A new region-edge based level set model with applications to image segmentation

NASA Astrophysics Data System (ADS)

Zhi, Xuhao; Shen, Hong-Bin

2018-04-01

Level set model has advantages in handling complex shapes and topological changes, and is widely used in image processing tasks. The image segmentation oriented level set models can be grouped into region-based models and edge-based models, both of which have merits and drawbacks. Region-based level set model relies on fitting to color intensity of separated regions, but is not sensitive to edge information. Edge-based level set model evolves by fitting to local gradient information, but can get easily affected by noise. We propose a region-edge based level set model, which considers saliency information into energy function and fuses color intensity with local gradient information. The evolution of the proposed model is implemented by a hierarchical two-stage protocol, and the experimental results show flexible initialization, robust evolution and precise segmentation.

Phylogenetic analyses of mode of larval development.

PubMed

Hart, M

2000-12-01

Phylogenies based on morphological or molecular characters have been used to provide an evolutionary context for analysis of larval evolution. Studies of gastropods, bivalves, tunicates, sea stars, sea urchins, and polychaetes have revealed massive parallel evolution of similar larval forms. Some of these studies were designed to test, and have rejected, the species selection hypothesis for evolutionary trends in the frequency of derived larvae or life history traits. However, the lack of well supported models of larval character evolution leave some doubt about the quality of inferences of larval evolution from phylogenies of living taxa. Better models based on maximum likelihood methods and known prior probabilities of larval character state changes will improve our understanding of the history of larval evolution. Copyright 2000 Academic Press.

Asymptotic stability of spectral-based PDF modeling for homogeneous turbulent flows

NASA Astrophysics Data System (ADS)

Campos, Alejandro; Duraisamy, Karthik; Iaccarino, Gianluca

2015-11-01

Engineering models of turbulence, based on one-point statistics, neglect spectral information inherent in a turbulence field. It is well known, however, that the evolution of turbulence is dictated by a complex interplay between the spectral modes of velocity. For example, for homogeneous turbulence, the pressure-rate-of-strain depends on the integrated energy spectrum weighted by components of the wave vectors. The Interacting Particle Representation Model (IPRM) (Kassinos & Reynolds, 1996) and the Velocity/Wave-Vector PDF model (Van Slooten & Pope, 1997) emulate spectral information in an attempt to improve the modeling of turbulence. We investigate the evolution and asymptotic stability of the IPRM using three different approaches. The first approach considers the Lagrangian evolution of individual realizations (idealized as particles) of the stochastic process defined by the IPRM. The second solves Lagrangian evolution equations for clusters of realizations conditional on a given wave vector. The third evolves the solution of the Eulerian conditional PDF corresponding to the aforementioned clusters. This last method avoids issues related to discrete particle noise and slow convergence associated with Lagrangian particle-based simulations.

Evolvable social agents for bacterial systems modeling.

PubMed

Paton, Ray; Gregory, Richard; Vlachos, Costas; Saunders, Jon; Wu, Henry

2004-09-01

We present two approaches to the individual-based modeling (IbM) of bacterial ecologies and evolution using computational tools. The IbM approach is introduced, and its important complementary role to biosystems modeling is discussed. A fine-grained model of bacterial evolution is then presented that is based on networks of interactivity between computational objects representing genes and proteins. This is followed by a coarser grained agent-based model, which is designed to explore the evolvability of adaptive behavioral strategies in artificial bacteria represented by learning classifier systems. The structure and implementation of the two proposed individual-based bacterial models are discussed, and some results from simulation experiments are presented, illustrating their adaptive properties.

Gamma Prime Precipitate Evolution During Aging of a Model Nickel-Based Superalloy

NASA Astrophysics Data System (ADS)

Goodfellow, A. J.; Galindo-Nava, E. I.; Christofidou, K. A.; Jones, N. G.; Martin, T.; Bagot, P. A. J.; Boyer, C. D.; Hardy, M. C.; Stone, H. J.

2018-03-01

The microstructural stability of nickel-based superalloys is critical for maintaining alloy performance during service in gas turbine engines. In this study, the precipitate evolution in a model polycrystalline Ni-based superalloy during aging to 1000 hours has been studied via transmission electron microscopy, atom probe tomography, and neutron diffraction. Variations in phase composition and precipitate morphology, size, and volume fraction were observed during aging, while the constrained lattice misfit remained constant at approximately zero. The experimental composition of the γ matrix phase was consistent with thermodynamic equilibrium predictions, while significant differences were identified between the experimental and predicted results from the γ' phase. These results have implications for the evolution of mechanical properties in service and their prediction using modeling methods.

Research program for a search of the origin of Darwinian evolution. Research program for a vesicle-based model of the origin of Darwinian evolution on prebiotic early Earth

NASA Astrophysics Data System (ADS)

Tessera, Marc

2017-03-01

The search for origin of `life' is made even more complicated by differing definitions of the subject matter, although a general consensus is that an appropriate definition should center on Darwinian evolution (Cleland and Chyba 2002). Within a physical approach which has been defined as a level-4 evolution (Tessera and Hoelzer 2013), one mechanism could be described showing that only three conditions are required to allow natural selection to apply to populations of different system lineages. This approach leads to a vesicle- based model with the necessary properties. Of course such a model has to be tested. Thus, after a brief presentation of the model an experimental program is proposed that implements the different steps able to show whether this new direction of the research in the field is valid and workable.

Research program for a search of the origin of Darwinian evolution : Research program for a vesicle-based model of the origin of Darwinian evolution on prebiotic early Earth.

PubMed

Tessera, Marc

2017-03-01

The search for origin of 'life' is made even more complicated by differing definitions of the subject matter, although a general consensus is that an appropriate definition should center on Darwinian evolution (Cleland and Chyba 2002). Within a physical approach which has been defined as a level-4 evolution (Tessera and Hoelzer 2013), one mechanism could be described showing that only three conditions are required to allow natural selection to apply to populations of different system lineages. This approach leads to a vesicle- based model with the necessary properties. Of course such a model has to be tested. Thus, after a brief presentation of the model an experimental program is proposed that implements the different steps able to show whether this new direction of the research in the field is valid and workable.

In silico modelling of directed evolution: Implications for experimental design and stepwise evolution.

PubMed

Wedge, David C; Rowe, William; Kell, Douglas B; Knowles, Joshua

2009-03-07

We model the process of directed evolution (DE) in silico using genetic algorithms. Making use of the NK fitness landscape model, we analyse the effects of mutation rate, crossover and selection pressure on the performance of DE. A range of values of K, the epistatic interaction of the landscape, are considered, and high- and low-throughput modes of evolution are compared. Our findings suggest that for runs of or around ten generations' duration-as is typical in DE-there is little difference between the way in which DE needs to be configured in the high- and low-throughput regimes, nor across different degrees of landscape epistasis. In all cases, a high selection pressure (but not an extreme one) combined with a moderately high mutation rate works best, while crossover provides some benefit but only on the less rugged landscapes. These genetic algorithms were also compared with a "model-based approach" from the literature, which uses sequential fixing of the problem parameters based on fitting a linear model. Overall, we find that purely evolutionary techniques fare better than do model-based approaches across all but the smoothest landscapes.

History, Epidemic Evolution, and Model Burn-In for a Network of Annual Invasion: Soybean Rust.

PubMed

Sanatkar, M R; Scoglio, C; Natarajan, B; Isard, S A; Garrett, K A

2015-07-01

Ecological history may be an important driver of epidemics and disease emergence. We evaluated the role of history and two related concepts, the evolution of epidemics and the burn-in period required for fitting a model to epidemic observations, for the U.S. soybean rust epidemic (caused by Phakopsora pachyrhizi). This disease allows evaluation of replicate epidemics because the pathogen reinvades the United States each year. We used a new maximum likelihood estimation approach for fitting the network model based on observed U.S. epidemics. We evaluated the model burn-in period by comparing model fit based on each combination of other years of observation. When the miss error rates were weighted by 0.9 and false alarm error rates by 0.1, the mean error rate did decline, for most years, as more years were used to construct models. Models based on observations in years closer in time to the season being estimated gave lower miss error rates for later epidemic years. The weighted mean error rate was lower in backcasting than in forecasting, reflecting how the epidemic had evolved. Ongoing epidemic evolution, and potential model failure, can occur because of changes in climate, host resistance and spatial patterns, or pathogen evolution.

Coronal hole evolution from multi-viewpoint data as input for a STEREO solar wind speed persistence model

NASA Astrophysics Data System (ADS)

Temmer, Manuela; Hinterreiter, Jürgen; Reiss, Martin A.

2018-03-01

We present a concept study of a solar wind forecasting method for Earth, based on persistence modeling from STEREO in situ measurements combined with multi-viewpoint EUV observational data. By comparing the fractional areas of coronal holes (CHs) extracted from EUV data of STEREO and SoHO/SDO, we perform an uncertainty assessment derived from changes in the CHs and apply those changes to the predicted solar wind speed profile at 1 AU. We evaluate the method for the time period 2008-2012, and compare the results to a persistence model based on ACE in situ measurements and to the STEREO persistence model without implementing the information on CH evolution. Compared to an ACE based persistence model, the performance of the STEREO persistence model which takes into account the evolution of CHs, is able to increase the number of correctly predicted high-speed streams by about 12%, and to decrease the number of missed streams by about 23%, and the number of false alarms by about 19%. However, the added information on CH evolution is not able to deliver more accurate speed values for the forecast than using the STEREO persistence model without CH information which performs better than an ACE based persistence model. Investigating the CH evolution between STEREO and Earth view for varying separation angles over ˜25-140° East of Earth, we derive some relation between expanding CHs and increasing solar wind speed, but a less clear relation for decaying CHs and decreasing solar wind speed. This fact most likely prevents the method from making more precise forecasts. The obtained results support a future L5 mission and show the importance and valuable contribution using multi-viewpoint data.

The Evolution of ICT Markets: An Agent-Based Model on Complex Networks

NASA Astrophysics Data System (ADS)

Zhao, Liangjie; Wu, Bangtao; Chen, Zhong; Li, Li

Information and communication technology (ICT) products exhibit positive network effects.The dynamic process of ICT markets evolution has two intrinsic characteristics: (1) customers are influenced by each others’ purchasing decision; (2) customers are intelligent agents with bounded rationality.Guided by complex systems theory, we construct an agent-based model and simulate on complex networks to examine how the evolution can arise from the interaction of customers, which occur when they make expectations about the future installed base of a product by the fraction of neighbors who are using the same product in his personal network.We demonstrate that network effects play an important role in the evolution of markets share, which make even an inferior product can dominate the whole market.We also find that the intensity of customers’ communication can influence whether the best initial strategy for firms is to improve product quality or expand their installed base.

Deep Drawing Simulations With Different Polycrystalline Models

NASA Astrophysics Data System (ADS)

Duchêne, Laurent; de Montleau, Pierre; Bouvier, Salima; Habraken, Anne Marie

2004-06-01

The goal of this research is to study the anisotropic material behavior during forming processes, represented by both complex yield loci and kinematic-isotropic hardening models. A first part of this paper describes the main concepts of the `Stress-strain interpolation' model that has been implemented in the non-linear finite element code Lagamine. This model consists of a local description of the yield locus based on the texture of the material through the full constraints Taylor's model. The texture evolution due to plastic deformations is computed throughout the FEM simulations. This `local yield locus' approach was initially linked to the classical isotropic Swift hardening law. Recently, a more complex hardening model was implemented: the physically-based microstructural model of Teodosiu. It takes into account intergranular heterogeneity due to the evolution of dislocation structures, that affects isotropic and kinematic hardening. The influence of the hardening model is compared to the influence of the texture evolution thanks to deep drawing simulations.

A Cyclic-Plasticity-Based Mechanistic Approach for Fatigue Evaluation of 316 Stainless Steel Under Arbitrary Loading

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

Barua, Bipul; Mohanty, Subhasish; Listwan, Joseph T.

In this paper, a cyclic-plasticity based fully mechanistic fatigue modeling approach is presented. This is based on time-dependent stress-strain evolution of the material over the entire fatigue life rather than just based on the end of live information typically used for empirical S~N curve based fatigue evaluation approaches. Previously we presented constant amplitude fatigue test based related material models for 316 SS base, 508 LAS base and 316 SS- 316 SS weld which are used in nuclear reactor components such as pressure vessels, nozzles, and surge line pipes. However, we found that constant amplitude fatigue data based models have limitationmore » in capturing the stress-strain evolution under arbitrary fatigue loading. To address the above mentioned limitation, in this paper, we present a more advanced approach that can be used for modeling the cyclic stress-strain evolution and fatigue life not only under constant amplitude but also under any arbitrary (random/variable) fatigue loading. The related material model and analytical model results are presented for 316 SS base metal. Two methodologies (either based on time/cycle or based on accumulated plastic strain energy) to track the material parameters at a given time/cycle are discussed and associated analytical model results are presented. From the material model and analytical cyclic plasticity model results, it is found that the proposed cyclic plasticity model can predict all the important stages of material behavior during the entire fatigue life of the specimens with more than 90% accuracy« less

A Cyclic-Plasticity-Based Mechanistic Approach for Fatigue Evaluation of 316 Stainless Steel Under Arbitrary Loading

DOE PAGES

Barua, Bipul; Mohanty, Subhasish; Listwan, Joseph T.; ...

2017-12-05

In this paper, a cyclic-plasticity based fully mechanistic fatigue modeling approach is presented. This is based on time-dependent stress-strain evolution of the material over the entire fatigue life rather than just based on the end of live information typically used for empirical S~N curve based fatigue evaluation approaches. Previously we presented constant amplitude fatigue test based related material models for 316 SS base, 508 LAS base and 316 SS- 316 SS weld which are used in nuclear reactor components such as pressure vessels, nozzles, and surge line pipes. However, we found that constant amplitude fatigue data based models have limitationmore » in capturing the stress-strain evolution under arbitrary fatigue loading. To address the above mentioned limitation, in this paper, we present a more advanced approach that can be used for modeling the cyclic stress-strain evolution and fatigue life not only under constant amplitude but also under any arbitrary (random/variable) fatigue loading. The related material model and analytical model results are presented for 316 SS base metal. Two methodologies (either based on time/cycle or based on accumulated plastic strain energy) to track the material parameters at a given time/cycle are discussed and associated analytical model results are presented. From the material model and analytical cyclic plasticity model results, it is found that the proposed cyclic plasticity model can predict all the important stages of material behavior during the entire fatigue life of the specimens with more than 90% accuracy« less

Local Orientation and the Evolution of Foraging: Changes in Decision Making Can Eliminate Evolutionary Trade-offs

PubMed Central

van der Post, Daniel J.; Semmann, Dirk

2011-01-01

Information processing is a major aspect of the evolution of animal behavior. In foraging, responsiveness to local feeding opportunities can generate patterns of behavior which reflect or “recognize patterns” in the environment beyond the perception of individuals. Theory on the evolution of behavior generally neglects such opportunity-based adaptation. Using a spatial individual-based model we study the role of opportunity-based adaptation in the evolution of foraging, and how it depends on local decision making. We compare two model variants which differ in the individual decision making that can evolve (restricted and extended model), and study the evolution of simple foraging behavior in environments where food is distributed either uniformly or in patches. We find that opportunity-based adaptation and the pattern recognition it generates, plays an important role in foraging success, particularly in patchy environments where one of the main challenges is “staying in patches”. In the restricted model this is achieved by genetic adaptation of move and search behavior, in light of a trade-off on within- and between-patch behavior. In the extended model this trade-off does not arise because decision making capabilities allow for differentiated behavioral patterns. As a consequence, it becomes possible for properties of movement to be specialized for detection of patches with more food, a larger scale information processing not present in the restricted model. Our results show that changes in decision making abilities can alter what kinds of pattern recognition are possible, eliminate an evolutionary trade-off and change the adaptive landscape. PMID:21998571

Local orientation and the evolution of foraging: changes in decision making can eliminate evolutionary trade-offs.

PubMed

van der Post, Daniel J; Semmann, Dirk

2011-10-01

Information processing is a major aspect of the evolution of animal behavior. In foraging, responsiveness to local feeding opportunities can generate patterns of behavior which reflect or "recognize patterns" in the environment beyond the perception of individuals. Theory on the evolution of behavior generally neglects such opportunity-based adaptation. Using a spatial individual-based model we study the role of opportunity-based adaptation in the evolution of foraging, and how it depends on local decision making. We compare two model variants which differ in the individual decision making that can evolve (restricted and extended model), and study the evolution of simple foraging behavior in environments where food is distributed either uniformly or in patches. We find that opportunity-based adaptation and the pattern recognition it generates, plays an important role in foraging success, particularly in patchy environments where one of the main challenges is "staying in patches". In the restricted model this is achieved by genetic adaptation of move and search behavior, in light of a trade-off on within- and between-patch behavior. In the extended model this trade-off does not arise because decision making capabilities allow for differentiated behavioral patterns. As a consequence, it becomes possible for properties of movement to be specialized for detection of patches with more food, a larger scale information processing not present in the restricted model. Our results show that changes in decision making abilities can alter what kinds of pattern recognition are possible, eliminate an evolutionary trade-off and change the adaptive landscape.

An Analysis on a Negotiation Model Based on Multiagent Systems with Symbiotic Learning and Evolution

NASA Astrophysics Data System (ADS)

Hossain, Md. Tofazzal

This study explores an evolutionary analysis on a negotiation model based on Masbiole (Multiagent Systems with Symbiotic Learning and Evolution) which has been proposed as a new methodology of Multiagent Systems (MAS) based on symbiosis in the ecosystem. In Masbiole, agents evolve in consideration of not only their own benefits and losses, but also the benefits and losses of opponent agents. To aid effective application of Masbiole, we develop a competitive negotiation model where rigorous and advanced intelligent decision-making mechanisms are required for agents to achieve solutions. A Negotiation Protocol is devised aiming at developing a set of rules for agents' behavior during evolution. Simulations use a newly developed evolutionary computing technique, called Genetic Network Programming (GNP) which has the directed graph-type gene structure that can develop and design the required intelligent mechanisms for agents. In a typical scenario, competitive negotiation solutions are reached by concessions that are usually predetermined in the conventional MAS. In this model, however, not only concession is determined automatically by symbiotic evolution (making the system intelligent, automated, and efficient) but the solution also achieves Pareto optimal automatically.

TA [B] Predicting Microstructure-Creep Resistance Correlation in High Temperature Alloys over Multiple Time Scales

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

Tomar, Vikas

2017-03-06

DoE-NETL partnered with Purdue University to predict the creep and associated microstructure evolution of tungsten-based refractory alloys. Researchers use grain boundary (GB) diagrams, a new concept, to establish time-dependent creep resistance and associated microstructure evolution of grain boundaries/intergranular films GB/IGF controlled creep as a function of load, environment, and temperature. The goal was to conduct a systematic study that includes the development of a theoretical framework, multiscale modeling, and experimental validation using W-based body-centered-cubic alloys, doped/alloyed with one or two of the following elements: nickel, palladium, cobalt, iron, and copper—typical refractory alloys. Prior work has already established and validated amore » basic theory for W-based binary and ternary alloys; the study conducted under this project extended this proven work. Based on interface diagrams phase field models were developed to predict long term microstructural evolution. In order to validate the models nanoindentation creep data was used to elucidate the role played by the interface properties in predicting long term creep strength and microstructure evolution.« less

Stellar Parameters, Chemical composition and Models of chemical evolution

NASA Astrophysics Data System (ADS)

Mishenina, T.; Pignatari, M.; Côté, B.; Thielemann, F.-K.; Soubiran, C.; Basak, N.; Gorbaneva, T.; Korotin, S. A.; Kovtyukh, V. V.; Wehmeyer, B.; Bisterzo, S.; Travaglio, C.; Gibson, B. K.; Jordan, C.; Paul, A.; Ritter, C.; Herwig, F.

2018-04-01

We present an in-depth study of metal-poor stars, based high resolution spectra combined with newly released astrometric data from Gaia, with special attention to observational uncertainties. The results are compared to those of other studies, including Gaia benchmark stars. Chemical evolution models are discussed, highlighting few puzzles that are still affecting our understanding of stellar nucleosynthesis and of the evolution of our Galaxy.

Active contour-based visual tracking by integrating colors, shapes, and motions.

PubMed

Hu, Weiming; Zhou, Xue; Li, Wei; Luo, Wenhan; Zhang, Xiaoqin; Maybank, Stephen

2013-05-01

In this paper, we present a framework for active contour-based visual tracking using level sets. The main components of our framework include contour-based tracking initialization, color-based contour evolution, adaptive shape-based contour evolution for non-periodic motions, dynamic shape-based contour evolution for periodic motions, and the handling of abrupt motions. For the initialization of contour-based tracking, we develop an optical flow-based algorithm for automatically initializing contours at the first frame. For the color-based contour evolution, Markov random field theory is used to measure correlations between values of neighboring pixels for posterior probability estimation. For adaptive shape-based contour evolution, the global shape information and the local color information are combined to hierarchically evolve the contour, and a flexible shape updating model is constructed. For the dynamic shape-based contour evolution, a shape mode transition matrix is learnt to characterize the temporal correlations of object shapes. For the handling of abrupt motions, particle swarm optimization is adopted to capture the global motion which is applied to the contour in the current frame to produce an initial contour in the next frame.

A resonance based model of biological evolution

NASA Astrophysics Data System (ADS)

Damasco, Achille; Giuliani, Alessandro

2017-04-01

We propose a coarse grained physical model of evolution. The proposed model 'at least in principle' is amenable of an experimental verification even if this looks as a conundrum: evolution is a unique historical process and the tape cannot be reversed and played again. Nevertheless, we can imagine a phenomenological scenario tailored upon state transitions in physical chemistry in which different agents of evolution play the role of the elements of a state transition like thermal noise or resonance effects. The abstract model we propose can be of help for sketching hypotheses and getting rid of some well-known features of natural history like the so-called Cambrian explosion. The possibility of an experimental proof of the model is discussed as well.

Introductory Biology Students' Conceptual Models and Explanations of the Origin of Variation

ERIC Educational Resources Information Center

Bray Speth, Elena; Shaw, Neil; Momsen, Jennifer; Reinagel, Adam; Le, Paul; Taqieddin, Ranya; Long, Tammy

2014-01-01

Mutation is the key molecular mechanism generating phenotypic variation, which is the basis for evolution. In an introductory biology course, we used a model-based pedagogy that enabled students to integrate their understanding of genetics and evolution within multiple case studies. We used student-generated conceptual models to assess…

A Micro-Mechanism-Based Continuum Corrosion Fatigue Damage Model for Steels

NASA Astrophysics Data System (ADS)

Sun, Bin; Li, Zhaoxia

2018-05-01

A micro-mechanism-based corrosion fatigue damage model is developed for studying the high-cycle corrosion fatigue of steel from multi-scale viewpoint. The developed physical corrosion fatigue damage model establishes micro-macro relationships between macroscopic continuum damage evolution and collective evolution behavior of microscopic pits and cracks, which can be used to describe the multi-scale corrosion fatigue process of steel. As a case study, the model is used to predict continuum damage evolution and number density of the corrosion pit and short crack of steel component in 5% NaCl water under constant stress amplitude at 20 kHz, and the numerical results are compared with experimental results. It shows that the model is effective and can be used to evaluate the continuum macroscopic corrosion fatigue damage and study microscopic corrosion fatigue mechanisms of steel.

A Micro-Mechanism-Based Continuum Corrosion Fatigue Damage Model for Steels

NASA Astrophysics Data System (ADS)

Sun, Bin; Li, Zhaoxia

2018-04-01

A micro-mechanism-based corrosion fatigue damage model is developed for studying the high-cycle corrosion fatigue of steel from multi-scale viewpoint. The developed physical corrosion fatigue damage model establishes micro-macro relationships between macroscopic continuum damage evolution and collective evolution behavior of microscopic pits and cracks, which can be used to describe the multi-scale corrosion fatigue process of steel. As a case study, the model is used to predict continuum damage evolution and number density of the corrosion pit and short crack of steel component in 5% NaCl water under constant stress amplitude at 20 kHz, and the numerical results are compared with experimental results. It shows that the model is effective and can be used to evaluate the continuum macroscopic corrosion fatigue damage and study microscopic corrosion fatigue mechanisms of steel.

Topographic evolution of orogens: The long term perspective

NASA Astrophysics Data System (ADS)

Robl, Jörg; Hergarten, Stefan; Prasicek, Günther

2017-04-01

The landscape of mountain ranges reflects the competition of tectonics and climate, that build up and destroy topography, respectively. While there is a broad consensus on the acting processes, there is a vital debate whether the topography of individual orogens reflects stages of growth, steady-state or decay. This debate is fuelled by the million-year time scales hampering direct observations on landscape evolution in mountain ranges, the superposition of various process patterns and the complex interactions among different processes. In this presentation we focus on orogen-scale landscape evolution based on time-dependent numerical models and explore model time series to constrain the development of mountain range topography during an orogenic cycle. The erosional long term response of rivers and hillslopes to uplift can be mathematically formalised by the stream power and mass diffusion equations, respectively, which enables us to describe the time-dependent evolution of topography in orogens. Based on a simple one-dimensional model consisting of two rivers separated by a watershed we explain the influence of uplift rate and rock erodibility on steady-state channel profiles and show the time-dependent development of the channel - drainage divide system. The effect of dynamic drainage network reorganization adds additional complexity and its effect on topography is explored on the basis of two-dimensional models. Further complexity is introduced by coupling a mechanical model (thin viscous sheet approach) describing continental collision, crustal thickening and topography formation with a stream power-based landscape evolution model. Model time series show the impact of crustal deformation on drainage networks and consequently on the evolution of mountain range topography (Robl et al., in review). All model outcomes, from simple one-dimensional to coupled two dimensional models are presented as movies featuring a high spatial and temporal resolution. Robl, J., S. Hergarten, and G. Prasicek (in review), The topographic state of mountain ranges, Earth Science Reviews.

Computational modeling of bedform evolution in rivers with implications for predictions of flood stage and bed evolution

USGS Publications Warehouse

Nelson, Jonathan M.; Shimizu, Yasuyuki; Giri, Sanjay; McDonald, Richard R.

2010-01-01

Uncertainties in flood stage prediction and bed evolution in rivers are frequently associated with the evolution of bedforms over a hydrograph. For the case of flood prediction, the evolution of the bedforms may alter the effective bed roughness, so predictions of stage and velocity based on assuming bedforms retain the same size and shape over a hydrograph will be incorrect. These same effects will produce errors in the prediction of the sediment transport and bed evolution, but in this latter case the errors are typically larger, as even small errors in the prediction of bedform form drag can make very large errors in predicting the rates of sediment motion and the associated erosion and deposition. In situations where flows change slowly, it may be possible to use empirical results that relate bedform morphology to roughness and effective form drag to avoid these errors; but in many cases where the bedforms evolve rapidly and are in disequilibrium with the instantaneous flow, these empirical methods cannot be accurately applied. Over the past few years, computational models for bedform development, migration, and adjustment to varying flows have been developed and tested with a variety of laboratory and field data. These models, which are based on detailed multidimensional flow modeling incorporating large eddy simulation, appear to be capable of predicting bedform dimensions during steady flows as well as their time dependence during discharge variations. In the work presented here, models of this type are used to investigate the impacts of bedform on stage and bed evolution in rivers during flood hydrographs. The method is shown to reproduce hysteresis in rating curves as well as other more subtle effects in the shape of flood waves. Techniques for combining the bedform evolution models with larger-scale models for river reach flow, sediment transport, and bed evolution are described and used to show the importance of including dynamic bedform effects in river modeling. For example calculations for a flood on the Kootenai River, errors of almost 1m in predicted stage and errors of about a factor of two in the predicted maximum depths of erosion can be attributed to bedform evolution. Thus, treating bedforms explicitly in flood and bed evolution models can decrease uncertainty and increase the accuracy of predictions.

Toward Agent-Based Models of the Development And Evolution of Business Relations and Networks

NASA Astrophysics Data System (ADS)

Wilkinson, Ian F.; Marks, Robert E.; Young, Louise

Firms achieve competitive advantage in part through the development of cooperative relations with other firms and organisations. We describe a program of research designed to map and model the development of cooperative inter-firm relations, including the processes and paths by which firms may evolve from adversarial to more cooperative relations. Narrative-event-history methods will be used to develop stylised histories of the emergence of business relations in various contexts and to identify relevant causal mechanisms to be included in the agent-based models of relationship and network evolution. The relationship histories will provide the means of assuring the agent-based models developed.

Community evolution mining and analysis in social network

NASA Astrophysics Data System (ADS)

Liu, Hongtao; Tian, Yuan; Liu, Xueyan; Jian, Jie

2017-03-01

With the development of digital and network technology, various social platforms emerge. These social platforms have greatly facilitated access to information, attracting more and more users. They use these social platforms every day to work, study and communicate, so every moment social platforms are generating massive amounts of data. These data can often be modeled as complex networks, making large-scale social network analysis possible. In this paper, the existing evolution classification model of community has been improved based on community evolution relationship over time in dynamic social network, and the Evolution-Tree structure is proposed which can show the whole life cycle of the community more clearly. The comparative test result shows that the improved model can excavate the evolution relationship of the community well.

Multi-Topic Tracking Model for dynamic social network

NASA Astrophysics Data System (ADS)

Li, Yuhua; Liu, Changzheng; Zhao, Ming; Li, Ruixuan; Xiao, Hailing; Wang, Kai; Zhang, Jun

2016-07-01

The topic tracking problem has attracted much attention in the last decades. However, existing approaches rarely consider network structures and textual topics together. In this paper, we propose a novel statistical model based on dynamic bayesian network, namely Multi-Topic Tracking Model for Dynamic Social Network (MTTD). It takes influence phenomenon, selection phenomenon, document generative process and the evolution of textual topics into account. Specifically, in our MTTD model, Gibbs Random Field is defined to model the influence of historical status of users in the network and the interdependency between them in order to consider the influence phenomenon. To address the selection phenomenon, a stochastic block model is used to model the link generation process based on the users' interests to topics. Probabilistic Latent Semantic Analysis (PLSA) is used to describe the document generative process according to the users' interests. Finally, the dependence on the historical topic status is also considered to ensure the continuity of the topic itself in topic evolution model. Expectation Maximization (EM) algorithm is utilized to estimate parameters in the proposed MTTD model. Empirical experiments on real datasets show that the MTTD model performs better than Popular Event Tracking (PET) and Dynamic Topic Model (DTM) in generalization performance, topic interpretability performance, topic content evolution and topic popularity evolution performance.

The "New Family" Model: The Evolution of Group Treatment for Adult Survivors of Childhood Sexual Abuse.

ERIC Educational Resources Information Center

Kriedler, Maryhelen C.; Fluharty, Leslie Barnes

1994-01-01

Discusses the evolution of a group therapy protocol for adult survivors of incest and the theoretical model on which it is based, the learned helplessness model of depression. Learned helplessness theory supports the assumption that victims internalize trauma. Group activities were aimed at changing negative self-beliefs and at providing…

Full three-dimensional morphology evolution of amorphous thin films for atomic layer deposition

NASA Astrophysics Data System (ADS)

Jin, Lingpeng; Li, Yawei; Hu, Zhigao; Chu, Junhao

2018-04-01

We introduce a Monte Carlo model based on random deposition and diffusion limited aggregation in order to study the morphological evolution of deposition of nanofilm, which is difficult to carry out by the experimental methods. The instantaneous evolution of morphology and the corresponding parameters are observed when employing a novel perspective, modeling the aggregation of nanoscale units. Despite simplifying the chemical details, the simulation results qualitatively describe experiments with bulky precursors, and the strong dependence of growth rate on steric hindrance is obtained. Moreover, the well know behavior that the delay before steady growth is accurately predicted and analyzed based solely on modeling. Through this work, the great influence of steric hindrance on the initial stage of ALD is described.

Biological intuition in alignment-free methods: response to Posada.

PubMed

Ragan, Mark A; Chan, Cheong Xin

2013-08-01

A recent editorial in Journal of Molecular Evolution highlights opportunities and challenges facing molecular evolution in the era of next-generation sequencing. Abundant sequence data should allow more-complex models to be fit at higher confidence, making phylogenetic inference more reliable and improving our understanding of evolution at the molecular level. However, concern that approaches based on multiple sequence alignment may be computationally infeasible for large datasets is driving the development of so-called alignment-free methods for sequence comparison and phylogenetic inference. The recent editorial characterized these approaches as model-free, not based on the concept of homology, and lacking in biological intuition. We argue here that alignment-free methods have not abandoned models or homology, and can be biologically intuitive.

The Further Evolution of Cooperation

NASA Astrophysics Data System (ADS)

Axelrod, Robert; Dion, Douglas

1988-12-01

Axelrod's model of the evolution of cooperation was based on the iterated Prisoner's Dilemma. Empirical work following this approach has helped establish the prevalence of cooperation based on reciprocity. Theoretical work has led to a deeper understanding of the role of other factors in the evolution of cooperation: the number of players, the range of possible choices, variation in the payoff structure, noise, the shadow of the future, population dynamics, and population structure.

Coupling Landform Evolution and Soil Pedogenesis - Initial Results From the SSSPAM5D Model

NASA Astrophysics Data System (ADS)

Willgoose, G. R.; Welivitiya, W. D. D. P.; Hancock, G. R.; Cohen, S.

2015-12-01

Evolution of soil on a dynamic landform is a crucial next step in landscape evolution modelling. Some attempts have been taken such as MILESD by Vanwalleghem et al. to develop a first model which is capable of simultaneously evolving both the soil profile and the landform. In previous work we have presented physically based models for soil pedogenesis, mARM and SSSPAM. In this study we present the results of coupling a landform evolution model with our SSSPAM5D soil pedogenesis model. In previous work the SSSPAM5D soil evolution model was used to identify trends of the soil profile evolution on a static landform. Two pedogenetic processes, namely (1) armouring due to erosion, and (2) physical and chemical weathering were used in those simulations to evolve the soil profile. By incorporating elevation changes (due to erosion and deposition) we have advanced the SSSPAM5D modelling framework into the realm of landscape evolution. Simulations have been run using elevation and soil grading data of the engineered landform (spoil heap) at the Ranger Uranium Mine, Northern Territory, Australia. The results obtained for the coupled landform-soil evolution simulations predict the erosion of high slope areas, development of rudimentary channel networks in the landform and deposition of sediments in lowland areas, and qualitatively consistent with landform evolution models on their own. Examination of the soil profile characteristics revealed that hill crests are weathering dominated and tend to develop a thick soil layer. The steeper hillslopes at the edge of the landform are erosion dominated with shallow soils while the foot slopes are deposition dominated with thick soil layers. The simulation results of our coupled landform and soil evolution model provide qualitatively correct and timely characterization of the soil evolution on a dynamic landscape. Finally we will compare the characteristics of erosion and deposition predicted by the coupled landform-soil SSSPAM landscape simulator, with landform evolution simulations using a static soil.

Stimulating Scientific Reasoning with Drawing-Based Modeling

ERIC Educational Resources Information Center

Heijnes, Dewi; van Joolingen, Wouter; Leenaars, Frank

2018-01-01

We investigate the way students' reasoning about evolution can be supported by drawing-based modeling. We modified the drawing-based modeling tool SimSketch to allow for modeling evolutionary processes. In three iterations of development and testing, students in lower secondary education worked on creating an evolutionary model. After each…

Validity of strong lensing statistics for constraints on the galaxy evolution model

NASA Astrophysics Data System (ADS)

Matsumoto, Akiko; Futamase, Toshifumi

2008-02-01

We examine the usefulness of the strong lensing statistics to constrain the evolution of the number density of lensing galaxies by adopting the values of the cosmological parameters determined by recent Wilkinson Microwave Anisotropy Probe observation. For this purpose, we employ the lens-redshift test proposed by Kochanek and constrain the parameters in two evolution models, simple power-law model characterized by the power-law indexes νn and νv, and the evolution model by Mitchell et al. based on cold dark matter structure formation scenario. We use the well-defined lens sample from the Sloan Digital Sky Survey (SDSS) and this is similarly sized samples used in the previous studies. Furthermore, we adopt the velocity dispersion function of early-type galaxies based on SDSS DR1 and DR5. It turns out that the indexes of power-law model are consistent with the previous studies, thus our results indicate the mild evolution in the number and velocity dispersion of early-type galaxies out to z = 1. However, we found that the values for p and q used by Mitchell et al. are inconsistent with the presently available observational data. More complete sample is necessary to withdraw more realistic determination on these parameters.

Markov Chain-Like Quantum Biological Modeling of Mutations, Aging, and Evolution.

PubMed

Djordjevic, Ivan B

2015-08-24

Recent evidence suggests that quantum mechanics is relevant in photosynthesis, magnetoreception, enzymatic catalytic reactions, olfactory reception, photoreception, genetics, electron-transfer in proteins, and evolution; to mention few. In our recent paper published in Life, we have derived the operator-sum representation of a biological channel based on codon basekets, and determined the quantum channel model suitable for study of the quantum biological channel capacity. However, this model is essentially memoryless and it is not able to properly model the propagation of mutation errors in time, the process of aging, and evolution of genetic information through generations. To solve for these problems, we propose novel quantum mechanical models to accurately describe the process of creation spontaneous, induced, and adaptive mutations and their propagation in time. Different biological channel models with memory, proposed in this paper, include: (i) Markovian classical model, (ii) Markovian-like quantum model, and (iii) hybrid quantum-classical model. We then apply these models in a study of aging and evolution of quantum biological channel capacity through generations. We also discuss key differences of these models with respect to a multilevel symmetric channel-based Markovian model and a Kimura model-based Markovian process. These models are quite general and applicable to many open problems in biology, not only biological channel capacity, which is the main focus of the paper. We will show that the famous quantum Master equation approach, commonly used to describe different biological processes, is just the first-order approximation of the proposed quantum Markov chain-like model, when the observation interval tends to zero. One of the important implications of this model is that the aging phenotype becomes determined by different underlying transition probabilities in both programmed and random (damage) Markov chain-like models of aging, which are mutually coupled.

Markov Chain-Like Quantum Biological Modeling of Mutations, Aging, and Evolution

PubMed Central

Djordjevic, Ivan B.

2015-01-01

Recent evidence suggests that quantum mechanics is relevant in photosynthesis, magnetoreception, enzymatic catalytic reactions, olfactory reception, photoreception, genetics, electron-transfer in proteins, and evolution; to mention few. In our recent paper published in Life, we have derived the operator-sum representation of a biological channel based on codon basekets, and determined the quantum channel model suitable for study of the quantum biological channel capacity. However, this model is essentially memoryless and it is not able to properly model the propagation of mutation errors in time, the process of aging, and evolution of genetic information through generations. To solve for these problems, we propose novel quantum mechanical models to accurately describe the process of creation spontaneous, induced, and adaptive mutations and their propagation in time. Different biological channel models with memory, proposed in this paper, include: (i) Markovian classical model, (ii) Markovian-like quantum model, and (iii) hybrid quantum-classical model. We then apply these models in a study of aging and evolution of quantum biological channel capacity through generations. We also discuss key differences of these models with respect to a multilevel symmetric channel-based Markovian model and a Kimura model-based Markovian process. These models are quite general and applicable to many open problems in biology, not only biological channel capacity, which is the main focus of the paper. We will show that the famous quantum Master equation approach, commonly used to describe different biological processes, is just the first-order approximation of the proposed quantum Markov chain-like model, when the observation interval tends to zero. One of the important implications of this model is that the aging phenotype becomes determined by different underlying transition probabilities in both programmed and random (damage) Markov chain-like models of aging, which are mutually coupled. PMID:26305258

Micromechanics and constitutive models for soft active materials with phase evolution

NASA Astrophysics Data System (ADS)

Wang, Binglian

Soft active materials, such as shape memory polymers, liquid crystal elastomers, soft tissues, gels etc., are materials that can deform largely in response to external stimuli. Micromechanics analysis of heterogeneous materials based on finite element method is a typically numerical way to study the thermal-mechanical behaviors of soft active materials with phase evolution. While the constitutive models that can precisely describe the stress and strain fields of materials in the process of phase evolution can not be found in the databases of some commercial finite element analysis (FEA) tools such as ANSYS or Abaqus, even the specific constitutive behavior for each individual phase either the new formed one or the original one has already been well-known. So developing a computationally efficient and general three dimensional (3D) thermal-mechanical constitutive model for soft active materials with phase evolution which can be implemented into FEA is eagerly demanded. This paper first solved this problem theoretically by recording the deformation history of each individual phase in the phase evolution process, and adopted the idea of effectiveness by regarding all the new formed phase as an effective phase with an effective deformation to make this theory computationally efficient. A user material subroutine (UMAT) code based on this theoretical constitutive model has been finished in this work which can be added into the material database in Abaqus or ANSYS and can be easily used for most soft active materials with phase evolution. Model validation also has been done through comparison between micromechanical FEA and experiments on a particular composite material, shape memory elastomeric composite (SMEC) which consisted of an elastomeric matrix and the crystallizable fibre. Results show that the micromechanics and the constitutive models developed in this paper for soft active materials with phase evolution are completely relied on.

Neutral null models for diversity in serial transfer evolution experiments.

PubMed

Harpak, Arbel; Sella, Guy

2014-09-01

Evolution experiments with microorganisms coupled with genome-wide sequencing now allow for the systematic study of population genetic processes under a wide range of conditions. In learning about these processes in natural, sexual populations, neutral models that describe the behavior of diversity and divergence summaries have played a pivotal role. It is therefore natural to ask whether neutral models, suitably modified, could be useful in the context of evolution experiments. Here, we introduce coalescent models for polymorphism and divergence under the most common experimental evolution assay, a serial transfer experiment. This relatively simple setting allows us to address several issues that could affect diversity patterns in evolution experiments, whether selection is operating or not: the transient behavior of neutral polymorphism in an experiment beginning from a single clone, the effects of randomness in the timing of cell division and noisiness in population size in the dilution stage. In our analyses and discussion, we emphasize the implications for experiments aimed at measuring diversity patterns and making inferences about population genetic processes based on these measurements. © 2014 The Author(s). Evolution © 2014 The Society for the Study of Evolution.

Deriving urban dynamic evolution rules from self-adaptive cellular automata with multi-temporal remote sensing images

NASA Astrophysics Data System (ADS)

He, Yingqing; Ai, Bin; Yao, Yao; Zhong, Fajun

2015-06-01

Cellular automata (CA) have proven to be very effective for simulating and predicting the spatio-temporal evolution of complex geographical phenomena. Traditional methods generally pose problems in determining the structure and parameters of CA for a large, complex region or a long-term simulation. This study presents a self-adaptive CA model integrated with an artificial immune system to discover dynamic transition rules automatically. The model's parameters are allowed to be self-modified with the application of multi-temporal remote sensing images: that is, the CA can adapt itself to the changed and complex environment. Therefore, urban dynamic evolution rules over time can be efficiently retrieved by using this integrated model. The proposed AIS-based CA model was then used to simulate the rural-urban land conversion of Guangzhou city, located in the core of China's Pearl River Delta. The initial urban land was directly classified from TM satellite image in the year 1990. Urban land in the years 1995, 2000, 2005, 2009 and 2012 was correspondingly used as the observed data to calibrate the model's parameters. With the quantitative index figure of merit (FoM) and pattern similarity, the comparison was further performed between the AIS-based model and a Logistic CA model. The results indicate that the AIS-based CA model can perform better and with higher precision in simulating urban evolution, and the simulated spatial pattern is closer to the actual development situation.

BioJazz: in silico evolution of cellular networks with unbounded complexity using rule-based modeling.

PubMed

Feng, Song; Ollivier, Julien F; Swain, Peter S; Soyer, Orkun S

2015-10-30

Systems biologists aim to decipher the structure and dynamics of signaling and regulatory networks underpinning cellular responses; synthetic biologists can use this insight to alter existing networks or engineer de novo ones. Both tasks will benefit from an understanding of which structural and dynamic features of networks can emerge from evolutionary processes, through which intermediary steps these arise, and whether they embody general design principles. As natural evolution at the level of network dynamics is difficult to study, in silico evolution of network models can provide important insights. However, current tools used for in silico evolution of network dynamics are limited to ad hoc computer simulations and models. Here we introduce BioJazz, an extendable, user-friendly tool for simulating the evolution of dynamic biochemical networks. Unlike previous tools for in silico evolution, BioJazz allows for the evolution of cellular networks with unbounded complexity by combining rule-based modeling with an encoding of networks that is akin to a genome. We show that BioJazz can be used to implement biologically realistic selective pressures and allows exploration of the space of network architectures and dynamics that implement prescribed physiological functions. BioJazz is provided as an open-source tool to facilitate its further development and use. Source code and user manuals are available at: http://oss-lab.github.io/biojazz and http://osslab.lifesci.warwick.ac.uk/BioJazz.aspx. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Wind growth and wave breaking in higher-order spectral phase resolved wave models

NASA Astrophysics Data System (ADS)

Leighton, R.; Walker, D. T.

2016-02-01

Wind growth and wave breaking are a integral parts of the wave evolution. Higher-OrderSpectral models (HoS) describing the non-linear evolution require empirical models for these effects. In particular, the assimilation of phase-resolved remotesensing data will require the prediction and modeling of wave breaking events.The HoS formulation used in this effort is based on fully nonlinear model of O. Nwogu (2009). The model for wave growth due to wind is based on the early normal and tangential stress model of Munk (1947). The model for wave breaking contains two parts. The first part initiates the breaking events based on the local wave geometry and the second part is a model for the pressure field, which acting against the surface normal velocity extracts energy from the wave. The models are tuned to balance the wind energy input with the breaking wave losses and to be similarfield observations of breaking wave coverage. The initial wave field, based on a Pierson-Moskowitz spectrum for 10 meter wind speed of 5-15 m/s, defined over a region of up to approximate 2.5 km on a side with the simulation running for several hundreds of peak wave periods. Results will be presented describing the evolution of the wave field.Sponsored by Office of Naval Research, Code 322

Evolution dynamics modeling and simulation of logistics enterprise's core competence based on service innovation

NASA Astrophysics Data System (ADS)

Yang, Bo; Tong, Yuting

2017-04-01

With the rapid development of economy, the development of logistics enterprises in China is also facing a huge challenge, especially the logistics enterprises generally lack of core competitiveness, and service innovation awareness is not strong. Scholars in the process of studying the core competitiveness of logistics enterprises are mainly from the perspective of static stability, not from the perspective of dynamic evolution to explore. So the author analyzes the influencing factors and the evolution process of the core competence of logistics enterprises, using the method of system dynamics to study the cause and effect of the evolution of the core competence of logistics enterprises, construct a system dynamics model of evolution of core competence logistics enterprises, which can be simulated by vensim PLE. The analysis for the effectiveness and sensitivity of simulation model indicates the model can be used as the fitting of the evolution process of the core competence of logistics enterprises and reveal the process and mechanism of the evolution of the core competence of logistics enterprises, and provide management strategies for improving the core competence of logistics enterprises. The construction and operation of computer simulation model offers a kind of effective method for studying the evolution of logistics enterprise core competence.

The species-area relationship and evolution.

PubMed

Lawson, Daniel; Jensen, Henrik Jeldtoft

2006-08-07

Models relating to the species-area curve usually assume the existence of species, and are concerned mainly with ecological timescales. We examine an individual-based model of co-evolution on a spatial lattice based on the tangled nature model in which species are emergent structures, and show that reproduction, mutation and dispersion by diffusion, with interaction via genotype space, produces power-law species-area relations as observed in ecological measurements at medium scales. We find that long-lasting co-evolutionary habitats form, allowing high diversity levels in a spatially homogenous system.

Brownian model of transcriptome evolution and phylogenetic network visualization between tissues.

PubMed

Gu, Xun; Ruan, Hang; Su, Zhixi; Zou, Yangyun

2017-09-01

While phylogenetic analysis of transcriptomes of the same tissue is usually congruent with the species tree, the controversy emerges when multiple tissues are included, that is, whether species from the same tissue are clustered together, or different tissues from the same species are clustered together. Recent studies have suggested that phylogenetic network approach may shed some lights on our understanding of multi-tissue transcriptome evolution; yet the underlying evolutionary mechanism remains unclear. In this paper we develop a Brownian-based model of transcriptome evolution under the phylogenetic network that can statistically distinguish between the patterns of species-clustering and tissue-clustering. Our model can be used as a null hypothesis (neutral transcriptome evolution) for testing any correlation in tissue evolution, can be applied to cancer transcriptome evolution to study whether two tumors of an individual appeared independently or via metastasis, and can be useful to detect convergent evolution at the transcriptional level. Copyright © 2017. Published by Elsevier Inc.

A last updating evolution model for online social networks

NASA Astrophysics Data System (ADS)

Bu, Zhan; Xia, Zhengyou; Wang, Jiandong; Zhang, Chengcui

2013-05-01

As information technology has advanced, people are turning to electronic media more frequently for communication, and social relationships are increasingly found on online channels. However, there is very limited knowledge about the actual evolution of the online social networks. In this paper, we propose and study a novel evolution network model with the new concept of “last updating time”, which exists in many real-life online social networks. The last updating evolution network model can maintain the robustness of scale-free networks and can improve the network reliance against intentional attacks. What is more, we also found that it has the “small-world effect”, which is the inherent property of most social networks. Simulation experiment based on this model show that the results and the real-life data are consistent, which means that our model is valid.

SIGNUM: A Matlab, TIN-based landscape evolution model

NASA Astrophysics Data System (ADS)

Refice, A.; Giachetta, E.; Capolongo, D.

2012-08-01

Several numerical landscape evolution models (LEMs) have been developed to date, and many are available as open source codes. Most are written in efficient programming languages such as Fortran or C, but often require additional code efforts to plug in to more user-friendly data analysis and/or visualization tools to ease interpretation and scientific insight. In this paper, we present an effort to port a common core of accepted physical principles governing landscape evolution directly into a high-level language and data analysis environment such as Matlab. SIGNUM (acronym for Simple Integrated Geomorphological Numerical Model) is an independent and self-contained Matlab, TIN-based landscape evolution model, built to simulate topography development at various space and time scales. SIGNUM is presently capable of simulating hillslope processes such as linear and nonlinear diffusion, fluvial incision into bedrock, spatially varying surface uplift which can be used to simulate changes in base level, thrust and faulting, as well as effects of climate changes. Although based on accepted and well-known processes and algorithms in its present version, it is built with a modular structure, which allows to easily modify and upgrade the simulated physical processes to suite virtually any user needs. The code is conceived as an open-source project, and is thus an ideal tool for both research and didactic purposes, thanks to the high-level nature of the Matlab environment and its popularity among the scientific community. In this paper the simulation code is presented together with some simple examples of surface evolution, and guidelines for development of new modules and algorithms are proposed.

Thermodynamic evolution far from equilibrium

NASA Astrophysics Data System (ADS)

Khantuleva, Tatiana A.

2018-05-01

The presented model of thermodynamic evolution of an open system far from equilibrium is based on the modern results of nonequilibrium statistical mechanics, the nonlocal theory of nonequilibrium transport developed by the author and the Speed Gradient principle introduced in the theory of adaptive control. Transition to a description of the system internal structure evolution at the mesoscopic level allows a new insight at the stability problem of non-equilibrium processes. The new model is used in a number of specific tasks.

Strong Stellar-driven Outflows Shape the Evolution of Galaxies at Cosmic Dawn

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

Fontanot, Fabio; De Lucia, Gabriella; Hirschmann, Michaela

We study galaxy mass assembly and cosmic star formation rate (SFR) at high redshift (z ≳ 4), by comparing data from multiwavelength surveys with predictions from the GAlaxy Evolution and Assembly (gaea) model. gaea implements a stellar feedback scheme partially based on cosmological hydrodynamical simulations, which features strong stellar-driven outflows and mass-dependent timescales for the re-accretion of ejected gas. In previous work, we have shown that this scheme is able to correctly reproduce the evolution of the galaxy stellar mass function (GSMF) up to z ∼ 3. We contrast model predictions with both rest-frame ultraviolet (UV) and optical luminosity functionsmore » (LFs), which are mostly sensitive to the SFR and stellar mass, respectively. We show that gaea is able to reproduce the shape and redshift evolution of both sets of LFs. We study the impact of dust on the predicted LFs, and we find that the required level of dust attenuation is in qualitative agreement with recent estimates based on the UV continuum slope. The consistency between data and model predictions holds for the redshift evolution of the physical quantities well beyond the redshift range considered for the calibration of the original model. In particular, we show that gaea is able to recover the evolution of the GSMF up to z ∼ 7 and the cosmic SFR density up to z ∼ 10.« less

A Numerical Method for Simulating the Microscopic Damage Evolution in Composites Under Uniaxial Transverse Tension

NASA Astrophysics Data System (ADS)

Zhi, Jie; Zhao, Libin; Zhang, Jianyu; Liu, Zhanli

2016-06-01

In this paper, a new numerical method that combines a surface-based cohesive model and extended finite element method (XFEM) without predefining the crack paths is presented to simulate the microscopic damage evolution in composites under uniaxial transverse tension. The proposed method is verified to accurately capture the crack kinking into the matrix after fiber/matrix debonding. A statistical representative volume element (SRVE) under periodic boundary conditions is used to approximate the microstructure of the composites. The interface parameters of the cohesive models are investigated, in which the initial interface stiffness has a great effect on the predictions of the fiber/matrix debonding. The detailed debonding states of SRVE with strong and weak interfaces are compared based on the surface-based and element-based cohesive models. The mechanism of damage in composites under transverse tension is described as the appearance of the interface cracks and their induced matrix micro-cracking, both of which coalesce into transversal macro-cracks. Good agreement is found between the predictions of the model and the in situ experimental observations, demonstrating the efficiency of the presented model for simulating the microscopic damage evolution in composites.

Hybrid discrete-time neural networks.

PubMed

Cao, Hongjun; Ibarz, Borja

2010-11-13

Hybrid dynamical systems combine evolution equations with state transitions. When the evolution equations are discrete-time (also called map-based), the result is a hybrid discrete-time system. A class of biological neural network models that has recently received some attention falls within this category: map-based neuron models connected by means of fast threshold modulation (FTM). FTM is a connection scheme that aims to mimic the switching dynamics of a neuron subject to synaptic inputs. The dynamic equations of the neuron adopt different forms according to the state (either firing or not firing) and type (excitatory or inhibitory) of their presynaptic neighbours. Therefore, the mathematical model of one such network is a combination of discrete-time evolution equations with transitions between states, constituting a hybrid discrete-time (map-based) neural network. In this paper, we review previous work within the context of these models, exemplifying useful techniques to analyse them. Typical map-based neuron models are low-dimensional and amenable to phase-plane analysis. In bursting models, fast-slow decomposition can be used to reduce dimensionality further, so that the dynamics of a pair of connected neurons can be easily understood. We also discuss a model that includes electrical synapses in addition to chemical synapses with FTM. Furthermore, we describe how master stability functions can predict the stability of synchronized states in these networks. The main results are extended to larger map-based neural networks.

Study on Capturing Functional Requirements of the New Product Based on Evolution

NASA Astrophysics Data System (ADS)

Liu, Fang; Song, Liya; Bai, Zhonghang; Zhang, Peng

In order to exist in an increasingly competitive global marketplace, it is important for corporations to forecast the evolutionary direction of new products rapidly and effectively. Most products in the world are developed based on the design of existing products. In the product design, capturing functional requirements is a key step. Function is continuously evolving, which is driven by the evolution of needs and technologies. So the functional requirements of new product can be forecasted based on the functions of existing product. Eight laws of function evolution are put forward in this paper. The process model of capturing the functional requirements of new product based on function evolution is proposed. An example illustrates the design process.

Evolution of vaporizing pulsars

NASA Technical Reports Server (NTRS)

Mccormick, P.

1994-01-01

We construct evolutional scenarios for LMXB's using a simplified stellar model. We discuss the origin and evolution of short-period, low mass binary pulsars with evaporating companions. We suggest that these systems descend from low-mass X-ray binaries and that angular momentum loss mainly due to evaporative wind drives their evolution. We derive limits on the energy and angular momentum carried away by the wind based on the observed low eccentricity. In our model the companion remains near contact, and its quasiadiabatic expansion causes the binary to expand. Short-term oscillations of the orbital period may occur if the Roche-lobe overflow forms an evaporating disk.

Magnetic Flux Transport at the Solar Surface

NASA Astrophysics Data System (ADS)

Jiang, J.; Hathaway, D. H.; Cameron, R. H.; Solanki, S. K.; Gizon, L.; Upton, L.

2014-12-01

After emerging to the solar surface, the Sun's magnetic field displays a complex and intricate evolution. The evolution of the surface field is important for several reasons. One is that the surface field, and its dynamics, sets the boundary condition for the coronal and heliospheric magnetic fields. Another is that the surface evolution gives us insight into the dynamo process. In particular, it plays an essential role in the Babcock-Leighton model of the solar dynamo. Describing this evolution is the aim of the surface flux transport model. The model starts from the emergence of magnetic bipoles. Thereafter, the model is based on the induction equation and the fact that after emergence the magnetic field is observed to evolve as if it were purely radial. The induction equation then describes how the surface flows—differential rotation, meridional circulation, granular, supergranular flows, and active region inflows—determine the evolution of the field (now taken to be purely radial). In this paper, we review the modeling of the various processes that determine the evolution of the surface field. We restrict our attention to their role in the surface flux transport model. We also discuss the success of the model and some of the results that have been obtained using this model.

Magnetospheric Substorm Evolution in the Magnetotail: Challenge to Global MHD Modeling.

NASA Astrophysics Data System (ADS)

Kuznetsova, M. M.; Hesse, M.; Dorelli, J.; Rastaetter, L.

2003-12-01

Testing the ability of global MHD models to describe magnetotail evolution during substroms is one of the elements of science based validation efforts at CCMC. We perform simulations of magnetotail dynamics using global MHD models residing at CCMC. We select solar wind conditions which drive the accumulation of magnetic field in the tail lobes and subsequent magnetic reconnection and energy release. We will analyze the effects of spatial resolution in the plasma sheet on modeled expansion phase evolution, maximum energy stored in the tail, and details of magnetotail reconnection. We will pay special attention to current sheet thinning and multiple plasmoid formation.

Generalized fractional diffusion equations for subdiffusion in arbitrarily growing domains

NASA Astrophysics Data System (ADS)

Angstmann, C. N.; Henry, B. I.; McGann, A. V.

2017-10-01

The ubiquity of subdiffusive transport in physical and biological systems has led to intensive efforts to provide robust theoretical models for this phenomena. These models often involve fractional derivatives. The important physical extension of this work to processes occurring in growing materials has proven highly nontrivial. Here we derive evolution equations for modeling subdiffusive transport in a growing medium. The derivation is based on a continuous-time random walk. The concise formulation of these evolution equations requires the introduction of a new, comoving, fractional derivative. The implementation of the evolution equation is illustrated with a simple model of subdiffusing proteins in a growing membrane.

Virus replication as a phenotypic version of polynucleotide evolution.

PubMed

Antoneli, Fernando; Bosco, Francisco; Castro, Diogo; Janini, Luiz Mario

2013-04-01

In this paper, we revisit and adapt to viral evolution an approach based on the theory of branching process advanced by Demetrius et al. (Bull. Math. Biol. 46:239-262, 1985), in their study of polynucleotide evolution. By taking into account beneficial effects, we obtain a non-trivial multivariate generalization of their single-type branching process model. Perturbative techniques allows us to obtain analytical asymptotic expressions for the main global parameters of the model, which lead to the following rigorous results: (i) a new criterion for "no sure extinction", (ii) a generalization and proof, for this particular class of models, of the lethal mutagenesis criterion proposed by Bull et al. (J. Virol. 18:2930-2939, 2007), (iii) a new proposal for the notion of relaxation time with a quantitative prescription for its evaluation, (iv) the quantitative description of the evolution of the expected values in four distinct "stages": extinction threshold, lethal mutagenesis, stationary "equilibrium", and transient. Finally, based on these quantitative results, we are able to draw some qualitative conclusions.

Numerical Study of Microstructural Evolution During Homogenization of Al-Si-Mg-Fe-Mn Alloys

NASA Astrophysics Data System (ADS)

Priya, Pikee; Johnson, David R.; Krane, Matthew J. M.

2016-09-01

Microstructural evolution during homogenization of Al-Si-Mg-Fe-Mn alloys occurs in two stages at different length scales: while holding at the homogenization temperature (diffusion on the scale of the secondary dendrite arm spacing (SDAS) in micrometers) and during quenching to room temperature (dispersoid precipitation at the nanometer to submicron scale). Here a numerical study estimates microstructural changes during both stages. A diffusion-based model developed to simulate evolution at the SDAS length scale predicts homogenization times and microstructures matching experiments. That model is coupled with a Kampmann Wagner Neumann-based precipitate nucleation and growth model to study the effect of temperature, composition, as-cast microstructure, and cooling rates during posthomogenization quenching on microstructural evolution. A homogenization schedule of 853 K (580 °C) for 8 hours, followed by cooling at 250 K/h, is suggested to optimize microstructures for easier extrusion, consisting of minimal α-Al(FeMn)Si, no β-AlFeSi, and Mg2Si dispersoids <1 μm size.

Quantum information and the problem of mechanisms of biological evolution.

PubMed

Melkikh, Alexey V

2014-01-01

One of the most important conditions for replication in early evolution is the de facto elimination of the conformational degrees of freedom of the replicators, the mechanisms of which remain unclear. In addition, realistic evolutionary timescales can be established based only on partially directed evolution, further complicating this issue. A division of the various evolutionary theories into two classes has been proposed based on the presence or absence of a priori information about the evolving system. A priori information plays a key role in solving problems in evolution. Here, a model of partially directed evolution, based on the learning automata theory, which includes a priori information about the fitness space, is proposed. A potential repository of such prior information is the states of biologically important molecules. Thus, the need for extended evolutionary synthesis is discussed. Experiments to test the hypothesis of partially directed evolution are proposed. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Rooted tRNAomes and evolution of the genetic code

PubMed Central

Pak, Daewoo; Du, Nan; Kim, Yunsoo; Sun, Yanni

2018-01-01

ABSTRACT We advocate for a tRNA- rather than an mRNA-centric model for evolution of the genetic code. The mechanism for evolution of cloverleaf tRNA provides a root sequence for radiation of tRNAs and suggests a simplified understanding of code evolution. To analyze code sectoring, rooted tRNAomes were compared for several archaeal and one bacterial species. Rooting of tRNAome trees reveals conserved structures, indicating how the code was shaped during evolution and suggesting a model for evolution of a LUCA tRNAome tree. We propose the polyglycine hypothesis that the initial product of the genetic code may have been short chain polyglycine to stabilize protocells. In order to describe how anticodons were allotted in evolution, the sectoring-degeneracy hypothesis is proposed. Based on sectoring, a simple stepwise model is developed, in which the code sectors from a 1→4→8→∼16 letter code. At initial stages of code evolution, we posit strong positive selection for wobble base ambiguity, supporting convergence to 4-codon sectors and ∼16 letters. In a later stage, ∼5–6 letters, including stops, were added through innovating at the anticodon wobble position. In archaea and bacteria, tRNA wobble adenine is negatively selected, shrinking the maximum size of the primordial genetic code to 48 anticodons. Because 64 codons are recognized in mRNA, tRNA-mRNA coevolution requires tRNA wobble position ambiguity leading to degeneracy of the code. PMID:29372672

Corneal changes induced by laser ablation: study of the visual-quality evolution by a customized eye model

NASA Astrophysics Data System (ADS)

Ortiz, D.; Anera, R. G.; Saiz, J. M.; Jiménez, J. R.; Moreno, F.; Jiménez Del Barco, L.; González, F.

2006-11-01

This study focuses on the changes induced in both the asphericity and homogeneity of the cornea for a group of myopic eyes undergoing LASIK surgery. Eyes were characterized by a Kooijman-based customized eye model in which changes were introduced in the form of Gaussian-distributed refractive-index variations of given correlation length for the inhomogeneities and in the form of an expression, based on the modified Munnerlyn's paraxial formula, for the post-LASIK asphericity. Visual quality was evaluated in terms of the Modulation Transfer Function and the Point-Spread Function. The results show that, on average, the evolution of visual acuity is consistent with the change in corneal asphericity, while the evolution of contrast sensitivity requires a loss in corneal homogeneity in order to be explained. By including both effects in the model, the overall model performance in predicting visual quality is improved.

On the upscaling of process-based models in deltaic applications

NASA Astrophysics Data System (ADS)

Li, L.; Storms, J. E. A.; Walstra, D. J. R.

2018-03-01

Process-based numerical models are increasingly used to study the evolution of marine and terrestrial depositional environments. Whilst a detailed description of small-scale processes provides an accurate representation of reality, application on geological timescales is restrained by the associated increase in computational time. In order to reduce the computational time, a number of acceleration methods are combined and evaluated for a schematic supply-driven delta (static base level) and an accommodation-driven delta (variable base level). The performance of the combined acceleration methods is evaluated by comparing the morphological indicators such as distributary channel networking and delta volumes derived from the model predictions for various levels of acceleration. The results of the accelerated models are compared to the outcomes from a series of simulations to capture autogenic variability. Autogenic variability is quantified by re-running identical models on an initial bathymetry with 1 cm added noise. The overall results show that the variability of the accelerated models fall within the autogenic variability range, suggesting that the application of acceleration methods does not significantly affect the simulated delta evolution. The Time-scale compression method (the acceleration method introduced in this paper) results in an increased computational efficiency of 75% without adversely affecting the simulated delta evolution compared to a base case. The combination of the Time-scale compression method with the existing acceleration methods has the potential to extend the application range of process-based models towards geologic timescales.

Using Agent-Based Modelling to Predict the Role of Wild Refugia in the Evolution of Resistance of Sea Lice to Chemotherapeutants.

PubMed

McEwan, Gregor F; Groner, Maya L; Fast, Mark D; Gettinby, George; Revie, Crawford W

2015-01-01

A major challenge for Atlantic salmon farming in the northern hemisphere is infestation by the sea louse parasite Lepeophtheirus salmonis. The most frequent method of controlling these sea louse infestations is through the use of chemical treatments. However, most major salmon farming areas have observed resistance to common chemotherapeutants. In terrestrial environments, many strategies employed to manage the evolution of resistance involve the use of refugia, where a portion of the population is left untreated to maintain susceptibility. While refugia have not been deliberately used in Atlantic salmon farming, wild salmon populations that migrate close to salmon farms may act as natural refugia. In this paper we describe an agent-based model that explores the influence of different sizes of wild salmon populations on resistance evolution in sea lice on a salmon farm. Using the model, we demonstrate that wild salmon populations can act as refugia that limit the evolution of resistance in the sea louse populations. Additionally, we demonstrate that an increase in the size of the population of wild salmon results in an increased effect in slowing the evolution of resistance. We explore the effect of a population fitness cost associated with resistance, finding that in some cases it substantially reduces the speed of evolution to chemical treatments.

The Evolution of Institutional Planning Models in Higher Education. AIR 1986 Annual Forum Paper.

ERIC Educational Resources Information Center

Winstead, Philip C.; Ruff, Dan G.

The evolution of the "planning process" from the 1940s to the present is considered, especially as it relates to higher education. It was hypothesized that institutional planning has experienced historical evolution: new planning innovations over the years have added to the existing institutional planning knowledge base. A literature…

Gradient Plasticity Model and its Implementation into MARMOT

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

Barker, Erin I.; Li, Dongsheng; Zbib, Hussein M.

2013-08-01

The influence of strain gradient on deformation behavior of nuclear structural materials, such as boby centered cubic (bcc) iron alloys has been investigated. We have developed and implemented a dislocation based strain gradient crystal plasticity material model. A mesoscale crystal plasticity model for inelastic deformation of metallic material, bcc steel, has been developed and implemented numerically. Continuum Dislocation Dynamics (CDD) with a novel constitutive law based on dislocation density evolution mechanisms was developed to investigate the deformation behaviors of single crystals, as well as polycrystalline materials by coupling CDD and crystal plasticity (CP). The dislocation density evolution law in thismore » model is mechanism-based, with parameters measured from experiments or simulated with lower-length scale models, not an empirical law with parameters back-fitted from the flow curves.« less

Following the Social Media: Aspect Evolution of Online Discussion

NASA Astrophysics Data System (ADS)

Tang, Xuning; Yang, Christopher C.

Due to the advance of Internet and Web 2.0 technologies, it is easy to extract thousands of threads about a topic of interest from an online forum but it is nontrivial to capture the blueprint of different aspects (i.e., subtopic, or facet) associated with the topic. To better understand and analyze a forum discussion given topic, it is important to uncover the evolution relationships (temporal dependencies) between different topic aspects (i.e. how the discussion topic is evolving). Traditional Topic Detection and Tracking (TDT) techniques usually organize topics as a flat structure but it does not present the evolution relationships between topic aspects. In addition, the properties of short and sparse messages make the content-based TDT techniques difficult to perform well in identifying evolution relationships. The contributions in this paper are two-folded. We formally define a topic aspect evolution graph modeling framework and propose to utilize social network information, content similarity and temporal proximity to model evolution relationships between topic aspects. The experimental results showed that, by incorporating social network information, our technique significantly outperformed content-based technique in the task of extracting evolution relationships between topic aspects.

Divergence and evolution of assortative mating in a polygenic trait model of speciation with gene flow.

PubMed

Sachdeva, Himani; Barton, Nicholas H

2017-06-01

Assortative mating is an important driver of speciation in populations with gene flow and is predicted to evolve under certain conditions in few-locus models. However, the evolution of assortment is less understood for mating based on quantitative traits, which are often characterized by high genetic variability and extensive linkage disequilibrium between trait loci. We explore this scenario for a two-deme model with migration, by considering a single polygenic trait subject to divergent viability selection across demes, as well as assortative mating and sexual selection within demes, and investigate how trait divergence is shaped by various evolutionary forces. Our analysis reveals the existence of sharp thresholds of assortment strength, at which divergence increases dramatically. We also study the evolution of assortment via invasion of modifiers of mate discrimination and show that the ES assortment strength has an intermediate value under a range of migration-selection parameters, even in diverged populations, due to subtle effects which depend sensitively on the extent of phenotypic variation within these populations. The evolutionary dynamics of the polygenic trait is studied using the hypergeometric and infinitesimal models. We further investigate the sensitivity of our results to the assumptions of the hypergeometric model, using individual-based simulations. © 2017 The Author(s). Evolution © 2017 The Society for the Study of Evolution.

Modeling the Flow Behavior, Recrystallization, and Crystallographic Texture in Hot-Deformed Fe-30 Wt Pct Ni Austenite

NASA Astrophysics Data System (ADS)

Abbod, M. F.; Sellars, C. M.; Cizek, P.; Linkens, D. A.; Mahfouf, M.

2007-10-01

The present work describes a hybrid modeling approach developed for predicting the flow behavior, recrystallization characteristics, and crystallographic texture evolution in a Fe-30 wt pct Ni austenitic model alloy subjected to hot plane strain compression. A series of compression tests were performed at temperatures between 850 °C and 1050 °C and strain rates between 0.1 and 10 s-1. The evolution of grain structure, crystallographic texture, and dislocation substructure was characterized in detail for a deformation temperature of 950 °C and strain rates of 0.1 and 10 s-1, using electron backscatter diffraction and transmission electron microscopy. The hybrid modeling method utilizes a combination of empirical, physically-based, and neuro-fuzzy models. The flow stress is described as a function of the applied variables of strain rate and temperature using an empirical model. The recrystallization behavior is predicted from the measured microstructural state variables of internal dislocation density, subgrain size, and misorientation between subgrains using a physically-based model. The texture evolution is modeled using artificial neural networks.

Kalman filter with a linear state model for PDR+WLAN positioning and its application to assisting a particle filter

NASA Astrophysics Data System (ADS)

Raitoharju, Matti; Nurminen, Henri; Piché, Robert

2015-12-01

Indoor positioning based on wireless local area network (WLAN) signals is often enhanced using pedestrian dead reckoning (PDR) based on an inertial measurement unit. The state evolution model in PDR is usually nonlinear. We present a new linear state evolution model for PDR. In simulated-data and real-data tests of tightly coupled WLAN-PDR positioning, the positioning accuracy with this linear model is better than with the traditional models when the initial heading is not known, which is a common situation. The proposed method is computationally light and is also suitable for smoothing. Furthermore, we present modifications to WLAN positioning based on Gaussian coverage areas and show how a Kalman filter using the proposed model can be used for integrity monitoring and (re)initialization of a particle filter.

Investigating ice cliff evolution and contribution to glacier mass-balance using a physically-based dynamic model

NASA Astrophysics Data System (ADS)

Buri, Pascal; Miles, Evan; Ragettli, Silvan; Brun, Fanny; Steiner, Jakob; Pellicciotti, Francesca

2016-04-01

Supraglacial cliffs are a surface feature typical of debris-covered glaciers, affecting surface evolution, glacier downwasting and mass balance by providing a direct ice-atmosphere interface. As a result, melt rates can be very high and ice cliffs may account for a significant portion of the total glacier mass loss. However, their contribution to glacier mass balance has rarely been quantified through physically-based models. Most cliff energy balance models are point scale models which calculate energy fluxes at individual cliff locations. Results from the only grid based model to date accurately reflect energy fluxes and cliff melt, but modelled backwasting patterns are in some cases unrealistic, as the distribution of melt rates would lead to progressive shallowing and disappearance of cliffs. Based on a unique multitemporal dataset of cliff topography and backwasting obtained from high-resolution terrestrial and aerial Structure-from-Motion analysis on Lirung Glacier in Nepal, it is apparent that cliffs exhibit a range of behaviours but most do not rapidly disappear. The patterns of evolution cannot be explained satisfactorily by atmospheric melt alone, and are moderated by the presence of supraglacial ponds at the base of cliffs and by cliff reburial with debris. Here, we document the distinct patterns of evolution including disappearance, growth and stability. We then use these observations to improve the grid-based energy balance model, implementing periodic updates of the cliff geometry resulting from modelled melt perpendicular to the ice surface. Based on a slope threshold, pixels can be reburied by debris or become debris-free. The effect of ponds are taken into account through enhanced melt rates in horizontal direction on pixels selected based on an algorithm considering distance to the water surface, slope and lake level. We use the dynamic model to first study the evolution of selected cliffs for which accurate, high resolution DEMs are available, and then apply the model to the entirety of Lirung and Langtang glaciers to quantify the total contributions of cliffs to glacier mass balance. Observations and model results suggest a strong dependency of the cliffs' life cycle on supraglacial ponds, as the water body keeps the cliff geometry constant through a combination of backwasting and calving at the bottom and maintenance of steep slopes in the lowest sections. The absence of ponds causes the progressive flattening of the cliff, which finally leads to complete disappearance. Modelled volume losses from May to October 2013 range from 2650 to 9415 m3 w.e., in agreement with the estimates with the SfM-approach. Mean error of modelled elevation within the cliff outline ranges from -1.3 to 0.6m. This work sheds light on mechanisms of cliffs' changes by quantifying them for the first time with a physically-based, dynamic model, and presents the first complete estimate of the relevance of supraglacial ice-cliffs to total glacier mass-balance for two distinct glaciers.

Teacher Evaluation Models: Compliance or Growth Oriented?

ERIC Educational Resources Information Center

Clenchy, Kelly R.

2017-01-01

This research study reviewed literature specific to the evolution of teacher evaluation models and explored the effectiveness of standards-based evaluation models' potential to facilitate professional growth. The researcher employed descriptive phenomenology to conduct a study of teachers' perceptions of a standard-based evaluation model's…

Research on Capturing of Customer Requirements Based on Innovation Theory

NASA Astrophysics Data System (ADS)

junwu, Ding; dongtao, Yang; zhenqiang, Bao

To exactly and effectively capture customer requirements information, a new customer requirements capturing modeling method was proposed. Based on the analysis of function requirement models of previous products and the application of technology system evolution laws of the Theory of Innovative Problem Solving (TRIZ), the customer requirements could be evolved from existing product designs, through modifying the functional requirement unit and confirming the direction of evolution design. Finally, a case study was provided to illustrate the feasibility of the proposed approach.

Complex networks generated by the Penna bit-string model: Emergence of small-world and assortative mixing

NASA Astrophysics Data System (ADS)

Li, Chunguang; Maini, Philip K.

2005-10-01

The Penna bit-string model successfully encompasses many phenomena of population evolution, including inheritance, mutation, evolution, and aging. If we consider social interactions among individuals in the Penna model, the population will form a complex network. In this paper, we first modify the Verhulst factor to control only the birth rate, and introduce activity-based preferential reproduction of offspring in the Penna model. The social interactions among individuals are generated by both inheritance and activity-based preferential increase. Then we study the properties of the complex network generated by the modified Penna model. We find that the resulting complex network has a small-world effect and the assortative mixing property.

Cooperation induces other cooperation: Fruiting bodies promote the evolution of macrocysts in Dictyostelium discoideum.

PubMed

Shibasaki, Shota; Shirokawa, Yuka; Shimada, Masakazu

2017-05-21

Biological studies of the evolution of cooperation are challenging because this process is vulnerable to cheating. Many mechanisms, including kin discrimination, spatial structure, or by-products of self-interested behaviors, can explain this evolution. Here we propose that the evolution of cooperation can be induced by other cooperation. To test this idea, we used a model organism Dictyostelium discoideum because it exhibits two cooperative dormant phases, the fruiting body and the macrocyst. In both phases, the same chemoattractant, cyclic AMP (cAMP), is used to collect cells. This common feature led us to hypothesize that the evolution of macrocyst formation would be induced by coexistence with fruiting bodies. Before forming a mathematical model, we confirmed that macrocysts coexisted with fruiting bodies, at least under laboratory conditions. Next, we analyzed our evolutionary game theory-based model to investigate whether coexistence with fruiting bodies would stabilize macrocyst formation. The model suggests that macrocyst formation represents an evolutionarily stable strategy and a global invader strategy under this coexistence, but is unstable if the model ignores the fruiting body formation. This result indicates that the evolution of macrocyst formation and maintenance is attributable to coexistence with fruiting bodies. Therefore, macrocyst evolution can be considered as an example of evolution of cooperation induced by other cooperation. Copyright © 2017 Elsevier Ltd. All rights reserved.

Constructing Palaeo-DEMs in landscape evolution: example of the Geren catchment, Turkey

NASA Astrophysics Data System (ADS)

van Gorp, Wouter; Schoorl, Jeroen M.; Veldkamp, Tom; Maddy, Darrel; Demir, Tuncer; Aytac, Serdar

2017-04-01

How to reconstruct the past landscape and how does this influence your modelling results? This is an important paradigma in the soilscape and landscape evolution modelling community. Here an example of Turkey will be presented where a 300 ka LEM simulation requested to the thoroughly think about the initial landscape as an important input. What information can be used to know the morphology of a landscape 300 ka ago? The Geren catchment, a tributary of the upstream Gediz river near Kula, Turkey, has been influenced by base level changes during the Late Pleistocene and Holocene. Different lavaflows have blocked the Gediz and Geren river several times over in the timespan of the last 300 ka -200 Ka and in the recent Holocene. The heavily dissected Geren catchment shows a landscape evolution which is more complex than just a reaction on these base level changes. The steps and inputs of the palaeo DEM reconstruction will be presented and the modelling results will be presented. Keywords: Digital Elevation Model, Palaeo DEMs, Numerical modelling

Shaping asteroid models using genetic evolution (SAGE)

NASA Astrophysics Data System (ADS)

Bartczak, P.; Dudziński, G.

2018-02-01

In this work, we present SAGE (shaping asteroid models using genetic evolution), an asteroid modelling algorithm based solely on photometric lightcurve data. It produces non-convex shapes, orientations of the rotation axes and rotational periods of asteroids. The main concept behind a genetic evolution algorithm is to produce random populations of shapes and spin-axis orientations by mutating a seed shape and iterating the process until it converges to a stable global minimum. We tested SAGE on five artificial shapes. We also modelled asteroids 433 Eros and 9 Metis, since ground truth observations for them exist, allowing us to validate the models. We compared the derived shape of Eros with the NEAR Shoemaker model and that of Metis with adaptive optics and stellar occultation observations since other models from various inversion methods were available for Metis.

Regional-Scale Salt Tectonics Modelling: Bench-Scale Validation and Extension to Field-Scale

NASA Astrophysics Data System (ADS)

Crook, A. J. L.; Yu, J. G.; Thornton, D. A.

2010-05-01

The role of salt in the evolution of the West African continental margin, and in particular its impact on hydrocarbon migration and trap formation, is an important research topic. It has attracted many researchers who have based their research on bench-scale experiments, numerical models and seismic observations. This research has shown that the evolution is very complex. For example, regional analogue bench-scale models of the Angolan margin (Fort et al., 2004) indicate a complex system with an upslope extensional domain with sealed tilted blocks, growth fault and rollover systems and extensional diapers, and a downslope contractional domain with squeezed diapirs, polyharmonic folds and thrust faults, and late-stage folding and thrusting. Numerical models have the potential to provide additional insight into the evolution of these salt driven passive margins. The longer-term aim is to calibrate regional-scale evolution models, and then to evaluate the effect of the depositional history on the current day geomechanical and hydrogeologic state in potential target hydrocarbon reservoir formations adjacent to individual salt bodies. To achieve this goal the burial and deformational history of the sediment must be modelled from initial deposition to the current-day state, while also accounting for the reaction and transport processes occurring in the margin. Accurate forward modeling is, however complex, and necessitates advanced procedures for the prediction of fault formation and evolution, representation of the extreme deformations in the salt, and for coupling the geomechanical, fluid flow and temperature fields. The evolution of the sediment due to a combination of mechanical compaction, chemical compaction and creep relaxation must also be represented. In this paper ongoing research on a computational approach for forward modelling complex structural evolution, with particular reference to passive margins driven by salt tectonics is presented. The approach is an extension of a previously published approach (Crook et al., 2006a, 2006b) that focused on predictive modelling of structure evolution in 2-D sandbox experiments, and in particular two extensional sand box experiments that exhibit complex fault development including a series of superimposed crestal collapse graben systems (McClay, 1990) . The formulation adopts a finite strain Lagrangian method, complemented by advanced localization prediction algorithms and robust and efficient automated adaptive meshing techniques. The sediment is represented by an elasto-viscoplastic constitutive model based on extended critical state concepts, which enables representation of the combined effect of mechanical and chemical compaction. This is achieved by directly coupling the evolution of the material state boundary surface with both the mechanically and chemically driven porosity change. Using these procedures the evolution of the geological structures arises naturally from the imposed boundary conditions without the requirement of seeding using initial imperfections. Simulations are presented for regional bench-scale models based on the analogue experiments presented by Fort et al. (2004), together with additional insights provided by the numerical models. It is shown that the behaviour observed in both the extensional and compressional zones of these analogue models arises naturally in the finite element simulations. Extension of these models to the field-scale is then discussed and several simulations are presented to highlight important issues related to practical field-scale numerical modelling.

Fitting models of continuous trait evolution to incompletely sampled comparative data using approximate Bayesian computation.

PubMed

Slater, Graham J; Harmon, Luke J; Wegmann, Daniel; Joyce, Paul; Revell, Liam J; Alfaro, Michael E

2012-03-01

In recent years, a suite of methods has been developed to fit multiple rate models to phylogenetic comparative data. However, most methods have limited utility at broad phylogenetic scales because they typically require complete sampling of both the tree and the associated phenotypic data. Here, we develop and implement a new, tree-based method called MECCA (Modeling Evolution of Continuous Characters using ABC) that uses a hybrid likelihood/approximate Bayesian computation (ABC)-Markov-Chain Monte Carlo approach to simultaneously infer rates of diversification and trait evolution from incompletely sampled phylogenies and trait data. We demonstrate via simulation that MECCA has considerable power to choose among single versus multiple evolutionary rate models, and thus can be used to test hypotheses about changes in the rate of trait evolution across an incomplete tree of life. We finally apply MECCA to an empirical example of body size evolution in carnivores, and show that there is no evidence for an elevated rate of body size evolution in the pinnipeds relative to terrestrial carnivores. ABC approaches can provide a useful alternative set of tools for future macroevolutionary studies where likelihood-dependent approaches are lacking. © 2011 The Author(s). Evolution© 2011 The Society for the Study of Evolution.

Simulating CRN derived erosion rates in a transient Andean catchment using the TTLEM model

NASA Astrophysics Data System (ADS)

Campforts, Benjamin; Vanacker, Veerle; Herman, Frédéric; Schwanghart, Wolfgang; Tenrorio Poma, Gustavo; Govers, Gerard

2017-04-01

Assessing the impact of mountain building and erosion on the earth surface is key to reconstruct and predict terrestrial landscape evolution. Landscape evolution models (LEMs) are an essential tool in this research effort as they allow to integrate our growing understanding of physical processes governing erosion and transport of mass across the surface. The recent development of several LEMs opens up new areas of research in landscape evolution. Here, we want to seize this opportunity by answering a fundamental research question: does a model designed to simulate landscape evolution over geological timescales allows to simulate spatially varying erosion rates at a millennial timescale? We selected the highly transient Paute catchment in the Southeastern Ecuadorian Andes as a study area. We found that our model (TTLEM) is capable to better explain the spatial patterns of ca. 30 Cosmogenic Radio Nuclide (CRN) derived catchment wide erosion rates in comparison to a classical, statistical approach. Thus, the use of process-based landscape evolution models may not only be of great help to understand long-term landscape evolution but also in understanding spatial and temporal variations in sediment fluxes at the millennial time scale.

How Darwinian is cultural evolution?

PubMed Central

Claidière, Nicolas; Scott-Phillips, Thomas C.; Sperber, Dan

2014-01-01

Darwin-inspired population thinking suggests approaching culture as a population of items of different types, whose relative frequencies may change over time. Three nested subtypes of populational models can be distinguished: evolutionary, selectional and replicative. Substantial progress has been made in the study of cultural evolution by modelling it within the selectional frame. This progress has involved idealizing away from phenomena that may be critical to an adequate understanding of culture and cultural evolution, particularly the constructive aspect of the mechanisms of cultural transmission. Taking these aspects into account, we describe cultural evolution in terms of cultural attraction, which is populational and evolutionary, but only selectional under certain circumstances. As such, in order to model cultural evolution, we must not simply adjust existing replicative or selectional models but we should rather generalize them, so that, just as replicator-based selection is one form that Darwinian selection can take, selection itself is one of several different forms that attraction can take. We present an elementary formalization of the idea of cultural attraction. PMID:24686939

How Darwinian is cultural evolution?

PubMed

Claidière, Nicolas; Scott-Phillips, Thomas C; Sperber, Dan

2014-05-19

Darwin-inspired population thinking suggests approaching culture as a population of items of different types, whose relative frequencies may change over time. Three nested subtypes of populational models can be distinguished: evolutionary, selectional and replicative. Substantial progress has been made in the study of cultural evolution by modelling it within the selectional frame. This progress has involved idealizing away from phenomena that may be critical to an adequate understanding of culture and cultural evolution, particularly the constructive aspect of the mechanisms of cultural transmission. Taking these aspects into account, we describe cultural evolution in terms of cultural attraction, which is populational and evolutionary, but only selectional under certain circumstances. As such, in order to model cultural evolution, we must not simply adjust existing replicative or selectional models but we should rather generalize them, so that, just as replicator-based selection is one form that Darwinian selection can take, selection itself is one of several different forms that attraction can take. We present an elementary formalization of the idea of cultural attraction.

General predictive model of friction behavior regimes for metal contacts based on the formation stability and evolution of nanocrystalline surface films.

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

Argibay, Nicolas; Cheng, Shengfeng; Sawyer, W. G.

2015-09-01

The prediction of macro-scale friction and wear behavior based on first principles and material properties has remained an elusive but highly desirable target for tribologists and material scientists alike. Stochastic processes (e.g. wear), statistically described parameters (e.g. surface topography) and their evolution tend to defeat attempts to establish practical general correlations between fundamental nanoscale processes and macro-scale behaviors. We present a model based on microstructural stability and evolution for the prediction of metal friction regimes, founded on recently established microstructural deformation mechanisms of nanocrystalline metals, that relies exclusively on material properties and contact stress models. We show through complementary experimentalmore » and simulation results that this model overcomes longstanding practical challenges and successfully makes accurate and consistent predictions of friction transitions for a wide range of contact conditions. This framework not only challenges the assumptions of conventional causal relationships between hardness and friction, and between friction and wear, but also suggests a pathway for the design of higher performance metal alloys.« less

Modeling of the flow behavior of SAE 8620H combing microstructure evolution in hot forming

NASA Astrophysics Data System (ADS)

Fu, Xiaobin; Wang, Baoyu; Tang, Xuefeng

2017-10-01

With the development of net-shape forming technology, hot forming process is widely applied to manufacturing gear parts, during which, materials suffer severe plastic distortion and microstructure changes continually. In this paper, to understand and model the flow behavior and microstructure evolution, SAE 8620H, a widely used gear steel, is selected as the object and the flow behavior and microstructure evolution are observed by an isothermal hot compression tests at 1273-1373 K with a strain rate of 0.1-10 s-1. Depending on the results of the compression test, a set of internal-state-variable based unified constitutive equations is put forward to describe the flow behavior and microstructure evaluation of SAE 8620H. Moreover, the evaluation of the dislocation density and the fraction of dynamic recrystallization based on the theory of thermal activation is modeled and reincorporated into the constitutive law. The material parameters in the constitutive model are calculated based on the measured flow stress and dynamic recrystallization fraction. The predicted flow stress under different deformation conditions has a good agreement with the measured results.

Reverse engineering a social agent-based hidden markov model--visage.

PubMed

Chen, Hung-Ching Justin; Goldberg, Mark; Magdon-Ismail, Malik; Wallace, William A

2008-12-01

We present a machine learning approach to discover the agent dynamics that drives the evolution of the social groups in a community. We set up the problem by introducing an agent-based hidden Markov model for the agent dynamics: an agent's actions are determined by micro-laws. Nonetheless, We learn the agent dynamics from the observed communications without knowing state transitions. Our approach is to identify the appropriate micro-laws corresponding to an identification of the appropriate parameters in the model. The model identification problem is then formulated as a mixed optimization problem. To solve the problem, we develop a multistage learning process for determining the group structure, the group evolution, and the micro-laws of a community based on the observed set of communications among actors, without knowing the semantic contents. Finally, to test the quality of our approximations and the feasibility of the approach, we present the results of extensive experiments on synthetic data as well as the results on real communities, such as Enron email and Movie newsgroups. Insight into agent dynamics helps us understand the driving forces behind social evolution.

Modeling of Microstructure Evolution During Alloy Solidification

NASA Astrophysics Data System (ADS)

Zhu, Mingfang; Pan, Shiyan; Sun, Dongke

In recent years, considerable advances have been achieved in the numerical modeling of microstructure evolution during solidification. This paper presents the models based on the cellular automaton (CA) technique and lattice Boltzmann method (LBM), which can reproduce a wide variety of solidification microstructure features observed experimentally with an acceptable computational efficiency. The capabilities of the models are addressed by presenting representative examples encompassing a broad variety of issues, such as the evolution of dendritic structure and microsegregation in two and three dimensions, dendritic growth in the presence of convection, divorced eutectic solidification of spheroidal graphite irons, and gas porosity formation. The simulations offer insights into the underlying physics of microstructure formation during alloy solidification.

Is a larger refuge always better? Dispersal and dose in pesticide resistance evolution

PubMed Central

Takahashi, Daisuke; Yamanaka, Takehiko; Sudo, Masaaki; Andow, David A.

2017-01-01

The evolution of resistance against pesticides is an important problem of modern agriculture. The high‐dose/refuge strategy, which divides the landscape into treated and nontreated (refuge) patches, has proven effective at delaying resistance evolution. However, theoretical understanding is still incomplete, especially for combinations of limited dispersal and partially recessive resistance. We reformulate a two‐patch model based on the Comins model and derive a simple quadratic approximation to analyze the effects of limited dispersal, refuge size, and dominance for high efficacy treatments on the rate of evolution. When a small but substantial number of heterozygotes can survive in the treated patch, a larger refuge always reduces the rate of resistance evolution. However, when dominance is small enough, the evolutionary dynamics in the refuge population, which is indirectly driven by migrants from the treated patch, mainly describes the resistance evolution in the landscape. In this case, for small refuges, increasing the refuge size will increase the rate of resistance evolution. Our analysis distils major driving forces from the model, and can provide a framework for understanding directional selection in source‐sink environments. PMID:28422284

Space evolution model and empirical analysis of an urban public transport network

NASA Astrophysics Data System (ADS)

Sui, Yi; Shao, Feng-jing; Sun, Ren-cheng; Li, Shu-jing

2012-07-01

This study explores the space evolution of an urban public transport network, using empirical evidence and a simulation model validated on that data. Public transport patterns primarily depend on traffic spatial-distribution, demands of passengers and expected utility of investors. Evolution is an iterative process of satisfying the needs of passengers and investors based on a given traffic spatial-distribution. The temporal change of urban public transport network is evaluated both using topological measures and spatial ones. The simulation model is validated using empirical data from nine big cities in China. Statistical analyses on topological and spatial attributes suggest that an evolution network with traffic demands characterized by power-law numerical values which distribute in a mode of concentric circles tallies well with these nine cities.

New Frontiers in Language Evolution and Development.

PubMed

Oller, D Kimbrough; Dale, Rick; Griebel, Ulrike

2016-04-01

This article introduces the Special Issue and its focus on research in language evolution with emphasis on theory as well as computational and robotic modeling. A key theme is based on the growth of evolutionary developmental biology or evo-devo. The Special Issue consists of 13 articles organized in two sections: A) Theoretical foundations and B) Modeling and simulation studies. All the papers are interdisciplinary in nature, encompassing work in biological and linguistic foundations for the study of language evolution as well as a variety of computational and robotic modeling efforts shedding light on how language may be developed and may have evolved. Copyright © 2016 Cognitive Science Society, Inc.

Extension of the Genetic Algorithm Based Malware Strategy Evolution Forecasting Model for Botnet Strategy Evolution Modeling

DTIC Science & Technology

2010-11-01

CHEN, Yan; PAXSON, Vern (2009). Automating Analysis of Large- Scale Botnet Probing Events. ASIACCS 󈧍: Proceedings of the 4th International...2004). Email Virus Propagation Modeling and Analysis. Technical report TRCSE- 03-04. – University of Massachussets, 2004. [37] RAMACHANDRAN, Krishna ...20, 8 pp. [38] STANIFORD, Stuart; PAXSON, Vern ; WEAVER, Nicholas (2002). How to 0wn the Internet in Your Spare Time. Proceedings of the 11 th

Optimality models in the age of experimental evolution and genomics.

PubMed

Bull, J J; Wang, I-N

2010-09-01

Optimality models have been used to predict evolution of many properties of organisms. They typically neglect genetic details, whether by necessity or design. This omission is a common source of criticism, and although this limitation of optimality is widely acknowledged, it has mostly been defended rather than evaluated for its impact. Experimental adaptation of model organisms provides a new arena for testing optimality models and for simultaneously integrating genetics. First, an experimental context with a well-researched organism allows dissection of the evolutionary process to identify causes of model failure--whether the model is wrong about genetics or selection. Second, optimality models provide a meaningful context for the process and mechanics of evolution, and thus may be used to elicit realistic genetic bases of adaptation--an especially useful augmentation to well-researched genetic systems. A few studies of microbes have begun to pioneer this new direction. Incompatibility between the assumed and actual genetics has been demonstrated to be the cause of model failure in some cases. More interestingly, evolution at the phenotypic level has sometimes matched prediction even though the adaptive mutations defy mechanisms established by decades of classic genetic studies. Integration of experimental evolutionary tests with genetics heralds a new wave for optimality models and their extensions that does not merely emphasize the forces driving evolution.

Experimental evolution in silico: a custom-designed mathematical model for virulence evolution of Bacillus thuringiensis.

PubMed

Strauß, Jakob Friedrich; Crain, Philip; Schulenburg, Hinrich; Telschow, Arndt

2016-08-01

Most mathematical models on the evolution of virulence are based on epidemiological models that assume parasite transmission follows the mass action principle. In experimental evolution, however, mass action is often violated due to controlled infection protocols. This "theory-experiment mismatch" raises the question whether there is a need for new mathematical models to accommodate the particular characteristics of experimental evolution. Here, we explore the experimental evolution model system of Bacillus thuringiensis as a parasite and Caenorhabditis elegans as a host. Recent experimental studies with strict control of parasite transmission revealed that one-sided adaptation of B. thuringiensis with non-evolving hosts selects for intermediate or no virulence, sometimes coupled with parasite extinction. In contrast, host-parasite coevolution selects for high virulence and for hosts with strong resistance against B. thuringiensis. In order to explain the empirical results, we propose a new mathematical model that mimics the basic experimental set-up. The key assumptions are: (i) controlled parasite transmission (no mass action), (ii) discrete host generations, and (iii) context-dependent cost of toxin production. Our model analysis revealed the same basic trends as found in the experiments. Especially, we could show that resistant hosts select for highly virulent bacterial strains. Moreover, we found (i) that the evolved level of virulence is independent of the initial level of virulence, and (ii) that the average amount of bacteria ingested significantly affects the evolution of virulence with fewer bacteria ingested selecting for highly virulent strains. These predictions can be tested in future experiments. This study highlights the usefulness of custom-designed mathematical models in the analysis and interpretation of empirical results from experimental evolution. Copyright © 2016 The Authors. Published by Elsevier GmbH.. All rights reserved.

Concepts in solid tumor evolution.

PubMed

Sidow, Arend; Spies, Noah

2015-04-01

Evolutionary mechanisms in cancer progression give tumors their individuality. Cancer evolution is different from organismal evolution, however, and we discuss where concepts from evolutionary genetics are useful or limited in facilitating an understanding of cancer. Based on these concepts we construct and apply the simplest plausible model of tumor growth and progression. Simulations using this simple model illustrate the importance of stochastic events early in tumorigenesis, highlight the dominance of exponential growth over linear growth and differentiation, and explain the clonal substructure of tumors. Copyright © 2015 Elsevier Ltd. All rights reserved.

Modeling of the Orbital Evolution of 2060 Chiron

NASA Astrophysics Data System (ADS)

Kovalenko, Nataliya S.; Babenko, Yury G.; Churyumov, Klim I.

2002-03-01

The origin of Centaurs is one of the most interesting problems of Solar system science, and it has not yet been solved. To shed light on this problem one can investigate Centaurs' past and future orbital evolution. In this paper we discuss the results of Chiron's orbital evolution modeling. It was the first discovered Centaur and is the brightest one. Numerical integration was produced for 1 Myr forward and backward from the present time. A program based on the Everhart single sequence method for integrating orbits was used.

Using Agent-Based Modelling to Predict the Role of Wild Refugia in the Evolution of Resistance of Sea Lice to Chemotherapeutants

PubMed Central

McEwan, Gregor F.; Groner, Maya L.; Fast, Mark D.; Revie, Crawford W.

2015-01-01

A major challenge for Atlantic salmon farming in the northern hemisphere is infestation by the sea louse parasite Lepeophtheirus salmonis. The most frequent method of controlling these sea louse infestations is through the use of chemical treatments. However, most major salmon farming areas have observed resistance to common chemotherapeutants. In terrestrial environments, many strategies employed to manage the evolution of resistance involve the use of refugia, where a portion of the population is left untreated to maintain susceptibility. While refugia have not been deliberately used in Atlantic salmon farming, wild salmon populations that migrate close to salmon farms may act as natural refugia. In this paper we describe an agent-based model that explores the influence of different sizes of wild salmon populations on resistance evolution in sea lice on a salmon farm. Using the model, we demonstrate that wild salmon populations can act as refugia that limit the evolution of resistance in the sea louse populations. Additionally, we demonstrate that an increase in the size of the population of wild salmon results in an increased effect in slowing the evolution of resistance. We explore the effect of a population fitness cost associated with resistance, finding that in some cases it substantially reduces the speed of evolution to chemical treatments. PMID:26485023

The Nature of Culture: an eight-grade model for the evolution and expansion of cultural capacities in hominins and other animals.

PubMed

Haidle, Miriam Noël; Bolus, Michael; Collard, Mark; Conard, Nicholas; Garofoli, Duilio; Lombard, Marlize; Nowell, April; Tennie, Claudio; Whiten, Andrew

2015-07-20

Tracing the evolution of human culture through time is arguably one of the most controversial and complex scholarly endeavors, and a broad evolutionary analysis of how symbolic, linguistic, and cultural capacities emerged and developed in our species is lacking. Here we present a model that, in broad terms, aims to explain the evolution and portray the expansion of human cultural capacities (the EECC model), that can be used as a point of departure for further multidisciplinary discussion and more detailed investigation. The EECC model is designed to be flexible, and can be refined to accommodate future archaeological, paleoanthropological, genetic or evolutionary psychology/behavioral analyses and discoveries. Our proposed concept of cultural behavior differentiates between empirically traceable behavioral performances and behavioral capacities that are theoretical constructs. Based largely on archaeological data (the 'black box' that most directly opens up hominin cultural evolution), and on the extension of observable problem-solution distances, we identify eight grades of cultural capacity. Each of these grades is considered within evolutionary-biological and historical-social trajectories. Importantly, the model does not imply an inevitable progression, but focuses on expansion of cultural capacities based on the integration of earlier achievements. We conclude that there is not a single cultural capacity or a single set of abilities that enabled human culture; rather, several grades of cultural capacity in animals and hominins expanded during our evolution to shape who we are today.

An in situ USAXS-SAXS-WAXS study of precipitate size distribution evolution in a model Ni-based alloy.

PubMed

Andrews, Ross N; Serio, Joseph; Muralidharan, Govindarajan; Ilavsky, Jan

2017-06-01

Intermetallic γ' precipitates typically strengthen nickel-based superalloys. The shape, size and spatial distribution of strengthening precipitates critically influence alloy strength, while their temporal evolution characteristics determine the high-temperature alloy stability. Combined ultra-small-, small- and wide-angle X-ray scattering (USAXS-SAXS-WAXS) analysis can be used to evaluate the temporal evolution of an alloy's precipitate size distribution (PSD) and phase structure during in situ heat treatment. Analysis of PSDs from USAXS-SAXS data employs either least-squares fitting of a preordained PSD model or a maximum entropy (MaxEnt) approach, the latter avoiding a priori definition of a functional form of the PSD. However, strong low- q scattering from grain boundaries and/or structure factor effects inhibit MaxEnt analysis of typical alloys. This work describes the extension of Bayesian-MaxEnt analysis methods to data exhibiting structure factor effects and low- q power law slopes and demonstrates their use in an in situ study of precipitate size evolution during heat treatment of a model Ni-Al-Si alloy.

The evolution of dispersal conditioned on migration status

PubMed Central

Asaduzzaman, Sarder Mohammed; Wild, Geoff

2012-01-01

We consider a model for the evolution of dispersal of offspring. Dispersal is treated as a parental trait that is expressed conditional upon a parent’s own “migration status,” that is, whether a parent, itself, is native or nonnative to the area in which it breeds. We compare the evolution of this kind of conditional dispersal to the evolution of unconditional dispersal, in order to determine the extent to which the former changes predictions about population-wide levels of dispersal. We use numerical simulations of an inclusive-fitness model, and individual-based simulations to predict population-average dispersal rates for the case in which dispersal based on migration status occurs. When our model predictions are compared to predictions that neglect conditional dispersal, observed differences between rates are only slight, and never exceed 0.06. While the effect of dispersal conditioned upon migration status could be detected in a carefully designed experiment, we argue that less-than-ideal experimental conditions, and factors such as dispersal conditioned on sex are likely to play a larger role that the type of conditional dispersal studied here. PMID:22837829

An in situ USAXS–SAXS–WAXS study of precipitate size distribution evolution in a model Ni-based alloy

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

Andrews, Ross N.; Serio, Joseph A.; Muralidharan, Govindarajan

Intermetallic γ' precipitates typically strengthen nickel-based superalloys. The shape, size and spatial distribution of strengthening precipitates critically influence alloy strength, while their temporal evolution characteristics determine the high-temperature alloy stability. Combined ultra-small-, small- and wide-angle X-ray scattering (USAXS–SAXS–WAXS) analysis can be used to evaluate the temporal evolution of an alloy's precipitate size distribution (PSD) and phase structure duringin situheat treatment. Analysis of PSDs from USAXS–SAXS data employs either least-squares fitting of a preordained PSD model or a maximum entropy (MaxEnt) approach, the latter avoidinga prioridefinition of a functional form of the PSD. However, strong low-qscattering from grain boundaries and/or structuremore » factor effects inhibit MaxEnt analysis of typical alloys. Lastly, this work describes the extension of Bayesian–MaxEnt analysis methods to data exhibiting structure factor effects and low-qpower law slopes and demonstrates their use in anin situstudy of precipitate size evolution during heat treatment of a model Ni–Al–Si alloy.« less

An in situ USAXS–SAXS–WAXS study of precipitate size distribution evolution in a model Ni-based alloy1

PubMed Central

Andrews, Ross N.; Serio, Joseph; Muralidharan, Govindarajan; Ilavsky, Jan

2017-01-01

Intermetallic γ′ precipitates typically strengthen nickel-based superalloys. The shape, size and spatial distribution of strengthening precipitates critically influence alloy strength, while their temporal evolution characteristics determine the high-temperature alloy stability. Combined ultra-small-, small- and wide-angle X-ray scattering (USAXS–SAXS–WAXS) analysis can be used to evaluate the temporal evolution of an alloy’s precipitate size distribution (PSD) and phase structure during in situ heat treatment. Analysis of PSDs from USAXS–SAXS data employs either least-squares fitting of a preordained PSD model or a maximum entropy (MaxEnt) approach, the latter avoiding a priori definition of a functional form of the PSD. However, strong low-q scattering from grain boundaries and/or structure factor effects inhibit MaxEnt analysis of typical alloys. This work describes the extension of Bayesian–MaxEnt analysis methods to data exhibiting structure factor effects and low-q power law slopes and demonstrates their use in an in situ study of precipitate size evolution during heat treatment of a model Ni–Al–Si alloy. PMID:28656039

An in situ USAXS–SAXS–WAXS study of precipitate size distribution evolution in a model Ni-based alloy

DOE PAGES

Andrews, Ross N.; Serio, Joseph A.; Muralidharan, Govindarajan; ...

2017-05-30

Intermetallic γ' precipitates typically strengthen nickel-based superalloys. The shape, size and spatial distribution of strengthening precipitates critically influence alloy strength, while their temporal evolution characteristics determine the high-temperature alloy stability. Combined ultra-small-, small- and wide-angle X-ray scattering (USAXS–SAXS–WAXS) analysis can be used to evaluate the temporal evolution of an alloy's precipitate size distribution (PSD) and phase structure duringin situheat treatment. Analysis of PSDs from USAXS–SAXS data employs either least-squares fitting of a preordained PSD model or a maximum entropy (MaxEnt) approach, the latter avoidinga prioridefinition of a functional form of the PSD. However, strong low-qscattering from grain boundaries and/or structuremore » factor effects inhibit MaxEnt analysis of typical alloys. Lastly, this work describes the extension of Bayesian–MaxEnt analysis methods to data exhibiting structure factor effects and low-qpower law slopes and demonstrates their use in anin situstudy of precipitate size evolution during heat treatment of a model Ni–Al–Si alloy.« less

Past and Future of Astronomy and SETI Cast in Maths

NASA Astrophysics Data System (ADS)

Maccone, C.

Assume that the history of Astronomy and SETI is the leading proof of the evolution of human knowledge on Earth over the last 3000 years. Then, human knowledge has increased a lot, although not at a uniform pace. A mathematical description of how much human knowledge has increased, however, is difficult to achieve. In this paper, we cast a mathematical model of the evolution of human knowledge over the last three thousand years that seems to reflect reasonably well both what is known from the past and might be extrapolated into the future. Our model is based on two seminal books by Sagan and Finney and Jones. Our model is based on the use of two cubic curves, representing the evolution of Astronomy and of SETI, respectively. We conclude by extrapolating these curves into the future and reach the conclusion that the "Star Trek" age of humankind might possibly begin by the end of this century.

Asymmetric Evolutionary Games.

PubMed

McAvoy, Alex; Hauert, Christoph

2015-08-01

Evolutionary game theory is a powerful framework for studying evolution in populations of interacting individuals. A common assumption in evolutionary game theory is that interactions are symmetric, which means that the players are distinguished by only their strategies. In nature, however, the microscopic interactions between players are nearly always asymmetric due to environmental effects, differing baseline characteristics, and other possible sources of heterogeneity. To model these phenomena, we introduce into evolutionary game theory two broad classes of asymmetric interactions: ecological and genotypic. Ecological asymmetry results from variation in the environments of the players, while genotypic asymmetry is a consequence of the players having differing baseline genotypes. We develop a theory of these forms of asymmetry for games in structured populations and use the classical social dilemmas, the Prisoner's Dilemma and the Snowdrift Game, for illustrations. Interestingly, asymmetric games reveal essential differences between models of genetic evolution based on reproduction and models of cultural evolution based on imitation that are not apparent in symmetric games.

Oxidation-Assisted Crack Growth in Single-Crystal Superalloys during Fatigue with Compressive Holds

NASA Astrophysics Data System (ADS)

Lafata, M. A.; Rettberg, L. H.; He, M. Y.; Pollock, T. M.

2018-01-01

The mechanism of oxidation-assisted growth of surface cracks during fatigue with compressive holds has been studied experimentally and via a model that describes the role of oxide and substrate properties. The creep-based finite element model has been employed to examine the role of material parameters in the damage evolution in a Ni-base single-crystal superalloy René N5. Low-cycle fatigue experiments with compressive holds were conducted at 1255 K and 1366 K (982 °C and 1093 °C). Interrupted and failed specimens were characterized for crack depth and spacing, oxide thickness, and microstructural evolution. Comparison of experimental to modeled hysteresis loops indicates that transient creep drives the macroscopic stress-strain response. Crack penetration rates are strongly influenced by growth stresses in the oxide, structural evolution in the substrate, and the development of γ ^' } denuded zones. Implications for design of alloys resistant to this mode of degradation are discussed.

Is a larger refuge always better? Dispersal and dose in pesticide resistance evolution.

PubMed

Takahashi, Daisuke; Yamanaka, Takehiko; Sudo, Masaaki; Andow, David A

2017-06-01

The evolution of resistance against pesticides is an important problem of modern agriculture. The high-dose/refuge strategy, which divides the landscape into treated and nontreated (refuge) patches, has proven effective at delaying resistance evolution. However, theoretical understanding is still incomplete, especially for combinations of limited dispersal and partially recessive resistance. We reformulate a two-patch model based on the Comins model and derive a simple quadratic approximation to analyze the effects of limited dispersal, refuge size, and dominance for high efficacy treatments on the rate of evolution. When a small but substantial number of heterozygotes can survive in the treated patch, a larger refuge always reduces the rate of resistance evolution. However, when dominance is small enough, the evolutionary dynamics in the refuge population, which is indirectly driven by migrants from the treated patch, mainly describes the resistance evolution in the landscape. In this case, for small refuges, increasing the refuge size will increase the rate of resistance evolution. Our analysis distils major driving forces from the model, and can provide a framework for understanding directional selection in source-sink environments. © 2017 The Author(s). Evolution published by Wiley Periodicals, Inc. on behalf of The Society for the Study of Evolution.

Hydrochemical characteristics and groundwater evolution modeling in sedimentary rocks of the Tono mine, Japan

NASA Astrophysics Data System (ADS)

Sasamoto, Hiroshi; Yui, Mikazu; Arthur, Randolph C.

Based on geochemical data collected by Japan Nuclear Cycle Development Institute (JNC) in the Tono uranium mine, a conceptual groundwater evolution model developed by JNC is tested to evaluate whether equilibrium-based concepts of water-rock interaction are consistent with observed variations in the mineralogy and hydrochemistry of the Tono mine area. The chemical evolution of the groundwaters is modeled assuming local equilibrium for selected mineral-fluid reactions, taking into account the rainwater origin of these solutions. Results suggest that it is possible to interpret approximately the actual groundwater chemistry (i.e., pH, Eh, total dissolved concentrations of Si, Na, Ca, K, Al, carbonate and sulfate) if the following assumptions are adopted (a) CO 2 concentration in the gas phase contacting pore solutions in the overlying soil zone=10 -1 atm, and (b) minerals in the rock zone that control the solubility of respective elements in the groundwater include: chalcedony (Si), albite (Na), kaolinite (Al), calcite (Ca and carbonate), muscovite (K) and pyrite (Eh and sulfate). This result helps to build confidence in the use of simplified geochemical modeling techniques to develop an understanding of dominant geochemical reactions controlling groundwater chemistry in rocks similar to those that could be used for the geological disposal of radioactive wastes. It is noted, however, that the available field data may not be sufficient to adequately constrain parameters in the groundwater evolution model. In particular, more detailed information characterizing certain site properties are needed to improve the model. For this reason, a model that accounts for ion-exchange reactions among clay minerals, and which is based on the results of laboratory experiments, has also been evaluated in the present study. Further improvement of model considering ion-exchange reactions are needed in future, however.

Unity and disunity in evolutionary sciences: process-based analogies open common research avenues for biology and linguistics.

PubMed

List, Johann-Mattis; Pathmanathan, Jananan Sylvestre; Lopez, Philippe; Bapteste, Eric

2016-08-20

For a long time biologists and linguists have been noticing surprising similarities between the evolution of life forms and languages. Most of the proposed analogies have been rejected. Some, however, have persisted, and some even turned out to be fruitful, inspiring the transfer of methods and models between biology and linguistics up to today. Most proposed analogies were based on a comparison of the research objects rather than the processes that shaped their evolution. Focusing on process-based analogies, however, has the advantage of minimizing the risk of overstating similarities, while at the same time reflecting the common strategy to use processes to explain the evolution of complexity in both fields. We compared important evolutionary processes in biology and linguistics and identified processes specific to only one of the two disciplines as well as processes which seem to be analogous, potentially reflecting core evolutionary processes. These new process-based analogies support novel methodological transfer, expanding the application range of biological methods to the field of historical linguistics. We illustrate this by showing (i) how methods dealing with incomplete lineage sorting offer an introgression-free framework to analyze highly mosaic word distributions across languages; (ii) how sequence similarity networks can be used to identify composite and borrowed words across different languages; (iii) how research on partial homology can inspire new methods and models in both fields; and (iv) how constructive neutral evolution provides an original framework for analyzing convergent evolution in languages resulting from common descent (Sapir's drift). Apart from new analogies between evolutionary processes, we also identified processes which are specific to either biology or linguistics. This shows that general evolution cannot be studied from within one discipline alone. In order to get a full picture of evolution, biologists and linguists need to complement their studies, trying to identify cross-disciplinary and discipline-specific evolutionary processes. The fact that we found many process-based analogies favoring transfer from biology to linguistics further shows that certain biological methods and models have a broader scope than previously recognized. This opens fruitful paths for collaboration between the two disciplines. This article was reviewed by W. Ford Doolittle and Eugene V. Koonin.

Prebiological evolution and the metabolic origins of life.

PubMed

Pratt, Andrew J

2011-01-01

The chemoton model of cells posits three subsystems: metabolism, compartmentalization, and information. A specific model for the prebiological evolution of a reproducing system with rudimentary versions of these three interdependent subsystems is presented. This is based on the initial emergence and reproduction of autocatalytic networks in hydrothermal microcompartments containing iron sulfide. The driving force for life was catalysis of the dissipation of the intrinsic redox gradient of the planet. The codependence of life on iron and phosphate provides chemical constraints on the ordering of prebiological evolution. The initial protometabolism was based on positive feedback loops associated with in situ carbon fixation in which the initial protometabolites modified the catalytic capacity and mobility of metal-based catalysts, especially iron-sulfur centers. A number of selection mechanisms, including catalytic efficiency and specificity, hydrolytic stability, and selective solubilization, are proposed as key determinants for autocatalytic reproduction exploited in protometabolic evolution. This evolutionary process led from autocatalytic networks within preexisting compartments to discrete, reproducing, mobile vesicular protocells with the capacity to use soluble sugar phosphates and hence the opportunity to develop nucleic acids. Fidelity of information transfer in the reproduction of these increasingly complex autocatalytic networks is a key selection pressure in prebiological evolution that eventually leads to the selection of nucleic acids as a digital information subsystem and hence the emergence of fully functional chemotons capable of Darwinian evolution.

Three-dimensional microstructure simulation of Ni-based superalloy investment castings

NASA Astrophysics Data System (ADS)

Pan, Dong; Xu, Qingyan; Liu, Baicheng

2011-05-01

An integrated macro and micro multi-scale model for the three-dimensional microstructure simulation of Ni-based superalloy investment castings was developed, and applied to industrial castings to investigate grain evolution during solidification. A ray tracing method was used to deal with the complex heat radiation transfer. The microstructure evolution was simulated based on the Modified Cellular Automaton method, which was coupled with three-dimensional nested macro and micro grids. Experiments for Ni-based superalloy turbine wheel investment casting were carried out, which showed a good correspondence with the simulated results. It is indicated that the proposed model is able to predict the microstructure of the casting precisely, which provides a tool for the optimizing process.

Software evolution. What kind of evolution?

NASA Astrophysics Data System (ADS)

Torres-Carbonell, J. J.; Parets-Llorca, J.

2001-06-01

Most Software Systems capable of adapting to the environment or of performing some kind of adaptive activity (such as pattern learning, behavior simulations and the like) use concepts and models from Biology. Nevertheless, such approaches are based on the Modern Synthesis, i.e., Darwinism plus Mendelism, and this implies preadaptive mutations in, and subsequent selection of the better adapted individuals. These pre-adaptive changes usually do not produce the desired effect, are virtually useless and require some kind of backtracking for the system to obtain profit from adaptation. It is our contention that an evolutionary approach in Software Systems development cannot be based on pre-adaptive mutations, but rather on post-adaptive ones, that is, anticipatory mutations and modifications (Lamarkism). A novel way of understanding evolution in Software Systems based on applied Lamarkism is presented and a framework that allows the incorporation of modifications according to the necessities of the system and the will of the modeller is proposed.

The Evolution of Haploid Chromosome Numbers in the Sunflower Family

PubMed Central

Mota, Lucie; Torices, Rubén; Loureiro, João

2016-01-01

Chromosome number changes during the evolution of angiosperms are likely to have played a major role in speciation. Their study is of utmost importance, especially now, as a probabilistic model is available to study chromosome evolution within a phylogenetic framework. In the present study, likelihood models of chromosome number evolution were fitted to the largest family of flowering plants, the Asteraceae. Specifically, a phylogenetic supertree of this family was used to reconstruct the ancestral chromosome number and infer genomic events. Our approach inferred that the ancestral chromosome number of the family is n = 9. Also, according to the model that best explained our data, the evolution of haploid chromosome numbers in Asteraceae was a very dynamic process, with genome duplications and descending dysploidy being the most frequent genomic events in the evolution of this family. This model inferred more than one hundred whole genome duplication events; however, it did not find evidence for a paleopolyploidization at the base of this family, which has previously been hypothesized on the basis of sequence data from a limited number of species. The obtained results and potential causes of these discrepancies are discussed. PMID:27797951

Order reduction for a model of marine bacteriophage evolution

NASA Astrophysics Data System (ADS)

Pagliarini, Silvia; Korobeinikov, Andrei

2017-02-01

A typical mechanistic model of viral evolution necessary includes several time scales which can differ by orders of magnitude. Such a diversity of time scales makes analysis of these models difficult. Reducing the order of a model is highly desirable when handling such a model. A typical approach applied to such slow-fast (or singularly perturbed) systems is the time scales separation technique. Constructing the so-called quasi-steady-state approximation is the usual first step in applying the technique. While this technique is commonly applied, in some cases its straightforward application can lead to unsatisfactory results. In this paper we construct the quasi-steady-state approximation for a model of evolution of marine bacteriophages based on the Beretta-Kuang model. We show that for this particular model the quasi-steady-state approximation is able to produce only qualitative but not quantitative fit.

Evolution of the Radial Abundance Gradient and Cold Gas along the Milky Way Disk

NASA Astrophysics Data System (ADS)

Chen, Q. S.; Chang, R. X.; Yin, J.

2014-03-01

We have constructed a phenomenological model of the chemical evolution of the Milky Way disk, and treated the molecular and atomic gas separately. Using this model, we explore the radial profiles of oxygen abundance, the surface density of cold gas, and their time evolutions. It is shown that the model predictions are very sensitive to the adopted infall time-scale. By comparing the model predictions with the observations, we find that the model adopting the star formation law based on H_2 can properly predict the observed radial distributions of cold gas and oxygen abundance gradient along the disk. We also compare the model results with the predictions of the model which adopts the instantaneous recycling approximation (IRA), and find that the IRA assumption has little influence on the model results, especially in the low-density gas region.

Information of Complex Systems and Applications in Agent Based Modeling.

PubMed

Bao, Lei; Fritchman, Joseph C

2018-04-18

Information about a system's internal interactions is important to modeling the system's dynamics. This study examines the finer categories of the information definition and explores the features of a type of local information that describes the internal interactions of a system. Based on the results, a dual-space agent and information modeling framework (AIM) is developed by explicitly distinguishing an information space from the material space. The two spaces can evolve both independently and interactively. The dual-space framework can provide new analytic methods for agent based models (ABMs). Three examples are presented including money distribution, individual's economic evolution, and artificial stock market. The results are analyzed in the dual-space, which more clearly shows the interactions and evolutions within and between the information and material spaces. The outcomes demonstrate the wide-ranging applicability of using the dual-space AIMs to model and analyze a broad range of interactive and intelligent systems.

Crystal plasticity assisted prediction on the yield locus evolution and forming limit curves

NASA Astrophysics Data System (ADS)

Lian, Junhe; Liu, Wenqi; Shen, Fuhui; Münstermann, Sebastian

2017-10-01

The aim of this study is to predict the plastic anisotropy evolution and its associated forming limit curves of bcc steels purely based on their microstructural features by establishing an integrated multiscale modelling approach. Crystal plasticity models are employed to describe the micro deformation mechanism and correlate the microstructure with mechanical behaviour on micro and mesoscale. Virtual laboratory is performed considering the statistical information of the microstructure, which serves as the input for the phenomenological plasticity model on the macroscale. For both scales, the microstructure evolution induced evolving features, such as the anisotropic hardening, r-value and yield locus evolution are seamlessly integrated. The predicted plasticity behaviour by the numerical simulations are compared with experiments. These evolutionary features of the material deformation behaviour are eventually considered for the prediction of formability.

Stochastic damage evolution in textile laminates

NASA Technical Reports Server (NTRS)

Dzenis, Yuris A.; Bogdanovich, Alexander E.; Pastore, Christopher M.

1993-01-01

A probabilistic model utilizing random material characteristics to predict damage evolution in textile laminates is presented. Model is based on a division of each ply into two sublaminas consisting of cells. The probability of cell failure is calculated using stochastic function theory and maximal strain failure criterion. Three modes of failure, i.e. fiber breakage, matrix failure in transverse direction, as well as matrix or interface shear cracking, are taken into account. Computed failure probabilities are utilized in reducing cell stiffness based on the mesovolume concept. A numerical algorithm is developed predicting the damage evolution and deformation history of textile laminates. Effect of scatter of fiber orientation on cell properties is discussed. Weave influence on damage accumulation is illustrated with the help of an example of a Kevlar/epoxy laminate.

Phenomenological approach to mechanical damage growth analysis.

PubMed

Pugno, Nicola; Bosia, Federico; Gliozzi, Antonio S; Delsanto, Pier Paolo; Carpinteri, Alberto

2008-10-01

The problem of characterizing damage evolution in a generic material is addressed with the aim of tracing it back to existing growth models in other fields of research. Based on energetic considerations, a system evolution equation is derived for a generic damage indicator describing a material system subjected to an increasing external stress. The latter is found to fit into the framework of a recently developed phenomenological universality (PUN) approach and, more specifically, the so-called U2 class. Analytical results are confirmed by numerical simulations based on a fiber-bundle model and statistically assigned local strengths at the microscale. The fits with numerical data prove, with an excellent degree of reliability, that the typical evolution of the damage indicator belongs to the aforementioned PUN class. Applications of this result are briefly discussed and suggested.

Recent topographic evolution and erosion of the deglaciated Washington Cascades inferred from a stochastic landscape evolution model

NASA Astrophysics Data System (ADS)

Moon, Seulgi; Shelef, Eitan; Hilley, George E.

2015-05-01

In this study, we model postglacial surface processes and examine the evolution of the topography and denudation rates within the deglaciated Washington Cascades to understand the controls on and time scales of landscape response to changes in the surface process regime after deglaciation. The postglacial adjustment of this landscape is modeled using a geomorphic-transport-law-based numerical model that includes processes of river incision, hillslope diffusion, and stochastic landslides. The surface lowering due to landslides is parameterized using a physically based slope stability model coupled to a stochastic model of the generation of landslides. The model parameters of river incision and stochastic landslides are calibrated based on the rates and distribution of thousand-year-time scale denudation rates measured from cosmogenic 10Be isotopes. The probability distributions of those model parameters calculated based on a Bayesian inversion scheme show comparable ranges from previous studies in similar rock types and climatic conditions. The magnitude of landslide denudation rates is determined by failure density (similar to landslide frequency), whereas precipitation and slopes affect the spatial variation in landslide denudation rates. Simulation results show that postglacial denudation rates decay over time and take longer than 100 kyr to reach time-invariant rates. Over time, the landslides in the model consume the steep slopes characteristic of deglaciated landscapes. This response time scale is on the order of or longer than glacial/interglacial cycles, suggesting that frequent climatic perturbations during the Quaternary may produce a significant and prolonged impact on denudation and topography.

Feature saltation and the evolution of mimicry.

PubMed

Gamberale-Stille, Gabriella; Balogh, Alexandra C V; Tullberg, Birgitta S; Leimar, Olof

2012-03-01

In Batesian mimicry, a harmless prey species imitates the warning coloration of an unpalatable model species. A traditional suggestion is that mimicry evolves in a two-step process, in which a large mutation first achieves approximate similarity to the model, after which smaller changes improve the likeness. However, it is not known which aspects of predator psychology cause the initial mutant to be perceived by predators as being similar to the model, leaving open the question of how the crucial first step of mimicry evolution occurs. Using theoretical evolutionary simulations and reconstruction of examples of mimicry evolution, we show that the evolution of Batesian mimicry can be initiated by a mutation that causes prey to acquire a trait that is used by predators as a feature to categorize potential prey as unsuitable. The theory that species gain entry to mimicry through feature saltation allows us to formulate scenarios of the sequence of events during mimicry evolution and to reconstruct an initial mimetic appearance for important examples of Batesian mimicry. Because feature-based categorization by predators entails a qualitative distinction between nonmimics and passable mimics, the theory can explain the occurrence of imperfect mimicry. © 2011 The Author(s). Evolution© 2011 The Society for the Study of Evolution.

Modelling Influence and Opinion Evolution in Online Collective Behaviour

PubMed Central

Gend, Pascal; Rentfrow, Peter J.; Hendrickx, Julien M.; Blondel, Vincent D.

2016-01-01

Opinion evolution and judgment revision are mediated through social influence. Based on a large crowdsourced in vitro experiment (n = 861), it is shown how a consensus model can be used to predict opinion evolution in online collective behaviour. It is the first time the predictive power of a quantitative model of opinion dynamics is tested against a real dataset. Unlike previous research on the topic, the model was validated on data which did not serve to calibrate it. This avoids to favor more complex models over more simple ones and prevents overfitting. The model is parametrized by the influenceability of each individual, a factor representing to what extent individuals incorporate external judgments. The prediction accuracy depends on prior knowledge on the participants’ past behaviour. Several situations reflecting data availability are compared. When the data is scarce, the data from previous participants is used to predict how a new participant will behave. Judgment revision includes unpredictable variations which limit the potential for prediction. A first measure of unpredictability is proposed. The measure is based on a specific control experiment. More than two thirds of the prediction errors are found to occur due to unpredictability of the human judgment revision process rather than to model imperfection. PMID:27336834

Modeling the long-term evolution of space debris

DOEpatents

Nikolaev, Sergei; De Vries, Willem H.; Henderson, John R.; Horsley, Matthew A.; Jiang, Ming; Levatin, Joanne L.; Olivier, Scot S.; Pertica, Alexander J.; Phillion, Donald W.; Springer, Harry K.

2017-03-07

A space object modeling system that models the evolution of space debris is provided. The modeling system simulates interaction of space objects at simulation times throughout a simulation period. The modeling system includes a propagator that calculates the position of each object at each simulation time based on orbital parameters. The modeling system also includes a collision detector that, for each pair of objects at each simulation time, performs a collision analysis. When the distance between objects satisfies a conjunction criterion, the modeling system calculates a local minimum distance between the pair of objects based on a curve fitting to identify a time of closest approach at the simulation times and calculating the position of the objects at the identified time. When the local minimum distance satisfies a collision criterion, the modeling system models the debris created by the collision of the pair of objects.

A coevolving model based on preferential triadic closure for social media networks

PubMed Central

Li, Menghui; Zou, Hailin; Guan, Shuguang; Gong, Xiaofeng; Li, Kun; Di, Zengru; Lai, Choy-Heng

2013-01-01

The dynamical origin of complex networks, i.e., the underlying principles governing network evolution, is a crucial issue in network study. In this paper, by carrying out analysis to the temporal data of Flickr and Epinions–two typical social media networks, we found that the dynamical pattern in neighborhood, especially the formation of triadic links, plays a dominant role in the evolution of networks. We thus proposed a coevolving dynamical model for such networks, in which the evolution is only driven by the local dynamics–the preferential triadic closure. Numerical experiments verified that the model can reproduce global properties which are qualitatively consistent with the empirical observations. PMID:23979061

A mathematical model of marine bacteriophage evolution.

PubMed

Pagliarini, Silvia; Korobeinikov, Andrei

2018-03-01

To explore how particularities of a host cell-virus system, and in particular host cell replication, affect viral evolution, in this paper we formulate a mathematical model of marine bacteriophage evolution. The intrinsic simplicity of real-life phage-bacteria systems, and in particular aquatic systems, for which the assumption of homogeneous mixing is well justified, allows for a reasonably simple model. The model constructed in this paper is based upon the Beretta-Kuang model of bacteria-phage interaction in an aquatic environment (Beretta & Kuang 1998 Math. Biosci. 149 , 57-76. (doi:10.1016/S0025-5564(97)10015-3)). Compared to the original Beretta-Kuang model, the model assumes the existence of a multitude of viral variants which correspond to continuously distributed phenotypes. It is noteworthy that the model is mechanistic (at least as far as the Beretta-Kuang model is mechanistic). Moreover, this model does not include any explicit law or mechanism of evolution; instead it is assumed, in agreement with the principles of Darwinian evolution, that evolution in this system can occur as a result of random mutations and natural selection. Simulations with a simplistic linear fitness landscape (which is chosen for the convenience of demonstration only and is not related to any real-life system) show that a pulse-type travelling wave moving towards increasing Darwinian fitness appears in the phenotype space. This implies that the overall fitness of a viral quasi-species steadily increases with time. That is, the simulations demonstrate that for an uneven fitness landscape random mutations combined with a mechanism of natural selection (for this particular system this is given by the conspecific competition for the resource) lead to the Darwinian evolution. It is noteworthy that in this system the speed of propagation of this wave (and hence the rate of evolution) is not constant but varies, depending on the current viral fitness and the abundance of susceptible bacteria. A specific feature of the original Beretta-Kuang model is that this model exhibits a supercritical Hopf bifurcation, leading to the loss of stability and the rise of self-sustained oscillations in the system. This phenomenon corresponds to the paradox of enrichment in the system. It is remarkable that under the conditions that ensure the bifurcation in the Beretta-Kuang model, the viral evolution model formulated in this paper also exhibits a rise in self-sustained oscillations of the abundance of all interacting populations. The propagation of the travelling wave, however, remains stable under these conditions. The only visible impact of the oscillations on viral evolution is a lower speed of the evolution.

Ca-Pri a Cellular Automata Phenomenological Research Investigation: Simulation Results

NASA Astrophysics Data System (ADS)

Iannone, G.; Troisi, A.

2013-05-01

Following the introduction of a phenomenological cellular automata (CA) model capable to reproduce city growth and urban sprawl, we develop a toy model simulation considering a realistic framework. The main characteristic of our approach is an evolution algorithm based on inhabitants preferences. The control of grown cells is obtained by means of suitable functions which depend on the initial condition of the simulation. New born urban settlements are achieved by means of a logistic evolution of the urban pattern while urban sprawl is controlled by means of the population evolution function. In order to compare model results with a realistic urban framework we have considered, as the area of study, the island of Capri (Italy) in the Mediterranean Sea. Two different phases of the urban evolution on the island have been taken into account: a new born initial growth as induced by geographic suitability and the simulation of urban spread after 1943 induced by the population evolution after this date.

Analysis of a Moodle-Based Training Program about the Pedagogical Content Knowledge of Evolution Theory and Natural Selection

ERIC Educational Resources Information Center

Stasinakis, Panagiotis K.; Kalogiannnakis, Michail

2017-01-01

In this study we aim to find out whether a training program for secondary school science teachers which was organized based on the model of Pedagogical Content Knowledge (PCK), could improve their individual PCK for a specific scientific issue. The Evolution Theory (ET) and the Natural Selection (NS) were chosen as the scientific issues of…

Exploring the impact of multiple grain sizes in numerical landscape evolution model

NASA Astrophysics Data System (ADS)

Guerit, Laure; Braun, Jean; Yuan, Xiaoping; Rouby, Delphine

2017-04-01

Numerical evolution models have been widely developed in order to understand the evolution of landscape over different time-scales, but also the response of the topography to changes in external conditions, such as tectonics or climate, or to changes in the bedrock characteristics, such as its density or its erodability. Few models have coupled the evolution of the relief in erosion to the evolution of the related area in deposition, and in addition, such models generally do not consider the role of the size of the sediments reached the depositional domain. Here, we present a preliminary work based on an enhanced version of Fastscape, a very-efficient model solving the stream power equation, which now integrates a sedimentary basin at the front of a relief, together with the integration of multiple grain sizes in the system. Several simulations were performed in order to explore the impact of several grain sizes in terms of stratigraphy in the marine basin. A simple setting is considered, with uniform uplift rate, precipitation rate, and rock properties onshore. The pros and cons of this approach are discussed with respect to similar simulations performed considering only flux.

A new model of physical evolution of Jupiter-family comets

NASA Astrophysics Data System (ADS)

Rickman, H.; Szutowicz, S.; Wójcikowski, K.

2014-07-01

We aim to find the statistical physical lifetimes of Jupiter Family comets. For this purpose, we try to model the processes that govern the dynamical and physical evolution of comets. We pay special attention to physical evolution; attempts at such modelling have been made before, but we propose a more accurate model, which will include more physical effects. The model is tested on a sample of fictitious comets based on real Jupiter Family comets with some orbital elements changed to a state before the capture by Jupiter. We model four different physical effects: erosion by sublimation, dust mantling, rejuvenation (mantle blow-off), and splitting. While for sublimation and splitting there already are some models, like di Sisto et. al. (2009), and we only wish to make them more accurate, dust mantling and rejuvenation have not been included in previous, statistical physical evolution models. Each of these effects depends on one or more tunable parameters, which we establish by choosing the model that best fits the observed comet sample in a way similar to di Sisto et. al. (2009). In contrast to di Sisto et. al., our comparison also involves the observed active fractions vs. nuclear radii.

A two-scale model for dynamic damage evolution

NASA Astrophysics Data System (ADS)

Keita, Oumar; Dascalu, Cristian; François, Bertrand

2014-03-01

This paper presents a new micro-mechanical damage model accounting for inertial effect. The two-scale damage model is fully deduced from small-scale descriptions of dynamic micro-crack propagation under tensile loading (mode I). An appropriate micro-mechanical energy analysis is combined with homogenization based on asymptotic developments in order to obtain the macroscopic evolution law for damage. Numerical simulations are presented in order to illustrate the ability of the model to describe known behaviors like size effects for the structural response, strain-rate sensitivity, brittle-ductile transition and wave dispersion.

Hidden long evolutionary memory in a model biochemical network

NASA Astrophysics Data System (ADS)

Ali, Md. Zulfikar; Wingreen, Ned S.; Mukhopadhyay, Ranjan

2018-04-01

We introduce a minimal model for the evolution of functional protein-interaction networks using a sequence-based mutational algorithm, and apply the model to study neutral drift in networks that yield oscillatory dynamics. Starting with a functional core module, random evolutionary drift increases network complexity even in the absence of specific selective pressures. Surprisingly, we uncover a hidden order in sequence space that gives rise to long-term evolutionary memory, implying strong constraints on network evolution due to the topology of accessible sequence space.

Grandmothering life histories and human pair bonding.

PubMed

Coxworth, James E; Kim, Peter S; McQueen, John S; Hawkes, Kristen

2015-09-22

The evolution of distinctively human life history and social organization is generally attributed to paternal provisioning based on pair bonds. Here we develop an alternative argument that connects the evolution of human pair bonds to the male-biased mating sex ratios that accompanied the evolution of human life history. We simulate an agent-based model of the grandmother hypothesis, compare simulated sex ratios to data on great apes and human hunter-gatherers, and note associations between a preponderance of males and mate guarding across taxa. Then we explore a recent model that highlights the importance of mating sex ratios for differences between birds and mammals and conclude that lessons for human evolution cannot ignore mammalian reproductive constraints. In contradiction to our claim that male-biased sex ratios are characteristically human, female-biased ratios are reported in some populations. We consider the likelihood that fertile men are undercounted and conclude that the mate-guarding hypothesis for human pair bonds gains strength from explicit links with our grandmothering life history.

Evolving dynamics of trading behavior based on coordination game in complex networks

NASA Astrophysics Data System (ADS)

Bian, Yue-tang; Xu, Lu; Li, Jin-sheng

2016-05-01

This work concerns the modeling of evolvement of trading behavior in stock markets. Based on the assumption of the investors' limited rationality, the evolution mechanism of trading behavior is modeled according to the investment strategy of coordination game in network, that investors are prone to imitate their neighbors' activity through comprehensive analysis on the risk dominance degree of certain investment behavior, the network topology of their relationship and its heterogeneity. We investigate by mean-field analysis and extensive simulations the evolution of investors' trading behavior in various typical networks under different risk dominance degree of investment behavior. Our results indicate that the evolution of investors' behavior is affected by the network structure of stock market and the effect of risk dominance degree of investment behavior; the stability of equilibrium states of investors' behavior dynamics is directly related with the risk dominance degree of some behavior; connectivity and heterogeneity of the network plays an important role in the evolution of the investment behavior in stock market.

Modeling carbon production and transport during ELMs in DIII-D

NASA Astrophysics Data System (ADS)

Hogan, J.; Wade, M.; Coster, D.; Lasnier, C.

2004-11-01

Large-scale Type I ELM events could provide a significant C source in ITER, and C production rates depend on incident D flux density and surface temperature, quantities which can vary significantly during an ELM event. Recent progress on DIII-D has improved opportunities for code comparison. Fast time-scale measurements of divertor CIII evolution [1] and fast edge CER measurements of C profile evolution during low-density DIII-D LSN ELMy H-modes (type I) [2] have been modeled using the solps5.0/Eirene99 coupled edge code and time dependent thermal analysis codes. An ELM model based on characteristics of MHD peeling-ballooning modes reproduces the pedestal evolution. Qualitative agreement for the CIII evolution during an ELM event is found using the Roth et al annealing model for chemical sputtering and the sensitivity to other models is described. Significant ELM-to-ELM variations in observed maximum divertor target IR temperature during nominally identical ELMs are investigated with models for C emission from micron-scale dust particles. [1] M Groth, M Fenstermacher et al J Nucl Mater 2003, [2] M Wade, K Burrell et al PSI-16

Barrier displacement on a neutral landscape: Towards a theory of continental biogeography

USGS Publications Warehouse

Albert, James S.; Schoolmaster, Donald; Tagliacollo, Victor; Duke-Sylvester, Scott M.

2017-01-01

Here we present SEAMLESS (Spatially-Explicit Area Model of Landscape Evolution by SimulationS) that generates clade diversification by moving geographic barriers on a continuous, neutral landscape. SEAMLESS is a neutral Landscape Evolution Model (LEM) that treats species and barriers as functionally equivalent with respect to model parameters. SEAMLESS differs from other model-based biogeographic methods (e.g. Lagrange, GeoSSE, BayArea, BioGeoBEARS) by modeling properties of dispersal barriers rather than areas, and by modeling the evolution of species lineages on a continuous landscape, rather than the evolution of geographic ranges along branches of a phylogeny. SEAMLESS shows how dispersal is required to maintain species richness and avoid clade-wide extinction, demonstrates that ancestral range size does not predict species richness, and provides a unified explanation for the suite of commonly observed biogeographic and phylogenetic patterns listed above. SEAMLESS explains how a simple barrier-displacement mechanism affects lineage diversification under neutral conditions, and is advanced here towards the formulation of a general theory of continental biogeography.                   

Battery parameterisation based on differential evolution via a boundary evolution strategy

NASA Astrophysics Data System (ADS)

Yang, Guangya

2014-01-01

Attention has been given to the battery modelling in the electric engineering field following the current development of renewable energy and electrification of transportation. The establishment of the equivalent circuit model of the battery requires data preparation and parameterisation. Besides, as the equivalent circuit model is an abstract map of the battery electric characteristics, the determination of the possible ranges of parameters can be a challenging task. In this paper, an efficient yet easy to implement method is proposed to parameterise the equivalent circuit model of batteries utilising the advances of evolutionary algorithms (EAs). Differential evolution (DE) is selected and modified to parameterise an equivalent circuit model of lithium-ion batteries. A boundary evolution strategy (BES) is developed and incorporated into the DE to update the parameter boundaries during the parameterisation. The method can parameterise the model without extensive data preparation. In addition, the approach can also estimate the initial SOC and the available capacity. The efficiency of the approach is verified through two battery packs, one is an 8-cell battery module and one from an electrical vehicle.

Modeling damage evolution in a hybrid ceramic matrix composite under static tensile load

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

Bonora, N.; Newaz, G.

In this investigation, damage evolution in a unidirectional hybrid ceramic composite made from Nicalon and SiC fibers in a Lithium Aluminosilicate (LAS) glass matrix was studied. The static stress-strain response of the composite exhibited a linear response followed by load drop in a progressive manner. Careful experiments were conducted stopping the tests at various strain levels and using replication technique, scanning and optical microscopy to monitor the evolution of damage in these composites. It was observed that the constituents of the composite failed in a sequential manner at increasing strain levels. The matrix cracks were followed by SiC fiber failuresmore » near ultimate tensile stress. After that, the load drop was associated with progressive failure of the Nicalon fibers. Identification of these failure modes were critical to the development of a concentric cylinder model representing all three constituent phases to predict the constitutive response of the CMC computationally. The strain-to-failure of the matrix and fibers were used to progressively fail the constituents in the model and the overall experimental constitutive response of the CMC was recovered. A strain based analytical representation was developed relating stiffness loss to applied strain. Based on this formulation, damage evolution and its consequence on tensile stress-strain response was predicted for room temperature behavior of hybrid CMCs. The contribution of the current work is that the proposed strain-damage phenomenological model can capture the damage evolution and the corresponding material response for continuous fiber-reinforced CMCs. The modeling approach shows much promise for the complex damage processes observed in hybrid CMCs.« less

A new model for biological effects of radiation and the driven force of molecular evolution

NASA Astrophysics Data System (ADS)

Wada, Takahiro; Manabe, Yuichiro; Nakajima, Hiroo; Tsunoyama, Yuichi; Bando, Masako

We proposed a new mathematical model to estimate biological effects of radiation, which we call Whack-A-Mole (WAM) model. A special feature of WAM model is that it involves the dose rate of radiation as a key ingredient. We succeeded to reproduce the experimental data of various species concerning the radiation induced mutation frequencies. From the analysis of the mega-mouse experiments, we obtained the mutation rate per base-pair per year for mice which is consistent with the so-called molecular clock in evolution genetics, 10-9 mutation/base-pair/year. Another important quantity is the equivalent dose rate for the whole spontaneous mutation, deff. The value of deff for mice is 1.1*10-3 Gy/hour which is much larger than the dose rate of natural radiation (10- (6 - 7) Gy/hour) by several orders of magnitude. We also analyzed Drosophila data and obtained essentially the same numbers. This clearly indicates that the natural radiation is not the dominant driving force of the molecular evolution, but we should look for other factors, such as miscopy of DNA in duplication process. We believe this is the first quantitative proof of the small contribution of the natural radiation in the molecular evolution.

Cloud computing task scheduling strategy based on improved differential evolution algorithm

NASA Astrophysics Data System (ADS)

Ge, Junwei; He, Qian; Fang, Yiqiu

2017-04-01

In order to optimize the cloud computing task scheduling scheme, an improved differential evolution algorithm for cloud computing task scheduling is proposed. Firstly, the cloud computing task scheduling model, according to the model of the fitness function, and then used improved optimization calculation of the fitness function of the evolutionary algorithm, according to the evolution of generation of dynamic selection strategy through dynamic mutation strategy to ensure the global and local search ability. The performance test experiment was carried out in the CloudSim simulation platform, the experimental results show that the improved differential evolution algorithm can reduce the cloud computing task execution time and user cost saving, good implementation of the optimal scheduling of cloud computing tasks.

Using Decision Structures for Policy Analysis in Software Product-line Evolution - A Case Study

NASA Astrophysics Data System (ADS)

Sarang, Nita; Sanglikar, Mukund A.

Project management decisions are the primary basis for project success (or failure). Mostly, such decisions are based on an intuitive understanding of the underlying software engineering and management process and have a likelihood of being misjudged. Our problem domain is product-line evolution. We model the dynamics of the process by incorporating feedback loops appropriate to two decision structures: staffing policy, and the forces of growth associated with long-term software evolution. The model is executable and supports project managers to assess the long-term effects of possible actions. Our work also corroborates results from earlier studies of E-type systems, in particular the FEAST project and the rules for software evolution, planning and management.

Comparative empirical analysis of flow-weighted transit route networks in R-space and evolution modeling

NASA Astrophysics Data System (ADS)

Huang, Ailing; Zang, Guangzhi; He, Zhengbing; Guan, Wei

2017-05-01

Urban public transit system is a typical mixed complex network with dynamic flow, and its evolution should be a process coupling topological structure with flow dynamics, which has received little attention. This paper presents the R-space to make a comparative empirical analysis on Beijing’s flow-weighted transit route network (TRN) and we found that both the Beijing’s TRNs in the year of 2011 and 2015 exhibit the scale-free properties. As such, we propose an evolution model driven by flow to simulate the development of TRNs with consideration of the passengers’ dynamical behaviors triggered by topological change. The model simulates that the evolution of TRN is an iterative process. At each time step, a certain number of new routes are generated driven by travel demands, which leads to dynamical evolution of new routes’ flow and triggers perturbation in nearby routes that will further impact the next round of opening new routes. We present the theoretical analysis based on the mean-field theory, as well as the numerical simulation for this model. The results obtained agree well with our empirical analysis results, which indicate that our model can simulate the TRN evolution with scale-free properties for distributions of node’s strength and degree. The purpose of this paper is to illustrate the global evolutional mechanism of transit network that will be used to exploit planning and design strategies for real TRNs.

The bankfull hydraulic geometry of evolving meander bends

NASA Astrophysics Data System (ADS)

Monegaglia, F.; Tubino, M.; Zolezzi, G.

2017-12-01

Changes in the bankfull hydraulic geometry of meandering rivers associated with meander growth from incipient meandering to cutoffs have seldom been analysed in detail. Such information is also needed by meander morphodynamic models, most of which simulate the evolution of bankfull channel geometry by simply accounting for channel slope reduction inversely proportional to elongation, while changes in bankfull channel width are often neglected or, when they are considered, they are not consistent with the few available observations. To address these gaps we first perform an extensive, systematic, bend-scale evolutionary analysis of bankfull channel widths in several large meandering rivers in the Amazon basin, over a three decades time period, from remotely sensed field data. The analysis consistently show a slight decreasing trend of the bankfull channel width during the planform evolution towards cutoff. Furthermore, we develop a physically based model for the evolution of bankfull channel geometry during the planform development of meandering rivers. The model is based on the conservation of sediment discharge. An integrated one-dimensional Exner equation that accounts for meander elongation, sediment supply conservation and sediment income from the channel banks, allows us to predict the evolution of the channel slope. The evolution of the channel width is modeled through a threshold equation. The model correctly predicts the slight variability of channel width during meander development and a gentler reduction of the channel slope, which is mitigated by the conservation of sediment supply. The bankfull geometry of highly dynamic meandering rivers is predicted to be elongation-dominated, while the one related to slowly evolving meandering rivers is sediment supply-dominated. Finally, we discuss the implications of the proposed modeling framework in terms of planform structure, meander shape and morphodynamic influence.

Size Evolution and Stochastic Models: Explaining Ostracod Size through Probabilistic Distributions

NASA Astrophysics Data System (ADS)

Krawczyk, M.; Decker, S.; Heim, N. A.; Payne, J.

2014-12-01

The biovolume of animals has functioned as an important benchmark for measuring evolution throughout geologic time. In our project, we examined the observed average body size of ostracods over time in order to understand the mechanism of size evolution in these marine organisms. The body size of ostracods has varied since the beginning of the Ordovician, where the first true ostracods appeared. We created a stochastic branching model to create possible evolutionary trees of ostracod size. Using stratigraphic ranges for ostracods compiled from over 750 genera in the Treatise on Invertebrate Paleontology, we calculated overall speciation and extinction rates for our model. At each timestep in our model, new lineages can evolve or existing lineages can become extinct. Newly evolved lineages are assigned sizes based on their parent genera. We parameterized our model to generate neutral and directional changes in ostracod size to compare with the observed data. New sizes were chosen via a normal distribution, and the neutral model selected new sizes differentials centered on zero, allowing for an equal chance of larger or smaller ostracods at each speciation. Conversely, the directional model centered the distribution on a negative value, giving a larger chance of smaller ostracods. Our data strongly suggests that the overall direction of ostracod evolution has been following a model that directionally pushes mean ostracod size down, shying away from a neutral model. Our model was able to match the magnitude of size decrease. Our models had a constant linear decrease while the actual data had a much more rapid initial rate followed by a constant size. The nuance of the observed trends ultimately suggests a more complex method of size evolution. In conclusion, probabilistic methods can provide valuable insight into possible evolutionary mechanisms determining size evolution in ostracods.

Investigation on temporal evolution of the grain refinement in copper under high strain rate loading via in-situ synchrotron measurement and predictive modeling

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

Shah, Pooja Nitin; Shin, Yung C.; Sun, Tao

Synchrotron X-rays are integrated with a modified Kolsky tension bar to conduct in situ tracking of the grain refinement mechanism operating during the dynamic deformation of metals. Copper with an initial average grain size of 36 μm is refined to 6.3 μm when loaded at a constant high strain rate of 1200 s -1. The synchrotron measurements revealed the temporal evolution of the grain refinement mechanism in terms of the initiation and rate of refinement throughout the loading test. A multiscale coupled probabilistic cellular automata based recrystallization model has been developed to predict the microstructural evolution occurring during dynamic deformationmore » processes. The model accurately predicts the initiation of the grain refinement mechanism with a predicted final average grain size of 2.4 μm. As a result, the model also accurately predicts the temporal evolution in terms of the initiation and extent of refinement when compared with the experimental results.« less

Modelling evolution of asteroid's rotation due to the YORP effect

NASA Astrophysics Data System (ADS)

Golubov, Oleksiy; Lipatova, Veronika; Scheeres, Daniel J.

2016-05-01

The Yarkovsky--O'Keefe--Radzievskii--Paddack (or YORP) effect is influence of light pressure on rotation of asteroids. It is the most important factor for evolution of rotation state of small asteroids, which can drastically alter their rotation rate and obliquity over cosmologic timescales.In the poster we present our program, which calculates evolution of ratation state of small asteroids subject to the YORP effect. The program accounts for both axial and obliquity components of YORP, takes into account the thermal inertia of the asteroid's soil, and the tangential YORP. The axial component of YORP is computed using the model by Steinberg and Sari (AJ, 141, 55). The thermal inertia is accounted for in the framework of Golubov et al. 2016 (MNRAS, stw540). Computation of the tangential YORP is based on a siple analytical model, whose applicability is verified via comparison to exact numeric simulations.We apply the program to different shape models of asteroids, and study coupled evolution of their rotation rate and obliquity.

Investigation on temporal evolution of the grain refinement in copper under high strain rate loading via in-situ synchrotron measurement and predictive modeling

DOE PAGES

Shah, Pooja Nitin; Shin, Yung C.; Sun, Tao

2017-10-03

Synchrotron X-rays are integrated with a modified Kolsky tension bar to conduct in situ tracking of the grain refinement mechanism operating during the dynamic deformation of metals. Copper with an initial average grain size of 36 μm is refined to 6.3 μm when loaded at a constant high strain rate of 1200 s -1. The synchrotron measurements revealed the temporal evolution of the grain refinement mechanism in terms of the initiation and rate of refinement throughout the loading test. A multiscale coupled probabilistic cellular automata based recrystallization model has been developed to predict the microstructural evolution occurring during dynamic deformationmore » processes. The model accurately predicts the initiation of the grain refinement mechanism with a predicted final average grain size of 2.4 μm. As a result, the model also accurately predicts the temporal evolution in terms of the initiation and extent of refinement when compared with the experimental results.« less

Simulation of Heterogeneous Atom Probe Tip Shapes Evolution during Field Evaporation Using a Level Set Method and Different Evaporation Models

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

Xu, Zhijie; Li, Dongsheng; Xu, Wei

2015-04-01

In atom probe tomography (APT), accurate reconstruction of the spatial positions of field evaporated ions from measured detector patterns depends upon a correct understanding of the dynamic tip shape evolution and evaporation laws of component atoms. Artifacts in APT reconstructions of heterogeneous materials can be attributed to the assumption of homogeneous evaporation of all the elements in the material in addition to the assumption of a steady state hemispherical dynamic tip shape evolution. A level set method based specimen shape evolution model is developed in this study to simulate the evaporation of synthetic layered-structured APT tips. The simulation results ofmore » the shape evolution by the level set model qualitatively agree with the finite element method and the literature data using the finite difference method. The asymmetric evolving shape predicted by the level set model demonstrates the complex evaporation behavior of heterogeneous tip and the interface curvature can potentially lead to the artifacts in the APT reconstruction of such materials. Compared with other APT simulation methods, the new method provides smoother interface representation with the aid of the intrinsic sub-grid accuracy. Two evaporation models (linear and exponential evaporation laws) are implemented in the level set simulations and the effect of evaporation laws on the tip shape evolution is also presented.« less

Computation of bone remodelling after Duracon knee arthroplasty using a thermodynamic-based model.

PubMed

Bougherara, H; Nazgooei, S; Sayyidmousavi, A; Marsik, F; Marík, I A

2011-07-01

The present study utilizes a recently developed literature model for the bone remodelling process to predict the evolution of bone density following Duracon total knee arthroplasty (TKA). In this model, which is based on chemical kinetics and irreversible thermodynamics, bone is treated as a self-organizing system capable of exchanging matter, energy, and entropy with its surroundings. Unlike previous models in which mechanical loading is regarded as the only stimulus for bone remodelling, the present model establishes a unique coupling between mechanical loading and the chemical reactions involved in the process of bone remodelling. This model was incorporated into the finite element software ANSYS by means of a macro to compute density distribution in distal femoral bone both before and after TKA. Consistent with dual-energy X-ray absorptiometry (DEXA) scans reported in the literature, the results showed that the most severe bone loss occurs in the anterior region of the distal femur and that there is more bone resorption in the lateral than the medial condyle following TKA. Furthermore, the bone density distribution predicted using the present model showed a gradual and uniform pattern and thus a more realistic bone evolution contrary to the strain energy density model, where there is no gradual bone density evolution.

Evolving Ideas on the Origin and Evolution of Flowers: New Perspectives in the Genomic Era

PubMed Central

Chanderbali, Andre S.; Berger, Brent A.; Howarth, Dianella G.; Soltis, Pamela S.; Soltis, Douglas E.

2016-01-01

The origin of the flower was a key innovation in the history of complex organisms, dramatically altering Earth’s biota. Advances in phylogenetics, developmental genetics, and genomics during the past 25 years have substantially advanced our understanding of the evolution of flowers, yet crucial aspects of floral evolution remain, such as the series of genetic and morphological changes that gave rise to the first flowers; the factors enabling the origin of the pentamerous eudicot flower, which characterizes ∼70% of all extant angiosperm species; and the role of gene and genome duplications in facilitating floral innovations. A key early concept was the ABC model of floral organ specification, developed by Elliott Meyerowitz and Enrico Coen and based on two model systems, Arabidopsis thaliana and Antirrhinum majus. Yet it is now clear that these model systems are highly derived species, whose molecular genetic-developmental organization must be very different from that of ancestral, as well as early, angiosperms. In this article, we will discuss how new research approaches are illuminating the early events in floral evolution and the prospects for further progress. In particular, advancing the next generation of research in floral evolution will require the development of one or more functional model systems from among the basal angiosperms and basal eudicots. More broadly, we urge the development of “model clades” for genomic and evolutionary-developmental analyses, instead of the primary use of single “model organisms.” We predict that new evolutionary models will soon emerge as genetic/genomic models, providing unprecedented new insights into floral evolution. PMID:27053123

State-transition diagrams for biologists.

PubMed

Bersini, Hugues; Klatzmann, David; Six, Adrien; Thomas-Vaslin, Véronique

2012-01-01

It is clearly in the tradition of biologists to conceptualize the dynamical evolution of biological systems in terms of state-transitions of biological objects. This paper is mainly concerned with (but obviously not limited too) the immunological branch of biology and shows how the adoption of UML (Unified Modeling Language) state-transition diagrams can ease the modeling, the understanding, the coding, the manipulation or the documentation of population-based immune software model generally defined as a set of ordinary differential equations (ODE), describing the evolution in time of populations of various biological objects. Moreover, that same UML adoption naturally entails a far from negligible representational economy since one graphical item of the diagram might have to be repeated in various places of the mathematical model. First, the main graphical elements of the UML state-transition diagram and how they can be mapped onto a corresponding ODE mathematical model are presented. Then, two already published immune models of thymocyte behavior and time evolution in the thymus, the first one originally conceived as an ODE population-based model whereas the second one as an agent-based one, are refactored and expressed in a state-transition form so as to make them much easier to understand and their respective code easier to access, to modify and run. As an illustrative proof, for any immunologist, it should be possible to understand faithfully enough what the two software models are supposed to reproduce and how they execute with no need to plunge into the Java or Fortran lines.

State-Transition Diagrams for Biologists

PubMed Central

Bersini, Hugues; Klatzmann, David; Six, Adrien; Thomas-Vaslin, Véronique

2012-01-01

It is clearly in the tradition of biologists to conceptualize the dynamical evolution of biological systems in terms of state-transitions of biological objects. This paper is mainly concerned with (but obviously not limited too) the immunological branch of biology and shows how the adoption of UML (Unified Modeling Language) state-transition diagrams can ease the modeling, the understanding, the coding, the manipulation or the documentation of population-based immune software model generally defined as a set of ordinary differential equations (ODE), describing the evolution in time of populations of various biological objects. Moreover, that same UML adoption naturally entails a far from negligible representational economy since one graphical item of the diagram might have to be repeated in various places of the mathematical model. First, the main graphical elements of the UML state-transition diagram and how they can be mapped onto a corresponding ODE mathematical model are presented. Then, two already published immune models of thymocyte behavior and time evolution in the thymus, the first one originally conceived as an ODE population-based model whereas the second one as an agent-based one, are refactored and expressed in a state-transition form so as to make them much easier to understand and their respective code easier to access, to modify and run. As an illustrative proof, for any immunologist, it should be possible to understand faithfully enough what the two software models are supposed to reproduce and how they execute with no need to plunge into the Java or Fortran lines. PMID:22844438

Optimized temporal pattern of brain stimulation designed by computational evolution

PubMed Central

Brocker, David T.; Swan, Brandon D.; So, Rosa Q.; Turner, Dennis A.; Gross, Robert E.; Grill, Warren M.

2017-01-01

Brain stimulation is a promising therapy for several neurological disorders, including Parkinson’s disease. Stimulation parameters are selected empirically and are limited to the frequency and intensity of stimulation. We used the temporal pattern of stimulation as a novel parameter of deep brain stimulation to ameliorate symptoms in a parkinsonian animal model and in humans with Parkinson’s disease. We used model-based computational evolution to optimize the stimulation pattern. The optimized pattern produced symptom relief comparable to that from standard high-frequency stimulation (a constant rate of 130 or 185 Hz) and outperformed frequency-matched standard stimulation in the parkinsonian rat and in patients. Both optimized and standard stimulation suppressed abnormal oscillatory activity in the basal ganglia of rats and humans. The results illustrate the utility of model-based computational evolution to design temporal pattern of stimulation to increase the efficiency of brain stimulation in Parkinson’s disease, thereby requiring substantially less energy than traditional brain stimulation. PMID:28053151

Asymmetric Evolutionary Games

PubMed Central

McAvoy, Alex; Hauert, Christoph

2015-01-01

Evolutionary game theory is a powerful framework for studying evolution in populations of interacting individuals. A common assumption in evolutionary game theory is that interactions are symmetric, which means that the players are distinguished by only their strategies. In nature, however, the microscopic interactions between players are nearly always asymmetric due to environmental effects, differing baseline characteristics, and other possible sources of heterogeneity. To model these phenomena, we introduce into evolutionary game theory two broad classes of asymmetric interactions: ecological and genotypic. Ecological asymmetry results from variation in the environments of the players, while genotypic asymmetry is a consequence of the players having differing baseline genotypes. We develop a theory of these forms of asymmetry for games in structured populations and use the classical social dilemmas, the Prisoner’s Dilemma and the Snowdrift Game, for illustrations. Interestingly, asymmetric games reveal essential differences between models of genetic evolution based on reproduction and models of cultural evolution based on imitation that are not apparent in symmetric games. PMID:26308326

Complex temporal topic evolution modelling using the Kullback-Leibler divergence and the Bhattacharyya distance.

PubMed

Andrei, Victor; Arandjelović, Ognjen

2016-12-01

The rapidly expanding corpus of medical research literature presents major challenges in the understanding of previous work, the extraction of maximum information from collected data, and the identification of promising research directions. We present a case for the use of advanced machine learning techniques as an aide in this task and introduce a novel methodology that is shown to be capable of extracting meaningful information from large longitudinal corpora and of tracking complex temporal changes within it. Our framework is based on (i) the discretization of time into epochs, (ii) epoch-wise topic discovery using a hierarchical Dirichlet process-based model, and (iii) a temporal similarity graph which allows for the modelling of complex topic changes. More specifically, this is the first work that discusses and distinguishes between two groups of particularly challenging topic evolution phenomena: topic splitting and speciation and topic convergence and merging, in addition to the more widely recognized emergence and disappearance and gradual evolution. The proposed framework is evaluated on a public medical literature corpus.

Biogeographic patterns in ocean microbes emerge in a neutral agent-based model.

PubMed

Hellweger, Ferdi L; van Sebille, Erik; Fredrick, Neil D

2014-09-12

A key question in ecology and evolution is the relative role of natural selection and neutral evolution in producing biogeographic patterns. We quantify the role of neutral processes by simulating division, mutation, and death of 100,000 individual marine bacteria cells with full 1 million-base-pair genomes in a global surface ocean circulation model. The model is run for up to 100,000 years and output is analyzed using BLAST (Basic Local Alignment Search Tool) alignment and metagenomics fragment recruitment. Simulations show the production and maintenance of biogeographic patterns, characterized by distinct provinces subject to mixing and periodic takeovers by neighbors (coalescence), after which neutral evolution reestablishes the province and the patterns reorganize. The emergent patterns are substantial (e.g., down to 99.5% DNA identity between North and Central Pacific provinces) and suggest that microbes evolve faster than ocean currents can disperse them. This approach can also be used to explore environmental selection. Copyright © 2014, American Association for the Advancement of Science.

Mapping the spatial distribution and time evolution of snow water equivalent with passive microwave measurements

USGS Publications Warehouse

Guo, J.; Tsang, L.; Josberger, E.G.; Wood, A.W.; Hwang, J.-N.; Lettenmaier, D.P.

2003-01-01

This paper presents an algorithm that estimates the spatial distribution and temporal evolution of snow water equivalent and snow depth based on passive remote sensing measurements. It combines the inversion of passive microwave remote sensing measurements via dense media radiative transfer modeling results with snow accumulation and melt model predictions to yield improved estimates of snow depth and snow water equivalent, at a pixel resolution of 5 arc-min. In the inversion, snow grain size evolution is constrained based on pattern matching by using the local snow temperature history. This algorithm is applied to produce spatial snow maps of Upper Rio Grande River basin in Colorado. The simulation results are compared with that of the snow accumulation and melt model and a linear regression method. The quantitative comparison with the ground truth measurements from four Snowpack Telemetry (SNOTEL) sites in the basin shows that this algorithm is able to improve the estimation of snow parameters.

Biophysics of protein evolution and evolutionary protein biophysics

PubMed Central

Sikosek, Tobias; Chan, Hue Sun

2014-01-01

The study of molecular evolution at the level of protein-coding genes often entails comparing large datasets of sequences to infer their evolutionary relationships. Despite the importance of a protein's structure and conformational dynamics to its function and thus its fitness, common phylogenetic methods embody minimal biophysical knowledge of proteins. To underscore the biophysical constraints on natural selection, we survey effects of protein mutations, highlighting the physical basis for marginal stability of natural globular proteins and how requirement for kinetic stability and avoidance of misfolding and misinteractions might have affected protein evolution. The biophysical underpinnings of these effects have been addressed by models with an explicit coarse-grained spatial representation of the polypeptide chain. Sequence–structure mappings based on such models are powerful conceptual tools that rationalize mutational robustness, evolvability, epistasis, promiscuous function performed by ‘hidden’ conformational states, resolution of adaptive conflicts and conformational switches in the evolution from one protein fold to another. Recently, protein biophysics has been applied to derive more accurate evolutionary accounts of sequence data. Methods have also been developed to exploit sequence-based evolutionary information to predict biophysical behaviours of proteins. The success of these approaches demonstrates a deep synergy between the fields of protein biophysics and protein evolution. PMID:25165599

Recent Evolution of the Introductory Curriculum in Computing.

ERIC Educational Resources Information Center

Tucker, Allen B.; Garnick, David K.

1991-01-01

Traces the evolution of introductory computing courses for undergraduates based on the Association for Computing Machinery (ACM) guidelines published in "Curriculum 78." Changes in the curricula are described, including the role of discrete mathematics and theory; and the need for a broader model for designing introductory courses is…

Organic chemical evolution

NASA Technical Reports Server (NTRS)

Chang, S.

1981-01-01

The course of organic chemical evolution preceding the emergence of life on earth is discussed based on evidence of processes occurring in interstellar space, the solar system and the primitive earth. Following a brief review of the equilibrium condensation model for the origin and evolution of the solar system, consideration is given to the nature and organic chemistry of interstellar clouds, comets, Jupiter, meteorites, Venus and Mars, and the prebiotic earth. Major issues to be resolved in the study of organic chemical evolution on earth are identified regarding condensation and accretion in the solar nebula, early geological evolution, the origin and evolution of the atmosphere, organic production rates, organic-inorganic interactions, environmental fluctuations, phase separation and molecular selectivity.

Modeling "Tiktaalik": Using a Model-Based Inquiry Approach to Engage Community College Students in the Practices of Science during an Evolution Unit

ERIC Educational Resources Information Center

Baze, Christina L.; Gray, Ron

2018-01-01

Inquiry methods have been successful in improving science literacy in students of all ages. Model-Based Inquiry (MBI) is an instructional model that engages students in the practices of science through the collaborative development of scientific models to explain an anchoring phenomenon. Student ideas are tested through engagement in content-rich…

Catching the radio flare in CTA 102. I. Light curve analysis

NASA Astrophysics Data System (ADS)

Fromm, C. M.; Perucho, M.; Ros, E.; Savolainen, T.; Lobanov, A. P.; Zensus, J. A.; Aller, M. F.; Aller, H. D.; Gurwell, M. A.; Lähteenmäki, A.

2011-07-01

Context. The blazar CTA 102 (z = 1.037) underwent a historical radio outburst in April 2006. This event offered a unique chance to study the physical properties of the jet. Aims: We used multifrequency radio and mm observations to analyze the evolution of the spectral parameters during the flare as a test of the shock-in-jet model under these extreme conditions. Methods: For the analysis of the flare we took into account that the flaring spectrum is superimposed on a quiescent spectrum. We reconstructed the latter from archival data and fitted a synchrotron self-absorbed distribution of emission. The uncertainties of the derived spectral parameters were calculated using Monte Carlo simulations. The spectral evolution is modeled by the shock-in-jet model, and the derived results are discussed in the context of a geometrical model (varying viewing angle) and shock-shock interaction Results: The evolution of the flare in the turnover frequency-turnover flux density (νm - Sm) plane shows a double peak structure. The nature of this evolution is dicussed in the frame of shock-in-jet models. We discard the generation of the double peak structure in the νm - Sm plane purely based on geometrical changes (variation of the Doppler factor). The detailed modeling of the spectral evolution favors a shock-shock interaction as a possible physical mechanism behind the deviations from the standard shock-in-jet model.

Interpreting intraplate tectonics for seismic hazard: a UK historical perspective

NASA Astrophysics Data System (ADS)

Musson, R. M. W.

2012-04-01

It is notoriously difficult to construct seismic source models for probabilistic seismic hazard assessment in intraplate areas on the basis of geological information, and many practitioners have given up the task in favour of purely seismicity-based models. This risks losing potentially valuable information in regions where the earthquake catalogue is short compared to the seismic cycle. It is interesting to survey how attitudes to this issue have evolved over the past 30 years. This paper takes the UK as an example, and traces the evolution of seismic source models through generations of hazard studies. It is found that in the UK, while the earliest studies did not consider regional tectonics in any way, there has been a gradual evolution towards more tectonically based models. Experience in other countries, of course, may differ.

An Interdisciplinary Model for Teaching Evolutionary Ecology.

ERIC Educational Resources Information Center

Coletta, John

1992-01-01

Describes a general systems evolutionary model and demonstrates how a previously established ecological model is a function of its past development based on the evolution of the rock, nutrient, and water cycles. Discusses the applications of the model in environmental education. (MDH)

Spectral evolution of weakly nonlinear random waves: kinetic description vs direct numerical simulations

NASA Astrophysics Data System (ADS)

Annenkov, Sergei; Shrira, Victor

2016-04-01

We study numerically the long-term evolution of water wave spectra without wind forcing, using three different models, aiming at understanding the role of different sets of assumptions. The first model is the classical Hasselmann kinetic equation (KE). We employ the WRT code kindly provided by G. van Vledder. Two other models are new. As the second model, we use the generalised kinetic equation (gKE), derived without the assumption of quasi-stationarity. Thus, unlike the KE, the gKE is valid in the cases when a wave spectrum is changing rapidly (e.g. at the initial stage of evolution of a narrow spectrum). However, the gKE employs the same statistical closure as the KE. The third model is based on the Zakharov integrodifferential equation for water waves and does not depend on any statistical assumptions. Since the Zakharov equation plays the role of the primitive equation of the theory of wave turbulence, we refer to this model as direct numerical simulation of spectral evolution (DNS-ZE). For initial conditions, we choose two narrow-banded spectra with the same frequency distribution (a JONSWAP spectrum with high peakedness γ = 6) and different degrees of directionality. These spectra are from the set of observations collected in a directional wave tank by Onorato et al (2009). Spectrum A is very narrow in angle (corresponding to N = 840 in the cosN directional model). Spectrum B is initially wider in angle (corresponds to N = 24). Short-term evolution of both spectra (O(102) wave periods) has been studied numerically by Xiao et al (2013) using two other approaches (broad-band modified nonlinear Schrödinger equation and direct numerical simulation based on the high-order spectral method). We use these results to verify the initial stage of our DNS-ZE simulations. However, the advantage of the DNS-ZE method is that it allows to study long-term spectral evolution (up to O(104) periods), which was previously possible only with the KE. In the short-term evolution, we find a good agreement between our DNS-ZE results and simulations by Xiao et al (2013), both for the evolution of frequency spectra and for the directional spreading. In the long term, all three approaches demonstrate very close evolution of integral characteristics of spectra, approaching for large time the theoretical asymptotes of the self-similar stage of evolution. However, the detailed comparison of the spectral evolution shows certain notable differences. Both kinetic equations give virtually identical evolution of spectrum B, but in the case of initially nearly one-dimensional spectrum A the KE overestimates the amplitude of the spectral peak. Meanwhile, the DNS-ZE results show considerably wider spectra with less pronounced peak. There is a striking difference for the rate of spectral broadening, which is much larger for the gKE and especially for the KE, than for the DNS-ZE. We show that the rates of change of the spectra obtained with the DNS-ZE are proportional to the fourth power of nonlinearity, corresponding to the dynamical timescale of evolution, rather than the statistical timescale of both kinetic equations.

Investigation of shear damage considering the evolution of anisotropy

NASA Astrophysics Data System (ADS)

Kweon, S.

2013-12-01

The damage that occurs in shear deformations in view of anisotropy evolution is investigated. It is widely believed in the mechanics research community that damage (or porosity) does not evolve (increase) in shear deformations since the hydrostatic stress in shear is zero. This paper proves that the above statement can be false in large deformations of simple shear. The simulation using the proposed anisotropic ductile fracture model (macro-scale) in this study indicates that hydrostatic stress becomes nonzero and (thus) porosity evolves (increases or decreases) in the simple shear deformation of anisotropic (orthotropic) materials. The simple shear simulation using a crystal plasticity based damage model (meso-scale) shows the same physics as manifested in the above macro-scale model that porosity evolves due to the grain-to-grain interaction, i.e., due to the evolution of anisotropy. Through a series of simple shear simulations, this study investigates the effect of the evolution of anisotropy, i.e., the rotation of the orthotropic axes onto the damage (porosity) evolution. The effect of the evolutions of void orientation and void shape onto the damage (porosity) evolution is investigated as well. It is found out that the interaction among porosity, the matrix anisotropy and void orientation/shape plays a crucial role in the ductile damage of porous materials.

CF Metadata Conventions: Founding Principles, Governance, and Future Directions

NASA Astrophysics Data System (ADS)

Taylor, K. E.

2016-12-01

The CF Metadata Conventions define attributes that promote sharing of climate and forecasting data and facilitate automated processing by computers. The development, maintenance, and evolution of the conventions have mainly been provided by voluntary community contributions. Nevertheless, an organizational framework has been established, which relies on established rules and web-based discussion to ensure smooth (but relatively efficient) evolution of the standard to accommodate new types of data. The CF standard has been essential to the success of high-profile internationally-coordinated modeling activities (e.g, the Coupled Model Intercomparison Project). A summary of CF's founding principles and the prospects for its future evolution will be discussed.

Speciation and Neutral Molecular Evolution in One-Dimensional Closed Population

NASA Astrophysics Data System (ADS)

Semovski, Sergei V.; Bukin, Yuri S.; Sherbakov, Dmitry Yu.

Models are presented suitable for a description of speciation processes arising due to reproductive isolation depending on genetic distance. The main attention is paid to the model of a one-dimensional closed population, which describes the evolution of littoral benthic organisms. In order to correspond the modeling results to the results obtained in the course of experimental phylogenetic studies, all individual-based models described here involve neutrally evolving and maternally inherited DNA sequence. Sub-samples of the resulting sequences were used for a posteriori phylogenetic inferences which then were compared to the "true" evolutionary histories.

Investigating the Consistency of Stellar Evolution Models with Globular Cluster Observations via the Red Giant Branch Bump

NASA Astrophysics Data System (ADS)

Joyce, Meridith; Chaboyer, Brian

2016-01-01

Synthetic Red Giant Branch Bump (RGBB) magnitudes are generated with the most recent theoretical stellar evolution models computed with the Dartmouth Stellar Evolution Program (DSEP) code. They are compared to the observational work of Nataf et al. (2013), who present RGBB magnitudes for 72 globular clusters. A DSEP model using a chemical composition with enhanced α capture [α/Fe] =+0.4 and an age of 13 Gyr shows agreement with observations over metallicities ranging from [Fe/H] = 0 to [Fe/H] ≈-1.5, with discrepancy emerging at lower metallicities. A model-independent, density-based outlier detection routine known as the Local Outlying Factor (LOF) algorithm is applied to the observations in order to identify clusters that deviate most in magnitude-metallicity space from the bulk of the observations. Our model's fit is scrutinized with a series of χ^2 routines performed on subsets of the data from which highly anomalous clusters have been selectively removed based on LOF identification. In particular, NGCs 6254, 6681, 6218, and 1904 are tagged recurrently as outliers. The effects of systematic and non-systematic error in metallicity are assessed, and the robustness of observational error bars is investigated.

Physics-based Control-oriented Modeling of the Current Profile Evolution in NSTX-Upgrade

NASA Astrophysics Data System (ADS)

Ilhan, Zeki; Barton, Justin; Shi, Wenyu; Schuster, Eugenio; Gates, David; Gerhardt, Stefan; Kolemen, Egemen; Menard, Jonathan

2013-10-01

The operational goals for the NSTX-Upgrade device include non-inductive sustainment of high- β plasmas, realization of the high performance equilibrium scenarios with neutral beam heating, and achievement of longer pulse durations. Active feedback control of the current profile is proposed to enable these goals. Motivated by the coupled, nonlinear, multivariable, distributed-parameter plasma dynamics, the first step towards feedback control design is the development of a physics-based, control-oriented model for the current profile evolution in response to non-inductive current drives and heating systems. For this purpose, the nonlinear magnetic-diffusion equation is coupled with empirical models for the electron density, electron temperature, and non-inductive current drives (neutral beams). The resulting first-principles-driven, control-oriented model is tailored for NSTX-U based on the PTRANSP predictions. Main objectives and possible challenges associated with the use of the developed model for control design are discussed. This work was supported by PPPL.

Chaotic universe model.

PubMed

Aydiner, Ekrem

2018-01-15

In this study, we consider nonlinear interactions between components such as dark energy, dark matter, matter and radiation in the framework of the Friedman-Robertson-Walker space-time and propose a simple interaction model based on the time evolution of the densities of these components. By using this model we show that these interactions can be given by Lotka-Volterra type equations. We numerically solve these coupling equations and show that interaction dynamics between dark energy-dark matter-matter or dark energy-dark matter-matter-radiation has a strange attractor for 0 > w de  >-1, w dm  ≥ 0, w m  ≥ 0 and w r  ≥ 0 values. These strange attractors with the positive Lyapunov exponent clearly show that chaotic dynamics appears in the time evolution of the densities. These results provide that the time evolution of the universe is chaotic. The present model may have potential to solve some of the cosmological problems such as the singularity, cosmic coincidence, big crunch, big rip, horizon, oscillation, the emergence of the galaxies, matter distribution and large-scale organization of the universe. The model also connects between dynamics of the competing species in biological systems and dynamics of the time evolution of the universe and offers a new perspective and a new different scenario for the universe evolution.

Knowledge representation to support reasoning based on multiple models

NASA Technical Reports Server (NTRS)

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

1990-01-01

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

Numerical Implementation of a Multiple-ISV Thermodynamically-Based Work Potential Theory for Modeling Progressive Damage and Failure in Fiber-Reinforced Laminates

NASA Technical Reports Server (NTRS)

Pineda, Evan J.; Waas, Anthony M.

2011-01-01

A thermodynamically-based work potential theory for modeling progressive damage and failure in fiber-reinforced laminates is presented. The current, multiple-internal state variable (ISV) formulation, enhanced Schapery theory (EST), utilizes separate ISVs for modeling the effects of damage and failure. Damage is considered to be the effect of any structural changes in a material that manifest as pre-peak non-linearity in the stress versus strain response. Conversely, failure is taken to be the effect of the evolution of any mechanisms that results in post-peak strain softening. It is assumed that matrix microdamage is the dominant damage mechanism in continuous fiber-reinforced polymer matrix laminates, and its evolution is controlled with a single ISV. Three additional ISVs are introduced to account for failure due to mode I transverse cracking, mode II transverse cracking, and mode I axial failure. Typically, failure evolution (i.e., post-peak strain softening) results in pathologically mesh dependent solutions within a finite element method (FEM) setting. Therefore, consistent character element lengths are introduced into the formulation of the evolution of the three failure ISVs. Using the stationarity of the total work potential with respect to each ISV, a set of thermodynamically consistent evolution equations for the ISVs is derived. The theory is implemented into commercial FEM software. Objectivity of total energy dissipated during the failure process, with regards to refinements in the FEM mesh, is demonstrated. The model is also verified against experimental results from two laminated, T800/3900-2 panels containing a central notch and different fiber-orientation stacking sequences. Global load versus displacement, global load versus local strain gage data, and macroscopic failure paths obtained from the models are compared to the experiments.

A software development and evolution model based on decision-making

NASA Technical Reports Server (NTRS)

Wild, J. Christian; Dong, Jinghuan; Maly, Kurt

1991-01-01

Design is a complex activity whose purpose is to construct an artifact which satisfies a set of constraints and requirements. However the design process is not well understood. The software design and evolution process is the focus of interest, and a three dimensional software development space organized around a decision-making paradigm is presented. An initial instantiation of this model called 3DPM(sub p) which was partly implemented, is presented. Discussion of the use of this model in software reuse and process management is given.

On spatial mutation-selection models

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

Kondratiev, Yuri, E-mail: kondrat@math.uni-bielefeld.de; Kutoviy, Oleksandr, E-mail: kutoviy@math.uni-bielefeld.de, E-mail: kutovyi@mit.edu; Department of Mathematics, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, Massachusetts 02139

2013-11-15

We discuss the selection procedure in the framework of mutation models. We study the regulation for stochastically developing systems based on a transformation of the initial Markov process which includes a cost functional. The transformation of initial Markov process by cost functional has an analytic realization in terms of a Kimura-Maruyama type equation for the time evolution of states or in terms of the corresponding Feynman-Kac formula on the path space. The state evolution of the system including the limiting behavior is studied for two types of mutation-selection models.

TRIADS: A phase-resolving model for nonlinear shoaling of directional wave spectra

NASA Astrophysics Data System (ADS)

Sheremet, Alex; Davis, Justin R.; Tian, Miao; Hanson, Jeffrey L.; Hathaway, Kent K.

2016-03-01

We investigate the performance of TRIADS, a numerical implementation of a phase-resolving, nonlinear, spectral model describing directional wave evolution in intermediate and shallow water. TRIADS simulations of shoaling waves generated by Hurricane Bill, 2009 are compared to directional spectral estimates based on observations collected at the Field Research Facility of the US Army Corps Of Engineers, at Duck, NC. Both the ability of the model to capture the processes essential to the nonlinear wave evolution, and the efficiency of the numerical implementations are analyzed and discussed.

Determining Selection across Heterogeneous Landscapes: A Perturbation-Based Method and Its Application to Modeling Evolution in Space.

PubMed

Wickman, Jonas; Diehl, Sebastian; Blasius, Bernd; Klausmeier, Christopher A; Ryabov, Alexey B; Brännström, Åke

2017-04-01

Spatial structure can decisively influence the way evolutionary processes unfold. To date, several methods have been used to study evolution in spatial systems, including population genetics, quantitative genetics, moment-closure approximations, and individual-based models. Here we extend the study of spatial evolutionary dynamics to eco-evolutionary models based on reaction-diffusion equations and adaptive dynamics. Specifically, we derive expressions for the strength of directional and stabilizing/disruptive selection that apply both in continuous space and to metacommunities with symmetrical dispersal between patches. For directional selection on a quantitative trait, this yields a way to integrate local directional selection across space and determine whether the trait value will increase or decrease. The robustness of this prediction is validated against quantitative genetics. For stabilizing/disruptive selection, we show that spatial heterogeneity always contributes to disruptive selection and hence always promotes evolutionary branching. The expression for directional selection is numerically very efficient and hence lends itself to simulation studies of evolutionary community assembly. We illustrate the application and utility of the expressions for this purpose with two examples of the evolution of resource utilization. Finally, we outline the domain of applicability of reaction-diffusion equations as a modeling framework and discuss their limitations.

Computational model, method, and system for kinetically-tailoring multi-drug chemotherapy for individuals

DOEpatents

Gardner, Shea Nicole

2007-10-23

A method and system for tailoring treatment regimens to individual patients with diseased cells exhibiting evolution of resistance to such treatments. A mathematical model is provided which models rates of population change of proliferating and quiescent diseased cells using cell kinetics and evolution of resistance of the diseased cells, and pharmacokinetic and pharmacodynamic models. Cell kinetic parameters are obtained from an individual patient and applied to the mathematical model to solve for a plurality of treatment regimens, each having a quantitative efficacy value associated therewith. A treatment regimen may then be selected from the plurlaity of treatment options based on the efficacy value.

Calibration of a stochastic health evolution model using NHIS data

NASA Astrophysics Data System (ADS)

Gupta, Aparna; Li, Zhisheng

2011-10-01

This paper presents and calibrates an individual's stochastic health evolution model. In this health evolution model, the uncertainty of health incidents is described by a stochastic process with a finite number of possible outcomes. We construct a comprehensive health status index (HSI) to describe an individual's health status, as well as a health risk factor system (RFS) to classify individuals into different risk groups. Based on the maximum likelihood estimation (MLE) method and the method of nonlinear least squares fitting, model calibration is formulated in terms of two mixed-integer nonlinear optimization problems. Using the National Health Interview Survey (NHIS) data, the model is calibrated for specific risk groups. Longitudinal data from the Health and Retirement Study (HRS) is used to validate the calibrated model, which displays good validation properties. The end goal of this paper is to provide a model and methodology, whose output can serve as a crucial component of decision support for strategic planning of health related financing and risk management.

Medial-based deformable models in nonconvex shape-spaces for medical image segmentation.

PubMed

McIntosh, Chris; Hamarneh, Ghassan

2012-01-01

We explore the application of genetic algorithms (GA) to deformable models through the proposition of a novel method for medical image segmentation that combines GA with nonconvex, localized, medial-based shape statistics. We replace the more typical gradient descent optimizer used in deformable models with GA, and the convex, implicit, global shape statistics with nonconvex, explicit, localized ones. Specifically, we propose GA to reduce typical deformable model weaknesses pertaining to model initialization, pose estimation and local minima, through the simultaneous evolution of a large number of models. Furthermore, we constrain the evolution, and thus reduce the size of the search-space, by using statistically-based deformable models whose deformations are intuitive (stretch, bulge, bend) and are driven in terms of localized principal modes of variation, instead of modes of variation across the entire shape that often fail to capture localized shape changes. Although GA are not guaranteed to achieve the global optima, our method compares favorably to the prevalent optimization techniques, convex/nonconvex gradient-based optimizers and to globally optimal graph-theoretic combinatorial optimization techniques, when applied to the task of corpus callosum segmentation in 50 mid-sagittal brain magnetic resonance images.

A Nanoflare-Based Cellular Automaton Model and the Observed Properties of the Coronal Plasma

NASA Technical Reports Server (NTRS)

Lopez-Fuentes, Marcelo; Klimchuk, James Andrew

2016-01-01

We use the cellular automaton model described in Lopez Fuentes and Klimchuk to study the evolution of coronal loop plasmas. The model, based on the idea of a critical misalignment angle in tangled magnetic fields, produces nanoflares of varying frequency with respect to the plasma cooling time. We compare the results of the model with active region (AR) observations obtained with the Hinode/XRT and SDOAIA instruments. The comparison is based on the statistical properties of synthetic and observed loop light curves. Our results show that the model reproduces the main observational characteristics of the evolution of the plasma in AR coronal loops. The typical intensity fluctuations have amplitudes of 10 percent - 15 percent both for the model and the observations. The sign of the skewness of the intensity distributions indicates the presence of cooling plasma in the loops. We also study the emission measure (EM) distribution predicted by the model and obtain slopes in log(EM) versus log(T) between 2.7 and 4.3, in agreement with published observational values.

A NANOFLARE-BASED CELLULAR AUTOMATON MODEL AND THE OBSERVED PROPERTIES OF THE CORONAL PLASMA

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

Fuentes, Marcelo López; Klimchuk, James A., E-mail: lopezf@iafe.uba.ar

2016-09-10

We use the cellular automaton model described in López Fuentes and Klimchuk to study the evolution of coronal loop plasmas. The model, based on the idea of a critical misalignment angle in tangled magnetic fields, produces nanoflares of varying frequency with respect to the plasma cooling time. We compare the results of the model with active region (AR) observations obtained with the Hinode /XRT and SDO /AIA instruments. The comparison is based on the statistical properties of synthetic and observed loop light curves. Our results show that the model reproduces the main observational characteristics of the evolution of the plasmamore » in AR coronal loops. The typical intensity fluctuations have amplitudes of 10%–15% both for the model and the observations. The sign of the skewness of the intensity distributions indicates the presence of cooling plasma in the loops. We also study the emission measure (EM) distribution predicted by the model and obtain slopes in log(EM) versus log(T) between 2.7 and 4.3, in agreement with published observational values.« less

An Agent-Based Dynamic Model for Analysis of Distributed Space Exploration Architectures

NASA Astrophysics Data System (ADS)

Sindiy, Oleg V.; DeLaurentis, Daniel A.; Stein, William B.

2009-07-01

A range of complex challenges, but also potentially unique rewards, underlie the development of exploration architectures that use a distributed, dynamic network of resources across the solar system. From a methodological perspective, the prime challenge is to systematically model the evolution (and quantify comparative performance) of such architectures, under uncertainty, to effectively direct further study of specialized trajectories, spacecraft technologies, concept of operations, and resource allocation. A process model for System-of-Systems Engineering is used to define time-varying performance measures for comparative architecture analysis and identification of distinguishing patterns among interoperating systems. Agent-based modeling serves as the means to create a discrete-time simulation that generates dynamics for the study of architecture evolution. A Solar System Mobility Network proof-of-concept problem is introduced representing a set of longer-term, distributed exploration architectures. Options within this set revolve around deployment of human and robotic exploration and infrastructure assets, their organization, interoperability, and evolution, i.e., a system-of-systems. Agent-based simulations quantify relative payoffs for a fully distributed architecture (which can be significant over the long term), the latency period before they are manifest, and the up-front investment (which can be substantial compared to alternatives). Verification and sensitivity results provide further insight on development paths and indicate that the framework and simulation modeling approach may be useful in architectural design of other space exploration mass, energy, and information exchange settings.

A stochastic evolution model for residue Insertion-Deletion Independent from Substitution.

PubMed

Lèbre, Sophie; Michel, Christian J

2010-12-01

We develop here a new class of stochastic models of gene evolution based on residue Insertion-Deletion Independent from Substitution (IDIS). Indeed, in contrast to all existing evolution models, insertions and deletions are modeled here by a concept in population dynamics. Therefore, they are not only independent from each other, but also independent from the substitution process. After a separate stochastic analysis of the substitution and the insertion-deletion processes, we obtain a matrix differential equation combining these two processes defining the IDIS model. By deriving a general solution, we give an analytical expression of the residue occurrence probability at evolution time t as a function of a substitution rate matrix, an insertion rate vector, a deletion rate and an initial residue probability vector. Various mathematical properties of the IDIS model in relation with time t are derived: time scale, time step, time inversion and sequence length. Particular expressions of the nucleotide occurrence probability at time t are given for classical substitution rate matrices in various biological contexts: equal insertion rate, insertion-deletion only and substitution only. All these expressions can be directly used for biological evolutionary applications. The IDIS model shows a strongly different stochastic behavior from the classical substitution only model when compared on a gene dataset. Indeed, by considering three processes of residue insertion, deletion and substitution independently from each other, it allows a more realistic representation of gene evolution and opens new directions and applications in this research field. Copyright © 2010 Elsevier Ltd. All rights reserved.

Quasi-brittle damage modeling based on incremental energy relaxation combined with a viscous-type regularization

NASA Astrophysics Data System (ADS)

Langenfeld, K.; Junker, P.; Mosler, J.

2018-05-01

This paper deals with a constitutive model suitable for the analysis of quasi-brittle damage in structures. The model is based on incremental energy relaxation combined with a viscous-type regularization. A similar approach—which also represents the inspiration for the improved model presented in this paper—was recently proposed in Junker et al. (Contin Mech Thermodyn 29(1):291-310, 2017). Within this work, the model introduced in Junker et al. (2017) is critically analyzed first. This analysis leads to an improved model which shows the same features as that in Junker et al. (2017), but which (i) eliminates unnecessary model parameters, (ii) can be better interpreted from a physics point of view, (iii) can capture a fully softened state (zero stresses), and (iv) is characterized by a very simple evolution equation. In contrast to the cited work, this evolution equation is (v) integrated fully implicitly and (vi) the resulting time-discrete evolution equation can be solved analytically providing a numerically efficient closed-form solution. It is shown that the final model is indeed well-posed (i.e., its tangent is positive definite). Explicit conditions guaranteeing this well-posedness are derived. Furthermore, by additively decomposing the stress rate into deformation- and purely time-dependent terms, the functionality of the model is explained. Illustrative numerical examples confirm the theoretical findings.

Observing Clonal Dynamics across Spatiotemporal Axes: A Prelude to Quantitative Fitness Models for Cancer.

PubMed

McPherson, Andrew W; Chan, Fong Chun; Shah, Sohrab P

2018-02-01

The ability to accurately model evolutionary dynamics in cancer would allow for prediction of progression and response to therapy. As a prelude to quantitative understanding of evolutionary dynamics, researchers must gather observations of in vivo tumor evolution. High-throughput genome sequencing now provides the means to profile the mutational content of evolving tumor clones from patient biopsies. Together with the development of models of tumor evolution, reconstructing evolutionary histories of individual tumors generates hypotheses about the dynamics of evolution that produced the observed clones. In this review, we provide a brief overview of the concepts involved in predicting evolutionary histories, and provide a workflow based on bulk and targeted-genome sequencing. We then describe the application of this workflow to time series data obtained for transformed and progressed follicular lymphomas (FL), and contrast the observed evolutionary dynamics between these two subtypes. We next describe results from a spatial sampling study of high-grade serous (HGS) ovarian cancer, propose mechanisms of disease spread based on the observed clonal mixtures, and provide examples of diversification through subclonal acquisition of driver mutations and convergent evolution. Finally, we state implications of the techniques discussed in this review as a necessary but insufficient step on the path to predictive modelling of disease dynamics. Copyright © 2018 Cold Spring Harbor Laboratory Press; all rights reserved.

Application of biomarkers in cancer risk management: evaluation from stochastic clonal evolutionary and dynamic system optimization points of view.

PubMed

Li, Xiaohong; Blount, Patricia L; Vaughan, Thomas L; Reid, Brian J

2011-02-01

Aside from primary prevention, early detection remains the most effective way to decrease mortality associated with the majority of solid cancers. Previous cancer screening models are largely based on classification of at-risk populations into three conceptually defined groups (normal, cancer without symptoms, and cancer with symptoms). Unfortunately, this approach has achieved limited successes in reducing cancer mortality. With advances in molecular biology and genomic technologies, many candidate somatic genetic and epigenetic "biomarkers" have been identified as potential predictors of cancer risk. However, none have yet been validated as robust predictors of progression to cancer or shown to reduce cancer mortality. In this Perspective, we first define the necessary and sufficient conditions for precise prediction of future cancer development and early cancer detection within a simple physical model framework. We then evaluate cancer risk prediction and early detection from a dynamic clonal evolution point of view, examining the implications of dynamic clonal evolution of biomarkers and the application of clonal evolution for cancer risk management in clinical practice. Finally, we propose a framework to guide future collaborative research between mathematical modelers and biomarker researchers to design studies to investigate and model dynamic clonal evolution. This approach will allow optimization of available resources for cancer control and intervention timing based on molecular biomarkers in predicting cancer among various risk subsets that dynamically evolve over time.

Mathematical modeling of the malignancy of cancer using graph evolution.

PubMed

Gunduz-Demir, Cigdem

2007-10-01

We report a novel computational method based on graph evolution process to model the malignancy of brain cancer called glioma. In this work, we analyze the phases that a graph passes through during its evolution and demonstrate strong relation between the malignancy of cancer and the phase of its graph. From the photomicrographs of tissues, which are diagnosed as normal, low-grade cancerous and high-grade cancerous, we construct cell-graphs based on the locations of cells; we probabilistically generate an edge between every pair of cells depending on the Euclidean distance between them. For a cell-graph, we extract connectivity information including the properties of its connected components in order to analyze the phase of the cell-graph. Working with brain tissue samples surgically removed from 12 patients, we demonstrate that cell-graphs generated for different tissue types evolve differently and that they exhibit different phase properties, which distinguish a tissue type from another.

The Evolution of El Nino-Precipitation Relationships from Satellites and Gauges

NASA Technical Reports Server (NTRS)

Curtis, Scott; Adler, Robert F.; Starr, David OC (Technical Monitor)

2002-01-01

This study uses a twenty-three year (1979-2001) satellite-gauge merged community data set to further describe the relationship between El Nino Southern Oscillation (ENSO) and precipitation. The globally complete precipitation fields reveal coherent bands of anomalies that extend from the tropics to the polar regions. Also, ENSO-precipitation relationships were analyzed during the six strongest El Ninos from 1979 to 2001. Seasons of evolution, Pre-onset, Onset, Peak, Decay, and Post-decay, were identified based on the strength of the El Nino. Then two simple and independent models, first order harmonic and linear, were fit to the monthly time series of normalized precipitation anomalies for each grid block. The sinusoidal model represents a three-phase evolution of precipitation, either dry-wet-dry or wet-dry-wet. This model is also highly correlated with the evolution of sea surface temperatures in the equatorial Pacific. The linear model represents a two-phase evolution of precipitation, either dry-wet or wet-dry. These models combine to account for over 50% of the precipitation variability for over half the globe during El Nino. Most regions, especially away from the Equator, favor the linear model. Areas that show the largest trend from dry to wet are southeastern Australia, eastern Indian Ocean, southern Japan, and off the coast of Peru. The northern tropical Pacific and Southeast Asia show the opposite trend.

Collection Directions: The Evolution of Library Collections and Collecting

ERIC Educational Resources Information Center

Dempsey, Lorcan; Malpas, Constance; Lavoie, Brian

2014-01-01

This article takes a broad view of the evolution of collecting behaviors in a network environment and suggests some future directions based on various simple models. The authors look at the changing dynamics of print collections, at the greater engagement with research and learning behaviors, and at trends in scholarly communication. The goal is…

Information-theoretic metamodel of organizational evolution

NASA Astrophysics Data System (ADS)

Sepulveda, Alfredo

2011-12-01

Social organizations are abstractly modeled by holarchies---self-similar connected networks---and intelligent complex adaptive multiagent systems---large networks of autonomous reasoning agents interacting via scaled processes. However, little is known of how information shapes evolution in such organizations, a gap that can lead to misleading analytics. The research problem addressed in this study was the ineffective manner in which classical model-predict-control methods used in business analytics attempt to define organization evolution. The purpose of the study was to construct an effective metamodel for organization evolution based on a proposed complex adaptive structure---the info-holarchy. Theoretical foundations of this study were holarchies, complex adaptive systems, evolutionary theory, and quantum mechanics, among other recently developed physical and information theories. Research questions addressed how information evolution patterns gleamed from the study's inductive metamodel more aptly explained volatility in organization. In this study, a hybrid grounded theory based on abstract inductive extensions of information theories was utilized as the research methodology. An overarching heuristic metamodel was framed from the theoretical analysis of the properties of these extension theories and applied to business, neural, and computational entities. This metamodel resulted in the synthesis of a metaphor for, and generalization of organization evolution, serving as the recommended and appropriate analytical tool to view business dynamics for future applications. This study may manifest positive social change through a fundamental understanding of complexity in business from general information theories, resulting in more effective management.

Single-bubble sonoluminescence in sulfuric acid and water: bubble dynamics, stability, and continuous spectra.

PubMed

Puente, Gabriela F; García-Martínez, Pablo; Bonetto, Fabián J

2007-01-01

We present theoretical calculations of an argon bubble in a liquid solution of 85%wt sulfuric acid and 15%wt water in single-bubble sonoluminescence. We used a model without free parameters to be adjusted. We predict from first principles the region in parameter space for stable bubble evolution, the temporal evolution of the bubble radius, the maximum temperature, pressures, and the light spectra due to thermal emissions. We also used a partial differential equation based model (hydrocode) to compute the temperature and pressure evolutions at the center of the bubble during maximum compression. We found the behavior of this liquid mixture to be very different from water in several aspects. Most of the models in sonoluminescence were compared with water experimental results.

Calibration and analysis of genome-based models for microbial ecology.

PubMed

Louca, Stilianos; Doebeli, Michael

2015-10-16

Microbial ecosystem modeling is complicated by the large number of unknown parameters and the lack of appropriate calibration tools. Here we present a novel computational framework for modeling microbial ecosystems, which combines genome-based model construction with statistical analysis and calibration to experimental data. Using this framework, we examined the dynamics of a community of Escherichia coli strains that emerged in laboratory evolution experiments, during which an ancestral strain diversified into two coexisting ecotypes. We constructed a microbial community model comprising the ancestral and the evolved strains, which we calibrated using separate monoculture experiments. Simulations reproduced the successional dynamics in the evolution experiments, and pathway activation patterns observed in microarray transcript profiles. Our approach yielded detailed insights into the metabolic processes that drove bacterial diversification, involving acetate cross-feeding and competition for organic carbon and oxygen. Our framework provides a missing link towards a data-driven mechanistic microbial ecology.

Transient and sustained elementary flux mode networks on a catalytic string-based chemical evolution model.

PubMed

Pereira, José A

2014-08-01

Theoretical models designed to test the metabolism-first hypothesis for prebiotic evolution have yield strong indications about the hypothesis validity but could sometimes use a more extensive identification between model objects and real objects towards a more meaningful interpretation of results. In an attempt to go in that direction, the string-based model SSE ("steady state evolution") was developed, where abstract molecules (strings) and catalytic interaction rules are based on some of the most important features of carbon compounds in biological chemistry. The system is open with a random inflow and outflow of strings but also with a permanent string food source. Although specific catalysis is a key aspect of the model, used to define reaction rules, the focus is on energetics rather than kinetics. Standard energy change tables were constructed and used with standard formation reactions to track energy flows through the interpretation of equilibrium constant values. Detection of metabolic networks on the reaction system was done with elementary flux mode (EFM) analysis. The combination of these model design and analysis options enabled obtaining metabolic and catalytic networks showing several central features of biological metabolism, some more clearly than in previous models: metabolic networks with stepwise synthesis, energy coupling, catalysts regulation, SN2 coupling, redox coupling, intermediate cycling, coupled inverse pathways (metabolic cycling), autocatalytic cycles and catalytic cascades. The results strongly suggest that the main biological metabolism features, including the genotype-phenotype interpretation, are caused by the principles of catalytic systems and are prior to modern genetic systems principles. It also gives further theoretical support to the thesis that the basic features of biologic metabolism are a consequence of the time evolution of a random catalyst search working on an open system with a permanent food source. The importance of the food source characteristics and evolutionary possibilities are discussed. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

A new general circulation model of Jupiter's atmosphere based on the UKMO Unified Model: Three-dimensional evolution of isolated vortices and zonal jets in mid-latitudes

NASA Astrophysics Data System (ADS)

Yamazaki, Y. H.; Skeet, D. R.; Read, P. L.

2004-04-01

We have been developing a new three-dimensional general circulation model for the stratosphere and troposphere of Jupiter based on the dynamical core of a portable version of the Unified Model of the UK Meteorological Office. Being one of the leading terrestrial GCMs, employed for operational weather forecasting and climate research, the Unified Model has been thoroughly tested and performance tuned for both vector and parallel computers. It is formulated as a generalized form of the standard primitive equations to handle a thick atmosphere, using a scaled pressure as the vertical coordinate. It is able to accurately simulate the dynamics of a three-dimensional fully compressible atmosphere on the whole or a part of a spherical shell at high spatial resolution in all three directions. Using the current version of the GCM, we examine the characteristics of the Jovian winds in idealized configurations based on the observed vertical structure of temperature. Our initial focus is on the evolution of isolated eddies in the mid-latitudes. Following a brief theoretical investigation of the vertical structure of the atmosphere, limited-area cyclic channel domains are used to numerically investigate the nonlinear evolution of the mid-latitude winds. First, the evolution of deep and shallow cyclones and anticyclones are tested in the atmosphere at rest to identify a preferred horizontal and vertical structure of the vortices. Then, the dependency of the migration characteristics of the vortices are investigated against modelling parameters to find that it is most sensitive to the horizontal diffusion. We also examine the hydrodynamical stability of observed subtropical jets in both northern and southern hemispheres in the three-dimensional nonlinear model as initial value problems. In both cases, it was found that the prominent jets are unstable at various scales and that vorteces of various sizes are generated including those comparable to the White Ovals and the Great Red Spot.

Microstructure Modeling of Third Generation Disk Alloys

NASA Technical Reports Server (NTRS)

Jou, Herng-Jeng

2010-01-01

The objective of this program was to model, validate, and predict the precipitation microstructure evolution, using PrecipiCalc (QuesTek Innovations LLC) software, for 3rd generation Ni-based gas turbine disc superalloys during processing and service, with a set of logical and consistent experiments and characterizations. Furthermore, within this program, the originally research-oriented microstructure simulation tool was to be further improved and implemented to be a useful and user-friendly engineering tool. In this report, the key accomplishments achieved during the third year (2009) of the program are summarized. The activities of this year included: Further development of multistep precipitation simulation framework for gamma prime microstructure evolution during heat treatment; Calibration and validation of gamma prime microstructure modeling with supersolvus heat treated LSHR; Modeling of the microstructure evolution of the minor phases, particularly carbides, during isothermal aging, representing the long term microstructure stability during thermal exposure; and the implementation of software tools. During the research and development efforts to extend the precipitation microstructure modeling and prediction capability in this 3-year program, we identified a hurdle, related to slow gamma prime coarsening rate, with no satisfactory scientific explanation currently available. It is desirable to raise this issue to the Ni-based superalloys research community, with hope that in future there will be a mechanistic understanding and physics-based treatment to overcome the hurdle. In the mean time, an empirical correction factor was developed in this modeling effort to capture the experimental observations.

Construction of Optimally Reduced Empirical Model by Spatially Distributed Climate Data

NASA Astrophysics Data System (ADS)

Gavrilov, A.; Mukhin, D.; Loskutov, E.; Feigin, A.

2016-12-01

We present an approach to empirical reconstruction of the evolution operator in stochastic form by space-distributed time series. The main problem in empirical modeling consists in choosing appropriate phase variables which can efficiently reduce the dimension of the model at minimal loss of information about system's dynamics which consequently leads to more robust model and better quality of the reconstruction. For this purpose we incorporate in the model two key steps. The first step is standard preliminary reduction of observed time series dimension by decomposition via certain empirical basis (e. g. empirical orthogonal function basis or its nonlinear or spatio-temporal generalizations). The second step is construction of an evolution operator by principal components (PCs) - the time series obtained by the decomposition. In this step we introduce a new way of reducing the dimension of the embedding in which the evolution operator is constructed. It is based on choosing proper combinations of delayed PCs to take into account the most significant spatio-temporal couplings. The evolution operator is sought as nonlinear random mapping parameterized using artificial neural networks (ANN). Bayesian approach is used to learn the model and to find optimal hyperparameters: the number of PCs, the dimension of the embedding, the degree of the nonlinearity of ANN. The results of application of the method to climate data (sea surface temperature, sea level pressure) and their comparing with the same method based on non-reduced embedding are presented. The study is supported by Government of Russian Federation (agreement #14.Z50.31.0033 with the Institute of Applied Physics of RAS).

TTLEM: Open access tool for building numerically accurate landscape evolution models in MATLAB

NASA Astrophysics Data System (ADS)

Campforts, Benjamin; Schwanghart, Wolfgang; Govers, Gerard

2017-04-01

Despite a growing interest in LEMs, accuracy assessment of the numerical methods they are based on has received little attention. Here, we present TTLEM which is an open access landscape evolution package designed to develop and test your own scenarios and hypothesises. TTLEM uses a higher order flux-limiting finite-volume method to simulate river incision and tectonic displacement. We show that this scheme significantly influences the evolution of simulated landscapes and the spatial and temporal variability of erosion rates. Moreover, it allows the simulation of lateral tectonic displacement on a fixed grid. Through the use of a simple GUI the software produces visible output of evolving landscapes through model run time. In this contribution, we illustrate numerical landscape evolution through a set of movies spanning different spatial and temporal scales. We focus on the erosional domain and use both spatially constant and variable input values for uplift, lateral tectonic shortening, erodibility and precipitation. Moreover, we illustrate the relevance of a stochastic approach for realistic hillslope response modelling. TTLEM is a fully open source software package, written in MATLAB and based on the TopoToolbox platform (topotoolbox.wordpress.com). Installation instructions can be found on this website and the therefore designed GitHub repository.

Testing Phylogenetic Hypotheses of the Subgenera of the Freshwater Crayfish Genus Cambarus (Decapoda: Cambaridae)

PubMed Central

Breinholt, Jesse W.; Porter, Megan L.; Crandall, Keith A.

2012-01-01

Background The genus Cambarus is one of three most species rich crayfish genera in the Northern Hemisphere. The genus has its center of diversity in the Southern Appalachians of the United States and has been divided into 12 subgenera. Using Cambarus we test the correspondence of subgeneric designations based on morphology used in traditional crayfish taxonomy to the underlying evolutionary history for these crayfish. We further test for significant correlation and explanatory power of geographic distance, taxonomic model, and a habitat model to estimated phylogenetic distance with multiple variable regression. Methodology/Principal Findings We use three mitochondrial and one nuclear gene regions to estimate the phylogenetic relationships for species within the genus Cambarus and test evolutionary hypotheses of relationships and associated morphological and biogeographical hypotheses. Our resulting phylogeny indicates that the genus Cambarus is polyphyletic, however we fail to reject the monophyly of Cambarus with a topology test. The majority of the Cambarus subgenera are rejected as monophyletic, suggesting the morphological characters used to define those taxa are subject to convergent evolution. While we found incongruence between taxonomy and estimated phylogenetic relationships, a multiple model regression analysis indicates that taxonomy had more explanatory power of genetic relationships than either habitat or geographic distance. Conclusions We find convergent evolution has impacted the morphological features used to delimit Cambarus subgenera. Studies of the crayfish genus Orconectes have shown gonopod morphology used to delimit subgenera is also affected by convergent evolution. This suggests that morphological diagnoses based on traditional crayfish taxonomy might be confounded by convergent evolution across the cambarids and has little utility in diagnosing relationships or defining natural groups. We further suggest that convergent morphological evolution appears to be a common occurrence in invertebrates suggesting the need for careful phylogenetically based interpretations of morphological evolution in invertebrate systematics. PMID:23049950

The evolution of cooperative turn-taking in animal conflict

PubMed Central

2011-01-01

Background A fundamental assumption in animal socio-ecology is that animals compete over limited resources. This view has been challenged by the finding that individuals might cooperatively partition resources by "taking turns". Turn-taking occurs when two individuals coordinate their agonistic behaviour in a way that leads to an alternating pattern in who obtains a resource without engaging in costly fights. Cooperative turn-taking has been largely ignored in models of animal conflict and socio-ecological models that explain the evolution of social behaviours based only on contest and scramble competition. Currently it is unclear whether turn-taking should be included in socio-ecological models because the evolution of turn-taking is not well understood. In particular, it is unknown whether turn-taking can evolve when fighting costs and assessment of fighting abilities are not fixed but emerge from evolved within-fight behaviour. We address this problem with an evolutionary agent-based model. Results We found that turn-taking evolves for small resource values, alongside a contest strategy that leads to stable dominance relationships. Turn-taking leads to egalitarian societies with unclear dominance relationships and non-linear dominance hierarchies. Evolutionary stability of turn-taking emerged despite strength differences among individuals and the possibility to evolve within-fight behaviour that allows good assessment of fighting abilities. Evolutionary stability emerged from frequency-dependent effects on fitness, which are modulated by feedbacks between the evolution of within-fight behaviour and the evolution of higher-level conflict strategies. Conclusions Our results reveal the impact of feedbacks between the evolution of within-fight behaviour and the evolution of higher-level conflict strategies, such as turn-taking. Similar feedbacks might be important for the evolution of other conflict strategies such as winner-loser effects or coalitions. However, we are not aware of any study that investigated such feedbacks. Furthermore, our model suggests that turn-taking could be used by animals to partition low value resources, but to our knowledge this has never been tested. The existence of turn-taking might have been overlooked because it leads to societies with similar characteristics that have been expected to emerge from scramble competition. Analyses of temporal interaction patterns could be used to test whether turn-taking occurs in animals. PMID:22054254

The evolution of cooperative turn-taking in animal conflict.

PubMed

Franz, Mathias; van der Post, Daniel; Schülke, Oliver; Ostner, Julia

2011-11-03

A fundamental assumption in animal socio-ecology is that animals compete over limited resources. This view has been challenged by the finding that individuals might cooperatively partition resources by "taking turns". Turn-taking occurs when two individuals coordinate their agonistic behaviour in a way that leads to an alternating pattern in who obtains a resource without engaging in costly fights. Cooperative turn-taking has been largely ignored in models of animal conflict and socio-ecological models that explain the evolution of social behaviours based only on contest and scramble competition. Currently it is unclear whether turn-taking should be included in socio-ecological models because the evolution of turn-taking is not well understood. In particular, it is unknown whether turn-taking can evolve when fighting costs and assessment of fighting abilities are not fixed but emerge from evolved within-fight behaviour. We address this problem with an evolutionary agent-based model. We found that turn-taking evolves for small resource values, alongside a contest strategy that leads to stable dominance relationships. Turn-taking leads to egalitarian societies with unclear dominance relationships and non-linear dominance hierarchies. Evolutionary stability of turn-taking emerged despite strength differences among individuals and the possibility to evolve within-fight behaviour that allows good assessment of fighting abilities. Evolutionary stability emerged from frequency-dependent effects on fitness, which are modulated by feedbacks between the evolution of within-fight behaviour and the evolution of higher-level conflict strategies. Our results reveal the impact of feedbacks between the evolution of within-fight behaviour and the evolution of higher-level conflict strategies, such as turn-taking. Similar feedbacks might be important for the evolution of other conflict strategies such as winner-loser effects or coalitions. However, we are not aware of any study that investigated such feedbacks. Furthermore, our model suggests that turn-taking could be used by animals to partition low value resources, but to our knowledge this has never been tested. The existence of turn-taking might have been overlooked because it leads to societies with similar characteristics that have been expected to emerge from scramble competition. Analyses of temporal interaction patterns could be used to test whether turn-taking occurs in animals.

Prediction of dynamical systems by symbolic regression

NASA Astrophysics Data System (ADS)

Quade, Markus; Abel, Markus; Shafi, Kamran; Niven, Robert K.; Noack, Bernd R.

2016-07-01

We study the modeling and prediction of dynamical systems based on conventional models derived from measurements. Such algorithms are highly desirable in situations where the underlying dynamics are hard to model from physical principles or simplified models need to be found. We focus on symbolic regression methods as a part of machine learning. These algorithms are capable of learning an analytically tractable model from data, a highly valuable property. Symbolic regression methods can be considered as generalized regression methods. We investigate two particular algorithms, the so-called fast function extraction which is a generalized linear regression algorithm, and genetic programming which is a very general method. Both are able to combine functions in a certain way such that a good model for the prediction of the temporal evolution of a dynamical system can be identified. We illustrate the algorithms by finding a prediction for the evolution of a harmonic oscillator based on measurements, by detecting an arriving front in an excitable system, and as a real-world application, the prediction of solar power production based on energy production observations at a given site together with the weather forecast.

Experimental evidence that the Ornstein-Uhlenbeck model best describes the evolution of leaf litter decomposability.

PubMed

Pan, Xu; Cornelissen, Johannes H C; Zhao, Wei-Wei; Liu, Guo-Fang; Hu, Yu-Kun; Prinzing, Andreas; Dong, Ming; Cornwell, William K

2014-09-01

Leaf litter decomposability is an important effect trait for ecosystem functioning. However, it is unknown how this effect trait evolved through plant history as a leaf 'afterlife' integrator of the evolution of multiple underlying traits upon which adaptive selection must have acted. Did decomposability evolve in a Brownian fashion without any constraints? Was evolution rapid at first and then slowed? Or was there an underlying mean-reverting process that makes the evolution of extreme trait values unlikely? Here, we test the hypothesis that the evolution of decomposability has undergone certain mean-reverting forces due to strong constraints and trade-offs in the leaf traits that have afterlife effects on litter quality to decomposers. In order to test this, we examined the leaf litter decomposability and seven key leaf traits of 48 tree species in the temperate area of China and fitted them to three evolutionary models: Brownian motion model (BM), Early burst model (EB), and Ornstein-Uhlenbeck model (OU). The OU model, which does not allow unlimited trait divergence through time, was the best fit model for leaf litter decomposability and all seven leaf traits. These results support the hypothesis that neither decomposability nor the underlying traits has been able to diverge toward progressively extreme values through evolutionary time. These results have reinforced our understanding of the relationships between leaf litter decomposability and leaf traits in an evolutionary perspective and may be a helpful step toward reconstructing deep-time carbon cycling based on taxonomic composition with more confidence.

Gravitational wave content and stability of uniformly, rotating, triaxial neutron stars in general relativity.

PubMed

Tsokaros, Antonios; Ruiz, Milton; Paschalidis, Vasileios; Shapiro, Stuart L; Baiotti, Luca; Uryū, Kōji

2017-06-15

Targets for ground-based gravitational wave interferometers include continuous, quasiperiodic sources of gravitational radiation, such as isolated, spinning neutron stars. In this work, we perform evolution simulations of uniformly rotating, triaxially deformed stars, the compressible analogs in general relativity of incompressible, Newtonian Jacobi ellipsoids. We investigate their stability and gravitational wave emission. We employ five models, both normal and supramassive, and track their evolution with different grid setups and resolutions, as well as with two different evolution codes. We find that all models are dynamically stable and produce a strain that is approximately one-tenth the average value of a merging binary system. We track their secular evolution and find that all our stars evolve toward axisymmetry, maintaining their uniform rotation, rotational kinetic energy, and angular momentum profiles while losing their triaxiality.

Finite element simulation of texture evolution and Swift effect in NiAl under torsion

NASA Astrophysics Data System (ADS)

Böhlke, Thomas; Glüge, Rainer; Klöden, Burghardt; Skrotzki, Werner; Bertram, Albrecht

2007-09-01

The texture evolution and the Swift effect in NiAl under torsion at 727 °C are studied by finite element simulations for two different initial textures. The material behaviour is modelled by an elastic-viscoplastic Taylor model. In order to overcome the well-known shortcomings of Taylor's approach, the texture evolution is also investigated by a representative volume element (RVE) with periodic boundary conditions and a compatible microstructure at the opposite faces of the RVE. Such a representative volume element takes into account the grain morphology and the grain interaction. The numerical results are compared with experimental data. It is shown that the modelling of a finite element based RVE leads to a better prediction of the final textures. However, the texture evolution path is not accounted for correctly. The simulated Swift effect depends much more on the initial orientation distribution than observed in experiment. Deviations between simulation and experiment may be due to continuous dynamic recrystallization.

Allowing for Slow Evolution of Background Plasma in the 3D FDTD Plasma, Sheath, and Antenna Model

NASA Astrophysics Data System (ADS)

Smithe, David; Jenkins, Thomas; King, Jake

2015-11-01

We are working to include a slow-time evolution capability for what has previously been the static background plasma parameters, in the 3D finite-difference time-domain (FDTD) plasma and sheath model used to model ICRF antennas in fusion plasmas. A key aspect of this is SOL-density time-evolution driven by ponderomotive rarefaction from the strong fields in the vicinity of the antenna. We demonstrate and benchmark a Scalar Ponderomotive Potential method, based on local field amplitudes, which is included in the 3D simulation. And present a more advanced Tensor Ponderomotive Potential approach, which we hope to employ in the future, which should improve the physical fidelity in the highly anisotropic environment of the SOL. Finally, we demonstrate and benchmark slow time (non-linear) evolution of the RF sheath, and include realistic collisional effects from the neutral gas. Support from US DOE Grants DE-FC02-08ER54953, DE-FG02-09ER55006.

Simulation of dual carbon-bromine stable isotope fractionation during 1,2-dibromoethane degradation.

PubMed

Jin, Biao; Nijenhuis, Ivonne; Rolle, Massimo

2018-06-01

We performed a model-based investigation to simultaneously predict the evolution of concentration, as well as stable carbon and bromine isotope fractionation during 1,2-dibromoethane (EDB, ethylene dibromide) transformation in a closed system. The modelling approach considers bond-cleavage mechanisms during different reactions and allows evaluating dual carbon-bromine isotopic signals for chemical and biotic reactions, including aerobic and anaerobic biological transformation, dibromoelimination by Zn(0) and alkaline hydrolysis. The proposed model allowed us to accurately simulate the evolution of concentrations and isotope data observed in a previous laboratory study and to successfully identify different reaction pathways. Furthermore, we illustrated the model capabilities in degradation scenarios involving complex reaction systems. Specifically, we examined (i) the case of sequential multistep transformation of EDB and the isotopic evolution of the parent compound, the intermediate and the reaction product and (ii) the case of parallel competing abiotic pathways of EDB transformation in alkaline solution.

A Bayesian compound stochastic process for modeling nonstationary and nonhomogeneous sequence evolution.

PubMed

Blanquart, Samuel; Lartillot, Nicolas

2006-11-01

Variations of nucleotidic composition affect phylogenetic inference conducted under stationary models of evolution. In particular, they may cause unrelated taxa sharing similar base composition to be grouped together in the resulting phylogeny. To address this problem, we developed a nonstationary and nonhomogeneous model accounting for compositional biases. Unlike previous nonstationary models, which are branchwise, that is, assume that base composition only changes at the nodes of the tree, in our model, the process of compositional drift is totally uncoupled from the speciation events. In addition, the total number of events of compositional drift distributed across the tree is directly inferred from the data. We implemented the method in a Bayesian framework, relying on Markov Chain Monte Carlo algorithms, and applied it to several nucleotidic data sets. In most cases, the stationarity assumption was rejected in favor of our nonstationary model. In addition, we show that our method is able to resolve a well-known artifact. By Bayes factor evaluation, we compared our model with 2 previously developed nonstationary models. We show that the coupling between speciations and compositional shifts inherent to branchwise models may lead to an overparameterization, resulting in a lesser fit. In some cases, this leads to incorrect conclusions, concerning the nature of the compositional biases. In contrast, our compound model more flexibly adapts its effective number of parameters to the data sets under investigation. Altogether, our results show that accounting for nonstationary sequence evolution may require more elaborate and more flexible models than those currently used.

A New Automated Design Method Based on Machine Learning for CMOS Analog Circuits

NASA Astrophysics Data System (ADS)

Moradi, Behzad; Mirzaei, Abdolreza

2016-11-01

A new simulation based automated CMOS analog circuit design method which applies a multi-objective non-Darwinian-type evolutionary algorithm based on Learnable Evolution Model (LEM) is proposed in this article. The multi-objective property of this automated design of CMOS analog circuits is governed by a modified Strength Pareto Evolutionary Algorithm (SPEA) incorporated in the LEM algorithm presented here. LEM includes a machine learning method such as the decision trees that makes a distinction between high- and low-fitness areas in the design space. The learning process can detect the right directions of the evolution and lead to high steps in the evolution of the individuals. The learning phase shortens the evolution process and makes remarkable reduction in the number of individual evaluations. The expert designer's knowledge on circuit is applied in the design process in order to reduce the design space as well as the design time. The circuit evaluation is made by HSPICE simulator. In order to improve the design accuracy, bsim3v3 CMOS transistor model is adopted in this proposed design method. This proposed design method is tested on three different operational amplifier circuits. The performance of this proposed design method is verified by comparing it with the evolutionary strategy algorithm and other similar methods.

Effect of polarization on the evolution of electromagnetic hollow Gaussian Schell-model beam

NASA Astrophysics Data System (ADS)

Long, Xuewen; Lu, Keqing; Zhang, Yuhong; Guo, Jianbang; Li, Kehao

2011-02-01

Based on the theory of coherence, an analytical propagation formula for partially polarized and partially coherent hollow Gaussian Schell-model beams (HGSMBs) passing through a paraxial optical system is derived. Furthermore, we show that the degree of polarization of source may affect the evolution of HGSMBs and a tunable dark region may exist. For two special cases of fully coherent and partially coherent δxx = δyy, normalized intensity distributions are independent of the polarization of source.

Modeling the Long-term Planform Evolution of Meandering Rivers in Confined Alluvial Valleys: Etsch-Adige River, NE Italy.

NASA Astrophysics Data System (ADS)

Zen, S.; Bogoni, M.; Zolezzi, G.; Lanzoni, S.; Scorpio, V.

2016-12-01

We combine the use of a morphodynamic model for river meander planform evolution with a geological dataset to investigate the influence of external confinements on the long-term evolution of a meandering river flowing in an Alpine valley. The analysis focuses on a 100 km reach of the Adige River, NE Italy, which had several sinuous/meandering sections before being extensively channelized in the 1800s. Geological surveys and historical maps revealed that many sections of the study reach impinge on the borders of the valley during its evolution. Moreover, a marked spatial heterogeneity in floodplain vertical accretion rates likely reflects preferential positions of the river channel in the floodplain. Valley confinements are represented by bedrock outcrops and by alluvial fans created by lateral tributaries, and were extracted from the geological and historical maps to build the computational domain for the meander morphodynamic model. The model predicts the long-term planform evolution of a meandering river based on a linear solution of the 2D De St Venant-Exner differential system and can manage changes in floodplain erodibility. Model applications allow to isolate the effects of valley bedrock and of alluvial fans in constraining the lateral channel migration. Modeled river channel persistence maps are compared with the available geological information. The present work allows further insights into the role of external confinements to river meander belts, which have been conducted so far mostly assuming the channel to evolve in unconfined floodplains. Future research shall incorporate model components for floodplain vertical accretion rates and for the advancement of alluvial fans occurring at the same time scale considered for meander evolution.

Adaptive Multiscale Modeling of Geochemical Impacts on Fracture Evolution

NASA Astrophysics Data System (ADS)

Molins, S.; Trebotich, D.; Steefel, C. I.; Deng, H.

2016-12-01

Understanding fracture evolution is essential for many subsurface energy applications, including subsurface storage, shale gas production, fracking, CO2 sequestration, and geothermal energy extraction. Geochemical processes in particular play a significant role in the evolution of fractures through dissolution-driven widening, fines migration, and/or fracture sealing due to precipitation. One obstacle to understanding and exploiting geochemical fracture evolution is that it is a multiscale process. However, current geochemical modeling of fractures cannot capture this multi-scale nature of geochemical and mechanical impacts on fracture evolution, and is limited to either a continuum or pore-scale representation. Conventional continuum-scale models treat fractures as preferential flow paths, with their permeability evolving as a function (often, a cubic law) of the fracture aperture. This approach has the limitation that it oversimplifies flow within the fracture in its omission of pore scale effects while also assuming well-mixed conditions. More recently, pore-scale models along with advanced characterization techniques have allowed for accurate simulations of flow and reactive transport within the pore space (Molins et al., 2014, 2015). However, these models, even with high performance computing, are currently limited in their ability to treat tractable domain sizes (Steefel et al., 2013). Thus, there is a critical need to develop an adaptive modeling capability that can account for separate properties and processes, emergent and otherwise, in the fracture and the rock matrix at different spatial scales. Here we present an adaptive modeling capability that treats geochemical impacts on fracture evolution within a single multiscale framework. Model development makes use of the high performance simulation capability, Chombo-Crunch, leveraged by high resolution characterization and experiments. The modeling framework is based on the adaptive capability in Chombo which not only enables mesh refinement, but also refinement of the model-pore scale or continuum Darcy scale-in a dynamic way such that the appropriate model is used only when and where it is needed. Explicit flux matching provides coupling betwen the scales.

Enthalpy-Based Thermal Evolution of Loops: II. Improvements to the Model

NASA Technical Reports Server (NTRS)

Cargill, P. J.; Bradshaw, S. J.; Klimchuk, J. A.

2011-01-01

This paper further develops the zero-dimensional (0D) hydrodynamic coronal loop model "Enthalpy-based Thermal Evolution of Loops" (EBTEL) originally proposed by Klimchuk et al (2008), which studies the plasma response to evolving coronal heating. It has typically been applied to impulsive heating events. The basis of EBTEL is the modelling of mass exchange between the corona and transition region and chromosphere in response to heating variations, with the key parameter being the ratio of transition region to coronal radiation. We develop new models for this parameter that now include gravitational stratification and a physically motivated approach to radiative cooling. A number of examples are presented, including nanoflares in short and long loops, and a small flare. It is found that while the evolution of the loop temperature is rather insensitive to the details of the model, accurate tracking of the density requires the inclusion of our new features. In particular, we are able to now obtain highly over-dense loops in the late cooling phase and decreases to the coronal density arising due to stratification. The 0D results are compared to a 1D hydro code (Hydrad). The agreement is acceptable, with the exception of the flare case where some versions of Hydrad can give significantly lower densities. This is attributed to the method used to model the chromosphere in a flare. EBTEL is suitable for general use as a tool for (a) quick-look results of loop evolution in response to a given heating function and (b) situations where the modelling of hundreds or thousands of elemental loops is needed. A single run takes a few seconds on a contemporary laptop.

Decoupled scheme based on the Hermite expansion to construct lattice Boltzmann models for the compressible Navier-Stokes equations with arbitrary specific heat ratio.

PubMed

Hu, Kainan; Zhang, Hongwu; Geng, Shaojuan

2016-10-01

A decoupled scheme based on the Hermite expansion to construct lattice Boltzmann models for the compressible Navier-Stokes equations with arbitrary specific heat ratio is proposed. The local equilibrium distribution function including the rotational velocity of particle is decoupled into two parts, i.e., the local equilibrium distribution function of the translational velocity of particle and that of the rotational velocity of particle. From these two local equilibrium functions, two lattice Boltzmann models are derived via the Hermite expansion, namely one is in relation to the translational velocity and the other is connected with the rotational velocity. Accordingly, the distribution function is also decoupled. After this, the evolution equation is decoupled into the evolution equation of the translational velocity and that of the rotational velocity. The two evolution equations evolve separately. The lattice Boltzmann models used in the scheme proposed by this work are constructed via the Hermite expansion, so it is easy to construct new schemes of higher-order accuracy. To validate the proposed scheme, a one-dimensional shock tube simulation is performed. The numerical results agree with the analytical solutions very well.

Assessing the Suitability of the ClOud Reflection Algorithm (CORA) in Modelling the Evolution of an Artificial Plasma Cloud in the Ionosphere

NASA Astrophysics Data System (ADS)

Jackson-Booth, N.

2016-12-01

Artificial Ionospheric Modification (AIM) attempts to modify the ionosphere in order to alter the propagation environment. It can be achieved through injecting the ionosphere with aerosols, chemicals or radio signals. The effects of any such release can be detected through the deployment of sensors, including ground based high frequency (HF) sounders. During the Metal Oxide Space Clouds (MOSC) experiment (undertaken in April/May 2013 in the Kwajalein Atoll, part of the Marshall Islands) several oblique ionograms were recorded from a ground based HF system. These ionograms were collected over multiple geometries and allowed the effects on the HF propagation environment to be understood. These ionograms have subsequently been used in the ClOud Reflection Algorithm (CORA) to attempt to model the evolution of the cloud following release. This paper describes the latest validation results from CORA, both from testing against ionograms, but also other independent models of cloud evolution from MOSC. For all testing the various cloud models (including that generated by CORA) were incorporated into a background ionosphere through which a 3D numerical ray trace was run to produce synthetic ionograms that could be compared with the ionograms recorded during MOSC.

Evolution of equal division among unequal partners.

PubMed

Debove, Stéphane; Baumard, Nicolas; André, Jean-Baptiste

2015-02-01

One of the hallmarks of human fairness is its insensitivity to power: although strong individuals are often in a position to coerce weak individuals, fairness requires them to share the benefits of cooperation equally. The existence of such egalitarianism is poorly explained by current evolutionary models. We present a model based on cooperation and partner choice that can account for the emergence of a psychological disposition toward fairness, whatever the balance of power between the cooperative partners. We model the evolution of the division of a benefit in an interaction similar to an ultimatum game, in a population made up of individuals of variable strength. The model shows that strong individuals will not receive any advantage from their strength, instead having to share the benefits of cooperation equally with weak individuals at the evolutionary equilibrium, a result that is robust to variations in population size and the proportion of weak individuals. We discuss how this model suggests an explanation for why egalitarian behaviors toward everyone, including the weak, should be more likely to evolve in humans than in any other species. © 2015 The Author(s). Evolution © 2015 The Society for the Study of Evolution.

Thermal Evolution of Neutron Stars

NASA Astrophysics Data System (ADS)

Geppert, Ulrich R. M. E.

The thermal evolution of neutron stars is a subject of intense research, both theoretical and observational. The evolution depends very sensitively on the state of dense matter at supranuclear densities, which essentially controls the neutrino emission. The evolution depends, too, on the structure of the stellar outer layers which control the photon emission. Various internal heating processes and the magnetic field strength and structure will influence the thermal evolution. Of great importance for the cooling processes is also whether, when, and where superfluidity and superconductivity appear within the neutron star. This article describes and discusses these issues and presents neutron star cooling calculations based on a broad collection of equations of state for neutron star matter and internal magnetic field geometries. X-ray observations provide reliable data, which allow conclusions about the surface temperatures of neutron stars. To verify the thermal evolution models, the results of model calculations are compared with the body of observed surface temperatures and their distribution. Through these comparisons, a better understanding can be obtained of the physical processes that take place under extreme conditions in the interior of neutron

Dynamics of functional failures and recovery in complex road networks

NASA Astrophysics Data System (ADS)

Zhan, Xianyuan; Ukkusuri, Satish V.; Rao, P. Suresh C.

2017-11-01

We propose a new framework for modeling the evolution of functional failures and recoveries in complex networks, with traffic congestion on road networks as the case study. Differently from conventional approaches, we transform the evolution of functional states into an equivalent dynamic structural process: dual-vertex splitting and coalescing embedded within the original network structure. The proposed model successfully explains traffic congestion and recovery patterns at the city scale based on high-resolution data from two megacities. Numerical analysis shows that certain network structural attributes can amplify or suppress cascading functional failures. Our approach represents a new general framework to model functional failures and recoveries in flow-based networks and allows understanding of the interplay between structure and function for flow-induced failure propagation and recovery.

Sediment transport by runoff on debris-mantled dryland hillslopes

NASA Astrophysics Data System (ADS)

Michaelides, Katerina; Martin, Gareth J.

2012-09-01

Hillslopes supply sediment to river channels, and therefore impact drainage basin functioning and evolution. The relationship between hillslope attributes and sediment flux forms the basis of geomorphic transport laws used to model the long-term topographic evolution of drainage basins, but their specific interactions during individual storm events are not well understood. Runoff-driven erosion of coarse particles, prevalent in dryland environments, presents a particular set of conditions for sediment transport that is poorly resolved in current models. In order to address this gap, we developed a particle-based, force-balance model for sheetwash sediment transport on coarse, debris-mantled hillslopes within a rainfall-runoff model. We use the model to examine how the interplay between hillslope attributes (gradient, length and grain size distribution) and runoff characteristics affects sediment transport, grain-size changes on the hillslope, and sediment supply to the slope base. The relationship between sediment flux and hillslope gradient was found to transition from linear above a threshold to sigmoidal depending on hillslope length, initial grain sizes, and runoff characteristics. Grain sizes supplied to the slope base vary in a complex manner with hillslope attributes but an overall coarsening of the hillslopes is found to occur with increasing gradient, corroborating previous findings from field measurements. Intense, short duration storms result in within-hillslope sediment redistribution and equifinality in sediment supply for different hillslope characteristics, which explain the lack of field evidence for any systematic relationships. Our model findings provide insights into hillslope responses to climatic forcing and have theoretical implications for modeling hillslope evolution in dry lands.

Evolution of weighted complex bus transit networks with flow

NASA Astrophysics Data System (ADS)

Huang, Ailing; Xiong, Jie; Shen, Jinsheng; Guan, Wei

2016-02-01

Study on the intrinsic properties and evolutional mechanism of urban public transit networks (PTNs) has great significance for transit planning and control, particularly considering passengers’ dynamic behaviors. This paper presents an empirical analysis for exploring the complex properties of Beijing’s weighted bus transit network (BTN) based on passenger flow in L-space, and proposes a bi-level evolution model to simulate the development of transit routes from the view of complex network. The model is an iterative process that is driven by passengers’ travel demands and dual-controlled interest mechanism, which is composed of passengers’ spatio-temporal requirements and cost constraint of transit agencies. Also, the flow’s dynamic behaviors, including the evolutions of travel demand, sectional flow attracted by a new link and flow perturbation triggered in nearby routes, are taken into consideration in the evolutional process. We present the numerical experiment to validate the model, where the main parameters are estimated by using distribution functions that are deduced from real-world data. The results obtained have proven that our model can generate a BTN with complex properties, such as the scale-free behavior or small-world phenomenon, which shows an agreement with our empirical results. Our study’s results can be exploited to optimize the real BTN’s structure and improve the network’s robustness.

Evolution and mass extinctions as lognormal stochastic processes

NASA Astrophysics Data System (ADS)

Maccone, Claudio

2014-10-01

In a series of recent papers and in a book, this author put forward a mathematical model capable of embracing the search for extra-terrestrial intelligence (SETI), Darwinian Evolution and Human History into a single, unified statistical picture, concisely called Evo-SETI. The relevant mathematical tools are: (1) Geometric Brownian motion (GBM), the stochastic process representing evolution as the stochastic increase of the number of species living on Earth over the last 3.5 billion years. This GBM is well known in the mathematics of finances (Black-Sholes models). Its main features are that its probability density function (pdf) is a lognormal pdf, and its mean value is either an increasing or, more rarely, decreasing exponential function of the time. (2) The probability distributions known as b-lognormals, i.e. lognormals starting at a certain positive instant b>0 rather than at the origin. These b-lognormals were then forced by us to have their peak value located on the exponential mean-value curve of the GBM (Peak-Locus theorem). In the framework of Darwinian Evolution, the resulting mathematical construction was shown to be what evolutionary biologists call Cladistics. (3) The (Shannon) entropy of such b-lognormals is then seen to represent the `degree of progress' reached by each living organism or by each big set of living organisms, like historic human civilizations. Having understood this fact, human history may then be cast into the language of b-lognormals that are more and more organized in time (i.e. having smaller and smaller entropy, or smaller and smaller `chaos'), and have their peaks on the increasing GBM exponential. This exponential is thus the `trend of progress' in human history. (4) All these results also match with SETI in that the statistical Drake equation (generalization of the ordinary Drake equation to encompass statistics) leads just to the lognormal distribution as the probability distribution for the number of extra-terrestrial civilizations existing in the Galaxy (as a consequence of the central limit theorem of statistics). (5) But the most striking new result is that the well-known `Molecular Clock of Evolution', namely the `constant rate of Evolution at the molecular level' as shown by Kimura's Neutral Theory of Molecular Evolution, identifies with growth rate of the entropy of our Evo-SETI model, because they both grew linearly in time since the origin of life. (6) Furthermore, we apply our Evo-SETI model to lognormal stochastic processes other than GBMs. For instance, we provide two models for the mass extinctions that occurred in the past: (a) one based on GBMs and (b) the other based on a parabolic mean value capable of covering both the extinction and the subsequent recovery of life forms. (7) Finally, we show that the Markov & Korotayev (2007, 2008) model for Darwinian Evolution identifies with an Evo-SETI model for which the mean value of the underlying lognormal stochastic process is a cubic function of the time. In conclusion: we have provided a new mathematical model capable of embracing molecular evolution, SETI and entropy into a simple set of statistical equations based upon b-lognormals and lognormal stochastic processes with arbitrary mean, of which the GBMs are the particular case of exponential growth.

Crystal plasticity simulation of Zirconium tube rolling using multi-grain representative volume element

NASA Astrophysics Data System (ADS)

Isaenkova, Margarita; Perlovich, Yuriy; Zhuk, Dmitry; Krymskaya, Olga

2017-10-01

The rolling of Zirconium tube is studied by means of the crystal plasticity viscoplastic self-consistent (VPSC) constitutive modeling. This modeling performed by a dislocation-based constitutive model and a spectral solver using open-source simulation of DAMASK kit. The multi-grain representative volume elements with periodic boundary conditions are used to predict the texture evolution and distributions of strain and stresses. Two models for randomly textured and partially rolled material are deformed to 30% reduction in tube wall thickness and 7% reduction in tube diameter. The resulting shapes of the models are shown and distributions of strain are plotted. Also, evolution of grain's shape during deformation is shown.

The nearly neutral and selection theories of molecular evolution under the fisher geometrical framework: substitution rate, population size, and complexity.

PubMed

Razeto-Barry, Pablo; Díaz, Javier; Vásquez, Rodrigo A

2012-06-01

The general theories of molecular evolution depend on relatively arbitrary assumptions about the relative distribution and rate of advantageous, deleterious, neutral, and nearly neutral mutations. The Fisher geometrical model (FGM) has been used to make distributions of mutations biologically interpretable. We explored an FGM-based molecular model to represent molecular evolutionary processes typically studied by nearly neutral and selection models, but in which distributions and relative rates of mutations with different selection coefficients are a consequence of biologically interpretable parameters, such as the average size of the phenotypic effect of mutations and the number of traits (complexity) of organisms. A variant of the FGM-based model that we called the static regime (SR) represents evolution as a nearly neutral process in which substitution rates are determined by a dynamic substitution process in which the population's phenotype remains around a suboptimum equilibrium fitness produced by a balance between slightly deleterious and slightly advantageous compensatory substitutions. As in previous nearly neutral models, the SR predicts a negative relationship between molecular evolutionary rate and population size; however, SR does not have the unrealistic properties of previous nearly neutral models such as the narrow window of selection strengths in which they work. In addition, the SR suggests that compensatory mutations cannot explain the high rate of fixations driven by positive selection currently found in DNA sequences, contrary to what has been previously suggested. We also developed a generalization of SR in which the optimum phenotype can change stochastically due to environmental or physiological shifts, which we called the variable regime (VR). VR models evolution as an interplay between adaptive processes and nearly neutral steady-state processes. When strong environmental fluctuations are incorporated, the process becomes a selection model in which evolutionary rate does not depend on population size, but is critically dependent on the complexity of organisms and mutation size. For SR as well as VR we found that key parameters of molecular evolution are linked by biological factors, and we showed that they cannot be fixed independently by arbitrary criteria, as has usually been assumed in previous molecular evolutionary models.

The Nearly Neutral and Selection Theories of Molecular Evolution Under the Fisher Geometrical Framework: Substitution Rate, Population Size, and Complexity

PubMed Central

Razeto-Barry, Pablo; Díaz, Javier; Vásquez, Rodrigo A.

2012-01-01

The general theories of molecular evolution depend on relatively arbitrary assumptions about the relative distribution and rate of advantageous, deleterious, neutral, and nearly neutral mutations. The Fisher geometrical model (FGM) has been used to make distributions of mutations biologically interpretable. We explored an FGM-based molecular model to represent molecular evolutionary processes typically studied by nearly neutral and selection models, but in which distributions and relative rates of mutations with different selection coefficients are a consequence of biologically interpretable parameters, such as the average size of the phenotypic effect of mutations and the number of traits (complexity) of organisms. A variant of the FGM-based model that we called the static regime (SR) represents evolution as a nearly neutral process in which substitution rates are determined by a dynamic substitution process in which the population’s phenotype remains around a suboptimum equilibrium fitness produced by a balance between slightly deleterious and slightly advantageous compensatory substitutions. As in previous nearly neutral models, the SR predicts a negative relationship between molecular evolutionary rate and population size; however, SR does not have the unrealistic properties of previous nearly neutral models such as the narrow window of selection strengths in which they work. In addition, the SR suggests that compensatory mutations cannot explain the high rate of fixations driven by positive selection currently found in DNA sequences, contrary to what has been previously suggested. We also developed a generalization of SR in which the optimum phenotype can change stochastically due to environmental or physiological shifts, which we called the variable regime (VR). VR models evolution as an interplay between adaptive processes and nearly neutral steady-state processes. When strong environmental fluctuations are incorporated, the process becomes a selection model in which evolutionary rate does not depend on population size, but is critically dependent on the complexity of organisms and mutation size. For SR as well as VR we found that key parameters of molecular evolution are linked by biological factors, and we showed that they cannot be fixed independently by arbitrary criteria, as has usually been assumed in previous molecular evolutionary models. PMID:22426879

On The Importance of Connecting Laboratory Measurements of Ice Crystal Growth with Model Parameterizations: Predicting Ice Particle Properties

NASA Astrophysics Data System (ADS)

Harrington, J. Y.

2017-12-01

Parameterizing the growth of ice particles in numerical models is at an interesting cross-roads. Most parameterizations developed in the past, including some that I have developed, parse model ice into numerous categories based primarily on the growth mode of the particle. Models routinely possess smaller ice, snow crystals, aggregates, graupel, and hail. The snow and ice categories in some models are further split into subcategories to account for the various shapes of ice. There has been a relatively recent shift towards a new class of microphysical models that predict the properties of ice particles instead of using multiple categories and subcategories. Particle property models predict the physical characteristics of ice, such as aspect ratio, maximum dimension, effective density, rime density, effective area, and so forth. These models are attractive in the sense that particle characteristics evolve naturally in time and space without the need for numerous (and somewhat artificial) transitions among pre-defined classes. However, particle property models often require fundamental parameters that are typically derived from laboratory measurements. For instance, the evolution of particle shape during vapor depositional growth requires knowledge of the growth efficiencies for the various axis of the crystals, which in turn depends on surface parameters that can only be determined in the laboratory. The evolution of particle shapes and density during riming, aggregation, and melting require data on the redistribution of mass across a crystals axis as that crystal collects water drops, ice crystals, or melts. Predicting the evolution of particle properties based on laboratory-determined parameters has a substantial influence on the evolution of some cloud systems. Radiatively-driven cirrus clouds show a broader range of competition between heterogeneous nucleation and homogeneous freezing when ice crystal properties are predicted. Even strongly convective squall lines show a substantial influence to predicted particle properties: The more natural evolution of ice crystals during riming produces graupel-like particles with size and fall-speeds required for the formation of a classic transition zone and extended stratiform precipitation region.

Advantages of Computer Simulation in Enhancing Students' Learning about Landform Evolution: A Case Study Using the Grand Canyon

ERIC Educational Resources Information Center

Luo, Wei; Pelletier, Jon; Duffin, Kirk; Ormand, Carol; Hung, Wei-chen; Shernoff, David J.; Zhai, Xiaoming; Iverson, Ellen; Whalley, Kyle; Gallaher, Courtney; Furness, Walter

2016-01-01

The long geological time needed for landform development and evolution poses a challenge for understanding and appreciating the processes involved. The Web-based Interactive Landform Simulation Model--Grand Canyon (WILSIM-GC, http://serc.carleton.edu/landform/) is an educational tool designed to help students better understand such processes,…

Rank-dependent deactivation in network evolution.

PubMed

Xu, Xin-Jian; Zhou, Ming-Chen

2009-12-01

A rank-dependent deactivation mechanism is introduced to network evolution. The growth dynamics of the network is based on a finite memory of individuals, which is implemented by deactivating one site at each time step. The model shows striking features of a wide range of real-world networks: power-law degree distribution, high clustering coefficient, and disassortative degree correlation.

A study of lunar models based on Apollo and other data

NASA Technical Reports Server (NTRS)

1973-01-01

The research concerned with the interpretation of lunar data developed during the Apollo Program is reported. The areas of research include: X-ray emission spectra and molecular orbitals of lunar materials, magnetic properties of lunar rock, lunar features, thermal history and evolution of the moon, and the internal constitution and evolution of the moon.

Evolution of Cygnus X-3 through its Radio and X-ray States

NASA Astrophysics Data System (ADS)

Szostek, A.; Zdziarski, A. A.; McCollough, M. L.

2009-05-01

Based on X-ray spectra and studies of the long-term correlated behavior between radio and soft X-ray, we present a detailed evolution of Cyg X-3 through its radio and X-ray states. We comment on the nature of the hard X-ray tail and possible Simbol X contribution in constraining the models.

Reconstructing Anaximander's biological model unveils a theory of evolution akin to Darwin's, though centuries before the birth of science.

PubMed

Trevisanato, Siro Igino

2016-08-01

Anaximander's fragments on biology report a theory of evolution, which, unlike the development of other biological systems in the ancient Aegean, is naturalistic and is not based on metaphysics. According to Anaximander, evolution affected all living beings, including humans. The first biological systems formed in an aquatic environment, and were encased in a rugged and robust envelope. Evolution progressed with modifications that enabled the formation of more dynamic biological systems. For instance, after reaching land, the robust armors around aquatic beings dried up, and became brittle, This led to the loss of the armor and the development of more mobile life forms. Anaximander's theory combines observations of animals with speculations, and as such mirrors the more famous theory of evolution by Charles Darwin expressed 24 centuries later. The poor reception received by Anaximander's model in his time, illustrates a zeitgeist that would explain the contemporary lag phase in the development of biology and, as a result, medicine, in the ancient western world.

A new molecular evolution model for limited insertion independent of substitution.

PubMed

Lèbre, Sophie; Michel, Christian J

2013-10-01

We recently introduced a new molecular evolution model called the IDIS model for Insertion Deletion Independent of Substitution [13,14]. In the IDIS model, the three independent processes of substitution, insertion and deletion of residues have constant rates. In order to control the genome expansion during evolution, we generalize here the IDIS model by introducing an insertion rate which decreases when the sequence grows and tends to 0 for a maximum sequence length nmax. This new model, called LIIS for Limited Insertion Independent of Substitution, defines a matrix differential equation satisfied by a vector P(t) describing the sequence content in each residue at evolution time t. An analytical solution is obtained for any diagonalizable substitution matrix M. Thus, the LIIS model gives an expression of the sequence content vector P(t) in each residue under evolution time t as a function of the eigenvalues and the eigenvectors of matrix M, the residue insertion rate vector R, the total insertion rate r, the initial and maximum sequence lengths n0 and nmax, respectively, and the sequence content vector P(t0) at initial time t0. The derivation of the analytical solution is much more technical, compared to the IDIS model, as it involves Gauss hypergeometric functions. Several propositions of the LIIS model are derived: proof that the IDIS model is a particular case of the LIIS model when the maximum sequence length nmax tends to infinity, fixed point, time scale, time step and time inversion. Using a relation between the sequence length l and the evolution time t, an expression of the LIIS model as a function of the sequence length l=n(t) is obtained. Formulas for 'insertion only', i.e. when the substitution rates are all equal to 0, are derived at evolution time t and sequence length l. Analytical solutions of the LIIS model are explicitly derived, as a function of either evolution time t or sequence length l, for two classical substitution matrices: the 3-parameter symmetric substitution matrix [12] (LIIS-SYM3) and the HKY asymmetric substitution matrix[9] (LIIS-HKY). An evaluation of the LIIS model (precisely, LIIS-HKY) based on four statistical analyses of the GC content in complete genomes of four prokaryotic taxonomic groups, namely Chlamydiae, Crenarchaeota, Spirochaetes and Thermotogae, shows the expected improvement from the theory of the LIIS model compared to the IDIS model. Copyright © 2013 Elsevier Inc. All rights reserved.

Integrated modeling of second phase precipitation in cold-worked 316 stainless steels under irradiation

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

Mamivand, Mahmood; Yang, Ying; Busby, Jeremy T.

The current work combines the Cluster Dynamics (CD) technique and CALPHAD-based precipitation modeling to address the second phase precipitation in cold-worked (CW) 316 stainless steels (SS) under irradiation at 300–400 °C. CD provides the radiation enhanced diffusion and dislocation evolution as inputs for the precipitation model. The CALPHAD-based precipitation model treats the nucleation, growth and coarsening of precipitation processes based on classical nucleation theory and evolution equations, and simulates the composition, size and size distribution of precipitate phases. We benchmark the model against available experimental data at fast reactor conditions (9.4 × 10 –7 dpa/s and 390 °C) and thenmore » use the model to predict the phase instability of CW 316 SS under light water reactor (LWR) extended life conditions (7 × 10 –8 dpa/s and 275 °C). The model accurately predicts the γ' (Ni 3Si) precipitation evolution under fast reactor conditions and that the formation of this phase is dominated by radiation enhanced segregation. The model also predicts a carbide volume fraction that agrees well with available experimental data from a PWR reactor but is much higher than the volume fraction observed in fast reactors. We propose that radiation enhanced dissolution and/or carbon depletion at sinks that occurs at high flux could be the main sources of this inconsistency. The integrated model predicts ~1.2% volume fraction for carbide and ~3.0% volume fraction for γ' for typical CW 316 SS (with 0.054 wt% carbon) under LWR extended life conditions. Finally, this work provides valuable insights into the magnitudes and mechanisms of precipitation in irradiated CW 316 SS for nuclear applications.« less

Integrated modeling of second phase precipitation in cold-worked 316 stainless steels under irradiation

DOE PAGES

Mamivand, Mahmood; Yang, Ying; Busby, Jeremy T.; ...

2017-03-11

The current work combines the Cluster Dynamics (CD) technique and CALPHAD-based precipitation modeling to address the second phase precipitation in cold-worked (CW) 316 stainless steels (SS) under irradiation at 300–400 °C. CD provides the radiation enhanced diffusion and dislocation evolution as inputs for the precipitation model. The CALPHAD-based precipitation model treats the nucleation, growth and coarsening of precipitation processes based on classical nucleation theory and evolution equations, and simulates the composition, size and size distribution of precipitate phases. We benchmark the model against available experimental data at fast reactor conditions (9.4 × 10 –7 dpa/s and 390 °C) and thenmore » use the model to predict the phase instability of CW 316 SS under light water reactor (LWR) extended life conditions (7 × 10 –8 dpa/s and 275 °C). The model accurately predicts the γ' (Ni 3Si) precipitation evolution under fast reactor conditions and that the formation of this phase is dominated by radiation enhanced segregation. The model also predicts a carbide volume fraction that agrees well with available experimental data from a PWR reactor but is much higher than the volume fraction observed in fast reactors. We propose that radiation enhanced dissolution and/or carbon depletion at sinks that occurs at high flux could be the main sources of this inconsistency. The integrated model predicts ~1.2% volume fraction for carbide and ~3.0% volume fraction for γ' for typical CW 316 SS (with 0.054 wt% carbon) under LWR extended life conditions. Finally, this work provides valuable insights into the magnitudes and mechanisms of precipitation in irradiated CW 316 SS for nuclear applications.« less

Incorporation of Plasticity and Damage Into an Orthotropic Three-Dimensional Model with Tabulated Input Suitable for Use in Composite Impact Problems

NASA Technical Reports Server (NTRS)

Goldberg, Robert K.; Carney, Kelly S.; DuBois, Paul; Hoffarth, Canio; Rajan, Subramaniam; Blackenhorn, Gunther

2015-01-01

The need for accurate material models to simulate the deformation, damage and failure of polymer matrix composites under impact conditions is becoming critical as these materials are gaining increased usage in the aerospace and automotive industries. While there are several composite material models currently available within commercial transient dynamic finite element codes, several features have been identified as being lacking in the currently available material models that could substantially enhance the predictive capability of the impact simulations. A specific desired feature pertains to the incorporation of both plasticity and damage within the material model. Another desired feature relates to using experimentally based tabulated stress-strain input to define the evolution of plasticity and damage as opposed to specifying discrete input properties (such as modulus and strength) and employing analytical functions to track the response of the material. To begin to address these needs, a combined plasticity and damage model suitable for use with both solid and shell elements is being developed for implementation within the commercial code LS-DYNA. The plasticity model is based on extending the Tsai-Wu composite failure model into a strain-hardening based orthotropic plasticity model with a non-associative flow rule. The evolution of the yield surface is determined based on tabulated stress-strain curves in the various normal and shear directions and is tracked using the effective plastic strain. The effective plastic strain is computed by using the non-associative flow rule in combination with appropriate numerical methods. To compute the evolution of damage, a strain equivalent semi-coupled formulation is used, in which a load in one direction results in a stiffness reduction in multiple coordinate directions. A specific laminated composite is examined to demonstrate the process of characterizing and analyzing the response of a composite using the developed model.

A Thermodynamically-Based Mesh Objective Work Potential Theory for Predicting Intralaminar Progressive Damage and Failure in Fiber-Reinforced Laminates

NASA Technical Reports Server (NTRS)

Pineda, Evan J.; Waas, Anthony M.

2012-01-01

A thermodynamically-based work potential theory for modeling progressive damage and failure in fiber-reinforced laminates is presented. The current, multiple-internal state variable (ISV) formulation, enhanced Schapery theory (EST), utilizes separate ISVs for modeling the effects of damage and failure. Damage is considered to be the effect of any structural changes in a material that manifest as pre-peak non-linearity in the stress versus strain response. Conversely, failure is taken to be the effect of the evolution of any mechanisms that results in post-peak strain softening. It is assumed that matrix microdamage is the dominant damage mechanism in continuous fiber-reinforced polymer matrix laminates, and its evolution is controlled with a single ISV. Three additional ISVs are introduced to account for failure due to mode I transverse cracking, mode II transverse cracking, and mode I axial failure. Typically, failure evolution (i.e., post-peak strain softening) results in pathologically mesh dependent solutions within a finite element method (FEM) setting. Therefore, consistent character element lengths are introduced into the formulation of the evolution of the three failure ISVs. Using the stationarity of the total work potential with respect to each ISV, a set of thermodynamically consistent evolution equations for the ISVs is derived. The theory is implemented into commercial FEM software. Objectivity of total energy dissipated during the failure process, with regards to refinements in the FEM mesh, is demonstrated. The model is also verified against experimental results from two laminated, T800/3900-2 panels containing a central notch and different fiber-orientation stacking sequences. Global load versus displacement, global load versus local strain gage data, and macroscopic failure paths obtained from the models are compared to the experiments.

Effect of Streamflow Forecast Uncertainty on Real-Time Reservoir Operation

NASA Astrophysics Data System (ADS)

Zhao, T.; Cai, X.; Yang, D.

2010-12-01

Various hydrological forecast products have been applied to real-time reservoir operation, including deterministic streamflow forecast (DSF), DSF-based probabilistic streamflow forecast (DPSF), and ensemble streamflow forecast (ESF), which represent forecast uncertainty in the form of deterministic forecast error, deterministic forecast error-based uncertainty distribution, and ensemble forecast errors, respectively. Compared to previous studies that treat these forecast products as ad hoc inputs for reservoir operation models, this paper attempts to model the uncertainties involved in the various forecast products and explores their effect on real-time reservoir operation decisions. In hydrology, there are various indices reflecting the magnitude of streamflow forecast uncertainty; meanwhile, few models illustrate the forecast uncertainty evolution process. This research introduces Martingale Model of Forecast Evolution (MMFE) from supply chain management and justifies its assumptions for quantifying the evolution of uncertainty in streamflow forecast as time progresses. Based on MMFE, this research simulates the evolution of forecast uncertainty in DSF, DPSF, and ESF, and applies the reservoir operation models (dynamic programming, DP; stochastic dynamic programming, SDP; and standard operation policy, SOP) to assess the effect of different forms of forecast uncertainty on real-time reservoir operation. Through a hypothetical single-objective real-time reservoir operation model, the results illustrate that forecast uncertainty exerts significant effects. Reservoir operation efficiency, as measured by a utility function, decreases as the forecast uncertainty increases. Meanwhile, these effects also depend on the type of forecast product being used. In general, the utility of reservoir operation with ESF is nearly as high as the utility obtained with a perfect forecast; the utilities of DSF and DPSF are similar to each other but not as efficient as ESF. Moreover, streamflow variability and reservoir capacity can change the magnitude of the effects of forecast uncertainty, but not the relative merit of DSF, DPSF, and ESF. Schematic diagram of the increase in forecast uncertainty with forecast lead-time and the dynamic updating property of real-time streamflow forecast

Evolution of the solar irradiance during the Holocene

NASA Astrophysics Data System (ADS)

Vieira, L. E. A.; Solanki, S. K.; Krivova, N. A.; Usoskin, I.

2011-07-01

Context. Long-term records of solar radiative output are vital for understanding solar variability and past climate change. Measurements of solar irradiance are available for only the last three decades, which calls for reconstructions of this quantity over longer time scales using suitable models. Aims: We present a physically consistent reconstruction of the total solar irradiance for the Holocene. Methods: We extend the SATIRE (Spectral And Total Irradiance REconstruction) models to estimate the evolution of the total (and partly spectral) solar irradiance over the Holocene. The basic assumption is that the variations of the solar irradiance are due to the evolution of the dark and bright magnetic features on the solar surface. The evolution of the decadally averaged magnetic flux is computed from decadal values of cosmogenic isotope concentrations recorded in natural archives employing a series of physics-based models connecting the processes from the modulation of the cosmic ray flux in the heliosphere to their record in natural archives. We then compute the total solar irradiance (TSI) as a linear combination of the jth and jth + 1 decadal values of the open magnetic flux. In order to evaluate the uncertainties due to the evolution of the Earth's magnetic dipole moment, we employ four reconstructions of the open flux which are based on conceptually different paleomagnetic models. Results: Reconstructions of the TSI over the Holocene, each valid for a different paleomagnetic time series, are presented. Our analysis suggests that major sources of uncertainty in the TSI in this model are the heritage of the uncertainty of the TSI since 1610 reconstructed from sunspot data and the uncertainty of the evolution of the Earth's magnetic dipole moment. The analysis of the distribution functions of the reconstructed irradiance for the last 3000 years, which is the period that the reconstructions overlap, indicates that the estimates based on the virtual axial dipole moment are significantly lower at earlier times than the reconstructions based on the virtual dipole moment. We also present a combined reconstruction, which represents our best estimate of total solar irradiance for any given time during the Holocene. Conclusions: We present the first physics-based reconstruction of the total solar irradiance over the Holocene, which will be of interest for studies of climate change over the last 11 500 years. The reconstruction indicates that the decadally averaged total solar irradiance ranges over approximately 1.5 W/m2 from grand maxima to grand minima. Appendix A is available in electronic form at http://www.aanda.orgThe TSI data is only available at the CDS via anonymous ftp to cdsarc.u-strasbg.fr (130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/531/A6

Genetic-evolution-based optimization methods for engineering design

NASA Technical Reports Server (NTRS)

Rao, S. S.; Pan, T. S.; Dhingra, A. K.; Venkayya, V. B.; Kumar, V.

1990-01-01

This paper presents the applicability of a biological model, based on genetic evolution, for engineering design optimization. Algorithms embodying the ideas of reproduction, crossover, and mutation are developed and applied to solve different types of structural optimization problems. Both continuous and discrete variable optimization problems are solved. A two-bay truss for maximum fundamental frequency is considered to demonstrate the continuous variable case. The selection of locations of actuators in an actively controlled structure, for minimum energy dissipation, is considered to illustrate the discrete variable case.

What does convergent evolution mean? The interpretation of convergence and its implications in the search for limits to evolution

PubMed Central

Stayton, C. Tristan

2015-01-01

Convergent evolution is central to the study of life's evolutionary history. Researchers have documented the ubiquity of convergence and have used this ubiquity to make inferences about the nature of limits on evolution. However, these inferences are compromised by unrecognized inconsistencies in the definitions, measures, significance tests and inferred causes of convergent evolution. I review these inconsistencies and provide recommendations for standardizing studies of convergence. A fundamental dichotomy exists between definitions that describe convergence as a pattern and those that describe it as a pattern caused by a particular process. When this distinction is not acknowledged it becomes easy to assume that a pattern of convergence indicates that a particular process has been active, leading researchers away from alternative explanations. Convergence is not necessarily caused by limits to evolution, either adaptation or constraint; even substantial amounts of convergent evolution can be generated by a purely stochastic process. In the absence of null models, long lists of examples of convergent events do not necessarily indicate that convergence or any evolutionary process is ubiquitous throughout the history of life. Pattern-based definitions of convergence, coupled with quantitative measures and null models, must be applied before drawing inferences regarding large-scale limits to evolution. PMID:26640646

Evolution of cranial telescoping in echolocating whales (Cetacea: Odontoceti).

PubMed

Churchill, Morgan; Geisler, Jonathan H; Beatty, Brian L; Goswami, Anjali

2018-05-01

Odontocete (echolocating whale) skulls exhibit extreme posterior displacement and overlapping of facial bones, here referred to as retrograde cranial telescoping. To examine retrograde cranial telescoping across 40 million years of whale evolution, we collected 3D scans of whale skulls spanning odontocete evolution. We used a sliding semilandmark morphometric approach with Procrustes superimposition and PCA to capture and describe the morphological variation present in the facial region, followed by Ancestral Character State Reconstruction (ACSR) and evolutionary model fitting on significant components to determine how retrograde cranial telescoping evolved. The first PC score explains the majority of variation associated with telescoping and reflects the posterior migration of the external nares and premaxilla alongside expansion of the maxilla and frontal. The earliest diverging fossil odontocetes were found to exhibit a lesser degree of cranial telescoping than later diverging but contemporary whale taxa. Major shifts in PC scores and centroid size are identified at the base of Odontoceti, and early burst and punctuated equilibrium models best fit the evolution of retrograde telescoping. This indicates that the Oligocene was a period of unusually high diversity and evolution in whale skull morphology, with little subsequent evolution in telescoping. © 2018 The Author(s). Evolution © 2018 The Society for the Study of Evolution.

Networks of Learning

NASA Astrophysics Data System (ADS)

Bettencourt, Luis; Kaiser, David

2004-03-01

Based on an a historically documented example of scientific discovery - Feynman diagrams as the main calculational tool of theoretical high energy Physics - we map the time evolution of the social network of early adopters through in the US, UK, Japan and the USSR. The spread of the technique for total number of users in each region is then modelled in terms of epidemic models, highlighting parallel and divergent aspects of this analogy. We also show that transient social arrangements develop as the idea is introduced and learned, which later disappear as the technique becomes common knowledge. Such early transient is characterized by abnormally low connectivity distribution powers and by high clustering. This interesting early non-equilibrium stage of network evolution is captured by a new dynamical model for network evolution, which coincides in its long time limit with familiar preferential aggregation dynamics.

Scaling and efficiency determine the irreversible evolution of a market

PubMed Central

Baldovin, F.; Stella, A. L.

2007-01-01

In setting up a stochastic description of the time evolution of a financial index, the challenge consists in devising a model compatible with all stylized facts emerging from the analysis of financial time series and providing a reliable basis for simulating such series. Based on constraints imposed by market efficiency and on an inhomogeneous-time generalization of standard simple scaling, we propose an analytical model which accounts simultaneously for empirical results like the linear decorrelation of successive returns, the power law dependence on time of the volatility autocorrelation function, and the multiscaling associated to this dependence. In addition, our approach gives a justification and a quantitative assessment of the irreversible character of the index dynamics. This irreversibility enters as a key ingredient in a novel simulation strategy of index evolution which demonstrates the predictive potential of the model.

Multiphysics of bone remodeling: A 2D mesoscale activation simulation.

PubMed

Spingarn, C; Wagner, D; Rémond, Y; George, D

2017-01-01

In this work, we present an evolutive trabecular model for bone remodeling based on a boundary detection algorithm accounting for both biology and applied mechanical forces, known to be an important factor in bone evolution. A finite element (FE) numerical model using the Abaqus/Standard® software was used with a UMAT subroutine to solve the governing coupled mechanical-biological non-linear differential equations of the bone evolution model. The simulations present cell activation on a simplified trabeculae configuration organization with trabecular thickness of 200µm. For this activation process, the results confirm that the trabeculae are mainly oriented in the active direction of the principal mechanical stresses and according to the principal applied mechanical load directions. The trabeculae surface activation is clearly identified and can provide understanding of the different bone cell activations in more complex geometries and load conditions.

Predicting infant cortical surface development using a 4D varifold-based learning framework and local topography-based shape morphing.

PubMed

Rekik, Islem; Li, Gang; Lin, Weili; Shen, Dinggang

2016-02-01

Longitudinal neuroimaging analysis methods have remarkably advanced our understanding of early postnatal brain development. However, learning predictive models to trace forth the evolution trajectories of both normal and abnormal cortical shapes remains broadly absent. To fill this critical gap, we pioneered the first prediction model for longitudinal developing cortical surfaces in infants using a spatiotemporal current-based learning framework solely from the baseline cortical surface. In this paper, we detail this prediction model and even further improve its performance by introducing two key variants. First, we use the varifold metric to overcome the limitations of the current metric for surface registration that was used in our preliminary study. We also extend the conventional varifold-based surface registration model for pairwise registration to a spatiotemporal surface regression model. Second, we propose a morphing process of the baseline surface using its topographic attributes such as normal direction and principal curvature sign. Specifically, our method learns from longitudinal data both the geometric (vertices positions) and dynamic (temporal evolution trajectories) features of the infant cortical surface, comprising a training stage and a prediction stage. In the training stage, we use the proposed varifold-based shape regression model to estimate geodesic cortical shape evolution trajectories for each training subject. We then build an empirical mean spatiotemporal surface atlas. In the prediction stage, given an infant, we select the best learnt features from training subjects to simultaneously predict the cortical surface shapes at all later timepoints, based on similarity metrics between this baseline surface and the learnt baseline population average surface atlas. We used a leave-one-out cross validation method to predict the inner cortical surface shape at 3, 6, 9 and 12 months of age from the baseline cortical surface shape at birth. Our method attained a higher prediction accuracy and better captured the spatiotemporal dynamic change of the highly folded cortical surface than the previous proposed prediction method. Copyright © 2015 Elsevier B.V. All rights reserved.

The SPACE 1.0 model: a Landlab component for 2-D calculation of sediment transport, bedrock erosion, and landscape evolution

NASA Astrophysics Data System (ADS)

Shobe, Charles M.; Tucker, Gregory E.; Barnhart, Katherine R.

2017-12-01

Models of landscape evolution by river erosion are often either transport-limited (sediment is always available but may or may not be transportable) or detachment-limited (sediment must be detached from the bed but is then always transportable). While several models incorporate elements of, or transition between, transport-limited and detachment-limited behavior, most require that either sediment or bedrock, but not both, are eroded at any given time. Modeling landscape evolution over large spatial and temporal scales requires a model that can (1) transition freely between transport-limited and detachment-limited behavior, (2) simultaneously treat sediment transport and bedrock erosion, and (3) run in 2-D over large grids and be coupled with other surface process models. We present SPACE (stream power with alluvium conservation and entrainment) 1.0, a new model for simultaneous evolution of an alluvium layer and a bedrock bed based on conservation of sediment mass both on the bed and in the water column. The model treats sediment transport and bedrock erosion simultaneously, embracing the reality that many rivers (even those commonly defined as bedrock rivers) flow over a partially alluviated bed. SPACE improves on previous models of bedrock-alluvial rivers by explicitly calculating sediment erosion and deposition rather than relying on a flux-divergence (Exner) approach. The SPACE model is a component of the Landlab modeling toolkit, a Python-language library used to create models of Earth surface processes. Landlab allows efficient coupling between the SPACE model and components simulating basin hydrology, hillslope evolution, weathering, lithospheric flexure, and other surface processes. Here, we first derive the governing equations of the SPACE model from existing sediment transport and bedrock erosion formulations and explore the behavior of local analytical solutions for sediment flux and alluvium thickness. We derive steady-state analytical solutions for channel slope, alluvium thickness, and sediment flux, and show that SPACE matches predicted behavior in detachment-limited, transport-limited, and mixed conditions. We provide an example of landscape evolution modeling in which SPACE is coupled with hillslope diffusion, and demonstrate that SPACE provides an effective framework for simultaneously modeling 2-D sediment transport and bedrock erosion.

Negotiation and appeasement can be more effective drivers of sociality than kin selection.

PubMed

Quiñones, Andrés E; van Doorn, G Sander; Pen, Ido; Weissing, Franz J; Taborsky, Michael

2016-02-05

Two alternative frameworks explain the evolution of cooperation in the face of conflicting interests. Conflicts can be alleviated by kinship, the alignment of interests by virtue of shared genes, or by negotiation strategies, allowing mutually beneficial trading of services or commodities. Although negotiation often occurs in kin-structured populations, the interplay of kin- and negotiation-based mechanisms in the evolution of cooperation remains an unresolved issue. Inspired by the biology of a cooperatively breeding fish, we developed an individual-based simulation model to study the evolution of negotiation-based cooperation in relation to different levels of genetic relatedness. We show that the evolution of negotiation strategies leads to an equilibrium where subordinates appease dominants by conditional cooperation, resulting in high levels of help and low levels of aggression. This negotiation-based equilibrium can be reached both in the absence of relatedness and in a kin-structured population. However, when relatedness is high, evolution often ends up in an alternative equilibrium where subordinates help their kin unconditionally. The level of help at this kin-selected equilibrium is considerably lower than at the negotiation-based equilibrium, and it corresponds to a level reached when responsiveness is prevented from evolving in the simulations. A mathematical invasion analysis reveals that, quite generally, the alignment of payoffs due to the relatedness of interaction partners tends to impede selection for harsh but effective punishment of defectors. Hence kin structure will often hamper rather than facilitate the evolution of productive cooperation. © 2016 The Author(s).

Negotiation and appeasement can be more effective drivers of sociality than kin selection

PubMed Central

van Doorn, G. Sander; Pen, Ido; Weissing, Franz J.

2016-01-01

Two alternative frameworks explain the evolution of cooperation in the face of conflicting interests. Conflicts can be alleviated by kinship, the alignment of interests by virtue of shared genes, or by negotiation strategies, allowing mutually beneficial trading of services or commodities. Although negotiation often occurs in kin-structured populations, the interplay of kin- and negotiation-based mechanisms in the evolution of cooperation remains an unresolved issue. Inspired by the biology of a cooperatively breeding fish, we developed an individual-based simulation model to study the evolution of negotiation-based cooperation in relation to different levels of genetic relatedness. We show that the evolution of negotiation strategies leads to an equilibrium where subordinates appease dominants by conditional cooperation, resulting in high levels of help and low levels of aggression. This negotiation-based equilibrium can be reached both in the absence of relatedness and in a kin-structured population. However, when relatedness is high, evolution often ends up in an alternative equilibrium where subordinates help their kin unconditionally. The level of help at this kin-selected equilibrium is considerably lower than at the negotiation-based equilibrium, and it corresponds to a level reached when responsiveness is prevented from evolving in the simulations. A mathematical invasion analysis reveals that, quite generally, the alignment of payoffs due to the relatedness of interaction partners tends to impede selection for harsh but effective punishment of defectors. Hence kin structure will often hamper rather than facilitate the evolution of productive cooperation. PMID:26729929

Inequity aversion and the evolution of cooperation

NASA Astrophysics Data System (ADS)

Ahmed, Asrar; Karlapalem, Kamalakar

2014-02-01

Evolution of cooperation is a widely studied problem in biology, social science, economics, and artificial intelligence. Most of the existing approaches that explain cooperation rely on some notion of direct or indirect reciprocity. These reciprocity based models assume agents recognize their partner and know their previous interactions, which requires advanced cognitive abilities. In this paper we are interested in developing a model that produces cooperation without requiring any explicit memory of previous game plays. Our model is based on the notion of inequity aversion, a concept introduced within behavioral economics, whereby individuals care about payoff equality in outcomes. Here we explore the effect of using income inequality to guide partner selection and interaction. We study our model by considering both the well-mixed and the spatially structured population and present the conditions under which cooperation becomes dominant. Our results support the hypothesis that inequity aversion promotes cooperative relationship among nonkin.

Inequity aversion and the evolution of cooperation.

PubMed

Ahmed, Asrar; Karlapalem, Kamalakar

2014-02-01

Evolution of cooperation is a widely studied problem in biology, social science, economics, and artificial intelligence. Most of the existing approaches that explain cooperation rely on some notion of direct or indirect reciprocity. These reciprocity based models assume agents recognize their partner and know their previous interactions, which requires advanced cognitive abilities. In this paper we are interested in developing a model that produces cooperation without requiring any explicit memory of previous game plays. Our model is based on the notion of inequity aversion, a concept introduced within behavioral economics, whereby individuals care about payoff equality in outcomes. Here we explore the effect of using income inequality to guide partner selection and interaction. We study our model by considering both the well-mixed and the spatially structured population and present the conditions under which cooperation becomes dominant. Our results support the hypothesis that inequity aversion promotes cooperative relationship among nonkin.

Numerical Predictions of Damage and Failure in Carbon Fiber Reinforced Laminates Using a Thermodynamically-Based Work Potential Theory

NASA Technical Reports Server (NTRS)

Pineda, Evan Jorge; Waas, Anthony M.

2013-01-01

A thermodynamically-based work potential theory for modeling progressive damage and failure in fiber-reinforced laminates is presented. The current, multiple-internal state variable (ISV) formulation, referred to as enhanced Schapery theory (EST), utilizes separate ISVs for modeling the effects of damage and failure. Consistent characteristic lengths are introduced into the formulation to govern the evolution of the failure ISVs. Using the stationarity of the total work potential with respect to each ISV, a set of thermodynamically consistent evolution equations for the ISVs are derived. The theory is implemented into a commercial finite element code. The model is verified against experimental results from two laminated, T800/3900-2 panels containing a central notch and different fiber-orientation stacking sequences. Global load versus displacement, global load versus local strain gage data, and macroscopic failure paths obtained from the models are compared against the experimental results.

Exhumation and topographic evolution of the Namche Barwa Syntaxis, eastern Himalaya

NASA Astrophysics Data System (ADS)

Yang, Rong; Herman, Frédéric; Fellin, Maria Giuditta; Maden, Colin

2018-01-01

The Namche Barwa Syntaxis, as one of the most tectonically active regions, remains an appropriate place to explore the relationship between tectonics, surface processes, and landscape evolution. Two leading models have been proposed for the formation and evolution of this syntaxis, including the tectonic aneurysm model and the syntaxis expansion model. Here we use a multi-disciplinary approach based on low-temperature thermochronometry, numerical modeling, river profile and topographic analyses to investigate the interactions between tectonics, erosion, and landscape evolution and to test these models. Our results emphasize the presence of young cooling ages (i.e., < 1 Ma) along the Parlung River, to the north of the syntaxis. Using numerical modeling we argue that a recent increase in exhumation rate is required to expose these young ages. Our river analysis reveals spatial variations in channel steepness, which we interpret to reflect the rock uplift pattern. By establishing the relationship between erosion rates and topographic features, we find that erosion rates are poorly to weakly correlated with topographic features, suggesting that the landscape is still evolving. Altogether, these results seem better explained by a mechanism that involves a northward expansion of the syntaxis, which causes high rock uplift rates to the north of the syntaxis and a transient state of topography adjusting to an evolving tectonic setting.

Model for macroevolutionary dynamics.

PubMed

Maruvka, Yosef E; Shnerb, Nadav M; Kessler, David A; Ricklefs, Robert E

2013-07-02

The highly skewed distribution of species among genera, although challenging to macroevolutionists, provides an opportunity to understand the dynamics of diversification, including species formation, extinction, and morphological evolution. Early models were based on either the work by Yule [Yule GU (1925) Philos Trans R Soc Lond B Biol Sci 213:21-87], which neglects extinction, or a simple birth-death (speciation-extinction) process. Here, we extend the more recent development of a generic, neutral speciation-extinction (of species)-origination (of genera; SEO) model for macroevolutionary dynamics of taxon diversification. Simulations show that deviations from the homogeneity assumptions in the model can be detected in species-per-genus distributions. The SEO model fits observed species-per-genus distributions well for class-to-kingdom-sized taxonomic groups. The model's predictions for the appearance times (the time of the first existing species) of the taxonomic groups also approximately match estimates based on molecular inference and fossil records. Unlike estimates based on analyses of phylogenetic reconstruction, fitted extinction rates for large clades are close to speciation rates, consistent with high rates of species turnover and the relatively slow change in diversity observed in the fossil record. Finally, the SEO model generally supports the consistency of generic boundaries based on morphological differences between species and provides a comparator for rates of lineage splitting and morphological evolution.

A thermomechanical constitutive model for cemented granular materials with quantifiable internal variables. Part I-Theory

NASA Astrophysics Data System (ADS)

Tengattini, Alessandro; Das, Arghya; Nguyen, Giang D.; Viggiani, Gioacchino; Hall, Stephen A.; Einav, Itai

2014-10-01

This is the first of two papers introducing a novel thermomechanical continuum constitutive model for cemented granular materials. Here, we establish the theoretical foundations of the model, and highlight its novelties. At the limit of no cement, the model is fully consistent with the original Breakage Mechanics model. An essential ingredient of the model is the use of measurable and micro-mechanics based internal variables, describing the evolution of the dominant inelastic processes. This imposes a link between the macroscopic mechanical behavior and the statistically averaged evolution of the microstructure. As a consequence this model requires only a few physically identifiable parameters, including those of the original breakage model and new ones describing the cement: its volume fraction, its critical damage energy and bulk stiffness, and the cohesion.

Probabilistic models of eukaryotic evolution: time for integration

PubMed Central

Lartillot, Nicolas

2015-01-01

In spite of substantial work and recent progress, a global and fully resolved picture of the macroevolutionary history of eukaryotes is still under construction. This concerns not only the phylogenetic relations among major groups, but also the general characteristics of the underlying macroevolutionary processes, including the patterns of gene family evolution associated with endosymbioses, as well as their impact on the sequence evolutionary process. All these questions raise formidable methodological challenges, calling for a more powerful statistical paradigm. In this direction, model-based probabilistic approaches have played an increasingly important role. In particular, improved models of sequence evolution accounting for heterogeneities across sites and across lineages have led to significant, although insufficient, improvement in phylogenetic accuracy. More recently, one main trend has been to move away from simple parametric models and stepwise approaches, towards integrative models explicitly considering the intricate interplay between multiple levels of macroevolutionary processes. Such integrative models are in their infancy, and their application to the phylogeny of eukaryotes still requires substantial improvement of the underlying models, as well as additional computational developments. PMID:26323768

Multi-agent fare optimization model of two modes problem and its analysis based on edge of chaos

NASA Astrophysics Data System (ADS)

Li, Xue-yan; Li, Xue-mei; Li, Xue-wei; Qiu, He-ting

2017-03-01

This paper proposes a new framework of fare optimization & game model for studying the competition between two travel modes (high speed railway and civil aviation) in which passengers' group behavior is taken into consideration. The small-world network is introduced to construct the multi-agent model of passengers' travel mode choice. The cumulative prospect theory is adopted to depict passengers' bounded rationality, the heterogeneity of passengers' reference point is depicted using the idea of group emotion computing. The conceptions of "Langton parameter" and "evolution entropy" in the theory of "edge of chaos" are introduced to create passengers' "decision coefficient" and "evolution entropy of travel mode choice" which are used to quantify passengers' group behavior. The numerical simulation and the analysis of passengers' behavior show that (1) the new model inherits the features of traditional model well and the idea of self-organizing traffic flow evolution fully embodies passengers' bounded rationality, (2) compared with the traditional model (logit model), when passengers are in the "edge of chaos" state, the total profit of the transportation system is higher.

Wolf-Rayet stars, black holes and the first detected gravitational wave source

NASA Astrophysics Data System (ADS)

Bogomazov, A. I.; Cherepashchuk, A. M.; Lipunov, V. M.; Tutukov, A. V.

2018-01-01

The recently discovered burst of gravitational waves GW150914 provides a good new chance to verify the current view on the evolution of close binary stars. Modern population synthesis codes help to study this evolution from two main sequence stars up to the formation of two final remnant degenerate dwarfs, neutron stars or black holes (Masevich and Tutukov, 1988). To study the evolution of the GW150914 predecessor we use the ;Scenario Machine; code presented by Lipunov et al. (1996). The scenario modeling conducted in this study allowed to describe the evolution of systems for which the final stage is a massive BH+BH merger. We find that the initial mass of the primary component can be 100÷140M⊙ and the initial separation of the components can be 50÷350R⊙. Our calculations show the plausibility of modern evolutionary scenarios for binary stars and the population synthesis modeling based on it.

When does female multiple mating evolve to adjust inbreeding? Effects of inbreeding depression, direct costs, mating constraints, and polyandry as a threshold trait.

PubMed

Duthie, A Bradley; Bocedi, Greta; Reid, Jane M

2016-09-01

Polyandry is often hypothesized to evolve to allow females to adjust the degree to which they inbreed. Multiple factors might affect such evolution, including inbreeding depression, direct costs, constraints on male availability, and the nature of polyandry as a threshold trait. Complex models are required to evaluate when evolution of polyandry to adjust inbreeding is predicted to arise. We used a genetically explicit individual-based model to track the joint evolution of inbreeding strategy and polyandry defined as a polygenic threshold trait. Evolution of polyandry to avoid inbreeding only occurred given strong inbreeding depression, low direct costs, and severe restrictions on initial versus additional male availability. Evolution of polyandry to prefer inbreeding only occurred given zero inbreeding depression and direct costs, and given similarly severe restrictions on male availability. However, due to its threshold nature, phenotypic polyandry was frequently expressed even when strongly selected against and hence maladaptive. Further, the degree to which females adjusted inbreeding through polyandry was typically very small, and often reflected constraints on male availability rather than adaptive reproductive strategy. Evolution of polyandry solely to adjust inbreeding might consequently be highly restricted in nature, and such evolution cannot necessarily be directly inferred from observed magnitudes of inbreeding adjustment. © 2016 The Author(s). Evolution published by Wiley Periodicals, Inc. on behalf of The Society for the Study of Evolution.

Calculating the spatio-temporal variability of bedrock exposure on seasonal hydrograph timescales as a prerequisite to modeling bedrock river evolution

NASA Astrophysics Data System (ADS)

Hurst, A. A.; Anderson, R. S.; Tucker, G. E.

2017-12-01

Erosion of bedrock river channels exerts significant control on landscape evolution because it communicates climatic and tectonic signals across a landscape by setting the lower erosional boundaries for hillslopes. Hillslope erosion delivers sediment to the channels, which then either store or transport the sediment. At times of high storage, access to the bedrock floor of the channel is limited, inhibiting bedrock erosion. This affects the timescale of channel response to imposed base-level lowering, which in turn affects hillslope erosion. Because occasional exposure of the bedrock bed is a minimum prerequisite for bedrock erosion, we seek to understand the evolution of sediment cover, or scour history, with sufficient resolution to answer when and where the bed is exposed. The scour history at a site is governed by grain size, bed and channel morphology, sediment concentration in the water, and seasonal flow conditions (hydrograph). The transient nature of bedrock exposure during high-flow events implies that short-term sediment cover dynamics are important for predicting long-term bedrock incision rates. Models of channel profile evolution, or of landscape evolution, generally ignore evolution of sediment cover on the hydrograph timescale. To develop insight into the necessary and sufficient conditions for bedrock exposure followed by reburial, we have developed a 1-D model of the evolution of alluvial cover thickness in a long channel profile in response to a seasonal hydrograph. This model tracks erosion, deposition, and the concentration of sediment in the water column separately, and generates histories of scour and fill over the course of the hydrograph. We compare the model's predictions with net-scour measurements in tributaries of the Grand Canyon and with scour-chain and accelerometer measurements in the Cedar River, Washington. By addressing alluvial scour on short timescales, we acknowledge the processes required to allow bedrock incision and landscape evolution over longer timescales.

Plio-Pleistocene time evolution of the 100-ky cycle in marine paleoclimate records

NASA Technical Reports Server (NTRS)

Park, Jeffrey; Maasch, Kirk A.

1992-01-01

To constrain theories for the dynamical evolution of global ice mass through the late Neogene, it is important to determine whether major changes in the record were gradual or rapid. Of particular interest is the evolution of the near 100-ky ice age cycle in the middle Pleistocene. We have applied a new technique based on multiple taper spectrum analysis which allows us to model the time evolution of quasi-periodic signals. This technique uses both phase and amplitude information, and enables us to address the question of abrupt versus gradual onset of the 100-ky periodicity in the middle Pleistocene.

Iterated learning and the evolution of language.

PubMed

Kirby, Simon; Griffiths, Tom; Smith, Kenny

2014-10-01

Iterated learning describes the process whereby an individual learns their behaviour by exposure to another individual's behaviour, who themselves learnt it in the same way. It can be seen as a key mechanism of cultural evolution. We review various methods for understanding how behaviour is shaped by the iterated learning process: computational agent-based simulations; mathematical modelling; and laboratory experiments in humans and non-human animals. We show how this framework has been used to explain the origins of structure in language, and argue that cultural evolution must be considered alongside biological evolution in explanations of language origins. Copyright © 2014 Elsevier Ltd. All rights reserved.

Evolving nutritional strategies in the presence of competition: a geometric agent-based model.

PubMed

Senior, Alistair M; Charleston, Michael A; Lihoreau, Mathieu; Buhl, Jerome; Raubenheimer, David; Simpson, Stephen J

2015-03-01

Access to nutrients is a key factor governing development, reproduction and ultimately fitness. Within social groups, contest-competition can fundamentally affect nutrient access, potentially leading to reproductive asymmetry among individuals. Previously, agent-based models have been combined with the Geometric Framework of nutrition to provide insight into how nutrition and social interactions affect one another. Here, we expand this modelling approach by incorporating evolutionary algorithms to explore how contest-competition over nutrient acquisition might affect the evolution of animal nutritional strategies. Specifically, we model tolerance of nutrient excesses and deficits when ingesting nutritionally imbalanced foods, which we term 'nutritional latitude'; a higher degree of nutritional latitude constitutes a higher tolerance of nutritional excess and deficit. Our results indicate that a transition between two alternative strategies occurs at moderate to high levels of competition. When competition is low, individuals display a low level of nutritional latitude and regularly switch foods in search of an optimum. When food is scarce and contest-competition is intense, high nutritional latitude appears optimal, and individuals continue to consume an imbalanced food for longer periods before attempting to switch to an alternative. However, the relative balance of nutrients within available foods also strongly influences at what levels of competition, if any, transitions between these two strategies occur. Our models imply that competition combined with reproductive skew in social groups can play a role in the evolution of diet breadth. We discuss how the integration of agent-based, nutritional and evolutionary modelling may be applied in future studies to further understand the evolution of nutritional strategies across social and ecological contexts.

Simulating the elimination of sleeping sickness with an agent-based model.

PubMed

Grébaut, Pascal; Girardin, Killian; Fédérico, Valentine; Bousquet, François

2016-01-01

Although Human African Trypanosomiasis is largely considered to be in the process of extinction today, the persistence of human and animal reservoirs, as well as the vector, necessitates a laborious elimination process. In this context, modeling could be an effective tool to evaluate the ability of different public health interventions to control the disease. Using the Cormas ® system, we developed HATSim, an agent-based model capable of simulating the possible endemic evolutions of sleeping sickness and the ability of National Control Programs to eliminate the disease. This model takes into account the analysis of epidemiological, entomological, and ecological data from field studies conducted during the last decade, making it possible to predict the evolution of the disease within this area over a 5-year span. In this article, we first present HATSim according to the Overview, Design concepts, and Details (ODD) protocol that is classically used to describe agent-based models, then, in a second part, we present predictive results concerning the evolution of Human African Trypanosomiasis in the village of Lambi (Cameroon), in order to illustrate the interest of such a tool. Our results are consistent with what was observed in the field by the Cameroonian National Control Program (CNCP). Our simulations also revealed that regular screening can be sufficient, although vector control applied to all areas with human activities could be significantly more efficient. Our results indicate that the current model can already help decision-makers in planning the elimination of the disease in foci. © P. Grébaut et al., published by EDP Sciences, 2016.

Experimental evidence that the Ornstein-Uhlenbeck model best describes the evolution of leaf litter decomposability

PubMed Central

Pan, Xu; Cornelissen, Johannes H C; Zhao, Wei-Wei; Liu, Guo-Fang; Hu, Yu-Kun; Prinzing, Andreas; Dong, Ming; Cornwell, William K

2014-01-01

Leaf litter decomposability is an important effect trait for ecosystem functioning. However, it is unknown how this effect trait evolved through plant history as a leaf ‘afterlife’ integrator of the evolution of multiple underlying traits upon which adaptive selection must have acted. Did decomposability evolve in a Brownian fashion without any constraints? Was evolution rapid at first and then slowed? Or was there an underlying mean-reverting process that makes the evolution of extreme trait values unlikely? Here, we test the hypothesis that the evolution of decomposability has undergone certain mean-reverting forces due to strong constraints and trade-offs in the leaf traits that have afterlife effects on litter quality to decomposers. In order to test this, we examined the leaf litter decomposability and seven key leaf traits of 48 tree species in the temperate area of China and fitted them to three evolutionary models: Brownian motion model (BM), Early burst model (EB), and Ornstein-Uhlenbeck model (OU). The OU model, which does not allow unlimited trait divergence through time, was the best fit model for leaf litter decomposability and all seven leaf traits. These results support the hypothesis that neither decomposability nor the underlying traits has been able to diverge toward progressively extreme values through evolutionary time. These results have reinforced our understanding of the relationships between leaf litter decomposability and leaf traits in an evolutionary perspective and may be a helpful step toward reconstructing deep-time carbon cycling based on taxonomic composition with more confidence. PMID:25535551

Morphological bubble evolution induced by air diffusion on submerged hydrophobic structures

NASA Astrophysics Data System (ADS)

Lv, Pengyu; Xiang, Yaolei; Xue, Yahui; Lin, Hao; Duan, Huiling

2017-03-01

Bubbles trapped in the cavities always play important roles in the underwater applications of structured hydrophobic surfaces. Air exchange between bubbles and surrounding water has a significant influence on the morphological bubble evolution, which in turn frequently affects the functionalities of the surfaces, such as superhydrophobicity and drag reduction. In this paper, air diffusion induced bubble evolution on submerged hydrophobic micropores under reduced pressures is investigated experimentally and theoretically. The morphological behaviors of collective and single bubbles are observed using confocal microscopy. Four representative evolution phases of bubbles are captured in situ. After depressurization, bubbles will not only grow and coalesce but also shrink and split although the applied pressure remains negative. A diffusion-based model is used to analyze the evolution behavior and the results are consistent with the experimental data. A criterion for bubble growth and shrinkage is also derived along with a phase diagram, revealing that the competition of effective gas partial pressures across the two sides of the diffusion layer dominates the bubble evolution process. Strategies for controlling the bubble evolution behavior are also proposed based on the phase diagram. The current work provides a further understanding of the general behavior of bubble evolution induced by air diffusion and can be employed to better designs of functional microstructured hydrophobic surfaces.

Evolution of precopulatory and post-copulatory strategies of inbreeding avoidance and associated polyandry.

PubMed

Duthie, A B; Bocedi, G; Germain, R R; Reid, J M

2018-01-01

Inbreeding depression is widely hypothesized to drive adaptive evolution of precopulatory and post-copulatory mechanisms of inbreeding avoidance, which in turn are hypothesized to affect evolution of polyandry (i.e. female multiple mating). However, surprisingly little theory or modelling critically examines selection for precopulatory or post-copulatory inbreeding avoidance, or both strategies, given evolutionary constraints and direct costs, or examines how evolution of inbreeding avoidance strategies might feed back to affect evolution of polyandry. Selection for post-copulatory inbreeding avoidance, but not for precopulatory inbreeding avoidance, requires polyandry, whereas interactions between precopulatory and post-copulatory inbreeding avoidance might cause functional redundancy (i.e. 'degeneracy') potentially generating complex evolutionary dynamics among inbreeding strategies and polyandry. We used individual-based modelling to quantify evolution of interacting precopulatory and post-copulatory inbreeding avoidance and associated polyandry given strong inbreeding depression and different evolutionary constraints and direct costs. We found that evolution of post-copulatory inbreeding avoidance increased selection for initially rare polyandry and that evolution of a costly inbreeding avoidance strategy became negligible over time given a lower-cost alternative strategy. Further, fixed precopulatory inbreeding avoidance often completely precluded evolution of polyandry and hence post-copulatory inbreeding avoidance, but fixed post-copulatory inbreeding avoidance did not preclude evolution of precopulatory inbreeding avoidance. Evolution of inbreeding avoidance phenotypes and associated polyandry is therefore affected by evolutionary feedbacks and degeneracy. All else being equal, evolution of precopulatory inbreeding avoidance and resulting low polyandry is more likely when post-copulatory inbreeding avoidance is precluded or costly, and evolution of post-copulatory inbreeding avoidance greatly facilitates evolution of costly polyandry. © The Authors. Journal of Evolutionary Biology published by John Wiley & Sons Ltd on behalf of European Society for Evolutionary Biology.

Integrating Intracellular Dynamics Using CompuCell3D and Bionetsolver: Applications to Multiscale Modelling of Cancer Cell Growth and Invasion

PubMed Central

Andasari, Vivi; Roper, Ryan T.; Swat, Maciej H.; Chaplain, Mark A. J.

2012-01-01

In this paper we present a multiscale, individual-based simulation environment that integrates CompuCell3D for lattice-based modelling on the cellular level and Bionetsolver for intracellular modelling. CompuCell3D or CC3D provides an implementation of the lattice-based Cellular Potts Model or CPM (also known as the Glazier-Graner-Hogeweg or GGH model) and a Monte Carlo method based on the metropolis algorithm for system evolution. The integration of CC3D for cellular systems with Bionetsolver for subcellular systems enables us to develop a multiscale mathematical model and to study the evolution of cell behaviour due to the dynamics inside of the cells, capturing aspects of cell behaviour and interaction that is not possible using continuum approaches. We then apply this multiscale modelling technique to a model of cancer growth and invasion, based on a previously published model of Ramis-Conde et al. (2008) where individual cell behaviour is driven by a molecular network describing the dynamics of E-cadherin and -catenin. In this model, which we refer to as the centre-based model, an alternative individual-based modelling technique was used, namely, a lattice-free approach. In many respects, the GGH or CPM methodology and the approach of the centre-based model have the same overall goal, that is to mimic behaviours and interactions of biological cells. Although the mathematical foundations and computational implementations of the two approaches are very different, the results of the presented simulations are compatible with each other, suggesting that by using individual-based approaches we can formulate a natural way of describing complex multi-cell, multiscale models. The ability to easily reproduce results of one modelling approach using an alternative approach is also essential from a model cross-validation standpoint and also helps to identify any modelling artefacts specific to a given computational approach. PMID:22461894

Experimental Study of Damage Evolution in Circular Stirrup-Confined Concrete

PubMed Central

Li, Zuohua; Peng, Zhihan; Teng, Jun; Wang, Ying

2016-01-01

This paper presents an experimental study on circular stirrup-confined concrete specimens under uniaxial and monotonic load. The effects of stirrup volume ratio, stirrup yield strength and concrete strength on damage evolution of stirrup-confined concrete were investigated. The experimental results showed that the strength and ductility of concrete are improved by appropriate arrangement of the stirrup confinement. Firstly, the concrete damage evolution can be relatively restrained with the increase of the stirrup volume ratio. Secondly, higher stirrup yield strength usually causes larger confining pressures and slower concrete damage evolution. In contrast, higher concrete strength leads to higher brittleness, which accelerates the concrete damage evolution. A plastic strain expression is obtained through curve fitting, and a damage evolution equation for circular stirrup-confined concrete is proposed by introducing a confinement factor (C) based on the experimental data. The comparison results demonstrate that the proposed damage evolution model can accurately describe the experimental results. PMID:28773402

Experimental Study of Damage Evolution in Circular Stirrup-Confined Concrete.

PubMed

Li, Zuohua; Peng, Zhihan; Teng, Jun; Wang, Ying

2016-04-08

This paper presents an experimental study on circular stirrup-confined concrete specimens under uniaxial and monotonic load. The effects of stirrup volume ratio, stirrup yield strength and concrete strength on damage evolution of stirrup-confined concrete were investigated. The experimental results showed that the strength and ductility of concrete are improved by appropriate arrangement of the stirrup confinement. Firstly, the concrete damage evolution can be relatively restrained with the increase of the stirrup volume ratio. Secondly, higher stirrup yield strength usually causes larger confining pressures and slower concrete damage evolution. In contrast, higher concrete strength leads to higher brittleness, which accelerates the concrete damage evolution. A plastic strain expression is obtained through curve fitting, and a damage evolution equation for circular stirrup-confined concrete is proposed by introducing a confinement factor ( C ) based on the experimental data. The comparison results demonstrate that the proposed damage evolution model can accurately describe the experimental results.

Plant domestication slows pest evolution.

PubMed

Turcotte, Martin M; Lochab, Amaneet K; Turley, Nash E; Johnson, Marc T J

2015-09-01

Agricultural practices such as breeding resistant varieties and pesticide use can cause rapid evolution of pest species, but it remains unknown how plant domestication itself impacts pest contemporary evolution. Using experimental evolution on a comparative phylogenetic scale, we compared the evolutionary dynamics of a globally important economic pest - the green peach aphid (Myzus persicae) - growing on 34 plant taxa, represented by 17 crop species and their wild relatives. Domestication slowed aphid evolution by 13.5%, maintained 10.4% greater aphid genotypic diversity and 5.6% higher genotypic richness. The direction of evolution (i.e. which genotypes increased in frequency) differed among independent domestication events but was correlated with specific plant traits. Individual-based simulation models suggested that domestication affects aphid evolution directly by reducing the strength of selection and indirectly by increasing aphid density and thus weakening genetic drift. Our results suggest that phenotypic changes during domestication can alter pest evolutionary dynamics. © 2015 John Wiley & Sons Ltd/CNRS.

An overview of structurally complex network-based modeling of public opinion in the “We the Media” era

NASA Astrophysics Data System (ADS)

Wang, Guanghui; Wang, Yufei; Liu, Yijun; Chi, Yuxue

2018-05-01

As the transmission of public opinion on the Internet in the “We the Media” era tends to be supraterritorial, concealed and complex, the traditional “point-to-surface” transmission of information has been transformed into “point-to-point” reciprocal transmission. A foundation for studies of the evolution of public opinion and its transmission on the Internet in the “We the Media” era can be laid by converting the massive amounts of fragmented information on public opinion that exists on “We the Media” platforms into structurally complex networks of information. This paper describes studies of structurally complex network-based modeling of public opinion on the Internet in the “We the Media” era from the perspective of the development and evolution of complex networks. The progress that has been made in research projects relevant to the structural modeling of public opinion on the Internet is comprehensively summarized. The review considers aspects such as regular grid-based modeling of the rules that describe the propagation of public opinion on the Internet in the “We the Media” era, social network modeling, dynamic network modeling, and supernetwork modeling. Moreover, an outlook for future studies that address complex network-based modeling of public opinion on the Internet is put forward as a summary from the perspective of modeling conducted using the techniques mentioned above.

Biophysical and structural considerations for protein sequence evolution

PubMed Central

2011-01-01

Background Protein sequence evolution is constrained by the biophysics of folding and function, causing interdependence between interacting sites in the sequence. However, current site-independent models of sequence evolutions do not take this into account. Recent attempts to integrate the influence of structure and biophysics into phylogenetic models via statistical/informational approaches have not resulted in expected improvements in model performance. This suggests that further innovations are needed for progress in this field. Results Here we develop a coarse-grained physics-based model of protein folding and binding function, and compare it to a popular informational model. We find that both models violate the assumption of the native sequence being close to a thermodynamic optimum, causing directional selection away from the native state. Sampling and simulation show that the physics-based model is more specific for fold-defining interactions that vary less among residue type. The informational model diffuses further in sequence space with fewer barriers and tends to provide less support for an invariant sites model, although amino acid substitutions are generally conservative. Both approaches produce sequences with natural features like dN/dS < 1 and gamma-distributed rates across sites. Conclusions Simple coarse-grained models of protein folding can describe some natural features of evolving proteins but are currently not accurate enough to use in evolutionary inference. This is partly due to improper packing of the hydrophobic core. We suggest possible improvements on the representation of structure, folding energy, and binding function, as regards both native and non-native conformations, and describe a large number of possible applications for such a model. PMID:22171550

Complexities’ day-to-day dynamic evolution analysis and prediction for a Didi taxi trip network based on complex network theory

NASA Astrophysics Data System (ADS)

Zhang, Lin; Lu, Jian; Zhou, Jialin; Zhu, Jinqing; Li, Yunxuan; Wan, Qian

2018-03-01

Didi Dache is the most popular taxi order mobile app in China, which provides online taxi-hailing service. The obtained big database from this app could be used to analyze the complexities’ day-to-day dynamic evolution of Didi taxi trip network (DTTN) from the level of complex network dynamics. First, this paper proposes the data cleaning and modeling methods for expressing Nanjing’s DTTN as a complex network. Second, the three consecutive weeks’ data are cleaned to establish 21 DTTNs based on the proposed big data processing technology. Then, multiple topology measures that characterize the complexities’ day-to-day dynamic evolution of these networks are provided. Third, these measures of 21 DTTNs are calculated and subsequently explained with actual implications. They are used as a training set for modeling the BP neural network which is designed for predicting DTTN complexities evolution. Finally, the reliability of the designed BP neural network is verified by comparing with the actual data and the results obtained from ARIMA method simultaneously. Because network complexities are the basis for modeling cascading failures and conducting link prediction in complex system, this proposed research framework not only provides a novel perspective for analyzing DTTN from the level of system aggregated behavior, but can also be used to improve the DTTN management level.

Subgrid Modeling Geomorphological and Ecological Processes in Salt Marsh Evolution

NASA Astrophysics Data System (ADS)

Shi, F.; Kirby, J. T., Jr.; Wu, G.; Abdolali, A.; Deb, M.

2016-12-01

Numerical modeling a long-term evolution of salt marshes is challenging because it requires an extensive use of computational resources. Due to the presence of narrow tidal creeks, variations of salt marsh topography can be significant over spatial length scales on the order of a meter. With growing availability of high-resolution bathymetry measurements, like LiDAR-derived DEM data, it is increasingly desirable to run a high-resolution model in a large domain and for a long period of time to get trends of sedimentation patterns, morphological change and marsh evolution. However, high spatial-resolution poses a big challenge in both computational time and memory storage, when simulating a salt marsh with dimensions of up to O(100 km^2) with a small time step. In this study, we have developed a so-called Pre-storage, Sub-grid Model (PSM, Wu et al., 2015) for simulating flooding and draining processes in salt marshes. The simulation of Brokenbridge salt marsh, Delaware, shows that, with the combination of the sub-grid model and the pre-storage method, over 2 orders of magnitude computational speed-up can be achieved with minimal loss of model accuracy. We recently extended PSM to include a sediment transport component and models for biomass growth and sedimentation in the sub-grid model framework. The sediment transport model is formulated based on a newly derived sub-grid sediment concentration equation following Defina's (2000) area-averaging procedure. Suspended sediment transport is modeled by the advection-diffusion equation in the coarse grid level, but the local erosion and sedimentation rates are integrated over the sub-grid level. The morphological model is based on the existing morphological model in NearCoM (Shi et al., 2013), extended to include organic production from the biomass model. The vegetation biomass is predicted by a simple logistic equation model proposed by Marani et al. (2010). The biomass component is loosely coupled with hydrodynamic and sedimentation models owing to the different time scales of the physical and ecological processes. The coupled model is being applied to Delaware marsh evolution in response to rising sea level and changing sediment supplies.

Towards physical principles of biological evolution

NASA Astrophysics Data System (ADS)

Katsnelson, Mikhail I.; Wolf, Yuri I.; Koonin, Eugene V.

2018-03-01

Biological systems reach organizational complexity that far exceeds the complexity of any known inanimate objects. Biological entities undoubtedly obey the laws of quantum physics and statistical mechanics. However, is modern physics sufficient to adequately describe, model and explain the evolution of biological complexity? Detailed parallels have been drawn between statistical thermodynamics and the population-genetic theory of biological evolution. Based on these parallels, we outline new perspectives on biological innovation and major transitions in evolution, and introduce a biological equivalent of thermodynamic potential that reflects the innovation propensity of an evolving population. Deep analogies have been suggested to also exist between the properties of biological entities and processes, and those of frustrated states in physics, such as glasses. Such systems are characterized by frustration whereby local state with minimal free energy conflict with the global minimum, resulting in ‘emergent phenomena’. We extend such analogies by examining frustration-type phenomena, such as conflicts between different levels of selection, in biological evolution. These frustration effects appear to drive the evolution of biological complexity. We further address evolution in multidimensional fitness landscapes from the point of view of percolation theory and suggest that percolation at level above the critical threshold dictates the tree-like evolution of complex organisms. Taken together, these multiple connections between fundamental processes in physics and biology imply that construction of a meaningful physical theory of biological evolution might not be a futile effort. However, it is unrealistic to expect that such a theory can be created in one scoop; if it ever comes to being, this can only happen through integration of multiple physical models of evolutionary processes. Furthermore, the existing framework of theoretical physics is unlikely to suffice for adequate modeling of the biological level of complexity, and new developments within physics itself are likely to be required.

Evolution of Geometric Sensitivity Derivatives from Computer Aided Design Models

NASA Technical Reports Server (NTRS)

Jones, William T.; Lazzara, David; Haimes, Robert

2010-01-01

The generation of design parameter sensitivity derivatives is required for gradient-based optimization. Such sensitivity derivatives are elusive at best when working with geometry defined within the solid modeling context of Computer-Aided Design (CAD) systems. Solid modeling CAD systems are often proprietary and always complex, thereby necessitating ad hoc procedures to infer parameter sensitivity. A new perspective is presented that makes direct use of the hierarchical associativity of CAD features to trace their evolution and thereby track design parameter sensitivity. In contrast to ad hoc methods, this method provides a more concise procedure following the model design intent and determining the sensitivity of CAD geometry directly to its respective defining parameters.

Explaining evolution via constrained persistent perfect phylogeny

PubMed Central

2014-01-01

Background The perfect phylogeny is an often used model in phylogenetics since it provides an efficient basic procedure for representing the evolution of genomic binary characters in several frameworks, such as for example in haplotype inference. The model, which is conceptually the simplest, is based on the infinite sites assumption, that is no character can mutate more than once in the whole tree. A main open problem regarding the model is finding generalizations that retain the computational tractability of the original model but are more flexible in modeling biological data when the infinite site assumption is violated because of e.g. back mutations. A special case of back mutations that has been considered in the study of the evolution of protein domains (where a domain is acquired and then lost) is persistency, that is the fact that a character is allowed to return back to the ancestral state. In this model characters can be gained and lost at most once. In this paper we consider the computational problem of explaining binary data by the Persistent Perfect Phylogeny model (referred as PPP) and for this purpose we investigate the problem of reconstructing an evolution where some constraints are imposed on the paths of the tree. Results We define a natural generalization of the PPP problem obtained by requiring that for some pairs (character, species), neither the species nor any of its ancestors can have the character. In other words, some characters cannot be persistent for some species. This new problem is called Constrained PPP (CPPP). Based on a graph formulation of the CPPP problem, we are able to provide a polynomial time solution for the CPPP problem for matrices whose conflict graph has no edges. Using this result, we develop a parameterized algorithm for solving the CPPP problem where the parameter is the number of characters. Conclusions A preliminary experimental analysis shows that the constrained persistent perfect phylogeny model allows to explain efficiently data that do not conform with the classical perfect phylogeny model. PMID:25572381

Brittle fracture phase-field modeling of a short-rod specimen

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

Escobar, Ivana; Tupek, Michael R.; Bishop, Joseph E.

2015-09-01

Predictive simulation capabilities for modeling fracture evolution provide further insight into quantities of interest in comparison to experimental testing. Based on the variational approach to fracture, the advent of phase-field modeling achieves the goal to robustly model fracture for brittle materials and captures complex crack topologies in three dimensions.

Analyzing the evolutionary mechanisms of the Air Transportation System-of-Systems using network theory and machine learning algorithms

NASA Astrophysics Data System (ADS)

Kotegawa, Tatsuya

Complexity in the Air Transportation System (ATS) arises from the intermingling of many independent physical resources, operational paradigms, and stakeholder interests, as well as the dynamic variation of these interactions over time. Currently, trade-offs and cost benefit analyses of new ATS concepts are carried out on system-wide evaluation simulations driven by air traffic forecasts that assume fixed airline routes. However, this does not well reflect reality as airlines regularly add and remove routes. A airline service route network evolution model that projects route addition and removal was created and combined with state-of-the-art air traffic forecast methods to better reflect the dynamic properties of the ATS in system-wide simulations. Guided by a system-of-systems framework, network theory metrics and machine learning algorithms were applied to develop the route network evolution models based on patterns extracted from historical data. Constructing the route addition section of the model posed the greatest challenge due to the large pool of new link candidates compared to the actual number of routes historically added to the network. Of the models explored, algorithms based on logistic regression, random forests, and support vector machines showed best route addition and removal forecast accuracies at approximately 20% and 40%, respectively, when validated with historical data. The combination of network evolution models and a system-wide evaluation tool quantified the impact of airline route network evolution on air traffic delay. The expected delay minutes when considering network evolution increased approximately 5% for a forecasted schedule on 3/19/2020. Performance trade-off studies between several airline route network topologies from the perspectives of passenger travel efficiency, fuel burn, and robustness were also conducted to provide bounds that could serve as targets for ATS transformation efforts. The series of analysis revealed that high robustness is achievable only in exchange of lower passenger travel and fuel burn efficiency. However, increase in the network density can mitigate this trade-off.

An extended car-following model considering the acceleration derivative in some typical traffic environments

NASA Astrophysics Data System (ADS)

Zhou, Tong; Chen, Dong; Liu, Weining

2018-03-01

Based on the full velocity difference and acceleration car-following model, an extended car-following model is proposed by considering the vehicle’s acceleration derivative. The stability condition is given by applying the control theory. Considering some typical traffic environments, the results of theoretical analysis and numerical simulation show the extended model has a more actual acceleration of string vehicles than that of the previous models in starting process, stopping process and sudden brake. Meanwhile, the traffic jams more easily occur when the coefficient of vehicle’s acceleration derivative increases, which is presented by space-time evolution. The results confirm that the vehicle’s acceleration derivative plays an important role in the traffic jamming transition and the evolution of traffic congestion.

[Environmental health: the evolution of Colombia's current regulatory framework].

PubMed

García-Ubaque, Cesar A; García-Ubaque, Juan C; Vaca-Bohórquez, Martha L

2013-01-01

This essay presents an analysis of the evolution of environmental health management in Colombia, covering the period from the introduction of the Colombian Healthcare Code (1979) to laws 99 and 100 in 1993 and the introduction of Environmental Health Policy in Bogotá DC (2011). It proposes a conceptual model for environmental health management at three levels: proximal (physical, chemical and biological setting), intermediate (natural and cultural environment) and distal (economic, political and social structures). Relevant aspects of environmental health policy in Bogotá are analysed based on the proposed model.

Iron-sulfur mineralogy of Mars - Magmatic evolution and chemical weathering products

NASA Technical Reports Server (NTRS)

Burns, Roger G.; Fisher, Duncan S.

1990-01-01

Models are developed for the magmatic evolution and the oxidative weathering of sulfide minerals on Mars, based on petrogenetic associations among komatiitic rock types, Viking geochemical data, SNC meteorites, and terrestrial Fi-Ni deposits. The weathering model was tested by exposing komatiitic pyrrhotites and olivines to sulfuric acid solutions, with or without dissolved ferric iron, and identifying the reaction products by Moessbauer spectroscopy. The results suggest that, on Mars, acidic groundwater has induced oxidative weathering of pyrrhotite, yielding FeS2 and then FeOOH.

Predation's role in life-history evolution of a livebearing fish and a test of the Trexler-DeAngelis model of maternal provisioning.

PubMed

Riesch, Rüdiger; Martin, Ryan A; Langerhans, R Brian

2013-01-01

Populations experiencing consistent differences in predation risk and resource availability are expected to follow divergent evolutionary trajectories. For example, live-history theory makes specific predictions for how predation should drive life-history evolution, and according to the Trexler-DeAngelis model for the evolution of matrotrophy, postfertilization maternal provisioning is most likely to evolve in environments with consistent, high levels of resource availability. Using the model system of Bahamas mosquitofish (Gambusia hubbsi) inhabiting blue holes with and without the piscivorous bigmouth sleeper (Gobiomorus dormitor), we provide some of the strongest tests of these predictions to date, as resource availability does not covary with predation regime in this system, and we examine numerous (14) isolated natural populations. We found clear evidence for the expected life-history divergence between predation regimes and empirical support of the Trexler-DeAngelis model. Moreover, based on molecular and lab-rearing data, our study offers strong evidence for convergent evolution of similar life histories in similar predation regimes, largely matching previous phenotypic patterns observed in other poeciliid lineages (Brachyrhaphis spp., Poecilia reticulata), and further supports the notion that matrotrophy is most likely to evolve in stable high-resource environments.

A Hybrid Approach to Data Assimilation for Reconstructing the Evolution of Mantle Dynamics

NASA Astrophysics Data System (ADS)

Zhou, Quan; Liu, Lijun

2017-11-01

Quantifying past mantle dynamic processes represents a major challenge in understanding the temporal evolution of the solid earth. Mantle convection modeling with data assimilation is one of the most powerful tools to investigate the dynamics of plate subduction and mantle convection. Although various data assimilation methods, both forward and inverse, have been created, these methods all have limitations in their capabilities to represent the real earth. Pure forward models tend to miss important mantle structures due to the incorrect initial condition and thus may lead to incorrect mantle evolution. In contrast, pure tomography-based models cannot effectively resolve the fine slab structure and would fail to predict important subduction-zone dynamic processes. Here we propose a hybrid data assimilation approach that combines the unique power of the sequential and adjoint algorithms, which can properly capture the detailed evolution of the downgoing slab and the tomographically constrained mantle structures, respectively. We apply this new method to reconstructing mantle dynamics below the western U.S. while considering large lateral viscosity variations. By comparing this result with those from several existing data assimilation methods, we demonstrate that the hybrid modeling approach recovers the realistic 4-D mantle dynamics the best.

A model for evolution of overlapping community networks

NASA Astrophysics Data System (ADS)

Karan, Rituraj; Biswal, Bibhu

2017-05-01

A model is proposed for the evolution of network topology in social networks with overlapping community structure. Starting from an initial community structure that is defined in terms of group affiliations, the model postulates that the subsequent growth and loss of connections is similar to the Hebbian learning and unlearning in the brain and is governed by two dominant factors: the strength and frequency of interaction between the members, and the degree of overlap between different communities. The temporal evolution from an initial community structure to the current network topology can be described based on these two parameters. It is possible to quantify the growth occurred so far and predict the final stationary state to which the network is likely to evolve. Applications in epidemiology or the spread of email virus in a computer network as well as finding specific target nodes to control it are envisaged. While facing the challenge of collecting and analyzing large-scale time-resolved data on social groups and communities one faces the most basic questions: how do communities evolve in time? This work aims to address this issue by developing a mathematical model for the evolution of community networks and studying it through computer simulation.

A Hybrid Forward-Adjoint Data Assimilation Method for Reconstructing the Temporal Evolution of Mantle Dynamics

NASA Astrophysics Data System (ADS)

Zhou, Q.; Liu, L.

2017-12-01

Quantifying past mantle dynamic processes represents a major challenge in understanding the temporal evolution of the solid earth. Mantle convection modeling with data assimilation is one of the most powerful tools to investigate the dynamics of plate subduction and mantle convection. Although various data assimilation methods, both forward and inverse, have been created, these methods all have limitations in their capabilities to represent the real earth. Pure forward models tend to miss important mantle structures due to the incorrect initial condition and thus may lead to incorrect mantle evolution. In contrast, pure tomography-based models cannot effectively resolve the fine slab structure and would fail to predict important subduction-zone dynamic processes. Here we propose a hybrid data assimilation method that combines the unique power of the sequential and adjoint algorithms, which can properly capture the detailed evolution of the downgoing slab and the tomographically constrained mantle structures, respectively. We apply this new method to reconstructing mantle dynamics below the western U.S. while considering large lateral viscosity variations. By comparing this result with those from several existing data assimilation methods, we demonstrate that the hybrid modeling approach recovers the realistic 4-D mantle dynamics to the best.

An Examination of Interactive Whiteboard Perceptions using the Concerns-Based Adoption Model Stages of Concern and the Apple Classrooms of Tomorrow Model of Instructional Evolution

ERIC Educational Resources Information Center

Hall, Jeffrey; Chamblee, Gregory; Slough, Scott

2013-01-01

Two high school mathematics teachers who use Interactive Whiteboards (IWBs) in the classroom were interviewed annually over the course of three years regarding their perceptions of the technology. During the third year, the two teachers were asked to complete the Concerns-Based Adoption Model Stages of Concern Questionnaire. The data obtained from…

A Simple Model for the Evolution of Multi-Stranded Coronal Loops

NASA Technical Reports Server (NTRS)

Fuentes, M. C. Lopez; Klimchuk, J. A.

2010-01-01

We develop and analyze a simple cellular automaton (CA) model that reproduces the main properties of the evolution of soft X-ray coronal loops. We are motivated by the observation that these loops evolve in three distinguishable phases that suggest the development, maintainance, and decay of a self-organized system. The model is based on the idea that loops are made of elemental strands that are heated by the relaxation of magnetic stress in the form of nanoflares. In this vision, usually called "the Parker conjecture" (Parker 1988), the origin of stress is the displacement of the strand footpoints due to photospheric convective motions. Modeling the response and evolution of the plasma we obtain synthetic light curves that have the same characteristic properties (intensity, fluctuations, and timescales) as the observed cases. We study the dependence of these properties on the model parameters and find scaling laws that can be used as observational predictions of the model. We discuss the implications of our results for the interpretation of recent loop observations in different wavelengths. Subject headings: Sun: corona - Sun: flares - Sun: magnetic topology - Sun: X-rays, gamma rays

Micromechanical Fatigue Visco-Damage Model for Short Glass Fiber Reinforced Polyamide-66

NASA Astrophysics Data System (ADS)

Despringre, N.; Chemisky, Y.; Robert, G.; Meraghni, F.

This work presents a micromechanical fatigue damage model developed for short glass fiber reinforced PA66. It has been developed to predict the high cycle fatigue behavior of PA66/GF30. The model is based on an extended Mori-Tanaka method which includes coated inclusions, matrix viscoelasticity and the evolution of micro-scale damage. The developed model accounts for the nonlinear matrix viscoelasticity and the reinforcement orientation. The description of the damage processes is based on the experimental investigation of damage mechanisms previously performed through in-situ SEM tests and X-ray micro-computed tomography observations. Damage chronologies have been proposed involving three different processes: interface debonding/coating, matrix micro-cracking and fiber breakages. Their occurrence strongly depends on the microstructure and the relative humidity. Each damage mechanism is introduced through an evolution law coupled to local stress fields. The developed model is implemented using a UMAT subroutine. Its experimental validation is achieved under stress or strain controlled fatigue tests.

Shape Optimization of Rubber Bushing Using Differential Evolution Algorithm

PubMed Central

2014-01-01

The objective of this study is to design rubber bushing at desired level of stiffness characteristics in order to achieve the ride quality of the vehicle. A differential evolution algorithm based approach is developed to optimize the rubber bushing through integrating a finite element code running in batch mode to compute the objective function values for each generation. Two case studies were given to illustrate the application of proposed approach. Optimum shape parameters of 2D bushing model were determined by shape optimization using differential evolution algorithm. PMID:25276848

Predicting the emergence of H3N2 influenza viruses reveals contrasted modes of evolution of HA and NA antigens.

PubMed

Sandie, Reatha; Aris-Brosou, Stéphane

2014-01-01

Vaccine design for rapidly changing viruses is based on empirical surveillance of strains circulating in a given season to assess those that will most likely spread during the next season. The choice of which strains to include in the vaccine is critical, as an erroneous decision can lead to a nonimmunized human population that will then be at risk in the face of an epidemic or, worse, a pandemic. Here, we present the first steps toward a very general phylogenetic approach to predict the emergence of novel viruses. Our genomic model builds upon natural features of viral evolution such as selection and recombination / reassortment, and incorporates episodic bursts of evolution and or of recombination. As a proof-of-concept, we assess the performance of this model in a retrospective study, focusing: (i) on the emergence of an unexpected H3N2 influenza strain in 2007, and (ii) on a longitudinal design. Based on the analysis of hemagglutinin (HA) and neuraminidase (NA) genes, our results show a lack of predictive power in both experimental designs, but shed light on the mode of evolution of these two antigens: (i) supporting the lack of significance of recombination in the evolution of this influenza virus, and (ii) showing that HA evolves episodically while NA changes gradually.

No Future in the Past? The role of initial topography on landform evolution model predictions

NASA Astrophysics Data System (ADS)

Hancock, G. R.; Coulthard, T. J.; Lowry, J.

2014-12-01

Our understanding of earth surface processes is based on long-term empirical understandings, short-term field measurements as well as numerical models. In particular, numerical landscape evolution models (LEMs) have been developed which have the capability to capture a range of both surface (erosion and deposition), tectonics, as well as near surface or critical zone processes (i.e. pedogenesis). These models have a range of applications for understanding both surface and whole of landscape dynamics through to more applied situations such as degraded site rehabilitation. LEMs are now at the stage of development where if calibrated, can provide some level of reliability. However, these models are largely calibrated based on parameters determined from present surface conditions which are the product of much longer-term geology-soil-climate-vegetation interactions. Here, we assess the effect of the initial landscape dimensions and associated error as well as parameterisation for a potential post-mining landform design. The results demonstrate that subtle surface changes in the initial DEM as well as parameterisation can have a large impact on landscape behaviour, erosion depth and sediment discharge. For example, the predicted sediment output from LEM's is shown to be highly variable even with very subtle changes in initial surface conditions. This has two important implications in that decadal time scale field data is needed to (a) better parameterise models and (b) evaluate their predictions. We question how a LEM using parameters derived from field plots can firstly be employed to examine long-term landscape evolution. Secondly, the potential range of outcomes is examined based on estimated temporal parameter change and thirdly, the need for more detailed and rigorous field data for calibration and validation of these models is discussed.

CHEMICAL EVOLUTION LIBRARY FOR GALAXY FORMATION SIMULATION

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

Saitoh, Takayuki R., E-mail: saitoh@elsi.jp

We have developed a software library for chemical evolution simulations of galaxy formation under the simple stellar population (SSP) approximation. In this library, all of the necessary components concerning chemical evolution, such as initial mass functions, stellar lifetimes, yields from Type II and Type Ia supernovae, asymptotic giant branch stars, and neutron star mergers, are compiled from the literature. Various models are pre-implemented in this library so that users can choose their favorite combination of models. Subroutines of this library return released energy and masses of individual elements depending on a given event type. Since the redistribution manner of thesemore » quantities depends on the implementation of users’ simulation codes, this library leaves it up to the simulation code. As demonstrations, we carry out both one-zone, closed-box simulations and 3D simulations of a collapsing gas and dark matter system using this library. In these simulations, we can easily compare the impact of individual models on the chemical evolution of galaxies, just by changing the control flags and parameters of the library. Since this library only deals with the part of chemical evolution under the SSP approximation, any simulation codes that use the SSP approximation—namely, particle-base and mesh codes, as well as semianalytical models—can use it. This library is named “CELib” after the term “Chemical Evolution Library” and is made available to the community.« less

A cricket Gene Index: a genomic resource for studying neurobiology, speciation, and molecular evolution

PubMed Central

Danley, Patrick D; Mullen, Sean P; Liu, Fenglong; Nene, Vishvanath; Quackenbush, John; Shaw, Kerry L

2007-01-01

Background As the developmental costs of genomic tools decline, genomic approaches to non-model systems are becoming more feasible. Many of these systems may lack advanced genetic tools but are extremely valuable models in other biological fields. Here we report the development of expressed sequence tags (EST's) in an orthopteroid insect, a model for the study of neurobiology, speciation, and evolution. Results We report the sequencing of 14,502 EST's from clones derived from a nerve cord cDNA library, and the subsequent construction of a Gene Index from these sequences, from the Hawaiian trigonidiine cricket Laupala kohalensis. The Gene Index contains 8607 unique sequences comprised of 2575 tentative consensus (TC) sequences and 6032 singletons. For each of the unique sequences, an attempt was made to assign a provisional annotation and to categorize its function using a Gene Ontology-based classification through a sequence-based comparison to known proteins. In addition, a set of unique 70 base pair oligomers that can be used for DNA microarrays was developed. All Gene Index information is posted at the DFCI Gene Indices web page Conclusion Orthopterans are models used to understand the neurophysiological basis of complex motor patterns such as flight and stridulation. The sequences presented in the cricket Gene Index will provide neurophysiologists with many genetic tools that have been largely absent in this field. The cricket Gene Index is one of only two gene indices to be developed in an evolutionary model system. Species within the genus Laupala have speciated recently, rapidly, and extensively. Therefore, the genes identified in the cricket Gene Index can be used to study the genomics of speciation. Furthermore, this gene index represents a significant EST resources for basal insects. As such, this resource is a valuable comparative tool for the understanding of invertebrate molecular evolution. The sequences presented here will provide much needed genomic resources for three distinct but overlapping fields of inquiry: neurobiology, speciation, and molecular evolution. PMID:17459168

Stochastic modeling of mode interactions via linear parabolized stability equations

NASA Astrophysics Data System (ADS)

Ran, Wei; Zare, Armin; Hack, M. J. Philipp; Jovanovic, Mihailo

2017-11-01

Low-complexity approximations of the Navier-Stokes equations have been widely used in the analysis of wall-bounded shear flows. In particular, the parabolized stability equations (PSE) and Floquet theory have been employed to capture the evolution of primary and secondary instabilities in spatially-evolving flows. We augment linear PSE with Floquet analysis to formally treat modal interactions and the evolution of secondary instabilities in the transitional boundary layer via a linear progression. To this end, we leverage Floquet theory by incorporating the primary instability into the base flow and accounting for different harmonics in the flow state. A stochastic forcing is introduced into the resulting linear dynamics to model the effect of nonlinear interactions on the evolution of modes. We examine the H-type transition scenario to demonstrate how our approach can be used to model nonlinear effects and capture the growth of the fundamental and subharmonic modes observed in direct numerical simulations and experiments.

Evolutionary Game Theory in Growing Populations

NASA Astrophysics Data System (ADS)

Melbinger, Anna; Cremer, Jonas; Frey, Erwin

2010-10-01

Existing theoretical models of evolution focus on the relative fitness advantages of different mutants in a population while the dynamic behavior of the population size is mostly left unconsidered. We present here a generic stochastic model which combines the growth dynamics of the population and its internal evolution. Our model thereby accounts for the fact that both evolutionary and growth dynamics are based on individual reproduction events and hence are highly coupled and stochastic in nature. We exemplify our approach by studying the dilemma of cooperation in growing populations and show that genuinely stochastic events can ease the dilemma by leading to a transient but robust increase in cooperation.

Decoherence and discrete symmetries in deformed relativistic kinematics

NASA Astrophysics Data System (ADS)

Arzano, Michele

2018-01-01

Models of deformed Poincaré symmetries based on group valued momenta have long been studied as effective modifications of relativistic kinematics possibly capturing quantum gravity effects. In this contribution we show how they naturally lead to a generalized quantum time evolution of the type proposed to model fundamental decoherence for quantum systems in the presence of an evaporating black hole. The same structures which determine such generalized evolution also lead to a modification of the action of discrete symmetries and of the CPT operator. These features can in principle be used to put phenomenological constraints on models of deformed relativistic symmetries using precision measurements of neutral kaons.

Critical zone evolution and the origins of organised complexity in watersheds

NASA Astrophysics Data System (ADS)

Harman, C.; Troch, P. A.; Pelletier, J.; Rasmussen, C.; Chorover, J.

2012-04-01

The capacity of the landscape to store and transmit water is the result of a historical trajectory of landscape, soil and vegetation development, much of which is driven by hydrology itself. Progress in geomorphology and pedology has produced models of surface and sub-surface evolution in soil-mantled uplands. These dissected, denuding modeled landscapes are emblematic of the kinds of dissipative self-organized flow structures whose hydrologic organization may also be understood by low-dimensional hydrologic models. They offer an exciting starting-point for examining the mapping between the long-term controls on landscape evolution and the high-frequency hydrologic dynamics. Here we build on recent theoretical developments in geomorphology and pedology to try to understand how the relative rates of erosion, sediment transport and soil development in a landscape determine catchment storage capacity and the relative dominance of runoff process, flow pathways and storage-discharge relationships. We do so by using a combination of landscape evolution models, hydrologic process models and data from a variety of sources, including the University of Arizona Critical Zone Observatory. A challenge to linking the landscape evolution and hydrologic model representations is the vast differences in the timescales implicit in the process representations. Furthermore the vast array of processes involved makes parameterization of such models an enormous challenge. The best data-constrained geomorphic transport and soil development laws only represent hydrologic processes implicitly, through the transport and weathering rate parameters. In this work we propose to avoid this problem by identifying the relationship between the landscape and soil evolution parameters and macroscopic climate and geological controls. These macroscopic controls (such as the aridity index) have two roles: 1) they express the water and energy constraints on the long-term evolution of the landscape system, and 2) they bound the range of plausible short-term hydroclimatic regimes that may drive a particular landscape's hydrologic dynamics. To ensure that the hydrologic dynamics implicit in the evolutionary parameters are compatible with the dynamics observed in the hydrologic modeling, a set of consistency checks based on flow process dominance are developed.

Evolution of Cooperation in Adaptive Social Networks

NASA Astrophysics Data System (ADS)

Segbroeck, Sven Van; Santos, Francisco C.; Traulsen, Arne; Lenaerts, Tom; Pacheco, Jorge M.

Humans are organized in societies, a phenomenon that would never have been possible without the evolution of cooperative behavior. Several mechanisms that foster this evolution have been unraveled over the years, with population structure as a prominent promoter of cooperation. Modern networks of exchange and cooperation are, however, becoming increasingly volatile, and less and less based on long-term stable structure. Here, we address how this change of paradigm aspects the evolution of cooperation. We discuss analytical and numerical models in which individuals can break social ties and create new ones. Interactions are modeled as two-player dilemmas of cooperation. Once a link between two individuals has formed, the productivity of this link is evaluated. Links can be broken off at different rates. This individual capacity of forming new links or severing inconvenient ones can effectively change the nature of the game. We address random formation of new links and local linking rules as well as different individual capacities to maintain social interactions. We conclude by discussing how adaptive social networks can become an important step towards more realistic models of cultural dynamics.

Cultural evolution and individual development of openness and conservatism

PubMed Central

Acerbi, Alberto; Enquist, Magnus; Ghirlanda, Stefano

2009-01-01

We present a model of cultural evolution in which an individual's propensity to engage in social learning is affected by social learning itself. We assume that individuals observe cultural traits displayed by others and decide whether to copy them based on their overall preference for the displayed traits. Preferences, too, can be transmitted between individuals. Our results show that such cultural dynamics tends to produce conservative individuals, i.e., individuals who are reluctant to copy new traits. Openness to new information, however, can be maintained when individuals need significant time to acquire the cultural traits that make them effective cultural models. We show that a gradual enculturation of young individuals by many models and a larger cultural repertoire to be acquired are favorable circumstances for the long-term maintenance of openness in individuals and groups. Our results agree with data about lifetime personality change, showing that openness to new information decreases with age. Our results show that cultural remodeling of cultural transmission is a powerful force in cultural evolution, i.e., that cultural evolution can change its own dynamics. PMID:19858478

AWARE: Adaptive Software Monitoring and Dynamic Reconfiguration for Critical Infrastructure Protection

DTIC Science & Technology

2015-04-29

in which we applied these adaptation patterns to an adaptive news web server intended to tolerate extremely heavy, unexpected loads. To address...collection of existing models used as benchmarks for OO-based refactoring and an existing web -based repository called REMODD to provide users with model...invariant properties. Specifically, we developed Avida- MDE (based on the Avida digital evolution platform) to support the automatic generation of software

The scatter and evolution of the global hot gas properties of simulated galaxy cluster populations

NASA Astrophysics Data System (ADS)

Le Brun, Amandine M. C.; McCarthy, Ian G.; Schaye, Joop; Ponman, Trevor J.

2017-04-01

We use the cosmo-OverWhelmingly Large Simulation (cosmo-OWLS) suite of cosmological hydrodynamical simulations to investigate the scatter and evolution of the global hot gas properties of large simulated populations of galaxy groups and clusters. Our aim is to compare the predictions of different physical models and to explore the extent to which commonly adopted assumptions in observational analyses (e.g. self-similar evolution) are violated. We examine the relations between (true) halo mass and the X-ray temperature, X-ray luminosity, gas mass, Sunyaev-Zel'dovich (SZ) flux, the X-ray analogue of the SZ flux (YX) and the hydrostatic mass. For the most realistic models, which include active galactic nuclei (AGN) feedback, the slopes of the various mass-observable relations deviate substantially from the self-similar ones, particularly at late times and for low-mass clusters. The amplitude of the mass-temperature relation shows negative evolution with respect to the self-similar prediction (I.e. slower than the prediction) for all models, driven by an increase in non-thermal pressure support at higher redshifts. The AGN models predict strong positive evolution of the gas mass fractions at low halo masses. The SZ flux and YX show positive evolution with respect to self-similarity at low mass but negative evolution at high mass. The scatter about the relations is well approximated by log-normal distributions, with widths that depend mildly on halo mass. The scatter decreases significantly with increasing redshift. The exception is the hydrostatic mass-halo mass relation, for which the scatter increases with redshift. Finally, we discuss the relative merits of various hot gas-based mass proxies.

Evolution of female multiple mating: A quantitative model of the “sexually selected sperm” hypothesis

PubMed Central

Bocedi, Greta; Reid, Jane M

2015-01-01

Explaining the evolution and maintenance of polyandry remains a key challenge in evolutionary ecology. One appealing explanation is the sexually selected sperm (SSS) hypothesis, which proposes that polyandry evolves due to indirect selection stemming from positive genetic covariance with male fertilization efficiency, and hence with a male's success in postcopulatory competition for paternity. However, the SSS hypothesis relies on verbal analogy with “sexy-son” models explaining coevolution of female preferences for male displays, and explicit models that validate the basic SSS principle are surprisingly lacking. We developed analogous genetically explicit individual-based models describing the SSS and “sexy-son” processes. We show that the analogy between the two is only partly valid, such that the genetic correlation arising between polyandry and fertilization efficiency is generally smaller than that arising between preference and display, resulting in less reliable coevolution. Importantly, indirect selection was too weak to cause polyandry to evolve in the presence of negative direct selection. Negatively biased mutations on fertilization efficiency did not generally rescue runaway evolution of polyandry unless realized fertilization was highly skewed toward a single male, and coevolution was even weaker given random mating order effects on fertilization. Our models suggest that the SSS process is, on its own, unlikely to generally explain the evolution of polyandry. PMID:25330405

An integrative top-down and bottom-up qualitative model construction framework for exploration of biochemical systems.

PubMed

Wu, Zujian; Pang, Wei; Coghill, George M

Computational modelling of biochemical systems based on top-down and bottom-up approaches has been well studied over the last decade. In this research, after illustrating how to generate atomic components by a set of given reactants and two user pre-defined component patterns, we propose an integrative top-down and bottom-up modelling approach for stepwise qualitative exploration of interactions among reactants in biochemical systems. Evolution strategy is applied to the top-down modelling approach to compose models, and simulated annealing is employed in the bottom-up modelling approach to explore potential interactions based on models constructed from the top-down modelling process. Both the top-down and bottom-up approaches support stepwise modular addition or subtraction for the model evolution. Experimental results indicate that our modelling approach is feasible to learn the relationships among biochemical reactants qualitatively. In addition, hidden reactants of the target biochemical system can be obtained by generating complex reactants in corresponding composed models. Moreover, qualitatively learned models with inferred reactants and alternative topologies can be used for further web-lab experimental investigations by biologists of interest, which may result in a better understanding of the system.

Model-based Optimization and Feedback Control of the Current Density Profile Evolution in NSTX-U

NASA Astrophysics Data System (ADS)

Ilhan, Zeki Okan

Nuclear fusion research is a highly challenging, multidisciplinary field seeking contributions from both plasma physics and multiple engineering areas. As an application of plasma control engineering, this dissertation mainly explores methods to control the current density profile evolution within the National Spherical Torus eXperiment-Upgrade (NSTX-U), which is a substantial upgrade based on the NSTX device, which is located in Princeton Plasma Physics Laboratory (PPPL), Princeton, NJ. Active control of the toroidal current density profile is among those plasma control milestones that the NSTX-U program must achieve to realize its next-step operational goals, which are characterized by high-performance, long-pulse, MHD-stable plasma operation with neutral beam heating. Therefore, the aim of this work is to develop model-based, feedforward and feedback controllers that can enable time regulation of the current density profile in NSTX-U by actuating the total plasma current, electron density, and the powers of the individual neutral beam injectors. Motivated by the coupled, nonlinear, multivariable, distributed-parameter plasma dynamics, the first step towards control design is the development of a physics-based, control-oriented model for the current profile evolution in NSTX-U in response to non-inductive current drives and heating systems. Numerical simulations of the proposed control-oriented model show qualitative agreement with the high-fidelity physics code TRANSP. The next step is to utilize the proposed control-oriented model to design an open-loop actuator trajectory optimizer. Given a desired operating state, the optimizer produces the actuator trajectories that can steer the plasma to such state. The objective of the feedforward control design is to provide a more systematic approach to advanced scenario planning in NSTX-U since the development of such scenarios is conventionally carried out experimentally by modifying the tokamak's actuator trajectories and analyzing the resulting plasma evolution. Finally, the proposed control-oriented model is embedded in feedback control schemes based on optimal control and Model Predictive Control (MPC) approaches. Integrators are added to the standard Linear Quadratic Gaussian (LQG) and MPC formulations to provide robustness against various modeling uncertainties and external disturbances. The effectiveness of the proposed feedback controllers in regulating the current density profile in NSTX-U is demonstrated in closed-loop nonlinear simulations. Moreover, the optimal feedback control algorithm has been implemented successfully in closed-loop control simulations within TRANSP through the recently developed Expert routine. (Abstract shortened by ProQuest.).

Regional tectonic analysis of Venus equatorial highlands and comparison with Earth-based Magellan radar images

NASA Technical Reports Server (NTRS)

Williams, David R.; Wetherill, George

1993-01-01

Research on regional tectonic analysis of Venus equatorial highlands and comparison with earth-based and Magellan radar images is presented. Over the past two years, the tectonic analysis of Venus performed centered on global properties of the planet, in order to understand fundamental aspects of the dynamics of the mantle and lithosphere of Venus. These include studies pertaining to the original constitutive and thermal character of the planet, as well as the evolution of Venus through time, and the present day tectonics. Parameterized convection models of the Earth and Venus were developed. The parameterized convection code was reformulated to model Venus with an initially hydrous mantle to determine how the cold-trap could affect the evolution of the planet.

When does female multiple mating evolve to adjust inbreeding? Effects of inbreeding depression, direct costs, mating constraints, and polyandry as a threshold trait

PubMed Central

Duthie, A. Bradley; Bocedi, Greta; Reid, Jane M.

2016-01-01

Polyandry is often hypothesized to evolve to allow females to adjust the degree to which they inbreed. Multiple factors might affect such evolution, including inbreeding depression, direct costs, constraints on male availability, and the nature of polyandry as a threshold trait. Complex models are required to evaluate when evolution of polyandry to adjust inbreeding is predicted to arise. We used a genetically explicit individual‐based model to track the joint evolution of inbreeding strategy and polyandry defined as a polygenic threshold trait. Evolution of polyandry to avoid inbreeding only occurred given strong inbreeding depression, low direct costs, and severe restrictions on initial versus additional male availability. Evolution of polyandry to prefer inbreeding only occurred given zero inbreeding depression and direct costs, and given similarly severe restrictions on male availability. However, due to its threshold nature, phenotypic polyandry was frequently expressed even when strongly selected against and hence maladaptive. Further, the degree to which females adjusted inbreeding through polyandry was typically very small, and often reflected constraints on male availability rather than adaptive reproductive strategy. Evolution of polyandry solely to adjust inbreeding might consequently be highly restricted in nature, and such evolution cannot necessarily be directly inferred from observed magnitudes of inbreeding adjustment. PMID:27464756

X-Ray Probes of Cosmic Star Formation History

NASA Technical Reports Server (NTRS)

Ghosh, Pranab; White, Nicholas E.

2001-01-01

We discuss the imprints left by a cosmological evolution of the star formation rate (SFR) on the evolution of X-ray luminosities Lx of normal galaxies, using the scheme earlier proposed by us, wherein the evolution of LX of a galaxy is driven by the evolution of its X-ray binary population. As indicated in our earlier work, the profile of Lx with redshift can both serve as a diagnostic probe of the SFR profile and constrain evolutionary models for X-ray binaries. We report here the first calculation of the expected evolution of X-ray luminosities of galaxies, updating our work by using a suite of more recently developed SFR profiles that span the currently plausible range. The first Chandra deep imaging results on Lx evolution are beginning to probe the SFR profile of bright spiral galaxies; the early results are consistent with predictions based on current SFR models. Using these new SFR profiles, the resolution of the "birthrate problem" of low-mass X-ray binaries and recycled, millisecond pulsars in terms of an evolving global SFR is more complete. We discuss the possible impact of the variations in the SFR profile of individual galaxies and galaxy types.

A systemic approach for modeling biological evolution using Parallel DEVS.

PubMed

Heredia, Daniel; Sanz, Victorino; Urquia, Alfonso; Sandín, Máximo

2015-08-01

A new model for studying the evolution of living organisms is proposed in this manuscript. The proposed model is based on a non-neodarwinian systemic approach. The model is focused on considering several controversies and open discussions about modern evolutionary biology. Additionally, a simplification of the proposed model, named EvoDEVS, has been mathematically described using the Parallel DEVS formalism and implemented as a computer program using the DEVSLib Modelica library. EvoDEVS serves as an experimental platform to study different conditions and scenarios by means of computer simulations. Two preliminary case studies are presented to illustrate the behavior of the model and validate its results. EvoDEVS is freely available at http://www.euclides.dia.uned.es. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

A simulation-based analytic model of radio galaxies

NASA Astrophysics Data System (ADS)

Hardcastle, M. J.

2018-04-01

I derive and discuss a simple semi-analytical model of the evolution of powerful radio galaxies which is not based on assumptions of self-similar growth, but rather implements some insights about the dynamics and energetics of these systems derived from numerical simulations, and can be applied to arbitrary pressure/density profiles of the host environment. The model can qualitatively and quantitatively reproduce the source dynamics and synchrotron light curves derived from numerical modelling. Approximate corrections for radiative and adiabatic losses allow it to predict the evolution of radio spectral index and of inverse-Compton emission both for active and `remnant' sources after the jet has turned off. Code to implement the model is publicly available. Using a standard model with a light relativistic (electron-positron) jet, subequipartition magnetic fields, and a range of realistic group/cluster environments, I simulate populations of sources and show that the model can reproduce the range of properties of powerful radio sources as well as observed trends in the relationship between jet power and radio luminosity, and predicts their dependence on redshift and environment. I show that the distribution of source lifetimes has a significant effect on both the source length distribution and the fraction of remnant sources expected in observations, and so can in principle be constrained by observations. The remnant fraction is expected to be low even at low redshift and low observing frequency due to the rapid luminosity evolution of remnants, and to tend rapidly to zero at high redshift due to inverse-Compton losses.

Modelling morphology evolution during solidification of IPP in processing conditions

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

Pantani, R., E-mail: rpantani@unisa.it, E-mail: fedesantis@unisa.it, E-mail: vsperanza@unisa.it, E-mail: gtitomanlio@unisa.it; De Santis, F., E-mail: rpantani@unisa.it, E-mail: fedesantis@unisa.it, E-mail: vsperanza@unisa.it, E-mail: gtitomanlio@unisa.it; Speranza, V., E-mail: rpantani@unisa.it, E-mail: fedesantis@unisa.it, E-mail: vsperanza@unisa.it, E-mail: gtitomanlio@unisa.it

During polymer processing, crystallization takes place during or soon after flow. In most of cases, the flow field dramatically influences both the crystallization kinetics and the crystal morphology. On their turn, crystallinity and morphology affect product properties. Consequently, in the last decade, researchers tried to identify the main parameters determining crystallinity and morphology evolution during solidification In processing conditions. In this work, we present an approach to model flow-induced crystallization with the aim of predicting the morphology after processing. The approach is based on: interpretation of the FIC as the effect of molecular stretch on the thermodynamic crystallization temperature; modelingmore » the molecular stretch evolution by means of a model simple and easy to be implemented in polymer processing simulation codes; identification of the effect of flow on nucleation density and spherulites growth rate by means of simple experiments; determination of the condition under which fibers form instead of spherulites. Model predictions reproduce most of the features of final morphology observed in the samples after solidification.« less

The Minimum-Mass Surface Density of the Solar Nebula using the Disk Evolution Equation

NASA Technical Reports Server (NTRS)

Davis, Sanford S.

2005-01-01

The Hayashi minimum-mass power law representation of the pre-solar nebula (Hayashi 1981, Prog. Theo. Phys.70,35) is revisited using analytic solutions of the disk evolution equation. A new cumulative-planetary-mass-model (an integrated form of the surface density) is shown to predict a smoother surface density compared with methods based on direct estimates of surface density from planetary data. First, a best-fit transcendental function is applied directly to the cumulative planetary mass data with the surface density obtained by direct differentiation. Next a solution to the time-dependent disk evolution equation is parametrically adapted to the planetary data. The latter model indicates a decay rate of r -1/2 in the inner disk followed by a rapid decay which results in a sharper outer boundary than predicted by the minimum mass model. The model is shown to be a good approximation to the finite-size early Solar Nebula and by extension to extra solar protoplanetary disks.

Evidence of Repeated and Independent Saltational Evolution in a Peculiar Genus of Sphinx Moths (Proserpinus: Sphingidae)

PubMed Central

Rubinoff, Daniel; Le Roux, Johannes J.

2008-01-01

Background Saltational evolution in which a particular lineage undergoes relatively rapid, significant, and unparalleled change as compared with its closest relatives is rarely invoked as an alternative model to the dominant paradigm of gradualistic evolution. Identifying saltational events is an important first-step in assessing the importance of this discontinuous model in generating evolutionary novelty. We offer evidence for three independent instances of saltational evolution in a charismatic moth genus with only eight species. Methodology/Principal Findings Maximum parsimony, maximum likelihood and Bayesian search criteria offered congruent, well supported phylogenies based on 1,965 base pairs of DNA sequence using the mitochondrial gene cytochrome oxidase subunit I, and the nuclear genes elongation factor-1 alpha and wingless. Using a comparative methods approach, we examined three taxa exhibiting novelty in the form of Batesian mimicry, host plant shift, and dramatic physiological differences in light of the phylogenetic data. All three traits appear to have evolved relatively rapidly and independently in three different species of Proserpinus. Each saltational species exhibits a markedly different and discrete example of discontinuous trait evolution while remaining canalized for other typical traits shared by the rest of the genus. All three saltational taxa show insignificantly different levels of overall genetic change as compared with their congeners, implying that their divergence is targeted to particular traits and not genome-wide. Conclusions/Significance Such rapid evolution of novel traits in individual species suggests that the pace of evolution can be quick, dramatic, and isolated—even on the species level. These results may be applicable to other groups in which specific taxa have generated pronounced evolutionary novelty. Genetic mechanisms and methods for assessing such relatively rapid changes are postulated. PMID:19107205

Evidence of repeated and independent saltational evolution in a peculiar genus of sphinx moths (Proserpinus: Sphingidae).

PubMed

Rubinoff, Daniel; Le Roux, Johannes J

2008-01-01

Saltational evolution in which a particular lineage undergoes relatively rapid, significant, and unparalleled change as compared with its closest relatives is rarely invoked as an alternative model to the dominant paradigm of gradualistic evolution. Identifying saltational events is an important first-step in assessing the importance of this discontinuous model in generating evolutionary novelty. We offer evidence for three independent instances of saltational evolution in a charismatic moth genus with only eight species. Maximum parsimony, maximum likelihood and Bayesian search criteria offered congruent, well supported phylogenies based on 1,965 base pairs of DNA sequence using the mitochondrial gene cytochrome oxidase subunit I, and the nuclear genes elongation factor-1 alpha and wingless. Using a comparative methods approach, we examined three taxa exhibiting novelty in the form of Batesian mimicry, host plant shift, and dramatic physiological differences in light of the phylogenetic data. All three traits appear to have evolved relatively rapidly and independently in three different species of Proserpinus. Each saltational species exhibits a markedly different and discrete example of discontinuous trait evolution while remaining canalized for other typical traits shared by the rest of the genus. All three saltational taxa show insignificantly different levels of overall genetic change as compared with their congeners, implying that their divergence is targeted to particular traits and not genome-wide. Such rapid evolution of novel traits in individual species suggests that the pace of evolution can be quick, dramatic, and isolated--even on the species level. These results may be applicable to other groups in which specific taxa have generated pronounced evolutionary novelty. Genetic mechanisms and methods for assessing such relatively rapid changes are postulated.

Late paleozoic fusulinoidean gigantism driven by atmospheric hyperoxia.

PubMed

Payne, Jonathan L; Groves, John R; Jost, Adam B; Nguyen, Thienan; Moffitt, Sarah E; Hill, Tessa M; Skotheim, Jan M

2012-09-01

Atmospheric hyperoxia, with pO(2) in excess of 30%, has long been hypothesized to account for late Paleozoic (360-250 million years ago) gigantism in numerous higher taxa. However, this hypothesis has not been evaluated statistically because comprehensive size data have not been compiled previously at sufficient temporal resolution to permit quantitative analysis. In this study, we test the hyperoxia-gigantism hypothesis by examining the fossil record of fusulinoidean foraminifers, a dramatic example of protistan gigantism with some individuals exceeding 10 cm in length and exceeding their relatives by six orders of magnitude in biovolume. We assembled and examined comprehensive regional and global, species-level datasets containing 270 and 1823 species, respectively. A statistical model of size evolution forced by atmospheric pO(2) is conclusively favored over alternative models based on random walks or a constant tendency toward size increase. Moreover, the ratios of volume to surface area in the largest fusulinoideans are consistent in magnitude and trend with a mathematical model based on oxygen transport limitation. We further validate the hyperoxia-gigantism model through an examination of modern foraminiferal species living along a measured gradient in oxygen concentration. These findings provide the first quantitative confirmation of a direct connection between Paleozoic gigantism and atmospheric hyperoxia. © 2012 The Author(s). Evolution© 2012 The Society for the Study of Evolution.

A Stochastic Framework for Modeling the Population Dynamics of Convective Clouds

DOE PAGES

Hagos, Samson; Feng, Zhe; Plant, Robert S.; ...

2018-02-20

A stochastic prognostic framework for modeling the population dynamics of convective clouds and representing them in climate models is proposed. The framework follows the nonequilibrium statistical mechanical approach to constructing a master equation for representing the evolution of the number of convective cells of a specific size and their associated cloud-base mass flux, given a large-scale forcing. In this framework, referred to as STOchastic framework for Modeling Population dynamics of convective clouds (STOMP), the evolution of convective cell size is predicted from three key characteristics of convective cells: (i) the probability of growth, (ii) the probability of decay, and (iii)more » the cloud-base mass flux. STOMP models are constructed and evaluated against CPOL radar observations at Darwin and convection permitting model (CPM) simulations. Multiple models are constructed under various assumptions regarding these three key parameters and the realisms of these models are evaluated. It is shown that in a model where convective plumes prefer to aggregate spatially and the cloud-base mass flux is a nonlinear function of convective cell area, the mass flux manifests a recharge-discharge behavior under steady forcing. Such a model also produces observed behavior of convective cell populations and CPM simulated cloud-base mass flux variability under diurnally varying forcing. Finally, in addition to its use in developing understanding of convection processes and the controls on convective cell size distributions, this modeling framework is also designed to serve as a nonequilibrium closure formulations for spectral mass flux parameterizations.« less

A Stochastic Framework for Modeling the Population Dynamics of Convective Clouds

NASA Astrophysics Data System (ADS)

Hagos, Samson; Feng, Zhe; Plant, Robert S.; Houze, Robert A.; Xiao, Heng

2018-02-01

A stochastic prognostic framework for modeling the population dynamics of convective clouds and representing them in climate models is proposed. The framework follows the nonequilibrium statistical mechanical approach to constructing a master equation for representing the evolution of the number of convective cells of a specific size and their associated cloud-base mass flux, given a large-scale forcing. In this framework, referred to as STOchastic framework for Modeling Population dynamics of convective clouds (STOMP), the evolution of convective cell size is predicted from three key characteristics of convective cells: (i) the probability of growth, (ii) the probability of decay, and (iii) the cloud-base mass flux. STOMP models are constructed and evaluated against CPOL radar observations at Darwin and convection permitting model (CPM) simulations. Multiple models are constructed under various assumptions regarding these three key parameters and the realisms of these models are evaluated. It is shown that in a model where convective plumes prefer to aggregate spatially and the cloud-base mass flux is a nonlinear function of convective cell area, the mass flux manifests a recharge-discharge behavior under steady forcing. Such a model also produces observed behavior of convective cell populations and CPM simulated cloud-base mass flux variability under diurnally varying forcing. In addition to its use in developing understanding of convection processes and the controls on convective cell size distributions, this modeling framework is also designed to serve as a nonequilibrium closure formulations for spectral mass flux parameterizations.

A Stochastic Framework for Modeling the Population Dynamics of Convective Clouds

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

Hagos, Samson; Feng, Zhe; Plant, Robert S.

A stochastic prognostic framework for modeling the population dynamics of convective clouds and representing them in climate models is proposed. The framework follows the nonequilibrium statistical mechanical approach to constructing a master equation for representing the evolution of the number of convective cells of a specific size and their associated cloud-base mass flux, given a large-scale forcing. In this framework, referred to as STOchastic framework for Modeling Population dynamics of convective clouds (STOMP), the evolution of convective cell size is predicted from three key characteristics of convective cells: (i) the probability of growth, (ii) the probability of decay, and (iii)more » the cloud-base mass flux. STOMP models are constructed and evaluated against CPOL radar observations at Darwin and convection permitting model (CPM) simulations. Multiple models are constructed under various assumptions regarding these three key parameters and the realisms of these models are evaluated. It is shown that in a model where convective plumes prefer to aggregate spatially and the cloud-base mass flux is a nonlinear function of convective cell area, the mass flux manifests a recharge-discharge behavior under steady forcing. Such a model also produces observed behavior of convective cell populations and CPM simulated cloud-base mass flux variability under diurnally varying forcing. Finally, in addition to its use in developing understanding of convection processes and the controls on convective cell size distributions, this modeling framework is also designed to serve as a nonequilibrium closure formulations for spectral mass flux parameterizations.« less

A storm-time plasmasphere evolution study using data assimilation

NASA Astrophysics Data System (ADS)

Nikoukar, R.; Bust, G. S.; Bishop, R. L.; Coster, A. J.; Lemon, C.; Turner, D. L.; Roeder, J. L.

2017-12-01

In this work, we study the evolution of the Earth's plasmasphere during geomagnetic active periods using the Plasmasphere Data Assimilation (PDA) model. The total electron content (TEC) measurements from an extensive network of global ground-based GPS receivers as well as GPS receivers on-board Constellation Observing System for Meteorology, Ionosphere and Climate (COSMIC) satellites and Communications/Navigation Outage Forecasting System (C/NOFS) satellite are ingested into the model. Global Core Plasma model, which is an empirical plasmasphere model, is utilized as the background model. Based on the 3D-VAR optimization, the PDA assimilative model benefits from incorporation of regularization techniques to prevent non-physical altitudinal variation in density estimates due to the limited-angle observational geometry. This work focuses on the plasmapause location, plasmasphere erosion time scales and refilling rates during the main and recovery phases of geomagnetic storms as estimated from the PDA 3-dimensional global maps of electron density in the ionosphere/plasmasphere. The comparison between the PDA results with in-situ density measurements from THEMIS and Van Allen Probes, and the RCM-E first-principle model will be also presented.

Purely Dry Mergers do not Explain the Observed Evolution of Massive Early-type Galaxies since z ~ 1

NASA Astrophysics Data System (ADS)

Sonnenfeld, Alessandro; Nipoti, Carlo; Treu, Tommaso

2014-05-01

Several studies have suggested that the observed size evolution of massive early-type galaxies (ETGs) can be explained as a combination of dry mergers and progenitor bias, at least since z ~ 1. In this paper we carry out a new test of the dry-merger scenario based on recent lensing measurements of the evolution of the mass density profile of ETGs. We construct a theoretical model for the joint evolution of the size and mass density profile slope γ' driven by dry mergers occurring at rates given by cosmological simulations. Such dry-merger model predicts a strong decrease of γ' with cosmic time, inconsistent with the almost constant γ' inferred from observations in the redshift range 0 < z < 1. We then show with a simple toy model that a modest amount of cold gas in the mergers—consistent with the upper limits on recent star formation in ETGs—is sufficient to reconcile the model with measurements of γ'. By fitting for the amount of gas accreted during mergers, we find that models with dissipation are consistent with observations of the evolution in both size and density slope, if ~4% of the total final stellar mass arises from the gas accreted since z ~ 1. Purely dry merger models are ruled out at >99% CL. We thus suggest a scenario where the outer regions of massive ETGs grow by accretion of stars and dark matter, while small amounts of dissipation and nuclear star formation conspire to keep the mass density profile constant and approximately isothermal.

A level set approach for shock-induced α-γ phase transition of RDX

NASA Astrophysics Data System (ADS)

Josyula, Kartik; Rahul; De, Suvranu

2018-02-01

We present a thermodynamically consistent level sets approach based on regularization energy functional which can be directly incorporated into a Galerkin finite element framework to model interface motion. The regularization energy leads to a diffusive form of flux that is embedded within the level sets evolution equation which maintains the signed distance property of the level set function. The scheme is shown to compare well with the velocity extension method in capturing the interface position. The proposed level sets approach is employed to study the α-γphase transformation in RDX single crystal shocked along the (100) plane. Example problems in one and three dimensions are presented. We observe smooth evolution of the phase interface along the shock direction in both models. There is no diffusion of the interface during the zero level set evolution in the three dimensional model. The level sets approach is shown to capture the characteristics of the shock-induced α-γ phase transformation such as stress relaxation behind the phase interface and the finite time required for the phase transformation to complete. The regularization energy based level sets approach is efficient, robust, and easy to implement.

Opinion formation in time-varying social networks: The case of the naming game

NASA Astrophysics Data System (ADS)

Maity, Suman Kalyan; Manoj, T. Venkat; Mukherjee, Animesh

2012-09-01

We study the dynamics of the naming game as an opinion formation model on time-varying social networks. This agent-based model captures the essential features of the agreement dynamics by means of a memory-based negotiation process. Our study focuses on the impact of time-varying properties of the social network of the agents on the naming game dynamics. In particular, we perform a computational exploration of this model using simulations on top of real networks. We investigate the outcomes of the dynamics on two different types of time-varying data: (1) the networks vary on a day-to-day basis and (2) the networks vary within very short intervals of time (20 sec). In the first case, we find that networks with strong community structure hinder the system from reaching global agreement; the evolution of the naming game in these networks maintains clusters of coexisting opinions indefinitely leading to metastability. In the second case, we investigate the evolution of the naming game in perfect synchronization with the time evolution of the underlying social network shedding new light on the traditional emergent properties of the game that differ largely from what has been reported in the existing literature.

Learning and evolution in bacterial taxis: an operational amplifier circuit modeling the computational dynamics of the prokaryotic 'two component system' protein network.

PubMed

Di Paola, Vieri; Marijuán, Pedro C; Lahoz-Beltra, Rafael

2004-01-01

Adaptive behavior in unicellular organisms (i.e., bacteria) depends on highly organized networks of proteins governing purposefully the myriad of molecular processes occurring within the cellular system. For instance, bacteria are able to explore the environment within which they develop by utilizing the motility of their flagellar system as well as a sophisticated biochemical navigation system that samples the environmental conditions surrounding the cell, searching for nutrients or moving away from toxic substances or dangerous physical conditions. In this paper we discuss how proteins of the intervening signal transduction network could be modeled as artificial neurons, simulating the dynamical aspects of the bacterial taxis. The model is based on the assumption that, in some important aspects, proteins can be considered as processing elements or McCulloch-Pitts artificial neurons that transfer and process information from the bacterium's membrane surface to the flagellar motor. This simulation of bacterial taxis has been carried out on a hardware realization of a McCulloch-Pitts artificial neuron using an operational amplifier. Based on the behavior of the operational amplifier we produce a model of the interaction between CheY and FliM, elements of the prokaryotic two component system controlling chemotaxis, as well as a simulation of learning and evolution processes in bacterial taxis. On the one side, our simulation results indicate that, computationally, these protein 'switches' are similar to McCulloch-Pitts artificial neurons, suggesting a bridge between evolution and learning in dynamical systems at cellular and molecular levels and the evolutive hardware approach. On the other side, important protein 'tactilizing' properties are not tapped by the model, and this suggests further complexity steps to explore in the approach to biological molecular computing.

Inferring the photometric and size evolution of galaxies from image simulations. I. Method

NASA Astrophysics Data System (ADS)

Carassou, Sébastien; de Lapparent, Valérie; Bertin, Emmanuel; Le Borgne, Damien

2017-09-01

Context. Current constraints on models of galaxy evolution rely on morphometric catalogs extracted from multi-band photometric surveys. However, these catalogs are altered by selection effects that are difficult to model, that correlate in non trivial ways, and that can lead to contradictory predictions if not taken into account carefully. Aims: To address this issue, we have developed a new approach combining parametric Bayesian indirect likelihood (pBIL) techniques and empirical modeling with realistic image simulations that reproduce a large fraction of these selection effects. This allows us to perform a direct comparison between observed and simulated images and to infer robust constraints on model parameters. Methods: We use a semi-empirical forward model to generate a distribution of mock galaxies from a set of physical parameters. These galaxies are passed through an image simulator reproducing the instrumental characteristics of any survey and are then extracted in the same way as the observed data. The discrepancy between the simulated and observed data is quantified, and minimized with a custom sampling process based on adaptive Markov chain Monte Carlo methods. Results: Using synthetic data matching most of the properties of a Canada-France-Hawaii Telescope Legacy Survey Deep field, we demonstrate the robustness and internal consistency of our approach by inferring the parameters governing the size and luminosity functions and their evolutions for different realistic populations of galaxies. We also compare the results of our approach with those obtained from the classical spectral energy distribution fitting and photometric redshift approach. Conclusions: Our pipeline infers efficiently the luminosity and size distribution and evolution parameters with a very limited number of observables (three photometric bands). When compared to SED fitting based on the same set of observables, our method yields results that are more accurate and free from systematic biases.

Viral genetic variation accounts for a third of variability in HIV-1 set-point viral load in Europe.

PubMed

Blanquart, François; Wymant, Chris; Cornelissen, Marion; Gall, Astrid; Bakker, Margreet; Bezemer, Daniela; Hall, Matthew; Hillebregt, Mariska; Ong, Swee Hoe; Albert, Jan; Bannert, Norbert; Fellay, Jacques; Fransen, Katrien; Gourlay, Annabelle J; Grabowski, M Kate; Gunsenheimer-Bartmeyer, Barbara; Günthard, Huldrych F; Kivelä, Pia; Kouyos, Roger; Laeyendecker, Oliver; Liitsola, Kirsi; Meyer, Laurence; Porter, Kholoud; Ristola, Matti; van Sighem, Ard; Vanham, Guido; Berkhout, Ben; Kellam, Paul; Reiss, Peter; Fraser, Christophe

2017-06-01

HIV-1 set-point viral load-the approximately stable value of viraemia in the first years of chronic infection-is a strong predictor of clinical outcome and is highly variable across infected individuals. To better understand HIV-1 pathogenesis and the evolution of the viral population, we must quantify the heritability of set-point viral load, which is the fraction of variation in this phenotype attributable to viral genetic variation. However, current estimates of heritability vary widely, from 6% to 59%. Here we used a dataset of 2,028 seroconverters infected between 1985 and 2013 from 5 European countries (Belgium, Switzerland, France, the Netherlands and the United Kingdom) and estimated the heritability of set-point viral load at 31% (CI 15%-43%). Specifically, heritability was measured using models of character evolution describing how viral load evolves on the phylogeny of whole-genome viral sequences. In contrast to previous studies, (i) we measured viral loads using standardized assays on a sample collected in a strict time window of 6 to 24 months after infection, from which the viral genome was also sequenced; (ii) we compared 2 models of character evolution, the classical "Brownian motion" model and another model ("Ornstein-Uhlenbeck") that includes stabilising selection on viral load; (iii) we controlled for covariates, including age and sex, which may inflate estimates of heritability; and (iv) we developed a goodness of fit test based on the correlation of viral loads in cherries of the phylogenetic tree, showing that both models of character evolution fit the data well. An overall heritability of 31% (CI 15%-43%) is consistent with other studies based on regression of viral load in donor-recipient pairs. Thus, about a third of variation in HIV-1 virulence is attributable to viral genetic variation.

The Effect of Velocity Correlation on the Spatial Evolution of Breakthrough Curves in Heterogeneous Media

NASA Astrophysics Data System (ADS)

Massoudieh, A.; Dentz, M.; Le Borgne, T.

2017-12-01

In heterogeneous media, the velocity distribution and the spatial correlation structure of velocity for solute particles determine the breakthrough curves and how they evolve as one moves away from the solute source. The ability to predict such evolution can help relating the spatio-statistical hydraulic properties of the media to the transport behavior and travel time distributions. While commonly used non-local transport models such as anomalous dispersion and classical continuous time random walk (CTRW) can reproduce breakthrough curve successfully by adjusting the model parameter values, they lack the ability to relate model parameters to the spatio-statistical properties of the media. This in turns limits the transferability of these models. In the research to be presented, we express concentration or flux of solutes as a distribution over their velocity. We then derive an integrodifferential equation that governs the evolution of the particle distribution over velocity at given times and locations for a particle ensemble, based on a presumed velocity correlation structure and an ergodic cross-sectional velocity distribution. This way, the spatial evolution of breakthrough curves away from the source is predicted based on cross-sectional velocity distribution and the connectivity, which is expressed by the velocity transition probability density. The transition probability is specified via a copula function that can help construct a joint distribution with a given correlation and given marginal velocities. Using this approach, we analyze the breakthrough curves depending on the velocity distribution and correlation properties. The model shows how the solute transport behavior evolves from ballistic transport at small spatial scales to Fickian dispersion at large length scales relative to the velocity correlation length.

Appraisal of jump distributions in ensemble-based sampling algorithms

NASA Astrophysics Data System (ADS)

Dejanic, Sanda; Scheidegger, Andreas; Rieckermann, Jörg; Albert, Carlo

2017-04-01

Sampling Bayesian posteriors of model parameters is often required for making model-based probabilistic predictions. For complex environmental models, standard Monte Carlo Markov Chain (MCMC) methods are often infeasible because they require too many sequential model runs. Therefore, we focused on ensemble methods that use many Markov chains in parallel, since they can be run on modern cluster architectures. Little is known about how to choose the best performing sampler, for a given application. A poor choice can lead to an inappropriate representation of posterior knowledge. We assessed two different jump moves, the stretch and the differential evolution move, underlying, respectively, the software packages EMCEE and DREAM, which are popular in different scientific communities. For the assessment, we used analytical posteriors with features as they often occur in real posteriors, namely high dimensionality, strong non-linear correlations or multimodality. For posteriors with non-linear features, standard convergence diagnostics based on sample means can be insufficient. Therefore, we resorted to an entropy-based convergence measure. We assessed the samplers by means of their convergence speed, robustness and effective sample sizes. For posteriors with strongly non-linear features, we found that the stretch move outperforms the differential evolution move, w.r.t. all three aspects.

Trait-based diversification shifts reflect differential extinction among fossil taxa.

PubMed

Wagner, Peter J; Estabrook, George F

2014-11-18

Evolution provides many cases of apparent shifts in diversification associated with particular anatomical traits. Three general models connect these patterns to anatomical evolution: (i) elevated net extinction of taxa bearing particular traits, (ii) elevated net speciation of taxa bearing particular traits, and (iii) elevated evolvability expanding the range of anatomies available to some species. Trait-based diversification shifts predict elevated hierarchical stratigraphic compatibility (i.e., primitive→derived→highly derived sequences) among pairs of anatomical characters. The three specific models further predict (i) early loss of diversity for taxa retaining primitive conditions (elevated net extinction), (ii) increased diversification among later members of a clade (elevated net speciation), and (iii) increased disparity among later members in a clade (elevated evolvability). Analyses of 319 anatomical and stratigraphic datasets for fossil species and genera show that hierarchical stratigraphic compatibility exceeds the expectations of trait-independent diversification in the vast majority of cases, which was expected if trait-dependent diversification shifts are common. Excess hierarchical stratigraphic compatibility correlates with early loss of diversity for groups retaining primitive conditions rather than delayed bursts of diversity or disparity across entire clades. Cambrian clades (predominantly trilobites) alone fit null expectations well. However, it is not clear whether evolution was unusual among Cambrian taxa or only early trilobites. At least among post-Cambrian taxa, these results implicate models, such as competition and extinction selectivity/resistance, as major drivers of trait-based diversification shifts at the species and genus levels while contradicting the predictions of elevated net speciation and elevated evolvability models.

Estimating the Effect of Competition on Trait Evolution Using Maximum Likelihood Inference.

PubMed

Drury, Jonathan; Clavel, Julien; Manceau, Marc; Morlon, Hélène

2016-07-01

Many classical ecological and evolutionary theoretical frameworks posit that competition between species is an important selective force. For example, in adaptive radiations, resource competition between evolving lineages plays a role in driving phenotypic diversification and exploration of novel ecological space. Nevertheless, current models of trait evolution fit to phylogenies and comparative data sets are not designed to incorporate the effect of competition. The most advanced models in this direction are diversity-dependent models where evolutionary rates depend on lineage diversity. However, these models still treat changes in traits in one branch as independent of the value of traits on other branches, thus ignoring the effect of species similarity on trait evolution. Here, we consider a model where the evolutionary dynamics of traits involved in interspecific interactions are influenced by species similarity in trait values and where we can specify which lineages are in sympatry. We develop a maximum likelihood based approach to fit this model to combined phylogenetic and phenotypic data. Using simulations, we demonstrate that the approach accurately estimates the simulated parameter values across a broad range of parameter space. Additionally, we develop tools for specifying the biogeographic context in which trait evolution occurs. In order to compare models, we also apply these biogeographic methods to specify which lineages interact sympatrically for two diversity-dependent models. Finally, we fit these various models to morphological data from a classical adaptive radiation (Greater Antillean Anolis lizards). We show that models that account for competition and geography perform better than other models. The matching competition model is an important new tool for studying the influence of interspecific interactions, in particular competition, on phenotypic evolution. More generally, it constitutes a step toward a better integration of interspecific interactions in many ecological and evolutionary processes. © The Author(s) 2016. Published by Oxford University Press, on behalf of the Society of Systematic Biologists. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Baculovirus phylogeny and evolution.

PubMed

Herniou, Elisabeth A; Jehle, Johannes A

2007-10-01

The family Baculoviridae represents one of the largest and most diverse groups of viruses and a unique model for studying the forces driving the evolution and biodiversity of double-stranded DNA viruses with large genomes. With the advent of comparative genomics, the phylogenetic relationships of baculoviruses have been put on solid bases. This, as well as improved bioinformatic approaches, has provided a detailed picture of baculovirus phylogeny and evolution. According to the present knowledge, baculoviruses can be classified into at least four evolutionary lineages: the most ancestral dipteran nucleopolyhedroviruses, the hymenopteran nucleopolyhedroviruses and the lepidopteran nucleopolyhedroviruses and granuloviruses. Despite the growing understanding of baculovirus phylogeny and macro-evolution, our knowledge of the micro-evolutionary processes within baculovirus species and virus populations is still limited. Here we present the state of the art on baculovirus phylogeny and evolution.

Testing the hypothesis on cognitive evolution of modern humans' learning ability: current status of past-climatic approaches.

NASA Astrophysics Data System (ADS)

Yoneda, Minoru; Abe-Ouchi, Ayako; Kawahata, Hodaka; Yokoyama, Yusuke; Oguchi, Takashi

2014-05-01

The impact of climate change on human evolution is important and debating topic for many years. Since 2010, we have involved in a general joint project entitled "Replacement of Neanderthal by Modern Humans: Testing Evolutional Models of Learning", which based on a theoretical prediction that the cognitive ability related to individual and social learning divide fates of ancient humans in very unstable Late Pleistocene climate. This model predicts that the human populations which experienced a series of environmental changes would have higher rate of individual learners, while detailed reconstructions of global climate change have reported fluent and drastic change based on ice cores and stalagmites. However, we want to understand the difference between anatomically modern human which survived and the other archaic extinct humans including European Neanderthals and Asian Denisovans. For this purpose the global synchronized change is not useful for understanding but the regional difference in the amplitude and impact of climate change is the information required. Hence, we invited a geophysicist busing Global Circulation Model to reconstruct the climatic distribution and temporal change in a continental scale. At the same time, some geochemists and geographers construct a database of local climate changes recorded in different proxies. At last, archaeologists and anthropologists tried to interpret the emergence and disappearance of human species in Europe and Asia on the reconstructed past climate maps using some tools, such as Eco-cultural niche model. Our project will show the regional difference in climate change and related archaeological events and its impact on the evolution of learning ability of modern humans.

Developing and exploring a theory for the lateral erosion of bedrock channels for use in landscape evolution models

NASA Astrophysics Data System (ADS)

Langston, Abigail L.; Tucker, Gregory E.

2018-01-01

Understanding how a bedrock river erodes its banks laterally is a frontier in geomorphology. Theories for the vertical incision of bedrock channels are widely implemented in the current generation of landscape evolution models. However, in general existing models do not seek to implement the lateral migration of bedrock channel walls. This is problematic, as modeling geomorphic processes such as terrace formation and hillslope-channel coupling depends on the accurate simulation of valley widening. We have developed and implemented a theory for the lateral migration of bedrock channel walls in a catchment-scale landscape evolution model. Two model formulations are presented, one representing the slow process of widening a bedrock canyon and the other representing undercutting, slumping, and rapid downstream sediment transport that occurs in softer bedrock. Model experiments were run with a range of values for bedrock erodibility and tendency towards transport- or detachment-limited behavior and varying magnitudes of sediment flux and water discharge in order to determine the role that each plays in the development of wide bedrock valleys. The results show that this simple, physics-based theory for the lateral erosion of bedrock channels produces bedrock valleys that are many times wider than the grid discretization scale. This theory for the lateral erosion of bedrock channel walls and the numerical implementation of the theory in a catchment-scale landscape evolution model is a significant first step towards understanding the factors that control the rates and spatial extent of wide bedrock valleys.

Synergistic Effects of Temperature, Oxidation and Multicracking Modes on Damage Evolution and Life Prediction of 2D Woven Ceramic-Matrix Composites under Tension-Tension Fatigue Loading

NASA Astrophysics Data System (ADS)

Longbiao, Li

2017-08-01

In this paper, the synergistic effects of temperature, oxidation and multicracking modes on damage evolution and life prediction in 2D woven ceramic-matrix composites (CMCs) have been investigated. The damage parameter of fatigue hysteresis dissipated energy and the interface shear stress were used to monitor the damage evolution inside of CMCs. Under cyclic fatigue loading, the fibers broken fraction was determined by combining the interface/fiber oxidation model, interface wear model and fibers statistical failure model at elevated temperature, based on the assumption that the fiber strength is subjected to two-parameter Weibull distribution and the load carried by broken and intact fibers satisfy the Global Load Sharing (GLS) criterion. When the broken fibers fraction approaches to the critical value, the composite fatigue fractures. The evolution of fatigue hysteresis dissipated energy, the interface shear stress and broken fibers fraction versus cycle number, and the fatigue life S-N curves of SiC/SiC at 1000, 1200 and 1300 °C in air and steam condition have been predicted. The synergistic effects of temperature, oxidation, fatigue peak stress, and multicracking modes on the evolution of interface shear stress and fatigue hysteresis dissipated energy versus cycle numbers curves have been analyzed.

Characterization of the Spatio-temporal Evolution of the Energy of Recent Tsunamis in Chile and its Connection with the Seismic Source and Geomorphological Conditions

NASA Astrophysics Data System (ADS)

Quiroz, M.; Cienfuegos, R.

2017-12-01

At present, there is good knowledge acquired by the scientific community on characterizing the evolution of tsunami energy at ocean and shelf scales. For instance, the investigations of Rabinovich (2013) and Yamazaki (2011), represent some important advances in this subject. In the present paper we rather focus on tsunami energy evolution, and ultimately its decay, in coastal areas because characteristic time scales of this process has implications for early warning, evacuation initiation, and cancelling. We address the tsunami energy evolution analysis at three different spatial scales, a global scale at the ocean basin level, in particular the Pacific Ocean basin, a regional scale comprising processes that occur at the continental shelf level, and finally a local scale comprising coastal areas or bays. These scales were selected following the motivation to understand how the response is associated with tsunami, and how the energy evolves until it is completely dissipated. Through signal processing methods, such as discrete and wavelets analysis, we analyze time series of recent tsunamigenic events in the main Chilean coastal cities. Based on this analysis, we propose a conceptual model based on the influence of geomorphological variables on the evolution and decay of tsunami energy. This model acts as a filter from the seismic source to the observed response in coastal zones. Finally, we hope to conclude with practical tools that will establish patterns of behavior and scaling of energy evolution through interconnections from seismic source variables and the geomorphological component to understand the response and predict behavior for a given site.

Asteroid and comet impacts on Mars and their influence on atmospheric mass evolution and habitability.

NASA Astrophysics Data System (ADS)

Karatekin, Özgür

2015-04-01

Impacts by asteroids and comets could have significant affects on the habitability and atmospheric evolution of terrestrial planets by removing part of its atmosphere, by delivering into it material and volatiles. Large impacts could have repeatedly destroyed the existing biosphere, but in the mean time new subsurface habitats have likely formed from impact induced hydrothermal systems. Early in its history, Mars could have a much denser atmosphere and higher surface temperatures to sustain the presence of stable liquid water or saline solution at the surface, as suggested by several studies. The environmental effects of a period of impact bombardment on terrestrial planets remain poorly constrained. In this study we revisit the atmospheric loss and delivery of volatiles on Mars between the end of the Noachian and present using numerical models. Following an impact, the quantity of escaped atmosphere, as well as impactor and target materials can be estimated using numerical simulations. Studies on the atmospheric loss and delivery due to impacts differ sometimes by orders of magnitude, mainly due to different equation of state and dynamical models used. The hydrocode simulations designed to simulate a single impact are not suitable to study the cumulative effect of impact erosion and delivery in the long term due to their extremely high computation costs. Instead, empirical approximations based on hydrocode simulations have been used to estimate atmospheric evolution. Comparison between different hydrocode results and atmospheric mass evolution upon impacts based on empirical models will be presented using revised model parameters. In addition, different delivery and lost mechanisms including volcanic outgassing and non-thermal escape, can be taken into account to study various atmospheric evolution scenarios. Our results suggest that impacts alone can hardly remove a significant amount of atmospheric mass over this period. Contribution of additional factors such as outgassing and non- thermal escape processes can not explain neither the presence of surface pressure larger than few hundreds of mbars 3.9 Gyr ago. Based on extreme case scenarios, maximum surface pressures at the end of the Noachian, could be as much as 0.25 bar or 1.9 bar, with and without CO2 storage into carbonate reservoirs, respectively.

A generative model for scientific concept hierarchies.

PubMed

Datta, Srayan; Adar, Eytan

2018-01-01

In many scientific disciplines, each new 'product' of research (method, finding, artifact, etc.) is often built upon previous findings-leading to extension and branching of scientific concepts over time. We aim to understand the evolution of scientific concepts by placing them in phylogenetic hierarchies where scientific keyphrases from a large, longitudinal academic corpora are used as a proxy of scientific concepts. These hierarchies exhibit various important properties, including power-law degree distribution, power-law component size distribution, existence of a giant component and less probability of extending an older concept. We present a generative model based on preferential attachment to simulate the graphical and temporal properties of these hierarchies which helps us understand the underlying process behind scientific concept evolution and may be useful in simulating and predicting scientific evolution.

A generative model for scientific concept hierarchies

PubMed Central

Adar, Eytan

2018-01-01

In many scientific disciplines, each new ‘product’ of research (method, finding, artifact, etc.) is often built upon previous findings–leading to extension and branching of scientific concepts over time. We aim to understand the evolution of scientific concepts by placing them in phylogenetic hierarchies where scientific keyphrases from a large, longitudinal academic corpora are used as a proxy of scientific concepts. These hierarchies exhibit various important properties, including power-law degree distribution, power-law component size distribution, existence of a giant component and less probability of extending an older concept. We present a generative model based on preferential attachment to simulate the graphical and temporal properties of these hierarchies which helps us understand the underlying process behind scientific concept evolution and may be useful in simulating and predicting scientific evolution. PMID:29474409

A multi-group firefly algorithm for numerical optimization

NASA Astrophysics Data System (ADS)

Tong, Nan; Fu, Qiang; Zhong, Caiming; Wang, Pengjun

2017-08-01

To solve the problem of premature convergence of firefly algorithm (FA), this paper analyzes the evolution mechanism of the algorithm, and proposes an improved Firefly algorithm based on modified evolution model and multi-group learning mechanism (IMGFA). A Firefly colony is divided into several subgroups with different model parameters. Within each subgroup, the optimal firefly is responsible for leading the others fireflies to implement the early global evolution, and establish the information mutual system among the fireflies. And then, each firefly achieves local search by following the brighter firefly in its neighbors. At the same time, learning mechanism among the best fireflies in various subgroups to exchange information can help the population to obtain global optimization goals more effectively. Experimental results verify the effectiveness of the proposed algorithm.

A physical model for strain accumulation in the San Francisco Bay region: Stress evolution since 1838

USGS Publications Warehouse

Pollitz, F.; Bakun, W.H.; Nyst, M.

2004-01-01

Understanding of the behavior of plate boundary zones has progressed to the point where reasonably comprehensive physical models can predict their evolution. The San Andreas fault system in the San Francisco Bay region (SFBR) is dominated by a few major faults whose behavior over about one earthquake cycle is fairly well understood. By combining the past history of large ruptures on SFBR faults with a recently proposed physical model of strain accumulation in the SFBR, we derive the evolution of regional stress from 1838 until the present. This effort depends on (1) an existing compilation of the source properties of historic and contemporary SFBR earthquakes based on documented shaking, geodetic data, and seismic data (Bakun, 1999) and (2) a few key parameters of a simple regional viscoelastic coupling model constrained by recent GPS data (Pollitz and Nyst, 2004). Although uncertainties abound in the location, magnitude, and fault geometries of historic ruptures and the physical model relies on gross simplifications, the resulting stress evolution model is sufficiently detailed to provide a useful window into the past stress history. In the framework of Coulomb failure stress, we find that virtually all M ??? 5.8 earthquakes prior to 1906 and M ??? 5.5 earthquakes after 1906 are consistent with stress triggering from previous earthquakes. These events systematically lie in zones of predicted stress concentration elevated 5-10 bars above the regional average. The SFBR is predicted to have emerged from the 1906 "shadow" in about 1980, consistent with the acceleration in regional seismicity at that time. The stress evolution model may be a reliable indicator of the most likely areas to experience M ??? 5.5 shocks in the future.

A dislocation-based crystal plasticity framework for dynamic ductile failure of single crystals

DOE PAGES

Nguyen, Thao; Luscher, D. J.; Wilkerson, J. W.

2017-08-02

We developed a framework for dislocation-based viscoplasticity and dynamic ductile failure to model high strain rate deformation and damage in single crystals. The rate-dependence of the crystal plasticity formulation is based on the physics of relativistic dislocation kinetics suited for extremely high strain rates. The damage evolution is based on the dynamics of void growth, which are governed by both micro-inertia as well as dislocation kinetics and dislocation substructure evolution. Furthermore, an averaging scheme is proposed in order to approximate the evolution of the dislocation substructure in both the macroscale as well as its spatial distribution at the microscale. Inmore » addition, a concept of a single equivalent dislocation density that effectively captures the collective influence of dislocation density on all active slip systems is proposed here. Together, these concepts and approximations enable the use of semi-analytic solutions for void growth dynamics developed in [J. Wilkerson and K. Ramesh. A dynamic void growth model governed by dislocation kinetics. J. Mech. Phys. Solids, 70:262–280, 2014.], which greatly reduce the computational overhead that would otherwise be required. The resulting homogenized framework has been implemented into a commercially available finite element package, and a validation study against a suite of direct numerical simulations was carried out.« less

Computer simulation of morphological evolution and rafting of {gamma}{prime} particles in Ni-based superalloys under applied stresses

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

Li, D.Y.; Chen, L.Q.

Mechanical properties of Ni-based superalloys are strongly affected by the morphology, distribution, and size of {gamma}{prime} precipitates in the {gamma} matrix. The main purpose of this paper is to propose a continuum field approach for modeling the morphology and rafting kinetics of coherent precipitates under applied stresses. This approach can be used to simulate the temporal evolution of arbitrary morphologies and microstructures without any a priori assumption. Recently, the authors applied this approach to the selected variant growth in Ni-Ti alloys under applied stresses using an inhomogeneous modulus approximation. For the {gamma}{prime} precipitates in Ni-based superalloys, the eigenstrain is dilatational,more » and hence the {gamma}{prime} morphological evolution can be affected by applied stresses only when the elastic modulus is inhomogeneous. In the present work, the elastic inhomogeneity was taken into account by reformulating a sharp-interface elasticity theory developed recently by Khachaturyan et al. in terms of diffuse interfaces. Although the present work is for a {gamma}{prime} {minus} {gamma} system, this model is general in a sense that it can be applied to other alloy systems containing coherent ordered intermetallic precipitates with elastic inhomogeneity.« less

Fragment-based lead generation: identification of seed fragments by a highly efficient fragment screening technology

NASA Astrophysics Data System (ADS)

Neumann, Lars; Ritscher, Allegra; Müller, Gerhard; Hafenbradl, Doris

2009-08-01

For the detection of the precise and unambiguous binding of fragments to a specific binding site on the target protein, we have developed a novel reporter displacement binding assay technology. The application of this technology for the fragment screening as well as the fragment evolution process with a specific modelling based design strategy is demonstrated for inhibitors of the protein kinase p38alpha. In a fragment screening approach seed fragments were identified which were then used to build compounds from the deep-pocket towards the hinge binding area of the protein kinase p38alpha based on a modelling approach. BIRB796 was used as a blueprint for the alignment of the fragments. The fragment evolution of these deep-pocket binding fragments towards the fully optimized inhibitor BIRB796 included the modulation of the residence time as well as the affinity. The goal of our study was to evaluate the robustness and efficiency of our novel fragment screening technology at high fragment concentrations, compare the screening data with biochemical activity data and to demonstrate the evolution of the hit fragments with fast kinetics, into slow kinetic inhibitors in an in silico approach.

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

Nguyen, Thao; Luscher, D. J.; Wilkerson, J. W.

We developed a framework for dislocation-based viscoplasticity and dynamic ductile failure to model high strain rate deformation and damage in single crystals. The rate-dependence of the crystal plasticity formulation is based on the physics of relativistic dislocation kinetics suited for extremely high strain rates. The damage evolution is based on the dynamics of void growth, which are governed by both micro-inertia as well as dislocation kinetics and dislocation substructure evolution. Furthermore, an averaging scheme is proposed in order to approximate the evolution of the dislocation substructure in both the macroscale as well as its spatial distribution at the microscale. Inmore » addition, a concept of a single equivalent dislocation density that effectively captures the collective influence of dislocation density on all active slip systems is proposed here. Together, these concepts and approximations enable the use of semi-analytic solutions for void growth dynamics developed in [J. Wilkerson and K. Ramesh. A dynamic void growth model governed by dislocation kinetics. J. Mech. Phys. Solids, 70:262–280, 2014.], which greatly reduce the computational overhead that would otherwise be required. The resulting homogenized framework has been implemented into a commercially available finite element package, and a validation study against a suite of direct numerical simulations was carried out.« less

NUMERICAL MODELING OF THE COAGULATION AND POROSITY EVOLUTION OF DUST AGGREGATES

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

Okuzumi, Satoshi; Sakagami, Masa-aki; Tanaka, Hidekazu, E-mail: satoshi.okuzumi@ax2.ecs.kyoto-u.ac.j

2009-12-20

Porosity evolution of dust aggregates is crucial in understanding dust evolution in protoplanetary disks. In this study, we present useful tools to study the coagulation and porosity evolution of dust aggregates. First, we present a new numerical method for simulating dust coagulation and porosity evolution as an extension of the conventional Smoluchowski equation. This method follows the evolution of the mean porosity for each aggregate mass simultaneously with the evolution of the mass distribution function. This method reproduces the results of previous Monte Carlo simulations with much less computational expense. Second, we propose a new collision model for porous dustmore » aggregates on the basis of our N-body experiments on aggregate collisions. As the first step, we focus on 'hit-and-stick' collisions, which involve neither compression nor fragmentation of aggregates. We first obtain empirical data on porosity changes between the classical limits of ballistic cluster-cluster and particle-cluster aggregation. Using the data, we construct a recipe for the porosity change due to general hit-and-stick collisions as well as formulae for the aerodynamical and collisional cross sections. Our collision model is thus more realistic than a previous model of Ormel et al. based on the classical aggregation limits only. Simple coagulation simulations using the extended Smoluchowski method show that our collision model explains the fractal dimensions of porous aggregates observed in a full N-body simulation and a laboratory experiment. By contrast, similar simulations using the collision model of Ormel et al. result in much less porous aggregates, meaning that this model underestimates the porosity increase upon unequal-sized collisions. Besides, we discover that aggregates at the high-mass end of the distribution can have a considerably small aerodynamical cross section per unit mass compared with aggregates of lower masses. This occurs when aggregates drift under uniform acceleration (e.g., gravity) and their collision is induced by the difference in their terminal velocities. We point out an important implication of this discovery for dust growth in protoplanetary disks.« less

Genetic algorithm dynamics on a rugged landscape

NASA Astrophysics Data System (ADS)

Bornholdt, Stefan

1998-04-01

The genetic algorithm is an optimization procedure motivated by biological evolution and is successfully applied to optimization problems in different areas. A statistical mechanics model for its dynamics is proposed based on the parent-child fitness correlation of the genetic operators, making it applicable to general fitness landscapes. It is compared to a recent model based on a maximum entropy ansatz. Finally it is applied to modeling the dynamics of a genetic algorithm on the rugged fitness landscape of the NK model.

a Predator-Prey Model Based on the Fully Parallel Cellular Automata

NASA Astrophysics Data System (ADS)

He, Mingfeng; Ruan, Hongbo; Yu, Changliang

We presented a predator-prey lattice model containing moveable wolves and sheep, which are characterized by Penna double bit strings. Sexual reproduction and child-care strategies are considered. To implement this model in an efficient way, we build a fully parallel Cellular Automata based on a new definition of the neighborhood. We show the roles played by the initial densities of the populations, the mutation rate and the linear size of the lattice in the evolution of this model.

An Improved Binary Differential Evolution Algorithm to Infer Tumor Phylogenetic Trees.

PubMed

Liang, Ying; Liao, Bo; Zhu, Wen

2017-01-01

Tumourigenesis is a mutation accumulation process, which is likely to start with a mutated founder cell. The evolutionary nature of tumor development makes phylogenetic models suitable for inferring tumor evolution through genetic variation data. Copy number variation (CNV) is the major genetic marker of the genome with more genes, disease loci, and functional elements involved. Fluorescence in situ hybridization (FISH) accurately measures multiple gene copy number of hundreds of single cells. We propose an improved binary differential evolution algorithm, BDEP, to infer tumor phylogenetic tree based on FISH platform. The topology analysis of tumor progression tree shows that the pathway of tumor subcell expansion varies greatly during different stages of tumor formation. And the classification experiment shows that tree-based features are better than data-based features in distinguishing tumor. The constructed phylogenetic trees have great performance in characterizing tumor development process, which outperforms other similar algorithms.

An Agent-Based Data Mining System for Ontology Evolution

NASA Astrophysics Data System (ADS)

Hadzic, Maja; Dillon, Darshan

We have developed an evidence-based mental health ontological model that represents mental health in multiple dimensions. The ongoing addition of new mental health knowledge requires a continual update of the Mental Health Ontology. In this paper, we describe how the ontology evolution can be realized using a multi-agent system in combination with data mining algorithms. We use the TICSA methodology to design this multi-agent system which is composed of four different types of agents: Information agent, Data Warehouse agent, Data Mining agents and Ontology agent. We use UML 2.1 sequence diagrams to model the collaborative nature of the agents and a UML 2.1 composite structure diagram to model the structure of individual agents. The Mental Heath Ontology has the potential to underpin various mental health research experiments of a collaborative nature which are greatly needed in times of increasing mental distress and illness.

A mixing evolution model for bidirectional microblog user networks

NASA Astrophysics Data System (ADS)

Yuan, Wei-Guo; Liu, Yun

2015-08-01

Microblogs have been widely used as a new form of online social networking. Based on the user profile data collected from Sina Weibo, we find that the number of microblog user bidirectional friends approximately corresponds with the lognormal distribution. We then build two microblog user networks with real bidirectional relationships, both of which have not only small-world and scale-free but also some special properties, such as double power-law degree distribution, disassortative network, hierarchical and rich-club structure. Moreover, by detecting the community structures of the two real networks, we find both of their community scales follow an exponential distribution. Based on the empirical analysis, we present a novel evolution network model with mixed connection rules, including lognormal fitness preferential and random attachment, nearest neighbor interconnected in the same community, and global random associations in different communities. The simulation results show that our model is consistent with real network in many topology features.

Mechanisms of carbon dimer formation in colliding laser-produced carbon plasmas

NASA Astrophysics Data System (ADS)

Sizyuk, Tatyana; Oliver, John; Diwakar, Prasoon K.

2017-07-01

It has been demonstrated that the hot stagnation region formed during the collision of laser-produced carbon plasmas is rich with carbon dimers which have been shown to be synthesized into large carbon macromolecules such as carbon fullerene onions and nanotubes. In this study, we developed and integrated experimental and multidimensional modeling techniques to access the temporal and spatial resolution of colliding plasma characteristics that elucidated the mechanism for early carbon dimer formation. Plume evolution imaging, monochromatic imaging, and optical emission spectroscopy of graphite-produced, carbon plasmas were performed. Experimental results were compared with the results of the 3D comprehensive modeling using our HEIGHTS simulation package. The results are explained based on a fundamental analysis of plasma evolution, colliding layer formation, stagnation, and expansion. The precise mechanisms of the plasma collision, plume propagation, and particle formation are discussed based on the experimental and modeling results.

A Monte Carlo model for 3D grain evolution during welding

NASA Astrophysics Data System (ADS)

Rodgers, Theron M.; Mitchell, John A.; Tikare, Veena

2017-09-01

Welding is one of the most wide-spread processes used in metal joining. However, there are currently no open-source software implementations for the simulation of microstructural evolution during a weld pass. Here we describe a Potts Monte Carlo based model implemented in the SPPARKS kinetic Monte Carlo computational framework. The model simulates melting, solidification and solid-state microstructural evolution of material in the fusion and heat-affected zones of a weld. The model does not simulate thermal behavior, but rather utilizes user input parameters to specify weld pool and heat-affect zone properties. Weld pool shapes are specified by Bézier curves, which allow for the specification of a wide range of pool shapes. Pool shapes can range from narrow and deep to wide and shallow representing different fluid flow conditions within the pool. Surrounding temperature gradients are calculated with the aide of a closest point projection algorithm. The model also allows simulation of pulsed power welding through time-dependent variation of the weld pool size. Example simulation results and comparisons with laboratory weld observations demonstrate microstructural variation with weld speed, pool shape, and pulsed-power.

Observation and numerical modeling of tidal dune dynamics

NASA Astrophysics Data System (ADS)

Doré, Arnaud; Bonneton, Philippe; Marieu, Vincent; Garlan, Thierry

2018-05-01

Tidal sand dune dynamics is observed for two tidal cycles in the Arcachon tidal inlet, southwest France. An array of instruments is deployed to measure bathymetric and current variations along dune profiles. Based on the measurements, dune crest horizontal and vertical displacements are quantified and show important dynamics in phase with tidal currents. We observed superimposed ripples on the dune stoss side and front, migrating and changing polarity as tidal currents reverse. A 2D RANS numerical model is used to simulate the morphodynamic evolution of a flat non-cohesive sand bed submitted to a tidal current. The model reproduces the bed evolution until a field of sand bedforms is obtained that are comparable with observed superimposed ripples in terms of geometrical dimensions and dynamics. The model is then applied to simulate the dynamics of a field of large sand dunes of similar size as the dunes observed in situ. In both cases, simulation results compare well with measurements qualitatively and quantitatively. This research allows for a better understanding of tidal sand dune and superimposed ripple morphodynamics and opens new perspectives for the use of numerical models to predict their evolution.

Habitability of super-Earth planets around other suns: models including Red Giant Branch evolution.

PubMed

von Bloh, W; Cuntz, M; Schröder, K-P; Bounama, C; Franck, S

2009-01-01

The unexpected diversity of exoplanets includes a growing number of super-Earth planets, i.e., exoplanets with masses of up to several Earth masses and a similar chemical and mineralogical composition as Earth. We present a thermal evolution model for a 10 Earth-mass planet orbiting a star like the Sun. Our model is based on the integrated system approach, which describes the photosynthetic biomass production and takes into account a variety of climatological, biogeochemical, and geodynamical processes. This allows us to identify a so-called photosynthesis-sustaining habitable zone (pHZ), as determined by the limits of biological productivity on the planetary surface. Our model considers solar evolution during the main-sequence stage and along the Red Giant Branch as described by the most recent solar model. We obtain a large set of solutions consistent with the principal possibility of life. The highest likelihood of habitability is found for "water worlds." Only mass-rich water worlds are able to realize pHZ-type habitability beyond the stellar main sequence on the Red Giant Branch.

A visual model for object detection based on active contours and level-set method.

PubMed

Satoh, Shunji

2006-09-01

A visual model for object detection is proposed. In order to make the detection ability comparable with existing technical methods for object detection, an evolution equation of neurons in the model is derived from the computational principle of active contours. The hierarchical structure of the model emerges naturally from the evolution equation. One drawback involved with initial values of active contours is alleviated by introducing and formulating convexity, which is a visual property. Numerical experiments show that the proposed model detects objects with complex topologies and that it is tolerant of noise. A visual attention model is introduced into the proposed model. Other simulations show that the visual properties of the model are consistent with the results of psychological experiments that disclose the relation between figure-ground reversal and visual attention. We also demonstrate that the model tends to perceive smaller regions as figures, which is a characteristic observed in human visual perception.

Evolving Nutritional Strategies in the Presence of Competition: A Geometric Agent-Based Model

PubMed Central

Senior, Alistair M.; Charleston, Michael A.; Lihoreau, Mathieu; Buhl, Jerome; Raubenheimer, David; Simpson, Stephen J.

2015-01-01

Access to nutrients is a key factor governing development, reproduction and ultimately fitness. Within social groups, contest-competition can fundamentally affect nutrient access, potentially leading to reproductive asymmetry among individuals. Previously, agent-based models have been combined with the Geometric Framework of nutrition to provide insight into how nutrition and social interactions affect one another. Here, we expand this modelling approach by incorporating evolutionary algorithms to explore how contest-competition over nutrient acquisition might affect the evolution of animal nutritional strategies. Specifically, we model tolerance of nutrient excesses and deficits when ingesting nutritionally imbalanced foods, which we term ‘nutritional latitude’; a higher degree of nutritional latitude constitutes a higher tolerance of nutritional excess and deficit. Our results indicate that a transition between two alternative strategies occurs at moderate to high levels of competition. When competition is low, individuals display a low level of nutritional latitude and regularly switch foods in search of an optimum. When food is scarce and contest-competition is intense, high nutritional latitude appears optimal, and individuals continue to consume an imbalanced food for longer periods before attempting to switch to an alternative. However, the relative balance of nutrients within available foods also strongly influences at what levels of competition, if any, transitions between these two strategies occur. Our models imply that competition combined with reproductive skew in social groups can play a role in the evolution of diet breadth. We discuss how the integration of agent-based, nutritional and evolutionary modelling may be applied in future studies to further understand the evolution of nutritional strategies across social and ecological contexts. PMID:25815976

Structural evolution of 2D microporous covalent triazine-based framework toward the study of high-performance supercapacitors.

PubMed

Hao, Long; Ning, Jing; Luo, Bin; Wang, Bin; Zhang, Yunbo; Tang, Zhihong; Yang, Junhe; Thomas, Arne; Zhi, Linjie

2015-01-14

A series of nitrogen-containing micropore-donimated materials, porous triazine-based frameworks (PTFs), are constructed through the structural evolution of a 2D microporous covalent triazine-based framework. The PTFs feature predictable and controllable nitrogen doping and pore structures, which serve as a model-like system to more deeply understand the heteroatom effect and micropore effect in ionic liquid-based supercapacitors. The experimental results reveal that the nitrogen doping can enhance the supercapacitor performance mainly through affecting the relative permittivity of the electrode materials. Although microspores' contribution is not as obvious as the doped nitrogen, the great performances of the micropore-dominated PTF suggest that micropore-dominated materials still have great potential in ionic liquid-based supercapacitors.

The evolution history of the extended solar neighbourhood

NASA Astrophysics Data System (ADS)

Just, Andreas; Sysoliatina, Kseniia; Koutsouridou, Ioanna

2018-04-01

Our detailed analytic local disc model (JJ-model) quantifies the interrelation between kinematic properties (e.g. velocity dispersions and asymmetric drift), spatial parameters (scale-lengths and vertical density profiles), and properties of stellar sub-populations (age and abundance distributions). We discuss a radial extension of the disc evolution model representing an inside-out growth of the thin disc with constant thickness. Based on metallicity distributions of APOGEE red clump stars we derive the AMR as function of galactrocentric distance and show that mono-abundance as well as mono-age populations are flaring. The predictions of the JJ-model are consistent with the TGAS-RAVE data, which provide a significant improvement of the kinematic data and unbiased distances for more than 250,000 stars.

A simulation method for the stability analysis of landscape scenarios by using a NetLogo application in GIS environment

NASA Astrophysics Data System (ADS)

Gobattoni, Federica; Lauro, Giuliana; Leone, Antonio; Monaco, Roberto; Pelorosso, Raffaele

2010-05-01

Landscape continually evolves under the influence of a complex and broad range of natural processes, directly or indirectly determined by land use, but also under the impact of anthropic actions of planning and territorial management. While processes such as earthquakes, landslides, and so on, are manifestations of this evolutionary process, human decisions concerning land government (cropping, urbanization etc.) may affect dramatically the landscape evolution in a complex mechanism of cause-and-effect leading to accelerated erosion phenomena, hydro-geological instability and flood events. To better understand landscape evolution and change in time, several numerical and empirical models have been developed and implemented with the aim to explore and explain such complex processes; reproducing landscape evolution through models and schematic representation of reality could be a powerful and reliable tool for natural resources planning and decision making in land management. Even understanding interactions and relations between the involved variables, predicting how the system will react to external inputs such as political, social or economic constraints, could be strongly difficult. Decision support systems could help in choosing among possible alternatives by integrating different sources of information and "What if" scenarios could be developed as possible future states of the world that represent alternative plausible conditions under different assumptions (Mahmoud M. wt al., 2009). Modelling approaches can be successfully applied to describe and assess both the natural spatial environmental variability and the anthropic impacts at different temporal and spatial scales even if they usually takes into account each aspect of the environmental system separately and without looking directly at landscape as a unique system and without understanding its intrinsic evolution mechanisms (H. Siegrist, 2002, S. Demberel, 2003, A. Brenner, 2005). GIS-based models which could be able to predict the response of the landscape working as a unique system, are expected to advance through a development of sustainable planning strategies and to evaluate the equilibrium-non equilibrium status of landscape evolution and the availability of vital resources in space and time. In this context mathematical models adapted in GIS environment may really give an heavy contribution in such a complex problem- solving, providing a real and concrete Decision System Support. An integrated GIS (Geographic Information System)-based approach was developed (G. Lauro, R. Monaco, 2008) combining an ecological graph model for the analysis of the relationship between spatial pattern and ecological flows and a mathematical model, based on a system of two nonlinear differential equations, that studies meta-stability and bifurcation phenomena. These equations are mainly based on a balance law between a logistic growth of bio-energy and its reduction due to limiting factors coming from environmental constraints. The energy exchange among them will be more or less strong depending on the degree of permeability of the barriers which can obstruct the energy passage from each "landscape unit" to the other. Through NetLogo, a cross-platform multi-agent programmable modelling environment, a completely automatic GIS-based mathematical model, based on the ecological graph and on the cited two differential equations, is presented and discussed here. A study case in Central Italy is analysed to better underline the importance of such a user friendly model in GIS environment.

LAPSUS: soil erosion - landscape evolution model

NASA Astrophysics Data System (ADS)

van Gorp, Wouter; Temme, Arnaud; Schoorl, Jeroen

2015-04-01

LAPSUS is a soil erosion - landscape evolution model which is capable of simulating landscape evolution of a gridded DEM by using multiple water, mass movement and human driven processes on multiple temporal and spatial scales. It is able to deal with a variety of human landscape interventions such as landuse management and tillage and it can model their interactions with natural processes. The complex spatially explicit feedbacks the model simulates demonstrate the importance of spatial interaction of human activity and erosion deposition patterns. In addition LAPSUS can model shallow landsliding, slope collapse, creep, solifluction, biological and frost weathering, fluvial behaviour. Furthermore, an algorithm to deal with natural depressions has been added and event-based modelling with an improved infiltration description and dust deposition has been pursued. LAPSUS has been used for case studies in many parts of the world and is continuously developing and expanding. it is now available for third-party and educational use. It has a comprehensive user interface and it is accompanied by a manual and exercises. The LAPSUS model is highly suitable to quantify and understand catchment-scale erosion processes. More information and a download link is available on www.lapsusmodel.nl.

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.

Testing the Accuracy of Data-driven MHD Simulations of Active Region Evolution and Eruption

NASA Astrophysics Data System (ADS)

Leake, J. E.; Linton, M.; Schuck, P. W.

2017-12-01

Models for the evolution of the solar coronal magnetic field are vital for understanding solar activity, yet the best measurements of the magnetic field lie at the photosphere, necessitating the recent development of coronal models which are "data-driven" at the photosphere. Using magnetohydrodynamic simulations of active region formation and our recently created validation framework we investigate the source of errors in data-driven models that use surface measurements of the magnetic field, and derived MHD quantities, to model the coronal magnetic field. The primary sources of errors in these studies are the temporal and spatial resolution of the surface measurements. We will discuss the implications of theses studies for accurately modeling the build up and release of coronal magnetic energy based on photospheric magnetic field observations.

A Team Training Model: A Regional Approach to Changing Economic Conditions. Hard Times: Communities in Transition.

ERIC Educational Resources Information Center

Butler, Lorna Michael; Coppedge, Robert O.

A guide for community leaders, extension staff, and community or rural development practitioners outlines the evolution of a regional training model for community-based problem solving in rural areas experiencing economic decline. The paper discusses the model's underlying concepts and implementation process and includes descriptions of four…

Modeling the stepping mechanism in negative lightning leaders

NASA Astrophysics Data System (ADS)

Iudin, Dmitry; Syssoev, Artem; Davydenko, Stanislav; Rakov, Vladimir

2017-04-01

It is well-known that the negative leaders develop in a step manner using a mechanism of the so-called space leaders in contrary to positive ones, which propagate continuously. Despite this fact has been known for about a hundred years till now no one had developed any plausible model explaining this asymmetry. In this study we suggest a model of the stepped development of the negative lightning leader which for the first time allows carrying out the numerical simulation of its evolution. The model is based on the probability approach and description of temporal evolution of the discharge channels. One of the key features of our model is accounting for the presence of so called space streamers/leaders which play a fundamental role in the formation of negative leader's steps. Their appearance becomes possible due to the accounting of potential influence of the space charge injected into the discharge gap by the streamer corona. The model takes into account an asymmetry of properties of negative and positive streamers which is based on well-known from numerous laboratory measurements fact that positive streamers need about twice weaker electric field to appear and propagate as compared to negative ones. An extinction of the conducting channel as a possible way of its evolution is also taken into account. This allows us to describe the leader channel's sheath formation. To verify the morphology and characteristics of the model discharge, we use the results of the high-speed video observations of natural negative stepped leaders. We can conclude that the key properties of the model and natural negative leaders are very similar.

Evaluation of the WRF-Urban Modeling System Coupled to Noah and Noah-MP Land Surface Models Over a Semiarid Urban Environment

NASA Astrophysics Data System (ADS)

Salamanca, Francisco; Zhang, Yizhou; Barlage, Michael; Chen, Fei; Mahalov, Alex; Miao, Shiguang

2018-03-01

We have augmented the existing capabilities of the integrated Weather Research and Forecasting (WRF)-urban modeling system by coupling three urban canopy models (UCMs) available in the WRF model with the new community Noah with multiparameterization options (Noah-MP) land surface model (LSM). The WRF-urban modeling system's performance has been evaluated by conducting six numerical experiments at high spatial resolution (1 km horizontal grid spacing) during a 15 day clear-sky summertime period for a semiarid urban environment. To assess the relative importance of representing urban surfaces, three different urban parameterizations are used with the Noah and Noah-MP LSMs, respectively, over the two major cities of Arizona: Phoenix and Tucson metropolitan areas. Our results demonstrate that Noah-MP reproduces somewhat better than Noah the daily evolution of surface skin temperature and near-surface air temperature (especially nighttime temperature) and wind speed. Concerning the urban areas, bulk urban parameterization overestimates nighttime 2 m air temperature compared to the single-layer and multilayer UCMs that reproduce more accurately the daily evolution of near-surface air temperature. Regarding near-surface wind speed, only the multilayer UCM was able to reproduce realistically the daily evolution of wind speed, although maximum winds were slightly overestimated, while both the single-layer and bulk urban parameterizations overestimated wind speed considerably. Based on these results, this paper demonstrates that the new community Noah-MP LSM coupled to an UCM is a promising physics-based predictive modeling tool for urban applications.

Coupling landscapes to solid-Earth deformation over the ice-age

NASA Astrophysics Data System (ADS)

Pico, T.; Mitrovica, J. X.; Ferrier, K.; Braun, J.

2016-12-01

We present initial results of a coupled ice-age sea level - landscape evolution code. Deformation of the solid Earth in response to the growth and ablation of continental ice sheets produces spatially-variable patterns of sea-level change. Recent modeling has considered the impact of sedimentation and erosion on sea level predictions across the last glacial cycle, but these studies have imposed, a-priori, a record of sediment flux and erosion, rather than computing them from a physics-based model of landscape evolution in the presence of sea-level (topography) changes. These topography changes range from 1-10 m/kyr in the near and intermediate field of the Late Pleistocene ice cover, and are thus comparable to (or exceed) tectonic rates in such regions. Our simulations aim to address the following question: how does solid-Earth deformation influence the evolution of landscapes over glacial periods? To address this issue, we couple a highly-efficient landscape evolution code, Fastscape (Braun & Willett, 2013), to a global, gravitationally-self consistent sea-level theory. Fastscape adopts standard geomorphic laws governing incision and marine deposition, and the sea-level model is based on the canonical work of Farrell & Clark (1976), with extensions to include the effects of rotation and time varying shoreline geometries (Kendall et al., 2005), and sediment erosion and deposition (Dalca et al, 2013). We will present global results and focus on a few regional case studies where deposition rates from a dataset of sedimentary cores can be used as a check on the simulations. These predictions quantify the influence of sea-level change (including that associated with sedimentation and erosion) on geomorphic drivers of landscape evolution, and in turn, the solid Earth deformation caused by these surface processes over an ice age.

The comparison of the use of holonic and agent-based methods in modelling of manufacturing systems

NASA Astrophysics Data System (ADS)

Foit, K.; Banaś, W.; Gwiazda, A.; Hryniewicz, P.

2017-08-01

The rapid evolution in the field of industrial automation and manufacturing is often called the 4th Industry Revolution. Worldwide availability of the internet access contributes to the competition between manufacturers, gives the opportunity for buying materials, parts and for creating the partnership networks, like cloud manufacturing, grid manufacturing (MGrid), virtual enterprises etc. The effect of the industry evolution is the need to search for new solutions in the field of manufacturing systems modelling and simulation. During the last decade researchers have developed the agent-based approach of modelling. This methodology have been taken from the computer science, but was adapted to the philosophy of industrial automation and robotization. The operation of the agent-based system depends on the simultaneous acting of different agents that may have different roles. On the other hand, there is the holon-based approach that uses the structures created by holons. It differs from the agent-based structure in some aspects, while the other ones are quite similar in both methodologies. The aim of this paper is to present the both methodologies and discuss the similarities and the differences. This may could help to select the optimal method of modelling, according to the considered problem and software resources.

Large-scale transportation network congestion evolution prediction using deep learning theory.

PubMed

Ma, Xiaolei; Yu, Haiyang; Wang, Yunpeng; Wang, Yinhai

2015-01-01

Understanding how congestion at one location can cause ripples throughout large-scale transportation network is vital for transportation researchers and practitioners to pinpoint traffic bottlenecks for congestion mitigation. Traditional studies rely on either mathematical equations or simulation techniques to model traffic congestion dynamics. However, most of the approaches have limitations, largely due to unrealistic assumptions and cumbersome parameter calibration process. With the development of Intelligent Transportation Systems (ITS) and Internet of Things (IoT), transportation data become more and more ubiquitous. This triggers a series of data-driven research to investigate transportation phenomena. Among them, deep learning theory is considered one of the most promising techniques to tackle tremendous high-dimensional data. This study attempts to extend deep learning theory into large-scale transportation network analysis. A deep Restricted Boltzmann Machine and Recurrent Neural Network architecture is utilized to model and predict traffic congestion evolution based on Global Positioning System (GPS) data from taxi. A numerical study in Ningbo, China is conducted to validate the effectiveness and efficiency of the proposed method. Results show that the prediction accuracy can achieve as high as 88% within less than 6 minutes when the model is implemented in a Graphic Processing Unit (GPU)-based parallel computing environment. The predicted congestion evolution patterns can be visualized temporally and spatially through a map-based platform to identify the vulnerable links for proactive congestion mitigation.

Large-Scale Transportation Network Congestion Evolution Prediction Using Deep Learning Theory

PubMed Central

Ma, Xiaolei; Yu, Haiyang; Wang, Yunpeng; Wang, Yinhai

2015-01-01

Understanding how congestion at one location can cause ripples throughout large-scale transportation network is vital for transportation researchers and practitioners to pinpoint traffic bottlenecks for congestion mitigation. Traditional studies rely on either mathematical equations or simulation techniques to model traffic congestion dynamics. However, most of the approaches have limitations, largely due to unrealistic assumptions and cumbersome parameter calibration process. With the development of Intelligent Transportation Systems (ITS) and Internet of Things (IoT), transportation data become more and more ubiquitous. This triggers a series of data-driven research to investigate transportation phenomena. Among them, deep learning theory is considered one of the most promising techniques to tackle tremendous high-dimensional data. This study attempts to extend deep learning theory into large-scale transportation network analysis. A deep Restricted Boltzmann Machine and Recurrent Neural Network architecture is utilized to model and predict traffic congestion evolution based on Global Positioning System (GPS) data from taxi. A numerical study in Ningbo, China is conducted to validate the effectiveness and efficiency of the proposed method. Results show that the prediction accuracy can achieve as high as 88% within less than 6 minutes when the model is implemented in a Graphic Processing Unit (GPU)-based parallel computing environment. The predicted congestion evolution patterns can be visualized temporally and spatially through a map-based platform to identify the vulnerable links for proactive congestion mitigation. PMID:25780910

Titan Polar Landscape Evolution

NASA Technical Reports Server (NTRS)

Moore, Jeffrey M.

2016-01-01

With the ongoing Cassini-era observations and studies of Titan it is clear that the intensity and distribution of surface processes (particularly fluvial erosion by methane and Aeolian transport) has changed through time. Currently however, alternate hypotheses substantially differ among specific scenarios with respect to the effects of atmospheric evolution, seasonal changes, and endogenic processes. We have studied the evolution of Titan's polar region through a combination of analysis of imaging, elevation data, and geomorphic mapping, spatially explicit simulations of landform evolution, and quantitative comparison of the simulated landscapes with corresponding Titan morphology. We have quantitatively evaluated alternate scenarios for the landform evolution of Titan's polar terrain. The investigations have been guided by recent geomorphic mapping and topographic characterization of the polar regions that are used to frame hypotheses of process interactions, which have been evaluated using simulation modeling. Topographic information about Titan's polar region is be based on SAR-Topography and altimetry archived on PDS, SAR-based stereo radar-grammetry, radar-sounding lake depth measurements, and superposition relationships between geomorphologic map units, which we will use to create a generalized topographic map.

Recent advances in understanding the role of nutrition in human genome evolution.

PubMed

Ye, Kaixiong; Gu, Zhenglong

2011-11-01

Dietary transitions in human history have been suggested to play important roles in the evolution of mankind. Genetic variations caused by adaptation to diet during human evolution could have important health consequences in current society. The advance of sequencing technologies and the rapid accumulation of genome information provide an unprecedented opportunity to comprehensively characterize genetic variations in human populations and unravel the genetic basis of human evolution. Series of selection detection methods, based on various theoretical models and exploiting different aspects of selection signatures, have been developed. Their applications at the species and population levels have respectively led to the identification of human specific selection events that distinguish human from nonhuman primates and local adaptation events that contribute to human diversity. Scrutiny of candidate genes has revealed paradigms of adaptations to specific nutritional components and genome-wide selection scans have verified the prevalence of diet-related selection events and provided many more candidates awaiting further investigation. Understanding the role of diet in human evolution is fundamental for the development of evidence-based, genome-informed nutritional practices in the era of personal genomics.

Process-based, forecast modeling of decadal morphological evolution of the Yangtze Estuary

NASA Astrophysics Data System (ADS)

Luan, Hualong; Ding, Pingxing; Wang, Zhengbing; Ge, Jianzhong

2017-04-01

Understanding the decadal morphodynamic evolution of estuaries and deltas and their controls is of vital importance regarding management for estuarine function and sustainable development. This work addresses this issue by applying a process-based model system (Delft3D) to hindcast and then forecast the morphodynamic evolution of the Yangtze Estuary at a decadal time scale. Forced by the river and tides, the model considers sand-mud mixture and the seasonal variations of river water discharge and sediment discharge. The morphodynamic model is validated against three periods, i.e., an accretion period (1958-1978), an erosion period (1986-1997) and a recent accretion period with human activities (2002-2010). Model results show good performance with respect to spatial erosion and deposition patterns, sediment volume changes, and hypsometry curves. The model reveals quite different behaviors for mud transport between the dry and wet seasons, which is subject to prescription of river boundary conditions and bed composition. We then define four scenarios to project evolution to 2030 under decreased river inputs and increased relative sea-level. The simulations reveal that overwhelming amount of erosion will likely occur in the inner and mouth bar area of the estuary. Particularly, the mouth zone will shift from net deposition before 2010 to net erosion by 2030, mainly because of decreasing sediment supply. Changes in water discharge have minor effects on the projected trend. Net erosion will be considerable when the sediment supply is extremely low (100 Mt yr-1) due to the abundance of erodible modern sediment in the Yangtze Estuary. Erosion within the mouth bar area may be unexpected, including the deepening of the tidal inlet at East Chongming Mudflat and the formation of a flood channel on the seaward side of Jiuduan Shoal. Overall, the model results provide valuable information for sustainable delta management under changing conditions for both the Yangtze system and other similar estuaries and deltas with diminishing sediment supplies.

Process-based morphodynamic modeling of the Yangtze Estuary at a decadal timescale: Controls on estuarine evolution and future trends

NASA Astrophysics Data System (ADS)

Luan, Hua Long; Ding, Ping Xing; Wang, Zheng Bing; Ge, Jian Zhong

2017-08-01

Understanding the decadal morphodynamic evolution of estuaries and deltas and their controls is of vital importance regarding management for estuarine function and sustainable development. This work addresses this issue by applying a process-based model system (Delft3D) to hindcast and then forecast the morphodynamic evolution of the Yangtze Estuary at a decadal timescale. Forced by the river and tides, the model considers sand-mud mixture and the variations of river water discharge and sediment discharge. The morphodynamic model is validated against three periods, i.e., an accretion period (1958-1978), an erosion period (1986-1997) and a recent accretion period with human activities (2002 - 2010). Model results show good performance with respect to spatial erosion and deposition patterns, sediment volume changes, and hypsometry curves. The model reveals quite different behaviors for mud transport between the dry and wet seasons, which is subject to the prescription of river boundary conditions and bed composition. We define six scenarios to project evolution to the year 2030 under decreased river inputs and increased relative sea level. The simulations reveal that overwhelming amount of erosion will likely occur in the inner and mouth bar area of the estuary. Particularly, the mouth zone will shift from net deposition before 2010 to net erosion by 2030, mainly because of decreasing sediment supply. Changes in water discharge have minor effects on the projected trend. Net erosion will be considerable when the sediment supply is extremely low (100 Mt yr- 1) due to the abundance of erodible modern sediment in the Yangtze Estuary. Erosion within the mouth bar area may be unexpected, including the deepening of the tidal inlet at East Chongming mudflat and the formation of a flood channel on the seaward side of Jiuduansha Shoal. Overall, the model results provide valuable information for sustainable delta management under changing conditions for both the Yangtze system and other similar estuaries and deltas with diminishing sediment supplies.

TALEN-based generation of a cynomolgus monkey disease model for human microcephaly

PubMed Central

Ke, Qiong; Li, Weiqiang; Lai, Xingqiang; Chen, Hong; Huang, Lihua; Kang, Zhuang; Li, Kai; Ren, Jie; Lin, Xiaofeng; Zheng, Haiqing; Huang, Weijun; Ma, Yunhan; Xu, Dongdong; Chen, Zheng; Song, Xinming; Lin, Xinyi; Zhuang, Min; Wang, Tao; Zhuang, Fengfeng; Xi, Jianzhong; Mao, Frank Fuxiang; Xia, Huimin; Lahn, Bruce T; Zhou, Qi; Yang, Shihua; Xiang, Andy Peng

2016-01-01

Gene editing in non-human primates may lead to valuable models for exploring the etiologies and therapeutic strategies of genetically based neurological disorders in humans. However, a monkey model of neurological disorders that closely mimics pathological and behavioral deficits in humans has not yet been successfully generated. Microcephalin 1 (MCPH1) is implicated in the evolution of the human brain, and MCPH1 mutation causes microcephaly accompanied by mental retardation. Here we generated a cynomolgus monkey (Macaca fascicularis) carrying biallelic MCPH1 mutations using transcription activator-like effector nucleases. The monkey recapitulated most of the important clinical features observed in patients, including marked reductions in head circumference, premature chromosome condensation (PCC), hypoplasia of the corpus callosum and upper limb spasticity. Moreover, overexpression of MCPH1 in mutated dermal fibroblasts rescued the PCC syndrome. This monkey model may help us elucidate the role of MCPH1 in the pathogenesis of human microcephaly and better understand the function of this protein in the evolution of primate brain size. PMID:27502025

The inevitable youthfulness of known high-redshift radio galaxies

NASA Astrophysics Data System (ADS)

Blundell, Katherine M.; Rawlings, Steve

1999-05-01

Some galaxies are very luminous in the radio part of the spectrum. These `radio galaxies' have extensive (hundreds of kiloparsecs) lobes of emission powered by plasma jets originating at a central black hole. Some radio galaxies can be seen at very high redshifts, where in principle they can serve as probes of the early evolution of the Universe. Here we show that, for any model of radio-galaxy evolution in which the luminosity decreases with time after an initial rapid increase (that is, essentially all reasonable models), all observable high-redshift radio galaxies must be seen when the lobes are less than 107 years old. This means that high-redshift radio galaxies can be used as a high-time-resolution probe of evolution in the early Universe. Moreover, this result explains many observed trends of radio-galaxy properties with redshift, without needing to invoke explanations based on cosmology or strong evolution of the surrounding intergalactic medium with cosmic time, thereby avoiding conflict with current theories of structure formation.

Modelling of anisotropic growth in biological tissues. A new approach and computational aspects.

PubMed

Menzel, A

2005-03-01

In this contribution, we develop a theoretical and computational framework for anisotropic growth phenomena. As a key idea of the proposed phenomenological approach, a fibre or rather structural tensor is introduced, which allows the description of transversely isotropic material behaviour. Based on this additional argument, anisotropic growth is modelled via appropriate evolution equations for the fibre while volumetric remodelling is realised by an evolution of the referential density. Both the strength of the fibre as well as the density follow Wolff-type laws. We however elaborate on two different approaches for the evolution of the fibre direction, namely an alignment with respect to strain or with respect to stress. One of the main benefits of the developed framework is therefore the opportunity to address the evolutions of the fibre strength and the fibre direction separately. It is then straightforward to set up appropriate integration algorithms such that the developed framework fits nicely into common, finite element schemes. Finally, several numerical examples underline the applicability of the proposed formulation.

A Balanced Mixture of Antagonistic Pressures Promotes the Evolution of Parallel Movement

NASA Astrophysics Data System (ADS)

Demšar, Jure; Štrumbelj, Erik; Lebar Bajec, Iztok

2016-12-01

A common hypothesis about the origins of collective behaviour suggests that animals might live and move in groups to increase their chances of surviving predator attacks. This hypothesis is supported by several studies that use computational models to simulate natural evolution. These studies, however, either tune an ad-hoc model to ‘reproduce’ collective behaviour, or concentrate on a single type of predation pressure, or infer the emergence of collective behaviour from an increase in prey density. In nature, prey are often targeted by multiple predator species simultaneously and this might have played a pivotal role in the evolution of collective behaviour. We expand on previous research by using an evolutionary rule-based system to simulate the evolution of prey behaviour when prey are subject to multiple simultaneous predation pressures. We analyse the evolved behaviour via prey density, polarization, and angular momentum. Our results suggest that a mixture of antagonistic external pressures that simultaneously steer prey towards grouping and dispersing might be required for prey individuals to evolve dynamic parallel movement.

Evolution of periodicity in periodical cicadas.

PubMed

Ito, Hiromu; Kakishima, Satoshi; Uehara, Takashi; Morita, Satoru; Koyama, Takuya; Sota, Teiji; Cooley, John R; Yoshimura, Jin

2015-09-14

Periodical cicadas (Magicicada spp.) in the USA are famous for their unique prime-numbered life cycles of 13 and 17 years and their nearly perfectly synchronized mass emergences. Because almost all known species of cicada are non-periodical, periodicity is assumed to be a derived state. A leading hypothesis for the evolution of periodicity in Magicicada implicates the decline in average temperature during glacial periods. During the evolution of periodicity, the determinant of maturation in ancestral cicadas is hypothesized to have switched from size dependence to time (period) dependence. The selection for the prime-numbered cycles should have taken place only after the fixation of periodicity. Here, we build an individual-based model of cicadas under conditions of climatic cooling to explore the fixation of periodicity. In our model, under cold environments, extremely long juvenile stages lead to extremely low adult densities, limiting mating opportunities and favouring the evolution of synchronized emergence. Our results indicate that these changes, which were triggered by glacial cooling, could have led to the fixation of periodicity in the non-periodical ancestors.

Rapid climate change and the rate of adaptation: insight from experimental quantitative genetics.

PubMed

Shaw, Ruth G; Etterson, Julie R

2012-09-01

Evolution proceeds unceasingly in all biological populations. It is clear that climate-driven evolution has molded plants in deep time and within extant populations. However, it is less certain whether adaptive evolution can proceed sufficiently rapidly to maintain the fitness and demographic stability of populations subjected to exceptionally rapid contemporary climate change. Here, we consider this question, drawing on current evidence on the rate of plant range shifts and the potential for an adaptive evolutionary response. We emphasize advances in understanding based on theoretical studies that model interacting evolutionary processes, and we provide an overview of quantitative genetic approaches that can parameterize these models to provide more meaningful predictions of the dynamic interplay between genetics, demography and evolution. We outline further research that can clarify both the adaptive potential of plant populations as climate continues to change and the role played by ongoing adaptation in their persistence. © 2012 The Authors. New Phytologist © 2012 New Phytologist Trust.

Individual-based models for adaptive diversification in high-dimensional phenotype spaces.

PubMed

Ispolatov, Iaroslav; Madhok, Vaibhav; Doebeli, Michael

2016-02-07

Most theories of evolutionary diversification are based on equilibrium assumptions: they are either based on optimality arguments involving static fitness landscapes, or they assume that populations first evolve to an equilibrium state before diversification occurs, as exemplified by the concept of evolutionary branching points in adaptive dynamics theory. Recent results indicate that adaptive dynamics may often not converge to equilibrium points and instead generate complicated trajectories if evolution takes place in high-dimensional phenotype spaces. Even though some analytical results on diversification in complex phenotype spaces are available, to study this problem in general we need to reconstruct individual-based models from the adaptive dynamics generating the non-equilibrium dynamics. Here we first provide a method to construct individual-based models such that they faithfully reproduce the given adaptive dynamics attractor without diversification. We then show that a propensity to diversify can be introduced by adding Gaussian competition terms that generate frequency dependence while still preserving the same adaptive dynamics. For sufficiently strong competition, the disruptive selection generated by frequency-dependence overcomes the directional evolution along the selection gradient and leads to diversification in phenotypic directions that are orthogonal to the selection gradient. Copyright © 2015 Elsevier Ltd. All rights reserved.

Void Formation during Diffusion - Two-Dimensional Approach

NASA Astrophysics Data System (ADS)

Wierzba, Bartek

2016-06-01

The final set of equations defining the interdiffusion process in solid state is presented. The model is supplemented by vacancy evolution equation. The competition between the Kirkendall shift, backstress effect and vacancy migration is considered. The proper diffusion flux based on the Nernst-Planck formula is proposed. As a result, the comparison of the experimental and calculated evolution of the void formation in the Fe-Pd diffusion couple is shown.

Classifying stages of cirrus life-cycle evolution

NASA Astrophysics Data System (ADS)

Urbanek, Benedikt; Groß, Silke; Schäfler, Andreas; Wirth, Martin

2018-04-01

Airborne lidar backscatter data is used to determine in- and out-of-cloud regions. Lidar measurements of water vapor together with model temperature fields are used to calculate relative humidity over ice (RHi). Based on temperature and RHi we identify different stages of cirrus evolution: homogeneous and heterogeneous freezing, depositional growth, ice sublimation and sedimentation. We will present our classification scheme and first applications on mid-latitude cirrus clouds.

Evolution analysis of EUV radiation from laser-produced tin plasmas based on a radiation hydrodynamics model

PubMed Central

Su, M. G.; Min, Q.; Cao, S. Q.; Sun, D. X.; Hayden, P.; O’Sullivan, G.; Dong, C. Z.

2017-01-01

One of fundamental aims of extreme ultraviolet (EUV) lithography is to maximize brightness or conversion efficiency of laser energy to radiation at specific wavelengths from laser produced plasmas (LPPs) of specific elements for matching to available multilayer optical systems. Tin LPPs have been chosen for operation at a wavelength of 13.5 nm. For an investigation of EUV radiation of laser-produced tin plasmas, it is crucial to study the related atomic processes and their evolution so as to reliably predict the optimum plasma and experimental conditions. Here, we present a simplified radiation hydrodynamic model based on the fluid dynamic equations and the radiative transfer equation to rapidly investigate the evolution of radiation properties and dynamics in laser-produced tin plasmas. The self-absorption features of EUV spectra measured at an angle of 45° to the direction of plasma expansion have been successfully simulated and explained, and the evolution of some parameters, such as the plasma temperature, ion distribution and density, expansion size and velocity, have also been evaluated. Our results should be useful for further understanding of current research on extreme ultraviolet and soft X-ray source development for applications such as lithography, metrology and biological imaging. PMID:28332621

Atomic quantum simulation of dynamical gauge fields coupled to fermionic matter: from string breaking to evolution after a quench.

PubMed

Banerjee, D; Dalmonte, M; Müller, M; Rico, E; Stebler, P; Wiese, U-J; Zoller, P

2012-10-26

Using a Fermi-Bose mixture of ultracold atoms in an optical lattice, we construct a quantum simulator for a U(1) gauge theory coupled to fermionic matter. The construction is based on quantum links which realize continuous gauge symmetry with discrete quantum variables. At low energies, quantum link models with staggered fermions emerge from a Hubbard-type model which can be quantum simulated. This allows us to investigate string breaking as well as the real-time evolution after a quench in gauge theories, which are inaccessible to classical simulation methods.

Regulation, Competition and Network Evolution in Aviation

NASA Technical Reports Server (NTRS)

Gillen, David; Morrison, William

2003-01-01

Our focus is the evolution of business strategies and network structure decisions in the commercial passenger aviation industry. The paper reviews the growth of hub-and-spoke networks as the dominant business model following deregulation in the latter part of the 20 century, followed by the emergence of value-based airlines as a global phenomenon at the end of the century. The paper highlights the link between airline business strategies and network structures, and examines the resulting competition between divergent network structure business models. In this context we discuss issues of market structure stability and the role played by competition policy.

Chemical evolution of the Magellanic Clouds

NASA Astrophysics Data System (ADS)

Barbuy, B.; de Freitas Pacheco, J. A.; Idiart, T.

We have obtained integrated spectra for 14 clusters in the Magellanic Clouds, on which the spectral indices Hβ, Mg2, Fe5270, Fe5335 were measured. Selecting indices whose behaviour depends essentially on age and metallicity (Hβ and ), together with (B-V) and (V-K) colours, we were able to determine age and metallicities for these clusters, using calibrations based on single stellar population models (Borges et al. 1995). A chemical evolution model which follows a star formation history as indicated by the field population is checked with the age and metallicity data for our sample star clusters.

The theoretical and experimental study of a material structure evolution in gigacyclic fatigue regime

NASA Astrophysics Data System (ADS)

Plekhov, Oleg; Naimark, Oleg; Narykova, Maria; Kadomtsev, Andrey; Betekhtin, Vladimir

2015-10-01

The work is devoted to the study of the metal structure evolution under gigacyclic fatigue (VHCF) regime. The study of the mechanical properties of the samples (Armco iron) with different state of life time existing was carried out on the base of the acoustic resonance method. The damage accumulation (porosity of the samples) was studied by the hydrostatic weighing method. A statistical model of damage accumulation was proposed in order to describe the damage accumulation process. The model describes the influence of the sample surface on the location of fatigue crack initiation.

Genesis and Evolution of the Skyrme Model from 1954 TO the Present

NASA Astrophysics Data System (ADS)

Sanyuk, Valery I.

Not widely known facts on the genesis of the Skyrme model are presented in a historical survey, based on Skyrme's earliest papers and on his own published remembrance. We consider the evolution of Skyrme's model description of nuclear matter from the "Mesonic Fluid" model up to its final version, known as the baryon model. We pay special tribute to some well-known ideas in contemporary particle physics which one can find in Skyrme's earlier papers, such as: Nuclear Democracy, the Solitonic Mechanism, the Nonlinear Realization of Chiral Symmetry, Topological Charges, Fermi-Bose Transmutations, etc. It is curious to note in the final version of the Skyrme model gleams of Kelvin's "Vortex Atoms" theory. In conclusion we make a brief analysis of the validity of Skyrme's conjectures in view of recent results and pinpoint some questions which still remain.

Origin of the moon - The collision hypothesis

NASA Technical Reports Server (NTRS)

Stevenson, D. J.

1987-01-01

Theoretical models of lunar origin involving one or more collisions between the earth and other large sun-orbiting bodies are examined in a critical review. Ten basic propositions of the collision hypothesis (CH) are listed; observational data on mass and angular momentum, bulk chemistry, volatile depletion, trace elements, primordial high temperatures, and orbital evolution are summarized; and the basic tenets of alternative models (fission, capture, and coformation) are reviewed. Consideration is given to the thermodynamics of large impacts, rheological and dynamical problems, numerical simulations based on the CH, disk evolution models, and the chemical implications of the CH. It is concluded that the sound arguments and evidence supporting the CH are not (yet) sufficient to rule out other hypotheses.

Basin infilling of a schematic 1D estuary using two different approaches: an aggregate diffusive type model and a processed based model.

NASA Astrophysics Data System (ADS)

Laginha Silva, Patricia; Martins, Flávio A.; Boski, Tomász; Sampath, Dissanayake M. R.

2010-05-01

Fluvial sediment transport creates great challenges for river scientists and engineers. The interaction between the fluid (water) and the solid (dispersed sediment particles) phases is crucial in morphodynamics. The process of sediment transport and the resulting morphological evolution of rivers get more complex with the exposure of the fluvial systems to the natural and variable environment (climatic, geological, ecological and social, etc.). The earlier efforts in mathematical river modelling were almost exclusively built on traditional fluvial hydraulics. The last half century has seen more and more developments and applications of mathematical models for fluvial flow, sediment transport and morphological evolution. The first attempts for a quantitative description and simulation of basin filling in geological time scales started in the late 60´s of the last century (eg. Schwarzacher, 1966; Briggs & Pollack, 1967). However, the quality of this modelling practice has emerged as a crucial issue for concern, which is widely viewed as the key that could unlock the full potential of computational fluvial hydraulics. Most of the models presently used to study fluvial basin filling are of the "diffusion type" (Flemmings and Jordan, 1989). It must be noted that this type of models do not assume that the sediment transport is performed by a physical diffusive process. Rather they are synthetic models based on mass conservation. In the "synthesist" viewpoint (Tipper, 1992; Goldenfeld & Kadanoff, 1999; Werner, 1999 in Paola, 2000) the dynamics of complex systems may occur on many levels (time or space scales) and the dynamics of higher levels may be more or less independent of that at lower levels. In this type of models the low frequency dynamics is controlled by only a few important processes and the high frequency processes are not included. In opposition to this is the "reductionist" viewpoint that states that there is no objective reason to discard high frequency processes. In this viewpoint the system is broken down into its fundamental components and processes and the model is build up by selecting the important processes regardless of its time and space scale. This viewpoint was only possible to pursue in the recent years due to improvement in system knowledge and computer power (Paola, 2000). The primary aim of this paper is to demonstrate that it is possible to simulate the evolution of the sediment river bed, traditionally studied with synthetic models, with a process-based hydrodynamic, sediment transport and morphodynamic model, solving explicitly the mass and momentum conservation equations. With this objective, a comparison between two mathematical models for alluvial rivers is made to simulate the evolution of the sediment river bed of a conceptual 1D embayment for periods in the order of a thousand years: the traditional synthetic basin infilling aggregate diffusive type model based on the diffusion equation (Paola, 2000), used in the "synthesist" viewpoint and the process-based model MOHID (Miranda et al., 2000). The simulation of the sediment river bed evolution achieved by the process-based model MOHID is very similar to those obtained by the diffusive type model, but more complete due to the complexity of the process-based model. In the MOHID results it is possible to observe a more comprehensive and realistic results because this type of model include processes that is impossible to a synthetic model to describe. At last the combined effect of tide, sea level rise and river discharges was investigated in the process based model. These effects cannot be simulated using the diffusive type model. The results demonstrate the feasibility of using process based models to perform studies in scales of 10000 years. This is an advance relative to the use of synthetic models, enabling the use of variable forcing. REFERENCES • Briggs, L.I. and Pollack, H.N., 1967. Digital model of evaporate sedimentation. Science, 155, 453-456. • Flemmings, P.B. and Jordan, T.E., 1989. A synthetic stratigraphic model of foreland basin development. J. Geophys. Res., 94, 3851-3866. • Miranda, R., Braunschweig, F., Leitão, P., Neves, R., Martins, F. & Santos A., 2000. MOHID 2000 - A coastal integrated object oriented model. Proc. Hydraulic Engineering Software VIII, Lisbon, 2000, 393-401, Ed. W.R. Blain & C.A. Brebbia, WITpress. • Paola, C., 2000. Quantitative models of sedimentary basin filing. Sedimentology, 47, 121-178. • Schwarzacher, W., 1966. Sedimentation in a subsiding basin. Nature, 5043, 1349-1350. ACKNOWLEDGMENTS This work was supported by the EVEDUS PTDC/CLI/68488/2006 Research Project

Web-based Interactive Landform Simulation Model - Grand Canyon

NASA Astrophysics Data System (ADS)

Luo, W.; Pelletier, J. D.; Duffin, K.; Ormand, C. J.; Hung, W.; Iverson, E. A.; Shernoff, D.; Zhai, X.; Chowdary, A.

2013-12-01

Earth science educators need interactive tools to engage and enable students to better understand how Earth systems work over geologic time scales. The evolution of landforms is ripe for interactive, inquiry-based learning exercises because landforms exist all around us. The Web-based Interactive Landform Simulation Model - Grand Canyon (WILSIM-GC, http://serc.carleton.edu/landform/) is a continuation and upgrade of the simple cellular automata (CA) rule-based model (WILSIM-CA, http://www.niu.edu/landform/) that can be accessed from anywhere with an Internet connection. Major improvements in WILSIM-GC include adopting a physically based model and the latest Java technology. The physically based model is incorporated to illustrate the fluvial processes involved in land-sculpting pertaining to the development and evolution of one of the most famous landforms on Earth: the Grand Canyon. It is hoped that this focus on a famous and specific landscape will attract greater student interest and provide opportunities for students to learn not only how different processes interact to form the landform we observe today, but also how models and data are used together to enhance our understanding of the processes involved. The latest development in Java technology (such as Java OpenGL for access to ubiquitous fast graphics hardware, Trusted Applet for file input and output, and multithreaded ability to take advantage of modern multi-core CPUs) are incorporated into building WILSIM-GC and active, standards-aligned curricula materials guided by educational psychology theory on science learning will be developed to accompany the model. This project is funded NSF-TUES program.

The global evolution of the primordial solar nebula

NASA Technical Reports Server (NTRS)

Ruden, S. P.; Lin, D. N. C.

1986-01-01

Complete radial, time-dependent calculations of the structure and evolution of the primordial solar nebula during the viscous diffusion stage are presented. The viscous stress is derived from analytic one-zone models of the vertical nebular structure based on detailed grain opacities. Comparisons with full numerical integrations indicate that the effective viscous alpha parameter is about 0.01. The evolution time of a minimum mass nebula is one-million yr or less. The flow pattern of fluid elements in the disk is examined and the implications the results have on the theory of the formation of the solar system are discussed.

Backward modelling of the subsidence evolution of the Colorado Basin, offshore Argentina and its relation to the evolution of the conjugate Orange Basin, offshore SW Africa

NASA Astrophysics Data System (ADS)

Dressel, Ingo; Scheck-Wenderoth, Magdalena; Cacace, Mauro

2017-10-01

In this study we focus on reconstructing the post-rift subsidence evolution of the Colorado Basin, offshore Argentina. We make use of detailed structural information about its present-day configuration of the sedimentary infill and the crystalline crust. This information is used as input in a backward modelling approach which relies on the assumption of local isostasy to reconstruct the amount of subsidence as induced by the sedimentary load through different time stages. We also attempt a quantification of the thermal effects on the subsidence as induced by the rifting, here included by following the uniform stretching model of lithosphere thinning and exponentially cooling through time. Based on the available information about the present-day geological state of the system, our modelling results indicate a rather continuous post-rift subsidence for the Colorado Basin, and give no significant evidence of any noticeable uplift phase. In a second stage, we compare the post-rift evolution of the Colorado Basin with the subsidence evolution as constrained for its conjugate SW African passive margin, the Orange Basin. Despite these two basins formed almost coevally and therefore in a similar large scale geodynamic context, their post-rift subsidence histories differ. Based on this result, we discuss causative tectonic processes likely to provide an explanation to the observed differences. We therefore conclude that it is most probable that additional tectonic components, other than the ridge-push from the spreading of the South Atlantic Ocean, are required to explain the observed differences in the subsidence of the two basins along the conjugate passive margins. Such additional tectonic components might be related to a dynamic mantle component in the form of either plume activity (Africa) or a subducting slab and the presence of an ongoing compressional stress system as revealed for different areas in South America.

Modeling the evolution of regulatory elements by simultaneous detection and alignment with phylogenetic pair HMMs.

PubMed

Majoros, William H; Ohler, Uwe

2010-12-16

The computational detection of regulatory elements in DNA is a difficult but important problem impacting our progress in understanding the complex nature of eukaryotic gene regulation. Attempts to utilize cross-species conservation for this task have been hampered both by evolutionary changes of functional sites and poor performance of general-purpose alignment programs when applied to non-coding sequence. We describe a new and flexible framework for modeling binding site evolution in multiple related genomes, based on phylogenetic pair hidden Markov models which explicitly model the gain and loss of binding sites along a phylogeny. We demonstrate the value of this framework for both the alignment of regulatory regions and the inference of precise binding-site locations within those regions. As the underlying formalism is a stochastic, generative model, it can also be used to simulate the evolution of regulatory elements. Our implementation is scalable in terms of numbers of species and sequence lengths and can produce alignments and binding-site predictions with accuracy rivaling or exceeding current systems that specialize in only alignment or only binding-site prediction. We demonstrate the validity and power of various model components on extensive simulations of realistic sequence data and apply a specific model to study Drosophila enhancers in as many as ten related genomes and in the presence of gain and loss of binding sites. Different models and modeling assumptions can be easily specified, thus providing an invaluable tool for the exploration of biological hypotheses that can drive improvements in our understanding of the mechanisms and evolution of gene regulation.

Position-based dynamic of a particle system: a configurable algorithm to describe complex behaviour of continuum material starting from swarm robotics

NASA Astrophysics Data System (ADS)

dell'Erba, Ramiro

2018-04-01

In a previous work, we considered a two-dimensional lattice of particles and calculated its time evolution by using an interaction law based on the spatial position of the particles themselves. The model reproduced the behaviour of deformable bodies both according to the standard Cauchy model and second gradient theory; this success led us to use this method in more complex cases. This work is intended as the natural evolution of the previous one in which we shall consider both energy aspects, coherence with the principle of Saint Venant and we start to manage a more general tool that can be adapted to different physical phenomena, supporting complex effects like lateral contraction, anisotropy or elastoplasticity.

A finite-strain homogenization model for viscoplastic porous single crystals: II - Applications

NASA Astrophysics Data System (ADS)

Song, Dawei; Ponte Castañeda, P.

2017-10-01

In part I of this work (Song and Ponte Castañeda, 2017a), a new homogenization-based constitutive model was developed for the finite-strain, macroscopic response of porous viscoplastic single crystals. In this second part, the new model is first used to investigate the instantaneous response and the evolution of the microstructure for porous FCC single crystals for a wide range of loading conditions. The loading orientation, Lode angle and stress triaxiality are found to have significant effects on the evolution of porosity and average void shape, which play crucial roles in determining the overall hardening/softening behavior of porous single crystals. The predictions of the model are found to be in fairly good agreement with numerical simulations available from the literature for all loadings considered, especially for low triaxiality conditions. The model is then used to investigate the strong effect of crystal anisotropy on the instantaneous response and the evolution of the microstructure for porous HCP single crystals. For uniaxial tension and compression, the overall hardening/softening behavior of porous HCP crystals is found to be controlled mostly by the evolution of void shape, and not so much by the evolution of porosity. In particular, porous HCP crystals exhibit overall hardening behavior with increasing porosity, while they exhibit overall softening behavior with decreasing porosity. This interesting behavior is consistent with corresponding results for porous FCC crystals, but is found to be more significant for porous HCP crystals with large anisotropy, such as porous ice, where the non-basal slip systems are much harder than the basal systems.

Analysis and Characterization of Damage Utilizing an Orthotropic Generalized Composite Material Model Suitable for Use in Impact Problems

NASA Technical Reports Server (NTRS)

Goldberg, Robert K.; Carney, Kelly S.; DuBois, Paul; Hoffarth, Canio; Rajan, Subramaniam; Blankenhorn, Gunther

2016-01-01

The need for accurate material models to simulate the deformation, damage and failure of polymer matrix composites under impact conditions is becoming critical as these materials are gaining increased usage in the aerospace and automotive communities. In order to address a series of issues identified by the aerospace community as being desirable to include in a next generation composite impact model, an orthotropic, macroscopic constitutive model incorporating both plasticity and damage suitable for implementation within the commercial LS-DYNA computer code is being developed. The plasticity model is based on extending the Tsai-Wu composite failure model into a strain hardening-based orthotropic plasticity model with a non-associative flow rule. The evolution of the yield surface is determined based on tabulated stress-strain curves in the various normal and shear directions and is tracked using the effective plastic strain. To compute the evolution of damage, a strain equivalent semi-coupled formulation is used in which a load in one direction results in a stiffness reduction in multiple material coordinate directions. A detailed analysis is carried out to ensure that the strain equivalence assumption is appropriate for the derived plasticity and damage formulations that are employed in the current model. Procedures to develop the appropriate input curves for the damage model are presented and the process required to develop an appropriate characterization test matrix is discussed

Analysis and Characterization of Damage Utilizing an Orthotropic Generalized Composite Material Model Suitable for Use in Impact Problems

NASA Technical Reports Server (NTRS)

Goldberg, Robert K.; Carney, Kelly S.; DuBois, Paul; Hoffarth, Canio; Rajan, Subramaniam; Blankenhorn, Gunther

2016-01-01

The need for accurate material models to simulate the deformation, damage and failure of polymer matrix composites under impact conditions is becoming critical as these materials are gaining increased usage in the aerospace and automotive communities. In order to address a series of issues identified by the aerospace community as being desirable to include in a next generation composite impact model, an orthotropic, macroscopic constitutive model incorporating both plasticity and damage suitable for implementation within the commercial LS-DYNA computer code is being developed. The plasticity model is based on extending the Tsai-Wu composite failure model into a strain hardening-based orthotropic plasticity model with a non-associative flow rule. The evolution of the yield surface is determined based on tabulated stress-strain curves in the various normal and shear directions and is tracked using the effective plastic strain. To compute the evolution of damage, a strain equivalent semi-coupled formulation is used in which a load in one direction results in a stiffness reduction in multiple material coordinate directions. A detailed analysis is carried out to ensure that the strain equivalence assumption is appropriate for the derived plasticity and damage formulations that are employed in the current model. Procedures to develop the appropriate input curves for the damage model are presented and the process required to develop an appropriate characterization test matrix is discussed.

Modeling the growth and branching of plants: A simple rod-based model

NASA Astrophysics Data System (ADS)

Faruk Senan, Nur Adila; O'Reilly, Oliver M.; Tresierras, Timothy N.

A rod-based model for plant growth and branching is developed in this paper. Specifically, Euler's theory of the elastica is modified to accommodate growth and remodeling. In addition, branching is characterized using a configuration force and evolution equations are postulated for the flexural stiffness and intrinsic curvature. The theory is illustrated with examples of multiple static equilibria of a branched plant and the remodeling and tip growth of a plant stem under gravitational loading.

Dynamic and quantitative method of analyzing service consistency evolution based on extended hierarchical finite state automata.

PubMed

Fan, Linjun; Tang, Jun; Ling, Yunxiang; Li, Benxian

2014-01-01

This paper is concerned with the dynamic evolution analysis and quantitative measurement of primary factors that cause service inconsistency in service-oriented distributed simulation applications (SODSA). Traditional methods are mostly qualitative and empirical, and they do not consider the dynamic disturbances among factors in service's evolution behaviors such as producing, publishing, calling, and maintenance. Moreover, SODSA are rapidly evolving in terms of large-scale, reusable, compositional, pervasive, and flexible features, which presents difficulties in the usage of traditional analysis methods. To resolve these problems, a novel dynamic evolution model extended hierarchical service-finite state automata (EHS-FSA) is constructed based on finite state automata (FSA), which formally depict overall changing processes of service consistency states. And also the service consistency evolution algorithms (SCEAs) based on EHS-FSA are developed to quantitatively assess these impact factors. Experimental results show that the bad reusability (17.93% on average) is the biggest influential factor, the noncomposition of atomic services (13.12%) is the second biggest one, and the service version's confusion (1.2%) is the smallest one. Compared with previous qualitative analysis, SCEAs present good effectiveness and feasibility. This research can guide the engineers of service consistency technologies toward obtaining a higher level of consistency in SODSA.

Dynamic and Quantitative Method of Analyzing Service Consistency Evolution Based on Extended Hierarchical Finite State Automata

PubMed Central

Fan, Linjun; Tang, Jun; Ling, Yunxiang; Li, Benxian

2014-01-01

This paper is concerned with the dynamic evolution analysis and quantitative measurement of primary factors that cause service inconsistency in service-oriented distributed simulation applications (SODSA). Traditional methods are mostly qualitative and empirical, and they do not consider the dynamic disturbances among factors in service's evolution behaviors such as producing, publishing, calling, and maintenance. Moreover, SODSA are rapidly evolving in terms of large-scale, reusable, compositional, pervasive, and flexible features, which presents difficulties in the usage of traditional analysis methods. To resolve these problems, a novel dynamic evolution model extended hierarchical service-finite state automata (EHS-FSA) is constructed based on finite state automata (FSA), which formally depict overall changing processes of service consistency states. And also the service consistency evolution algorithms (SCEAs) based on EHS-FSA are developed to quantitatively assess these impact factors. Experimental results show that the bad reusability (17.93% on average) is the biggest influential factor, the noncomposition of atomic services (13.12%) is the second biggest one, and the service version's confusion (1.2%) is the smallest one. Compared with previous qualitative analysis, SCEAs present good effectiveness and feasibility. This research can guide the engineers of service consistency technologies toward obtaining a higher level of consistency in SODSA. PMID:24772033

Opinion evolution in different social acquaintance networks.

PubMed

Chen, Xi; Zhang, Xiao; Wu, Zhan; Wang, Hongwei; Wang, Guohua; Li, Wei

2017-11-01

Social acquaintance networks influenced by social culture and social policy have a great impact on public opinion evolution in daily life. Based on the differences between socio-culture and social policy, three different social acquaintance networks (kinship-priority acquaintance network, independence-priority acquaintance network, and hybrid acquaintance network) incorporating heredity proportion p h and variation proportion p v are proposed in this paper. Numerical experiments are conducted to investigate network topology and different phenomena during opinion evolution, using the Deffuant model. We found that in kinship-priority acquaintance networks, similar to the Chinese traditional acquaintance networks, opinions always achieve fragmentation, resulting in the formation of multiple large clusters and many small clusters due to the fact that individuals believe more in their relatives and live in a relatively closed environment. In independence-priority acquaintance networks, similar to Western acquaintance networks, the results are similar to those in the kinship-priority acquaintance network. In hybrid acquaintance networks, similar to the Chinese modern acquaintance networks, only a few clusters are formed indicating that in modern China, opinions are more likely to reach consensus on a large scale. These results are similar to the opinion evolution phenomena in modern society, proving the rationality and applicability of network models combined with social culture and policy. We also found a threshold curve p v +2p h =2.05 in the results for the final opinion clusters and evolution time. Above the threshold curve, opinions could easily reach consensus. Based on the above experimental results, a culture-policy-driven mechanism for the opinion dynamic is worth promoting in this paper, that is, opinion dynamics can be driven by different social cultures and policies through the influence of heredity and variation in interpersonal relationship networks. This finding is of great significance for predicting opinion evolution under different acquaintance networks and formulating reasonable policies based on cultural characteristics to guide public opinion.

Opinion evolution in different social acquaintance networks

NASA Astrophysics Data System (ADS)

Chen, Xi; Zhang, Xiao; Wu, Zhan; Wang, Hongwei; Wang, Guohua; Li, Wei

2017-11-01

Social acquaintance networks influenced by social culture and social policy have a great impact on public opinion evolution in daily life. Based on the differences between socio-culture and social policy, three different social acquaintance networks (kinship-priority acquaintance network, independence-priority acquaintance network, and hybrid acquaintance network) incorporating heredity proportion ph and variation proportion pv are proposed in this paper. Numerical experiments are conducted to investigate network topology and different phenomena during opinion evolution, using the Deffuant model. We found that in kinship-priority acquaintance networks, similar to the Chinese traditional acquaintance networks, opinions always achieve fragmentation, resulting in the formation of multiple large clusters and many small clusters due to the fact that individuals believe more in their relatives and live in a relatively closed environment. In independence-priority acquaintance networks, similar to Western acquaintance networks, the results are similar to those in the kinship-priority acquaintance network. In hybrid acquaintance networks, similar to the Chinese modern acquaintance networks, only a few clusters are formed indicating that in modern China, opinions are more likely to reach consensus on a large scale. These results are similar to the opinion evolution phenomena in modern society, proving the rationality and applicability of network models combined with social culture and policy. We also found a threshold curve pv+2 ph=2.05 in the results for the final opinion clusters and evolution time. Above the threshold curve, opinions could easily reach consensus. Based on the above experimental results, a culture-policy-driven mechanism for the opinion dynamic is worth promoting in this paper, that is, opinion dynamics can be driven by different social cultures and policies through the influence of heredity and variation in interpersonal relationship networks. This finding is of great significance for predicting opinion evolution under different acquaintance networks and formulating reasonable policies based on cultural characteristics to guide public opinion.

The angular momentum of cosmological coronae and the inside-out growth of spiral galaxies

NASA Astrophysics Data System (ADS)

Pezzulli, Gabriele; Fraternali, Filippo; Binney, James

2017-05-01

Massive and diffuse haloes of hot gas (coronae) are important intermediaries between cosmology and galaxy evolution, storing mass and angular momentum acquired from the cosmic web until eventual accretion on to star-forming discs. We introduce a method to reconstruct the rotation of a galactic corona, based on its angular momentum distribution (AMD). This allows us to investigate in what conditions the angular momentum acquired from tidal torques can be transferred to star-forming discs and explain observed galaxy-scale processes, such as inside-out growth and the build-up of abundance gradients. We find that a simple model of an isothermal corona with a temperature slightly smaller than virial and a cosmologically motivated AMD is in good agreement with galaxy evolution requirements, supporting hot-mode accretion as a viable driver for the evolution of spiral galaxies in a cosmological context. We predict moderately sub-centrifugal rotation close to the disc and slow rotation close to the virial radius. Motivated by the observation that the Milky Way has a relatively hot corona (T ≃ 2 × 106 K), we also explore models with a temperature larger than virial. To be able to drive inside-out growth, these models must be significantly affected by feedback, either mechanical (ejection of low angular momentum material) or thermal (heating of the central regions). However, the agreement with galaxy evolution constraints becomes, in these cases, only marginal, suggesting that our first and simpler model may apply to a larger fraction of galaxy evolution history.

A MODELING AND SIMULATION LANGUAGE FOR BIOLOGICAL CELLS WITH COUPLED MECHANICAL AND CHEMICAL PROCESSES

PubMed Central

Somogyi, Endre; Glazier, James A.

2017-01-01

Biological cells are the prototypical example of active matter. Cells sense and respond to mechanical, chemical and electrical environmental stimuli with a range of behaviors, including dynamic changes in morphology and mechanical properties, chemical uptake and secretion, cell differentiation, proliferation, death, and migration. Modeling and simulation of such dynamic phenomena poses a number of computational challenges. A modeling language describing cellular dynamics must naturally represent complex intra and extra-cellular spatial structures and coupled mechanical, chemical and electrical processes. Domain experts will find a modeling language most useful when it is based on concepts, terms and principles native to the problem domain. A compiler must then be able to generate an executable model from this physically motivated description. Finally, an executable model must efficiently calculate the time evolution of such dynamic and inhomogeneous phenomena. We present a spatial hybrid systems modeling language, compiler and mesh-free Lagrangian based simulation engine which will enable domain experts to define models using natural, biologically motivated constructs and to simulate time evolution of coupled cellular, mechanical and chemical processes acting on a time varying number of cells and their environment. PMID:29303160

A MODELING AND SIMULATION LANGUAGE FOR BIOLOGICAL CELLS WITH COUPLED MECHANICAL AND CHEMICAL PROCESSES.

PubMed

Somogyi, Endre; Glazier, James A

2017-04-01

Biological cells are the prototypical example of active matter. Cells sense and respond to mechanical, chemical and electrical environmental stimuli with a range of behaviors, including dynamic changes in morphology and mechanical properties, chemical uptake and secretion, cell differentiation, proliferation, death, and migration. Modeling and simulation of such dynamic phenomena poses a number of computational challenges. A modeling language describing cellular dynamics must naturally represent complex intra and extra-cellular spatial structures and coupled mechanical, chemical and electrical processes. Domain experts will find a modeling language most useful when it is based on concepts, terms and principles native to the problem domain. A compiler must then be able to generate an executable model from this physically motivated description. Finally, an executable model must efficiently calculate the time evolution of such dynamic and inhomogeneous phenomena. We present a spatial hybrid systems modeling language, compiler and mesh-free Lagrangian based simulation engine which will enable domain experts to define models using natural, biologically motivated constructs and to simulate time evolution of coupled cellular, mechanical and chemical processes acting on a time varying number of cells and their environment.

A Quasiphysics Intelligent Model for a Long Range Fast Tool Servo

PubMed Central

Liu, Qiang; Zhou, Xiaoqin; Lin, Jieqiong; Xu, Pengzi; Zhu, Zhiwei

2013-01-01

Accurately modeling the dynamic behaviors of fast tool servo (FTS) is one of the key issues in the ultraprecision positioning of the cutting tool. Herein, a quasiphysics intelligent model (QPIM) integrating a linear physics model (LPM) and a radial basis function (RBF) based neural model (NM) is developed to accurately describe the dynamic behaviors of a voice coil motor (VCM) actuated long range fast tool servo (LFTS). To identify the parameters of the LPM, a novel Opposition-based Self-adaptive Replacement Differential Evolution (OSaRDE) algorithm is proposed which has been proved to have a faster convergence mechanism without compromising with the quality of solution and outperform than similar evolution algorithms taken for consideration. The modeling errors of the LPM and the QPIM are investigated by experiments. The modeling error of the LPM presents an obvious trend component which is about ±1.15% of the full span range verifying the efficiency of the proposed OSaRDE algorithm for system identification. As for the QPIM, the trend component in the residual error of LPM can be well suppressed, and the error of the QPIM maintains noise level. All the results verify the efficiency and superiority of the proposed modeling and identification approaches. PMID:24163627

A Synthesis Of Cosmic X-ray And Infrared Background

NASA Astrophysics Data System (ADS)

Shi, Yong; Helou, G.; Armus, L.; Stierwalt, S.

2012-01-01

We present a synthesis model of cosmic IR and X-ray background, with the goal to derive a complete census of cosmic evolution of star formation (SF) and black-hole (BH) growth by complementing advantages of X-ray and IR surveys to each other. By assuming that individual galaxies are experiencing both SF and BH accretion, our model decomposes the total IR LF into SF and BH components while taking into account the luminosity-dependent SED and its dispersion of the SF component, and the extinction-dependent SED of the BH component. The best-fit parameters are derived by fitting to the number counts and redshift distributions at X-ray including both hard and soft bands, and mid-IR to submm bands including IRAS, Spitzer, Herschel, SCUBA, Aztec and MAMBO. Based on the fit result, our models provide a series of predictions on galaxy evolution and black-hole growth. For evolution of infrared galaxies, the model predicts that the total infrared luminosity function is best described through evolution in both luminosity and density. For evolution of AGN populations, the model predicts that the evolution of X-ray LF also shows luminosity and density dependent, that the type-1/type-2 AGN fraction is a function of both luminosity and redshift, and that the Compton-thick AGN number density evolves strongly with redshift, contributing about 20% to the total cosmic BH growth. For BH growth in IR galaxies, the model predicts that the majority of BH growth at z>1 occurs in infrared luminous galaxies and the AGN fraction as a function of IR survey is a strong function of the survey depth, ranging from >50% at bright end to below 10% at faint end. We also evaluates various AGN selection techniques at X-ray and IR wavelengths and offer predictions for future missions at X-ray and IR.

Probing heat transfer, fluid flow and microstructural evolution during fusion welding of alloys

NASA Astrophysics Data System (ADS)

Zhang, Wei

The composition, geometry, structure and properties of the welded joints are affected by the various physical processes that take place during fusion welding. Understanding these processes has been an important goal in the contemporary welding research to achieve structurally sound and reliable welds. In the present thesis research, several important physical processes including the heat transfer, fluid flow and microstructural evolution in fusion welding were modeled based on the fundamentals of transport phenomena and phase transformation theory. The heat transfer and fluid flow calculation is focused on the predictions of the liquid metal convection in the weld pool, the temperature distribution in the entire weldment, and the shape and size of the fusion zone (FZ) and heat affected zone (HAZ). The modeling of microstructural evolution is focused on the quantitative understanding of phase transformation kinetics during welding of several important alloys under both low and high heating and cooling conditions. Three numerical models were developed in the present thesis work: (1) a three-dimensional heat transfer and free surface flow model for the gas metal arc (GMA) fillet welding considering the complex weld joint geometry, (2) a phase transformation model based on the Johnson-Mehl-Avrami (JMA) theory, and (3) a one-dimensional numerical diffusion model considering multiple moving interfaces. To check the capabilities of the developed models, several cases were investigated, in which the predictions from the models were compared with the experimental results. The cases studied are the follows. For the modeling of heat transfer and fluid flow, the welding processes studied included gas tungsten arc (GTA) linear welding, GTA transient spot welding, and GMA fillet welding. The calculated weldment geometry and thermal cycles was validated against the experimental data under various welding conditions. For the modeling of microstructural evolution, the welded materials investigated included AISI 1005 low-carbon steel, 1045 medium-carbon steel, 2205 duplex stainless steel (DSS) and Ti-6Al-4V alloy. The calculated phase transformation kinetics were compared with the experimental results obtained using an x-ray diffraction technique by Dr. John W. Elmer of Lawrence Livermore National Laboratory. (Abstract shortened by UMI.)

Alternative modeling methods for plasma-based Rf ion sources

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

Veitzer, Seth A., E-mail: veitzer@txcorp.com; Kundrapu, Madhusudhan, E-mail: madhusnk@txcorp.com; Stoltz, Peter H., E-mail: phstoltz@txcorp.com

Rf-driven ion sources for accelerators and many industrial applications benefit from detailed numerical modeling and simulation of plasma characteristics. For instance, modeling of the Spallation Neutron Source (SNS) internal antenna H{sup −} source has indicated that a large plasma velocity is induced near bends in the antenna where structural failures are often observed. This could lead to improved designs and ion source performance based on simulation and modeling. However, there are significant separations of time and spatial scales inherent to Rf-driven plasma ion sources, which makes it difficult to model ion sources with explicit, kinetic Particle-In-Cell (PIC) simulation codes. Inmore » particular, if both electron and ion motions are to be explicitly modeled, then the simulation time step must be very small, and total simulation times must be large enough to capture the evolution of the plasma ions, as well as extending over many Rf periods. Additional physics processes such as plasma chemistry and surface effects such as secondary electron emission increase the computational requirements in such a way that even fully parallel explicit PIC models cannot be used. One alternative method is to develop fluid-based codes coupled with electromagnetics in order to model ion sources. Time-domain fluid models can simulate plasma evolution, plasma chemistry, and surface physics models with reasonable computational resources by not explicitly resolving electron motions, which thereby leads to an increase in the time step. This is achieved by solving fluid motions coupled with electromagnetics using reduced-physics models, such as single-temperature magnetohydrodynamics (MHD), extended, gas dynamic, and Hall MHD, and two-fluid MHD models. We show recent results on modeling the internal antenna H{sup −} ion source for the SNS at Oak Ridge National Laboratory using the fluid plasma modeling code USim. We compare demonstrate plasma temperature equilibration in two-temperature MHD models for the SNS source and present simulation results demonstrating plasma evolution over many Rf periods for different plasma temperatures. We perform the calculations in parallel, on unstructured meshes, using finite-volume solvers in order to obtain results in reasonable time.« less

Alternative modeling methods for plasma-based Rf ion sources.

PubMed

Veitzer, Seth A; Kundrapu, Madhusudhan; Stoltz, Peter H; Beckwith, Kristian R C

2016-02-01

Rf-driven ion sources for accelerators and many industrial applications benefit from detailed numerical modeling and simulation of plasma characteristics. For instance, modeling of the Spallation Neutron Source (SNS) internal antenna H(-) source has indicated that a large plasma velocity is induced near bends in the antenna where structural failures are often observed. This could lead to improved designs and ion source performance based on simulation and modeling. However, there are significant separations of time and spatial scales inherent to Rf-driven plasma ion sources, which makes it difficult to model ion sources with explicit, kinetic Particle-In-Cell (PIC) simulation codes. In particular, if both electron and ion motions are to be explicitly modeled, then the simulation time step must be very small, and total simulation times must be large enough to capture the evolution of the plasma ions, as well as extending over many Rf periods. Additional physics processes such as plasma chemistry and surface effects such as secondary electron emission increase the computational requirements in such a way that even fully parallel explicit PIC models cannot be used. One alternative method is to develop fluid-based codes coupled with electromagnetics in order to model ion sources. Time-domain fluid models can simulate plasma evolution, plasma chemistry, and surface physics models with reasonable computational resources by not explicitly resolving electron motions, which thereby leads to an increase in the time step. This is achieved by solving fluid motions coupled with electromagnetics using reduced-physics models, such as single-temperature magnetohydrodynamics (MHD), extended, gas dynamic, and Hall MHD, and two-fluid MHD models. We show recent results on modeling the internal antenna H(-) ion source for the SNS at Oak Ridge National Laboratory using the fluid plasma modeling code USim. We compare demonstrate plasma temperature equilibration in two-temperature MHD models for the SNS source and present simulation results demonstrating plasma evolution over many Rf periods for different plasma temperatures. We perform the calculations in parallel, on unstructured meshes, using finite-volume solvers in order to obtain results in reasonable time.

Technical Note: Approximate Bayesian parameterization of a complex tropical forest model

NASA Astrophysics Data System (ADS)

Hartig, F.; Dislich, C.; Wiegand, T.; Huth, A.

2013-08-01

Inverse parameter estimation of process-based models is a long-standing problem in ecology and evolution. A key problem of inverse parameter estimation is to define a metric that quantifies how well model predictions fit to the data. Such a metric can be expressed by general cost or objective functions, but statistical inversion approaches are based on a particular metric, the probability of observing the data given the model, known as the likelihood. Deriving likelihoods for dynamic models requires making assumptions about the probability for observations to deviate from mean model predictions. For technical reasons, these assumptions are usually derived without explicit consideration of the processes in the simulation. Only in recent years have new methods become available that allow generating likelihoods directly from stochastic simulations. Previous applications of these approximate Bayesian methods have concentrated on relatively simple models. Here, we report on the application of a simulation-based likelihood approximation for FORMIND, a parameter-rich individual-based model of tropical forest dynamics. We show that approximate Bayesian inference, based on a parametric likelihood approximation placed in a conventional MCMC, performs well in retrieving known parameter values from virtual field data generated by the forest model. We analyze the results of the parameter estimation, examine the sensitivity towards the choice and aggregation of model outputs and observed data (summary statistics), and show results from using this method to fit the FORMIND model to field data from an Ecuadorian tropical forest. Finally, we discuss differences of this approach to Approximate Bayesian Computing (ABC), another commonly used method to generate simulation-based likelihood approximations. Our results demonstrate that simulation-based inference, which offers considerable conceptual advantages over more traditional methods for inverse parameter estimation, can successfully be applied to process-based models of high complexity. The methodology is particularly suited to heterogeneous and complex data structures and can easily be adjusted to other model types, including most stochastic population and individual-based models. Our study therefore provides a blueprint for a fairly general approach to parameter estimation of stochastic process-based models in ecology and evolution.

The effects of shockwave profile shape and shock obliquity on spallation in Cu and Ta: kinetic and stress-state effects on damage evolution(u)

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

Gray, George T

2010-12-14

Widespread research over the past five decades has provided a wealth of experimental data and insight concerning shock hardening and the spallation response of materials subjected to square-topped shock-wave loading profiles. Less quantitative data have been gathered on the effect of direct, in-contact, high explosive (HE)-driven Taylor wave (or triangular-wave) loading profile shock loading on the shock hardening, damage evolution, or spallation response of materials. Explosive loading induces an impulse dubbed a 'Taylor Wave'. This is a significantly different loading history than that achieved by a square-topped impulse in terms of both the pulse duration at a fixed peak pressure,more » and a different unloading strain rate from the peak Hugoniot state achieved. The goal of this research is to quantify the influence of shockwave obliquity on the spallation response of copper and tantalum by subjecting plates of each material to HE-driven sweeping detonation-wave loading and quantify both the wave propagation and the post-mortem damage evolution. This talk will summarize our current understanding of damage evolution during sweeping detonation-wave spallation loading in Cu and Ta and show comparisons to modeling simulations. The spallation responses of Cu and Ta are both shown to be critically dependent on the shockwave profile and the stress-state of the shock. Based on variations in the specifics of the shock drive (pulse shape, peak stress, shock obliquity) and sample geometry in Cu and Ta, 'spall strength' varies by over a factor of two and the details of the mechanisms of the damage evolution is seen to vary. Simplistic models of spallation, such as P{sub min} based on 1-D square-top shock data lack the physics to capture the influence of kinetics on damage evolution such as that operative during sweeping detonation loading. Such considerations are important for the development of predictive models of damage evolution and spallation in metals and alloys.« less

Phylogenetic and Evolutionary Patterns in Microbial Carotenoid Biosynthesis Are Revealed by Comparative Genomics

PubMed Central

Klassen, Jonathan L.

2010-01-01

Background Carotenoids are multifunctional, taxonomically widespread and biotechnologically important pigments. Their biosynthesis serves as a model system for understanding the evolution of secondary metabolism. Microbial carotenoid diversity and evolution has hitherto been analyzed primarily from structural and biosynthetic perspectives, with the few phylogenetic analyses of microbial carotenoid biosynthetic proteins using either used limited datasets or lacking methodological rigor. Given the recent accumulation of microbial genome sequences, a reappraisal of microbial carotenoid biosynthetic diversity and evolution from the perspective of comparative genomics is warranted to validate and complement models of microbial carotenoid diversity and evolution based upon structural and biosynthetic data. Methodology/Principal Findings Comparative genomics were used to identify and analyze in silico microbial carotenoid biosynthetic pathways. Four major phylogenetic lineages of carotenoid biosynthesis are suggested composed of: (i) Proteobacteria; (ii) Firmicutes; (iii) Chlorobi, Cyanobacteria and photosynthetic eukaryotes; and (iv) Archaea, Bacteroidetes and two separate sub-lineages of Actinobacteria. Using this phylogenetic framework, specific evolutionary mechanisms are proposed for carotenoid desaturase CrtI-family enzymes and carotenoid cyclases. Several phylogenetic lineage-specific evolutionary mechanisms are also suggested, including: (i) horizontal gene transfer; (ii) gene acquisition followed by differential gene loss; (iii) co-evolution with other biochemical structures such as proteorhodopsins; and (iv) positive selection. Conclusions/Significance Comparative genomics analyses of microbial carotenoid biosynthetic proteins indicate a much greater taxonomic diversity then that identified based on structural and biosynthetic data, and divides microbial carotenoid biosynthesis into several, well-supported phylogenetic lineages not evident previously. This phylogenetic framework is applicable to understanding the evolution of specific carotenoid biosynthetic proteins or the unique characteristics of carotenoid biosynthetic evolution in a specific phylogenetic lineage. Together, these analyses suggest a “bramble” model for microbial carotenoid biosynthesis whereby later biosynthetic steps exhibit greater evolutionary plasticity and reticulation compared to those closer to the biosynthetic “root”. Structural diversification may be constrained (“trimmed”) where selection is strong, but less so where selection is weaker. These analyses also highlight likely productive avenues for future research and bioprospecting by identifying both gaps in current knowledge and taxa which may particularly facilitate carotenoid diversification. PMID:20582313

Unidirectional circulation in a prebiotic photochemical cycle

PubMed Central

Careri, Giorgio; Wyman, Jeffries

1985-01-01

In this brief note, we suggest the possibility that a soliton-assisted unidirectional photochemical cycle has played a role in prebiotic evolution. This suggestion is based on a model calculation which is itself based on the detection of Davydov-type soliton overtones in acetanilide. PMID:16593575

A process model for the heat-affected zone microstructure evolution in duplex stainless steel weldments: Part I. the model

NASA Astrophysics Data System (ADS)

Hemmer, H.; Grong, Ø.

1999-11-01

The present investigation is concerned with modeling of the microstructure evolution in duplex stainless steels under thermal conditions applicable to welding. The important reactions that have been modeled are the dissolution of austenite during heating, subsequent grain growth in the delta ferrite regime, and finally, the decomposition of the delta ferrite to austenite during cooling. As a starting point, a differential formulation of the underlying diffusion problem is presented, based on the internal-state variable approach. These solutions are later manipulated and expressed in terms of the Scheil integral in the cases where the evolution equation is separable or can be made separable by a simple change of variables. The models have then been applied to describe the heat-affected zone microstructure evolution during both thick-plate and thin-plate welding of three commercial duplex stainless steel grades: 2205, 2304, and 2507. The results may conveniently be presented in the form of novel process diagrams, which display contours of constant delta ferrite grain size along with information about dissolution and reprecipitation of austenite for different combinations of weld input energy and peak temperature. These diagrams are well suited for quantitative readings and illustrate, in a condensed manner, the competition between the different variables that lead to structural changes during welding of duplex stainless steels.

Constraints on millisecond magnetars as the engines of prompt emission in gamma-ray bursts

NASA Astrophysics Data System (ADS)

Beniamini, Paz; Giannios, Dimitrios; Metzger, Brian D.

2017-12-01

We examine millisecond magnetars as central engines of gamma-ray bursts' (GRBs) prompt emission. Using the protomagnetar wind model of Metzger et al., we estimate the temporal evolution of the magnetization and power injection at the base of the GRB jet and apply these to different prompt emission models to make predictions for the GRB energetics, spectra and light curves. We investigate both shock and magnetic reconnection models for the particle acceleration, as well as the effects of energy dissipation across optically thick and thin regions of the jet. The magnetization at the base of the jet, σ0, is the main parameter driving the GRB evolution in the magnetar model and the emission is typically released for 100 ≲σ0 ≲3000. Given the rapid increase in σ0 as the protomagnetar cools and its neutrino-driven mass loss subsides, the GRB duration is typically limited to ≲100 s. This low baryon loading at late times challenges magnetar models for ultralong GRBs, though black hole models likely run into similar difficulties without substantial entrainment from the jet walls. The maximum radiated gamma-ray energy is ≲5 × 1051 erg, significantly less than the magnetar's total initial rotational energy and in strong tension with the high end of the observed GRB energy distribution. However, the gradual magnetic dissipation model applied to a magnetar central engine, naturally explains several key observables of typical GRBs, including energetics, durations, stable peak energies, spectral slopes and a hard to soft evolution during the burst.

Diffusion of Super-Gaussian Profiles

ERIC Educational Resources Information Center

Rosenberg, C.-J.; Anderson, D.; Desaix, M.; Johannisson, P.; Lisak, M.

2007-01-01

The present analysis describes an analytically simple and systematic approximation procedure for modelling the free diffusive spreading of initially super-Gaussian profiles. The approach is based on a self-similar ansatz for the evolution of the diffusion profile, and the parameter functions involved in the modelling are determined by suitable…

ScaleNet: A literature-based model of scale insect biology and systematics

USDA-ARS?s Scientific Manuscript database

Scale insects (Hemiptera: Coccoidea) are small herbivorous insects found in all continents except Antarctica. They are extremely invasive, and many species are serious agricultural pests. They are also emerging models for studies of the evolution of genetic systems, endosymbiosis, and plant-insect i...

Transverse single spin asymmetry in e +p↑→e +J /ψ +X and Q2 evolution of Sivers function-II

NASA Astrophysics Data System (ADS)

Godbole, Rohini M.; Kaushik, Abhiram; Misra, Anuradha; Rawoot, Vaibhav S.

2015-01-01

We present estimates of single spin asymmetry in the electroproduction of J /ψ taking into account the transverse momentum-dependent (TMD) evolution of the gluon Sivers function. We estimate single spin asymmetry for JLab, HERMES, COMPASS and eRHIC energies using the color evaporation model of J /ψ . We have calculated the asymmetry using recent parameters extracted by Echevarria et al. using the Collins-Soper-Sterman approach to TMD evolution. These recent TMD evolution fits are based on the evolution kernel in which the perturbative part is resummed up to next-to-leading logarithmic accuracy. We have also estimated the asymmetry by using parameters which had been obtained by a fit by Anselmino et al., using both an exact numerical and an approximate analytical solution of the TMD evolution equations. We find that the variation among the different estimates obtained using TMD evolution is much smaller than between these on one hand and the estimates obtained using DGLAP evolution on the other. Even though the use of TMD evolution causes an overall reduction in asymmetries compared to the ones obtained without it, they remain sizable. Overall, upon use of TMD evolution, predictions for asymmetries stabilize.

Modeling eutrophic lakes: From mass balance laws to ordinary differential equations

NASA Astrophysics Data System (ADS)

Marasco, Addolorata; Ferrara, Luciano; Romano, Antonio

Starting from integral balance laws, a model based on nonlinear ordinary differential equations (ODEs) describing the evolution of Phosphorus cycle in a lake is proposed. After showing that the usual homogeneous model is not compatible with the mixture theory, we prove that an ODEs model still holds but for the mean values of the state variables provided that the nonhomogeneous involved fields satisfy suitable conditions. In this model the trophic state of a lake is described by the mean densities of Phosphorus in water and sediments, and phytoplankton biomass. All the quantities appearing in the model can be experimentally evaluated. To propose restoration programs, the evolution of these state variables toward stable steady state conditions is analyzed. Moreover, the local stability analysis is performed with respect to all the model parameters. Some numerical simulations and a real application to lake Varese conclude the paper.

Chemical Ionization Mass Spectrometry-Based Measurements of HO2 and RO2 During TRACE-P

NASA Technical Reports Server (NTRS)

Cantrell, Christopher A.; Eisele, Fred L.

2004-01-01

The Transport and Chemical Evolution over the Pacific (TRACE-P) mission extends NASA's Global Tropospheric Experiment (GTE) series of campaigns. TRACE-P was an aircraft-based campaign that was part of a larger ground-based and aircraft-based program (APARE) under the auspices of the International Global Atmospheric Chemistry (IGAC) program. TRACE-P was designed to (1) determine the chemical composition of Asian outflow over the western Pacific, and to (2) determine the chemical evolution of the Asian outflow. These objectives were addressed through a variety of observations and numerical modeling exercises. In particular, the goals included sampling strategies that would improve understanding of the budgets of odd hydrogen species (OH and HO2), budgets of NOx (NO, NO2, and their reservoirs), and impacts of oxidants produced in the outflow on air quality in the United States. The NASA DC-8 and P-3B aircraft were deployed in the March and April, 2001 out of primary bases of operation in Hong Kong and Yokota Air Base in Japan. These two aircraft have complementary capabilities which allow high altitude and long range impacts, as well as low altitude, local impacts to be assessed. In order to quantify the composition and evolution of Asian outflow, it is important to quantify as many species as possible including photochemically active species (e.g. NO2, CH2O, O3, acetone, etc.), sources species (VOCs, CO, NOx, SO2, aerosols), reactive intermediates including free radicals (OH, HO2, RO2, and their reservoirs), and end products (nitric acid, sulfuric acid, secondary aerosols, etc.). The more complete the measurement suite, the more tightly constrained the numerical modeling can be (within the uncertainties of the measurements). The numerical models range in sophistication from simple steady state box models (as employed in this study) to multi-dimensional chemical transport models. Data were collected on approximately 20 flights of the DC-8 and 21 flights of the P-3B. Observations from both aircraft were used in the present analysis, but primarily focused on the P-3B flights since that was the platform on which the peroxy radical instrumentation was based.

Temperature and precipitation in the context of the annual cycle over Asia: Model evaluation and future change

NASA Astrophysics Data System (ADS)

Moon, Suyeon; Ha, Kyung-Ja

2017-05-01

Since the early or late arrival of monsoon rainfall can be devastating to agriculture and economy, the prediction of the onset of monsoon is a very important issue. The Asian monsoon is characterized by a strong annual cycle with rainy summer and dry winter. Nevertheless, most of monsoon studies have focused on the seasonal-mean of temperature and precipitation. The present study aims to evaluate a total of 27 coupled models that participated in phase 5 of the Coupled Model Intercomparison Project (CMIP5) for projection of the time evolution and the intensity of Asian monsoon on the basis of the annual cycle of temperature and precipitation. And future changes of onset, retreat, and intensity of monsoon are analyzed. Four models for good seasonal-mean (GSM) and good harmonic (GH) groups, respectively, are selected. GSM is based on the seasonal-mean of temperature and precipitation in summer and winter, and GH is based on the annual cycle of temperature and precipitation which represents a characteristic of the monsoon. To compare how well the time evolution of the monsoon is simulated in each group, the onset, retreat, and duration of Asian monsoon are examined. The highest pattern correlation coefficient (PCC) of onset, retreat, and duration between the reanalysis data and model outputs demonstrates that GH models' MME predicts time evolution of monsoon most precisely, with PCC values of 0.80, 0.52, and 0.63, respectively. To predict future changes of the monsoon, the representative concentration pathway 4.5 (RCP 4.5) experiments for the period of 2073-2099 are compared with historical simulations for the period of 1979-2005 from CMIP5 using GH models' MME. The Asian monsoon domain is expanded by 22.6% in the future projection. The onset date in the future is advanced over most parts of Asian monsoon region. The duration of summer Asian monsoon in the future projection will be lengthened by up to 2 pentads over the Asian monsoon region, as a result of advanced onset. The Asian monsoon intensity becomes stronger with the passage of time. This study has important implication for assessment of CMIP5 models in terms of the prediction of time evolution and intensity of Asian monsoon based on the annual cycle of temperature and precipitation.

Modeling evolution of crosstalk in noisy signal transduction networks

NASA Astrophysics Data System (ADS)

Tareen, Ammar; Wingreen, Ned S.; Mukhopadhyay, Ranjan

2018-02-01

Signal transduction networks can form highly interconnected systems within cells due to crosstalk between constituent pathways. To better understand the evolutionary design principles underlying such networks, we study the evolution of crosstalk for two parallel signaling pathways that arise via gene duplication. We use a sequence-based evolutionary algorithm and evolve the network based on two physically motivated fitness functions related to information transmission. We find that one fitness function leads to a high degree of crosstalk while the other leads to pathway specificity. Our results offer insights on the relationship between network architecture and information transmission for noisy biomolecular networks.

Intent, Future, Anticipation: A Semiotic, Transdisciplinary Approach

NASA Astrophysics Data System (ADS)

Loeckenhoff, Hellmut

2008-10-01

Encouraged e.g. by chaos theory and (bio-)semiotics science is trying to attempt a deeper understanding of life. The paradigms of physics alone prove not sufficient to explain f. ex. evolution or phylogenesis and ontogenesis. In complement, research on life systems reassesses paradigmatic models not only for living systems and not only on the strict biological level. The ontological as well as the epistemological base of science in toto is to be reconsidered. Science itself proves a historical and cultural phenomenon and can be seen as shaped by evolution and semiosis. -Living systems are signified by purpose, intent and, necessarily, by the faculty to anticipate e.g. the cyclic changes of their environment. To understand the concepts behind a proposal is developed towards a model set constituting a transdisciplinary approach. It rests e.g. on concepts of systems, evolution, complexity and semiodynamics.

Cosmological backreaction within the Szekeres model and emergence of spatial curvature

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

Bolejko, Krzysztof, E-mail: krzysztof.bolejko@sydney.edu.au

This paper discusses the phenomenon of backreaction within the Szekeres model. Cosmological backreaction describes how the mean global evolution of the Universe deviates from the Friedmannian evolution. The analysis is based on models of a single cosmological environment and the global ensemble of the Szekeres models (of the Swiss-Cheese-type and Styrofoam-type). The obtained results show that non-linear growth of cosmic structures is associated with the growth of the spatial curvature Ω{sub R} (in the FLRW limit Ω{sub R} → Ω {sub k} ). If averaged over global scales the result depends on the assumed global model of the Universe. Withinmore » the Swiss-Cheese model, which does have a fixed background, the volume average follows the evolution of the background, and the global spatial curvature averages out to zero (the background model is the ΛCDM model, which is spatially flat). In the Styrofoam-type model, which does not have a fixed background, the mean evolution deviates from the spatially flat ΛCDM model, and the mean spatial curvature evolves from Ω{sub R} =0 at the CMB to Ω{sub R} ∼ 0.1 at 0 z =. If the Styrofoam-type model correctly captures evolutionary features of the real Universe then one should expect that in our Universe, the spatial curvature should build up (local growth of cosmic structures) and its mean global average should deviate from zero (backreaction). As a result, this paper predicts that the low-redshift Universe should not be spatially flat (i.e. Ω {sub k} ≠ 0, even if in the early Universe Ω {sub k} = 0) and therefore when analysing low- z cosmological data one should keep Ω {sub k} as a free parameter and independent from the CMB constraints.« less

Cosmological backreaction within the Szekeres model and emergence of spatial curvature

NASA Astrophysics Data System (ADS)

Bolejko, Krzysztof

2017-06-01

This paper discusses the phenomenon of backreaction within the Szekeres model. Cosmological backreaction describes how the mean global evolution of the Universe deviates from the Friedmannian evolution. The analysis is based on models of a single cosmological environment and the global ensemble of the Szekeres models (of the Swiss-Cheese-type and Styrofoam-type). The obtained results show that non-linear growth of cosmic structures is associated with the growth of the spatial curvature ΩScript R (in the FLRW limit ΩScript R → Ωk). If averaged over global scales the result depends on the assumed global model of the Universe. Within the Swiss-Cheese model, which does have a fixed background, the volume average follows the evolution of the background, and the global spatial curvature averages out to zero (the background model is the ΛCDM model, which is spatially flat). In the Styrofoam-type model, which does not have a fixed background, the mean evolution deviates from the spatially flat ΛCDM model, and the mean spatial curvature evolves from ΩScript R =0 at the CMB to ΩScript R ~ 0.1 at 0z =. If the Styrofoam-type model correctly captures evolutionary features of the real Universe then one should expect that in our Universe, the spatial curvature should build up (local growth of cosmic structures) and its mean global average should deviate from zero (backreaction). As a result, this paper predicts that the low-redshift Universe should not be spatially flat (i.e. Ωk ≠ 0, even if in the early Universe Ωk = 0) and therefore when analysing low-z cosmological data one should keep Ωk as a free parameter and independent from the CMB constraints.

Eocene to mid-Pliocene landscape evolution in Scandinavia inferred from offshore sediment volumes and pre-glacial topography using inverse modelling

NASA Astrophysics Data System (ADS)

Pedersen, Vivi K.; Braun, Jean; Huismans, Ritske S.

2018-02-01

The origin of high topography in Scandinavia is highly debated, both in terms of its age and the underlying mechanism for its formation. Traditionally, the current high topography is assumed to have formed by several Cenozoic (mainly Neogene) phases of surface uplift and dissection of an old peneplain surface. These same surface uplift events are suggested to explain the increased deposition observed in adjacent offshore basins on the Norwegian shelf and in the North Sea. However, more recently it has been suggested that erosion and isostatic rock uplift of existing topography may also explain the recent evolution of topography in Scandinavia. For this latter view, the increased sedimentation towards the present is assumed to be a consequence of a climate related increase in erosion. In this study we explore whether inverse modelling of landscape evolution can give new insight into Eocene to mid-Pliocene (54-4 Ma) landscape evolution in the Scandinavian region. We do this by combining a highly efficient forward-in-time landscape evolution model (FastScape) with an optimization scheme suitable for non-linear inverse problems (the neighbourhood algorithm - NA). To limit our approach to the fluvial regime, we exclude the most recent mid-Pliocene-Quaternary time period where glacial erosion processes are expected to dominate landscape evolution. The "goodness" of our landscape evolution models is evaluated using i) sediment fluxes based on decompacted offshore sediment volumes and ii) maximum pre-glacial topography from a mid-Pliocene landscape, reconstructed using geophysical relief and offshore sediment volumes from the mid-Pliocene-Quaternary. We find several tested scenarios consistent with the offshore sediment record and the maximum elevation for our reconstructed pre-glacial (mid-Pliocene) landscape reconstruction, including: I) substantial initial topography ( 2 km) at 54 Ma and no induced tectonic rock uplift, II) the combination of some initial topography ( 1.1 km) at 54 Ma and minor continued rock uplift (< 0.04 mm/yr) until 4 Ma, and III) a two-phased tectonic rock uplift of an initially low topography ( 0.1 km). However, out of these, only scenario I (no tectonic rock uplift) matches large-scale characteristics of our reconstructed pre-glacial (mid-Pliocene) topography well. Our preferred model for Eocene to mid-Pliocene landscape evolution in Scandinavia is therefore one where high topography ( 2 km) has existed throughout the time interval from 54 to 4 Ma. We do not find several phases of peneplain surface uplift necessary to explain offshore sediment volumes and large-scale topographic patterns. On the contrary, extensive peneplain dissection seems inconsistent with the low rates of erosion we infer based on the offshore sediment volumes.

Dynamical Models of Elliptical Galaxies in z = 0.5 Clusters. I. Data-Model Comparison and Evolution of Galaxy Rotation

NASA Astrophysics Data System (ADS)

van der Marel, Roeland P.; van Dokkum, Pieter G.

2007-10-01

We present spatially resolved stellar rotation velocity and velocity dispersion profiles from Keck/LRIS absorption-line spectra for 25 galaxies, mostly visually classified ellipticals, in three clusters at z~0.5. We interpret the kinematical data and HST photometry using oblate axisymmetric two-integral f(E,Lz) dynamical models based on the Jeans equations. This yields good fits, provided that the seeing and observational characteristics are carefully modeled. The fits yield for each galaxy the dynamical mass-to-light ratio (M/L) and a measure of the galaxy rotation rate. Paper II addresses the implied M/L evolution. Here we study the rotation-rate evolution by comparison to a sample of local elliptical galaxies of similar present-day luminosity. The brightest galaxies in the sample all rotate too slowly to account for their flattening, as is also observed at z=0. But the average rotation rate is higher at z~0.5 than locally. This may be due to a higher fraction of misclassified S0 galaxies (although this effect is insufficient to explain the observed strong evolution of the cluster S0 fraction with redshift). Alternatively, dry mergers between early-type galaxies may have decreased the average rotation rate over time. It is unclear whether such mergers are numerous enough in clusters to explain the observed trend quantitatively. Disk-disk mergers may affect the comparison through the so-called ``progenitor bias,'' but this cannot explain the direction of the observed rotation-rate evolution. Additional samples are needed to constrain possible environmental dependencies and cosmic variance in galaxy rotation rates. Either way, studies of the internal stellar dynamics of distant galaxies provide a valuable new approach for exploring galaxy evolution.

Evolution of Collective Behaviour in an Artificial World Using Linguistic Fuzzy Rule-Based Systems

PubMed Central

Lebar Bajec, Iztok

2017-01-01

Collective behaviour is a fascinating and easily observable phenomenon, attractive to a wide range of researchers. In biology, computational models have been extensively used to investigate various properties of collective behaviour, such as: transfer of information across the group, benefits of grouping (defence against predation, foraging), group decision-making process, and group behaviour types. The question ‘why,’ however remains largely unanswered. Here the interest goes into which pressures led to the evolution of such behaviour, and evolutionary computational models have already been used to test various biological hypotheses. Most of these models use genetic algorithms to tune the parameters of previously presented non-evolutionary models, but very few attempt to evolve collective behaviour from scratch. Of these last, the successful attempts display clumping or swarming behaviour. Empirical evidence suggests that in fish schools there exist three classes of behaviour; swarming, milling and polarized. In this paper we present a novel, artificial life-like evolutionary model, where individual agents are governed by linguistic fuzzy rule-based systems, which is capable of evolving all three classes of behaviour. PMID:28045964

Evolution of Collective Behaviour in an Artificial World Using Linguistic Fuzzy Rule-Based Systems.

PubMed

Demšar, Jure; Lebar Bajec, Iztok

2017-01-01

Collective behaviour is a fascinating and easily observable phenomenon, attractive to a wide range of researchers. In biology, computational models have been extensively used to investigate various properties of collective behaviour, such as: transfer of information across the group, benefits of grouping (defence against predation, foraging), group decision-making process, and group behaviour types. The question 'why,' however remains largely unanswered. Here the interest goes into which pressures led to the evolution of such behaviour, and evolutionary computational models have already been used to test various biological hypotheses. Most of these models use genetic algorithms to tune the parameters of previously presented non-evolutionary models, but very few attempt to evolve collective behaviour from scratch. Of these last, the successful attempts display clumping or swarming behaviour. Empirical evidence suggests that in fish schools there exist three classes of behaviour; swarming, milling and polarized. In this paper we present a novel, artificial life-like evolutionary model, where individual agents are governed by linguistic fuzzy rule-based systems, which is capable of evolving all three classes of behaviour.

Small strain multiphase-field model accounting for configurational forces and mechanical jump conditions

NASA Astrophysics Data System (ADS)

Schneider, Daniel; Schoof, Ephraim; Tschukin, Oleg; Reiter, Andreas; Herrmann, Christoph; Schwab, Felix; Selzer, Michael; Nestler, Britta

2018-03-01

Computational models based on the phase-field method have become an essential tool in material science and physics in order to investigate materials with complex microstructures. The models typically operate on a mesoscopic length scale resolving structural changes of the material and provide valuable information about the evolution of microstructures and mechanical property relations. For many interesting and important phenomena, such as martensitic phase transformation, mechanical driving forces play an important role in the evolution of microstructures. In order to investigate such physical processes, an accurate calculation of the stresses and the strain energy in the transition region is indispensable. We recall a multiphase-field elasticity model based on the force balance and the Hadamard jump condition at the interface. We show the quantitative characteristics of the model by comparing the stresses, strains and configurational forces with theoretical predictions in two-phase cases and with results from sharp interface calculations in a multiphase case. As an application, we choose the martensitic phase transformation process in multigrain systems and demonstrate the influence of the local homogenization scheme within the transition regions on the resulting microstructures.

A New Model for the Seasonal Evolution of Triton

NASA Astrophysics Data System (ADS)

Forget, F.; Decamp, N.; Berthier, J.; Le Guyader, C.

2000-10-01

The seasonal evolution of Triton's surface and atmosphere remains poorly understood. No model [1] has been able to fully reproduce the main characterictics of the Voyager 2 observations in 1989 in combination with the "Global warming" recently inferred from stellar occultations [2]. Within this context, we have developped a new thermal model to study the seasonal nitrogen cycle on Triton. The model is the surface part of a Triton atmosphere General circulation model developped at LMD [3]. The nitrogen cycle was found to be very sensitive to Triton complex seasonal variations of the subsolar point latitude, especially during the current decade (south summer solstice). Since only pre-Voyager formulations were available for such a study, this has motivated some new calculations of Triton's motion based on more recent rotationnal elements combined with a relatively complete dynamic solution [4] adapted to Triton. A new analytic formulation suitable for climate modelling has been derived. On this basis, we wish to suggest a new, realistic scenario to explain Triton's apparence and evolution based on solar-induced variation of the frost albedo. Such variations have been observed in Mars CO2 ice seasonal polar caps [5]. Although they seem to result from complex microphysical behavior, they are likely to occur on Triton since both Triton and Mars polar caps are composed of weakly absorbing ice (N2 or CO2) in vapor pressure equilibrium with the main constituant of the atmosphere. [1] e.g. Hansen and Paige, Icarus 99, 273-288 (1992); Brown and Kirk, J. Geophys. Res. 99, 1965-1981 (1994); Spencer and Moore, Icarus 99, 261-272 (1992). [2] Elliot et al., Nature 393, 765-767 (1998). [3] Forget, Descamp and Hourdin, in ``Pluto and Triton, comparisons and evolution over time", Lowell Observatory's fourth annual workshop, Flagstaff, Arizona. (1999) [4] Le Guyader, Astron. Astrophys. 272, 687-694 (1993). [5] Kieffer et al., J. Geophys. Res. 105, 9653-9700 (2000).

Variational formulation and stability analysis of a three dimensional superelastic model for shape memory alloys

NASA Astrophysics Data System (ADS)

Alessi, Roberto; Pham, Kim

2016-02-01

This paper presents a variational framework for the three-dimensional macroscopic modelling of superelastic shape memory alloys in an isothermal setting. Phase transformation is accounted through a unique second order tensorial internal variable, acting as the transformation strain. Postulating the total strain energy density as the sum of a free energy and a dissipated energy, the model depends on two material scalar functions of the norm of the transformation strain and a material scalar constant. Appropriate calibration of these material functions allows to render a wide range of constitutive behaviours including stress-softening and stress-hardening. The quasi-static evolution problem of a domain is formulated in terms of two physical principles based on the total energy of the system: a stability criterion, which selects the local minima of the total energy, and an energy balance condition, which ensures the consistency of the evolution of the total energy with respect to the external loadings. The local phase transformation laws in terms of Kuhn-Tucker relations are deduced from the first-order stability condition and the energy balance condition. The response of the model is illustrated with a numerical traction-torsion test performed on a thin-walled cylinder. Evolutions of homogeneous states are given for proportional and non-proportional loadings. Influence of the stress-hardening/softening properties on the evolution of the transformation domain is emphasized. Finally, in view of an identification process, the issue of stability of homogeneous states in a multi-dimensional setting is answered based on the study of second-order derivative of the total energy. Explicit necessary and sufficient conditions of stability are provided.

Using Star Clusters as Tracers of Star Formation and Chemical Evolution: The Chemical Enrichment History of the Large Magellanic Cloud

NASA Astrophysics Data System (ADS)

Chilingarian, Igor V.; Asa’d, Randa

2018-05-01

The star formation (SFH) and chemical enrichment (CEH) histories of Local Group galaxies are traditionally studied by analyzing their resolved stellar populations in a form of color–magnitude diagrams obtained with the Hubble Space Telescope. Star clusters can be studied in integrated light using ground-based telescopes to much larger distances. They represent snapshots of the chemical evolution of their host galaxy at different ages. Here we present a simple theoretical framework for the chemical evolution based on the instantaneous recycling approximation (IRA) model. We infer a CEH from an SFH and vice versa using observational data. We also present a more advanced model for the evolution of individual chemical elements that takes into account the contribution of supernovae type Ia. We demonstrate that ages, iron, and α-element abundances of 15 star clusters derived from the fitting of their integrated optical spectra reliably trace the CEH of the Large Magellanic Cloud obtained from resolved stellar populations in the age range 40 Myr < t < 3.5 Gyr. The CEH predicted by our model from the global SFH of the LMC agrees remarkably well with the observed cluster age–metallicity relation. Moreover, the present-day total gas mass of the LMC estimated by the IRA model (6.2× {10}8 {M}ȯ ) matches within uncertainties the observed H I mass corrected for the presence of molecular gas (5.8+/- 0.5× {10}8 {M}ȯ ). We briefly discuss how our approach can be used to study SFHs of galaxies as distant as 10 Mpc at the level of detail that is currently available only in a handful of nearby Milky Way satellites. .

Modeling aeolian dune and dune field evolution

NASA Astrophysics Data System (ADS)

Diniega, Serina

Aeolian sand dune morphologies and sizes are strongly connected to the environmental context and physical processes active since dune formation. As such, the patterns and measurable features found within dunes and dune fields can be interpreted as records of environmental conditions. Using mathematical models of dune and dune field evolution, it should be possible to quantitatively predict dune field dynamics from current conditions or to determine past field conditions based on present-day observations. In this dissertation, we focus on the construction and quantitative analysis of a continuum dune evolution model. We then apply this model towards interpretation of the formative history of terrestrial and martian dunes and dune fields. Our first aim is to identify the controls for the characteristic lengthscales seen in patterned dune fields. Variations in sand flux, binary dune interactions, and topography are evaluated with respect to evolution of individual dunes. Through the use of both quantitative and qualitative multiscale models, these results are then extended to determine the role such processes may play in (de)stabilization of the dune field. We find that sand flux variations and topography generally destabilize dune fields, while dune collisions can yield more similarly-sized dunes. We construct and apply a phenomenological macroscale dune evolution model to then quantitatively demonstrate how dune collisions cause a dune field to evolve into a set of uniformly-sized dunes. Our second goal is to investigate the influence of reversing winds and polar processes in relation to dune slope and morphology. Using numerical experiments, we investigate possible causes of distinctive morphologies seen in Antarctic and martian polar dunes. Finally, we discuss possible model extensions and needed observations that will enable the inclusion of more realistic physical environments in the dune and dune field evolution models. By elucidating the qualitative and quantitative connections between environmental conditions, physical processes, and resultant dune and dune field morphologies, this research furthers our ability to interpret spacecraft images of dune fields, and to use present-day observations to improve our understanding of past terrestrial and martian environments.

Trait-based diversification shifts reflect differential extinction among fossil taxa

PubMed Central

Wagner, Peter J.; Estabrook, George F.

2014-01-01

Evolution provides many cases of apparent shifts in diversification associated with particular anatomical traits. Three general models connect these patterns to anatomical evolution: (i) elevated net extinction of taxa bearing particular traits, (ii) elevated net speciation of taxa bearing particular traits, and (iii) elevated evolvability expanding the range of anatomies available to some species. Trait-based diversification shifts predict elevated hierarchical stratigraphic compatibility (i.e., primitive→derived→highly derived sequences) among pairs of anatomical characters. The three specific models further predict (i) early loss of diversity for taxa retaining primitive conditions (elevated net extinction), (ii) increased diversification among later members of a clade (elevated net speciation), and (iii) increased disparity among later members in a clade (elevated evolvability). Analyses of 319 anatomical and stratigraphic datasets for fossil species and genera show that hierarchical stratigraphic compatibility exceeds the expectations of trait-independent diversification in the vast majority of cases, which was expected if trait-dependent diversification shifts are common. Excess hierarchical stratigraphic compatibility correlates with early loss of diversity for groups retaining primitive conditions rather than delayed bursts of diversity or disparity across entire clades. Cambrian clades (predominantly trilobites) alone fit null expectations well. However, it is not clear whether evolution was unusual among Cambrian taxa or only early trilobites. At least among post-Cambrian taxa, these results implicate models, such as competition and extinction selectivity/resistance, as major drivers of trait-based diversification shifts at the species and genus levels while contradicting the predictions of elevated net speciation and elevated evolvability models. PMID:25331898

Structure of Solar Ejecta

NASA Astrophysics Data System (ADS)

Muñoz, G.; Cantó, J.; Lara, A.; González, R.; Schwenn, R.

Solar Ejecta (SE) have been of interest in the last years, especially those which may reach Earth environment. It is possible to observe the SE early evolution, when they are in the field of view of coronagraphs. There are few indirect observations, as the case of interplanetary scintillation, of SEs in the interplanetary medium. Finally, we observe SEs in situ when they arrive at 1 AU.The SEs structure and evolution are important to understand the origin of these phenomena but to predict the possible effects in the space weather. It is of general acceptance that SEs are "Erupting Flux Ropes" traveling trough the Solar Wind. The "shapes" have been modeled as cylinders or as "ice cream cones" in order to represent the many different projections observed on Coronagraphs.We present a model of the SE evolution based on purely Hydrodynamic considerations. This model reproduces in good approximation some of the features observed in the images and in the measures of the shocks near Earth.

Strategy evolution driven by switching probabilities in structured multi-agent systems

NASA Astrophysics Data System (ADS)

Zhang, Jianlei; Chen, Zengqiang; Li, Zhiqi

2017-10-01

Evolutionary mechanism driving the commonly seen cooperation among unrelated individuals is puzzling. Related models for evolutionary games on graphs traditionally assume that players imitate their successful neighbours with higher benefits. Notably, an implicit assumption here is that players are always able to acquire the required pay-off information. To relax this restrictive assumption, a contact-based model has been proposed, where switching probabilities between strategies drive the strategy evolution. However, the explicit and quantified relation between a player's switching probability for her strategies and the number of her neighbours remains unknown. This is especially a key point in heterogeneously structured system, where players may differ in the numbers of their neighbours. Focusing on this, here we present an augmented model by introducing an attenuation coefficient and evaluate its influence on the evolution dynamics. Results show that the individual influence on others is negatively correlated with the contact numbers specified by the network topologies. Results further provide the conditions under which the coexisting strategies can be calculated analytically.

Plants, Weathering, and the Evolution of Atmospheric Carbon Dioxide and Oxygen

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

Berner, Robert A

Over the past six years we have published 24 papers that can be divided into three sections: (1) Study of plants and weathering, (2) modeling the evolution of atmospheric CO2 over Phanerozoic time (past 550 million years). (3) Modeling of atmospheric O2 over Phanerozoic time. References to papers published acknowledging this grant can be found at the end of this report and almost all are supplied in pdf form. (1) In the temperate forests of the Cascade Mountains, USA, calcium and magnesium meet vastly different fates beneath angiosperms vs gymnosperms. Calcium is leached beneath both groves of trees, but leachedmore » 20-40% more beneath the angiosperms. Magnesium is retained in the forest system beneath the angiosperms and leached from beneath the gymnosperms. (2) We have shown that climate and CO2, based on both carbon cycle modeling and hundreds of independent proxies for paleo-CO2, correlate very well over the past 550 million year. In a recent paper we use this correlation to deduce the sensitivity of global mean temperature to a doubling of atmospheric CO2, and results are in excellent agreement with the results of climatologists based on the historical record and on theoretical climate models (GCM’s).(3) We have shown that concentrations of atmospheric oxygen, calculated by a combined carbon-sulfur cycle model, over the past 550 million years have varied with and influenced biological evolution.« less

MuSE: accounting for tumor heterogeneity using a sample-specific error model improves sensitivity and specificity in mutation calling from sequencing data.

PubMed

Fan, Yu; Xi, Liu; Hughes, Daniel S T; Zhang, Jianjun; Zhang, Jianhua; Futreal, P Andrew; Wheeler, David A; Wang, Wenyi

2016-08-24

Subclonal mutations reveal important features of the genetic architecture of tumors. However, accurate detection of mutations in genetically heterogeneous tumor cell populations using next-generation sequencing remains challenging. We develop MuSE ( http://bioinformatics.mdanderson.org/main/MuSE ), Mutation calling using a Markov Substitution model for Evolution, a novel approach for modeling the evolution of the allelic composition of the tumor and normal tissue at each reference base. MuSE adopts a sample-specific error model that reflects the underlying tumor heterogeneity to greatly improve the overall accuracy. We demonstrate the accuracy of MuSE in calling subclonal mutations in the context of large-scale tumor sequencing projects using whole exome and whole genome sequencing.

Oparin's coacervates as an important milestone in chemical evolution

NASA Astrophysics Data System (ADS)

Kolb, Vera M.

2015-09-01

Although Oparin's coacervate model for the origin of life by chemical evolution is almost 100 years old, it is still valid. However, the structure of his originally proposed coacervate is not considered prebiotic, based on some recent developments in prebiotic chemistry. We have remedied this deficiency of the Oparin's model, by substituting his coacervate with a prebiotically feasible one. Oparin's coacervates are aqueous structures, but have a boundary with the rest of the aqueous medium. They exhibit properties of self-replication, and provide a path to a primitive metabolism, via chemical competition and thus a primitive selection. Thus, coacervates are good models for proto-cells. We review here some salient points of Oparin's model and address also some philosophical views on the beginning of natural selection in primitive chemical systems.

Optimization of seasonal ARIMA models using differential evolution - simulated annealing (DESA) algorithm in forecasting dengue cases in Baguio City

NASA Astrophysics Data System (ADS)

Addawe, Rizavel C.; Addawe, Joel M.; Magadia, Joselito C.

2016-10-01

Accurate forecasting of dengue cases would significantly improve epidemic prevention and control capabilities. This paper attempts to provide useful models in forecasting dengue epidemic specific to the young and adult population of Baguio City. To capture the seasonal variations in dengue incidence, this paper develops a robust modeling approach to identify and estimate seasonal autoregressive integrated moving average (SARIMA) models in the presence of additive outliers. Since the least squares estimators are not robust in the presence of outliers, we suggest a robust estimation based on winsorized and reweighted least squares estimators. A hybrid algorithm, Differential Evolution - Simulated Annealing (DESA), is used to identify and estimate the parameters of the optimal SARIMA model. The method is applied to the monthly reported dengue cases in Baguio City, Philippines.

A coupled ductile fracture phase-field model for crystal plasticity

NASA Astrophysics Data System (ADS)

Hernandez Padilla, Carlos Alberto; Markert, Bernd

2017-07-01

Nowadays crack initiation and evolution play a key role in the design of mechanical components. In the past few decades, several numerical approaches have been developed with the objective to predict these phenomena. The objective of this work is to present a simplified, nonetheless representative phenomenological model to predict the crack evolution of ductile fracture in single crystals. The proposed numerical approach is carried out by merging a conventional elasto-plastic crystal plasticity model and a phase-field model modified to predict ductile fracture. A two-dimensional initial boundary value problem of ductile fracture is introduced considering a single-crystal setup and Nickel-base superalloy material properties. The model is implemented into the finite element context subjected to a quasi-static uniaxial tension test. The results are then qualitatively analyzed and briefly compared to current benchmark results in the literature.

Model and simulation of Krause model in dynamic open network

NASA Astrophysics Data System (ADS)

Zhu, Meixia; Xie, Guangqiang

2017-08-01

The construction of the concept of evolution is an effective way to reveal the formation of group consensus. This study is based on the modeling paradigm of the HK model (Hegsekmann-Krause). This paper analyzes the evolution of multi - agent opinion in dynamic open networks with member mobility. The results of the simulation show that when the number of agents is constant, the interval distribution of the initial distribution will affect the number of the final view, The greater the distribution of opinions, the more the number of views formed eventually; The trust threshold has a decisive effect on the number of views, and there is a negative correlation between the trust threshold and the number of opinions clusters. The higher the connectivity of the initial activity group, the more easily the subjective opinion in the evolution of opinion to achieve rapid convergence. The more open the network is more conducive to the unity of view, increase and reduce the number of agents will not affect the consistency of the group effect, but not conducive to stability.

3D microstructural evolution of primary recrystallization and grain growth in cold rolled single-phase aluminum alloys

NASA Astrophysics Data System (ADS)

Adam, Khaled; Zöllner, Dana; Field, David P.

2018-04-01

Modeling the microstructural evolution during recrystallization is a powerful tool for the profound understanding of alloy behavior and for use in optimizing engineering properties through annealing. In particular, the mechanical properties of metallic alloys are highly dependent upon evolved microstructure and texture from the softening process. In the present work, a Monte Carlo (MC) Potts model was used to model the primary recrystallization and grain growth in cold rolled single-phase Al alloy. The microstructural representation of two kinds of dislocation densities, statistically stored dislocations and geometrically necessary dislocations were quantified based on the ViscoPlastic Fast Fourier transform method. This representation was then introduced into the MC Potts model to identify the favorable sites for nucleation where orientation gradients and entanglements of dislocations are high. Additionally, in situ observations of non-isothermal microstructure evolution for single-phase aluminum alloy 1100 were made to validate the simulation. The influence of the texture inhomogeneity is analyzed from a theoretical point of view using an orientation distribution function for deformed and evolved texture.

The medicago genome provides insight into evolution of rhizobial symbiosis

USDA-ARS?s Scientific Manuscript database

Medicago truncatula is an excellent model for the study of legume-specific biology, especially endosymbiotic interactions with bacteria and fungi. This paper describes the sequence of the euchromatic portion of the M. truncatula genome based on a recently completed BAC-based assembly supplemented by...

The Independent Evolution Method Is Not a Viable Phylogenetic Comparative Method

PubMed Central

2015-01-01

Phylogenetic comparative methods (PCMs) use data on species traits and phylogenetic relationships to shed light on evolutionary questions. Recently, Smaers and Vinicius suggested a new PCM, Independent Evolution (IE), which purportedly employs a novel model of evolution based on Felsenstein’s Adaptive Peak Model. The authors found that IE improves upon previous PCMs by producing more accurate estimates of ancestral states, as well as separate estimates of evolutionary rates for each branch of a phylogenetic tree. Here, we document substantial theoretical and computational issues with IE. When data are simulated under a simple Brownian motion model of evolution, IE produces severely biased estimates of ancestral states and changes along individual branches. We show that these branch-specific changes are essentially ancestor-descendant or “directional” contrasts, and draw parallels between IE and previous PCMs such as “minimum evolution”. Additionally, while comparisons of branch-specific changes between variables have been interpreted as reflecting the relative strength of selection on those traits, we demonstrate through simulations that regressing IE estimated branch-specific changes against one another gives a biased estimate of the scaling relationship between these variables, and provides no advantages or insights beyond established PCMs such as phylogenetically independent contrasts. In light of our findings, we discuss the results of previous papers that employed IE. We conclude that Independent Evolution is not a viable PCM, and should not be used in comparative analyses. PMID:26683838

Study of grain structure evolution during annealing of a twin-roll-cast Mg alloy

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

Tripathi, A.; Department of Metallurgical Engineering and Materials Science, IIT Bombay; Department of Materials Engineering, Monash University

2016-04-15

The evolution of microstructure under static annealing was studied for mid-thickness section of a twin-roll-cast (TRC) magnesium alloy. Annealing was performed at 300 °C and 500 °C for different times. Microstructural evolution was quantitatively analyzed, from optical micrographs, using grain path envelope analysis. Additional information from electron backscatter diffraction (EBSD) was used for addressing the possible mechanism(s). It was found that the TRC structure had a bimodal grain size, which was preserved even after annealing at 300 °C. However, the annealing at 500 °C led to a unimodal grain size. This difference in the grain size distribution created a contrastingmore » behavior in the normalized standard deviations. This was primarily attributed to a competition between recovery and recrystallization, and their respective dominance at 300° and 500 °C. A deformation induced recrystallization recovery (DIRR) model was proposed. The proposed model could successfully address the experimental microstructural evolution. - Highlights: • Annealing of twin roll cast (TRC) magnesium alloy was done at temperatures of 300 °C and 500 °C. • TRC had bimodal structure. Bimodality preserved for annealing at 300 °C. Annealing at 500 °C led to unimodal structure. • Grain evolution was described based on the competition between recovery and recrystallization. • Deformation induced recrystallization recovery (DIRR) mechanistic model was developed.« less

Modeling Educational Content: The Cognitive Approach of the PALO Language

ERIC Educational Resources Information Center

Rodriguez-Artacho, Miguel; Verdejo Maillo, M. Felisa

2004-01-01

This paper presents a reference framework to describe educational material. It introduces the PALO Language as a cognitive based approach to Educational Modeling Languages (EML). In accordance with recent trends for reusability and interoperability in Learning Technologies, EML constitutes an evolution of the current content-centered…

School Site Strategic Planning To Improve District Performance.

ERIC Educational Resources Information Center

Lytle, James H.

This paper describes the evolution of a school-based planning model that accommodates independent approaches to School District of Philadelphia goals. The description centers on key strategic planning decisions made during a 6-year period and three components of the planning model: the organizational monitoring and feedback system; organizational…

The 2-10 keV unabsorbed luminosity function of AGN from the LSS, CDFS, and COSMOS surveys

NASA Astrophysics Data System (ADS)

Ranalli, P.; Koulouridis, E.; Georgantopoulos, I.; Fotopoulou, S.; Hsu, L.-T.; Salvato, M.; Comastri, A.; Pierre, M.; Cappelluti, N.; Carrera, F. J.; Chiappetti, L.; Clerc, N.; Gilli, R.; Iwasawa, K.; Pacaud, F.; Paltani, S.; Plionis, E.; Vignali, C.

2016-05-01

The XMM-Large scale structure (XMM-LSS), XMM-Cosmological evolution survey (XMM-COSMOS), and XMM-Chandra deep field south (XMM-CDFS) surveys are complementary in terms of sky coverage and depth. Together, they form a clean sample with the least possible variance in instrument effective areas and point spread function. Therefore this is one of the best samples available to determine the 2-10 keV luminosity function of active galactic nuclei (AGN) and their evolution. The samples and the relevant corrections for incompleteness are described. A total of 2887 AGN is used to build the LF in the luminosity interval 1042-1046 erg s-1 and in the redshift interval 0.001-4. A new method to correct for absorption by considering the probability distribution for the column density conditioned on the hardness ratio is presented. The binned luminosity function and its evolution is determined with a variant of the Page-Carrera method, which is improved to include corrections for absorption and to account for the full probability distribution of photometric redshifts. Parametric models, namely a double power law with luminosity and density evolution (LADE) or luminosity-dependent density evolution (LDDE), are explored using Bayesian inference. We introduce the Watanabe-Akaike information criterion (WAIC) to compare the models and estimate their predictive power. Our data are best described by the LADE model, as hinted by the WAIC indicator. We also explore the recently proposed 15-parameter extended LDDE model and find that this extension is not supported by our data. The strength of our method is that it provides unabsorbed, non-parametric estimates, credible intervals for luminosity function parameters, and a model choice based on predictive power for future data. Based on observations obtained with XMM-Newton, an ESA science mission with instruments and contributions directly funded by ESA member states and NASA.Tables with the samples of the posterior probability distributions are only available at the CDS via anonymous ftp to http://cdsarc.u-strasbg.fr (http://130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/590/A80

Approximating basins of attraction for dynamical systems via stable radial bases

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

Cavoretto, R.; De Rossi, A.; Perracchione, E.

2016-06-08

In applied sciences it is often required to model and supervise temporal evolution of populations via dynamical systems. In this paper, we focus on the problem of approximating the basins of attraction of such models for each stable equilibrium point. We propose to reconstruct the basins via an implicit interpolant using stable radial bases, obtaining the surfaces by partitioning the phase space into disjoint regions. An application to a competition model presenting jointly three stable equilibria is considered.

The effect of Livermore OPAL opacities on the evolutionary masses of RR Lyrae stars

NASA Technical Reports Server (NTRS)

Yi, Sukyoung; Lee, Young-Wook; Demarque, Pierre

1993-01-01

We have investigated the effect of the new Livermore OPAL opacities on the evolution of horizontal-branch (HB) stars. This work was motivated by the recent stellar pulsation calculations using the new Livermore opacities, which suggest that the masses of double-mode RR Lyrae stars are 0.1-0.2 solar mass larger than those based on earlier opacities. Unlike the pulsation calculations, we find that the effect of opacity change on the evolution of HB stars is not significant. In particular, the effect of the mean masses of RR Lyrae stars is very small, showing a decrease of only 0.01-0.02 solar mass compared to the models based on old Cox-Stewart opacities. Consequently, with the new Livermore OPAL opacities, both the stellar pulsation and evolution models now predict approximately the same masses for the RR Lyrae stars. Our evolutionary models suggest that the mean masses of the RR Lyrae stars are about 0.76 and about 0.71 solar mass for M15 (Oosterhoff group II) and M3 (group I), respectively. If (alpha/Fe) = 0.4, these values are decreased by about 0.03 solar mass. Variations of the mean masses of RR Lyrae stars with HB morphology and metallicity are also presented.

Integrated model of multiple kernel learning and differential evolution for EUR/USD trading.

PubMed

Deng, Shangkun; Sakurai, Akito

2014-01-01

Currency trading is an important area for individual investors, government policy decisions, and organization investments. In this study, we propose a hybrid approach referred to as MKL-DE, which combines multiple kernel learning (MKL) with differential evolution (DE) for trading a currency pair. MKL is used to learn a model that predicts changes in the target currency pair, whereas DE is used to generate the buy and sell signals for the target currency pair based on the relative strength index (RSI), while it is also combined with MKL as a trading signal. The new hybrid implementation is applied to EUR/USD trading, which is the most traded foreign exchange (FX) currency pair. MKL is essential for utilizing information from multiple information sources and DE is essential for formulating a trading rule based on a mixture of discrete structures and continuous parameters. Initially, the prediction model optimized by MKL predicts the returns based on a technical indicator called the moving average convergence and divergence. Next, a combined trading signal is optimized by DE using the inputs from the prediction model and technical indicator RSI obtained from multiple timeframes. The experimental results showed that trading using the prediction learned by MKL yielded consistent profits.

National Center for Mathematics and Science - K-12 education research

Science.gov Websites

motion, calculus, statistics, genetics, evolution, astronomy, and other topics. Teacher professional ). Extensive materials developed for instruction in evolutionary biology and astronomy - using the model-based

An improved NSGA - II algorithm for mixed model assembly line balancing

NASA Astrophysics Data System (ADS)

Wu, Yongming; Xu, Yanxia; Luo, Lifei; Zhang, Han; Zhao, Xudong

2018-05-01

Aiming at the problems of assembly line balancing and path optimization for material vehicles in mixed model manufacturing system, a multi-objective mixed model assembly line (MMAL), which is based on optimization objectives, influencing factors and constraints, is established. According to the specific situation, an improved NSGA-II algorithm based on ecological evolution strategy is designed. An environment self-detecting operator, which is used to detect whether the environment changes, is adopted in the algorithm. Finally, the effectiveness of proposed model and algorithm is verified by examples in a concrete mixing system.

Fast hydrological model calibration based on the heterogeneous parallel computing accelerated shuffled complex evolution method

NASA Astrophysics Data System (ADS)

Kan, Guangyuan; He, Xiaoyan; Ding, Liuqian; Li, Jiren; Hong, Yang; Zuo, Depeng; Ren, Minglei; Lei, Tianjie; Liang, Ke

2018-01-01

Hydrological model calibration has been a hot issue for decades. The shuffled complex evolution method developed at the University of Arizona (SCE-UA) has been proved to be an effective and robust optimization approach. However, its computational efficiency deteriorates significantly when the amount of hydrometeorological data increases. In recent years, the rise of heterogeneous parallel computing has brought hope for the acceleration of hydrological model calibration. This study proposed a parallel SCE-UA method and applied it to the calibration of a watershed rainfall-runoff model, the Xinanjiang model. The parallel method was implemented on heterogeneous computing systems using OpenMP and CUDA. Performance testing and sensitivity analysis were carried out to verify its correctness and efficiency. Comparison results indicated that heterogeneous parallel computing-accelerated SCE-UA converged much more quickly than the original serial version and possessed satisfactory accuracy and stability for the task of fast hydrological model calibration.

Understanding protein evolution: from protein physics to Darwinian selection.

PubMed

Zeldovich, Konstantin B; Shakhnovich, Eugene I

2008-01-01

Efforts in whole-genome sequencing and structural proteomics start to provide a global view of the protein universe, the set of existing protein structures and sequences. However, approaches based on the selection of individual sequences have not been entirely successful at the quantitative description of the distribution of structures and sequences in the protein universe because evolutionary pressure acts on the entire organism, rather than on a particular molecule. In parallel to this line of study, studies in population genetics and phenomenological molecular evolution established a mathematical framework to describe the changes in genome sequences in populations of organisms over time. Here, we review both microscopic (physics-based) and macroscopic (organism-level) models of protein-sequence evolution and demonstrate that bridging the two scales provides the most complete description of the protein universe starting from clearly defined, testable, and physiologically relevant assumptions.

Large Eddy Simulations of Continental Boundary Layer Clouds Observed during the RACORO Field Campaign

NASA Astrophysics Data System (ADS)

Endo, S.; Fridlind, A. M.; Lin, W.; Vogelmann, A. M.; Toto, T.; Liu, Y.

2013-12-01

Three cases of boundary layer clouds are analyzed in the FAst-physics System TEstbed and Research (FASTER) project, based on continental boundary-layer-cloud observations during the RACORO Campaign [Routine Atmospheric Radiation Measurement (ARM) Aerial Facility (AAF) Clouds with Low Optical Water Depths (CLOWD) Optical Radiative Observations] at the ARM Climate Research Facility's Southern Great Plains (SGP) site. The three 60-hour case study periods are selected to capture the temporal evolution of cumulus, stratiform, and drizzling boundary-layer cloud systems under a range of conditions, intentionally including those that are relatively more mixed or transitional in nature versus being of a purely canonical type. Multi-modal and temporally varying aerosol number size distribution profiles are derived from aircraft observations. Large eddy simulations (LESs) are performed for the three case study periods using the GISS Distributed Hydrodynamic Aerosol and Radiative Modeling Application (DHARMA) model and the WRF-FASTER model, which is the Weather Research and Forecasting (WRF) model implemented with forcing ingestion and other functions to constitute a flexible LES. The two LES models commonly capture the significant transitions of cloud-topped boundary layers in the three periods: diurnal evolution of cumulus layers repeating over multiple days, nighttime evolution/daytime diminution of thick stratus, and daytime breakup of stratus and stratocumulus clouds. Simulated transitions of thermodynamic structures of the cloud-topped boundary layers are examined by balloon-borne soundings and ground-based remote sensors. Aircraft observations are then used to statistically evaluate the predicted cloud droplet number size distributions under varying aerosol and cloud conditions. An ensemble approach is used to refine the model configuration for the combined use of observations with parallel LES and single-column model simulations. See Lin et al. poster for single-column model investigation.

Evolution of chemical-specific adjustment factors (CSAF) based on recent international experience; increasing utility and facilitating regulatory acceptance.

PubMed

Bhat, Virunya S; Meek, M E Bette; Valcke, Mathieu; English, Caroline; Boobis, Alan; Brown, Richard

2017-10-01

The application of chemical-specific toxicokinetic or toxicodynamic data to address interspecies differences and human variability in the quantification of hazard has potential to reduce uncertainty and better characterize variability compared with the use of traditional default or categorically-based uncertainty factors. The present review summarizes the state-of-the-science since the introduction of the World Health Organization/International Programme on Chemical Safety (WHO/IPCS) guidance on chemical-specific adjustment factors (CSAF) in 2005 and the availability of recent applicable guidance including the WHO/IPCS guidance on physiologically-based pharmacokinetic (PBPK) modeling in 2010 as well as the U.S. EPA guidance on data-derived extrapolation factors in 2014. A summary of lessons learned from an analysis of more than 100 case studies from global regulators or published literature illustrates the utility and evolution of CSAF in regulatory decisions. Challenges in CSAF development related to the adequacy of, or confidence in, the supporting data, including verification or validation of PBPK models. The analysis also identified issues related to adequacy of CSAF documentation, such as inconsistent terminology and often limited and/or inconsistent reporting, of both supporting data and/or risk assessment context. Based on this analysis, recommendations for standardized terminology, documentation and relevant interdisciplinary research and engagement are included to facilitate the continuing evolution of CSAF development and guidance.

Erosion of volcanic ocean islands: insights from modeling, topographic analyses, and cosmogenic exposure dating

NASA Astrophysics Data System (ADS)

Huppert, K.; Perron, J. T.; Ferrier, K.; Mukhopadhyay, S.; Rosener, M.; Douglas, M.

2016-12-01

With homogeneous bedrock, dramatic rainfall gradients, paleoshorelines, and datable remnant topography, volcanic ocean islands provide an exceptional natural experiment in landscape evolution. Analyses traversing gradients in island climate and bedrock age have the potential to advance our understanding of landscape evolution in a diverse range of continental settings. However, as small, conical, dominantly subsiding, and initially highly permeable landmasses, islands are unique, and it remains unclear how these properties influence their erosional history. We use a landscape evolution model and observations from the Hawaiian island of Kaua'i and other islands to characterize the topographic evolution of volcanic ocean islands. We present new measurements of helium-3 concentrations in detrital olivine from 20 rivers on Kaua'i. These measurements indicate that minimum erosion rates over the past 3 to 48 kyr are on average 2.6 times faster than erosion rates averaged over the past 3.9 to 4.4 Myr estimated from the volume of river canyons. This apparent acceleration of erosion rates on Kaua'i is consistent with observations on other islands; erosion rates estimated from the volume of river canyons on 31 islands worldwide, combined with observations of minimal incision on young island volcanoes, suggest a progressive increase in erosion rates over the first few million years of island landscape development. Using a landscape evolution model, we perform a set of experiments to quantify the contribution of subsidence, climate change, and initial geometry to changes in island erosion rates through time. We base these experiments on the evolution of Kaua'i, and we use measured erosion rates and the observed topography to calibrate the model. We find that progressive steepening of island topography by canyon incision drives an acceleration of erosion rates over time. Increases in mean channel and hillslope gradient with island age in the global compilation suggest this may be a general trend in the topographic evolution of volcanic ocean islands.

A database perspective of the transition from single-use (ancillary-based) systems to integrated models supporting clinical care and research in a MUMPS-based system.

PubMed

Siegel, J; Kirkland, D

1991-01-01

The Composite Health Care System (CHCS), a MUMPS-based hospital information system (HIS), has evolved from the Decentralized Hospital Computer Program (DHCP) installed within VA Hospitals. The authors explore the evolution of an ancillary-based system toward an integrated model with a look at its current state and possible future. The history and relationships between orders of different types tie specific patient-related data into a logical and temporal model. Diagrams demonstrate how the database structure has evolved to support clinical needs for integration. It is suggested that a fully integrated model is capable of meeting traditional HIS needs.

Magnetic resonance imaging and image analysis for assessment of HPMC matrix tablets structural evolution in USP Apparatus 4.

PubMed

Kulinowski, Piotr; Dorożyński, Przemysław; Młynarczyk, Anna; Węglarz, Władysław P

2011-05-01

The purpose of the study was to present a methodology for the processing of Magnetic Resonance Imaging (MRI) data for the quantification of the dosage form matrix evolution during drug dissolution. The results of the study were verified by comparison with other approaches presented in literature. A commercially available, HPMC-based quetiapine fumarate tablet was studied with a 4.7T MR system. Imaging was performed inside an MRI probe-head coupled with a flow-through cell for 12 h in circulating water. The images were segmented into three regions using threshold-based segmentation algorithms due to trimodal structure of the image intensity histograms. Temporal evolution of dry glassy, swollen glassy and gel regions was monitored. The characteristic features were observed: initial high expansion rate of the swollen glassy and gel layers due to initial water uptake, dry glassy core disappearance and maximum area of swollen glassy region at 4 h, and subsequent gel layer thickness increase at the expense of swollen glassy layer. The temporal evolution of an HPMC-based tablet by means of noninvasive MRI integrated with USP Apparatus 4 was found to be consistent with both the theoretical model based on polymer disentanglement concentration and experimental VIS/FTIR studies.

Change detection of polarimetric SAR images based on the KummerU Distribution

NASA Astrophysics Data System (ADS)

Chen, Quan; Zou, Pengfei; Li, Zhen; Zhang, Ping

2014-11-01

In the society of PolSAR image segmentation, change detection and classification, the classical Wishart distribution has been used for a long time, but it especially suit to low-resolution SAR image, because in traditional sensors, only a small number of scatterers are present in each resolution cell. With the improving of SAR systems these years, the classical statistical models can therefore be reconsidered for high resolution and polarimetric information contained in the images acquired by these advanced systems. In this study, SAR image segmentation algorithm based on level-set method, added with distance regularized level-set evolution (DRLSE) is performed using Envisat/ASAR single-polarization data and Radarsat-2 polarimetric images, respectively. KummerU heterogeneous clutter model is used in the later to overcome the homogeneous hypothesis at high resolution cell. An enhanced distance regularized level-set evolution (DRLSE-E) is also applied in the later, to ensure accurate computation and stable level-set evolution. Finally, change detection based on four polarimetric Radarsat-2 time series images is carried out at Genhe area of Inner Mongolia Autonomous Region, NorthEastern of China, where a heavy flood disaster occurred during the summer of 2013, result shows the recommend segmentation method can detect the change of watershed effectively.

Physically based modeling of rainfall-triggered landslides: a case study in the Luquillo forest, Puerto Rico

NASA Astrophysics Data System (ADS)

Lepore, C.; Arnone, E.; Noto, L. V.; Sivandran, G.; Bras, R. L.

2013-09-01

This paper presents the development of a rainfall-triggered landslide module within an existing physically based spatially distributed ecohydrologic model. The model, tRIBS-VEGGIE (Triangulated Irregular Networks-based Real-time Integrated Basin Simulator and Vegetation Generator for Interactive Evolution), is capable of a sophisticated description of many hydrological processes; in particular, the soil moisture dynamics are resolved at a temporal and spatial resolution required to examine the triggering mechanisms of rainfall-induced landslides. The validity of the tRIBS-VEGGIE model to a tropical environment is shown with an evaluation of its performance against direct observations made within the study area of Luquillo Forest. The newly developed landslide module builds upon the previous version of the tRIBS landslide component. This new module utilizes a numerical solution to the Richards' equation (present in tRIBS-VEGGIE but not in tRIBS), which better represents the time evolution of soil moisture transport through the soil column. Moreover, the new landslide module utilizes an extended formulation of the factor of safety (FS) to correctly quantify the role of matric suction in slope stability and to account for unsaturated conditions in the evaluation of FS. The new modeling framework couples the capabilities of the detailed hydrologic model to describe soil moisture dynamics with the infinite slope model, creating a powerful tool for the assessment of rainfall-triggered landslide risk.

Global Evolution of Plasmaspheric Plasma: Spacecraft-Model Reconstructions

NASA Astrophysics Data System (ADS)

Walsh, B.; Welling, D. T.; Morley, S.

2017-12-01

During times of geomagnetic disturbance, material from the plasmasphere will move radially outward into the magnetosphere. Once introduced to the outer magnetosphere, this material has been shown to impact a variety of plasma populations as well as the coupling of energy from the solar wind into the magnetosphere and ionosphere. The magnitude of any of these effects is inherently linked to the density and evolution of the plasmaspheric plasma. Much of our idea of how this population behaves in the outer-magnetosphere is however based on statistical pictures and model results. Here, in-situ measurements from 10 spacecraft are used to constrain a coupled, global numerical modeling in order to identify true spatial extents, time histories, and densities of the plasmasphere and plumes in the outer magnetosphere.

Modelling the public opinion transmission on social networks under opinion leaders

NASA Astrophysics Data System (ADS)

Li, Zuozhi; Li, Meng; Ji, Wanwan

2017-06-01

In this paper, based on Social Network Analysis (SNA), the social network model of opinion leaders influencing the public opinion transmission is explored. The hot event, A Female Driver Was Beaten Due To Lane Change, has characteristics of individual short-term and non-government intervention, which is used to data extraction, and formed of the network structure on opinion leaders influencing the public opinion transmission. And the evolution mechanism are analyzed in the three evolutionary situations. Opinion leaders influence micro-blogging public opinion on social network evolution model shows that this type of network public opinion transmission is largely constrained by opinion leaders, so the opinion leaders behavior supervising on the spread of this public opinion is pivotal, and which has a guiding significance.

Crystal plasticity modeling of irradiation growth in Zircaloy-2

DOE PAGES

Patra, Anirban; Tome, Carlos; Golubov, Stanislav I.

2017-05-10

A reaction-diffusion based mean field rate theory model is implemented in the viscoplastic self-consistent (VPSC) crystal plasticity framework to simulate irradiation growth in hcp Zr and its alloys. A novel scheme is proposed to model the evolution (both number density and radius) of irradiation-induced dislocation loops that can be informed directly from experimental data of dislocation density evolution during irradiation. This framework is used to predict the irradiation growth behavior of cold-worked Zircaloy-2 and trends compared to available experimental data. The role of internal stresses in inducing irradiation creep is discussed. Effects of grain size, texture, and external stress onmore » the coupled irradiation growth and creep behavior are also studied.« less

Crystal plasticity modeling of irradiation growth in Zircaloy-2

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

Patra, Anirban; Tome, Carlos; Golubov, Stanislav I.

A reaction-diffusion based mean field rate theory model is implemented in the viscoplastic self-consistent (VPSC) crystal plasticity framework to simulate irradiation growth in hcp Zr and its alloys. A novel scheme is proposed to model the evolution (both number density and radius) of irradiation-induced dislocation loops that can be informed directly from experimental data of dislocation density evolution during irradiation. This framework is used to predict the irradiation growth behavior of cold-worked Zircaloy-2 and trends compared to available experimental data. The role of internal stresses in inducing irradiation creep is discussed. Effects of grain size, texture, and external stress onmore » the coupled irradiation growth and creep behavior are also studied.« less

A 1-D evolutionary model for icy satellites, applied to Enceladus

NASA Astrophysics Data System (ADS)

Malamud, Uri; Prialnik, Dina

2016-04-01

We develop a long-term 1-D evolution model for icy satellites that couples multiple processes: water migration and differentiation, geochemical reactions and silicate phase transitions, compaction by self-gravity, and ablation. The model further considers the following energy sources and sinks: tidal heating, radiogenic heating, geochemical energy released by serpentinization or absorbed by mineral dehydration, gravitational energy and insolation, and heat transport by conduction, convection, and advection. We apply the model to Enceladus, by guessing the initial conditions that would render a structure compatible with present-day observations, assuming the initial structure to have been homogeneous. Assuming the satellite has been losing water continually along its evolution, we postulate that it was formed as a more massive, more icy and more porous satellite, and gradually transformed into its present day state due to sustained long-term tidal heating. We consider several initial compositions and evolution scenarios and follow the evolution for the age of the Solar System, testing the present day model results against the available observational constraints. Our model shows the present configuration to be differentiated into a pure icy mantle, several tens of km thick, overlying a rocky core, composed of dehydrated rock at the center and hydrated rock in the outer part. For Enceladus, it predicts a higher rock/ice mass ratio than previously assumed and a thinner ice mantle, compatible with recent estimates based on gravity field measurements. Although, obviously, the model cannot be used to explain local phenomena, it sheds light on the internal structure invoked in explanations of localized features and activities.

System crash as dynamics of complex networks.

PubMed

Yu, Yi; Xiao, Gaoxi; Zhou, Jie; Wang, Yubo; Wang, Zhen; Kurths, Jürgen; Schellnhuber, Hans Joachim

2016-10-18

Complex systems, from animal herds to human nations, sometimes crash drastically. Although the growth and evolution of systems have been extensively studied, our understanding of how systems crash is still limited. It remains rather puzzling why some systems, appearing to be doomed to fail, manage to survive for a long time whereas some other systems, which seem to be too big or too strong to fail, crash rapidly. In this contribution, we propose a network-based system dynamics model, where individual actions based on the local information accessible in their respective system structures may lead to the "peculiar" dynamics of system crash mentioned above. Extensive simulations are carried out on synthetic and real-life networks, which further reveal the interesting system evolution leading to the final crash. Applications and possible extensions of the proposed model are discussed.

Dynamical graph theory networks techniques for the analysis of sparse connectivity networks in dementia

NASA Astrophysics Data System (ADS)

Tahmassebi, Amirhessam; Pinker-Domenig, Katja; Wengert, Georg; Lobbes, Marc; Stadlbauer, Andreas; Romero, Francisco J.; Morales, Diego P.; Castillo, Encarnacion; Garcia, Antonio; Botella, Guillermo; Meyer-Bäse, Anke

2017-05-01

Graph network models in dementia have become an important computational technique in neuroscience to study fundamental organizational principles of brain structure and function of neurodegenerative diseases such as dementia. The graph connectivity is reflected in the connectome, the complete set of structural and functional connections of the graph network, which is mostly based on simple Pearson correlation links. In contrast to simple Pearson correlation networks, the partial correlations (PC) only identify direct correlations while indirect associations are eliminated. In addition to this, the state-of-the-art techniques in brain research are based on static graph theory, which is unable to capture the dynamic behavior of the brain connectivity, as it alters with disease evolution. We propose a new research avenue in neuroimaging connectomics based on combining dynamic graph network theory and modeling strategies at different time scales. We present the theoretical framework for area aggregation and time-scale modeling in brain networks as they pertain to disease evolution in dementia. This novel paradigm is extremely powerful, since we can derive both static parameters pertaining to node and area parameters, as well as dynamic parameters, such as system's eigenvalues. By implementing and analyzing dynamically both disease driven PC-networks and regular concentration networks, we reveal differences in the structure of these network that play an important role in the temporal evolution of this disease. The described research is key to advance biomedical research on novel disease prediction trajectories and dementia therapies.

Range of interaction in an opinion evolution model of ideological self-positioning: Contagion, hesitance and polarization

NASA Astrophysics Data System (ADS)

Gimenez, M. Cecilia; Paz García, Ana Pamela; Burgos Paci, Maxi A.; Reinaudi, Luis

2016-04-01

The evolution of public opinion using tools and concepts borrowed from Statistical Physics is an emerging area within the field of Sociophysics. In the present paper, a Statistical Physics model was developed to study the evolution of the ideological self-positioning of an ensemble of agents. The model consists of an array of L components, each one of which represents the ideology of an agent. The proposed mechanism is based on the ;voter model;, in which one agent can adopt the opinion of another one if the difference of their opinions lies within a certain range. The existence of ;undecided; agents (i.e. agents with no definite opinion) was implemented in the model. The possibility of radicalization of an agent's opinion upon interaction with another one was also implemented. The results of our simulations are compared to statistical data taken from the Latinobarómetro databank for the cases of Argentina, Chile, Brazil and Uruguay in the last decade. Among other results, the effect of taking into account the undecided agents is the formation of a single peak at the middle of the ideological spectrum (which corresponds to a centrist ideological position), in agreement with the real cases studied.

A Monte Carlo model for 3D grain evolution during welding

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

Rodgers, Theron M.; Mitchell, John A.; Tikare, Veena

Welding is one of the most wide-spread processes used in metal joining. However, there are currently no open-source software implementations for the simulation of microstructural evolution during a weld pass. Here we describe a Potts Monte Carlo based model implemented in the SPPARKS kinetic Monte Carlo computational framework. The model simulates melting, solidification and solid-state microstructural evolution of material in the fusion and heat-affected zones of a weld. The model does not simulate thermal behavior, but rather utilizes user input parameters to specify weld pool and heat-affect zone properties. Weld pool shapes are specified by Bezier curves, which allow formore » the specification of a wide range of pool shapes. Pool shapes can range from narrow and deep to wide and shallow representing different fluid flow conditions within the pool. Surrounding temperature gradients are calculated with the aide of a closest point projection algorithm. Furthermore, the model also allows simulation of pulsed power welding through time-dependent variation of the weld pool size. Example simulation results and comparisons with laboratory weld observations demonstrate microstructural variation with weld speed, pool shape, and pulsed-power.« less

Mesoscale Thermodynamically motivated Statistical Mechanics based Kinetic Model for Sintering monoliths

NASA Astrophysics Data System (ADS)

Mohan, Nisha

Modeling the evolution of microstructure during sintering is a persistent challenge in ceramics science, although needed as the microstructure impacts properties of an engineered material. Bridging the gap between microscopic and continuum models, kinetic Monte Carlo (kMC) methods provide a stochastic approach towards sintering and microstructure evolution. These kMC models work at the mesoscale, with length and time-scales between those of atomistic and continuum approaches. We develop a sintering/compacting model for the two-phase sintering of boron nitride ceramics and allotropes alike. Our formulation includes mechanisms for phase transformation between h-BN and c-BN and takes into account thermodynamics of pressure and temperature on interaction energies and mechanism rates. In addition to replicating the micro-structure evolution observed in experiments, it also captures the phase diagram of Boron Nitride materials. Results have been analyzed in terms of phase diagrams and crystal growth. It also serves with insights to guide the choice of additives and conditions for the sintering process.While detailed time and spatial resolutions are lost in any MC, the progression of stochastic events still captures plausible local energy minima and long-time temporal developments. DARPA.

A Monte Carlo model for 3D grain evolution during welding

DOE PAGES

Rodgers, Theron M.; Mitchell, John A.; Tikare, Veena

2017-08-04

Welding is one of the most wide-spread processes used in metal joining. However, there are currently no open-source software implementations for the simulation of microstructural evolution during a weld pass. Here we describe a Potts Monte Carlo based model implemented in the SPPARKS kinetic Monte Carlo computational framework. The model simulates melting, solidification and solid-state microstructural evolution of material in the fusion and heat-affected zones of a weld. The model does not simulate thermal behavior, but rather utilizes user input parameters to specify weld pool and heat-affect zone properties. Weld pool shapes are specified by Bezier curves, which allow formore » the specification of a wide range of pool shapes. Pool shapes can range from narrow and deep to wide and shallow representing different fluid flow conditions within the pool. Surrounding temperature gradients are calculated with the aide of a closest point projection algorithm. Furthermore, the model also allows simulation of pulsed power welding through time-dependent variation of the weld pool size. Example simulation results and comparisons with laboratory weld observations demonstrate microstructural variation with weld speed, pool shape, and pulsed-power.« less

Evolution of the PWWP-domain encoding genes in the plant and animal lineages

PubMed Central

2012-01-01

Background Conserved domains are recognized as the building blocks of eukaryotic proteins. Domains showing a tendency to occur in diverse combinations (‘promiscuous’ domains) are involved in versatile architectures in proteins with different functions. Current models, based on global-level analyses of domain combinations in multiple genomes, have suggested that the propensity of some domains to associate with other domains in high-level architectures increases with organismal complexity. Alternative models using domain-based phylogenetic trees propose that domains have become promiscuous independently in different lineages through convergent evolution and are, thus, random with no functional or structural preferences. Here we test whether complex protein architectures have occurred by accretion from simpler systems and whether the appearance of multidomain combinations parallels organismal complexity. As a model, we analyze the modular evolution of the PWWP domain and ask whether its appearance in combinations with other domains into multidomain architectures is linked with the occurrence of more complex life-forms. Whether high-level combinations of domains are conserved and transmitted as stable units (cassettes) through evolution is examined in the genomes of plant or metazoan species selected for their established position in the evolution of the respective lineages. Results Using the domain-tree approach, we analyze the evolutionary origins and distribution patterns of the promiscuous PWWP domain to understand the principles of its modular evolution and its existence in combination with other domains in higher-level protein architectures. We found that as a single module the PWWP domain occurs only in proteins with a limited, mainly, species-specific distribution. Earlier, it was suggested that domain promiscuity is a fast-changing (volatile) feature shaped by natural selection and that only a few domains retain their promiscuity status throughout evolution. In contrast, our data show that most of the multidomain PWWP combinations in extant multicellular organisms (humans or land plants) are present in their unicellular ancestral relatives suggesting they have been transmitted through evolution as conserved linear arrangements (‘cassettes’). Among the most interesting biologically relevant results is the finding that the genes of the two plant Trithorax family subgroups (ATX1/2 and ATX3/4/5) have different phylogenetic origins. The two subgroups occur together in the earliest land plants Physcomitrella patens and Selaginella moellendorffii. Conclusion Gain/loss of a single PWWP domain is observed throughout evolution reflecting dynamic lineage- or species-specific events. In contrast, higher-level protein architectures involving the PWWP domain have survived as stable arrangements driven by evolutionary descent. The association of PWWP domains with the DNA methyltransferases in O. tauri and in the metazoan lineage seems to have occurred independently consistent with convergent evolution. Our results do not support models wherein more complex protein architectures involving the PWWP domain occur with the appearance of more evolutionarily advanced life forms. PMID:22734652

Rate and State Friction Relation for Nanoscale Contacts: Thermally Activated Prandtl-Tomlinson Model with Chemical Aging

NASA Astrophysics Data System (ADS)

Tian, Kaiwen; Goldsby, David L.; Carpick, Robert W.

2018-05-01

Rate and state friction (RSF) laws are widely used empirical relationships that describe macroscale to microscale frictional behavior. They entail a linear combination of the direct effect (the increase of friction with sliding velocity due to the reduced influence of thermal excitations) and the evolution effect (the change in friction with changes in contact "state," such as the real contact area or the degree of interfacial chemical bonds). Recent atomic force microscope (AFM) experiments and simulations found that nanoscale single-asperity amorphous silica-silica contacts exhibit logarithmic aging (increasing friction with time) over several decades of contact time, due to the formation of interfacial chemical bonds. Here we establish a physically based RSF relation for such contacts by combining the thermally activated Prandtl-Tomlinson (PTT) model with an evolution effect based on the physics of chemical aging. This thermally activated Prandtl-Tomlinson model with chemical aging (PTTCA), like the PTT model, uses the loading point velocity for describing the direct effect, not the tip velocity (as in conventional RSF laws). Also, in the PTTCA model, the combination of the evolution and direct effects may be nonlinear. We present AFM data consistent with the PTTCA model whereby in aging tests, for a given hold time, static friction increases with the logarithm of the loading point velocity. Kinetic friction also increases with the logarithm of the loading point velocity at sufficiently high velocities, but at a different increasing rate. The discrepancy between the rates of increase of static and kinetic friction with velocity arises from the fact that appreciable aging during static contact changes the energy landscape. Our approach extends the PTT model, originally used for crystalline substrates, to amorphous materials. It also establishes how conventional RSF laws can be modified for nanoscale single-asperity contacts to provide a physically based friction relation for nanoscale contacts that exhibit chemical bond-induced aging, as well as other aging mechanisms with similar physical characteristics.

Modelling the temperature evolution of bone under high intensity focused ultrasound

NASA Astrophysics Data System (ADS)

ten Eikelder, H. M. M.; Bošnački, D.; Elevelt, A.; Donato, K.; Di Tullio, A.; Breuer, B. J. T.; van Wijk, J. H.; van Dijk, E. V. M.; Modena, D.; Yeo, S. Y.; Grüll, H.

2016-02-01

Magnetic resonance-guided high intensity focused ultrasound (MR-HIFU) has been clinically shown to be effective for palliative pain management in patients suffering from skeletal metastasis. The underlying mechanism is supposed to be periosteal denervation caused by ablative temperatures reached through ultrasound heating of the cortex. The challenge is exact temperature control during sonication as MR-based thermometry approaches for bone tissue are currently not available. Thus, in contrast to the MR-HIFU ablation of soft tissue, a thermometry feedback to the HIFU is lacking, and the treatment of bone metastasis is entirely based on temperature information acquired in the soft tissue adjacent to the bone surface. However, heating of the adjacent tissue depends on the exact sonication protocol and requires extensive modelling to estimate the actual temperature of the cortex. Here we develop a computational model to calculate the spatial temperature evolution in bone and the adjacent tissue during sonication. First, a ray-tracing technique is used to compute the heat production in each spatial point serving as a source term for the second part, where the actual temperature is calculated as a function of space and time by solving the Pennes bio-heat equation. Importantly, our model includes shear waves that arise at the bone interface as well as all geometrical considerations of transducer and bone geometry. The model was compared with a theoretical approach based on the far field approximation and an MR-HIFU experiment using a bone phantom. Furthermore, we investigated the contribution of shear waves to the heat production and resulting temperatures in bone. The temperature evolution predicted by our model was in accordance with the far field approximation and agreed well with the experimental data obtained in phantoms. Our model allows the simulation of the HIFU treatments of bone metastasis in patients and can be extended to a planning tool prior to MR-HIFU treatments.

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.

Synergy from reproductive division of labor and genetic complexity drive the evolution of sex.

PubMed

Jaffe, Klaus

2018-04-16

Computer experiments that mirror the evolutionary dynamics of sexual and asexual organisms as they occur in nature were used to test features proposed to explain the evolution of sexual recombination. Results show that this evolution is better described as a network of interactions between possible sexual forms, including diploidy, thelytoky, facultative sex, assortation, bisexuality, and division of labor between the sexes, rather than a simple transition from parthenogenesis to sexual recombination. Diploidy was shown to be fundamental for the evolution of sex; bisexual reproduction emerged only among anisogamic diploids with a synergistic division of reproductive labor; and facultative sex was more likely to evolve among haploids practicing assortative mating. Looking at the evolution of sex as a complex system through individual-based simulations explains better the diversity of sexual strategies known to exist in nature, compared to classical analytical models.

A Replicable, Zero-Based Model for Marketing Curriculum Innovation

ERIC Educational Resources Information Center

Borin, Norm; Metcalf, Lynn E.; Tietje, Brian C.

2007-01-01

As university curriculums inevitably change, their evolution typically occurs through a series of minor incremental adjustments to individual courses that cause the curriculum to lose strategic consistency and focus. This article demonstrates a zero-based approach to marketing curriculum innovation. The authors describe forces of change that led…

Analyzing endocrine system conservation and evolution.

PubMed

Bonett, Ronald M

2016-08-01

Analyzing variation in rates of evolution can provide important insights into the factors that constrain trait evolution, as well as those that promote diversification. Metazoan endocrine systems exhibit apparent variation in evolutionary rates of their constituent components at multiple levels, yet relatively few studies have quantified these patterns and analyzed them in a phylogenetic context. This may be in part due to historical and current data limitations for many endocrine components and taxonomic groups. However, recent technological advancements such as high-throughput sequencing provide the opportunity to collect large-scale comparative data sets for even non-model species. Such ventures will produce a fertile data landscape for evolutionary analyses of nucleic acid and amino acid based endocrine components. Here I summarize evolutionary rate analyses that can be applied to categorical and continuous endocrine traits, and also those for nucleic acid and protein-based components. I emphasize analyses that could be used to test whether other variables (e.g., ecology, ontogenetic timing of expression, etc.) are related to patterns of rate variation and endocrine component diversification. The application of phylogenetic-based rate analyses to comparative endocrine data will greatly enhance our understanding of the factors that have shaped endocrine system evolution. Copyright © 2016 Elsevier Inc. All rights reserved.

Hybrid evolutionary computing model for mobile agents of wireless Internet multimedia

NASA Astrophysics Data System (ADS)

Hortos, William S.

2001-03-01

The ecosystem is used as an evolutionary paradigm of natural laws for the distributed information retrieval via mobile agents to allow the computational load to be added to server nodes of wireless networks, while reducing the traffic on communication links. Based on the Food Web model, a set of computational rules of natural balance form the outer stage to control the evolution of mobile agents providing multimedia services with a wireless Internet protocol WIP. The evolutionary model shows how mobile agents should behave with the WIP, in particular, how mobile agents can cooperate, compete and learn from each other, based on an underlying competition for radio network resources to establish the wireless connections to support the quality of service QoS of user requests. Mobile agents are also allowed to clone themselves, propagate and communicate with other agents. A two-layer model is proposed for agent evolution: the outer layer is based on the law of natural balancing, the inner layer is based on a discrete version of a Kohonen self-organizing feature map SOFM to distribute network resources to meet QoS requirements. The former is embedded in the higher OSI layers of the WIP, while the latter is used in the resource management procedures of Layer 2 and 3 of the protocol. Algorithms for the distributed computation of mobile agent evolutionary behavior are developed by adding a learning state to the agent evolution state diagram. When an agent is in an indeterminate state, it can communicate to other agents. Computing models can be replicated from other agents. Then the agents transitions to the mutating state to wait for a new information-retrieval goal. When a wireless terminal or station lacks a network resource, an agent in the suspending state can change its policy to submit to the environment before it transitions to the searching state. The agents learn the facts of agent state information entered into an external database. In the cloning process, two agents on a host station sharing a common goal can be merged or married to compose a new agent. Application of the two-layer set of algorithms for mobile agent evolution, performed in a distributed processing environment, is made to the QoS management functions of the IP multimedia IM sub-network of the third generation 3G Wideband Code-division Multiple Access W-CDMA wireless network.