Modelling of Patterns in Space and Time

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Murray, James

1984-01-01

This volume contains a selection of papers presented at the work­ shop "Modelling of Patterns in Space and Time", organized by the 80nderforschungsbereich 123, "8tochastische Mathematische Modelle", in Heidelberg, July 4-8, 1983. The main aim of this workshop was to bring together physicists, chemists, biologists and mathematicians for an exchange of ideas and results in modelling patterns. Since the mathe­ matical problems arising depend only partially on the particular field of applications the interdisciplinary cooperation proved very useful. The workshop mainly treated phenomena showing spatial structures. The special areas covered were morphogenesis, growth in cell cultures, competition systems, structured populations, chemotaxis, chemical precipitation, space-time oscillations in chemical reactors, patterns in flames and fluids and mathematical methods. The discussions between experimentalists and theoreticians were especially interesting and effective. The editors hope that these proceedings reflect ...

Size- and food-dependent growth drives patterns of competitive dominance along productivity gradients.

Science.gov (United States)

Huss, Magnus; Gårdmark, Anna; Van Leeuwen, Anieke; de Roos, André M

2012-04-01

Patterns of coexistence among competing species exhibiting size- and food-dependent growth remain largely unexplored. Here we studied mechanisms behind coexistence and shifts in competitive dominance in a size-structured fish guild, representing sprat and herring stocks in the Baltic Sea, using a physiologically structured model of competing populations. The influence of degree of resource overlap and the possibility of undergoing ontogenetic diet shifts were studied as functions of zooplankton and zoobenthos productivity. By imposing different size-dependent mortalities, we could study the outcome of competition under contrasting environmental regimes representing poor and favorable growth conditions. We found that the identity of the dominant species shifted between low and high productivity. Adding a herring-exclusive benthos resource only provided a competitive advantage over sprat when size-dependent mortality was high enough to allow for rapid growth in the zooplankton niche. Hence, the importance of a bottom-up effect of varying productivity was dependent on a strong top-down effect. Although herring could depress shared resources to lower levels than could sprat and also could access an exclusive resource, the smaller size at maturation of sprat allowed it to coexist with herring and, in some cases, exclude it. Our model system, characterized by interactions among size cohorts, allowed for consumer coexistence even at full resource overlap at intermediate productivities when size-dependent mortality was low. Observed shifts in community patterns were crucially dependent on the explicit consideration of size- and food-dependent growth. Accordingly, we argue that accounting for food-dependent growth and size-dependent interactions is necessary to better predict changes in community structure and dynamics following changes in major ecosystem drivers such as resource productivity and mortality, which are fundamental for our ability to manage exploitation of

Khat (Catha edulis Forsk. Dependence Potential and Pattern of Use in Saudi Arabia

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Siddig Ibrahim Abdelwahab

2015-01-01

Full Text Available Background. Catha edulis Forsk. (Khat is used for its psychoactive effects among people in Africa and the Arabian Peninsula, although its utilization is illegal in some countries such as Saudi Arabia. This study examined the pattern of Khat use and assessed the applicability of the Drug Abuse Screening Test-10 (DAST-10 to measure Khat dependence. Methods. A pretested questionnaire was used to gather data from 603 respondents. Variables included demographic characteristics, pattern of use, reasons for Khat chewing, and DAST-10. Stepwise-logistic regression was used to explore predictors of Khat dependence. Results. The majority of the respondents were married, had a secondary school level of education, were employed, were younger than 35 years old, and were living in rural areas. Many chewers gave more than one reason for using Khat. It was mainly used to increase mental capacity, physical strength, and social entertainment, as well as enhance cheerfulness and orgasms. Statistical modeling of Khat dependence suggested that the most significant predictors were residence (OR = 1.67, P<0.02, frequency of Khat chewing (OR = 4.8, P<0.01, age of starting Khat chewing (OR = 1.15, P<0.01, and time of Khat effect (OR = 1.15, P<0.04. Conclusion. Our study provides important information on the pattern of Khat use and its potential to cause dependence.

An equilibrium-point model for fast, single-joint movement: I. Emergence of strategy-dependent EMG patterns.

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Latash, M L; Gottlieb, G L

1991-09-01

We describe a model for the regulation of fast, single-joint movements, based on the equilibrium-point hypothesis. Limb movement follows constant rate shifts of independently regulated neuromuscular variables. The independently regulated variables are tentatively identified as thresholds of a length sensitive reflex for each of the participating muscles. We use the model to predict EMG patterns associated with changes in the conditions of movement execution, specifically, changes in movement times, velocities, amplitudes, and moments of limb inertia. The approach provides a theoretical neural framework for the dual-strategy hypothesis, which considers certain movements to be results of one of two basic, speed-sensitive or speed-insensitive strategies. This model is advanced as an alternative to pattern-imposing models based on explicit regulation of timing and amplitudes of signals that are explicitly manifest in the EMG patterns.

Vegetation pattern formation in a fog-dependent ecosystem.

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Borthagaray, Ana I; Fuentes, Miguel A; Marquet, Pablo A

2010-07-07

Vegetation pattern formation is a striking characteristic of several water-limited ecosystems around the world. Typically, they have been described on runoff-based ecosystems emphasizing local interactions between water, biomass interception, growth and dispersal. Here, we show that this situation is by no means general, as banded patterns in vegetation can emerge in areas without rainfall and in plants without functional root (the Bromeliad Tillandsia landbeckii) and where fog is the principal source of moisture. We show that a simple model based on the advection of fog-water by wind and its interception by the vegetation can reproduce banded patterns which agree with empirical patterns observed in the Coastal Atacama Desert. Our model predicts how the parameters may affect the conditions to form the banded pattern, showing a transition from a uniform vegetated state, at high water input or terrain slope to a desert state throughout intermediate banded states. Moreover, the model predicts that the pattern wavelength is a decreasing non-linear function of fog-water input and slope, and an increasing function of plant loss and fog-water flow speed. Finally, we show that the vegetation density is increased by the formation of the regular pattern compared to the density expected by the spatially homogeneous model emphasizing the importance of self-organization in arid ecosystems. (c) 2010 Elsevier Ltd. All rights reserved.

A Muscle’s Force Depends on the Recruitment Patterns of Its Fibers

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Wakeling, James M.; Lee, Sabrina S. M.; Arnold, Allison S.; de Boef Miara, Maria; Biewener, Andrew A.

2012-01-01

Biomechanical models of whole muscles commonly used in simulations of musculoskeletal function and movement typically assume that the muscle generates force as a scaled-up muscle fiber. However, muscles are comprised of motor units that have different intrinsic properties and that can be activated at different times. This study tested whether a muscle model comprised of motor units that could be independently activated resulted in more accurate predictions of force than traditional Hill-type models. Forces predicted by the models were evaluated by direct comparison with the muscle forces measured in situ from the gastrocnemii in goats. The muscle was stimulated tetanically at a range of frequencies, muscle fiber strains were measured using sonomicrometry, and the activation patterns of the different types of motor unit were calculated from electromyographic recordings. Activation patterns were input into five different muscle models. Four models were traditional Hill-type models with different intrinsic speeds and fiber-type properties. The fifth model incorporated differential groups of fast and slow motor units. For all goats, muscles and stimulation frequencies the differential model resulted in the best predictions of muscle force. The in situ muscle output was shown to depend on the recruitment of different motor units within the muscle. PMID:22350666

Time-dependent patterns in quasivertical cylindrical binary convection

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Alonso, Arantxa; Mercader, Isabel; Batiste, Oriol

2018-02-01

This paper reports on numerical investigations of the effect of a slight inclination α on pattern formation in a shallow vertical cylindrical cell heated from below for binary mixtures with a positive value of the Soret coefficient. By using direct numerical simulation of the three-dimensional Boussinesq equations with Soret effect in cylindrical geometry, we show that a slight inclination of the cell in the range α ≈0.036 rad =2∘ strongly influences pattern selection. The large-scale shear flow (LSSF) induced by the small tilt of gravity overcomes the squarelike arrangements observed in noninclined cylinders in the Soret regime, stratifies the fluid along the direction of inclination, and produces an enhanced separation of the two components of the mixture. The competition between shear effects and horizontal and vertical buoyancy alters significantly the dynamics observed in noninclined convection. Additional unexpected time-dependent patterns coexist with the basic LSSF. We focus on an unsual periodic state recently discovered in an experiment, the so-called superhighway convection state (SHC), in which ascending and descending regions of fluid move in opposite directions. We provide numerical confirmation that Boussinesq Navier-Stokes equations with standard boundary conditions contain the essential ingredients that allow for the existence of such a state. Also, we obtain a persistent heteroclinic structure where regular oscillations between a SHC pattern and a state of nearly stationary longitudinal rolls take place. We characterize numerically these time-dependent patterns and investigate the dynamics around the threshold of convection.

Patterns, Attitudes, and Dependence toward WhatsApp among College Students

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Harshavardhan Sampath

2017-01-01

Full Text Available Background: WhatsApp (WA, a free cross-platform smartphone application has revolutionized social communication over the virtual world. It enables information sharing, both personal and professional, individually and across social groups. Despite these positive changes, there have been concerns about excessive WA use, especially among college students, resulting in the neglect of important social and academic commitments. However, there is lack of quality research on WA use in this vulnerable population. Aims: The aim of this study is to understand the patterns and attitudes toward WA use and measure the level of dependence among college students. Materials and Methods: In a sample of 150 undergraduate medical college students who provided informed consent, comprehensive questionnaires were administered to assess the patterns, attitudes, and dependence toward WA use. Results: WA was the most common social media platform used (70% which eclipsed the time spend on other apps (Facebook, Twitter, etc. While half of the students spent 1–2 h/day, a significant minority (10.67% spent almost 6–7 h/day on WA. Nearly 12% (n = 18 of students qualified for WA dependence. There were no significant differences in patterns of WA use between students with or without WA dependence. Students with WA dependence had significantly lesser negative attitudes toward its use compared to the rest. Scores on all dimensions of WA addiction, namely, salience, mood modification, tolerance, withdrawal, conflict, and relapse were significantly higher in students with WA dependence. Conclusion: WA dependence is an emerging behavioral addiction among college students. With no specific pattern of use to distinguish dependent users, it is difficult to recognize this problem. Changing the attitudes towards WA use by creating awareness about it's addictive potential, monitoring and restricting the use of mobile phones especially during class hours, encouraging face to face

Time-series analysis of multiple foreign exchange rates using time-dependent pattern entropy

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Ishizaki, Ryuji; Inoue, Masayoshi

2018-01-01

Time-dependent pattern entropy is a method that reduces variations to binary symbolic dynamics and considers the pattern of symbols in a sliding temporal window. We use this method to analyze the instability of daily variations in multiple foreign exchange rates. The time-dependent pattern entropy of 7 foreign exchange rates (AUD/USD, CAD/USD, CHF/USD, EUR/USD, GBP/USD, JPY/USD, and NZD/USD) was found to be high in the long period after the Lehman shock, and be low in the long period after Mar 2012. We compared the correlation matrix between exchange rates in periods of high and low of the time-dependent pattern entropy.

A model for optimizing file access patterns using spatio-temporal parallelism

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Boonthanome, Nouanesengsy [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Patchett, John [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Geveci, Berk [Kitware Inc., Clifton Park, NY (United States); Ahrens, James [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Bauer, Andy [Kitware Inc., Clifton Park, NY (United States); Chaudhary, Aashish [Kitware Inc., Clifton Park, NY (United States); Miller, Ross G. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Shipman, Galen M. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Williams, Dean N. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

2013-01-01

For many years now, I/O read time has been recognized as the primary bottleneck for parallel visualization and analysis of large-scale data. In this paper, we introduce a model that can estimate the read time for a file stored in a parallel filesystem when given the file access pattern. Read times ultimately depend on how the file is stored and the access pattern used to read the file. The file access pattern will be dictated by the type of parallel decomposition used. We employ spatio-temporal parallelism, which combines both spatial and temporal parallelism, to provide greater flexibility to possible file access patterns. Using our model, we were able to configure the spatio-temporal parallelism to design optimized read access patterns that resulted in a speedup factor of approximately 400 over traditional file access patterns.

Modelling survival: exposure pattern, species sensitivity and uncertainty.

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Ashauer, Roman; Albert, Carlo; Augustine, Starrlight; Cedergreen, Nina; Charles, Sandrine; Ducrot, Virginie; Focks, Andreas; Gabsi, Faten; Gergs, André; Goussen, Benoit; Jager, Tjalling; Kramer, Nynke I; Nyman, Anna-Maija; Poulsen, Veronique; Reichenberger, Stefan; Schäfer, Ralf B; Van den Brink, Paul J; Veltman, Karin; Vogel, Sören; Zimmer, Elke I; Preuss, Thomas G

2016-07-06

The General Unified Threshold model for Survival (GUTS) integrates previously published toxicokinetic-toxicodynamic models and estimates survival with explicitly defined assumptions. Importantly, GUTS accounts for time-variable exposure to the stressor. We performed three studies to test the ability of GUTS to predict survival of aquatic organisms across different pesticide exposure patterns, time scales and species. Firstly, using synthetic data, we identified experimental data requirements which allow for the estimation of all parameters of the GUTS proper model. Secondly, we assessed how well GUTS, calibrated with short-term survival data of Gammarus pulex exposed to four pesticides, can forecast effects of longer-term pulsed exposures. Thirdly, we tested the ability of GUTS to estimate 14-day median effect concentrations of malathion for a range of species and use these estimates to build species sensitivity distributions for different exposure patterns. We find that GUTS adequately predicts survival across exposure patterns that vary over time. When toxicity is assessed for time-variable concentrations species may differ in their responses depending on the exposure profile. This can result in different species sensitivity rankings and safe levels. The interplay of exposure pattern and species sensitivity deserves systematic investigation in order to better understand how organisms respond to stress, including humans.

Large-Scale Patterns in a Minimal Cognitive Flocking Model: Incidental Leaders, Nematic Patterns, and Aggregates

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Barberis, Lucas; Peruani, Fernando

2016-12-01

We study a minimal cognitive flocking model, which assumes that the moving entities navigate using the available instantaneous visual information exclusively. The model consists of active particles, with no memory, that interact by a short-ranged, position-based, attractive force, which acts inside a vision cone (VC), and lack velocity-velocity alignment. We show that this active system can exhibit—due to the VC that breaks Newton's third law—various complex, large-scale, self-organized patterns. Depending on parameter values, we observe the emergence of aggregates or millinglike patterns, the formation of moving—locally polar—files with particles at the front of these structures acting as effective leaders, and the self-organization of particles into macroscopic nematic structures leading to long-ranged nematic order. Combining simulations and nonlinear field equations, we show that position-based active models, as the one analyzed here, represent a new class of active systems fundamentally different from other active systems, including velocity-alignment-based flocking systems. The reported results are of prime importance in the study, interpretation, and modeling of collective motion patterns in living and nonliving active systems.

Simulating discrete models of pattern formation by ion beam sputtering

International Nuclear Information System (INIS)

Hartmann, Alexander K; Kree, Reiner; Yasseri, Taha

2009-01-01

A class of simple, (2+1)-dimensional, discrete models is reviewed, which allow us to study the evolution of surface patterns on solid substrates during ion beam sputtering (IBS). The models are based on the same assumptions about the erosion process as the existing continuum theories. Several distinct physical mechanisms of surface diffusion are added, which allow us to study the interplay of erosion-driven and diffusion-driven pattern formation. We present results from our own work on evolution scenarios of ripple patterns, especially for longer timescales, where nonlinear effects become important. Furthermore we review kinetic phase diagrams, both with and without sample rotation, which depict the systematic dependence of surface patterns on the shape of energy depositing collision cascades after ion impact. Finally, we discuss some results from more recent work on surface diffusion with Ehrlich-Schwoebel barriers as the driving force for pattern formation during IBS and on Monte Carlo simulations of IBS with codeposition of surfactant atoms.

Time-series analysis of foreign exchange rates using time-dependent pattern entropy

Science.gov (United States)

Ishizaki, Ryuji; Inoue, Masayoshi

2013-08-01

Time-dependent pattern entropy is a method that reduces variations to binary symbolic dynamics and considers the pattern of symbols in a sliding temporal window. We use this method to analyze the instability of daily variations in foreign exchange rates, in particular, the dollar-yen rate. The time-dependent pattern entropy of the dollar-yen rate was found to be high in the following periods: before and after the turning points of the yen from strong to weak or from weak to strong, and the period after the Lehman shock.

Dependency distance: A new perspective on syntactic patterns in natural languages

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Liu, Haitao; Xu, Chunshan; Liang, Junying

2017-07-01

Dependency distance, measured by the linear distance between two syntactically related words in a sentence, is generally held as an important index of memory burden and an indicator of syntactic difficulty. Since this constraint of memory is common for all human beings, there may well be a universal preference for dependency distance minimization (DDM) for the sake of reducing memory burden. This human-driven language universal is supported by big data analyses of various corpora that consistently report shorter overall dependency distance in natural languages than in artificial random languages and long-tailed distributions featuring a majority of short dependencies and a minority of long ones. Human languages, as complex systems, seem to have evolved to come up with diverse syntactic patterns under the universal pressure for dependency distance minimization. However, there always exist a small number of long-distance dependencies in natural languages, which may reflect some other biological or functional constraints. Language system may adapt itself to these sporadic long-distance dependencies. It is these universal constraints that have shaped such a rich diversity of syntactic patterns in human languages.

Voronoi Cell Patterns: theoretical model and application to submonolayer growth

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González, Diego Luis; Einstein, T. L.

2012-02-01

We use a simple fragmentation model to describe the statistical behavior of the Voronoi cell patterns generated by a homogeneous and isotropic set of points in 1D and in 2D. In particular, we are interested in the distribution of sizes of these Voronoi cells. Our model is completely defined by two probability distributions in 1D and again in 2D, the probability to add a new point inside an existing cell and the probability that this new point is at a particular position relative to the preexisting point inside this cell. In 1D the first distribution depends on a single parameter while the second distribution is defined through a fragmentation kernel; in 2D both distributions depend on a single parameter. The fragmentation kernel and the control parameters are closely related to the physical properties of the specific system under study. We apply our model to describe the Voronoi cell patterns of island nucleation for critical island sizes i=0,1,2,3. Experimental results for the Voronoi cells of InAs/GaAs quantum dots are also described by our model.

Deterministic integer multiple firing depending on initial state in Wang model

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Xie Yong [Institute of Nonlinear Dynamics, MSSV, Department of Engineering Mechanics, Xi' an Jiaotong University, Xi' an 710049 (China)]. E-mail: yxie@mail.xjtu.edu.cn; Xu Jianxue [Institute of Nonlinear Dynamics, MSSV, Department of Engineering Mechanics, Xi' an Jiaotong University, Xi' an 710049 (China); Jiang Jun [Institute of Nonlinear Dynamics, MSSV, Department of Engineering Mechanics, Xi' an Jiaotong University, Xi' an 710049 (China)

2006-12-15

We investigate numerically dynamical behaviour of the Wang model, which describes the rhythmic activities of thalamic relay neurons. The model neuron exhibits Type I excitability from a global view, but Type II excitability from a local view. There exists a narrow range of bistability, in which a subthreshold oscillation and a suprathreshold firing behaviour coexist. A special firing pattern, integer multiple firing can be found in the certain part of the bistable range. The characteristic feature of such firing pattern is that the histogram of interspike intervals has a multipeaked structure, and the peaks are located at about integer multiples of a basic interspike interval. Since the Wang model is noise-free, the integer multiple firing is a deterministic firing pattern. The existence of bistability leads to the deterministic integer multiple firing depending on the initial state of the model neuron, i.e., the initial values of the state variables.

Deterministic integer multiple firing depending on initial state in Wang model

International Nuclear Information System (INIS)

Xie Yong; Xu Jianxue; Jiang Jun

2006-01-01

We investigate numerically dynamical behaviour of the Wang model, which describes the rhythmic activities of thalamic relay neurons. The model neuron exhibits Type I excitability from a global view, but Type II excitability from a local view. There exists a narrow range of bistability, in which a subthreshold oscillation and a suprathreshold firing behaviour coexist. A special firing pattern, integer multiple firing can be found in the certain part of the bistable range. The characteristic feature of such firing pattern is that the histogram of interspike intervals has a multipeaked structure, and the peaks are located at about integer multiples of a basic interspike interval. Since the Wang model is noise-free, the integer multiple firing is a deterministic firing pattern. The existence of bistability leads to the deterministic integer multiple firing depending on the initial state of the model neuron, i.e., the initial values of the state variables

Patterns of data modeling

CERN Document Server

Blaha, Michael

2010-01-01

Best-selling author and database expert with more than 25 years of experience modeling application and enterprise data, Dr. Michael Blaha provides tried and tested data model patterns, to help readers avoid common modeling mistakes and unnecessary frustration on their way to building effective data models. Unlike the typical methodology book, "Patterns of Data Modeling" provides advanced techniques for those who have mastered the basics. Recognizing that database representation sets the path for software, determines its flexibility, affects its quality, and influences whether it succ

Dependency distance: A new perspective on syntactic patterns in natural languages.

Science.gov (United States)

Liu, Haitao; Xu, Chunshan; Liang, Junying

2017-07-01

Dependency distance, measured by the linear distance between two syntactically related words in a sentence, is generally held as an important index of memory burden and an indicator of syntactic difficulty. Since this constraint of memory is common for all human beings, there may well be a universal preference for dependency distance minimization (DDM) for the sake of reducing memory burden. This human-driven language universal is supported by big data analyses of various corpora that consistently report shorter overall dependency distance in natural languages than in artificial random languages and long-tailed distributions featuring a majority of short dependencies and a minority of long ones. Human languages, as complex systems, seem to have evolved to come up with diverse syntactic patterns under the universal pressure for dependency distance minimization. However, there always exist a small number of long-distance dependencies in natural languages, which may reflect some other biological or functional constraints. Language system may adapt itself to these sporadic long-distance dependencies. It is these universal constraints that have shaped such a rich diversity of syntactic patterns in human languages. Copyright © 2017. Published by Elsevier B.V.

Turing and Non-Turing patterns in diffusive plankton model

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N. K. Thakur

2015-03-01

Full Text Available In this paper, we investigate a Rosenzweig-McAurthur model and its variant for phytoplankton, zooplankton and fish population dynamics with Holling type II and III functional responses. We present the theoretical analysis of processes of pattern formation that involves organism distribution and their interaction of spatially distributed population with local diffusion. The choice of parameter values is important to study the effect of diffusion, also it depends more on the nonlinearity of the system. With the help of numerical simulations, we observe the formation of spatiotemporal patterns both inside and outside the Turing space.

Modeling Architectural Patterns Using Architectural Primitives

NARCIS (Netherlands)

Zdun, Uwe; Avgeriou, Paris

2005-01-01

Architectural patterns are a key point in architectural documentation. Regrettably, there is poor support for modeling architectural patterns, because the pattern elements are not directly matched by elements in modeling languages, and, at the same time, patterns support an inherent variability that

Detecting Hidden Diversification Shifts in Models of Trait-Dependent Speciation and Extinction.

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Beaulieu, Jeremy M; O'Meara, Brian C

2016-07-01

The distribution of diversity can vary considerably from clade to clade. Attempts to understand these patterns often employ state-dependent speciation and extinction models to determine whether the evolution of a particular novel trait has increased speciation rates and/or decreased extinction rates. It is still unclear, however, whether these models are uncovering important drivers of diversification, or whether they are simply pointing to more complex patterns involving many unmeasured and co-distributed factors. Here we describe an extension to the popular state-dependent speciation and extinction models that specifically accounts for the presence of unmeasured factors that could impact diversification rates estimated for the states of any observed trait, addressing at least one major criticism of BiSSE (Binary State Speciation and Extinction) methods. Specifically, our model, which we refer to as HiSSE (Hidden State Speciation and Extinction), assumes that related to each observed state in the model are "hidden" states that exhibit potentially distinct diversification dynamics and transition rates than the observed states in isolation. We also demonstrate how our model can be used as character-independent diversification models that allow for a complex diversification process that is independent of the evolution of a character. Under rigorous simulation tests and when applied to empirical data, we find that HiSSE performs reasonably well, and can at least detect net diversification rate differences between observed and hidden states and detect when diversification rate differences do not correlate with the observed states. We discuss the remaining issues with state-dependent speciation and extinction models in general, and the important ways in which HiSSE provides a more nuanced understanding of trait-dependent diversification. © The Author(s) 2016. Published by Oxford University Press, on behalf of the Society of Systematic Biologists. All rights reserved

Patterns of drug dependence in a Queensland (Australia) sample of Indigenous and non-Indigenous people who inject drugs.

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Smirnov, Andrew; Kemp, Robert; Ward, James; Henderson, Suzanna; Williams, Sidney; Dev, Abhilash; Najman, Jake M

2016-09-01

Despite over-representation of Indigenous Australians in sentinel studies of injecting drug use, little is known about relevant patterns of drug use and dependence. This study compares drug dependence and possible contributing factors in Indigenous and non-Indigenous Australians who inject drugs. Respondent-driven sampling was used in major cities and 'peer recruitment' in regional towns of Queensland to obtain a community sample of Indigenous (n = 282) and non-Indigenous (n = 267) injectors. Data are cross sectional. Multinomial models were developed for each group to examine types of dependence on injected drugs (no dependence, methamphetamine-dependent only, opioid-dependent only, dependent on methamphetamine and opioids). Around one-fifth of Indigenous and non-Indigenous injectors were dependent on both methamphetamine and opioids in the previous 12 months. Psychological distress was associated with dual dependence on these drugs for Indigenous [adjusted relative risk (ARR) 4.86, 95% confidence interval (CI) 2.08-11.34] and non-Indigenous (ARR 4.14, 95% CI 1.59-10.78) participants. Unemployment (ARR 8.98, 95% CI 2.25-35.82) and repeated (> once) incarceration as an adult (ARR 3.78, 95% CI 1.43-9.97) were associated with dual dependence for Indigenous participants only. Indigenous participants had high rates of alcohol dependence, except for those dependent on opioids only. The drug dependence patterns of Indigenous and non-Indigenous people who inject drugs were similar, including the proportions dependent on both methamphetamine and opioids. However, for Indigenous injectors, there was a stronger association between drug dependence and contextual factors such as unemployment and incarceration. Expansion of treatment options and community-level programs may be required. [Smirnov A, Kemp R, Ward J, Henderson S, Williams S, Dev A, Najman J M. Patterns of drug dependence in a Queensland (Australia) sample of Indigenous and non-Indigenous people who

Stochastic Modeling of Usage Patterns in a Web-Based Information System.

Science.gov (United States)

Chen, Hui-Min; Cooper, Michael D.

2002-01-01

Uses continuous-time stochastic models, mainly based on semi-Markov chains, to derive user state transition patterns, both in rates and in probabilities, in a Web-based information system. Describes search sessions from transaction logs of the University of California's MELVYL library catalog system and discusses sequential dependency. (Author/LRW)

A software tool to model genetic regulatory networks. Applications to the modeling of threshold phenomena and of spatial patterning in Drosophila.

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Rui Dilão

Full Text Available We present a general methodology in order to build mathematical models of genetic regulatory networks. This approach is based on the mass action law and on the Jacob and Monod operon model. The mathematical models are built symbolically by the Mathematica software package GeneticNetworks. This package accepts as input the interaction graphs of the transcriptional activators and repressors of a biological process and, as output, gives the mathematical model in the form of a system of ordinary differential equations. All the relevant biological parameters are chosen automatically by the software. Within this framework, we show that concentration dependent threshold effects in biology emerge from the catalytic properties of genes and its associated conservation laws. We apply this methodology to the segment patterning in Drosophila early development and we calibrate the genetic transcriptional network responsible for the patterning of the gap gene proteins Hunchback and Knirps, along the antero-posterior axis of the Drosophila embryo. In this approach, the zygotically produced proteins Hunchback and Knirps do not diffuse along the antero-posterior axis of the embryo of Drosophila, developing a spatial pattern due to concentration dependent thresholds. This shows that patterning at the gap genes stage can be explained by the concentration gradients along the embryo of the transcriptional regulators.

Stimulus-dependent maximum entropy models of neural population codes.

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Einat Granot-Atedgi

Full Text Available Neural populations encode information about their stimulus in a collective fashion, by joint activity patterns of spiking and silence. A full account of this mapping from stimulus to neural activity is given by the conditional probability distribution over neural codewords given the sensory input. For large populations, direct sampling of these distributions is impossible, and so we must rely on constructing appropriate models. We show here that in a population of 100 retinal ganglion cells in the salamander retina responding to temporal white-noise stimuli, dependencies between cells play an important encoding role. We introduce the stimulus-dependent maximum entropy (SDME model-a minimal extension of the canonical linear-nonlinear model of a single neuron, to a pairwise-coupled neural population. We find that the SDME model gives a more accurate account of single cell responses and in particular significantly outperforms uncoupled models in reproducing the distributions of population codewords emitted in response to a stimulus. We show how the SDME model, in conjunction with static maximum entropy models of population vocabulary, can be used to estimate information-theoretic quantities like average surprise and information transmission in a neural population.

Realization of spin-dependent splitting with arbitrary intensity patterns based on all-dielectric metasurfaces

Energy Technology Data Exchange (ETDEWEB)

Ke, Yougang; Liu, Yachao; He, Yongli; Zhou, Junxiao; Luo, Hailu, E-mail: hailuluo@hnu.edu.cn; Wen, Shuangchun [Laboratory for Spin Photonics, School of Physics and Electronics, Hunan University, Changsha 410082 (China)

2015-07-27

We report the realization of spin-dependent splitting with arbitrary intensity patterns based on all-dielectric metasurfaces. Compared with the plasmonic metasurfaces, the all-dielectric metasurface exhibits more high transmission efficiency and conversion efficiency, which makes it possible to achieve the spin-dependent splitting with arbitrary intensity patterns. Our findings suggest a way for generation and manipulation of spin photons, and thereby offer the possibility of developing spin-based nanophotonic applications.

Capacity for patterns and sequences in Kanerva's SDM as compared to other associative memory models

Science.gov (United States)

Keeler, James D.

1987-01-01

The information capacity of Kanerva's Sparse Distributed Memory (SDM) and Hopfield-type neural networks is investigated. Under the approximations used, it is shown that the total information stored in these systems is proportional to the number connections in the network. The proportionality constant is the same for the SDM and Hopfield-type models independent of the particular model, or the order of the model. The approximations are checked numerically. This same analysis can be used to show that the SDM can store sequences of spatiotemporal patterns, and the addition of time-delayed connections allows the retrieval of context dependent temporal patterns. A minor modification of the SDM can be used to store correlated patterns.

Workflow Patterns for Business Process Modeling

NARCIS (Netherlands)

Thom, Lucineia Heloisa; Lochpe, Cirano; Reichert, M.U.

For its reuse advantages, workflow patterns (e.g., control flow patterns, data patterns, resource patterns) are increasingly attracting the interest of both researchers and vendors. Frequently, business process or workflow models can be assembeled out of a set of recurrent process fragments (or

Onset patterns in a simple model of localized parametric forcing.

Science.gov (United States)

Porter, J; Tinao, I; Laverón-Simavilla, A; Rodríguez, J

2013-10-01

We investigate pattern selection at onset in a parametrically and inhomogeneously forced partial differential equation obtained by generalizing Mathieu's equation to include spatial interactions. No separation of scales is assumed. The proposed model is directly relevant to the case of parametrically forced surface waves, such as cross-waves, excited by the horizontal vibration of a fluid, where the forcing is localized to a finite region near the endwall or wavemaker. The availability of analytical solutions in the limit of piecewise constant forcing allows us investigate in detail the dependence of selected eigenfunctions on spatial detuning, forcing width, damping, boundary conditions, and container size. A wide range of onset patterns are located and described, many of which are rotated, modulated, or both, and deviate far from simple crosswise oriented standing waves. The linear selection mechanisms governing this multiplicity of potential onset patterns are discussed.

Complex degradation processes lead to non-exponential decay patterns and age-dependent decay rates of messenger RNA.

Directory of Open Access Journals (Sweden)

Carlus Deneke

Full Text Available Experimental studies on mRNA stability have established several, qualitatively distinct decay patterns for the amount of mRNA within the living cell. Furthermore, a variety of different and complex biochemical pathways for mRNA degradation have been identified. The central aim of this paper is to bring together both the experimental evidence about the decay patterns and the biochemical knowledge about the multi-step nature of mRNA degradation in a coherent mathematical theory. We first introduce a mathematical relationship between the mRNA decay pattern and the lifetime distribution of individual mRNA molecules. This relationship reveals that the mRNA decay patterns at steady state expression level must obey a general convexity condition, which applies to any degradation mechanism. Next, we develop a theory, formulated as a Markov chain model, that recapitulates some aspects of the multi-step nature of mRNA degradation. We apply our theory to experimental data for yeast and explicitly derive the lifetime distribution of the corresponding mRNAs. Thereby, we show how to extract single-molecule properties of an mRNA, such as the age-dependent decay rate and the residual lifetime. Finally, we analyze the decay patterns of the whole translatome of yeast cells and show that yeast mRNAs can be grouped into three broad classes that exhibit three distinct decay patterns. This paper provides both a method to accurately analyze non-exponential mRNA decay patterns and a tool to validate different models of degradation using decay data.

Modeling and Compensating Temperature-Dependent Non-Uniformity Noise in IR Microbolometer Cameras

Directory of Open Access Journals (Sweden)

Alejandro Wolf

2016-07-01

Full Text Available Images rendered by uncooled microbolometer-based infrared (IR cameras are severely degraded by the spatial non-uniformity (NU noise. The NU noise imposes a fixed-pattern over the true images, and the intensity of the pattern changes with time due to the temperature instability of such cameras. In this paper, we present a novel model and a compensation algorithm for the spatial NU noise and its temperature-dependent variations. The model separates the NU noise into two components: a constant term, which corresponds to a set of NU parameters determining the spatial structure of the noise, and a dynamic term, which scales linearly with the fluctuations of the temperature surrounding the array of microbolometers. We use a black-body radiator and samples of the temperature surrounding the IR array to offline characterize both the constant and the temperature-dependent NU noise parameters. Next, the temperature-dependent variations are estimated online using both a spatially uniform Hammerstein-Wiener estimator and a pixelwise least mean squares (LMS estimator. We compensate for the NU noise in IR images from two long-wave IR cameras. Results show an excellent NU correction performance and a root mean square error of less than 0.25 ∘ C, when the array’s temperature varies by approximately 15 ∘ C.

Validating EHR clinical models using ontology patterns.

Science.gov (United States)

Martínez-Costa, Catalina; Schulz, Stefan

2017-12-01

Clinical models are artefacts that specify how information is structured in electronic health records (EHRs). However, the makeup of clinical models is not guided by any formal constraint beyond a semantically vague information model. We address this gap by advocating ontology design patterns as a mechanism that makes the semantics of clinical models explicit. This paper demonstrates how ontology design patterns can validate existing clinical models using SHACL. Based on the Clinical Information Modelling Initiative (CIMI), we show how ontology patterns detect both modeling and terminology binding errors in CIMI models. SHACL, a W3C constraint language for the validation of RDF graphs, builds on the concept of "Shape", a description of data in terms of expected cardinalities, datatypes and other restrictions. SHACL, as opposed to OWL, subscribes to the Closed World Assumption (CWA) and is therefore more suitable for the validation of clinical models. We have demonstrated the feasibility of the approach by manually describing the correspondences between six CIMI clinical models represented in RDF and two SHACL ontology design patterns. Using a Java-based SHACL implementation, we found at least eleven modeling and binding errors within these CIMI models. This demonstrates the usefulness of ontology design patterns not only as a modeling tool but also as a tool for validation. Copyright © 2017 Elsevier Inc. All rights reserved.

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

Science.gov (United States)

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

2014-01-01

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

Modeling of Scale-Dependent Bacterial Growth by Chemical Kinetics Approach

Directory of Open Access Journals (Sweden)

Haydee Martínez

2014-01-01

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

Enforcing a security pattern in stakeholder goal models

OpenAIRE

Yu, Yijun; Kaiya, Haruhiko; Washizaki, Hironori; Xiong, Yingfei; Hu, Zhenjiang; Yoshioka, Nobukazu

2008-01-01

Patterns are useful knowledge about recurring problems and solutions. Detecting a security problem using patterns in requirements models may lead to its early solution. In order to facilitate early detection and resolution of security problems, in this paper, we formally describe a role-based access control (RBAC) as a pattern that may occur in stakeholder requirements models. We also implemented in our goal-oriented modeling tool the formally described pattern using model-driven queries and ...

Simple models for studying complex spatiotemporal patterns of animal behavior

Science.gov (United States)

Tyutyunov, Yuri V.; Titova, Lyudmila I.

2017-06-01

Minimal mathematical models able to explain complex patterns of animal behavior are essential parts of simulation systems describing large-scale spatiotemporal dynamics of trophic communities, particularly those with wide-ranging species, such as occur in pelagic environments. We present results obtained with three different modelling approaches: (i) an individual-based model of animal spatial behavior; (ii) a continuous taxis-diffusion-reaction system of partial-difference equations; (iii) a 'hybrid' approach combining the individual-based algorithm of organism movements with explicit description of decay and diffusion of the movement stimuli. Though the models are based on extremely simple rules, they all allow description of spatial movements of animals in a predator-prey system within a closed habitat, reproducing some typical patterns of the pursuit-evasion behavior observed in natural populations. In all three models, at each spatial position the animal movements are determined by local conditions only, so the pattern of collective behavior emerges due to self-organization. The movement velocities of animals are proportional to the density gradients of specific cues emitted by individuals of the antagonistic species (pheromones, exometabolites or mechanical waves of the media, e.g., sound). These cues play a role of taxis stimuli: prey attract predators, while predators repel prey. Depending on the nature and the properties of the movement stimulus we propose using either a simplified individual-based model, a continuous taxis pursuit-evasion system, or a little more detailed 'hybrid' approach that combines simulation of the individual movements with the continuous model describing diffusion and decay of the stimuli in an explicit way. These can be used to improve movement models for many species, including large marine predators.

Modelling biomechanics of bark patterning in grasstrees.

Science.gov (United States)

Dale, Holly; Runions, Adam; Hobill, David; Prusinkiewicz, Przemyslaw

2014-09-01

Bark patterns are a visually important characteristic of trees, typically attributed to fractures occurring during secondary growth of the trunk and branches. An understanding of bark pattern formation has been hampered by insufficient information regarding the biomechanical properties of bark and the corresponding difficulties in faithfully modelling bark fractures using continuum mechanics. This study focuses on the genus Xanthorrhoea (grasstrees), which have an unusual bark-like structure composed of distinct leaf bases connected by sticky resin. Due to its discrete character, this structure is well suited for computational studies. A dynamic computational model of grasstree development was created. The model captures both the phyllotactic pattern of leaf bases during primary growth and the changes in the trunk's width during secondary growth. A biomechanical representation based on a system of masses connected by springs is used for the surface of the trunk, permitting the emergence of fractures during secondary growth to be simulated. The resulting fracture patterns were analysed statistically and compared with images of real trees. The model reproduces key features of grasstree bark patterns, including their variability, spanning elongated and reticulate forms. The patterns produced by the model have the same statistical character as those seen in real trees. The model was able to support the general hypothesis that the patterns observed in the grasstree bark-like layer may be explained in terms of mechanical fractures driven by secondary growth. Although the generality of the results is limited by the unusual structure of grasstree bark, it supports the hypothesis that bark pattern formation is primarily a biomechanical phenomenon.

Incorporating Context Dependency of Species Interactions in Species Distribution Models.

Science.gov (United States)

Lany, Nina K; Zarnetske, Phoebe L; Gouhier, Tarik C; Menge, Bruce A

2017-07-01

Species distribution models typically use correlative approaches that characterize the species-environment relationship using occurrence or abundance data for a single species. However, species distributions are determined by both abiotic conditions and biotic interactions with other species in the community. Therefore, climate change is expected to impact species through direct effects on their physiology and indirect effects propagated through their resources, predators, competitors, or mutualists. Furthermore, the sign and strength of species interactions can change according to abiotic conditions, resulting in context-dependent species interactions that may change across space or with climate change. Here, we incorporated the context dependency of species interactions into a dynamic species distribution model. We developed a multi-species model that uses a time-series of observational survey data to evaluate how abiotic conditions and species interactions affect the dynamics of three rocky intertidal species. The model further distinguishes between the direct effects of abiotic conditions on abundance and the indirect effects propagated through interactions with other species. We apply the model to keystone predation by the sea star Pisaster ochraceus on the mussel Mytilus californianus and the barnacle Balanus glandula in the rocky intertidal zone of the Pacific coast, USA. Our method indicated that biotic interactions between P. ochraceus and B. glandula affected B. glandula dynamics across >1000 km of coastline. Consistent with patterns from keystone predation, the growth rate of B. glandula varied according to the abundance of P. ochraceus in the previous year. The data and the model did not indicate that the strength of keystone predation by P. ochraceus varied with a mean annual upwelling index. Balanus glandula cover increased following years with high phytoplankton abundance measured as mean annual chlorophyll-a. M. californianus exhibited the same

How pattern formation in ring networks of excitatory and inhibitoryspiking neurons depends on the input current regime

Directory of Open Access Journals (Sweden)

Birgit eKriener

2014-01-01

Full Text Available Pattern formation, i.e., the generation of an inhomogeneous spatial activity distribution in a dynamical system with translation invariant structure, is a well-studied phenomenon in neuronal network dynamics,specifically in neural field models. These are population models to describe the spatio-temporal dynamics of large groups of neurons in terms of macroscopic variables such as population firing rates. Though neural field models are often deduced from and equipped with biophysically meaningfulproperties, a direct mapping to simulations of individual spiking neuron populations is rarely considered. Neurons have a distinct identity defined by their action on their postsynaptic targets. In its simplest form they act either excitatorily or inhibitorily.When the distribution of neuron identities is assumed to be periodic, pattern formation can be observed, given the coupling strength is supercritical, i.e., larger than a critical weight. We find that this critical weight is strongly dependent on the characteristics of the neuronal input, i.e., depends on whether neurons are mean- orfluctuation driven, and different limits in linearizing the full non-linear system apply in order to assess stability.In particular, if neurons are mean-driven, the linearization has a very simple form and becomesindependent of both the fixed point firing rate and the variance of the input current, while in the very strongly fluctuation-driven regime the fixed point rate, as well as the input mean and variance areimportant parameters in the determination of the critical weight.We demonstrate that interestingly even in ``intermediate'' regimes, when the system is technically fluctuation-driven, the simple linearization neglecting the variance of the input can yield the better prediction of the critical couplingstrength. We moreover analyze the effects of structural randomness by rewiring individualsynapses or redistributing weights, as well as coarse-graining on pattern

Unusual polarity-dependent patterns in a bent-core nematic liquid crystal under low-frequency ac field.

Science.gov (United States)

Xiang, Ying; Zhou, Meng-jie; Xu, Ming-Ya; Salamon, Péter; Éber, Nándor; Buka, Ágnes

2015-04-01

Electric-field-induced patterns of diverse morphology have been observed over a wide frequency range in a recently synthesized bent-core nematic (BCN) liquid crystal. At low frequencies (up to ∼25 Hz), the BCN exhibited unusual polarity-dependent patterns. When the amplitude of the ac field was enhanced, these two time-asymmetrical patterns turned into time-symmetrical prewavylike stripes. At ac frequencies in the middle-frequency range (∼50-3000 Hz), zigzag patterns were detected whose obliqueness varied with the frequency. Finally, if the frequency was increased above 3 kHz, the zigzag pattern was replaced by another, prewavylike pattern, whose threshold voltage depended on the frequency; however, the wave vector did not. For a more complete characterization, material parameters such as elastic constants, dielectric permittivities, and the anisotropy of the diamagnetic susceptibility were also determined.

Deformation patterning driven by rate dependent non-convex strain gradient plasticity

NARCIS (Netherlands)

Yalcinkaya, T.; Brekelmans, W.A.M.; Geers, M.G.D.

2011-01-01

A rate dependent strain gradient plasticity framework for the description of plastic slip patterning in a system with non-convex energetic hardening is presented. Both the displacement and the plastic slip fields are considered as primary variables. These fields are determined on a global level by

Criterion of Semi-Markov Dependent Risk Model

Institute of Scientific and Technical Information of China (English)

Xiao Yun MO; Xiang Qun YANG

2014-01-01

A rigorous definition of semi-Markov dependent risk model is given. This model is a generalization of the Markov dependent risk model. A criterion and necessary conditions of semi-Markov dependent risk model are obtained. The results clarify relations between elements among semi-Markov dependent risk model more clear and are applicable for Markov dependent risk model.

Chopper model of pattern recognition

NARCIS (Netherlands)

van Hemmen, J.L.; Enter, A.C.D. van

A simple model is proposed that allows an efficient storage and retrieval of random patterns. Also correlated patterns can be handled. The data are stored in an Ising-spin system with ferromagnetic interactions between all the spins and the main idea is to "chop" the system along the boundaries

Modelling Behaviour Patterns of Pedestrians for Mobile Robot Trajectory Generation

Directory of Open Access Journals (Sweden)

Yusuke Tamura

2013-08-01

Full Text Available Robots are expected to be operated in environments where they coexist with humans, such as shopping malls and offices. Both the safety and efficiency of a robot are necessary in such environments. To achieve this, pedestrian behaviour should be accurately predicted. However, the behaviour is uncertain and cannot be easily predicted. This paper proposes a probabilistic method of determining pedestrian trajectory based on an estimation of pedestrian behaviour patterns. The proposed method focuses on the specific behaviour of pedestrians around the robot. The proposed model classifies the behaviours of pedestrians into definite patterns. The behaviour patterns, distribution of the positions of the pedestrians, and the direction of each behaviour pattern are determined by learning through observation. The behaviour pattern of a pedestrian can be estimated correctly by a likelihood calculation. A robot decides to move with an emphasis on either safety or efficiency depending on the result of the pattern estimation. If the pedestrian trajectory follows a known behaviour pattern, the robot would move with an emphasis on efficiency because the pedestrian trajectory can be predicted. Otherwise, the robot would move with an emphasis on safety because the behaviour of the pedestrian cannot be predicted. Experimental results show that robots can move efficiently and safely when passing by a pedestrian by applying the proposed method.

A model of hygiene practices and consumption patterns in the consumer phase

DEFF Research Database (Denmark)

Christensen, Bjarke Bak; Rosenquist, Hanne; Sommer, Helle Mølgaard

2005-01-01

A mathematical model is presented, which addresses individual hygiene practices during food preparation and consumption patterns in private homes. Further, the model links food preparers and consumers based on their relationship to household types. For different age and gender groups, the model...... was highest for young males (aged 18-29 years) and lowest for the elderly above 60 years of age. Children aged 0-4 years had a higher probability of ingesting a risk meal than children aged 5-17 years. This difference between age and gender groups was ascribed to the variations in the hygiene levels of food....... The simulated results show that the probability of ingesting a chicken risk meal at home does not only depend on the hygiene practices of the persons preparing the food, but also on the consumption patterns of consumers, and the relationship between people preparing and ingesting food. This finding supports...

Occurrence patterns of dead wood and wood-dependent lichens in managed boreal forest landscapes

OpenAIRE

Svensson, Måns

2013-01-01

Dead wood is a key resource for biodiversity, on which thousands of forest organisms are dependent. Because of current forest management, there has been a large-scale change in dead wood amounts and qualities, and consequently, many wood-dependent species are threatened. The general aim of this thesis is to increase our understanding of habitat requirements and occurrence patterns of wood-dependent lichens in managed, boreal forest landscapes. We surveyed dead wood and wood-dependent lichens ...

How pattern formation in ring networks of excitatory and inhibitory spiking neurons depends on the input current regime.

Science.gov (United States)

Kriener, Birgit; Helias, Moritz; Rotter, Stefan; Diesmann, Markus; Einevoll, Gaute T

2013-01-01

Pattern formation, i.e., the generation of an inhomogeneous spatial activity distribution in a dynamical system with translation invariant structure, is a well-studied phenomenon in neuronal network dynamics, specifically in neural field models. These are population models to describe the spatio-temporal dynamics of large groups of neurons in terms of macroscopic variables such as population firing rates. Though neural field models are often deduced from and equipped with biophysically meaningful properties, a direct mapping to simulations of individual spiking neuron populations is rarely considered. Neurons have a distinct identity defined by their action on their postsynaptic targets. In its simplest form they act either excitatorily or inhibitorily. When the distribution of neuron identities is assumed to be periodic, pattern formation can be observed, given the coupling strength is supracritical, i.e., larger than a critical weight. We find that this critical weight is strongly dependent on the characteristics of the neuronal input, i.e., depends on whether neurons are mean- or fluctuation driven, and different limits in linearizing the full non-linear system apply in order to assess stability. In particular, if neurons are mean-driven, the linearization has a very simple form and becomes independent of both the fixed point firing rate and the variance of the input current, while in the very strongly fluctuation-driven regime the fixed point rate, as well as the input mean and variance are important parameters in the determination of the critical weight. We demonstrate that interestingly even in "intermediate" regimes, when the system is technically fluctuation-driven, the simple linearization neglecting the variance of the input can yield the better prediction of the critical coupling strength. We moreover analyze the effects of structural randomness by rewiring individual synapses or redistributing weights, as well as coarse-graining on the formation of

Firing patterns in the adaptive exponential integrate-and-fire model.

Science.gov (United States)

Naud, Richard; Marcille, Nicolas; Clopath, Claudia; Gerstner, Wulfram

2008-11-01

For simulations of large spiking neuron networks, an accurate, simple and versatile single-neuron modeling framework is required. Here we explore the versatility of a simple two-equation model: the adaptive exponential integrate-and-fire neuron. We show that this model generates multiple firing patterns depending on the choice of parameter values, and present a phase diagram describing the transition from one firing type to another. We give an analytical criterion to distinguish between continuous adaption, initial bursting, regular bursting and two types of tonic spiking. Also, we report that the deterministic model is capable of producing irregular spiking when stimulated with constant current, indicating low-dimensional chaos. Lastly, the simple model is fitted to real experiments of cortical neurons under step current stimulation. The results provide support for the suitability of simple models such as the adaptive exponential integrate-and-fire neuron for large network simulations.

Capacity for patterns and sequences in Kanerva's SDM as compared to other associative memory models. [Sparse, Distributed Memory

Science.gov (United States)

Keeler, James D.

1988-01-01

The information capacity of Kanerva's Sparse Distributed Memory (SDM) and Hopfield-type neural networks is investigated. Under the approximations used here, it is shown that the total information stored in these systems is proportional to the number connections in the network. The proportionality constant is the same for the SDM and Hopfield-type models independent of the particular model, or the order of the model. The approximations are checked numerically. This same analysis can be used to show that the SDM can store sequences of spatiotemporal patterns, and the addition of time-delayed connections allows the retrieval of context dependent temporal patterns. A minor modification of the SDM can be used to store correlated patterns.

Dependency distance in language evolution. Comment on "Dependency distance: A new perspective on syntactic patterns in natural languages" by Haitao Liu et al.

Science.gov (United States)

Liu, Bingli; Chen, Xinying

2017-07-01

In the target article [1], Liu et al. provide an informative introduction to the dependency distance studies and proclaim that language syntactic patterns, that relate to the dependency distance, are associated with human cognitive mechanisms, such as limited working memory and syntax processing. Therefore, such syntactic patterns are probably 'human-driven' language universals. Sufficient evidence based on big data analysis is also given in the article for supporting this idea. The hypotheses generally seem very convincing yet still need further tests from various perspectives. Diachronic linguistic study based on authentic language data, on our opinion, can be one of those 'further tests'.

The Dependent Poisson Race Model and Modeling Dependence in Conjoint Choice Experiments

Science.gov (United States)

Ruan, Shiling; MacEachern, Steven N.; Otter, Thomas; Dean, Angela M.

2008-01-01

Conjoint choice experiments are used widely in marketing to study consumer preferences amongst alternative products. We develop a class of choice models, belonging to the class of Poisson race models, that describe a "random utility" which lends itself to a process-based description of choice. The models incorporate a dependence structure which…

Modelling the effect of temperature on hatching and settlement patterns of meroplanktonic organisms: the case of octopus

Directory of Open Access Journals (Sweden)

Stelios Katsanevakis

2006-12-01

Full Text Available The duration of embryonic development and the planktonic stage of meroplanktonic species is highly temperature dependent and thus the seasonal temperature oscillations of temperate regions greatly affect the patterns of hatching and benthic settlement. Based on data from the literature on embryonic development and planktonic duration of Octopus vulgaris (common octopus in relation to temperature, and on observed temperature patterns, several models of hatching and settlement patterns were created. There was a good fit between observed settlement patterns and model predictions. Based on these models we concluded that in temperate regions: (1 when temperature is increasing (from early spring to mid summer the hatching and settlement periods tend to shorten, while when the temperature is decreasing (during autumn the hatching and settlement periods tend to lengthen; (2 hatching and settlement peaks are narrower and more intense than a spring spawning peak but wider and less intense than an autumn spawning peak; (3 at lower latitudes, hatching and settlement patterns tend to follow the spawning pattern more closely, (4 the periodic temperature pattern of temperate areas has the potential to cause a convergence of hatching during spring.

TRPM8-Dependent Dynamic Response in a Mathematical Model of Cold Thermoreceptor

Science.gov (United States)

Olivares, Erick; Salgado, Simón; Maidana, Jean Paul; Herrera, Gaspar; Campos, Matías; Madrid, Rodolfo; Orio, Patricio

2015-01-01

Cold-sensitive nerve terminals (CSNTs) encode steady temperatures with regular, rhythmic temperature-dependent firing patterns that range from irregular tonic firing to regular bursting (static response). During abrupt temperature changes, CSNTs show a dynamic response, transiently increasing their firing frequency as temperature decreases and silencing when the temperature increases (dynamic response). To date, mathematical models that simulate the static response are based on two depolarizing/repolarizing pairs of membrane ionic conductance (slow and fast kinetics). However, these models fail to reproduce the dynamic response of CSNTs to rapid changes in temperature and notoriously they lack a specific cold-activated conductance such as the TRPM8 channel. We developed a model that includes TRPM8 as a temperature-dependent conductance with a calcium-dependent desensitization. We show by computer simulations that it appropriately reproduces the dynamic response of CSNTs from mouse cornea, while preserving their static response behavior. In this model, the TRPM8 conductance is essential to display a dynamic response. In agreement with experimental results, TRPM8 is also needed for the ongoing activity in the absence of stimulus (i.e. neutral skin temperature). Free parameters of the model were adjusted by an evolutionary optimization algorithm, allowing us to find different solutions. We present a family of possible parameters that reproduce the behavior of CSNTs under different temperature protocols. The detection of temperature gradients is associated to a homeostatic mechanism supported by the calcium-dependent desensitization. PMID:26426259

TRPM8-Dependent Dynamic Response in a Mathematical Model of Cold Thermoreceptor.

Directory of Open Access Journals (Sweden)

Erick Olivares

Full Text Available Cold-sensitive nerve terminals (CSNTs encode steady temperatures with regular, rhythmic temperature-dependent firing patterns that range from irregular tonic firing to regular bursting (static response. During abrupt temperature changes, CSNTs show a dynamic response, transiently increasing their firing frequency as temperature decreases and silencing when the temperature increases (dynamic response. To date, mathematical models that simulate the static response are based on two depolarizing/repolarizing pairs of membrane ionic conductance (slow and fast kinetics. However, these models fail to reproduce the dynamic response of CSNTs to rapid changes in temperature and notoriously they lack a specific cold-activated conductance such as the TRPM8 channel. We developed a model that includes TRPM8 as a temperature-dependent conductance with a calcium-dependent desensitization. We show by computer simulations that it appropriately reproduces the dynamic response of CSNTs from mouse cornea, while preserving their static response behavior. In this model, the TRPM8 conductance is essential to display a dynamic response. In agreement with experimental results, TRPM8 is also needed for the ongoing activity in the absence of stimulus (i.e. neutral skin temperature. Free parameters of the model were adjusted by an evolutionary optimization algorithm, allowing us to find different solutions. We present a family of possible parameters that reproduce the behavior of CSNTs under different temperature protocols. The detection of temperature gradients is associated to a homeostatic mechanism supported by the calcium-dependent desensitization.

Discharge competence and pattern formation in peatlands: a meta-ecosystem model of the Everglades ridge-slough landscape.

Directory of Open Access Journals (Sweden)

James B Heffernan

Full Text Available Regular landscape patterning arises from spatially-dependent feedbacks, and can undergo catastrophic loss in response to changing landscape drivers. The central Everglades (Florida, USA historically exhibited regular, linear, flow-parallel orientation of high-elevation sawgrass ridges and low-elevation sloughs that has degraded due to hydrologic modification. In this study, we use a meta-ecosystem approach to model a mechanism for the establishment, persistence, and loss of this landscape. The discharge competence (or self-organizing canal hypothesis assumes non-linear relationships between peat accretion and water depth, and describes flow-dependent feedbacks of microtopography on water depth. Closed-form model solutions demonstrate that 1 this mechanism can produce spontaneous divergence of local elevation; 2 divergent and homogenous states can exhibit global bi-stability; and 3 feedbacks that produce divergence act anisotropically. Thus, discharge competence and non-linear peat accretion dynamics may explain the establishment, persistence, and loss of landscape pattern, even in the absence of other spatial feedbacks. Our model provides specific, testable predictions that may allow discrimination between the self-organizing canal hypotheses and competing explanations. The potential for global bi-stability suggested by our model suggests that hydrologic restoration may not re-initiate spontaneous pattern establishment, particularly where distinct soil elevation modes have been lost. As a result, we recommend that management efforts should prioritize maintenance of historic hydroperiods in areas of conserved pattern over restoration of hydrologic regimes in degraded regions. This study illustrates the value of simple meta-ecosystem models for investigation of spatial processes.

Generation of predictive price and trading volume patterns in a model of dynamically evolving free market supply and demand

Directory of Open Access Journals (Sweden)

J. K. Wang

2001-01-01

Full Text Available I present a model of stock market price fluctuations incorporating effects of share supply as a history-dependent function of previous purchases and share demand as a function of price deviation from moving averages. Price charts generated show intervals of oscillations switching amplitude and frequency suddenly in time, forming price and trading volume patterns well-known in market technical analysis. Ultimate price trends agree with traditional predictions for specific patterns. The consideration of dynamically evolving supply and demand in this model resolves the apparent contradiction with the Efficient Market Hypothesis: perceptions of imprecise equity values by a world of investors evolve over non-negligible periods of time, with dependence on price history.

Cyber Epidemic Models with Dependences

OpenAIRE

Xu, Maochao; Da, Gaofeng; Xu, Shouhuai

2016-01-01

Studying models of cyber epidemics over arbitrary complex networks can deepen our understanding of cyber security from a whole-system perspective. In this paper, we initiate the investigation of cyber epidemic models that accommodate the {\\em dependences} between the cyber attack events. Due to the notorious difficulty in dealing with such dependences, essentially all existing cyber epidemic models have assumed them away. Specifically, we introduce the idea of Copulas into cyber epidemic mode...

Generative models versus underlying symmetries to explain biological pattern.

Science.gov (United States)

Frank, S A

2014-06-01

Mathematical models play an increasingly important role in the interpretation of biological experiments. Studies often present a model that generates the observations, connecting hypothesized process to an observed pattern. Such generative models confirm the plausibility of an explanation and make testable hypotheses for further experiments. However, studies rarely consider the broad family of alternative models that match the same observed pattern. The symmetries that define the broad class of matching models are in fact the only aspects of information truly revealed by observed pattern. Commonly observed patterns derive from simple underlying symmetries. This article illustrates the problem by showing the symmetry associated with the observed rate of increase in fitness in a constant environment. That underlying symmetry reveals how each particular generative model defines a single example within the broad class of matching models. Further progress on the relation between pattern and process requires deeper consideration of the underlying symmetries. © 2014 The Author. Journal of Evolutionary Biology © 2014 European Society For Evolutionary Biology.

Optimal moment determination in POME-copula based hydrometeorological dependence modelling

Science.gov (United States)

Liu, Dengfeng; Wang, Dong; Singh, Vijay P.; Wang, Yuankun; Wu, Jichun; Wang, Lachun; Zou, Xinqing; Chen, Yuanfang; Chen, Xi

2017-07-01

Copula has been commonly applied in multivariate modelling in various fields where marginal distribution inference is a key element. To develop a flexible, unbiased mathematical inference framework in hydrometeorological multivariate applications, the principle of maximum entropy (POME) is being increasingly coupled with copula. However, in previous POME-based studies, determination of optimal moment constraints has generally not been considered. The main contribution of this study is the determination of optimal moments for POME for developing a coupled optimal moment-POME-copula framework to model hydrometeorological multivariate events. In this framework, margins (marginals, or marginal distributions) are derived with the use of POME, subject to optimal moment constraints. Then, various candidate copulas are constructed according to the derived margins, and finally the most probable one is determined, based on goodness-of-fit statistics. This optimal moment-POME-copula framework is applied to model the dependence patterns of three types of hydrometeorological events: (i) single-site streamflow-water level; (ii) multi-site streamflow; and (iii) multi-site precipitation, with data collected from Yichang and Hankou in the Yangtze River basin, China. Results indicate that the optimal-moment POME is more accurate in margin fitting and the corresponding copulas reflect a good statistical performance in correlation simulation. Also, the derived copulas, capturing more patterns which traditional correlation coefficients cannot reflect, provide an efficient way in other applied scenarios concerning hydrometeorological multivariate modelling.

Organizational Change, Absenteeism, and Welfare Dependency

Science.gov (United States)

Roed, Knut; Fevang, Elisabeth

2007-01-01

Based on Norwegian register data, we set up a multivariate mixed proportional hazard model (MMPH) to analyze nurses' pattern of work, sickness absence, nonemployment, and social insurance dependency from 1992 to 2000, and how that pattern was affected by workplace characteristics. The model is estimated by means of the nonparametric…

Detection of dependence patterns with delay.

Science.gov (United States)

Chevallier, Julien; Laloë, Thomas

2015-11-01

The Unitary Events (UE) method is a popular and efficient method used this last decade to detect dependence patterns of joint spike activity among simultaneously recorded neurons. The first introduced method is based on binned coincidence count (Grün, 1996) and can be applied on two or more simultaneously recorded neurons. Among the improvements of the methods, a transposition to the continuous framework has recently been proposed by Muiño and Borgelt (2014) and fully investigated by Tuleau-Malot et al. (2014) for two neurons. The goal of the present paper is to extend this study to more than two neurons. The main result is the determination of the limit distribution of the coincidence count. This leads to the construction of an independence test between L≥2 neurons. Finally, we propose a multiple test procedure via a Benjamini and Hochberg approach (Benjamini and Hochberg, 1995). All the theoretical results are illustrated by a simulation study, and compared to the UE method proposed by Grün et al. (2002). Furthermore our method is applied on real data. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Incorporating Pass-Phrase Dependent Background Models for Text-Dependent Speaker verification

DEFF Research Database (Denmark)

Sarkar, Achintya Kumar; Tan, Zheng-Hua

2018-01-01

-dependent. We show that the proposed method significantly reduces the error rates of text-dependent speaker verification for the non-target types: target-wrong and impostor-wrong while it maintains comparable TD-SV performance when impostors speak a correct utterance with respect to the conventional system......In this paper, we propose pass-phrase dependent background models (PBMs) for text-dependent (TD) speaker verification (SV) to integrate the pass-phrase identification process into the conventional TD-SV system, where a PBM is derived from a text-independent background model through adaptation using...... the utterances of a particular pass-phrase. During training, pass-phrase specific target speaker models are derived from the particular PBM using the training data for the respective target model. While testing, the best PBM is first selected for the test utterance in the maximum likelihood (ML) sense...

A bio-inspired spatial patterning circuit.

Science.gov (United States)

Chen, Kai-Yuan; Joe, Danial J; Shealy, James B; Land, Bruce R; Shen, Xiling

2014-01-01

Lateral Inhibition (LI) is a widely conserved patterning mechanism in biological systems across species. Distinct from better-known Turing patterns, LI depend on cell-cell contact rather than diffusion. We built an in silico genetic circuit model to analyze the dynamic properties of LI. The model revealed that LI amplifies differences between neighboring cells to push them into opposite states, hence forming stable 2-D patterns. Inspired by this insight, we designed and implemented an electronic circuit that recapitulates LI patterning dynamics. This biomimetic system serve as a physical model to elucidate the design principle of generating robust patterning through spatial feedback, regardless of the underlying devices being biological or electrical.

Analog electronic model of the lobster pyloric central pattern generator

Energy Technology Data Exchange (ETDEWEB)

Volkovskii, A [Institute for Nonlinear Science, University of California San Diego, CA (United States); Brugioni, S [Institute for Nonlinear Science, University of California San Diego, CA (United States); Istituto Nazionale di Ottica Applicata Largo E. Fermi 6 50125 Florence (Italy); Levi, R [Institute for Nonlinear Science, University of California San Diego, CA (United States); Rabinovich, M [Institute for Nonlinear Science, University of California San Diego, CA (United States); Selverston, A [Institute for Nonlinear Science, University of California San Diego, CA (United States); Abarbane, H D I [Institute for Nonlinear Science, University of California San Diego, CA (United States)

2005-01-01

An electronic circuit intended to simulate the nonlinear dynamics of a simplified 3-cell model of the pyloric central pattern generator in California spiny lobster stomato gastric ganglion is presented. The model employs the synaptic phase locked loop (SPLL) concept where the frequency of oscillations of a postsynaptic cell is mainly controlled by the synaptic current which depends on the phase shift between the oscillations. The theoretical study showed that the system has a stable steady state with correct phase shifts between the oscillations and that this regime is stable when the frequency of the pacemaker cell is varied over a wide range. The main bifurcations in the system were studied analytically, in computer simulations, and in experiments with the electronic circuit. The experimental measurements are in good agreement with the expectations of the theoretical model.

Size- and food-dependent growth drives patterns of competitive dominance along productivity gradients

NARCIS (Netherlands)

Huss, M.; Gårdmark, A.; van Leeuwen, A.; de Roos, A.M.

2012-01-01

Patterns of coexistence among competing species exhibiting size- and food-dependent growth remain largely unexplored. Here we studied mechanisms behind coexistence and shifts in competitive dominance in a size-structured fish guild, representing sprat and herring stocks in the Baltic Sea, using a

System-dependent regulations of colour-pattern development: a mutagenesis study of the pale grass blue butterfly

Science.gov (United States)

Iwata, Masaki; Hiyama, Atsuki; Otaki, Joji M.

2013-01-01

Developmental studies on wing colour patterns have been performed in nymphalid butterflies, but efficient genetic manipulations, including mutagenesis, have not been well established. Here, we have performed mutagenesis experiments in a lycaenid butterfly, the pale grass blue Zizeeria maha, to produce colour-pattern mutants. We fed the P-generation larvae an artificial diet containing the mutagen ethyl methane sulfonate (EMS), and the F1- and F2-generation adults showed various aberrant colour patterns: dorsoventral transformation, anterioposterior background colouration gap, weak contrast, disarrangement of spots, reduction of the size of spots, loss of spots, fusion of spots, and ectopic spots. Among them, the disarrangement, reduction, and loss of spots were likely produced by the coordinated changes of many spots of a single wing around the discal spot in a system-dependent manner, demonstrating the existence of the central symmetry system. The present study revealed multiple genetic regulations for system-dependent and wing-wide colour-pattern determination in lycaenid butterflies. PMID:23917124

Radiatively induced neutrino mass model with flavor dependent gauge symmetry

Science.gov (United States)

Lee, SangJong; Nomura, Takaaki; Okada, Hiroshi

2018-06-01

We study a radiative seesaw model at one-loop level with a flavor dependent gauge symmetry U(1) μ - τ, in which we consider bosonic dark matter. We also analyze the constraints from lepton flavor violations, muon g - 2, relic density of dark matter, and collider physics, and carry out numerical analysis to search for allowed parameter region which satisfy all the constraints and to investigate some predictions. Furthermore we find that a simple but adhoc hypothesis induces specific two zero texture with inverse mass matrix, which provides us several predictions such as a specific pattern of Dirac CP phase.

Emergent patterns of social affiliation in primates, a model.

Directory of Open Access Journals (Sweden)

Ivan Puga-Gonzalez

2009-12-01

Full Text Available Many patterns of affiliative behaviour have been described for primates, for instance: reciprocation and exchange of grooming, grooming others of similar rank, reconciliation of fights, and preferential reconciliation with more valuable partners. For these patterns several functions and underlying cognitive processes have been suggested. It is, however, difficult to imagine how animals may combine these diverse considerations in their mind. Although the co-variation hypothesis, by limiting the social possibilities an individual has, constrains the number of cognitive considerations an individual has to take, it does not present an integrated theory of affiliative patterns either. In the present paper, after surveying patterns of affiliation in egalitarian and despotic macaques, we use an individual-based model with a high potential for self-organisation as a starting point for such an integrative approach. In our model, called GrooFiWorld, individuals group and, upon meeting each other, may perform a dominance interaction of which the outcomes of winning and losing are self-reinforcing. Besides, if individuals think they will be defeated, they consider grooming others. Here, the greater their anxiety is, the greater their "motivation" to groom others. Our model generates patterns similar to many affiliative patterns of empirical data. By merely increasing the intensity of aggression, affiliative patterns in the model change from those resembling egalitarian macaques to those resembling despotic ones. Our model produces such patterns without assuming in the mind of the individual the specific cognitive processes that are usually thought to underlie these patterns (such as recordkeeping of the acts given and received, a tendency to exchange, memory of the former fight, selective attraction to the former opponent, and estimation of the value of a relationship. Our model can be used as a null model to increase our understanding of affiliative

Excitation block in a nerve fibre model owing to potassium-dependent changes in myelin resistance

DEFF Research Database (Denmark)

Brazhe, Alexey; Maksimov, G. V.; Mosekilde, Erik

2011-01-01

. Uptake of potassium leads to Schwann cell swelling and myelin restructuring that impacts the electrical properties of the myelin. In order to further understand the dynamic interaction that takes place between the myelin and the axon, we have modelled submyelin potassium accumulation and related changes...... in myelin resistance during prolonged high-frequency stimulation. We predict that potassium-mediated decrease in myelin resistance leads to a functional excitation block with various patterns of altered spike trains. The patterns are found to depend on stimulation frequency and amplitude and to range from...

Dependency distance distribution - from the perspective of genre variation. Comment on "Dependency distance: a new perspective on syntactic patterns in natural languages" by Haitao Liu et al.

Science.gov (United States)

Wang, Yaqin

2017-07-01

Language can be regarded as a system where different components fit together, according to Saussure [1]. Likewise, the central axiom of synergetic linguistic is that language is a self-organized and self-adapting system. One of its main concerns is to view language as ;a psycho-social phenomenon and a biological-cognitive one at the same time; [2, 760]. Based on this assumption, Liu, Xu and Liang propose a novel approach, i.e., dependency distance, to study the general tendency hidden beneath diverse human languages [3]. As the authors describe in sections 1-3, variations within and between human languages all show the similar tendency towards dependency distance minimization (DDM). In sections 4-5, they introduce certain syntactic patterns related to both short and long dependency distances. However, the effect of genre seems to be given less sufficient attention by the authors. A study suggests that different distributions of closeness and degree centralities across genres can broaden the understanding of dependency distance distribution [4]. Another one shows that different genres have different parameters in terms of modeling dependency distance distribution [5]. Further research on the genre variation, therefore, can provide additional support for this issue.

Time-dependent Hartree approximation and time-dependent harmonic oscillator model

International Nuclear Information System (INIS)

Blaizot, J.P.

1982-01-01

We present an analytically soluble model for studying nuclear collective motion within the framework of the time-dependent Hartree (TDH) approximation. The model reduces the TDH equations to the Schroedinger equation of a time-dependent harmonic oscillator. Using canonical transformations and coherent states we derive a few properties of the time-dependent harmonic oscillator which are relevant for applications. We analyse the role of the normal modes in the time evolution of a system governed by TDH equations. We show how these modes couple together due to the anharmonic terms generated by the non-linearity of the theory. (orig.)

Models for dependent time series

CERN Document Server

Tunnicliffe Wilson, Granville; Haywood, John

2015-01-01

Models for Dependent Time Series addresses the issues that arise and the methodology that can be applied when the dependence between time series is described and modeled. Whether you work in the economic, physical, or life sciences, the book shows you how to draw meaningful, applicable, and statistically valid conclusions from multivariate (or vector) time series data.The first four chapters discuss the two main pillars of the subject that have been developed over the last 60 years: vector autoregressive modeling and multivariate spectral analysis. These chapters provide the foundational mater

Oscillation-Driven Spike-Timing Dependent Plasticity Allows Multiple Overlapping Pattern Recognition in Inhibitory Interneuron Networks

DEFF Research Database (Denmark)

Garrido, Jesús A.; Luque, Niceto R.; Tolu, Silvia

2016-01-01

The majority of operations carried out by the brain require learning complex signal patterns for future recognition, retrieval and reuse. Although learning is thought to depend on multiple forms of long-term synaptic plasticity, the way this latter contributes to pattern recognition is still poorly...... and at the inhibitory interneuron-interneuron synapses, the interneurons rapidly learned complex input patterns. Interestingly, induction of plasticity required that the network be entrained into theta-frequency band oscillations, setting the internal phase-reference required to drive STDP. Inhibitory plasticity...... effectively distributed multiple patterns among available interneurons, thus allowing the simultaneous detection of multiple overlapping patterns. The addition of plasticity in intrinsic excitability made the system more robust allowing self-adjustment and rescaling in response to a broad range of input...

Bilateral versus ipsilesional cortico-subcortical activity patterns in stroke show hemispheric dependence.

Science.gov (United States)

Vidal, Ana C; Banca, Paula; Pascoal, Augusto G; Cordeiro, Gustavo; Sargento-Freitas, João; Gouveia, Ana; Castelo-Branco, Miguel

2018-01-01

Background Understanding of interhemispheric interactions in stroke patients during motor control is an important clinical neuroscience quest that may provide important clues for neurorehabilitation. In stroke patients bilateral overactivation in both hemispheres has been interpreted as a poor prognostic indicator of functional recovery. In contrast, ipsilesional patterns have been linked with better motor outcomes. Aim We investigated the pathophysiology of hemispheric interactions during limb movement without and with contralateral restraint, to mimic the effects of constraint-induced movement therapy. We used neuroimaging to probe brain activity with such a movement-dependent interhemispheric modulation paradigm. Methods We used a functional magnetic resonance imaging block design during which the plegic/paretic upper limb was recruited/mobilized to perform unilateral arm elevation, as a function of presence versus absence of contralateral limb restriction (n = 20, with balanced left/right lesion sites). Results Analysis of 10 right hemispheric stroke participants yielded bilateral sensorimotor cortex activation in all movement phases in contrast with the unilateral dominance seen in the 10 left hemispheric stroke participants. Superimposition of contralateral restriction led to a prominent shift from activation to deactivation response patterns, in particular in cortical and basal ganglia motor areas in right hemispheric stroke. Left hemispheric stroke was, in general, characterized by reduced activation patterns, even in the absence of restriction, which induced additional cortical silencing. Conclusion The observed hemispheric-dependent activation/deactivation shifts is novel and these pathophysiological observations suggest short-term neuroplasticity that may be useful for hemisphere-tailored neurorehabilitation.

Position-dependent patterning of spontaneous action potentials in immature cochlear inner hair cells.

Science.gov (United States)

Johnson, Stuart L; Eckrich, Tobias; Kuhn, Stephanie; Zampini, Valeria; Franz, Christoph; Ranatunga, Kishani M; Roberts, Terri P; Masetto, Sergio; Knipper, Marlies; Kros, Corné J; Marcotti, Walter

2011-06-01

Spontaneous action potential activity is crucial for mammalian sensory system development. In the auditory system, patterned firing activity has been observed in immature spiral ganglion and brain-stem neurons and is likely to depend on cochlear inner hair cell (IHC) action potentials. It remains uncertain whether spiking activity is intrinsic to developing IHCs and whether it shows patterning. We found that action potentials were intrinsically generated by immature IHCs of altricial rodents and that apical IHCs showed bursting activity as opposed to more sustained firing in basal cells. We show that the efferent neurotransmitter acetylcholine fine-tunes the IHC's resting membrane potential (V(m)), and as such is crucial for the bursting pattern in apical cells. Endogenous extracellular ATP also contributes to the V(m) of apical and basal IHCs by triggering small-conductance Ca(2+)-activated K(+) (SK2) channels. We propose that the difference in firing pattern along the cochlea instructs the tonotopic differentiation of IHCs and auditory pathway.

Position-dependent patterning of spontaneous action potentials in immature cochlear inner hair cells

Science.gov (United States)

Johnson, Stuart L.; Eckrich, Tobias; Kuhn, Stephanie; Zampini, Valeria; Franz, Christoph; Ranatunga, Kishani M.; Roberts, Terri P.; Masetto, Sergio; Knipper, Marlies; Kros, Corné J.; Marcotti, Walter

2011-01-01

Spontaneous action potential activity is crucial for mammalian sensory system development. In the auditory system, patterned firing activity has been observed in immature spiral ganglion cells and brain-stem neurons and is likely to depend on cochlear inner hair cell (IHC) action potentials. It remains uncertain whether spiking activity is intrinsic to developing IHCs and whether it shows patterning. We found that action potentials are intrinsically generated by immature IHCs of altricial rodents and that apical IHCs exhibit bursting activity as opposed to more sustained firing in basal cells. We show that the efferent neurotransmitter ACh, by fine-tuning the IHC’s resting membrane potential (Vm), is crucial for the bursting pattern in apical cells. Endogenous extracellular ATP also contributes to the Vm of apical and basal IHCs by activating SK2 channels. We hypothesize that the difference in firing pattern along the cochlea instructs the tonotopic differentiation of IHCs and auditory pathway. PMID:21572434

Enterprise Pattern: integrating the business process into a unified enterprise model of modern service company

Science.gov (United States)

Li, Ying; Luo, Zhiling; Yin, Jianwei; Xu, Lida; Yin, Yuyu; Wu, Zhaohui

2017-01-01

Modern service company (MSC), the enterprise involving special domains, such as the financial industry, information service industry and technology development industry, depends heavily on information technology. Modelling of such enterprise has attracted much research attention because it promises to help enterprise managers to analyse basic business strategies (e.g. the pricing strategy) and even optimise the business process (BP) to gain benefits. While the existing models proposed by economists cover the economic elements, they fail to address the basic BP and its relationship with the economic characteristics. Those proposed in computer science regardless of achieving great success in BP modelling perform poorly in supporting the economic analysis. Therefore, the existing approaches fail to satisfy the requirement of enterprise modelling for MSC, which demands simultaneous consideration of both economic analysing and business processing. In this article, we provide a unified enterprise modelling approach named Enterprise Pattern (EP) which bridges the gap between the BP model and the enterprise economic model of MSC. Proposing a language named Enterprise Pattern Description Language (EPDL) covering all the basic language elements of EP, we formulate the language syntaxes and two basic extraction rules assisting economic analysis. Furthermore, we extend Business Process Model and Notation (BPMN) to support EPDL, named BPMN for Enterprise Pattern (BPMN4EP). The example of mobile application platform is studied in detail for a better understanding of EPDL.

Coupled Particle Transport and Pattern Formation in a Nonlinear Leaky-Box Model

Science.gov (United States)

Barghouty, A. F.; El-Nemr, K. W.; Baird, J. K.

2009-01-01

Effects of particle-particle coupling on particle characteristics in nonlinear leaky-box type descriptions of the acceleration and transport of energetic particles in space plasmas are examined in the framework of a simple two-particle model based on the Fokker-Planck equation in momentum space. In this model, the two particles are assumed coupled via a common nonlinear source term. In analogy with a prototypical mathematical system of diffusion-driven instability, this work demonstrates that steady-state patterns with strong dependence on the magnetic turbulence but a rather weak one on the coupled particles attributes can emerge in solutions of a nonlinearly coupled leaky-box model. The insight gained from this simple model may be of wider use and significance to nonlinearly coupled leaky-box type descriptions in general.

Seasonal dependence of the predictable low-level circulation patterns over the tropical Indo-Pacific domain

Science.gov (United States)

Zhang, Tuantuan; Huang, Bohua; Yang, Song; Laohalertchai, Charoon

2018-06-01

The seasonal dependence of the prediction skill of 850-hPa monthly zonal wind over the tropical Indo-Pacific domain is examined using the ensemble reforecasts for 1983-2010 from the National Centers for Environmental Prediction (NCEP) Climate Forecast System Reanalysis and Reforecast (CFSRR) project. According to a maximum signal-to-noise empirical orthogonal function analysis, the most predictable patterns of atmospheric low-level circulation are associated with the developing and maturing phases of El Niño-Southern Oscillation (ENSO). The CFSv2 is capable of predicting these ENSO-related patterns up to 9-months in advance for all months, except for May-June when the effect of the spring barrier is strong. The other predictable climate processes associated with the low-level atmospheric circulation are more seasonally dependent. For winter and spring, the second most predictable patterns are associated with the ENSO decaying phase. Within these seasons, the monthly evolution of the predictable patterns is characterized by a southward shift of westerly wind anomalies, generated by the interaction between the annual cycle and the ENSO signals (i.e., the combination-mode). In general, the CFSv2 hindcast well predicts these patterns at least 5 months in advance for spring, while shows much lower skills for winter months. In summer, the second predictable patterns are associated with the western North Pacific (WNP) monsoon (i.e., the WNP anticyclone/cyclone) in short leads while associated with ENSO in longer leads (after 4-month lead). The second predictable patterns in fall are mainly associated with tropical Indian Ocean Dipole, which can be predicted 3 months in advance.

Concentration-Dependant Changes of PCB Patterns in Fish-Eating Mammals

DEFF Research Database (Denmark)

Boon, J.P.; van der Meer, J.; Allchin, C.R.

1997-01-01

Data sets on CB concentrations in fish-eating mammals from five laboratories were combined to test and refine a pharmacokinetic model. Clear differences in PCB patterns were observed between species, The ability to metabolize chlorobiphenyl (CB) congeners with vicinal H-atoms only in the ortho...

A multi-Poisson dynamic mixture model to cluster developmental patterns of gene expression by RNA-seq.

Science.gov (United States)

Ye, Meixia; Wang, Zhong; Wang, Yaqun; Wu, Rongling

2015-03-01

Dynamic changes of gene expression reflect an intrinsic mechanism of how an organism responds to developmental and environmental signals. With the increasing availability of expression data across a time-space scale by RNA-seq, the classification of genes as per their biological function using RNA-seq data has become one of the most significant challenges in contemporary biology. Here we develop a clustering mixture model to discover distinct groups of genes expressed during a period of organ development. By integrating the density function of multivariate Poisson distribution, the model accommodates the discrete property of read counts characteristic of RNA-seq data. The temporal dependence of gene expression is modeled by the first-order autoregressive process. The model is implemented with the Expectation-Maximization algorithm and model selection to determine the optimal number of gene clusters and obtain the estimates of Poisson parameters that describe the pattern of time-dependent expression of genes from each cluster. The model has been demonstrated by analyzing a real data from an experiment aimed to link the pattern of gene expression to catkin development in white poplar. The usefulness of the model has been validated through computer simulation. The model provides a valuable tool for clustering RNA-seq data, facilitating our global view of expression dynamics and understanding of gene regulation mechanisms. © The Author 2014. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Dependency models and probability of joint events

International Nuclear Information System (INIS)

Oerjasaeter, O.

1982-08-01

Probabilistic dependencies between components/systems are discussed with reference to a broad classification of potential failure mechanisms. Further, a generalized time-dependency model, based on conditional probabilities for estimation of the probability of joint events and event sequences is described. The applicability of this model is clarified/demonstrated by various examples. It is concluded that the described model of dependency is a useful tool for solving a variety of practical problems concerning the probability of joint events and event sequences where common cause and time-dependent failure mechanisms are involved. (Auth.)

Pattern-oriented modelling: a 'multi-scope' for predictive systems ecology.

Science.gov (United States)

Grimm, Volker; Railsback, Steven F

2012-01-19

Modern ecology recognizes that modelling systems across scales and at multiple levels-especially to link population and ecosystem dynamics to individual adaptive behaviour-is essential for making the science predictive. 'Pattern-oriented modelling' (POM) is a strategy for doing just this. POM is the multi-criteria design, selection and calibration of models of complex systems. POM starts with identifying a set of patterns observed at multiple scales and levels that characterize a system with respect to the particular problem being modelled; a model from which the patterns emerge should contain the right mechanisms to address the problem. These patterns are then used to (i) determine what scales, entities, variables and processes the model needs, (ii) test and select submodels to represent key low-level processes such as adaptive behaviour, and (iii) find useful parameter values during calibration. Patterns are already often used in these ways, but a mini-review of applications of POM confirms that making the selection and use of patterns more explicit and rigorous can facilitate the development of models with the right level of complexity to understand ecological systems and predict their response to novel conditions.

Exploratory graphical models of functional and structural connectivity patterns for Alzheimer's Disease diagnosis

Directory of Open Access Journals (Sweden)

Andres eOrtiz

2015-11-01

Full Text Available Alzheimer’s Disease (AD is the most common neurodegenerative disease in elderly people. Itsdevelopment has been shown to be closely related to changes in the brain connectivity networkand in the brain activation patterns along with structural changes caused by the neurodegenerativeprocess.Methods to infer dependence between brain regions are usually derived from the analysis ofcovariance between activation levels in the different areas. However, these covariance-basedmethods are not able to estimate conditional independence between variables to factor out theinfluence of other regions. Conversely, models based on the inverse covariance, or precisionmatrix, such as Sparse Gaussian Graphical Models allow revealing conditional independencebetween regions by estimating the covariance between two variables given the rest as constant.This paper uses Sparse Inverse Covariance Estimation (SICE methods to learn undirectedgraphs in order to derive functional and structural connectivity patterns from Fludeoxyglucose(18F-FDG Position Emission Tomography (PET data and segmented Magnetic Resonanceimages (MRI, drawn from the ADNI database, for Control, MCI (Mild Cognitive ImpairmentSubjects and AD subjects. Sparse computation fits perfectly here as brain regions usually onlyinteract with a few other areas.The models clearly show different metabolic covariation patters between subject groups, revealingthe loss of strong connections in AD and MCI subjects when compared to Controls. Similarly,the variance between GM (Grey Matter densities of different regions reveals different structuralcovariation patterns between the different groups. Thus, the different connectivity patterns forcontrols and AD are used in this paper to select regions of interest in PET and GM images withdiscriminative power for early AD diagnosis. Finally, functional an structural models are combinedto leverage the classification accuracy.The results obtained in this work show the usefulness

MTR core loading pattern optimization using burnup dependent group constants

Directory of Open Access Journals (Sweden)

Iqbal Masood

2008-01-01

Full Text Available A diffusion theory based MTR fuel management methodology has been developed for finding superior core loading patterns at any stage for MTR systems, keeping track of burnup of individual fuel assemblies throughout their history. It is based on using burnup dependent group constants obtained by the WIMS-D/4 computer code for standard fuel elements and control fuel elements. This methodology has been implemented in a computer program named BFMTR, which carries out detailed five group diffusion theory calculations using the CITATION code as a subroutine. The core-wide spatial flux and power profiles thus obtained are used for calculating the peak-to-average power and flux-ratios along with the available excess reactivity of the system. The fuel manager can use the BFMTR code for loading pattern optimization for maximizing the excess reactivity, keeping the peak-to-average power as well as flux-ratio within constraints. The results obtained by the BFMTR code have been found to be in good agreement with the corresponding experimental values for the equilibrium core of the Pakistan Research Reactor-1.

Cascading walks model for human mobility patterns.

Science.gov (United States)

Han, Xiao-Pu; Wang, Xiang-Wen; Yan, Xiao-Yong; Wang, Bing-Hong

2015-01-01

Uncovering the mechanism behind the scaling laws and series of anomalies in human trajectories is of fundamental significance in understanding many spatio-temporal phenomena. Recently, several models, e.g. the explorations-returns model (Song et al., 2010) and the radiation model for intercity travels (Simini et al., 2012), have been proposed to study the origin of these anomalies and the prediction of human movements. However, an agent-based model that could reproduce most of empirical observations without priori is still lacking. In this paper, considering the empirical findings on the correlations of move-lengths and staying time in human trips, we propose a simple model which is mainly based on the cascading processes to capture the human mobility patterns. In this model, each long-range movement activates series of shorter movements that are organized by the law of localized explorations and preferential returns in prescribed region. Based on the numerical simulations and analytical studies, we show more than five statistical characters that are well consistent with the empirical observations, including several types of scaling anomalies and the ultraslow diffusion properties, implying the cascading processes associated with the localized exploration and preferential returns are indeed a key in the understanding of human mobility activities. Moreover, the model shows both of the diverse individual mobility and aggregated scaling displacements, bridging the micro and macro patterns in human mobility. In summary, our model successfully explains most of empirical findings and provides deeper understandings on the emergence of human mobility patterns.

3-D time-dependent numerical model of flow patterns within a large-scale Czochralski system

Science.gov (United States)

Nam, Phil-Ouk; O, Sang-Kun; Yi, Kyung-Woo

2008-04-01

Silicon single crystals grown through the Czochralski (Cz) method have increased in size to 300 mm, resulting in the use of larger crucibles. The objective of this study is to investigate the continuous Cz method in a large crucible (800 mm), which is performed by inserting a polycrystalline silicon rod into the melt. The numerical model is based on a time-dependent and three-dimensional standard k- ɛ turbulent model using the analytical software package CFD-ACE+, version 2007. Wood's metal melt, which has a low melting point ( Tm=70 °C), was used as the modeling fluid. Crystal rotation given in the clockwise direction with rotation rates varying from 0 to 15 rpm, while the crucible was rotated counter-clockwise, with rotation rates between 0 and 3 rpm. The results show that asymmetrical phenomena of fluid flow arise as results of crystal and crucible rotation, and that these phenomena move with the passage of time. Near the crystal, the flow moves towards the crucible at the pole of the asymmetrical phenomena. Away from the poles, a vortex begins to form, which is strongly pronounced in the region between the poles.

Phase separation driven by density-dependent movement: A novel mechanism for ecological patterns.

Science.gov (United States)

Liu, Quan-Xing; Rietkerk, Max; Herman, Peter M J; Piersma, Theunis; Fryxell, John M; van de Koppel, Johan

2016-12-01

Many ecosystems develop strikingly regular spatial patterns because of small-scale interactions between organisms, a process generally referred to as spatial self-organization. Self-organized spatial patterns are important determinants of the functioning of ecosystems, promoting the growth and survival of the involved organisms, and affecting the capacity of the organisms to cope with changing environmental conditions. The predominant explanation for self-organized pattern formation is spatial heterogeneity in establishment, growth and mortality, resulting from the self-organization processes. A number of recent studies, however, have revealed that movement of organisms can be an important driving process creating extensive spatial patterning in many ecosystems. Here, we review studies that detail movement-based pattern formation in contrasting ecological settings. Our review highlights that a common principle, where movement of organisms is density-dependent, explains observed spatial regular patterns in all of these studies. This principle, well known to physics as the Cahn-Hilliard principle of phase separation, has so-far remained unrecognized as a general mechanism for self-organized complexity in ecology. Using the examples presented in this paper, we explain how this movement principle can be discerned in ecological settings, and clarify how to test this mechanism experimentally. Our study highlights that animal movement, both in isolation and in unison with other processes, is an important mechanism for regular pattern formation in ecosystems. Copyright © 2016 Elsevier B.V. All rights reserved.

Modeling spatial processes with unknown extremal dependence class

KAUST Repository

Huser, Raphaël G.

2017-03-17

Many environmental processes exhibit weakening spatial dependence as events become more extreme. Well-known limiting models, such as max-stable or generalized Pareto processes, cannot capture this, which can lead to a preference for models that exhibit a property known as asymptotic independence. However, weakening dependence does not automatically imply asymptotic independence, and whether the process is truly asymptotically (in)dependent is usually far from clear. The distinction is key as it can have a large impact upon extrapolation, i.e., the estimated probabilities of events more extreme than those observed. In this work, we present a single spatial model that is able to capture both dependence classes in a parsimonious manner, and with a smooth transition between the two cases. The model covers a wide range of possibilities from asymptotic independence through to complete dependence, and permits weakening dependence of extremes even under asymptotic dependence. Censored likelihood-based inference for the implied copula is feasible in moderate dimensions due to closed-form margins. The model is applied to oceanographic datasets with ambiguous true limiting dependence structure.

Lethal body concentrations and accumulation patterns determine time-dependent toxicity of cadmium in soil arthropods

Energy Technology Data Exchange (ETDEWEB)

Crommentuijn, T.; Doodeman, C.J.A.M.; Doornekamp, A.; Pol, J.J.C. van der; Bedaux, J.J.M.; Gestel, C.A.M. van (Vrije Univ., Amsterdam (Netherlands))

1994-11-01

Time-dependent toxicity in bioassays is usually explained in terms of uptake and elimination kinetics of the toxicant. By comparing different species with essentially different accumulation kinetics, a firm test of this concept may be made. This article compares the sensitivity of six soil arthropods, the collembolans Orchesella cincta and Tomocerus minor, the oribatid mite Platynothrus peltifer, the isopods Porcellio scaber and Oniscus asellus, and the diplopod Cylindroiulus britannicus, when exposed to cadmium in the food. Survival was determined at various time intervals; accumulation of cadmium in the animals was measured at one time interval. Kinetic-based toxicity models were fitted to the data, and estimates were obtained for lethal body concentration, uptake rate constant, elimination rate constant, and ultimate LC50. Two different accumulation patterns could be discerned; these were correlated with time-survival relationships. One, species that have the possibility to eliminate cadmium will reach an equilibrium for the internal concentration and also an ultimate LC50. Two, species that are unable to eliminate cadmium but store it in the body will have an ultimate LC50 equal to zero. For these species the time in which the lethal body concentration is reached is more important. Taxonomically related species appeared to have comparable accumulation patterns, but lethal body concentrations differed. It is concluded that knowledge of the accumulation pattern is indispensable for the evaluation of species' sensitivities to toxicants.

Pattern formation in superdiffusion Oregonator model

Science.gov (United States)

Feng, Fan; Yan, Jia; Liu, Fu-Cheng; He, Ya-Feng

2016-10-01

Pattern formations in an Oregonator model with superdiffusion are studied in two-dimensional (2D) numerical simulations. Stability analyses are performed by applying Fourier and Laplace transforms to the space fractional reaction-diffusion systems. Antispiral, stable turing patterns, and travelling patterns are observed by changing the diffusion index of the activator. Analyses of Floquet multipliers show that the limit cycle solution loses stability at the wave number of the primitive vector of the travelling hexagonal pattern. We also observed a transition between antispiral and spiral by changing the diffusion index of the inhibitor. Project supported by the National Natural Science Foundation of China (Grant Nos. 11205044 and 11405042), the Research Foundation of Education Bureau of Hebei Province, China (Grant Nos. Y2012009 and ZD2015025), the Program for Young Principal Investigators of Hebei Province, China, and the Midwest Universities Comprehensive Strength Promotion Project.

Modeling of metal nanocluster growth on patterned substrates and surface pattern formation under ion bombardment

Energy Technology Data Exchange (ETDEWEB)

Numazawa, Satoshi

2012-11-01

are considered as local transition events constrained in potential energy wells over certain local time periods. These processes are represented by Markov chains of multi-dimensional Boolean valued functions in three dimensional lattice space. Consequently, the fluctuating system evolution process is implemented as a Markov chain of equivalence class objects. It is shown that the process can be characterized by the acceptance of metastable local transitions. The method is applied to a problem of Au and Ag cluster growth on a rippled surface. The simulation predicts the existence of a morphology dependent transition time limit from a local metastable to stable state for subsequent cluster growth by accretion. The third topic is the formation of ripple structures on ion bombarded semiconductor surfaces treated in the first topic as the prepatterned substrate of the metallic deposition. This intriguing phenomenon has been known since the 1960's and various theoretical approaches have been explored. These previous models are discussed and a new non-linear model is formulated, based on the local atomic flow and associated density change in the near surface region. Within this framework ripple structures are shown to form without the necessity to invoke surface diffusion or large sputtering as important mechanisms. The model can also be extended to the case where sputtering is important and it is shown that in this case, certain 'magic' angles can occur at which the ripple patterns are most clearly defined. The results including some analytic solutions of the nonlinear equation of motions are in very good agreement with experimental observation.

Modeling of metal nanocluster growth on patterned substrates and surface pattern formation under ion bombardment

Energy Technology Data Exchange (ETDEWEB)

Numazawa, Satoshi

2012-11-01

are considered as local transition events constrained in potential energy wells over certain local time periods. These processes are represented by Markov chains of multi-dimensional Boolean valued functions in three dimensional lattice space. Consequently, the fluctuating system evolution process is implemented as a Markov chain of equivalence class objects. It is shown that the process can be characterized by the acceptance of metastable local transitions. The method is applied to a problem of Au and Ag cluster growth on a rippled surface. The simulation predicts the existence of a morphology dependent transition time limit from a local metastable to stable state for subsequent cluster growth by accretion. The third topic is the formation of ripple structures on ion bombarded semiconductor surfaces treated in the first topic as the prepatterned substrate of the metallic deposition. This intriguing phenomenon has been known since the 1960's and various theoretical approaches have been explored. These previous models are discussed and a new non-linear model is formulated, based on the local atomic flow and associated density change in the near surface region. Within this framework ripple structures are shown to form without the necessity to invoke surface diffusion or large sputtering as important mechanisms. The model can also be extended to the case where sputtering is important and it is shown that in this case, certain 'magic' angles can occur at which the ripple patterns are most clearly defined. The results including some analytic solutions of the nonlinear equation of motions are in very good agreement with experimental observation.

Drought Patterns Forecasting using an Auto-Regressive Logistic Model

Science.gov (United States)

del Jesus, M.; Sheffield, J.; Méndez Incera, F. J.; Losada, I. J.; Espejo, A.

2014-12-01

Drought is characterized by a water deficit that may manifest across a large range of spatial and temporal scales. Drought may create important socio-economic consequences, many times of catastrophic dimensions. A quantifiable definition of drought is elusive because depending on its impacts, consequences and generation mechanism, different water deficit periods may be identified as a drought by virtue of some definitions but not by others. Droughts are linked to the water cycle and, although a climate change signal may not have emerged yet, they are also intimately linked to climate.In this work we develop an auto-regressive logistic model for drought prediction at different temporal scales that makes use of a spatially explicit framework. Our model allows to include covariates, continuous or categorical, to improve the performance of the auto-regressive component.Our approach makes use of dimensionality reduction (principal component analysis) and classification techniques (K-Means and maximum dissimilarity) to simplify the representation of complex climatic patterns, such as sea surface temperature (SST) and sea level pressure (SLP), while including information on their spatial structure, i.e. considering their spatial patterns. This procedure allows us to include in the analysis multivariate representation of complex climatic phenomena, as the El Niño-Southern Oscillation. We also explore the impact of other climate-related variables such as sun spots. The model allows to quantify the uncertainty of the forecasts and can be easily adapted to make predictions under future climatic scenarios. The framework herein presented may be extended to other applications such as flash flood analysis, or risk assessment of natural hazards.

Spatio-temporal patterns in simple models of marine systems

Science.gov (United States)

Feudel, U.; Baurmann, M.; Gross, T.

2009-04-01

Spatio-temporal patterns in marine systems are a result of the interaction of population dynamics with physical transport processes. These physical transport processes can be either diffusion processes in marine sediments or in the water column. We study the dynamics of one population of bacteria and its nutrient in in a simplified model of a marine sediments, taking into account that the considered bacteria possess an active as well as an inactive state, where activation is processed by signal molecules. Furthermore the nutrients are transported actively by bioirrigation and passively by diffusion. It is shown that under certain conditions Turing patterns can occur which yield heterogeneous spatial patterns of the species. The influence of bioirrigation on Turing patterns leads to the emergence of ''hot spots``, i.e. localized regions of enhanced bacterial activity. All obtained patterns fit quite well to observed patterns in laboratory experiments. Spatio-temporal patterns appear in a predator-prey model, used to describe plankton dynamics. These patterns appear due to the simultaneous emergence of Turing patterns and oscillations in the species abundance in the neighborhood of a Turing-Hopf bifurcation. We observe a large variety of different patterns where i) stationary heterogeneous patterns (e.g. hot and cold spots) compete with spatio-temporal patterns ii) slowly moving patterns are embedded in an oscillatory background iii) moving fronts and spiral waves appear.

Parameter dependence and outcome dependence in dynamical models for state vector reduction

International Nuclear Information System (INIS)

Ghirardi, G.C.; Grassi, R.; Butterfield, J.; Fleming, G.N.

1993-01-01

The authors apply the distinction between parameter independence and outcome independence to the linear and nonlinear models of a recent nonrelativistic theory of continuous state vector reduction. It is shown that in the nonlinear model there is a set of realizations of the stochastic process that drives the state vector reduction for which parameter independence is violated for parallel spin components in the EPR-Bohm setup. Such a set has an appreciable probability of occurrence (∼ 1/2). On the other hand, the linear model exhibits only extremely small parameter dependence effects. Some specific features of the models are investigated and it is recalled that, as has been pointed out recently, to be able to speak of definite outcomes (or equivalently of possessed objective elements of reality) at finite times, the criteria for their attribution to physical systems must be slightly changed. The concluding section is devoted to a detailed discussion of the difficulties met when attempting to take, as a starting point for the formulation of a relativistic theory, a nonrelativistic scheme which exhibits parameter dependence. Here the authors derive a theorem which identifies the precise sense in which the occurrence of parameter dependence forbids a genuinely relativistic generalization. Finally, the authors show how the appreciable parameter dependence of the nonlinear model gives rise to problems with relativity, while the extremely weak parameter dependence of the linear model does not give rise to any difficulty, provided the appropriate criteria for the attribution of definite outcomes are taken into account. 19 refs

Physically-based modeling of topographic effects on spatial evapotranspiration and soil moisture patterns through radiation and wind

Directory of Open Access Journals (Sweden)

M. Liu

2012-02-01

Full Text Available In this paper, simulations with the Soil Water Atmosphere Plant (SWAP model are performed to quantify the spatial variability of both potential and actual evapotranspiration (ET, and soil moisture content (SMC caused by topography-induced spatial wind and radiation differences. To obtain the spatially distributed ET/SMC patterns, the field scale SWAP model is applied in a distributed way for both pointwise and catchment wide simulations. An adapted radiation model from r.sun and the physically-based meso-scale wind model METRAS PC are applied to obtain the spatial radiation and wind patterns respectively, which show significant spatial variation and correlation with aspect and elevation respectively. Such topographic dependences and spatial variations further propagate to ET/SMC. A strong spatial, seasonal-dependent, scale-relevant intra-catchment variability in daily/annual ET and less variability in SMC can be observed from the numerical experiments. The study concludes that topography has a significant effect on ET/SMC in the humid region where ET is a energy limited rather than water availability limited process. It affects the spatial runoff generation through spatial radiation and wind, therefore should be applied to inform hydrological model development. In addition, the methodology used in the study can serve as a general method for physically-based ET estimation for data sparse regions.

Temperature dependence of ordered GeSi island growth on patterned Si (001) substrates

International Nuclear Information System (INIS)

ZhongZhenyang; Chen Peixuan; Jiang Zuimin; Bauer, Guenther

2008-01-01

Statistical information on GeSi islands grown on two-dimensionally pit-patterned Si substrates at different temperatures is presented. Three growth regimes on patterned substrates are identified: (i) kinetically limited growth at low growth temperatures, (ii) ordered island growth in an intermediate temperature range, and (iii) stochastic island growth within pits at high temperatures. A qualitative model based on growth kinetics is proposed to explain these phenomena. It can serve as a guidance to realize optimum growth conditions for ordered islands on patterned substrates

Patterns of flavour violation in models with vector-like quarks

Energy Technology Data Exchange (ETDEWEB)

Bobeth, Christoph [TUM Institute for Advanced Study, Lichtenbergstr. 2a, D-85748 Garching (Germany); Physik Department, TU München, James-Franck-Straße, D-85748 Garching (Germany); Excellence Cluster Universe, Technische Universität München,Boltzmannstr. 2, D-85748 Garching (Germany); Buras, Andrzej J. [TUM Institute for Advanced Study, Lichtenbergstr. 2a, D-85748 Garching (Germany); Physik Department, TU München, James-Franck-Straße, D-85748 Garching (Germany); Celis, Alejandro [Ludwig-Maximilians-Universität München, Fakultät für Physik,Arnold Sommerfeld Center for Theoretical Physics, 80333 München (Germany); Jung, Martin [TUM Institute for Advanced Study, Lichtenbergstr. 2a, D-85748 Garching (Germany); Excellence Cluster Universe, Technische Universität München,Boltzmannstr. 2, D-85748 Garching (Germany)

2017-04-13

We study the patterns of flavour violation in renormalisable extensions of the Standard Model (SM) that contain vector-like quarks (VLQs) in a single complex representation of either the SM gauge group G{sub SM} or G{sub SM}{sup ′}≡G{sub SM}⊗U(1){sub L{sub μ−L{sub τ}}}. We first decouple VLQs in the M=(1−10) TeV range and then at the electroweak scale also Z,Z{sup ′} gauge bosons and additional scalars to study the phenomenology. The results depend on the relative size of Z- and Z{sup ′}-induced flavour-changing neutral currents, as well as the size of |ΔF|=2 contributions including the effects of renormalisation group Yukawa evolution from M to the electroweak scale that turn out to be very important for models with right-handed currents through the generation of left-right operators. In addition to rare decays like P→ℓℓ̄, P→P{sup ′}ℓℓ̄, P→P{sup ′}νν̄ with P=K,B{sub s},B{sub d} and |ΔF|=2 observables we analyze the ratio ε{sup ′}/ε which appears in the SM to be significantly below the data. We study patterns and correlations between these observables which taken together should in the future allow for differentiating between VLQ models. In particular the patterns in models with left-handed and right-handed currents are markedly different from each other. Among the highlights are large Z-mediated new physics effects in Kaon observables in some of the models and significant effects in B{sub s,d}-observables. ε{sup ′}/ε can easily be made consistent with the data, implying then uniquely the suppression of K{sub L}→π{sup 0}νν̄. Significant enhancements of Br(K{sup +}→π{sup +}νν̄) are still possible. We point out that the combination of NP effects to |ΔF|=2 and |ΔF|=1 observables in a given meson system generally allows to determine the masses of VLQs in a given representation independently of the size of VLQ couplings.

Modeling and analyzing stripe patterns in fish skin

Science.gov (United States)

Zheng, Yibo; Zhang, Lei; Wang, Yuan; Liang, Ping; Kang, Junjian

2009-11-01

The formation mechanism of stripe patterns in the skin of tropical fishes has been investigated by a coupled two variable reaction diffusion model. Two types of spatial inhomogeneities have been introduced into a homogenous system. Several Turing modes pumped by the Turing instability give rise to a simple stripe pattern. It is found that the Turing mechanism can only determine the wavelength of stripe pattern. The orientation of stripe pattern is determined by the spatial inhomogeneity. Our numerical results suggest that it may be the most possible mechanism for the forming process of fish skin patterns.

Dynamic response and transfer function of social systems: A neuro-inspired model of collective human activity patterns.

Science.gov (United States)

Lymperopoulos, Ilias N

2017-10-01

The interaction of social networks with the external environment gives rise to non-stationary activity patterns reflecting the temporal structure and strength of exogenous influences that drive social dynamical processes far from an equilibrium state. Following a neuro-inspired approach, based on the dynamics of a passive neuronal membrane, and the firing rate dynamics of single neurons and neuronal populations, we build a state-of-the-art model of the collective social response to exogenous interventions. In this regard, we analyze online activity patterns with a view to determining the transfer function of social systems, that is, the dynamic relationship between external influences and the resulting activity. To this end, first we estimate the impulse response (Green's function) of collective activity, and then we show that the convolution of the impulse response with a time-varying external influence field accurately reproduces empirical activity patterns. To capture the dynamics of collective activity when the generating process is in a state of statistical equilibrium, we incorporate into the model a noisy input convolved with the impulse response function, thus precisely reproducing the fluctuations of stationary collective activity around a resting value. The outstanding goodness-of-fit of the model results to empirical observations, indicates that the model explains human activity patterns generated by time-dependent external influences in various socio-economic contexts. The proposed model can be used for inferring the temporal structure and strength of external influences, as well as the inertia of collective social activity. Furthermore, it can potentially predict social activity patterns. Copyright © 2017 Elsevier Ltd. All rights reserved.

Time-dependent scaling patterns in high frequency financial data

Science.gov (United States)

Nava, Noemi; Di Matteo, Tiziana; Aste, Tomaso

2016-10-01

We measure the influence of different time-scales on the intraday dynamics of financial markets. This is obtained by decomposing financial time series into simple oscillations associated with distinct time-scales. We propose two new time-varying measures of complexity: 1) an amplitude scaling exponent and 2) an entropy-like measure. We apply these measures to intraday, 30-second sampled prices of various stock market indices. Our results reveal intraday trends where different time-horizons contribute with variable relative amplitudes over the course of the trading day. Our findings indicate that the time series we analysed have a non-stationary multifractal nature with predominantly persistent behaviour at the middle of the trading session and anti-persistent behaviour at the opening and at the closing of the session. We demonstrate that these patterns are statistically significant, robust, reproducible and characteristic of each stock market. We argue that any modelling, analytics or trading strategy must take into account these non-stationary intraday scaling patterns.

Turing Patterns in a Reaction-Diffusion System

International Nuclear Information System (INIS)

Wu Yanning; Wang Pingjian; Hou Chunju; Liu Changsong; Zhu Zhengang

2006-01-01

We have further investigated Turing patterns in a reaction-diffusion system by theoretical analysis and numerical simulations. Simple Turing patterns and complex superlattice structures are observed. We find that the shape and type of Turing patterns depend on dynamical parameters and external periodic forcing, and is independent of effective diffusivity rate σ in the Lengyel-Epstein model. Our numerical results provide additional insight into understanding the mechanism of development of Turing patterns and predicting new pattern formations.

Stochastic Turing Patterns: Analysis of Compartment-Based Approaches

KAUST Repository

Cao, Yang; Erban, Radek

2014-01-01

© 2014, Society for Mathematical Biology. Turing patterns can be observed in reaction-diffusion systems where chemical species have different diffusion constants. In recent years, several studies investigated the effects of noise on Turing patterns and showed that the parameter regimes, for which stochastic Turing patterns are observed, can be larger than the parameter regimes predicted by deterministic models, which are written in terms of partial differential equations (PDEs) for species concentrations. A common stochastic reaction-diffusion approach is written in terms of compartment-based (lattice-based) models, where the domain of interest is divided into artificial compartments and the number of molecules in each compartment is simulated. In this paper, the dependence of stochastic Turing patterns on the compartment size is investigated. It has previously been shown (for relatively simpler systems) that a modeler should not choose compartment sizes which are too small or too large, and that the optimal compartment size depends on the diffusion constant. Taking these results into account, we propose and study a compartment-based model of Turing patterns where each chemical species is described using a different set of compartments. It is shown that the parameter regions where spatial patterns form are different from the regions obtained by classical deterministic PDE-based models, but they are also different from the results obtained for the stochastic reaction-diffusion models which use a single set of compartments for all chemical species. In particular, it is argued that some previously reported results on the effect of noise on Turing patterns in biological systems need to be reinterpreted.

Stochastic Turing Patterns: Analysis of Compartment-Based Approaches

KAUST Repository

Cao, Yang

2014-11-25

© 2014, Society for Mathematical Biology. Turing patterns can be observed in reaction-diffusion systems where chemical species have different diffusion constants. In recent years, several studies investigated the effects of noise on Turing patterns and showed that the parameter regimes, for which stochastic Turing patterns are observed, can be larger than the parameter regimes predicted by deterministic models, which are written in terms of partial differential equations (PDEs) for species concentrations. A common stochastic reaction-diffusion approach is written in terms of compartment-based (lattice-based) models, where the domain of interest is divided into artificial compartments and the number of molecules in each compartment is simulated. In this paper, the dependence of stochastic Turing patterns on the compartment size is investigated. It has previously been shown (for relatively simpler systems) that a modeler should not choose compartment sizes which are too small or too large, and that the optimal compartment size depends on the diffusion constant. Taking these results into account, we propose and study a compartment-based model of Turing patterns where each chemical species is described using a different set of compartments. It is shown that the parameter regions where spatial patterns form are different from the regions obtained by classical deterministic PDE-based models, but they are also different from the results obtained for the stochastic reaction-diffusion models which use a single set of compartments for all chemical species. In particular, it is argued that some previously reported results on the effect of noise on Turing patterns in biological systems need to be reinterpreted.

A Multiscale Survival Process for Modeling Human Activity Patterns.

Science.gov (United States)

Zhang, Tianyang; Cui, Peng; Song, Chaoming; Zhu, Wenwu; Yang, Shiqiang

2016-01-01

Human activity plays a central role in understanding large-scale social dynamics. It is well documented that individual activity pattern follows bursty dynamics characterized by heavy-tailed interevent time distributions. Here we study a large-scale online chatting dataset consisting of 5,549,570 users, finding that individual activity pattern varies with timescales whereas existing models only approximate empirical observations within a limited timescale. We propose a novel approach that models the intensity rate of an individual triggering an activity. We demonstrate that the model precisely captures corresponding human dynamics across multiple timescales over five orders of magnitudes. Our model also allows extracting the population heterogeneity of activity patterns, characterized by a set of individual-specific ingredients. Integrating our approach with social interactions leads to a wide range of implications.

Discrimination of gender-, speed-, and shoe-dependent movement patterns in runners using full-body kinematics.

Science.gov (United States)

Maurer, Christian; Federolf, Peter; von Tscharner, Vinzenz; Stirling, Lisa; Nigg, Benno M

2012-05-01

Changes in gait kinematics have often been analyzed using pattern recognition methods such as principal component analysis (PCA). It is usually just the first few principal components that are analyzed, because they describe the main variability within a dataset and thus represent the main movement patterns. However, while subtle changes in gait pattern (for instance, due to different footwear) may not change main movement patterns, they may affect movements represented by higher principal components. This study was designed to test two hypotheses: (1) speed and gender differences can be observed in the first principal components, and (2) small interventions such as changing footwear change the gait characteristics of higher principal components. Kinematic changes due to different running conditions (speed - 3.1m/s and 4.9 m/s, gender, and footwear - control shoe and adidas MicroBounce shoe) were investigated by applying PCA and support vector machine (SVM) to a full-body reflective marker setup. Differences in speed changed the basic movement pattern, as was reflected by a change in the time-dependent coefficient derived from the first principal. Gender was differentiated by using the time-dependent coefficient derived from intermediate principal components. (Intermediate principal components are characterized by limb rotations of the thigh and shank.) Different shoe conditions were identified in higher principal components. This study showed that different interventions can be analyzed using a full-body kinematic approach. Within the well-defined vector space spanned by the data of all subjects, higher principal components should also be considered because these components show the differences that result from small interventions such as footwear changes. Crown Copyright © 2012. Published by Elsevier B.V. All rights reserved.

Hopfield's Model of Patterns Recognition and Laws of Artistic Perception

Science.gov (United States)

Yevin, Igor; Koblyakov, Alexander

The model of patterns recognition or attractor network model of associative memory, offered by J.Hopfield 1982, is the most known model in theoretical neuroscience. This paper aims to show, that such well-known laws of art perception as the Wundt curve, perception of visual ambiguity in art, and also the model perception of musical tonalities are nothing else than special cases of the Hopfield’s model of patterns recognition.

Modeling and Verification of Dependable Electronic Power System Architecture

Science.gov (United States)

Yuan, Ling; Fan, Ping; Zhang, Xiao-fang

The electronic power system can be viewed as a system composed of a set of concurrently interacting subsystems to generate, transmit, and distribute electric power. The complex interaction among sub-systems makes the design of electronic power system complicated. Furthermore, in order to guarantee the safe generation and distribution of electronic power, the fault tolerant mechanisms are incorporated in the system design to satisfy high reliability requirements. As a result, the incorporation makes the design of such system more complicated. We propose a dependable electronic power system architecture, which can provide a generic framework to guide the development of electronic power system to ease the development complexity. In order to provide common idioms and patterns to the system *designers, we formally model the electronic power system architecture by using the PVS formal language. Based on the PVS model of this system architecture, we formally verify the fault tolerant properties of the system architecture by using the PVS theorem prover, which can guarantee that the system architecture can satisfy high reliability requirements.

Scale dependent inference in landscape genetics

Science.gov (United States)

Samuel A. Cushman; Erin L. Landguth

2010-01-01

Ecological relationships between patterns and processes are highly scale dependent. This paper reports the first formal exploration of how changing scale of research away from the scale of the processes governing gene flow affects the results of landscape genetic analysis. We used an individual-based, spatially explicit simulation model to generate patterns of genetic...

Pattern-oriented modelling: a ‘multi-scope’ for predictive systems ecology

Science.gov (United States)

Grimm, Volker; Railsback, Steven F.

2012-01-01

Modern ecology recognizes that modelling systems across scales and at multiple levels—especially to link population and ecosystem dynamics to individual adaptive behaviour—is essential for making the science predictive. ‘Pattern-oriented modelling’ (POM) is a strategy for doing just this. POM is the multi-criteria design, selection and calibration of models of complex systems. POM starts with identifying a set of patterns observed at multiple scales and levels that characterize a system with respect to the particular problem being modelled; a model from which the patterns emerge should contain the right mechanisms to address the problem. These patterns are then used to (i) determine what scales, entities, variables and processes the model needs, (ii) test and select submodels to represent key low-level processes such as adaptive behaviour, and (iii) find useful parameter values during calibration. Patterns are already often used in these ways, but a mini-review of applications of POM confirms that making the selection and use of patterns more explicit and rigorous can facilitate the development of models with the right level of complexity to understand ecological systems and predict their response to novel conditions. PMID:22144392

Numerical approaches to model perturbation fire in turing pattern formations

Science.gov (United States)

Campagna, R.; Brancaccio, M.; Cuomo, S.; Mazzoleni, S.; Russo, L.; Siettos, K.; Giannino, F.

2017-11-01

Turing patterns were observed in chemical, physical and biological systems described by coupled reaction-diffusion equations. Several models have been formulated proposing the water as the causal mechanism of vegetation pattern formation, but this isn't an exhaustive hypothesis in some natural environments. An alternative explanation has been related to the plant-soil negative feedback. In Marasco et al. [1] the authors explored the hypothesis that both mechanisms contribute in the formation of regular and irregular vegetation patterns. The mathematical model consists in three partial differential equations (PDEs) that take into account for a dynamic balance between biomass, water and toxic compounds. A numerical approach is mandatory also to investigate on the predictions of this kind of models. In this paper we start from the mathematical model described in [1], set the model parameters such that the biomass reaches a stable spatial pattern (spots) and present preliminary studies about the occurrence of perturbing events, such as wildfire, that can affect the regularity of the biomass configuration.

A sequence-dependent rigid-base model of DNA

Science.gov (United States)

Gonzalez, O.; Petkevičiutė, D.; Maddocks, J. H.

2013-02-01

A novel hierarchy of coarse-grain, sequence-dependent, rigid-base models of B-form DNA in solution is introduced. The hierarchy depends on both the assumed range of energetic couplings, and the extent of sequence dependence of the model parameters. A significant feature of the models is that they exhibit the phenomenon of frustration: each base cannot simultaneously minimize the energy of all of its interactions. As a consequence, an arbitrary DNA oligomer has an intrinsic or pre-existing stress, with the level of this frustration dependent on the particular sequence of the oligomer. Attention is focussed on the particular model in the hierarchy that has nearest-neighbor interactions and dimer sequence dependence of the model parameters. For a Gaussian version of this model, a complete coarse-grain parameter set is estimated. The parameterized model allows, for an oligomer of arbitrary length and sequence, a simple and explicit construction of an approximation to the configuration-space equilibrium probability density function for the oligomer in solution. The training set leading to the coarse-grain parameter set is itself extracted from a recent and extensive database of a large number of independent, atomic-resolution molecular dynamics (MD) simulations of short DNA oligomers immersed in explicit solvent. The Kullback-Leibler divergence between probability density functions is used to make several quantitative assessments of our nearest-neighbor, dimer-dependent model, which is compared against others in the hierarchy to assess various assumptions pertaining both to the locality of the energetic couplings and to the level of sequence dependence of its parameters. It is also compared directly against all-atom MD simulation to assess its predictive capabilities. The results show that the nearest-neighbor, dimer-dependent model can successfully resolve sequence effects both within and between oligomers. For example, due to the presence of frustration, the model can

A sequence-dependent rigid-base model of DNA.

Science.gov (United States)

Gonzalez, O; Petkevičiūtė, D; Maddocks, J H

2013-02-07

A novel hierarchy of coarse-grain, sequence-dependent, rigid-base models of B-form DNA in solution is introduced. The hierarchy depends on both the assumed range of energetic couplings, and the extent of sequence dependence of the model parameters. A significant feature of the models is that they exhibit the phenomenon of frustration: each base cannot simultaneously minimize the energy of all of its interactions. As a consequence, an arbitrary DNA oligomer has an intrinsic or pre-existing stress, with the level of this frustration dependent on the particular sequence of the oligomer. Attention is focussed on the particular model in the hierarchy that has nearest-neighbor interactions and dimer sequence dependence of the model parameters. For a Gaussian version of this model, a complete coarse-grain parameter set is estimated. The parameterized model allows, for an oligomer of arbitrary length and sequence, a simple and explicit construction of an approximation to the configuration-space equilibrium probability density function for the oligomer in solution. The training set leading to the coarse-grain parameter set is itself extracted from a recent and extensive database of a large number of independent, atomic-resolution molecular dynamics (MD) simulations of short DNA oligomers immersed in explicit solvent. The Kullback-Leibler divergence between probability density functions is used to make several quantitative assessments of our nearest-neighbor, dimer-dependent model, which is compared against others in the hierarchy to assess various assumptions pertaining both to the locality of the energetic couplings and to the level of sequence dependence of its parameters. It is also compared directly against all-atom MD simulation to assess its predictive capabilities. The results show that the nearest-neighbor, dimer-dependent model can successfully resolve sequence effects both within and between oligomers. For example, due to the presence of frustration, the model can

Modelling electricity futures prices using seasonal path-dependent volatility

International Nuclear Information System (INIS)

Fanelli, Viviana; Maddalena, Lucia; Musti, Silvana

2016-01-01

Highlights: • A no-arbitrage term structure model is applied to the electricity market. • Volatility parameters of the HJM model are estimated by using German data. • The model captures the seasonal price behaviour. • Electricity futures prices are forecasted. • Call options are evaluated according to different strike prices. - Abstract: The liberalization of electricity markets gave rise to new patterns of futures prices and the need of models that could efficiently describe price dynamics grew exponentially, in order to improve decision making for all of the agents involved in energy issues. Although there are papers focused on modelling electricity as a flow commodity by using Heath et al. (1992) approach in order to price futures contracts, the literature is scarce on attempts to consider a seasonal volatility as input to models. In this paper, we propose a futures price model that allows looking into observed stylized facts in the electricity market, in particular stochastic price variability, and periodic behavior. We consider a seasonal path-dependent volatility for futures returns that are modelled in Heath et al. (1992) framework and we obtain the dynamics of futures prices. We use these series to price the underlying asset of a call option in a risk management perspective. We test the model on the German electricity market, and we find that it is accurate in futures and option value estimates. In addition, the obtained results and the proposed methodology can be useful as a starting point for risk management or portfolio optimization under uncertainty in the current context of energy markets.

Total deposition of inhaled particles related to age: comparison with age-dependent model calculations

International Nuclear Information System (INIS)

Becquemin, M.H.; Bouchikhi, A.; Yu, C.P.; Roy, M.

1991-01-01

To compare experimental data with age-dependent model calculations, total airway deposition of polystyrene aerosols (1, 2.05 and 2.8 μm aerodynamic diameter) was measured in ten adults, twenty children aged 12 to 15 years, ten children aged 8 to 12, and eleven under 8 years old. Ventilation was controlled, and breathing patterns were appropriate for each age, either at rest or at light exercise. Individually, deposition percentages increased with particle size and also from rest to exercise, except in children under 12 years, in whom they decreased from 20-21.5 to 14-14.5 for 1 μm particles and from 36.8-36.9 to 32.2-33.1 for 2.05 μm particles. Comparisons with the age-dependent model showed that, at rest, the observed data concerning children agreed with those predicted and were close to the adults' values, when the latter were higher than predicted. At exercise, child data were lower than predicted and lower than adult experimental data, when the latter agreed fairly well with the model. (author)

On Input Vector Representation for the SVR model of Reactor Core Loading Pattern Critical Parameters

International Nuclear Information System (INIS)

Trontl, K.; Pevec, D.; Smuc, T.

2008-01-01

Determination and optimization of reactor core loading pattern is an important factor in nuclear power plant operation. The goal is to minimize the amount of enriched uranium (fresh fuel) and burnable absorbers placed in the core, while maintaining nuclear power plant operational and safety characteristics. The usual approach to loading pattern optimization involves high degree of engineering judgment, a set of heuristic rules, an optimization algorithm and a computer code used for evaluating proposed loading patterns. The speed of the optimization process is highly dependent on the computer code used for the evaluation. Recently, we proposed a new method for fast loading pattern evaluation based on general robust regression model relying on the state of the art research in the field of machine learning. We employed Support Vector Regression (SVR) technique. SVR is a supervised learning method in which model parameters are automatically determined by solving a quadratic optimization problem. The preliminary tests revealed a good potential of the SVR method application for fast and accurate reactor core loading pattern evaluation. However, some aspects of model development are still unresolved. The main objective of the work reported in this paper was to conduct additional tests and analyses required for full clarification of the SVR applicability for loading pattern evaluation. We focused our attention on the parameters defining input vector, primarily its structure and complexity, and parameters defining kernel functions. All the tests were conducted on the NPP Krsko reactor core, using MCRAC code for the calculation of reactor core loading pattern critical parameters. The tested input vector structures did not influence the accuracy of the models suggesting that the initially tested input vector, consisted of the number of IFBAs and the k-inf at the beginning of the cycle, is adequate. The influence of kernel function specific parameters (σ for RBF kernel

Modeling and inferring cleavage patterns in proliferating epithelia.

Directory of Open Access Journals (Sweden)

Ankit B Patel

2009-06-01

Full Text Available The regulation of cleavage plane orientation is one of the key mechanisms driving epithelial morphogenesis. Still, many aspects of the relationship between local cleavage patterns and tissue-level properties remain poorly understood. Here we develop a topological model that simulates the dynamics of a 2D proliferating epithelium from generation to generation, enabling the exploration of a wide variety of biologically plausible cleavage patterns. We investigate a spectrum of models that incorporate the spatial impact of neighboring cells and the temporal influence of parent cells on the choice of cleavage plane. Our findings show that cleavage patterns generate "signature" equilibrium distributions of polygonal cell shapes. These signatures enable the inference of local cleavage parameters such as neighbor impact, maternal influence, and division symmetry from global observations of the distribution of cell shape. Applying these insights to the proliferating epithelia of five diverse organisms, we find that strong division symmetry and moderate neighbor/maternal influence are required to reproduce the predominance of hexagonal cells and low variability in cell shape seen empirically. Furthermore, we present two distinct cleavage pattern models, one stochastic and one deterministic, that can reproduce the empirical distribution of cell shapes. Although the proliferating epithelia of the five diverse organisms show a highly conserved cell shape distribution, there are multiple plausible cleavage patterns that can generate this distribution, and experimental evidence suggests that indeed plants and fruitflies use distinct division mechanisms.

Model dependence of isospin sensitive observables at high densities

Energy Technology Data Exchange (ETDEWEB)

Guo, Wen-Mei [Institute of Modern Physics, Chinese Academy of Sciences, Lanzhou 730000 (China); University of Chinese Academy of Sciences, Beijing 100049 (China); School of Science, Huzhou Teachers College, Huzhou 313000 (China); Yong, Gao-Chan, E-mail: yonggaochan@impcas.ac.cn [Institute of Modern Physics, Chinese Academy of Sciences, Lanzhou 730000 (China); State Key Laboratory of Theoretical Physics, Institute of Theoretical Physics, Chinese Academy of Sciences, Beijing 100190 (China); Wang, Yongjia [School of Science, Huzhou Teachers College, Huzhou 313000 (China); School of Nuclear Science and Technology, Lanzhou University, Lanzhou 730000 (China); Li, Qingfeng [School of Science, Huzhou Teachers College, Huzhou 313000 (China); Zhang, Hongfei [School of Nuclear Science and Technology, Lanzhou University, Lanzhou 730000 (China); State Key Laboratory of Theoretical Physics, Institute of Theoretical Physics, Chinese Academy of Sciences, Beijing 100190 (China); Zuo, Wei [Institute of Modern Physics, Chinese Academy of Sciences, Lanzhou 730000 (China); State Key Laboratory of Theoretical Physics, Institute of Theoretical Physics, Chinese Academy of Sciences, Beijing 100190 (China)

2013-10-07

Within two different frameworks of isospin-dependent transport model, i.e., Boltzmann–Uehling–Uhlenbeck (IBUU04) and Ultrarelativistic Quantum Molecular Dynamics (UrQMD) transport models, sensitive probes of nuclear symmetry energy are simulated and compared. It is shown that neutron to proton ratio of free nucleons, π{sup −}/π{sup +} ratio as well as isospin-sensitive transverse and elliptic flows given by the two transport models with their “best settings”, all have obvious differences. Discrepancy of numerical value of isospin-sensitive n/p ratio of free nucleon from the two models mainly originates from different symmetry potentials used and discrepancies of numerical value of charged π{sup −}/π{sup +} ratio and isospin-sensitive flows mainly originate from different isospin-dependent nucleon–nucleon cross sections. These demonstrations call for more detailed studies on the model inputs (i.e., the density- and momentum-dependent symmetry potential and the isospin-dependent nucleon–nucleon cross section in medium) of isospin-dependent transport model used. The studies of model dependence of isospin sensitive observables can help nuclear physicists to pin down the density dependence of nuclear symmetry energy through comparison between experiments and theoretical simulations scientifically.

Level of khat dependence, use patterns, and psychosocial correlates in Yemen: a cross-sectional investigation.

Science.gov (United States)

Nakajima, Motohiro; Hoffman, Richard; al'Absi, Mustafa

2017-05-01

Chronic khat use is associated with negative health consequences. However, no study has fully characterized individuals who are khat dependent. This paper examines socio-demographic and psychosocial correlates of adult khat dependence. A total of 270 khat users (129 women) in Yemen completed face-to-face interviews and provided demographic information and data on patterns of khat use, subjective mood, and sleep quality. The Severity of Dependence Scale-Khat (SDS-khat) was used to assess level of khat dependence. A series of analysis of variance was conducted. Khat users, on average, used khat for 5.2 hours a day (SD = 2.3) for 5.7 days a week (SD = 2.0). Individuals who screened positive for khat dependence reported longer duration of khat sessions per day, higher frequency of khat use per week, greater levels of negative mood and sleep disturbances, and were more likely to endorse physical symptoms after khat use (P < 0.05). Future research should elucidate mechanisms responsible for khat dependence symptomatology.

Modeling the Spatial Distribution and Fruiting Pattern of a Key Tree Species in a Neotropical Forest: Methodology and Potential Applications

NARCIS (Netherlands)

Caillaud, D.; Crofoot, M.C.; Scarpino, S.V.; Jansen, P.A.; Garzon-Lopez, C.X.; Winkelhagen, A.J.S.; Bohlman, S.A.; Walsh, P.D.

2010-01-01

Background - The movement patterns of wild animals depend crucially on the spatial and temporal availability of resources in their habitat. To date, most attempts to model this relationship were forced to rely on simplified assumptions about the spatiotemporal distribution of food resources. Here we

Modeling the Spatial Distribution and Fruiting Pattern of a Key Tree Species in a Neotropical Forest : Methodology and Potential Applications

NARCIS (Netherlands)

Caillaud, Damien; Crofoot, Margaret C.; Scarpino, Samuel V.; Jansen, Patrick A.; Garzon-Lopez, Carol X.; Winkelhagen, Annemarie J. S.; Bohlman, Stephanie A.; Walsh, Peter D.

2010-01-01

Background: The movement patterns of wild animals depend crucially on the spatial and temporal availability of resources in their habitat. To date, most attempts to model this relationship were forced to rely on simplified assumptions about the spatiotemporal distribution of food resources. Here we

Mapping National Plant Biodiversity Patterns in South Korea with the MARS Species Distribution Model.

Directory of Open Access Journals (Sweden)

Hyeyeong Choe

Full Text Available Accurate information on the distribution of existing species is crucial to assess regional biodiversity. However, data inventories are insufficient in many areas. We examine the ability of Multivariate Adaptive Regression Splines (MARS multi-response species distribution model to overcome species' data limitations and portray plant species distribution patterns for 199 South Korean plant species. The study models species with two or more observations, examines their contribution to national patterns of species richness, provides a sensitivity analysis of different range threshold cutoff approaches for modeling species' ranges, and presents considerations for species modeling at fine spatial resolution. We ran MARS models for each species and tested four threshold methods to transform occurrence probabilities into presence or absence range maps. Modeled occurrence probabilities were extracted at each species' presence points, and the mean, median, and one standard deviation (SD calculated to define data-driven thresholds. A maximum sum of sensitivity and specificity threshold was also calculated, and the range maps from the four cutoffs were tested using independent plant survey data. The single SD values were the best threshold tested for minimizing omission errors and limiting species ranges to areas where the associated occurrence data were correctly classed. Eight individual species range maps for rare plant species were identified that are potentially affected by resampling predictor variables to fine spatial scales. We portray spatial patterns of high species richness by assessing the combined range maps from three classes of species: all species, endangered and endemic species, and range-size rarity of all species, which could be used in conservation planning for South Korea. The MARS model is promising for addressing the common problem of few species occurrence records. However, projected species ranges are highly dependent on the

Low-frequency (0.7-7.4 mHz geomagnetic field fluctuations at high latitude: frequency dependence of the polarization pattern

Directory of Open Access Journals (Sweden)

L. Cafarella

2001-06-01

Full Text Available A statistical analysis of the polarization pattern of low-frequency geomagnetic field fluctuations (0.7-7.4 mHz covering the entire 24-h interval was performed at the Antarctic station Terra Nova Bay (80.0°S geomagnetic latitude throughout 1997 and 1998. The results show that the polarization pattern exhibits a frequency dependence, as can be expected from the frequency dependence of the latitude where the coupling between the magnetospheric compressional mode and the field line resonance takes place. The polarization analysis of single pulsation events shows that wave packets with different polarization sense, depending on frequency, can be simultaneously observed.

Patterns in the distribution of vegetation in paramo areas: heterogeneity and spacial dependence

OpenAIRE

Arellano-P., Henry; Rangel-CH, J. Orlando

2012-01-01

Two methods of exploratory spatial data analysis (ESDA), analysis of spatial heterogeneity and dependence (auto-correlation), - - were applied to the cover patterns from ten paramo localities in the Central and Eastern cordilleras of Colombia. Among the localities studied, the high montane region of the Serrania de Perija, the paramo region of the Los Nevados National Park, and the paramo region under management of CORPOGUAVIO showed a good state of conservation and satisfactory level of conn...

Stripe patterns in a model for block polymers

NARCIS (Netherlands)

Peletier, M.A.; Veneroni, M.

2009-01-01

We consider a pattern-forming system in two space dimensions defined by an energy Ge. The functional Ge models strong phase separation in AB diblock copolymer melts, and patterns are represented by {0, 1}-valued functions; the values 0 and 1 correspond to the A and B phases. The parameter e is the

Stripe patterns in a model for block polymers

NARCIS (Netherlands)

Peletier, M.A.; Veneroni, M.

2010-01-01

We consider a pattern-forming system in two space dimensions defined by an energy Ge. The functional Ge models strong phase separation in AB diblock copolymer melts, and patterns are represented by {0, 1}-valued functions; the values 0 and 1 correspond to the A and B phases. The parameter e is the

Rank dependent expected utility models of tax evasion.

OpenAIRE

Erling Eide

2001-01-01

In this paper the rank-dependent expected utility theory is substituted for the expected utility theory in models of tax evasion. It is demonstrated that the comparative statics results of the expected utility, portfolio choice model of tax evasion carry over to the more general rank dependent expected utility model.

Active patterning and asymmetric transport in a model actomyosin network

Energy Technology Data Exchange (ETDEWEB)

Wang, Shenshen [Department of Chemical Engineering and Department of Physics, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139 (United States); Wolynes, Peter G. [Department of Chemistry and Center for Theoretical Biological Physics, Rice University, Houston, Texas 77005 (United States)

2013-12-21

Cytoskeletal networks, which are essentially motor-filament assemblies, play a major role in many developmental processes involving structural remodeling and shape changes. These are achieved by nonequilibrium self-organization processes that generate functional patterns and drive intracellular transport. We construct a minimal physical model that incorporates the coupling between nonlinear elastic responses of individual filaments and force-dependent motor action. By performing stochastic simulations we show that the interplay of motor processes, described as driving anti-correlated motion of the network vertices, and the network connectivity, which determines the percolation character of the structure, can indeed capture the dynamical and structural cooperativity which gives rise to diverse patterns observed experimentally. The buckling instability of individual filaments is found to play a key role in localizing collapse events due to local force imbalance. Motor-driven buckling-induced node aggregation provides a dynamic mechanism that stabilizes the two-dimensional patterns below the apparent static percolation limit. Coordinated motor action is also shown to suppress random thermal noise on large time scales, the two-dimensional configuration that the system starts with thus remaining planar during the structural development. By carrying out similar simulations on a three-dimensional anchored network, we find that the myosin-driven isotropic contraction of a well-connected actin network, when combined with mechanical anchoring that confers directionality to the collective motion, may represent a novel mechanism of intracellular transport, as revealed by chromosome translocation in the starfish oocyte.

Statistical Characterization of the Charge State and Residue Dependence of Low-Energy CID Peptide Dissociation Patterns

International Nuclear Information System (INIS)

Huang, Yingying; Triscari, Joseph M.; Tseng, George C.; Pasa-Tolic, Ljiljana; Lipton, Mary S.; Smith, Richard D.; Wysocki, Vicki H.

2005-01-01

Data mining was performed on 28 330 unique peptide tandem mass spectra for which sequences were assigned with high confidence. By dividing the spectra into different sets based on structural features and charge states of the corresponding peptides, chemical interactions involved in promoting specific cleavage patterns in gas-phase peptides were characterized. Pairwise fragmentation maps describing cleavages at all Xxx-Zzz residue combinations for b and y ions reveal that the difference in basicity between Arg and Lys results in different dissociation patterns for singly charged Arg- and Lys-ending tryptic peptides. While one dominant protonation form (proton localized) exists for Arg-ending peptides, a heterogeneous population of different protonated forms or more facile interconversion of protonated forms (proton partially mobile) exists for Lys-ending peptides. Cleavage C-terminal to acidic residues dominates spectra from peptides that have a localized proton and cleavage N-terminal to Pro dominates those that have a mobile or partially mobile proton. When Pro is absent from peptides that have a mobile or partially mobile proton, cleavage at each peptide bond becomes much more prominent. Whether the above patterns can be found in b ions, y ions, or both depends on the location of the proton holder(s). Enhanced cleavages C-terminal to branched aliphatic residues (Ile, Val, Leu) are observed in both b and y ions from peptides that have a mobile proton, as well as in y ions from peptides that have a partially mobile proton; enhanced cleavages N-terminal to these residues are observed in b ions from peptides that have a partially mobile proton. Statistical tools have been designed to visualize the fragmentation maps and measure the similarity between them. The pairwise cleavage patterns observed expand our knowledge of peptide gas-phase fragmentation behaviors and should be useful in algorithm development that employs improved models to predict fragment ion

BUSINESS MODEL PATTERNS FOR DISRUPTIVE TECHNOLOGIES

OpenAIRE

BENJAMIN AMSHOFF; CHRISTIAN DÜLME; JULIAN ECHTERFELD; JÜRGEN GAUSEMEIER

2015-01-01

Companies nowadays face a myriad of business opportunities as a direct consequence of manifold disruptive technology developments. As a basic characteristic, disruptive technologies lead to a severe shift in value-creation networks giving rise to new market segments. One of the key challenges is to anticipate the business logics within these nascent and formerly unknown markets. Business model patterns promise to tackle this challenge. They can be interpreted as proven business model elements...

Revealing the Driving Forces of Mid-Cities Urban Growth Patterns Using Spatial Modeling: a Case Study of Los Ángeles, Chile

Directory of Open Access Journals (Sweden)

Mauricio I. Aguayo

2007-06-01

Full Text Available City growth and changes in land-use patterns cause various important social and environmental impacts. To understand the spatial and temporal dynamics of these processes, the factors that drive urban development must be identified and analyzed, especially those factors that can be used to predict future changes and their potential environmental effects. Our objectives were to quantify the relationship between urban growth and its driving forces and to predict the spatial growth pattern based on historical land-use changes for the city of Los Ángeles in central Chile. This involved the analysis of images from 1978, 1992, and 1998 and characterization of the spatial pattern of land-use change; the construction of digital coverage in GIS; the selection of predictive variables through univariate analysis; the construction of logistic regression models using growth vs. nongrowth for 1978-1992 as the dependent variable; and the prediction of the probability of land-use change by applying the regression model to the 1992-1998 period. To investigate the influence of spatial scale, we constructed several sets of models that contained (1 only distance variables, e.g., distance to highways; (2 only scale-dependent density variables, e.g., density of urban area within a 600-m radius; (3 both distance and density variables; and (4 both distance and density variables at several spatial scales. The environmental variables were included in all models. The combination of distance and density variables at several scales is required to appropriately capture the multiscale urban growth process. The best models correctly predict ~90% of the observed land-use changes for 1992-1998. The distance to access roads, densities of the urban road system and urbanized area at various scales, and soil type were the strongest predictors of the growth pattern. Other variables were less important or not significant in explaining the urban growth process. Our approach, which

Modelling fast spreading patterns of airborne infectious diseases using complex networks

Science.gov (United States)

Brenner, Frank; Marwan, Norbert; Hoffmann, Peter

2017-04-01

The pandemics of SARS (2002/2003) and H1N1 (2009) have impressively shown the potential of epidemic outbreaks of infectious diseases in a world that is strongly connected. Global air travelling established an easy and fast opportunity for pathogens to migrate globally in only a few days. This made epidemiological prediction harder. By understanding this complex development and its link to climate change we can suggest actions to control a part of global human health affairs. In this study we combine the following data components to simulate the outbreak of an airborne infectious disease that is directly transmitted from human to human: em{Global Air Traffic Network (from openflights.org) with information on airports, airport location, direct flight connection, airplane type} em{Global population dataset (from SEDAC, NASA)} em{Susceptible-Infected-Recovered (SIR) compartmental model to simulate disease spreading in the vicinity of airports. A modified Susceptible-Exposed-Infected-Recovered (SEIR) model to analyze the impact of the incubation period.} em{WATCH-Forcing-Data-ERA-Interim (WFDEI) climate data: temperature, specific humidity, surface air pressure, and water vapor pressure} These elements are implemented into a complex network. Nodes inside the network represent airports. Each single node is equipped with its own SIR/SEIR compartmental model with node specific attributes. Edges between those nodes represent direct flight connections that allow infected individuals to move between linked nodes. Therefore the interaction of the set of unique SIR models creates the model dynamics we will analyze. To better figure out the influence on climate change on disease spreading patterns, we focus on Influenza-like-Illnesses (ILI). The transmission rate of ILI has a dependency on climate parameters like humidity and temperature. Even small changes of environmental variables can trigger significant differences in the global outbreak behavior. Apart from the direct

Pattern Formation in Predator-Prey Model with Delay and Cross Diffusion

Directory of Open Access Journals (Sweden)

Xinze Lian

2013-01-01

Full Text Available We consider the effect of time delay and cross diffusion on the dynamics of a modified Leslie-Gower predator-prey model incorporating a prey refuge. Based on the stability analysis, we demonstrate that delayed feedback may generate Hopf and Turing instability under some conditions, resulting in spatial patterns. One of the most interesting findings is that the model exhibits complex pattern replication: the model dynamics exhibits a delay and diffusion controlled formation growth not only to spots, stripes, and holes, but also to spiral pattern self-replication. The results indicate that time delay and cross diffusion play important roles in pattern formation.

Memory and pattern storage in neural networks with activity dependent synapses

Science.gov (United States)

Mejias, J. F.; Torres, J. J.

2009-01-01

We present recently obtained results on the influence of the interplay between several activity dependent synaptic mechanisms, such as short-term depression and facilitation, on the maximum memory storage capacity in an attractor neural network [1]. In contrast with the case of synaptic depression, which drastically reduces the capacity of the network to store and retrieve activity patterns [2], synaptic facilitation is able to enhance the memory capacity in different situations. In particular, we find that a convenient balance between depression and facilitation can enhance the memory capacity, reaching maximal values similar to those obtained with static synapses, that is, without activity-dependent processes. We also argue, employing simple arguments, that this level of balance is compatible with experimental data recorded from some cortical areas, where depression and facilitation may play an important role for both memory-oriented tasks and information processing. We conclude that depressing synapses with a certain level of facilitation allow to recover the good retrieval properties of networks with static synapses while maintaining the nonlinear properties of dynamic synapses, convenient for information processing and coding.

Model-assisted template extraction SRAF application to contact holes patterns in high-end flash memory device fabrication

Science.gov (United States)

Seoud, Ahmed; Kim, Juhwan; Ma, Yuansheng; Jayaram, Srividya; Hong, Le; Chae, Gyu-Yeol; Lee, Jeong-Woo; Park, Dae-Jin; Yune, Hyoung-Soon; Oh, Se-Young; Park, Chan-Ha

2018-03-01

Sub-resolution assist feature (SRAF) insertion techniques have been effectively used for a long time now to increase process latitude in the lithography patterning process. Rule-based SRAF and model-based SRAF are complementary solutions, and each has its own benefits, depending on the objectives of applications and the criticality of the impact on manufacturing yield, efficiency, and productivity. Rule-based SRAF provides superior geometric output consistency and faster runtime performance, but the associated recipe development time can be of concern. Model-based SRAF provides better coverage for more complicated pattern structures in terms of shapes and sizes, with considerably less time required for recipe development, although consistency and performance may be impacted. In this paper, we introduce a new model-assisted template extraction (MATE) SRAF solution, which employs decision tree learning in a model-based solution to provide the benefits of both rule-based and model-based SRAF insertion approaches. The MATE solution is designed to automate the creation of rules/templates for SRAF insertion, and is based on the SRAF placement predicted by model-based solutions. The MATE SRAF recipe provides optimum lithographic quality in relation to various manufacturing aspects in a very short time, compared to traditional methods of rule optimization. Experiments were done using memory device pattern layouts to compare the MATE solution to existing model-based SRAF and pixelated SRAF approaches, based on lithographic process window quality, runtime performance, and geometric output consistency.

Multivariate Non-Symmetric Stochastic Models for Spatial Dependence Models

Science.gov (United States)

Haslauer, C. P.; Bárdossy, A.

2017-12-01

A copula based multivariate framework allows more flexibility to describe different kind of dependences than what is possible using models relying on the confining assumption of symmetric Gaussian models: different quantiles can be modelled with a different degree of dependence; it will be demonstrated how this can be expected given process understanding. maximum likelihood based multivariate quantitative parameter estimation yields stable and reliable results; not only improved results in cross-validation based measures of uncertainty are obtained but also a more realistic spatial structure of uncertainty compared to second order models of dependence; as much information as is available is included in the parameter estimation: incorporation of censored measurements (e.g., below detection limit, or ones that are above the sensitive range of the measurement device) yield to more realistic spatial models; the proportion of true zeros can be jointly estimated with and distinguished from censored measurements which allow estimates about the age of a contaminant in the system; secondary information (categorical and on the rational scale) has been used to improve the estimation of the primary variable; These copula based multivariate statistical techniques are demonstrated based on hydraulic conductivity observations at the Borden (Canada) site, the MADE site (USA), and a large regional groundwater quality data-set in south-west Germany. Fields of spatially distributed K were simulated with identical marginal simulation, identical second order spatial moments, yet substantially differing solute transport characteristics when numerical tracer tests were performed. A statistical methodology is shown that allows the delineation of a boundary layer separating homogenous parts of a spatial data-set. The effects of this boundary layer (macro structure) and the spatial dependence of K (micro structure) on solute transport behaviour is shown.

SIMULATING THE TIMESCALE-DEPENDENT COLOR VARIATION IN QUASARS WITH A REVISED INHOMOGENEOUS DISK MODEL

Energy Technology Data Exchange (ETDEWEB)

Cai, Zhen-Yi; Wang, Jun-Xian; Sun, Yu-Han; Wu, Mao-Chun; Huang, Xing-Xing; Chen, Xiao-Yang [CAS Key Laboratory for Researches in Galaxies and Cosmology, University of Science and Technology of China, Chinese Academy of Sciences, Hefei, Anhui 230026 (China); Gu, Wei-Min, E-mail: zcai@ustc.edu.cn, E-mail: jxw@ustc.edu.cn [Department of Astronomy and Institute of Theoretical Physics and Astrophysics, Xiamen University, Xiamen, Fujian 361005 (China)

2016-07-20

The UV–optical variability of active galactic nuclei and quasars is useful for understanding the physics of the accretion disk and is gradually being attributed to stochastic fluctuations over the accretion disk. Quasars generally appear bluer when they brighten in the UV–optical bands; the nature of this phenomenon remains controversial. Recently, Sun et al. discovered that the color variation of quasars is timescale-dependent, in the way that faster variations are even bluer than longer term ones. While this discovery can directly rule out models that simply attribute the color variation to contamination from the host galaxies, or to changes in the global accretion rates, it favors the stochastic disk fluctuation model as fluctuations in the inner-most hotter disk could dominate the short-term variations. In this work, we show that a revised inhomogeneous disk model, where the characteristic timescales of thermal fluctuations in the disk are radius-dependent (i.e., τ ∼ r ; based on that originally proposed by Dexter and Agol), can reproduce well a timescale-dependent color variation pattern, similar to the observed one and unaffected by the uneven sampling and photometric error. This demonstrates that one may statistically use variation emission at different timescales to spatially resolve the accretion disk in quasars, thus opening a new window with which to probe and test the accretion disk physics in the era of time domain astronomy. Caveats of the current model, which ought to be addressed in future simulations, are discussed.

Dynamic agglomeration patterns in a two-country new economic geography model with four regions

International Nuclear Information System (INIS)

Commendatore, Pasquale; Kubin, Ingrid; Mossay, Pascal; Sushko, Iryna

2015-01-01

We introduce a two-country New Economic Geography model with four regions. It is defined by a 2D piecewise smooth map that depends on 8 parameters. Using reductions of this map to 1D maps defined on invariant straight lines, we obtain stability conditions of the Core–Periphery fixed points, and show how such reductions can be used to describe basins of attraction of coexisting attractors. Typical bifurcation sequences obtained when varying some parameters are discussed. We find patterns that are much richer than those observed in standard NEG models: there are more types of fixed points including fixed points attracting in Milnor’s sense; their basins of attraction are quite complicated; and coexistence is pervasive.

A computational model of pattern separation efficiency in the dentate gyrus with implications in schizophrenia

Science.gov (United States)

Faghihi, Faramarz; Moustafa, Ahmed A.

2015-01-01

Information processing in the hippocampus begins by transferring spiking activity of the entorhinal cortex (EC) into the dentate gyrus (DG). Activity pattern in the EC is separated by the DG such that it plays an important role in hippocampal functions including memory. The structural and physiological parameters of these neural networks enable the hippocampus to be efficient in encoding a large number of inputs that animals receive and process in their life time. The neural encoding capacity of the DG depends on its single neurons encoding and pattern separation efficiency. In this study, encoding by the DG is modeled such that single neurons and pattern separation efficiency are measured using simulations of different parameter values. For this purpose, a probabilistic model of single neurons efficiency is presented to study the role of structural and physiological parameters. Known neurons number of the EC and the DG is used to construct a neural network by electrophysiological features of granule cells of the DG. Separated inputs as activated neurons in the EC with different firing probabilities are presented into the DG. For different connectivity rates between the EC and DG, pattern separation efficiency of the DG is measured. The results show that in the absence of feedback inhibition on the DG neurons, the DG demonstrates low separation efficiency and high firing frequency. Feedback inhibition can increase separation efficiency while resulting in very low single neuron’s encoding efficiency in the DG and very low firing frequency of neurons in the DG (sparse spiking). This work presents a mechanistic explanation for experimental observations in the hippocampus, in combination with theoretical measures. Moreover, the model predicts a critical role for impaired inhibitory neurons in schizophrenia where deficiency in pattern separation of the DG has been observed. PMID:25859189

A Computational Model of Pattern Separation Efficiency in the Dentate Gyrus with Implications in Schizophrenia

Directory of Open Access Journals (Sweden)

Faramarz eFaghihi

2015-03-01

Full Text Available Information processing in the hippocampus begins by transferring spiking activity of the Entorhinal Cortex (EC into the Dentate Gyrus (DG. Activity pattern in the EC is separated by the DG such that it plays an important role in hippocampal functions including memory. The structural and physiological parameters of these neural networks enable the hippocampus to be efficient in encoding a large number of inputs that animals receive and process in their life time. The neural encoding capacity of the DG depends on its single neurons encoding and pattern separation efficiency. In this study, encoding by the DG is modelled such that single neurons and pattern separation efficiency are measured using simulations of different parameter values. For this purpose, a probabilistic model of single neurons efficiency is presented to study the role of structural and physiological parameters. Known neurons number of the EC and the DG is used to construct a neural network by electrophysiological features of neuron in the DG. Separated inputs as activated neurons in the EC with different firing probabilities are presented into the DG. For different connectivity rates between the EC and DG, pattern separation efficiency of the DG is measured. The results show that in the absence of feedback inhibition on the DG neurons, the DG demonstrates low separation efficiency and high firing frequency. Feedback inhibition can increase separation efficiency while resulting in very low single neuron’s encoding efficiency in the DG and very low firing frequency of neurons in the DG (sparse spiking. This work presents a mechanistic explanation for experimental observations in the hippocampus, in combination with theoretical measures. Moreover, the model predicts a critical role for impaired inhibitory neurons in schizophrenia where deficiency in pattern separation of the DG has been observed.

Modelling dependable systems using hybrid Bayesian networks

International Nuclear Information System (INIS)

Neil, Martin; Tailor, Manesh; Marquez, David; Fenton, Norman; Hearty, Peter

2008-01-01

A hybrid Bayesian network (BN) is one that incorporates both discrete and continuous nodes. In our extensive applications of BNs for system dependability assessment, the models are invariably hybrid and the need for efficient and accurate computation is paramount. We apply a new iterative algorithm that efficiently combines dynamic discretisation with robust propagation algorithms on junction tree structures to perform inference in hybrid BNs. We illustrate its use in the field of dependability with two example of reliability estimation. Firstly we estimate the reliability of a simple single system and next we implement a hierarchical Bayesian model. In the hierarchical model we compute the reliability of two unknown subsystems from data collected on historically similar subsystems and then input the result into a reliability block model to compute system level reliability. We conclude that dynamic discretisation can be used as an alternative to analytical or Monte Carlo methods with high precision and can be applied to a wide range of dependability problems

Crossover patterning by the beam-film model: analysis and implications.

Directory of Open Access Journals (Sweden)

Liangran Zhang

2014-01-01

Full Text Available Crossing-over is a central feature of meiosis. Meiotic crossover (CO sites are spatially patterned along chromosomes. CO-designation at one position disfavors subsequent CO-designation(s nearby, as described by the classical phenomenon of CO interference. If multiple designations occur, COs tend to be evenly spaced. We have previously proposed a mechanical model by which CO patterning could occur. The central feature of a mechanical mechanism is that communication along the chromosomes, as required for CO interference, can occur by redistribution of mechanical stress. Here we further explore the nature of the beam-film model, its ability to quantitatively explain CO patterns in detail in several organisms, and its implications for three important patterning-related phenomena: CO homeostasis, the fact that the level of zero-CO bivalents can be low (the "obligatory CO", and the occurrence of non-interfering COs. Relationships to other models are discussed.

Model-driven dependability assessment of software systems

CERN Document Server

Bernardi, Simona; Petriu, Dorina C

2013-01-01

In this book, the authors present cutting-edge model-driven techniques for modeling and analysis of software dependability. Most of them are based on the use of UML as software specification language. From the software system specification point of view, such techniques exploit the standard extension mechanisms of UML (i.e., UML profiling). UML profiles enable software engineers to add non-functional properties to the software model, in addition to the functional ones. The authors detail the state of the art on UML profile proposals for dependability specification and rigorously describe the t

Risk attitudes in a changing environment: An evolutionary model of the fourfold pattern of risk preferences.

Science.gov (United States)

Mallpress, Dave E W; Fawcett, Tim W; Houston, Alasdair I; McNamara, John M

2015-04-01

A striking feature of human decision making is the fourfold pattern of risk attitudes, involving risk-averse behavior in situations of unlikely losses and likely gains, but risk-seeking behavior in response to likely losses and unlikely gains. Current theories to explain this pattern assume particular psychological processes to reproduce empirical observations, but do not address whether it is adaptive for the decision maker to respond to risk in this way. Here, drawing on insights from behavioral ecology, we build an evolutionary model of risk-sensitive behavior, to investigate whether particular types of environmental conditions could favor a fourfold pattern of risk attitudes. We consider an individual foraging in a changing environment, where energy is needed to prevent starvation and build up reserves for reproduction. The outcome, in terms of reproductive value (a rigorous measure of evolutionary success), of a one-off choice between a risky and a safe gain, or between a risky and a safe loss, determines the risk-sensitive behavior we should expect to see in this environment. Our results show that the fourfold pattern of risk attitudes may be adaptive in an environment in which conditions vary stochastically but are autocorrelated in time. In such an environment the current options provide information about the likely environmental conditions in the future, which affect the optimal pattern of risk sensitivity. Our model predicts that risk preferences should be both path dependent and affected by the decision maker's current state. (c) 2015 APA, all rights reserved).

Modeling of DNA damage-cluster, cell-cycle and repair pathway dependent radiosensitivity after low- and high-LET irradiation

International Nuclear Information System (INIS)

Guenther, Paul

2017-01-01

This work focuses on modeling of the effects of ionizing radiation on cells, primarily on, the influence of the DNA repair pathway availability and the radiation quality on the cell-survival probability. The availability of DNA repair pathways depends on the replication state and defects of the DNA repair pathways. The radiation quality manifests itself in the microscopic ionization pattern. The Giant LOop Binary LEsion (GLOBLE) model and the Local Effect Model (LEM) describe the cell-survival after photon and ion irradiation, respectively. Both models assume that cell survival can be modeled based on the spatial distribution of Double-Strand Breaks (DSB) of the DNA (damage pattern), within a higher order chromatin structure. Single DSB are referred to as isolated DSB (iDSB) and two or more DSB in close proximity (within 540 nm) are called complex DSB (cDSB). In order to predict the cell-survival, the GLOBLE-Model considers different iDSB repair-pathways and their availability. One central assumption of the LEM is that the same damage patterns imply same effects, regardless of the radiation quality. In order to predict the damage pattern the microscopic local dose distribution of ions, described by the amorphous track structure, is evaluated. The cell survival after ion irradiation is predicted from a comparison with corresponding damage patterns after photon irradiation. The cell-survival curves after high dose photon irradiation cannot be predicted from the Linear Quadratic (LQ) Model due to their transition towards a linear dose dependence. This work uses the GLOBLE-Model to introduce a novel mechanistic approach, which allows the threshold dose to be predicted for the transition from a linear quadratic dose dependence, of survival curves at low doses, to a linear dose dependence at high doses. Furthermore, a method is presented, which allows LEM to predict the survival of synchronous cells after ion irradiation based on the cell survival after photon

Turing patterns and long-time behavior in a three-species food-chain model

KAUST Repository

Parshad, Rana D.

2014-08-01

We consider a spatially explicit three-species food chain model, describing generalist top predator-specialist middle predator-prey dynamics. We investigate the long-time dynamics of the model and show the existence of a finite dimensional global attractor in the product space, L2(Ω). We perform linear stability analysis and show that the model exhibits the phenomenon of Turing instability, as well as diffusion induced chaos. Various Turing patterns such as stripe patterns, mesh patterns, spot patterns, labyrinth patterns and weaving patterns are obtained, via numerical simulations in 1d as well as in 2d. The Turing and non-Turing space, in terms of model parameters, is also explored. Finally, we use methods from nonlinear time series analysis to reconstruct a low dimensional chaotic attractor of the model, and estimate its fractal dimension. This provides a lower bound, for the fractal dimension of the attractor, of the spatially explicit model. © 2014 Elsevier Inc.

Pattern recognition techniques and neo-deterministic seismic hazard: Time dependent scenarios for North-Eastern Italy

International Nuclear Information System (INIS)

Peresan, A.; Vaccari, F.; Panza, G.F.; Zuccolo, E.; Gorshkov, A.

2009-05-01

An integrated neo-deterministic approach to seismic hazard assessment has been developed that combines different pattern recognition techniques, designed for the space-time identification of strong earthquakes, with algorithms for the realistic modeling of seismic ground motion. The integrated approach allows for a time dependent definition of the seismic input, through the routine updating of earthquake predictions. The scenarios of expected ground motion, associated with the alarmed areas, are defined by means of full waveform modeling. A set of neo-deterministic scenarios of ground motion is defined at regional and local scale, thus providing a prioritization tool for timely prevention and mitigation actions. Constraints about the space and time of occurrence of the impending strong earthquakes are provided by three formally defined and globally tested algorithms, which have been developed according to a pattern recognition scheme. Two algorithms, namely CN and M8, are routinely used for intermediate-term middle-range earthquake predictions, while a third algorithm allows for the identification of the areas prone to large events. These independent procedures have been combined to better constrain the alarmed area. The pattern recognition of earthquake-prone areas does not belong to the family of earthquake prediction algorithms since it does not provide any information about the time of occurrence of the expected earthquakes. Nevertheless, it can be considered as the term-less zero-approximation, which restrains the alerted areas (e.g. defined by CN or M8) to the more precise location of large events. Italy is the only region of moderate seismic activity where the two different prediction algorithms CN and M8S (i.e. a spatially stabilized variant of M8) are applied simultaneously and a real-time test of predictions, for earthquakes with magnitude larger than 5.4, is ongoing since 2003. The application of the CN to the Adriatic region (s.l.), which is relevant

Concentration-Dependent Patterns of Leucine Incorporation by Coastal Picoplankton

Science.gov (United States)

Alonso, Cecilia; Pernthaler, Jakob

2006-01-01

Coastal pelagic environments are believed to feature concentration gradients of dissolved organic carbon at a microscale, and they are characterized by pronounced seasonal differences in substrate availability for the heterotrophic picoplankton. Microbial taxa that coexist in such habitats might thus differ in their ability to incorporate substrates at various concentrations. We investigated the incorporation patterns of leucine in four microbial lineages from the coastal North Sea at concentrations between 0.1 and 100 nM before and during a spring phytoplankton bloom. Community bulk incorporation rates and the fraction of leucine-incorporating cells in the different populations were analyzed. Significantly fewer bacterial cells incorporated the amino acid before (13 to 35%) than during (23 to 47%) the bloom at all but the highest concentration. The incorporation rate per active cell in the prebloom situation was constant above 0.1 nM added leucine, whereas it increased steeply with substrate concentration during the bloom. At both time points, a high proportion of members of the Roseobacter clade incorporated leucine at all concentrations (55 to 80% and 86 to 94%, respectively). In contrast, the fractions of leucine-incorporating cells increased substantially with substrate availability in bacteria from the SAR86 clade (8 to 31%) and from DE cluster 2 of the Flavobacteria-Sphingobacteria (14 to 33%). The incorporation patterns of marine Euryarchaeota were between these extremes (30 to 56% and 48 to 70%, respectively). Our results suggest that the contribution of microbial taxa to the turnover of particular substrates may be concentration dependent. This may help us to understand the specific niches of coexisting populations that appear to compete for the same resources. PMID:16517664

Type-2 fuzzy graphical models for pattern recognition

CERN Document Server

Zeng, Jia

2015-01-01

This book discusses how to combine type-2 fuzzy sets and graphical models to solve a range of real-world pattern recognition problems such as speech recognition, handwritten Chinese character recognition, topic modeling as well as human action recognition. It covers these recent developments while also providing a comprehensive introduction to the fields of type-2 fuzzy sets and graphical models. Though primarily intended for graduate students, researchers and practitioners in fuzzy logic and pattern recognition, the book can also serve as a valuable reference work for researchers without any previous knowledge of these fields. Dr. Jia Zeng is a Professor at the School of Computer Science and Technology, Soochow University, China. Dr. Zhi-Qiang Liu is a Professor at the School of Creative Media, City University of Hong Kong, China.

Cellular automaton modeling of biological pattern formation characterization, examples, and analysis

CERN Document Server

Deutsch, Andreas

2017-01-01

This text explores the use of cellular automata in modeling pattern formation in biological systems. It describes several mathematical modeling approaches utilizing cellular automata that can be used to study the dynamics of interacting cell systems both in simulation and in practice. New in this edition are chapters covering cell migration, tissue development, and cancer dynamics, as well as updated references and new research topic suggestions that reflect the rapid development of the field. The book begins with an introduction to pattern-forming principles in biology and the various mathematical modeling techniques that can be used to analyze them. Cellular automaton models are then discussed in detail for different types of cellular processes and interactions, including random movement, cell migration, adhesive cell interaction, alignment and cellular swarming, growth processes, pigment cell pattern formation, tissue development, tumor growth and invasion, and Turing-type patterns and excitable media. In ...

Semantic concept-enriched dependence model for medical information retrieval.

Science.gov (United States)

Choi, Sungbin; Choi, Jinwook; Yoo, Sooyoung; Kim, Heechun; Lee, Youngho

2014-02-01

In medical information retrieval research, semantic resources have been mostly used by expanding the original query terms or estimating the concept importance weight. However, implicit term-dependency information contained in semantic concept terms has been overlooked or at least underused in most previous studies. In this study, we incorporate a semantic concept-based term-dependence feature into a formal retrieval model to improve its ranking performance. Standardized medical concept terms used by medical professionals were assumed to have implicit dependency within the same concept. We hypothesized that, by elaborately revising the ranking algorithms to favor documents that preserve those implicit dependencies, the ranking performance could be improved. The implicit dependence features are harvested from the original query using MetaMap. These semantic concept-based dependence features were incorporated into a semantic concept-enriched dependence model (SCDM). We designed four different variants of the model, with each variant having distinct characteristics in the feature formulation method. We performed leave-one-out cross validations on both a clinical document corpus (TREC Medical records track) and a medical literature corpus (OHSUMED), which are representative test collections in medical information retrieval research. Our semantic concept-enriched dependence model consistently outperformed other state-of-the-art retrieval methods. Analysis shows that the performance gain has occurred independently of the concept's explicit importance in the query. By capturing implicit knowledge with regard to the query term relationships and incorporating them into a ranking model, we could build a more robust and effective retrieval model, independent of the concept importance. Copyright © 2013 Elsevier Inc. All rights reserved.

Inventory Model for Non – Instantaneous Deteriorating Items, Stock Dependent Demand, Partial Backlogging, and Inflation over a Finite Time Horizon

Directory of Open Access Journals (Sweden)

Neeraj Kumar

2016-05-01

Full Text Available In the present study, the Economic Order Quantity (EOQ model of two-warehouse deals with non-instantaneous deteriorating items, the demand rate considered as stock dependent and model affected by inflation under the pattern of time value of money over a finite planning horizon. Shortages are allowed and partially backordered depending on the waiting time for the next replenishment. The main objective of this work is to minimize the total inventory cost and finding the optimal interval and the optimal order quantity. An algorithm is designed to find the optimum solution of the proposed model. Numerical examples are given to demonstrate the results. Also, the effect of changes in the different parameters on the optimal total cost is graphically presented.

Finite horizon EOQ model for non-instantaneous deteriorating items with price and advertisement dependent demand and partial backlogging under inflation

Science.gov (United States)

Palanivel, M.; Uthayakumar, R.

2015-07-01

This paper deals with an economic order quantity (EOQ) model for non-instantaneous deteriorating items with price and advertisement dependent demand pattern under the effect of inflation and time value of money over a finite planning horizon. In this model, shortages are allowed and partially backlogged. The backlogging rate is dependent on the waiting time for the next replenishment. This paper aids the retailer in minimising the total inventory cost by finding the optimal interval and the optimal order quantity. An algorithm is designed to find the optimum solution of the proposed model. Numerical examples are given to demonstrate the results. Also, the effect of changes in the different parameters on the optimal total cost is graphically presented and the implications are discussed in detail.

Modeling of the angular dependence of plasma etching

International Nuclear Information System (INIS)

Guo Wei; Sawin, Herbert H.

2009-01-01

An understanding of the angular dependence of etching yield is essential to investigate the origins of sidewall roughness during plasma etching. In this article the angular dependence of polysilicon etching in Cl 2 plasma was modeled as a combination of individual angular-dependent etching yields for ion-initiated processes including physical sputtering, ion-induced etching, vacancy generation, and removal. The modeled etching yield exhibited a maximum at ∼60 degree sign off-normal ion angle at low flux ratio, indicative of physical sputtering. It transformed to the angular dependence of ion-induced etching with the increase in the neutral-to-ion flux ratio. Good agreement between the modeling and the experiments was achieved for various flux ratios and ion energies. The variation of etching yield in response to the ion angle was incorporated in the three-dimensional profile simulation and qualitative agreement was obtained. The surface composition was calculated and compared to x-ray photoelectron spectroscopy (XPS) analysis. The modeling indicated a Cl areal density of 3x10 15 atoms/cm 2 on the surface that is close to the value determined by the XPS analysis. The response of Cl fraction to ion energy and flux ratio was modeled and correlated with the etching yields. The complete mixing-layer kinetics model with the angular dependence effect will be used for quantitative surface roughening analysis using a profile simulator in future work.

Dependency distance minimization in understanding of ambiguous structure. Comment on "Dependency distance: A new perspective on syntactic patterns in natural languages" by Haitao Liu et al.

Science.gov (United States)

Zhao, Yiyi

2017-07-01

Dependency Distance, proposed by Hudson [1], calculated by Liu [2,3], is an important concept in Dependency Theory. It can be used as a measure of the syntactic difficulty, and lots of research [2,4] have testified the universal of Dependency Distance in various languages. Human languages seem to present a preference for short dependency distance, which may be explained in terms of general cognitive constraint of limited working memory [5]. Psychological experiments in English, German, Russian and Chinese support the hypothesis that Dependency Distance minimization (DDM) make languages to evolve into some syntactic patterns to reduce memory burden [6-9]. The study of psychology focuses on the process and mechanism of syntactic structure selection in speech comprehension. In many speech comprehension experiments [10], ambiguous structure is an important experimental material.

Modeling dependencies in product families with COVAMOF

NARCIS (Netherlands)

Sinnema, Marco; Deelstra, Sybren; Nijhuis, Jos; Bosch, Jan; Riebisch, M; Tabeling, P; Zorn, W

2006-01-01

Many variability modeling approaches consider only formalized dependencies, i.e. in- or exclude relations between variants. However, in real industrial product families, dependencies are often much more complicated. In this paper, we discuss the product derivation problems associated with

Gait pattern recognition in cerebral palsy patients using neural network modelling

International Nuclear Information System (INIS)

Muhammad, J.; Gibbs, S.; Abboud, R.; Anand, S.

2015-01-01

Interpretation of gait data obtained from modern 3D gait analysis is a challenging and time consuming task. The aim of this study was to create neural network models which can recognise the gait patterns from pre- and post-treatment and the normal ones. Neural network is a method which works on the principle of learning from experience and then uses the obtained knowledge to predict the unknown. Methods: Twenty-eight patients with cerebral palsy were recruited as subjects whose gait was analysed in pre- and post-treatment. A group of twenty-six normal subjects also participated in this study as control group. All subjects gait was analysed using Vicon Nexus to obtain the gait parameters and kinetic and kinematic parameters of hip, knee and ankle joints in three planes of both limbs. The gait data was used as input to create neural network models. A total of approximately 300 trials were split into 70% and 30% to train and test the models, respectively. Different models were built using different parameters. The gait was categorised as three patterns, i.e., normal, pre- and post-treatments. Result: The results showed that the models using all parameters or using the joint angles and moments could predict the gait patterns with approximately 95% accuracy. Some of the models e.g., the models using joint power and moments, had lower rate in recognition of gait patterns with approximately 70-90% successful ratio. Conclusion: Neural network model can be used in clinical practice to recognise the gait pattern for cerebral palsy patients. (author)

Effects of early afterdepolarizations on excitation patterns in an accurate model of the human ventricles

Science.gov (United States)

Seemann, Gunnar; Panfilov, Alexander V.; Vandersickel, Nele

2017-01-01

Early Afterdepolarizations, EADs, are defined as the reversal of the action potential before completion of the repolarization phase, which can result in ectopic beats. However, the series of mechanisms of EADs leading to these ectopic beats and related cardiac arrhythmias are not well understood. Therefore, we aimed to investigate the influence of this single cell behavior on the whole heart level. For this study we used a modified version of the Ten Tusscher-Panfilov model of human ventricular cells (TP06) which we implemented in a 3D ventricle model including realistic fiber orientations. To increase the likelihood of EAD formation at the single cell level, we reduced the repolarization reserve (RR) by reducing the rapid delayed rectifier Potassium current and raising the L-type Calcium current. Varying these parameters defined a 2D parametric space where different excitation patterns could be classified. Depending on the initial conditions, by either exciting the ventricles with a spiral formation or burst pacing protocol, we found multiple different spatio-temporal excitation patterns. The spiral formation protocol resulted in the categorization of a stable spiral (S), a meandering spiral (MS), a spiral break-up regime (SB), spiral fibrillation type B (B), spiral fibrillation type A (A) and an oscillatory excitation type (O). The last three patterns are a 3D generalization of previously found patterns in 2D. First, the spiral fibrillation type B showed waves determined by a chaotic bi-excitable regime, i.e. mediated by both Sodium and Calcium waves at the same time and in same tissue settings. In the parameter region governed by the B pattern, single cells were able to repolarize completely and different (spiral) waves chaotically burst into each other without finishing a 360 degree rotation. Second, spiral fibrillation type A patterns consisted of multiple small rotating spirals. Single cells failed to repolarize to the resting membrane potential hence

Effects of Rhyme and Spelling Patterns on Auditory Word ERPs Depend on Selective Attention to Phonology

Science.gov (United States)

Yoncheva, Yuliya N.; Maurer, Urs; Zevin, Jason D.; McCandliss, Bruce D.

2013-01-01

ERP responses to spoken words are sensitive to both rhyming effects and effects of associated spelling patterns. Are such effects automatically elicited by spoken words or dependent on selectively attending to phonology? To address this question, ERP responses to spoken word pairs were investigated under two equally demanding listening tasks that…

A dependent stress-strength interference model based on mixed copula function

Energy Technology Data Exchange (ETDEWEB)

Gao, Jian Xiong; An, Zong Wen; Liu, Bo [School of Mechatronics Engineering, Lanzhou University of Technology, Lanzhou (China)

2016-10-15

In the traditional Stress-strength interference (SSI) model, stress and strength must satisfy the basic assumption of mutual independence. However, a complex dependence between stress and strength exists in practical engineering. To evaluate structural reliability under the case that stress and strength are dependent, a mixed copula function is introduced to a new dependent SSI model. This model can fully characterize the dependence between stress and strength. The residual square sum method and genetic algorithm are also used to estimate the unknown parameters of the model. Finally, the validity of the proposed model is demonstrated via a practical case. Results show that traditional SSI model ignoring the dependence between stress and strength more easily overestimates product reliability than the new dependent SSI model.

Modelling of Context: Designing Mobile Systems from Domain-Dependent Models

DEFF Research Database (Denmark)

Nielsen, Peter Axel; Stage, Jan

2009-01-01

Modelling of domain-dependent aspects is a key prerequisite for the design of software for mobile systems. Most mobile systems include a more or less advanced model of selected aspects of the domain in which they are used. This paper discusses the creation of such a model and its relevance for te...

Patterns in new dimensionless quantities containing melting temperature, and their dependence on pressure

Directory of Open Access Journals (Sweden)

U. WALZER

1980-06-01

Full Text Available The relationships existing between melting temperature and other
macroscopic physical quantities are investigated. A new dimensionless
quantity Q(1 not containing the Grtineisen parameter proves to be suited for serving in future studies as a tool for the determination of the melting temperature in the outer core of the Earth. The pressure dependence of more general dimensionless quantities Q„ is determined analytically and, for the chemical elements, numerically, too. The patterns of various interesting dimensionless quantities are shown in the Periodic Table and compared.

Patterning characteristics of a chemically-amplified negative resist in synchrotron radiation lithography

International Nuclear Information System (INIS)

Deguchi, Kimiyoshi; Miyoshi, Kazunori; Ishii, Tetsuyoshi; Matsuda, Tadahito

1992-01-01

To explore the applicability of synchrotron radiation X-ray lithography for fabricating sub-quartermicron devices, we investigate the patterning characteristics of the chemically-amplified negative resist SAL601-ER7. Since these characteristics depend strongly on the conditions of the chemical amplification process, the effects of post-exposure baking and developing conditions on sensitivity and resolution are examined. The resolution-limiting factors are investigated, revealing that pattern collapse during the development process and fog caused by Fresnel diffraction, photo-electron scattering, and acid diffusion in the resist determine the resolution and the maximum aspect ratio of the lines and spaces pattern. Using the model of a swaying beam supported at one end, it is shown that pattern collapse depends on the resist pattern's flexural stiffness. Patterning stability, which depends on the delay time between exposure and baking, is also discussed. (author)

Input dependent cell assembly dynamics in a model of the striatal medium spiny neuron network

Directory of Open Access Journals (Sweden)

Adam ePonzi

2012-03-01

Full Text Available The striatal medium spiny neuron (MSNs network is sparsely connected with fairly weak GABAergic collaterals receiving an excitatory glutamatergic cortical projection. Peri stimulus time histograms (PSTH of MSN population response investigated in various experimental studies display strong firing rate modulations distributed throughout behavioural task epochs. In previous work we have shown by numerical simulation that sparse random networks of inhibitory spiking neurons with characteristics appropriate for UP state MSNs form cell assemblies which fire together coherently in sequences on long behaviourally relevant timescales when the network receives a fixed pattern of constant input excitation. Here we first extend that model to the case where cortical excitation is composed of many independent noisy Poisson processes and demonstrate that cell assembly dynamics is still observed when the input is sufficiently weak. However if cortical excitation strength is increased more regularly firing and completely quiescent cells are found, which depend on the cortical stimulation. Subsequently we further extend previous work to consider what happens when the excitatory input varies as it would in when the animal is engaged in behavior. We investigate how sudden switches in excitation interact with network generated patterned activity. We show that sequences of cell assembly activations can be locked to the excitatory input sequence and delineate the range of parameters where this behaviour is shown. Model cell population PSTH display both stimulus and temporal specificity, with large population firing rate modulations locked to elapsed time from task events. Thus the random network can generate a large diversity of temporally evolving stimulus dependent responses even though the input is fixed between switches. We suggest the MSN network is well suited to the generation of such slow coherent task dependent response

Input dependent cell assembly dynamics in a model of the striatal medium spiny neuron network.

Science.gov (United States)

Ponzi, Adam; Wickens, Jeff

2012-01-01

The striatal medium spiny neuron (MSN) network is sparsely connected with fairly weak GABAergic collaterals receiving an excitatory glutamatergic cortical projection. Peri-stimulus time histograms (PSTH) of MSN population response investigated in various experimental studies display strong firing rate modulations distributed throughout behavioral task epochs. In previous work we have shown by numerical simulation that sparse random networks of inhibitory spiking neurons with characteristics appropriate for UP state MSNs form cell assemblies which fire together coherently in sequences on long behaviorally relevant timescales when the network receives a fixed pattern of constant input excitation. Here we first extend that model to the case where cortical excitation is composed of many independent noisy Poisson processes and demonstrate that cell assembly dynamics is still observed when the input is sufficiently weak. However if cortical excitation strength is increased more regularly firing and completely quiescent cells are found, which depend on the cortical stimulation. Subsequently we further extend previous work to consider what happens when the excitatory input varies as it would when the animal is engaged in behavior. We investigate how sudden switches in excitation interact with network generated patterned activity. We show that sequences of cell assembly activations can be locked to the excitatory input sequence and outline the range of parameters where this behavior is shown. Model cell population PSTH display both stimulus and temporal specificity, with large population firing rate modulations locked to elapsed time from task events. Thus the random network can generate a large diversity of temporally evolving stimulus dependent responses even though the input is fixed between switches. We suggest the MSN network is well suited to the generation of such slow coherent task dependent response which could be utilized by the animal in behavior.

The Uses and Dependency Model of Mass Communication.

Science.gov (United States)

Rubin, Alan M.; Windahl, Sven

1986-01-01

Responds to criticism of the uses and gratification model by proposing a modified model integrating the dependency perspective. Suggests that this integrated model broadens the heuristic application of the earlier model. (MS)

Automobile dependence in cities: An international comparison of urban transport and land use patterns with implications for sustainability

International Nuclear Information System (INIS)

Kenworthy, J.R.; Laube, F.B.

1996-01-01

Cities around the world are subject to increasing levels of environmental impact from dependence on the automobile. In the highly auto-dependent cities of the US and Australia, this is manifested in problems such as urban sprawl and its destruction of prime farming land and natural landscapes, photochemical smog that can be primarily attributed to auto emissions. On top of the more local impacts of the automobile, the global dimension should not be forgotten. Perhaps the two most pressing issues in this regard are the oil problem and the greenhouse problem. A comparison of global cities over the period 1980 to 1990 reveals large differences in automobile dependence with implications for the future sustainability of cities in different countries. This study explores some of the underlying land use, transport, and economic reasons for these different transport patterns. It briefly reviews what the sustainability agenda means for transport and land use patterns in cities and suggests a suite of targets or goals for sustainability by which cities might measure their current directions and plans

The pattern of eigenfrequencies of radial overtones which is predicted for a specified Earth-model

Directory of Open Access Journals (Sweden)

E. R. LAPWOOD

1977-06-01

Full Text Available In 1974 Anderssen and Cleary examined the distribution of eigenfrequencies
of radial overtones in torsional oscillations of Earth-models.
They pointed out that according to Sturm-Liouville theory this distribution
should approach asymptotically, for large overtone number m,
the value nnz/y, where y is the time taken by a shear-wave to travel
along a radius from the core-mantle interface to the surface, provided
elastic parameters vary continuously along the radius. They found that,
for all the models which they considered, the distributions of eigenfrequencies
deviated from the asymptote by amounts which depended on
the existence and size of internal discontinuities. Lapwood (1975 showed
that such deviations were to be expected from Sturm-Liouville theory,
and McNabb, Anderssen and Lapwood (1976 extended Sturm-Liouville
theory to apply to differential equations with discontinuous coefficients.
Anderssen (1977 used their results to show how to predict the pattern
of deviations —called by McNabb et al. the solotone effect— for a
given discontinuity in an Earth-model.
Recently Sato and Lapwood (1977, in a series of papers which will
be referred to here simply as I, II, III, have explored the solotone effect
for layered spherical shells, using approximations derived from an exacttheory which holds for uniform layering. They have shown how the
form of the pattern of eigenfrequencies, which is the graph of
S — YMUJI/N — m against m, where ,„CJI is the frequency of the m"'
overtone in the I"' (Legendre mode of torsional oscillation, is determined
as to periodicity (or quasi-periodicity by the thicknesses and velocities
of the layers, and as to amplitude by the amounts of the discontinuities
(III. The pattern of eigenfrequencies proves to be extremely sensitive
to small changes in layer-thicknesses in a model.
In

Actual building energy use patterns and their implications for predictive modeling

International Nuclear Information System (INIS)

Heidarinejad, Mohammad; Cedeño-Laurent, Jose G.; Wentz, Joshua R.; Rekstad, Nicholas M.; Spengler, John D.; Srebric, Jelena

2017-01-01

Highlights: • Developed three building categories based on energy use patterns of campus buildings. • Evaluated implication of temporal energy data granularity on predictive modeling. • Demonstrated importance of monitoring daily chilled water consumption. • Identified interval electricity data as an indicator of building operation schedules. • Demonstrated a calibration process for energy modeling of a campus building. - Abstract: The main goal of this study is to understand the patterns in which commercial buildings consume energy, rather than evaluating building energy use based on aggregate utility bills typically linked to building principal tenant activity or occupancy type. The energy consumption patterns define buildings as externally-load, internally-load, or mixed-load dominated buildings. Penn State and Harvard campuses serve as case studies for this particular research project. The buildings in these two campuses use steam, chilled water, and electricity as energy commodities and maintain databases of different resolutions to include minute, hourly, daily, and monthly data instances depending on the commodity and available data acquisition system. The results of this study show monthly steam consumption directly correlates to outdoor environmental conditions for 88% of the studied buildings, while chilled water consumption has negligible correlation to the outdoor environmental conditions. Thus, in terms of monthly chilled water consumption, 86% of buildings are internally-load and mixed-load dominated, respectively. Chilled water consumption is better suited for the daily analyses compared to the monthly and hourly analyses. While the influence of building operation schedules affects the analyses at the hourly level, the monthly chilled water consumptions are not good indicators of the building energy consumption patterns. Electricity consumption at the monthly (or seasonal) level can support the building energy simulation tools for the

From lag synchronization to pattern formation in one-dimensional open flow models

International Nuclear Information System (INIS)

Liu Zengrong; Luo Jigui

2006-01-01

In this paper, the relation between synchronization and pattern formation in one-dimensional discrete and continuous open flow models is investigated in detail. Firstly a sufficient condition for globally asymptotical stability of lag/anticipating synchronization among lattices of these models is proved by analytic method. Then, by analyzing and simulating lag/anticipating synchronization in discrete case, three kinds of pattern of wave (it is called wave pattern) travelling in the lattices are discovered. Finally, a proper definition for these kinds of pattern is proposed

Long-time integration methods for mesoscopic models of pattern-forming systems

International Nuclear Information System (INIS)

Abukhdeir, Nasser Mohieddin; Vlachos, Dionisios G.; Katsoulakis, Markos; Plexousakis, Michael

2011-01-01

Spectral methods for simulation of a mesoscopic diffusion model of surface pattern formation are evaluated for long simulation times. Backwards-differencing time-integration, coupled with an underlying Newton-Krylov nonlinear solver (SUNDIALS-CVODE), is found to substantially accelerate simulations, without the typical requirement of preconditioning. Quasi-equilibrium simulations of patterned phases predicted by the model are shown to agree well with linear stability analysis. Simulation results of the effect of repulsive particle-particle interactions on pattern relaxation time and short/long-range order are discussed.

Dependence in probabilistic modeling Dempster-Shafer theory and probability bounds analysis

Energy Technology Data Exchange (ETDEWEB)

Ferson, Scott [Applied Biomathematics, Setauket, NY (United States); Nelsen, Roger B. [Lewis & Clark College, Portland OR (United States); Hajagos, Janos [Applied Biomathematics, Setauket, NY (United States); Berleant, Daniel J. [Iowa State Univ., Ames, IA (United States); Zhang, Jianzhong [Iowa State Univ., Ames, IA (United States); Tucker, W. Troy [Applied Biomathematics, Setauket, NY (United States); Ginzburg, Lev R. [Applied Biomathematics, Setauket, NY (United States); Oberkampf, William L. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

2015-05-01

This report summarizes methods to incorporate information (or lack of information) about inter-variable dependence into risk assessments that use Dempster-Shafer theory or probability bounds analysis to address epistemic and aleatory uncertainty. The report reviews techniques for simulating correlated variates for a given correlation measure and dependence model, computation of bounds on distribution functions under a specified dependence model, formulation of parametric and empirical dependence models, and bounding approaches that can be used when information about the intervariable dependence is incomplete. The report also reviews several of the most pervasive and dangerous myths among risk analysts about dependence in probabilistic models.

Modeling urbanization patterns at a global scale with generative adversarial networks

Science.gov (United States)

Albert, A. T.; Strano, E.; Gonzalez, M.

2017-12-01

Current demographic projections show that, in the next 30 years, global population growth will mostly take place in developing countries. Coupled with a decrease in density, such population growth could potentially double the land occupied by settlements by 2050. The lack of reliable and globally consistent socio-demographic data, coupled with the limited predictive performance underlying traditional urban spatial explicit models, call for developing better predictive methods, calibrated using a globally-consistent dataset. Thus, richer models of the spatial interplay between the urban built-up land, population distribution and energy use are central to the discussion around the expansion and development of cities, and their impact on the environment in the context of a changing climate. In this talk we discuss methods for, and present an analysis of, urban form, defined as the spatial distribution of macroeconomic quantities that characterize a city, using modern machine learning methods and best-available remote-sensing data for the world's largest 25,000 cities. We first show that these cities may be described by a small set of patterns in radial building density, nighttime luminosity, and population density, which highlight, to first order, differences in development and land use across the world. We observe significant, spatially-dependent variance around these typical patterns, which would be difficult to model using traditional statistical methods. We take a first step in addressing this challenge by developing CityGAN, a conditional generative adversarial network model for simulating realistic urban forms. To guide learning and measure the quality of the simulated synthetic cities, we develop a specialized loss function for GAN optimization that incorporates standard spatial statistics used by urban analysis experts. Our framework is a stark departure from both the standard physics-based approaches in the literature (that view urban forms as fractals with a

Simulating pattern-process relationships to validate landscape genetic models

Science.gov (United States)

A. J. Shirk; S. A. Cushman; E. L. Landguth

2012-01-01

Landscapes may resist gene flow and thereby give rise to a pattern of genetic isolation within a population. The mechanism by which a landscape resists gene flow can be inferred by evaluating the relationship between landscape models and an observed pattern of genetic isolation. This approach risks false inferences because researchers can never feasibly test all...

Excitation block in a nerve fibre model owing to potassium-dependent changes in myelin resistance.

Science.gov (United States)

Brazhe, A R; Maksimov, G V; Mosekilde, E; Sosnovtseva, O V

2011-02-06

The myelinated nerve fibre is formed by an axon and Schwann cells or oligodendrocytes that sheath the axon by winding around it in tight myelin layers. Repetitive stimulation of a fibre is known to result in accumulation of extracellular potassium ions, especially between the axon and the myelin. Uptake of potassium leads to Schwann cell swelling and myelin restructuring that impacts the electrical properties of the myelin. In order to further understand the dynamic interaction that takes place between the myelin and the axon, we have modelled submyelin potassium accumulation and related changes in myelin resistance during prolonged high-frequency stimulation. We predict that potassium-mediated decrease in myelin resistance leads to a functional excitation block with various patterns of altered spike trains. The patterns are found to depend on stimulation frequency and amplitude and to range from no block (less than 100 Hz) to a complete block (greater than 500 Hz). The transitional patterns include intermittent periodic block with interleaved spiking and non-spiking intervals of different relative duration as well as an unstable regime with chaotic switching between the spiking and non-spiking states. Intermittent conduction blocks are accompanied by oscillations of extracellular potassium. The mechanism of conductance block based on myelin restructuring complements the already known and modelled block via hyperpolarization mediated by the axonal sodium pump and potassium depolarization.

Use of fugacity model to analyze temperature-dependent removal of micro-contaminants in sewage treatment plants.

Science.gov (United States)

Thompson, Kelly; Zhang, Jianying; Zhang, Chunlong

2011-08-01

Effluents from sewage treatment plants (STPs) are known to contain residual micro-contaminants including endocrine disrupting chemicals (EDCs) despite the utilization of various removal processes. Temperature alters the efficacy of removal processes; however, experimental measurements of EDC removal at various temperatures are limited. Extrapolation of EDC behavior over a wide temperature range is possible using available physicochemical property data followed by the correction of temperature dependency. A level II fugacity-based STP model was employed by inputting parameters obtained from the literature and estimated by the US EPA's Estimations Programs Interface (EPI) including EPI's BIOWIN for temperature-dependent biodegradation half-lives. EDC removals in a three-stage activated sludge system were modeled under various temperatures and hydraulic retention times (HRTs) for representative compounds of various properties. Sensitivity analysis indicates that temperature plays a significant role in the model outcomes. Increasing temperature considerably enhances the removal of β-estradiol, ethinyestradiol, bisphenol, phenol, and tetrachloroethylene, but not testosterone with the highest biodegradation rate. The shortcomings of BIOWIN were mitigated by the correction of highly temperature-dependent biodegradation rates using the Arrhenius equation. The model predicts well the effects of operating temperature and HRTs on the removal via volatilization, adsorption, and biodegradation. The model also reveals that an impractically long HRT is needed to achieve a high EDC removal. The STP model along with temperature corrections is able to provide some useful insight into the different patterns of STP performance, and useful operational considerations relevant to EDC removal at winter low temperatures. Copyright © 2011 Elsevier Ltd. All rights reserved.

Characterization of Models for Time-Dependent Behavior of Soils

DEFF Research Database (Denmark)

Liingaard, Morten; Augustesen, Anders; Lade, Poul V.

2004-01-01

  Different classes of constitutive models have been developed to capture the time-dependent viscous phenomena ~ creep, stress relaxation, and rate effects ! observed in soils. Models based on empirical, rheological, and general stress-strain-time concepts have been studied. The first part....... Special attention is paid to elastoviscoplastic models that combine inviscid elastic and time-dependent plastic behavior. Various general elastoviscoplastic models can roughly be divided into two categories: Models based on the concept of overstress and models based on nonstationary flow surface theory...

Detecting consistent patterns of directional adaptation using differential selection codon models.

Science.gov (United States)

Parto, Sahar; Lartillot, Nicolas

2017-06-23

Phylogenetic codon models are often used to characterize the selective regimes acting on protein-coding sequences. Recent methodological developments have led to models explicitly accounting for the interplay between mutation and selection, by modeling the amino acid fitness landscape along the sequence. However, thus far, most of these models have assumed that the fitness landscape is constant over time. Fluctuations of the fitness landscape may often be random or depend on complex and unknown factors. However, some organisms may be subject to systematic changes in selective pressure, resulting in reproducible molecular adaptations across independent lineages subject to similar conditions. Here, we introduce a codon-based differential selection model, which aims to detect and quantify the fine-grained consistent patterns of adaptation at the protein-coding level, as a function of external conditions experienced by the organism under investigation. The model parameterizes the global mutational pressure, as well as the site- and condition-specific amino acid selective preferences. This phylogenetic model is implemented in a Bayesian MCMC framework. After validation with simulations, we applied our method to a dataset of HIV sequences from patients with known HLA genetic background. Our differential selection model detects and characterizes differentially selected coding positions specifically associated with two different HLA alleles. Our differential selection model is able to identify consistent molecular adaptations as a function of repeated changes in the environment of the organism. These models can be applied to many other problems, ranging from viral adaptation to evolution of life-history strategies in plants or animals.

Spatial pattern of diarrhea based on regional economic and environment by spatial autoregressive model

Science.gov (United States)

Bekti, Rokhana Dwi; Nurhadiyanti, Gita; Irwansyah, Edy

2014-10-01

The diarrhea case pattern information, especially for toddler, is very important. It is used to show the distribution of diarrhea in every region, relationship among that locations, and regional economic characteristic or environmental behavior. So, this research uses spatial pattern to perform them. This method includes: Moran's I, Spatial Autoregressive Models (SAR), and Local Indicator of Spatial Autocorrelation (LISA). It uses sample from 23 sub districts of Bekasi Regency, West Java, Indonesia. Diarrhea case, regional economic, and environmental behavior of households have a spatial relationship among sub district. SAR shows that the percentage of Regional Gross Domestic Product is significantly effect on diarrhea at α = 10%. Therefore illiteracy and health center facilities are significant at α = 5%. With LISA test, sub districts in southern Bekasi have high dependencies with Cikarang Selatan, Serang Baru, and Setu. This research also builds development application that is based on java and R to support data analysis.

An Evaluation of ADLs on Modeling Patterns for Software Architecture

NARCIS (Netherlands)

Waqas Kamal, Ahmad; Avgeriou, Paris

2007-01-01

Architecture patterns provide solutions to recurring design problems at the architecture level. In order to model patterns during software architecture design, one may use a number of existing Architecture Description Languages (ADLs), including the UML, a generic language but also a de facto

Mixed models, linear dependency, and identification in age-period-cohort models.

Science.gov (United States)

O'Brien, Robert M

2017-07-20

This paper examines the identification problem in age-period-cohort models that use either linear or categorically coded ages, periods, and cohorts or combinations of these parameterizations. These models are not identified using the traditional fixed effect regression model approach because of a linear dependency between the ages, periods, and cohorts. However, these models can be identified if the researcher introduces a single just identifying constraint on the model coefficients. The problem with such constraints is that the results can differ substantially depending on the constraint chosen. Somewhat surprisingly, age-period-cohort models that specify one or more of ages and/or periods and/or cohorts as random effects are identified. This is the case without introducing an additional constraint. I label this identification as statistical model identification and show how statistical model identification comes about in mixed models and why which effects are treated as fixed and which are treated as random can substantially change the estimates of the age, period, and cohort effects. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

Modelling comonotonic group-life under dependent decrement causes

OpenAIRE

Wang, Dabuxilatu

2011-01-01

Comonotonicity had been a extreme case of dependency between random variables. This article consider an extension of single life model under multiple dependent decrement causes to the case of comonotonic group-life.

Temperature Dependent Models of Semiconductor Devices for ...

African Journals Online (AJOL)

The paper presents an investigation of the temperature dependent model of a diode and bipolar transistor built-in to the NAP-2 program and comparison of these models with experimentally measured characteristics of the BA 100 diode and BC 109 transistor. The detail of the modelling technique has been discussed and ...

Regularization dependence on phase diagram in Nambu–Jona-Lasinio model

International Nuclear Information System (INIS)

Kohyama, H.; Kimura, D.; Inagaki, T.

2015-01-01

We study the regularization dependence on meson properties and the phase diagram of quark matter by using the two flavor Nambu–Jona-Lasinio model. The model also has the parameter dependence in each regularization, so we explicitly give the model parameters for some sets of the input observables, then investigate its effect on the phase diagram. We find that the location or the existence of the critical end point highly depends on the regularization methods and the model parameters. Then we think that regularization and parameters are carefully considered when one investigates the QCD critical end point in the effective model studies

Pattern-based approach for logical traffic isolation forensic modelling

CSIR Research Space (South Africa)

Dlamini, I

2009-08-01

Full Text Available reusability and flexibility of the LTI model. This model is viewed as a three-tier architecture, which for experimental purposes is composed of the following components: traffic generator, DiffServ network and the sink server. The Mediator pattern is used...

A Physics-Inspired Mechanistic Model of Migratory Movement Patterns in Birds.

Science.gov (United States)

Revell, Christopher; Somveille, Marius

2017-08-29

In this paper, we introduce a mechanistic model of migratory movement patterns in birds, inspired by ideas and methods from physics. Previous studies have shed light on the factors influencing bird migration but have mainly relied on statistical correlative analysis of tracking data. Our novel method offers a bottom up explanation of population-level migratory movement patterns. It differs from previous mechanistic models of animal migration and enables predictions of pathways and destinations from a given starting location. We define an environmental potential landscape from environmental data and simulate bird movement within this landscape based on simple decision rules drawn from statistical mechanics. We explore the capacity of the model by qualitatively comparing simulation results to the non-breeding migration patterns of a seabird species, the Black-browed Albatross (Thalassarche melanophris). This minimal, two-parameter model was able to capture remarkably well the previously documented migration patterns of the Black-browed Albatross, with the best combination of parameter values conserved across multiple geographically separate populations. Our physics-inspired mechanistic model could be applied to other bird and highly-mobile species, improving our understanding of the relative importance of various factors driving migration and making predictions that could be useful for conservation.

General Business Model Patterns for Local Energy Management Concepts

International Nuclear Information System (INIS)

Facchinetti, Emanuele; Sulzer, Sabine

2016-01-01

The transition toward a more sustainable global energy system, significantly relying on renewable energies and decentralized energy systems, requires a deep reorganization of the energy sector. The way how energy services are generated, delivered, and traded is expected to be very different in the coming years. Business model innovation is recognized as a key driver for the successful implementation of the energy turnaround. This work contributes to this topic by introducing a heuristic methodology easing the identification of general business model patterns best suited for Local Energy Management concepts such as Energy Hubs. A conceptual framework characterizing the Local Energy Management business model solution space is developed. Three reference business model patterns providing orientation across the defined solution space are identified, analyzed, and compared. Through a market review, a number of successfully implemented innovative business models have been analyzed and allocated within the defined solution space. The outcomes of this work offer to potential stakeholders a starting point and guidelines for the business model innovation process, as well as insights for policy makers on challenges and opportunities related to Local Energy Management concepts.

General Business Model Patterns for Local Energy Management Concepts

Energy Technology Data Exchange (ETDEWEB)

Facchinetti, Emanuele, E-mail: emanuele.facchinetti@hslu.ch; Sulzer, Sabine [Lucerne Competence Center for Energy Research, Lucerne University of Applied Science and Arts, Horw (Switzerland)

2016-03-03

The transition toward a more sustainable global energy system, significantly relying on renewable energies and decentralized energy systems, requires a deep reorganization of the energy sector. The way how energy services are generated, delivered, and traded is expected to be very different in the coming years. Business model innovation is recognized as a key driver for the successful implementation of the energy turnaround. This work contributes to this topic by introducing a heuristic methodology easing the identification of general business model patterns best suited for Local Energy Management concepts such as Energy Hubs. A conceptual framework characterizing the Local Energy Management business model solution space is developed. Three reference business model patterns providing orientation across the defined solution space are identified, analyzed, and compared. Through a market review, a number of successfully implemented innovative business models have been analyzed and allocated within the defined solution space. The outcomes of this work offer to potential stakeholders a starting point and guidelines for the business model innovation process, as well as insights for policy makers on challenges and opportunities related to Local Energy Management concepts.

Analyzing Unsaturated Flow Patterns in Fractured Rock Using an Integrated Modeling Approach

International Nuclear Information System (INIS)

Y.S. Wu; G. Lu; K. Zhang; L. Pan; G.S. Bodvarsson

2006-01-01

Characterizing percolation patterns in unsaturated fractured rock has posed a greater challenge to modeling investigations than comparable saturated zone studies, because of the heterogeneous nature of unsaturated media and the great number of variables impacting unsaturated flow. This paper presents an integrated modeling methodology for quantitatively characterizing percolation patterns in the unsaturated zone of Yucca Mountain, Nevada, a proposed underground repository site for storing high-level radioactive waste. The modeling approach integrates a wide variety of moisture, pneumatic, thermal, and isotopic geochemical field data into a comprehensive three-dimensional numerical model for modeling analyses. It takes into account the coupled processes of fluid and heat flow and chemical isotopic transport in Yucca Mountain's highly heterogeneous, unsaturated fractured tuffs. Modeling results are examined against different types of field-measured data and then used to evaluate different hydrogeological conceptualizations and their results of flow patterns in the unsaturated zone. In particular, this model provides a much clearer understanding of percolation patterns and flow behavior through the unsaturated zone, both crucial issues in assessing repository performance. The integrated approach for quantifying Yucca Mountain's flow system is demonstrated to provide a practical modeling tool for characterizing flow and transport processes in complex subsurface systems

Mapping vegetation patterns in arable land using the models STICS and DAISY

Science.gov (United States)

Heuer, Antje; Casper, Markus

2010-05-01

Several statistical methods exist to detect spatial and / or temporal variability with regard to ecological data-analysis: Semivariance-analysis, Trend surface analysis, Kriging, Voronoi polygons, Moran's I and Mantel-test, to mention just some of them. In this contribution, we concentrate on spatial vegetation patterns within the soil-vegetation-atmosphere (SVAT) system. Using variography, spatial analysis with a geographic information system and self-organizing maps, spatial patterns of yield have been isolated in an agro-ecosystem (see poster contribution EGU 2009, EGU2009-8948). Data were derived from two agricultural plots, each about 5 hectare, in the area of Newel, located in Western Palatinate, Germany. The plots have been conventionally cultivated with a crop rotation of winter rape, winter wheat and spring barley. The aim of the present study is to find out if the existing natural spatial patterns can be mapped by means of SVAT models. If so, the discretization of a landscape according to its spatial patterns could be the basis for parameterization of SVAT models in order to model soil-vegetation-atmosphere interaction over a large area, that is for up-scaling. For this purpose the SVAT models STICS (developed by INRA, France) and DAISY (developed at Tåstrup University, Denmark) are applied. After a wide sensitivity analysis both models are parameterized with field data according to the given situation of each of the detected spatial patterns. The results of the simulation per representative location of a pattern are validated first with field data concerning yield, soil water content and soil nitrogen; besides, above ground dry matter, root depth and specific stress indices are used for validation. The conclusions that can be made with regard to up-scaling are discussed in detail. In a second step the results of the STICS model are compared with those of the DAISY model to analyse the models' behaviour, to get further knowledge about the inner structure

Dependence of two-proton radioactivity on nuclear pairing models

Science.gov (United States)

Oishi, Tomohiro; Kortelainen, Markus; Pastore, Alessandro

2017-10-01

Sensitivity of two-proton emitting decay to nuclear pairing correlation is discussed within a time-dependent three-body model. We focus on the 6Be nucleus assuming α +p +p configuration, and its decay process is described as a time evolution of the three-body resonance state. For a proton-proton subsystem, a schematic density-dependent contact (SDDC) pairing model is employed. From the time-dependent calculation, we observed the exponential decay rule of a two-proton emission. It is shown that the density dependence does not play a major role in determining the decay width, which can be controlled only by the asymptotic strength of the pairing interaction. This asymptotic pairing sensitivity can be understood in terms of the dynamics of the wave function driven by the three-body Hamiltonian, by monitoring the time-dependent density distribution. With this simple SDDC pairing model, there remains an impossible trinity problem: it cannot simultaneously reproduce the empirical Q value, decay width, and the nucleon-nucleon scattering length. This problem suggests that a further sophistication of the theoretical pairing model is necessary, utilizing the two-proton radioactivity data as the reference quantities.

Variance-based sensitivity indices for models with dependent inputs

International Nuclear Information System (INIS)

Mara, Thierry A.; Tarantola, Stefano

2012-01-01

Computational models are intensively used in engineering for risk analysis or prediction of future outcomes. Uncertainty and sensitivity analyses are of great help in these purposes. Although several methods exist to perform variance-based sensitivity analysis of model output with independent inputs only a few are proposed in the literature in the case of dependent inputs. This is explained by the fact that the theoretical framework for the independent case is set and a univocal set of variance-based sensitivity indices is defined. In the present work, we propose a set of variance-based sensitivity indices to perform sensitivity analysis of models with dependent inputs. These measures allow us to distinguish between the mutual dependent contribution and the independent contribution of an input to the model response variance. Their definition relies on a specific orthogonalisation of the inputs and ANOVA-representations of the model output. In the applications, we show the interest of the new sensitivity indices for model simplification setting. - Highlights: ► Uncertainty and sensitivity analyses are of great help in engineering. ► Several methods exist to perform variance-based sensitivity analysis of model output with independent inputs. ► We define a set of variance-based sensitivity indices for models with dependent inputs. ► Inputs mutual contributions are distinguished from their independent contributions. ► Analytical and computational tests are performed and discussed.

Testing a Conceptual Model of Working through Self-Defeating Patterns

Science.gov (United States)

Wei, Meifen; Ku, Tsun-Yao

2007-01-01

The present study developed and examined a conceptual model of working through self-defeating patterns. Participants were 390 college students at a large midwestern university. Results indicated that self-defeating patterns mediated the relations between attachment and distress. Also, self-esteem mediated the link between self-defeating patterns…

Characterization of free breathing patterns with 5D lung motion model

Energy Technology Data Exchange (ETDEWEB)

Zhao Tianyu; Lu Wei; Yang Deshan; Mutic, Sasa; Noel, Camille E.; Parikh, Parag J.; Bradley, Jeffrey D.; Low, Daniel A. [Department of Radiation Oncology, Washington University School of Medicine, St. Louis, Missouri 63110 (United States)

2009-11-15

Purpose: To determine the quiet respiration breathing motion model parameters for lung cancer and nonlung cancer patients. Methods: 49 free breathing patient 4DCT image datasets (25 scans, cine mode) were collected with simultaneous quantitative spirometry. A cross-correlation registration technique was employed to track the lung tissue motion between scans. The registration results were applied to a lung motion model: X-vector=X-vector{sub 0}+{alpha}-vector{beta}-vector f, where X-vector is the position of a piece of tissue located at reference position X-vector{sub 0} during a reference breathing phase (zero tidal volume v, zero airflow f). {alpha}-vector is a parameter that characterizes the motion due to air filling (motion as a function of tidal volume v) and {beta}-vector is the parameter that accounts for the motion due to the imbalance of dynamical stress distributions during inspiration and exhalation that causes lung motion hysteresis (motion as a function of airflow f). The parameters {alpha}-vector and {beta}-vector together provide a quantitative characterization of breathing motion that inherently includes the complex hysteresis interplay. The {alpha}-vector and {beta}-vector distributions were examined for each patient to determine overall general patterns and interpatient pattern variations. Results: For 44 patients, the greatest values of |{alpha}-vector| were observed in the inferior and posterior lungs. For the rest of the patients, |{alpha}-vector| reached its maximum in the anterior lung in three patients and the lateral lung in two patients. The hysteresis motion {beta}-vector had greater variability, but for the majority of patients, |{beta}-vector| was largest in the lateral lungs. Conclusions: This is the first report of the three-dimensional breathing motion model parameters for a large cohort of patients. The model has the potential for noninvasively predicting lung motion. The majority of patients exhibited similar |{alpha}-vector| maps

A stochastic differential equation model of diurnal cortisol patterns

Science.gov (United States)

Brown, E. N.; Meehan, P. M.; Dempster, A. P.

2001-01-01

Circadian modulation of episodic bursts is recognized as the normal physiological pattern of diurnal variation in plasma cortisol levels. The primary physiological factors underlying these diurnal patterns are the ultradian timing of secretory events, circadian modulation of the amplitude of secretory events, infusion of the hormone from the adrenal gland into the plasma, and clearance of the hormone from the plasma by the liver. Each measured plasma cortisol level has an error arising from the cortisol immunoassay. We demonstrate that all of these three physiological principles can be succinctly summarized in a single stochastic differential equation plus measurement error model and show that physiologically consistent ranges of the model parameters can be determined from published reports. We summarize the model parameters in terms of the multivariate Gaussian probability density and establish the plausibility of the model with a series of simulation studies. Our framework makes possible a sensitivity analysis in which all model parameters are allowed to vary simultaneously. The model offers an approach for simultaneously representing cortisol's ultradian, circadian, and kinetic properties. Our modeling paradigm provides a framework for simulation studies and data analysis that should be readily adaptable to the analysis of other endocrine hormone systems.

The spin dependent odderon in the diquark model

Energy Technology Data Exchange (ETDEWEB)

Szymanowski, Lech [National Centre for Nuclear Research (NCBJ), Warsaw (Poland); Zhou, Jian, E-mail: jzhou@sdu.edu.cn [School of Physics, & Key Laboratory of Particle Physics and Particle Irradiation (MOE), Shandong University, Jinan, Shandong 250100 (China); Nikhef and Department of Physics and Astronomy, VU University Amsterdam, De Boelelaan 1081, NL-1081 HV Amsterdam (Netherlands)

2016-09-10

In this short note, we report a di-quark model calculation for the spin dependent odderon and demonstrate that the asymmetrical color source distribution in the transverse plane of a transversely polarized hadron plays an essential role in yielding the spin dependent odderon. This calculation confirms the earlier finding that the spin dependent odderon is closely related to the parton orbital angular momentum.

Analysis of Local Dependence and Multidimensionality in Graphical Loglinear Rasch Models

DEFF Research Database (Denmark)

Kreiner, Svend; Christensen, Karl Bang

2004-01-01

Local independence; Multidimensionality; Differential item functioning; Uniform local dependence and DIF; Graphical Rasch models; Loglinear Rasch model......Local independence; Multidimensionality; Differential item functioning; Uniform local dependence and DIF; Graphical Rasch models; Loglinear Rasch model...

A novel spatial performance metric for robust pattern optimization of distributed hydrological models

Science.gov (United States)

Stisen, S.; Demirel, C.; Koch, J.

2017-12-01

Evaluation of performance is an integral part of model development and calibration as well as it is of paramount importance when communicating modelling results to stakeholders and the scientific community. There exists a comprehensive and well tested toolbox of metrics to assess temporal model performance in the hydrological modelling community. On the contrary, the experience to evaluate spatial performance is not corresponding to the grand availability of spatial observations readily available and to the sophisticate model codes simulating the spatial variability of complex hydrological processes. This study aims at making a contribution towards advancing spatial pattern oriented model evaluation for distributed hydrological models. This is achieved by introducing a novel spatial performance metric which provides robust pattern performance during model calibration. The promoted SPAtial EFficiency (spaef) metric reflects three equally weighted components: correlation, coefficient of variation and histogram overlap. This multi-component approach is necessary in order to adequately compare spatial patterns. spaef, its three components individually and two alternative spatial performance metrics, i.e. connectivity analysis and fractions skill score, are tested in a spatial pattern oriented model calibration of a catchment model in Denmark. The calibration is constrained by a remote sensing based spatial pattern of evapotranspiration and discharge timeseries at two stations. Our results stress that stand-alone metrics tend to fail to provide holistic pattern information to the optimizer which underlines the importance of multi-component metrics. The three spaef components are independent which allows them to complement each other in a meaningful way. This study promotes the use of bias insensitive metrics which allow comparing variables which are related but may differ in unit in order to optimally exploit spatial observations made available by remote sensing

Stability analysis for a general age-dependent vaccination model

International Nuclear Information System (INIS)

El Doma, M.

1995-05-01

An SIR epidemic model of a general age-dependent vaccination model is investigated when the fertility, mortality and removal rates depends on age. We give threshold criteria of the existence of equilibriums and perform stability analysis. Furthermore a critical vaccination coverage that is sufficient to eradicate the disease is determined. (author). 12 refs

Modulation of Corticospinal Excitability Depends on the Pattern of Mechanical Tactile Stimulation

Directory of Open Access Journals (Sweden)

Sho Kojima

2018-01-01

Full Text Available We investigated the effects of different patterns of mechanical tactile stimulation (MS on corticospinal excitability by measuring the motor-evoked potential (MEP. This was a single-blind study that included nineteen healthy subjects. MS was applied for 20 min to the right index finger. MS intervention was defined as simple, lateral, rubbing, vertical, or random. Simple intervention stimulated the entire finger pad at the same time. Lateral intervention stimulated with moving between left and right on the finger pad. Rubbing intervention stimulated with moving the stimulus probe, fixed by protrusion pins. Vertical intervention stimulated with moving in the forward and backward directions on the finger pad. Random intervention stimulated to finger pad with either row protrudes. MEPs were measured in the first dorsal interosseous muscle to transcranial magnetic stimulation of the left motor cortex before, immediately after, and 5–20 min after intervention. Following simple intervention, MEP amplitudes were significantly smaller than preintervention, indicating depression of corticospinal excitability. Following lateral, rubbing, and vertical intervention, MEP amplitudes were significantly larger than preintervention, indicating facilitation of corticospinal excitability. The modulation of corticospinal excitability depends on MS patterns. These results contribute to knowledge regarding the use of MS as a neurorehabilitation tool to neurological disorder.

Modulation of Corticospinal Excitability Depends on the Pattern of Mechanical Tactile Stimulation.

Science.gov (United States)

Kojima, Sho; Onishi, Hideaki; Miyaguchi, Shota; Kotan, Shinichi; Sasaki, Ryoki; Nakagawa, Masaki; Kirimoto, Hikari; Tamaki, Hiroyuki

2018-01-01

We investigated the effects of different patterns of mechanical tactile stimulation (MS) on corticospinal excitability by measuring the motor-evoked potential (MEP). This was a single-blind study that included nineteen healthy subjects. MS was applied for 20 min to the right index finger. MS intervention was defined as simple, lateral, rubbing, vertical, or random. Simple intervention stimulated the entire finger pad at the same time. Lateral intervention stimulated with moving between left and right on the finger pad. Rubbing intervention stimulated with moving the stimulus probe, fixed by protrusion pins. Vertical intervention stimulated with moving in the forward and backward directions on the finger pad. Random intervention stimulated to finger pad with either row protrudes. MEPs were measured in the first dorsal interosseous muscle to transcranial magnetic stimulation of the left motor cortex before, immediately after, and 5-20 min after intervention. Following simple intervention, MEP amplitudes were significantly smaller than preintervention, indicating depression of corticospinal excitability. Following lateral, rubbing, and vertical intervention, MEP amplitudes were significantly larger than preintervention, indicating facilitation of corticospinal excitability. The modulation of corticospinal excitability depends on MS patterns. These results contribute to knowledge regarding the use of MS as a neurorehabilitation tool to neurological disorder.

Modelling time-dependent mechanical behaviour of softwood using deformation kinetics

DEFF Research Database (Denmark)

Engelund, Emil Tang; Svensson, Staffan

2010-01-01

The time-dependent mechanical behaviour (TDMB) of softwood is relevant, e.g., when wood is used as building material where the mechanical properties must be predicted for decades ahead. The established mathematical models should be able to predict the time-dependent behaviour. However, these models...... are not always based on the actual physical processes causing time-dependent behaviour and the physical interpretation of their input parameters is difficult. The present study describes the TDMB of a softwood tissue and its individual tracheids. A model is constructed with a local coordinate system that follows...... macroscopic viscoelasticity, i.e., the time-dependent processes are to a significant degree reversible....

Different patterns in the prognostic value of age for bladder cancer-specific survival depending on tumor stages.

Science.gov (United States)

Feng, Huan; Zhang, Wei; Li, Jiajun; Lu, Xiaozhe

2015-01-01

To compare the pathological features and long-term survival of bladder cancer (BCa) in young patients with elderly counterparts. Using the U.S. National Cancer Institute's Surveillance, Epidemiology, and End Results (SEER) population-based data, we identified 93115 patients with non-metastatic bladder cancer diagnosed between 1988 and 2003. Patients were categorized into young (50 years and under) and elderly groups (over 50 years of age). The overall and five-year bladder cancer specific survival (BCSS) data were obtained using Kaplan-Meier plots. Multivariable Cox regression models were built for the analysis of long-term survival outcomes and risk factors. There were significant differences between the two groups in primary site, pathologic grading, histologic type, AJCC stage (pstage patients. The study findings show different patterns in the prognostic value of age for determining BCSS, depending on the tumor stages. Compared with elderly patients, young patients with bladder cancer surgery appear to have unique characteristics and a higher overall and cancer specific survival rate.

A Pattern-Oriented Approach to a Methodical Evaluation of Modeling Methods

Directory of Open Access Journals (Sweden)

Michael Amberg

1996-11-01

Full Text Available The paper describes a pattern-oriented approach to evaluate modeling methods and to compare various methods with each other from a methodical viewpoint. A specific set of principles (the patterns is defined by investigating the notations and the documentation of comparable modeling methods. Each principle helps to examine some parts of the methods from a specific point of view. All principles together lead to an overall picture of the method under examination. First the core ("method neutral" meaning of each principle is described. Then the methods are examined regarding the principle. Afterwards the method specific interpretations are compared with each other and with the core meaning of the principle. By this procedure, the strengths and weaknesses of modeling methods regarding methodical aspects are identified. The principles are described uniformly using a principle description template according to descriptions of object oriented design patterns. The approach is demonstrated by evaluating a business process modeling method.

Bias-dependent hybrid PKI empirical-neural model of microwave FETs

Science.gov (United States)

Marinković, Zlatica; Pronić-Rančić, Olivera; Marković, Vera

2011-10-01

Empirical models of microwave transistors based on an equivalent circuit are valid for only one bias point. Bias-dependent analysis requires repeated extractions of the model parameters for each bias point. In order to make model bias-dependent, a new hybrid empirical-neural model of microwave field-effect transistors is proposed in this article. The model is a combination of an equivalent circuit model including noise developed for one bias point and two prior knowledge input artificial neural networks (PKI ANNs) aimed at introducing bias dependency of scattering (S) and noise parameters, respectively. The prior knowledge of the proposed ANNs involves the values of the S- and noise parameters obtained by the empirical model. The proposed hybrid model is valid in the whole range of bias conditions. Moreover, the proposed model provides better accuracy than the empirical model, which is illustrated by an appropriate modelling example of a pseudomorphic high-electron mobility transistor device.

Modelling spatiotemporal distribution patterns of earthworms in order to indicate hydrological soil processes

Science.gov (United States)

Palm, Juliane; Klaus, Julian; van Schaik, Loes; Zehe, Erwin; Schröder, Boris

2010-05-01

environmental predictors which explain the distribution and dynamics of different ecological earthworm types can help us to understand where or when these processes are relevant in the landscape. Therefore, we develop species distribution models which are a useful tool to predict spatiotemporal distributions of earthworm occurrence and abundance under changing environmental conditions. On field scale, geostatistical distribution maps have shown that the spatial distribution of earthworms depends on soil parameters such as food supply, soil moisture, bulk density but with different patterns for earthworm stages (adult, juvenile) and ecological types (anecic, endogeic, epigeic). On landscape scales, earthworm distribution seems to be strongly controlled by management/disturbance-related factors. Our study shows different modelling approaches for predicting distribution patterns of earthworms in the Weiherbach area, an agricultural site in Kraichtal (Baden-Württemberg, Germany). We carried out field studies on arable fields differing in soil management practices (conventional, conservational), soil properties (organic matter content, texture, soil moisture), and topography (slope, elevation) in order to identify predictors for earthworm occurrence, abundance and biomass. Our earthworm distribution models consider all ecological groups as well as different life stages, accounting for the fact that the activity of juveniles is sometimes different from those of adults. Within our BIOPORE-project it is our final goal to couple our distribution models with population dynamic models and a preferential flow model to an integrated ecohydrological model to analyse feedbacks between earthworm engineering and transport characteristics affecting the functioning of (agro-) ecosystems.

Specimen-specific modeling of hip fracture pattern and repair.

Science.gov (United States)

Ali, Azhar A; Cristofolini, Luca; Schileo, Enrico; Hu, Haixiang; Taddei, Fulvia; Kim, Raymond H; Rullkoetter, Paul J; Laz, Peter J

2014-01-22

Hip fracture remains a major health problem for the elderly. Clinical studies have assessed fracture risk based on bone quality in the aging population and cadaveric testing has quantified bone strength and fracture loads. Prior modeling has primarily focused on quantifying the strain distribution in bone as an indicator of fracture risk. Recent advances in the extended finite element method (XFEM) enable prediction of the initiation and propagation of cracks without requiring a priori knowledge of the crack path. Accordingly, the objectives of this study were to predict femoral fracture in specimen-specific models using the XFEM approach, to perform one-to-one comparisons of predicted and in vitro fracture patterns, and to develop a framework to assess the mechanics and load transfer in the fractured femur when it is repaired with an osteosynthesis implant. Five specimen-specific femur models were developed from in vitro experiments under a simulated stance loading condition. Predicted fracture patterns closely matched the in vitro patterns; however, predictions of fracture load differed by approximately 50% due to sensitivity to local material properties. Specimen-specific intertrochanteric fractures were induced by subjecting the femur models to a sideways fall and repaired with a contemporary implant. Under a post-surgical stance loading, model-predicted load sharing between the implant and bone across the fracture surface varied from 59%:41% to 89%:11%, underscoring the importance of considering anatomic and fracture variability in the evaluation of implants. XFEM modeling shows potential as a macro-level analysis enabling fracture investigations of clinical cohorts, including at-risk groups, and the design of robust implants. © 2013 Published by Elsevier Ltd.

Understanding Activation Patterns in Shared Circuits: Toward a Value Driven Model

Directory of Open Access Journals (Sweden)

Lisa Aziz-Zadeh

2018-05-01

Full Text Available Over the past decade many studies indicate that we utilize our own motor system to understand the actions of other people. This mirror neuron system (MNS has been proposed to be involved in social cognition and motor learning. However, conflicting findings regarding the underlying mechanisms that drive these shared circuits make it difficult to decipher a common model of their function. Here we propose adapting a “value-driven” model to explain discrepancies in the human mirror system literature and to incorporate this model with existing models. We will use this model to explain discrepant activation patterns in multiple shared circuits in the human data, such that a unified model may explain reported activation patterns from previous studies as a function of value.

Image decomposition model Shearlet-Hilbert-L2 with better performance for denoising in ESPI fringe patterns.

Science.gov (United States)

Xu, Wenjun; Tang, Chen; Su, Yonggang; Li, Biyuan; Lei, Zhenkun

2018-02-01

In this paper, we propose an image decomposition model Shearlet-Hilbert-L 2 with better performance for denoising in electronic speckle pattern interferometry (ESPI) fringe patterns. In our model, the low-density fringes, high-density fringes, and noise are, respectively, described by shearlet smoothness spaces, adaptive Hilbert space, and L 2 space and processed individually. Because the shearlet transform has superior directional sensitivity, our proposed Shearlet-Hilbert-L 2 model achieves commendable filtering results for various types of ESPI fringe patterns, including uniform density fringe patterns, moderately variable density fringe patterns, and greatly variable density fringe patterns. We evaluate the performance of our proposed Shearlet-Hilbert-L 2 model via application to two computer-simulated and nine experimentally obtained ESPI fringe patterns with various densities and poor quality. Furthermore, we compare our proposed model with windowed Fourier filtering and coherence-enhancing diffusion, both of which are the state-of-the-art methods for ESPI fringe patterns denoising in transform domain and spatial domain, respectively. We also compare our proposed model with the previous image decomposition model BL-Hilbert-L 2 .

Dependence of AeroMACS Interference on Airport Radiation Pattern Characteristics

Science.gov (United States)

Wilson, Jeffrey D.

2012-01-01

AeroMACS (Aeronautical Mobile Airport Communications System), which is based upon the IEEE 802.16e mobile wireless standard, is expected to be implemented in the 5091 to 5150 MHz frequency band. As this band is also occupied by Mobile Satellite Service (MSS) feeder uplinks, AeroMACS must be designed to avoid interference with this incumbent service. The aspects of AeroMACS operation that present potential interference are under analysis in order to enable the definition of standards that assure that such interference will be avoided. In this study, the cumulative interference power distribution at low earth orbit from AeroMACS transmitters at the 497 major airports in the contiguous United States was simulated with the Visualyse Professional software. The dependence of the interference power on the number of antenna beams per airport, gain patterns, and beam direction orientations was simulated. As a function of these parameters, the simulation results are presented in terms of the limitations on transmitter power required to maintain the cumulative interference power under the established threshold.

Various oscillation patterns in phase models with locally attractive and globally repulsive couplings.

Science.gov (United States)

Sato, Katsuhiko; Shima, Shin-ichiro

2015-10-01

We investigate a phase model that includes both locally attractive and globally repulsive coupling in one dimension. This model exhibits nontrivial spatiotemporal patterns that have not been observed in systems that contain only local or global coupling. Depending on the relative strengths of the local and global coupling and on the form of global coupling, the system can show a spatially uniform state (in-phase synchronization), a monotonically increasing state (traveling wave), and three types of oscillations of relative phase difference. One of the oscillations of relative phase difference has the characteristic of being locally unstable but globally attractive. That is, any small perturbation to the periodic orbit in phase space destroys its periodic motion, but after a long time the system returns to the original periodic orbit. This behavior is closely related to the emergence of saddle two-cluster states for global coupling only, which are connected to each other by attractive heteroclinic orbits. The mechanism of occurrence of this type of oscillation is discussed.

In vitro burn model illustrating heat conduction patterns using compressed thermal papers.

Science.gov (United States)

Lee, Jun Yong; Jung, Sung-No; Kwon, Ho

2015-01-01

To date, heat conduction from heat sources to tissue has been estimated by complex mathematical modeling. In the present study, we developed an intuitive in vitro skin burn model that illustrates heat conduction patterns inside the skin. This was composed of tightly compressed thermal papers with compression frames. Heat flow through the model left a trace by changing the color of thermal papers. These were digitized and three-dimensionally reconstituted to reproduce the heat conduction patterns in the skin. For standardization, we validated K91HG-CE thermal paper using a printout test and bivariate correlation analysis. We measured the papers' physical properties and calculated the estimated depth of heat conduction using Fourier's equation. Through contact burns of 5, 10, 15, 20, and 30 seconds on porcine skin and our burn model using a heated brass comb, and comparing the burn wound and heat conduction trace, we validated our model. The heat conduction pattern correlation analysis (intraclass correlation coefficient: 0.846, p < 0.001) and the heat conduction depth correlation analysis (intraclass correlation coefficient: 0.93, p < 0.001) showed statistically significant high correlations between the porcine burn wound and our model. Our model showed good correlation with porcine skin burn injury and replicated its heat conduction patterns. © 2014 by the Wound Healing Society.

Dependent-Chance Programming Models for Capital Budgeting in Fuzzy Environments

Institute of Scientific and Technical Information of China (English)

LIANG Rui; GAO Jinwu

2008-01-01

Capital budgeting is concerned with maximizing the total net profit subject to budget constraints by selecting an appropriate combination of projects. This paper presents chance maximizing models for capital budgeting with fuzzy input data and multiple conflicting objectives. When the decision maker sets a prospec-tive profit level and wants to maximize the chances of the total profit achieving the prospective profit level, a fuzzy dependent-chance programming model, a fuzzy multi-objective dependent-chance programming model, and a fuzzy goal dependent-chance programming model are used to formulate the fuzzy capital budgeting problem. A fuzzy simulation based genetic algorithm is used to solve these models. Numerical examples are provided to illustrate the effectiveness of the simulation-based genetic algorithm and the po-tential applications of these models.

A TESSELLATION MODEL FOR CRACK PATTERNS ON SURFACES

Directory of Open Access Journals (Sweden)

Werner Nagel

2011-05-01

Full Text Available This paper presents a model of random tessellations that reflect several features of crack pattern. There are already several theoretical results derivedwhich indicate that thismodel can be an appropriate referencemodel. Some potential applications are presented in a tentative statistical study.

and density-dependent quark mass model

Indian Academy of Sciences (India)

Since a fair proportion of such dense proto stars are likely to be ... the temperature- and density-dependent quark mass (TDDQM) model which we had em- ployed in .... instead of Tc ~170 MeV which is a favoured value for the ud matter [26].

Conditional Random Fields for Pattern Recognition Applied to Structured Data

Directory of Open Access Journals (Sweden)

Tom Burr

2015-07-01

Full Text Available Pattern recognition uses measurements from an input domain, X, to predict their labels from an output domain, Y. Image analysis is one setting where one might want to infer whether a pixel patch contains an object that is “manmade” (such as a building or “natural” (such as a tree. Suppose the label for a pixel patch is “manmade”; if the label for a nearby pixel patch is then more likely to be “manmade” there is structure in the output domain that can be exploited to improve pattern recognition performance. Modeling P(X is difficult because features between parts of the model are often correlated. Therefore, conditional random fields (CRFs model structured data using the conditional distribution P(Y|X = x, without specifying a model for P(X, and are well suited for applications with dependent features. This paper has two parts. First, we overview CRFs and their application to pattern recognition in structured problems. Our primary examples are image analysis applications in which there is dependence among samples (pixel patches in the output domain. Second, we identify research topics and present numerical examples.

Machine Learning of the Reactor Core Loading Pattern Critical Parameters

Directory of Open Access Journals (Sweden)

Krešimir Trontl

2008-01-01

Full Text Available The usual approach to loading pattern optimization involves high degree of engineering judgment, a set of heuristic rules, an optimization algorithm, and a computer code used for evaluating proposed loading patterns. The speed of the optimization process is highly dependent on the computer code used for the evaluation. In this paper, we investigate the applicability of a machine learning model which could be used for fast loading pattern evaluation. We employ a recently introduced machine learning technique, support vector regression (SVR, which is a data driven, kernel based, nonlinear modeling paradigm, in which model parameters are automatically determined by solving a quadratic optimization problem. The main objective of the work reported in this paper was to evaluate the possibility of applying SVR method for reactor core loading pattern modeling. We illustrate the performance of the solution and discuss its applicability, that is, complexity, speed, and accuracy.

Machine Learning of the Reactor Core Loading Pattern Critical Parameters

International Nuclear Information System (INIS)

Trontl, K.; Pevec, D.; Smuc, T.

2008-01-01

The usual approach to loading pattern optimization involves high degree of engineering judgment, a set of heuristic rules, an optimization algorithm, and a computer code used for evaluating proposed loading patterns. The speed of the optimization process is highly dependent on the computer code used for the evaluation. In this paper, we investigate the applicability of a machine learning model which could be used for fast loading pattern evaluation. We employ a recently introduced machine learning technique, support vector regression (SVR), which is a data driven, kernel based, nonlinear modeling paradigm, in which model parameters are automatically determined by solving a quadratic optimization problem. The main objective of the work reported in this paper was to evaluate the possibility of applying SVR method for reactor core loading pattern modeling. We illustrate the performance of the solution and discuss its applicability, that is, complexity, speed, and accuracy

Time-dependent plug-in hybrid electric vehicle charging based on national driving patterns and demographics

International Nuclear Information System (INIS)

Kelly, Jarod C.; MacDonald, Jason S.; Keoleian, Gregory A.

2012-01-01

Highlights: ► Analyzed National Household Travel Survey to simulate driving and charging patterns. ► Average compact PHEVs used 49 kW h of electricity and 6.8 L of gasoline per week. ► Percent of electrically driven miles increased from 64.3 in 2001 to 66.7 in 2009. ► Investigated demographic effects of sex, age, income, and household location. ► Analysis shows higher utility factors for females versus males and high age variation. -- Abstract: Plug-in hybrid electric vehicles (PHEVs) are one promising technology for addressing concerns around petroleum consumption, energy security and greenhouse gas emissions. However, there is much uncertainty in the impact that PHEVs can have on energy consumption and related emissions, as they are dependent on vehicle technology, driving patterns, and charging behavior. A methodology is used to simulate PHEV charging and gasoline consumption based on driving pattern data in USDOT’s National Household Travel Survey. The method uses information from each trip taken by approximately 170,000 vehicles to track their battery state of charge throughout the day, and to determine the timing and quantity of electricity and gasoline consumption for a fleet of PHEVs. Scenarios were developed to examine the effects of charging location, charging rate, time of charging and battery size. Additionally, demographic information was examined to see how driver and household characteristics influence consumption patterns. Results showed that a compact vehicle with a 10.4 kW h useable battery (approximately a 42 mile [68 km] all electric range) travels between 62.5% and 75.7% on battery electricity, depending on charging scenario. The percent of travel driven electrically (Utility Factor, UF) in a baseline charging scenario increased from 64.3% using 2001 NHTS data to 66.7% using 2009 data. The average UF was 63.5% for males and 72.9% for females and in both cases they are highly sensitive to age. Vehicle charging load profiles across

A simple shear limited, single size, time dependent flocculation model

Science.gov (United States)

Kuprenas, R.; Tran, D. A.; Strom, K.

2017-12-01

This research focuses on the modeling of flocculation of cohesive sediment due to turbulent shear, specifically, investigating the dependency of flocculation on the concentration of cohesive sediment. Flocculation is important in larger sediment transport models as cohesive particles can create aggregates which are orders of magnitude larger than their unflocculated state. As the settling velocity of each particle is determined by the sediment size, density, and shape, accounting for this aggregation is important in determining where the sediment is deposited. This study provides a new formulation for flocculation of cohesive sediment by modifying the Winterwerp (1998) flocculation model (W98) so that it limits floc size to that of the Kolmogorov micro length scale. The W98 model is a simple approach that calculates the average floc size as a function of time. Because of its simplicity, the W98 model is ideal for implementing into larger sediment transport models; however, the model tends to over predict the dependency of the floc size on concentration. It was found that the modification of the coefficients within the original model did not allow for the model to capture the dependency on concentration. Therefore, a new term within the breakup kernel of the W98 formulation was added. The new formulation results is a single size, shear limited, and time dependent flocculation model that is able to effectively capture the dependency of the equilibrium size of flocs on both suspended sediment concentration and the time to equilibrium. The overall behavior of the new model is explored and showed align well with other studies on flocculation. Winterwerp, J. C. (1998). A simple model for turbulence induced flocculation of cohesive sediment. .Journal of Hydraulic Research, 36(3):309-326.

Modeling spatial processes with unknown extremal dependence class

KAUST Repository

Huser, Raphaë l G.; Wadsworth, Jennifer L.

2017-01-01

Many environmental processes exhibit weakening spatial dependence as events become more extreme. Well-known limiting models, such as max-stable or generalized Pareto processes, cannot capture this, which can lead to a preference for models

Demographic models reveal the shape of density dependence for a specialist insect herbivore on variable host plants.

Science.gov (United States)

Miller, Tom E X

2007-07-01

1. It is widely accepted that density-dependent processes play an important role in most natural populations. However, persistent challenges in our understanding of density-dependent population dynamics include evaluating the shape of the relationship between density and demographic rates (linear, concave, convex), and identifying extrinsic factors that can mediate this relationship. 2. I studied the population dynamics of the cactus bug Narnia pallidicornis on host plants (Opuntia imbricata) that varied naturally in relative reproductive effort (RRE, the proportion of meristems allocated to reproduction), an important plant quality trait. I manipulated per-plant cactus bug densities, quantified subsequent dynamics, and fit stage-structured models to the experimental data to ask if and how density influences demographic parameters. 3. In the field experiment, I found that populations with variable starting densities quickly converged upon similar growth trajectories. In the model-fitting analyses, the data strongly supported a model that defined the juvenile cactus bug retention parameter (joint probability of surviving and not dispersing) as a nonlinear decreasing function of density. The estimated shape of this relationship shifted from concave to convex with increasing host-plant RRE. 4. The results demonstrate that host-plant traits are critical sources of variation in the strength and shape of density dependence in insects, and highlight the utility of integrated experimental-theoretical approaches for identifying processes underlying patterns of change in natural populations.

Factor copula models for data with spatio-temporal dependence

KAUST Repository

Krupskii, Pavel

2017-10-13

We propose a new copula model for spatial data that are observed repeatedly in time. The model is based on the assumption that there exists a common factor that affects the measurements of a process in space and in time. Unlike models based on multivariate normality, our model can handle data with tail dependence and asymmetry. The likelihood for the proposed model can be obtained in a simple form and therefore parameter estimation is quite fast. Simulation from this model is straightforward and data can be predicted at any spatial location and time point. We use simulation studies to show different types of dependencies, both in space and in time, that can be generated by this model. We apply the proposed copula model to hourly wind data and compare its performance with some classical models for spatio-temporal data.

Factor copula models for data with spatio-temporal dependence

KAUST Repository

Krupskii, Pavel; Genton, Marc G.

2017-01-01

We propose a new copula model for spatial data that are observed repeatedly in time. The model is based on the assumption that there exists a common factor that affects the measurements of a process in space and in time. Unlike models based on multivariate normality, our model can handle data with tail dependence and asymmetry. The likelihood for the proposed model can be obtained in a simple form and therefore parameter estimation is quite fast. Simulation from this model is straightforward and data can be predicted at any spatial location and time point. We use simulation studies to show different types of dependencies, both in space and in time, that can be generated by this model. We apply the proposed copula model to hourly wind data and compare its performance with some classical models for spatio-temporal data.

Scale dependence of the halo bias in general local-type non-Gaussian models I: analytical predictions and consistency relations

International Nuclear Information System (INIS)

Nishimichi, Takahiro

2012-01-01

The large-scale clustering pattern of biased tracers is known to be a powerful probe of the non-Gaussianities in the primordial fluctuations. The so-called scale-dependent bias has been reported in various type of models of primordial non-Gaussianities. We focus on local-type non-Gaussianities, and unify the derivations in the literature of the scale-dependent bias in the presence of multiple Gaussian source fields as well as higher-order coupling to cover the models described by frequently-discussed f NL , g NL and t NL parameterization. We find that the resultant power spectrum is characterized by two parameters responsible for the shape and the amplitude of the scale-dependent bias in addition to the Gaussian bias factor. We show how (a generalized version of) Suyama-Yamaguchi inequality between f NL and t NL can directly be accessible from the observed power spectrum through the dependence on our new parameter which controls the shape of the scale-dependent bias. The other parameter for the amplitude of the scale-dependent bias is shown to be useful to distinguish the simplest quadratic non-Gaussianities (i.e., f NL -type) from higher-order ones (g NL and higher), if one measures it from multiple species of galaxies or clusters of galaxies. We discuss the validity and limitations of our analytic results by comparison with numerical simulations in an accompanying paper

Transcription patterns of genes encoding four metallothionein homologs in Daphnia pulex exposed to copper and cadmium are time- and homolog-dependent

International Nuclear Information System (INIS)

Asselman, Jana; Shaw, Joseph R.; Glaholt, Stephen P.; Colbourne, John K.; De Schamphelaere, Karel A.C.

2013-01-01

Highlights: •Transcription patterns of 4 metallothionein isoforms in Daphnia pulex. •Under cadmium and copper stress these patterns are time-dependent. •Under cadmium and copper stress these patterns are homolog-dependent. •The results stress the complex regulation of metallothioneins. -- Abstract: Metallothioneins are proteins that play an essential role in metal homeostasis and detoxification in nearly all organisms studied to date. Yet discrepancies between outcomes of chronic and acute exposure experiments hamper the understanding of the regulatory mechanisms of their isoforms following metal exposure. Here, we investigated transcriptional differences among four identified homologs (mt1–mt4) in Daphnia pulex exposed across time to copper and cadmium relative to a control. Transcriptional upregulation of mt1 and mt3 was detected on day four following exposure to cadmium, whereas that of mt2 and mt4 was detected on day two and day eight following exposure to copper. These results confirm temporal and metal-specific differences in the transcriptional induction of genes encoding metallothionein homologs upon metal exposure which should be considered in ecotoxicological monitoring programs of metal-contaminated water bodies. Indeed, the mRNA expression patterns observed here illustrate the complex regulatory system associated with metallothioneins, as these patterns are not only dependent on the metal, but also on exposure time and the homolog studied. Further phylogenetic analysis and analysis of regulatory elements in upstream promoter regions revealed a high degree of similarity between metallothionein genes of Daphnia pulex and Daphnia magna, a species belonging to the same genus. These findings, combined with a limited amount of available expression data for D. magna metallothionein genes, tentatively suggest a potential generalization of the metallothionein response system between these Daphnia species

Transcription patterns of genes encoding four metallothionein homologs in Daphnia pulex exposed to copper and cadmium are time- and homolog-dependent

Energy Technology Data Exchange (ETDEWEB)

Asselman, Jana, E-mail: jana.asselman@ugent.be [Laboratory of Environmental Toxicology and Aquatic Ecology, Ghent University, Ghent (Belgium); Shaw, Joseph R.; Glaholt, Stephen P. [The School of Public and Environmental Affairs, Indiana University, Bloomington, IN (United States); Colbourne, John K. [School of Biosciences, The University of Birmingham, Birmingham (United Kingdom); De Schamphelaere, Karel A.C. [Laboratory of Environmental Toxicology and Aquatic Ecology, Ghent University, Ghent (Belgium)

2013-10-15

Highlights: •Transcription patterns of 4 metallothionein isoforms in Daphnia pulex. •Under cadmium and copper stress these patterns are time-dependent. •Under cadmium and copper stress these patterns are homolog-dependent. •The results stress the complex regulation of metallothioneins. -- Abstract: Metallothioneins are proteins that play an essential role in metal homeostasis and detoxification in nearly all organisms studied to date. Yet discrepancies between outcomes of chronic and acute exposure experiments hamper the understanding of the regulatory mechanisms of their isoforms following metal exposure. Here, we investigated transcriptional differences among four identified homologs (mt1–mt4) in Daphnia pulex exposed across time to copper and cadmium relative to a control. Transcriptional upregulation of mt1 and mt3 was detected on day four following exposure to cadmium, whereas that of mt2 and mt4 was detected on day two and day eight following exposure to copper. These results confirm temporal and metal-specific differences in the transcriptional induction of genes encoding metallothionein homologs upon metal exposure which should be considered in ecotoxicological monitoring programs of metal-contaminated water bodies. Indeed, the mRNA expression patterns observed here illustrate the complex regulatory system associated with metallothioneins, as these patterns are not only dependent on the metal, but also on exposure time and the homolog studied. Further phylogenetic analysis and analysis of regulatory elements in upstream promoter regions revealed a high degree of similarity between metallothionein genes of Daphnia pulex and Daphnia magna, a species belonging to the same genus. These findings, combined with a limited amount of available expression data for D. magna metallothionein genes, tentatively suggest a potential generalization of the metallothionein response system between these Daphnia species.

Fixed transaction costs and modelling limited dependent variables

NARCIS (Netherlands)

Hempenius, A.L.

1994-01-01

As an alternative to the Tobit model, for vectors of limited dependent variables, I suggest a model, which follows from explicitly using fixed costs, if appropriate of course, in the utility function of the decision-maker.

The Dependencies of Ecosystem Pattern, Structure, and Dynamics on Climate, Climate Variability, and Climate Change

Science.gov (United States)

Flanagan, S.; Hurtt, G. C.; Fisk, J. P.; Rourke, O.

2012-12-01

A robust understanding of the sensitivity of the pattern, structure, and dynamics of ecosystems to climate, climate variability, and climate change is needed to predict ecosystem responses to current and projected climate change. We present results of a study designed to first quantify the sensitivity of ecosystems to climate through the use of climate and ecosystem data, and then use the results to test the sensitivity of the climate data in a state-of the art ecosystem model. A database of available ecosystem characteristics such as mean canopy height, above ground biomass, and basal area was constructed from sources like the National Biomass and Carbon Dataset (NBCD). The ecosystem characteristics were then paired by latitude and longitude with the corresponding climate characteristics temperature, precipitation, photosynthetically active radiation (PAR) and dew point that were retrieved from the North American Regional Reanalysis (NARR). The average yearly and seasonal means of the climate data, and their associated maximum and minimum values, over the 1979-2010 time frame provided by NARR were constructed and paired with the ecosystem data. The compiled results provide natural patterns of vegetation structure and distribution with regard to climate data. An advanced ecosystem model, the Ecosystem Demography model (ED), was then modified to allow yearly alterations to its mechanistic climate lookup table and used to predict the sensitivities of ecosystem pattern, structure, and dynamics to climate data. The combined ecosystem structure and climate data results were compared to ED's output to check the validity of the model. After verification, climate change scenarios such as those used in the last IPCC were run and future forest structure changes due to climate sensitivities were identified. The results of this study can be used to both quantify and test key relationships for next generation models. The sensitivity of ecosystem characteristics to climate data

Constitutive modeling for uniaxial time-dependent ratcheting of SS304 stainless steel

International Nuclear Information System (INIS)

Kan Qianhua; Kang Guozheng; Zhang Juan

2007-01-01

Based on the experimental results of uniaxial time-dependent ratcheting behavior of SS304 stainless steel at room temperature and 973K, a new time-dependent constitutive model was proposed. The model describes the time-dependent ratcheting by adding a static/thermal recovery into the Abdel-Karim-Ohno non-linear kinematic hardening rule. The capability of the model to describe the time-dependent ratcheting was discussed by comparing the simulations with the corresponding experimental results. It is shown that the revised unified viscoplastic model can simulate the time-dependent ratcheting reasonably both at room and high temperatures. (authors)

A random energy model for size dependence : recurrence vs. transience

NARCIS (Netherlands)

Külske, Christof

1998-01-01

We investigate the size dependence of disordered spin models having an infinite number of Gibbs measures in the framework of a simplified 'random energy model for size dependence'. We introduce two versions (involving either independent random walks or branching processes), that can be seen as

Empirical angle-dependent Biot and MBA models for acoustic anisotropy in cancellous bone

International Nuclear Information System (INIS)

Lee, Kang ll; Hughes, E R; Humphrey, V F; Leighton, T G; Choi, Min Joo

2007-01-01

The Biot and the modified Biot-Attenborough (MBA) models have been found useful to understand ultrasonic wave propagation in cancellous bone. However, neither of the models, as previously applied to cancellous bone, allows for the angular dependence of acoustic properties with direction. The present study aims to account for the acoustic anisotropy in cancellous bone, by introducing empirical angle-dependent input parameters, as defined for a highly oriented structure, into the Biot and the MBA models. The anisotropy of the angle-dependent Biot model is attributed to the variation in the elastic moduli of the skeletal frame with respect to the trabecular alignment. The angle-dependent MBA model employs a simple empirical way of using the parametric fit for the fast and the slow wave speeds. The angle-dependent models were used to predict both the fast and slow wave velocities as a function of propagation angle with respect to the trabecular alignment of cancellous bone. The predictions were compared with those of the Schoenberg model for anisotropy in cancellous bone and in vitro experimental measurements from the literature. The angle-dependent models successfully predicted the angular dependence of phase velocity of the fast wave with direction. The root-mean-square errors of the measured versus predicted fast wave velocities were 79.2 m s -1 (angle-dependent Biot model) and 36.1 m s -1 (angle-dependent MBA model). They also predicted the fact that the slow wave is nearly independent of propagation angle for angles about 50 0 , but consistently underestimated the slow wave velocity with the root-mean-square errors of 187.2 m s -1 (angle-dependent Biot model) and 240.8 m s -1 (angle-dependent MBA model). The study indicates that the angle-dependent models reasonably replicate the acoustic anisotropy in cancellous bone

Integrating temperature-dependent life table data into a matrix projection model for Drosophila suzukii population estimation.

Directory of Open Access Journals (Sweden)

Nik G Wiman

Full Text Available Temperature-dependent fecundity and survival data was integrated into a matrix population model to describe relative Drosophila suzukii Matsumura (Diptera: Drosophilidae population increase and age structure based on environmental conditions. This novel modification of the classic Leslie matrix population model is presented as a way to examine how insect populations interact with the environment, and has application as a predictor of population density. For D. suzukii, we examined model implications for pest pressure on crops. As case studies, we examined model predictions in three small fruit production regions in the United States (US and one in Italy. These production regions have distinctly different climates. In general, patterns of adult D. suzukii trap activity broadly mimicked seasonal population levels predicted by the model using only temperature data. Age structure of estimated populations suggest that trap and fruit infestation data are of limited value and are insufficient for model validation. Thus, we suggest alternative experiments for validation. The model is advantageous in that it provides stage-specific population estimation, which can potentially guide management strategies and provide unique opportunities to simulate stage-specific management effects such as insecticide applications or the effect of biological control on a specific life-stage. The two factors that drive initiation of the model are suitable temperatures (biofix and availability of a suitable host medium (fruit. Although there are many factors affecting population dynamics of D. suzukii in the field, temperature-dependent survival and reproduction are believed to be the main drivers for D. suzukii populations.

Computational design of patterned interfaces using reduced order models

International Nuclear Information System (INIS)

Vattre, A.J.; Abdolrahim, N.; Kolluri, K.; Demkowicz, M.J.

2014-01-01

Patterning is a familiar approach for imparting novel functionalities to free surfaces. We extend the patterning paradigm to interfaces between crystalline solids. Many interfaces have non-uniform internal structures comprised of misfit dislocations, which in turn govern interface properties. We develop and validate a computational strategy for designing interfaces with controlled misfit dislocation patterns by tailoring interface crystallography and composition. Our approach relies on a novel method for predicting the internal structure of interfaces: rather than obtaining it from resource-intensive atomistic simulations, we compute it using an efficient reduced order model based on anisotropic elasticity theory. Moreover, our strategy incorporates interface synthesis as a constraint on the design process. As an illustration, we apply our approach to the design of interfaces with rapid, 1-D point defect diffusion. Patterned interfaces may be integrated into the microstructure of composite materials, markedly improving performance. (authors)

Modelling Global Pattern Formations for Collaborative Learning Environments

DEFF Research Database (Denmark)

Grappiolo, Corrado; Cheong, Yun-Gyung; Khaled, Rilla

2012-01-01

We present our research towards the design of a computational framework capable of modelling the formation and evolution of global patterns (i.e. group structures) in a population of social individuals. The framework is intended to be used in collaborative environments, e.g. social serious games...

Modeling patterns of hot water use in households

Energy Technology Data Exchange (ETDEWEB)

Lutz, James D.; Liu, Xiaomin; McMahon, James E.; Dunham, Camilla; Shown, Leslie J.; McCure, Quandra T.

1996-01-01

This report presents a detailed model of hot water use patterns in individual households. The model improves upon an existing model by including the effects of four conditions that were previously unaccounted for: the absence of a clothes washer; the absence of a dishwasher; a household consisting of seniors only; and a household that does not pay for its own hot water use. Although these four conditions can significantly affect residential hot water use, and have been noted in other studies, this is the first time that they have been incorporated into a detailed model. This model allows detailed evaluation of the impact of potential efficiency standards for water heaters and other market transformation policies.

Neutrino flavor instabilities in a time-dependent supernova model

Energy Technology Data Exchange (ETDEWEB)

Abbar, Sajad; Duan, Huaiyu, E-mail: duan@unm.edu

2015-12-17

A dense neutrino medium such as that inside a core-collapse supernova can experience collective flavor conversion or oscillations because of the neutral-current weak interaction among the neutrinos. This phenomenon has been studied in a restricted, stationary supernova model which possesses the (spatial) spherical symmetry about the center of the supernova and the (directional) axial symmetry around the radial direction. Recently it has been shown that these spatial and directional symmetries can be broken spontaneously by collective neutrino oscillations. In this letter we analyze the neutrino flavor instabilities in a time-dependent supernova model. Our results show that collective neutrino oscillations start at approximately the same radius in both the stationary and time-dependent supernova models unless there exist very rapid variations in local physical conditions on timescales of a few microseconds or shorter. Our results also suggest that collective neutrino oscillations can vary rapidly with time in the regimes where they do occur which need to be studied in time-dependent supernova models.

Pattern formation in individual-based systems with time-varying parameters

Science.gov (United States)

Ashcroft, Peter; Galla, Tobias

2013-12-01

We study the patterns generated in finite-time sweeps across symmetry-breaking bifurcations in individual-based models. Similar to the well-known Kibble-Zurek scenario of defect formation, large-scale patterns are generated when model parameters are varied slowly, whereas fast sweeps produce a large number of small domains. The symmetry breaking is triggered by intrinsic noise, originating from the discrete dynamics at the microlevel. Based on a linear-noise approximation, we calculate the characteristic length scale of these patterns. We demonstrate the applicability of this approach in a simple model of opinion dynamics, a model in evolutionary game theory with a time-dependent fitness structure, and a model of cell differentiation. Our theoretical estimates are confirmed in simulations. In further numerical work, we observe a similar phenomenon when the symmetry-breaking bifurcation is triggered by population growth.

Blood oxygen level-dependent magnetic resonance imaging for detecting pathological patterns in patients with lupus nephritis: a preliminary study using gray-level co-occurrence matrix analysis.

Science.gov (United States)

Shi, Huilan; Jia, Junya; Li, Dong; Wei, Li; Shang, Wenya; Zheng, Zhenfeng

2018-01-01

Objective Blood oxygen level-dependent magnetic resonance imaging (BOLD MRI) is a noninvasive technique useful in patients with renal disease. The current study was performed to determine whether BOLD MRI can contribute to the diagnosis of renal pathological patterns. Methods BOLD MRI was used to obtain functional magnetic resonance parameter R2* values. Gray-level co-occurrence matrixes (GLCMs) were generated for gray-scale maps. Several GLCM parameters were calculated and used to construct algorithmic models for renal pathological patterns. Results Histopathology and BOLD MRI were used to examine 12 patients. Two GLCM parameters, including correlation and energy, revealed differences among four groups of renal pathological patterns. Four Fisher's linear discriminant formulas were constructed using two variables, including the correlation at 45° and correlation at 90°. A cross-validation test showed that the formulas correctly predicted 28 of 36 samples, and the rate of correct prediction was 77.8%. Conclusions Differences in the texture characteristics of BOLD MRI in patients with lupus nephritis may be detected by GLCM analysis. Discriminant formulas constructed using GLCM parameters may facilitate prediction of renal pathological patterns.

Patterns of glycogen turnover in liver characterized by computer modeling

International Nuclear Information System (INIS)

Youn, J.H.; Bergman, R.N.

1987-01-01

The authors used a computer model of liver glycogen turnover to reexamine the data of Devos and Hers, who reported the time course of accumulation in and loss from glycogen of label originating in [1- 14 C]galactose injected at different times after the start of refeeding of 40-h fasted mice or rats. In the present study computer representation of individual glycogen molecules was utilized to account for growth and degradation of glycogen according to specific hypothetical patterns. Using this model they could predict the accumulation and localization within glycogen of labeled glucose residues and compare the predictions with the previously published data. They considered three specific hypotheses of glycogen accumulation during refeeding: (1) simultaneous, (2) sequential, and (3) accelerating growth. Hypothetical patterns of glycogen degradation were (1) ordered and (2) random degradation. The pattern of glycogen synthesis consistent with experimental data was a steadily increasing number of growing glycogen molecules, whereas during degradation glycogen molecules are exposed to degrading enzymes randomly, rather than in a specific reverse order of synthesis. These patterns predict the existence of a specific mechanism for the steadily increasing seeding of new glycogen molecules during synthesis

Patterns of flavor signals in supersymmetric models

Energy Technology Data Exchange (ETDEWEB)

Goto, T. [KEK National High Energy Physics, Tsukuba (Japan)]|[Kyoto Univ. (Japan). YITP; Okada, Y. [KEK National High Energy Physics, Tsukuba (Japan)]|[Graduate Univ. for Advanced Studies, Tsukuba (Japan). Dept. of Particle and Nucelar Physics; Shindou, T. [Deutsches Elektronen-Synchrotron (DESY), Hamburg (Germany)]|[International School for Advanced Studies, Trieste (Italy); Tanaka, M. [Osaka Univ., Toyonaka (Japan). Dept. of Physics

2007-11-15

Quark and lepton flavor signals are studied in four supersymmetric models, namely the minimal supergravity model, the minimal supersymmetric standard model with right-handed neutrinos, SU(5) supersymmetric grand unified theory with right-handed neutrinos and the minimal supersymmetric standard model with U(2) flavor symmetry. We calculate b{yields}s(d) transition observables in B{sub d} and B{sub s} decays, taking the constraint from the B{sub s}- anti B{sub s} mixing recently observed at Tevatron into account. We also calculate lepton flavor violating processes {mu} {yields} e{gamma}, {tau} {yields} {mu}{gamma} and {tau} {yields} e{gamma} for the models with right-handed neutrinos. We investigate possibilities to distinguish the flavor structure of the supersymmetry breaking sector with use of patterns of various flavor signals which are expected to be measured in experiments such as MEG, LHCb and a future Super B Factory. (orig.)

Patterns of flavor signals in supersymmetric models

International Nuclear Information System (INIS)

Goto, T.; Tanaka, M.

2007-11-01

Quark and lepton flavor signals are studied in four supersymmetric models, namely the minimal supergravity model, the minimal supersymmetric standard model with right-handed neutrinos, SU(5) supersymmetric grand unified theory with right-handed neutrinos and the minimal supersymmetric standard model with U(2) flavor symmetry. We calculate b→s(d) transition observables in B d and B s decays, taking the constraint from the B s - anti B s mixing recently observed at Tevatron into account. We also calculate lepton flavor violating processes μ → eγ, τ → μγ and τ → eγ for the models with right-handed neutrinos. We investigate possibilities to distinguish the flavor structure of the supersymmetry breaking sector with use of patterns of various flavor signals which are expected to be measured in experiments such as MEG, LHCb and a future Super B Factory. (orig.)

Pattern formation through spatial interactions in a modified Daisyworld model

Science.gov (United States)

Alberti, Tommaso; Primavera, Leonardo; Lepreti, Fabio; Vecchio, Antonio; Carbone, Vincenzo

2015-04-01

The Daisyworld model is based on a hypothetical planet, like the Earth, which receives the radiant energy coming from a Sun-like star, and populated by two kinds of identical plants differing by their colour: white daisies reflecting light and black daisies absorbing light. The interactions and feedbacks between the collective biota of the planet and the incoming radiation form a self-regulating system where the conditions for life are maintained. We investigate a modified version of the Daisyworld model where a spatial dependency on latitude is introduced, and both a variable heat diffusivity along latitude and a simple greenhouse model are included. We show that the spatial interactions between the variables of the system can generate some equilibrium patterns which can locally stabilize the coexistence of the two vegetation types. The feedback on albedo is able to generate new equilibrium solutions which can efficiently self-regulate the planet climate, even for values of the solar luminosity relatively far from the current Earth conditions. The extension to spatial Daisyworld gives room to the possibility of inhomogeneous solar forcing in a curved planet, with explicit differences between poles and equator and the direct use of the heat diffusion equation. As a first approach, to describe a spherical planet, we consider the temperature T(θ,t) and the surface coverage as depending only on time and on latitude θ (-90° ≤ θ ≤ 90°). A second step is the introduction of the greenhouse effect in the model, the process by which outgoing infrared radiation is partly screened by greenhouse gases. This effect can be described by relaxing the black-body radiation hypothesis and by introducing a grayness function g(T) in the heat equation. As a third step, we consider a latitude dependence of the Earth's conductivity, χ = χ(θ). Considering these terms, using spherical coordinates and symmetry with respect to θ, the modified Daisyworld equations reduce to the

Autonomous change of behavior for environmental context: An intermittent search model with misunderstanding search pattern

Science.gov (United States)

Murakami, Hisashi; Gunji, Yukio-Pegio

2017-07-01

Although foraging patterns have long been predicted to optimally adapt to environmental conditions, empirical evidence has been found in recent years. This evidence suggests that the search strategy of animals is open to change so that animals can flexibly respond to their environment. In this study, we began with a simple computational model that possesses the principal features of an intermittent strategy, i.e., careful local searches separated by longer steps, as a mechanism for relocation, where an agent in the model follows a rule to switch between two phases, but it could misunderstand this rule, i.e., the agent follows an ambiguous switching rule. Thanks to this ambiguity, the agent's foraging strategy can continuously change. First, we demonstrate that our model can exhibit an optimal change of strategy from Brownian-type to Lévy-type depending on the prey density, and we investigate the distribution of time intervals for switching between the phases. Moreover, we show that the model can display higher search efficiency than a correlated random walk.

The ecology and evolution of temperature-dependent reaction norms for sex determination in reptiles: a mechanistic conceptual model.

Science.gov (United States)

Pezaro, Nadav; Doody, J Sean; Thompson, Michael B

2017-08-01

Sex-determining mechanisms are broadly categorised as being based on either genetic or environmental factors. Vertebrate sex determination exhibits remarkable diversity but displays distinct phylogenetic patterns. While all eutherian mammals possess XY male heterogamety and female heterogamety (ZW) is ubiquitous in birds, poikilothermic vertebrates (fish, amphibians and reptiles) exhibit multiple genetic sex-determination (GSD) systems as well as environmental sex determination (ESD). Temperature is the factor controlling ESD in reptiles and temperature-dependent sex determination (TSD) in reptiles has become a focal point in the study of this phenomenon. Current patterns of climate change may cause detrimental skews in the population sex ratios of reptiles exhibiting TSD. Understanding the patterns of variation, both within and among populations and linking such patterns with the selection processes they are associated with, is the central challenge of research aimed at predicting the capacity of populations to adapt to novel conditions. Here we present a conceptual model that innovates by defining an individual reaction norm for sex determination as a range of incubation temperatures. By deconstructing individual reaction norms for TSD and revealing their underlying interacting elements, we offer a conceptual solution that explains how variation among individual reaction norms can be inferred from the pattern of population reaction norms. The model also links environmental variation with the different patterns of TSD and describes the processes from which they may arise. Specific climate scenarios are singled out as eco-evolutionary traps that may lead to demographic extinction or a transition to either male or female heterogametic GSD. We describe how the conceptual principles can be applied to interpret TSD data and to explain the adaptive capacity of TSD to climate change as well as its limits and the potential applications for conservation and management

An expanded Notch-Delta model exhibiting long-range patterning and incorporating MicroRNA regulation.

Directory of Open Access Journals (Sweden)

Jerry S Chen

2014-06-01

Full Text Available Notch-Delta signaling is a fundamental cell-cell communication mechanism that governs the differentiation of many cell types. Most existing mathematical models of Notch-Delta signaling are based on a feedback loop between Notch and Delta leading to lateral inhibition of neighboring cells. These models result in a checkerboard spatial pattern whereby adjacent cells express opposing levels of Notch and Delta, leading to alternate cell fates. However, a growing body of biological evidence suggests that Notch-Delta signaling produces other patterns that are not checkerboard, and therefore a new model is needed. Here, we present an expanded Notch-Delta model that builds upon previous models, adding a local Notch activity gradient, which affects long-range patterning, and the activity of a regulatory microRNA. This model is motivated by our experiments in the ascidian Ciona intestinalis showing that the peripheral sensory neurons, whose specification is in part regulated by the coordinate activity of Notch-Delta signaling and the microRNA miR-124, exhibit a sparse spatial pattern whereby consecutive neurons may be spaced over a dozen cells apart. We perform rigorous stability and bifurcation analyses, and demonstrate that our model is able to accurately explain and reproduce the neuronal pattern in Ciona. Using Monte Carlo simulations of our model along with miR-124 transgene over-expression assays, we demonstrate that the activity of miR-124 can be incorporated into the Notch decay rate parameter of our model. Finally, we motivate the general applicability of our model to Notch-Delta signaling in other animals by providing evidence that microRNAs regulate Notch-Delta signaling in analogous cell types in other organisms, and by discussing evidence in other organisms of sparse spatial patterns in tissues where Notch-Delta signaling is active.

A Two-Dimensional Gridded Solar Forecasting System using Situation-Dependent Blending of Multiple Weather Models

Science.gov (United States)

Lu, S.; Hwang, Y.; Shao, X.; Hamann, H.

2015-12-01

Previously, we reported the application of a "weather situation" dependent multi-model blending approach to improve the forecast accuracy of solar irradiance and other atmospheric parameters. The approach uses machine-learning techniques to classify "weather situations" by a set of atmospheric parameters. The "weather situation" classification is location-dependent and each "weather situation" has characteristic forecast errors from a set of individual input numerical weather prediction (NWP) models. The input models are thus corrected or combined differently for different "weather situations" to minimize the overall forecast error. While the original implementation of the model-blending is applicable to only point-like locations having historical data of both measurements and forecasts, here we extend the approach to provide two-dimensional (2D) gridded forecasts. An experimental 2D forecasting system has been set up to provide gridded forecasts of solar irradiance (global horizontal irradiance), temperature, wind speed, and humidity for the contiguous United States (CONUS). Validation results show around 30% enhancement of 0 to 48 hour ahead solar irradiance forecast accuracy compared to the best input NWP model. The forecasting system may be leveraged by other site- or region-specific solar energy forecast products. To enable the 2D forecasting system, historical solar irradiance measurements from around 1,600 selected sites of the remote automated weather stations (RAWS) network have been employed. The CONUS was divided into smaller sub-regions, each containing a group of 10 to 20 RAWS sites. A group of sites, as classified by statistical analysis, have similar "weather patterns", i.e. the NWPs have similar "weather situation" dependent forecast errors for all sites in a group. The model-blending trained by the historical data from a group of sites is then applied for all locations in the corresponding sub-region. We discuss some key techniques developed for

English Writing Teaching Model Dependent on Computer Network Corpus Drive Model

Directory of Open Access Journals (Sweden)

Shi Lei

2018-03-01

Full Text Available At present, the mainstream lexicalized English writing methods take only the corpus dependence between words into consideration, without introducing the corpus collocation and other issues. “Drive” is a relatively essential feature of words. And once the drive structure of a word is determined, it will be relatively clear what kinds of words to collocate with, hence the structure of the sentence can be derived relatively directly. In this paper, the English writing model that relies on the computer network corpus drive model is put forward. In this model, rich English corpus is introduced in the decomposition of the rules and the calculation of the probability, which includes not only the corpus dependence information, but also the drive structure and other corpus collocation information. Improved computer network corpus drive model is used to carry out the English writing teaching experiment. The experimental results show that the precision and the recall rate are 88.76% and 87.43%, respectively. The F value of the comprehensive index is improved by 6.65% compared with the Collins headword driven English modes of writing.

A simplified memory network model based on pattern formations

Science.gov (United States)

Xu, Kesheng; Zhang, Xiyun; Wang, Chaoqing; Liu, Zonghua

2014-12-01

Many experiments have evidenced the transition with different time scales from short-term memory (STM) to long-term memory (LTM) in mammalian brains, while its theoretical understanding is still under debate. To understand its underlying mechanism, it has recently been shown that it is possible to have a long-period rhythmic synchronous firing in a scale-free network, provided the existence of both the high-degree hubs and the loops formed by low-degree nodes. We here present a simplified memory network model to show that the self-sustained synchronous firing can be observed even without these two necessary conditions. This simplified network consists of two loops of coupled excitable neurons with different synaptic conductance and with one node being the sensory neuron to receive an external stimulus signal. This model can be further used to show how the diversity of firing patterns can be selectively formed by varying the signal frequency, duration of the stimulus and network topology, which corresponds to the patterns of STM and LTM with different time scales. A theoretical analysis is presented to explain the underlying mechanism of firing patterns.

USING COPULAS TO MODEL DEPENDENCE IN SIMULATION RISK ASSESSMENT

Energy Technology Data Exchange (ETDEWEB)

Dana L. Kelly

2007-11-01

Typical engineering systems in applications with high failure consequences such as nuclear reactor plants often employ redundancy and diversity of equipment in an effort to lower the probability of failure and therefore risk. However, it has long been recognized that dependencies exist in these redundant and diverse systems. Some dependencies, such as common sources of electrical power, are typically captured in the logic structure of the risk model. Others, usually referred to as intercomponent dependencies, are treated implicitly by introducing one or more statistical parameters into the model. Such common-cause failure models have limitations in a simulation environment. In addition, substantial subjectivity is associated with parameter estimation for these models. This paper describes an approach in which system performance is simulated by drawing samples from the joint distributions of dependent variables. The approach relies on the notion of a copula distribution, a notion which has been employed by the actuarial community for ten years or more, but which has seen only limited application in technological risk assessment. The paper also illustrates how equipment failure data can be used in a Bayesian framework to estimate the parameter values in the copula model. This approach avoids much of the subjectivity required to estimate parameters in traditional common-cause failure models. Simulation examples are presented for failures in time. The open-source software package R is used to perform the simulations. The open-source software package WinBUGS is used to perform the Bayesian inference via Markov chain Monte Carlo sampling.

Model Building – A Circular Approach to Evaluate Multidimensional Patterns and Operationalized Procedures

Directory of Open Access Journals (Sweden)

Franz HAAS

2017-12-01

Full Text Available Managers operate in highly different fields. Decision-making can be based on models reflecting in part these differences. The challenge is to connect the respective models without too great a disruption. A threefold procedural approach is proposed by chaining a scheme of modeling in a complex field to an operationalized model to statistical multivariate methods. Multivariate pattern-detecting methods offer the chance to evaluate patterns within the complex field partly. This step completes the cycle of research and improved models can be used in a further cycle.

Modeling patterns of hot water use in households

Energy Technology Data Exchange (ETDEWEB)

Lutz, J.D.; Liu, Xiaomin; McMahon, J.E. [and others

1996-11-01

This report presents a detailed model of hot water use patterns in individual household. The model improves upon an existing model by including the effects of four conditions that were previously unaccounted for: the absence of a clothes washer; the absence of a dishwasher; a household consisting of seniors only; and a household that does not pay for its own hot water use. Although these four conditions can significantly affect residential hot water use, and have been noted in other studies, this is the first time that they have been incorporated into a detailed model. This model allows detailed evaluation of the impact of potential efficiency standards for water heaters and other market transformation policies. 21 refs., 3 figs., 10 tabs.

Spiking and bursting patterns of fractional-order Izhikevich model

Science.gov (United States)

Teka, Wondimu W.; Upadhyay, Ranjit Kumar; Mondal, Argha

2018-03-01

Bursting and spiking oscillations play major roles in processing and transmitting information in the brain through cortical neurons that respond differently to the same signal. These oscillations display complex dynamics that might be produced by using neuronal models and varying many model parameters. Recent studies have shown that models with fractional order can produce several types of history-dependent neuronal activities without the adjustment of several parameters. We studied the fractional-order Izhikevich model and analyzed different kinds of oscillations that emerge from the fractional dynamics. The model produces a wide range of neuronal spike responses, including regular spiking, fast spiking, intrinsic bursting, mixed mode oscillations, regular bursting and chattering, by adjusting only the fractional order. Both the active and silent phase of the burst increase when the fractional-order model further deviates from the classical model. For smaller fractional order, the model produces memory dependent spiking activity after the pulse signal turned off. This special spiking activity and other properties of the fractional-order model are caused by the memory trace that emerges from the fractional-order dynamics and integrates all the past activities of the neuron. On the network level, the response of the neuronal network shifts from random to scale-free spiking. Our results suggest that the complex dynamics of spiking and bursting can be the result of the long-term dependence and interaction of intracellular and extracellular ionic currents.

Mechanochemical pattern formation in simple models of active viscoelastic fluids and solids

Science.gov (United States)

Alonso, Sergio; Radszuweit, Markus; Engel, Harald; Bär, Markus

2017-11-01

The cytoskeleton of the organism Physarum polycephalum is a prominent example of a complex active viscoelastic material wherein stresses induce flows along the organism as a result of the action of molecular motors and their regulation by calcium ions. Experiments in Physarum polycephalum have revealed a rich variety of mechanochemical patterns including standing, traveling and rotating waves that arise from instabilities of spatially homogeneous states without gradients in stresses and resulting flows. Herein, we investigate simple models where an active stress induced by molecular motors is coupled to a model describing the passive viscoelastic properties of the cellular material. Specifically, two models for viscoelastic fluids (Maxwell and Jeffrey model) and two models for viscoelastic solids (Kelvin-Voigt and Standard model) are investigated. Our focus is on the analysis of the conditions that cause destabilization of spatially homogeneous states and the related onset of mechano-chemical waves and patterns. We carry out linear stability analyses and numerical simulations in one spatial dimension for different models. In general, sufficiently strong activity leads to waves and patterns. The primary instability is stationary for all active fluids considered, whereas all active solids have an oscillatory primary instability. All instabilities found are of long-wavelength nature reflecting the conservation of the total calcium concentration in the models studied.

Conduction Delay Learning Model for Unsupervised and Supervised Classification of Spatio-Temporal Spike Patterns.

Science.gov (United States)

Matsubara, Takashi

2017-01-01

Precise spike timing is considered to play a fundamental role in communications and signal processing in biological neural networks. Understanding the mechanism of spike timing adjustment would deepen our understanding of biological systems and enable advanced engineering applications such as efficient computational architectures. However, the biological mechanisms that adjust and maintain spike timing remain unclear. Existing algorithms adopt a supervised approach, which adjusts the axonal conduction delay and synaptic efficacy until the spike timings approximate the desired timings. This study proposes a spike timing-dependent learning model that adjusts the axonal conduction delay and synaptic efficacy in both unsupervised and supervised manners. The proposed learning algorithm approximates the Expectation-Maximization algorithm, and classifies the input data encoded into spatio-temporal spike patterns. Even in the supervised classification, the algorithm requires no external spikes indicating the desired spike timings unlike existing algorithms. Furthermore, because the algorithm is consistent with biological models and hypotheses found in existing biological studies, it could capture the mechanism underlying biological delay learning.

State-Dependent Impulsive Control Strategies for a Tumor-Immune Model

Directory of Open Access Journals (Sweden)

Kwang Su Kim

2016-01-01

Full Text Available Controlling the number of tumor cells leads us to expect more efficient strategies for treatment of tumor. Towards this goal, a tumor-immune model with state-dependent impulsive treatments is established. This model may give an efficient treatment schedule to control tumor’s abnormal growth. By using the Poincaré map and analogue of Poincaré criterion, some conditions for the existence and stability of a positive order-1 periodic solution of this model are obtained. Moreover, we carry out numerical simulations to illustrate the feasibility of our main results and compare fixed-time impulsive treatment effects with state-dependent impulsive treatment effects. The results of our simulations say that, in determining optimal treatment timing, the model with state-dependent impulsive control is more efficient than that with fixed-time impulsive control.

Model dependence of the 2H electric dipole moment

International Nuclear Information System (INIS)

Afnan, I. R.; Gibson, B. F.

2010-01-01

Background: Direct measurement of the electric dipole moment (EDM) of the neutron is in the future; measurement of a nuclear EDM may well come first. The deuteron is one nucleus for which exact model calculations are feasible. Purpose: We explore the model dependence of deuteron EDM calculations. Methods: Using a separable potential formulation of the Hamiltonian, we examine the sensitivity of the deuteron EDM to variation in the nucleon-nucleon interaction. We write the EDM as the sum of two terms, the first depending on the target wave function with plane-wave intermediate states, and the second depending on intermediate multiple scattering in the 3 P 1 channel, the latter being sensitive to the off-shell behavior of the 3 P 1 amplitude. Results: We compare the full calculation with the plane-wave approximation result, examine the tensor force contribution to the model results, and explore the effect of short-range repulsion found in realistic, contemporary potential models of the deuteron. Conclusions: Because one-pion exchange dominates the EDM calculation, separable potential model calculations will provide an adequate description of the 2 H EDM until such time as a measurement better than 10% is obtained.

Modeling the time-changing dependence in stock markets

International Nuclear Information System (INIS)

Frezza, Massimiliano

2012-01-01

The time-changing dependence in stock markets is investigated by assuming the multifractional process with random exponent (MPRE) as model for actual log price dynamics. By modeling its functional parameter S(t, ω) via the square root process (S.R.) a twofold aim is obtained. From one hand both the main financial and statistical properties shown by the estimated S(t) are captured by surrogates, on the other hand this capability reveals able to model the time-changing dependence shown by stocks or indexes. In particular, a new dynamical approach to interpreter market mechanisms is given. Empirical evidences are offered by analysing the behaviour of the daily closing prices of a very known index, the Industrial Average Dow Jones (DJIA), beginning on March,1990 and ending on February, 2005.

A copula method for modeling directional dependence of genes

Directory of Open Access Journals (Sweden)

Park Changyi

2008-05-01

our results with those from other methods in the literature. Although microarray results show a transcriptional co-regulation pattern and do not imply that the gene products are physically interactive, this tight genetic connection may suggest that each gene product has either direct or indirect connections between the other gene products. Indeed, recent comprehensive analysis of a protein interaction map revealed that those histone genes are physically connected with each other, supporting the results obtained by our method. Conclusion The results illustrate that our method can be an alternative to Bayesian networks in modeling gene interactions. One advantage of our approach is that dependence between genes is not assumed to be linear. Another advantage is that our approach can detect directional dependence. We expect that our study may help to design artificial drug candidates, which can block or activate biologically meaningful pathways. Moreover, our copula approach can be extended to investigate the effects of local environments on protein-protein interactions. The copula mutual information approach will help to propose the new variant of ARACNE (Algorithm for the Reconstruction of Accurate Cellular Networks: an algorithm for the reconstruction of gene regulatory networks.

System of systems dependability – Theoretical models and applications examples

International Nuclear Information System (INIS)

Bukowski, L.

2016-01-01

The aim of this article is to generalise the concept of 'dependability' in a way, that could be applied to all types of systems, especially the system of systems (SoS), operating under both normal and abnormal work conditions. In order to quantitatively assess the dependability we applied service continuity oriented approach. This approach is based on the methodology of service engineering and is closely related to the idea of resilient enterprise as well as to the concept of disruption-tolerant operation. On this basis a framework for evaluation of SoS dependability has been developed in a static as well as dynamic approach. The static model is created as a fuzzy logic-oriented advisory expert system and can be particularly useful at the design stage of SoS. The dynamic model is based on the risk oriented approach, and can be useful both at the design stage and for management of SoS. The integrated model of dependability can also form the basis for a new definition of the dependability engineering, namely as a superior discipline to reliability engineering, safety engineering, security engineering, resilience engineering and risk engineering. - Highlights: • A framework for evaluation of system of systems dependability is presented. • The model is based on the service continuity concept and consists of two parts. • The static part can be created as a fuzzy logic-oriented advisory expert system. • The dynamic, risk oriented part, is related to the concept of throughput chain. • A new definition of dependability engineering is proposed.

Single-cell and coupled GRN models of cell patterning in the Arabidopsis thaliana root stem cell niche

Directory of Open Access Journals (Sweden)

Alvarez-Buylla Elena R

2010-10-01

Full Text Available Abstract Background Recent experimental work has uncovered some of the genetic components required to maintain the Arabidopsis thaliana root stem cell niche (SCN and its structure. Two main pathways are involved. One pathway depends on the genes SHORTROOT and SCARECROW and the other depends on the PLETHORA genes, which have been proposed to constitute the auxin readouts. Recent evidence suggests that a regulatory circuit, composed of WOX5 and CLE40, also contributes to the SCN maintenance. Yet, we still do not understand how the niche is dynamically maintained and patterned or if the uncovered molecular components are sufficient to recover the observed gene expression configurations that characterize the cell types within the root SCN. Mathematical and computational tools have proven useful in understanding the dynamics of cell differentiation. Hence, to further explore root SCN patterning, we integrated available experimental data into dynamic Gene Regulatory Network (GRN models and addressed if these are sufficient to attain observed gene expression configurations in the root SCN in a robust and autonomous manner. Results We found that an SCN GRN model based only on experimental data did not reproduce the configurations observed within the root SCN. We developed several alternative GRN models that recover these expected stable gene configurations. Such models incorporate a few additional components and interactions in addition to those that have been uncovered. The recovered configurations are stable to perturbations, and the models are able to recover the observed gene expression profiles of almost all the mutants described so far. However, the robustness of the postulated GRNs is not as high as that of other previously studied networks. Conclusions These models are the first published approximations for a dynamic mechanism of the A. thaliana root SCN cellular pattering. Our model is useful to formally show that the data now available are not

Mathematical modeling of high-rate Anammox UASB reactor based on granular packing patterns

International Nuclear Information System (INIS)

Tang, Chong-Jian; He, Rui; Zheng, Ping; Chai, Li-Yuan; Min, Xiao-Bo

2013-01-01

Highlights: ► A novel model was conducted to estimate volumetric nitrogen conversion rates. ► The packing patterns of the granules in Anammox reactor are investigated. ► The simple cubic packing pattern was simulated in high-rate Anammox UASB reactor. ► Operational strategies concerning sludge concentration were proposed by the modeling. -- Abstract: A novel mathematical model was developed to estimate the volumetric nitrogen conversion rates of a high-rate Anammox UASB reactor based on the packing patterns of granular sludge. A series of relationships among granular packing density, sludge concentration, hydraulic retention time and volumetric conversion rate were constructed to correlate Anammox reactor performance with granular packing patterns. It was suggested that the Anammox granules packed as the equivalent simple cubic pattern in high-rate UASB reactor with packing density of 50–55%, which not only accommodated a high concentration of sludge inside the reactor, but also provided large pore volume, thus prolonging the actual substrate conversion time. Results also indicated that it was necessary to improve Anammox reactor performance by enhancing substrate loading when sludge concentration was higher than 37.8 gVSS/L. The established model was carefully calibrated and verified, and it well simulated the performance of granule-based high-rate Anammox UASB reactor

Mathematical modeling of high-rate Anammox UASB reactor based on granular packing patterns

Energy Technology Data Exchange (ETDEWEB)

Tang, Chong-Jian, E-mail: chjtangzju@yahoo.com.cn [Department of Environmental Engineering, School of Metallurgical Science and Engineering, Central South University, Changsha 410083 (China); National Engineering Research Center for Control and Treatment of Heavy Metal Pollution, Changsha 410083 (China); He, Rui; Zheng, Ping [Department of Environmental Engineering, Zhejiang University, Zijingang Campus, Hangzhou 310058 (China); Chai, Li-Yuan; Min, Xiao-Bo [Department of Environmental Engineering, School of Metallurgical Science and Engineering, Central South University, Changsha 410083 (China); National Engineering Research Center for Control and Treatment of Heavy Metal Pollution, Changsha 410083 (China)

2013-04-15

Highlights: ► A novel model was conducted to estimate volumetric nitrogen conversion rates. ► The packing patterns of the granules in Anammox reactor are investigated. ► The simple cubic packing pattern was simulated in high-rate Anammox UASB reactor. ► Operational strategies concerning sludge concentration were proposed by the modeling. -- Abstract: A novel mathematical model was developed to estimate the volumetric nitrogen conversion rates of a high-rate Anammox UASB reactor based on the packing patterns of granular sludge. A series of relationships among granular packing density, sludge concentration, hydraulic retention time and volumetric conversion rate were constructed to correlate Anammox reactor performance with granular packing patterns. It was suggested that the Anammox granules packed as the equivalent simple cubic pattern in high-rate UASB reactor with packing density of 50–55%, which not only accommodated a high concentration of sludge inside the reactor, but also provided large pore volume, thus prolonging the actual substrate conversion time. Results also indicated that it was necessary to improve Anammox reactor performance by enhancing substrate loading when sludge concentration was higher than 37.8 gVSS/L. The established model was carefully calibrated and verified, and it well simulated the performance of granule-based high-rate Anammox UASB reactor.

Pattern solutions of the Klausmeier Model for banded vegetation in semi-arid environments I

International Nuclear Information System (INIS)

Sherratt, Jonathan A

2010-01-01

In many semi-arid environments, vegetation cover is sparse, and is self-organized into large-scale spatial patterns. In particular, banded vegetation is typical on hillsides. Mathematical modelling is widely used to study these banded patterns, and many models are effectively extensions of a coupled reaction–diffusion–advection system proposed by Klausmeier (1999 Science 284 1826–8). However, there is currently very little mathematical theory on pattern solutions of these equations. This paper is the first in a series whose aim is a comprehensive understanding of these solutions, which can act as a springboard both for future simulation-based studies of the Klausmeier model, and for analysis of model extensions. The author focusses on a particular part of parameter space, and derives expressions for the boundaries of the parameter region in which patterns occur. The calculations are valid to leading order at large values of the 'slope parameter', which reflects a comparison of the rate of water flow downhill with the rate of vegetation dispersal. The form of the corresponding patterns is also studied, and the author shows that the leading order equations change close to one boundary of the parameter region in which there are patterns, leading to a homoclinic solution. Conclusions are drawn on the way in which changes in mean annual rainfall affect pattern properties, including overall biomass productivity

Neutrino flavor instabilities in a time-dependent supernova model

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Sajad Abbar

2015-12-01

Full Text Available A dense neutrino medium such as that inside a core-collapse supernova can experience collective flavor conversion or oscillations because of the neutral-current weak interaction among the neutrinos. This phenomenon has been studied in a restricted, stationary supernova model which possesses the (spatial spherical symmetry about the center of the supernova and the (directional axial symmetry around the radial direction. Recently it has been shown that these spatial and directional symmetries can be broken spontaneously by collective neutrino oscillations. In this letter we analyze the neutrino flavor instabilities in a time-dependent supernova model. Our results show that collective neutrino oscillations start at approximately the same radius in both the stationary and time-dependent supernova models unless there exist very rapid variations in local physical conditions on timescales of a few microseconds or shorter. Our results also suggest that collective neutrino oscillations can vary rapidly with time in the regimes where they do occur which need to be studied in time-dependent supernova models.

An equilibrium-point model of electromyographic patterns during single-joint movements based on experimentally reconstructed control signals.

Science.gov (United States)

Latash, M L; Goodman, S R

1994-01-01

The purpose of this work has been to develop a model of electromyographic (EMG) patterns during single-joint movements based on a version of the equilibrium-point hypothesis, a method for experimental reconstruction of the joint compliant characteristics, the dual-strategy hypothesis, and a kinematic model of movement trajectory. EMG patterns are considered emergent properties of hypothetical control patterns that are equally affected by the control signals and peripheral feedback reflecting actual movement trajectory. A computer model generated the EMG patterns based on simulated movement kinematics and hypothetical control signals derived from the reconstructed joint compliant characteristics. The model predictions have been compared to published recordings of movement kinematics and EMG patterns in a variety of movement conditions, including movements over different distances, at different speeds, against different-known inertial loads, and in conditions of possible unexpected decrease in the inertial load. Changes in task parameters within the model led to simulated EMG patterns qualitatively similar to the experimentally recorded EMG patterns. The model's predictive power compares it favourably to the existing models of the EMG patterns. Copyright © 1994. Published by Elsevier Ltd.

Analysis of multi-species point patterns using multivariate log Gaussian Cox processes

DEFF Research Database (Denmark)

Waagepetersen, Rasmus; Guan, Yongtao; Jalilian, Abdollah

Multivariate log Gaussian Cox processes are flexible models for multivariate point patterns. However, they have so far only been applied in bivariate cases. In this paper we move beyond the bivariate case in order to model multi-species point patterns of tree locations. In particular we address t...... of the data. The selected number of common latent fields provides an index of complexity of the multivariate covariance structure. Hierarchical clustering is used to identify groups of species with similar patterns of dependence on the common latent fields.......Multivariate log Gaussian Cox processes are flexible models for multivariate point patterns. However, they have so far only been applied in bivariate cases. In this paper we move beyond the bivariate case in order to model multi-species point patterns of tree locations. In particular we address...... the problems of identifying parsimonious models and of extracting biologically relevant information from the fitted models. The latent multivariate Gaussian field is decomposed into components given in terms of random fields common to all species and components which are species specific. This allows...

Terminal-Dependent Statistical Inference for the FBSDEs Models

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Yunquan Song

2014-01-01

Full Text Available The original stochastic differential equations (OSDEs and forward-backward stochastic differential equations (FBSDEs are often used to model complex dynamic process that arise in financial, ecological, and many other areas. The main difference between OSDEs and FBSDEs is that the latter is designed to depend on a terminal condition, which is a key factor in some financial and ecological circumstances. It is interesting but challenging to estimate FBSDE parameters from noisy data and the terminal condition. However, to the best of our knowledge, the terminal-dependent statistical inference for such a model has not been explored in the existing literature. We proposed a nonparametric terminal control variables estimation method to address this problem. The reason why we use the terminal control variables is that the newly proposed inference procedures inherit the terminal-dependent characteristic. Through this new proposed method, the estimators of the functional coefficients of the FBSDEs model are obtained. The asymptotic properties of the estimators are also discussed. Simulation studies show that the proposed method gives satisfying estimates for the FBSDE parameters from noisy data and the terminal condition. A simulation is performed to test the feasibility of our method.

Location Contexts of User Check-Ins to Model Urban Geo Life-Style Patterns

Science.gov (United States)

Hasan, Samiul; Ukkusuri, Satish V.

2015-01-01

Geo-location data from social media offers us information, in new ways, to understand people's attitudes and interests through their activity choices. In this paper, we explore the idea of inferring individual life-style patterns from activity-location choices revealed in social media. We present a model to understand life-style patterns using the contextual information (e. g. location categories) of user check-ins. Probabilistic topic models are developed to infer individual geo life-style patterns from two perspectives: i) to characterize the patterns of user interests to different types of places and ii) to characterize the patterns of user visits to different neighborhoods. The method is applied to a dataset of Foursquare check-ins of the users from New York City. The co-existence of several location contexts and the corresponding probabilities in a given pattern provide useful information about user interests and choices. It is found that geo life-style patterns have similar items—either nearby neighborhoods or similar location categories. The semantic and geographic proximity of the items in a pattern reflects the hidden regularity in user preferences and location choice behavior. PMID:25970430

SOA Modeling Patterns for Service Oriented Discovery and Analysis

CERN Document Server

Bell, Michael

2010-01-01

Learn the essential tools for developing a sound service-oriented architecture. SOA Modeling Patterns for Service-Oriented Discovery and Analysis introduces a universal, easy-to-use, and nimble SOA modeling language to facilitate the service identification and examination life cycle stage. This business and technological vocabulary will benefit your service development endeavors and foster organizational software asset reuse and consolidation, and reduction of expenditure. Whether you are a developer, business architect, technical architect, modeler, business analyst, team leader, or manager,

Morphogenesis and pattern formation in biological systems experiments and models

CERN Document Server

Noji, Sumihare; Ueno, Naoto; Maini, Philip

2003-01-01

A central goal of current biology is to decode the mechanisms that underlie the processes of morphogenesis and pattern formation. Concerned with the analysis of those phenomena, this book covers a broad range of research fields, including developmental biology, molecular biology, plant morphogenesis, ecology, epidemiology, medicine, paleontology, evolutionary biology, mathematical biology, and computational biology. In Morphogenesis and Pattern Formation in Biological Systems: Experiments and Models, experimental and theoretical aspects of biology are integrated for the construction and investigation of models of complex processes. This collection of articles on the latest advances by leading researchers not only brings together work from a wide spectrum of disciplines, but also provides a stepping-stone to the creation of new areas of discovery.

Comprehensive analyses of ventricular myocyte models identify targets exhibiting favorable rate dependence.

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Megan A Cummins

2014-03-01

Full Text Available Reverse rate dependence is a problematic property of antiarrhythmic drugs that prolong the cardiac action potential (AP. The prolongation caused by reverse rate dependent agents is greater at slow heart rates, resulting in both reduced arrhythmia suppression at fast rates and increased arrhythmia risk at slow rates. The opposite property, forward rate dependence, would theoretically overcome these parallel problems, yet forward rate dependent (FRD antiarrhythmics remain elusive. Moreover, there is evidence that reverse rate dependence is an intrinsic property of perturbations to the AP. We have addressed the possibility of forward rate dependence by performing a comprehensive analysis of 13 ventricular myocyte models. By simulating populations of myocytes with varying properties and analyzing population results statistically, we simultaneously predicted the rate-dependent effects of changes in multiple model parameters. An average of 40 parameters were tested in each model, and effects on AP duration were assessed at slow (0.2 Hz and fast (2 Hz rates. The analysis identified a variety of FRD ionic current perturbations and generated specific predictions regarding their mechanisms. For instance, an increase in L-type calcium current is FRD when this is accompanied by indirect, rate-dependent changes in slow delayed rectifier potassium current. A comparison of predictions across models identified inward rectifier potassium current and the sodium-potassium pump as the two targets most likely to produce FRD AP prolongation. Finally, a statistical analysis of results from the 13 models demonstrated that models displaying minimal rate-dependent changes in AP shape have little capacity for FRD perturbations, whereas models with large shape changes have considerable FRD potential. This can explain differences between species and between ventricular cell types. Overall, this study provides new insights, both specific and general, into the determinants of

Model dependence and its effect on ensemble projections in CMIP5

Science.gov (United States)

Abramowitz, G.; Bishop, C.

2013-12-01

Conceptually, the notion of model dependence within climate model ensembles is relatively simple - modelling groups share a literature base, parametrisations, data sets and even model code - the potential for dependence in sampling different climate futures is clear. How though can this conceptual problem inform a practical solution that demonstrably improves the ensemble mean and ensemble variance as an estimate of system uncertainty? While some research has already focused on error correlation or error covariance as a candidate to improve ensemble mean estimates, a complete definition of independence must at least implicitly subscribe to an ensemble interpretation paradigm, such as the 'truth-plus-error', 'indistinguishable', or more recently 'replicate Earth' paradigm. Using a definition of model dependence based on error covariance within the replicate Earth paradigm, this presentation will show that accounting for dependence in surface air temperature gives cooler projections in CMIP5 - by as much as 20% globally in some RCPs - although results differ significantly for each RCP, especially regionally. The fact that the change afforded by accounting for dependence across different RCPs is different is not an inconsistent result. Different numbers of submissions to each RCP by different modelling groups mean that differences in projections from different RCPs are not entirely about RCP forcing conditions - they also reflect different sampling strategies.

Calibration of a distributed hydrologic model using observed spatial patterns from MODIS data

Science.gov (United States)

Demirel, Mehmet C.; González, Gorka M.; Mai, Juliane; Stisen, Simon

2016-04-01

Distributed hydrologic models are typically calibrated against streamflow observations at the outlet of the basin. Along with these observations from gauging stations, satellite based estimates offer independent evaluation data such as remotely sensed actual evapotranspiration (aET) and land surface temperature. The primary objective of the study is to compare model calibrations against traditional downstream discharge measurements with calibrations against simulated spatial patterns and combinations of both types of observations. While the discharge based model calibration typically improves the temporal dynamics of the model, it seems to give rise to minimum improvement of the simulated spatial patterns. In contrast, objective functions specifically targeting the spatial pattern performance could potentially increase the spatial model performance. However, most modeling studies, including the model formulations and parameterization, are not designed to actually change the simulated spatial pattern during calibration. This study investigates the potential benefits of incorporating spatial patterns from MODIS data to calibrate the mesoscale hydrologic model (mHM). This model is selected as it allows for a change in the spatial distribution of key soil parameters through the optimization of pedo-transfer function parameters and includes options for using fully distributed daily Leaf Area Index (LAI) values directly as input. In addition the simulated aET can be estimated at a spatial resolution suitable for comparison to the spatial patterns observed with MODIS data. To increase our control on spatial calibration we introduced three additional parameters to the model. These new parameters are part of an empirical equation to the calculate crop coefficient (Kc) from daily LAI maps and used to update potential evapotranspiration (PET) as model inputs. This is done instead of correcting/updating PET with just a uniform (or aspect driven) factor used in the mHM model

A Structural Equation Approach to Models with Spatial Dependence

NARCIS (Netherlands)

Oud, Johan H. L.; Folmer, Henk

We introduce the class of structural equation models (SEMs) and corresponding estimation procedures into a spatial dependence framework. SEM allows both latent and observed variables within one and the same (causal) model. Compared with models with observed variables only, this feature makes it

A structural equation approach to models with spatial dependence

NARCIS (Netherlands)

Oud, J.H.L.; Folmer, H.

2008-01-01

We introduce the class of structural equation models (SEMs) and corresponding estimation procedures into a spatial dependence framework. SEM allows both latent and observed variables within one and the same (causal) model. Compared with models with observed variables only, this feature makes it

A Structural Equation Approach to Models with Spatial Dependence

NARCIS (Netherlands)

Oud, J.H.L.; Folmer, H.

2008-01-01

We introduce the class of structural equation models (SEMs) and corresponding estimation procedures into a spatial dependence framework. SEM allows both latent and observed variables within one and the same (causal) model. Compared with models with observed variables only, this feature makes it

Dependability modeling and assessment in UML-based software development.

Science.gov (United States)

Bernardi, Simona; Merseguer, José; Petriu, Dorina C

2012-01-01

Assessment of software nonfunctional properties (NFP) is an important problem in software development. In the context of model-driven development, an emerging approach for the analysis of different NFPs consists of the following steps: (a) to extend the software models with annotations describing the NFP of interest; (b) to transform automatically the annotated software model to the formalism chosen for NFP analysis; (c) to analyze the formal model using existing solvers; (d) to assess the software based on the results and give feedback to designers. Such a modeling→analysis→assessment approach can be applied to any software modeling language, be it general purpose or domain specific. In this paper, we focus on UML-based development and on the dependability NFP, which encompasses reliability, availability, safety, integrity, and maintainability. The paper presents the profile used to extend UML with dependability information, the model transformation to generate a DSPN formal model, and the assessment of the system properties based on the DSPN results.

A simple model for research interest evolution patterns

Science.gov (United States)

Jia, Tao; Wang, Dashun; Szymanski, Boleslaw

Sir Isaac Newton supposedly remarked that in his scientific career he was like ``...a boy playing on the sea-shore ...finding a smoother pebble or a prettier shell than ordinary''. His remarkable modesty and famous understatement motivate us to seek regularities in how scientists shift their research focus as the career develops. Indeed, despite intensive investigations on how microscopic factors, such as incentives and risks, would influence a scientist's choice of research agenda, little is known on the macroscopic patterns in the research interest change undertaken by individual scientists throughout their careers. Here we make use of over 14,000 authors' publication records in physics. By quantifying statistical characteristics in the interest evolution, we model scientific research as a random walk, which reproduces patterns in individuals' careers observed empirically. Despite myriad of factors that shape and influence individual choices of research subjects, we identified regularities in this dynamical process that are well captured by a simple statistical model. The results advance our understanding of scientists' behaviors during their careers and open up avenues for future studies in the science of science.

Spatial pattern evaluation of a calibrated national hydrological model - a remote-sensing-based diagnostic approach

Science.gov (United States)

Mendiguren, Gorka; Koch, Julian; Stisen, Simon

2017-11-01

Distributed hydrological models are traditionally evaluated against discharge stations, emphasizing the temporal and neglecting the spatial component of a model. The present study widens the traditional paradigm by highlighting spatial patterns of evapotranspiration (ET), a key variable at the land-atmosphere interface, obtained from two different approaches at the national scale of Denmark. The first approach is based on a national water resources model (DK-model), using the MIKE-SHE model code, and the second approach utilizes a two-source energy balance model (TSEB) driven mainly by satellite remote sensing data. Ideally, the hydrological model simulation and remote-sensing-based approach should present similar spatial patterns and driving mechanisms of ET. However, the spatial comparison showed that the differences are significant and indicate insufficient spatial pattern performance of the hydrological model.The differences in spatial patterns can partly be explained by the fact that the hydrological model is configured to run in six domains that are calibrated independently from each other, as it is often the case for large-scale multi-basin calibrations. Furthermore, the model incorporates predefined temporal dynamics of leaf area index (LAI), root depth (RD) and crop coefficient (Kc) for each land cover type. This zonal approach of model parameterization ignores the spatiotemporal complexity of the natural system. To overcome this limitation, this study features a modified version of the DK-model in which LAI, RD and Kc are empirically derived using remote sensing data and detailed soil property maps in order to generate a higher degree of spatiotemporal variability and spatial consistency between the six domains. The effects of these changes are analyzed by using empirical orthogonal function (EOF) analysis to evaluate spatial patterns. The EOF analysis shows that including remote-sensing-derived LAI, RD and Kc in the distributed hydrological model adds

Storm-time ring current: model-dependent results

Directory of Open Access Journals (Sweden)

N. Yu. Ganushkina

2012-01-01

Full Text Available The main point of the paper is to investigate how much the modeled ring current depends on the representations of magnetic and electric fields and boundary conditions used in simulations. Two storm events, one moderate (SymH minimum of −120 nT on 6–7 November 1997 and one intense (SymH minimum of −230 nT on 21–22 October 1999, are modeled. A rather simple ring current model is employed, namely, the Inner Magnetosphere Particle Transport and Acceleration model (IMPTAM, in order to make the results most evident. Four different magnetic field and two electric field representations and four boundary conditions are used. We find that different combinations of the magnetic and electric field configurations and boundary conditions result in very different modeled ring current, and, therefore, the physical conclusions based on simulation results can differ significantly. A time-dependent boundary outside of 6.6 RE gives a possibility to take into account the particles in the transition region (between dipole and stretched field lines forming partial ring current and near-Earth tail current in that region. Calculating the model SymH* by Biot-Savart's law instead of the widely used Dessler-Parker-Sckopke (DPS relation gives larger and more realistic values, since the currents are calculated in the regions with nondipolar magnetic field. Therefore, the boundary location and the method of SymH* calculation are of key importance for ring current data-model comparisons to be correctly interpreted.

Mutual inactivation of Notch receptors and ligands facilitates developmental patterning.

Directory of Open Access Journals (Sweden)

David Sprinzak

2011-06-01

Full Text Available Developmental patterning requires juxtacrine signaling in order to tightly coordinate the fates of neighboring cells. Recent work has shown that Notch and Delta, the canonical metazoan juxtacrine signaling receptor and ligand, mutually inactivate each other in the same cell. This cis-interaction generates mutually exclusive sending and receiving states in individual cells. It generally remains unclear, however, how this mutual inactivation and the resulting switching behavior can impact developmental patterning circuits. Here we address this question using mathematical modeling in the context of two canonical pattern formation processes: boundary formation and lateral inhibition. For boundary formation, in a model motivated by Drosophila wing vein patterning, we find that mutual inactivation allows sharp boundary formation across a broader range of parameters than models lacking mutual inactivation. This model with mutual inactivation also exhibits robustness to correlated gene expression perturbations. For lateral inhibition, we find that mutual inactivation speeds up patterning dynamics, relieves the need for cooperative regulatory interactions, and expands the range of parameter values that permit pattern formation, compared to canonical models. Furthermore, mutual inactivation enables a simple lateral inhibition circuit architecture which requires only a single downstream regulatory step. Both model systems show how mutual inactivation can facilitate robust fine-grained patterning processes that would be difficult to implement without it, by encoding a difference-promoting feedback within the signaling system itself. Together, these results provide a framework for analysis of more complex Notch-dependent developmental systems.

A Theoretical Model of Jigsaw-Puzzle Pattern Formation by Plant Leaf Epidermal Cells.

Science.gov (United States)

Higaki, Takumi; Kutsuna, Natsumaro; Akita, Kae; Takigawa-Imamura, Hisako; Yoshimura, Kenji; Miura, Takashi

2016-04-01

Plant leaf epidermal cells exhibit a jigsaw puzzle-like pattern that is generated by interdigitation of the cell wall during leaf development. The contribution of two ROP GTPases, ROP2 and ROP6, to the cytoskeletal dynamics that regulate epidermal cell wall interdigitation has already been examined; however, how interactions between these molecules result in pattern formation remains to be elucidated. Here, we propose a simple interface equation model that incorporates both the cell wall remodeling activity of ROP GTPases and the diffusible signaling molecules by which they are regulated. This model successfully reproduces pattern formation observed in vivo, and explains the counterintuitive experimental results of decreased cellulose production and increased thickness. Our model also reproduces the dynamics of three-way cell wall junctions. Therefore, this model provides a possible mechanism for cell wall interdigitation formation in vivo.

Combining satellite data and appropriate objective functions for improved spatial pattern performance of a distributed hydrologic model

DEFF Research Database (Denmark)

Demirel, Mehmet C.; Mai, Juliane; Mendiguren Gonzalez, Gorka

2018-01-01

Satellite-based earth observations offer great opportunities to improve spatial model predictions by means of spatial-pattern-oriented model evaluations. In this study, observed spatial patterns of actual evapotranspiration (AET) are utilised for spatial model calibration tailored to target...... and potential evapotranspiration correction parameterisations, based on soil type and vegetation density. These parameterisations are utilised as they are most relevant for simulated AET patterns from the hydrologic model. Due to the fundamental challenges encountered when evaluating spatial pattern performance...

Multiple sequential failure model: A probabilistic approach to quantifying human error dependency

International Nuclear Information System (INIS)

Samanta

1985-01-01

This paper rpesents a probabilistic approach to quantifying human error dependency when multiple tasks are performed. Dependent human failures are dominant contributors to risks from nuclear power plants. An overview of the Multiple Sequential Failure (MSF) model developed and its use in probabilistic risk assessments (PRAs) depending on the available data are discussed. A small-scale psychological experiment was conducted on the nature of human dependency and the interpretation of the experimental data by the MSF model show remarkable accommodation of the dependent failure data. The model, which provides an unique method for quantification of dependent failures in human reliability analysis, can be used in conjunction with any of the general methods currently used for performing the human reliability aspect in PRAs

Constitutive model with time-dependent deformations

DEFF Research Database (Denmark)

Krogsbøll, Anette

1998-01-01

are common in time as well as size. This problem is adressed by means of a new constitutive model for soils. It is able to describe the behavior of soils at different deformation rates. The model defines time-dependent and stress-related deformations separately. They are related to each other and they occur...... was the difference in time scale between the geological process of deposition (millions of years) and the laboratory measurements of mechanical properties (minutes or hours). In addition, the time scale relevant to the production history of the oil field was interesting (days or years)....

Spatial Patterns of Development Drive Water Use

Science.gov (United States)

Sanchez, G. M.; Smith, J. W.; Terando, A.; Sun, G.; Meentemeyer, R. K.

2018-03-01

Water availability is becoming more uncertain as human populations grow, cities expand into rural regions and the climate changes. In this study, we examine the functional relationship between water use and the spatial patterns of developed land across the rapidly growing region of the southeastern United States. We quantified the spatial pattern of developed land within census tract boundaries, including multiple metrics of density and configuration. Through non-spatial and spatial regression approaches we examined relationships and spatial dependencies between the spatial pattern metrics, socio-economic and environmental variables and two water use variables: a) domestic water use, and b) total development-related water use (a combination of public supply, domestic self-supply and industrial self-supply). Metrics describing the spatial patterns of development had the highest measure of relative importance (accounting for 53% of model's explanatory power), explaining significantly more variance in water use compared to socio-economic or environmental variables commonly used to estimate water use. Integrating metrics characterizing the spatial pattern of development into water use models is likely to increase their utility and could facilitate water-efficient land use planning.

Spatial patterns of development drive water use

Science.gov (United States)

Sanchez, G.M.; Smith, J.W.; Terando, Adam J.; Sun, G.; Meentemeyer, R.K.

2018-01-01

Water availability is becoming more uncertain as human populations grow, cities expand into rural regions and the climate changes. In this study, we examine the functional relationship between water use and the spatial patterns of developed land across the rapidly growing region of the southeastern United States. We quantified the spatial pattern of developed land within census tract boundaries, including multiple metrics of density and configuration. Through non‐spatial and spatial regression approaches we examined relationships and spatial dependencies between the spatial pattern metrics, socio‐economic and environmental variables and two water use variables: a) domestic water use, and b) total development‐related water use (a combination of public supply, domestic self‐supply and industrial self‐supply). Metrics describing the spatial patterns of development had the highest measure of relative importance (accounting for 53% of model's explanatory power), explaining significantly more variance in water use compared to socio‐economic or environmental variables commonly used to estimate water use. Integrating metrics characterizing the spatial pattern of development into water use models is likely to increase their utility and could facilitate water‐efficient land use planning.

Modeling on bubbly to churn flow pattern transition in narrow rectangular channel

International Nuclear Information System (INIS)

Wang Yanlin; Chen Bingde; Huang Yanping; Wang Junfeng

2012-01-01

A theoretical model based on some reasonable concepts was developed to predict the bubbly flow to churn flow pattern transition in vertical narrow rectangular channel under flow boiling condition. The maximum size of ideal bubble in narrow rectangular channel was calculated based on previous literature. The thermal hydraulics boundary condition of bubbly to churn flow pattern transition was exported from Helmholtz and maximum size of ideal bubble. The theoretical model was validated by existent experimental data. (authors)

Bursty communication patterns facilitate spreading in a threshold-based epidemic dynamics.

Science.gov (United States)

Takaguchi, Taro; Masuda, Naoki; Holme, Petter

2013-01-01

Records of social interactions provide us with new sources of data for understanding how interaction patterns affect collective dynamics. Such human activity patterns are often bursty, i.e., they consist of short periods of intense activity followed by long periods of silence. This burstiness has been shown to affect spreading phenomena; it accelerates epidemic spreading in some cases and slows it down in other cases. We investigate a model of history-dependent contagion. In our model, repeated interactions between susceptible and infected individuals in a short period of time is needed for a susceptible individual to contract infection. We carry out numerical simulations on real temporal network data to find that bursty activity patterns facilitate epidemic spreading in our model.

Bursty communication patterns facilitate spreading in a threshold-based epidemic dynamics.

Directory of Open Access Journals (Sweden)

Taro Takaguchi

Full Text Available Records of social interactions provide us with new sources of data for understanding how interaction patterns affect collective dynamics. Such human activity patterns are often bursty, i.e., they consist of short periods of intense activity followed by long periods of silence. This burstiness has been shown to affect spreading phenomena; it accelerates epidemic spreading in some cases and slows it down in other cases. We investigate a model of history-dependent contagion. In our model, repeated interactions between susceptible and infected individuals in a short period of time is needed for a susceptible individual to contract infection. We carry out numerical simulations on real temporal network data to find that bursty activity patterns facilitate epidemic spreading in our model.

Pattern recognition model to estimate intergranular stress corrosion cracking (IGSCC) at crevices and pit sites of 304 SS in BWR environments

International Nuclear Information System (INIS)

Urquidi-Macdonald, Mirna

2004-01-01

Many publications have shown that crack growth rates (CGR) due to intergranular stress corrosion cracking (IGSCC) of metals is dependent on many parameters related to the manufacturing process of the steel and the environment to which the steel is exposed. Those parameters include, but are not restricted to, the concentration of chloride, fluoride, nitrates, and sulfates, pH, fluid velocity, electrochemical potential (ECP), electrolyte conductivity, stress and sensitization applied to the steel during its production and use. It is not well established how combinations of each of these parameters impact the CGR. Many different models and beliefs have been published, resulting in predictions that sometimes disagree with experimental observations. To some extent, the models are the closest to the nature of IGSCC, however, there is not a model that fully describes the entire range of observations, due to the difficulty of the problem. Among the models, the Fracture Environment Model, developed by Macdonald et al., is the most physico-chemical model, accounting for experimental observations in a wide range of environments or ECPs. In this work, we collected experimental data on BWR environments and designed a data mining pattern recognition model to learn from that data. The model was used to generate CGR estimations as a function of ECP on a BWR environment. The results of the predictive model were compared to the Fracture Environment Model predictions. The results from those two models are very close to the experimental observations of the area corresponding to creep and IGSCC controlled by diffusion. At more negative ECPs than the potential corresponding to creep, the pattern recognition predicts an increase of CGR with decreasing ECP, while the Fracture Environment Model predicts the opposite. The results of this comparison confirm that the pattern recognition model covers 3 phenomena: hydrogen embrittlement at very negative ECP, creep at intermediate ECP, and IGSCC

Pattern recognition model to estimate intergranular stress corrosion cracking (IGSCC) at crevices and pit sites of 304 SS in BWR environments

Energy Technology Data Exchange (ETDEWEB)

Urquidi-Macdonald, Mirna [Penn State University, 212 Earth-Engineering Science Building, University Park, PA 16801 (United States)

2004-07-01

Many publications have shown that crack growth rates (CGR) due to intergranular stress corrosion cracking (IGSCC) of metals is dependent on many parameters related to the manufacturing process of the steel and the environment to which the steel is exposed. Those parameters include, but are not restricted to, the concentration of chloride, fluoride, nitrates, and sulfates, pH, fluid velocity, electrochemical potential (ECP), electrolyte conductivity, stress and sensitization applied to the steel during its production and use. It is not well established how combinations of each of these parameters impact the CGR. Many different models and beliefs have been published, resulting in predictions that sometimes disagree with experimental observations. To some extent, the models are the closest to the nature of IGSCC, however, there is not a model that fully describes the entire range of observations, due to the difficulty of the problem. Among the models, the Fracture Environment Model, developed by Macdonald et al., is the most physico-chemical model, accounting for experimental observations in a wide range of environments or ECPs. In this work, we collected experimental data on BWR environments and designed a data mining pattern recognition model to learn from that data. The model was used to generate CGR estimations as a function of ECP on a BWR environment. The results of the predictive model were compared to the Fracture Environment Model predictions. The results from those two models are very close to the experimental observations of the area corresponding to creep and IGSCC controlled by diffusion. At more negative ECPs than the potential corresponding to creep, the pattern recognition predicts an increase of CGR with decreasing ECP, while the Fracture Environment Model predicts the opposite. The results of this comparison confirm that the pattern recognition model covers 3 phenomena: hydrogen embrittlement at very negative ECP, creep at intermediate ECP, and IGSCC

Spiking patterns of a hippocampus model in electric fields

International Nuclear Information System (INIS)

Men Cong; Wang Jiang; Qin Ying-Mei; Wei Xi-Le; Deng Bin; Che Yan-Qiu

2011-01-01

We develop a model of CA3 neurons embedded in a resistive array to mimic the effects of electric fields from a new perspective. Effects of DC and sinusoidal electric fields on firing patterns in CA3 neurons are investigated in this study. The firing patterns can be switched from no firing pattern to burst or from burst to fast periodic firing pattern with the increase of DC electric field intensity. It is also found that the firing activities are sensitive to the frequency and amplitude of the sinusoidal electric field. Different phase-locking states and chaotic firing regions are observed in the parameter space of frequency and amplitude. These findings are qualitatively in accordance with the results of relevant experimental and numerical studies. It is implied that the external or endogenous electric field can modulate the neural code in the brain. Furthermore, it is helpful to develop control strategies based on electric fields to control neural diseases such as epilepsy. (interdisciplinary physics and related areas of science and technology)

Modeling how shark and dolphin skin patterns control transitional wall-turbulence vorticity patterns using spatiotemporal phase reset mechanisms.

Science.gov (United States)

Bandyopadhyay, Promode R; Hellum, Aren M

2014-10-23

Many slow-moving biological systems like seashells and zebrafish that do not contend with wall turbulence have somewhat organized pigmentation patterns flush with their outer surfaces that are formed by underlying autonomous reaction-diffusion (RD) mechanisms. In contrast, sharks and dolphins contend with wall turbulence, are fast swimmers, and have more organized skin patterns that are proud and sometimes vibrate. A nonlinear spatiotemporal analytical model is not available that explains the mechanism underlying control of flow with such proud patterns, despite the fact that shark and dolphin skins are major targets of reverse engineering mechanisms of drag and noise reduction. Comparable to RD, a minimal self-regulation model is given for wall turbulence regeneration in the transitional regime--laterally coupled, diffusively--which, although restricted to pre-breakdown durations and to a plane close and parallel to the wall, correctly reproduces many experimentally observed spatiotemporal organizations of vorticity in both laminar-to-turbulence transitioning and very low Reynolds number but turbulent regions. We further show that the onset of vorticity disorganization is delayed if the skin organization is treated as a spatiotemporal template of olivo-cerebellar phase reset mechanism. The model shows that the adaptation mechanisms of sharks and dolphins to their fluid environment have much in common.

Isospin-dependent properties of asymmetric nuclear matter in relativistic mean-field models

OpenAIRE

Chen, Lie-Wen; Ko, Che Ming; Li, Bao-An

2007-01-01

Using various relativistic mean-field models, including the nonlinear ones with meson field self-interactions, those with density-dependent meson-nucleon couplings, and the point-coupling models without meson fields, we have studied the isospin-dependent bulk and single-particle properties of asymmetric nuclear matter. In particular, we have determined the density dependence of nuclear symmetry energy from these different relativistic mean-field models and compare the results with the constra...

State-Dependence of the Climate Sensitivity in Earth System Models of Intermediate Complexity

Science.gov (United States)

Pfister, Patrik L.; Stocker, Thomas F.

2017-10-01

Growing evidence from general circulation models (GCMs) indicates that the equilibrium climate sensitivity (ECS) depends on the magnitude of forcing, which is commonly referred to as state-dependence. We present a comprehensive assessment of ECS state-dependence in Earth system models of intermediate complexity (EMICs) by analyzing millennial simulations with sustained 2×CO2 and 4×CO2 forcings. We compare different extrapolation methods and show that ECS is smaller in the higher-forcing scenario in 12 out of 15 EMICs, in contrast to the opposite behavior reported from GCMs. In one such EMIC, the Bern3D-LPX model, this state-dependence is mainly due to the weakening sea ice-albedo feedback in the Southern Ocean, which depends on model configuration. Due to ocean-mixing adjustments, state-dependence is only detected hundreds of years after the abrupt forcing, highlighting the need for long model integrations. Adjustments to feedback parametrizations of EMICs may be necessary if GCM intercomparisons confirm an opposite state-dependence.

A plastic damage model with stress triaxiality-dependent hardening

International Nuclear Information System (INIS)

Shen Xinpu; Shen Guoxiao; Zhou Lin

2005-01-01

Emphases of this study were placed on the modelling of plastic damage behaviour of prestressed structural concrete, with special attention being paid to the stress-triaxiality dependent plastic hardening law and the corresponding damage evolution law. A definition of stress triaxiality was proposed and introduced in the model presented here. Drucker-Prager -type plasticity was adopted in the formulation of the plastic damage constitutive equations. Numerical validations were performed for the proposed plasticity-based damage model with a driver subroutine developed in this study. The predicted stress-strain behaviour seems reasonably accurate for the uniaxial tension and uniaxial compression compared with the experimental data reported in references. Numerical calculations of compressions under various hydrostatic stress confinements were carried out in order to validate the stress triaxiality dependent properties of the model. (authors)

An age dependent model for radium metabolism in man.

Science.gov (United States)

Johnson, J R

1983-01-01

The model developed by a Task Group of Committee 2 of ICRP to describe Alkaline Earth Metabolism in Adult Man (ICRP Publication 20) has been modified so that recycling is handled explicitly, and retention in mineral bone is represented by second compartments rather than by the product of a power function and an exponential. This model has been extended to include all ages from birth to adult man, and has been coupled with modified "ICRP" lung and G.I. tract models so that activity in organs can be calculated as functions of time during or after exposures. These activities, and age dependent "specific effective energy" factors, are then used to calculate age dependent dose rates, and dose commitments. This presentation describes this work, with emphasis on the model parameters and results obtained for radium.

Variability in connectivity patterns of fish with ontogenetic migrations: Modelling effects of abiotic and biotic factors

Directory of Open Access Journals (Sweden)

Susanne Eva Tanner

2015-10-01

Full Text Available Connectivity is a critical property of marine fish populations as it drives population replenishment, determines colonization patterns and the resilience of populations to harvest. Understanding connectivity patterns is particularly important in species that present ontogenetic migrations and segregated habitat use during their life history, such as marine species with estuarine nursery areas. Albeit challenging, fish movement can be estimated and quantified using different methodologies depending on the life history stages of interest (e.g. biophysical modelling, otolith chemistry, genetic markers. Relative contributions from estuarine nursery areas to the adult coastal populations were determined using otolith elemental composition and maximum likelihood estimation for four commercially important species (Dicentrarchus labrax, Plathichtys flesus, Solea senegalensis and Solea solea and showed high interannual variability. Here, the effects of abiotic and biotic factors on the observed variability in connectivity rates and extent between estuarine juvenile and coastal adult subpopulations are investigated using generalized linear models (GLM and generalized mixed models (GMM. Abiotic factors impacting both larval and juvenile life history stages are included in the models (e.g. wind force and direction, NAO, water temperature while biotic factors relative to the estuarine residency of juvenile fish are evaluated (e.g. juvenile density, food availability. Factors contributing most to the observed variability in connectivity rates are singled out and compared among species. General trends are identified and results area discussed in the general context of identifying potential management frameworks applicable to different life stages and which may prove useful for ontogenetically migrating species.

Global asymptotic stability of density dependent integral population projection models.

Science.gov (United States)

Rebarber, Richard; Tenhumberg, Brigitte; Townley, Stuart

2012-02-01

Many stage-structured density dependent populations with a continuum of stages can be naturally modeled using nonlinear integral projection models. In this paper, we study a trichotomy of global stability result for a class of density dependent systems which include a Platte thistle model. Specifically, we identify those systems parameters for which zero is globally asymptotically stable, parameters for which there is a positive asymptotically stable equilibrium, and parameters for which there is no asymptotically stable equilibrium. Copyright © 2011 Elsevier Inc. All rights reserved.

Muscle activity pattern dependent pain development and alleviation

DEFF Research Database (Denmark)

Sjøgaard, Gisela; Søgaard, Karen

2014-01-01

Muscle activity is for decades considered to provide health benefits irrespectively of the muscle activity pattern performed and whether it is during e.g. sports, transportation, or occupational work tasks. Accordingly, the international recommendations for public health-promoting physical activity...... do not distinguish between occupational and leisure time physical activity. However, in this body of literature, attention has not been paid to the extensive documentation on occupational physical activity imposing a risk of impairment of health - in particular musculoskeletal health in terms...... during physical activities at leisure and sport the motor recruitment patterns are more dynamic including regularly relatively high muscle forces - also activating type 2 muscles fibers - as well as periods of full relaxation even of the type 1 muscle fibers. Such activity is unrelated to muscle pain...

Micromechanical modeling of rate-dependent behavior of Connective tissues.

Science.gov (United States)

Fallah, A; Ahmadian, M T; Firozbakhsh, K; Aghdam, M M

2017-03-07

In this paper, a constitutive and micromechanical model for prediction of rate-dependent behavior of connective tissues (CTs) is presented. Connective tissues are considered as nonlinear viscoelastic material. The rate-dependent behavior of CTs is incorporated into model using the well-known quasi-linear viscoelasticity (QLV) theory. A planar wavy representative volume element (RVE) is considered based on the tissue microstructure histological evidences. The presented model parameters are identified based on the available experiments in the literature. The presented constitutive model introduced to ABAQUS by means of UMAT subroutine. Results show that, monotonic uniaxial test predictions of the presented model at different strain rates for rat tail tendon (RTT) and human patellar tendon (HPT) are in good agreement with experimental data. Results of incremental stress-relaxation test are also presented to investigate both instantaneous and viscoelastic behavior of connective tissues. Copyright © 2017 Elsevier Ltd. All rights reserved.

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

Science.gov (United States)

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

2014-09-12

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

Climate change induced rainfall patterns affect wheat productivity and agroecosystem functioning dependent on soil types

Science.gov (United States)

Tabi Tataw, James; Baier, Fabian; Krottenthaler, Florian; Pachler, Bernadette; Schwaiger, Elisabeth; Whylidal, Stefan; Formayer, Herbert; Hösch, Johannes; Baumgarten, Andreas; Zaller, Johann G.

2014-05-01

Wheat is a crop of global importance supplying more than half of the world's population with carbohydrates. We examined, whether climate change induced rainfall patterns towards less frequent but heavier events alter wheat agroecosystem productivity and functioning under three different soil types. Therefore, in a full-factorial experiment Triticum aestivum L. was cultivated in 3 m2 lysimeter plots containing the soil types sandy calcaric phaeozem, gleyic phaeozem or calcic chernozem. Prognosticated rainfall patterns based on regionalised climate change model calculations were compared with current long-term rainfall patterns; each treatment combination was replicated three times. Future rainfall patterns significantly reduced wheat growth and yield, reduced the leaf area index, accelerated crop development, reduced arbuscular mycorrhizal fungi colonisation of roots, increased weed density and the stable carbon isotope signature (δ13C) of both old and young wheat leaves. Different soil types affected wheat growth and yield, ecosystem root production as well as weed abundance and biomass. The interaction between climate and soil type was significant only for the harvest index. Our results suggest that even slight changes in rainfall patterns can significantly affect the functioning of wheat agroecosystems. These rainfall effects seemed to be little influenced by soil types suggesting more general impacts of climate change across different soil types. Wheat production under future conditions will likely become more challenging as further concurrent climate change factors become prevalent.

Physical optics modeling of modal patterns in a crossed porro prism resonator

CSIR Research Space (South Africa)

Litvin, IA

2006-07-01

Full Text Available A physical optics model is proposed to describe the transverse modal patterns in crossed Porro prism resonators. The model departs from earlier attempts in that the prisms are modeled as non-classical rotating elements with amplitude and phase...

Energy based model for temperature dependent behavior of ferromagnetic materials

International Nuclear Information System (INIS)

Sah, Sanjay; Atulasimha, Jayasimha

2017-01-01

An energy based model for temperature dependent anhysteretic magnetization curves of ferromagnetic materials is proposed and benchmarked against experimental data. This is based on the calculation of macroscopic magnetic properties by performing an energy weighted average over all possible orientations of the magnetization vector. Most prior approaches that employ this method are unable to independently account for the effect of both inhomogeneity and temperature in performing the averaging necessary to model experimental data. Here we propose a way to account for both effects simultaneously and benchmark the model against experimental data from ~5 K to ~300 K for two different materials in both annealed (fewer inhomogeneities) and deformed (more inhomogeneities) samples. This demonstrates that this framework is well suited to simulate temperature dependent experimental magnetic behavior. - Highlights: • Energy based model for temperature dependent ferromagnetic behavior. • Simultaneously accounts for effect of temperature and inhomogeneities. • Benchmarked against experimental data from 5 K to 300 K.

Stochastic time-dependent vehicle routing problem: Mathematical models and ant colony algorithm

Directory of Open Access Journals (Sweden)

Zhengyu Duan

2015-11-01

Full Text Available This article addresses the stochastic time-dependent vehicle routing problem. Two mathematical models named robust optimal schedule time model and minimum expected schedule time model are proposed for stochastic time-dependent vehicle routing problem, which can guarantee delivery within the time windows of customers. The robust optimal schedule time model only requires the variation range of link travel time, which can be conveniently derived from historical traffic data. In addition, the robust optimal schedule time model based on robust optimization method can be converted into a time-dependent vehicle routing problem. Moreover, an ant colony optimization algorithm is designed to solve stochastic time-dependent vehicle routing problem. As the improvements in initial solution and transition probability, ant colony optimization algorithm has a good performance in convergence. Through computational instances and Monte Carlo simulation tests, robust optimal schedule time model is proved to be better than minimum expected schedule time model in computational efficiency and coping with the travel time fluctuations. Therefore, robust optimal schedule time model is applicable in real road network.

Unified thalamic model generates multiple distinct oscillations with state-dependent entrainment by stimulation.

Directory of Open Access Journals (Sweden)

Guoshi Li

2017-10-01

Full Text Available The thalamus plays a critical role in the genesis of thalamocortical oscillations, yet the underlying mechanisms remain elusive. To understand whether the isolated thalamus can generate multiple distinct oscillations, we developed a biophysical thalamic model to test the hypothesis that generation of and transition between distinct thalamic oscillations can be explained as a function of neuromodulation by acetylcholine (ACh and norepinephrine (NE and afferent synaptic excitation. Indeed, the model exhibited four distinct thalamic rhythms (delta, sleep spindle, alpha and gamma oscillations that span the physiological states corresponding to different arousal levels from deep sleep to focused attention. Our simulation results indicate that generation of these distinct thalamic oscillations is a result of both intrinsic oscillatory cellular properties and specific network connectivity patterns. We then systematically varied the ACh/NE and input levels to generate a complete map of the different oscillatory states and their transitions. Lastly, we applied periodic stimulation to the thalamic network and found that entrainment of thalamic oscillations is highly state-dependent. Our results support the hypothesis that ACh/NE modulation and afferent excitation define thalamic oscillatory states and their response to brain stimulation. Our model proposes a broader and more central role of the thalamus in the genesis of multiple distinct thalamo-cortical rhythms than previously assumed.

SensibleSleep: A Bayesian Model for Learning Sleep Patterns from Smartphone Events

DEFF Research Database (Denmark)

Cuttone, Andrea; Bækgaard, Per; Sekara, Vedran

2017-01-01

We propose a Bayesian model for extracting sleep patterns from smartphone events. Our method is able to identify individuals' daily sleep periods and their evolution over time, and provides an estimation of the probability of sleep and wake transitions. The model is fitted to more than 400...... to quantify uncertainty and encode prior knowledge about sleep patterns. Compared with existing smartphone-based systems, our method requires only screen on/off events, and is therefore much less intrusive in terms of privacy and more battery-efficient....

Combining satellite data and appropriate objective functions for improved spatial pattern performance of a distributed hydrologic model

Science.gov (United States)

Demirel, Mehmet C.; Mai, Juliane; Mendiguren, Gorka; Koch, Julian; Samaniego, Luis; Stisen, Simon

2018-02-01

Satellite-based earth observations offer great opportunities to improve spatial model predictions by means of spatial-pattern-oriented model evaluations. In this study, observed spatial patterns of actual evapotranspiration (AET) are utilised for spatial model calibration tailored to target the pattern performance of the model. The proposed calibration framework combines temporally aggregated observed spatial patterns with a new spatial performance metric and a flexible spatial parameterisation scheme. The mesoscale hydrologic model (mHM) is used to simulate streamflow and AET and has been selected due to its soil parameter distribution approach based on pedo-transfer functions and the build in multi-scale parameter regionalisation. In addition two new spatial parameter distribution options have been incorporated in the model in order to increase the flexibility of root fraction coefficient and potential evapotranspiration correction parameterisations, based on soil type and vegetation density. These parameterisations are utilised as they are most relevant for simulated AET patterns from the hydrologic model. Due to the fundamental challenges encountered when evaluating spatial pattern performance using standard metrics, we developed a simple but highly discriminative spatial metric, i.e. one comprised of three easily interpretable components measuring co-location, variation and distribution of the spatial data. The study shows that with flexible spatial model parameterisation used in combination with the appropriate objective functions, the simulated spatial patterns of actual evapotranspiration become substantially more similar to the satellite-based estimates. Overall 26 parameters are identified for calibration through a sequential screening approach based on a combination of streamflow and spatial pattern metrics. The robustness of the calibrations is tested using an ensemble of nine calibrations based on different seed numbers using the shuffled complex

hESC Differentiation toward an Autonomic Neuronal Cell Fate Depends on Distinct Cues from the Co-Patterning Vasculature

Directory of Open Access Journals (Sweden)

Lisette M. Acevedo

2015-06-01

Full Text Available To gain insight into the cellular and molecular cues that promote neurovascular co-patterning at the earliest stages of human embryogenesis, we developed a human embryonic stem cell model to mimic the developing epiblast. Contact of ectoderm-derived neural cells with mesoderm-derived vasculature is initiated via the neural crest (NC, not the neural tube (NT. Neurovascular co-patterning then ensues with specification of NC toward an autonomic fate requiring vascular endothelial cell (EC-secreted nitric oxide (NO and direct contact with vascular smooth muscle cells (VSMCs via T-cadherin-mediated homotypic interactions. Once a neurovascular template has been established, NT-derived central neurons then align themselves with the vasculature. Our findings reveal that, in early human development, the autonomic nervous system forms in response to distinct molecular cues from VSMCs and ECs, providing a model for how other developing lineages might coordinate their co-patterning.

Data Mining and Pattern Recognition Models for Identifying Inherited Diseases: Challenges and Implications

OpenAIRE

Iddamalgoda, Lahiru; Das, Partha S.; Aponso, Achala; Sundararajan, Vijayaraghava S.; Suravajhala, Prashanth; Valadi, Jayaraman K.

2016-01-01

Data mining and pattern recognition methods reveal interesting findings in genetic studies, especially on how the genetic makeup is associated with inherited diseases. Although researchers have proposed various data mining models for biomedical approaches, there remains a challenge in accurately prioritizing the single nucleotide polymorphisms (SNP) associated with the disease. In this commentary, we review the state-of-art data mining and pattern recognition models for identifying inherited ...

Modeling the temperature dependence of thermophysical properties: Study on the effect of temperature dependence for RFA.

Science.gov (United States)

Watanabe, Hiroki; Kobayashi, Yo; Hashizume, Makoto; Fujie, Masakatsu G

2009-01-01

Radio frequency ablation (RFA) has increasingly been used over the past few years and RFA treatment is minimally invasive for patients. However, it is difficult for operators to control the precise formation of coagulation zones due to inadequate imaging modalities. With this in mind, an ablation system using numerical simulation to analyze the temperature distribution of the organ is needed to overcome this deficiency. The objective of our work is to develop a temperature dependent thermophysical liver model. First, an overview is given of the development of the thermophysical liver model. Second, a simulation to evaluate the effect of temperature dependence of the thermophysical properties of the liver is explained. Finally, the result of the simulation, which indicated that the temperature dependence of thermophysical properties accounts for temperature differences influencing the accuracy of RFA treatment is described.

System Identification for Nonlinear FOPDT Model with Input-Dependent Dead-Time

DEFF Research Database (Denmark)

Sun, Zhen; Yang, Zhenyu

2011-01-01

An on-line iterative method of system identification for a kind of nonlinear FOPDT system is proposed in the paper. The considered nonlinear FOPDT model is an extension of the standard FOPDT model by means that its dead time depends on the input signal and the other parameters are time dependent....

Model dependence of energy-weighted sum rules

International Nuclear Information System (INIS)

Kirson, M.W.

1977-01-01

The contribution of the nucleon-nucleon interaction to energy-weighted sum rules for electromagnetic multipole transitions is investigated. It is found that only isoscalar electric transitions might have model-independent energy-weighted sum rules. For these transitions, explicit momentum and angular momentum dependence of the nuclear force give rise to corrections to the sum rule which are found to be negligibly small, thus confirming the model independence of these specific sum rules. These conclusions are unaffected by correlation effects. (author)

Simple model for polar cap convection patterns and generation of theta auroras

International Nuclear Information System (INIS)

Lyons, L.R.

1985-01-01

The simple addition of a uniform interplanetary magnetic field and the Earth's dipole magnetic field is used to evaluate electric field convection patterns over the polar caps that result from solar wind flow across open geomagnetic field lines. This model is found to account for observed polar-cap convection patterns as a function of the interplanetary magnetic field components B/sub y/ and B/sub z/. In particular, the model offers an explanation for sunward and antisunward convection over the polar caps for B/sub z/>0. Observed field-aligned current patterns within the polar cap and observed auroral arcs across the polar cap are also explained by the model. In addition, the model gives several predictions concerning the polar cap that should be testable. Effects of solar wind pressure and magnetospheric currents on magnetospheric electric and magnetic fields are neglected. That observed polar cap features are reproduced suggests that the neglected effects do not modify the large-scale topology of magnetospheric electric and magnetic fields along open polar cap field lines. Of course, the neglected effects significantly modify the magnetic geometry, so that the results of this paper are not quantitatively realistic and many details may be incorrect. Nevertheless, the model provides a simple explanation for many qualitative features of polar cap convection

Multivariate operational risk: dependence modelling with Lévy copulas

OpenAIRE

Böcker, K. and Klüppelberg, C.

2015-01-01

Simultaneous modelling of operational risks occurring in different event type/business line cells poses the challenge for operational risk quantification. Invoking the new concept of L´evy copulas for dependence modelling yields simple approximations of high quality for multivariate operational VAR.

Vector spin modeling for magnetic tunnel junctions with voltage dependent effects

International Nuclear Information System (INIS)

Manipatruni, Sasikanth; Nikonov, Dmitri E.; Young, Ian A.

2014-01-01

Integration and co-design of CMOS and spin transfer devices requires accurate vector spin conduction modeling of magnetic tunnel junction (MTJ) devices. A physically realistic model of the MTJ should comprehend the spin torque dynamics of nanomagnet interacting with an injected vector spin current and the voltage dependent spin torque. Vector spin modeling allows for calculation of 3 component spin currents and potentials along with the charge currents/potentials in non-collinear magnetic systems. Here, we show 4-component vector spin conduction modeling of magnetic tunnel junction devices coupled with spin transfer torque in the nanomagnet. Nanomagnet dynamics, voltage dependent spin transport, and thermal noise are comprehended in a self-consistent fashion. We show comparison of the model with experimental magnetoresistance (MR) of MTJs and voltage degradation of MR with voltage. Proposed model enables MTJ circuit design that comprehends voltage dependent spin torque effects, switching error rates, spin degradation, and back hopping effects

Global patterns in lake ecosystem responses to warming based on the temperature dependence of metabolism.

Science.gov (United States)

Kraemer, Benjamin M; Chandra, Sudeep; Dell, Anthony I; Dix, Margaret; Kuusisto, Esko; Livingstone, David M; Schladow, S Geoffrey; Silow, Eugene; Sitoki, Lewis M; Tamatamah, Rashid; McIntyre, Peter B

2017-05-01

Climate warming is expected to have large effects on ecosystems in part due to the temperature dependence of metabolism. The responses of metabolic rates to climate warming may be greatest in the tropics and at low elevations because mean temperatures are warmer there and metabolic rates respond exponentially to temperature (with exponents >1). However, if warming rates are sufficiently fast in higher latitude/elevation lakes, metabolic rate responses to warming may still be greater there even though metabolic rates respond exponentially to temperature. Thus, a wide range of global patterns in the magnitude of metabolic rate responses to warming could emerge depending on global patterns of temperature and warming rates. Here we use the Boltzmann-Arrhenius equation, published estimates of activation energy, and time series of temperature from 271 lakes to estimate long-term (1970-2010) changes in 64 metabolic processes in lakes. The estimated responses of metabolic processes to warming were usually greatest in tropical/low-elevation lakes even though surface temperatures in higher latitude/elevation lakes are warming faster. However, when the thermal sensitivity of a metabolic process is especially weak, higher latitude/elevation lakes had larger responses to warming in parallel with warming rates. Our results show that the sensitivity of a given response to temperature (as described by its activation energy) provides a simple heuristic for predicting whether tropical/low-elevation lakes will have larger or smaller metabolic responses to warming than higher latitude/elevation lakes. Overall, we conclude that the direct metabolic consequences of lake warming are likely to be felt most strongly at low latitudes and low elevations where metabolism-linked ecosystem services may be most affected. © 2016 John Wiley & Sons Ltd.

Colour dependence of zodiacal light models

Science.gov (United States)

Giese, R. H.; Hanner, M. S.; Leinert, C.

1973-01-01

Colour models of the zodiacal light in the ecliptic have been calculated for both dielectric and metallic particles in the sub-micron and micron size range. Two colour ratios were computed, a blue ratio and a red ratio. The models with a size distribution proportional to s to the -2.5 power ds (where s is the particle radius) generally show a colour close to the solar colour and almost independent of elongation. Especially in the blue colour ratio there is generally no significant dependence on the lower cutoff size (0.1-1 micron). The main feature of absorbing particles is a reddening at small elongations. The models for size distributions proportional to s to the -4 power ds show larger departures from solar colour and more variation with model parameters. Colour measurements, including red and near infra-red, therefore are useful to distinguish between flat and steep size spectra and to verify the presence of slightly absorbing particles.

Pattern of alveolar bone loss and reliability of measurements with the radiographic technique

International Nuclear Information System (INIS)

Rise, J.; Albandar, J.M.

1988-01-01

The purposes of this paper were to study the pattern of bone loss among different teeth at the individual level and to study the effect of using different aggregated units of analysis on measurement error. Bone loss was assessed in standardized periapical radiographs from 293 subjects (18-68 years), and the mean bone loss score for each tooth type was calculated. These were then correlated by means of factor analysis to study the bone loss pattern. Reliability (measurement error) was studied by the internal consistency and the test-retest methods. The pattern of bone loss showed a unidimensional pattern, indicating that any tooth will work equally well as a dependent variable for epidemiologic descriptive purposes. However, a more thorough analysis also showed a multidimensional pattern in terms of four dimensions, which correspond to four tooth groups: incisors, upper premolars, lower premolars and molars. The four dimensions accounted for 80% of the toal variance. The multidimensional pattern may be important for the modeling of bone loss; thus different models may explain the four dimension (indices) used as dependent variables. The reliability (internal consistency) of the four indices was satisfactory. By the test-retest method, reliability was higher when the more aggregated unit (the individual) was used

The Role of Different Plant Soil-Water Feedbacks in Models of Dryland Vegetation Patterns

Science.gov (United States)

Silber, M.; Bonetti, S.; Gandhi, P.; Gowda, K.; Iams, S.; Porporato, A. M.

2017-12-01

Understanding the processes underlying the formation of regular vegetation patterns in arid and semi-arid regions is important to assessing desertification risk under increasing anthropogenic pressure. Various modeling frameworks have been proposed, which are all capable of generating similar patterns through self-organizing mechanisms that stem from assumptions about plant feedbacks on surface/subsurface water transport. We critically discuss a hierarchy of hydrology-vegetation models for the coupled dynamics of surface water, soil moisture, and vegetation biomass on a hillslope. We identify distinguishing features and trends for the periodic traveling wave solutions when there is an imposed idealized topography and make some comparisons to satellite images of large-scale banded vegetation patterns in drylands of Africa, Australia and North America. This work highlights the potential for constraining models by considerations of where the patterns may lie on a landscape, such as whether on a ridge or in a valley.

Cell-Cell Contact Area Affects Notch Signaling and Notch-Dependent Patterning.

Science.gov (United States)

Shaya, Oren; Binshtok, Udi; Hersch, Micha; Rivkin, Dmitri; Weinreb, Sheila; Amir-Zilberstein, Liat; Khamaisi, Bassma; Oppenheim, Olya; Desai, Ravi A; Goodyear, Richard J; Richardson, Guy P; Chen, Christopher S; Sprinzak, David

2017-03-13

During development, cells undergo dramatic changes in their morphology. By affecting contact geometry, these morphological changes could influence cellular communication. However, it has remained unclear whether and how signaling depends on contact geometry. This question is particularly relevant for Notch signaling, which coordinates neighboring cell fates through direct cell-cell signaling. Using micropatterning with a receptor trans-endocytosis assay, we show that signaling between pairs of cells correlates with their contact area. This relationship extends across contact diameters ranging from micrometers to tens of micrometers. Mathematical modeling predicts that dependence of signaling on contact area can bias cellular differentiation in Notch-mediated lateral inhibition processes, such that smaller cells are more likely to differentiate into signal-producing cells. Consistent with this prediction, analysis of developing chick inner ear revealed that ligand-producing hair cell precursors have smaller apical footprints than non-hair cells. Together, these results highlight the influence of cell morphology on fate determination processes. Copyright © 2017 Elsevier Inc. All rights reserved.

Intercohort density dependence drives brown trout habitat selection

Science.gov (United States)

Ayllón, Daniel; Nicola, Graciela G.; Parra, Irene; Elvira, Benigno; Almodóvar, Ana

2013-01-01

Habitat selection can be viewed as an emergent property of the quality and availability of habitat but also of the number of individuals and the way they compete for its use. Consequently, habitat selection can change across years due to fluctuating resources or to changes in population numbers. However, habitat selection predictive models often do not account for ecological dynamics, especially density dependent processes. In stage-structured population, the strength of density dependent interactions between individuals of different age classes can exert a profound influence on population trajectories and evolutionary processes. In this study, we aimed to assess the effects of fluctuating densities of both older and younger competing life stages on the habitat selection patterns (described as univariate and multivariate resource selection functions) of young-of-the-year, juvenile and adult brown trout Salmo trutta. We observed all age classes were selective in habitat choice but changed their selection patterns across years consistently with variations in the densities of older but not of younger age classes. Trout of an age increased selectivity for positions highly selected by older individuals when their density decreased, but this pattern did not hold when the density of younger age classes varied. It suggests that younger individuals are dominated by older ones but can expand their range of selected habitats when density of competitors decreases, while older trout do not seem to consider the density of younger individuals when distributing themselves even though they can negatively affect their final performance. Since these results may entail critical implications for conservation and management practices based on habitat selection models, further research should involve a wider range of river typologies and/or longer time frames to fully understand the patterns of and the mechanisms underlying the operation of density dependence on brown trout habitat

An integrated vendor-buyer model with stock-dependent demand

DEFF Research Database (Denmark)

Sajadieh, Mohsen S.; Thorstenson, Anders; Akbari Jokar, Mohammad R.

in a display area. The end-customer demand is assumed to be positively dependent on the amount of items shown in the display area. With the proposed model we determine the buyer's optimal shipment quantity and number of shipments, as well as the vendor's optimal production batch. The objective is to maximize...... total supply chain profit. The numerical analysis shows that it is more profitable for the buyer and the vendor to cooperate in situations when the demand is more stock-dependent. The analysis also shows the effect of double marginalization in this integrated vendor-buyer model....

An Integrated Vendor-Buyer Model with Stock-Dependent Demand

DEFF Research Database (Denmark)

Thorstenson, Anders; Sajadieh, Mohsen S.; Akbari Jokar, Mohammad R.

2009-01-01

in the buyer's warehouse. The demand is assumed to be positively dependent on the amount of items shown in the display area. The proposed model determines the buyer's optimal shipment quantity and number of shipments, as well as the vendor's optimal production batch. The objective is to maximize total supply......-chain profit. The numerical analysis shows that as long as the maximum display area is not used, it is more valuable for the buyer and the vendor to cooperate in situations when the demand is more stock- dependent. It also shows the effect of double marginalization in this integrated vendor-buyer model....

Isospin-dependent properties of asymmetric nuclear matter in relativistic mean field models

Science.gov (United States)

Chen, Lie-Wen; Ko, Che Ming; Li, Bao-An

2007-11-01

Using various relativistic mean-field models, including nonlinear ones with meson field self-interactions, models with density-dependent meson-nucleon couplings, and point-coupling models without meson fields, we have studied the isospin-dependent bulk and single-particle properties of asymmetric nuclear matter. In particular, we have determined the density dependence of nuclear symmetry energy from these different relativistic mean-field models and compared the results with the constraints recently extracted from analyses of experimental data on isospin diffusion and isotopic scaling in intermediate energy heavy-ion collisions as well as from measured isotopic dependence of the giant monopole resonances in even-A Sn isotopes. Among the 23 parameter sets in the relativistic mean-field model that are commonly used for nuclear structure studies, only a few are found to give symmetry energies that are consistent with the empirical constraints. We have also studied the nuclear symmetry potential and the isospin splitting of the nucleon effective mass in isospin asymmetric nuclear matter. We find that both the momentum dependence of the nuclear symmetry potential at fixed baryon density and the isospin splitting of the nucleon effective mass in neutron-rich nuclear matter depend not only on the nuclear interactions but also on the definition of the nucleon optical potential.

Modeling Spatial Dependence of Rainfall Extremes Across Multiple Durations

Science.gov (United States)

Le, Phuong Dong; Leonard, Michael; Westra, Seth

2018-03-01

Determining the probability of a flood event in a catchment given that another flood has occurred in a nearby catchment is useful in the design of infrastructure such as road networks that have multiple river crossings. These conditional flood probabilities can be estimated by calculating conditional probabilities of extreme rainfall and then transforming rainfall to runoff through a hydrologic model. Each catchment's hydrological response times are unlikely to be the same, so in order to estimate these conditional probabilities one must consider the dependence of extreme rainfall both across space and across critical storm durations. To represent these types of dependence, this study proposes a new approach for combining extreme rainfall across different durations within a spatial extreme value model using max-stable process theory. This is achieved in a stepwise manner. The first step defines a set of common parameters for the marginal distributions across multiple durations. The parameters are then spatially interpolated to develop a spatial field. Storm-level dependence is represented through the max-stable process for rainfall extremes across different durations. The dependence model shows a reasonable fit between the observed pairwise extremal coefficients and the theoretical pairwise extremal coefficient function across all durations. The study demonstrates how the approach can be applied to develop conditional maps of the return period and return level across different durations.

Age-dependent reliability model considering effects of maintenance and working conditions

International Nuclear Information System (INIS)

Martorell, Sebastian; Sanchez, Ana; Serradell, Vicente

1999-01-01

Nowadays, there is some doubt about building new nuclear power plants (NPPs). Instead, there is a growing interest in analyzing the possibility to extend current NPP operation, where life management programs play an important role. The evolution of the NPP safety depends on the evolution of the reliability of its safety components, which, in turn, is a function of their age along the NPP operational life. In this paper, a new age-dependent reliability model is presented, which includes parameters related to surveillance and maintenance effectiveness and working conditions of the equipment, both environmental and operational. This model may be used to support NPP life management and life extension programs, by improving or optimizing surveillance and maintenance tasks using risk and cost models based on such an age-dependent reliability model. The results of the sensitivity study in the example application show that the selection of the most appropriate maintenance strategy would directly depend on the previous parameters. Then, very important differences are expected to appear under certain circumstances, particularly, in comparison with other models that do not consider maintenance effectiveness and working conditions simultaneously

Traffic Management as a Service: The Traffic Flow Pattern Classification Problem

Directory of Open Access Journals (Sweden)

Carlos T. Calafate

2015-01-01

Full Text Available Intelligent Transportation System (ITS technologies can be implemented to reduce both fuel consumption and the associated emission of greenhouse gases. However, such systems require intelligent and effective route planning solutions to reduce travel time and promote stable traveling speeds. To achieve such goal these systems should account for both estimated and real-time traffic congestion states, but obtaining reliable traffic congestion estimations for all the streets/avenues in a city for the different times of the day, for every day in a year, is a complex task. Modeling such a tremendous amount of data can be time-consuming and, additionally, centralized computation of optimal routes based on such time-dependencies has very high data processing requirements. In this paper we approach this problem through a heuristic to considerably reduce the modeling effort while maintaining the benefits of time-dependent traffic congestion modeling. In particular, we propose grouping streets by taking into account real traces describing the daily traffic pattern. The effectiveness of this heuristic is assessed for the city of Valencia, Spain, and the results obtained show that it is possible to reduce the required number of daily traffic flow patterns by a factor of 4210 while maintaining the essence of time-dependent modeling requirements.

Temperature-dependent behaviours are genetically variable in the nematode Caenorhabditis briggsae.

Science.gov (United States)

Stegeman, Gregory W; de Mesquita, Matthew Bueno; Ryu, William S; Cutter, Asher D

2013-03-01

Temperature-dependent behaviours in Caenorhabditis elegans, such as thermotaxis and isothermal tracking, are complex behavioural responses that integrate sensation, foraging and learning, and have driven investigations to discover many essential genetic and neural pathways. The ease of manipulation of the Caenorhabditis model system also has encouraged its application to comparative analyses of phenotypic evolution, particularly contrasts of the classic model C. elegans with C. briggsae. And yet few studies have investigated natural genetic variation in behaviour in any nematode. Here we measure thermotaxis and isothermal tracking behaviour in genetically distinct strains of C. briggsae, further motivated by the latitudinal differentiation in C. briggsae that is associated with temperature-dependent fitness differences in this species. We demonstrate that C. briggsae performs thermotaxis and isothermal tracking largely similar to that of C. elegans, with a tendency to prefer its rearing temperature. Comparisons of these behaviours among strains reveal substantial heritable natural variation within each species that corresponds to three general patterns of behavioural response. However, intraspecific genetic differences in thermal behaviour often exceed interspecific differences. These patterns of temperature-dependent behaviour motivate further development of C. briggsae as a model system for dissecting the genetic underpinnings of complex behavioural traits.

Current Trends of Drug Resistance Patterns of Acinetobacter baumannii Infection in Blood Transfusion-dependent Thalassemia Patients.

Science.gov (United States)

Almani, Suhail Ahmed; Naseer, Ali; Maheshwari, Sanjay Kumar; Maroof, Pir; Naseer, Raza; Khoharo, Haji Khan

2017-01-01

The present study aimed to evaluate the current trends of drug resistance patterns of Acinetobacter baumannii infection in blood transfusion-dependent thalassemia patients. This study was a cross sectional study, conducted at the Liaquat University of Medical and Health Sciences, Jamshoro/Hyderabad, Sindh, Pakistan from October 2014 to January 2016. Of 921 blood samples, A. baumannii strains were isolated from 100 blood samples. Blood samples were processed for the isolation, identification, and drugs sensitivity as per the Clinical and Laboratory Standards Institute. A. baumannii strains were identified by microbiological methods and Gram's staining. API 20 E kit (Biomeriuex, USA) was also used for identification. Data were analyzed on Statisti × 8.1 (USA). Mean ± standard deviation age was 11.5 ± 2.8 years. Nearly 70% were male and 30% were female ( P = 0.0001). Of 921 blood transfusion-dependent thalassemia patients, 100 (10.8%) patients showed growth of A. baumannii . Drug resistance was observed against the ceftazidime, cefixime, cefepime, imipenem, meropenem, amikacin, minocycline, tigecycline, and tazocin except for the colistin. The present study reports drug-resistant A. baumannii in blood transfusion-dependent thalassemia patients. National multicenter studies are recommended to estimate the size of the problem.

Competitive STDP Learning of Overlapping Spatial Patterns.

Science.gov (United States)

Krunglevicius, Dalius

2015-08-01

Spike-timing-dependent plasticity (STDP) is a set of Hebbian learning rules firmly based on biological evidence. It has been demonstrated that one of the STDP learning rules is suited for learning spatiotemporal patterns. When multiple neurons are organized in a simple competitive spiking neural network, this network is capable of learning multiple distinct patterns. If patterns overlap significantly (i.e., patterns are mutually inclusive), however, competition would not preclude trained neuron's responding to a new pattern and adjusting synaptic weights accordingly. This letter presents a simple neural network that combines vertical inhibition and Euclidean distance-dependent synaptic strength factor. This approach helps to solve the problem of pattern size-dependent parameter optimality and significantly reduces the probability of a neuron's forgetting an already learned pattern. For demonstration purposes, the network was trained for the first ten letters of the Braille alphabet.

Inclusion of temperature dependence of fission barriers in statistical model calculations

International Nuclear Information System (INIS)

Newton, J.O.; Popescu, D.G.; Leigh, J.R.

1990-08-01

The temperature dependence of fission barriers has been interpolated from the results of recent theoretical calculations and included in the statistical model code PACE2. It is shown that the inclusion of temperature dependence causes significant changes to the values of the statistical model parameters deduced from fits to experimental data. 21 refs., 2 figs

Similar expression patterns of bestrophin-4 and cGMP dependent Ca2+-activated chloride channel activity in the vasculature

DEFF Research Database (Denmark)

Bouzinova, Elena V.; Larsen, Per; Matchkov, Vladimir

2008-01-01

(abstract by Matchkov et. al) that siRNA mediated downregulation of bestrophin-4 is associated with the disappearance of a recently demonstrated2 cGMP-dependent Ca2+-activated Cl- current in vascular smooth muscle cells (SMCs). Here we study the distribution of bestrophin-4-and cGMP dependent Cl- channel...... expressed epitope) Western blot detected a ~65 kDa band in cell lysates from rat mesenteric small arteries and aorta, which was not seen in pulmonary arteries and when preincubated with the immunizing peptide. The distribution of bestrophin-4 mRNA and protein has a pattern similar to the cGMP-dependent Cl......- current in SMCs of different origins. Immunohistochemistry identified bestrophin-4 both in endothelial and SMCs of the vascular tree in the brain, heart, kidney and mesentery, but not in the lungs. We suggest that bestrophin-4 is important for the cGMP dependent, Ca2+ activated Cl- conductance in many...

Combining satellite data and appropriate objective functions for improved spatial pattern performance of a distributed hydrologic model

Directory of Open Access Journals (Sweden)

M. C. Demirel

2018-02-01

Full Text Available Satellite-based earth observations offer great opportunities to improve spatial model predictions by means of spatial-pattern-oriented model evaluations. In this study, observed spatial patterns of actual evapotranspiration (AET are utilised for spatial model calibration tailored to target the pattern performance of the model. The proposed calibration framework combines temporally aggregated observed spatial patterns with a new spatial performance metric and a flexible spatial parameterisation scheme. The mesoscale hydrologic model (mHM is used to simulate streamflow and AET and has been selected due to its soil parameter distribution approach based on pedo-transfer functions and the build in multi-scale parameter regionalisation. In addition two new spatial parameter distribution options have been incorporated in the model in order to increase the flexibility of root fraction coefficient and potential evapotranspiration correction parameterisations, based on soil type and vegetation density. These parameterisations are utilised as they are most relevant for simulated AET patterns from the hydrologic model. Due to the fundamental challenges encountered when evaluating spatial pattern performance using standard metrics, we developed a simple but highly discriminative spatial metric, i.e. one comprised of three easily interpretable components measuring co-location, variation and distribution of the spatial data. The study shows that with flexible spatial model parameterisation used in combination with the appropriate objective functions, the simulated spatial patterns of actual evapotranspiration become substantially more similar to the satellite-based estimates. Overall 26 parameters are identified for calibration through a sequential screening approach based on a combination of streamflow and spatial pattern metrics. The robustness of the calibrations is tested using an ensemble of nine calibrations based on different seed numbers using the

The irradiance and temperature dependent mathematical model for estimation of photovoltaic panel performances

International Nuclear Information System (INIS)

Barukčić, M.; Ćorluka, V.; Miklošević, K.

2015-01-01

Highlights: • The temperature and irradiance dependent model for the I–V curve estimation is presented. • The purely mathematical model based on the analysis of the I–V curve shape is presented. • The model includes the Gompertz function with temperature and irradiance dependent parameters. • The input data are extracted from the data sheet I–V curves. - Abstract: The temperature and irradiance dependent mathematical model for photovoltaic panel performances estimation is proposed in the paper. The base of the model is the mathematical function of the photovoltaic panel current–voltage curve. The model of the current–voltage curve is based on the sigmoid function with temperature and irradiance dependent parameters. The temperature and irradiance dependencies of the parameters are proposed in the form of analytic functions. The constant parameters are involved in the analytical functions. The constant parameters need to be estimated to get the temperature and irradiance dependent current–voltage curve. The mathematical model contains 12 constant parameters and they are estimated by using the evolutionary algorithm. The optimization problem is defined for this purpose. The optimization problem objective function is based on estimated and extracted (measured) current and voltage values. The current and voltage values are extracted from current–voltage curves given in datasheet of the photovoltaic panels. The new procedure for estimation of open circuit voltage value at any temperature and irradiance is proposed in the model. The performance of the proposed mathematical model is presented for three different photovoltaic panel technologies. The simulation results indicate that the proposed mathematical model is acceptable for estimation of temperature and irradiance dependent current–voltage curve and photovoltaic panel performances within temperature and irradiance ranges

On the Temperature Dependence of the UNIQUAC/UNIFAC Models

DEFF Research Database (Denmark)

Skjold-Jørgensen, Steen; Rasmussen, Peter; Fredenslund, Aage

1980-01-01

of the simultaneous correlation. The temperature dependent parameters have, however, little physical meaning and very odd results are frequently obtained when the interaction parameters obtained from excess enthalpy information alone are used for the prediction of vapor-liquid equilibria. The UNIQUAC/UNIFAC models...... parameters based on excess enthalpy data, and the prediction of excess enthalpy information from only one isothermal set of vapor-liquid equilibrium data is qualitatively acceptable. A parameter table for the modified UNIFAC model is given for the five main groups: CH2, C = C, ACH, ACCH2 and CH2O.......Local composition models for the description of the properties of liquid mixtures do not in general give an accurate representation of excess Gibbs energy and excess enthalpy simultaneously. The introduction of temperature dependent interaction parameters leads to considerable improvements...

Nuclear symmetry energy in density dependent hadronic models

International Nuclear Information System (INIS)

Haddad, S.

2008-12-01

The density dependence of the symmetry energy and the correlation between parameters of the symmetry energy and the neutron skin thickness in the nucleus 208 Pb are investigated in relativistic Hadronic models. The dependency of the symmetry energy on density is linear around saturation density. Correlation exists between the neutron skin thickness in the nucleus 208 Pb and the value of the nuclear symmetry energy at saturation density, but not with the slope of the symmetry energy at saturation density. (author)

Response of heat shock protein genes of the oriental fruit moth under diapause and thermal stress reveals multiple patterns dependent on the nature of stress exposure.

Science.gov (United States)

Zhang, Bo; Peng, Yu; Zheng, Jincheng; Liang, Lina; Hoffmann, Ary A; Ma, Chun-Sen

2016-07-01

Heat shock protein gene (Hsp) families are thought to be important in thermal adaptation, but their expression patterns under various thermal stresses have still been poorly characterized outside of model systems. We have therefore characterized Hsp genes and their stress responses in the oriental fruit moth (OFM), Grapholita molesta, a widespread global orchard pest, and compared patterns of expression in this species to that of other insects. Genes from four Hsp families showed variable expression levels among tissues and developmental stages. Members of the Hsp40, 70, and 90 families were highly expressed under short exposures to heat and cold. Expression of Hsp40, 70, and Hsc70 family members increased in OFM undergoing diapause, while Hsp90 was downregulated. We found that there was strong sequence conservation of members of large Hsp families (Hsp40, Hsp60, Hsp70, Hsc70) across taxa, but this was not always matched by conservation of expression patterns. When the large Hsps as well as small Hsps from OFM were compared under acute and ramping heat stress, two groups of sHsps expression patterns were apparent, depending on whether expression increased or decreased immediately after stress exposure. These results highlight potential differences in conservation of function as opposed to sequence in this gene family and also point to Hsp genes potentially useful as bioindicators of diapause and thermal stress in OFM.

How can we model selectively neutral density dependence in evolutionary games.

Science.gov (United States)

Argasinski, Krzysztof; Kozłowski, Jan

2008-03-01

The problem of density dependence appears in all approaches to the modelling of population dynamics. It is pertinent to classic models (i.e., Lotka-Volterra's), and also population genetics and game theoretical models related to the replicator dynamics. There is no density dependence in the classic formulation of replicator dynamics, which means that population size may grow to infinity. Therefore the question arises: How is unlimited population growth suppressed in frequency-dependent models? Two categories of solutions can be found in the literature. In the first, replicator dynamics is independent of background fitness. In the second type of solution, a multiplicative suppression coefficient is used, as in a logistic equation. Both approaches have disadvantages. The first one is incompatible with the methods of life history theory and basic probabilistic intuitions. The logistic type of suppression of per capita growth rate stops trajectories of selection when population size reaches the maximal value (carrying capacity); hence this method does not satisfy selective neutrality. To overcome these difficulties, we must explicitly consider turn-over of individuals dependent on mortality rate. This new approach leads to two interesting predictions. First, the equilibrium value of population size is lower than carrying capacity and depends on the mortality rate. Second, although the phase portrait of selection trajectories is the same as in density-independent replicator dynamics, pace of selection slows down when population size approaches equilibrium, and then remains constant and dependent on the rate of turn-over of individuals.

Immediate effects of modified landing pattern on a probabilistic tibial stress fracture model in runners.

Science.gov (United States)

Chen, T L; An, W W; Chan, Z Y S; Au, I P H; Zhang, Z H; Cheung, R T H

2016-03-01

Tibial stress fracture is a common injury in runners. This condition has been associated with increased impact loading. Since vertical loading rates are related to the landing pattern, many heelstrike runners attempt to modify their footfalls for a lower risk of tibial stress fracture. Such effect of modified landing pattern remains unknown. This study examined the immediate effects of landing pattern modification on the probability of tibial stress fracture. Fourteen experienced heelstrike runners ran on an instrumented treadmill and they were given augmented feedback for landing pattern switch. We measured their running kinematics and kinetics during different landing patterns. Ankle joint contact force and peak tibial strains were estimated using computational models. We used an established mathematical model to determine the effect of landing pattern on stress fracture probability. Heelstrike runners experienced greater impact loading immediately after landing pattern switch (Ptibial strains and the risk of tibial stress fracture in runners with different landing patterns (P>0.986). Immediate transitioning of the landing pattern in heelstrike runners may not offer timely protection against tibial stress fracture, despite a reduction of impact loading. Long-term effects of landing pattern switch remains unknown. Copyright © 2016 Elsevier Ltd. All rights reserved.

Model-Based Dependability Analysis of Physical Systems with Modelica

Directory of Open Access Journals (Sweden)

Andrea Tundis

2017-01-01

Full Text Available Modelica is an innovative, equation-based, and acausal language that allows modeling complex physical systems, which are made of mechanical, electrical, and electrotechnical components, and evaluates their design through simulation techniques. Unfortunately, the increasing complexity and accuracy of such physical systems require new, more powerful, and flexible tools and techniques for evaluating important system properties and, in particular, the dependability ones such as reliability, safety, and maintainability. In this context, the paper describes some extensions of the Modelica language to support the modeling of system requirements and their relationships. Such extensions enable the requirement verification analysis through native constructs in the Modelica language. Furthermore, they allow exporting a Modelica-based system design as a Bayesian Network in order to analyze its dependability by employing a probabilistic approach. The proposal is exemplified through a case study concerning the dependability analysis of a Tank System.

On the Modelling of Biological Patterns with Mechanochemical Models: Insights from Analysis and Computation

KAUST Repository

Moreo, P.

2009-11-14

The diversity of biological form is generated by a relatively small number of underlying mechanisms. Consequently, mathematical and computational modelling can, and does, provide insight into how cellular level interactions ultimately give rise to higher level structure. Given cells respond to mechanical stimuli, it is therefore important to consider the effects of these responses within biological self-organisation models. Here, we consider the self-organisation properties of a mechanochemical model previously developed by three of the authors in Acta Biomater. 4, 613-621 (2008), which is capable of reproducing the behaviour of a population of cells cultured on an elastic substrate in response to a variety of stimuli. In particular, we examine the conditions under which stable spatial patterns can emerge with this model, focusing on the influence of mechanical stimuli and the interplay of non-local phenomena. To this end, we have performed a linear stability analysis and numerical simulations based on a mixed finite element formulation, which have allowed us to study the dynamical behaviour of the system in terms of the qualitative shape of the dispersion relation. We show that the consideration of mechanotaxis, namely changes in migration speeds and directions in response to mechanical stimuli alters the conditions for pattern formation in a singular manner. Furthermore without non-local effects, responses to mechanical stimuli are observed to result in dispersion relations with positive growth rates at arbitrarily large wavenumbers, in turn yielding heterogeneity at the cellular level in model predictions. This highlights the sensitivity and necessity of non-local effects in mechanically influenced biological pattern formation models and the ultimate failure of the continuum approximation in their absence. © 2009 Society for Mathematical Biology.

Thinking After Drinking: Impaired Hippocampal Dependent Cognition in Human Alcoholics and Animal Models of Alcohol Dependence

Directory of Open Access Journals (Sweden)

Miranda Staples

2016-09-01

Full Text Available Alcohol use disorder currently affects approximately 18 million Americans, with at least half of these individuals having significant cognitive impairments subsequent to their chronic alcohol use. This is most widely apparent as frontal cortex dependent cognitive dysfunction, where executive function and decision making are severely compromised, as well as hippocampus dependent cognitive dysfunction, where contextual and temporal reasoning are negatively impacted. This review discusses the relevant clinical literature to support the theory that cognitive recovery in tasks dependent on the prefrontal cortex and hippocampus is temporally different across extended periods of abstinence from alcohol. Additional studies from preclinical models are discussed to support clinical findings. Finally, the unique cellular composition of the hippocampus and cognitive impairment dependent on the hippocampus is highlighted in the context of alcohol dependence.

Epigenetic change detection and pattern recognition via Bayesian hierarchical hidden Markov models.

Science.gov (United States)

Wang, Xinlei; Zang, Miao; Xiao, Guanghua

2013-06-15

Epigenetics is the study of changes to the genome that can switch genes on or off and determine which proteins are transcribed without altering the DNA sequence. Recently, epigenetic changes have been linked to the development and progression of disease such as psychiatric disorders. High-throughput epigenetic experiments have enabled researchers to measure genome-wide epigenetic profiles and yield data consisting of intensity ratios of immunoprecipitation versus reference samples. The intensity ratios can provide a view of genomic regions where protein binding occur under one experimental condition and further allow us to detect epigenetic alterations through comparison between two different conditions. However, such experiments can be expensive, with only a few replicates available. Moreover, epigenetic data are often spatially correlated with high noise levels. In this paper, we develop a Bayesian hierarchical model, combined with hidden Markov processes with four states for modeling spatial dependence, to detect genomic sites with epigenetic changes from two-sample experiments with paired internal control. One attractive feature of the proposed method is that the four states of the hidden Markov process have well-defined biological meanings and allow us to directly call the change patterns based on the corresponding posterior probabilities. In contrast, none of existing methods can offer this advantage. In addition, the proposed method offers great power in statistical inference by spatial smoothing (via hidden Markov modeling) and information pooling (via hierarchical modeling). Both simulation studies and real data analysis in a cocaine addiction study illustrate the reliability and success of this method. Copyright © 2012 John Wiley & Sons, Ltd.

Color-flavor locked strange quark matter in a mass density-dependent model

International Nuclear Information System (INIS)

Chen Yuede; Wen Xinjian

2007-01-01

Properties of color-flavor locked (CFL) strange quark matter have been studied in a mass-density-dependent model, and compared with the results in the conventional bag model. In both models, the CFL phase is more stable than the normal nuclear matter for reasonable parameters. However, the lower density behavior of the sound velocity in this model is completely opposite to that in the bag model, which makes the maximum mass of CFL quark stars in the mass-density-dependent model larger than that in the bag model. (authors)

Modeling spatiotemporal dynamics of DNA methylation

DEFF Research Database (Denmark)

Lövkvist, Cecilia Elisabet

into how epigenetic marks are distributed in the human genome. In the first part of the thesis, we investigate DNA methylation and maintenance of methylation patterns throughout cell division. We argue that collaborative models, those where the methylation of CpG sites depends on the methylation status...... into the game more explicitly in another type of model that speaks out the duality of the two aspects. Using statistical analysis of experimental data, this thesis further explores a link between DNA methylation and nucleosome occupancy. By comparing the patterns on promoters to regions with similar Cp...... division. The patterns of epigentic marks depend on enzymes that ensure their maintenance and introduction. Using theoretical models, this thesis proposes new mechanisms for how enzymes operate to maintain patterns of epigenetic marks. Through analysis of experimental data this work gives new insight...

A hydroclimatic model of global fire patterns

Science.gov (United States)

Boer, Matthias

2015-04-01

Satellite-based earth observation is providing an increasingly accurate picture of global fire patterns. The highest fire activity is observed in seasonally dry (sub-)tropical environments of South America, Africa and Australia, but fires occur with varying frequency, intensity and seasonality in almost all biomes on Earth. The particular combination of these fire characteristics, or fire regime, is known to emerge from the combined influences of climate, vegetation, terrain and land use, but has so far proven difficult to reproduce by global models. Uncertainty about the biophysical drivers and constraints that underlie current global fire patterns is propagated in model predictions of how ecosystems, fire regimes and biogeochemical cycles may respond to projected future climates. Here, I present a hydroclimatic model of global fire patterns that predicts the mean annual burned area fraction (F) of 0.25° x 0.25° grid cells as a function of the climatic water balance. Following Bradstock's four-switch model, long-term fire activity levels were assumed to be controlled by fuel productivity rates and the likelihood that the extant fuel is dry enough to burn. The frequency of ignitions and favourable fire weather were assumed to be non-limiting at long time scales. Fundamentally, fuel productivity and fuel dryness are a function of the local water and energy budgets available for the production and desiccation of plant biomass. The climatic water balance summarizes the simultaneous availability of biologically usable energy and water at a site, and may therefore be expected to explain a significant proportion of global variation in F. To capture the effect of the climatic water balance on fire activity I focused on the upper quantiles of F, i.e. the maximum level of fire activity for a given climatic water balance. Analysing GFED4 data for annual burned area together with gridded climate data, I found that nearly 80% of the global variation in the 0.99 quantile of F

A model-based exploration of the role of pattern generating circuits during locomotor adaptation.

Science.gov (United States)

Marjaninejad, Ali; Finley, James M

2016-08-01

In this study, we used a model-based approach to explore the potential contributions of central pattern generating circuits (CPGs) during adaptation to external perturbations during locomotion. We constructed a neuromechanical modeled of locomotion using a reduced-phase CPG controller and an inverted pendulum mechanical model. Two different forms of locomotor adaptation were examined in this study: split-belt treadmill adaptation and adaptation to a unilateral, elastic force field. For each simulation, we first examined the effects of phase resetting and varying the model's initial conditions on the resulting adaptation. After evaluating the effect of phase resetting on the adaptation of step length symmetry, we examined the extent to which the results from these simple models could explain previous experimental observations. We found that adaptation of step length symmetry during split-belt treadmill walking could be reproduced using our model, but this model failed to replicate patterns of adaptation observed in response to force field perturbations. Given that spinal animal models can adapt to both of these types of perturbations, our findings suggest that there may be distinct features of pattern generating circuits that mediate each form of adaptation.

An inventory model with dependent product demands and returns

NARCIS (Netherlands)

Kiesmüller, G.P.; Laan, van der E.P.

2001-01-01

In this paper an inventory model for a single reusable product is investigated, in which the random returns depend explicitly on the demand stream. Further, the model distinguishes itself from most other research in this field by considering leadtimes and a finite planning horizon. We show that

Conditional Stochastic Models in Reduced Space: Towards Efficient Simulation of Tropical Cyclone Precipitation Patterns

Science.gov (United States)

Dodov, B.

2017-12-01

Stochastic simulation of realistic and statistically robust patterns of Tropical Cyclone (TC) induced precipitation is a challenging task. It is even more challenging in a catastrophe modeling context, where tens of thousands of typhoon seasons need to be simulated in order to provide a complete view of flood risk. Ultimately, one could run a coupled global climate model and regional Numerical Weather Prediction (NWP) model, but this approach is not feasible in the catastrophe modeling context and, most importantly, may not provide TC track patterns consistent with observations. Rather, we propose to leverage NWP output for the observed TC precipitation patterns (in terms of downscaled reanalysis 1979-2015) collected on a Lagrangian frame along the historical TC tracks and reduced to the leading spatial principal components of the data. The reduced data from all TCs is then grouped according to timing, storm evolution stage (developing, mature, dissipating, ETC transitioning) and central pressure and used to build a dictionary of stationary (within a group) and non-stationary (for transitions between groups) covariance models. Provided that the stochastic storm tracks with all the parameters describing the TC evolution are already simulated, a sequence of conditional samples from the covariance models chosen according to the TC characteristics at a given moment in time are concatenated, producing a continuous non-stationary precipitation pattern in a Lagrangian framework. The simulated precipitation for each event is finally distributed along the stochastic TC track and blended with a non-TC background precipitation using a data assimilation technique. The proposed framework provides means of efficient simulation (10000 seasons simulated in a couple of days) and robust typhoon precipitation patterns consistent with observed regional climate and visually undistinguishable from high resolution NWP output. The framework is used to simulate a catalog of 10000 typhoon

A collision avoidance model for two-pedestrian groups: Considering random avoidance patterns

Science.gov (United States)

Zhou, Zhuping; Cai, Yifei; Ke, Ruimin; Yang, Jiwei

2017-06-01

Grouping is a common phenomenon in pedestrian crowds and group modeling is still an open challenging problem. When grouping pedestrians avoid each other, different patterns can be observed. Pedestrians can keep close with group members and avoid other groups in cluster. Also, they can avoid other groups separately. Considering this randomness in avoidance patterns, we propose a collision avoidance model for two-pedestrian groups. In our model, the avoidance model is proposed based on velocity obstacle method at first. Then grouping model is established using Distance constrained line (DCL), by transforming DCL into the framework of velocity obstacle, the avoidance model and grouping model are successfully put into one unified calculation structure. Within this structure, an algorithm is developed to solve the problem when solutions of the two models conflict with each other. Two groups of bidirectional pedestrian experiments are designed to verify the model. The accuracy of avoidance behavior and grouping behavior is validated in the microscopic level, while the lane formation phenomenon and fundamental diagrams is validated in the macroscopic level. The experiments results show our model is convincing and has a good expansibility to describe three or more pedestrian groups.

Age-dependent metabolic model of radionuclides in Human body

International Nuclear Information System (INIS)

Ye Changqing

1986-01-01

Age-dependent metabolic model of radionuclides in human body was introduced briefly. These data are necessary in setting up the secondary dose limit of internal exposure of the general public. For the gastro-intestinal tract model, it was shown that the dose of various sections of GI tract caused by unsoluble radioactive materials were influenced by the mass of section and mean residence time, both of which are age-dependent, but the absorption fraction f 1 through gastro-intestinal tract should be corrected only for the infant less than 1 year of age. For the lung model, it was indicated that the fraction of deposition or clearance of particles in the different compartments of lung were related to age. The doses of tracheobronchial and pulmonary compartment of adult for 222 Rn or 220 Rn with their decay products were one third of that of 6-years old child who received the maximum dose in comparison with other ages. The age-dependent metabolic models in organ and/or body of Tritium, Iodine-131, Caesium-137, radioactive Strontium, Radium and Plutonium were reported. A generalized approach for estimating the effect of age on deposition fractions and retention half-time were presented. Calculated results indicated that younger ages were characterized by increased deposition fraction and decreased half-time for retention. Representative examples were provided for 21 elements of current interest in health physics

Structural Implications of Reciprocal Exchange: A Power-Dependence Approach

Science.gov (United States)

Bonacich, Phillip; Bienenstock, Elisa Jayne

2009-01-01

This paper presents and tests a general model to predict emergent exchange patterns and power differences in reciprocal exchange networks when individual actors follow the norm of reciprocity. With an interesting qualification, the experimental results reported here support the power-dependence approach (Emerson 1972a, b): those who acquire the…

SensibleSleep: A Bayesian Model for Learning Sleep Patterns from Smartphone Events

DEFF Research Database (Denmark)

Cuttone, Andrea; Bækgaard, Per; Sekara, Vedran

2017-01-01

We propose a Bayesian model for extracting sleep patterns from smartphone events. Our method is able to identify individuals' daily sleep periods and their evolution over time, and provides an estimation of the probability of sleep and wake transitions. The model is fitted to more than 400...... to quantify uncertainty and encode prior knowledge about sleep patterns. Compared with existing smartphone-based systems, our method requires only screen on/off events, and is therefore much less intrusive in terms of privacy and more battery-efficient....... participants from two different datasets, and we verify the results against ground truth from dedicated armband sleep trackers. We show that the model is able to produce reliable sleep estimates with an accuracy of 0.89, both at the individual and at the collective level. Moreover the Bayesian model is able...

SensibleSleep: A Bayesian Model for Learning Sleep Patterns from Smartphone Events.

Science.gov (United States)

Cuttone, Andrea; Bækgaard, Per; Sekara, Vedran; Jonsson, Håkan; Larsen, Jakob Eg; Lehmann, Sune

2017-01-01

We propose a Bayesian model for extracting sleep patterns from smartphone events. Our method is able to identify individuals' daily sleep periods and their evolution over time, and provides an estimation of the probability of sleep and wake transitions. The model is fitted to more than 400 participants from two different datasets, and we verify the results against ground truth from dedicated armband sleep trackers. We show that the model is able to produce reliable sleep estimates with an accuracy of 0.89, both at the individual and at the collective level. Moreover the Bayesian model is able to quantify uncertainty and encode prior knowledge about sleep patterns. Compared with existing smartphone-based systems, our method requires only screen on/off events, and is therefore much less intrusive in terms of privacy and more battery-efficient.

SensibleSleep: A Bayesian Model for Learning Sleep Patterns from Smartphone Events.

Directory of Open Access Journals (Sweden)

Andrea Cuttone

Full Text Available We propose a Bayesian model for extracting sleep patterns from smartphone events. Our method is able to identify individuals' daily sleep periods and their evolution over time, and provides an estimation of the probability of sleep and wake transitions. The model is fitted to more than 400 participants from two different datasets, and we verify the results against ground truth from dedicated armband sleep trackers. We show that the model is able to produce reliable sleep estimates with an accuracy of 0.89, both at the individual and at the collective level. Moreover the Bayesian model is able to quantify uncertainty and encode prior knowledge about sleep patterns. Compared with existing smartphone-based systems, our method requires only screen on/off events, and is therefore much less intrusive in terms of privacy and more battery-efficient.

From dysfunction to adaptation: an interactionist model of dependency.

Science.gov (United States)

Bornstein, Robert F

2012-01-01

Contrary to clinical lore, a dependent personality style is associated with active as well as passive behavior and may be adaptive in certain contexts (e.g., in fostering compliance with medical and psychotherapeutic treatment regimens). The cognitive/interactionist model conceptualizes dependency-related responding in terms of four components: (a) motivational (a marked need for guidance, support, and approval from others); (b) cognitive (a perception of oneself as powerless and ineffectual); (c) affective (a tendency to become anxious when required to function autonomously); and (d) behavioral (use of diverse self-presentation strategies to strengthen ties to potential caregivers). Clinicians' understanding of the etiology and dynamics of dependency has improved substantially in recent years; current challenges include delineating useful subtypes of dependency, developing valid symptom criteria for Dependent Personality Disorder in DSM-5 and beyond, and working effectively with dependent patients in the age of managed care.

Automatic pattern identification of rock moisture based on the Staff-RF model

Science.gov (United States)