Growing up and Role Modeling: A Theory in Iranian Nursing Students’ Education

PubMed Central

Nouri, Jamileh Mokhtari; Ebadi, Abbas; Alhani, Fatemeh; Rejeh, Nahid

2015-01-01

One of the key strategies in students’ learning is being affected by models. Understanding the role-modeling process in education will help to make greater use of this training strategy. The aim of this grounded theory study was to explore Iranian nursing students and instructors’ experiences about role modeling process. Data was analyzed by Glaserian’s Grounded Theory methodology through semi-structured interviews with 7 faculty members, 2 nursing students; the three focus group discussions with 20 nursing students based on purposive and theoretical sampling was done for explaining role modeling process from four nursing faculties in Tehran. Through basic coding, an effort to comprehensive growth and excellence was made with the basic social process consisting the core category and through selective coding three phases were identified as: realizing and exposure to inadequate human and professional growth, facilitating human and professional growth and evolution. The role modeling process is taking place unconscious, involuntary, dynamic and with positive progressive process in order to facilitate overall growth in nursing student. Accordingly, the design and implementation of the designed model can be used to make this unconscious to conscious, active and voluntarily processes a process to help education administrators of nursing colleges and supra organization to prevent threats to human and professional in nursing students’ education and promote nursing students’ growth. PMID:25716391

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.

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

PubMed

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

2008-05-01

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

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

PubMed Central

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

2008-01-01

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

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

PubMed

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

2013-01-01

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

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

PubMed Central

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

2013-01-01

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

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

Treesearch

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

1990-01-01

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

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

ERIC Educational Resources Information Center

Pirie, Susan; Kieren, Thomas

1994-01-01

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

Mistletoe-induced growth reductions at the forest stand scale.

PubMed

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

2018-05-01

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

Single Plant Root System Modeling under Soil Moisture Variation

NASA Astrophysics Data System (ADS)

Yabusaki, S.; Fang, Y.; Chen, X.; Scheibe, T. D.

2016-12-01

A prognostic Virtual Plant-Atmosphere-Soil System (vPASS) model is being developed that integrates comprehensively detailed mechanistic single plant modeling with microbial, atmospheric, and soil system processes in its immediate environment. Three broad areas of process module development are targeted: Incorporating models for root growth and function, rhizosphere interactions with bacteria and other organisms, litter decomposition and soil respiration into established porous media flow and reactive transport models Incorporating root/shoot transport, growth, photosynthesis and carbon allocation process models into an integrated plant physiology model Incorporating transpiration, Volatile Organic Compounds (VOC) emission, particulate deposition and local atmospheric processes into a coupled plant/atmosphere model. The integrated plant ecosystem simulation capability is being developed as open source process modules and associated interfaces under a modeling framework. The initial focus addresses the coupling of root growth, vascular transport system, and soil under drought scenarios. Two types of root water uptake modeling approaches are tested: continuous root distribution and constitutive root system architecture. The continuous root distribution models are based on spatially averaged root development process parameters, which are relatively straightforward to accommodate in the continuum soil flow and reactive transport module. Conversely, the constitutive root system architecture models use root growth rates, root growth direction, and root branching to evolve explicit root geometries. The branching topologies require more complex data structures and additional input parameters. Preliminary results are presented for root model development and the vascular response to temporal and spatial variations in soil conditions.

Modeling Physiological Processes That Relate Toxicant Exposure and Bacterial Population Dynamics

PubMed Central

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

2012-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

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.

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

NASA Astrophysics Data System (ADS)

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

2017-07-01

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

Unravelling the Gordian knot! Key processes impacting overwintering larval survival and growth: A North Sea herring case study

NASA Astrophysics Data System (ADS)

Hufnagl, Marc; Peck, Myron A.; Nash, Richard D. M.; Dickey-Collas, Mark

2015-11-01

Unraveling the key processes affecting marine fish recruitment will ultimately require a combination of field, laboratory and modelling studies. We combined analyzes of long-term (30-year) field data on larval fish abundance, distribution and length, and biophysical model simulations of different levels of complexity to identify processes impacting the survival and growth of autumn- and winter-spawned Atlantic herring (Clupea harengus) larvae. Field survey data revealed interannual changes in intensity of utilization of the five major spawning grounds (Orkney/Shetland, Buchan, Banks north, Banks south, and Downs) as well as spatio-temporal variability in the length and abundance of overwintered larvae. The mean length of larvae captured in post-winter surveys was negatively correlated to the proportion of larvae from the southern-most (Downs) winter-spawning component. Furthermore, the mean length of larvae originating from all spawning components has decreased since 1990 suggesting ecosystem-wide changes impacting larval growth potential, most likely due to changes in prey fields. A simple biophysical model assuming temperature-dependent growth and constant mortality underestimated larval growth rates suggesting that larval mortality rates steeply declined with increasing size and/or age during winter as no match with field data could be obtained. In contrast better agreement was found between observed and modelled post-winter abundance for larvae originating from four spawning components when a more complex, physiological-based foraging and growth model was employed using a suite of potential prey field and size-based mortality scenarios. Nonetheless, agreement between field and model-derived estimates was poor for larvae originating from the winter-spawned Downs component. In North Sea herring, the dominant processes impacting larval growth and survival appear to have shifted in time and space highlighting how environmental forcing, ecosystem state and other factors can form a Gordian knot of marine fish recruitment processes. We highlight gaps in process knowledge and recommend specific field, laboratory and modelling studies which, in our opinion, are most likely to unravel the dominant processes and advance predictive capacity of the environmental regulation of recruitment in autumn and winter-spawned fishes in temperate areas such as herring in the North Sea.

Monte Carlo grain growth modeling with local temperature gradients

NASA Astrophysics Data System (ADS)

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

2017-09-01

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

A kinetic Monte Carlo simulation method of van der Waals epitaxy for atomistic nucleation-growth processes of transition metal dichalcogenides.

PubMed

Nie, Yifan; Liang, Chaoping; Cha, Pil-Ryung; Colombo, Luigi; Wallace, Robert M; Cho, Kyeongjae

2017-06-07

Controlled growth of crystalline solids is critical for device applications, and atomistic modeling methods have been developed for bulk crystalline solids. Kinetic Monte Carlo (KMC) simulation method provides detailed atomic scale processes during a solid growth over realistic time scales, but its application to the growth modeling of van der Waals (vdW) heterostructures has not yet been developed. Specifically, the growth of single-layered transition metal dichalcogenides (TMDs) is currently facing tremendous challenges, and a detailed understanding based on KMC simulations would provide critical guidance to enable controlled growth of vdW heterostructures. In this work, a KMC simulation method is developed for the growth modeling on the vdW epitaxy of TMDs. The KMC method has introduced full material parameters for TMDs in bottom-up synthesis: metal and chalcogen adsorption/desorption/diffusion on substrate and grown TMD surface, TMD stacking sequence, chalcogen/metal ratio, flake edge diffusion and vacancy diffusion. The KMC processes result in multiple kinetic behaviors associated with various growth behaviors observed in experiments. Different phenomena observed during vdW epitaxy process are analysed in terms of complex competitions among multiple kinetic processes. The KMC method is used in the investigation and prediction of growth mechanisms, which provide qualitative suggestions to guide experimental study.

Modeling of the HiPco process for carbon nanotube production. II. Reactor-scale analysis

NASA Technical Reports Server (NTRS)

Gokcen, Tahir; Dateo, Christopher E.; Meyyappan, M.

2002-01-01

The high-pressure carbon monoxide (HiPco) process, developed at Rice University, has been reported to produce single-walled carbon nanotubes from gas-phase reactions of iron carbonyl in carbon monoxide at high pressures (10-100 atm). Computational modeling is used here to develop an understanding of the HiPco process. A detailed kinetic model of the HiPco process that includes of the precursor, decomposition metal cluster formation and growth, and carbon nanotube growth was developed in the previous article (Part I). Decomposition of precursor molecules is necessary to initiate metal cluster formation. The metal clusters serve as catalysts for carbon nanotube growth. The diameter of metal clusters and number of atoms in these clusters are some of the essential information for predicting carbon nanotube formation and growth, which is then modeled by the Boudouard reaction with metal catalysts. Based on the detailed model simulations, a reduced kinetic model was also developed in Part I for use in reactor-scale flowfield calculations. Here this reduced kinetic model is integrated with a two-dimensional axisymmetric reactor flow model to predict reactor performance. Carbon nanotube growth is examined with respect to several process variables (peripheral jet temperature, reactor pressure, and Fe(CO)5 concentration) with the use of the axisymmetric model, and the computed results are compared with existing experimental data. The model yields most of the qualitative trends observed in the experiments and helps to understanding the fundamental processes in HiPco carbon nanotube production.

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

NASA Astrophysics Data System (ADS)

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

2017-02-01

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

Population balance modeling: current status and future prospects.

PubMed

Ramkrishna, Doraiswami; Singh, Meenesh R

2014-01-01

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

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

Treesearch

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

2014-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2002-04-01

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

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

PubMed

Verduzco Chavez, B

1991-01-01

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

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

PubMed

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

2015-01-01

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

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

PubMed Central

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

2015-01-01

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

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

Treesearch

A. Weiskittel; D. Maguire; R. Monserud

2007-01-01

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

A new generic plant growth model framework (PMF): Simulating distributed dynamic interaction of biomass production and its interaction with water and nutrients fluxes

NASA Astrophysics Data System (ADS)

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

2010-05-01

Today, crop models have a widespread application in natural sciences, because plant growth interacts and modifies the environment. Transport processes involve water and nutrient uptake from the saturated and unsaturated zone in the pedosphere. Turnover processes include the conversion of dead root biomass into organic matter. Transpiration and the interception of radiation influence the energy exchange between atmosphere and biosphere. But many more feedback mechanisms might be of interest, including erosion, soil compaction or trace gas exchanges. Most of the existing crop models have a closed structure and do not provide interfaces or code design elements for easy data transfer or process exchange with other models during runtime. Changes in the model structure, the inclusion of alternative process descriptions or the implementation of additional functionalities requires a lot of coding. The same is true if models are being upscaled from field to landscape or catchment scale. We therefore conclude that future integrated model developments would benefit from a model structure that has the following requirements: replaceability, expandability and independency. In addition to these requirements we also propose the interactivity of models, which means that models that are being coupled are highly interacting and depending on each other, i.e. the model should be open for influences from other independent models and react on influences directly. Hence, a model which consists of building blocks seems to be reasonable. The aim of the study is the presentation of the new crop model type, the plant growth model framework, PMF. The software concept refers to an object-oriented approach, which is developed with the Unified Modeling Language (UML). The model is implemented with Python, a high level object-oriented programming language. The integration of the models with a setup code enables the data transfer on the computer memory level and direct exchange of information about changing boundary conditions. The crop model concept refers to two main elements. A plant model, which represents an abstract network of plant organs and processes and a process library, which holds mathematical solutions for the growth processes. Growth processes were mainly taken from existing, well known crop models such as SUCROS and CERES. The crop specific properties of root architecture are described based on a maximum rooting depth and a vertical growth rate. The biomass distribution depends on an interactive allocation process due to the soil layers with a daily time step. In order to show the performance and capabilities of PMF, the model is coupled with the Catchment Modeling Framework (CMF) and the simple nitrogen mineralization model DeComp. The main feature of the integrated model set up is the interaction between root growth, water uptake and nitrogen supply of the soil. We show a virtual case study on the hillslope scale and spatially dependence of water and nitrogen stress based on topographic position and seasonal development.

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

PubMed

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

2012-06-01

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

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

PubMed

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

2014-01-01

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

The fiber walk: a model of tip-driven growth with lateral expansion.

PubMed

Bucksch, Alexander; Turk, Greg; Weitz, Joshua S

2014-01-01

Tip-driven growth processes underlie the development of many plants. To date, tip-driven growth processes have been modeled as an elongating path or series of segments, without taking into account lateral expansion during elongation. Instead, models of growth often introduce an explicit thickness by expanding the area around the completed elongated path. Modeling expansion in this way can lead to contradictions in the physical plausibility of the resulting surface and to uncertainty about how the object reached certain regions of space. Here, we introduce fiber walks as a self-avoiding random walk model for tip-driven growth processes that includes lateral expansion. In 2D, the fiber walk takes place on a square lattice and the space occupied by the fiber is modeled as a lateral contraction of the lattice. This contraction influences the possible subsequent steps of the fiber walk. The boundary of the area consumed by the contraction is derived as the dual of the lattice faces adjacent to the fiber. We show that fiber walks generate fibers that have well-defined curvatures, and thus enable the identification of the process underlying the occupancy of physical space. Hence, fiber walks provide a base from which to model both the extension and expansion of physical biological objects with finite thickness.

The Fiber Walk: A Model of Tip-Driven Growth with Lateral Expansion

PubMed Central

Bucksch, Alexander; Turk, Greg; Weitz, Joshua S.

2014-01-01

Tip-driven growth processes underlie the development of many plants. To date, tip-driven growth processes have been modeled as an elongating path or series of segments, without taking into account lateral expansion during elongation. Instead, models of growth often introduce an explicit thickness by expanding the area around the completed elongated path. Modeling expansion in this way can lead to contradictions in the physical plausibility of the resulting surface and to uncertainty about how the object reached certain regions of space. Here, we introduce fiber walks as a self-avoiding random walk model for tip-driven growth processes that includes lateral expansion. In 2D, the fiber walk takes place on a square lattice and the space occupied by the fiber is modeled as a lateral contraction of the lattice. This contraction influences the possible subsequent steps of the fiber walk. The boundary of the area consumed by the contraction is derived as the dual of the lattice faces adjacent to the fiber. We show that fiber walks generate fibers that have well-defined curvatures, and thus enable the identification of the process underlying the occupancy of physical space. Hence, fiber walks provide a base from which to model both the extension and expansion of physical biological objects with finite thickness. PMID:24465607

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

PubMed

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

2015-11-01

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

A kinetic modeling of chondrocyte culture for manufacture of tissue-engineered cartilage.

PubMed

Kino-Oka, Masahiro; Maeda, Yoshikatsu; Yamamoto, Takeyuki; Sugawara, Katsura; Taya, Masahito

2005-03-01

For repairing articular cartilage defects, innovative techniques based on tissue engineering have been developed and are now entering into the practical stage of clinical application by means of grafting in vitro cultured products. A variety of natural and artificial materials available for scaffolds, which permit chondrocyte cells to aggregate, have been designed for their ability to promote cell growth and differentiation. From the viewpoint of the manufacturing process for tissue-engineered cartilage, the diverse nature of raw materials (seeding cells) and end products (cultured cartilage) oblige us to design a tailor-made process with less reproducibility, which is an obstacle to establishing a production doctrine based on bioengineering knowledge concerning growth kinetics and modeling as well as designs of bioreactors and culture operations for certification of high product quality. In this article, we review the recent advances in the manufacturing of tissue-engineered cartilage. After outlining the manufacturing processes for tissue-engineered cartilage in the first section, the second and third sections, respectively, describe the three-dimensional culture of chondrocytes with Aterocollagen gel and kinetic model consideration as a tool for evaluating this culture process. In the final section, culture strategy is discussed in terms of the combined processes of monolayer growth (ex vivo chondrocyte cell expansion) and three-dimensional growth (construction of cultured cartilage in the gel).

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.

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

PubMed

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

1996-03-20

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

Cellular automata-based modelling and simulation of biofilm structure on multi-core computers.

PubMed

Skoneczny, Szymon

2015-01-01

The article presents a mathematical model of biofilm growth for aerobic biodegradation of a toxic carbonaceous substrate. Modelling of biofilm growth has fundamental significance in numerous processes of biotechnology and mathematical modelling of bioreactors. The process following double-substrate kinetics with substrate inhibition proceeding in a biofilm has not been modelled so far by means of cellular automata. Each process in the model proposed, i.e. diffusion of substrates, uptake of substrates, growth and decay of microorganisms and biofilm detachment, is simulated in a discrete manner. It was shown that for flat biofilm of constant thickness, the results of the presented model agree with those of a continuous model. The primary outcome of the study was to propose a mathematical model of biofilm growth; however a considerable amount of focus was also placed on the development of efficient algorithms for its solution. Two parallel algorithms were created, differing in the way computations are distributed. Computer programs were created using OpenMP Application Programming Interface for C++ programming language. Simulations of biofilm growth were performed on three high-performance computers. Speed-up coefficients of computer programs were compared. Both algorithms enabled a significant reduction of computation time. It is important, inter alia, in modelling and simulation of bioreactor dynamics.

Examining the effect of down regulation under high [CO2] on the growth of soybean assimilating a semi process-based model and FACE data

NASA Astrophysics Data System (ADS)

Sakurai, G.; Iizumi, T.; Yokozawa, M.

2011-12-01

The actual impact of elevated [CO2] with the interaction of the other climatic factors on the crop growth is still debated. In many process-based crop models, the response of photosynthesis per single leaf to environmental factors is basically described using the biochemical model of Farquhar et al. (1980). However, the decline in photosynthetic enhancement known as down regulation has not been taken into account. On the other hand, the mechanisms causing photosynthetic down regulation is still unknown, which makes it difficult to include the effect of down regulation into process-based crop models. The current results of Free-air CO2 enrichment (FACE) experiments have reported the effect of down regulation under actual environments. One of the effective approaches to involve these results into future crop yield prediction is developing a semi process-based crop growth model, which includes the effect of photosynthetic down regulation as a statistical model, and assimilating the data obtained in FACE experiments. In this study, we statistically estimated the parameters of a semi process-based model for soybean growth ('SPM-soybean') using a hierarchical Baysian method with the FACE data on soybeans (Morgan et al. 2005). We also evaluated the effect of down regulation on the soybean yield in future climatic conditions. The model selection analysis showed that the effective correction to the overestimation of the Farquhar's biochemical C3 model was to reduce the maximum rate of carboxylation (Vcmax) under elevated [CO2]. However, interestingly, the difference in the estimated final crop yields between the corrected model and the non-corrected model was very slight (Fig.1a) for future projection under climate change scenario (Miroc-ESM). This was due to that the reduction in Vcmax also brought about the reduction of the base dark respiration rate of leaves. Because the dark respiration rate exponentially increases with temperature, the slight difference in base respiration rate becomes a large difference under high temperature under the future climate scenarios. In other words, if the temperature rise is very small or zero under elevated [CO2] condition, the effect of down regulation significantly appears (Fig.1b). This result suggest that further experimental data that considering high CO2 effect and high temperature effect in field conditions should be important and elaborate the model projection of the future crop yield through data assimilation method.

Research on animation design of growing plant based on 3D MAX technology

NASA Astrophysics Data System (ADS)

Chen, Yineng; Fang, Kui; Bu, Weiqiong; Zhang, Xiaoling; Lei, Menglong

In view of virtual plant has practical demands on quality, image and degree of realism animation in growing process of plant, this thesis design the animation based on mechanism and regularity of plant growth, and propose the design method based on 3D MAX technology. After repeated analysis and testing, it is concluded that there are modeling, rendering, animation fabrication and other key technologies in the animation design process. Based on this, designers can subdivid the animation into seed germination animation, plant growth prophase animation, catagen animation, later animation and blossom animation. This paper compounds the animation of these five stages by VP window to realize the completed 3D animation. Experimental result shows that the animation can realized rapid, visual and realistic simulatation the plant growth process.

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.

Effects of microscale inertia on dynamic ductile crack growth

NASA Astrophysics Data System (ADS)

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

2012-04-01

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

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

NASA Astrophysics Data System (ADS)

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

2014-05-01

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

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

NASA Astrophysics Data System (ADS)

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

2013-12-01

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

Global sensitivity analysis of DRAINMOD-FOREST, an integrated forest ecosystem model

Treesearch

Shiying Tian; Mohamed A. Youssef; Devendra M. Amatya; Eric D. Vance

2014-01-01

Global sensitivity analysis is a useful tool to understand process-based ecosystem models by identifying key parameters and processes controlling model predictions. This study reported a comprehensive global sensitivity analysis for DRAINMOD-FOREST, an integrated model for simulating water, carbon (C), and nitrogen (N) cycles and plant growth in lowland forests. The...

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

NASA Astrophysics Data System (ADS)

Barraza-Barraza, Diana; Tercero-Gómez, Víctor G.; Beruvides, Mario G.; Limón-Robles, Jorge

2017-01-01

A wide variety of Condition-Based Maintenance (CBM) techniques deal with the problem of predicting the time for an asset fault. Most statistical approaches rely on historical failure data that might not be available in several practical situations. To address this issue, practitioners might require the use of self-starting approaches that consider only the available knowledge about the current degradation process and the asset operating context to update the prognostic model. Some authors use Autoregressive (AR) models for this purpose that are adequate when the asset operating context is constant, however, if it is variable, the accuracy of the models can be affected. In this paper, three autoregressive models with exogenous variables (ARX) were constructed, and their capability to estimate the remaining useful life (RUL) of a process was evaluated following the case of the aluminum crack growth problem. An existing stochastic model of aluminum crack growth was implemented and used to assess RUL estimation performance of the proposed ARX models through extensive Monte Carlo simulations. Point and interval estimations were made based only on individual history, behavior, operating conditions and failure thresholds. Both analytic and bootstrapping techniques were used in the estimation process. Finally, by including recursive parameter estimation and a forgetting factor, the ARX methodology adapts to changing operating conditions and maintain the focus on the current degradation level of an asset.

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

Treesearch

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

2015-01-01

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

A Crack Growth Evaluation Method for Interacting Multiple Cracks

NASA Astrophysics Data System (ADS)

Kamaya, Masayuki

When stress corrosion cracking or corrosion fatigue occurs, multiple cracks are frequently initiated in the same area. According to section XI of the ASME Boiler and Pressure Vessel Code, multiple cracks are considered as a single combined crack in crack growth analysis, if the specified conditions are satisfied. In crack growth processes, however, no prescription for the interference between multiple cracks is given in this code. The JSME Post-Construction Code, issued in May 2000, prescribes the conditions of crack coalescence in the crack growth process. This study aimed to extend this prescription to more general cases. A simulation model was applied, to simulate the crack growth process, taking into account the interference between two cracks. This model made it possible to analyze multiple crack growth behaviors for many cases (e. g. different relative position and length) that could not be studied by experiment only. Based on these analyses, a new crack growth analysis method was suggested for taking into account the interference between multiple cracks.

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

PubMed

Aßmann, Christian; Hermanussen, Michael

2013-07-01

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

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.

Numerical Simulation and Experimental Casting of Nickel-Based Single-Crystal Superalloys by HRS and LMC Directional Solidification Processes

NASA Astrophysics Data System (ADS)

Yan, Xuewei; Wang, Run'nan; Xu, Qingyan; Liu, Baicheng

2017-04-01

Mathematical models for dynamic heat radiation and convection boundary in directional solidification processes are established to simulate the temperature fields. Cellular automaton (CA) method and Kurz-Giovanola-Trivedi (KGT) growth model are used to describe nucleation and growth. Primary dendritic arm spacing (PDAS) and secondary dendritic arm spacing (SDAS) are calculated by the Ma-Sham (MS) and Furer-Wunderlin (FW) models respectively. The mushy zone shape is investigated based on the temperature fields, for both high-rate solidification (HRS) and liquid metal cooling (LMC) processes. The evolution of the microstructure and crystallographic orientation are analyzed by simulation and electron back-scattered diffraction (EBSD) technique, respectively. Comparison of the simulation results from PDAS and SDAS with experimental results reveals a good agreement with each other. The results show that LMC process can provide both dendritic refinement and superior performance for castings due to the increased cooling rate and thermal gradient.

Simulation of wheat growth and development based on organ-level photosynthesis and assimilate allocation.

PubMed

Evers, J B; Vos, J; Yin, X; Romero, P; van der Putten, P E L; Struik, P C

2010-05-01

Intimate relationships exist between form and function of plants, determining many processes governing their growth and development. However, in most crop simulation models that have been created to simulate plant growth and, for example, predict biomass production, plant structure has been neglected. In this study, a detailed simulation model of growth and development of spring wheat (Triticum aestivum) is presented, which integrates degree of tillering and canopy architecture with organ-level light interception, photosynthesis, and dry-matter partitioning. An existing spatially explicit 3D architectural model of wheat development was extended with routines for organ-level microclimate, photosynthesis, assimilate distribution within the plant structure according to organ demands, and organ growth and development. Outgrowth of tiller buds was made dependent on the ratio between assimilate supply and demand of the plants. Organ-level photosynthesis, biomass production, and bud outgrowth were simulated satisfactorily. However, to improve crop simulation results more efforts are needed mechanistically to model other major plant physiological processes such as nitrogen uptake and distribution, tiller death, and leaf senescence. Nevertheless, the work presented here is a significant step forwards towards a mechanistic functional-structural plant model, which integrates plant architecture with key plant processes.

Localisation in a Growth Model with Interaction

NASA Astrophysics Data System (ADS)

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

2018-05-01

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

Localisation in a Growth Model with Interaction

NASA Astrophysics Data System (ADS)

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

2018-06-01

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

Heterogeneously Catalyzed Endothermic Fuel Cracking

DTIC Science & Technology

2016-08-28

Much of this literature is in the context of gas -to- liquids technology and industrial dehydrogenation processes. Based on the published measurements...certain zeolites. Comparisons of conversion, major product distributions and molecular weight growth processes in the gas -phase pyrolysis of model...thereby maximizing the extent of cooling, (b) increase catalyst activity for fuel decomposition, but inhibit gas -phase molecular weight growth

Integration and scaling of UV-B radiation effects on plants: from molecular interactions to whole plant responses.

PubMed

Suchar, Vasile Alexandru; Robberecht, Ronald

2016-07-01

A process based model integrating the effects of UV-B radiation to molecular level processes and their consequences to whole plant growth and development was developed from key parameters in the published literature. Model simulations showed that UV-B radiation induced changes in plant metabolic and/or photosynthesis rates can result in plant growth inhibitions. The costs of effective epidermal UV-B radiation absorptive compounds did not result in any significant changes in plant growth, but any associated metabolic costs effectively reduced the potential plant biomass. The model showed significant interactions between UV-B radiation effects and temperature and any factor leading to inhibition of photosynthetic production or plant growth during the midday, but the effects were not cumulative for all factors. Vegetative growth were significantly delayed in species that do not exhibit reproductive cycles during a growing season, but vegetative growth and reproductive yield in species completing their life cycle in one growing season did not appear to be delayed more than 2-5 days, probably within the natural variability of the life cycles for many species. This is the first model to integrate the effects of increased UV-B radiation through molecular level processes and their consequences to whole plant growth and development.

A structurally based analytic model for estimation of biomass and fuel loads of woodland trees

Treesearch

Robin J. Tausch

2009-01-01

Allometric/structural relationships in tree crowns are a consequence of the physical, physiological, and fluid conduction processes of trees, which control the distribution, efficient support, and growth of foliage in the crown. The structural consequences of these processes are used to develop an analytic model based on the concept of branch orders. A set of...

Separation of time scales in one-dimensional directed nucleation-growth processes

NASA Astrophysics Data System (ADS)

Pierobon, Paolo; Miné-Hattab, Judith; Cappello, Giovanni; Viovy, Jean-Louis; Lagomarsino, Marco Cosentino

2010-12-01

Proteins involved in homologous recombination such as RecA and hRad51 polymerize on single- and double-stranded DNA according to a nucleation-growth kinetics, which can be monitored by single-molecule in vitro assays. The basic models currently used to extract biochemical rates rely on ensemble averages and are typically based on an underlying process of bidirectional polymerization, in contrast with the often observed anisotropic polymerization of similar proteins. For these reasons, if one considers single-molecule experiments, the available models are useful to understand observations only in some regimes. In particular, recent experiments have highlighted a steplike polymerization kinetics. The classical model of one-dimensional nucleation growth, the Kolmogorov-Avrami-Mehl-Johnson (KAMJ) model, predicts the correct polymerization kinetics only in some regimes and fails to predict the steplike behavior. This work illustrates by simulations and analytical arguments the limitation of applicability of the KAMJ description and proposes a minimal model for the statistics of the steps based on the so-called stick-breaking stochastic process. We argue that this insight might be useful to extract information on the time and length scales involved in the polymerization kinetics.

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

PubMed

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

2017-06-01

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

A functional-structural model of rice linking quantitative genetic information with morphological development and physiological processes.

PubMed

Xu, Lifeng; Henke, Michael; Zhu, Jun; Kurth, Winfried; Buck-Sorlin, Gerhard

2011-04-01

Although quantitative trait loci (QTL) analysis of yield-related traits for rice has developed rapidly, crop models using genotype information have been proposed only relatively recently. As a first step towards a generic genotype-phenotype model, we present here a three-dimensional functional-structural plant model (FSPM) of rice, in which some model parameters are controlled by functions describing the effect of main-effect and epistatic QTLs. The model simulates the growth and development of rice based on selected ecophysiological processes, such as photosynthesis (source process) and organ formation, growth and extension (sink processes). It was devised using GroIMP, an interactive modelling platform based on the Relational Growth Grammar formalism (RGG). RGG rules describe the course of organ initiation and extension resulting in final morphology. The link between the phenotype (as represented by the simulated rice plant) and the QTL genotype was implemented via a data interface between the rice FSPM and the QTLNetwork software, which computes predictions of QTLs from map data and measured trait data. Using plant height and grain yield, it is shown how QTL information for a given trait can be used in an FSPM, computing and visualizing the phenotypes of different lines of a mapping population. Furthermore, we demonstrate how modification of a particular trait feeds back on the entire plant phenotype via the physiological processes considered. We linked a rice FSPM to a quantitative genetic model, thereby employing QTL information to refine model parameters and visualizing the dynamics of development of the entire phenotype as a result of ecophysiological processes, including the trait(s) for which genetic information is available. Possibilities for further extension of the model, for example for the purposes of ideotype breeding, are discussed.

A functional–structural model of rice linking quantitative genetic information with morphological development and physiological processes

PubMed Central

Xu, Lifeng; Henke, Michael; Zhu, Jun; Kurth, Winfried; Buck-Sorlin, Gerhard

2011-01-01

Background and Aims Although quantitative trait loci (QTL) analysis of yield-related traits for rice has developed rapidly, crop models using genotype information have been proposed only relatively recently. As a first step towards a generic genotype–phenotype model, we present here a three-dimensional functional–structural plant model (FSPM) of rice, in which some model parameters are controlled by functions describing the effect of main-effect and epistatic QTLs. Methods The model simulates the growth and development of rice based on selected ecophysiological processes, such as photosynthesis (source process) and organ formation, growth and extension (sink processes). It was devised using GroIMP, an interactive modelling platform based on the Relational Growth Grammar formalism (RGG). RGG rules describe the course of organ initiation and extension resulting in final morphology. The link between the phenotype (as represented by the simulated rice plant) and the QTL genotype was implemented via a data interface between the rice FSPM and the QTLNetwork software, which computes predictions of QTLs from map data and measured trait data. Key Results Using plant height and grain yield, it is shown how QTL information for a given trait can be used in an FSPM, computing and visualizing the phenotypes of different lines of a mapping population. Furthermore, we demonstrate how modification of a particular trait feeds back on the entire plant phenotype via the physiological processes considered. Conclusions We linked a rice FSPM to a quantitative genetic model, thereby employing QTL information to refine model parameters and visualizing the dynamics of development of the entire phenotype as a result of ecophysiological processes, including the trait(s) for which genetic information is available. Possibilities for further extension of the model, for example for the purposes of ideotype breeding, are discussed. PMID:21247905

Integrated modeling and heat treatment simulation of austempered ductile iron

NASA Astrophysics Data System (ADS)

Hepp, E.; Hurevich, V.; Schäfer, W.

2012-07-01

The integrated modeling and simulation of the casting and heat treatment processes for producing austempered ductile iron (ADI) castings is presented. The focus is on describing different models to simulate the austenitization, quenching and austempering steps during ADI heat treatment. The starting point for the heat treatment simulation is the simulated microstructure after solidification and cooling. The austenitization model considers the transformation of the initial ferrite-pearlite matrix into austenite as well as the dissolution of graphite in austenite to attain a uniform carbon distribution. The quenching model is based on measured CCT diagrams. Measurements have been carried out to obtain these diagrams for different alloys with varying Cu, Ni and Mo contents. The austempering model includes nucleation and growth kinetics of the ADI matrix. The model of ADI nucleation is based on experimental measurements made for varied Cu, Ni, Mo contents and austempering temperatures. The ADI kinetic model uses a diffusion controlled approach to model the growth. The models have been integrated in a tool for casting process simulation. Results are shown for the optimization of the heat treatment process of a planetary carrier casting.

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.

Prediction model of austenite growth and the role of MnS inclusions in non-quenched and tempered steel

NASA Astrophysics Data System (ADS)

Jiang, Bo; Wu, Meng; Sun, He; Wang, Zhilin; Zhao, Zhigang; Liu, Yazheng

2018-01-01

The austenite growth behavior of non-quenched and tempered steels (casted by continuous casting and molding casting processes) was studied. The austenite grain size of steel B casted by continuous casting process is smaller than that of steel A casted by molding casting process at the same heating parameters. The abnormal austenite growth temperature of the steels A and B are 950 °C and 1000 °C, respectively. Based on the results, the models for the austenite grain growth below and above the abnormal austenite growth temperature of the investigated steels were established. The dispersedly distributed fine particles MnS in steel B is the key factor refining the austenite grain by pinning the migration of austenite grain boundary. The elongated inclusions MnS are ineffective in preventing the austenite grain growth at high heating temperature. For the non-quenched and tempered steel, the continuous casting process should be adopted and the inclusion MnS should be elliptical, smaller in size and distributed uniformly in order to refine the final microstructure and also improve the mechanical properties.

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

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

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

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

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

2D Process-based Microbialite Growth Model

NASA Astrophysics Data System (ADS)

Airo, A.; Smith, A.

2007-12-01

A 2D process-based microbialite growth model (MGM) has been developed that integrates the coupled effects of the microbialite growth and sediment distribution within a two-dimensional cross-section of a subaqueous bedrock profile. Sediment transport is realized through particle erosion and deposition that are a function of local wave energy which is computed on the basis of linear wave theory. Surface-normal microbialite growth is directly correlated to light intensity, which is computed for every point of the microbialite surface by using a Henyey- Greenstein-type relation for scattering and the Beer's Law for absorption in the water column. Shadowing effects by surrounding obstacles and/or overlying sediment are also considered. Sediment particles can be incorporated into the microbialite framework if growth occurs in the presence of sediment. The resulting meter-size microbialite constructs develop morphologies that correspond well to natural microbialites. Furthermore, changes of environmental factors such as light intensity, wave energy, and bedrock profile result in morphological variations of the microbialites that would be expected on the basis of the current understanding of microbialite growth and development.

Radial Growth of Self-Catalyzed GaAs Nanowires and the Evolution of the Liquid Ga-Droplet Studied by Time-Resolved in Situ X-ray Diffraction.

PubMed

Schroth, Philipp; Jakob, Julian; Feigl, Ludwig; Mostafavi Kashani, Seyed Mohammad; Vogel, Jonas; Strempfer, Jörg; Keller, Thomas F; Pietsch, Ullrich; Baumbach, Tilo

2018-01-10

We report on a growth study of self-catalyzed GaAs nanowires based on time-resolved in situ X-ray structure characterization during molecular-beam-epitaxy in combination with ex situ scanning-electron-microscopy. We reveal the evolution of nanowire radius and polytypism and distinguish radial growth processes responsible for tapering and side-wall growth. We interpret our results using a model for diameter self-stabilization processes during growth of self-catalyzed GaAs nanowires including the shape of the liquid Ga-droplet and its evolution during growth.

Modeling and simulation of the deposition/relaxation processes of polycrystalline diatomic structures of metallic nitride films

NASA Astrophysics Data System (ADS)

García, M. F.; Restrepo-Parra, E.; Riaño-Rojas, J. C.

2015-05-01

This work develops a model that mimics the growth of diatomic, polycrystalline thin films by artificially splitting the growth into deposition and relaxation processes including two stages: (1) a grain-based stochastic method (grains orientation randomly chosen) is considered and by means of the Kinetic Monte Carlo method employing a non-standard version, known as Constant Time Stepping, the deposition is simulated. The adsorption of adatoms is accepted or rejected depending on the neighborhood conditions; furthermore, the desorption process is not included in the simulation and (2) the Monte Carlo method combined with the metropolis algorithm is used to simulate the diffusion. The model was developed by accounting for parameters that determine the morphology of the film, such as the growth temperature, the interacting atomic species, the binding energy and the material crystal structure. The modeled samples exhibited an FCC structure with grain formation with orientations in the family planes of < 111 >, < 200 > and < 220 >. The grain size and film roughness were analyzed. By construction, the grain size decreased, and the roughness increased, as the growth temperature increased. Although, during the growth process of real materials, the deposition and relaxation occurs simultaneously, this method may perhaps be valid to build realistic polycrystalline samples.

Nonlinear Growth Curves in Developmental Research

PubMed Central

Grimm, Kevin J.; Ram, Nilam; Hamagami, Fumiaki

2011-01-01

Developmentalists are often interested in understanding change processes and growth models are the most common analytic tool for examining such processes. Nonlinear growth curves are especially valuable to developmentalists because the defining characteristics of the growth process such as initial levels, rates of change during growth spurts, and asymptotic levels can be estimated. A variety of growth models are described beginning with the linear growth model and moving to nonlinear models of varying complexity. A detailed discussion of nonlinear models is provided, highlighting the added insights into complex developmental processes associated with their use. A collection of growth models are fit to repeated measures of height from participants of the Berkeley Growth and Guidance Studies from early childhood through adulthood. PMID:21824131

Analysing growth and development of plants jointly using developmental growth stages

PubMed Central

Dambreville, Anaëlle; Lauri, Pierre-Éric; Normand, Frédéric; Guédon, Yann

2015-01-01

Background and Aims Plant growth, the increase of organ dimensions over time, and development, the change in plant structure, are often studied as two separate processes. However, there is structural and functional evidence that these two processes are strongly related. The aim of this study was to investigate the co-ordination between growth and development using mango trees, which have well-defined developmental stages. Methods Developmental stages, determined in an expert way, and organ sizes, determined from objective measurements, were collected during the vegetative growth and flowering phases of two cultivars of mango, Mangifera indica. For a given cultivar and growth unit type (either vegetative or flowering), a multistage model based on absolute growth rate sequences deduced from the measurements was first built, and then growth stages deduced from the model were compared with developmental stages. Key Results Strong matches were obtained between growth stages and developmental stages, leading to a consistent definition of integrative developmental growth stages. The growth stages highlighted growth asynchronisms between two topologically connected organs, namely the vegetative axis and its leaves. Conclusions Integrative developmental growth stages emphasize that developmental stages are closely related to organ growth rates. The results are discussed in terms of the possible physiological processes underlying these stages, including plant hydraulics, biomechanics and carbohydrate partitioning. PMID:25452250

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.

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.

Simulating effects of fire on northern Rocky Mountain landscapes with the ecological process model FIRE-BGC.

PubMed

Keane, R E; Ryan, K C; Running, S W

1996-03-01

A mechanistic, biogeochemical succession model, FIRE-BGC, was used to investigate the role of fire on long-term landscape dynamics in northern Rocky Mountain coniferous forests of Glacier National Park, Montana, USA. FIRE-BGC is an individual-tree model-created by merging the gap-phase process-based model FIRESUM with the mechanistic ecosystem biogeochemical model FOREST-BGC-that has mixed spatial and temporal resolution in its simulation architecture. Ecological processes that act at a landscape level, such as fire and seed dispersal, are simulated annually from stand and topographic information. Stand-level processes, such as tree establishment, growth and mortality, organic matter accumulation and decomposition, and undergrowth plant dynamics are simulated both daily and annually. Tree growth is mechanistically modeled based on the ecosystem process approach of FOREST-BGC where carbon is fixed daily by forest canopy photosynthesis at the stand level. Carbon allocated to the tree stem at the end of the year generates the corresponding diameter and height growth. The model also explicitly simulates fire behavior and effects on landscape characteristics. We simulated the effects of fire on ecosystem characteristics of net primary productivity, evapotranspiration, standing crop biomass, nitrogen cycling and leaf area index over 200 years for the 50,000-ha McDonald Drainage in Glacier National Park. Results show increases in net primary productivity and available nitrogen when fires are included in the simulation. Standing crop biomass and evapotranspiration decrease under a fire regime. Shade-intolerant species dominate the landscape when fires are excluded. Model tree increment predictions compared well with field data.

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

NASA Astrophysics Data System (ADS)

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

2003-01-01

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

Kinetic modeling of microscopic processes during electron cyclotron resonance microwave plasma-assisted molecular beam epitaxial growth of GaN/GaAs-based heterostructures

NASA Astrophysics Data System (ADS)

Bandić, Z. Z.; Hauenstein, R. J.; O'Steen, M. L.; McGill, T. C.

1996-03-01

Microscopic growth processes associated with GaN/GaAs molecular beam epitaxy (MBE) are examined through the introduction of a first-order kinetic model. The model is applied to the electron cyclotron resonance microwave plasma-assisted MBE (ECR-MBE) growth of a set of δ-GaNyAs1-y/GaAs strained-layer superlattices that consist of nitrided GaAs monolayers separated by GaAs spacers, and that exhibit a strong decrease of y with increasing T over the range 540-580 °C. This y(T) dependence is quantitatively explained in terms of microscopic anion exchange, and thermally activated N surface-desorption and surface-segregation processes. N surface segregation is found to be significant during GaAs overgrowth of GaNyAs1-y layers at typical GaN ECR-MBE growth temperatures, with an estimated activation energy Es˜0.9 eV. The observed y(T) dependence is shown to result from a combination of N surface segregation/desorption processes.

A Model of Differential Growth-Guided Apical Hook Formation in Plants

PubMed Central

Žádníková, Petra; Wabnik, Krzysztof; Abuzeineh, Anas; Prusinkiewicz, Przemysław

2016-01-01

Differential cell growth enables flexible organ bending in the presence of environmental signals such as light or gravity. A prominent example of the developmental processes based on differential cell growth is the formation of the apical hook that protects the fragile shoot apical meristem when it breaks through the soil during germination. Here, we combined in silico and in vivo approaches to identify a minimal mechanism producing auxin gradient-guided differential growth during the establishment of the apical hook in the model plant Arabidopsis thaliana. Computer simulation models based on experimental data demonstrate that asymmetric expression of the PIN-FORMED auxin efflux carrier at the concave (inner) versus convex (outer) side of the hook suffices to establish an auxin maximum in the epidermis at the concave side of the apical hook. Furthermore, we propose a mechanism that translates this maximum into differential growth, and thus curvature, of the apical hook. Through a combination of experimental and in silico computational approaches, we have identified the individual contributions of differential cell elongation and proliferation to defining the apical hook and reveal the role of auxin-ethylene crosstalk in balancing these two processes. PMID:27754878

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.

An atomistically informed mesoscale model for growth and coarsening during discharge in lithium-oxygen batteries

DOE PAGES

Welland, Michael J.; Lau, Kah Chun; Redfern, Paul C.; ...

2015-12-10

An atomistically informed mesoscale model is developed for the deposition of a discharge product in a Li-O 2 battery. This mescocale model includes particle growth and coarsening as well as a simplified nucleation model. The model involves LiO 2 formation through reaction of O 2 - and Li + in the electrolyte, which deposits on the cathode surface when the LiO 2 concentration reaches supersaturation in the electrolyte. A reaction-diffusion (rate-equation) model is used to describe the processes occurring in the electrolyte and a phase-field model is used to capture microstructural evolution. This model predicts that coarsening, in which largemore » particles grow and small ones disappear, has a substantial effect on the size distribution of the LiO 2 particles during the discharge process. The size evolution during discharge is the result of the interplay between this coarsening process and particle growth. The growth through continued deposition of LiO 2 has the effect of causing large particles to grow ever faster while delaying the dissolution of small particles. The predicted size evolution is consistent with experimental results for a previously reported cathode material based on activated carbon during discharge and when it is at rest, although kinetic factors need to be included. Finally, the approach described in this paper synergistically combines models on different length scales with experimental observations and should have applications in studying other related discharge processes, such as Li 2O 2 deposition, in Li-O 2 batteries and nucleation and growth in Li-S batteries.« less

Module-based multiscale simulation of angiogenesis in skeletal muscle

PubMed Central

2011-01-01

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

Subcritical crack growth in fibrous materials

NASA Astrophysics Data System (ADS)

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

2006-05-01

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

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

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

Raj, Abhijeet; Celnik, Matthew; Shirley, Raphael

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

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

Optimal bioprocess design through a gene regulatory network - growth kinetic hybrid model: Towards Replacing Monod kinetics.

PubMed

Tsipa, Argyro; Koutinas, Michalis; Usaku, Chonlatep; Mantalaris, Athanasios

2018-05-02

Currently, design and optimisation of biotechnological bioprocesses is performed either through exhaustive experimentation and/or with the use of empirical, unstructured growth kinetics models. Whereas, elaborate systems biology approaches have been recently explored, mixed-substrate utilisation is predominantly ignored despite its significance in enhancing bioprocess performance. Herein, bioprocess optimisation for an industrially-relevant bioremediation process involving a mixture of highly toxic substrates, m-xylene and toluene, was achieved through application of a novel experimental-modelling gene regulatory network - growth kinetic (GRN-GK) hybrid framework. The GRN model described the TOL and ortho-cleavage pathways in Pseudomonas putida mt-2 and captured the transcriptional kinetics expression patterns of the promoters. The GRN model informed the formulation of the growth kinetics model replacing the empirical and unstructured Monod kinetics. The GRN-GK framework's predictive capability and potential as a systematic optimal bioprocess design tool, was demonstrated by effectively predicting bioprocess performance, which was in agreement with experimental values, when compared to four commonly used models that deviated significantly from the experimental values. Significantly, a fed-batch biodegradation process was designed and optimised through the model-based control of TOL Pr promoter expression resulting in 61% and 60% enhanced pollutant removal and biomass formation, respectively, compared to the batch process. This provides strong evidence of model-based bioprocess optimisation at the gene level, rendering the GRN-GK framework as a novel and applicable approach to optimal bioprocess design. Finally, model analysis using global sensitivity analysis (GSA) suggests an alternative, systematic approach for model-driven strain modification for synthetic biology and metabolic engineering applications. Copyright © 2018. Published by Elsevier Inc.

Integrated Predictive Tools for Customizing Microstructure and Material Properties of Additively Manufactured Aerospace Components

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

Radhakrishnan, Balasubramaniam; Fattebert, Jean-Luc; Gorti, Sarma B.

Additive Manufacturing (AM) refers to a process by which digital three-dimensional (3-D) design data is converted to build up a component by depositing material layer-by-layer. United Technologies Corporation (UTC) is currently involved in fabrication and certification of several AM aerospace structural components made from aerospace materials. This is accomplished by using optimized process parameters determined through numerous design-of-experiments (DOE)-based studies. Certification of these components is broadly recognized as a significant challenge, with long lead times, very expensive new product development cycles and very high energy consumption. Because of these challenges, United Technologies Research Center (UTRC), together with UTC business unitsmore » have been developing and validating an advanced physics-based process model. The specific goal is to develop a physics-based framework of an AM process and reliably predict fatigue properties of built-up structures as based on detailed solidification microstructures. Microstructures are predicted using process control parameters including energy source power, scan velocity, deposition pattern, and powder properties. The multi-scale multi-physics model requires solution and coupling of governing physics that will allow prediction of the thermal field and enable solution at the microstructural scale. The state-of-the-art approach to solve these problems requires a huge computational framework and this kind of resource is only available within academia and national laboratories. The project utilized the parallel phase-fields codes at Oak Ridge National Laboratory (ORNL) and Lawrence Livermore National Laboratory (LLNL), along with the high-performance computing (HPC) capabilities existing at the two labs to demonstrate the simulation of multiple dendrite growth in threedimensions (3-D). The LLNL code AMPE was used to implement the UTRC phase field model that was previously developed for a model binary alloy, and the simulation results were compared against the UTRC simulation results, followed by extension of the UTRC model to simulate multiple dendrite growth in 3-D. The ORNL MEUMAPPS code was used to simulate dendritic growth in a model ternary alloy with the same equilibrium solidification range as the Ni-base alloy 718 using realistic model parameters, including thermodynamic integration with a Calphad based model for the ternary alloy. Implementation of the UTRC model in AMPE met with several numerical and parametric issues that were resolved and good comparison between the simulation results obtained by the two codes was demonstrated for two dimensional (2-D) dendrites. 3-D dendrite growth was then demonstrated with the AMPE code using nondimensional parameters obtained in 2-D simulations. Multiple dendrite growth in 2-D and 3-D were demonstrated using ORNL’s MEUMAPPS code using simple thermal boundary conditions. MEUMAPPS was then modified to incorporate the complex, time-dependent thermal boundary conditions obtained by UTRC’s thermal modeling of single track AM experiments to drive the phase field simulations. The results were in good agreement with UTRC’s experimental measurements.« less

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

Three dimensional modeling of cirrus during the 1991 FIRE IFO 2: Detailed process study

NASA Technical Reports Server (NTRS)

Jensen, Eric J.; Toon, Owen B.; Westphal, Douglas L.

1993-01-01

A three-dimensional model of cirrus cloud formation and evolution, including microphysical, dynamical, and radiative processes, was used to simulate cirrus observed in the FIRE Phase 2 Cirrus field program (13 Nov. - 7 Dec. 1991). Sulfate aerosols, solution drops, ice crystals, and water vapor are all treated as interactive elements in the model. Ice crystal size distributions are fully resolved based on calculations of homogeneous freezing of solution drops, growth by water vapor deposition, evaporation, aggregation, and vertical transport. Visible and infrared radiative fluxes, and radiative heating rates are calculated using the two-stream algorithm described by Toon et al. Wind velocities, diffusion coefficients, and temperatures were taken from the MAPS analyses and the MM4 mesoscale model simulations. Within the model, moisture is transported and converted to liquid or vapor by the microphysical processes. The simulated cloud bulk and microphysical properties are shown in detail for the Nov. 26 and Dec. 5 case studies. Comparisons with lidar, radar, and in situ data are used to determine how well the simulations reproduced the observed cirrus. The roles played by various processes in the model are described in detail. The potential modes of nucleation are evaluated, and the importance of small-scale variations in temperature and humidity are discussed. The importance of competing ice crystal growth mechanisms (water vapor deposition and aggregation) are evaluated based on model simulations. Finally, the importance of ice crystal shape for crystal growth and vertical transport of ice are discussed.

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

PubMed

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

2018-03-31

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

On the development of nugget growth model for resistance spot welding

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

Zhou, Kang, E-mail: zhoukang326@126.com, E-mail: melcai@ust.hk; Cai, Lilong, E-mail: zhoukang326@126.com, E-mail: melcai@ust.hk

2014-04-28

In this paper, we developed a general mathematical model to estimate the nugget growth process based on the heat energy delivered into the welds by the resistance spot welding. According to the principles of thermodynamics and heat transfer, and the effect of electrode force during the welding process, the shape of the nugget can be estimated. Then, a mathematical model between heat energy absorbed and nugget diameter can be obtained theoretically. It is shown in this paper that the nugget diameter can be precisely described by piecewise fractal polynomial functions. Experiments were conducted with different welding operation conditions, such asmore » welding currents, workpiece thickness, and widths, to validate the model and the theoretical analysis. All the experiments confirmed that the proposed model can predict the nugget diameters with high accuracy based on the input heat energy to the welds.« less

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

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

Large historical growth in global terrestrial gross primary production

DOE PAGES

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

2017-04-05

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

Large historical growth in global terrestrial gross primary production

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

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

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

Monotonic entropy growth for a nonlinear model of random exchanges.

PubMed

Apenko, S M

2013-02-01

We present a proof of the monotonic entropy growth for a nonlinear discrete-time model of a random market. This model, based on binary collisions, also may be viewed as a particular case of Ulam's redistribution of energy problem. We represent each step of this dynamics as a combination of two processes. The first one is a linear energy-conserving evolution of the two-particle distribution, for which the entropy growth can be easily verified. The original nonlinear process is actually a result of a specific "coarse graining" of this linear evolution, when after the collision one variable is integrated away. This coarse graining is of the same type as the real space renormalization group transformation and leads to an additional entropy growth. The combination of these two factors produces the required result which is obtained only by means of information theory inequalities.

Monotonic entropy growth for a nonlinear model of random exchanges

NASA Astrophysics Data System (ADS)

Apenko, S. M.

2013-02-01

We present a proof of the monotonic entropy growth for a nonlinear discrete-time model of a random market. This model, based on binary collisions, also may be viewed as a particular case of Ulam's redistribution of energy problem. We represent each step of this dynamics as a combination of two processes. The first one is a linear energy-conserving evolution of the two-particle distribution, for which the entropy growth can be easily verified. The original nonlinear process is actually a result of a specific “coarse graining” of this linear evolution, when after the collision one variable is integrated away. This coarse graining is of the same type as the real space renormalization group transformation and leads to an additional entropy growth. The combination of these two factors produces the required result which is obtained only by means of information theory inequalities.

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.

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

DOE PAGES

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

2016-07-28

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

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.

Theoretical and Experimental Study of Bacterial Colony Growth in 3D

NASA Astrophysics Data System (ADS)

Shao, Xinxian; Mugler, Andrew; Nemenman, Ilya

2014-03-01

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

Application of evolutionary games to modeling carcinogenesis.

PubMed

Swierniak, Andrzej; Krzeslak, Michal

2013-06-01

We review a quite large volume of literature concerning mathematical modelling of processes related to carcinogenesis and the growth of cancer cell populations based on the theory of evolutionary games. This review, although partly idiosyncratic, covers such major areas of cancer-related phenomena as production of cytotoxins, avoidance of apoptosis, production of growth factors, motility and invasion, and intra- and extracellular signaling. We discuss the results of other authors and append to them some additional results of our own simulations dealing with the possible dynamics and/or spatial distribution of the processes discussed.

Simulating Cancer Growth with Multiscale Agent-Based Modeling

PubMed Central

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

2014-01-01

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

Processing of laser formed SiC powder

NASA Technical Reports Server (NTRS)

Haggerty, J. S.; Bowen, H. K.

1987-01-01

Processing research was undertaken to demonstrate that superior SiC characteristics could be achieved through the use of ideal constituent powders and careful post-synthesis processing steps. Initial research developed the means to produce approximately 1000 A uniform diameter, nonagglomerated, spherical, high purity SiC powders. Accomplishing this goal required major revision of the particle formation and growth model from one based on classical nucleation and growth to one based on collision and coalescence of Si particles followed by their carburization. Dispersions based on pure organic solvents as well as steric stabilization were investigated. Test parts were made by the colloidal pressing technique; both liquid filtration and consolidation (rearrangement) stages were modeled. Green densities corresponding to a random close packed structure were achieved. After drying, parts were densified at temperatures ranging from 1800 to 2100 C. This research program accomplished all of its major objectives. Superior microstructures and properties were attained by using powders having ideal characteristics and special post-synthesis processing procedures.

A mathematical model and computational framework for three-dimensional chondrocyte cell growth in a porous tissue scaffold placed inside a bi-directional flow perfusion bioreactor.

PubMed

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

2015-12-01

The in vitro chondrocyte cell culture for cartilage tissue regeneration in a perfusion bioreactor is a complex process. Mathematical modeling and computational simulation can provide important insights into the culture process, which would be helpful for selecting culture conditions to improve the quality of the developed tissue constructs. However, simulation of the cell culture process is a challenging task due to the complicated interaction between the cells and local fluid flow and nutrient transport inside the complex porous scaffolds. In this study, a mathematical model and computational framework has been developed to simulate the three-dimensional (3D) cell growth in a porous scaffold placed inside a bi-directional flow perfusion bioreactor. The model was developed by taking into account the two-way coupling between the cell growth and local flow field and associated glucose concentration, and then used to perform a resolved-scale simulation based on the lattice Boltzmann method (LBM). The simulation predicts the local shear stress, glucose concentration, and 3D cell growth inside the porous scaffold for a period of 30 days of cell culture. The predicted cell growth rate was in good overall agreement with the experimental results available in the literature. This study demonstrates that the bi-directional flow perfusion culture system can enhance the homogeneity of the cell growth inside the scaffold. The model and computational framework developed is capable of providing significant insight into the culture process, thus providing a powerful tool for the design and optimization of the cell culture process. © 2015 Wiley Periodicals, Inc.

Analysing growth and development of plants jointly using developmental growth stages.

PubMed

Dambreville, Anaëlle; Lauri, Pierre-Éric; Normand, Frédéric; Guédon, Yann

2015-01-01

Plant growth, the increase of organ dimensions over time, and development, the change in plant structure, are often studied as two separate processes. However, there is structural and functional evidence that these two processes are strongly related. The aim of this study was to investigate the co-ordination between growth and development using mango trees, which have well-defined developmental stages. Developmental stages, determined in an expert way, and organ sizes, determined from objective measurements, were collected during the vegetative growth and flowering phases of two cultivars of mango, Mangifera indica. For a given cultivar and growth unit type (either vegetative or flowering), a multistage model based on absolute growth rate sequences deduced from the measurements was first built, and then growth stages deduced from the model were compared with developmental stages. Strong matches were obtained between growth stages and developmental stages, leading to a consistent definition of integrative developmental growth stages. The growth stages highlighted growth asynchronisms between two topologically connected organs, namely the vegetative axis and its leaves. Integrative developmental growth stages emphasize that developmental stages are closely related to organ growth rates. The results are discussed in terms of the possible physiological processes underlying these stages, including plant hydraulics, biomechanics and carbohydrate partitioning. © The Author 2014. Published by Oxford University Press on behalf of the Annals of Botany Company. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Reconstruction of late Holocene climate based on tree growth and mechanistic hierarchical models

USGS Publications Warehouse

Tipton, John; Hooten, Mevin B.; Pederson, Neil; Tingley, Martin; Bishop, Daniel

2016-01-01

Reconstruction of pre-instrumental, late Holocene climate is important for understanding how climate has changed in the past and how climate might change in the future. Statistical prediction of paleoclimate from tree ring widths is challenging because tree ring widths are a one-dimensional summary of annual growth that represents a multi-dimensional set of climatic and biotic influences. We develop a Bayesian hierarchical framework using a nonlinear, biologically motivated tree ring growth model to jointly reconstruct temperature and precipitation in the Hudson Valley, New York. Using a common growth function to describe the response of a tree to climate, we allow for species-specific parameterizations of the growth response. To enable predictive backcasts, we model the climate variables with a vector autoregressive process on an annual timescale coupled with a multivariate conditional autoregressive process that accounts for temporal correlation and cross-correlation between temperature and precipitation on a monthly scale. Our multi-scale temporal model allows for flexibility in the climate response through time at different temporal scales and predicts reasonable climate scenarios given tree ring width data.

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.

Moon Munchies: Human Exploration Project Engineering Design Challenge--A Standards-Based Elementary School Model Unit Guide--Design, Build, and Evaluate (Lessons 1-6). Engineering By Design: Advancing Technological Literacy--A Standards-Based Program Series. EP-2007-08-92-MSFC

ERIC Educational Resources Information Center

Weaver, Kim M.

2005-01-01

In this unit, elementary students design and build a lunar plant growth chamber using the Engineering Design Process. The purpose of the unit is to help students understand and apply the design process as it relates to plant growth on the moon. This guide includes six lessons, which meet a number of national standards and benchmarks in…

Modeling & processing of ceramic and polymer precursor ceramic matrix composite materials

NASA Astrophysics Data System (ADS)

Wang, Xiaolin

Synthesis and processing of novel materials with various advanced approaches have attracted much attention of engineers and scientists for the past thirty years. Many advanced materials display a number of exceptional properties and can be produced with different novel processing techniques. For example, AlN is a promising candidate for electronic, optical and opto-electronic applications due to its high thermal conductivity, high electrical resistivity, high acoustic wave velocity and large band gap. Large bulk AlN crystal can be produced by sublimation of AlN powder. Novel nonostructured multicomponent refractory metal-based ceramics (carbides, borides and nitrides) show a lot of exceptional mechanical, thermal and chemical properties, and can be easily produced by pyrolysis of suitable preceramic precursors mixed with metal particles. The objective of this work is to study sublimation and synthesis of AlN powder, and synthesis of SiC-based metal ceramics. For AlN sublimation crystal growth, we will focus on modeling the processes in the powder source that affect significantly the sublimation growth as a whole. To understand the powder porosity evolution and vapor transport during powder sublimation, the interplay between vapor transport and powder sublimation will be studied. A physics-based computational model will be developed considering powder sublimation and porosity evolution. Based on the proposed model, the effect of a central hole in the powder on the sublimation rate is studied and the result is compared to the case of powder without a hole. The effect of hole size on the sublimation rate will be studied. The effects of initial porosity, particle size and driving force on the sublimation rate are also studied. Moreover, the optimal growth condition for large diameter crystal quality and high growth rate will be determined. For synthesis of SiC-based metal ceramics, we will focus on developing a multi-scale process model to describe the dynamic behavior of filler particle reaction, microstructure evolution, at the microscale as well as transient fluid flow, heat transfer, and species transport at the macroscale. The model comprises of (i) a microscale model and (ii) a macroscale transport model, and aims to provide optimal conditions for the fabrication process of the ceramics. The porous media macroscale model for SiC-based metal-ceramic materials processing will be developed to understand the thermal polymer pyrolysis, chemical reaction of active fillers and transport phenomena in the porous media. The macroscale model will include heat and mass transfer, curing, pyrolysis, chemical reaction and crystallization in a mixture of preceramic polymers and submicron/nano-sized metal particles of uranium, zirconium, niobium, or hafnium. The effects of heating rate, sample size, size and volume ratio of the metal particles on the reaction rate and product uniformity will be studied. The microscale model will be developed for modeling the synthesis of SiC matrix and metal particles. The macroscale model provides thermal boundary conditions to the microscale model. The microscale model applies to repetitive units in the porous structure and describes mass transport, composition changes and motion of metal particles. The unit-cell is the representation unit of the source material, and it consists of several metal particles, SiC matrix and other components produced from the synthesis process. The reactions between different components, the microstructure evolution of the product will be considered. The effects of heating rate and metal particle size on species uniformity and microstructure are investigated.

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

Determining individual variation in growth and its implication for life-history and population processes using the empirical Bayes method.

PubMed

Vincenzi, Simone; Mangel, Marc; Crivelli, Alain J; Munch, Stephan; Skaug, Hans J

2014-09-01

The differences in demographic and life-history processes between organisms living in the same population have important consequences for ecological and evolutionary dynamics. Modern statistical and computational methods allow the investigation of individual and shared (among homogeneous groups) determinants of the observed variation in growth. We use an Empirical Bayes approach to estimate individual and shared variation in somatic growth using a von Bertalanffy growth model with random effects. To illustrate the power and generality of the method, we consider two populations of marble trout Salmo marmoratus living in Slovenian streams, where individually tagged fish have been sampled for more than 15 years. We use year-of-birth cohort, population density during the first year of life, and individual random effects as potential predictors of the von Bertalanffy growth function's parameters k (rate of growth) and L∞ (asymptotic size). Our results showed that size ranks were largely maintained throughout marble trout lifetime in both populations. According to the Akaike Information Criterion (AIC), the best models showed different growth patterns for year-of-birth cohorts as well as the existence of substantial individual variation in growth trajectories after accounting for the cohort effect. For both populations, models including density during the first year of life showed that growth tended to decrease with increasing population density early in life. Model validation showed that predictions of individual growth trajectories using the random-effects model were more accurate than predictions based on mean size-at-age of fish.

Mathematical models to characterize early epidemic growth: A Review

PubMed Central

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

2016-01-01

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

Mathematical models to characterize early epidemic growth: A review

NASA Astrophysics Data System (ADS)

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

2016-09-01

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

A mechanistic Individual-based Model of microbial communities.

PubMed

Jayathilake, Pahala Gedara; Gupta, Prashant; Li, Bowen; Madsen, Curtis; Oyebamiji, Oluwole; González-Cabaleiro, Rebeca; Rushton, Steve; Bridgens, Ben; Swailes, David; Allen, Ben; McGough, A Stephen; Zuliani, Paolo; Ofiteru, Irina Dana; Wilkinson, Darren; Chen, Jinju; Curtis, Tom

2017-01-01

Accurate predictive modelling of the growth of microbial communities requires the credible representation of the interactions of biological, chemical and mechanical processes. However, although biological and chemical processes are represented in a number of Individual-based Models (IbMs) the interaction of growth and mechanics is limited. Conversely, there are mechanically sophisticated IbMs with only elementary biology and chemistry. This study focuses on addressing these limitations by developing a flexible IbM that can robustly combine the biological, chemical and physical processes that dictate the emergent properties of a wide range of bacterial communities. This IbM is developed by creating a microbiological adaptation of the open source Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS). This innovation should provide the basis for "bottom up" prediction of the emergent behaviour of entire microbial systems. In the model presented here, bacterial growth, division, decay, mechanical contact among bacterial cells, and adhesion between the bacteria and extracellular polymeric substances are incorporated. In addition, fluid-bacteria interaction is implemented to simulate biofilm deformation and erosion. The model predicts that the surface morphology of biofilms becomes smoother with increased nutrient concentration, which agrees well with previous literature. In addition, the results show that increased shear rate results in smoother and more compact biofilms. The model can also predict shear rate dependent biofilm deformation, erosion, streamer formation and breakup.

A mechanistic Individual-based Model of microbial communities

PubMed Central

Gupta, Prashant; Li, Bowen; Madsen, Curtis; Oyebamiji, Oluwole; González-Cabaleiro, Rebeca; Rushton, Steve; Bridgens, Ben; Swailes, David; Allen, Ben; McGough, A. Stephen; Zuliani, Paolo; Ofiteru, Irina Dana; Wilkinson, Darren; Chen, Jinju; Curtis, Tom

2017-01-01

Accurate predictive modelling of the growth of microbial communities requires the credible representation of the interactions of biological, chemical and mechanical processes. However, although biological and chemical processes are represented in a number of Individual-based Models (IbMs) the interaction of growth and mechanics is limited. Conversely, there are mechanically sophisticated IbMs with only elementary biology and chemistry. This study focuses on addressing these limitations by developing a flexible IbM that can robustly combine the biological, chemical and physical processes that dictate the emergent properties of a wide range of bacterial communities. This IbM is developed by creating a microbiological adaptation of the open source Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS). This innovation should provide the basis for “bottom up” prediction of the emergent behaviour of entire microbial systems. In the model presented here, bacterial growth, division, decay, mechanical contact among bacterial cells, and adhesion between the bacteria and extracellular polymeric substances are incorporated. In addition, fluid-bacteria interaction is implemented to simulate biofilm deformation and erosion. The model predicts that the surface morphology of biofilms becomes smoother with increased nutrient concentration, which agrees well with previous literature. In addition, the results show that increased shear rate results in smoother and more compact biofilms. The model can also predict shear rate dependent biofilm deformation, erosion, streamer formation and breakup. PMID:28771505

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

PubMed

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

2017-07-01

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

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

NASA Astrophysics Data System (ADS)

Yan, Xuewei; Xu, Qingyan; Liu, Baicheng

2017-12-01

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

Nucleation and growth of microdroplets of ionic liquids deposited by physical vapor method onto different surfaces

NASA Astrophysics Data System (ADS)

Costa, José C. S.; Coelho, Ana F. S. M. G.; Mendes, Adélio; Santos, Luís M. N. B. F.

2018-01-01

Nanoscience and technology has generated an important area of research in the field of properties and functionality of ionic liquids (ILs) based materials and their thin films. This work explores the deposition process of ILs droplets as precursors for the fabrication of thin films, by means of physical vapor deposition (PVD). It was found that the deposition (by PVD on glass, indium tin oxide, graphene/nickel and gold-coated quartz crystal surfaces) of imidazolium [C4mim][NTf2] and pyrrolidinium [C4C1Pyrr][NTf2] based ILs generates micro/nanodroplets with a shape, size distribution and surface coverage that could be controlled by the evaporation flow rate and deposition time. No indication of the formation of a wetting-layer prior to the island growth was found. Based on the time-dependent morphological analysis of the micro/nanodroplets, a simple model for the description of the nucleation process and growth of ILs droplets is presented. The proposed model is based on three main steps: minimum free area to promote nucleation; first order coalescence; second order coalescence.

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

PubMed

Akkermans, Simen; Van Impe, Jan F

2018-06-01

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

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

PubMed

Sahoo, R K; Jacob, C

2014-06-01

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

Estimating plant available water for general crop simulations in ALMANAC/APEX/EPIC/SWAT

USDA-ARS?s Scientific Manuscript database

Process-based simulation models ALMANAC/APEX/EPIC/SWAT contain generalized plant growth subroutines to predict biomass and crop yield. Environmental constraints typically restrict plant growth and yield. Water stress is often an important limiting factor; it is calculated as the sum of water use f...

A Harris-Todaro Agent-Based Model to Rural-Urban Migration

NASA Astrophysics Data System (ADS)

Espíndola, Aquino L.; Silveira, Jaylson J.; Penna, T. J. P.

2006-09-01

The Harris-Todaro model of the rural-urban migration process is revisited under an agent-based approach. The migration of the workers is interpreted as a process of social learning by imitation, formalized by a computational model. By simulating this model, we observe a transitional dynamics with continuous growth of the urban fraction of overall population toward an equilibrium. Such an equilibrium is characterized by stabilization of rural-urban expected wages differential (generalized Harris-Todaro equilibrium condition), urban concentration and urban unemployment. These classic results obtained originally by Harris and Todaro are emergent properties of our model.

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

NASA Astrophysics Data System (ADS)

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

2014-09-01

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

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

NASA Technical Reports Server (NTRS)

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

1993-01-01

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

Metabolic modeling of energy balances in Mycoplasma hyopneumoniae shows that pyruvate addition increases growth rate.

PubMed

Kamminga, Tjerko; Slagman, Simen-Jan; Bijlsma, Jetta J E; Martins Dos Santos, Vitor A P; Suarez-Diez, Maria; Schaap, Peter J

2017-10-01

Mycoplasma hyopneumoniae is cultured on large-scale to produce antigen for inactivated whole-cell vaccines against respiratory disease in pigs. However, the fastidious nutrient requirements of this minimal bacterium and the low growth rate make it challenging to reach sufficient biomass yield for antigen production. In this study, we sequenced the genome of M. hyopneumoniae strain 11 and constructed a high quality constraint-based genome-scale metabolic model of 284 chemical reactions and 298 metabolites. We validated the model with time-series data of duplicate fermentation cultures to aim for an integrated model describing the dynamic profiles measured in fermentations. The model predicted that 84% of cellular energy in a standard M. hyopneumoniae cultivation was used for non-growth associated maintenance and only 16% of cellular energy was used for growth and growth associated maintenance. Following a cycle of model-driven experimentation in dedicated fermentation experiments, we were able to increase the fraction of cellular energy used for growth through pyruvate addition to the medium. This increase in turn led to an increase in growth rate and a 2.3 times increase in the total biomass concentration reached after 3-4 days of fermentation, enhancing the productivity of the overall process. The model presented provides a solid basis to understand and further improve M. hyopneumoniae fermentation processes. Biotechnol. Bioeng. 2017;114: 2339-2347. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Stochastic modelling of tree architecture and biomass allocation: application to teak (Tectona grandis L. f.), a tree species with polycyclic growth and leaf neoformation.

PubMed

Tondjo, Kodjo; Brancheriau, Loïc; Sabatier, Sylvie; Kokutse, Adzo Dzifa; Kokou, Kouami; Jaeger, Marc; de Reffye, Philippe; Fourcaud, Thierry

2018-06-08

For a given genotype, the observed variability of tree forms results from the stochasticity of meristem functioning and from changing and heterogeneous environmental factors affecting biomass formation and allocation. In response to climate change, trees adapt their architecture by adjusting growth processes such as pre- and neoformation, as well as polycyclic growth. This is the case for the teak tree. The aim of this work was to adapt the plant model, GreenLab, in order to take into consideration both these processes using existing data on this tree species. This work adopted GreenLab formalism based on source-sink relationships at organ level that drive biomass production and partitioning within the whole plant over time. The stochastic aspect of phytomer production can be modelled by a Bernoulli process. The teak model was designed, parameterized and analysed using the architectural data from 2- to 5-year-old teak trees in open field stands. Growth and development parameters were identified, fitting the observed compound organic series with the theoretical series, using generalized least squares methods. Phytomer distributions of growth units and branching pattern varied depending on their axis category, i.e. their physiological age. These emerging properties were in accordance with the observed growth patterns and biomass allocation dynamics during a growing season marked by a short dry season. Annual growth patterns observed on teak, including shoot pre- and neoformation and polycyclism, were reproduced by the new version of the GreenLab model. However, further updating is discussed in order to ensure better consideration of radial variation in basic specific gravity of wood. Such upgrading of the model will enable teak ideotypes to be defined for improving wood production in terms of both volume and quality.

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

Biomechanical differences in the stem straightening process among Pinus pinaster provenances. A new approach for early selection of stem straightness.

PubMed

Sierra-de-Grado, Rosario; Pando, Valentín; Martínez-Zurimendi, Pablo; Peñalvo, Alejandro; Báscones, Esther; Moulia, Bruno

2008-06-01

Stem straightness is an important selection trait in Pinus pinaster Ait. breeding programs. Despite the stability of stem straightness rankings in provenance trials, the efficiency of breeding programs based on a quantitative index of stem straightness remains low. An alternative approach is to analyze biomechanical processes that underlie stem form. The rationale for this selection method is that genetic differences in the biomechanical processes that maintain stem straightness in young plants will continue to control stem form throughout the life of the tree. We analyzed the components contributing most to genetic differences among provenances in stem straightening processes by kinetic analysis and with a biomechanical model defining the interactions between the variables involved (Fournier's model). This framework was tested on three P. pinaster provenances differing in adult stem straightness and growth. One-year-old plants were tilted at 45 degrees, and individual stem positions and sizes were recorded weekly for 5 months. We measured the radial extension of reaction wood and the anatomical features of wood cells in serial stem cross sections. The integral effect of reaction wood on stem leaning was computed with Fournier's model. Responses driven by both primary and secondary growth were involved in the stem straightening process, but secondary-growth-driven responses accounted for most differences among provenances. Plants from the straight-stemmed provenance showed a greater capacity for stem straightening than plants from the sinuous provenances mainly because of (1) more efficient reaction wood (higher maturation strains) and (2) more pronounced secondary-growth-driven autotropic decurving. These two process-based traits are thus good candidates for early selection of stem straightness, but additional tests on a greater number of genotypes over a longer period are required.

Graphene growth process modeling: a physical-statistical approach

NASA Astrophysics Data System (ADS)

Wu, Jian; Huang, Qiang

2014-09-01

As a zero-band semiconductor, graphene is an attractive material for a wide variety of applications such as optoelectronics. Among various techniques developed for graphene synthesis, chemical vapor deposition on copper foils shows high potential for producing few-layer and large-area graphene. Since fabrication of high-quality graphene sheets requires the understanding of growth mechanisms, and methods of characterization and control of grain size of graphene flakes, analytical modeling of graphene growth process is therefore essential for controlled fabrication. The graphene growth process starts with randomly nucleated islands that gradually develop into complex shapes, grow in size, and eventually connect together to cover the copper foil. To model this complex process, we develop a physical-statistical approach under the assumption of self-similarity during graphene growth. The growth kinetics is uncovered by separating island shapes from area growth rate. We propose to characterize the area growth velocity using a confined exponential model, which not only has clear physical explanation, but also fits the real data well. For the shape modeling, we develop a parametric shape model which can be well explained by the angular-dependent growth rate. This work can provide useful information for the control and optimization of graphene growth process on Cu foil.

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.

Modeling the effects of ozone on soybean growth and yield.

PubMed

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

1990-01-01

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

On the implications of the classical ergodic theorems: analysis of developmental processes has to focus on intra-individual variation.

PubMed

Molenaar, Peter C M

2008-01-01

It is argued that general mathematical-statistical theorems imply that standard statistical analysis techniques of inter-individual variation are invalid to investigate developmental processes. Developmental processes have to be analyzed at the level of individual subjects, using time series data characterizing the patterns of intra-individual variation. It is shown that standard statistical techniques based on the analysis of inter-individual variation appear to be insensitive to the presence of arbitrary large degrees of inter-individual heterogeneity in the population. An important class of nonlinear epigenetic models of neural growth is described which can explain the occurrence of such heterogeneity in brain structures and behavior. Links with models of developmental instability are discussed. A simulation study based on a chaotic growth model illustrates the invalidity of standard analysis of inter-individual variation, whereas time series analysis of intra-individual variation is able to recover the true state of affairs. (c) 2007 Wiley Periodicals, Inc.

Investigating calcite growth rates using a quartz crystal microbalance with dissipation (QCM-D)

NASA Astrophysics Data System (ADS)

Cao, Bo; Stack, Andrew G.; Steefel, Carl I.; DePaolo, Donald J.; Lammers, Laura N.; Hu, Yandi

2018-02-01

Calcite precipitation plays a significant role in processes such as geological carbon sequestration and toxic metal sequestration and, yet, the rates and mechanisms of calcite growth under close to equilibrium conditions are far from well understood. In this study, a quartz crystal microbalance with dissipation (QCM-D) was used for the first time to measure macroscopic calcite growth rates. Calcite seed crystals were first nucleated and grown on sensors, then growth rates of calcite seed crystals were measured in real-time under close to equilibrium conditions (saturation index, SI = log ({Ca2+}/{CO32-}/Ksp) = 0.01-0.7, where {i} represent ion activities and Ksp = 10-8.48 is the calcite thermodynamic solubility constant). At the end of the experiments, total masses of calcite crystals on sensors measured by QCM-D and inductively coupled plasma mass spectrometry (ICP-MS) were consistent, validating the QCM-D measurements. Calcite growth rates measured by QCM-D were compared with reported macroscopic growth rates measured with auto-titration, ICP-MS, and microbalance. Calcite growth rates measured by QCM-D were also compared with microscopic growth rates measured by atomic force microscopy (AFM) and with rates predicted by two process-based crystal growth models. The discrepancies in growth rates among AFM measurements and model predictions appear to mainly arise from differences in step densities, and the step velocities were consistent among the AFM measurements as well as with both model predictions. Using the predicted steady-state step velocity and the measured step densities, both models predict well the growth rates measured using QCM-D and AFM. This study provides valuable insights into the effects of reactive site densities on calcite growth rate, which may help design future growth models to predict transient-state step densities.

Modelling the growth of porous alumina matrix for creating hyperbolic media

NASA Astrophysics Data System (ADS)

Aryslanova, E. M.; Alfimov, A. V.; Chivilikhin, S. A.

2016-08-01

Porous aluminum oxide is a regular self-assembled structure. During anodization it is possible to control nano-parameters of the structure using macroscopic parameters of anodization. Porous alumina films can be used as a template for the creation of hyperbolic media. In this work we consider the anodization process, our model takes into account the influence of layers of aluminum and electrolyte on the rate of growth of aluminum oxide, as well as the effect of surface diffusion. As a result of our model we obtain the minimum distance between centers of alumina pores in the beginning of anodizing process. We also present the results obtained by numerical modelling of hyperbolic media based on porous alumina film.

Bayesian methods to estimate urban growth potential

USGS Publications Warehouse

Smith, Jordan W.; Smart, Lindsey S.; Dorning, Monica; Dupéy, Lauren Nicole; Méley, Andréanne; Meentemeyer, Ross K.

2017-01-01

Urban growth often influences the production of ecosystem services. The impacts of urbanization on landscapes can subsequently affect landowners’ perceptions, values and decisions regarding their land. Within land-use and land-change research, very few models of dynamic landscape-scale processes like urbanization incorporate empirically-grounded landowner decision-making processes. Very little attention has focused on the heterogeneous decision-making processes that aggregate to influence broader-scale patterns of urbanization. We examine the land-use tradeoffs faced by individual landowners in one of the United States’ most rapidly urbanizing regions − the urban area surrounding Charlotte, North Carolina. We focus on the land-use decisions of non-industrial private forest owners located across the region’s development gradient. A discrete choice experiment is used to determine the critical factors influencing individual forest owners’ intent to sell their undeveloped properties across a series of experimentally varied scenarios of urban growth. Data are analyzed using a hierarchical Bayesian approach. The estimates derived from the survey data are used to modify a spatially-explicit trend-based urban development potential model, derived from remotely-sensed imagery and observed changes in the region’s socioeconomic and infrastructural characteristics between 2000 and 2011. This modeling approach combines the theoretical underpinnings of behavioral economics with spatiotemporal data describing a region’s historical development patterns. By integrating empirical social preference data into spatially-explicit urban growth models, we begin to more realistically capture processes as well as patterns that drive the location, magnitude and rates of urban growth.

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

PubMed

Lobacz, Adriana; Kowalik, Jaroslaw; Tarczynska, Anna

2013-06-01

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

Simulating cancer growth with multiscale agent-based modeling.

PubMed

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

2015-02-01

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

Determining Individual Variation in Growth and Its Implication for Life-History and Population Processes Using the Empirical Bayes Method

PubMed Central

Vincenzi, Simone; Mangel, Marc; Crivelli, Alain J.; Munch, Stephan; Skaug, Hans J.

2014-01-01

The differences in demographic and life-history processes between organisms living in the same population have important consequences for ecological and evolutionary dynamics. Modern statistical and computational methods allow the investigation of individual and shared (among homogeneous groups) determinants of the observed variation in growth. We use an Empirical Bayes approach to estimate individual and shared variation in somatic growth using a von Bertalanffy growth model with random effects. To illustrate the power and generality of the method, we consider two populations of marble trout Salmo marmoratus living in Slovenian streams, where individually tagged fish have been sampled for more than 15 years. We use year-of-birth cohort, population density during the first year of life, and individual random effects as potential predictors of the von Bertalanffy growth function's parameters k (rate of growth) and (asymptotic size). Our results showed that size ranks were largely maintained throughout marble trout lifetime in both populations. According to the Akaike Information Criterion (AIC), the best models showed different growth patterns for year-of-birth cohorts as well as the existence of substantial individual variation in growth trajectories after accounting for the cohort effect. For both populations, models including density during the first year of life showed that growth tended to decrease with increasing population density early in life. Model validation showed that predictions of individual growth trajectories using the random-effects model were more accurate than predictions based on mean size-at-age of fish. PMID:25211603

Modeling of multiphase flow with solidification and chemical reaction in materials processing

NASA Astrophysics Data System (ADS)

Wei, Jiuan

Understanding of multiphase flow and related heat transfer and chemical reactions are the keys to increase the productivity and efficiency in industrial processes. The objective of this thesis is to utilize the computational approaches to investigate the multiphase flow and its application in the materials processes, especially in the following two areas: directional solidification, and pyrolysis and synthesis. In this thesis, numerical simulations will be performed for crystal growth of several III-V and II-VI compounds. The effects of Prandtl and Grashof numbers on the axial temperature profile, the solidification interface shape, and melt flow are investigated. For the material with high Prandtl and Grashof numbers, temperature field and growth interface will be significantly influenced by melt flow, resulting in the complicated temperature distribution and curved interface shape, so it will encounter tremendous difficulty using a traditional Bridgman growth system. A new design is proposed to reduce the melt convection. The geometric configuration of top cold and bottom hot in the melt will dramatically reduce the melt convection. The new design has been employed to simulate the melt flow and heat transfer in crystal growth with large Prandtl and Grashof numbers and the design parameters have been adjusted. Over 90% of commercial solar cells are made from silicon and directional solidification system is the one of the most important method to produce multi-crystalline silicon ingots due to its tolerance to feedstock impurities and lower manufacturing cost. A numerical model is developed to simulate the silicon ingot directional solidification process. Temperature distribution and solidification interface location are presented. Heat transfer and solidification analysis are performed to determine the energy efficiency of the silicon production furnace. Possible improvements are identified. The silicon growth process is controlled by adjusting heating power and moving the side insulation layer upward. It is possible to produce high quality crystal with a good combination of heating and cooling. SiC based ceramic materials fabricated by polymer pyrolysis and synthesis becomes a promising candidate for nuclear applications. To obtain high uniformity of microstructure/concentration fuel without crack at high operating temperature, it is important to understand transport phenomena in material processing at different scale levels. In our prior work, a system level model based on reactive porous media theory was developed to account for the pyrolysis process in uranium-ceramic nuclear fabrication In this thesis, a particle level mesoscopic model based on the Smoothed Particle Hydrodynamics (SPH) is developed for modeling the synthesis of filler U3O8 particles and SiC matrix. The system-level model provides the thermal boundary conditions needed in the particle level simulation. The evolution of particle concentration and structure as well as composition of composite produced will be investigated. Since the process temperature and heat flux play the important roles in material quality and uniformity, the effects of heating rate at different directions, filler particle size and distribution on uniformity and microstructure of the final product are investigated. Uncertainty issue is also discussed. For the multiphase flow with directional solidification, a system level based on FVM is established. In this model, melt convection, temperature distribution, phase change and solidification interface can be investigated. For the multiphase flow with chemical reaction, a particle level model based on SPH method is developed to describe the pyrolysis and synthesis process of uranium-ceramic nuclear fuel. Due to its mesh-free nature, SPH can easily handle the problems with multi phases and components, large deformation, chemical reactions and even solidifications. A multi-scale meso-macroscopic approach, which combine a mesoscopic model based on SPH method and macroscopic model based on FVM, FEM and FDM, can be applied to even more complicated system. In the mesoscopic model by SPH method, some fundamental mesoscopic phenomena, such as the microstructure evolution, interface morphology represented by high resolution, particle entrapment in solidification can be studied. In the macroscopic model, the heat transfer, fluid flow, species transport can be modeled, and the simulation results provided the velocity, temperature and species boundary condition necessary for the mesoscopic model. This part falls into the region of future work. (Abstract shortened by UMI.)

Modeling Growth of Nanostructures in Plasmas

NASA Technical Reports Server (NTRS)

Hwang, Helen H.; Bose, Deepak; Govindan, T. R.; Meyyappan, M.

2004-01-01

As semiconductor circuits shrink to CDs below 0.1 nm, it is becoming increasingly critical to replace and/or enhance existing technology with nanoscale structures, such as nanowires for interconnects. Nanowires grown in plasmas are strongly dependent on processing conditions, such as gas composition and substrate temperature. Growth occurs at specific sites, or step-edges, with the bulk growth rate of the nanowires determined from the equation of motion of the nucleating crystalline steps. Traditional front-tracking algorithms, such as string-based or level set methods, suffer either from numerical complications in higher spatial dimensions, or from difficulties in incorporating surface-intense physical and chemical phenomena. Phase field models have the robustness of the level set method, combined with the ability to implement surface-specific chemistry that is required to model crystal growth, although they do not necessarily directly solve for the advancing front location. We have adopted a phase field approach and will present results of the adatom density and step-growth location in time as a function of processing conditions, such as temperature and plasma gas composition.

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.

Disentangling the Effects of Water Stress on Carbon Acquisition, Vegetative Growth, and Fruit Quality of Peach Trees by Means of the QualiTree Model.

PubMed

Rahmati, Mitra; Mirás-Avalos, José M; Valsesia, Pierre; Lescourret, Françoise; Génard, Michel; Davarynejad, Gholam H; Bannayan, Mohammad; Azizi, Majid; Vercambre, Gilles

2018-01-01

Climate change projections predict warmer and drier conditions. In general, moderate to severe water stress reduce plant vegetative growth and leaf photosynthesis. However, vegetative and reproductive growths show different sensitivities to water deficit. In fruit trees, water restrictions may have serious implications not only on tree growth and yield, but also on fruit quality, which might be improved. Therefore, it is of paramount importance to understand the complex interrelations among the physiological processes involved in within-tree carbon acquisition and allocation, water uptake and transpiration, organ growth, and fruit composition when affected by water stress. This can be studied using process-based models of plant functioning, which allow assessing the sensitivity of various physiological processes to water deficit and their relative impact on vegetative growth and fruit quality. In the current study, an existing fruit-tree model (QualiTree) was adapted for describing the water stress effects on peach ( Prunus persica L. Batsch) vegetative growth, fruit size and composition. First, an energy balance calculation at the fruit-bearing shoot level and a water transfer formalization within the plant were integrated into the model. Next, a reduction function of vegetative growth according to tree water status was added to QualiTree. Then, the model was parameterized and calibrated for a late-maturing peach cultivar ("Elberta") under semi-arid conditions, and for three different irrigation practices. Simulated vegetative and fruit growth variability over time was consistent with observed data. Sugar concentrations in fruit flesh were well simulated. Finally, QualiTree allowed for determining the relative importance of photosynthesis and vegetative growth reduction on carbon acquisition, plant growth and fruit quality under water constrains. According to simulations, water deficit impacted vegetative growth first through a direct effect on its sink strength, and; secondly, through an indirect reducing effect on photosynthesis. Fruit composition was moderately affected by water stress. The enhancements performed in the model broadened its predictive capabilities and proved that QualiTree allows for a better understanding of the water stress effects on fruit-tree functioning and might be useful for designing innovative horticultural practices in a changing climate scenario.

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

PubMed

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

2017-01-01

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

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.

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.

Simulation of metastatic progression using a computer model including chemotherapy and radiation therapy.

PubMed

Bethge, Anja; Schumacher, Udo; Wedemann, Gero

2015-10-01

Despite considerable research efforts, the process of metastasis formation is still a subject of intense discussion, and even established models differ considerably in basic details and in the conclusions drawn from them. Mathematical and computational models add a new perspective to the research as they can quantitatively investigate the processes of metastasis and the effects of treatment. However, existing models look at only one treatment option at a time. We enhanced a previously developed computer model (called CaTSiT) that enables quantitative comparison of different metastasis formation models with clinical and experimental data, to include the effects of chemotherapy, external beam radiation, radioimmunotherapy and radioembolization. CaTSiT is based on a discrete event simulation procedure. The growth of the primary tumor and its metastases is modeled by a piecewise-defined growth function that describes the growth behavior of the primary tumor and metastases during various time intervals. The piecewise-defined growth function is composed of analytical functions describing the growth behavior of the tumor based on characteristics of the tumor, such as dormancy, or the effects of various therapies. The spreading of malignant cells into the blood is modeled by intravasation events, which are generated according to a rate function. Further events in the model describe the behavior of the released malignant cells until the formation of a new metastasis. The model is published under the GNU General Public License version 3. To demonstrate the application of the computer model, a case of a patient with a hepatocellular carcinoma and multiple metastases in the liver was simulated. Besides the untreated case, different treatments were simulated at two time points: one directly after diagnosis of the primary tumor and the other several months later. Except for early applied radioimmunotherapy, no treatment strategy was able to eliminate all metastases. These results emphasize the importance of early diagnosis and of proceeding with treatment even if no clinically detectable metastases are present at the time of diagnosis of the primary tumor. CaTSiT could be a valuable tool for quantitative investigation of the process of tumor growth and metastasis formation, including the effects of various treatment options. Copyright © 2015 Elsevier Inc. All rights reserved.

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.

Discrete and continuous models for tissue growth and shrinkage.

PubMed

Yates, Christian A

2014-06-07

The incorporation of domain growth into stochastic models of biological processes is of increasing interest to mathematical modellers and biologists alike. In many situations, especially in developmental biology, the growth of the underlying tissue domain plays an important role in the redistribution of particles (be they cells or molecules) which may move and react atop the domain. Although such processes have largely been modelled using deterministic, continuum models there is an increasing appetite for individual-based stochastic models which can capture the fine details of the biological movement processes which are being elucidated by modern experimental techniques, and also incorporate the inherent stochasticity of such systems. In this work we study a simple stochastic model of domain growth. From a basic version of this model, Hywood et al. (2013) were able to derive a Fokker-Plank equation (FPE) (in this case an advection-diffusion partial differential equation on a growing domain) which describes the evolution of the probability density of some tracer particles on the domain. We extend their work so that a variety of different domain growth mechanisms can be incorporated and demonstrate a good agreement between the mean tracer density and the solution of the FPE in each case. In addition we incorporate domain shrinkage (via element death) into our individual-level model and demonstrate that we are able to derive coefficients for the FPE in this case as well. For situations in which the drift and diffusion coefficients are not readily available we introduce a numerical coefficient estimation approach and demonstrate the accuracy of this approach by comparing it with situations in which an analytical solution is obtainable. Copyright © 2014 Elsevier Ltd. All rights reserved.

Development of dynamic wheat crop model in ISAM and estimation of impacts of environmental factors on wheat production in India

NASA Astrophysics Data System (ADS)

Gahlot, S.; Lin, T. S.; Jain, A. K.; Baidya Roy, S.; Sehgal, V. K.; Dhakar, R.

2017-12-01

With changing environmental conditions, such as climate and elevated atmospheric CO2 concentrations, questions about food security can be answered by modeling crops based on our understanding of the dynamic crop growth processes and interactions between the crops and their environment in the form of carbon, water and energy fluxes. These interactions and their effect on cropland ecosystems are non-linear because of the feedback mechanisms. Hence, process-based modelling approach can be used to conduct numerical experiments to derive insights into these processes and interactive feedbacks. In this study we have implemented dynamic crop growth processes for wheat into a data-modeling framework, Integrated Science Assessment Model (ISAM), to estimate the impacts of different factors like CO2 fertilization, irrigation, nitrogen limitation and climate change on wheat in India. In specific, we have implemented wheat-specific phenology, C3 photosynthesis mechanism and phenology-specific carbon allocation schemes for assimilated carbon to leaf, stem, root and grain pools. Crop growth limiting stress factors like nutrients, temperature and light have been included. The impact of high temperatures on leaf senescence, anthesis and grain filling has been modeled and found to be causing significant reduction in yield in the recent years. Field data from an experimental wheat site located at the Indian Agricultural Research Institute (IARI), New Delhi, India has been collected for aboveground biomass and leaf area index (LAI) for two growing seasons 2014-15 and 2015-16. This data has been used to study the phenology, growing season length, thermal requirements and growth stages of wheat. Using the field data, the dynamic model for wheat has been evaluated for the site level seasonal variability in leaf area index (LAI) and aboveground biomass. The variations in carbon, water and energy fluxes, plant height and rooting depth have been analyzed on the site level. Model experiments have been performed to calculate the yield for wheat for India for the historical years. In order to identify wheat production regions in India that are prone to one or multiple stresses in years to come, model experiments have been performed based on future climate scenarios RCP 4.5 and 8.5.

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

PubMed

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

2014-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2018-07-01

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

Hormone-Mediated Pattern Formation in Seedling of Plants: a Competitive Growth Dynamics Model

NASA Astrophysics Data System (ADS)

Kawaguchi, Satoshi; Mimura, Masayasu; Ohya, Tomoyuki; Oikawa, Noriko; Okabe, Hirotaka; Kai, Shoichi

2001-10-01

An ecologically relevant pattern formation process mediated by hormonal interactions among growing seedlings is modeled based on the experimental observations on the effects of indole acetic acid, which can act as an inhibitor and activator of root growth depending on its concentration. In the absence of any lateral root with constant hormone-sensitivity, the edge effect phenomenon is obtained depending on the secretion rate of hormone from the main root. Introduction of growth-stage-dependent hormone-sensitivity drastically amplifies the initial randomness, resulting in spatially irregular macroscopic patterns. When the lateral root growth is introduced, periodic patterns are obtained whose periodicity depends on the length of lateral roots. The growth-stage-dependent hormone-sensitivity and the lateral root growth are crucial for macroscopic periodic-pattern formation.

Effects of doping impurity and growth orientation on dislocation generation in GaAs crystals grown from the melt: A qualitative finite-element study

NASA Astrophysics Data System (ADS)

Zhu, X. A.; Tsai, C. T.

2000-09-01

Dislocations in gallium arsenide (GaAs) crystals are generated by excessive thermal stresses induced during the crystal growth process. The presence of dislocations has adverse effects on the performance and reliability of the GaAs-based devices. It is well known that dislocation density can be significantly reduced by doping impurity atoms into a GaAs crystal during its growth process. A viscoplastic constitutive equation that couples the microscopic dislocation density with the macroscopic plastic deformation is employed in a crystallographic finite element model for calculating the dislocation density generated in the GaAs crystal during its growth process. The dislocation density is considered as an internal state variable and the drag stress caused by doping impurity is included in this constitutive equation. A GaAs crystal grown by the vertical Bridgman process is adopted as an example to study the influences of doping impurity and growth orientation on dislocation generation. The calculated results show that doping impurity can significantly reduce the dislocation density generated in the crystal. The level of reduction is also influenced by the growth orientation during the crystal growth process.

A Novel BA Complex Network Model on Color Template Matching

PubMed Central

Han, Risheng; Yue, Guangxue; Ding, Hui

2014-01-01

A novel BA complex network model of color space is proposed based on two fundamental rules of BA scale-free network model: growth and preferential attachment. The scale-free characteristic of color space is discovered by analyzing evolving process of template's color distribution. And then the template's BA complex network model can be used to select important color pixels which have much larger effects than other color pixels in matching process. The proposed BA complex network model of color space can be easily integrated into many traditional template matching algorithms, such as SSD based matching and SAD based matching. Experiments show the performance of color template matching results can be improved based on the proposed algorithm. To the best of our knowledge, this is the first study about how to model the color space of images using a proper complex network model and apply the complex network model to template matching. PMID:25243235

A novel BA complex network model on color template matching.

PubMed

Han, Risheng; Shen, Shigen; Yue, Guangxue; Ding, Hui

2014-01-01

A novel BA complex network model of color space is proposed based on two fundamental rules of BA scale-free network model: growth and preferential attachment. The scale-free characteristic of color space is discovered by analyzing evolving process of template's color distribution. And then the template's BA complex network model can be used to select important color pixels which have much larger effects than other color pixels in matching process. The proposed BA complex network model of color space can be easily integrated into many traditional template matching algorithms, such as SSD based matching and SAD based matching. Experiments show the performance of color template matching results can be improved based on the proposed algorithm. To the best of our knowledge, this is the first study about how to model the color space of images using a proper complex network model and apply the complex network model to template matching.

Issues of Spatial and Temporal Scale in Modeling the Effects of Field Operatiions on Soil Properties

USDA-ARS?s Scientific Manuscript database

Tillage is an important procedure for modifying the soil environment in order to enhance crop growth and conserve soil and water resources. Process-based models of crop production are widely used in decision support, but few explicitly simulate tillage. The Cropping Systems Model (CSM) was modified ...

Model for growth of fractal solid state surface and possibility of its verification by means of atomic force microscopy

NASA Astrophysics Data System (ADS)

Kulikov, D. A.; Potapov, A. A.; Rassadin, A. E.; Stepanov, A. V.

2017-10-01

In the paper, methods of verification of models for growth of solid state surface by means of atomic force microscopy are suggested. Simulation of growth of fractals with cylindrical generatrix on the solid state surface is presented. Our mathematical model of this process is based on generalization of the Kardar-Parisi-Zhang equation. Corner stones of this generalization are both conjecture of anisotropy of growth of the surface and approximation of small angles. The method of characteristics has been applied to solve the Kardar-Parisi-Zhang equation. Its solution should be considered up to the gradient catastrophe. The difficulty of nondifferentiability of fractal initial generatrix has been overcome by transition from a mathematical fractal to a physical one.

Modeling of an integrated fermentation/membrane extraction process for the production of 2-phenylethanol and 2-phenylethylacetate.

PubMed

Adler, Philipp; Hugen, Thorsten; Wiewiora, Marzena; Kunz, Benno

2011-03-07

An unstructured model for an integrated fermentation/membrane extraction process for the production of the aroma compounds 2-phenylethanol and 2-phenylethylacetate by Kluyveromyces marxianus CBS 600 was developed. The extent to which this model, based only on data from the conventional fermentation and separation processes, provided an estimation of the integrated process was evaluated. The effect of product inhibition on specific growth rate and on biomass yield by both aroma compounds was approximated by multivariate regression. Simulations of the respective submodels for fermentation and the separation process matched well with experimental results. With respect to the in situ product removal (ISPR) process, the effect of reduced product inhibition due to product removal on specific growth rate and biomass yield was predicted adequately by the model simulations. Overall product yields were increased considerably in this process (4.0 g/L 2-PE+2-PEA vs. 1.4 g/L in conventional fermentation) and were even higher than predicted by the model. To describe the effect of product concentration on product formation itself, the model was extended using results from the conventional and the ISPR process, thus agreement between model and experimental data improved notably. Therefore, this model can be a useful tool for the development and optimization of an efficient integrated bioprocess. Copyright © 2010 Elsevier Inc. All rights reserved.

Ag2S atomic switch-based `tug of war' for decision making

NASA Astrophysics Data System (ADS)

Lutz, C.; Hasegawa, T.; Chikyow, T.

2016-07-01

For a computing process such as making a decision, a software controlled chip of several transistors is necessary. Inspired by how a single cell amoeba decides its movements, the theoretical `tug of war' computing model was proposed but not yet implemented in an analogue device suitable for integrated circuits. Based on this model, we now developed a new electronic element for decision making processes, which will have no need for prior programming. The devices are based on the growth and shrinkage of Ag filaments in α-Ag2+δS gap-type atomic switches. Here we present the adapted device design and the new materials. We demonstrate the basic `tug of war' operation by IV-measurements and Scanning Electron Microscopy (SEM) observation. These devices could be the base for a CMOS-free new computer architecture.For a computing process such as making a decision, a software controlled chip of several transistors is necessary. Inspired by how a single cell amoeba decides its movements, the theoretical `tug of war' computing model was proposed but not yet implemented in an analogue device suitable for integrated circuits. Based on this model, we now developed a new electronic element for decision making processes, which will have no need for prior programming. The devices are based on the growth and shrinkage of Ag filaments in α-Ag2+δS gap-type atomic switches. Here we present the adapted device design and the new materials. We demonstrate the basic `tug of war' operation by IV-measurements and Scanning Electron Microscopy (SEM) observation. These devices could be the base for a CMOS-free new computer architecture. Electronic supplementary information (ESI) available. See DOI: 10.1039/c6nr00690f

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

PubMed

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

2017-01-01

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

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.

Fractal dimension and universality in avascular tumor growth

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

Interspecific variation in growth responses to climate and competition of five eastern tree species.

PubMed

Rollinson, Christine R; Kaye, Margot W; Canham, Charles D

2016-04-01

Climate and competition are often presented from two opposing views of the dominant driver of individual tree growth and species distribution in temperate forests, such as those in the eastern United States. Previous studies have provided abundant evidence indicating that both factors influence tree growth, and we argue that these effects are not independent of one another and rather that interactions between climate, competition, and size best describe tree growth. To illustrate this point, we describe the growth responses of five common eastern tree species to interacting effects of temperature, precipitation, competition, and individual size using maximum likelihood estimation. Models that explicitly include interactions among these four factors explained over half of the variance in annual growth for four out of five species using annual climate. Expanding temperature and precipitation analyses to include seasonal interactions resulted in slightly improved models with a mean R2 of 0.61 (SD 0.10). Growth responses to individual factors as well their interactions varied greatly among species. For example, growth sensitivity to temperature for Quercus rubra increased with maximum annual precipitation, but other species showed no change in sensitivity or slightly reduced annual growth. Our results also indicate that three-way interactions among individual stem size, competition, and temperature may determine which of the five co-occurring species in our study could have the highest growth rate in a given year. Continued consideration and quantification of interactions among climate, competition, and individual-based characteristics are likely to increase understanding of key biological processes such as tree growth. Greater parameterization of interactions between traditionally segregated factors such as climate and competition may also help build a framework to reconcile drivers of individual-based processes such as growth with larger-scale patterns of species distribution.

Temporal consistency of spatial pattern in growth of the mussel, Mytilus edulis: Implications for predictive modelling

NASA Astrophysics Data System (ADS)

Bergström, Per; Lindegarth, Susanne; Lindegarth, Mats

2013-10-01

Human pressures on coastal seas are increasing and methods for sustainable management, including spatial planning and mitigative actions, are therefore needed. In coastal areas worldwide, the development of mussel farming as an economically and ecologically sustainable industry requires geographic information on the growth and potential production capacity. In practice this means that coherent maps of temporally stable spatial patterns of growth need to be available in the planning process and that maps need to be based on mechanistic or empirical models. Therefore, as a first step towards development of models of growth, we assessed empirically the fundamental requirement that there are temporally consistent spatial patterns of growth in the blue mussel, Mytilus edulis. Using a pilot study we designed and dimensioned a transplant experiment, where the spatial consistency in the growth of mussels was evaluated at two resolutions. We found strong temporal and scale-dependent spatial variability in growth but patterns suggested that spatial patterns were uncoupled between growth of shell and that of soft tissue. Spatial patterns of shell growth were complex and largely inconsistent among years. Importantly, however, the growth of soft tissue was qualitatively consistent among years at the scale of km. The results suggest that processes affecting the whole coastal area cause substantial differences in growth of soft tissue among years but that factors varying at the scale of km create strong and persistent spatial patterns of growth, with a potential doubling of productivity by identifying the most suitable locations. We conclude that the observed spatial consistency provides a basis for further development of predictive modelling and mapping of soft tissue growth in these coastal areas. Potential causes of observed patterns, consequences for mussel-farming as a tool for mitigating eutrophication, aspects of precision of modelling and sampling of mussel growth as well as ecological functions in general are discussed.

The Nucleation and Growth of Protein Crystals

NASA Technical Reports Server (NTRS)

Pusey, Marc

2004-01-01

Obtaining crystals of suitable size and high quality continues to be a major bottleneck in macromolecular crystallography. Currently, structural genomics efforts are achieving on average about a 10% success rate in going from purified protein to a deposited crystal structure. Growth of crystals in microgravity was proposed as a means of overcoming size and quality problems, which subsequently led to a major NASA effort in microgravity crystal growth, with the agency also funding research into understanding the process. Studies of the macromolecule crystal nucleation and growth process were carried out in a number of labs in an effort to understand what affected the resultant crystal quality on Earth, and how microgravity improved the process. Based upon experimental evidence, as well as simple starting assumptions, we have proposed that crystal nucleation occurs by a series of discrete self assembly steps, which 'set' the underlying crystal symmetry. This talk will review the model developed, and its origins, in our laboratory for how crystals nucleate and grow, and will then present, along with preliminary data, how we propose to use this model to improve the success rate for obtaining crystals from a given protein.

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

PubMed

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

2016-12-14

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

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

PubMed Central

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

2016-01-01

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

Stochastic model for fatigue crack size and cost effective design decisions. [for aerospace structures

NASA Technical Reports Server (NTRS)

Hanagud, S.; Uppaluri, B.

1975-01-01

This paper describes a methodology for making cost effective fatigue design decisions. The methodology is based on a probabilistic model for the stochastic process of fatigue crack growth with time. The development of a particular model for the stochastic process is also discussed in the paper. The model is based on the assumption of continuous time and discrete space of crack lengths. Statistical decision theory and the developed probabilistic model are used to develop the procedure for making fatigue design decisions on the basis of minimum expected cost or risk function and reliability bounds. Selections of initial flaw size distribution, NDT, repair threshold crack lengths, and inspection intervals are discussed.

Modeling Calculation and Synthesis of Alumina Whiskers Based on the Vapor Deposition Process.

PubMed

Gong, Wei; Li, Xiangcheng; Zhu, Boquan

2017-10-17

This study simulated the bulk structure and surface energy of Al₂O₃ based on the density of states (DOS) and studied the synthesis and microstructure of one-dimensional Al₂O₃ whiskers. The simulation results indicate that the (001) surface has a higher surface energy than the others. The growth mechanism of Al₂O₃ whiskers follows vapor-solid (VS) growth. For the (001) surface with the higher surface energy, the driving force of crystal growth would be more intense in the (001) plane, and the alumina crystal would tend to grow preferentially along the direction of the (001) plane from the tip of the crystal. The Al₂O₃ grows to the shape of whisker with [001] orientation, which is proved both through modeling and experimentation.

Kinetics modeling of precipitation with characteristic shape during post-implantation annealing

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

Li, Kun-Dar, E-mail: kundar@mail.nutn.edu.tw; Chen, Kwanyu

2015-11-15

In this study, we investigated the precipitation with characteristic shape in the microstructure during post-implantation annealing via a theoretical modeling approach. The processes of precipitates formation and evolution during phase separation were based on a nucleation and growth mechanism of atomic diffusion. Different stages of the precipitation, including the nucleation, growth and coalescence, were distinctly revealed in the numerical simulations. In addition, the influences of ion dose, temperature and crystallographic symmetry on the processes of faceted precipitation were also demonstrated. To comprehend the kinetic mechanism, the simulation results were further analyzed quantitatively by the Kolmogorov-Johnson-Mehl-Avrami (KJMA) equation. The Avrami exponentsmore » obtained from the regression curves varied from 1.47 to 0.52 for different conditions. With the increase of ion dose and temperature, the nucleation and growth of precipitations were expedited in accordance with the shortened incubation time and the raised coefficient of growth rate. A miscellaneous shape of precipitates in various crystallographic symmetry systems could be simulated through this anisotropic model. From the analyses of the kinetics, more fundamental information about the nucleation and growth mechanism of faceted precipitation during post-implantation annealing was acquired for future application.« less

Knowledge Ecology for Conceptual Growth: Teachers as Active Agents in Developing a Pluriliteracies Approach to Teaching for Learning (PTL)

ERIC Educational Resources Information Center

Coyle, Do; Halbach, Ana; Meyer, Oliver; Schuck, Kevin

2018-01-01

This article explores how a group of educators and researchers enacted an inclusive process of conceptual growth involving teachers and teacher educators as active agents, knowledge builders and meaning-makers in the development of a Pluriliteracies approach to Teaching for Learning (PTL). The evolution of a working model based on five emergent…

Using the SWAT model to improve process descriptions and define hydrologic partitioning in South Korea

NASA Astrophysics Data System (ADS)

Shope, C. L.; Maharjan, G. R.; Tenhunen, J.; Seo, B.; Kim, K.; Riley, J.; Arnhold, S.; Koellner, T.; Ok, Y. S.; Peiffer, S.; Kim, B.; Park, J.-H.; Huwe, B.

2014-02-01

Watershed-scale modeling can be a valuable tool to aid in quantification of water quality and yield; however, several challenges remain. In many watersheds, it is difficult to adequately quantify hydrologic partitioning. Data scarcity is prevalent, accuracy of spatially distributed meteorology is difficult to quantify, forest encroachment and land use issues are common, and surface water and groundwater abstractions substantially modify watershed-based processes. Our objective is to assess the capability of the Soil and Water Assessment Tool (SWAT) model to capture event-based and long-term monsoonal rainfall-runoff processes in complex mountainous terrain. To accomplish this, we developed a unique quality-control, gap-filling algorithm for interpolation of high-frequency meteorological data. We used a novel multi-location, multi-optimization calibration technique to improve estimations of catchment-wide hydrologic partitioning. The interdisciplinary model was calibrated to a unique combination of statistical, hydrologic, and plant growth metrics. Our results indicate scale-dependent sensitivity of hydrologic partitioning and substantial influence of engineered features. The addition of hydrologic and plant growth objective functions identified the importance of culverts in catchment-wide flow distribution. While this study shows the challenges of applying the SWAT model to complex terrain and extreme environments; by incorporating anthropogenic features into modeling scenarios, we can enhance our understanding of the hydroecological impact.

Phenotypic switching of populations of cells in a stochastic environment

NASA Astrophysics Data System (ADS)

Hufton, Peter G.; Lin, Yen Ting; Galla, Tobias

2018-02-01

In biology phenotypic switching is a common bet-hedging strategy in the face of uncertain environmental conditions. Existing mathematical models often focus on periodically changing environments to determine the optimal phenotypic response. We focus on the case in which the environment switches randomly between discrete states. Starting from an individual-based model we derive stochastic differential equations to describe the dynamics, and obtain analytical expressions for the mean instantaneous growth rates based on the theory of piecewise-deterministic Markov processes. We show that optimal phenotypic responses are non-trivial for slow and intermediate environmental processes, and systematically compare the cases of periodic and random environments. The best response to random switching is more likely to be heterogeneity than in the case of deterministic periodic environments, net growth rates tend to be higher under stochastic environmental dynamics. The combined system of environment and population of cells can be interpreted as host-pathogen interaction, in which the host tries to choose environmental switching so as to minimise growth of the pathogen, and in which the pathogen employs a phenotypic switching optimised to increase its growth rate. We discuss the existence of Nash-like mutual best-response scenarios for such host-pathogen games.

Forward modeling of tree-ring data: a case study with a global network

NASA Astrophysics Data System (ADS)

Breitenmoser, P. D.; Frank, D.; Brönnimann, S.

2012-04-01

Information derived from tree-rings is one of the most powerful tools presently available for studying past climatic variability as well as identifying fundamental relationships between tree-growth and climate. Climate reconstructions are typically performed by extending linear relationships, established during the overlapping period of instrumental and climate proxy archives into the past. Such analyses, however, are limited by methodological assumptions, including stationarity and linearity of the climate-proxy relationship. We investigate climate and tree-ring data using the Vaganov-Shashkin-Lite (VS-Lite) forward model of tree-ring width formation to examine the relations among actual tree growth and climate (as inferred from the simulated chronologies) to reconstruct past climate variability. The VS-lite model has been shown to produce skill comparable to that achieved using classical dendrochronological statistical modeling techniques when applied on simulations of a network of North American tree-ring chronologies. Although the detailed mechanistic processes such as photosynthesis, storage, or cell processes are not modeled directly, the net effect of the dominating nonlinear climatic controls on tree-growth are implemented into the model by the principle of limiting factors and threshold growth response functions. The VS-lite model requires as inputs only latitude, monthly mean temperature and monthly accumulated precipitation. Hence, this simple, process-based model enables ring-width simulation at any location where monthly climate records exist. In this study, we analyse the growth response of simulated tree-rings to monthly climate conditions obtained from the 20th century reanalysis project back to 1871. These simulated tree-ring chronologies are compared to the climate-driven variability in worldwide observed tree-ring chronologies from the International Tree Ring Database. Results point toward the suitability of the relationship among actual tree growth and climate (as inferred from the simulated chronologies) for use in global palaeoclimate reconstructions.

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

NASA Astrophysics Data System (ADS)

Shafizadeh-Moghadam, Hossein; Helbich, Marco

2015-03-01

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

Comparing crop growth and carbon budgets simulated across AmeriFlux agricultural sites using the community land model (CLM)

USDA-ARS?s Scientific Manuscript database

Improving process-based crop models is needed to achieve high fidelity forecasts of regional energy, water, and carbon exchange. However, most state-of-the-art Land Surface Models (LSMs) assessed in the fifth phase of the Coupled Model Inter-comparison project (CMIP5) simulated crops as simple C3 or...

SuMoToRI, an Ecophysiological Model to Predict Growth and Sulfur Allocation and Partitioning in Oilseed Rape (Brassica napus L.) Until the Onset of Pod Formation

PubMed Central

Brunel-Muguet, Sophie; Mollier, Alain; Kauffmann, François; Avice, Jean-Christophe; Goudier, Damien; Sénécal, Emmanuelle; Etienne, Philippe

2015-01-01

Sulfur (S) nutrition in rapeseed (Brassica napus L.) is a major concern for this high S-demanding crop, especially in the context of soil S oligotrophy. Therefore, predicting plant growth, S plant allocation (between the plant’s compartments) and S pool partitioning (repartition of the mobile-S vs. non-mobile-S fractions) until the onset of reproductive phase could help in the diagnosis of S deficiencies during the early stages. For this purpose, a process-based model, SuMoToRI (Sulfur Model Toward Rapeseed Improvement), was developed up to the onset of pod formation. The key features rely on (i) the determination of the S requirements used for growth (structural and metabolic functions) through critical S dilution curves and (ii) the estimation of a mobile pool of S that is regenerated by daily S uptake and remobilization from senescing leaves. This study describes the functioning of the model and presents the model’s calibration and evaluation. SuMoToRI was calibrated and evaluated with independent datasets from greenhouse experiments under contrasting S supply conditions. It is run with a small number of parameters with generic values, except in the case of the radiation use efficiency, which was shown to be modulated by S supply. The model gave satisfying predictions of the dynamics of growth, S allocation between compartments and S partitioning, such as the mobile-S fraction in the leaves, which is an indicator of the remobilization potential toward growing sinks. The mechanistic features of SuMoToRI provide a process-based framework that has enabled the description of the S remobilizing process in a species characterized by senescence during the vegetative phase. We believe that this model structure could be useful for modeling S dynamics in other arable crops that have similar senescence-related characteristics. PMID:26635825

Using energy budgets to combine ecology and toxicology in a mammalian sentinel species

NASA Astrophysics Data System (ADS)

Desforges, Jean-Pierre W.; Sonne, Christian; Dietz, Rune

2017-04-01

Process-driven modelling approaches can resolve many of the shortcomings of traditional descriptive and non-mechanistic toxicology. We developed a simple dynamic energy budget (DEB) model for the mink (Mustela vison), a sentinel species in mammalian toxicology, which coupled animal physiology, ecology and toxicology, in order to mechanistically investigate the accumulation and adverse effects of lifelong dietary exposure to persistent environmental toxicants, most notably polychlorinated biphenyls (PCBs). Our novel mammalian DEB model accurately predicted, based on energy allocations to the interconnected metabolic processes of growth, development, maintenance and reproduction, lifelong patterns in mink growth, reproductive performance and dietary accumulation of PCBs as reported in the literature. Our model results were consistent with empirical data from captive and free-ranging studies in mink and other wildlife and suggest that PCB exposure can have significant population-level impacts resulting from targeted effects on fetal toxicity, kit mortality and growth and development. Our approach provides a simple and cross-species framework to explore the mechanistic interactions of physiological processes and ecotoxicology, thus allowing for a deeper understanding and interpretation of stressor-induced adverse effects at all levels of biological organization.

Combining a generic process-based productivity model classification method to predict the presence and absence species in the Pacific Northwest, U.S.A

Treesearch

Nicholas C. Coops; Richard H. Waring; Todd A. Schroeder

2009-01-01

Although long-lived tree species experience considerable environmental variation over their life spans, their geographical distributions reflect sensitivity mainly to mean monthly climatic conditions.We introduce an approach that incorporates a physiologically based growth model to illustrate how a half-dozen tree species differ in their responses to monthly variation...

A statistical analysis of three ensembles of crop model responses to temperature and CO2 concentration

USDA-ARS?s Scientific Manuscript database

Ensembles of process-based crop models are now commonly used to simulate crop growth and development for climate scenarios of temperature and/or precipitation changes corresponding to different projections of atmospheric CO2 concentrations. This approach generates large datasets with thousands of de...

Linking Agricultural Crop Management and Air Quality Models for Regional to National-Scale Nitrogen Assessments

EPA Science Inventory

While nitrogen (N) is an essential element for life, human population growth and demands for energy, transportation and food can lead to excess nitrogen in the environment. A modeling framework is described and implemented to promote a more integrated, process-based and system le...

Consequences of cannibalism and competition for food in a smallmouth bass population: An individual-based modeling study

USGS Publications Warehouse

Dong, Q.; DeAngelis, D.L.

1998-01-01

We used an individual-based modeling approach to study the consequences of cannibalism and competition for food in a freshwater fish population. We simulated the daily foraging, growth, and survival of the age-0 fish and older juvenile individuals of a sample population to reconstruct patterns of density dependence in the age-0 fish during the growth season. Cannibalism occurs as a part of the foraging process. For age-0 fish, older juvenile fish are both potential cannibals and competitors of food. We found that competition and cannibalism produced intraclass and interclass density dependence. Our modeling results suggested the following. (1) With low density of juvenile fish and weak interclass interactions, the age-0 fish recruitment shows a Beverton-Holt type of density dependence. (2) With high density of juvenile fish and strong interclass interactions, the age-0 fish recruitment shows a Ricker type of density dependence, and overcompensation occurs. (3) Interclass competition of food is responsible for much of the overcompensation. (4) Cannibalism intensifies the changes in the recruitment that are brought about by competition. Cannibalism can (a) generally reduce the recruitment, (b) particularly reduce the maximum level of recruitment, (c) cause overcompensation to occur at lower densities, and (d) produce a stronger overcompensation. (5) Growth is also a function of density. Cannibalism generally improves average growth of cannibals. (6) Variation in the lengths of age-0 fish increases with density and with a decreased average growth. These results imply that cannibalism and competition for food could strongly affect recruitment dynamics. Our model also showed that the rate of cannibalism either could be fairly even through the whole season or could vary dramatically. The individual-based modeling approach can help ecologists understand the mechanistic connection between daily behavioral and physiological processes operating at the level of individual organisms and seasonal patterns of population structure and dynamics. ?? Copyright by the American Fisheries Society 1998.

Plant growth modelling and applications: the increasing importance of plant architecture in growth models.

PubMed

Fourcaud, Thierry; Zhang, Xiaopeng; Stokes, Alexia; Lambers, Hans; Körner, Christian

2008-05-01

Modelling plant growth allows us to test hypotheses and carry out virtual experiments concerning plant growth processes that could otherwise take years in field conditions. The visualization of growth simulations allows us to see directly and vividly the outcome of a given model and provides us with an instructive tool useful for agronomists and foresters, as well as for teaching. Functional-structural (FS) plant growth models are nowadays particularly important for integrating biological processes with environmental conditions in 3-D virtual plants, and provide the basis for more advanced research in plant sciences. In this viewpoint paper, we ask the following questions. Are we modelling the correct processes that drive plant growth, and is growth driven mostly by sink or source activity? In current models, is the importance of soil resources (nutrients, water, temperature and their interaction with meristematic activity) considered adequately? Do classic models account for architectural adjustment as well as integrating the fundamental principles of development? Whilst answering these questions with the available data in the literature, we put forward the opinion that plant architecture and sink activity must be pushed to the centre of plant growth models. In natural conditions, sinks will more often drive growth than source activity, because sink activity is often controlled by finite soil resources or developmental constraints. PMA06: This viewpoint paper also serves as an introduction to this Special Issue devoted to plant growth modelling, which includes new research covering areas stretching from cell growth to biomechanics. All papers were presented at the Second International Symposium on Plant Growth Modeling, Simulation, Visualization and Applications (PMA06), held in Beijing, China, from 13-17 November, 2006. Although a large number of papers are devoted to FS models of agricultural and forest crop species, physiological and genetic processes have recently been included and point the way to a new direction in plant modelling research.

Mechanochemical Modeling of Dynamic Microtubule Growth Involving Sheet-to-Tube Transition

PubMed Central

Ji, Xiang-Ying; Feng, Xi-Qiao

2011-01-01

Microtubule dynamics is largely influenced by nucleotide hydrolysis and the resultant tubulin configuration changes. The GTP cap model has been proposed to interpret the stabilizing mechanisms of microtubule growth from the view of hydrolysis effects. Besides, the growth of a microtubule involves the closure of a curved sheet at its growing end. The curvature conversion from the longitudinal direction to the circumferential direction also helps to stabilize the successive growth, and the curved sheet is referred to as the conformational cap. However, there still lacks theoretical investigation on the mechanical–chemical coupling growth process of microtubules. In this paper, we study the growth mechanisms of microtubules by using a coarse-grained molecular method. First, the closure process involving a sheet-to-tube transition is simulated. The results verify the stabilizing effect of the sheet structure and predict that the minimum conformational cap length that can stabilize the growth is two dimers. Then, we show that the conformational cap and the GTP cap can function independently and harmoniously, signifying the pivotal role of mechanical factors. Furthermore, based on our theoretical results, we describe a Tetris-like growth style of microtubules: the stochastic tubulin assembly is regulated by energy and harmonized with the seam zipping such that the sheet keeps a practically constant length during growth. PMID:22205994

Creating a stage-based deterministic PVA model - the western prairie fringed orchid [Exercise 12

Treesearch

Carolyn Hull Sieg; Rudy M. King; Fred Van Dyke

2003-01-01

Contemporary efforts to conserve populations and species often employ population viability analysis (PVA), a specific application of population modeling that estimates the effects of environmental and demographic processes on population growth rates. These models can also be used to estimate probabilities that a population will fall below a certain level. This...

Modeling the Non-Equilibrium Process of the Chemical Adsorption of Ammonia on GaN(0001) Reconstructed Surfaces Based on Steepest-Entropy-Ascent Quantum Thermodynamics.

PubMed

Kusaba, Akira; Li, Guanchen; von Spakovsky, Michael R; Kangawa, Yoshihiro; Kakimoto, Koichi

2017-08-15

Clearly understanding elementary growth processes that depend on surface reconstruction is essential to controlling vapor-phase epitaxy more precisely. In this study, ammonia chemical adsorption on GaN(0001) reconstructed surfaces under metalorganic vapor phase epitaxy (MOVPE) conditions (3Ga-H and N ad -H + Ga-H on a 2 × 2 unit cell) is investigated using steepest-entropy-ascent quantum thermodynamics (SEAQT). SEAQT is a thermodynamic-ensemble based, first-principles framework that can predict the behavior of non-equilibrium processes, even those far from equilibrium where the state evolution is a combination of reversible and irreversible dynamics. SEAQT is an ideal choice to handle this problem on a first-principles basis since the chemical adsorption process starts from a highly non-equilibrium state. A result of the analysis shows that the probability of adsorption on 3Ga-H is significantly higher than that on N ad -H + Ga-H. Additionally, the growth temperature dependence of these adsorption probabilities and the temperature increase due to the heat of reaction is determined. The non-equilibrium thermodynamic modeling applied can lead to better control of the MOVPE process through the selection of preferable reconstructed surfaces. The modeling also demonstrates the efficacy of DFT-SEAQT coupling for determining detailed non-equilibrium process characteristics with a much smaller computational burden than would be entailed with mechanics-based, microscopic-mesoscopic approaches.

Modeling the Non-Equilibrium Process of the Chemical Adsorption of Ammonia on GaN(0001) Reconstructed Surfaces Based on Steepest-Entropy-Ascent Quantum Thermodynamics

PubMed Central

Kusaba, Akira; von Spakovsky, Michael R.; Kangawa, Yoshihiro; Kakimoto, Koichi

2017-01-01

Clearly understanding elementary growth processes that depend on surface reconstruction is essential to controlling vapor-phase epitaxy more precisely. In this study, ammonia chemical adsorption on GaN(0001) reconstructed surfaces under metalorganic vapor phase epitaxy (MOVPE) conditions (3Ga-H and Nad-H + Ga-H on a 2 × 2 unit cell) is investigated using steepest-entropy-ascent quantum thermodynamics (SEAQT). SEAQT is a thermodynamic-ensemble based, first-principles framework that can predict the behavior of non-equilibrium processes, even those far from equilibrium where the state evolution is a combination of reversible and irreversible dynamics. SEAQT is an ideal choice to handle this problem on a first-principles basis since the chemical adsorption process starts from a highly non-equilibrium state. A result of the analysis shows that the probability of adsorption on 3Ga-H is significantly higher than that on Nad-H + Ga-H. Additionally, the growth temperature dependence of these adsorption probabilities and the temperature increase due to the heat of reaction is determined. The non-equilibrium thermodynamic modeling applied can lead to better control of the MOVPE process through the selection of preferable reconstructed surfaces. The modeling also demonstrates the efficacy of DFT-SEAQT coupling for determining detailed non-equilibrium process characteristics with a much smaller computational burden than would be entailed with mechanics-based, microscopic-mesoscopic approaches. PMID:28809816

Suppression of Metastasis by Primary Tumor and Acceleration of Metastasis Following Primary Tumor Resection: A Natural Law?

PubMed

Hanin, Leonid; Rose, Jason

2018-03-01

We study metastatic cancer progression through an extremely general individual-patient mathematical model that is rooted in the contemporary understanding of the underlying biomedical processes yet is essentially free of specific biological assumptions of mechanistic nature. The model accounts for primary tumor growth and resection, shedding of metastases off the primary tumor and their selection, dormancy and growth in a given secondary site. However, functional parameters descriptive of these processes are assumed to be essentially arbitrary. In spite of such generality, the model allows for computing the distribution of site-specific sizes of detectable metastases in closed form. Under the assumption of exponential growth of metastases before and after primary tumor resection, we showed that, regardless of other model parameters and for every set of site-specific volumes of detected metastases, the model-based likelihood-maximizing scenario is always the same: complete suppression of metastatic growth before primary tumor resection followed by an abrupt growth acceleration after surgery. This scenario is commonly observed in clinical practice and is supported by a wealth of experimental and clinical studies conducted over the last 110 years. Furthermore, several biological mechanisms have been identified that could bring about suppression of metastasis by the primary tumor and accelerated vascularization and growth of metastases after primary tumor resection. To the best of our knowledge, the methodology for uncovering general biomedical principles developed in this work is new.

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.

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

PubMed

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

2018-04-02

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

Numerical Simulation of Nanostructure Growth

NASA Technical Reports Server (NTRS)

Hwang, Helen H.; Bose, Deepak; Govindan, T. R.; Meyyappan, M.

2004-01-01

Nanoscale structures, such as nanowires and carbon nanotubes (CNTs), are often grown in gaseous or plasma environments. Successful growth of these structures is defined by achieving a specified crystallinity or chirality, size or diameter, alignment, etc., which in turn depend on gas mixture ratios. pressure, flow rate, substrate temperature, and other operating conditions. To date, there has not been a rigorous growth model that addresses the specific concerns of crystalline nanowire growth, while demonstrating the correct trends of the processing conditions on growth rates. Most crystal growth models are based on the Burton, Cabrera, and Frank (BCF) method, where adatoms are incorporated into a growing crystal at surface steps or spirals. When the supersaturation of the vapor is high, islands nucleate to form steps, and these steps subsequently spread (grow). The overall bulk growth rate is determined by solving for the evolving motion of the steps. Our approach is to use a phase field model to simulate the growth of finite sized nanowire crystals, linking the free energy equation with the diffusion equation of the adatoms. The phase field method solves for an order parameter that defines the evolving steps in a concentration field. This eliminates the need for explicit front tracking/location, or complicated shadowing routines, both of which can be computationally expensive, particularly in higher dimensions. We will present results demonstrating the effect of process conditions, such as substrate temperature, vapor supersaturation, etc. on the evolving morphologies and overall growth rates of the nanostructures.

Nucleation, aggregative growth and detachment of metal nanoparticles during electrodeposition at electrode surfaces.

PubMed

Lai, Stanley C S; Lazenby, Robert A; Kirkman, Paul M; Unwin, Patrick R

2015-02-01

The nucleation and growth of metal nanoparticles (NPs) on surfaces is of considerable interest with regard to creating functional interfaces with myriad applications. Yet, key features of these processes remain elusive and are undergoing revision. Here, the mechanism of the electrodeposition of silver on basal plane highly oriented pyrolytic graphite (HOPG) is investigated as a model system at a wide range of length scales, spanning electrochemical measurements from the macroscale to the nanoscale using scanning electrochemical cell microscopy (SECCM), a pipette-based approach. The macroscale measurements show that the nucleation process cannot be modelled as either truly instantaneous or progressive, and that step edge sites of HOPG do not play a dominant role in nucleation events compared to the HOPG basal plane, as has been widely proposed. Moreover, nucleation numbers extracted from electrochemical analysis do not match those determined by atomic force microscopy (AFM). The high time and spatial resolution of the nanoscale pipette set-up reveals individual nucleation and growth events at the graphite basal surface that are resolved and analysed in detail. Based on these results, corroborated with complementary microscopy measurements, we propose that a nucleation-aggregative growth-detachment mechanism is an important feature of the electrodeposition of silver NPs on HOPG. These findings have major implications for NP electrodeposition and for understanding electrochemical processes at graphitic materials generally.

Ductile fracture theories for pressurised pipes and containers

NASA Technical Reports Server (NTRS)

Erdogan, F.

1976-01-01

Two mechanisms of fracture are distinguished. Plane strain fractures occur in materials which do not undergo large-scale plastic deformations prior to and during a possible fracture deformation. Plane stress or high energy fractures are generally accompanied by large inelastic deformations. Theories for analyzing plane stress are based on the concepts of critical crack opening stretch, K(R) characterization, J-integral, and plastic instability. This last is considered in some detail. The ductile fracture process involves fracture initiation followed by a stable crack growth and the onset of unstable fracture propagation. The ductile fracture propagation process may be characterized by either a multiparameter (discrete) model, or some type of a resistance curve which may be considered as a continuous model expressed graphically. These models are studied and an alternative model is also proposed for ductile fractures which cannot be modeled as progressive crack growth phenomena.

Modeling Tetragonal Lysozyme Crystal Growth Rates

NASA Technical Reports Server (NTRS)

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

2003-01-01

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

DOE Final Report: A Unified Understanding of Residual Stress in Thin Films: Kinetic Models, Experiments and Simulations

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

Chason, Eric

Thin films are critical for a wide range of advanced technologies. However, the deposited films often have high levels of residual stress that can limit their performance or lead to failure. The stress is known to depend on many variables, including the processing conditions, type of material, deposition technique and the film’s microstructure. The goal of this DOE program was to develop a fundamental understanding of how the different processes that control thin film growth under different conditions can be related to the development of stress. In the program, systematic experiments were performed or analyzed that related the stress tomore » the processing conditions that were used. Measurements of stress were obtained for films that were grown at different rates, different solutions (for electrodeposition), different particle energies (for sputter deposition) and different microstructures. Based on this data, models were developed to explain the observed dependence on the different parameters. The models were based on considering the balance among different stress-inducing mechanism occurring as the film grows (for both non-energetic and energetic deposition). Comparison of the model predictions with the experiments enabled the kinetic parameters to be determined for different materials. The resulting model equations provide a comprehensive picture of how stress changes with the processing conditions that can be used to optimize the growth of thin films.« less

Modeling of frost crystal growth over a flat plate using artificial neural networks and fractal geometries

NASA Astrophysics Data System (ADS)

Tahavvor, Ali Reza

2017-03-01

In the present study artificial neural network and fractal geometry are used to predict frost thickness and density on a cold flat plate having constant surface temperature under forced convection for different ambient conditions. These methods are very applicable in this area because phase changes such as melting and solidification are simulated by conventional methods but frost formation is a most complicated phase change phenomenon consists of coupled heat and mass transfer. Therefore conventional mathematical techniques cannot capture the effects of all parameters on its growth and development because this process influenced by many factors and it is a time dependent process. Therefore, in this work soft computing method such as artificial neural network and fractal geometry are used to do this manner. The databases for modeling are generated from the experimental measurements. First, multilayer perceptron network is used and it is found that the back-propagation algorithm with Levenberg-Marquardt learning rule is the best choice to estimate frost growth properties due to accurate and faster training procedure. Second, fractal geometry based on the Von-Koch curve is used to model frost growth procedure especially in frost thickness and density. Comparison is performed between experimental measurements and soft computing methods. Results show that soft computing methods can be used more efficiently to determine frost properties over a flat plate. Based on the developed models, wide range of frost formation over flat plates can be determined for various conditions.

Condensational Droplet Growth in Rarefied Quiescent Vapor and Forced Convective Conditions

NASA Astrophysics Data System (ADS)

Anand, Sushant

Multiphase Heat transfer is ubiquitous in diverse fields of application such as cooling systems, micro and mini power systems and many chemical processes. By now, single phase dynamics are mostly understood in their applications in vast fields, however multiphase systems especially involving phase changes are still a challenge. Present study aims to enhance understanding in this domain especially in the field of condensation heat transfer. Of special relevance to present studies is study of condensation phenomenon for detection of airborne nanoparticles using heterogeneous nucleation. Detection of particulate matter in the environment via heterogeneous condensation is based on the droplet growth phenomenon where seeding particles in presence of supersaturated vapor undergo condensation on their surface and amplify in size to micrometric ranges, thereby making them optically visible. Previous investigations show that condensation is a molecular exchange process affected by mean free path of vapor molecules (lambda) in conjunction with size of condensing droplet (d), which is measured in terms of Knudsen number (Kn=lambda/ d). In an event involving heterogeneous nucleation with favorable thermodynamic conditions for condensation to take place, the droplet growth process begins with accretion of vapor molecules on a surface through random molecular collision (Kn>1) until diffusive forces start dominating the mass transport process (Kn<<1). Knowledge of droplet growth thus requires understanding of mass transport in both of these regimes. Present study aims to understand the dynamics of the Microthermofluidic sensor which has been developed, based on above mentioned fundamentals. Using continuum approach, numerical modeling was carried to understand the effect of various system parameters for improving the device performance to produce conditions which can lead to conditions abetting condensational growth. The study reveals that the minimum size of nanoparticle which can be detected is critically dependent upon controlling wall geometry and size, wall temperature, flow rate and relative humidity of nanoparticle laden air stream. Droplet growths rates and sizes have been predicted based on different models. The efficacy of the device under various conditions has been measured in terms of its ability to activate nanoparticles of different sizes. Since the condensation mechanism is dependent upon the Knudsen regime in which droplets are growing via condensation, special consideration was made to understand their behavior in large Knudsen number conditions. For this purpose, ESEM was used to study condensation on a bare surface. Droplet growth obtained as a function of time reveals that the rate of growth decreases as the droplet increases in size. The experimental results obtained from these experiments were matched with theoretical description provided by a model based on framework of kinetic theory. Evidence was also found which establishes the presence of submicroscopic droplets nucleating and growing in between microscopic droplets for partially wetting case.

Micromechanics based simulation of ductile fracture in structural steels

NASA Astrophysics Data System (ADS)

Yellavajjala, Ravi Kiran

The broader aim of this research is to develop fundamental understanding of ductile fracture process in structural steels, propose robust computational models to quantify the associated damage, and provide numerical tools to simplify the implementation of these computational models into general finite element framework. Mechanical testing on different geometries of test specimens made of ASTM A992 steels is conducted to experimentally characterize the ductile fracture at different stress states under monotonic and ultra-low cycle fatigue (ULCF) loading. Scanning electron microscopy studies of the fractured surfaces is conducted to decipher the underlying microscopic damage mechanisms that cause fracture in ASTM A992 steels. Detailed micromechanical analyses for monotonic and cyclic loading are conducted to understand the influence of stress triaxiality and Lode parameter on the void growth phase of ductile fracture. Based on monotonic analyses, an uncoupled micromechanical void growth model is proposed to predict ductile fracture. This model is then incorporated in to finite element program as a weakly coupled model to simulate the loss of load carrying capacity in the post microvoid coalescence regime for high triaxialities. Based on the cyclic analyses, an uncoupled micromechanics based cyclic void growth model is developed to predict the ULCF life of ASTM A992 steels subjected to high stress triaxialities. Furthermore, a computational fracture locus for ASTM A992 steels is developed and incorporated in to finite element program as an uncoupled ductile fracture model. This model can be used to predict the ductile fracture initiation under monotonic loading in a wide range of triaxiality and Lode parameters. Finally, a coupled microvoid elongation and dilation based continuum damage model is proposed, implemented, calibrated and validated. This model is capable of simulating the local softening caused by the various phases of ductile fracture process under monotonic loading for a wide range of stress states. Novel differentiation procedures based on complex analyses along with existing finite difference methods and automatic differentiation are extended using perturbation techniques to evaluate tensor derivatives. These tensor differentiation techniques are then used to automate nonlinear constitutive models into implicit finite element framework. Finally, the efficiency of these automation procedures is demonstrated using benchmark problems.

Verbal Knowledge, Working Memory, and Processing Speed as Predictors of Verbal Learning in Older Adults

ERIC Educational Resources Information Center

Rast, Philippe

2011-01-01

The present study aimed at modeling individual differences in a verbal learning task by means of a latent structured growth curve approach based on an exponential function that yielded 3 parameters: initial recall, learning rate, and asymptotic performance. Three cognitive variables--speed of information processing, verbal knowledge, working…

Millisecond-Timescale Monitoring of PbS Nanoparticle Nucleation and Growth Using Droplet-Based Microfluidics.

PubMed

Lignos, Ioannis; Stavrakis, Stavros; Kilaj, Ardita; deMello, Andrew J

2015-08-26

The early-time kinetics (<1 s) of lead sulfide (PbS) quantum dot formation are probed using a novel droplet-based microfluidic platform, which allows for high-throughput and real-time optical analysis of the reactive process with millisecond time resolution. The reaction platform enables the concurrent investigation of the emission characteristics of PbS quantum dots and a real-time estimation of their size and concentration during nucleation and growth. These investigations reveal a two-stage mechanism for PbS nanoparticle formation. The first stage corresponds to the fast conversion of precursor species to PbS crystals, followed by the growth of the formed particles. The growth kinetics of the PbS nanoparticles follow the Lifshitz-Slyozov-Wagner model for Ostwald ripening, allowing direct estimation of the rate constants for the process. In addition, the extraction of absorption spectra of ultrasmall quantum dots is demonstrated for first time in an online manner. The droplet-based microfluidic platform integrated with online spectroscopic analysis provides a new tool for the quantitative extraction of high temperature kinetics for systems with rapid nucleation and growth stages. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Multirate state and parameter estimation in an antibiotic fermentation with delayed measurements.

PubMed

Gudi, R D; Shah, S L; Gray, M R

1994-12-01

This article discusses issues related to estimation and monitoring of fermentation processes that exhibit endogenous metabolism and time-varying maintenance activity. Such culture-related activities hamper the use of traditional, software sensor-based algorithms, such as the extended kalman filter (EKF). In the approach presented here, the individual effects of the endogenous decay and the true maintenance processes have been lumped to represent a modified maintenance coefficient, m(c). Model equations that relate measurable process outputs, such as the carbon dioxide evolution rate (CER) and biomass, to the observable process parameters (such as net specific growth rate and the modified maintenance coefficient) are proposed. These model equations are used in an estimator that can formally accommodate delayed, infrequent measurements of the culture states (such as the biomass) as well as frequent, culture-related secondary measurements (such as the CER). The resulting multirate software sensor-based estimation strategy is used to monitor biomass profiles as well as profiles of critical fermentation parameters, such as the specific growth for a fed-batch fermentation of Streptomyces clavuligerus.

Mathematical modelling of disintegration-limited co-digestion of OFMSW and sewage sludge.

PubMed

Esposito, G; Frunzo, L; Panico, A; d'Antonio, G

2008-01-01

This paper presents a mathematical model able to simulate under dynamic conditions the physical, chemical and biological processes prevailing in a OFMSW and sewage sludge anaerobic digestion system. The model proposed is based on differential mass balance equations for substrates, products and bacterial groups involved in the co-digestion process and includes the biochemical reactions of the substrate conversion and the kinetics of microbial growth and decay. The main peculiarity of the model is the surface based kinetic description of the OFMSW disintegration process, whereas the pH determination is based on a nine-order polynomial equation derived by acid-base equilibria. The model can be applied to simulate the co-digestion process for several purposes, such as the evaluation of the optimal process conditions in terms of OFMSW/sewage sludge ratio, temperature, OFMSW particle size, solid mixture retention time, reactor stirring rate, etc. Biogas production and composition can also be evaluated to estimate the potential energy production under different process conditions. In particular, model simulations reported in this paper show the model capability to predict the OFMSW amount which can be treated in the digester of an existing MWWTP and to assess the OFMSW particle size diminution pre-treatment required to increase the rate of the disintegration process, which otherwise can highly limit the co-digestion system. Copyright IWA Publishing 2008.

Simulating stand climate, phenology, and photosynthesis of a forest stand with a process-based growth model.

PubMed

Rötzer, Thomas; Leuchner, Michael; Nunn, Angela J

2010-07-01

In the face of climate change and accompanying risks, forest management in Europe is becoming increasingly important. Model simulations can help to understand the reactions and feedbacks of a changing environment on tree growth. In order to simulate forest growth based on future climate change scenarios, we tested the basic processes underlying the growth model BALANCE, simulating stand climate (air temperature, photosynthetically active radiation (PAR) and precipitation), tree phenology, and photosynthesis. A mixed stand of 53- to 60-year-old Norway spruce (Picea abies) and European beech (Fagus sylvatica) in Southern Germany was used as a reference. The results show that BALANCE is able to realistically simulate air temperature gradients in a forest stand using air temperature measurements above the canopy and PAR regimes at different heights for single trees inside the canopy. Interception as a central variable for water balance of a forest stand was also estimated. Tree phenology, i.e. bud burst and leaf coloring, could be reproduced convincingly. Simulated photosynthesis rates were in accordance with measured values for beech both in the sun and the shade crown. For spruce, however, some discrepancies in the rates were obvious, probably due to changed environmental conditions after bud break. Overall, BALANCE has shown to respond to scenario simulations of a changing environment (e.g., climate change, change of forest stand structure).

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.

Integration of Genetic Algorithms and Fuzzy Logic for Urban Growth Modeling

NASA Astrophysics Data System (ADS)

Foroutan, E.; Delavar, M. R.; Araabi, B. N.

2012-07-01

Urban growth phenomenon as a spatio-temporal continuous process is subject to spatial uncertainty. This inherent uncertainty cannot be fully addressed by the conventional methods based on the Boolean algebra. Fuzzy logic can be employed to overcome this limitation. Fuzzy logic preserves the continuity of dynamic urban growth spatially by choosing fuzzy membership functions, fuzzy rules and the fuzzification-defuzzification process. Fuzzy membership functions and fuzzy rule sets as the heart of fuzzy logic are rather subjective and dependent on the expert. However, due to lack of a definite method for determining the membership function parameters, certain optimization is needed to tune the parameters and improve the performance of the model. This paper integrates genetic algorithms and fuzzy logic as a genetic fuzzy system (GFS) for modeling dynamic urban growth. The proposed approach is applied for modeling urban growth in Tehran Metropolitan Area in Iran. Historical land use/cover data of Tehran Metropolitan Area extracted from the 1988 and 1999 Landsat ETM+ images are employed in order to simulate the urban growth. The extracted land use classes of the year 1988 include urban areas, street, vegetation areas, slope and elevation used as urban growth physical driving forces. Relative Operating Characteristic (ROC) curve as an fitness function has been used to evaluate the performance of the GFS algorithm. The optimum membership function parameter is applied for generating a suitability map for the urban growth. Comparing the suitability map and real land use map of 1999 gives the threshold value for the best suitability map which can simulate the land use map of 1999. The simulation outcomes in terms of kappa of 89.13% and overall map accuracy of 95.58% demonstrated the efficiency and reliability of the proposed model.

Time-dependent crack growth behavior of alloy 617 and alloy 230 at elevated temperatures

NASA Astrophysics Data System (ADS)

Roy, Shawoon Kumar

2011-12-01

Two Ni-base solid-solution-strengthened superalloys: INCONEL 617 and HAYNES 230 were studied to check sustained loading crack growth (SLCG) behavior at elevated temperatures appropriate for Next Generation Nuclear Plant (NGNP) applictaions with constant stress intensity factor (Kmax= 27.75 MPa✓m) in air. The results indicate a time-dependent rate controlling process which can be characterized by a linear elastic fracture mechanics (LEFM) parameter -- stress intensity factor (K). At elevated temperatures, the crack growth mechanism was best described using a damage zone concept. Based on results and study, SAGBOE (stress accelerated grain boundary oxidation embrittlement) is considered the primary reason for time-dependent SLCG. A thermodynamic equation was considered to correlate all the SLCG results to determine the thermal activation energy in the process. A phenomenological model based on a time-dependent factor was developed considering the previous researcher's time-dependent fatigue crack propagation (FCP) results and current SLCG results to relate cycle-dependent and time-dependent FCP for both alloys. Further study includes hold time (3+300s) fatigue testing and no hold (1s) fatigue testing with various load ratios (R) at 700°C with a Kmax of 27.75 MPa✓m. Study results suggest an interesting point: crack growth behavior is significantly affected with the change in R value in cycle-dependent process whereas in time-dependent process, change in R does not have any significant effect. Fractography study showed intergranular cracking mode for all time-dependent processes and transgranular cracking mode for cycle-dependent processes. In Alloy 230, SEM images display intergranular cracking with carbide particles, dense oxides and dimple mixed secondary cracks for time-dependent 3+300s FCP and SLCG test. In all cases, Alloy 230 shows better crack growth resistance compared to Alloy 617.

Biochemomechanical poroelastic theory of avascular tumor growth

NASA Astrophysics Data System (ADS)

Xue, Shi-Lei; Li, Bo; Feng, Xi-Qiao; Gao, Huajian

2016-09-01

Tumor growth is a complex process involving genetic mutations, biochemical regulations, and mechanical deformations. In this paper, a thermodynamics-based nonlinear poroelastic theory is established to model the coupling among the mechanical, chemical, and biological mechanisms governing avascular tumor growth. A volumetric growth law accounting for mechano-chemo-biological coupled effects is proposed to describe the development of solid tumors. The regulating roles of stresses and nutrient transport in the tumor growth are revealed under different environmental constraints. We show that the mechano-chemo-biological coupling triggers anisotropic and heterogeneous growth, leading to the formation of layered structures in a growing tumor. There exists a steady state in which tumor growth is balanced by resorption. The influence of external confinements on tumor growth is also examined. A phase diagram is constructed to illustrate how the elastic modulus and thickness of the confinements jointly dictate the steady state of tumor volume. Qualitative and quantitative agreements with experimental observations indicate the developed model is capable of capturing the essential features of avascular tumor growth in various environments.

Explicit simulation of ice particle habits in a Numerical Weather Prediction Model

NASA Astrophysics Data System (ADS)

Hashino, Tempei

2007-05-01

This study developed a scheme for explicit simulation of ice particle habits in Numerical Weather Prediction (NWP) Models. The scheme is called Spectral Ice Habit Prediction System (SHIPS), and the goal is to retain growth history of ice particles in the Eulerian dynamics framework. It diagnoses characteristics of ice particles based on a series of particle property variables (PPVs) that reflect history of microphysieal processes and the transport between mass bins and air parcels in space. Therefore, categorization of ice particles typically used in bulk microphysical parameterization and traditional bin models is not necessary, so that errors that stem from the categorization can be avoided. SHIPS predicts polycrystals as well as hexagonal monocrystals based on empirically derived habit frequency and growth rate, and simulates the habit-dependent aggregation and riming processes by use of the stochastic collection equation with predicted PPVs. Idealized two dimensional simulations were performed with SHIPS in a NWP model. The predicted spatial distribution of ice particle habits and types, and evolution of particle size distributions showed good quantitative agreement with observation This comprehensive model of ice particle properties, distributions, and evolution in clouds can be used to better understand problems facing wide range of research disciplines, including microphysics processes, radiative transfer in a cloudy atmosphere, data assimilation, and weather modification.

Kinetic characteristics and modeling of microalgae Chlorella vulgaris growth and CO2 biofixation considering the coupled effects of light intensity and dissolved inorganic carbon.

PubMed

Chang, Hai-Xing; Huang, Yun; Fu, Qian; Liao, Qiang; Zhu, Xun

2016-04-01

Understanding and optimizing the microalgae growth process is an essential prerequisite for effective CO2 capture using microalgae in photobioreactors. In this study, the kinetic characteristics of microalgae Chlorella vulgaris growth in response to light intensity and dissolved inorganic carbon (DIC) concentration were investigated. The greatest values of maximum biomass concentration (Xmax) and maximum specific growth rate (μmax) were obtained as 2.303 g L(-1) and 0.078 h(-1), respectively, at a light intensity of 120 μmol m(-2) s(-1) and DIC concentration of 17 mM. Based on the results, mathematical models describing the coupled effects of light intensity and DIC concentration on microalgae growth and CO2 biofixation are proposed. The models are able to predict the temporal evolution of C. vulgaris growth and CO2 biofixation rates from lag to stationary phases. Verification experiments confirmed that the model predictions agreed well with the experimental results. Copyright © 2016 Elsevier Ltd. All rights reserved.

Networks for image acquisition, processing and display

NASA Technical Reports Server (NTRS)

Ahumada, Albert J., Jr.

1990-01-01

The human visual system comprises layers of networks which sample, process, and code images. Understanding these networks is a valuable means of understanding human vision and of designing autonomous vision systems based on network processing. Ames Research Center has an ongoing program to develop computational models of such networks. The models predict human performance in detection of targets and in discrimination of displayed information. In addition, the models are artificial vision systems sharing properties with biological vision that has been tuned by evolution for high performance. Properties include variable density sampling, noise immunity, multi-resolution coding, and fault-tolerance. The research stresses analysis of noise in visual networks, including sampling, photon, and processing unit noises. Specific accomplishments include: models of sampling array growth with variable density and irregularity comparable to that of the retinal cone mosaic; noise models of networks with signal-dependent and independent noise; models of network connection development for preserving spatial registration and interpolation; multi-resolution encoding models based on hexagonal arrays (HOP transform); and mathematical procedures for simplifying analysis of large networks.

System-Wide Water Resources Program Nutrient Sub-Model (SWWRP-NSM) Version 1.1

DTIC Science & Technology

2008-09-01

species including crops, native grasses, and trees . The process descriptions utilize a single plant growth model to simulate all types of land covers...characteristics: • Multi- species , multi-phase, and multi-reaction system • Fast (equilibrium-based) and slow (non-equilibrium-based or rate- based...Transformation and loading of N and P species in the overland flow • Simulation of the N and P cycle in the water column (both overland and

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.

Optimal allocation in annual plants and its implications for drought response

NASA Astrophysics Data System (ADS)

Caldararu, Silvia; Smith, Matthew; Purves, Drew

2015-04-01

The concept of plant optimality refers to the plastic behaviour of plants that results in lifetime and offspring fitness. Optimality concepts have been used in vegetation models for a variety of processes, including stomatal conductance, leaf phenology and biomass allocation. Including optimality in vegetation models has the advantages of creating process based models with a relatively low complexity in terms of parameter numbers but which are capable of reproducing complex plant behaviour. We present a general model of plant growth for annual plants based on the hypothesis that plants allocate biomass to aboveground and belowground vegetative organs in order to maintain an optimal C:N ratio. The model also represents reproductive growth through a second optimality criteria, which states that plants flower when they reach peak nitrogen uptake. We apply this model to wheat and maize crops at 15 locations corresponding to FLUXNET cropland sites. The model parameters are data constrained using a Bayesian fitting algorithm to eddy covariance data, satellite derived vegetation indices, specifically the MODIS fAPAR product and field level crop yield data. We use the model to simulate the plant drought response under the assumption of plant optimality and show that the plants maintain unstressed total biomass levels under drought for a reduction in precipitation of up to 40%. Beyond that level plant response stops being plastic and growth decreases sharply. This behaviour results simply from the optimal allocation criteria as the model includes no explicit drought sensitivity component. Models that use plant optimality concepts are a useful tool for simulation plant response to stress without the addition of artificial thresholds and parameters.

Helical Growth of Aluminum Nitride: New Insights into Its Growth Habit from Nanostructures to Single Crystals

PubMed Central

Zhang, Xing-Hong; Shao, Rui-Wen; Jin, Lei; Wang, Jian-Yu; Zheng, Kun; Zhao, Chao-Liang; Han, Jie-Cai; Chen, Bin; Sekiguchi, Takashi; Zhang, Zhi; Zou, Jin; Song, Bo

2015-01-01

By understanding the growth mechanism of nanomaterials, the morphological features of nanostructures can be rationally controlled, thereby achieving the desired physical properties for specific applications. Herein, the growth habits of aluminum nitride (AlN) nanostructures and single crystals synthesized by an ultrahigh-temperature, catalyst-free, physical vapor transport process were investigated by transmission electron microscopy. The detailed structural characterizations strongly suggested that the growth of AlN nanostructures including AlN nanowires and nanohelixes follow a sequential and periodic rotation in the growth direction, which is independent of the size and shape of the material. Based on these experimental observations, an helical growth mechanism that may originate from the coeffect of the polar-surface and dislocation-driven growth is proposed, which offers a new insight into the related growth kinetics of low-dimensional AlN structures and will enable the rational design and synthesis of novel AlN nanostructures. Further, with the increase of temperature, the growth process of AlN grains followed the helical growth model. PMID:25976071

Eye growth and myopia development: Unifying theory and Matlab model.

PubMed

Hung, George K; Mahadas, Kausalendra; Mohammad, Faisal

2016-03-01

The aim of this article is to present an updated unifying theory of the mechanisms underlying eye growth and myopia development. A series of model simulation programs were developed to illustrate the mechanism of eye growth regulation and myopia development. Two fundamental processes are presumed to govern the relationship between physiological optics and eye growth: genetically pre-programmed signaling and blur feedback. Cornea/lens is considered to have only a genetically pre-programmed component, whereas eye growth is considered to have both a genetically pre-programmed and a blur feedback component. Moreover, based on the Incremental Retinal-Defocus Theory (IRDT), the rate of change of blur size provides the direction for blur-driven regulation. The various factors affecting eye growth are shown in 5 simulations: (1 - unregulated eye growth): blur feedback is rendered ineffective, as in the case of form deprivation, so there is only genetically pre-programmed eye growth, generally resulting in myopia; (2 - regulated eye growth): blur feedback regulation demonstrates the emmetropization process, with abnormally excessive or reduced eye growth leading to myopia and hyperopia, respectively; (3 - repeated near-far viewing): simulation of large-to-small change in blur size as seen in the accommodative stimulus/response function, and via IRDT as well as nearwork-induced transient myopia (NITM), leading to the development of myopia; (4 - neurochemical bulk flow and diffusion): release of dopamine from the inner plexiform layer of the retina, and the subsequent diffusion and relay of neurochemical cascade show that a decrease in dopamine results in a reduction of proteoglycan synthesis rate, which leads to myopia; (5 - Simulink model): model of genetically pre-programmed signaling and blur feedback components that allows for different input functions to simulate experimental manipulations that result in hyperopia, emmetropia, and myopia. These model simulation programs (available upon request) can provide a useful tutorial for the general scientist and serve as a quantitative tool for researchers in eye growth and myopia. Copyright © 2016 Elsevier Ltd. All rights reserved.

Graphene growth on Ge(100)/Si(100) substrates by CVD method.

PubMed

Pasternak, Iwona; Wesolowski, Marek; Jozwik, Iwona; Lukosius, Mindaugas; Lupina, Grzegorz; Dabrowski, Pawel; Baranowski, Jacek M; Strupinski, Wlodek

2016-02-22

The successful integration of graphene into microelectronic devices is strongly dependent on the availability of direct deposition processes, which can provide uniform, large area and high quality graphene on nonmetallic substrates. As of today the dominant technology is based on Si and obtaining graphene with Si is treated as the most advantageous solution. However, the formation of carbide during the growth process makes manufacturing graphene on Si wafers extremely challenging. To overcome these difficulties and reach the set goals, we proposed growth of high quality graphene layers by the CVD method on Ge(100)/Si(100) wafers. In addition, a stochastic model was applied in order to describe the graphene growth process on the Ge(100)/Si(100) substrate and to determine the direction of further processes. As a result, high quality graphene was grown, which was proved by Raman spectroscopy results, showing uniform monolayer films with FWHM of the 2D band of 32 cm(-1).

Visual simulation of fatigue crack growth

NASA Astrophysics Data System (ADS)

Wang, Shuanzhu; Margolin, Harold; Lin, Fengbao

1998-07-01

An attempt has been made to visually simulate fatigue crack propagation from a precrack. An integrated program was developed for this purpose. The crack-tip shape was determined at four load positions in the first load cycle. The final shape was a blunt front with an “ear” profile at the precrack tip. A more general model, schematically illustrating the mechanism of fatigue crack growth and striation formation in a ductile material, was proposed based on this simulation. According to the present model, fatigue crack growth is an intermittent process; cyclic plastic shear strain is the driving force applied to both state I and II crack growth. No fracture mode transition occurs between the two stages in the present study. The crack growth direction alternates, moving up and down successively, producing fatigue striations. A brief examination has been made of the crack growth path in a ductile two-phase material.

Velocity locking and pulsed invasions of fragmented habitats with seasonal growth

NASA Astrophysics Data System (ADS)

Korolev, Kirill; Wang, Ching-Hao

From crystal growth to epidemics, spatial spreading is a common mechanism of change in nature. Typically, spreading results from two processes: growth and dispersal in ecology or chemical reactions and diffusion in physics. These two processes combine to produce a reaction-diffusion wave, an invasion front advancing at a constant velocity. We show that the properties of these waves are remarkably different depending whether space and time are continuous, as they are for a chemical reaction, or discrete, as they are for a pest invading a patchy habitat in seasonal climates. For discrete space and time, we report a new type of expansions with velocities that can lock into specific values and become insensitive to changes in dispersal and growth, i.e. the dependence of the velocity on model parameters exhibits plateaus or pauses. As a result, the evolution and response to perturbations in locked expansions can be markedly different compared to the expectations based on continuous models. The phenomenon of velocity locking requires cooperative growth and does not occur when per capita growth rate decline monotonically with population density. We obtain both numerical and analytical results describing highly non-analytic properties of locked expansions.

Nonlinear Growth Curves in Developmental Research

ERIC Educational Resources Information Center

Grimm, Kevin J.; Ram, Nilam; Hamagami, Fumiaki

2011-01-01

Developmentalists are often interested in understanding change processes, and growth models are the most common analytic tool for examining such processes. Nonlinear growth curves are especially valuable to developmentalists because the defining characteristics of the growth process such as initial levels, rates of change during growth spurts, and…

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

PubMed

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

2017-01-02

Microbiological limits are widely used in food processing as an aid to reduce the exposure to hazardous microorganisms for the consumers. However, in pork, the prevalence and concentrations of Salmonella are generally low and microbiological limits are not considered an efficient tool to support hygiene interventions. The objective of the present study was to develop an approach which could make it possible to define potential risk-based microbiological limits for an indicator, enterococci, in order to evaluate the risk from potential growth of Salmonella. A positive correlation between the concentration of enterococci and the prevalence and concentration of Salmonella was shown for 6640 pork samples taken at Danish cutting plants and retail butchers. The samples were collected in five different studies in 2001, 2002, 2010, 2011 and 2013. The observations that both Salmonella and enterococci are carried in the intestinal tract, contaminate pork by the same mechanisms and share similar growth characteristics (lag phase and maximum specific growth rate) at temperatures around 5-10°C, suggest a potential of enterococci to be used as an indicator of potential growth of Salmonella in pork. Elevated temperatures during processing will lead to growth of both enterococci and, if present, also Salmonella. By combining the correlation between enterococci and Salmonella with risk modelling, it is possible to predict the risk of salmonellosis based on the level of enterococci. The risk model used for this purpose includes the dose-response relationship for Salmonella and a reduction factor to account for preparation of the fresh pork. By use of the risk model, it was estimated that the majority of salmonellosis cases, caused by the consumption of pork in Denmark, is caused by the small fraction of pork products that has enterococci concentrations above 5logCFU/g. This illustrates that our approach can be used to evaluate the potential effect of different microbiological limits and therefore, the perspective of this novel approach is that it can be used for definition of a risk-based microbiological limit for enterococci. The limit for enterococci can then be used for development of a process hygiene criterion in cutting plants and retail butcher shops, with the purpose of reducing the risk of Salmonella for the consumer. Copyright © 2016 Elsevier B.V. All rights reserved.

Construction of a biodynamic model for Cry protein production studies.

PubMed

Navarro-Mtz, Ana Karin; Pérez-Guevara, Fermín

2014-12-01

Mathematical models have been used from growth kinetic simulation to gen regulatory networks prediction for B. thuringiensis culture. However, this culture is a time dependent dynamic process where cells physiology suffers several changes depending on the changes in the cell environment. Therefore, through its culture, B. thuringiensis presents three phases related with the predominance of three major metabolic pathways: vegetative growth (Embded-Meyerhof-Parnas pathway), transition (γ-aminobutiric cycle) and sporulation (tricarboxylic acid cycle). There is not available a mathematical model that relates the different stages of cultivation with the metabolic pathway active on each one of them. Therefore, in the present study, and based on published data, a biodynamic model was generated to describe the dynamic of the three different phases based on their major metabolic pathways. The biodynamic model is used to study the interrelation between the different culture phases and their relationship with the Cry protein production. The model consists of three interconnected modules where each module represents one culture phase and its principal metabolic pathway. For model validation four new fermentations were done showing that the model constructed describes reasonably well the dynamic of the three phases. The main results of this model imply that poly-β-hydroxybutyrate is crucial for endospore and Cry protein production. According to the yields of dipicolinic acid and Cry from poly-β-hydroxybutyrate, calculated with the model, the endospore and Cry protein production are not just simultaneous and parallel processes they are also competitive processes.

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

PubMed Central

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

2017-01-01

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

Quantifying model uncertainty in seasonal Arctic sea-ice forecasts

NASA Astrophysics Data System (ADS)

Blanchard-Wrigglesworth, Edward; Barthélemy, Antoine; Chevallier, Matthieu; Cullather, Richard; Fučkar, Neven; Massonnet, François; Posey, Pamela; Wang, Wanqiu; Zhang, Jinlun; Ardilouze, Constantin; Bitz, Cecilia; Vernieres, Guillaume; Wallcraft, Alan; Wang, Muyin

2017-04-01

Dynamical model forecasts in the Sea Ice Outlook (SIO) of September Arctic sea-ice extent over the last decade have shown lower skill than that found in both idealized model experiments and hindcasts of previous decades. Additionally, it is unclear how different model physics, initial conditions or post-processing techniques contribute to SIO forecast uncertainty. In this work, we have produced a seasonal forecast of 2015 Arctic summer sea ice using SIO dynamical models initialized with identical sea-ice thickness in the central Arctic. Our goals are to calculate the relative contribution of model uncertainty and irreducible error growth to forecast uncertainty and assess the importance of post-processing, and to contrast pan-Arctic forecast uncertainty with regional forecast uncertainty. We find that prior to forecast post-processing, model uncertainty is the main contributor to forecast uncertainty, whereas after forecast post-processing forecast uncertainty is reduced overall, model uncertainty is reduced by an order of magnitude, and irreducible error growth becomes the main contributor to forecast uncertainty. While all models generally agree in their post-processed forecasts of September sea-ice volume and extent, this is not the case for sea-ice concentration. Additionally, forecast uncertainty of sea-ice thickness grows at a much higher rate along Arctic coastlines relative to the central Arctic ocean. Potential ways of offering spatial forecast information based on the timescale over which the forecast signal beats the noise are also explored.

Identification of a constitutive law for trabecular bone samples under remodeling in the framework of irreversible thermodynamics

NASA Astrophysics Data System (ADS)

Louna, Zineeddine; Goda, Ibrahim; Ganghoffer, Jean-François

2018-01-01

We construct in the present paper constitutive models for bone remodeling based on micromechanical analyses at the scale of a representative unit cell (RUC) including a porous trabecular microstructure. The time evolution of the microstructure is simulated as a surface remodeling process by relating the surface growth remodeling velocity to a surface driving force incorporating a (surface) Eshelby tensor. Adopting the framework of irreversible thermodynamics, a 2D constitutive model based on the setting up of the free energy density and a dissipation potential is identified from FE simulations performed over a unit cell representative of the trabecular architecture obtained from real bone microstructures. The static and evolutive effective properties of bone at the scale of the RUC are obtained by combining a methodology for the evaluation of the average kinematic and static variables over a prototype unit cell and numerical simulations with controlled imposed first gradient rates. The formulated effective growth constitutive law at the scale of the homogenized set of trabeculae within the RUC is of viscoplastic type and relates the average growth strain rate to the homogenized stress tensor. The postulated model includes a power law function of an effective stress chosen to depend on the first and second stress invariants. The model coefficients are calibrated from a set of virtual testing performed over the RUC subjected to a sequence of loadings. Numerical simulations show that overall bone growth does not show any growth kinematic hardening. The obtained results quantify the strength and importance of different types of external loads (uniaxial tension, simple shear, and biaxial loading) on the overall remodeling process and the development of elastic deformations within the RUC.

Effects of uncertainty and variability on population declines and IUCN Red List classifications.

PubMed

Rueda-Cediel, Pamela; Anderson, Kurt E; Regan, Tracey J; Regan, Helen M

2018-01-22

The International Union for Conservation of Nature (IUCN) Red List Categories and Criteria is a quantitative framework for classifying species according to extinction risk. Population models may be used to estimate extinction risk or population declines. Uncertainty and variability arise in threat classifications through measurement and process error in empirical data and uncertainty in the models used to estimate extinction risk and population declines. Furthermore, species traits are known to affect extinction risk. We investigated the effects of measurement and process error, model type, population growth rate, and age at first reproduction on the reliability of risk classifications based on projected population declines on IUCN Red List classifications. We used an age-structured population model to simulate true population trajectories with different growth rates, reproductive ages and levels of variation, and subjected them to measurement error. We evaluated the ability of scalar and matrix models parameterized with these simulated time series to accurately capture the IUCN Red List classification generated with true population declines. Under all levels of measurement error tested and low process error, classifications were reasonably accurate; scalar and matrix models yielded roughly the same rate of misclassifications, but the distribution of errors differed; matrix models led to greater overestimation of extinction risk than underestimations; process error tended to contribute to misclassifications to a greater extent than measurement error; and more misclassifications occurred for fast, rather than slow, life histories. These results indicate that classifications of highly threatened taxa (i.e., taxa with low growth rates) under criterion A are more likely to be reliable than for less threatened taxa when assessed with population models. Greater scrutiny needs to be placed on data used to parameterize population models for species with high growth rates, particularly when available evidence indicates a potential transition to higher risk categories. © 2018 Society for Conservation Biology.

Modeling plasma-assisted growth of graphene-carbon nanotube hybrid

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

Tewari, Aarti

2016-08-15

A theoretical model describing the growth of graphene-CNT hybrid in a plasma medium is presented. Using the model, the growth of carbon nanotube (CNT) on a catalyst particle and thereafter the growth of the graphene on the CNT is studied under the purview of plasma sheath and number density kinetics of different plasma species. It is found that the plasma parameter such as ion density; gas ratios and process parameter such as source power affect the CNT and graphene dimensions. The variation in growth rates of graphene and CNT under different plasma power, gas ratios, and ion densities is analyzed.more » Based on the results obtained, it can be concluded that higher hydrocarbon ion densities and gas ratios of hydrocarbon to hydrogen favor the growth of taller CNTs and graphene, respectively. In addition, the CNT tip radius reduces with hydrogen ion density and higher plasma power favors graphene with lesser thickness. The present study can help in better understanding of the graphene-CNT hybrid growth in a plasma medium.« less

Modelling breast cancer tumour growth for a stable disease population.

PubMed

Isheden, Gabriel; Humphreys, Keith

2017-01-01

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

Model-based evaluation of two BNR processes--UCT and A2N.

PubMed

Hao, X; Van Loosdrecht, M C; Meijer, S C; Qian, Y

2001-08-01

The activity of denitrifying P-accumulating bacteria (DPB) has been verified to exist in most WWTPs with biological nutrient removal (BNR). The modified UCT process has a high content of DPB. A new BNR process with a two-sludge system named A2N was especially developed to exploit denitrifying dephosphatation. With the identical inflow and effluent standards, an existing full-scale UCT-type WWTP and a designed A2N process were evaluated by simulation. The used model is based on the Delft metabolical model for bio-P removal and ASM2d model for COD and N removal. Both processes accommodate denitrifying dephosphatation, but the A2N process has a more stable performance in N removal. Although excess sludge is increased by 6%, the A2N process leads to savings of 35, 85 and 30% in aeration energy, mixed liquor internal recirculation and land occupation respectively, as compared to the UCT process. Low temperature has a negative effect on growth of poly-P bacteria, which becomes to especially appear in the A2N process.

Materials processing in a centrifuge - Numerical modeling of macrogravity effects

NASA Technical Reports Server (NTRS)

Ramachandran, N.; Downey, J. P.; Jones, J. C.; Curreri, P. A.

1992-01-01

The fluid mechanics associated with crystal growth processes on a centrifuge is investigated. A simple scaling analysis is used to examine the relative magnitudes of the forces acting on the system and good agreement is obtained with previous studies. A two-dimensional model of crystal growth on a centrifuge is proposed and calculations are undertaken to help in understanding the fundamental transport processes within the crystal growth cell. Results from three-dimensional calculations of actual centrifuge-based crystal growth systems are presented both for the thermodynamically stable and unstable configurations. The calculations show the existence of flow bifurcations in certain configurations but not in all instances. The numerical simulations also show that the centrifugal force is the dominant stabilizing force on fluid convection in the stable configuration. The stabilizing influence of the Coriolis force is found to be only secondary in nature. No significant impact of gravity gradient is found in the calculations. Simulations of unstable configurations show that the Coriolis force has a stabilizing influence on fluid motion by delaying the onset of unsteady convection. Detailed flow and thermal field characteristics are presented for all the different cases that are simulated.

Analytical solution of Luedeking-Piret equation for a batch fermentation obeying Monod growth kinetics.

PubMed

Garnier, Alain; Gaillet, Bruno

2015-12-01

Not so many fermentation mathematical models allow analytical solutions of batch process dynamics. The most widely used is the combination of the logistic microbial growth kinetics with Luedeking-Piret bioproduct synthesis relation. However, the logistic equation is principally based on formalistic similarities and only fits a limited range of fermentation types. In this article, we have developed an analytical solution for the combination of Monod growth kinetics with Luedeking-Piret relation, which can be identified by linear regression and used to simulate batch fermentation evolution. Two classical examples are used to show the quality of fit and the simplicity of the method proposed. A solution for the combination of Haldane substrate-limited growth model combined with Luedeking-Piret relation is also provided. These models could prove useful for the analysis of fermentation data in industry as well as academia. © 2015 Wiley Periodicals, Inc.

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.

Analysis of ? twinning via automated atomistic post-processing methods

NASA Astrophysics Data System (ADS)

Barrett, Christopher D.

2017-05-01

? twinning is the most prominent and most studied twin mode in hexagonal close-packed materials. Many works have been devoted to describing its nucleation, growth and interactions with other defects. Despite this, gaps and disagreements remain in the literature regarding some fundamental aspects of the twinning process. A rigorous understanding of the twinning process is imperative because without it higher scale models of plasticity cannot accurately capture deformation in important materials such as Mg, Ti, Zr and Zn. Motivated by this necessity, we have studied ? twinning using molecular dynamics, focusing on automated processing techniques which can extract mechanistic information generalisable to continuum scale deformation. This demonstrates for the first time the automatic identification of twinning dislocation lines and Burgers vectors, and the elasto-plastic decomposition of the deformation gradient inside and around a twin embryo. These results confirm predictions of most authors regarding the dislocation-based twin growth process, while contradicting others who have argued that ? twin growth stems from a shuffling process with no dislocation line.

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).

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.

Time delay and noise explaining the behaviour of the cell growth in fermentation process

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

Ayuobi, Tawfiqullah; Rosli, Norhayati; Bahar, Arifah

2015-02-03

This paper proposes to investigate the interplay between time delay and external noise in explaining the behaviour of the microbial growth in batch fermentation process. Time delay and noise are modelled jointly via stochastic delay differential equations (SDDEs). The typical behaviour of cell concentration in batch fermentation process under this model is investigated. Milstein scheme is applied for solving this model numerically. Simulation results illustrate the effects of time delay and external noise in explaining the lag and stationary phases, respectively for the cell growth of fermentation process.

Time delay and noise explaining the behaviour of the cell growth in fermentation process

NASA Astrophysics Data System (ADS)

Ayuobi, Tawfiqullah; Rosli, Norhayati; Bahar, Arifah; Salleh, Madihah Md

2015-02-01

This paper proposes to investigate the interplay between time delay and external noise in explaining the behaviour of the microbial growth in batch fermentation process. Time delay and noise are modelled jointly via stochastic delay differential equations (SDDEs). The typical behaviour of cell concentration in batch fermentation process under this model is investigated. Milstein scheme is applied for solving this model numerically. Simulation results illustrate the effects of time delay and external noise in explaining the lag and stationary phases, respectively for the cell growth of fermentation process.

Development of the chorioallantoic placenta in Octodon degus--a model for growth processes in caviomorph rodents?

PubMed

Mess, Andrea

2007-07-15

The degu Octodon degus is one of the very few members of caviomorph or hystricognath Rodentia that possesses a simply arranged chorioallantoic placenta without advanced lobulation. Therefore this species was used as a model to study regional development and growth processes of the placenta, based on the examination of 20 individuals by light and electron microscopy as well as by using markers for proliferation, trophoblast and endometrial stroma. The results were interpreted by comparison with other hystricognaths in the light of their evolutionary history. It was found that trophoblast derived from the trophospongium is essential for extension of the placenta including the labyrinth: extensive proliferation is restricted to trophoblast cells at the outer margin of the placenta and along internally directed, finger-tip like protrusions of fetal mesenchyme towards the labyrinth. This kind of placental development is regarded as part of the stem species pattern of hystricognaths, evolved more than 40 million years ago. It is indicated for the first time that the replenishment of the syncytiotrophoblast is similar to corresponding processes in the human placenta. In conclusion, the degu is a useful model for placental growth dynamics, particularly because of its simply arranged placental architecture, and may also serve as an animal model in comparison to human pregnancies.

Mathematical modeling of the fermentation of acid-hydrolyzed pyrolytic sugars to ethanol by the engineered strain Escherichia coli ACCC 11177.

PubMed

Chang, Dongdong; Yu, Zhisheng; Islam, Zia Ul; Zhang, Hongxun

2015-05-01

Pyrolysate from waste cotton was acid hydrolyzed and detoxified to yield pyrolytic sugars, which were fermented to ethanol by the strain Escherichia coli ACCC 11177. Mathematical models based on the fermentation data were also constructed. Pyrolysate containing an initial levoglucosan concentration of 146.34 g/L gave a glucose yield of 150 % after hydrolysis, suggesting that other compounds were hydrolyzed to glucose as well. Ethyl acetate-based extraction of bacterial growth inhibitors with an ethyl acetate/hydrolysate ratio of 1:0.5 enabled hydrolysate fermentation by E. coli ACCC 11177, without a standard absorption treatment. Batch processing in a fermenter exhibited a maximum ethanol yield and productivity of 0.41 g/g and 0.93 g/L·h(-1), respectively. The cell growth rate (r x ) was consistent with a logistic equation [Formula: see text], which was determined as a function of cell growth (X). Glucose consumption rate (r s ) and ethanol formation rate (r p ) were accurately validated by the equations [Formula: see text] and [Formula: see text], respectively. Together, our results suggest that combining mathematical models with fermenter fermentation processes can enable optimized ethanol production from cellulosic pyrolysate with E. coli. Similar approaches may facilitate the production of other commercially important organic substances.

Cellular trade-offs and optimal resource allocation during cyanobacterial diurnal growth

PubMed Central

Knoop, Henning; Bockmayr, Alexander; Steuer, Ralf

2017-01-01

Cyanobacteria are an integral part of Earth’s biogeochemical cycles and a promising resource for the synthesis of renewable bioproducts from atmospheric CO2. Growth and metabolism of cyanobacteria are inherently tied to the diurnal rhythm of light availability. As yet, however, insight into the stoichiometric and energetic constraints of cyanobacterial diurnal growth is limited. Here, we develop a computational framework to investigate the optimal allocation of cellular resources during diurnal phototrophic growth using a genome-scale metabolic reconstruction of the cyanobacterium Synechococcus elongatus PCC 7942. We formulate phototrophic growth as an autocatalytic process and solve the resulting time-dependent resource allocation problem using constraint-based analysis. Based on a narrow and well-defined set of parameters, our approach results in an ab initio prediction of growth properties over a full diurnal cycle. The computational model allows us to study the optimality of metabolite partitioning during diurnal growth. The cyclic pattern of glycogen accumulation, an emergent property of the model, has timing characteristics that are in qualitative agreement with experimental findings. The approach presented here provides insight into the time-dependent resource allocation problem of phototrophic diurnal growth and may serve as a general framework to assess the optimality of metabolic strategies that evolved in phototrophic organisms under diurnal conditions. PMID:28720699

Agent-based model of angiogenesis simulates capillary sprout initiation in multicellular networks

PubMed Central

Walpole, J.; Chappell, J.C.; Cluceru, J.G.; Mac Gabhann, F.; Bautch, V.L.; Peirce, S. M.

2015-01-01

Many biological processes are controlled by both deterministic and stochastic influences. However, efforts to model these systems often rely on either purely stochastic or purely rule-based methods. To better understand the balance between stochasticity and determinism in biological processes a computational approach that incorporates both influences may afford additional insight into underlying biological mechanisms that give rise to emergent system properties. We apply a combined approach to the simulation and study of angiogenesis, the growth of new blood vessels from existing networks. This complex multicellular process begins with selection of an initiating endothelial cell, or tip cell, which sprouts from the parent vessels in response to stimulation by exogenous cues. We have constructed an agent-based model of sprouting angiogenesis to evaluate endothelial cell sprout initiation frequency and location, and we have experimentally validated it using high-resolution time-lapse confocal microscopy. ABM simulations were then compared to a Monte Carlo model, revealing that purely stochastic simulations could not generate sprout locations as accurately as the rule-informed agent-based model. These findings support the use of rule-based approaches for modeling the complex mechanisms underlying sprouting angiogenesis over purely stochastic methods. PMID:26158406

Agent-based model of angiogenesis simulates capillary sprout initiation in multicellular networks.

PubMed

Walpole, J; Chappell, J C; Cluceru, J G; Mac Gabhann, F; Bautch, V L; Peirce, S M

2015-09-01

Many biological processes are controlled by both deterministic and stochastic influences. However, efforts to model these systems often rely on either purely stochastic or purely rule-based methods. To better understand the balance between stochasticity and determinism in biological processes a computational approach that incorporates both influences may afford additional insight into underlying biological mechanisms that give rise to emergent system properties. We apply a combined approach to the simulation and study of angiogenesis, the growth of new blood vessels from existing networks. This complex multicellular process begins with selection of an initiating endothelial cell, or tip cell, which sprouts from the parent vessels in response to stimulation by exogenous cues. We have constructed an agent-based model of sprouting angiogenesis to evaluate endothelial cell sprout initiation frequency and location, and we have experimentally validated it using high-resolution time-lapse confocal microscopy. ABM simulations were then compared to a Monte Carlo model, revealing that purely stochastic simulations could not generate sprout locations as accurately as the rule-informed agent-based model. These findings support the use of rule-based approaches for modeling the complex mechanisms underlying sprouting angiogenesis over purely stochastic methods.

Is it growing exponentially fast? -- Impact of assuming exponential growth for characterizing and forecasting epidemics with initial near-exponential growth dynamics.

PubMed

Chowell, Gerardo; Viboud, Cécile

2016-10-01

The increasing use of mathematical models for epidemic forecasting has highlighted the importance of designing models that capture the baseline transmission characteristics in order to generate reliable epidemic forecasts. Improved models for epidemic forecasting could be achieved by identifying signature features of epidemic growth, which could inform the design of models of disease spread and reveal important characteristics of the transmission process. In particular, it is often taken for granted that the early growth phase of different growth processes in nature follow early exponential growth dynamics. In the context of infectious disease spread, this assumption is often convenient to describe a transmission process with mass action kinetics using differential equations and generate analytic expressions and estimates of the reproduction number. In this article, we carry out a simulation study to illustrate the impact of incorrectly assuming an exponential-growth model to characterize the early phase (e.g., 3-5 disease generation intervals) of an infectious disease outbreak that follows near-exponential growth dynamics. Specifically, we assess the impact on: 1) goodness of fit, 2) bias on the growth parameter, and 3) the impact on short-term epidemic forecasts. Designing transmission models and statistical approaches that more flexibly capture the profile of epidemic growth could lead to enhanced model fit, improved estimates of key transmission parameters, and more realistic epidemic forecasts.

Dendritic growth model of multilevel marketing

NASA Astrophysics Data System (ADS)

Pang, James Christopher S.; Monterola, Christopher P.

2017-02-01

Biologically inspired dendritic network growth is utilized to model the evolving connections of a multilevel marketing (MLM) enterprise. Starting from agents at random spatial locations, a network is formed by minimizing a distance cost function controlled by a parameter, termed the balancing factor bf, that weighs the wiring and the path length costs of connection. The paradigm is compared to an actual MLM membership data and is shown to be successful in statistically capturing the membership distribution, better than the previously reported agent based preferential attachment or analytic branching process models. Moreover, it recovers the known empirical statistics of previously studied MLM, specifically: (i) a membership distribution characterized by the existence of peak levels indicating limited growth, and (ii) an income distribution obeying the 80 - 20 Pareto principle. Extensive types of income distributions from uniform to Pareto to a "winner-take-all" kind are also modeled by varying bf. Finally, the robustness of our dendritic growth paradigm to random agent removals is explored and its implications to MLM income distributions are discussed.

Stochastic Dynamical Model of a Growing Citation Network Based on a Self-Exciting Point Process

NASA Astrophysics Data System (ADS)

Golosovsky, Michael; Solomon, Sorin

2012-08-01

We put under experimental scrutiny the preferential attachment model that is commonly accepted as a generating mechanism of the scale-free complex networks. To this end we chose a citation network of physics papers and traced the citation history of 40 195 papers published in one year. Contrary to common belief, we find that the citation dynamics of the individual papers follows the superlinear preferential attachment, with the exponent α=1.25-1.3. Moreover, we show that the citation process cannot be described as a memoryless Markov chain since there is a substantial correlation between the present and recent citation rates of a paper. Based on our findings we construct a stochastic growth model of the citation network, perform numerical simulations based on this model and achieve an excellent agreement with the measured citation distributions.

Does health promote economic growth? Portuguese case study: from dictatorship to full democracy.

PubMed

Morgado, Sónia Maria Aniceto

2014-07-01

This paper revisits the debate on health and economic growth (Deaton in J Econ Lit 51:113-158, 2003) focusing on the Portuguese case by testing the relationship between growth and health. We test Portuguese insights, using time series data from 1960 to 2005, taking into account different variables (life expectancy, labour, capital, infant mortality) and considering the years that included major events on the political scene, such as the dictatorship and a closed economy (1960-1974), a revolution (1974) and full democracy and an open economy (1975-2005), factors that influence major economic, cultural, social and politic indicators. Therefore the analysis is carried out adopting Lucas' (J Monet Econ 22(1):3-42, 1988) endogenous growth model that considers human capital as one factor of production, it adopts a VAR (vector autoregressive) model to test the causality between growth and health. Estimates based on the VAR seem to confirm that economic growth influences the health process, but health does not promote growth, during the period under study.

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

Validation of mathematical model for CZ process using small-scale laboratory crystal growth furnace

NASA Astrophysics Data System (ADS)

Bergfelds, Kristaps; Sabanskis, Andrejs; Virbulis, Janis

2018-05-01

The present material is focused on the modelling of small-scale laboratory NaCl-RbCl crystal growth furnace. First steps towards fully transient simulations are taken in the form of stationary simulations that deal with the optimization of material properties to match the model to experimental conditions. For this purpose, simulation software primarily used for the modelling of industrial-scale silicon crystal growth process was successfully applied. Finally, transient simulations of the crystal growth are presented, giving a sufficient agreement to experimental results.

The impacts of data constraints on the predictive performance of a general process-based crop model (PeakN-crop v1.0)

NASA Astrophysics Data System (ADS)

Caldararu, Silvia; Purves, Drew W.; Smith, Matthew J.

2017-04-01

Improving international food security under a changing climate and increasing human population will be greatly aided by improving our ability to modify, understand and predict crop growth. What we predominantly have at our disposal are either process-based models of crop physiology or statistical analyses of yield datasets, both of which suffer from various sources of error. In this paper, we present a generic process-based crop model (PeakN-crop v1.0) which we parametrise using a Bayesian model-fitting algorithm to three different sources: data-space-based vegetation indices, eddy covariance productivity measurements and regional crop yields. We show that the model parametrised without data, based on prior knowledge of the parameters, can largely capture the observed behaviour but the data-constrained model greatly improves both the model fit and reduces prediction uncertainty. We investigate the extent to which each dataset contributes to the model performance and show that while all data improve on the prior model fit, the satellite-based data and crop yield estimates are particularly important for reducing model error and uncertainty. Despite these improvements, we conclude that there are still significant knowledge gaps, in terms of available data for model parametrisation, but our study can help indicate the necessary data collection to improve our predictions of crop yields and crop responses to environmental changes.

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

PubMed

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

2013-11-01

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

Dilation and Hypertrophy: A Cell-Based Continuum Mechanics Approach Towards Ventricular Growth and Remodeling

NASA Astrophysics Data System (ADS)

Ulerich, J.; Göktepe, S.; Kuhl, E.

This manuscript presents a continuum approach towards cardiac growth and remodeling that is capable to predict chronic maladaptation of the heart in response to changes in mechanical loading. It is based on the multiplicative decomposition of the deformation gradient into and elastic and a growth part. Motivated by morphological changes in cardiomyocyte geometry, we introduce an anisotropic growth tensor that can capture both hypertrophic wall thickening and ventricular dilation within one generic concept. In agreement with clinical observations, we propose wall thickening to be a stress-driven phenomenon whereas dilation is introduced as a strain-driven process. The features of the proposed approach are illustrated in terms of the adaptation of thin heart slices and in terms overload-induced dilation in a generic bi-ventricular heart model.

Vascular endothelial growth factor receptor-2 (VEGFR-2) inhibitors: development and validation of predictive 3-D QSAR models through extensive ligand- and structure-based approaches

NASA Astrophysics Data System (ADS)

Ragno, Rino; Ballante, Flavio; Pirolli, Adele; Wickersham, Richard B.; Patsilinakos, Alexandros; Hesse, Stéphanie; Perspicace, Enrico; Kirsch, Gilbert

2015-08-01

Vascular endothelial growth factor receptor-2, (VEGFR-2), is a key element in angiogenesis, the process by which new blood vessels are formed, and is thus an important pharmaceutical target. Here, 3-D quantitative structure-activity relationship (3-D QSAR) were used to build a quantitative screening and pharmacophore model of the VEGFR-2 receptors for design of inhibitors with improved activities. Most of available experimental data information has been used as training set to derive optimized and fully cross-validated eight mono-probe and a multi-probe quantitative models. Notable is the use of 262 molecules, aligned following both structure-based and ligand-based protocols, as external test set confirming the 3-D QSAR models' predictive capability and their usefulness in design new VEGFR-2 inhibitors. From a survey on literature, this is the first generation of a wide-ranging computational medicinal chemistry application on VEGFR2 inhibitors.

Particle-Size-Grouping Model of Precipitation Kinetics in Microalloyed Steels

NASA Astrophysics Data System (ADS)

Xu, Kun; Thomas, Brian G.

2012-03-01

The formation, growth, and size distribution of precipitates greatly affects the microstructure and properties of microalloyed steels. Computational particle-size-grouping (PSG) kinetic models based on population balances are developed to simulate precipitate particle growth resulting from collision and diffusion mechanisms. First, the generalized PSG method for collision is explained clearly and verified. Then, a new PSG method is proposed to model diffusion-controlled precipitate nucleation, growth, and coarsening with complete mass conservation and no fitting parameters. Compared with the original population-balance models, this PSG method saves significant computation and preserves enough accuracy to model a realistic range of particle sizes. Finally, the new PSG method is combined with an equilibrium phase fraction model for plain carbon steels and is applied to simulate the precipitated fraction of aluminum nitride and the size distribution of niobium carbide during isothermal aging processes. Good matches are found with experimental measurements, suggesting that the new PSG method offers a promising framework for the future development of realistic models of precipitation.

Characterizing growth patterns in longitudinal MRI using image contrast

NASA Astrophysics Data System (ADS)

Vardhan, Avantika; Prastawa, Marcel; Vachet, Clement; Piven, Joseph; Gerig, Guido

2014-03-01

Understanding the growth patterns of the early brain is crucial to the study of neuro-development. In the early stages of brain growth, a rapid sequence of biophysical and chemical processes take place. A crucial component of these processes, known as myelination, consists of the formation of a myelin sheath around a nerve fiber, enabling the effective transmission of neural impulses. As the brain undergoes myelination, there is a subsequent change in the contrast between gray matter and white matter as observed in MR scans. In this work, gray-white matter contrast is proposed as an effective measure of appearance which is relatively invariant to location, scanner type, and scanning conditions. To validate this, contrast is computed over various cortical regions for an adult human phantom. MR (Magnetic Resonance) images of the phantom were repeatedly generated using different scanners, and at different locations. Contrast displays less variability over changing conditions of scan compared to intensity-based measures, demonstrating that it is less dependent than intensity on external factors. Additionally, contrast is used to analyze longitudinal MR scans of the early brain, belonging to healthy controls and Down's Syndrome (DS) patients. Kernel regression is used to model subject-specific trajectories of contrast changing with time. Trajectories of contrast changing with time, as well as time-based biomarkers extracted from contrast modeling, show large differences between groups. The preliminary applications of contrast based analysis indicate its future potential to reveal new information not covered by conventional volumetric or deformation-based analysis, particularly for distinguishing between normal and abnormal growth patterns.

Relaxation processes in a low-order three-dimensional magnetohydrodynamics model

NASA Technical Reports Server (NTRS)

Stribling, Troy; Matthaeus, William H.

1991-01-01

The time asymptotic behavior of a Galerkin model of 3D magnetohydrodynamics (MHD) has been interpreted using the selective decay and dynamic alignment relaxation theories. A large number of simulations has been performed that scan a parameter space defined by the rugged ideal invariants, including energy, cross helicity, and magnetic helicity. It is concluded that time asymptotic state can be interpreted as a relaxation to minimum energy. A simple decay model, based on absolute equilibrium theory, is found to predict a mapping of initial onto time asymptotic states, and to accurately describe the long time behavior of the runs when magnetic helicity is present. Attention is also given to two processes, operating on time scales shorter than selective decay and dynamic alignment, in which the ratio of kinetic to magnetic energy relaxes to values 0(1). The faster of the two processes takes states initially dominant in magnetic energy to a state of near-equipartition between kinetic and magnetic energy through power law growth of kinetic energy. The other process takes states initially dominant in kinetic energy to the near-equipartitioned state through exponential growth of magnetic energy.

Simulated crop yield in response to changes in climate and agricultural practices: results from a simple process based model

NASA Astrophysics Data System (ADS)

Caldararu, S.; Smith, M. J.; Purves, D.; Emmott, S.

2013-12-01

Global agriculture will, in the future, be faced with two main challenges: climate change and an increase in global food demand driven by an increase in population and changes in consumption habits. To be able to predict both the impacts of changes in climate on crop yields and the changes in agricultural practices necessary to respond to such impacts we currently need to improve our understanding of crop responses to climate and the predictive capability of our models. Ideally, what we would have at our disposal is a modelling tool which, given certain climatic conditions and agricultural practices, can predict the growth pattern and final yield of any of the major crops across the globe. We present a simple, process-based crop growth model based on the assumption that plants allocate above- and below-ground biomass to maintain overall carbon optimality and that, to maintain this optimality, the reproductive stage begins at peak nitrogen uptake. The model includes responses to available light, water, temperature and carbon dioxide concentration as well as nitrogen fertilisation and irrigation. The model is data constrained at two sites, the Yaqui Valley, Mexico for wheat and the Southern Great Plains flux site for maize and soybean, using a robust combination of space-based vegetation data (including data from the MODIS and Landsat TM and ETM+ instruments), as well as ground-based biomass and yield measurements. We show a number of climate response scenarios, including increases in temperature and carbon dioxide concentrations as well as responses to irrigation and fertiliser application.

Reliability growth modeling analysis of the space shuttle main engines based upon the Weibull process

NASA Technical Reports Server (NTRS)

Wheeler, J. T.

1990-01-01

The Weibull process, identified as the inhomogeneous Poisson process with the Weibull intensity function, is used to model the reliability growth assessment of the space shuttle main engine test and flight failure data. Additional tables of percentage-point probabilities for several different values of the confidence coefficient have been generated for setting (1-alpha)100-percent two sided confidence interval estimates on the mean time between failures. The tabled data pertain to two cases: (1) time-terminated testing, and (2) failure-terminated testing. The critical values of the three test statistics, namely Cramer-von Mises, Kolmogorov-Smirnov, and chi-square, were calculated and tabled for use in the goodness of fit tests for the engine reliability data. Numerical results are presented for five different groupings of the engine data that reflect the actual response to the failures.

The Use of Multidimensional Image-Based Analysis to Accurately Monitor Cell Growth in 3D Bioreactor Culture

PubMed Central

Baradez, Marc-Olivier; Marshall, Damian

2011-01-01

The transition from traditional culture methods towards bioreactor based bioprocessing to produce cells in commercially viable quantities for cell therapy applications requires the development of robust methods to ensure the quality of the cells produced. Standard methods for measuring cell quality parameters such as viability provide only limited information making process monitoring and optimisation difficult. Here we describe a 3D image-based approach to develop cell distribution maps which can be used to simultaneously measure the number, confluency and morphology of cells attached to microcarriers in a stirred tank bioreactor. The accuracy of the cell distribution measurements is validated using in silico modelling of synthetic image datasets and is shown to have an accuracy >90%. Using the cell distribution mapping process and principal component analysis we show how cell growth can be quantitatively monitored over a 13 day bioreactor culture period and how changes to manufacture processes such as initial cell seeding density can significantly influence cell morphology and the rate at which cells are produced. Taken together, these results demonstrate how image-based analysis can be incorporated in cell quality control processes facilitating the transition towards bioreactor based manufacture for clinical grade cells. PMID:22028809

The use of multidimensional image-based analysis to accurately monitor cell growth in 3D bioreactor culture.

PubMed

Baradez, Marc-Olivier; Marshall, Damian

2011-01-01

The transition from traditional culture methods towards bioreactor based bioprocessing to produce cells in commercially viable quantities for cell therapy applications requires the development of robust methods to ensure the quality of the cells produced. Standard methods for measuring cell quality parameters such as viability provide only limited information making process monitoring and optimisation difficult. Here we describe a 3D image-based approach to develop cell distribution maps which can be used to simultaneously measure the number, confluency and morphology of cells attached to microcarriers in a stirred tank bioreactor. The accuracy of the cell distribution measurements is validated using in silico modelling of synthetic image datasets and is shown to have an accuracy >90%. Using the cell distribution mapping process and principal component analysis we show how cell growth can be quantitatively monitored over a 13 day bioreactor culture period and how changes to manufacture processes such as initial cell seeding density can significantly influence cell morphology and the rate at which cells are produced. Taken together, these results demonstrate how image-based analysis can be incorporated in cell quality control processes facilitating the transition towards bioreactor based manufacture for clinical grade cells.

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

PubMed Central

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

2011-01-01

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

Outcompeting nitrite-oxidizing bacteria in single-stage nitrogen removal in sewage treatment plants: a model-based study.

PubMed

Pérez, Julio; Lotti, Tommaso; Kleerebezem, Robbert; Picioreanu, Cristian; van Loosdrecht, Mark C M

2014-12-01

This model-based study investigated the mechanisms and operational window for efficient repression of nitrite oxidizing bacteria (NOB) in an autotrophic nitrogen removal process. The operation of a continuous single-stage granular sludge process was simulated for nitrogen removal from pretreated sewage at 10 °C. The effects of the residual ammonium concentration were explicitly analyzed with the model. Competition for oxygen between ammonia-oxidizing bacteria (AOB) and NOB was found to be essential for NOB repression even when the suppression of nitrite oxidation is assisted by nitrite reduction by anammox (AMX). The nitrite half-saturation coefficient of NOB and AMX proved non-sensitive for the model output. The maximum specific growth rate of AMX bacteria proved a sensitive process parameter, because higher rates would provide a competitive advantage for AMX. Copyright © 2014 Elsevier Ltd. All rights reserved.

Development of a model and computer code to describe solar grade silicon production processes

NASA Technical Reports Server (NTRS)

Srivastava, R.; Gould, R. K.

1979-01-01

Mathematical models, and computer codes based on these models were developed which allow prediction of the product distribution in chemical reactors in which gaseous silicon compounds are converted to condensed phase silicon. The reactors to be modeled are flow reactors in which silane or one of the halogenated silanes is thermally decomposed or reacted with an alkali metal, H2 or H atoms. Because the product of interest is particulate silicon, processes which must be modeled, in addition to mixing and reaction of gas-phase reactants, include the nucleation and growth of condensed Si via coagulation, condensation, and heterogeneous reaction.

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.

Crystal Nucleation and Growth in Undercooled Melts of Pure Zr, Binary Zr-Based and Ternary Zr-Ni-Cu Glass-Forming Alloys

NASA Astrophysics Data System (ADS)

Herlach, Dieter M.; Kobold, Raphael; Klein, Stefan

2018-03-01

Glass formation of a liquid undercooled below its melting temperature requires the complete avoidance of crystal nucleation and subsequent crystal growth. Even though they are not part of the glass formation process, a detailed knowledge of both processes involved in crystallization is mandatory to determine the glass-forming ability of metals and metallic alloys. In the present work, methods of containerless processing of drops by electrostatic and electromagnetic levitation are applied to undercool metallic melts prior to solidification. Heterogeneous nucleation on crucible walls is completely avoided giving access to large undercoolings. A freely suspended drop offers the additional benefit of showing the rapid crystallization process of an undercooled melt in situ by proper diagnostic means. As a reference, crystal nucleation and dendrite growth in the undercooled melt of pure Zr are experimentally investigated. Equivalently, binary Zr-Cu, Zr-Ni and Zr-Pd and ternary Zr-Ni-Cu alloys are studied, whose glass-forming abilities differ. The experimental results are analyzed within classical nucleation theory and models of dendrite growth. The findings give detailed knowledge about the nucleation-undercooling statistics and the growth kinetics over a large range of undercooling.

Multi-model seasonal forecast of Arctic sea-ice: forecast uncertainty at pan-Arctic and regional scales

NASA Astrophysics Data System (ADS)

Blanchard-Wrigglesworth, E.; Barthélemy, A.; Chevallier, M.; Cullather, R.; Fučkar, N.; Massonnet, F.; Posey, P.; Wang, W.; Zhang, J.; Ardilouze, C.; Bitz, C. M.; Vernieres, G.; Wallcraft, A.; Wang, M.

2017-08-01

Dynamical model forecasts in the Sea Ice Outlook (SIO) of September Arctic sea-ice extent over the last decade have shown lower skill than that found in both idealized model experiments and hindcasts of previous decades. Additionally, it is unclear how different model physics, initial conditions or forecast post-processing (bias correction) techniques contribute to SIO forecast uncertainty. In this work, we have produced a seasonal forecast of 2015 Arctic summer sea ice using SIO dynamical models initialized with identical sea-ice thickness in the central Arctic. Our goals are to calculate the relative contribution of model uncertainty and irreducible error growth to forecast uncertainty and assess the importance of post-processing, and to contrast pan-Arctic forecast uncertainty with regional forecast uncertainty. We find that prior to forecast post-processing, model uncertainty is the main contributor to forecast uncertainty, whereas after forecast post-processing forecast uncertainty is reduced overall, model uncertainty is reduced by an order of magnitude, and irreducible error growth becomes the main contributor to forecast uncertainty. While all models generally agree in their post-processed forecasts of September sea-ice volume and extent, this is not the case for sea-ice concentration. Additionally, forecast uncertainty of sea-ice thickness grows at a much higher rate along Arctic coastlines relative to the central Arctic ocean. Potential ways of offering spatial forecast information based on the timescale over which the forecast signal beats the noise are also explored.

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.

Quantification of the impact of hydrology on agricultural production as a result of too dry, too wet or too saline conditions

NASA Astrophysics Data System (ADS)

Hack-ten Broeke, Mirjam J. D.; Kroes, Joop G.; Bartholomeus, Ruud P.; van Dam, Jos C.; de Wit, Allard J. W.; Supit, Iwan; Walvoort, Dennis J. J.; van Bakel, P. Jan T.; Ruijtenberg, Rob

2016-08-01

For calculating the effects of hydrological measures on agricultural production in the Netherlands a new comprehensive and climate proof method is being developed: WaterVision Agriculture (in Dutch: Waterwijzer Landbouw). End users have asked for a method that considers current and future climate, that can quantify the differences between years and also the effects of extreme weather events. Furthermore they would like a method that considers current farm management and that can distinguish three different causes of crop yield reduction: drought, saline conditions or too wet conditions causing oxygen shortage in the root zone. WaterVision Agriculture is based on the hydrological simulation model SWAP and the crop growth model WOFOST. SWAP simulates water transport in the unsaturated zone using meteorological data, boundary conditions (like groundwater level or drainage) and soil parameters. WOFOST simulates crop growth as a function of meteorological conditions and crop parameters. Using the combination of these process-based models we have derived a meta-model, i.e. a set of easily applicable simplified relations for assessing crop growth as a function of soil type and groundwater level. These relations are based on multiple model runs for at least 72 soil units and the possible groundwater regimes in the Netherlands. So far, we parameterized the model for the crops silage maize and grassland. For the assessment, the soil characteristics (soil water retention and hydraulic conductivity) are very important input parameters for all soil layers of these 72 soil units. These 72 soil units cover all soils in the Netherlands. This paper describes (i) the setup and examples of application of the process-based model SWAP-WOFOST, (ii) the development of the simplified relations based on this model and (iii) how WaterVision Agriculture can be used by farmers, regional government, water boards and others to assess crop yield reduction as a function of groundwater characteristics or as a function of the salt concentration in the root zone for the various soil types.

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

PubMed

Valero, A; Hervás, C; García-Gimeno, R M; Zurera, G

2007-08-01

A new approach to predict the growth/no growth interface of Listeria monocytogenes as a function of storage temperature, pH, citric acid (CA) and ascorbic acid (AA) is presented. A linear logistic regression procedure was performed and a non-linear model was obtained by adding new variables by means of a Neural Network model based on Product Units (PUNN). The classification efficiency of the training data set and the generalization data of the new Logistic Regression PUNN model (LRPU) were compared with Linear Logistic Regression (LLR) and Polynomial Logistic Regression (PLR) models. 92% of the total cases from the LRPU model were correctly classified, an improvement on the percentage obtained using the PLR model (90%) and significantly higher than the results obtained with the LLR model, 80%. On the other hand predictions of LRPU were closer to data observed which permits to design proper formulations in minimally processed foods. This novel methodology can be applied to predictive microbiology for describing growth/no growth interface of food-borne microorganisms such as L. monocytogenes. The optimal balance is trying to find models with an acceptable interpretation capacity and with good ability to fit the data on the boundaries of variable range. The results obtained conclude that these kinds of models might well be very a valuable tool for mathematical modeling.

Growth-Mortality Relationships in Piñon Pine (Pinus edulis) during Severe Droughts of the Past Century: Shifting Processes in Space and Time

PubMed Central

Macalady, Alison K.; Bugmann, Harald

2014-01-01

The processes leading to drought-associated tree mortality are poorly understood, particularly long-term predisposing factors, memory effects, and variability in mortality processes and thresholds in space and time. We use tree rings from four sites to investigate Pinus edulis mortality during two drought periods in the southwestern USA. We draw on recent sampling and archived collections to (1) analyze P. edulis growth patterns and mortality during the 1950s and 2000s droughts; (2) determine the influence of climate and competition on growth in trees that died and survived; and (3) derive regression models of growth-mortality risk and evaluate their performance across space and time. Recent growth was 53% higher in surviving vs. dying trees, with some sites exhibiting decades-long growth divergences associated with previous drought. Differential growth response to climate partly explained growth differences between live and dead trees, with responses wet/cool conditions most influencing eventual tree status. Competition constrained tree growth, and reduced trees’ ability to respond to favorable climate. The best predictors in growth-mortality models included long-term (15–30 year) average growth rate combined with a metric of growth variability and the number of abrupt growth increases over 15 and 10 years, respectively. The most parsimonious models had high discriminatory power (ROC>0.84) and correctly classified ∼70% of trees, suggesting that aspects of tree growth, especially over decades, can be powerful predictors of widespread drought-associated die-off. However, model discrimination varied across sites and drought events. Weaker growth-mortality relationships and higher growth at lower survival probabilities for some sites during the 2000s event suggest a shift in mortality processes from longer-term growth-related constraints to shorter-term processes, such as rapid metabolic decline even in vigorous trees due to acute drought stress, and/or increases in the attack rate of both chronically stressed and more vigorous trees by bark beetles. PMID:24786646

Growth-mortality relationships in piñon pine (Pinus edulis) during severe droughts of the past century: shifting processes in space and time.

PubMed

Macalady, Alison K; Bugmann, Harald

2014-01-01

The processes leading to drought-associated tree mortality are poorly understood, particularly long-term predisposing factors, memory effects, and variability in mortality processes and thresholds in space and time. We use tree rings from four sites to investigate Pinus edulis mortality during two drought periods in the southwestern USA. We draw on recent sampling and archived collections to (1) analyze P. edulis growth patterns and mortality during the 1950s and 2000s droughts; (2) determine the influence of climate and competition on growth in trees that died and survived; and (3) derive regression models of growth-mortality risk and evaluate their performance across space and time. Recent growth was 53% higher in surviving vs. dying trees, with some sites exhibiting decades-long growth divergences associated with previous drought. Differential growth response to climate partly explained growth differences between live and dead trees, with responses wet/cool conditions most influencing eventual tree status. Competition constrained tree growth, and reduced trees' ability to respond to favorable climate. The best predictors in growth-mortality models included long-term (15-30 year) average growth rate combined with a metric of growth variability and the number of abrupt growth increases over 15 and 10 years, respectively. The most parsimonious models had high discriminatory power (ROC>0.84) and correctly classified ∼ 70% of trees, suggesting that aspects of tree growth, especially over decades, can be powerful predictors of widespread drought-associated die-off. However, model discrimination varied across sites and drought events. Weaker growth-mortality relationships and higher growth at lower survival probabilities for some sites during the 2000s event suggest a shift in mortality processes from longer-term growth-related constraints to shorter-term processes, such as rapid metabolic decline even in vigorous trees due to acute drought stress, and/or increases in the attack rate of both chronically stressed and more vigorous trees by bark beetles.

Numerical modeling study on the epitaxial growth of silicon from dichlorosilane

NASA Astrophysics Data System (ADS)

Zaidi, Imama; Jang, Yeon-Ho; Ko, Dong Guk; Im, Ik-Tae

2018-02-01

Computer simulations play an important role in determining the optimal design parameters for chemical vapor deposition (CVD) reactors, such as flow rates, positions of the inlet and outlet orifices, and rotational rates, etc. Reliability of the results of these simulations depends on the set of chemical reaction used to represent the process of deposition in the reactor. Aim of the present work is to validate the simple empirical reaction to model the epitaxial growth of silicon for a Dichlorosilane-H2 (DCS)-H2 system. Governing equations for continuity, momentum, energy, and reacting species are solved numerically using the finite volume method. The agreement between experimental and predicted growth rates for various DCS flow rates is shown to be satisfactory. The increase in growth rate with the increase in pressure is in accordance with the available data. Based on the validated chemical reaction model, a study was carried out to analyze the uniformity of the silicon layer thickness for two different flow rates in a planetary reactor. It was concluded that, based on the operating conditions, the uniformity of the silicon layer over the wafer is independent of the satellite rotational rate in the reactor.

Model-supported phototrophic growth studies with Scenedesmus obtusiusculus in a flat-plate photobioreactor.

PubMed

Koller, Anja Pia; Löwe, Hannes; Schmid, Verena; Mundt, Sabine; Weuster-Botz, Dirk

2017-02-01

Light-dependent growth of microalgae can vary remarkably depending on the cultivation system and microalgal strain. Cell size and the pigmentation of each strain, as well as reactor geometry have a great impact on absorption and scattering behavior within a photobioreactor. In this study, the light-dependent, cell-specific growth kinetics of a novel green algae isolate, Scenedesmus obtusiusculus, was studied in a LED-illuminated flat-plate photobioreactor on a lab-scale (1.8 L, 0.09 m 2 ). First, pH-controlled batch processes were performed with S. obtusiusculus at different constant incident photon flux densities. The best performance was achieved by illuminating S. obtusiusculus with 1400 μmol photons m -2  s -1 at the surface of the flat-plate photobioreactor, resulting in the highest biomass concentration (4.95 ± 0.16 g CDW  L -1 within 3.5 d) and the highest specific growth rate (0.22 h -1 ). The experimental data were used to identify the kinetic parameters of different growth models considering light inhibition for S. obtusiusculus. Light attenuation within the flat-plate photobioreactor was considered by varying light transfer models. Based on the identified kinetic growth model of S. obtusiusculus, an optimum growth rate of 0.22 h -1 was estimated at a mean integral photon flux density of 1072 μmol photons m -2  s -1 with the Beer-Lambert law and 1590 μmol photons m -2  s -1 with Schuster's light transfer model in the flat-plate photobioreactor. LED illumination was, thus, increased to keep the identified optimum mean integral photon flux density constant in the batch process assuming Schuster's light transfer model. Compared to the same constant incident photon flux density (1590 μmol photons m -2  s -1 ), biomass concentration was up to 24% higher using the lighting profile until a dry cell mass concentration of 14.4 ± 1.4 g CDW  L -1 was reached. Afterward, the biomass concentration remained constant, whereas cell growth continued in the batch process with constant incident photon flux density. Finally, biomass concentration was 15.5 ± 1.5 g CDW  L -1 and, thus, 7% higher compared to the corresponding batch process with lighting profile. Biotechnol. Bioeng. 2017;114: 308-320. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Modelling approaches for relating effects of change in river flow to populations of Atlantic salmon and brown trout

Treesearch

John D. Armstrong; Keith H. Nislow

2012-01-01

Modelling approaches for relating discharge to the biology of Atlantic salmon, Salmo salar L., and brown trout, Salmo trutta L., growing in rivers are reviewed. Process-based and empirical models are set within a common framework of input of water flow and output of characteristics of fish, such as growth and survival, which relate directly to population dynamics. A...

Slow crack growth: Models and experiments

NASA Astrophysics Data System (ADS)

Santucci, S.; Vanel, L.; Ciliberto, S.

2007-07-01

The properties of slow crack growth in brittle materials are analyzed both theoretically and experimentally. We propose a model based on a thermally activated rupture process. Considering a 2D spring network submitted to an external load and to thermal noise, we show that a preexisting crack in the network may slowly grow because of stress fluctuations. An analytical solution is found for the evolution of the crack length as a function of time, the time to rupture and the statistics of the crack jumps. These theoretical predictions are verified by studying experimentally the subcritical growth of a single crack in thin sheets of paper. A good agreement between the theoretical predictions and the experimental results is found. In particular, our model suggests that the statistical stress fluctuations trigger rupture events at a nanometric scale corresponding to the diameter of cellulose microfibrils.

Investigation of Mediational Processes Using Parallel Process Latent Growth Curve Modeling.

ERIC Educational Resources Information Center

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

2003-01-01

Investigated a method to evaluate mediational processes using latent growth curve modeling and tested it with empirical data from a longitudinal steroid use prevention program focusing on 1,506 high school football players over 4 years. Findings suggest the usefulness of the approach. (SLD)

Dynamic modeling of green algae cultivation in a photobioreactor for sustainable biodiesel production.

PubMed

Del Rio-Chanona, Ehecatl A; Liu, Jiao; Wagner, Jonathan L; Zhang, Dongda; Meng, Yingying; Xue, Song; Shah, Nilay

2018-02-01

Biodiesel produced from microalgae has been extensively studied due to its potentially outstanding advantages over traditional transportation fuels. In order to facilitate its industrialization and improve the process profitability, it is vital to construct highly accurate models capable of predicting the complex behavior of the investigated biosystem for process optimization and control, which forms the current research goal. Three original contributions are described in this paper. Firstly, a dynamic model is constructed to simulate the complicated effect of light intensity, nutrient supply and light attenuation on both biomass growth and biolipid production. Secondly, chlorophyll fluorescence, an instantly measurable variable and indicator of photosynthetic activity, is embedded into the model to monitor and update model accuracy especially for the purpose of future process optimal control, and its correlation between intracellular nitrogen content is quantified, which to the best of our knowledge has never been addressed so far. Thirdly, a thorough experimental verification is conducted under different scenarios including both continuous illumination and light/dark cycle conditions to testify the model predictive capability particularly for long-term operation, and it is concluded that the current model is characterized by a high level of predictive capability. Based on the model, the optimal light intensity for algal biomass growth and lipid synthesis is estimated. This work, therefore, paves the way to forward future process design and real-time optimization. © 2017 Wiley Periodicals, Inc.

Linking growth and yield and process models to estimate impact of environmental changes on growth of loblolly pine

Treesearch

V. Clark Baldwin; Harold E. Burkhart; James A. Westfall; Kelly D. Peterson

2001-01-01

PTAEDA2 is a distance-dependent, individual tree model that simulates the growth and yield of a plantation of loblolly pine (Pinus taeda L.)on an annual basis. The MAESTRO model utilizes an array of trees in a stand to calculate and integrate the effects of biological and physical variables on the photosynthesis and respiration processes of a target...

Systematic optimization of fed-batch simultaneous saccharification and fermentation at high-solid loading based on enzymatic hydrolysis and dynamic metabolic modeling of Saccharomyces cerevisiae.

PubMed

Unrean, Pornkamol; Khajeeram, Sutamat; Laoteng, Kobkul

2016-03-01

An integrative simultaneous saccharification and fermentation (SSF) modeling is a useful guiding tool for rapid process optimization to meet the techno-economic requirement of industrial-scale lignocellulosic ethanol production. In this work, we have developed the SSF model composing of a metabolic network of a Saccharomyces cerevisiae cell associated with fermentation kinetics and enzyme hydrolysis model to quantitatively capture dynamic responses of yeast cell growth and fermentation during SSF. By using model-based design of feeding profiles for substrate and yeast cell in the fed-batch SSF process, an efficient ethanol production with high titer of up to 65 g/L and high yield of 85 % of theoretical yield was accomplished. The ethanol titer and productivity was increased by 47 and 41 %, correspondingly, in optimized fed-batch SSF as compared to batch process. The developed integrative SSF model is, therefore, considered as a promising approach for systematic design of economical and sustainable SSF bioprocessing of lignocellulose.

In vitro 3D regeneration-like growth of human patient brain tissue.

PubMed

Tang-Schomer, M D; Wu, W B; Kaplan, D L; Bookland, M J

2018-05-01

In vitro culture of primary neurons is widely adapted with embryonic but not mature brain tissue. Here, we extended a previously developed bioengineered three-dimensional (3D) embryonic brain tissue model to resected normal patient brain tissue in an attempt to regenerate human neurons in vitro. Single cells and small sized (diameter < 100 μm) spheroids from dissociated brain tissue were seeded into 3D silk fibroin-based scaffolds, with or without collagen or Matrigel, and compared with two-dimensional cultures and scaffold-free suspension cultures. Changes of cell phenotypes (neuronal, astroglial, neural progenitor, and neuroepithelial) were quantified with flow cytometry and analyzed with a new method of statistical analysis specifically designed for percentage comparison. Compared with a complete lack of viable cells in conventional neuronal cell culture condition, supplements of vascular endothelial growth factor-containing pro-endothelial cell condition led to regenerative growth of neurons and astroglial cells from "normal" human brain tissue of epilepsy surgical patients. This process involved delayed expansion of Nestin+ neural progenitor cells, emergence of TUJ1+ immature neurons, and Vimentin+ neuroepithelium-like cell sheet formation in prolonged cultures (14 weeks). Micro-tissue spheroids, but not single cells, supported the brain tissue growth, suggesting importance of preserving native cell-cell interactions. The presence of 3D scaffold, but not hydrogel, allowed for Vimentin+ cell expansion, indicating a different growth mechanism than pluripotent cell-based brain organoid formation. The slow and delayed process implied an origin of quiescent neural precursors in the neocortex tissue. Further optimization of the 3D tissue model with primary human brain cells could provide personalized brain disease models. Copyright © 2018 John Wiley & Sons, Ltd.

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 Knowledge Generation Model via the Hypernetwork

PubMed Central

Liu, Jian-Guo; Yang, Guang-Yong; Hu, Zhao-Long

2014-01-01

The influence of the statistical properties of the network on the knowledge diffusion has been extensively studied. However, the structure evolution and the knowledge generation processes are always integrated simultaneously. By introducing the Cobb-Douglas production function and treating the knowledge growth as a cooperative production of knowledge, in this paper, we present two knowledge-generation dynamic evolving models based on different evolving mechanisms. The first model, named “HDPH model,” adopts the hyperedge growth and the hyperdegree preferential attachment mechanisms. The second model, named “KSPH model,” adopts the hyperedge growth and the knowledge stock preferential attachment mechanisms. We investigate the effect of the parameters on the total knowledge stock of the two models. The hyperdegree distribution of the HDPH model can be theoretically analyzed by the mean-field theory. The analytic result indicates that the hyperdegree distribution of the HDPH model obeys the power-law distribution and the exponent is . Furthermore, we present the distributions of the knowledge stock for different parameters . The findings indicate that our proposed models could be helpful for deeply understanding the scientific research cooperation. PMID:24626143

A knowledge generation model via the hypernetwork.

PubMed

Liu, Jian-Guo; Yang, Guang-Yong; Hu, Zhao-Long

2014-01-01

The influence of the statistical properties of the network on the knowledge diffusion has been extensively studied. However, the structure evolution and the knowledge generation processes are always integrated simultaneously. By introducing the Cobb-Douglas production function and treating the knowledge growth as a cooperative production of knowledge, in this paper, we present two knowledge-generation dynamic evolving models based on different evolving mechanisms. The first model, named "HDPH model," adopts the hyperedge growth and the hyperdegree preferential attachment mechanisms. The second model, named "KSPH model," adopts the hyperedge growth and the knowledge stock preferential attachment mechanisms. We investigate the effect of the parameters (α,β) on the total knowledge stock of the two models. The hyperdegree distribution of the HDPH model can be theoretically analyzed by the mean-field theory. The analytic result indicates that the hyperdegree distribution of the HDPH model obeys the power-law distribution and the exponent is γ = 2 + 1/m. Furthermore, we present the distributions of the knowledge stock for different parameters (α,β). The findings indicate that our proposed models could be helpful for deeply understanding the scientific research cooperation.

Growth rate of YBCO-Ag superconducting single grains

NASA Astrophysics Data System (ADS)

Congreve, J. V. J.; Shi, Y. H.; Dennis, A. R.; Durrell, J. H.; Cardwell, D. A.

2017-12-01

The large scale use of (RE)Ba2Cu3O7 bulk superconductors, where RE=Y, Gd, Sm, is, in part, limited by the relatively poor mechanical properties of these inherently brittle ceramic materials. It is reported that alloying of (RE)Ba2Cu3O7 with silver enables a significant improvement in the mechanical strength of bulk, single grain samples without any detrimental effect on their superconducting properties. However, due to the complexity and number of inter-related variables involved in the top seeded melt growth (TSMG) process, the growth of large single grains is difficult and the addition of silver makes it even more difficult to achieve successful growth reliably. The key processing variables in the TSMG process include the times and temperatures of the stages within the heating profile, which can be derived from the growth rate during the growth process. To date, the growth rate of the YBa2Cu3O7-Ag system has not been reported in detail and it is this lacuna that we have sought to address. In this work we measure the growth rate of the YBCO-Ag system using a method based on continuous cooling and isothermal holding (CCIH). We have determined the growth rate by measuring the side length of the crystallised region for a number of samples for specified isothermal hold temperatures and periods. This has enabled the growth rate to be modelled and from this an optimized heating profile for the successful growth of YBCO-Ag single grains to be derived.

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

PubMed Central

Keren, Leeat; Segal, Eran; Milo, Ron

2016-01-01

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

Climate change, global warming and coral reefs: modelling the effects of temperature.

PubMed

Crabbe, M James C

2008-10-01

Climate change and global warming have severe consequences for the survival of scleractinian (reef-building) corals and their associated ecosystems. This review summarizes recent literature on the influence of temperature on coral growth, coral bleaching, and modelling the effects of high temperature on corals. Satellite-based sea surface temperature (SST) and coral bleaching information available on the internet is an important tool in monitoring and modelling coral responses to temperature. Within the narrow temperature range for coral growth, corals can respond to rate of temperature change as well as to temperature per se. We need to continue to develop models of how non-steady-state processes such as global warming and climate change will affect coral reefs.

Linking stem cell function and growth pattern of intestinal organoids.

PubMed

Thalheim, Torsten; Quaas, Marianne; Herberg, Maria; Braumann, Ulf-Dietrich; Kerner, Christiane; Loeffler, Markus; Aust, Gabriela; Galle, Joerg

2018-01-15

Intestinal stem cells (ISCs) require well-defined signals from their environment in order to carry out their specific functions. Most of these signals are provided by neighboring cells that form a stem cell niche, whose shape and cellular composition self-organize. Major features of this self-organization can be studied in ISC-derived organoid culture. In this system, manipulation of essential pathways of stem cell maintenance and differentiation results in well-described growth phenotypes. We here provide an individual cell-based model of intestinal organoids that enables a mechanistic explanation of the observed growth phenotypes. In simulation studies of the 3D structure of expanding organoids, we investigate interdependences between Wnt- and Notch-signaling which control the shape of the stem cell niche and, thus, the growth pattern of the organoids. Similar to in vitro experiments, changes of pathway activities alter the cellular composition of the organoids and, thereby, affect their shape. Exogenous Wnt enforces transitions from branched into a cyst-like growth pattern; known to occur spontaneously during long term organoid expansion. Based on our simulation results, we predict that the cyst-like pattern is associated with biomechanical changes of the cells which assign them a growth advantage. The results suggest ongoing stem cell adaptation to in vitro conditions during long term expansion by stabilizing Wnt-activity. Our study exemplifies the potential of individual cell-based modeling in unraveling links between molecular stem cell regulation and 3D growth of tissues. This kind of modeling combines experimental results in the fields of stem cell biology and cell biomechanics constituting a prerequisite for a better understanding of tissue regeneration as well as developmental processes. Copyright © 2017 Elsevier Inc. All rights reserved.

The Biasing Effects of Unmodeled ARMA Time Series Processes on Latent Growth Curve Model Estimates

ERIC Educational Resources Information Center

Sivo, Stephen; Fan, Xitao; Witta, Lea

2005-01-01

The purpose of this study was to evaluate the robustness of estimated growth curve models when there is stationary autocorrelation among manifest variable errors. The results suggest that when, in practice, growth curve models are fitted to longitudinal data, alternative rival hypotheses to consider would include growth models that also specify…

Numerical simulation of plagioclase rim growth during magma ascent at Bezymianny Volcano, Kamchatka

NASA Astrophysics Data System (ADS)

Gorokhova, N. V.; Melnik, O. E.; Plechov, P. Yu.; Shcherbakov, V. D.

2013-08-01

Slow CaAl-NaSi interdiffusion in plagioclase crystals preserves chemical zoning of plagioclase in detail, which, along with strong dependence of anorthite content in plagioclase on melt composition, pressure, and temperature, make this mineral an important source of information on magma processes. A numerical model of zoned crystal growth is developed in the paper. The model is based on equations of multicomponent diffusion with diagonal cross-component diffusion terms and accounts for mass conservation on the melt-crystal interface and growth rate controlled by undercooling. The model is applied to the data of plagioclase rim zoning from several recent Bezymianny Volcano (Kamchatka) eruptions. We show that an equilibrium growth model cannot explain crystallization of naturally observed plagioclase during magma ascent. The developed non-equilibrium model reproduced natural plagioclase zoning and allowed magma ascent rates to be constrained. Matching of natural and simulated zoning suggests ascent from 100 to 50 MPa during 15-20 days. Magma ascent rate from 50 MPa to the surface varies from eruption to eruption: plagioclase zoning from the December 2006 eruption suggests ascent to the surface in less than 1 day, whereas plagioclase zoning from March 2000 and May 2007 eruptions are better explained by magma ascent over periods of more than 30 days). Based on comparison of diffusion coefficients for individual elements a mechanism of atomic diffusion during plagioclase crystallization is proposed.

On-lattice agent-based simulation of populations of cells within the open-source Chaste framework.

PubMed

Figueredo, Grazziela P; Joshi, Tanvi V; Osborne, James M; Byrne, Helen M; Owen, Markus R

2013-04-06

Over the years, agent-based models have been developed that combine cell division and reinforced random walks of cells on a regular lattice, reaction-diffusion equations for nutrients and growth factors; and ordinary differential equations for the subcellular networks regulating the cell cycle. When linked to a vascular layer, this multiple scale model framework has been applied to tumour growth and therapy. Here, we report on the creation of an agent-based multi-scale environment amalgamating the characteristics of these models within a Virtual Physiological Human (VPH) Exemplar Project. This project enables reuse, integration, expansion and sharing of the model and relevant data. The agent-based and reaction-diffusion parts of the multi-scale model have been implemented and are available for download as part of the latest public release of Chaste (Cancer, Heart and Soft Tissue Environment; http://www.cs.ox.ac.uk/chaste/), part of the VPH Toolkit (http://toolkit.vph-noe.eu/). The environment functionalities are verified against the original models, in addition to extra validation of all aspects of the code. In this work, we present the details of the implementation of the agent-based environment, including the system description, the conceptual model, the development of the simulation model and the processes of verification and validation of the simulation results. We explore the potential use of the environment by presenting exemplar applications of the 'what if' scenarios that can easily be studied in the environment. These examples relate to tumour growth, cellular competition for resources and tumour responses to hypoxia (low oxygen levels). We conclude our work by summarizing the future steps for the expansion of the current system.

A simple 2D biofilm model yields a variety of morphological features.

PubMed

Hermanowicz, S W

2001-01-01

A two-dimensional biofilm model was developed based on the concept of cellular automata. Three simple, generic processes were included in the model: cell growth, internal and external mass transport and cell detachment (erosion). The model generated a diverse range of biofilm morphologies (from dense layers to open, mushroom-like forms) similar to those observed in real biofilm systems. Bulk nutrient concentration and external mass transfer resistance had a large influence on the biofilm structure.

Cloud Based Metalearning System for Predictive Modeling of Biomedical Data

PubMed Central

Vukićević, Milan

2014-01-01

Rapid growth and storage of biomedical data enabled many opportunities for predictive modeling and improvement of healthcare processes. On the other side analysis of such large amounts of data is a difficult and computationally intensive task for most existing data mining algorithms. This problem is addressed by proposing a cloud based system that integrates metalearning framework for ranking and selection of best predictive algorithms for data at hand and open source big data technologies for analysis of biomedical data. PMID:24892101

Loblolly pine foliar patterns and growth dynamics at age 12 in response to planting density and cultural intensity

Treesearch

Madison Katherine Akers; Michael Kane; Dehai Zhao; Richard F. Daniels; Robert O. Teskey

2015-01-01

Examining the role of foliage in stand development across a range of stand structures provides a more detailed understanding of the processes driving productivity and allows further development of process-based models for prediction. Productivity changes observed at the stand scale will be the integration of changes at the individual tree scale, but few studies have...

Drastic reduction in the growth temperature of graphene on copper via enhanced London dispersion force

PubMed Central

Choi, Jin-Ho; Li, Zhancheng; Cui, Ping; Fan, Xiaodong; Zhang, Hui; Zeng, Changgan; Zhang, Zhenyu

2013-01-01

London dispersion force is ubiquitous in nature, and is increasingly recognized to be an important factor in a variety of surface processes. Here we demonstrate unambiguously the decisive role of London dispersion force in non-equilibrium growth of ordered nanostructures on metal substrates using aromatic source molecules. Our first-principles based multi-scale modeling shows that a drastic reduction in the growth temperature, from ~1000°C to ~300°C, can be achieved in graphene growth on Cu(111) when the typical carbon source of methane is replaced by benzene or p-Terphenyl. The London dispersion force enhances their adsorption energies by about (0.5–1.8) eV, thereby preventing their easy desorption, facilitating dehydrogenation, and promoting graphene growth at much lower temperatures. These quantitative predictions are validated in our experimental tests, showing convincing demonstration of monolayer graphene growth using the p-Terphenyl source. The general trends established are also more broadly applicable in molecular synthesis of surface-based nanostructures. PMID:23722566

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

NASA Astrophysics Data System (ADS)

Laurini, Márcio Poletti

2017-10-01

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

Temperature Dependence of Density, Viscosity and Electrical Conductivity for Hg-Based II-VI Semiconductor Melts

NASA Technical Reports Server (NTRS)

Li, C.; Ban, H.; Lin, B.; Scripa, R. N.; Su, C.-H.; Lehoczky, S. L.

2004-01-01

The relaxation phenomenon of semiconductor melts, or the change of melt structure with time, impacts the crystal growth process and the eventual quality of the crystal. The thermophysical properties of the melt are good indicators of such changes in melt structure. Also, thermophysical properties are essential to the accurate predication of the crystal growth process by computational modeling. Currently, the temperature dependent thermophysical property data for the Hg-based II-VI semiconductor melts are scarce. This paper reports the results on the temperature dependence of melt density, viscosity and electrical conductivity of Hg-based II-VI compounds. The melt density was measured using a pycnometric method, and the viscosity and electrical conductivity were measured by a transient torque method. Results were compared with available published data and showed good agreement. The implication of the structural changes at different temperature ranges was also studied and discussed.

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.

A study of tumour growth based on stoichiometric principles: a continuous model and its discrete analogue.

PubMed

Saleem, M; Agrawal, Tanuja; Anees, Afzal

2014-01-01

In this paper, we consider a continuous mathematically tractable model and its discrete analogue for the tumour growth. The model formulation is based on stoichiometric principles considering tumour-immune cell interactions in potassium (K (+))-limited environment. Our both continuous and discrete models illustrate 'cancer immunoediting' as a dynamic process having all three phases namely elimination, equilibrium and escape. The stoichiometric principles introduced into the model allow us to study its dynamics with the variation in the total potassium in the surrounding of the tumour region. It is found that an increase in the total potassium may help the patient fight the disease for a longer period of time. This result seems to be in line with the protective role of the potassium against the risk of pancreatic cancer as has been reported by Bravi et al. [Dietary intake of selected micronutrients and risk of pancreatic cancer: An Italian case-control study, Ann. Oncol. 22 (2011), pp. 202-206].

A study of tumour growth based on stoichiometric principles: a continuous model and its discrete analogue

PubMed Central

Saleem, M.; Agrawal, Tanuja; Anees, Afzal

2014-01-01

In this paper, we consider a continuous mathematically tractable model and its discrete analogue for the tumour growth. The model formulation is based on stoichiometric principles considering tumour-immune cell interactions in potassium (K +)-limited environment. Our both continuous and discrete models illustrate ‘cancer immunoediting’ as a dynamic process having all three phases namely elimination, equilibrium and escape. The stoichiometric principles introduced into the model allow us to study its dynamics with the variation in the total potassium in the surrounding of the tumour region. It is found that an increase in the total potassium may help the patient fight the disease for a longer period of time. This result seems to be in line with the protective role of the potassium against the risk of pancreatic cancer as has been reported by Bravi et al. [Dietary intake of selected micronutrients and risk of pancreatic cancer: An Italian case-control study, Ann. Oncol. 22 (2011), pp. 202–206]. PMID:24963981

The Role of Light in the Emergence of Weeds: Using Camelina microcarpa as an Example.

PubMed

Royo-Esnal, Aritz; Gesch, Russell W; Forcella, Frank; Torra, Joel; Recasens, Jordi; Necajeva, Jevgenija

2015-01-01

When modelling the emergence of weeds, two main factors are considered that condition this process: temperature and soil moisture. Optimum temperature is necessary for metabolic processes that generate energy for growth, while turgor pressure is necessary for root and shoot elongation which eventually leads to seedling emergence from the soil. Most emergence models do not usually consider light as a residual factor, but it could have an important role as it can alter directly or indirectly the dormancy and germination of seeds. In this paper, inclusion of light as an additional factor to photoperiod and radiation in emergence models is explored and compared with the classical hydrothermal time (HTT) model using Camelina microcarpa as an example. HTT based on hourly estimates is also compared with that based on daily estimates. Results suggest that, although HTT based models are accurate enough for local applications, the precision of these models is improved when HTT is estimated hourly and solar radiation is included as a factor.

A prototypic mathematical model of the human hair cycle.

PubMed

Al-Nuaimi, Yusur; Goodfellow, Marc; Paus, Ralf; Baier, Gerold

2012-10-07

The human hair cycle is a complex, dynamic organ-transformation process during which the hair follicle repetitively progresses from a growth phase (anagen) to a rapid apoptosis-driven involution (catagen) and finally a relative quiescent phase (telogen) before returning to anagen. At present no theory satisfactorily explains the origin of the hair cycle rhythm. Based on experimental evidence we propose a prototypic model that focuses on the dynamics of hair matrix keratinocytes. We argue that a plausible feedback-control structure between two key compartments (matrix keratinocytes and dermal papilla) leads to dynamic instabilities in the population dynamics resulting in rhythmic hair growth. The underlying oscillation consists of an autonomous switching between two quasi-steady states. Additional features of the model, namely bistability and excitability, lead to new hypotheses about the impact of interventions on hair growth. We show how in silico testing may facilitate testing of candidate hair growth modulatory agents in human HF organ culture or in clinical trials. Copyright © 2012 Elsevier Ltd. All rights reserved.

Chemical models for simulating single-walled nanotube production in arc vaporization and laser ablation processes

NASA Technical Reports Server (NTRS)

Scott, Carl D.

2004-01-01

Chemical kinetic models for the nucleation and growth of clusters and single-walled carbon nanotube (SWNT) growth are developed for numerical simulations of the production of SWNTs. Two models that involve evaporation and condensation of carbon and metal catalysts, a full model involving all carbon clusters up to C80, and a reduced model are discussed. The full model is based on a fullerene model, but nickel and carbon/nickel cluster reactions are added to form SWNTs from soot and fullerenes. The full model has a large number of species--so large that to incorporate them into a flow field computation for simulating laser ablation and arc processes requires that they be simplified. The model is reduced by defining large clusters that represent many various sized clusters. Comparisons are given between these models for cases that may be applicable to arc and laser ablation production. Solutions to the system of chemical rate equations of these models for a ramped temperature profile show that production of various species, including SWNTs, agree to within about 50% for a fast ramp, and within 10% for a slower temperature decay time.

Novel metamaterials and their applications in subwavelength waveguides, imanging and modulation

NASA Astrophysics Data System (ADS)

Zhang, Chaomin

GaAs-based solar cells have attracted much interest because of their high conversion efficiencies of ~28% under one sun illumination. The main carrier recombination mechanisms in the GaAs-based solar cells are surface recombination, radiative recombination and non-radiative recombination. Photon recycling reduces the effect of radiative recombination and is an approach to obtain the device performance described by detailed balance theory. The photon recycling model has been developed and was applied to investigate the loss mechanisms in the state-of-the-art GaAs-based solar cell structures using PC1D software. A standard fabrication process of the GaAs-based solar cells is as follows: wafer preparation, individual cell isolation by mesa, n- and p-type metallization, rapid thermal annealing (RTA), cap layer etching, and anti-reflection coating (ARC). The growth rate for GaAs-based materials is one of critical factors to determine the cost for the growth of GaAs-based solar cells. The cost for fabricating GaAs-based solar cells can be reduced if the growth rate is increased without degrading the crystalline quality. The solar cell wafers grown at different growth rates of 14 mum/hour and 55 mum/hour were discussed in this work. The structural properties of the wafers were characterized by X-ray diffraction (XRD) to identify the crystalline quality, and then the as-grown wafers were fabricated into solar cell devices under the same process conditions. The optical and electrical properties such as surface reflection, external quantum efficiency (EQE), dark I-V, Suns-Voc, and illuminated I-V under one sun using a solar simulator were measured to compare the performances of the solar cells with different growth rates. Some simulations in PC1D have been demonstrated to investigate the reasons of the different device performances between fast growth and slow growth structures. A further analysis of the minority carrier lifetime is needed to investigate into the difference in device performances.

Ion Electrodiffusion Governs Silk Electrogelation.

PubMed

Kojic, Nikola; Panzer, Matthew J; Leisk, Gary G; Raja, Waseem K; Kojic, Milos; Kaplan, David L

2012-07-14

Silk electrogelation involves the transition of an aqueous silk fibroin solution to a gel state (E-gel) in the presence of an electric current. The process is based on local pH changes as a result of water electrolysis - generating H(+) and OH(-) ions at the (+) and (-) electrodes, respectively. Silk fibroin has a pI=4.2 and when local pH

Island growth as a growth mode in atomic layer deposition: A phenomenological model

NASA Astrophysics Data System (ADS)

Puurunen, Riikka L.; Vandervorst, Wilfried

2004-12-01

Atomic layer deposition (ALD) has recently gained world-wide attention because of its suitability for the fabrication of conformal material layers with thickness in the nanometer range. Although the principles of ALD were realized about 40 years ago, the description of many physicochemical processes that occur during ALD growth is still under development. A constant amount of material deposited in an ALD reaction cycle, that is, growth-per-cycle (GPC), has been a paradigm in ALD through decades. The GPC may vary, however, especially in the beginning of the ALD growth. In this work, a division of ALD processes to four classes is proposed, on the basis of how the GPC varies with the number of ALD reaction cycles: linear growth, substrate-enhanced growth, and substrate-inhibited growth of type 1 and type 2. Island growth is identified as a likely origin for type 2 substrate-inhibited growth, where the GPC increases and goes through a maximum before it settles to a constant value characteristic of a steady growth. A simple phenomenological model is developed to describe island growth in ALD. The model assumes that the substrate is unreactive with the ALD reactants, except for reactive defects. ALD growth is assumed to proceed symmetrically from the defects, resulting islands of a conical shape. Random deposition is the growth mode on the islands. The model allows the simulation of GPC curves, surface fraction curves, and surface roughness, with physically significant parameters. When the model is applied to the zirconium tetrachloride/water and the trimethylaluminum/water ALD processes on hydrogen-terminated silicon, the calculated GPC curves and surface fractions agree with the experiments. The island growth model can be used to assess the occurrence of island growth, the size of islands formed, and point of formation of a continuous ALD-grown film. The benefits and limitations of the model and the general characteristics of type 2 substrate-inhibited ALD are discussed.

Cognitive Predictors of Achievement Growth in Mathematics: A Five Year Longitudinal Study

PubMed Central

Geary, David C.

2011-01-01

The study's goal was to identify the beginning of first grade quantitative competencies that predict mathematics achievement start point and growth through fifth grade. Measures of number, counting, and arithmetic competencies were administered in early first grade and used to predict mathematics achievement through fifth (n = 177), while controlling for intelligence, working memory, and processing speed. Multilevel models revealed intelligence, processing speed, and the central executive component of working memory predicted achievement or achievement growth in mathematics and, as a contrast domain, word reading. The phonological loop was uniquely predictive of word reading and the visuospatial sketch pad of mathematics. Early fluency in processing and manipulating numerical set size and Arabic numerals, accurate use of sophisticated counting procedures for solving addition problems, and accuracy in making placements on a mathematical number line were uniquely predictive of mathematics achievement. Use of memory-based processes to solve addition problems predicted mathematics and reading achievement but in different ways. The results identify the early quantitative competencies that uniquely contribute to mathematics learning. PMID:21942667

Statistical analysis of large simulated yield datasets for studying climate effects

USDA-ARS?s Scientific Manuscript database

Ensembles of process-based crop models are now commonly used to simulate crop growth and development for climate scenarios of temperature and/or precipitation changes corresponding to different projections of atmospheric CO2 concentrations. This approach generates large datasets with thousands of de...

ASSESSMENT OF SYNAPSE FORMATION IN RAT PRIMARY NEURAL CELL CULTURE USING HIGH CONTENT MICROSCOPY.

EPA Science Inventory

Cell-based assays can model neurodevelopmental processes including neurite growth and synaptogenesis, and may be useful for screening and evaluation of large numbers of chemicals for developmental neurotoxicity. This work describes the use of high content screening (HCS) to dete...

Differential tissue growth and cell adhesion alone drive early tooth morphogenesis: An ex vivo and in silico study

PubMed Central

Savriama, Yoland; Jernvall, Jukka

2018-01-01

From gastrulation to late organogenesis animal development involves many genetic and bio-mechanical interactions between epithelial and mesenchymal tissues. Ectodermal organs, such as hairs, feathers and teeth are well studied examples of organs whose development is based on epithelial-mesenchymal interactions. These develop from a similar primordium through an epithelial folding and its interaction with the mesenchyme. Despite extensive knowledge on the molecular pathways involved, little is known about the role of bio-mechanical processes in the morphogenesis of these organs. We propose a simple computational model for the biomechanics of one such organ, the tooth, and contrast its predictions against cell-tracking experiments, mechanical relaxation experiments and the observed tooth shape changes over developmental time. We found that two biomechanical processes, differential tissue growth and differential cell adhesion, were enough, in the model, for the development of the 3D morphology of the early tooth germ. This was largely determined by the length and direction of growth of the cervical loops, lateral folds of the enamel epithelium. The formation of these cervical loops was found to require accelerated epithelial growth relative to other tissues and their direction of growth depended on specific differential adhesion between the three tooth tissues. These two processes and geometrical constraints in early tooth bud also explained the shape asymmetry between the lateral cervical loops and those forming in the anterior and posterior of the tooth. By performing mechanical perturbations ex vivo and in silico we inferred the distribution and direction of tensile stresses in the mesenchyme that restricted cervical loop lateral growth and forced them to grow downwards. Overall our study suggests detailed quantitative explanations for how bio-mechanical processes lead to specific morphological 3D changes over developmental time. PMID:29481561

Unsteady Crystal Growth Due to Step-Bunch Cascading

NASA Technical Reports Server (NTRS)

Vekilov, Peter G.; Lin, Hong; Rosenberger, Franz

1997-01-01

Based on our experimental findings of growth rate fluctuations during the crystallization of the protein lysozym, we have developed a numerical model that combines diffusion in the bulk of a solution with diffusive transport to microscopic growth steps that propagate on a finite crystal facet. Nonlinearities in layer growth kinetics arising from step interaction by bulk and surface diffusion, and from step generation by surface nucleation, are taken into account. On evaluation of the model with properties characteristic for the solute transport, and the generation and propagation of steps in the lysozyme system, growth rate fluctuations of the same magnitude and characteristic time, as in the experiments, are obtained. The fluctuation time scale is large compared to that of step generation. Variations of the governing parameters of the model reveal that both the nonlinearity in step kinetics and mixed transport-kinetics control of the crystallization process are necessary conditions for the fluctuations. On a microscopic scale, the fluctuations are associated with a morphological instability of the vicinal face, in which a step bunch triggers a cascade of new step bunches through the microscopic interfacial supersaturation distribution.

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.

[Construction of information management-based virtual forest landscape and its application].

PubMed

Chen, Chongcheng; Tang, Liyu; Quan, Bing; Li, Jianwei; Shi, Song

2005-11-01

Based on the analysis of the contents and technical characteristics of different scale forest visualization modeling, this paper brought forward the principles and technical systems of constructing an information management-based virtual forest landscape. With the combination of process modeling and tree geometric structure description, a software method of interactively and parameterized tree modeling was developed, and the corresponding renderings and geometrical elements simplification algorithms were delineated to speed up rendering run-timely. As a pilot study, the geometrical model bases associated with the typical tree categories in Zhangpu County of Fujian Province, southeast China were established as template files. A Virtual Forest Management System prototype was developed with GIS component (ArcObject), OpenGL graphics environment, and Visual C++ language, based on forest inventory and remote sensing data. The prototype could be used for roaming between 2D and 3D, information query and analysis, and virtual and interactive forest growth simulation, and its reality and accuracy could meet the needs of forest resource management. Some typical interfaces of the system and the illustrative scene cross-sections of simulated masson pine growth under conditions of competition and thinning were listed.

Ecological invasion, roughened fronts, and a competitor's extreme advance: integrating stochastic spatial-growth models.

PubMed

O'Malley, Lauren; Korniss, G; Caraco, Thomas

2009-07-01

Both community ecology and conservation biology seek further understanding of factors governing the advance of an invasive species. We model biological invasion as an individual-based, stochastic process on a two-dimensional landscape. An ecologically superior invader and a resident species compete for space preemptively. Our general model includes the basic contact process and a variant of the Eden model as special cases. We employ the concept of a "roughened" front to quantify effects of discreteness and stochasticity on invasion; we emphasize the probability distribution of the front-runner's relative position. That is, we analyze the location of the most advanced invader as the extreme deviation about the front's mean position. We find that a class of models with different assumptions about neighborhood interactions exhibits universal characteristics. That is, key features of the invasion dynamics span a class of models, independently of locally detailed demographic rules. Our results integrate theories of invasive spatial growth and generate novel hypotheses linking habitat or landscape size (length of the invading front) to invasion velocity, and to the relative position of the most advanced invader.

Parameter estimation and sensitivity analysis in an agent-based model of Leishmania major infection

PubMed Central

Jones, Douglas E.; Dorman, Karin S.

2009-01-01

Computer models of disease take a systems biology approach toward understanding host-pathogen interactions. In particular, data driven computer model calibration is the basis for inference of immunological and pathogen parameters, assessment of model validity, and comparison between alternative models of immune or pathogen behavior. In this paper we describe the calibration and analysis of an agent-based model of Leishmania major infection. A model of macrophage loss following uptake of necrotic tissue is proposed to explain macrophage depletion following peak infection. Using Gaussian processes to approximate the computer code, we perform a sensitivity analysis to identify important parameters and to characterize their influence on the simulated infection. The analysis indicates that increasing growth rate can favor or suppress pathogen loads, depending on the infection stage and the pathogen’s ability to avoid detection. Subsequent calibration of the model against previously published biological observations suggests that L. major has a relatively slow growth rate and can replicate for an extended period of time before damaging the host cell. PMID:19837088

Current state of aerosol nucleation parameterizations for air-quality and climate modeling

NASA Astrophysics Data System (ADS)

Semeniuk, Kirill; Dastoor, Ashu

2018-04-01

Aerosol nucleation parameterization models commonly used in 3-D air quality and climate models have serious limitations. This includes classical nucleation theory based variants, empirical models and other formulations. Recent work based on detailed and extensive laboratory measurements and improved quantum chemistry computation has substantially advanced the state of nucleation parameterizations. In terms of inorganic nucleation involving BHN and THN including ion effects these new models should be considered as worthwhile replacements for the old models. However, the contribution of organic species to nucleation remains poorly quantified. New particle formation consists of a distinct post-nucleation growth regime which is characterized by a strong Kelvin curvature effect and is thus dependent on availability of very low volatility organic species or sulfuric acid. There have been advances in the understanding of the multiphase chemistry of biogenic and anthropogenic organic compounds which facilitate to overcome the initial aerosol growth barrier. Implementation of processes influencing new particle formation is challenging in 3-D models and there is a lack of comprehensive parameterizations. This review considers the existing models and recent innovations.

Rumination, event centrality, and perceived control as predictors of post-traumatic growth and distress: The Cognitive Growth and Stress model.

PubMed

Brooks, Matthew; Graham-Kevan, Nicola; Lowe, Michelle; Robinson, Sarita

2017-09-01

The Cognitive Growth and Stress (CGAS) model draws together cognitive processing factors previously untested into a single model. Intrusive rumination, deliberate rumination, present and future perceptions of control, and event centrality were assessed as predictors of post-traumatic growth (PTG) and post-traumatic stress (PTS). The CGAS model is tested on a sample of survivors (N = 250) of a diverse range of adverse events using structural equation modelling techniques. Overall, the best fitting model was supportive of the theorized relations between cognitive constructs and accounted for 30% of the variance in PTG and 68% of the variance in PTS across the sample. Rumination, centrality, and perceived control factors are significant determinants of positive and negative psychological change across the wide spectrum of adversarial events. In its first phase of development, the CGAS model also provides further evidence of the distinct processes of growth and distress following adversity. Clinical implications People can experience positive change after adversity, regardless of life background or types of events experienced. While growth and distress are possible outcomes after adversity, they occur through distinct processes. Support or intervention should consider rumination, event centrality, and perceived control factors to enhance psychological well-being. Cautions/limitations Longitudinal research would further clarify the findings found in this study. Further extension of the model is recommended to include other viable cognitive processes implicated in the development of positive and negative changes after adversity. © 2017 The British Psychological Society.

Stochastic modeling for neural spiking events based on fractional superstatistical Poisson process

NASA Astrophysics Data System (ADS)

Konno, Hidetoshi; Tamura, Yoshiyasu

2018-01-01

In neural spike counting experiments, it is known that there are two main features: (i) the counting number has a fractional power-law growth with time and (ii) the waiting time (i.e., the inter-spike-interval) distribution has a heavy tail. The method of superstatistical Poisson processes (SSPPs) is examined whether these main features are properly modeled. Although various mixed/compound Poisson processes are generated with selecting a suitable distribution of the birth-rate of spiking neurons, only the second feature (ii) can be modeled by the method of SSPPs. Namely, the first one (i) associated with the effect of long-memory cannot be modeled properly. Then, it is shown that the two main features can be modeled successfully by a class of fractional SSPP (FSSPP).

Effect of TiO2 Addition on Grain Growth, Anodic Bubble Evolution and Anodic Overvoltage of NiFe2O4-Based Composite Inert Anodes

NASA Astrophysics Data System (ADS)

Wang, Bin; Du, Jinjing; Liu, Yihan; Fang, Zhao; Hu, Ping

2017-11-01

A two-step powder compaction and sintering process was employed to fabricate TiO2-doped NiFe2O4 ceramic-based inert anodes. Grain growth during isothermal sintering was analyzed using Brook grain growth model. The bubble behavior of NiFe2O4 ceramic-based inert anodes was investigated in a two-compartment see-through quartz cell for aluminum electrolysis process. Anodic overvoltage and potential decay curves of the inert anodes were measured by using the steady state and current interruption technique. The results showed that the kinetic index of grain growth decreased with an increase in temperature. The average activation energy of grain growth for 1.0 wt.% TiO2-doped NiFe2O4 ceramic samples with a sintering temperature range from 1373 to 1673 K dropped from 675.30 to 183.47 kJ/mol. The diameter size of bubbles before releasing from the bottom surface of the anodes was reduced with increasing the current density, and the larger average releasing bubble size for carbon anode at the same current density could be obtained, which was compared to the NiFe2O4 inert anodes. Besides, the cell voltage of carbon anodes fluctuated much more violently under the same experimental conditions. After adding small amount of TiO2, a minor reduction in anodic overvoltage of NiFe2O4-based anodes can be observed.

Toward Multiscale Models of Cyanobacterial Growth: A Modular Approach

PubMed Central

Westermark, Stefanie; Steuer, Ralf

2016-01-01

Oxygenic photosynthesis dominates global primary productivity ever since its evolution more than three billion years ago. While many aspects of phototrophic growth are well understood, it remains a considerable challenge to elucidate the manifold dependencies and interconnections between the diverse cellular processes that together facilitate the synthesis of new cells. Phototrophic growth involves the coordinated action of several layers of cellular functioning, ranging from the photosynthetic light reactions and the electron transport chain, to carbon-concentrating mechanisms and the assimilation of inorganic carbon. It requires the synthesis of new building blocks by cellular metabolism, protection against excessive light, as well as diurnal regulation by a circadian clock and the orchestration of gene expression and cell division. Computational modeling allows us to quantitatively describe these cellular functions and processes relevant for phototrophic growth. As yet, however, computational models are mostly confined to the inner workings of individual cellular processes, rather than describing the manifold interactions between them in the context of a living cell. Using cyanobacteria as model organisms, this contribution seeks to summarize existing computational models that are relevant to describe phototrophic growth and seeks to outline their interactions and dependencies. Our ultimate aim is to understand cellular functioning and growth as the outcome of a coordinated operation of diverse yet interconnected cellular processes. PMID:28083530

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

PubMed

Wilkinson, Sarah; Ogée, Jérôme; Domec, Jean-Christophe; Rayment, Mark; Wingate, Lisa

2015-03-01

Process-based models that link seasonally varying environmental signals to morphological features within tree rings are essential tools to predict tree growth response and commercially important wood quality traits under future climate scenarios. This study evaluated model portrayal of radial growth and wood anatomy observations within a mature maritime pine (Pinus pinaster (L.) Aït.) stand exposed to seasonal droughts. Intra-annual variations in tracheid anatomy and wood density were identified through image analysis and X-ray densitometry on stem cores covering the growth period 1999-2010. A cambial growth model was integrated with modelled plant water status and sugar availability from the soil-plant-atmosphere transfer model MuSICA to generate estimates of cell number, cell volume, cell mass and wood density on a weekly time step. The model successfully predicted inter-annual variations in cell number, ring width and maximum wood density. The model was also able to predict the occurrence of special anatomical features such as intra-annual density fluctuations (IADFs) in growth rings. Since cell wall thickness remained surprisingly constant within and between growth rings, variations in wood density were primarily the result of variations in lumen diameter, both in the model and anatomical data. In the model, changes in plant water status were identified as the main driver of the IADFs through a direct effect on cell volume. The anatomy data also revealed that a trade-off existed between hydraulic safety and hydraulic efficiency. Although a simplified description of cambial physiology is presented, this integrated modelling approach shows potential value for identifying universal patterns of tree-ring growth and anatomical features over a broad climatic gradient. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Porosity and Variations in Microgravity Aerogel Nano-Structures. 2; New Laser Speckle Characterization Methods

NASA Technical Reports Server (NTRS)

Hunt, A. J.; Ayers, M. R.; Sibille, L.; Smith, D. D.

2001-01-01

The transition from sol to gel is a process that is critical to the properties of engineered nanomaterials, but one with few available techniques for observing the dynamic processes occurring during the evolution of the gel network. Specifically, the observation of various cluster aggregation models, such as diffusion-limited and reaction-limited cluster growth can be quite difficult. This can be rather important as the actual aggregation model can dramatically influence the mechanical properties of gels, and is significantly affected by the presence of convective flows, or their absence in microgravity. We have developed two new non-intrusive optical methods for observing the aggregation processes within gels in real time. These make use of the dynamic behavior of laser speckle patterns produced when an intense laser source is passed through a gelling sol. The first method is a simplified time-correlation measurement, where the speckle pattern is observed using a CCD camera and information on the movement of the scattering objects is readily apparent. This approach is extremely sensitive to minute variations in the flow field as the observed speckle pattern is a diffraction-based image, and is therefore sensitive to motions within the sol on the order of the wavelength of the probing light. Additionally, this method has proven useful in determining a precise time for the gel-point, an event often difficult to measure. Monitoring the evolution of contrast within the speckle field is another method that has proven useful for studying aeration. In this case, speckle contrast is dependent upon the size (correlation length) and number of scattering centers, increasing with increasing size, and decreasing with increasing numbers. The dynamic behavior of cluster growth in gels causes both of these to change simultaneously with time, the exact rate of which is determined by the specific aggregation model involved. Actual growth processes can now be observed, and the effects of varying gravity fields on the growth processes qualitatively described. Results on preliminary ground-based measurements have been obtained.

Microstructure and growth model for rice-hull-derived SiC whiskers

NASA Technical Reports Server (NTRS)

Nutt, Steven R.

1988-01-01

The microstructure of silicon carbide whiskers grown from rice hulls has been studied using methods of high-resolution analytical electron microscopy. Small, partially crystalline inclusions (about 10 nm) containing calcium, manganese, and oxygen are concentrated in whisker core regions, while peripheral regions are generally inclusion free. The distinct microphase distribution is evidence of a two-stage growth process in which the core region grows first, followed by normal growth toward whisker sides. Partial dislocations extend radially from the core region to the surface and tend to be paired in V-shaped configurations. Whisker surfaces exhibit microroughness due to a tendency to develop small facets on close-packed planes. The microstructural data obtained from TEM observations are used as a basis for discussion of the mechanisms involved in whisker growth, and a model of the growth process is proposed. The model includes a two-dimensional growth mechanism involving vapor, liquid, and solid phases, although it is significantly different from the classical vapor-liquid-solid (VLS) process of whisker growth.

Towards a model-based inventory of soil organic carbon in agricultural soils for the Swiss greenhouse gas reporting

NASA Astrophysics Data System (ADS)

Staudt, K.; Leifeld, J.; Bretscher, D.; Fuhrer, J.

2012-04-01

The Swiss inventory submission under the United Nations Framework Convention on Climate Change (UNFCCC) reports on changes in soil organic carbon stocks under different land-uses and land-use changes. The approach currently employed for cropland and grassland soils combines Tier 1 and Tier 2 methods and is considered overly simplistic. As the UNFCC encourages countries to develop Tier 3 methods for national greenhouse gas reporting, we aim to build up a model-based inventory of soil organic carbon in agricultural soils in Switzerland. We conducted a literature research on currently employed higher-tier methods using process-based models in four countries: Denmark, Sweden, Finland and the USA. The applied models stem from two major groups differing in complexity - those belonging to the group of general ecosystem models that include a plant-growth submodel, e.g. Century, and those that simulate soil organic matter turnover but not plant-growth, e.g. ICBM. For the latter group, carbon inputs to the soil from plant residues and roots have to be determined separately. We will present some aspects of the development of a model-based inventory of soil organic carbon in agricultural soils in Switzerland. Criteria for model evaluation are, among others, modeled land-use classes and land-use changes, spatial and temporal resolution, and coverage of relevant processes. For model parameterization and model evaluation at the field scale, data from several long-term agricultural experiments and monitoring sites in Switzerland is available. A subsequent regional application of a model requires the preparation of regional input data for the whole country - among others spatio-temporal meteorological data, agricultural and soil data. Following the evaluation of possible models and of available data, preference for application in the Swiss inventory will be given to simpler model structures, i.e. models without a plant-growth module. Thus, we compared different allometric relations for the estimation of plant carbon inputs to the soil from yield data that are usually provided with the models. Calculated above- and below-ground carbon inputs vary substantially between methods and exhibit different sensitivities to yield data. As a benchmark, inputs to the soil from above- and below-ground crop residues are calculated with the IPCC default method. Furthermore, the suitability of these estimation methods for Swiss conditions is tested.

Experimental analysis and modeling of melt growth processes

NASA Astrophysics Data System (ADS)

Müller, Georg

2002-04-01

Melt growth processes provide the basic crystalline materials for many applications. The research and development of crystal growth processes is therefore driven by the demands which arise from these specific applications; however, common goals include an increased uniformity of the relevant crystal properties at the micro- and macro-scale, a decrease of deleterious crystal defects, and an increase of crystal dimensions. As melt growth equipment and experimentation becomes more and more expensive, little room remains for improvements by trial and error procedures. A more successful strategy is to optimize the crystal growth process by a combined use of experimental process analysis and computer modeling. This will be demonstrated in this paper by several examples from the bulk growth of silicon, gallium arsenide, indium phosphide, and calcium fluoride. These examples also involve the most important melt growth techniques, crystal pulling (Czochralski methods) and vertical gradient freeze (Bridgman-type methods). The power and success of the above optimization strategy, however, is not limited only to the given examples but can be generalized and applied to many types of bulk crystal growth.

Numerical simulations of epitaxial growth process in MOVPE reactor as a tool for design of modern semiconductors for high power electronics

NASA Astrophysics Data System (ADS)

Skibinski, Jakub; Caban, Piotr; Wejrzanowski, Tomasz; Kurzydlowski, Krzysztof J.

2014-10-01

In the present study numerical simulations of epitaxial growth of gallium nitride in Metal Organic Vapor Phase Epitaxy reactor AIX-200/4RF-S is addressed. Epitaxial growth means crystal growth that progresses while inheriting the laminar structure and the orientation of substrate crystals. One of the technological problems is to obtain homogeneous growth rate over the main deposit area. Since there are many agents influencing reaction on crystal area such as temperature, pressure, gas flow or reactor geometry, it is difficult to design optimal process. According to the fact that it's impossible to determine experimentally the exact distribution of heat and mass transfer inside the reactor during crystal growth, modeling is the only solution to understand the process precisely. Numerical simulations allow to understand the epitaxial process by calculation of heat and mass transfer distribution during growth of gallium nitride. Including chemical reactions in numerical model allows to calculate the growth rate of the substrate and estimate the optimal process conditions for obtaining the most homogeneous product.

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

PubMed

May, Christian P; Kolokotroni, Eleni; Stamatakos, Georgios S; Büchler, Philippe

2011-10-01

Modeling of tumor growth has been performed according to various approaches addressing different biocomplexity levels and spatiotemporal scales. Mathematical treatments range from partial differential equation based diffusion models to rule-based cellular level simulators, aiming at both improving our quantitative understanding of the underlying biological processes and, in the mid- and long term, constructing reliable multi-scale predictive platforms to support patient-individualized treatment planning and optimization. The aim of this paper is to establish a multi-scale and multi-physics approach to tumor modeling taking into account both the cellular and the macroscopic mechanical level. Therefore, an already developed biomodel of clinical tumor growth and response to treatment is self-consistently coupled with a biomechanical model. Results are presented for the free growth case of the imageable component of an initially point-like glioblastoma multiforme tumor. The composite model leads to significant tumor shape corrections that are achieved through the utilization of environmental pressure information and the application of biomechanical principles. Using the ratio of smallest to largest moment of inertia of the tumor material to quantify the effect of our coupled approach, we have found a tumor shape correction of 20% by coupling biomechanics to the cellular simulator as compared to a cellular simulation without preferred growth directions. We conclude that the integration of the two models provides additional morphological insight into realistic tumor growth behavior. Therefore, it might be used for the development of an advanced oncosimulator focusing on tumor types for which morphology plays an important role in surgical and/or radio-therapeutic treatment planning. Copyright © 2011 Elsevier Ltd. All rights reserved.

How can model comparison help improving species distribution models?

PubMed

Gritti, Emmanuel Stephan; Gaucherel, Cédric; Crespo-Perez, Maria-Veronica; Chuine, Isabelle

2013-01-01

Today, more than ever, robust projections of potential species range shifts are needed to anticipate and mitigate the impacts of climate change on biodiversity and ecosystem services. Such projections are so far provided almost exclusively by correlative species distribution models (correlative SDMs). However, concerns regarding the reliability of their predictive power are growing and several authors call for the development of process-based SDMs. Still, each of these methods presents strengths and weakness which have to be estimated if they are to be reliably used by decision makers. In this study we compare projections of three different SDMs (STASH, LPJ and PHENOFIT) that lie in the continuum between correlative models and process-based models for the current distribution of three major European tree species, Fagussylvatica L., Quercusrobur L. and Pinussylvestris L. We compare the consistency of the model simulations using an innovative comparison map profile method, integrating local and multi-scale comparisons. The three models simulate relatively accurately the current distribution of the three species. The process-based model performs almost as well as the correlative model, although parameters of the former are not fitted to the observed species distributions. According to our simulations, species range limits are triggered, at the European scale, by establishment and survival through processes primarily related to phenology and resistance to abiotic stress rather than to growth efficiency. The accuracy of projections of the hybrid and process-based model could however be improved by integrating a more realistic representation of the species resistance to water stress for instance, advocating for pursuing efforts to understand and formulate explicitly the impact of climatic conditions and variations on these processes.

How Can Model Comparison Help Improving Species Distribution Models?

PubMed Central

Gritti, Emmanuel Stephan; Gaucherel, Cédric; Crespo-Perez, Maria-Veronica; Chuine, Isabelle

2013-01-01

Today, more than ever, robust projections of potential species range shifts are needed to anticipate and mitigate the impacts of climate change on biodiversity and ecosystem services. Such projections are so far provided almost exclusively by correlative species distribution models (correlative SDMs). However, concerns regarding the reliability of their predictive power are growing and several authors call for the development of process-based SDMs. Still, each of these methods presents strengths and weakness which have to be estimated if they are to be reliably used by decision makers. In this study we compare projections of three different SDMs (STASH, LPJ and PHENOFIT) that lie in the continuum between correlative models and process-based models for the current distribution of three major European tree species, Fagus sylvatica L., Quercus robur L. and Pinus sylvestris L. We compare the consistency of the model simulations using an innovative comparison map profile method, integrating local and multi-scale comparisons. The three models simulate relatively accurately the current distribution of the three species. The process-based model performs almost as well as the correlative model, although parameters of the former are not fitted to the observed species distributions. According to our simulations, species range limits are triggered, at the European scale, by establishment and survival through processes primarily related to phenology and resistance to abiotic stress rather than to growth efficiency. The accuracy of projections of the hybrid and process-based model could however be improved by integrating a more realistic representation of the species resistance to water stress for instance, advocating for pursuing efforts to understand and formulate explicitly the impact of climatic conditions and variations on these processes. PMID:23874779

Compound equation developed for postnatal growth of birds and mammals

NASA Technical Reports Server (NTRS)

Laird, A. K.

1968-01-01

Compound growth equation was developed in which the rate of this linear growth process is regarded as proportional to the mass already attained at any instant by an underlying Gompertz process. This compound growth model was fitted to the growth data of a variety of birds and mammals of both sexes.

Recrystallization and Grain Growth Kinetics in Binary Alpha Titanium-Aluminum Alloys

NASA Astrophysics Data System (ADS)

Trump, Anna Marie

Titanium alloys are used in a variety of important naval and aerospace applications and often undergo thermomechanical processing which leads to recrystallization and grain growth. Both of these processes have a significant impact on the mechanical properties of the material. Therefore, understanding the kinetics of these processes is crucial to being able to predict the final properties. Three alloys are studied with varying concentrations of aluminum which allows for the direct quantification of the effect of aluminum content on the kinetics of recrystallization and grain growth. Aluminum is the most common alpha stabilizing alloying element used in titanium alloys, however the effect of aluminum on these processes has not been previously studied. This work is also part of a larger Integrated Computational Materials Engineering (ICME) effort whose goal is to combine both computational and experimental efforts to develop computationally efficient models that predict materials microstructure and properties based on processing history. The static recrystallization kinetics are measured using an electron backscatter diffraction (EBSD) technique and a significant retardation in the kinetics is observed with increasing aluminum concentration. An analytical model is then used to capture these results and is able to successfully predict the effect of solute concentration on the time to 50% recrystallization. The model reveals that this solute effect is due to a combination of a decrease in grain boundary mobility and a decrease in driving force with increasing aluminum concentration. The effect of microstructural inhomogeneities is also experimentally quantified and the results are validated with a phase field model for recrystallization. These microstructural inhomogeneities explain the experimentally measured Avrami exponent, which is lower than the theoretical value calculated by the JMAK model. Similar to the effect seen in recrystallization, the addition of aluminum also significantly slows downs the grain growth kinetics. This is generally attributed to the solute drag effect due to segregation of solute atoms at the grain boundaries, however aluminum segregation is not observed in these alloys. The mechanism for this result is explained and is used to validate the prediction of an existing model for solute drag.

Comparing root architectural models

NASA Astrophysics Data System (ADS)

Schnepf, Andrea; Javaux, Mathieu; Vanderborght, Jan

2017-04-01

Plant roots play an important role in several soil processes (Gregory 2006). Root architecture development determines the sites in soil where roots provide input of carbon and energy and take up water and solutes. However, root architecture is difficult to determine experimentally when grown in opaque soil. Thus, root architectural models have been widely used and been further developed into functional-structural models that are able to simulate the fate of water and solutes in the soil-root system (Dunbabin et al. 2013). Still, a systematic comparison of the different root architectural models is missing. In this work, we focus on discrete root architecture models where roots are described by connected line segments. These models differ (a) in their model concepts, such as the description of distance between branches based on a prescribed distance (inter-nodal distance) or based on a prescribed time interval. Furthermore, these models differ (b) in the implementation of the same concept, such as the time step size, the spatial discretization along the root axes or the way stochasticity of parameters such as root growth direction, growth rate, branch spacing, branching angles are treated. Based on the example of two such different root models, the root growth module of R-SWMS and RootBox, we show the impact of these differences on simulated root architecture and aggregated information computed from this detailed simulation results, taking into account the stochastic nature of those models. References Dunbabin, V.M., Postma, J.A., Schnepf, A., Pagès, L., Javaux, M., Wu, L., Leitner, D., Chen, Y.L., Rengel, Z., Diggle, A.J. Modelling root-soil interactions using three-dimensional models of root growth, architecture and function (2013) Plant and Soil, 372 (1-2), pp. 93 - 124. Gregory (2006) Roots, rhizosphere and soil: the route to a better understanding of soil science? European Journal of Soil Science 57: 2-12.

Numerical simulation of the hair formation -modeling of hair cycle

NASA Astrophysics Data System (ADS)

Kajihara, Narumichi; Nagayama, Katsuya

2018-01-01

In the recent years, the fields of study of anti-aging, health and beauty, cosmetics, and hair diseases have attracted significant attention. In particular, human hair is considered to be an important aspect with regard to an attractive appearance. To this end, many workers have sought to understand the formation mechanism of the hair root. However, observing growth in the hair root is difficult, and a detailed mechanism of the process has not yet been elucidated. Hair repeats growth, retraction, and pause cycles (hair cycle) in a repetitive process. In the growth phase, hair is formed through processes of cell proliferation and differentiation (keratinization). During the retraction phase, hair growth stops, and during the resting period, hair fall occurs and new hair grows. This hair cycle is believed to affect the elongation rate, thickness, strength, and shape of hair. Therefore, in this study, we introduce a particle model as a new method to elucidate the unknown process of hair formation, and to model the hair formation process accompanying the proliferation and differentiation of the hair root cells in all three dimensions. In addition, to the growth period, the retraction and the resting periods are introduced to realize the hair cycle using this model.

Recruiting Conventional Tree Architecture Models into State-of-the-Art LiDAR Mapping for Investigating Tree Growth Habits in Structure.

PubMed

Lin, Yi; Jiang, Miao; Pellikka, Petri; Heiskanen, Janne

2018-01-01

Mensuration of tree growth habits is of considerable importance for understanding forest ecosystem processes and forest biophysical responses to climate changes. However, the complexity of tree crown morphology that is typically formed after many years of growth tends to render it a non-trivial task, even for the state-of-the-art 3D forest mapping technology-light detection and ranging (LiDAR). Fortunately, botanists have deduced the large structural diversity of tree forms into only a limited number of tree architecture models, which can present a-priori knowledge about tree structure, growth, and other attributes for different species. This study attempted to recruit Hallé architecture models (HAMs) into LiDAR mapping to investigate tree growth habits in structure. First, following the HAM-characterized tree structure organization rules, we run the kernel procedure of tree species classification based on the LiDAR-collected point clouds using a support vector machine classifier in the leave-one-out-for-cross-validation mode. Then, the HAM corresponding to each of the classified tree species was identified based on expert knowledge, assisted by the comparison of the LiDAR-derived feature parameters. Next, the tree growth habits in structure for each of the tree species were derived from the determined HAM. In the case of four tree species growing in the boreal environment, the tests indicated that the classification accuracy reached 85.0%, and their growth habits could be derived by qualitative and quantitative means. Overall, the strategy of recruiting conventional HAMs into LiDAR mapping for investigating tree growth habits in structure was validated, thereby paving a new way for efficiently reflecting tree growth habits and projecting forest structure dynamics.

Recruiting Conventional Tree Architecture Models into State-of-the-Art LiDAR Mapping for Investigating Tree Growth Habits in Structure

PubMed Central

Lin, Yi; Jiang, Miao; Pellikka, Petri; Heiskanen, Janne

2018-01-01

Mensuration of tree growth habits is of considerable importance for understanding forest ecosystem processes and forest biophysical responses to climate changes. However, the complexity of tree crown morphology that is typically formed after many years of growth tends to render it a non-trivial task, even for the state-of-the-art 3D forest mapping technology—light detection and ranging (LiDAR). Fortunately, botanists have deduced the large structural diversity of tree forms into only a limited number of tree architecture models, which can present a-priori knowledge about tree structure, growth, and other attributes for different species. This study attempted to recruit Hallé architecture models (HAMs) into LiDAR mapping to investigate tree growth habits in structure. First, following the HAM-characterized tree structure organization rules, we run the kernel procedure of tree species classification based on the LiDAR-collected point clouds using a support vector machine classifier in the leave-one-out-for-cross-validation mode. Then, the HAM corresponding to each of the classified tree species was identified based on expert knowledge, assisted by the comparison of the LiDAR-derived feature parameters. Next, the tree growth habits in structure for each of the tree species were derived from the determined HAM. In the case of four tree species growing in the boreal environment, the tests indicated that the classification accuracy reached 85.0%, and their growth habits could be derived by qualitative and quantitative means. Overall, the strategy of recruiting conventional HAMs into LiDAR mapping for investigating tree growth habits in structure was validated, thereby paving a new way for efficiently reflecting tree growth habits and projecting forest structure dynamics. PMID:29515616

Dynamic Analysis of Recalescence Process and Interface Growth of Eutectic Fe82B17Si1 Alloy

NASA Astrophysics Data System (ADS)

Fan, Y.; Liu, A. M.; Chen, Z.; Li, P. Z.; Zhang, C. H.

2018-03-01

By employing the glass fluxing technique in combination with cyclical superheating, the microstructural evolution of the undercooled Fe82B17Si1 alloy in the obtained undercooling range was studied. With increase in undercooling, a transition of cooling curves was detected from one recalescence to two recalescences, followed by one recalescence. The two types of cooling curves were fitted by the break equation and the Johnson-Mehl-Avrami-Kolmogorov model. Based on the cooling curves at different undercoolings, the recalescence rate was calculated by the multi-logistic growth model and the Boettinger-Coriel-Trivedi model. Both the recalescence features and the interface growth kinetics of the eutectic Fe82B17Si1 alloy were explored. The fitting results that were obtained using TEM (SAED), SEM and XRD were consistent with the changing rule of microstructures. Finally, the relationship between the microstructure and hardness was also investigated.

Joint Segmentation and Deformable Registration of Brain Scans Guided by a Tumor Growth Model

PubMed Central

Gooya, Ali; Pohl, Kilian M.; Bilello, Michel; Biros, George; Davatzikos, Christos

2011-01-01

This paper presents an approach for joint segmentation and deformable registration of brain scans of glioma patients to a normal atlas. The proposed method is based on the Expectation Maximization (EM) algorithm that incorporates a glioma growth model for atlas seeding, a process which modifies the normal atlas into one with a tumor and edema. The modified atlas is registered into the patient space and utilized for the posterior probability estimation of various tissue labels. EM iteratively refines the estimates of the registration parameters, the posterior probabilities of tissue labels and the tumor growth model parameters. We have applied this approach to 10 glioma scans acquired with four Magnetic Resonance (MR) modalities (T1, T1-CE, T2 and FLAIR ) and validated the result by comparing them to manual segmentations by clinical experts. The resulting segmentations look promising and quantitatively match well with the expert provided ground truth. PMID:21995070

Joint segmentation and deformable registration of brain scans guided by a tumor growth model.

PubMed

Gooya, Ali; Pohl, Kilian M; Bilello, Michel; Biros, George; Davatzikos, Christos

2011-01-01

This paper presents an approach for joint segmentation and deformable registration of brain scans of glioma patients to a normal atlas. The proposed method is based on the Expectation Maximization (EM) algorithm that incorporates a glioma growth model for atlas seeding, a process which modifies the normal atlas into one with a tumor and edema. The modified atlas is registered into the patient space and utilized for the posterior probability estimation of various tissue labels. EM iteratively refines the estimates of the registration parameters, the posterior probabilities of tissue labels and the tumor growth model parameters. We have applied this approach to 10 glioma scans acquired with four Magnetic Resonance (MR) modalities (T1, T1-CE, T2 and FLAIR) and validated the result by comparing them to manual segmentations by clinical experts. The resulting segmentations look promising and quantitatively match well with the expert provided ground truth.

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.

Application of remote sensing in crop growth simulation and an ensembles approach to reduce model uncertainties

NASA Astrophysics Data System (ADS)

Setiyono, T. D.; Nelson, A.; Ravis, J.; Maunahan, A.; Villano, L.; Li, T.; Bouman, B.

2012-12-01

A semi-empirical model derived from the water-cloud model was used to convert synthetic- aperture radar (SAR) backscattering data into LAI. The SAR-based LAI at early rice growth stages were in a close agreement (90%) with LAI derived from MODIS data for the same study location in Nueva Ecija, Philippines. ORYZA2000 simulated rice yield of 4.5 Mg ha-1 for the 2008 wet season in Nueva Ejica, Philippines when using LAI inputs derived from SAR data, which is closer to the observed yield of 3.9 Mg ha-1, whereas simulated yield without SAR-derived LAI inputs was 5.4 Mg ha-1. The dynamic water and nitrogen balances were accounted in these simulations based on site-specific soil properties and actual fertilizer N and water management. The use of remote sensing data was promising for model application to approximate actual growth conditions and to compensate for limitations in the model due to relevant underlining processes absent in model formulations such as detailed tillering, leaf shading effect, etc., and also limiting factors not accounted in the model such as biotic factors and abiotic factors other than water and N shortages. This study also demonstrated the use an ensembles approach for provincial level rice yield estimation in the Philippines. Such ensembles approach involved statistical classifications of agronomic management settings into 25% percentile, median, and 75% levels followed by generation of factorial combinations. For irrigated lowland system, 4 factors were considered that include transplanting date, plant density, fertilizer N rate, and amount of irrigation water. For rainfed lowland system, there were 3 agronomic management factors (transplanting date, plant density, fertilizer N) and 1 soil parameter (depth of ground water table). These 4 management/soil factors and 3 statistical levels resulted in 81 total factorial combinations representing simulation scenarios for each area of interest (province in the Philippines) and water environments (irrigated vs. rainfed). Finally a normal distribution was assumed and applied to the simulations outputs. This ensembles approach provided an efficient and yet effective method of aggregating point-based crop model results into a larger spatial level of interest. Lack of access to accurate model parameters (e.g. depth of ground water table) could be solved with this approach. The use of process-based crop growth model was critical because the ultimate aim of this study was not just to establish a reliable rice yield estimation system but also to allow yield estimation outputs explainable by the underlining agronomic practices such as transplanting date, fertilizer N application, and water management.

Large-cell Monte Carlo renormalization of irreversible growth processes

NASA Technical Reports Server (NTRS)

Nakanishi, H.; Family, F.

1985-01-01

Monte Carlo sampling is applied to a recently formulated direct-cell renormalization method for irreversible, disorderly growth processes. Large-cell Monte Carlo renormalization is carried out for various nonequilibrium problems based on the formulation dealing with relative probabilities. Specifically, the method is demonstrated by application to the 'true' self-avoiding walk and the Eden model of growing animals for d = 2, 3, and 4 and to the invasion percolation problem for d = 2 and 3. The results are asymptotically in agreement with expectations; however, unexpected complications arise, suggesting the possibility of crossovers, and in any case, demonstrating the danger of using small cells alone, because of the very slow convergence as the cell size b is extrapolated to infinity. The difficulty of applying the present method to the diffusion-limited-aggregation model, is commented on.

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…

Repeal of the Sustainable Growth Rate: an overview for surgeons.

PubMed

Sangji, Naveen F

2014-10-01

The Medicare sustainable growth rate (SGR) formula is used to control Medicare spending on physician services. Under the current SGR formula, physicians face an almost 24% cut to the Medicare fee schedule on April 1, 2015. The US House Way & Means and Energy & Commerce Committees and the Senate Finance Committee released jointly proposed legislation to permanently repeal the SGR, and transition Medicare physician payment to a value-based payment method. This review summarizes the key components of the proposed legislation, and discusses some of the political challenges ahead. House Committees on Energy & Commerce and Ways & Means, and the Senate Committee on Finance staff write-ups. Physician Medicare reimbursement will move from a volume-based model to a value-based model over the next decade. Surgeons should remain engaged with the political process to ensure repeal of the SGR. Copyright © 2014 Elsevier Inc. All rights reserved.

Windows(Registered Trademark)-Based Software Models Cyclic Oxidation Behavior

NASA Technical Reports Server (NTRS)

Smialek, J. L.; Auping, J. V.

2004-01-01

Oxidation of high-temperature aerospace materials is a universal issue for combustion-path components in turbine or rocket engines. In addition to the question of the consumption of material due to growth of protective scale at use temperatures, there is also the question of cyclic effects and spallation of scale on cooldown. The spallation results in the removal of part of the protective oxide in a discontinuous step and thereby opens the way for more rapid oxidation upon reheating. In experiments, cyclic oxidation behavior is most commonly characterized by measuring changes in weight during extended time intervals that include hundreds or thousands of heating and cooling cycles. Weight gains occurring during isothermal scale-growth processes have been well characterized as being parabolic or nearly parabolic functions of time because diffusion controls reaction rates. In contrast, the net weight change in cyclic oxidation is the sum of the effects of the growth and spallation of scale. Typically, the net weight gain in cyclic oxidation is determined only empirically (that is, by measurement), with no unique or straightforward mathematical connection to either the rate of growth or the amount of metal consumed. Thus, there is a need for mathematical modeling to infer spallation mechanisms. COSP is a computer program that models the growth and spallation processes of cyclic oxidation on the basis of a few elementary assumptions that were discussed in COSP: A Computer Model of Cyclic Oxidation, Oxidation of Metals, vol. 36, numbers 1 and 2, 1991, pages 81-112. Inputs to the model include the selection of an oxidation-growth law and a spalling geometry, plus oxide-phase, growth-rate, cycle-duration, and spall-constant parameters. (The spalling fraction is often shown to be a constant factor times the existing amount of scale.) The output of COSP includes the net change in weight, the amounts of retained and spalled oxide, the total amounts of oxygen and metal consumed, and the terminal rates of weight loss and metal consumption.

HYDRAULIC REDISTRIBUTION OF SOIL WATER IN TWO OLD-GROWTH CONIFEROUS FORESTS: QUANTIFYING PATTERNS AND CONTROLS

EPA Science Inventory

Although hydraulic redistribution of soil water (HR) by roots is a widespread phenomenon, the processes governing spatial and temporal patterns of HR are not well understood. We incorporated soil/plant biophysical properties into a simple model based on Darcy's law to predict sea...

Non-isothermal crystallization kinetics of eucalyptus lignosulfonate/polyvinyl alcohol composite.

PubMed

Ye, De-Zhan; Zhang, Xi; Gu, Shaojin; Zhou, Yingshan; Xu, Weilin

2017-04-01

The nonisothermal crystallinization kinetic was performed on Polyvinyl alcohol (PVA) mixed with eucalyptus lignosulfonate calcuim (HLS) as the biobased thermal stabilizer, which was systematically analyzed based on Jeziorny model, Ozawa equation and the Mo method. The results indicated that the entire crystallization process took place through two main stages involving the primary and secondary crystallization processes. The Mo method described nonisothermal crystallization behavior well. Based on the results of the half time for completing crystallization, k c value in Jeziorny model, F(T) value in Mo method and crystallization activation energy, it was concluded that low loading of HLS accelerated PVA crystallization process, however, the growth rate of PVA crystallization was impeded at high content of HLS. Copyright © 2017 Elsevier B.V. All rights reserved.

Simulating carbon stocks and fluxes of an African tropical montane forest with an individual-based forest model.

PubMed

Fischer, Rico; Ensslin, Andreas; Rutten, Gemma; Fischer, Markus; Schellenberger Costa, David; Kleyer, Michael; Hemp, Andreas; Paulick, Sebastian; Huth, Andreas

2015-01-01

Tropical forests are carbon-dense and highly productive ecosystems. Consequently, they play an important role in the global carbon cycle. In the present study we used an individual-based forest model (FORMIND) to analyze the carbon balances of a tropical forest. The main processes of this model are tree growth, mortality, regeneration, and competition. Model parameters were calibrated using forest inventory data from a tropical forest at Mt. Kilimanjaro. The simulation results showed that the model successfully reproduces important characteristics of tropical forests (aboveground biomass, stem size distribution and leaf area index). The estimated aboveground biomass (385 t/ha) is comparable to biomass values in the Amazon and other tropical forests in Africa. The simulated forest reveals a gross primary production of 24 tcha(-1) yr(-1). Modeling above- and belowground carbon stocks, we analyzed the carbon balance of the investigated tropical forest. The simulated carbon balance of this old-growth forest is zero on average. This study provides an example of how forest models can be used in combination with forest inventory data to investigate forest structure and local carbon balances.

Transition Models for Engineering Calculations

NASA Technical Reports Server (NTRS)

Fraser, C. J.

2007-01-01

While future theoretical and conceptual developments may promote a better understanding of the physical processes involved in the latter stages of boundary layer transition, the designers of rotodynamic machinery and other fluid dynamic devices need effective transition models now. This presentation will therefore center around the development of of some transition models which have been developed as design aids to improve the prediction codes used in the performance evaluation of gas turbine blading. All models are based on Narasimba's concentrated breakdown and spot growth.

Mathematical Modeling of the Dynamics of Shoot-Root Interactions and Resource Partitioning in Plant Growth.

PubMed

Feller, Chrystel; Favre, Patrick; Janka, Ales; Zeeman, Samuel C; Gabriel, Jean-Pierre; Reinhardt, Didier

2015-01-01

Plants are highly plastic in their potential to adapt to changing environmental conditions. For example, they can selectively promote the relative growth of the root and the shoot in response to limiting supply of mineral nutrients and light, respectively, a phenomenon that is referred to as balanced growth or functional equilibrium. To gain insight into the regulatory network that controls this phenomenon, we took a systems biology approach that combines experimental work with mathematical modeling. We developed a mathematical model representing the activities of the root (nutrient and water uptake) and the shoot (photosynthesis), and their interactions through the exchange of the substrates sugar and phosphate (Pi). The model has been calibrated and validated with two independent experimental data sets obtained with Petunia hybrida. It involves a realistic environment with a day-and-night cycle, which necessitated the introduction of a transitory carbohydrate storage pool and an endogenous clock for coordination of metabolism with the environment. Our main goal was to grasp the dynamic adaptation of shoot:root ratio as a result of changes in light and Pi supply. The results of our study are in agreement with balanced growth hypothesis, suggesting that plants maintain a functional equilibrium between shoot and root activity based on differential growth of these two compartments. Furthermore, our results indicate that resource partitioning can be understood as the emergent property of many local physiological processes in the shoot and the root without explicit partitioning functions. Based on its encouraging predictive power, the model will be further developed as a tool to analyze resource partitioning in shoot and root crops.

Modelling growth of Escherichia coli O157:H7 in fresh-cut lettuce submitted to commercial process conditions: chlorine washing and modified atmosphere packaging.

PubMed

Posada-Izquierdo, Guiomar D; Pérez-Rodríguez, Fernando; López-Gálvez, Francisco; Allende, Ana; Selma, María V; Gil, María I; Zurera, Gonzalo

2013-04-01

Fresh-cut iceberg lettuce inoculated with Escherichia coli O157:H7 was submitted to chlorine washing (150 mg/mL) and modified atmosphere packaging on laboratory scale. Populations of E. coli O157:H7 were assessed in fresh-cut lettuce stored at 4, 8, 13 and 16 °C using 6-8 replicates in each analysis point in order to capture experimental variability. The pathogen was able to grow at temperatures ≥8 °C, although at low temperatures, growth data presented a high variability between replicates. Indeed, at 8 °C after 15 days, some replicates did not show growth while other replicates did present an increase. A growth primary model was fitted to the raw growth data to estimate lag time and maximum growth rate. The prediction and confidence bands for the fitted growth models were estimated based on Monte-Carlo method. The estimated maximum growth rates (log cfu/day) corresponded to 0.14 (95% CI: 0.06-0.31), 0.55 (95% CI: 0.17-1.20) and 1.43 (95% CI: 0.82-2.15) for 8, 13 and 16 °C, respectively. A square-root secondary model was satisfactorily derived from the estimated growth rates (R(2) > 0.80; Bf = 0.97; Af = 1.46). Predictive models and data obtained in this study are intended to improve quantitative risk assessment studies for E. coli O157:H7 in leafy green products. Copyright © 2012. Published by Elsevier Ltd.

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.

Elastic force restricts growth of the murine utricle

PubMed Central

Gnedeva, Ksenia; Jacobo, Adrian; Salvi, Joshua D; Petelski, Aleksandra A; Hudspeth, A J

2017-01-01

Dysfunctions of hearing and balance are often irreversible in mammals owing to the inability of cells in the inner ear to proliferate and replace lost sensory receptors. To determine the molecular basis of this deficiency we have investigated the dynamics of growth and cellular proliferation in a murine vestibular organ, the utricle. Based on this analysis, we have created a theoretical model that captures the key features of the organ’s morphogenesis. Our experimental data and model demonstrate that an elastic force opposes growth of the utricular sensory epithelium during development, confines cellular proliferation to the organ’s periphery, and eventually arrests its growth. We find that an increase in cellular density and the subsequent degradation of the transcriptional cofactor Yap underlie this process. A reduction in mechanical constraints results in accumulation and nuclear translocation of Yap, which triggers proliferation and restores the utricle’s growth; interfering with Yap’s activity reverses this effect. DOI: http://dx.doi.org/10.7554/eLife.25681.001 PMID:28742024

Effects of soil freezing and thawing on vegetation carbon density in Siberia: A modeling analysis with the Lund-Potsdam-Jena Dynamic Global Vegetation Model (LPJ-DGVM)

NASA Astrophysics Data System (ADS)

Beer, C.; Lucht, W.; Gerten, D.; Thonicke, K.; Schmullius, C.

2007-03-01

The current latitudinal gradient in biomass suggests a climate-driven limitation of biomass in high latitudes. Understanding of the underlying processes, and quantification of their relative importance, is required to assess the potential carbon uptake of the biosphere in response to anticipated warming and related changes in tree growth and forest extent in these regions. We analyze the hydrological effects of thawing and freezing of soil on vegetation carbon density (VCD) in permafrost-dominated regions of Siberia using a process-based biogeochemistry-biogeography model, the Lund-Potsdam-Jena Dynamic Global Vegetation Model (LPJ-DGVM). The analysis is based on spatially explicit simulations of coupled daily thaw depth, site hydrology, vegetation distribution, and carbon fluxes influencing VCD subject to climate, soil texture, and atmospheric CO2 concentration. LPJ represents the observed high spring peak of runoff of large Arctic rivers, and simulates a realistic fire return interval of 100 to 200 years in Siberia. The simulated VCD changeover from taiga to tundra is comparable to inventory-based information. Without the consideration of freeze-thaw processes VCD would be overestimated by a factor of 2 in southern taiga to a factor of 5 in northern forest tundra, mainly because available soil water would be overestimated with major effects on fire occurrence and net primary productivity. This suggests that forest growth in high latitudes is not only limited by temperature, radiation, and nutrient availability but also by the availability of liquid soil water.

Measuring Leaf Area in Soy Plants by HSI Color Model Filtering and Mathematical Morphology

NASA Astrophysics Data System (ADS)

Benalcázar, M.; Padín, J.; Brun, M.; Pastore, J.; Ballarin, V.; Peirone, L.; Pereyra, G.

2011-12-01

There has been lately a significant progress in automating tasks for the agricultural sector. One of the advances is the development of robots, based on computer vision, applied to care and management of soy crops. In this task, digital image processing plays an important role, but must solve some important problems, like the ones associated to the variations in lighting conditions during image acquisition. Such variations influence directly on the brightness level of the images to be processed. In this paper we propose an algorithm to segment and measure automatically the leaf area of soy plants. This information is used by the specialists to evaluate and compare the growth of different soy genotypes. This algorithm, based on color filtering using the HSI model, detects green objects from the image background. The segmentation of leaves (foliage) was made applying Mathematical Morphology. The foliage area was estimated counting the pixels that belong to the segmented leaves. From several experiments, consisting in applying the algorithm to measure the foliage of about fifty plants of various genotypes of soy, at different growth stages, we obtained successful results, despite the high brightness variations and shadows in the processed images.

Short term storage stability at room temperature of two different platelet-rich plasma preparations from equine donors and potential impact on growth factor concentrations.

PubMed

Hauschild, Gregor; Geburek, Florian; Gosheger, Georg; Eveslage, Maria; Serrano, Daniela; Streitbürger, Arne; Johannlükens, Sara; Menzel, Dirk; Mischke, Reinhard

2017-01-05

The increasing interest in platelet-rich plasma (PRP) based therapies is as yet accompanied by inconsistent information regarding nearly all aspects of handling and application. Among these storage stability of processed platelet-rich products may be the basis for a more flexible application mode. The objective of this study was (1) to estimate the storage stability of growth factors platelet derived growth factor BB (PDGF-BB) and transforming growth factor ß1 (TGF-ß1) in both, a single-step softspin centrifugation-based pure-PRP (P-PRP, ACP®), and a gravity filtration system-based leukocyte-rich-PRP (L-PRP, E-PET), over a six hours time span after preparation at room temperature and (2) to identify possible factors influencing these growth factor concentrations in an equine model. Growth factor concentrations remained stable over the entire investigation period in L-PRP as well as P-PRP preparations revealing a mean of 3569 pg/ml PDGF-BB for E-PET and means of 1276 pg/ml PDGF-BB and 5086 pg/ml TGF-ß1 for ACP®. Pearson correlations yielded no significant impact of whole blood platelet (PLT), white blood cell (WBC) and red blood cell (RBC) counts on resulting cytokine values. In case of ACP® no significant dependencies between PLT, WBC and RBC counts of the processed platelet-rich product and resulting cytokine content occurred with exception of TGF-ß1 concentrations showing a strong correlation with the WBC content. PDGF-BB content of E-PET preparations showed a strong positive correlation with PLT and a strong negative with WBC of these preparations but not with RBC. L-PRP ad modum E-PET and P-PRP ad modum ACP® are applicable over at least a six hours time span at room temperature without loss of growth factor content. Based on the results of this study factors influencing the resulting growth factor concentrations still remain questionable. Additional studies implicating a further standardization of preparation protocols are necessary to identify consistent impact on cytokine content after PRP processing.

Mechanistic Understanding of Microbial Plugging for Improved Sweep Efficiency

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

Steven Bryant; Larry Britton

2008-09-30

Microbial plugging has been proposed as an effective low cost method of permeability reduction. Yet there is a dearth of information on the fundamental processes of microbial growth in porous media, and there are no suitable data to model the process of microbial plugging as it relates to sweep efficiency. To optimize the field implementation, better mechanistic and volumetric understanding of biofilm growth within a porous medium is needed. In particular, the engineering design hinges upon a quantitative relationship between amount of nutrient consumption, amount of growth, and degree of permeability reduction. In this project experiments were conducted to obtainmore » new data to elucidate this relationship. Experiments in heterogeneous (layered) beadpacks showed that microbes could grow preferentially in the high permeability layer. Ultimately this caused flow to be equally divided between high and low permeability layers, precisely the behavior needed for MEOR. Remarkably, classical models of microbial nutrient uptake in batch experiments do not explain the nutrient consumption by the same microbes in flow experiments. We propose a simple extension of classical kinetics to account for the self-limiting consumption of nutrient observed in our experiments, and we outline a modeling approach based on architecture and behavior of biofilms. Such a model would account for the changing trend of nutrient consumption by bacteria with the increasing biomass and the onset of biofilm formation. However no existing model can explain the microbial preference for growth in high permeability regions, nor is there any obvious extension of the model for this observation. An attractive conjecture is that quorum sensing is involved in the heterogeneous bead packs.« less

Analysis of algae growth mechanism and water bloom prediction under the effect of multi-affecting factor.

PubMed

Wang, Li; Wang, Xiaoyi; Jin, Xuebo; Xu, Jiping; Zhang, Huiyan; Yu, Jiabin; Sun, Qian; Gao, Chong; Wang, Lingbin

2017-03-01

The formation process of algae is described inaccurately and water blooms are predicted with a low precision by current methods. In this paper, chemical mechanism of algae growth is analyzed, and a correlation analysis of chlorophyll-a and algal density is conducted by chemical measurement. Taking into account the influence of multi-factors on algae growth and water blooms, the comprehensive prediction method combined with multivariate time series and intelligent model is put forward in this paper. Firstly, through the process of photosynthesis, the main factors that affect the reproduction of the algae are analyzed. A compensation prediction method of multivariate time series analysis based on neural network and Support Vector Machine has been put forward which is combined with Kernel Principal Component Analysis to deal with dimension reduction of the influence factors of blooms. Then, Genetic Algorithm is applied to improve the generalization ability of the BP network and Least Squares Support Vector Machine. Experimental results show that this method could better compensate the prediction model of multivariate time series analysis which is an effective way to improve the description accuracy of algae growth and prediction precision of water blooms.

Application of a Snow Growth Model to Radar Remote Sensing

NASA Astrophysics Data System (ADS)

Erfani, E.; Mitchell, D. L.

2014-12-01

Microphysical growth processes of diffusion, aggregation and riming are incorporated analytically in a steady-state snow growth model (SGM) to solve the zeroth- and second- moment conservation equations with respect to mass. The SGM is initiated by radar reflectivity (Zw), supersaturation, temperature, and a vertical profile of the liquid water content (LWC), and it uses a gamma size distribution (SD) to predict the vertical evolution of size spectra. Aggregation seems to play an important role in the evolution of snowfall rates and the snowfall rates produced by aggregation, diffusion and riming are considerably greater than those produced by diffusion and riming alone, demonstrating the strong interaction between aggregation and riming. The impact of ice particle shape on particle growth rates and fall speeds is represented in the SGM in terms of ice particle mass-dimension (m-D) power laws (m = αDβ). These growth rates are qualitatively consistent with empirical growth rates, with slower (faster) growth rates predicted for higher (lower) β values. In most models, β is treated constant for a given ice particle habit, but it is well known that β is larger for the smaller crystals. Our recent work quantitatively calculates β and α for cirrus clouds as a function of D where the m-D expression is a second-order polynomial in log-log space. By adapting this method to the SGM, the ice particle growth rates and fall speeds are predicted more accurately. Moreover, the size spectra predicted by the SGM are in good agreement with those from aircraft measurements during Lagrangian spiral descents through frontal clouds, indicating the successful modeling of microphysical processes. Since the lowest Zw over complex topography is often significantly above cloud base, the precipitation is often underestimated by radar quantitative precipitation estimates (QPE). Our SGM is capable of being initialized with Zw at the lowest reliable radar echo and consequently improves QPE at ground level.

Numerical simulation of biofilm growth in flow channels using a cellular automaton approach coupled with a macro flow computation.

PubMed

Yamamoto, Takehiro; Ueda, Shuya

2013-01-01

Biofilm is a slime-like complex aggregate of microorganisms and their products, extracellular polymer substances, that grows on a solid surface. The growth phenomenon of biofilm is relevant to the corrosion and clogging of water pipes, the chemical processes in a bioreactor, and bioremediation. In these phenomena, the behavior of the biofilm under flow has an important role. Therefore, controlling the biofilm behavior in each process is important. To provide a computational tool for analyzing biofilm growth, the present study proposes a computational model for the simulation of biofilm growth in flows. This model accounts for the growth, decay, detachment and adhesion of biofilms. The proposed model couples the computation of the surrounding fluid flow, using the finite volume method, with the simulation of biofilm growth, using the cellular automaton approach, a relatively low-computational-cost method. Furthermore, a stochastic approach for considering the adhesion process is proposed. Numerical simulations for the biofilm growth on a planar wall and that in an L-shaped rectangular channel were carried out. A variety of biofilm structures were observed depending on the strength of the flow. Moreover, the importance of the detachment and adhesion processes was confirmed.

The Role of Convection and Growth Competition in Phase Selection in Microgravity: Controlled Convection in the Containerless Processing of Steel Alloys

NASA Technical Reports Server (NTRS)

Matson, D. M.; Loser, W.; Rogers, J. R.; Flemings, M. C.

2001-01-01

Containerless processing using electromagnetic levitation (EML) is a powerful technique in the investigation of reactive molten metal systems. On ground, the power required to overcome the weight of the sample is sufficient to cause significant heating and induce substantial melt convection. In microgravity, the heating and positioning fields may be decoupled and the field strength may be varied to achieve the desired level of convection within the limits set by the geometry of the levitation coil and the sample size. From high-speed digital images of the double recalescence behavior of Fe-Cr-Ni alloys in ground-based testing and in reduced-gravity aboard the NASA KC-135 parabolic aircraft, we have shown that phase selection can be predicted based on a growth competition model. An important parameter in this model is the delay time between primary nucleation and subsequent nucleation of the stable solid within the liquid/metastable solid array. This delay time is a strong function of composition and a weak function of the undercooling of the melt below the metastable liquidus. From the results obtained during the first Microgravity Sciences Laboratory (MSL-1) mission, we also know that convection may significantly influence the delay time, especially at low undercoolings. Currently, it is unclear what mechanism controls the formation of a heterogeneous site that allows nucleation of the austenitic phase on the pre-existing ferrite skeleton. By examining the behavior of the delay time under different convective conditions, we hypothesize that we can differentiate between several of these mechanisms to gain an understanding of how to control microstructural. evolution. We will anchor these predictions by examining samples quenched at different times following primary recalescence in microgravity. A second important parameter in the growth competition model is the identification of the growth rate of the stable phase into the semi-solid array that formed during primary recalescence. Current dendritic growth theory is inadequate in predicting solidification behavior under these conditions as metallographic analyses show that stable phase growth proceeds along the interface between the metastable solid and residual liquid. Since growth velocity is independent of the initial undercooling relative to the metastable liquidus, we hypothesize that purely thermal effects can be separated from other important growth model parameters by careful selection of the liquid composition in a ternary system.

Otolith reading and multi-model inference for improved estimation of age and growth in the gilthead seabream Sparus aurata (L.)

NASA Astrophysics Data System (ADS)

Mercier, Lény; Panfili, Jacques; Paillon, Christelle; N'diaye, Awa; Mouillot, David; Darnaude, Audrey M.

2011-05-01

Accurate knowledge of fish age and growth is crucial for species conservation and management of exploited marine stocks. In exploited species, age estimation based on otolith reading is routinely used for building growth curves that are used to implement fishery management models. However, the universal fit of the von Bertalanffy growth function (VBGF) on data from commercial landings can lead to uncertainty in growth parameter inference, preventing accurate comparison of growth-based history traits between fish populations. In the present paper, we used a comprehensive annual sample of wild gilthead seabream ( Sparus aurata L.) in the Gulf of Lions (France, NW Mediterranean) to test a methodology improving growth modelling for exploited fish populations. After validating the timing for otolith annual increment formation for all life stages, a comprehensive set of growth models (including VBGF) were fitted to the obtained age-length data, used as a whole or sub-divided between group 0 individuals and those coming from commercial landings (ages 1-6). Comparisons in growth model accuracy based on Akaike Information Criterion allowed assessment of the best model for each dataset and, when no model correctly fitted the data, a multi-model inference (MMI) based on model averaging was carried out. The results provided evidence that growth parameters inferred with VBGF must be used with high caution. Hence, VBGF turned to be among the less accurate for growth prediction irrespective of the dataset and its fit to the whole population, the juvenile or the adult datasets provided different growth parameters. The best models for growth prediction were the Tanaka model, for group 0 juveniles, and the MMI, for the older fish, confirming that growth differs substantially between juveniles and adults. All asymptotic models failed to correctly describe the growth of adult S. aurata, probably because of the poor representation of old individuals in the dataset. Multi-model inference associated with separate analysis of juveniles and adult fish is then advised to obtain objective estimations of growth parameters when sampling cannot be corrected towards older fish.

Representation of Arctic mixed-phase clouds and the Wegener-Bergeron-Findeisen process in climate models: Perspectives from a cloud-resolving study

NASA Astrophysics Data System (ADS)

Fan, Jiwen; Ghan, Steven; Ovchinnikov, Mikhail; Liu, Xiaohong; Rasch, Philip J.; Korolev, Alexei

2011-01-01

Two types of Arctic mixed-phase clouds observed during the ISDAC and M-PACE field campaigns are simulated using a 3-dimensional cloud-resolving model (CRM) with size-resolved cloud microphysics. The modeled cloud properties agree reasonably well with aircraft measurements and surface-based retrievals. Cloud properties such as the probability density function (PDF) of vertical velocity (w), cloud liquid and ice, regimes of cloud particle growth, including the Wegener-Bergeron-Findeisen (WBF) process, and the relationships among properties/processes in mixed-phase clouds are examined to gain insights for improving their representation in General Circulation Models (GCMs). The PDF of the simulated w is well represented by a Gaussian function, validating, at least for arctic clouds, the subgrid treatment used in GCMs. The PDFs of liquid and ice water contents can be approximated by Gamma functions, and a Gaussian function can describe the total water distribution, but a fixed variance assumption should be avoided in both cases. The CRM results support the assumption frequently used in GCMs that mixed phase clouds maintain water vapor near liquid saturation. Thus, ice continues to grow throughout the stratiform cloud but the WBF process occurs in about 50% of cloud volume where liquid and ice co-exist, predominantly in downdrafts. In updrafts, liquid and ice particles grow simultaneously. The relationship between the ice depositional growth rate and cloud ice strongly depends on the capacitance of ice particles. The simplified size-independent capacitance of ice particles used in GCMs could lead to large deviations in ice depositional growth.

Dynamic predictive model for the growth of Salmonella spp. in liquid whole egg.

PubMed

Singh, Aikansh; Korasapati, Nageswara R; Juneja, Vijay K; Subbiah, Jeyamkondan; Froning, Glenn; Thippareddi, Harshavardhan

2011-04-01

A dynamic model for the growth of Salmonella spp. in liquid whole egg (LWE) (approximately pH 7.8) under continuously varying temperature was developed. The model was validated using 2 (5 to 15 °C; 600 h and 10 to 40 °C; 52 h) sinusoidal, continuously varying temperature profiles. LWE adjusted to pH 7.8 was inoculated with approximately 2.5-3.0 log CFU/mL of Salmonella spp., and the growth data at several isothermal conditions (5, 7, 10, 15, 20, 25, 30, 35, 37, 39, 41, 43, 45, and 47 °C) was collected. A primary model (Baranyi model) was fitted for each temperature growth data and corresponding maximum growth rates were estimated. Pseudo-R2 values were greater than 0.97 for primary models. Modified Ratkowsky model was used to fit the secondary model. The pseudo-R2 and root mean square error were 0.99 and 0.06 log CFU/mL, respectively, for the secondary model. A dynamic model for the prediction of Salmonella spp. growth under varying temperature conditions was developed using 4th-order Runge-Kutta method. The developed dynamic model was validated for 2 sinusoidal temperature profiles, 5 to 15 °C (for 600 h) and 10 to 40 °C (for 52 h) with corresponding root mean squared error values of 0.28 and 0.23 log CFU/mL, respectively, between predicted and observed Salmonella spp. populations. The developed dynamic model can be used to predict the growth of Salmonella spp. in LWE under varying temperature conditions.   Liquid egg and egg products are widely used in food processing and in restaurant operations. These products can be contaminated with Salmonella spp. during breaking and other unit operations during processing. The raw, liquid egg products are stored under refrigeration prior to pasteurization. However, process deviations can occur such as refrigeration failure, leading to temperature fluctuations above the required temperatures as specified in the critical limits within hazard analysis and critical control point plans for the operations. The processors are required to evaluate the potential growth of Salmonella spp. in such products before the product can be used, or further processed. Dynamic predictive models are excellent tools for regulators as well as the processing plant personnel to evaluate the microbiological safety of the product under such conditions.

Mathematics in Marine Botany: Examples of the Modelling Process. Part II: Continuous Models.

ERIC Educational Resources Information Center

Nyman, Melvin A.; Brown, Murray T.

1996-01-01

Describes some continuous models for growth of the seaweed Macrocystis pyrifera. Uses observed growth rates over several months to derive first-order differential equations as models for growth rates of individual fronds. The nature of the solutions is analyzed and comparison between these theoretical results and documented characteristics of…

Numerical prediction of mechanical properties of Pb-Sn solder alloys containing antimony, bismuth and or silver ternary trace elements

NASA Astrophysics Data System (ADS)

Gadag, Shiva P.; Patra, Susant

2000-12-01

Solder joint interconnects are mechanical means of structural support for bridging the various electronic components and providing electrical contacts and a thermal path for heat dissipation. The functionality of the electronic device often relies on the structural integrity of the solder. The dimensional stability of solder joints is numerically predicted based on their mechanical properties. Algorithms to model the kinetics of dissolution and subsequent growth of intermetallic from the complete knowledge of a single history of time-temperature-reflow profile, by considering equivalent isothermal time intervals, have been developed. The information for dissolution is derived during the heating cycle of reflow and for the growth process from cooling curve of reflow profile. A simple and quick analysis tool to derive tensile stress-strain maps as a function of the reflow temperature of solder and strain rate has been developed by numerical program. The tensile properties are used in modeling thermal strain, thermal fatigue and to predict the overall fatigue life of solder joints. The numerical analysis of the tensile properties as affected by their composition and rate of testing, has been compiled in this paper. A numerical model using constitutive equation has been developed to evaluate the interfacial fatigue crack growth rate. The model can assess the effect of cooling rate, which depends on the level of strain energy release rate. Increasing cooling rate from normalizing to water-quenching, enhanced the fatigue resistance to interfacial crack growth by up to 50% at low strain energy release rate. The increased cooling rates enhanced the fatigue crack growth resistance by surface roughening at the interface of solder joint. This paper highlights salient features of process modeling. Interfacial intermetallic microstructure is affected by cooling rate and thereby affects the mechanical properties.

Analysis of “Favorable Growth Element” Based on Rare Earth-aluminum Composite Mechanism of Compound Process

NASA Astrophysics Data System (ADS)

Hao, Baohong; Zeng, Qihui; Zhao, Jin

2018-01-01

Under the background that failure resulted in by high temperature once only aluminum oxide is used as the gasoline additive. This paper, with the purpose to solve this problem, is to synthesize AcAl oxide for gasoline additive. In order to get the rare-earth-aluminum oxide, first, a complex model of rare earth oxide based on theories about ion coordination is established. Then, by the complex model, the type of “compound growth unit” when rare earth elements join the hydrothermal conditions and the inclination that “diversification” might probably happen are deduced. Depending on the results got by complex model, this paper introduces the type of compound and its existence conditions of “Compound growth unit” owned by stable rare-earth-aluminum oxide. By adjusting the compositions of modifier, compound materials of rare earth-aluminum oxide used for gasoline additive is made. By XRD test, aperture test, adsorption test and desorption test, the theoretical deduction is proved to be right. From the experiment, it is concluded that: a dense environment is the pre-condition to form rare-earth-aluminum polymer, which is also an essential condition for the polymer to update to a favorable growth unit and produce mesoporous rare-earth-aluminum oxide with high activity.

The C23A system, an exmaple of quantitative control of plant growth associated with a data base

NASA Technical Reports Server (NTRS)

Andre, M.; Daguenet, A.; Massimino, D.; Gerbaud, A.

1986-01-01

The architecture of the C23A (Chambers de Culture Automatique en Atmosphere Artificielles) system for the controlled study of plant physiology is described. A modular plant growth chambers and associated instruments (I.R. CO2 analyser, Mass spectrometer and Chemical analyser); network of frontal processors controlling this apparatus; a central computer for the periodic control and the multiplex work of processors; and a network of terminal computers able to ask the data base for data processing and modeling are discussed. Examples of present results are given. A growth curve analysis study of CO2 and O2 gas exchanges of shoots and roots, and daily evolution of algal photosynthesis and of the pools of dissolved CO2 in sea water are discussed.

Simulation and modeling of whistler mode wave growth through cyclotron resonance with energetic electrons in the magnetosphere

NASA Astrophysics Data System (ADS)

Carlson, Curtis Ray

New models and simulations of wave growth experienced by electromagnetic waves propagating through the magnetosphere in the whistler mode are presented. The main emphasis is to simulate single frequency wave pulses, in the 2 to 6 kHz range, that have been injected into the magnetosphere, near L approximately 4. Simulations using a new transient model reproduce exponential wave growth and saturation coincident with a linearly increasing frequency versus time (up to 60 Hz/s). Unique methods for calculating the phased bunched currents, stimulated radiation, and radiation propagation are based upon test particle trajectories calculated by integrating nonlinear equations of motion generalized to allow the evolution of the frequency and wave number at each point in space. Results show the importance of the transient aspects in the wave growth process. The wave growth established as the wave propagates toward the equator is given a spatially advancing wave phase structure by the geomagnetic inhomogeneity. Through the feedback of this radiation upon other electrons, the conditions are set up which result in the linearly increasing output frequency with time. The transient simulations also show that features like growth rate and total growth are simply related to the various parameters, such as applied wave intensity, energetic electron flux, and energetic electron distribution.

Evolutionary model of the growth and size of firms

NASA Astrophysics Data System (ADS)

Kaldasch, Joachim

2012-07-01

The key idea of this model is that firms are the result of an evolutionary process. Based on demand and supply considerations the evolutionary model presented here derives explicitly Gibrat's law of proportionate effects as the result of the competition between products. Applying a preferential attachment mechanism for firms, the theory allows to establish the size distribution of products and firms. Also established are the growth rate and price distribution of consumer goods. Taking into account the characteristic property of human activities to occur in bursts, the model allows also an explanation of the size-variance relationship of the growth rate distribution of products and firms. Further the product life cycle, the learning (experience) curve and the market size in terms of the mean number of firms that can survive in a market are derived. The model also suggests the existence of an invariant of a market as the ratio of total profit to total revenue. The relationship between a neo-classic and an evolutionary view of a market is discussed. The comparison with empirical investigations suggests that the theory is able to describe the main stylized facts concerning the size and growth of firms.

Evolution of the potential distribution area of french mediterranean forests under global warming

NASA Astrophysics Data System (ADS)

Gaucherel, C.; Guiot, J.; Misson, L.

2008-02-01

This work aims at understanding future spatial and temporal distributions of tree species in the Mediterranean region of France under various climates. We focused on two different species (Pinus Halepensis and Quercus Ilex) and compared their growth under the IPCC-B2 climate scenario in order to quantify significant changes between present and future. The influence of environmental factors such as atmospheric CO2 increase and topography on the tree growth has also been quantified. We modeled species growths with the help of a process-based model (MAIDEN), previously calibrated over measured ecophysiological and dendrochronological series with a Bayesian scheme. The model was fed with the ARPEGE - MeteoFrance climate model, combined with an explicit increase in CO2 atmospheric concentration. The main output of the model gives the carbon allocation in boles and thus tree production. Our results show that the MAIDEN model is correctly able to simulate pine and oak production in space and time, after detailed calibration and validation stages. Yet, these simulations, mainly based on climate, are indicative and not predictive. The comparison of simulated growth at end of 20 and 21 centuries, show a shift of the pine production optimum from about 650 to 950 m due to 2.5°K temperature increase, while no optimum has been found for oak. With the direct effect of CO2 increase taken into account, both species show a significant increase in productivity (+26 and +43% for pine and oak, respectively) at the end of the 21 century. While both species have complementary growth mechanisms, they have a good chance to extend their spatial distribution and their elevation in the Alps during the 21 century under the IPCC-B2 climate scenario. This extension is mainly due to the CO2 fertilization effect.

Growth Control and Disease Mechanisms in Computational Embryogeny

NASA Technical Reports Server (NTRS)

Shapiro, Andrew A.; Yogev, Or; Antonsson, Erik K.

2008-01-01

This paper presents novel approach to applying growth control and diseases mechanisms in computational embryogeny. Our method, which mimics fundamental processes from biology, enables individuals to reach maturity in a controlled process through a stochastic environment. Three different mechanisms were implemented; disease mechanisms, gene suppression, and thermodynamic balancing. This approach was integrated as part of a structural evolutionary model. The model evolved continuum 3-D structures which support an external load. By using these mechanisms we were able to evolve individuals that reached a fixed size limit through the growth process. The growth process was an integral part of the complete development process. The size of the individuals was determined purely by the evolutionary process where different individuals matured to different sizes. Individuals which evolved with these characteristics have been found to be very robust for supporting a wide range of external loads.

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.

Multiscale Modeling of Angiogenesis and Predictive Capacity

NASA Astrophysics Data System (ADS)

Pillay, Samara; Byrne, Helen; Maini, Philip

Tumors induce the growth of new blood vessels from existing vasculature through angiogenesis. Using an agent-based approach, we model the behavior of individual endothelial cells during angiogenesis. We incorporate crowding effects through volume exclusion, motility of cells through biased random walks, and include birth and death-like processes. We use the transition probabilities associated with the discrete model and a discrete conservation equation for cell occupancy to determine collective cell behavior, in terms of partial differential equations (PDEs). We derive three PDE models incorporating single, multi-species and no volume exclusion. By fitting the parameters in our PDE models and other well-established continuum models to agent-based simulations during a specific time period, and then comparing the outputs from the PDE models and agent-based model at later times, we aim to determine how well the PDE models predict the future behavior of the agent-based model. We also determine whether predictions differ across PDE models and the significance of those differences. This may impact drug development strategies based on PDE models.

A first-principle model of 300 mm Czochralski single-crystal Si production process for predicting crystal radius and crystal growth rate

NASA Astrophysics Data System (ADS)

Zheng, Zhongchao; Seto, Tatsuru; Kim, Sanghong; Kano, Manabu; Fujiwara, Toshiyuki; Mizuta, Masahiko; Hasebe, Shinji

2018-06-01

The Czochralski (CZ) process is the dominant method for manufacturing large cylindrical single-crystal ingots for the electronics industry. Although many models and control methods for the CZ process have been proposed, they were only tested with small equipment and only a few industrial application were reported. In this research, we constructed a first-principle model for controlling industrial CZ processes that produce 300 mm single-crystal silicon ingots. The developed model, which consists of energy, mass balance, hydrodynamic, and geometrical equations, calculates the crystal radius and the crystal growth rate as output variables by using the heater input, the crystal pulling rate, and the crucible rise rate as input variables. To improve accuracy, we modeled the CZ process by considering factors such as changes in the positions of the crucible and the melt level. The model was validated with the operation data from an industrial 300 mm CZ process. We compared the calculated and actual values of the crystal radius and the crystal growth rate, and the results demonstrated that the developed model simulated the industrial process with high accuracy.

Earth surface modeling for education: How effective is it? Latest classroom tests with Web-based Interactive Landform Simulation Model - Grand Canyon (WILSIM-GC)

NASA Astrophysics Data System (ADS)

Luo, W.; Pelletier, J. D.; Smith, T.; Whalley, K.; Shelhamer, A.; Darling, A.; Ormand, C. J.; Duffin, K.; Hung, W. C.; Iverson, E. A. R.; Shernoff, D.; Zhai, X.; Chiang, J. L.; Lotter, N.

2016-12-01

The Web-based Interactive Landform Simulation Model - Grand Canyon (WILSIM-GC, http://serc.carleton.edu/landform/) is a simplified version of a physically-based model that simulates bedrock channel erosion, cliff retreat, and base level change. Students can observe the landform evolution in animation under different scenarios by changing parameter values. In addition, cross-sections and profiles at different time intervals can be displayed and saved for further quantitative analysis. Students were randomly assigned to a treatment group (using WILSIM-GC simulation) or a control group (using traditional paper-based material). Pre- and post-tests were administered to measure students' understanding of the concepts and processes related to Grand Canyon formation and evolution. Results from the ANOVA showed that for both groups there were statistically significant growth in scores from pre-test to post-test [F(1, 47) = 25.82, p < .001], but the growth in scores between the two groups was not statistically significant [F(1, 47) = 0.08, p =.774]. In semester 1, the WILSIM-GC group showed greater growth, while in semester 2, the paper-based group showed greater growth. Additionally, a significant time × group × gender × semester interaction effect was observed [F(1, 47) = 4.76, p =.034]. Here, in semester 1 female students were more strongly advantaged by the WILSIM-GC intervention than male students, while in semester 2, female students were less strongly advantaged than male students. The new results are consistent with our initial findings (Luo et al., 2016) and others reported in the literature, i.e., simulation approach is at least equally effective as traditional paper-based method in teaching students about landform evolution. Survey data indicate that students favor the simulation approach. Further study is needed to investigate the reasons for the difference by gender.

Aging, Maturation and Growth of Sauropodomorph Dinosaurs as Deduced from Growth Curves Using Long Bone Histological Data: An Assessment of Methodological Constraints and Solutions

PubMed Central

Griebeler, Eva Maria; Klein, Nicole; Sander, P. Martin

2013-01-01

Information on aging, maturation, and growth is important for understanding life histories of organisms. In extinct dinosaurs, such information can be derived from the histological growth record preserved in the mid-shaft cortex of long bones. Here, we construct growth models to estimate ages at death, ages at sexual maturity, ages at which individuals were fully-grown, and maximum growth rates from the growth record preserved in long bones of six sauropod dinosaur individuals (one indeterminate mamenchisaurid, two Apatosaurus sp., two indeterminate diplodocids, and one Camarasaurus sp.) and one basal sauropodomorph dinosaur individual (Plateosaurus engelhardti). Using these estimates, we establish allometries between body mass and each of these traits and compare these to extant taxa. Growth models considered for each dinosaur individual were the von Bertalanffy model, the Gompertz model, and the logistic model (LGM), all of which have inherently fixed inflection points, and the Chapman-Richards model in which the point is not fixed. We use the arithmetic mean of the age at the inflection point and of the age at which 90% of asymptotic mass is reached to assess respectively the age at sexual maturity or the age at onset of reproduction, because unambiguous indicators of maturity in Sauropodomorpha are lacking. According to an AIC-based model selection process, the LGM was the best model for our sauropodomorph sample. Allometries established are consistent with literature data on other Sauropodomorpha. All Sauropodomorpha reached full size within a time span similar to scaled-up modern mammalian megaherbivores and had similar maximum growth rates to scaled-up modern megaherbivores and ratites, but growth rates of Sauropodomorpha were lower than of an average mammal. Sauropodomorph ages at death probably were lower than that of average scaled-up ratites and megaherbivores. Sauropodomorpha were older at maturation than scaled-up ratites and average mammals, but younger than scaled-up megaherbivores. PMID:23840575

Aging, Maturation and Growth of Sauropodomorph Dinosaurs as Deduced from Growth Curves Using Long Bone Histological Data: An Assessment of Methodological Constraints and Solutions.

PubMed

Griebeler, Eva Maria; Klein, Nicole; Sander, P Martin

2013-01-01

Information on aging, maturation, and growth is important for understanding life histories of organisms. In extinct dinosaurs, such information can be derived from the histological growth record preserved in the mid-shaft cortex of long bones. Here, we construct growth models to estimate ages at death, ages at sexual maturity, ages at which individuals were fully-grown, and maximum growth rates from the growth record preserved in long bones of six sauropod dinosaur individuals (one indeterminate mamenchisaurid, two Apatosaurus sp., two indeterminate diplodocids, and one Camarasaurus sp.) and one basal sauropodomorph dinosaur individual (Plateosaurus engelhardti). Using these estimates, we establish allometries between body mass and each of these traits and compare these to extant taxa. Growth models considered for each dinosaur individual were the von Bertalanffy model, the Gompertz model, and the logistic model (LGM), all of which have inherently fixed inflection points, and the Chapman-Richards model in which the point is not fixed. We use the arithmetic mean of the age at the inflection point and of the age at which 90% of asymptotic mass is reached to assess respectively the age at sexual maturity or the age at onset of reproduction, because unambiguous indicators of maturity in Sauropodomorpha are lacking. According to an AIC-based model selection process, the LGM was the best model for our sauropodomorph sample. Allometries established are consistent with literature data on other Sauropodomorpha. All Sauropodomorpha reached full size within a time span similar to scaled-up modern mammalian megaherbivores and had similar maximum growth rates to scaled-up modern megaherbivores and ratites, but growth rates of Sauropodomorpha were lower than of an average mammal. Sauropodomorph ages at death probably were lower than that of average scaled-up ratites and megaherbivores. Sauropodomorpha were older at maturation than scaled-up ratites and average mammals, but younger than scaled-up megaherbivores.

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

PubMed Central

Wiechers, Dirk; Kahlen, Katrin; Stützel, Hartmut

2011-01-01

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

A novel in-line NIR spectroscopy application for the monitoring of tablet film coating in an industrial scale process.

PubMed

Möltgen, C-V; Puchert, T; Menezes, J C; Lochmann, D; Reich, G

2012-04-15

Film coating of tablets is a multivariate pharmaceutical unit operation. In this study an innovative in-line Fourier-Transform Near-Infrared Spectroscopy (FT-NIRS) application is described which enables real-time monitoring of a full industrial scale pan coating process of heart-shaped tablets. The tablets were coated with a thin hydroxypropyl methylcellulose (HPMC) film of up to approx. 28 μm on the tablet face as determined by SEM, corresponding to a weight gain of 2.26%. For a better understanding of the aqueous coating process the NIR probe was positioned inside the rotating tablet bed. Five full scale experimental runs have been performed to evaluate the impact of process variables such as pan rotation, exhaust air temperature, spray rate and pan load and elaborate robust and selective quantitative calibration models for the real-time determination of both coating growth and tablet moisture content. Principal Component (PC) score plots allowed each coating step, namely preheating, spraying and drying to be distinguished and the dominating factors and their spectral effects to be identified (e.g. temperature, moisture, coating growth, change of tablet bed density, and core/coat interactions). The distinct separation of HPMC coating growth and tablet moisture in different PCs enabled a real-time in-line monitoring of both attributes. A PLS calibration model based on Karl Fischer reference values allowed the tablet moisture trajectory to be determined throughout the entire coating process. A 1-latent variable iPLS weight gain calibration model with calibration samples from process stages dominated by the coating growth (i.e. ≥ 30% of the theoretically applied amount of coating) was sufficiently selective and accurate to predict the progress of the thin HPMC coating layer. At-line NIR Chemical Imaging (NIR-CI) in combination with PLS Discriminant Analysis (PLSDA) verified the HPMC coating growth and physical changes at the core/coat interface during the initial stages of the coating process. In addition, inter- and intra-tablet coating variability throughout the process could be assessed. These results clearly demonstrate that in-line NIRS and at-line NIR-CI can be applied as complimentary PAT tools to monitor a challenging pan coating process. Copyright © 2012 Elsevier B.V. All rights reserved.

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

PubMed Central

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

2014-01-01

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

A model framework to describe growth-linked biodegradation of trace-level pollutants in the presence of coincidental carbon substrates and microbes.

PubMed

Liu, Li; Helbling, Damian E; Kohler, Hans-Peter E; Smets, Barth F

2014-11-18

Pollutants such as pesticides and their degradation products occur ubiquitously in natural aquatic environments at trace concentrations (μg L(-1) and lower). Microbial biodegradation processes have long been known to contribute to the attenuation of pesticides in contaminated environments. However, challenges remain in developing engineered remediation strategies for pesticide-contaminated environments because the fundamental processes that regulate growth-linked biodegradation of pesticides in natural environments remain poorly understood. In this research, we developed a model framework to describe growth-linked biodegradation of pesticides at trace concentrations. We used experimental data reported in the literature or novel simulations to explore three fundamental kinetic processes in isolation. We then combine these kinetic processes into a unified model framework. The three kinetic processes described were: the growth-linked biodegradation of micropollutant at environmentally relevant concentrations; the effect of coincidental assimilable organic carbon substrates; and the effect of coincidental microbes that compete for assimilable organic carbon substrates. We used Monod kinetic models to describe substrate utilization and microbial growth rates for specific pesticide and degrader pairs. We then extended the model to include terms for utilization of assimilable organic carbon substrates by the specific degrader and coincidental microbes, growth on assimilable organic carbon substrates by the specific degrader and coincidental microbes, and endogenous metabolism. The proposed model framework enables interpretation and description of a range of experimental observations on micropollutant biodegradation. The model provides a useful tool to identify environmental conditions with respect to the occurrence of assimilable organic carbon and coincidental microbes that may result in enhanced or reduced micropollutant biodegradation.

Improving ecophysiological simulation models to predict the impact of elevated atmospheric CO2 concentration on crop productivity

PubMed Central

Yin, Xinyou

2013-01-01

Background Process-based ecophysiological crop models are pivotal in assessing responses of crop productivity and designing strategies of adaptation to climate change. Most existing crop models generally over-estimate the effect of elevated atmospheric [CO2], despite decades of experimental research on crop growth response to [CO2]. Analysis A review of the literature indicates that the quantitative relationships for a number of traits, once expressed as a function of internal plant nitrogen status, are altered little by the elevated [CO2]. A model incorporating these nitrogen-based functional relationships and mechanisms simulated photosynthetic acclimation to elevated [CO2], thereby reducing the chance of over-estimating crop response to [CO2]. Robust crop models to have small parameterization requirements and yet generate phenotypic plasticity under changing environmental conditions need to capture the carbon–nitrogen interactions during crop growth. Conclusions The performance of the improved models depends little on the type of the experimental facilities used to obtain data for parameterization, and allows accurate projections of the impact of elevated [CO2] and other climatic variables on crop productivity. PMID:23388883

Monitoring damage growth in titanium matrix composites using acoustic emission

NASA Technical Reports Server (NTRS)

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

1993-01-01

The application of the acoustic emission (AE) technique to locate and monitor damage growth in titanium matrix composites (TMC) was investigated. Damage growth was studied using several optical techniques including a long focal length, high magnification microscope system with image acquisition capabilities. Fracture surface examinations were conducted using a scanning electron microscope (SEM). The AE technique was used to locate damage based on the arrival times of AE events between two sensors. Using model specimens exhibiting a dominant failure mechanism, correlations were established between the observed damage growth mechanisms and the AE results in terms of the events amplitude. These correlations were used to monitor the damage growth process in laminates exhibiting multiple modes of damage. Results revealed that the AE technique is a viable and effective tool to monitor damage growth in TMC.

Mechanisms Determining the Structure of Gold-Catalyzed GaAs Nanowires Studied by in Situ X-ray Diffraction

DOE PAGES

Takahasi, Masamitu; Kozu, Miwa; Sasaki, Takuo; ...

2015-09-02

The evolution of polytypism during GaAs nanowire growth was investigated with in situ X-ray diffraction. The growth of nanowires was found to start with the formation of zincblende structure, followed by the growth of wurtzite structure. The growth process was well reproduced by a simulation based on a layer-by-layer nucleation model. The good agreement between the measured and simulated results confirms that nucleation costs higher energy for the stackings changing the crystal structure than for those conserving the preceding structure. The transition in prevalent structure can be accounted for by the change of local growth conditions related to the shapemore » of triple phase line rather than by the change in supersaturation level, which quickly reaches steady state after starting growth.« less

Spatial variability in growth-increment chronologies of long-lived freshwater mussels: Implications for climate impacts and reconstructions

USGS Publications Warehouse

Black, Bryan A.; Dunham, Jason B.; Blundon, Brett W.; Raggon, Mark F.; Zima, Daniela

2010-01-01

Estimates of historical variability in river ecosystems are often lacking, but long-lived freshwater mussels could provide unique opportunities to understand past conditions in these environments. We applied dendrochronology techniques to quantify historical variability in growth-increment widths in valves (shells) of western pearlshell freshwater mussels (Margaritifera falcata). A total of 3 growth-increment chronologies, spanning 19 to 26 y in length, were developed. Growth was highly synchronous among individuals within each site, and to a lesser extent, chronologies were synchronous among sites. All 3 chronologies negatively related to instrumental records of stream discharge, while correlations with measures of water temperature were consistently positive but weaker. A reconstruction of stream discharge was performed using linear regressions based on a mussel growth chronology and the regional Palmer Drought Severity Index (PDSI). Models based on mussel growth and PDSI yielded similar coefficients of prediction (R2Pred) of 0.73 and 0.77, respectively, for predicting out-ofsample observations. From an ecological perspective, we found that mussel chronologies provided a rich source of information for understanding climate impacts. Responses of mussels to changes in climate and stream ecosystems can be very site- and process-specific, underscoring the complex nature of biotic responses to climate change and the need to understand both regional and local processes in projecting climate impacts on freshwater species.

Geometrical approach to tumor growth.

PubMed

Escudero, Carlos

2006-08-01

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

Nucleation, aggregative growth and detachment of metal nanoparticles during electrodeposition at electrode surfaces† †Electronic supplementary information (ESI) available: S1 Scharifker–Hills model, S2 tapping mode-atomic force microscopy (TM-AFM) image of AM grade HOPG, after exposure to a droplet of 50 mM KNO3, S3 distribution of induction times, S4 results of the modified Cottrell fits at different potentials, S5 FE-SEM images of HOPG after control tip breaking, S6 extended current–time trace. See DOI: 10.1039/c4sc02792b Click here for additional data file.

PubMed Central

Lazenby, Robert A.; Kirkman, Paul M.

2015-01-01

The nucleation and growth of metal nanoparticles (NPs) on surfaces is of considerable interest with regard to creating functional interfaces with myriad applications. Yet, key features of these processes remain elusive and are undergoing revision. Here, the mechanism of the electrodeposition of silver on basal plane highly oriented pyrolytic graphite (HOPG) is investigated as a model system at a wide range of length scales, spanning electrochemical measurements from the macroscale to the nanoscale using scanning electrochemical cell microscopy (SECCM), a pipette-based approach. The macroscale measurements show that the nucleation process cannot be modelled as either truly instantaneous or progressive, and that step edge sites of HOPG do not play a dominant role in nucleation events compared to the HOPG basal plane, as has been widely proposed. Moreover, nucleation numbers extracted from electrochemical analysis do not match those determined by atomic force microscopy (AFM). The high time and spatial resolution of the nanoscale pipette set-up reveals individual nucleation and growth events at the graphite basal surface that are resolved and analysed in detail. Based on these results, corroborated with complementary microscopy measurements, we propose that a nucleation-aggregative growth-detachment mechanism is an important feature of the electrodeposition of silver NPs on HOPG. These findings have major implications for NP electrodeposition and for understanding electrochemical processes at graphitic materials generally. PMID:29560200

Terrestrial ecosystem process model Biome-BGCMuSo v4.0: summary of improvements and new modeling possibilities

NASA Astrophysics Data System (ADS)

Hidy, Dóra; Barcza, Zoltán; Marjanović, Hrvoje; Zorana Ostrogović Sever, Maša; Dobor, Laura; Gelybó, Györgyi; Fodor, Nándor; Pintér, Krisztina; Churkina, Galina; Running, Steven; Thornton, Peter; Bellocchi, Gianni; Haszpra, László; Horváth, Ferenc; Suyker, Andrew; Nagy, Zoltán

2016-12-01

The process-based biogeochemical model Biome-BGC was enhanced to improve its ability to simulate carbon, nitrogen, and water cycles of various terrestrial ecosystems under contrasting management activities. Biome-BGC version 4.1.1 was used as a base model. Improvements included addition of new modules such as the multilayer soil module, implementation of processes related to soil moisture and nitrogen balance, soil-moisture-related plant senescence, and phenological development. Vegetation management modules with annually varying options were also implemented to simulate management practices of grasslands (mowing, grazing), croplands (ploughing, fertilizer application, planting, harvesting), and forests (thinning). New carbon and nitrogen pools have been defined to simulate yield and soft stem development of herbaceous ecosystems. The model version containing all developments is referred to as Biome-BGCMuSo (Biome-BGC with multilayer soil module; in this paper, Biome-BGCMuSo v4.0 is documented). Case studies on a managed forest, cropland, and grassland are presented to demonstrate the effect of model developments on the simulation of plant growth as well as on carbon and water balance.

The Coupled Photothermal Reaction and Transport in a Laser Additive Metal Nanolayer Simultaneous Synthesis and Pattering for Flexible Electronics.

PubMed

Tsai, Song-Ling; Liu, Yi-Kai; Pan, Heng; Liu, Chien-Hung; Lee, Ming-Tsang

2016-01-08

The Laser Direct Synthesis and Patterning (LDSP) technology has advantages in terms of processing time and cost compared to nanomaterials-based laser additive microfabrication processes. In LDSP, a scanning laser on the substrate surface induces chemical reactions in the reactive liquid solution and selectively deposits target material in a preselected pattern on the substrate. In this study, we experimentally investigated the effect of the processing parameters and type and concentration of the additive solvent on the properties and growth rate of the resulting metal film fabricated by this LDSP technology. It was shown that reactive metal ion solutions with substantial viscosity yield metal films with superior physical properties. A numerical analysis was also carried out the first time to investigate the coupled opto-thermo-fluidic transport phenomena and the effects on the metal film growth rate. To complete the simulation, the optical properties of the LDSP deposited metal film with a variety of thicknesses were measured. The characteristics of the temperature field and the thermally induced flow associated with the moving heat source are discussed. It was shown that the processing temperature range of the LDSP is from 330 to 390 K. A semi-empirical model for estimating the metal film growth rate using this process was developed based on these results. From the experimental and numerical results, it is seen that, owing to the increased reflectivity of the silver film as its thickness increases, the growth rate decreases gradually from about 40 nm at initial to 10 nm per laser scan after ten scans. This self-controlling effect of LDSP process controls the thickness and improves the uniformity of the fabricated metal film. The growth rate and resulting thickness of the metal film can also be regulated by adjustment of the processing parameters, and thus can be utilized for controllable additive nano/microfabrication.

Growth and Filling Regularities of Filamentary Channels in Non-Metallic Inorganic Coatings Under Anodic Oxidation of Valve Metals. Mathematical Modeling

NASA Astrophysics Data System (ADS)

Mamaev, A. I.; Mamaeva, V. A.; Kolenchin, N. F.; Chubenko, A. K.; Kovalskaya, Ya. B.; Dolgova, Yu. N.; Beletskaya, E. Yu.

2015-12-01

Theoretical models are developed for growth and filling processes in filamentary channels of nanostructured non-metallic coatings produced by anodizing and microplasma oxidation. Graphical concentration distributions are obtained for channel-reacting anions, cations, and sparingly soluble reaction products depending on the time of electric current transmission and the length of the filamentary channel. Graphical distributions of the front moving velocity for the sparingly soluble compound are presented. The resulting model representation increases the understanding of the anodic process nature and can be used for a description and prediction of porous anodic film growth and filling. It is shown that the character of the filamentary channel growth and filling causes a variety of processes determining the textured metal - nonmetallic inorganic coating phase boundary formation.

Low-temperature plasma-deposited silicon epitaxial films: Growth and properties

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

Demaurex, Bénédicte, E-mail: benedicte.demaurex@epfl.ch; Bartlome, Richard; Seif, Johannes P.

2014-08-07

Low-temperature (≤200 °C) epitaxial growth yields precise thickness, doping, and thermal-budget control, which enables advanced-design semiconductor devices. In this paper, we use plasma-enhanced chemical vapor deposition to grow homo-epitaxial layers and study the different growth modes on crystalline silicon substrates. In particular, we determine the conditions leading to epitaxial growth in light of a model that depends only on the silane concentration in the plasma and the mean free path length of surface adatoms. For such growth, we show that the presence of a persistent defective interface layer between the crystalline silicon substrate and the epitaxial layer stems not only frommore » the growth conditions but also from unintentional contamination of the reactor. Based on our findings, we determine the plasma conditions to grow high-quality bulk epitaxial films and propose a two-step growth process to obtain device-grade material.« less

Grain growth behavior at absolute zero during nanocrystalline metal indentation

NASA Astrophysics Data System (ADS)

Sansoz, F.; Dupont, V.

2006-09-01

The authors show using atomistic simulations that stress-driven grain growth can be obtained in the athermal limit during nanocrystalline aluminum indentation. They find that the grain growth results from rotation of nanograins and propagation of shear bands. Together, these mechanisms are shown to lead to the unstable migration of grain boundaries via process of coupled motion. An analytical model is used to explain this behavior based on the atomic-level shear stress acting on the interfaces during the shear band propagation. This study sheds light on the atomic mechanism at play during the abnormal grain coarsening observed at low temperature in nanocrystalline metals.

Applying Dynamic Energy Budget (DEB) theory to simulate growth and bio-energetics of blue mussels under low seston conditions

NASA Astrophysics Data System (ADS)

Rosland, R.; Strand, Ø.; Alunno-Bruscia, M.; Bacher, C.; Strohmeier, T.

2009-08-01

A Dynamic Energy Budget (DEB) model for simulation of growth and bioenergetics of blue mussels ( Mytilus edulis) has been tested in three low seston sites in southern Norway. The observations comprise four datasets from laboratory experiments (physiological and biometrical mussel data) and three datasets from in situ growth experiments (biometrical mussel data). Additional in situ data from commercial farms in southern Norway were used for estimation of biometrical relationships in the mussels. Three DEB parameters (shape coefficient, half saturation coefficient, and somatic maintenance rate coefficient) were estimated from experimental data, and the estimated parameters were complemented with parameter values from literature to establish a basic parameter set. Model simulations based on the basic parameter set and site specific environmental forcing matched fairly well with observations, but the model was not successful in simulating growth at the extreme low seston regimes in the laboratory experiments in which the long period of negative growth caused negative reproductive mass. Sensitivity analysis indicated that the model was moderately sensitive to changes in the parameter and initial conditions. The results show the robust properties of the DEB model as it manages to simulate mussel growth in several independent datasets from a common basic parameter set. However, the results also demonstrate limitations of Chl a as a food proxy for blue mussels and limitations of the DEB model to simulate long term starvation. Future work should aim at establishing better food proxies and improving the model formulations of the processes involved in food ingestion and assimilation. The current DEB model should also be elaborated to allow shrinking in the structural tissue in order to produce more realistic growth simulations during long periods of starvation.

Efficient embedding of complex networks to hyperbolic space via their Laplacian

PubMed Central

Alanis-Lobato, Gregorio; Mier, Pablo; Andrade-Navarro, Miguel A.

2016-01-01

The different factors involved in the growth process of complex networks imprint valuable information in their observable topologies. How to exploit this information to accurately predict structural network changes is the subject of active research. A recent model of network growth sustains that the emergence of properties common to most complex systems is the result of certain trade-offs between node birth-time and similarity. This model has a geometric interpretation in hyperbolic space, where distances between nodes abstract this optimisation process. Current methods for network hyperbolic embedding search for node coordinates that maximise the likelihood that the network was produced by the afore-mentioned model. Here, a different strategy is followed in the form of the Laplacian-based Network Embedding, a simple yet accurate, efficient and data driven manifold learning approach, which allows for the quick geometric analysis of big networks. Comparisons against existing embedding and prediction techniques highlight its applicability to network evolution and link prediction. PMID:27445157

Monitoring of Batch Industrial Crystallization with Growth, Nucleation, and Agglomeration. Part 1: Modeling with Method of Characteristics.

PubMed

Porru, Marcella; Özkan, Leyla

2017-05-24

This paper develops a new simulation model for crystal size distribution dynamics in industrial batch crystallization. The work is motivated by the necessity of accurate prediction models for online monitoring purposes. The proposed numerical scheme is able to handle growth, nucleation, and agglomeration kinetics by means of the population balance equation and the method of characteristics. The former offers a detailed description of the solid phase evolution, while the latter provides an accurate and efficient numerical solution. In particular, the accuracy of the prediction of the agglomeration kinetics, which cannot be ignored in industrial crystallization, has been assessed by comparing it with solutions in the literature. The efficiency of the solution has been tested on a simulation of a seeded flash cooling batch process. Since the proposed numerical scheme can accurately simulate the system behavior more than hundred times faster than the batch duration, it is suitable for online applications such as process monitoring tools based on state estimators.

Efficient embedding of complex networks to hyperbolic space via their Laplacian

NASA Astrophysics Data System (ADS)

Alanis-Lobato, Gregorio; Mier, Pablo; Andrade-Navarro, Miguel A.

2016-07-01

The different factors involved in the growth process of complex networks imprint valuable information in their observable topologies. How to exploit this information to accurately predict structural network changes is the subject of active research. A recent model of network growth sustains that the emergence of properties common to most complex systems is the result of certain trade-offs between node birth-time and similarity. This model has a geometric interpretation in hyperbolic space, where distances between nodes abstract this optimisation process. Current methods for network hyperbolic embedding search for node coordinates that maximise the likelihood that the network was produced by the afore-mentioned model. Here, a different strategy is followed in the form of the Laplacian-based Network Embedding, a simple yet accurate, efficient and data driven manifold learning approach, which allows for the quick geometric analysis of big networks. Comparisons against existing embedding and prediction techniques highlight its applicability to network evolution and link prediction.

Monitoring of Batch Industrial Crystallization with Growth, Nucleation, and Agglomeration. Part 1: Modeling with Method of Characteristics

PubMed Central

2017-01-01

This paper develops a new simulation model for crystal size distribution dynamics in industrial batch crystallization. The work is motivated by the necessity of accurate prediction models for online monitoring purposes. The proposed numerical scheme is able to handle growth, nucleation, and agglomeration kinetics by means of the population balance equation and the method of characteristics. The former offers a detailed description of the solid phase evolution, while the latter provides an accurate and efficient numerical solution. In particular, the accuracy of the prediction of the agglomeration kinetics, which cannot be ignored in industrial crystallization, has been assessed by comparing it with solutions in the literature. The efficiency of the solution has been tested on a simulation of a seeded flash cooling batch process. Since the proposed numerical scheme can accurately simulate the system behavior more than hundred times faster than the batch duration, it is suitable for online applications such as process monitoring tools based on state estimators. PMID:28603342

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.

Investigation of Biogrout processes by numerical analysis at pore scale

NASA Astrophysics Data System (ADS)

Bergwerff, Luke; van Paassen, Leon A.; Picioreanu, Cristian; van Loosdrecht, Mark C. M.

2013-04-01

Biogrout is a soil improving process that aims to improve the strength of sandy soils. The process is based on microbially induced calcite precipitation (MICP). In this study the main process is based on denitrification facilitated by bacteria indigenous to the soil using substrates, which can be derived from pretreated waste streams containing calcium salts of fatty acids and calcium nitrate, making it a cost effective and environmentally friendly process. The goal of this research is to improve the understanding of the process by numerical analysis so that it may be improved and applied properly for varying applications, such as borehole stabilization, liquefaction prevention, levee fortification and mitigation of beach erosion. During the denitrification process there are many phases present in the pore space including a liquid phase containing solutes, crystals, bacteria forming biofilms and gas bubbles. Due to the amount of phases and their dynamic changes (multiphase flow with (non-linear) reactive transport), there are many interactions making the process very complex. To understand this complexity in the system, the interactions between these phases are studied in a reductionist approach, increasing the complexity of the system by one phase at a time. The model will initially include flow, solute transport, crystal nucleation and growth in 2D at pore scale. The flow will be described by Navier-Stokes equations. Initial study and simulations has revealed that describing crystal growth for this application on a fixed grid can introduce significant fundamental errors. Therefore a level set method will be employed to better describe the interface of developing crystals in between sand grains. Afterwards the model will be expanded to 3D to provide more realistic flow, nucleation and clogging behaviour at pore scale. Next biofilms and lastly gas bubbles may be added to the model. From the results of these pore scale models the behaviour of the system may be studied and eventually observations may be extrapolated to a larger continuum scale.

The Effects of Autocorrelation on the Curve-of-Factors Growth Model

ERIC Educational Resources Information Center

Murphy, Daniel L.; Beretvas, S. Natasha; Pituch, Keenan A.

2011-01-01

This simulation study examined the performance of the curve-of-factors model (COFM) when autocorrelation and growth processes were present in the first-level factor structure. In addition to the standard curve-of factors growth model, 2 new models were examined: one COFM that included a first-order autoregressive autocorrelation parameter, and a…

Intranasal PRGF-Endoret enhances neuronal survival and attenuates NF-κB-dependent inflammation process in a mouse model of Parkinson's disease.

PubMed

Anitua, Eduardo; Pascual, Consuelo; Pérez-Gonzalez, Rocio; Orive, Gorka; Carro, Eva

2015-04-10

Parkinson's disease is a common neurodegenerative disorder of unknown pathogenesis characterized by the loss of nigrostriatal dopaminergic neurons. Oxidative stress, microglial activation and inflammatory responses seem to contribute to the pathogenesis. Recent data showed that growth factors mediate neuroprotection in rodent models of Parkinson's disease, modulating pro-inflammatory processes. Based on our recent studies showing that plasma rich in growth factors (PRGF-Endoret) mediates neuroprotection as inflammatory moderator in Alzheimer's disease, in the present study we examined the effects of plasma rich in growth factors (PRGF-Endoret) in the 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)-lesioned mouse as a translational therapeutic approach for Parkinson's disease. We found substantial neuroprotection by PRGF-Endoret in our model of Parkinson's disease, which resulted in diminished inflammatory responses and improved motor performance. Additionally, these effects were associated with robust reduction in nuclear transcription factor-κB (NF-κB) activation, and nitric oxide (NO), cyclooxygenase-2 (COX-2), and tumor necrosis factor-alpha (TNF-α) expression in the substantia nigra. We propose that PRGF-Endoret can prevent dopaminergic degeneration via an NF-κB-dependent signaling process. As the clinical safety profile of PRGF-Endoret is already established, these data suggest that PRGF-Endoret provides a novel neuroprotective strategy for Parkinson's disease. Copyright © 2015 Elsevier B.V. All rights reserved.

Implementation and Validation of a Laminar-to-Turbulent Transition Model in the Wind-US Code

NASA Technical Reports Server (NTRS)

Denissen, Nicholas A.; Yoder, Dennis A.; Georgiadis, Nicholas J.

2008-01-01

A bypass transition model has been implemented in the Wind-US Reynolds Averaged Navier-Stokes (RANS) solver. The model is based on the Shear Stress Transport (SST) turbulence model and was built starting from a previous SST-based transition model. Several modifications were made to enable (1) consistent solutions regardless of flow field initialization procedure and (2) fully turbulent flow beyond the transition region. This model is intended for flows where bypass transition, in which the transition process is dominated by large freestream disturbances, is the key transition mechanism as opposed to transition dictated by modal growth. Validation of the new transition model is performed for flows ranging from incompressible to hypersonic conditions.

Environmental influence on mussel (Mytilus edulis) growth - A quantile regression approach

NASA Astrophysics Data System (ADS)

Bergström, Per; Lindegarth, Mats

2016-03-01

The need for methods for sustainable management and use of coastal ecosystems has increased in the last century. A key aspect for obtaining ecologically and economically sustainable aquaculture in threatened coastal areas is the requirement of geographic information of growth and potential production capacity. Growth varies over time and space and depends on a complex pattern of interactions between the bivalve and a diverse range of environmental factors (e.g. temperature, salinity, food availability). Understanding these processes and modelling the environmental control of bivalve growth has been central in aquaculture. In contrast to the most conventional modelling techniques, quantile regression can handle cases where not all factors are measured and provide the possibility to estimate the effect at different levels of the response distribution and give therefore a more complete picture of the relationship between environmental factors and biological response. Observation of the relationships between environmental factors and growth of the bivalve Mytilus edulis revealed relationships that varied both among level of growth rate and within the range of environmental variables along the Swedish west coast. The strongest patterns were found for water oxygen concentration level which had a negative effect on growth for all oxygen levels and growth levels. However, these patterns coincided with differences in growth among periods and very little of the remaining variability within periods could be explained indicating that interactive processes masked the importance of the individual variables. By using quantile regression and local regression (LOESS) this study was able to provide valuable information on environmental factors influencing the growth of M. edulis and important insight for the development of ecosystem based management tools of aquaculture activities, its use in mitigation efforts and successful management of human use of coastal areas.

Growth kinetics and island evolution during double-pulsed molecular beam epitaxy of InN

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

Kraus, A.; Hein, C.; Bremers, H.

The kinetic processes of InN growth using alternating source fluxes with sub-monolayer In pulses in plasma-assisted molecular beam epitaxy have been investigated. Growth at various temperatures reveals the existence of two growth regimes. While growth at low temperatures is solely governed by surface diffusion, a combination of decomposition, desorption, and diffusion becomes decisive at growth temperatures of 470 °C and above. At this critical temperature, the surface morphology changes from a grainy structure to a structure made of huge islands. The formation of those islands is attributed to the development of an indium adlayer, which can be observed via reflection highmore » energy electron diffraction monitoring. Based on the growth experiments conducted at temperatures below T{sub Growth} = 470 °C, an activation energy for diffusion of 0.54 ± 0.02 eV has been determined from the decreasing InN island density. A comparison between growth on metalorganic vapor phase epitaxy GaN templates and pseudo bulk GaN indicates that step edges and dislocations are favorable nucleation sites. Based on the results, we developed a growth model, which describes the main mechanisms of the growth.« less

Digital Image Analysis of Yeast Single Cells Growing in Two Different Oxygen Concentrations to Analyze the Population Growth and to Assist Individual-Based Modeling.

PubMed

Ginovart, Marta; Carbó, Rosa; Blanco, Mónica; Portell, Xavier

2017-01-01

Nowadays control of the growth of Saccharomyces to obtain biomass or cellular wall components is crucial for specific industrial applications. The general aim of this contribution is to deal with experimental data obtained from yeast cells and from yeast cultures to attempt the integration of the two levels of information, individual and population, to progress in the control of yeast biotechnological processes by means of the overall analysis of this set of experimental data, and to assist in the improvement of an individual-based model, namely, INDISIM- Saccha . Populations of S. cerevisiae growing in liquid batch culture, in aerobic and microaerophilic conditions, were studied. A set of digital images was taken during the population growth, and a protocol for the treatment and analyses of the images obtained was established. The piecewise linear model of Buchanan was adjusted to the temporal evolutions of the yeast populations to determine the kinetic parameters and changes of growth phases. In parallel, for all the yeast cells analyzed, values of direct morphological parameters, such as area, perimeter, major diameter, minor diameter, and derived ones, such as circularity and elongation, were obtained. Graphical and numerical methods from descriptive statistics were applied to these data to characterize the growth phases and the budding state of the yeast cells in both experimental conditions, and inferential statistical methods were used to compare the diverse groups of data achieved. Oxidative metabolism of yeast in a medium with oxygen available and low initial sugar concentration can be taken into account in order to obtain a greater number of cells or larger cells. Morphological parameters were analyzed statistically to identify which were the most useful for the discrimination of the different states, according to budding and/or growth phase, in aerobic and microaerophilic conditions. The use of the experimental data for subsequent modeling work was then discussed and compared to simulation results generated with INDISIM- Saccha , which allowed us to advance in the development of this yeast model, and illustrated the utility of data at different levels of observation and the needs and logic behind the development of a microbial individual-based model.

Midlife Divorce and Archetypes for Women.

ERIC Educational Resources Information Center

Bobo, Terry Skinner

Midlife divorce for women can be a time for creative growth or divorce can lead to loneliness, bitterness, and depression. Middle-aged women appear to experience an inordinate amount of stress from divorce because of loss of roles and lack of new role models. Based upon role theory and divorce as a normal developmental process, a feminist…

Modelling fungal growth in heterogeneous soil: analyses of the effect of soil physical structure on fungal community dynamics

NASA Astrophysics Data System (ADS)

Falconer, R.; Radoslow, P.; Grinev, D.; Otten, W.

2009-04-01

Fungi play a pivital role in soil ecosystems contributing to plant productivity. The underlying soil physical and biological processes responsible for community dynamics are interrelated and, at present, poorly understood. If these complex processes can be understood then this knowledge can be managed with an aim to providing more sustainable agriculture. Our understanding of microbial dynamics in soil has long been hampered by a lack of a theoretical framework and difficulties in observation and quantification. We will demonstrate how the spatial and temporal dynamics of fungi in soil can be understood by linking mathematical modelling with novel techniques that visualise the complex structure of the soil. The combination of these techniques and mathematical models opens up new possibilities to understand how the physical structure of soil affects fungal colony dynamics and also how fungal dynamics affect soil structure. We will quantify, using X ray tomography, soil structure for a range of artificially prepared microcosms. We characterise the soil structures using soil metrics such as porosity, fractal dimension, and the connectivity of the pore volume. Furthermore we will use the individual based fungal colony growth model of Falconer et al. 2005, which is based on the physiological processes of fungi, to assess the effect of soil structure on microbial dynamics by qualifying biomass abundances and distributions. We demonstrate how soil structure can critically affect fungal species interactions with consequences for biological control and fungal biodiversity.

Effect of Magnetic Fields on g-jitter Induced Convection and Solute Striation During Space Processing of Single Crystals

NASA Technical Reports Server (NTRS)

deGroh, H. C.; Li, K.; Li, B. Q.

2002-01-01

A 2-D finite element model is presented for the melt growth of single crystals in a microgravity environment with a superimposed DC magnetic field. The model is developed based on the deforming finite element methodology and is capable of predicting the phenomena of the steady and transient convective flows, heat transfer, solute distribution, and solid-liquid interface morphology associated with the melt growth of single crystals in microgravity with and without an applied magnetic field. Numerical simulations were carried out for a wide range of parameters including idealized microgravity conditions, the synthesized g-jitter and the real g-jitter data taken by on-board accelerometers during space flights. The results reveal that the time varying g-jitter disturbances, although small in magnitude, cause an appreciable convective flow in the liquid pool, which in turn produces detrimental effects during the space processing of single crystal growth. An applied magnetic field of appropriate strength, superimposed on microgravity, can be very effective in suppressing the deleterious effects resulting from the g-jitter disturbances.

Growth and modelling of spherical crystalline morphologies of molecular materials

NASA Astrophysics Data System (ADS)

Shalev, O.; Biswas, S.; Yang, Y.; Eddir, T.; Lu, W.; Clarke, R.; Shtein, M.

2014-10-01

Crystalline, yet smooth, sphere-like morphologies of small molecular compounds are desirable in a wide range of applications but are very challenging to obtain using common growth techniques, where either amorphous films or faceted crystallites are the norm. Here we show solvent-free, guard flow-assisted organic vapour jet printing of non-faceted, crystalline microspheroids of archetypal small molecular materials used in organic electronic applications. We demonstrate how process parameters control the size distribution of the spheroids and propose an analytical model and a phase diagram predicting the surface morphology evolution of different molecules based on processing conditions, coupled with the thermophysical and mechanical properties of the molecules. This experimental approach opens a path for exciting applications of small molecular organic compounds in optical coatings, textured surfaces with controlled wettability, pharmaceutical and food substance printing and others, where thick organic films and particles with high surface area are needed.

A Linked Model for Simulating Stand Development and Growth Processes of Loblolly Pine

Treesearch

V. Clark Baldwin; Phillip M. Dougherty; Harold E. Burkhart

1998-01-01

Linking models of different scales (e.g., process, tree-stand-ecosystem) is essential for furthering our understanding of stand, climatic, and edaphic effects on tree growth and forest productivity. Moreover, linking existing models that differ in scale and levels of resolution quickly identifies knowledge gaps in information required to scale from one level to another...

Combining cellular automata and Lattice Boltzmann method to model multiscale avascular tumor growth coupled with nutrient diffusion and immune competition.

PubMed

Alemani, Davide; Pappalardo, Francesco; Pennisi, Marzio; Motta, Santo; Brusic, Vladimir

2012-02-28

In the last decades the Lattice Boltzmann method (LB) has been successfully used to simulate a variety of processes. The LB model describes the microscopic processes occurring at the cellular level and the macroscopic processes occurring at the continuum level with a unique function, the probability distribution function. Recently, it has been tried to couple deterministic approaches with probabilistic cellular automata (probabilistic CA) methods with the aim to model temporal evolution of tumor growths and three dimensional spatial evolution, obtaining hybrid methodologies. Despite the good results attained by CA-PDE methods, there is one important issue which has not been completely solved: the intrinsic stochastic nature of the interactions at the interface between cellular (microscopic) and continuum (macroscopic) level. CA methods are able to cope with the stochastic phenomena because of their probabilistic nature, while PDE methods are fully deterministic. Even if the coupling is mathematically correct, there could be important statistical effects that could be missed by the PDE approach. For such a reason, to be able to develop and manage a model that takes into account all these three level of complexity (cellular, molecular and continuum), we believe that PDE should be replaced with a statistic and stochastic model based on the numerical discretization of the Boltzmann equation: The Lattice Boltzmann (LB) method. In this work we introduce a new hybrid method to simulate tumor growth and immune system, by applying Cellular Automata Lattice Boltzmann (CA-LB) approach. Copyright © 2011 Elsevier B.V. All rights reserved.

Wide-bandgap III-Nitride based Second Harmonic Generation

DTIC Science & Technology

2014-10-02

fabrication process for a GaN LPS. Fig. 1: 3-step Fabrication process of a GaN based lateral polar structure. ( a ) Growth of a 20 nm AlN buffer layer...etching of the LT-AlN stripes. This results are shown in Fig. 2 ( a ) and (b). Fig. 2: AFM images of KOH ( a ) and RIE (b) patterned templates for lateral ...was varied between 0.6 - 1.0. FIG. 3: Growth process of AlGaN based Lateral Polar Structures. ( a ) RIE patterning. (b) Growth of HT- AlN. (c

A numerical model to simulate foams during devolatilization of polymers

NASA Astrophysics Data System (ADS)

Khan, Irfan; Dixit, Ravindra

2014-11-01

Customers often demand that the polymers sold in the market have low levels of volatile organic compounds (VOC). Some of the processes for making polymers involve the removal of volatiles to the levels of parts per million (devolatilization). During this step the volatiles are phase separated out of the polymer through a combination of heating and applying lower pressure, creating foam with the pure polymer in liquid phase and the volatiles in the gas phase. The efficiency of the devolatilization process depends on predicting the onset of solvent phase change in the polymer and volatiles mixture accurately based on the processing conditions. However due to the complex relationship between the polymer properties and the processing conditions this is not trivial. In this work, a bubble scale model is coupled with a bulk scale transport model to simulate the processing conditions of polymer devolatilization. The bubble scale model simulates the nucleation and bubble growth based on the classical nucleation theory and the popular ``influence volume approach.'' As such it provides the information of bubble size distribution and number density inside the polymer at any given time and position. This information is used to predict the bulk properties of the polymer and its behavior under the applied processing conditions. Initial results of this modeling approach will be presented.

Principles of quantitation of viral loads using nucleic acid sequence-based amplification in combination with homogeneous detection using molecular beacons.

PubMed

Weusten, Jos J A M; Carpay, Wim M; Oosterlaken, Tom A M; van Zuijlen, Martien C A; van de Wiel, Paul A

2002-03-15

For quantitative NASBA-based viral load assays using homogeneous detection with molecular beacons, such as the NucliSens EasyQ HIV-1 assay, a quantitation algorithm is required. During the amplification process there is a constant growth in the concentration of amplicons to which the beacon can bind while generating a fluorescence signal. The overall fluorescence curve contains kinetic information on both amplicon formation and beacon binding, but only the former is relevant for quantitation. In the current paper, mathematical modeling of the relevant processes is used to develop an equation describing the fluorescence curve as a function of the amplification time and the relevant kinetic parameters. This equation allows reconstruction of RNA formation, which is characterized by an exponential increase in concentrations as long as the primer concentrations are not rate limiting and by linear growth over time after the primer pool is depleted. During the linear growth phase, the actual quantitation is based on assessing the amplicon formation rate from the viral RNA relative to that from a fixed amount of calibrator RNA. The quantitation procedure has been successfully applied in the NucliSens EasyQ HIV-1 assay.

Predicting paddlefish roe yields using an extension of the Beverton–Holt equilibrium yield-per-recruit model

USGS Publications Warehouse

Colvin, M.E.; Bettoli, Phillip William; Scholten, G.D.

2013-01-01

Equilibrium yield models predict the total biomass removed from an exploited stock; however, traditional yield models must be modified to simulate roe yields because a linear relationship between age (or length) and mature ovary weight does not typically exist. We extended the traditional Beverton-Holt equilibrium yield model to predict roe yields of Paddlefish Polyodon spathula in Kentucky Lake, Tennessee-Kentucky, as a function of varying conditional fishing mortality rates (10-70%), conditional natural mortality rates (cm; 9% and 18%), and four minimum size limits ranging from 864 to 1,016mm eye-to-fork length. These results were then compared to a biomass-based yield assessment. Analysis of roe yields indicated the potential for growth overfishing at lower exploitation rates and smaller minimum length limits than were suggested by the biomass-based assessment. Patterns of biomass and roe yields in relation to exploitation rates were similar regardless of the simulated value of cm, thus indicating that the results were insensitive to changes in cm. Our results also suggested that higher minimum length limits would increase roe yield and reduce the potential for growth overfishing and recruitment overfishing at the simulated cm values. Biomass-based equilibrium yield assessments are commonly used to assess the effects of harvest on other caviar-based fisheries; however, our analysis demonstrates that such assessments likely underestimate the probability and severity of growth overfishing when roe is targeted. Therefore, equilibrium roe yield-per-recruit models should also be considered to guide the management process for caviar-producing fish species.

Towards a feminist empowerment model of forgiveness psychotherapy.

PubMed

McKay, Kevin M; Hill, Melanie S; Freedman, Suzanne R; Enright, Robert D

2007-03-01

In recent years Enright and Fitzgibbon's (2000) process model of forgiveness therapy has received substantial theoretical and empirical attention. However, both the process model of forgiveness therapy and the social-cognitive developmental model on which it is based have received criticism from feminist theorists. The current paper considers feminist criticisms of forgiveness therapy and uses a feminist lens to identify potential areas for growth. Specifically, Worell and Remer's (2003) model of synthesizing feminist ideals into existing theory was consulted, areas of bias within the forgiveness model of psychotherapy were identified, and strategies for restructuring areas of potential bias were introduced. Further, the authors consider unique aspects of forgiveness therapy that can potentially strengthen existing models of feminist therapy. (PsycINFO Database Record (c) 2010 APA, all rights reserved).

Inferring physiological energetics of loggerhead turtle (Caretta caretta) from existing data using a general metabolic theory.

PubMed

Marn, Nina; Kooijman, S A L M; Jusup, Marko; Legović, Tarzan; Klanjšček, Tin

2017-05-01

Loggerhead turtle is an endangered sea turtle species with a migratory lifestyle and worldwide distribution, experiencing markedly different habitats throughout its lifetime. Environmental conditions, especially food availability and temperature, constrain the acquisition and the use of available energy, thus affecting physiological processes such as growth, maturation, and reproduction. These physiological processes at the population level determine survival, fecundity, and ultimately the population growth rate-a key indicator of the success of conservation efforts. As a first step towards the comprehensive understanding of how environment shapes the physiology and the life cycle of a loggerhead turtle, we constructed a full life cycle model based on the principles of energy acquisition and utilization embedded in the Dynamic Energy Budget (DEB) theory. We adapted the standard DEB model using data from published and unpublished sources to obtain parameter estimates and model predictions that could be compared with data. The outcome was a successful mathematical description of ontogeny and life history traits of the loggerhead turtle. Some deviations between the model and the data existed (such as an earlier age at sexual maturity and faster growth of the post-hatchlings), yet probable causes for these deviations were found informative and discussed in great detail. Physiological traits such as the capacity to withstand starvation, trade-offs between reproduction and growth, and changes in the energy budget throughout the ontogeny were inferred from the model. The results offer new insights into physiology and ecology of loggerhead turtle with the potential to lead to novel approaches in conservation of this endangered species. Copyright © 2017 Elsevier Ltd. All rights reserved.

A Computational Model Predicting Disruption of Blood Vessel Development

PubMed Central

Kleinstreuer, Nicole; Dix, David; Rountree, Michael; Baker, Nancy; Sipes, Nisha; Reif, David; Spencer, Richard; Knudsen, Thomas

2013-01-01

Vascular development is a complex process regulated by dynamic biological networks that vary in topology and state across different tissues and developmental stages. Signals regulating de novo blood vessel formation (vasculogenesis) and remodeling (angiogenesis) come from a variety of biological pathways linked to endothelial cell (EC) behavior, extracellular matrix (ECM) remodeling and the local generation of chemokines and growth factors. Simulating these interactions at a systems level requires sufficient biological detail about the relevant molecular pathways and associated cellular behaviors, and tractable computational models that offset mathematical and biological complexity. Here, we describe a novel multicellular agent-based model of vasculogenesis using the CompuCell3D (http://www.compucell3d.org/) modeling environment supplemented with semi-automatic knowledgebase creation. The model incorporates vascular endothelial growth factor signals, pro- and anti-angiogenic inflammatory chemokine signals, and the plasminogen activating system of enzymes and proteases linked to ECM interactions, to simulate nascent EC organization, growth and remodeling. The model was shown to recapitulate stereotypical capillary plexus formation and structural emergence of non-coded cellular behaviors, such as a heterologous bridging phenomenon linking endothelial tip cells together during formation of polygonal endothelial cords. Molecular targets in the computational model were mapped to signatures of vascular disruption derived from in vitro chemical profiling using the EPA's ToxCast high-throughput screening (HTS) dataset. Simulating the HTS data with the cell-agent based model of vascular development predicted adverse effects of a reference anti-angiogenic thalidomide analog, 5HPP-33, on in vitro angiogenesis with respect to both concentration-response and morphological consequences. These findings support the utility of cell agent-based models for simulating a morphogenetic series of events and for the first time demonstrate the applicability of these models for predictive toxicology. PMID:23592958

Aircraft- and ground-based assessment of the CCN-AOD relationship and implications on model analysis of ACI and underlying aerosol processes

NASA Astrophysics Data System (ADS)

Shinozuka, Y.; Clarke, A. D.; Nenes, A.; Lathem, T. L.; Redemann, J.; Jefferson, A.; Wood, R.

2014-12-01

Contrary to common assumptions in satellite-based modeling of aerosol-cloud interactions, ∂logCCN/∂logAOD is less than unity, i.e., the number concentration of cloud condensation nuclei (CCN) less than doubles as aerosol optical depth (AOD) doubles. This can be explained by omnipresent aerosol processes. Condensation, coagulation and cloud processing, for example, generally make particles scatter more light while hardly increasing their number. This paper reports on the relationship in local air masses between CCN concentration, aerosol size distribution and light extinction observed from aircraft and the ground at diverse locations. The CCN-to-local-extinction relationship, when averaged over ~1 km distance and sorted by the wavelength dependence of extinction, varies approximately by a factor of 2, reflecting the variability in aerosol intensive properties. This, together with retrieval uncertainties and the variability in aerosol spatio-temporal distribution and hygroscopic growth, challenges satellite-based CCN estimates. However, the large differences in estimated CCN may correspond to a considerably lower uncertainty in cloud drop number concentration (CDNC), given the sublinear response of CDNC to CCN. Overall, our findings from airborne and ground-based observations call for model-based reexamination of aerosol-cloud interactions and underlying aerosol processes.

Silicon materials task of the low cost solar array project. Phase 3: Effect of impurities and processing on silicon solar cells

NASA Technical Reports Server (NTRS)

Hopkins, R. H.; Davis, J. R.; Blais, P. D.; Rohatgi, A.; Campbell, R. B.; Rai-Choudhury, P.; Mollenkopf, H. C.; Mccormick, J. R.

1979-01-01

The 13th quarterly report of a study entitled an Investigation of the Effects of Impurities and Processing on Silicon Solar Cells is given. The objective of the program is to define the effects of impurities, various thermochemical processes and any impurity-process interactions on the performance of terrestrial silicon solar cells. The Phase 3 program effort falls in five areas: (1) cell processing studies; (2) completion of the data base and impurity-performance modeling for n-base cells; (3) extension of p-base studies to include contaminants likely to be introduced during silicon production, refining or crystal growth; (4) anisotropy effects; and (5) a preliminary study of the permanence of impurity effects in silicon solar cells. The quarterly activities for this report focus on tasks (1), (3) and (4).

The Net Carbon Flux due to Deforestation and Forest Re-Growth in the Brazilian Amazon: Analysis using a Process-Based Model

NASA Technical Reports Server (NTRS)

Hirsch, A. I.; Little, W. S.; Houghton, R. A.; Scott, N. A.; White, J. D.

2004-01-01

We developed a process-based model of forest growth, carbon cycling, and land cover dynamics named CARLUC (for CARbon and Land Use Change) to estimate the size of terrestrial carbon pools in terra firme (non-flooded) forests across the Brazilian Legal Amazon and the net flux of carbon resulting from forest disturbance and forest recovery from disturbance. Our goal in building the model was to construct a relatively simple ecosystem model that would respond to soil and climatic heterogeneity that allows us to study of the impact of Amazonian deforestation, selective logging, and accidental fire on the global carbon cycle. This paper focuses on the net flux caused by deforestation and forest re-growth over the period from 1970-1998. We calculate that the net flux to the atmosphere during this period reached a maximum of approx. 0.35 PgC/yr (1PgC = 1 x 10(exp I5) gC) in 1990, with a cumulative release of approx. 7 PgC from 1970- 1998. The net flux is higher than predicted by an earlier study by a total of 1 PgC over the period 1989-1 998 mainly because CARLUC predicts relatively high mature forest carbon storage compared to the datasets used in the earlier study. Incorporating the dynamics of litter and soil carbon pools into the model increases the cumulative net flux by approx. 1 PgC from 1970-1998, while different assumptions about land cover dynamics only caused small changes. The uncertainty of the net flux, calculated with a Monte-Carlo approach, is roughly 35% of the mean value (1 SD).

A Dynamic Energy Budget (DEB) Model for the Keystone Predator Pisaster ochraceus

PubMed Central

Monaco, Cristián J.; Wethey, David S.; Helmuth, Brian

2014-01-01

We present a Dynamic Energy Budget (DEB) model for the quintessential keystone predator, the rocky-intertidal sea star Pisaster ochraceus. Based on first principles, DEB theory is used to illuminate underlying physiological processes (maintenance, growth, development, and reproduction), thus providing a framework to predict individual-level responses to environmental change. We parameterized the model for P. ochraceus using both data from the literature and experiments conducted specifically for the DEB framework. We devoted special attention to the model’s capacity to (1) describe growth trajectories at different life-stages, including pelagic larval and post-metamorphic phases, (2) simulate shrinkage when prey availability is insufficient to meet maintenance requirements, and (3) deal with the combined effects of changing body temperature and food supply. We further validated the model using an independent growth data set. Using standard statistics to compare model outputs with real data (e.g. Mean Absolute Percent Error, MAPE) we demonstrated that the model is capable of tracking P. ochraceus’ growth in length at different life-stages (larvae: MAPE = 12.27%; post-metamorphic, MAPE = 9.22%), as well as quantifying reproductive output index. However, the model’s skill dropped when trying to predict changes in body mass (MAPE = 24.59%), potentially because of the challenge of precisely anticipating spawning events. Interestingly, the model revealed that P. ochraceus reserves contribute little to total biomass, suggesting that animals draw energy from structure when food is limited. The latter appears to drive indeterminate growth dynamics in P. ochraceus. Individual-based mechanistic models, which can illuminate underlying physiological responses, offer a viable framework for forecasting population dynamics in the keystone predator Pisaster ochraceus. The DEB model herein represents a critical step in that direction, especially in a period of increased anthropogenic pressure on natural systems and an observed recent decline in populations of this keystone species. PMID:25166351

Modeling of Macroscopic/Microscopic Transport and Growth Phenomena in Zeolite Crystal Solutions Under Microgravity Conditions

NASA Technical Reports Server (NTRS)

Gatsonis, Nikos A.; Alexandrou, Andreas; Shi, Hui; Ongewe, Bernard; Sacco, Albert, Jr.

1999-01-01

Crystals grown from liquid solutions have important industrial applications. Zeolites, for instance, a class of crystalline aluminosilicate materials, form the backbone of the chemical process industry worldwide, as they are used as adsorbents and catalysts. Many of the phenomena associated with crystal growth processes are not well understood due to complex microscopic and macroscopic interactions. Microgravity could help elucidate these phenomena and allow the control of defect locations, concentration, as well as size of crystals. Microgravity in an orbiting spacecraft could help isolate the possible effects of natural convection (which affects defect formation) and minimize sedimentation. In addition, crystals will stay essentially suspended in the nutrient pool under a diffusion-limited growth condition. This is expected to promote larger crystals by allowing a longer residence time in a high-concentration nutrient field. Among other factors, the crystal size distribution depends on the nucleation rate and crystallization. These two are also related to the "gel" polymerization/depolymerization rate. Macroscopic bulk mass and flow transport and especially gravity, force the crystals down to the bottom of the reactor, thus forming a sedimentation layer. In this layer, the growth rate of the crystals slows down as crystals compete for a limited amount of nutrients. The macroscopic transport phenomena under certain conditions can, however, enhance the nutrient supply and therefore, accelerate crystal growth. Several zeolite experiments have been performed in space with mixed results. The results from our laboratory have indicated an enhancement in size of 30 to 70 percent compared to the best ground based controls, and a reduction of lattice defects in many of the space grown crystals. Such experiments are difficult to interpret, and cannot be easily used to derive empirical or other laws since many physical parameters are simultaneously involved in the process. At the same time, however, there is increased urgency to develop such an understanding in order to more accurately quantify the process. In order to better understand the results obtained from our prior space experiments, and design future experiments, a detailed fluid dynamic model simulating the crystal growth mechanism is required. This will not only add to the fundamental knowledge on the crystallization of zeolites, but also be useful in predicting the limits of size and growth of these important industrial materials. Our objective is to develop macro/microscopic theoretical and computational models to study the effect of transport phenomena in the growth of crystals grown in solutions. Our effort has concentrated so far in the development of separate macroscopic and microscopic models. The major highlights of our accomplishments are described.

Fire risk in San Diego County, California: A weighted Bayesian model approach

USGS Publications Warehouse

Kolden, Crystal A.; Weigel, Timothy J.

2007-01-01

Fire risk models are widely utilized to mitigate wildfire hazards, but models are often based on expert opinions of less understood fire-ignition and spread processes. In this study, we used an empirically derived weights-of-evidence model to assess what factors produce fire ignitions east of San Diego, California. We created and validated a dynamic model of fire-ignition risk based on land characteristics and existing fire-ignition history data, and predicted ignition risk for a future urbanization scenario. We then combined our empirical ignition-risk model with a fuzzy fire behavior-risk model developed by wildfire experts to create a hybrid model of overall fire risk. We found that roads influence fire ignitions and that future growth will increase risk in new rural development areas. We conclude that empirically derived risk models and hybrid models offer an alternative method to assess current and future fire risk based on management actions.

Dynamic modeling of Listeria monocytogenes growth in pasteurized vanilla cream after postprocessing contamination.

PubMed

Panagou, Efstathios Z; Nychas, George-John E

2008-09-01

A product-specific model was developed and validated under dynamic temperature conditions for predicting the growth of Listeria monocytogenes in pasteurized vanilla cream, a traditional milk-based product. Model performance was also compared with Growth Predictor and Sym'Previus predictive microbiology software packages. Commercially prepared vanilla cream samples were artificially inoculated with a five-strain cocktail of L. monocytogenes, with an initial concentration of 102 CFU g(-1), and stored at 3, 5, 10, and 15 degrees C for 36 days. The growth kinetic parameters at each temperature were determined by the primary model of Baranyi and Roberts. The maximum specific growth rate (mu(max)) was further modeled as a function of temperature by means of a square root-type model. The performance of the model in predicting the growth of the pathogen under dynamic temperature conditions was based on two different temperature scenarios with periodic changes from 4 to 15 degrees C. Growth prediction for dynamic temperature profiles was based on the square root model and the differential equations of the Baranyi and Roberts model, which were numerically integrated with respect to time. Model performance was based on the bias factor (B(f)), the accuracy factor (A(f)), the goodness-of-fit index (GoF), and the percent relative errors between observed and predicted growth. The product-specific model developed in the present study accurately predicted the growth of L. monocytogenes under dynamic temperature conditions. The average values for the performance indices were 1.038, 1.068, and 0.397 for B(f), A(f), and GoF, respectively for both temperature scenarios assayed. Predictions from Growth Predictor and Sym'Previus overestimated pathogen growth. The average values of B(f), A(f), and GoF were 1.173, 1.174, 1.162, and 0.956, 1.115, 0.713 for [corrected] Growth Predictor and Sym'Previus, respectively.

Fragmentation approach to the point-island model with hindered aggregation: Accessing the barrier energy

NASA Astrophysics Data System (ADS)

González, Diego Luis; Pimpinelli, Alberto; Einstein, T. L.

2017-07-01

We study the effect of hindered aggregation on the island formation process in a one- (1D) and two-dimensional (2D) point-island model for epitaxial growth with arbitrary critical nucleus size i . In our model, the attachment of monomers to preexisting islands is hindered by an additional attachment barrier, characterized by length la. For la=0 the islands behave as perfect sinks while for la→∞ they behave as reflecting boundaries. For intermediate values of la, the system exhibits a crossover between two different kinds of processes, diffusion-limited aggregation and attachment-limited aggregation. We calculate the growth exponents of the density of islands and monomers for the low coverage and aggregation regimes. The capture-zone (CZ) distributions are also calculated for different values of i and la. In order to obtain a good spatial description of the nucleation process, we propose a fragmentation model, which is based on an approximate description of nucleation inside of the gaps for 1D and the CZs for 2D. In both cases, the nucleation is described by using two different physically rooted probabilities, which are related with the microscopic parameters of the model (i and la). We test our analytical model with extensive numerical simulations and previously established results. The proposed model describes excellently the statistical behavior of the system for arbitrary values of la and i =1 , 2, and 3.

Analysis of l-glutamic acid fermentation by using a dynamic metabolic simulation model of Escherichia coli

PubMed Central

2013-01-01

Background Understanding the process of amino acid fermentation as a comprehensive system is a challenging task. Previously, we developed a literature-based dynamic simulation model, which included transcriptional regulation, transcription, translation, and enzymatic reactions related to glycolysis, the pentose phosphate pathway, the tricarboxylic acid (TCA) cycle, and the anaplerotic pathway of Escherichia coli. During simulation, cell growth was defined such as to reproduce the experimental cell growth profile of fed-batch cultivation in jar fermenters. However, to confirm the biological appropriateness of our model, sensitivity analysis and experimental validation were required. Results We constructed an l-glutamic acid fermentation simulation model by removing sucAB, a gene encoding α-ketoglutarate dehydrogenase. We then performed systematic sensitivity analysis for l-glutamic acid production; the results of this process corresponded with previous experimental data regarding l-glutamic acid fermentation. Furthermore, it allowed us to predicted the possibility that accumulation of 3-phosphoglycerate in the cell would regulate the carbon flux into the TCA cycle and lead to an increase in the yield of l-glutamic acid via fermentation. We validated this hypothesis through a fermentation experiment involving a model l-glutamic acid-production strain, E. coli MG1655 ΔsucA in which the phosphoglycerate kinase gene had been amplified to cause accumulation of 3-phosphoglycerate. The observed increase in l-glutamic acid production verified the biologically meaningful predictive power of our dynamic metabolic simulation model. Conclusions In this study, dynamic simulation using a literature-based model was shown to be useful for elucidating the precise mechanisms involved in fermentation processes inside the cell. Further exhaustive sensitivity analysis will facilitate identification of novel factors involved in the metabolic regulation of amino acid fermentation. PMID:24053676

Analysis of L-glutamic acid fermentation by using a dynamic metabolic simulation model of Escherichia coli.

PubMed

Nishio, Yousuke; Ogishima, Soichi; Ichikawa, Masao; Yamada, Yohei; Usuda, Yoshihiro; Masuda, Tadashi; Tanaka, Hiroshi

2013-09-22

Understanding the process of amino acid fermentation as a comprehensive system is a challenging task. Previously, we developed a literature-based dynamic simulation model, which included transcriptional regulation, transcription, translation, and enzymatic reactions related to glycolysis, the pentose phosphate pathway, the tricarboxylic acid (TCA) cycle, and the anaplerotic pathway of Escherichia coli. During simulation, cell growth was defined such as to reproduce the experimental cell growth profile of fed-batch cultivation in jar fermenters. However, to confirm the biological appropriateness of our model, sensitivity analysis and experimental validation were required. We constructed an L-glutamic acid fermentation simulation model by removing sucAB, a gene encoding α-ketoglutarate dehydrogenase. We then performed systematic sensitivity analysis for L-glutamic acid production; the results of this process corresponded with previous experimental data regarding L-glutamic acid fermentation. Furthermore, it allowed us to predicted the possibility that accumulation of 3-phosphoglycerate in the cell would regulate the carbon flux into the TCA cycle and lead to an increase in the yield of L-glutamic acid via fermentation. We validated this hypothesis through a fermentation experiment involving a model L-glutamic acid-production strain, E. coli MG1655 ΔsucA in which the phosphoglycerate kinase gene had been amplified to cause accumulation of 3-phosphoglycerate. The observed increase in L-glutamic acid production verified the biologically meaningful predictive power of our dynamic metabolic simulation model. In this study, dynamic simulation using a literature-based model was shown to be useful for elucidating the precise mechanisms involved in fermentation processes inside the cell. Further exhaustive sensitivity analysis will facilitate identification of novel factors involved in the metabolic regulation of amino acid fermentation.

Perspectives on integrated modeling of transport processes in semiconductor crystal growth

NASA Technical Reports Server (NTRS)

Brown, Robert A.

1992-01-01

The wide range of length and time scales involved in industrial scale solidification processes is demonstrated here by considering the Czochralski process for the growth of large diameter silicon crystals that become the substrate material for modern microelectronic devices. The scales range in time from microseconds to thousands of seconds and in space from microns to meters. The physics and chemistry needed to model processes on these different length scales are reviewed.

[A simplified model for kinetics of a tumor cells' population].

PubMed

Gut, R; Zharinov, G M; Iakubov, E

2009-01-01

A mathematical model of solid tumor growth is suggested. The external influence from the tumor-bearing organism is described separately for cell growth and apoptosis. The model is an ordinary differential equation which provides for use of a variety of dependences for both processes. A solution for a specific example of the processes is obtained in the form of a generalized logistic curve. Our results give clues for such experimental phenomena as spontaneous cessation of cell growth, dependence of life duration on insignificant variations in apoptosis, etc.

CROSS-DISCIPLINARY PHYSICS AND RELATED AREAS OF SCIENCE AND TECHNOLOGY: Noise effect in metabolic networks

NASA Astrophysics Data System (ADS)

Li, Zheng-Yan; Xie, Zheng-Wei; Chen, Tong; Ouyang, Qi

2009-12-01

Constraint-based models such as flux balance analysis (FBA) are a powerful tool to study biological metabolic networks. Under the hypothesis that cells operate at an optimal growth rate as the result of evolution and natural selection, this model successfully predicts most cellular behaviours in growth rate. However, the model ignores the fact that cells can change their cellular metabolic states during evolution, leaving optimal metabolic states unstable. Here, we consider all the cellular processes that change metabolic states into a single term 'noise', and assume that cells change metabolic states by randomly walking in feasible solution space. By simulating a state of a cell randomly walking in the constrained solution space of metabolic networks, we found that in a noisy environment cells in optimal states tend to travel away from these points. On considering the competition between the noise effect and the growth effect in cell evolution, we found that there exists a trade-off between these two effects. As a result, the population of the cells contains different cellular metabolic states, and the population growth rate is at suboptimal states.

Processing of laser formed SiC powder

NASA Technical Reports Server (NTRS)

Haggerty, J. S.; Bowen, H. K.

1985-01-01

Superior SiC characteristics can be achieved through the use of ideal constituent powders and careful post-synthesis processing steps. High purity SiC powders of approx. 1000 A uniform diameter, nonagglomerated and spherical were produced. This required major revision of the particle formation and growth model from one based on classical nucleation and growth to one based on collision and coalescence of Si particles followed by their carburization. Dispersions based on pure organic solvents as well as steric stabilization were investigated. Although stable dispersions were formed by both, subsequent part fabrication emphasized the pure solvents since fewer problems with drying and residuals of the high purity particles were anticipated. Test parts were made by the colloidal pressing technique; both liquid filtration and consolidation (rearrangement) stages were modeled. Green densities corresponding to a random close packed structure (approx. 63%) were achieved; this highly perfect structure has a high, uniform coordination number (greater than 11) approaching the quality of an ordered structure without introducing domain boundary effects. After drying, parts were densified at temperatures ranging from 1800 to 2100 C. Optimum densification temperatures will probably be in the 1900 to 2000 C range based on these preliminary results which showed that 2050 C samples had experienced substantial grain growth. Although overfired, the 2050 C samples exhibited excellent mechanical properties. Biaxial tensile strengths up to 714 MPa and Vickers hardness values of 2430 kg/sq mm 2 were both more typical of hot pressed than sintered SiC. Both result from the absence of large defects and the confinement of residual porosity (less than 2.5%) to small diameter, uniformly distributed pores.

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

PubMed

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

2014-09-01

Various predictive models are available for high pressure inactivation of Listeria monocytogenes in food, but currently available models do not consider the growth kinetics of surviving cells during the subsequent storage of products. Therefore, we characterised the growth of L. monocytogenes in sliced cooked meat products after a pressurization treatment. Two inoculum levels (10(7) or 10(4) CFU/g) and two physiological states before pressurization (freeze-stressed or cold-adapted) were evaluated. Samples of cooked ham and mortadella were inoculated, high pressure processed (400 MPa, 5 min) and subsequently stored at 4, 8 and 12 °C. The Logistic model with delay was used to estimate lag phase (λ) and maximum specific growth rate (μmax) values from the obtained growth curves. The effect of storage temperature on μmax and λ was modelled using the Ratkowsky square root model and the relative lag time (RLT) concept. Compared with cold-adapted cells the freeze-stressed cells were more pressure-resistant and showed a much longer lag phase during growth after the pressure treatment. Interestingly, for high-pressure inactivation and subsequent growth, the time to achieve a concentration of L. monocytogenes 100-fold (2-log) higher than the cell concentration prior to the pressure treatment was similar for the two studied physiological states of the inoculum. Two secondary models were necessary to describe the different growth behaviour of L. monocytogenes on ready-to-eat cooked ham (lean product) and mortadella (fatty product). This supported the need of a product-oriented approach to assess growth after high pressure processing. The performance of the developed predictive models for the growth of L. monocytogenes in high-pressure processed cooked ham and mortadella was evaluated by comparison with available data from the literature and by using the Acceptable Simulation Zone approach. Overall, 91% of the relative errors fell into the Acceptable Simulation Zone. Copyright © 2014 Elsevier B.V. All rights reserved.

Directionally Solidified Aluminum - 7 wt% Silicon Alloys: Comparison of Earth and International Space Station Processed Samples

NASA Technical Reports Server (NTRS)

Grugel, Richard N,; Tewari, Surendra; Rajamure, R. S.; Erdman, Robert; Poirier, David

2012-01-01

Primary dendrite arm spacings of Al-7 wt% Si alloy directionally solidified in low gravity environment of space (MICAST-6 and MICAST-7: Thermal gradient approx. 19 to 26 K/cm, Growth speeds varying from 5 to 50 microns/s show good agreement with the Hunt-Lu model. Primary dendrite trunk diameters of the ISS processed samples show a good fit with a simple analytical model based on Kirkwood s approach, proposed here. Natural convection, a) decreases primary dendrite arm spacing. b) appears to increase primary dendrite trunk diameter.

An individual based computational model of intestinal crypt fission and its application to predicting unrestrictive growth of the intestinal epithelium.

PubMed

Pin, Carmen; Parker, Aimee; Gunning, A Patrick; Ohta, Yuki; Johnson, Ian T; Carding, Simon R; Sato, Toshiro

2015-02-01

Intestinal crypt fission is a homeostatic phenomenon, observable in healthy adult mucosa, but which also plays a pathological role as the main mode of growth of some intestinal polyps. Building on our previous individual based model for the small intestinal crypt and on in vitro cultured intestinal organoids, we here model crypt fission as a budding process based on fluid mechanics at the individual cell level and extrapolated predictions for growth of the intestinal epithelium. Budding was always observed in regions of organoids with abundant Paneth cells. Our data support a model in which buds are biomechanically initiated by single stem cells surrounded by Paneth cells which exhibit greater resistance to viscoelastic deformation, a hypothesis supported by atomic force measurements of single cells. Time intervals between consecutive budding events, as simulated by the model and observed in vitro, were 2.84 and 2.62 days, respectively. Predicted cell dynamics was unaffected within the original crypt which retained its full capability of providing cells to the epithelium throughout fission. Mitotic pressure in simulated primary crypts forced upward migration of buds, which simultaneously grew into new protruding crypts at a rate equal to 1.03 days(-1) in simulations and 0.99 days(-1) in cultured organoids. Simulated crypts reached their final size in 4.6 days, and required 6.2 days to migrate to the top of the primary crypt. The growth of the secondary crypt is independent of its migration along the original crypt. Assuming unrestricted crypt fission and multiple budding events, a maximal growth rate of the intestinal epithelium of 0.10 days(-1) is predicted and thus approximately 22 days are required for a 10-fold increase of polyp size. These predictions are in agreement with the time reported to develop macroscopic adenomas in mice after loss of Apc in intestinal stem cells.

A path-dependent fatigue crack propagation model under non-proportional modes I and III loading conditions

DOE PAGES

Mei, J.; Dong, P.; Kalnaus, S.; ...

2017-07-21

It has been well established that fatigue damage process is load-path dependent under non-proportional multi-axial loading conditions. Most of studies to date have been focusing on interpretation of S-N based test data by constructing a path-dependent fatigue damage model. Our paper presents a two-parameter mixed-mode fatigue crack growth model which takes into account of crack growth dependency on both load path traversed and a maximum effective stress intensity attained in a stress intensity factor plane (e.g.,KI-KIII plane). Furthermore, by taking advantage of a path-dependent maximum range (PDMR) cycle definition (Dong et al., 2010; Wei and Dong, 2010), the two parametersmore » are formulated by introducing a moment of load path (MLP) based equivalent stress intensity factor range (ΔKNP) and a maximum effective stress intensity parameter KMax incorporating an interaction term KI·KIII. To examine the effectiveness of the proposed model, two sets of crack growth rate test data are considered. The first set is obtained as a part of this study using 304 stainless steel disk specimens subjected to three combined non-proportional modes I and III loading conditions (i.e., with a phase angle of 0°, 90°, and 180°). The second set was obtained by Feng et al. (2007) using 1070 steel disk specimens subjected to similar types of non-proportional mixed-mode conditions. Once the proposed two-parameter non-proportional mixed-mode crack growth model is used, it is shown that a good correlation can be achieved for both sets of the crack growth rate test data.« less

A path-dependent fatigue crack propagation model under non-proportional modes I and III loading conditions

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

Mei, J.; Dong, P.; Kalnaus, S.

It has been well established that fatigue damage process is load-path dependent under non-proportional multi-axial loading conditions. Most of studies to date have been focusing on interpretation of S-N based test data by constructing a path-dependent fatigue damage model. Our paper presents a two-parameter mixed-mode fatigue crack growth model which takes into account of crack growth dependency on both load path traversed and a maximum effective stress intensity attained in a stress intensity factor plane (e.g.,KI-KIII plane). Furthermore, by taking advantage of a path-dependent maximum range (PDMR) cycle definition (Dong et al., 2010; Wei and Dong, 2010), the two parametersmore » are formulated by introducing a moment of load path (MLP) based equivalent stress intensity factor range (ΔKNP) and a maximum effective stress intensity parameter KMax incorporating an interaction term KI·KIII. To examine the effectiveness of the proposed model, two sets of crack growth rate test data are considered. The first set is obtained as a part of this study using 304 stainless steel disk specimens subjected to three combined non-proportional modes I and III loading conditions (i.e., with a phase angle of 0°, 90°, and 180°). The second set was obtained by Feng et al. (2007) using 1070 steel disk specimens subjected to similar types of non-proportional mixed-mode conditions. Once the proposed two-parameter non-proportional mixed-mode crack growth model is used, it is shown that a good correlation can be achieved for both sets of the crack growth rate test data.« less

Mathematical Modeling of the Dynamics of Shoot-Root Interactions and Resource Partitioning in Plant Growth

PubMed Central

Feller, Chrystel; Favre, Patrick; Janka, Ales; Zeeman, Samuel C.; Gabriel, Jean-Pierre; Reinhardt, Didier

2015-01-01

Plants are highly plastic in their potential to adapt to changing environmental conditions. For example, they can selectively promote the relative growth of the root and the shoot in response to limiting supply of mineral nutrients and light, respectively, a phenomenon that is referred to as balanced growth or functional equilibrium. To gain insight into the regulatory network that controls this phenomenon, we took a systems biology approach that combines experimental work with mathematical modeling. We developed a mathematical model representing the activities of the root (nutrient and water uptake) and the shoot (photosynthesis), and their interactions through the exchange of the substrates sugar and phosphate (Pi). The model has been calibrated and validated with two independent experimental data sets obtained with Petunia hybrida. It involves a realistic environment with a day-and-night cycle, which necessitated the introduction of a transitory carbohydrate storage pool and an endogenous clock for coordination of metabolism with the environment. Our main goal was to grasp the dynamic adaptation of shoot:root ratio as a result of changes in light and Pi supply. The results of our study are in agreement with balanced growth hypothesis, suggesting that plants maintain a functional equilibrium between shoot and root activity based on differential growth of these two compartments. Furthermore, our results indicate that resource partitioning can be understood as the emergent property of many local physiological processes in the shoot and the root without explicit partitioning functions. Based on its encouraging predictive power, the model will be further developed as a tool to analyze resource partitioning in shoot and root crops. PMID:26154262

Modeling of microstructure evolution of magnesium alloy during the high pressure die casting process

NASA Astrophysics Data System (ADS)

Wu, Mengwu; Xiong, Shoumei

2012-07-01

Two important microstructure characteristics of high pressure die cast magnesium alloy are the externally solidified crystals (ESCs) and the fully divorced eutectic which form at the filling stage of the shot sleeve and at the last stage of solidification in the die cavity, respectively. Both of them have a significant influence on the mechanical properties and performance of magnesium alloy die castings. In the present paper, a numerical model based on the cellular automaton (CA) method was developed to simulate the microstructure evolution of magnesium alloy during cold-chamber high pressure die casting (HPDC) process. Modeling of dendritic growth of magnesium alloy with six-fold symmetry was achieved by defining a special neighbourhood configuration and calculating of the growth kinetics from complete solution of the transport equations. Special attention was paid to establish a nucleation model considering both of the nucleation of externally solidified crystals in the shot sleeve and the massive nucleation in the die cavity. Meanwhile, simulation of the formation of fully divorced eutectic was also taken into account in the present CA model. Validation was performed and the capability of the present model was addressed by comparing the simulated results with those obtained by experiments.

Quantitative determination of zero-gravity effects on electronic materials processing germanium crystal growth with simultaneous interface demarcation. Experiment MA-060

NASA Technical Reports Server (NTRS)

Gatos, H. C.; Witt, A. F.

1977-01-01

Experiment MA-060 was designed to establish the crystal growth and segregation characteristics of a melt in a directional solidification configuration under near zero-g conditions. The interface demarcation technique was incorporated into the experiment since it constitutes a unique tool for recording the morphology of the growth rate throughout solidification, and for establishing an absolute time reference framework for all stages of the solidification process. An extensive study was performed of the germanium crystals grown during the Apollo-Soyuz Test Project mission. It was found that single crystal growth was achieved and that the interface demarcation functioned successfully. There was no indication that convection driven by thermal or surface tension gradients was present in the melt. The gallium segregation, in the absence of gravity, was found to be fundamentally different in its initial and its subsequent stages from that of the ground-based tests. None of the existing theoretical models for growth and segregation can account for the observed segregation behavior in the absence of gravity.

Numerical analysis of thermal stress and dislocation density distributions in large size multi-crystalline silicon ingots during the seeded growth process

NASA Astrophysics Data System (ADS)

Nguyen, Thi Hoai Thu; Chen, Jyh-Chen; Hu, Chieh; Chen, Chun-Hung; Huang, Yen-Hao; Lin, Huang-Wei; Yu, Andy; Hsu, Bruce

2017-06-01

In this study, a global transient numerical simulation of silicon growth from the beginning of the solidification process until the end of the cooling process is carried out modeling the growth of an 800 kg ingot in an industrial seeded directional solidification furnace. The standard furnace is modified by the addition of insulating blocks in the hot zone. The simulation results show that there is a significant decrease in the thermal stress and dislocation density in the modified model as compared to the standard one (a maximal decrease of 23% and 75% along the center line of ingot for thermal stress and dislocation density, respectively). This modification reduces the heating power consumption for solidification of the silicon melt by about 17% and shortens the growth time by about 2.5 h. Moreover, it is found that adjusting the operating conditions of modified model to obtain the lower growth rate during the early stages of the solidification process can lower dislocation density and total heater power.

Agent-Based Modeling of Cancer Stem Cell Driven Solid Tumor Growth.

PubMed

Poleszczuk, Jan; Macklin, Paul; Enderling, Heiko

2016-01-01

Computational modeling of tumor growth has become an invaluable tool to simulate complex cell-cell interactions and emerging population-level dynamics. Agent-based models are commonly used to describe the behavior and interaction of individual cells in different environments. Behavioral rules can be informed and calibrated by in vitro assays, and emerging population-level dynamics may be validated with both in vitro and in vivo experiments. Here, we describe the design and implementation of a lattice-based agent-based model of cancer stem cell driven tumor growth.

Surface diffusion effects on growth of nanowires by chemical beam epitaxy

NASA Astrophysics Data System (ADS)

Persson, A. I.; Fröberg, L. E.; Jeppesen, S.; Björk, M. T.; Samuelson, L.

2007-02-01

Surface processes play a large role in the growth of semiconductor nanowires by chemical beam epitaxy. In particular, for III-V nanowires the surface diffusion of group-III species is important to understand in order to control the nanowire growth. In this paper, we have grown InAs-based nanowires positioned by electron beam lithography and have investigated the dependence of the diffusion of In species on temperature, group-III and -V source pressure and group-V source combinations by measuring nanowire growth rate for different nanowire spacings. We present a model which relates the nanowire growth rate to the migration length of In species. The model is fitted to the experimental data for different growth conditions, using the migration length as fitting parameter. The results show that the migration length increases with decreasing temperature and increasing group-V/group-III source pressure ratio. This will most often lead to an increase in growth rate, but deviations will occur due to incomplete decomposition and changes in sticking coefficient for group-III species. The results also show that the introduction of phosphorous precursor for growth of InAs1-xPx nanowires decreases the migration length of the In species followed by a decrease in nanowire growth rate.

Integration of an Individual-Based Fish Bioenergetics Model into a Spatially Explicit Water Quality Model (CE-QUAL-ICM)

DTIC Science & Technology

2010-04-01

energy a fish can devote to growth being the difference between consumption in the form of food and the sum of life process expenditures , including...can incur an elemental deficit, and subsequently retain higher fractions of that element when it is in abun- dance to regain the target composition...Organic nitrogen and caloric content of detritus. Estuarine, Coastal, and Shelf Science 12: 39-47

Examining responses of ecosystem carbon exchange to environmental changes using particle filtering mathod

NASA Astrophysics Data System (ADS)

Yokozawa, M.

2017-12-01

Attention has been paid to the agricultural field that could regulate ecosystem carbon exchange by water management and residual treatments. However, there have been less known about the dynamic responses of the ecosystem to environmental changes. In this study, focussing on paddy field, where CO2 emissions due to microbial decomposition of organic matter are suppressed and alternatively CH4 emitted under flooding condition during rice growth season and subsequently CO2 emission following the fallow season after harvest, the responses of ecosystem carbon exchange were examined. We conducted model data fusion analysis for examining the response of cropland-atmosphere carbon exchange to environmental variation. The used model consists of two sub models, paddy rice growth sub-model and soil decomposition sub-model. The crop growth sub-model mimics the rice plant growth processes including formation of reproductive organs as well as leaf expansion. The soil decomposition sub-model simulates the decomposition process of soil organic carbon. Assimilating the data on the time changes in CO2 flux measured by eddy covariance method, rice plant biomass, LAI and the final yield with the model, the parameters were calibrated using a stochastic optimization algorithm with a particle filter method. The particle filter method, which is one of the Monte Carlo filters, enable us to evaluating time changes in parameters based on the observed data until the time and to make prediction of the system. Iterative filtering and prediction with changing parameters and/or boundary condition enable us to obtain time changes in parameters governing the crop production as well as carbon exchange. In this study, we focused on the parameters related to crop production as well as soil carbon storage. As the results, the calibrated model with estimated parameters could accurately predict the NEE flux in the subsequent years. The temperature sensitivity, denoted by Q10s in the decomposition rate of soil organic carbon (SOC) were obtained as 1.4 for no cultivation period and 2.9 for cultivation period (submerged soil condition in flooding season). It suggests that the response of ecosystem carbon exchange differs due to SOC decomposition process which is sensitive to environmental variation during paddy rice cultivation period.

Latent Growth and Dynamic Structural Equation Models.

PubMed

Grimm, Kevin J; Ram, Nilam

2018-05-07

Latent growth models make up a class of methods to study within-person change-how it progresses, how it differs across individuals, what are its determinants, and what are its consequences. Latent growth methods have been applied in many domains to examine average and differential responses to interventions and treatments. In this review, we introduce the growth modeling approach to studying change by presenting different models of change and interpretations of their model parameters. We then apply these methods to examining sex differences in the development of binge drinking behavior through adolescence and into adulthood. Advances in growth modeling methods are then discussed and include inherently nonlinear growth models, derivative specification of growth models, and latent change score models to study stochastic change processes. We conclude with relevant design issues of longitudinal studies and considerations for the analysis of longitudinal data.

Research on monocentric model of urbanization by agent-based simulation

NASA Astrophysics Data System (ADS)

Xue, Ling; Yang, Kaizhong

2008-10-01

Over the past years, GIS have been widely used for modeling urbanization from a variety of perspectives such as digital terrain representation and overlay analysis using cell-based data platform. Similarly, simulation of urban dynamics has been achieved with the use of Cellular Automata. In contrast to these approaches, agent-based simulation provides a much more powerful set of tools. This allows researchers to set up a counterpart for real environmental and urban systems in computer for experimentation and scenario analysis. This Paper basically reviews the research on the economic mechanism of urbanization and an agent-based monocentric model is setup for further understanding the urbanization process and mechanism in China. We build an endogenous growth model with dynamic interactions between spatial agglomeration and urban development by using agent-based simulation. It simulates the migration decisions of two main types of agents, namely rural and urban households between rural and urban area. The model contains multiple economic interactions that are crucial in understanding urbanization and industrial process in China. These adaptive agents can adjust their supply and demand according to the market situation by a learning algorithm. The simulation result shows this agent-based urban model is able to perform the regeneration and to produce likely-to-occur projections of reality.

Mathematical modeling of static layer crystallization for propellant grade hydrogen peroxide

NASA Astrophysics Data System (ADS)

Hao, Lin; Chen, Xinghua; Sun, Yaozhou; Liu, Yangyang; Li, Shuai; Zhang, Mengqian

2017-07-01

Hydrogen peroxide (H2O2) is an important raw material widely used in many fields. In this work a mathematical model of heat conduction with a moving boundary was proposed to study the melt crystallization process of hydrogen peroxide which was carried out outside a cylindrical crystallizer. Considering the effects of the temperature of the cooling fluid on the thermal conductivity of crude crystal, the model is an improvement of Guardani's research and can be solved by analytic iteration method. An experiment was designed to measure the thickness of crystal layer with time under different conditions. A series of analysis, including the effects of different refrigerant temperature on crystal growth rate, the effects of different cooling rates on crystal layer growth rate, the effects of crystallization temperature on heat transfer and the model's application scope were conducted based on the comparison between experimental results and simulation results of the model.

Computational Modeling of Morphogenesis Regulated by Mechanical Feedback

PubMed Central

Ramasubramanian, Ashok; Taber, Larry A.

2008-01-01

Mechanical forces cause changes in form during embryogenesis and likely play a role in regulating these changes. This paper explores the idea that changes in homeostatic tissue stress (target stress), possibly modulated by genes, drive some morphogenetic processes. Computational models are presented to illustrate how regional variations in target stress can cause a range of complex behaviors involving the bending of epithelia. These models include growth and cytoskeletal contraction regulated by stress-based mechanical feedback. All simulations were carried out using the commercial finite element code ABAQUS, with growth and contraction included by modifying the zero-stress state in the material constitutive relations. Results presented for bending of bilayered beams and invagination of cylindrical and spherical shells provide insight into some of the mechanical aspects that must be considered in studying morphogenetic mechanisms. PMID:17318485

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

PubMed

García, Míriam R; Vázquez, José A; Teixeira, Isabel G; Alonso, Antonio A

2017-01-01

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

Exploring Third-Grade Student Model-Based Explanations about Plant Relationships within an Ecosystem

NASA Astrophysics Data System (ADS)

Zangori, Laura; Forbes, Cory T.

2015-12-01

Elementary students should have opportunities to develop scientific models to reason and build understanding about how and why plants depend on relationships within an ecosystem for growth and survival. However, scientific modeling practices are rarely included within elementary science learning environments and disciplinary content is often treated as discrete pieces separate from scientific practice. Elementary students have few, if any, opportunities to reason about how individual organisms, such as plants, hold critical relationships with their surrounding environment. The purpose of this design-based research study is to build a learning performance to identify and explore the third-grade students' baseline understanding of and their reasoning about plant-ecosystem relationships when engaged in the practices of modeling. The developed learning performance integrated scientific content and core scientific activity to identify and measure how students build knowledge about the role of plants in ecosystems through the practices of modeling. Our findings indicate that the third-grade students' ideas about plant growth include abiotic and biotic relationships. Further, they used their models to reason about how and why these relationships were necessary to maintain plant stasis. However, while the majority of the third-grade students were able to identify and reason about plant-abiotic relationships, a much smaller group reasoned about plant-abiotic-animal relationships. Implications from the study suggest that modeling serves as a tool to support elementary students in reasoning about system relationships, but they require greater curricular and instructional support in conceptualizing how and why ecosystem relationships are necessary for plant growth and development. This paper is based on data from a doctoral dissertation. An earlier version of this paper was presented at the 2015 international conference for the National Association for Research in Science Teaching (NARST) Zangori, L., & Forbes, C. T. (2015). Exploring 3rd-grade student model-based explanations about plant process interactions within the hydrosphere Portions of this paper are based on that work.

Mobil Solar Energy Corporation thin EFG octagons

NASA Astrophysics Data System (ADS)

Kalejs, J. P.

1994-06-01

Mobil Solar Energy Corporation manufactures photovoltaic modules based on its unique Edge-defined Film-fed Growth (EFG) process for producing octagon-shaped hollow polycrystalline silicon tubes. The octagons are cut by lasers into 100 mm x 100 mm wafers which are suitable for solar cell processing. This process avoids slicing, grinding and polishing operations which are wasteful of material and are typical of most other wafer production methods. EFG wafers are fabricated into solar cells and modules using processes that have been specially developed to allow scaling up to high throughput rates. The goals of the Photovoltaic Manufacturing Technology Initiative (PVMaT) program at Mobil Solar were to improve the EFG manufacturing line through technology advances that accelerate cost reduction in production and stimulate market growth for its product. The program was structured into three main tasks: to decrease silicon utilization by lowering wafer thickness from 400 to 200 (mu)m; to enhance laser cutting yields and throughput while improving the wafer strength; and to raise crystal growth productivity and yield. The technical problems faced and the advances made in the Mobil Solar PVMaT program are described. The author concludes with a presentation of the results of a detailed cost model for EFT module production. This model describes the accelerated reductions in manufacturing costs which are already in place and the future benefits anticipated to result from the technical achievements of the PVMaT program.

Dynamic predictive model for growth of Salmonella spp. in scrambled egg mix.

PubMed

Li, Lin; Cepeda, Jihan; Subbiah, Jeyamkondan; Froning, Glenn; Juneja, Vijay K; Thippareddi, Harshavardhan

2017-06-01

Liquid egg products can be contaminated with Salmonella spp. during processing. A dynamic model for the growth of Salmonella spp. in scrambled egg mix - high solids (SEM) was developed and validated. SEM was prepared and inoculated with ca. 2 log CFU/mL of a five serovar Salmonella spp. cocktail. Salmonella spp. growth data at isothermal temperatures (10, 15, 20, 25, 30, 35, 37, 39, 41, 43, 45, and 47 °C) in SEM were collected. Baranyi model was used (primary model) to fit growth data and the maximum growth rate and lag phase duration for each temperature were determined. A secondary model was developed with maximum growth rate as a function of temperature. The model performance measures, root mean squared error (RMSE, 0.09) and pseudo-R 2 (1.00) indicated good fit for both primary and secondary models. A dynamic model was developed by integrating the primary and secondary models and validated using two sinusoidal temperature profiles, 5-15 °C (low temperature) for 480 h and 10-40 °C (high temperature) for 48 h. The RMSE values for the sinusoidal low and high temperature profiles were 0.47 and 0.42 log CFU/mL, respectively. The model can be used to predict Salmonella spp. growth in case of temperature abuse during liquid egg processing. Copyright © 2016. Published by Elsevier Ltd.

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

NASA Astrophysics Data System (ADS)

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

2013-09-01

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

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

NASA Astrophysics Data System (ADS)

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

2012-12-01

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

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

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

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

2013-09-07

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

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.

Detecting Appropriate Trajectories of Growth in Latent Growth Models: The Performance of Information-Based Criteria

ERIC Educational Resources Information Center

Whittaker, Tiffany A.; Khojasteh, Jam

2017-01-01

Latent growth modeling (LGM) is a popular and flexible technique that may be used when data are collected across several different measurement occasions. Modeling the appropriate growth trajectory has important implications with respect to the accurate interpretation of parameter estimates of interest in a latent growth model that may impact…

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

PubMed

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

2015-05-20

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

A tumor growth model with deformable ECM

NASA Astrophysics Data System (ADS)

Sciumè, G.; Santagiuliana, R.; Ferrari, M.; Decuzzi, P.; Schrefler, B. A.

2014-12-01

Existing tumor growth models based on fluid analogy for the cells do not generally include the extracellular matrix (ECM), or if present, take it as rigid. The three-fluid model originally proposed by the authors and comprising tumor cells (TC), host cells (HC), interstitial fluid (IF) and an ECM, considered up to now only a rigid ECM in the applications. This limitation is here relaxed and the deformability of the ECM is investigated in detail. The ECM is modeled as a porous solid matrix with Green-elastic and elasto-visco-plastic material behavior within a large strain approach. Jauman and Truesdell objective stress measures are adopted together with the deformation rate tensor. Numerical results are first compared with those of a reference experiment of a multicellular tumor spheroid (MTS) growing in vitro, then three different tumor cases are studied: growth of an MTS in a decellularized ECM, growth of a spheroid in the presence of host cells and growth of a melanoma. The influence of the stiffness of the ECM is evidenced and comparison with the case of a rigid ECM is made. The processes in a deformable ECM are more rapid than in a rigid ECM and the obtained growth pattern differs. The reasons for this are due to the changes in porosity induced by the tumor growth. These changes are inhibited in a rigid ECM. This enhanced computational model emphasizes the importance of properly characterizing the biomechanical behavior of the malignant mass in all its components to correctly predict its temporal and spatial pattern evolution.

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.

Assimilation of pseudo-tree-ring-width observations into an atmospheric general circulation model

NASA Astrophysics Data System (ADS)

Acevedo, Walter; Fallah, Bijan; Reich, Sebastian; Cubasch, Ulrich

2017-05-01

Paleoclimate data assimilation (DA) is a promising technique to systematically combine the information from climate model simulations and proxy records. Here, we investigate the assimilation of tree-ring-width (TRW) chronologies into an atmospheric global climate model using ensemble Kalman filter (EnKF) techniques and a process-based tree-growth forward model as an observation operator. Our results, within a perfect-model experiment setting, indicate that the "online DA" approach did not outperform the "off-line" one, despite its considerable additional implementation complexity. On the other hand, it was observed that the nonlinear response of tree growth to surface temperature and soil moisture does deteriorate the operation of the time-averaged EnKF methodology. Moreover, for the first time we show that this skill loss appears significantly sensitive to the structure of the growth rate function, used to represent the principle of limiting factors (PLF) within the forward model. In general, our experiments showed that the error reduction achieved by assimilating pseudo-TRW chronologies is modulated by the magnitude of the yearly internal variability in the model. This result might help the dendrochronology community to optimize their sampling efforts.

Simulating Carbon Stocks and Fluxes of an African Tropical Montane Forest with an Individual-Based Forest Model

PubMed Central

Fischer, Rico; Ensslin, Andreas; Rutten, Gemma; Fischer, Markus; Schellenberger Costa, David; Kleyer, Michael; Hemp, Andreas; Paulick, Sebastian; Huth, Andreas

2015-01-01

Tropical forests are carbon-dense and highly productive ecosystems. Consequently, they play an important role in the global carbon cycle. In the present study we used an individual-based forest model (FORMIND) to analyze the carbon balances of a tropical forest. The main processes of this model are tree growth, mortality, regeneration, and competition. Model parameters were calibrated using forest inventory data from a tropical forest at Mt. Kilimanjaro. The simulation results showed that the model successfully reproduces important characteristics of tropical forests (aboveground biomass, stem size distribution and leaf area index). The estimated aboveground biomass (385 t/ha) is comparable to biomass values in the Amazon and other tropical forests in Africa. The simulated forest reveals a gross primary production of 24 tcha-1yr-1. Modeling above- and belowground carbon stocks, we analyzed the carbon balance of the investigated tropical forest. The simulated carbon balance of this old-growth forest is zero on average. This study provides an example of how forest models can be used in combination with forest inventory data to investigate forest structure and local carbon balances. PMID:25915854

Assessing the Impact of Model Parameter Uncertainty in Simulating Grass Biomass Using a Hybrid Carbon Allocation Strategy

NASA Astrophysics Data System (ADS)

Reyes, J. J.; Adam, J. C.; Tague, C.

2016-12-01

Grasslands play an important role in agricultural production as forage for livestock; they also provide a diverse set of ecosystem services including soil carbon (C) storage. The partitioning of C between above and belowground plant compartments (i.e. allocation) is influenced by both plant characteristics and environmental conditions. The objectives of this study are to 1) develop and evaluate a hybrid C allocation strategy suitable for grasslands, and 2) apply this strategy to examine the importance of various parameters related to biogeochemical cycling, photosynthesis, allocation, and soil water drainage on above and belowground biomass. We include allocation as an important process in quantifying the model parameter uncertainty, which identifies the most influential parameters and what processes may require further refinement. For this, we use the Regional Hydro-ecologic Simulation System, a mechanistic model that simulates coupled water and biogeochemical processes. A Latin hypercube sampling scheme was used to develop parameter sets for calibration and evaluation of allocation strategies, as well as parameter uncertainty analysis. We developed the hybrid allocation strategy to integrate both growth-based and resource-limited allocation mechanisms. When evaluating the new strategy simultaneously for above and belowground biomass, it produced a larger number of less biased parameter sets: 16% more compared to resource-limited and 9% more compared to growth-based. This also demonstrates its flexible application across diverse plant types and environmental conditions. We found that higher parameter importance corresponded to sub- or supra-optimal resource availability (i.e. water, nutrients) and temperature ranges (i.e. too hot or cold). For example, photosynthesis-related parameters were more important at sites warmer than the theoretical optimal growth temperature. Therefore, larger values of parameter importance indicate greater relative sensitivity in adequately representing the relevant process to capture limiting resources or manage atypical environmental conditions. These results may inform future experimental work by focusing efforts on quantifying specific parameters under various environmental conditions or across diverse plant functional types.

Ion and lipid signaling in apical growth-a dynamic machinery responding to extracellular cues.

PubMed

Malhó, Rui; Serrazina, Susana; Saavedra, Laura; Dias, Fernando V; Ul-Rehman, Reiaz

2015-01-01

Apical cell growth seems to have independently evolved throughout the major lineages of life. To a certain extent, so does our body of knowledge on the mechanisms regulating this morphogenetic process. Studies on pollen tubes, root hairs, rhizoids, fungal hyphae, even nerve cells, have highlighted tissue and cell specificities but also common regulatory characteristics (e.g., ions, proteins, phospholipids) that our focused research sometimes failed to grasp. The working hypothesis to test how apical cell growth is established and maintained have thus been shaped by the model organism under study and the type of methods used to study them. The current picture is one of a dynamic and adaptative process, based on a spatial segregation of components that network to achieve growth and respond to environmental (extracellular) cues. Here, we explore some examples of our live imaging research, namely on cyclic nucleotide gated ion channels, lipid kinases and syntaxins involved in exocytosis. We discuss how their spatial distribution, activity and concentration suggest that the players regulating apical cell growth may display more mobility than previously thought. Furthermore, we speculate on the implications of such perspective in our understanding of the mechanisms regulating apical cell growth and their responses to extracellular cues.

Modeling the Gas Nitriding Process of Low Alloy Steels

NASA Astrophysics Data System (ADS)

Yang, M.; Zimmerman, C.; Donahue, D.; Sisson, R. D.

2013-07-01

The effort to simulate the nitriding process has been ongoing for the last 20 years. Most of the work has been done to simulate the nitriding process of pure iron. In the present work a series of experiments have been done to understand the effects of the nitriding process parameters such as the nitriding potential, temperature, and time as well as surface condition on the gas nitriding process for the steels. The compound layer growth model has been developed to simulate the nitriding process of AISI 4140 steel. In this paper the fundamentals of the model are presented and discussed including the kinetics of compound layer growth and the determination of the nitrogen diffusivity in the diffusion zone. The excellent agreements have been achieved for both as-washed and pre-oxided nitrided AISI 4140 between the experimental data and simulation results. The nitrogen diffusivity in the diffusion zone is determined to be constant and only depends on the nitriding temperature, which is ~5 × 10-9 cm2/s at 548 °C. It proves the concept of utilizing the compound layer growth model in other steels. The nitriding process of various steels can thus be modeled and predicted in the future.

Comparison of Modeling Approaches for Carbon Partitioning: Impact on Estimates of Global Net Primary Production and Equilibrium Biomass of Woody Vegetation from MODIS GPP

NASA Astrophysics Data System (ADS)

Ise, T.; Litton, C. M.; Giardina, C. P.; Ito, A.

2009-12-01

Plant partitioning of carbon (C) to above- vs. belowground, to growth vs. respiration, and to short vs. long lived tissues exerts a large influence on ecosystem structure and function with implications for the global C budget. Importantly, outcomes of process-based terrestrial vegetation models are likely to vary substantially with different C partitioning algorithms. However, controls on C partitioning patterns remain poorly quantified, and studies have yielded variable, and at times contradictory, results. A recent meta-analysis of forest studies suggests that the ratio of net primary production (NPP) and gross primary production (GPP) is fairly conservative across large scales. To illustrate the effect of this unique meta-analysis-based partitioning scheme (MPS), we compared an application of MPS to a terrestrial satellite-based (MODIS) GPP to estimate NPP vs. two global process-based vegetation models (Biome-BGC and VISIT) to examine the influence of C partitioning on C budgets of woody plants. Due to the temperature dependence of maintenance respiration, NPP/GPP predicted by the process-based models increased with latitude while the ratio remained constant with MPS. Overall, global NPP estimated with MPS was 17 and 27% lower than the process-based models for temperate and boreal biomes, respectively, with smaller differences in the tropics. Global equilibrium biomass of woody plants was then calculated from the NPP estimates and tissue turnover rates from VISIT. Since turnover rates differed greatly across tissue types (i.e., metabolically active vs. structural), global equilibrium biomass estimates were sensitive to the partitioning scheme employed. The MPS estimate of global woody biomass was 7-21% lower than that of the process-based models. In summary, we found that model output for NPP and equilibrium biomass was quite sensitive to the choice of C partitioning schemes. Carbon use efficiency (CUE; NPP/GPP) by forest biome and the globe. Values are means for 2001-2006.

"Development of an interactive crop growth web service architecture to review and forecast agricultural sustainability"

NASA Astrophysics Data System (ADS)

Seamon, E.; Gessler, P. E.; Flathers, E.; Walden, V. P.

2014-12-01

As climate change and weather variability raise issues regarding agricultural production, agricultural sustainability has become an increasingly important component for farmland management (Fisher, 2005, Akinci, 2013). Yet with changes in soil quality, agricultural practices, weather, topography, land use, and hydrology - accurately modeling such agricultural outcomes has proven difficult (Gassman et al, 2007, Williams et al, 1995). This study examined agricultural sustainability and soil health over a heterogeneous multi-watershed area within the Inland Pacific Northwest of the United States (IPNW) - as part of a five year, USDA funded effort to explore the sustainability of cereal production systems (Regional Approaches to Climate Change for Pacific Northwest Agriculture - award #2011-68002-30191). In particular, crop growth and soil erosion were simulated across a spectrum of variables and time periods - using the CropSyst crop growth model (Stockle et al, 2002) and the Water Erosion Protection Project Model (WEPP - Flanagan and Livingston, 1995), respectively. A preliminary range of historical scenarios were run, using a high-resolution, 4km gridded dataset of surface meteorological variables from 1979-2010 (Abatzoglou, 2012). In addition, Coupled Model Inter-comparison Project (CMIP5) global climate model (GCM) outputs were used as input to run crop growth model and erosion future scenarios (Abatzoglou and Brown, 2011). To facilitate our integrated data analysis efforts, an agricultural sustainability web service architecture (THREDDS/Java/Python based) is under development, to allow for the programmatic uploading, sharing and processing of variable input data, running model simulations, as well as downloading and visualizing output results. The results of this study will assist in better understanding agricultural sustainability and erosion relationships in the IPNW, as well as provide a tangible server-based tool for use by researchers and farmers - for both small scale field examination, or more regionalized scenarios.

Assessing the effects of management on forest growth across France: insights from a new functional-structural model.

PubMed

Guillemot, Joannès; Delpierre, Nicolas; Vallet, Patrick; François, Christophe; Martin-StPaul, Nicolas K; Soudani, Kamel; Nicolas, Manuel; Badeau, Vincent; Dufrêne, Eric

2014-09-01

The structure of a forest stand, i.e. the distribution of tree size features, has strong effects on its functioning. The management of the structure is therefore an important tool in mitigating the impact of predicted changes in climate on forests, especially with respect to drought. Here, a new functional-structural model is presented and is used to assess the effects of management on forest functioning at a national scale. The stand process-based model (PBM) CASTANEA was coupled to a stand structure module (SSM) based on empirical tree-to-tree competition rules. The calibration of the SSM was based on a thorough analysis of intersite and interannual variability of competition asymmetry. The coupled CASTANEA-SSM model was evaluated across France using forest inventory data, and used to compare the effect of contrasted silvicultural practices on simulated stand carbon fluxes and growth. The asymmetry of competition varied consistently with stand productivity at both spatial and temporal scales. The modelling of the competition rules enabled efficient prediction of changes in stand structure within the CASTANEA PBM. The coupled model predicted an increase in net primary productivity (NPP) with management intensity, resulting in higher growth. This positive effect of management was found to vary at a national scale across France: the highest increases in NPP were attained in forests facing moderate to high water stress; however, the absolute effect of management on simulated stand growth remained moderate to low because stand thinning involved changes in carbon allocation at the tree scale. This modelling approach helps to identify the areas where management efforts should be concentrated in order to mitigate near-future drought impact on national forest productivity. Around a quarter of the French temperate oak and beech forests are currently in zones of high vulnerability, where management could thus mitigate the influence of climate change on forest yield.

Markov-chain model of classified atomistic transition states for discrete kinetic Monte Carlo simulations.

PubMed

Numazawa, Satoshi; Smith, Roger

2011-10-01

Classical harmonic transition state theory is considered and applied in discrete lattice cells with hierarchical transition levels. The scheme is then used to determine transitions that can be applied in a lattice-based kinetic Monte Carlo (KMC) atomistic simulation model. The model results in an effective reduction of KMC simulation steps by utilizing a classification scheme of transition levels for thermally activated atomistic diffusion processes. Thermally activated atomistic movements are considered as local transition events constrained in potential energy wells over certain local time periods. These processes are represented by Markov chains of multidimensional Boolean valued functions in three-dimensional lattice space. The events inhibited by the barriers under a certain level are regarded as thermal fluctuations of the canonical ensemble and accepted freely. Consequently, the fluctuating system evolution process is implemented as a Markov chain of equivalence class objects. It is shown that the process can be characterized by the acceptance of metastable local transitions. The method is applied to a problem of Au and Ag cluster growth on a rippled surface. The simulation predicts the existence of a morphology-dependent transition time limit from a local metastable to stable state for subsequent cluster growth by accretion. Excellent agreement with observed experimental results is obtained.

Stock-specific advection of larval walleye (Sander vitreus) in western Lake Erie: Implications for larval growth, mixing, and stock discrimination

USGS Publications Warehouse

Fraker, Michael E.; Anderson, Eric J.; May, Cassandra J.; Chen, Kuan-Yu; Davis, Jeremiah J.; DeVanna, Kristen M.; DuFour, Mark R.; Marschall, Elizabeth A.; Mayer, Christine M.; Miner, Jeffery G.; Pangle, Kevin L.; Pritt, Jeremy J.; Roseman, Edward F.; Tyson, Jeffrey T.; Zhao, Yingming; Ludsin, Stuart A

2015-01-01

Physical processes can generate spatiotemporal heterogeneity in habitat quality for fish and also influence the overlap of pre-recruit individuals (e.g., larvae) with high-quality habitat through hydrodynamic advection. In turn, individuals from different stocks that are produced in different spawning locations or at different times may experience dissimilar habitat conditions, which can underlie within- and among-stock variability in larval growth and survival. While such physically-mediated variation has been shown to be important in driving intra- and inter-annual patterns in recruitment in marine ecosystems, its role in governing larval advection, growth, survival, and recruitment has received less attention in large lake ecosystems such as the Laurentian Great Lakes. Herein, we used a hydrodynamic model linked to a larval walleye (Sander vitreus) individual-based model to explore how the timing and location of larval walleye emergence from several spawning sites in western Lake Erie (Maumee, Sandusky, and Detroit rivers; Ohio reef complex) can influence advection pathways and mixing among these local spawning populations (stocks), and how spatiotemporal variation in thermal habitat can influence stock-specific larval growth. While basin-wide advection patterns were fairly similar during 2011 and 2012, smaller scale advection patterns and the degree of stock mixing varied both within and between years. Additionally, differences in larval growth were evident among stocks and among cohorts within stocks which were attributed to spatiotemporal differences in water temperature. Using these findings, we discuss the value of linked physical–biological models for understanding the recruitment process and addressing fisheries management problems in the world's Great Lakes.

Transformation and Sorption of Illicit Drug Biomarkers in Sewer Systems: Understanding the Role of Suspended Solids in Raw Wastewater.

PubMed

Ramin, Pedram; Libonati Brock, Andreas; Polesel, Fabio; Causanilles, Ana; Emke, Erik; de Voogt, Pim; Plósz, Benedek Gy

2016-12-20

Sewer pipelines, although primarily designed for sewage transport, can also be considered as bioreactors. In-sewer processes may lead to significant variations of chemical loadings from source release points to the treatment plant influent. In this study, we assessed in-sewer utilization of growth substrates (primary metabolic processes) and transformation of illicit drug biomarkers (secondary metabolic processes) by suspended biomass. Sixteen drug biomarkers were targeted, including mephedrone, methadone, cocaine, heroin, codeine, and tetrahydrocannabinol (THC) and their major human metabolites. Batch experiments were performed under aerobic and anaerobic conditions using raw wastewater. Abiotic biomarker transformation and partitioning to suspended solids and reactor wall were separately investigated under both redox conditions. A process model was identified by combining and extending the Wastewater Aerobic/anaerobic Transformations in Sewers (WATS) model and Activated Sludge Model for Xenobiotics (ASM-X). Kinetic and stoichiometric model parameters were estimated using experimental data via the Bayesian optimization method DREAM (ZS) . Results suggest that biomarker transformation significantly differs from aerobic to anaerobic conditions, and abiotic conversion is the dominant mechanism for many of the selected substances. Notably, an explicit description of biomass growth during batch experiments was crucial to avoid significant overestimation (up to 385%) of aerobic biotransformation rate constants. Predictions of in-sewer transformation provided here can reduce the uncertainty in the estimation of drug consumption as part of wastewater-based epidemiological studies.

Terrane accretion: Insights from numerical modelling

NASA Astrophysics Data System (ADS)

Vogt, Katharina; Gerya, Taras

2016-04-01

The oceanic crust is not homogenous, but contains significantly thicker crust than norm, i.e. extinct arcs, spreading ridges, detached continental fragments, volcanic piles or oceanic swells. These (crustal) fragments may collide with continental crust and form accretionary complexes, contributing to its growth. We analyse this process using a thermo-mechanical computer model (i2vis) of an ocean-continent subduction zone. In this model the oceanic plate can bend spontaneously under the control of visco-plastic rheologies. It moreover incorporates effects such as mineralogical phase changes, fluid release and consumption, partial melting and melt extraction. Based on our 2-D experiments we suggest that the lithospheric buoyancy of the downgoing slab and the rheological strength of crustal material may result in a variety of accretionary processes. In addition to terrane subduction, we are able to identify three distinct modes of terrane accretion: frontal accretion, basal accretion and underplating plateaus. We show that crustal fragments may dock onto continental crust and cease subduction, be scrapped off the downgoing plate, or subduct to greater depth prior to slab break off and subsequent exhumation. Direct consequences of these processes include slab break off, subduction zone transference, structural reworking, formation of high-pressure terranes, partial melting and crustal growth.

Using Design-Based Latent Growth Curve Modeling with Cluster-Level Predictor to Address Dependency

ERIC Educational Resources Information Center

Wu, Jiun-Yu; Kwok, Oi-Man; Willson, Victor L.

2014-01-01

The authors compared the effects of using the true Multilevel Latent Growth Curve Model (MLGCM) with single-level regular and design-based Latent Growth Curve Models (LGCM) with or without the higher-level predictor on various criterion variables for multilevel longitudinal data. They found that random effect estimates were biased when the…

Optimal Number and Allocation of Data Collection Points for Linear Spline Growth Curve Modeling: A Search for Efficient Designs

ERIC Educational Resources Information Center

Wu, Wei; Jia, Fan; Kinai, Richard; Little, Todd D.

2017-01-01

Spline growth modelling is a popular tool to model change processes with distinct phases and change points in longitudinal studies. Focusing on linear spline growth models with two phases and a fixed change point (the transition point from one phase to the other), we detail how to find optimal data collection designs that maximize the efficiency…

Sensitivity of open-water ice growth and ice concentration evolution in a coupled atmosphere-ocean-sea ice model

NASA Astrophysics Data System (ADS)

Shi, Xiaoxu; Lohmann, Gerrit

2017-09-01

A coupled atmosphere-ocean-sea ice model is applied to investigate to what degree the area-thickness distribution of new ice formed in open water affects the ice and ocean properties. Two sensitivity experiments are performed which modify the horizontal-to-vertical aspect ratio of open-water ice growth. The resulting changes in the Arctic sea-ice concentration strongly affect the surface albedo, the ocean heat release to the atmosphere, and the sea-ice production. The changes are further amplified through a positive feedback mechanism among the Arctic sea ice, the Atlantic Meridional Overturning Circulation (AMOC), and the surface air temperature in the Arctic, as the Fram Strait sea ice import influences the freshwater budget in the North Atlantic Ocean. Anomalies in sea-ice transport lead to changes in sea surface properties of the North Atlantic and the strength of AMOC. For the Southern Ocean, the most pronounced change is a warming along the Antarctic Circumpolar Current (ACC), owing to the interhemispheric bipolar seasaw linked to AMOC weakening. Another insight of this study lies on the improvement of our climate model. The ocean component FESOM is a newly developed ocean-sea ice model with an unstructured mesh and multi-resolution. We find that the subpolar sea-ice boundary in the Northern Hemisphere can be improved by tuning the process of open-water ice growth, which strongly influences the sea ice concentration in the marginal ice zone, the North Atlantic circulation, salinity and Arctic sea ice volume. Since the distribution of new ice on open water relies on many uncertain parameters and the knowledge of the detailed processes is currently too crude, it is a challenge to implement the processes realistically into models. Based on our sensitivity experiments, we conclude a pronounced uncertainty related to open-water sea ice growth which could significantly affect the climate system sensitivity.

Construction and Setup of a Bench-scale Algal Photosynthetic Bioreactor with Temperature, Light, and pH Monitoring for Kinetic Growth Tests.

PubMed

Karam, Amanda L; McMillan, Catherine C; Lai, Yi-Chun; de Los Reyes, Francis L; Sederoff, Heike W; Grunden, Amy M; Ranjithan, Ranji S; Levis, James W; Ducoste, Joel J

2017-06-14

The optimal design and operation of photosynthetic bioreactors (PBRs) for microalgal cultivation is essential for improving the environmental and economic performance of microalgae-based biofuel production. Models that estimate microalgal growth under different conditions can help to optimize PBR design and operation. To be effective, the growth parameters used in these models must be accurately determined. Algal growth experiments are often constrained by the dynamic nature of the culture environment, and control systems are needed to accurately determine the kinetic parameters. The first step in setting up a controlled batch experiment is live data acquisition and monitoring. This protocol outlines a process for the assembly and operation of a bench-scale photosynthetic bioreactor that can be used to conduct microalgal growth experiments. This protocol describes how to size and assemble a flat-plate, bench-scale PBR from acrylic. It also details how to configure a PBR with continuous pH, light, and temperature monitoring using a data acquisition and control unit, analog sensors, and open-source data acquisition software.

Nanophase diagram of binary eutectic Au-Ge nanoalloys for vapor-liquid-solid semiconductor nanowires growth

NASA Astrophysics Data System (ADS)

Lu, Haiming; Meng, Xiangkang

2015-06-01

Although the vapor-liquid-solid growth of semiconductor nanowire is a non-equilibrium process, the equilibrium phase diagram of binary alloy provides important guidance on the growth conditions, such as the temperature and the equilibrium composition of the alloy. Given the small dimensions of the alloy seeds and the nanowires, the known phase diagram of bulk binary alloy cannot be expected to accurately predict the behavior of the nanowire growth. Here, we developed a unified model to describe the size- and dimensionality-dependent equilibrium phase diagram of Au-Ge binary eutectic nanoalloys based on the size-dependent cohesive energy model. It is found that the liquidus curves reduce and shift leftward with decreasing size and dimensionality. Moreover, the effects of size and dimensionality on the eutectic composition are small and negligible when both components in binary eutectic alloys have the same dimensionality. However, when two components have different dimensionality (e.g. Au nanoparticle-Ge nanowire usually used in the semiconductor nanowires growth), the eutectic composition reduces with decreasing size.

Construction and Setup of a Bench-scale Algal Photosynthetic Bioreactor with Temperature, Light, and pH Monitoring for Kinetic Growth Tests

PubMed Central

Karam, Amanda L.; McMillan, Catherine C.; Lai, Yi-Chun; de los Reyes, Francis L.; Sederoff, Heike W.; Grunden, Amy M.; Ranjithan, Ranji S.; Levis, James W.; Ducoste, Joel J.

2017-01-01

The optimal design and operation of photosynthetic bioreactors (PBRs) for microalgal cultivation is essential for improving the environmental and economic performance of microalgae-based biofuel production. Models that estimate microalgal growth under different conditions can help to optimize PBR design and operation. To be effective, the growth parameters used in these models must be accurately determined. Algal growth experiments are often constrained by the dynamic nature of the culture environment, and control systems are needed to accurately determine the kinetic parameters. The first step in setting up a controlled batch experiment is live data acquisition and monitoring. This protocol outlines a process for the assembly and operation of a bench-scale photosynthetic bioreactor that can be used to conduct microalgal growth experiments. This protocol describes how to size and assemble a flat-plate, bench-scale PBR from acrylic. It also details how to configure a PBR with continuous pH, light, and temperature monitoring using a data acquisition and control unit, analog sensors, and open-source data acquisition software. PMID:28654054

A diffusion-based approach to stochastic individual growth and energy budget, with consequences to life-history optimization and population dynamics.

PubMed

Filin, I

2009-06-01

Using diffusion processes, I model stochastic individual growth, given exogenous hazards and starvation risk. By maximizing survival to final size, optimal life histories (e.g. switching size for habitat/dietary shift) are determined by two ratios: mean growth rate over growth variance (diffusion coefficient) and mortality rate over mean growth rate; all are size dependent. For example, switching size decreases with either ratio, if both are positive. I provide examples and compare with previous work on risk-sensitive foraging and the energy-predation trade-off. I then decompose individual size into reversibly and irreversibly growing components, e.g. reserves and structure. I provide a general expression for optimal structural growth, when reserves grow stochastically. I conclude that increased growth variance of reserves delays structural growth (raises threshold size for its commencement) but may eventually lead to larger structures. The effect depends on whether the structural trait is related to foraging or defence. Implications for population dynamics are discussed.

Going around the Circle Again: Exploring Kolb's Theory of Growth and Development.

ERIC Educational Resources Information Center

Johns, Krista R.

Thirty years after their development, David A. Kolb's Cycle of Learning and Learning Style Inventory are widely used to understand the stages of learning and the ways people prefer to receive and process new information. The model and the self-assessment are both based on Kolb's experiential learning theory, which emphasizes the need for learner…

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.

The stochastic dance of early HIV infection

NASA Astrophysics Data System (ADS)

Merrill, Stephen J.

2005-12-01

The stochastic nature of early HIV infection is described in a series of models, each of which captures aspects of the dance of HIV during the early stages of infection. It is to this highly variable target that the immune response must respond. The adaptability of the various components of the immune response is an important aspect of the system's operation, as the nature of the pathogens that the response will be required to respond to and the order in which those responses must be made cannot be known beforehand. As HIV infection has direct influence over cells responsible for the immune response, the dance predicts that the immune response will be also in a variable state of readiness and capability for this task of adaptation. The description of the stochastic dance of HIV here will use the tools of stochastic models, and for the most part, simulation. The justification for this approach is that the early stages and the development of HIV diversity require that the model to be able to describe both individual sample path and patient-to-patient variability. In addition, as early viral dynamics are best described using branching processes, the explosive growth of these models both predicts high variability and rapid response of HIV to changes in system parameters.In this paper, a basic viral growth model based on a time dependent continuous-time branching process is used to describe the growth of HIV infected cells in the macrophage and lymphocyte populations. Immigration from the reservoir population is added to the basic model to describe the incubation time distribution. This distribution is deduced directly from the modeling assumptions and the model of viral growth. A system of two branching processes, one in the infected macrophage population and one in the infected lymphocyte population is used to provide a description of the relationship between the development of HIV diversity as it relates to tropism (host cell preference). The role of the immune response to HIV and HIV infected cells is used to describe the movement of the infection from a few infected macrophages to a disease of infected CD4+ T lymphocytes.

Growth dynamics of SiGe nanowires by the vapour-liquid-solid method and its impact on SiGe/Si axial heterojunction abruptness.

PubMed

Pura, J L; Periwal, P; Baron, T; Jiménez, J

2018-08-31

The vapour-liquid-solid (VLS) method is by far the most extended procedure for bottom-up nanowire growth. This method also allows for the manufacture of nanowire axial heterojunctions in a straightforward way. To do this, during the growth process, precursor gases are switched on/off to obtain the desired change in the nanowire composition. Using this technique, axially heterostructured nanowires can be grown, which are crucial for the fabrication of electronic and optoelectronic devices. SiGe/Si nanowires are compatible with complementary metal oxide semiconductor (CMOS) technology, which improves their versatility and the possibility of integration with current electronic technologies. Abrupt heterointerfaces are fundamental for the development and correct operation of electronic and optoelectronic devices. Unfortunately, the VLS growth of SiGe/Si heterojunctions does not provide abrupt transitions because of the high solubility of group IV semiconductors in Au, with the corresponding reservoir effect that precludes the growth of sharp interfaces. In this work, we studied the growth dynamics of SiGe/Si heterojunctions based on already developed models for VLS growth. A composition map of the Si-Ge-Au liquid alloy is proposed to better understand the impact of the growing conditions on the nanowire growth process and the heterojunction formation. The solution of our model provides heterojunction profiles that are in good agreement with the experimental measurements. Finally, an in-depth study of the composition map provides a practical approach to the drastic reduction of heterojunction abruptness by reducing the Si and Ge concentrations in the catalyst droplet. This converges with previous approaches, which use catalysts aiming to reduce the solubility of the atomic species. This analysis opens new paths to the reduction of heterojunction abruptness using Au catalysts, but the model can be naturally extended to other catalysts and semiconductors.

Numerical, micro-mechanical prediction of crack growth resistance in a fibre-reinforced/brittle matrix composite

NASA Technical Reports Server (NTRS)

Jenkins, Michael G.; Ghosh, Asish; Salem, Jonathan A.

1990-01-01

Micromechanics fracture models are incorporated into three distinct fracture process zones which contribute to the crack growth resistance of fibrous composites. The frontal process zone includes microcracking, fiber debonding, and some fiber failure. The elastic process zone is related only to the linear elastic creation of new matrix and fiber fracture surfaces. The wake process zone includes fiber bridging, fiber pullout, and fiber breakage. The R-curve predictions of the model compare well with empirical results for a unidirectional, continuous fiber C/C composite. Separating the contributions of each process zone reveals the wake region to contain the dominant crack growth resistance mechanisms. Fractography showed the effects of the micromechanisms on the macroscopic fracture behavior.

Experimental, theoretical, and device application development of nanoscale focused electron-beam-induced deposition

NASA Astrophysics Data System (ADS)

Randolph, Steven Jeffrey

Electron-beam-induced deposition (EBID) is a highly versatile nanofabrication technique that allows for growth of a variety of materials with nanoscale precision and resolution. While several applications and studies of EBID have been reported and published, there is still a significant lack of understanding of the complex mechanisms involved in the process. Consequently, EBID process control is, in general, limited and certain common experimental results regarding nanofiber growth have yet to be fully explained. Such anomalous results have been addressed in this work both experimentally and by computer simulation. Specifically, a correlation between SiOx nanofiber deposition observations and the phenomenon of electron beam heating (EBH) was shown by comparison of thermal computer models and experimental results. Depending on the beam energy, beam current, and nanostructure geometry, the heat generated can be substantial and may influence the deposition rate. Temperature dependent EBID growth experiments qualitatively verified the results of the EBH model. Additionally, EBID was used to produce surface image layers for maskless, direct-write lithography (MDL). A single layer process used directly written SiOx features as a masking layer for amorphous silicon thin films. A bilayer process implemented a secondary masking layer consisting of standard photoresist into which a pattern---directly written by EBID tungsten---was transferred. The single layer process was found to be extremely sensitive to the etch selectivity of the plasma etch. In the bilayer process, EBID tungsten was written onto photoresist and the pattern transferred by means of oxygen plasma dry development following a brief refractory descum. Conditions were developed to reduce the spatial spread of electrons in the photoresist layer and obtain ˜ 35 nm lines. Finally, an EBID-based technique for field emitter repair was applied to the Digital Electrostatically focused e-beam Array Lithography (DEAL) parallel electron beam lithography configuration to repair damaged or missing carbon nanofiber cathodes. The I-V response and lithography results from EBID tungsten-based devices were comparable to CNF-based DEAL devices indicating a successful repair technique.