungus, Pleurotus ostreatus, is attractive since it effectively degrades lignin and produces edible mushrooms. This work describes an unstructured model for the growth of P. ostreatus in a solid-state fermentation system using lignocellulosic plant materials from Brassica napus (rapeseed) as a substrate at three different particle sizes. A logisticmore » function model based on area was found to fit the surface growth of the mycelium on the solid substrate with respect to time, whereas a model based on diameter, alone, did not fit the data as well. The difference between the two measures of growth was also evident for mycelial growth in a bioreactor designed to facilitate a slow flowrate of air through the 1.5 cm thick mat of lignocellulosic biomass particles. The result is consistent with the concept of competition of the mycelium for the substrate that surrounds it, rather than just substrate that is immediately available to single cells. This approach provides a quantitative measure of P. ostreatus growth on lignocellulosic biomass in a solid-state fermentation system. The experimental data show that the best growth is obtained for the largest particles (1 cm) of the lignocellulosic substrate. 13 refs., 6 figs., 2 tabs.« less

Defect, Kinetics and Heat Transfer of CDTE Bridgman Growth without Wall Contact

NASA Technical Reports Server (NTRS)

Larson, D. J., Jr.; Zhang, H.

2003-01-01

A detached growth mechanism has been proposed, which is similar to that proposed by Duffar et al. and used to study the current detached growth system. From numerical results, we can conclude that detached growth will more likely appear if the growth and wetting angles are large and meniscus is flat. Detached thickness is dependent on growth angle, wetting angle, and gap width and shape of the fins. The model can also explain why the detached growth will not happen for metals in which the growth angle is almost zero. Since the growth angle of CdZnTe cannot be changed, to promote detached growth, the number density of the fins should be low and the wetting angle should be high. Also, a much smaller gap width of the fins should be used in the ground experiment and the detached gap width is much smaller. The shape of the fins has minor influence on detached growth. An integrated numerical model for detached solidification has been developed combining a global heat transfer sub-model and a wall contact sub-model. The global heat transfer sub-model accounts for heat and mass transfer in the multiphase system, convection in the melt, macro-segregation, and interface dynamics. The location and dynamics of the solidification interface are accurately tracked by a multizone adaptive grid generation scheme. The wall contact sub-model accounts for the meniscus dynamics at the three-phase boundary. Simulations have been performed for crystal growth in a conventional ampoule and a designed ampoule to understand the benefits of detached solidification and its impacts on crystalline structural quality, e.g., stoichiometry, macro-segregation, and stress. From simulation results, both the Grashof and Marangoni numbers will have significant effects on the shape of growth front, Zn concentration distribution, and radial segregation. The integrated model can be used in designing apparatus and determining the optimal geometry for detached solidification in space and on the ground.

Software reliability models for fault-tolerant avionics computers and related topics

NASA Technical Reports Server (NTRS)

Miller, Douglas R.

1987-01-01

Software reliability research is briefly described. General research topics are reliability growth models, quality of software reliability prediction, the complete monotonicity property of reliability growth, conceptual modelling of software failure behavior, assurance of ultrahigh reliability, and analysis techniques for fault-tolerant systems.

Description of Aspergillus flavus growth under the influence of different factors (water activity, incubation temperature, protein and fat concentration, pH, and cinnamon essential oil concentration) by kinetic, probability of growth, and time-to-detection models.

PubMed

Kosegarten, Carlos E; Ramírez-Corona, Nelly; Mani-López, Emma; Palou, Enrique; López-Malo, Aurelio

2017-01-02

A Box-Behnken design was used to determine the effect of protein concentration (0, 5, or 10g of casein/100g), fat (0, 3, or 6g of corn oil/100g), a w (0.900, 0.945, or 0.990), pH (3.5, 5.0, or 6.5), concentration of cinnamon essential oil (CEO, 0, 200, or 400μL/kg) and incubation temperature (15, 25, or 35°C) on the growth of Aspergillus flavus during 50days of incubation. Mold response under the evaluated conditions was modeled by the modified Gompertz equation, logistic regression, and time-to-detection model. The obtained polynomial regression models allow the significant coefficients (p<0.05) for linear, quadratic and interaction effects for the Gompertz equation's parameters to be identified, which adequately described (R 2 >0.967) the studied mold responses. After 50days of incubation, every tested model system was classified according to the observed response as 1 (growth) or 0 (no growth), then a binary logistic regression was utilized to model A. flavus growth interface, allowing to predict the probability of mold growth under selected combinations of tested factors. The time-to-detection model was utilized to estimate the time at which A. flavus visible growth begins. Water activity, temperature, and CEO concentration were the most important factors affecting fungal growth. It was observed that there is a range of possible combinations that may induce growth, such that incubation conditions and the amount of essential oil necessary for fungal growth inhibition strongly depend on protein and fat concentrations as well as on the pH of studied model systems. The probabilistic model and the time-to-detection models constitute another option to determine appropriate storage/processing conditions and accurately predict the probability and/or the time at which A. flavus growth occurs. Copyright © 2016 Elsevier B.V. All rights reserved.

A Model System to Investigate the Effect of BRCA1 and/or p53 Inactivation in the Ovarian Stroma on Growth and Transformation Potential of the Ovarian Epithelium

DTIC Science & Technology

2009-10-01

Effect of BRCA1 and/or p53 Inactivation in the Ovarian Stroma on Growth and Transformation Potential of the Ovarian Epithelium PRINCIPAL...AND SUBTITLE 5a. CONTRACT NUMBER A Model System To Investigate the Effect of BRCA1 and/or p53 Inactivation in the Ovarian Stroma on Growth and... effects of loss of function of BRCA1 or BRCA1 and Trp53 in the stroma on the growth and neoplastic transformation of epithelial cells using 2D and 3D in

Drosophila as a genetic and cellular model for studies on axonal growth

PubMed Central

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

Growth of Lactobacillus paracasei ATCC334 in a cheese model system: A biochemical approach

USDA-ARS?s Scientific Manuscript database

Growth of Lactobacillus paracasei ATCC 334, in a cheese-ripening model system based upon a medium prepared from ripening Cheddar cheese extract (CCE) was evaluated. Lactobacillus paracasei ATCC 334 grows in CCE made from cheese ripened for 2 (2mCCE), 6 (6mCCE), and 8 (8mCCE) mo, to final cell densit...

USE OF MOLECULAR BIOLOGICAL TECHNIQUES TO EVALUATE EFFECT OF ENDOGENOUS HORMONES AND A XENOBIOTIC PESTICIDE ON GROWTH OF SHEEPSHEAD MINNOW

EPA Science Inventory

We have developed a teleost model to screen physiological effects of endocrine disrupting chemicals (EDCs) on somatic growth. Growth is largely controlled by the endocrine system via the growth-hormone releasing hormone (GRF) - growth hormone (GH) - insulin-like growth factor (IG...

Oil and gas reserve growth-a model for the Volga-Ural Province, Russia

USGS Publications Warehouse

Verma, M.K.; Ulmishek, G.F.; Gilbershtein, A.P.

2000-01-01

An understanding of reserve growth in known oil and gas fields has become a critical component of energy resource analysis. Significant statistical studies of reserve growth have been published in the U.S., whereas little information is available on other regions of the world. It may be expected that in many countries the magnitude of reserve growth is different from that in the U.S. because of differences in reporting systems and in exploration and production practices. This paper describes the results of a reserve growth study in a group of largest oil and gas fields of the Volga-Ural petroleum province, Russia. The dynamics of reserve growth in these fields shows rapid reserve additions during the first 5 years of field exploration and development, which results from intensive step-out and delineation drilling. Later reserve growth is slow and is related to improvements in recovery technologies and discoveries of new pools and extensions. These two stages of reserve growth are described by two different groups of empirical models. A comparison of these models with the models developed for the lower 48 states and Gulf Coast offshore of the U.S. demonstrates that the reserve growth in the Volga-Ural province is significantly lower than in the U.S. The proposed models may be used for assessment of future reserve additions in known fields of countries that presently have or recently had a centrally-planned economic system.

Retardation analytical model to extend service life

NASA Technical Reports Server (NTRS)

Matejczyk, J.

1984-01-01

A fatigue crack growth model that incorporates crack growth retardation effects and is applicable to the materials characteristics and service environments of high performance LH2/LO2 engine systems is discussed. Future Research plans are outlined.

Longitudinal growth of skeletal myotubes in vitro in a new horizontal mechanical cell stimulator

NASA Technical Reports Server (NTRS)

Vandenburgh, Herman H.; Karlisch, Patricia

1989-01-01

A tissue-culture model system for growing skeletal-muscle cells under more dynamic conditions than found in normal tissue-culture environments is described. A computerized device presented allows mechanical stimulation of the cell's substratum by 300 to 400 pct in length in the horizontal plane. Cell growth rates and skeletal-muscle organogenesis are stimulated in this in vitro system. It is noted that longitudinal myotube growth observed is accompanied by increased rates of cell proliferation and myoblast fusion. Prestretching the collagen-coated substratum before cell plating is shown to lead to increased cell proliferation, myotube orientation, and longitudinal myotube growth. The effects of substratum stretching on myogenesis in the model system are also assessed and attributed to alterations in the cell's extracellular matrix.

The use of rats and mice as animal models in ex vivo bone growth and development studies

PubMed Central

Abubakar, A. A.; Noordin, M. M.; Azmi, T. I.; Kaka, U.

2016-01-01

In vivo animal experimentation has been one of the cornerstones of biological and biomedical research, particularly in the field of clinical medicine and pharmaceuticals. The conventional in vivo model system is invariably associated with high production costs and strict ethical considerations. These limitations led to the evolution of an ex vivo model system which partially or completely surmounted some of the constraints faced in an in vivo model system. The ex vivo rodent bone culture system has been used to elucidate the understanding of skeletal physiology and pathophysiology for more than 90 years. This review attempts to provide a brief summary of the historical evolution of the rodent bone culture system with emphasis on the strengths and limitations of the model. It encompasses the frequency of use of rats and mice for ex vivo bone studies, nutritional requirements in ex vivo bone growth and emerging developments and technologies. This compilation of information could assist researchers in the field of regenerative medicine and bone tissue engineering towards a better understanding of skeletal growth and development for application in general clinical medicine. Cite this article: A. A. Abubakar, M. M. Noordin, T. I. Azmi, U. Kaka, M. Y. Loqman. The use of rats and mice as animal models in ex vivo bone growth and development studies. Bone Joint Res 2016;5:610–618. DOI: 10.1302/2046-3758.512.BJR-2016-0102.R2. PMID:27965220

Variability and Reliabiltiy in Axon Growth Cone Navigation Decision Making

NASA Astrophysics Data System (ADS)

Garnelo, Marta; Ricoult, Sébastien G.; Juncker, David; Kennedy, Timothy E.; Faisal, Aldo A.

2015-03-01

The nervous system's wiring is a result of axon growth cones navigating through specific molecular environments during development. In order to reach their target, growth cones need to make decisions under uncertainty as they are faced with stochastic sensory information and probabilistic movements. The overall system therefore exhibits features of whole organisms (perception, decision making, action) in the subset of a single cell. We aim to characterise growth cone navigation in defined nano-dot guidance cue environments, by using the tools of computational neuroscience to conduct ``molecular psychophysics.'' We start with a generative model of growth cone behaviour and we 1. characterise sensory and internal sources of noise contributing to behavioural variables, by combining knowledge of the underlying stochastic dynamics in cue sensing and the growth of the cytoskeleton. This enables us to 2. produce bottom-up lower limit estimates of behavioural response reliability and visualise it as probability distributions over axon growth trajectories. Given this information we can match our in silico model's ``psychometric'' decision curves with empirical data. Finally we use a Monte-Carlo approach to predict response distributions of axon trajectories from our model.

Mathematical Modeling and Nonlinear Dynamical Analysis of Cell Growth in Response to Antibiotics

NASA Astrophysics Data System (ADS)

Jin, Suoqin; Niu, Lili; Wang, Gang; Zou, Xiufen

2015-06-01

This study is devoted to the revelation of the dynamical mechanisms of cell growth in response to antibiotics. We establish a mathematical model of ordinary differential equations for an antibiotic-resistant growth system with one positive feedback loop. We perform a dynamical analysis of the behavior of this model system. We present adequate sets of conditions that can guarantee the existence and stability of biologically-reasonable steady states. Using bifurcation analysis and numerical simulation, we show that the relative growth rate, which is defined as the ratio of the cell growth rate to the basal cell growth rate in the absence of antibiotics, can exhibit bistable behavior in an extensive range of parameters that correspond to a growth state and a nongrowth state in biology. We discover that both antibiotic and antibiotic resistance genes can cooperatively enhance bistability, whereas the cooperative coefficient of feedback can contribute to the onset of bistability. These results would contribute to a better understanding of not only the evolution of antibiotics but also the emergence of drug resistance in other diseases.

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

ERIC Educational Resources Information Center

Nese, Joseph F. T.

2013-01-01

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

Interim Report on the Evaluation of the Growth Model Pilot Project

ERIC Educational Resources Information Center

Hoffer, Thomas B.; Hedberg, E. C.; Brown, Kevin L.; Halverson, Marie L.; McDonald, Sarah-Kathryn

2010-01-01

The Growth Model Pilot Project (GMPP) was initiated to allow states to experiment with adjustments to the No Child Left Behind Act (NCLB) status accountability system in order to improve the validity of AYP determinations by giving schools credit for students who are making significant growth. The pilot allowed states, districts, and schools to…

The mathematical properties of the quasi-chemical model for microorganism growth-death kinetics in foods.

PubMed

Ross, E W; Taub, I A; Doona, C J; Feeherry, F E; Kustin, K

2005-03-15

Knowledge of the mathematical properties of the quasi-chemical model [Taub, Feeherry, Ross, Kustin, Doona, 2003. A quasi-chemical kinetics model for the growth and death of Staphylococcus aureus in intermediate moisture bread. J. Food Sci. 68 (8), 2530-2537], which is used to characterize and predict microbial growth-death kinetics in foods, is important for its applications in predictive microbiology. The model consists of a system of four ordinary differential equations (ODEs), which govern the temporal dependence of the bacterial life cycle (the lag, exponential growth, stationary, and death phases, respectively). The ODE system derives from a hypothetical four-step reaction scheme that postulates the activity of a critical intermediate as an antagonist to growth (perhaps through a quorum sensing biomechanism). The general behavior of the solutions to the ODEs is illustrated by several examples. In instances when explicit mathematical solutions to these ODEs are not obtainable, mathematical approximations are used to find solutions that are helpful in evaluating growth in the early stages and again near the end of the process. Useful solutions for the ODE system are also obtained in the case where the rate of antagonist formation is small. The examples and the approximate solutions provide guidance in the parameter estimation that must be done when fitting the model to data. The general behavior of the solutions is illustrated by examples, and the MATLAB programs with worked examples are included in the appendices for use by predictive microbiologists for data collected independently.

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

NASA Astrophysics Data System (ADS)

Setiyono, T. D.

2014-12-01

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

Regulated release of serotonin from axonal growth cones isolated from the fetal rat brain.

PubMed

Mercado, R; Floran, B; Hernandez, J

1998-01-01

In the present work we propose an hypothetical model related to a molecular recognizing system for serotonin in isolated growth cone particles. This model is supported by previous results from our laboratory plus new ones which show that growth cones release serotonin tonically and such release can be stimulated by potassium in a calcium-dependent manner. The present results, together with other author's data, suggest a physiological basis for the putative role of serotonin as a trophic factor during nervous system development.

Comprehensive evaluation system of intelligent urban growth

NASA Astrophysics Data System (ADS)

Li, Lian-Yan; Ren, Xiao-Bin

2017-06-01

With the rapid urbanization of the world, urban planning has become increasingly important and necessary to ensure people have access to equitable and sustainable homes, resources and jobs.This article is to talk about building an intelligent city evaluation system.First,using System Analysis Model(SAM) which concludes literature data analysis and stepwise regression analysis to describe intelligent growth scientifically and obtain the evaluation index. Then,using the improved entropy method to obtain the weight of the evaluation index.Afterwards, establishing a complete Smart Growth Comprehensive Evaluation Model(SGCEM).Finally,testing the correctness of the model.Choosing Otago(New Zealand )and Yumen(China) as research object by data mining and SGCEM model,then we get Yumen and Otago’s rational degree’s values are 0.3485 and 0.5376 respectively. It’s believed that the Otago’s smart level is higher,and it is found that the estimated value of rationality is consistent with the reality.

New simulation model of multicomponent crystal growth and inhibition.

PubMed

Wathen, Brent; Kuiper, Michael; Walker, Virginia; Jia, Zongchao

2004-04-02

We review a novel computational model for the study of crystal structures both on their own and in conjunction with inhibitor molecules. The model advances existing Monte Carlo (MC) simulation techniques by extending them from modeling 3D crystal surface patches to modeling entire 3D crystals, and by including the use of "complex" multicomponent molecules within the simulations. These advances makes it possible to incorporate the 3D shape and non-uniform surface properties of inhibitors into simulations, and to study what effect these inhibitor properties have on the growth of whole crystals containing up to tens of millions of molecules. The application of this extended MC model to the study of antifreeze proteins (AFPs) and their effects on ice formation is reported, including the success of the technique in achieving AFP-induced ice-growth inhibition with concurrent changes to ice morphology that mimic experimental results. Simulations of ice-growth inhibition suggest that the degree of inhibition afforded by an AFP is a function of its ice-binding position relative to the underlying anisotropic growth pattern of ice. This extended MC technique is applicable to other crystal and crystal-inhibitor systems, including more complex crystal systems such as clathrates.

Removal of metal from acid mine drainage using a hybrid system including a pipes inserted microalgae reactor.

PubMed

Park, Young-Tae; Lee, Hongkyun; Yun, Hyun-Shik; Song, Kyung-Guen; Yeom, Sung-Ho; Choi, Jaeyoung

2013-12-01

In this study, the microalgae culture system to combined active treatment system and pipe inserted microalgae reactor (PIMR) was investigated. After pretreated AMD in active treatment system, the effluent load to PIMR in order to Nephroselmis sp. KGE 8 culture. In experiment, effect of iron on growth and lipid accumulation in microalgae were inspected. The 2nd pretreatment effluent was economic feasibility of microalgae culture and lipid accumulation. The growth kinetics of the microalgae are modeled using logistic growth model and the model is primarily parameterized from data obtained through an experimental study where PIMR were dosed with BBM, BBM added 10 mg L(-1) iron and 2nd pretreatment effluent. Moreover, the continuous of microalgae culture in PIMR can be available. Overall, this study indicated that the use of pretreated AMD is a viable method for culture microalgae and lipid accumulation. Copyright © 2013 Elsevier Ltd. All rights reserved.

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

PubMed

Nilsson, Avlant; Mardinoglu, Adil; Nielsen, Jens

2017-01-01

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

VERIFICATION OF URBAN RUNOFF MODELS

EPA Science Inventory

Wet Weather Flow Models are used throughout the United States for evaluation of the sanitary, storm and combined sewer systems. Models are used for planning new systems or upgrading of existing systems to accommodate growth or to control undersirable overflows and associated wat...

Growth Dynamics of Information Search Services

ERIC Educational Resources Information Center

Lindquist, Mats G.

1978-01-01

An analysis of computer-based search services (ISSs) from a system's viewpoint, using a continuous simulation model to reveal growth and stagnation of a typical system is presented, as well as an analysis of decision making for an ISS. (Author/MBR)

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

NASA Astrophysics Data System (ADS)

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

2010-12-01

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

Theoretical analysis of the axial growth of nanowires starting with a binary eutectic droplet via vapor-liquid-solid mechanism

NASA Astrophysics Data System (ADS)

Liu, Qing; Li, Hejun; Zhang, Yulei; Zhao, Zhigang

2018-06-01

A series of theoretical analysis is carried out for the axial vapor-liquid-solid (VLS) growth of nanowires starting with a binary eutectic droplet. The growth model considering the entire process of axial VLS growth is a development of the approaches already developed by previous studies. In this model, the steady and unsteady state growth are considered both. The amount of solute species in a variable liquid droplet, the nanowire length, radius, growth rate and all other parameters during the entire axial growth process are treated as functions of growth time. The model provides theoretical predictions for the formation of nanowire shape, the length-radius and growth rate-radius dependences. It is also suggested by the model that the initial growth of single nanowire is significantly affected by Gibbs-Thompson effect due to the shape change. The model was applied on predictions of available experimental data of Si and Ge nanowires grown from Au-Si and Au-Ge systems respectively reported by other works. The calculations with the proposed model are in satisfactory agreement with the experimental results of the previous works.

Mathematical modeling of solid cancer growth with angiogenesis

PubMed Central

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

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

PubMed

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

2017-01-31

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

Modeling complexity in engineered infrastructure system: Water distribution network as an example

NASA Astrophysics Data System (ADS)

Zeng, Fang; Li, Xiang; Li, Ke

2017-02-01

The complex topology and adaptive behavior of infrastructure systems are driven by both self-organization of the demand and rigid engineering solutions. Therefore, engineering complex systems requires a method balancing holism and reductionism. To model the growth of water distribution networks, a complex network model was developed following the combination of local optimization rules and engineering considerations. The demand node generation is dynamic and follows the scaling law of urban growth. The proposed model can generate a water distribution network (WDN) similar to reported real-world WDNs on some structural properties. Comparison with different modeling approaches indicates that a realistic demand node distribution and co-evolvement of demand node and network are important for the simulation of real complex networks. The simulation results indicate that the efficiency of water distribution networks is exponentially affected by the urban growth pattern. On the contrary, the improvement of efficiency by engineering optimization is limited and relatively insignificant. The redundancy and robustness, on another aspect, can be significantly improved through engineering methods.

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

PubMed Central

Kalmykov, Lev V.

2015-01-01

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

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

NASA Technical Reports Server (NTRS)

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

1992-01-01

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

Oxidation stress evolution and relaxation of oxide film/metal substrate system

NASA Astrophysics Data System (ADS)

Dong, Xuelin; Feng, Xue; Hwang, Keh-Chih

2012-07-01

Stresses in the oxide film/metal substrate system are crucial to the reliability of the system at high temperature. Two models for predicting the stress evolution during isothermal oxidation are proposed. The deformation of the system is depicted by the curvature for single surface oxidation. The creep strain of the oxide and metal, and the lateral growth strain of the oxide are considered. The proposed models are compared with the experimental results in literature, which demonstrates that the elastic model only considering for elastic strain gives an overestimated stress in magnitude, but the creep model is consistent with the experimental data and captures the stress relaxation phenomenon during oxidation. The effects of the parameter for the lateral growth strain rate are also analyzed.

Vibroconvective mixing applied to vertical Bridgman growth

NASA Astrophysics Data System (ADS)

Zawilski, Kevin T.; Claudia, M.; Custodio, C.; DeMattei, Robert C.; Feigelson, Robert S.

2003-10-01

A promising method for stirring melts during vertical Bridgman growth is the coupled vibrational stirring (CVS) method. It involves the application of low frequency vibrations to the outside of the growth ampoule and produces strong flows emanating from the fluid surface. Although the technique was pioneered a number of years ago, previous studies have not provided sufficient information to explain how to control CVS generated flows in a particular system. This paper examines both the fluid flow produced by CVS and the effect of these flows on a model oxide growth system. CVS generated flows were studied using tracer particles in a water/glycerin system. The particle velocities were measured as a function of distance from the fluid surface. A large velocity gradient, decreasing from the surface, was found to be present. The velocity profile produced was dependent on the vibrational amplitude and frequency, the crucible diameter, and the fluid viscosity. The effects of CVS flows on the crystal growth interface were studied using NaNO 3 as a model oxide. Under non-growth conditions (i.e. no furnace or crucible translation), the solid-liquid interface position was found to be a strong function of vibrational frequency once CVS generated flows approached the interface. During crystal growth, undesirable growth rate fluctuations were found as the growth interface moved into regions of increasing fluid flow. This data suggests that a control system in which CVS flows are continuously decreased during growth to maintain a constant flow rate in the vicinity of the growth interface is necessary in order to prevent or reduce growth rate fluctuations.

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

Treesearch

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

2010-01-01

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

Modeling Vascularized Bone Regeneration Within a Porous Biodegradable CaP Scaffold Loaded with Growth Factors

PubMed Central

Sun, X; Kang, Y; Bao, J; Zhang, Y; Yang, Y; Zhou, X

2013-01-01

Osteogenetic microenvironment is a complex constitution in which extracellular matrix (ECM) molecules, stem cells and growth factors each interact to direct the coordinate regulation of bone tissue development. Importantly, angiogenesis improvement and revascularization are critical for osteogenesis during bone tissue regeneration processes. In this study, we developed a three-dimensional (3D) multi-scale system model to study cell response to growth factors released from a 3D biodegradable porous calcium phosphate (CaP) scaffold. Our model reconstructed the 3D bone regeneration system and examined the effects of pore size and porosity on bone formation and angiogenesis. The results suggested that scaffold porosity played a more dominant role in affecting bone formation and angiogenesis compared with pore size, while the pore size could be controlled to tailor the growth factor release rate and release fraction. Furthermore, a combination of gradient VEGF with BMP2 and Wnt released from the multi-layer scaffold promoted angiogenesis and bone formation more readily than single growth factors. These results demonstrated that the developed model can be potentially applied to predict vascularized bone regeneration with specific scaffold and growth factors. PMID:23566802

A smart growth evaluation model based on data envelopment analysis

NASA Astrophysics Data System (ADS)

Zhang, Xiaokun; Guan, Yongyi

2018-04-01

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

Stochastic cellular automata model of neurosphere growth: Roles of proliferative potential, contact inhibition, cell death, and phagocytosis.

PubMed

Sipahi, Rifat; Zupanc, Günther K H

2018-05-14

Neural stem and progenitor cells isolated from the central nervous system form, under specific culture conditions, clonal cell clusters known as neurospheres. The neurosphere assay has proven to be a powerful in vitro system to study the behavior of such cells and the development of their progeny. However, the theory of neurosphere growth has remained poorly understood. To overcome this limitation, we have, in the present paper, developed a cellular automata model, with which we examined the effects of proliferative potential, contact inhibition, cell death, and clearance of dead cells on growth rate, final size, and composition of neurospheres. Simulations based on this model indicated that the proliferative potential of the founder cell and its progenitors has a major influence on neurosphere size. On the other hand, contact inhibition of proliferation limits the final size, and reduces the growth rate, of neurospheres. The effect of this inhibition is particularly dramatic when a stem cell becomes encapsulated by differentiated or other non-proliferating cells, thereby suppressing any further mitotic division - despite the existing proliferative potential of the stem cell. Conversely, clearance of dead cells through phagocytosis is predicted to accelerate growth by reducing contact inhibition. A surprising prediction derived from our model is that cell death, while resulting in a decrease in growth rate and final size of neurospheres, increases the degree of differentiation of neurosphere cells. It is likely that the cellular automata model developed as part of the present investigation is applicable to the study of tissue growth in a wide range of systems. Copyright © 2018 Elsevier Ltd. All rights reserved.

Power-law Growth and Punctuated Equilibrium Dynamics in Water Resources Systems

NASA Astrophysics Data System (ADS)

Parolari, A.; Katul, G. G.; Porporato, A. M.

2015-12-01

The global rise in population-driven water scarcity and recent appreciation of strong dynamic coupling between human and natural systems has called for new approaches to predict the future sustainability of regional and global water resources systems. The dynamics of coupled human-water systems are driven by a complex set of social, environmental, and technological factors. Present projections of water resources systems range from a finite carrying capacity regulated by accessible freshwater, or `peak renewable water,' to punctuated evolution with new supplied and improved efficiency gained from technological and social innovation. However, these projections have yet to be quantified from observations or in a comprehensive theoretical framework. Using data on global water withdrawals and storage capacity of regional water supply systems, non-trivial dynamics are identified in water resources systems development over time, including power-law growth and punctuated equilibria. Two models are introduced to explain this behavior: (1) a delay differential equation and (2) a power-law with log-periodic oscillations, both of which rely on past conditions (or system memory) to describe the present rate of growth in the system. In addition, extension of the first model demonstrates how system delays and punctuated equilibria can emerge from coupling between human population growth and associated resource demands. Lastly, anecdotal evidence is used to demonstrate the likelihood of power-law growth in global water use from the agricultural revolution 3000 BC to the present. In a practical sense, the presence of these patterns in models with delayed oscillations suggests that current decision-making related to water resources development results from the historical accumulation of resource use decisions, technological and social changes, and their consequences.

Kinetic Monte Carlo Simulation of the Growth of Various Nanostructures through Atomic and Cluster Deposition: Application to Gold Nanostructure Growth on Graphite

NASA Astrophysics Data System (ADS)

Claassens, C. H.; Hoffman, M. J. H.; Terblans, J. J.; Swart, H. C.

2006-01-01

A Kinetic Monte Carlo (KMC) method is presented to describe the growth of metallic nanostructures through atomic and cluster deposition in the mono -and multilayer regime. The model makes provision for homo- and heteroepitaxial systems with small lattice mismatch. The accuracy of the model is tested with simulations of the growth of gold nanostructures on HOPG and comparisons are made with existing experimental data.

Stochastic nonlinear dynamics pattern formation and growth models

PubMed Central

Yaroslavsky, Leonid P

2007-01-01

Stochastic evolutionary growth and pattern formation models are treated in a unified way in terms of algorithmic models of nonlinear dynamic systems with feedback built of a standard set of signal processing units. A number of concrete models is described and illustrated by numerous examples of artificially generated patterns that closely imitate wide variety of patterns found in the nature. PMID:17908341

The role of model dynamics in ensemble Kalman filter performance for chaotic systems

USGS Publications Warehouse

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.

Treatment of CELSS and PCELSS waste to produce nutrients for plant growth. [Controlled Ecological Life Support Systems and Partially Controlled Ecological Life Support Systems

NASA Technical Reports Server (NTRS)

Modell, M.; Meissner, H.; Karel, M.; Carden, J.; Lewis, S.

1981-01-01

The research program entitled 'Development of a Prototype Experiment for Treating CELSS (Controlled Ecological Life Support Systems) and PCELSS (Partially Controlled Ecological Life Support Systems) Wastes to Produce Nutrients for Plant Growth' consists of two phases: (1) the development of the neccessary facilities, chemical methodologies and models for meaningful experimentation, and (2) the application of what methods and devices are developed to the interfacing of waste oxidation with plant growth. Homogeneous samples of freeze-dried human feces and urine have been prepared to ensure comparability of test results between CELSS waste treatment research groups. A model of PCELSS food processing wastes has been developed, and an automated gas chromatographic system to analyze oxidizer effluents was designed and brought to operational status. Attention is given the component configuration of the wet oxidation system used by the studies.

A quasi-chemical model for the growth and death of microorganisms in foods by non-thermal and high-pressure processing.

PubMed

Doona, Christopher J; Feeherry, Florence E; Ross, Edward W

2005-04-15

Predictive microbial models generally rely on the growth of bacteria in laboratory broth to approximate the microbial growth kinetics expected to take place in actual foods under identical environmental conditions. Sigmoidal functions such as the Gompertz or logistics equation accurately model the typical microbial growth curve from the lag to the stationary phase and provide the mathematical basis for estimating parameters such as the maximum growth rate (MGR). Stationary phase data can begin to show a decline and make it difficult to discern which data to include in the analysis of the growth curve, a factor that influences the calculated values of the growth parameters. In contradistinction, the quasi-chemical kinetics model provides additional capabilities in microbial modelling and fits growth-death kinetics (all four phases of the microbial lifecycle continuously) for a general set of microorganisms in a variety of actual food substrates. The quasi-chemical model is differential equations (ODEs) that derives from a hypothetical four-step chemical mechanism involving an antagonistic metabolite (quorum sensing) and successfully fits the kinetics of pathogens (Staphylococcus aureus, Escherichia coli and Listeria monocytogenes) in various foods (bread, turkey meat, ham and cheese) as functions of different hurdles (a(w), pH, temperature and anti-microbial lactate). The calculated value of the MGR depends on whether growth-death data or only growth data are used in the fitting procedure. The quasi-chemical kinetics model is also exploited for use with the novel food processing technology of high-pressure processing. The high-pressure inactivation kinetics of E. coli are explored in a model food system over the pressure (P) range of 207-345 MPa (30,000-50,000 psi) and the temperature (T) range of 30-50 degrees C. In relatively low combinations of P and T, the inactivation curves are non-linear and exhibit a shoulder prior to a more rapid rate of microbial destruction. In the higher P, T regime, the inactivation plots tend to be linear. In all cases, the quasi-chemical model successfully fit the linear and curvi-linear inactivation plots for E. coli in model food systems. The experimental data and the quasi-chemical mathematical model described herein are candidates for inclusion in ComBase, the developing database that combines data and models from the USDA Pathogen Modeling Program and the UK Food MicroModel.

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

NASA Astrophysics Data System (ADS)

Dehghan, Mehdi; Mohammadi, Vahid

2017-03-01

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

Modelling the growth of plants with a uniform growth logistics.

PubMed

Kilian, H G; Bartkowiak, D; Kazda, M; Kaufmann, D

2014-05-21

The increment model has previously been used to describe the growth of plants in general. Here, we examine how the same logistics enables the development of different superstructures. Data from the literature are analyzed with the increment model. Increments are growth-invariant molecular clusters, treated as heuristic particles. This approach formulates the law of mass action for multi-component systems, describing the general properties of superstructures which are optimized via relaxation processes. The daily growth patterns of hypocotyls can be reproduced implying predetermined growth invariant model parameters. In various species, the coordinated formation and death of fine roots are modeled successfully. Their biphasic annual growth follows distinct morphological programs but both use the same logistics. In tropical forests, distributions of the diameter in breast height of trees of different species adhere to the same pattern. Beyond structural fluctuations, competition and cooperation within and between the species may drive optimization. All superstructures of plants examined so far could be reproduced with our approach. With genetically encoded growth-invariant model parameters (interaction with the environment included) perfect morphological development runs embedded in the uniform logistics of the increment model. Copyright © 2014 Elsevier Ltd. All rights reserved.

Revisiting the Stability of Spatially Heterogeneous Predator-Prey Systems Under Eutrophication.

PubMed

Farkas, J Z; Morozov, A Yu; Arashkevich, E G; Nikishina, A

2015-10-01

We employ partial integro-differential equations to model trophic interaction in a spatially extended heterogeneous environment. Compared to classical reaction-diffusion models, this framework allows us to more realistically describe the situation where movement of individuals occurs on a faster time scale than on the demographic (population) time scale, and we cannot determine population growth based on local density. However, most of the results reported so far for such systems have only been verified numerically and for a particular choice of model functions, which obviously casts doubts about these findings. In this paper, we analyse a class of integro-differential predator-prey models with a highly mobile predator in a heterogeneous environment, and we reveal the main factors stabilizing such systems. In particular, we explore an ecologically relevant case of interactions in a highly eutrophic environment, where the prey carrying capacity can be formally set to 'infinity'. We investigate two main scenarios: (1) the spatial gradient of the growth rate is due to abiotic factors only, and (2) the local growth rate depends on the global density distribution across the environment (e.g. due to non-local self-shading). For an arbitrary spatial gradient of the prey growth rate, we analytically investigate the possibility of the predator-prey equilibrium in such systems and we explore the conditions of stability of this equilibrium. In particular, we demonstrate that for a Holling type I (linear) functional response, the predator can stabilize the system at low prey density even for an 'unlimited' carrying capacity. We conclude that the interplay between spatial heterogeneity in the prey growth and fast displacement of the predator across the habitat works as an efficient stabilizing mechanism. These results highlight the generality of the stabilization mechanisms we find in spatially structured predator-prey ecological systems in a heterogeneous environment.

Direct atomic force microscopy observation of DNA tile crystal growth at the single-molecule level.

PubMed

Evans, Constantine G; Hariadi, Rizal F; Winfree, Erik

2012-06-27

While the theoretical implications of models of DNA tile self-assembly have been extensively researched and such models have been used to design DNA tile systems for use in experiments, there has been little research testing the fundamental assumptions of those models. In this paper, we use direct observation of individual tile attachments and detachments of two DNA tile systems on a mica surface imaged with an atomic force microscope (AFM) to compile statistics of tile attachments and detachments. We show that these statistics fit the widely used kinetic Tile Assembly Model and demonstrate AFM movies as a viable technique for directly investigating DNA tile systems during growth rather than after assembly.

Growth-promoting technologies decrease the carbon footprint, ammonia emissions, and costs of California beef production systems.

PubMed

Stackhouse, K R; Rotz, C A; Oltjen, J W; Mitloehner, F M

2012-12-01

Increased animal performance is suggested as one of the most effective mitigation strategies to decrease greenhouse gas (GHG) and ammonia (NH(3)) emissions from livestock production per unit of product produced. Little information exists, however, on the effects of increased animal productivity on the net decrease in emission from beef production systems. A partial life cycle assessment (LCA) was conducted using the Integrated Farm System Model (IFSM) to estimate GHG and NH(3) emissions from representative beef production systems in California that use various management technologies to enhance animal performance. The IFSM is a farm process model that simulates crop growth, feed production, animal performance, and manure production and handling through time to predict the performance, economics, and environmental impacts of production systems. The simulated beef production systems compared were 1) Angus-natural, with no use of growth-enhancing technologies, 2) Angus-implant, with ionophore and growth-promoting implant (e.g., estrogen/trenbolone acetate-based) application, 3) Angus-ß2-adrenergic agonists (BAA; e.g., zilpaterol), with ionophore, growth-promoting implant, and BAA application, 4) Holstein-implant, with growth implant and ionophore application, and 5) Holstein-BAA, with ionophore, growth implant, and BAA use. During the feedlot phase, use of BAA decreased NH(3) emission by 4 to 9 g/kg HCW, resulting in a 7% decrease in NH(3) loss from the full production system. Combined use of ionophore, growth implant, and BAA treatments decreased NH(3) emission from the full production system by 14 g/kg HCW, or 13%. The C footprint of beef was decreased by 2.2 kg carbon dioxide equivalent (CO(2)e)/kg HCW using all the growth-promoting technologies, and the Holstein beef footprint was decreased by 0.5 kg CO(2)e/kg HCW using BAA. Over the full production systems, these decreases were relatively small at 9% and 5% for Angus and Holstein beef, respectively. The growth-promoting technologies we evaluated are a cost-effective way to mitigate GHG and NH(3) emissions, but naturally managed cattle can bring a similar net return to Angus cattle treated with growth-promoting technologies when sold at an 8% greater premium price.

Stochastic ontogenetic growth model

NASA Astrophysics Data System (ADS)

West, B. J.; West, D.

2012-02-01

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

A diameter growth model for the SRS FIA

Treesearch

David Gartner

2015-01-01

Changes in the national Forest Inventory and Analysis (FIA) processing system required the Southern Research Station’s FIA unit to create a diameter growth model to estimate the growth of trees that could not be measured at both ends of a measurement interval. Examples of such trees are trees that have died or been harvested, and trees that grow over the minimum...

The GP problem: quantifying gene-to-phenotype relationships.

PubMed

Cooper, Mark; Chapman, Scott C; Podlich, Dean W; Hammer, Graeme L

2002-01-01

In this paper we refer to the gene-to-phenotype modeling challenge as the GP problem. Integrating information across levels of organization within a genotype-environment system is a major challenge in computational biology. However, resolving the GP problem is a fundamental requirement if we are to understand and predict phenotypes given knowledge of the genome and model dynamic properties of biological systems. Organisms are consequences of this integration, and it is a major property of biological systems that underlies the responses we observe. We discuss the E(NK) model as a framework for investigation of the GP problem and the prediction of system properties at different levels of organization. We apply this quantitative framework to an investigation of the processes involved in genetic improvement of plants for agriculture. In our analysis, N genes determine the genetic variation for a set of traits that are responsible for plant adaptation to E environment-types within a target population of environments. The N genes can interact in epistatic NK gene-networks through the way that they influence plant growth and development processes within a dynamic crop growth model. We use a sorghum crop growth model, available within the APSIM agricultural production systems simulation model, to integrate the gene-environment interactions that occur during growth and development and to predict genotype-to-phenotype relationships for a given E(NK) model. Directional selection is then applied to the population of genotypes, based on their predicted phenotypes, to simulate the dynamic aspects of genetic improvement by a plant-breeding program. The outcomes of the simulated breeding are evaluated across cycles of selection in terms of the changes in allele frequencies for the N genes and the genotypic and phenotypic values of the populations of genotypes.

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

NASA Astrophysics Data System (ADS)

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

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

Genome-scale biological models for industrial microbial systems.

PubMed

Xu, Nan; Ye, Chao; Liu, Liming

2018-04-01

The primary aims and challenges associated with microbial fermentation include achieving faster cell growth, higher productivity, and more robust production processes. Genome-scale biological models, predicting the formation of an interaction among genetic materials, enzymes, and metabolites, constitute a systematic and comprehensive platform to analyze and optimize the microbial growth and production of biological products. Genome-scale biological models can help optimize microbial growth-associated traits by simulating biomass formation, predicting growth rates, and identifying the requirements for cell growth. With regard to microbial product biosynthesis, genome-scale biological models can be used to design product biosynthetic pathways, accelerate production efficiency, and reduce metabolic side effects, leading to improved production performance. The present review discusses the development of microbial genome-scale biological models since their emergence and emphasizes their pertinent application in improving industrial microbial fermentation of biological products.

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

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

Lovelett, Robert J.; Pang, Xueqi; Roberts, Tyler M.

Developing high fidelity quantitative models of solid state reaction systems can be challenging, especially in deposition systems where, in addition to the multiple competing processes occurring simultaneously, the solid interacts with its atmosphere. In this work, we develop a model for the growth of a thin solid film where species from the atmosphere adsorb, diffuse, and react with the film. The model is mesoscale and describes an entire film with thickness on the order of microns. Because it is stochastic, the model allows us to examine inhomogeneities and agglomerations that would be impossible to characterize with deterministic methods. We demonstratemore » the modeling approach with the example of chalcopyrite Cu(InGa)(SeS){sub 2} thin film growth via precursor reaction, which is a common industrial method for fabricating thin film photovoltaic modules. The model is used to understand how and why through-film variation in the composition of Cu(InGa)(SeS){sub 2} thin films arises and persists. We believe that the model will be valuable as an effective quantitative description of many other materials systems used in semiconductors, energy storage, and other fast-growing industries.« less

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

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

Lovelett, Robert J.; Pang, Xueqi; Roberts, Tyler M.

Developing high fidelity quantitative models of solid state reaction systems can be challenging, especially in deposition systems where, in addition to the multiple competing processes occurring simultaneously, the solid interacts with its atmosphere. Here, we develop a model for the growth of a thin solid film where species from the atmosphere adsorb, diffuse, and react with the film. The model is mesoscale and describes an entire film with thickness on the order of microns. Because it is stochastic, the model allows us to examine inhomogeneities and agglomerations that would be impossible to characterize with deterministic methods. We also demonstrate themore » modeling approach with the example of chalcopyrite Cu(InGa)(SeS) 2 thin film growth via precursor reaction, which is a common industrial method for fabricating thin film photovoltaic modules. The model is used to understand how and why through-film variation in the composition of Cu(InGa)(SeS) 2 thin films arises and persists. Finally, we believe that the model will be valuable as an effective quantitative description of many other materials systems used in semiconductors, energy storage, and other fast-growing industries.« less

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

DOE PAGES

Lovelett, Robert J.; Pang, Xueqi; Roberts, Tyler M.; ...

2016-04-01

Developing high fidelity quantitative models of solid state reaction systems can be challenging, especially in deposition systems where, in addition to the multiple competing processes occurring simultaneously, the solid interacts with its atmosphere. Here, we develop a model for the growth of a thin solid film where species from the atmosphere adsorb, diffuse, and react with the film. The model is mesoscale and describes an entire film with thickness on the order of microns. Because it is stochastic, the model allows us to examine inhomogeneities and agglomerations that would be impossible to characterize with deterministic methods. We also demonstrate themore » modeling approach with the example of chalcopyrite Cu(InGa)(SeS) 2 thin film growth via precursor reaction, which is a common industrial method for fabricating thin film photovoltaic modules. The model is used to understand how and why through-film variation in the composition of Cu(InGa)(SeS) 2 thin films arises and persists. Finally, we believe that the model will be valuable as an effective quantitative description of many other materials systems used in semiconductors, energy storage, and other fast-growing industries.« less

A Model of Controlled Growth

NASA Astrophysics Data System (ADS)

Bressan, Alberto; Lewicka, Marta

2018-03-01

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

A mathematical model of microalgae growth in cylindrical photobioreactor

NASA Astrophysics Data System (ADS)

Bakeri, Noorhadila Mohd; Jamaian, Siti Suhana

2017-08-01

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

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

NASA Astrophysics Data System (ADS)

Donatelli, Donatella; Trivisa, Konstantina

2014-07-01

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

Control of fluid flow during Bridgman crystal growth using low-frequency vibrational stirring

NASA Astrophysics Data System (ADS)

Zawilski, Kevin Thomas

The goal of this research program was to develop an in depth understanding of a promising new method for stirring crystal growth melts called coupled vibrational stirring (CVS). CVS is a mixing technique that can be used in sealed systems and produces rapid mixing through vortex flows. Under normal operating conditions, CVS uses low-frequency vibrations to move the growth crucible along a circular path, producing a surface wave and convection in the melt. This research focused on the application of CVS to the vertical Bridgman technique. CVS generated flows were directly studied using a physical modeling system containing water/glycerin solutions. Sodium nitrate was chosen as a model growth system because the growth process could be directly observed using a transparent furnace. Lead magnesium niobate-lead titanate (PMNT) was chosen as the third system because of its potential application for high performance solid state transducers and actuators. In this study, the critical parameters for controlling CVS flows in cylindrical Bridgman systems were established. One of the most important results obtained was the dependence of an axial velocity gradient on the vibrational frequency. By changing the frequency, the intensity of fluid flow at a given depth can be easily manipulated. The intensity of CVS flows near the crystal-melt interface was found to be important. When flow intensity near the interface increased during growth, large growth rate fluctuations and significant changes in interface shape were observed. To eliminate such fluctuations, a constant flow rate near the crystal-melt interface was maintained by decreasing the vibrational frequency. A continuous frequency ramp was found to be essential to grow crystals of good quality under strong CVS flows. CVS generated flows were also useful in controlling the shape of the growth interface. In the sodium nitrate system without stirring, high growth rates produced a very concave interface. By adjusting the flow intensity near the interface, CVS flows were able to flatten the growth interface under these extreme growth conditions.

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.

Emergent dynamics of the climate-economy system in the Anthropocene.

PubMed

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.

Local stability of a five dimensional food chain model in the ocean

NASA Astrophysics Data System (ADS)

Kusumawinahyu, W. M.; Hidayatulloh, M. R.

2014-02-01

This paper discuss a food chain model on a microbiology ecosystem in the ocean, where predation process occurs. Four population growth rates are discussed, namely bacteria, phytoplankton, zooplankton, and protozoa growth rate. When the growth of nutrient density is also considered, the model is governed by a five dimensional dynamical system. The system considered in this paper is a modification of a model proposed by Hadley and Forbes [1], by taking Holling Type I as the functional response. For sake of simplicity, the model needs to be scaled. Dynamical behavior, such as existence condition of equilibrium points and their local stability are addressed. There are eight equilibrium points, where two of them exist under certain conditions. Three equilibrium points are unstable, while two points stable under certain conditions and the other three points are stable if the Ruth-Hurwitz criteria are satisfied. Numerical simulations are carried out to illustrate analytical findings.

Morphological stability and kinetics in crystal growth from vapors

NASA Technical Reports Server (NTRS)

Rosenberger, Franz

1990-01-01

The following topics are discussed: (1) microscopy image storage and processing system; (2) growth kinetics and morphology study with carbon tetrabromide; (3) photothermal deflection vapor growth setup; (4) bridgman growth of iodine single crystals; (5) vapor concentration distribution measurement during growth; and (6) Monte Carlo modeling of anisotropic growth kinetics and morphology. A collection of presentations and publications of these results are presented.

NASA Earth Science Research Results for Improved Regional Crop Yield Prediction

NASA Astrophysics Data System (ADS)

Mali, P.; O'Hara, C. G.; Shrestha, B.; Sinclair, T. R.; G de Goncalves, L. G.; Salado Navarro, L. R.

2007-12-01

National agencies such as USDA Foreign Agricultural Service (FAS), Production Estimation and Crop Assessment Division (PECAD) work specifically to analyze and generate timely crop yield estimates that help define national as well as global food policies. The USDA/FAS/PECAD utilizes a Decision Support System (DSS) called CADRE (Crop Condition and Data Retrieval Evaluation) mainly through an automated database management system that integrates various meteorological datasets, crop and soil models, and remote sensing data; providing significant contribution to the national and international crop production estimates. The "Sinclair" soybean growth model has been used inside CADRE DSS as one of the crop models. This project uses Sinclair model (a semi-mechanistic crop growth model) for its potential to be effectively used in a geo-processing environment with remote-sensing-based inputs. The main objective of this proposed work is to verify, validate and benchmark current and future NASA earth science research results for the benefit in the operational decision making process of the PECAD/CADRE DSS. For this purpose, the NASA South American Land Data Assimilation System (SALDAS) meteorological dataset is tested for its applicability as a surrogate meteorological input in the Sinclair model meteorological input requirements. Similarly, NASA sensor MODIS products is tested for its applicability in the improvement of the crop yield prediction through improving precision of planting date estimation, plant vigor and growth monitoring. The project also analyzes simulated Visible/Infrared Imager/Radiometer Suite (VIIRS, a future NASA sensor) vegetation product for its applicability in crop growth prediction to accelerate the process of transition of VIIRS research results for the operational use of USDA/FAS/PECAD DSS. The research results will help in providing improved decision making capacity to the USDA/FAS/PECAD DSS through improved vegetation growth monitoring from high spatial and temporal resolution remote sensing datasets; improved time-series meteorological inputs required for crop growth models; and regional prediction capability through geo-processing-based yield modeling.

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

PubMed Central

Llorente, Isidre; Montesinos, Emilio; Moragrega, Concepció

2017-01-01

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

Unraveling irradiation induced grain growth with in situ transmission electron microscopy and coordinated modeling

DOE PAGES

Bufford, D. C.; Abdeljawad, F. F.; Foiles, S. M.; ...

2015-11-09

Here, nanostructuring has been proposed as a method to enhance radiation tolerance, but many metallic systems are rejected due to significant concerns regarding long term grain boundary and interface stability. This work utilized recent advancements in transmission electron microscopy (TEM) to quantitatively characterize the grain size, texture, and individual grain boundary character in a nanocrystalline gold model system before and after in situ TEM ion irradiation with 10 MeV Si. The initial experimental measurements were fed into a mesoscale phase field model, which incorporates the role of irradiation-induced thermal events on boundary properties, to directly compare the observed and simulatedmore » grain growth with varied parameters. The observed microstructure evolution deviated subtly from previously reported normal grain growth in which some boundaries remained essentially static. In broader terms, the combined experimental and modeling techniques presented herein provide future avenues to enhance quantification and prediction of the thermal, mechanical, or radiation stability of grain boundaries in nanostructured crystalline systems.« less

Dynamic energy budget modeling reveals the potential of future growth and calcification for the coccolithophore Emiliania huxleyi in an acidified ocean.

PubMed

Muller, Erik B; Nisbet, Roger M

2014-06-01

Ocean acidification is likely to impact the calcification potential of marine organisms. In part due to the covarying nature of the ocean carbonate system components, including pH and CO2 and CO3(2-) levels, it remains largely unclear how each of these components may affect calcification rates quantitatively. We develop a process-based bioenergetic model that explains how several components of the ocean carbonate system collectively affect growth and calcification rates in Emiliania huxleyi, which plays a major role in marine primary production and biogeochemical carbon cycling. The model predicts that under the IPCC A2 emission scenario, its growth and calcification potential will have decreased by the end of the century, although those reductions are relatively modest. We anticipate that our model will be relevant for many other marine calcifying organisms, and that it can be used to improve our understanding of the impact of climate change on marine systems. © 2014 John Wiley & Sons Ltd.

An In vitro Model for Bacterial Growth on Human Stratum Corneum.

PubMed

van der Krieken, Danique A; Ederveen, Thomas H A; van Hijum, Sacha A F T; Jansen, Patrick A M; Melchers, Willem J G; Scheepers, Paul T J; Schalkwijk, Joost; Zeeuwen, Patrick L J M

2016-11-02

The diversity and dynamics of the skin microbiome in health and disease have been studied recently, but adequate model systems to study skin microbiotas in vitro are largely lacking. We developed an in vitro system that mimics human stratum corneum, using human callus as substrate and nutrient source for bacterial growth. The growth of several commensal and pathogenic bacterial strains was measured for up to one week by counting colony-forming units or by quantitative PCR with strain-specific primers. Human skin pathogens were found to survive amidst a minimal microbiome consisting of 2 major skin commensals: Staphylococcus epidermidis and Propionibacterium acnes. In addition, complete microbiomes, taken from the backs of healthy volunteers, were inoculated and maintained using this system. This model may enable the modulation of skin microbiomes in vitro and allow testing of pathogens, biological agents and antibiotics in a medium-throughput format.

Prediction of Land use changes using CA in GIS Environment

NASA Astrophysics Data System (ADS)

Kiavarz Moghaddam, H.; Samadzadegan, F.

2009-04-01

Urban growth is a typical self-organized system that results from the interaction between three defined systems; developed urban system, natural non-urban system and planned urban system. Urban growth simulation for an artificial city is carried out first. It evaluates a number of urban sprawl parameters including the size and shape of neighborhood besides testing different types of constraints on urban growth simulation. The results indicate that circular-type neighborhood shows smoother but faster urban growth as compared to nine-cell Moore neighborhood. Cellular Automata is proved to be very efficient in simulating the urban growth simulation over time. The strength of this technology comes from the ability of urban modeler to implement the growth simulation model, evaluating the results and presenting the output simulation results in visual interpretable environment. Artificial city simulation model provides an excellent environment to test a number of simulation parameters such as neighborhood influence on growth results and constraints role in driving the urban growth .Also, CA rules definition is critical stage in simulating the urban growth pattern in a close manner to reality. CA urban growth simulation and prediction of Tehran over the last four decades succeeds to simulate specified tested growth years at a high accuracy level. Some real data layer have been used in the CA simulation training phase such as 1995 while others used for testing the prediction results such as 2002. Tuning the CA growth rules is important through comparing the simulated images with the real data to obtain feedback. An important notice is that CA rules need also to be modified over time to adapt to the urban growth pattern. The evaluation method used on region basis has its advantage in covering the spatial distribution component of the urban growth process. Next step includes running the developed CA simulation over classified raster data for three years in a developed ArcGIS extention. A set of crisp rules are defined and calibrated based on real urban growth pattern. Uncertainty analysis is performed to evaluate the accuracy of the simulated results as compared to the historical real data. Evaluation shows promising results represented by the high average accuracies achieved. The average accuracy for the predicted growth images 1964 and 2002 is over 80 %. Modifying CA growth rules over time to match the growth pattern changes is important to obtain accurate simulation. This modification is based on the urban growth relationship for Tehran over time as can be seen in the historical raster data. The feedback obtained from comparing the simulated and real data is crucial in identifying the optimal set of CA rules for reliable simulation and calibrating growth steps.

Treatment Analysis in a Cancer Stem Cell Context Using a Tumor Growth Model Based on Cellular Automata.

PubMed

Monteagudo, Ángel; Santos, José

2015-01-01

Cancer can be viewed as an emergent behavior in terms of complex system theory and artificial life, Cellular Automata (CA) being the tool most used for studying and characterizing the emergent behavior. Different approaches with CA models were used to model cancer growth. The use of the abstract model of acquired cancer hallmarks permits the direct modeling at cellular level, where a cellular automaton defines the mitotic and apoptotic behavior of cells, and allows for an analysis of different dynamics of the cellular system depending on the presence of the different hallmarks. A CA model based on the presence of hallmarks in the cells, which includes a simulation of the behavior of Cancer Stem Cells (CSC) and their implications for the resultant growth behavior of the multicellular system, was employed. This modeling of cancer growth, in the avascular phase, was employed to analyze the effect of cancer treatments in a cancer stem cell context. The model clearly explains why, after treatment against non-stem cancer cells, the regrowth capability of CSCs generates a faster regrowth of tumor behavior, and also shows that a continuous low-intensity treatment does not favor CSC proliferation and differentiation, thereby allowing an unproblematic control of future tumor regrowth. The analysis performed indicates that, contrary to the current attempts at CSC control, trying to make CSC proliferation more difficult is an important point to consider, especially in the immediate period after a standard treatment for controlling non-stem cancer cell proliferation.

Feedback control of acoustic disturbance transient growth in triggering thermoacoustic instability

NASA Astrophysics Data System (ADS)

Zhao, Dan; Reyhanoglu, Mahmut

2014-08-01

Transient growth of acoustic disturbances could trigger thermoacoustic instability in a combustion system with non-orthogonal eigenmodes, even with stable eigenvalues. In this work, feedback control of transient growth of flow perturbations in a Rijke-type combustion system is considered. For this, a generalized thermoacoustic model with distributed monopole-like actuators is developed. The model is formulated in state-space to gain insights on the interaction between various eigenmodes and the dynamic response of the system to the actuators. Three critical parameters are identified: (1) the mode number, (2) the number of actuators, and (3) the locations of the actuators. It is shown that in general the number of the actuators K is related to the mode number N as K=N2. For simplicity in illustrating the main results of the paper, two different thermoacoustic systems are considered: system (a) with one mode and system (b) that involves two modes. The actuator location effect is studied in system (a) and it is found that the actuator location plays an important role in determining the control effort. In addition, sensitivity analysis of pressure- and velocity-related control parameters is conducted. In system (b), when the actuators are turned off (i.e., open-loop configuration), it is observed that acoustic energy transfers from the high frequency mode to the lower frequency mode. After some time, the energy is transferred back. Moreover, the high frequency oscillation grows into nonlinear limit cycle with the low frequency oscillation amplified. As a linear-quadratic regulator (LQR) is implemented to tune the actuators, both systems become asymptotically stable. However, the LQR controller fails in eliminating the transient growth, which may potentially trigger thermoacoustic instability. In order to achieve strict dissipativity (i.e., unity maximum transient growth), a transient growth controller is systematically designed and tested in both systems. Comparison is then made between the performance of the LQR controller and that of the transient growth controller. It is found in both systems that the transient growth controller achieves both exponential decay of the flow disturbance energy and unity maximum transient growth.

The 1974 AVCR Young Scholar Paper: An Open-System Model of Learning

ERIC Educational Resources Information Center

Winn, William

1975-01-01

Rejecting the cybernetic model of the learner, the author offers an open-system model based on von Bertalanffy's equation for growth of the living organism. The model produces four learning curves, not just the logarithmic curve produced by the successive approximations of the cybernetic model. (Editor)

Predicting crystal growth via a unified kinetic three-dimensional partition model

NASA Astrophysics Data System (ADS)

Anderson, Michael W.; Gebbie-Rayet, James T.; Hill, Adam R.; Farida, Nani; Attfield, Martin P.; Cubillas, Pablo; Blatov, Vladislav A.; Proserpio, Davide M.; Akporiaye, Duncan; Arstad, Bjørnar; Gale, Julian D.

2017-04-01

Understanding and predicting crystal growth is fundamental to the control of functionality in modern materials. Despite investigations for more than one hundred years, it is only recently that the molecular intricacies of these processes have been revealed by scanning probe microscopy. To organize and understand this large amount of new information, new rules for crystal growth need to be developed and tested. However, because of the complexity and variety of different crystal systems, attempts to understand crystal growth in detail have so far relied on developing models that are usually applicable to only one system. Such models cannot be used to achieve the wide scope of understanding that is required to create a unified model across crystal types and crystal structures. Here we describe a general approach to understanding and, in theory, predicting the growth of a wide range of crystal types, including the incorporation of defect structures, by simultaneous molecular-scale simulation of crystal habit and surface topology using a unified kinetic three-dimensional partition model. This entails dividing the structure into ‘natural tiles’ or Voronoi polyhedra that are metastable and, consequently, temporally persistent. As such, these units are then suitable for re-construction of the crystal via a Monte Carlo algorithm. We demonstrate our approach by predicting the crystal growth of a diverse set of crystal types, including zeolites, metal-organic frameworks, calcite, urea and L-cystine.

Cells competition in tumor growth poroelasticity

NASA Astrophysics Data System (ADS)

Fraldi, Massimiliano; Carotenuto, Angelo R.

2018-03-01

Growth of biological tissues has been recently treated within the framework of Continuum Mechanics, by adopting heterogeneous poroelastic models where the interaction between soft matrix and interstitial fluid flow is coupled with inelastic effects ad hoc introduced to simulate the macroscopic volumetric growth determined by cells division, cells growth and extracellular matrix changes occurring at the micro-scale level. These continuum models seem to overcome some limitations intrinsically associated to other alternative approaches based on mass balances in multiphase systems, because the crucial role played by residual stresses accompanying growth and nutrients walkway is preserved. Nevertheless, when these strategies are applied to analyze solid tumors, mass growth is usually assigned in a prescribed form that essentially copies the in vitro measured intrinsic growth rates of the cell species. As a consequence, some important cell-cell dynamics governing mass evolution and invasion rates of cancer cells, as well as their coupling with feedback mechanisms associated to in situ stresses, are inevitably lost and thus the spatial distribution and the evolution with time of the growth inside the tumor -which would be results rather than inputs- are forced to enter in the model simply as data. In order to solve this paradox, it is here proposed an enhanced multi-scale poroelastic model undergoing large deformations and embodying inelastic growth, where the net growth terms directly result from the "interspecific" predator-prey (Volterra/Lotka-like) competition occurring at the micro-scale level between healthy and abnormal cell species. In this way, a system of fully-coupled non-linear PDEs is derived to describe how the fight among cell species to grab the available common resources, stress field, pressure gradients, interstitial fluid flows driving nutrients and inhomogeneous growth all simultaneously interact to decide the tumor fate.

The statistical mechanics of complex signaling networks: nerve growth factor signaling

NASA Astrophysics Data System (ADS)

Brown, K. S.; Hill, C. C.; Calero, G. A.; Myers, C. R.; Lee, K. H.; Sethna, J. P.; Cerione, R. A.

2004-10-01

The inherent complexity of cellular signaling networks and their importance to a wide range of cellular functions necessitates the development of modeling methods that can be applied toward making predictions and highlighting the appropriate experiments to test our understanding of how these systems are designed and function. We use methods of statistical mechanics to extract useful predictions for complex cellular signaling networks. A key difficulty with signaling models is that, while significant effort is being made to experimentally measure the rate constants for individual steps in these networks, many of the parameters required to describe their behavior remain unknown or at best represent estimates. To establish the usefulness of our approach, we have applied our methods toward modeling the nerve growth factor (NGF)-induced differentiation of neuronal cells. In particular, we study the actions of NGF and mitogenic epidermal growth factor (EGF) in rat pheochromocytoma (PC12) cells. Through a network of intermediate signaling proteins, each of these growth factors stimulates extracellular regulated kinase (Erk) phosphorylation with distinct dynamical profiles. Using our modeling approach, we are able to predict the influence of specific signaling modules in determining the integrated cellular response to the two growth factors. Our methods also raise some interesting insights into the design and possible evolution of cellular systems, highlighting an inherent property of these systems that we call 'sloppiness.'

The effect of crystallinity on cell growth in semi-crystalline microcellular foams by solid-state process: modeling and numerical simulation

NASA Astrophysics Data System (ADS)

Rezvanpanah, Elham; Ghaffarian Anbaran, S. Reza

2017-11-01

This study establishes a model and simulation scheme to describe the effect of crystallinity as one of the most effective parameters on cell growth phenomena in a solid batch foaming process. The governing model of cell growth dynamics, based on the well-known ‘Cell model’, is attained in details. To include the effect of crystallinity in the model, the properties of the polymer/gas mixtures (i.e. solubility, diffusivity, surface tension and viscosity) are estimated by modifying relations to consider the effect of crystallinity. A finite element-finite difference (FEFD) method is employed to solve the highly nonlinear and coupled equations of cell growth dynamics. The proposed simulation is able to evaluate all properties of the system at the given process condition and uses them to calculate the cell size, pressure and gas concentration gradient with time. A high-density polyethylene/nitrogen (HDPE/N2) system is used herein as a case study. Comparing the simulation results with the others works and experimental results verify the accuracy of the simulation scheme. The cell growth is a complicated combination of several phenomena. This study attempted to reach a better understanding of cell growth trend, driving and retarding forces and the effect of crystallinity on them.

Large-area sheet task advanced dendritic web growth development

NASA Technical Reports Server (NTRS)

Duncan, C. S.; Seidensticker, R. G.; Mchugh, J. P.

1983-01-01

Modeling in the development of low stress configurations for wide web growth is presented. Parametric sensitivity to identify design features which can be used for dynamic trimming of the furnace element was studied. Temperature measurements of experimental growth behavior led to modification in the growth system to improve lateral temperature distributions.

Multiscale model for microstructure evolution in multiphase materials: Application to the growth of isolated inclusions in presence of elasticity.

PubMed

Perez, Danny; Lewis, Laurent J

2006-09-01

We present a multiscale model based on the classical lattice time-dependent density-functional theory to study microstructure evolution in multiphase systems. As a first test of the method, we study the static and dynamic properties of isolated inclusions. Three cases are explored: elastically homogeneous systems, elastically inhomogeneous systems with soft inclusions, and elastically inhomogeneous systems with hard inclusions. The equilibrium properties of inclusions are shown to be consistent with previous results: both homogeneous and hard inclusions adopt a circular shape independent of their size, whereas soft inclusions are circular below a critical radius and elliptic above. In all cases, the Gibbs-Thomson relation is obeyed, except for a change in the prefactor at the critical radius in soft inclusions. Under growth conditions, homogeneous inclusions exhibit a Mullins-Sekerka shape instability [W. Mullins and R. Sekerka, J. Appl. Phys. 34, 323 (1963)], whereas in inhomogeneous systems, the growth of perturbations follows the Leo-Sekerka model [P. Leo and R. Sekerka, Acta Metall. 37, 3139 (1989)]. For soft inclusions, the mode instability regime is gradually replaced by a tip-growing mechanism, which leads to stable, strongly out-of-equilibrium shapes even at very low supersaturation. This mechanism is shown to significantly affect the growth dynamics of soft inclusions, whereas dynamical corrections to the growth rates are negligible in homogeneous and hard inclusions. Finally, due to its microscopic formulation, the model is shown to automatically take into account phenomena caused by the presence of the underlying discrete lattice: anisotropy of the interfacial energy, anisotropy of the kinetics, and preferential excitation of shape perturbations commensurate with the rotational symmetry of the lattice.

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.

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

USDA-ARS?s Scientific Manuscript database

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

Cotton growth modeling and assessment using UAS visual-band imagery

USDA-ARS?s Scientific Manuscript database

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

Dynamic metabolic modeling for a MAB bioprocess.

PubMed

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

2007-01-01

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

Endogenous fertility, altruistic behavior across generations, and social security systems.

PubMed

Prinz, A

1990-01-01

This study examines the possible link between the existence of a pay-as-you-go social security program and individual procreative behavior. When a public old-age income support system takes the place of within-family support, the theoretical literature preducts that fertility rates will decline since children are no longer perceived as important to the old age security of the parents. The author takes up this theoretical problem and examines it through three different but related issues: optimal capital accumulation, optimal population growth and the role of social institutions affecting efficient intergenerational allocations. Econometric analysis employing a steady state growth model is used. Altruism between generations is studied for effect on the standard model. The model shows that for social optimum the per capita pension is related to the growth rate of the population, therefore, for society as a whole, children are investment goods. However, given the existence of a social security system, it is in each household's best interest to have no children at all. Only a government transfer, a child allowance to parents, changes the model and fertility rates. When modified to account for "caring" the model demonstrates that altruistic behavior between generations is not symmetrical. The study concludes that a pay-as-you-go funded social security system should be supplemented by a system of child allowances or replaced by a fully funded social security system.

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

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

Pan, Y.

1993-01-01

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

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

NASA Astrophysics Data System (ADS)

Roy Chowdhury, P. K.; Maithani, Sandeep

2014-12-01

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

Growth of adult spinal cord in knifefish: Development and parametrization of a distributed model.

PubMed

Ilieş, Iulian; Sipahi, Rifat; Zupanc, Günther K H

2018-01-21

The study of indeterminate-growing organisms such as teleost fish presents a unique opportunity for improving our understanding of central nervous tissue growth during adulthood. Integrating the existing experimental data associated with this process into a theoretical framework through mathematical or computational modeling provides further research avenues through sensitivity analysis and optimization. While this type of approach has been used extensively in investigations of tumor growth, wound healing, and bone regeneration, the development of nervous tissue has been rarely studied within a modeling framework. To address this gap, the present work introduces a distributed model of spinal cord growth in the knifefish Apteronotus leptorhynchus, an established teleostean model of adult growth in the central nervous system. The proposed model incorporates two mechanisms, cell proliferation by active stem/progenitor cells and cell drift due to population pressure, both of which are subject to global constraints. A coupled reaction-diffusion equation approach was adopted to represent the densities of actively-proliferating and non-proliferating cells along the longitudinal axis of the spinal cord. Computer simulations using this model yielded biologically-feasible growth trajectories. Subsequent comparisons with whole-organism growth curves allowed the estimation of previously-unknown parameters, such as relative growth rates. Copyright © 2017 Elsevier Ltd. All rights reserved.

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

Treesearch

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

2013-01-01

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

Model of the Dynamic Construction Process of Texts and Scaling Laws of Words Organization in Language Systems

PubMed Central

Li, Shan; Lin, Ruokuang; Bian, Chunhua; Ma, Qianli D. Y.

2016-01-01

Scaling laws characterize diverse complex systems in a broad range of fields, including physics, biology, finance, and social science. The human language is another example of a complex system of words organization. Studies on written texts have shown that scaling laws characterize the occurrence frequency of words, words rank, and the growth of distinct words with increasing text length. However, these studies have mainly concentrated on the western linguistic systems, and the laws that govern the lexical organization, structure and dynamics of the Chinese language remain not well understood. Here we study a database of Chinese and English language books. We report that three distinct scaling laws characterize words organization in the Chinese language. We find that these scaling laws have different exponents and crossover behaviors compared to English texts, indicating different words organization and dynamics of words in the process of text growth. We propose a stochastic feedback model of words organization and text growth, which successfully accounts for the empirically observed scaling laws with their corresponding scaling exponents and characteristic crossover regimes. Further, by varying key model parameters, we reproduce differences in the organization and scaling laws of words between the Chinese and English language. We also identify functional relationships between model parameters and the empirically observed scaling exponents, thus providing new insights into the words organization and growth dynamics in the Chinese and English language. PMID:28006026

Model of the Dynamic Construction Process of Texts and Scaling Laws of Words Organization in Language Systems.

PubMed

Li, Shan; Lin, Ruokuang; Bian, Chunhua; Ma, Qianli D Y; Ivanov, Plamen Ch

2016-01-01

Scaling laws characterize diverse complex systems in a broad range of fields, including physics, biology, finance, and social science. The human language is another example of a complex system of words organization. Studies on written texts have shown that scaling laws characterize the occurrence frequency of words, words rank, and the growth of distinct words with increasing text length. However, these studies have mainly concentrated on the western linguistic systems, and the laws that govern the lexical organization, structure and dynamics of the Chinese language remain not well understood. Here we study a database of Chinese and English language books. We report that three distinct scaling laws characterize words organization in the Chinese language. We find that these scaling laws have different exponents and crossover behaviors compared to English texts, indicating different words organization and dynamics of words in the process of text growth. We propose a stochastic feedback model of words organization and text growth, which successfully accounts for the empirically observed scaling laws with their corresponding scaling exponents and characteristic crossover regimes. Further, by varying key model parameters, we reproduce differences in the organization and scaling laws of words between the Chinese and English language. We also identify functional relationships between model parameters and the empirically observed scaling exponents, thus providing new insights into the words organization and growth dynamics in the Chinese and English language.

Coupling sensing to crop models for closed-loop plant production in advanced life support systems

NASA Astrophysics Data System (ADS)

Cavazzoni, James; Ling, Peter P.

1999-01-01

We present a conceptual framework for coupling sensing to crop models for closed-loop analysis of plant production for NASA's program in advanced life support. Crop status may be monitored through non-destructive observations, while models may be independently applied to crop production planning and decision support. To achieve coupling, environmental variables and observations are linked to mode inputs and outputs, and monitoring results compared with model predictions of plant growth and development. The information thus provided may be useful in diagnosing problems with the plant growth system, or as a feedback to the model for evaluation of plant scheduling and potential yield. In this paper, we demonstrate this coupling using machine vision sensing of canopy height and top projected canopy area, and the CROPGRO crop growth model. Model simulations and scenarios are used for illustration. We also compare model predictions of the machine vision variables with data from soybean experiments conducted at New Jersey Agriculture Experiment Station Horticulture Greenhouse Facility, Rutgers University. Model simulations produce reasonable agreement with the available data, supporting our illustration.

Modeling pure culture heterotrophic production of polyhydroxybutyrate (PHB).

PubMed

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

2014-03-01

In this contribution a mechanistic model describing the production of polyhydroxybutyrate (PHB) through pure-culture fermentation was developed, calibrated and validated for two different substrates, namely glucose and waste glycerol. In both cases, non-growth-associated PHB production was triggered by applying nitrogen limitation. The occurrence of some growth-associated PHB production besides non-growth-associated PHB production was demonstrated, although it is inhibited in the presence of nitrogen. Other phenomena observed experimentally and described by the model included biomass growth on PHB and non-linear product inhibition of PHB production. The accumulated impurities from the waste substrate negatively affected the obtained maximum PHB content. Overall, the developed mathematical model provided an accurate prediction of the dynamic behavior of heterotrophic biomass growth and PHB production in a two-phase pure culture system. Copyright © 2013 Elsevier Ltd. All rights reserved.

Numerical Estimation of the Curvature of Biological Surfaces

NASA Technical Reports Server (NTRS)

Todd, P. H.

1985-01-01

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

Modelling Nitrogen Cycling in a Mariculture Ecosystem as a Tool to Evaluate its Outflow

NASA Astrophysics Data System (ADS)

Lefebvre, S.; Bacher, C.; Meuret, A.; Hussenot, J.

2001-03-01

A model was constructed to describe an intensive mariculture ecosystem growing sea bass ( Dicentrarchus labrax), located in the salt marshes of the Fiers d'Ars Bay on the French Atlantic coast, in order to assess nitrogen cycling within the system and nitrogen outflow from the system. The land-based system was separated into three main compartments: a seawater reservoir, fish ponds and a lagoon (sedimentation pond). Three submodels were built for simulation purposes: (1) a hydrological submodel which simulated water exchange; (2) a fish growth and excretion bioenergetic submodel; and (3) a nitrogen compound transformation and loss submodel (i.e. ammonification, nitrification and assimilation processes). A two-year sampling period of nitrogen water quality concentrations and fish growth was used to validate the model. The model fitted the observations of dissolved nitrogen components, fish growth and water fluxes on a daily basis in all the compartments. The dissolved inorganic nitrogen ranged widely and over time from 0·5 to 9 g N m -3within the system, depending on seawater supply and water temperature, without affecting fish growth. Fish feed was the most important input of nitrogen into the system. The mean average input of nitrogen in the feed was 205 kg N day -1, of which 19% was retained by fish, 4% accumulated in the sediment and 61% flowed from the system as dissolved components. The farm represented about 25% of the total dissolved nitrogen export from the bay, although the farm surface area was 100 times smaller than that of the bay.

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

PubMed

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

2014-08-01

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

CDK5-A Novel Role in Prostate Cancer Immunotherapy

DTIC Science & Technology

2017-10-01

of the involvement of a T cell antitumor response in impaired growth of prostate cancer in immunocompetent murine models of prostate cancer, and...of immune system activation by Cdk5 deletion in prostate cancer. We will confirm the involvement of a T cell antitumor response in impaired growth of...project? Major Task 1: Involvement of T cell anticancer immune response in impaired growth of TRAMP Cdk5-/- model. Months 1-10. Completed, month 10

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

PubMed

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

2016-03-29

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

Impact of membrane-induced particle immobilization on seeded growth monitored by in situ liquid scanning transmission electron microscopy

DOE PAGES

Weiner, Rebecca G.; Chen, Dennis P.; Unocic, Raymond R.; ...

2016-04-01

In situ liquid cell scanning transmission electron microscopy probes seeded growth in real time. The growth of Pd on Au nanocubes is monitored as a model system to compare growth within a liquid cell and traditional colloidal synthesis. Furthermore, different growth patterns are observed due to seed immobilization and the highly reducing environment within the liquid cell.

Determining the potential productivity of food crops in controlled environments

NASA Technical Reports Server (NTRS)

Bugbee, Bruce

1992-01-01

The quest to determine the maximum potential productivity of food crops is greatly benefitted by crop growth models. Many models have been developed to analyze and predict crop growth in the field, but it is difficult to predict biological responses to stress conditions. Crop growth models for the optimal environments of a Controlled Environment Life Support System (CELSS) can be highly predictive. This paper discusses the application of a crop growth model to CELSS; the model is used to evaluate factors limiting growth. The model separately evaluates the following four physiological processes: absorption of PPF by photosynthetic tissue, carbon fixation (photosynthesis), carbon use (respiration), and carbon partitioning (harvest index). These constituent processes determine potentially achievable productivity. An analysis of each process suggests that low harvest index is the factor most limiting to yield. PPF absorption by plant canopies and respiration efficiency are also of major importance. Research concerning productivity in a CELSS should emphasize: (1) the development of gas exchange techniques to continuously monitor plant growth rates and (2) environmental techniques to reduce plant height in communities.

Stochastic phase segregation on surfaces

PubMed Central

Gera, Prerna

2017-01-01

Phase separation and coarsening is a phenomenon commonly seen in binary physical and chemical systems that occur in nature. Often, thermal fluctuations, modelled as stochastic noise, are present in the system and the phase segregation process occurs on a surface. In this work, the segregation process is modelled via the Cahn–Hilliard–Cook model, which is a fourth-order parabolic stochastic system. Coarsening is analysed on two sample surfaces: a unit sphere and a dumbbell. On both surfaces, a statistical analysis of the growth rate is performed, and the influence of noise level and mobility is also investigated. For the spherical interface, it is also shown that a lognormal distribution fits the growth rate well. PMID:28878994

A system dynamics feedback control model study of population of "India 2001" and policies for stabilizing growth.

PubMed

Patil, M K; Janahanlal, P S

1978-06-01

A mathematical population model is presented and diagrammed. The model is a nonlinear, higher order, self-regulating, goal-seeking system. In other words, the model treats the population system like a biological system which has positive and negative feedbacks. The model incorporates the effects of important economic factors that influence human birth and death rates. It calculates the total population size, which is a determinant of resource usage. It also indicates the demographic response, through a changing birth and death rate, to a changing resource supply. The model is illustrated with Indian population data, disaggregated by age into 15 levels each of which is, in turn, divided into 4 income levels. The effect on population growth of various alternative population policies is analyzed with the goal of stabilizing the population growth quickly without causing undue hardship. Different computer runs of the model are conducted, using different levels of family planning practice, different ages at marriage, and different distributions of income throughout the country. The policy which would result in the lowest population for the year 2001 is 1 in which family planning acceptance levels would increase from 15% in 1975 to 60% in 1980 and 100% from 1990 on. However, there is widespread opposition to this policy. It is felt that a much slower rise in family planning acceptance would be a more acceptable policy for stabilizing population in India.

A Growth and Yield Model for Thinned Stands of Yellow-Poplar

Treesearch

Bruce R. Knoebel; Harold E. Burkhart; Donald E. Beck

1986-01-01

Simultaneous growth and yield equations were developed for predicting basal area growth and cubic-foot volume growth and yield in thinned stands of yellow-poplar. A joint loss function involving both volume and basal area was used to estimate the coefficients in the system of equations. The estimates obtained were analytically compatible, invariant for projection...

Incorporating temporal heterogeneity in environmental conditions into a somatic growth model

USGS Publications Warehouse

Dzul, Maria C.; Yackulic, Charles B.; Korman, Josh; Yard, Michael D.; Muehlbauer, Jeffrey D.

2017-01-01

Evaluating environmental effects on fish growth can be challenging because environmental conditions may vary at relatively fine temporal scales compared to sampling occasions. Here we develop a Bayesian state-space growth model to evaluate effects of monthly environmental data on growth of fish that are observed less frequently (e.g., from mark-recapture data where time between captures can range from months to years). We assess effects of temperature, turbidity duration, food availability, flow variability, and trout abundance on subadult humpback chub (Gila cypha) growth in two rivers, the Colorado River (CR) and the Little Colorado River (LCR), and we use out-of-sample prediction to rank competing models. Environmental covariates explained a high proportion of the variation in growth in both rivers; however, the best growth models were river-specific and included either positive temperature and turbidity duration effects (CR) or positive temperature and food availability effects (LCR). Our approach to analyzing environmental controls on growth should be applicable in other systems where environmental data vary over relatively short time scales compared to animal observations.

Frost Growth CFD Model of an Integrated Active Desiccant Rooftop Unit

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

Geoghegan, Patrick J; Petrov, Andrei Y; Vineyard, Edward Allan

2008-01-01

A frost growth model is incorporated into a Computational Fluid Dynamics (CFD) simulation of a heat pump by means of a user-defined function in FLUENT, a commercial CFD code. The transient model is applied to the outdoor section of an Integrated Active Desiccant Rooftop (IADR) unit in heating mode. IADR is a hybrid vapor compression and active desiccant unit capable of handling 100% outdoor air (dedicated outdoor air system) or as a total conditioning system, handling both outdoor air and space cooling or heating loads. The predicted increase in flow resistance and loss in heat transfer capacity due to frostmore » build-up are compared to experimental pressure drop readings and thermal imaging. The purpose of this work is to develop a CFD model that is capable of predicting frost growth, an invaluable tool in evaluating the effectiveness of defrost-on-demand cycles.« less

Impurity effects in crystal growth from solutions: Steady states, transients and step bunch motion

NASA Astrophysics Data System (ADS)

Ranganathan, Madhav; Weeks, John D.

2014-05-01

We analyze a recently formulated model in which adsorbed impurities impede the motion of steps in crystals grown from solutions, while moving steps can remove or deactivate adjacent impurities. In this model, the chemical potential change of an atom on incorporation/desorption to/from a step is calculated for different step configurations and used in the dynamical simulation of step motion. The crucial difference between solution growth and vapor growth is related to the dependence of the driving force for growth of the main component on the size of the terrace in front of the step. This model has features resembling experiments in solution growth, which yields a dead zone with essentially no growth at low supersaturation and the motion of large coherent step bunches at larger supersaturation. The transient behavior shows a regime wherein steps bunch together and move coherently as the bunch size increases. The behavior at large line tension is reminiscent of the kink-poisoning mechanism of impurities observed in calcite growth. Our model unifies different impurity models and gives a picture of nonequilibrium dynamics that includes both steady states and time dependent behavior and shows similarities with models of disordered systems and the pinning/depinning transition.

Crystal Growth of ZnSe by Physical Vapor Transport: A Modeling Study

NASA Technical Reports Server (NTRS)

Ramachandran, Narayanan; Su, Ching-Hua

1998-01-01

Crystal growth from the vapor phase has various advantages over melt growth. The main advantage is from a lower processing temperature which makes the process more amenable in instances where the melting temperature of the crystal is high. Other benefits stem from the inherent purification mechanism in the process due to differences in the vapor pressures of the native elements and impurities, and the enhanced interfacial morphological stability during the growth process. Further, the implementation of Physical Vapor Transport (PVT) growth in closed ampoules affords experimental simplicity with minimal needs for complex process control which makes it an ideal candidate for space investigations in systems where gravity tends to have undesirable effects on the growth process. Bulk growth of wide band gap II-VI semiconductors by physical vapor transport has been developed and refined over the past several years at NASA MSFC. Results from a modeling study of PVT crystal growth of ZnSe arc reported in this paper. The PVI process is numerically investigated using both two-dimensional and fully three-dimensional formulation of the governing equations and associated boundary conditions. Both the incompressible Boussinesq approximation and the compressible model are tested to determine the influence of gravity on the process and to discern the differences between the two approaches. The influence of a residual gas is included in the models. The preliminary results show that both the incompressible and compressible approximations provide comparable results and the presence of a residual gas tends to measurably reduce the mass flux in the system. Detailed flow, thermal and concentration profiles will be provided in the final manuscript along with computed heat and mass transfer rates. Comparisons with the 1-D model will also be provided.

Delivery of growth factors for tissue regeneration and wound healing.

PubMed

Koria, Piyush

2012-06-01

Growth factors are soluble secreted proteins capable of affecting a variety of cellular processes important for tissue regeneration. Consequently, the self-healing capacity of patients can be augmented by artificially enhancing one or more processes important for healing through the application of growth factors. However, their application in clinics remains limited due to lack of robust delivery systems and biomaterial carriers. Interestingly, all clinically approved therapies involving growth factors utilize some sort of a biomaterial carrier for growth factor delivery. This suggests that biomaterial delivery systems are extremely important for successful usage of growth factors in regenerative medicine. This review outlines the role of growth factors in tissue regeneration, and their application in both pre-clinical animal models of regeneration and clinical trials is discussed. Additionally, current status of biomaterial substrates and sophisticated delivery systems such as nanoparticles for delivery of exogenous growth factors and peptides in humans are reviewed. Finally, issues and possible future research directions for growth factor therapy in regenerative medicine are discussed.

Using Markov Models of Fault Growth Physics and Environmental Stresses to Optimize Control Actions

NASA Technical Reports Server (NTRS)

Bole, Brian; Goebel, Kai; Vachtsevanos, George

2012-01-01

A generalized Markov chain representation of fault dynamics is presented for the case that available modeling of fault growth physics and future environmental stresses can be represented by two independent stochastic process models. A contrived but representatively challenging example will be presented and analyzed, in which uncertainty in the modeling of fault growth physics is represented by a uniformly distributed dice throwing process, and a discrete random walk is used to represent uncertain modeling of future exogenous loading demands to be placed on the system. A finite horizon dynamic programming algorithm is used to solve for an optimal control policy over a finite time window for the case that stochastic models representing physics of failure and future environmental stresses are known, and the states of both stochastic processes are observable by implemented control routines. The fundamental limitations of optimization performed in the presence of uncertain modeling information are examined by comparing the outcomes obtained from simulations of an optimizing control policy with the outcomes that would be achievable if all modeling uncertainties were removed from the system.

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

NASA Astrophysics Data System (ADS)

Gharagozloo, P. E.

2014-12-01

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

A General Multivariate Latent Growth Model with Applications to Student Achievement

ERIC Educational Resources Information Center

Bianconcini, Silvia; Cagnone, Silvia

2012-01-01

The evaluation of the formative process in the University system has been assuming an ever increasing importance in the European countries. Within this context, the analysis of student performance and capabilities plays a fundamental role. In this work, the authors propose a multivariate latent growth model for studying the performances of a…

A Dynamic Model of Sustainment Investment

DTIC Science & Technology

2015-02-01

Sustainment System Dynamics Model 11 Figure 7: Core Structure of Sustainment Work 12 Figure 8: Bandwagon Effect Loop 13 Figure 9: Limits to Growth Loop 14...Dynamics Model sustainment capacity sustainment performance gap Bandwagon Effect R1 Limits to Growth B1 S Work Smarter B3 Work Bigger B2 desired...which is of concern primarily when using the model as a vehicle for research. Figure 8 depicts a reinforcing loop called the “ Bandwagon Effect

Confirming Time-reversal Symmetry of a Directed Percolation Phase Transition in a Model of Neutral Evolutionary Dynamics

NASA Astrophysics Data System (ADS)

Ordway, Stephen; King, Dawn; Bahar, Sonya

Reaction-diffusion processes, such as branching-coalescing random walks, can be used to describe the underlying dynamics of nonequilibrium phase transitions. In an agent-based, neutral model of evolutionary dynamics, we have previously shown that our system undergoes a continuous, nonequilibrium phase transition, from extinction to survival, as various system parameters were tuned. This model was shown to belong to the directed percolation (DP) universality class, by measuring the critical exponents corresponding to correlation length ξ⊥, correlation time ξ| |, and particle density β. The fourth critical exponent that defines the DP universality class is β', which measures the survival probability of growth from a single seed organism. Since DP universality is theorized to have time-reversal symmetry, it is assumed that β = β '. In order to confirm the existence of time-reversal symmetry in our model, we evaluate the system growth from a single asexually reproducing organism. Importantly, the critical exponent β' could be useful for comparison to experimental studies of phase transitions in biological systems, since observing growth of microbial populations is significantly easier than observing death. This research was supported by funding from the James S. McDonnell Foundation.

Monte Carlo Studies of Phase Separation in Compressible 2-dim Ising Models

NASA Astrophysics Data System (ADS)

Mitchell, S. J.; Landau, D. P.

2006-03-01

Using high resolution Monte Carlo simulations, we study time-dependent domain growth in compressible 2-dim ferromagnetic (s=1/2) Ising models with continuous spin positions and spin-exchange moves [1]. Spins interact with slightly modified Lennard-Jones potentials, and we consider a model with no lattice mismatch and one with 4% mismatch. For comparison, we repeat calculations for the rigid Ising model [2]. For all models, large systems (512^2) and long times (10^ 6 MCS) are examined over multiple runs, and the growth exponent is measured in the asymptotic scaling regime. For the rigid model and the compressible model with no lattice mismatch, the growth exponent is consistent with the theoretically expected value of 1/3 [1] for Model B type growth. However, we find that non-zero lattice mismatch has a significant and unexpected effect on the growth behavior.Supported by the NSF.[1] D.P. Landau and K. Binder, A Guide to Monte Carlo Simulations in Statistical Physics, second ed. (Cambridge University Press, New York, 2005).[2] J. Amar, F. Sullivan, and R.D. Mountain, Phys. Rev. B 37, 196 (1988).

A model of economic growth with physical and human capital: The role of time delays.

PubMed

Gori, Luca; Guerrini, Luca; Sodini, Mauro

2016-09-01

This article aims at analysing a two-sector economic growth model with discrete delays. The focus is on the dynamic properties of the emerging system. In particular, this study concentrates on the stability properties of the stationary solution, characterised by analytical results and geometrical techniques (stability crossing curves), and the conditions under which oscillatory dynamics emerge (through Hopf bifurcations). In addition, this article proposes some numerical simulations to illustrate the behaviour of the system when the stationary equilibrium is unstable.

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

PubMed

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

2013-01-01

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

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

PubMed Central

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

2013-01-01

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

Generation of a modeling and simulation system for a semi-closed plant growth chamber

NASA Technical Reports Server (NTRS)

Blackwell, A. L.; Maa, S.; Kliss, M.; Blackwell, C. C.

1993-01-01

The fluid and thermal dynamics of the environment of plants in a small controlled-environment system have been modeled. The results of the simulation under two scenarios have been compared to measurements taken during tests on the actual system. The motivation for the modeling effort and the status of the modeling exercise and system scenario studies are described. An evaluation of the model and a discussion of future studies are included.

Examples of Mathematical Modeling

PubMed Central

Johnston, Matthew D.; Edwards, Carina M.; Bodmer, Walter F.; Maini, Philip K.; Chapman, S. Jonathan

2008-01-01

Mathematical modeling is being increasingly recognized within the biomedical sciences as an important tool that can aid the understanding of biological systems. The heavily regulated cell renewal cycle in the colonic crypt provides a good example of how modeling can be used to find out key features of the system kinetics, and help to explain both the breakdown of homeostasis and the initiation of tumorigenesis. We use the cell population model by Johnston et al.5 to illustrate the power of mathematical modeling by considering two key questions about the cell population dynamics in the colonic crypt. We ask: how can a model describe both homeostasis and unregulated growth in tumorigenesis; and to which parameters in the system is the model most sensitive? In order to address these questions, we discuss what type of modeling approach is most appropriate in the crypt. We use the model to argue why tumorigenesis is observed to occur in stages with long lag phases between periods of rapid growth, and we identify the key parameters. PMID:17873520

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

NASA Astrophysics Data System (ADS)

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

2016-07-01

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

Modeling duckweed growth in wastewater treatment systems

USGS Publications Warehouse

Landesman, L.; Parker, N.C.; Fedler, C.B.; Konikoff, M.

2005-01-01

Species of the genera Lemnaceae, or duckweeds, are floating aquatic plants that show great promise for both wastewater treatment and livestock feed production. Research conducted in the Southern High Plains of Texas has shown that Lemna obscura grew well in cattle feedlot runoff water and produced leaf tissue with a high protein content. A model or mathematical expression derived from duckweed growth data was used to fit data from experiments conducted in a greenhouse in Lubbock, Texas. The relationship between duckweed growth and the total nitrogen concentration in the mediium follows the Mitscherlich Function and is similar to that of other plants. Empirically derived model equations have successfully predicted the growth response of Lemna obscura.

An agent architecture for an integrated forest ecosystem management decision support system

Treesearch

Donald Nute; Walter D. Potter; Mayukh Dass; Astrid Glende; Frederick Maier; Hajime Uchiyama; Jin Wang; Mark Twery; Peter Knopp; Scott Thomasma; H. Michael Rauscher

2003-01-01

A wide variety of software tools are available to support decision in the management of forest ecosystems. These tools include databases, growth and yield models, wildlife models, silvicultural expert systems, financial models, geographical informations systems, and visualization tools. Typically, each of these tools has its own complex interface and data format. To...

Urban Growth Modeling Using AN Artificial Neural Network a Case Study of Sanandaj City, Iran

NASA Astrophysics Data System (ADS)

Mohammady, S.; Delavar, M. R.; Pahlavani, P.

2014-10-01

Land use activity is a major issue and challenge for town and country planners. Modelling and managing urban growth is a complex problem. Cities are now recognized as complex, non-linear and dynamic process systems. The design of a system that can handle these complexities is a challenging prospect. Local governments that implement urban growth models need to estimate the amount of urban land required in the future given anticipated growth of housing, business, recreation and other urban uses within the boundary. There are so many negative implications related with the type of inappropriate urban development such as increased traffic and demand for mobility, reduced landscape attractively, land use fragmentation, loss of biodiversity and alterations of the hydrological cycle. The aim of this study is to use the Artificial Neural Network (ANN) to make a powerful tool for simulating urban growth patterns. Our study area is Sanandaj city located in the west of Iran. Landsat imageries acquired at 2000 and 2006 are used. Dataset were used include distance to principle roads, distance to residential areas, elevation, slope, distance to green spaces and distance to region centers. In this study an appropriate methodology for urban growth modelling using satellite remotely sensed data is presented and evaluated. Percent Correct Match (PCM) and Figure of Merit were used to evaluate ANN results.

Cancer growth and metastasis as a metaphor of Go gaming: An Ising model approach.

PubMed

Barradas-Bautista, Didier; Alvarado-Mentado, Matias; Agostino, Mark; Cocho, Germinal

2018-01-01

This work aims for modeling and simulating the metastasis of cancer, via the analogy between the cancer process and the board game Go. In the game of Go, black stones that play first could correspond to a metaphor of the birth, growth, and metastasis of cancer. Moreover, playing white stones on the second turn could correspond the inhibition of cancer invasion. Mathematical modeling and algorithmic simulation of Go may therefore benefit the efforts to deploy therapies to surpass cancer illness by providing insight into the cellular growth and expansion over a tissue area. We use the Ising Hamiltonian, that models the energy exchange in interacting particles, for modeling the cancer dynamics. Parameters in the energy function refer the biochemical elements that induce cancer birth, growth, and metastasis; as well as the biochemical immune system process of defense.

Strategies for the coupling of global and local crystal growth models

NASA Astrophysics Data System (ADS)

Derby, Jeffrey J.; Lun, Lisa; Yeckel, Andrew

2007-05-01

The modular coupling of existing numerical codes to model crystal growth processes will provide for maximum effectiveness, capability, and flexibility. However, significant challenges are posed to make these coupled models mathematically self-consistent and algorithmically robust. This paper presents sample results from a coupling of the CrysVUn code, used here to compute furnace-scale heat transfer, and Cats2D, used to calculate melt fluid dynamics and phase-change phenomena, to form a global model for a Bridgman crystal growth system. However, the strategy used to implement the CrysVUn-Cats2D coupling is unreliable and inefficient. The implementation of under-relaxation within a block Gauss-Seidel iteration is shown to be ineffective for improving the coupling performance in a model one-dimensional problem representative of a melt crystal growth model. Ideas to overcome current convergence limitations using approximations to a full Newton iteration method are discussed.

Intelligent Model Management in a Forest Ecosystem Management Decision Support System

Treesearch

Donald Nute; Walter D. Potter; Frederick Maier; Jin Wang; Mark Twery; H. Michael Rauscher; Peter Knopp; Scott Thomasma; Mayukh Dass; Hajime Uchiyama

2002-01-01

Decision making for forest ecosystem management can include the use of a wide variety of modeling tools. These tools include vegetation growth models, wildlife models, silvicultural models, GIS, and visualization tools. NED-2 is a robust, intelligent, goal-driven decision support system that integrates tools in each of these categories. NED-2 uses a blackboard...

Optimization of cell seeding in a 2D bio-scaffold system using computational models.

PubMed

Ho, Nicholas; Chua, Matthew; Chui, Chee-Kong

2017-05-01

The cell expansion process is a crucial part of generating cells on a large-scale level in a bioreactor system. Hence, it is important to set operating conditions (e.g. initial cell seeding distribution, culture medium flow rate) to an optimal level. Often, the initial cell seeding distribution factor is neglected and/or overlooked in the design of a bioreactor using conventional seeding distribution methods. This paper proposes a novel seeding distribution method that aims to maximize cell growth and minimize production time/cost. The proposed method utilizes two computational models; the first model represents cell growth patterns whereas the second model determines optimal initial cell seeding positions for adherent cell expansions. Cell growth simulation from the first model demonstrates that the model can be a representation of various cell types with known probabilities. The second model involves a combination of combinatorial optimization, Monte Carlo and concepts of the first model, and is used to design a multi-layer 2D bio-scaffold system that increases cell production efficiency in bioreactor applications. Simulation results have shown that the recommended input configurations obtained from the proposed optimization method are the most optimal configurations. The results have also illustrated the effectiveness of the proposed optimization method. The potential of the proposed seeding distribution method as a useful tool to optimize the cell expansion process in modern bioreactor system applications is highlighted. Copyright © 2017 Elsevier Ltd. All rights reserved.

Econometric Models of Education, Some Applications. Education and Development, Technical Reports.

ERIC Educational Resources Information Center

Tinbergen, Jan; And Others

This report contains five papers which describe mathematical models of the educational system as it relates to economic growth. Experimental applications of the models to particular educational systems are discussed. Three papers, by L. J. Emmerij, J. Blum, and G. Williams, discuss planning models for the calculation of educational requirements…

Assimilating Leaf Area Index Estimates from Remote Sensing into the Simulations of a Cropping Systems Model

USDA-ARS?s Scientific Manuscript database

Spatial extrapolation of cropping systems models for regional crop growth and water use assessment and farm-level precision management has been limited by the vast model input requirements and the model sensitivity to parameter uncertainty. Remote sensing has been proposed as a viable source of spat...

Understanding the oriented-attachment growth of nanocrystals from an energy point of view: a review

NASA Astrophysics Data System (ADS)

Lv, Weiqiang; He, Weidong; Wang, Xiaoning; Niu, Yinghua; Cao, Huanqi; Dickerson, James H.; Wang, Zhiguo

2014-02-01

Since Penn et al. first discovered the oriented attachment growth of crystals, the oriented attachment mechanism has now become a major research focus in the crystal field, and extensive efforts have been carried out over the past decade to systematically investigate the growth mechanism and the statistical kinetic models. However, most of the work mainly focuses on the experimental results on the oriented attachment growth. In contrast to the previous reviews, our review provides an overview of the recent theoretical advances in oriented attachment kinetics combined with experimental evidences. After a brief introduction to the van der Waals interaction and Coulombic interaction in a colloidal system, the correlation between the kinetic models of oriented attachment growth and the interactions is then our focus. The impact of in situ experimental observation techniques on the study of oriented attachment growth is examined with insightful examples. In addition, the advances in theoretical simulations mainly investigating the thermodynamic origin of these interactions at the atomic level are reviewed. This review seeks to understand the oriented attachment crystal growth from a kinetic point of view and provide a quantitative methodology to rationally design an oriented attachment system with pre-evaluated crystal growth parameters.

Phase diagrams for understanding gold-seeded growth of GaAs and InAs nanowires

NASA Astrophysics Data System (ADS)

Ghasemi, Masoomeh; Johansson, Jonas

2017-04-01

Phase diagrams are useful tools to study the phase equilibria of nanowire materials systems because the growth of nanowires is accompanied by phase formation and phase transition. We have modeled the phase equilibria of the As-Au-Ga ternary system by means of the CALPHAD method. This method is a well-established semi-empirical technique for thermodynamic modeling in which Gibbs energy functions with free parameters are defined for all phases in a system followed by adjusting these parameters to the experimental data. Using the resulting As-Au-Ga thermodynamic database, four vertical cuts of this ternary system are calculated and all show good agreement with experiments. This ternary system is particularly useful for predicting the state of the Au seed alloys when growing GaAs nanowires and we discuss such predictions. Similar calculations are performed for Au-seeded InAs nanowires. We show that the vapor-liquid-solid (VLS) growth fails for InAs nanowires, while GaAs nanowires can grow from a liquid particle. Our calculations are in agreement with experimental data on the growth of Au-seeded GaAs and InAs nanowires.

Nonequilibrium Thermodynamics of Hydrate Growth on a Gas-Liquid Interface

NASA Astrophysics Data System (ADS)

Fu, Xiaojing; Cueto-Felgueroso, Luis; Juanes, Ruben

2018-04-01

We develop a continuum-scale phase-field model to study gas-liquid-hydrate systems far from thermodynamic equilibrium. We design a Gibbs free energy functional for methane-water mixtures that recovers the isobaric temperature-composition phase diagram under thermodynamic equilibrium conditions. The proposed free energy is incorporated into a phase-field model to study the dynamics of hydrate formation on a gas-liquid interface. We elucidate the role of initial aqueous concentration in determining the direction of hydrate growth at the interface, in agreement with experimental observations. Our model also reveals two stages of hydrate growth at an interface—controlled by a crossover in how methane is supplied from the gas and liquid phases—which could explain the persistence of gas conduits in hydrate-bearing sediments and other nonequilibrium phenomena commonly observed in natural methane hydrate systems.

Nonequilibrium Thermodynamics of Hydrate Growth on a Gas-Liquid Interface.

PubMed

Fu, Xiaojing; Cueto-Felgueroso, Luis; Juanes, Ruben

2018-04-06

We develop a continuum-scale phase-field model to study gas-liquid-hydrate systems far from thermodynamic equilibrium. We design a Gibbs free energy functional for methane-water mixtures that recovers the isobaric temperature-composition phase diagram under thermodynamic equilibrium conditions. The proposed free energy is incorporated into a phase-field model to study the dynamics of hydrate formation on a gas-liquid interface. We elucidate the role of initial aqueous concentration in determining the direction of hydrate growth at the interface, in agreement with experimental observations. Our model also reveals two stages of hydrate growth at an interface-controlled by a crossover in how methane is supplied from the gas and liquid phases-which could explain the persistence of gas conduits in hydrate-bearing sediments and other nonequilibrium phenomena commonly observed in natural methane hydrate systems.

Regenerative life support system research

NASA Technical Reports Server (NTRS)

1988-01-01

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

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.

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

NASA Astrophysics Data System (ADS)

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

2014-12-01

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

A New Strategy in Observer Modeling for Greenhouse Cucumber Seedling Growth

PubMed Central

Qiu, Quan; Zheng, Chenfei; Wang, Wenping; Qiao, Xiaojun; Bai, He; Yu, Jingquan; Shi, Kai

2017-01-01

State observer is an essential component in computerized control loops for greenhouse-crop systems. However, the current accomplishments of observer modeling for greenhouse-crop systems mainly focus on mass/energy balance, ignoring physiological responses of crops. As a result, state observers for crop physiological responses are rarely developed, and control operations are typically made based on experience rather than actual crop requirements. In addition, existing observer models require a large number of parameters, leading to heavy computational load and poor application feasibility. To address these problems, we present a new state observer modeling strategy that takes both environmental information and crop physiological responses into consideration during the observer modeling process. Using greenhouse cucumber seedlings as an instance, we sample 10 physiological parameters of cucumber seedlings at different time point during the exponential growth stage, and employ them to build growth state observers together with 8 environmental parameters. Support vector machine (SVM) acts as the mathematical tool for observer modeling. Canonical correlation analysis (CCA) is used to select the dominant environmental and physiological parameters in the modeling process. With the dominant parameters, simplified observer models are built and tested. We conduct contrast experiments with different input parameter combinations on simplified and un-simplified observers. Experimental results indicate that physiological information can improve the prediction accuracies of the growth state observers. Furthermore, the simplified observer models can give equivalent or even better performance than the un-simplified ones, which verifies the feasibility of CCA. The current study can enable state observers to reflect crop requirements and make them feasible for applications with simplified shapes, which is significant for developing intelligent greenhouse control systems for modern greenhouse production. PMID:28848565

A New Strategy in Observer Modeling for Greenhouse Cucumber Seedling Growth.

PubMed

Qiu, Quan; Zheng, Chenfei; Wang, Wenping; Qiao, Xiaojun; Bai, He; Yu, Jingquan; Shi, Kai

2017-01-01

State observer is an essential component in computerized control loops for greenhouse-crop systems. However, the current accomplishments of observer modeling for greenhouse-crop systems mainly focus on mass/energy balance, ignoring physiological responses of crops. As a result, state observers for crop physiological responses are rarely developed, and control operations are typically made based on experience rather than actual crop requirements. In addition, existing observer models require a large number of parameters, leading to heavy computational load and poor application feasibility. To address these problems, we present a new state observer modeling strategy that takes both environmental information and crop physiological responses into consideration during the observer modeling process. Using greenhouse cucumber seedlings as an instance, we sample 10 physiological parameters of cucumber seedlings at different time point during the exponential growth stage, and employ them to build growth state observers together with 8 environmental parameters. Support vector machine (SVM) acts as the mathematical tool for observer modeling. Canonical correlation analysis (CCA) is used to select the dominant environmental and physiological parameters in the modeling process. With the dominant parameters, simplified observer models are built and tested. We conduct contrast experiments with different input parameter combinations on simplified and un-simplified observers. Experimental results indicate that physiological information can improve the prediction accuracies of the growth state observers. Furthermore, the simplified observer models can give equivalent or even better performance than the un-simplified ones, which verifies the feasibility of CCA. The current study can enable state observers to reflect crop requirements and make them feasible for applications with simplified shapes, which is significant for developing intelligent greenhouse control systems for modern greenhouse production.

Characterizing the physics of plant root gravitropism: A systems modeling approach

NASA Astrophysics Data System (ADS)

Yoder, Thomas Lynn

Root gravitropism is divided into three mechanisms; the gravity sensor, transduction, and differential growth. The gravitropic response has been imitated with various mathematical constructs, but a coherent model based on systems engineering concepts does not exist. The goal of this research is to create models of the gravitropic sensor and differential growth response that are consistent with actual physical characteristics of these mechanisms. The study initially establishes that the amyloplasts within the central columella cells of maize are feasible gravity sensors; statoliths. Video-microscopy studies of live root cap sections are used to quantify the dynamics of the statoliths. Extensive MATLAB analysis of amyloplast sedimentation indicates that an actin network interferes with the free sedimentation of the statoliths. This interference is most significant in the central region of the cell and less significant near the periphery. This obstruction of actin creates a channeling behavior in amyloplasts sedimenting through the cell's central region. The amyloplasts also appear to exhibit cross-correlated motions. Cytochalasin D mediates both the channeling and correlated behaviors, confirming that the obstructive influence is actin-based. The video analysis produced a refined value for maize cytoplasmic viscosity. Efforts to model the differential growth mechanism examined historical growth data from numerous researchers. RELEL (relative elemental elongation) growth data applied to a model set analogous to bi-metallic bending is used. Testing and analysis of the model highlights an extremely high sensitivity of curvature to all RELEL parameters. This sensitivity appears to be the reason for the significant differences between gravitropic responses within like species. Newly observed gravitropic responses, along with historical data, are used to explore the gravitropic time response specifications as opposed to averaging individual time-curvature data into single responses. This approach highlights the significant disadvantages of time-averaging, low sampling rates, and a lack of frequency components being incorporated into the response. A single feedback "black box" model is created so that, along with the sensor and differential growth models, some inferences could be made about the elusive transduction mechanism. Numerous pieces of circumstantial evidence are found that indicate that the gravitropic mechanism is not a single-pathway system.

Reliability Growth in Space Life Support Systems

NASA Technical Reports Server (NTRS)

Jones, Harry W.

2014-01-01

A hardware system's failure rate often increases over time due to wear and aging, but not always. Some systems instead show reliability growth, a decreasing failure rate with time, due to effective failure analysis and remedial hardware upgrades. Reliability grows when failure causes are removed by improved design. A mathematical reliability growth model allows the reliability growth rate to be computed from the failure data. The space shuttle was extensively maintained, refurbished, and upgraded after each flight and it experienced significant reliability growth during its operational life. In contrast, the International Space Station (ISS) is much more difficult to maintain and upgrade and its failure rate has been constant over time. The ISS Carbon Dioxide Removal Assembly (CDRA) reliability has slightly decreased. Failures on ISS and with the ISS CDRA continue to be a challenge.

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

DTIC Science & Technology

2007-01-01

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

Numerical Modeling of Crystal of ZnSe by Physical Vapor Transport - Towards a more Comprehensive Formulations

NASA Technical Reports Server (NTRS)

Ramachandran, N.

1999-01-01

Crystal growth from the vapor phase has various advantages over melt growth. The main advantage is from a lower processing temperature which makes the process more amenable in instances where the melting temperature of the crystal is high. Other benefits stem from the inherent purification mechanism in the process due to differences in the vapor pressures of the native elements and impurities, and the enhanced interfacial morphological stability during the growth process. Further, the implementation of PVT growth in closed ampoules affords experimental simplicity with minimal needs for complex process control which makes it an ideal candidate for space investigations in systems where gravity tends to have undesirable effects on the growth process. Bulk growth of wide band gap II-VI semiconductors by physical vapor transport has been developed and refined over the past several years at NASA MSFC. Results from a modeling study of PVT crystal growth of ZnSe are reported in this paper. The PVT process is numerically investigated using both two-dimensional and fully three-dimensional formulation of the governing equations and associated boundary conditions. Both the incompressible Boussinesq approximation and the compressible model are tested to determine the influence of gravity on the process and to discern the differences between the two approaches. The influence of a residual gas is included in the models. The results show that both the incompressible and compressible approximations provide comparable results and the presence of a residual gas tends to measurably reduce the mass flux in the system. Detailed flow, thermal and concentration profiles will be provided in the final manuscript along with computed heat and mass transfer rates. Comparisons with the 1-D model will also be provided. The effect of gravity on the process from numerical computations shows subtle effects although experimental evidence from vertically and horizontally grown samples show dramatic evidence of gravitational effects. The shortcomings of the problem formulation will be discussed and a framework will be provided leading up towards a more comprehensive model of PVT systems.

Process modelling for space station experiments

NASA Technical Reports Server (NTRS)

Rosenberger, Franz; Alexander, J. Iwan D.

1988-01-01

The work performed during the first year 1 Oct. 1987 to 30 Sept. 1988 involved analyses of crystal growth from the melt and from solution. The particular melt growth technique under investigation is directional solidification by the Bridgman-Stockbarger method. Two types of solution growth systems are also being studied. One involves growth from solution in a closed container, the other concerns growth of protein crystals by the hanging drop method. Following discussions with Dr. R. J. Naumann of the Low Gravity Science Division at MSFC it was decided to tackle the analysis of crystal growth from the melt earlier than originally proposed. Rapid progress was made in this area. Work is on schedule and full calculations were underway for some time. Progress was also made in the formulation of the two solution growth models.

Fitness model for the Italian interbank money market.

PubMed

De Masi, G; Iori, G; Caldarelli, G

2006-12-01

We use the theory of complex networks in order to quantitatively characterize the formation of communities in a particular financial market. The system is composed by different banks exchanging on a daily basis loans and debts of liquidity. Through topological analysis and by means of a model of network growth we can determine the formation of different group of banks characterized by different business strategy. The model based on Pareto's law makes no use of growth or preferential attachment and it reproduces correctly all the various statistical properties of the system. We believe that this network modeling of the market could be an efficient way to evaluate the impact of different policies in the market of liquidity.

Introducing uncertainty analysis of nucleation and crystal growth models in Process Analytical Technology (PAT) system design of crystallization processes.

PubMed

Samad, Noor Asma Fazli Abdul; Sin, Gürkan; Gernaey, Krist V; Gani, Rafiqul

2013-11-01

This paper presents the application of uncertainty and sensitivity analysis as part of a systematic model-based process monitoring and control (PAT) system design framework for crystallization processes. For the uncertainty analysis, the Monte Carlo procedure is used to propagate input uncertainty, while for sensitivity analysis, global methods including the standardized regression coefficients (SRC) and Morris screening are used to identify the most significant parameters. The potassium dihydrogen phosphate (KDP) crystallization process is used as a case study, both in open-loop and closed-loop operation. In the uncertainty analysis, the impact on the predicted output of uncertain parameters related to the nucleation and the crystal growth model has been investigated for both a one- and two-dimensional crystal size distribution (CSD). The open-loop results show that the input uncertainties lead to significant uncertainties on the CSD, with appearance of a secondary peak due to secondary nucleation for both cases. The sensitivity analysis indicated that the most important parameters affecting the CSDs are nucleation order and growth order constants. In the proposed PAT system design (closed-loop), the target CSD variability was successfully reduced compared to the open-loop case, also when considering uncertainty in nucleation and crystal growth model parameters. The latter forms a strong indication of the robustness of the proposed PAT system design in achieving the target CSD and encourages its transfer to full-scale implementation. Copyright © 2013 Elsevier B.V. All rights reserved.

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

NASA Astrophysics Data System (ADS)

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

2008-10-01

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

Bayesian methods in reliability

NASA Astrophysics Data System (ADS)

Sander, P.; Badoux, R.

1991-11-01

The present proceedings from a course on Bayesian methods in reliability encompasses Bayesian statistical methods and their computational implementation, models for analyzing censored data from nonrepairable systems, the traits of repairable systems and growth models, the use of expert judgment, and a review of the problem of forecasting software reliability. Specific issues addressed include the use of Bayesian methods to estimate the leak rate of a gas pipeline, approximate analyses under great prior uncertainty, reliability estimation techniques, and a nonhomogeneous Poisson process. Also addressed are the calibration sets and seed variables of expert judgment systems for risk assessment, experimental illustrations of the use of expert judgment for reliability testing, and analyses of the predictive quality of software-reliability growth models such as the Weibull order statistics.

Using FIA data in the Forest Vegetation Simulator

Treesearch

John D. Shaw

2009-01-01

The Forest Vegetation Simulator (FVS) is a national system of forest growth models maintained by the USDA Forest Service. It is the official tool for stand growth projection on National Forest lands, but it is also used widely on other ownerships. Model extensions and post-processors permit FVS users to perform a broad range of functions, including silvicultural...

A Role for M-Matrices in Modelling Population Growth

ERIC Educational Resources Information Center

James, Glyn; Rumchev, Ventsi

2006-01-01

Adopting a discrete-time cohort-type model to represent the dynamics of a population, the problem of achieving a desired total size of the population under a balanced growth (contraction) and the problem of maintaining the desired size, once achieved, are studied. Properties of positive-time systems and M-matrices are used to develop the results,…

Selecting Growth Measures for Use in School Evaluation Systems: Should Proportionality Matter?

ERIC Educational Resources Information Center

Ehlert, Mark; Koedel, Cory; Parsons, Eric; Podgursky, Michael

2016-01-01

The specifics of how growth models should be constructed and used for educational evaluation is a topic of lively policy debate in states and school districts nationwide. In this article, we take up the question of model choice--framed within a policy context--and examine three competing approaches. The first approach, reflected in the popular…

Simulation of Climate Change Impacts on Wheat-Fallow Cropping Systems

USDA-ARS?s Scientific Manuscript database

Agricultural system simulation models are predictive tools for assessing climate change impacts on crop production. In this study, RZWQM2 that contains the DSSAT 4.0-CERES model was evaluated for simulating climate change impacts on wheat growth. The model was calibrated and validated using data fro...

Model reduction in mathematical pharmacology : Integration, reduction and linking of PBPK and systems biology models.

PubMed

Snowden, Thomas J; van der Graaf, Piet H; Tindall, Marcus J

2018-03-26

In this paper we present a framework for the reduction and linking of physiologically based pharmacokinetic (PBPK) models with models of systems biology to describe the effects of drug administration across multiple scales. To address the issue of model complexity, we propose the reduction of each type of model separately prior to being linked. We highlight the use of balanced truncation in reducing the linear components of PBPK models, whilst proper lumping is shown to be efficient in reducing typically nonlinear systems biology type models. The overall methodology is demonstrated via two example systems; a model of bacterial chemotactic signalling in Escherichia coli and a model of extracellular regulatory kinase activation mediated via the extracellular growth factor and nerve growth factor receptor pathways. Each system is tested under the simulated administration of three hypothetical compounds; a strong base, a weak base, and an acid, mirroring the parameterisation of pindolol, midazolam, and thiopental, respectively. Our method can produce up to an 80% decrease in simulation time, allowing substantial speed-up for computationally intensive applications including parameter fitting or agent based modelling. The approach provides a straightforward means to construct simplified Quantitative Systems Pharmacology models that still provide significant insight into the mechanisms of drug action. Such a framework can potentially bridge pre-clinical and clinical modelling - providing an intermediate level of model granularity between classical, empirical approaches and mechanistic systems describing the molecular scale.

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

NASA Astrophysics Data System (ADS)

Zhang, Chengzhu

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

The crystallization kinetic model of nano-CaCO3 in CO2-ammonia-phosphogypsum three-phase reaction system

NASA Astrophysics Data System (ADS)

Liu, Hao; Lan, Peiqiang; Lu, Shangqing; Wu, Sufang

2018-06-01

Phosphogypsum (PG) as a low-cost calcium resource was used to prepare nano-CaCO3 in a three-phase system by reactions. Based on the population balance equation, nano-CaCO3 crystal nucleation and growth model in the gas (CO2)-liquid (NH3·H2O)-solid (CaSO4) three-phase system was established. The crystallization kinetic model of nano-CaCO3 in CO2-NH3·H2O-CaSO4 reactions system was experimental developed over an optimized temperature range of 20-40 °C and CO2 flow rate range of 138-251 ml/min as rCaCO3 =kn 32 πM2γ3/3R3ρ2T3 (C -C∗)0.8/[ ln (C /C∗) ]3 + πρ/3M kg3 kn(C -C∗) 2t3 , where nano-CaCO3 nucleation rate constant was kn = 6.24 ×1019 exp(-15940/RT) and nano-CaCO3 growth rate constant was kg = 0.79 exp(-47650/RT) respectively. Research indicated that nucleation rates and growth rates both increased with the increasing of temperature and CO32- ion concentration. And crystal growth was dependent on temperature more than that of nucleation process because the activation energy of CaCO3 growth was bigger than that of CaCO3 nucleation. Decreasing the reaction temperature and CO2 flow rate was more beneficial for producing nano-size CaCO3 because of the lower CaCO3 growth rates. The deduced kinetic equation could briefly predict the average particle sizes of nano-CaCO3.

Coupled Growth in Hypermonotectics

NASA Technical Reports Server (NTRS)

Andrews, J. Barry; Coriell, Sam R.

2001-01-01

The overall objective of this project is to obtain a fundamental understanding of the physics controlling solidification processes in immiscible alloy systems. The investigation involves both experimentation and the development of a model describing solidification in monotectic systems. The experimental segment was designed to first demonstrate that it is possible to obtain interface stability and steady state coupled growth in hypermonotectic alloys through microgravity processing. Microgravity results obtained to date have verified this possibility. Future flights will permit experimental determination of the limits of interface stability and the influence of alloy composition and growth rate on microstructure. The objectives of the modeling segment of the investigation include prediction of the limits of interface stability, modeling of convective flow due to residual acceleration, and the influence of surface tension driven flows at the solidification interface. The study of solidification processes in immiscible alloy systems is hindered by the inherent convective flow that occurs on Earth and by the possibility of sedimentation of the higher density immiscible liquid phase. It has been shown that processing using a high thermal gradient and a low growth rate can lead to a stable macroscopically planar growth front even in hypermonotectic alloys. Processing under these growth conditions can avoid constitutional supercooling and prevent the formation of the minor immiscible liquid phase in advance of the solidification front. However, the solute depleted boundary layer that forms in advance of the solidification front is almost always less dense than the liquid away from the solidification front. As a result, convective instability is expected. Ground based testing has indicated that convection is a major problem in these alloy systems and leads to gross compositional variations along the sample and difficulties maintaining interface stability. Sustained low gravity processing conditions are necessary in order to minimize these problems and obtain solidification conditions which approach steady state.

Validating a model that predicts daily growth and feed quality of New Zealand dairy pastures.

PubMed

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.

An exploitation-competition system with negative effect of prey on its predator.

PubMed

Wang, Yuanshi

2015-05-01

This paper considers an exploitation-competition system in which exploitation is the dominant interaction when the prey is at low density, while competition is dominant when the prey is at high density due to its negative effect on the predator. The two-species system is characterized by differential equations, which are the combination of Lotka-Volterra competitive and predator-prey models. Global dynamics of the model demonstrate some basic properties of exploitation-competition systems: (i) When the growth rate of prey is extremely small, the prey cannot promote the growth of predator. (ii) When the growth rate is small, an obligate predator can survive by preying on the prey, while a facultative predator can approach a high density by the predation. (iii) When the growth rate is intermediate, the predator can approach the maximal density by an intermediate predation. (iv) When the growth rate is large, the predator can persist only if it has a large density and its predation on the prey is big. (v) Intermediate predation is beneficial to the predator under certain parameter range, while over- or under-predation is not good. Extremely big/small predation would lead to extinction of species. Numerical simulations confirm and extend our results. Copyright © 2015 Elsevier Inc. All rights reserved.

Comparison of Allogeneic and Syngeneic Rat Glioma Models by Using MRI and Histopathologic Evaluation.

PubMed

Biasibetti, Elena; Valazza, Alberto; Capucchio, Maria T; Annovazzi, Laura; Battaglia, Luigi; Chirio, Daniela; Gallarate, Marina; Mellai, Marta; Muntoni, Elisabetta; Peira, Elena; Riganti, Chiara; Schiffer, Davide; Panciani, Pierpaolo; Lanotte, Michele

2017-03-01

Research in neurooncology traditionally requires appropriate in vivo animal models, on which therapeutic strategies are tested before human trials are designed and proceed. Several reproducible animal experimental models, in which human physiologic conditions can be mimicked, are available for studying glioblastoma multiforme. In an ideal rat model, the tumor is of glial origin, grows in predictable and reproducible patterns, closely resembles human gliomas histopathologically, and is weakly or nonimmunogenic. In the current study, we used MRI and histopathologic evaluation to compare the most widely used allogeneic rat glioma model, C6-Wistar, with the F98-Fischer syngeneic rat glioma model in terms of percentage tumor growth or regression and growth rate. In vivo MRI demonstrated considerable variation in tumor volume and frequency between the 2 rat models despite the same stereotactic implantation technique. Faster and more reproducible glioma growth occurred in the immunoresponsive environment of the F98-Fischer model, because the immune response is minimized toward syngeneic cells. The marked inability of the C6-Wistar allogeneic system to generate a reproducible model and the episodes of spontaneous tumor regression with this system may have been due to the increased humoral and cellular immune responses after tumor implantation.

Towards optimization of ACRT schedules applied to the gradient freeze growth of cadmium zinc telluride

NASA Astrophysics Data System (ADS)

Divecha, Mia S.; Derby, Jeffrey J.

2017-12-01

Historically, the melt growth of II-VI crystals has benefitted from the application of the accelerated crucible rotation technique (ACRT). Here, we employ a comprehensive numerical model to assess the impact of two ACRT schedules designed for a cadmium zinc telluride growth system per the classical recommendations of Capper and co-workers. The ;flow maximizing; ACRT schedule, with higher rotation, effectively mixes the solutal field in the melt but does not reduce supercooling adjacent to the growth interface. The ACRT schedule derived for stable Ekman flow, with lower rotation, proves more effective in reducing supercooling and promoting stable growth. These counterintuitive results highlight the need for more comprehensive studies on the optimization of ACRT schedules for specific growth systems and for desired growth outcomes.

A dynamic growth model of vegetative soya bean plants: model structure and behaviour under varying root temperature and nitrogen concentration

NASA Technical Reports Server (NTRS)

Lim, J. T.; Wilkerson, G. G.; Raper, C. D. Jr; Gold, H. J.

1990-01-01

A differential equation model of vegetative growth of the soya bean plant (Glycine max (L.) Merrill cv. Ransom') was developed to account for plant growth in a phytotron system under variation of root temperature and nitrogen concentration in nutrient solution. The model was tested by comparing model outputs with data from four different experiments. Model predictions agreed fairly well with measured plant performance over a wide range of root temperatures and over a range of nitrogen concentrations in nutrient solution between 0.5 and 10.0 mmol NO3- in the phytotron environment. Sensitivity analyses revealed that the model was most sensitive to changes in parameters relating to carbohydrate concentration in the plant and nitrogen uptake rate.

Targeted delivery of growth factors in ischemic stroke animal models.

PubMed

Rhim, Taiyoun; Lee, Minhyung

2016-01-01

Ischemic stroke is caused by reduced blood supply and leads to loss of brain function. The reduced oxygen and nutrient supply stimulates various physiological responses, including induction of growth factors. Growth factors prevent neuronal cell death, promote neovascularization, and induce cell growth. However, the concentration of growth factors is not sufficient to recover brain function after the ischemic damage, suggesting that delivery of growth factors into the ischemic brain may be a useful treatment for ischemic stroke. In this review, various approaches for the delivery of growth factors to ischemic brain tissue are discussed, including local and targeting delivery systems. To develop growth factor therapy for ischemic stroke, important considerations should be taken into account. First, growth factors may have possible side effects. Thus, concentration of growth factors should be restricted to the ischemic tissues by local administration or targeted delivery. Second, the duration of growth factor therapy should be optimized. Growth factor proteins may be degraded too fast to have a high enough therapeutic effect. Therefore, delivery systems for controlled release or gene delivery may be useful. Third, the delivery systems to the brain should be optimized according to the delivery route.

Optimization of Phenotyping Assays for the Model Monocot Setaria viridis

PubMed Central

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

2017-01-01

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

Optimization of Phenotyping Assays for the Model Monocot Setaria viridis.

PubMed

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

2017-01-01

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

Bifurcations of a periodically forced microbial continuous culture model with restrained growth rate

NASA Astrophysics Data System (ADS)

Ren, Jingli; Yuan, Qigang

2017-08-01

A three dimensional microbial continuous culture model with a restrained microbial growth rate is studied in this paper. Two types of dilution rates are considered to investigate the dynamic behaviors of the model. For the unforced system, fold bifurcation and Hopf bifurcation are detected, and numerical simulations reveal that the system undergoes degenerate Hopf bifurcation. When the system is periodically forced, bifurcation diagrams for periodic solutions of period-one and period-two are given by researching the Poincaré map, corresponding to different bifurcation cases in the unforced system. Stable and unstable quasiperiodic solutions are obtained by Neimark-Sacker bifurcation with different parameter values. Periodic solutions of various periods can occur or disappear and even change their stability, when the Poincaré map of the forced system undergoes Neimark-Sacker bifurcation, flip bifurcation, and fold bifurcation. Chaotic attractors generated by a cascade of period doublings and some phase portraits are given at last.

Mixture theory-based poroelasticity as a model of interstitial tissue growth

PubMed Central

Cowin, Stephen C.; Cardoso, Luis

2011-01-01

This contribution presents an alternative approach to mixture theory-based poroelasticity by transferring some poroelastic concepts developed by Maurice Biot to mixture theory. These concepts are a larger RVE and the subRVE-RVE velocity average tensor, which Biot called the micro-macro velocity average tensor. This velocity average tensor is assumed here to depend upon the pore structure fabric. The formulation of mixture theory presented is directed toward the modeling of interstitial growth, that is to say changing mass and changing density of an organism. Traditional mixture theory considers constituents to be open systems, but the entire mixture is a closed system. In this development the mixture is also considered to be an open system as an alternative method of modeling growth. Growth is slow and accelerations are neglected in the applications. The velocity of a solid constituent is employed as the main reference velocity in preference to the mean velocity concept from the original formulation of mixture theory. The standard development of statements of the conservation principles and entropy inequality employed in mixture theory are modified to account for these kinematic changes and to allow for supplies of mass, momentum and energy to each constituent and to the mixture as a whole. The objective is to establish a basis for the development of constitutive equations for growth of tissues. PMID:22184481

Mixture theory-based poroelasticity as a model of interstitial tissue growth.

PubMed

Cowin, Stephen C; Cardoso, Luis

2012-01-01

This contribution presents an alternative approach to mixture theory-based poroelasticity by transferring some poroelastic concepts developed by Maurice Biot to mixture theory. These concepts are a larger RVE and the subRVE-RVE velocity average tensor, which Biot called the micro-macro velocity average tensor. This velocity average tensor is assumed here to depend upon the pore structure fabric. The formulation of mixture theory presented is directed toward the modeling of interstitial growth, that is to say changing mass and changing density of an organism. Traditional mixture theory considers constituents to be open systems, but the entire mixture is a closed system. In this development the mixture is also considered to be an open system as an alternative method of modeling growth. Growth is slow and accelerations are neglected in the applications. The velocity of a solid constituent is employed as the main reference velocity in preference to the mean velocity concept from the original formulation of mixture theory. The standard development of statements of the conservation principles and entropy inequality employed in mixture theory are modified to account for these kinematic changes and to allow for supplies of mass, momentum and energy to each constituent and to the mixture as a whole. The objective is to establish a basis for the development of constitutive equations for growth of tissues.

Analysis of turbulence and surface growth models on the estimation of soot level in ethylene non-premixed flames

NASA Astrophysics Data System (ADS)

Yunardi, Y.; Munawar, Edi; Rinaldi, Wahyu; Razali, Asbar; Iskandar, Elwina; Fairweather, M.

2018-02-01

Soot prediction in a combustion system has become a subject of attention, as many factors influence its accuracy. An accurate temperature prediction will likely yield better soot predictions, since the inception, growth and destruction of the soot are affected by the temperature. This paper reported the study on the influences of turbulence closure and surface growth models on the prediction of soot levels in turbulent flames. The results demonstrated that a substantial distinction was observed in terms of temperature predictions derived using the k-ɛ and the Reynolds stress models, for the two ethylene flames studied here amongst the four types of surface growth rate model investigated, the assumption of the soot surface growth rate proportional to the particle number density, but independent on the surface area of soot particles, f ( A s ) = ρ N s , yields in closest agreement with the radial data. Without any adjustment to the constants in the surface growth term, other approaches where the surface growth directly proportional to the surface area and square root of surface area, f ( A s ) = A s and f ( A s ) = √ A s , result in an under- prediction of soot volume fraction. These results suggest that predictions of soot volume fraction are sensitive to the modelling of surface growth.

A predictability study of Lorenz's 28-variable model as a dynamical system

NASA Technical Reports Server (NTRS)

Krishnamurthy, V.

1993-01-01

The dynamics of error growth in a two-layer nonlinear quasi-geostrophic model has been studied to gain an understanding of the mathematical theory of atmospheric predictability. The growth of random errors of varying initial magnitudes has been studied, and the relation between this classical approach and the concepts of the nonlinear dynamical systems theory has been explored. The local and global growths of random errors have been expressed partly in terms of the properties of an error ellipsoid and the Liapunov exponents determined by linear error dynamics. The local growth of small errors is initially governed by several modes of the evolving error ellipsoid but soon becomes dominated by the longest axis. The average global growth of small errors is exponential with a growth rate consistent with the largest Liapunov exponent. The duration of the exponential growth phase depends on the initial magnitude of the errors. The subsequent large errors undergo a nonlinear growth with a steadily decreasing growth rate and attain saturation that defines the limit of predictability. The degree of chaos and the largest Liapunov exponent show considerable variation with change in the forcing, which implies that the time variation in the external forcing can introduce variable character to the predictability.

Gas-phase kinetics during diamond growth: CH4 as-growth species

NASA Astrophysics Data System (ADS)

Harris, Stephen J.

1989-04-01

We have used a one-dimensional kinetic analysis to model the gas-phase chemistry that occurred during the diamond growth experiments of Chauhan, Angus, and Gardner [J. Appl. Phys. 47, 4746 (1976)]. In those experiments the weight of diamond seed crystals heated by lamps in a CH4/H2 environment was monitored by a microbalance. No filament or electric discharge was present. Our analysis shows that diamond growth occurred in this system by direct reaction of CH4 on the diamond surface. C2H2 and CH3, which have been proposed as diamond growth species, played no significant role there, although our results do not address their possible contributions in other systems such as filament- or plasma-assisted diamond growth.

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

PubMed

Rahmandad, Hazhir

2014-01-01

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

Human Growth and Body Weight Dynamics: An Integrative Systems Model

PubMed Central

Rahmandad, Hazhir

2014-01-01

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

Co-culture of oligodendrocytes and neurons can be used to assess drugs for axon regeneration in the central nervous system

PubMed Central

Gang, Lin; Yao, Yu-chen; Liu, Ying-fu; Li, Yi-peng; Yang, Kai; Lu, Lei; Cheng, Yuan-chi; Chen, Xu-yi; Tu, Yue

2015-01-01

We present a novel in vitro model in which to investigate the efficacy of experimental drugs for the promotion of axon regeneration in the central nervous system. We co-cultured rat hippocampal neurons and cerebral cortical oligodendrocytes, and tested the co-culture system using a Nogo-66 receptor antagonist peptide (NEP1–40), which promotes axonal growth. Primary cultured oligodendrocytes suppressed axonal growth in the rat hippocampus, but NEP1–40 stimulated axonal growth in the co-culture system. Our results confirm the validity of the neuron-oligodendrocyte co-culture system as an assay for the evaluation of drugs for axon regeneration in the central nervous system. PMID:26692858

Reconstruction of an Immune Dynamic Model to Simulate the Contrasting Role of Auxin and Cytokinin in Plant Immunity.

PubMed

Kaltdorf, Martin; Dandekar, Thomas; Naseem, Muhammad

2017-01-01

In order to increase our understanding of biological dependencies in plant immune signaling pathways, the known interactions involved in plant immune networks are modeled. This allows computational analysis to predict the functions of growth related hormones in plant-pathogen interaction. The SQUAD (Standardized Qualitative Dynamical Systems) algorithm first determines stable system states in the network and then use them to compute continuous dynamical system states. Our reconstructed Boolean model encompassing hormone immune networks of Arabidopsis thaliana (Arabidopsis) and pathogenicity factors injected by model pathogen Pseudomonas syringae pv. tomato DC3000 (Pst DC3000) can be exploited to determine the impact of growth hormones in plant immunity. We describe a detailed working protocol how to use the modified SQUAD-package by exemplifying the contrasting effects of auxin and cytokinins in shaping plant-pathogen interaction.

Microgravity crystal growth

NASA Technical Reports Server (NTRS)

2001-01-01

Advanced finite element models are used to study three-dimensional, time-dependent flow and segregation in crystal growth systems. In this image of a prototypical model for melt and crystal growth, pathlines at one instant in time are shown for the flow of heated liquid silicon in a cylindrical container. The container is subjected to g-jitter disturbances along the vertical axis. A transverse magnetic field is applied to control them. Such computations are extremely powerful for understanding melt growth in microgravity where g-jitter drives buoyant flows. The simulation is part of the Theoretical Analysis of 3D, Transient Convection and Segregation in Microgravity Bridgman Crystal Growth investigation by Dr. Jeffrey J. Derby of the University of Mirnesota, Minneapolis.

Combination of a higher-tier flow-through system and population modeling to assess the effects of time-variable exposure of isoproturon on the green algae Desmodesmus subspicatus and Pseudokirchneriella subcapitata.

PubMed

Weber, Denis; Schaefer, Dieter; Dorgerloh, Michael; Bruns, Eric; Goerlitz, Gerhard; Hammel, Klaus; Preuss, Thomas G; Ratte, Hans Toni

2012-04-01

A flow-through system was developed to investigate the effects of time-variable exposure of pesticides on algae. A recently developed algae population model was used for simulations supported and verified by laboratory experiments. Flow-through studies with Desmodesmus subspicatus and Pseudokirchneriella subcapitata under time-variable exposure to isoproturon were performed, in which the exposure patterns were based on the results of FOrum for Co-ordination of pesticide fate models and their USe (FOCUS) model calculations for typical exposure situations via runoff or drain flow. Different types of pulsed exposure events were realized, including a whole range of repeated pulsed and steep peaks as well as periods of constant exposure. Both species recovered quickly in terms of growth from short-term exposure and according to substance dissipation from the system. Even at a peak 10 times the maximum predicted environmental concentration of isoproturon, only transient effects occurred on algae populations. No modified sensitivity or reduced growth was observed after repeated exposure. Model predictions of algal growth in the flow-through tests agreed well with the experimental data. The experimental boundary conditions and the physiological properties of the algae were used as the only model input. No calibration or parameter fitting was necessary. The combination of the flow-through experiments with the algae population model was revealed to be a powerful tool for the assessment of pulsed exposure on algae. It allowed investigating the growth reduction and recovery potential of algae after complex exposure, which is not possible with standard laboratory experiments alone. The results of the combined approach confirm the beneficial use of population models as supporting tools in higher-tier risk assessments of pesticides. Copyright © 2012 SETAC.

Cancer growth and metastasis as a metaphor of Go gaming: An Ising model approach

PubMed Central

Barradas-Bautista, Didier; Agostino, Mark; Cocho, Germinal

2018-01-01

This work aims for modeling and simulating the metastasis of cancer, via the analogy between the cancer process and the board game Go. In the game of Go, black stones that play first could correspond to a metaphor of the birth, growth, and metastasis of cancer. Moreover, playing white stones on the second turn could correspond the inhibition of cancer invasion. Mathematical modeling and algorithmic simulation of Go may therefore benefit the efforts to deploy therapies to surpass cancer illness by providing insight into the cellular growth and expansion over a tissue area. We use the Ising Hamiltonian, that models the energy exchange in interacting particles, for modeling the cancer dynamics. Parameters in the energy function refer the biochemical elements that induce cancer birth, growth, and metastasis; as well as the biochemical immune system process of defense. PMID:29718932

Non-normal perturbation growth in idealised island and headland wakes

NASA Astrophysics Data System (ADS)

Aiken, C. M.; Moore, A. M.; Middleton, J. H.

2003-12-01

Generalised linear stability theory is used to calculate the linear perturbations that furnish most rapid growth in energy in a model of a steady recirculating island wake. This optimal peturbation is found to be antisymmetric and to evolve into a von Kármán vortex street. Eigenanalysis of the linearised system reveals that the eigenmodes corresponding to vortex sheet formation are damped, so the growth of the perturbation is understood through the non-normality of the linearised system. Qualitatively similar perturbation growth is shown to occur in a non-linear model of stochastically-forced subcritical flow, resulting in transition to an unsteady wake. Free-stream variability with amplitude 8% of the mean inflow speed sustains vortex street structures in the non-linear model with perturbation velocities the order of the inflow speed, suggesting that environmental stochastic forcing may similarly be capable of exciting growing disturbances in real island wakes. To support this, qualitatively similar perturbation growth is demonstrated in the straining wake of a realistic island obstacle. It is shown that for the case of an idealised headland, where the vortex street eigenmodes are lacking, vortex sheets are produced through a similar non-normal process.

A toy model of sea ice growth

NASA Technical Reports Server (NTRS)

Thorndike, Alan S.

1992-01-01

My purpose here is to present a simplified treatment of the growth of sea ice. By ignoring many details, it is possible to obtain several results that help to clarify the ways in which the sea ice cover will respond to climate change. Three models are discussed. The first deals with the growth of sea ice during the cold season. The second describes the cycle of growth and melting for perennial ice. The third model extends the second to account for the possibility that the ice melts away entirely in the summer. In each case, the objective is to understand what physical processes are most important, what ice properties determine the ice behavior, and to which climate variables the system is most sensitive.

An analysis of the productivity of a CELSS continuous algal culture system

NASA Technical Reports Server (NTRS)

Radmer, R.; Behrens, P.; Fernandez, E.; Arnett, K.

1986-01-01

One of the most attractive aspects of using algal cultures as plant components for a Closed Ecological Life Support Systems (CELSS) is the efficiency with which they can be grown. Although algae are not necessarily intrinsically more efficient than higher plants, the ease which they can be handled and manipulated (more like chemical reagents than plants), and the culturing techniques available, result in much higher growth rates than are usually attainable with higher plants. Furthermore, preliminary experiments have demonstrated that algal growth and physiology is not detectable altered in a microgravity environment, (1) whereas the response of higher plants to zero gravity is unknown. In order to rationally design and operate culture systems, it is necessary to understand how the macroparameters of a culture system, e.g., productivity, are related to the physiological aspects of the algal culture. A first principles analysis of culture system is discussed, and a mathematical model that describes the relationship of culture productivity to the cell concentration of light-limited culture is derived. The predicted productivity vs cell concentration curve agrees well with the experimental data obtained to test this model, indicating that this model permits an accurate prediction of culture productivity given the growth parameters of the system.

Effect of irrigation systems on temporal distribution of malaria vectors in semi-arid regions

NASA Astrophysics Data System (ADS)

Ohta, Shunji; Kaga, Takumi

2014-04-01

Previous research models have used climate data to explain habitat conditions of Anopheles mosquitoes transmitting malaria parasites. Although they can estimate mosquito populations with sufficient accuracy in many areas, observational data show that there is a tendency to underestimate the active growth and reproduction period of mosquitoes in semi-arid agricultural regions. In this study, a new, modified model that includes irrigation as a factor was developed to predict the active growing period of mosquitoes more precisely than the base model for ecophysiological and climatological distribution of mosquito generations (ECD-mg). Five sites with complete sets of observational data were selected in semi-arid regions of India for the comparison. The active growing period of mosquitoes determined from the modified ECD-mg model that incorporated the irrigation factor was in agreement with the observational data, whereas the active growing period was underestimated by the previous ECD-mg model that did not incorporate irrigation. This suggests that anthropogenic changes in the water supply due to extensive irrigation can encourage the growth of Anopheles mosquitoes through the alteration of the natural water balance in their habitat. In addition, it was found that the irrigation systems not only enable the active growth of mosquitoes in dry seasons but also play an important role in stabilizing the growth in rainy seasons. Consequently, the irrigation systems could lengthen the annual growing period of Anopheles mosquitoes and increase the maximum generation number of mosquitoes in semi-arid subtropical regions.

Modeling Studies of PVT Growth of ZnSe: Current Status and Future Course

NASA Technical Reports Server (NTRS)

Ramachandran, N.; Su, Ching-Hua

1999-01-01

Bulk growth of wide band gap II-VI semiconductors by physical vapor transport (PVT) has been developed and refined over the past several years at NASA Marshall Space Flight Center. Results from a modeling study of PVT crystal growth of ZnSe are reported in this paper. The PVT process is numerically investigated using a two-dimensional formulation of the governing equations and associated boundary conditions. Both the incompressible Boussinesq approximation and a compressible model are tested to determine the influence of gravity on the process and to discern the differences between the two approaches. The influence of a residual gas is included in the models. The results show that both the incompressible and compressible approximations provide comparable results and the presence of a residual gas tends to measurably reduce the mass flux in the system. Detailed flow, thermal and concentration profiles are provided. The simulations show that the Stefan flux dominates the system flow field and the subtle gravitational effects can be gauged by subtracting this flux from the calculated profiles. Shear flows, due to solutal buoyancy, of the order of 50 microns/s for the liorizont,-d growth orientation and 10 microns/s for the vertical orientation are predicted. Whether these flows can fully account for the observed gravity related growth morphological effects and inhomogeneous solute and dopant distributions is a matter of conjecture. A template for future modeling efforts in this area is suggested which incorporates a mathematical approach to the tracking of the growth front based on energy of formation concepts.

Visual Simulation of Microalgae Growth in Bioregenerative Life Support System

NASA Astrophysics Data System (ADS)

Zhao, Ming

Bioregenerative life support system is one of the key technologies for future human deep space exploration and long-term space missions. BLSS use biological system as its core unit in combination with other physical and chemical equipments, under the proper control and manipulation by crew to complete a specific task to support life. Food production, waste treatment, oxygen and water regeneration are all conducted by higher plants or microalgae in BLSS, which is the most import characteristic different from other kinds of life support systems. Microalgae is light autotrophic micro-organisms, light undoubtedly is the most import factor which limits its growth and reproduction. Increasing or decreasing the light intensity changes the growth rate of microalgae, and then regulates the concentration of oxygen and carbon dioxide in the system. In this paper, based on the mathematical model of microalgae which grew under the different light intensity, three-dimensional visualization model was built and realized through using 3ds max, Virtools and some other three dimensional software, in order to display its change and impacting on oxygen and carbon dioxide intuitively. We changed its model structure and parameters, such as establishing closed-loop control system, light intensity, temperature and Nutrient fluid’s velocity and so on, carried out computer virtual simulation, and observed dynamic change of system with the aim of providing visualization support for system research.

Model of photoinduced structural change induced by THz pulse irradiation

NASA Astrophysics Data System (ADS)

Ishida, Kunio; Nasu, Keiichiro

Recently intense optical pulses with THz frequency have been obtained, and it is of interest to study the effect of irradiated THz pulses on electronic systems. We theoretically study the photoinduced cooperative dynamics triggered by irradiation of THz pulses. We employed a model of two-level localized electrons coupled with an optical phonon mode taking into account the nonadiabaticity of the electron dynamics, and solved the time-dependent Schrödinger equation numerically. We consider the cases in which the THz pulses create phonons near the surface of the system, and pursue the electronic transitions induced by the propagation of the phonons. We found that they are able to induce excited-state domain growth, and that the interference between them plays an important role in the growth dynamics. Hence, the domain growth is affected by the geometry of the surface of the system, which is different from the photoinduced structural change by visible/UV pulses. We also show that the nonadiabatic/adiabatic electronic transitions should be taken into account though the domain growth mainly proceeds on the ground-state potential energy surfaces(PESs). In other words, the energy level/structure of excited-state PESs are relevant to the domain-growth dynamics.

Mathematical model for the growth of phases in binary multiphase systems upon isothermic annealing

NASA Astrophysics Data System (ADS)

Molokhina, L. A.; Rogalin, V. E.; Filin, S. A.; Kaplunov, I. A.

2017-09-01

A phenomenological mathematical model of the formation and growth of phases in a binary multiphase system with allowance for factors influencing the process of diffusion in a binary system is presented. It is shown that phases can grow for a certain time at different ratios between diffusion parameters according to a parabolic law that depends on the duration of isothermic annealing. They then slow their growth after successor phases appear at their interface with one component and can completely disappear from a diffusion layer or begin to grow again, but only at a rate slower than during their initial formation. The dependence of the thickness of each phase layer in a multiphase diffusion zone on the duration of isothermic annealing and the ratio between the diffusion parameters in neighboring phases is obtained. It is established that a certain ratio between the phase growth and rates of dissolution with allowance for the coefficients of diffusion in each phase and the periods of incubation can result in the complete disappearance of one phase as early as the onset of the growth of phase nuclei and be interpreted as a process of reaction diffusion.

Growth of wormlike micelles in nonionic surfactant solutions: Quantitative theory vs. experiment.

PubMed

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.

Dynamic Urban Growth Models

DOT National Transportation Integrated Search

1978-12-01

In the report the concept of 'order by fluctuation,' that has appeared recently in physico-chemical and biological systems, is applied to the description of urban growth. It is shown that fluctuations play a vital role in the evolutionary process of ...

Dynamic Urban Growth Models

DOT National Transportation Integrated Search

1979-12-01

In the report the concept of 'order by fluctuation,' that has appeared recently in physico-chemical and biological systems, is applied to the description of urban growth. It is shown that fluctuations play a vital role in the evolutionary process of ...

Fatigue reliability of deck structures subjected to correlated crack growth

NASA Astrophysics Data System (ADS)

Feng, G. Q.; Garbatov, Y.; Guedes Soares, C.

2013-12-01

The objective of this work is to analyse fatigue reliability of deck structures subjected to correlated crack growth. The stress intensity factors of the correlated cracks are obtained by finite element analysis and based on which the geometry correction functions are derived. The Monte Carlo simulations are applied to predict the statistical descriptors of correlated cracks based on the Paris-Erdogan equation. A probabilistic model of crack growth as a function of time is used to analyse the fatigue reliability of deck structures accounting for the crack propagation correlation. A deck structure is modelled as a series system of stiffened panels, where a stiffened panel is regarded as a parallel system composed of plates and are longitudinal. It has been proven that the method developed here can be conveniently applied to perform the fatigue reliability assessment of structures subjected to correlated crack growth.

An engineering analysis of a closed cycle plant growth module

NASA Technical Reports Server (NTRS)

Stickford, G. H., Jr.; Jakob, F. E.; Landstrom, D. K.

1986-01-01

The SOLGEM model is a numerical engineering model which solves the flow and energy balance equations for the air flowing through a growing environment, assuming quasi-steady state conditions within the system. SOLGEM provides a dynamic simulation of the controlled environment system in that the temperature and flow conditions of the growing environment are estimated on an hourly basis in response to the weather data and the plant growth parameters. The flow energy balance considers the incident solar flux; incoming air temperature, humidity, and flow rate; heat exchange with the roof and floor; and heat and moisture exchange with the plants. A plant transpiration subroutine was developed based plant growth research facility, intended for the study of bioregenerative life support theories. The results of a performance analysis of the plant growth module are given. The estimated energy requirements of the module components and the total energy are given.

Boundedness and global existence in the higher-dimensional parabolic-parabolic chemotaxis system with/without growth source

NASA Astrophysics Data System (ADS)

Xiang, Tian

2015-06-01

In this paper, we are concerned with a general class of quasilinear parabolic-parabolic chemotaxis systems with/without growth source, under homogeneous Neumann boundary conditions in a smooth bounded domain Ω ⊂Rn with n ≥ 2. It is recently known that blowup is possible even in the presence of superlinear growth restrictions. Here, we derive new and interesting characterizations on the growth versus the boundedness. We show that the hard task of proving the L∞-boundedness of the cell density can be reduced to proving its Lr-boundedness. In other words, we show that the Lr-boundedness of the cell density can successfully guarantee its L∞-boundedness and hence its global boundedness, where r = n + ɛ or n/2 + ɛ depending on whether the growth restriction is essentially linear (including no growth) or superlinear. Hence, a blowup solution also blows up in Lp-norm for any suitably large p. More detailed information on how the growth source affects the boundedness of the solution is derived. These results reveal deep understandings of blowup mechanism for chemotaxis models. Then we use these criteria to establish uniform boundedness and hence global existence of the underlying models: logistic source in 2-D, cubic source as initially proposed by Mimura and Tsujikawa in 3-D, [ (n - 1) + ɛ ]st source in n-D with n ≥ 4. As a consequence, in a chemotaxis-growth model, blowup is impossible if the growth effect is suitably strong. Finally, we underline that our results remove the commonly assumed convexity on the domain Ω.

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

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

Newes, Emily K; Biddy, Mary J; Bush, Brian W

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

Simulation of an integrated system for the production of methane and single cell protein from biomass

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

Thomas, M.V.

1989-01-01

A numerical model was developed to simulate the operation of an integrated system for the production of methane and single-cell algal protein from a variety of biomass energy crops or waste streams. Economic analysis was performed at the end of each simulation. The model was capable of assisting in the determination of design parameters by providing relative economic information for various strategies. Three configurations of anaerobic reactors were simulated. These included fed-bed reactors, conventional stirred tank reactors, and continuously expanding reactors. A generic anaerobic digestion process model, using lumped substrate parameters, was developed for use by type-specific reactor models. Themore » generic anaerobic digestion model provided a tool for the testing of conversion efficiencies and kinetic parameters for a wide range of substrate types and reactor designs. Dynamic growth models were used to model the growth of algae and Eichornia crassipes was modeled as a function of daily incident radiation and temperature. The growth of Eichornia crassipes was modeled for the production of biomass as a substrate for digestion. Computer simulations with the system model indicated that tropical or subtropical locations offered the most promise for a viable system. The availability of large quantities of digestible waste and low land prices were found to be desirable in order to take advantage of the economies of scale. Other simulations indicated that poultry and swine manure produced larger biogas yields than cattle manure. The model was created in a modular fashion to allow for testing of a wide variety of unit operations. Coding was performed in the Pascal language for use on personal computers.« less

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

NASA Astrophysics Data System (ADS)

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

2009-07-01

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

The amazing evolutionary dynamics of non-linear optical systems with feedback

NASA Astrophysics Data System (ADS)

Yaroslavsky, Leonid

2013-09-01

Optical systems with feedback are, generally, non-linear dynamic systems. As such, they exhibit evolutionary behavior. In the paper we present results of experimental investigation of evolutionary dynamics of several models of such systems. The models are modifications of the famous mathematical "Game of Life". The modifications are two-fold: "Game of Life" rules are made stochastic and mutual influence of cells is made spatially non-uniform. A number of new phenomena in the evolutionary dynamics of the models are revealed: - "Ordering of chaos". Formation, from seed patterns, of stable maze-like patterns with chaotic "dislocations" that resemble natural patterns, such as skin patterns of some animals and fishes, see shell, fingerprints, magnetic domain patterns and alike, which one can frequently find in the nature. These patterns and their fragments exhibit a remarkable capability of unlimited growth. - "Self-controlled growth" of chaotic "live" formations into "communities" bounded, depending on the model, by a square, hexagon or octagon, until they reach a certain critical size, after which the growth stops. - "Eternal life in a bounded space" of "communities" after reaching a certain size and shape. - "Coherent shrinkage" of "mature", after reaching a certain size, "communities" into one of stable or oscillating patterns preserving in this process isomorphism of their bounding shapes until the very end.

A niching genetic algorithm applied to optimize a SiC-bulk crystal growth system

NASA Astrophysics Data System (ADS)

Su, Juan; Chen, Xuejiang; Li, Yuan; Pons, Michel; Blanquet, Elisabeth

2017-06-01

A niching genetic algorithm (NGA) was presented to optimize a SiC-bulk crystal growth system by PVT. The NGA based on clearing mechanism and its combination method with heat transfer model for SiC crystal growth were described in details. Then three inverse problems for optimization of growth system were carried out by NGA. Firstly, the radius of blind hole was optimized to decrease the radial temperature gradient along the substrate while the center temperature on the surface of substrate is fixed at 2500 K. Secondly, insulation materials with anisotropic thermal conductivities were selected to obtain much higher growth rate as 600, 800 and 1000 μm/h. Finally, the density of coils was also rearranged to minimize the temperature variation in the SiC powder. All the results were analyzed and discussed.

Field experimental data for crop modeling of wheat growth response to nitrogen fertilizer, elevated CO2, water stress, and high temperature

USDA-ARS?s Scientific Manuscript database

Field experimental data of five experiments covering a wide range Field experimental data of five experiments covering a wide range of growing conditions are assembled for wheat growth and cropping systems modeling. The data include (i) an experiment on interactive effects of elevated CO2 by water a...

Modeling the effect of competition on tree diameter growth as applied in STEMS.

Treesearch

Margaret R. Holdaway

1984-01-01

The modifier function used in STEMS (Stand and Tree Evaluation and Modeling System) mathematically represents the effect that the surrounding forest community has on the growth of an individual tree. This paper 1) develops the most recent modifier function, 2) discusses its form, 3) reports the results of the analysis with biological considerations and 4) evaluates the...

Growth and ligninolytic system production dynamics of the Phanerochaete chrysosporium fungus A modelling and optimization approach.

PubMed

Hormiga, J A; Vera, J; Frías, I; Torres Darias, N V

2008-10-10

The well-documented ability to degrade lignin and a variety of complex chemicals showed by the white-rot fungus Phanerochaete chrysosporium has made it the subject of many studies in areas of environmental concern, including pulp bioleaching and bioremediation technologies. However, until now, most of the work in this field has been focused on the ligninolytic sub-system but, due to the great complexity of the involved processes, less progress has been made in understanding the biochemical regulatory structure that could explain growth dynamics, the substrate utilization and the ligninolytic system production itself. In this work we want to tackle this problem from the perspectives and approaches of systems biology, which have been shown to be effective in the case of complex systems. We will use a top-down approach to the construction of this model aiming to identify the cellular sub-systems that play a major role in the whole process. We have investigated growth dynamics, substrate consumption and lignin peroxidase production of the P. chrysosporium wild type under a set of definite culture conditions. Based on data gathered from different authors and in our own experimental determinations, we built a model using a GMA power-law representation, which was used as platform to make predictive simulations. Thereby, we could assess the consistency of some current assumptions about the regulatory structure of the overall process. The model parameters were estimated from a time series experimental measurements by means of an algorithm previously adapted and optimized for power-law models. The model was subsequently checked for quality by comparing its predictions with the experimental behavior observed in new, different experimental settings and through perturbation analysis aimed to test the robustness of the model. Hence, the model showed to be able to predict the dynamics of two critical variables such as biomass and lignin peroxidase activity when in conditions of nutrient deprivation and after pulses of veratryl alcohol. Moreover, it successfully predicts the evolution of the variables during both, the active growth phase and after the deprivation shock. The close agreement between the predicted and observed behavior and the advanced understanding of its kinetic structure and regulatory features provides the necessary background for the design of a biotechnological set-up designed for the continuous production of the ligninolityc system and its optimization.

Towards systems biology of the gravity response of higher plants -multiscale analysis of Arabidopsis thaliana root growth

NASA Astrophysics Data System (ADS)

Palme, Klaus; Aubry, D.; Bensch, M.; Schmidt, T.; Ronneberger, O.; Neu, C.; Li, X.; Wang, H.; Santos, F.; Wang, B.; Paponov, I.; Ditengou, F. A.; Teale, W. T.; Volkmann, D.; Baluska, F.; Nonis, A.; Trevisan, S.; Ruperti, B.; Dovzhenko, A.

Gravity plays a fundamental role in plant growth and development. Up to now, little is known about the molecular organisation of the signal transduction cascades and networks which co-ordinate gravity perception and response. By using an integrated systems biological approach, a systems analysis of gravity perception and the subsequent tightly-regulated growth response is planned in the model plant Arabidopsis thaliana. This approach will address questions such as: (i) what are the components of gravity signal transduction pathways? (ii) what are the dynamics of these components? (iii) what is their spatio-temporal regulation in different tis-sues? Using Arabidopsis thaliana as a model-we use root growth to obtain insights in the gravity response. New techniques enable identification of the individual genes affected by grav-ity and further integration of transcriptomics and proteomics data into interaction networks and cell communication events that operate during gravitropic curvature. Using systematic multiscale analysis we have identified regulatory networks consisting of transcription factors, the protein degradation machinery, vesicle trafficking and cellular signalling during the gravire-sponse. We developed approach allowing to incorporate key features of the root system across all relevant spatial and temporal scales to describe gene-expression patterns and correlate them with individual gene and protein functions. Combination of high-resolution microscopy and novel computational tools resulted in development of the root 3D model in which quantitative descriptions of cellular network properties and of multicellular interactions important in root growth and gravitropism can be integrated for the first time.

Impact of Membrane-Induced Particle Immobilization on Seeded Growth Monitored by In Situ Liquid Scanning Transmission Electron Microscopy.

PubMed

Weiner, Rebecca G; Chen, Dennis P; Unocic, Raymond R; Skrabalak, Sara E

2016-05-01

In situ liquid cell scanning transmission electron microscopy probes seeded growth in real time. The growth of Pd on Au nanocubes is monitored as a model system to compare growth within a liquid cell and traditional colloidal synthesis. Different growth patterns are observed due to seed immobilization and the highly reducing environment within the liquid cell. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

On geological interpretations of crystal size distributions: Constant vs. proportionate growth

USGS Publications Warehouse

Eberl, D.D.; Kile, D.E.; Drits, V.A.

2002-01-01

Geological interpretations of crystal size distributions (CSDs) depend on understanding the crystal growth laws that generated the distributions. Most descriptions of crystal growth, including a population-balance modeling equation that is widely used in petrology, assume that crystal growth rates at any particular time are identical for all crystals, and, therefore, independent of crystal size. This type of growth under constant conditions can be modeled by adding a constant length to the diameter of each crystal for each time step. This growth equation is unlikely to be correct for most mineral systems because it neither generates nor maintains the shapes of lognormal CSDs, which are among the most common types of CSDs observed in rocks. In an alternative approach, size-dependent (proportionate) growth is modeled approximately by multiplying the size of each crystal by a factor, an operation that maintains CSD shape and variance, and which is in accord with calcite growth experiments. The latter growth law can be obtained during supply controlled growth using a modified version of the Law of Proportionate Effect (LPE), an equation that simulates the reaction path followed by a CSD shape as mean size increases.

Tree growth and competition in an old-growth Picea abies forest of boreal Sweden: influence of tree spatial patterning

USGS Publications Warehouse

Fraver, Shawn; D'Amato, Anthony W.; Bradford, John B.; Jonsson, Bengt Gunnar; Jönsson, Mari; Esseen, Per-Anders

2013-01-01

Question: What factors best characterize tree competitive environments in this structurally diverse old-growth forest, and do these factors vary spatially within and among stands? Location: Old-growth Picea abies forest of boreal Sweden. Methods: Using long-term, mapped permanent plot data augmented with dendrochronological analyses, we evaluated the effect of neighbourhood competition on focal tree growth by means of standard competition indices, each modified to include various metrics of trees size, neighbour mortality weighting (for neighbours that died during the inventory period), and within-neighbourhood tree clustering. Candidate models were evaluated using mixed-model linear regression analyses, with mean basal area increment as the response variable. We then analysed stand-level spatial patterns of competition indices and growth rates (via kriging) to determine if the relationship between these patterns could further elucidate factors influencing tree growth. Results: Inter-tree competition clearly affected growth rates, with crown volume being the size metric most strongly influencing the neighbourhood competitive environment. Including neighbour tree mortality weightings in models only slightly improved descriptions of competitive interactions. Although the within-neighbourhood clustering index did not improve model predictions, competition intensity was influenced by the underlying stand-level tree spatial arrangement: stand-level clustering locally intensified competition and reduced tree growth, whereas in the absence of such clustering, inter-tree competition played a lesser role in constraining tree growth. Conclusions: Our findings demonstrate that competition continues to influence forest processes and structures in an old-growth system that has not experienced major disturbances for at least two centuries. The finding that the underlying tree spatial pattern influenced the competitive environment suggests caution in interpreting traditional tree competition studies, in which tree spatial patterning is typically not taken into account. Our findings highlight the importance of forest structure – particularly the spatial arrangement of trees – in regulating inter-tree competition and growth in structurally diverse forests, and they provide insight into the causes and consequences of heterogeneity in this old-growth system.

A perspective on CELSS control issues

NASA Technical Reports Server (NTRS)

Blackwell, Ann L.

1990-01-01

Some issues of Closed Ecological Life Support System (CELSS) analysis and design are effectively addressed from a systems control perspective. CELSS system properties that may be elucidated using control theory in conjunction with mathematical and simulation modeling are enumerated. The approach that is being taken to the design of a control strategy for the Crop Growth Research Chamber (CGRC) and the relationship of that approach to CELSS plant growth unit subsystems control is described.

QSAR and 3D QSAR of inhibitors of the epidermal growth factor receptor

NASA Astrophysics Data System (ADS)

Pinto-Bazurco, Mariano; Tsakovska, Ivanka; Pajeva, Ilza

This article reports quantitative structure-activity relationships (QSAR) and 3D QSAR models of 134 structurally diverse inhibitors of the epidermal growth factor receptor (EGFR) tyrosine kinase. Free-Wilson analysis was used to derive the QSAR model. It identified the substituents in aniline, the polycyclic system, and the substituents at the 6- and 7-positions of the polycyclic system as the most important structural features. Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were used in the 3D QSAR modeling. The steric and electrostatic interactions proved the most important for the inhibitory effect. Both QSAR and 3D QSAR models led to consistent results. On the basis of the statistically significant models, new structures were proposed and their inhibitory activities were predicted.

Open system models of isotopic evolution in Earth's silicate reservoirs: Implications for crustal growth and mantle heterogeneity

NASA Astrophysics Data System (ADS)

Kumari, Seema; Paul, Debajyoti; Stracke, Andreas

2016-12-01

An open system evolutionary model of the Earth, comprising continental crust (CC), upper and lower mantle (UM, LM), and an additional isolated reservoir (IR) has been developed to study the isotopic evolution of the silicate Earth. The model is solved numerically at 1 Myr time steps over 4.55 Gyr of Earth history to reproduce both the present-day concentrations and isotope ratios of key radioactive decay systems (Rb-Sr, Sm-Nd, and U-Th-Pb) in these terrestrial reservoirs. Various crustal growth scenarios - continuous versus episodic and early versus late crustal growth - and their effect on the evolution of Sr-Nd-Pb isotope systematics in the silicate reservoirs have been evaluated. Modeling results where the present-day UM is ∼60% of the total mantle mass and a lower mantle that is non-primitive reproduce the estimated geochemical composition and isotope ratios in Earth's silicate reservoirs. The isotopic evolution of the silicate Earth is strongly affected by the mode of crustal growth; only an exponential crustal growth pattern with crustal growth since the early Archean satisfactorily explains the chemical and isotopic evolution of the crust-mantle system and accounts for the so-called Pb paradoxes. Assuming that the OIB source is located in the deeper mantle, our model could, however, not reproduce its target ɛNd of +4.6 for the UM, which has been estimated from the average isotope ratios of 32 individual ocean island localities. Hence, either mantle plumes sample the LM in a non-representative way, or the simplified model set-up does not capture the full complexity of Earth's lower mantle (Nd isotope) evolution. Compared to the results obtained for a 4.55 Ga Earth, a model assuming a protracted U-Pb evolution of silicate Earth by ca. 100 Myr reproduces a slightly better fit for the Pb isotope ratios in Earth's silicate reservoirs. One notable feature of successful models is the early depletion of incompatible elements (as well as rapid decrease in Th/U) in the UM within the initial 500 Myr, as a result of early formation of CC, which supports other evidence in favor of the presence of Hadean continental crust. Therefore, a chondritic Th/U ratio (4 ± 0.2) in the UM until 2 Gyr appears rather unlikely. We find that the κ conundrum - the observation that measured Th/U ratios and those deduced from 208Pb-206Pb isotope systematics differ - is a natural outcome of an open system evolution in which preferential recycling of U for the past 2 Gyr has played a dominant role. Overall, our simulations strongly favor exponential crustal growth, starting in the early Hadean, the transient preservation of compositionally distinct mantle reservoirs over billion year time periods, and a generally less incompatible element depleted, but non-primitive composition of the lower mantle.

Nonselective Harvesting of a Prey-Predator Fishery with Gompertz Law of Growth

ERIC Educational Resources Information Center

Purohit, D.; Chaudhuri, K. S.

2002-01-01

This paper develops a mathematical model for the nonselective harvesting of a prey-predator system in which both the prey and the predator obey the Gompertz law of growth and some prey avoid predation by hiding. The steady states of the system are determined, and the dynamical behaviour of both species is examined. The possibility of existence of…

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

TESP combines existing domain simulators in the electric power grid, with new transactive agents, growth models and evaluation scripts. The existing domain simulators include GridLAB-D for the distribution grid and single-family residential buildings, MATPOWER for transmission and bulk generation, and EnergyPlus for large buildings. More are planned for subsequent versions of TESP. The new elements are: TEAgents - simulate market participants and transactive systems for market clearing. Some of this functionality was extracted from GridLAB-D and implemented in Python for customization by PNNL and others; Growth Model - a means for simulating system changes over a multiyear period, including bothmore » normal load growth and specific investment decisions. Customizable in Python code; and Evaluation Script - a means of evaluating different transactive systems through customizable post-processing in Python code. TESP provides a method for other researchers and vendors to design transactive systems, and test them in a virtual environment. It allows customization of the key components by modifying Python code.« less

New self-limiting assembly model for Si quantum rings on Si(100).

PubMed

Yu, L W; Chen, K J; Song, J; Xu, J; Li, W; Li, X F; Wang, J M; Huang, X F

2007-04-20

We propose a new self-limiting assembly model for Si quantum rings on Si(100) where the ring's formation and evolution are driven by a growth-etching competition mechanism. The as-grown ring structure in a plasma enhanced chemical vapor deposition system has excellent rotational symmetry and superior morphology with a typical diameter, edge width, and height of 150-300, 10, and 5 nm, respectively. Based on this model, the size and morphology can be controlled well by simply tuning the timing procedure. We suggest that this growth model is not limited to certain material system, but provides a general scheme to control and tailor the self-assembly nanostructures into the desired size, shape, and complexity.

An L-system model for root system mycorrhization

NASA Astrophysics Data System (ADS)

Schnepf, Andrea; Schweiger, Peter; Jansa, Jan; Leitner, Daniel

2014-05-01

Mineral phosphate fertilisers are a non-renewable resource; rock phosphate reserves are estimated to be depleted in 50 to 100 years. In order to prevent a severe phosphate crisis in the 21st century, there is a need to decrease agricultural inputs such as P fertilisers by making use of plant mechanisms that increase P acquisition efficiency. Most plants establish mycorrhizal symbiosis as an adaptation to increase/economize their P acquisition from the soil. However, there is a great functional diversity in P acquisition mechanisms among different fungal species that colonize the roots (Thonar et al. 2011), and the composition of mycorrhizal community is known to depend strongly on agricultural management practices. Thus, the agroecosystem management may substantially affect the mycorrhizal functioning and also the use of P fertilizers. To date, it is still difficult to quantify the potential input savings for the agricultural crops through manipulation of their symbiotic microbiome, mainly due to lack of mechanistic understanding of P uptake dynamics by the fungal hyphae. In a first attempt, Schnepf et al. (2008b) have used mathematical modelling to show on the single root scale how different fungal growth pattern influence root P uptake. However, their approach was limited by the fact that it was restricted to the scale of a single root. The goal of this work is to advance the dynamic, three-dimensional root architecture model of Leitner et al. (2010) to include root system infection with arbuscular mycorrhizal fungi and growth of external mycelium. The root system infection model assumes that there is an average probability of infection (primary infection), that the probability of infection of a new root segment immediately adjacent to an existing infection is much higher than the average (secondary infection), that infected root segments have entry points that are the link between internal and external mycelium, that only uninfected root segments are susceptible (since new infection can only be detected in previously uninfected root) and that there is a maximum percentage of overall root system infection. Growth of external mycelium is based on the model of Schnepf et al. (2008a) but translated into L-system form. Different hypotheses about the effect of inoculum position (dispersed vs. localized) and about root system infection mechanisms can be tested with this model. This will help to quantify the role of the complex geometric structure of external mycelia in plant P acquisition and to gain mechanistic insights into whole-plant processes affected by mycorrhizal symbiosis. Literature Leitner, D., Klepsch, S., Bodner, G., Schnepf, A., 2010a. A dynamic root system growth model based on L-Systems. Plant Soil 332, 177-192. Schnepf, A., Roose, T., Schweiger, P., 2008a. Growth model for arbuscular mycorrhizal fungi. J R Soc Interface 5, 773-784. Schnepf, A., Roose, T., Schweiger, P., 2008b. Impact of growth and uptake patterns of arbuscular mycorrhizal fungi on plant phosphorus uptake - a modelling study. Plant Soil 312, 85-99. Thonar C, Schnepf A, Frossard E, Roose T, Jansa J (2011) Traits related to differences in function among three arbuscular mycorrhizal fungi. Plant and Soil 339: 231-245. Acknowledgements This research was partly supported by the Austrian Science Fund FWF (Grant No.: V220-N13) and by an APART fellowship of the Austrian Academy of Sciences at the Computational Science Center, University of Vienna (to D.L.).

Towards Optimization of ACRT Schedules Applied to the Gradient Freeze Growth of Cadmium Zinc Telluride

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

Divecha, Mia S.; Derby, Jeffrey J.

Historically, the melt growth of II-VI crystals has benefitted by the application of the accelerated crucible rotation technique (ACRT). Here, we employ a comprehensive numerical model to assess the impact of two ACRT schedules designed for a cadmium zinc telluride growth system per the classical recommendations of Capper and co-workers. The “flow maximizing” ACRT schedule, with higher rotation, effectively mixes the solutal field in the melt but does not reduce supercooling adjacent to the growth interface. The ACRT schedule derived for stable Ekman flow, with lower rotation, proves more effective in reducing supercooling and promoting stable growth. Furthermore, these counterintuitivemore » results highlight the need for more comprehensive studies on the optimization of ACRT schedules for specific growth systems and for desired growth outcomes.« less

Towards Optimization of ACRT Schedules Applied to the Gradient Freeze Growth of Cadmium Zinc Telluride

DOE PAGES

Divecha, Mia S.; Derby, Jeffrey J.

2017-10-03

Historically, the melt growth of II-VI crystals has benefitted by the application of the accelerated crucible rotation technique (ACRT). Here, we employ a comprehensive numerical model to assess the impact of two ACRT schedules designed for a cadmium zinc telluride growth system per the classical recommendations of Capper and co-workers. The “flow maximizing” ACRT schedule, with higher rotation, effectively mixes the solutal field in the melt but does not reduce supercooling adjacent to the growth interface. The ACRT schedule derived for stable Ekman flow, with lower rotation, proves more effective in reducing supercooling and promoting stable growth. Furthermore, these counterintuitivemore » results highlight the need for more comprehensive studies on the optimization of ACRT schedules for specific growth systems and for desired growth outcomes.« less

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.

EXPERIMENTAL STUDIES OF IBS (INTRA-BEAM SCATTERING) IN RHIC AND COMPARISON WITH THEORY.

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

FEDOTOV, A.V.; FISCHER, W.; TEPIKIAN, S.

A high-energy electron cooling system is presently being developed to overcome emittance growth due to Intra-beam Scattering (IBS) in RHIC. A critical item for choosing appropriate parameters of the cooler is an accurate description of the IBS. The analytic models were verified vs dedicated IBS measurements. Analysis of the 2004 data with the Au ions showed very good agreement for the longitudinal growth rates but significant disagreement with exact IBS models for the transverse growth rates. Experimental measurements were improved for the 2005 run with the Cu ions. Here, we present comparison of the 2005 data with theoretical models.

Bio-physical model provides insight into dispersal of plaice (Pleuronectes platessa L.) from putative spawning grounds to nursery areas on the west coast of Ireland

NASA Astrophysics Data System (ADS)

Zölck, Melanie; Brophy, Deirdre; Mohn, Christian; Minto, Cóilín; McGrath, David

2015-05-01

In this study we use an individual-based coupled physical biological model (ICPBM) to reconstruct the dispersal pathways of 0-group juveniles (young of the year) collected from nursery grounds in Galway Bay and to identify probable spawning ground locations for plaice on the west coast of Ireland. The relative importance of passive transport, behaviour and individual growth rates on successful larval delivery, from three putative spawning grounds to suitable nursery areas, was also investigated. Using a hydrodynamic Regional Ocean Modelling System (ROMS), combined with a particle tracking model, three model scenarios were tested: a passive tracer scenario (PTS), a linear growth scenario (LGS) and a temperature-dependent growth scenario (TDS). Hydrodynamic conditions were modelled and biological information (pelagic larval durations and size at settlement) incorporated. The LGS and TDS included vertical migration and tidally synchronised behaviour. Generalized Linear Model (GLM) comparisons showed that incorporation of behaviour and temperature-dependent growth, resulted in approximately two to three times more particles being delivered to sites of suitable depth for settlement (≤ 10 m), compared to passive transport alone (p < 0.001, LGS 19-78%; TDS 40-81%). The probability of successful delivery also varied significantly depending on the location, year and week of release (p < 0.05). A comparison of temperature histories between particles that were delivered to shallow inshore areas and those that failed to reach depths suitable for settlement indicated that dispersal to coastal nursery areas is facilitated by entrainment into a cool coastal current system. This study identifies a probable plaice spawning area in western Ireland and reconfirms the importance of including behaviour and growth in dispersal simulations. The model results suggest that differences in growth can influence larval delivery to potentially suitable nursery areas.

iTREE: Long-term variability of tree growth in a changing environment - identifying physiological mechanisms using stable C and O isotopes in tree rings.

NASA Astrophysics Data System (ADS)

Siegwolf, R. T. W.; Buchmann, N.; Frank, D.; Joos, F.; Kahmen, A.; Treydte, K.; Leuenberger, M.; Saurer, M.

2012-04-01

Trees play are a critical role in the carbon cycle - their photosynthetic assimilation is one of the largest terrestrial carbon fluxes and their standing biomass represents the largest carbon pool of the terrestrial biosphere. Understanding how tree physiology and growth respond to long-term environmental change is pivotal to predict the magnitude and direction of the terrestrial carbon sink. iTREE is an interdisciplinary research framework to capitalize on synergies among leading dendroclimatologists, plant physiologists, isotope specialists, and global carbon cycle modelers with the objectives of reducing uncertainties related to tree/forest growth in the context of changing natural environments. Cross-cutting themes in our project are tree rings, stable isotopes, and mechanistic modelling. We will (i) establish a European network of tree-ring based isotope time-series to retrodict interannual to long-term tree physiological changes, (ii) conduct laboratory and field experiments to adapt a mechanistic isotope model to derive plant physiological variables from tree-ring isotopes, (iii) implement this model into a dynamic global vegetation model, and perform subsequent model-data validation exercises to refine model representation of plant physiological processes and (iv) attribute long-term variation in tree growth to plant physiological and environmental drivers, and identify how our refined knowledge revises predictions of the coupled carbon-cycle climate system. We will contribute to i) advanced quantifications of long-term variation in tree growth across Central Europe, ii) novel long-term information on key physiological processes that underlie variations in tree growth, and iii) improved carbon cycle models that can be employed to revise predictions of the coupled carbon-cycle climate system. Hence iTREE will significantly contribute towards a seamless understanding of the responses of terrestrial ecosystems to long-term environmental change, and ultimately help reduce uncertainties of the magnitude and direction of the past and future terrestrial carbon sink.

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

An improved, low-cost, hydroponic system for growing Arabidopsis and other plant species under aseptic conditions

PubMed Central

2014-01-01

Background Hydroponics is a plant growth system that provides a more precise control of growth media composition. Several hydroponic systems have been reported for Arabidopsis and other model plants. The ease of system set up, cost of the growth system and flexibility to characterize and harvest plant material are features continually improved in new hydroponic system reported. Results We developed a hydroponic culture system for Arabidopsis and other model plants. This low cost, proficient, and novel system is based on recyclable and sterilizable plastic containers, which are readily available from local suppliers. Our system allows a large-scale manipulation of seedlings. It adapts to different growing treatments and has an extended growth window until adult plants are established. The novel seed-holder also facilitates the transfer and harvest of seedlings. Here we report the use of our hydroponic system to analyze transcriptomic responses of Arabidopsis to nutriment availability and plant/pathogen interactions. Conclusions The efficiency and functionality of our proposed hydroponic system is demonstrated in nutrient deficiency and pathogenesis experiments. Hydroponically grown Arabidopsis seedlings under long-time inorganic phosphate (Pi) deficiency showed typical changes in root architecture and high expression of marker genes involved in signaling and Pi recycling. Genome-wide transcriptional analysis of gene expression of Arabidopsis roots depleted of Pi by short time periods indicates that genes related to general stress are up-regulated before those specific to Pi signaling and metabolism. Our hydroponic system also proved useful for conducting pathogenesis essays, revealing early transcriptional activation of pathogenesis-related genes. PMID:24649917

An improved, low-cost, hydroponic system for growing Arabidopsis and other plant species under aseptic conditions.

PubMed

Alatorre-Cobos, Fulgencio; Calderón-Vázquez, Carlos; Ibarra-Laclette, Enrique; Yong-Villalobos, Lenin; Pérez-Torres, Claudia-Anahí; Oropeza-Aburto, Araceli; Méndez-Bravo, Alfonso; González-Morales, Sandra-Isabel; Gutiérrez-Alanís, Dolores; Chacón-López, Alejandra; Peña-Ocaña, Betsy-Anaid; Herrera-Estrella, Luis

2014-03-21

Hydroponics is a plant growth system that provides a more precise control of growth media composition. Several hydroponic systems have been reported for Arabidopsis and other model plants. The ease of system set up, cost of the growth system and flexibility to characterize and harvest plant material are features continually improved in new hydroponic system reported. We developed a hydroponic culture system for Arabidopsis and other model plants. This low cost, proficient, and novel system is based on recyclable and sterilizable plastic containers, which are readily available from local suppliers. Our system allows a large-scale manipulation of seedlings. It adapts to different growing treatments and has an extended growth window until adult plants are established. The novel seed-holder also facilitates the transfer and harvest of seedlings. Here we report the use of our hydroponic system to analyze transcriptomic responses of Arabidopsis to nutriment availability and plant/pathogen interactions. The efficiency and functionality of our proposed hydroponic system is demonstrated in nutrient deficiency and pathogenesis experiments. Hydroponically grown Arabidopsis seedlings under long-time inorganic phosphate (Pi) deficiency showed typical changes in root architecture and high expression of marker genes involved in signaling and Pi recycling. Genome-wide transcriptional analysis of gene expression of Arabidopsis roots depleted of Pi by short time periods indicates that genes related to general stress are up-regulated before those specific to Pi signaling and metabolism. Our hydroponic system also proved useful for conducting pathogenesis essays, revealing early transcriptional activation of pathogenesis-related genes.

Growth on demand: Reviewing the mechanobiology of stretched skin

PubMed Central

Zöllner, Alexander M.; Holland, Maria A.; Honda, Kord S.; Gosain, Arun K.; Kuhl, Ellen

2013-01-01

Skin is a highly dynamic, autoregulated, living system that responds to mechanical stretch through a net gain in skin surface area. Tissue expansion uses the concept of controlled overstretch to grow extra skin for defect repair in situ. While the short-term mechanics of stretched skin have been studied intensely by testing explanted tissue samples ex vivo, we know very little about the long-term biomechanics and mechanobiology of living skin in vivo. redHere we explore the long-term effects of mechanical stretch on the characteristics of living skin using a mathematical model for skin growth. We review the molecular mechanisms by which skin responds to mechanical loading and model their effects collectively in a single scalar-valued internal variable, the surface area growth. redThis allows us to adopt a continuum model for growing skin based on the multiplicative decomposition of the deformation gradient into a reversible elastic and an irreversible growth part.redTo demonstrate the inherent modularity of this approach, we implement growth as a user-defined constitutive subroutine into the general purpose implicit finite element program Abaqus/Standard. To illustrate the features of the model, we simulate the controlled area growth of skin in response to tissue expansion with multiple filling points in time. Our results demonstrate that the field theories of continuum mechanics can reliably predict the manipulation of thin biological membranes through mechanical overstretch. Our model could serve as a valuable tool to rationalize clinical process parameters such as expander geometry, expander size, filling volume, filling pressure, and inflation timing to minimize tissue necrosis and maximize patient comfort in plastic and reconstructive surgery. While initially developed for growing skin, our model can easily be generalized to arbitrary biological structures to explore the physiology and pathology of stretch-induced growth of other living systems such as hearts, arteries, bladders, intestines, ureters, muscles, and nerves. PMID:23623569

Preferential attachment and growth dynamics in complex systems

NASA Astrophysics Data System (ADS)

Yamasaki, Kazuko; Matia, Kaushik; Buldyrev, Sergey V.; Fu, Dongfeng; Pammolli, Fabio; Riccaboni, Massimo; Stanley, H. Eugene

2006-09-01

Complex systems can be characterized by classes of equivalency of their elements defined according to system specific rules. We propose a generalized preferential attachment model to describe the class size distribution. The model postulates preferential growth of the existing classes and the steady influx of new classes. According to the model, the distribution changes from a pure exponential form for zero influx of new classes to a power law with an exponential cut-off form when the influx of new classes is substantial. Predictions of the model are tested through the analysis of a unique industrial database, which covers both elementary units (products) and classes (markets, firms) in a given industry (pharmaceuticals), covering the entire size distribution. The model’s predictions are in good agreement with the data. The paper sheds light on the emergence of the exponent τ≈2 observed as a universal feature of many biological, social and economic problems.

Estimating non-isothermal bacterial growth in foods from isothermal experimental data.

PubMed

Corradini, M G; Peleg, M

2005-01-01

To develop a mathematical method to estimate non-isothermal microbial growth curves in foods from experiments performed under isothermal conditions and demonstrate the method's applicability with published growth data. Published isothermal growth curves of Pseudomonas spp. in refrigerated fish at 0-8 degrees C and Escherichia coli 1952 in a nutritional broth at 27.6-36 degrees C were fitted with two different three-parameter 'primary models' and the temperature dependence of their parameters was fitted by ad hoc empirical 'secondary models'. These were used to generate non-isothermal growth curves by solving, numerically, a differential equation derived on the premise that the momentary non-isothermal growth rate is the isothermal rate at the momentary temperature, at a time that corresponds to the momentary growth level of the population. The predicted non-isothermal growth curves were in agreement with the reported experimental ones and, as expected, the quality of the predictions did not depend on the 'primary model' chosen for the calculation. A common type of sigmoid growth curve can be adequately described by three-parameter 'primary models'. At least in the two systems examined, these could be used to predict growth patterns under a variety of continuous and discontinuous non-isothermal temperature profiles. The described mathematical method whenever validated experimentally will enable the simulation of the microbial quality of stored and transported foods under a large variety of existing or contemplated commercial temperature histories.

Functional approach to high-throughput plant growth analysis

PubMed Central

2013-01-01

Method Taking advantage of the current rapid development in imaging systems and computer vision algorithms, we present HPGA, a high-throughput phenotyping platform for plant growth modeling and functional analysis, which produces better understanding of energy distribution in regards of the balance between growth and defense. HPGA has two components, PAE (Plant Area Estimation) and GMA (Growth Modeling and Analysis). In PAE, by taking the complex leaf overlap problem into consideration, the area of every plant is measured from top-view images in four steps. Given the abundant measurements obtained with PAE, in the second module GMA, a nonlinear growth model is applied to generate growth curves, followed by functional data analysis. Results Experimental results on model plant Arabidopsis thaliana show that, compared to an existing approach, HPGA reduces the error rate of measuring plant area by half. The application of HPGA on the cfq mutant plants under fluctuating light reveals the correlation between low photosynthetic rates and small plant area (compared to wild type), which raises a hypothesis that knocking out cfq changes the sensitivity of the energy distribution under fluctuating light conditions to repress leaf growth. Availability HPGA is available at http://www.msu.edu/~jinchen/HPGA. PMID:24565437

Nucleation and growth in one dimension

NASA Astrophysics Data System (ADS)

Ben-Naim, E.; Krapivsky, P. L.

1996-10-01

We study statistical properties of the Kolmogorov-Avrami-Johnson-Mehl nucleation-and-growth model in one dimension. We obtain exact results for the gap density as well as the island distribution. When all nucleation events occur simultaneously, we show that the island distribution has discontinuous derivatives on the rays xn(t)=nt, n=1,2,3... . We introduce an accelerated growth mechanism with growth rate increasing linearly with the island size. We solve for the interisland gap density and show that the system reaches complete coverage in a finite time and that the near-critical behavior of the system is robust; i.e., it is insensitive to details such as the nucleation mechanism.

Monte Carlo simulation of ferroelectric domain growth

NASA Astrophysics Data System (ADS)

Li, B. L.; Liu, X. P.; Fang, F.; Zhu, J. L.; Liu, J.-M.

2006-01-01

The kinetics of two-dimensional isothermal domain growth in a quenched ferroelectric system is investigated using Monte Carlo simulation based on a realistic Ginzburg-Landau ferroelectric model with cubic-tetragonal (square-rectangle) phase transitions. The evolution of the domain pattern and domain size with annealing time is simulated, and the stability of trijunctions and tetrajunctions of domain walls is analyzed. It is found that in this much realistic model with strong dipole alignment anisotropy and long-range Coulomb interaction, the powerlaw for normal domain growth still stands applicable. Towards the late stage of domain growth, both the average domain area and reciprocal density of domain wall junctions increase linearly with time, and the one-parameter dynamic scaling of the domain growth is demonstrated.

Structural Health Monitoring System Trade Space Analysis Tool with Consideration for Crack Growth, Sensor Degradation and a Variable Detection Threshold

DTIC Science & Technology

2014-09-18

Erdogan , 1963). 26 Paris’s Law Under a fatigue stress regime Paris’s Law relates sub-critical crack growth to stress intensity factor. The basic...Paris and Erdogan , 1963). After takeoff, the model generates a probability distribution for the crack length in that specific sortie based on the...Law is one of the most widely used fatigue crack growth models and was used in this research effort (Paris and Erdogan , 1963). Paris’s Law Under a

Experimente ueber den Einflusse von Metaboliten und Antimetaboliten am Modell von Trichomonas Vaginalis. VI. (Experiments on the Influence of Metabolites and Antimetabolites on the Model of Trichomonas Vaginalis. VI. Communication: Effect of Vitamins and Vitamin-Like Substances),

DTIC Science & Technology

A number of substances (folic acid, axerophtol, tokopherol and others) stimulate the growth of Trichomonas vaginalis and, therefore, are very well...group of vitamins (thiamine, lactoflavin, pyridoxine and others) are without recognizeable effect upon the growth of Trichomonas vaginalis . The third...inhibiting effect upon the growth of Trichomonas vaginalis . Further investigations with these substances within a combined inhibition system seem to be important. (Modified author abstract)

A model for plant lighting system selection.

PubMed

Ciolkosz, D E; Albright, L D; Sager, J C; Langhans, R W

2002-01-01

A decision model is presented that compares lighting systems for a plant growth scenario and chooses the most appropriate system from a given set of possible choices. The model utilizes a Multiple Attribute Utility Theory approach, and incorporates expert input and performance simulations to calculate a utility value for each lighting system being considered. The system with the highest utility is deemed the most appropriate system. The model was applied to a greenhouse scenario, and analyses were conducted to test the model's output for validity. Parameter variation indicates that the model performed as expected. Analysis of model output indicates that differences in utility among the candidate lighting systems were sufficiently large to give confidence that the model's order of selection was valid.

Computational Combustion

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

Westbrook, C K; Mizobuchi, Y; Poinsot, T J

2004-08-26

Progress in the field of computational combustion over the past 50 years is reviewed. Particular attention is given to those classes of models that are common to most system modeling efforts, including fluid dynamics, chemical kinetics, liquid sprays, and turbulent flame models. The developments in combustion modeling are placed into the time-dependent context of the accompanying exponential growth in computer capabilities and Moore's Law. Superimposed on this steady growth, the occasional sudden advances in modeling capabilities are identified and their impacts are discussed. Integration of submodels into system models for spark ignition, diesel and homogeneous charge, compression ignition engines, surfacemore » and catalytic combustion, pulse combustion, and detonations are described. Finally, the current state of combustion modeling is illustrated by descriptions of a very large jet lifted 3D turbulent hydrogen flame with direct numerical simulation and 3D large eddy simulations of practical gas burner combustion devices.« less

Modeling the growth dynamics of four candidate crops for Controlled Ecological Life Support Systems (CELSS)

NASA Technical Reports Server (NTRS)

Volk, Tyler

1987-01-01

The production of food for human life support for advanced space missions will require the management of many different crops. The research to design these food production capabilities along with the waste management to recycle human metabolic wastes and inedible plant components are parts of Controlled Ecological Life Support Systems (CELSS). Since complete operating CELSS were not yet built, a useful adjunct to the research developing the various pieces of a CELSS are system simulation models that can examine what is currently known about the possible assembly of subsystems into a full CELSS. The growth dynamics of four crops (wheat, soybeans, potatoes, and lettuce) are examined for their general similarities and differences within the context of their important effects upon the dynamics of the gases, liquids, and solids in the CELSS. Data for the four crops currently under active research in the CELSS program using high-production hydroponics are presented. Two differential equations are developed and applied to the general characteristics of each crop growth pattern. Model parameters are determined by closely approximating each crop's data.

Effect of heat transfer of melt/solid interface shape and solute segregation in Edge-Defined Film-Fed growth - Finite element analysis

NASA Technical Reports Server (NTRS)

Ettouney, H. M.; Brown, R. A.

1982-01-01

The effects of the heat transfer environment in Edge-Defined Film-Fed Growth on melt-solid interface shape and lateral dopant segregation are studied by finite-element analysis of two-dimensional models for heat and mass transfer. Heat transfer configurations are studied that correspond to the uniform surroundings assumed in previous models and to lowand high-speed growth systems. The maximum growth rate for a silicon sheet is calculated and the range of validity of one-dimensional heat transfer models is established. The lateral segregation that results from curvature of the solidification interface is calculated for two solutes, boron and aluminum. In this way, heat transfer is linked directly to the uniformity of the product crystal.

Postbuckling and Growth of Delaminations in Composite Plates Subjected to Axial Compression

NASA Technical Reports Server (NTRS)

Reeder, James R.; Chunchu, Prasad B.; Song, Kyongchan; Ambur, Damodar R.

2002-01-01

The postbuckling response and growth of circular delaminations in flat and curved plates are investigated as part of a study to identify the criticality of delamination locations through the laminate thickness. The experimental results from tests on delaminated plates are compared with finite element analysis results generated using shell models. The analytical prediction of delamination growth is obtained by assessing the strain energy release rate results from the finite element model and comparing them to a mixed-mode fracture toughness failure criterion. The analytical results for onset of delamination growth compare well with experimental results generated using a 3-dimensional displacement visualization system. The record of delamination progression measured in this study has resulted in a fully 3-dimensional test case with which progressive failure models can be validated.

Gradient microfluidics enables rapid bacterial growth inhibition testing.

PubMed

Li, Bing; Qiu, Yong; Glidle, Andrew; McIlvenna, David; Luo, Qian; Cooper, Jon; Shi, Han-Chang; Yin, Huabing

2014-03-18

Bacterial growth inhibition tests have become a standard measure of the adverse effects of inhibitors for a wide range of applications, such as toxicity testing in the medical and environmental sciences. However, conventional well-plate formats for these tests are laborious and provide limited information (often being restricted to an end-point assay). In this study, we have developed a microfluidic system that enables fast quantification of the effect of an inhibitor on bacteria growth and survival, within a single experiment. This format offers a unique combination of advantages, including long-term continuous flow culture, generation of concentration gradients, and single cell morphology tracking. Using Escherichia coli and the inhibitor amoxicillin as one model system, we show excellent agreement between an on-chip single cell-based assay and conventional methods to obtain quantitative measures of antibiotic inhibition (for example, minimum inhibition concentration). Furthermore, we show that our methods can provide additional information, over and above that of the standard well-plate assay, including kinetic information on growth inhibition and measurements of bacterial morphological dynamics over a wide range of inhibitor concentrations. Finally, using a second model system, we show that this chip-based systems does not require the bacteria to be labeled and is well suited for the study of naturally occurring species. We illustrate this using Nitrosomonas europaea, an environmentally important bacteria, and show that the chip system can lead to a significant reduction in the period required for growth and inhibition measurements (<4 days, compared to weeks in a culture flask).

An integrated microalgal growth model and its application to optimize the biomass production of Scenedesmus sp. LX1 in open pond under the nutrient level of domestic secondary effluent.

PubMed

Wu, Yin-Hu; Li, Xin; Yu, Yin; Hu, Hong-Ying; Zhang, Tian-Yuan; Li, Feng-Min

2013-09-01

Microalgal growth is the key to the coupled system of wastewater treatment and microalgal biomass production. In this study, Monod model, Droop model and Steele model were incorporated to obtain an integrated growth model describing the combined effects of nitrogen, phosphorus and light intensity on the growth rate of Scenedesmus sp. LX1. The model parameters were obtained via fitting experimental data to these classical models. Furthermore, the biomass production of Scenedesmus sp. LX1 in open pond under nutrient level of secondary effluent was analyzed based on the integrated model, predicting a maximal microalgal biomass production rate about 20 g m(-2) d(-1). In order to optimize the biomass production of open pond the microalgal biomass concentration, light intensity on the surface of open pond, total depth of culture medium and hydraulic retention time should be 500 g m(-3), 16,000 lx, 0.2 m and 5.2 d in the conditions of this study, respectively. Copyright © 2013 Elsevier Ltd. All rights reserved.

A conceptual socio-hydrological model of the co-evolution of humans and water: case study of the Tarim River basin, western China

NASA Astrophysics Data System (ADS)

Liu, D.; Tian, F.; Lin, M.; Sivapalan, M.

2015-02-01

The complex interactions and feedbacks between humans and water are critically important issues but remain poorly understood in the newly proposed discipline of socio-hydrology (Sivapalan et al., 2012). An exploratory model with the appropriate level of simplification can be valuable for improving our understanding of the co-evolution and self-organization of socio-hydrological systems driven by interactions and feedbacks operating at different scales. In this study, a simplified conceptual socio-hydrological model based on logistic growth curves is developed for the Tarim River basin in western China and is used to illustrate the explanatory power of such a co-evolutionary model. The study area is the main stream of the Tarim River, which is divided into two modeling units. The socio-hydrological system is composed of four sub-systems, i.e., the hydrological, ecological, economic, and social sub-systems. In each modeling unit, the hydrological equation focusing on water balance is coupled to the other three evolutionary equations to represent the dynamics of the social sub-system (denoted by population), the economic sub-system (denoted by irrigated crop area ratio), and the ecological sub-system (denoted by natural vegetation cover), each of which is expressed in terms of a logistic growth curve. Four feedback loops are identified to represent the complex interactions among different sub-systems and different spatial units, of which two are inner loops occurring within each separate unit and the other two are outer loops linking the two modeling units. The feedback mechanisms are incorporated into the constitutive relations for model parameters, i.e., the colonization and mortality rates in the logistic growth curves that are jointly determined by the state variables of all sub-systems. The co-evolution of the Tarim socio-hydrological system is then analyzed with this conceptual model to gain insights into the overall system dynamics and its sensitivity to the external drivers and internal system variables. The results show a costly pendulum swing between a balanced distribution of socio-economic and natural ecologic resources among the upper and lower reaches and a highly skewed distribution towards the upper reach. This evolution is principally driven by the attitudinal changes occurring within water resources management policies that reflect the evolving community awareness of society to concerns regarding the ecology and environment.

Estimating the probability of survival of individual shortleaf pine (Pinus echinata mill.) trees

Treesearch

Sudip Shrestha; Thomas B. Lynch; Difei Zhang; James M. Guldin

2012-01-01

A survival model is needed in a forest growth system which predicts the survival of trees on individual basis or on a stand basis (Gertner, 1989). An individual-tree modeling approach is one of the better methods available for predicting growth and yield as it provides essential information about particular tree species; tree size, tree quality and tree present status...

Three-dimensional magnetic induction model of an octagonal edge-defined film-fed growth system

NASA Astrophysics Data System (ADS)

Rajendran, S.; Holmes, K.; Menna, A.

1994-03-01

Silicon wafers for the photovoltaic industry are produced by growing thin octagonal tubes by the edge-defined film-fed growth (EFG) process. The thermal origin of the wafer thickness variations was studied with a three-dimensional (3D) magnetic induction model. The implementation of the computer code and the significance of the computed results for improving the thickness uniformity are discussed.

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.

Comparison of Allogeneic and Syngeneic Rat Glioma Models by Using MRI and Histopathologic Evaluation

PubMed Central

Biasibetti, Elena; Valazza, Alberto; Capucchio, Maria T; Annovazzi, Laura; Battaglia, Luigi; Chirio, Daniela; Gallarate, Marina; Mellai, Marta; Muntoni, Elisabetta; Peira, Elena; Riganti, Chiara; Schiffer, Davide; Panciani, Pierpaolo; Lanotte, Michele

2017-01-01

Research in neurooncology traditionally requires appropriate in vivo animal models, on which therapeutic strategies are tested before human trials are designed and proceed. Several reproducible animal experimental models, in which human physiologic conditions can be mimicked, are available for studying glioblastoma multiforme. In an ideal rat model, the tumor is of glial origin, grows in predictable and reproducible patterns, closely resembles human gliomas histopathologically, and is weakly or nonimmunogenic. In the current study, we used MRI and histopathologic evaluation to compare the most widely used allogeneic rat glioma model, C6-Wistar, with the F98-Fischer syngeneic rat glioma model in terms of percentage tumor growth or regression and growth rate. In vivo MRI demonstrated considerable variation in tumor volume and frequency between the 2 rat models despite the same stereotactic implantation technique. Faster and more reproducible glioma growth occurred in the immunoresponsive environment of the F98-Fischer model, because the immune response is minimized toward syngeneic cells. The marked inability of the C6-Wistar allogeneic system to generate a reproducible model and the episodes of spontaneous tumor regression with this system may have been due to the increased humoral and cellular immune responses after tumor implantation. PMID:28381315

A Microstructure-Based Time-Dependent Crack Growth Model for Life and Reliability Prediction of Turbopropulsion Systems

NASA Astrophysics Data System (ADS)

Chan, Kwai S.; Enright, Michael P.; Moody, Jonathan; Fitch, Simeon H. K.

2014-01-01

The objective of this investigation was to develop an innovative methodology for life and reliability prediction of hot-section components in advanced turbopropulsion systems. A set of generic microstructure-based time-dependent crack growth (TDCG) models was developed and used to assess the sources of material variability due to microstructure and material parameters such as grain size, activation energy, and crack growth threshold for TDCG. A comparison of model predictions and experimental data obtained in air and in vacuum suggests that oxidation is responsible for higher crack growth rates at high temperatures, low frequencies, and long dwell times, but oxidation can also induce higher crack growth thresholds (Δ K th or K th) under certain conditions. Using the enhanced risk analysis tool and material constants calibrated to IN 718 data, the effect of TDCG on the risk of fracture in turboengine components was demonstrated for a generic rotor design and a realistic mission profile using the DARWIN® probabilistic life-prediction code. The results of this investigation confirmed that TDCG and cycle-dependent crack growth in IN 718 can be treated by a simple summation of the crack increments over a mission. For the temperatures considered, TDCG in IN 718 can be considered as a K-controlled or a diffusion-controlled oxidation-induced degradation process. This methodology provides a pathway for evaluating microstructural effects on multiple damage modes in hot-section components.

Contaminant concentration versus flow velocity: drivers of biodegradation and microbial growth in groundwater model systems.

PubMed

Grösbacher, Michael; Eckert, Dominik; Cirpka, Olaf A; Griebler, Christian

2018-06-01

Aromatic hydrocarbons belong to the most abundant contaminants in groundwater systems. They can serve as carbon and energy source for a multitude of indigenous microorganisms. Predictions of contaminant biodegradation and microbial growth in contaminated aquifers are often vague because the parameters of microbial activity in the mathematical models used for predictions are typically derived from batch experiments, which don't represent conditions in the field. In order to improve our understanding of key drivers of natural attenuation and the accuracy of predictive models, we conducted comparative experiments in batch and sediment flow-through systems with varying concentrations of contaminant in the inflow and flow velocities applying the aerobic Pseudomonas putida strain F1 and the denitrifying Aromatoleum aromaticum strain EbN1. We followed toluene degradation and bacterial growth by measuring toluene and oxygen concentrations and by direct cell counts. In the sediment columns, the total amount of toluene degraded by P. putida F1 increased with increasing source concentration and flow velocity, while toluene removal efficiency gradually decreased. Results point at mass transfer limitation being an important process controlling toluene biodegradation that cannot be assessed with batch experiments. We also observed a decrease in the maximum specific growth rate with increasing source concentration and flow velocity. At low toluene concentrations, the efficiencies in carbon assimilation within the flow-through systems exceeded those in the batch systems. In all column experiments the number of attached cells plateaued after an initial growth phase indicating a specific "carrying capacity" depending on contaminant concentration and flow velocity. Moreover, in all cases, cells attached to the sediment dominated over those in suspension, and toluene degradation was performed practically by attached cells only. The observed effects of varying contaminant inflow concentration and flow velocity on biodegradation could be captured by a reactive-transport model. By monitoring both attached and suspended cells we could quantify the release of new-grown cells from the sediments to the mobile aqueous phase. Studying flow velocity and contaminant concentrations as key drivers of contaminant transformation in sediment flow-through microcosms improves our system understanding and eventually the prediction of microbial biodegradation at contaminated sites.

The probability of growth of Listeria monocytogenes in cooked salmon and tryptic soy broth as affected by salt, smoke compound, and storage temperature.

PubMed

Hwang, Cheng-An

2009-05-01

The objectives of this study were to examine and model the probability of growth of Listeria monocytogenes in cooked salmon containing salt and smoke (phenol) compound and stored at various temperatures. A growth probability model was developed, and the model was compared to a model developed from tryptic soy broth (TSB) to assess the possibility of using TSB as a substitute for salmon. A 6-strain mixture of L. monocytogenes was inoculated into minced cooked salmon and TSB containing 0-10% NaCl and 0-34 ppm phenol to levels of 10(2-3) cfu/g, and the samples were vacuum-packed and stored at 0--25 degrees C for up to 42 days. A total 32 treatments, each with 16 samples, selected by central composite designs were tested. A logistic regression was used to model the probability of growth of L. monocytogenes as a function of concentrations of salt and phenol, and storage temperature. Resulted models showed that the probabilities of growth of L. monocytogenes in both salmon and TSB decreased when the salt and/or phenol concentrations increased, and at lower storage temperatures. In general, the growth probabilities of L. monocytogenes were affected more profoundly by salt and storage temperature than by phenol. The growth probabilities of L. monocytogenes estimated by the TSB model were higher than those by the salmon model at the same salt/phenol concentrations and storage temperatures. The growth probabilities predicted by the salmon and TSB models were comparable at higher storage temperatures, indicating the potential use of TSB as a model system to substitute salmon in studying the growth behavior of L. monocytogenes may only be suitable when the temperatures of interest are in higher storage temperatures (e.g., >12 degrees C). The model for salmon demonstrated the effects of salt, phenol, and storage temperature and their interactions on the growth probabilities of L. monocytogenes, and may be used to determine the growth probability of L. monocytogenes in smoked seafood.

Assessment of Heterotrophic Growth Supported by Soluble Microbial Products in Anammox Biofilm using Multidimensional Modeling

PubMed Central

Liu, Yiwen; Sun, Jing; Peng, Lai; Wang, Dongbo; Dai, Xiaohu; Ni, Bing-Jie

2016-01-01

Anaerobic ammonium oxidation (anammox) is known to autotrophically convert ammonium to dinitrogen gas with nitrite as the electron acceptor, but little is known about their released microbial products and how these are relative to heterotrophic growth in anammox system. In this work, we applied a mathematical model to assess the heterotrophic growth supported by three key microbial products produced by bacteria in anammox biofilm (utilization associated products (UAP), biomass associated products (BAP), and decay released substrate). Both One-dimensional and two-dimensional numerical biofilm models were developed to describe the development of anammox biofilm as a function of the multiple bacteria–substrate interactions. Model simulations show that UAP of anammox is the main organic carbon source for heterotrophs. Heterotrophs are mainly dominant at the surface of the anammox biofilm with small fraction inside the biofilm. 1-D model is sufficient to describe the main substrate concentrations/fluxes within the anammox biofilm, while the 2-D model can give a more detailed biomass distribution. The heterotrophic growth on UAP is mainly present at the outside of anammox biofilm, their growth on BAP (HetB) are present throughout the biofilm, while the growth on decay released substrate (HetD) is mainly located in the inner layers of the biofilm. PMID:27273460

Modelling grain growth in the framework of Rational Extended Thermodynamics

NASA Astrophysics Data System (ADS)

Kertsch, Lukas; Helm, Dirk

2016-05-01

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

Model Capabilities | Regional Energy Deployment System Model | Energy

Science.gov Websites

representation of those effects throughout the scenario. Because those effects are highly non-linear and other models, limited foresight, price penalties for rapid growth, and other non-linear effects

Cellodextrin transport in yeast for improved biofuel production.

PubMed

Galazka, Jonathan M; Tian, Chaoguang; Beeson, William T; Martinez, Bruno; Glass, N Louise; Cate, Jamie H D

2010-10-01

Fungal degradation of plant biomass may provide insights for improving cellulosic biofuel production. We show that the model cellulolytic fungus Neurospora crassa relies on a high-affinity cellodextrin transport system for rapid growth on cellulose. Reconstitution of the N. crassa cellodextrin transport system in Saccharomyces cerevisiae promotes efficient growth of this yeast on cellodextrins. In simultaneous saccharification and fermentation experiments, the engineered yeast strains more rapidly convert cellulose to ethanol when compared with yeast lacking this system.

Normal growth and development in the absence of hepatic insulin-like growth factor I

PubMed Central

Yakar, Shoshana; Liu, Jun-Li; Stannard, Bethel; Butler, Andrew; Accili, Domenici; Sauer, Brian; LeRoith, Derek

1999-01-01

The somatomedin hypothesis proposed that insulin-like growth factor I (IGF-I) was a hepatically derived circulating mediator of growth hormone and is a crucial factor for postnatal growth and development. To reassess this hypothesis, we have used the Cre/loxP recombination system to delete the igf1 gene exclusively in the liver. igf1 gene deletion in the liver abrogated expression of igf1 mRNA and caused a dramatic reduction in circulating IGF-I levels. However, growth as determined by body weight, body length, and femoral length did not differ from wild-type littermates. Although our model proves that hepatic IGF-I is indeed the major contributor to circulating IGF-I levels in mice it challenges the concept that circulating IGF-I is crucial for normal postnatal growth. Rather, our model provides direct evidence for the importance of the autocrine/paracrine role of IGF-I. PMID:10377413

Scaling behavior in the dynamics of citations to scientific journals

NASA Astrophysics Data System (ADS)

Picoli, S., Jr.; Mendes, R. S.; Malacarne, L. C.; Lenzi, E. K.

2006-08-01

We analyze a database comprising the impact factor (citations per recent items published) of scientific journals for a 13-year period (1992 2004). We find that i) the distribution of impact factors follows asymptotic power law behavior, ii) the distribution of annual logarithmic growth rates has an exponential form, and iii) the width of this distribution decays with the impact factor as a power law with exponent β simeq 0.22. The results ii) and iii) are surprising similar to those observed in the growth dynamics of organizations with complex internal structure suggesting the existence of common mechanisms underlying the dynamics of these systems. We propose a general model for such systems, an extension of the simplest model for firm growth, and compare their predictions with our empirical results.

The wing and the eye: a parsimonious theory for scaling and growth control?

PubMed

Romanova-Michaelides, Maria; Aguilar-Hidalgo, Daniel; Jülicher, Frank; Gonzalez-Gaitan, Marcos

2015-01-01

How a developing organ grows and patterns to its final shape is an important question in developmental biology. Studies of growth and patterning in the Drosophila wing imaginal disc have identified a key player, the morphogen Decapentaplegic (Dpp). These studies provided insights into our understanding of growth control and scaling: expansion of the Dpp gradient correlated with the growth of the tissue. A recent report on growth of a Drosophila organ other than the wing, the eye imaginal disc, prompts a reconsideration of our models of growth control. Despite striking differences between the two, the Dpp gradient scales with the target tissues of both organs and the growth of both the wing and the eye is controlled by Dpp. The goal of this review is to discuss whether a parsimonious model of scaling and growth control can explain the relationship between the Dpp gradient and growth in these two different developmental systems. © 2015 Wiley Periodicals, Inc.

The influence of external subsidies on diet, growth and Hg concentrations of freshwater sport fish: implications for management and fish consumption advisories

USGS Publications Warehouse

Lepak, J.M.; Hooten, M.B.; Johnson, B.M.

2012-01-01

Mercury (Hg) contamination in sport fish is a global problem. In freshwater systems, food web structure, sport fish sex, size, diet and growth rates influence Hg bioaccumulation. Fish stocking is a common management practice worldwide that can introduce external energy and contaminants into freshwater systems. Thus, stocking can alter many of the factors that influence Hg concentrations in sport fish. Here we evaluated the influence of external subsidies, in the form of hatchery-raised rainbow trout Oncorhynchus mykiss on walleye Sander vitreus diet, growth and Hg concentrations in two freshwater systems. Stocking differentially influenced male and female walleye diets and growth, producing a counterintuitive size-contamination relationship. Modeling indicated that walleye growth rate and diet were important explanatory variables when predicting Hg concentrations. Thus, hatchery contributions to freshwater systems in the form of energy and contaminants can influence diet, growth and Hg concentrations in sport fish. Given the extensive scale of fish stocking, and the known health risks associated with Hg contamination, this represents a significant issue for managers monitoring and manipulating freshwater food web structures, and policy makers attempting to develop fish consumption advisories to protect human health in stocked systems.

The influence of external subsidies on diet, growth and Hg concentrations of freshwater sport fish: implications for management and fish consumption advisories.

PubMed

Lepak, Jesse M; Hooten, Mevin B; Johnson, Brett M

2012-10-01

Mercury (Hg) contamination in sport fish is a global problem. In freshwater systems, food web structure, sport fish sex, size, diet and growth rates influence Hg bioaccumulation. Fish stocking is a common management practice worldwide that can introduce external energy and contaminants into freshwater systems. Thus, stocking can alter many of the factors that influence Hg concentrations in sport fish. Here we evaluated the influence of external subsidies, in the form of hatchery-raised rainbow trout Oncorhynchus mykiss on walleye Sander vitreus diet, growth and Hg concentrations in two freshwater systems. Stocking differentially influenced male and female walleye diets and growth, producing a counterintuitive size-contamination relationship. Modeling indicated that walleye growth rate and diet were important explanatory variables when predicting Hg concentrations. Thus, hatchery contributions to freshwater systems in the form of energy and contaminants can influence diet, growth and Hg concentrations in sport fish. Given the extensive scale of fish stocking, and the known health risks associated with Hg contamination, this represents a significant issue for managers monitoring and manipulating freshwater food web structures, and policy makers attempting to develop fish consumption advisories to protect human health in stocked systems.

The Relationship between Growth Scores and the Overall Observation Ratings for Teachers in a Public School System in Tennessee

ERIC Educational Resources Information Center

Davis, Joshua; Lampley, James H.; Foley, Virginia

2016-01-01

The purpose of this study was to investigate the relationship between the TVAAS growth score given by the Tennessee Department of Education and the overall Tennessee Educator Assessment Model (TEAM) observation rating for teachers in grades 3 through 8. The participating county public school system for this study is located in Northeast Tennessee.…

Development of a basal area growth system for maritime pine in northwestern Spain using the generalized algebraic difference approach

Treesearch

Marcos Barrio Anta; Fernando Castedo Dorado; Ulises Dieguez-Aranda; Juan G. Alvarez Gonzalez; Bernard R. Parresol; Roque Rodriguez Soalleiro

2006-01-01

A basal area growth system for single-species, even-aged maritime pine (Pinus pinaster Ait.) stands in Galicia (northwestern Spain) was developed from data of 212 plots measured between one and four times. Six dynamic equations were considered for analysis, and both numerical and graphical methods were used to compare alternative models. The double...

Fractal attractors in economic growth models with random pollution externalities

NASA Astrophysics Data System (ADS)

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

2018-05-01

We analyze a discrete time two-sector economic growth model where the production technologies in the final and human capital sectors are affected by random shocks both directly (via productivity and factor shares) and indirectly (via a pollution externality). We determine the optimal dynamics in the decentralized economy and show how these dynamics can be described in terms of a two-dimensional affine iterated function system with probability. This allows us to identify a suitable parameter configuration capable of generating exactly the classical Barnsley's fern as the attractor of the log-linearized optimal dynamical system.

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

Ruggerone, G.T.; Rogers, D.E.

Adult sockeye salmon scales, which provide an index of annual salmon growth in fresh and marine waters during 1965--1997, were measured to examine the effects on growth and adult returns of large spawning escapements influenced by the Exxon Valdez oil spill. Scale growth in freshwater was significantly reduced by the large 1989 spawning escapements in the Kenai River system, Red Lake, and Akalura Lake, but not in Chignik Lake. These data suggest that sockeye growth in freshwater may be less stable following the large escapement. Furthermore, the observations of large escapement adversely affecting growth of adjacent brood years of salmonmore » has important implications for stock-recruitment modeling. In Prince William Sound, Coghill Lake sockeye salmon that migrated through oil-contaminated waters did not exhibit noticeably reduced marine growth, but a model was developed that might explain low adult returns in recent years.« less

Minimising losses to predation during microalgae cultivation.

PubMed

Flynn, Kevin J; Kenny, Philip; Mitra, Aditee

2017-01-01

We explore approaches to minimise impacts of zooplanktonic pests upon commercial microalgal crops using system dynamics models to describe algal growth controlled by light and nutrient availability and zooplankton growth controlled by crop abundance and nutritional quality. Losses of microalgal crops are minimised when their growth is fastest and, in contrast, also when growing slowly under conditions of nutrient exhaustion. In many culture systems, however, dwindling light availability due to self-shading in dense suspensions favours slow growth under nutrient sufficiency. Such a situation improves microalgal quality as prey, enhancing zooplankton growth, and leads to rapid crop collapse. Timing of pest entry is important; crop losses are least likely in established, nutrient-exhausted microalgal communities grown for high C-content (e.g. for biofuels). A potentially useful approach is to promote a low level of P-stress that does not adversely affect microalgal growth but which produces a crop that is suboptimal for zooplankton growth.

A photon-driven micromotor can direct nerve fibre growth

NASA Astrophysics Data System (ADS)

Wu, Tao; Nieminen, Timo A.; Mohanty, Samarendra; Miotke, Jill; Meyer, Ronald L.; Rubinsztein-Dunlop, Halina; Berns, Michael W.

2012-01-01

Axonal path-finding is important in the development of the nervous system, nerve repair and nerve regeneration. The behaviour of the growth cone at the tip of the growing axon determines the direction of axonal growth and migration. We have developed an optical-based system to control the direction of growth of individual axons (nerve fibres) using laser-driven spinning birefringent spheres. One or two optical traps position birefringent beads adjacent to growth cones of cultured goldfish retinal ganglion cell axons. Circularly polarized light with angular momentum causes the trapped bead to spin. This creates a localized microfluidic flow generating an estimated 0.17 pN shear force against the growth cone that turns in response to the shear. The direction of axonal growth can be precisely manipulated by changing the rotation direction and position of this optically driven micromotor. A physical model estimating the shear force density on the axon is described.

Mechanical forces and their second messengers in stimulating cell growth in vitro

NASA Technical Reports Server (NTRS)

Vandenburgh, Herman H.

1992-01-01

Mechanical forces play an important role in modulating the growth of a number of different tissues including skeletal muscle, smooth muscle, cardiac muscle, bone, endothelium, epithelium, and lung. As interest increases in the molecular mechanisms by which mechanical forces are transduced into growth alterations, model systems are being developed to study these processes in tissue culture. This paper reviews the current methods available for mechanically stimulating tissue cultured cells. It then outlines some of the putative 'mechanogenic' second messengers involved in altering cell growth. Not surprisingly, many mechanogenic second messengers are the same as those involved in growth factor-induced cell growth. It is hypothesized that from an evolutionary standpoint, some second messenger systems may have initially evolved for unicellular organisms to respond to physical forces such as gravity and mechanical perturbation in their environment. As multicellular organisms came into existence, they appropriated these mechanogenic second messenger cascades for cellular regulation by growth factors.

The Growth of Community Colleges in the American States: An Application of Count Models to Institutional Growth

ERIC Educational Resources Information Center

Doyle, William R.; Gorbunov, Alexander V.

2011-01-01

Background/Context: The establishment of community colleges in the American states stands as one of the most unique features of our system of postsecondary education. Four possible explanations have been suggested for the growth of community colleges. An economic perspective argues that the development of community colleges came about as a result…

Coccolithophore growth and calcification in a changing ocean

NASA Astrophysics Data System (ADS)

Krumhardt, Kristen M.; Lovenduski, Nicole S.; Iglesias-Rodriguez, M. Debora; Kleypas, Joan A.

2017-12-01

Coccolithophores are the most abundant calcifying phytoplankton in the ocean. These tiny primary producers have an important role in the global carbon cycle, substantially contributing to global ocean calcification, ballasting organic matter to the deep sea, forming part of the marine food web base, and influencing ocean-atmosphere CO2 exchange. Despite these important impacts, coccolithophores are not explicitly simulated in most marine ecosystem models and, therefore, their impacts on carbon cycling are not represented in most Earth system models. Here, we compile field and laboratory data to synthesize overarching, across-species relationships between environmental conditions and coccolithophore growth rates and relative calcification (reported as a ratio of particulate inorganic carbon to particulate organic carbon in coccolithophore biomass, PIC/POC). We apply our relationships in a generalized coccolithophore model, estimating current surface ocean coccolithophore growth rates and relative calcification, and projecting how these may change over the 21st century using output from the Community Earth System Model large ensemble. We find that average increases in sea surface temperature of ∼ 2-3 ° C lead to faster coccolithophore growth rates globally (> 10% increase) and increased calcification at high latitudes. Roughly an ubiquitous doubling of surface ocean pCO2 by the end of the century has the potential to moderately stimulate coccolithophore growth rates, but leads to reduced calcification (∼ 25% decrease). Decreasing nutrient availability (from warming-induced increases in stratification) produces increases in relative calcification, but leads to ∼ 25% slower growth rates. With all drivers combined, we observe decreases in calcification and growth in most low and mid latitude regions, with possible increases in both of these responses in most high latitude regions. Major limitations of our coccolithophore model stem from a lack of conclusive physiological responses to changes in irradiance (we do not include light limitation in our model), and a lack of physiological data for major coccolithophore species. Species within the Umbellosphaera genus, for example, are dominant in mid to low latitude regions where we predict some of the largest decreases in coccolithophore growth rate and calcification.

White noise analysis of Phycomyces light growth response system. I. Normal intensity range.

PubMed Central

Lipson, E D

1975-01-01

The Wiener-Lee-Schetzen method for the identification of a nonlinear system through white gaussian noise stimulation was applied to the transient light growth response of the sporangiophore of Phycomyces. In order to cover a moderate dynamic range of light intensity I, the imput variable was defined to be log I. The experiments were performed in the normal range of light intensity, centered about I0 = 10(-6) W/cm2. The kernels of the Wierner functionals were computed up to second order. Within the range of a few decades the system is reasonably linear with log I. The main nonlinear feature of the second-order kernel corresponds to the property of rectification. Power spectral analysis reveals that the slow dynamics of the system are of at least fifth order. The system can be represented approximately by a linear transfer function, including a first-order high-pass (adaptation) filter with a 4 min time constant and an underdamped fourth-order low-pass filter. Accordingly a linear electronic circuit was constructed to simulate the small scale response characteristics. In terms of the adaptation model of Delbrück and Reichardt (1956, in Cellular Mechanisms in Differentiation and Growth, Princeton University Press), kernels were deduced for the dynamic dependence of the growth velocity (output) on the "subjective intensity", a presumed internal variable. Finally the linear electronic simulator above was generalized to accommodate the large scale nonlinearity of the adaptation model and to serve as a tool for deeper test of the model. PMID:1203444

Predictive Modeling of Neuroblastoma Growth Dynamics in Xenograft Model After Bevacizumab Anti-VEGF Therapy.

PubMed

He, Yixuan; Kodali, Anita; Wallace, Dorothy I

2018-06-14

Neuroblastoma is the leading cause of cancer death in young children. Although treatment for neuroblastoma has improved, the 5-year survival rate of patients still remains less than half. Recent studies have indicated that bevacizumab, an anti-VEGF drug used in treatment of several other cancer types, may be effective for treating neuroblastoma as well. However, its effect on neuroblastoma has not been well characterized. While traditional experiments are costly and time-consuming, mathematical models are capable of simulating complex systems quickly and inexpensively. In this study, we present a model of vascular tumor growth of neuroblastoma IMR-32 that is complex enough to replicate experimental data across a range of tumor cell properties measured in a suite of in vitro and in vivo experiments. The model provides quantitative insight into tumor vasculature, predicting a linear relationship between vasculature and tumor volume. The tumor growth model was coupled with known pharmacokinetics and pharmacodynamics of the VEGF blocker bevacizumab to study its effect on neuroblastoma growth dynamics. The results of our model suggest that total administered bevacizumab concentration per week, as opposed to dosage regimen, is the major determining factor in tumor suppression. Our model also establishes an exponentially decreasing relationship between administered bevacizumab concentration and tumor growth rate.

Plant growth and architectural modelling and its applications

PubMed Central

Guo, Yan; Fourcaud, Thierry; Jaeger, Marc; Zhang, Xiaopeng; Li, Baoguo

2011-01-01

Over the last decade, a growing number of scientists around the world have invested in research on plant growth and architectural modelling and applications (often abbreviated to plant modelling and applications, PMA). By combining physical and biological processes, spatially explicit models have shown their ability to help in understanding plant–environment interactions. This Special Issue on plant growth modelling presents new information within this topic, which are summarized in this preface. Research results for a variety of plant species growing in the field, in greenhouses and in natural environments are presented. Various models and simulation platforms are developed in this field of research, opening new features to a wider community of researchers and end users. New modelling technologies relating to the structure and function of plant shoots and root systems are explored from the cellular to the whole-plant and plant-community levels. PMID:21638797

Preliminary results of Physiological plant growth modelling for human life support in space

NASA Astrophysics Data System (ADS)

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

2012-07-01

Human life support is fundamental and crucial in any kind of space explorations. MELiSSA project of European Space Agency aims at developing a closed, artificial ecological life support system involving human, plants and micro organisms. Consuming carbon dioxide and water from the life support system, plants grow in one of the chambers and convert it into food and oxygen along with potable water. The environmental conditions, nutrient availability and its consumption of plants should be studied and necessarily modeled to predict the amount of food, oxygen and water with respect to the environmental changes and limitations. The reliability of a completely closed system mainly depends on the control laws and strategies used. An efficient control can occur, only if the system to control is itself well known, described and ideally if the responses of the system to environmental changes are predictable. In this aspect, the general structure of plant growth model has been designed together with physiological modelling.The physiological model consists of metabolic models of leaves, stem and roots, of which concern specific metabolisms of the associated plant parts. On the basis of the carbon source transport (eg. sucrose) through stem, the metabolic models (leaf and root) can be interconnected to each other and finally coupled to obtain the entire plant model. For the first step, leaf metabolic model network was built using stoichiometric, mass and energy balanced metabolic equations under steady state approach considering all necessary plant pathways for growth and maintenance of leaves. As the experimental data for lettuce plants grown in closed and controlled environmental chambers were available, the leaf metabolic model has been established for lettuce leaves. The constructed metabolic network is analyzed using known stoichiometric metabolic technique called metabolic flux analysis (MFA). Though, the leaf metabolic model alone is not sufficient to achieve the physiological plant model, in the case of lettuce (since the leaf metabolic model predominates), the developed model was verified with the carbon consumption of plant, as input. The model predicts the biomass production (as output) with respect to the quantum of light absorbed by the plant. The obtained result was found satisfying for the first initiation in the physiological plant modelling.

Organically Grown Architectures: Creating Decentralized, Autonomous Systems by Embryomorphic Engineering

NASA Astrophysics Data System (ADS)

Doursat, René

Exploding growth growth in computational systems forces us to gradually replace rigid design and control with decentralization and autonomy. Information technologies will progress, instead, by"meta-designing" mechanisms of system self-assembly, self-regulation and evolution. Nature offers a great variety of efficient complex systems, in which numerous small elements form large-scale, adaptive patterns. The new engineering challenge is to recreate this self-organization and let it freely generate innovative designs under guidance. This article presents an original model of artificial system growth inspired by embryogenesis. A virtual organism is a lattice of cells that proliferate, migrate and self-pattern into differentiated domains. Each cell's fate is controlled by an internal gene regulatory network network. Embryomorphic engineering emphasizes hyperdistributed architectures, and their development as a prerequisite of evolutionary design.

Application of a microcomputer-based system to control and monitor bacterial growth.

PubMed

Titus, J A; Luli, G W; Dekleva, M L; Strohl, W R

1984-02-01

A modular microcomputer-based system was developed to control and monitor various modes of bacterial growth. The control system was composed of an Apple II Plus microcomputer with 64-kilobyte random-access memory; a Cyborg ISAAC model 91A multichannel analog-to-digital and digital-to-analog converter; paired MRR-1 pH, pO(2), and foam control units; and in-house-designed relay, servo control, and turbidimetry systems. To demonstrate the flexibility of the system, we grew bacteria under various computer-controlled and monitored modes of growth, including batch, turbidostat, and chemostat systems. The Apple-ISAAC system was programmed in Labsoft BASIC (extended Applesoft) with an average control program using ca. 6 to 8 kilobytes of memory and up to 30 kilobytes for datum arrays. This modular microcomputer-based control system was easily coupled to laboratory scale fermentors for a variety of fermentations.

Application of a Microcomputer-Based System to Control and Monitor Bacterial Growth

PubMed Central

Titus, Jeffrey A.; Luli, Gregory W.; Dekleva, Michael L.; Strohl, William R.

1984-01-01

A modular microcomputer-based system was developed to control and monitor various modes of bacterial growth. The control system was composed of an Apple II Plus microcomputer with 64-kilobyte random-access memory; a Cyborg ISAAC model 91A multichannel analog-to-digital and digital-to-analog converter; paired MRR-1 pH, pO2, and foam control units; and in-house-designed relay, servo control, and turbidimetry systems. To demonstrate the flexibility of the system, we grew bacteria under various computer-controlled and monitored modes of growth, including batch, turbidostat, and chemostat systems. The Apple-ISAAC system was programmed in Labsoft BASIC (extended Applesoft) with an average control program using ca. 6 to 8 kilobytes of memory and up to 30 kilobytes for datum arrays. This modular microcomputer-based control system was easily coupled to laboratory scale fermentors for a variety of fermentations. PMID:16346462

A versatile mathematical work-flow to explore how Cancer Stem Cell fate influences tumor progression.

PubMed

Fornari, Chiara; Balbo, Gianfranco; Halawani, Sami M; Ba-Rukab, Omar; Ahmad, Ab Rahman; Calogero, Raffaele A; Cordero, Francesca; Beccuti, Marco

2015-01-01

Nowadays multidisciplinary approaches combining mathematical models with experimental assays are becoming relevant for the study of biological systems. Indeed, in cancer research multidisciplinary approaches are successfully used to understand the crucial aspects implicated in tumor growth. In particular, the Cancer Stem Cell (CSC) biology represents an area particularly suited to be studied through multidisciplinary approaches, and modeling has significantly contributed to pinpoint the crucial aspects implicated in this theory. More generally, to acquire new insights on a biological system it is necessary to have an accurate description of the phenomenon, such that making accurate predictions on its future behaviors becomes more likely. In this context, the identification of the parameters influencing model dynamics can be advantageous to increase model accuracy and to provide hints in designing wet experiments. Different techniques, ranging from statistical methods to analytical studies, have been developed. Their applications depend on case-specific aspects, such as the availability and quality of experimental data, and the dimension of the parameter space. The study of a new model on the CSC-based tumor progression has been the motivation to design a new work-flow that helps to characterize possible system dynamics and to identify those parameters influencing such behaviors. In detail, we extended our recent model on CSC-dynamics creating a new system capable of describing tumor growth during the different stages of cancer progression. Indeed, tumor cells appear to progress through lineage stages like those of normal tissues, being their division auto-regulated by internal feedback mechanisms. These new features have introduced some non-linearities in the model, making it more difficult to be studied by solely analytical techniques. Our new work-flow, based on statistical methods, was used to identify the parameters which influence the tumor growth. The effectiveness of the presented work-flow was firstly verified on two well known models and then applied to investigate our extended CSC model. We propose a new work-flow to study in a practical and informative way complex systems, allowing an easy identification, interpretation, and visualization of the key model parameters. Our methodology is useful to investigate possible model behaviors and to establish factors driving model dynamics. Analyzing our new CSC model guided by the proposed work-flow, we found that the deregulation of CSC asymmetric proliferation contributes to cancer initiation, in accordance with several experimental evidences. Specifically, model results indicated that the probability of CSC symmetric proliferation is responsible of a switching-like behavior which discriminates between tumorigenesis and unsustainable tumor growth.

An energy-economy-environment model for simulating the impacts of socioeconomic development on energy and environment.

PubMed

Wang, Wenyi; Zeng, Weihua; Yao, Bo

2014-01-01

Many rapidly developing regions have begun to draw the attention of the world. Meanwhile, the energy and environmental issues associated with rapid economic growth have aroused widespread critical concern. Therefore, studying energy, economic, and environmental systems is of great importance. This study establishes a system dynamic model that covers multiple aspects of those systems, such as energy, economy, population, water pollution, air pollution, solid waste, and technology. The model designed here attempts to determine the impacts of socioeconomic development on the energy and environment of Tongzhou District in three scenarios: under current, planning, and sustainable conditions. The results reveal that energy shortages and water pollutions are very serious and are the key issues constraining future social and economic development. Solid waste emissions increase with population growth. The prediction results provide valuable insights into social advancement.

solveME: fast and reliable solution of nonlinear ME models.

PubMed

Yang, Laurence; Ma, Ding; Ebrahim, Ali; Lloyd, Colton J; Saunders, Michael A; Palsson, Bernhard O

2016-09-22

Genome-scale models of metabolism and macromolecular expression (ME) significantly expand the scope and predictive capabilities of constraint-based modeling. ME models present considerable computational challenges: they are much (>30 times) larger than corresponding metabolic reconstructions (M models), are multiscale, and growth maximization is a nonlinear programming (NLP) problem, mainly due to macromolecule dilution constraints. Here, we address these computational challenges. We develop a fast and numerically reliable solution method for growth maximization in ME models using a quad-precision NLP solver (Quad MINOS). Our method was up to 45 % faster than binary search for six significant digits in growth rate. We also develop a fast, quad-precision flux variability analysis that is accelerated (up to 60× speedup) via solver warm-starts. Finally, we employ the tools developed to investigate growth-coupled succinate overproduction, accounting for proteome constraints. Just as genome-scale metabolic reconstructions have become an invaluable tool for computational and systems biologists, we anticipate that these fast and numerically reliable ME solution methods will accelerate the wide-spread adoption of ME models for researchers in these fields.

On valuing patches: Estimating contributions to metapopulation growth with reverse-time capture-recapture modelling

USGS Publications Warehouse

Sanderlin, J.S.; Waser, P.M.; Hines, J.E.; Nichols, J.D.

2012-01-01

Metapopulation ecology has historically been rich in theory, yet analytical approaches for inferring demographic relationships among local populations have been few. We show how reverse-time multi-state capture-recapture models can be used to estimate the importance of local recruitment and interpopulation dispersal to metapopulation growth. We use 'contribution metrics' to infer demographic connectedness among eight local populations of banner-tailed kangaroo rats, to assess their demographic closure, and to investigate sources of variation in these contributions. Using a 7 year dataset, we show that: (i) local populations are relatively independent demographically, and contributions to local population growth via dispersal within the system decline with distance; (ii) growth contributions via local survival and recruitment are greater for adults than juveniles, while contributions involving dispersal are greater for juveniles; (iii) central populations rely more on local recruitment and survival than peripheral populations; (iv) contributions involving dispersal are not clearly related to overall metapopulation density; and (v) estimated contributions from outside the system are unexpectedly large. Our analytical framework can classify metapopulations on a continuum between demographic independence and panmixia, detect hidden population growth contributions, and make inference about other population linkage forms, including rescue effects and source-sink structures. Finally, we discuss differences between demographic and genetic population linkage patterns for our system. ?? 2011 The Royal Society.

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

Iwamoto, Y.; Shin, S.G.; Matsubara, H.

The grain growth behavior of ceramic materials under the existence of a liquid phase was investigated for Si{sub 3}N{sub 4}-Y{sub 2}O{sub 3}-SiO{sub 2}, TiC-Ni, and WC-Co systems. The kinetics of grain growth behavior of these systems closely fitted to the cubic relation of d{sup 3} - d{sub 0}{sup 3} = Kt. The growth rate of {beta}-Si{sub 3}N{sub 4} grain was approximately one order of magnitude larger in length direction than that in width direction. The growth rate slightly increased with increasing liquid phase content in both these directions of the {beta}-Si{sub 3}N{sub 4} grain. TiC-Ni and WC-Co cermets had amore » peak in growth rate at a certain liquid phase content. The rate constant values of these systems were much smaller by a factor of 10{sup 3}{approximately}10{sup 5} compared to the theoretical values expected from the diffusion-controlled growth model. The experimental growth rates tended to decrease with increasing contiguity of the solid phase. The grain growth behavior of these systems could be explained by the mechanism resulting from the existence of contiguous boundaries of solid phase, which suppressed the movement of solid/liquid interfaces during liquid phase sintering.« less

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.

A computerized test system for thermal-mechanical fatigue crack growth

NASA Technical Reports Server (NTRS)

Marchand, N.; Pelloux, R. M.

1986-01-01

A computerized testing system to measure fatigue crack growth under thermal-mechanical fatigue conditions is described. Built around a servohydraulic machine, the system is capable of a push-pull test under stress-controlled or strain-controlled conditions in the temperature range of 25 to 1050 C. Temperature and mechanical strain are independently controlled by the closed-loop system to simulate the complex inservice strain-temperature relationship. A d-c electrical potential method is used to measure crack growth rates. The correction procedure of the potential signal to take into account powerline and RF-induced noises and thermal changes is described. It is shown that the potential drop technique can be used for physical mechanism studies and for modelling crack tip processes.

NASA Experimental Program to Stimulate Competitive Research: South Carolina

NASA Technical Reports Server (NTRS)

Sutton, Michael A.

2004-01-01

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

Carbon-climate-human interactions in an integrated human-Earth system model

NASA Astrophysics Data System (ADS)

Calvin, K. V.; Bond-Lamberty, B. P.; Jones, A. D.; Shi, X.

2016-12-01

The C4MIP and CMIP5 results highlighted large uncertainties in climate projections, driven to a large extent by limited understanding of the interactions between terrestrial carbon-cycle and climate feedbacks, and their associated uncertainties. These feedbacks are dominated by uncertainties in soil processes, disturbance dynamics, ecosystem response to climate change, and agricultural productivity, and land-use change. This research addresses three questions: (1) how do terrestrial feedbacks vary across different levels of climate change, (2) what is the relative contribution of CO2 fertilization and climate change, and (3) how robust are the results across different models and methods? We used a coupled modeling framework that integrates an Integrated Assessment Model (modeling economic and energy activity) with an Earth System Model (modeling the natural earth system) to examine how business-as-usual (RCP 8.5) climate change will affect ecosystem productivity, cropland extent, and other aspects of the human-Earth system. We find that higher levels of radiative forcing result in higher productivity growth, that increases in CO2 concentrations are the dominant contributors to that growth, and that our productivity increases fall in the middle of the range when compared to other CMIP5 models and the AgMIP models. These results emphasize the importance of examining both the anthropogenic and natural components of the earth system, and their long-term interactive feedbacks.

The CasKR Two-Component System Is Required for the Growth of Mesophilic and Psychrotolerant Bacillus cereus Strains at Low Temperatures

PubMed Central

Diomandé, Sara Esther; Chamot, Stéphanie; Antolinos, Vera; Vasai, Florian; Guinebretière, Marie-Hélène; Bornard, Isabelle; Nguyen-the, Christophe; Broussolle, Véronique

2014-01-01

The different strains of Bacillus cereus can grow at temperatures covering a very diverse range. Some B. cereus strains can grow in chilled food and consequently cause food poisoning. We have identified a new sensor/regulator mechanism involved in low-temperature B. cereus growth. Construction of a mutant of this two-component system enabled us to show that this system, called CasKR, is required for growth at the minimal temperature (Tmin). CasKR was also involved in optimal cold growth above Tmin and in cell survival below Tmin. Microscopic observation showed that CasKR plays a key role in cell shape during cold growth. Introducing the casKR genes in a ΔcasKR mutant restored its ability to grow at Tmin. Although it was first identified in the ATCC 14579 model strain, this mechanism has been conserved in most strains of the B. cereus group. We show that the role of CasKR in cold growth is similar in other B. cereus sensu lato strains with different growth temperature ranges, including psychrotolerant strains. PMID:24509924

Dry matter partitioning models for the simulation of individual fruit growth in greenhouse cucumber canopies

PubMed Central

Wiechers, Dirk; Kahlen, Katrin; Stützel, Hartmut

2011-01-01

Background and Aims Growth imbalances between individual fruits are common in indeterminate plants such as cucumber (Cucumis sativus). In this species, these imbalances can be related to differences in two growth characteristics, fruit growth duration until reaching a given size and fruit abortion. Both are related to distribution, and environmental factors as well as canopy architecture play a key role in their differentiation. Furthermore, events leading to a fruit reaching its harvestable size before or simultaneously with a prior fruit can be observed. Functional–structural plant models (FSPMs) allow for interactions between environmental factors, canopy architecture and physiological processes. Here, we tested hypotheses which account for these interactions by introducing dominance and abortion thresholds for the partitioning of assimilates between growing fruits. Methods Using the L-System formalism, an FSPM was developed which combined a model for architectural development, a biochemical model of photosynthesis and a model for assimilate partitioning, the last including a fruit growth model based on a size-related potential growth rate (RP). Starting from a distribution proportional to RP, the model was extended by including abortion and dominance. Abortion was related to source strength and dominance to sink strength. Both thresholds were varied to test their influence on fruit growth characteristics. Simulations were conducted for a dense row and a sparse isometric canopy. Key Results The simple partitioning models failed to simulate individual fruit growth realistically. The introduction of abortion and dominance thresholds gave the best results. Simulations of fruit growth durations and abortion rates were in line with measurements, and events in which a fruit was harvestable earlier than an older fruit were reproduced. Conclusions Dominance and abortion events need to be considered when simulating typical fruit growth traits. By integrating environmental factors, the FSPM can be a valuable tool to analyse and improve existing knowledge about the dynamics of assimilates partitioning. PMID:21715366

Microgravity

NASA Image and Video Library

2001-01-24

Advanced finite element models are used to study three-dimensional, time-dependent flow and segregation in crystal growth systems. In this image of a prototypical model for melt and crystal growth, pathlines at one instant in time are shown for the flow of heated liquid silicon in a cylindrical container. The container is subjected to g-jitter disturbances along the vertical axis. A transverse magnetic field is applied to control them. Such computations are extremely powerful for understanding melt growth in microgravity where g-jitter drives buoyant flows. The simulation is part of the Theoretical Analysis of 3D, Transient Convection and Segregation in Microgravity Bridgman Crystal Growth investigation by Dr. Jeffrey J. Derby of the University of Mirnesota, Minneapolis.

A growth stage and heat unit model for Hedysarum Boreale

USDA-ARS?s Scientific Manuscript database

A system for staging sweetvetch (Hedysarum boreale Nutt. [Fabaceae]) through vegetative and reproductive plant development was developed that corresponds with a heat-unit or growing degree day (GDD) model. This system designates 14 finite stages, V1 through V6 (pre-flowering or vegetative), and R1 ...

Ontogenetic scaling of metabolism, growth, and assimilation: testing metabolic scaling theory with Manduca sexta larvae.

PubMed

Sears, Katie E; Kerkhoff, Andrew J; Messerman, Arianne; Itagaki, Haruhiko

2012-01-01

Metabolism, growth, and the assimilation of energy and materials are essential processes that are intricately related and depend heavily on animal size. However, models that relate the ontogenetic scaling of energy assimilation and metabolism to growth rely on assumptions that have yet to be rigorously tested. Based on detailed daily measurements of metabolism, growth, and assimilation in tobacco hornworms, Manduca sexta, we provide a first experimental test of the core assumptions of a metabolic scaling model of ontogenetic growth. Metabolic scaling parameters changed over development, in violation of the model assumptions. At the same time, the scaling of growth rate matches that of metabolic rate, with similar scaling exponents both across and within developmental instars. Rates of assimilation were much higher than expected during the first two instars and did not match the patterns of scaling of growth and metabolism, which suggests high costs of biosynthesis early in development. The rapid increase in size and discrete instars observed in larval insect development provide an ideal system for understanding how patterns of growth and metabolism emerge from fundamental cellular processes and the exchange of materials and energy between an organism and its environment.

GIT2 Gene: Androgenic Regulation of White Adipose Tissue-Prostate Cancer Interactions

DTIC Science & Technology

2014-05-01

survival of growth factor–expressing ASCs, which enter the systemic circulation and promote PCa progression. An important note is that the prostate...surgical castration and systemic GLIPR1-ΔTM in vivo using VCaP xenograft model: 1. Generate orthotopic VCaP tumors in athymic nude male mice and...effects of systemic GLIPR1-ΔTM on orthotopic VCaP tumor growth and ASCs infiltration profiles ± surgical castration at acute (3d), intermediate (14d

Placental angiogenesis in sheep models of compromised pregnancy

PubMed Central

Reynolds, Lawrence P; Borowicz, Pawel P; Vonnahme, Kimberly A; Johnson, Mary Lynn; Grazul-Bilska, Anna T; Redmer, Dale A; Caton, Joel S

2005-01-01

Because the placenta is the organ that transports nutrients, respiratory gases and wastes between the maternal and fetal systems, development of its vascular beds is essential to normal placental function, and thus in supporting normal fetal growth. Compromised fetal growth and development have adverse health consequences during the neonatal period and throughout adult life. To establish the role of placental angiogenesis in compromised pregnancies, we first evaluated the pattern of placental angiogenesis and expression of angiogenic factors throughout normal pregnancy. In addition, we and others have established a variety of sheep models to evaluate the effects on fetal growth of various factors including maternal nutrient excess or deprivation and specific nutrients, maternal age, maternal and fetal genotype, increased numbers of fetuses, environmental thermal stress, and high altitude (hypobaric) conditions. Although placental angiogenesis is altered in each of these models in which fetal growth is adversely affected, the specific effect on placental angiogenesis depends on the type of ‘stress’ to which the pregnancy is subjected, and also differs between the fetal and maternal systems and between genotypes. We believe that the models of compromised pregnancy and the methods described in this review will enable us to develop a much better understanding of the mechanisms responsible for alterations in placental vascular development. PMID:15760944

Fatigue crack growth spectrum simplification: Facilitation of on-board damage prognosis systems

NASA Astrophysics Data System (ADS)

Adler, Matthew Adam

2009-12-01

Better lifetime predictions of systems subjected to fatigue loading are needed in support of the optimization of the costs of life-cycle engineering. In particular, the climate is especially encouraging for the development of safer aircraft. One issue is that aircraft experience complex fatigue loading and current methods for the prediction of fatigue damage accumulation rely on intensive computational tools that are not currently carried onboard during flight. These tools rely on complex models that are made more difficult by the complicated load spectra themselves. This presents an overhead burden as offline analysis must be performed at an offsite facility. This architecture is thus unable to provide online, timely information for on-board use. The direct objective of this research was to facilitate the real-time fatigue damage assessments of on-board systems with a particular emphasis on aging aircraft. To achieve the objective, the goal of this research was to simplify flight spectra. Variable-amplitude spectra, in which the load changes on a cycle-by-cycle basis, cannot readily be supported by an onboard system because the models required to predict fatigue crack growth during variable-amplitude loading are too complicated. They are too complicated because variable-amplitude fatigue crack growth analysis must be performed on a cycle-by-cycle basis as no closed-form solution exists. This makes these calculations too time-consuming and requires impractical, heavy onboard systems or offsite facilities. The hypothesis is to replace a variable-amplitude spectrum with an equivalent constant-amplitude spectrum. The advantage is a dramatic reduction in the complexity of the problem so that damage predictions can be made onboard by simple, fast calculations in real-time without the need to add additional weight to the aircraft. The intent is to reduce the computational burden and facilitate on-board projection of damage evolution and prediction for the accurate monitoring and management of aircraft. A spectrum reduction method was proposed and experimentally validated that reduces a variable-amplitude spectrum to a constant-amplitude equivalent. The reduction from a variable-amplitude (VA) spectrum to a constant-amplitude equivalent (CAE) was proposed as a two-part process. Preliminary spectrum reduction is first performed by elimination of those loading events shown to be too negligible to significantly contribute to fatigue crack growth. This is accomplished by rainflow counting. The next step is to calculate the appropriate, equivalent maximum and minimum loads by means of a root-mean-square average. This reduced spectrum defines the CAE and replaces the original spectrum. The simplified model was experimentally shown to provide the approximately same fatigue crack growth as the original spectrum. Fatigue crack growth experiments for two dissimilar aircraft spectra across a wide-range of stress-intensity levels validated the proposed spectrum reduction procedure. Irrespective of the initial K-level, the constant-amplitude equivalent spectra were always conservative in crack growth rate, and were so by an average of 50% over the full range tested. This corresponds to a maximum 15% overestimation in driving force Delta K. Given other typical sources of scatter that occur during fatigue crack growth, a consistent 50% conservative prediction on crack growth rate is very satisfying. This is especially attractive given the reduction in cost gained by the simplification. We now have a seamless system that gives an acceptably good approximation of damage occurring in the aircraft. This contribution is significant because in a very simple way we now have given a path to bypass the current infrastructure and ground-support requirements. The decision-making is now a lot simpler. In managing an entire fleet we now have a workable system where the strength is in no need for a massive, isolated computational center. The fidelity of the model gives credence because experimental data show that the approximate spectrum model captures the essential spectrum response. The discrepancy between the models is such that an experimental parameter is sufficient to converge the models. The proposed spectrum reduction procedure significantly mitigates the computational burden and allows for the probabilistic assessment of fatigue in real-time. This, in turn, provides support for crack-growth monitoring systems in facilitation of aircraft prognosis and fleet management.

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

NASA Astrophysics Data System (ADS)

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

2012-12-01

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

Modeling pinchoff and reconnection in a Hele-Shaw cell. I. The models and their calibration

NASA Astrophysics Data System (ADS)

Lee, Hyeong-Gi; Lowengrub, J. S.; Goodman, J.

2002-02-01

This is the first paper in a two-part series in which we analyze two model systems to study pinchoff and reconnection in binary fluid flow in a Hele-Shaw cell with arbitrary density and viscosity contrast between the components. The systems stem from a simplification of a general system of equations governing the motion of a binary fluid (NSCH model [Lowengrub and Truskinovsky, Proc. R. Soc. London, Ser. A 454, 2617 (1998)]) to flow in a Hele-Shaw cell. The system takes into account the chemical diffusivity between different components of a fluid mixture and the reactive stresses induced by inhomogeneity. In one of the systems we consider (HSCH), the binary fluid may be compressible due to diffusion. In the other system (BHSCH), a Boussinesq approximation is used and the fluid is incompressible. In this paper, we motivate, present and calibrate the HSCH/BHSCH equations so as to yield the classical sharp interface model as a limiting case. We then analyze their equilibria, one dimensional evolution and linear stability. In the second paper [paper II, Phys. Fluids 14, 514 (2002)], we analyze the behavior of the models in the fully nonlinear regime. In the BHSCH system, the equilibrium concentration profile is obtained using the classical Maxwell construction [Rowlinson and Widom, Molecular Theory of Capillarity (Clarendon, Oxford, 1979)] and does not depend on the orientation of the gravitational field. We find that the equilibria in the HSCH model are somewhat surprising as the gravitational field actually affects the internal structure of an isolated interface by driving additional stratification of light and heavy fluids over that predicted in the Boussinesq case. A comparison of the linear growth rates indicates that the HSCH system is slightly more diffusive than the BHSCH system. In both, linear convergence to the sharp interface growth rates is observed in a parameter controlling the interface thickness. In addition, we identify the effect that each of the parameters, in the HSCH/BHSCH models, has on the linear growth rates. We then show how this analysis may be used to suggest a set of modified parameters which, when used in the HSCH/BHSCH systems, yield improved agreement with the sharp interface model at a finite interface thickness. Evidence of this improved agreement may be found in paper II.

Plant growth and respiration re-visited: maintenance respiration defined – it is an emergent property of, not a separate process within, the system – and why the respiration : photosynthesis ratio is conservative

PubMed Central

Thornley, John H. M.

2011-01-01

Background and Aims Plant growth and respiration still has unresolved issues, examined here using a model. The aims of this work are to compare the model's predictions with McCree's observation-based respiration equation which led to the ‘growth respiration/maintenance respiration paradigm’ (GMRP) – this is required to give the model credibility; to clarify the nature of maintenance respiration (MR) using a model which does not represent MR explicitly; and to examine algebraic and numerical predictions for the respiration:photosynthesis ratio. Methods A two-state variable growth model is constructed, with structure and substrate, applicable on plant to ecosystem scales. Four processes are represented: photosynthesis, growth with growth respiration (GR), senescence giving a flux towards litter, and a recycling of some of this flux. There are four significant parameters: growth efficiency, rate constants for substrate utilization and structure senescence, and fraction of structure returned to the substrate pool. Key Results The model can simulate McCree's data on respiration, providing an alternative interpretation to the GMRP. The model's parameters are related to parameters used in this paradigm. MR is defined and calculated in terms of the model's parameters in two ways: first during exponential growth at zero growth rate; and secondly at equilibrium. The approaches concur. The equilibrium respiration:photosynthesis ratio has the value of 0·4, depending only on growth efficiency and recycling fraction. Conclusions McCree's equation is an approximation that the model can describe; it is mistaken to interpret his second coefficient as a maintenance requirement. An MR rate is defined and extracted algebraically from the model. MR as a specific process is not required and may be replaced with an approach from which an MR rate emerges. The model suggests that the respiration:photosynthesis ratio is conservative because it depends on two parameters only whose values are likely to be similar across ecosystems. PMID:21948663

Systems and Photosystems: Cellular Limits of Autotrophic Productivity in Cyanobacteria

PubMed Central

Burnap, Robert L.

2014-01-01

Recent advances in the modeling of microbial growth and metabolism have shown that growth rate critically depends upon the optimal allocation of finite proteomic resources among different cellular functions and that modeling growth rates becomes more realistic with the explicit accounting for the costs of macromolecular synthesis, most importantly, protein expression. The “proteomic constraint” is considered together with its application to understanding photosynthetic microbial growth. The central hypothesis is that physical limits of cellular space (and corresponding solvation capacity) in conjunction with cell surface-to-volume ratios represent the underlying constraints on the maximal rate of autotrophic microbial growth. The limitation of cellular space thus constrains the size the total complement of macromolecules, dissolved ions, and metabolites. To a first approximation, the upper limit in the cellular amount of the total proteome is bounded this space limit. This predicts that adaptation to osmotic stress will result in lower maximal growth rates due to decreased cellular concentrations of core metabolic proteins necessary for cell growth owing the accumulation of compatible osmolytes, as surmised previously. The finite capacity of membrane and cytoplasmic space also leads to the hypothesis that the species-specific differences in maximal growth rates likely reflect differences in the allocation of space to niche-specific proteins with the corresponding diminution of space devoted to other functions including proteins of core autotrophic metabolism, which drive cell reproduction. An optimization model for autotrophic microbial growth, the autotrophic replicator model, was developed based upon previous work investigating heterotrophic growth. The present model describes autotrophic growth in terms of the allocation protein resources among core functional groups including the photosynthetic electron transport chain, light-harvesting antennae, and the ribosome groups. PMID:25654078

Adaptive self-organization during growth of bacterial colonies

NASA Astrophysics Data System (ADS)

Ben-Jacob, Eshel; Shmueli, Haim; Shochet, Ofer; Tenenbaum, Adam

1992-09-01

We present a study of interfacial pattern formation during diffusion-limited growth of Bacillus subtilis. It is demonstrated that bacterial colonies can develop patterns similar to morphologies observed during diffusion-limited growth in non-living (azoic) systems such as solidification and electro-chemical deposition. The various growth morphologies, that is the global structure of the colony, are observed as we vary the growth conditions. These include fractal growth, dense-branching growth, compact growth, dendritic growth and chiral growth. The results demonstrate the action of a singular interplay between the micro-level (individual bacterium) and macro-level (the colony) in selecting the observed morphologies as is understood for non-living systems. Furthermore, the observed morphologies can be organized within a morphology diagram indicating the existence of a morphology selection principle similar to the one proposed for azoic systems. We propose a phase-field-like model (the phase being the bacterial concentration and the field being the nutrient concentration) to describe the growth. The bacteria-bacteria interaction is manifested as a phase dependent diffusion constant. Growth of a bacterial colony presents an inherent additional level of complexity compared to azoic systems, since the building blocks themselves are living systems. Thus, our studies also focus on the transition between morphologies. We have observed extended morphology transitions due to phenotypic changes of the bacteria, as well as bursts of new morphologies resulting from genotypic changes. In addition, we have observed extended and heritable transitions (mainly between dense branching growth and chiral growth) as well as phenotypic transitions that turn genotypic over time. We discuss the implications of our results in the context of the evolving picture of genome cybernetics. Diffusion limited growth of bacterial colonies combined with new understanding of pattern formation in azoic systems provide new tools for the study of adaptive self-organization and mutation in the presence of selective pressures. We include brief reviews of both the recent developments in the study of interfacial pattern formation in non-living systems and the current trends in the view of mutation dynamics.

Compilation of 1993 Annual Reports of the Navy ELF Communications System Ecological Monitoring Program

DTIC Science & Technology

1994-04-01

variation in non-treatment factors that may affect growth or health such as soil, stand conditions and background and treatment EM field levels. The time...diameter growth residuals were much greater than expected given existing climatic conditions . In 1992, when the antenna returned to full power operation...growing seasons. If an enviromental factor which is not accounted for in the growth model significantly impacts seasonal height growth , then the observed

Atomic force microscopy investigation of growth process of organic TCNQ aggregates on SiO2 and mica substrates

NASA Astrophysics Data System (ADS)

Huan, Qing; Hu, Hao; Pan, Li-Da; Xiao, Jiang; Du, Shi-Xuan; Gao, Hong-Jun

2010-08-01

Deposition patterns of tetracyanoquinodimethane (TCNQ) molecules on different surfaces are investigated by atomic force microscopy. A homemade physical vapour deposition system allows the better control of molecule deposition. Taking advantage of this system, we investigate TCNQ thin film growth on both SiO2 and mica surfaces. It is found that dense island patterns form at a high deposition rate, and a unique seahorse-like pattern forms at a low deposition rate. Growth patterns on different substrates suggest that the fractal pattern formation is dominated by molecule-molecule interaction. Finally, a phenomenal “two-branch" model is proposed to simulate the growth process of the seahorse pattern.

Tissue Engineering Organs for Space Biology Research

NASA Technical Reports Server (NTRS)

Vandenburgh, H. H.; Shansky, J.; DelTatto, M.; Lee, P.; Meir, J.

1999-01-01

Long-term manned space flight requires a better understanding of skeletal muscle atrophy resulting from microgravity. Atrophy most likely results from changes at both the systemic level (e.g. decreased circulating growth hormone, increased circulating glucocorticoids) and locally (e.g. decreased myofiber resting tension). Differentiated skeletal myofibers in tissue culture have provided a model system over the last decade for gaining a better understanding of the interactions of exogenous growth factors, endogenous growth factors, and muscle fiber tension in regulating protein turnover rates and muscle cell growth. Tissue engineering these cells into three dimensional bioartificial muscle (BAM) constructs has allowed us to extend their use to Space flight studies for the potential future development of countermeasures.

The Timber Resource Inventory Model (TRIM): a projection model for timber supply and policy analysis.

Treesearch

P.L. Tedder; R.N. La Mont; J.C. Kincaid

1987-01-01

TRIM (Timber Resource Inventory Model) is a yield table projection system developed for timber supply projections and policy analysis. TRIM simulates timber growth, inventories, management and area changes, and removals over the projection period. Programs in the TRIM system, card-by-card descriptions of required inputs, table formats, and sample results are presented...

Experimental and computational models of neurite extension at a choice point in response to controlled diffusive gradients

NASA Astrophysics Data System (ADS)

Catig, G. C.; Figueroa, S.; Moore, M. J.

2015-08-01

Ojective. Axons are guided toward desired targets through a series of choice points that they navigate by sensing cues in the cellular environment. A better understanding of how microenvironmental factors influence neurite growth during development can inform strategies to address nerve injury. Therefore, there is a need for biomimetic models to systematically investigate the influence of guidance cues at such choice points. Approach. We ran an adapted in silico biased turning axon growth model under the influence of nerve growth factor (NGF) and compared the results to corresponding in vitro experiments. We examined if growth simulations were predictive of neurite population behavior at a choice point. We used a biphasic micropatterned hydrogel system consisting of an outer cell restrictive mold that enclosed a bifurcated cell permissive region and placed a well near a bifurcating end to allow proteins to diffuse and form a gradient. Experimental diffusion profiles in these constructs were used to validate a diffusion computational model that utilized experimentally measured diffusion coefficients in hydrogels. The computational diffusion model was then used to establish defined soluble gradients within the permissive region of the hydrogels and maintain the profiles in physiological ranges for an extended period of time. Computational diffusion profiles informed the neurite growth model, which was compared with neurite growth experiments in the bifurcating hydrogel constructs. Main results. Results indicated that when applied to the constrained choice point geometry, the biased turning model predicted experimental behavior closely. Results for both simulated and in vitro neurite growth studies showed a significant chemoattractive response toward the bifurcated end containing an NGF gradient compared to the control, though some neurites were found in the end with no NGF gradient. Significance. The integrated model of neurite growth we describe will allow comparison of experimental studies against growth cone guidance computational models applied to axon pathfinding at choice points.

Preliminary characterization of persisting circadian rhythms during space flight: Neurospora as a model system

NASA Technical Reports Server (NTRS)

Sulzman, F. W.

1981-01-01

The effects of the Spacelab environment on the circadian rhythms in microorganisms are investigated. Neurospora is chosen because of its well characterized circadian rhythm of growth. Growth rate, banding patterns, and circadian period and phase information are studied.

Electrical System Technology Working Group (WG) Report

NASA Technical Reports Server (NTRS)

Silverman, S.; Ford, F. E.

1984-01-01

The technology needs for space power systems (military, public, commercial) were assessed for the period 1995 to 2005 in the area of power management and distribution, components, circuits, subsystems, controls and autonomy, modeling and simulation. There was general agreement that the military requirements for pulse power would be the dominant factor in the growth of power systems. However, the growth of conventional power to the 100 to 250kw range would be in the public sector, with low Earth orbit needs being the driver toward large 100kw systems. An overall philosophy for large power system development is also described.

Thermal analysis of the vertical bridgman semiconductor crystal growth technique. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Jasinski, T. J.

1982-01-01

The quality of semiconductor crystals grown by the vertical Bridgman technique is strongly influenced by the axial and radial variations of temperature within the charge. The relationship between the thermal parameters of the vertical Bridgman system and the thermal behavior of the charge are examined. Thermal models are developed which are capable of producing results expressable in analytical form and which can be used without recourse to extensive computer work for the preliminary thermal design of vertical Bridgman crystal growth systems. These models include the effects of thermal coupling between the furnace and the charge, charge translation rate, charge diameter, thickness and thermal conductivity of the confining crucible, thermal conductivity change and liberation of latent heat at the growth interface, and infinite charge length. The hot and cold zone regions, considered to be at spatially uniform temperatures, are separated by a gradient control region which provides added thermal design flexibility for controlling the temperature variations near the growth interface.

Interface dynamics and crystal phase switching in GaAs nanowires

NASA Astrophysics Data System (ADS)

Jacobsson, Daniel; Panciera, Federico; Tersoff, Jerry; Reuter, Mark C.; Lehmann, Sebastian; Hofmann, Stephan; Dick, Kimberly A.; Ross, Frances M.

2016-03-01

Controlled formation of non-equilibrium crystal structures is one of the most important challenges in crystal growth. Catalytically grown nanowires are ideal systems for studying the fundamental physics of phase selection, and could lead to new electronic applications based on the engineering of crystal phases. Here we image gallium arsenide (GaAs) nanowires during growth as they switch between phases as a result of varying growth conditions. We find clear differences between the growth dynamics of the phases, including differences in interface morphology, step flow and catalyst geometry. We explain these differences, and the phase selection, using a model that relates the catalyst volume, the contact angle at the trijunction (the point at which solid, liquid and vapour meet) and the nucleation site of each new layer of GaAs. This model allows us to predict the conditions under which each phase should be observed, and use these predictions to design GaAs heterostructures. These results could apply to phase selection in other nanowire systems.

Interface dynamics and crystal phase switching in GaAs nanowires.

PubMed

Jacobsson, Daniel; Panciera, Federico; Tersoff, Jerry; Reuter, Mark C; Lehmann, Sebastian; Hofmann, Stephan; Dick, Kimberly A; Ross, Frances M

2016-03-17

Controlled formation of non-equilibrium crystal structures is one of the most important challenges in crystal growth. Catalytically grown nanowires are ideal systems for studying the fundamental physics of phase selection, and could lead to new electronic applications based on the engineering of crystal phases. Here we image gallium arsenide (GaAs) nanowires during growth as they switch between phases as a result of varying growth conditions. We find clear differences between the growth dynamics of the phases, including differences in interface morphology, step flow and catalyst geometry. We explain these differences, and the phase selection, using a model that relates the catalyst volume, the contact angle at the trijunction (the point at which solid, liquid and vapour meet) and the nucleation site of each new layer of GaAs. This model allows us to predict the conditions under which each phase should be observed, and use these predictions to design GaAs heterostructures. These results could apply to phase selection in other nanowire systems.

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

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

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

Simulation of the dc Plasma in Carbon Nanotube Growth

NASA Technical Reports Server (NTRS)

Hash, David; Bose, Deepak; Govindan, T. R.; Meyyappan, M.; Biegel, Bryan (Technical Monitor)

2003-01-01

A model for the dc plasma used in carbon nanotube growth is presented, and one-dimensional simulations of an acetylene/ammonia/argon system are performed. The effect of dc bias is illustrated by examining electron temperature, electron and ion densities, and neutral densities. Introducing a tungsten filament in the dc plasma, as in hot filament chemical vapor deposition with plasma assistance, shows negligible influence on the system characteristics.

Accumulation of Biomass and Mineral Elements with Calendar Time by Corn: Application of the Expanded Growth Model

PubMed Central

Overman, Allen R.; Scholtz, Richard V.

2011-01-01

The expanded growth model is developed to describe accumulation of plant biomass (Mg ha−1) and mineral elements (kg ha−1) in with calendar time (wk). Accumulation of plant biomass with calendar time occurs as a result of photosynthesis for green land-based plants. A corresponding accumulation of mineral elements such as nitrogen, phosphorus, and potassium occurs from the soil through plant roots. In this analysis, the expanded growth model is tested against high quality, published data on corn (Zea mays L.) growth. Data from a field study in South Carolina was used to evaluate the application of the model, where the planting time of April 2 in the field study maximized the capture of solar energy for biomass production. The growth model predicts a simple linear relationship between biomass yield and the growth quantifier, which is confirmed with the data. The growth quantifier incorporates the unit processes of distribution of solar energy which drives biomass accumulation by photosynthesis, partitioning of biomass between light-gathering and structural components of the plants, and an aging function. A hyperbolic relationship between plant nutrient uptake and biomass yield is assumed, and is confirmed for the mineral elements nitrogen (N), phosphorus (P), and potassium (K). It is concluded that the rate limiting process in the system is biomass accumulation by photosynthesis and that nutrient accumulation occurs in virtual equilibrium with biomass accumulation. PMID:22194842

Phase field models for heterogeneous nucleation: Application to inoculation in alpha-solidifying Ti-Al-B alloys

NASA Astrophysics Data System (ADS)

Apel, M.; Eiken, J.; Hecht, U.

2014-02-01

This paper aims at briefly reviewing phase field models applied to the simulation of heterogeneous nucleation and subsequent growth, with special emphasis on grain refinement by inoculation. The spherical cap and free growth model (e.g. A.L. Greer, et al., Acta Mater. 48, 2823 (2000)) has proven its applicability for different metallic systems, e.g. Al or Mg based alloys, by computing the grain refinement effect achieved by inoculation of the melt with inert seeding particles. However, recent experiments with peritectic Ti-Al-B alloys revealed that the grain refinement by TiB2 is less effective than predicted by the model. Phase field simulations can be applied to validate the approximations of the spherical cap and free growth model, e.g. by computing explicitly the latent heat release associated with different nucleation and growth scenarios. Here, simulation results for point-shaped nucleation, as well as for partially and completely wetted plate-like seed particles will be discussed with respect to recalescence and impact on grain refinement. It will be shown that particularly for large seeding particles (up to 30 μm), the free growth morphology clearly deviates from the assumed spherical cap and the initial growth - until the free growth barrier is reached - significantly contributes to the latent heat release and determines the recalescence temperature.

A combined model of human erythropoiesis and granulopoiesis under growth factor and chemotherapy treatment

PubMed Central

2014-01-01

Background Haematotoxicity of conventional chemotherapies often results in delays of treatment or reduction of chemotherapy dose. To ameliorate these side-effects, patients are routinely treated with blood transfusions or haematopoietic growth factors such as erythropoietin (EPO) or granulocyte colony-stimulating factor (G-CSF). For the latter ones, pharmaceutical derivatives are available, which differ in absorption kinetics, pharmacokinetic and -dynamic properties. Due to the complex interaction of cytotoxic effects of chemotherapy and the stimulating effects of different growth factor derivatives, optimal treatment is a non-trivial task. In the past, we developed mathematical models of thrombopoiesis, granulopoiesis and erythropoiesis under chemotherapy and growth-factor applications which can be used to perform clinically relevant predictions regarding the feasibility of chemotherapy schedules and cytopenia prophylaxis with haematopoietic growth factors. However, interactions of lineages and growth-factors were ignored so far. Results To close this gap, we constructed a hybrid model of human granulopoiesis and erythropoiesis under conventional chemotherapy, G-CSF and EPO applications. This was achieved by combining our single lineage models of human erythropoiesis and granulopoiesis with a common stem cell model. G-CSF effects on erythropoiesis were also implemented. Pharmacodynamic models are based on ordinary differential equations describing proliferation and maturation of haematopoietic cells. The system is regulated by feedback loops partly mediated by endogenous and exogenous EPO and G-CSF. Chemotherapy is modelled by depletion of cells. Unknown model parameters were determined by fitting the model predictions to time series data of blood counts and cytokine profiles. Data were extracted from literature or received from cooperating clinical study groups. Our model explains dynamics of mature blood cells and cytokines after growth-factor applications in healthy volunteers. Moreover, we modelled 15 different chemotherapeutic drugs by estimating their bone marrow toxicity. Taking into account different growth-factor schedules, this adds up to 33 different chemotherapy regimens explained by the model. Conclusions We conclude that we established a comprehensive biomathematical model to explain the dynamics of granulopoiesis and erythropoiesis under combined chemotherapy, G-CSF, and EPO applications. We demonstrate how it can be used to make predictions regarding haematotoxicity of yet untested chemotherapy and growth-factor schedules. PMID:24886056

Water Temperature, Invertebrate Drift, and the Scope for Growth for Juvenile Spring Chinook Salmon.

NASA Astrophysics Data System (ADS)

Lovtang, J. C.; Li, H. W.

2005-05-01

We present a bioenergetic assessment of habitat quality based on the concept of the scope for growth for juvenile Chinook salmon. Growth of juvenile salmonids during the freshwater phase of their life history depends on a balance between two main factors: energy intake and metabolic costs. The metabolic demands of temperature and the availability of food play integral roles in determining the scope for growth of juvenile salmonids in stream systems. We investigated differences in size of juvenile spring Chinook salmon in relation to water temperature and invertebrate drift density in six unique study reaches in the Metolius River Basin, a tributary of the Deschutes River in Central Oregon. This project was initiated to determine the relative quality and potential productivity of habitat in the Metolius Basin prior to the reintroduction of spring Chinook salmon, which were extirpated from the middle Deschutes basin in the early 1970's due to the construction of a hydroelectric dam. Variations in the growth of juvenile Chinook salmon can be described using a multiple regression model of water temperature and invertebrate drift density. We also discuss the relationships between our bioenergetic model, variations of the ideal free distribution model, and physiological growth models.

Vertically aligned GaAs nanowires on graphite and few-layer graphene: generic model and epitaxial growth.

PubMed

Munshi, A Mazid; Dheeraj, Dasa L; Fauske, Vidar T; Kim, Dong-Chul; van Helvoort, Antonius T J; Fimland, Bjørn-Ove; Weman, Helge

2012-09-12

By utilizing the reduced contact area of nanowires, we show that epitaxial growth of a broad range of semiconductors on graphene can in principle be achieved. A generic atomic model is presented which describes the epitaxial growth configurations applicable to all conventional semiconductor materials. The model is experimentally verified by demonstrating the growth of vertically aligned GaAs nanowires on graphite and few-layer graphene by the self-catalyzed vapor-liquid-solid technique using molecular beam epitaxy. A two-temperature growth strategy was used to increase the nanowire density. Due to the self-catalyzed growth technique used, the nanowires were found to have a regular hexagonal cross-sectional shape, and are uniform in length and diameter. Electron microscopy studies reveal an epitaxial relationship of the grown nanowires with the underlying graphitic substrates. Two relative orientations of the nanowire side-facets were observed, which is well explained by the proposed atomic model. A prototype of a single GaAs nanowire photodetector demonstrates a high-quality material. With GaAs being a model system, as well as a very useful material for various optoelectronic applications, we anticipate this particular GaAs nanowire/graphene hybrid to be promising for flexible and low-cost solar cells.

User's guide to the stand-damage model: a component of the gypsy moth life system model

Treesearch

J. J. Colbert; George Racin

1995-01-01

The Stand-Damage Model (a component of the Gypsy Moth Life System Model) simulates the growth of a mixed hardwood forest and incorporates the effects of defoliation by gypsy moth or tree harvesting as prescribed by the user. It can be used to assess the damage from expected defoliation, view the differences between various degrees of defoliation, and describe the...

Multiscale Systems Analysis of Root Growth and Development: Modeling Beyond the Network and Cellular Scales

PubMed Central

Band, Leah R.; Fozard, John A.; Godin, Christophe; Jensen, Oliver E.; Pridmore, Tony; Bennett, Malcolm J.; King, John R.

2012-01-01

Over recent decades, we have gained detailed knowledge of many processes involved in root growth and development. However, with this knowledge come increasing complexity and an increasing need for mechanistic modeling to understand how those individual processes interact. One major challenge is in relating genotypes to phenotypes, requiring us to move beyond the network and cellular scales, to use multiscale modeling to predict emergent dynamics at the tissue and organ levels. In this review, we highlight recent developments in multiscale modeling, illustrating how these are generating new mechanistic insights into the regulation of root growth and development. We consider how these models are motivating new biological data analysis and explore directions for future research. This modeling progress will be crucial as we move from a qualitative to an increasingly quantitative understanding of root biology, generating predictive tools that accelerate the development of improved crop varieties. PMID:23110897

SOYCHMBR.I - A model designed for the study of plant growth in a closed chamber

NASA Technical Reports Server (NTRS)

Reinhold, C.

1982-01-01

The analytical model SOYCHMBER.I, an update and alteration of the SOYMOD/OARDC model, for describing the total processes experienced by a plant in a controlled mass environment is outlined. The model is intended for use with growth chambers for examining plant growth in a completely controlled environment, leading toward a data base for the design of spacecraft food supply systems. SOYCHMBER.I accounts for the assimilation, respiration, and partitioning of photosynthate and nitrogen compounds among leaves, stems, roots, and potentially, flowers of the soybean plant. The derivation of the governing equations is traced, and the results of the prediction of CO2 dynamics for a seven day experiment with rice in a closed chamber are reported, together with data from three model runs for soybean. It is concluded that the model needs expansion to account for factors such as relative humidity.

Knowledge representation to support reasoning based on multiple models

NASA Technical Reports Server (NTRS)

Gillam, April; Seidel, Jorge P.; Parker, Alice C.

1990-01-01

Model Based Reasoning is a powerful tool used to design and analyze systems, which are often composed of numerous interactive, interrelated subsystems. Models of the subsystems are written independently and may be used together while they are still under development. Thus the models are not static. They evolve as information becomes obsolete, as improved artifact descriptions are developed, and as system capabilities change. Researchers are using three methods to support knowledge/data base growth, to track the model evolution, and to handle knowledge from diverse domains. First, the representation methodology is based on having pools, or types, of knowledge from which each model is constructed. In addition information is explicit. This includes the interactions between components, the description of the artifact structure, and the constraints and limitations of the models. The third principle we have followed is the separation of the data and knowledge from the inferencing and equation solving mechanisms. This methodology is used in two distinct knowledge-based systems: one for the design of space systems and another for the synthesis of VLSI circuits. It has facilitated the growth and evolution of our models, made accountability of results explicit, and provided credibility for the user community. These capabilities have been implemented and are being used in actual design projects.

On a nonlocal reaction-diffusion-advection system modelling the growth of phytoplankton with cell quota structure

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.

Modeling Global Spatial-Temporal Evolution of Society: Hyperbolic Growth and Historical Cycles

NASA Astrophysics Data System (ADS)

Kurkina, E. S.

2011-09-01

The global historical processes are under consideration; and laws of global evolution of the world community are studied. The world community is considered as a united complex self-developing and self-organizing system. It supposed that the main driving force of social-economical evolution was the positive feedback between the population size and the level of technological development, which was a cause of growth in blow-up regime both of population and of global economic indexes. The study is supported by the results of mathematical modeling founded on a nonlinear heat equation with a source. Every social-economical epoch characterizes by own specific spatial distributed structures. So the global dynamics of world community during the whole history is investigated throughout the prism of the developing of spatial-temporal structures. The model parameters have been chosen so that 1) total population follows stable hyperbolic growth, consistently with the demographic data; 2) the evolution of the World-System goes through 11 stages corresponding to the main historical epochs.

Environment-dependent morphology in plasmodium of true slime mold Physarum polycephalum and a network growth model.

PubMed

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.

System dynamic modelling of industrial growth and landscape ecology in China.

PubMed

Xu, Jian; Kang, Jian; Shao, Long; Zhao, Tianyu

2015-09-15

With the rapid development of large industrial corridors in China, the landscape ecology of the country is currently being affected. Therefore, in this study, a system dynamic model with multi-dimensional nonlinear dynamic prediction function that considers industrial growth and landscape ecology is developed and verified to allow for more sustainable development. Firstly, relationships between industrial development and landscape ecology in China are examined, and five subsystems are then established: industry, population, urban economy, environment and landscape ecology. The main influencing factors are then examined for each subsystem to establish flow charts connecting those factors. Consequently, by connecting the subsystems, an overall industry growth and landscape ecology model is established. Using actual data and landscape index calculated based on GIS of the Ha-Da-Qi industrial corridor, a typical industrial corridor in China, over the period 2005-2009, the model is validated in terms of historical behaviour, logical structure and future prediction, where for 84.8% of the factors, the error rate of the model is less than 5%, the mean error rate of all factors is 2.96% and the error of the simulation test for the landscape ecology subsystem is less than 2%. Moreover, a model application has been made to consider the changes in landscape indices under four industrial development modes, and the optimal industrial growth plan has been examined for landscape ecological protection through the simulation prediction results over 2015-2020. Copyright © 2015 Elsevier Ltd. All rights reserved.

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

NASA Astrophysics Data System (ADS)

Zhao, Yaolong; Zhao, Junsan; Murayama, Yuji

2008-10-01

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

The influence of working memory on reading growth in subgroups of children with reading disabilities.

PubMed

Swanson, H Lee; Jerman, Olga

2007-04-01

This 3-year longitudinal study determined whether (a) subgroups of children with reading disabilities (RD) (children with RD only, children with both reading and arithmetic deficits, and low verbal IQ readers) and skilled readers varied in working memory (WM) and short-term memory (STM) growth and (b) whether growth in an executive system and/or a phonological storage system mediated growth in reading performance. A battery of memory and reading measures was administered to 84 children (11-17 years of age) across three testing waves spaced 1 year apart. The results showed that skilled readers yielded higher WM growth estimates than did the RD groups. No significant differentiation among subgroups of children with RD on growth measures emerged. Hierarchical linear modeling showed that WM (controlled attention), rather than STM (phonological loop), was related to growth in reading comprehension and reading fluency. The results support the notion that deficient growth in the executive component of WM underlies RD.

Molecular Physiology of Root System Architecture in Model Grasses

NASA Astrophysics Data System (ADS)

Hixson, K.; Ahkami, A. H.; Anderton, C.; Veličković, D.; Myers, G. L.; Chrisler, W.; Lindenmaier, R.; Fang, Y.; Yabusaki, S.; Rosnow, J. J.; Farris, Y.; Khan, N. E.; Bernstein, H. C.; Jansson, C.

2017-12-01

Unraveling the molecular and physiological mechanisms involved in responses of Root System Architecture (RSA) to abiotic stresses and shifts in microbiome structure is critical to understand and engineer plant-microbe-soil interactions in the rhizosphere. In this study, accessions of Brachypodium distachyon Bd21 (C3 model grass) and Setaria viridis A10.1 (C4 model grass) were grown in phytotron chambers under current and elevated CO2 levels. Detailed growth stage-based phenotypic analysis revealed different above- and below-ground morphological and physiological responses in C3 and C4 grasses to enhanced CO2 levels. Based on our preliminary results and by screening values of total biomass, water use efficiency, root to shoot ratio, RSA parameters and net assimilation rates, we postulated a three-phase physiological mechanism, i.e. RootPlus, BiomassPlus and YieldPlus phases, for grass growth under elevated CO2 conditions. Moreover, this comprehensive set of morphological and process-based observations are currently in use to develop, test, and calibrate biophysical whole-plant models and in particular to simulate leaf-level photosynthesis at various developmental stages of C3 and C4 using the model BioCro. To further link the observed phenotypic traits at the organismal level to tissue and molecular levels, and to spatially resolve the origin and fate of key metabolites involved in primary carbohydrate metabolism in different root sections, we complement root phenotypic observations with spatial metabolomics data using mass spectrometry imaging (MSI) methods. Focusing on plant-microbe interactions in the rhizosphere, six bacterial strains with plant growth promoting features are currently in use in both gel-based and soil systems to screen root growth and development in Brachypodium. Using confocal microscopy, GFP-tagged bacterial systems are utilized to study the initiation of different root types of RSA, including primary root (PR), coleoptile node axile root (CNR) and leaf node axile root (LNR) during developmental stages of root formation. The root exudates also will be quantified and preliminary data will be used to engineer our microbial consortium to improve plant growth.

Reliability-based management of buried pipelines considering external corrosion defects

NASA Astrophysics Data System (ADS)

Miran, Seyedeh Azadeh

Corrosion is one of the main deteriorating mechanisms that degrade the energy pipeline integrity, due to transferring corrosive fluid or gas and interacting with corrosive environment. Corrosion defects are usually detected by periodical inspections using in-line inspection (ILI) methods. In order to ensure pipeline safety, this study develops a cost-effective maintenance strategy that consists of three aspects: corrosion growth model development using ILI data, time-dependent performance evaluation, and optimal inspection interval determination. In particular, the proposed study is applied to a cathodic protected buried steel pipeline located in Mexico. First, time-dependent power-law formulation is adopted to probabilistically characterize growth of the maximum depth and length of the external corrosion defects. Dependency between defect depth and length are considered in the model development and generation of the corrosion defects over time is characterized by the homogenous Poisson process. The growth models unknown parameters are evaluated based on the ILI data through the Bayesian updating method with Markov Chain Monte Carlo (MCMC) simulation technique. The proposed corrosion growth models can be used when either matched or non-matched defects are available, and have ability to consider newly generated defects since last inspection. Results of this part of study show that both depth and length growth models can predict damage quantities reasonably well and a strong correlation between defect depth and length is found. Next, time-dependent system failure probabilities are evaluated using developed corrosion growth models considering prevailing uncertainties where three failure modes, namely small leak, large leak and rupture are considered. Performance of the pipeline is evaluated through failure probability per km (or called a sub-system) where each subsystem is considered as a series system of detected and newly generated defects within that sub-system. Sensitivity analysis is also performed to determine to which incorporated parameter(s) in the growth models reliability of the studied pipeline is most sensitive. The reliability analysis results suggest that newly generated defects should be considered in calculating failure probability, especially for prediction of long-term performance of the pipeline and also, impact of the statistical uncertainty in the model parameters is significant that should be considered in the reliability analysis. Finally, with the evaluated time-dependent failure probabilities, a life cycle-cost analysis is conducted to determine optimal inspection interval of studied pipeline. The expected total life-cycle costs consists construction cost and expected costs of inspections, repair, and failure. The repair is conducted when failure probability from any described failure mode exceeds pre-defined probability threshold after each inspection. Moreover, this study also investigates impact of repair threshold values and unit costs of inspection and failure on the expected total life-cycle cost and optimal inspection interval through a parametric study. The analysis suggests that a smaller inspection interval leads to higher inspection costs, but can lower failure cost and also repair cost is less significant compared to inspection and failure costs.

Magnetic islands modelled by a phase-field-crystal approach

NASA Astrophysics Data System (ADS)

Faghihi, Niloufar; Mkhonta, Simiso; Elder, Ken R.; Grant, Martin

2018-03-01

Using a minimal model based on the phase-field-crystal formalism, we study the coupling between the density and magnetization in ferromagnetic solids. Analytical calculations for the square phase in two dimensions are presented and the small deformation properties of the system are examined. Furthermore, numerical simulations are conducted to study the influence of an external magnetic field on various phase transitions, the anisotropic properties of the free energy functional, and the scaling behaviour of the growth of the magnetic domains in a crystalline solid. It is shown that the energy of the system can depend on the direction of the magnetic moments, with respect to the crystalline direction. Furthermore, the growth of the magnetic domains in a crystalline solid is studied and is shown that the growth of domains is in agreement with expected behaviour.

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

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

Growth in terrestrial gross primary production (GPP) may provide a feedback for climate change, but there is still strong disagreement on the extent to which biogeochemical processes may suppress this GPP growth at the ecosystem to continental scales. The consequent uncertainty in modeling of future carbon storage by the terrestrial biosphere constitutes one of the largest unknowns in global climate projections for the next century. Here we provide a global, measurement-based estimate of historical GPP growth using long-term atmospheric carbonyl sulfide (COS) records derived from ice core, firn, and ambient air samples. We interpret these records using a model thatmore » relates changes in the COS concentration to changes in its sources and sinks, the largest of which is proportional to GPP. The COS history was most consistent with simulations that assume a large historical GPP growth. Carbon-climate models that assume little to no GPP growth predicted trajectories of COS concentration over the anthropogenic era that differ from those observed. Continued COS monitoring may be useful for detecting ongoing changes in GPP while extending the ice core record to glacial cycles could provide further opportunities to evaluate earth system models.« less

Prey-producing predators: the ecology of human intensification.

PubMed

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.

Dependence of growth of the phases of multiphase binary systems on the diffusion parameters

NASA Astrophysics Data System (ADS)

Molokhina, L. A.; Rogalin, V. E.; Filin, S. A.; Kaplunov, I. A.

2017-12-01

A mathematical model of the diffusion interaction of a binary system with several phases on the equilibrium phase diagram is presented. The theoretical and calculated dependences of the layer thickness of each phase in the multiphase diffusion zone on the isothermal annealing time and the ratio of the diffusion parameters in the neighboring phases with an unlimited supply of both components were constructed. The phase formation and growth in the diffusion zone during "reactive" diffusion corresponds to the equilibrium state diagram for two components, and the order of their appearance in the diffusion zone depends only on the ratio of the diffusion parameters in the phases themselves and on the duration of the incubation periods. The dependence of phase appearance on the incubation periods, annealing time, and difference in the movement rates of the components across the interface boundaries was obtained. An example of the application of the model for processing the experimental data on phase growth in a two-component three-phase system was given.

Morphological phase diagrams of C60 and C70 films on graphite

NASA Astrophysics Data System (ADS)

Sato, Kazuma; Tanaka, Tomoyasu; Akaike, Kouki; Kanai, Kaname

2017-10-01

The morphologies of C60 and C70 fullerene films vacuum-deposited onto graphite at various deposition rates and grown at several temperatures were investigated using atomic force microscopy. These fullerene films on graphite are model systems of physisorption of organic molecules that likely exhibit little chemical interaction with the graphite's surface. The morphologies of C60 and C70 films grown on graphite can be understood well from growth models previously reported. Comparison of the morphological phase diagrams obtained for C60 and C70 indicate that the diffusion properties of the adsorbed molecule are key in determining the morphology of the obtained film. The low diffusion rate of C70 resulted in various film morphologies for all deposition conditions tested. Also, the obtained phase diagrams can be understood by the results of fractal dimension analysis on the C60 and C70 islands. The fundamental understanding of film growth obtained using these ideal physisorption systems will aid in understanding film growth by other molecular adsorption systems.

Modelling the interaction between flooding events and economic growth

NASA Astrophysics Data System (ADS)

Grames, J.; Prskawetz, A.; Grass, D.; Blöschl, G.

2015-06-01

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

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

PubMed

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

2011-07-01

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

Segregation effects during solidification in weightless melts. [effects of evaporation and solidification on crystalization

NASA Technical Reports Server (NTRS)

Li, C.

1975-01-01

Computer programs are developed and used in the study of the combined effects of evaporation and solidification in space processing. The temperature and solute concentration profiles during directional solidification of binary alloys with surface evaporation were mathematically formulated. Computer results are included along with an econotechnical model of crystal growth. This model allows: prediction of crystal size, quality, and cost; systematic selection of the best growth equipment or alloy system; optimization of growth or material parameters; and a maximization of zero-gravity effects. Segregation in GaAs crystals was examined along with vibration effects on GaAs crystal growth. It was found that a unique segregation pattern and strong convention currents exist in GaAs crystal growth. Some beneficial effects from vibration during GaAs growth were discovered. The implications of the results in space processing are indicated.

Transparent metal model study of the use of a cellular growth front to form aligned monotectic composite materials

NASA Technical Reports Server (NTRS)

Kaukler, William F.

1988-01-01

The purpose of this work was to resolve a scientific controversy in the understanding of how second phase particles become aligned during unidirectional growth of a monotectic alloy. A second aspect was to make the first systematic observations of the solidification behavior of a monotectic alloy during cellular growth in-situ. This research provides the first systematic transparent model study of cellular solidification. An interface stability diagram was developed for the planar to cellular transition of the succinonitrile glycerol (SNG) system. A method was developed utilizing Fourier Transform Infrared Spectroscopy which allows quantitative compositional analysis of directionally solidified SNG along the growth axis. To determine the influence of cellular growth front on alignment for directionally solidified monotectic alloys, the planar and cellular growth morphology was observed in-situ for SNG between 8 and 17 percent glycerol and for a range of over two orders of magnitude G/R.

Physcomitrella patens: a model for tip cell growth and differentiation.

PubMed

Vidali, Luis; Bezanilla, Magdalena

2012-12-01

The moss Physcomitrella patens has emerged as an excellent model system owing to its amenability to reverse genetics. The moss gametophyte has three filamentous tissues that grow by tip growth: chloronemata, caulonemata, and rhizoids. Because establishment of the moss plant relies on this form of growth, it is particularly suited for dissecting the molecular basis of tip growth. Recent studies demonstrate that a core set of actin cytoskeletal proteins is essential for tip growth. Additional actin cytoskeletal components are required for modulating growth to produce caulonemata and rhizoids. Differentiation into these cell types has previously been linked to auxin, light and nutrients. Recent studies have identified that core auxin signaling components as well as transcription factors that respond to auxin or nutrient levels are required for tip-growing cell differentiation. Future studies may establish a connection between the actin cytoskeleton and auxin or nutrient-induced cell differentiation. Copyright © 2012 Elsevier Ltd. All rights reserved.

Markov Modeling of Component Fault Growth over a Derived Domain of Feasible Output Control Effort Modifications

NASA Technical Reports Server (NTRS)

Bole, Brian; Goebel, Kai; Vachtsevanos, George

2012-01-01

This paper introduces a novel Markov process formulation of stochastic fault growth modeling, in order to facilitate the development and analysis of prognostics-based control adaptation. A metric representing the relative deviation between the nominal output of a system and the net output that is actually enacted by an implemented prognostics-based control routine, will be used to define the action space of the formulated Markov process. The state space of the Markov process will be defined in terms of an abstracted metric representing the relative health remaining in each of the system s components. The proposed formulation of component fault dynamics will conveniently relate feasible system output performance modifications to predictions of future component health deterioration.

Early warning signal for interior crises in excitable systems.

PubMed

Karnatak, Rajat; Kantz, Holger; Bialonski, Stephan

2017-10-01

The ability to reliably predict critical transitions in dynamical systems is a long-standing goal of diverse scientific communities. Previous work focused on early warning signals related to local bifurcations (critical slowing down) and nonbifurcation-type transitions. We extend this toolbox and report on a characteristic scaling behavior (critical attractor growth) which is indicative of an impending global bifurcation, an interior crisis in excitable systems. We demonstrate our early warning signal in a conceptual climate model as well as in a model of coupled neurons known to exhibit extreme events. We observed critical attractor growth prior to interior crises of chaotic as well as strange-nonchaotic attractors. These observations promise to extend the classes of transitions that can be predicted via early warning signals.

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

PubMed

Kareva, Irina; Karev, Georgy

2018-01-01

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

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

PubMed

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

2016-10-15

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

Optimizing amorphous indium zinc oxide film growth for low residual stress and high electrical conductivity

NASA Astrophysics Data System (ADS)

Kumar, Mukesh; Sigdel, A. K.; Gennett, T.; Berry, J. J.; Perkins, J. D.; Ginley, D. S.; Packard, C. E.

2013-10-01

With recent advances in flexible electronics, there is a growing need for transparent conductors with optimum conductivity tailored to the application and nearly zero residual stress to ensure mechanical reliability. Within amorphous transparent conducting oxide (TCO) systems, a variety of sputter growth parameters have been shown to separately impact film stress and optoelectronic properties due to the complex nature of the deposition process. We apply a statistical design of experiments (DOE) approach to identify growth parameter-material property relationships in amorphous indium zinc oxide (a-IZO) thin films and observed large, compressive residual stresses in films grown under conditions typically used for the deposition of highly conductive samples. Power, growth pressure, oxygen partial pressure, and RF power ratio (RF/(RF + DC)) were varied according to a full-factorial test matrix and each film was characterized. The resulting regression model and analysis of variance (ANOVA) revealed significant contributions to the residual stress from individual growth parameters as well as interactions of different growth parameters, but no conditions were found within the initial growth space that simultaneously produced low residual stress and high electrical conductivity. Extrapolation of the model results to lower oxygen partial pressures, combined with prior knowledge of conductivity-growth parameter relationships in the IZO system, allowed the selection of two promising growth conditions that were both empirically verified to achieve nearly zero residual stress and electrical conductivities >1480 S/cm. This work shows that a-IZO can be simultaneously optimized for high conductivity and low residual stress.

Simple growth patterns can create complex trajectories for the ontogeny of constitutive chemical defences in seaweeds.

PubMed

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.

Projection of Big Cities Waste Management and Cost Based on Economic and Demographic Factors in Indonesia

NASA Astrophysics Data System (ADS)

Prajati, Gita; Padmi, Tri; Benno Rahardyan, dan

2017-12-01

Nowadays, solid waste management continues to be a major challenge in urban areas, especially in developing country. It is triggered by population growth, economic growth, industrialization and urbanization. Indonesia itselfs categorized into developing country. Indonesia's government has many program in order to increase the economic growth. One of them is MP3EI (Masterplan Percepatan dan Perluasan Pembangunan Ekonomi Indonesia. This program should be suppported by right waste management system. If Indonesia's waste management system can't afford the economic growth, it will trigger health and environmental problems. This study's purpose is to develop the socio-economic-environment model that can be used as a basis planning for the facility and cost of waste management systems. In this paper we used the development of Khajuria model test method. This method used six variables, which are GDP, population, population density, illiteracy, school's period and economic growth. The result showed that development of Khajuria test could explained the influence of economic and demographic factors to waste generation, 65.6%. The projection of waste generation shows that Pangkalpinang, Pekanbaru and Serang are the cities with the highest waste generation for the next five years. The number of dump truck and TPS in DKI Jakarata is the highest within another city, which is 39.37%. For the next five years, the waste management system in our study areas cost maximum 0.8% from GDP (Gross Domestic Products).

A novel 3-dimensional culture system uncovers growth stimulatory actions by TGFβ in pancreatic cancer cells.

PubMed

Sempere, Lorenzo F; Gunn, Jason R; Korc, Murray

2011-08-01

Transforming Growth Factor-β (TGF-β) exerts cell type-specific and context-dependent effects. Understanding the intrinsic effects of TGF-β on cancer cells in pancreatic ductal adenocarcinoma (PDAC) is a prerequisite for rationalized clinical implementation of TGF-β targeting therapies. Since the tumor microenvironment can affect how cancer cell respond to TGF-β, we employed a novel three-dimensional (3D) culturing system to recapitulate stromal and extracellular matrix interactions. We show here that TGF-β stimulates growth of human and murine pancreatic cancer cell lines (PCCs) when embedded in a 3% collagen IV/laminin-rich gelatinous medium (Matrigel™) over a solidified layer of soft agar. Moreover, in this novel 3D model, concomitant treatment with TGF-β1 and epidermal growth factor (EGF) enhanced PCC growth to a greater extent than either growth factor alone, and conferred increased chemoresistance to cytotoxic compounds. These cooperative growth-stimulatory effects were blocked by pharmacological inhibition of TGF-β type I receptor with SB431542 or the EGF receptor with erlotinib. Co-incubation with SB431542 and erlotinib enhanced the efficacy of gemcitabine and cisplatin in PCCs and in primary cell cultures established from pancreata of genetically-engineered mouse models of PDAC. These findings suggest that concomitant inhibition of TGF-β and EGF signaling may represent an effective therapeutic strategy in PDAC, and that this 3D culturing system could be utilized to test ex vivo the therapeutic response of pancreatic tumor biopsies from PDAC patients, thereby providing a functional assay to facilitate personalized targeted therapies.

Morphogen-based simulation model of ray growth and joint patterning during fin development and regeneration.

PubMed

Rolland-Lagan, Anne-Gaëlle; Paquette, Mathieu; Tweedle, Valerie; Akimenko, Marie-Andrée

2012-03-01

The fact that some organisms are able to regenerate organs of the correct shape and size following amputation is particularly fascinating, but the mechanism by which this occurs remains poorly understood. The zebrafish (Danio rerio) caudal fin has emerged as a model system for the study of bone development and regeneration. The fin comprises 16 to 18 bony rays, each containing multiple joints along its proximodistal axis that give rise to segments. Experimental observations on fin ray growth, regeneration and joint formation have been described, but no unified theory has yet been put forward to explain how growth and joint patterns are controlled. We present a model for the control of fin ray growth during development and regeneration, integrated with a model for joint pattern formation, which is in agreement with published, as well as new, experimental data. We propose that fin ray growth and joint patterning are coordinated through the interaction of three morphogens. When the model is extended to incorporate multiple rays across the fin, it also accounts for how the caudal fin acquires its shape during development, and regains its correct size and shape following amputation.

Novel Multiscale Modeling Tool Applied to Pseudomonas aeruginosa Biofilm Formation

PubMed Central

Biggs, Matthew B.; Papin, Jason A.

2013-01-01

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

Novel multiscale modeling tool applied to Pseudomonas aeruginosa biofilm formation.

PubMed

Biggs, Matthew B; Papin, Jason A

2013-01-01

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

TOPICAL PROBLEMS: The phenomenological theory of world population growth

NASA Astrophysics Data System (ADS)

Kapitza, Sergei P.

1996-01-01

Of all global problems world population growth is the most significant. Demographic data describe this process in a concise and quantitative way in its past and present. Analysing this development it is possible by applying the concepts of systems analysis and synergetics, to work out a mathematical model for a phenomenological description of the global demographic process and to project its trends into the future. Assuming self-similarity as the dynamic principle of development, growth can be described practically over the whole of human history, assuming the growth rate to be proportional to the square of the number of people. The large parameter of the theory and the effective size of a coherent population group is of the order of 105 and the microscopic parameter of the phenomenology is the human lifespan. The demographic transition — a transition to a stabilised world population of some 14 billion in a foreseeable future — is a systemic singularity and is determined by the inherent pattern of growth of an open system, rather than by the lack of resources. The development of a quantitative nonlinear theory of the world population is of interest for interdisciplinary research in anthropology and demography, history and sociology, for population genetics and epidemiology, for studies in evolution of humankind and the origin of man. The model also provides insight into the stability of growth and the present predicament of humankind, and provides a setting for discussing the main global problems.

An Energy-Economy-Environment Model for Simulating the Impacts of Socioeconomic Development on Energy and Environment

PubMed Central

Yao, Bo

2014-01-01

Many rapidly developing regions have begun to draw the attention of the world. Meanwhile, the energy and environmental issues associated with rapid economic growth have aroused widespread critical concern. Therefore, studying energy, economic, and environmental systems is of great importance. This study establishes a system dynamic model that covers multiple aspects of those systems, such as energy, economy, population, water pollution, air pollution, solid waste, and technology. The model designed here attempts to determine the impacts of socioeconomic development on the energy and environment of Tongzhou District in three scenarios: under current, planning, and sustainable conditions. The results reveal that energy shortages and water pollutions are very serious and are the key issues constraining future social and economic development. Solid waste emissions increase with population growth. The prediction results provide valuable insights into social advancement. PMID:24683332

Critical Point in Self-Organized Tissue Growth

NASA Astrophysics Data System (ADS)

Aguilar-Hidalgo, Daniel; Werner, Steffen; Wartlick, Ortrud; González-Gaitán, Marcos; Friedrich, Benjamin M.; Jülicher, Frank

2018-05-01

We present a theory of pattern formation in growing domains inspired by biological examples of tissue development. Gradients of signaling molecules regulate growth, while growth changes these graded chemical patterns by dilution and advection. We identify a critical point of this feedback dynamics, which is characterized by spatially homogeneous growth and proportional scaling of patterns with tissue length. We apply this theory to the biological model system of the developing wing of the fruit fly Drosophila melanogaster and quantitatively identify signatures of the critical point.

The dynamics of hydroponic crops for simulation studies of the CELSS initial reference configurations

NASA Technical Reports Server (NTRS)

Volk, Tyler

1993-01-01

During the past several years, the NASA Program in Controlled Ecological Life Support Systems (CELSS) has continued apace with crop research and logistic, technological, and scientific strides. These include the CELSS Test Facility planned for the space station and its prototype Engineering Development Unit, soon to be active at Ames Research Center (as well as the advanced crop growth research chamber at Ames); the large environmental growth chambers and the planned human test bed facility at Johnson Space Center; the NSCORT at Purdue with new candidate crops and diverse research into the CELSS components; the gas exchange data for soy, potatoes, and wheat from Kennedy Space Center (KSC); and the high-precision gas exchange data for wheat from Utah State University (USU). All these developments, taken together, speak to the need for crop modeling as a means to connect the findings of the crop physiologists with the engineers designing the system. A need also exists for crop modeling to analyze and predict the gas exchange data from the various locations to maximize the scientific yield from the experiments. One fruitful approach employs what has been called the 'energy cascade'. Useful as a basis for CELSS crop growth experimental design, the energy cascade as a generic modeling approach for CELSS crops is a featured accomplishment in this report. The energy cascade is a major tool for linking CELSS crop experiments to the system design. The energy cascade presented here can help collaborations between modelers and crop experimenters to develop the most fruitful experiments for pushing the limits of crop productivity. Furthermore, crop models using the energy cascade provide a natural means to compare, feature for feature, the crop growth components between different CELSS experiments, for example, at Utah State University and Kennedy Space Center.

Assimilation of spatially sparse in situ soil moisture networks into a continuous model domain

USDA-ARS?s Scientific Manuscript database

Growth in the availability of near-real-time soil moisture observations from ground-based networks has spurred interest in the assimilation of these observations into land surface models via a two-dimensional data assimilation system. However, the design of such systems is currently hampered by our ...

Modeling truck traffic volume growth congestion.

DOT National Transportation Integrated Search

2009-05-01

Modeling of the statewide transportation system is an important element in understanding issues and programming of funds to thwart potential congestion. As Alabama grows its manufacturing economy, the number of heavy vehicles traversing its highways ...

Centralised, decentralised or hybrid sanitation systems? Economic evaluation under urban development uncertainty and phased expansion.

PubMed

Roefs, Ivar; Meulman, Brendo; Vreeburg, Jan H G; Spiller, Marc

2017-02-01

Sanitation systems are built to be robust, that is, they are dimensioned to cope with population growth and other variability that occurs throughout their lifetime. It was recently shown that building sanitation systems in phases is more cost effective than one robust design. This phasing can take place by building small autonomous decentralised units that operate closer to the actual demand. Research has shown that variability and uncertainty in urban development does affect the cost effectiveness of this approach. Previous studies do not, however, consider the entire sanitation system from collection to treatment. The aim of this study is to assess the economic performance of three sanitation systems with different scales and systems characteristics under a variety of urban development pathways. Three systems are studied: (I) a centralised conventional activated sludge treatment, (II) a community on site source separation grey water and black water treatment and (III) a hybrid with grey water treatment at neighbourhood scale and black water treatment off site. A modelling approach is taken that combines a simulation of greenfield urban growth, a model of the wastewater collection and treatment infrastructure design properties and a model that translates design parameters into discounted asset lifetime costs. Monte Carlo simulations are used to evaluate the economic performance under uncertain development trends. Results show that the conventional system outperforms both of the other systems when total discounted lifetime costs are assessed, because it benefits from economies of scale. However, when population growth is lower than expected, the source-separated system is more cost effective, because of reduced idle capacity. The hybrid system is not competitive under any circumstance due to the costly double piping and treatment. Copyright © 2016 Elsevier Ltd. All rights reserved.

Developmental programming: the concept, large animal models, and the key role of uteroplacental vascular development.

PubMed

Reynolds, L P; Borowicz, P P; Caton, J S; Vonnahme, K A; Luther, J S; Hammer, C J; Maddock Carlin, K R; Grazul-Bilska, A T; Redmer, D A

2010-04-01

Developmental programming refers to the programming of various bodily systems and processes by a stressor of the maternal system during pregnancy or during the neonatal period. Such stressors include nutritional stress, multiple pregnancy (i.e., increased numbers of fetuses in the gravid uterus), environmental stress (e.g., high environmental temperature, high altitude, prenatal steroid exposure), gynecological immaturity, and maternal or fetal genotype. Programming refers to impaired function of numerous bodily systems or processes, leading to poor growth, altered body composition, metabolic dysfunction, and poor productivity (e.g., poor growth, reproductive dysfunction) of the offspring throughout their lifespan and even across generations. A key component of developmental programming seems to be placental dysfunction, leading to altered fetal growth and development. We discuss various large animal models of developmental programming and how they have and will continue to contribute to our understanding of the mechanisms underlying altered placental function and developmental programming, and, further, how large animal models also will be critical to the identification and application of therapeutic strategies that will alleviate the negative consequences of developmental programming to improve offspring performance in livestock production and human medicine.

The US business cycle: power law scaling for interacting units with complex internal structure

NASA Astrophysics Data System (ADS)

Ormerod, Paul

2002-11-01

In the social sciences, there is increasing evidence of the existence of power law distributions. The distribution of recessions in capitalist economies has recently been shown to follow such a distribution. The preferred explanation for this is self-organised criticality. Gene Stanley and colleagues propose an alternative, namely that power law scaling can arise from the interplay between random multiplicative growth and the complex structure of the units composing the system. This paper offers a parsimonious model of the US business cycle based on similar principles. The business cycle, along with long-term growth, is one of the two features which distinguishes capitalism from all previously existing societies. Yet, economics lacks a satisfactory theory of the cycle. The source of cycles is posited in economic theory to be a series of random shocks which are external to the system. In this model, the cycle is an internal feature of the system, arising from the level of industrial concentration of the agents and the interactions between them. The model-in contrast to existing economic theories of the cycle-accounts for the key features of output growth in the US business cycle in the 20th century.

Modeling salt movement and halophytic crop growth on marginal lands with the APEX model

NASA Astrophysics Data System (ADS)

Goehring, N.; Saito, L.; Verburg, P.; Jeong, J.; Garrett, A.

2016-12-01

Saline soils negatively impact crop productivity in nearly 20% of irrigated agricultural lands worldwide. At these saline sites, cultivation of highly salt-tolerant plants, known as halophytes, may increase productivity compared to conventional salt-sensitive crops (i.e., glycophytes), thereby increasing the economic potential of marginal lands. Through a variety of mechanisms, halophytes are more effective than glycophytes at excluding, accumulating, and secreting salts from their tissues. Each mechanism can have a different impact on the salt balance in the plant-soil-water system. To date, little information is available to understand the long-term impacts of halophyte cultivation on environmental quality. This project utilizes the Agricultural Policy/Environmental Extender (APEX) model, developed by the US Department of Agriculture, to model the growth and production of two halophytic crops. The crops being modeled include quinoa (Chenopodium quinoa), which has utilities for human consumption and forage, and AC Saltlander green wheatgrass (Elymus hoffmannii), which has forage utility. APEX simulates salt movement between soil layers and accounts for the salt balance in the plant-soil-water system, including salinity in irrigation water and crop-specific salt uptake. Key crop growth parameters in APEX are derived from experimental growth data obtained under non-stressed conditions. Data from greenhouse and field experiments in which quinoa and AC Saltlander were grown under various soil salinity and irrigation salinity treatments are being used to parameterize, calibrate, and test the model. This presentation will discuss progress on crop parameterization and completed model runs under different salt-affected soil and irrigation conditions.

Physical principles for DNA tile self-assembly.

PubMed

Evans, Constantine G; Winfree, Erik

2017-06-19

DNA tiles provide a promising technique for assembling structures with nanoscale resolution through self-assembly by basic interactions rather than top-down assembly of individual structures. Tile systems can be programmed to grow based on logical rules, allowing for a small number of tile types to assemble large, complex assemblies that can retain nanoscale resolution. Such algorithmic systems can even assemble different structures using the same tiles, based on inputs that seed the growth. While programming and theoretical analysis of tile self-assembly often makes use of abstract logical models of growth, experimentally implemented systems are governed by nanoscale physical processes that can lead to very different behavior, more accurately modeled by taking into account the thermodynamics and kinetics of tile attachment and detachment in solution. This review discusses the relationships between more abstract and more physically realistic tile assembly models. A central concern is how consideration of model differences enables the design of tile systems that robustly exhibit the desired abstract behavior in realistic physical models and in experimental implementations. Conversely, we identify situations where self-assembly in abstract models can not be well-approximated by physically realistic models, putting constraints on physical relevance of the abstract models. To facilitate the discussion, we introduce a unified model of tile self-assembly that clarifies the relationships between several well-studied models in the literature. Throughout, we highlight open questions regarding the physical principles for DNA tile self-assembly.

Embedded biofilm, a new biofilm model based on the embedded growth of bacteria.

PubMed

Jung, Yong-Gyun; Choi, Jungil; Kim, Soo-Kyoung; Lee, Joon-Hee; Kwon, Sunghoon

2015-01-01

A variety of systems have been developed to study biofilm formation. However, most systems are based on the surface-attached growth of microbes under shear stress. In this study, we designed a microfluidic channel device, called a microfluidic agarose channel (MAC), and found that microbial cells in the MAC system formed an embedded cell aggregative structure (ECAS). ECASs were generated from the embedded growth of bacterial cells in an agarose matrix and better mimicked the clinical environment of biofilms formed within mucus or host tissue under shear-free conditions. ECASs were developed with the production of extracellular polymeric substances (EPS), the most important feature of biofilms, and eventually burst to release planktonic cells, which resembles the full developmental cycle of biofilms. Chemical and genetic effects have also confirmed that ECASs are a type of biofilm. Unlike the conventional biofilms formed in the flow cell model system, this embedded-type biofilm completes the developmental cycle in only 9 to 12 h and can easily be observed with ordinary microscopes. We suggest that ECASs are a type of biofilm and that the MAC is a system for observing biofilm formation. Copyright © 2015, American Society for Microbiology. All Rights Reserved.

Actual measurement, hygrothermal response experiment and growth prediction analysis of microbial contamination of central air conditioning system in Dalian, China

PubMed Central

Lv, Yang; Hu, Guangyao; Wang, Chunyang; Yuan, Wenjie; Wei, Shanshan; Gao, Jiaoqi; Wang, Boyuan; Song, Fangchao

2017-01-01

The microbial contamination of central air conditioning system is one of the important factors that affect the indoor air quality. Actual measurement and analysis were carried out on microbial contamination in central air conditioning system at a venue in Dalian, China. Illumina miseq method was used and three fungal samples of two units were analysed by high throughput sequencing. Results showed that the predominant fungus in air conditioning unit A and B were Candida spp. and Cladosporium spp., and two fungus were further used in the hygrothermal response experiment. Based on the data of Cladosporium in hygrothermal response experiment, this paper used the logistic equation and the Gompertz equation to fit the growth predictive model of Cladosporium genera in different temperature and relative humidity conditions, and the square root model was fitted based on the two environmental factors. In addition, the models were carried on the analysis to verify the accuracy and feasibility of the established model equation. PMID:28367963

Spatiotemporal pattern formation in a prey-predator model under environmental driving forces

NASA Astrophysics Data System (ADS)

Sirohi, Anuj Kumar; Banerjee, Malay; Chakraborti, Anirban

2015-09-01

Many existing studies on pattern formation in the reaction-diffusion systems rely on deterministic models. However, environmental noise is often a major factor which leads to significant changes in the spatiotemporal dynamics. In this paper, we focus on the spatiotemporal patterns produced by the predator-prey model with ratio-dependent functional response and density dependent death rate of predator. We get the reaction-diffusion equations incorporating the self-diffusion terms, corresponding to random movement of the individuals within two dimensional habitats, into the growth equations for the prey and predator population. In order to have the noise added model, small amplitude heterogeneous perturbations to the linear intrinsic growth rates are introduced using uncorrelated Gaussian white noise terms. For the noise added system, we then observe spatial patterns for the parameter values lying outside the Turing instability region. With thorough numerical simulations we characterize the patterns corresponding to Turing and Turing-Hopf domain and study their dependence on different system parameters like noise-intensity, etc.

Actual measurement, hygrothermal response experiment and growth prediction analysis of microbial contamination of central air conditioning system in Dalian, China.

PubMed

Lv, Yang; Hu, Guangyao; Wang, Chunyang; Yuan, Wenjie; Wei, Shanshan; Gao, Jiaoqi; Wang, Boyuan; Song, Fangchao

2017-04-03

The microbial contamination of central air conditioning system is one of the important factors that affect the indoor air quality. Actual measurement and analysis were carried out on microbial contamination in central air conditioning system at a venue in Dalian, China. Illumina miseq method was used and three fungal samples of two units were analysed by high throughput sequencing. Results showed that the predominant fungus in air conditioning unit A and B were Candida spp. and Cladosporium spp., and two fungus were further used in the hygrothermal response experiment. Based on the data of Cladosporium in hygrothermal response experiment, this paper used the logistic equation and the Gompertz equation to fit the growth predictive model of Cladosporium genera in different temperature and relative humidity conditions, and the square root model was fitted based on the two environmental factors. In addition, the models were carried on the analysis to verify the accuracy and feasibility of the established model equation.

Multiscale digital Arabidopsis predicts individual organ and whole-organism growth.

PubMed

Chew, Yin Hoon; Wenden, Bénédicte; Flis, Anna; Mengin, Virginie; Taylor, Jasper; Davey, Christopher L; Tindal, Christopher; Thomas, Howard; Ougham, Helen J; de Reffye, Philippe; Stitt, Mark; Williams, Mathew; Muetzelfeldt, Robert; Halliday, Karen J; Millar, Andrew J

2014-09-30

Understanding how dynamic molecular networks affect whole-organism physiology, analogous to mapping genotype to phenotype, remains a key challenge in biology. Quantitative models that represent processes at multiple scales and link understanding from several research domains can help to tackle this problem. Such integrated models are more common in crop science and ecophysiology than in the research communities that elucidate molecular networks. Several laboratories have modeled particular aspects of growth in Arabidopsis thaliana, but it was unclear whether these existing models could productively be combined. We test this approach by constructing a multiscale model of Arabidopsis rosette growth. Four existing models were integrated with minimal parameter modification (leaf water content and one flowering parameter used measured data). The resulting framework model links genetic regulation and biochemical dynamics to events at the organ and whole-plant levels, helping to understand the combined effects of endogenous and environmental regulators on Arabidopsis growth. The framework model was validated and tested with metabolic, physiological, and biomass data from two laboratories, for five photoperiods, three accessions, and a transgenic line, highlighting the plasticity of plant growth strategies. The model was extended to include stochastic development. Model simulations gave insight into the developmental control of leaf production and provided a quantitative explanation for the pleiotropic developmental phenotype caused by overexpression of miR156, which was an open question. Modular, multiscale models, assembling knowledge from systems biology to ecophysiology, will help to understand and to engineer plant behavior from the genome to the field.

Convergence dynamics and pseudo almost periodicity of a class of nonautonomous RFDEs with applications

NASA Astrophysics Data System (ADS)

Fan, Meng; Ye, Dan

2005-09-01

This paper studies the dynamics of a system of retarded functional differential equations (i.e., RF=Es), which generalize the Hopfield neural network models, the bidirectional associative memory neural networks, the hybrid network models of the cellular neural network type, and some population growth model. Sufficient criteria are established for the globally exponential stability and the existence and uniqueness of pseudo almost periodic solution. The approaches are based on constructing suitable Lyapunov functionals and the well-known Banach contraction mapping principle. The paper ends with some applications of the main results to some neural network models and population growth models and numerical simulations.

Modeling and simulating two cut-to-length harvesting systems in central Appalachian hardwoods

Treesearch

Jingxin Wang; Chris B. LeDoux; Yaoxiang Li

2003-01-01

The production rates and costs of two cut-to-length harvesting systems was simulated using a modular ground-based simulation model and stand yield data from fully stocked, second growth even aged central Appalachian hardwood forests. The two harvesters simulated were a modified John Deere 988 tracked excavator with a model RP 1600 single grip sawhead and an excavator...

Modeling the Growth of Filamentous Fungi at the Particle Scale in Solid-State Fermentation Systems.

PubMed

Sugai-Guérios, Maura Harumi; Balmant, Wellington; Furigo, Agenor; Krieger, Nadia; Mitchell, David Alexander

2015-01-01

Solid-state fermentation (SSF) with filamentous fungi is a promising technique for the production of a range of biotechnological products and has the potential to play an important role in future biorefineries. The performance of such processes is intimately linked with the mycelial mode of growth of these fungi: Not only is the production of extracellular enzymes related to morphological characteristics, but also the mycelium can affect bed properties and, consequently, the efficiency of heat and mass transfer within the bed. A mathematical model that describes the development of the fungal mycelium in SSF systems at the particle scale would be a useful tool for investigating these phenomena, but, as yet, a sufficiently complete model has not been proposed. This review presents the biological and mass transfer phenomena that should be included in such a model and then evaluates how these phenomena have been modeled previously in the SSF and related literature. We conclude that a discrete lattice-based model that uses differential equations to describe the mass balances of the components within the system would be most appropriate and that mathematical expressions for describing the individual phenomena are available in the literature. It remains for these phenomena to be integrated into a complete model describing the development of fungal mycelia in SSF systems.

Modelling the root system architecture of Poaceae. Can we simulate integrated traits from morphological parameters of growth and branching?

PubMed

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.

Proposition of a model elucidating the AlN-on-Si (111) microstructure

NASA Astrophysics Data System (ADS)

Mante, N.; Rennesson, S.; Frayssinet, E.; Largeau, L.; Semond, F.; Rouvière, J. L.; Feuillet, G.; Vennéguès, P.

2018-06-01

AlN-on-Si can be considered as a model system for heteroepitaxial growth of highly mismatched materials. Indeed, AlN and Si drastically differ in terms of chemistry, crystalline structure, and lattice parameters. In this paper, we present a transmission electron microscopy and grazing incidence X-ray diffraction study of the microstructure of AlN layers epitaxially grown on Si (111) by molecular beam epitaxy. The large interfacial energy due to the dissimilarities between AlN and Si results in a 3D Volmer-Weber growth mode with the nucleation of independent and relaxed AlN islands. Despite a well-defined epitaxial relationship, these islands exhibit in-plane misorientations up to 6°-7°. We propose a model which quantitatively explains these misorientations by taking into account the relaxation of the islands through the introduction of 60° a-type misfit dislocations. Threading dislocations (TDs) are formed to compensate these misorientations when islands coalesce. TD density depends on two parameters: the islands' misorientation and density. We show that the former is related to the mismatch between AlN and Si, while the latter depends on the growth parameters. A large decrease in TD density occurs during the 3D growth stage by overlap and overgrowth of highly misoriented islands. On the other hand, the TD density does not change significantly when the growth becomes 2D. The proposed model, explaining the misorientations of 3D-grown islands, may be extended to other (0001)-oriented III-nitrides and more generally to any heteroepitaxial system exhibiting a 3D Volmer-Weber growth mode with islands relaxed thanks to the introduction of mixed-type misfit dislocations.

Traveling Magnetic Field Applications for Vertical Bridgman Growth: Modeling and Experiment

NASA Technical Reports Server (NTRS)

Mazuruk, Konstantin

2004-01-01

Traveling magnetic fields offer a direct control of the metallic melt meridional flow in long cylinders. It induces the Lorentz body force that can counteract with the buoyancy force induced by radial temperature non-uniformity. It can significantly offset a natural convection in the system, or it can even set up the flow in opposite direction, thus affecting the interface shape, the growth rate and macrosegregation. Results of our numerical modeling of the Vertical Bridgman crystal growth of InSb will be discussed. The experimental part of this investigation will address the effect of the applied traveling magnetic fields on the interface shape of InSb crystals. Specifics of the growth apparatus design for this research will be provided in details.

The relationship between leaf area growth and biomass accumulation in Arabidopsis thaliana

PubMed Central

Weraduwage, Sarathi M.; Chen, Jin; Anozie, Fransisca C.; Morales, Alejandro; Weise, Sean E.; Sharkey, Thomas D.

2015-01-01

Leaf area growth determines the light interception capacity of a crop and is often used as a surrogate for plant growth in high-throughput phenotyping systems. The relationship between leaf area growth and growth in terms of mass will depend on how carbon is partitioned among new leaf area, leaf mass, root mass, reproduction, and respiration. A model of leaf area growth in terms of photosynthetic rate and carbon partitioning to different plant organs was developed and tested with Arabidopsis thaliana L. Heynh. ecotype Columbia (Col-0) and a mutant line, gigantea-2 (gi-2), which develops very large rosettes. Data obtained from growth analysis and gas exchange measurements was used to train a genetic programming algorithm to parameterize and test the above model. The relationship between leaf area and plant biomass was found to be non-linear and variable depending on carbon partitioning. The model output was sensitive to the rate of photosynthesis but more sensitive to the amount of carbon partitioned to growing thicker leaves. The large rosette size of gi-2 relative to that of Col-0 resulted from relatively small differences in partitioning to new leaf area vs. leaf thickness. PMID:25914696

Placental Adaptations in Growth Restriction

PubMed Central

Zhang, Song; Regnault, Timothy R.H.; Barker, Paige L.; Botting, Kimberley J.; McMillen, Isabella C.; McMillan, Christine M.; Roberts, Claire T.; Morrison, Janna L.

2015-01-01

The placenta is the primary interface between the fetus and mother and plays an important role in maintaining fetal development and growth by facilitating the transfer of substrates and participating in modulating the maternal immune response to prevent immunological rejection of the conceptus. The major substrates required for fetal growth include oxygen, glucose, amino acids and fatty acids, and their transport processes depend on morphological characteristics of the placenta, such as placental size, morphology, blood flow and vascularity. Other factors including insulin-like growth factors, apoptosis, autophagy and glucocorticoid exposure also affect placental growth and substrate transport capacity. Intrauterine growth restriction (IUGR) is often a consequence of insufficiency, and is associated with a high incidence of perinatal morbidity and mortality, as well as increased risk of cardiovascular and metabolic diseases in later life. Several different experimental methods have been used to induce placental insufficiency and IUGR in animal models and a range of factors that regulate placental growth and substrate transport capacity have been demonstrated. While no model system completely recapitulates human IUGR, these animal models allow us to carefully dissect cellular and molecular mechanisms to improve our understanding and facilitate development of therapeutic interventions. PMID:25580812

Regulation of skeletal growth and mineral acquisition by the GH/IGF-1 axis: Lessons from mouse models.

PubMed

Yakar, Shoshana; Isaksson, Olle

2016-06-01

The growth hormone (GH) and its downstream mediator, the insulin-like growth factor-1 (IGF-1), construct a pleotropic axis affecting growth, metabolism, and organ function. Serum levels of GH/IGF-1 rise during pubertal growth and associate with peak bone acquisition, while during aging their levels decline and associate with bone loss. The GH/IGF-1 axis was extensively studied in numerous biological systems including rodent models and cell cultures. Both hormones act in an endocrine and autocrine/paracrine fashion and understanding their distinct and overlapping contributions to skeletal acquisition is still a matter of debate. GH and IGF-1 exert their effects on osteogenic cells via binding to their cognate receptor, leading to activation of an array of genes that mediate cellular differentiation and function. Both hormones interact with other skeletal regulators, such as sex-steroids, thyroid hormone, and parathyroid hormone, to facilitate skeletal growth and metabolism. In this review we summarized several rodent models of the GH/IGF-1 axis and described key experiments that shed new light on the regulation of skeletal growth by the GH/IGF-1 axis. Copyright © 2015 Elsevier Ltd. All rights reserved.

Regulation of skeletal growth and mineral acquisition by the GH/IGF-1 axis: Lessons from mouse models

PubMed Central

Yakar, Shoshana; Isaksson, Olle

2015-01-01

The growth hormone (GH) and its downstream mediator, the insulin-like growth factor-1 (IGF-1), construct a pleotropic axis affecting growth, metabolism, and organ function. Serum levels of GH/IGF-1 rise during pubertal growth and associate with peak bone acquisition, while during aging their levels decline and associate with bone loss. The GH/IGF-1 axis was extensively studied in numerous biological systems including rodent models and cell cultures. Both hormones act in an endocrine and autocrine/paracrine fashion and understanding their distinct and overlapping contributions to skeletal acquisition is still a matter of debate. GH and IGF-1 exert their effects on osteogenic cells via binding to their cognate receptor, leading to activation of an array of genes that mediate cellular differentiation and function. Both hormones interact with other skeletal regulators, such as sex-steroids, thyroid hormone, and parathyroid hormone, to facilitate skeletal growth and metabolism. In this review we summarized several rodent models of the GH/IGF-1 axis and described key experiments that shed new light on the regulation of skeletal growth by the GH/IGF-1 axis. PMID:26432542

Critical thresholds for eventual extinction in randomly disturbed population growth models.

PubMed

Peckham, Scott D; Waymire, Edward C; De Leenheer, Patrick

2018-02-16

This paper considers several single species growth models featuring a carrying capacity, which are subject to random disturbances that lead to instantaneous population reduction at the disturbance times. This is motivated in part by growing concerns about the impacts of climate change. Our main goal is to understand whether or not the species can persist in the long run. We consider the discrete-time stochastic process obtained by sampling the system immediately after the disturbances, and find various thresholds for several modes of convergence of this discrete process, including thresholds for the absence or existence of a positively supported invariant distribution. These thresholds are given explicitly in terms of the intensity and frequency of the disturbances on the one hand, and the population's growth characteristics on the other. We also perform a similar threshold analysis for the original continuous-time stochastic process, and obtain a formula that allows us to express the invariant distribution for this continuous-time process in terms of the invariant distribution of the discrete-time process, and vice versa. Examples illustrate that these distributions can differ, and this sends a cautionary message to practitioners who wish to parameterize these and related models using field data. Our analysis relies heavily on a particular feature shared by all the deterministic growth models considered here, namely that their solutions exhibit an exponentially weighted averaging property between a function of the initial condition, and the same function applied to the carrying capacity. This property is due to the fact that these systems can be transformed into affine systems.

Growth control of the eukaryote cell: a systems biology study in yeast.

PubMed

Castrillo, Juan I; Zeef, Leo A; Hoyle, David C; Zhang, Nianshu; Hayes, Andrew; Gardner, David Cj; Cornell, Michael J; Petty, June; Hakes, Luke; Wardleworth, Leanne; Rash, Bharat; Brown, Marie; Dunn, Warwick B; Broadhurst, David; O'Donoghue, Kerry; Hester, Svenja S; Dunkley, Tom Pj; Hart, Sarah R; Swainston, Neil; Li, Peter; Gaskell, Simon J; Paton, Norman W; Lilley, Kathryn S; Kell, Douglas B; Oliver, Stephen G

2007-01-01

Cell growth underlies many key cellular and developmental processes, yet a limited number of studies have been carried out on cell-growth regulation. Comprehensive studies at the transcriptional, proteomic and metabolic levels under defined controlled conditions are currently lacking. Metabolic control analysis is being exploited in a systems biology study of the eukaryotic cell. Using chemostat culture, we have measured the impact of changes in flux (growth rate) on the transcriptome, proteome, endometabolome and exometabolome of the yeast Saccharomyces cerevisiae. Each functional genomic level shows clear growth-rate-associated trends and discriminates between carbon-sufficient and carbon-limited conditions. Genes consistently and significantly upregulated with increasing growth rate are frequently essential and encode evolutionarily conserved proteins of known function that participate in many protein-protein interactions. In contrast, more unknown, and fewer essential, genes are downregulated with increasing growth rate; their protein products rarely interact with one another. A large proportion of yeast genes under positive growth-rate control share orthologs with other eukaryotes, including humans. Significantly, transcription of genes encoding components of the TOR complex (a major controller of eukaryotic cell growth) is not subject to growth-rate regulation. Moreover, integrative studies reveal the extent and importance of post-transcriptional control, patterns of control of metabolic fluxes at the level of enzyme synthesis, and the relevance of specific enzymatic reactions in the control of metabolic fluxes during cell growth. This work constitutes a first comprehensive systems biology study on growth-rate control in the eukaryotic cell. The results have direct implications for advanced studies on cell growth, in vivo regulation of metabolic fluxes for comprehensive metabolic engineering, and for the design of genome-scale systems biology models of the eukaryotic cell.

Growth control of the eukaryote cell: a systems biology study in yeast

PubMed Central

Castrillo, Juan I; Zeef, Leo A; Hoyle, David C; Zhang, Nianshu; Hayes, Andrew; Gardner, David CJ; Cornell, Michael J; Petty, June; Hakes, Luke; Wardleworth, Leanne; Rash, Bharat; Brown, Marie; Dunn, Warwick B; Broadhurst, David; O'Donoghue, Kerry; Hester, Svenja S; Dunkley, Tom PJ; Hart, Sarah R; Swainston, Neil; Li, Peter; Gaskell, Simon J; Paton, Norman W; Lilley, Kathryn S; Kell, Douglas B; Oliver, Stephen G

2007-01-01

Background Cell growth underlies many key cellular and developmental processes, yet a limited number of studies have been carried out on cell-growth regulation. Comprehensive studies at the transcriptional, proteomic and metabolic levels under defined controlled conditions are currently lacking. Results Metabolic control analysis is being exploited in a systems biology study of the eukaryotic cell. Using chemostat culture, we have measured the impact of changes in flux (growth rate) on the transcriptome, proteome, endometabolome and exometabolome of the yeast Saccharomyces cerevisiae. Each functional genomic level shows clear growth-rate-associated trends and discriminates between carbon-sufficient and carbon-limited conditions. Genes consistently and significantly upregulated with increasing growth rate are frequently essential and encode evolutionarily conserved proteins of known function that participate in many protein-protein interactions. In contrast, more unknown, and fewer essential, genes are downregulated with increasing growth rate; their protein products rarely interact with one another. A large proportion of yeast genes under positive growth-rate control share orthologs with other eukaryotes, including humans. Significantly, transcription of genes encoding components of the TOR complex (a major controller of eukaryotic cell growth) is not subject to growth-rate regulation. Moreover, integrative studies reveal the extent and importance of post-transcriptional control, patterns of control of metabolic fluxes at the level of enzyme synthesis, and the relevance of specific enzymatic reactions in the control of metabolic fluxes during cell growth. Conclusion This work constitutes a first comprehensive systems biology study on growth-rate control in the eukaryotic cell. The results have direct implications for advanced studies on cell growth, in vivo regulation of metabolic fluxes for comprehensive metabolic engineering, and for the design of genome-scale systems biology models of the eukaryotic cell. PMID:17439666

Controlled growth factor release from synthetic extracellular matrices

NASA Astrophysics Data System (ADS)

Lee, Kuen Yong; Peters, Martin C.; Anderson, Kenneth W.; Mooney, David J.

2000-12-01

Polymeric matrices can be used to grow new tissues and organs, and the delivery of growth factors from these matrices is one method to regenerate tissues. A problem with engineering tissues that exist in a mechanically dynamic environment, such as bone, muscle and blood vessels, is that most drug delivery systems have been designed to operate under static conditions. We thought that polymeric matrices, which release growth factors in response to mechanical signals, might provide a new approach to guide tissue formation in mechanically stressed environments. Critical design features for this type of system include the ability to undergo repeated deformation, and a reversible binding of the protein growth factors to polymeric matrices to allow for responses to repeated stimuli. Here we report a model delivery system that can respond to mechanical signalling and upregulate the release of a growth factor to promote blood vessel formation. This approach may find a number of applications, including regeneration and engineering of new tissues and more general drug-delivery applications.

Simulation model for plant growth in controlled environment systems

NASA Technical Reports Server (NTRS)

Raper, C. D., Jr.; Wann, M.

1986-01-01

The role of the mathematical model is to relate the individual processes to environmental conditions and the behavior of the whole plant. Using the controlled-environment facilities of the phytotron at North Carolina State University for experimentation at the whole-plant level and methods for handling complex models, researchers developed a plant growth model to describe the relationships between hierarchial levels of the crop production system. The fundamental processes that are considered are: (1) interception of photosynthetically active radiation by leaves, (2) absorption of photosynthetically active radiation, (3) photosynthetic transformation of absorbed radiation into chemical energy of carbon bonding in solube carbohydrates in the leaves, (4) translocation between carbohydrate pools in leaves, stems, and roots, (5) flow of energy from carbohydrate pools for respiration, (6) flow from carbohydrate pools for growth, and (7) aging of tissues. These processes are described at the level of organ structure and of elementary function processes. The driving variables of incident photosynthetically active radiation and ambient temperature as inputs pertain to characterization at the whole-plant level. The output of the model is accumulated dry matter partitioned among leaves, stems, and roots; thus, the elementary processes clearly operate under the constraints of the plant structure which is itself the output of the model.

New theories of root growth modelling

NASA Astrophysics Data System (ADS)

Landl, Magdalena; Schnepf, Andrea; Vanderborght, Jan; Huber, Katrin; Javaux, Mathieu; Bengough, A. Glyn; Vereecken, Harry

2016-04-01

In dynamic root architecture models, root growth is represented by moving root tips whose line trajectory results in the creation of new root segments. Typically, the direction of root growth is calculated as the vector sum of various direction-affecting components. However, in our simulations this did not reproduce experimental observations of root growth in structured soil. We therefore developed a new approach to predict the root growth direction. In this approach we distinguish between, firstly, driving forces for root growth, i.e. the force exerted by the root which points in the direction of the previous root segment and gravitropism, and, secondly, the soil mechanical resistance to root growth or penetration resistance. The latter can be anisotropic, i.e. depending on the direction of growth, which leads to a difference between the direction of the driving force and the direction of the root tip movement. Anisotropy of penetration resistance can be caused either by microscale differences in soil structure or by macroscale features, including macropores. Anisotropy at the microscale is neglected in our model. To allow for this, we include a normally distributed random deflection angle α to the force which points in the direction of the previous root segment with zero mean and a standard deviation σ. The standard deviation σ is scaled, so that the deflection from the original root tip location does not depend on the spatial resolution of the root system model. Similarly to the water flow equation, the direction of the root tip movement corresponds to the water flux vector while the driving forces are related to the water potential gradient. The analogue of the hydraulic conductivity tensor is the root penetrability tensor. It is determined by the inverse of soil penetration resistance and describes the ease with which a root can penetrate the soil. By adapting the three dimensional soil and root water uptake model R-SWMS (Javaux et al., 2008) in this way, we were able to simulate root growth and root water uptake in soil with macropores. The model was parametrized using experimental results of studies by Hirth et al. (2005) and Stirzaker et al. (1996). It proved to be capable of reproducing observed root growth responses to structured soil both at the single root and the plant root system scale. This new approach enables us to investigate how plant roots use macropores to gain access to water and nutrient reservoirs in deeper, highly dense soil layers. Acknowledgements: Funding by German Research Foundation within the Research Unit 888 is gratefully acknowledged. The James Hutton Institute receives funding from the Scottish Government.

Modelling microbial metabolic rewiring during growth in a complex medium.

PubMed

Fondi, Marco; Bosi, Emanuele; Presta, Luana; Natoli, Diletta; Fani, Renato

2016-11-24

In their natural environment, bacteria face a wide range of environmental conditions that change over time and that impose continuous rearrangements at all the cellular levels (e.g. gene expression, metabolism). When facing a nutritionally rich environment, for example, microbes first use the preferred compound(s) and only later start metabolizing the other one(s). A systemic re-organization of the overall microbial metabolic network in response to a variation in the composition/concentration of the surrounding nutrients has been suggested, although the range and the entity of such modifications in organisms other than a few model microbes has been scarcely described up to now. We used multi-step constraint-based metabolic modelling to simulate the growth in a complex medium over several time steps of the Antarctic model organism Pseudoalteromonas haloplanktis TAC125. As each of these phases is characterized by a specific set of amino acids to be used as carbon and energy source our modelling framework describes the major consequences of nutrients switching at the system level. The model predicts that a deep metabolic reprogramming might be required to achieve optimal biomass production in different stages of growth (different medium composition), with at least half of the cellular metabolic network involved (more than 50% of the metabolic genes). Additionally, we show that our modelling framework is able to capture metabolic functional association and/or common regulatory features of the genes embedded in our reconstruction (e.g. the presence of common regulatory motifs). Finally, to explore the possibility of a sub-optimal biomass objective function (i.e. that cells use resources in alternative metabolic processes at the expense of optimal growth) we have implemented a MOMA-based approach (called nutritional-MOMA) and compared the outcomes with those obtained with Flux Balance Analysis (FBA). Growth simulations under this scenario revealed the deep impact of choosing among alternative objective functions on the resulting predictions of fluxes distribution. Here we provide a time-resolved, systems-level scheme of PhTAC125 metabolic re-wiring as a consequence of carbon source switching in a nutritionally complex medium. Our analyses suggest the presence of a potential efficient metabolic reprogramming machinery to continuously and promptly adapt to this nutritionally changing environment, consistent with adaptation to fast growth in a fairly, but probably inconstant and highly competitive, environment. Also, we show i) how functional partnership and co-regulation features can be predicted by integrating multi-step constraint-based metabolic modelling with fed-batch growth data and ii) that performing simulations under a sub-optimal objective function may lead to different flux distributions in respect to canonical FBA.

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

PubMed Central

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

2016-01-01

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

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

DOE PAGES

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

2016-11-18

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

Influence of diffusion and convective transport on dendritic growth in dilute alloys

NASA Technical Reports Server (NTRS)

Glicksman, M. E.; Singh, N. B.; Chopra, M.

1982-01-01

Experimentation has been carried out in which the kinetics and morphology of dendritic growth were measured as a function of thermal supercooling, solute concentration, and spatial orientation of the dendritic growth axis. The crystal growth system studied is succinonitrile, NC(CH2)2CN, with additions of argon (up to 0.1 mole percent). This system is especially useful as a model for alloy studies because kinetic data are available for high purity (7-9's) succinonitrile. The influence of the solute, at fixed thermal supercooling, is to increase the growth velocity and correspondingly decrease intrinsic crystal dimensions. Morphological measurements are described in detail relating tip size, perturbation wavelength, supercooling, and solute concentration. The analysis of these effects based on morphological stability theory is also discussed, and experiments permitting the separation of convective and diffusive heat transport during crystal growth of succinonitrile are described. The studies underscore the importance of gravitationally-induced buoyancy effects on crystal growth.

Use of microcomputers for planning and managing silviculture habitat relationships.

Treesearch

B.G. Marcot; R.S. McNay; R.E. Page

1988-01-01

Microcomputers aid in monitoring, modeling, and decision support for integrating objectives of silviculture and wildlife habitat management. Spreadsheets, data bases, statistics, and graphics programs are described for use in monitoring. Stand growth models, modeling languages, area and geobased information systems, and optimization models are discussed for use in...

Gypsy moth life system model

Treesearch

J. J. Colbert; G. E. Racin

1991-01-01

The model is composed of four major subsystems that are driven by weather. The stand subsystem incorporates the effects of damage by the gypsy moth into annual tree diameter and height growth as well as tree mortality.

Integrating Kinetic Model of E. coli with Genome Scale Metabolic Fluxes Overcomes Its Open System Problem and Reveals Bistability in Central Metabolism

PubMed Central

Mannan, Ahmad A.; Toya, Yoshihiro; Shimizu, Kazuyuki; McFadden, Johnjoe; Kierzek, Andrzej M.; Rocco, Andrea

2015-01-01

An understanding of the dynamics of the metabolic profile of a bacterial cell is sought from a dynamical systems analysis of kinetic models. This modelling formalism relies on a deterministic mathematical description of enzyme kinetics and their metabolite regulation. However, it is severely impeded by the lack of available kinetic information, limiting the size of the system that can be modelled. Furthermore, the subsystem of the metabolic network whose dynamics can be modelled is faced with three problems: how to parameterize the model with mostly incomplete steady state data, how to close what is now an inherently open system, and how to account for the impact on growth. In this study we address these challenges of kinetic modelling by capitalizing on multi-‘omics’ steady state data and a genome-scale metabolic network model. We use these to generate parameters that integrate knowledge embedded in the genome-scale metabolic network model, into the most comprehensive kinetic model of the central carbon metabolism of E. coli realized to date. As an application, we performed a dynamical systems analysis of the resulting enriched model. This revealed bistability of the central carbon metabolism and thus its potential to express two distinct metabolic states. Furthermore, since our model-informing technique ensures both stable states are constrained by the same thermodynamically feasible steady state growth rate, the ensuing bistability represents a temporal coexistence of the two states, and by extension, reveals the emergence of a phenotypically heterogeneous population. PMID:26469081

Controlled Ecological Life Support Systems: CELSS '89 Workshop

NASA Technical Reports Server (NTRS)

Macelroy, Robert D. (Editor)

1990-01-01

Topics discussed at NASA's Controlled Ecological Life Support Systems (CELSS) workshop concerned the production of edible biomass. Specific areas of interest ranged from the efficiency of plant growth, to the conversion of inedible plant material to edible food, to the use of plant culture techniques. Models of plant growth and whole CELSS systems are included. The use of algae to supplement and improve dietary requirements is addressed. Flight experimentation is covered in topics ranging from a Salad Machine for use on the Space Station Freedom to conceptual designs for a lunar base CELSS.

Urban growth and landscape connectivity threats assessment at Saguaro National Park, Arizona, USA

USGS Publications Warehouse

Perkl, Ryan; Norman, Laura M.; Mitchell, David; Feller, Mark R.; Smith, Garrett; Wilson, Natalie R.

2018-01-01

Urban and exurban expansion results in habitat and biodiversity loss globally. We hypothesize that a coupled-model approach could connect urban planning for future cities with landscape ecology to consider wildland habitat connectivity. Our work combines urban growth simulations with models of wildlife corridors to examine how species will be impacted by development to test this hypothesis. We leverage a land use change model (SLEUTH) with structural and functional landscape-connectivity modeling techniques to ascertain the spatial extent and locations of connectivity related threats to a national park in southern Arizona, USA, and describe how protected areas might be impacted by urban expansion. Results of projected growth significantly altered structural connectivity (80%) when compared to current (baseline) corridor conditions. Moreover, projected growth impacted functional connectivity differently amongst species, indicating resilience of some species and near-complete displacement of others. We propose that implementing a geospatial-design-based model will allow for a better understanding of the impacts management decisions have on wildlife populations. The application provides the potential to understand both human and environmental impacts of land-system dynamics, critical for long-term sustainability.

A refined genome-scale reconstruction of Chlamydomonas metabolism provides a platform for systems-level analyses.

PubMed

Imam, Saheed; Schäuble, Sascha; Valenzuela, Jacob; López García de Lomana, Adrián; Carter, Warren; Price, Nathan D; Baliga, Nitin S

2015-12-01

Microalgae have reemerged as organisms of prime biotechnological interest due to their ability to synthesize a suite of valuable chemicals. To harness the capabilities of these organisms, we need a comprehensive systems-level understanding of their metabolism, which can be fundamentally achieved through large-scale mechanistic models of metabolism. In this study, we present a revised and significantly improved genome-scale metabolic model for the widely-studied microalga, Chlamydomonas reinhardtii. The model, iCre1355, represents a major advance over previous models, both in content and predictive power. iCre1355 encompasses a broad range of metabolic functions encoded across the nuclear, chloroplast and mitochondrial genomes accounting for 1355 genes (1460 transcripts), 2394 and 1133 metabolites. We found improved performance over the previous metabolic model based on comparisons of predictive accuracy across 306 phenotypes (from 81 mutants), lipid yield analysis and growth rates derived from chemostat-grown cells (under three conditions). Measurement of macronutrient uptake revealed carbon and phosphate to be good predictors of growth rate, while nitrogen consumption appeared to be in excess. We analyzed high-resolution time series transcriptomics data using iCre1355 to uncover dynamic pathway-level changes that occur in response to nitrogen starvation and changes in light intensity. This approach enabled accurate prediction of growth rates, the cessation of growth and accumulation of triacylglycerols during nitrogen starvation, and the temporal response of different growth-associated pathways to increased light intensity. Thus, iCre1355 represents an experimentally validated genome-scale reconstruction of C. reinhardtii metabolism that should serve as a useful resource for studying the metabolic processes of this and related microalgae. © 2015 The Authors The Plant Journal © 2015 John Wiley & Sons Ltd.

A refined genome-scale reconstruction of Chlamydomonas metabolism provides a platform for systems-level analyses

DOE PAGES

Imam, Saheed; Schäuble, Sascha; Valenzuela, Jacob; ...

2015-10-20

Microalgae have reemerged as organisms of prime biotechnological interest due to their ability to synthesize a suite of valuable chemicals. To harness the capabilities of these organisms, we need a comprehensive systems-level understanding of their metabolism, which can be fundamentally achieved through large-scale mechanistic models of metabolism. In this study, we present a revised and significantly improved genome-scale metabolic model for the widely-studied microalga, Chlamydomonas reinhardtii. The model, iCre1355, represents a major advance over previous models, both in content and predictive power. iCre1355 encompasses a broad range of metabolic functions encoded across the nuclear, chloroplast and mitochondrial genomes accounting formore » 1355 genes (1460 transcripts), 2394 and 1133 metabolites. We found improved performance over the previous metabolic model based on comparisons of predictive accuracy across 306 phenotypes (from 81 mutants), lipid yield analysis and growth rates derived from chemostat-grown cells (under three conditions). Measurement of macronutrient uptake revealed carbon and phosphate to be good predictors of growth rate, while nitrogen consumption appeared to be in excess. We analyzed high-resolution time series transcriptomics data using iCre1355 to uncover dynamic pathway-level changes that occur in response to nitrogen starvation and changes in light intensity. This approach enabled accurate prediction of growth rates, the cessation of growth and accumulation of triacylglycerols during nitrogen starvation, and the temporal response of different growth-associated pathways to increased light intensity. Thus, iCre1355 represents an experimentally validated genome-scale reconstruction of C. reinhardtii metabolism that should serve as a useful resource for studying the metabolic processes of this and related microalgae.« less

Development of human epithelial cell systems for radiation risk assessment

NASA Astrophysics Data System (ADS)

Yang, C. H.; Craise, L. M.

1994-10-01

The most important health effect of space radiation for astronauts is cancer induction. For radiation risk assessment, an understanding of carcinogenic effect of heavy ions in human cells is most essential. In our laboratory, we have successfully developed a human mammary epithelial cell system for studying the neoplastic transformation in vitro. Growth variants were obtained from heavy ion irradiated immortal mammary cell line. These cloned growth variants can grow in regular tissue culture media and maintain anchorage dependent growth and density inhibition property. Upon further irradiation with high-LET radiation, transformed foci were found. Experimental results from these studies suggest that multiexposure of radiation is required to induce neoplastic transformation of human epithelial cells. This multihits requirement may be due to high genomic stability of human cells. These growth variants can be useful model systems for space flight experiments to determine the carcinogenic effect of space radiation in human epithelial cells.

Development of human epithelial cell systems for radiation risk assessment

NASA Technical Reports Server (NTRS)

Yang, C. H.; Craise, L. M.

1994-01-01

The most important health effect of space radiation for astronauts is cancer induction. For radiation risk assessment, an understanding of carcinogenic effect of heavy ions in human cells is most essential. In our laboratory, we have successfully developed a human mammary epithelial cell system for studying the neoplastic transformation in vitro. Growth variants were obtained from heavy ion irradiated immortal mammary cell line. These cloned growth variants can grow in regular tissue culture media and maintain anchorage dependent growth and density inhibition property. Upon further irradiation with high-Linear Energy Transfer (LET) radiation, transformed foci were found. Experimental results from these studies suggest that multiexposure of radiation is required to induce neoplastic tranformation of human epithelial cells. This multihits requirement may be due to high genomic stability of human cells. These growth variants can be useful model systems for space flight experiments to determine the carcinogenic effect of space radiation in human epithelial cells.

Adherence to stainless steel by foodborne microorganisms during growth in model food systems.

PubMed

Hood, S K; Zottola, E A

1997-07-22

Biofilm formation on stainless steel by Salmonella typhimurium, Listeria monocytogenes, Escherichia coli O157:H7, Pseudomonas fragi and Pseudomonas fluorescens during growth in model food systems was studied. Test growth media included tryptic soy broth (TSB), diluted TSB (dTSB), 1% reconstituted skim milk (RSM) and diluted meat juice (DMJ). Adherent cells were stained with acridine orange and enumerated using epifluorescent microscopy and computerized image analysis. Cells were observed on the stainless steel surface after 1 h in all of the media. However, the increases in the number of adherent cells over time was seen only with S. typhimurium in DMJ, E. coli O157:H7 in TSB, dTSB and DMJ, P. fragi in RSM and P. fluorescens in RSM. The medium which produced the highest observed level of adherent cells was different for each microorganism.

Naval Health Research Center (NHRC) Report for the Calendar Year 1981.

DTIC Science & Technology

1981-01-01

r, liminary study on growth patterns of Shigella. The Abbott MS-2 Research Model %%as used to show that of 35 cultures studied 5 distinctive growth...vaccination system may provide a suitabl( model for control of ceretrospinal meningitis epidemics in the rural areas of many countries. 81-5 KOILB, D F...rates among Marine Corps basic training platoons suggested that a general factor such as emergent social climate within the platoons might affect

Fluctuation-controlled front propagation

NASA Astrophysics Data System (ADS)

Ridgway, Douglas Thacher

1997-09-01

A number of fundamental pattern-forming systems are controlled by fluctuations at the front. These problems involve the interaction of an infinite dimensional probability distribution with a strongly nonlinear, spatially extended pattern-forming system. We have examined fluctuation-controlled growth in the context of the specific problems of diffusion-limited growth and biological evolution. Mean field theory of diffusion-limited growth exhibits a finite time singularity. Near the leading edge of a diffusion-limited front, this leads to acceleration and blowup. This may be resolved, in an ad hoc manner, by introducing a cutoff below which growth is weakened or eliminated (8). This model, referred to as the BLT model, captures a number of qualitative features of global pattern formation in diffusion-limited aggregation: contours of the mean field match contours of averaged particle density in simulation, and the modified mean field theory can form dendritic features not possible in the naive mean field theory. The morphology transition between dendritic and non-dendritic global patterns requires that BLT fronts have a Mullins-Sekerka instability of the wavefront shape, in order to form concave patterns. We compute the stability of BLT fronts numerically, and compare the results to fronts without a cutoff. A significant morphological instability of the BLT fronts exists, with a dominant wavenumber on the scale of the front width. For standard mean field fronts, no instability is found. The naive and ad hoc mean field theories are continuum-deterministic models intended to capture the behavior of a discrete stochastic system. A transformation which maps discrete systems into a continuum model with a singular multiplicative noise is known, however numerical simulations of the continuum stochastic system often give mean field behavior instead of the critical behavior of the discrete system. We have found a new interpretation of the singular noise, based on maintaining the symmetry of the absorbing state, but which is unsuccessful at capturing the behavior of diffusion-limited growth. In an effort to find a simpler model system, we turned to modelling fitness increases in evolution. The work was motivated by an experiment on vesicular stomatitis virus, a short (˜9600bp) single-stranded RNA virus. A highly bottlenecked viral population increases in fitness rapidly until a certain point, after which the fitness increases at a slower rate. This is well modeled by a constant population reproducing and mutating on a smooth fitness landscape. Mean field theory of this system displays the same infinite propagation velocity blowup as mean field diffusion-limited aggregation. However, we have been able to make progress on a number of fronts. One is solving systems of moment equations, where a hierarchy of moments is truncated arbitrarily at some level. Good results for front propagation velocity are found with just two moments, corresponding to inclusion of the basic finite population clustering effect ignored by mean field theory. In addition, for small mutation rates, most of the population will be entirely on a single site or two adjacent sites, and the density of these cases can be described and solved. (Abstract shortened by UMI.)

Mapping of Biophysical Parameters of Rice Agriculture System from Hyperspectral Imagery

NASA Astrophysics Data System (ADS)

Moharana, Shreedevi; Duta, Subashisa

2017-04-01

Chlorophyll, nitrogen and leaf water content are the most essential parameters for paddy crop growth. Ground hyperspectral observations were collected at canopy level during critical growth period of rice by using hand held Spectroradiometer. Chemical analysis was carried out to quantify the total chlorophyll, nitrogen and leaf water content. By exploiting the in-situ hyperspectral measurements, regression models were established between each of the crop growth parameters and the spectral indices specifically designed for chlorophyll, nitrogen and water stress. Narrow band vegetation index models were developed for mapping these parameters from Hyperion imagery in an agriculture system. It was inferred that the modified simple ratio (SR) and leaf nitrogen concentration (LNC) predictive index models, which followed a linear and nonlinear relationship respectively, produced satisfactory results in predicting rice nitrogen content from hyperspectral imagery. The presently developed model was compared with other models proposed by researchers. It was ascertained that, nitrogen content varied widely from 1-4 percentage and only 2-3 percentage for paddy crop using present modified index models and well-known predicted Tian et al. (2011) model respectively. The modified present LNC index model performed better than the established Tian et al. (2011) model as far as the estimated nitrogen content from Hyperion imagery was concerned. Moreover, within the observed chlorophyll range attained from the rice genotypes cultivated in the studied rice agriculture system, the index models (LNC, OASVI, Gitelson, mSR and MTCI) accomplished satisfactory results in the spatial distribution of rice chlorophyll content from Hyperion imagery. Spatial distribution of total chlorophyll content widely varied from 1.77-5.81 mg/g (LNC), 3.0-13 mg/g (OASVI) and 2.90-5.40 mg/g (MTCI). Following the similar guideline, it was found that normalized difference water index (NDWI) and normalized difference infrared index (NDII) predictive models demonstrated the spatial variability of leaf water content from 40 percentage to 90 percentage in the same rice agriculture system which has a good agreement with observed in-situ leaf water measurements. The spatial information of these parameters will be useful for crop nutrient management and yield forecasting, and will serve as inputs to various crop-forecasting models for developing a precision rice agriculture system. Key words: Rice agriculture system, nitrogen, chlorophyll, leaf water content, vegetation index

Coupling root architecture and pore network modeling - an attempt towards better understanding root-soil interactions

NASA Astrophysics Data System (ADS)

Leitner, Daniel; Bodner, Gernot; Raoof, Amir

2013-04-01

Understanding root-soil interactions is of high importance for environmental and agricultural management. Root uptake is an essential component in water and solute transport modeling. The amount of groundwater recharge and solute leaching significantly depends on the demand based plant extraction via its root system. Plant uptake however not only responds to the potential demand, but in most situations is limited by supply form the soil. The ability of the plant to access water and solutes in the soil is governed mainly by root distribution. Particularly under conditions of heterogeneous distribution of water and solutes in the soil, it is essential to capture the interaction between soil and roots. Root architecture models allow studying plant uptake from soil by describing growth and branching of root axes in the soil. Currently root architecture models are able to respond dynamically to water and nutrient distribution in the soil by directed growth (tropism), modified branching and enhanced exudation. The porous soil medium as rooting environment in these models is generally described by classical macroscopic water retention and sorption models, average over the pore scale. In our opinion this simplified description of the root growth medium implies several shortcomings for better understanding root-soil interactions: (i) It is well known that roots grow preferentially in preexisting pores, particularly in more rigid/dry soil. Thus the pore network contributes to the architectural form of the root system; (ii) roots themselves can influence the pore network by creating preferential flow paths (biopores) which are an essential element of structural porosity with strong impact on transport processes; (iii) plant uptake depend on both the spatial location of water/solutes in the pore network as well as the spatial distribution of roots. We therefore consider that for advancing our understanding in root-soil interactions, we need not only to extend our root models, but also improve the description of the rooting environment. Until now there have been no attempts to couple root architecture and pore network models. In our work we present a first attempt to join both types of models using the root architecture model of Leitner et al., (2010) and a pore network model presented by Raoof et al. (2010). The two main objectives of coupling both models are: (i) Representing the effect of root induced biopores on flow and transport processes: For this purpose a fixed root architecture created by the root model is superimposed as a secondary root induced pore network to the primary soil network, thus influencing the final pore topology in the network generation. (ii) Representing the influence of pre-existing pores on root branching: Using a given network of (rigid) pores, the root architecture model allocates its root axes into these preexisting pores as preferential growth paths with thereby shape the final root architecture. The main objective of our study is to reveal the potential of using a pore scale description of the plant growth medium for an improved representation of interaction processes at the interface of root and soil. References Raoof, A., Hassanizadeh, S.M. 2010. A New Method for Generating Pore-Network Models. Transp. Porous Med. 81, 391-407. Leitner, D, Klepsch, S., Bodner, G., Schnepf, S. 2010. A dynamic root system growth model based on L-Systems. Tropisms and coupling to nutrient uptake from soil. Plant Soil 332, 177-192.

A numerical study of biofilm growth in a microgravity environment

NASA Astrophysics Data System (ADS)

Aristotelous, A. C.; Papanicolaou, N. C.

2017-10-01

A mathematical model is proposed to investigate the effect of microgravity on biofilm growth. We examine the case of biofilm suspended in a quiescent aqueous nutrient solution contained in a rectangular tank. The bacterial colony is assumed to follow logistic growth whereas nutrient absorption is assumed to follow Monod kinetics. The problem is modeled by a coupled system of nonlinear partial differential equations in two spatial dimensions solved using the Discontinuous Galerkin Finite Element method. Nutrient and biofilm concentrations are computed in microgravity and normal gravity conditions. A preliminary quantitative relationship between the biofilm concentration and the gravity field intensity is derived.

Developmental Trajectories of Attention in Typically Developing Chinese Children: A Four-Wave Longitudinal Study.

PubMed

Yan, Chao; Zhou, Hui; Wei, Wei; Wang, Yi-Ji; Cui, Lixian; Chan, Raymond C K; Deng, Ci-Ping

2018-06-22

We conducted a 4-year longitudinal study to investigate trajectories of attention in a sample of 145 Chinese children. The Test of Everyday Attention was administered and latent growth modeling was used to capture developmental trajectories. We found that children's selective attention showed a linear increase, whereas attentional control and sustained attention increased rapidly then slowed down over 4 years. There was no significant correlation between the slopes of growth model for any subsystems. Girls showed higher initial levels of selective attention than boys, but no difference in growth rate. These findings support different developmental patterns in the attention network systems.

Modelling coupled microbial processes in the subsurface: Model development, verification, evaluation and application

NASA Astrophysics Data System (ADS)

Masum, Shakil A.; Thomas, Hywel R.

2018-06-01

To study subsurface microbial processes, a coupled model which has been developed within a Thermal-Hydraulic-Chemical-Mechanical (THCM) framework is presented. The work presented here, focuses on microbial transport, growth and decay mechanisms under the influence of multiphase flow and bio-geochemical reactions. In this paper, theoretical formulations and numerical implementations of the microbial model are presented. The model has been verified and also evaluated against relevant experimental results. Simulated results show that the microbial processes have been accurately implemented and their impacts on porous media properties can be predicted either qualitatively or quantitatively or both. The model has been applied to investigate biofilm growth in a sandstone core that is subjected to a two-phase flow and variable pH conditions. The results indicate that biofilm growth (if not limited by substrates) in a multiphase system largely depends on the hydraulic properties of the medium. When the change in porewater pH which occurred due to dissolution of carbon dioxide gas is considered, growth processes are affected. For the given parameter regime, it has been shown that the net biofilm growth is favoured by higher pH; whilst the processes are considerably retarded at lower pH values. The capabilities of the model to predict microbial respiration in a fully coupled multiphase flow condition and microbial fermentation leading to production of a gas phase are also demonstrated.

Biological system interactions.

PubMed Central

Adomian, G; Adomian, G E; Bellman, R E

1984-01-01

Mathematical modeling of cellular population growth, interconnected subsystems of the body, blood flow, and numerous other complex biological systems problems involves nonlinearities and generally randomness as well. Such problems have been dealt with by mathematical methods often changing the actual model to make it tractable. The method presented in this paper (and referenced works) allows much more physically realistic solutions. PMID:6585837

Operations Research techniques in the management of large-scale reforestation programs

Treesearch

Joseph Buongiorno; D.E. Teeguarden

1978-01-01

A reforestation planning system for the Douglas-fir region of the Western United States is described. Part of the system is a simulation model to predict plantation growth and to determine economic thinning regimes and rotation ages as a function of site characteristics, initial density, reforestation costs, and management constraints. A second model estimates the...

The Expansion of National Educational Systems: Tests of a Population Ecology Model

ERIC Educational Resources Information Center

Nielsen, Francois; Hannan, Michael T.

1977-01-01

This paper investigates the expansion of enrollments in national systems of education during the 1950-1970 period from the point of view of the population ecology of organizations. A simplified dynamic model of the growth of a population of educational organizations is estimated using various techniques for pooling time series of data. (Author/JM)

Mathematical modeling of continuous ethanol fermentation in a membrane bioreactor by pervaporation compared to conventional system: Genetic algorithm.

PubMed

Esfahanian, Mehri; Shokuhi Rad, Ali; Khoshhal, Saeed; Najafpour, Ghasem; Asghari, Behnam

2016-07-01

In this paper, genetic algorithm was used to investigate mathematical modeling of ethanol fermentation in a continuous conventional bioreactor (CCBR) and a continuous membrane bioreactor (CMBR) by ethanol permselective polydimethylsiloxane (PDMS) membrane. A lab scale CMBR with medium glucose concentration of 100gL(-1) and Saccharomyces cerevisiae microorganism was designed and fabricated. At dilution rate of 0.14h(-1), maximum specific cell growth rate and productivity of 0.27h(-1) and 6.49gL(-1)h(-1) were respectively found in CMBR. However, at very high dilution rate, the performance of CMBR was quite similar to conventional fermentation on account of insufficient incubation time. In both systems, genetic algorithm modeling of cell growth, ethanol production and glucose concentration were conducted based on Monod and Moser kinetic models during each retention time at unsteady condition. The results showed that Moser kinetic model was more satisfactory and desirable than Monod model. Copyright © 2016 Elsevier Ltd. All rights reserved.

Multimodel ensembles of wheat growth: many models are better than one.

PubMed

Martre, Pierre; Wallach, Daniel; Asseng, Senthold; Ewert, Frank; Jones, James W; Rötter, Reimund P; Boote, Kenneth J; Ruane, Alex C; Thorburn, Peter J; Cammarano, Davide; Hatfield, Jerry L; Rosenzweig, Cynthia; Aggarwal, Pramod K; Angulo, Carlos; Basso, Bruno; Bertuzzi, Patrick; Biernath, Christian; Brisson, Nadine; Challinor, Andrew J; Doltra, Jordi; Gayler, Sebastian; Goldberg, Richie; Grant, Robert F; Heng, Lee; Hooker, Josh; Hunt, Leslie A; Ingwersen, Joachim; Izaurralde, Roberto C; Kersebaum, Kurt Christian; Müller, Christoph; Kumar, Soora Naresh; Nendel, Claas; O'leary, Garry; Olesen, Jørgen E; Osborne, Tom M; Palosuo, Taru; Priesack, Eckart; Ripoche, Dominique; Semenov, Mikhail A; Shcherbak, Iurii; Steduto, Pasquale; Stöckle, Claudio O; Stratonovitch, Pierre; Streck, Thilo; Supit, Iwan; Tao, Fulu; Travasso, Maria; Waha, Katharina; White, Jeffrey W; Wolf, Joost

2015-02-01

Crop models of crop growth are increasingly used to quantify the impact of global changes due to climate or crop management. Therefore, accuracy of simulation results is a major concern. Studies with ensembles of crop models can give valuable information about model accuracy and uncertainty, but such studies are difficult to organize and have only recently begun. We report on the largest ensemble study to date, of 27 wheat models tested in four contrasting locations for their accuracy in simulating multiple crop growth and yield variables. The relative error averaged over models was 24-38% for the different end-of-season variables including grain yield (GY) and grain protein concentration (GPC). There was little relation between error of a model for GY or GPC and error for in-season variables. Thus, most models did not arrive at accurate simulations of GY and GPC by accurately simulating preceding growth dynamics. Ensemble simulations, taking either the mean (e-mean) or median (e-median) of simulated values, gave better estimates than any individual model when all variables were considered. Compared to individual models, e-median ranked first in simulating measured GY and third in GPC. The error of e-mean and e-median declined with an increasing number of ensemble members, with little decrease beyond 10 models. We conclude that multimodel ensembles can be used to create new estimators with improved accuracy and consistency in simulating growth dynamics. We argue that these results are applicable to other crop species, and hypothesize that they apply more generally to ecological system models. © 2014 John Wiley & Sons Ltd.

Multimodel Ensembles of Wheat Growth: More Models are Better than One

NASA Technical Reports Server (NTRS)

Martre, Pierre; Wallach, Daniel; Asseng, Senthold; Ewert, Frank; Jones, James W.; Rotter, Reimund P.; Boote, Kenneth J.; Ruane, Alex C.; Thorburn, Peter J.; Cammarano, Davide;

Multimodel Ensembles of Wheat Growth: Many Models are Better than One

NASA Technical Reports Server (NTRS)

Martre, Pierre; Wallach, Daniel; Asseng, Senthold; Ewert, Frank; Jones, James W.; Rotter, Reimund P.; Boote, Kenneth J.; Ruane, Alexander C.; Thorburn, Peter J.; Cammarano, Davide;

Development of a model describing the inhibitory effect of selected preservatives on the growth of Listeria monocytogenes in a meat model system.

PubMed

Dussault, Dominic; Vu, Khanh Dang; Lacroix, Monique

2016-02-01

The objective of this study was to evaluate the impact of seven independent factors consisting of sodium nitrite, pH, sodium chloride, sodium acetate, sodium lactate syrup, calcium propionate and a blend of nisin and hop alpha acids on the growth rate of Listeria monocytogenes in ham as a model of ready-to-eat (RTE) meat products. A central composite consisted of seven factors mentioned above was designed and the response surface methodology was applied for creating a mathematic model to predict the growth rate of L. monocytogenes in RTE meat products. Six parameters showed a significant (P ≤ 0.1) influence on the growth rate of L. monocytogenes. Only the blend of nisin and hop alpha acids did not show any significant effect (P > 0.1) in the concentrations used in this study. Increasing concentration of sodium chloride, sodium nitrite, sodium acetate, potassium lactate and calcium propionate in meat reduced bacterial growth rate while increasing pH in meat increased the growth rate of L. monocytogenes. The current mathematical equation will be an important tool in order to reduce the required number of challenge studies performed in order to ensure a safe food product. Copyright © 2015 Elsevier Ltd. All rights reserved.

A Model to Explain Plant Growth Promotion Traits: A Multivariate Analysis of 2,211 Bacterial Isolates

PubMed Central

da Costa, Pedro Beschoren; Granada, Camille E.; Ambrosini, Adriana; Moreira, Fernanda; de Souza, Rocheli; dos Passos, João Frederico M.; Arruda, Letícia; Passaglia, Luciane M. P.

2014-01-01

Plant growth-promoting bacteria can greatly assist sustainable farming by improving plant health and biomass while reducing fertilizer use. The plant-microorganism-environment interaction is an open and complex system, and despite the active research in the area, patterns in root ecology are elusive. Here, we simultaneously analyzed the plant growth-promoting bacteria datasets from seven independent studies that shared a methodology for bioprospection and phenotype screening. The soil richness of the isolate's origin was classified by a Principal Component Analysis. A Categorical Principal Component Analysis was used to classify the soil richness according to isolate's indolic compound production, siderophores production and phosphate solubilization abilities, and bacterial genera composition. Multiple patterns and relationships were found and verified with nonparametric hypothesis testing. Including niche colonization in the analysis, we proposed a model to explain the expression of bacterial plant growth-promoting traits according to the soil nutritional status. Our model shows that plants favor interaction with growth hormone producers under rich nutrient conditions but favor nutrient solubilizers under poor conditions. We also performed several comparisons among the different genera, highlighting interesting ecological interactions and limitations. Our model could be used to direct plant growth-promoting bacteria bioprospection and metagenomic sampling. PMID:25542031

GDP and efficiency of Russian economy

NASA Astrophysics Data System (ADS)

Borodachev, Sergey M.

2018-01-01

The goal is to study GDP (gross domestic product) as an unobservable characteristic of the Russian national economy state on the basis of more reliable observed data on gross output (systems output) and final consumption (systems control). To do this, the dynamic Leontief model is presented in a system-like form and its parameters and GDP dynamics are estimated by the Kalman filter (KF). We consider that all previous year's investments affect the growth of the gross output by the next year. The weights of these investments in the sum are equal to unity and decrease in geometric progression. The estimation of the model parameters was carried out by the maximum likelihood method. The original data on the gross output and final consumption in the period from 1995 to 2015 years where taken from the Rosstat website, where maximally aggregated economy of Russia is reflected in the system of national accounts. The growth of direct costs and capital expenditures at gross output increase has been discovered, which indicates the extensive character of the development of the economy. Investments are being absorbed 2 - 4 years; any change of them causes a surge of commissioned fixed assets fluctuation with a period of 2 years. Then these parameter values were used in the KF to estimate the states of the system. The emerging tendency of the transition of GDP growth to its fall means that the rate of growth of final consumption is higher than the rate of GDP growth. In general, the behavior of the curve of Rosstat GDP obviously follows the declared investments, whereas in the present calculation it is closer to the behavior of final consumption. Estimated GDP and investments that really increased it were significantly less after the crisis of 2008-2009 years than officially published data.

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

PubMed Central

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

2012-01-01

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

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

PubMed

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

2010-11-07

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

Etiologic theories of idiopathic scoliosis. Somatic nervous system and the NOTOM escalator concept as one component in the pathogenesis of adolescent idiopathic scoliosis.

PubMed

Burwell, R G; Dangerfield, P H; Freeman, B J C

2008-01-01

There is no generally accepted scientific theory for the causes of adolescent idiopathic scoliosis (AIS). In recent years encouraging advances thought to be related to the pathogenesis of AIS have been made in several fields. After reviewing concepts of AIS pathogenesis we formulated a collective model of pathogenesis. The central concept of this collective model is a normal neuro-osseous timing of maturation (NOTOM) system operating in a child's internal world during growth and maturation; this provides a dynamic physiological balance of postural equilibrium continuously renewed between two synchronous, polarized processes (NOTOM escalator) linked through sensory input and motor output, namely: 1) osseous escalator-increasing skeletal size and relative segmental mass, and 2) neural escalator - including the CNS body schema. The latter is recalibrated continuously as the body adjusts to biomechanical and kinematic changes resulting from skeletal enlargement, enabling it to coordinate motor actions. We suggest that AIS progression results from abnormality of the neural and/or osseous components of these normal escalator in time and/or space - as asynchrony and/or asymmetries - which cause a failure of neural systems to control asymmetric growth of a rapidly enlarging and moving adolescent spine. This putative initiating asymmetric growth in the spine is explained in separate papers as resulting from dysfunction of the hypothalamus expressed through the sympathetic nervous system (leptin-sympathetic nervous system concept for AIS pathogenesis). In girls, the expression of AIS may result from disharmony between the somatic and autonomic nervous systems - relative postural maturational delay in the somatic nervous system and hypothalamic dysfunction in the autonomic nervous system, with the conflict being fought out in the spine and trunk of the girl and compounded by biomechanical spinal growth modulation.

B-Transform and Its Application to a Fish-Hyacinth Model

ERIC Educational Resources Information Center

Oyelami, B. O.; Ale, S. O.

2002-01-01

A new transform proposed by Oyelami and Ale for impulsive systems is applied to an impulsive fish-hyacinth model. A biological policy regarding the growth of the fish and the hyacinth populations is formulated.

A modified Chang Brown model for the determination of the dopant distribution in a Bridgman Stockbarger semiconductor crystal growth system

NASA Astrophysics Data System (ADS)

Balint, A. M.; Mihailovici, M. M.; Bãltean, D. G.; Balint, St.

2001-08-01

In this paper, we start from the Chang-Brown model which allows computation of flow, temperature and dopant concentration in a vertical Bridgman-Stockbarger semiconductor growth system. The modifications made by us concern the melt/solid interface. Namely, we assume that the phase transition does not take place on a flat mathematical surface, but in a thin region (the so-called precrystallization-zone), masking the crystal, where both phases, liquid and solid, co-exist. We deduce for this zone new effective equations which govern flow, heat and dopant transport and make the coupling of these equations with those governing the same phenomena in the pure melt. We compute flow, temperature and dopant concentration for crystal and melt with thermophysical properties similar to gallium-doped germanium using the modified Chang-Brown model and compare the results to those obtained using the Chang-Brown model.

Fluid Flow and Solidification Under Combined Action of Magnetic Fields and Microgravity

NASA Technical Reports Server (NTRS)

Li, B. Q.; Shu, Y.; Li, K.; deGroh, H. C.

2002-01-01

Mathematical models, both 2-D and 3-D, are developed to represent g-jitter induced fluid flows and their effects on solidification under combined action of magnetic fields and microgravity. The numerical model development is based on the finite element solution of governing equations describing the transient g-jitter driven fluid flows, heat transfer and solutal transport during crystal growth with and without an applied magnetic field in space vehicles. To validate the model predictions, a ground-based g-jitter simulator is developed using the oscillating wall temperatures where timely oscillating fluid flows are measured using a laser PIV system. The measurements are compared well with numerical results obtained from the numerical models. Results show that a combined action derived from magnetic damping and microgravity can be an effective means to control the melt flow and solutal transport in space single crystal growth systems.

Numerical modeling perspectives on zircon crystallization and magma reservoir growth at the Laguna del Maule volcanic field, central Chile

NASA Astrophysics Data System (ADS)

Andersen, N. L.; Dufek, J.; Singer, B. S.

2017-12-01

Magma reservoirs in the middle to upper crust are though to accumulate incrementally over 104 -105 years. Coupled crystallization ages and compositions of zircon are a potentially powerful tracer of reservoir growth and magma evolution. However, complex age distributions and disequilibrium trace element partitioning complicate the interpretation of the zircon record in terms of magmatic processes. In order to make quantitative predictions of the effects of magmatic processes that contribute reservoir growth and evolution—such as cooling and crystallization, magma recharge and mixing, and rejuvenation and remelting of cumulate-rich reservoir margins—we develop a model of zircon saturation and growth within a numerical framework of coupled thermal transfer, phase equilibrium, and magma dynamics. We apply this model to the Laguna del Maule volcanic field (LdM), located in central Chile. LdM has erupted at least 40 km3 of rhyolite from 36 vents distributed within a 250 km2 lake basin. Ongoing unrest demonstrates the large, silicic magma system beneath LdM remains active to this day. Zircon from rhyolite erupted between c. 23 and 1.8 ka produce a continuous distribution of 230Th-238U ages ranging from eruption to 40 ka, as well as less common crystal domains up to 165 ka and rare xenocrysts. Zircon trace element compositions fingerprint compositionally distinct reservoirs that grew within the larger magma system. Despite the dominantly continuous distributions of ages, many crystals are characterized by volumetrically substantial, trace element enriched domains consistent with rapid crystal growth. We utilize numerical simulations to assess the magmatic conditions required to catalyze these "blooms" of crystallization and the magma dynamics that contributed to the assembly of the LdM magma system.

Contact (kallikrein/kinin) system activation in whole human blood induced by low concentrations of α-Fe2O3 nanoparticles.

PubMed

Ekdahl, Kristina N; Davoodpour, Padideh; Ekstrand-Hammarström, Barbro; Fromell, Karin; Hamad, Osama A; Hong, Jaan; Bucht, Anders; Mohlin, Camilla; Seisenbaeva, Gulaim A; Kessler, Vadim G; Nilsson, Bo

2018-04-01

Iron-oxide nanoparticles (NPs) generated by environmental events are likely to represent health problems. α-Fe 2 O 3 NPs were synthesized, characterized and tested in a model for toxicity utilizing human whole blood without added anticoagulant. MALDI-TOF of the corona was performed and activation markers for plasma cascade systems (complement, contact and coagulation systems), platelet consumption and release of growth factors, MPO, and chemokine/cytokines from blood cells were analyzed. The coronas formed on the pristine α-Fe 2 O 3 NPs contained contact system proteins and they induced massive activation of the contact (kinin/kallikrein) system, as well as thrombin generation, platelet activation, and release of two pro-angiogeneic growth factors: platelet-derived growth factor and vascular endothelial growth factor, whereas complement activation was unaffected. The α-Fe 2 O 3 NPs exhibited a noticeable toxicity, with kinin/kallikrein activation, which may be associated with hypotension and long-term angiogenesis in vivo, with implications for cancer, arteriosclerosis and pulmonary disease. Copyright © 2017 Elsevier Inc. All rights reserved.

Predictive microbiology in a dynamic environment: a system theory approach.

PubMed

Van Impe, J F; Nicolaï, B M; Schellekens, M; Martens, T; De Baerdemaeker, J

1995-05-01

The main factors influencing the microbial stability of chilled prepared food products for which there is an increased consumer interest-are temperature, pH, and water activity. Unlike the pH and the water activity, the temperature may vary extensively throughout the complete production and distribution chain. The shelf life of this kind of foods is usually limited due to spoilage by common microorganisms, and the increased risk for food pathogens. In predicting the shelf life, mathematical models are a powerful tool to increase the insight in the different subprocesses and their interactions. However, the predictive value of the sigmoidal functions reported in the literature to describe a bacterial growth curve as an explicit function of time is only guaranteed at a constant temperature within the temperature range of microbial growth. As a result, they are less appropriate in optimization studies of a whole production and distribution chain. In this paper a more general modeling approach, inspired by system theory concepts, is presented if for instance time varying temperature profiles are to be taken into account. As a case study, we discuss a recently proposed dynamic model to predict microbial growth and inactivation under time varying temperature conditions from a system theory point of view. Further, the validity of this methodology is illustrated with experimental data of Brochothrix thermosphacta and Lactobacillus plantarum. Finally, we propose some possible refinements of this model inspired by experimental results.

Evolutionary Systems Theory, Universities, and Endogenous Regional Economic Development

ERIC Educational Resources Information Center

Bowen, William M.

2007-01-01

Universities today are increasingly being viewed in terms of serving the purpose of economic development. This paper postulates that their chief purpose is to advance knowledge and that in doing so they effectuate regional economic growth and development through processes specified in the endogenous economic growth model. To achieve this purpose…

Growth Dynamics of Information Search Services.

ERIC Educational Resources Information Center

Lindqvist, Mats

Computer based information search services, ISS's, of the type that provide on-line literature searches are analyzed from a system's viewpoint using a continuous simulation model. The analysis shows that the observed growth and stagnation of a typical ISS can be explained as a natural consequence of market responses to the service together with a…

Urban Middle-Grade Student Mathematics Achievement Growth under Comprehensive School Reform

ERIC Educational Resources Information Center

Mac Iver, Martha Abele; Mac Iver, Douglas J.

2009-01-01

Recognizing the need to implement standards-based instructional materials with school-wide coherence led some Philadelphia schools to adopt whole-school reform (WSR) models during the late 1990s. The authors report on the relation between mathematics achievement growth for middle-grade students on the Pennsylvania System of School Assessments and…

Adaptive variation in Pinus ponderosa from Intermountain regions. II. Middle Columbia River system

Treesearch

Gerald Rehfeldt

1986-01-01

Seedling populations were grown and compared in common environments. Statistical analyses detected genetic differences between populations for numerous traits reflecting growth potential and periodicity of shoot elongation. Multiple regression models described an adaptive landscape in which populations from low elevations have a high growth potential while those from...

Can Multifactor Models of Teaching Improve Teacher Effectiveness Measures?

ERIC Educational Resources Information Center

Lazarev, Valeriy; Newman, Denis

2014-01-01

NCLB waiver requirements have led to development of teacher evaluation systems, in which student growth is a significant component. Recent empirical research has been focusing on metrics of student growth--value-added scores in particular--and their relationship to other metrics. An extensive set of recent teacher-evaluation studies conducted by…

Extreme Mechanics of Growing Matter

NASA Astrophysics Data System (ADS)

Kuhl, Ellen

2013-03-01

Growth is a distinguishing feature of all living things. Unlike standard materials, living matter can autonomously respond to alterations in its environment. As a result of a continuous ultrastructural turnover and renewal of cells and extracellular matrix, living matter can undergo extreme changes in composition, size, and shape within the order of months, weeks, or days. While hard matter typically adapts by increasing its density to grow strong, soft matter adapts by increasing its volume to grow large. Here we provide a state-of-the-art review of growing matter, and compare existing mathematical models for growth and remodeling of living systems. Applications are plentiful ranging from plant growth to tumor growth, from asthma in the lungs to restenosis in the vasculature, from plastic to reconstructive surgery, and from skeletal muscle adaptation to heart failure. Using these examples, we discuss current challenges and potential future directions. We hope to initiate critical discussions around the biophysical modeling of growing matter as a powerful tool to better understand biological systems in health and disease. This research has been supported by the NSF CAREER award CMMI 0952021.

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.

EGFR gene overexpression retained in an invasive xenograft model by solid orthotopic transplantation of human glioblastoma multiforme into nude mice.

PubMed

Yi, Diao; Hua, Tian Xin; Lin, Huang Yan

2011-03-01

Orthotopic xenograft animal model from human glioblastoma multiforme (GBM) cell lines often do not recapitulate an extremely important aspect of invasive growth and epidermal growth factor receptor (EGFR) gene overexpression of human GBM. We developed an orthotopic xenograft model by solid transplantation of human GBM into the brain of nude mouse. The orthotopic xenografts sharing the same histopathological features with their original human GBMs were highly invasive and retained the overexpression of EGFR gene. The murine orthotopic GBM models constitute a valuable in vivo system for preclinical studies to test novel therapies for human GBM.

A functional-structural kiwifruit vine model integrating architecture, carbon dynamics and effects of the environment.

PubMed

Cieslak, Mikolaj; Seleznyova, Alla N; Hanan, Jim

2011-04-01

Functional-structural modelling can be used to increase our understanding of how different aspects of plant structure and function interact, identify knowledge gaps and guide priorities for future experimentation. By integrating existing knowledge of the different aspects of the kiwifruit (Actinidia deliciosa) vine's architecture and physiology, our aim is to develop conceptual and mathematical hypotheses on several of the vine's features: (a) plasticity of the vine's architecture; (b) effects of organ position within the canopy on its size; (c) effects of environment and horticultural management on shoot growth, light distribution and organ size; and (d) role of carbon reserves in early shoot growth. Using the L-system modelling platform, a functional-structural plant model of a kiwifruit vine was created that integrates architectural development, mechanistic modelling of carbon transport and allocation, and environmental and management effects on vine and fruit growth. The branching pattern was captured at the individual shoot level by modelling axillary shoot development using a discrete-time Markov chain. An existing carbon transport resistance model was extended to account for several source/sink components of individual plant elements. A quasi-Monte Carlo path-tracing algorithm was used to estimate the absorbed irradiance of each leaf. Several simulations were performed to illustrate the model's potential to reproduce the major features of the vine's behaviour. The model simulated vine growth responses that were qualitatively similar to those observed in experiments, including the plastic response of shoot growth to local carbon supply, the branching patterns of two Actinidia species, the effect of carbon limitation and topological distance on fruit size and the complex behaviour of sink competition for carbon. The model is able to reproduce differences in vine and fruit growth arising from various experimental treatments. This implies it will be a valuable tool for refining our understanding of kiwifruit growth and for identifying strategies to improve production.

Population growth rates: issues and an application.

PubMed Central

Godfray, H Charles J; Rees, Mark

2002-01-01

Current issues in population dynamics are discussed in the context of The Royal Society Discussion Meeting 'Population growth rate: determining factors and role in population regulation'. In particular, different views on the centrality of population growth rates to the study of population dynamics and the role of experiments and theory are explored. Major themes emerging include the role of modern statistical techniques in bringing together experimental and theoretical studies, the importance of long-term experimentation and the need for ecology to have model systems, and the value of population growth rate as a means of understanding and predicting population change. The last point is illustrated by the application of a recently introduced technique, integral projection modelling, to study the population growth rate of a monocarpic perennial plant, its elasticities to different life-history components and the evolution of an evolutionarily stable strategy size at flowering. PMID:12396521

Modelling the effect of environmental factors on resource allocation in mixed plants systems

NASA Astrophysics Data System (ADS)

Gayler, Sebastian; Priesack, Eckart

2010-05-01

In most cases, growth of plants is determined by competition against neighbours for the local resources light, water and nutrients and by defending against herbivores and pathogens. Consequently, it is important for a plant to grow fast without neglecting defence. However, plant internal substrates and energy required to support maintenance, growth and defence are limited and the total demand for these processes cannot be met in most cases. Therefore, allocation of carbohydrates to growth related primary metabolism or to defence related secondary metabolism can be seen as a trade-off between the demand of plants for being competitive against neighbours and for being more resistant against pathogens. A modelling approach is presented which can be used to simulate competition for light, water and nutrients between plant individuals in mixed canopies. The balance of resource allocation between growth processes and synthesis of secondary compounds is modelled by a concept originating from different plant defence hypothesis. The model is used to analyse the impact of environmental factors such as soil water and nitrogen availability, planting density and atmospheric concentration of CO2 on growth of plant individuals within mixed canopies and variations in concentration of carbon-based secondary metabolites in plant tissues.

A multiphase model for tissue construct growth in a perfusion bioreactor.

PubMed

O'Dea, R D; Waters, S L; Byrne, H M

2010-06-01

The growth of a cell population within a rigid porous scaffold in a perfusion bioreactor is studied, using a three-phase continuum model of the type presented by Lemon et al. (2006, Multiphase modelling of tissue growth using the theory of mixtures. J. Math. Biol., 52, 571-594) to represent the cell population (and attendant extracellular matrix), culture medium and porous scaffold. The bioreactor system is modelled as a 2D channel containing the cell-seeded rigid porous scaffold (tissue construct) which is perfused with culture medium. The study concentrates on (i) the cell-cell and cell-scaffold interactions and (ii) the impact of mechanotransduction mechanisms on construct composition. A numerical and analytical analysis of the model equations is presented and, depending upon the relative importance of cell aggregation and repulsion, markedly different cell movement is revealed. Additionally, mechanotransduction effects due to cell density, pressure and shear stress-mediated tissue growth are shown to generate qualitative differences in the composition of the resulting construct. The results of our simulations indicate that this model formulation (in conjunction with appropriate experimental data) has the potential to provide a means of identifying the dominant regulatory stimuli in a cell population.

Taguchi method for partial differential equations with application in tumor growth.

PubMed

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.

The value of volume and growth measurements in timber sales management of the National Forests

NASA Technical Reports Server (NTRS)

Lietzke, K. R.

1977-01-01

This paper summarizes work performed in the estimation of gross social value of timber volume and growth rate information used in making regional harvest decisions in the National Forest System. A model was developed to permit parametric analysis. The problem is formulated as one of finding optimal inventory holding patterns. Public timber management differs from other inventory holding problems in that the inventory, itself, generates value over time in providing recreational, aesthetic and environmental goods. 'Nontimber' demand estimates are inferred from past Forest Service harvest and sales levels. The solution requires a description of the harvest rates which maintain the optimum inventory level. Gross benefits of the Landsat systems are estimated by comparison with Forest Service information gathering models. Gross annual benefits are estimated to be $5.9 million for the MSS system and $7.2 million for the TM system.

Large area sheet task: Advanced dendritic web growth development

NASA Technical Reports Server (NTRS)

Duncan, C. S.; Seidensticker, R. G.; Mchugh, J. P.; Hopkins, R. H.; Meier, D.; Schruben, J.

1981-01-01

The growth of silicon dendritic web for photovoltaic applications was investigated. The application of a thermal model for calculating buckling stresses as a function of temperature profile in the web is discussed. Lid and shield concepts were evaluated to provide the data base for enhancing growth velocity. An experimental web growth machine which embodies in one unit the mechanical and electronic features developed in previous work was developed. In addition, evaluation of a melt level control system was begun, along with preliminary tests of an elongated crucible design. The economic analysis was also updated to incorporate some minor cost changes. The initial applications of the thermal model to a specific configuration gave results consistent with experimental observation in terms of the initiation of buckling vs. width for a given crystal thickness.

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

PubMed

Klier, Christine

2012-03-06

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

Influence of rhizobacterial volatiles on the root system architecture and the production and allocation of biomass in the model grass Brachypodium distachyon (L.) P. Beauv.

PubMed

Delaplace, Pierre; Delory, Benjamin M; Baudson, Caroline; Mendaluk-Saunier de Cazenave, Magdalena; Spaepen, Stijn; Varin, Sébastien; Brostaux, Yves; du Jardin, Patrick

2015-08-12

Plant growth-promoting rhizobacteria are increasingly being seen as a way of complementing conventional inputs in agricultural systems. The effects on their host plants are diverse and include volatile-mediated growth enhancement. This study sought to assess the effects of bacterial volatiles on the biomass production and root system architecture of the model grass Brachypodium distachyon (L.) Beauv. An in vitro experiment allowing plant-bacteria interaction throughout the gaseous phase without any physical contact was used to screen 19 bacterial strains for their growth-promotion ability over a 10-day co-cultivation period. Five groups of bacteria were defined and characterised based on their combined influence on biomass production and root system architecture. The observed effects ranged from unchanged to greatly increased biomass production coupled with increased root length and branching. Primary root length was increased only by the volatile compounds emitted by Enterobacter cloacae JM22 and Bacillus pumilus T4. Overall, the most significant results were obtained with Bacillus subtilis GB03, which induced an 81 % increase in total biomass, as well as enhancing total root length, total secondary root length and total adventitious root length by 88.5, 201.5 and 474.5 %, respectively. This study is the first report on bacterial volatile-mediated growth promotion of a grass plant. Contrasting modulations of biomass production coupled with changes in root system architecture were observed. Most of the strains that increased total plant biomass also modulated adventitious root growth. Under our screening conditions, total biomass production was strongly correlated with the length and branching of the root system components, except for primary root length. An analysis of the emission kinetics of the bacterial volatile compounds is being undertaken and should lead to the identification of the compounds responsible for the observed growth-promotion effects. Within the context of the inherent characteristics of our in vitro system, this paper identifies the next critical experimental steps and discusses them from both a fundamental and an applied perspective.

An Application of Satir's Model to Family Counseling.

ERIC Educational Resources Information Center

Seligman, Linda

1981-01-01

Describes the use of Virginia Satir's model to family counseling, emphasizing prevention, personal growth, self-esteem, and communication in improving the functioning of the family system. Presents a case study using the model. Results indicate the family became more nurturing as a result of counseling. (JAC)

An Off-Lattice Hybrid Discrete-Continuum Model of Tumor Growth and Invasion

PubMed Central

Jeon, Junhwan; Quaranta, Vito; Cummings, Peter T.

2010-01-01

Abstract We have developed an off-lattice hybrid discrete-continuum (OLHDC) model of tumor growth and invasion. The continuum part of the OLHDC model describes microenvironmental components such as matrix-degrading enzymes, nutrients or oxygen, and extracellular matrix (ECM) concentrations, whereas the discrete portion represents individual cell behavior such as cell cycle, cell-cell, and cell-ECM interactions and cell motility by the often-used persistent random walk, which can be depicted by the Langevin equation. Using this framework of the OLHDC model, we develop a phenomenologically realistic and bio/physically relevant model that encompasses the experimentally observed superdiffusive behavior (at short times) of mammalian cells. When systemic simulations based on the OLHDC model are performed, tumor growth and its morphology are found to be strongly affected by cell-cell adhesion and haptotaxis. There is a combination of the strength of cell-cell adhesion and haptotaxis in which fingerlike shapes, characteristic of invasive tumor, are observed. PMID:20074513

Inhibition of non-small cell lung cancer (NSCLC) growth by a novel small molecular inhibitor of EGFR

PubMed Central

Fang, Yuanzhang; Vaughn, Amanda; Cai, Xiaopan; Xu, Leqin; Wan, Wei; Li, Zhenxi; Chen, Shijie; Yang, Xinghai; Wu, Song; Xiao, Jianru

2015-01-01

The epidermal growth factor receptor (EGFR) is a therapeutic target (oncotarget) in NSCLC. Using in vitro EGFR kinase activity system, we identified a novel small molecule, WB-308, as an inhibitor of EGFR. WB-308 decreased NSCLC cell proliferation and colony formation, by causing G2/M arrest and apoptosis. Furthermore, WB-308 inhibited the engraft tumor growths in two animal models in vivo (lung orthotopic transplantation model and patient-derived engraft mouse model). WB-308 impaired the phosphorylation of EGFR, AKT, and ERK1/2 protein. WB-308 was less cytotoxic than Gefitinib. Our study suggests that WB-308 is a novel EGFR-TKI and may be considered to substitute for Gefitinib in clinical therapy for NSCLC. PMID:25730907

Time-dependent probability density functions and information geometry in stochastic logistic and Gompertz models

NASA Astrophysics Data System (ADS)

Tenkès, Lucille-Marie; Hollerbach, Rainer; Kim, Eun-jin

2017-12-01

A probabilistic description is essential for understanding growth processes in non-stationary states. In this paper, we compute time-dependent probability density functions (PDFs) in order to investigate stochastic logistic and Gompertz models, which are two of the most popular growth models. We consider different types of short-correlated multiplicative and additive noise sources and compare the time-dependent PDFs in the two models, elucidating the effects of the additive and multiplicative noises on the form of PDFs. We demonstrate an interesting transition from a unimodal to a bimodal PDF as the multiplicative noise increases for a fixed value of the additive noise. A much weaker (leaky) attractor in the Gompertz model leads to a significant (singular) growth of the population of a very small size. We point out the limitation of using stationary PDFs, mean value and variance in understanding statistical properties of the growth in non-stationary states, highlighting the importance of time-dependent PDFs. We further compare these two models from the perspective of information change that occurs during the growth process. Specifically, we define an infinitesimal distance at any time by comparing two PDFs at times infinitesimally apart and sum these distances in time. The total distance along the trajectory quantifies the total number of different states that the system undergoes in time, and is called the information length. We show that the time-evolution of the two models become more similar when measured in units of the information length and point out the merit of using the information length in unifying and understanding the dynamic evolution of different growth processes.

Evaluation of a whole-farm model for pasture-based dairy systems.

PubMed

Beukes, P C; Palliser, C C; Macdonald, K A; Lancaster, J A S; Levy, G; Thorrold, B S; Wastney, M E

2008-06-01

In the temperate climate of New Zealand, animals can be grazed outdoors all year round. The pasture is supplemented with conserved feed, with the amount being determined by seasonal pasture growth, genetics of the herd, and stocking rate. The large number of factors that affect production makes it impractical and expensive to use field trials to explore all the farm system options. A model of an in situ-grazed pasture system has been developed to provide a tool for developing and testing novel farm systems; for example, different levels of bought-in supplements and different levels of nitrogen fertilizer application, to maintain sustainability or environmental integrity and profitability. It consists of a software framework that links climate information, on a daily basis, with dynamic, mechanistic component-models for pasture growth and animal metabolism, as well as management policies. A unique feature is that the component models were developed and published by other groups, and are retained in their original software language. The aim of this study was to compare the model, called the whole-farm model (WFM) with a farm trial that was conducted over 3 yr and in which data were collected specifically for evaluating the WFM. Data were used from the first year to develop the WFM and data from the second and third year to evaluate the model. The model predicted annual pasture production, end-of-season cow liveweight, cow body condition score, and pasture cover across season with relative prediction error <20%. Milk yield and milksolids (fat + protein) were overpredicted by approximately 30% even though both annual and monthly pasture and supplement intake were predicted with acceptable accuracy, suggesting that the metabolic conversion of feed to fat, protein, and lactose in the mammary gland needs to be refined. Because feed growth and intake predictions were acceptable, economic predictions can be made using the WFM, with an adjustment for milk yield, to test different management policies, alterations in climate, or the use of genetically improved animals, pastures, or crops.

Modeling of subglacial hydrological development following rapid supraglacial lake drainage.

PubMed

Dow, C F; Kulessa, B; Rutt, I C; Tsai, V C; Pimentel, S; Doyle, S H; van As, D; Lindbäck, K; Pettersson, R; Jones, G A; Hubbard, A

2015-06-01

The rapid drainage of supraglacial lakes injects substantial volumes of water to the bed of the Greenland ice sheet over short timescales. The effect of these water pulses on the development of basal hydrological systems is largely unknown. To address this, we develop a lake drainage model incorporating both (1) a subglacial radial flux element driven by elastic hydraulic jacking and (2) downstream drainage through a linked channelized and distributed system. Here we present the model and examine whether substantial, efficient subglacial channels can form during or following lake drainage events and their effect on the water pressure in the surrounding distributed system. We force the model with field data from a lake drainage site, 70 km from the terminus of Russell Glacier in West Greenland. The model outputs suggest that efficient subglacial channels do not readily form in the vicinity of the lake during rapid drainage and instead water is evacuated primarily by a transient turbulent sheet and the distributed system. Following lake drainage, channels grow but are not large enough to reduce the water pressure in the surrounding distributed system, unless preexisting channels are present throughout the domain. Our results have implications for the analysis of subglacial hydrological systems in regions where rapid lake drainage provides the primary mechanism for surface-to-bed connections. Model for subglacial hydrological analysis of rapid lake drainage eventsLimited subglacial channel growth during and following rapid lake drainagePersistence of distributed drainage in inland areas where channel growth is limited.