Further experimentation on bubble generation during transformer overload

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

Oommen, T.V.

1992-03-01

This report covers additional work done during 1990 and 1991 on gas bubble generation under overload conditions. To improve visual bubble detection, a single disc coil was used. To further improve detection, a corona device was also used which signaled the onset of corona activity in the early stages of bubble formation. A total of fourteen model tests were conducted, half of which used the Inertaire system, and the remaining, a conservator (COPS). Moisture content of paper in the coil varied from 1.0% to 8.0%; gas (nitrogen) content varied from 1.0% to 8.8%. The results confirmed earlier observations that themore » mathematical bubble prediction model was not valid for high gas content model with relatively low moisture levels in the coil. An empirical relationship was formulated to accurately predict bubble evolution temperatures from known moisture and gas content values. For low moisture content models (below 2%), the simple Piper relationship was sufficient to predict bubble evolution temperatures, regardless of gas content. Moisture in the coil appears to be the key factor in bubble generation. Gas blanketed (Inertaire) systems do not appear to be prone to premature bubble generation from overloads as previously thought. The new bubble prediction model reveals that for a coil with 2% moisture, the bubble evolution temperature would be about 140{degrees}C. Since old transformers in service may have as much as 2% moisture in paper, the 140{degrees}C bubble evolution temperature may be taken as the lower limit of bubble evolution temperature under overload conditions for operating transformers. Drier insulation would raise the bubble evolution temperature.« less

A theoretical model and phase field simulation on the evolution of interface roughness in the oxidation process

NASA Astrophysics Data System (ADS)

Yang, Fan; Fang, Dai-Ning; Liu, Bin

2012-01-01

An oxidation kinetics model is developed to account for the effects of the oxidation interface curvature and the oxidation-induced volume change or Pilling-Bedworth ratio. For the oxidation of Fe-Cr-Al-Y alloy fiber, the predictions agree well with experimental results. By considering the influence of the oxidation interface curvature on oxidation rates, the evolution of fluctuant oxidation interface is predicted. We also developed the phase field method (PFM) to simulate the evolution of the interface roughness. Both the theoretical model and the PFM results show that the interface will become smooth during high temperature oxidation. Stress distribution and evolution are calculated by PFM, which indicates that the stress level decreases as the interface morphology evolves.

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

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

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.

Predictive Modeling of Polymer Mechanical Behavior Coupled to Chemical Change/ Technique Development for Measuring Polymer Physical Aging.

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

Kropka, Jamie Michael; Stavig, Mark E.; Arechederra, Gabe Kenneth

Develop an understanding of the evolution of glassy polymer mechanical response during aging and the mechanisms associated with that evolution. That understanding will be used to develop constitutive models to assess the impact of stress evolution in encapsulants on NW designs.

A life prediction model for laminated composite structural components

NASA Technical Reports Server (NTRS)

Allen, David H.

1990-01-01

A life prediction methodology for laminated continuous fiber composites subjected to fatigue loading conditions was developed. A summary is presented of research completed. A phenomenological damage evolution law was formulated for matrix cracking which is independent of stacking sequence. Mechanistic and physical support was developed for the phenomenological evolution law proposed above. The damage evolution law proposed above was implemented to a finite element computer program. And preliminary predictions were obtained for a structural component undergoing fatigue loading induced damage.

Phase-field Model for Interstitial Loop Growth Kinetics and Thermodynamic and Kinetic Models of Irradiated Fe-Cr Alloys

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

Li, Yulan; Hu, Shenyang Y.; Sun, Xin

2011-06-15

Microstructure evolution kinetics in irradiated materials has strongly spatial correlation. For example, void and second phases prefer to nucleate and grow at pre-existing defects such as dislocations, grain boundaries, and cracks. Inhomogeneous microstructure evolution results in inhomogeneity of microstructure and thermo-mechanical properties. Therefore, the simulation capability for predicting three dimensional (3-D) microstructure evolution kinetics and its subsequent impact on material properties and performance is crucial for scientific design of advanced nuclear materials and optimal operation conditions in order to reduce uncertainty in operational and safety margins. Very recently the meso-scale phase-field (PF) method has been used to predict gas bubblemore » evolution, void swelling, void lattice formation and void migration in irradiated materials,. Although most results of phase-field simulations are qualitative due to the lake of accurate thermodynamic and kinetic properties of defects, possible missing of important kinetic properties and processes, and the capability of current codes and computers for large time and length scale modeling, the simulations demonstrate that PF method is a promising simulation tool for predicting 3-D heterogeneous microstructure and property evolution, and providing microstructure evolution kinetics for higher scale level simulations of microstructure and property evolution such as mean field methods. This report consists of two parts. In part I, we will present a new phase-field model for predicting interstitial loop growth kinetics in irradiated materials. The effect of defect (vacancy/interstitial) generation, diffusion and recombination, sink strength, long-range elastic interaction, inhomogeneous and anisotropic mobility on microstructure evolution kinetics is taken into account in the model. The model is used to study the effect of elastic interaction on interstitial loop growth kinetics, the interstitial flux, and sink strength of interstitial loop for interstitials. In part II, we present a generic phase field model and discuss the thermodynamic and kinetic properties in phase-field models including the reaction kinetics of radiation defects and local free energy of irradiated materials. In particular, a two-sublattice thermodynamic model is suggested to describe the local free energy of alloys with irradiated defects. Fe-Cr alloy is taken as an example to explain the required thermodynamic and kinetic properties for quantitative phase-field modeling. Finally the great challenges in phase-field modeling will be discussed.« less

Bubble generation during transformer overload

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

Oommen, T.V.

1990-03-01

Bubble generation in transformers has been demonstrated under certain overload conditions. The release of large quantities of bubbles would pose a dielectric breakdown hazard. A bubble prediction model developed under EPRI Project 1289-4 attempts to predict the bubble evolution temperature under different overload conditions. This report details a verification study undertaken to confirm the validity of the above model using coil structures subjected to overload conditions. The test variables included moisture in paper insulation, gas content in oil, and the type of oil preservation system. Two aged coils were also tested. The results indicated that the observed bubble temperatures weremore » close to the predicted temperatures for models with low initial gas content in the oil. The predicted temperatures were significantly lower than the observed temperatures for models with high gas content. Some explanations are provided for the anomalous behavior at high gas levels in oil. It is suggested that the dissolved gas content is not a significant factor in bubble evolution. The dominant factor in bubble evolution appears to be the water vapor pressure which must reach critical levels before bubbles can be released. Further study is needed to make a meaningful revision of the bubble prediction model. 8 refs., 13 figs., 11 tabs.« less

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.

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.

The impact of fishing-induced mortality on the evolution of alternative life-history tactics in brook charr

PubMed Central

Thériault, Véronique; Dunlop, Erin S; Dieckmann, Ulf; Bernatchez, Louis; Dodson, Julian J

2008-01-01

Although contemporary trends indicative of evolutionary change have been detected in the life-history traits of exploited populations, it is not known to what extent fishing influences the evolution of alternative life-history tactics in migratory species such as salmonids. Here, we build a model to predict the evolution of anadromy and residency in an exploited population of brook charr, Salvelinus fontinalis. Our model allows for both phenotypic plasticity and genetic change in the age and size at migration by including migration reaction norms. Using this model, we predict that fishing of anadromous individuals over the course of 100 years causes evolution in the migration reaction norm, resulting in a decrease in average probabilities of migration with increasing harvest rate. Moreover, we show that differences in natural mortalities in freshwater greatly influence the magnitude and rate of evolutionary change. The fishing-induced changes in migration predicted by our model alter population abundances and reproductive output and should be accounted for in the sustainable management of salmonids. PMID:25567640

No cataclysmic variables missing: higher merger rate brings into agreement observed and predicted space densities

NASA Astrophysics Data System (ADS)

Belloni, Diogo; Schreiber, Matthias R.; Zorotovic, Mónica; Iłkiewicz, Krystian; Hurley, Jarrod R.; Giersz, Mirek; Lagos, Felipe

2018-06-01

The predicted and observed space density of cataclysmic variables (CVs) have been for a long time discrepant by at least an order of magnitude. The standard model of CV evolution predicts that the vast majority of CVs should be period bouncers, whose space density has been recently measured to be ρ ≲ 2 × 10-5 pc-3. We performed population synthesis of CVs using an updated version of the Binary Stellar Evolution (BSE) code for single and binary star evolution. We find that the recently suggested empirical prescription of consequential angular momentum loss (CAML) brings into agreement predicted and observed space densities of CVs and period bouncers. To progress with our understanding of CV evolution it is crucial to understand the physical mechanism behind empirical CAML. Our changes to the BSE code are also provided in details, which will allow the community to accurately model mass transfer in interacting binaries in which degenerate objects accrete from low-mass main-sequence donor stars.

Further experimentation on bubble generation during transformer overload. Final report

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

Oommen, T.V.

1992-03-01

This report covers additional work done during 1990 and 1991 on gas bubble generation under overload conditions. To improve visual bubble detection, a single disc coil was used. To further improve detection, a corona device was also used which signaled the onset of corona activity in the early stages of bubble formation. A total of fourteen model tests were conducted, half of which used the Inertaire system, and the remaining, a conservator (COPS). Moisture content of paper in the coil varied from 1.0% to 8.0%; gas (nitrogen) content varied from 1.0% to 8.8%. The results confirmed earlier observations that themore » mathematical bubble prediction model was not valid for high gas content model with relatively low moisture levels in the coil. An empirical relationship was formulated to accurately predict bubble evolution temperatures from known moisture and gas content values. For low moisture content models (below 2%), the simple Piper relationship was sufficient to predict bubble evolution temperatures, regardless of gas content. Moisture in the coil appears to be the key factor in bubble generation. Gas blanketed (Inertaire) systems do not appear to be prone to premature bubble generation from overloads as previously thought. The new bubble prediction model reveals that for a coil with 2% moisture, the bubble evolution temperature would be about 140{degrees}C. Since old transformers in service may have as much as 2% moisture in paper, the 140{degrees}C bubble evolution temperature may be taken as the lower limit of bubble evolution temperature under overload conditions for operating transformers. Drier insulation would raise the bubble evolution temperature.« less

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.

A generalised individual-based algorithm for modelling the evolution of quantitative herbicide resistance in arable weed populations.

PubMed

Liu, Chun; Bridges, Melissa E; Kaundun, Shiv S; Glasgow, Les; Owen, Micheal Dk; Neve, Paul

2017-02-01

Simulation models are useful tools for predicting and comparing the risk of herbicide resistance in weed populations under different management strategies. Most existing models assume a monogenic mechanism governing herbicide resistance evolution. However, growing evidence suggests that herbicide resistance is often inherited in a polygenic or quantitative fashion. Therefore, we constructed a generalised modelling framework to simulate the evolution of quantitative herbicide resistance in summer annual weeds. Real-field management parameters based on Amaranthus tuberculatus (Moq.) Sauer (syn. rudis) control with glyphosate and mesotrione in Midwestern US maize-soybean agroecosystems demonstrated that the model can represent evolved herbicide resistance in realistic timescales. Sensitivity analyses showed that genetic and management parameters were impactful on the rate of quantitative herbicide resistance evolution, whilst biological parameters such as emergence and seed bank mortality were less important. The simulation model provides a robust and widely applicable framework for predicting the evolution of quantitative herbicide resistance in summer annual weed populations. The sensitivity analyses identified weed characteristics that would favour herbicide resistance evolution, including high annual fecundity, large resistance phenotypic variance and pre-existing herbicide resistance. Implications for herbicide resistance management and potential use of the model are discussed. © 2016 Society of Chemical Industry. © 2016 Society of Chemical Industry.

Biophysics, environmental stochasticity, and the evolution of thermal safety margins in intertidal limpets.

PubMed

Denny, M W; Dowd, W W

2012-03-15

As the air temperature of the Earth rises, ecological relationships within a community might shift, in part due to differences in the thermal physiology of species. Prediction of these shifts - an urgent task for ecologists - will be complicated if thermal tolerance itself can rapidly evolve. Here, we employ a mechanistic approach to predict the potential for rapid evolution of thermal tolerance in the intertidal limpet Lottia gigantea. Using biophysical principles to predict body temperature as a function of the state of the environment, and an environmental bootstrap procedure to predict how the environment fluctuates through time, we create hypothetical time-series of limpet body temperatures, which are in turn used as a test platform for a mechanistic evolutionary model of thermal tolerance. Our simulations suggest that environmentally driven stochastic variation of L. gigantea body temperature results in rapid evolution of a substantial 'safety margin': the average lethal limit is 5-7°C above the average annual maximum temperature. This predicted safety margin approximately matches that found in nature, and once established is sufficient, in our simulations, to allow some limpet populations to survive a drastic, century-long increase in air temperature. By contrast, in the absence of environmental stochasticity, the safety margin is dramatically reduced. We suggest that the risk of exceeding the safety margin, rather than the absolute value of the safety margin, plays an underappreciated role in the evolution of thermal tolerance. Our predictions are based on a simple, hypothetical, allelic model that connects genetics to thermal physiology. To move beyond this simple model - and thereby potentially to predict differential evolution among populations and among species - will require significant advances in our ability to translate the details of thermal histories into physiological and population-genetic consequences.

The structure of common-envelope remnants

NASA Astrophysics Data System (ADS)

Hall, Philip D.

2015-05-01

We investigate the structure and evolution of the remnants of common-envelope evolution in binary star systems. In a common-envelope phase, two stars become engulfed in a gaseous envelope and, under the influence of drag forces, spiral to smaller separations. They may merge to form a single star or the envelope may be ejected to leave the stars in a shorter period orbit. This process explains the short orbital periods of many observed binary systems, such as cataclysmic variables and low-mass X-ray binary systems. Despite the importance of these systems, and of common-envelope evolution to their formation, it remains poorly understood. Specifically, we are unable to confidently predict the outcome of a common-envelope phase from the properties at its onset. After presenting a review of work on stellar evolution, binary systems, common-envelope evolution and the computer programs used, we describe the results of three computational projects on common-envelope evolution. Our work specifically relates to the methods and prescriptions which are used for predicting the outcome. We use the Cambridge stellar-evolution code STARS to produce detailed models of the structure and evolution of remnants of common-envelope evolution. We compare different assumptions about the uncertain end-of-common envelope structure and envelope mass of remnants which successfully eject their common envelopes. In the first project, we use detailed remnant models to investigate whether planetary nebulae are predicted after common-envelope phases initiated by low-mass red giants. We focus on the requirement that a remnant evolves rapidly enough to photoionize the nebula and compare the predictions for different ideas about the structure at the end of a common-envelope phase. We find that planetary nebulae are possible for some prescriptions for the end-of-common envelope structure. In our second contribution, we compute a large set of single-star models and fit new formulae to the core radii of evolved stars. These formulae can be used to better compute the outcome of common-envelope evolution with rapid evolution codes. We find that the new formulae are necessary for accurate predictions of the properties of post-common envelope systems. Finally, we use detailed remnant models of massive stars to investigate whether hydrogen may be retained after a common-envelope phase to the point of core-collapse and so be observable in supernovae. We find that this is possible and thus common-envelope evolution may contribute to the formation of Type IIb supernovae.

Modeling the evolution of channel shape: Balancing computational efficiency with hydraulic fidelity

USGS Publications Warehouse

Wobus, C.W.; Kean, J.W.; Tucker, G.E.; Anderson, R. Scott

2008-01-01

The cross-sectional shape of a natural river channel controls the capacity of the system to carry water off a landscape, to convey sediment derived from hillslopes, and to erode its bed and banks. Numerical models that describe the response of a landscape to changes in climate or tectonics therefore require formulations that can accommodate evolution of channel cross-sectional geometry. However, fully two-dimensional (2-D) flow models are too computationally expensive to implement in large-scale landscape evolution models, while available simple empirical relationships between width and discharge do not adequately capture the dynamics of channel adjustment. We have developed a simplified 2-D numerical model of channel evolution in a cohesive, detachment-limited substrate subject to steady, unidirectional flow. Erosion is assumed to be proportional to boundary shear stress, which is calculated using an approximation of the flow field in which log-velocity profiles are assumed to apply along vectors that are perpendicular to the local channel bed. Model predictions of the velocity structure, peak boundary shear stress, and equilibrium channel shape compare well with predictions of a more sophisticated but more computationally demanding ray-isovel model. For example, the mean velocities computed by the two models are consistent to within ???3%, and the predicted peak shear stress is consistent to within ???7%. Furthermore, the shear stress distributions predicted by our model compare favorably with available laboratory measurements for prescribed channel shapes. A modification to our simplified code in which the flow includes a high-velocity core allows the model to be extended to estimate shear stress distributions in channels with large width-to-depth ratios. Our model is efficient enough to incorporate into large-scale landscape evolution codes and can be used to examine how channels adjust both cross-sectional shape and slope in response to tectonic and climatic forcing. Copyright 2008 by the American Geophysical Union.

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

EXTREMELY METAL-POOR STARS AND A HIERARCHICAL CHEMICAL EVOLUTION MODEL

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

Komiya, Yutaka

2011-07-20

Early phases of the chemical evolution of the Galaxy and formation history of extremely metal-poor (EMP) stars are investigated using hierarchical galaxy formation models. We build a merger tree of the Galaxy according to the extended Press-Schechter theory. We follow the chemical evolution along the tree and compare the model results to the metallicity distribution function and abundance ratio distribution of the Milky Way halo. We adopt three different initial mass functions (IMFs). In a previous study, we argued that the typical mass, M{sub md}, of EMP stars should be high, M{sub md} {approx} 10 M{sub sun}, based on studiesmore » of binary origin carbon-rich EMP stars. In this study, we show that only the high-mass IMF can explain an observed small number of EMP stars. For relative element abundances, the high-mass IMF and the Salpeter IMF predict similar distributions. We also investigate dependence on nucleosynthetic yields of supernovae (SNe). The theoretical SN yields by Kobayashi et al. and Chieffi and Limongi show reasonable agreement with observations for {alpha}-elements. Our model predicts a significant scatter of element abundances at [Fe/H] < -3. We adopted the stellar yields derived in the work of Francois et al., which produce the best agreement between the observational data and the one-zone chemical evolution model. Their yields well reproduce a trend of the averaged abundances of EMP stars but predict much larger scatter than do the observations. The model with hypernovae predicts Zn abundance, in agreement with the observations, but other models predict lower [Zn/Fe]. Ejecta from the hypernovae with large explosion energy is mixed in large mass and decreases the scatter of the element abundances.« less

Predictable transcriptome evolution in the convergent and complex bioluminescent organs of squid

PubMed Central

Pankey, M. Sabrina; Minin, Vladimir N.; Imholte, Greg C.; Suchard, Marc A.; Oakley, Todd H.

2014-01-01

Despite contingency in life’s history, the similarity of evolutionarily convergent traits may represent predictable solutions to common conditions. However, the extent to which overall gene expression levels (transcriptomes) underlying convergent traits are themselves convergent remains largely unexplored. Here, we show strong statistical support for convergent evolutionary origins and massively parallel evolution of the entire transcriptomes in symbiotic bioluminescent organs (bacterial photophores) from two divergent squid species. The gene expression similarities are so strong that regression models of one species’ photophore can predict organ identity of a distantly related photophore from gene expression levels alone. Our results point to widespread parallel changes in gene expression evolution associated with convergent origins of complex organs. Therefore, predictable solutions may drive not only the evolution of novel, complex organs but also the evolution of overall gene expression levels that underlie them. PMID:25336755

Robust regression and posterior predictive simulation increase power to detect early bursts of trait evolution.

PubMed

Slater, Graham J; Pennell, Matthew W

2014-05-01

A central prediction of much theory on adaptive radiations is that traits should evolve rapidly during the early stages of a clade's history and subsequently slowdown in rate as niches become saturated--a so-called "Early Burst." Although a common pattern in the fossil record, evidence for early bursts of trait evolution in phylogenetic comparative data has been equivocal at best. We show here that this may not necessarily be due to the absence of this pattern in nature. Rather, commonly used methods to infer its presence perform poorly when when the strength of the burst--the rate at which phenotypic evolution declines--is small, and when some morphological convergence is present within the clade. We present two modifications to existing comparative methods that allow greater power to detect early bursts in simulated datasets. First, we develop posterior predictive simulation approaches and show that they outperform maximum likelihood approaches at identifying early bursts at moderate strength. Second, we use a robust regression procedure that allows for the identification and down-weighting of convergent taxa, leading to moderate increases in method performance. We demonstrate the utility and power of these approach by investigating the evolution of body size in cetaceans. Model fitting using maximum likelihood is equivocal with regards the mode of cetacean body size evolution. However, posterior predictive simulation combined with a robust node height test return low support for Brownian motion or rate shift models, but not the early burst model. While the jury is still out on whether early bursts are actually common in nature, our approach will hopefully facilitate more robust testing of this hypothesis. We advocate the adoption of similar posterior predictive approaches to improve the fit and to assess the adequacy of macroevolutionary models in general.

Niche evolution and diversification in a Neotropical radiation of birds (Aves: Furnariidae).

PubMed

Seeholzer, Glenn F; Claramunt, Santiago; Brumfield, Robb T

2017-03-01

Rapid diversification may be caused by ecological adaptive radiation via niche divergence. In this model, speciation is coupled with niche divergence and lineage diversification is predicted to be correlated with rates of niche evolution. Studies of the role of niche evolution in diversification have generally focused on ecomorphological diversification but climatic-niche evolution may also be important. We tested these alternatives using a phylogeny of 298 species of ovenbirds (Aves: Furnariidae). We found that within Furnariidae, variation in species richness and diversification rates of subclades were best predicted by rate of climatic-niche evolution than ecomorphological evolution. Although both are clearly important, univariate regression and multivariate model averaging more consistently supported the climatic-niche as the best predictor of lineage diversification. Our study adds to the growing body of evidence, suggesting that climatic-niche divergence may be an important driver of rapid diversification in addition to ecomorphological evolution. However, this pattern may depend on the phylogenetic scale at which rate heterogeneity is examined. © 2017 The Author(s). Evolution © 2017 The Society for the Study of Evolution.

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.

The evolution of sexes: A specific test of the disruptive selection theory.

PubMed

da Silva, Jack

2018-01-01

The disruptive selection theory of the evolution of anisogamy posits that the evolution of a larger body or greater organismal complexity selects for a larger zygote, which in turn selects for larger gametes. This may provide the opportunity for one mating type to produce more numerous, small gametes, forcing the other mating type to produce fewer, large gametes. Predictions common to this and related theories have been partially upheld. Here, a prediction specific to the disruptive selection theory is derived from a previously published game-theoretic model that represents the most complete description of the theory. The prediction, that the ratio of macrogamete to microgamete size should be above three for anisogamous species, is supported for the volvocine algae. A fully population genetic implementation of the model, involving mutation, genetic drift, and selection, is used to verify the game-theoretic approach and accurately simulates the evolution of gamete sizes in anisogamous species. This model was extended to include a locus for gamete motility and shows that oogamy should evolve whenever there is costly motility. The classic twofold cost of sex may be derived from the fitness functions of these models, showing that this cost is ultimately due to genetic conflict.

Maximal Predictability Approach for Identifying the Right Descriptors for Electrocatalytic Reactions.

PubMed

Krishnamurthy, Dilip; Sumaria, Vaidish; Viswanathan, Venkatasubramanian

2018-02-01

Density functional theory (DFT) calculations are being routinely used to identify new material candidates that approach activity near fundamental limits imposed by thermodynamics or scaling relations. DFT calculations are associated with inherent uncertainty, which limits the ability to delineate materials (distinguishability) that possess high activity. Development of error-estimation capabilities in DFT has enabled uncertainty propagation through activity-prediction models. In this work, we demonstrate an approach to propagating uncertainty through thermodynamic activity models leading to a probability distribution of the computed activity and thereby its expectation value. A new metric, prediction efficiency, is defined, which provides a quantitative measure of the ability to distinguish activity of materials and can be used to identify the optimal descriptor(s) ΔG opt . We demonstrate the framework for four important electrochemical reactions: hydrogen evolution, chlorine evolution, oxygen reduction and oxygen evolution. Future studies could utilize expected activity and prediction efficiency to significantly improve the prediction accuracy of highly active material candidates.

Two-dimensional global hybrid simulation of pressure evolution and waves in the magnetosheath

NASA Astrophysics Data System (ADS)

Lin, Y.; Denton, R. E.; Lee, L. C.; Chao, J. K.

2001-06-01

A two-dimensional hybrid simulation is carried out for the global structure of the magnetosheath. Quasi-perpendicular magnetosonic/fast mode waves with large-amplitude in-phase oscillations of the magnetic field and the ion density are seen near the bow shock transition. Alfvén/ion-cyclotron waves are observed along the streamlines in the magnetosheath, and the wave power peaks in the middle magnetosheath. Antiphase oscillations in the magnetic field and density are present away from the shock transition. Transport ratio analysis suggests that these oscillations result from mirror mode waves. Since fluid simulations are currently best able to model the global magnetosphere and the pressure in the magnetosphere is inherently anisotropic (parallel pressure p∥≠perpendicular pressure p⊥), it is of some interest to see if a fluid model can be used to predict the anisotropic pressure evolution of a plasma. Here the predictions of double adiabatic theory, the bounded anisotropy model, and the double polytropic model are tested using the two-dimensional hybrid simulation of the magnetosheath. Inputs to the models from the hybrid simulation are the initial post bow shock pressures and the time-dependent density and magnetic field strength along streamlines of the plasma. The success of the models is evaluated on the basis of how well they predict the subsequent evolution of p∥ and p⊥. The bounded anisotropy model, which encorporates a bound on p⊥/p∥ due to the effect of ion cyclotron pitch angle scattering, does a very good job of predicting the evolution of p⊥ this is evidence that local transfer of energy due to waves is occurring. Further evidence is the positive identification of ion-cyclotron waves in the simulation. The lack of such a good prediction for the evolution of p∥ appears to be due to the model's lack of time dependence for the wave-particle interaction and its neglect of the parallel heat flux. Estimates indicate that these effects will be less significant in the real magnetosheath, though perhaps not negligible.

Abundance Patterns in S-type AGB Stars: Setting Constraints on Nucleosynthesis and Stellar Evolution Models

NASA Astrophysics Data System (ADS)

Neyskens, P.; van Eck, S.; Plez, B.; Goriely, S.; Siess, L.; Jorissen, A.

2011-09-01

During evolution on the AGB, stars of type S are the first to experience s-process nucleosynthesis and the third dredge-up, and therefore to exhibit s-process signatures in their atmospheres. Their high mass-loss rates (10-7 to 10-6 M⊙/year) make them major contributors to the AGB nucleosynthesis yields at solar metallicity. Precise abundance determinations in S stars are of the utmost importance for constraining e.g. the third dredge-up luminosity and efficiency (which has been only crudely parameterized in current nucleosynthetic models so far). Here, dedicated S-star model atmospheres are used to determine precise abundances of key s-process elements, and to set constraints on nucleosynthesis and stellar evolution models. Special interest is paid to technetium, an element with no stable isotopes. Its detection is considered the best signature that the star effectively populates the thermally-pulsing AGB phase of evolution. The derived Tc/Zr abundances are compared, as a function of the derived [Zr/Fe] overabundances, with AGB stellar model predictions. The [Zr/Fe] overabundances are in good agreement with model predictions, while the Tc/Zr abundances are slightly overpredicted. This discrepancy can help to set better constraints on nucleosynthesis and stellar evolution models of AGB stars.

Application of a new dynamic transport model to predict the evolution of performances throughout the nanofiltration of single salt solutions in concentration and diafiltration modes.

PubMed

Déon, Sébastien; Lam, Boukary; Fievet, Patrick

2018-06-01

Although many knowledge models describing the rejection of ionic compounds by nanofiltration membranes are available in literature, they are all used in full recycling mode. Indeed, both permeate and retentate streams are recycled in order to maintain constant concentrations in the feed solution. However, nanofiltration of real effluents is implemented either in concentration or diafiltration modes, for which the permeate stream is collected. In these conditions, concentrations progressively evolve during filtration and classical models fail to predict performances. In this paper, an improvement of the so called "Donnan Steric Pore Model", which includes both volume and concentration variations over time is proposed. This dynamic model is used here to predict the evolution of volumes and concentrations in both permeate and retentate streams during the filtration of salt solutions. This model was found to predict accurately the filtration performances with various salts whether the filtration is performed in concentration or diafiltration modes. The parameters of the usual model can be easily assessed from full batch experiments before being used in the dynamic version. Nevertheless, it is also highlighted that the variation of the membrane charge due to the evolution of feed concentration over time has to be taken into account in the model through the use of adsorption isotherms. Copyright © 2018 Elsevier Ltd. All rights reserved.

Evolution of the social network of scientific collaborations

NASA Astrophysics Data System (ADS)

Barabasi, Albert-Laszlo; Jeong, Hawoong; Neda, Zoltan; Ravasz, Erzsebet; Schubert, Andras; Vicsek, Tamas

2002-03-01

The co-authorship network of scientists represents a prototype of complex evolving networks. By mapping the electronic database containing all relevant journals in mathematics and neuro-science for an eight-year period (1991-98), we infer the dynamic and the structural mechanisms that govern the evolution and topology of this complex system. First, empirical measurements allow us to uncover the topological measures that characterize the network at a given moment, as well as the time evolution of these quantities. The results indicate that the network is scale-free, and that the network evolution is governed by preferential attachment, affecting both internal and external links. However, in contrast with most model predictions the average degree increases in time, and the node separation decreases. Second, we propose a simple model that captures the network's time evolution. Third, numerical simulations are used to uncover the behavior of quantities that could not be predicted analytically.

Eco-genetic modeling of contemporary life-history evolution.

PubMed

Dunlop, Erin S; Heino, Mikko; Dieckmann, Ulf

2009-10-01

We present eco-genetic modeling as a flexible tool for exploring the course and rates of multi-trait life-history evolution in natural populations. We build on existing modeling approaches by combining features that facilitate studying the ecological and evolutionary dynamics of realistically structured populations. In particular, the joint consideration of age and size structure enables the analysis of phenotypically plastic populations with more than a single growth trajectory, and ecological feedback is readily included in the form of density dependence and frequency dependence. Stochasticity and life-history trade-offs can also be implemented. Critically, eco-genetic models permit the incorporation of salient genetic detail such as a population's genetic variances and covariances and the corresponding heritabilities, as well as the probabilistic inheritance and phenotypic expression of quantitative traits. These inclusions are crucial for predicting rates of evolutionary change on both contemporary and longer timescales. An eco-genetic model can be tightly coupled with empirical data and therefore may have considerable practical relevance, in terms of generating testable predictions and evaluating alternative management measures. To illustrate the utility of these models, we present as an example an eco-genetic model used to study harvest-induced evolution of multiple traits in Atlantic cod. The predictions of our model (most notably that harvesting induces a genetic reduction in age and size at maturation, an increase or decrease in growth capacity depending on the minimum-length limit, and an increase in reproductive investment) are corroborated by patterns observed in wild populations. The predicted genetic changes occur together with plastic changes that could phenotypically mask the former. Importantly, our analysis predicts that evolutionary changes show little signs of reversal following a harvest moratorium. This illustrates how predictions offered by eco-genetic models can enable and guide evolutionarily sustainable resource management.

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.

Prediction and assimilation of surf-zone processes using a Bayesian network: Part I: Forward models

USGS Publications Warehouse

Plant, Nathaniel G.; Holland, K. Todd

2011-01-01

Prediction of coastal processes, including waves, currents, and sediment transport, can be obtained from a variety of detailed geophysical-process models with many simulations showing significant skill. This capability supports a wide range of research and applied efforts that can benefit from accurate numerical predictions. However, the predictions are only as accurate as the data used to drive the models and, given the large temporal and spatial variability of the surf zone, inaccuracies in data are unavoidable such that useful predictions require corresponding estimates of uncertainty. We demonstrate how a Bayesian-network model can be used to provide accurate predictions of wave-height evolution in the surf zone given very sparse and/or inaccurate boundary-condition data. The approach is based on a formal treatment of a data-assimilation problem that takes advantage of significant reduction of the dimensionality of the model system. We demonstrate that predictions of a detailed geophysical model of the wave evolution are reproduced accurately using a Bayesian approach. In this surf-zone application, forward prediction skill was 83%, and uncertainties in the model inputs were accurately transferred to uncertainty in output variables. We also demonstrate that if modeling uncertainties were not conveyed to the Bayesian network (i.e., perfect data or model were assumed), then overly optimistic prediction uncertainties were computed. More consistent predictions and uncertainties were obtained by including model-parameter errors as a source of input uncertainty. Improved predictions (skill of 90%) were achieved because the Bayesian network simultaneously estimated optimal parameters while predicting wave heights.

Simulating the evolution of glyphosate resistance in grains farming in northern Australia.

PubMed

Thornby, David F; Walker, Steve R

2009-09-01

The evolution of resistance to herbicides is a substantial problem in contemporary agriculture. Solutions to this problem generally consist of the use of practices to control the resistant population once it evolves, and/or to institute preventative measures before populations become resistant. Herbicide resistance evolves in populations over years or decades, so predicting the effectiveness of preventative strategies in particular relies on computational modelling approaches. While models of herbicide resistance already exist, none deals with the complex regional variability in the northern Australian sub-tropical grains farming region. For this reason, a new computer model was developed. The model consists of an age- and stage-structured population model of weeds, with an existing crop model used to simulate plant growth and competition, and extensions to the crop model added to simulate seed bank ecology and population genetics factors. Using awnless barnyard grass (Echinochloa colona) as a test case, the model was used to investigate the likely rate of evolution under conditions expected to produce high selection pressure. Simulating continuous summer fallows with glyphosate used as the only means of weed control resulted in predicted resistant weed populations after approx. 15 years. Validation of the model against the paddock history for the first real-world glyphosate-resistant awnless barnyard grass population shows that the model predicted resistance evolution to within a few years of the real situation. This validation work shows that empirical validation of herbicide resistance models is problematic. However, the model simulates the complexities of sub-tropical grains farming in Australia well, and can be used to investigate, generate and improve glyphosate resistance prevention strategies.

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.

When Theory Meets Data: Comparing Model Predictions Of Hillslope Sediment Size With Field Measurements.

NASA Astrophysics Data System (ADS)

Mahmoudi, M.; Sklar, L. S.; Leclere, S.; Davis, J. D.; Stine, A.

2017-12-01

The size distributions of sediment produced on hillslopes and supplied to river channels influence a wide range of fluvial processes, from bedrock river incision to the creation of aquatic habitats. However, the factors that control hillslope sediment size are poorly understood, limiting our ability to predict sediment size and model the evolution of sediment size distributions across landscapes. Recently separate field and theoretical investigations have begun to address this knowledge gap. Here we compare the predictions of several emerging modeling approaches to landscapes where high quality field data are available. Our goals are to explore the sensitivity and applicability of the theoretical models in each field context, and ultimately to provide a foundation for incorporating hillslope sediment size into models of landscape evolution. The field data include published measurements of hillslope sediment size from the Kohala peninsula on the island of Hawaii and tributaries to the Feather River in the northern Sierra Nevada mountains of California, and an unpublished data set from the Inyo Creek catchment of the southern Sierra Nevada. These data are compared to predictions adapted from recently published modeling approaches that include elements of topography, geology, structure, climate and erosion rate. Predictive models for each site are built in ArcGIS using field condition datasets: DEM topography (slope, aspect, curvature), bedrock geology (lithology, mineralogy), structure (fault location, fracture density), climate data (mean annual precipitation and temperature), and estimates of erosion rates. Preliminary analysis suggests that models may be finely tuned to the calibration sites, particularly when field conditions most closely satisfy model assumptions, leading to unrealistic predictions from extrapolation. We suggest a path forward for developing a computationally tractable method for incorporating spatial variation in production of hillslope sediment size distributions in landscape evolution models. Overall, this work highlights the need for additional field data sets as well as improved theoretical models, but also demonstrates progress in predicting the size distribution of sediments produced on hillslopes and supplied to channels.

Prediction of porosity of food materials during drying: Current challenges and directions.

PubMed

Joardder, Mohammad U H; Kumar, C; Karim, M A

2017-07-18

Pore formation in food samples is a common physical phenomenon observed during dehydration processes. The pore evolution during drying significantly affects the physical properties and quality of dried foods. Therefore, it should be taken into consideration when predicting transport processes in the drying sample. Characteristics of pore formation depend on the drying process parameters, product properties and processing time. Understanding the physics of pore formation and evolution during drying will assist in accurately predicting the drying kinetics and quality of food materials. Researchers have been trying to develop mathematical models to describe the pore formation and evolution during drying. In this study, existing porosity models are critically analysed and limitations are identified. Better insight into the factors affecting porosity is provided, and suggestions are proposed to overcome the limitations. These include considerations of process parameters such as glass transition temperature, sample temperature, and variable material properties in the porosity models. Several researchers have proposed models for porosity prediction of food materials during drying. However, these models are either very simplistic or empirical in nature and failed to consider relevant significant factors that influence porosity. In-depth understanding of characteristics of the pore is required for developing a generic model of porosity. A micro-level analysis of pore formation is presented for better understanding, which will help in developing an accurate and generic porosity model.

CenH3 evolution reflects meiotic symmetry as predicted by the centromere drive model

PubMed Central

Zedek, František; Bureš, Petr

2016-01-01

The centromere drive model explaining rapid evolution of eukaryotic centromeres predicts higher frequency of positive selection acting on centromeric histone H3 (CenH3) in clades with asymmetric meiosis compared to the clades with only symmetric meiosis. However, despite the impression one might get from the literature, this key prediction of the centromere drive model has not only never been confirmed, but it has never been tested, because all the previous studies dealt only with the presence or absence instead of the frequency of positive selection. To provide evidence for or against different frequencies of positively selected CenH3 in asymmetrics and symmetrics, we have inferred the selective pressures acting on CenH3 in seventeen eukaryotic clades, including plants, animals, fungi, ciliates and apicomplexa, using codon-substitution models, and compared the inferred frequencies between asymmetrics and symmetrics in a quantitative manner. We have found that CenH3 has been evolving adaptively much more frequently in clades with asymmetric meiosis compared with clades displaying only symmetric meiosis which confirms the prediction of centromere drive model. Our findings indicate that the evolution of asymmetric meiosis required CenH3 to evolve adaptively more often to counterbalance the negative consequences of centromere drive. PMID:27629066

Dioecy and the evolution of sex ratios in ants

PubMed Central

Wiernasz, Diane C.; Cole, Blaine J.

2009-01-01

Split sex ratios, when some colonies produce only male and others only female reproductives, is a common feature of social insects, especially ants. The most widely accepted explanation for split sex ratios was proposed by Boomsma and Grafen, and is driven by conflicts of interest among colonies that vary in relatedness. The predictions of the Boomsma–Grafen model have been confirmed in many cases, but contradicted in several others. We adapt a model for the evolution of dioecy in plants to make predictions about the evolution of split sex ratios in social insects. Reproductive specialization results from the instability of the evolutionarily stable strategy (ESS) sex ratio, and is independent of variation in relatedness. We test predictions of the model with data from a long-term study of harvester ants, and show that it correctly predicts the intermediate sex ratios we observe in our study species. The dioecy model provides a comprehensive framework for sex allocation that is based on the pay-offs to the colony via production of males and females, and is independent of the genetic variation among colonies. However, in populations where the conditions for the Boomsma–Grafen model hold, kin selection will still lead to an association between sex ratio and relatedness. PMID:19324757

Design and analysis of forward and reverse models for predicting defect accumulation, defect energetics, and irradiation conditions

DOE PAGES

Stewart, James A.; Kohnert, Aaron A.; Capolungo, Laurent; ...

2018-03-06

The complexity of radiation effects in a material’s microstructure makes developing predictive models a difficult task. In principle, a complete list of all possible reactions between defect species being considered can be used to elucidate damage evolution mechanisms and its associated impact on microstructure evolution. However, a central limitation is that many models use a limited and incomplete catalog of defect energetics and associated reactions. Even for a given model, estimating its input parameters remains a challenge, especially for complex material systems. Here, we present a computational analysis to identify the extent to which defect accumulation, energetics, and irradiation conditionsmore » can be determined via forward and reverse regression models constructed and trained from large data sets produced by cluster dynamics simulations. A global sensitivity analysis, via Sobol’ indices, concisely characterizes parameter sensitivity and demonstrates how this can be connected to variability in defect evolution. Based on this analysis and depending on the definition of what constitutes the input and output spaces, forward and reverse regression models are constructed and allow for the direct calculation of defect accumulation, defect energetics, and irradiation conditions. Here, this computational analysis, exercised on a simplified cluster dynamics model, demonstrates the ability to design predictive surrogate and reduced-order models, and provides guidelines for improving model predictions within the context of forward and reverse engineering of mathematical models for radiation effects in a materials’ microstructure.« less

Design and analysis of forward and reverse models for predicting defect accumulation, defect energetics, and irradiation conditions

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

Stewart, James A.; Kohnert, Aaron A.; Capolungo, Laurent

The complexity of radiation effects in a material’s microstructure makes developing predictive models a difficult task. In principle, a complete list of all possible reactions between defect species being considered can be used to elucidate damage evolution mechanisms and its associated impact on microstructure evolution. However, a central limitation is that many models use a limited and incomplete catalog of defect energetics and associated reactions. Even for a given model, estimating its input parameters remains a challenge, especially for complex material systems. Here, we present a computational analysis to identify the extent to which defect accumulation, energetics, and irradiation conditionsmore » can be determined via forward and reverse regression models constructed and trained from large data sets produced by cluster dynamics simulations. A global sensitivity analysis, via Sobol’ indices, concisely characterizes parameter sensitivity and demonstrates how this can be connected to variability in defect evolution. Based on this analysis and depending on the definition of what constitutes the input and output spaces, forward and reverse regression models are constructed and allow for the direct calculation of defect accumulation, defect energetics, and irradiation conditions. Here, this computational analysis, exercised on a simplified cluster dynamics model, demonstrates the ability to design predictive surrogate and reduced-order models, and provides guidelines for improving model predictions within the context of forward and reverse engineering of mathematical models for radiation effects in a materials’ microstructure.« less

Evolution in Stage-Structured Populations

PubMed Central

Barfield, Michael; Holt, Robert D.; Gomulkiewicz, Richard

2016-01-01

For many organisms, stage is a better predictor of demographic rates than age. Yet no general theoretical framework exists for understanding or predicting evolution in stage-structured populations. Here, we provide a general modeling approach that can be used to predict evolution and demography of stage-structured populations. This advances our ability to understand evolution in stage-structured populations to a level previously available only for populations structured by age. We use this framework to provide the first rigorous proof that Lande’s theorem, which relates adaptive evolution to population growth, applies to stage-classified populations, assuming only normality and that evolution is slow relative to population dynamics. We extend this theorem to allow for different means or variances among stages. Our next major result is the formulation of Price’s theorem, a fundamental law of evolution, for stage-structured populations. In addition, we use data from Trillium grandiflorum to demonstrate how our models can be applied to a real-world population and thereby show their practical potential to generate accurate projections of evolutionary and population dynamics. Finally, we use our framework to compare rates of evolution in age- versus stage-structured populations, which shows how our methods can yield biological insights about evolution in stage-structured populations. PMID:21460563

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.

Modeling postshock evolution of large electropores

NASA Astrophysics Data System (ADS)

Neu, John C.; Krassowska, Wanda

2003-02-01

The Smoluchowski equation (SE), which describes the evolution of pores created by electric shocks, cannot be applied to modeling large and long-lived pores for two reasons: (1) it does not predict pores of radius above 20 nm without also predicting membrane rupture; (2) it does not predict postshock growth of pores. This study proposes a model in which pores are coupled by membrane tension, resulting in a nonlinear generalization of SE. The predictions of the model are explored using examples of homogeneous (all pore radii r are equal) and heterogeneous (0⩽r⩽rmax) distributions of pores. Pores in a homogeneous population either shrink to zero or assume a stable radius corresponding to the minimum of the bilayer energy. For a heterogeneous population, such a stable radius does not exist. All pores, except rmax, shrink to zero and rmax grows to infinity. However, the unbounded growth of rmax is not physical because the number of pores per cell decreases in time and the continuum model loses validity. When the continuum formulation is replaced by the discrete one, the model predicts the coarsening process: all pores, except rmax, shrink to zero and rmax assumes a stable radius. Thus, the model with tension-coupled pores does not predict membrane rupture and the predicted postshock growth of pores is consistent with experimental evidence.

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.

Evolution of viral virulence: empirical studies

USGS Publications Warehouse

Kurath, Gael; Wargo, Andrew R.

2016-01-01

The concept of virulence as a pathogen trait that can evolve in response to selection has led to a large body of virulence evolution theory developed in the 1980-1990s. Various aspects of this theory predict increased or decreased virulence in response to a complex array of selection pressures including mode of transmission, changes in host, mixed infection, vector-borne transmission, environmental changes, host vaccination, host resistance, and co-evolution of virus and host. A fundamental concept is prediction of trade-offs between the costs and benefits associated with higher virulence, leading to selection of optimal virulence levels. Through a combination of observational and experimental studies, including experimental evolution of viruses during serial passage, many of these predictions have now been explored in systems ranging from bacteriophage to viruses of plants, invertebrates, and vertebrate hosts. This chapter summarizes empirical studies of viral virulence evolution in numerous diverse systems, including the classic models myxomavirus in rabbits, Marek's disease virus in chickens, and HIV in humans. Collectively these studies support some aspects of virulence evolution theory, suggest modifications for other aspects, and show that predictions may apply in some virus:host interactions but not in others. Finally, we consider how virulence evolution theory applies to disease management in the field.

Viscous anisotropy of textured olivine aggregates: 2. Micromechanical model

NASA Astrophysics Data System (ADS)

Hansen, Lars N.; Conrad, Clinton P.; Boneh, Yuval; Skemer, Philip; Warren, Jessica M.; Kohlstedt, David L.

2016-10-01

The significant viscous anisotropy that results from crystallographic alignment (texture) of olivine grains in deformed upper mantle rocks strongly influences a large variety of geodynamic processes. Our ability to explore the effects of anisotropic viscosity in simulations of these processes requires a mechanical model that can predict the magnitude of anisotropy and its evolution. Unfortunately, existing models of olivine textural evolution and viscous anisotropy are calibrated for relatively small deformations and simple strain paths, making them less general than desired for many large-scale geodynamic scenarios. Here we develop a new set of micromechanical models to describe the mechanical behavior and textural evolution of olivine through a large range of strains and complex strain histories. For the mechanical behavior, we explore two extreme scenarios, one in which each grain experiences the same stress tensor (Sachs model) and one in which each grain undergoes a strain rate as close as possible to the macroscopic strain rate (pseudo-Taylor model). For the textural evolution, we develop a new model in which the director method is used to control the rate of grain rotation and the available slip systems in olivine are used to control the axis of rotation. Only recently has enough laboratory data on the deformation of olivine become available to calibrate these models. We use these new data to conduct inversions for the best parameters to characterize both the mechanical and textural evolution models. These inversions demonstrate that the calibrated pseudo-Taylor model best reproduces the mechanical observations. Additionally, the pseudo-Taylor textural evolution model can reasonably reproduce the observed texture strength, shape, and orientation after large and complex deformations. A quantitative comparison between our calibrated models and previously published models reveals that our new models excel in predicting the magnitude of viscous anisotropy and the details of the textural evolution. In addition, we demonstrate that the mechanical and textural evolution models can be coupled and used to reproduce mechanical evolution during large-strain torsion tests. This set of models therefore provides a new geodynamic tool for incorporating viscous anisotropy into large-scale numerical simulations.

Variations on Debris Disks. IV. An Improved Analytical Model for Collisional Cascades

NASA Astrophysics Data System (ADS)

Kenyon, Scott J.; Bromley, Benjamin C.

2017-04-01

We derive a new analytical model for the evolution of a collisional cascade in a thin annulus around a single central star. In this model, r max the size of the largest object changes with time, {r}\\max \\propto {t}-γ , with γ ≈ 0.1-0.2. Compared to standard models where r max is constant in time, this evolution results in a more rapid decline of M d , the total mass of solids in the annulus, and L d , the luminosity of small particles in the annulus: {M}d\\propto {t}-(γ +1) and {L}d\\propto {t}-(γ /2+1). We demonstrate that the analytical model provides an excellent match to a comprehensive suite of numerical coagulation simulations for annuli at 1 au and at 25 au. If the evolution of real debris disks follows the predictions of the analytical or numerical models, the observed luminosities for evolved stars require up to a factor of two more mass than predicted by previous analytical models.

Predicting rates of interspecific interaction from phylogenetic trees.

PubMed

Nuismer, Scott L; Harmon, Luke J

2015-01-01

Integrating phylogenetic information can potentially improve our ability to explain species' traits, patterns of community assembly, the network structure of communities, and ecosystem function. In this study, we use mathematical models to explore the ecological and evolutionary factors that modulate the explanatory power of phylogenetic information for communities of species that interact within a single trophic level. We find that phylogenetic relationships among species can influence trait evolution and rates of interaction among species, but only under particular models of species interaction. For example, when interactions within communities are mediated by a mechanism of phenotype matching, phylogenetic trees make specific predictions about trait evolution and rates of interaction. In contrast, if interactions within a community depend on a mechanism of phenotype differences, phylogenetic information has little, if any, predictive power for trait evolution and interaction rate. Together, these results make clear and testable predictions for when and how evolutionary history is expected to influence contemporary rates of species interaction. © 2014 John Wiley & Sons Ltd/CNRS.

Using MELTS to understand the evolution of silicic magmas: Challenges and successes in modeling the Highland Range Volcanic Sequence (NV)

NASA Astrophysics Data System (ADS)

Vaum, R. C.; Gualda, G. A.; Ghiorso, M. S.; Miller, C. F.; Colombini, L. L.

2009-12-01

The Highland Range near Searchlight, Nevada is comprised of mid-Miocene, intermediate to silicic volcanic rocks. This study focuses on the most silicic portion of the eruptive sequence (16.0-16.5 Ma). The first eruptions during this interval were effusive and produced trachydacite (66-70 wt% SiO2), but later the eruptive style shifted to explosive and compositions were more evolved (70-78 wt% SiO2). Glass compositions in rocks saturated in both quartz and sanidine align along the 150 MPa quartz+sanidine saturation surface, suggesting that the Highland Range magmas equilibrated in a single reservoir at that pressure. We are interested in better understanding this transition in eruptive style from effusive to eruptive, and our approach is based on modeling melt evolution using MELTS thermodynamic modeling software. We selected representative samples from key stratigraphic units, and focused on samples for which whole-rock and glass compositions, as well as mineral abundances, are available. This allows for direct comparison of simulation results with existing data. Initial simulations showed that MELTS predicts unrealistic paths of evolution when compared to the glass compositions and to the phase relations in the Qz-Ab-Or ternary. In particular, the stability field of quartz predicted by MELTS is much too small, causing melts to become exceedingly silicic (>80 wt% SiO2). Sanidine, on the other hand, has fairly sodic compositions and crystallizes too early in the sequence; therefore, simulated melt compositions are never as potassic as the analyzed glasses. Similar results are obtained when modeling the evolution of the Bishop and Campanian magmas, showing that these are systematic problems in MELTS calibration. Accordingly, we have adjusted the enthalpy of quartz and potassium end-member of the feldspar solid solution in MELTS so that the quartz-sanidine saturation surface is correctly predicted. We find that this modified version of MELTS much better models the evolution of silicic magmas. Sanidine begins to crystallize at lower temperatures, causing evolved melts to become significantly more potassic. Also, MELTS prediction of quartz saturation is in agreement with the position of the experimentally determined 150 MPa quartz+sanidine saturation surface. Importantly, the melt evolution that this modified version of MELTS predicts is very consistent with whole-rock data, glass chemistry, and mineral abundances in samples from the Highland Range. Simulations using the modified version of MELTS show that it works remarkably well, at least for relatively low degrees of crystallization. But a more reliable model to simulate the evolution of silicic magmas is necessary to more properly simulate the evolution of silicic systems, in particular at high degrees of crystallinity. We are currently working to create gMELTS, an associated solution model of the haplogranitic system, which, once completed, will be optimized to simulate the evolution of silicic systems.

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.

When should we expect early bursts of trait evolution in comparative data? Predictions from an evolutionary food web model.

PubMed

Ingram, T; Harmon, L J; Shurin, J B

2012-09-01

Conceptual models of adaptive radiation predict that competitive interactions among species will result in an early burst of speciation and trait evolution followed by a slowdown in diversification rates. Empirical studies often show early accumulation of lineages in phylogenetic trees, but usually fail to detect early bursts of phenotypic evolution. We use an evolutionary simulation model to assemble food webs through adaptive radiation, and examine patterns in the resulting phylogenetic trees and species' traits (body size and trophic position). We find that when foraging trade-offs result in food webs where all species occupy integer trophic levels, lineage diversity and trait disparity are concentrated early in the tree, consistent with the early burst model. In contrast, in food webs in which many omnivorous species feed at multiple trophic levels, high levels of turnover of species' identities and traits tend to eliminate the early burst signal. These results suggest testable predictions about how the niche structure of ecological communities may be reflected by macroevolutionary patterns. © 2012 The Authors. Journal of Evolutionary Biology © 2012 European Society For Evolutionary Biology.

Independent evolution of the sexes promotes amphibian diversification.

PubMed

De Lisle, Stephen P; Rowe, Locke

2015-03-22

Classic ecological theory predicts that the evolution of sexual dimorphism constrains diversification by limiting morphospace available for speciation. Alternatively, sexual selection may lead to the evolution of reproductive isolation and increased diversification. We test contrasting predictions of these hypotheses by examining the relationship between sexual dimorphism and diversification in amphibians. Our analysis shows that the evolution of sexual size dimorphism (SSD) is associated with increased diversification and speciation, contrary to the ecological theory. Further, this result is unlikely to be explained by traditional sexual selection models because variation in amphibian SSD is unlikely to be driven entirely by sexual selection. We suggest that relaxing a central assumption of classic ecological models-that the sexes share a common adaptive landscape-leads to the alternative hypothesis that independent evolution of the sexes may promote diversification. Once the constraints of sexual conflict are relaxed, the sexes can explore morphospace that would otherwise be inaccessible. Consistent with this novel hypothesis, the evolution of SSD in amphibians is associated with reduced current extinction threat status, and an historical reduction in extinction rate. Our work reconciles conflicting predictions from ecological and evolutionary theory and illustrates that the ability of the sexes to evolve independently is associated with a spectacular vertebrate radiation. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

Forming limit prediction by an evolving non-quadratic yield criterion considering the anisotropic hardening and r-value evolution

NASA Astrophysics Data System (ADS)

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

2018-05-01

The constitutive model development has been driven to a very accurate and fine-resolution description of the material behaviour responding to various environmental variable changes. The evolving features of the anisotropic behaviour during deformation, therefore, has drawn particular attention due to its possible impacts on the sheet metal forming industry. An evolving non-associated Hill48 (enHill48) model was recently proposed and applied to the forming limit prediction by coupling with the modified maximum force criterion. On the one hand, the study showed the significance to include the anisotropic evolution for accurate forming limit prediction. On the other hand, it also illustrated that the enHill48 model introduced an instability region that suddenly decreases the formability. Therefore, in this study, an alternative model that is based on the associated flow rule and provides similar anisotropic predictive capability is extended to chapter the evolving effects and further applied to the forming limit prediction. The final results are compared with experimental data as well as the results by enHill48 model.

Evidence for determinism in species diversification and contingency in phenotypic evolution during adaptive radiation.

PubMed

Burbrink, Frank T; Chen, Xin; Myers, Edward A; Brandley, Matthew C; Pyron, R Alexander

2012-12-07

Adaptive radiation (AR) theory predicts that groups sharing the same source of ecological opportunity (EO) will experience deterministic species diversification and morphological evolution. Thus, deterministic ecological and morphological evolution should be correlated with deterministic patterns in the tempo and mode of speciation for groups in similar habitats and time periods. We test this hypothesis using well-sampled phylogenies of four squamate groups that colonized the New World (NW) in the Late Oligocene. We use both standard and coalescent models to assess species diversification, as well as likelihood models to examine morphological evolution. All squamate groups show similar early pulses of speciation, as well as diversity-dependent ecological limits on clade size at a continental scale. In contrast, processes of morphological evolution are not easily predictable and do not show similar pulses of early and rapid change. Patterns of morphological and species diversification thus appear uncoupled across these groups. This indicates that the processes that drive diversification and disparification are not mechanistically linked, even among similar groups of taxa experiencing the same sources of EO. It also suggests that processes of phenotypic diversification cannot be predicted solely from the existence of an AR or knowledge of the process of diversification.

Evidence for determinism in species diversification and contingency in phenotypic evolution during adaptive radiation

PubMed Central

Burbrink, Frank T.; Chen, Xin; Myers, Edward A.; Brandley, Matthew C.; Pyron, R. Alexander

2012-01-01

Adaptive radiation (AR) theory predicts that groups sharing the same source of ecological opportunity (EO) will experience deterministic species diversification and morphological evolution. Thus, deterministic ecological and morphological evolution should be correlated with deterministic patterns in the tempo and mode of speciation for groups in similar habitats and time periods. We test this hypothesis using well-sampled phylogenies of four squamate groups that colonized the New World (NW) in the Late Oligocene. We use both standard and coalescent models to assess species diversification, as well as likelihood models to examine morphological evolution. All squamate groups show similar early pulses of speciation, as well as diversity-dependent ecological limits on clade size at a continental scale. In contrast, processes of morphological evolution are not easily predictable and do not show similar pulses of early and rapid change. Patterns of morphological and species diversification thus appear uncoupled across these groups. This indicates that the processes that drive diversification and disparification are not mechanistically linked, even among similar groups of taxa experiencing the same sources of EO. It also suggests that processes of phenotypic diversification cannot be predicted solely from the existence of an AR or knowledge of the process of diversification. PMID:23034709

Predicting Key Events in the Popularity Evolution of Online Information.

PubMed

Hu, Ying; Hu, Changjun; Fu, Shushen; Fang, Mingzhe; Xu, Wenwen

2017-01-01

The popularity of online information generally experiences a rising and falling evolution. This paper considers the "burst", "peak", and "fade" key events together as a representative summary of popularity evolution. We propose a novel prediction task-predicting when popularity undergoes these key events. It is of great importance to know when these three key events occur, because doing so helps recommendation systems, online marketing, and containment of rumors. However, it is very challenging to solve this new prediction task due to two issues. First, popularity evolution has high variation and can follow various patterns, so how can we identify "burst", "peak", and "fade" in different patterns of popularity evolution? Second, these events usually occur in a very short time, so how can we accurately yet promptly predict them? In this paper we address these two issues. To handle the first one, we use a simple moving average to smooth variation, and then a universal method is presented for different patterns to identify the key events in popularity evolution. To deal with the second one, we extract different types of features that may have an impact on the key events, and then a correlation analysis is conducted in the feature selection step to remove irrelevant and redundant features. The remaining features are used to train a machine learning model. The feature selection step improves prediction accuracy, and in order to emphasize prediction promptness, we design a new evaluation metric which considers both accuracy and promptness to evaluate our prediction task. Experimental and comparative results show the superiority of our prediction solution.

Predicting Key Events in the Popularity Evolution of Online Information

PubMed Central

Fu, Shushen; Fang, Mingzhe; Xu, Wenwen

2017-01-01

The popularity of online information generally experiences a rising and falling evolution. This paper considers the “burst”, “peak”, and “fade” key events together as a representative summary of popularity evolution. We propose a novel prediction task—predicting when popularity undergoes these key events. It is of great importance to know when these three key events occur, because doing so helps recommendation systems, online marketing, and containment of rumors. However, it is very challenging to solve this new prediction task due to two issues. First, popularity evolution has high variation and can follow various patterns, so how can we identify “burst”, “peak”, and “fade” in different patterns of popularity evolution? Second, these events usually occur in a very short time, so how can we accurately yet promptly predict them? In this paper we address these two issues. To handle the first one, we use a simple moving average to smooth variation, and then a universal method is presented for different patterns to identify the key events in popularity evolution. To deal with the second one, we extract different types of features that may have an impact on the key events, and then a correlation analysis is conducted in the feature selection step to remove irrelevant and redundant features. The remaining features are used to train a machine learning model. The feature selection step improves prediction accuracy, and in order to emphasize prediction promptness, we design a new evaluation metric which considers both accuracy and promptness to evaluate our prediction task. Experimental and comparative results show the superiority of our prediction solution. PMID:28046121

Simulating the evolution of glyphosate resistance in grains farming in northern Australia

PubMed Central

Thornby, David F.; Walker, Steve R.

2009-01-01

Background and Aims The evolution of resistance to herbicides is a substantial problem in contemporary agriculture. Solutions to this problem generally consist of the use of practices to control the resistant population once it evolves, and/or to institute preventative measures before populations become resistant. Herbicide resistance evolves in populations over years or decades, so predicting the effectiveness of preventative strategies in particular relies on computational modelling approaches. While models of herbicide resistance already exist, none deals with the complex regional variability in the northern Australian sub-tropical grains farming region. For this reason, a new computer model was developed. Methods The model consists of an age- and stage-structured population model of weeds, with an existing crop model used to simulate plant growth and competition, and extensions to the crop model added to simulate seed bank ecology and population genetics factors. Using awnless barnyard grass (Echinochloa colona) as a test case, the model was used to investigate the likely rate of evolution under conditions expected to produce high selection pressure. Key Results Simulating continuous summer fallows with glyphosate used as the only means of weed control resulted in predicted resistant weed populations after approx. 15 years. Validation of the model against the paddock history for the first real-world glyphosate-resistant awnless barnyard grass population shows that the model predicted resistance evolution to within a few years of the real situation. Conclusions This validation work shows that empirical validation of herbicide resistance models is problematic. However, the model simulates the complexities of sub-tropical grains farming in Australia well, and can be used to investigate, generate and improve glyphosate resistance prevention strategies. PMID:19567415

Empirical fitness landscapes and the predictability of evolution.

PubMed

de Visser, J Arjan G M; Krug, Joachim

2014-07-01

The genotype-fitness map (that is, the fitness landscape) is a key determinant of evolution, yet it has mostly been used as a superficial metaphor because we know little about its structure. This is now changing, as real fitness landscapes are being analysed by constructing genotypes with all possible combinations of small sets of mutations observed in phylogenies or in evolution experiments. In turn, these first glimpses of empirical fitness landscapes inspire theoretical analyses of the predictability of evolution. Here, we review these recent empirical and theoretical developments, identify methodological issues and organizing principles, and discuss possibilities to develop more realistic fitness landscape models.

Split-Ring Springback Simulations with the Non-associated Flow Rule and Evolutionary Elastic-Plasticity Models

NASA Astrophysics Data System (ADS)

Lee, K. J.; Choi, Y.; Choi, H. J.; Lee, J. Y.; Lee, M. G.

2018-03-01

Finite element simulations and experiments for the split-ring test were conducted to investigate the effect of anisotropic constitutive models on the predictive capability of sheet springback. As an alternative to the commonly employed associated flow rule, a non-associated flow rule for Hill1948 yield function was implemented in the simulations. Moreover, the evolution of anisotropy with plastic deformation was efficiently modeled by identifying equivalent plastic strain-dependent anisotropic coefficients. Comparative study with different yield surfaces and elasticity models showed that the split-ring springback could be best predicted when the anisotropy in both the R value and yield stress, their evolution and variable apparent elastic modulus were taken into account in the simulations. Detailed analyses based on deformation paths superimposed on the anisotropic yield functions predicted by different constitutive models were provided to understand the complex springback response in the split-ring test.

Split-Ring Springback Simulations with the Non-associated Flow Rule and Evolutionary Elastic-Plasticity Models

NASA Astrophysics Data System (ADS)

Lee, K. J.; Choi, Y.; Choi, H. J.; Lee, J. Y.; Lee, M. G.

2018-06-01

Finite element simulations and experiments for the split-ring test were conducted to investigate the effect of anisotropic constitutive models on the predictive capability of sheet springback. As an alternative to the commonly employed associated flow rule, a non-associated flow rule for Hill1948 yield function was implemented in the simulations. Moreover, the evolution of anisotropy with plastic deformation was efficiently modeled by identifying equivalent plastic strain-dependent anisotropic coefficients. Comparative study with different yield surfaces and elasticity models showed that the split-ring springback could be best predicted when the anisotropy in both the R value and yield stress, their evolution and variable apparent elastic modulus were taken into account in the simulations. Detailed analyses based on deformation paths superimposed on the anisotropic yield functions predicted by different constitutive models were provided to understand the complex springback response in the split-ring test.

The morphological state space revisited: what do phylogenetic patterns in homoplasy tell us about the number of possible character states?

PubMed Central

Hoyal Cuthill, Jennifer F.

2015-01-01

Biological variety and major evolutionary transitions suggest that the space of possible morphologies may have varied among lineages and through time. However, most models of phylogenetic character evolution assume that the potential state space is finite. Here, I explore what the morphological state space might be like, by analysing trends in homoplasy (repeated derivation of the same character state). Analyses of ten published character matrices are compared against computer simulations with different state space models: infinite states, finite states, ordered states and an ‘inertial' model, simulating phylogenetic constraints. Of these, only the infinite states model results in evolution without homoplasy, a prediction which is not generally met by real phylogenies. Many authors have interpreted the ubiquity of homoplasy as evidence that the number of evolutionary alternatives is finite. However, homoplasy is also predicted by phylogenetic constraints on the morphological distance that can be traversed between ancestor and descendent. Phylogenetic rarefaction (sub-sampling) shows that finite and inertial state spaces do produce contrasting trends in the distribution of homoplasy. Two clades show trends characteristic of phylogenetic inertia, with decreasing homoplasy (increasing consistency index) as we sub-sample more distantly related taxa. One clade shows increasing homoplasy, suggesting exhaustion of finite states. Different clades may, therefore, show different patterns of character evolution. However, when parsimony uninformative characters are excluded (which may occur without documentation in cladistic studies), it may no longer be possible to distinguish inertial and finite state spaces. Interestingly, inertial models predict that homoplasy should be clustered among comparatively close relatives (parallel evolution), whereas finite state models do not. If morphological evolution is often inertial in nature, then homoplasy (false homology) may primarily occur between close relatives, perhaps being replaced by functional analogy at higher taxonomic scales. PMID:26640650

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.

Landscape scale prediction of earthquake-induced landsliding based on seismological and geomorphological parameters.

NASA Astrophysics Data System (ADS)

Marc, O.; Hovius, N.; Meunier, P.; Rault, C.

2017-12-01

In tectonically active areas, earthquakes are an important trigger of landslides with significant impact on hillslopes and river evolutions. However, detailed prediction of landslides locations and properties for a given earthquakes remain difficult.In contrast we propose, landscape scale, analytical prediction of bulk coseismic landsliding, that is total landslide area and volume (Marc et al., 2016a) as well as the regional area within which most landslide must distribute (Marc et al., 2017). The prediction is based on a limited number of seismological (seismic moment, source depth) and geomorphological (landscape steepness, threshold acceleration) parameters, and therefore could be implemented in landscape evolution model aiming at engaging with erosion dynamics at the scale of the seismic cycle. To assess the model we have compiled and normalized estimates of total landslide volume, total landslide area and regional area affected by landslides for 40, 17 and 83 earthquakes, respectively. We have found that low landscape steepness systematically leads to overprediction of the total area and volume of landslides. When this effect is accounted for, the model is able to predict within a factor of 2 the landslide areas and associated volumes for about 70% of the cases in our databases. The prediction of regional area affected do not require a calibration for the landscape steepness and gives a prediction within a factor of 2 for 60% of the database. For 7 out of 10 comprehensive inventories we show that our prediction compares well with the smallest region around the fault containing 95% of the total landslide area. This is a significant improvement on a previously published empirical expression based only on earthquake moment.Some of the outliers seems related to exceptional rock mass strength in the epicentral area or shaking duration and other seismic source complexities ignored by the model. Applications include prediction on the mass balance of earthquakes and this model predicts that only earthquakes generated on a narrow range of fault sizes may cause more erosion than uplift (Marc et al., 2016b), while very large earthquakes are expected to always build topography. The model could also be used to physically calibrate hillslope erosion or perturbations to river network within landscape evolution model.

Temperature evolution during compaction of pharmaceutical powders.

PubMed

Zavaliangos, Antonios; Galen, Steve; Cunningham, John; Winstead, Denita

2008-08-01

A numerical approach to the prediction of temperature evolution in tablet compaction is presented here. It is based on a coupled thermomechanical finite element analysis and a calibrated Drucker-Prager Cap model. This approach is capable of predicting transient temperatures during compaction, which cannot be assessed by experimental techniques due to inherent test limitations. Model predictions are validated with infrared (IR) temperature measurements of the top tablet surface after ejection and match well with experiments. The dependence of temperature fields on speed and degree of compaction are naturally captured. The estimated transient temperatures are maximum at the end of compaction at the center of the tablet and close to the die wall next to the powder/die interface.

Integrated modeling of plasma ramp-up in DIII-D ITER-like and high bootstrap current scenario discharges

NASA Astrophysics Data System (ADS)

Wu, M. Q.; Pan, C. K.; Chan, V. S.; Li, G. Q.; Garofalo, A. M.; Jian, X.; Liu, L.; Ren, Q. L.; Chen, J. L.; Gao, X.; Gong, X. Z.; Ding, S. Y.; Qian, J. P.; Cfetr Physics Team

2018-04-01

Time-dependent integrated modeling of DIII-D ITER-like and high bootstrap current plasma ramp-up discharges has been performed with the equilibrium code EFIT, and the transport codes TGYRO and ONETWO. Electron and ion temperature profiles are simulated by TGYRO with the TGLF (SAT0 or VX model) turbulent and NEO neoclassical transport models. The VX model is a new empirical extension of the TGLF turbulent model [Jian et al., Nucl. Fusion 58, 016011 (2018)], which captures the physics of multi-scale interaction between low-k and high-k turbulence from nonlinear gyro-kinetic simulation. This model is demonstrated to accurately model low Ip discharges from the EAST tokamak. Time evolution of the plasma current density profile is simulated by ONETWO with the experimental current ramp-up rate. The general trend of the predicted evolution of the current density profile is consistent with that obtained from the equilibrium reconstruction with Motional Stark effect constraints. The predicted evolution of βN , li , and βP also agrees well with the experiments. For the ITER-like cases, the predicted electron and ion temperature profiles using TGLF_Sat0 agree closely with the experimental measured profiles, and are demonstrably better than other proposed transport models. For the high bootstrap current case, the predicted electron and ion temperature profiles perform better in the VX model. It is found that the SAT0 model works well at high IP (>0.76 MA) while the VX model covers a wider range of plasma current ( IP > 0.6 MA). The results reported in this paper suggest that the developed integrated modeling could be a candidate for ITER and CFETR ramp-up engineering design modeling.

Prediction of barrier island restoration response and its interactions with the natural environment

NASA Astrophysics Data System (ADS)

Plant, N. G.; Stockdon, H. F.; Flocks, J.; Sallenger, A. H.; Long, J. W.; Cormier, J. M.; Guy, K.; Thompson, D. M.

2012-12-01

A 2-meter high sand berm was constructed along Chandeleur Island, Louisiana, in an attempt to provide protection against the Deepwater Horizon oil spill. Berm construction started in June 2010 and ended in April 2011. Variations in both island morphology and construction of the 15-km long berm resulted in the development of four different morphologies: a berm built on a submerged island platform to the north of the existing island, a berm built seaward of the existing island, a berm built along the island shoreline, and portions of the island where no berm was constructed. These different morphologies provide a natural laboratory for testing the understanding of berm and barrier island response to storms. In particular, the ability to predict berm evolution using statistical modeling of the interactions between the island, berm, and oceanographic processes was tested. This particular test was part of a broader USGS research effort to understand processes that bridge the gap between short-term storm response and longer-term geologic and climate interactions that shape barrier-island systems. Berm construction and subsequent berm and island evolution were monitored using satellite and aerial remote sensing and topographic and bathymetric surveys. To date, significant berm evolution occurred in both the north (including terminal erosion, overwash, and a large breach), center (overwash and numerous breaches), and south (overwash). The response of the central portion of the berm to winter and tropical storms was significant such that none of the residual berm remained within its construction footprint. The evolution of the central portion of the berm was well predicted using a statistical modeling approach that used predicted and modeled wave conditions to identify the likelihood of overwash events. Comparison of different modeled evolution scenarios to the one that was observed showed that berm response was sensitive to the frequency and severity of winter and tropical storms. These findings demonstrate an observation and modeling approach that can be applied to understanding and managing other natural and restored barrier islands.

A Model Connecting Galaxy Masses, Star Formation Rates, and Dust Temperatures across Cosmic Time

NASA Astrophysics Data System (ADS)

Imara, Nia; Loeb, Abraham; Johnson, Benjamin D.; Conroy, Charlie; Behroozi, Peter

2018-02-01

We investigate the evolution of dust content in galaxies from redshifts z = 0 to z = 9.5. Using empirically motivated prescriptions, we model galactic-scale properties—including halo mass, stellar mass, star formation rate, gas mass, and metallicity—to make predictions for the galactic evolution of dust mass and dust temperature in main-sequence galaxies. Our simple analytic model, which predicts that galaxies in the early universe had greater quantities of dust than their low-redshift counterparts, does a good job of reproducing observed trends between galaxy dust and stellar mass out to z ≈ 6. We find that for fixed galaxy stellar mass, the dust temperature increases from z = 0 to z = 6. Our model forecasts a population of low-mass, high-redshift galaxies with interstellar dust as hot as, or hotter than, their more massive counterparts; but this prediction needs to be constrained by observations. Finally, we make predictions for observing 1.1 mm flux density arising from interstellar dust emission with the Atacama Large Millimeter Array.

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.

Evolution of non-interacting entropic dark energy and its phantom nature

NASA Astrophysics Data System (ADS)

Mathew, Titus K.; Murali, Chinthak; Shejeelammal, J.

2016-04-01

Assuming the form of the entropic dark energy (EDE) as it arises from the surface term in the Einstein-Hilbert’s action, its evolution was analyzed in an expanding flat universe. The model parameters were evaluated by constraining the model using the Union data on Type Ia supernovae. We found that in the non-interacting case, the model predicts an early decelerated phase and a later accelerated phase at the background level. The evolutions of the Hubble parameter, dark energy (DE) density, equation of state parameter and deceleration parameter were obtained. The model hardly seems to be supporting the linear perturbation growth for the structure formation. We also found that the EDE shows phantom nature for redshifts z < 0.257. During the phantom epoch, the model predicts big rip effect at which both the scale factor of expansion and the DE density become infinitely large and the big rip time is found to be around 36 Giga years from now.

Rapid evolution accelerates plant population spread in fragmented experimental landscapes.

PubMed

Williams, Jennifer L; Kendall, Bruce E; Levine, Jonathan M

2016-07-29

Predicting the speed of biological invasions and native species migrations requires an understanding of the ecological and evolutionary dynamics of spreading populations. Theory predicts that evolution can accelerate species' spread velocity, but how landscape patchiness--an important control over traits under selection--influences this process is unknown. We manipulated the response to selection in populations of a model plant species spreading through replicated experimental landscapes of varying patchiness. After six generations of change, evolving populations spread 11% farther than nonevolving populations in continuously favorable landscapes and 200% farther in the most fragmented landscapes. The greater effect of evolution on spread in patchier landscapes was consistent with the evolution of dispersal and competitive ability. Accounting for evolutionary change may be critical when predicting the velocity of range expansions. Copyright © 2016, American Association for the Advancement of Science.

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.

Identifying the Flow Physics and Modeling Transient Forces on Two-Dimensional Wings

DTIC Science & Technology

2016-09-02

MODELS USING EDMD (a) ( b ) (c) (d) ( e ) (f) (g) (h... Model EDMD Model , β = 0.5 EDMD Model , optimal β ( b ) Model order 5 10 15 20 25 L im it c y c le f re q u e n c y 0.12 0.125 0.13 0.135 0.14 0.145...GP and EDMD nonlinear models in predicting the evolution of POD coefficients for transitional flow past a cylinder, showing (a) time evolution and ( b

Predictions of barrier island berm evolution in a time-varying storm climatology

USGS Publications Warehouse

Plant, Nathaniel G.; Flocks, James; Stockdon, Hilary F.; Long, Joseph W.; Guy, Kristy K.; Thompson, David M.; Cormier, Jamie M.; Smith, Christopher G.; Miselis, Jennifer L.; Dalyander, P. Soupy

2014-01-01

Low-lying barrier islands are ubiquitous features of the world's coastlines, and the processes responsible for their formation, maintenance, and destruction are related to the evolution of smaller, superimposed features including sand dunes, beach berms, and sandbars. The barrier island and its superimposed features interact with oceanographic forces (e.g., overwash) and exchange sediment with each other and other parts of the barrier island system. These interactions are modulated by changes in storminess. An opportunity to study these interactions resulted from the placement and subsequent evolution of a 2 m high sand berm constructed along the northern Chandeleur Islands, LA. We show that observed berm length evolution is well predicted by a model that was fit to the observations by estimating two parameters describing the rate of berm length change. The model evaluates the probability and duration of berm overwash to predict episodic berm erosion. A constant berm length change rate is also predicted that persists even when there is no overwash. The analysis is extended to a 16 year time series that includes both intraannual and interannual variability of overwash events. This analysis predicts that as many as 10 or as few as 1 day of overwash conditions would be expected each year. And an increase in berm elevation from 2 m to 3.5 m above mean sea level would reduce the expected frequency of overwash events from 4 to just 0.5 event-days per year. This approach can be applied to understanding barrier island and berm evolution at other locations using past and future storm climatologies.

Predictions of barrier island berm evolution in a time-varying storm climatology

NASA Astrophysics Data System (ADS)

Plant, Nathaniel G.; Flocks, James; Stockdon, Hilary F.; Long, Joseph W.; Guy, Kristy; Thompson, David M.; Cormier, Jamie M.; Smith, Christopher G.; Miselis, Jennifer L.; Dalyander, P. Soupy

2014-02-01

Low-lying barrier islands are ubiquitous features of the world's coastlines, and the processes responsible for their formation, maintenance, and destruction are related to the evolution of smaller, superimposed features including sand dunes, beach berms, and sandbars. The barrier island and its superimposed features interact with oceanographic forces (e.g., overwash) and exchange sediment with each other and other parts of the barrier island system. These interactions are modulated by changes in storminess. An opportunity to study these interactions resulted from the placement and subsequent evolution of a 2 m high sand berm constructed along the northern Chandeleur Islands, LA. We show that observed berm length evolution is well predicted by a model that was fit to the observations by estimating two parameters describing the rate of berm length change. The model evaluates the probability and duration of berm overwash to predict episodic berm erosion. A constant berm length change rate is also predicted that persists even when there is no overwash. The analysis is extended to a 16 year time series that includes both intraannual and interannual variability of overwash events. This analysis predicts that as many as 10 or as few as 1 day of overwash conditions would be expected each year. And an increase in berm elevation from 2 m to 3.5 m above mean sea level would reduce the expected frequency of overwash events from 4 to just 0.5 event-days per year. This approach can be applied to understanding barrier island and berm evolution at other locations using past and future storm climatologies.

Probing the evolution of the EAS muon content in the atmosphere with KASCADE-Grande

NASA Astrophysics Data System (ADS)

Apel, W. D.; Arteaga-Velázquez, J. C.; Bekk, K.; Bertaina, M.; Blümer, J.; Bozdog, H.; Brancus, I. M.; Cantoni, E.; Chiavassa, A.; Cossavella, F.; Daumiller, K.; de Souza, V.; Di Pierro, F.; Doll, P.; Engel, R.; Fuhrmann, D.; Gherghel-Lascu, A.; Gils, H. J.; Glasstetter, R.; Grupen, C.; Haungs, A.; Heck, D.; Hörandel, J. R.; Huege, T.; Kampert, K.-H.; Kang, D.; Klages, H. O.; Link, K.; Łuczak, P.; Mathes, H. J.; Mayer, H. J.; Milke, J.; Mitrica, B.; Morello, C.; Oehlschläger, J.; Ostapchenko, S.; Pierog, T.; Rebel, H.; Roth, M.; Schieler, H.; Schoo, S.; Schröder, F. G.; Sima, O.; Toma, G.; Trinchero, G. C.; Ulrich, H.; Weindl, A.; Wochele, J.; Zabierowski, J.

2017-10-01

The evolution of the muon content of very high energy air showers (EAS) in the atmosphere is investigated with data of the KASCADE-Grande observatory. For this purpose, the muon attenuation length in the atmosphere is obtained to Λμ = 1256 ± 85-232+229 (syst) g/cm2 from the experimental data for shower energies between 1016.3 and 1017.0 eV. Comparison of this quantity with predictions of the high-energy hadronic interaction models QGSJET-II-02, SIBYLL 2.1, QGSJET-II-04 and EPOS-LHC reveals that the attenuation of the muon content of measured EAS in the atmosphere is lower than predicted. Deviations are, however, less significant with the post-LHC models. The presence of such deviations seems to be related to a difference between the simulated and the measured zenith angle evolutions of the lateral muon density distributions of EAS, which also causes a discrepancy between the measured absorption lengths of the density of shower muons and the predicted ones at large distances from the EAS core. The studied deficiencies show that all four considered hadronic interaction models fail to describe consistently the zenith angle evolution of the muon content of EAS in the aforesaid energy regime.

An improved numerical model suggests potential differences of wind-blown sand between on Earth and Mars

NASA Astrophysics Data System (ADS)

Bo, T. L.; Fu, L. T.; Liu, L.; Zheng, X. J.

2017-06-01

The studies on wind-blown sand are crucial for understanding the change of climate and landscape on Mars. However, the disadvantages of the saltation models may result in unreliable predictions. In this paper, the saltation model has been improved from two main aspects, the aerodynamic surface roughness and the lift-off parameters. The aerodynamic surface roughness is expressed as function of particle size, wind strength, air density, and air dynamic viscosity. The lift-off parameters are improved through including the dependence of restitution coefficient on incident parameters and the correlation between saltating speed and angle. The improved model proved to be capable of reproducing the observed data well in both stable stage and evolution process. The modeling of wind-blown sand is promoted by all improved aspects, and the dependence of restitution coefficient on incident parameters could not be ignored. The constant restitution coefficient and uncorrelated lift-off parameter distributions would lead to both the overestimation of the sand transport rate and apparent surface roughness and the delay of evolution process. The distribution of lift-off speed and the evolution of lift-off parameters on Mars are found to be different from those on Earth. This may thus suggest that it is inappropriate to predict the evolution of wind-blown sand by using the lift-off velocity obtained in steady state saltation. And it also may be problematic to predict the wind-blown sand on Mars through applying the lift-off velocity obtained upon terrestrial conditions directly.

Evolution of dispersal in spatially and temporally variable environments: The importance of life cycles.

PubMed

Massol, François; Débarre, Florence

2015-07-01

Spatiotemporal variability of the environment is bound to affect the evolution of dispersal, and yet model predictions strongly differ on this particular effect. Recent studies on the evolution of local adaptation have shown that the life cycle chosen to model the selective effects of spatiotemporal variability of the environment is a critical factor determining evolutionary outcomes. Here, we investigate the effect of the order of events in the life cycle on the evolution of unconditional dispersal in a spatially heterogeneous, temporally varying landscape. Our results show that the occurrence of intermediate singular strategies and disruptive selection are conditioned by the temporal autocorrelation of the environment and by the life cycle. Life cycles with dispersal of adults versus dispersal of juveniles, local versus global density regulation, give radically different evolutionary outcomes that include selection for total philopatry, evolutionary bistability, selection for intermediate stable states, and evolutionary branching points. Our results highlight the importance of accounting for life-cycle specifics when predicting the effects of the environment on evolutionarily selected trait values, such as dispersal, as well as the need to check the robustness of model conclusions against modifications of the life cycle. © 2015 The Author(s). Evolution © 2015 The Society for the Study of Evolution.

Integrating machine learning to achieve an automatic parameter prediction for practical continuous-variable quantum key distribution

NASA Astrophysics Data System (ADS)

Liu, Weiqi; Huang, Peng; Peng, Jinye; Fan, Jianping; Zeng, Guihua

2018-02-01

For supporting practical quantum key distribution (QKD), it is critical to stabilize the physical parameters of signals, e.g., the intensity, phase, and polarization of the laser signals, so that such QKD systems can achieve better performance and practical security. In this paper, an approach is developed by integrating a support vector regression (SVR) model to optimize the performance and practical security of the QKD system. First, a SVR model is learned to precisely predict the time-along evolutions of the physical parameters of signals. Second, such predicted time-along evolutions are employed as feedback to control the QKD system for achieving the optimal performance and practical security. Finally, our proposed approach is exemplified by using the intensity evolution of laser light and a local oscillator pulse in the Gaussian modulated coherent state QKD system. Our experimental results have demonstrated three significant benefits of our SVR-based approach: (1) it can allow the QKD system to achieve optimal performance and practical security, (2) it does not require any additional resources and any real-time monitoring module to support automatic prediction of the time-along evolutions of the physical parameters of signals, and (3) it is applicable to any measurable physical parameter of signals in the practical QKD system.

Short-term predictions in forex trading

NASA Astrophysics Data System (ADS)

Muriel, A.

2004-12-01

Using a kinetic equation that is used to model turbulence (Physica A, 1985-1988, Physica D, 2001-2003), we redefine variables to model the time evolution of the foreign exchange rates of three major currencies. We display live and predicted data for one period of trading in October, 2003.

Tectonic predictions with mantle convection models

NASA Astrophysics Data System (ADS)

Coltice, Nicolas; Shephard, Grace E.

2018-04-01

Over the past 15 yr, numerical models of convection in Earth's mantle have made a leap forward: they can now produce self-consistent plate-like behaviour at the surface together with deep mantle circulation. These digital tools provide a new window into the intimate connections between plate tectonics and mantle dynamics, and can therefore be used for tectonic predictions, in principle. This contribution explores this assumption. First, initial conditions at 30, 20, 10 and 0 Ma are generated by driving a convective flow with imposed plate velocities at the surface. We then compute instantaneous mantle flows in response to the guessed temperature fields without imposing any boundary conditions. Plate boundaries self-consistently emerge at correct locations with respect to reconstructions, except for small plates close to subduction zones. As already observed for other types of instantaneous flow calculations, the structure of the top boundary layer and upper-mantle slab is the dominant character that leads to accurate predictions of surface velocities. Perturbations of the rheological parameters have little impact on the resulting surface velocities. We then compute fully dynamic model evolution from 30 and 10 to 0 Ma, without imposing plate boundaries or plate velocities. Contrary to instantaneous calculations, errors in kinematic predictions are substantial, although the plate layout and kinematics in several areas remain consistent with the expectations for the Earth. For these calculations, varying the rheological parameters makes a difference for plate boundary evolution. Also, identified errors in initial conditions contribute to first-order kinematic errors. This experiment shows that the tectonic predictions of dynamic models over 10 My are highly sensitive to uncertainties of rheological parameters and initial temperature field in comparison to instantaneous flow calculations. Indeed, the initial conditions and the rheological parameters can be good enough for an accurate prediction of instantaneous flow, but not for a prediction after 10 My of evolution. Therefore, inverse methods (sequential or data assimilation methods) using short-term fully dynamic evolution that predict surface kinematics are promising tools for a better understanding of the state of the Earth's mantle.

Understanding the Early Evolution of M dwarf Extreme Ultraviolet Radiation

NASA Astrophysics Data System (ADS)

Peacock, Sarah; Barman, Travis; Shkolnik, Evgenya

2015-11-01

The chemistry and evolution of planetary atmospheres depends on the evolution of high-energy radiation emitted by its host star. High levels of extreme ultraviolet (EUV) radiation can drastically alter the atmospheres of terrestrial planets through ionizing, heating, expanding, chemically modifying and eroding them during the first few billion years of a planetary lifetime. While there is evidence that stars emit their highest levels of far and near ultraviolet (FUV; NUV) radiation in the earliest stages of their evolution, we are currently unable to directly measure the EUV radiation. Most previous stellar atmosphere models under-predict FUV and EUV emission from M dwarfs; here we present new models for M stars that include prescriptions for the hot, lowest density atmospheric layers (chromosphere, transition region and corona), from which this radiation is emitted. By comparing our model spectra to GALEX near and far ultraviolet fluxes, we are able to predict the evolution of EUV radiation for M dwarfs from 10 Myr to a few Gyr. This research is the next major step in the HAZMAT (HAbitable Zones and M dwarf Activity across Time) project to analyze how the habitable zone evolves with the evolving properties of stellar and planetary atmospheres.

Prediction of cloud condensation nuclei activity for organic compounds using functional group contribution methods

DOE PAGES

Petters, M. D.; Kreidenweis, S. M.; Ziemann, P. J.

2016-01-19

A wealth of recent laboratory and field experiments demonstrate that organic aerosol composition evolves with time in the atmosphere, leading to changes in the influence of the organic fraction to cloud condensation nuclei (CCN) spectra. There is a need for tools that can realistically represent the evolution of CCN activity to better predict indirect effects of organic aerosol on clouds and climate. This work describes a model to predict the CCN activity of organic compounds from functional group composition. Following previous methods in the literature, we test the ability of semi-empirical group contribution methods in Kohler theory to predict themore » effective hygroscopicity parameter, kappa. However, in our approach we also account for liquid–liquid phase boundaries to simulate phase-limited activation behavior. Model evaluation against a selected database of published laboratory measurements demonstrates that kappa can be predicted within a factor of 2. Simulation of homologous series is used to identify the relative effectiveness of different functional groups in increasing the CCN activity of weakly functionalized organic compounds. Hydroxyl, carboxyl, aldehyde, hydroperoxide, carbonyl, and ether moieties promote CCN activity while methylene and nitrate moieties inhibit CCN activity. Furthermore, the model can be incorporated into scale-bridging test beds such as the Generator of Explicit Chemistry and Kinetics of Organics in the Atmosphere (GECKO-A) to evaluate the evolution of kappa for a complex mix of organic compounds and to develop suitable parameterizations of CCN evolution for larger-scale models.« less

Modelling rate distributions using character compatibility: implications for morphological evolution among fossil invertebrates.

PubMed

Wagner, Peter J

2012-02-23

Rate distributions are important considerations when testing hypotheses about morphological evolution or phylogeny. They also have implications about general processes underlying character evolution. Molecular systematists often assume that rates are Poisson processes with gamma distributions. However, morphological change is the product of multiple probabilistic processes and should theoretically be affected by hierarchical integration of characters. Both factors predict lognormal rate distributions. Here, a simple inverse modelling approach assesses the best single-rate, gamma and lognormal models given observed character compatibility for 115 invertebrate groups. Tests reject the single-rate model for nearly all cases. Moreover, the lognormal outperforms the gamma for character change rates and (especially) state derivation rates. The latter in particular is consistent with integration affecting morphological character evolution.

A Review of Texture Evolution Mechanisms During Deformation by Rolling in Aluminum Alloys

NASA Astrophysics Data System (ADS)

Li, Shasha; Zhao, Qi; Liu, Zhiyi; Li, Fudong

2018-06-01

The current understanding of texture evolution during deformation by rolling in aluminum alloys was summarized. This included understanding the evolution mechanisms and several key factors of initial texture, microstructure, alloy composition, deformation temperature, stress-strain condition, and rolling geometry. Related models on predicting texture evolution during rolling were also discussed. Finally, for this research field, the recommendations for controlling the formation of rolling textures were proposed.

High-Temperature Cast Aluminum for Efficient Engines

NASA Astrophysics Data System (ADS)

Bobel, Andrew C.

Accurate thermodynamic databases are the foundation of predictive microstructure and property models. An initial assessment of the commercially available Thermo-Calc TCAL2 database and the proprietary aluminum database of QuesTek demonstrated a large degree of deviation with respect to equilibrium precipitate phase prediction in the compositional region of interest when compared to 3-D atom probe tomography (3DAPT) and transmission electron microscopy (TEM) experimental results. New compositional measurements of the Q-phase (Al-Cu-Mg-Si phase) led to a remodeling of the Q-phase thermodynamic description in the CALPHAD databases which has produced significant improvements in the phase prediction capabilities of the thermodynamic model. Due to the unique morphologies of strengthening precipitate phases commonly utilized in high-strength cast aluminum alloys, the development of new microstructural evolution models to describe both rod and plate particle growth was critical for accurate mechanistic strength models which rely heavily on precipitate size and shape. Particle size measurements through both 3DAPT and TEM experiments were used in conjunction with literature results of many alloy compositions to develop a physical growth model for the independent prediction of rod radii and rod length evolution. In addition a machine learning (ML) model was developed for the independent prediction of plate thickness and plate diameter evolution as a function of alloy composition, aging temperature, and aging time. The developed models are then compared with physical growth laws developed for spheres and modified for ellipsoidal morphology effects. Analysis of the effect of particle morphology on strength enhancement has been undertaken by modification of the Orowan-Ashby equation for 〈110〉 alpha-Al oriented finite rods in addition to an appropriate version for similarly oriented plates. A mechanistic strengthening model was developed for cast aluminum alloys containing both rod and plate-like precipitates. The model accurately accounts for the temperature dependence of particle nucleation and growth, solid solution strengthening, Si eutectic strength, and base aluminum yield strength. Strengthening model predictions of tensile yield strength are in excellent agreement with experimental observations over a wide range of aluminum alloy systems, aging temperatures, and test conditions. The developed models enable the prediction of the required particle morphology and volume fraction necessary to achieve target property goals in the design of future aluminum alloys. The effect of partitioning elements to the Q-phase was also considered for the potential to control the nucleation rate, reduce coarsening, and control the evolution of particle morphology. Elements were selected based on density functional theory (DFT) calculations showing the prevalence of certain elements to partition to the Q-phase. 3DAPT experiments were performed on Q-phase containing wrought alloys with these additions and show segregation of certain elements to the Q-phase with relative agreement to DFT predictions.

Continuously growing rodent molars result from a predictable quantitative evolutionary change over 50 million years

PubMed Central

Mushegyan, Vagan; Eronen, Jussi T.; Lawing, A. Michelle; Sharir, Amnon; Janis, Christine; Jernvall, Jukka; Klein, Ophir D.

2015-01-01

Summary The fossil record is widely informative about evolution, but fossils are not systematically used to study the evolution of stem cell-driven renewal. Here, we examined evolution of the continuous growth (hypselodonty) of rodent molar teeth, which is fuelled by the presence of dental stem cells. We studied occurrences of 3500 North American rodent fossils, ranging from 50 million years ago (mya) to 2 mya. We examined changes in molar height to determine if evolution of hypselodonty shows distinct patterns in the fossil record, and we found that hypselodont taxa emerged through intermediate forms of increasing crown height. Next, we designed a Markov simulation model, which replicated molar height increases throughout the Cenozoic, and, moreover, evolution of hypselodonty. Thus, by extension, the retention of the adult stem-cell niche appears to be a predictable quantitative rather than a stochastic qualitative process. Our analyses predict that hypselodonty will eventually become the dominant phenotype. PMID:25921530

Evolution of the social network of scientific collaborations

NASA Astrophysics Data System (ADS)

Barabási, A. L.; Jeong, H.; Néda, Z.; Ravasz, E.; Schubert, A.; Vicsek, T.

2002-08-01

The co-authorship network of scientists represents a prototype of complex evolving networks. In addition, it offers one of the most extensive database to date on social networks. By mapping the electronic database containing all relevant journals in mathematics and neuro-science for an 8-year period (1991-98), we infer the dynamic and the structural mechanisms that govern the evolution and topology of this complex system. Three complementary approaches allow us to obtain a detailed characterization. First, empirical measurements allow us to uncover the topological measures that characterize the network at a given moment, as well as the time evolution of these quantities. The results indicate that the network is scale-free, and that the network evolution is governed by preferential attachment, affecting both internal and external links. However, in contrast with most model predictions the average degree increases in time, and the node separation decreases. Second, we propose a simple model that captures the network's time evolution. In some limits the model can be solved analytically, predicting a two-regime scaling in agreement with the measurements. Third, numerical simulations are used to uncover the behavior of quantities that could not be predicted analytically. The combined numerical and analytical results underline the important role internal links play in determining the observed scaling behavior and network topology. The results and methodologies developed in the context of the co-authorship network could be useful for a systematic study of other complex evolving networks as well, such as the world wide web, Internet, or other social networks.

Evolution of Secondary Phases Formed upon Solidification of a Ni-Based Alloy

NASA Astrophysics Data System (ADS)

Zuo, Qiang; Liu, Feng; Wang, Lei; Chen, Changfeng

2013-07-01

The solidification of UNS N08028 alloy subjected to different cooling rates was studied, where primary austenite dendrites occur predominantly and different amounts of sigma phase form in the interdendritic regions. The solidification path and elemental segregation upon solidification were simulated using the CALPHAD method, where THERMO-CALC software packages and two classical segregation models were employed to predict the real process. It is thus revealed that the interdendritic sigma phase is formed via eutectic reaction at the last stage of solidification. On this basis, an analytical model was developed to predict the evolution of nonequilibrium eutectic phase, while the isolated morphology of sigma phase can be described using divorced eutectic theory. Size, fraction, and morphology of the sigma phase were quantitatively studied by a series of experiments; the results are in good agreement with the model prediction.

Modeling the evolution of infrared galaxies: a parametric backward evolution model

NASA Astrophysics Data System (ADS)

Béthermin, M.; Dole, H.; Lagache, G.; Le Borgne, D.; Penin, A.

2011-05-01

Aims: We attempt to model the infrared galaxy evolution in as simple a way as possible and reproduce statistical properties such as the number counts between 15 μm and 1.1 mm, the luminosity functions, and the redshift distributions. We then use the fitted model to interpret observations from Spitzer, AKARI, BLAST, LABOCA, AzTEC, SPT, and Herschel, and make predictions for Planck and future experiments such as CCAT or SPICA. Methods: This model uses an evolution in density and luminosity of the luminosity function parametrized by broken power-laws with two breaks at redshift ~0.9 and 2, and contains the two populations of the Lagache model: normal and starburst galaxies. We also take into account the effect of the strong lensing of high-redshift sub-millimeter galaxies. This effect is significant in the sub-mm and mm range near 50 mJy. It has 13 free parameters and eight additional calibration parameters. We fit the parameters to the IRAS, Spitzer, Herschel, and AzTEC measurements with a Monte Carlo Markov chain. Results: The model adjusted to deep counts at key wavelengths reproduces the counts from mid-infrared to millimeter wavelengths, as well as the mid-infrared luminosity functions. We discuss the contribution to both the cosmic infrared background (CIB) and the infrared luminosity density of the different populations. We also estimate the effect of the lensing on the number counts, and discuss the discovery by the South Pole Telescope (SPT) of a very bright population lying at high redshift. We predict the contribution of the lensed sources to the Planck number counts, the confusion level for future missions using a P(D) formalism, and the Universe opacity to TeV photons caused by the CIB. Material of the model (software, tables and predictions) is available online.

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.

Intergranular Strain Evolution During Biaxial Loading: A Multiscale FE-FFT Approach

NASA Astrophysics Data System (ADS)

Upadhyay, M. V.; Capek, J.; Van Petegem, S.; Lebensohn, R. A.; Van Swygenhoven, H.

2017-05-01

Predicting the macroscopic and microscopic mechanical response of metals and alloys subjected to complex loading conditions necessarily requires a synergistic combination of multiscale material models and characterization techniques. This article focuses on the use of a multiscale approach to study the difference between intergranular lattice strain evolution for various grain families measured during in situ neutron diffraction on dog bone and cruciform 316L samples. At the macroscale, finite element simulations capture the complex coupling between applied forces and gauge stresses in cruciform geometries. The predicted gauge stresses are used as macroscopic boundary conditions to drive a mesoscale full-field elasto-viscoplastic fast Fourier transform crystal plasticity model. The results highlight the role of grain neighborhood on the intergranular strain evolution under uniaxial and equibiaxial loading.

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

NASA Astrophysics Data System (ADS)

Hashino, Tempei

2007-05-01

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

Prediction of stock markets by the evolutionary mix-game model

NASA Astrophysics Data System (ADS)

Chen, Fang; Gou, Chengling; Guo, Xiaoqian; Gao, Jieping

2008-06-01

This paper presents the efforts of using the evolutionary mix-game model, which is a modified form of the agent-based mix-game model, to predict financial time series. Here, we have carried out three methods to improve the original mix-game model by adding the abilities of strategy evolution to agents, and then applying the new model referred to as the evolutionary mix-game model to forecast the Shanghai Stock Exchange Composite Index. The results show that these modifications can improve the accuracy of prediction greatly when proper parameters are chosen.

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.

Understanding the evolution and propagation of coronal mass ejections and associated plasma sheaths in interplanetary space

NASA Astrophysics Data System (ADS)

Hess, Phillip

A Coronal Mass Ejection (CME) is an eruption of magnetized plasma from the Coronaof the Sun. Understanding the physical process of CMEs is a fundamental challenge in solarphysics, and is also of increasing importance for our technological society. CMEs are knownthe main driver of space weather that has adverse effects on satellites, power grids, com-munication and navigation systems and astronauts. Understanding and predicting CMEs is still in the early stage of research. In this dissertation, improved observational methods and advanced theoretical analysis are used to study CMEs. Unlike many studies in the past that treat CMEs as a single object, this study divides aCME into two separate components: the ejecta from the corona and the sheath region thatis the ambient plasma compressed by the shock/wave running ahead of the ejecta; bothstructures are geo-effective but evolve differently. Stereoscopic observations from multiplespacecraft, including STEREO and SOHO, are combined to provide a three-dimensionalgeometric reconstruction of the structures studied. True distances and velocities of CMEs are accurately determined, free of projection effects, and with continuous tracking from the low corona to 1 AU.To understand the kinematic evolution of CMEs, an advanced drag-based model (DBM) is proposed, with several improvements to the original DBM model. The new model varies the drag parameter with distance; the variation is constrained by thenecessary conservation of physical parameters. Second, the deviation of CME-nose from the Sun-Earth-line is taken into account. Third, the geometric correction of the shape of the ejecta front is considered, based on the assumption that the true front is a flattened croissant-shaped flux rope front. These improvements of the DBM model provide a framework for using measurement data to make accurate prediction of the arrival times of CME ejecta and sheaths. Using a set of seven events to test the model, it is found that the evolution of the ejecta front can be accurately predicted, with a slightly poorer performance on the sheath front. To improve the sheath prediction, the standoff-distance between the ejecta and the sheath front is used to model the evolution. The predicted arrivals of both the sheath and ejecta fronts at Earth are determined to within an average 3.5 hours and 1.5 hours of observed arrivals,respectively. These prediction errors show a significant improvement over predictions made by other researches. The results of this dissertation study demonstrate that accurate space weather prediction is possible, and also reveals what observations are needed in the future for realistic operational space weather prediction.

Extreme possible variations of the deuterium abundance within the Galaxy

NASA Astrophysics Data System (ADS)

Delbourgo-Salvador, P.; Audouze, J.; Vidal-Madjar, A.

1987-03-01

In order to reconcile the present baryonic densities deduced respectively from the primordial abundances of D and 4He, some recent chemical evolution models imply that D could have been destroyed more thoroughly during the Galaxy evolution than what was previously predicted. Under the conditions outlined by these models, the present abundance of D may vary by factors as large as 50 in different parts of the Galaxy. If such variations are not observed, this implies that the ratio X(D)prim/X(D)present is not large (2 - 3): the simplest Big Bang models may then be unable to reconcile the baryonic densities predicted by D and 4He respectively.

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.

Meta-analysis suggests choosy females get sexy sons more than "good genes".

PubMed

Prokop, Zofia M; Michalczyk, Łukasz; Drobniak, Szymon M; Herdegen, Magdalena; Radwan, Jacek

2012-09-01

Female preferences for specific male phenotypes have been documented across a wide range of animal taxa, including numerous species where males contribute only gametes to offspring production. Yet, selective pressures maintaining such preferences are among the major unknowns of evolutionary biology. Theoretical studies suggest that preferences can evolve if they confer genetic benefits in terms of increased attractiveness of sons ("Fisherian" models) or overall fitness of offspring ("good genes" models). These two types of models predict, respectively, that male attractiveness is heritable and genetically correlated with fitness. In this meta-analysis, we draw general conclusions from over two decades worth of empirical studies testing these predictions (90 studies on 55 species in total). We found evidence for heritability of male attractiveness. However, attractiveness showed no association with traits directly associated with fitness (life-history traits). Interestingly, it did show a positive correlation with physiological traits, which include immunocompetence and condition. In conclusion, our results support "Fisherian" models of preference evolution, while providing equivocal evidence for "good genes." We pinpoint research directions that should stimulate progress in our understanding of the evolution of female choice. © 2012 The Author(s). Evolution© 2012 The Society for the Study of Evolution.

Simulation of Seasonal Snow Microwave TB Using Coupled Multi-Layered Snow Evolution and Microwave Emission Models

NASA Technical Reports Server (NTRS)

Brucker, Ludovic; Royer, Alain; Picard, Ghislain; Langlois, Alex; Fily, Michel

2014-01-01

The accurate quantification of SWE has important societal benefits, including improving domestic and agricultural water planning, flood forecasting and electric power generation. However, passive-microwave SWE algorithms suffer from variations in TB due to snow metamorphism, difficult to distinguish from those due to SWE variations. Coupled snow evolution-emission models are able to predict snow metamorphism, allowing us to account for emissivity changes. They can also be used to identify weaknesses in the snow evolution model. Moreover, thoroughly evaluating coupled models is a contribution toward the assimilation of TB, which leads to a significant increase in the accuracy of SWE estimates.

A review: applications of the phase field method in predicting microstructure and property evolution of irradiated nuclear materials

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

Li, Yulan; Hu, Shenyang; Sun, Xin

Here, complex microstructure changes occur in nuclear fuel and structural materials due to the extreme environments of intense irradiation and high temperature. This paper evaluates the role of the phase field method in predicting the microstructure evolution of irradiated nuclear materials and the impact on their mechanical, thermal, and magnetic properties. The paper starts with an overview of the important physical mechanisms of defect evolution and the significant gaps in simulating microstructure evolution in irradiated nuclear materials. Then, the phase field method is introduced as a powerful and predictive tool and its applications to microstructure and property evolution in irradiatedmore » nuclear materials are reviewed. The review shows that (1) Phase field models can correctly describe important phenomena such as spatial-dependent generation, migration, and recombination of defects, radiation-induced dissolution, the Soret effect, strong interfacial energy anisotropy, and elastic interaction; (2) The phase field method can qualitatively and quantitatively simulate two-dimensional and three-dimensional microstructure evolution, including radiation-induced segregation, second phase nucleation, void migration, void and gas bubble superlattice formation, interstitial loop evolution, hydrate formation, and grain growth, and (3) The Phase field method correctly predicts the relationships between microstructures and properties. The final section is dedicated to a discussion of the strengths and limitations of the phase field method, as applied to irradiation effects in nuclear materials.« less

A review: applications of the phase field method in predicting microstructure and property evolution of irradiated nuclear materials

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

Li, Yulan; Hu, Shenyang; Sun, Xin

Complex microstructure changes occur in nuclear fuel and structural materials due to the extreme environments of intense irradiation and high temperature. This paper evaluates the role of the phase field (PF) method in predicting the microstructure evolution of irradiated nuclear materials and the impact on their mechanical, thermal, and magnetic properties. The paper starts with an overview of the important physical mechanisms of defect evolution and the significant gaps in simulating microstructure evolution in irradiated nuclear materials. Then, the PF method is introduced as a powerful and predictive tool and its applications to microstructure and property evolution in irradiated nuclearmore » materials are reviewed. The review shows that 1) FP models can correctly describe important phenomena such as spatial dependent generation, migration, and recombination of defects, radiation-induced dissolution, the Soret effect, strong interfacial energy anisotropy, and elastic interaction; 2) The PF method can qualitatively and quantitatively simulate 2-D and 3-D microstructure evolution, including radiation-induced segregation, second phase nucleation, void migration, void and gas bubble superlattice formation, interstitial loop evolution, hydrate formation, and grain growth, and 3) The FP method correctly predicts the relationships between microstructures and properties. The final section is dedicated to a discussion of the strengths and limitations of the PF method, as applied to irradiation effects in nuclear materials.« less

A review: applications of the phase field method in predicting microstructure and property evolution of irradiated nuclear materials

DOE PAGES

Li, Yulan; Hu, Shenyang; Sun, Xin; ...

2017-04-14

Here, complex microstructure changes occur in nuclear fuel and structural materials due to the extreme environments of intense irradiation and high temperature. This paper evaluates the role of the phase field method in predicting the microstructure evolution of irradiated nuclear materials and the impact on their mechanical, thermal, and magnetic properties. The paper starts with an overview of the important physical mechanisms of defect evolution and the significant gaps in simulating microstructure evolution in irradiated nuclear materials. Then, the phase field method is introduced as a powerful and predictive tool and its applications to microstructure and property evolution in irradiatedmore » nuclear materials are reviewed. The review shows that (1) Phase field models can correctly describe important phenomena such as spatial-dependent generation, migration, and recombination of defects, radiation-induced dissolution, the Soret effect, strong interfacial energy anisotropy, and elastic interaction; (2) The phase field method can qualitatively and quantitatively simulate two-dimensional and three-dimensional microstructure evolution, including radiation-induced segregation, second phase nucleation, void migration, void and gas bubble superlattice formation, interstitial loop evolution, hydrate formation, and grain growth, and (3) The Phase field method correctly predicts the relationships between microstructures and properties. The final section is dedicated to a discussion of the strengths and limitations of the phase field method, as applied to irradiation effects in nuclear materials.« less

Extended Kalman Filter framework for forecasting shoreline evolution

USGS Publications Warehouse

Long, Joseph; Plant, Nathaniel G.

2012-01-01

A shoreline change model incorporating both long- and short-term evolution is integrated into a data assimilation framework that uses sparse observations to generate an updated forecast of shoreline position and to estimate unobserved geophysical variables and model parameters. Application of the assimilation algorithm provides quantitative statistical estimates of combined model-data forecast uncertainty which is crucial for developing hazard vulnerability assessments, evaluation of prediction skill, and identifying future data collection needs. Significant attention is given to the estimation of four non-observable parameter values and separating two scales of shoreline evolution using only one observable morphological quantity (i.e. shoreline position).

Joint Prediction of Longitudinal Development of Cortical Surfaces and White Matter Fibers from Neonatal MRI

PubMed Central

Rekik, Islem; Li, Gang; Yap, Pew-Thian; Chen, Geng; Lin, Weili; Shen, Dinggang

2017-01-01

The human brain can be modeled as multiple interrelated shapes (or a multishape), each for characterizing one aspect of the brain, such as the cortex and white matter pathways. Predicting the developing multishape is a very challenging task due to the contrasting nature of the developmental trajectories of the constituent shapes: smooth for the cortical surface and non-smooth for white matter tracts due to changes such as bifurcation. We recently addressed this problem and proposed an approach for predicting the multishape developmental spatiotemporal trajectories of infant brains based only on neonatal MRI data using a set of geometric, dynamic, and fiber-to-surface connectivity features. In this paper, we propose two key innovations to further improve the prediction of multishape evolution. First, for a more accurate cortical surface prediction, instead of simply relying on one neonatal atlas to guide the prediction of the multishape, we propose to use multiple neonatal atlases to build a spatially heterogeneous atlas using the multidirectional varifold representation. This individualizes the atlas by locally maximizing its similarity to the testing baseline cortical shape for each cortical region, thereby better representing the baseline testing cortical surface, which founds the multishape prediction process. Second, for temporally consistent fiber prediction, we propose to reliably estimate spatiotemporal connectivity features using low-rank tensor completion, thereby capturing the variability and richness of the temporal development of fibers. Experimental results confirm that the proposed variants significantly improve the prediction performance of our original multishape prediction framework for both cortical surfaces and fiber tracts shape at 3, 6, and 9 months of age. Our pioneering model will pave the way for learning how to predict the evolution of anatomical shapes with abnormal changes. Ultimately, devising accurate shape evolution prediction models that can help quantify and predict the severity of a brain disorder as it progresses will be of great aid in individualized treatment planning. PMID:28284800

Joint prediction of longitudinal development of cortical surfaces and white matter fibers from neonatal MRI.

PubMed

Rekik, Islem; Li, Gang; Yap, Pew-Thian; Chen, Geng; Lin, Weili; Shen, Dinggang

2017-05-15

The human brain can be modeled as multiple interrelated shapes (or a multishape), each for characterizing one aspect of the brain, such as the cortex and white matter pathways. Predicting the developing multishape is a very challenging task due to the contrasting nature of the developmental trajectories of the constituent shapes: smooth for the cortical surface and non-smooth for white matter tracts due to changes such as bifurcation. We recently addressed this problem and proposed an approach for predicting the multishape developmental spatiotemporal trajectories of infant brains based only on neonatal MRI data using a set of geometric, dynamic, and fiber-to-surface connectivity features. In this paper, we propose two key innovations to further improve the prediction of multishape evolution. First, for a more accurate cortical surface prediction, instead of simply relying on one neonatal atlas to guide the prediction of the multishape, we propose to use multiple neonatal atlases to build a spatially heterogeneous atlas using the multidirectional varifold representation. This individualizes the atlas by locally maximizing its similarity to the testing baseline cortical shape for each cortical region, thereby better representing the baseline testing cortical surface, which founds the multishape prediction process. Second, for temporally consistent fiber prediction, we propose to reliably estimate spatiotemporal connectivity features using low-rank tensor completion, thereby capturing the variability and richness of the temporal development of fibers. Experimental results confirm that the proposed variants significantly improve the prediction performance of our original multishape prediction framework for both cortical surfaces and fiber tracts shape at 3, 6, and 9 months of age. Our pioneering model will pave the way for learning how to predict the evolution of anatomical shapes with abnormal changes. Ultimately, devising accurate shape evolution prediction models that can help quantify and predict the severity of a brain disorder as it progresses will be of great aid in individualized treatment planning. Copyright © 2017 Elsevier Inc. All rights reserved.

A novel multilayer model for missing link prediction and future link forecasting in dynamic complex networks

NASA Astrophysics Data System (ADS)

Yasami, Yasser; Safaei, Farshad

2018-02-01

The traditional complex network theory is particularly focused on network models in which all network constituents are dealt with equivalently, while fail to consider the supplementary information related to the dynamic properties of the network interactions. This is a main constraint leading to incorrect descriptions of some real-world phenomena or incomplete capturing the details of certain real-life problems. To cope with the problem, this paper addresses the multilayer aspects of dynamic complex networks by analyzing the properties of intrinsically multilayered co-authorship networks, DBLP and Astro Physics, and presenting a novel multilayer model of dynamic complex networks. The model examines the layers evolution (layers birth/death process and lifetime) throughout the network evolution. Particularly, this paper models the evolution of each node's membership in different layers by an Infinite Factorial Hidden Markov Model considering feature cascade, and thereby formulates the link generation process for intra-layer and inter-layer links. Although adjacency matrixes are useful to describe the traditional single-layer networks, such a representation is not sufficient to describe and analyze the multilayer dynamic networks. This paper also extends a generalized mathematical infrastructure to address the problems issued by multilayer complex networks. The model inference is performed using some Markov Chain Monte Carlo sampling strategies, given synthetic and real complex networks data. Experimental results indicate a tremendous improvement in the performance of the proposed multilayer model in terms of sensitivity, specificity, positive and negative predictive values, positive and negative likelihood ratios, F1-score, Matthews correlation coefficient, and accuracy for two important applications of missing link prediction and future link forecasting. The experimental results also indicate the strong predictivepower of the proposed model for the application of cascade prediction in terms of accuracy.

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

Chaos and unpredictability in evolution.

PubMed

Doebeli, Michael; Ispolatov, Iaroslav

2014-05-01

The possibility of complicated dynamic behavior driven by nonlinear feedbacks in dynamical systems has revolutionized science in the latter part of the last century. Yet despite examples of complicated frequency dynamics, the possibility of long-term evolutionary chaos is rarely considered. The concept of "survival of the fittest" is central to much evolutionary thinking and embodies a perspective of evolution as a directional optimization process exhibiting simple, predictable dynamics. This perspective is adequate for simple scenarios, when frequency-independent selection acts on scalar phenotypes. However, in most organisms many phenotypic properties combine in complicated ways to determine ecological interactions, and hence frequency-dependent selection. Therefore, it is natural to consider models for evolutionary dynamics generated by frequency-dependent selection acting simultaneously on many different phenotypes. Here we show that complicated, chaotic dynamics of long-term evolutionary trajectories in phenotype space is very common in a large class of such models when the dimension of phenotype space is large, and when there are selective interactions between the phenotypic components. Our results suggest that the perspective of evolution as a process with simple, predictable dynamics covers only a small fragment of long-term evolution. © 2014 The Author(s). Evolution © 2014 The Society for the Study of Evolution.

Testing Lithospheric versus Deep-Mantle Dynamics on Post-100 Ma Evolution of Western U.S. using Landscape Evolution Modeling

NASA Astrophysics Data System (ADS)

Chang, C.; Liu, L.

2017-12-01

Driving mechanisms of the topographic evolution of central-western North America from the Cretaceous Western Interior Seaway (WIS) to its present-day high elevation remain ellusive. Quantifying the effects of lithospheric deformation versus deep-mantle induced topography on the landscape evolution of the region is a key to better constraining the history of North American tectonics and mantle dynamics. One way to tackle this problem is through running landscape evolution simulation coupled with uplift histories characteristic to these tectonic processes. We then use available surface observations, e.g., sedimentation records, land erosion, and drainage evolution, to infer the likely lithospheric and mantle processes that formed the WIS, the subsequent Laramide orogeny, and the present-day high topography of central-western North America. In practice, we use BadLands to simulate the evolution of surface process. To validate a given uplift history, we quantitatively compare model predictions with onshore and offshore stratigraphy data from the literature. Furthermore, critical forcings of landscape evolution, such as climate, lithology and sea level, will also be examined to better attest the effects of different uplift scenarios. Preliminary results demonstrate that only with geographically migratory subsidence, as predicted by an inverse mantle convection model, can we re-produce large scale tilted strata and shifting sediment deposition observed in the WIS basins. Ongoing work will also look into styles of Cenozoic uplift events that ended the WIS and produced the landscape features today. Eventually, we hope to place new constraints on the evolution and properties of lithospheric and deep-mantle dynamics of North American and to locate the best-fit scenario of its coresponding surface evolution since 100 Ma.

Prediction of failure in notched carbon-fibre-reinforced-polymer laminates under multi-axial loading.

PubMed

Tan, J L Y; Deshpande, V S; Fleck, N A

2016-07-13

A damage-based finite-element model is used to predict the fracture behaviour of centre-notched quasi-isotropic carbon-fibre-reinforced-polymer laminates under multi-axial loading. Damage within each ply is associated with fibre tension, fibre compression, matrix tension and matrix compression. Inter-ply delamination is modelled by cohesive interfaces using a traction-separation law. Failure envelopes for a notch and a circular hole are predicted for in-plane multi-axial loading and are in good agreement with the observed failure envelopes from a parallel experimental study. The ply-by-ply (and inter-ply) damage evolution and the critical mechanisms of ultimate failure also agree with the observed damage evolution. It is demonstrated that accurate predictions of notched compressive strength are obtained upon employing the band broadening stress for microbuckling, highlighting the importance of this damage mode in compression. This article is part of the themed issue 'Multiscale modelling of the structural integrity of composite materials'. © 2016 The Author(s).

Prediction of chemical biodegradability using support vector classifier optimized with differential evolution.

PubMed

Cao, Qi; Leung, K M

2014-09-22

Reliable computer models for the prediction of chemical biodegradability from molecular descriptors and fingerprints are very important for making health and environmental decisions. Coupling of the differential evolution (DE) algorithm with the support vector classifier (SVC) in order to optimize the main parameters of the classifier resulted in an improved classifier called the DE-SVC, which is introduced in this paper for use in chemical biodegradability studies. The DE-SVC was applied to predict the biodegradation of chemicals on the basis of extensive sample data sets and known structural features of molecules. Our optimization experiments showed that DE can efficiently find the proper parameters of the SVC. The resulting classifier possesses strong robustness and reliability compared with grid search, genetic algorithm, and particle swarm optimization methods. The classification experiments conducted here showed that the DE-SVC exhibits better classification performance than models previously used for such studies. It is a more effective and efficient prediction model for chemical biodegradability.

The isotopic and chemical evolution of planets: Mars as a missing link

NASA Technical Reports Server (NTRS)

Depaolo, D. J.

1988-01-01

The study of planetary bodies has advanced to a stage where it is possible to contemplate general models for the chemical and physical evolution of planetary interiors, which might be referred to as UMPES (Unified Models of Planetary Evolution and Structure). UMPES would be able to predict the internal evolution and structure of a planet given certain input parameters such as mass, distance from the sun, and a time scale for accretion. Such models are highly dependent on natural observations because the basic material properties of planetary interiors, and the processes that take place during the evolution of planets are imperfectly understood. The idea of UMPES was particularly unrealistic when the only information available was from the earth. However, advances have been made in the understanding of the general aspects of planetary evolution now that there is geochemical and petrological data available for the moon and for meteorites.

Modelling rate distributions using character compatibility: implications for morphological evolution among fossil invertebrates

PubMed Central

Wagner, Peter J.

2012-01-01

Rate distributions are important considerations when testing hypotheses about morphological evolution or phylogeny. They also have implications about general processes underlying character evolution. Molecular systematists often assume that rates are Poisson processes with gamma distributions. However, morphological change is the product of multiple probabilistic processes and should theoretically be affected by hierarchical integration of characters. Both factors predict lognormal rate distributions. Here, a simple inverse modelling approach assesses the best single-rate, gamma and lognormal models given observed character compatibility for 115 invertebrate groups. Tests reject the single-rate model for nearly all cases. Moreover, the lognormal outperforms the gamma for character change rates and (especially) state derivation rates. The latter in particular is consistent with integration affecting morphological character evolution. PMID:21795266

Accurate abundance determinations in S stars

NASA Astrophysics Data System (ADS)

Neyskens, P.; Van Eck, S.; Plez, B.; Goriely, S.; Siess, L.; Jorissen, A.

2011-12-01

S-type stars are thought to be the first objects, during their evolution on the asymptotic giant branch (AGB), to experience s-process nucleosynthesis and third dredge-ups, and therefore to exhibit s-process signatures in their atmospheres. Until present, the modeling of these processes is subject to large uncertainties. Precise abundance determinations in S stars are of extreme importance for constraining e.g., the depth and the formation of the 13C pocket. In this paper a large grid of MARCS model atmospheres for S stars is used to derive precise abundances of key s-process elements and iron. A first estimation of the atmospheric parameters is obtained using a set of well-chosen photometric and spectroscopic indices for selecting the best model atmosphere of each S star. Abundances are derived from spectral line synthesis, using the selected model atmosphere. Special interest is paid to technetium, an element without stable isotopes. Its detection in stars is considered as the best possible signature that the star effectively populates the thermally-pulsing AGB (TP-AGB) phase of evolution. The derived Tc/Zr abundances are compared, as a function of the derived [Zr/Fe] overabundances, with AGB stellar model predictions. The computed [Zr/Fe] overabundances are in good agreement with the AGB stellar evolution model predictions, while the Tc/Zr abundances are slightly over-predicted. This discrepancy can help to set stronger constraints on nucleosynthesis and mixing mechanisms in AGB stars.

Computational Examination of Orientation-Dependent Morphological Evolution during the Electrodeposition and Electrodissolution of Magnesium

DOE PAGES

DeWitt, S.; Hahn, N.; Zavadil, K.; ...

2015-12-30

Here a new model of electrodeposition and electrodissolution is developed and applied to the evolution of Mg deposits during anode cycling. The model captures Butler-Volmer kinetics, facet evolution, the spatially varying potential in the electrolyte, and the time-dependent electrolyte concentration. The model utilizes a diffuse interface approach, employing the phase field and smoothed boundary methods. Scanning electron microscope (SEM) images of magnesium deposited on a gold substrate show the formation of faceted deposits, often in the form of hexagonal prisms. Orientation-dependent reaction rate coefficients were parameterized using the experimental SEM images. Three-dimensional simulations of the growth of magnesium deposits yieldmore » deposit morphologies consistent with the experimental results. The simulations predict that the deposits become narrower and taller as the current density increases due to the depletion of the electrolyte concentration near the sides of the deposits. Increasing the distance between the deposits leads to increased depletion of the electrolyte surrounding the deposit. Two models relating the orientation-dependence of the deposition and dissolution reactions are presented. Finally, the morphology of the Mg deposit after one deposition-dissolution cycle is significantly different between the two orientation-dependence models, providing testable predictions that suggest the underlying physical mechanisms governing morphology evolution during deposition and dissolution.« less

The evolution of sex chromosomes in organisms with separate haploid sexes.

PubMed

Immler, Simone; Otto, Sarah Perin

2015-03-01

The evolution of dimorphic sex chromosomes is driven largely by the evolution of reduced recombination and the subsequent accumulation of deleterious mutations. Although these processes are increasingly well understood in diploid organisms, the evolution of dimorphic sex chromosomes in haploid organisms (U/V) has been virtually unstudied theoretically. We analyze a model to investigate the evolution of linkage between fitness loci and the sex-determining region in U/V species. In a second step, we test how prone nonrecombining regions are to degeneration due to accumulation of deleterious mutations. Our modeling predicts that the decay of recombination on the sex chromosomes and the addition of strata via fusions will be just as much a part of the evolution of haploid sex chromosomes as in diploid sex chromosome systems. Reduced recombination is broadly favored, as long as there is some fitness difference between haploid males and females. The degeneration of the sex-determining region due to the accumulation of deleterious mutations is expected to be slower in haploid organisms because of the absence of masking. Nevertheless, balancing selection often drives greater differentiation between the U/V sex chromosomes than in X/Y and Z/W systems. We summarize empirical evidence for haploid sex chromosome evolution and discuss our predictions in light of these findings. © 2015 The Author(s).

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.

New developments in isotropic turbulent models for FENE-P fluids

NASA Astrophysics Data System (ADS)

Resende, P. R.; Cavadas, A. S.

2018-04-01

The evolution of viscoelastic turbulent models, in the last years, has been significant due to the direct numeric simulation (DNS) advances, which allowed us to capture in detail the evolution of the viscoelastic effects and the development of viscoelastic closures. New viscoelastic closures are proposed for viscoelastic fluids described by the finitely extensible nonlinear elastic-Peterlin constitutive model. One of the viscoelastic closure developed in the context of isotropic turbulent models, consists in a modification of the turbulent viscosity to include an elastic effect, capable of predicting, with good accuracy, the behaviour for different drag reductions. Another viscoelastic closure essential to predict drag reduction relates the viscoelastic term involving velocity and the tensor conformation fluctuations. The DNS data show the high impact of this term to predict correctly the drag reduction, and for this reason is proposed a simpler closure capable of predicting the viscoelastic behaviour with good performance. In addition, a new relation is developed to predict the drag reduction, quantity based on the trace of the tensor conformation at the wall, eliminating the need of the typically parameters of Weissenberg and Reynolds numbers, which depend on the friction velocity. This allows future developments for complex geometries.

Formation and evolution of Lakshmi Planum, Venus: Assessment of models using observations from geological mapping

NASA Astrophysics Data System (ADS)

Ivanov, M. A.; Head, J. W.

2008-12-01

Detailed geological analysis of the Lakshmi Planum region of western Ishtar Terra results in the establishment of the sequence of major events during the formation and evolution of western Ishtar Terra, an important and somewhat unique area on Venus characterized by a raised volcanic plateau surrounded by distinctive folded mountain belts, such as Maxwell Montes. These mapping results and the stratigraphic and structural relationships provide a basis for addressing the complicated problem of Lakshmi Planum formation and for testing the suite of models previously proposed to explain this structure. We review and classify previous models of formation for western Ishtar Terra into "downwelling" models (generally involving convergence and underthrusting) and "upwelling" models (generally involving plume-like upwelling and divergence). The interpreted nature of units and the sequence of events derived from geological mapping are in contrast to the predictions of the divergent models. The major contradictions are as follows: (1) The very likely presence of an ancient (craton-like) tessera massif in the core of Lakshmi, which is inconsistent with the model of formation of Lakshmi due to rise and collapse of a mantle diapir; (2) The absence of rift zones in the interior of Lakshmi that are predicted by the divergent models; (3) The apparent migration of volcanic activity toward the center of Lakshmi, whereas divergent models predict the opposite trend; (4) The abrupt cessation of ridges of the mountain ranges at the edge of Lakshmi Planum and propagation of these ridges over hundreds of kilometers outside Lakshmi; the divergent models predict the opposite progression in the development of major contractional features. In contrast, convergent models of formation and evolution of Lakshmi Planum appear to be more consistent with the observations and explain this structure by collision and underthrusting/subduction of lower-lying plains with the elevated and rigid block of tessera. These models are capable of explaining formation of the major features of western Ishtar (for example, the mountain belts), the sequences of events, and principal volcanic and tectonic trends during the evolution of Lakshmi. To explain the pronounced north-south asymmetry of Lakshmi these models need to consider the likelihood that the major focal points of collision are at the north and north-west margins of the plateau. We note that pure downwelling models, however, face three important difficulties: (1) The possibly unrealistically long time span that appears to be required to produce the major features of Lakshmi; (2) The strong north-south asymmetry of the Planum; the pure downwelling models predict the formation of a more symmetrical structure; and (3) The absence of radial contractional structures (arches and ridges) in the interior of Lakshmi that would represent the predictions of the downwelling models.

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.

Testing Feedback Models with Nearby Star Forming Regions

NASA Astrophysics Data System (ADS)

Doran, E.; Crowther, P.

2012-12-01

The feedback from massive stars plays a crucial role in the evolution of galaxies. Accurate modelling of this feedback is essential in understanding distant star forming regions. Young nearby, high mass (> 104 M⊙) clusters such as R136 (in the 30 Doradus region) are ideal test beds for population synthesis since they host large numbers of spatially resolved massive stars at a pre-supernovae stage. We present a quantitative comparison of empirical calibrations of radiative and mechanical feedback from individual stars in R136, with instantaneous burst predictions from the popular Starburst99 evolution synthesis code. We find that empirical results exceed predictions by factors of ˜3-9, as a result of limiting simulations to an upper limit of 100 M⊙. 100-300 M⊙ stars should to be incorporated in population synthesis models for high mass clusters to bring predictions into close agreement with empirical results.

Energy Dissipation-Based Method for Fatigue Life Prediction of Rock Salt

NASA Astrophysics Data System (ADS)

He, Mingming; Huang, Bingqian; Zhu, Caihui; Chen, Yunsheng; Li, Ning

2018-05-01

The fatigue test for rock salt is conducted under different stress amplitudes, loading frequencies, confining pressures and loading rates, from which the evaluation rule of the dissipated energy is revealed and analysed. The evolution of energy dissipation under fatigue loading is divided into three stages: the initial stage, the second stage and the acceleration stage. In the second stage, the energy dissipation per cycle remains stable and shows an exponential relation with the stress amplitude; the failure dissipated energy only depends on the mechanical behaviour of the rock salt and confining pressure, but it is immune to the loading conditions. The energy dissipation of fatigued rock salt is discussed, and a novel model for fatigue life prediction is proposed on the basis of energy dissipation. A simple model for evolution of the accumulative dissipated energy is established. Its prediction results are compared with the test results, and the proposed model is validated.

Coordinated Hard Sphere Mixture (CHaSM): A fast approximate model for oxide and silicate melts at extreme conditions

NASA Astrophysics Data System (ADS)

Wolf, A. S.; Asimow, P. D.; Stevenson, D. J.

2015-12-01

Recent first-principles calculations (e.g. Stixrude, 2009; de Koker, 2013), shock-wave experiments (Mosenfelder, 2009), and diamond-anvil cell investigations (Sanloup, 2013) indicate that silicate melts undergo complex structural evolution at high pressure. The observed increase in cation-coordination (e.g. Karki, 2006; 2007) induces higher compressibilities and lower adiabatic thermal gradients in melts as compared with their solid counterparts. These properties are crucial for understanding the evolution of impact-generated magma oceans, which are dominated by the poorly understood behavior of silicates at mantle pressures and temperatures (e.g. Stixrude et al. 2009). Probing these conditions is difficult for both theory and experiment, especially given the large compositional space (MgO-SiO2-FeO-Al2O3-etc). We develop a new model to understand and predict the behavior of oxide and silicate melts at extreme P-T conditions (Wolf et al., 2015). The Coordinated Hard Sphere Mixture (CHaSM) extends the Hard Sphere mixture model, accounting for the range of coordination states for each cation in the liquid. Using approximate analytic expressions for the hard sphere model, this fast statistical method compliments classical and first-principles methods, providing accurate thermodynamic and structural property predictions for melts. This framework is applied to the MgO system, where model parameters are trained on a collection of crystal polymorphs, producing realistic predictions of coordination evolution and the equation of state of MgO melt over a wide P-T range. Typical Mg-coordination numbers are predicted to evolve continuously from 5.25 (0 GPa) to 8.5 (250 GPa), comparing favorably with first-principles Molecular Dynamics (MD) simulations. We begin extending the model to a simplified mantle chemistry using empirical potentials (generally accurate over moderate pressure ranges, <~30 GPa), yielding predictions rooted in statistical representations of melt structure that compare well with more time-consuming classical MD calculations. This approach also sheds light on the universality of the increasing Grüneisen parameter trend for liquids (opposite that of solids), which directly reflects their progressive evolution toward more compact solid-like structures upon compression.

Extant-only comparative methods fail to recover the disparity preserved in the bird fossil record.

PubMed

Mitchell, Jonathan S

2015-09-01

Most extant species are in clades with poor fossil records, and recent studies of comparative methods show they have low power to infer even highly simplified models of trait evolution without fossil data. Birds are a well-studied radiation, yet their early evolutionary patterns are still contentious. The fossil record suggests that birds underwent a rapid ecological radiation after the end-Cretaceous mass extinction, and several smaller, subsequent radiations. This hypothesized series of repeated radiations from fossil data is difficult to test using extant data alone. By uniting morphological and phylogenetic data on 604 extant genera of birds with morphological data on 58 species of extinct birds from 50 million years ago, the "halfway point" of avian evolution, I have been able to test how well extant-only methods predict the diversity of fossil forms. All extant-only methods underestimate the disparity, although the ratio of within- to between-clade disparity does suggest high early rates. The failure of standard models to predict high early disparity suggests that recent radiations are obscuring deep time patterns in the evolution of birds. Metrics from different models can be used in conjunction to provide more valuable insights than simply finding the model with the highest relative fit. © 2015 The Author(s). Evolution © 2015 The Society for the Study of Evolution.

The evolution of dispersal in a Levins' type metapopulation model.

PubMed

Jansen, Vincent A A; Vitalis, Renaud

2007-10-01

We study the evolution of the dispersal rate in a metapopulation model with extinction and colonization dynamics, akin to the model as originally described by Levins. To do so we extend the metapopulation model with a description of the within patch dynamics. By means of a separation of time scales we analytically derive a fitness expression from first principles for this model. The fitness function can be written as an inclusive fitness equation (Hamilton's rule). By recasting this equation in a form that emphasizes the effects of competition we show the effect of the local competition and the local population size on the evolution of dispersal. We find that the evolution of dispersal cannot be easily interpreted in terms of avoidance of kin competition, but rather that increased dispersal reduces the competitive ability. Our model also yields a testable prediction in term of relatedness and life-history parameters.

Impact of the terrestrial-aquatic transition on disparity and rates of evolution in the carnivoran skull.

PubMed

Jones, Katrina E; Smaers, Jeroen B; Goswami, Anjali

2015-02-04

Which factors influence the distribution patterns of morphological diversity among clades? The adaptive radiation model predicts that a clade entering new ecological niche will experience high rates of evolution early in its history, followed by a gradual slowing. Here we measure disparity and rates of evolution in Carnivora, specifically focusing on the terrestrial-aquatic transition in Pinnipedia. We analyze fissiped (mostly terrestrial, arboreal, and semi-arboreal, but also including the semi-aquatic otter) and pinniped (secondarily aquatic) carnivorans as a case study of an extreme ecological transition. We used 3D geometric morphometrics to quantify cranial shape in 151 carnivoran specimens (64 fissiped, 87 pinniped) and five exceptionally-preserved fossil pinnipeds, including the stem-pinniped Enaliarctos emlongi. Range-based and variance-based disparity measures were compared between pinnipeds and fissipeds. To distinguish between evolutionary modes, a Brownian motion model was compared to selective regime shifts associated with the terrestrial-aquatic transition and at the base of Pinnipedia. Further, evolutionary patterns were estimated on individual branches using both Ornstein-Uhlenbeck and Independent Evolution models, to examine the origin of pinniped diversity. Pinnipeds exhibit greater cranial disparity than fissipeds, even though they are less taxonomically diverse and, as a clade nested within fissipeds, phylogenetically younger. Despite this, there is no increase in the rate of morphological evolution at the base of Pinnipedia, as would be predicted by an adaptive radiation model, and a Brownian motion model of evolution is supported. Instead basal pinnipeds populated new areas of morphospace via low to moderate rates of evolution in new directions, followed by later bursts within the crown-group, potentially associated with ecological diversification within the marine realm. The transition to an aquatic habitat in carnivorans resulted in a shift in cranial morphology without an increase in rate in the stem lineage, contra to the adaptive radiation model. Instead these data suggest a release from evolutionary constraint model, followed by aquatic diversifications within crown families.

Predictive modeling of multicellular structure formation by using Cellular Particle Dynamics simulations

NASA Astrophysics Data System (ADS)

McCune, Matthew; Shafiee, Ashkan; Forgacs, Gabor; Kosztin, Ioan

2014-03-01

Cellular Particle Dynamics (CPD) is an effective computational method for describing and predicting the time evolution of biomechanical relaxation processes of multicellular systems. A typical example is the fusion of spheroidal bioink particles during post bioprinting structure formation. In CPD cells are modeled as an ensemble of cellular particles (CPs) that interact via short-range contact interactions, characterized by an attractive (adhesive interaction) and a repulsive (excluded volume interaction) component. The time evolution of the spatial conformation of the multicellular system is determined by following the trajectories of all CPs through integration of their equations of motion. CPD was successfully applied to describe and predict the fusion of 3D tissue construct involving identical spherical aggregates. Here, we demonstrate that CPD can also predict tissue formation involving uneven spherical aggregates whose volumes decrease during the fusion process. Work supported by NSF [PHY-0957914]. Computer time provided by the University of Missouri Bioinformatics Consortium.

Modeling Wind Wave Evolution from Deep to Shallow Water

DTIC Science & Technology

2014-09-30

results are very promising (see Figure 2). However, for the sake of efficiency, non-hydrostatic models assume a single-valued free surface in the...1996) are ongoing. Figure 3 Smoothed-Particle Hydrodynamics ( SPH ) simulations of waves breaking over an artificial reef in the laboratory (see... surface as predicted by the SPH model (see Dalrymple & Rogers, 2006). The agreement in the breaker dynamics predicted by the model and seen in the

Model predictive control of P-time event graphs

NASA Astrophysics Data System (ADS)

Hamri, H.; Kara, R.; Amari, S.

2016-12-01

This paper deals with model predictive control of discrete event systems modelled by P-time event graphs. First, the model is obtained by using the dater evolution model written in the standard algebra. Then, for the control law, we used the finite-horizon model predictive control. For the closed-loop control, we used the infinite-horizon model predictive control (IH-MPC). The latter is an approach that calculates static feedback gains which allows the stability of the closed-loop system while respecting the constraints on the control vector. The problem of IH-MPC is formulated as a linear convex programming subject to a linear matrix inequality problem. Finally, the proposed methodology is applied to a transportation system.

Testing the effects of topography, geometry, and kinematics on modeled thermochronometer cooling ages in the eastern Bhutan Himalaya

NASA Astrophysics Data System (ADS)

Gilmore, Michelle E.; McQuarrie, Nadine; Eizenhöfer, Paul R.; Ehlers, Todd A.

2018-05-01

In this study, reconstructions of a balanced geologic cross section in the Himalayan fold-thrust belt of eastern Bhutan are used in flexural-kinematic and thermokinematic models to understand the sensitivity of predicted cooling ages to changes in fault kinematics, geometry, topography, and radiogenic heat production. The kinematics for each scenario are created by sequentially deforming the cross section with ˜ 10 km deformation steps while applying flexural loading and erosional unloading at each step to develop a high-resolution evolution of deformation, erosion, and burial over time. By assigning ages to each increment of displacement, we create a suite of modeled scenarios that are input into a 2-D thermokinematic model to predict cooling ages. Comparison of model-predicted cooling ages to published thermochronometer data reveals that cooling ages are most sensitive to (1) the location and size of fault ramps, (2) the variable shortening rates between 68 and 6.4 mm yr-1, and (3) the timing and magnitude of out-of-sequence faulting. The predicted ages are less sensitive to (4) radiogenic heat production and (5) estimates of topographic evolution. We used the observed misfit of predicted to measured cooling ages to revise the cross section geometry and separate one large ramp previously proposed for the modern décollement into two smaller ramps. The revised geometry results in an improved fit to observed ages, particularly young AFT ages (2-6 Ma) located north of the Main Central Thrust. This study presents a successful approach for using thermochronometer data to test the viability of a proposed cross section geometry and kinematics and describes a viable approach to estimating the first-order topographic evolution of a compressional orogen.

Predicting evolutionary rescue via evolving plasticity in stochastic environments

PubMed Central

Baskett, Marissa L.

2016-01-01

Phenotypic plasticity and its evolution may help evolutionary rescue in a novel and stressful environment, especially if environmental novelty reveals cryptic genetic variation that enables the evolution of increased plasticity. However, the environmental stochasticity ubiquitous in natural systems may alter these predictions, because high plasticity may amplify phenotype–environment mismatches. Although previous studies have highlighted this potential detrimental effect of plasticity in stochastic environments, they have not investigated how it affects extinction risk in the context of evolutionary rescue and with evolving plasticity. We investigate this question here by integrating stochastic demography with quantitative genetic theory in a model with simultaneous change in the mean and predictability (temporal autocorrelation) of the environment. We develop an approximate prediction of long-term persistence under the new pattern of environmental fluctuations, and compare it with numerical simulations for short- and long-term extinction risk. We find that reduced predictability increases extinction risk and reduces persistence because it increases stochastic load during rescue. This understanding of how stochastic demography, phenotypic plasticity, and evolution interact when evolution acts on cryptic genetic variation revealed in a novel environment can inform expectations for invasions, extinctions, or the emergence of chemical resistance in pests. PMID:27655762

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.

Validation of neoclassical bootstrap current models in the edge of an H-mode plasma.

PubMed

Wade, M R; Murakami, M; Politzer, P A

2004-06-11

Analysis of the parallel electric field E(parallel) evolution following an L-H transition in the DIII-D tokamak indicates the generation of a large negative pulse near the edge which propagates inward, indicative of the generation of a noninductive edge current. Modeling indicates that the observed E(parallel) evolution is consistent with a narrow current density peak generated in the plasma edge. Very good quantitative agreement is found between the measured E(parallel) evolution and that expected from neoclassical theory predictions of the bootstrap current.

φ-evo: A program to evolve phenotypic models of biological networks.

PubMed

Henry, Adrien; Hemery, Mathieu; François, Paul

2018-06-01

Molecular networks are at the core of most cellular decisions, but are often difficult to comprehend. Reverse engineering of network architecture from their functions has proved fruitful to classify and predict the structure and function of molecular networks, suggesting new experimental tests and biological predictions. We present φ-evo, an open-source program to evolve in silico phenotypic networks performing a given biological function. We include implementations for evolution of biochemical adaptation, adaptive sorting for immune recognition, metazoan development (somitogenesis, hox patterning), as well as Pareto evolution. We detail the program architecture based on C, Python 3, and a Jupyter interface for project configuration and network analysis. We illustrate the predictive power of φ-evo by first recovering the asymmetrical structure of the lac operon regulation from an objective function with symmetrical constraints. Second, we use the problem of hox-like embryonic patterning to show how a single effective fitness can emerge from multi-objective (Pareto) evolution. φ-evo provides an efficient approach and user-friendly interface for the phenotypic prediction of networks and the numerical study of evolution itself.

Modeling the effect of subgrain rotation recrystallization on the evolution of olivine crystal preferred orientations in simple shear

NASA Astrophysics Data System (ADS)

Signorelli, Javier; Tommasi, Andréa

2015-11-01

Homogenization models are widely used to predict the evolution of texture (crystal preferred orientations) and resulting anisotropy of physical properties in metals, rocks, and ice. They fail, however, in predicting two main features of texture evolution in simple shear (the dominant deformation regime on Earth) for highly anisotropic crystals, like olivine: (1) the fast rotation of the CPO towards a stable position characterized by parallelism of the dominant slip system and the macroscopic shear and (2) the asymptotical evolution towards a constant intensity. To better predict CPO-induced anisotropy in the mantle, but limiting computational costs and use of poorly-constrained physical parameters, we modified a viscoplastic self-consistent code to simulate the effects of subgrain rotation recrystallization. To each crystal is associated a finite number of fragments (possible subgrains). Formation of a subgrain corresponds to introduction of a disorientation (relative to the parent) and resetting of the fragment strain and internal energy. The probability of formation of a subgrain is controlled by comparison between the local internal energy and the average value in the polycrystal. A two-level mechanical interaction scheme is applied for simulating the intracrystalline strain heterogeneity allowed by the formation of low-angle grain boundaries. Within a crystal, interactions between subgrains follow a constant stress scheme. The interactions between grains are simulated by a tangent viscoplastic self-consistent approach. This two-level approach better reproduces the evolution of olivine CPO in simple shear in experiments and nature. It also predicts a marked weakening at low shear strains, consistently with experimental data.

AFT: Extending Solar Cycle Prediction with Data Assimilation

NASA Astrophysics Data System (ADS)

Upton, L.; Hathaway, D. H.

2017-12-01

The Advective Flux Transport (AFT) model is an innovative surface flux transport model that simulates the evolution of the radial magnetic field on the surface of the Sun. AFT was designed to be as realistic as possible by 1: incorporating the observed surface flows (meridional flow, differential rotation, and an explicit evolving convective pattern) and by 2: using data assimilation to incorporate the observed magnetic fields directly from line-of-sight (LOS) magnetograms. AFT has proven to be successful in simulating the evolution of the surface magnetic fields on both short time scales (days-weeks) as well as for long time scales (years). In particular, AFT has been shown to accurately predict the evolution of the Sun's dipolar magnetic field 3-5 years in advance. Since the Sun's polar magnetic field strength at solar cycle minimum is the best indicator of the amplitude of the next cycle, this has in turn extended our ability to make solar cycle predictions to 3-5 years before solar minimum occurs. Here, we will discuss some of the challenges of implementing data assimilation into AFT. We will also discuss the role of data assimilation in advancing solar cycle predictive capability.

Ready or Not: Microbial Adaptive Responses in Dynamic Symbiosis Environments.

PubMed

Cao, Mengyi; Goodrich-Blair, Heidi

2017-08-01

In mutually beneficial and pathogenic symbiotic associations, microbes must adapt to the host environment for optimal fitness. Both within an individual host and during transmission between hosts, microbes are exposed to temporal and spatial variation in environmental conditions. The phenomenon of phenotypic variation, in which different subpopulations of cells express distinctive and potentially adaptive characteristics, can contribute to microbial adaptation to a lifestyle that includes rapidly changing environments. The environments experienced by a symbiotic microbe during its life history can be erratic or predictable, and each can impact the evolution of adaptive responses. In particular, the predictability of a rhythmic or cyclical series of environments may promote the evolution of signal transduction cascades that allow preadaptive responses to environments that are likely to be encountered in the future, a phenomenon known as adaptive prediction. In this review, we summarize environmental variations known to occur in some well-studied models of symbiosis and how these may contribute to the evolution of microbial population heterogeneity and anticipatory behavior. We provide details about the symbiosis between Xenorhabdus bacteria and Steinernema nematodes as a model to investigate the concept of environmental adaptation and adaptive prediction in a microbial symbiosis. Copyright © 2017 American Society for Microbiology.

Numerical formulation for the prediction of solid/liquid change of a binary alloy

NASA Technical Reports Server (NTRS)

Schneider, G. E.; Tiwari, S. N.

1990-01-01

A computational model is presented for the prediction of solid/liquid phase change energy transport including the influence of free convection fluid flow in the liquid phase region. The computational model considers the velocity components of all non-liquid phase change material control volumes to be zero but fully solves the coupled mass-momentum problem within the liquid region. The thermal energy model includes the entire domain and uses an enthalpy like model and a recently developed method for handling the phase change interface nonlinearity. Convergence studies are performed and comparisons made with experimental data for two different problem specifications. The convergence studies indicate that grid independence was achieved and the comparison with experimental data indicates excellent quantitative prediction of the melt fraction evolution. Qualitative data is also provided in the form of velocity vector diagrams and isotherm plots for selected times in the evolution of both problems. The computational costs incurred are quite low by comparison with previous efforts on solving these problems.

Independent evolution of the sexes promotes amphibian diversification

PubMed Central

De Lisle, Stephen P.; Rowe, Locke

2015-01-01

Classic ecological theory predicts that the evolution of sexual dimorphism constrains diversification by limiting morphospace available for speciation. Alternatively, sexual selection may lead to the evolution of reproductive isolation and increased diversification. We test contrasting predictions of these hypotheses by examining the relationship between sexual dimorphism and diversification in amphibians. Our analysis shows that the evolution of sexual size dimorphism (SSD) is associated with increased diversification and speciation, contrary to the ecological theory. Further, this result is unlikely to be explained by traditional sexual selection models because variation in amphibian SSD is unlikely to be driven entirely by sexual selection. We suggest that relaxing a central assumption of classic ecological models—that the sexes share a common adaptive landscape—leads to the alternative hypothesis that independent evolution of the sexes may promote diversification. Once the constraints of sexual conflict are relaxed, the sexes can explore morphospace that would otherwise be inaccessible. Consistent with this novel hypothesis, the evolution of SSD in amphibians is associated with reduced current extinction threat status, and an historical reduction in extinction rate. Our work reconciles conflicting predictions from ecological and evolutionary theory and illustrates that the ability of the sexes to evolve independently is associated with a spectacular vertebrate radiation. PMID:25694616

A model for the evolution of CO2 on Mars

NASA Technical Reports Server (NTRS)

Haberle, Robert M.; Tyler, D.; Mckay, C. P.; Davis, W. L.

1993-01-01

Our MSATT work has focused on the evolution of CO2 on Mars. We have constructed a model that predicts the evolution of CO2 on Mars from a specified initial amount at the end of the heavy bombardment to the present. The model draws on published estimates of the main process believed to affect the fate of CO2 during this period: chemical weathering, regolith uptake, polar cap formation, and atmospheric escape. Except for escape, the rate at which these processes act is controlled by surface temperatures that we calculate using a modified version of the Gierasch and Toon energy balance model. Various aspects of this work are covered.

Coordinated Hard Sphere Mixture (CHaSM): A simplified model for oxide and silicate melts at mantle pressures and temperatures

NASA Astrophysics Data System (ADS)

Wolf, Aaron S.; Asimow, Paul D.; Stevenson, David J.

2015-08-01

We develop a new model to understand and predict the behavior of oxide and silicate melts at extreme temperatures and pressures, including deep mantle conditions like those in the early Earth magma ocean. The Coordinated Hard Sphere Mixture (CHaSM) is based on an extension of the hard sphere mixture model, accounting for the range of coordination states available to each cation in the liquid. By utilizing approximate analytic expressions for the hard sphere model, this method is capable of predicting complex liquid structure and thermodynamics while remaining computationally efficient, requiring only minutes of calculation time on standard desktop computers. This modeling framework is applied to the MgO system, where model parameters are trained on a collection of crystal polymorphs, producing realistic predictions of coordination evolution and the equation of state of MgO melt over a wide range of pressures and temperatures. We find that the typical coordination number of the Mg cation evolves continuously upward from 5.25 at 0 GPa to 8.5 at 250 GPa. The results produced by CHaSM are evaluated by comparison with predictions from published first-principles molecular dynamics calculations, indicating that CHaSM is accurately capturing the dominant physics controlling the behavior of oxide melts at high pressure. Finally, we present a simple quantitative model to explain the universality of the increasing Grüneisen parameter trend for liquids, which directly reflects their progressive evolution toward more compact solid-like structures upon compression. This general behavior is opposite that of solid materials, and produces steep adiabatic thermal profiles for silicate melts, thus playing a crucial role in magma ocean evolution.

Predicting Galaxy Star Formation Rates via the Co-evolution of Galaxies and Halos

DOE PAGES

Watson, Douglas F.; Hearin, Andrew P.; Berlind, Andreas A.; ...

2014-03-06

In this paper, we test the age matching hypothesis that the star formation rate (SFR) of a galaxy is determined by its dark matter halo formation history, and as such, that more quiescent galaxies reside in older halos. This simple model has been remarkably successful at predicting color-based galaxy statistics at low redshift as measured in the Sloan Digital Sky Survey (SDSS). To further test this method with observations, we present new SDSS measurements of the galaxy two-point correlation function and galaxy-galaxy lensing as a function of stellar mass and SFR, separated into quenched and star forming galaxy samples. Wemore » find that our age matching model is in excellent agreement with these new measurements. We also employ a galaxy group finder and show that our model is able to predict: (1) the relative SFRs of central and satellite galaxies, (2) the SFR-dependence of the radial distribution of satellite galaxy populations within galaxy groups, rich groups, and clusters and their surrounding larger scale environments, and (3) the interesting feature that the satellite quenched fraction as a function of projected radial distance from the central galaxy exhibits an approx r -.15 slope, independent of environment. The accurate prediction for the spatial distribution of satellites is intriguing given the fact that we do not explicitly model satellite-specific processes after infall, and that in our model the virial radius does not mark a special transition region in the evolution of a satellite, contrary to most galaxy evolution models. The success of the model suggests that present-day galaxy SFR is strongly correlated with halo mass assembly history.« less

Modeling copper precipitation hardening and embrittlement in a dilute Fe-0.3at.%Cu alloy under neutron irradiation

NASA Astrophysics Data System (ADS)

Bai, Xian-Ming; Ke, Huibin; Zhang, Yongfeng; Spencer, Benjamin W.

2017-11-01

Neutron irradiation in light water reactors can induce precipitation of nanometer sized Cu clusters in reactor pressure vessel steels. The Cu precipitates impede dislocation gliding, leading to an increase in yield strength (hardening) and an upward shift of ductile-to-brittle transition temperature (embrittlement). In this work, cluster dynamics modeling is used to model the entire Cu precipitation process (nucleation, growth, and coarsening) in a Fe-0.3at.%Cu alloy under neutron irradiation at 300°C based on the homogenous nucleation mechanism. The evolution of the Cu cluster number density and mean radius predicted by the modeling agrees well with experimental data reported in literature for the same alloy under the same irradiation conditions. The predicted precipitation kinetics is used as input for a dispersed barrier hardening model to correlate the microstructural evolution with the radiation hardening and embrittlement in this alloy. The predicted radiation hardening agrees well with the mechanical test results in the literature. Limitations of the model and areas for future improvement are also discussed in this work.

On the r-mode spectrum of relativistic stars: the inclusion of the radiation reaction

NASA Astrophysics Data System (ADS)

Ruoff, Johannes; Kokkotas, Kostas D.

2002-03-01

We consider both mode calculations and time-evolutions of axial r modes for relativistic uniformly rotating non-barotropic neutron stars, using the slow-rotation formalism, in which rotational corrections are considered up to linear order in the angular velocity Ω. We study various stellar models, such as uniform density models, polytropic models with different polytropic indices n, and some models based on realistic equations of state. For weakly relativistic uniform density models and polytropes with small values of n, we can recover the growth times predicted from Newtonian theory when standard multipole formulae for the gravitational radiation are used. However, for more compact models, we find that relativistic linear perturbation theory predicts a weakening of the instability compared to the Newtonian results. When turning to polytropic equations of state, we find that for certain ranges of the polytropic index n, the r mode disappears, and instead of a growth, the time-evolutions show a rapid decay of the amplitude. This is clearly at variance with the Newtonian predictions. It is, however, fully consistent with our previous results obtained in the low-frequency approximation.

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.

Optimal feature selection using a modified differential evolution algorithm and its effectiveness for prediction of heart disease.

PubMed

Vivekanandan, T; Sriman Narayana Iyengar, N Ch

2017-11-01

Enormous data growth in multiple domains has posed a great challenge for data processing and analysis techniques. In particular, the traditional record maintenance strategy has been replaced in the healthcare system. It is vital to develop a model that is able to handle the huge amount of e-healthcare data efficiently. In this paper, the challenging tasks of selecting critical features from the enormous set of available features and diagnosing heart disease are carried out. Feature selection is one of the most widely used pre-processing steps in classification problems. A modified differential evolution (DE) algorithm is used to perform feature selection for cardiovascular disease and optimization of selected features. Of the 10 available strategies for the traditional DE algorithm, the seventh strategy, which is represented by DE/rand/2/exp, is considered for comparative study. The performance analysis of the developed modified DE strategy is given in this paper. With the selected critical features, prediction of heart disease is carried out using fuzzy AHP and a feed-forward neural network. Various performance measures of integrating the modified differential evolution algorithm with fuzzy AHP and a feed-forward neural network in the prediction of heart disease are evaluated in this paper. The accuracy of the proposed hybrid model is 83%, which is higher than that of some other existing models. In addition, the prediction time of the proposed hybrid model is also evaluated and has shown promising results. Copyright © 2017 Elsevier Ltd. All rights reserved.

Evolution of cosmic string networks

NASA Technical Reports Server (NTRS)

Albrecht, Andreas; Turok, Neil

1989-01-01

A discussion of the evolution and observable consequences of a network of cosmic strings is given. A simple model for the evolution of the string network is presented, and related to the statistical mechanics of string networks. The model predicts the long string density throughout the history of the universe from a single parameter, which researchers calculate in radiation era simulations. The statistical mechanics arguments indicate a particular thermal form for the spectrum of loops chopped off the network. Detailed numerical simulations of string networks in expanding backgrounds are performed to test the model. Consequences for large scale structure, the microwave and gravity wave backgrounds, nucleosynthesis and gravitational lensing are calculated.

A stochastic model for tumor geometry evolution during radiation therapy in cervical cancer

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

Liu, Yifang; Lee, Chi-Guhn; Chan, Timothy C. Y., E-mail: tcychan@mie.utoronto.ca

2014-02-15

Purpose: To develop mathematical models to predict the evolution of tumor geometry in cervical cancer undergoing radiation therapy. Methods: The authors develop two mathematical models to estimate tumor geometry change: a Markov model and an isomorphic shrinkage model. The Markov model describes tumor evolution by investigating the change in state (either tumor or nontumor) of voxels on the tumor surface. It assumes that the evolution follows a Markov process. Transition probabilities are obtained using maximum likelihood estimation and depend on the states of neighboring voxels. The isomorphic shrinkage model describes tumor shrinkage or growth in terms of layers of voxelsmore » on the tumor surface, instead of modeling individual voxels. The two proposed models were applied to data from 29 cervical cancer patients treated at Princess Margaret Cancer Centre and then compared to a constant volume approach. Model performance was measured using sensitivity and specificity. Results: The Markov model outperformed both the isomorphic shrinkage and constant volume models in terms of the trade-off between sensitivity (target coverage) and specificity (normal tissue sparing). Generally, the Markov model achieved a few percentage points in improvement in either sensitivity or specificity compared to the other models. The isomorphic shrinkage model was comparable to the Markov approach under certain parameter settings. Convex tumor shapes were easier to predict. Conclusions: By modeling tumor geometry change at the voxel level using a probabilistic model, improvements in target coverage and normal tissue sparing are possible. Our Markov model is flexible and has tunable parameters to adjust model performance to meet a range of criteria. Such a model may support the development of an adaptive paradigm for radiation therapy of cervical cancer.« less

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.

Vertical Wave Coupling associated with Stratospheric Sudden Warming Events analyzed in an Isentropic-Coordinate NWP Model.

NASA Astrophysics Data System (ADS)

Bleck, R.; Sun, S.; Benjamin, S.; Brown, J. M.

2017-12-01

Two- to four-week predictions of stratospheric sudden warming events during the winter seasons of 1999-2014, carried out with a high-resolution icosahedral NWP model using potential temperature as vertical coordinate, are inspected for commonalities in the evolution of both minor and major warmings. Emphasis is on the evolution of the potential vorticity field at different levels in the stratosphere, as well as on the sign and magnitude of the vertical component of the Eliassen-Palm flux vector suggestive of wave forcing in either direction. Material is presented shedding light on the skill of the model (FIM, developed at NOAA/ESRL) in predicting stratospheric warmings generally 2 weeks in advance. With an icosahedral grid ideally suited for studying polar processes, and a vertical coordinate faithfully reproducing details in the evolution of the potential vorticity and EP flux vector fields, FIM is found to be a good tool for investigating the SSW mechanism.

Karstification of an aquifer along the Birs River, Switzerland - from natural to anthropogenic dominated boundary conditions

NASA Astrophysics Data System (ADS)

Romanov, D.; Epting, J.; Huggenberger, P.; Kaufmann, G.

2009-04-01

Karst aquifers are very sensitive to environmental changes. Small variations of boundary conditions can trigger significant and fast changes of the basic properties of these geological formations. Furthermore, a large number of hydraulic structures have been built in Karst terrains and close to urban areas. Within such settings it is of primary importance to understand the basic processes governing the system and to predict the evolution of Karst aquifers in order to mitigate hazards. There has been great progress in numerical modeling of the evolution of Karst during the last decades. We are now able to model early karstification of locations with complicated geological and geochemical settings and our knowledge about basic processes governing Karst evolution has increased significantly. However, there are still not many modeling attempts with data from real Karst aquifers. A model describing the evolution of a gypsum Karst aquifer along the Birs River in Switzerland is presented in this study. The initial and boundary conditions for the simulations are taken from results of geophysical and geological field studies and a detailed 3D hydrogeological model of the area. Three time intervals of the aquifer's development are discussed in details. The first covers the natural karstification for a period between several hundreds up to a few thousands years. The results from this evolution period are used as initial conditions for the second interval, which covers the time between 1890 and 2007 AD. This period is characterized by anthropogenic alterations of the system through a man-made river dam, which considerably changes the evolution of the aquifer. In 2006 and 2007 AD - after serious subsidence of a nearby highway has been observed - technical measures have been conducted and thus the boundary conditions have changed once again. This is the beginning for the third modeled interval. A forecast for the following 100 years is developed. Our results correlate very well with the findings of the field studies of the area. Furthermore, predicted evolution timescales are reasonable from what is known about the past of the aquifer. The Karst evolution models allowed simulating the development of aquifer properties, which subsequently could be transferred to the 3D hydrogeological model, allowing a more realistic representation of subsurface heterogeneities. It could be demonstrated that the various investigative methods for Karst aquifer characterization are complementing each other and allow the interpretation of short-term impacts and long-term development on system-dynamics. The obtained results show that our models can be applied not only for theoretical research of simplified and idealized Karst aquifers, but also to places with complex geological and hydrological properties. Investigative methods for similar subsidence problems can be optimized, leading from general measurements and monitoring technologies to tools with predictive character.

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.

Many-to-one form-to-function mapping weakens parallel morphological evolution.

PubMed

Thompson, Cole J; Ahmed, Newaz I; Veen, Thor; Peichel, Catherine L; Hendry, Andrew P; Bolnick, Daniel I; Stuart, Yoel E

2017-11-01

Evolutionary ecologists aim to explain and predict evolutionary change under different selective regimes. Theory suggests that such evolutionary prediction should be more difficult for biomechanical systems in which different trait combinations generate the same functional output: "many-to-one mapping." Many-to-one mapping of phenotype to function enables multiple morphological solutions to meet the same adaptive challenges. Therefore, many-to-one mapping should undermine parallel morphological evolution, and hence evolutionary predictability, even when selection pressures are shared among populations. Studying 16 replicate pairs of lake- and stream-adapted threespine stickleback (Gasterosteus aculeatus), we quantified three parts of the teleost feeding apparatus and used biomechanical models to calculate their expected functional outputs. The three feeding structures differed in their form-to-function relationship from one-to-one (lower jaw lever ratio) to increasingly many-to-one (buccal suction index, opercular 4-bar linkage). We tested for (1) weaker linear correlations between phenotype and calculated function, and (2) less parallel evolution across lake-stream pairs, in the many-to-one systems relative to the one-to-one system. We confirm both predictions, thus supporting the theoretical expectation that increasing many-to-one mapping undermines parallel evolution. Therefore, sole consideration of morphological variation within and among populations might not serve as a proxy for functional variation when multiple adaptive trait combinations exist. © 2017 The Author(s). Evolution © 2017 The Society for the Study of Evolution.

Evolution of the Antarctic polar vortex in spring: Response of a GCM to a prescribed Antarctic ozone hole

NASA Technical Reports Server (NTRS)

Boville, B. A.; Kiehl, J. T.; Briegleb, B. P.

1988-01-01

The possible effect of the Antartic ozone hole on the evolution of the polar vortex during late winter and spring using a general circulation model (GCM) is examined. The GCM is a version of the NCAR Community Climate Model whose domain extends from the surface to the mesosphere and is similar to that described on Boville and Randel (1986). Ozone is not a predicted variable in the model. A zonally averaged ozone distribution is specified as a function of latitude, pressure and month for the radiation parameterization. Rather that explicitly address reasons for the formation of the ozone hole, researchers postulate its existence and ask what effect it has on the subsequent evolution of the vortex. The evolution of the model when an ozone hole is imposed is then discussed.

Governing Laws of Complex System Predictability under Co-evolving Uncertainty Sources: Theory and Nonlinear Geophysical Applications

NASA Astrophysics Data System (ADS)

Perdigão, R. A. P.

2017-12-01

Predictability assessments are traditionally made on a case-by-case basis, often by running the particular model of interest with randomly perturbed initial/boundary conditions and parameters, producing computationally expensive ensembles. These approaches provide a lumped statistical view of uncertainty evolution, without eliciting the fundamental processes and interactions at play in the uncertainty dynamics. In order to address these limitations, we introduce a systematic dynamical framework for predictability assessment and forecast, by analytically deriving governing equations of predictability in terms of the fundamental architecture of dynamical systems, independent of any particular problem under consideration. The framework further relates multiple uncertainty sources along with their coevolutionary interplay, enabling a comprehensive and explicit treatment of uncertainty dynamics along time, without requiring the actual model to be run. In doing so, computational resources are freed and a quick and effective a-priori systematic dynamic evaluation is made of predictability evolution and its challenges, including aspects in the model architecture and intervening variables that may require optimization ahead of initiating any model runs. It further brings out universal dynamic features in the error dynamics elusive to any case specific treatment, ultimately shedding fundamental light on the challenging issue of predictability. The formulated approach, framed with broad mathematical physics generality in mind, is then implemented in dynamic models of nonlinear geophysical systems with various degrees of complexity, in order to evaluate their limitations and provide informed assistance on how to optimize their design and improve their predictability in fundamental dynamical terms.

Age and size at maturity: a quantitative review of diet-induced reaction norms in insects.

PubMed

Teder, Tiit; Vellau, Helen; Tammaru, Toomas

2014-11-01

Optimality models predict that diet-induced bivariate reaction norms for age and size at maturity can have diverse shapes, with the slope varying from negative to positive. To evaluate these predictions, we perform a quantitative review of relevant data, using a literature-derived database of body sizes and development times for over 200 insect species. We show that bivariate reaction norms with a negative slope prevail in nearly all taxonomic and ecological categories of insects as well as in some other ectotherm taxa with comparable life histories (arachnids and amphibians). In insects, positive slopes are largely limited to species, which feed on discrete resource items, parasitoids in particular. By contrast, with virtually no meaningful exceptions, herbivorous and predatory insects display reaction norms with a negative slope. This is consistent with the idea that predictable resource depletion, a scenario selecting for positively sloped reaction norms, is not frequent for these insects. Another source of such selection-a positive correlation between resource levels and juvenile mortality rates-should similarly be rare among insects. Positive slopes can also be predicted by models which integrate life-history evolution and population dynamics. As bottom-up regulation is not common in most insect groups, such models may not be most appropriate for insects. © 2014 The Author(s). Evolution © 2014 The Society for the Study of Evolution.

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

Dispersion Modeling Using Ensemble Forecasts Compared to ETEX Measurements.

NASA Astrophysics Data System (ADS)

Straume, Anne Grete; N'dri Koffi, Ernest; Nodop, Katrin

1998-11-01

Numerous numerical models are developed to predict long-range transport of hazardous air pollution in connection with accidental releases. When evaluating and improving such a model, it is important to detect uncertainties connected to the meteorological input data. A Lagrangian dispersion model, the Severe Nuclear Accident Program, is used here to investigate the effect of errors in the meteorological input data due to analysis error. An ensemble forecast, produced at the European Centre for Medium-Range Weather Forecasts, is then used as model input. The ensemble forecast members are generated by perturbing the initial meteorological fields of the weather forecast. The perturbations are calculated from singular vectors meant to represent possible forecast developments generated by instabilities in the atmospheric flow during the early part of the forecast. The instabilities are generated by errors in the analyzed fields. Puff predictions from the dispersion model, using ensemble forecast input, are compared, and a large spread in the predicted puff evolutions is found. This shows that the quality of the meteorological input data is important for the success of the dispersion model. In order to evaluate the dispersion model, the calculations are compared with measurements from the European Tracer Experiment. The model manages to predict the measured puff evolution concerning shape and time of arrival to a fairly high extent, up to 60 h after the start of the release. The modeled puff is still too narrow in the advection direction.

Predicting the resilience and recovery of aquatic systems: A framework for model evolution within environmental observatories

NASA Astrophysics Data System (ADS)

Hipsey, Matthew R.; Hamilton, David P.; Hanson, Paul C.; Carey, Cayelan C.; Coletti, Janaine Z.; Read, Jordan S.; Ibelings, Bas W.; Valesini, Fiona J.; Brookes, Justin D.

2015-09-01

Maintaining the health of aquatic systems is an essential component of sustainable catchment management, however, degradation of water quality and aquatic habitat continues to challenge scientists and policy-makers. To support management and restoration efforts aquatic system models are required that are able to capture the often complex trajectories that these systems display in response to multiple stressors. This paper explores the abilities and limitations of current model approaches in meeting this challenge, and outlines a strategy based on integration of flexible model libraries and data from observation networks, within a learning framework, as a means to improve the accuracy and scope of model predictions. The framework is comprised of a data assimilation component that utilizes diverse data streams from sensor networks, and a second component whereby model structural evolution can occur once the model is assessed against theoretically relevant metrics of system function. Given the scale and transdisciplinary nature of the prediction challenge, network science initiatives are identified as a means to develop and integrate diverse model libraries and workflows, and to obtain consensus on diagnostic approaches to model assessment that can guide model adaptation. We outline how such a framework can help us explore the theory of how aquatic systems respond to change by bridging bottom-up and top-down lines of enquiry, and, in doing so, also advance the role of prediction in aquatic ecosystem management.

A model integrating longshore and cross-shore processes for predicting long-term shoreline response to climate change

USGS Publications Warehouse

Vitousek, Sean; Barnard, Patrick; Limber, Patrick W.; Erikson, Li; Cole, Blake

2017-01-01

We present a shoreline change model for coastal hazard assessment and management planning. The model, CoSMoS-COAST (Coastal One-line Assimilated Simulation Tool), is a transect-based, one-line model that predicts short-term and long-term shoreline response to climate change in the 21st century. The proposed model represents a novel, modular synthesis of process-based models of coastline evolution due to longshore and cross-shore transport by waves and sea-level rise. Additionally, the model uses an extended Kalman filter for data assimilation of historical shoreline positions to improve estimates of model parameters and thereby improve confidence in long-term predictions. We apply CoSMoS-COAST to simulate sandy shoreline evolution along 500 km of coastline in Southern California, which hosts complex mixtures of beach settings variably backed by dunes, bluffs, cliffs, estuaries, river mouths, and urban infrastructure, providing applicability of the model to virtually any coastal setting. Aided by data assimilation, the model is able to reproduce the observed signal of seasonal shoreline change for the hindcast period of 1995-2010, showing excellent agreement between modeled and observed beach states. The skill of the model during the hindcast period improves confidence in the model's predictive capability when applied to the forecast period (2010-2100) driven by GCM-projected wave and sea-level conditions. Predictions of shoreline change with limited human intervention indicate that 31% to 67% of Southern California beaches may become completely eroded by 2100 under sea-level rise scenarios of 0.93 to 2.0 m.

A model integrating longshore and cross-shore processes for predicting long-term shoreline response to climate change

NASA Astrophysics Data System (ADS)

Vitousek, Sean; Barnard, Patrick L.; Limber, Patrick; Erikson, Li; Cole, Blake

2017-04-01

We present a shoreline change model for coastal hazard assessment and management planning. The model, CoSMoS-COAST (Coastal One-line Assimilated Simulation Tool), is a transect-based, one-line model that predicts short-term and long-term shoreline response to climate change in the 21st century. The proposed model represents a novel, modular synthesis of process-based models of coastline evolution due to longshore and cross-shore transport by waves and sea level rise. Additionally, the model uses an extended Kalman filter for data assimilation of historical shoreline positions to improve estimates of model parameters and thereby improve confidence in long-term predictions. We apply CoSMoS-COAST to simulate sandy shoreline evolution along 500 km of coastline in Southern California, which hosts complex mixtures of beach settings variably backed by dunes, bluffs, cliffs, estuaries, river mouths, and urban infrastructure, providing applicability of the model to virtually any coastal setting. Aided by data assimilation, the model is able to reproduce the observed signal of seasonal shoreline change for the hindcast period of 1995-2010, showing excellent agreement between modeled and observed beach states. The skill of the model during the hindcast period improves confidence in the model's predictive capability when applied to the forecast period (2010-2100) driven by GCM-projected wave and sea level conditions. Predictions of shoreline change with limited human intervention indicate that 31% to 67% of Southern California beaches may become completely eroded by 2100 under sea level rise scenarios of 0.93 to 2.0 m.

Primordial alchemy: from the Big Bang to the present universe

NASA Astrophysics Data System (ADS)

Steigman, Gary

Of the light nuclides observed in the universe today, D, 3He, 4He, and 7Li are relics from its early evolution. The primordial abundances of these relics, produced via Big Bang Nucleosynthesis (BBN) during the first half hour of the evolution of the universe provide a unique window on Physics and Cosmology at redshifts ~1010. Comparing the BBN-predicted abundances with those inferred from observational data tests the consistency of the standard cosmological model over ten orders of magnitude in redshift, constrains the baryon and other particle content of the universe, and probes both Physics and Cosmology beyond the current standard models. These lectures are intended to introduce students, both of theory and observation, to those aspects of the evolution of the universe relevant to the production and evolution of the light nuclides from the Big Bang to the present. The current observational data is reviewed and compared with the BBN predictions and the implications for cosmology (e.g., universal baryon density) and particle physics (e.g., relativistic energy density) are discussed. While this comparison reveals the stunning success of the standard model(s), there are currently some challenge which leave open the door for more theoretical and observational work with potential implications for astronomy, cosmology, and particle physics.

Cognitive algorithms: dynamic logic, working of the mind, evolution of consciousness and cultures

NASA Astrophysics Data System (ADS)

Perlovsky, Leonid I.

2007-04-01

The paper discusses evolution of consciousness driven by the knowledge instinct, a fundamental mechanism of the mind which determines its higher cognitive functions. Dynamic logic mathematically describes the knowledge instinct. It overcomes past mathematical difficulties encountered in modeling intelligence and relates it to mechanisms of concepts, emotions, instincts, consciousness and unconscious. The two main aspects of the knowledge instinct are differentiation and synthesis. Differentiation is driven by dynamic logic and proceeds from vague and unconscious states to more crisp and conscious states, from less knowledge to more knowledge at each hierarchical level of the mind. Synthesis is driven by dynamic logic operating in a hierarchical organization of the mind; it strives to achieve unity and meaning of knowledge: every concept finds its deeper and more general meaning at a higher level. These mechanisms are in complex relationship of symbiosis and opposition, which leads to complex dynamics of evolution of consciousness and cultures. Modeling this dynamics in a population leads to predictions for the evolution of consciousness, and cultures. Cultural predictive models can be compared to experimental data and used for improvement of human conditions. We discuss existing evidence and future research directions.

Dietary specialization is linked to reduced species durations in North American fossil canids

NASA Astrophysics Data System (ADS)

Balisi, Mairin; Casey, Corinna; Van Valkenburgh, Blaire

2018-04-01

How traits influence species persistence is a fundamental question in ecology, evolution and palaeontology. We test the relationship between dietary traits and both species duration and locality coverage over 40 million years in North American canids, a clade with considerable ecomorphological disparity and a dense fossil record. Because ecomorphological generalization-broad resource use-may enable species to withstand disturbance, we predicted that canids of average size and mesocarnivory would exhibit longer durations and wider distributions than specialized larger or smaller species. Second, because locality coverage might reflect dispersal ability and/or survivability in a range of habitats, we predicted that high coverage would correspond with longer durations. We find a nonlinear relationship between species duration and degree of carnivory: species at either end of the carnivory spectrum tend to have shorter durations than mesocarnivores. Locality coverage shows no relationship with size, diet or duration. To test whether generalization (medium size, mesocarnivory) corresponds to an adaptive optimum, we fit trait evolution models to previously generated canid phylogenies. Our analyses identify no single optimum in size or diet. Instead, the primary model of size evolution is a classic Cope's Rule increase over time, while dietary evolution does not conform to a single model.

Modeling the Evolution of Female Meiotic Drive in Maize

PubMed Central

Hall, David W.; Dawe, R. Kelly

2017-01-01

Autosomal drivers violate Mendel’s law of segregation in that they are overrepresented in gametes of heterozygous parents. For drivers to be polymorphic within populations rather than fixing, their transmission advantage must be offset by deleterious effects on other fitness components. In this paper, we develop an analytical model for the evolution of autosomal drivers that is motivated by the neocentromere drive system found in maize. In particular, we model both the transmission advantage and deleterious fitness effects on seed viability, pollen viability, seed to adult survival mediated by maternal genotype, and seed to adult survival mediated by offspring genotype. We derive general, biologically intuitive conditions for the four most likely evolutionary outcomes and discuss the expected evolution of autosomal drivers given these conditions. Finally, we determine the expected equilibrium allele frequencies predicted by the model given recent estimates of fitness components for all relevant genotypes and show that the predicted equilibrium is within the range observed in maize land races for levels of drive at the low end of what has been observed. PMID:29122849

Yardang evolution from maturity to demise

NASA Astrophysics Data System (ADS)

Barchyn, Thomas E.; Hugenholtz, Chris H.

2015-07-01

Yardangs are enigmatic wind-parallel ridges sculpted by aeolian processes that are found extensively in arid environments on Earth and Mars. No general theory exists to explain the long-term evolution of yardangs, curtailing modeling of landscape evolution and dynamics of suspended sediment release. We present a hypothesis of yardang evolution using relative rates of sediment flux, interyardang corridor downcutting, yardang denudation, substrate erodibility, and substrate clast content. To develop and sustain yardangs, corridor downcutting must exceed yardang vertical denudation and deflation. However, erosion of substrate yields considerable quantities of sediment that shelters corridors, slowing downcutting. We model the evolution of yardangs through various combinations of rates and substrate compositions, demonstrating the life span, suspended sediment release, and resulting landscape evolution. We find that yardangs have a distinct and predictable evolution, with inevitable demise and unexpectedly dynamic and autogenic erosion rates driven by subtle differences in substrate clast composition.

Evolution of increased phenotypic diversity enhances population performance by reducing sexual harassment in damselflies.

PubMed

Takahashi, Yuma; Kagawa, Kotaro; Svensson, Erik I; Kawata, Masakado

2014-07-18

The effect of evolutionary changes in traits and phenotypic/genetic diversity on ecological dynamics has received much theoretical attention; however, the mechanisms and ecological consequences are usually unknown. Female-limited colour polymorphism in damselflies is a counter-adaptation to male mating harassment, and thus, is expected to alter population dynamics through relaxing sexual conflict. Here we show the side effect of the evolution of female morph diversity on population performance (for example, population productivity and sustainability) in damselflies. Our theoretical model incorporating key features of the sexual interaction predicts that the evolution of increased phenotypic diversity will reduce overall fitness costs to females from sexual conflict, which in turn will increase productivity, density and stability of a population. Field data and mesocosm experiments support these model predictions. Our study suggests that increased phenotypic diversity can enhance population performance that can potentially reduce extinction rates and thereby influence macroevolutionary processes.

Anatomy of scientific evolution.

PubMed

Yun, Jinhyuk; Kim, Pan-Jun; Jeong, Hawoong

2015-01-01

The quest for historically impactful science and technology provides invaluable insight into the innovation dynamics of human society, yet many studies are limited to qualitative and small-scale approaches. Here, we investigate scientific evolution through systematic analysis of a massive corpus of digitized English texts between 1800 and 2008. Our analysis reveals great predictability for long-prevailing scientific concepts based on the levels of their prior usage. Interestingly, once a threshold of early adoption rates is passed even slightly, scientific concepts can exhibit sudden leaps in their eventual lifetimes. We developed a mechanistic model to account for such results, indicating that slowly-but-commonly adopted science and technology surprisingly tend to have higher innate strength than fast-and-commonly adopted ones. The model prediction for disciplines other than science was also well verified. Our approach sheds light on unbiased and quantitative analysis of scientific evolution in society, and may provide a useful basis for policy-making.

Anatomy of Scientific Evolution

PubMed Central

Yun, Jinhyuk; Kim, Pan-Jun; Jeong, Hawoong

2015-01-01

The quest for historically impactful science and technology provides invaluable insight into the innovation dynamics of human society, yet many studies are limited to qualitative and small-scale approaches. Here, we investigate scientific evolution through systematic analysis of a massive corpus of digitized English texts between 1800 and 2008. Our analysis reveals great predictability for long-prevailing scientific concepts based on the levels of their prior usage. Interestingly, once a threshold of early adoption rates is passed even slightly, scientific concepts can exhibit sudden leaps in their eventual lifetimes. We developed a mechanistic model to account for such results, indicating that slowly-but-commonly adopted science and technology surprisingly tend to have higher innate strength than fast-and-commonly adopted ones. The model prediction for disciplines other than science was also well verified. Our approach sheds light on unbiased and quantitative analysis of scientific evolution in society, and may provide a useful basis for policy-making. PMID:25671617

Experimental and Numerical Analysis of Microstructures and Stress States of Shot-Peened GH4169 Superalloys

NASA Astrophysics Data System (ADS)

Hu, Dianyin; Gao, Ye; Meng, Fanchao; Song, Jun; Wang, Rongqiao

2018-04-01

Combining experiments and finite element analysis (FEA), a systematic study was performed to analyze the microstructural evolution and stress states of shot-peened GH4169 superalloy over a variety of peening intensities and coverages. A dislocation density evolution model was integrated into the representative volume FEA model to quantitatively predict microstructural evolution in the surface layers and compared with experimental results. It was found that surface roughness and through-depth residual stress profile are more sensitive to shot-peening intensity compared to coverage due to the high kinetic energy involved. Moreover, a surface nanocrystallization layer was discovered in the top surface region of GH4169 for all shot-peening conditions. However, the grain refinement was more intensified under high shot-peening coverage, under which enough time was permitted for grain refinement. The grain size gradient predicted by the numerical framework showed good agreement with experimental observations.

Predicting the resilience and recovery of aquatic systems: a framework for model evolution within environmental observatories

USGS Publications Warehouse

Hipsey, Matthew R.; Hamilton, David P.; Hanson, Paul C.; Carey, Cayelan C.; Coletti, Janaine Z; Read, Jordan S.; Ibelings, Bas W; Valensini, Fiona J; Brookes, Justin D

2015-01-01

Maintaining the health of aquatic systems is an essential component of sustainable catchmentmanagement, however, degradation of water quality and aquatic habitat continues to challenge scientistsand policy-makers. To support management and restoration efforts aquatic system models are requiredthat are able to capture the often complex trajectories that these systems display in response to multiplestressors. This paper explores the abilities and limitations of current model approaches in meeting this chal-lenge, and outlines a strategy based on integration of flexible model libraries and data from observationnetworks, within a learning framework, as a means to improve the accuracy and scope of model predictions.The framework is comprised of a data assimilation component that utilizes diverse data streams from sensornetworks, and a second component whereby model structural evolution can occur once the model isassessed against theoretically relevant metrics of system function. Given the scale and transdisciplinarynature of the prediction challenge, network science initiatives are identified as a means to develop and inte-grate diverse model libraries and workflows, and to obtain consensus on diagnostic approaches to modelassessment that can guide model adaptation. We outline how such a framework can help us explore thetheory of how aquatic systems respond to change by bridging bottom-up and top-down lines of enquiry,and, in doing so, also advance the role of prediction in aquatic ecosystem management.

Evolution-informed forecasting of seasonal influenza A (H3N2)

PubMed Central

Du, Xiangjun; King, Aaron A.; Woods, Robert J.; Pascual, Mercedes

2018-01-01

Inter-pandemic or seasonal influenza exacts an enormous annual burden both in terms of human health and economic impact. Incidence prediction ahead of season remains a challenge largely because of the virus’ antigenic evolution. We propose here a forecasting approach that incorporates evolutionary change into a mechanistic epidemiological model. The proposed models are simple enough that their parameters can be estimated from retrospective surveillance data. These models link amino-acid sequences of hemagglutinin epitopes with a transmission model for seasonal H3N2 influenza, also informed by H1N1 levels. With a monthly time series of H3N2 incidence in the United States over 10 years, we demonstrate the feasibility of prediction ahead of season and an accurate real-time forecast for the 2016/2017 influenza season. PMID:29070700

Weakly Nonlinear Model with Exact Coefficients for the Fluttering and Spiraling Motion of Buoyancy-Driven Bodies

NASA Astrophysics Data System (ADS)

Tchoufag, Joël; Fabre, David; Magnaudet, Jacques

2015-09-01

Gravity- or buoyancy-driven bodies moving in a slightly viscous fluid frequently follow fluttering or helical paths. Current models of such systems are largely empirical and fail to predict several of the key features of their evolution, especially close to the onset of path instability. Here, using a weakly nonlinear expansion of the full set of governing equations, we present a new generic reduced-order model based on a pair of amplitude equations with exact coefficients that drive the evolution of the first pair of unstable modes. We show that the predictions of this model for the style (e.g., fluttering or spiraling) and characteristics (e.g., frequency and maximum inclination angle) of path oscillations compare well with various recent data for both solid disks and air bubbles.

A weakly nonlinear model with exact coefficients for the fluttering and spiraling motions of buoyancy-driven bodies

NASA Astrophysics Data System (ADS)

Magnaudet, Jacques; Tchoufag, Joel; Fabre, David

2015-11-01

Gravity/buoyancy-driven bodies moving in a slightly viscous fluid frequently follow fluttering or helical paths. Current models of such systems are largely empirical and fail to predict several of the key features of their evolution, especially close to the onset of path instability. Using a weakly nonlinear expansion of the full set of governing equations, we derive a new generic reduced-order model of this class of phenomena based on a pair of amplitude equations with exact coefficients that drive the evolution of the first pair of unstable modes. We show that the predictions of this model for the style (eg. fluttering or spiraling) and characteristics (eg. frequency and maximum inclination angle) of path oscillations compare well with various recent data for both solid disks and air bubbles.

Cold formability prediction by the modified maximum force criterion with a non-associated Hill48 model accounting for anisotropic hardening

NASA Astrophysics Data System (ADS)

Lian, J.; Ahn, D. C.; Chae, D. C.; Münstermann, S.; Bleck, W.

2016-08-01

Experimental and numerical investigations on the characterisation and prediction of cold formability of a ferritic steel sheet are performed in this study. Tensile tests and Nakajima tests were performed for the plasticity characterisation and the forming limit diagram determination. In the numerical prediction, the modified maximum force criterion is selected as the localisation criterion. For the plasticity model, a non-associated formulation of the Hill48 model is employed. With the non-associated flow rule, the model can result in a similar predictive capability of stress and r-value directionality to the advanced non-quadratic associated models. To accurately characterise the anisotropy evolution during hardening, the anisotropic hardening is also calibrated and implemented into the model for the prediction of the formability.

Empirical approaches to the study of language evolution.

PubMed

Fitch, W Tecumseh

2017-02-01

The study of language evolution, and human cognitive evolution more generally, has often been ridiculed as unscientific, but in fact it differs little from many other disciplines that investigate past events, such as geology or cosmology. Well-crafted models of language evolution make numerous testable hypotheses, and if the principles of strong inference (simultaneous testing of multiple plausible hypotheses) are adopted, there is an increasing amount of relevant data allowing empirical evaluation of such models. The articles in this special issue provide a concise overview of current models of language evolution, emphasizing the testable predictions that they make, along with overviews of the many sources of data available to test them (emphasizing comparative, neural, and genetic data). The key challenge facing the study of language evolution is not a lack of data, but rather a weak commitment to hypothesis-testing approaches and strong inference, exacerbated by the broad and highly interdisciplinary nature of the relevant data. This introduction offers an overview of the field, and a summary of what needed to evolve to provide our species with language-ready brains. It then briefly discusses different contemporary models of language evolution, followed by an overview of different sources of data to test these models. I conclude with my own multistage model of how different components of language could have evolved.

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.

Reduced quasilinear models for energetic particles interaction with Alfvenic eigenmodes

NASA Astrophysics Data System (ADS)

Ghantous, Katy

The Line Broadened Quasilinear (LBQ) and the 1.5D reduced models are able to predict the effect of Alfvenic eigenmodes' interaction with energetic particles in burning plasmas. This interaction can result in energetic-particle losses that can damage the first wall, deteriorate the plasma performance, and even prevent ignition. The 1.5D model assumes a broad spectrum of overlapping modes and, based on analytic expressions for the growth and damping rates, calculates the pressure profiles that the energetic particles relax to upon interacting with the modes. 1.5D is validated with DIII-D experiments and predicted neutron losses consistent with observation. The model is employed to predict alpha-particle fusion-product losses in a large-scale operational parameter-space for burning plasmas. The LBQ model captures the interaction both in the regime of isolated modes as well as in the conventional regime of overlapping modes. Rules were established that allow quasilinear equations to replicate the expected steady-state saturation levels of isolated modes. The fitting formula is improved and the model is benchmarked with a Vlasov code, BOT. The saturation levels are accurately predicted and the mode evolution is well-replicated in the case of steady-state evolution where the collisions are high enough that coherent structures do not form. When the collisionality is low, oscillatory behavior can occur. LBQ can also exhibit non-steady behavior, but the onset of oscillations occurs for much higher collisional rates in BOT than in LBQ. For certain parameters of low collisionality, hole-clump creation and frequency chirping can occur which are not captured by the LBQ model. Also, there are cases of non-steady evolution without chirping which is possible for LBQ to study. However the results are inconclusive since the periods and amplitudes of the oscillations in the mode evolution are not well-replicated. If multiple modes exist, they can grow to the point of overlap which results in two-dimensional diffusion with cross terms. A diffusion scheme is proposed and validated to resolve this dynamics in (Pφ,E) phase-space.

Forecasting the Northern African Dust Outbreak Towards Europe in April 2011: A Model Intercomparison

NASA Technical Reports Server (NTRS)

Huneeus, N.; Basart, S.; Fiedler, S.; Morcrette, J.-J.; Benedetti, A.; Mulcahy, J.; Terradellas, E.; Pérez García-Pando, C.; Pejanovic, G.; Nickovic, S.

2016-01-01

In the framework of the World Meteorological Organisation's Sand and Dust Storm Warning Advisory and Assessment System, we evaluated the predictions of five state-of-the-art dust forecast models during an intense Saharan dust outbreak affecting western and northern Europe in April 2011. We assessed the capacity of the models to predict the evolution of the dust cloud with lead times of up to 72 hours using observations of aerosol optical depth (AOD) from the AErosol RObotic NETwork (AERONET) and the Moderate Resolution Imaging Spectroradiometer (MODIS) and dust surface concentrations from a ground-based measurement network. In addition, the predicted vertical dust distribution was evaluated with vertical extinction profiles from the Cloud and Aerosol Lidar with Orthogonal Polarization (CALIOP). To assess the diversity in forecast capability among the models, the analysis was extended to wind field (both surface and profile), synoptic conditions, emissions and deposition fluxes. Models predict the onset and evolution of the AOD for all analysed lead times. On average, differences among the models are larger than differences among lead times for each individual model. In spite of large differences in emission and deposition, the models present comparable skill for AOD. In general, models are better in predicting AOD than near-surface dust concentration over the Iberian Peninsula. Models tend to underestimate the long-range transport towards northern Europe. Our analysis suggests that this is partly due to difficulties in simulating the vertical distribution dust and horizontal wind. Differences in the size distribution and wet scavenging efficiency may also account for model diversity in long-range transport.

Solid phase evolution in the Biosphere 2 hillslope experiment as predicted by modeling of hydrologic and geochemical fluxes

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

Dontsova, K.; Steefel, C.I.; Desilets, S.

2009-07-15

A reactive transport geochemical modeling study was conducted to help predict the mineral transformations occurring over a ten year time-scale that are expected to impact soil hydraulic properties in the Biosphere 2 (B2) synthetic hillslope experiment. The modeling sought to predict the rate and extent of weathering of a granular basalt (selected for hillslope construction) as a function of climatic drivers, and to assess the feedback effects of such weathering processes on the hydraulic properties of the hillslope. Flow vectors were imported from HYDRUS into a reactive transport code, CrunchFlow2007, which was then used to model mineral weathering coupled tomore » reactive solute transport. Associated particle size evolution was translated into changes in saturated hydraulic conductivity using Rosetta software. We found that flow characteristics, including velocity and saturation, strongly influenced the predicted extent of incongruent mineral weathering and neo-phase precipitation on the hillslope. Results were also highly sensitive to specific surface areas of the soil media, consistent with surface reaction controls on dissolution. Effects of fluid flow on weathering resulted in significant differences in the prediction of soil particle size distributions, which should feedback to alter hillslope hydraulic conductivities.« less

Integrated Model of Multiple Kernel Learning and Differential Evolution for EUR/USD Trading

PubMed Central

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. PMID:25097891

Alternating high and low climate variability: The context of natural selection and speciation in Plio-Pleistocene hominin evolution.

PubMed

Potts, Richard; Faith, J Tyler

2015-10-01

Interaction of orbital insolation cycles defines a predictive model of alternating phases of high- and low-climate variability for tropical East Africa over the past 5 million years. This model, which is described in terms of climate variability stages, implies repeated increases in landscape/resource instability and intervening periods of stability in East Africa. It predicts eight prolonged (>192 kyr) eras of intensified habitat instability (high variability stages) in which hominin evolutionary innovations are likely to have occurred, potentially by variability selection. The prediction that repeated shifts toward high climate variability affected paleoenvironments and evolution is tested in three ways. In the first test, deep-sea records of northeast African terrigenous dust flux (Sites 721/722) and eastern Mediterranean sapropels (Site 967A) show increased and decreased variability in concert with predicted shifts in climate variability. These regional measurements of climate dynamics are complemented by stratigraphic observations in five basins with lengthy stratigraphic and paleoenvironmental records: the mid-Pleistocene Olorgesailie Basin, the Plio-Pleistocene Turkana and Olduvai Basins, and the Pliocene Tugen Hills sequence and Hadar Basin--all of which show that highly variable landscapes inhabited by hominin populations were indeed concentrated in predicted stages of prolonged high climate variability. Second, stringent null-model tests demonstrate a significant association of currently known first and last appearance datums (FADs and LADs) of the major hominin lineages, suites of technological behaviors, and dispersal events with the predicted intervals of prolonged high climate variability. Palynological study in the Nihewan Basin, China, provides a third test, which shows the occupation of highly diverse habitats in eastern Asia, consistent with the predicted increase in adaptability in dispersing Oldowan hominins. Integration of fossil, archeological, sedimentary, and paleolandscape evidence illustrates the potential influence of prolonged high variability on the origin and spread of critical adaptations and lineages in the evolution of Homo. The growing body of data concerning environmental dynamics supports the idea that the evolution of adaptability in response to climate and overall ecological instability represents a unifying theme in hominin evolutionary history. Published by Elsevier Ltd.

Machine remaining useful life prediction: An integrated adaptive neuro-fuzzy and high-order particle filtering approach

NASA Astrophysics Data System (ADS)

Chen, Chaochao; Vachtsevanos, George; Orchard, Marcos E.

2012-04-01

Machine prognosis can be considered as the generation of long-term predictions that describe the evolution in time of a fault indicator, with the purpose of estimating the remaining useful life (RUL) of a failing component/subsystem so that timely maintenance can be performed to avoid catastrophic failures. This paper proposes an integrated RUL prediction method using adaptive neuro-fuzzy inference systems (ANFIS) and high-order particle filtering, which forecasts the time evolution of the fault indicator and estimates the probability density function (pdf) of RUL. The ANFIS is trained and integrated in a high-order particle filter as a model describing the fault progression. The high-order particle filter is used to estimate the current state and carry out p-step-ahead predictions via a set of particles. These predictions are used to estimate the RUL pdf. The performance of the proposed method is evaluated via the real-world data from a seeded fault test for a UH-60 helicopter planetary gear plate. The results demonstrate that it outperforms both the conventional ANFIS predictor and the particle-filter-based predictor where the fault growth model is a first-order model that is trained via the ANFIS.

Comparison of equilibrium ohmic and nonequilibrium swarm models for monitoring conduction electron evolution in high-altitude EMP calculations

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

Pusateri, Elise N.; Morris, Heidi E.; Nelson, Eric

2016-10-17

Here, atmospheric electromagnetic pulse (EMP) events are important physical phenomena that occur through both man-made and natural processes. Radiation-induced currents and voltages in EMP can couple with electrical systems, such as those found in satellites, and cause significant damage. Due to the disruptive nature of EMP, it is important to accurately predict EMP evolution and propagation with computational models. CHAP-LA (Compton High Altitude Pulse-Los Alamos) is a state-of-the-art EMP code that solves Maxwell inline images equations for gamma source-induced electromagnetic fields in the atmosphere. In EMP, low-energy, conduction electrons constitute a conduction current that limits the EMP by opposing themore » Compton current. CHAP-LA calculates the conduction current using an equilibrium ohmic model. The equilibrium model works well at low altitudes, where the electron energy equilibration time is short compared to the rise time or duration of the EMP. At high altitudes, the equilibration time increases beyond the EMP rise time and the predicted equilibrium ionization rate becomes very large. The ohmic model predicts an unphysically large production of conduction electrons which prematurely and abruptly shorts the EMP in the simulation code. An electron swarm model, which implicitly accounts for the time evolution of the conduction electron energy distribution, can be used to overcome the limitations exhibited by the equilibrium ohmic model. We have developed and validated an electron swarm model previously in Pusateri et al. (2015). Here we demonstrate EMP damping behavior caused by the ohmic model at high altitudes and show improvements on high-altitude, upward EMP modeling obtained by integrating a swarm model into CHAP-LA.« less

Comparison of equilibrium ohmic and nonequilibrium swarm models for monitoring conduction electron evolution in high-altitude EMP calculations

NASA Astrophysics Data System (ADS)

Pusateri, Elise N.; Morris, Heidi E.; Nelson, Eric; Ji, Wei

2016-10-01

Atmospheric electromagnetic pulse (EMP) events are important physical phenomena that occur through both man-made and natural processes. Radiation-induced currents and voltages in EMP can couple with electrical systems, such as those found in satellites, and cause significant damage. Due to the disruptive nature of EMP, it is important to accurately predict EMP evolution and propagation with computational models. CHAP-LA (Compton High Altitude Pulse-Los Alamos) is a state-of-the-art EMP code that solves Maxwell's equations for gamma source-induced electromagnetic fields in the atmosphere. In EMP, low-energy, conduction electrons constitute a conduction current that limits the EMP by opposing the Compton current. CHAP-LA calculates the conduction current using an equilibrium ohmic model. The equilibrium model works well at low altitudes, where the electron energy equilibration time is short compared to the rise time or duration of the EMP. At high altitudes, the equilibration time increases beyond the EMP rise time and the predicted equilibrium ionization rate becomes very large. The ohmic model predicts an unphysically large production of conduction electrons which prematurely and abruptly shorts the EMP in the simulation code. An electron swarm model, which implicitly accounts for the time evolution of the conduction electron energy distribution, can be used to overcome the limitations exhibited by the equilibrium ohmic model. We have developed and validated an electron swarm model previously in Pusateri et al. (2015). Here we demonstrate EMP damping behavior caused by the ohmic model at high altitudes and show improvements on high-altitude, upward EMP modeling obtained by integrating a swarm model into CHAP-LA.

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.

Effects of Extrinsic Mortality on the Evolution of Aging: A Stochastic Modeling Approach

PubMed Central

Shokhirev, Maxim Nikolaievich; Johnson, Adiv Adam

2014-01-01

The evolutionary theories of aging are useful for gaining insights into the complex mechanisms underlying senescence. Classical theories argue that high levels of extrinsic mortality should select for the evolution of shorter lifespans and earlier peak fertility. Non-classical theories, in contrast, posit that an increase in extrinsic mortality could select for the evolution of longer lifespans. Although numerous studies support the classical paradigm, recent data challenge classical predictions, finding that high extrinsic mortality can select for the evolution of longer lifespans. To further elucidate the role of extrinsic mortality in the evolution of aging, we implemented a stochastic, agent-based, computational model. We used a simulated annealing optimization approach to predict which model parameters predispose populations to evolve longer or shorter lifespans in response to increased levels of predation. We report that longer lifespans evolved in the presence of rising predation if the cost of mating is relatively high and if energy is available in excess. Conversely, we found that dramatically shorter lifespans evolved when mating costs were relatively low and food was relatively scarce. We also analyzed the effects of increased predation on various parameters related to density dependence and energy allocation. Longer and shorter lifespans were accompanied by increased and decreased investments of energy into somatic maintenance, respectively. Similarly, earlier and later maturation ages were accompanied by increased and decreased energetic investments into early fecundity, respectively. Higher predation significantly decreased the total population size, enlarged the shared resource pool, and redistributed energy reserves for mature individuals. These results both corroborate and refine classical predictions, demonstrating a population-level trade-off between longevity and fecundity and identifying conditions that produce both classical and non-classical lifespan effects. PMID:24466165

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 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.

Sixty-Five Million Years of Change in Temperature and Topography Explain Evolutionary History in Eastern North American Plethodontid Salamanders.

PubMed

Barnes, Richard; Clark, Adam Thomas

2017-07-01

For many taxa and systems, species richness peaks at midelevations. One potential explanation for this pattern is that large-scale changes in climate and geography have, over evolutionary time, selected for traits that are favored under conditions found in contemporary midelevation regions. To test this hypothesis, we use records of historical temperature and topographic changes over the past 65 Myr to construct a general simulation model of plethodontid salamander evolution in eastern North America. We then explore possible mechanisms constraining species to midelevation bands by using the model to predict plethodontid evolutionary history and contemporary geographic distributions. Our results show that models that incorporate both temperature and topographic changes are better able to predict these patterns, suggesting that both processes may have played an important role in driving plethodontid evolution in the region. Additionally, our model (whose annotated source code is included as a supplement) represents a proof of concept to encourage future work that takes advantage of recent advances in computing power to combine models of ecology, evolution, and earth history to better explain the abundance and distribution of species over time.

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

NASA Astrophysics Data System (ADS)

Zhang, Chengzhu

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

Observational properties of massive black hole binary progenitors

NASA Astrophysics Data System (ADS)

Hainich, R.; Oskinova, L. M.; Shenar, T.; Marchant, P.; Eldridge, J. J.; Sander, A. A. C.; Hamann, W.-R.; Langer, N.; Todt, H.

2018-01-01

Context. The first directly detected gravitational waves (GW 150914) were emitted by two coalescing black holes (BHs) with masses of ≈ 36 M⊙ and ≈ 29 M⊙. Several scenarios have been proposed to put this detection into an astrophysical context. The evolution of an isolated massive binary system is among commonly considered models. Aims: Various groups have performed detailed binary-evolution calculations that lead to BH merger events. However, the question remains open as to whether binary systems with the predicted properties really exist. The aim of this paper is to help observers to close this gap by providing spectral characteristics of massive binary BH progenitors during a phase where at least one of the companions is still non-degenerate. Methods: Stellar evolution models predict fundamental stellar parameters. Using these as input for our stellar atmosphere code (Potsdam Wolf-Rayet), we compute a set of models for selected evolutionary stages of massive merging BH progenitors at different metallicities. Results: The synthetic spectra obtained from our atmosphere calculations reveal that progenitors of massive BH merger events start their lives as O2-3V stars that evolve to early-type blue supergiants before they undergo core-collapse during the Wolf-Rayet phase. When the primary has collapsed, the remaining system will appear as a wind-fed high-mass X-ray binary. Based on our atmosphere models, we provide feedback parameters, broad band magnitudes, and spectral templates that should help to identify such binaries in the future. Conclusions: While the predicted parameter space for massive BH binary progenitors is partly realized in nature, none of the known massive binaries match our synthetic spectra of massive BH binary progenitors exactly. Comparisons of empirically determined mass-loss rates with those assumed by evolution calculations reveal significant differences. The consideration of the empirical mass-loss rates in evolution calculations will possibly entail a shift of the maximum in the predicted binary-BH merger rate to higher metallicities, that is, more candidates should be expected in our cosmic neighborhood than previously assumed.

NARMAX model identification of a palm oil biodiesel engine using multi-objective optimization differential evolution

NASA Astrophysics Data System (ADS)

Mansor, Zakwan; Zakaria, Mohd Zakimi; Nor, Azuwir Mohd; Saad, Mohd Sazli; Ahmad, Robiah; Jamaluddin, Hishamuddin

2017-09-01

This paper presents the black-box modelling of palm oil biodiesel engine (POB) using multi-objective optimization differential evolution (MOODE) algorithm. Two objective functions are considered in the algorithm for optimization; minimizing the number of term of a model structure and minimizing the mean square error between actual and predicted outputs. The mathematical model used in this study to represent the POB system is nonlinear auto-regressive moving average with exogenous input (NARMAX) model. Finally, model validity tests are applied in order to validate the possible models that was obtained from MOODE algorithm and lead to select an optimal model.

Thermal Modeling of Al-Al and Al-Steel Friction Stir Spot Welding

NASA Astrophysics Data System (ADS)

Jedrasiak, P.; Shercliff, H. R.; Reilly, A.; McShane, G. J.; Chen, Y. C.; Wang, L.; Robson, J.; Prangnell, P.

2016-09-01

This paper presents a finite element thermal model for similar and dissimilar alloy friction stir spot welding (FSSW). The model is calibrated and validated using instrumented lap joints in Al-Al and Al-Fe automotive sheet alloys. The model successfully predicts the thermal histories for a range of process conditions. The resulting temperature histories are used to predict the growth of intermetallic phases at the interface in Al-Fe welds. Temperature predictions were used to study the evolution of hardness of a precipitation-hardened aluminum alloy during post-weld aging after FSSW.

Evaluating the Discrete Element Method as a Tool for Predicting the Seasonal Evolution of the MIZ

DTIC Science & Technology

2015-09-30

wave-ice interaction (Hopkins & Shen 2001), and the mesoscale evolution of the floe size distribution (Hopkins & Thorndike 2006). This modeling effort...33(1), 355-360. Hopkins, M. A., & Thorndike , A. S. (2006) Floe formation in Arctic sea ice. Journal of Geophysical Research: Oceans (1978–2012), 111

A general model for the scaling of offspring size and adult size.

PubMed

Falster, Daniel S; Moles, Angela T; Westoby, Mark

2008-09-01

Understanding evolutionary coordination among different life-history traits is a key challenge for ecology and evolution. Here we develop a general quantitative model predicting how offspring size should scale with adult size by combining a simple model for life-history evolution with a frequency-dependent survivorship model. The key innovation is that larger offspring are afforded three different advantages during ontogeny: higher survivorship per time, a shortened juvenile phase, and advantage during size-competitive growth. In this model, it turns out that size-asymmetric advantage during competition is the factor driving evolution toward larger offspring sizes. For simplified and limiting cases, the model is shown to produce the same predictions as the previously existing theory on which it is founded. The explicit treatment of different survival advantages has biologically important new effects, mainly through an interaction between total maternal investment in reproduction and the duration of competitive growth. This goes on to explain alternative allometries between log offspring size and log adult size, as observed in mammals (slope = 0.95) and plants (slope = 0.54). Further, it suggests how these differences relate quantitatively to specific biological processes during recruitment. In these ways, the model generalizes across previous theory and provides explanations for some differences between major taxa.

Acceleration of Relativistic Electrons: A Comparison of Two Models

NASA Astrophysics Data System (ADS)

Green, J. C.; Kivelson, M. G.

2001-12-01

Observations of relativistic electron fluxes show order of magnitude increases during some geomagnetic storms. Many electron acceleration models have been proposed to explain the flux enhancements but attempts to validate these models have yielded ambiguous results. Here we examine two models of electron acceleration, radial diffusion via enhanced ULF wave activity [Elkington et al.,1999] and acceleration by resonant interaction with whistler waves[Summers,1998; Roth et al.,1999]. Two methods are used to compare observations with features predicted by the models. First, the evolution of phase space density as a function of L during flux enhancement events is evaluated. The phase space density (PSD) is calculated at constant first, second and third adiabatic invariants using data obtained by the CEPPAD-HIST instrument and the MFE instrument onboard the Polar spacecraft. Liouville's theorem states that PSD calculated at constant adiabatic invariants does not change with time unless some mechanism violates one of the invariants. The radial diffusion model predicts that only the flux invariant will be violated during the acceleration process while acceleration by whistler waves violates the first invariant. Therefore, the two models predict a different evolution of the PSD as a function of time and L. Previous examinations of the evolution of PSD have yielded ambiguous results because PSD calculations are highly dependent on the global accuracy of magnetic field models. We examine the PSD versus L profiles for a series of geomagnetic storms and in addition determine how errors in the Tsyganenko 96 field model affect the results by comparing the measured magnetic field to the model magnetic field used in the calculations. Second, the evolution of the relativistic electron pitch angle distributions is evaluated. Previous studies of pitch angle distributions were limited because few spacecraft have the necessary instrumentation and global coverage. The CEPPAD-HIST instrument measures 16 look directions and along with measurements from the MFE experiment allows calculation of complete pitch angle distributions. The evolving orbit of the Polar spacecraft over the 6 years mission has given measurements over a wide range of L and local time. Using data extending over the entire mission we use superposed epoch analysis to examine the evolution of pitch angle distributions during flux enhancement events as a function of L, magnetic local time, and storm phase.

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.

Tropical cyclones over the North Indian Ocean: experiments with the high-resolution global icosahedral grid point model GME

NASA Astrophysics Data System (ADS)

Kumkar, Yogesh V.; Sen, P. N.; Chaudhari, Hemankumar S.; Oh, Jai-Ho

2018-02-01

In this paper, an attempt has been made to conduct a numerical experiment with the high-resolution global model GME to predict the tropical storms in the North Indian Ocean during the year 2007. Numerical integrations using the icosahedral hexagonal grid point global model GME were performed to study the evolution of tropical cyclones, viz., Akash, Gonu, Yemyin and Sidr over North Indian Ocean during 2007. It has been seen that the GME model forecast underestimates cyclone's intensity, but the model can capture the evolution of cyclone's intensity especially its weakening during landfall, which is primarily due to the cutoff of the water vapor supply in the boundary layer as cyclones approach the coastal region. A series of numerical simulation of tropical cyclones have been performed with GME to examine model capability in prediction of intensity and track of the cyclones. The model performance is evaluated by calculating the root mean square errors as cyclone track errors.

Studying the highly bent spectra of FR II-type radio galaxies with the KDA EXT model

NASA Astrophysics Data System (ADS)

Kuligowska, Elżbieta

2018-04-01

Context. The Kaiser, Dennett-Thorpe & Alexander (KDA, 1997, MNRAS, 292, 723) EXT model, that is, the extension of the KDA model of Fanaroff & Riley (FR) II-type source evolution, is applied and confronted with the observational data for selected FR II-type radio sources with significantly aged radio spectra. Aim. A sample of FR II-type radio galaxies with radio spectra strongly bent at their highest frequencies is used for testing the usefulness of the KDA EXT model. Methods: The dynamical evolution of FR II-type sources predicted with the KDA EXT model is briefly presented and discussed. The results are then compared to the ones obtained with the classical KDA approach, assuming the source's continuous injection and self-similarity. Results: The results and corresponding diagrams obtained for the eight sample sources indicate that the KDA EXT model predicts the observed radio spectra significantly better than the best spectral fit provided by the original KDA model.

Temporal association between the influenza virus and respiratory syncytial virus (RSV): RSV as a predictor of seasonal influenza.

PubMed

Míguez, A; Iftimi, A; Montes, F

2016-09-01

Epidemiologists agree that there is a prevailing seasonality in the presentation of epidemic waves of respiratory syncytial virus (RSV) infections and influenza. The aim of this study is to quantify the potential relationship between the activity of RSV, with respect to the influenza virus, in order to use the RSV seasonal curve as a predictor of the evolution of an influenza virus epidemic wave. Two statistical tools, logistic regression and time series, are used for predicting the evolution of influenza. Both logistic models and time series of influenza consider RSV information from previous weeks. Data consist of influenza and confirmed RSV cases reported in Comunitat Valenciana (Spain) during the period from week 40 (2010) to week 8 (2014). Binomial logistic regression models used to predict the two states of influenza wave, basal or peak, result in a rate of correct classification higher than 92% with the validation set. When a finer three-states categorization is established, basal, increasing peak and decreasing peak, the multinomial logistic model performs well in 88% of cases of the validation set. The ARMAX model fits well for influenza waves and shows good performance for short-term forecasts up to 3 weeks. The seasonal evolution of influenza virus can be predicted a minimum of 4 weeks in advance using logistic models based on RSV. It would be necessary to study more inter-pandemic seasons to establish a stronger relationship between the epidemic waves of both viruses.

Observational breakthroughs lead the way to improved hydrological predictions

NASA Astrophysics Data System (ADS)

Lettenmaier, Dennis P.

2017-04-01

New data sources are revolutionizing the hydrological sciences. The capabilities of hydrological models have advanced greatly over the last several decades, but until recently model capabilities have outstripped the spatial resolution and accuracy of model forcings (atmospheric variables at the land surface) and the hydrologic state variables (e.g., soil moisture; snow water equivalent) that the models predict. This has begun to change, as shown in two examples here: soil moisture and drought evolution over Africa as predicted by a hydrology model forced with satellite-derived precipitation, and observations of snow water equivalent at very high resolution over a river basin in California's Sierra Nevada.

Demographics, political power and economic growth.

PubMed

Holtz-eakin, D

1993-01-01

"Growth theory may be used to predict the response of saving, capital formation, and output growth to large demographic shifts. Such large shifts would also be expected to alter the demand for government services and the desired levels of taxation in the population. This paper extends the overlapping-generations model of economic growth to predict the evolution of government tax and spending policy through the course of a major demographic shift. Simulations suggest that this approach may yield valuable insights into the evolution of policy in the United States and other industrialized economies." excerpt

Sexual selection favours male parental care, when females can choose

PubMed Central

Alonzo, Suzanne H.

2012-01-01

Explaining the evolution of male care has proved difficult. Recent theory predicts that female promiscuity and sexual selection on males inherently disfavour male care. In sharp contrast to these expectations, male-only care is often found in species with high extra-pair paternity and striking variation in mating success, where current theory predicts female-only care. Using a model that examines the coevolution of male care, female care and female choice; I show that inter-sexual selection can drive the evolution of male care when females are able to bias mating or paternity towards parental males. Surprisingly, female choice for parental males allows male care to evolve despite low relatedness between the male and the offspring in his care. These results imply that predicting how sexual selection affects parental care evolution will require further understanding of why females, in many species, either do not prefer or cannot favour males that provide care. PMID:22171082

Damage evolution and mechanical response of cross-ply ceramic composite laminates

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

Weitsman, Y.; Yu, N.; Zhu, H.

1995-12-31

A mechanistic model for the damage evolution and mechanical response of cross-ply ceramic composite laminates under monotonically increasing uniaxial tension is presented. The model accounts for a variety of damage mechanisms evolving in cross-ply ceramic composite laminates, such as fiber-bridged matrix cracks in 0{degrees}-plies, transversely oriented matrix cracks in 90{degrees}-plies, and slips at 0{degrees}/90{degrees} ply interfaces as well as at the fiber/matrix interfaces. Energy criteria are developed to determine the creation and progression of matrix cracks and slip zones. The model predicts that the crack density in 0{degrees}-plies becomes higher than that within the 90{degrees}-plies as the applied load ismore » incrementally increased, which agrees with the experimental observation. It is also shown that the model provides a reasonable prediction for the nonlinear stress-strain behavior of crossply SiC/CAS ceramic composites.« less

Evolution of Rotor Wake in Swirling Flow

NASA Technical Reports Server (NTRS)

El-Haldidi, Basman; Atassi, Hafiz; Envia, Edmane; Podboy, Gary

2000-01-01

A theory is presented for modeling the evolution of rotor wakes as a function of axial distance in swirling mean flows. The theory, which extends an earlier work to include arbitrary radial distributions of mean swirl, indicates that swirl can significantly alter the wake structure of the rotor especially at large downstream distances (i.e., for moderate to large rotor-stator spacings). Using measured wakes of a representative scale model fan stage to define the mean swirl and initial wake perturbations, the theory is used to predict the subsequent evolution of the wakes. The results indicate the sensitivity of the wake evolution to the initial profile and the need to have complete and consistent initial definition of both velocity and pressure perturbations.

Arms race between selfishness and policing: two-trait quantitative genetic model for caste fate conflict in eusocial Hymenoptera.

PubMed

Dobata, Shigeto

2012-12-01

Policing against selfishness is now regarded as the main force maintaining cooperation, by reducing costly conflict in complex social systems. Although policing has been studied extensively in social insect colonies, its coevolution against selfishness has not been fully captured by previous theories. In this study, I developed a two-trait quantitative genetic model of the conflict between selfish immature females (usually larvae) and policing workers in eusocial Hymenoptera over the immatures' propensity to develop into new queens. This model allows for the analysis of coevolution between genomes expressed in immatures and workers that collectively determine the immatures' queen caste fate. The main prediction of the model is that a higher level of polyandry leads to a smaller fraction of queens produced among new females through caste fate policing. The other main prediction of the present model is that, as a result of arms race, caste fate policing by workers coevolves with exaggerated selfishness of the immatures achieving maximum potential to develop into queens. Moreover, the model can incorporate genetic correlation between traits, which has been largely unexplored in social evolution theory. This study highlights the importance of understanding social traits as influenced by the coevolution of conflicting genomes. © 2012 The Author. Evolution© 2012 The Society for the Study of Evolution.

The Lande-Kirkpatrick mechanism is the null model of evolution by intersexual selection: implications for meaning, honesty, and design in intersexual signals.

PubMed

Prum, Richard O

2010-11-01

The Fisher-inspired, arbitrary intersexual selection models of Lande (1981) and Kirkpatrick (1982), including both stable and unstable equilibrium conditions, provide the appropriate null model for the evolution of traits and preferences by intersexual selection. Like the Hardy–Weinberg equilibrium, the Lande–Kirkpatrick (LK) mechanism arises as an intrinsic consequence of genetic variation in trait and preference in the absence of other evolutionary forces. The LK mechanism is equivalent to other intersexual selection mechanisms in the absence of additional selection on preference and with additional trait-viability and preference-viability correlations equal to zero. The LK null model predicts the evolution of arbitrary display traits that are neither honest nor dishonest, indicate nothing other than mating availability, and lack any meaning or design other than their potential to correspond to mating preferences. The current standard for demonstrating an arbitrary trait is impossible to meet because it requires proof of the null hypothesis. The LK null model makes distinct predictions about the evolvability of traits and preferences. Examples of recent intersexual selection research document the confirmationist pitfalls of lacking a null model. Incorporation of the LK null into intersexual selection will contribute to serious examination of the extent to which natural selection on preferences shapes signals.

TESIS - The TNG EROs Spectroscopic Identification Survey

NASA Astrophysics Data System (ADS)

Saracco, P.; Longhetti, M.; Severgnini, P.; della Ceca, R.; Mannucci, F.; Ghinassi, F.; Drory, N.; Feulner, G.; Bender, R.; Maraston, C.; Hopp, U.

2003-06-01

The epoch at which massive galaxies (M [star] > 10^11M[ scriptstyle sun ]) have assembled provides crucial constraints on the current galaxy formation and evolution models. The LCDM hierarchical merging model predicts that massive galaxies are assembled through mergers of pre-existing disk galaxies at z <= 1.5 (Kauffmann & Charlot 1998; Cole et al. 2000). In the alternative view massive ellipticals formed at z> 3 in a single episode of star formation and follow a pure luminosity evolution (PLE).

The evolution of recombination in a heterogeneous environment.

PubMed Central

Lenormand, T; Otto, S P

2000-01-01

Most models describing the evolution of recombination have focused on the case of a single population, implicitly assuming that all individuals are equally likely to mate and that spatial heterogeneity in selection is absent. In these models, the evolution of recombination is driven by linkage disequilibria generated either by epistatic selection or drift. Models based on epistatic selection show that recombination can be favored if epistasis is negative and weak compared to directional selection and if the recombination modifier locus is tightly linked to the selected loci. In this article, we examine the joint effects of spatial heterogeneity in selection and epistasis on the evolution of recombination. In a model with two patches, each subject to different selection regimes, we consider the cases of mutation-selection and migration-selection balance as well as the spread of beneficial alleles. We find that including spatial heterogeneity extends the range of epistasis over which recombination can be favored. Indeed, recombination can be favored without epistasis, with negative and even with positive epistasis depending on environmental circumstances. The selection pressure acting on recombination-modifier loci is often much stronger with spatial heterogeneity, and even loosely linked modifiers and free linkage may evolve. In each case, predicting whether recombination is favored requires knowledge of both the type of environmental heterogeneity and epistasis, as none of these factors alone is sufficient to predict the outcome. PMID:10978305

The Prediction of Microstructure Evolution of 6005A Aluminum Alloy in a P-ECAP Extrusion Study

NASA Astrophysics Data System (ADS)

Lei, Shi; Jiu-Ba, Wen; Chang, Ren

2018-05-01

Finite element modeling (FEM) was applied for predicting the recrystallized structure in extruded 6005 aluminum alloy, and simulated results were experimentally validated. First, microstructure evolution of 6005 aluminum alloy during deformation was studied by means of isothermal compression test, where the processing parameters were chosen to reproduce the typical industrial conditions. Second, microstructure evolution was analyzed, and the obtained information was used to fit a dynamic recrystallization model implementing inside the DEFORM-3D FEM code environment. FEM of deformation of 6005 aluminum has been established and validated by microstructure comparison. Finally, the obtained dynamic recrystallization model was applied to tube extrusion by using a portholes-equal channel angular pressing die. The finite element analysis results showed that coarse DRX grains occur in the extruded tube at higher temperature and in the extruded tube at the faster speed of the stem. The test results showed material from the front end of the extruded tube has coarse grains (60 μm) and other extruded tube has finer grains (20 μm).

The Prediction of Microstructure Evolution of 6005A Aluminum Alloy in a P-ECAP Extrusion Study

NASA Astrophysics Data System (ADS)

Lei, Shi; Jiu-Ba, Wen; Chang, Ren

2018-04-01

Finite element modeling (FEM) was applied for predicting the recrystallized structure in extruded 6005 aluminum alloy, and simulated results were experimentally validated. First, microstructure evolution of 6005 aluminum alloy during deformation was studied by means of isothermal compression test, where the processing parameters were chosen to reproduce the typical industrial conditions. Second, microstructure evolution was analyzed, and the obtained information was used to fit a dynamic recrystallization model implementing inside the DEFORM-3D FEM code environment. FEM of deformation of 6005 aluminum has been established and validated by microstructure comparison. Finally, the obtained dynamic recrystallization model was applied to tube extrusion by using a portholes-equal channel angular pressing die. The finite element analysis results showed that coarse DRX grains occur in the extruded tube at higher temperature and in the extruded tube at the faster speed of the stem. The test results showed material from the front end of the extruded tube has coarse grains (60 μm) and other extruded tube has finer grains (20 μm).

Failures no More: The Radical Consequences of Realistic Stellar Feedback for Dwarf Galaxies, the Milky Way, and Reionization

NASA Astrophysics Data System (ADS)

Hopkins, Philip F.

2016-06-01

Many of the most fundamental unsolved questions in star and galaxy formation revolve around star formation and "feedback" from massive stars, in-extricably linking galaxy formation and stellar evolution. I'll present simulations with un-precedented resolution of Milky-Way (MW) mass galaxies, followed cosmologically to redshift zero. For the first time, these simulations resolve the internal structure of small dwarf satellites around a MW-like host, with detailed models for stellar evolution including radiation pressure, supernovae, stellar winds, and photo-heating. I'll show that, without fine-tuning, these feedback processes naturally resolve the "missing satellites," "too big to fail," and "cusp-core" problems, and produce realistic galaxy populations. At high redshifts however, the realistic ISM structure predicted, coupled to standard stellar population models, naively leads to the prediction that only ~1-2% of ionizing photons can ever escape galaxies, insufficient to ionize the Universe. But these models assume all stars are single: if we account for binary evolution, the escape fraction increases dramatically to ~20% for the small, low-metallicity galaxies believed to ionize the Universe.

Model of adipose tissue cellularity dynamics during food restriction.

PubMed

Soula, H A; Géloën, A; Soulage, C O

2015-01-07

Adipose tissue and adipocytes play a central role in the pathogenesis of metabolic diseases related to obesity. Size of fat cells depends on the balance of synthesis and mobilization of lipids and can undergo important variations throughout the life of the organism. These variations usually occur when storing and releasing lipids according to energy demand. In particular when confronted to severe food restriction, adipocyte releases its lipid content via a process called lipolysis. We propose a mathematical model that combines cell diameter distribution and lipolytic response to show that lipid release is a surface (radius squared) limited mechanism. Since this size-dependent rate affects the cell׳s shrinkage speed, we are able to predict the cell size distribution evolution when lipolysis is the only factor at work: such as during an important food restriction. Performing recurrent surgical biopsies on rats, we measured the evolution of adipose cell size distribution for the same individual throughout the duration of the food restriction protocol. We show that our microscopic model of size dependent lipid release can predict macroscopic size distribution evolution. Copyright © 2014 Elsevier Ltd. All rights reserved.

The Cosmic Abundance of 3He: Green Bank Telescope Observations

NASA Astrophysics Data System (ADS)

Balser, Dana; Bania, Thomas

2018-01-01

The Big Bang theory for the origin of the Universe predicts that during the first ~1,000 seconds significant amounts of the light elements (2H, 3He, 4He, and 7Li) were produced. Many generations of stellar evolution in the Galaxy modifies these primordial abundances. Observations of the 3He+ hyperfine transition in Galactic HII regions reveals a 3He/H abundance ratio that is constant with Galactocentric radius to within the uncertainties, and is consistent with the primordial value as determined from cosmic microwave background experiments (e.g., WMAP). This "3He Plateau" indicates that the net production and destruction of 3He in stars is approximately zero. Recent stellar evolution models that include thermohaline mixing, however, predict that 3He/H abundance ratios should slightly decrease with Galactocentric radius, or in places in the Galaxy with lower star formation rates. Here we discuss sensitive Green Bank Telescope (GBT) observations of 3He+ at 3.46 cm in a subset of our HII region sample. We develop HII region models and derive accurate 3He/H abundance ratios to better constrain these new stellar evolution models.

Inferring evolution of gene duplicates using probabilistic models and nonparametric belief propagation.

PubMed

Zeng, Jia; Hannenhalli, Sridhar

2013-01-01

Gene duplication, followed by functional evolution of duplicate genes, is a primary engine of evolutionary innovation. In turn, gene expression evolution is a critical component of overall functional evolution of paralogs. Inferring evolutionary history of gene expression among paralogs is therefore a problem of considerable interest. It also represents significant challenges. The standard approaches of evolutionary reconstruction assume that at an internal node of the duplication tree, the two duplicates evolve independently. However, because of various selection pressures functional evolution of the two paralogs may be coupled. The coupling of paralog evolution corresponds to three major fates of gene duplicates: subfunctionalization (SF), conserved function (CF) or neofunctionalization (NF). Quantitative analysis of these fates is of great interest and clearly influences evolutionary inference of expression. These two interrelated problems of inferring gene expression and evolutionary fates of gene duplicates have not been studied together previously and motivate the present study. Here we propose a novel probabilistic framework and algorithm to simultaneously infer (i) ancestral gene expression and (ii) the likely fate (SF, NF, CF) at each duplication event during the evolution of gene family. Using tissue-specific gene expression data, we develop a nonparametric belief propagation (NBP) algorithm to predict the ancestral expression level as a proxy for function, and describe a novel probabilistic model that relates the predicted and known expression levels to the possible evolutionary fates. We validate our model using simulation and then apply it to a genome-wide set of gene duplicates in human. Our results suggest that SF tends to be more frequent at the earlier stage of gene family expansion, while NF occurs more frequently later on.

Primordial lithium and the standard model(s)

NASA Technical Reports Server (NTRS)

Deliyannis, Constantine P.; Demarque, Pierre; Kawaler, Steven D.; Romanelli, Paul; Krauss, Lawrence M.

1989-01-01

The results of new theoretical work on surface Li-7 and Li-6 evolution in the oldest halo stars are presented, along with a new and refined analysis of the predicted primordial Li abundance resulting from big-bang nucleosynthesis. This makes it possible to determine the constraints which can be imposed on cosmology using primordial Li and both standard big-bang and stellar-evolution models. This leads to limits on the baryon density today of 0.0044-0.025 (where the Hubble constant is 100h km/sec Mpc) and imposes limitations on alternative nucleosynthesis scenarios.

Fire feedbacks over geological time and the evolution of atmospheric oxygen concentration

NASA Astrophysics Data System (ADS)

Mills, B.; Belcher, C.; Lenton, T. M.

2017-12-01

During the 4.5 billion year history of the Earth, the concentration of oxygen in the atmosphere has risen from trace levels to today's 21%. Yet over the last 400 million years, O2 concentration appears to have remained within a relatively narrow range (around 15% - 30%), despite dramatic changes in the nature of global biogeochemical cycling. This stability has been crucial for continued animal evolution, and is thought to have arisen through feedbacks between oxygen, wildfire and plant productivity: the strong oxygen- dependence of fire initiation and spread means that global photosynthetic primary productivity is suppressed when oxygen levels are high, and enhanced when levels are low. We present biogeochemical modelling of the long term carbon and oxygen cycles, which aims to capture the operation of the wildfire feedback alongside other key processes. We find that wildfire can effectively stabilize long term oxygen concentrations, but that the nature of this feedback has changed as plant evolution has provided different fuels. Specifically, the evolution of early angiosperms during the Cretaceous period provided new understory fuels that more easily facilitated crown and canopy fires. Adding these dynamics to our model produces a more stable system over long timescales, and the model predicts that oxygen concentration has declined towards the present day - a prediction that is supported by other independent estimates.

Dietary specialization is linked to reduced species durations in North American fossil canids

PubMed Central

Casey, Corinna; Van Valkenburgh, Blaire

2018-01-01

How traits influence species persistence is a fundamental question in ecology, evolution and palaeontology. We test the relationship between dietary traits and both species duration and locality coverage over 40 million years in North American canids, a clade with considerable ecomorphological disparity and a dense fossil record. Because ecomorphological generalization—broad resource use—may enable species to withstand disturbance, we predicted that canids of average size and mesocarnivory would exhibit longer durations and wider distributions than specialized larger or smaller species. Second, because locality coverage might reflect dispersal ability and/or survivability in a range of habitats, we predicted that high coverage would correspond with longer durations. We find a nonlinear relationship between species duration and degree of carnivory: species at either end of the carnivory spectrum tend to have shorter durations than mesocarnivores. Locality coverage shows no relationship with size, diet or duration. To test whether generalization (medium size, mesocarnivory) corresponds to an adaptive optimum, we fit trait evolution models to previously generated canid phylogenies. Our analyses identify no single optimum in size or diet. Instead, the primary model of size evolution is a classic Cope's Rule increase over time, while dietary evolution does not conform to a single model. PMID:29765649

Predictive biophysical modeling and understanding of the dynamics of mRNA translation and its evolution

PubMed Central

Zur, Hadas; Tuller, Tamir

2016-01-01

mRNA translation is the fundamental process of decoding the information encoded in mRNA molecules by the ribosome for the synthesis of proteins. The centrality of this process in various biomedical disciplines such as cell biology, evolution and biotechnology, encouraged the development of dozens of mathematical and computational models of translation in recent years. These models aimed at capturing various biophysical aspects of the process. The objective of this review is to survey these models, focusing on those based and/or validated on real large-scale genomic data. We consider aspects such as the complexity of the models, the biophysical aspects they regard and the predictions they may provide. Furthermore, we survey the central systems biology discoveries reported on their basis. This review demonstrates the fundamental advantages of employing computational biophysical translation models in general, and discusses the relative advantages of the different approaches and the challenges in the field. PMID:27591251

Early bursts of body size and shape evolution are rare in comparative data.

PubMed

Harmon, Luke J; Losos, Jonathan B; Jonathan Davies, T; Gillespie, Rosemary G; Gittleman, John L; Bryan Jennings, W; Kozak, Kenneth H; McPeek, Mark A; Moreno-Roark, Franck; Near, Thomas J; Purvis, Andy; Ricklefs, Robert E; Schluter, Dolph; Schulte Ii, James A; Seehausen, Ole; Sidlauskas, Brian L; Torres-Carvajal, Omar; Weir, Jason T; Mooers, Arne Ø

2010-08-01

George Gaylord Simpson famously postulated that much of life's diversity originated as adaptive radiations-more or less simultaneous divergences of numerous lines from a single ancestral adaptive type. However, identifying adaptive radiations has proven difficult due to a lack of broad-scale comparative datasets. Here, we use phylogenetic comparative data on body size and shape in a diversity of animal clades to test a key model of adaptive radiation, in which initially rapid morphological evolution is followed by relative stasis. We compared the fit of this model to both single selective peak and random walk models. We found little support for the early-burst model of adaptive radiation, whereas both other models, particularly that of selective peaks, were commonly supported. In addition, we found that the net rate of morphological evolution varied inversely with clade age. The youngest clades appear to evolve most rapidly because long-term change typically does not attain the amount of divergence predicted from rates measured over short time scales. Across our entire analysis, the dominant pattern was one of constraints shaping evolution continually through time rather than rapid evolution followed by stasis. We suggest that the classical model of adaptive radiation, where morphological evolution is initially rapid and slows through time, may be rare in comparative data.

Inference of ecological and social drivers of human brain-size evolution.

PubMed

González-Forero, Mauricio; Gardner, Andy

2018-05-01

The human brain is unusually large. It has tripled in size from Australopithecines to modern humans 1 and has become almost six times larger than expected for a placental mammal of human size 2 . Brains incur high metabolic costs 3 and accordingly a long-standing question is why the large human brain has evolved 4 . The leading hypotheses propose benefits of improved cognition for overcoming ecological 5-7 , social 8-10 or cultural 11-14 challenges. However, these hypotheses are typically assessed using correlative analyses, and establishing causes for brain-size evolution remains difficult 15,16 . Here we introduce a metabolic approach that enables causal assessment of social hypotheses for brain-size evolution. Our approach yields quantitative predictions for brain and body size from formalized social hypotheses given empirical estimates of the metabolic costs of the brain. Our model predicts the evolution of adult Homo sapiens-sized brains and bodies when individuals face a combination of 60% ecological, 30% cooperative and 10% between-group competitive challenges, and suggests that between-individual competition has been unimportant for driving human brain-size evolution. Moreover, our model indicates that brain expansion in Homo was driven by ecological rather than social challenges, and was perhaps strongly promoted by culture. Our metabolic approach thus enables causal assessments that refine, refute and unify hypotheses of brain-size evolution.

Forecasting the northern African dust outbreak towards Europe in April 2011: A model intercomparison

DOE PAGES

Huneeus, N.; Basart, S.; Fiedler, S.; ...

2016-04-21

In the framework of the World Meteorological Organisation's Sand and Dust Storm Warning Advisory and Assessment System, we evaluated the predictions of five state-of-the-art dust forecast models during an intense Saharan dust outbreak affecting western and northern Europe in April 2011. We assessed the capacity of the models to predict the evolution of the dust cloud with lead times of up to 72 h using observations of aerosol optical depth (AOD) from the AErosol RObotic NETwork (AERONET) and the Moderate Resolution Imaging Spectroradiometer (MODIS) and dust surface concentrations from a ground-based measurement network. In addition, the predicted vertical dust distributionmore » was evaluated with vertical extinction profiles from the Cloud and Aerosol Lidar with Orthogonal Polarization (CALIOP). To assess the diversity in forecast capability among the models, the analysis was extended to wind field (both surface and profile), synoptic conditions, emissions and deposition fluxes. Models predict the onset and evolution of the AOD for all analysed lead times. On average, differences among the models are larger than differences among lead times for each individual model. In spite of large differences in emission and deposition, the models present comparable skill for AOD. In general, models are better in predicting AOD than near-surface dust concentration over the Iberian Peninsula. Models tend to underestimate the long-range transport towards northern Europe. In this paper, our analysis suggests that this is partly due to difficulties in simulating the vertical distribution dust and horizontal wind. Differences in the size distribution and wet scavenging efficiency may also account for model diversity in long-range transport.« less

Solvable Hydrodynamics of Quantum Integrable Systems

NASA Astrophysics Data System (ADS)

Bulchandani, Vir B.; Vasseur, Romain; Karrasch, Christoph; Moore, Joel E.

2017-12-01

The conventional theory of hydrodynamics describes the evolution in time of chaotic many-particle systems from local to global equilibrium. In a quantum integrable system, local equilibrium is characterized by a local generalized Gibbs ensemble or equivalently a local distribution of pseudomomenta. We study time evolution from local equilibria in such models by solving a certain kinetic equation, the "Bethe-Boltzmann" equation satisfied by the local pseudomomentum density. Explicit comparison with density matrix renormalization group time evolution of a thermal expansion in the XXZ model shows that hydrodynamical predictions from smooth initial conditions can be remarkably accurate, even for small system sizes. Solutions are also obtained in the Lieb-Liniger model for free expansion into vacuum and collisions between clouds of particles, which model experiments on ultracold one-dimensional Bose gases.

Chempy: A flexible chemical evolution model for abundance fitting. Do the Sun's abundances alone constrain chemical evolution models?

NASA Astrophysics Data System (ADS)

Rybizki, Jan; Just, Andreas; Rix, Hans-Walter

2017-09-01

Elemental abundances of stars are the result of the complex enrichment history of their galaxy. Interpretation of observed abundances requires flexible modeling tools to explore and quantify the information about Galactic chemical evolution (GCE) stored in such data. Here we present Chempy, a newly developed code for GCE modeling, representing a parametrized open one-zone model within a Bayesian framework. A Chempy model is specified by a set of five to ten parameters that describe the effective galaxy evolution along with the stellar and star-formation physics: for example, the star-formation history (SFH), the feedback efficiency, the stellar initial mass function (IMF), and the incidence of supernova of type Ia (SN Ia). Unlike established approaches, Chempy can sample the posterior probability distribution in the full model parameter space and test data-model matches for different nucleosynthetic yield sets. It is essentially a chemical evolution fitting tool. We straightforwardly extend Chempy to a multi-zone scheme. As an illustrative application, we show that interesting parameter constraints result from only the ages and elemental abundances of the Sun, Arcturus, and the present-day interstellar medium (ISM). For the first time, we use such information to infer the IMF parameter via GCE modeling, where we properly marginalize over nuisance parameters and account for different yield sets. We find that 11.6+ 2.1-1.6% of the IMF explodes as core-collapse supernova (CC-SN), compatible with Salpeter (1955, ApJ, 121, 161). We also constrain the incidence of SN Ia per 103M⊙ to 0.5-1.4. At the same time, this Chempy application shows persistent discrepancies between predicted and observed abundances for some elements, irrespective of the chosen yield set. These cannot be remedied by any variations of Chempy's parameters and could be an indication of missing nucleosynthetic channels. Chempy could be a powerful tool to confront predictions from stellar nucleosynthesis with far more complex abundance data sets and to refine the physical processes governing the chemical evolution of stellar systems.

Effect of Anisotropic Yield Function Evolution on Estimation of Forming Limit Diagram

NASA Astrophysics Data System (ADS)

Bandyopadhyay, K.; Basak, S.; Choi, H. J.; Panda, S. K.; Lee, M. G.

2017-09-01

In case of theoretical prediction of the FLD, the variations in yield stress and R-values along different material directions, were long been implemented to enhance the accuracy. Although influences of different yield models and hardening laws on formability were well addressed, anisotropic evolution of yield loci under monotonic loading with different deformation modes is yet to be explored. In the present study, Marciniak-Kuckzinsky (M-K) model was modified to incorporate the change in the shape of the initial yield function with evolution due to anisotropic hardening. Swift’s hardening law along with two different anisotropic yield criteria, namely Hill48 and Yld2000-2d were implemented in the model. The Hill48 yield model was applied with non-associated flow rule to comprehend the effect of variations in both yield stress and R-values. The numerically estimated FLDs were validated after comparing with FLD evaluated through experiments. A low carbon steel was selected, and hemispherical punch stretching test was performed for FLD evaluation. Additionally, the numerically estimated FLDs were incorporated in FE simulations to predict limiting dome heights for validation purpose. Other formability performances like strain distributions over the deformed cup surface were validated with experimental results.

Agriculture and groundwater nitrate contamination in the Seine basin. The STICS-MODCOU modelling chain.

PubMed

Ledoux, E; Gomez, E; Monget, J M; Viavattene, C; Viennot, P; Ducharne, A; Benoit, M; Mignolet, C; Schott, C; Mary, B

2007-04-01

A software package is presented here to predict the fate of nitrogen fertilizers and the transport of nitrate from the rooting zone of agricultural areas to surface water and groundwater in the Seine basin, taking into account the long residence times of water and nitrate in the unsaturated and aquifer systems. Information on pedological characteristics, land use and farming practices is used to determine the spatial units to be considered. These data are converted into input data for the crop model STICS which simulates the water and nitrogen balances in the soil-plant system with a daily time-step. A spatial application of STICS has been derived at the catchment scale which computes the water and nitrate fluxes at the bottom of the rooting zone. These fluxes are integrated into a surface and groundwater coupled model MODCOU which calculates the daily water balance in the hydrological system, the flow in the rivers and the piezometric variations in the aquifers, using standard climatic data (rainfall, PET). The transport of nitrate and the evolution of nitrate contamination in groundwater and to rivers is computed by the model NEWSAM. This modelling chain is a valuable tool to predict the evolution of crop productivity and nitrate contamination according to various scenarios modifying farming practices and/or climatic changes. Data for the period 1970-2000 are used to simulate the past evolution of nitrogen contamination. The method has been validated using available data bases of nitrate concentrations in the three main aquifers of the Paris basin (Oligocene, Eocene and chalk). The approach has then been used to predict the future evolution of nitrogen contamination up to 2015. A statistical approach allowed estimating the probability of transgression of different concentration thresholds in various areas in the basin. The model is also used to evaluate the cost of the damage resulting of the treatment of drinking water at the scale of a groundwater management unit in the Seine river basin.

The evolution of the Brewer-Dobson Circulation from 1960-2100 in simulations with the Chemistry Climate Model EMAC

NASA Astrophysics Data System (ADS)

Oberländer, Sophie; Langematz, Ulrike; Kubin, Anne; Abalichin, Janna; Meul, Stefanie; Jöckel, Patrick; Brühl, Christoph

2010-05-01

First results of research performed within the new DFG Research Unit Stratospheric Change and its Role for Climate Prediction (SHARP) will be presented. SHARP investigates past and future changes in stratospheric dynamics and composition to improve the understanding of global climate change and the accuracy of climate change predictions. SHARP combines the efforts of eight German research institutes and expertise in state-of-the-art climate modelling and observations. Within the scope of the scientific sub-project SHARP-BDC (Brewer-Dobson-Circulation) the past and future evolution of the BDC in an atmosphere with changing composition will be analysed. Radiosonde data show an annual mean cooling of the tropical lower stratosphere over the past few decades (Thompson and Solomon, 2005). Several independent model simulations indicate an acceleration of the BDC due to higher greenhouse gas (GHG) concentrations with direct impact on the exchange of air masses between the troposphere and stratosphere (e.g., Butchart et al, 2006). In contrast, from balloon-born measurements no significant acceleration in the BDC could be identified (Engel et al, 2008). This disagreement between observations and model analyses motivates further studies. For the future, expected changes in planetary wave generation and propagation in an atmosphere with increasing GHG concentrations are a major source of uncertainty for predicting future levels of stratospheric composition. To analyse and interpret the past and future evolution of the BDC, results from a transient multi-decadal simulation with the Chemistry-Climate Model (CCM) EMAC will be presented. The model has been integrated from 1960 to 2100 following the SCN2d scenario recommendations of the SPARC CCMVal initiative for the temporal evolution of GHGs, ozone depleting substances and sea surface temperatures as well as sea ice. The role of increasing GHG concentrations for the BDC will be assessed by comparing the SCN2d-results with a ‘non-climate change' (NCC) simulation, in which greenhouse gases have been kept fixed at their 1960 concentrations.

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.

Predicting network modules of cell cycle regulators using relative protein abundance statistics.

PubMed

Oguz, Cihan; Watson, Layne T; Baumann, William T; Tyson, John J

2017-02-28

Parameter estimation in systems biology is typically done by enforcing experimental observations through an objective function as the parameter space of a model is explored by numerical simulations. Past studies have shown that one usually finds a set of "feasible" parameter vectors that fit the available experimental data equally well, and that these alternative vectors can make different predictions under novel experimental conditions. In this study, we characterize the feasible region of a complex model of the budding yeast cell cycle under a large set of discrete experimental constraints in order to test whether the statistical features of relative protein abundance predictions are influenced by the topology of the cell cycle regulatory network. Using differential evolution, we generate an ensemble of feasible parameter vectors that reproduce the phenotypes (viable or inviable) of wild-type yeast cells and 110 mutant strains. We use this ensemble to predict the phenotypes of 129 mutant strains for which experimental data is not available. We identify 86 novel mutants that are predicted to be viable and then rank the cell cycle proteins in terms of their contributions to cumulative variability of relative protein abundance predictions. Proteins involved in "regulation of cell size" and "regulation of G1/S transition" contribute most to predictive variability, whereas proteins involved in "positive regulation of transcription involved in exit from mitosis," "mitotic spindle assembly checkpoint" and "negative regulation of cyclin-dependent protein kinase by cyclin degradation" contribute the least. These results suggest that the statistics of these predictions may be generating patterns specific to individual network modules (START, S/G2/M, and EXIT). To test this hypothesis, we develop random forest models for predicting the network modules of cell cycle regulators using relative abundance statistics as model inputs. Predictive performance is assessed by the areas under receiver operating characteristics curves (AUC). Our models generate an AUC range of 0.83-0.87 as opposed to randomized models with AUC values around 0.50. By using differential evolution and random forest modeling, we show that the model prediction statistics generate distinct network module-specific patterns within the cell cycle network.

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.

A Macroevolutionary Perspective on Multiple Sexual Traits in the Phasianidae (Galliformes)

PubMed Central

Kimball, Rebecca T.; Mary, Colette M. St.; Braun, Edward L.

2011-01-01

Traits involved in sexual signaling are ubiquitous among animals. Although a single trait appears sufficient to convey information, many sexually dimorphic species exhibit multiple sexual signals, which may be costly to signalers and receivers. Given that one signal may be enough, there are many microevolutionary hypotheses to explain the evolution of multiple signals. Here we extend these hypotheses to a macroevolutionary scale and compare those predictions to the patterns of gains and losses of sexual dimorphism in pheasants and partridges. Among nine dimorphic characters, including six intersexual signals and three indicators of competitive ability, all exhibited both gains and losses of dimorphism within the group. Although theories of intersexual selection emphasize gain and elaboration, those six characters exhibited greater rates of loss than gain; in contrast, the competitive traits showed a slight bias towards gains. The available models, when examined in a macroevolutionary framework, did not yield unique predictions, making it difficult to distinguish among them. Even with this limitation, when the predictions of these alternative models were compared with the heterogeneous patterns of evolution of dimorphism in phasianids, it is clear that many different selective processes have been involved in the evolution of sexual signals in this group. PMID:21716735

Selfish evolution of cytonuclear hybrid incompatibility in Mimulus

PubMed Central

Finseth, Findley R.; Barr, Camille M.; Fishman, Lila

2016-01-01

Intraspecific coevolution between selfish elements and suppressors may promote interspecific hybrid incompatibility, but evidence of this process is rare. Here, we use genomic data to test alternative models for the evolution of cytonuclear hybrid male sterility in Mimulus. In hybrids between Iron Mountain (IM) Mimulus guttatus × Mimulus nasutus, two tightly linked M. guttatus alleles (Rf1/Rf2) each restore male fertility by suppressing a local mitochondrial male-sterility gene (IM-CMS). Unlike neutral models for the evolution of hybrid incompatibility loci, selfish evolution predicts that the Rf alleles experienced strong selection in the presence of IM-CMS. Using whole-genome sequences, we compared patterns of population-genetic variation in Rf at IM to a neighbouring population that lacks IM-CMS. Consistent with local selection in the presence of IM-CMS, the Rf region shows elevated FST, high local linkage disequilibrium and a distinct haplotype structure at IM, but not at Cone Peak (CP), suggesting a recent sweep in the presence of IM-CMS. In both populations, Rf2 exhibited lower polymorphism than other regions, but the low-diversity outliers were different between CP and IM. Our results confirm theoretical predictions of ubiquitous cytonuclear conflict in plants and provide a population-genetic mechanism for the evolution of a common form of hybrid incompatibility. PMID:27629037

Selfish evolution of cytonuclear hybrid incompatibility in Mimulus.

PubMed

Case, Andrea L; Finseth, Findley R; Barr, Camille M; Fishman, Lila

2016-09-14

Intraspecific coevolution between selfish elements and suppressors may promote interspecific hybrid incompatibility, but evidence of this process is rare. Here, we use genomic data to test alternative models for the evolution of cytonuclear hybrid male sterility in Mimulus In hybrids between Iron Mountain (IM) Mimulus guttatus × Mimulus nasutus, two tightly linked M. guttatus alleles (Rf1/Rf2) each restore male fertility by suppressing a local mitochondrial male-sterility gene (IM-CMS). Unlike neutral models for the evolution of hybrid incompatibility loci, selfish evolution predicts that the Rf alleles experienced strong selection in the presence of IM-CMS. Using whole-genome sequences, we compared patterns of population-genetic variation in Rf at IM to a neighbouring population that lacks IM-CMS. Consistent with local selection in the presence of IM-CMS, the Rf region shows elevated FST, high local linkage disequilibrium and a distinct haplotype structure at IM, but not at Cone Peak (CP), suggesting a recent sweep in the presence of IM-CMS. In both populations, Rf2 exhibited lower polymorphism than other regions, but the low-diversity outliers were different between CP and IM. Our results confirm theoretical predictions of ubiquitous cytonuclear conflict in plants and provide a population-genetic mechanism for the evolution of a common form of hybrid incompatibility. © 2016 The Author(s).

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.

Mantle convection and the distribution of geochemical reservoirs in the silicate shell of the Earth

NASA Astrophysics Data System (ADS)

Walzer, Uwe; Hendel, Roland

2010-05-01

We present a dynamic 3-D spherical-shell model of mantle convection and the evolution of the chemical reservoirs of the Earth`s silicate shell. Chemical differentiation, convection, stirring and thermal evolution constitute an inseparable dynamic system. Our model is based on the solution of the balance equations of mass, momentum, energy, angular momentum, and four sums of the number of atoms of the pairs 238U-206Pb, 235U-207Pb, 232Th-208Pb, and 40K-40Ar. Similar to the present model, the continental crust of the real Earth was not produced entirely at the start of the evolution but developed episodically in batches [1-7]. The details of the continental distribution of the model are largely stochastic, but the spectral properties are quite similar to the present real Earth. The calculated Figures reveal that the modeled present-day mantle has no chemical stratification but we find a marble-cake structure. If we compare the observational results of the present-day proportion of depleted MORB mantle with the model then we find a similar order of magnitude. The MORB source dominates under the lithosphere. In our model, there are nowhere pure unblended reservoirs in the mantle. It is, however, remarkable that, in spite of 4500 Ma of solid-state mantle convection, certain strong concentrations of distributed chemical reservoirs continue to persist in certain volumes, although without sharp abundance boundaries. We deal with the question of predictable and stochastic portions of the phenomena. Although the convective flow patterns and the chemical differentiation of oceanic plateaus are coupled, the evolution of time-dependent Rayleigh number, Rat , is relatively well predictable and the stochastic parts of the Rat(t)-curves are small. Regarding the juvenile growth rates of the total mass of the continents, predictions are possible only in the first epoch of the evolution. Later on, the distribution of the continental-growth episodes is increasingly stochastic. Independently of the varying individual runs, our model shows that the total mass of the present-day continents is not generated in a single process at the beginning of the thermal evolution of the Earth but in episodically distributed processes in the course of geological time. This is in accord with observation. Finally, we present results regarding the numerical method, implementation, scalability and performance. References [1] Condie, K. C., Episodie continental growth models: Afterthoughts and extensions, Tectonophysics, 322 (2000), 153-162. [2] Davidson, J. P. and Arculus, R. J., The significance of Phanerozoic arc magmatism in generating continental crust, in Evolution and Differentiation of the Continental Crust, edited by M. Brown and T. Rushmer (2006), 135-172, Cambridge Univ. Press, Cambridge, UK. [3] Hofmann, A. W., Sampling mantle heterogeneity through oceanic basalts: Isotopes and trace elements, in Treatise on Geochemistry, Vol. 2: The Mantle and the Core, edited by R. W. Carlson (2003), 61-101, Elsevier, Amsterdam. [4] Rollinson, H., Crustal generation in the Archean, in Evolution and Differentiation of the Continental Crust, edited by M. Brown and T. Rushmer (2006), 173-230, Cambridge Univ. Press, Cambridge, UK: [5] Taylor, S. R. and McLennan, S. M., Planetary Crusts. Their Composition, Origin and Evolution. (2009), 1-378, Cambridge Univ. Press, Cambridge, UK. [6] Walzer, U. and Hendel, R., Mantle convection and evolution with growing continents. J. Geophys. Res. 113 (2008), B09405, doi: 10.1029/2007JB005459 [7] http://www.igw.uni-jena.de/geodyn

Effect of Interfacial Turbulence and Accommodation Coefficient on CFD Predictions of Pressurization and Pressure Control in Cryogenic Storage Tank

NASA Technical Reports Server (NTRS)

Kassemi, Mohammad; Kartuzova, Olga; Hylton, Sonya

2015-01-01

Laminar models agree closely with the pressure evolution and vapor phase temperature stratification but under-predict liquid temperatures. Turbulent SST k-w and k-e models under-predict the pressurization rate and extent of stratification in the vapor but represent liquid temperature distributions fairly well. These conclusions seem to equally apply to large cryogenic tank simulations as well as small scale simulant fluid pressurization cases. Appropriate turbulent models that represent both interfacial and bulk vapor phase turbulence with greater fidelity are needed. Application of LES models to the tank pressurization problem can serve as a starting point.

Evolution of the mating system in colonizing plants.

PubMed

Pannell, John R

2015-05-01

Colonization is likely to be more successful for species with an ability to self-fertilize and thus to establish new populations as single individuals. As a result, self-compatibility should be common among colonizing species. This idea, labelled 'Baker's law', has been influential in discussions of sexual-system and mating-system evolution. However, its generality has been questioned, because models of the evolution of dispersal and the mating system predict an association between high dispersal rates and outcrossing rather than selfing, and because of many apparent counter examples to the law. The contrasting predictions made by models invoking Baker's law versus those for the evolution of the mating system and dispersal urges a reassessment of how we should view both these traits. Here, I review the literature on the evolution of mating and dispersal in colonizing species, with a focus on conceptual issues. I argue for the importance of distinguishing between the selfing or outcrossing rate and a simple ability to self-fertilize, as well as for the need for a more nuanced consideration of dispersal. Colonizing species will be characterized by different phases in their life pattern: dispersal to new habitat, implying an ecological sieve on dispersal traits; establishment and a phase of growth following colonization, implying a sieve on reproductive traits; and a phase of demographic stasis at high density, during which new trait associations can evolve through local adaptation. This dynamic means that the sorting of mating-system and dispersal traits should change over time, making simple predictions difficult. © 2015 John Wiley & Sons Ltd.

Constrains on the South Atlantic Anomaly from Réunion Island

NASA Astrophysics Data System (ADS)

Béguin, A.; de Groot, L. V.

2017-12-01

The South Atlantic Anomaly (SAA) is a region where the geomagnetic field intensity is about half as strong as would be expected from the current geomagnetic dipole moment that arises from geomagnetic field models. Those field models predict a westward movement of the SAA and predicts its origin East of Africa around 1500 AD. The onset and evolution of the SAA, however, are poorly constrained due to a lack of full-vector paleomagnetic data from Africa and the Indian Ocean for the past centuries. Here we present a full-vector paleosecular variation (PSV) curve for Réunion Island (21°S, 55°E) located East the African continent, in the region that currently shows the fastest increase in geomagnetic field strength in contrast to the average global decay. We sampled 27 sites covering the last 700 years, and subjected them to a directional and multi-method paleointensity study. The obtained directional records reveal shallower inclinations and less variation in the declination compared to current geomagnetic field model predictions. Scrutinizing the IZZI-Thellier, Multispecimen, and calibrated pseudo-Thellier results produces a coherent paleointensity record. The predicted intensity trend from the geomagnetic field models generally agrees with the trend in our data, however, the high paleointensities are higher than the models predict, and the low paleointensities are lower than the models. This illustrates the inevitable smoothing inherent to geomagnetic field modelling. We will discuss the constraints on the onset of the SAA that arise from the new full-vector PSV curve for Réunion that we present and the implications for the past and future evolution of this geomagnetic phenomenon.

Wave-ice interaction, observed and modelled

NASA Astrophysics Data System (ADS)

Gemmrich, Johannes

2017-04-01

The need for wide-spread, up-to-date sea state predictions and observations in the emerging ice-free Arctic will further increase as the region will open up to marine operations. Wave models for arctic regions have to capture the additional wave physics associated with wave-ice interactions, and different prediction schemes have to be tested against observations. Here we present examples of spatial wave field parameters obtained from TerraSAR-X StripMap swaths in the southern Beaufort Sea taken as part of the "Arctic Sea State and Boundary Layer DRI". Fetch evolution of the significant wave height and length in open waters, and dominant wave lengths and the high frequency cut-off of the wave spectrum in ice are readily extracted from the SAR (synthetic aperture radar) data. A surprising result is that wave evolution in off-ice wind conditions is more rapidly than the fetch evolution in off-land cases, suggesting seeding of the wave field within the ice-covered region.

Predicting turns in proteins with a unified model.

PubMed

Song, Qi; Li, Tonghua; Cong, Peisheng; Sun, Jiangming; Li, Dapeng; Tang, Shengnan

2012-01-01

Turns are a critical element of the structure of a protein; turns play a crucial role in loops, folds, and interactions. Current prediction methods are well developed for the prediction of individual turn types, including α-turn, β-turn, and γ-turn, etc. However, for further protein structure and function prediction it is necessary to develop a uniform model that can accurately predict all types of turns simultaneously. In this study, we present a novel approach, TurnP, which offers the ability to investigate all the turns in a protein based on a unified model. The main characteristics of TurnP are: (i) using newly exploited features of structural evolution information (secondary structure and shape string of protein) based on structure homologies, (ii) considering all types of turns in a unified model, and (iii) practical capability of accurate prediction of all turns simultaneously for a query. TurnP utilizes predicted secondary structures and predicted shape strings, both of which have greater accuracy, based on innovative technologies which were both developed by our group. Then, sequence and structural evolution features, which are profile of sequence, profile of secondary structures and profile of shape strings are generated by sequence and structure alignment. When TurnP was validated on a non-redundant dataset (4,107 entries) by five-fold cross-validation, we achieved an accuracy of 88.8% and a sensitivity of 71.8%, which exceeded the most state-of-the-art predictors of certain type of turn. Newly determined sequences, the EVA and CASP9 datasets were used as independent tests and the results we achieved were outstanding for turn predictions and confirmed the good performance of TurnP for practical applications.

Predicting Turns in Proteins with a Unified Model

PubMed Central

Song, Qi; Li, Tonghua; Cong, Peisheng; Sun, Jiangming; Li, Dapeng; Tang, Shengnan

2012-01-01

Motivation Turns are a critical element of the structure of a protein; turns play a crucial role in loops, folds, and interactions. Current prediction methods are well developed for the prediction of individual turn types, including α-turn, β-turn, and γ-turn, etc. However, for further protein structure and function prediction it is necessary to develop a uniform model that can accurately predict all types of turns simultaneously. Results In this study, we present a novel approach, TurnP, which offers the ability to investigate all the turns in a protein based on a unified model. The main characteristics of TurnP are: (i) using newly exploited features of structural evolution information (secondary structure and shape string of protein) based on structure homologies, (ii) considering all types of turns in a unified model, and (iii) practical capability of accurate prediction of all turns simultaneously for a query. TurnP utilizes predicted secondary structures and predicted shape strings, both of which have greater accuracy, based on innovative technologies which were both developed by our group. Then, sequence and structural evolution features, which are profile of sequence, profile of secondary structures and profile of shape strings are generated by sequence and structure alignment. When TurnP was validated on a non-redundant dataset (4,107 entries) by five-fold cross-validation, we achieved an accuracy of 88.8% and a sensitivity of 71.8%, which exceeded the most state-of-the-art predictors of certain type of turn. Newly determined sequences, the EVA and CASP9 datasets were used as independent tests and the results we achieved were outstanding for turn predictions and confirmed the good performance of TurnP for practical applications. PMID:23144872

Molecular modeling of the microstructure evolution during carbon fiber processing

NASA Astrophysics Data System (ADS)

Desai, Saaketh; Li, Chunyu; Shen, Tongtong; Strachan, Alejandro

2017-12-01

The rational design of carbon fibers with desired properties requires quantitative relationships between the processing conditions, microstructure, and resulting properties. We developed a molecular model that combines kinetic Monte Carlo and molecular dynamics techniques to predict the microstructure evolution during the processes of carbonization and graphitization of polyacrylonitrile (PAN)-based carbon fibers. The model accurately predicts the cross-sectional microstructure of the fibers with the molecular structure of the stabilized PAN fibers and physics-based chemical reaction rates as the only inputs. The resulting structures exhibit key features observed in electron microcopy studies such as curved graphitic sheets and hairpin structures. In addition, computed X-ray diffraction patterns are in good agreement with experiments. We predict the transverse moduli of the resulting fibers between 1 GPa and 5 GPa, in good agreement with experimental results for high modulus fibers and slightly lower than those of high-strength fibers. The transverse modulus is governed by sliding between graphitic sheets, and the relatively low value for the predicted microstructures can be attributed to their perfect longitudinal texture. Finally, the simulations provide insight into the relationships between chemical kinetics and the final microstructure; we observe that high reaction rates result in porous structures with lower moduli.

A two-phase debris-flow model that includes coupled evolution of volume fractions, granular dilatancy, and pore-fluid pressure

USGS Publications Warehouse

George, David L.; Iverson, Richard M.

2011-01-01

Pore-fluid pressure plays a crucial role in debris flows because it counteracts normal stresses at grain contacts and thereby reduces intergranular friction. Pore-pressure feedback accompanying debris deformation is particularly important during the onset of debrisflow motion, when it can dramatically influence the balance of forces governing downslope acceleration. We consider further effects of this feedback by formulating a new, depth-averaged mathematical model that simulates coupled evolution of granular dilatancy, solid and fluid volume fractions, pore-fluid pressure, and flow depth and velocity during all stages of debris-flow motion. To illustrate implications of the model, we use a finite-volume method to compute one-dimensional motion of a debris flow descending a rigid, uniformly inclined slope, and we compare model predictions with data obtained in large-scale experiments at the USGS debris-flow flume. Predictions for the first 1 s of motion show that increasing pore pressures (due to debris contraction) cause liquefaction that enhances flow acceleration. As acceleration continues, however, debris dilation causes dissipation of pore pressures, and this dissipation helps stabilize debris-flow motion. Our numerical predictions of this process match experimental data reasonably well, but predictions might be improved by accounting for the effects of grain-size segregation.

Galactic chemical evolution in hierarchical formation models

NASA Astrophysics Data System (ADS)

Arrigoni, Matias

2010-10-01

The chemical properties and abundance ratios of galaxies provide important information about their formation histories. Galactic chemical evolution has been modelled in detail within the monolithic collapse scenario. These models have successfully described the abundance distributions in our Galaxy and other spiral discs, as well as the trends of metallicity and abundance ratios observed in early-type galaxies. In the last three decades, however, the paradigm of hierarchical assembly in a Cold Dark Matter (CDM) cosmology has revised the picture of how structure in the Universe forms and evolves. In this scenario, galaxies form when gas radiatively cools and condenses inside dark matter haloes, which themselves follow dissipationless gravitational collapse. The CDM picture has been successful at predicting many observed properties of galaxies (for example, the luminosity and stellar mass function of galaxies, color-magnitude or star formation rate vs. stellar mass distributions, relative numbers of early and late-type galaxies, gas fractions and size distributions of spiral galaxies, and the global star formation history), though many potential problems and open questions remain. It is therefore interesting to see whether chemical evolution models, when implemented within this modern cosmological context, are able to correctly predict the observed chemical properties of galaxies. With the advent of more powerfull telescopes and detectors, precise observations of chemical abundances and abundance ratios in various phases (stellar, ISM, ICM) offer the opportunity to obtain strong constraints on galaxy formation histories and the physics that shapes them. However, in order to take advantage of these observations, it is necessary to implement detailed modeling of chemical evolution into a modern cosmological model of hierarchical assembly.

A mechano-biological model of multi-tissue evolution in bone

NASA Astrophysics Data System (ADS)

Frame, Jamie; Rohan, Pierre-Yves; Corté, Laurent; Allena, Rachele

2017-12-01

Successfully simulating tissue evolution in bone is of significant importance in predicting various biological processes such as bone remodeling, fracture healing and osseointegration of implants. Each of these processes involves in different ways the permanent or transient formation of different tissue types, namely bone, cartilage and fibrous tissues. The tissue evolution in specific circumstances such as bone remodeling and fracturing healing is currently able to be modeled. Nevertheless, it remains challenging to predict which tissue types and organization can develop without any a priori assumptions. In particular, the role of mechano-biological coupling in this selective tissue evolution has not been clearly elucidated. In this work, a multi-tissue model has been created which simultaneously describes the evolution of bone, cartilage and fibrous tissues. The coupling of the biological and mechanical factors involved in tissue formation has been modeled by defining two different tissue states: an immature state corresponding to the early stages of tissue growth and representing cell clusters in a weakly neo-formed Extra Cellular Matrix (ECM), and a mature state corresponding to well-formed connective tissues. This has allowed for the cellular processes of migration, proliferation and apoptosis to be described simultaneously with the changing ECM properties through strain driven diffusion, growth, maturation and resorption terms. A series of finite element simulations were carried out on idealized cantilever bending geometries. Starting from a tissue composition replicating a mid-diaphysis section of a long bone, a steady-state tissue formation was reached over a statically loaded period of 10,000 h (60 weeks). The results demonstrated that bone formation occurred in regions which are optimally physiologically strained. In two additional 1000 h bending simulations both cartilaginous and fibrous tissues were shown to form under specific geometrical and loading cases and cartilage was shown to lead to the formation of bone in a beam replicating a fracture healing initial tissue distribution. This finding is encouraging in that it is corroborated by similar experimental observations of cartilage leading bone formation during the fracture healing process. The results of this work demonstrate that a multi-tissue mechano-biological model of tissue evolution has the potential for predictive analysis in the design and implementations of implants, describing fracture healing and bone remodeling processes.

Mutation predicts 40 million years of fly wing evolution.

PubMed

Houle, David; Bolstad, Geir H; van der Linde, Kim; Hansen, Thomas F

2017-08-24

Mutation enables evolution, but the idea that adaptation is also shaped by mutational variation is controversial. Simple evolutionary hypotheses predict such a relationship if the supply of mutations constrains evolution, but it is not clear that constraints exist, and, even if they do, they may be overcome by long-term natural selection. Quantification of the relationship between mutation and phenotypic divergence among species will help to resolve these issues. Here we use precise data on over 50,000 Drosophilid fly wings to demonstrate unexpectedly strong positive relationships between variation produced by mutation, standing genetic variation, and the rate of evolution over the last 40 million years. Our results are inconsistent with simple constraint hypotheses because the rate of evolution is very low relative to what both mutational and standing variation could allow. In principle, the constraint hypothesis could be rescued if the vast majority of mutations are so deleterious that they cannot contribute to evolution, but this also requires the implausible assumption that deleterious mutations have the same pattern of effects as potentially advantageous ones. Our evidence for a strong relationship between mutation and divergence in a slowly evolving structure challenges the existing models of mutation in evolution.

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.

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.

A group evolving-based framework with perturbations for link prediction

NASA Astrophysics Data System (ADS)

Si, Cuiqi; Jiao, Licheng; Wu, Jianshe; Zhao, Jin

2017-06-01

Link prediction is a ubiquitous application in many fields which uses partially observed information to predict absence or presence of links between node pairs. The group evolving study provides reasonable explanations on the behaviors of nodes, relations between nodes and community formation in a network. Possible events in group evolution include continuing, growing, splitting, forming and so on. The changes discovered in networks are to some extent the result of these events. In this work, we present a group evolving-based characterization of node's behavioral patterns, and via which we can estimate the probability they tend to interact. In general, the primary aim of this paper is to offer a minimal toy model to detect missing links based on evolution of groups and give a simpler explanation on the rationality of the model. We first introduce perturbations into networks to obtain stable cluster structures, and the stable clusters determine the stability of each node. Then fluctuations, another node behavior, are assumed by the participation of each node to its own belonging group. Finally, we demonstrate that such characteristics allow us to predict link existence and propose a model for link prediction which outperforms many classical methods with a decreasing computational time in large scales. Encouraging experimental results obtained on real networks show that our approach can effectively predict missing links in network, and even when nearly 40% of the edges are missing, it also retains stationary performance.

An innovative approach to predict technology evolution for the desoldering of printed circuit boards: A perspective from China and America.

PubMed

Wang, Chen; Zhao, Wu; Wang, Jie; Chen, Ling; Luo, Chun-Jing

2016-06-01

The printed circuit boards basis of electronic equipment have seen a rapid growth in recent years and played a significant role in modern life. Nowadays, the fact that electronic devices upgrade quickly necessitates a proper management of waste printed circuit boards. Non-destructive desoldering of waste printed circuit boards becomes the first and the most crucial step towards recycling electronic components. Owing to the diversity of materials and components, the separation process is difficult, which results in complex and expensive recovery of precious materials and electronic components from waste printed circuit boards. To cope with this problem, we proposed an innovative approach integrating Theory of Inventive Problem Solving (TRIZ) evolution theory and technology maturity mapping system to forecast the evolution trends of desoldering technology of waste printed circuit boards. This approach can be applied to analyse the technology evolution, as well as desoldering technology evolution, then research and development strategy and evolution laws can be recommended. As an example, the maturity of desoldering technology is analysed with a technology maturity mapping system model. What is more, desoldering methods in different stages are analysed and compared. According to the analysis, the technological evolution trends are predicted to be 'the law of energy conductivity' and 'increasing the degree of idealisation'. And the potential technology and evolutionary state of waste printed circuit boards are predicted, offering reference for future waste printed circuit boards recycling. © The Author(s) 2016.

Origin and Functional Prediction of Pollen Allergens in Plants1[OPEN

PubMed Central

Chen, Miaolin; Xu, Jie; Ren, Kang; Searle, Iain

2016-01-01

Pollen allergies have long been a major pandemic health problem for human. However, the evolutionary events and biological function of pollen allergens in plants remain largely unknown. Here, we report the genome-wide prediction of pollen allergens and their biological function in the dicotyledonous model plant Arabidopsis (Arabidopsis thaliana) and the monocotyledonous model plant rice (Oryza sativa). In total, 145 and 107 pollen allergens were predicted from rice and Arabidopsis, respectively. These pollen allergens are putatively involved in stress responses and metabolic processes such as cell wall metabolism during pollen development. Interestingly, these putative pollen allergen genes were derived from large gene families and became diversified during evolution. Sequence analysis across 25 plant species from green alga to angiosperms suggest that about 40% of putative pollen allergenic proteins existed in both lower and higher plants, while other allergens emerged during evolution. Although a high proportion of gene duplication has been observed among allergen-coding genes, our data show that these genes might have undergone purifying selection during evolution. We also observed that epitopes of an allergen might have a biological function, as revealed by comprehensive analysis of two known allergens, expansin and profilin. This implies a crucial role of conserved amino acid residues in both in planta biological function and allergenicity. Finally, a model explaining how pollen allergens were generated and maintained in plants is proposed. Prediction and systematic analysis of pollen allergens in model plants suggest that pollen allergens were evolved by gene duplication and then functional specification. This study provides insight into the phylogenetic and evolutionary scenario of pollen allergens that will be helpful to future characterization and epitope screening of pollen allergens. PMID:27436829

Origin and Functional Prediction of Pollen Allergens in Plants.

PubMed

Chen, Miaolin; Xu, Jie; Devis, Deborah; Shi, Jianxin; Ren, Kang; Searle, Iain; Zhang, Dabing

2016-09-01

Pollen allergies have long been a major pandemic health problem for human. However, the evolutionary events and biological function of pollen allergens in plants remain largely unknown. Here, we report the genome-wide prediction of pollen allergens and their biological function in the dicotyledonous model plant Arabidopsis (Arabidopsis thaliana) and the monocotyledonous model plant rice (Oryza sativa). In total, 145 and 107 pollen allergens were predicted from rice and Arabidopsis, respectively. These pollen allergens are putatively involved in stress responses and metabolic processes such as cell wall metabolism during pollen development. Interestingly, these putative pollen allergen genes were derived from large gene families and became diversified during evolution. Sequence analysis across 25 plant species from green alga to angiosperms suggest that about 40% of putative pollen allergenic proteins existed in both lower and higher plants, while other allergens emerged during evolution. Although a high proportion of gene duplication has been observed among allergen-coding genes, our data show that these genes might have undergone purifying selection during evolution. We also observed that epitopes of an allergen might have a biological function, as revealed by comprehensive analysis of two known allergens, expansin and profilin. This implies a crucial role of conserved amino acid residues in both in planta biological function and allergenicity. Finally, a model explaining how pollen allergens were generated and maintained in plants is proposed. Prediction and systematic analysis of pollen allergens in model plants suggest that pollen allergens were evolved by gene duplication and then functional specification. This study provides insight into the phylogenetic and evolutionary scenario of pollen allergens that will be helpful to future characterization and epitope screening of pollen allergens. © 2016 American Society of Plant Biologists. All rights reserved.

Limit of Predictability in Mantle Convection

NASA Astrophysics Data System (ADS)

Bello, L.; Coltice, N.; Rolf, T.; Tackley, P. J.

2013-12-01

Linking mantle convection models with Earth's tectonic history has received considerable attention in recent years: modeling the evolution of supercontinent cycles, predicting present-day mantle structure or improving plate reconstructions. Predictions of future supercontinents are currently being made based on seismic tomography images, plate motion history and mantle convection models, and methods of data assimilation for mantle flow are developing. However, so far there are no studies of the limit of predictability these models are facing. Indeed, given the chaotic nature of mantle convection, we can expect forecasts and hindcasts to have a limited range of predictability. We propose here to use an approach similar to those used in dynamic meteorology, and more recently for the geodynamo, to evaluate the predictability limit of mantle dynamics forecasts. Following the pioneering works in weather forecast (Lorenz 1965), we study the time evolution of twin experiments, started from two very close initial temperature fields and monitor the error growth. We extract a characteristic time of the system, known as the e-folding timescale, which will be used to estimate the predictability limit. The final predictability time will depend on the imposed initial error and the error tolerance in our model. We compute 3D spherical convection solutions using StagYY (Tackley, 2008). We first evaluate the influence of the Rayleigh number on the limit of predictability of isoviscous convection. Then, we investigate the effects of various rheologies, from the simplest (isoviscous mantle) to more complex ones (plate-like behavior and floating continents). We show that the e-folding time increases with the wavelength of the flow and reaches 10Myrs with plate-like behavior and continents. Such an e-folding time together with the uncertainties in mantle temperature distribution suggests prediction of mantle structure from an initial given state is limited to <50 Myrs. References: 1. Lorenz, B. E. N., Norake, D. & Meteorologiake, I. A study of the predictability of a 28-variable atmospheric model. Tellus XXVII, 322-333 (1965). 2. Tackley, P. J. Modelling compressible mantle convection with large viscosity contrasts in a three-dimensional spherical shell using the yin-yang grid. Physics of the Earth and Planetary Interiors 171, 7-18 (2008).

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.

The Fast Debris Evolution Model

NASA Astrophysics Data System (ADS)

Lewis, Hugh G.; Swinerd, Graham; Newland, Rebecca; Saunders, Arrun

The ‘Particles-in-a-box' (PIB) model introduced by Talent (1992) removed the need for computerintensive Monte Carlo simulation to predict the gross characteristics of an evolving debris environment. The PIB model was described using a differential equation that allows the stability of the low Earth orbit (LEO) environment to be tested by a straightforward analysis of the equation's coefficients. As part of an ongoing research effort to investigate more efficient approaches to evolutionary modelling and to develop a suite of educational tools, a new PIB model has been developed. The model, entitled Fast Debris Evolution (FaDE), employs a first-order differential equation to describe the rate at which new objects (˜ 10 cm) are added and removed from the environment. Whilst Talent (1992) based the collision theory for the PIB approach on collisions between gas particles and adopted specific values for the parameters of the model from a number of references, the form and coefficients of the FaDE model equations can be inferred from the outputs of future projections produced by high-fidelity models, such as the DAMAGE model. The FaDE model has been implemented as a client-side, web-based service using Javascript embedded within a HTML document. Due to the simple nature of the algorithm, FaDE can deliver the results of future projections immediately in a graphical format, with complete user-control over key simulation parameters. Historical and future projections for the ˜ 10 cm low Earth orbit (LEO) debris environment under a variety of different scenarios are possible, including business as usual, no future launches, post-mission disposal and remediation. A selection of results is presented with comparisons with predictions made using the DAMAGE environment model. The results demonstrate that the FaDE model is able to capture comparable time-series of collisions and number of objects as predicted by DAMAGE in several scenarios. Further, and perhaps more importantly, its speed and flexibility allows the user to explore and understand the evolution of the space debris environment.

A multisensor evaluation of the asymmetric convective model, version 2, in southeast Texas.

PubMed

Kolling, Jenna S; Pleim, Jonathan E; Jeffries, Harvey E; Vizuete, William

2013-01-01

There currently exist a number of planetary boundary layer (PBL) schemes that can represent the effects of turbulence in daytime convective conditions, although these schemes remain a large source of uncertainty in meteorology and air quality model simulations. This study evaluates a recently developed combined local and nonlocal closure PBL scheme, the Asymmetric Convective Model, version 2 (ACM2), against PBL observations taken from radar wind profilers, a ground-based lidar, and multiple daytime radiosonde balloon launches. These observations were compared against predictions of PBLs from the Weather Research and Forecasting (WRF) model version 3.1 with the ACM2 PBL scheme option, and the Fifth-Generation Meteorological Model (MM5) version 3.7.3 with the Eta PBL scheme option that is currently being used to develop ozone control strategies in southeast Texas. MM5 and WRF predictions during the regulatory modeling episode were evaluated on their ability to predict the rise and fall of the PBL during daytime convective conditions across southeastern Texas. The MM5 predicted PBLs consistently underpredicted observations, and were also less than the WRF PBL predictions. The analysis reveals that the MM5 predicted a slower rising and shallower PBL not representative of the daytime urban boundary layer. Alternatively, the WRF model predicted a more accurate PBL evolution improving the root mean square error (RMSE), both temporally and spatially. The WRF model also more accurately predicted vertical profiles of temperature and moisture in the lowest 3 km of the atmosphere. Inspection of median surface temperature and moisture time-series plots revealed higher predicted surface temperatures in WRF and more surface moisture in MM5. These could not be attributed to surface heat fluxes, and thus the differences in performance of the WRF and MM5 models are likely due to the PBL schemes. An accurate depiction of the diurnal evolution of the planetary boundary layer (PBL) is necessary for realistic air quality simulations, and for formulating effective policy. The meteorological model used to support the southeast Texas 03 attainment demonstration made predictions of the PBL that were consistently less than those found in observations. The use of the Asymmetric Convective Model, version 2 (ACM2), predicted taller PBL heights and improved model predictions. A lower predicted PBL height in an air quality model would increase precursor concentrations and change the chemical production of O3 and possibly the response to control strategies.

Modelling of the physico-chemical behaviour of clay minerals with a thermo-kinetic model taking into account particles morphology in compacted material.

NASA Astrophysics Data System (ADS)

Sali, D.; Fritz, B.; Clément, C.; Michau, N.

2003-04-01

Modelling of fluid-mineral interactions is largely used in Earth Sciences studies to better understand the involved physicochemical processes and their long-term effect on the materials behaviour. Numerical models simplify the processes but try to preserve their main characteristics. Therefore the modelling results strongly depend on the data quality describing initial physicochemical conditions for rock materials, fluids and gases, and on the realistic way of processes representations. The current geo-chemical models do not well take into account rock porosity and permeability and the particle morphology of clay minerals. In compacted materials like those considered as barriers in waste repositories, low permeability rocks like mudstones or compacted powders will be used : they contain mainly fine particles and the geochemical models used for predicting their interactions with fluids tend to misjudge their surface areas, which are fundamental parameters in kinetic modelling. The purpose of this study was to improve how to take into account the particles morphology in the thermo-kinetic code KINDIS and the reactive transport code KIRMAT. A new function was integrated in these codes, considering the reaction surface area as a volume depending parameter and the calculated evolution of the mass balance in the system was coupled with the evolution of reactive surface areas. We made application exercises for numerical validation of these new versions of the codes and the results were compared with those of the pre-existing thermo-kinetic code KINDIS. Several points are highlighted. Taking into account reactive surface area evolution during simulation modifies the predicted mass transfers related to fluid-minerals interactions. Different secondary mineral phases are also observed during modelling. The evolution of the reactive surface parameter helps to solve the competition effects between different phases present in the system which are all able to fix the chemical elements mobilised by the water-minerals interaction processes. To validate our model we simulated the compacted bentonite (MX80) studied for engineered barriers for radioactive waste confinement and mainly composed of Na-Ca-montmorillonite. The study of particles morphology and reactive surfaces evolutions reveals that aqueous ions have a complex behaviour, especially when competitions between various mineral phases occur. In that case, our model predicts a preferential precipitation of finest particles, favouring smectites instead of zeolites. This work is a part of a PhD Thesis supported by Andra, the French Radioactive Waste Management Agency.

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.                   

A Channel Network Evolution Model with Subsurface Saturation Mechanism and Analysis of the Chaotic Behavior of the Model

DTIC Science & Technology

1990-09-01

between basin shapes and hydrologic responses is fundamental for the purpose of hydrologic predictions , especially in ungaged basins. Another goal is...47] studied this model and showed analitically how very small differences in the c field generated completely different leaf vein network structures... predictability impossible. Complexity is by no means a requirement in order for a system to exhibit SIC. A system as simple as the logistic equation x,,,,=ax,,(l

Computational modelling of large deformations in layered-silicate/PET nanocomposites near the glass transition

NASA Astrophysics Data System (ADS)

Figiel, Łukasz; Dunne, Fionn P. E.; Buckley, C. Paul

2010-01-01

Layered-silicate nanoparticles offer a cost-effective reinforcement for thermoplastics. Computational modelling has been employed to study large deformations in layered-silicate/poly(ethylene terephthalate) (PET) nanocomposites near the glass transition, as would be experienced during industrial forming processes such as thermoforming or injection stretch blow moulding. Non-linear numerical modelling was applied, to predict the macroscopic large deformation behaviour, with morphology evolution and deformation occurring at the microscopic level, using the representative volume element (RVE) approach. A physically based elasto-viscoplastic constitutive model, describing the behaviour of the PET matrix within the RVE, was numerically implemented into a finite element solver (ABAQUS) using an UMAT subroutine. The implementation was designed to be robust, for accommodating large rotations and stretches of the matrix local to, and between, the nanoparticles. The nanocomposite morphology was reconstructed at the RVE level using a Monte-Carlo-based algorithm that placed straight, high-aspect ratio particles according to the specified orientation and volume fraction, with the assumption of periodicity. Computational experiments using this methodology enabled prediction of the strain-stiffening behaviour of the nanocomposite, observed experimentally, as functions of strain, strain rate, temperature and particle volume fraction. These results revealed the probable origins of the enhanced strain stiffening observed: (a) evolution of the morphology (through particle re-orientation) and (b) early onset of stress-induced pre-crystallization (and hence lock-up of viscous flow), triggered by the presence of particles. The computational model enabled prediction of the effects of process parameters (strain rate, temperature) on evolution of the morphology, and hence on the end-use properties.

Resource-driven changes to host population stability alter the evolution of virulence and transmission.

PubMed

Hite, Jessica L; Cressler, Clayton E

2018-05-05

What drives the evolution of parasite life-history traits? Recent studies suggest that linking within- and between-host processes can provide key insight into both disease dynamics and parasite evolution. Still, it remains difficult to understand how to pinpoint the critical factors connecting these cross-scale feedbacks, particularly under non-equilibrium conditions; many natural host populations inherently fluctuate and parasites themselves can strongly alter the stability of host populations. Here, we develop a general model framework that mechanistically links resources to parasite evolution across a gradient of stable and unstable conditions. First, we dynamically link resources and between-host processes (host density, stability, transmission) to virulence evolution, using a 'non-nested' model. Then, we consider a 'nested' model where population-level processes (transmission and virulence) depend on resource-driven changes to individual-level (within-host) processes (energetics, immune function, parasite production). Contrary to 'non-nested' model predictions, the 'nested' model reveals complex effects of host population dynamics on parasite evolution, including regions of evolutionary bistability; evolution can push parasites towards strongly or weakly stabilizing strategies. This bistability results from dynamic feedbacks between resource-driven changes to host density, host immune function and parasite production. Together, these results highlight how cross-scale feedbacks can provide key insights into the structuring role of parasites and parasite evolution.This article is part of the theme issue 'Anthropogenic resource subsidies and host-parasite dynamics in wildlife'. © 2018 The Author(s).

State-space prediction model for chaotic time series

NASA Astrophysics Data System (ADS)

Alparslan, A. K.; Sayar, M.; Atilgan, A. R.

1998-08-01

A simple method for predicting the continuation of scalar chaotic time series ahead in time is proposed. The false nearest neighbors technique in connection with the time-delayed embedding is employed so as to reconstruct the state space. A local forecasting model based upon the time evolution of the topological neighboring in the reconstructed phase space is suggested. A moving root-mean-square error is utilized in order to monitor the error along the prediction horizon. The model is tested for the convection amplitude of the Lorenz model. The results indicate that for approximately 100 cycles of the training data, the prediction follows the actual continuation very closely about six cycles. The proposed model, like other state-space forecasting models, captures the long-term behavior of the system due to the use of spatial neighbors in the state space.

The Primordial Entropy of Jupiter

NASA Astrophysics Data System (ADS)

Cumming, Andrew; Helled, Ravit; Venturini, Julia

2018-04-01

The formation history of giant planets determines their primordial structure and consequent evolution. We simulate various formation paths of Jupiter to determine its primordial entropy, and find that a common outcome is for proto-Jupiter to have non-convective regions in its interior. We use planet formation models to calculate how the entropy and post-formation luminosity depend on model properties such as the solid accretion rate and opacity, and show that the gas accretion rate and its time evolution play a key role in determining the entropy profile. The predicted luminosity of Jupiter shortly after formation varies by a factor of 2-3 for different choices of model parameters. We find that entropy gradients inside Jupiter persist for ˜10 Myr after formation. We suggest that these gradients should be considered together with heavy-element composition gradients when modeling Jupiter's evolution and internal structure.

The primordial entropy of Jupiter

NASA Astrophysics Data System (ADS)

Cumming, Andrew; Helled, Ravit; Venturini, Julia

2018-07-01

The formation history of giant planets determines their primordial structure and consequent evolution. We simulate various formation paths of Jupiter to determine its primordial entropy, and find that a common outcome is for proto-Jupiter to have non-convective regions in its interior. We use planet formation models to calculate how the entropy and post-formation luminosity depend on model properties such as the solid accretion rate and opacity, and show that the gas accretion rate and its time evolution play a key role in determining the entropy profile. The predicted luminosity of Jupiter shortly after formation varies by a factor of 2-3 for different choices of model parameters. We find that entropy gradients inside Jupiter persist for ˜10 Myr after formation. We suggest that these gradients should be considered together with heavy-element composition gradients when modelling Jupiter's evolution and internal structure.

Discovering mechanisms relevant for radiation damage evolution

DOE PAGES

Uberuaga, Blas Pedro; Martinez, Enrique Saez; Perez, Danny; ...

2018-02-22

he response of a material to irradiation is a consequence of the kinetic evolution of defects produced during energetic damage events. Thus, accurate predictions of radiation damage evolution require knowing the atomic scale mechanisms associated with those defects. Atomistic simulations are a key tool in providing insight into the types of mechanisms possible. Further, by extending the time scale beyond what is achievable with conventional molecular dynamics, even greater insight can be obtained. Here, we provide examples in which such simulations have revealed new kinetic mechanisms that were not obvious before performing the simulations. We also demonstrate, through the couplingmore » with higher level models, how those mechanisms impact experimental observables in irradiated materials. Lastly, we discuss the importance of these types of simulations in the context of predicting material behavior.« less

Discovering mechanisms relevant for radiation damage evolution

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

Uberuaga, Blas Pedro; Martinez, Enrique Saez; Perez, Danny

he response of a material to irradiation is a consequence of the kinetic evolution of defects produced during energetic damage events. Thus, accurate predictions of radiation damage evolution require knowing the atomic scale mechanisms associated with those defects. Atomistic simulations are a key tool in providing insight into the types of mechanisms possible. Further, by extending the time scale beyond what is achievable with conventional molecular dynamics, even greater insight can be obtained. Here, we provide examples in which such simulations have revealed new kinetic mechanisms that were not obvious before performing the simulations. We also demonstrate, through the couplingmore » with higher level models, how those mechanisms impact experimental observables in irradiated materials. Lastly, we discuss the importance of these types of simulations in the context of predicting material behavior.« less

Hyperextended Cosmological Perturbation Theory: Predicting Nonlinear Clustering Amplitudes

NASA Astrophysics Data System (ADS)

Scoccimarro, Román; Frieman, Joshua A.

1999-07-01

We consider the long-standing problem of predicting the hierarchical clustering amplitudes Sp in the strongly nonlinear regime of gravitational evolution. N-body results for the nonlinear evolution of the bispectrum (the Fourier transform of the three-point density correlation function) suggest a physically motivated Ansatz that yields the strongly nonlinear behavior of the skewness, S3, starting from leading-order perturbation theory. When generalized to higher order (p>3) polyspectra or correlation functions, this Ansatz leads to a good description of nonlinear amplitudes in the strongly nonlinear regime for both scale-free and cold dark matter models. Furthermore, these results allow us to provide a general fitting formula for the nonlinear evolution of the bispectrum that interpolates between the weakly and strongly nonlinear regimes, analogous to previous expressions for the power spectrum.

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.

Application of a Reduced Order Kalman Filter to Initialize a Coupled Atmosphere-Ocean Model: Impact on the Prediction of El Nino

NASA Technical Reports Server (NTRS)

Ballabrera-Poy, J.; Busalacchi, A.; Murtugudde, R.

2000-01-01

A reduced order Kalman Filter, based on a simplification of the Singular Evolutive Extended Kalman (SEEK) filter equations, is used to assimilate observed fields of the surface wind stress, sea surface temperature and sea level into the nonlinear coupled ocean-atmosphere model of Zebiak and Cane. The SEEK filter projects the Kalman Filter equations onto a subspace defined by the eigenvalue decomposition of the error forecast matrix, allowing its application to high dimensional systems. The Zebiak and Cane model couples a linear reduced gravity ocean model with a single vertical mode atmospheric model of Zebiak. The compatibility between the simplified physics of the model and each observed variable is studied separately and together. The results show the ability of the model to represent the simultaneous value of the wind stress, SST and sea level, when the fields are limited to the latitude band 10 deg S - 10 deg N In this first application of the Kalman Filter to a coupled ocean-atmosphere prediction model, the sea level fields are assimilated in terms of the Kelvin and Rossby modes of the thermocline depth anomaly. An estimation of the error of these modes is derived from the projection of an estimation of the sea level error over such modes. This method gives a value of 12 for the error of the Kelvin amplitude, and 6 m of error for the Rossby component of the thermocline depth. The ability of the method to reconstruct the state of the equatorial Pacific and predict its time evolution is demonstrated. The method is shown to be quite robust for predictions up to six months, and able to predict the onset of the 1997 warm event fifteen months before its occurrence.

Application of a Reduced Order Kalman Filter to Initialize a Coupled Atmosphere-Ocean Model: Impact on the Prediction of El Nino

NASA Technical Reports Server (NTRS)

Ballabrera-Poy, Joaquim; Busalacchi, Antonio J.; Murtugudde, Ragu

2000-01-01

A reduced order Kalman Filter, based on a simplification of the Singular Evolutive Extended Kalman (SEEK) filter equations, is used to assimilate observed fields of the surface wind stress, sea surface temperature and sea level into the nonlinear coupled ocean-atmosphere model. The SEEK filter projects the Kalman Filter equations onto a subspace defined by the eigenvalue decomposition of the error forecast matrix, allowing its application to high dimensional systems. The Zebiak and Cane model couples a linear reduced gravity ocean model with a single vertical mode atmospheric model of Zebiak. The compatibility between the simplified physics of the model and each observed variable is studied separately and together. The results show the ability of the model to represent the simultaneous value of the wind stress, SST and sea level, when the fields are limited to the latitude band 10 deg S - 10 deg N. In this first application of the Kalman Filter to a coupled ocean-atmosphere prediction model, the sea level fields are assimilated in terms of the Kelvin and Rossby modes of the thermocline depth anomaly. An estimation of the error of these modes is derived from the projection of an estimation of the sea level error over such modes. This method gives a value of 12 for the error of the Kelvin amplitude, and 6 m of error for the Rossby component of the thermocline depth. The ability of the method to reconstruct the state of the equatorial Pacific and predict its time evolution is demonstrated. The method is shown to be quite robust for predictions I up to six months, and able to predict the onset of the 1997 warm event fifteen months before its occurrence.

Applications of statistical physics to technology price evolution

NASA Astrophysics Data System (ADS)

McNerney, James

Understanding how changing technology affects the prices of goods is a problem with both rich phenomenology and important policy consequences. Using methods from statistical physics, I model technology-driven price evolution. First, I examine a model for the price evolution of individual technologies. The price of a good often follows a power law equation when plotted against its cumulative production. This observation turns out to have significant consequences for technology policy aimed at mitigating climate change, where technologies are needed that achieve low carbon emissions at low cost. However, no theory adequately explains why technology prices follow power laws. To understand this behavior, I simplify an existing model that treats technologies as machines composed of interacting components. I find that the power law exponent of the price trajectory is inversely related to the number of interactions per component. I extend the model to allow for more realistic component interactions and make a testable prediction. Next, I conduct a case-study on the cost evolution of coal-fired electricity. I derive the cost in terms of various physical and economic components. The results suggest that commodities and technologies fall into distinct classes of price models, with commodities following martingales, and technologies following exponentials in time or power laws in cumulative production. I then examine the network of money flows between industries. This work is a precursor to studying the simultaneous evolution of multiple technologies. Economies resemble large machines, with different industries acting as interacting components with specialized functions. To begin studying the structure of these machines, I examine 20 economies with an emphasis on finding common features to serve as targets for statistical physics models. I find they share the same money flow and industry size distributions. I apply methods from statistical physics to show that industries cluster the same way according to industry type. Finally, I use these industry money flows to model the price evolution of many goods simultaneously, where network effects become important. I derive a prediction for which goods tend to improve most rapidly. The fastest-improving goods are those with the highest mean path lengths in the money flow network.

New battery model considering thermal transport and partial charge stationary effects in photovoltaic off-grid applications

NASA Astrophysics Data System (ADS)

Sanz-Gorrachategui, Iván; Bernal, Carlos; Oyarbide, Estanis; Garayalde, Erik; Aizpuru, Iosu; Canales, Jose María; Bono-Nuez, Antonio

2018-02-01

The optimization of the battery pack in an off-grid Photovoltaic application must consider the minimum sizing that assures the availability of the system under the worst environmental conditions. Thus, it is necessary to predict the evolution of the state of charge of the battery under incomplete daily charging and discharging processes and fluctuating temperatures over day-night cycles. Much of previous development work has been carried out in order to model the short term evolution of battery variables. Many works focus on the on-line parameter estimation of available charge, using standard or advanced estimators, but they are not focused on the development of a model with predictive capabilities. Moreover, normally stable environmental conditions and standard charge-discharge patterns are considered. As the actual cycle-patterns differ from the manufacturer's tests, batteries fail to perform as expected. This paper proposes a novel methodology to model these issues, with predictive capabilities to estimate the remaining charge in a battery after several solar cycles. A new non-linear state space model is proposed as a basis, and the methodology to feed and train the model is introduced. The new methodology is validated using experimental data, providing only 5% of error at higher temperatures than the nominal one.

Sperm competition games: a general model for precopulatory male-male competition.

PubMed

Parker, Geoff A; Lessells, Catherine M; Simmons, Leigh W

2013-01-01

Reproductive males face a trade-off between expenditure on precopulatory male-male competition--increasing the number of females that they secure as mates--and sperm competition--increasing their fertilization success with those females. Previous sperm allocation models have focused on scramble competition in which males compete by searching for mates and the number of matings rises linearly with precopulatory expenditure. However, recent studies have emphasized contest competition involving precopulatory expenditure on armaments, where winning contests may be highly dependent on marginal increases in relative armament level. Here, we develop a general model of sperm allocation that allows us to examine the effect of all forms of precopulatory competition on sperm allocation patterns. The model predicts that sperm allocation decreases if either the "mate-competition loading,"a, or the number of males competing for each mating, M, increases. Other predictions remain unchanged from previous models: (i) expenditure per ejaculate should increase and then decrease, and (ii) total postcopulatory expenditure should increase, as the level of sperm competition increases. A negative correlation between a and M is biologically plausible, and may buffer deviations from the previous models. There is some support for our predictions from comparative analyses across dung beetle species and frog populations. © 2012 The Author(s). Evolution© 2012 The Society for the Study of Evolution.

Fear and Loving in Las Vegas: Evolution, Emotion, and Persuasion.

PubMed

Griskevicius, Vladas; Goldstein, Noah J; Mortensen, Chad R; Sundie, Jill M; Cialdini, Robert B; Kenrick, Douglas T

2009-06-01

How do arousal-inducing contexts, such as frightening or romantic television programs, influence the effectiveness of basic persuasion heuristics? Different predictions are made by three theoretical models: A general arousal model predicts that arousal should increase effectiveness of heuristics; an affective valence model predicts that effectiveness should depend on whether the context elicits positive or negative affect; an evolutionary model predicts that persuasiveness should depend on both the specific emotion that is elicited and the content of the particular heuristic. Three experiments examined how fear-inducing versus romantic contexts influenced the effectiveness of two widely used heuristics-social proof (e.g., "most popular") and scarcity (e.g., "limited edition"). Results supported predictions from an evolutionary model, showing that fear can lead scarcity appeals to be counter-persuasive, and that romantic desire can lead social proof appeals to be counter-persuasive. The findings highlight how an evolutionary theoretical approach can lead to novel theoretical and practical marketing insights.

Effect of Evolutionary Anisotropy on Earing Prediction in Cylindrical Cup Drawing

NASA Astrophysics Data System (ADS)

Choi, H. J.; Lee, K. J.; Choi, Y.; Bae, G.; Ahn, D.-C.; Lee, M.-G.

2017-05-01

The formability of sheet metals is associated with their planar anisotropy, and finite element simulations have been applied to the sheet metal-forming process by describing the anisotropic behaviors using yield functions and hardening models. In this study, the evaluation of anisotropic constitutive models was performed based on the non-uniform height profile or earing in circular cylindrical cup drawing. Two yield functions, a quadratic Hill1948 and a non-quadratic Yld2000-2d model, were used under non-associated and associated flow rules, respectively, to simultaneously capture directional differences in yield stress and r value. The effect of the evolution of anisotropy on the earing prediction was also investigated by employing simplified equivalent plastic strain rate-dependent anisotropic coefficients. The computational results were in good agreement with experiments when the proper choice of the yield function and flow rule, which predicts the planar anisotropy, was made. Moreover, the accuracy of the earing profile could be significantly enhanced if the evolution of anisotropy between uniaxial and biaxial stress states was additionally considered.

Numerical and Experimental Validation of a New Damage Initiation Criterion

NASA Astrophysics Data System (ADS)

Sadhinoch, M.; Atzema, E. H.; Perdahcioglu, E. S.; van den Boogaard, A. H.

2017-09-01

Most commercial finite element software packages, like Abaqus, have a built-in coupled damage model where a damage evolution needs to be defined in terms of a single fracture energy value for all stress states. The Johnson-Cook criterion has been modified to be Lode parameter dependent and this Modified Johnson-Cook (MJC) criterion is used as a Damage Initiation Surface (DIS) in combination with the built-in Abaqus ductile damage model. An exponential damage evolution law has been used with a single fracture energy value. Ultimately, the simulated force-displacement curves are compared with experiments to validate the MJC criterion. 7 out of 9 fracture experiments were predicted accurately. The limitations and accuracy of the failure predictions of the newly developed damage initiation criterion will be discussed shortly.

The evolution of dominance in sporophytic self-incompatibility systems. II. Mate availability and recombination.

PubMed

Schoen, Daniel J; Busch, Jeremiah W

2009-08-01

Sporophytic self-incompatibility (SSI) is a self-pollen recognition system that enforces outcrossing in plants. Recognition in SSI systems is typically controlled by a complex locus (S-locus) with separate genes that determine pollen and stigma specificity. Experimental studies show that S-alleles can be dominant, recessive, or codominant, and that the dominance level of a given S-allele can depend upon whether pollen or stigma specificity is examined. Here and in the companion paper by Llaurens and colleagues, the evolution of dominance in single-locus SSI is explored using numerical models and simulation. Particular attention is directed at factors that can cause S-allele dominance to differ in pollen versus stigma. The effect of recombination between the S-locus and modifier locus is also examined. The models predict that limitation in the number of compatible mates is required for the evolution of S-allele dominance in the stigma but not in the pollen. Tight linkage between the S-locus and modifier promotes the evolution of S-allele dominance hierarchies. Model results are interpreted with respect to published information on the molecular basis of dominance in SSI systems, and reported S-allele dominance relationships in a variety of species. These studies show that dominant S-alleles are more common in the pollen than in the stigma, a pattern that when interpreted in light of model predictions, suggests that mate limitation may be relatively infrequent in natural populations with SSI.

DISTINGUISHING COMPACT BINARY POPULATION SYNTHESIS MODELS USING GRAVITATIONAL WAVE OBSERVATIONS OF COALESCING BINARY BLACK HOLES

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

Stevenson, Simon; Ohme, Frank; Fairhurst, Stephen, E-mail: simon.stevenson@ligo.org

2015-09-01

The coalescence of compact binaries containing neutron stars or black holes is one of the most promising signals for advanced ground-based laser interferometer gravitational-wave (GW) detectors, with the first direct detections expected over the next few years. The rate of binary coalescences and the distribution of component masses is highly uncertain, and population synthesis models predict a wide range of plausible values. Poorly constrained parameters in population synthesis models correspond to poorly understood astrophysics at various stages in the evolution of massive binary stars, the progenitors of binary neutron star and binary black hole systems. These include effects such asmore » supernova kick velocities, parameters governing the energetics of common envelope evolution and the strength of stellar winds. Observing multiple binary black hole systems through GWs will allow us to infer details of the astrophysical mechanisms that lead to their formation. Here we simulate GW observations from a series of population synthesis models including the effects of known selection biases, measurement errors and cosmology. We compare the predictions arising from different models and show that we will be able to distinguish between them with observations (or the lack of them) from the early runs of the advanced LIGO and Virgo detectors. This will allow us to narrow down the large parameter space for binary evolution models.« less

Dynamics of electrical double layer formation in room-temperature ionic liquids under constant-current charging conditions

NASA Astrophysics Data System (ADS)

Jiang, Xikai; Huang, Jingsong; Zhao, Hui; Sumpter, Bobby G.; Qiao, Rui

2014-07-01

We report detailed simulation results on the formation dynamics of an electrical double layer (EDL) inside an electrochemical cell featuring room-temperature ionic liquids (RTILs) enclosed between two planar electrodes. Under relatively small charging currents, the evolution of cell potential from molecular dynamics (MD) simulations during charging can be suitably predicted by the Landau-Ginzburg-type continuum model proposed recently (Bazant et al 2011 Phys. Rev. Lett. 106 046102). Under very large charging currents, the cell potential from MD simulations shows pronounced oscillation during the initial stage of charging, a feature not captured by the continuum model. Such oscillation originates from the sequential growth of the ionic space charge layers near the electrode surface. This allows the evolution of EDLs in RTILs with time, an atomistic process difficult to visualize experimentally, to be studied by analyzing the cell potential under constant-current charging conditions. While the continuum model cannot predict the potential oscillation under such far-from-equilibrium charging conditions, it can nevertheless qualitatively capture the growth of cell potential during the later stage of charging. Improving the continuum model by introducing frequency-dependent dielectric constant and density-dependent ion diffusion coefficients may help to further extend the applicability of the model. The evolution of ion density profiles is also compared between the MD and the continuum model, showing good agreement.

Dynamics of electrical double layer formation in room-temperature ionic liquids under constant-current charging conditions.

PubMed

Jiang, Xikai; Huang, Jingsong; Zhao, Hui; Sumpter, Bobby G; Qiao, Rui

2014-07-16

We report detailed simulation results on the formation dynamics of an electrical double layer (EDL) inside an electrochemical cell featuring room-temperature ionic liquids (RTILs) enclosed between two planar electrodes. Under relatively small charging currents, the evolution of cell potential from molecular dynamics (MD) simulations during charging can be suitably predicted by the Landau-Ginzburg-type continuum model proposed recently (Bazant et al 2011 Phys. Rev. Lett. 106 046102). Under very large charging currents, the cell potential from MD simulations shows pronounced oscillation during the initial stage of charging, a feature not captured by the continuum model. Such oscillation originates from the sequential growth of the ionic space charge layers near the electrode surface. This allows the evolution of EDLs in RTILs with time, an atomistic process difficult to visualize experimentally, to be studied by analyzing the cell potential under constant-current charging conditions. While the continuum model cannot predict the potential oscillation under such far-from-equilibrium charging conditions, it can nevertheless qualitatively capture the growth of cell potential during the later stage of charging. Improving the continuum model by introducing frequency-dependent dielectric constant and density-dependent ion diffusion coefficients may help to further extend the applicability of the model. The evolution of ion density profiles is also compared between the MD and the continuum model, showing good agreement.

Introducing ab initio based neural networks for transition-rate prediction in kinetic Monte Carlo simulations

NASA Astrophysics Data System (ADS)

Messina, Luca; Castin, Nicolas; Domain, Christophe; Olsson, Pär

2017-02-01

The quality of kinetic Monte Carlo (KMC) simulations of microstructure evolution in alloys relies on the parametrization of point-defect migration rates, which are complex functions of the local chemical composition and can be calculated accurately with ab initio methods. However, constructing reliable models that ensure the best possible transfer of physical information from ab initio to KMC is a challenging task. This work presents an innovative approach, where the transition rates are predicted by artificial neural networks trained on a database of 2000 migration barriers, obtained with density functional theory (DFT) in place of interatomic potentials. The method is tested on copper precipitation in thermally aged iron alloys, by means of a hybrid atomistic-object KMC model. For the object part of the model, the stability and mobility properties of copper-vacancy clusters are analyzed by means of independent atomistic KMC simulations, driven by the same neural networks. The cluster diffusion coefficients and mean free paths are found to increase with size, confirming the dominant role of coarsening of medium- and large-sized clusters in the precipitation kinetics. The evolution under thermal aging is in better agreement with experiments with respect to a previous interatomic-potential model, especially concerning the experiment time scales. However, the model underestimates the solubility of copper in iron due to the excessively high solution energy predicted by the chosen DFT method. Nevertheless, this work proves the capability of neural networks to transfer complex ab initio physical properties to higher-scale models, and facilitates the extension to systems with increasing chemical complexity, setting the ground for reliable microstructure evolution simulations in a wide range of alloys and applications.

Use of Ocean Remote Sensing Data to Enhance Predictions with a Coupled General Circulation Model

NASA Technical Reports Server (NTRS)

Rienecker, Michele M.

1999-01-01

Surface height, sea surface temperature and surface wind observations from satellites have given a detailed time sequence of the initiation and evolution of the 1997/98 El Nino. The data have beet complementary to the subsurface TAO moored data in their spatial resolution and extent. The impact of satellite observations on seasonal prediction in the tropical Pacific using a coupled ocean-atmosphere general circulation model will be presented.

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.

Finite Element Modeling of In-Situ Stresses near Salt Bodies

NASA Astrophysics Data System (ADS)

Sanz, P.; Gray, G.; Albertz, M.

2011-12-01

The in-situ stress field is modified around salt bodies because salt rock has no ability to sustain shear stresses. A reliable prediction of stresses near salt is important for planning safe and economic drilling programs. A better understanding of in-situ stresses before drilling can be achieved using finite element models that account for the creeping salt behavior and the elastoplastic response of the surrounding sediments. Two different geomechanical modeling techniques can be distinguished: "dynamic" modeling and "static" modeling. "Dynamic" models, also known as forward models, simulate the development of structural processes in geologic time. This technique provides the evolution of stresses and so it is used to simulate the initiation and development of structural features, such as, faults, folds, fractures, and salt diapers. The original or initial configuration and the unknown final configuration of forward models are usually significantly different therefore geometric non-linearities need to be considered. These models may be difficult to constrain when different tectonic, deposition, and erosion events, and the timing among them, needs to be accounted for. While dynamic models provide insight into the stress evolution, in many cases is very challenging, if not impossible, to forward model a configuration to its known present-day geometry; particularly in the case of salt layers that evolve into highly irregular and complex geometries. Alternatively, "static" models use the present-day geometry and present-day far-field stresses to estimate the present-day in-situ stress field inside a domain. In this case, it is appropriate to use a small deformation approach because initial and final configurations should be very similar, and more important, because the equilibrium of stresses should be stated in the present-day initial configuration. The initial stresses and the applied boundary conditions are constrained by the geologic setting and available data. This modeling technique does not predict the evolution of structural elements or stresses with time; therefore it does not provide any insight into the formation of fractures that were previously developed under a different stress condition or the development of overpressure generated by a high sedimentation rate. This work provides a validation for predicting in-situ stresses near salt using "static" models. We compare synthetic examples using both modeling techniques and show that stresses near salt predicted with "static" models are comparable to the ones generated by "dynamic" models.

Cosmological implications of a large complete quasar sample.

PubMed

Segal, I E; Nicoll, J F

1998-04-28

Objective and reproducible determinations of the probabilistic significance levels of the deviations between theoretical cosmological prediction and direct model-independent observation are made for the Large Bright Quasar Sample [Foltz, C., Chaffee, F. H., Hewett, P. C., MacAlpine, G. M., Turnshek, D. A., et al. (1987) Astron. J. 94, 1423-1460]. The Expanding Universe model as represented by the Friedman-Lemaitre cosmology with parameters qo = 0, Lambda = 0 denoted as C1 and chronometric cosmology (no relevant adjustable parameters) denoted as C2 are the cosmologies considered. The mean and the dispersion of the apparent magnitudes and the slope of the apparent magnitude-redshift relation are the directly observed statistics predicted. The C1 predictions of these cosmology-independent quantities are deviant by as much as 11sigma from direct observation; none of the C2 predictions deviate by >2sigma. The C1 deviations may be reconciled with theory by the hypothesis of quasar "evolution," which, however, appears incapable of being substantiated through direct observation. The excellent quantitative agreement of the C1 deviations with those predicted by C2 without adjustable parameters for the results of analysis predicated on C1 indicates that the evolution hypothesis may well be a theoretical artifact.

Spatial Evolution of Human Dialects

NASA Astrophysics Data System (ADS)

Burridge, James

2017-07-01

The geographical pattern of human dialects is a result of history. Here, we formulate a simple spatial model of language change which shows that the final result of this historical evolution may, to some extent, be predictable. The model shows that the boundaries of language dialect regions are controlled by a length minimizing effect analogous to surface tension, mediated by variations in population density which can induce curvature, and by the shape of coastline or similar borders. The predictability of dialect regions arises because these effects will drive many complex, randomized early states toward one of a smaller number of stable final configurations. The model is able to reproduce observations and predictions of dialectologists. These include dialect continua, isogloss bundling, fanning, the wavelike spread of dialect features from cities, and the impact of human movement on the number of dialects that an area can support. The model also provides an analytical form for Séguy's curve giving the relationship between geographical and linguistic distance, and a generalization of the curve to account for the presence of a population center. A simple modification allows us to analytically characterize the variation of language use by age in an area undergoing linguistic change.

How self-organization can guide evolution.

PubMed

Glancy, Jonathan; Stone, James V; Wilson, Stuart P

2016-11-01

Self-organization and natural selection are fundamental forces that shape the natural world. Substantial progress in understanding how these forces interact has been made through the study of abstract models. Further progress may be made by identifying a model system in which the interaction between self-organization and selection can be investigated empirically. To this end, we investigate how the self-organizing thermoregulatory huddling behaviours displayed by many species of mammals might influence natural selection of the genetic components of metabolism. By applying a simple evolutionary algorithm to a well-established model of the interactions between environmental, morphological, physiological and behavioural components of thermoregulation, we arrive at a clear, but counterintuitive, prediction: rodents that are able to huddle together in cold environments should evolve a lower thermal conductance at a faster rate than animals reared in isolation. The model therefore explains how evolution can be accelerated as a consequence of relaxed selection , and it predicts how the effect may be exaggerated by an increase in the litter size, i.e. by an increase in the capacity to use huddling behaviours for thermoregulation. Confirmation of these predictions in future experiments with rodents would constitute strong evidence of a mechanism by which self-organization can guide natural selection.

Merger-driven evolution of the effective stellar initial mass function of massive early-type galaxies

NASA Astrophysics Data System (ADS)

Sonnenfeld, Alessandro; Nipoti, Carlo; Treu, Tommaso

2017-02-01

The stellar initial mass function (IMF) of early-type galaxies is the combination of the IMF of the stellar population formed in situ and that of accreted stellar populations. Using as an observable the effective IMF αIMF, defined as the ratio between the true stellar mass of a galaxy and the stellar mass inferred assuming a Salpeter IMF, we present a theoretical model for its evolution as a result of dry mergers. We use a simple dry-merger evolution model, based on cosmological N-body simulations, together with empirically motivated prescriptions for the IMF to make predictions on how the effective IMF of massive early-type galaxies changes from z = 2 to z = 0. We find that the IMF normalization of individual galaxies becomes lighter with time. At fixed velocity dispersion, αIMF is predicted to be constant with redshift. Current dynamical constraints on the evolution of the IMF are in slight tension with this prediction, even though systematic uncertainties, including the effect of radial gradients in the IMF, prevent a conclusive statement. The correlation of αIMF with stellar mass becomes shallower with time, while the correlation between αIMF and velocity dispersion is mostly preserved by dry mergers. We also find that dry mergers can mix the dependence of the IMF on stellar mass and velocity dispersion, making it challenging to infer, from z = 0 observations of global galactic properties, what is the quantity that is originally coupled with the IMF.

A first attempt to reproduce basaltic soil chronosequences using a process-based soil profile model: implications for our understanding of soil evolution

NASA Astrophysics Data System (ADS)

Johnson, M.; Gloor, M.; Lloyd, J.

2012-04-01

Soils are complex systems which hold a wealth of information on both current and past conditions and many biogeochemical processes. The ability to model soil forming processes and predict soil properties will enable us to quantify such conditions and contribute to our understanding of long-term biogeochemical cycles, particularly the carbon cycle and plant nutrient cycles. However, attempts to confront such soil model predictions with data are rare, although increasingly more data from chronosquence studies is becoming available for such a purpose. Here we present initial results of an attempt to reproduce soil properties with a process-based soil evolution model similar to the model of Kirkby (1985, J. Soil Science). We specifically focus on the basaltic soils in both Hawaii and north Queensland, Australia. These soils are formed on a series of volcanic lava flows which provide sequences of different aged soils all with a relatively uniform parent material. These soil chronosequences provide a snapshot of a soil profile during different stages of development. Steep rainfall gradients in these regions also provide a system which allows us to test the model's ability to reproduce soil properties under differing climates. The mechanistic, soil evolution model presented here includes the major processes of soil formation such as i) mineral weathering, ii) percolation of rainfall through the soil, iii) leaching of solutes out of the soil profile iv) surface erosion and v) vegetation and biotic interactions. The model consists of a vertical profile and assumes simple geometry with a constantly sloping surface. The timescales of interest are on the order of tens to hundreds of thousand years. The specific properties the model predicts are, soil depth, the proportion of original elemental oxides remaining in each soil layer, pH of the soil solution, organic carbon distribution and CO2 production and concentration. The presentation will focus on a brief introduction of the model, followed by a description of novel methods using tracers such as optically stimulated luminescence (OSL) dates and meteoric 10Be to evaluate the modelled processes of bioturbation and surface erosion. We will also discuss comparisons of modelled properties with observations and conclude with implications on our understanding of soil evolution.

Outbursts and Gradualism: Megaflood erosion consistent with long-term landscape evolution

NASA Astrophysics Data System (ADS)

Garcia-Castellanos, Daniel; O'Connor, Jim

2017-04-01

Existing models for the development of topography and relief over geological timescales are fundamentally based on semi-empirical laws of the erosion and sediment transport performed by rivers. The prediction power of these laws is hindered by limitations in measuring river incision and by the scant knowledge of the past hydrological conditions, specifically average water flow and its variability. Consequently, models adopt 'gradualistic' (time-averaged) assumptions and the erodability values derived from modelling long-term erosion rates in rivers remain ambiguously tied not only to the lithology and nature of the bedrock but also to uncertainties in the quantification of past climate. This prevents the use of those erodabilities to predict the landscape evolution in different scenarios. Here, we apply the fundamentals of river erosion models to outburst floods triggered by overtopping lakes, for which the hydrograph is intrinsically known from the geomorphological record or from direct measures. We obtain the outlet erodability from the peak water discharge and lake area observed in 86 floods that span over 16 orders of magnitude in water volume. The obtained erodability-lithology correlation is consistent with that seen in 22 previous long-term river incision quantifications, showing that outburst floods can be used to estimate erodability values that remain valid for a wide range of hydrological regimes and for erosion timescales spanning from hours-long outburst floods to million-year-scale landscape evolution. The results constrain the conditions leading to the runaway erosion responsible for outburst floods triggered by overtopping lakes. They also call for the explicit incorporation of climate episodicity to the landscape evolution models. [Funded by CGL2014-59516].

HCV prevalence can predict HIV epidemic potential among people who inject drugs: mathematical modeling analysis.

PubMed

Akbarzadeh, Vajiheh; Mumtaz, Ghina R; Awad, Susanne F; Weiss, Helen A; Abu-Raddad, Laith J

2016-12-03

Hepatitis C virus (HCV) and HIV are both transmitted through percutaneous exposures among people who inject drugs (PWID). Ecological analyses on global epidemiological data have identified a positive association between HCV and HIV prevalence among PWID. Our objective was to demonstrate how HCV prevalence can be used to predict HIV epidemic potential among PWID. Two population-level models were constructed to simulate the evolution of HCV and HIV epidemics among PWID. The models described HCV and HIV parenteral transmission, and were solved both deterministically and stochastically. The modeling results provided a good fit to the epidemiological data describing the ecological HCV and HIV association among PWID. HCV was estimated to be eight times more transmissible per shared injection than HIV. A threshold HCV prevalence of 29.0% (95% uncertainty interval (UI): 20.7-39.8) and 46.5% (95% UI: 37.6-56.6) were identified for a sustainable HIV epidemic (HIV prevalence >1%) and concentrated HIV epidemic (HIV prevalence >5%), respectively. The association between HCV and HIV was further described with six dynamical regimes depicting the overlapping epidemiology of the two infections, and was quantified using defined and estimated measures of association. Modeling predictions across a wide range of HCV prevalence indicated overall acceptable precision in predicting HIV prevalence at endemic equilibrium. Modeling predictions were found to be robust with respect to stochasticity and behavioral and biological parameter uncertainty. In an illustrative application of the methodology, the modeling predictions of endemic HIV prevalence in Iran agreed with the scale and time course of the HIV epidemic in this country. Our results show that HCV prevalence can be used as a proxy biomarker of HIV epidemic potential among PWID, and that the scale and evolution of HIV epidemic expansion can be predicted with sufficient precision to inform HIV policy, programming, and resource allocation.

An Efficient Deterministic Approach to Model-based Prediction Uncertainty Estimation

DTIC Science & Technology

2012-09-01

94035, USA abhinav.saxena@nasa.gov ABSTRACT Prognostics deals with the prediction of the end of life ( EOL ) of a system. EOL is a random variable, due...future evolution of the system, accumulating additional uncertainty into the predicted EOL . Prediction algorithms that do not account for these sources of...uncertainty are misrepresenting the EOL and can lead to poor decisions based on their results. In this paper, we explore the impact of uncertainty in

Bridging scales in the evolution of infectious disease life histories: theory.

PubMed

Day, Troy; Alizon, Samuel; Mideo, Nicole

2011-12-01

A significant goal of recent theoretical research on pathogen evolution has been to develop theory that bridges within- and between-host dynamics. The main approach used to date is one that nests within-host models of pathogen replication in models for the between-host spread of infectious diseases. Although this provides an elegant approach, it nevertheless suffers from some practical difficulties. In particular, the information required to satisfactorily model the mechanistic details of the within-host dynamics is not often available. Here, we present a theoretical approach that circumvents these difficulties by quantifying the relevant within-host factors in an empirically tractable way. The approach is closely related to quantitative genetic models for function-valued traits, and it also allows for the prediction of general characteristics of disease life history, including the timing of virulence, transmission, and host recovery. In a companion paper, we illustrate the approach by applying it to data from a model system of malaria. © 2011 The Author(s). Evolution© 2011 The Society for the Study of Evolution.

Probabilistic Fatigue Damage Prognosis Using a Surrogate Model Trained Via 3D Finite Element Analysis

NASA Technical Reports Server (NTRS)

Leser, Patrick E.; Hochhalter, Jacob D.; Newman, John A.; Leser, William P.; Warner, James E.; Wawrzynek, Paul A.; Yuan, Fuh-Gwo

2015-01-01

Utilizing inverse uncertainty quantification techniques, structural health monitoring can be integrated with damage progression models to form probabilistic predictions of a structure's remaining useful life. However, damage evolution in realistic structures is physically complex. Accurately representing this behavior requires high-fidelity models which are typically computationally prohibitive. In the present work, a high-fidelity finite element model is represented by a surrogate model, reducing computation times. The new approach is used with damage diagnosis data to form a probabilistic prediction of remaining useful life for a test specimen under mixed-mode conditions.

Models of social evolution: can we do better to predict 'who helps whom to achieve what'?

PubMed

Rodrigues, António M M; Kokko, Hanna

2016-02-05

Models of social evolution and the evolution of helping have been classified in numerous ways. Two categorical differences have, however, escaped attention in the field. Models tend not to justify why they use a particular assumption structure about who helps whom: a large number of authors model peer-to-peer cooperation of essentially identical individuals, probably for reasons of mathematical convenience; others are inspired by particular cooperatively breeding species, and tend to assume unidirectional help where subordinates help a dominant breed more efficiently. Choices regarding what the help achieves (i.e. which life-history trait of the helped individual is improved) are similarly made without much comment: fecundity benefits are much more commonly modelled than survival enhancements, despite evidence that these may interact when the helped individual can perform life-history reallocations (load-lightening and related phenomena). We review our current theoretical understanding of effects revealed when explicitly asking 'who helps whom to achieve what', from models of mutual aid in partnerships to the very few models that explicitly contrast the strength of selection to help enhance another individual's fecundity or survival. As a result of idiosyncratic modelling choices in contemporary literature, including the varying degree to which demographic consequences are made explicit, there is surprisingly little agreement on what types of help are predicted to evolve most easily. We outline promising future directions to fill this gap. © 2016 The Author(s).

Models of social evolution: can we do better to predict ‘who helps whom to achieve what’?

PubMed Central

Rodrigues, António M. M.; Kokko, Hanna

2016-01-01

Models of social evolution and the evolution of helping have been classified in numerous ways. Two categorical differences have, however, escaped attention in the field. Models tend not to justify why they use a particular assumption structure about who helps whom: a large number of authors model peer-to-peer cooperation of essentially identical individuals, probably for reasons of mathematical convenience; others are inspired by particular cooperatively breeding species, and tend to assume unidirectional help where subordinates help a dominant breed more efficiently. Choices regarding what the help achieves (i.e. which life-history trait of the helped individual is improved) are similarly made without much comment: fecundity benefits are much more commonly modelled than survival enhancements, despite evidence that these may interact when the helped individual can perform life-history reallocations (load-lightening and related phenomena). We review our current theoretical understanding of effects revealed when explicitly asking ‘who helps whom to achieve what’, from models of mutual aid in partnerships to the very few models that explicitly contrast the strength of selection to help enhance another individual's fecundity or survival. As a result of idiosyncratic modelling choices in contemporary literature, including the varying degree to which demographic consequences are made explicit, there is surprisingly little agreement on what types of help are predicted to evolve most easily. We outline promising future directions to fill this gap. PMID:26729928

Are relationships between pollen-ovule ratio and pollen and seed size explained by sex allocation?

PubMed

Burd, Martin

2011-10-01

Positive correlations between pollen-ovule ratio and seed size, and negative correlations between pollen-ovule ratio and pollen grain size have been noted frequently in a wide variety of angiosperm taxa. These relationships are commonly explained as a consequence of sex allocation on the basis of a simple model proposed by Charnov. Indeed, the theoretical expectation from the model has been the basis for interest in the empirical pattern. However, the predicted relationship is a necessary consequence of the mathematics of the model, which therefore has little explanatory power, even though its predictions are consistent with empirical results. The evolution of pollen-ovule ratios is likely to depend on selective factors affecting mating system, pollen presentation and dispensing, patterns of pollen receipt, pollen tube competition, female mate choice through embryo abortion, as well as genetic covariances among pollen, ovule, and seed size and other reproductive traits. To the extent the empirical correlations involving pollen-ovule ratios are interesting, they will need explanation in terms of a suite of selective factors. They are not explained simply by sex allocation trade-offs. © 2011 The Author(s). Evolution© 2011 The Society for the Study of Evolution.

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.

Model for texture evolution in cold rolling of 2.4 wt.-% Si non-oriented electrical steel

NASA Astrophysics Data System (ADS)

Wei, X.; Hojda, S.; Dierdorf, J.; Lohmar, J.; Hirt, G.

2017-10-01

Iron loss and limited magnetic flux density are constraints for NGO electrical steel used in highly efficient electrical machinery cores. The most important factors that affect these properties are the final microstructure and the texture of the NGO steel. Reviewing the whole process chain, cold rolling plays an important role because the recrystallization and grain growth during the final heat treatment can be strongly affected by the stored energy and microstructure of cold rolling, and some texture characteristics can be inherited as well. Therefore, texture evolution during cold rolling of NGO steel is worth a detailed investigation. In this paper, texture evolution in cold rolling of non-oriented (NGO) electrical steel is simulated with a crystal plasticity finite element method (CPFEM) model. In previous work, a CPFEM model has been implemented for simulating the texture evolution with periodic boundary conditions and a phenomenological constitutive law. In a first step the microstructure in the core of the workpiece was investigated and mapped to a representative volume element to predict the texture evolution. In this work an improved version of the CPFEM model is described that better reflects the texture evolution in cold rolling of NGO electrical steel containing 2.4 wt.-% Si. This is achieved by applying the deformation gradient and calibrating the flow curve within the CPFEM model. Moreover, the evolution of dislocation density is calculated and visualized in this model. An in depth comparison of the numerical and experimental results reveals, that the improved CPFEM model is able to represent the important characteristics of texture evolution in the core of the workpiece during cold rolling with high precision.

On the time to steady state: insights from numerical modeling

NASA Astrophysics Data System (ADS)

Goren, L.; Willett, S.; McCoy, S. W.; Perron, J.

2013-12-01

How fast do fluvial landscapes approach steady state after an application of tectonic or climatic perturbation? While theory and some numerical models predict that the celerity of the advective wave (knickpoint) controls the response time for perturbations, experiments and other landscape evolution models demonstrate that the time to steady state is much longer than the theoretically predicted response time. We posit that the longevity of transient features and the time to steady state are controlled by the stability of the topology and geometry of channel networks. Evolution of a channel network occurs by a combination of discrete capture events and continuous migration of water divides, processes, which are difficult to represent accurately in landscape evolution models. We therefore address the question of the time to steady state using the DAC landscape evolution model that solves accurately for the location of water divides, using a combination of analytical solution for hillslopes and low-order channels together with a numerical solution for higher order channels. DAC also includes an explicit capture criterion. We have tested fundamental predictions from DAC and show that modeled networks reproduce natural network characteristics such as the Hack's exponent and coefficient and the fractal dimension. We define two steady-state criteria: a topographic steady state, defined by global, pointwise steady elevation, and a topological steady state defined as the state in which no further reorganization of the drainage network takes place. Analyzing block uplift simulations, we find that the time to achieve either topographic or topological steady state exceeds by an order of magnitude the theoretical response time of the fluvial network. The longevity of the transient state is the result of the area feedback, by which, migration of a divide changes the local contributing area. This change propagates downstream as a slope adjustment, forcing further divide migrations and area change in adjacent tributaries and basins. In order to characterize the evolution of the drainage network on its way to steady state, we define a proxy to steady state elevation, χ, which is also the characteristic parameter of the transient stream power PDE. Through simulations of tectonic tilting we find that reorganization tends to minimize moments of the χ distribution of the landscape and of Δχ across divides.

Evolution of Inbreeding Avoidance and Inbreeding Preference through Mate Choice among Interacting Relatives.

PubMed

Duthie, A Bradley; Reid, Jane M

2016-12-01

While extensive population genetic theory predicts conditions favoring evolution of self-fertilization versus outcrossing, there is no analogous theory that predicts conditions favoring evolution of inbreeding avoidance or inbreeding preference enacted through mate choice given obligate biparental reproduction. Multiple interacting processes complicate the dynamics of alleles underlying such inbreeding strategies, including sexual conflict, distributions of kinship, genetic drift, purging of mutation load, direct costs, and restricted kin discrimination. We incorporated these processes into an individual-based model to predict conditions where selection should increase or decrease frequencies of alleles causing inbreeding avoidance or inbreeding preference when females or males controlled mating. Selection for inbreeding avoidance occurred given strong inbreeding depression when either sex chose mates, while selection for inbreeding preference occurred given very weak inbreeding depression when females chose but never occurred when males chose. Selection for both strategies was constrained by direct costs and restricted kin discrimination. Purging was negligible, but allele frequencies were strongly affected by drift in small populations, while selection for inbreeding avoidance was weak in larger populations because inbreeding risk decreased. Therefore, while selection sometimes favored alleles underlying inbreeding avoidance or preference, evolution of such strategies may be much more restricted and stochastic than is commonly presumed.

Modelling and simulation of the consolidation behavior during thermoplastic prepreg composites forming process

NASA Astrophysics Data System (ADS)

Xiong, H.; Hamila, N.; Boisse, P.

2017-10-01

Pre-impregnated thermoplastic composites have recently attached increasing interest in the automotive industry for their excellent mechanical properties and their rapid cycle manufacturing process, modelling and numerical simulations of forming processes for composites parts with complex geometry is necessary to predict and optimize manufacturing practices, especially for the consolidation effects. A viscoelastic relaxation model is proposed to characterize the consolidation behavior of thermoplastic prepregs based on compaction tests with a range of temperatures. The intimate contact model is employed to predict the evolution of the consolidation which permits the microstructure prediction of void presented through the prepreg. Within a hyperelastic framework, several simulation tests are launched by combining a new developed solid shell finite element and the consolidation models.

Comparing the line broadened quasilinear model to Vlasov code

NASA Astrophysics Data System (ADS)

Ghantous, K.; Berk, H. L.; Gorelenkov, N. N.

2014-03-01

The Line Broadened Quasilinear (LBQ) model is revisited to study its predicted saturation level as compared with predictions of a Vlasov solver BOT [Lilley et al., Phys. Rev. Lett. 102, 195003 (2009) and M. Lilley, BOT Manual. The parametric dependencies of the model are modified to achieve more accuracy compared to the results of the Vlasov solver both in regards to a mode amplitude's time evolution to a saturated state and its final steady state amplitude in the parameter space of the model's applicability. However, the regions of stability as predicted by LBQ model and BOT are found to significantly differ from each other. The solutions of the BOT simulations are found to have a larger region of instability than the LBQ simulations.

Efficient rolling texture predictions and texture-sensitive properties of α-uranium foils

DOE PAGES

Steiner, Matthew A.; Klein, Robert W.; Calhoun, Christopher A.; ...

2017-01-01

Here, finite element (FE) analysis was used to simulate the strain history of an α-uranium foil during cold-rolling, with the sheet modeled as an isotropic elastoplastic continuum. The resulting strain history was then used as input for a viscoplastic self-consistent (VPSC) polycrystal plasticity model to simulate crystallographic texture evolution. Mid-plane textures predicted via the combined FE→VPSC approach show alignment of the (010) poles along the rolling direction (RD), and the (001) poles along the normal direction (ND) with a symmetric splitting along RD. The surface texture is similar to that of the mid-plane, but with a shear-induced asymmetry that favorsmore » one of the RD split features of the (001) pole figure. Both the mid-plane and surface textures predicted by the FE→VPSC approach agree with published experimental results for cold-rolled α-uranium plates, as well as predictions made by a more computationally intensive full-field crystal plasticity based finite element model. α-uranium foils produced by cold-rolling must typically undergo a final recrystallization anneal to restore ductility prior to their final application, resulting in significant texture evolution from the cold-rolled plate deformation texture. Using the texture measured from a foil in the final recrystallized state, coefficients of the thermal expansion and elastic stiffness tensors were calculated using a thermo-elastic self-consistent model, and the anisotropic yield loci and flow curves along the RD, TD, and ND were predicted using the VPSC code.« less

Efficient rolling texture predictions and texture-sensitive properties of α-uranium foils

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

Steiner, Matthew A.; Klein, Robert W.; Calhoun, Christopher A.

Here, finite element (FE) analysis was used to simulate the strain history of an α-uranium foil during cold-rolling, with the sheet modeled as an isotropic elastoplastic continuum. The resulting strain history was then used as input for a viscoplastic self-consistent (VPSC) polycrystal plasticity model to simulate crystallographic texture evolution. Mid-plane textures predicted via the combined FE→VPSC approach show alignment of the (010) poles along the rolling direction (RD), and the (001) poles along the normal direction (ND) with a symmetric splitting along RD. The surface texture is similar to that of the mid-plane, but with a shear-induced asymmetry that favorsmore » one of the RD split features of the (001) pole figure. Both the mid-plane and surface textures predicted by the FE→VPSC approach agree with published experimental results for cold-rolled α-uranium plates, as well as predictions made by a more computationally intensive full-field crystal plasticity based finite element model. α-uranium foils produced by cold-rolling must typically undergo a final recrystallization anneal to restore ductility prior to their final application, resulting in significant texture evolution from the cold-rolled plate deformation texture. Using the texture measured from a foil in the final recrystallized state, coefficients of the thermal expansion and elastic stiffness tensors were calculated using a thermo-elastic self-consistent model, and the anisotropic yield loci and flow curves along the RD, TD, and ND were predicted using the VPSC code.« less

Efficient rolling texture predictions and texture-sensitive thermomechanical properties of α-uranium foils

NASA Astrophysics Data System (ADS)

Steiner, Matthew A.; Klein, Robert W.; Calhoun, Christopher A.; Knezevic, Marko; Garlea, Elena; Agnew, Sean R.

2017-11-01

Finite element (FE) analysis was used to simulate the strain history of an α-uranium foil during cold straight-rolling, with the sheet modeled as an isotropic elastoplastic continuum. The resulting strain history was then used as input for a viscoplastic self-consistent (VPSC) polycrystal plasticity model to simulate crystallographic texture evolution. Mid-plane textures predicted via the combined FE→VPSC approach show alignment of the (010) poles along the rolling direction (RD), and the (001) poles along the normal direction (ND) with a symmetric splitting along RD. The surface texture is similar to that of the mid-plane, but with a shear-induced asymmetry that favors one of the RD split features of the (001) pole figure. Both the mid-plane and surface textures predicted by the FE→VPSC approach agree with published experimental results for cold straight-rolled α-uranium plates, as well as predictions made by a more computationally intensive full-field crystal plasticity based finite element model. α-uranium foils produced by cold-rolling must typically undergo a recrystallization anneal to restore ductility prior to their final application, resulting in significant texture evolution from the cold-rolled plate deformation texture. Using the texture measured from a foil in the final recrystallized state, coefficients of thermal expansion and the elastic stiffness tensors were calculated using a thermo-elastic self-consistent model, and the anisotropic yield loci and flow curves along the RD, TD, and ND were predicted using the VPSC code.

A gene network model accounting for development and evolution of mammalian teeth

PubMed Central

Salazar-Ciudad, Isaac; Jernvall, Jukka

2002-01-01

Generation of morphological diversity remains a challenge for evolutionary biologists because it is unclear how an ultimately finite number of genes involved in initial pattern formation integrates with morphogenesis. Ideally, models used to search for the simplest developmental principles on how genes produce form should account for both developmental process and evolutionary change. Here we present a model reproducing the morphology of mammalian teeth by integrating experimental data on gene interactions and growth into a morphodynamic mechanism in which developing morphology has a causal role in patterning. The model predicts the course of tooth-shape development in different mammalian species and also reproduces key transitions in evolution. Furthermore, we reproduce the known expression patterns of several genes involved in tooth development and their dynamics over developmental time. Large morphological effects frequently can be achieved by small changes, according to this model, and similar morphologies can be produced by different changes. This finding may be consistent with why predicting the morphological outcomes of molecular experiments is challenging. Nevertheless, models incorporating morphology and gene activity show promise for linking genotypes to phenotypes. PMID:12048258

Mathematical modeling of microstructural development in hypoeutectic cast iron

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

Maijer, D.; Cockcroft, S.L.; Patt, W.

A mathematical heat-transfer/microstructural model has been developed to predict the evolution of proeutectic austenite, white iron eutectic, and gray iron eutectic during solidification of hypoeutectic cast iron, based on the commercial finite-element code ABAQUS. Specialized routines which employ relationships describing nucleation and growth of equiaxed primary austenite, gray iron eutectic, and white iron eutectic have been formulated and incorporated into ABAQUS through user-specified subroutines. The relationships used in the model to describe microstructural evolution have been adapted from relationships describing equiaxed growth in the literature. The model has been validated/fine tuned against temperature data collected from a QuiK-Cup sample, whichmore » contained a thermocouple embedded approximately in the center of the casting. The phase distribution predicted with the model has been compared to the measured phase distribution inferred from the variation in hardness within the QuiK-Cup sample and from image analysis of photomicrographs of the polished and etched microstructure. Overall, the model results were found to agree well with the measured distribution of the microstructure.« less

MY Cam: can homogeneous evolution produce gravitational-wave progenitors?

NASA Astrophysics Data System (ADS)

Negueruela, Ignacio

2016-10-01

Besides opening the era of gravitational-wave astrophysics, GW150914 has revolutionized the field of massive stars. GW150914 proves the existence of stellar-mass black holes in a configuration that current models for stellar evolution can only reproduce in special conditions of homogeneous evolution and/or low metallicity.Only a handful of very-massive binaries that could lead to a binary black hole are known. We request UV spectroscopy of MY Cam (38Msun+32Msun), the best laboratory to test several predictions by current models, in order to derive stellar abundances and wind parameters that are inaccessible from the ground. Together with our previous photometric and spectroscopic exhaustive coverage, the STIS spectra will be key to characterize the pre-common envelope phase and test the homogeneous evolution hypothesis, critical ingredients of the different progenitor scenarios proposed to explain GW15091.

The next generation of galaxy evolution models: A symbiosis of stellar populations and chemical abundances

NASA Astrophysics Data System (ADS)

Kotulla, Ralf

2012-10-01

Over its lifespan Hubble has invested significant effort into detailed observations of galaxies both in the local and distant universe. To extract the physical information from the observed {spectro-}photometry requires detailed and accurate models. Stellar population synthesis models are frequently used to obtain stellar masses, star formation rate, galaxy ages and star formation histories. Chemical evolution models offer another valuable and complementary approach to gain insight into many of the same aspects, yet these two methods have rarely been used in combination.Our proposed next generation of galaxy evolution models will help us improve our understanding of how galaxies form and evolve. Building on GALEV evolutionary synthesis models we incorporate state-of-the-art input physics for stellar evolution of binaries and rotating stars as well as new spectral libraries well matched to the modern observational capabilities. Our improved chemical evolution model allows us to self-consistently trace abundances of individual elements, fully accounting for the increasing initial abundances of successive stellar generations. GALEV will support variable Initial Mass Functions {IMF}, enabling us to test recent observational findings of a non-universal IMF by predicting chemical properties and integrated spectra in an integrated and consistent manner.HST is the perfect instrument for testing this approach. Its wide wavelength coverage from UV to NIR enables precise SED fitting, and with its spatial resolution we can compare the inferred chemical evolution to studies of star clusters and resolved stellar populations in nearby galaxies.

What do Simulations Predict for the Galaxy Stellar Mass Function and its Evolution in Different Environments?

NASA Astrophysics Data System (ADS)

Vulcani, Benedetta; De Lucia, Gabriella; Poggianti, Bianca M.; Bundy, Kevin; More, Surhud; Calvi, Rosa

2014-06-01

We present a comparison between the observed galaxy stellar mass function and the one predicted from the De Lucia & Blaizot semi-analytic model applied to the Millennium Simulation, for cluster satellites and galaxies in the field (meant as a wide portion of the sky, including all environments), in the local universe (z ~ 0.06), and at intermediate redshift (z ~ 0.6), with the aim to shed light on the processes which regulate the mass distribution in different environments. While the mass functions in the field and in its finer environments (groups, binary, and single systems) are well matched in the local universe down to the completeness limit of the observational sample, the model overpredicts the number of low-mass galaxies in the field at z ~ 0.6 and in clusters at both redshifts. Above M * = 1010.25 M ⊙, it reproduces the observed similarity of the cluster and field mass functions but not the observed evolution. Our results point out two shortcomings of the model: an incorrect treatment of cluster-specific environmental effects and an overefficient galaxy formation at early times (as already found by, e.g., Weinmann et al.). Next, we consider only simulations. Also using the Guo et al. model, we find that the high-mass end of the mass functions depends on halo mass: only very massive halos host massive galaxies, with the result that their mass function is flatter. Above M * = 109.4 M ⊙, simulations show an evolution in the number of the most massive galaxies in all environments. Mass functions obtained from the two prescriptions are different, however, results are qualitatively similar, indicating that the adopted methods to model the evolution of central and satellite galaxies still have to be better implemented in semi-analytic models.

Molecular Cloud Evolution VI. Measuring cloud ages

NASA Astrophysics Data System (ADS)

Vázquez-Semadeni, Enrique; Zamora-Avilés, Manuel; Galván-Madrid, Roberto; Forbrich, Jan

2018-06-01

In previous contributions, we have presented an analytical model describing the evolution of molecular clouds (MCs) undergoing hierarchical gravitational contraction. The cloud's evolution is characterized by an initial increase in its mass, density, and star formation rate (SFR) and efficiency (SFE) as it contracts, followed by a decrease of these quantities as newly formed massive stars begin to disrupt the cloud. The main parameter of the model is the maximum mass reached by the cloud during its evolution. Thus, specifying the instantaneous mass and some other variable completely determines the cloud's evolutionary stage. We apply the model to interpret the observed scatter in SFEs of the cloud sample compiled by Lada et al. as an evolutionary effect so that, although clouds such as California and Orion A have similar masses, they are in very different evolutionary stages, causing their very different observed SFRs and SFEs. The model predicts that the California cloud will eventually reach a significantly larger total mass than the Orion A cloud. Next, we apply the model to derive estimated ages of the clouds since the time when approximately 25% of their mass had become molecular. We find ages from ˜1.5 to 27 Myr, with the most inactive clouds being the youngest. Further predictions of the model are that clouds with very low SFEs should have massive atomic envelopes constituting the majority of their gravitational mass, and that low-mass clouds (M ˜ 103-104M⊙) end their lives with a mini-burst of star formation, reaching SFRs ˜300-500 M⊙ Myr-1. By this time, they have contracted to become compact (˜1 pc) massive star-forming clumps, in general embedded within larger GMCs.

Model-data assimilation of multiple phenological observations to constrain and predict leaf area index.

PubMed

Viskari, Toni; Hardiman, Brady; Desai, Ankur R; Dietze, Michael C

2015-03-01

Our limited ability to accurately simulate leaf phenology is a leading source of uncertainty in models of ecosystem carbon cycling. We evaluate if continuously updating canopy state variables with observations is beneficial for predicting phenological events. We employed ensemble adjustment Kalman filter (EAKF) to update predictions of leaf area index (LAI) and leaf extension using tower-based photosynthetically active radiation (PAR) and moderate resolution imaging spectrometer (MODIS) data for 2002-2005 at Willow Creek, Wisconsin, USA, a mature, even-aged, northern hardwood, deciduous forest. The ecosystem demography model version 2 (ED2) was used as the prediction model, forced by offline climate data. EAKF successfully incorporated information from both the observations and model predictions weighted by their respective uncertainties. The resulting. estimate reproduced the observed leaf phenological cycle in the spring and the fall better than a parametric model prediction. These results indicate that during spring the observations contribute most in determining the correct bud-burst date, after which the model performs well, but accurately modeling fall leaf senesce requires continuous model updating from observations. While the predicted net ecosystem exchange (NEE) of CO2 precedes tower observations and unassimilated model predictions in the spring, overall the prediction follows observed NEE better than the model alone. Our results show state data assimilation successfully simulates the evolution of plant leaf phenology and improves model predictions of forest NEE.

Price-cap Regulation, Uncertainty and the Price Evolution of New Pharmaceuticals.

PubMed

Shajarizadeh, Ali; Hollis, Aidan

2015-08-01

This paper examines the effect of the regulations restricting price increases on the evolution of pharmaceutical prices. A novel theoretical model shows that this policy leads firms to price new drugs with uncertain demand above the expected value initially. Price decreases after drug launch are more likely, the higher the uncertainty. We empirically test the model's predictions using data from the Canadian pharmaceutical market. The level of uncertainty is shown to play a crucial role in drug pricing strategies. © 2014 The Authors. Health Economics Published by John Wiley & Sons Ltd.

Numerical simulation of elasto-plastic deformation of composites: evolution of stress microfields and implications for homogenization models

NASA Astrophysics Data System (ADS)

González, C.; Segurado, J.; LLorca, J.

2004-07-01

The deformation of a composite made up of a random and homogeneous dispersion of elastic spheres in an elasto-plastic matrix was simulated by the finite element analysis of three-dimensional multiparticle cubic cells with periodic boundary conditions. "Exact" results (to a few percent) in tension and shear were determined by averaging 12 stress-strain curves obtained from cells containing 30 spheres, and they were compared with the predictions of secant homogenization models. In addition, the numerical simulations supplied detailed information of the stress microfields, which was used to ascertain the accuracy and the limitations of the homogenization models to include the nonlinear deformation of the matrix. It was found that secant approximations based on the volume-averaged second-order moment of the matrix stress tensor, combined with a highly accurate linear homogenization model, provided excellent predictions of the composite response when the matrix strain hardening rate was high. This was not the case, however, in composites which exhibited marked plastic strain localization in the matrix. The analysis of the evolution of the matrix stresses revealed that better predictions of the composite behavior can be obtained with new homogenization models which capture the essential differences in the stress carried by the elastic and plastic regions in the matrix at the onset of plastic deformation.

ORION: a web server for protein fold recognition and structure prediction using evolutionary hybrid profiles

PubMed Central

Ghouzam, Yassine; Postic, Guillaume; Guerin, Pierre-Edouard; de Brevern, Alexandre G.; Gelly, Jean-Christophe

2016-01-01

Protein structure prediction based on comparative modeling is the most efficient way to produce structural models when it can be performed. ORION is a dedicated webserver based on a new strategy that performs this task. The identification by ORION of suitable templates is performed using an original profile-profile approach that combines sequence and structure evolution information. Structure evolution information is encoded into profiles using structural features, such as solvent accessibility and local conformation —with Protein Blocks—, which give an accurate description of the local protein structure. ORION has recently been improved, increasing by 5% the quality of its results. The ORION web server accepts a single protein sequence as input and searches homologous protein structures within minutes. Various databases such as PDB, SCOP and HOMSTRAD can be mined to find an appropriate structural template. For the modeling step, a protein 3D structure can be directly obtained from the selected template by MODELLER and displayed with global and local quality model estimation measures. The sequence and the predicted structure of 4 examples from the CAMEO server and a recent CASP11 target from the ‘Hard’ category (T0818-D1) are shown as pertinent examples. Our web server is accessible at http://www.dsimb.inserm.fr/ORION/. PMID:27319297

ORION: a web server for protein fold recognition and structure prediction using evolutionary hybrid profiles.

PubMed

Ghouzam, Yassine; Postic, Guillaume; Guerin, Pierre-Edouard; de Brevern, Alexandre G; Gelly, Jean-Christophe

2016-06-20

Protein structure prediction based on comparative modeling is the most efficient way to produce structural models when it can be performed. ORION is a dedicated webserver based on a new strategy that performs this task. The identification by ORION of suitable templates is performed using an original profile-profile approach that combines sequence and structure evolution information. Structure evolution information is encoded into profiles using structural features, such as solvent accessibility and local conformation -with Protein Blocks-, which give an accurate description of the local protein structure. ORION has recently been improved, increasing by 5% the quality of its results. The ORION web server accepts a single protein sequence as input and searches homologous protein structures within minutes. Various databases such as PDB, SCOP and HOMSTRAD can be mined to find an appropriate structural template. For the modeling step, a protein 3D structure can be directly obtained from the selected template by MODELLER and displayed with global and local quality model estimation measures. The sequence and the predicted structure of 4 examples from the CAMEO server and a recent CASP11 target from the 'Hard' category (T0818-D1) are shown as pertinent examples. Our web server is accessible at http://www.dsimb.inserm.fr/ORION/.

Can beaches survive climate change?

USGS Publications Warehouse

Vitousek, Sean; Barnard, Patrick L.; Limber, Patrick W.

2017-01-01

Anthropogenic climate change is driving sea level rise, leading to numerous impacts on the coastal zone, such as increased coastal flooding, beach erosion, cliff failure, saltwater intrusion in aquifers, and groundwater inundation. Many beaches around the world are currently experiencing chronic erosion as a result of gradual, present-day rates of sea level rise (about 3 mm/year) and human-driven restrictions in sand supply (e.g., harbor dredging and river damming). Accelerated sea level rise threatens to worsen coastal erosion and challenge the very existence of natural beaches throughout the world. Understanding and predicting the rates of sea level rise and coastal erosion depends on integrating data on natural systems with computer simulations. Although many computer modeling approaches are available to simulate shoreline change, few are capable of making reliable long-term predictions needed for full adaption or to enhance resilience. Recent advancements have allowed convincing decadal to centennial-scale predictions of shoreline evolution. For example, along 500 km of the Southern California coast, a new model featuring data assimilation predicts that up to 67% of beaches may completely erode by 2100 without large-scale human interventions. In spite of recent advancements, coastal evolution models must continue to improve in their theoretical framework, quantification of accuracy and uncertainty, computational efficiency, predictive capability, and integration with observed data, in order to meet the scientific and engineering challenges produced by a changing climate.

The Role of Small-Scale Processes in Solar Active Region Decay

NASA Astrophysics Data System (ADS)

Meyer, Karen; Mackay, Duncan

2017-08-01

Active regions are locations of intense magnetic activity on the Sun, whose evolution can result in highly energetic eruptive phenomena such as solar flares and coronal mass ejections (CMEs). Therefore, fast and accurate simulation of their evolution and decay is essential in the prediction of Space Weather events. In this talk we present initial results from our new model for the photospheric evolution of active region magnetic fields. Observations show that small-scale processes appear to play a role in the dispersal and decay of solar active regions, for example through cancellation at the boundary of sunspot outflows and erosion of flux by surrounding convective cells. Our active region model is coupled to our existing model for the evolution of small-scale photospheric magnetic features. Focusing first on the active region decay phase, we consider the evolution of its magnetic field due to both large-scale (e.g. differential rotation) and small-scale processes, such as its interaction with surrounding small-scale magnetic features and convective flows.This project is funded by The Carnegie Trust for the Universities of Scotland, through their Research Incentives Grant scheme.

Introduction to Galactic Chemical Evolution

NASA Astrophysics Data System (ADS)

Matteucci, Francesca

2016-04-01

In this lecture I will introduce the concept of galactic chemical evolution, namely the study of how and where the chemical elements formed and how they were distributed in the stars and gas in galaxies. The main ingredients to build models of galactic chemical evolution will be described. They include: initial conditions, star formation history, stellar nucleosynthesis and gas flows in and out of galaxies. Then some simple analytical models and their solutions will be discussed together with the main criticisms associated to them. The yield per stellar generation will be defined and the hypothesis of instantaneous recycling approximation will be critically discussed. Detailed numerical models of chemical evolution of galaxies of different morphological type, able to follow the time evolution of the abundances of single elements, will be discussed and their predictions will be compared to observational data. The comparisons will include stellar abundances as well as interstellar medium ones, measured in galaxies. I will show how, from these comparisons, one can derive important constraints on stellar nucleosynthesis and galaxy formation mechanisms. Most of the concepts described in this lecture can be found in the monograph by Matteucci (2012).

Non-adaptive plasticity potentiates rapid adaptive evolution of gene expression in nature.

PubMed

Ghalambor, Cameron K; Hoke, Kim L; Ruell, Emily W; Fischer, Eva K; Reznick, David N; Hughes, Kimberly A

2015-09-17

Phenotypic plasticity is the capacity for an individual genotype to produce different phenotypes in response to environmental variation. Most traits are plastic, but the degree to which plasticity is adaptive or non-adaptive depends on whether environmentally induced phenotypes are closer or further away from the local optimum. Existing theories make conflicting predictions about whether plasticity constrains or facilitates adaptive evolution. Debate persists because few empirical studies have tested the relationship between initial plasticity and subsequent adaptive evolution in natural populations. Here we show that the direction of plasticity in gene expression is generally opposite to the direction of adaptive evolution. We experimentally transplanted Trinidadian guppies (Poecilia reticulata) adapted to living with cichlid predators to cichlid-free streams, and tested for evolutionary divergence in brain gene expression patterns after three to four generations. We find 135 transcripts that evolved parallel changes in expression within the replicated introduction populations. These changes are in the same direction exhibited in a native cichlid-free population, suggesting rapid adaptive evolution. We find 89% of these transcripts exhibited non-adaptive plastic changes in expression when the source population was reared in the absence of predators, as they are in the opposite direction to the evolved changes. By contrast, the remaining transcripts exhibiting adaptive plasticity show reduced population divergence. Furthermore, the most plastic transcripts in the source population evolved reduced plasticity in the introduction populations, suggesting strong selection against non-adaptive plasticity. These results support models predicting that adaptive plasticity constrains evolution, whereas non-adaptive plasticity potentiates evolution by increasing the strength of directional selection. The role of non-adaptive plasticity in evolution has received relatively little attention; however, our results suggest that it may be an important mechanism that predicts evolutionary responses to new environments.

Tracing the evolution of the Galactic bulge with chemodynamical modelling of alpha-elements

NASA Astrophysics Data System (ADS)

Friaça, A. C. S.; Barbuy, B.

2017-02-01

Context. Galactic bulge abundances can be best understood as indicators of bulge formation and nucleosynthesis processes by comparing them with chemo-dynamical evolution models. Aims: The aim of this work is to study the abundances of alpha-elements in the Galactic bulge, including a revision of the oxygen abundance in a sample of 56 bulge red giants. Methods: Literature abundances for O, Mg, Si, Ca and Ti in Galactic bulge stars are compared with chemical evolution models. For oxygen in particular, we reanalysed high-resolution spectra obtained using FLAMES+UVES on the Very Large Telescope, now taking each star's carbon abundances, derived from CI and C2 lines, into account simultaneously. Results: We present a chemical evolution model of alpha-element enrichment in a massive spheroid that represents a typical classical bulge evolution. The code includes multi-zone chemical evolution coupled with hydrodynamics of the gas. Comparisons between the model predictions and the abundance data suggest a typical bulge formation timescale of 1-2 Gyr. The main constraint on the bulge evolution is provided by the O data from analyses that have taken the C abundance and dissociative equilibrium into account. Mg, Si, Ca and Ti trends are well reproduced, whereas the level of overabundance critically depends on the adopted nucleosynthesis prescriptions. Observations collected both at the European Southern Observatory, Paranal, Chile (ESO programmes 71.B-0617A, 73.B0074A, and GTO 71.B-0196)

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.

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.

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

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

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.

Forward and backward evolution of the Calhoun CZO: the effect of natural and anthropogenic disturbances

NASA Astrophysics Data System (ADS)

Bonetti, S.; Porporato, A. M.

2017-12-01

The time evolution of a landscape topography through erosional and depositional mechanisms is modified by both human and natural disturbances. This is particularly evident in the Calhoun Critical Zone Observatory, where decades of land-use resulted in a distinct topography with gullies, interfluves, hillslopes and significantly eroded areas. Understanding the role of different geomorphological processes that led to these conditions is crucial to reconstruct sediment and soil carbon fluxes, predict critical conditions of landscape degradation, and implement strategies of land recovery. To model these dynamics, an analytical theory of the drainage area (which represents a surrogate for water surface runoff responsible for fluvial incision) is used to evolve ridge and valley lines. Furthermore, the coupled dynamics of surface water runoff and landscape evolution is analyzed theoretically and numerically to detect thresholds leading to either stable landscape configurations or critical conditions of land erosion. Observed erosional cycles due to vegetation disturbances are explored and used to predict future evolutions under various levels of anthropogenic disturbance.

Coarsening Kinetics and Morphological Evolution in a Two-Phase Titanium Alloy During Heat Treatment

NASA Astrophysics Data System (ADS)

Xu, Jianwei; Zeng, Weidong; Jia, Zhiqiang; Sun, Xin; Zhao, Yawei

2016-03-01

The effects of alpha/beta heat treatment on microstructure evolution of Ti-17 alloy with a lamellar colony structure are established. Heat treatment experiments are conducted at 1103 or 1063 K for times ranging from 10 min to 8 h. The main features of microstructure evolution during heat treatment comprise static globularization and coarsening of primary alpha phase. Such behaviors can be accelerated by higher heat treatment temperature. Furthermore, globularization and coarsening behaviors show a faster rate at higher prestrain. In order to better understand the microstructure evolution of Ti-17 alloy during alpha/beta heat treatment, static globularization and coarsening behaviors are modeled in the theoretical frame of the Johnson-Mehl-Avarmi-Kolmogorov (JMAK) and Lifshitz-Slyozov-Wagner (LSW) theories, respectively. The JMAK and LSW kinetics parameters are derived under different experimental conditions. Agreements between measurements and predictions are found, indicating that the JMAK and LSW theories can be used to predict and trace static globularization and coarsening processes of Ti-17 alloy during alpha/beta heat treatment.

Probabilistic prediction of outbreaks of meningococcus W-135 infections over the next few years in Spain

NASA Astrophysics Data System (ADS)

Acedo, L.; Burgos, C.; Cortés, J.-C.; Villanueva, R.-J.

2017-11-01

The genogroups of meningococcal and other bacteria are in competition in the ecosystem they form with the human hosts. Changes in vaccination strategies, prophylactic measures or usual habits, may also change the distribution of the genogroups in the ecosystem but, usually, this competition is ignored in most epidemiological models, despite it can be highly influential in the evolution of infection diseases and outbreaks. Our goal is to propose a susceptible-carrier-susceptible (SCS) epidemiological model to determine the percentage of carriers in the population, and introduce a fractional Lotka-Volterra competition model to describe the evolution of the meningococcal genogroups in Spain among the carriers. Using data from the distribution of the genogroups in Spain in 2011 and 2012, we find the model parameters and their uncertainties according to a probabilistic fitting approach. On this basis, we predict the evolution of the carriers of the different genogroups over the next few years and, in particular, the percentage of carriers of meningococcus W-135 with a 95% confidence interval. Then, we estimate the probability of having a possible outbreak of meningococcus W-135 in Spain over the next few years. According to our model and, under the present conditions, the risk of a serious outbreak of W-135 in Spain in the next 3 years is below 0 . 3%.

Cancer Evolution: Mathematical Models and Computational Inference

PubMed Central

Beerenwinkel, Niko; Schwarz, Roland F.; Gerstung, Moritz; Markowetz, Florian

2015-01-01

Cancer is a somatic evolutionary process characterized by the accumulation of mutations, which contribute to tumor growth, clinical progression, immune escape, and drug resistance development. Evolutionary theory can be used to analyze the dynamics of tumor cell populations and to make inference about the evolutionary history of a tumor from molecular data. We review recent approaches to modeling the evolution of cancer, including population dynamics models of tumor initiation and progression, phylogenetic methods to model the evolutionary relationship between tumor subclones, and probabilistic graphical models to describe dependencies among mutations. Evolutionary modeling helps to understand how tumors arise and will also play an increasingly important prognostic role in predicting disease progression and the outcome of medical interventions, such as targeted therapy. PMID:25293804

Simulation and experimental comparison of the thermo-mechanical history and 3D microstructure evolution of 304L stainless steel tubes manufactured using LENS

NASA Astrophysics Data System (ADS)

Johnson, Kyle L.; Rodgers, Theron M.; Underwood, Olivia D.; Madison, Jonathan D.; Ford, Kurtis R.; Whetten, Shaun R.; Dagel, Daryl J.; Bishop, Joseph E.

2018-05-01

Additive manufacturing enables the production of previously unachievable designs in conjunction with time and cost savings. However, spatially and temporally fluctuating thermal histories can lead to residual stress states and microstructural variations that challenge conventional assumptions used to predict part performance. Numerical simulations offer a viable way to explore the root causes of these characteristics, and can provide insight into methods of controlling them. Here, the thermal history of a 304L stainless steel cylinder produced using the Laser Engineered Net Shape process is simulated using finite element analysis (FEA). The resultant thermal history is coupled to both a solid mechanics FEA simulation to predict residual stress and a kinetic Monte Carlo model to predict the three-dimensional grain structure evolution. Experimental EBSD measurements of grain structure and in-process infrared thermal data are compared to the predictions.

Simulation and experimental comparison of the thermo-mechanical history and 3D microstructure evolution of 304L stainless steel tubes manufactured using LENS

NASA Astrophysics Data System (ADS)

Johnson, Kyle L.; Rodgers, Theron M.; Underwood, Olivia D.; Madison, Jonathan D.; Ford, Kurtis R.; Whetten, Shaun R.; Dagel, Daryl J.; Bishop, Joseph E.

2017-12-01

Additive manufacturing enables the production of previously unachievable designs in conjunction with time and cost savings. However, spatially and temporally fluctuating thermal histories can lead to residual stress states and microstructural variations that challenge conventional assumptions used to predict part performance. Numerical simulations offer a viable way to explore the root causes of these characteristics, and can provide insight into methods of controlling them. Here, the thermal history of a 304L stainless steel cylinder produced using the Laser Engineered Net Shape process is simulated using finite element analysis (FEA). The resultant thermal history is coupled to both a solid mechanics FEA simulation to predict residual stress and a kinetic Monte Carlo model to predict the three-dimensional grain structure evolution. Experimental EBSD measurements of grain structure and in-process infrared thermal data are compared to the predictions.

Fluorine in the solar neighborhood: Chemical evolution models

NASA Astrophysics Data System (ADS)

Spitoni, E.; Matteucci, F.; Jönsson, H.; Ryde, N.; Romano, D.

2018-04-01

Context. In light of new observational data related to fluorine abundances in solar neighborhood stars, we present chemical evolution models testing various fluorine nucleosynthesis prescriptions with the aim to best fit those new data. Aim. We consider chemical evolution models in the solar neighborhood testing various nucleosynthesis prescriptions for fluorine production with the aim of reproducing the observed abundance ratios [F/O] versus [O/H] and [F/Fe] versus [Fe/H]. We study in detail the effects of various stellar yields on fluorine production. Methods: We adopted two chemical evolution models: the classical two-infall model, which follows the chemical evolution of halo-thick disk and thin disk phases; and the one-infall model, which is designed only for thin disk evolution. We tested the effects on the predicted fluorine abundance ratios of various nucleosynthesis yield sources, that is, asymptotic giant branch (AGB) stars, Wolf-Rayet (W-R) stars, Type II and Type Ia supernovae, and novae. Results: The fluorine production is dominated by AGB stars but the W-R stars are required to reproduce the trend of the observed data in the solar neighborhood with our chemical evolution models. In particular, the best model both for the two-infall and one-infall cases requires an increase by a factor of 2 of the W-R yields. We also show that the novae, even if their yields are still uncertain, could help to better reproduce the secondary behavior of F in the [F/O] versus [O/H] relation. Conclusions: The inclusion of the fluorine production by W-R stars seems to be essential to reproduce the new observed ratio [F/O] versus [O/H] in the solar neighborhood. Moreover, the inclusion of novae helps to reproduce the observed fluorine secondary behavior substantially.

Present-day Mars' Seismicity Predicted from 3-D Thermal Evolution Models of Interior Dynamics

NASA Astrophysics Data System (ADS)

Knapmeyer, M.; Plesa, A. C.; Golombek, M.

2016-12-01

The InSight (Interior exploration using Seismic Investigations, Geodesy and Heat Transport) mission, to be launched in 2018, will carry the first in-situ seismic and heat flow instruments as well as a precision tracking on Mars. This Discovery-class mission will perform the most comprehensive geophysical investigation of the planet and provide an important baseline to constrain the present-day interior structure and heat budget of the planet, and, in turn, the thermal and chemical evolution of its interior. As the InSight lander will perform the measurements at a single location, numerical simulations of planetary interiors will greatly help to interpret the data in a global context. In this study we have used a series of numerical models of thermal evolution in a 3-D spherical geometry to assess the magnitude of present-day Mars seismicity. Our models assume a fixed crust with a variable thickness as inferred from gravity and topography data, that is enriched in radiogenic heat sources according to the surface abundances inferred from gamma-ray measurements. We test a diversity of parameters by varying the mantle reference viscosity as well as the depth-dependence of the viscosity, considering constant and variable thermal expansivity, varying the crustal thermal conductivity and the size of the core [1]. Our results predict an annual moment release between 1.60 x 1016 Nm and 5.46 x 1018 Nm similar to the values presented previously in [2] and [3]. However, while [2] used a mapping of tectonic surface faults to predict the spatial distribution of epicenters, we derive the distribution from the thermal evolution. Besides the Null-Hypothesis of a uniform distribution and the model of [2], this provides a new, self-consistent, competing hypothesis for both the amount and distribution of seismicity on Mars. [1] Plesa et al., LPSC, 2016 [2] Knapmeyer et al., JGR, 2006 [3] Golombek et al., Science 1992; LPSC 2002

Monogamy and high relatedness do not preferentially favor the evolution of cooperation.

PubMed

Nonacs, Peter

2011-03-04

Phylogenetic analyses strongly associate nonsocial ancestors of cooperatively-breeding or eusocial species with monogamy. Because monogamy creates high-relatedness family groups, kin selection has been concluded to drive the evolution of cooperative breeding (i.e., the monogamy hypothesis). Although kin selection is criticized as inappropriate for modeling and predicting the evolution of cooperation, there are no examples where specific inclusive fitness-based predictions are intrinsically wrong. The monogamy hypothesis may be the first case of such a flawed calculation. A simulation model mutated helping alleles into non-cooperative populations where females mated either once or multiply. Although multiple mating produces sibling broods of lower relatedness, it also increases the likelihood that one offspring will adopt a helper role. Examining this tradeoff showed that under a wide range of conditions polygamy, rather than monogamy, allowed helping to spread more rapidly through populations. Further simulations with mating strategies as heritable traits confirmed that multiple-mating is selectively advantageous. Although cooperation evolves similarly regardless of whether dependent young are close or more distant kin, it does not evolve if they are unrelated. The solitary ancestral species to cooperative breeders may have been predominantly monogamous, but it cannot be concluded that monogamy is a predisposing state for the evolution of helping behavior. Monogamy may simply be coincidental to other more important life history characteristics such as nest defense or sequential provisioning of offspring. The differing predictive outcome from a gene-based model also supports arguments that inclusive fitness formulations poorly model some evolutionary questions. Nevertheless, cooperation only evolves when benefits are provided for kin: helping alleles did not increase in frequency in the absence of potential gains in indirect fitness. The key question, therefore, is not whether kin selection occurs, but how best to elucidate the differing evolutionary advantages of genetic relatedness versus genetic diversity.

Monogamy and high relatedness do not preferentially favor the evolution of cooperation

PubMed Central

2011-01-01

Background Phylogenetic analyses strongly associate nonsocial ancestors of cooperatively-breeding or eusocial species with monogamy. Because monogamy creates high-relatedness family groups, kin selection has been concluded to drive the evolution of cooperative breeding (i.e., the monogamy hypothesis). Although kin selection is criticized as inappropriate for modeling and predicting the evolution of cooperation, there are no examples where specific inclusive fitness-based predictions are intrinsically wrong. The monogamy hypothesis may be the first case of such a flawed calculation. Results A simulation model mutated helping alleles into non-cooperative populations where females mated either once or multiply. Although multiple mating produces sibling broods of lower relatedness, it also increases the likelihood that one offspring will adopt a helper role. Examining this tradeoff showed that under a wide range of conditions polygamy, rather than monogamy, allowed helping to spread more rapidly through populations. Further simulations with mating strategies as heritable traits confirmed that multiple-mating is selectively advantageous. Although cooperation evolves similarly regardless of whether dependent young are close or more distant kin, it does not evolve if they are unrelated. Conclusions The solitary ancestral species to cooperative breeders may have been predominantly monogamous, but it cannot be concluded that monogamy is a predisposing state for the evolution of helping behavior. Monogamy may simply be coincidental to other more important life history characteristics such as nest defense or sequential provisioning of offspring. The differing predictive outcome from a gene-based model also supports arguments that inclusive fitness formulations poorly model some evolutionary questions. Nevertheless, cooperation only evolves when benefits are provided for kin: helping alleles did not increase in frequency in the absence of potential gains in indirect fitness. The key question, therefore, is not whether kin selection occurs, but how best to elucidate the differing evolutionary advantages of genetic relatedness versus genetic diversity. PMID:21375755

Prediction, experimental results and analysis of the ITER TF insert coil quench propagation tests, using the 4C code

NASA Astrophysics Data System (ADS)

Zanino, R.; Bonifetto, R.; Brighenti, A.; Isono, T.; Ozeki, H.; Savoldi, L.

2018-07-01

The ITER toroidal field insert (TFI) coil is a single-layer Nb3Sn solenoid tested in 2016-2017 at the National Institutes for Quantum and Radiological Science and Technology (former JAEA) in Naka, Japan. The TFI, the last in a series of ITER insert coils, was tested in operating conditions relevant for the actual ITER TF coils, inserting it in the borehole of the central solenoid model coil, which provided the background magnetic field. In this paper, we consider the five quench propagation tests that were performed using one or two inductive heaters (IHs) as drivers; out of these, three used just one IH but with increasing delay times, up to 7.5 s, between the quench detection and the TFI current dump. The results of the 4C code prediction of the quench propagation up to the current dump are presented first, based on simulations performed before the tests. We then describe the experimental results, showing good reproducibility. Finally, we compare the 4C code predictions with the measurements, confirming the 4C code capability to accurately predict the quench propagation, and the evolution of total and local voltages, as well as of the hot spot temperature. To the best of our knowledge, such a predictive validation exercise is performed here for the first time for the quench of a Nb3Sn coil. Discrepancies between prediction and measurement are found in the evolution of the jacket temperatures, in the He pressurization and quench acceleration in the late phase of the transient before the dump, as well as in the early evolution of the inlet and outlet He mass flow rate. Based on the lessons learned in the predictive exercise, the model is then refined to try and improve a posteriori (i.e. in interpretive, as opposed to predictive mode) the agreement between simulation and experiment.

Time-programmable drug dosing allows the manipulation, suppression and reversal of antibiotic drug resistance in vitro

NASA Astrophysics Data System (ADS)

Yoshida, Mari; Reyes, Sabrina Galiñanes; Tsuda, Soichiro; Horinouchi, Takaaki; Furusawa, Chikara; Cronin, Leroy

2017-06-01

Multi-drug strategies have been attempted to prolong the efficacy of existing antibiotics, but with limited success. Here we show that the evolution of multi-drug-resistant Escherichia coli can be manipulated in vitro by administering pairs of antibiotics and switching between them in ON/OFF manner. Using a multiplexed cell culture system, we find that switching between certain combinations of antibiotics completely suppresses the development of resistance to one of the antibiotics. Using this data, we develop a simple deterministic model, which allows us to predict the fate of multi-drug evolution in this system. Furthermore, we are able to reverse established drug resistance based on the model prediction by modulating antibiotic selection stresses. Our results support the idea that the development of antibiotic resistance may be potentially controlled via continuous switching of drugs.

The effects of van der Waals attractions on cloud droplet growth by coalescence

NASA Technical Reports Server (NTRS)

Rogers, Jan R.; Davis, Robert H.

1990-01-01

The inclusion of van der Waals attractions in the interaction between cloud droplets has been recently shown to significantly increase the collision efficiencies of the smaller droplets. In the current work, these larger values for the collision efficiencies are used in a population dynamics model of the droplet size distribution evolution with time, in hopes of at least partially resolving the long-standing paradox in cloud microphysics that predicted rates of the onset of precipitation are generally much lower than those which are observed. Evolutions of several initial cloud droplet spectra have been tracked in time. Size evolutions are compared as predicted from the use of collision efficiencies computed using two different models to allow for droplet-droplet contact: one which considers slip flow effects only, and one which considers the combined effects of van der Waals forces and slip flow. The rate at which the droplet mass density function shifts to larger droplet sizes is increased by typically 20-25 percent, when collision efficiencies which include van der Waals forces are used.

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.

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.

Bayesian inference of galaxy formation from the K-band luminosity function of galaxies: tensions between theory and observation

NASA Astrophysics Data System (ADS)

Lu, Yu; Mo, H. J.; Katz, Neal; Weinberg, Martin D.

2012-04-01

We conduct Bayesian model inferences from the observed K-band luminosity function of galaxies in the local Universe, using the semi-analytic model (SAM) of galaxy formation introduced in Lu et al. The prior distributions for the 14 free parameters include a large range of possible models. We find that some of the free parameters, e.g. the characteristic scales for quenching star formation in both high-mass and low-mass haloes, are already tightly constrained by the single data set. The posterior distribution includes the model parameters adopted in other SAMs. By marginalizing over the posterior distribution, we make predictions that include the full inferential uncertainties for the colour-magnitude relation, the Tully-Fisher relation, the conditional stellar mass function of galaxies in haloes of different masses, the H I mass function, the redshift evolution of the stellar mass function of galaxies and the global star formation history. Using posterior predictive checking with the available observational results, we find that the model family (i) predicts a Tully-Fisher relation that is curved; (ii) significantly overpredicts the satellite fraction; (iii) vastly overpredicts the H I mass function; (iv) predicts high-z stellar mass functions that have too many low-mass galaxies and too few high-mass ones and (v) predicts a redshift evolution of the stellar mass density and the star formation history that are in moderate disagreement. These results suggest that some important processes are still missing in the current model family, and we discuss a number of possible solutions to solve the discrepancies, such as interactions between galaxies and dark matter haloes, tidal stripping, the bimodal accretion of gas, preheating and a redshift-dependent initial mass function.

Data Based Prediction of Blood Glucose Concentrations Using Evolutionary Methods.

PubMed

Hidalgo, J Ignacio; Colmenar, J Manuel; Kronberger, Gabriel; Winkler, Stephan M; Garnica, Oscar; Lanchares, Juan

2017-08-08

Predicting glucose values on the basis of insulin and food intakes is a difficult task that people with diabetes need to do daily. This is necessary as it is important to maintain glucose levels at appropriate values to avoid not only short-term, but also long-term complications of the illness. Artificial intelligence in general and machine learning techniques in particular have already lead to promising results in modeling and predicting glucose concentrations. In this work, several machine learning techniques are used for the modeling and prediction of glucose concentrations using as inputs the values measured by a continuous monitoring glucose system as well as also previous and estimated future carbohydrate intakes and insulin injections. In particular, we use the following four techniques: genetic programming, random forests, k-nearest neighbors, and grammatical evolution. We propose two new enhanced modeling algorithms for glucose prediction, namely (i) a variant of grammatical evolution which uses an optimized grammar, and (ii) a variant of tree-based genetic programming which uses a three-compartment model for carbohydrate and insulin dynamics. The predictors were trained and tested using data of ten patients from a public hospital in Spain. We analyze our experimental results using the Clarke error grid metric and see that 90% of the forecasts are correct (i.e., Clarke error categories A and B), but still even the best methods produce 5 to 10% of serious errors (category D) and approximately 0.5% of very serious errors (category E). We also propose an enhanced genetic programming algorithm that incorporates a three-compartment model into symbolic regression models to create smoothed time series of the original carbohydrate and insulin time series.

Debris disc constraints on planetesimal formation

NASA Astrophysics Data System (ADS)

Krivov, Alexander V.; Ide, Aljoscha; Löhne, Torsten; Johansen, Anders; Blum, Jürgen

2018-02-01

Two basic routes for planetesimal formation have been proposed over the last decades. One is a classical `slow-growth' scenario. Another one is particle concentration models, in which small pebbles are concentrated locally and then collapse gravitationally to form planetesimals. Both types of models make certain predictions for the size spectrum and internal structure of newly born planetesimals. We use these predictions as input to simulate collisional evolution of debris discs left after the gas dispersal. The debris disc emission as a function of a system's age computed in these simulations is compared with several Spitzer and Herschel debris disc surveys around A-type stars. We confirm that the observed brightness evolution for the majority of discs can be reproduced by classical models. Further, we find that it is equally consistent with the size distribution of planetesimals predicted by particle concentration models - provided the objects are loosely bound `pebble piles' as these models also predict. Regardless of the assumed planetesimal formation mechanism, explaining the brightest debris discs in the samples uncovers a `disc mass problem'. To reproduce such discs by collisional simulations, a total mass of planetesimals of up to ˜1000 Earth masses is required, which exceeds the total mass of solids available in the protoplanetary progenitors of debris discs. This may indicate that stirring was delayed in some of the bright discs, that giant impacts occurred recently in some of them, that some systems may be younger than previously thought or that non-collisional processes contribute significantly to the dust production.

Simple stochastic birth and death models of genome evolution: was there enough time for us to evolve?

PubMed

Karev, Georgy P; Wolf, Yuri I; Koonin, Eugene V

2003-10-12

The distributions of many genome-associated quantities, including the membership of paralogous gene families can be approximated with power laws. We are interested in developing mathematical models of genome evolution that adequately account for the shape of these distributions and describe the evolutionary dynamics of their formation. We show that simple stochastic models of genome evolution lead to power-law asymptotics of protein domain family size distribution. These models, called Birth, Death and Innovation Models (BDIM), represent a special class of balanced birth-and-death processes, in which domain duplication and deletion rates are asymptotically equal up to the second order. The simplest, linear BDIM shows an excellent fit to the observed distributions of domain family size in diverse prokaryotic and eukaryotic genomes. However, the stochastic version of the linear BDIM explored here predicts that the actual size of large paralogous families is reached on an unrealistically long timescale. We show that introduction of non-linearity, which might be interpreted as interaction of a particular order between individual family members, allows the model to achieve genome evolution rates that are much better compatible with the current estimates of the rates of individual duplication/loss events.

SaLEM (v1.0) - the Soil and Landscape Evolution Model (SaLEM) for simulation of regolith depth in periglacial environments

NASA Astrophysics Data System (ADS)

Bock, Michael; Conrad, Olaf; Günther, Andreas; Gehrt, Ernst; Baritz, Rainer; Böhner, Jürgen

2018-04-01

We propose the implementation of the Soil and Landscape Evolution Model (SaLEM) for the spatiotemporal investigation of soil parent material evolution following a lithologically differentiated approach. Relevant parts of the established Geomorphic/Orogenic Landscape Evolution Model (GOLEM) have been adapted for an operational Geographical Information System (GIS) tool within the open-source software framework System for Automated Geoscientific Analyses (SAGA), thus taking advantage of SAGA's capabilities for geomorphometric analyses. The model is driven by palaeoclimatic data (temperature, precipitation) representative of periglacial areas in northern Germany over the last 50 000 years. The initial conditions have been determined for a test site by a digital terrain model and a geological model. Weathering, erosion and transport functions are calibrated using extrinsic (climatic) and intrinsic (lithologic) parameter data. First results indicate that our differentiated SaLEM approach shows some evidence for the spatiotemporal prediction of important soil parental material properties (particularly its depth). Future research will focus on the validation of the results against field data, and the influence of discrete events (mass movements, floods) on soil parent material formation has to be evaluated.

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.

Progress on Complex Langevin simulations of a finite density matrix model for QCD

NASA Astrophysics Data System (ADS)

Bloch, Jacques; Glesaaen, Jonas; Verbaarschot, Jacobus; Zafeiropoulos, Savvas

2018-03-01

We study the Stephanov model, which is an RMT model for QCD at finite density, using the Complex Langevin algorithm. Naive implementation of the algorithm shows convergence towards the phase quenched or quenched theory rather than to intended theory with dynamical quarks. A detailed analysis of this issue and a potential resolution of the failure of this algorithm are discussed. We study the effect of gauge cooling on the Dirac eigenvalue distribution and time evolution of the norm for various cooling norms, which were specifically designed to remove the pathologies of the complex Langevin evolution. The cooling is further supplemented with a shifted representation for the random matrices. Unfortunately, none of these modifications generate a substantial improvement on the complex Langevin evolution and the final results still do not agree with the analytical predictions.

Laboratory evolution of the migratory polymorphism in the sand cricket: combining physiology with quantitative genetics.

PubMed

Roff, Derek A; Fairbairn, Daphne J

2007-01-01

Predicting evolutionary change is the central goal of evolutionary biology because it is the primary means by which we can test evolutionary hypotheses. In this article, we analyze the pattern of evolutionary change in a laboratory population of the wing-dimorphic sand cricket Gryllus firmus resulting from relaxation of selection favoring the migratory (long-winged) morph. Based on a well-characterized trade-off between fecundity and flight capability, we predict that evolution in the laboratory environment should result in a reduction in the proportion of long-winged morphs. We also predict increased fecundity and reduced functionality and weight of the major flight muscles in long-winged females but little change in short-winged (flightless) females. Based on quantitative genetic theory, we predict that the regression equation describing the trade-off between ovary weight and weight of the major flight muscles will show a change in its intercept but not in its slope. Comparisons across generations verify all of these predictions. Further, using values of genetic parameters estimated from previous studies, we show that a quantitative genetic simulation model can account for not only the qualitative changes but also the evolutionary trajectory. These results demonstrate the power of combining quantitative genetic and physiological approaches for understanding the evolution of complex traits.

FireProt: Energy- and Evolution-Based Computational Design of Thermostable Multiple-Point Mutants.

PubMed

Bednar, David; Beerens, Koen; Sebestova, Eva; Bendl, Jaroslav; Khare, Sagar; Chaloupkova, Radka; Prokop, Zbynek; Brezovsky, Jan; Baker, David; Damborsky, Jiri

2015-11-01

There is great interest in increasing proteins' stability to enhance their utility as biocatalysts, therapeutics, diagnostics and nanomaterials. Directed evolution is a powerful, but experimentally strenuous approach. Computational methods offer attractive alternatives. However, due to the limited reliability of predictions and potentially antagonistic effects of substitutions, only single-point mutations are usually predicted in silico, experimentally verified and then recombined in multiple-point mutants. Thus, substantial screening is still required. Here we present FireProt, a robust computational strategy for predicting highly stable multiple-point mutants that combines energy- and evolution-based approaches with smart filtering to identify additive stabilizing mutations. FireProt's reliability and applicability was demonstrated by validating its predictions against 656 mutations from the ProTherm database. We demonstrate that thermostability of the model enzymes haloalkane dehalogenase DhaA and γ-hexachlorocyclohexane dehydrochlorinase LinA can be substantially increased (ΔTm = 24°C and 21°C) by constructing and characterizing only a handful of multiple-point mutants. FireProt can be applied to any protein for which a tertiary structure and homologous sequences are available, and will facilitate the rapid development of robust proteins for biomedical and biotechnological applications.

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

DOE PAGES

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

2015-12-10

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

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

Constraining Gamma-Ray Pulsar Gap Models with a Simulated Pulsar Population

NASA Technical Reports Server (NTRS)

Pierbattista, Marco; Grenier, I. A.; Harding, A. K.; Gonthier, P. L.

2012-01-01

With the large sample of young gamma-ray pulsars discovered by the Fermi Large Area Telescope (LAT), population synthesis has become a powerful tool for comparing their collective properties with model predictions. We synthesised a pulsar population based on a radio emission model and four gamma-ray gap models (Polar Cap, Slot Gap, Outer Gap, and One Pole Caustic). Applying gamma-ray and radio visibility criteria, we normalise the simulation to the number of detected radio pulsars by a select group of ten radio surveys. The luminosity and the wide beams from the outer gaps can easily account for the number of Fermi detections in 2 years of observations. The wide slot-gap beam requires an increase by a factor of 10 of the predicted luminosity to produce a reasonable number of gamma-ray pulsars. Such large increases in the luminosity may be accommodated by implementing offset polar caps. The narrow polar-cap beams contribute at most only a handful of LAT pulsars. Using standard distributions in birth location and pulsar spin-down power (E), we skew the initial magnetic field and period distributions in a an attempt to account for the high E Fermi pulsars. While we compromise the agreement between simulated and detected distributions of radio pulsars, the simulations fail to reproduce the LAT findings: all models under-predict the number of LAT pulsars with high E , and they cannot explain the high probability of detecting both the radio and gamma-ray beams at high E. The beaming factor remains close to 1.0 over 4 decades in E evolution for the slot gap whereas it significantly decreases with increasing age for the outer gaps. The evolution of the enhanced slot-gap luminosity with E is compatible with the large dispersion of gamma-ray luminosity seen in the LAT data. The stronger evolution predicted for the outer gap, which is linked to the polar cap heating by the return current, is apparently not supported by the LAT data. The LAT sample of gamma-ray pulsars therefore provides a fresh perspective on the early evolution of the luminosity and beam width of the gamma-ray emission from young pulsars, calling for thin and more luminous gaps.

The fast debris evolution model

NASA Astrophysics Data System (ADS)

Lewis, H. G.; Swinerd, G. G.; Newland, R. J.; Saunders, A.

2009-09-01

The 'particles-in-a-box' (PIB) model introduced by Talent [Talent, D.L. Analytic model for orbital debris environmental management. J. Spacecraft Rocket, 29 (4), 508-513, 1992.] removed the need for computer-intensive Monte Carlo simulation to predict the gross characteristics of an evolving debris environment. The PIB model was described using a differential equation that allows the stability of the low Earth orbit (LEO) environment to be tested by a straightforward analysis of the equation's coefficients. As part of an ongoing research effort to investigate more efficient approaches to evolutionary modelling and to develop a suite of educational tools, a new PIB model has been developed. The model, entitled Fast Debris Evolution (FADE), employs a first-order differential equation to describe the rate at which new objects ⩾10 cm are added and removed from the environment. Whilst Talent [Talent, D.L. Analytic model for orbital debris environmental management. J. Spacecraft Rocket, 29 (4), 508-513, 1992.] based the collision theory for the PIB approach on collisions between gas particles and adopted specific values for the parameters of the model from a number of references, the form and coefficients of the FADE model equations can be inferred from the outputs of future projections produced by high-fidelity models, such as the DAMAGE model. The FADE model has been implemented as a client-side, web-based service using JavaScript embedded within a HTML document. Due to the simple nature of the algorithm, FADE can deliver the results of future projections immediately in a graphical format, with complete user-control over key simulation parameters. Historical and future projections for the ⩾10 cm LEO debris environment under a variety of different scenarios are possible, including business as usual, no future launches, post-mission disposal and remediation. A selection of results is presented with comparisons with predictions made using the DAMAGE environment model. The results demonstrate that the FADE model is able to capture comparable time-series of collisions and number of objects as predicted by DAMAGE in several scenarios. Further, and perhaps more importantly, its speed and flexibility allows the user to explore and understand the evolution of the space debris environment.

Prediction of Indian Summer-Monsoon Onset Variability: A Season in Advance.

PubMed

Pradhan, Maheswar; Rao, A Suryachandra; Srivastava, Ankur; Dakate, Ashish; Salunke, Kiran; Shameera, K S

2017-10-27

Monsoon onset is an inherent transient phenomenon of Indian Summer Monsoon and it was never envisaged that this transience can be predicted at long lead times. Though onset is precipitous, its variability exhibits strong teleconnections with large scale forcing such as ENSO and IOD and hence may be predictable. Despite of the tremendous skill achieved by the state-of-the-art models in predicting such large scale processes, the prediction of monsoon onset variability by the models is still limited to just 2-3 weeks in advance. Using an objective definition of onset in a global coupled ocean-atmosphere model, it is shown that the skillful prediction of onset variability is feasible under seasonal prediction framework. The better representations/simulations of not only the large scale processes but also the synoptic and intraseasonal features during the evolution of monsoon onset are the comprehensions behind skillful simulation of monsoon onset variability. The changes observed in convection, tropospheric circulation and moisture availability prior to and after the onset are evidenced in model simulations, which resulted in high hit rate of early/delay in monsoon onset in the high resolution model.

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.

Predicting galaxy star formation rates via the co-evolution of galaxies and haloes

NASA Astrophysics Data System (ADS)

Watson, Douglas F.; Hearin, Andrew P.; Berlind, Andreas A.; Becker, Matthew R.; Behroozi, Peter S.; Skibba, Ramin A.; Reyes, Reinabelle; Zentner, Andrew R.; van den Bosch, Frank C.

2015-01-01

In this paper, we test the age matching hypothesis that the star formation rate (SFR) of a galaxy of fixed stellar mass is determined by its dark matter halo formation history, e.g. more quiescent galaxies reside in older haloes. We present new Sloan Digital Sky Survey measurements of the galaxy two-point correlation function and galaxy-galaxy lensing as a function of stellar mass and SFR, separated into quenched and star-forming galaxy samples to test this simple model. We find that our age matching model is in excellent agreement with these new measurements. We also find that our model is able to predict: (1) the relative SFRs of central and satellite galaxies, (2) the SFR dependence of the radial distribution of satellite galaxy populations within galaxy groups, rich groups, and clusters and their surrounding larger scale environments, and (3) the interesting feature that the satellite quenched fraction as a function of projected radial distance from the central galaxy exhibits an ˜r-.15 slope, independent of environment. These accurate predictions are intriguing given that we do not explicitly model satellite-specific processes after infall, and that in our model the virial radius does not mark a special transition region in the evolution of a satellite. The success of the model suggests that present-day galaxy SFR is strongly correlated with halo mass assembly history.

Constraints on the Evolution of the Galaxy Stellar Mass Function I: Role of Star Formation, Mergers, and Stellar Stripping

NASA Astrophysics Data System (ADS)

Contini, E.; Kang, Xi; Romeo, A. D.; Xia, Q.

2017-03-01

We study the connection between the observed star formation rate-stellar mass (SFR-M *) relation and the evolution of the stellar mass function (SMF) by means of a subhalo abundance matching technique coupled to merger trees extracted from an N-body simulation. Our approach, which considers both galaxy mergers and stellar stripping, is to force the model to match the observed SMF at redshift z> 2, and let it evolve down to the present time according to the observed SFR-M * relation. In this study, we use two different sets of SMFs and two SFR-M * relations: a simple power law and a relation with a mass-dependent slope. Our analysis shows that the evolution of the SMF is more consistent with an SFR-M * relation with a mass-dependent slope, in agreement with predictions from other models of galaxy evolution and recent observations. In order to fully and realistically describe the evolution of the SMF, both mergers and stellar stripping must be considered, and we find that both have almost equal effects on the evolution of SMF at the massive end. Taking into account the systematic uncertainties in the observed data, the high-mass end of the SMF obtained by considering stellar stripping results in good agreement with recent observational data from the Sloan Digital Sky Survey. At {log} {M}* < 11.2, our prediction at z = 0.1 is close to Li & White data, but the high-mass end ({log} {M}* > 11.2) is in better agreement with D’Souza et al. data which account for more massive galaxies.

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.

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.

Numerically calibrated model for propagation of a relativistic unmagnetized jet in dense media

NASA Astrophysics Data System (ADS)

Harrison, Richard; Gottlieb, Ore; Nakar, Ehud

2018-06-01

Relativistic jets reside in high-energy astrophysical systems of all scales. Their interaction with the surrounding media is critical as it determines the jet evolution, observable signature, and feedback on the environment. During its motion, the interaction of the jet with the ambient media inflates a highly pressurized cocoon, which under certain conditions collimates the jet and strongly affects its propagation. Recently, Bromberg et al. derived a general simplified (semi-)analytic solution for the evolution of the jet and the cocoon in case of an unmagnetized jet that propagates in a medium with a range of density profiles. In this work we use a large suite of 2D and 3D relativistic hydrodynamic simulations in order to test the validity and accuracy of this model. We discuss the similarities and differences between the analytic model and numerical simulations and also, to some extent, between 2D and 3D simulations. Our main finding is that although the analytic model is highly simplified, it properly predicts the evolution of the main ingredients of the jet-cocoon system, including its temporal evolution and the transition between various regimes (e.g. collimated to uncollimated). The analytic solution predicts a jet head velocity that is faster by a factor of about 3 compared to the simulations, as long as the head velocity is Newtonian. We use the results of the simulations to calibrate the analytic model which significantly increases its accuracy. We provide an applet that calculates semi-analytically the propagation of a jet in an arbitrary density profile defined by the user at http://www.astro.tau.ac.il/˜ore/propagation.html.

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

NASA Technical Reports Server (NTRS)

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

1993-01-01

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

Improvisation in evolution of genes and genomes: whose structure is it anyway?

PubMed

Shakhnovich, Boris E; Shakhnovich, Eugene I

2008-06-01

Significant progress has been made in recent years in a variety of seemingly unrelated fields such as sequencing, protein structure prediction, and high-throughput transcriptomics and metabolomics. At the same time, new microscopic models have been developed that made it possible to analyze the evolution of genes and genomes from first principles. The results from these efforts enable, for the first time, a comprehensive insight into the evolution of complex systems and organisms on all scales--from sequences to organisms and populations. Every newly sequenced genome uncovers new genes, families, and folds. Where do these new genes come from? How do gene duplication and subsequent divergence of sequence and structure affect the fitness of the organism? What role does regulation play in the evolution of proteins and folds? Emerging synergism between data and modeling provides first robust answers to these questions.

Evolution and prognosis of long intensive care unit stay patients suffering a deterioration: A multicenter study.

PubMed

Hernández-Tejedor, Alberto; Cabré-Pericas, Lluís; Martín-Delgado, María Cruz; Leal-Micharet, Ana María; Algora-Weber, Alejandro

2015-06-01

The prognosis of a patient who deteriorates during a prolonged intensive care unit (ICU) stay is difficult to predict. We analyze the prognostic value of the serialized Sequential Organ Failure Assessment (SOFA) score and other variables in the early days after a complication and to build a new predictive score. EPIPUSE (Evolución y pronóstico de los pacientes con ingreso prolongado en UCI que sufren un empeoramiento, Evolution and prognosis of long intensive care unit stay patients suffering a deterioration) study is a prospective, observational study during a 3-month recruitment period in 75 Spanish ICUs. We focused on patients admitted in the ICU for 7 days or more with complications of adverse events that involve organ dysfunction impairment. Demographics, clinical variables, and serialized SOFA after a supervening clinical deterioration were recorded. Univariate and multivariate analyses were performed, and a predictive model was created with the most discriminating variables. We included 589 patients who experienced 777 cases of severe complication or adverse event. The entire sample was randomly divided into 2 subsamples, one for development purposes (528 cases) and the other for validation (249 cases). The predictive model maximizing specificity is calculated by minimum SOFA + 2 * cardiovascular risk factors + 2 * history of any oncologic disease or immunosuppressive treatment + 3 * dependence for basic activities of daily living. The area under the receiver operating characteristic curve is 0.82. A 14-point cutoff has a positive predictive value of 100% (92.7%-100%) and negative predictive value of 51% (46.4%-55.5%) for death. EPIPUSE model can predict mortality with a specificity and positive predictive value of 99% in some groups of patients. Copyright © 2015 Elsevier Inc. All rights reserved.

Hidden Markov models for evolution and comparative genomics analysis.

PubMed

Bykova, Nadezda A; Favorov, Alexander V; Mironov, Andrey A

2013-01-01

The problem of reconstruction of ancestral states given a phylogeny and data from extant species arises in a wide range of biological studies. The continuous-time Markov model for the discrete states evolution is generally used for the reconstruction of ancestral states. We modify this model to account for a case when the states of the extant species are uncertain. This situation appears, for example, if the states for extant species are predicted by some program and thus are known only with some level of reliability; it is common for bioinformatics field. The main idea is formulation of the problem as a hidden Markov model on a tree (tree HMM, tHMM), where the basic continuous-time Markov model is expanded with the introduction of emission probabilities of observed data (e.g. prediction scores) for each underlying discrete state. Our tHMM decoding algorithm allows us to predict states at the ancestral nodes as well as to refine states at the leaves on the basis of quantitative comparative genomics. The test on the simulated data shows that the tHMM approach applied to the continuous variable reflecting the probabilities of the states (i.e. prediction score) appears to be more accurate then the reconstruction from the discrete states assignment defined by the best score threshold. We provide examples of applying our model to the evolutionary analysis of N-terminal signal peptides and transcription factor binding sites in bacteria. The program is freely available at http://bioinf.fbb.msu.ru/~nadya/tHMM and via web-service at http://bioinf.fbb.msu.ru/treehmmweb.

Fear and Loving in Las Vegas: Evolution, Emotion, and Persuasion

PubMed Central

Griskevicius, Vladas; Goldstein, Noah J.; Mortensen, Chad R.; Sundie, Jill M.; Cialdini, Robert B.; Kenrick, Douglas T.

2009-01-01

How do arousal-inducing contexts, such as frightening or romantic television programs, influence the effectiveness of basic persuasion heuristics? Different predictions are made by three theoretical models: A general arousal model predicts that arousal should increase effectiveness of heuristics; an affective valence model predicts that effectiveness should depend on whether the context elicits positive or negative affect; an evolutionary model predicts that persuasiveness should depend on both the specific emotion that is elicited and the content of the particular heuristic. Three experiments examined how fear-inducing versus romantic contexts influenced the effectiveness of two widely used heuristics—social proof (e.g., “most popular”) and scarcity (e.g., “limited edition”). Results supported predictions from an evolutionary model, showing that fear can lead scarcity appeals to be counter-persuasive, and that romantic desire can lead social proof appeals to be counter-persuasive. The findings highlight how an evolutionary theoretical approach can lead to novel theoretical and practical marketing insights. PMID:19727416

A model of ecological and evolutionary consequences of color polymorphism.

PubMed

Forsman, Anders; Ahnesjö, Jonas; Caesar, Sofia; Karlsson, Magnus

2008-01-01

We summarize direct and indirect effects on fitness components of animal color pattern and present a synthesis of theories concerning the ecological and evolutionary dynamics of chromatic multiple niche polymorphisms. Previous endeavors have aimed primarily at identifying conditions that promote the evolution and maintenance of polymorphisms. We consider in a conceptual model also the reciprocal influence of color polymorphism on population processes and propose that polymorphism entails selective advantages that may promote the ecological success of polymorphic species. The model begins with an evolutionary branching event from mono- to polymorphic condition that, under the influence of correlational selection, is predicted to promote the evolution of physical integration of coloration and other traits (cf. multi-trait coevolution and complex phenotypes). We propose that the coexistence within a population of alternative ecomorphs with coadapted gene complexes promotes utilization of diverse environmental resources, population stability and persistence, colonization success, and range expansions, and enhances the evolutionary potential and speciation. Conversely, we predict polymorphic populations to be less vulnerable to environmental change and at lower risk of range contractions and extinctions compared with monomorphic populations. We offer brief suggestions as to how these falsifiable predictions may be tested.

Cosmological implications of a large complete quasar sample

PubMed Central

Segal, I. E.; Nicoll, J. F.

1998-01-01

Objective and reproducible determinations of the probabilistic significance levels of the deviations between theoretical cosmological prediction and direct model-independent observation are made for the Large Bright Quasar Sample [Foltz, C., Chaffee, F. H., Hewett, P. C., MacAlpine, G. M., Turnshek, D. A., et al. (1987) Astron. J. 94, 1423–1460]. The Expanding Universe model as represented by the Friedman–Lemaitre cosmology with parameters qo = 0, Λ = 0 denoted as C1 and chronometric cosmology (no relevant adjustable parameters) denoted as C2 are the cosmologies considered. The mean and the dispersion of the apparent magnitudes and the slope of the apparent magnitude–redshift relation are the directly observed statistics predicted. The C1 predictions of these cosmology-independent quantities are deviant by as much as 11σ from direct observation; none of the C2 predictions deviate by >2σ. The C1 deviations may be reconciled with theory by the hypothesis of quasar “evolution,” which, however, appears incapable of being substantiated through direct observation. The excellent quantitative agreement of the C1 deviations with those predicted by C2 without adjustable parameters for the results of analysis predicated on C1 indicates that the evolution hypothesis may well be a theoretical artifact. PMID:9560182

Interaction times change evolutionary outcomes: Two-player matrix games.

PubMed

Křivan, Vlastimil; Cressman, Ross

2017-03-07

Two most influential models of evolutionary game theory are the Hawk-Dove and Prisoner's dilemma models. The Hawk-Dove model explains evolution of aggressiveness, predicting individuals should be aggressive when the cost of fighting is lower than its benefit. As the cost of aggressiveness increases and outweighs benefits, aggressiveness in the population should decrease. Similarly, the Prisoner's dilemma models evolution of cooperation. It predicts that individuals should never cooperate despite cooperation leading to a higher collective fitness than defection. The question is then what are the conditions under which cooperation evolves? These classic matrix games, which are based on pair-wise interactions between two opponents with player payoffs given in matrix form, do not consider the effect that conflict duration has on payoffs. However, interactions between different strategies often take different amounts of time. In this article, we develop a new approach to an old idea that opportunity costs lost while engaged in an interaction affect individual fitness. When applied to the Hawk-Dove and Prisoner's dilemma, our theory that incorporates general interaction times leads to qualitatively different predictions. In particular, not all individuals will behave as Hawks when fighting cost is lower than benefit, and cooperation will evolve in the Prisoner's dilemma. Copyright © 2017 Elsevier Ltd. All rights reserved.

Linkages Between Critical Wedges and Crustal Channels Using 2-D Coupled Thermomechanical Finite Element Models: Implications for Himalayan Orogenic Evolution

NASA Astrophysics Data System (ADS)

Sparks, S. A.; Thigpen, J. R.

2017-12-01

In continental tectonics, questions remain regarding the dominant mechanisms of shortening accommodation during orogen evolution. Two quantitatively-supported models, critical wedge and channel flow, have been applied to the Himalaya and proposed for other large collisional systems. These two models represent fundamentally distinct mechanisms for accommodating shortening in collisional systems and until recently have been viewed as mutually exclusive. While there remains support for these mechanisms being incompatible end-members, in more recent studies it has been proposed that either: (1) both geodynamic mechanisms may operate simultaneously yet in spatially distinct parts of the larger composite orogenic system or (2) both mechanisms are present yet they operate at temporally distinct intervals, wherein the orogen progressively develops through stages dominated by mid-crustal channel flow followed by shallow thrust stacking and duplex development. In both scenarios, the mechanism active at each stage in orogen evolution is presumably dependent upon local to regional scale rheological conditions (as a function of orogen dynamic and thermal evolution) that are likely to be transient in both space and time. However, questions regarding the dynamic, mechanical, and thermal-kinematic relationships of such a system remain. Also, while field observations and deformation records derived from analyses of transects within the Himalaya can be interpreted in such a way to be consistent with a unified model, numerical models that predict the behavior of interactions between the end-member models have - until now - not existed. Here, we present results from 2-D coupled thermomechanical finite-element numerical experiments that examine the necessary conditions for mechanical compatibility between the channel and critical wedge by focusing on the role of rheology. These model results will eventually allow us to make preliminary comparisons between model-derived stress predictions and differential stress values determined from quartz paleopiezometry from samples collected in the Langtang and Annapurna regions of central Nepal.

Morphology of viscoplastic drop impact on viscoplastic surfaces.

PubMed

Chen, Simeng; Bertola, Volfango

2017-01-25

The impact of viscoplastic drops onto viscoplastic substrates characterized by different magnitudes of the yield stress is investigated experimentally. The interaction between viscoplastic drops and surfaces has an important application in additive manufacturing, where a fresh layer of material is deposited on a partially cured or dried layer of the same material. So far, no systematic studies on this subject have been reported in literature. The impact morphology of different drop/substrate combinations, with yield stresses ranging from 1.13 Pa to 11.7 Pa, was studied by high speed imaging for impact Weber numbers between 15 and 85. Experimental data were compared with one of the existing models for Newtonian drop impact onto liquid surfaces. Results show the magnitude of the yield stress of drop/substrate strongly affects the final shape of the impacting drop, permanently deformed at the end of impact. The comparison between experimental data and model predictions suggests the crater evolution model is only valid when predicting the evolution of the crater at sufficiently high Weber numbers.

Simulations of the formation, evolution and clustering of galaxies and quasars.

PubMed

Springel, Volker; White, Simon D M; Jenkins, Adrian; Frenk, Carlos S; Yoshida, Naoki; Gao, Liang; Navarro, Julio; Thacker, Robert; Croton, Darren; Helly, John; Peacock, John A; Cole, Shaun; Thomas, Peter; Couchman, Hugh; Evrard, August; Colberg, Jörg; Pearce, Frazer

2005-06-02

The cold dark matter model has become the leading theoretical picture for the formation of structure in the Universe. This model, together with the theory of cosmic inflation, makes a clear prediction for the initial conditions for structure formation and predicts that structures grow hierarchically through gravitational instability. Testing this model requires that the precise measurements delivered by galaxy surveys can be compared to robust and equally precise theoretical calculations. Here we present a simulation of the growth of dark matter structure using 2,160(3) particles, following them from redshift z = 127 to the present in a cube-shaped region 2.230 billion lightyears on a side. In postprocessing, we also follow the formation and evolution of the galaxies and quasars. We show that baryon-induced features in the initial conditions of the Universe are reflected in distorted form in the low-redshift galaxy distribution, an effect that can be used to constrain the nature of dark energy with future generations of observational surveys of galaxies.

Direct reciprocity stabilizes simultaneous hermaphroditism at high mating rates: A model of sex allocation with egg trading.

PubMed

Henshaw, Jonathan M; Kokko, Hanna; Jennions, Michael D

2015-08-01

Simultaneous hermaphroditism is predicted to be unstable at high mating rates given an associated increase in sperm competition. The existence of reciprocal egg trading, which requires both hermaphroditism and high mating rates to evolve, is consequently hard to explain. We show using mathematical models that the presence of a trading economy creates an additional fitness benefit to egg production, which selects for traders to bias their sex allocation toward the female function. This female-biased sex allocation prevents pure females from invading a trading population, thereby allowing simultaneous hermaphroditism to persist stably at much higher levels of sperm competition than would otherwise be expected. More generally, our model highlights that simultaneous hermaphroditism can persist stably when mating opportunities are abundant, as long as sperm competition remains low. It also predicts that reciprocity will select for heavier investment in the traded resource. © 2015 The Author(s). Evolution © 2015 The Society for the Study of Evolution.

Correlating Free-Volume Hole Distribution to the Glass Transition Temperature of Epoxy Polymers.

PubMed

Aramoon, Amin; Breitzman, Timothy D; Woodward, Christopher; El-Awady, Jaafar A

2017-09-07

A new algorithm is developed to quantify the free-volume hole distribution and its evolution in coarse-grained molecular dynamics simulations of polymeric networks. This is achieved by analyzing the geometry of the network rather than a voxelized image of the structure to accurately and efficiently find and quantify free-volume hole distributions within large scale simulations of polymer networks. The free-volume holes are quantified by fitting the largest ellipsoids and spheres in the free-volumes between polymer chains. The free-volume hole distributions calculated from this algorithm are shown to be in excellent agreement with those measured from positron annihilation lifetime spectroscopy (PALS) experiments at different temperature and pressures. Based on the results predicted using this algorithm, an evolution model is proposed for the thermal behavior of an individual free-volume hole. This model is calibrated such that the average radius of free-volumes holes mimics the one predicted from the simulations. The model is then employed to predict the glass-transition temperature of epoxy polymers with different degrees of cross-linking and lengths of prepolymers. Comparison between the predicted glass-transition temperatures and those measured from simulations or experiments implies that this model is capable of successfully predicting the glass-transition temperature of the material using only a PDF of the initial free-volume holes radii of each microstructure. This provides an effective approach for the optimized design of polymeric systems on the basis of the glass-transition temperature, degree of cross-linking, and average length of prepolymers.

GALACTIC CHEMICAL EVOLUTION: THE IMPACT OF THE {sup 13}C-POCKET STRUCTURE ON THE s -PROCESS DISTRIBUTION

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

Bisterzo, S.; Travaglio, C.; Wiescher, M.

2017-01-20

The solar s -process abundances have been analyzed in the framework of a Galactic Chemical Evolution (GCE) model. The aim of this work is to implement the study by Bisterzo et al., who investigated the effect of one of the major uncertainties of asymptotic giant branch (AGB) yields, the internal structure of the {sup 13}C pocket. We present GCE predictions of s -process elements computed with additional tests in the light of suggestions provided in recent publications. The analysis is extended to different metallicities, by comparing GCE results and updated spectroscopic observations of unevolved field stars. We verify that themore » GCE predictions obtained with different tests may represent, on average, the evolution of selected neutron-capture elements in the Galaxy. The impact of an additional weak s -process contribution from fast-rotating massive stars is also explored.« less

Real time forecasting of near-future evolution.

PubMed

Gerrish, Philip J; Sniegowski, Paul D

2012-09-07

A metaphor for adaptation that informs much evolutionary thinking today is that of mountain climbing, where horizontal displacement represents change in genotype, and vertical displacement represents change in fitness. If it were known a priori what the 'fitness landscape' looked like, that is, how the myriad possible genotypes mapped onto fitness, then the possible paths up the fitness mountain could each be assigned a probability, thus providing a dynamical theory with long-term predictive power. Such detailed genotype-fitness data, however, are rarely available and are subject to change with each change in the organism or in the environment. Here, we take a very different approach that depends only on fitness or phenotype-fitness data obtained in real time and requires no a priori information about the fitness landscape. Our general statistical model of adaptive evolution builds on classical theory and gives reasonable predictions of fitness and phenotype evolution many generations into the future.

Selection towards different adaptive optima drove the early diversification of locomotor phenotypes in the radiation of Neotropical geophagine cichlids.

PubMed

Astudillo-Clavijo, Viviana; Arbour, Jessica H; López-Fernández, Hernán

2015-05-01

Simpson envisaged a conceptual model of adaptive radiation in which lineages diversify into "adaptive zones" within a macroevolutionary adaptive landscape. However, only a handful of studies have empirically investigated this adaptive landscape and its consequences for our interpretation of the underlying mechanisms of phenotypic evolution. In fish radiations the evolution of locomotor phenotypes may represent an important dimension of ecomorphological diversification given the implications of locomotion for feeding and habitat use. Neotropical geophagine cichlids represent a newly identified adaptive radiation and provide a useful system for studying patterns of locomotor diversification and the implications of selective constraints on phenotypic divergence in general. We use multivariate ordination, models of phenotypic evolution and posterior predictive approaches to investigate the macroevolutionary adaptive landscape and test for evidence of early divergence of locomotor phenotypes in Geophagini. The evolution of locomotor phenotypes was characterized by selection towards at least two distinct adaptive peaks and the early divergence of modern morphological disparity. One adaptive peak included the benthic and epibenthic invertivores and was characterized by fishes with deep, laterally compressed bodies that optimize precise, slow-swimming manoeuvres. The second adaptive peak resulted from a shift in adaptive optima in the species-rich ram-feeding/rheophilic Crenicichla-Teleocichla clade and was characterized by species with streamlined bodies that optimize fast starts and rapid manoeuvres. Evolutionary models and posterior predictive approaches favoured an early shift to a new adaptive peak over decreasing rates of evolution as the underlying process driving the early divergence of locomotor phenotypes. The influence of multiple adaptive peaks on the divergence of locomotor phenotypes in Geophagini is compatible with the expectations of an ecologically driven adaptive radiation. This study confirms that the diversification of locomotor phenotypes represents an important dimension of phenotypic evolution in the geophagine adaptive radiation. It also suggests that the commonly observed early burst of phenotypic evolution during adaptive radiations may be better explained by the concentration of shifts to new adaptive peaks deep in the phylogeny rather than overall decreasing rates of evolution.

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.

Chemical differentiation, thermal evolution, and catastrophic overturn on Venus: Predictions and geologic observations

NASA Technical Reports Server (NTRS)

Head, James W.; Parmentier, E. M.; Hess, P. C.

1993-01-01

Observations from Magellan show that: (1) the surface of Venus is generally geologically young, (2) there is no evidence for widespread recent crustal spreading or subduction, (3) the crater population permits the hypothesis that the surface is in production, and (4) relatively few impact craters appear to be embayed by volcanic deposits suggesting that the volcanic flux has drastically decreased as a function of time. These observations have led to consideration of hypotheses suggesting that the geological history of Venus may have changed dramatically as a function of time due to general thermal evolution, and/or thermal and chemical evolution of a depleted mantle layer, perhaps punctuated by catastrophic overturn of upper layers or episodic plate tectonics. We have previously examined the geological implications of some of these models, and here we review the predictions associated with two periods of Venus history. Stationary thick lithosphere and depleted mantle layer, and development of regional to global development of regional to global instabilities, and compare these predictions to the geological characteristics of Venus revealed by Magellan.

Demonstrating the improvement of predictive maturity of a computational model

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

Hemez, Francois M; Unal, Cetin; Atamturktur, Huriye S

2010-01-01

We demonstrate an improvement of predictive capability brought to a non-linear material model using a combination of test data, sensitivity analysis, uncertainty quantification, and calibration. A model that captures increasingly complicated phenomena, such as plasticity, temperature and strain rate effects, is analyzed. Predictive maturity is defined, here, as the accuracy of the model to predict multiple Hopkinson bar experiments. A statistical discrepancy quantifies the systematic disagreement (bias) between measurements and predictions. Our hypothesis is that improving the predictive capability of a model should translate into better agreement between measurements and predictions. This agreement, in turn, should lead to a smallermore » discrepancy. We have recently proposed to use discrepancy and coverage, that is, the extent to which the physical experiments used for calibration populate the regime of applicability of the model, as basis to define a Predictive Maturity Index (PMI). It was shown that predictive maturity could be improved when additional physical tests are made available to increase coverage of the regime of applicability. This contribution illustrates how the PMI changes as 'better' physics are implemented in the model. The application is the non-linear Preston-Tonks-Wallace (PTW) strength model applied to Beryllium metal. We demonstrate that our framework tracks the evolution of maturity of the PTW model. Robustness of the PMI with respect to the selection of coefficients needed in its definition is also studied.« less

Spatially structured superinfection and the evolution of disease virulence.

PubMed

Caraco, Thomas; Glavanakov, Stephan; Li, Shengua; Maniatty, William; Szymanski, Boleslaw K

2006-06-01

When pathogen strains differing in virulence compete for hosts, spatial structuring of disease transmission can govern both evolved levels of virulence and patterns in strain coexistence. We develop a spatially detailed model of superinfection, a form of contest competition between pathogen strains; the probability of superinfection depends explicitly on the difference in levels of virulence. We apply methods of adaptive dynamics to address the interplay of spatial dynamics and evolution. The mean-field approximation predicts evolution to criticality; any small increase in virulence capable of dynamical persistence is favored. Both pair approximation and simulation of the detailed model indicate that spatial structure constrains disease virulence. Increased spatial clustering reduces the maximal virulence capable of single-strain persistence and, more importantly, reduces the convergent-stable virulence level under strain competition. The spatially detailed model predicts that increasing the probability of superinfection, for given difference in virulence, increases the likelihood of between-strain coexistence. When strains differing in virulence can coexist ecologically, our results may suggest policies for managing diseases with localized transmission. Comparing equilibrium densities from the pair approximation, we find that introducing a more virulent strain into a host population infected by a less virulent strain can sometimes reduce total host mortality and increase global host density.

Natural and sexual selection giveth and taketh away reproductive barriers: models of population divergence in guppies.

PubMed

Labonne, Jacques; Hendry, Andrew P

2010-07-01

The standard predictions of ecological speciation might be nuanced by the interaction between natural and sexual selection. We investigated this hypothesis with an individual-based model tailored to the biology of guppies (Poecilia reticulata). We specifically modeled the situation where a high-predation population below a waterfall colonizes a low-predation population above a waterfall. Focusing on the evolution of male color, we confirm that divergent selection causes the appreciable evolution of male color within 20 generations. The rate and magnitude of this divergence were reduced when dispersal rates were high and when female choice did not differ between environments. Adaptive divergence was always coupled to the evolution of two reproductive barriers: viability selection against immigrants and hybrids. Different types of sexual selection, however, led to contrasting results for another potential reproductive barrier: mating success of immigrants. In some cases, the effects of natural and sexual selection offset each other, leading to no overall reproductive isolation despite strong adaptive divergence. Sexual selection acting through female choice can thus strongly modify the effects of divergent natural selection and thereby alter the standard predictions of ecological speciation. We also found that under no circumstances did divergent selection cause appreciable divergence in neutral genetic markers.

Modelling of Damage Evolution in Braided Composites: Recent Developments

NASA Astrophysics Data System (ADS)

Wang, Chen; Roy, Anish; Silberschmidt, Vadim V.; Chen, Zhong

2017-12-01

Composites reinforced with woven or braided textiles exhibit high structural stability and excellent damage tolerance thanks to yarn interlacing. With their high stiffness-to-weight and strength-to-weight ratios, braided composites are attractive for aerospace and automotive components as well as sports protective equipment. In these potential applications, components are typically subjected to multi-directional static, impact and fatigue loadings. To enhance material analysis and design for such applications, understanding mechanical behaviour of braided composites and development of predictive capabilities becomes crucial. Significant progress has been made in recent years in development of new modelling techniques allowing elucidation of static and dynamic responses of braided composites. However, because of their unique interlacing geometric structure and complicated failure modes, prediction of damage initiation and its evolution in components is still a challenge. Therefore, a comprehensive literature analysis is presented in this work focused on a review of the state-of-the-art progressive damage analysis of braided composites with finite-element simulations. Recently models employed in the studies on mechanical behaviour, impact response and fatigue analyses of braided composites are presented systematically. This review highlights the importance, advantages and limitations of as-applied failure criteria and damage evolution laws for yarns and composite unit cells. In addition, this work provides a good reference for future research on FE simulations of braided composites.

Predicting soil formation on the basis of transport-limited chemical weathering

NASA Astrophysics Data System (ADS)

Yu, Fang; Hunt, Allen Gerhard

2018-01-01

Soil production is closely related to chemical weathering. It has been shown that, under the assumption that chemical weathering is limited by solute transport, the process of soil production is predictable. However, solute transport in soil cannot be described by Gaussian transport. In this paper, we propose an approach based on percolation theory describing non-Gaussian transport of solute to predict soil formation (the net production of soil) by considering both soil production from chemical weathering and removal of soil from erosion. Our prediction shows agreement with observed soil depths in the field. Theoretical soil formation rates are also compared with published rates predicted using soil age-profile thickness (SAST) method. Our formulation can be incorporated directly into landscape evolution models on a point-to-point basis as long as such models account for surface water routing associated with overland flow. Further, our treatment can be scaled-up to address complications associated with continental-scale applications, including those from climate change, such as changes in vegetation, or surface flow organization. The ability to predict soil formation rates has implications for understanding Earth's climate system on account of the relationship to chemical weathering of silicate minerals with the associated drawdown of atmospheric carbon, but it is also important in geomorphology for understanding landscape evolution, including for example, the shapes of hillslopes, and the net transport of sediments to sedimentary basins.

Multi-Scale Modeling of the Gamma Radiolysis of Nitrate Solutions.

PubMed

Horne, Gregory P; Donoclift, Thomas A; Sims, Howard E; Orr, Robin M; Pimblott, Simon M

2016-11-17

A multiscale modeling approach has been developed for the extended time scale long-term radiolysis of aqueous systems. The approach uses a combination of stochastic track structure and track chemistry as well as deterministic homogeneous chemistry techniques and involves four key stages: radiation track structure simulation, the subsequent physicochemical processes, nonhomogeneous diffusion-reaction kinetic evolution, and homogeneous bulk chemistry modeling. The first three components model the physical and chemical evolution of an isolated radiation chemical track and provide radiolysis yields, within the extremely low dose isolated track paradigm, as the input parameters for a bulk deterministic chemistry model. This approach to radiation chemical modeling has been tested by comparison with the experimentally observed yield of nitrite from the gamma radiolysis of sodium nitrate solutions. This is a complex radiation chemical system which is strongly dependent on secondary reaction processes. The concentration of nitrite is not just dependent upon the evolution of radiation track chemistry and the scavenging of the hydrated electron and its precursors but also on the subsequent reactions of the products of these scavenging reactions with other water radiolysis products. Without the inclusion of intratrack chemistry, the deterministic component of the multiscale model is unable to correctly predict experimental data, highlighting the importance of intratrack radiation chemistry in the chemical evolution of the irradiated system.

On the evolution of the star formation rate function of massive galaxies: constraints at 0.4 < z < 1.8 from the GOODS-MUSIC catalogue

NASA Astrophysics Data System (ADS)

Fontanot, Fabio; Cristiani, Stefano; Santini, Paola; Fontana, Adriano; Grazian, Andrea; Somerville, Rachel S.

2012-03-01

We study the evolution of the star formation rate function (SFRF) of massive (M★ > 1010 M⊙) galaxies over the 0.4 < z < 1.8 redshift range and its implications for our understanding of the physical processes responsible for galaxy evolution. We use multiwavelength observations included in the Great Observatories Origins Deep Survey-Multiwavelength Southern Infrared Catalog (GOODS-MUSIC) catalogue, which provides a suitable coverage of the spectral region from 0.3 to 24 ?m and either spectroscopic or photometric redshifts for each object. Individual SFRs have been obtained by combining ultraviolet and 24-?m observations, when the latter were available. For all other sources a 'spectral energy distribution (SED) fitting' SFR estimate has been considered. We then define a stellar mass limited sample, complete in the M★ > 1010 M⊙ range and determine the SFRF using the 1/Vmax algorithm. We thus define simulated galaxy catalogues based on the predictions of three different state-of-the-art semi-analytical models (SAMs) of galaxy formation and evolution, and compare them with the observed SFRF. We show that the theoretical SFRFs are well described by a double power law functional form and its redshift evolution is approximated with high accuracy by a pure evolution of the typical SFR (SFR★). We find good agreement between model predictions and the high-SFR end of the SFRF, when the observational errors on the SFR are taken into account. However, the observational SFRF is characterized by a double-peaked structure, which is absent in its theoretical counterparts. At z > 1.0 the observed SFRF shows a relevant density evolution, which is not reproduced by SAMs, due to the well-known overprediction of intermediate-mass galaxies at z˜ 2. SAMs are thus able to reproduce the most intense SFR events observed in the GOODS-MUSIC sample and their redshift distribution. At the same time, the agreement at the low-SFR end is poor: all models overpredict the space density of SFR ˜ 1 M⊙ yr-1 and no model reproduces the double-peaked shape of the observational SFRF. If confirmed by deeper infrared observations, this discrepancy will provide a key constraint on theoretical modelling of star formation and stellar feedback.

Stress-dependent grain size evolution of nanocrystalline Ni-W and its impact on friction behavior

DOE PAGES

Argibay, N.; Furnish, T. A.; Boyce, B. L.; ...

2016-06-07

The friction behavior of ultra-nanocrystalline Ni-W coatings was investigated. A critical stress threshold was identified below which friction remained low, and above which a time-dependent evolution toward higher friction behavior occurred. Founded on established plasticity models we propose a correlation between surface grain size and applied stress that can be used to predict the critical stress separating the two friction regimes. Lastly, this interpretation of plasticity models suggests that macro-scale low and high friction regimes are respectively associated with the nano-scale mechanisms of grain boundary and dislocation-mediated plasticity.

Diffusion of non-Gaussianity in heavy ion collisions

NASA Astrophysics Data System (ADS)

Kitazawa, Masakiyo; Asakawa, Masayuki; Ono, Hirosato

2014-05-01

We investigate the time evolution of higher order cumulants of bulk fluctuations of conserved charges in the hadronic stage in relativistic heavy ion collisions. The dynamical evolution of non-Gaussian fluctuations is modeled by the diffusion master equation. Using this model we predict that the fourth-order cumulant of net-electric charge is suppressed compared with the recently observed second-order one at ALICE for a reasonable parameter range. Significance of the measurements of various cumulants as functions of rapidity window to probe dynamical history of the hot medium created by heavy ion collisions is emphasized.

Gross Motor Function Measure Evolution Ratio: Use as a Control for Natural Progression in Cerebral Palsy.

PubMed

Marois, Pierre; Marois, Mikael; Pouliot-Laforte, Annie; Vanasse, Michel; Lambert, Jean; Ballaz, Laurent

2016-05-01

To develop a new way to interpret Gross Motor Function Measure (GMFM-66) score improvement in studies conducted without control groups in children with cerebral palsy (CP). The curves, which describe the pattern of motor development according to the children's Gross Motor Function Classification System level, were used as historical control to define the GMFM-66 expected natural evolution in children with CP. These curves have been modeled and generalized to fit the curve to particular children characteristics. Research center. Not applicable. Not applicable. Not applicable. Assuming that the GMFM-66 score evolution followed the shape of the Rosenbaum curves, by taking into account the age and GMFM-66 score of children, the expected natural evolution of the GMFM-66 score was predicted for any group of children with CP who were <8 years old. Because the expected natural evolution could be predicted for a specific group of children with CP, the efficacy of a treatment could be determined by comparing the GMFM-66 score evolution measured before and after treatment with the expected natural evolution for the same period. A new index, the Gross Motor Function Measure Evolution Ratio, was defined as follows: Gross Motor Function Measure Evolution Ratio=measured GMFM-66 score change/expected natural evolution. For practical or ethical reasons, it is almost impossible to use control groups in studies evaluating effectiveness of many therapeutic modalities. The Gross Motor Function Measure Evolution Ratio gives the opportunity to take into account the expected natural evolution of the gross motor function of children with CP, which is essential to accurately interpret the therapy effect on the GMFM-66. Copyright © 2016 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

Selection on Network Dynamics Drives Differential Rates of Protein Domain Evolution

PubMed Central

Mannakee, Brian K.; Gutenkunst, Ryan N.

2016-01-01

The long-held principle that functionally important proteins evolve slowly has recently been challenged by studies in mice and yeast showing that the severity of a protein knockout only weakly predicts that protein’s rate of evolution. However, the relevance of these studies to evolutionary changes within proteins is unknown, because amino acid substitutions, unlike knockouts, often only slightly perturb protein activity. To quantify the phenotypic effect of small biochemical perturbations, we developed an approach to use computational systems biology models to measure the influence of individual reaction rate constants on network dynamics. We show that this dynamical influence is predictive of protein domain evolutionary rate within networks in vertebrates and yeast, even after controlling for expression level and breadth, network topology, and knockout effect. Thus, our results not only demonstrate the importance of protein domain function in determining evolutionary rate, but also the power of systems biology modeling to uncover unanticipated evolutionary forces. PMID:27380265

Quantifying and Validating Rapid Floodplain Geomorphic Evolution, a Monitoring and Modelling Case Study

NASA Astrophysics Data System (ADS)

Scott, R.; Entwistle, N. S.

2017-12-01

Gravel bed rivers and their associated wider systems present an ideal subject for development and improvement of rapid monitoring tools, with features dynamic enough to evolve within relatively short-term timescales. For detecting and quantifying topographical evolution, UAV based remote sensing has manifested as a reliable, low cost, and accurate means of topographic data collection. Here we present some validated methodologies for detection of geomorphic change at resolutions down to 0.05 m, building on the work of Wheaton et al. (2009) and Milan et al. (2007), to generate mesh based and pointcloud comparison data to produce a reliable picture of topographic evolution. Results are presented for the River Glen, Northumberland, UK. Recent channel avulsion and floodplain interaction, resulting in damage to flood defence structures make this site a particularly suitable case for application of geomorphic change detection methods, with the UAV platform at its centre. We compare multi-temporal, high-resolution point clouds derived from SfM processing, cross referenced with aerial LiDAR data, over a 1.5 km reach of the watercourse. Changes detected included bank erosion, bar and splay deposition, vegetation stripping and incipient channel avulsion. Utilisation of the topographic data for numerical modelling, carried out using CAESAR-Lisflood predicted the avulsion of the main channel, resulting in erosion of and potentially complete circumvention of original channel and flood levees. A subsequent UAV survey highlighted topographic change and reconfiguration of the local sedimentary conveyor as we predicted with preliminary modelling. The combined monitoring and modelling approach has allowed probable future geomorphic configurations to be predicted permitting more informed implementation of channel and floodplain management strategies.

Tightly congruent bursts of lineage and phenotypic diversification identified in a continental ant radiation.

PubMed

Price, Shauna L; Etienne, Rampal S; Powell, Scott

2016-04-01

Adaptive diversification is thought to be shaped by ecological opportunity. A prediction of this ecological process of diversification is that it should result in congruent bursts of lineage and phenotypic diversification, but few studies have found this expected association. Here, we study the relationship between rates of lineage diversification and body size evolution in the turtle ants, a diverse Neotropical clade. Using a near complete, time-calibrated phylogeny we investigated lineage diversification dynamics and body size disparity through model fitting analyses and estimation of per-lineage rates of cladogenesis and phenotypic evolution. We identify an exceptionally high degree of congruence between the high rates of lineage and body size diversification in a young clade undergoing renewed diversification in the ecologically distinct Chacoan biogeographical region of South America. It is likely that the region presented turtle ants with novel ecological opportunity, which facilitated a nested burst of diversification and phenotypic evolution within the group. Our results provide a compelling quantitative example of tight congruence between rates of lineage and phenotypic diversification, meeting the key predicted pattern of adaptive diversification shaped by ecological opportunity. © 2016 The Author(s). Evolution © 2016 The Society for the Study of Evolution.

Reduced model prediction of electron temperature profiles in microtearing-dominated National Spherical Torus eXperiment plasmas

NASA Astrophysics Data System (ADS)

Kaye, S. M.; Guttenfelder, W.; Bell, R. E.; Gerhardt, S. P.; LeBlanc, B. P.; Maingi, R.

2014-08-01

A representative H-mode discharge from the National Spherical Torus eXperiment is studied in detail to utilize it as a basis for a time-evolving prediction of the electron temperature profile using an appropriate reduced transport model. The time evolution of characteristic plasma variables such as β e , νe ∗ , the MHD α parameter, and the gradient scale lengths of Te, Ti, and ne were examined as a prelude to performing linear gyrokinetic calculations to determine the fastest growing micro instability at various times and locations throughout the discharge. The inferences from the parameter evolutions and the linear stability calculations were consistent. Early in the discharge, when βe and νe ∗ were relatively low, ballooning parity modes were dominant. As time progressed and both βe and νe ∗ increased, microtearing became the dominant low-kθ mode, especially in the outer half of the plasma. There are instances in time and radius, however, where other modes, at higher-kθ, may, in addition to microtearing, be important for driving electron transport. Given these results, the Rebut-Lallia-Watkins (RLW) electron thermal diffusivity model, which is based on microtearing-induced transport, was used to predict the time-evolving electron temperature across most of the profile. The results indicate that RLW does a good job of predicting Te for times and locations where microtearing was determined to be important, but not as well when microtearing was predicted to be stable or subdominant.

Reduced model prediction of electron temperature profiles in microtearing-dominated NSTX plasmas

NASA Astrophysics Data System (ADS)

Kaye, S. M.; Guttenfelder, W.; Bell, R.; Gerhardt, S.; Leblanc, B.; Maingi, R.

2014-10-01

A representative H-mode discharge from the National Spherical Torus Experiment (NSTX) is studied in detail as a basis for a time-evolving prediction of the electron temperature profile using an appropriate reduced transport model. The time evolution of characteristic plasma variables such as βe, νe*, the MHD α parameter and the gradient scale lengths of Te, Ti and ne were examined prior to performing linear gyrokinetic calculations to determine the fastest growing microinstability at various times and locations throughout the discharge. The inferences from the parameter evolutions and the linear stability calculations were consistent. Early in the discharge, when βe and νe* were relatively low, ballooning parity modes were dominant. As both βe and νe* increased with time, microtearing became the dominant low-kθmode, especially in the outer half of the plasma. There are instances in time and radius where other modes, at higher-kθ, may be important for driving electron transport. The Rebut-Lallia-Watkins (RLW) electron thermal diffusivity model, which is based on microtearing-induced transport, was used to predict the time-evolving electron temperature across most of the profile. The results indicate that RLW does a good job of predicting Te for times and locations where microtearing was determined to be important, but not as well when microtearing was predicted to be stable or subdominant. This work has been supported by U.S. Dept of Energy contracts DE-AC02-09CH11466.

[Simulation and data mining model for identifying and prediction budget changes in the care of patients with hypertension].

PubMed

Joyanes-Aguilar, Luis; Castaño, Néstor J; Osorio, José H

2015-10-01

Objective To present a simulation model that establishes the economic impact to the health care system produced by the diagnostic evolution of patients suffering from arterial hypertension. Methodology The information used corresponds to that available in Individual Health Records (RIPs, in Spanish). A statistical characterization was carried out and a model for matrix storage in MATLAB was proposed. Data mining was used to create predictors. Finally, a simulation environment was built to determine the economic cost of diagnostic evolution. Results 5.7 % of the population progresses from the diagnosis, and the cost overrun associated with it is 43.2 %. Conclusions Results shows the applicability and possibility of focussing research on establishing diagnosis relationships using all the information reported in the RIPS in order to create econometric indicators that can determine which diagnostic evolutions are most relevant to budget allocation.

Progress on Complex Langevin simulations of a finite density matrix model for QCD

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

Bloch, Jacques; Glesaan, Jonas; Verbaarschot, Jacobus

We study the Stephanov model, which is an RMT model for QCD at finite density, using the Complex Langevin algorithm. Naive implementation of the algorithm shows convergence towards the phase quenched or quenched theory rather than to intended theory with dynamical quarks. A detailed analysis of this issue and a potential resolution of the failure of this algorithm are discussed. We study the effect of gauge cooling on the Dirac eigenvalue distribution and time evolution of the norm for various cooling norms, which were specifically designed to remove the pathologies of the complex Langevin evolution. The cooling is further supplementedmore » with a shifted representation for the random matrices. Unfortunately, none of these modifications generate a substantial improvement on the complex Langevin evolution and the final results still do not agree with the analytical predictions.« less

A novel coupled system of non-local integro-differential equations modelling Young's modulus evolution, nutrients' supply and consumption during bone fracture healing

NASA Astrophysics Data System (ADS)

Lu, Yanfei; Lekszycki, Tomasz

2016-10-01

During fracture healing, a series of complex coupled biological and mechanical phenomena occurs. They include: (i) growth and remodelling of bone, whose Young's modulus varies in space and time; (ii) nutrients' diffusion and consumption by living cells. In this paper, we newly propose to model these evolution phenomena. The considered features include: (i) a new constitutive equation for growth simulation involving the number of sensor cells; (ii) an improved equation for nutrient concentration accounting for the switch between Michaelis-Menten kinetics and linear consumption regime; (iii) a new constitutive equation for Young's modulus evolution accounting for its dependence on nutrient concentration and variable number of active cells. The effectiveness of the model and its predictive capability are qualitatively verified by numerical simulations (using COMSOL) describing the healing of bone in the presence of damaged tissue between fractured parts.

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.

Studying the evolutionary significance of thermal adaptation in ectotherms: The diversification of amphibians' energetics.

PubMed

Nespolo, Roberto F; Figueroa, Julio; Solano-Iguaran, Jaiber J

2017-08-01

A fundamental problem in evolutionary biology is the understanding of the factors that promote or constrain adaptive evolution, and assessing the role of natural selection in this process. Here, comparative phylogenetics, that is, using phylogenetic information and traits to infer evolutionary processes has been a major paradigm . In this study, we discuss Ornstein-Uhlenbeck models (OU) in the context of thermal adaptation in ectotherms. We specifically applied this approach to study amphibians's evolution and energy metabolism. It has been hypothesized that amphibians exploit adaptive zones characterized by low energy expenditure, which generate specific predictions in terms of the patterns of diversification in standard metabolic rate (SMR). We complied whole-animal metabolic rates for 122 species of amphibians, and adjusted several models of diversification. According to the adaptive zone hypothesis, we expected: (1) to find "accelerated evolution" in SMR (i.e., diversification above Brownian Motion expectations, BM), (2) that a model assuming evolutionary optima (i.e., an OU model) fits better than a white-noise model and (3) that a model assuming multiple optima (according to the three amphibians's orders) fits better than a model assuming a single optimum. As predicted, we found that the diversification of SMR occurred most of the time, above BM expectations. Also, we found that a model assuming an optimum explained the data in a better way than a white-noise model. However, we did not find evidence that an OU model with multiple optima fits the data better, suggesting a single optimum in SMR for Anura, Caudata and Gymnophiona. These results show how comparative phylogenetics could be applied for testing adaptive hypotheses regarding history and physiological performance in ectotherms. Copyright © 2016 Elsevier Ltd. All rights reserved.

Numerical Investigation of Desulfurization Kinetics in Gas-Stirred Ladles by a Quick Modeling Analysis Approach

NASA Astrophysics Data System (ADS)

Cao, Qing; Nastac, Laurentiu; Pitts-Baggett, April; Yu, Qiulin

2018-03-01

A quick modeling analysis approach for predicting the slag-steel reaction and desulfurization kinetics in argon gas-stirred ladles has been developed in this study. The model consists of two uncoupled components: (i) a computational fluid dynamics (CFD) model for predicting the fluid flow and the characteristics of slag-steel interface, and (ii) a multicomponent reaction kinetics model for calculating the desulfurization evolution. The steel-slag interfacial area and mass transfer coefficients predicted by the CFD simulation are used as the processing data for the reaction model. Since the desulfurization predictions are uncoupled from the CFD simulation, the computational time of this uncoupled predictive approach is decreased by at least 100 times for each case study when compared with the CFD-reaction kinetics fully coupled model. The uncoupled modeling approach was validated by comparing the evolution of steel and slag compositions with the experimentally measured data during ladle metallurgical furnace (LMF) processing at Nucor Steel Tuscaloosa, Inc. Then, the validated approach was applied to investigate the effects of the initial steel and slag compositions, as well as different types of additions during the refining process on the desulfurization efficiency. The results revealed that the sulfur distribution ratio and the desulfurization reaction can be promoted by making Al and CaO additions during the refining process. It was also shown that by increasing the initial Al content in liquid steel, both Al oxidation and desulfurization rates rapidly increase. In addition, it was found that the variation of the initial Si content in steel has no significant influence on the desulfurization rate. Lastly, if the initial CaO content in slag is increased or the initial Al2O3 content is decreased in the fluid-slag compositional range, the desulfurization rate can be improved significantly during the LMF process.

Numerical Investigation of Desulfurization Kinetics in Gas-Stirred Ladles by a Quick Modeling Analysis Approach

NASA Astrophysics Data System (ADS)

Cao, Qing; Nastac, Laurentiu; Pitts-Baggett, April; Yu, Qiulin

2018-06-01

A quick modeling analysis approach for predicting the slag-steel reaction and desulfurization kinetics in argon gas-stirred ladles has been developed in this study. The model consists of two uncoupled components: (i) a computational fluid dynamics (CFD) model for predicting the fluid flow and the characteristics of slag-steel interface, and (ii) a multicomponent reaction kinetics model for calculating the desulfurization evolution. The steel-slag interfacial area and mass transfer coefficients predicted by the CFD simulation are used as the processing data for the reaction model. Since the desulfurization predictions are uncoupled from the CFD simulation, the computational time of this uncoupled predictive approach is decreased by at least 100 times for each case study when compared with the CFD-reaction kinetics fully coupled model. The uncoupled modeling approach was validated by comparing the evolution of steel and slag compositions with the experimentally measured data during ladle metallurgical furnace (LMF) processing at Nucor Steel Tuscaloosa, Inc. Then, the validated approach was applied to investigate the effects of the initial steel and slag compositions, as well as different types of additions during the refining process on the desulfurization efficiency. The results revealed that the sulfur distribution ratio and the desulfurization reaction can be promoted by making Al and CaO additions during the refining process. It was also shown that by increasing the initial Al content in liquid steel, both Al oxidation and desulfurization rates rapidly increase. In addition, it was found that the variation of the initial Si content in steel has no significant influence on the desulfurization rate. Lastly, if the initial CaO content in slag is increased or the initial Al2O3 content is decreased in the fluid-slag compositional range, the desulfurization rate can be improved significantly during the LMF process.

Numerical analyses of ventilated cavitation over a 2-D NACA0015 hydrofoil using two turbulence modeling methods

NASA Astrophysics Data System (ADS)

Yang, Dan-dan; Yu, An; Ji, Bin; Zhou, Jia-jian; Luo, Xian-wu

2018-04-01

The present paper studies the ventilated cavitation over a NACA0015 hydrofoil by numerical methods. The corresponding cavity evolutions are obtained at three ventilation rates by using the level set method. To depict the complicated turbulent flow structure, the filter-based density corrected model (FBDCM) and the modified partially-averaged Navier-Stokes (MPANS) model are applied in the present numerical analyses. It is indicated that the predicted results of the cavitation shedding dynamics by both turbulence models agree fairly well with the experimental data. It is also noted that the shedding frequency and the super cavity length predicted by the MPANS method are closer to the experiment data as compared to that predicted by the FBDCM model. The simulation results show that in the ventilated cavitation, the vapor cavity and the air cavity have the same shedding frequency. As the ventilated rate increases, the vapor cavity is depressed rapidly. The cavitation-vortex interaction in the ventilated cavitation is studied based on the vorticity transport equation (VTE) and the Lagrangian coherent structure (LCS). Those results demonstrate that the vortex dilatation and baroclinic torque terms are highly dependent on the evolution of the cavitation. In addition, from the LCSs and the tracer particles in the flow field, one may see the process from the attached cavity to the cloud cavity.

Mushy zone modeling

NASA Astrophysics Data System (ADS)

Glicksman, Martin E.; Smith, Richard N.; Marsh, Steven P.; Kuklinski, Robert

A key element of mushy zone modeling is the description of the microscopic evolution of the lengthscales within the mushy zone and the influence of macroscopic transport processes. This paper describes some recent progress in developing a mean-field statistical theory of phase coarsening in adiabatic mushy zones. The main theoretical predictions are temporal scaling laws that indicate that average lengthscale increases as time 1/3, a self-similar distribution of mushy zone lengthscales based on spherical solid particle shapes, and kinetic rate constants which provide the dependences of the coarsening process on material parameters and the volume fraction of the solid phase. High precision thermal decay experiments are described which verify aspects of the theory in pure material mushy zones held under adiabatic conditions. The microscopic coarsening theory is then integrated within a macroscopic heat transfer model of one-dimensional alloy solidification, using the Double Integral Method. The method demonstrates an ability to predict the influence of macroscopic heat transfer on the evolution of primary and secondary dendrite arm spacings in Al-Cu alloys. Finally, some suggestions are made for future experimental and theoretical studies required in developing comprehensive solidification processing models.

Evolution-informed forecasting of seasonal influenza A (H3N2).

PubMed

Du, Xiangjun; King, Aaron A; Woods, Robert J; Pascual, Mercedes

2017-10-25

Interpandemic or seasonal influenza A, currently subtypes H3N2 and H1N1, exacts an enormous annual burden both in terms of human health and economic impact. Incidence prediction ahead of season remains a challenge largely because of the virus' antigenic evolution. We propose a forecasting approach that incorporates evolutionary change into a mechanistic epidemiological model. The proposed models are simple enough that their parameters can be estimated from retrospective surveillance data. These models link amino acid sequences of hemagglutinin epitopes with a transmission model for seasonal H3N2 influenza, also informed by H1N1 levels. With a monthly time series of H3N2 incidence in the United States for more than 10 years, we demonstrate the feasibility of skillful prediction for total cases ahead of season, with a tendency to underpredict monthly peak epidemic size, and an accurate real-time forecast for the 2016/2017 influenza season. Copyright © 2017 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

Numerical simulation of dune-flat bed transition and stage‐discharge relationship with hysteresis effect

USGS Publications Warehouse

Shimizu, Yasuyuki; Giri, Sanjay; Yamaguchi, Satomi; Nelson, Jonathan M.

2009-01-01

This work presents recent advances on morphodynamic modeling of bed forms under unsteady discharge. This paper includes further development of a morphodynamic model proposed earlier by Giri and Shimizu (2006a). This model reproduces the temporal development of river dunes and accurately replicates the physical properties associated with bed form evolution. Model results appear to provide accurate predictions of bed form geometry and form drag over bed forms for arbitrary steady flows. However, accurate predictions of temporal changes of form drag are key to the prediction of stage‐discharge relation during flood events. Herein, the model capability is extended to replicate the dune–flat bed transition, and in turn, the variation of form drag produced by the temporal growth or decay of bed forms under unsteady flow conditions. Some numerical experiments are performed to analyze hysteresis of the stage‐discharge relationship caused by the transition between dune and flat bed regimes during rising and falling stages of varying flows. The numerical model successfully simulates dune–flat bed transition and the associated hysteresis of the stage‐discharge relationship; this is in good agreement with physical observations but has been treated in the past only using empirical methods. A hypothetical relationship for a sediment parameter (the mean step length) is proposed to a first level of approximation that enables reproduction of the dune–flat bed transition. The proposed numerical model demonstrates its ability to address an important practical problem associated with bed form evolution and flow resistance in varying flows.

A 1-D mechanistic model for the evolution of earthflow-prone hillslopes

NASA Astrophysics Data System (ADS)

Booth, Adam M.; Roering, Josh J.

2011-12-01

In mountainous terrain, deep-seated landslides transport large volumes of material on hillslopes, exerting a dominant control on erosion rates and landscape form. Here, we develop a mathematical landscape evolution model to explore interactions between deep-seated earthflows, soil creep, and gully processes at the drainage basin scale over geomorphically relevant (>103 year) timescales. In the model, sediment flux or incision laws for these three geomorphic processes combine to determine the morphology of actively uplifting and eroding steady state topographic profiles. We apply the model to three sites, one in the Gabilan Mesa, California, with no earthflow activity, and two along the Eel River, California, with different lithologies and varying levels of historic earthflow activity. Representative topographic profiles from these sites are consistent with model predictions in which the magnitude of a dimensionless earthflow number, based on a non-Newtonian flow rheology, reflects the magnitude of recent earthflow activity on the different hillslopes. The model accurately predicts the behavior of earthflow collection and transport zones observed in the field and estimates long-term average sediment fluxes that are due to earthflows, in agreement with historical rates at our field sites. Finally, our model predicts that steady state hillslope relief in earthflow-prone terrain increases nonlinearly with the tectonic uplift rate, suggesting that the mean hillslope angle may record uplift rate in earthflow-prone landscapes even at high uplift rates, where threshold slope processes normally limit further topographic development.

Asymmetric ecological conditions favor Red-Queen type of continued evolution over stasis.

PubMed

Nordbotten, Jan Martin; Stenseth, Nils C

2016-02-16

Four decades ago, Leigh Van Valen presented the Red Queen's hypothesis to account for evolution of species within a multispecies ecological community [Van Valen L (1973) Evol Theory 1(1):1-30]. The overall conclusion of Van Valen's analysis was that evolution would continue even in the absence of abiotic perturbations. Stenseth and Maynard Smith presented in 1984 [Stenseth NC, Maynard Smith J (1984) Evolution 38(4):870-880] a model for the Red Queen's hypothesis showing that both Red-Queen type of continuous evolution and stasis could result from a model with biotically driven evolution. However, although that contribution demonstrated that both evolutionary outcomes were possible, it did not identify which ecological conditions would lead to each of these evolutionary outcomes. Here, we provide, using a simple, yet general population-biologically founded eco-evolutionary model, such analytically derived conditions: Stasis will predominantly emerge whenever the ecological system contains only symmetric ecological interactions, whereas both Red-Queen and stasis type of evolution may result if the ecological interactions are asymmetrical, and more likely so with increasing degree of asymmetry in the ecological system (i.e., the more trophic interactions, host-pathogen interactions, and the like there are [i.e., +/- type of ecological interactions as well as asymmetric competitive (-/-) and mutualistic (+/+) ecological interactions]). In the special case of no between-generational genetic variance, our results also predict dynamics within these types of purely ecological systems.

Microstructure and Property Evolution in Advanced Cladding and Duct Materials Under Long-Term and Elevated Temperature Irradiation: Modeling and Experimental Investigation

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

Wirth, Brian; Morgan, Dane; Kaoumi, Djamel

2013-12-01

The in-service degradation of reactor core materials is related to underlying changes in the irradiated microstructure. During reactor operation, structural components and cladding experience displacement of atoms by collisions with neutrons at temperatures at which the radiation-induced defects are mobile, leading to microstructure evolution under irradiation that can degrade material properties. At the doses and temperatures relevant to fast reactor operation, the microstructure evolves by dislocation loop formation and growth, microchemistry changes due to radiation-induced segregation, radiation-induced precipitation, destabilization of the existing precipitate structure, and in some cases, void formation and growth. These processes do not occur independently; rather, theirmore » evolution is highly interlinked. Radiationinduced segregation of Cr and existing chromium carbide coverage in irradiated alloy T91 track each other closely. The radiation-induced precipitation of Ni-Si precipitates and RIS of Ni and Si in alloys T91 and HCM12A are likely related. Neither the evolution of these processes nor their coupling is understood under the conditions required for materials performance in fast reactors (temperature range 300-600°C and doses beyond 200 dpa). Further, predictive modeling is not yet possible as models for microstructure evolution must be developed along with experiments to characterize these key processes and provide tools for extrapolation. To extend the range of operation of nuclear fuel cladding and structural materials in advanced nuclear energy and transmutation systems to that required for the fast reactor, the irradiation-induced evolution of the microstructure, microchemistry, and the associated mechanical properties at relevant temperatures and doses must be understood. Predictive modeling relies on an understanding of the physical processes and also on the development of microstructure and microchemical models to describe their evolution under irradiation. This project will focus on modeling microstructural and microchemical evolution of irradiated alloys by performing detailed modeling of such microstructure evolution processes coupled with well-designed in situ experiments that can provide validation and benchmarking to the computer codes. The broad scientific and technical objectives of this proposal are to evaluate the microstructure and microchemical evolution in advanced ferritic/martensitic and oxide dispersion strengthened (ODS) alloys for cladding and duct reactor materials under long-term and elevated temperature irradiation, leading to improved ability to model structural materials performance and lifetime. Specifically, we propose four research thrusts, namely Thrust 1: Identify the formation mechanism and evolution for dislocation loops with Burgers vector of a<100> and determine whether the defect microstructure (predominately dislocation loop/dislocation density) saturates at high dose. Thrust 2: Identify whether a threshold irradiation temperature or dose exists for the nucleation of growing voids that mark the beginning of irradiation-induced swelling, and begin to probe the limits of thermal stability of the tempered Martensitic structure under irradiation. Thrust 3: Evaluate the stability of nanometer sized Y- Ti-O based oxide dispersion strengthened (ODS) particles at high fluence/temperature. Thrust 4: Evaluate the extent to which precipitates form and/or dissolve as a function of irradiation temperature and dose, and how these changes are driven by radiation induced segregation and microchemical evolutions and determined by the initial microstructure.« less

Machine health prognostics using the Bayesian-inference-based probabilistic indication and high-order particle filtering framework

NASA Astrophysics Data System (ADS)

Yu, Jianbo

2015-12-01

Prognostics is much efficient to achieve zero-downtime performance, maximum productivity and proactive maintenance of machines. Prognostics intends to assess and predict the time evolution of machine health degradation so that machine failures can be predicted and prevented. A novel prognostics system is developed based on the data-model-fusion scheme using the Bayesian inference-based self-organizing map (SOM) and an integration of logistic regression (LR) and high-order particle filtering (HOPF). In this prognostics system, a baseline SOM is constructed to model the data distribution space of healthy machine under an assumption that predictable fault patterns are not available. Bayesian inference-based probability (BIP) derived from the baseline SOM is developed as a quantification indication of machine health degradation. BIP is capable of offering failure probability for the monitored machine, which has intuitionist explanation related to health degradation state. Based on those historic BIPs, the constructed LR and its modeling noise constitute a high-order Markov process (HOMP) to describe machine health propagation. HOPF is used to solve the HOMP estimation to predict the evolution of the machine health in the form of a probability density function (PDF). An on-line model update scheme is developed to adapt the Markov process changes to machine health dynamics quickly. The experimental results on a bearing test-bed illustrate the potential applications of the proposed system as an effective and simple tool for machine health prognostics.

Tachyon cosmology, supernovae data, and the big brake singularity

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

Keresztes, Z.; Gergely, L. A.; Gorini, V.

2009-04-15

We compare the existing observational data on type Ia supernovae with the evolutions of the Universe predicted by a one-parameter family of tachyon models which we have introduced recently [Phys. Rev. D 69, 123512 (2004)]. Among the set of the trajectories of the model which are compatible with the data there is a consistent subset for which the Universe ends up in a new type of soft cosmological singularity dubbed big brake. This opens up yet another scenario for the future history of the Universe besides the one predicted by the standard {lambda}CDM model.

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

NASA Astrophysics Data System (ADS)

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

2012-07-01

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

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 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

The star formation history of low-mass disk galaxies: A case study of NGC 300

NASA Astrophysics Data System (ADS)

Kang, Xiaoyu; Zhang, Fenghui; Chang, Ruixiang; Wang, Lang; Cheng, Liantao

2016-01-01

Context. Since NGC 300 is a bulgeless, isolated low-mass galaxy and it has not experienced radial migration during its evolution history, it can be treated as an ideal laboratory to test the simple galactic chemical evolution model. Aims: Our main aim is to investigate the main properties of the star formation history (SFH) of NGC 300 and compare its SFH with that of M 33 to explore the common properties and differences between these two nearby low-mass systems. Methods: We construct a simple chemical evolution model for NGC 300, assuming its disk forms gradually from continuous accretion of primordial gas and including the gas-outflow process. The model allows us to build a bridge between the SFH and observed data of NGC 300, in particular, the present-day radial profiles and global observed properties (e.g., cold gas mass, star formation rate, and metallicity). By means of comparing the model predictions with the corresponding observations, we adopt the classical χ2 methodology to find out the best combination of free parameters a, b, and bout. Results: Our results show that by assuming an inside-out formation scenario and an appropriate outflow rate, our model reproduces well most of the present-day observational values. The model not only reproduces well the radial profiles, but also the global observational data for the NGC 300 disk. Our results suggest that NGC 300 may experience a rapid growth of its disk. Through comparing the best-fitting, model-predicted SFH of NGC 300 with that of M 33, we find that the mean stellar age of NGC 300 is older than that of M 33 and there is a recent lack of primordial gas infall onto the disk of NGC 300. Our results also imply that the local environment may play a key role in the secular evolution of galaxy disks.

Modeling of yield surface evolution in uniaxial and biaxial loading conditions using a prestrained large scale specimen

NASA Astrophysics Data System (ADS)

Zaman, Shakil Bin; Barlat, Frédéric; Kim, Jin Hwan

2018-05-01

Large-scale advanced high strength steel (AHSS) sheet specimens were deformed in uniaxial tension, using a novel grip system mounted on a MTS universal tension machine. After pre-strain, they were used as a pre-strained material to examine the anisotropic response in the biaxial tension tests with various load ratios, and orthogonal tension tests at 45° and 90° from the pre-strain axis. The flow curve and the instantaneous r-value of the pre-strained steel in each of the aforementioned uniaxial testing conditions were also measured and compared with those of the undeformed steel. Furthermore, an exhaustive analysis of the yield surface was also conducted and the results, prior and post-prestrain were represented and compared. The homogeneous anisotropic hardening (HAH) model [1] was employed to predict the behavior of the pre-strained material. It was found that the HAH-predicted flow curves after non-linear strain path change and the yield loci after uniaxial pre-strain were in good agreement with the experiments, while the r-value evolution after strain path change was qualitatively well predicted.

Quasar X-Ray Spectra At z=1.5

NASA Technical Reports Server (NTRS)

Siemiginowska, Aneta

2001-01-01

The predicted counts for ASCA observation was much higher than actually observed counts in the quasar. However, there are three weak hard x-ray sources in the GIS field. We are adding them to the source counts in modeling of hard x-ray background. The work is in progress. We have published a paper in Ap.J. on the luminosity function and the quasar evolution. Based on the theory described in this paper we are predicting a number of sources and their contribution to the x-ray background at different redshifts. These model predictions will be compared to the observed data in the final paper.

Preliminary conceptual model for mineral evolution in Yucca Mountain

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

Duffy, C.J.

1993-12-01

A model is presented for mineral alteration in Yucca Mountain, Nevada, that suggests that the mineral transformations observed there are primarily controlled by the activity of aqueous silica. The rate of these reactions is related to the rate of evolution of the metastable silica polymorphs opal-CT and cristobalite assuming that a{sub SiO{sub 2(aq)}} is fixed at the equilibrium solubility of the most soluble silica polymorph present. The rate equations accurately predict the present depths of disappearance of opal-CT and cristobalite. The rate equations have also been used to predict the extent of future mineral alteration that may result from emplacementmore » of a high-level nuclear waste repository in Yucca Mountain. Relatively small changes in mineralogy are predicted, but these predictions are based on the assumption that emplacement of a repository would not increase the pH of water in Yucca Mountain nor increase its carbonate content. Such changes may significantly increase mineral alteration. Some of the reactions currently occurring in Yucca Mountain consume H{sup +} and CO{sub 3}{sup 2{minus}}. Combining reaction rate models for these reactions with water chemistry data may make it possible to estimate water flux through the basal vitrophyre of the Topopah Spring Member and to help confirm the direction and rate of flow of groundwater in Yucca Mountain.« less

Predicting future spatial distribution of SOC across entire France

NASA Astrophysics Data System (ADS)

Meersmans, Jeroen; Van Rompaey, Anton; Quine, Tim; Martin, Manuel; Pagé, Christian; Arrouays, Dominique

2013-04-01

Soil organic carbon (SOC) is widely recognized as a key factor controlling soil quality and as a crucial and active component of the global C-cycle. Hence, there exists a growing interest in monitoring and modeling the spatial and temporal behavior of this pool. So far, a large attempt has been made to map SOC at national scales for current and/or past situations. Despite some coarse predictions, detailed spatial SOC predictions for the future are still lacking. In this study we aim to predict future spatial evolution of SOC driven by climate and land use change for France up to the year 2100. Therefore, we combined 1) an existing model, predicting SOC as a function of soil type, climate, land use and management (Meersmans et al 2012), with 2) eight different IPCC spatial explicit climate change predictions (conducted by CERFACS) and 3) Land use change scenario predictions. We created business-as-usual land use change scenarios by extrapolating observed trends and calibrating logistic regression models, incorporating a large set of physical and socio-economic factors, at the regional level in combination with a multi-objective land allocation (MOLA) procedure. The resultant detailed projections of future SOC evolution across all regions of France, allow us to identify regions that are most likely to be characterized by a significant gain or loss of SOC and the degree to which land use decisions/outcomes control the scale of loss and gain. Therefore, this methodology and resulting maps can be considered as powerful tools to aid decision making concerning appropriate soil management, in order to enlarge SOC storage possibilities and reduce soil related CO2 fluxes.

Phylogeny suggests nondirectional and isometric evolution of sexual size dimorphism in argiopine spiders.

PubMed

Cheng, Ren-Chung; Kuntner, Matjaž

2014-10-01

Sexual dimorphism describes substantial differences between male and female phenotypes. In spiders, sexual dimorphism research almost exclusively focuses on size, and recent studies have recovered steady evolutionary size increases in females, and independent evolutionary size changes in males. Their discordance is due to negative allometric size patterns caused by different selection pressures on male and female sizes (converse Rensch's rule). Here, we investigated macroevolutionary patterns of sexual size dimorphism (SSD) in Argiopinae, a global lineage of orb-weaving spiders with varying degrees of SSD. We devised a Bayesian and maximum-likelihood molecular species-level phylogeny, and then used it to reconstruct sex-specific size evolution, to examine general hypotheses and different models of size evolution, to test for sexual size coevolution, and to examine allometric patterns of SSD. Our results, revealing ancestral moderate sizes and SSD, failed to reject the Brownian motion model, which suggests a nondirectional size evolution. Contrary to predictions, male and female sizes were phylogenetically correlated, and SSD evolution was isometric. We interpret these results to question the classical explanations of female-biased SSD via fecundity, gravity, and differential mortality. In argiopines, SSD evolution may be driven by these or additional selection mechanisms, but perhaps at different phylogenetic scales. © 2014 The Author(s). Evolution © 2014 The Society for the Study of Evolution.

Natural selection and the predictability of evolution in Timema stick insects.

PubMed

Nosil, Patrik; Villoutreix, Romain; de Carvalho, Clarissa F; Farkas, Timothy E; Soria-Carrasco, Víctor; Feder, Jeffrey L; Crespi, Bernard J; Gompert, Zach

2018-02-16

Predicting evolution remains difficult. We studied the evolution of cryptic body coloration and pattern in a stick insect using 25 years of field data, experiments, and genomics. We found that evolution is more difficult to predict when it involves a balance between multiple selective factors and uncertainty in environmental conditions than when it involves feedback loops that cause consistent back-and-forth fluctuations. Specifically, changes in color-morph frequencies are modestly predictable through time ( r 2 = 0.14) and driven by complex selective regimes and yearly fluctuations in climate. In contrast, temporal changes in pattern-morph frequencies are highly predictable due to negative frequency-dependent selection ( r 2 = 0.86). For both traits, however, natural selection drives evolution around a dynamic equilibrium, providing some predictability to the process. Copyright © 2018 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

On the thermomechanical coupling in dissipative materials: A variational approach for generalized standard materials

NASA Astrophysics Data System (ADS)

Bartels, A.; Bartel, T.; Canadija, M.; Mosler, J.

2015-09-01

This paper deals with the thermomechanical coupling in dissipative materials. The focus lies on finite strain plasticity theory and the temperature increase resulting from plastic deformation. For this type of problem, two fundamentally different modeling approaches can be found in the literature: (a) models based on thermodynamical considerations and (b) models based on the so-called Taylor-Quinney factor. While a naive straightforward implementation of thermodynamically consistent approaches usually leads to an over-prediction of the temperature increase due to plastic deformation, models relying on the Taylor-Quinney factor often violate fundamental physical principles such as the first and the second law of thermodynamics. In this paper, a thermodynamically consistent framework is elaborated which indeed allows the realistic prediction of the temperature evolution. In contrast to previously proposed frameworks, it is based on a fully three-dimensional, finite strain setting and it naturally covers coupled isotropic and kinematic hardening - also based on non-associative evolution equations. Considering a variationally consistent description based on incremental energy minimization, it is shown that the aforementioned problem (thermodynamical consistency and a realistic temperature prediction) is essentially equivalent to correctly defining the decomposition of the total energy into stored and dissipative parts. Interestingly, this decomposition shows strong analogies to the Taylor-Quinney factor. In this respect, the Taylor-Quinney factor can be well motivated from a physical point of view. Furthermore, certain intervals for this factor can be derived in order to guarantee that fundamental physically principles are fulfilled a priori. Representative examples demonstrate the predictive capabilities of the final constitutive modeling framework.

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.

The Impact of Modeling Assumptions in Galactic Chemical Evolution Models

NASA Astrophysics Data System (ADS)

Côté, Benoit; O'Shea, Brian W.; Ritter, Christian; Herwig, Falk; Venn, Kim A.

2017-02-01

We use the OMEGA galactic chemical evolution code to investigate how the assumptions used for the treatment of galactic inflows and outflows impact numerical predictions. The goal is to determine how our capacity to reproduce the chemical evolution trends of a galaxy is affected by the choice of implementation used to include those physical processes. In pursuit of this goal, we experiment with three different prescriptions for galactic inflows and outflows and use OMEGA within a Markov Chain Monte Carlo code to recover the set of input parameters that best reproduces the chemical evolution of nine elements in the dwarf spheroidal galaxy Sculptor. This provides a consistent framework for comparing the best-fit solutions generated by our different models. Despite their different degrees of intended physical realism, we found that all three prescriptions can reproduce in an almost identical way the stellar abundance trends observed in Sculptor. This result supports the similar conclusions originally claimed by Romano & Starkenburg for Sculptor. While the three models have the same capacity to fit the data, the best values recovered for the parameters controlling the number of SNe Ia and the strength of galactic outflows, are substantially different and in fact mutually exclusive from one model to another. For the purpose of understanding how a galaxy evolves, we conclude that only reproducing the evolution of a limited number of elements is insufficient and can lead to misleading conclusions. More elements or additional constraints such as the Galaxy’s star-formation efficiency and the gas fraction are needed in order to break the degeneracy between the different modeling assumptions. Our results show that the successes and failures of chemical evolution models are predominantly driven by the input stellar yields, rather than by the complexity of the Galaxy model itself. Simple models such as OMEGA are therefore sufficient to test and validate stellar yields. OMEGA is part of the NuGrid chemical evolution package and is publicly available online at http://nugrid.github.io/NuPyCEE.

Tidal Dissipation In Rotating Low Mass Stars: Implications For The Orbital Evolution Of Close In Planets

NASA Astrophysics Data System (ADS)

Gallet, Florian; Bolmont, Emeline; Mathis, Stéphane; Charbonnel, Corinne; Amard, Louis; Alibert, Yann

2017-10-01

Close-in planets represent a large fraction of the population of confirmed exoplanets. To understand the dynamical evolution of these planets, star-planet interactions must be taken into account. In particular, the dependence of the tidal interactions on the structural parameters of the star, its rotation, and its metallicity should be treated in the models. We quantify how the tidal dissipation in the convective envelope of rotating low-mass stars evolves in time. We also investigate the possible consequences of this evolution on planetary orbital evolution. In Gallet et al. (2017) and Bolmont et al. (2017) we generalized the work of Bolmont & Mathis (2016) by following the orbital evolution of close-in planets using the new tidal dissipation predictions for advanced phases of stellar evolution and non-solar metallicity. We find that during the pre-main sequence the evolution of tidal dissipation is controlled by the evolution of the internal structure of the star through the stellar contraction. On the main-sequence tidal dissipation is strongly driven by the evolution of the surface rotation that is impacted by magnetized stellar winds braking. Finally, during the more evolved phases, the tidal dissipation sharply decreases as radiative core retreats in mass and radius towards the red-giant branch. Using an orbital evolution model, we also show that changing the metallicity leads to diUerent orbital evolutions (e.g., planets migrate farther out from an initially fast rotating metal rich star). By using this model, we qualitatively reproduced the observational trends of the population of hot Jupiters with the metallicity of their host stars. However, more work still remain to be do so as to be able to quantitatively fit our results to the observations.

Numerical Simulation of Austempering Heat Treatment of a Ductile Cast Iron

NASA Astrophysics Data System (ADS)

Boccardo, Adrián D.; Dardati, Patricia M.; Celentano, Diego J.; Godoy, Luis A.; Górny, Marcin; Tyrała, Edward

2016-02-01

This paper presents a coupled thermo-mechanical-metallurgical formulation to predict the dimensional changes and microstructure of a ductile cast iron part as a consequence of an austempering heat process. To take into account the different complex phenomena which are present in the process, the stress-strain law and plastic evolution equations are defined within the context of the associate rate-independent thermo-plasticity theory. The metallurgical model considers the reverse eutectoid, ausferritic, and martensitic transformations using macro- and micro-models. The resulting model is solved using the finite element method. The performance of this model is evaluated by comparison with experimental results of a dilatometric test. The results indicate that both the experimental evolution of deformation and temperature are well represented by the numerical model.

Damage-based life prediction model for uniaxial low-cycle stress fatigue of super-elastic NiTi shape memory alloy microtubes

NASA Astrophysics Data System (ADS)

Song, Di; Kang, Guozheng; Kan, Qianhua; Yu, Chao; Zhang, Chuanzeng

2015-08-01

Based on the experimental observations for the uniaxial low-cycle stress fatigue failure of super-elastic NiTi shape memory alloy microtubes (Song et al 2015 Smart Mater. Struct. 24 075004) and a new definition of damage variable corresponding to the variation of accumulated dissipation energy, a phenomenological damage model is proposed to describe the damage evolution of the NiTi microtubes during cyclic loading. Then, with a failure criterion of Dc = 1, the fatigue lives of the NiTi microtubes are predicted by the damage-based model, the predicted lives are in good agreement with the experimental ones, and all of the points are located within an error band of 1.5 times.

Models and observations of Arctic melt ponds

NASA Astrophysics Data System (ADS)

Golden, K. M.

2016-12-01

During the Arctic melt season, the sea ice surface undergoes a striking transformation from vast expanses of snow covered ice to complex mosaics of ice and melt ponds. Sea ice albedo, a key parameter in climate modeling, is largely determined by the complex evolution of melt pond configurations. In fact, ice-albedo feedback has played a significant role in the recent declines of the summer Arctic sea ice pack. However, understanding melt pond evolution remains a challenge to improving climate projections. It has been found that as the ponds grow and coalesce, the fractal dimension of their boundaries undergoes a transition from 1 to about 2, around a critical length scale of 100 square meters in area. As the ponds evolve they take complex, self-similar shapes with boundaries resembling space-filling curves. I will outline how mathematical models of composite materials and statistical physics, such as percolation and Ising models, are being used to describe this evolution and predict key geometrical parameters that agree very closely with observations.

Thermodynamic and kinetic modeling of Mn-Ni-Si precipitates in low-Cu reactor pressure vessel steels

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

Ke, Huibin; Wells, Peter; Edmondson, Philip D.

Formation of large volume fractions of Mn-Ni-Si precipitates (MNSPs) causes excess irradiation embrittlement of reactor pressure vessel (RPV) steels at high, extended-life fluences. Thus, a new and unique, semi-empirical cluster dynamics model was developed to study the evolution of MNSPs in low-Cu RPV steels. The model is based on CALPHAD thermodynamics and radiation enhanced diffusion kinetics. The thermodynamics dictates the compositional and temperature dependence of the free energy reductions that drive precipitation. The model treats both homogeneous and heterogeneous nucleation, where the latter occurs on cascade damage, like dislocation loops. The model has only four adjustable parameters that were fitmore » to an atom probe tomography (APT) database. The model predictions are in semi-quantitative agreement with systematic Mn, Ni and Si composition variations in alloys characterized by APT, including a sensitivity to local tip-to-tip variations even in the same steel. The model predicts that heterogeneous nucleation plays a critical role in MNSP formation in lower alloy Ni contents. Single variable assessments of compositional effects show that Ni plays a dominant role, while even small variations in irradiation temperature can have a large effect on the MNSP evolution. Within typical RPV steel ranges, Mn and Si have smaller effects. Furthermore, the delayed but then rapid growth of MNSPs to large volume fractions at high fluence is well predicted by the model. For purposes of illustration, the effect of MNSPs on transition temperature shifts are presented based on well-established microstructure-property and property-property models.« less

Thermodynamic and kinetic modeling of Mn-Ni-Si precipitates in low-Cu reactor pressure vessel steels

DOE PAGES

Ke, Huibin; Wells, Peter; Edmondson, Philip D.; ...

2017-07-12

Formation of large volume fractions of Mn-Ni-Si precipitates (MNSPs) causes excess irradiation embrittlement of reactor pressure vessel (RPV) steels at high, extended-life fluences. Thus, a new and unique, semi-empirical cluster dynamics model was developed to study the evolution of MNSPs in low-Cu RPV steels. The model is based on CALPHAD thermodynamics and radiation enhanced diffusion kinetics. The thermodynamics dictates the compositional and temperature dependence of the free energy reductions that drive precipitation. The model treats both homogeneous and heterogeneous nucleation, where the latter occurs on cascade damage, like dislocation loops. The model has only four adjustable parameters that were fitmore » to an atom probe tomography (APT) database. The model predictions are in semi-quantitative agreement with systematic Mn, Ni and Si composition variations in alloys characterized by APT, including a sensitivity to local tip-to-tip variations even in the same steel. The model predicts that heterogeneous nucleation plays a critical role in MNSP formation in lower alloy Ni contents. Single variable assessments of compositional effects show that Ni plays a dominant role, while even small variations in irradiation temperature can have a large effect on the MNSP evolution. Within typical RPV steel ranges, Mn and Si have smaller effects. Furthermore, the delayed but then rapid growth of MNSPs to large volume fractions at high fluence is well predicted by the model. For purposes of illustration, the effect of MNSPs on transition temperature shifts are presented based on well-established microstructure-property and property-property models.« less

Evolution of learning and levels of selection: A lesson from avian parent-offspring communication.

PubMed

Lotem, Arnon; Biran-Yoeli, Inbar

2013-09-20

In recent years, it has become increasingly clear that the evolution of behavior may be better understood as the evolution of the learning mechanisms that produce it, and that such mechanisms should be modeled and tested explicitly. However, this approach, which has recently been applied to animal foraging and decision-making, has rarely been applied to the social and communicative behaviors that are likely to operate in complex social environments and be subject to multi-level selection. Here we use genetic, agent-based evolutionary simulations to explore how learning mechanisms may evolve to adjust the level of nestling begging (offspring signaling of need), and to examine the possible consequences of this process for parent-offspring conflict and communication. In doing so, we also provide the first step-by-step dynamic model of parent-offspring communication. The results confirm several previous theoretical predictions and demonstrate three novel phenomena. First, negatively frequency-dependent group-level selection can generate a stable polymorphism of learning strategies and parental responses. Second, while conventional reinforcement learning models fail to cope successfully with family dynamics at the nest, a newly developed learning model (incorporating behaviors that are consistent with recent experimental results on learning in nestling begging) produced effective learning, which evolved successfully. Third, while kin-selection affects the frequency of the different learning genes, its impact on begging slope and intensity was unexpectedly negligible, demonstrating that evolution is a complex process, and showing that the effect of kin-selection on behaviors that are shaped by learning may not be predicted by simple application of Hamilton's rule. Copyright © 2013 Elsevier Inc. All rights reserved.

Evolution of learning and levels of selection: a lesson from avian parent-offspring communication.

PubMed

Lotem, Arnon; Biran-Yoeli, Inbar

2014-02-01

In recent years, it has become increasingly clear that the evolution of behavior may be better understood as the evolution of the learning mechanisms that produce it, and that such mechanisms should be modeled and tested explicitly. However, this approach, which has recently been applied to animal foraging and decision-making, has rarely been applied to the social and communicative behaviors that are likely to operate in complex social environments and be subject to multi-level selection. Here we use genetic, agent-based evolutionary simulations to explore how learning mechanisms may evolve to adjust the level of nestling begging (offspring signaling of need), and to examine the possible consequences of this process for parent-offspring conflict and communication. In doing so, we also provide the first step-by-step dynamic model of parent-offspring communication. The results confirm several previous theoretical predictions and demonstrate three novel phenomena. First, negatively frequency-dependent group-level selection can generate a stable polymorphism of learning strategies and parental responses. Second, while conventional reinforcement learning models fail to cope successfully with family dynamics at the nest, a newly developed learning model (incorporating behaviors that are consistent with recent experimental results on learning in nestling begging) produced effective learning, which evolved successfully. Third, while kin-selection affects the frequency of the different learning genes, its impact on begging slope and intensity was unexpectedly negligible, demonstrating that evolution is a complex process, and showing that the effect of kin-selection on behaviors that are shaped by learning may not be predicted by simple application of Hamilton's rule. Copyright © 2013 Elsevier Inc. All rights reserved.

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

Lessons from (co-)evolution in the docking of proteins and peptides for CAPRI Rounds 28-35.

PubMed

Yu, Jinchao; Andreani, Jessica; Ochsenbein, Françoise; Guerois, Raphaël

2017-03-01

Computational protein-protein docking is of great importance for understanding protein interactions at the structural level. Critical assessment of prediction of interactions (CAPRI) experiments provide the protein docking community with a unique opportunity to blindly test methods based on real-life cases and help accelerate methodology development. For CAPRI Rounds 28-35, we used an automatic docking pipeline integrating the coarse-grained co-evolution-based potential InterEvScore. This score was developed to exploit the information contained in the multiple sequence alignments of binding partners and selectively recognize co-evolved interfaces. Together with Zdock/Frodock for rigid-body docking, SOAP-PP for atomic potential and Rosetta applications for structural refinement, this pipeline reached high performance on a majority of targets. For protein-peptide docking and interfacial water position predictions, we also explored different means of taking evolutionary information into account. Overall, our group ranked 1 st by correctly predicting 10 targets, composed of 1 High, 7 Medium and 2 Acceptable predictions. Excellent and Outstanding levels of accuracy were reached for each of the two water prediction targets, respectively. Altogether, in 15 out of 18 targets in total, evolutionary information, either through co-evolution or conservation analyses, could provide key constraints to guide modeling towards the most likely assemblies. These results open promising perspectives regarding the way evolutionary information can be valuable to improve docking prediction accuracy. Proteins 2017; 85:378-390. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Predictability of the Ningaloo Niño/Niña

PubMed Central

Doi, Takeshi; Behera, Swadhin K.; Yamagata, Toshio

2013-01-01

The seasonal prediction of the coastal oceanic warm event off West Australia, recently named the Ningaloo Niño, is explored by use of a state-of-the-art ocean-atmosphere coupled general circulation model. The Ningaloo Niño/Niña, which generally matures in austral summer, is found to be predictable two seasons ahead. In particular, the unprecedented extreme warm event in February 2011 was successfully predicted 9 months in advance. The successful prediction of the Ningaloo Niño is mainly due to the high prediction skill of La Niña in the Pacific. However, the model deficiency to underestimate its early evolution and peak amplitude needs to be improved. Since the Ningaloo Niño/Niña has potential impacts on regional societies and industries through extreme events, the present success of its prediction may encourage development of its early warning system. PMID:24100593

Estuarine wetland evolution including sea-level rise and infrastructure effects.

NASA Astrophysics Data System (ADS)

Rodriguez, Jose Fernando; Trivisonno, Franco; Rojas, Steven Sandi; Riccardi, Gerardo; Stenta, Hernan; Saco, Patricia Mabel

2015-04-01

Estuarine wetlands are an extremely valuable resource in terms of biotic diversity, flood attenuation, storm surge protection, groundwater recharge, filtering of surface flows and carbon sequestration. On a large scale the survival of these systems depends on the slope of the land and a balance between the rates of accretion and sea-level rise, but local man-made flow disturbances can have comparable effects. Climate change predictions for most of Australia include an accelerated sea level rise, which may challenge the survival of estuarine wetlands. Furthermore, coastal infrastructure poses an additional constraint on the adaptive capacity of these ecosystems. Numerical models are increasingly being used to assess wetland dynamics and to help manage some of these situations. We present results of a wetland evolution model that is based on computed values of hydroperiod and tidal range that drive vegetation preference. Our first application simulates the long term evolution of an Australian wetland heavily constricted by infrastructure that is undergoing the effects of predicted accelerated sea level rise. The wetland presents a vegetation zonation sequence mudflats - mangrove - saltmarsh from the seaward margin and up the topographic gradient but is also affected by compartmentalization due to internal road embankments and culverts that effectively attenuates tidal input to the upstream compartments. For this reason, the evolution model includes a 2D hydrodynamic module which is able to handle man-made flow controls and spatially varying roughness. It continually simulates tidal inputs into the wetland and computes annual values of hydroperiod and tidal range to update vegetation distribution based on preference to hydrodynamic conditions of the different vegetation types. It also computes soil accretion rates and updates roughness coefficient values according to evolving vegetation types. In order to explore in more detail the magnitude of flow attenuation due to roughness and its effects on the computation of tidal range and hydroperiod, we performed numerical experiments simulating floodplain flow on the side of a tidal creek using different roughness values. Even though the values of roughness that produce appreciable changes in hydroperiod and tidal range are relatively high, they are within the range expected for some of the wetland vegetation. Both applications of the model show that flow attenuation can play a major role in wetland hydrodynamics and that its effects must be considered when predicting wetland evolution under climate change scenarios, particularly in situations where existing infrastructure affects the flow.

Texas lignite and the visual resource: an objective approach to visual resource evaluation and management

Treesearch

Harlow C. Landphair

1979-01-01

This paper relates the evolution of an empirical model used to predict public response to scenic quality objectively. The text relates the methods used to develop the visual quality index model, explains the terms used in the equation and briefly illustrates how the model is applied and how it is tested. While the technical application of the model relies heavily on...

Critical Zone Architecture and the Last Glacial Legacy in Unglaciated North America

NASA Astrophysics Data System (ADS)

Marshall, J. A.; Roering, J. J.; Rempel, A. W.; Bartlein, P. J.; Merritts, D. J.; Walter, R. C.

2015-12-01

As fresh bedrock is exhumed into the Critical Zone and intersects with water and life, rock attributes controlling geochemical reactions, hydrologic routing, accommodation space for roots, surface area, and the mobile fraction of regolith are set not just by present-day processes, but are predicated on the 'ghosts' of past processes embedded in the subsurface architecture. Easily observable modern ecosystem processes such as tree throw can erase the past and bias our interpretation of landscape evolution. Abundant paleoenvironmental records demonstrate that unglaciated regions experienced profound climate changes through the late Pleistocene-Holocene transition, but studies quantifying how environmental variables affect erosion and weathering rates in these settings often marginalize or even forego consideration of the role of past climate regimes. Here we combine seven downscaled Last Glacial Maximum (LGM) paleoclimate reconstructions with a state of the art frost cracking model to explore frost weathering potential across the North American continent 21 ka. We analyze existing evidence of LGM periglacial processes and features to better constrain frost weathering model predictions. All seven models predict frost cracking across a large swath to the west of the Continental Divide, with the southernmost extent at ~ latitude 35° N, and increasing latitude towards the buffering influence of the Pacific Ocean. All models predict significant frost cracking in the unglaciated Rocky Mountains. To the east of the Continental Divide, models results diverge more, but all predict regions with LGM temperatures too cold for significant frost cracking (mean annual temperatures < 15 °C), corroborated by observations of permafrost relics such as ice wedges in some areas. Our results provide a framework for coupling paleoclimate reconstructions with a predictive frost weathering model, and importantly, suggest that modeling modern Critical Zone process evolution may require a consideration of vastly different processes when rock was first exhumed into the Critical Zone reactor.

An idealised study for the long term evolution of crescentic bars

NASA Astrophysics Data System (ADS)

Chen, W. L.; Dodd, N.; Tiessen, M. C. H.; Calvete, D.

2018-01-01

An idealised study that identifies the mechanisms in the long term evolution of crescentic bar systems in nature is presented. Growth to finite amplitude (i.e., equilibration, sometimes referred to as saturation) and higher harmonic interaction are hypothesised to be the leading nonlinear effects in long-term evolution of these systems. These nonlinear effects are added to a linear stability model and used to predict crescentic bar development along a beach in Duck, North Carolina (USA) over a 2-month period. The equilibration prolongs the development of bed patterns, thus allowing the long term evolution. Higher harmonic interaction enables the amplitude to be transferred from longer to shorter lengthscales, which leads to the dominance of shorter lengthscales in latter post-storm stages, as observed at Duck. The comparison with observations indicates the importance of higher harmonic interaction in the development of nearshore crescentic bar systems in nature. Additionally, it is concluded that these nonlinear effects should be included in models simulating the development of different bed patterns, and that this points a way forward for long-term morphodynamical modelling in general.

The effects of a deleterious mutation load on patterns of influenza A/H3N2's antigenic evolution in humans

PubMed Central

Koelle, Katia; Rasmussen, David A

2015-01-01

Recent phylogenetic analyses indicate that RNA virus populations carry a significant deleterious mutation load. This mutation load has the potential to shape patterns of adaptive evolution via genetic linkage to beneficial mutations. Here, we examine the effect of deleterious mutations on patterns of influenza A subtype H3N2's antigenic evolution in humans. By first analyzing simple models of influenza that incorporate a mutation load, we show that deleterious mutations, as expected, act to slow the virus's rate of antigenic evolution, while making it more punctuated in nature. These models further predict three distinct molecular pathways by which antigenic cluster transitions occur, and we find phylogenetic patterns consistent with each of these pathways in influenza virus sequences. Simulations of a more complex phylodynamic model further indicate that antigenic mutations act in concert with deleterious mutations to reproduce influenza's spindly hemagglutinin phylogeny, co-circulation of antigenic variants, and high annual attack rates. DOI: http://dx.doi.org/10.7554/eLife.07361.001 PMID:26371556

Linking microstructural evolution and macro-scale friction behavior in metals [Predicting the friction behavior of metals using a microstructural evolution model

DOE PAGES

Argibay, N.; Chandross, M.; Cheng, S.; ...

2016-11-21

A correlation is established between the macro-scale friction regimes of metals and a transition between two dominant atomistic mechanisms of deformation. Metals tend to exhibit bi-stable friction behavior—low and converging or high and diverging. These general trends in behavior are shown to be largely explained using a simplified model based on grain size evolution, as a function of contact stress and temperature, and are demonstrated for self-mated pure copper and gold sliding contacts. Specifically, the low-friction regime (where µ < 0.5) is linked to the formation of ultra-nanocrystalline surface films (10–20 nm), driving toward shear accommodation by grain boundary sliding.more » Above a critical combination of stress and temperature—demonstrated to be a material property—shear accommodation transitions to dislocation dominated plasticity and high friction, with µ > 0.5. We utilize a combination of experimental and computational methods to develop and validate the proposed structure–property relationship. As a result, this quantitative framework provides a shift from phenomenological to mechanistic and predictive fundamental understanding of friction for crystalline materials, including engineering alloys.« less

The knowledge instinct, cognitive algorithms, modeling of language and cultural evolution

NASA Astrophysics Data System (ADS)

Perlovsky, Leonid I.

2008-04-01

The talk discusses mechanisms of the mind and their engineering applications. The past attempts at designing "intelligent systems" encountered mathematical difficulties related to algorithmic complexity. The culprit turned out to be logic, which in one way or another was used not only in logic rule systems, but also in statistical, neural, and fuzzy systems. Algorithmic complexity is related to Godel's theory, a most fundamental mathematical result. These difficulties were overcome by replacing logic with a dynamic process "from vague to crisp," dynamic logic. It leads to algorithms overcoming combinatorial complexity, and resulting in orders of magnitude improvement in classical problems of detection, tracking, fusion, and prediction in noise. I present engineering applications to pattern recognition, detection, tracking, fusion, financial predictions, and Internet search engines. Mathematical and engineering efficiency of dynamic logic can also be understood as cognitive algorithm, which describes fundamental property of the mind, the knowledge instinct responsible for all our higher cognitive functions: concepts, perception, cognition, instincts, imaginations, intuitions, emotions, including emotions of the beautiful. I present our latest results in modeling evolution of languages and cultures, their interactions in these processes, and role of music in cultural evolution. Experimental data is presented that support the theory. Future directions are outlined.

Emergent Neutrality in Adaptive Asexual Evolution

PubMed Central

Schiffels, Stephan; Szöllősi, Gergely J.; Mustonen, Ville; Lässig, Michael

2011-01-01

In nonrecombining genomes, genetic linkage can be an important evolutionary force. Linkage generates interference interactions, by which simultaneously occurring mutations affect each other’s chance of fixation. Here, we develop a comprehensive model of adaptive evolution in linked genomes, which integrates interference interactions between multiple beneficial and deleterious mutations into a unified framework. By an approximate analytical solution, we predict the fixation rates of these mutations, as well as the probabilities of beneficial and deleterious alleles at fixed genomic sites. We find that interference interactions generate a regime of emergent neutrality: all genomic sites with selection coefficients smaller in magnitude than a characteristic threshold have nearly random fixed alleles, and both beneficial and deleterious mutations at these sites have nearly neutral fixation rates. We show that this dynamic limits not only the speed of adaptation, but also a population’s degree of adaptation in its current environment. We apply the model to different scenarios: stationary adaptation in a time-dependent environment and approach to equilibrium in a fixed environment. In both cases, the analytical predictions are in good agreement with numerical simulations. Our results suggest that interference can severely compromise biological functions in an adapting population, which sets viability limits on adaptive evolution under linkage. PMID:21926305

The Limits to Parapatric Speciation: Dobzhansky–Muller Incompatibilities in a Continent–Island Model

PubMed Central

Bank, Claudia; Bürger, Reinhard; Hermisson, Joachim

2012-01-01

How much gene flow is needed to inhibit speciation by the accumulation of Dobzhansky–Muller incompatibilities (DMIs) in a structured population? Here, we derive these limits in a classical migration–selection model with two haploid or diploid loci and unidirectional gene flow from a continent to an island. We discuss the dependence of the maximum gene-flow rate on ecological factors (exogeneous selection), genetic factors (epistasis, recombination), and the evolutionary history. Extensive analytical and numerical results show the following: (1) The maximum rate of gene flow is limited by exogeneous selection. In particular, maintenance of neutral DMIs is impossible with gene flow. (2) There are two distinct mechanisms that drive DMI evolution in parapatry, selection against immigrants in a heterogeneous environment and selection against hybrids due to the incompatibility. (3) Depending on the mechanism, opposite predictions result concerning the genetic architecture that maximizes the rate of gene flow a DMI can sustain. Selection against immigrants favors evolution of tightly linked DMIs of arbitrary strength, whereas selection against hybrids promotes the evolution of strong unlinked DMIs. In diploids, the fitness of the double heterozygotes is the decisive factor to predict the pattern of DMI stability. PMID:22542972

Cellular Particle Dynamics simulation of biomechanical relaxation processes of multi-cellular systems

NASA Astrophysics Data System (ADS)

McCune, Matthew; Kosztin, Ioan

2013-03-01

Cellular Particle Dynamics (CPD) is a theoretical-computational-experimental framework for describing and predicting the time evolution of biomechanical relaxation processes of multi-cellular systems, such as fusion, sorting and compression. In CPD, cells are modeled as an ensemble of cellular particles (CPs) that interact via short range contact interactions, characterized by an attractive (adhesive interaction) and a repulsive (excluded volume interaction) component. The time evolution of the spatial conformation of the multicellular system is determined by following the trajectories of all CPs through numerical integration of their equations of motion. Here we present CPD simulation results for the fusion of both spherical and cylindrical multi-cellular aggregates. First, we calibrate the relevant CPD model parameters for a given cell type by comparing the CPD simulation results for the fusion of two spherical aggregates to the corresponding experimental results. Next, CPD simulations are used to predict the time evolution of the fusion of cylindrical aggregates. The latter is relevant for the formation of tubular multi-cellular structures (i.e., primitive blood vessels) created by the novel bioprinting technology. Work supported by NSF [PHY-0957914]. Computer time provided by the University of Missouri Bioinformatics Consortium.

Evolution of the luminosity function of extragalactic objects

NASA Technical Reports Server (NTRS)

Petrosian, V.

1985-01-01

A nonparametric procedure for determination of the evolution of the luminosity function of extragalactic objects and use of this for prediction of expected redshift and luminosity distribution of objects is described. The relation between this statistical evolution of the population and their physical evolution, such as the variation with cosmological epoch of their luminosity and formation rate is presented. This procedure when applied to a sample of optically selected quasars with redshifts less than two shows that the luminosity function evolves more strongly for higher luminosities, indicating a larger quasar activity at earlier epochs and a more rapid evolution of the objects during their higher luminosity phases. It is also shown that absence of many quasars at redshifts greater than three implies slowing down of this evolution in the conventional cosmological models, perhaps indicating that this is near the epoch of the birth of the quasar (and galaxies).

Host allometry influences the evolution of parasite host-generalism: theory and meta-analysis

PubMed Central

Hurford, Amy; Ellison, Amy R.

2017-01-01

Parasites vary widely in the diversity of hosts they infect: some parasite species are specialists—infecting just a single host species, while others are generalists, capable of infecting many. Understanding the factors that drive parasite host-generalism is of basic biological interest, but also directly relevant to predicting disease emergence in new host species, identifying parasites that are likely to have unidentified additional hosts, and assessing transmission risk. Here, we use mathematical models to investigate how variation in host body size and environmental temperature affect the evolution of parasite host-generalism. We predict that parasites are more likely to evolve a generalist strategy when hosts are large-bodied, when variation in host body size is large, and in cooler environments. We then explore these predictions using a newly updated database of over 20 000 fish–macroparasite associations. Within the database we see some evidence supporting these predictions, but also highlight mismatches between theory and data. By combining these two approaches, we establish a theoretical basis for interpreting empirical data on parasites' host specificity and identify key areas for future work that will help untangle the drivers of parasite host-generalism. This article is part of the themed issue ‘Opening the black box: re-examining the ecology and evolution of parasite transmission’. PMID:28289257

Host allometry influences the evolution of parasite host-generalism: theory and meta-analysis.

PubMed

Walker, Josephine G; Hurford, Amy; Cable, Jo; Ellison, Amy R; Price, Stephen J; Cressler, Clayton E

2017-05-05

Parasites vary widely in the diversity of hosts they infect: some parasite species are specialists-infecting just a single host species, while others are generalists, capable of infecting many. Understanding the factors that drive parasite host-generalism is of basic biological interest, but also directly relevant to predicting disease emergence in new host species, identifying parasites that are likely to have unidentified additional hosts, and assessing transmission risk. Here, we use mathematical models to investigate how variation in host body size and environmental temperature affect the evolution of parasite host-generalism. We predict that parasites are more likely to evolve a generalist strategy when hosts are large-bodied, when variation in host body size is large, and in cooler environments. We then explore these predictions using a newly updated database of over 20 000 fish-macroparasite associations. Within the database we see some evidence supporting these predictions, but also highlight mismatches between theory and data. By combining these two approaches, we establish a theoretical basis for interpreting empirical data on parasites' host specificity and identify key areas for future work that will help untangle the drivers of parasite host-generalism.This article is part of the themed issue 'Opening the black box: re-examining the ecology and evolution of parasite transmission'. © 2017 The Authors.

An elastic-plastic contact model for line contact structures

NASA Astrophysics Data System (ADS)

Zhu, Haibin; Zhao, Yingtao; He, Zhifeng; Zhang, Ruinan; Ma, Shaopeng

2018-06-01

Although numerical simulation tools are now very powerful, the development of analytical models is very important for the prediction of the mechanical behaviour of line contact structures for deeply understanding contact problems and engineering applications. For the line contact structures widely used in the engineering field, few analytical models are available for predicting the mechanical behaviour when the structures deform plastically, as the classic Hertz's theory would be invalid. Thus, the present study proposed an elastic-plastic model for line contact structures based on the understanding of the yield mechanism. A mathematical expression describing the global relationship between load history and contact width evolution of line contact structures was obtained. The proposed model was verified through an actual line contact test and a corresponding numerical simulation. The results confirmed that this model can be used to accurately predict the elastic-plastic mechanical behaviour of a line contact structure.

Modeling Progressive Damage Using Local Displacement Discontinuities Within the FEAMAC Multiscale Modeling Framework

NASA Technical Reports Server (NTRS)

Ranatunga, Vipul; Bednarcyk, Brett A.; Arnold, Steven M.

2010-01-01

A method for performing progressive damage modeling in composite materials and structures based on continuum level interfacial displacement discontinuities is presented. The proposed method enables the exponential evolution of the interfacial compliance, resulting in unloading of the tractions at the interface after delamination or failure occurs. In this paper, the proposed continuum displacement discontinuity model has been used to simulate failure within both isotropic and orthotropic materials efficiently and to explore the possibility of predicting the crack path, therein. Simulation results obtained from Mode-I and Mode-II fracture compare the proposed approach with the cohesive element approach and Virtual Crack Closure Techniques (VCCT) available within the ABAQUS (ABAQUS, Inc.) finite element software. Furthermore, an eccentrically loaded 3-point bend test has been simulated with the displacement discontinuity model, and the resulting crack path prediction has been compared with a prediction based on the extended finite element model (XFEM) approach.

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.

Controlled experiments of hillslope co-evolution at the Biosphere 2 Landscape Evolution Observatory: toward prediction of coupled hydrological, biogeochemical, and ecological change

NASA Astrophysics Data System (ADS)

Volkmann, T. H. M.; Sengupta, A.; Pangle, L.; Abramson, N.; Barron-Gafford, G.; Breshears, D. D.; Bugaj, A.; Chorover, J.; Dontsova, K.; Durcik, M.; Ferre, T. P. A.; Harman, C. J.; Hunt, E.; Huxman, T. E.; Kim, M.; Maier, R. M.; Matos, K.; Alves Meira Neto, A.; Meredith, L. K.; Monson, R. K.; Niu, G. Y.; Pelletier, J. D.; Rasmussen, C.; Ruiz, J.; Saleska, S. R.; Schaap, M. G.; Sibayan, M.; Tuller, M.; Van Haren, J. L. M.; Wang, Y.; Zeng, X.; Troch, P. A.

2017-12-01

Understanding the process interactions and feedbacks among water, microbes, plants, and porous geological media is crucial for improving predictions of the response of Earth's critical zone to future climatic conditions. However, the integrated co-evolution of landscapes under change is notoriously difficult to investigate. Laboratory studies are typically limited in spatial and temporal scale, while field studies lack observational density and control. To bridge the gap between controlled lab and uncontrolled field studies, the University of Arizona - Biosphere 2 built a macrocosm experiment of unprecedented scale: the Landscape Evolution Observatory (LEO). LEO consists of three replicated, 330-m2 hillslope landscapes inside a 5000-m2 environmentally controlled facility. The engineered landscapes contain 1-m depth of basaltic tephra ground to homogenous loamy sand that will undergo physical, chemical, and mineralogical changes over many years. Each landscape contains a dense sensor network capable of resolving water, carbon, and energy cycling processes at sub-meter to whole-landscape scale. Embedded sampling devices allow for quantification of biogeochemical processes, and facilitate the use of chemical tracers applied with the artificial rainfall. LEO is now fully operational and intensive forcing experiments have been launched. While operating the massive infrastructure poses significant challenges, LEO has demonstrated the capacity of tracking multi-scale matter and energy fluxes at a level of detail impossible in field experiments. Initial sensor, sampler, and restricted soil coring data are already providing insights into the tight linkages between water flow, weathering, and (micro-) biological community development during incipient landscape evolution. Over the years to come, these interacting processes are anticipated to drive the model systems to increasingly complex states, potentially perturbed by changes in climatic forcing. By intensively monitoring the evolutionary trajectory, integrating data with models, and fostering community-wide collaborations, we envision that emergent landscape structures and functions can be linked and significant progress can be made toward predicting the coupled hydro-biogeochemical and ecological responses to global change.

Constraints on Omega_0 and cluster evolution using the ROSAT log N-log S relation

NASA Astrophysics Data System (ADS)

Mathiesen, B.; Evrard, A. E.

1998-04-01

We examine the likelihoods of different cosmological models and cluster evolutionary histories by comparing semi-analytical predictions of X-ray cluster number counts with observational data from the ROSAT satellite. We model cluster abundance as a function of mass and redshift using a Press-Schechter distribution, and assume that the temperature T(M,z) and bolometric luminosity L_X(M,z) scale as power laws in mass and epoch, in order to construct expected counts as a function of X-ray flux. The L_X-M scaling is fixed using the local luminosity function, while the degree of evolution in the X-ray luminosity with redshift L_X~(1+z)^s is left open, with s an interesting free parameter which we investigate. We examine open and flat cosmologies with initial, scale-free fluctuation spectra having indices n=0, -1 and -2. An independent constraint arising from the slope of the luminosity-temperature relation strongly favours the n=-2 spectrum. The expected counts demonstrate a strong dependence on Omega_0 and s, with lesser dependence on lambda_0 and n. Comparison with the observed counts reveals a `ridge' of acceptable models in the Omega_0-s plane, roughly following the relation s~6Omega_0 and spanning low-density models with a small degree of evolution to Omega=1 models with strong evolution. Models with moderate evolution are revealed to have a strong lower limit of Omega_0>~0.3, and low-evolution models imply that Omega_0<1 at a very high confidence level. We suggest observational tests for breaking the degeneracy along this ridge, and discuss implications for evolutionary histories of the intracluster medium.

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.

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.

Chemical evolution in spiral and irregular galaxies

NASA Technical Reports Server (NTRS)

Torres-Peimbert, S.

1986-01-01

A brief review of models of chemical evolution of the interstellar medium in our galaxy and other galaxies is presented. These models predict the time variation and radial dependence of chemical composition in the gas as function of the input parameters; initial mass function, stellar birth rate, chemical composition of mass lost by stars during their evolution (yields), and the existence of large scale mass flows, like infall from the halo, outflow to the intergalactic medium or radial flows within a galaxy. At present there is a considerable wealth of observational data on the composition of HII regions in spiral and irregular galaxies to constrain the models. Comparisons are made between theory and the observed physical conditions. In particular, studies of helium, carbon, nitrogen and oxygen abundances are reviewed. In many molecular clouds the information we have on the amount of H2 is derived from the observed CO column density, and a standard CO/H2 ratio derived for the solar neighborhood. Chemical evolution models and the observed variations in O/H and N/O values, point out the need to include these results in a CO/H2 relation that should be, at least, a function of the O/H ratio. This aspect is also discussed.

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.

The plume head-continental lithosphere interaction using a tectonically realistic formulation for the lithosphere

NASA Astrophysics Data System (ADS)

Burov, E.; Guillou-Frottier, L.

2005-05-01

Current debates on the existence of mantle plumes largely originate from interpretations of supposed signatures of plume-induced surface topography that are compared with predictions of geodynamic models of plume-lithosphere interactions. These models often inaccurately predict surface evolution: in general, they assume a fixed upper surface and consider the lithosphere as a single viscous layer. In nature, the surface evolution is affected by the elastic-brittle-ductile deformation, by a free upper surface and by the layered structure of the lithosphere. We make a step towards reconciling mantle- and tectonic-scale studies by introducing a tectonically realistic continental plate model in large-scale plume-lithosphere interaction. This model includes (i) a natural free surface boundary condition, (ii) an explicit elastic-viscous(ductile)-plastic(brittle) rheology and (iii) a stratified structure of continental lithosphere. The numerical experiments demonstrate a number of important differences from predictions of conventional models. In particular, this relates to plate bending, mechanical decoupling of crustal and mantle layers and tension-compression instabilities, which produce transient topographic signatures such as uplift and subsidence at large (>500 km) and small scale (300-400, 200-300 and 50-100 km). The mantle plumes do not necessarily produce detectable large-scale topographic highs but often generate only alternating small-scale surface features that could otherwise be attributed to regional tectonics. A single large-wavelength deformation, predicted by conventional models, develops only for a very cold and thick lithosphere. Distinct topographic wavelengths or temporarily spaced events observed in the East African rift system, as well as over French Massif Central, can be explained by a single plume impinging at the base of the continental lithosphere, without evoking complex asthenospheric upwelling.

CO 2 Leakage Into Shallow Aquifers: Modeling CO 2 Gas Evolution and Accumulation at Interfaces of Heterogeneity

DOE PAGES

Porter, Mark L.; Plampin, Michael; Pawar, Rajesh; ...

2014-12-31

The physicochemical processes associated with CO 2 leakage into shallow aquifer systems are complex and span multiple spatial and time scales. Continuum-scale numerical models that faithfully represent the underlying pore-scale physics are required to predict the long-term behavior and aid in risk analysis regarding regulatory and management decisions. This study focuses on benchmarking the numerical simulator, FEHM, with intermediate-scale column experiments of CO 2 gas evolution in homogeneous and heterogeneous sand configurations. Inverse modeling was conducted to calibrate model parameters and determine model sensitivity to the observed steady-state saturation profiles. It is shown that FEHM is a powerful tool thatmore » is capable of capturing the experimentally observed out ow rates and saturation profiles. Moreover, FEHM captures the transition from single- to multi-phase flow and CO 2 gas accumulation at interfaces separating sands. We also derive a simple expression, based on Darcy's law, for the pressure at which CO 2 free phase gas is observed and show that it reliably predicts the location at which single-phase flow transitions to multi-phase flow.« less

Questions regarding the predictive value of one evolved complex adaptive system for a second: exemplified by the SOD1 mouse.

PubMed

Greek, Ray; Hansen, Lawrence A

2013-11-01

We surveyed the scientific literature regarding amyotrophic lateral sclerosis, the SOD1 mouse model, complex adaptive systems, evolution, drug development, animal models, and philosophy of science in an attempt to analyze the SOD1 mouse model of amyotrophic lateral sclerosis in the context of evolved complex adaptive systems. Humans and animals are examples of evolved complex adaptive systems. It is difficult to predict the outcome from perturbations to such systems because of the characteristics of complex systems. Modeling even one complex adaptive system in order to predict outcomes from perturbations is difficult. Predicting outcomes to one evolved complex adaptive system based on outcomes from a second, especially when the perturbation occurs at higher levels of organization, is even more problematic. Using animal models to predict human outcomes to perturbations such as disease and drugs should have a very low predictive value. We present empirical evidence confirming this and suggest a theory to explain this phenomenon. We analyze the SOD1 mouse model of amyotrophic lateral sclerosis in order to illustrate this position. Copyright © 2013 The Authors. Published by Elsevier Ltd.. All rights reserved.

Link prediction measures considering different neighbors’ effects and application in social networks

NASA Astrophysics Data System (ADS)

Luo, Peng; Wu, Chong; Li, Yongli

Link prediction measures have been attracted particular attention in the field of mathematical physics. In this paper, we consider the different effects of neighbors in link prediction and focus on four different situations: only consider the individual’s own effects; consider the effects of individual, neighbors and neighbors’ neighbors; consider the effects of individual, neighbors, neighbors’ neighbors, neighbors’ neighbors’ neighbors and neighbors’ neighbors’ neighbors’ neighbors; consider the whole network participants’ effects. Then, according to the four situations, we present our link prediction models which also take the effects of social characteristics into consideration. An artificial network is adopted to illustrate the parameter estimation based on logistic regression. Furthermore, we compare our methods with the some other link prediction methods (LPMs) to examine the validity of our proposed model in online social networks. The results show the superior of our proposed link prediction methods compared with others. In the application part, our models are applied to study the social network evolution and used to recommend friends and cooperators in social networks.

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.

Cancer evolution: mathematical models and computational inference.

PubMed

Beerenwinkel, Niko; Schwarz, Roland F; Gerstung, Moritz; Markowetz, Florian

2015-01-01

Cancer is a somatic evolutionary process characterized by the accumulation of mutations, which contribute to tumor growth, clinical progression, immune escape, and drug resistance development. Evolutionary theory can be used to analyze the dynamics of tumor cell populations and to make inference about the evolutionary history of a tumor from molecular data. We review recent approaches to modeling the evolution of cancer, including population dynamics models of tumor initiation and progression, phylogenetic methods to model the evolutionary relationship between tumor subclones, and probabilistic graphical models to describe dependencies among mutations. Evolutionary modeling helps to understand how tumors arise and will also play an increasingly important prognostic role in predicting disease progression and the outcome of medical interventions, such as targeted therapy. © The Author(s) 2014. Published by Oxford University Press on behalf of the Society of Systematic Biologists.

Confronting Models of Massive Star Evolution and Explosions with Remnant Mass Measurements

NASA Astrophysics Data System (ADS)

Raithel, Carolyn A.; Sukhbold, Tuguldur; Özel, Feryal

2018-03-01

The mass distribution of compact objects provides a fossil record that can be studied to uncover information on the late stages of massive star evolution, the supernova explosion mechanism, and the dense matter equation of state. Observations of neutron star masses indicate a bimodal Gaussian distribution, while the observed black hole mass distribution decays exponentially for stellar-mass black holes. We use these observed distributions to directly confront the predictions of stellar evolution models and the neutrino-driven supernova simulations of Sukhbold et al. We find strong agreement between the black hole and low-mass neutron star distributions created by these simulations and the observations. We show that a large fraction of the stellar envelope must be ejected, either during the formation of stellar-mass black holes or prior to the implosion through tidal stripping due to a binary companion, in order to reproduce the observed black hole mass distribution. We also determine the origins of the bimodal peaks of the neutron star mass distribution, finding that the low-mass peak (centered at ∼1.4 M ⊙) originates from progenitors with M ZAMS ≈ 9–18 M ⊙. The simulations fail to reproduce the observed peak of high-mass neutron stars (centered at ∼1.8 M ⊙) and we explore several possible explanations. We argue that the close agreement between the observed and predicted black hole and low-mass neutron star mass distributions provides new, promising evidence that these stellar evolution and explosion models capture the majority of relevant stellar, nuclear, and explosion physics involved in the formation of compact objects.

Computer simulation of solder joint failure

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

Burchett, S.N.; Frear, D.R.; Rashid, M.M.

The thermomechanical fatigue failure of solder joints is increasingly becoming an important reliability issue for electronic packages. The purpose of this Laboratory Directed Research and Development (LDRD) project was to develop computational tools for simulating the behavior of solder joints under strain and temperature cycling, taking into account the microstructural heterogeneities that exist in as-solidified near eutectic Sn-Pb joints, as well as subsequent microstructural evolution. The authors present two computational constitutive models, a two-phase model and a single-phase model, that were developed to predict the behavior of near eutectic Sn-Pb solder joints under fatigue conditions. Unique metallurgical tests provide themore » fundamental input for the constitutive relations. The two-phase model mathematically predicts the heterogeneous coarsening behavior of near eutectic Sn-Pb solder. The finite element simulations with this model agree qualitatively with experimental thermomechanical fatigue tests. The simulations show that the presence of an initial heterogeneity in the solder microstructure could significantly degrade the fatigue lifetime. The single-phase model was developed to predict solder joint behavior using materials data for constitutive relation constants that could be determined through straightforward metallurgical experiments. Special thermomechanical fatigue tests were developed to give fundamental materials input to the models, and an in situ SEM thermomechanical fatigue test system was developed to characterize microstructural evolution and the mechanical behavior of solder joints during the test. A shear/torsion test sample was developed to impose strain in two different orientations. Materials constants were derived from these tests. The simulation results from the two-phase model showed good fit to the experimental test results.« less

Velocity bias in the distribution of dark matter halos

NASA Astrophysics Data System (ADS)

Baldauf, Tobias; Desjacques, Vincent; Seljak, Uroš

2015-12-01

The standard formalism for the coevolution of halos and dark matter predicts that any initial halo velocity bias rapidly decays to zero. We argue that, when the purpose is to compute statistics like power spectra etc., the coupling in the momentum conservation equation for the biased tracers must be modified. Our new formulation predicts the constancy in time of any statistical halo velocity bias present in the initial conditions, in agreement with peak theory. We test this prediction by studying the evolution of a conserved halo population in N -body simulations. We establish that the initial simulated halo density and velocity statistics show distinct features of the peak model and, thus, deviate from the simple local Lagrangian bias. We demonstrate, for the first time, that the time evolution of their velocity is in tension with the rapid decay expected in the standard approach.

The dynamics of recreation participation: ski touring in Minnesota

Treesearch

Timothy B. Knopp; G. Ballman; L. C. Merriam

1980-01-01

A realistic model or framework for the analysis of recreation behavior must be both comprehensive and dynamic. Most attempts to explain recreation behavior are static in that they do not allow for changes in the character of an activity or the evolution of a participant's involvement. Even predictive models tend to assume that relationships remain constant over...

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.)

Atomic scale modeling of defect production and microstructure evolution in irradiated metals

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

Diaz de la Rubia, T.; Soneda, N.; Shimomura, Y.

1997-04-01

Irradiation effects in materials depend in a complex way on the form of the as-produced primary damage state and its spatial and temporal evolution. Thus, while collision cascades produce defects on a time scale of tens of picosecond, diffusion occurs over much longer time scales, of the order of seconds, and microstructure evolution over even longer time scales. In this report the authors present work aimed at describing damage production and evolution in metals across all the relevant time and length scales. They discuss results of molecular dynamics simulations of displacement cascades in Fe and V. They show that interstitialmore » clusters are produced in cascades above 5 keV, but not vacancy clusters. Next, they discuss the development of a kinetic Monte Carlo model that enables calculations of damage evolution over much longer time scales (1000`s of s) than the picosecond lifetime of the cascade. They demonstrate the applicability of the method by presenting predictions on the fraction of freely migrating defects in {alpha}Fe during irradiation at 600 K.« less