Science.gov

Sample records for state interindustry models

  1. Network structure of inter-industry flows

    NASA Astrophysics Data System (ADS)

    McNerney, James; Fath, Brian D.; Silverberg, Gerald

    2013-12-01

    We study the structure of inter-industry relationships using networks of money flows between industries in 45 national economies. We find these networks vary around a typical structure characterized by a Weibull link weight distribution, exponential industry size distribution, and a common community structure. The community structure is hierarchical, with the top level of the hierarchy comprising five industry communities: food industries, chemical industries, manufacturing industries, service industries, and extraction industries.

  2. Interindustry Wage Differentials and the Gender Wage Gap.

    ERIC Educational Resources Information Center

    Fields, Judith; Wolff, Edward N.

    1995-01-01

    Wages of female workers differ significantly by industry. The average woman earns about 65% as much as the average man; 12%-22% of the gap is explained by differences in patterns of interindustry wage differentials and 15%-19% by differences in gender distribution of workers. Combined industry effects explain about one-third of the gender wage…

  3. Fluctuation-dissipation theory of input-output interindustrial relations

    NASA Astrophysics Data System (ADS)

    Iyetomi, Hiroshi; Nakayama, Yasuhiro; Aoyama, Hideaki; Fujiwara, Yoshi; Ikeda, Yuichi; Souma, Wataru

    2011-01-01

    In this study, the fluctuation-dissipation theory is invoked to shed light on input-output interindustrial relations at a macroscopic level by its application to indices of industrial production (IIP) data for Japan. Statistical noise arising from finiteness of the time series data is carefully removed by making use of the random matrix theory in an eigenvalue analysis of the correlation matrix; as a result, two dominant eigenmodes are detected. Our previous study successfully used these two modes to demonstrate the existence of intrinsic business cycles. Here a correlation matrix constructed from the two modes describes genuine interindustrial correlations in a statistically meaningful way. Furthermore, it enables us to quantitatively discuss the relationship between shipments of final demand goods and production of intermediate goods in a linear response framework. We also investigate distinctive external stimuli for the Japanese economy exerted by the current global economic crisis. These stimuli are derived from residuals of moving-average fluctuations of the IIP remaining after subtracting the long-period components arising from inherent business cycles. The observation reveals that the fluctuation-dissipation theory is applicable to an economic system that is supposed to be far from physical equilibrium.

  4. Model State Efforts.

    ERIC Educational Resources Information Center

    Morgan, Gwen

    Models of state involvement in training child care providers are briefly discussed and the employers' role in training is explored. Six criteria for states that are taken as models are identified, and four are described. Various state activities are described for each criterion. It is noted that little is known about employer and other private…

  5. The economic impact of Sandia National Laboratories on central New Mexico and the state of New Mexico fiscal year 1997

    SciTech Connect

    Lansford, R.R.; Nielsen, T.G.; Schultz, J.; Adcock, L.D.; Gentry, L.M.; Ben-David, S.; Temple, J.

    1998-05-29

    Sandia National Laboratories (SNL) was established in 1949 to perform the engineering development and ordnance responsibilities associated with nuclear weapons. By the early 1960`s the facility had evolved into an engineering research and development laboratory and became a multiprogram laboratory during the 1970s. Sandia is operated for the US Department of Energy by the Sandia Corporation, a wholly-owned subsidiary of Lockheed Martin, Incorporated. For several years, the US Department of Energy (DOE) Albuquerque Operations Office (AL) and New Mexico State University (NMSU) have maintained an inter-industry, input-output model with capabilities to assess the impacts of developments initiated outside the economy such as federal DOE monies that flow into the state, on an economy. This model will be used to assess economic, personal income and employment impacts of SNL on central New Mexico and the state of New Mexico. For this report, the reference period is FY 1997 (October 1, 1996, through September 30, 1997) and includes two major impact analyses: the impact of SNL activities on central New Mexico and the economic impacts of SNL on the state of New Mexico. For purposes of this report, the central New Mexico region includes Bernalillo, Sandoval, Valencia, and Torrance counties. Total impact represents both direct and indirect respending by business, including induced effects (respending by households). The standard multipliers used in determining impacts results from the inter-industry, input-output models developed for the four-county region and the state of New Mexico. 6 figs., 10 tabs.

  6. Models of multiquark states

    SciTech Connect

    Lipkin, H.J.

    1986-01-01

    The success of simple constituent quark models in single-hardon physics and their failure in multiquark physics is discussed, emphasizing the relation between meson and baryon spectra, hidden color and the color matrix, breakup decay modes, coupled channels, and hadron-hadron interactions via flipping and tunneling of flux tubes. Model-independent predictions for possible multiquark bound states are considered and the most promising candidates suggested. A quark approach to baryon-baryon interactions is discussed.

  7. The economic impact of the Department of Energy on the State of New Mexico Fiscal Year 1995

    SciTech Connect

    Lansford, R.R.; Adcock, L.D.; Gentry, L.M.; Ben-David, S.

    1996-08-01

    The U.S. Department of Energy (DOE) provides a major source of economic benefits in New Mexico, second only to the activities of the U.S. Department of Defense. The agency`s far-reaching economic influence within the state is the focus of this report. Economic benefits arising from the various activities and functions of both the Department and its contractors have accrued to the state continuously for over 45 years. For several years, DOE/Albuquerque Operations Office (AL) and New Mexico State University (NMSU) have maintained inter-industry, input-output modeling capabilities to assess DOE`s impacts on the state of New Mexico and the other substate regions most directly impacted by DOE activities. One of the major uses of input-output techniques is to assess the effects of developments initiated outside the economy such as federal DOE monies that flow into the state, on an economy.

  8. Inventory of state energy models

    SciTech Connect

    Melcher, A.G.; Gist, R.L.; Underwood, R.G.; Weber, J.C.

    1980-03-31

    These models address a variety of purposes, such as supply or demand of energy or of certain types of energy, emergency management of energy, conservation in end uses of energy, and economic factors. Fifty-one models are briefly described as to: purpose; energy system; applications;status; validation; outputs by sector, energy type, economic and physical units, geographic area, and time frame; structure and modeling techniques; submodels; working assumptions; inputs; data sources; related models; costs; references; and contacts. Discussions in the report include: project purposes and methods of research, state energy modeling in general, model types and terminology, and Federal legislation to which state modeling is relevant. Also, a state-by-state listing of modeling efforts is provided and other model inventories are identified. The report includes a brief encylopedia of terms used in energy models. It is assumed that many readers of the report will not be experienced in the technical aspects of modeling. The project was accomplished by telephone conversations and document review by a team from the Colorado School of Mines Research Institute and the faculty of the Colorado School of Mines. A Technical Committee (listed in the report) provided advice during the course of the project.

  9. Inter-Industry Wage Differentials and the Gender Wage Gap: An Identification Problem.

    ERIC Educational Resources Information Center

    Horrace, William C.; Oaxaca, Ronald L.

    2001-01-01

    States that a method for estimating gender wage gaps by industry yields estimates that vary according to arbitrary choice of omitted reference groups. Suggests alternative methods not susceptible to this problem that can be applied to other contexts, such as racial, union/nonunion, and immigrant/native wage differences. (SK)

  10. The economic impact of the Department of Energy on the State of New Mexico Fiscal Year 1998

    SciTech Connect

    Lansford, Robert R.; Adcock, Larry D.; Gentry, Lucille M.; Ben-David, Shaul; Temple, John

    1999-08-05

    The U.S. Department of Energy (DOE) provides a major source of economic benefits in New Mexico, second only to the activities of the U.S. Department of Defense. The agency's far-reaching economic influence within the state is the focus of this report. Economic benefits arising from the various activities and functions of both the Department and its contractors have accrued to the state continuously for over 50 years. For several years, DOE/Albuquerque Operations Office (AL) and New Mexico State University (NMSU) have maintained inter-industry, input-output modeling capabilities to assess DOE's impacts on the state of New Mexico and the other substate regions most directly impacted by DOE activities. One of the major uses of input-output techniques is to assess the effects of developments initiated outside the economy such as Federal DOE monies that flow into the state, on an economy. The information on which the models are based is updated periodically to ensure the most accurate depiction possible of the economy for the period of reference. For this report, the reference periods are Fiscal Year (FY) 1997 (October 1, 1996, through September 30, 1997), and FY 1998 (October 1, 1997, through September 30, 1998). Total impact represents both direct and indirect impacts (resending by business), including induced (resending by households) effects. The standard multipliers used in determining impacts result from the inter-industry, input-output models uniquely developed for New Mexico. This report includes seven main sections: (1) Introduction; (2) Profile of DOE Activities in New Mexico; (3) DOE Expenditure Patterns; (4) Measuring DOE/New Mexico's Economic Impact: (5) Technology Transfer within the Federal Labs funded by DOE/New Mexico; (6) Glossary of Terms; and (7) Technical Appendix containing a description of the model.

  11. The economic impact of the Department of Energy on the state of New Mexico fiscal year 1997

    SciTech Connect

    Lansford, R.R.; Nielsen, T.G.; Schultz, J.; Adcock, L.D.; Gentry, L.M.; Ben-David, S.; Temple, J.

    1998-05-29

    The US Department of Energy (DOE) provides a major source of economic benefits in New Mexico. The agency`s far-reaching economic influence within the state is the focus of this report. Economic benefits arising from the various activities and functions of both DOE and its contractors have accrued to the state continuously for over 50 years. For several years, DOE/Albuquerque Operations Office (AL) and New Mexico State University (NMSU) have maintained inter-industry, input-output modeling capabilities to assess DOE`s impacts on the state of New Mexico and the other substate regions most directly impacted by DOE activities. One of the major uses of input-output techniques is to assess the effects of developments initiated outside the economy such as federal DOE monies that flow into the state, on an economy. The information on which the models are based is updated periodically to ensure the most accurate depiction possible of the economy for the period of reference. For this report, the reference periods are Fiscal Year (FY) 1996 and FY 1997. Total impacts represents both direct and indirect impacts (respending by business), including induced (respending by households) effects. The standard multipliers used in determining impacts result from the inter-industry, input-output models uniquely developed for New Mexico. This report includes seven main sections: (1) introduction; (2) profile of DOE activities in New Mexico; (3) DOE expenditure patterns; (4) measuring DOE/New Mexico`s economic impact; (5) technology transfer within the federal labs funded by DOE/New Mexico; (6) glossary of terms; and (7) technical appendix containing a description of the model. 9 figs., 19 tabs.

  12. Battery-Charge-State Model

    NASA Technical Reports Server (NTRS)

    Vivian, H. C.

    1985-01-01

    Charge-state model for lead/acid batteries proposed as part of effort to make equivalent of fuel gage for battery-powered vehicles. Models based on equations that approximate observable characteristics of battery electrochemistry. Uses linear equations, easier to simulate on computer, and gives smooth transitions between charge, discharge, and recuperation.

  13. Modeling volatility using state space models.

    PubMed

    Timmer, J; Weigend, A S

    1997-08-01

    In time series problems, noise can be divided into two categories: dynamic noise which drives the process, and observational noise which is added in the measurement process, but does not influence future values of the system. In this framework, we show that empirical volatilities (the squared relative returns of prices) exhibit a significant amount of observational noise. To model and predict their time evolution adequately, we estimate state space models that explicitly include observational noise. We obtain relaxation times for shocks in the logarithm of volatility ranging from three weeks (for foreign exchange) to three to five months (for stock indices). In most cases, a two-dimensional hidden state is required to yield residuals that are consistent with white noise. We compare these results with ordinary autoregressive models (without a hidden state) and find that autoregressive models underestimate the relaxation times by about two orders of magnitude since they do not distinguish between observational and dynamic noise. This new interpretation of the dynamics of volatility in terms of relaxators in a state space model carries over to stochastic volatility models and to GARCH models, and is useful for several problems in finance, including risk management and the pricing of derivative securities. Data sets used: Olsen & Associates high frequency DEM/USD foreign exchange rates (8 years). Nikkei 225 index (40 years). Dow Jones Industrial Average (25 years). PMID:9730016

  14. Energy demand analytics using coupled technological and economic models

    EPA Science Inventory

    Impacts of a range of policy scenarios on end-use energy demand are examined using a coupling of MARKAL, an energy system model with extensive supply and end-use technological detail, with Inforum LIFT, a large-scale model of the us. economy with inter-industry, government, and c...

  15. Model Act for State Licensure of Psychologists

    ERIC Educational Resources Information Center

    American Psychologist, 2011

    2011-01-01

    As APA policy, the Model Act for State Licensure of Psychologists serves as a prototype for drafting state legislation regulating the practice of psychology. State legislatures are encouraged to use the language of this document and the policies that it espouses as the model for their own state licensure laws. Inevitably each state law will…

  16. Models of Communication in Multilingual States.

    ERIC Educational Resources Information Center

    Bamgbose, Ayo

    The paper draws attention to communication in multilingual states which may be said to exist at three levels: sub-state, state, and inter-state level. Communication at the sub-state level may involve an "in-group" language or a regional one, and hence a multilingual model is required at this level. At the state level, on the other hand, there will…

  17. The economic impact of Sandia National Laboratories on Central New Mexico and the State of New Mexico Fiscal Year 1998

    SciTech Connect

    Lansford, Robert R.; Adcock, Larry D.; Gentry, Lucille M.; Ben-David, Shaul; Temple, John

    1999-08-09

    Sandia National Laboratories (SNL) is a Department of Energy federally funded national security laboratory that uses engineering and science to ensure the security of the Nation. SNL provides scientific and engineering solutions to meet national needs in nuclear weapons and related defense systems, energy security, and environmental integrity. SNL works in partnerships with universities and industry to enhance their mission and transfer technology that will address emerging national challenges for both government and industry. For several years, the U.S. Department of Energy (DOE) Albuquerque Operations Office (AL) and New Mexico State University (NMSU) have maintained an inter-industry, input-output (I/O) model with capabilities to assess the impacts of developments initiated outside the economy such as federal DOE monies that flow into the state, on an economy. This model will be used to assess economic, personal income and employment impacts of SNL on Central New Mexico and the State of New Mexico. Caution should be exercised when comparing economic impacts between fiscal years prior to this report. The I/O model was rebased for FY 1998. The fringe benefits coefficients have been updated for the FY 1996 and FY 1997 economic impacts analysis. Prior to FY 1993 two different I/O base models were used to estimate the impacts. New technical information was released by the Bureau of Economic Analysis (BEA), U.S. Department of Commerce in 1991 and in 1994 and was incorporated in FY 1991, FY 1993, and FY 1994 I/O models. Also in 1993, the state and local tax coefficients and expenditure patterns were updated from a 1986 study for the FY 1992 report. Further details about the input-output model can be found in ''The Economic Impact of the Department of Energy on the State of New Mexico--FY 1998'' report by Lansford, et al. (1999). For this report, the reference period is FY 1998 (October 1, 1997, through September 30, 1998) and includes two major impact analyses: The

  18. Operationalizing resilience using state and transition models

    Technology Transfer Automated Retrieval System (TEKTRAN)

    In management, restoration, and policy contexts, the notion of resilience can be confusing. Systematic development of conceptual models of ecological state change (state transition models; STMs) can help overcome semantic confusion and promote a mechanistic understanding of resilience. Drawing on ex...

  19. Sandia Equation of State Model Library

    Energy Science and Technology Software Center (ESTSC)

    2013-08-29

    The software provides a general interface for querying thermodynamic states of material models along with implementation of both general and specific equation of state models. In particular, models are provided for the IAPWS-IF97 and IAPWS95 water standards as well as the associated water standards for viscosity, thermal conductivity, and surface tension. The interface supports implementation of models in a variety of independent variable spaces. Also, model support routines are included that allow for coupling ofmore » models and determination and representation of phase boundaries.« less

  20. Sandia Equation of State Model Library

    SciTech Connect

    Carpenter, John H.

    2013-08-29

    The software provides a general interface for querying thermodynamic states of material models along with implementation of both general and specific equation of state models. In particular, models are provided for the IAPWS-IF97 and IAPWS95 water standards as well as the associated water standards for viscosity, thermal conductivity, and surface tension. The interface supports implementation of models in a variety of independent variable spaces. Also, model support routines are included that allow for coupling of models and determination and representation of phase boundaries.

  1. Steady state HNG combustion modeling

    SciTech Connect

    Louwers, J.; Gadiot, G.M.H.J.L.; Brewster, M.Q.; Son, S.F.; Parr, T.; Hanson-Parr, D.

    1998-04-01

    Two simplified modeling approaches are used to model the combustion of Hydrazinium Nitroformate (HNF, N{sub 2}H{sub 5}-C(NO{sub 2}){sub 3}). The condensed phase is treated by high activation energy asymptotics. The gas phase is treated by two limit cases: the classical high activation energy, and the recently introduced low activation energy approach. This results in simplification of the gas phase energy equation, making an (approximate) analytical solution possible. The results of both models are compared with experimental results of HNF combustion. It is shown that the low activation energy approach yields better agreement with experimental observations (e.g. regression rate and temperature sensitivity), than the high activation energy approach.

  2. Modeling and the State Planning System.

    ERIC Educational Resources Information Center

    Bassett, Roger; Chisholm, Mark

    The State Planning System (SPS) is presented in the context of a mathematical model used to generate information about the possible impacts of postsecondary education policy decisions. Section I provides an introduction to modeling in higher education management, identifies some current postsecondary education modeling efforts, offers some…

  3. Occupancy estimation and modeling with multiple states and state uncertainty

    USGS Publications Warehouse

    Nichols, J.D.; Hines, J.E.; MacKenzie, D.I.; Seamans, M.E.; Gutierrez, R.J.

    2007-01-01

    The distribution of a species over space is of central interest in ecology, but species occurrence does not provide all of the information needed to characterize either the well-being of a population or the suitability of occupied habitat. Recent methodological development has focused on drawing inferences about species occurrence in the face of imperfect detection. Here we extend those methods by characterizing occupied locations by some additional state variable ( e. g., as producing young or not). Our modeling approach deals with both detection probabilities,1 and uncertainty in state classification. We then use the approach with occupancy and reproductive rate data from California Spotted Owls (Strix occidentalis occidentalis) collected in the central Sierra Nevada during the breeding season of 2004 to illustrate the utility of the modeling approach. Estimates of owl reproductive rate were larger than naive estimates, indicating the importance of appropriately accounting for uncertainty in detection and state classification.

  4. Bound States in Boson Impurity Models

    NASA Astrophysics Data System (ADS)

    Shi, Tao; Wu, Ying-Hai; González-Tudela, A.; Cirac, J. I.

    2016-04-01

    The formation of bound states involving multiple particles underlies many interesting quantum physical phenomena, such as Efimov physics or superconductivity. In this work, we show the existence of an infinite number of such states for some boson impurity models. They describe free bosons coupled to an impurity and include some of the most representative models in quantum optics. We also propose a family of wave functions to describe the bound states and verify that it accurately characterizes all parameter regimes by comparing its predictions with exact numerical calculations for a one-dimensional tight-binding Hamiltonian. For that model, we also analyze the nature of the bound states by studying the scaling relations of physical quantities, such as the ground-state energy and localization length, and find a nonanalytical behavior as a function of the coupling strength. Finally, we discuss how to test our theoretical predictions in experimental platforms, such as photonic crystal structures and cold atoms in optical lattices.

  5. Soil, resilience, and state and transition models

    Technology Transfer Automated Retrieval System (TEKTRAN)

    State and transition models are based on the assumption that less resilient systems are more susceptible to state changes. The objective of this paper is to show how two different types of soil properties contribute to resilience through their direct and indirect effects on ecosystem processes, and ...

  6. Crowd macro state detection using entropy model

    NASA Astrophysics Data System (ADS)

    Zhao, Ying; Yuan, Mengqi; Su, Guofeng; Chen, Tao

    2015-08-01

    In the crowd security research area a primary concern is to identify the macro state of crowd behaviors to prevent disasters and to supervise the crowd behaviors. The entropy is used to describe the macro state of a self-organization system in physics. The entropy change indicates the system macro state change. This paper provides a method to construct crowd behavior microstates and the corresponded probability distribution using the individuals' velocity information (magnitude and direction). Then an entropy model was built up to describe the crowd behavior macro state. Simulation experiments and video detection experiments were conducted. It was verified that in the disordered state, the crowd behavior entropy is close to the theoretical maximum entropy; while in ordered state, the entropy is much lower than half of the theoretical maximum entropy. The crowd behavior macro state sudden change leads to the entropy change. The proposed entropy model is more applicable than the order parameter model in crowd behavior detection. By recognizing the entropy mutation, it is possible to detect the crowd behavior macro state automatically by utilizing cameras. Results will provide data support on crowd emergency prevention and on emergency manual intervention.

  7. Modeling in the Common Core State Standards

    ERIC Educational Resources Information Center

    Tam, Kai Chung

    2011-01-01

    The inclusion of modeling and applications into the mathematics curriculum has proven to be a challenging task over the last fifty years. The Common Core State Standards (CCSS) has made mathematical modeling both one of its Standards for Mathematical Practice and one of its Conceptual Categories. This article discusses the need for mathematical…

  8. A Model of Mental State Transition Network

    NASA Astrophysics Data System (ADS)

    Xiang, Hua; Jiang, Peilin; Xiao, Shuang; Ren, Fuji; Kuroiwa, Shingo

    Emotion is one of the most essential and basic attributes of human intelligence. Current AI (Artificial Intelligence) research is concentrating on physical components of emotion, rarely is it carried out from the view of psychology directly(1). Study on the model of artificial psychology is the first step in the development of human-computer interaction. As affective computing remains unpredictable, creating a reasonable mental model becomes the primary task for building a hybrid system. A pragmatic mental model is also the fundament of some key topics such as recognition and synthesis of emotions. In this paper a Mental State Transition Network Model(2) is proposed to detect human emotions. By a series of psychological experiments, we present a new way to predict coming human's emotions depending on the various current emotional states under various stimuli. Besides, people in different genders and characters are taken into consideration in our investigation. According to the psychological experiments data derived from 200 questionnaires, a Mental State Transition Network Model for describing the transitions in distribution among the emotions and relationships between internal mental situations and external are concluded. Further more the coefficients of the mental transition network model were achieved. Comparing seven relative evaluating experiments, an average precision rate of 0.843 is achieved using a set of samples for the proposed model.

  9. A Model of Solid State Gas Sensors

    NASA Astrophysics Data System (ADS)

    Woestman, J. T.; Brailsford, A. D.; Shane, M.; Logothetis, E. M.

    1997-03-01

    Solid state gas sensors are widely used to measure the concentrations of gases such as CO, CH_4, C_3H_6, H_2, C_3H8 and O2 The applications of these sensors range from air-to-fuel ratio control in combustion processes including those in automotive engines and industrial furnaces to leakage detection of inflammable and toxic gases in domestic and industrial environments. As the need increases to accurately measure smaller and smaller concentrations, problems such as poor selectivity, stability and response time limit the use of these sensors. In an effort to overcome some of these limitations, a theoretical model of the transient behavior of solid state gas sensors has been developed. In this presentation, a model for the transient response of an electrochemical gas sensor to gas mixtures containing O2 and one reducing species, such as CO, is discussed. This model accounts for the transport of the reactive species to the sampling electrode, the catalyzed oxidation/reduction reaction of these species and the generation of the resulting electrical signal. The model will be shown to reproduce the results of published steady state models and to agree with experimental steady state and transient data.

  10. Optimized Markov state models for metastable systems

    NASA Astrophysics Data System (ADS)

    Guarnera, Enrico; Vanden-Eijnden, Eric

    2016-07-01

    A method is proposed to identify target states that optimize a metastability index amongst a set of trial states and use these target states as milestones (or core sets) to build Markov State Models (MSMs). If the optimized metastability index is small, this automatically guarantees the accuracy of the MSM, in the sense that the transitions between the target milestones is indeed approximately Markovian. The method is simple to implement and use, it does not require that the dynamics on the trial milestones be Markovian, and it also offers the possibility to partition the system's state-space by assigning every trial milestone to the target milestones it is most likely to visit next and to identify transition state regions. Here the method is tested on the Gly-Ala-Gly peptide, where it is shown to correctly identify the expected metastable states in the dihedral angle space of the molecule without a priori information about these states. It is also applied to analyze the folding landscape of the Beta3s mini-protein, where it is shown to identify the folded basin as a connecting hub between an helix-rich region, which is entropically stabilized, and a beta-rich region, which is energetically stabilized and acts as a kinetic trap.

  11. Energy/economic model analysis. Macroeconomic impacts of research and development in gas supply and end use technologies

    NASA Astrophysics Data System (ADS)

    Goettle, R. J., IV; Hudson, E. A.

    1980-06-01

    The Gas Research Institute (GRI) needs to consider the economic impact of the various technologies whose research and development is supported by GRI funding. Three energy-economic models are useful for such a technology assessment. These models are: Energy Economic Modeling System, Energy Policy Model, and Time Stepped Energy System Optimization/Long Term Inter-Industry Transaction Model. These three models were used to help in the economic impact evaluation of various GRI research and development programs.

  12. The Lipkin model and coherent states

    NASA Astrophysics Data System (ADS)

    Bhaumik, Debajyoti; Choudhury, Ajoy; De, Mira; Roy, Binayak Dutta

    1981-03-01

    It is shown that the Bloch or angular momentum coherent states furnish a particularly efficacious basis for a discussion of various aspects of the Lipkin model of the ''nucleus.'' The Hartree-Fock description (as well as its projected version) is elegantly obtained in this framework. It is demonstrated that the ''transition probability'' between the first excited and ground states is proportional to the square of the number of ''nucleons,'' representing (in contrast to what obtains in the random phase approximation) a cooperativity of the ''super-radiant'' type. The extension of the model through the introduction of bosons permits, with the use of Bloch and Glauber coherent states, a succinct description of the phenomenon of boson condensation.

  13. Excited states in the soliton bag model

    SciTech Connect

    Saly, R.; Sundaresan, M.K.

    1984-02-01

    Numerical analysis of the solutions of the soliton bag model of Friedberg and Lee is performed. The recent analysis of Goldflam and Wilets is extended to include even-parity as well as odd-parity radially excited states. It is shown that the existence of the solutions (especially the odd-parity ones) restrict severely the allowed range of parameters.

  14. Markov state models of protein misfolding.

    PubMed

    Sirur, Anshul; De Sancho, David; Best, Robert B

    2016-02-21

    Markov state models (MSMs) are an extremely useful tool for understanding the conformational dynamics of macromolecules and for analyzing MD simulations in a quantitative fashion. They have been extensively used for peptide and protein folding, for small molecule binding, and for the study of native ensemble dynamics. Here, we adapt the MSM methodology to gain insight into the dynamics of misfolded states. To overcome possible flaws in root-mean-square deviation (RMSD)-based metrics, we introduce a novel discretization approach, based on coarse-grained contact maps. In addition, we extend the MSM methodology to include "sink" states in order to account for the irreversibility (on simulation time scales) of processes like protein misfolding. We apply this method to analyze the mechanism of misfolding of tandem repeats of titin domains, and how it is influenced by confinement in a chaperonin-like cavity. PMID:26897000

  15. Markov state models of protein misfolding

    NASA Astrophysics Data System (ADS)

    Sirur, Anshul; De Sancho, David; Best, Robert B.

    2016-02-01

    Markov state models (MSMs) are an extremely useful tool for understanding the conformational dynamics of macromolecules and for analyzing MD simulations in a quantitative fashion. They have been extensively used for peptide and protein folding, for small molecule binding, and for the study of native ensemble dynamics. Here, we adapt the MSM methodology to gain insight into the dynamics of misfolded states. To overcome possible flaws in root-mean-square deviation (RMSD)-based metrics, we introduce a novel discretization approach, based on coarse-grained contact maps. In addition, we extend the MSM methodology to include "sink" states in order to account for the irreversibility (on simulation time scales) of processes like protein misfolding. We apply this method to analyze the mechanism of misfolding of tandem repeats of titin domains, and how it is influenced by confinement in a chaperonin-like cavity.

  16. Markov state models and molecular alchemy

    NASA Astrophysics Data System (ADS)

    Schütte, Christof; Nielsen, Adam; Weber, Marcus

    2015-01-01

    In recent years, Markov state models (MSMs) have attracted a considerable amount of attention with regard to modelling conformation changes and associated function of biomolecular systems. They have been used successfully, e.g. for peptides including time-resolved spectroscopic experiments, protein function and protein folding , DNA and RNA, and ligand-receptor interaction in drug design and more complicated multivalent scenarios. In this article, a novel reweighting scheme is introduced that allows to construct an MSM for certain molecular system out of an MSM for a similar system. This permits studying how molecular properties on long timescales differ between similar molecular systems without performing full molecular dynamics simulations for each system under consideration. The performance of the reweighting scheme is illustrated for simple test cases, including one where the main wells of the respective energy landscapes are located differently and an alchemical transformation of butane to pentane where the dimension of the state space is changed.

  17. Input to state stability in reservoir models

    NASA Astrophysics Data System (ADS)

    Müller, Markus; Sierra, Carlos

    2016-04-01

    Models in ecology and biogeochemistry, in particular models of the global carbon cycle, can be generalized as systems of non-autonomous ordinary differential equations (ODEs). For many applications, it is important to determine the stability properties for this type of systems, but most methods available for autonomous systems are not necessarily applicable for the non-autonomous case. We discuss here stability notions for non-autonomous nonlinear models represented by systems of ODEs explicitly dependent on time and a time-varying input signal. We propose Input to State Stability (ISS) as candidate for the necessary generalization of the established analysis with respect to equilibria or invariant sets for autonomous systems, and show its usefulness by applying it to reservoir models typical for element cycling in ecosystem, e.g. in soil organic matter decomposition. We also show how ISS generalizes existent concepts formerly only available for Linear Time Invariant (LTI) and Linear Time Variant (LTV) systems to the nonlinear case.

  18. Modeling Bivariate Longitudinal Hormone Profiles by Hierarchical State Space Models

    PubMed Central

    Liu, Ziyue; Cappola, Anne R.; Crofford, Leslie J.; Guo, Wensheng

    2013-01-01

    The hypothalamic-pituitary-adrenal (HPA) axis is crucial in coping with stress and maintaining homeostasis. Hormones produced by the HPA axis exhibit both complex univariate longitudinal profiles and complex relationships among different hormones. Consequently, modeling these multivariate longitudinal hormone profiles is a challenging task. In this paper, we propose a bivariate hierarchical state space model, in which each hormone profile is modeled by a hierarchical state space model, with both population-average and subject-specific components. The bivariate model is constructed by concatenating the univariate models based on the hypothesized relationship. Because of the flexible framework of state space form, the resultant models not only can handle complex individual profiles, but also can incorporate complex relationships between two hormones, including both concurrent and feedback relationship. Estimation and inference are based on marginal likelihood and posterior means and variances. Computationally efficient Kalman filtering and smoothing algorithms are used for implementation. Application of the proposed method to a study of chronic fatigue syndrome and fibromyalgia reveals that the relationships between adrenocorticotropic hormone and cortisol in the patient group are weaker than in healthy controls. PMID:24729646

  19. Markov state models of biomolecular conformational dynamics

    PubMed Central

    Chodera, John D.; Noé, Frank

    2014-01-01

    It has recently become practical to construct Markov state models (MSMs) that reproduce the long-time statistical conformational dynamics of biomolecules using data from molecular dynamics simulations. MSMs can predict both stationary and kinetic quantities on long timescales (e.g. milliseconds) using a set of atomistic molecular dynamics simulations that are individually much shorter, thus addressing the well-known sampling problem in molecular dynamics simulation. In addition to providing predictive quantitative models, MSMs greatly facilitate both the extraction of insight into biomolecular mechanism (such as folding and functional dynamics) and quantitative comparison with single-molecule and ensemble kinetics experiments. A variety of methodological advances and software packages now bring the construction of these models closer to routine practice. Here, we review recent progress in this field, considering theoretical and methodological advances, new software tools, and recent applications of these approaches in several domains of biochemistry and biophysics, commenting on remaining challenges. PMID:24836551

  20. State energy modeling. Volume 1: An analysis of state energy modeling

    NASA Astrophysics Data System (ADS)

    Melcher, A. G.

    1981-05-01

    An inventory and analysis of state energy models were made. The inventory identified 69 models developed or used at the state government level. Most of these deal with energy demand and area mix as regards the sectors modeled and the fuel types included. Nearly all of these are econometric or econometric engineering end use models. Fewer models deal with energy supply, and several address both supply and demand. The most common types of models are econometric, engineering and use, linear programming, and input-output. Purposes of models include: forecasting; policy analysis; impact analysis; and scenario analysis. Uses include short term emergency management, long term strategic assessment, and specific applications in decisions on facility siting, utility capacity expansion and rate increases proposed legislation, and analysis of federal policy.

  1. Model bridging chimera state and explosive synchronization

    NASA Astrophysics Data System (ADS)

    Zhang, Xiyun; Bi, Hongjie; Guan, Shuguang; Liu, Jinming; Liu, Zonghua

    2016-07-01

    Global synchronization and partial synchronization are the two distinctive forms of synchronization in coupled oscillators and have been well studied in recent decades. Recent attention on synchronization is focused on the chimera state (CS) and explosive synchronization (ES), but little attention has been paid to their relationship. Here we study this topic by presenting a model to bridge these two phenomena, which consists of two groups of coupled oscillators, and its coupling strength is adaptively controlled by a local order parameter. We find that this model displays either CS or ES in two limits. In between the two limits, this model exhibits both CS and ES, where CS can be observed for a fixed coupling strength and ES appears when the coupling is increased adiabatically. Moreover, we show both theoretically and numerically that there are a variety of CS basin patterns for the case of identical oscillators, depending on the distributions of both the initial order parameters and the initial average phases. This model suggests a way to easily observe CS, in contrast to other models having some (weak or strong) dependence on initial conditions.

  2. Granger causality for state-space models

    NASA Astrophysics Data System (ADS)

    Barnett, Lionel; Seth, Anil K.

    2015-04-01

    Granger causality has long been a prominent method for inferring causal interactions between stochastic variables for a broad range of complex physical systems. However, it has been recognized that a moving average (MA) component in the data presents a serious confound to Granger causal analysis, as routinely performed via autoregressive (AR) modeling. We solve this problem by demonstrating that Granger causality may be calculated simply and efficiently from the parameters of a state-space (SS) model. Since SS models are equivalent to autoregressive moving average models, Granger causality estimated in this fashion is not degraded by the presence of a MA component. This is of particular significance when the data has been filtered, downsampled, observed with noise, or is a subprocess of a higher dimensional process, since all of these operations—commonplace in application domains as diverse as climate science, econometrics, and the neurosciences—induce a MA component. We show how Granger causality, conditional and unconditional, in both time and frequency domains, may be calculated directly from SS model parameters via solution of a discrete algebraic Riccati equation. Numerical simulations demonstrate that Granger causality estimators thus derived have greater statistical power and smaller bias than AR estimators. We also discuss how the SS approach facilitates relaxation of the assumptions of linearity, stationarity, and homoscedasticity underlying current AR methods, thus opening up potentially significant new areas of research in Granger causal analysis.

  3. Finite state modeling of aeroelastic systems

    NASA Technical Reports Server (NTRS)

    Vepa, R.

    1977-01-01

    A general theory of finite state modeling of aerodynamic loads on thin airfoils and lifting surfaces performing completely arbitrary, small, time-dependent motions in an airstream is developed and presented. The nature of the behavior of the unsteady airloads in the frequency domain is explained, using as raw materials any of the unsteady linearized theories that have been mechanized for simple harmonic oscillations. Each desired aerodynamic transfer function is approximated by means of an appropriate Pade approximant, that is, a rational function of finite degree polynomials in the Laplace transform variable. The modeling technique is applied to several two dimensional and three dimensional airfoils. Circular, elliptic, rectangular and tapered planforms are considered as examples. Identical functions are also obtained for control surfaces for two and three dimensional airfoils.

  4. A 2-categorical state sum model

    SciTech Connect

    Baratin, Aristide; Freidel, Laurent

    2015-01-15

    It has long been argued that higher categories provide the proper algebraic structure underlying state sum invariants of 4-manifolds. This idea has been refined recently, by proposing to use 2-groups and their representations as specific examples of 2-categories. The challenge has been to make these proposals fully explicit. Here, we give a concrete realization of this program. Building upon our earlier work with Baez and Wise on the representation theory of 2-groups, we construct a four-dimensional state sum model based on a categorified version of the Euclidean group. We define and explicitly compute the simplex weights, which may be viewed a categorified analogue of Racah-Wigner 6j-symbols. These weights solve a hexagon equation that encodes the formal invariance of the state sum under the Pachner moves of the triangulation. This result unravels the combinatorial formulation of the Feynman amplitudes of quantum field theory on flat spacetime proposed in A. Baratin and L. Freidel [Classical Quantum Gravity 24, 2027–2060 (2007)] which was shown to lead after gauge-fixing to Korepanov’s invariant of 4-manifolds.

  5. Active State Model for Autonomous Systems

    NASA Technical Reports Server (NTRS)

    Park, Han; Chien, Steve; Zak, Michail; James, Mark; Mackey, Ryan; Fisher, Forest

    2003-01-01

    The concept of the active state model (ASM) is an architecture for the development of advanced integrated fault-detection-and-isolation (FDI) systems for robotic land vehicles, pilotless aircraft, exploratory spacecraft, or other complex engineering systems that will be capable of autonomous operation. An FDI system based on the ASM concept would not only provide traditional diagnostic capabilities, but also integrate the FDI system under a unified framework and provide mechanism for sharing of information between FDI subsystems to fully assess the overall health of the system. The ASM concept begins with definitions borrowed from psychology, wherein a system is regarded as active when it possesses self-image, self-awareness, and an ability to make decisions itself, such that it is able to perform purposeful motions and other transitions with some degree of autonomy from the environment. For an engineering system, self-image would manifest itself as the ability to determine nominal values of sensor data by use of a mathematical model of itself, and selfawareness would manifest itself as the ability to relate sensor data to their nominal values. The ASM for such a system may start with the closed-loop control dynamics that describe the evolution of state variables. As soon as this model was supplemented with nominal values of sensor data, it would possess self-image. The ability to process the current sensor data and compare them with the nominal values would represent self-awareness. On the basis of self-image and self-awareness, the ASM provides the capability for self-identification, detection of abnormalities, and self-diagnosis.

  6. Functional state modelling approach validation for yeast and bacteria cultivations

    PubMed Central

    Roeva, Olympia; Pencheva, Tania

    2014-01-01

    In this paper, the functional state modelling approach is validated for modelling of the cultivation of two different microorganisms: yeast (Saccharomyces cerevisiae) and bacteria (Escherichia coli). Based on the available experimental data for these fed-batch cultivation processes, three different functional states are distinguished, namely primary product synthesis state, mixed oxidative state and secondary product synthesis state. Parameter identification procedures for different local models are performed using genetic algorithms. The simulation results show high degree of adequacy of the models describing these functional states for both S. cerevisiae and E. coli cultivations. Thus, the local models are validated for the cultivation of both microorganisms. This fact is a strong structure model verification of the functional state modelling theory not only for a set of yeast cultivations, but also for bacteria cultivation. As such, the obtained results demonstrate the efficiency and efficacy of the functional state modelling approach. PMID:26740778

  7. State-space size considerations for disease-progression models.

    PubMed

    Regnier, Eva D; Shechter, Steven M

    2013-09-30

    Markov models of disease progression are widely used to model transitions in patients' health state over time. Usually, patients' health status may be classified according to a set of ordered health states. Modelers lump together similar health states into a finite and usually small, number of health states that form the basis of a Markov chain disease-progression model. This increases the number of observations used to estimate each parameter in the transition probability matrix. However, lumping together observably distinct health states also obscures distinctions among them and may reduce the predictive power of the model. Moreover, as we demonstrate, precision in estimating the model parameters does not necessarily improve as the number of states in the model declines. This paper explores the tradeoff between lumping error introduced by grouping distinct health states and sampling error that arises when there are insufficient patient data to precisely estimate the transition probability matrix. PMID:23609629

  8. Modeling diurnal hormone profiles by hierarchical state space models.

    PubMed

    Liu, Ziyue; Guo, Wensheng

    2015-10-30

    Adrenocorticotropic hormone (ACTH) diurnal patterns contain both smooth circadian rhythms and pulsatile activities. How to evaluate and compare them between different groups is a challenging statistical task. In particular, we are interested in testing (1) whether the smooth ACTH circadian rhythms in chronic fatigue syndrome and fibromyalgia patients differ from those in healthy controls and (2) whether the patterns of pulsatile activities are different. In this paper, a hierarchical state space model is proposed to extract these signals from noisy observations. The smooth circadian rhythms shared by a group of subjects are modeled by periodic smoothing splines. The subject level pulsatile activities are modeled by autoregressive processes. A functional random effect is adopted at the pair level to account for the matched pair design. Parameters are estimated by maximizing the marginal likelihood. Signals are extracted as posterior means. Computationally efficient Kalman filter algorithms are adopted for implementation. Application of the proposed model reveals that the smooth circadian rhythms are similar in the two groups but the pulsatile activities in patients are weaker than those in the healthy controls. PMID:26152819

  9. RNA fragment modeling with a nucleobase discrete-state model

    NASA Astrophysics Data System (ADS)

    Zhang, Jian; Bian, Yunqiang; Lin, Hui; Wang, Wei

    2012-02-01

    In this work we develop an approach for predicting the tertiary structures of RNA fragments by combining an RNA nucleobase discrete state (RNAnbds) model, a sequential Monte Carlo method, and a statistical potential. The RNAnbds model is designed for optimizing the configuration of nucleobases with respect to their preceding ones along the sequence and their spatial neighbors, in contrast to previous works that focus on RNA backbones. The tests of our approach with the fragments taken from a small RNA pseudoknot and a 23S ribosome RNA show that for short fragments (<10 nucleotides), the root mean square deviations (RMSDs) between the predicted and the experimental ones are generally smaller than 3 Å; for slightly longer fragments (10-15 nucleotides), most RMSDs are smaller than 4 Å. The comparison of our method with another physics-based predictor with a testing set containing nine loops shows that ours is superior in both accuracy and efficiency. Our approach is useful in facilitating RNA three-dimensional structure prediction as well as loop modeling. It also holds the promise of providing insight into the structural ensembles of RNA loops.

  10. The economic impact of Los Alamos National Laboratory on north-central New Mexico and the state of New Mexico fiscal year 1998

    SciTech Connect

    Lansford, R.R.; Adcock, L.D.; Gentry, L.M.; Ben-David, S.; Temple, J.

    1999-08-05

    Los Alamos National Laboratory (LANL) is a multidisciplinary, multiprogram laboratory with a mission to enhance national military and economic security through science and technology. Its mission is to reduce the nuclear danger through stewardship of the nation`s nuclear stockpile and through its nonproliferation and verification activities. An important secondary mission is to promote US industrial competitiveness by working with US companies in technology transfer and technology development partnerships. Los Alamos is involved in partnerships and collaborations with other federal agencies, with industry (including New Mexico businesses), and with universities worldwide. For this report, the reference period is FY 1998 (October 1, 1997, through September 30, 1998). It includes two major impact analysis: the impact of LANL activities on north-central New Mexico and the economic impacts of LANL on the state of New Mexico. Total impact represents both direct and indirect responding by business, including induced effects (responding by households). The standard multipliers used in determining impacts result from the inter-industry, input-output models developed for the three-county region and the state of New Mexico.

  11. The economic impact of Los Alamos National Laboratory on north-central New Mexico and the state of New Mexico fiscal year 1997

    SciTech Connect

    Lansford, R.R.; Nielsen, T.G.; Schultz, J.; Adcock, L.D.; Gentry, L.M.; Ben-David, S.; Temple, J.

    1998-05-29

    Los Alamos National Laboratory (LANL) is a multidisciplinary, multiprogram laboratory with a mission to enhance national military and economic security through science and technology. Its mission is to reduce the nuclear danger through stewardship of the nation`s nuclear stockpile and through its nonproliferation and verification activities. An important secondary mission is to promote US industrial competitiveness by working with US companies in technology transfer and technology development partnerships. Los Alamos is involved in partnerships and collaborations with other federal agencies, with industry (including New Mexico businesses), and with universities worldwide. For this report, the reference period is FY 1997 (October 1, 1996, through September 30, 1997) and includes two major impact analysis: the impact of LANL activities on north-central New Mexico and the economic impacts of LANL on the state of New Mexico. Total impact represents both direct and indirect respending by business, including induced effects (respending by households). The standard multipliers used in determining impacts result from the inter-industry, input-output models developed for the three-county region and the state of New Mexico. 5 figs., 12 tabs.

  12. Workforce Training: The Pellissippi State Model.

    ERIC Educational Resources Information Center

    Bogaty, Lisa; And Others

    A discussion is provided of the role of community colleges as the primary delivery sources for workforce retraining, using the Pellissippi State Workforce Innovation Program as a case study. The first sections of the paper document the need for worker retraining in the United States, reporting the Department of Labor Secretary's Commission on…

  13. Assessing the State of Substitution Models Describing Noncoding RNA Evolution

    PubMed Central

    Allen, James E.; Whelan, Simon

    2014-01-01

    Phylogenetic inference is widely used to investigate the relationships between homologous sequences. RNA molecules have played a key role in these studies because they are present throughout life and tend to evolve slowly. Phylogenetic inference has been shown to be dependent on the substitution model used. A wide range of models have been developed to describe RNA evolution, either with 16 states describing all possible canonical base pairs or with 7 states where the 10 mismatched nucleotides are reduced to a single state. Formal model selection has become a standard practice for choosing an inferential model and works well for comparing models of a specific type, such as comparisons within nucleotide models or within amino acid models. Model selection cannot function across different sized state spaces because the likelihoods are conditioned on different data. Here, we introduce statistical state-space projection methods that allow the direct comparison of likelihoods between nucleotide models and 7-state and 16-state RNA models. To demonstrate the general applicability of our new methods, we extract 287 RNA families from genomic alignments and perform model selection. We find that in 281/287 families, RNA models are selected in preference to nucleotide models, with simple 7-state RNA models selected for more conserved families with shorter stems and more complex 16-state RNA models selected for more divergent families with longer stems. Other factors, such as the function of the RNA molecule or the GC-content, have limited impact on model selection. Our models and model selection methods are freely available in the open-source PHASE 3.0 software. PMID:24391153

  14. Numerical implementation of a state variable model for friction

    SciTech Connect

    Korzekwa, D.A.; Boyce, D.E.

    1995-03-01

    A general state variable model for friction has been incorporated into a finite element code for viscoplasticity. A contact area evolution model is used in a finite element model of a sheet forming friction test. The results show that a state variable model can be used to capture complex friction behavior in metal forming simulations. It is proposed that simulations can play an important role in the analysis of friction experiments and the development of friction models.

  15. Viral kinetic modeling: state of the art

    SciTech Connect

    Canini, Laetitia; Perelson, Alan S.

    2014-06-25

    Viral kinetic modeling has led to increased understanding of the within host dynamics of viral infections and the effects of therapy. Here we review recent developments in the modeling of viral infection kinetics with emphasis on two infectious diseases: hepatitis C and influenza. We review how viral kinetic modeling has evolved from simple models of viral infections treated with a drug or drug cocktail with an assumed constant effectiveness to models that incorporate drug pharmacokinetics and pharmacodynamics, as well as phenomenological models that simply assume drugs have time varying-effectiveness. We also discuss multiscale models that include intracellular events in viral replication, models of drug-resistance, models that include innate and adaptive immune responses and models that incorporate cell-to-cell spread of infection. Overall, viral kinetic modeling has provided new insights into the understanding of the disease progression and the modes of action of several drugs. In conclusion, we expect that viral kinetic modeling will be increasingly used in the coming years to optimize drug regimens in order to improve therapeutic outcomes and treatment tolerability for infectious diseases.

  16. Viral kinetic modeling: state of the art

    DOE PAGESBeta

    Canini, Laetitia; Perelson, Alan S.

    2014-06-25

    Viral kinetic modeling has led to increased understanding of the within host dynamics of viral infections and the effects of therapy. Here we review recent developments in the modeling of viral infection kinetics with emphasis on two infectious diseases: hepatitis C and influenza. We review how viral kinetic modeling has evolved from simple models of viral infections treated with a drug or drug cocktail with an assumed constant effectiveness to models that incorporate drug pharmacokinetics and pharmacodynamics, as well as phenomenological models that simply assume drugs have time varying-effectiveness. We also discuss multiscale models that include intracellular events in viralmore » replication, models of drug-resistance, models that include innate and adaptive immune responses and models that incorporate cell-to-cell spread of infection. Overall, viral kinetic modeling has provided new insights into the understanding of the disease progression and the modes of action of several drugs. In conclusion, we expect that viral kinetic modeling will be increasingly used in the coming years to optimize drug regimens in order to improve therapeutic outcomes and treatment tolerability for infectious diseases.« less

  17. Identification of linear system models and state estimators for controls

    NASA Technical Reports Server (NTRS)

    Chen, Chung-Wen

    1992-01-01

    The following paper is presented in viewgraph format and covers topics including: (1) linear state feedback control system; (2) Kalman filter state estimation; (3) relation between residual and stochastic part of output; (4) obtaining Kalman filter gain; (5) state estimation under unknown system model and unknown noises; and (6) relationship between filter Markov parameters and system Markov parameters.

  18. Quantum entangled supercorrelated states in the Jaynes-Cummings model

    NASA Astrophysics Data System (ADS)

    Rajagopal, A. K.; Jensen, K. L.; Cummings, F. W.

    1999-08-01

    The regions of independent quantum states, maximally classically correlated states, and purely quantum entangled (supercorrelated) states described in a recent formulation of quantum information theory by Cerf and Adami are explored here numerically in the parameter space of the well-known exactly soluble Jaynes-Cummings model for equilibrium and nonequilibrium time-dependent ensembles.

  19. Comparing State SAT Scores Using a Mixture Modeling Approach

    ERIC Educational Resources Information Center

    Kim, YoungKoung Rachel

    2009-01-01

    Presented at the national conference for AERA (American Educational Research Association) in April 2009. The large variability of SAT taker population across states makes state-by-state comparisons of the SAT scores challenging. Using a mixture modeling approach, therefore, the current study presents a method of identifying subpopulations in terms…

  20. The folding transition state theory in simple model systems

    NASA Astrophysics Data System (ADS)

    Niewieczerzał, Szymon; Cieplak, Marek

    2008-06-01

    We present the results of an exact analysis of several model free energy landscapes of a protein to clarify the notion of the transition state and the physical meaning of the phi values determined in protein engineering experiments. We argue that a proper search strategy for the transition state in more realistic models should involve identification of a common part of various methods. Two of the models considered involve explicit conformations instead of just points on the free energy axis. These models are minimalistic as they are endowed only with five or 36 states to enumerate folding paths and to identify the transition state easily. Even though they display much of the two-state behavior, the phi values are found not to correspond to the conformation of the transition state.

  1. Development of Water Quality Modeling in the United States

    EPA Science Inventory

    This presentation describes historical trends in water quality model development in the United States, reviews current efforts, and projects promising future directions. Water quality modeling has a relatively long history in the United States. While its origins lie in the work...

  2. Matrix model for non-Abelian quantum Hall states

    NASA Astrophysics Data System (ADS)

    Dorey, Nick; Tong, David; Turner, Carl

    2016-08-01

    We propose a matrix quantum mechanics for a class of non-Abelian quantum Hall states. The model describes electrons which carry an internal SU(p ) spin. The ground states of the matrix model include spin-singlet generalizations of the Moore-Read and Read-Rezayi states and, in general, lie in a class previously introduced by Blok and Wen. The effective action for these states is a U(p ) Chern-Simons theory. We show how the matrix model can be derived from quantization of the vortices in this Chern-Simons theory and how the matrix model ground states can be reconstructed as correlation functions in the boundary WZW model.

  3. Descriptive Linear modeling of steady-state visual evoked response

    NASA Technical Reports Server (NTRS)

    Levison, W. H.; Junker, A. M.; Kenner, K.

    1986-01-01

    A study is being conducted to explore use of the steady state visual-evoke electrocortical response as an indicator of cognitive task loading. Application of linear descriptive modeling to steady state Visual Evoked Response (VER) data is summarized. Two aspects of linear modeling are reviewed: (1) unwrapping the phase-shift portion of the frequency response, and (2) parsimonious characterization of task-loading effects in terms of changes in model parameters. Model-based phase unwrapping appears to be most reliable in applications, such as manual control, where theoretical models are available. Linear descriptive modeling of the VER has not yet been shown to provide consistent and readily interpretable results.

  4. ADVANCED UTILITY SIMULATION MODEL DESCRIPTION OF MODIFICATIONS TO THE STATE LEVEL MODEL (VERSION 3.0)

    EPA Science Inventory

    The report documents modifications to the state level model portion of the Advanced Utility Simulation Model (AUSM), one of four stationary source emission and control cost forecasting models developed for the National Acid Precipitation Assessment Program (NAPAP). The AUSM model...

  5. State of Modeling Symmetry in Hohlraums

    SciTech Connect

    Jones, O. S.

    2015-07-22

    Modeling radiation drive asymmetry is challenging problem whose agreement with data depends on the hohlraum gas fill density. Modeling to date uses the HYDRA code with crossbeam energy transfer (CBET) calculated separately, and backscattered light removed from the input laser. For high fill hohlraums (~>1 mg/cc), matching symmetry requires ad hoc adjustments to CBET during picket and peak of drive. For near-vacuum hohlraums, there is little CBET or backscatter, and drive is more waist-high than predicted. For intermediate fill densities (~0.6 mg/cc) there appears to be a region of small CBET and backscatter where symmetry is reasonably well modeled. A new technique where backscatter and CBET are done “inline” appears it could bring high fill simulations closer to data.

  6. Minimal model for spoof acoustoelastic surface states

    SciTech Connect

    Christensen, J. Willatzen, M.; Liang, Z.

    2014-12-15

    Similar to textured perfect electric conductors for electromagnetic waves sustaining artificial or spoof surface plasmons we present an equivalent phenomena for the case of sound. Aided by a minimal model that is able to capture the complex wave interaction of elastic cavity modes and airborne sound radiation in perfect rigid panels, we construct designer acoustoelastic surface waves that are entirely controlled by the geometrical environment. Comparisons to results obtained by full-wave simulations confirm the feasibility of the model and we demonstrate illustrative examples such as resonant transmissions and waveguiding to show a few examples of many where spoof elastic surface waves are useful.

  7. Skyrme models and nuclear matter equation of state

    NASA Astrophysics Data System (ADS)

    Adam, C.; Haberichter, M.; Wereszczynski, A.

    2015-11-01

    We investigate the role of pressure in a class of generalized Skyrme models. We introduce pressure as the trace of the spatial part of the energy-momentum tensor and show that it obeys the usual thermodynamical relation. Then, we compute analytically the mean-field equation of state in the high- and medium-pressure regimes by applying topological bounds on compact domains. The equation of state is further investigated numerically for the charge-one Skyrmions. We identify which term in a generalized Skyrme model is responsible for which part in the equation of state. Further, we compare our findings with the corresponding results in the Walecka model.

  8. Metropolitan and state economic regions (MASTER) model - overview

    SciTech Connect

    Adams, R.C.; Moe, R.J.; Scott, M.J.

    1983-05-01

    The Metropolitan and State Economic Regions (MASTER) model is a unique multi-regional economic model designed to forecast regional economic activity and assess the regional economic impacts caused by national and regional economic changes (e.g., interest rate fluctuations, energy price changes, construction and operation of a nuclear waste storage facility, shutdown of major industrial operations). MASTER can be applied to any or all of the 268 Standard Metropolitan Statistical Areas (SMSAs) and 48 non-SMSA rest-of-state-areas (ROSAs) in the continental US. The model can also be applied to any or all of the continental US counties and states. This report is divided into four sections: capabilities and applications of the MASTER model, development of the model, model simulation, and validation testing.

  9. Infinite Factorial Unbounded-State Hidden Markov Model.

    PubMed

    Valera, Isabel; Ruiz, Francisco J R; Perez-Cruz, Fernando

    2016-09-01

    There are many scenarios in artificial intelligence, signal processing or medicine, in which a temporal sequence consists of several unknown overlapping independent causes, and we are interested in accurately recovering those canonical causes. Factorial hidden Markov models (FHMMs) present the versatility to provide a good fit to these scenarios. However, in some scenarios, the number of causes or the number of states of the FHMM cannot be known or limited a priori. In this paper, we propose an infinite factorial unbounded-state hidden Markov model (IFUHMM), in which the number of parallel hidden Markovmodels (HMMs) and states in each HMM are potentially unbounded. We rely on a Bayesian nonparametric (BNP) prior over integer-valued matrices, in which the columns represent the Markov chains, the rows the time indexes, and the integers the state for each chain and time instant. First, we extend the existent infinite factorial binary-state HMM to allow for any number of states. Then, we modify this model to allow for an unbounded number of states and derive an MCMC-based inference algorithm that properly deals with the trade-off between the unbounded number of states and chains. We illustrate the performance of our proposed models in the power disaggregation problem. PMID:26571511

  10. Resilience-based application of state-and-transition models

    Technology Transfer Automated Retrieval System (TEKTRAN)

    We recommend that several conceptual modifications be incorporated into the state-and-transition model (STM) framework to: 1) explicitly link this framework to the concept of ecological resilience, 2) direct management attention away from thresholds and toward the maintenance of state resilience, an...

  11. Steady-state CO/sub 2/ laser model

    SciTech Connect

    Scott, M.W.; Myers, G.D.

    1984-09-01

    A steady-state CO/sub 2/ lase model is reported which can be used to predict and evaluate the performance of cw slow-flow and no-flow CO/sub 2/ lasers. Traditional CO/sub 2/ laser models require the solution of several simultaneous differential equations and can be used to model pulsed and fast-flow lasers in addition to cw and slow-flow devices. The model reported here is computationally simpler, requiring only a routine to solve one equation in one unknown, but is only useful for lasers which operate in the steady state.

  12. A comparison of weighted ensemble and Markov state model methodologies

    NASA Astrophysics Data System (ADS)

    Feng, Haoyun; Costaouec, Ronan; Darve, Eric; Izaguirre, Jesús A.

    2015-06-01

    Computation of reaction rates and elucidation of reaction mechanisms are two of the main goals of molecular dynamics (MD) and related simulation methods. Since it is time consuming to study reaction mechanisms over long time scales using brute force MD simulations, two ensemble methods, Markov State Models (MSMs) and Weighted Ensemble (WE), have been proposed to accelerate the procedure. Both approaches require clustering of microscopic configurations into networks of "macro-states" for different purposes. MSMs model a discretization of the original dynamics on the macro-states. Accuracy of the model significantly relies on the boundaries of macro-states. On the other hand, WE uses macro-states to formulate a resampling procedure that kills and splits MD simulations for achieving better efficiency of sampling. Comparing to MSMs, accuracy of WE rate predictions is less sensitive to the definition of macro-states. Rigorous numerical experiments using alanine dipeptide and penta-alanine support our analyses. It is shown that MSMs introduce significant biases in the computation of reaction rates, which depend on the boundaries of macro-states, and Accelerated Weighted Ensemble (AWE), a formulation of weighted ensemble that uses the notion of colors to compute fluxes, has reliable flux estimation on varying definitions of macro-states. Our results suggest that whereas MSMs provide a good idea of the metastable sets and visualization of overall dynamics, AWE provides reliable rate estimations requiring less efforts on defining macro-states on the high dimensional conformational space.

  13. Analysis and Modelling of the Steady-State and Dynamic-State Discharge in SMES System

    NASA Astrophysics Data System (ADS)

    Chen, Xiao Yuan; Jin, Jian Xun

    The steady-state and dynamic-state discharge processes have been discussed to develop a superconducting magnetic energy storage (SMES) model in the paper. The SMES model allows the integrated analysis and optimization of the SMES devices, and their control systems, and can also serve as an independent storage module in the practical SMES application circuits, thus provide a method to link superconductivity technology to conventional power electronics in a SMES device.

  14. Neural mass model-based tracking of anesthetic brain states.

    PubMed

    Kuhlmann, Levin; Freestone, Dean R; Manton, Jonathan H; Heyse, Bjorn; Vereecke, Hugo E M; Lipping, Tarmo; Struys, Michel M R F; Liley, David T J

    2016-06-01

    Neural mass model-based tracking of brain states from electroencephalographic signals holds the promise of simultaneously tracking brain states while inferring underlying physiological changes in various neuroscientific and clinical applications. Here, neural mass model-based tracking of brain states using the unscented Kalman filter applied to estimate parameters of the Jansen-Rit cortical population model is evaluated through the application of propofol-based anesthetic state monitoring. In particular, 15 subjects underwent propofol anesthesia induction from awake to anesthetised while behavioral responsiveness was monitored and frontal electroencephalographic signals were recorded. The unscented Kalman filter Jansen-Rit model approach applied to frontal electroencephalography achieved reasonable testing performance for classification of the anesthetic brain state (sensitivity: 0.51; chance sensitivity: 0.17; nearest neighbor sensitivity 0.75) when compared to approaches based on linear (autoregressive moving average) modeling (sensitivity 0.58; nearest neighbor sensitivity: 0.91) and a high performing standard depth of anesthesia monitoring measure, Higuchi Fractal Dimension (sensitivity: 0.50; nearest neighbor sensitivity: 0.88). Moreover, it was found that the unscented Kalman filter based parameter estimates of the inhibitory postsynaptic potential amplitude varied in the physiologically expected direction with increases in propofol concentration, while the estimates of the inhibitory postsynaptic potential rate constant did not. These results combined with analysis of monotonicity of parameter estimates, error analysis of parameter estimates, and observability analysis of the Jansen-Rit model, along with considerations of extensions of the Jansen-Rit model, suggests that the Jansen-Rit model combined with unscented Kalman filtering provides a valuable reference point for future real-time brain state tracking studies. This is especially true for studies of

  15. State variable modeling of the integrated engine and aircraft dynamics

    NASA Astrophysics Data System (ADS)

    Rotaru, Constantin; Sprinţu, Iuliana

    2014-12-01

    This study explores the dynamic characteristics of the combined aircraft-engine system, based on the general theory of the state variables for linear and nonlinear systems, with details leading first to the separate formulation of the longitudinal and the lateral directional state variable models, followed by the merging of the aircraft and engine models into a single state variable model. The linearized equations were expressed in a matrix form and the engine dynamics was included in terms of variation of thrust following a deflection of the throttle. The linear model of the shaft dynamics for a two-spool jet engine was derived by extending the one-spool model. The results include the discussion of the thrust effect upon the aircraft response when the thrust force associated with the engine has a sizable moment arm with respect to the aircraft center of gravity for creating a compensating moment.

  16. Compact Two-State-Variable Second-Order Memristor Model.

    PubMed

    Kim, Sungho; Kim, Hee-Dong; Choi, Sung-Jin

    2016-06-01

    A key requirement for using memristors in functional circuits is a predictive physical model to capture the resistive switching behavior, which shall be compact enough to be implemented using a circuit simulator. Although a number of memristor models have been developed, most of these models (i.e., first-order memristor models) have utilized only a one-state-variable. However, such simplification is not adequate for accurate modeling because multiple mechanisms are involved in resistive switching. Here, a two-state-variable based second-order memristor model is presented, which considers the axial drift of the charged vacancies in an applied electric field and the radial vacancy motion caused by the thermophoresis and diffusion. In particular, this model emulates the details of the intrinsic short-term dynamics, such as decay and temporal heat summation, and therefore, it accurately predicts the resistive switching characteristics for both DC and AC input signals. PMID:27152649

  17. Modeling of bi-equilibrium states in dielectric elastomer

    NASA Astrophysics Data System (ADS)

    Peng, Longgui

    2014-03-01

    Dielectric elastomer is a soft active material, producing fast deformation under voltage-activation. Under a specific boundary condition, trussed dielectric elastomer elongates mimicking the behavior of biological muscle. During this process, dielectric elastomer experiences a snap from one deformation mode to another, though both at the electromechanical equilibrium states. Based on thermodynamics, models are established to investigate electromechanical coupling at the two equilibrium states. Particular emphasis is devoted to establishing the governing equations of the two deformation modes with physical interpretations. The transition of equilibrium state is discussed, to predict the attainable stable state for application.

  18. A nonlocal, ordinary, state-based plasticity model for peridynamics.

    SciTech Connect

    Mitchell, John Anthony

    2011-05-01

    An implicit time integration algorithm for a non-local, state-based, peridynamics plasticity model is developed. The flow rule was proposed in [3] without an integration strategy or yield criterion. This report addresses both of these issues and thus establishes the first ordinary, state-based peridynamics plasticity model. Integration of the flow rule follows along the lines of the classical theories of rate independent J{sub 2} plasticity. It uses elastic force state relations, an additive decomposition of the deformation state, an elastic force state domain, a flow rule, loading/un-loading conditions, and a consistency condition. Just as in local theories of plasticity (LTP), state variables are required. It is shown that the resulting constitutive model does not violate the 2nd law of thermodynamics. The report also develops a useful non-local yield criterion that depends upon the yield stress and horizon for the material. The modulus state for both the ordinary elastic material and aforementioned plasticity model is also developed and presented.

  19. Modeling solid-state transformations occurring in dissolution testing.

    PubMed

    Laaksonen, Timo; Aaltonen, Jaakko

    2013-04-15

    Changes in the solid-state form can occur during dissolution testing of drugs. This can often complicate interpretation of results. Additionally, there can be several mechanisms through which such a change proceeds, e.g. solvent-mediated transformation or crystal growth within the drug material itself. Here, a mathematical model was constructed to study the dissolution testing of a material, which undergoes such changes. The model consisted of two processes: the recrystallization of the drug from a supersaturated liquid state caused by the dissolution of the more soluble solid form and the crystal growth of the stable solid form at the surface of the drug formulation. Comparison to experimental data on theophylline dissolution showed that the results obtained with the model matched real solid-state changes and that it was able to distinguish between cases where the transformation was controlled either by solvent-mediated crystallization or solid-state crystal growth. PMID:23506958

  20. Ontology and modeling patterns for state-based behavior representation

    NASA Technical Reports Server (NTRS)

    Castet, Jean-Francois; Rozek, Matthew L.; Ingham, Michel D.; Rouquette, Nicolas F.; Chung, Seung H.; Kerzhner, Aleksandr A.; Donahue, Kenneth M.; Jenkins, J. Steven; Wagner, David A.; Dvorak, Daniel L.; Karban, Robert

    2015-01-01

    This paper provides an approach to capture state-based behavior of elements, that is, the specification of their state evolution in time, and the interactions amongst them. Elements can be components (e.g., sensors, actuators) or environments, and are characterized by state variables that vary with time. The behaviors of these elements, as well as interactions among them are represented through constraints on state variables. This paper discusses the concepts and relationships introduced in this behavior ontology, and the modeling patterns associated with it. Two example cases are provided to illustrate their usage, as well as to demonstrate the flexibility and scalability of the behavior ontology: a simple flashlight electrical model and a more complex spacecraft model involving instruments, power and data behaviors. Finally, an implementation in a SysML profile is provided.

  1. EXPOSURE ASSESSMENT MODELING: A STATE-OF-THE-ART REVIEW

    EPA Science Inventory

    The state-of-the-art review of exposure assessment modeling describes currently available models that simulate the environmental fate of substances, the exposure to such substances, and the effects of such exposure. The focus is first on exposure and effects, where relatively lit...

  2. Periodic ground state for the charged massive Schwinger model

    SciTech Connect

    Nagy, S.; Sailer, K.; Polonyi, J.

    2004-11-15

    It is shown that the charged massive Schwinger model supports a periodic vacuum structure for arbitrary charge density, similar to the common crystalline layout known in solid state physics. The dynamical origin of the inhomogeneity is identified in the framework of the bosonized model and in terms of the original fermionic variables.

  3. Simulation of the 3-state Potts model with chemical potential

    SciTech Connect

    Mercado, Ydalia Delgado; Gattringer, Christof; Evertz, Hans Gerd

    2011-05-23

    The 3-state Potts model with chemical potential is mapped to a flux representation where the complex action problem is resolved. We perform a Monte Carlo simulation based on a worm algorithm to study the phase diagram of the model. Our results shed light on the role which center symmetry and its breaking play for the QCD phase diagram.

  4. Funding Models of Community Colleges in 10 Midwest States

    ERIC Educational Resources Information Center

    Kenton, Carol Piper; Schuh, John H.; Huba, Mary E.; Shelley, Mack C., II

    2004-01-01

    The extent to which community colleges in 10 Midwest states relied on 12 current funds revenue sources between 1990 and 2000 is presented in this study. Four models of funding were identified and evaluated. All models generated revenue in excess of the change in the Higher Education Price Index (HEPI), a measure of inflation over the period…

  5. Thermodynamic State Ensemble Models of cis-Regulation

    PubMed Central

    Sherman, Marc S.; Cohen, Barak A.

    2012-01-01

    A major goal in computational biology is to develop models that accurately predict a gene's expression from its surrounding regulatory DNA. Here we present one class of such models, thermodynamic state ensemble models. We describe the biochemical derivation of the thermodynamic framework in simple terms, and lay out the mathematical components that comprise each model. These components include (1) the possible states of a promoter, where a state is defined as a particular arrangement of transcription factors bound to a DNA promoter, (2) the binding constants that describe the affinity of the protein–protein and protein–DNA interactions that occur in each state, and (3) whether each state is capable of transcribing. Using these components, we demonstrate how to compute a cis-regulatory function that encodes the probability of a promoter being active. Our intention is to provide enough detail so that readers with little background in thermodynamics can compose their own cis-regulatory functions. To facilitate this goal, we also describe a matrix form of the model that can be easily coded in any programming language. This formalism has great flexibility, which we show by illustrating how phenomena such as competition between transcription factors and cooperativity are readily incorporated into these models. Using this framework, we also demonstrate that Michaelis-like functions, another class of cis-regulatory models, are a subset of the thermodynamic framework with specific assumptions. By recasting Michaelis-like functions as thermodynamic functions, we emphasize the relationship between these models and delineate the specific circumstances representable by each approach. Application of thermodynamic state ensemble models is likely to be an important tool in unraveling the physical basis of combinatorial cis-regulation and in generating formalisms that accurately predict gene expression from DNA sequence. PMID:22479169

  6. Extensive ground state entropy in supersymmetric lattice models

    SciTech Connect

    Eerten, Hendrik van

    2005-12-15

    We present the result of calculations of the Witten index for a supersymmetric lattice model on lattices of various type and size. Because the model remains supersymmetric at finite lattice size, the Witten index can be calculated using row-to-row transfer matrices and the calculations are similar to calculations of the partition function at negative activity -1. The Witten index provides a lower bound on the number of ground states. We find strong numerical evidence that the Witten index grows exponentially with the number of sites of the lattice, implying that the model has extensive entropy in the ground state.

  7. An autonomous DNA model for finite state automata.

    PubMed

    Martinez-Perez, Israel M; Zimmermann, Karl-Heinz; Ignatova, Zoya

    2009-01-01

    In this paper we introduce an autonomous DNA model for finite state automata. This model called sticker automaton model is based on the hybridisation of single stranded DNA molecules (stickers) encoding transition rules and input data. The computation is carried out in an autonomous manner by one enzyme which allows us to determine whether a resulting double-stranded DNA molecule belongs to the automaton's language or not. PMID:19136366

  8. Component system identification and state-space model synthesis

    NASA Astrophysics Data System (ADS)

    Sjövall, Per; Abrahamsson, Thomas

    2007-10-01

    A scheme for synthesis of subsystem state-space models to be used for analysis of dynamic behaviour of built-up structures is presented. Using measurements on each component, subsystem models are identified adopting contemporary system identification methods. The subsystem state-space models are transformed into a coupling form, at which kinematic constraints and equilibrium conditions for the interfaces are introduced. The procedure is applied to a plane frame structure, which is built up of two components. It is found that the non-trivial model order determination constitutes a crucial step in the process. If the model order is incorrect at subsystem level, the synthesized model may radically fail to describe the properties of the built-up structure. It is also found that the identified subsystem models need to satisfy certain physically motivated constraints, e.g. reciprocity and passivity. Different approaches and methods to aid the model order determination and the estimation of physically consistent state-space models at subsystem level are discussed.

  9. On the time to steady state: insights from numerical modeling

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

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

  10. Stochastic EM algorithm for nonlinear state estimation with model uncertainties

    NASA Astrophysics Data System (ADS)

    Zia, Amin; Kirubarajan, Thiagalingam; Reilly, James P.; Shirani, Shahram

    2004-01-01

    In most solutions to state estimation problems like, for example, target tracking, it is generally assumed that the state evolution and measurement models are known a priori. The model parameters include process and measurement matrices or functions as well as the corresponding noise statistics. However, there are situations where the model parameters are not known a priori or are known only partially (i.e., with some uncertainty). Moreover, there are situations where the measurement is biased. In these scenarios, standard estimation algorithms like the Kalman filter and the extended Kalman Filter (EKF), which assume perfect knowledge of the model parameters, are not accurate. In this paper, the problem with uncertain model parameters is considered as a special case of maximum likelihood estimation with incomplete-data, for which a standard solution called the expectation-maximization (EM) algorithm exists. In this paper a new extension to the EM algorithm is proposed to solve the more general problem of joint state estimation and model parameter identification for nonlinear systems with possibly non-Gaussian noise. In the expectation (E) step, it is shown that the best variational distribution over the state variables is the conditional posterior distribution of states given all the available measurements and inputs. Therefore, a particular type of particle filter is used to estimate and update the posterior distribution. In the maximization (M) step the nonlinear measurement process parameters are approximated using a nonlinear regression method for adjusting the parameters of a mixture of Gaussians (MofG). The proposed algorithm is used to solve a nonlinear bearing-only tracking problem similar to the one reported recently with uncertain measurement process. It is shown that the algorithm is capable of accurately tracking the state vector while identifying the unknown measurement dynamics. Simulation results show the advantages of the new technique over standard

  11. Stochastic EM algorithm for nonlinear state estimation with model uncertainties

    NASA Astrophysics Data System (ADS)

    Zia, Amin; Kirubarajan, Thiagalingam; Reilly, James P.; Shirani, Shahram

    2003-12-01

    In most solutions to state estimation problems like, for example, target tracking, it is generally assumed that the state evolution and measurement models are known a priori. The model parameters include process and measurement matrices or functions as well as the corresponding noise statistics. However, there are situations where the model parameters are not known a priori or are known only partially (i.e., with some uncertainty). Moreover, there are situations where the measurement is biased. In these scenarios, standard estimation algorithms like the Kalman filter and the extended Kalman Filter (EKF), which assume perfect knowledge of the model parameters, are not accurate. In this paper, the problem with uncertain model parameters is considered as a special case of maximum likelihood estimation with incomplete-data, for which a standard solution called the expectation-maximization (EM) algorithm exists. In this paper a new extension to the EM algorithm is proposed to solve the more general problem of joint state estimation and model parameter identification for nonlinear systems with possibly non-Gaussian noise. In the expectation (E) step, it is shown that the best variational distribution over the state variables is the conditional posterior distribution of states given all the available measurements and inputs. Therefore, a particular type of particle filter is used to estimate and update the posterior distribution. In the maximization (M) step the nonlinear measurement process parameters are approximated using a nonlinear regression method for adjusting the parameters of a mixture of Gaussians (MofG). The proposed algorithm is used to solve a nonlinear bearing-only tracking problem similar to the one reported recently with uncertain measurement process. It is shown that the algorithm is capable of accurately tracking the state vector while identifying the unknown measurement dynamics. Simulation results show the advantages of the new technique over standard

  12. NARCCAP Model Validation for the Southeast United States

    NASA Astrophysics Data System (ADS)

    Kabela, E. D.; Carbone, G. J.

    2012-12-01

    Global climate models (GCMs) provide most projections of future climate change. But their coarse resolution limits their use in assessing regional climate change impacts on water resources, environmental quality, forest management, power plant operations, and many other fields. Such assessment requires translating global model output to more local scales. This research investigates dynamically downscaled regional climate model (RCM) output from the North American RegionalClimate Change Assessment Program (NARCCAP) in the Southeast United States. Analysis includes assessments of GCM and RCM performance and skill in the region during a historical reference period (1970-1999), with explanations of sources and magnitude of individual model bias. Three fundamental questions structure the research: 1) How skillful are dynamically downscaled models in simulating minimum and maximum temperature and mean precipitation in ahistorical reference period (1970-1999) for the Southeast United States? 2) What are the magnitude of biases for each NARCCAP member (and variable) and what is the potential source of the bias? 3) Does downscaling improve projections at local scales? In other words, is "value added" in downscaling? Analysis was performed on the states encompassing Alabama, Mississippi, and Tennessee (west sub-region), and Georgia, North Carolina, and South Carolina (east sub-region). Skill was determined using three methods: 1) Computing the overlap in probability density functions (PDF) between observations and models, 2) computing an index of agreement between models and observations, and 3) computing the root mean squared error (RMSE) between observations and models. Most models illustrated high skill for temperature. The outlier models included two RCMs run with the GFDL as their lateral boundary conditions; as these models suffered from a cold maximum temperature bias, attributed to erroneously high soil moisture. Precipitation skill using the PDF and index of

  13. Dynamic battery cell model and state of charge estimation

    NASA Astrophysics Data System (ADS)

    Wijewardana, S.; Vepa, R.; Shaheed, M. H.

    2016-03-01

    Mathematical modelling and the dynamic simulation of battery storage systems can be challenging and demanding due to the nonlinear nature of the battery chemistry. This paper introduces a new dynamic battery model, with application to state of charge estimation, considering all possible aspects of environmental conditions and variables. The aim of this paper is to present a suitable convenient, generic dynamic representation of rechargeable battery dynamics that can be used to model any Lithium-ion rechargeable battery. The proposed representation is used to develop a dynamic model considering the thermal balance of heat generation mechanism of the battery cell and the ambient temperature effect including other variables such as storage effects, cyclic charging, battery internal resistance, state of charge etc. The results of the simulations have been used to study the characteristics of a Lithium-ion battery and the proposed battery model is shown to produce responses within 98% of known experimental measurements.

  14. Animal Models of Psychosis: Current State and Future Directions

    PubMed Central

    Forrest, Alexandra D.; Coto, Carlos A.; Siegel, Steven J.

    2014-01-01

    Psychosis is an abnormal mental state characterized by disorganization, delusions and hallucinations. Animal models have become an increasingly important research tool in the effort to understand both the underlying pathophysiology and treatment of psychosis. There are multiple animal models for psychosis, with each formed by the coupling of a manipulation and a measurement. In this manuscript we do not address the diseases of which psychosis is a prominent comorbidity. Instead, we summarize the current state of affairs and future directions for animal models of psychosis. To accomplish this, our manuscript will first discuss relevant behavioral and electrophysiological measurements. We then provide an overview of the different manipulations that are combined with these measurements to produce animal models. The strengths and limitations of each model will be addressed in order to evaluate its cross-species comparability. PMID:25215267

  15. New Equation of State Models for Hydrodynamic Applications

    NASA Astrophysics Data System (ADS)

    Young, David A.; Barbee, Troy W., III; Rogers, Forrest J.

    1997-07-01

    Accurate models of the equation of state of matter at high pressures and temperatures are increasingly required for hydrodynamic simulations. We have developed two new approaches to accurate EOS modeling: 1) ab initio phonons from electron band structure theory for condensed matter and 2) the ACTEX dense plasma model for ultrahigh pressure shocks. We have studied the diamond and high pressure phases of carbon with the ab initio model and find good agreement between theory and experiment for shock Hugoniots, isotherms, and isobars. The theory also predicts a comprehensive phase diagram for carbon. For ultrahigh pressure shock states, we have studied the comparison of ACTEX theory with experiments for deuterium, beryllium, polystyrene, water, aluminum, and silicon dioxide. The agreement is good, showing that complex multispecies plasmas are treated adequately by the theory. These models will be useful in improving the numerical EOS tables used by hydrodynamic codes.

  16. Towards a Model Selection Rule for Quantum State Tomography

    NASA Astrophysics Data System (ADS)

    Scholten, Travis; Blume-Kohout, Robin

    Quantum tomography on large and/or complex systems will rely heavily on model selection techniques, which permit on-the-fly selection of small efficient statistical models (e.g. small Hilbert spaces) that accurately fit the data. Many model selection tools, such as hypothesis testing or Akaike's AIC, rely implicitly or explicitly on the Wilks Theorem, which predicts the behavior of the loglikelihood ratio statistic (LLRS) used to choose between models. We used Monte Carlo simulations to study the behavior of the LLRS in quantum state tomography, and found that it disagrees dramatically with Wilks' prediction. We propose a simple explanation for this behavior; namely, that boundaries (in state space and between models) play a significant role in determining the distribution of the LLRS. The resulting distribution is very complex, depending strongly both on the true state and the nature of the data. We consider a simplified model that neglects anistropy in the Fisher information, derive an almost analytic prediction for the mean value of the LLRS, and compare it to numerical experiments. While our simplified model outperforms the Wilks Theorem, it still does not predict the LLRS accurately, implying that alternative methods may be necessary for tomographic model selection. Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy's National Nuclear Security Administration under contract DE.

  17. Ground-state properties of the periodic Anderson model

    NASA Technical Reports Server (NTRS)

    Blankenbecler, R.; Fulco, J. R.; Gill, W.; Scalapino, D. J.

    1987-01-01

    The ground-state energy, hybridization matrix element, local moment, and spin-density correlations of a one-dimensional, finite-chain, periodic, symmetric Anderson model are obtained by numerical simulations and compared with perturbation theory and strong-coupling results. It is found that the local f-electron spins are compensated by correlation with other f-electrons as well as band electrons leading to a nonmagnetic ground state.

  18. Ground states of baryoleptonic Q-balls in supersymmetric models

    SciTech Connect

    Shoemaker, Ian M.; Kusenko, Alexander

    2008-10-01

    In supersymmetric generalizations of the standard model, all stable Q-balls are associated with some flat directions. We show that, if the flat direction has both the baryon number and the lepton number, the scalar field inside the Q-ball can deviate slightly from the flat direction in the ground state. We identify the true ground states of such nontopological solitons, including the electrically neutral and electrically charged Q-balls.

  19. Equation of State of the Two-Dimensional Hubbard Model.

    PubMed

    Cocchi, Eugenio; Miller, Luke A; Drewes, Jan H; Koschorreck, Marco; Pertot, Daniel; Brennecke, Ferdinand; Köhl, Michael

    2016-04-29

    The subtle interplay between kinetic energy, interactions, and dimensionality challenges our comprehension of strongly correlated physics observed, for example, in the solid state. In this quest, the Hubbard model has emerged as a conceptually simple, yet rich model describing such physics. Here we present an experimental determination of the equation of state of the repulsive two-dimensional Hubbard model over a broad range of interactions 0≲U/t≲20 and temperatures, down to k_{B}T/t=0.63(2) using high-resolution imaging of ultracold fermionic atoms in optical lattices. We show density profiles, compressibilities, and double occupancies over the whole doping range, and, hence, our results constitute benchmarks for state-of-the-art theoretical approaches. PMID:27176527

  20. Equation of State of the Two-Dimensional Hubbard Model

    NASA Astrophysics Data System (ADS)

    Cocchi, Eugenio; Miller, Luke A.; Drewes, Jan H.; Koschorreck, Marco; Pertot, Daniel; Brennecke, Ferdinand; Köhl, Michael

    2016-04-01

    The subtle interplay between kinetic energy, interactions, and dimensionality challenges our comprehension of strongly correlated physics observed, for example, in the solid state. In this quest, the Hubbard model has emerged as a conceptually simple, yet rich model describing such physics. Here we present an experimental determination of the equation of state of the repulsive two-dimensional Hubbard model over a broad range of interactions 0 ≲U /t ≲20 and temperatures, down to kBT /t =0.63 (2 ) using high-resolution imaging of ultracold fermionic atoms in optical lattices. We show density profiles, compressibilities, and double occupancies over the whole doping range, and, hence, our results constitute benchmarks for state-of-the-art theoretical approaches.

  1. Model Independent Decomposition of Two-State Data

    PubMed Central

    Landahl, Eric C.; Rice, Sarah E.

    2014-01-01

    Two-state models often provide an reasonable approximation of protein behaviors such as partner binding, folding, or conformational changes. Many different techniques have been developed to determine the population ratio between two states as a function of different experimental conditions. Data analysis is accomplished either by fitting individual measured spectra to a linear combination of known basis spectra, or alternatively by decomposing the entire set of spectra into two components using a least-squares optimization of free parameters within an assumed population model. Here we demonstrate that it is possible to directly determine the population ratio in a two-state system directly from data without an a priori model for basis spectra or populations by applying physical constraints iteratively to a Singular Value Decomposition of optical fluorescence, x-ray scattering, and electron paramagnetic resonance data. PMID:24483492

  2. Model-independent decomposition of two-state data.

    PubMed

    Landahl, Eric C; Rice, Sarah E

    2013-12-01

    Two-state models often provide a reasonable approximation of protein behaviors such as partner binding, folding, and conformational changes. Many different techniques have been developed to determine the population ratio between two states as a function of different experimental conditions. Data analysis is accomplished either by fitting individual measured spectra to a linear combination of known basis spectra or alternatively by decomposing the entire set of spectra into two components using a least-squares optimization of free parameters within an assumed population model. Here we demonstrate that it is possible to determine the population ratio in a two-state system directly from data without an a priori model for basis spectra or populations by applying physical constraints iteratively to a singular value decomposition of optical fluorescence, x-ray-scattering, and electron paramagnetic resonance data. PMID:24483492

  3. [Depression and the complete state model of health].

    PubMed

    Díaz, Darío; Blanco, Amalio; Horcajo, Javier; Valle, Carmen

    2007-05-01

    Health is a state of complete physical, mental, and social well-being and not merely the absence of disease or infirmity. In order to specify the contents of this positive state, the Complete State Model of Health (CSMH) considers mental health as a series of symptoms of hedonia and positive functioning, operationalized by measures of subjective, psychological, and social well-being. This model has empirically confirmed two new axioms: (a) rather than forming a single bipolar dimension, health and illness are correlated unipolar dimensions, and (b) the presence of mental health implies positive personal and social functioning. In the present article, we have taken the CSMH as the theoretical framework for the study of depression. Confirmatory factor analyses did not support the first axiom. In fact, the model that posits that measures of mental illness and health form a single bipolar dimension provided the best fit to the data. PMID:17425901

  4. Multi-state succession in wetlands: a novel use of state and transition models.

    PubMed

    Zweig, C L; Kitchens, W M

    2009-07-01

    The complexity of ecosystems and mechanisms of succession are often simplified by linear and mathematical models used to understand and predict system behavior. Such models often do not incorporate multivariate, nonlinear feedbacks in pattern and process that include multiple scales of organization inherent within real-world systems. Wetlands are ecosystems with unique, nonlinear patterns of succession due to the regular, but often inconstant, presence of water on the landscape. We develop a general, nonspatial state and transition (S and T) succession conceptual model for wetlands and apply the general framework by creating annotated succession/management models and hypotheses for use in impact analysis on a portion of an imperiled wetland. The S and T models for our study area, Water Conservation Area 3A South (WCA3), Florida, U.S.A., included hydrologic and peat depth values from multivariate analyses and classification and regression trees. We used the freeware Vegetation Dynamics Development Tool as an exploratory application to evaluate our S and T models with different management actions (equal chance [a control condition], deeper conditions, dry conditions, and increased hydrologic range) for three communities: slough, sawgrass (Cladium jamaicense), and wet prairie. Deeper conditions and increased hydrologic range behaved similarly, with the transition of community states to deeper states, particularly for sawgrass and slough. Hydrology is the primary mechanism for multi-state transitions within our study period, and we show both an immediate and lagged effect on vegetation, depending on community state. We consider these S and T succession models as a fraction of the framework for the Everglades. They are hypotheses for use in adaptive management, represent the community response to hydrology, and illustrate which aspects of hydrologic variability are important to community structure. We intend for these models to act as a foundation for further

  5. Multi-state succession in wetlands: a novel use of state and transition models

    USGS Publications Warehouse

    Zweig, Christa L.; Kitchens, Wiley M.

    2009-01-01

    The complexity of ecosystems and mechanisms of succession are often simplified by linear and mathematical models used to understand and predict system behavior. Such models often do not incorporate multivariate, nonlinear feedbacks in pattern and process that include multiple scales of organization inherent within real-world systems. Wetlands are ecosystems with unique, nonlinear patterns of succession due to the regular, but often inconstant, presence of water on the landscape. We develop a general, nonspatial state and transition (S and T) succession conceptual model for wetlands and apply the general framework by creating annotated succession/management models and hypotheses for use in impact analysis on a portion of an imperiled wetland. The S and T models for our study area, Water Conservation Area 3A South (WCA3), Florida, USA, included hydrologic and peat depth values from multivariate analyses and classification and regression trees. We used the freeware Vegetation Dynamics Development Tool as an exploratory application to evaluate our S and T models with different management actions (equal chance [a control condition], deeper conditions, dry conditions, and increased hydrologic range) for three communities: slough, sawgrass (Cladium jamaicense), and wet prairie. Deeper conditions and increased hydrologic range behaved similarly, with the transition of community states to deeper states, particularly for sawgrass and slough. Hydrology is the primary mechanism for multi-state transitions within our study period, and we show both an immediate and lagged effect on vegetation, depending on community state. We consider these S and T succession models as a fraction of the framework for the Everglades. They are hypotheses for use in adaptive management, represent the community response to hydrology, and illustrate which aspects of hydrologic variability are important to community structure. We intend for these models to act as a foundation for further restoration

  6. Computerized power supply analysis: State equation generation and terminal models

    NASA Technical Reports Server (NTRS)

    Garrett, S. J.

    1978-01-01

    To aid engineers that design power supply systems two analysis tools that can be used with the state equation analysis package were developed. These tools include integration routines that start with the description of a power supply in state equation form and yield analytical results. The first tool uses a computer program that works with the SUPER SCEPTRE circuit analysis program and prints the state equation for an electrical network. The state equations developed automatically by the computer program are used to develop an algorithm for reducing the number of state variables required to describe an electrical network. In this way a second tool is obtained in which the order of the network is reduced and a simpler terminal model is obtained.

  7. Series analysis of Q-state checkerboard Potts models

    SciTech Connect

    Hansel, D.; Maillard, J.M.

    1988-12-01

    The series analysis of the low temperature expansion of the checkerboard q-state Potts model in a magnetic field initiated in two previous papers is continued. In particular algebraic varieties of the parameter space (corresponding or generalizing the so-called disorder solutions), the checkerboard Potts model and its Bethe approximation are indistinguishable as far as one is concerned with the partition function and its first order derivatives. The difference between the two models occurs for higher order derivatives. In particular one gives the exact expression of the (low temperature expansion of the) susceptibility of the checkerboard Ising model in zero magnetic field on one of these varieties.

  8. Exploring extensions to multi-state models with multiple unobservable states

    USGS Publications Warehouse

    Bailey, L.L.; Kendall, W.L.; Church, D.R.

    2009-01-01

    Many biological systems include a portion of the target population that is unobservable during certain life history stages. Transition to and from an unobservable state may be of primary interest in many ecological studies and such movements are easily incorporated into multi-state models. Several authors have investigated properties of open-population multi-state mark-recapture models with unobservable states, and determined the scope and constraints under which parameters are identifiable (or, conversely, are redundant), but only in the context of a single observable and a single unobservable state (Schmidt et al. 2002; Kendall and Nichols 2002; Schaub et al. 2004; Kendall 2004). Some of these constraints can be relaxed if data are collected under a version of the robust design (Kendall and Bjorkland 2001; Kendall and Nichols 2002; Kendall 2004; Bailey et al. 2004), which entails >1 capture period per primary period of interest (e.g., 2 sampling periods within a breeding season). The critical assumption shared by all versions of the robust design is that the state of the individual (e.g. observable or unobservable) remains static for the duration of the primary period (Kendall 2004). In this paper, we extend previous work by relaxing this assumption to allow movement among observable states within primary periods while maintaining static observable or unobservable states. Stated otherwise, both demographic and geographic closure assumptions are relaxed, but all individuals are either observable or unobservable within primary periods. Within these primary periods transitions are possible among multiple observable states, but transitions are not allowed among the corresponding unobservable states. Our motivation for this work is exploring potential differences in population parameters for pond-breeding amphibians, where the quality of habitat surrounding the pond is not spatially uniform. The scenario is an example of a more general case where individuals move

  9. State to State and Charged Particle Kinetic Modeling of Time Filtering and Cs Addition

    SciTech Connect

    Capitelli, M.; Gorse, C.; Longo, S.; Diomede, P.; Pagano, D.

    2007-08-10

    We present here an account on the progress of kinetic simulation of non equilibrium plasmas in conditions of interest for negative ion production by using the 1D Bari code for hydrogen plasma simulation. The model includes the state to state kinetics of the vibrational level population of hydrogen molecules, plus a PIC/MCC module for the multispecies dynamics of charged particles. In particular we present new results for the modeling of two issues of great interest: the time filtering and the Cs addition via surface coverage.

  10. Distributed state-space generation of discrete-state stochastic models

    NASA Technical Reports Server (NTRS)

    Ciardo, Gianfranco; Gluckman, Joshua; Nicol, David

    1995-01-01

    High-level formalisms such as stochastic Petri nets can be used to model complex systems. Analysis of logical and numerical properties of these models of ten requires the generation and storage of the entire underlying state space. This imposes practical limitations on the types of systems which can be modeled. Because of the vast amount of memory consumed, we investigate distributed algorithms for the generation of state space graphs. The distributed construction allows us to take advantage of the combined memory readily available on a network of workstations. The key technical problem is to find effective methods for on-the-fly partitioning, so that the state space is evenly distributed among processors. In this paper we report on the implementation of a distributed state-space generator that may be linked to a number of existing system modeling tools. We discuss partitioning strategies in the context of Petri net models, and report on performance observed on a network of workstations, as well as on a distributed memory multi-computer.

  11. Nonequilibrium Steady States of a Stochastic Model System.

    NASA Astrophysics Data System (ADS)

    Zhang, Qiwei

    We study the nonequilibrium steady state of a stochastic lattice gas model, originally proposed by Katz, Lebowitz and Spohn (Phys. Rev. B 28: 1655 (1983)). Firstly, we solve the model on some small lattices exactly in order to see the general dependence of the steady state upon different parameters of the model. Nextly, we derive some analytical results for infinite lattice systems by taking some suitable limits. We then present some renormalization group results for the continuum version of the model via field theoretical techniques, the supersymmetry of the critical dynamics in zero field is also explored. Finally, we report some very recent 3-D Monte Carlo simulation results, which have been obtained by applying Multi-Spin-Coding techniques on a CDC vector supercomputer - Cyber 205 at John von Neumann Center.

  12. Magnetic models for the United States for 1985

    USGS Publications Warehouse

    Peddie, Norman W.; Zunde, Audronis K.

    1990-01-01

    New models describing the magnetic field in the United States at the beginning of 1985 and the rate of change expected during the next few years have been developed. The models--which will serve as the basis for a new set of magnetic charts--were derived from several tens of thousands of original field measurements from land, marine, and aerial surveys; from values derived from the MAGSAT-based International Geomagnetic Reference Field; and from recent data from magnetic observatories and repeat stations. , They are in the form of spherical harmonic series that represent the scalar magnetic potential from which all the field components can be derived. The models for the conterminous States and Alaska are of maximum degree and order 4 (24 coefficients each) and the models for Hawaii are of maximum degree and order 2 (8 coefficients each).

  13. Two Dimensional State Transition of a Swarming Model

    NASA Astrophysics Data System (ADS)

    Chuang, Yao-Li; Marthaler, Daniel

    2005-03-01

    A rotating mill is widely seen in swarming patterns of various species, such as ants, fishes, or daphnia. Levine et al. (2000) proposed an individual based model which produces a pair of co- existing clockwise and counter-clockwise mills on top of each other while a unified rotating mill can be achieved by switching the formula of the self-propulsion to an ensemble average. Without changing its fundamental concepts, we modify the model to include a Rayleigh-type self-driving mechanism, which has a cleaner connection to its continuum limit, i.e., macroscopic description, where analysis can be more efficiently done. By varying parameter values, we find that the modified model goes through a three-stage transition from the co-existing state to the unified state. We also compare the numerical results of the model and of its continuum counterpart.

  14. On rate-state and Coulomb failure models

    USGS Publications Warehouse

    Gomberg, J.; Beeler, N.; Blanpied, M.

    2000-01-01

    We examine the predictions of Coulomb failure stress and rate-state frictional models. We study the change in failure time (clock advance) Δt due to stress step perturbations (i.e., coseismic static stress increases) added to "background" stressing at a constant rate (i.e., tectonic loading) at time t0. The predictability of Δt implies a predictable change in seismicity rate r(t)/r0, testable using earthquake catalogs, where r0 is the constant rate resulting from tectonic stressing. Models of r(t)/r0, consistent with general properties of aftershock sequences, must predict an Omori law seismicity decay rate, a sequence duration that is less than a few percent of the mainshock cycle time and a return directly to the background rate. A Coulomb model requires that a fault remains locked during loading, that failure occur instantaneously, and that Δt is independent of t0. These characteristics imply an instantaneous infinite seismicity rate increase of zero duration. Numerical calculations of r(t)/r0 for different state evolution laws show that aftershocks occur on faults extremely close to failure at the mainshock origin time, that these faults must be "Coulomb-like," and that the slip evolution law can be precluded. Real aftershock population characteristics also may constrain rate-state constitutive parameters; a may be lower than laboratory values, the stiffness may be high, and/or normal stress may be lower than lithostatic. We also compare Coulomb and rate-state models theoretically. Rate-state model fault behavior becomes more Coulomb-like as constitutive parameter a decreases relative to parameter b. This is because the slip initially decelerates, representing an initial healing of fault contacts. The deceleration is more pronounced for smaller a, more closely simulating a locked fault. Even when the rate-state Δt has Coulomb characteristics, its magnitude may differ by some constant dependent on b. In this case, a rate-state model behaves like a modified

  15. Grothendieck's constant and local models for noisy entangled quantum states

    SciTech Connect

    Acin, Antonio; Gisin, Nicolas; Toner, Benjamin

    2006-06-15

    We relate the nonlocal properties of noisy entangled states to Grothendieck's constant, a mathematical constant appearing in Banach space theory. For two-qubit Werner states {rho}{sub p}{sup W}=p|{psi}{sup -}><{psi}{sup -}|+(1-p)1/4, we show that there is a local model for projective measurements if and only if p{<=}1/K{sub G}(3), where K{sub G}(3) is Grothendieck's constant of order 3. Known bounds on K{sub G}(3) prove the existence of this model at least for p < or approx. 0.66, quite close to the current region of Bell violation, p{approx}0.71. We generalize this result to arbitrary quantum states.

  16. The States of Matter: A Model that Makes Sense.

    ERIC Educational Resources Information Center

    Swartz, Clifford

    1989-01-01

    Provides instructional models for solids, liquids, and gases that incorporate a few adjustments for keeping the features and scale as valid as possible. States that 99 percent of the material in the universe is in a dominant form called plasma. (RT)

  17. Model for Vortex Ring State Influence on Rotorcraft Flight Dynamics

    NASA Technical Reports Server (NTRS)

    Johnson, Wayne

    2005-01-01

    The influence of vortex ring state (VRS) on rotorcraft flight dynamics is investigated, specifically the vertical velocity drop of helicopters and the roll-off of tiltrotors encountering VRS. The available wind tunnel and flight test data for rotors in vortex ring state are reviewed. Test data for axial flow, non-axial flow, two rotors, unsteadiness, and vortex ring state boundaries are described and discussed. Based on the available measured data, a VRS model is developed. The VRS model is a parametric extension of momentum theory for calculation of the mean inflow of a rotor, hence suitable for simple calculations and real-time simulations. This inflow model is primarily defined in terms of the stability boundary of the aircraft motion. Calculations of helicopter response during VRS encounter were performed, and good correlation is shown with the vertical velocity drop measured in flight tests. Calculations of tiltrotor response during VRS encounter were performed, showing the roll-off behavior characteristic of tiltrotors. Hence it is possible, using a model of the mean inflow of an isolated rotor, to explain the basic behavior of both helicopters and tiltrotors in vortex ring state.

  18. Model for Vortex Ring State Influence on Rotorcraft Flight Dynamics

    NASA Technical Reports Server (NTRS)

    Johnson, Wayne

    2004-01-01

    The influence of vortex ring state (VRS) on rotorcraft flight dynamics is investigated, specifically the vertical velocity drop of helicopters and the roll-off of tiltrotors encountering VRS. The available wind tunnel and flight test data for rotors in vortex ring state are reviewed. Test data for axial flow, nonaxial flow, two rotors, unsteadiness, and vortex ring state boundaries are described and discussed. Based on the available measured data, a VRS model is developed. The VRS model is a parametric extension of momentum theory for calculation of the mean inflow of a rotor, hence suitable for simple calculations and real-time simulations. This inflow model is primarily defined in terms of the stability boundary of the aircraft motion. Calculations of helicopter response during VRS encounter were performed, and good correlation is shown with the vertical velocity drop measured in flight tests. Calculations of tiltrotor response during VRS encounter were performed, showing the roll-off behavior characteristic of tiltrotors. Hence it is possible, using a model of the mean inflow of an isolated rotor, to explain the basic behavior of both helicopters and tiltrotors in vortex ring state.

  19. Molecular Modeling and Computational Chemistry at Humboldt State University.

    ERIC Educational Resources Information Center

    Paselk, Richard A.; Zoellner, Robert W.

    2002-01-01

    Describes a molecular modeling and computational chemistry (MM&CC) facility for undergraduate instruction and research at Humboldt State University. This facility complex allows the introduction of MM&CC throughout the chemistry curriculum with tailored experiments in general, organic, and inorganic courses as well as a new molecular modeling…

  20. LACIE: Wheat yield models for the United States, revision A

    NASA Technical Reports Server (NTRS)

    1977-01-01

    For abstract, see volume 1 N77-30577. The enclosed maps indicate the areal coverage of the various models for spring (durum and other spring) and winter wheat. The given regions are the combination of several climatic divisions and many times comprise an entire state.

  1. Practical guidance for developing state-and-transition models

    Technology Transfer Automated Retrieval System (TEKTRAN)

    State-and-transition models (STMs) are synthetic descriptions of the dynamics of vegetation and surface soils occurring within specific ecological sites. STMs consist of a diagram and narratives that describe the dynamics and its causes. STMs are developed using a broad array of evidence including h...

  2. Spatially-explicit representation of state-and-transition models

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The broad-scale assessment of natural resource conditions (e.g., rangeland health, restoration needs) requires knowledge of their spatial distribution. We argue that creating a database that links state-and-transition models (STMs) to spatial units is a valuable management tool for structuring groun...

  3. Structural Model of Weak Binding Actomyosin in the Prepowerstroke State*

    PubMed Central

    Várkuti, Boglárka H.; Yang, Zhenhui; Malnasi-Csizmadia, Andras

    2015-01-01

    We present the first in silico model of the weak binding actomyosin in the initial powerstroke state, representing the actin binding-induced major structural changes in myosin. First, we docked an actin trimer to prepowerstroke myosin then relaxed the complex by a 100-ns long unrestrained molecular dynamics. In the first few nanoseconds, actin binding induced an extra primed myosin state, i.e. the further priming of the myosin lever by 18° coupled to a further closure of switch 2 loop. We demonstrated that actin induces the extra primed state of myosin specifically through the actin N terminus-activation loop interaction. The applied in silico methodology was validated by forming rigor structures that perfectly fitted into an experimentally determined EM map of the rigor actomyosin. Our results unveiled the role of actin in the powerstroke by presenting that actin moves the myosin lever to the extra primed state that leads to the effective lever swing. PMID:25416786

  4. Energy modeling. Volume 2: Inventory and details of state energy models

    NASA Astrophysics Data System (ADS)

    Melcher, A. G.; Underwood, R. G.; Weber, J. C.; Gist, R. L.; Holman, R. P.; Donald, D. W.

    1981-05-01

    An inventory of energy models developed by or for state governments is presented, and certain models are discussed in depth. These models address a variety of purposes such as: supply or demand of energy or of certain types of energy; emergency management of energy; and energy economics. Ten models are described. The purpose, use, and history of the model is discussed, and information is given on the outputs, inputs, and mathematical structure of the model. The models include five models dealing with energy demand, one of which is econometric and four of which are econometric-engineering end-use models.

  5. Understanding x-ray driven impulsive electronic state redistribution using a three-state model

    NASA Astrophysics Data System (ADS)

    Ware, Matthew R.; Cryan, James; Bucksbaum, Philip H.

    2016-05-01

    The natural timescale for electron motion is extremely fast; electrons can move across molecular bonds in less than a femtosecond. To understand this fast motion and the role of electronic coherence, we are interested in creating a superposition of valence excited states through excitation with a broad bandwidth (>5eV) laser pulse. In the x-ray regime, the molecular ground state can couple to valence-excited states through an intermediate autoionizing resonance in a process known as stimulated x-ray Raman scattering (SXRS). X-rays excite electrons from the highly localized K-shells in a molecule, creating a superposition of valence-excited states initially localized around a target atom in the molecule. Coherences between states in the superposition will subsequently drive charge transfer as the wavepacket spreads out across the molecule. We use an effective 3-state model coupling the ground, auto-ionizing, and valence-excited states in diatomic systems to study the cross-section of SXRS as function of x-ray intensity, central frequency, bandwidth, and chirp. We also make observations on how the x-ray parameters affect the degree of initial localization to an atom of the wavepacket created in SXRS. This work was supported by the U.S. Department of Energy, Office of Science, Basic Energy Sciences, Chemical Sciences, Geosciences, and Biosciences Division.

  6. Three-state herding model of the financial markets

    NASA Astrophysics Data System (ADS)

    Kononovicius, A.; Gontis, V.

    2013-01-01

    We propose a Markov jump process with the three-state herding interaction. We see our approach as an agent-based model for the financial markets. Under certain assumptions this agent-based model can be related to the stochastic description exhibiting sophisticated statistical features. Along with power-law probability density function of the absolute returns we are able to reproduce the fractured power spectral density, which is observed in the high-frequency financial market data. The given example of consistent agent-based and stochastic modeling will provide a background for further developments in the research of complex social systems.

  7. Dynamic models for problems of species occurrence with multiple states

    USGS Publications Warehouse

    MacKenzie, D.I.; Nichols, J.D.; Seamans, M.E.; Gutierrez, R.J.

    2009-01-01

    Recent extensions of occupancy modeling have focused not only on the distribution of species over space, but also on additional state variables (e.g., reproducing or not, with or without disease organisms, relative abundance categories) that provide extra information about occupied sites. These biologist-driven extensions are characterized by ambiguity in both species presence and correct state classification, caused by imperfect detection. We first show the relationships between independently published approaches to the modeling of multistate occupancy. We then extend the pattern-based modeling to the case of sampling over multiple seasons or years in order to estimate state transition probabilities associated with system dynamics. The methodology and its potential for addressing relevant ecological questions are demonstrated using both maximum likelihood (occupancy and successful reproduction dynamics of California Spotted Owl) and Markov chain Monte Carlo estimation approaches (changes in relative abundance of green frogs in Maryland). Just as multistate capture?recapture modeling has revolutionized the study of individual marked animals, we believe that multistate occupancy modeling will dramatically increase our ability to address interesting questions about ecological processes underlying population-level dynamics.

  8. Modeling species occurrence dynamics with multiple states and imperfect detection

    USGS Publications Warehouse

    MacKenzie, D.I.; Nichols, J.D.; Seamans, M.E.; Gutierrez, R.J.

    2009-01-01

    Recent extensions of occupancy modeling have focused not only on the distribution of species over space, but also on additional state variables (e.g., reproducing or not, with or without disease organisms, relative abundance categories) that provide extra information about occupied sites. These biologist-driven extensions are characterized by ambiguity in both species presence and correct state classification, caused by imperfect detection. We first show the relationships between independently published approaches to the modeling of multistate occupancy. We then extend the pattern-based modeling to the case of sampling over multiple seasons or years in order to estimate state transition probabilities associated with system dynamics. The methodology and its potential for addressing relevant ecological questions are demonstrated using both maximum likelihood (occupancy and successful reproduction dynamics of California Spotted Owl) and Markov chain Monte Carlo estimation approaches (changes in relative abundance of green frogs in Maryland). Just as multistate capture-recapture modeling has revolutionized the study of individual marked animals, we believe that multistate occupancy modeling will dramatically increase our ability to address interesting questions about ecological processes underlying population-level dynamics. ?? 2009 by the Ecological Society of America.

  9. Using Markov state models to study self-assembly.

    PubMed

    Perkett, Matthew R; Hagan, Michael F

    2014-06-01

    Markov state models (MSMs) have been demonstrated to be a powerful method for computationally studying intramolecular processes such as protein folding and macromolecular conformational changes. In this article, we present a new approach to construct MSMs that is applicable to modeling a broad class of multi-molecular assembly reactions. Distinct structures formed during assembly are distinguished by their undirected graphs, which are defined by strong subunit interactions. Spatial inhomogeneities of free subunits are accounted for using a recently developed Gaussian-based signature. Simplifications to this state identification are also investigated. The feasibility of this approach is demonstrated on two different coarse-grained models for virus self-assembly. We find good agreement between the dynamics predicted by the MSMs and long, unbiased simulations, and that the MSMs can reduce overall simulation time by orders of magnitude. PMID:24907984

  10. Magnon edge states in the hardcore- Bose-Hubbard model.

    PubMed

    Owerre, S A

    2016-11-01

    Quantum Monte Carlo (QMC) simulation has uncovered nonzero Berry curvature and bosonic edge states in the hardcore-Bose-Hubbard model on the gapped honeycomb lattice. The competition between the chemical potential and staggered onsite potential leads to an interesting quantum phase diagram comprising the superfluid phase, Mott insulator, and charge density wave insulator. In this paper, we present a semiclassical perspective of this system by mapping to a spin-1/2 quantum XY model. We give an explicit analytical origin of the quantum phase diagram, the Berry curvatures, and the edge states using semiclassical approximations. We find very good agreement between the semiclassical analyses and the QMC results. Our results show that the topological properties of the hardcore-Bose-Hubbard model are the same as those of magnon in the corresponding quantum spin system. Our results are applicable to systems of ultracold bosonic atoms trapped in honeycomb optical lattices. PMID:27603092

  11. Using Markov state models to study self-assembly

    PubMed Central

    Perkett, Matthew R.; Hagan, Michael F.

    2014-01-01

    Markov state models (MSMs) have been demonstrated to be a powerful method for computationally studying intramolecular processes such as protein folding and macromolecular conformational changes. In this article, we present a new approach to construct MSMs that is applicable to modeling a broad class of multi-molecular assembly reactions. Distinct structures formed during assembly are distinguished by their undirected graphs, which are defined by strong subunit interactions. Spatial inhomogeneities of free subunits are accounted for using a recently developed Gaussian-based signature. Simplifications to this state identification are also investigated. The feasibility of this approach is demonstrated on two different coarse-grained models for virus self-assembly. We find good agreement between the dynamics predicted by the MSMs and long, unbiased simulations, and that the MSMs can reduce overall simulation time by orders of magnitude. PMID:24907984

  12. An Extended Equation of State Modeling Method I. Pure Fluids

    NASA Astrophysics Data System (ADS)

    Scalabrin, G.; Bettio, L.; Marchi, P.; Piazza, L.; Richon, D.

    2006-09-01

    A new technique is proposed here to represent the thermodynamic surface of a pure fluid in the fundamental Helmholtz energy form. The peculiarity of the present method is the extension of a generic equation of state for the target fluid, which is assumed as the basic equation, through the distortion of its independent variables by individual shape functions, which are represented by a neural network used as function approximator. The basic equation of state for the target fluid can have the simple functional form of a cubic equation, as, for instance, the Soave-Redlich-Kwong equation assumed in the present study. A set of nine fluids including hydrocarbons, haloalkane refrigerants, and strongly polar substances has been considered. For each of them the model has been regressed and then validated against volumetric and caloric properties generated in the vapor, liquid, and supercritical regions from highly accurate dedicated equations of state. In comparison with the underlying cubic equation of state, the prediction accuracy is improved by a factor between 10 and 100, depending on the property and on the region. It has been verified that about 100 density experimental points, together with from 10 to 20 coexistence data, are sufficient to guarantee high prediction accuracy for different thermodynamic properties. The method is a promising modeling technique for the heuristic development of multiparameter dedicated equations of state from experimental data.

  13. MODELING THE DEMAND FOR E85 IN THE UNITED STATES

    SciTech Connect

    Liu, Changzheng; Greene, David L

    2013-10-01

    How demand for E85 might evolve in the future in response to changing economics and policies is an important subject to include in the National Energy Modeling System (NEMS). This report summarizes a study to develop an E85 choice model for NEMS. Using the most recent data from the states of Minnesota, North Dakota, and Iowa, this study estimates a logit model that represents E85 choice as a function of prices of E10 and E85, as well as fuel availability of E85 relative to gasoline. Using more recent data than previous studies allows a better estimation of non-fleet demand and indicates that the price elasticity of E85 choice appears to be higher than previously estimated. Based on the results of the econometric analysis, a model for projecting E85 demand at the regional level is specified. In testing, the model produced plausible predictions of US E85 demand to 2040.

  14. Mathematical model for Dengue with three states of infection

    NASA Astrophysics Data System (ADS)

    Hincapie, Doracelly; Ospina, Juan

    2012-06-01

    A mathematical model for dengue with three states of infection is proposed and analyzed. The model consists in a system of differential equations. The three states of infection are respectively asymptomatic, partially asymptomatic and fully asymptomatic. The model is analyzed using computer algebra software, specifically Maple, and the corresponding basic reproductive number and the epidemic threshold are computed. The resulting basic reproductive number is an algebraic synthesis of all epidemic parameters and it makes clear the possible control measures. The microscopic structure of the epidemic parameters is established using the quantum theory of the interactions between the atoms and radiation. In such approximation, the human individual is represented by an atom and the mosquitoes are represented by radiation. The force of infection from the mosquitoes to the humans is considered as the transition probability from the fundamental state of atom to excited states. The combination of computer algebra software and quantum theory provides a very complete formula for the basic reproductive number and the possible control measures tending to stop the propagation of the disease. It is claimed that such result may be important in military medicine and the proposed method can be applied to other vector-borne diseases.

  15. Ground-state phase diagram of the quantum Rabi model

    NASA Astrophysics Data System (ADS)

    Ying, Zu-Jian; Liu, Maoxin; Luo, Hong-Gang; Lin, Hai-Qing; You, J. Q.

    2015-11-01

    The Rabi model plays a fundamental role in understanding light-matter interaction. It reduces to the Jaynes-Cummings model via the rotating-wave approximation, which is applicable only to the cases of near resonance and weak coupling. However, recent experimental breakthroughs in upgrading light-matter coupling order require understanding the physics of the full quantum Rabi model (QRM). Despite the fact that its integrability and energy spectra have been exactly obtained, the challenge to formulate an exact wave function in a general case still hinders physical exploration of the QRM. Here we unveil a ground-state phase diagram of the QRM, consisting of a quadpolaron and a bipolaron as well as their changeover in the weak-, strong-, and intermediate-coupling regimes, respectively. An unexpected overweighted antipolaron is revealed in the quadpolaron state, and a hidden scaling behavior relevant to symmetry breaking is found in the bipolaron state. An experimentally accessible parameter is proposed to test these states, which might provide novel insights into the nature of the light-matter interaction for all regimes of the coupling strengths.

  16. Modelling and simulation of large solid state laser systems

    SciTech Connect

    Simmons, W.W.; Warren, W.E.

    1986-01-01

    The role of numerical methods to simulate the several physical processes (e.g., diffraction, self-focusing, gain saturation) that are involved in coherent beam propagation through large laser systems is discussed. A comprehensive simulation code for modeling the pertinent physical phenomena observed in laser operations (growth of small-scale modulation, spatial filter, imaging, gain saturation and beam-induced damage) is described in some detail. Comparisons between code results and solid state laser output performance data are presented. Design and performance estimation of the large Nova laser system at LLNL are given. Finally, a global design rule for large, solid state laser systems is discussed.

  17. Control of discrete event systems modeled as hierarchical state machines

    NASA Technical Reports Server (NTRS)

    Brave, Y.; Heymann, M.

    1991-01-01

    The authors examine a class of discrete event systems (DESs) modeled as asynchronous hierarchical state machines (AHSMs). For this class of DESs, they provide an efficient method for testing reachability, which is an essential step in many control synthesis procedures. This method utilizes the asynchronous nature and hierarchical structure of AHSMs, thereby illustrating the advantage of the AHSM representation as compared with its equivalent (flat) state machine representation. An application of the method is presented where an online minimally restrictive solution is proposed for the problem of maintaining a controlled AHSM within prescribed legal bounds.

  18. Quasi-classical models of transition state absorption or emission

    NASA Astrophysics Data System (ADS)

    Lee, Soo-Y.; Pollard, W. Thomas; Mathies, Richard A.

    1989-11-01

    By making a short-time approximation to the correlation function in the quantum result for transition state absorption (or emission) we obtain the Lorentzian and reflection results as integrals of simple configuration space functions. These and the time-integrated quantum results are used to derive and unify the following descriptions of transition-state absorption: (a) the classical model of Bersohn and Zewail, (b) the time-dependent wave mechanical description by Agrawal, Mohan and Sathyamurthy, (c) the classical trajectory approach by Polanyi and coworkers and (d) the time-independent quantum-mechanical description by Engel, Bacic, Schinke and Shapiro.

  19. Coherent states and nonlinear dynamics of the three state quasi-spin model with soliton solutions

    NASA Astrophysics Data System (ADS)

    Agüero, M.; Alvarado, R.; Frias, M.

    1998-11-01

    In this paper the generalized coherent states defined as points of the coset space {SU(2)}/{U(1)} are used as trial wave functions in order to study the quasi-spin model of the nonlinear ϕ6-theory. In the simple version of the quasi-classical theory deduced from this method a complete integrable system is obtained. In a general context, the ground state and linear spectrum of the nonlinear lattice equation were evaluated. Finally, by analyzing the effective potential, the first and second order phase transitions are shown to exist.

  20. An Extended Equation of State Modeling Method II. Mixtures

    NASA Astrophysics Data System (ADS)

    Scalabrin, G.; Marchi, P.; Stringari, P.; Richon, D.

    2006-09-01

    This work is the extension of previous work dedicated to pure fluids. The same method is extended to the representation of thermodynamic properties of a mixture through a fundamental equation of state in terms of the Helmholtz energy. The proposed technique exploits the extended corresponding-states concept of distorting the independent variables of a dedicated equation of state for a reference fluid using suitable scale factor functions to adapt the equation to experimental data of a target system. An existing equation of state for the target mixture is used instead of an equation for the reference fluid, completely avoiding the need for a reference fluid. In particular, a Soave-Redlich-Kwong cubic equation with van der Waals mixing rules is chosen. The scale factors, which are functions of temperature, density, and mole fraction of the target mixture, are expressed in the form of a multilayer feedforward neural network, whose coefficients are regressed by minimizing a suitable objective function involving different kinds of mixture thermodynamic data. As a preliminary test, the model is applied to five binary and two ternary haloalkane mixtures, using data generated from existing dedicated equations of state for the selected mixtures. The results show that the method is robust and straightforward for the effective development of a mixture- specific equation of state directly from experimental data.

  1. Modeling of cortical signals using echo state networks

    NASA Astrophysics Data System (ADS)

    Zhou, Hanying; Wang, Yongji; Huang, Jiangshuai

    2009-10-01

    Diverse modeling frameworks have been utilized with the ultimate goal of translating brain cortical signals into prediction of visible behavior. The inputs to these models are usually multidimensional neural recordings collected from relevant regions of a monkey's brain while the outputs are the associated behavior which is typically the 2-D or 3-D hand position of a primate. Here our task is to set up a proper model in order to figure out the move trajectories by input the neural signals which are simultaneously collected in the experiment. In this paper, we propose to use Echo State Networks (ESN) to map the neural firing activities into hand positions. ESN is a newly developed recurrent neural network(RNN) model. Besides its dynamic property and short term memory just as other recurrent neural networks have, it has a special echo state property which endows it with the ability to model nonlinear dynamic systems powerfully. What distinguished it from transitional recurrent neural networks most significantly is its special learning method. In this paper we train this net with a refined version of its typical training method and get a better model.

  2. Nonequilibrium Steady States in Models of Prebiotic Evolution

    NASA Astrophysics Data System (ADS)

    Halley, J. W.; Wynveen, A.

    2014-12-01

    We report computational results from a model for prebiotic evolution.The model is schematic, but contains a correct description of thebasic statistical problem associated with understanding how the initiation of life can occur given the strong entropic barriers (sometimesknown as 'Eigen's paradox' and appearing in experiments as the 'tar problem'). The model is similar to one of the modelsintroduced years ago by Kauffman and coworkers. The important innovationwhich we introduce is imposition of the requirement that, to qualifyas a lifelike dynamical chemical system, the system must not be inchemical equilibrium. That constraint turns out to have major qualitativeeffects on the conclusions. In particular, very sparse chemical networksturn out to be the most favorable ones for generating autocatalyticnonequilibrium states. This suggests qualitatively that deserts might bebetter than ponds for initiating life. Some details of the models andsimulations will be described, including recent results in which weintroduce spatial diffusion and a proxy for temperature into the description ofthe model chemistry. Results on growth rates, convergence and theoverall probability of generation of lifelike states as a function ofparameters of the chemical network model will be presented.

  3. Evaluation of the Current State of Integrated Water Quality Modelling

    NASA Astrophysics Data System (ADS)

    Arhonditsis, G. B.; Wellen, C. C.; Ecological Modelling Laboratory

    2010-12-01

    Environmental policy and management implementation require robust methods for assessing the contribution of various point and non-point pollution sources to water quality problems as well as methods for estimating the expected and achieved compliance with the water quality goals. Water quality models have been widely used for creating the scientific basis for management decisions by providing a predictive link between restoration actions and ecosystem response. Modelling water quality and nutrient transport is challenging due a number of constraints associated with the input data and existing knowledge gaps related to the mathematical description of landscape and in-stream biogeochemical processes. While enormous effort has been invested to make watershed models process-based and spatially-distributed, there has not been a comprehensive meta-analysis of model credibility in watershed modelling literature. In this study, we evaluate the current state of integrated water quality modeling across the range of temporal and spatial scales typically utilized. We address several common modeling questions by providing a quantitative assessment of model performance and by assessing how model performance depends on model development. The data compiled represent a heterogeneous group of modeling studies, especially with respect to complexity, spatial and temporal scales and model development objectives. Beginning from 1992, the year when Beven and Binley published their seminal paper on uncertainty analysis in hydrological modelling, and ending in 2009, we selected over 150 papers fitting a number of criteria. These criteria involved publications that: (i) employed distributed or semi-distributed modelling approaches; (ii) provided predictions on flow and nutrient concentration state variables; and (iii) reported fit to measured data. Model performance was quantified with the Nash-Sutcliffe Efficiency, the relative error, and the coefficient of determination. Further, our

  4. A Bayesian state-space formulation of dynamic occupancy models.

    PubMed

    Royle, J Andrew; Kéry, Marc

    2007-07-01

    Species occurrence and its dynamic components, extinction and colonization probabilities, are focal quantities in biogeography and metapopulation biology, and for species conservation assessments. It has been increasingly appreciated that these parameters must be estimated separately from detection probability to avoid the biases induced by non-detection error. Hence, there is now considerable theoretical and practical interest in dynamic occupancy models that contain explicit representations of metapopulation dynamics such as extinction, colonization, and turnover as well as growth rates. We describe a hierarchical parameterization of these models that is analogous to the state-space formulation of models in time series, where the model is represented by two components, one for the partially observable occupancy process and another for the observations conditional on that process. This parameterization naturally allows estimation of all parameters of the conventional approach to occupancy models, but in addition, yields great flexibility and extensibility, e.g., to modeling heterogeneity or latent structure in model parameters. We also highlight the important distinction between population and finite sample inference; the latter yields much more precise estimates for the particular sample at hand. Finite sample estimates can easily be obtained using the state-space representation of the model but are difficult to obtain under the conventional approach of likelihood-based estimation. We use R and WinBUGS to apply the model to two examples. In a standard analysis for the European Crossbill in a large Swiss monitoring program, we fit a model with year-specific parameters. Estimates of the dynamic parameters varied greatly among years, highlighting the irruptive population dynamics of that species. In the second example, we analyze route occupancy of Cerulean Warblers in the North American Breeding Bird Survey (BBS) using a model allowing for site

  5. A Bayesian state-space formulation of dynamic occupancy models

    USGS Publications Warehouse

    Royle, J. Andrew; Kery, M.

    2007-01-01

    Species occurrence and its dynamic components, extinction and colonization probabilities, are focal quantities in biogeography and metapopulation biology, and for species conservation assessments. It has been increasingly appreciated that these parameters must be estimated separately from detection probability to avoid the biases induced by nondetection error. Hence, there is now considerable theoretical and practical interest in dynamic occupancy models that contain explicit representations of metapopulation dynamics such as extinction, colonization, and turnover as well as growth rates. We describe a hierarchical parameterization of these models that is analogous to the state-space formulation of models in time series, where the model is represented by two components, one for the partially observable occupancy process and another for the observations conditional on that process. This parameterization naturally allows estimation of all parameters of the conventional approach to occupancy models, but in addition, yields great flexibility and extensibility, e.g., to modeling heterogeneity or latent structure in model parameters. We also highlight the important distinction between population and finite sample inference; the latter yields much more precise estimates for the particular sample at hand. Finite sample estimates can easily be obtained using the state-space representation of the model but are difficult to obtain under the conventional approach of likelihood-based estimation. We use R and Win BUGS to apply the model to two examples. In a standard analysis for the European Crossbill in a large Swiss monitoring program, we fit a model with year-specific parameters. Estimates of the dynamic parameters varied greatly among years, highlighting the irruptive population dynamics of that species. In the second example, we analyze route occupancy of Cerulean Warblers in the North American Breeding Bird Survey (BBS) using a model allowing for site

  6. Modeling of Material Removal by Solid State Heat Capacity Lasers

    SciTech Connect

    Boley, C D; Rubenchik, A M

    2002-04-17

    Pulsed lasers offer the capability of rapid material removal. Here we present simulations of steel coupon tests by two solid state heat capacity lasers built at LLNL. Operating at 1.05 pm, these deliver pulse energies of about 80 J at 10 Hz, and about 500 J at 20 Hz. Each is flashlamp-pumped. The first laser was tested at LLNL, while the second laser has been delivered to HELSTF, White Sands Missile Range. Liquid ejection appears to be an important removal mechanism. We have modeled these experiments via a time-dependent code called THALES, which describes heat transport, melting, vaporization, and the hydrodynamics of liquid, vapor, and air. It was previously used, in a less advanced form, to model drilling by copper vapor lasers [1] . It was also used to model vaporization in beam dumps for a high-power laser [2]. The basic model is in 1D, while the liquid hydrodynamics is handled in 2D.

  7. The state of art model for thermal transistor

    NASA Astrophysics Data System (ADS)

    Vachhani, M. G.; Gajjar, P. N.

    2016-05-01

    A state of art model for thermal transistor is proposed using three FK 1D chains. In this paper we study how control over heat transfer in nanoscale materials be achieved using microscopic model of thermal transistor. We study the influence of spring constant of source segment on the switching efficiency, thermal amplification and working region of the thermal transistor. We found the increase in switching efficiency and thermal amplification where as decrease in working region with increase in spring constant of source segment.

  8. State-based models for planning and execution coordination

    NASA Technical Reports Server (NTRS)

    Bennett, Matthew B.; Knight, Russell L.; Rasmussen, Robert D.; Ingham, Michel D.

    2005-01-01

    Many traditional planners are built on top of existing execution engines that were not necessarily intended to be operated by a planner. The Mission Data System has been designed from the onset to have both an execution and planning engine and provides a framework for producing state-based models that can be used to coordinate planning and execution. The models provide a basis for ensuring the consistency of assumptions made by the execution engine and planner, and the frameworks provide a basis for run time communications between the planner and execution engines.

  9. Climatological Structures of the GRIPS Models: Mean States and Forcing

    NASA Technical Reports Server (NTRS)

    Pawson, Steven

    1999-01-01

    The GCM-Reality Intercomparison Project for SPARC (GRIPS) is assessing and monitoring the performance of state-of-the-art general circulation models (GCMs). A wide variety of tasks have been initiated. These are designed to: (1) assess the ability of the GCMs to represent the current climatological structure of the troposphere and middle atmosphere,(2) to compare their response to imposed forcing anomalies, and (3) to estimate the certainty with which future climate perturbations can be predicted. This paper is concerned with assessments of the climatological states in the GCM simulations. Comparing the simulations with observational datasets reveals considerable discrepancies in the modelled fields. While it might be anticipated that certain types of biases in the model simulations might be related to the formulation of different aspects of the numerical package (dynamical schemes, cloud schemes, radiation transfer, inclusion of gravity wave drag), there is no clear relationship between these features. This paper attempts to draw a more comprehensive picture of the GCMs'performance than has previously been shown, by comparing the dominant forcing mechanisms in the models with observational estimates, and relating model deficiencies to the differences in the physical mechanisms in the GCMS.

  10. Ground-state entanglement in the XXZ model

    SciTech Connect

    Gu Shijian; Lin Haiqing; Tian Guangshan

    2005-05-15

    In this paper, we investigate spin entanglement in the XXZ model defined on a d-dimensional bipartite lattice. The concurrence, a measure of the entanglement between two spins, is analyzed. We prove rigorously that the ground-state concurrence reaches maximum at the isotropic point. For dimensionality d{>=}2, the concurrence develops a cusp at the isotropic point and we attribute it to the existence of magnetic long-range order.

  11. Rapid State Space Modeling Tool for Rectangular Wing Aeroservoelastic Studies

    NASA Technical Reports Server (NTRS)

    Suh, Peter M.; Conyers, Howard J.; Mavris, Dimitri N.

    2014-01-01

    This paper introduces a modeling and simulation tool for aeroservoelastic analysis of rectangular wings with trailing edge control surfaces. The inputs to the code are planform design parameters such as wing span, aspect ratio and number of control surfaces. A doublet lattice approach is taken to compute generalized forces. A rational function approximation is computed. The output, computed in a few seconds, is a state space aeroservoelastic model which can be used for analysis and control design. The tool is fully parameterized with default information so there is little required interaction with the model developer. Although, all parameters can be easily modified if desired.The focus of this paper is on tool presentation, verification and validation. This process is carried out in stages throughout the paper. The rational function approximation is verified against computed generalized forces for a plate model. A model composed of finite element plates is compared to a modal analysis from commercial software and an independently conducted experimental ground vibration test analysis. Aeroservoelastic analysis is the ultimate goal of this tool. Therefore the flutter speed and frequency for a clamped plate are computed using V-g and V-f analysis. The computational results are compared to a previously published computational analysis and wind tunnel results for the same structure. Finally a case study of a generic wing model with a single control surface is presented. Verification of the state space model is presented in comparison to V-g and V-f analysis. This also includes the analysis of the model in response to a 1-cos gust.

  12. Rapid State Space Modeling Tool for Rectangular Wing Aeroservoelastic Studies

    NASA Technical Reports Server (NTRS)

    Suh, Peter M.; Conyers, Howard J.; Mavris, Dimitri N.

    2015-01-01

    This paper introduces a modeling and simulation tool for aeroservoelastic analysis of rectangular wings with trailing-edge control surfaces. The inputs to the code are planform design parameters such as wing span, aspect ratio, and number of control surfaces. Using this information, the generalized forces are computed using the doublet-lattice method. Using Roger's approximation, a rational function approximation is computed. The output, computed in a few seconds, is a state space aeroservoelastic model which can be used for analysis and control design. The tool is fully parameterized with default information so there is little required interaction with the model developer. All parameters can be easily modified if desired. The focus of this paper is on tool presentation, verification, and validation. These processes are carried out in stages throughout the paper. The rational function approximation is verified against computed generalized forces for a plate model. A model composed of finite element plates is compared to a modal analysis from commercial software and an independently conducted experimental ground vibration test analysis. Aeroservoelastic analysis is the ultimate goal of this tool, therefore, the flutter speed and frequency for a clamped plate are computed using damping-versus-velocity and frequency-versus-velocity analysis. The computational results are compared to a previously published computational analysis and wind-tunnel results for the same structure. A case study of a generic wing model with a single control surface is presented. Verification of the state space model is presented in comparison to damping-versus-velocity and frequency-versus-velocity analysis, including the analysis of the model in response to a 1-cos gust.

  13. Rapid State Space Modeling Tool for Rectangular Wing Aeroservoelastic Studies

    NASA Technical Reports Server (NTRS)

    Suh, Peter M.; Conyers, Howard Jason; Mavris, Dimitri N.

    2015-01-01

    This report introduces a modeling and simulation tool for aeroservoelastic analysis of rectangular wings with trailing-edge control surfaces. The inputs to the code are planform design parameters such as wing span, aspect ratio, and number of control surfaces. Using this information, the generalized forces are computed using the doublet-lattice method. Using Roger's approximation, a rational function approximation is computed. The output, computed in a few seconds, is a state space aeroservoelastic model which can be used for analysis and control design. The tool is fully parameterized with default information so there is little required interaction with the model developer. All parameters can be easily modified if desired. The focus of this report is on tool presentation, verification, and validation. These processes are carried out in stages throughout the report. The rational function approximation is verified against computed generalized forces for a plate model. A model composed of finite element plates is compared to a modal analysis from commercial software and an independently conducted experimental ground vibration test analysis. Aeroservoelastic analysis is the ultimate goal of this tool, therefore, the flutter speed and frequency for a clamped plate are computed using damping-versus-velocity and frequency-versus-velocity analysis. The computational results are compared to a previously published computational analysis and wind-tunnel results for the same structure. A case study of a generic wing model with a single control surface is presented. Verification of the state space model is presented in comparison to damping-versus-velocity and frequency-versus-velocity analysis, including the analysis of the model in response to a 1-cos gust.

  14. Modeling, State Estimation and Control of Unmanned Helicopters

    NASA Astrophysics Data System (ADS)

    Lau, Tak Kit

    Unmanned helicopters hold both tremendous potential and challenges. Without risking the lives of human pilots, these vehicles exhibit agile movement and the ability to hover and hence open up a wide range of applications in the hazardous situations. Sparing human lives, however, comes at a stiff price for technology. Some of the key difficulties that arise in these challenges are: (i) There are unexplained cross-coupled responses between the control axes on the hingeless helicopters that have puzzled researchers for years. (ii) Most, if not all, navigation on the unmanned helicopters relies on Global Navigation Satellite Systems (GNSSs), which are susceptible to jamming. (iii) It is often necessary to accommodate the re-configurations of the payload or the actuators on the helicopters by repeatedly tuning an autopilot, and that requires intensive human supervision and/or system identification. For the dynamics modeling and analysis, we present a comprehensive review on the helicopter actuation and dynamics, and contributes toward a more complete understanding on the on-axis and off-axis dynamical responses on the helicopter. We focus on a commonly used modeling technique, namely the phase-lag treatment, and employ a first-principles modeling method to justify that (i) why that phase-lag technique is inaccurate, (ii) how we can analyze the helicopter actuation and dynamics more accurately. Moreover, these dynamics modeling and analysis reveal the hard-to-measure but crucial parameters on a helicopter model that require the constant identifications, and hence convey the reasoning of seeking a model-implicit method to solve the state estimation and control problems on the unmanned helicopters. For the state estimation, we present a robust localization method for the unmanned helicopter against the GNSS outage. This method infers position from the acceleration measurement from an inertial measurement unit (IMU). In the core of our method are techniques of the sensor

  15. A Knowledge Discovery from POS Data using State Space Models

    NASA Astrophysics Data System (ADS)

    Sato, Tadahiko; Higuchi, Tomoyuki

    The number of competing-brands changes by new product's entry. The new product introduction is endemic among consumer packaged goods firm and is an integral component of their marketing strategy. As a new product's entry affects markets, there is a pressing need to develop market response model that can adapt to such changes. In this paper, we develop a dynamic model that capture the underlying evolution of the buying behavior associated with the new product. This extends an application of a dynamic linear model, which is used by a number of time series analyses, by allowing the observed dimension to change at some point in time. Our model copes with a problem that dynamic environments entail: changes in parameter over time and changes in the observed dimension. We formulate the model with framework of a state space model. We realize an estimation of the model using modified Kalman filter/fixed interval smoother. We find that new product's entry (1) decreases brand differentiation for existing brands, as indicated by decreasing difference between cross-price elasticities; (2) decreases commodity power for existing brands, as indicated by decreasing trend; and (3) decreases the effect of discount for existing brands, as indicated by a decrease in the magnitude of own-brand price elasticities. The proposed framework is directly applicable to other fields in which the observed dimension might be change, such as economic, bioinformatics, and so forth.

  16. BPS states in supersymmetric chiral models with higher derivative terms

    NASA Astrophysics Data System (ADS)

    Nitta, Muneto; Sasaki, Shin

    2014-11-01

    We study the higher derivative chiral models with four supercharges and Bogomol'nyi-Prasad-Sommerfield (BPS) states in these models. The off-shell Lagrangian generically includes higher powers of the auxiliary fields F , which causes distinct on-shell branches associated with the solutions to the auxiliary fields equation. We point out that the model admits a supersymmetric completion of arbitrary higher derivative bosonic models of a single complex scalar field, and an arbitrary scalar potential can be introduced even without superpotentials. As an example, we present a supersymmetric extension of the Faddeev-Skyrme model without four time derivatives, in contrast to the previously proposed supersymmetric Faddeev-Skyrme-like model containing four time derivatives. In general, higher derivative terms together with a superpotential result in deformed scalar potentials. We find that higher derivative corrections to 1 /2 BPS domain walls and 1 /2 BPS lumps are exactly canceled out, while the 1 /4 BPS lumps (as compact baby Skyrmions) depend on a characteristic feature of the higher derivative models. We also find a new 1 /4 BPS condition for domain wall junctions, which generically receives higher derivative corrections.

  17. Modeling of Solid State Transformer for the FREEDM System Demonstration

    NASA Astrophysics Data System (ADS)

    Jiang, Youyuan

    The Solid State Transformer (SST) is an essential component in the FREEDM system. This research focuses on the modeling of the SST and the controller hardware in the loop (CHIL) implementation of the SST for the support of the FREEDM system demonstration. The energy based control strategy for a three-stage SST is analyzed and applied. A simplified average model of the three-stage SST that is suitable for simulation in real time digital simulator (RTDS) has been developed in this study. The model is also useful for general time-domain power system analysis and simulation. The proposed simplified av-erage model has been validated in MATLAB and PLECS. The accuracy of the model has been verified through comparison with the cycle-by-cycle average (CCA) model and de-tailed switching model. These models are also implemented in PSCAD, and a special strategy to implement the phase shift modulation has been proposed to enable the switching model simulation in PSCAD. The implementation of the CHIL test environment of the SST in RTDS is described in this report. The parameter setup of the model has been discussed in detail. One of the dif-ficulties is the choice of the damping factor, which is revealed in this paper. Also the grounding of the system has large impact on the RTDS simulation. Another problem is that the performance of the system is highly dependent on the switch parameters such as voltage and current ratings. Finally, the functionalities of the SST have been realized on the platform. The distributed energy storage interface power injection and reverse power flow have been validated. Some limitations are noticed and discussed through the simulation on RTDS.

  18. Central United States Velocity Model Version 1: Description and Validation

    NASA Astrophysics Data System (ADS)

    Ramirez Guzman, L.; Williams, R. A.; Boyd, O. S.; Hartzell, S.

    2009-12-01

    We describe and test via numerical simulations a velocity model of the Central United States (CUSVM Version 1). Our model covers an area of 650,000 km2 and includes parts of Arkansas, Mississippi, Alabama, Illinois, Missouri, Kentucky and Tennessee. The model represents the compilation of research carried out for decades consisting of seismic refraction and reflection lines, geophysical logs, and inversions of the regional seismic properties. The CUSVM has a higher resolution description around Memphis and St. Louis, two of the largest urban areas in the Central United States. The density, p- and s-wave velocities are synthesized in a stand-alone spatial data base that can be queried to generate the required input for numerical simulations. We calibrate the CUSVM using three earthquakes located N, SW and SE of the zone encompassed by the model to sample different paths of propagation. The selected stations in the comparisons reflect different geological site conditions and cover distances ranging from 50 to 450 km away from the epicenters. The results indicate that both within and outside the Mississippi embayment, the CUSVM satisfactorily reproduces: a) the body wave arrival times and b) the observed regional variations in ground motion amplitude and duration in the frequency range 0-0.75Hz.

  19. Modeling Pilot State in Next Generation Aircraft Alert Systems

    NASA Technical Reports Server (NTRS)

    Carlin, Alan S.; Alexander, Amy L.; Schurr, Nathan

    2011-01-01

    The Next Generation Air Transportation System will introduce new, advanced sensor technologies into the cockpit that must convey a large number of potentially complex alerts. Our work focuses on the challenges associated with prioritizing aircraft sensor alerts in a quick and efficient manner, essentially determining when and how to alert the pilot This "alert decision" becomes very difficult in NextGen due to the following challenges: 1) the increasing number of potential hazards, 2) the uncertainty associated with the state of potential hazards as well as pilot slate , and 3) the limited time to make safely-critical decisions. In this paper, we focus on pilot state and present a model for anticipating duration and quality of pilot behavior, for use in a larger system which issues aircraft alerts. We estimate pilot workload, which we model as being dependent on factors including mental effort, task demands. and task performance. We perform a mathematically rigorous analysis of the model and resulting alerting plans. We simulate the model in software and present simulated results with respect to manipulation of the pilot measures.

  20. Steady state model of an industrial FCC unit

    SciTech Connect

    Lopez-Isunza, F.; Ancheyta-Juarez, J.

    1996-12-31

    A reactor model has been developed to simulate the steady-state of an industrial fluid catalytic cracking unit using a three-lump kinetic expression with parameters estimated from experiments in a microactivity test reactor. The model considers a transported bed reactor (riser) where gas-oil and catalyst are in contact to perform the endothermic cracking reactions, interacting with a two-phase moving bed regenerator with recirculation where the combustion of the coke deposited on the catalyst takes place. The model is used to find best operating conditions for maximizing gasoline yield in terms of gas-oil feed temperature (To) and recycled catalyst to gas-oil ratio (C/O). 12 refs., 4 figs.

  1. Finite element implementation of state variable-based viscoplasticity models

    NASA Technical Reports Server (NTRS)

    Iskovitz, I.; Chang, T. Y. P.; Saleeb, A. F.

    1991-01-01

    The implementation of state variable-based viscoplasticity models is made in a general purpose finite element code for structural applications of metals deformed at elevated temperatures. Two constitutive models, Walker's and Robinson's models, are studied in conjunction with two implicit integration methods: the trapezoidal rule with Newton-Raphson iterations and an asymptotic integration algorithm. A comparison is made between the two integration methods, and the latter method appears to be computationally more appealing in terms of numerical accuracy and CPU time. However, in order to make the asymptotic algorithm robust, it is necessary to include a self adaptive scheme with subincremental step control and error checking of the Jacobian matrix at the integration points. Three examples are given to illustrate the numerical aspects of the integration methods tested.

  2. Phenomenological model for transient deformation based on state variables

    SciTech Connect

    Jackson, M S; Cho, C W; Alexopoulos, P; Mughrabi, H; Li, C Y

    1980-01-01

    The state variable theory of Hart, while providing a unified description of plasticity-dominated deformation, exhibits deficiencies when it is applied to transient deformation phenomena at stresses below yield. It appears that the description of stored anelastic strain is oversimplified. Consideration of a simple physical picture based on continuum dislocation pileups suggests that the neglect of weak barriers to dislocation motion is the source of these inadequacies. An appropriately modified description incorporating such barriers then allows the construction of a macroscopic model including transient effects. Although the flow relations for the microplastic element required in the new theory are not known, tentative assignments may be made for such functions. The model then exhibits qualitatively correct behavior when tensile, loading-unloading, reverse loading, and load relaxation tests are simulated. Experimental procedures are described for determining the unknown parameters and functions in the new model.

  3. Finite state aeroelastic model for use in rotor design optimization

    NASA Technical Reports Server (NTRS)

    He, Chengjian; Peters, David A.

    1993-01-01

    In this article, a rotor aeroelastic model based on a newly developed finite state dynamic wake, coupled with blade finite element analysis, is described. The analysis is intended for application in rotor blade design optimization. A coupled simultaneous system of differential equations combining blade structural dynamics and aerodynamics is established in a formulation well-suited for design sensitivity computation. Each blade is assumed to be an elastic beam undergoing flap bending, lead-lag bending, elastic twist, and axial deflections. Aerodynamic loads are computed from unsteady blade element theory where the rotor three-dimensional unsteady wake is described by a generalized dynamic wake model. Correlation of results obtained from the analysis with flight test data is provided to assess model accuracy.

  4. Modeling individual effects in the Cormack-Jolly-Seber Model: A state-space formulation

    USGS Publications Warehouse

    Royle, J. Andrew

    2008-01-01

    In population and evolutionary biology, there exists considerable interest in individual heterogeneity in parameters of demographic models for open populations. However, flexible and practical solutions to the development of such models have proven to be elusive. In this article, I provide a state-space formulation of open population capture-recapture models with individual effects. The state-space formulation provides a generic and flexible framework for modeling and inference in models with individual effects, and it yields a practical means of estimation in these complex problems via contemporary methods of Markov chain Monte Carlo. A straightforward implementation can be achieved in the software package WinBUGS. I provide an analysis of a simple model with constant parameter detection and survival probability parameters. A second example is based on data from a 7-year study of European dippers, in which a model with year and individual effects is fitted.

  5. Using thermal stress to model aspects of disease states.

    PubMed

    Wilson, Thad E; Klabunde, Richard E; Monahan, Kevin D

    2014-07-01

    Exposure to acute heat or cold stress elicits numerous physiological responses aimed at maintaining body temperatures. Interestingly, many of the physiological responses, mediated by the cardiovascular and autonomic nervous systems, resemble aspects of, or responses to, certain disease states. The purpose of this Perspective is to highlight some of these areas in order to explore how they may help us better understand the pathophysiology underlying aspects of certain disease states. The benefits of using this human thermal stress approach are that (1) no adjustments for inherent comparative differences in animals are needed, (2) non-medicated healthy humans with no underlying co-morbidities can be studied in place of complex patients, and (3) more mechanistic perturbations can be safely employed without endangering potentially vulnerable populations. Cold stress can be used to induce stable elevations in blood pressure. Cold stress may also be used to model conditions where increases in myocardial oxygen demand are not met by anticipated increases in coronary blood flow, as occurs in older adults. Lower-body negative pressure has the capacity to model aspects of shock, and the further addition of heat stress improves and expands this model because passive-heat exposure lowers systemic vascular resistance at a time when central blood volume and left-ventricular filling pressure are reduced. Heat stress can model aspects of heat syncope and orthostatic intolerance as heat stress decreases cerebral blood flow and alters the Frank-Starling mechanism resulting in larger decreases in stroke volume for a given change in left-ventricular filling pressure. Combined, thermal perturbations may provide in vivo paradigms that can be employed to gain insights into pathophysiological aspects of certain disease states. PMID:24956954

  6. Modeling the human invader in the United States

    USGS Publications Warehouse

    Stohlgren, Thomas J.; Jarnevich, Catherine S.; Giri, Chandra P.

    2010-01-01

    Modern biogeographers recognize that humans are seen as constituents of ecosystems, drivers of significant change, and perhaps, the most invasive species on earth. We found it instructive to model humans as invasive organisms with the same environmental factors. We present a preliminary model of the spread of modern humans in the conterminous United States between 1992 and 2001 based on a subset of National Land Cover Data (NLCD), a time series LANDSAT product. We relied on the commonly used Maxent model, a species-environmental matching model, to map urbanization. Results: Urban areas represented 5.1% of the lower 48 states in 2001, an increase of 7.5% (18,112 km2) in the nine year period. At this rate, an area the size of Massachusetts is converted to urban land use every ten years. We used accepted models commonly used for mapping plant and animal distributions and found that climatic and environmental factors can strongly predict our spread (i.e., the conversion of forests, shrub/grass, and wetland areas into urban areas), with a 92.5% success rate (Area Under the Curve). Adding a roads layer in the model improved predictions to a 95.5% success rate. 8.8% of the 1-km2> cells in the conterminous U.S. now have a major road in them. In 2001, 0.8% of 1-km2 > cells in the U.S. had an urbanness value of > 800, (>89% of a 1-km2> cell is urban), while we predict that 24.5% of 1-km2> cells in the conterminous U.S. will be > 800 eventually. Main conclusion: Humans have a highly predictable pattern of urbanization based on climatic and topographic variables. Conservation strategies may benefit from that predictability.

  7. Nonlinear State Estimation and Modeling of a Helicopter UAV

    NASA Astrophysics Data System (ADS)

    Barczyk, Martin

    Experimentally-validated nonlinear flight control of a helicopter UAV has two necessary conditions: an estimate of the vehicle’s states from noisy multirate output measurements, and a nonlinear dynamics model with minimum complexity, physically controllable inputs and experimentally identified parameter values. This thesis addresses both these objectives for the Applied Nonlinear Controls Lab (ANCL)'s helicopter UAV project. A magnetometer-plus-GPS aided Inertial Navigation System (INS) for outdoor flight as well as an Attitude and Heading Reference System (AHRS) for indoor testing are designed, implemented and experimentally validated employing an Extended Kalman Filter (EKF), using a novel calibration technique for the magnetometer aiding sensor added to remove the limitations of an earlier GPS-only aiding design. Next the recently-developed nonlinear observer design methodology of invariant observers is adapted to the aided INS and AHRS examples, employing a rotation matrix representation for the state manifold to obtain designs amenable to global stability analysis, obtaining a direct nonlinear design for gains of the AHRS observer, modifying the previously-proposed Invariant EKF systematic method for computing gains, and culminating in simulation and experimental validation of the observers. Lastly a nonlinear control-oriented model of the helicopter UAV is derived from first principles, using a rigid-body dynamics formulation augmented with models of the on-board subsystems: main rotor forces and blade flapping dynamics, the Bell-Hiller system and flybar flapping dynamics, tail rotor forces, tail gyro unit, engine and rotor speed, servo operation, fuselage drag, and tail stabilizer forces. The parameter values in the resulting models are identified experimentally. Using these the model is further simplified to be tractable for model-based control design.

  8. Modeling the human invader in the United States

    NASA Astrophysics Data System (ADS)

    Stohlgren, Thomas J.; Jarnevich, Catherine S.; Giri, Chandra P.

    2010-02-01

    Modern biogeographers recognize that humans are seen as constituents of ecosystems, drivers of significant change, and perhaps, the most invasive species on earth. We found it instructive to model humans as invasive organisms with the same environmental factors. We present a preliminary model of the spread of modern humans in the conterminous United States between 1992 and 2001 based on a subset of National Land Cover Data (NLCD), a time series LANDSAT product. We relied on the commonly used Maxent model, a species-environmental matching model, to map urbanization. Results: Urban areas represented 5.1% of the lower 48 states in 2001, an increase of 7.5% (18,112 km2) in the nine year period. At this rate, an area the size of Massachusetts is converted to urban land use every ten years. We used accepted models commonly used for mapping plant and animal distributions and found that climatic and environmental factors can strongly predict our spread (i.e., the conversion of forests, shrub/grass, and wetland areas into urban areas), with a 92.5% success rate (Area Under the Curve). Adding a roads layer in the model improved predictions to a 95.5% success rate. 8.8% of the 1-km2 cells in the conterminous U.S. now have a major road in them. In 2001, 0.8% of 1-km2 cells in the U.S. had an urbanness value of > 800, (>89% of a 1-km2 cell is urban), while we predict that 24.5% of 1-km2 cells in the conterminous U.S. will be > 800 eventually. Main conclusion: Humans have a highly predictable pattern of urbanization based on climatic and topographic variables. Conservation strategies may benefit from that predictability.

  9. Specificity in Transition State Binding: The Pauling Model Revisited

    PubMed Central

    Amyes, Tina L.; Richard, John P.

    2013-01-01

    Linus Pauling proposed that the large rate accelerations for enzymes are due to the high specificity of the protein catalyst for binding the reaction transition state. The observation that stable analogs of the transition states for enzymatic reactions often act as tight-binding binding inhibitors provided early support for this simple and elegant proposal. We review experimental results which support the proposal that Pauling’s model provides a satisfactory explanation for the rate accelerations for many heterolytic enzymatic reactions through high energy reaction intermediates, such as proton transfer and decarboxylation. Specificity in transition state binding is obtained when the total intrinsic binding energy of the substrate is significantly larger than the binding energy observed at the Michaelis complex. The results of recent studies to characterize the specificity in binding of the enolate oxygen at the transition state for the 1,3-isomerization reaction catalyzed by ketosteroid isomerase are reviewed. Interactions between pig heart succinyl-CoA:3-oxoacid coenzyme A transferase (SCOT) and the nonreacting portions of CoA are responsible for a rate increase of 3 × 1012-fold, which is close to the estimated total 5 × 1013-fold enzymatic rate acceleration. Studies that partition the interactions between SCOT and CoA into their contributing parts are reviewed. Interactions of the protein with the substrate phosphodianion group provide a ca. 12 kcal/mol stabilization of the transition state for the reactions catalyzed by triosephosphate isomerase, orotidine 5′-monophosphate decarboxylase and α-glycerol phosphate dehydrogenase. The interactions of these enzymes with the substrate piece phosphite dianion provide a 6 – 8 kcal/mol stabilization of the transition state for reaction of the appropriate truncated substrate. Enzyme activation by phosphite dianion reflects the higher dianion affinity for binding to the enzyme-transition state complex compared

  10. Finite state model of locomotion for functional electrical stimulation systems.

    PubMed

    Popović, D B

    1993-01-01

    A finite state model of locomotion was developed to simplify a controller design for motor activities of handicapped humans. This paper presents a model developed for real time control of locomotion with functional electrical stimulation (FES) assistive systems. Hierarchical control of locomotion was adopted with three levels: voluntary, coordination and actuator level. This paper deals only with coordination level of control. In our previous studies we demonstrated that a skill-based expert system can be used for coordination level of control in multi-joint FES systems. Basic elements in this skill-based expert system are production rules. Production rules have the form of If-Then conditional expressions. A technique of automatic determination of these conditional expressions is presented in this paper. This technique for automatic synthesis of production rules uses fuzzy logic and artificial neural networks (ANN). The special class of fuzzy logic elements used in this research is called preferential neurons. The preferential neurons were used to estimate the relevance of each of the sensory inputs to the recognition of patterns defined as finite states. The combination of preferential neurons forms a preferential neural network. The preferential neural network belongs to a class of ANNs. The preferential neural network determined the set of finite states convenient for a skill-based expert system for different modalities of locomotion. PMID:8234764

  11. Pentaquark states in a diquark-triquark model

    NASA Astrophysics Data System (ADS)

    Zhu, Ruilin; Qiao, Cong-Feng

    2016-05-01

    The diquark-triquark model is used to explain charmonium-pentaquark states, i.e., Pc (4380) and Pc (4450), which were observed recently by the LHCb Collaboration. For the first time, we investigate the properties of the color attractive configuration of a triquark and we define a nonlocal light cone distribution amplitude for pentaquark states, where both diquark and triquark are not pointlike, but they have nonzero size. We establish an effective diquark-triquark Hamiltonian based on spin-orbital interaction. According to the Hamiltonian, we show that the minimum mass splitting between 5/2+ and 3/2- is around 100 MeV, which may naturally solve the challenging problem of small mass splitting between Pc (4450) and Pc (4380). This helps to understand the peculiarities of Pc (4380) with a broad decay width whereas Pc (4450) has a narrow decay width. Based on the diquark-triquark model, we predict more pentaquark states, which will hopefully be measured in future experiments.

  12. Modeling biofiltration of VOC mixtures under steady-state conditions

    SciTech Connect

    Baltzis, B.C.; Wojdyla, S.M.; Zarook, S.M.

    1997-06-01

    Treatment of air streams contaminated with binary volatile organic compound (VOC) mixtures in classical biofilters under steady-state conditions of operation was described with a general mathematical model. The model accounts for potential kinetic interactions among the pollutants, effects of oxygen availability on biodegradation, and biomass diversification in the filter bed. While the effects of oxygen were always taken into account, two distinct cases were considered for the experimental model validation. The first involves kinetic interactions, but no biomass differentiation, used for describing data from biofiltration of benzene/toluene mixtures. The second case assumes that each pollutant is treated by a different type of biomass. Each biomass type is assumed to form separate patches of biofilm on the solid packing material, thus kinetic interference does not occur. This model was used for describing biofiltration of ethanol/butanol mixtures. Experiments were performed with classical biofilters packed with mixtures of peat moss and perlite (2:3, volume:volume). The model equations were solved through the use of computer codes based on the fourth-order Runge-Kutta technique for the gas-phase mass balances and the method of orthogonal collocation for the concentration profiles in the biofilms. Good agreement between model predictions and experimental data was found in almost all cases. Oxygen was found to be extremely important in the case of polar VOCs (ethanol/butanol).

  13. Ground state of the three-band Hubbard model

    NASA Astrophysics Data System (ADS)

    Yanagisawa, Takashi; Koike, Soh; Yamaji, Kunihiko

    2001-11-01

    The ground state of the two-dimensional three-band Hubbard model in oxide superconductors is investigated by using the variational Monte Carlo method. The Gutzwiller-projected BCS and spin density wave (SDW) functions are employed in the search for a possible ground state with respect to dependences on electron density. Antiferromagnetic correlations are considerably strong near half-filling. It is shown that the d-wave state may exist away from half-filling for both the hole and electron doping cases. The overall structure of the phase diagram obtained by our calculations qualitatively agrees with experimental indications. The superconducting condensation energy is in reasonable agreement with the experimental value obtained from specific heat and critical magnetic field measurements for optimally doped samples. The inhomogeneous SDW state is also examined near 1/8 doping. Incommensurate magnetic structures become stable due to hole doping in the underdoped region, where the transfer tpp between oxygen orbitals plays an important role in determining a stable stripe structure.

  14. Periodic Striped Ground States in Ising Models with Competing Interactions

    NASA Astrophysics Data System (ADS)

    Giuliani, Alessandro; Seiringer, Robert

    2016-06-01

    We consider Ising models in two and three dimensions, with short range ferromagnetic and long range, power-law decaying, antiferromagnetic interactions. We let J be the ratio between the strength of the ferromagnetic to antiferromagnetic interactions. The competition between these two kinds of interactions induces the system to form domains of minus spins in a background of plus spins, or vice versa. If the decay exponent p of the long range interaction is larger than d + 1, with d the space dimension, this happens for all values of J smaller than a critical value J c (p), beyond which the ground state is homogeneous. In this paper, we give a characterization of the infinite volume ground states of the system, for p > 2d and J in a left neighborhood of J c (p). In particular, we prove that the quasi-one-dimensional states consisting of infinite stripes (d = 2) or slabs (d = 3), all of the same optimal width and orientation, and alternating magnetization, are infinite volume ground states. Our proof is based on localization bounds combined with reflection positivity.

  15. Modeling of efficient solid-state cooler on layered multiferroics.

    PubMed

    Starkov, Ivan; Starkov, Alexander

    2014-08-01

    We have developed theoretical foundations for the design and optimization of a solid-state cooler working through caloric and multicaloric effects. This approach is based on the careful consideration of the thermodynamics of a layered multiferroic system. The main section of the paper is devoted to the derivation and solution of the heat conduction equation for multiferroic materials. On the basis of the obtained results, we have performed the evaluation of the temperature distribution in the refrigerator under periodic external fields. A few practical examples are considered to illustrate the model. It is demonstrated that a 40-mm structure made of 20 ferroic layers is able to create a temperature difference of 25K. The presented work tries to address the whole hierarchy of physical phenomena to capture all of the essential aspects of solid-state cooling. PMID:25073143

  16. Language Model Combination and Adaptation Using Weighted Finite State Transducers

    NASA Technical Reports Server (NTRS)

    Liu, X.; Gales, M. J. F.; Hieronymus, J. L.; Woodland, P. C.

    2010-01-01

    In speech recognition systems language model (LMs) are often constructed by training and combining multiple n-gram models. They can be either used to represent different genres or tasks found in diverse text sources, or capture stochastic properties of different linguistic symbol sequences, for example, syllables and words. Unsupervised LM adaption may also be used to further improve robustness to varying styles or tasks. When using these techniques, extensive software changes are often required. In this paper an alternative and more general approach based on weighted finite state transducers (WFSTs) is investigated for LM combination and adaptation. As it is entirely based on well-defined WFST operations, minimum change to decoding tools is needed. A wide range of LM combination configurations can be flexibly supported. An efficient on-the-fly WFST decoding algorithm is also proposed. Significant error rate gains of 7.3% relative were obtained on a state-of-the-art broadcast audio recognition task using a history dependently adapted multi-level LM modelling both syllable and word sequences

  17. Modeling Clinical States and Metabolic Rhythms in Bioarcheology

    PubMed Central

    Qualls, Clifford; Bianucci, Raffaella; Spilde, Michael N.; Phillips, Genevieve; Wu, Cecilia; Appenzeller, Otto

    2015-01-01

    Bioarcheology is cross disciplinary research encompassing the study of human remains. However, life's activities have, up till now, eluded bioarcheological investigation. We hypothesized that growth lines in hair might archive the biologic rhythms, growth rate, and metabolism during life. Computational modeling predicted the physical appearance, derived from hair growth rate, biologic rhythms, and mental state for human remains from the Roman period. The width of repeat growth intervals (RI's) on the hair, shown by confocal microscopy, allowed computation of time series of periodicities of the RI's to model growth rates of the hairs. Our results are based on four hairs from controls yielding 212 data points and the RI's of six cropped hairs from Zweeloo woman's scalp yielding 504 data points. Hair growth was, ten times faster than normal consistent with hypertrichosis. Cantú syndrome consists of hypertrichosis, dyschondrosteosis, short stature, and cardiomegaly. Sympathetic activation and enhanced metabolic state suggesting arousal was also present. Two-photon microscopy visualized preserved portions of autonomic nerve fibers surrounding the hair bulb. Scanning electron microscopy found evidence that a knife was used to cut the hair three to five days before death. Thus computational modeling enabled the elucidation of life's activities 2000 years after death in this individual with Cantu syndrome. This may have implications for archeology and forensic sciences. PMID:26346040

  18. Regional Climate Model Projections for the State of Washington

    SciTech Connect

    Salathe, E.; Leung, Lai-Yung R.; Qian, Yun; Zhang, Yongxin

    2010-05-05

    Global climate models do not have sufficient spatial resolution to represent the atmospheric and land surface processes that determine the unique regional heterogeneity of the climate of the State of Washington. If future large-scale weather patterns interact differently with the local terrain and coastlines than current weather patterns, local changes in temperature and precipitation could be quite different from the coarse-scale changes projected by global models. Regional climate models explicitly simulate the interactions between the large-scale weather patterns simulated by a global model and the local terrain. We have performed two 100-year climate simulations using the Weather and Research Forecasting (WRF) model developed at the National Center for Atmospheric Research (NCAR). One simulation is forced by the NCAR Community Climate System Model version 3 (CCSM3) and the second is forced by a simulation of the Max Plank Institute, Hamburg, global model (ECHAM5). The mesoscale simulations produce regional changes in snow cover, cloudiness, and circulation patterns associated with interactions between the large-scale climate change and the regional topography and land-water contrasts. These changes substantially alter the temperature and precipitation trends over the region relative to the global model result or statistical downscaling. To illustrate this effect, we analyze the changes from the current climate (1970-1999) to the mid 21st century (2030-2059). Changes in seasonal-mean temperature, precipitation, and snowpack are presented. Several climatological indices of extreme daily weather are also presented: precipitation intensity, fraction of precipitation occurring in extreme daily events, heat wave frequency, growing season length, and frequency of warm nights. Despite somewhat different changes in seasonal precipitation and temperature from the two regional simulations, consistent results for changes in snowpack and extreme precipitation are found in

  19. A mathematical model of pan evaporation under steady state conditions

    NASA Astrophysics Data System (ADS)

    Lim, Wee Ho; Roderick, Michael L.; Farquhar, Graham D.

    2016-09-01

    In the context of changing climate, global pan evaporation records have shown a spatially-averaged trend of ∼ -2 to ∼ -3 mm a-2 over the past 30-50 years. This global phenomenon has motivated the development of the "PenPan" model (Rotstayn et al., 2006). However, the original PenPan model has yet to receive an independent experimental evaluation. Hence, we constructed an instrumented US Class A pan at Canberra Airport (Australia) and monitored it over a three-year period (2007-2010) to uncover the physics of pan evaporation under non-steady state conditions. The experimental investigations of pan evaporation enabled theoretical formulation and parameterisation of the aerodynamic function considering the wind, properties of air and (with or without) the bird guard effect. The energy balance investigation allowed for detailed formulation of the short- and long-wave radiation associated with the albedos and the emissivities of the pan water surface and the pan wall. Here, we synthesise and generalise those earlier works to develop a new model called the "PenPan-V2" model for application under steady state conditions (i.e., uses a monthly time step). Two versions (PenPan-V2C and PenPan-V2S) are tested using pan evaporation data available across the Australian continent. Both versions outperformed the original PenPan model with better representation of both the evaporation rate and the underlying physics of a US Class A pan. The results show the improved solar geometry related calculations (e.g., albedo, area) for the pan system led to a clear improvement in representing the seasonal cycle of pan evaporation. For general applications, the PenPan-V2S is simpler and suited for applications including an evaluation of long-term trends in pan evaporation.

  20. State estimation issues: External system modeling enhancements. Volume 1: External system modeling guidelines; Final report

    SciTech Connect

    Rahimi, A.F.; Kato, K.; Stadlin, W.; Ansari, S.H. |; Brandwajn, V.; Bose, A.

    1995-04-01

    The single largest source of error in state estimation, an inadequate external system model, affects the usefulness of energy management system (EMS) applications. EPRI has developed comprehensive guidelines to help utilities enhance external system modeling for state estimation and has demonstrated use of the guidelines on three host utility systems without data exchange. These guidelines address network topology, analog measurement, inter-utility data exchange, and application procedures and recommendations. They include specific guidelines for utility types and network analysis applications, and validate the Normalized Level of Impact (NLI) as a key index for external system modeling. This report provides valuable insight to the veteran, as well as first-time state estimator implementors and users. A useful reference source, the extensive guidelines supply answers and helpful advice, as well as recommendations for future work. Volume 1 contains external system modeling guidelines, and Volume 2 is a summary of responses to the utility and EMS supplier survey questionnaire used in this project.

  1. Current state of genome-scale modeling in filamentous fungi.

    PubMed

    Brandl, Julian; Andersen, Mikael R

    2015-06-01

    The group of filamentous fungi contains important species used in industrial biotechnology for acid, antibiotics and enzyme production. Their unique lifestyle turns these organisms into a valuable genetic reservoir of new natural products and biomass degrading enzymes that has not been used to full capacity. One of the major bottlenecks in the development of new strains into viable industrial hosts is the alteration of the metabolism towards optimal production. Genome-scale models promise a reduction in the time needed for metabolic engineering by predicting the most potent targets in silico before testing them in vivo. The increasing availability of high quality models and molecular biological tools for manipulating filamentous fungi renders the model-guided engineering of these fungal factories possible with comprehensive metabolic networks. A typical fungal model contains on average 1138 unique metabolic reactions and 1050 ORFs, making them a vast knowledge-base of fungal metabolism. In the present review we focus on the current state as well as potential future applications of genome-scale models in filamentous fungi. PMID:25700817

  2. A statistical model of steady-state solvatochromism.

    PubMed

    Roliński, O; Balter, A

    1995-12-01

    This work provides a description of the solvatochromic effect in terms of a hard-sphere model taking into account the microscopic parameters of the solution. The average energies of the solute-solvent system were calculated for Franck-Condon and relaxed states assuming pairwise electrostatic interactions between polarizable, dipolar molecules contained in clusters made of 1-solute and 10-solvent molecules. This in turn allowed us to estimate the values of the solvatochromic shifts. The dependence of these shifts on temperature and electronic properties of molecules expressed in terms of their polarity and polarizability was investigated. PMID:24226908

  3. New equation of state models for hydrodynamic applications

    NASA Astrophysics Data System (ADS)

    Young, David A.; Barbee, Troy W.; Rogers, Forrest J.

    1998-07-01

    Two new theoretical methods for computing the equation of state of hot, dense matter are discussed. The ab initio phonon theory gives a first-principles calculation of lattice frequencies, which can be used to compare theory and experiment for isothermal and shock compression of solids. The ACTEX dense plasma theory has been improved to allow it to be compared directly with ultrahigh pressure shock data on low-Z materials. The comparisons with experiment are good, suggesting that these models will be useful in generating global EOS tables for hydrodynamic simulations.

  4. Linear modeling of steady-state behavioral dynamics.

    PubMed Central

    Palya, William L; Walter, Donald; Kessel, Robert; Lucke, Robert

    2002-01-01

    The observed steady-state behavioral dynamics supported by unsignaled periods of reinforcement within repeating 2,000-s trials were modeled with a linear transfer function. These experiments employed improved schedule forms and analytical methods to improve the precision of the measured transfer function, compared to previous work. The refinements include both the use of multiple reinforcement periods that improve spectral coverage and averaging of independently determined transfer functions. A linear analysis was then used to predict behavior observed for three different test schedules. The fidelity of these predictions was determined. PMID:11831782

  5. New equation of state model for hydrodynamic applications

    SciTech Connect

    Young, D.A.; Barbee, T.W. III; Rogers, F.J.

    1997-07-01

    Two new theoretical methods for computing the equation of state of hot, dense matter are discussed.The ab initio phonon theory gives a first-principles calculation of lattice frequencies, which can be used to compare theory and experiment for isothermal and shock compression of solids. The ACTEX dense plasma theory has been improved to allow it to be compared directly with ultrahigh pressure shock data on low-Z materials. The comparisons with experiment are good, suggesting that these models will be useful in generating global EOS tables for hydrodynamic simulations.

  6. Approximate flash calculations for equation-of-state compositional models

    SciTech Connect

    Nghiem, L.X.; Li, Y.K.

    1985-02-01

    An approximate method for flash calculations (AFC) with an equation of state is presented. The equations for AFC are obtained by linearizing the thermodynamic equilibrium equations at an equilibrium condition termed reference condition. The AFC equations are much simpler than the actual equations for flash calculations and yet give almost the same results. A procedure for generating new reference conditions to keep the AFC results close to the true flash calculation (TFC) results is described. AFC is compared to TFC in the calculation of standard laboratory tests and in the simulation of gas injection processes with a composition model. Excellent results are obtained with AFC in less than half the original execution time.

  7. Constrained model predictive control, state estimation and coordination

    NASA Astrophysics Data System (ADS)

    Yan, Jun

    In this dissertation, we study the interaction between the control performance and the quality of the state estimation in a constrained Model Predictive Control (MPC) framework for systems with stochastic disturbances. This consists of three parts: (i) the development of a constrained MPC formulation that adapts to the quality of the state estimation via constraints; (ii) the application of such a control law in a multi-vehicle formation coordinated control problem in which each vehicle operates subject to a no-collision constraint posed by others' imperfect prediction computed from finite bit-rate, communicated data; (iii) the design of the predictors and the communication resource assignment problem that satisfy the performance requirement from Part (ii). Model Predictive Control (MPC) is of interest because it is one of the few control design methods which preserves standard design variables and yet handles constraints. MPC is normally posed as a full-state feedback control and is implemented in a certainty-equivalence fashion with best estimates of the states being used in place of the exact state. However, if the state constraints were handled in the same certainty-equivalence fashion, the resulting control law could drive the real state to violate the constraints frequently. Part (i) focuses on exploring the inclusion of state estimates into the constraints. It does this by applying constrained MPC to a system with stochastic disturbances. The stochastic nature of the problem requires re-posing the constraints in a probabilistic form. In Part (ii), we consider applying constrained MPC as a local control law in a coordinated control problem of a group of distributed autonomous systems. Interactions between the systems are captured via constraints. First, we inspect the application of constrained MPC to a completely deterministic case. Formation stability theorems are derived for the subsystems and conditions on the local constraint set are derived in order to

  8. Model-independent confirmation of the Z (4430 )- state

    NASA Astrophysics Data System (ADS)

    Aaij, R.; Adeva, B.; Adinolfi, M.; Affolder, A.; Ajaltouni, Z.; Albrecht, J.; Alessio, F.; Alexander, M.; Ali, S.; Alkhazov, G.; Alvarez Cartelle, P.; Alves, A. A.; Amato, S.; Amerio, S.; Amhis, Y.; An, L.; Anderlini, L.; Anderson, J.; Andreassen, R.; Andreotti, M.; Andrews, J. E.; Appleby, R. B.; Aquines Gutierrez, O.; Archilli, F.; Artamonov, A.; Artuso, M.; Aslanides, E.; Auriemma, G.; Baalouch, M.; Bachmann, S.; Back, J. J.; Badalov, A.; Balagura, V.; Baldini, W.; Barlow, R. J.; Barschel, C.; Barsuk, S.; Barter, W.; Batozskaya, V.; Bauer, Th.; Bay, A.; Beaucourt, L.; Beddow, J.; Bedeschi, F.; Bediaga, I.; Belogurov, S.; Belous, K.; Belyaev, I.; Ben-Haim, E.; Bencivenni, G.; Benson, S.; Benton, J.; Berezhnoy, A.; Bernet, R.; Bettler, M.-O.; van Beuzekom, M.; Bien, A.; Bifani, S.; Bird, T.; Bizzeti, A.; Bjørnstad, P. M.; Blake, T.; Blanc, F.; Blouw, J.; Blusk, S.; Bocci, V.; Bondar, A.; Bondar, N.; Bonivento, W.; Borghi, S.; Borgia, A.; Borsato, M.; Bowcock, T. J. V.; Bowen, E.; Bozzi, C.; Brambach, T.; van den Brand, J.; Bressieux, J.; Brett, D.; Britsch, M.; Britton, T.; Brodzicka, J.; Brook, N. H.; Brown, H.; Bursche, A.; Busetto, G.; Buytaert, J.; Cadeddu, S.; Calabrese, R.; Calvi, M.; Calvo Gomez, M.; Camboni, A.; Campana, P.; Campora Perez, D.; Carbone, A.; Carboni, G.; Cardinale, R.; Cardini, A.; Carranza-Mejia, H.; Carson, L.; Carvalho Akiba, K.; Casse, G.; Cassina, L.; Castillo Garcia, L.; Cattaneo, M.; Cauet, Ch.; Cenci, R.; Charles, M.; Charpentier, Ph.; Chen, S.; Cheung, S.-F.; Chiapolini, N.; Chrzaszcz, M.; Ciba, K.; Cid Vidal, X.; Ciezarek, G.; Clarke, P. E. L.; Clemencic, M.; Cliff, H. V.; Closier, J.; Coco, V.; Cogan, J.; Cogneras, E.; Collins, P.; Comerma-Montells, A.; Contu, A.; Cook, A.; Coombes, M.; Coquereau, S.; Corti, G.; Corvo, M.; Counts, I.; Couturier, B.; Cowan, G. A.; Craik, D. C.; Cruz Torres, M.; Cunliffe, S.; Currie, R.; D'Ambrosio, C.; Dalseno, J.; David, P.; David, P. N. Y.; Davis, A.; De Bruyn, K.; De Capua, S.; De Cian, M.; De Miranda, J. M.; De Paula, L.; De Silva, W.; De Simone, P.; Decamp, D.; Deckenhoff, M.; Del Buono, L.; Déléage, N.; Derkach, D.; Deschamps, O.; Dettori, F.; Di Canto, A.; Dijkstra, H.; Donleavy, S.; Dordei, F.; Dorigo, M.; Dosil Suárez, A.; Dossett, D.; Dovbnya, A.; Dujany, G.; Dupertuis, F.; Durante, P.; Dzhelyadin, R.; Dziurda, A.; Dzyuba, A.; Easo, S.; Egede, U.; Egorychev, V.; Eidelman, S.; Eisenhardt, S.; Eitschberger, U.; Ekelhof, R.; Eklund, L.; El Rifai, I.; Elsasser, Ch.; Ely, S.; Esen, S.; Evans, T.; Falabella, A.; Färber, C.; Farinelli, C.; Farley, N.; Farry, S.; Ferguson, D.; Fernandez Albor, V.; Ferreira Rodrigues, F.; Ferro-Luzzi, M.; Filippov, S.; Fiore, M.; Fiorini, M.; Firlej, M.; Fitzpatrick, C.; Fiutowski, T.; Fontana, M.; Fontanelli, F.; Forty, R.; Francisco, O.; Frank, M.; Frei, C.; Frosini, M.; Fu, J.; Furfaro, E.; Gallas Torreira, A.; Galli, D.; Gallorini, S.; Gambetta, S.; Gandelman, M.; Gandini, P.; Gao, Y.; Garofoli, J.; Garra Tico, J.; Garrido, L.; Gaspar, C.; Gauld, R.; Gavardi, L.; Gersabeck, E.; Gersabeck, M.; Gershon, T.; Ghez, Ph.; Gianelle, A.; Giani', S.; Gibson, V.; Giubega, L.; Gligorov, V. V.; Göbel, C.; Golubkov, D.; Golutvin, A.; Gomes, A.; Gordon, H.; Gotti, C.; Grabalosa Gándara, M.; Graciani Diaz, R.; Granado Cardoso, L. A.; Graugés, E.; Graziani, G.; Grecu, A.; Greening, E.; Gregson, S.; Griffith, P.; Grillo, L.; Grünberg, O.; Gui, B.; Gushchin, E.; Guz, Yu.; Gys, T.; Hadjivasiliou, C.; Haefeli, G.; Haen, C.; Haines, S. C.; Hall, S.; Hamilton, B.; Hampson, T.; Han, X.; Hansmann-Menzemer, S.; Harnew, N.; Harnew, S. T.; Harrison, J.; Hartmann, T.; He, J.; Head, T.; Heijne, V.; Hennessy, K.; Henrard, P.; Henry, L.; Hernando Morata, J. A.; van Herwijnen, E.; Heß, M.; Hicheur, A.; Hill, D.; Hoballah, M.; Hombach, C.; Hulsbergen, W.; Hunt, P.; Hussain, N.; Hutchcroft, D.; Hynds, D.; Idzik, M.; Ilten, P.; Jacobsson, R.; Jaeger, A.; Jalocha, J.; Jans, E.; Jaton, P.; Jawahery, A.; Jezabek, M.; Jing, F.; John, M.; Johnson, D.; Jones, C. R.; Joram, C.; Jost, B.; Jurik, N.; Kaballo, M.; Kandybei, S.; Kanso, W.; Karacson, M.; Karbach, T. M.; Kelsey, M.; Kenyon, I. R.; Ketel, T.; Khanji, B.; Khurewathanakul, C.; Klaver, S.; Kochebina, O.; Kolpin, M.; Komarov, I.; Koopman, R. F.; Koppenburg, P.; Korolev, M.; Kozlinskiy, A.; Kravchuk, L.; Kreplin, K.; Kreps, M.; Krocker, G.; Krokovny, P.; Kruse, F.; Kucharczyk, M.; Kudryavtsev, V.; Kurek, K.; Kvaratskheliya, T.; La Thi, V. N.; Lacarrere, D.; Lafferty, G.; Lai, A.; Lambert, D.; Lambert, R. W.; Lanciotti, E.; Lanfranchi, G.; Langenbruch, C.; Langhans, B.; Latham, T.; Lazzeroni, C.; Le Gac, R.; van Leerdam, J.; Lees, J.-P.; Lefèvre, R.; Leflat, A.; Lefrançois, J.; Leo, S.; Leroy, O.; Lesiak, T.; Leverington, B.; Li, Y.; Liles, M.; Lindner, R.; Linn, C.; Lionetto, F.; Liu, B.; Liu, G.; Lohn, S.; Longstaff, I.; Lopes, J. H.; Lopez-March, N.; Lowdon, P.; Lu, H.; Lucchesi, D.; Luo, H.; Lupato, A.; Luppi, E.; Lupton, O.; Machefert, F.; Machikhiliyan, I. V.; Maciuc, F.; Maev, O.; Malde, S.; Manca, G.; Mancinelli, G.; Manzali, M.; Maratas, J.; Marchand, J. F.; Marconi, U.; Marin Benito, C.; Marino, P.; Märki, R.; Marks, J.; Martellotti, G.; Martens, A.; Martín Sánchez, A.; Martinelli, M.; Martinez Santos, D.; Martinez Vidal, F.; Martins Tostes, D.; Massafferri, A.; Matev, R.; Mathe, Z.; Matteuzzi, C.; Mazurov, A.; McCann, M.; McCarthy, J.; McNab, A.; McNulty, R.; McSkelly, B.; Meadows, B.; Meier, F.; Meissner, M.; Merk, M.; Milanes, D. A.; Minard, M.-N.; Moggi, N.; Molina Rodriguez, J.; Monteil, S.; Moran, D.; Morandin, M.; Morawski, P.; Mordà, A.; Morello, M. J.; Moron, J.; Morris, A.-B.; Mountain, R.; Muheim, F.; Müller, K.; Muresan, R.; Mussini, M.; Muster, B.; Naik, P.; Nakada, T.; Nandakumar, R.; Nasteva, I.; Needham, M.; Neri, N.; Neubert, S.; Neufeld, N.; Neuner, M.; Nguyen, A. D.; Nguyen, T. D.; Nguyen-Mau, C.; Nicol, M.; Niess, V.; Niet, R.; Nikitin, N.; Nikodem, T.; Novoselov, A.; Oblakowska-Mucha, A.; Obraztsov, V.; Oggero, S.; Ogilvy, S.; Okhrimenko, O.; Oldeman, R.; Onderwater, G.; Orlandea, M.; Otalora Goicochea, J. M.; Owen, P.; Oyanguren, A.; Pal, B. K.; Palano, A.; Palombo, F.; Palutan, M.; Panman, J.; Papanestis, A.; Pappagallo, M.; Parkes, C.; Parkinson, C. J.; Passaleva, G.; Patel, G. D.; Patel, M.; Patrignani, C.; Pazos Alvarez, A.; Pearce, A.; Pellegrino, A.; Pepe Altarelli, M.; Perazzini, S.; Perez Trigo, E.; Perret, P.; Perrin-Terrin, M.; Pescatore, L.; Pesen, E.; Petridis, K.; Petrolini, A.; Picatoste Olloqui, E.; Pietrzyk, B.; Pilař, T.; Pinci, D.; Pistone, A.; Playfer, S.; Plo Casasus, M.; Polci, F.; Poluektov, A.; Polycarpo, E.; Popov, A.; Popov, D.; Popovici, B.; Potterat, C.; Powell, A.; Prisciandaro, J.; Pritchard, A.; Prouve, C.; Pugatch, V.; Puig Navarro, A.; Punzi, G.; Qian, W.; Rachwal, B.; Rademacker, J. H.; Rakotomiaramanana, B.; Rama, M.; Rangel, M. S.; Raniuk, I.; Rauschmayr, N.; Raven, G.; Reichert, S.; Reid, M. M.; dos Reis, A. C.; Ricciardi, S.; Richards, A.; Rihl, M.; Rinnert, K.; Rives Molina, V.; Roa Romero, D. A.; Robbe, P.; Rodrigues, A. B.; Rodrigues, E.; Rodriguez Perez, P.; Roiser, S.; Romanovsky, V.; Romero Vidal, A.; Rotondo, M.; Rouvinet, J.; Ruf, T.; Ruffini, F.; Ruiz, H.; Ruiz Valls, P.; Sabatino, G.; Saborido Silva, J. J.; Sagidova, N.; Sail, P.; Saitta, B.; Salustino Guimaraes, V.; Sanchez Mayordomo, C.; Sanmartin Sedes, B.; Santacesaria, R.; Santamarina Rios, C.; Santovetti, E.; Sapunov, M.; Sarti, A.; Satriano, C.; Satta, A.; Savrie, M.; Savrina, D.; Schiller, M.; Schindler, H.; Schlupp, M.; Schmelling, M.; Schmidt, B.; Schneider, O.; Schopper, A.; Schune, M.-H.; Schwemmer, R.; Sciascia, B.; Sciubba, A.; Seco, M.; Semennikov, A.; Senderowska, K.; Sepp, I.; Serra, N.; Serrano, J.; Sestini, L.; Seyfert, P.; Shapkin, M.; Shapoval, I.; Shcheglov, Y.; Shears, T.; Shekhtman, L.; Shevchenko, V.; Shires, A.; Silva Coutinho, R.; Simi, G.; Sirendi, M.; Skidmore, N.; Skwarnicki, T.; Smith, N. A.; Smith, E.; Smith, E.; Smith, J.; Smith, M.; Snoek, H.; Sokoloff, M. D.; Soler, F. J. P.; Soomro, F.; Souza, D.; Souza De Paula, B.; Spaan, B.; Sparkes, A.; Spinella, F.; Spradlin, P.; Stagni, F.; Stahl, S.; Steinkamp, O.; Stenyakin, O.; Stevenson, S.; Stoica, S.; Stone, S.; Storaci, B.; Stracka, S.; Straticiuc, M.; Straumann, U.; Stroili, R.; Subbiah, V. K.; Sun, L.; Sutcliffe, W.; Swientek, K.; Swientek, S.; Syropoulos, V.; Szczekowski, M.; Szczypka, P.; Szilard, D.; Szumlak, T.; T'Jampens, S.; Teklishyn, M.; Tellarini, G.; Teubert, F.; Thomas, C.; Thomas, E.; van Tilburg, J.; Tisserand, V.; Tobin, M.; Tolk, S.; Tomassetti, L.; Tonelli, D.; Topp-Joergensen, S.; Torr, N.; Tournefier, E.; Tourneur, S.; Tran, M. T.; Tresch, M.; Tsaregorodtsev, A.; Tsopelas, P.; Tuning, N.; Ubeda Garcia, M.; Ukleja, A.; Ustyuzhanin, A.; Uwer, U.; Vagnoni, V.; Valenti, G.; Vallier, A.; Vazquez Gomez, R.; Vazquez Regueiro, P.; Vázquez Sierra, C.; Vecchi, S.; Velthuis, J. J.; Veltri, M.; Veneziano, G.; Vesterinen, M.; Viaud, B.; Vieira, D.; Vieites Diaz, M.; Vilasis-Cardona, X.; Vollhardt, A.; Volyanskyy, D.; Voong, D.; Vorobyev, A.; Vorobyev, V.; Voß, C.; Voss, H.; de Vries, J. A.; Waldi, R.; Wallace, C.; Wallace, R.; Walsh, J.; Wandernoth, S.; Wang, J.; Ward, D. R.; Watson, N. K.; Websdale, D.; Whitehead, M.; Wicht, J.; Wiedner, D.; Wilkinson, G.; Williams, M. P.; Williams, M.; Wilson, F. F.; Wimberley, J.; Wishahi, J.; Wislicki, W.; Witek, M.; Wormser, G.; Wotton, S. A.; Wright, S.; Wu, S.; Wyllie, K.; Xie, Y.; Xing, Z.; Xu, Z.; Yang, Z.; Yuan, X.; Yushchenko, O.; Zangoli, M.; Zavertyaev, M.; Zhang, F.; Zhang, L.; Zhang, W. C.; Zhang, Y.; Zhelezov, A.; Zhokhov, A.; Zhong, L.; Zvyagin, A.; LHCb Collaboration

    2015-12-01

    The decay B0→ψ (2 S )K+π- is analyzed using 3 fb-1 of p p collision data collected with the LHCb detector. A model-independent description of the ψ (2 S )π mass spectrum is obtained, using as input the K π mass spectrum and angular distribution derived directly from data, without requiring a theoretical description of resonance shapes or their interference. The hypothesis that the ψ (2 S )π mass spectrum can be described in terms of K π reflections alone is rejected with more than 8 σ significance. This provides confirmation, in a model-independent way, of the need for an additional resonant component in the mass region of the Z (4430 )- exotic state.

  9. Modelling of pulsed and steady-state DEMO scenarios

    NASA Astrophysics Data System (ADS)

    Giruzzi, G.; Artaud, J. F.; Baruzzo, M.; Bolzonella, T.; Fable, E.; Garzotti, L.; Ivanova-Stanik, I.; Kemp, R.; King, D. B.; Schneider, M.; Stankiewicz, R.; Stępniewski, W.; Vincenzi, P.; Ward, D.; Zagórski, R.

    2015-07-01

    Scenario modelling for the demonstration fusion reactor (DEMO) has been carried out using a variety of simulation codes. Two DEMO concepts have been analysed: a pulsed tokamak, characterized by rather conventional physics and technology assumptions (DEMO1) and a steady-state tokamak, with moderately advanced physics and technology assumptions (DEMO2). Sensitivity to impurity concentrations, radiation, and heat transport models has been investigated. For DEMO2, the impact of current driven non-inductively by neutral beams has been studied by full Monte Carlo simulations of the fast ion distribution. The results obtained are a part of a more extensive research and development (R&D) effort carried out in the EU in order to develop a viable option for a DEMO reactor, to be adopted after ITER for fusion energy research.

  10. State-variable friction for the Burridge-Knopoff model

    NASA Astrophysics Data System (ADS)

    Clancy, Ian; Corcoran, David

    2009-07-01

    This work shows the relationship of the state variable rock-friction law proposed by Dieterich to the Carlson and Langer friction law commonly used in the Burridge-Knopoff (BK) model of earthquakes. Further to this, the Dieterich law is modified to allow slip rates of zero magnitude yielding a three parameter friction law that is included in the BK system. Dynamic phases of small scale and large scale events are found with a transition surface in the parameter space. Near this transition surface the event size distribution follows a power law with an exponent that varies as the transition is approached contrasting with the invariant exponent observed using the Carlson and Langer friction. This variability of the power-law exponent is consistent with the range of exponents measured in real earthquake systems and is more selective than the range observed in the Olami-Feder-Christensen model.

  11. Modeling Dynamic Ductility: An Equation of State for Porous Metals

    SciTech Connect

    Colvin, J

    2007-07-27

    Enhanced heating from shock compression of a porous material can potentially suppress or delay cracking of the material on subsequent expansion. In this paper we quantify the expected enhanced heating in an experiment in which a sector of a thin cylindrical shell is driven from the inside surface by SEMTEX high explosive ({approx}1 {micro}s FWHM pressure pulse with peak pressure {approx}21.5 GPa). We first derive an analytical equation of state (EOS) for porous metals, then discuss the coupling of this EOS with material elastic-plastic response in a 2D hydrocode, and then discuss the modeling of the HE experiment with both fully dense and 10% porous Ta and a Bi/Ta composite. Finally, we compare our modeling with some recent experimental data.

  12. Model Representation of Multi-Cyclic Phenomena Using Role State Variables: Model Based Fast Idling Control of SI Engine

    NASA Astrophysics Data System (ADS)

    Jimbo, Tomohiko; Hayakawa, Yoshikazu

    The present paper describes a model representation of multi-cyclic phenomena for a multi-cylinder engine system. The model is simplified for implementation as a practical engine controller. The simplified model with physically meaningful variables can be used in design considering practical objectives and constraints more effectively. The proposed approach consists of two steps. First, an approximate analytical discrete crank angle model (i.e., a periodically time-varying state space model) is derived from the conservation laws. Second, the concept of role state variables is proposed to transform the periodically time-varying state space model into a time-invariant state space model. The stabilizability and optimality of the time-invariant state space model imply those of the periodically time-varying state space model. The time-invariant state space model is used to design cold start feedforward and feedback controllers.

  13. Matrix product states and the non-Abelian rotor model

    NASA Astrophysics Data System (ADS)

    Milsted, Ashley

    2016-04-01

    We use uniform matrix product states to study the (1 +1 )D O (2 ) and O (4 ) rotor models, which are equivalent to the Kogut-Susskind formulation of matter-free non-Abelian lattice gauge theory on a "Hawaiian earring" graph for U (1 ) and S U (2 ), respectively. Applying tangent space methods to obtain ground states and determine the mass gap and the β function, we find excellent agreement with known results, locating the Berezinskii-Kosterlitz-Thouless transition for O (2 ) and successfully entering the asymptotic weak-coupling regime for O (4 ). To obtain a finite local Hilbert space, we truncate in the space of generalized Fourier modes of the gauge group, comparing the effects of different cutoff values. We find that higher modes become important in the crossover and weak-coupling regimes of the non-Abelian theory, where entanglement also suddenly increases. This could have important consequences for tensor network state studies of Yang-Mills on higher-dimensional graphs.

  14. Solid state stability studies of model dipeptides: aspartame and aspartylphenylalanine.

    PubMed

    Leung, S S; Grant, D J

    1997-01-01

    Some solid-state pharmaceutical properties and the solid-state thermal stability of the model dipeptides aspartame (APM) and aspartylphenylalanine (AP), have been investigated. Studies by differential scanning calorimetry (DSC), thermal gravimetric analysis (TGA), high-performance liquid chromatography, powder X-ray diffraction, and optical microscopy have shown that the dipeptides undergo solid state intramolecular aminolysis of the type, solid --> solid + gas. This reaction was observed for APM at 167-180 degrees C with the liberation of methanol and for AP at 186-202 degrees C with the liberation of water. The exclusive solid product of the degradation reaction of both dipeptides is the cyclic compound 3-(carboxymethyl)-6-benzyl-2,5-dioxopiperazine. The rates of the degradation reactions were monitored by isothermal TGA and by temperature-ramp DSC and were found to follow kinetics based on nucleation control with activation energies of about 266 kJ mol(-1) for APM and 234 kJ mol(-1) for AP. PMID:9002461

  15. An Examination of State Funding Models Regarding Virtual Schools for Public Elementary and Secondary Education in the United States

    ERIC Educational Resources Information Center

    Stedrak, Luke J.

    2012-01-01

    This study contains an analysis of virtual schools, public policy, and funding in the United States. The purpose of this study was to determine what public policies and legislation were in place regarding the funding models of virtual education on a state by state basis. Furthermore, this study addressed how allocations were being made by state…

  16. Ground-State of the Bose-Hubbard Model

    NASA Astrophysics Data System (ADS)

    Mancini, J. D.; Fessatidis, V.; Bowen, S. P.; Murawski, R. K.; Maly, J.

    The Bose-Hubbard Model represents a s simple theoretical model to describe the physics of interacting Boson systems. In particular it has proved to be an effective description of a number of physical systems such as arrays of Josephson arrays as well as dilute alkali gases in optical lattices. Here we wish to study the ground-state of this system using two disparate but related moments calculational schemes: the Lanczos (tridiagonal) method as well as a Generalized moments approach. The Hamiltonian to be studied is given by (in second-quantized notation): H = - t ∑ < i , j > bi†bj +U/2 ∑ inini - 1 - μ ∑ ini . Here i is summed over all lattice sites, and < i , j > denotes summation over all neighbhoring sites i and j, while bi† and bi are bosonic creation and annihilation operators. ni = bi†bi gives the number of particles on site i. Parameter t is the hopping amplitude, describing mobility of bosons in the lattice. Parameter U describes the on-site interaction, repulsive, if U > 0 , and attractive for U < 0 . μ is the chemical potential. Both the ground-state energy and energy gap are evaluated as a function of t, U and μ.

  17. Integrated stoichiometric, thermodynamic and kinetic modelling of steady state metabolism

    PubMed Central

    Fleming, R.M.T.; Thiele, I.; Provan, G.; Nasheuer, H.P.

    2010-01-01

    The quantitative analysis of biochemical reactions and metabolites is at frontier of biological sciences. The recent availability of high-throughput technology data sets in biology has paved the way for new modelling approaches at various levels of complexity including the metabolome of a cell or an organism. Understanding the metabolism of a single cell and multi-cell organism will provide the knowledge for the rational design of growth conditions to produce commercially valuable reagents in biotechnology. Here, we demonstrate how equations representing steady state mass conservation, energy conservation, the second law of thermodynamics, and reversible enzyme kinetics can be formulated as a single system of linear equalities and inequalities, in addition to linear equalities on exponential variables. Even though the feasible set is non-convex, the reformulation is exact and amenable to large-scale numerical analysis, a prerequisite for computationally feasible genome scale modelling. Integrating flux, concentration and kinetic variables in a unified constraint-based formulation is aimed at increasing the quantitative predictive capacity of flux balance analysis. Incorporation of experimental and theoretical bounds on thermodynamic and kinetic variables ensures that the predicted steady state fluxes are both thermodynamically and biochemically feasible. The resulting in silico predictions are tested against fluxomic data for central metabolism in E. coli and compare favourably with in silico prediction by flux balance analysis. PMID:20230840

  18. Integrated stoichiometric, thermodynamic and kinetic modelling of steady state metabolism.

    PubMed

    Fleming, R M T; Thiele, I; Provan, G; Nasheuer, H P

    2010-06-01

    The quantitative analysis of biochemical reactions and metabolites is at frontier of biological sciences. The recent availability of high-throughput technology data sets in biology has paved the way for new modelling approaches at various levels of complexity including the metabolome of a cell or an organism. Understanding the metabolism of a single cell and multi-cell organism will provide the knowledge for the rational design of growth conditions to produce commercially valuable reagents in biotechnology. Here, we demonstrate how equations representing steady state mass conservation, energy conservation, the second law of thermodynamics, and reversible enzyme kinetics can be formulated as a single system of linear equalities and inequalities, in addition to linear equalities on exponential variables. Even though the feasible set is non-convex, the reformulation is exact and amenable to large-scale numerical analysis, a prerequisite for computationally feasible genome scale modelling. Integrating flux, concentration and kinetic variables in a unified constraint-based formulation is aimed at increasing the quantitative predictive capacity of flux balance analysis. Incorporation of experimental and theoretical bounds on thermodynamic and kinetic variables ensures that the predicted steady state fluxes are both thermodynamically and biochemically feasible. The resulting in silico predictions are tested against fluxomic data for central metabolism in Escherichia coli and compare favourably with in silico prediction by flux balance analysis. PMID:20230840

  19. Excited states of ribosome translocation revealed through integrative molecular modeling

    PubMed Central

    Whitford, Paul C.; Ahmed, Aqeel; Yu, Yanan; Hennelly, Scott P.; Tama, Florence; Spahn, Christian M. T.; Onuchic, José N.; Sanbonmatsu, Karissa Y.

    2011-01-01

    The dynamic nature of biomolecules leads to significant challenges when characterizing the structural properties associated with function. While X-ray crystallography and imaging techniques (such as cryo-electron microscopy) can reveal the structural details of stable molecular complexes, strategies must be developed to characterize configurations that exhibit only marginal stability (such as intermediates) or configurations that do not correspond to minima on the energy landscape (such as transition-state ensembles). Here, we present a methodology (MDfit) that utilizes molecular dynamics simulations to generate configurations of excited states that are consistent with available biophysical and biochemical measurements. To demonstrate the approach, we present a sequence of configurations that are suggested to be associated with transfer RNA (tRNA) movement through the ribosome (translocation). The models were constructed by combining information from X-ray crystallography, cryo-electron microscopy, and biochemical data. These models provide a structural framework for translocation that may be further investigated experimentally and theoretically to determine the precise energetic character of each configuration and the transition dynamics between them. PMID:22080606

  20. Excited states of ribosome translocation revealed through integrative molecular modeling.

    PubMed

    Whitford, Paul C; Ahmed, Aqeel; Yu, Yanan; Hennelly, Scott P; Tama, Florence; Spahn, Christian M T; Onuchic, José N; Sanbonmatsu, Karissa Y

    2011-11-22

    The dynamic nature of biomolecules leads to significant challenges when characterizing the structural properties associated with function. While X-ray crystallography and imaging techniques (such as cryo-electron microscopy) can reveal the structural details of stable molecular complexes, strategies must be developed to characterize configurations that exhibit only marginal stability (such as intermediates) or configurations that do not correspond to minima on the energy landscape (such as transition-state ensembles). Here, we present a methodology (MDfit) that utilizes molecular dynamics simulations to generate configurations of excited states that are consistent with available biophysical and biochemical measurements. To demonstrate the approach, we present a sequence of configurations that are suggested to be associated with transfer RNA (tRNA) movement through the ribosome (translocation). The models were constructed by combining information from X-ray crystallography, cryo-electron microscopy, and biochemical data. These models provide a structural framework for translocation that may be further investigated experimentally and theoretically to determine the precise energetic character of each configuration and the transition dynamics between them. PMID:22080606

  1. Modeling switchgrass derived cellulosic ethanol distribution in the United States.

    PubMed

    Morrow, William R; Griffin, W Michael; Matthews, H Scott

    2006-05-01

    Discussions of alternative fuel and propulsion technologies for transportation often overlook the infrastructure required to make these options practical and cost-effective. We estimate ethanol production facility locations and use a linear optimization model to consider the economic costs of distributing various ethanol fuel blends to all metropolitan areas in the United States. Fuel options include corn-based E5 (5% ethanol, 95% gasoline) to E16 from corn and switchgrass, as short-term substitutes for petroleum-based fuel. Our estimates of 1-2 cents per L of ethanol blend for downstream rail or truck transportation remain a relatively small fraction of total fuel cost. However, for even the relatively small blends of ethanol modeled, the transportation infrastructure demands would be comparably larger than the current demands of petroleum. Thus if ethanol is to be competitive in the long run, then in addition to process efficiency improvements, more efficient transportation infrastructure will need to be developed, such as pipelines. In addition to these results, national and regional policy challenges on how to pay for and optimize a new fuel and distribution infrastructure in the United States are discussed. PMID:16719086

  2. Dislocation models of interseismic deformation in the western United States

    USGS Publications Warehouse

    Pollitz, F.F.; McCrory, P.; Svarc, J.; Murray, J.

    2008-01-01

    The GPS-derived crustal velocity field of the western United States is used to construct dislocation models in a viscoelastic medium of interseismic crustal deformation. The interseismic velocity field is constrained by 1052 GPS velocity vectors spanning the ???2500-km-long plate boundary zone adjacent to the San Andreas fault and Cascadia subduction zone and extending ???1000 km into the plate interior. The GPS data set is compiled from U.S. Geological Survey campaign data, Plate Boundary Observatory data, and the Western U.S. Cordillera velocity field of Bennett et al. (1999). In the context of viscoelastic cycle models of postearthquake deformation, the interseismic velocity field is modeled with a combination of earthquake sources on ???100 known faults plus broadly distributed sources. Models that best explain the observed interseismic velocity field include the contributions of viscoelastic relaxation from faulting near the major plate margins, viscoelastic relaxation from distributed faulting in the plate interior, as well as lateral variations in depth-averaged rigidity in the elastic lithosphere. Resulting rigidity variations are consistent with reduced effective elastic plate thickness in a zone a few tens of kilometers wide surrounding the San Andreas fault (SAF) system. Primary deformation characteristics are captured along the entire SAF system, Eastern California Shear Zone, Walker Lane, the Mendocino triple junction, the Cascadia margin, and the plate interior up to ???1000 km from the major plate boundaries.

  3. Dislocation models of interseismic deformation in the western United States

    NASA Astrophysics Data System (ADS)

    Pollitz, Fred F.; McCrory, Patricia; Svarc, Jerry; Murray, Jessica

    2008-04-01

    The GPS-derived crustal velocity field of the western United States is used to construct dislocation models in a viscoelastic medium of interseismic crustal deformation. The interseismic velocity field is constrained by 1052 GPS velocity vectors spanning the ˜2500-km-long plate boundary zone adjacent to the San Andreas fault and Cascadia subduction zone and extending ˜1000 km into the plate interior. The GPS data set is compiled from U.S. Geological Survey campaign data, Plate Boundary Observatory data, and the Western U.S. Cordillera velocity field of Bennett et al. (1999). In the context of viscoelastic cycle models of postearthquake deformation, the interseismic velocity field is modeled with a combination of earthquake sources on ˜100 known faults plus broadly distributed sources. Models that best explain the observed interseismic velocity field include the contributions of viscoelastic relaxation from faulting near the major plate margins, viscoelastic relaxation from distributed faulting in the plate interior, as well as lateral variations in depth-averaged rigidity in the elastic lithosphere. Resulting rigidity variations are consistent with reduced effective elastic plate thickness in a zone a few tens of kilometers wide surrounding the San Andreas fault (SAF) system. Primary deformation characteristics are captured along the entire SAF system, Eastern California Shear Zone, Walker Lane, the Mendocino triple junction, the Cascadia margin, and the plate interior up to ˜1000 km from the major plate boundaries.

  4. State-of-the-art Model M-2 Maintenance System

    SciTech Connect

    Herndon, J.N.; Martin, H.L.; Satterlee, P.E. Jr.; Jelatis, D.G.; Jennrich, C.E.

    1984-04-01

    The Model M-2 Maintenance System is part of an ongoing program within the Consolidated Fuel Reprocessing Program (CFRP) at Oak Ridge National Laboratory (ORNL) to improve remote manipulation technology for future nuclear fuel reprocessing and other remote applications. Techniques, equipment, and guidelines which can improve the efficiency of remote maintenance are being developed. The Model M-2 Maintenance System, installed in the Integrated Equipment Test (IET) Facility at ORNL, provides a complete, integrated remote maintenance system for the demonstration and development of remote maintenance techniques. The system comprises a pair of force-reflecting servomanipulator arms, television viewing, lighting, and auxiliary lifting capabilities, thereby allowing manlike maintenance operations to be executed remotely within the remote cell mockup area in the IET. The Model M-2 Maintenance System incorporates an upgraded version of the proven Central Research Laboratories' Model M servomanipulator. Included are state-of-the-art brushless dc servomotors for improved performance, remotely removable wrist assemblies, geared azimuth drive, and a distributed microprocessor-based digital control system. 5 references, 8 figures.

  5. The present state of geomagnetic comprehensive models and their applications

    NASA Astrophysics Data System (ADS)

    Sabaka, T.; Olsen, N.

    2003-04-01

    Over the last couple of years a marked advancement in magnetic field modelling capabilities has occurred, spawned by exciting new mapping missions such as Oersted, CHAMP and SACC. A new class of models, popularly known as "comprehensive models" (CMs), has arisen in which fields from the major near- Earth electric current systems have been parameterized, and these parameters coestimated from surface and satellite data such that an optimal partitioning of the constituent signals is achieved. The best CMs to date have been derived from observatory data as well as from POGO, Magsat, Oersted and CHAMP satellite data. While the implications from these models concerning core secular variation (SV), lithospheric fields, ionospheric currents systems, etc., are of great interest, perhaps the most intriguing CM contributions come in the form of applications to other problems. This talk will briefly outline the present state of the CMs and survey some of their current and anticipated applications, such as the removal of SV and diurnal signals from aeromagnetic surveys, inflight satellite magnetometer calibration, and induction studies.

  6. Developing a PLC-friendly state machine model: lessons learned

    NASA Astrophysics Data System (ADS)

    Pessemier, Wim; Deconinck, Geert; Raskin, Gert; Saey, Philippe; Van Winckel, Hans

    2014-07-01

    Modern Programmable Logic Controllers (PLCs) have become an attractive platform for controlling real-time aspects of astronomical telescopes and instruments due to their increased versatility, performance and standardization. Likewise, vendor-neutral middleware technologies such as OPC Unified Architecture (OPC UA) have recently demonstrated that they can greatly facilitate the integration of these industrial platforms into the overall control system. Many practical questions arise, however, when building multi-tiered control systems that consist of PLCs for low level control, and conventional software and platforms for higher level control. How should the PLC software be structured, so that it can rely on well-known programming paradigms on the one hand, and be mapped to a well-organized OPC UA interface on the other hand? Which programming languages of the IEC 61131-3 standard closely match the problem domains of the abstraction levels within this structure? How can the recent additions to the standard (such as the support for namespaces and object-oriented extensions) facilitate a model based development approach? To what degree can our applications already take advantage of the more advanced parts of the OPC UA standard, such as the high expressiveness of the semantic modeling language that it defines, or the support for events, aggregation of data, automatic discovery, ... ? What are the timing and concurrency problems to be expected for the higher level tiers of the control system due to the cyclic execution of control and communication tasks by the PLCs? We try to answer these questions by demonstrating a semantic state machine model that can readily be implemented using IEC 61131 and OPC UA. One that does not aim to capture all possible states of a system, but rather one that attempts to organize the course-grained structure and behaviour of a system. In this paper we focus on the intricacies of this seemingly simple task, and on the lessons that we

  7. Modeling the 1992 Landers Earthquake with a Rate and State Friction Model.

    NASA Astrophysics Data System (ADS)

    Mohammedi, H.; Madariaga, R.; Perrin, G.

    2002-12-01

    We study rupture propagation in realistic earthquake models under rate and state dependent friction and we apply it to the modeling of the 28 June 1992, Landers earthquake. In our simulations we use a modified version of rate and state proposed by Perrin, Rice and Zheng, the so called PRZ law. Full inversion with PRZ is not yet possible because of the much higher numerical cost of modeling a fault under rate and state than with slip weakening friction laws (SW). Also PRZ has a larger number of independent parameters than slip weakening. We obtain reasonable initial models through the use of the ratio κ between available strain energy and energy relase rate. Because in PRZ friction there are more parameters than in SW we have not yet been able to identify all relevant non-dimensional numbers that control rupture in this model, but a very important one is a logarithmic map that controls whether instable slip may occur or not. This map has the form log ˙ D/v0 = λ ˙ D/v0, where λ is a nondimensional number akin to κ . It includes the parameters of the friction law and the characteristic length of the initial stress, velocity or state fields. ˙ D is slip velocity and v0 a reference speed that defines the initial stress field. Using the results of dynamic inversion from Peyrat et al, we find reasonable rupture models for the initiation of the Landers earthquake. The slip weakening distance in rate and state Dc, as defined by Bizarri and Cocco, is of the order of a few tens of cm. Dc is determined from L, the relaxation length in rate and state, as a subproduct of the logarithmic map cited above.

  8. Multiscale air quality modeling of the Northeastern United States

    NASA Astrophysics Data System (ADS)

    Kumar, Naresh; Russell, Armistead G.

    The Urban and Regional Multiscale (URM) model has been used to study the ozone problem in the northeastern United States. The model was applied to a multiday ozone episode extending from 2 July 1988 to 8 July 1988. The URM model is particularly suitable for application to the Northeast as there is a dense network of urban centers along with large rural areas, and the model allows the use of variable grid sizes to effectively capture the pollutant dynamics while being computationally efficient. This study particularly concentrates on how spatial grid resolution affects results, particularly in the Northeast Corridor, a string of urban centers extending from Washington D.C. to Boston. Three different grid systems are employed in the model simulations to examine this issue. The most dynamic grid system uses grid sizes varying from 4.625 to 74 km, with the finest grids concentrated in the Northeast Corridor. The uniform grid system uses a uniform grid size of 18.5 km similar to that used in the regional oxidant model (ROM). The intermediate grid system uses grid sizes varying from 4.625 to 18.5 km. When finer grids are used over the urban areas, as in the intermediate and the most dynamic grid systems, the model predicted higher peak ozone concentrations with greater detail. Sensitivity calculations were performed to quantify the effect of various inputs on the predicted ozone. Effects of zeroing the initial conditions persisted until 7 July 1988. When using background levels of species concentrations as initial conditions, the effect lasted only for two days of simulation. Boundary conditions impacted the ozone concentrations near the boundary cells only. Emission inputs were the major factor in producing the large concentrations of ozone predicted in the Northeast Corridor. The URM model was also used to study ozone control strategy issues in the Northeast Corridor. A suite of simulations was performed where anthropogenic NO x and VOC emission levels were reducd

  9. State-transition modeling: a report of the ISPOR-SMDM Modeling Good Research Practices Task Force--3.

    PubMed

    Siebert, Uwe; Alagoz, Oguzhan; Bayoumi, Ahmed M; Jahn, Beate; Owens, Douglas K; Cohen, David J; Kuntz, Karen M

    2012-01-01

    State-transition modeling is an intuitive, flexible, and transparent approach of computer-based decision-analytic modeling including both Markov model cohort simulation and individual-based (first-order Monte Carlo) microsimulation. Conceptualizing a decision problem in terms of a set of (health) states and transitions among these states, state-transition modeling is one of the most widespread modeling techniques in clinical decision analysis, health technology assessment, and health-economic evaluation. State-transition models have been used in many different populations and diseases, and their applications range from personalized health care strategies to public health programs. Most frequently, state-transition models are used in the evaluation of risk factor interventions, screening, diagnostic procedures, treatment strategies, and disease management programs. The goal of this article was to provide consensus-based guidelines for the application of state-transition models in the context of health care. We structured the best practice recommendations in the following sections: choice of model type (cohort vs. individual-level model), model structure, model parameters, analysis, reporting, and communication. In each of these sections, we give a brief description, address the issues that are of particular relevance to the application of state-transition models, give specific examples from the literature, and provide best practice recommendations for state-transition modeling. These recommendations are directed both to modelers and to users of modeling results such as clinicians, clinical guideline developers, manufacturers, or policymakers. PMID:22999130

  10. Langevin equation with fluctuating diffusivity: A two-state model

    NASA Astrophysics Data System (ADS)

    Miyaguchi, Tomoshige; Akimoto, Takuma; Yamamoto, Eiji

    2016-07-01

    Recently, anomalous subdiffusion, aging, and scatter of the diffusion coefficient have been reported in many single-particle-tracking experiments, though the origins of these behaviors are still elusive. Here, as a model to describe such phenomena, we investigate a Langevin equation with diffusivity fluctuating between a fast and a slow state. Namely, the diffusivity follows a dichotomous stochastic process. We assume that the sojourn time distributions of these two states are given by power laws. It is shown that, for a nonequilibrium ensemble, the ensemble-averaged mean-square displacement (MSD) shows transient subdiffusion. In contrast, the time-averaged MSD shows normal diffusion, but an effective diffusion coefficient transiently shows aging behavior. The propagator is non-Gaussian for short time and converges to a Gaussian distribution in a long-time limit; this convergence to Gaussian is extremely slow for some parameter values. For equilibrium ensembles, both ensemble-averaged and time-averaged MSDs show only normal diffusion and thus we cannot detect any traces of the fluctuating diffusivity with these MSDs. Therefore, as an alternative approach to characterizing the fluctuating diffusivity, the relative standard deviation (RSD) of the time-averaged MSD is utilized and it is shown that the RSD exhibits slow relaxation as a signature of the long-time correlation in the fluctuating diffusivity. Furthermore, it is shown that the RSD is related to a non-Gaussian parameter of the propagator. To obtain these theoretical results, we develop a two-state renewal theory as an analytical tool.

  11. Langevin equation with fluctuating diffusivity: A two-state model.

    PubMed

    Miyaguchi, Tomoshige; Akimoto, Takuma; Yamamoto, Eiji

    2016-07-01

    Recently, anomalous subdiffusion, aging, and scatter of the diffusion coefficient have been reported in many single-particle-tracking experiments, though the origins of these behaviors are still elusive. Here, as a model to describe such phenomena, we investigate a Langevin equation with diffusivity fluctuating between a fast and a slow state. Namely, the diffusivity follows a dichotomous stochastic process. We assume that the sojourn time distributions of these two states are given by power laws. It is shown that, for a nonequilibrium ensemble, the ensemble-averaged mean-square displacement (MSD) shows transient subdiffusion. In contrast, the time-averaged MSD shows normal diffusion, but an effective diffusion coefficient transiently shows aging behavior. The propagator is non-Gaussian for short time and converges to a Gaussian distribution in a long-time limit; this convergence to Gaussian is extremely slow for some parameter values. For equilibrium ensembles, both ensemble-averaged and time-averaged MSDs show only normal diffusion and thus we cannot detect any traces of the fluctuating diffusivity with these MSDs. Therefore, as an alternative approach to characterizing the fluctuating diffusivity, the relative standard deviation (RSD) of the time-averaged MSD is utilized and it is shown that the RSD exhibits slow relaxation as a signature of the long-time correlation in the fluctuating diffusivity. Furthermore, it is shown that the RSD is related to a non-Gaussian parameter of the propagator. To obtain these theoretical results, we develop a two-state renewal theory as an analytical tool. PMID:27575079

  12. Models explaining motor vehicle death rates in the United States.

    PubMed

    Zlatoper, T J

    1989-04-01

    This paper is a selective survey of models explaining motor vehicle death rates in the United States. First, it reviews Peltzman's 1975 study of the effect of automobile safety regulation and critiques of the study. Then it summarizes several subsequent statistical studies of highway fatalities. The surveyed studies are typically regression analyses of the impact of various factors on motor vehicle deaths. They are categorized in this paper according to which of three types of data they utilized: time-series; cross-sectional; or pooled time-series, cross-sectional. This paper notes what can be inferred collectively from the surveyed studies regarding the impacts of various factors on highway fatalities. It also discusses certain shortcomings of the studies in general along with possible remedies, and makes recommendations regarding future research. Tabular summaries of the statistical studies surveyed in this paper are included in the Appendix. PMID:2785390

  13. Steady States in SIRS Epidemical Model of Mobile Individuals

    NASA Astrophysics Data System (ADS)

    Zhang, Duan-Ming; He, Min-Hua; Yu, Xiao-Ling; Pan, Gui-Jun; Sun, Hong-Zhang; Su, Xiang-Ying; Sun, Fan; Yin, Yan-Ping; Li, Rui; Liu, Dan

    2006-01-01

    We consider an epidemical model within socially interacting mobile individuals to study the behaviors of steady states of epidemic propagation in 2D networks. Using mean-field approximation and large scale simulations, we recover the usual epidemic behavior with critical thresholds δc and pc below which infectious disease dies out. For the population density δ far above δc, it is found that there is linear relationship between contact rate λ and the population density δ in the main. At the same time, the result obtained from mean-field approximation is compared with our numerical result, and it is found that these two results are similar by and large but not completely the same.

  14. Thermodynamics of bread baking: A two-state model

    NASA Astrophysics Data System (ADS)

    Zürcher, Ulrich

    2014-03-01

    Bread baking can be viewed as a complex physico-chemical process. It is governed by transport of heat and is accompanied by changes such as gelation of starch, the expansion of air cells within dough, and others. We focus on the thermodynamics of baking and investigate the heat flow through dough and find that the evaporation of excess water in dough is the rate-limiting step. We consider a simplified one-dimensional model of bread, treating the excess water content as a two-state variable that is zero for baked bread and a fixed constant for unbaked dough. We arrive at a system of coupled, nonlinear ordinary differential equations, which are solved using a standard Runge-Kutta integration method. The calculated baking times are consistent with common baking experience.

  15. Approximate flash calculations for equation-of-state compositional models--

    SciTech Connect

    Nghiem, L.X.; Li, Y.K. )

    1990-02-01

    An approximate flash-calculation (AFC) method with an equation of state (EOS) is presented. The equations for AFC are obtained by linearizing the thermodynamic equilibrium equations at an equilibrium condition called the reference condition. The AFC equations are much simpler than the actual equations for flash calculations and yet give almost the same results. A procedure for generating new reference conditions to keep the AFC results close to the true flash-calculation (TFC) results is described. AFC is compared with TFC in the calculation of standard laboratory tests and in the simulation of gas-injection processes with a compositional model. Excellent results are obtained with AFC in less than half the original execution time.

  16. An Inter-Industry Comparison of VET in Australian SMEs: Inter-Industry Comparison

    ERIC Educational Resources Information Center

    Jones, Janice

    2006-01-01

    Purpose: The purpose of this paper is to compare and contrast the extent and nature of Vocational Education and Training (VET) vis-a-vis other forms of training in three size categories of small-to-medium-sized enterprises (SMEs) from two industry sectors. Design/methodology/approach: The longitudinal panel data employed in this paper are drawn…

  17. Entanglement and Majorana edge states in the Kitaev model

    NASA Astrophysics Data System (ADS)

    Mandal, Saptarshi; Maiti, Moitri; Varma, Vipin Kerala

    2016-07-01

    We investigate the von Neumann entanglement entropy and Schmidt gap in the vortex-free ground state of the Kitaev model on the honeycomb lattice for square/rectangular and cylindrical subsystems. We find that, for both the subsystems, the free-fermionic contribution to the entanglement entropy SE exhibits signatures of the phase transitions between the gapless and gapped phases. However, within the gapless phase, we find that SE does not show an expected monotonic behavior as a function of the coupling Jz between the suitably defined one-dimensional chains for either geometry; moreover, the system generically reaches a point of minimum entanglement within the gapless phase before the entanglement saturates or increases again until the gapped phase is reached. This may be attributed to the onset of gapless modes in the bulk spectrum and the competition between the correlation functions along various bonds. In the gapped phase, on the other hand, SE always monotonically varies with Jz independent of the subregion size or shape. Finally, further confirming the Li-Haldane conjecture, we find that the Schmidt gap Δ defined from the entanglement spectrum also signals the topological transitions but only if there are corresponding zero-energy Majorana edge states that simultaneously appear or disappear across the transitions. We analytically corroborate some of our results on entanglement entropy, the Schmidt gap, and the bulk-edge correspondence using perturbation theory.

  18. Interactions of multiquark states in the chromodielectric model

    SciTech Connect

    Martens, Gunnar; Greiner, Carsten; Leupold, Stefan; Mosel, Ulrich

    2006-05-01

    We investigate 4-quark (qqqq) systems as well as multiquark states with a large number of quarks and antiquarks using the chromodielectric model. In the former type of systems the flux distribution and the corresponding energy of such systems for planar and nonplanar geometries are studied. From the comparison to the case of two independent qq-strings we deduce the interaction potential between two strings. We find an attraction between strings and a characteristic string flip if there are two degenerate string combinations between the four particles. The interaction shows no strong Van-der-Waals forces and the long range behavior of the potential is well described by a Yukawa potential, which might be confirmed in future lattice calculations. The multiquark states develop an inhomogeneous porous structure even for particle densities large compared to nuclear matter constituent quark densities. We present first results of the dependence of the system on the particle density pointing towards a percolation type of transition from a hadronic matter phase to a quark matter phase. The critical energy density is found at {epsilon}{sub c}=1.2 GeV/fm{sup 3}.

  19. Modeling thermophoretic effects in solid-state nanopores

    PubMed Central

    Belkin, Maxim; Chao, Shu-Han; Giannetti, Gino; Aksimentiev, Aleksei

    2014-01-01

    Local modulation of temperature has emerged as a new mechanism for regulation of molecular transport through nanopores. Predicting the effect of such modulations on nanopore transport requires simulation protocols capable of reproducing non-uniform temperature gradients observed in experiment. Conventional molecular dynamics (MD) method typically employs a single thermostat for maintaining a uniform distribution of temperature in the entire simulation domain, and, therefore, can not model local temperature variations. In this article, we describe a set of simulation protocols that enable modeling of nanopore systems featuring non-uniform distributions of temperature. First, we describe a method to impose a temperature gradient in all-atom MD simulations based on a boundary-driven non-equilibrium MD protocol. Then, we use this method to study the effect of temperature gradient on the distribution of ions in bulk solution (the thermophoretic effect). We show that DNA nucleotides exhibit differential response to the same temperature gradient. Next, we describe a method to directly compute the effective force of a thermal gradient on a prototypical biomolecule—a fragment of double-stranded DNA. Following that, we demonstrate an all-atom MD protocol for modeling thermophoretic effects in solid-state nanopores. We show that local heating of a nanopore volume can be used to regulate the nanopore ionic current. Finally, we show how continuum calculations can be coupled to a coarse-grained model of DNA to study the effect of local temperature modulation on electrophoretic motion of DNA through plasmonic nanopores. The computational methods described in this article are expected to find applications in rational design of temperature-responsive nanopore systems. PMID:25395899

  20. Review: Regional groundwater flow modeling in heavily irrigated basins of selected states in the western United States

    NASA Astrophysics Data System (ADS)

    Rossman, Nathan R.; Zlotnik, Vitaly A.

    2013-09-01

    Water resources in agriculture-dominated basins of the arid western United States are stressed due to long-term impacts from pumping. A review of 88 regional groundwater-flow modeling applications from seven intensively irrigated western states (Arizona, California, Colorado, Idaho, Kansas, Nebraska and Texas) was conducted to provide hydrogeologists, modelers, water managers, and decision makers insight about past modeling studies that will aid future model development. Groundwater models were classified into three types: resource evaluation models (39 %), which quantify water budgets and act as preliminary models intended to be updated later, or constitute re-calibrations of older models; management/planning models (55 %), used to explore and identify management plans based on the response of the groundwater system to water-development or climate scenarios, sometimes under water-use constraints; and water rights models (7 %), used to make water administration decisions based on model output and to quantify water shortages incurred by water users or climate changes. Results for 27 model characteristics are summarized by state and model type, and important comparisons and contrasts are highlighted. Consideration of modeling uncertainty and the management focus toward sustainability, adaptive management and resilience are discussed, and future modeling recommendations, in light of the reviewed models and other published works, are presented.

  1. Oxygen consumption dynamics in steady-state tumour models.

    PubMed

    Grimes, David Robert; Fletcher, Alexander G; Partridge, Mike

    2014-09-01

    Oxygen levels in cancerous tissue can have a significant effect on treatment response: hypoxic tissue is both more radioresistant and more chemoresistant than well-oxygenated tissue. While recent advances in medical imaging have facilitated real-time observation of macroscopic oxygenation, the underlying physics limits the resolution to the millimetre domain, whereas oxygen tension varies over a micrometre scale. If the distribution of oxygen in the tumour micro-environment can be accurately estimated, then the effect of potential dose escalation to these hypoxic regions could be better modelled, allowing more realistic simulation of biologically adaptive treatments. Reaction-diffusion models are commonly used for modelling oxygen dynamics, with a variety of functional forms assumed for the dependence of oxygen consumption rate (OCR) on cellular status and local oxygen availability. In this work, we examine reaction-diffusion models of oxygen consumption in spherically and cylindrically symmetric geometries. We consider two different descriptions of oxygen consumption: one in which the rate of consumption is constant and one in which it varies with oxygen tension in a hyperbolic manner. In each case, we derive analytic approximations to the steady-state oxygen distribution, which are shown to closely match the numerical solutions of the equations and accurately predict the extent to which oxygen can diffuse. The derived expressions relate the limit to which oxygen can diffuse into a tissue to the OCR of that tissue. We also demonstrate that differences between these functional forms are likely to be negligible within the range of literature estimates of the hyperbolic oxygen constant, suggesting that the constant consumption rate approximation suffices for modelling oxygen dynamics for most values of OCR. These approximations also allow the rapid identification of situations where hyperbolic consumption forms can result in significant differences from constant

  2. Simulating spin-boson models with matrix product states

    NASA Astrophysics Data System (ADS)

    Wall, Michael; Safavi-Naini, Arghavan; Rey, Ana Maria

    2016-05-01

    The global coupling of few-level quantum systems (``spins'') to a discrete set of bosonic modes is a key ingredient for many applications in quantum science, including large-scale entanglement generation, quantum simulation of the dynamics of long-range interacting spin models, and hybrid platforms for force and spin sensing. In many situations, the bosons are integrated out, leading to effective long-range interactions between the spins; however, strong spin-boson coupling invalidates this approach, and spin-boson entanglement degrades the fidelity of quantum simulation of spin models. We present a general numerical method for treating the out-of-equilibrium dynamics of spin-boson systems based on matrix product states. While most efficient for weak coupling or small numbers of boson modes, our method applies for any spatial and operator dependence of the spin-boson coupling. In addition, our approach allows straightforward computation of many quantities of interest, such as the full counting statistics of collective spin measurements and quantum simulation infidelity due to spin-boson entanglement. We apply our method to ongoing trapped ion quantum simulator experiments in analytically intractable regimes. This work is supported by JILA-NSF-PFC-1125844, NSF-PIF- 1211914, ARO, AFOSR, AFOSR-MURI, and the NRC.

  3. Steady state model of electrochemical gas sensors with multiple reactions

    SciTech Connect

    Brailsford, A.D.; Yussouff, M.; Logothetis, E.M.

    1996-12-31

    A general first-principles model of the steady state response of metal oxide gas sensors was developed by the authors and applied to the case of both electrochemical and resistive type oxygen sensors. It can describe many features of the experimentally observed response of commercial electrochemical zirconia sensors exposed to non-equilibrium gas mixtures consisting of O{sub 2} and one or more reducing species (CO, H{sub 2} , etc). However, the calculated sensor emf as a function of R`= 2p{sub O2}/P{sub CO} (or 2p{sub O2}/P{sub H2}) always showed a sharp transition from high to low values at some R` value and had a small value for R` >> 1. These results do not agree with the broad transitions and relatively high emf values for large R`, as observed experimentally at low temperatures. This paper discusses an extension of the model which is able to describe all aspects of the observed response.

  4. Natural State Model of the Nesjavellir Geothermal Field, Iceland

    SciTech Connect

    Bodvarsson, G.S.; Pruess, K.; Stefansson, V.; Steingrimsson, B.; Bjornsson, S.; Gunnarsson, A.; Gunnlaugsson, E.

    1986-01-21

    The Nesjavellir geothermal system in southern Iceland is very complex from both a thermal and hydrologic point of view. There are large pressure and temperature gradients in the wellfield and zones with drastically different pressure potentials. Thus, natural fluid flow is substantial in the system and flow patterns are complex. We have developed a two-dimensional natural state model for the Nesjavellir system that matches reasonably well the observed pressure and temperature distributions. The match with field data has allowed determination of the energy recharge to the system and the permeability distribution. Fluids recharge the system at rate of 0.02 kg/s/m with an enthalpy of 1460 kJ/kg. The permeability in the main reservoir is estimated to be in the range of 1.5 to 2.0 md, which agrees well with injection test results from individual wells. Permeabilities in shallower reservoirs are about an order of magnitude higher. Most of the main reservoir is under twephase conditions, as are shallow aquifers in the southern part of the field. The model results also suggest that the low temperatures in the shallow part of the northern region of the field may be due to the young age of the system; i.e., the system is gradually heating up. If this is the case the estimated age of the system near the wellfield is on the order of a few thousand years.

  5. An application of a queuing model for sea states

    NASA Astrophysics Data System (ADS)

    Loffredo, L.; Monbaliu, J.; Anderson, C.

    2012-04-01

    Unimodal approaches in design practice have shown inconsistencies in terms of directionality and limitations for accurate sea states description. Spectral multimodality needs to be included in the description of the wave climate. It can provide information about the coexistence of different wave systems originating from different meteorological events, such as locally generated wind waves and swell systems from distant storms. A 20 years dataset (1989-2008) for a location on the North Sea (K13, 53.2°N 3.2°E) has been retrieved from the ECMWF ERA- Interim re-analysis data archive, providing a consistent and homogeneous dataset. The work focuses on the joint and conditional probability distributions of wind sea and swell systems. For marine operations and design applications, critical combinations of wave systems may exist. We define a critical sea state on the basis of a set of thresholds, which can be not necessarily extreme, the emphasis is given to the dangerous combination of different wave systems concerning certain operations (i.e. small vessels navigation, dredging). The distribution of non-operability windows is described by a point process model with random and independent events, whose occurrences and lengths can be described only probabilistically. These characteristics allow to treat the emerging patterns as a part of a queuing system. According to this theory, generally adopted for several applications including traffic flows and waiting lines, the input process describes the sequence of requests for a service and the service mechanism the length of time that these requests will occupy the facilities. For weather-driven processes at sea an alternating renewal process appears as a suitable model. It consists of a sequence of critical events (period of inoperability), each of random duration, separated by calms, also of random durations. Inoperability periods and calms are assumed independent. In this model it is not possible more than one critical

  6. Marginal dimensions of the Potts model with invisible states

    NASA Astrophysics Data System (ADS)

    Krasnytska, M.; Sarkanych, P.; Berche, B.; Holovatch, Yu; Kenna, R.

    2016-06-01

    We reconsider the mean-field Potts model with q interacting and r non-interacting (invisible) states. The model was recently introduced to explain discrepancies between theoretical predictions and experimental observations of phase transitions in some systems where the Z q -symmetry is spontaneously broken. We analyse the marginal dimensions of the model, i.e., the value of r at which the order of the phase transition changes. In the q = 2 case, we determine that value to be {r}{{c}}=3.65(5); there is a second-order phase transition there when r\\lt {r}{{c}} and a first-order one at r\\gt {r}{{c}}. We also analyse the region 1≤slant q\\lt 2 and show that the change from second to first order there is manifest through a new mechanism involving two marginal values of r. The q = 1 limit gives bond percolation. Above the lower value r c1, the order parameters exhibit discontinuities at temperature \\tilde{t} below a critical value t c. The larger value r c2 marks the point at which the phase transition at t c changes from second to first order. Thus, for {r}{{c}1}\\lt r\\lt {r}{{c}2}, the transition at t c remains second order while at \\tilde{t} the system undergoes a first order phase transition. As r increases further, \\tilde{t} increases, bringing the discontinuity closer to t c. Finally, when r exceeds r c2 \\tilde{t} coincides with t c and the phase transition becomes first order. This new mechanism indicates how the discontinuity characteristic of first order phase transitions emerges.

  7. Excited-state quantum phase transitions in the interacting boson model: Spectral characteristics of 0+ states and effective order parameter

    NASA Astrophysics Data System (ADS)

    Zhang, Yu; Zuo, Yan; Pan, Feng; Draayer, J. P.

    2016-04-01

    The spectral characteristics of the Lπ=0+ excited states in the interacting boson model are systematically investigated. It is found that various types of excited-state quantum phase transitions may widely occur in the model as functions of the excitation energy, which indicates that the phase diagram of the interacting boson model can be dynamically extended along the direction of the excitation energy. It has also been justified that the d -boson occupation probability ρ (E ) is qualified to be taken as the effective order parameter to identify these excited-state quantum phase transitions. In addition, the underlying relation between the excite-state quantum phase transition and the chaotic dynamics is also stated.

  8. A microphysical model explains rate-and-state friction

    NASA Astrophysics Data System (ADS)

    Chen, Jianye; Spiers, Christopher J.

    2015-04-01

    The rate-and-state friction (RSF) laws were originally developed as a phenomenological description of the frictional behavior observed in lab experiments. In previous studies, the empirical RSF laws have been extensively and quite successfully applied to fault mechanisms. However, these laws can not readily be envisioned in terms of the underlying physics. There are several critical discrepancies between seismological constraints on RSF behavior associated with earthquakes and lab-derived RSF parameters, in particular regarding the static stress drop and characteristic slip distance associated with seismic events. Moreover, lab friction studies can address only limited fault topographies, displacements, experimental durations and P-T conditions, which means that scale issues, and especially processes like dilatation and fluid-rock interaction, cannot be fully taken into account. Without a physical basis accounting for such effects, extrapolation of lab-derived RSF data to nature involves significant, often unknown uncertainties. In order to more reliably apply experimental results to natural fault zones, and notably to extrapolate lab data beyond laboratory pressure, temperature and velocity conditions, an understanding of the microphysical mechanisms governing fault frictional behavior is required. Here, following some pioneering efforts (e.g. Niemeijer and Spiers, 2007; Den Hartog and Spiers, 2014), a mechanism-based microphysical model is developed for describing the frictional behavior of carbonate fault gouge, assuming that the frictional behavior seen in lab experiments is controlled by competing processes of intergranular slip versus contact creep by pressure solution. The model basically consists of two governing equations derived from energy/entropy balance considerations and the kinematic relations that apply to a granular fault gouge undergoing shear and dilation/compaction. These two equations can be written as ˙τ/K = Vimp- Lt[λ˙γsbps +(1-

  9. Multi-temperature model derived from state-to-state kinetics for hypersonic entry in Jupiter atmosphere

    SciTech Connect

    Colonna, G.; Pietanza, L. D.; D'Ammando, G.; Capitelli, M.

    2014-12-09

    A state-to-state model of H{sub 2}/He plasmas coupling the master equations for internal distributions of heavy species with the transport equation for the free electrons has been used as a basis for implementing a multi-temperature kinetic model. In the multi-temperature model internal distributions of heavy particles are Boltzmann, the electron energy distribution function is Maxwell, and the rate coefficients of the elementary processes become a function of local temperatures associated to the relevant equilibrium distributions. The state-to-state and multi-temperature models have been compared in the case of a homogenous recombining plasma, reproducing the conditions met during supersonic expansion though converging-diverging nozzles.

  10. Unfolding Physiological State: Mortality Modelling in Intensive Care Units

    PubMed Central

    Ghassemi, Marzyeh; Naumann, Tristan; Doshi-Velez, Finale; Brimmer, Nicole; Joshi, Rohit; Rumshisky, Anna; Szolovits, Peter

    2014-01-01

    Accurate knowledge of a patient’s disease state and trajectory is critical in a clinical setting. Modern electronic healthcare records contain an increasingly large amount of data, and the ability to automatically identify the factors that influence patient outcomes stand to greatly improve the efficiency and quality of care. We examined the use of latent variable models (viz. Latent Dirichlet Allocation) to decompose free-text hospital notes into meaningful features, and the predictive power of these features for patient mortality. We considered three prediction regimes: (1) baseline prediction, (2) dynamic (time-varying) outcome prediction, and (3) retrospective outcome prediction. In each, our prediction task differs from the familiar time-varying situation whereby data accumulates; since fewer patients have long ICU stays, as we move forward in time fewer patients are available and the prediction task becomes increasingly difficult. We found that latent topic-derived features were effective in determining patient mortality under three timelines: inhospital, 30 day post-discharge, and 1 year post-discharge mortality. Our results demonstrated that the latent topic features important in predicting hospital mortality are very different from those that are important in post-discharge mortality. In general, latent topic features were more predictive than structured features, and a combination of the two performed best. The time-varying models that combined latent topic features and baseline features had AUCs that reached 0.85, 0.80, and 0.77 for in-hospital, 30 day post-discharge and 1 year post-discharge mortality respectively. Our results agreed with other work suggesting that the first 24 hours of patient information are often the most predictive of hospital mortality. Retrospective models that used a combination of latent topic features and structured features achieved AUCs of 0.96, 0.82, and 0.81 for in-hospital, 30 day, and 1-year mortality prediction. Our

  11. Estimation of State Transition Probabilities: A Neural Network Model

    NASA Astrophysics Data System (ADS)

    Saito, Hiroshi; Takiyama, Ken; Okada, Masato

    2015-12-01

    Humans and animals can predict future states on the basis of acquired knowledge. This prediction of the state transition is important for choosing the best action, and the prediction is only possible if the state transition probability has already been learned. However, how our brains learn the state transition probability is unknown. Here, we propose a simple algorithm for estimating the state transition probability by utilizing the state prediction error. We analytically and numerically confirmed that our algorithm is able to learn the probability completely with an appropriate learning rate. Furthermore, our learning rule reproduced experimentally reported psychometric functions and neural activities in the lateral intraparietal area in a decision-making task. Thus, our algorithm might describe the manner in which our brains learn state transition probabilities and predict future states.

  12. A steady-state model of the lunar ejecta cloud

    NASA Astrophysics Data System (ADS)

    Christou, Apostolos

    2014-05-01

    Every airless body in the solar system is surrounded by a cloud of ejecta produced by the impact of interplanetary meteoroids on its surface [1]. Such ``dust exospheres'' have been observed around the Galilean satellites of Jupiter [2,3]. The prospect of long-term robotic and human operations on the Moon by the US and other countries has rekindled interest on the subject [4]. This interest has culminated with the - currently ongoing - investigation of the Moon's dust exosphere by the LADEE spacecraft [5]. Here a model is presented of a ballistic, collisionless, steady state population of ejecta launched vertically at randomly distributed times and velocities and moving under constant gravity. Assuming a uniform distribution of launch times I derive closed form solutions for the probability density functions (pdfs) of the height distribution of particles and the distribution of their speeds in a rest frame both at the surface and at altitude. The treatment is then extended to particle motion with respect to a moving platform such as an orbiting spacecraft. These expressions are compared with numerical simulations under lunar surface gravity where the underlying ejection speed distribution is (a) uniform (b) a power law. I discuss the predictions of the model, its limitations, and how it can be validated against near-surface and orbital measurements.[1] Gault, D. Shoemaker, E.M., Moore, H.J., 1963, NASA TN-D 1767. [2] Kruger, H., Krivov, A.V., Hamilton, D. P., Grun, E., 1999, Nature, 399, 558. [3] Kruger, H., Krivov, A.V., Sremcevic, M., Grun, E., 2003, Icarus, 164, 170. [4] Grun, E., Horanyi, M., Sternovsky, Z., 2011, Planetary and Space Science, 59, 1672. [5] Elphic, R.C., Hine, B., Delory, G.T., Salute, J.S., Noble, S., Colaprete, A., Horanyi, M., Mahaffy, P., and the LADEE Science Team, 2014, LPSC XLV, LPI Contr. 1777, 2677.

  13. Modeling lake trophic state: a random forest approach

    EPA Science Inventory

    Productivity of lentic ecosystems has been well studied and it is widely accepted that as nutrient inputs increase, productivity increases and lakes transition from low trophic state (e.g. oligotrophic) to higher trophic states (e.g. eutrophic). These broad trophic state classi...

  14. New York State Adult Functional Literacy Models. Final Report.

    ERIC Educational Resources Information Center

    Heller, Barbara R.

    This report discusses a nationwide study of Adult Performance Level (APL) which involved sixteen projects in seven states and was conducted to (1) examine the University of Texas at Austin's APL study and describe the results and recommendations in terms of the adult needs in New York State; (2) examine several New York State Adult Basic Education…

  15. Freed by interaction kinetic states in the Harper model

    NASA Astrophysics Data System (ADS)

    Frahm, Klaus M.; Shepelyansky, Dima L.

    2015-12-01

    We study the problem of two interacting particles in a one-dimensional quasiperiodic lattice of the Harper model. We show that a short or long range interaction between particles leads to emergence of delocalized pairs in the non-interacting localized phase. The properties of these freed by interaction kinetic states (FIKS) are analyzed numerically including the advanced Arnoldi method. We find that the number of sites populated by FIKS pairs grows algebraically with the system size with the maximal exponent b = 1, up to a largest lattice size N = 10 946 reached in our numerical simulations, thus corresponding to a complete delocalization of pairs. For delocalized FIKS pairs the spectral properties of such quasiperiodic operators represent a deep mathematical problem. We argue that FIKS pairs can be detected in the framework of recent cold atom experiments [M. Schreiber et al., Science 349, 842 (2015)] by a simple setup modification. We also discuss possible implications of FIKS pairs for electron transport in the regime of charge-density wave and high T c superconductivity.

  16. Modeling asymmetric cavity collapse with plasma equations of state

    NASA Astrophysics Data System (ADS)

    Tully, Brett; Hawker, Nicholas; Ventikos, Yiannis

    2016-05-01

    We explore the effect that equation of state (EOS) thermodynamics has on shock-driven cavity-collapse processes. We account for full, multidimensional, unsteady hydrodynamics and incorporate a range of relevant EOSs (polytropic, QEOS-type, and SESAME). In doing so, we show that simplified analytic EOSs, like ideal gas, capture certain critical parameters of the collapse such as velocity of the main transverse jet and pressure at jet strike, while also providing a good representation of overall trends. However, more sophisticated EOSs yield different and more relevant estimates of temperature and density, especially for higher incident shock strengths. We model incident shocks ranging from 0.1 to 1000 GPa, the latter being of interest in investigating the warm dense matter regime for which experimental and theoretical EOS data are difficult to obtain. At certain shock strengths, there is a factor of two difference in predicted density between QEOS-type and SESAME EOS, indicating cavity collapse as an experimental method for exploring EOS in this range.

  17. Characterizing the Relationship between Steady State and Response Using Analytical Expressions for the Steady States of Mass Action Models

    PubMed Central

    Loriaux, Paul Michael; Tesler, Glenn; Hoffmann, Alexander

    2013-01-01

    The steady states of cells affect their response to perturbation. Indeed, diagnostic markers for predicting the response to therapeutic perturbation are often based on steady state measurements. In spite of this, no method exists to systematically characterize the relationship between steady state and response. Mathematical models are established tools for studying cellular responses, but characterizing their relationship to the steady state requires that it have a parametric, or analytical, expression. For some models, this expression can be derived by the King-Altman method. However, King-Altman requires that no substrate act as an enzyme, and is therefore not applicable to most models of signal transduction. For this reason we developed py-substitution, a simple but general method for deriving analytical expressions for the steady states of mass action models. Where the King-Altman method is applicable, we show that py-substitution yields an equivalent expression, and at comparable efficiency. We use py-substitution to study the relationship between steady state and sensitivity to the anti-cancer drug candidate, dulanermin (recombinant human TRAIL). First, we use py-substitution to derive an analytical expression for the steady state of a published model of TRAIL-induced apoptosis. Next, we show that the amount of TRAIL required for cell death is sensitive to the steady state concentrations of procaspase 8 and its negative regulator, Bar, but not the other procaspase molecules. This suggests that activation of caspase 8 is a critical point in the death decision process. Finally, we show that changes in the threshold at which TRAIL results in cell death is not always equivalent to changes in the time of death, as is commonly assumed. Our work demonstrates that an analytical expression is a powerful tool for identifying steady state determinants of the cellular response to perturbation. All code is available at http://signalingsystems.ucsd.edu/models-and-code/ or

  18. Practical Application of Model-based Programming and State-based Architecture to Space Missions

    NASA Technical Reports Server (NTRS)

    Horvath, Gregory; Ingham, Michel; Chung, Seung; Martin, Oliver; Williams, Brian

    2006-01-01

    A viewgraph presentation to develop models from systems engineers that accomplish mission objectives and manage the health of the system is shown. The topics include: 1) Overview; 2) Motivation; 3) Objective/Vision; 4) Approach; 5) Background: The Mission Data System; 6) Background: State-based Control Architecture System; 7) Background: State Analysis; 8) Overview of State Analysis; 9) Background: MDS Software Frameworks; 10) Background: Model-based Programming; 10) Background: Titan Model-based Executive; 11) Model-based Execution Architecture; 12) Compatibility Analysis of MDS and Titan Architectures; 13) Integrating Model-based Programming and Execution into the Architecture; 14) State Analysis and Modeling; 15) IMU Subsystem State Effects Diagram; 16) Titan Subsystem Model: IMU Health; 17) Integrating Model-based Programming and Execution into the Software IMU; 18) Testing Program; 19) Computationally Tractable State Estimation & Fault Diagnosis; 20) Diagnostic Algorithm Performance; 21) Integration and Test Issues; 22) Demonstrated Benefits; and 23) Next Steps

  19. Bistability and State Transition of a Delay Differential Equation Model of Neutrophil Dynamics

    NASA Astrophysics Data System (ADS)

    Ma, Suqi; Zhu, Kaiyi; Lei, Jinzhi

    This paper studies the existence of bistable states and control strategies to induce state transitions of a delay differential equation model of neutrophil dynamics. We seek the conditions that a stable steady state and an oscillatory state coexist in the neutrophil dynamical system. Physiologically, stable steady state represents the healthy state, while oscillatory state is usually associated with diseases such as cyclical neutropenia. We study the control strategies to induce the transitions from the disease state to the healthy state by introducing temporal perturbations to system parameters. This study is valuable in designing clinical protocols for the treatment of cyclical neutropenia.

  20. Grey-Markov model with state membership degree and its application

    NASA Astrophysics Data System (ADS)

    Ye, Jing; Li, Bingjun; Liu, Fang

    2013-10-01

    In the Grey-Markov forecasting, the extent of a given state that a research object belongs to is expressed as state membership degree. The state membership degree can help compensate for the inaccurate states division and improve the predicted results. Based on the Grey-Markov forecasting analysis, this paper uses the central triangle albino function to calculate the state membership degrees of research objects and determine the state transition probability. Thereby, the new model achieves the improvement of conventional Grey-Markov model. Taking the grain production of Henan Province as an example, the validity and applicability of the improved model are verified.

  1. Quadractic Model of Thermodynamic States in SDF Explosions

    SciTech Connect

    Kuhl, A L; Khasainov, B

    2007-05-04

    We study the thermodynamic states encountered during Shock-Dispersed-Fuel (SDF) explosions. Such explosions contain up to six components: three fuels (PETN, TNT and Aluminum) and their products corresponding to stoichiometric combustion with air. We establish the loci in thermodynamic state space that correctly describes the behavior of the components. Results are fit with quadratic functions that serve as fast equations of state suitable for 3D numerical simulations of SDF explosions.

  2. A model of cerebellar computations for dynamical state estimation

    NASA Technical Reports Server (NTRS)

    Paulin, M. G.; Hoffman, L. F.; Assad, C.

    2001-01-01

    The cerebellum is a neural structure that is essential for agility in vertebrate movements. Its contribution to motor control appears to be due to a fundamental role in dynamical state estimation, which also underlies its role in various non-motor tasks. Single spikes in vestibular sensory neurons carry information about head state. We show how computations for optimal dynamical state estimation may be accomplished when signals are encoded in spikes. This provides a novel way to design dynamical state estimators, and a novel way to interpret the structure and function of the cerebellum.

  3. Modelling valuations for health states: the effect of duration.

    PubMed

    Dolan, P

    1996-12-01

    An important issue which has been raised in the measurement of health status is the effect that the time spent in a health state may have on the way that state is perceived. Recently a set of valuations for health states defined in terms of the EuroQol Descriptive System was generated from a study of over 3000 members of the UK general public. The valuations were elicited using the visual analogue scale (VAS) and time trade-off (TTO) methods and were for states that lasted for 10 years. Using VAS valuations for states lasting 1 month, 1 year and 10 years derived from a subset of respondents to the general population study, this paper presents valuation "tariffs" for all EuroQol states based on the different durations. The results support those of previous studies which suggest that poor states of health become more intolerable the longer they last. Such findings suggest that the results of studies in which the value given to a health state is assumed to be linearly related to the time spent in that health state should be treated with caution and subjected to sensitivity analysis over an appropriate range of values. PMID:10162421

  4. State-space models' dirty little secrets: even simple linear Gaussian models can have estimation problems.

    PubMed

    Auger-Méthé, Marie; Field, Chris; Albertsen, Christoffer M; Derocher, Andrew E; Lewis, Mark A; Jonsen, Ian D; Mills Flemming, Joanna

    2016-01-01

    State-space models (SSMs) are increasingly used in ecology to model time-series such as animal movement paths and population dynamics. This type of hierarchical model is often structured to account for two levels of variability: biological stochasticity and measurement error. SSMs are flexible. They can model linear and nonlinear processes using a variety of statistical distributions. Recent ecological SSMs are often complex, with a large number of parameters to estimate. Through a simulation study, we show that even simple linear Gaussian SSMs can suffer from parameter- and state-estimation problems. We demonstrate that these problems occur primarily when measurement error is larger than biological stochasticity, the condition that often drives ecologists to use SSMs. Using an animal movement example, we show how these estimation problems can affect ecological inference. Biased parameter estimates of a SSM describing the movement of polar bears (Ursus maritimus) result in overestimating their energy expenditure. We suggest potential solutions, but show that it often remains difficult to estimate parameters. While SSMs are powerful tools, they can give misleading results and we urge ecologists to assess whether the parameters can be estimated accurately before drawing ecological conclusions from their results. PMID:27220686

  5. Proton Therapy Expansion Under Current United States Reimbursement Models

    SciTech Connect

    Kerstiens, John; Johnstone, Peter A.S.

    2014-06-01

    Purpose: To determine whether all the existing and planned proton beam therapy (PBT) centers in the United States can survive on a local patient mix that is dictated by insurers, not by number of patients. Methods and Materials: We determined current and projected cancer rates for 10 major US metropolitan areas. Using published utilization rates, we calculated patient percentages who are candidates for PBT. Then, on the basis of current published insurer coverage policies, we applied our experience of what would be covered to determine the net number of patients for whom reimbursement is expected. Having determined the net number of covered patients, we applied our average beam delivery times to determine the total number of minutes needed to treat that patient over the course of their treatment. We then calculated our expected annual patient capacity per treatment room to determine the appropriate number of treatment rooms for the area. Results: The population of patients who will be both PBT candidates and will have treatments reimbursed by insurance is significantly smaller than the population who should receive PBT. Coverage decisions made by insurers reduce the number of PBT rooms that are economically viable. Conclusions: The expansion of PBT centers in the US is not sustainable under the current reimbursement model. Viability of new centers will be limited to those operating in larger regional metropolitan areas, and few metropolitan areas in the US can support multiple centers. In general, 1-room centers require captive (non–PBT-served) populations of approximately 1,000,000 lives to be economically viable, and a large center will require a population of >4,000,000 lives. In areas with smaller populations or where or a PBT center already exists, new centers require subsidy.

  6. Sensitivity of global model prediction to initial state uncertainty

    NASA Astrophysics Data System (ADS)

    Miguez-Macho, Gonzalo

    The sensitivity of global and North American forecasts to uncertainties in the initial conditions is studied. The Utah Global Model is initialized with reanalysis data sets obtained from the National Centers for Environmental Prediction (NCEP) and the European Centre for Medium- Range Weather Forecasts (ECMWF). The differences between these analyses provide an estimate of initial uncertainty. The influence of certain scales of the initial uncertainty is tested in experiments with initial data change from NCEP to ECMWF reanalysis in a selected spectral band. Experiments are also done to determine the benefits of targeting local regions for forecast errors over North America. In these tests, NCEP initial data are replaced by ECMWF data in the considered region. The accuracy of predictions with initial data from either reanalysis only differs over the mid-latitudes of the Southern Hemisphere, where ECMWF initialized forecasts have somewhat greater skill. Results from the spectral experiments indicate that most of this benefit is explained by initial differences of the longwave components (wavenumbers 0-15). Approximately 67% of the 120-h global forecast difference produced by changing initial data from ECMWF to NCEP reanalyses is due to initial changes only in wavenumbers 0-15, and more than 85% of this difference is produced by initial changes in wavenumbers 0-20. The results suggest that large-scale errors of the initial state may play a more prominent role than suggested in some singular vector analyses, and favor global observational coverage to resolve the long waves. Results from the regional targeting experiments indicate that for forecast errors over North America, a systematic benefit comes only when the ``targeted'' region includes most of the north Pacific, pointing again at large scale errors as being prominent, even for midrange predictions over a local area.

  7. Conceptual geologic model and native state model of the Roosevelt Hot Springs hydrothermal system

    SciTech Connect

    Faulder, D.D.

    1991-01-01

    A conceptual geologic model of the Roosevelt Hot Springs hydrothermal system was developed by a review of the available literature. The hydrothermal system consists of a meteoric recharge area in the Mineral Mountains, fluid circulation paths to depth, a heat source, and an outflow plume. A conceptual model based on the available data can be simulated in the native state using parameters that fall within observed ranges. The model temperatures, recharge rates, and fluid travel times are sensitive to the permeability in the Mineral Mountains. The simulation results suggests the presence of a magma chamber at depth as the likely heat source. A two-dimensional study of the hydrothermal system can be used to establish boundary conditions for further study of the geothermal reservoir.

  8. Establishing a State Outdoor Education Association: The New York Model.

    ERIC Educational Resources Information Center

    Benjamin, Thomas P.

    Because the New York Outdoor Education Association (NYSOEA) has made significant contributions to the establishment and expansion of outdoor education programs in the state and throughout the world, this guide is directed toward those who want to strengthen their own state or regional association or to create one. The paper provides an analysis of…

  9. Dreaming: The functional state-shift hypothesis. A neuropsychophysiological model.

    PubMed

    Koukkou, M; Lehmann, D

    1983-03-01

    The different brain functional states during sleep and wakefulness are associated with differences in processing strategies, memory stores, and EEG patterns. Shifts of functional state occur spontaneously or as orienting reactions to processed information, and cause the formal characteristics of dreams. Forgetting of dreams is a function of the magnitude of the difference between states during storage and recall. Based on EEG similarities between sleep stages and developmental stages, brain states during sleep in adults are proposed to correspond functionally with waking states during childhood. Repeated functional regressions occur during sleep, with access to earlier memory material and cognitive strategies unavailable during waking life, so that earlier experiences can be used for current problems. This dream work constitutes the biological significance of sleep. PMID:6860875

  10. A Cross-Institutional Factor Structure Replication of the Michigan State University Sirs Faculty Evaluation Model

    ERIC Educational Resources Information Center

    Arreola, Raoul A.

    1973-01-01

    Determines that the factor structure of the instructional model measured by the Michigan State University Student Instructional Rating System (SIRS) form could be replicated by an adapted version of the SIRS instrument at Florida State University. (Author)

  11. Oscillator-like coherent states for the Jaynes-Cummings Model

    NASA Technical Reports Server (NTRS)

    Berubelauziere, Y.; Hussin, V.; Nieto, Michael M.

    1995-01-01

    A new way of diagonalizing the Jaynes-Cummings Hamiltonian is proposed, which allows the definition of annihilation operators and coherent states for this model. Mean values and dispersions over these states are computed and interpreted.

  12. Intercomparison of state-of-the-art models for wind energy resources with mesoscale models:

    NASA Astrophysics Data System (ADS)

    Olsen, Bjarke Tobias; Hahmann, Andrea N.; Sempreviva, Anna Maria; Badger, Jake; Joergensen, Hans E.

    2016-04-01

    vertical resolution, model parameterizations, surface roughness length) that could be used to group the various models and interpret the results of the intercomparison. 3. Main body abstract Twenty separate entries were received by the deadline of 31 March 2015. They included simulations done with various versions of the Weather Research and Forecast (WRF) model, but also of six other well-known mesoscale models. The various entries represent an excellent sample of the various models used in by the wind energy industry today. The analysis of the submitted time series included comparison to observations, summarized with well-known measures such as biases, RMSE, correlations, and of sector-wise statistics, e.g. frequency and Weibull A and k. The comparison also includes the observed and modeled temporal spectra. The various statistics were grouped as a function of the various models, their spatial resolution, forcing data, and the various integration methods. Many statistics have been computed and will be presented in addition to those shown in the Helsinki presentation. 4. Conclusions The analysis of the time series from twenty entries has shown to be an invaluable source of information about state of the art in wind modeling with mesoscale models. Biases between the simulated and observed wind speeds at hub heights (80-100 m AGL) from the various models are around ±1.0 m/s and fairly independent of the site and do not seem to be directly related to the model horizontal resolution used in the modeling. As probably expected, the wind speeds from the simulations using the various version of the WRF model cluster close to each other, especially in their description of the wind profile.

  13. State-space reduction and equivalence class sampling for a molecular self-assembly model.

    PubMed

    Packwood, Daniel M; Han, Patrick; Hitosugi, Taro

    2016-07-01

    Direct simulation of a model with a large state space will generate enormous volumes of data, much of which is not relevant to the questions under study. In this paper, we consider a molecular self-assembly model as a typical example of a large state-space model, and present a method for selectively retrieving 'target information' from this model. This method partitions the state space into equivalence classes, as identified by an appropriate equivalence relation. The set of equivalence classes H, which serves as a reduced state space, contains none of the superfluous information of the original model. After construction and characterization of a Markov chain with state space H, the target information is efficiently retrieved via Markov chain Monte Carlo sampling. This approach represents a new breed of simulation techniques which are highly optimized for studying molecular self-assembly and, moreover, serves as a valuable guideline for analysis of other large state-space models. PMID:27493765

  14. State-space reduction and equivalence class sampling for a molecular self-assembly model

    PubMed Central

    Han, Patrick; Hitosugi, Taro

    2016-01-01

    Direct simulation of a model with a large state space will generate enormous volumes of data, much of which is not relevant to the questions under study. In this paper, we consider a molecular self-assembly model as a typical example of a large state-space model, and present a method for selectively retrieving ‘target information’ from this model. This method partitions the state space into equivalence classes, as identified by an appropriate equivalence relation. The set of equivalence classes H, which serves as a reduced state space, contains none of the superfluous information of the original model. After construction and characterization of a Markov chain with state space H, the target information is efficiently retrieved via Markov chain Monte Carlo sampling. This approach represents a new breed of simulation techniques which are highly optimized for studying molecular self-assembly and, moreover, serves as a valuable guideline for analysis of other large state-space models. PMID:27493765

  15. Analytical results for state-to-state transition probabilities in the multistate Landau-Zener model by nonstationary perturbation theory

    SciTech Connect

    Volkov, M. V.; Ostrovsky, V. N.

    2007-02-15

    Multistate generalizations of Landau-Zener model are studied by summing entire series of perturbation theory. A technique for analysis of the series is developed. Analytical expressions for probabilities of survival at the diabatic potential curves with extreme slope are proved. Degenerate situations are considered when there are several potential curves with extreme slope. Expressions for some state-to-state transition probabilities are derived in degenerate cases.

  16. Modeling Steady-State Groundwater Flow Using Microcomputer Spreadsheets.

    ERIC Educational Resources Information Center

    Ousey, John Russell, Jr.

    1986-01-01

    Describes how microcomputer spreadsheets are easily adapted for use in groundwater modeling. Presents spreadsheet set-ups and the results of five groundwater models. Suggests that this approach can provide a basis for demonstrations, laboratory exercises, and student projects. (ML)

  17. State-to-State Internal Energy Relaxation Following the Quantum-Kinetic Model in DSMC

    NASA Technical Reports Server (NTRS)

    Liechty, Derek S.

    2014-01-01

    A new model for chemical reactions, the Quantum-Kinetic (Q-K) model of Bird, has recently been introduced that does not depend on macroscopic rate equations or values of local flow field data. Subsequently, the Q-K model has been extended to include reactions involving charged species and electronic energy level transitions. Although this is a phenomenological model, it has been shown to accurately reproduce both equilibrium and non-equilibrium reaction rates. The usefulness of this model becomes clear as local flow conditions either exceed the conditions used to build previous models or when they depart from an equilibrium distribution. Presently, the applicability of the relaxation technique is investigated for the vibrational internal energy mode. The Forced Harmonic Oscillator (FHO) theory for vibrational energy level transitions is combined with the Q-K energy level transition model to accurately reproduce energy level transitions at a reduced computational cost compared to the older FHO models.

  18. Inference for finite-sample trajectories in dynamic multi-state site-occupancy models using hidden Markov model smoothing

    USGS Publications Warehouse

    Fiske, Ian J.; Royle, J. Andrew; Gross, Kevin

    2014-01-01

    Ecologists and wildlife biologists increasingly use latent variable models to study patterns of species occurrence when detection is imperfect. These models have recently been generalized to accommodate both a more expansive description of state than simple presence or absence, and Markovian dynamics in the latent state over successive sampling seasons. In this paper, we write these multi-season, multi-state models as hidden Markov models to find both maximum likelihood estimates of model parameters and finite-sample estimators of the trajectory of the latent state over time. These estimators are especially useful for characterizing population trends in species of conservation concern. We also develop parametric bootstrap procedures that allow formal inference about latent trend. We examine model behavior through simulation, and we apply the model to data from the North American Amphibian Monitoring Program.

  19. Photonic states mixing beyond the plasmon hybridization model

    NASA Astrophysics Data System (ADS)

    Suryadharma, Radius N. S.; Iskandar, Alexander A.; Tjia, May-On

    2016-07-01

    A study is performed on a photonic-state mixing-pattern in an insulator-metal-insulator cylindrical silver nanoshell and its rich variations induced by changes in the geometry and dielectric media of the system, representing the combined influences of plasmon coupling strength and cavity effects. This study is performed in terms of the photonic local density of states (LDOS) calculated using the Green tensor method, in order to elucidate those combined effects. The energy profiles of LDOS inside the dielectric core are shown to exhibit consistently growing number of redshifted photonic states due to an enhanced plasmon coupling induced state mixing arising from decreased shell thickness, increased cavity size effect, and larger symmetry breaking effect induced by increased permittivity difference between the core and the background media. Further, an increase in cavity size leads to increased additional peaks that spread out toward the lower energy regime. A systematic analysis of those variations for a silver nanoshell with a fixed inner radius in vacuum background reveals a certain pattern of those growing number of redshifted states with an analytic expression for the corresponding energy downshifts, signifying a photonic state mixing scheme beyond the commonly adopted plasmon hybridization scheme. Finally, a remarkable correlation is demonstrated between the LDOS energy profiles outside the shell and the corresponding scattering efficiencies.

  20. Multilevel Factor Analysis and Structural Equation Modeling of Daily Diary Coping Data: Modeling Trait and State Variation

    ERIC Educational Resources Information Center

    Roesch, Scott C.; Aldridge, Arianna A.; Stocking, Stephanie N.; Villodas, Feion; Leung, Queenie; Bartley, Carrie E.; Black, Lisa J.

    2010-01-01

    This study used multilevel modeling of daily diary data to model within-person (state) and between-person (trait) components of coping variables. This application included the introduction of multilevel factor analysis (MFA) and a comparison of the predictive ability of these trait/state factors. Daily diary data were collected on a large (n =…

  1. A modified model of mode approximation for nitrogen plasma based on the state-to-state approach

    NASA Astrophysics Data System (ADS)

    Kadochnikov, I. N.; Loukhovitski, B. I.; Starik, A. M.

    2015-10-01

    This paper addresses the analysis of thermally nonequilibrium processes in nitrogen plasma initiated by fast heating of the gas in a shock wave and by its expansion in a supersonic nozzle flow. A novel model of mode approximation has been developed that treats rate constants of plasma-chemical processes and processes of vibrational-translational, electronic-translational and electronic-electronic exchange obtained via summation of level rate coefficients of elementary reaction channels for given vibrational states, while suggesting the existence of a local Boltzmann distribution over the vibrational levels in each electronic state e=\\text{X} {}1Σ\\text{g}+ , \\text{A} {}3Σ\\text{u}+ , \\text{B} {}3{{\\Pi}g} , {{\\text{a}}'} {}1Σ\\text{u}- , \\text{C} {}3{{\\Pi}\\text{u}} , of the {{\\text{N}}2} molecule. Despite the fact that this level-based mode model is much simpler than the state-to-state model, it makes it possible to reproduce with high accuracy the evolution of nonequilibrium parameters and species concentrations predicted by the accurate state-to-state model in the post-shock-front region. However, in the expanding supersonic flow, this model cannot describe properly the variation of nonequilibrium parameters and species concentrations of electronically excited {{\\text{N}}2} molecules and N atoms. The inaccuracy rises on decreasing the initial temperature of preheated gas in the reservoir. The comprehensive analysis of different factors influencing the prediction ability of the developed level-based mode model is also reported.

  2. Modeling of free electronic state density in hydrogenic plasmas based on nearest neighbor approximation

    SciTech Connect

    Nishikawa, Takeshi

    2014-07-15

    Most conventional atomic models in a plasma do not treat the effect of the plasma on the free-electron state density. Using a nearest neighbor approximation, the state densities in hydrogenic plasmas for both bound and free electrons were evaluated and the effect of the plasma on the atomic model (especially for the state density of the free electron) was studied. The model evaluates the electron-state densities using the potential distribution formed by the superposition of the Coulomb potentials of two ions. The potential from one ion perturbs the electronic state density on the other. Using this new model, one can evaluate the free-state density without making any ad-hoc assumptions. The resulting contours of the average ionization degree, given as a function of the plasma temperature and density, are shifted slightly to lower temperatures because of the effect of the increasing free-state density.

  3. State-space representation of Li-ion battery porous electrode impedance model with balanced model reduction

    NASA Astrophysics Data System (ADS)

    Jun, Myungsoo; Smith, Kandler; Graf, Peter

    2015-01-01

    This paper presents an approximate time-domain solution for physics-based electrochemical lithium-ion cell battery models. The time-domain solution is represented in state-space form and can be easily used for the design of a state estimator or controller. It uses an interconnection-of-system approach to derive a state-space representation of a battery impedance model and provides a reduced order model based via the balanced truncation method. Simulation results are also provided to show the performance of the proposed model in the frequency domain.

  4. A model for electrophoretic transport of charged particles through membrane before steady state

    NASA Astrophysics Data System (ADS)

    de Souza, Tatiana Miranda; Fragoso, Viviane Muniz da Silva; Cruz, Frederico Alan de Oliveira

    2015-12-01

    In this paper, we are presenting a model for electrophoretic motion of a charged particle through the membrane before it reaches the steady state, based on concepts of Physics. Some results from analysis of the model are discussed.

  5. Modeling of Flood Risk for the Continental United States

    NASA Astrophysics Data System (ADS)

    Lohmann, D.; Li, S.; Katz, B.; Goteti, G.; Kaheil, Y. H.; Vojjala, R.

    2011-12-01

    The science of catastrophic risk modeling helps people to understand the physical and financial implications of natural catastrophes (hurricanes, flood, earthquakes, etc.), terrorism, and the risks associated with changes in life expectancy. As such it depends on simulation techniques that integrate multiple disciplines such as meteorology, hydrology, structural engineering, statistics, computer science, financial engineering, actuarial science, and more in virtually every field of technology. In this talk we will explain the techniques and underlying assumptions of building the RMS US flood risk model. We especially will pay attention to correlation (spatial and temporal), simulation and uncertainty in each of the various components in the development process. Recent extreme floods (e.g. US Midwest flood 2008, US Northeast flood, 2010) have increased the concern of flood risk. Consequently, there are growing needs to adequately assess the flood risk. The RMS flood hazard model is mainly comprised of three major components. (1) Stochastic precipitation simulation module based on a Monte-Carlo analogue technique, which is capable of producing correlated rainfall events for the continental US. (2) Rainfall-runoff and routing module. A semi-distributed rainfall-runoff model was developed to properly assess the antecedent conditions, determine the saturation area and runoff. The runoff is further routed downstream along the rivers by a routing model. Combined with the precipitation model, it allows us to correlate the streamflow and hence flooding from different rivers, as well as low and high return-periods across the continental US. (3) Flood inundation module. It transforms the discharge (output from the flow routing) into water level, which is further combined with a two-dimensional off-floodplain inundation model to produce comprehensive flood hazard map. The performance of the model is demonstrated by comparing to the observation and published data. Output from

  6. The State-Conspiracy Model of Political Socialization.

    ERIC Educational Resources Information Center

    Homan, Roger

    1980-01-01

    This essay reviews the political socialization literature and the assumptions underlying the theory that political socialization, formal and informal, is sponsored by the state to reinforce its stability and social order. The author argues that family influence and enlightened self-interest are strong, independent factors in personal political…

  7. A Model Training Program: NJASBO's State Certification Program.

    ERIC Educational Resources Information Center

    Rodabaugh, Karl

    1997-01-01

    In 1991, the New Jersey Association of School Business Officials was selected as a nontraditional provider and asked to develop and implement a new state-approved certification program. The idea was to produce administrators who are adept at strategic planning, financial management and accounting, school law, personnel management, facility…

  8. Models of Distance Education for Developing Island States.

    ERIC Educational Resources Information Center

    Meacham, David; Zubair, Shafeea

    The key to successful establishment of distance education in developing countries seems to be the initial choice of an appropriate model (a model that can be built upon the historical and cultural context, can survive in an environment of limited resources, and will be compatible with the views and ambitions of its political sponsors and clients).…

  9. Finite element cochlear models and their steady state response

    NASA Astrophysics Data System (ADS)

    Kagawa, Y.; Yamabuchi, T.; Watanabe, N.; Mizoguchi, T.

    1987-12-01

    Numerical cochlear models are constructed by means of a finite element approach and their frequency and spatial responses are calculated. The cochlea is modelled as a coupled fluid-membrane system, for which both two- and three-dimensional models are considered. The fluid in the scala canals is assumed to be incompressible and the basilar membrane is assumed to be a locally reactive impedance wall or a lossy elastic membrane. With the three-dimensional models, the effects are examined of the spiral configuration of the cochlea, of the presence of the lamina and the ligament that narrows the coupling area between the two fluid canals (scala vestibuli and scala tympani), and of the extended reaction of the basilar membrane which cannot be included in case of the two-dimensional models. The conclusion is that these effects on the cochlear response and the inherent mechanism governing the cochlear behaviour are found to be rather secondary.

  10. Matching State Goals to a Model of Outcomes and Indicators for Grade 8. Technical Report 16.

    ERIC Educational Resources Information Center

    Seppanen, Patricia; And Others

    A national survey of state-articulated student goals and outcomes led to the analysis of documents from 30 states for correspondence with the outcomes specified for grade 8 in the conceptual model developed by the National Center on Educational Outcomes for Students with Disabilities (NCEO). All of the 30 states' goal documents included statements…

  11. Gamow states and continua in the cluster-orbital shell model approach

    NASA Astrophysics Data System (ADS)

    Masui, H.; Kato, K.; Ikeda, K.

    2008-05-01

    Importance of the unbound states in loosely bound systems by comparing to the stable nuclei is investigated. We use the cluster-orbital shell model (COSM) approach and expand the wave function using the complete set of the single-particle states. The completeness relation is constructed by the Berggren metrics, which includes bound, resonant and anti-bound states, and continua. We precisely investigated such the contributions of the resonant states (Gamow states) and continua in the helium isotopes and compare them those obtained by the Gamow shell model.

  12. Current State of Animal (Mouse) Modeling in Melanoma Research

    PubMed Central

    Kuzu, Omer F.; Nguyen, Felix D.; Noory, Mohammad A.; Sharma, Arati

    2015-01-01

    Despite the considerable progress in understanding the biology of human cancer and technological advancement in drug discovery, treatment failure remains an inevitable outcome for most cancer patients with advanced diseases, including melanoma. Despite FDA-approved BRAF-targeted therapies for advanced stage melanoma showed a great deal of promise, development of rapid resistance limits the success. Hence, the overall success rate of melanoma therapy still remains to be one of the worst compared to other malignancies. Advancement of next-generation sequencing technology allowed better identification of alterations that trigger melanoma development. As development of successful therapies strongly depends on clinically relevant preclinical models, together with the new findings, more advanced melanoma models have been generated. In this article, besides traditional mouse models of melanoma, we will discuss recent ones, such as patient-derived tumor xenografts, topically inducible BRAF mouse model and RCAS/TVA-based model, and their advantages as well as limitations. Although mouse models of melanoma are often criticized as poor predictors of whether an experimental drug would be an effective treatment, development of new and more relevant models could circumvent this problem in the near future. PMID:26483610

  13. Quasi steady-state aerodynamic model development for race vehicle simulations

    NASA Astrophysics Data System (ADS)

    Mohrfeld-Halterman, J. A.; Uddin, M.

    2016-01-01

    Presented in this paper is a procedure to develop a high fidelity quasi steady-state aerodynamic model for use in race car vehicle dynamic simulations. Developed to fit quasi steady-state wind tunnel data, the aerodynamic model is regressed against three independent variables: front ground clearance, rear ride height, and yaw angle. An initial dual range model is presented and then further refined to reduce the model complexity while maintaining a high level of predictive accuracy. The model complexity reduction decreases the required amount of wind tunnel data thereby reducing wind tunnel testing time and cost. The quasi steady-state aerodynamic model for the pitch moment degree of freedom is systematically developed in this paper. This same procedure can be extended to the other five aerodynamic degrees of freedom to develop a complete six degree of freedom quasi steady-state aerodynamic model for any vehicle.

  14. Quasiparticle-phonon model and quadrupole mixed-symmetry states of 96Ru

    NASA Astrophysics Data System (ADS)

    Stoyanov, Ch.; Pietralla, N.

    2016-01-01

    The structure of low-lying quadrupole states of 96Ru was calculated within the Quasiparticle-Phonon Model. It is shown that symmetric and mixed-symmetry properties manifest themselves via the structure of the excited states. The first 2+ state is collective and neutron and proton transition matrix elements Mn and Mp are in-phase, while the neutron and proton transition matrix elements Mn and Mp have opposite signs for the third 2+ state. This property of the third 2+ state leads to a large M1 transition between the first and third 2+ states. It is an unambigous demonstration of the mixed-symmetry nature of the third 2+ state. The structure of the first 1+ state is calculated. The state is a member of the two-phonon multiplet generated by the coupling of the [21+]QRPA and the [22+]QRPA states.

  15. Multi-state models for the analysis of time-to-event data

    PubMed Central

    Meira-Machado, Luís; de Uña-Álvarez, Jacobo; Cadarso-Suárez, Carmen; Andersen, Per K

    2009-01-01

    The experience of a patient in a survival study may be modelled as a process with two states and one possible transition from an “alive” state to a “dead” state. In some studies, however, the “alive” state may be partitioned into two or more intermediate (transient) states, each of which corresponding to a particular stage of the illness. In such studies, multi-state models can be used to model the movement of patients among the various states. In these models issues, of interest include the estimation of progression rates, assessing the effects of individual risk factors, survival rates or prognostic forecasting. In this article, we review modelling approaches for multi-state models, and we focus on the estimation of quantities such as the transition probabilities and survival probabilities. Differences between these approaches are discussed, focussing on possible advantages and disadvantages for each method. We also review the existing software currently available to fit the various models and present new software developed in the form of an R library to analyse such models. Different approaches and software are illustrated using data from the Stanford heart transplant study and data from a study on breast cancer conducted in Galicia, Spain. PMID:18562394

  16. An assessment of state-and-transition models: Perceptions following two decades of development and implementation

    Technology Transfer Automated Retrieval System (TEKTRAN)

    State and transition models (STMs) are being developed for many areas in the United States and represent an important tool for assessing and managing public and private rangelands. Substantial resources have been invested in model development, yet minimal efforts have been made to evaluate the utili...

  17. Development of mathematical models for solid state switching devices

    NASA Technical Reports Server (NTRS)

    Raburn, W. D.; Kim, J. C.

    1980-01-01

    Models are developed for two types of remote power controllers (RPC). The models give the equations for the currents and voltages for all elements of passive loads as a function of time for both turn-on and turn-off. It is shown that the RPC can be considered as a combination of current and voltage sources. Equations are given for these sources which are essentially independent of the load being turned on and off. Experimental results are given for several types of loads and comparisons are made with the results obtained using the models.

  18. Modelling Subaqueous Debris Flows - A comparison of two state-of-the-art integrated models

    NASA Astrophysics Data System (ADS)

    Spinewine, Benoit; Sfouni-Grigoriadou, Mariangela; Ingarfield, Samuel

    2015-04-01

    With the gradual depletion of nearshore resources and technological advances in oil and gas production, developments are now often located beyond the continental shelf in environments susceptible to mass movement events. The risk to subsea infrastructure from these events is often quantified through: i) an assessment of potential unstable slope areas and ii) numerical modelling of the potential slide runout behaviour. This submission compares two different state-of-the-art depth-averaged numerical models for debris flow runout. These models both incorporate advanced rheology modelling and are capable of modelling slide behaviour over complex 3D bathymetry, but solve the governing equations in two drastically differing fashions - the first of which solves these equations within an Eulerian, Finite Volume framework, whilst the second solves the equations within a Lagrangian framework through a technique known as Smoothed Particle Hydrodynamics (SPH). The relationship between shear stress and shear strain rate is modelled using either the linear viscoplastic Bingham or non-linear viscoplastic Herschel-Bulkley model. These numerical models also have a facility for the modelling of soil strength degradation during runout as a consequence of remoulding, as well as through the entrainment of ambient fluid. The soil mass itself is modelled as a rigid plug layer with an internal shear strain rate of zero, overlying a sheared layer where the shear stress at the interface between these layers is equal to the yield stress of the soil. The velocity in the plug layer is constant throughout its depth, whilst in the sheared layer it gradually diminishes to zero. The Eurlerian model relies on an unstructured triangular mesh for the representation of the bathymetry. This is constructed using a generator which provides for local refinement in the area of anticipated runout and along steeper slopes or channelised areas. The equations are solved using a finite volume approach, using a

  19. Modeling of unsteady-state flows of viscoelastic plastic fluids

    SciTech Connect

    Shulman, Z.P.; Dornyak, O.R.; Khusid, B.M.; Ryklina, I.L.; Zal'tsgendler, E.A.

    1989-04-01

    Unsteady-state flows of media that possess a complex of rheological properties such as elasticity, viscosity and plasticity are studied. The fluid is assumed to exhibit elastic properties at stresses below the fluidity limit. A Trikomi-type boundary-value problem for describing the unsteady-state forced flows in these media is formulated. A difference scheme for the unobstructed calculation is constructed, and the conditions of its efficiency are investigated. The numerical results obtained illustrate the essential effect of elastic properties in the region where the stress is below the fluidity limit; in particular, those cases are studied wherein the period of the elastic shear wave is commensurable with the characteristic hydrodynamic time of the process.

  20. Three electronic state model of the primary phototransformation of bacteriorhodopsin.

    PubMed Central

    Humphrey, W; Lu, H; Logunov, I; Werner, H J; Schulten, K

    1998-01-01

    The primary all-trans --> 13-cis photoisomerization of retinal in bacteriorhodopsin has been investigated by means of quantum chemical and combined classical/quantum mechanical simulations employing the density matrix evolution method. Ab initio calculations on an analog of a protonated Schiff base of retinal in vacuo reveal two excited states S1 and S2, the potential surfaces of which intersect along the reaction coordinate through an avoided crossing, and then exhibit a second, weakly avoided, crossing or a conical intersection with the ground state surface. The dynamics governed by the three potential surfaces, scaled to match the in situ level spacings and represented through analytical functions, are described by a combined classical/quantum mechanical simulation. For a choice of nonadiabatic coupling constants close to the quantum chemistry calculation results, the simulations reproduce the observed photoisomerization quantum yield and predict the time needed to pass the avoided crossing region between S1 and S2 states at tau1 = 330 fs and the S1 --> ground state crossing at tau2 = 460 fs after light absorption. The first crossing follows after a 30 degrees torsion on a flat S1 surface, and the second crossing follows after a rapid torsion by a further 60 degrees. tau1 matches the observed fluorescence lifetime of S1. Adjusting the three energy levels to the spectral shift of D85N and D212N mutants of bacteriorhodospin changes the crossing region of S1 and S2 and leads to an increase in tau1 by factors 17 and 10, respectively, in qualitative agreement with the observed increase in fluorescent lifetimes. PMID:9746511

  1. A model for steady-state HNF combustion

    SciTech Connect

    Louwers, J.; Gadiot, G.M.H.J.L.; Brewster, M.Q.; Son, S.F.

    1997-09-01

    A simple model for the combustion of solid monopropellants is presented. The condensed phase is treated by high activation energy asymptotics. The gas phase is treated by two limit cases: high activation energy, and low activation energy. This results in simplification of the gas phase energy equation, making an (approximate) analytical solution possible. The results of the model are compared with experimental results of Hydrazinium Nitroformate (HNF) combustion.

  2. A three-state dynamical model for religious affiliation

    NASA Astrophysics Data System (ADS)

    McCartney, Mark; Glass, David H.

    2015-02-01

    In the last century the western world has seen a rapid increase in the number of people describing themselves as affiliated with no religious group. We construct a set of models using coupled differential equations in which members of a society can be in one of three groups; religiously committed, religiously affiliated or religiously not affiliated. These models are then used to analyse post World War II census data for Northern Ireland.

  3. Integration of massive states as contractions of nonlinear {sigma} models

    SciTech Connect

    Andrianopoli, L.; Ferrara, S.; Lledo, M.A.; Macia, O.

    2005-07-01

    We consider the contraction of some nonlinear {sigma} models which appear in effective supergravity theories. In particular we consider the contractions of maximally symmetric spaces corresponding to N=1 and N=2 theories, as they appear in certain low energy effective supergravity actions with mass deformations. The contraction procedure is shown to describe the integrating out of massive modes in the presence of interactions, as it happens in many supergravity models after spontaneous supersymmetry breaking.

  4. Empirical Geographic Modeling of Switchgrass Yields in the United States

    SciTech Connect

    Jager, Yetta; Baskaran, Latha Malar; Brandt, Craig C; Davis, Ethan; Gunderson, Carla A; Wullschleger, Stan D

    2010-01-01

    Switchgrass (Panicum virgatum L.) is a perennial grass native to the US that has been studied as a sustainable source of biomass fuel. Although many field-scale studies have examined the potential of this grass as a bioenergy crop, these studies have not been integrated. In this study, we present an empirical model for switchgrass yield and use this model to predict yield for the conterminous US. We added environmental covariates to assembled yield data from field trials based on geographic location. We developed empirical models based on these data. The resulting empirical models, which account for spatial autocorrelation in the field data, provide the ability to estimate yield from factors associated with climate, soils, and management for both lowland and upland varieties of switchgrass. Yields of both ecotypes showed quadratic responses to temperature, increased with precipitation and minimum winter temperature, and decreased with stand age. Only the upland ecotype showed a positive response to our index of soil wetness and only the lowland ecotype showed a positive response to fertilizer. We view this empirical modeling effort, not as an alternative to mechanistic plant-growth modeling, but rather as a first step in the process of functional validation that will compare patterns produced by the models with those found in data. For the upland variety, the correlation between measured yields and yields predicted by empirical models was 0.62 for the training subset and 0.58 for the test subset. For the lowland variety, the correlation was 0.46 for the training subset and 0.19 for the test subset. Because considerable variation in yield remains unexplained, it will be important in future to characterize spatial and local sources of uncertainty associated with empirical yield estimates.

  5. Ground state and excitations of the supersymmetric extended Hubbard model with long-range interaction

    SciTech Connect

    Wang, D.F.; Liu, J.T.

    1996-07-01

    We examine the ground state and excitations of the one-dimensional supersymmetric extended Hubbard model with long-range interaction. The ground state wave-function and low lying excitations are given explicitly in the form of a Jastrow product of two-body terms. This result motivates an asymptotic Bethe ansatz solution for the model. We present evidence that this solution is in fact exact and spans the complete spectrum of states. {copyright} {ital 1996 The American Physical Society.}

  6. Applicability of equations of state for modeling helium systems

    NASA Astrophysics Data System (ADS)

    Thomas, Rijo Jacob; Dutta, Rohan; Ghosh, Parthasarathi; Chowdhury, Kanchan

    2012-07-01

    Proper design of helium systems with large number of components and involved configurations such as helium liquefiers/refrigerators requires the use of tools like process simulators. The accuracy of the simulation results, to a great extent, depends on the accuracy of property data. For computation of thermodynamic properties of helium, the 32-parameter MBWR equation of state proposed by McCarty and Arp [1] is widely used. However, it is computationally involved, makes the simulation process more time-consuming and sometimes leads to computational difficulties such as numerical oscillations, divergence in solution especially, when the process operates over a wide thermodynamic region and is constituted of many components. Substituting MBWR EOS by simpler equations of state (EOS(s)) at selected thermodynamic planes, where the simpler EOS(s) have the similar accuracy as that of MBWR EOS may enhance ease of computation. In the present paper, the methodology to implement this concept has been elucidated with examples of steady state and dynamic simulation of helium liquefier/refrigerator based on Collins cycle. The above concept can be applied to thermodynamic analysis of other process cycles where computation of fluid property is involved.

  7. REFLECTIONS ON THE TWO-STATE ELECTRON TRANSFER MODEL.

    SciTech Connect

    Brunschwig, B.S.

    2000-01-12

    There is general agreement that the two most important factors determining electron transfer rates in solution are the degree of electronic interaction between the donor and acceptor sites, and the changes in the nuclear configurations of the donor, acceptor, and surrounding medium that occur upon the gain or loss of an electron Ll-51. The electronic interaction of the sites will be very weak, and the electron transfer slow, when the sites are far apart or their interaction is symmetry or spin forbidden. Since electron motion is much faster than nuclear motion, energy conservation requires that, prior to the actual electron transfer, the nuclear configurations of the reactants and the surrounding medium adjust from their equilibrium values to a configuration (generally) intermediate between that of the reactants and products. In the case of electron transfer between , two metal complexes in a polar solvent, the nuclear configuration changes involve adjustments in the metal-ligand and intraligand bond lengths and angles, and changes in the orientations of the surrounding solvent molecules. In common with ordinary chemical reactions, an electron transfer reaction can then be described in terms of the motion of the system on an energy surface from the reactant equilibrium configuration (initial state) to the product equilibrium configuration (final state) via the activated complex (transition state) configuration.

  8. Local hidden variable models for entangled quantum States using finite shared randomness.

    PubMed

    Bowles, Joseph; Hirsch, Flavien; Quintino, Marco Túlio; Brunner, Nicolas

    2015-03-27

    The statistics of local measurements performed on certain entangled states can be reproduced using a local hidden variable (LHV) model. While all known models make use of an infinite amount of shared randomness, we show that essentially all entangled states admitting a LHV model can be simulated with finite shared randomness. Our most economical model simulates noisy two-qubit Werner states using only log_{2}(12)≃3.58 bits of shared randomness. We also discuss the case of positive operator valued measures, and the simulation of nonlocal states with finite shared randomness and finite communication. Our work represents a first step towards quantifying the cost of LHV models for entangled quantum states. PMID:25860723

  9. Unstable rotational states of string models and width of a hadron

    SciTech Connect

    Sharov, G. S.

    2009-06-01

    Rotational states (planar uniform rotations) of various string hadron models are tested for stability with respect to small disturbances. These models include an open or closed string carrying n massive points (quarks), and their rotational states result in a set of quasilinear Regge trajectories. It is shown that rotations of the linear string baryon model q-q-q and the similar states of the closed string are unstable, because spectra of small disturbances for these states contain complex frequencies, corresponding to exponentially growing modes of disturbances. Rotations of the linear model are unstable for any values of points' masses, but for the closed string we have the threshold effect. This instability is important for describing excited hadrons; in particular, it increases predictions for their width {gamma}. Predicted large values {gamma} for N, {delta} and strange baryons in comparison with experimental data result in unacceptability of the linear string model q-q-q for describing these baryon states.

  10. Steady-state Analysis Model for Advanced Fuelcycle Schemes

    Energy Science and Technology Software Center (ESTSC)

    2006-05-12

    The model was developed as a part of the study, "Advanced Fuel Cycles and Waste Management", which was performed during 2003—2005 by an ad-hoc expert group under the Nuclear Development Committee in the OECD/NEA. The model was designed for an efficient conduct of nuclear fuel cycle scheme cost analyses. It is simple, transparent and offers users the capability to track down the cost analysis results. All the fuel cycle schemes considered in the model aremore » represented in a graphic format and all values related to a fuel cycle step are shown in the graphic interface, i.e., there are no hidden values embedded in the calculations. All data on the fuel cycle schemes considered in the study including mass flows, waste generation, cost data, and other data such as activities, decay heat and neutron sources of spent fuel and high—level waste along time are included in the model and can be displayed. The user can modify easily the values of mass flows and/or cost parameters and see the corresponding changes in the results. The model calculates: front—end fuel cycle mass flows such as requirements of enrichment and conversion services and natural uranium; mass of waste based on the waste generation parameters and the mass flow; and all costs. It performs Monte Carlo simulations with changing the values of all unit costs within their respective ranges (from lower to upper bounds).« less

  11. Regional Evacuation Modeling: A State of the Art Reviewing

    SciTech Connect

    Southworth, F.

    1991-01-01

    Regional evacuation modeling is treated as a five step process: involving vehicle trip generation, trip departure time, trip destination, and trip route selection modeling, supplemented by plan set-up and analysis procedures. Progress under each of these headings is reviewed and gaps in the process identified. The potential for emergency planners to make use of real time traffic data, resulting from the recent technical and economic revolutions in telecommunications and infrared traffic sensing, is identified as the single greatest opportunity for the near future; and some beginnings in the development of real time dynamic traffic modeling specifically geared to evacuation planning are highlighted. Significant data problems associated with the time of day location of large urban populations represent a second area requiring extensive research. A third area requiring much additional effort is the translation of the considerable knowledge we have on evacuee behavior in times of crisis into reliable quantitative measures of the timing of evacuee mobilization, notably by distance from the source of the hazard. Specific evacuation models are referenced and categorized by method. Incorporation of evacuation model findings into the definition of emergency planning zone boundaries is also discussed.

  12. Non-degenerated Ground States and Low-degenerated Excited States in the Antiferromagnetic Ising Model on Triangulations

    NASA Astrophysics Data System (ADS)

    Jiménez, Andrea

    2014-02-01

    We study the unexpected asymptotic behavior of the degeneracy of the first few energy levels in the antiferromagnetic Ising model on triangulations of closed Riemann surfaces. There are strong mathematical and physical reasons to expect that the number of ground states (i.e., degeneracy) of the antiferromagnetic Ising model on the triangulations of a fixed closed Riemann surface is exponential in the number of vertices. In the set of plane triangulations, the degeneracy equals the number of perfect matchings of the geometric duals, and thus it is exponential by a recent result of Chudnovsky and Seymour. From the physics point of view, antiferromagnetic triangulations are geometrically frustrated systems, and in such systems exponential degeneracy is predicted. We present results that contradict these predictions. We prove that for each closed Riemann surface S of positive genus, there are sequences of triangulations of S with exactly one ground state. One possible explanation of this phenomenon is that exponential degeneracy would be found in the excited states with energy close to the ground state energy. However, as our second result, we show the existence of a sequence of triangulations of a closed Riemann surface of genus 10 with exactly one ground state such that the degeneracy of each of the 1st, 2nd, 3rd and 4th excited energy levels belongs to O( n), O( n 2), O( n 3) and O( n 4), respectively.

  13. Modeling of an Adjustable Beam Solid State Light Project

    NASA Technical Reports Server (NTRS)

    Clark, Toni

    2015-01-01

    This proposal is for the development of a computational model of a prototype variable beam light source using optical modeling software, Zemax Optics Studio. The variable beam light source would be designed to generate flood, spot, and directional beam patterns, while maintaining the same average power usage. The optical model would demonstrate the possibility of such a light source and its ability to address several issues: commonality of design, human task variability, and light source design process improvements. An adaptive lighting solution that utilizes the same electronics footprint and power constraints while addressing variability of lighting needed for the range of exploration tasks can save costs and allow for the development of common avionics for lighting controls.

  14. The United States Geological Survey Science Data Lifecycle Model

    USGS Publications Warehouse

    Faundeen, John L.; Burley, Thomas E.; Carlino, Jennifer A.; Govoni, David L.; Henkel, Heather S.; Holl, Sally L.; Hutchison, Vivian B.; Martín, Elizabeth; Montgomery, Ellyn T.; Ladino, Cassandra; Tessler, Steven; Zolly, Lisa S.

    2014-01-01

    U.S. Geological Survey (USGS) data represent corporate assets with potential value beyond any immediate research use, and therefore need to be accounted for and properly managed throughout their lifecycle. Recognizing these motives, a USGS team developed a Science Data Lifecycle Model (SDLM) as a high-level view of data—from conception through preservation and sharing—to illustrate how data management activities relate to project workflows, and to assist with understanding the expectations of proper data management. In applying the Model to research activities, USGS scientists can ensure that data products will be well-described, preserved, accessible, and fit for re-use. The Model also serves as a structure to help the USGS evaluate and improve policies and practices for managing scientific data, and to identify areas in which new tools and standards are needed.

  15. State of the art of sonic boom modeling.

    PubMed

    Plotkin, Kenneth J

    2002-01-01

    Based on fundamental theory developed through the 1950s and 1960s, sonic boom modeling has evolved into practical tools. Over the past decade, there have been requirements for design tools for an advanced supersonic transport, and for tools for environmental assessment of various military and aerospace activities. This has resulted in a number of advances in the understanding of the physics of sonic booms, including shock wave rise times, propagation through turbulence, and blending sonic boom theory with modern computational fluid dynamics (CFD) aerodynamic design methods. This article reviews the early fundamental theory, recent advances in theory, and the application of these advances to practical models. PMID:11837958

  16. State-space model with deep learning for functional dynamics estimation in resting-state fMRI.

    PubMed

    Suk, Heung-Il; Wee, Chong-Yaw; Lee, Seong-Whan; Shen, Dinggang

    2016-04-01

    Studies on resting-state functional Magnetic Resonance Imaging (rs-fMRI) have shown that different brain regions still actively interact with each other while a subject is at rest, and such functional interaction is not stationary but changes over time. In terms of a large-scale brain network, in this paper, we focus on time-varying patterns of functional networks, i.e., functional dynamics, inherent in rs-fMRI, which is one of the emerging issues along with the network modelling. Specifically, we propose a novel methodological architecture that combines deep learning and state-space modelling, and apply it to rs-fMRI based Mild Cognitive Impairment (MCI) diagnosis. We first devise a Deep Auto-Encoder (DAE) to discover hierarchical non-linear functional relations among regions, by which we transform the regional features into an embedding space, whose bases are complex functional networks. Given the embedded functional features, we then use a Hidden Markov Model (HMM) to estimate dynamic characteristics of functional networks inherent in rs-fMRI via internal states, which are unobservable but can be inferred from observations statistically. By building a generative model with an HMM, we estimate the likelihood of the input features of rs-fMRI as belonging to the corresponding status, i.e., MCI or normal healthy control, based on which we identify the clinical label of a testing subject. In order to validate the effectiveness of the proposed method, we performed experiments on two different datasets and compared with state-of-the-art methods in the literature. We also analyzed the functional networks learned by DAE, estimated the functional connectivities by decoding hidden states in HMM, and investigated the estimated functional connectivities by means of a graph-theoretic approach. PMID:26774612

  17. A new state space model for the NASA/JPL 70-meter antenna servo controls

    NASA Technical Reports Server (NTRS)

    Hill, R. E.

    1987-01-01

    A control axis referenced model of the NASA/JPL 70-m antenna structure is combined with the dynamic equations of servo components to produce a comprehansive state variable (matrix) model of the coupled system. An interactive Fortran program for generating the linear system model and computing its salient parameters is described. Results are produced in a state variable, block diagram, and in factored transfer function forms to facilitate design and analysis by classical as well as modern control methods.

  18. Exactly Solvable Wormhole and Cosmological Models with a Barotropic Equation of State

    NASA Astrophysics Data System (ADS)

    Kuhfittig, P. K. F.

    An exact solution of the Einstein field equations given the barotropic equation of state $p=\\omega\\rho$ yields two possible models: (1) if $\\omega <-1$, we obtain the most general possible anisotropic model for wormholes supported by phantom energy and (2) if $\\omega >0$, we obtain a model for galactic rotation curves. Here the equation of state represents a perfect fluid which may include dark matter. These results illustrate the power and usefulness of exact solutions.

  19. Steady-State Analysis Model for Advanced Fuel Cycle Schemes.

    Energy Science and Technology Software Center (ESTSC)

    2008-03-17

    Version 00 SMAFS was developed as a part of the study, "Advanced Fuel Cycles and Waste Management", which was performed during 2003-2005 by an ad-hoc expert group under the Nuclear Development Committee in the OECD/NEA. The model was designed for an efficient conduct of nuclear fuel cycle scheme cost analyses. It is simple, transparent and offers users the capability to track down cost analysis results. All the fuel cycle schemes considered in the model aremore » represented in a graphic format and all values related to a fuel cycle step are shown in the graphic interface, i.e., there are no hidden values embedded in the calculations. All data on the fuel cycle schemes considered in the study including mass flows, waste generation, cost data, and other data such as activities, decay heat and neutron sources of spent fuel and high-level waste along time are included in the model and can be displayed. The user can easily modify values of mass flows and/or cost parameters and see corresponding changes in the results. The model calculates: front-end fuel cycle mass flows such as requirements of enrichment and conversion services and natural uranium; mass of waste based on the waste generation parameters and the mass flow; and all costs.« less

  20. Preliminary Exploration of Adaptive State Predictor Based Human Operator Modeling

    NASA Technical Reports Server (NTRS)

    Trujillo, Anna C.; Gregory, Irene M.

    2012-01-01

    Control-theoretic modeling of the human operator dynamic behavior in manual control tasks has a long and rich history. In the last two decades, there has been a renewed interest in modeling the human operator. There has also been significant work on techniques used to identify the pilot model of a given structure. The purpose of this research is to attempt to go beyond pilot identification based on collected experimental data and to develop a predictor of pilot behavior. An experiment was conducted to quantify the effects of changing aircraft dynamics on an operator s ability to track a signal in order to eventually model a pilot adapting to changing aircraft dynamics. A gradient descent estimator and a least squares estimator with exponential forgetting used these data to predict pilot stick input. The results indicate that individual pilot characteristics and vehicle dynamics did not affect the accuracy of either estimator method to estimate pilot stick input. These methods also were able to predict pilot stick input during changing aircraft dynamics and they may have the capability to detect a change in a subject due to workload, engagement, etc., or the effects of changes in vehicle dynamics on the pilot.

  1. Popping the Kernel Modeling the States of Matter

    ERIC Educational Resources Information Center

    Hitt, Austin; White, Orvil; Hanson, Debbie

    2005-01-01

    This article discusses how to use popcorn to engage students in model building and to teach them about the nature of matter. Popping kernels is a simple and effective method to connect the concepts of heat, motion, and volume with the different phases of matter. Before proceeding with the activity the class should discuss the nature of scientific…

  2. Gaussian modelling and Schmidt modes of SPDC biphoton states

    NASA Astrophysics Data System (ADS)

    Fedorov, M. V.; Mikhailova, Yu M.; Volkov, P. A.

    2009-09-01

    A double-Gaussian model and the Schmidt modes are found for the biphoton wavefunction characterizing spontaneous parametric down-conversion with the degenerate collinear phase-matching of type I and with a pulsed pump. The obtained results are valid for all durations of the pump pulses: short, long and intermediately long.

  3. The Illinois State Interdisciplinary Model for Teaching Languages for Business.

    ERIC Educational Resources Information Center

    Varner, Carson H., Jr.; Whitcomb, Richard O.

    This model combines in a team-taught course the study of business and a foreign language. The objective is to give business students a foreign language experience in a relatively brief time and also to offer them a business-oriented introduction to a culture other than their own. Students in business courses are preparing for a career in…

  4. Reduction of an eight-state mechanism of cotransport to a six-state model using a new computer program.

    PubMed Central

    Falk, S; Guay, A; Chenu, C; Patil, S D; Berteloot, A

    1998-01-01

    A computer program was developed to allow easy derivation of steady-state velocity and binding equations for multireactant mechanisms including or without rapid equilibrium segments. Its usefulness is illustrated by deriving the rate equation of the most general sequential iso ordered ter ter mechanism of cotransport in which two Na+ ions bind first to the carrier and mirror symmetry is assumed. It is demonstrated that this mechanism cannot be easily reduced to a previously proposed six-state model of Na+-D-glucose cotransport, which also includes a number of implicit assumptions. In fact, the latter model may only be valid over a restricted range of Na+ concentrations or when assuming very strong positive cooperativity for Na+ binding to the glucose symporter within a rapid equilibrium segment. We thus propose an equivalent eight-state model in which the concept of positive cooperativity is best explained within the framework of a polymeric structure of the transport protein involving a minimum number of two transport-competent and identical subunits. This model also includes an obligatory slow isomerization step between the Na+ and glucose-binding sequences, the nature of which might reflect the presence of functionally asymmetrical subunits. PMID:9533694

  5. Echo state networks as an alternative to traditional artificial neural networks in rainfall-runoff modelling

    NASA Astrophysics Data System (ADS)

    de Vos, N. J.

    2013-01-01

    Despite theoretical benefits of recurrent artificial neural networks over their feedforward counterparts, it is still unclear whether the former offer practical advantages as rainfall-runoff models. The main drawback of recurrent networks is the increased complexity of the training procedure due to their architecture. This work uses the recently introduced and conceptually simple echo state networks for streamflow forecasts on twelve river basins in the Eastern United States, and compares them to a variety of traditional feedforward and recurrent approaches. Two modifications on the echo state network models are made that increase the hydrologically relevant information content of their internal state. The results show that the echo state networks outperform feedforward networks and are competitive with state-of-the-art recurrent networks, across a range of performance measures. This, along with their simplicity and ease of training, suggests that they can be considered promising alternatives to traditional artificial neural networks in rainfall-runoff modelling.

  6. The steady-state phase distribution of the motor switch complex model of Halobacterium salinarum.

    PubMed

    del Rosario, Ricardo C H; Diener, Francine; Diener, Marc; Oesterhelt, Dieter

    2009-12-01

    Steady-state analysis is performed on the kinetic model for the switch complex of the flagellar motor of Halobacterium salinarum (Nutsch et al.). The existence and uniqueness of a positive steady-state of the system is established and it is demonstrated why the steady-state is centered around the competent phase, a state of the motor in which it is able to respond to light stimuli. It is also demonstrated why the steady-state shifts to the refractory phase when the steady-state value of the response regulator CheYP increases. This work is one aspect of modeling in systems biology wherein the mathematical properties of a model are established. PMID:19857501

  7. State Machine Modeling of the Space Launch System Solid Rocket Boosters

    NASA Technical Reports Server (NTRS)

    Harris, Joshua A.; Patterson-Hine, Ann

    2013-01-01

    The Space Launch System is a Shuttle-derived heavy-lift vehicle currently in development to serve as NASA's premiere launch vehicle for space exploration. The Space Launch System is a multistage rocket with two Solid Rocket Boosters and multiple payloads, including the Multi-Purpose Crew Vehicle. Planned Space Launch System destinations include near-Earth asteroids, the Moon, Mars, and Lagrange points. The Space Launch System is a complex system with many subsystems, requiring considerable systems engineering and integration. To this end, state machine analysis offers a method to support engineering and operational e orts, identify and avert undesirable or potentially hazardous system states, and evaluate system requirements. Finite State Machines model a system as a finite number of states, with transitions between states controlled by state-based and event-based logic. State machines are a useful tool for understanding complex system behaviors and evaluating "what-if" scenarios. This work contributes to a state machine model of the Space Launch System developed at NASA Ames Research Center. The Space Launch System Solid Rocket Booster avionics and ignition subsystems are modeled using MATLAB/Stateflow software. This model is integrated into a larger model of Space Launch System avionics used for verification and validation of Space Launch System operating procedures and design requirements. This includes testing both nominal and o -nominal system states and command sequences.

  8. Capturing the state transitions of seizure-like events using Hidden Markov models.

    PubMed

    Guirgis, Mirna; Serletis, Demitre; Carlen, Peter L; Bardakjian, Berj L

    2011-01-01

    The purpose of this study was to investigate the number of states present in the progression of a seizure-like event (SLE). Of particular interest is to determine if there are more than two clearly defined states, as this would suggest that there is a distinct state preceding an SLE. Whole-intact hippocampus from C57/BL mice was used to model epileptiform activity induced by the perfusion of a low Mg(2+)/high K(+) solution while extracellular field potentials were recorded from CA3 pyramidal neurons. Hidden Markov models (HMM) were used to model the state transitions of the recorded SLEs by incorporating various features of the Hilbert transform into the training algorithm; specifically, 2- and 3-state HMMs were explored. Although the 2-state model was able to distinguish between SLE and nonSLE behavior, it provided no improvements compared to visual inspection alone. However, the 3-state model was able to capture two distinct nonSLE states that visual inspection failed to discriminate. Moreover, by developing an HMM based system a priori knowledge of the state transitions was not required making this an ideal platform for seizure prediction algorithms. PMID:22254742

  9. Evaluating an interprofessional disease state and medication management review model.

    PubMed

    Hoti, Kreshnik; Forman, Dawn; Hughes, Jeffery

    2014-03-01

    There is lack of literature data reporting an incorporation of medication management reviews in students' interprofessional education (IPE) and practice programs in aged care settings. This pilot study reports how an interprofessional disease state and medication management review program (DSMMR) was established in a residential aged care facility in Perth, Western Australia. Students from the professions of nursing, pharmacy and physiotherapy focused on a wellness check in the areas of cognition, falls and continence while integrating a medication management review. Students' attitudes were explored using a pre- and post-placement questionnaire. Students indicated positive experience with the IPE DSMMR program which also resulted in their positive attitudinal shift towards IPE and practice. These findings indicated that aged care can be a suitable setting for student interprofessional programs focusing on DSMMR. PMID:24246025

  10. A NON-RADIAL OSCILLATION MODEL FOR PULSAR STATE SWITCHING

    SciTech Connect

    Rosen, R.; McLaughlin, M. A.; Thompson, S. E.

    2011-02-10

    Pulsars are unique astrophysical laboratories because of their clock-like timing precision, providing new ways to test general relativity and detect gravitational waves. One impediment to high-precision pulsar timing experiments is timing noise. Recently, Lyne et al. showed that the timing noise in a number of pulsars is due to quasi-periodic fluctuations in the pulsars' spin-down rates and that some of the pulsars have associated changes in pulse profile shapes. Here we show that a non-radial oscillation model based on asteroseismological theory can explain these quasi-periodic fluctuations. Application of this model to neutron stars will increase our knowledge of neutron star emission and neutron star interiors and may improve pulsar timing precision.

  11. Current state of the mass storage system reference model

    NASA Technical Reports Server (NTRS)

    Coyne, Robert

    1993-01-01

    IEEE SSSWG was chartered in May 1990 to abstract the hardware and software components of existing and emerging storage systems and to define the software interfaces between these components. The immediate goal is the decomposition of a storage system into interoperable functional modules which vendors can offer as separate commercial products. The ultimate goal is to develop interoperable standards which define the software interfaces, and in the distributed case, the associated protocols to each of the architectural modules in the model. The topics are presented in viewgraph form and include the following: IEEE SSSWG organization; IEEE SSSWG subcommittees & chairs; IEEE standards activity board; layered view of the reference model; layered access to storage services; IEEE SSSWG emphasis; and features for MSSRM version 5.

  12. State Space Modelling and Data Analysis Exercises in LISA Pathfinder

    NASA Astrophysics Data System (ADS)

    Nofrarias, M.; Antonucci, F.; Armano, M.; Audley, H.; Auger, G.; Benedetti, M.; Binetruy, P.; Bogenstahl, J.; Bortoluzzi, D.; Brandt, N.; Caleno, M.; Cavalleri, A.; Congedo, G.; Cruise, M.; Danzmann, K.; De Marchi, F.; Diaz-Aguilo, M.; Diepholz, I.; Dixon, G.; Dolesi, R.; Dunbar, N.; Fauste, J.; Ferraioli, L.; Ferroni, V.; Fichter, W.; Fitzsimons, E.; Freschi, M.; García Marirrodriga, C.; Gerndt, R.; Gesa, L.; Gibert, F.; Giardini, D.; Grimani, C.; Grynagier, A.; Guzmán, F.; Harrison, I.; Heinzel, G.; Hewitson, M.; Hollington, D.; Hoyland, D.; Hueller, M.; Huesler, J.; Jennrich, O.; Jetzer, P.; Johlander, B.; Karnesis, N.; Korsakova, N.; Killow, C.; Llamas, X.; Lloro, I.; Lobo, A.; Maarschalkerweerd, R.; Madden, S.; Mance, D.; Martin, V.; Mateos, I.; McNamara, P.; Mendes, J.; Mitchell, E.; Nicolodi, D.; Perreur-Lloyd, M.; Plagnol, E.; Prat, P.; Ramos-Castro, J.; Reiche, J.; Romera Perez, J. A.; Robertson, D.; Rozemeijer, H.; Russano, G.; Schleicher, A.; Shaul, D.; Sopuerta, C. F.; Sumner, T. J.; Taylor, A.; Texier, D.; Trenkel, C.; Tu, H. B.; Vitale, S.; Wanner, G.; Ward, H.; Waschke, S.; Wass, P.; Wealthy, D.; Wen, S.; Weber, W.; Ziegler, T.; Zweifel, P.

    2013-01-01

    LISA Pathfinder is a mission planned by the European Space Agency (ESA) to test the key technologies that will allow the detection of gravitational waves in space. The instrument on-board, the LISA Technology package, will undergo an exhaustive campaign of calibrations and noise characterisation campaigns in order to fully describe the noise model. Data analysis plays an important role in the mission and for that reason the data analysis team has been developing a toolbox which contains all the functionality required during operations. In this contribution we give an overview of recent activities, focusing on the improvements in the modelling of the instrument and in the data analysis campaigns performed both with real and simulated data.

  13. Monthly Water Balance Model Portal for the United States

    NASA Astrophysics Data System (ADS)

    Hay, L.; Bock, A.; Markstrom, S. L.; McCabe, G. J., Jr.; Atkinson, D.

    2014-12-01

    The Monthly Water Balance Model (MWBM) portal delivers MWBM output generated for current and future climatic conditions for stream segments and hydrologic response units derived from the US Geological Survey's National Hydrologic Model Geospatial Fabric. The MWBM is a modular system that provides monthly estimates of components of the hydrologic cycle (e.g. streamflow, potential and actual evapotranspiration, snowpack, and storage) computed from mean monthly temperature, monthly total precipitation, latitude, and available soil water capacity. The MWBM portal can generate reports and graphics using simulations from more than 200 current and future climate scenarios at any location within the contiguous US. This presentation will introduce users to the MWBM portal and demonstrate how to access and download MWBM portal data.

  14. Solid state convection models of lunar internal temperature

    NASA Technical Reports Server (NTRS)

    Schubert, G.; Young, R. E.; Cassen, P.

    1975-01-01

    Thermal models of the Moon were made which include cooling by subsolidus creep and consideration of the creep behavior of geologic material. Measurements from the Apollo program on seismic velocities, electrical conductivity of the Moon's interior, and heat flux at two locations were used in the calculations. Estimates of 1500 to 1600 K were calculated for the temperature, and one sextillion to ten sextillion sq cm/sec were calcualted for the viscosity of the deep lunar interior.

  15. State of the Art of Demand Surge Modeling

    NASA Astrophysics Data System (ADS)

    Olsen, A.; Porter, K.

    2009-04-01

    Among other phenomena, many insurance loss models estimate the increased losses in large-scale disasters--referred to here as catastrophes--compared to the losses in small-scale disasters. This amplification of loss has been traditionally and loosely called "demand surge," although there is a clear need for more specific terminology. Many factors have been identified as drivers of demand surge. First among them is the sudden and temporary increased demand for construction materials and labor that overwhelms local supplies. The purpose of the present research is to describe in qualitative terms the current understanding of demand surge in the broad sense of amplification of insured loss. Aspects of demand surge were observed following the 1886 Charleston, South Carolina, and 1906 San Francisco, U.S. earthquakes. More recently, the aftermaths of Cyclone Tracy, Hurricane Andrew, the Northridge Earthquake, the 1999 windstorms in France, the 2004-5 hurricane seasons on the Gulf Coast, and the 2007 floods in the U.K. all evidenced demand surge in one form or another. Each event highlights particular aspects of the broader demand-surge phenomena. In other words, there are general themes associated with demand surge, which have greater or lesser expression in each historic event. Pieces of the broader demand-surge phenomena have been described by mathematical models, with varying degrees of complexity. For example, researchers have used linear input-output or nonlinear computable general equilibrium models to describe the response of construction costs to a catastrophe. Ultimately the present research will include the gathering of evidence through interviews, field observations, reviews of academic and insurance industry literature, and data collection. This evidence will then inform and validate a general quantitative, mathematical model of the demand-surge process.

  16. Modeling of Biomass Burning Aerosols over Southeastern United States

    NASA Astrophysics Data System (ADS)

    Ivey, C.; Lavoue, D.; Davis, A.; Hu, Y.; Russell, A. G.

    2014-12-01

    The U.S. National Emissions Inventory (NEI) for area sources such as biomass burning have uncertainties in temporal variability due to temporal averaging of the final inventories. The Fire Inventory of NCAR (FINN) provides detailed emissions estimates of gaseous and aerosol emissions from individual wildland, prescribed, and open fires over North America. In an effort to improve PM2.5 source impact estimates from fire activity over Southeastern U.S., the Community Multi-Scale Air Quality (CMAQ) model is used to simulate PM2.5 concentrations and source impacts for fires during May of 2012. In this work, FINN emissions estimates replace NEI fire emissions estimates for more precise estimation of fire impact on air quality. Modeled results are evaluated using observations from monitoring networks such as the Chemical Speciation Network and the Southeastern Aerosol Research and Characterization network. Aircraft measurements from the Deep Convective Cloud and Chemistry (DC3) flight campaign and the Studies of Emissions and Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys (SEAC4RS) are also used to evaluate modeled simulations of aerosol concentrations.

  17. Ballistic quantum state transfer in spin chains: General theory for quasi-free models and arbitrary initial states

    NASA Astrophysics Data System (ADS)

    Banchi, Leonardo

    2013-11-01

    Ballistic quantum information transfer through spin chains is based on the idea of making the spin dynamics ruled by collective excitations with linear dispersion relation. Unlike perfect state transfer schemes, a ballistic transmission requires only a minimal engineering of the interactions; in fact, for most practical purposes, the optimization of the couplings to the ends of the chain is sufficient to obtain an almost perfect transmission. In this work we review different ballistic quantum state transfer protocols based on the dynamics of quasi-free spin chains, and further generalize them both at zero and finite temperature. In particular, besides presenting novel analytical results for XX, XY, and Ising spin models, it is shown how, via a complete control on the first and last two qubits of the chain, destructive thermal effects can be cancelled, leading to a high-quality state transmission irrespective of the temperature.

  18. Topological Edge States with Zero Hall Conductivity in a Dimerized Hofstadter Model

    NASA Astrophysics Data System (ADS)

    Lau, Alexander; Ortix, Carmine; van den Brink, Jeroen

    2015-11-01

    The Hofstadter model is a simple yet powerful Hamiltonian to study quantum Hall physics in a lattice system, manifesting its essential topological states. Lattice dimerization in the Hofstadter model opens an energy gap at half filling. Here we show that even if the ensuing insulator has a Chern number equal to zero, concomitantly a doublet of edge states appear that are pinned at specific momenta. We demonstrate that these states are topologically protected by inversion symmetry in specific one-dimensional cuts in momentum space, define and calculate the corresponding invariants, and identify a platform for the experimental detection of these novel topological states.

  19. Discontinuous phase transition in an annealed multi-state majority-vote model

    NASA Astrophysics Data System (ADS)

    Li, Guofeng; Chen, Hanshuang; Huang, Feng; Shen, Chuansheng

    2016-07-01

    In this paper, we generalize the original majority-vote (MV) model with noise from two states to arbitrary q states, where q is an integer no less than two. The main emphasis is paid to the comparison on the nature of phase transitions between the two-state MV (MV2) model and the three-state MV (MV3) model. By extensive Monte Carlo simulation and mean-field analysis, we find that the MV3 model undergoes a discontinuous order-disorder phase transition, in contrast to a continuous phase transition in the MV2 model. A central feature of such a discontinuous transition is a strong hysteresis behavior as noise intensity goes forward and backward. Within the hysteresis region, the disordered phase and ordered phase are coexisting.

  20. Critical behavior of absorbing phase transitions for models in the Manna class with natural initial states.

    PubMed

    Lee, Sang Bub

    2014-06-01

    The critical behavior of absorbing phase transitions for two typical models in the Manna universality class, the conserved Manna model and the conserved lattice gas model, both on a square lattice, was investigated using the natural initial states. Various critical exponents were estimated using the static and dynamic simulations. The exponents characterizing dynamics of active particles differ considerably from the known exponents obtained using the random initial states, whereas those associated with the steady-state quantities remain the same. The critical exponents for both models were consistent with errors of less than 1% and satisfied the known scaling relations; thus, the known violation of scaling relations for models with a conserved field was resolved using the natural initial states. The results differed by 7%∼12% from the directed percolation values. PMID:25019750

  1. Raw Data Maximum Likelihood Estimation for Common Principal Component Models: A State Space Approach.

    PubMed

    Gu, Fei; Wu, Hao

    2016-09-01

    The specifications of state space model for some principal component-related models are described, including the independent-group common principal component (CPC) model, the dependent-group CPC model, and principal component-based multivariate analysis of variance. Some derivations are provided to show the equivalence of the state space approach and the existing Wishart-likelihood approach. For each model, a numeric example is used to illustrate the state space approach. In addition, a simulation study is conducted to evaluate the standard error estimates under the normality and nonnormality conditions. In order to cope with the nonnormality conditions, the robust standard errors are also computed. Finally, other possible applications of the state space approach are discussed at the end. PMID:27364333

  2. Continuum limit of lattice models with Laughlin-like ground states containing quasiholes

    NASA Astrophysics Data System (ADS)

    Rodríguez, Iván D.; Nielsen, Anne E. B.

    2015-09-01

    There has been significant interest in recent years in finding fractional quantum Hall physics in lattice models, but it is not always clear how these models connect to the corresponding models in continuum systems. Here we introduce a family of models that is able to interpolate between a recently proposed set of lattice models with Laughlin-like ground states constructed from conformal field theory and models with ground states that are practically the usual bosonic/fermionic Laughlin states in the continuum. Both the ground state and the Hamiltonian are known analytically, and we find that the Hamiltonian in the continuum limit does not coincide with the usual delta interaction Hamiltonian for the Laughlin states. We introduce quasiholes into the models and show analytically that their braiding properties are as expected if the quasiholes are screened. We demonstrate screening numerically for the 1/3 Laughlin model and find that the quasiholes are slightly smaller in the continuum than in the lattice. Finally, we compute the effective magnetic field felt by the quasiholes and show that it is close to uniform when approaching the continuum limit. The techniques presented here to interpolate between the lattice and the continuum can also be applied to other fractional quantum Hall states that are constructed from conformal field theory.

  3. On Zero-Mass Ground States in Super-Membrane Matrix Models

    NASA Astrophysics Data System (ADS)

    Fröhlich, Jürg; Hoppe, Jens

    We recall a formulation of super-membrane theory in terms of certain matrix models. These models are known to have a mass spectrum given by the positive half-axis. We show that, for the simplest such matrix model, a normalizable zero-mass ground state does _n_o_t exist.

  4. Wang-Landau Algorithm for Continuous Models and Joint Density of States

    SciTech Connect

    Zhou, Chenggang; Schulthess, Thomas C; Torbrugge, S.; Landau, D. P.

    2006-01-01

    We present a modified Wang-Landau algorithm for models with continuous degrees of freedom. We demonstrate this algorithm with the calculation of the joint density of states of ferromagnet Heisenberg models and a model polymer chain. The joint density of states contains more information than the density of states of a single variable-energy, but is also much more time consuming to calculate. We present strategies to significantly speed up this calculation for large systems over a large range of energy and order parameter.

  5. Astronomy across State Lines: A Collaborative Model for Astronomical Research

    NASA Astrophysics Data System (ADS)

    Johnson, Chelen H.; Barge, Jacqueline; Linahan, Marcella; York, Donald G.; Cante, David; Cook, Mary; Daw, Maeve; Donahoe, Katherine E.; Ford, Sydney; Haecker, Lille W.; Hibbs, Cecily A.; Hogan, Eleanor B.; Karos, Demetra N.; Kozikowski, Kendall G.; Martin, Taylor A.; Miranda, Fernando; Ng, Emily; Noel, Imany; O'Bryan, Sophie E.; Sharma, Vikrant; Zegeye, David

    2015-01-01

    Scientists do not work in isolation, nor should student scientists. In a collaborative effort, students from three high schools examined plates from the Sloan Digital Sky Survey (SDSS) to estimate the number of galaxies that contain evidence of a black hole. Working under the direction of Don York, former SDSS director, the three teachers used Google hangouts to discuss weekly progress. At their home institutions, students examined optical spectra from SDSS Data Release 10 to determine if a quasar could be discerned. Both Type I and Type II quasars can be seen in the SDSS data. Seven teams of students from different schools compared their findings and collaborated online to discuss potential discoveries. This project can serve as a model for high school teachers who want to facilitate their students participating in an authentic research project. The keys to a successful project are working with a mentor who can guide the group through difficult concepts and communicating frequently throughout the project.

  6. Spatiotemporal modelling of ozone distribution in the State of California

    NASA Astrophysics Data System (ADS)

    Bogaert, P.; Christakos, G.; Jerrett, M.; Yu, H.-L.

    This paper is concerned with the spatiotemporal mapping of monthly 8-h average ozone ( O3) concentrations over California during a 15-years period. The basic methodology of our analysis is based on the spatiotemporal random field (S/TRF) theory. We use a S/TRF decomposition model with a dominant seasonal O3 component that may change significantly from site to site. O3 seasonal patterns are estimated and separated from stochastic fluctuations. By means of Bayesian Maximum Entropy (BME) analysis, physically meaningful and sufficiently detailed space-time maps of the seasonal O3 patterns are generated across space and time. During the summer and winter months the seasonal O3 concentration maps exhibit clear and progressively changing geographical patterns over time, suggesting the existence of relationships in accordance with the typical physiographic and climatologic features of California. BME mapping accuracy can be superior to that of other techniques commonly used by EPA; its framework can rigorously assimilate useful data sources that were previously unaccounted for; the generated maps offer valuable assessments of the spatiotemporal O3 patterns that can be helpful in the identification of physical mechanisms and their interrelations, the design of human exposure and population health models, and in risk assessment. As they focus on the seasonal patterns, the maps are not contingent on short-time and locally prevalent weather conditions, which are of no interest in a global and non-forecasting framework. Moreover, the maps offer valuable insight about the space-time O3 concentration patterns and are, thus, helpful for disentangling the influence of explanatory factors or even for identifying some influential ones that could have been otherwise overlooked.

  7. Two States Mapping Based Time Series Neural Network Model for Compensation Prediction Residual Error

    NASA Astrophysics Data System (ADS)

    Jung, Insung; Koo, Lockjo; Wang, Gi-Nam

    2008-11-01

    The objective of this paper was to design a model of human bio signal data prediction system for decreasing of prediction error using two states mapping based time series neural network BP (back-propagation) model. Normally, a lot of the industry has been applied neural network model by training them in a supervised manner with the error back-propagation algorithm for time series prediction systems. However, it still has got a residual error between real value and prediction result. Therefore, we designed two states of neural network model for compensation residual error which is possible to use in the prevention of sudden death and metabolic syndrome disease such as hypertension disease and obesity. We determined that most of the simulation cases were satisfied by the two states mapping based time series prediction model. In particular, small sample size of times series were more accurate than the standard MLP model.

  8. Determination of multiple steady states in a family of allosteric models for glycolysis

    NASA Astrophysics Data System (ADS)

    Li, Hsing-Ya

    1998-11-01

    To predict glycolytic oscillations, Goldbeter and Lefever [Biophys. J. 12, 1302 (1972)] proposed a complex allosteric model, consisting of 14 species and 32 reactions. Under the usual assumption of a quasisteady state for all the enzymatic forms, they simplified it to a two-variable model and ruled out the possibility of multiple steady states. In this work, the original network is determined to admit multiplicity of steady states by a zero eigenvalue analysis. It is shown that the existence of the multiplicity in the original network can be determined by a subnetwork with five species and eight reactions. The fourteen-species network can be treated as containing four such subnetworks. The analysis is extended to a general modified allosteric model, consisting of n active subunits. It can be shown that the general network has no steady-state multiplicity if all the four subnetworks follow the case of n=1; otherwise, multiple steady states can occur.

  9. One size does not fit all: Adapting mark-recapture and occupancy models for state uncertainty

    USGS Publications Warehouse

    Kendall, W.L.

    2009-01-01

    Multistate capture?recapture models continue to be employed with greater frequency to test hypotheses about metapopulation dynamics and life history, and more recently disease dynamics. In recent years efforts have begun to adjust these models for cases where there is uncertainty about an animal?s state upon capture. These efforts can be categorized into models that permit misclassification between two states to occur in either direction or one direction, where state is certain for a subset of individuals or is always uncertain, and where estimation is based on one sampling occasion per period of interest or multiple sampling occasions per period. State uncertainty also arises in modeling patch occupancy dynamics. I consider several case studies involving bird and marine mammal studies that illustrate how misclassified states can arise, and outline model structures for properly utilizing the data that are produced. In each case misclassification occurs in only one direction (thus there is a subset of individuals or patches where state is known with certainty), and there are multiple sampling occasions per period of interest. For the cases involving capture?recapture data I allude to a general model structure that could include each example as a special case. However, this collection of cases also illustrates how difficult it is to develop a model structure that can be directly useful for answering every ecological question of interest and account for every type of data from the field.

  10. No ψ-Epistemic Model Can Fully Explain the Indistinguishability of Quantum States

    NASA Astrophysics Data System (ADS)

    Barrett, Jonathan; Cavalcanti, Eric G.; Lal, Raymond; Maroney, Owen J. E.

    2014-06-01

    According to a recent no-go theorem [M. Pusey, J. Barrett and T. Rudolph, Nat. Phys. 8, 475 (2012), 10.1038/nphys2309], models in which quantum states correspond to probability distributions over the values of some underlying physical variables must have the following feature: the distributions corresponding to distinct quantum states do not overlap. In such a model, it cannot coherently be maintained that the quantum state merely encodes information about underlying physical variables. The theorem, however, considers only models in which the physical variables corresponding to independently prepared systems are independent, and this has been used to challenge the conclusions of that work. Here we consider models that are defined for a single quantum system of dimension d, such that the independence condition does not arise, and derive an upper bound on the extent to which the probability distributions can overlap. In particular, models in which the quantum overlap between pure states is equal to the classical overlap between the corresponding probability distributions cannot reproduce the quantum predictions in any dimension d ≥3. Thus any ontological model for quantum theory must postulate some extra principle, such as a limitation on the measurability of physical variables, to explain the indistinguishability of quantum states. Moreover, we show that as d→∞, the ratio of classical and quantum overlaps goes to zero for a class of states. The result is noise tolerant, and an experiment is motivated to distinguish the class of models ruled out from quantum theory.

  11. Ground-state properties of linear-exchange quantum spin models

    NASA Astrophysics Data System (ADS)

    Danu, Bimla; Kumar, Brijesh; Pai, Ramesh V.

    2012-10-01

    We study a class of one-dimensional antiferromagnetic quantum spin-1/2 models using DMRG. The exchange interaction in these models decreases linearly with the separation between the spins, Jij = R - |i - j| for |i - j| < R, where R is a positive integer ⩾2. For |i - j| ⩾ R, the interaction is zero. It is known that all the odd-R models have the same exact dimer ground state as the Majumdar-Ghosh (MG) model. In fact, R = 3 is the MG model. However, for an even R, the exact ground state is not known in general, except for R = 2 (the integrable nearest-neighbor Heisenberg chain) and the asymptotic limit of R in which the MG dimer state emerges as the exact ground state. Therefore, we numerically study the ground-state properties of the finite even-R ≠ 2 models, particularly for R = 4, 6 and 8. We find that, unlike R = 2, the higher even-R models are spin-gapped, and exhibit robust dimer order of the MG type in the ground state. The spin-spin correlations decay rapidly to zero, albeit showing weak periodic revivals.

  12. State-of-the-Science Report on Predictive Models and Modeling Approaches for Characterizing and Evaluating Exposure to Nanomaterials

    EPA Science Inventory

    This state-of-the-science review was undertaken to identify fate and transport models and alternative modeling approaches that could be used to predict exposure to engineered nanomaterials (ENMs) released into the environment, specifically, for aquatic systems. The development of...

  13. Delegating Superfund responsibilities: Implementation strategies and political ramifications of a state-wide lead model

    SciTech Connect

    Schwartz, S.

    1991-11-25

    Federal officials manage the great majority of Superfund program work. States have assisted in the process on a site-by-site basis. This contrasts with other EPA programs in which states take responsibility for all work within their boundaries. The paper presents a model for an increased delegation of Superfund responsibilities to qualified states and tribes. Guidelines for implementing the policy shift are addressed as well as political ramifications for various stakeholders.

  14. Poly 3D fault modeling scripts/data for permeability potential of Washington State geothermal prospects

    DOE Data Explorer

    Michael Swyer

    2015-02-05

    Matlab scripts/functions and data used to build Poly3D models and create permeability potential GIS layers for 1) Mount St Helen's, 2) Wind River Valley, and 3) Mount Baker geothermal prospect areas located in Washington state.

  15. State impulsive control strategies for a two-languages competitive model with bilingualism and interlinguistic similarity

    NASA Astrophysics Data System (ADS)

    Nie, Lin-Fei; Teng, Zhi-Dong; Nieto, Juan J.; Jung, Il Hyo

    2015-07-01

    For reasons of preserving endangered languages, we propose, in this paper, a novel two-languages competitive model with bilingualism and interlinguistic similarity, where state-dependent impulsive control strategies are introduced. The novel control model includes two control threshold values, which are different from the previous state-dependent impulsive differential equations. By using qualitative analysis method, we obtain that the control model exhibits two stable positive order-1 periodic solutions under some general conditions. Moreover, numerical simulations clearly illustrate the main theoretical results and feasibility of state-dependent impulsive control strategies. Meanwhile numerical simulations also show that state-dependent impulsive control strategy can be applied to other general two-languages competitive model and obtain the desired result. The results indicate that the fractions of two competitive languages can be kept within a reasonable level under almost any circumstances. Theoretical basis for finding a new control measure to protect the endangered language is offered.

  16. Investigating the northern Adriatic Sea ecosystem state with a very high resolution model

    NASA Astrophysics Data System (ADS)

    Mattia, Gelsomina; Zavatarelli, Marco; Lovato, Tomas

    2015-04-01

    The northern Adriatic Sea ecosystem dynamics is simulated using the coupling of the BFM (Biogeochemical Flux Model) with the NEMO (Nucleus for European Models of the Ocean) model. The modeling system is implemented at very high horizontal (~800 m) and vertical (95 z-level) resolution and is nested with a coarser scale Adriatic/Mediterranean model. Simulation in hindcast and projection mode are being executed and are aimed to evaluate the ecosystem attributes (vigor, organization, resilience), in order to understand the ecosystem state of the basin with respect to the so-called "Good Ecosystem State" (GES) as defined by the EU-MSF9 Directive. Skill of the model in replicating integrated environmental indices such as the EU-EEACS1023+ is also investigated. Finally the model is also open to an off-line coupling with an higher trophic level (HTL) model.

  17. Bidirectional texture function modeling: a state of the art survey.

    PubMed

    Filip, Jirí; Haindl, Michal

    2009-11-01

    An ever-growing number of real-world computer vision applications require classification, segmentation, retrieval, or realistic rendering of genuine materials. However, the appearance of real materials dramatically changes with illumination and viewing variations. Thus, the only reliable representation of material visual properties requires capturing of its reflectance in as wide range of light and camera position combinations as possible. This is a principle of the recent most advanced texture representation, the Bidirectional Texture Function (BTF). Multispectral BTF is a seven-dimensional function that depends on view and illumination directions as well as on planar texture coordinates. BTF is typically obtained by measurement of thousands of images covering many combinations of illumination and viewing angles. However, the large size of such measurements has prohibited their practical exploitation in any sensible application until recently. During the last few years, the first BTF measurement, compression, modeling, and rendering methods have emerged. In this paper, we categorize, critically survey, and psychophysically compare such approaches, which were published in this newly arising and important computer vision and graphics area. PMID:19762922

  18. Developing a Fundamental Model for an Integrated GPS/INS State Estimation System with Kalman Filtering

    NASA Technical Reports Server (NTRS)

    Canfield, Stephen

    1999-01-01

    This work will demonstrate the integration of sensor and system dynamic data and their appropriate models using an optimal filter to create a robust, adaptable, easily reconfigurable state (motion) estimation system. This state estimation system will clearly show the application of fundamental modeling and filtering techniques. These techniques are presented at a general, first principles level, that can easily be adapted to specific applications. An example of such an application is demonstrated through the development of an integrated GPS/INS navigation system. This system acquires both global position data and inertial body data, to provide optimal estimates of current position and attitude states. The optimal states are estimated using a Kalman filter. The state estimation system will include appropriate error models for the measurement hardware. The results of this work will lead to the development of a "black-box" state estimation system that supplies current motion information (position and attitude states) that can be used to carry out guidance and control strategies. This black-box state estimation system is developed independent of the vehicle dynamics and therefore is directly applicable to a variety of vehicles. Issues in system modeling and application of Kalman filtering techniques are investigated and presented. These issues include linearized models of equations of state, models of the measurement sensors, and appropriate application and parameter setting (tuning) of the Kalman filter. The general model and subsequent algorithm is developed in Matlab for numerical testing. The results of this system are demonstrated through application to data from the X-33 Michael's 9A8 mission and are presented in plots and simple animations.

  19. Spatial perspectives in state-and-transition models: A missing link to land management?

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Conceptual models of alternative states and thresholds are based largely on observations of ecosystem processes at a few points in space. Because the distribution of alternative states in spatially-structured ecosystems is the result of variations in pattern-process interactions at different scales,...

  20. Building a Multicontextual Model of Latino College Enrollment: Student, School, and State-Level Effects

    ERIC Educational Resources Information Center

    Nunez, Anne-Marie; Kim, Dongbin

    2012-01-01

    Latinos' college enrollment rates, particularly in four-year institutions, have not kept pace with their population growth in the United States. Using three-level hierarchical generalized linear modeling, this study analyzes data from the Educational Longitudinal Study (ELS) to examine the influence of high school and state contexts, in addition…

  1. STATE-WIDE COMPUTERIZED MODEL FOR DETERMINING OCCUPATIONAL OPPORTUNITIES IN NEBRASKA.

    ERIC Educational Resources Information Center

    Nebraska Occupational Needs Research Coordinating Unit, Lincoln.

    THE NEED FOR OCCUPATIONAL EDUCATION PROGRAMS WAS ASCERTAINED BY DESIGNING A MODEL FOR STATEWIDE ASSESSMENT OF EMPLOYMENT OPPORTUNITIES. A LIST OF 63,125 NEBRASKA EMPLOYERS WAS DEVELOPED IN COOPERATION WITH THE STATE TAX COMMISSIONER, INTERNAL REVENUE SERVICE, AND THE STATE DEPARTMENT OF LABOR. QUESTIONNAIRES CONSISTING OF 174 JOB CLUSTERS WERE…

  2. Community-Based Training: A Model for University and State Partnerships.

    ERIC Educational Resources Information Center

    White, Sally; And Others

    The community-based training model conducted at Pennsylvania State University in cooperation with the Pennsylvania Department of Public Welfare, Office for the Aging, provides accessible gerontological education throughout the State through a multi-faceted approach of informal seminars, undergraduate academic courses, short-term module…

  3. Two Models for Evaluating Alignment of State Standards and Assessments: Competing or Complementary Perspectives?

    ERIC Educational Resources Information Center

    Newton, Jill A.; Kasten, Sarah E.

    2013-01-01

    The release of the Common Core State Standards for Mathematics and their adoption across the United States calls for careful attention to the alignment between mathematics standards and assessments. This study investigates 2 models that measure alignment between standards and assessments, the Surveys of Enacted Curriculum (SEC) and the Webb…

  4. Excited states of many-body systems in the fermion dynamical symmetry model with random interactions

    NASA Astrophysics Data System (ADS)

    Fu, G. J.; Zhao, Y. M.; Ping, J. L.; Arima, A.

    2013-09-01

    In this Brief Report we investigate excited yrast states under random interactions in the framework of the fermion dynamical symmetry model, for the ensemble with spin-0 ground states. Interesting correlations are seen between R6 and R4 (where RI≡EI1+/E21+) by using the Mallmann plot, for cases with both SP(6) symmetry and SO(8) symmetry.

  5. Organizational Models for Online Education: District, State, or Charter School? Policy and Planning Series #109

    ERIC Educational Resources Information Center

    Cavalluzzo, Linda

    2004-01-01

    Opportunities for online K-12 education are expanding dramatically throughout the United States. This paper describes some of the organizational models that have been developed to provide online education to public school students, including their key strengths and challenges. The review is intended to help state and local school officials weigh…

  6. Modeling chlorophyll-a concentration in Taihu Lake based on different trophic state

    NASA Astrophysics Data System (ADS)

    Wang, Li-zhen; Li, Yun-mei; Le, Cheng-feng; Sun, De-yong

    2008-10-01

    In this paper, we want to search for the hyperspectral remote sensing bands most sensitive to chlorophyll-a concentration in different trophic states. Through repeated measurements in Taihu Lake, a large quantity of hyperspectral reflectance data and chlorophyll-a concentration data of lake were obtained from June to September of 2004 and 2005. The eligible hyperspectral data were analyzed to calculate remote sensing reflectance of water in Taihu Lake, and the data of chlorophyll-a concentration obtained from laboratory analysis were used to calculate Trophic State Index. According to the actual condition of Taihu Lake, the hyperspectral data were divided into three groups: mesotropher, eutropher and hyper eutropher. In each trophic state, chlorophyll-a concentration was then regressed against to identify the most sensitive hyperspectral bands. From the established regression models, we can get the conclusion: chlorophyll-a concentration is correspondingly lower under mesotrophic state, badly influenced by suspended matter, the spectral feature of chlorophyll-a is not evident, and the accuracy of regression model in this trophic state is not so satisfactory; in eutrophic state, differential algorithm has better retrieval result, the linear model based on this algorithm has the best estimation result; under hyper eutrophic state, the estimation accuracy is higher than the other two states as a whole. The fitting precision is the highest using the band ratio R719/R670 as independent variable in the quadratic equation model.

  7. Digital soil mapping as a tool for quantifying state-and-transition models

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Ecological sites and associated state-and-transition models (STMs) are rapidly becoming important land management tools in rangeland systems in the US and around the world. Descriptions of states and transitions are largely developed from expert knowledge and generally accepted species and community...

  8. State-and-transition models as guides for adaptive management: What are the needs?

    Technology Transfer Automated Retrieval System (TEKTRAN)

    State and transaction models (STMs) were conceived as a means to organize information about land potential and vegetation dynamics in rangelands to be used in their management. The basic idea is to describe the plant community states that can occur on a site and the causes of transitions between the...

  9. Spatiotemporal modeling of internal states distribution for lithium-ion battery

    NASA Astrophysics Data System (ADS)

    Wang, Mingliang; Li, Han-Xiong

    2016-01-01

    Electrochemical properties of the battery are described in partial differential equations that are impossible to compute online. These internal states are spatially distributed and thus difficult to measure in the battery operation. A space-time separation method is applied to model the electrochemical properties of the battery with the help of the extended Kalman filter. The model is efficiently optimized by using LASSO adaptation method and can be updated through data-based learning. The analytical model derived is able to offer a fast estimation of internal states of the battery, and thus has potential to become a prediction model for battery management system.

  10. State-and-transition prototype model of riparian vegetation downstream of Glen Canyon Dam, Arizona

    USGS Publications Warehouse

    Ralston, Barbara E.; Starfield, Anthony M.; Black, Ronald S.; Van Lonkhuyzen, Robert A.

    2014-01-01

    Facing an altered riparian plant community dominated by nonnative species, resource managers are increasingly interested in understanding how to manage and promote healthy riparian habitats in which native species dominate. For regulated rivers, managing flows is one tool resource managers consider to achieve these goals. Among many factors that can influence riparian community composition, hydrology is a primary forcing variable. Frame-based models, used successfully in grassland systems, provide an opportunity for stakeholders concerned with riparian systems to evaluate potential riparian vegetation responses to alternative flows. Frame-based, state-and-transition models of riparian vegetation for reattachment bars, separation bars, and the channel margin found on the Colorado River downstream of Glen Canyon Dam were constructed using information from the literature. Frame-based models can be simple spreadsheet models (created in Microsoft® Excel) or developed further with programming languages (for example, C-sharp). The models described here include seven community states and five dam operations that cause transitions between states. Each model divides operations into growing (April–September) and non-growing seasons (October–March) and incorporates upper and lower bar models, using stage elevation as a division. The inputs (operations) can be used by stakeholders to evaluate flows that may promote dynamic riparian vegetation states, or identify those flow options that may promote less desirable states (for example, Tamarisk [Tamarix sp.] temporarily flooded shrubland). This prototype model, although simple, can still elicit discussion about operational options and vegetation response.

  11. Dynamic modeling of the vascular system in the state-space.

    PubMed

    Monzon, Jorge E; Pisarello, Maria I; Alvarez Picaza, Carlos; Veglia, Julian I

    2010-01-01

    Modern control theory allows the representation of cardiac dynamics in the state-space, describing the operation of the vascular systems in terms of the cushioning effect of the arterial wall facing compliance changes. In this paper we use state equations to modeling the effect of the compliance variations on the arterial wall. The characteristics of the dynamics and of the calculated parameters of the model allow the distinction of hypertensive and normotensive subjects, in accordance to real clinical data. PMID:21096181

  12. Connecting neutron star observations to the high density equation of state of a quasiparticle model

    NASA Astrophysics Data System (ADS)

    Yan, Yan; Cao, Jing; Luo, Xin-Lian; Sun, Wei-Min; Zong, Hongshi

    2012-12-01

    The observation of the 1.97±0.04 solar-mass neutronlike star gives constraint on the equation of state of cold, condensed matter. In this paper, the equation of state for both the pure quark star and the hybrid star with a quark core described by the quasiparticle model are considered. The parameters of the quasiparticle model that affect the mass of both the quark star and the hybrid star can be constrained by the observation.

  13. Bianchi type-I cosmological model with quadratic equation of state

    NASA Astrophysics Data System (ADS)

    Reddy, D. R. K.; Adhav, K. S.; Purandare, M. A.

    2015-05-01

    Bianchi type-I cosmological model containing perfect fluid with quadratic equation of state has been studied in general theory of relativity. The general solutions of the Einstein's field equations for Bianchi type-I space-time have been obtained under the assumption of quadratic equation of state (EoS) p= αρ 2- ρ, where α is constant and strictly α≠0. The physical and geometrical aspects of the model are discussed.

  14. Wavelet modeling and prediction of the stability of states: the Roman Empire and the European Union

    NASA Astrophysics Data System (ADS)

    Yaroshenko, Tatyana Y.; Krysko, Dmitri V.; Dobriyan, Vitalii; Zhigalov, Maksim V.; Vos, Hendrik; Vandenabeele, Peter; Krysko, Vadim A.

    2015-09-01

    How can the stability of a state be quantitatively determined and its future stability predicted? The rise and collapse of empires and states is very complex, and it is exceedingly difficult to understand and predict it. Existing theories are usually formulated as verbal models and, consequently, do not yield sharply defined, quantitative prediction that can be unambiguously validated with data. Here we describe a model that determines whether the state is in a stable or chaotic condition and predicts its future condition. The central model, which we test, is that growth and collapse of states is reflected by the changes of their territories, populations and budgets. The model was simulated within the historical societies of the Roman Empire (400 BC to 400 AD) and the European Union (1957-2007) by using wavelets and analysis of the sign change of the spectrum of Lyapunov exponents. The model matches well with the historical events. During wars and crises, the state becomes unstable; this is reflected in the wavelet analysis by a significant increase in the frequency ω (t) and wavelet coefficients W (ω, t) and the sign of the largest Lyapunov exponent becomes positive, indicating chaos. We successfully reconstructed and forecasted time series in the Roman Empire and the European Union by applying artificial neural network. The proposed model helps to quantitatively determine and forecast the stability of a state.

  15. Exploratory Structural Equation Modeling of Resting-state fMRI: applicability of group models to individual subjects

    PubMed Central

    James, G. Andrew; Kelley, Mary E.; Craddock, R. Cameron; Holtzheimer, Paul E.; Dunlop, Boadie; Nemeroff, Charles; Mayberg, Helen S.; Hu, Xiaoping P.

    2009-01-01

    The extension of group-level connectivity methods to individual subjects remains a hurdle for statistical analyses of neuroimaging data. Previous group analyses of positron emission tomography data in clinically depressed patients, for example, have shown that resting-state connectivity prior to therapy predicts how patients eventually respond to pharmacological and cognitive-behavioral therapy. Such applications would be considerably more informative for clinical decision making if these connectivity methods could be extended into the individual subject domain. To test such an extension, 46 treatment-naïve depressed patients were enrolled in an fMRI study to model baseline resting-state functional connectivity. Resting-state fMRI scans were acquired and submitted to exploratory structural equation modeling (SEM) to derive the optimal group connectivity model. Jackknife and split sample tests confirm that group model was highly reproducible, and path weights were consistent across the best five group models. When this model was applied to data from individual subjects, 85% of patients fit the group model. Histogram analysis of individual subjects’ paths indicate that some paths are better representative of group membership. These results suggest that exploratory SEM is a viable technique for neuroimaging connectivity analyses of individual subjects’ resting-state fMRI data. PMID:19162206

  16. ψ-Epistemic models are exponentially bad at explaining the distinguishability of quantum states.

    PubMed

    Leifer, M S

    2014-04-25

    The status of the quantum state is perhaps the most controversial issue in the foundations of quantum theory. Is it an epistemic state (state of knowledge) or an ontic state (state of reality)? In realist models of quantum theory, the epistemic view asserts that nonorthogonal quantum states correspond to overlapping probability measures over the true ontic states. This naturally accounts for a large number of otherwise puzzling quantum phenomena. For example, the indistinguishability of nonorthogonal states is explained by the fact that the ontic state sometimes lies in the overlap region, in which case there is nothing in reality that could distinguish the two states. For this to work, the amount of overlap of the probability measures should be comparable to the indistinguishability of the quantum states. In this Letter, I exhibit a family of states for which the ratio of these two quantities must be ≤2de-cd in Hilbert spaces of dimension d that are divisible by 4. This implies that, for large Hilbert space dimension, the epistemic explanation of indistinguishability becomes implausible at an exponential rate as the Hilbert space dimension increases. PMID:24815627

  17. An ontological modeling approach for abnormal states and its application in the medical domain

    PubMed Central

    2014-01-01

    Background Recently, exchanging data and information has become a significant challenge in medicine. Such data include abnormal states. Establishing a unified representation framework of abnormal states can be a difficult task because of the diverse and heterogeneous nature of these states. Furthermore, in the definition of diseases found in several textbooks or dictionaries, abnormal states are not directly associated with the corresponding quantitative values of clinical test data, making the processing of such data by computers difficult. Results We focused on abnormal states in the definition of diseases and proposed a unified form to describe an abnormal state as a “property,” which can be decomposed into an “attribute” and a “value” in a qualitative representation. We have developed a three-layer ontological model of abnormal states from the generic to disease-specific level. By developing an is-a hierarchy and combining causal chains of diseases, 21,000 abnormal states from 6000 diseases have been captured as generic causal relations and commonalities have been found among diseases across 13 medical departments. Conclusions Our results showed that our representation framework promotes interoperability and flexibility of the quantitative raw data, qualitative information, and generic/conceptual knowledge of abnormal states. In addition, the results showed that our ontological model have found commonalities in abnormal states among diseases across 13 medical departments. PMID:24944781

  18. Two-state model based on the block-localized wave function method.

    PubMed

    Mo, Yirong

    2007-06-14

    The block-localized wave function (BLW) method is a variant of ab initio valence bond method but retains the efficiency of molecular orbital methods. It can derive the wave function for a diabatic (resonance) state self-consistently and is available at the Hartree-Fock (HF) and density functional theory (DFT) levels. In this work we present a two-state model based on the BLW method. Although numerous empirical and semiempirical two-state models, such as the Marcus-Hush two-state model, have been proposed to describe a chemical reaction process, the advantage of this BLW-based two-state model is that no empirical parameter is required. Important quantities such as the electronic coupling energy, structural weights of two diabatic states, and excitation energy can be uniquely derived from the energies of two diabatic states and the adiabatic state at the same HF or DFT level. Two simple examples of formamide and thioformamide in the gas phase and aqueous solution were presented and discussed. The solvation of formamide and thioformamide was studied with the combined ab initio quantum mechanical and molecular mechanical Monte Carlo simulations, together with the BLW-DFT calculations and analyses. Due to the favorable solute-solvent electrostatic interaction, the contribution of the ionic resonance structure to the ground state of formamide and thioformamide significantly increases, and for thioformamide the ionic form is even more stable than the covalent form. Thus, thioformamide in aqueous solution is essentially ionic rather than covalent. Although our two-state model in general underestimates the electronic excitation energies, it can predict relative solvatochromic shifts well. For instance, the intense pi-->pi* transition for formamide upon solvation undergoes a redshift of 0.3 eV, compared with the experimental data (0.40-0.5 eV). PMID:17581041

  19. Spin-glass model predicts metastable brain states that diminish in anesthesia

    PubMed Central

    Hudetz, Anthony G.; Humphries, Colin J.; Binder, Jeffrey R.

    2014-01-01

    Patterns of resting state connectivity change dynamically and may represent modes of cognitive information processing. The diversity of connectivity patterns (global brain states) reflects the information capacity of the brain and determines the state of consciousness. In this work, computer simulation was used to explore the repertoire of global brain states as a function of cortical activation level. We implemented a modified spin glass model to describe UP/DOWN state transitions of neuronal populations at a mesoscopic scale based on resting state BOLD fMRI data. Resting state fMRI was recorded in 20 participants and mapped to 10,000 cortical regions (sites) defined on a group-aligned cortical surface map. Each site represented the population activity of a ~20 mm2 area of the cortex. Cross-correlation matrices of the mapped BOLD time courses of the set of sites were calculated and averaged across subjects. In the model, each cortical site was allowed to interact with the 16 other sites that had the highest pair-wise correlation values. All sites stochastically transitioned between UP and DOWN states under the net influence of their 16 pairs. The probability of local state transitions was controlled by a single parameter T corresponding to the level of global cortical activation. To estimate the number of distinct global states, first we ran 10,000 simulations at T = 0. Simulations were started from random configurations that converged to one of several distinct patterns. Using hierarchical clustering, at 99% similarity, close to 300 distinct states were found. At intermediate T, metastable state configurations were formed suggesting critical behavior with a sharp increase in the number of metastable states at an optimal T. Both reduced activation (anesthesia, sleep) and increased activation (hyper-activation) moved the system away from equilibrium, presumably incompatible with conscious mentation. During equilibrium, the diversity of large-scale brain states was

  20. Analytic State Space Model for an Unsteady Finite-Span Wing

    NASA Astrophysics Data System (ADS)

    Izraelevitz, Jacob; Zhu, Qiang; Triantafyllou, Michael

    2015-11-01

    Real-time control of unsteady flows, such as force control in flapping wings, requires simple wake models that easily translate into robust control designs. We analytically derive a state-space model for the unsteady trailing vortex system behind a finite aspect-ratio flapping wing. Contrary to prior models, the downwash and lift distributions over the span can be arbitrary, including tip effects. The wake vorticity is assumed to be a fully unsteady distribution, with the exception of quasi-steady (no rollup) geometry. Each discretization along the span has one to four states to represent the local unsteady wake-induced downwash, lift, and circulation. The model supports independently time-varying velocity, heave, and twist along the span. We validate this state-space model through comparison with existing analytic solutions for elliptic wings and an unsteady inviscid panel method.

  1. Steady-state solutions of a diffusive energy-balance climate model and their stability

    NASA Technical Reports Server (NTRS)

    Ghil, M.

    1975-01-01

    A diffusive energy-balance climate model, governed by a nonlinear parabolic partial differential equation, was studied. Three positive steady-state solutions of this equation are found; they correspond to three possible climates of our planet: an interglacial (nearly identical to the present climate), a glacial, and a completely ice-covered earth. Models similar to the main one are considered, and the number of their steady states was determined. All the models have albedo continuously varying with latitude and temperature, and entirely diffusive horizontal heat transfer. The stability under small perturbations of the main model's climates was investigated. A stability criterion is derived, and its application shows that the present climate and the deep freeze are stable, whereas the model's glacial is unstable. The dependence was examined of the number of steady states and of their stability on the average solar radiation.

  2. Charge state evolution in the solar wind. III. Model comparison with observations

    SciTech Connect

    Landi, E.; Oran, R.; Lepri, S. T.; Zurbuchen, T. H.; Fisk, L. A.; Van der Holst, B.

    2014-08-01

    We test three theoretical models of the fast solar wind with a set of remote sensing observations and in-situ measurements taken during the minimum of solar cycle 23. First, the model electron density and temperature are compared to SOHO/SUMER spectroscopic measurements. Second, the model electron density, temperature, and wind speed are used to predict the charge state evolution of the wind plasma from the source regions to the freeze-in point. Frozen-in charge states are compared with Ulysses/SWICS measurements at 1 AU, while charge states close to the Sun are combined with the CHIANTI spectral code to calculate the intensities of selected spectral lines, to be compared with SOHO/SUMER observations in the north polar coronal hole. We find that none of the theoretical models are able to completely reproduce all observations; namely, all of them underestimate the charge state distribution of the solar wind everywhere, although the levels of disagreement vary from model to model. We discuss possible causes of the disagreement, namely, uncertainties in the calculation of the charge state evolution and of line intensities, in the atomic data, and in the assumptions on the wind plasma conditions. Last, we discuss the scenario where the wind is accelerated from a region located in the solar corona rather than in the chromosphere as assumed in the three theoretical models, and find that a wind originating from the corona is in much closer agreement with observations.

  3. A one-step-ahead pseudo-DIC for comparison of Bayesian state-space models.

    PubMed

    Millar, R B; McKechnie, S

    2014-12-01

    In the context of state-space modeling, conventional usage of the deviance information criterion (DIC) evaluates the ability of the model to predict an observation at time t given the underlying state at time t. Motivated by the failure of conventional DIC to clearly choose between competing multivariate nonlinear Bayesian state-space models for coho salmon population dynamics, and the computational challenge of alternatives, this work proposes a one-step-ahead DIC, DICp, where prediction is conditional on the state at the previous time point. Simulations revealed that DICp worked well for choosing between state-space models with different process or observation equations. In contrast, conventional DIC could be grossly misleading, with a strong preference for the wrong model. This can be explained by its failure to account for inflated estimates of process error arising from the model mis-specification. DICp is not based on a true conditional likelihood, but is shown to have interpretation as a pseudo-DIC in which the compensatory behavior of the inflated process errors is eliminated. It can be easily calculated using the DIC monitors within popular BUGS software when the process and observation equations are conjugate. The improved performance of DICp is demonstrated by application to the multi-stage modeling of coho salmon abundance in Lobster Creek, Oregon. PMID:25370730

  4. Charge State Evolution in the Solar Wind. III. Model Comparison with Observations

    NASA Astrophysics Data System (ADS)

    Landi, E.; Oran, R.; Lepri, S. T.; Zurbuchen, T. H.; Fisk, L. A.; van der Holst, B.

    2014-08-01

    We test three theoretical models of the fast solar wind with a set of remote sensing observations and in-situ measurements taken during the minimum of solar cycle 23. First, the model electron density and temperature are compared to SOHO/SUMER spectroscopic measurements. Second, the model electron density, temperature, and wind speed are used to predict the charge state evolution of the wind plasma from the source regions to the freeze-in point. Frozen-in charge states are compared with Ulysses/SWICS measurements at 1 AU, while charge states close to the Sun are combined with the CHIANTI spectral code to calculate the intensities of selected spectral lines, to be compared with SOHO/SUMER observations in the north polar coronal hole. We find that none of the theoretical models are able to completely reproduce all observations; namely, all of them underestimate the charge state distribution of the solar wind everywhere, although the levels of disagreement vary from model to model. We discuss possible causes of the disagreement, namely, uncertainties in the calculation of the charge state evolution and of line intensities, in the atomic data, and in the assumptions on the wind plasma conditions. Last, we discuss the scenario where the wind is accelerated from a region located in the solar corona rather than in the chromosphere as assumed in the three theoretical models, and find that a wind originating from the corona is in much closer agreement with observations.

  5. Observational constraints on cosmological models with Chaplygin gas and quadratic equation of state

    NASA Astrophysics Data System (ADS)

    Sharov, G. S.

    2016-06-01

    Observational manifestations of accelerated expansion of the universe, in particular, recent data for Type Ia supernovae, baryon acoustic oscillations, for the Hubble parameter H(z) and cosmic microwave background constraints are described with different cosmological models. We compare the ΛCDM, the models with generalized and modified Chaplygin gas and the model with quadratic equation of state. For these models we estimate optimal model parameters and their permissible errors with different approaches to calculation of sound horizon scale rs(zd). Among the considered models the best value of χ2 is achieved for the model with quadratic equation of state, but it has 2 additional parameters in comparison with the ΛCDM and therefore is not favored by the Akaike information criterion.

  6. Unified description of 0+ states in a large class of nuclear collective models.

    PubMed

    Bonatsos, Dennis; McCutchan, E A; Casten, R F

    2008-07-11

    A remarkably simple regularity in the energies of 0+ states in a broad class of collective models is discussed. A single formula for all 0+ states in flat-bottomed infinite potentials that depends only on the number of dimensions and a simpler expression applicable to all three interacting boson approximation symmetries in the large N(B) limit are presented. Finally, a connection between the energy expression for 0+ states given by the X5 model and the predictions of the interacting boson approximation near the critical point of the first order phase transition is explored. PMID:18764176

  7. Quantitative, steady-state properties of Catania's computational model of the operant reserve.

    PubMed

    Berg, John P; McDowell, J J

    2011-05-01

    Catania (2005) found that a computational model of the operant reserve (Skinner, 1938) produced realistic behavior in initial, exploratory analyses. Although Catania's operant reserve computational model demonstrated potential to simulate varied behavioral phenomena, the model was not systematically tested. The current project replicated and extended the Catania model, clarified its capabilities through systematic testing, and determined the extent to which it produces behavior corresponding to matching theory. Significant departures from both classic and modern matching theory were found in behavior generated by the model across all conditions. The results suggest that a simple, dynamic operant model of the reflex reserve does not simulate realistic steady state behavior. PMID:21238552

  8. Modeling the Effects of Irrigation on Land Surface Fluxes and States over the Conterminous United States: Sensitivity to Input Data and Model Parameters

    SciTech Connect

    Leng, Guoyong; Huang, Maoyi; Tang, Qiuhong; Sacks, William J.; Lei, Huimin; Leung, Lai-Yung R.

    2013-09-16

    Previous studies on irrigation impacts on land surface fluxes/states were mainly conducted as sensitivity experiments, with limited analysis of uncertainties from the input data and model irrigation schemes used. In this study, we calibrated and evaluated the performance of irrigation water use simulated by the Community Land Model version 4 (CLM4) against observations from agriculture census. We investigated the impacts of irrigation on land surface fluxes and states over the conterminous United States (CONUS) and explored possible directions of improvement. Specifically, we found large uncertainty in the irrigation area data from two widely used sources and CLM4 tended to produce unrealistically large temporal variations of irrigation demand for applications at the water resources region scale over CONUS. At seasonal to interannual time scales, the effects of irrigation on surface energy partitioning appeared to be large and persistent, and more pronounced in dry than wet years. Even with model calibration to yield overall good agreement with the irrigation amounts from the National Agricultural Statistics Service (NASS), differences between the two irrigation area datasets still dominate the differences in the interannual variability of land surface response to irrigation. Our results suggest that irrigation amount simulated by CLM4 can be improved by (1) calibrating model parameter values to account for regional differences in irrigation demand and (2) accurate representation of the spatial distribution and intensity of irrigated areas.

  9. Density-dependent state-space model for population-abundance data with unequal time intervals.

    PubMed

    Dennis, Brian; Ponciano, José Miguel

    2014-08-01

    The Gompertz state-space (GSS) model is a stochastic model for analyzing time-series observations of population abundances. The GSS model combines density dependence, environmental process noise, and observation error toward estimating quantities of interest in biological monitoring and population viability analysis. However, existing methods for estimating the model parameters apply only to population data with equal time intervals between observations. In the present paper, we extend the GSS model to data with unequal time intervals, by embedding it within a state-space version of the Ornstein-Uhlenbeck process, a continuous-time model of an equilibrating stochastic system. Maximum likelihood and restricted maximum likelihood calculations for the Ornstein-Uhlenbeck state-space model involve only numerical maximization of an explicit multivariate normal likelihood, and so the extension allows for easy bootstrapping, yielding confidence intervals for model parameters, statistical hypothesis testing of density dependence, and selection among sub-models using information criteria. Ecologists and managers previously drawn to models lacking density dependence or observation error because such models accommodated unequal time intervals (for example, due to missing data) now have an alternative analysis framework incorporating density dependence, process noise, and observation error. PMID:25230459

  10. Density dependent state space model for population abundance data with unequal time intervals

    PubMed Central

    Dennis, Brian; Ponciano, José Miguel

    2014-01-01

    The Gompertz state-space (GSS) model is a stochastic model for analyzing time series observations of population abundances. The GSS model combines density dependence, environmental process noise, and observation error toward estimating quantities of interest in biological monitoring and population viability analysis. However, existing methods for estimating the model parameters apply only to population data with equal time intervals between observations. In the present paper, we extend the GSS model to data with unequal time intervals, by embedding it within a state-space version of the Ornstein-Uhlenbeck process, a continuous-time model of an equilibrating stochastic system. Maximum likelihood and restricted maximum likelihood calculations for the Ornstein-Uhlenbeck state-space model involve only numerical maximization of an explicit multivariate normal likelihood, and so the extension allows for easy bootstrapping, yielding confidence intervals for model parameters, statistical hypothesis testing of density dependence, and selection among sub-models using information criteria. Ecologists and managers previously drawn to models lacking density dependence or observation error because such models accommodated unequal time intervals (for example, due to missing data) now have an alternative analysis framework incorporating density dependence, process noise and observation error. PMID:25230459

  11. Turbulence Modeling Effects on the Prediction of Equilibrium States of Buoyant Shear Flows

    NASA Technical Reports Server (NTRS)

    Zhao, C. Y.; So, R. M. C.; Gatski, T. B.

    2001-01-01

    The effects of turbulence modeling on the prediction of equilibrium states of turbulent buoyant shear flows were investigated. The velocity field models used include a two-equation closure, a Reynolds-stress closure assuming two different pressure-strain models and three different dissipation rate tensor models. As for the thermal field closure models, two different pressure-scrambling models and nine different temperature variance dissipation rate, Epsilon(0) equations were considered. The emphasis of this paper is focused on the effects of the Epsilon(0)-equation, of the dissipation rate models, of the pressure-strain models and of the pressure-scrambling models on the prediction of the approach to equilibrium turbulence. Equilibrium turbulence is defined by the time rate (if change of the scaled Reynolds stress anisotropic tensor and heat flux vector becoming zero. These conditions lead to the equilibrium state parameters. Calculations show that the Epsilon(0)-equation has a significant effect on the prediction of the approach to equilibrium turbulence. For a particular Epsilon(0)-equation, all velocity closure models considered give an equilibrium state if anisotropic dissipation is accounted for in one form or another in the dissipation rate tensor or in the Epsilon(0)-equation. It is further found that the models considered for the pressure-strain tensor and the pressure-scrambling vector have little or no effect on the prediction of the approach to equilibrium turbulence.

  12. Divergent projections of future land use in the United States arising from different models and scenarios

    USGS Publications Warehouse

    Sohl, Terry L.; Wimberly, Michael; Radeloff, Volker C.; Theobald, David M.; Sleeter, Benjamin M.

    2016-01-01

    A variety of land-use and land-cover (LULC) models operating at scales from local to global have been developed in recent years, including a number of models that provide spatially explicit, multi-class LULC projections for the conterminous United States. This diversity of modeling approaches raises the question: how consistent are their projections of future land use? We compared projections from six LULC modeling applications for the United States and assessed quantitative, spatial, and conceptual inconsistencies. Each set of projections provided multiple scenarios covering a period from roughly 2000 to 2050. Given the unique spatial, thematic, and temporal characteristics of each set of projections, individual projections were aggregated to a common set of basic, generalized LULC classes (i.e., cropland, pasture, forest, range, and urban) and summarized at the county level across the conterminous United States. We found very little agreement in projected future LULC trends and patterns among the different models. Variability among scenarios for a given model was generally lower than variability among different models, in terms of both trends in the amounts of basic LULC classes and their projected spatial patterns. Even when different models assessed the same purported scenario, model projections varied substantially. Projections of agricultural trends were often far above the maximum historical amounts, raising concerns about the realism of the projections. Comparisons among models were hindered by major discrepancies in categorical definitions, and suggest a need for standardization of historical LULC data sources. To capture a broader range of uncertainties, ensemble modeling approaches are also recommended. However, the vast inconsistencies among LULC models raise questions about the theoretical and conceptual underpinnings of current modeling approaches. Given the substantial effects that land-use change can have on ecological and societal processes, there

  13. Recognition of human activity characteristics based on state transitions modeling technique

    NASA Astrophysics Data System (ADS)

    Elangovan, Vinayak; Shirkhodaie, Amir

    2012-06-01

    Human Activity Discovery & Recognition (HADR) is a complex, diverse and challenging task but yet an active area of ongoing research in the Department of Defense. By detecting, tracking, and characterizing cohesive Human interactional activity patterns, potential threats can be identified which can significantly improve situation awareness, particularly, in Persistent Surveillance Systems (PSS). Understanding the nature of such dynamic activities, inevitably involves interpretation of a collection of spatiotemporally correlated activities with respect to a known context. In this paper, we present a State Transition model for recognizing the characteristics of human activities with a link to a prior contextbased ontology. Modeling the state transitions between successive evidential events determines the activities' temperament. The proposed state transition model poses six categories of state transitions including: Human state transitions of Object handling, Visibility, Entity-entity relation, Human Postures, Human Kinematics and Distance to Target. The proposed state transition model generates semantic annotations describing the human interactional activities via a technique called Casual Event State Inference (CESI). The proposed approach uses a low cost kinect depth camera for indoor and normal optical camera for outdoor monitoring activities. Experimental results are presented here to demonstrate the effectiveness and efficiency of the proposed technique.

  14. Ground-state energies of the nonlinear sigma model and the Heisenberg spin chains

    NASA Technical Reports Server (NTRS)

    Zhang, Shoucheng; Schulz, H. J.; Ziman, Timothy

    1989-01-01

    A theorem on the O(3) nonlinear sigma model with the topological theta term is proved, which states that the ground-state energy at theta = pi is always higher than the ground-state energy at theta = 0, for the same value of the coupling constant g. Provided that the nonlinear sigma model gives the correct description for the Heisenberg spin chains in the large-s limit, this theorem makes a definite prediction relating the ground-state energies of the half-integer and the integer spin chains. The ground-state energies obtained from the exact Bethe ansatz solution for the spin-1/2 chain and the numerical diagonalization on the spin-1, spin-3/2, and spin-2 chains support this prediction.

  15. Constraints of artificial neural networks for rainfall-runoff modelling: trade-offs in hydrological state representation and model evaluation

    NASA Astrophysics Data System (ADS)

    de Vos, N. J.; Rientjes, T. H. M.

    2005-07-01

    The application of Artificial Neural Networks (ANNs) in rainfall-runoff modelling needs to be researched more extensively in order to appreciate and fulfil the potential of this modelling approach. This paper reports on the application of multi-layer feedforward ANNs for rainfall-runoff modelling of the Geer catchment (Belgium) using both daily and hourly data. The daily forecast results indicate that ANNs can be considered good alternatives for traditional rainfall-runoff modelling approaches, but the simulations based on hourly data reveal timing errors as a result of a dominating autoregressive component. This component is introduced in model simulations by using previously observed runoff values as ANN model input, which is a popular method for indirectly representing the hydrological state of a catchment. Two possible solutions to this problem of lagged predictions are presented. Firstly, several alternatives for representation of the hydrological state are tested as ANN inputs: moving averages over time of observed discharges and rainfall, and the output of the simple GR4J model component for soil moisture. A combination of these hydrological state representers produces good results in terms of timing, but the overall goodness of fit is not as good as the simulations with previous runoff data. Secondly, the possibility of using multiple measures of model performance during ANN training is mentioned.

  16. Theoretical study of the position of the transition state for unimolecular reactions: an entropy model

    NASA Astrophysics Data System (ADS)

    Zou, Jian-Wei; Chen, Wei-Chen; Kao, Che-Lun; Yu, Chin-Hui

    2004-01-01

    An entropy model that can be used to quantitatively estimate the position of the transition state for unimolecular reaction is presented. A series of 12 isomeric reactions have been investigated to validate this model. It has been shown that the position of the transition state predicted by the entropy model ( χS≠) is qualitatively consistent with the Hammond postulate (HP) except for the isomerizations of FSSF and CH 3SH. The inconsistency for these two reactions may be well ascribed to the dissociated character of their transition states that would lead to the entropy deviating from a normal unimolecular behavior. Comparisons of χS≠ values with other quantities characterizing the position of the transition state have also been made.

  17. Optimal dosing of cancer chemotherapy using model predictive control and moving horizon state/parameter estimation.

    PubMed

    Chen, Tao; Kirkby, Norman F; Jena, Raj

    2012-12-01

    Model predictive control (MPC), originally developed in the community of industrial process control, is a potentially effective approach to optimal scheduling of cancer therapy. The basis of MPC is usually a state-space model (a system of ordinary differential equations), whereby existing studies usually assume that the entire states can be directly measured. This paper aims to demonstrate that when the system states are not fully measurable, in conjunction with model parameter discrepancy, MPC is still a useful method for cancer treatment. This aim is achieved through the application of moving horizon estimation (MHE), an optimisation-based method to jointly estimate the system states and parameters. The effectiveness of the MPC-MHE scheme is illustrated through scheduling the dose of tamoxifen for simulated tumour-bearing patients, and the impact of estimation horizon and magnitude of parameter discrepancy is also investigated. PMID:22739208

  18. Solvable four-state Landau-Zener model of two interacting qubits with path interference

    NASA Astrophysics Data System (ADS)

    Sinitsyn, N. A.

    2015-11-01

    I identify a nontrivial four-state Landau-Zener model for which transition probabilities between any pair of diabatic states can be determined analytically and exactly. The model describes an experimentally accessible system of two interacting qubits, such as a localized state in a Dirac material with both valley and spin degrees of freedom or a singly charged quantum dot (QD) molecule with spin orbit coupling. Application of the linearly time-dependent magnetic field induces a sequence of quantum level crossings with possibility of interference of different trajectories in a semiclassical picture. I argue that this system satisfies the criteria of integrability in the multistate Landau-Zener theory, which allows one to derive explicit exact analytical expressions for the transition probability matrix. I also argue that this model is likely a special case of a larger class of solvable systems, and present a six-state generalization as an example.

  19. A multi-state model approach for prediction in chronic myeloid leukaemia.

    PubMed

    Lauseker, Michael; Hasford, Joerg; Hoffmann, Verena S; Müller, Martin C; Hehlmann, Rüdiger; Pfirrmann, Markus

    2015-06-01

    Multi-state models support prediction in medicine. With different states of disease, chronic myeloid leukaemia (CML) is particularly suited for the application of multi-state models. In this article, we tried to find a model for CML that allows predicting the prevalence of three different states (initial state of disease, remission and progression) in dependence on treatment, adjusted for age, sex and risk score. Based on the German CML Study IV, one of the largest randomised studies in CML, the model was able to represent the known effects of age and risk score on the probabilities of remission and progression. Patients achieving a major molecular remission had a better chance of surviving without progression, but this effect was not significant. Comparing treatments, patient of the high-dose arm had the greatest chance to be in the state "remission" at 5 years but did not seem to have an advantage considering "progression". The proposed illness-death model can be useful for predicting the course of CML based on the patient's individual covariates (trial registration: this is an explorative analysis of ClinicalTrials.gov Identifier: NCT00055874). PMID:25465231

  20. Chimera states in a Hodgkin-Huxley model of thermally sensitive neurons.

    PubMed

    Glaze, Tera A; Lewis, Scott; Bahar, Sonya

    2016-08-01

    Chimera states occur when identically coupled groups of nonlinear oscillators exhibit radically different dynamics, with one group exhibiting synchronized oscillations and the other desynchronized behavior. This dynamical phenomenon has recently been studied in computational models and demonstrated experimentally in mechanical, optical, and chemical systems. The theoretical basis of these states is currently under active investigation. Chimera behavior is of particular relevance in the context of neural synchronization, given the phenomenon of unihemispheric sleep and the recent observation of asymmetric sleep in human patients with sleep apnea. The similarity of neural chimera states to neural "bump" states, which have been suggested as a model for working memory and visual orientation tuning in the cortex, adds to their interest as objects of study. Chimera states have been demonstrated in the FitzHugh-Nagumo model of excitable cells and in the Hindmarsh-Rose neural model. Here, we demonstrate chimera states and chimera-like behaviors in a Hodgkin-Huxley-type model of thermally sensitive neurons both in a system with Abrams-Strogatz (mean field) coupling and in a system with Kuramoto (distance-dependent) coupling. We map the regions of parameter space for which chimera behavior occurs in each of the two coupling schemes. PMID:27586615

  1. General three-state model with biased population replacement: Analytical solution and application to language dynamics

    NASA Astrophysics Data System (ADS)

    Colaiori, Francesca; Castellano, Claudio; Cuskley, Christine F.; Loreto, Vittorio; Pugliese, Martina; Tria, Francesca

    2015-01-01

    Empirical evidence shows that the rate of irregular usage of English verbs exhibits discontinuity as a function of their frequency: the most frequent verbs tend to be totally irregular. We aim to qualitatively understand the origin of this feature by studying simple agent-based models of language dynamics, where each agent adopts an inflectional state for a verb and may change it upon interaction with other agents. At the same time, agents are replaced at some rate by new agents adopting the regular form. In models with only two inflectional states (regular and irregular), we observe that either all verbs regularize irrespective of their frequency, or a continuous transition occurs between a low-frequency state, where the lemma becomes fully regular, and a high-frequency one, where both forms coexist. Introducing a third (mixed) state, wherein agents may use either form, we find that a third, qualitatively different behavior may emerge, namely, a discontinuous transition in frequency. We introduce and solve analytically a very general class of three-state models that allows us to fully understand these behaviors in a unified framework. Realistic sets of interaction rules, including the well-known naming game (NG) model, result in a discontinuous transition, in agreement with recent empirical findings. We also point out that the distinction between speaker and hearer in the interaction has no effect on the collective behavior. The results for the general three-state model, although discussed in terms of language dynamics, are widely applicable.

  2. A non-local, ordinary-state-based viscoelasticity model for peridynamics.

    SciTech Connect

    Mitchell, John Anthony

    2011-10-01

    A non-local, ordinary-state-based, peridynamics viscoelasticity model is developed. In this model, viscous effects are added to deviatoric deformations and the bulk response remains elastic. The model uses internal state variables and is conceptually similar to linearized isotropic viscolelasticity in the local theory. The modulus state, which is used to form the Jacobian matrix in Newton-Raphson algorithms, is presented. The model is shown to satisfy the 2nd law of thermodynamics and is applicable to problems in solid continuum mechanics where fracture and rate effects are important; it inherits all the advantages for modeling fracture associated with peridynamics. By combining this work with the previously published ordinary-state-based plasticity model, the model may be amenable to viscoplasticity problems where plasticity and rate effects are simultaneously important. Also, the model may be extended to include viscous effects for spherical deformations as well. The later two extensions are not presented and may be the subject of further work.

  3. Modeling Quality-Adjusted Life Expectancy Loss Resulting from Tobacco Use in the United States

    ERIC Educational Resources Information Center

    Kaplan, Robert M.; Anderson, John P.; Kaplan, Cameron M.

    2007-01-01

    Purpose: To describe the development of a model for estimating the effects of tobacco use upon Quality Adjusted Life Years (QALYs) and to estimate the impact of tobacco use on health outcomes for the United States (US) population using the model. Method: We obtained estimates of tobacco consumption from 6 years of the National Health Interview…

  4. Cross-State Comparisons of Former Special Education Students: Evaluation of a Follow-Along Model.

    ERIC Educational Resources Information Center

    Darrow, Melissa A.; Clark, Gary M.

    1992-01-01

    This study determined whether experts in special education transition services perceived a need for a common theoretical model and core set of outcome variables for follow-along research at the state level, evaluated a model for use in follow-along studies, and suggested research questions to be measured in a common format across statewide…

  5. A Predictive Model for Migrant Farmworker Movement in the United States.

    ERIC Educational Resources Information Center

    Davis, Benjamin G.

    Since migration is strongly influenced by economic variables, an economic model was developed to identify, locate, and track migrant and seasonal farmworkers as they move throughout the United States. Focusing on the Florida-based migrant agricultural workers who migrated at least once during the past five years, the model included the following…

  6. Exploring Solid-State Structure and Physical Properties: A Molecular and Crystal Model Exercise

    ERIC Educational Resources Information Center

    Bindel, Thomas H.

    2008-01-01

    A crystal model laboratory exercise is presented that allows students to examine relations among the microscopic-macroscopic-symbolic levels, using crystalline mineral samples and corresponding crystal models. Students explore the relationship between solid-state structure and crystal form. Other structure-property relationships are explored. The…

  7. States-of-Mind Model: Cognitive Balance in the Treatment of Agoraphobia.

    ERIC Educational Resources Information Center

    Schwartz, Robert M.; Michelson, Larry

    1987-01-01

    Used states-of-mind model to track therapeutic changes in cognitive balance of 39 agoraphobics. Descriptive and statistical analyses from an outcome study of graduated exposure, relaxation training, and paradoxical intention supported the model. Agoraphobics evinced negative dialogue at pretreatment, positive dialogue at mid and posttreatment, and…

  8. The Sustainability of Comprehensive School Reform Models in Changing District and State Contexts

    ERIC Educational Resources Information Center

    Datnow, Amanda

    2005-01-01

    This article addresses the sustainability of comprehensive school reform (CSR) models in the face of turbulent district and state contexts. It draws on qualitative data gathered in a longitudinal case study of six CSR models implemented in 13 schools in one urban district. Why do reforms sustain in some schools and not in others? How do changing…

  9. Longitudinal Stability of the Beck Depression Inventory II: A Latent Trait-State-Occasion Model

    ERIC Educational Resources Information Center

    Wu, Pei-Chen

    2016-01-01

    In a six-wave longitudinal study with two cohorts (660 adolescents and 630 young adults), this study investigated the longitudinal stability of the Beck Depression Inventory II (BDI-II) using the Trait-State-Occasion (TSO) model. The results revealed that the full TSO model was the best fitting representation of the depression measured by the…

  10. Mathematical modeling of a Ti:sapphire solid-state laser

    NASA Technical Reports Server (NTRS)

    Swetits, John J.

    1987-01-01

    The project initiated a study of a mathematical model of a tunable Ti:sapphire solid-state laser. A general mathematical model was developed for the purpose of identifying design parameters which will optimize the system, and serve as a useful predictor of the system's behavior.

  11. Massless ground state for a compact SU (2) matrix model in 4D

    NASA Astrophysics Data System (ADS)

    Boulton, Lyonell; Garcia del Moral, Maria Pilar; Restuccia, Alvaro

    2015-09-01

    We show the existence and uniqueness of a massless supersymmetric ground state wavefunction of a SU (2) matrix model in a bounded smooth domain with Dirichlet boundary conditions. This is a gauge system and we provide a new framework to analyze the quantum spectral properties of this class of supersymmetric matrix models subject to constraints which can be generalized for arbitrary number of colors.

  12. The longevity of Jacques Friedel's model of the virtual bound state

    NASA Astrophysics Data System (ADS)

    Levy, Peter M.; Fert, Albert

    2016-03-01

    We illustrate the continuing pertinence of Friedel's model of the virtual bound state to describe electron scattering in metals. This model has been applied to such disparate studies as the chirality of spin interactions in metals, and the spin Hall effect caused by scattering from impurities with spin-orbit coupling. xml:lang="fr"

  13. Technical Assistance Model for Long-Term Systems Change: Three State Examples

    ERIC Educational Resources Information Center

    Kasprzak, Christina; Hurth, Joicey; Lucas, Anne; Marshall, Jacqueline; Terrell, Adriane; Jones, Elizabeth

    2010-01-01

    The National Early Childhood Technical Assistance Center (NECTAC) Technical Assistance (TA) Model for Long-Term Systems Change (LTSC) is grounded in conceptual frameworks in the literature on systems change and systems thinking. The NECTAC conceptual framework uses a logic model approach to change developed specifically for states' infant and…

  14. User's instructions for the 41-node thermoregulatory model (steady state version)

    NASA Technical Reports Server (NTRS)

    Leonard, J. I.

    1974-01-01

    A user's guide for the steady-state thermoregulatory model is presented. The model was modified to provide conversational interaction on a remote terminal, greater flexibility for parameter estimation, increased efficiency of convergence, greater choice of output variable and more realistic equations for respiratory and skin diffusion water losses.

  15. State-and-transition model archetypes: a global taxonomy of rangeland change

    Technology Transfer Automated Retrieval System (TEKTRAN)

    State and transition models (STMs) synthesize science-based and local knowledge to formally represent the dynamics of rangeland and other ecosystems. Mental models or concepts of ecosystem dynamics implicitly underlie all management decisions in rangelands and thus how people influence rangeland sus...

  16. DEMOS: state-of-the-art application software for design, evaluation, and modeling of optical systems

    NASA Astrophysics Data System (ADS)

    Gan, Michael A.; Zhdanov, Dmitriy D.; Novoselskiy, Vadim V.; Ustinov, Sergey I.; Fedorov, Alexander O.; Potyemin, Igor S.

    1992-04-01

    A new version of the DEMOS program is presented. DEMOS (design, evaluation, and modeling of optical systems) is integrated dialog software for automatic modeling to estimate and design optical systems with conventional and hologram optical elements. The theoretical principles and the current state of the primary possibilities and application principles of the DEMOS program for optical systems design and simulation on computers are discussed.

  17. A Model for Creating Engaged Land-Grant Universities: Penn State's Engagement Ladder Model

    ERIC Educational Resources Information Center

    Aronson, Keith R.; Webster, Nicole

    2007-01-01

    The original mission of the state and land-grant university was to engage with communities to solve problems and improve the quality of life for the citizenry. Today most state and land-grant universities have moved far away from their original mission and are struggling to become engaged with the communities they serve. In this case study, we…

  18. Multi-State Physics Models of Aging Passive Components in Probabilistic Risk Assessment

    SciTech Connect

    Unwin, Stephen D.; Lowry, Peter P.; Layton, Robert F.; Heasler, Patrick G.; Toloczko, Mychailo B.

    2011-03-13

    Multi-state Markov modeling has proved to be a promising approach to estimating the reliability of passive components - particularly metallic pipe components - in the context of probabilistic risk assessment (PRA). These models consider the progressive degradation of a component through a series of observable discrete states, such as detectable flaw, leak and rupture. Service data then generally provides the basis for estimating the state transition rates. Research in materials science is producing a growing understanding of the physical phenomena that govern the aging degradation of passive pipe components. As a result, there is an emerging opportunity to incorporate these insights into PRA. This paper describes research conducted under the Risk-Informed Safety Margin Characterization Pathway of the Department of Energy’s Light Water Reactor Sustainability Program. A state transition model is described that addresses aging behavior associated with stress corrosion cracking in ASME Class 1 dissimilar metal welds – a component type relevant to LOCA analysis. The state transition rate estimates are based on physics models of weld degradation rather than service data. The resultant model is found to be non-Markov in that the transition rates are time-inhomogeneous and stochastic. Numerical solutions to the model provide insight into the effect of aging on component reliability.

  19. A five states survivability model for missions with ground-to-air threats

    NASA Astrophysics Data System (ADS)

    Erlandsson, Tina; Niklasson, Lars

    2013-05-01

    Fighter pilots are exposed to the risk of getting hit by enemy fire when flying missions with ground-to-air threats. A tactical support system including a survivability model could aid the pilot to assess and handle this risk. The survivability model presented here is a Markov model with five states; Undetected, Detected, Tracked, Engaged and Hit. The output from the model is the probabilities that the aircraft is in these states during the mission. The enemy's threat systems are represented with sensor and weapon areas and the transitions between the states depend on whether or not the aircraft is within any of these areas. Contrary to previous work, the model can capture the behaviors that the enemy's sensor systems communicate and that the risk of getting hit depends on the enemy's knowledge regarding the aircraft's kinematics. The paper includes a discussion regarding the interpretation of the states and the factors that influence the transitions between the states. Further developments are also identified for using the model to aid fighter pilots and operators of unmanned aerial vehicles with planning and evaluating missions as well as analyzing the situation during flight.

  20. Steady-state analysis of activated sludge processes with a settler model including sludge compression.

    PubMed

    Diehl, S; Zambrano, J; Carlsson, B

    2016-01-01

    A reduced model of a completely stirred-tank bioreactor coupled to a settling tank with recycle is analyzed in its steady states. In the reactor, the concentrations of one dominant particulate biomass and one soluble substrate component are modelled. While the biomass decay rate is assumed to be constant, growth kinetics can depend on both substrate and biomass concentrations, and optionally model substrate inhibition. Compressive and hindered settling phenomena are included using the Bürger-Diehl settler model, which consists of a partial differential equation. Steady-state solutions of this partial differential equation are obtained from an ordinary differential equation, making steady-state analysis of the entire plant difficult. A key result showing that the ordinary differential equation can be replaced with an approximate algebraic equation simplifies model analysis. This algebraic equation takes the location of the sludge-blanket during normal operation into account, allowing for the limiting flux capacity caused by compressive settling to easily be included in the steady-state mass balance equations for the entire plant system. This novel approach grants the possibility of more realistic solutions than other previously published reduced models, comprised of yet simpler settler assumptions. The steady-state concentrations, solids residence time, and the wastage flow ratio are functions of the recycle ratio. Solutions are shown for various growth kinetics; with different values of biomass decay rate, influent volumetric flow, and substrate concentration. PMID:26476681

  1. A macro traffic flow model accounting for real-time traffic state

    NASA Astrophysics Data System (ADS)

    Tang, Tie-Qiao; Chen, Liang; Wu, Yong-Hong; Caccetta, Lou

    2015-11-01

    In this paper, we propose a traffic flow model to study the effects of the real-time traffic state on traffic flow. The numerical results show that the proposed model can describe oscillation in traffic and stop-and-go traffic, where the speed-density relationship is qualitatively accordant with the empirical data of the Weizikeng segment of the Badaling freeway in Beijing, which means that the proposed model can qualitatively reproduce some complex traffic phenomena associated with real-time traffic state.

  2. Bayesian Path Specific Frailty Models for Multi-state Survival Data with Applications

    PubMed Central

    de Castro, Mário; Chen, Ming-Hui; Zhang, Yuanye

    2015-01-01

    Summary Multi-state models can be viewed as generalizations of both the standard and competing risks models for survival data. Models for multi-state data have been the theme of many recent published works. Motivated by bone marrow transplant data, we propose a Bayesian model using the gap times between two successive events in a path of events experienced by a subject. Path specific frailties are introduced to capture the dependence structure of the gap times in the paths with two or more states. Under improper prior distributions for the parameters, we establish propriety of the posterior distribution. An efficient Gibbs sampling algorithm is developed for drawing samples from the posterior distribution. An extensive simulation study is carried out to examine the empirical performance of the proposed approach. A bone marrow transplant data set is analyzed in detail to further demonstrate the proposed methodology. PMID:25762198

  3. Impact of the Equation of State in Models for Surfactant Spreading Experiments

    NASA Astrophysics Data System (ADS)

    Levy, Rachel

    2014-11-01

    Pulmonary surfactant spreading models often rely on an equation of state relating surfactant concentration to surface tension. Mathematically, these models have been analyzed with simple functional relationships. However, to model an experiment with a given fluid and surfactant, a physically meaningful equation of state can be derived from experimentally obtained isotherms. We discuss the comparison between model and experiment for NBD-PC lipid (surfactant) spreading on glycerol for an empirically-determined equation of state, and compare those results to simulations with traditionally employed functional forms. In particular we compare the timescales by tracking the leading edge of surfactant, the central fluid height and dynamics of the Marangoni ridge. We consider both outward spreading of a disk-shaped region of surfactant and the hole-closure problem in which a disk-shaped surfactant-free region self-heals. Support from NSF-DMS-FRG 0968154, RCSA-CCS-19788, and HHMI.

  4. Application of wheat yield model to United States and India. [Great Plains

    NASA Technical Reports Server (NTRS)

    Feyerherm, A. M. (Principal Investigator)

    1977-01-01

    The author has identified the following significant results. The wheat yield model was applied to the major wheat-growing areas of the US and India. In the US Great Plains, estimates from the winter and spring wheat models agreed closely with USDA-SRS values in years with the lowest yields, but underestimated in years with the highest yields. Application to the Eastern Plains and Northwest indicated the importance of cultural factors, as well as meteorological ones in the model. It also demonstrated that the model could be used, in conjunction with USDA-SRRS estimates, to estimate yield losses due to factors not included in the model, particularly diseases and freezes. A fixed crop calendar for India was built from a limited amount of available plot data from that country. Application of the yield model gave measurable evidence that yield variation from state to state was due to different mixes of levels of meteorological and cultural factors.

  5. Phase transitions of the q-state Potts model on multiply-laced Sierpinski gaskets

    NASA Astrophysics Data System (ADS)

    Tian, Liang; Ma, Hui; Guo, Wenan; Tang, Lei-Han

    2013-05-01

    We present an exact solution of the q-state Potts model on a class of generalized Sierpinski fractal lattices. The model is shown to possess an ordered phase at low temperatures and a continuous transition to the high temperature disordered phase at any q ≥ 1. Multicriticality is observed in the presence of a symmetry-breaking field. Exact renormalization group analysis yields the phase diagram of the model and a complete set of critical exponents at various transitions.

  6. A Comprehensive Model for Solid State Sintering and Its Application to Silicon Carbide

    NASA Astrophysics Data System (ADS)

    Riedel, H.; Blug, B.

    Previous models for partial aspects of solid state sintering and grain coarsening are combined to give a comprehensive model consisting of a set of equations. A series of sinter forging tests with a SiC powder is carried out, and the model is successfully adjusted to the experimental results. The resulting activation energy for bulk diffusion is substantially higher than activation energies reported in the literature.

  7. Squeezed States, Uncertainty Relations and the Pauli Principle in Composite and Cosmological Models

    NASA Technical Reports Server (NTRS)

    Terazawa, Hidezumi

    1996-01-01

    The importance of not only uncertainty relations but also the Pauli exclusion principle is emphasized in discussing various 'squeezed states' existing in the universe. The contents of this paper include: (1) Introduction; (2) Nuclear Physics in the Quark-Shell Model; (3) Hadron Physics in the Standard Quark-Gluon Model; (4) Quark-Lepton-Gauge-Boson Physics in Composite Models; (5) Astrophysics and Space-Time Physics in Cosmological Models; and (6) Conclusion. Also, not only the possible breakdown of (or deviation from) uncertainty relations but also the superficial violation of the Pauli principle at short distances (or high energies) in composite (and string) models is discussed in some detail.

  8. Joint state and parameter estimation of the hemodynamic model by particle smoother expectation maximization method

    NASA Astrophysics Data System (ADS)

    Aslan, Serdar; Taylan Cemgil, Ali; Akın, Ata

    2016-08-01

    Objective. In this paper, we aimed for the robust estimation of the parameters and states of the hemodynamic model by using blood oxygen level dependent signal. Approach. In the fMRI literature, there are only a few successful methods that are able to make a joint estimation of the states and parameters of the hemodynamic model. In this paper, we implemented a maximum likelihood based method called the particle smoother expectation maximization (PSEM) algorithm for the joint state and parameter estimation. Main results. Former sequential Monte Carlo methods were only reliable in the hemodynamic state estimates. They were claimed to outperform the local linearization (LL) filter and the extended Kalman filter (EKF). The PSEM algorithm is compared with the most successful method called square-root cubature Kalman smoother (SCKS) for both state and parameter estimation. SCKS was found to be better than the dynamic expectation maximization (DEM) algorithm, which was shown to be a better estimator than EKF, LL and particle filters. Significance. PSEM was more accurate than SCKS for both the state and the parameter estimation. Hence, PSEM seems to be the most accurate method for the system identification and state estimation for the hemodynamic model inversion literature. This paper do not compare its results with Tikhonov-regularized Newton—CKF (TNF-CKF), a recent robust method which works in filtering sense.

  9. Functional connectivity dynamics: modeling the switching behavior of the resting state.

    PubMed

    Hansen, Enrique C A; Battaglia, Demian; Spiegler, Andreas; Deco, Gustavo; Jirsa, Viktor K

    2015-01-15

    Functional connectivity (FC) sheds light on the interactions between different brain regions. Besides basic research, it is clinically relevant for applications in Alzheimer's disease, schizophrenia, presurgical planning, epilepsy, and traumatic brain injury. Simulations of whole-brain mean-field computational models with realistic connectivity determined by tractography studies enable us to reproduce with accuracy aspects of average FC in the resting state. Most computational studies, however, did not address the prominent non-stationarity in resting state FC, which may result in large intra- and inter-subject variability and thus preclude an accurate individual predictability. Here we show that this non-stationarity reveals a rich structure, characterized by rapid transitions switching between a few discrete FC states. We also show that computational models optimized to fit time-averaged FC do not reproduce these spontaneous state transitions and, thus, are not qualitatively superior to simplified linear stochastic models, which account for the effects of structure alone. We then demonstrate that a slight enhancement of the non-linearity of the network nodes is sufficient to broaden the repertoire of possible network behaviors, leading to modes of fluctuations, reminiscent of some of the most frequently observed Resting State Networks. Because of the noise-driven exploration of this repertoire, the dynamics of FC qualitatively change now and display non-stationary switching similar to empirical resting state recordings (Functional Connectivity Dynamics (FCD)). Thus FCD bear promise to serve as a better biomarker of resting state neural activity and of its pathologic alterations. PMID:25462790

  10. On inference of causality for discrete state models in a multiscale context

    PubMed Central

    Gerber, Susanne; Horenko, Illia

    2014-01-01

    Discrete state models are a common tool of modeling in many areas. E.g., Markov state models as a particular representative of this model family became one of the major instruments for analysis and understanding of processes in molecular dynamics (MD). Here we extend the scope of discrete state models to the case of systematically missing scales, resulting in a nonstationary and nonhomogeneous formulation of the inference problem. We demonstrate how the recently developed tools of nonstationary data analysis and information theory can be used to identify the simultaneously most optimal (in terms of describing the given data) and most simple (in terms of complexity and causality) discrete state models. We apply the resulting formalism to a problem from molecular dynamics and show how the results can be used to understand the spatial and temporal causality information beyond the usual assumptions. We demonstrate that the most optimal explanation for the appropriately discretized/coarse-grained MD torsion angles data in a polypeptide is given by the causality that is localized both in time and in space, opening new possibilities for deploying percolation theory and stochastic subgridscale modeling approaches in the area of MD. PMID:25267630

  11. Detecting critical state before phase transition of complex systems by hidden Markov model

    NASA Astrophysics Data System (ADS)

    Liu, Rui; Chen, Pei; Li, Yongjun; Chen, Luonan

    Identifying the critical state or pre-transition state just before the occurrence of a phase transition is a challenging task, because the state of the system may show little apparent change before this critical transition during the gradual parameter variations. Such dynamics of phase transition is generally composed of three stages, i.e., before-transition state, pre-transition state, and after-transition state, which can be considered as three different Markov processes. Thus, based on this dynamical feature, we present a novel computational method, i.e., hidden Markov model (HMM), to detect the switching point of the two Markov processes from the before-transition state (a stationary Markov process) to the pre-transition state (a time-varying Markov process), thereby identifying the pre-transition state or early-warning signals of the phase transition. To validate the effectiveness, we apply this method to detect the signals of the imminent phase transitions of complex systems based on the simulated datasets, and further identify the pre-transition states as well as their critical modules for three real datasets, i.e., the acute lung injury triggered by phosgene inhalation, MCF-7 human breast cancer caused by heregulin, and HCV-induced dysplasia and hepatocellular carcinoma.

  12. Mean state dependence of ENSO diversity resulting from an intermediate coupled model

    NASA Astrophysics Data System (ADS)

    Xie, Ruihuang; Jin, Fei-Fei; Mu, Mu

    2016-04-01

    ENSO diversity is referred to the event-to-event differences in the amplitude, longitudinal location of maximum sea surface temperature (SST) anomalies and evolutional mechanisms, as manifested in both observation data and climate model simulations. Previous studies argued that westerly wind burst (WWB) has strong influence on ENSO diversity. Here, we bring evidences, from a modified intermediate complexity Zebiak-Cane (ZC) coupled model, to illustrate that the ENSO diversity is also determined by the mean states. Stabilities of the linearized ZC model reveal that the mean state with weak (strong) wind stress and deep (shallow) thermocline prefers ENSO variation in the equitorial eastern (central) Pacific with a four-year (two-year) period. Weak wind stress and deep thermocline make the thermocline (TH) feedback the dominant contribution to the growth of ENSO SST anomalies, whereas the opposite mean state favors the zonal advective (ZA) feedback. Different leading dynamical SST-controller makes ENSO display its diversity. In a mean state that resembles the recent climate in the tropical Pacific, the four-year and two-year ENSO variations coexist with similar growth rate. Even without WWB forcing, the nonlinear integration results with adjusted parameters in this special mean state also present at least two types of El Niño, in which the maximum warming rates are contributed by either TH or ZA feedback. The consistency between linear and nonlinear model results indicates that the ENSO diversity is dependent on the mean states.

  13. Customized Steady-State Constraints for Parameter Estimation in Non-Linear Ordinary Differential Equation Models

    PubMed Central

    Rosenblatt, Marcus; Timmer, Jens; Kaschek, Daniel

    2016-01-01

    Ordinary differential equation models have become a wide-spread approach to analyze dynamical systems and understand underlying mechanisms. Model parameters are often unknown and have to be estimated from experimental data, e.g., by maximum-likelihood estimation. In particular, models of biological systems contain a large number of parameters. To reduce the dimensionality of the parameter space, steady-state information is incorporated in the parameter estimation process. For non-linear models, analytical steady-state calculation typically leads to higher-order polynomial equations for which no closed-form solutions can be obtained. This can be circumvented by solving the steady-state equations for kinetic parameters, which results in a linear equation system with comparatively simple solutions. At the same time multiplicity of steady-state solutions is avoided, which otherwise is problematic for optimization. When solved for kinetic parameters, however, steady-state constraints tend to become negative for particular model specifications, thus, generating new types of optimization problems. Here, we present an algorithm based on graph theory that derives non-negative, analytical steady-state expressions by stepwise removal of cyclic dependencies between dynamical variables. The algorithm avoids multiple steady-state solutions by construction. We show that our method is applicable to most common classes of biochemical reaction networks containing inhibition terms, mass-action and Hill-type kinetic equations. Comparing the performance of parameter estimation for different analytical and numerical methods of incorporating steady-state information, we show that our approach is especially well-tailored to guarantee a high success rate of optimization. PMID:27243005

  14. Customized Steady-State Constraints for Parameter Estimation in Non-Linear Ordinary Differential Equation Models.

    PubMed

    Rosenblatt, Marcus; Timmer, Jens; Kaschek, Daniel

    2016-01-01

    Ordinary differential equation models have become a wide-spread approach to analyze dynamical systems and understand underlying mechanisms. Model parameters are often unknown and have to be estimated from experimental data, e.g., by maximum-likelihood estimation. In particular, models of biological systems contain a large number of parameters. To reduce the dimensionality of the parameter space, steady-state information is incorporated in the parameter estimation process. For non-linear models, analytical steady-state calculation typically leads to higher-order polynomial equations for which no closed-form solutions can be obtained. This can be circumvented by solving the steady-state equations for kinetic parameters, which results in a linear equation system with comparatively simple solutions. At the same time multiplicity of steady-state solutions is avoided, which otherwise is problematic for optimization. When solved for kinetic parameters, however, steady-state constraints tend to become negative for particular model specifications, thus, generating new types of optimization problems. Here, we present an algorithm based on graph theory that derives non-negative, analytical steady-state expressions by stepwise removal of cyclic dependencies between dynamical variables. The algorithm avoids multiple steady-state solutions by construction. We show that our method is applicable to most common classes of biochemical reaction networks containing inhibition terms, mass-action and Hill-type kinetic equations. Comparing the performance of parameter estimation for different analytical and numerical methods of incorporating steady-state information, we show that our approach is especially well-tailored to guarantee a high success rate of optimization. PMID:27243005

  15. Stochastic Model of Gap Junctions Exhibiting Rectification and Multiple Closed States of Slow Gates.

    PubMed

    Snipas, Mindaugas; Kraujalis, Tadas; Paulauskas, Nerijus; Maciunas, Kestutis; Bukauskas, Feliksas F

    2016-03-29

    Gap-junction (GJ) channels formed from connexin (Cx) proteins provide direct pathways for electrical and metabolic cell-cell communication. Earlier, we developed a stochastic 16-state model (S16SM) of voltage gating of the GJ channel containing two pairs of fast and slow gates, each operating between open (o) and closed (c) states. However, experimental data suggest that gates may in fact contain two or more closed states. We developed a model in which the slow gate operates according to a linear reaction scheme, o↔c1↔c2, where c1 and c2 are initial-closed and deep-closed states that both close the channel fully, whereas the fast gate operates between the open state and the closed state and exhibits a residual conductance. Thus, we developed a stochastic 36-state model (S36SM) of GJ channel gating that is sensitive to transjunctional voltage (Vj). To accelerate simulation and eliminate noise in simulated junctional conductance (gj) records, we transformed an S36SM into a Markov chain 36-state model (MC36SM) of GJ channel gating. This model provides an explanation for well-established experimental data, such as delayed gj recovery after Vj gating, hysteresis of gj-Vj dependence, and the low ratio of functional channels to the total number of GJ channels clustered in junctional plaques, and it has the potential to describe chemically mediated gating, which cannot be reflected using an S16SM. The MC36SM, when combined with global optimization algorithms, can be used for automated estimation of gating parameters including probabilities of c1↔c2 transitions from experimental gj-time and gj-Vj dependencies. PMID:27028642

  16. Bias, precision, and parameter redundancy in complex multistate models with unobservable states.

    PubMed

    Bailey, Larissa L; Converse, Sarah J; Kendall, William L

    2010-06-01

    Multistate mark-recapture models with unobservable states can yield unbiased estimators of survival probabilities in the presence of temporary emigration (i.e., in cases where some individuals are temporarily unavailable for capture). In addition, these models permit the estimation of transition probabilities between states, which may themselves be of interest; for example, when only breeding animals are available for capture. However, parameter redundancy is frequently a problem in these models, yielding biased parameter estimates and influencing model selection. Using numerical methods, we examine complex multistate mark-recapture models involving two observable and two unobservable states. This model structure was motivated by two different biological systems: one involving island-nesting albatross, and another involving pond-breeding amphibians. We found that, while many models are theoretically identifiable given appropriate constraints, obtaining accurate and precise parameter estimates in practice can be difficult. Practitioners should consider ways to increase detection probabilities or adopt robust design sampling in order to improve the properties of estimates obtained from these models. We suggest that investigators interested in using these models explore both theoretical identifiability and possible near-singularity for likely parameter values using a combination of available methods. PMID:20583702

  17. Model Checking - My 27-Year Quest to Overcome the State Explosion Problem

    NASA Technical Reports Server (NTRS)

    Clarke, Ed

    2009-01-01

    Model Checking is an automatic verification technique for state-transition systems that are finite=state or that have finite-state abstractions. In the early 1980 s in a series of joint papers with my graduate students E.A. Emerson and A.P. Sistla, we proposed that Model Checking could be used for verifying concurrent systems and gave algorithms for this purpose. At roughly the same time, Joseph Sifakis and his student J.P. Queille at the University of Grenoble independently developed a similar technique. Model Checking has been used successfully to reason about computer hardware and communication protocols and is beginning to be used for verifying computer software. Specifications are written in temporal logic, which is particularly valuable for expressing concurrency properties. An intelligent, exhaustive search is used to determine if the specification is true or not. If the specification is not true, the Model Checker will produce a counterexample execution trace that shows why the specification does not hold. This feature is extremely useful for finding obscure errors in complex systems. The main disadvantage of Model Checking is the state-explosion problem, which can occur if the system under verification has many processes or complex data structures. Although the state-explosion problem is inevitable in worst case, over the past 27 years considerable progress has been made on the problem for certain classes of state-transition systems that occur often in practice. In this talk, I will describe what Model Checking is, how it works, and the main techniques that have been developed for combating the state explosion problem.

  18. Current Pressure Transducer Application of Model-based Prognostics Using Steady State Conditions

    NASA Technical Reports Server (NTRS)

    Teubert, Christopher; Daigle, Matthew J.

    2014-01-01

    Prognostics is the process of predicting a system's future states, health degradation/wear, and remaining useful life (RUL). This information plays an important role in preventing failure, reducing downtime, scheduling maintenance, and improving system utility. Prognostics relies heavily on wear estimation. In some components, the sensors used to estimate wear may not be fast enough to capture brief transient states that are indicative of wear. For this reason it is beneficial to be capable of detecting and estimating the extent of component wear using steady-state measurements. This paper details a method for estimating component wear using steady-state measurements, describes how this is used to predict future states, and presents a case study of a current/pressure (I/P) Transducer. I/P Transducer nominal and off-nominal behaviors are characterized using a physics-based model, and validated against expected and observed component behavior. This model is used to map observed steady-state responses to corresponding fault parameter values in the form of a lookup table. This method was chosen because of its fast, efficient nature, and its ability to be applied to both linear and non-linear systems. Using measurements of the steady state output, and the lookup table, wear is estimated. A regression is used to estimate the wear propagation parameter and characterize the damage progression function, which are used to predict future states and the remaining useful life of the system.

  19. Regression models for estimating urban storm-runoff quality and quantity in the United States

    USGS Publications Warehouse

    Driver, N.E.; Troutman, B.M.

    1989-01-01

    Urban planners and managers need information about the local quantity of precipitation and the quality and quantity of storm runoff if they are to plan adequately for the effects of storm runoff from urban areas. As a result of this need, linear regression models were developed for the estimation of storm-runoff loads and volumes from physical, land-use, and climatic characteristics of urban watersheds throughout the United States. Three statistically different regions were delineated, based on mean annual rainfall, to improve linear regression models. One use of these models is to estimate storm-runoff loads and volumes at gaged and ungaged urban watersheds. The most significant explanatory variables in all linear regression models were total storm rainfall and total contributing drainage area. Impervious area, land-use, and mean annual climatic characteristics were also significant explanatory variables in some linear regression models. Models for dissolved solids, total nitrogen, and total ammonia plus organic nitrogen as nitrogen were the most accurate models for most areas, whereas models for suspended solids were the least accurate. The most accurate models were those for more arid western United States, and the least accurate models were those for areas that had large quantities of mean annual rainfall.Linear regression models were developed for the estimation of storm-runoff loads and volumes from physical, land-use, and climatic characteristics of urban watersheds throughout the United States. Three statistically different regions were delineated, based on mean annual rainfall, to improve linear regression models. One use of these models is to estimate storm-runoff loads and volumes at gaged and ungaged urban watersheds. The most significant explanatory variables in all linear regression models were total storm rainfall and total contributing drainage area. Impervious area, land-use, and mean annual climatic characteristics were also significant

  20. An optimal state estimation model of sensory integration in human postural balance.

    PubMed

    Kuo, Arthur D

    2005-09-01

    We propose a model for human postural balance, combining state feedback control with optimal state estimation. State estimation uses an internal model of body and sensor dynamics to process sensor information and determine body orientation. Three sensory modalities are modeled: joint proprioception, vestibular organs in the inner ear, and vision. These are mated with a two degree-of-freedom model of body dynamics in the sagittal plane. Linear quadratic optimal control is used to design state feedback and estimation gains. Nine free parameters define the control objective and the signal-to-noise ratios of the sensors. The model predicts statistical properties of human sway in terms of covariance of ankle and hip motion. These predictions are compared with normal human responses to alterations in sensory conditions. With a single parameter set, the model successfully reproduces the general nature of postural motion as a function of sensory environment. Parameter variations reveal that the model is highly robust under normal sensory conditions, but not when two or more sensors are inaccurate. This behavior is similar to that of normal human subjects. We propose that age-related sensory changes may be modeled with decreased signal-to-noise ratios, and compare the model's behavior with degraded sensors against experimental measurements from older adults. We also examine removal of the model's vestibular sense, which leads to instability similar to that observed in bilateral vestibular loss subjects. The model may be useful for predicting which sensors are most critical for balance, and how much they can deteriorate before posture becomes unstable. PMID:16135887

  1. An optimal state estimation model of sensory integration in human postural balance

    NASA Astrophysics Data System (ADS)

    Kuo, Arthur D.

    2005-09-01

    We propose a model for human postural balance, combining state feedback control with optimal state estimation. State estimation uses an internal model of body and sensor dynamics to process sensor information and determine body orientation. Three sensory modalities are modeled: joint proprioception, vestibular organs in the inner ear, and vision. These are mated with a two degree-of-freedom model of body dynamics in the sagittal plane. Linear quadratic optimal control is used to design state feedback and estimation gains. Nine free parameters define the control objective and the signal-to-noise ratios of the sensors. The model predicts statistical properties of human sway in terms of covariance of ankle and hip motion. These predictions are compared with normal human responses to alterations in sensory conditions. With a single parameter set, the model successfully reproduces the general nature of postural motion as a function of sensory environment. Parameter variations reveal that the model is highly robust under normal sensory conditions, but not when two or more sensors are inaccurate. This behavior is similar to that of normal human subjects. We propose that age-related sensory changes may be modeled with decreased signal-to-noise ratios, and compare the model's behavior with degraded sensors against experimental measurements from older adults. We also examine removal of the model's vestibular sense, which leads to instability similar to that observed in bilateral vestibular loss subjects. The model may be useful for predicting which sensors are most critical for balance, and how much they can deteriorate before posture becomes unstable.

  2. Enabling intelligent copernicus services for carbon and water balance modeling of boreal forest ecosystems - North State

    NASA Astrophysics Data System (ADS)

    Häme, Tuomas; Mutanen, Teemu; Rauste, Yrjö; Antropov, Oleg; Molinier, Matthieu; Quegan, Shaun; Kantzas, Euripides; Mäkelä, Annikki; Minunno, Francesco; Atli Benediktsson, Jon; Falco, Nicola; Arnason, Kolbeinn; Storvold, Rune; Haarpaintner, Jörg; Elsakov, Vladimir; Rasinmäki, Jussi

    2015-04-01

    The objective of project North State, funded by Framework Program 7 of the European Union, is to develop innovative data fusion methods that exploit the new generation of multi-source data from Sentinels and other satellites in an intelligent, self-learning framework. The remote sensing outputs are interfaced with state-of-the-art carbon and water flux models for monitoring the fluxes over boreal Europe to reduce current large uncertainties. This will provide a paradigm for the development of products for future Copernicus services. The models to be interfaced are a dynamic vegetation model and a light use efficiency model. We have identified four groups of variables that will be estimated with remote sensed data: land cover variables, forest characteristics, vegetation activity, and hydrological variables. The estimates will be used as model inputs and to validate the model outputs. The earth observation variables are computed as automatically as possible, with an objective to completely automatic estimation. North State has two sites for intensive studies in southern and northern Finland, respectively, one in Iceland and one in state Komi of Russia. Additionally, the model input variables will be estimated and models applied over European boreal and sub-arctic region from Ural Mountains to Iceland. The accuracy assessment of the earth observation variables will follow statistical sampling design. Model output predictions are compared to earth observation variables. Also flux tower measurements are applied in the model assessment. In the paper, results of hyperspectral, Sentinel-1, and Landsat data and their use in the models is presented. Also an example of a completely automatic land cover class prediction is reported.

  3. Bayesian state space models for dynamic genetic network construction across multiple tissues.

    PubMed

    Liang, Yulan; Kelemen, Arpad

    2016-08-01

    Construction of gene-gene interaction networks and potential pathways is a challenging and important problem in genomic research for complex diseases while estimating the dynamic changes of the temporal correlations and non-stationarity are the keys in this process. In this paper, we develop dynamic state space models with hierarchical Bayesian settings to tackle this challenge for inferring the dynamic profiles and genetic networks associated with disease treatments. We treat both the stochastic transition matrix and the observation matrix time-variant and include temporal correlation structures in the covariance matrix estimations in the multivariate Bayesian state space models. The unevenly spaced short time courses with unseen time points are treated as hidden state variables. Hierarchical Bayesian approaches with various prior and hyper-prior models with Monte Carlo Markov Chain and Gibbs sampling algorithms are used to estimate the model parameters and the hidden state variables. We apply the proposed Hierarchical Bayesian state space models to multiple tissues (liver, skeletal muscle, and kidney) Affymetrix time course data sets following corticosteroid (CS) drug administration. Both simulation and real data analysis results show that the genomic changes over time and gene-gene interaction in response to CS treatment can be well captured by the proposed models. The proposed dynamic Hierarchical Bayesian state space modeling approaches could be expanded and applied to other large scale genomic data, such as next generation sequence (NGS) combined with real time and time varying electronic health record (EHR) for more comprehensive and robust systematic and network based analysis in order to transform big biomedical data into predictions and diagnostics for precision medicine and personalized healthcare with better decision making and patient outcomes. PMID:27343475

  4. Excited-state PAW Potentials: Modelling Hot-Dense Plasmas From First Principles

    NASA Astrophysics Data System (ADS)

    Hollebon, Patrick; Vinko, Sam; Ciricosta, Orlando; Wark, Justin

    2015-11-01

    Finite temperature density functional theory has proven to be a successful means of modelling warm and hot dense plasma systems, including the calculation of transport properties, equation of state and ionization potential depression. Such methods take into account the non-negligible influence of quantum mechanics on the electronic structure of these strongly coupled systems. We apply excited state frozen core potentials to model general core-hole states in high density plasma, allowing for the calculation of the electronic structure of a range of ionic configurations. The advantages of using excited-state potentials are explored and we investigate their application towards various response function calculations, with the results shown to be in good agreement with all-electron calculations at finite-temperatures.

  5. Analytic models for the density of a ground-state spinor condensate

    NASA Astrophysics Data System (ADS)

    Gautam, Sandeep; Adhikari, S. K.

    2015-08-01

    We demonstrate that the ground state of a trapped spin-1 and spin-2 spinor ferromagnetic Bose-Einstein condensate (BEC) can be well approximated by a single decoupled Gross-Pitaevskii (GP) equation. Useful analytic models for the ground-state densities of ferromagnetic BECs are obtained from the Thomas-Fermi approximation (TFA) to this decoupled equation. Similarly, for the ground states of spin-1 antiferromagnetic and spin-2 antiferromagnetic and cyclic BECs, some of the spin-component densities are zero, which reduces the coupled GP equation to a simple reduced form. Analytic models for ground-state densities are also obtained for antiferromagnetic and cyclic BECs from the TFA to the respective reduced GP equations. The analytic densities are illustrated and compared with the full numerical solution of the GP equation with realistic experimental parameters.

  6. Modeling trait and state variation using multilevel factor analysis with PANAS daily diary data.

    PubMed

    Merz, Erin L; Roesch, Scott C

    2011-02-01

    This study used daily diary data to model trait and state Positive Affect (PA) and Negative Affect (NA) using the Positive and Negative Affect Schedule (PANAS; Watson, Clark, & Tellegen, 1988). Data were collected from 364 college students over five days. Intraclass correlation coefficients suggested approximately equal amounts of variability at the trait and state levels. Multilevel factor analysis revealed that the model specifying two correlated factors (PA, NA) and correlated uniqueness terms among redundant items provided the best fit. Trait and state PA and NA were generally associated with stress, anxiety, depression, and three types of self-esteem (performance, academic, social). The coefficients describing these relationships differed somewhat, suggesting that trait and state measurement may have different predictive utility. PMID:21516166

  7. A heuristic finite-state model of the human driver in a car-following situation

    NASA Technical Reports Server (NTRS)

    Burnham, G. O.; Bekey, G. A.

    1976-01-01

    An approach to modeling human driver behavior in single-lane car following which is based on a finite-state decision structure is considered. The specific strategy at each point in the decision tree was obtained from observations of typical driver behavior. The synthesis of the decision logic is based on position and velocity thresholds and four states defined by regions in the phase plane. The performance of the resulting assumed intuitively logical model was compared with actual freeway data. The match of the model to the data was optimized by adapting the model parameters using a modified PARTAN algorithm. The results indicate that the heuristic model behavior matches actual car-following performance better during deceleration and constant velocity phases than during acceleration periods.

  8. Einstein's steady-state theory: an abandoned model of the cosmos

    NASA Astrophysics Data System (ADS)

    O'Raifeartaigh, Cormac; McCann, Brendan; Nahm, Werner; Mitton, Simon

    2014-09-01

    We present a translation and analysis of an unpublished manuscript by Albert Einstein in which he attempted to construct a `steady-state' model of the universe. The manuscript, which appears to have been written in early 1931, demonstrates that Einstein once explored a cosmic model in which the mean density of matter in an expanding universe is maintained constant by the continuous formation of matter from empty space. This model is very different to previously known Einsteinian models of the cosmos (both static and dynamic) but anticipates the later steady-state cosmology of Hoyle, Bondi and Gold in some ways. We find that Einstein's steady-state model contains a fundamental flaw and suggest that it was abandoned for this reason. We also suggest that he declined to explore a more sophisticated version because he found such theories rather contrived. The manuscript is of historical interest because it reveals that Einstein debated between steady-state and evolving models of the cosmos decades before a similar debate took place in the cosmological community.

  9. Adaptive behaviour and multiple equilibrium states in a predator-prey model.

    PubMed

    Pimenov, Alexander; Kelly, Thomas C; Korobeinikov, Andrei; O'Callaghan, Michael J A; Rachinskii, Dmitrii

    2015-05-01

    There is evidence that multiple stable equilibrium states are possible in real-life ecological systems. Phenomenological mathematical models which exhibit such properties can be constructed rather straightforwardly. For instance, for a predator-prey system this result can be achieved through the use of non-monotonic functional response for the predator. However, while formal formulation of such a model is not a problem, the biological justification for such functional responses and models is usually inconclusive. In this note, we explore a conjecture that a multitude of equilibrium states can be caused by an adaptation of animal behaviour to changes of environmental conditions. In order to verify this hypothesis, we consider a simple predator-prey model, which is a straightforward extension of the classic Lotka-Volterra predator-prey model. In this model, we made an intuitively transparent assumption that the prey can change a mode of behaviour in response to the pressure of predation, choosing either "safe" of "risky" (or "business as usual") behaviour. In order to avoid a situation where one of the modes gives an absolute advantage, we introduce the concept of the "cost of a policy" into the model. A simple conceptual two-dimensional predator-prey model, which is minimal with this property, and is not relying on odd functional responses, higher dimensionality or behaviour change for the predator, exhibits two stable co-existing equilibrium states with basins of attraction separated by a separatrix of a saddle point. PMID:25732186

  10. Two-polariton bound states in the Jaynes-Cummings-Hubbard model

    SciTech Connect

    Wong, Max T. C.; Law, C. K.

    2011-05-15

    We examine the eigenstates of the one-dimensional Jaynes-Cummings-Hubbard model in the two-excitation subspace. We discover that two-excitation bound states emerge when the ratio of vacuum Rabi frequency to the tunneling rate between cavities exceeds a critical value. We determine the critical value as a function of the quasimomentum quantum number, and indicate that the bound states carry a strong correlation in which the two polaritons appear to be spatially confined together.

  11. Control of spiral waves and turbulent states in a cardiac model by travelling-wave perturbations

    NASA Astrophysics Data System (ADS)

    Wang, Peng-Ye; Xie, Ping; Yin, Hua-Wei

    2003-06-01

    We propose a travelling-wave perturbation method to control the spatiotemporal dynamics in a cardiac model. It is numerically demonstrated that the method can successfully suppress the wave instability (alternans in action potential duration) in the one-dimensional case and convert spiral waves and turbulent states to the normal travelling wave states in the two-dimensional case. An experimental scheme is suggested which may provide a new design for a cardiac defibrillator.

  12. Non-equilibrium Steady States in Kac's Model Coupled to a Thermostat

    NASA Astrophysics Data System (ADS)

    Evans, Josephine

    2016-09-01

    This paper studies the existence, uniqueness and convergence to non-equilibrium steady states in Kac's model with an external coupling. We work in both Fourier distances and Wasserstein distances. Our methods work in the case where the external coupling is not a Maxwellian equilibrium. This provides an example of a non-equilibrium steady state. We also study the behaviour as the number of particles goes to infinity and show quantitative estimates on the convergence rate of the first marginal.

  13. Generalized Frequency Domain State-Space Models for Analyzing Flexible Rotating Spacecraft

    NASA Astrophysics Data System (ADS)

    Turner, James D.; Elgohary, Tarek A.

    2012-06-01

    The mathematical model for a flexible spacecraft that is rotating about a single axis rotation is described by coupled rigid and flexible body degrees-of-freedom, where the equations of motion are modeled by integro-partial differential equations. Beam-like structures are often useful for analyzing boom-like flexible appendages. The equations of motion are analyzed by introducing generalized Fourier series that transform the governing equations into a system of ordinary differential equations. Though technically straightforward, two problems arise with this approach: (1) the model is frequency-truncated because a finite number of series terms are retained in the model, and (2) computationally intense matrix-valued transfer function calculations are required for understanding the frequency domain behavior of the system. Both of these problems are resolved by: (1) computing the Laplace transform of the governing integro-partial differential equation of motion; and (2) introducing a generalized state space (consisting of the deformational coordinate and three spatial partial derivatives, as well as single and double spatial integrals of the deformational coordinate). The resulting math model is cast in the form of a linear state-space differential equation that is solved in terms of a matrix exponential and convolution integral. The structural boundary conditions defined by Hamilton's principle are enforced on the closed-form solution for the generalized state space. The generalized state space model is then manipulated to provide analytic scalar transfer function models for original integro-partial differential system dynamics. Symbolic methods are used to obtain closed-form eigen decomposition- based solutions for the matrix exponential/convolution integral algorithm. Numerical results are presented that compare the classical series based approach with the generalized state space approach for computing representative spacecraft transfer function models.

  14. Measurement of the Equation of State of the Two-Dimensional Hubbard Model

    NASA Astrophysics Data System (ADS)

    Miller, Luke; Cocchi, Eugenio; Drewes, Jan; Koschorreck, Marco; Pertot, Daniel; Brennecke, Ferdinand; Koehl, Michael

    2016-05-01

    The subtle interplay between kinetic energy, interactions and dimensionality challenges our comprehension of strongly-correlated physics observed, for example, in the solid state. In this quest, the Hubbard model has emerged as a conceptually simple, yet rich model describing such physics. Here we present an experimental determination of the equation of state of the repulsive two-dimensional Hubbard model over a broad range of interactions, 0 <= U / t <= 20 , and temperatures, down to kB T / t = 0 . 63(2) using high-resolution imaging of ultracold fermionic atoms in optical lattices. We show density profiles, compressibilities and double occupancies over the whole doping range, and hence our results constitute benchmarks for state-of-the-art theoretical approaches.

  15. A modified two-state empirical valence bond model for proton transport in aqueous solutions

    SciTech Connect

    Mabuchi, Takuya; Fukushima, Akinori; Tokumasu, Takashi

    2015-07-07

    A detailed analysis of the proton solvation structure and transport properties in aqueous solutions is performed using classical molecular dynamics simulations. A refined two-state empirical valence bond (aTS-EVB) method, which is based on the EVB model of Walbran and Kornyshev and the anharmonic water force field, is developed in order to describe efficiently excess proton transport via the Grotthuss mechanism. The new aTS-EVB model clearly satisfies the requirement for simpler and faster calculation, because of the simplicity of the two-state EVB algorithm, while providing a better description of diffusive dynamics of the excess proton and water in comparison with the previous two-state EVB models, which significantly improves agreement with the available experimental data. The results of activation energies for the excess proton and water calculated between 300 and 340 K (the temperature range used in this study) are also found to be in good agreement with the corresponding experimental data.

  16. Maximum profile likelihood estimation of differential equation parameters through model based smoothing state estimates.

    PubMed

    Campbell, D A; Chkrebtii, O

    2013-12-01

    Statistical inference for biochemical models often faces a variety of characteristic challenges. In this paper we examine state and parameter estimation for the JAK-STAT intracellular signalling mechanism, which exemplifies the implementation intricacies common in many biochemical inference problems. We introduce an extension to the Generalized Smoothing approach for estimating delay differential equation models, addressing selection of complexity parameters, choice of the basis system, and appropriate optimization strategies. Motivated by the JAK-STAT system, we further extend the generalized smoothing approach to consider a nonlinear observation process with additional unknown parameters, and highlight how the approach handles unobserved states and unevenly spaced observations. The methodology developed is generally applicable to problems of estimation for differential equation models with delays, unobserved states, nonlinear observation processes, and partially observed histories. PMID:23579098

  17. A modified two-state empirical valence bond model for proton transport in aqueous solutions

    NASA Astrophysics Data System (ADS)

    Mabuchi, Takuya; Fukushima, Akinori; Tokumasu, Takashi

    2015-07-01

    A detailed analysis of the proton solvation structure and transport properties in aqueous solutions is performed using classical molecular dynamics simulations. A refined two-state empirical valence bond (aTS-EVB) method, which is based on the EVB model of Walbran and Kornyshev and the anharmonic water force field, is developed in order to describe efficiently excess proton transport via the Grotthuss mechanism. The new aTS-EVB model clearly satisfies the requirement for simpler and faster calculation, because of the simplicity of the two-state EVB algorithm, while providing a better description of diffusive dynamics of the excess proton and water in comparison with the previous two-state EVB models, which significantly improves agreement with the available experimental data. The results of activation energies for the excess proton and water calculated between 300 and 340 K (the temperature range used in this study) are also found to be in good agreement with the corresponding experimental data.

  18. A model for charge transfer in ultracold Rydberg ground-state atomic collisions

    NASA Astrophysics Data System (ADS)

    Markson, Samuel; Sadeghpour, H. R.

    2016-06-01

    In excited molecules, the interaction between the covalent Rydberg and ion-pair channels forms a unique class of excited states, in which the infinite manifold of vibrational levels are the equivalent of atomic Rydberg states with a heavy electron mass. Production of the ion-pair states usually requires excitation through one or several interacting Rydberg states; these interacting channels lead to loss of flux, diminishing the rate of ion-pair production. Here, we develop an analytical, asymptotic charge-transfer model for the interaction between ultracold Rydberg molecular states, and employ this method to demonstrate the utility of off-resonant field control over the ion-pair formation, with near unity efficiency.

  19. Phenomenological neutron star equations of state. 3-window modeling of QCD matter

    NASA Astrophysics Data System (ADS)

    Kojo, Toru

    2016-03-01

    We discuss the 3-window modeling of cold, dense QCD matter equations of state at density relevant to neutron star properties. At low baryon density, nBlesssim 2ns (ns: nuclear saturation density), we utilize purely hadronic equations of state that are constrained by empirical observations at density n_B˜ n_s and neutron star radii. At high density, nBgtrsim 5ns, we use the percolated quark matter equations of state which must be very stiff to pass the two-solar mass constraints. The intermediate domain at 2lesssim nB/ns lesssim 5 is described as neither purely hadronic nor percolated quark matter, and the equations of state are inferred by interpolating hadronic and percolated quark matter equations of state. Possible forms of the interpolation are severely restricted by the condition on the (square of) speed of sound, 0le cs2 le 1. The characteristics of the 3-window equation of state are compared with those of conventional hybrid and self-bound quark matters. Using a schematic quark model for the percolated domain, it is argued that the two-solar mass constraint requires the model parameters to be as large as their vacuum values, indicating that the gluon dynamics remains strongly non-perturbative to nB˜ 10ns. The hyperon puzzle is also briefly discussed in light of quark descriptions.

  20. A generalised 17-state vibronic-coupling Hamiltonian model for ethylene

    NASA Astrophysics Data System (ADS)

    Jornet-Somoza, Joaquim; Lasorne, Benjamin; Robb, Michael A.; Meyer, Hans-Dieter; Lauvergnat, David; Gatti, Fabien

    2012-08-01

    In a previous work [B. Lasorne, M. A. Robb, H.-D. Meyer, and F. Gatti, "The electronic excited states of ethylene with large-amplitude deformations: A dynamical symmetry group investigation," Chem. Phys. 377, 30-45 (2010), 10.1016/j.chemphys.2010.08.011; B. Lasorne, M. A. Robb, H.-D. Meyer, and F. Gatti, Chem. Phys. 382, 132 (2011) (Erratum)], 10.1016/j.chemphys.2011.01.004, we investigated the electronic structure of ethylene (ethene, C2H4) in terms of 17 dominant configurations selected at the multiconfiguration self-consistent field level of theory. These were shown to be sufficient to recover most of the static electron correlation among the first valence and Rydberg states at all geometries. We also devised a strategy to build a 17-quasidiabatic-state matrix representation of the electronic Hamiltonian for curvilinear coordinates using dynamical symmetry. Here, we present fitted surfaces in the form of a generalised vibronic-coupling Hamiltonian model for two nuclear coordinates, CC bond stretching and torsion. Dynamic electron correlation is included into the electronic structure to improve the energetics of the Rydberg states at the multireference configuration interaction level of theory. The chemical interpretation of the adiabatic states of interest does not change qualitatively, which validates our choice of underlying quasidiabatic states in the model. The absorption spectrum is calculated with quantum dynamics and partially assigned. This first two-dimensional model shows a surprisingly good agreement with the experimental spectrum.

  1. Multi-state Markov model for disability: A case of Malaysia Social Security (SOCSO)

    NASA Astrophysics Data System (ADS)

    Samsuddin, Shamshimah; Ismail, Noriszura

    2016-06-01

    Studies of SOCSO's contributor outcomes like disability are usually restricted to a single outcome. In this respect, the study has focused on the approach of multi-state Markov model for estimating the transition probabilities among SOCSO's contributor in Malaysia between states: work, temporary disability, permanent disability and death at yearly intervals on age, gender, year and disability category; ignoring duration and past disability experience which is not consider of how or when someone arrived in that category. These outcomes represent different states which depend on health status among the workers.

  2. Entropy, chaos, and excited-state quantum phase transitions in the Dicke model.

    PubMed

    Lóbez, C M; Relaño, A

    2016-07-01

    We study nonequilibrium processes in an isolated quantum system-the Dicke model-focusing on the role played by the transition from integrability to chaos and the presence of excited-state quantum phase transitions. We show that both diagonal and entanglement entropies are abruptly increased by the onset of chaos. Also, this increase ends in both cases just after the system crosses the critical energy of the excited-state quantum phase transition. The link between entropy production, the development of chaos, and the excited-state quantum phase transition is more clear for the entanglement entropy. PMID:27575109

  3. Genuinely Multipartite Entangled Quantum States with Fully Local Hidden Variable Models and Hidden Multipartite Nonlocality.

    PubMed

    Bowles, Joseph; Francfort, Jérémie; Fillettaz, Mathieu; Hirsch, Flavien; Brunner, Nicolas

    2016-04-01

    The relation between entanglement and nonlocality is discussed in the case of multipartite quantum systems. We show that, for any number of parties, there exist genuinely multipartite entangled states that admit a fully local hidden variable model, i.e., where all parties are separated. Hence, although these states exhibit the strongest form of multipartite entanglement, they cannot lead to Bell inequality violation considering general nonsequential local measurements. Then, we show that the nonlocality of these states can nevertheless be activated using sequences of local measurements, thus revealing genuine multipartite hidden nonlocality. PMID:27081960

  4. Modeling winter rainfall in Northwest India using a hidden Markov model: understanding occurrence of different states and their dynamical connections

    NASA Astrophysics Data System (ADS)

    Pal, Indrani; Robertson, Andrew W.; Lall, Upmanu; Cane, Mark A.

    2015-02-01

    A multiscale-modeling framework for daily rainfall is considered and diagnostic results are presented for an application to the winter season in Northwest India. The daily rainfall process is considered to follow a hidden Markov model (HMM), with the hidden states assumed to be an unknown random function of slowly varying climatic modulation of the winter jet stream and moisture transport dynamics. The data used are from 14 stations over Satluj River basin in winter (December-January-February-March). The period considered is 1977/78-2005/06. The HMM identifies four discrete weather states, which are used to describe daily rainfall variability over study region. Each state was found to be associated with a distinct atmospheric circulation pattern, with the driest and drier states, State 1 and 2 respectively, characterized by a lack of synoptic wave activity. In contrast, the wetter and wettest states, States 3 and 4 respectively, are characterized by a zonally oriented wave train extending across Eurasia between 20N and 40N, identified with `western disturbances' (WD). The occurrence of State 4 is strongly conditioned by the El Nino and Indian Ocean Dipole (IOD) phenomena in winter, which is demonstrated using large-scale correlation maps based on mean sea level pressure and sea surface temperature. This suggests that there is a tendency of higher frequency of the wet days and intense WD activities in winter during El Nino and positive IOD years. These findings, derived from daily rainfall station records, help clarify the sequence of Northern Hemisphere mid-latitude storms bringing winter rainfall over Northwest India, and their association with potentially predictable low frequency modes on seasonal time scales and longer.

  5. Sharp Contradiction for Local-Hidden-State Model in Quantum Steering.

    PubMed

    Chen, Jing-Ling; Su, Hong-Yi; Xu, Zhen-Peng; Pati, Arun Kumar

    2016-01-01

    In quantum theory, no-go theorems are important as they rule out the existence of a particular physical model under consideration. For instance, the Greenberger-Horne-Zeilinger (GHZ) theorem serves as a no-go theorem for the nonexistence of local hidden variable models by presenting a full contradiction for the multipartite GHZ states. However, the elegant GHZ argument for Bell's nonlocality does not go through for bipartite Einstein-Podolsky-Rosen (EPR) state. Recent study on quantum nonlocality has shown that the more precise description of EPR's original scenario is "steering", i.e., the nonexistence of local hidden state models. Here, we present a simple GHZ-like contradiction for any bipartite pure entangled state, thus proving a no-go theorem for the nonexistence of local hidden state models in the EPR paradox. This also indicates that the very simple steering paradox presented here is indeed the closest form to the original spirit of the EPR paradox. PMID:27562658

  6. Sharp Contradiction for Local-Hidden-State Model in Quantum Steering

    PubMed Central

    Chen, Jing-Ling; Su, Hong-Yi; Xu, Zhen-Peng; Pati, Arun Kumar

    2016-01-01

    In quantum theory, no-go theorems are important as they rule out the existence of a particular physical model under consideration. For instance, the Greenberger-Horne-Zeilinger (GHZ) theorem serves as a no-go theorem for the nonexistence of local hidden variable models by presenting a full contradiction for the multipartite GHZ states. However, the elegant GHZ argument for Bell’s nonlocality does not go through for bipartite Einstein-Podolsky-Rosen (EPR) state. Recent study on quantum nonlocality has shown that the more precise description of EPR’s original scenario is “steering”, i.e., the nonexistence of local hidden state models. Here, we present a simple GHZ-like contradiction for any bipartite pure entangled state, thus proving a no-go theorem for the nonexistence of local hidden state models in the EPR paradox. This also indicates that the very simple steering paradox presented here is indeed the closest form to the original spirit of the EPR paradox. PMID:27562658

  7. A master equation formalism for macroscopic modeling of asynchronous irregular activity states.

    PubMed

    El Boustani, Sami; Destexhe, Alain

    2009-01-01

    Many efforts have been devoted to modeling asynchronous irregular (AI) activity states, which resemble the complex activity states seen in the cerebral cortex of awake animals. Most of models have considered balanced networks of excitatory and inhibitory spiking neurons in which AI states are sustained through recurrent sparse connectivity, with or without external input. In this letter we propose a mesoscopic description of such AI states. Using master equation formalism, we derive a second-order mean-field set of ordinary differential equations describing the temporal evolution of randomly connected balanced networks. This formalism takes into account finite size effects and is applicable to any neuron model as long as its transfer function can be characterized. We compare the predictions of this approach with numerical simulations for different network configurations and parameter spaces. Considering the randomly connected network as a unit, this approach could be used to build large-scale networks of such connected units, with an aim to model activity states constrained by macroscopic measurements, such as voltage-sensitive dye imaging. PMID:19210171

  8. Relative stability of network states in Boolean network models of gene regulation in development.

    PubMed

    Zhou, Joseph Xu; Samal, Areejit; d'Hérouël, Aymeric Fouquier; Price, Nathan D; Huang, Sui

    2016-01-01

    Progress in cell type reprogramming has revived the interest in Waddington's concept of the epigenetic landscape. Recently researchers developed the quasi-potential theory to represent the Waddington's landscape. The Quasi-potential U(x), derived from interactions in the gene regulatory network (GRN) of a cell, quantifies the relative stability of network states, which determine the effort required for state transitions in a multi-stable dynamical system. However, quasi-potential landscapes, originally developed for continuous systems, are not suitable for discrete-valued networks which are important tools to study complex systems. In this paper, we provide a framework to quantify the landscape for discrete Boolean networks (BNs). We apply our framework to study pancreas cell differentiation where an ensemble of BN models is considered based on the structure of a minimal GRN for pancreas development. We impose biologically motivated structural constraints (corresponding to specific type of Boolean functions) and dynamical constraints (corresponding to stable attractor states) to limit the space of BN models for pancreas development. In addition, we enforce a novel functional constraint corresponding to the relative ordering of attractor states in BN models to restrict the space of BN models to the biological relevant class. We find that BNs with canalyzing/sign-compatible Boolean functions best capture the dynamics of pancreas cell differentiation. This framework can also determine the genes' influence on cell state transitions, and thus can facilitate the rational design of cell reprogramming protocols. PMID:26965665

  9. A mathematical model of liver metabolism: from steady state to dynamic

    NASA Astrophysics Data System (ADS)

    Calvetti, D.; Kuceyeski, A.; Somersalo, E.

    2008-07-01

    The increase in Type 2 diabetes and other metabolic disorders has led to an intense focus on the areas of research related to metabolism. Because the liver is essential in regulating metabolite concentrations that maintain life, it is especially important to have good knowledge of the functions within this organ. In silico mathematical models that can adequately describe metabolite concentrations, flux and transport rates in the liver in vivo can be a useful predictive tool. Fully dynamic models, which contain expressions for Michaelis-Menten reaction kinetics can be utilized to investigate different metabolic states, for example exercise, fed or starved state. In this paper we describe a two compartment (blood and tissue) spatially lumped liver metabolism model. First, we use Bayesian Flux Balance Analysis (BFBA) to estimate the values of flux and transport rates at steady state, which agree closely with values from the literature. These values are then used to find a set of Michaelis-Menten parameters and initial concentrations which identify a dynamic model that can be used for exploring different metabolic states. In particular, we investigate the effect of doubling the concentration of lactate entering the system via the hepatic artery and portal vein. This change in lactate concentration forces the system to a new steady state, where glucose production is increased.

  10. Probabilistic modelling of chromatin code landscape reveals functional diversity of enhancer-like chromatin states

    PubMed Central

    Zhou, Jian; Troyanskaya, Olga G.

    2016-01-01

    Interpreting the functional state of chromatin from the combinatorial binding patterns of chromatin factors, that is, the chromatin codes, is crucial for decoding the epigenetic state of the cell. Here we present a systematic map of Drosophila chromatin states derived from data-driven probabilistic modelling of dependencies between chromatin factors. Our model not only recapitulates enhancer-like chromatin states as indicated by widely used enhancer marks but also divides these states into three functionally distinct groups, of which only one specific group possesses active enhancer activity. Moreover, we discover a strong association between one specific enhancer state and RNA Polymerase II pausing, linking transcription regulatory potential and chromatin organization. We also observe that with the exception of long-intron genes, chromatin state transition positions in transcriptionally active genes align with an absolute distance to their corresponding transcription start site, regardless of gene length. Using our method, we provide a resource that helps elucidate the functional and spatial organization of the chromatin code landscape. PMID:26841971

  11. State-space models for bio-loggers: A methodological road map

    NASA Astrophysics Data System (ADS)

    Jonsen, I. D.; Basson, M.; Bestley, S.; Bravington, M. V.; Patterson, T. A.; Pedersen, M. W.; Thomson, R.; Thygesen, U. H.; Wotherspoon, S. J.

    2013-04-01

    Ecologists have an unprecedented array of bio-logging technologies available to conduct in situ studies of horizontal and vertical movement patterns of marine animals. These tracking data provide key information about foraging, migratory, and other behaviours that can be linked with bio-physical datasets to understand physiological and ecological influences on habitat selection. In most cases, however, the behavioural context is not directly observable and therefore, must be inferred. Animal movement data are complex in structure, entailing a need for stochastic analysis methods. The recent development of state-space modelling approaches for animal movement data provides statistical rigor for inferring hidden behavioural states, relating these states to bio-physical data, and ultimately for predicting the potential impacts of climate change. Despite the widespread utility, and current popularity, of state-space models for analysis of animal tracking data, these tools are not simple and require considerable care in their use. Here we develop a methodological "road map" for ecologists by reviewing currently available state-space implementations. We discuss appropriate use of state-space methods for location and/or behavioural state estimation from different tracking data types. Finally, we outline key areas where the methodology is advancing, and where it needs further development.

  12. A Latent Transition Analysis Model for Latent-State-Dependent Nonignorable Missingness.

    PubMed

    Sterba, Sonya K

    2016-06-01

    Psychologists often use latent transition analysis (LTA) to investigate state-to-state change in discrete latent constructs involving delinquent or risky behaviors. In this setting, latent-state-dependent nonignorable missingness is a potential concern. For some longitudinal models (e.g., growth models), a large literature has addressed extensions to accommodate nonignorable missingness. In contrast, little research has addressed how to extend the LTA to accommodate nonignorable missingness. Here we present a shared parameter LTA that can reduce bias due to latent-state-dependent nonignorable missingness: a parallel-process missing-not-at-random (MNAR-PP) LTA. The MNAR-PP LTA allows outcome process parameters to be interpreted as in the conventional LTA, which facilitates sensitivity analyses assessing changes in estimates between LTA and MNAR-PP LTA. In a sensitivity analysis for our empirical example, previous and current membership in high-delinquency states predicted adolescents' membership in missingness states that had high nonresponse probabilities for some or all items. A conventional LTA overestimated the proportion of adolescents ending up in a low-delinquency state, compared to an MNAR-PP LTA. PMID:25697371

  13. A framework for modeling information propagation of biological systems at critical states.

    PubMed

    Hu, Feng; Yang, Fang

    2016-03-01

    We explore the dynamics of information propagation at the critical state of a biologically inspired system by an individual-based computer model. "Quorum response", a type of social interaction which has been recognized taxonomically in animal groups, is applied as the sole interaction rule among individuals. In the model, we assume a truncated Gaussian distribution to depict the distribution of the individuals' vigilance level. Each individual can assume either a naïve state or an alarmed one and only switches from the former state to the latter one. If an individual has turned into an alarmed state, it stays in the state during the process of information propagation. Initially, each individual is set to be at the naïve state and information is tapped into the system by perturbing an individual at the boundaries (alerting it to the alarmed state). The system evolves as individuals turn into the alarmed state, according to the quorum response rules, consecutively. We find that by fine-tuning the parameters of the mean and the standard deviation of the Gaussian distribution, the system is poised at a critical state. We present the phase diagrams to exhibit that the parameter space is divided into a super-critical and a sub-critical zone, in which the dynamics of information propagation varies largely. We then investigate the effects of the individuals' mobility on the critical state, and allow a proportion of randomly chosen individuals to exchange their positions at each time step. We find that mobility breaks down criticality of the system. PMID:26876332

  14. The f-deformed Jaynes-Cummings model and its nonlinear coherent states

    NASA Astrophysics Data System (ADS)

    de los Santos-Sánchez, O.; Récamier, J.

    2012-01-01

    Based on the f-oscillator formalism, we introduce a nonlinear Jaynes-Cummings model (NJCM) which is constructed from the standard JCM by deforming the single-mode field operators. Such a generalization of the JCM describes the interaction of a two-level atom with a single mode of the electromagnetic field in the presence of a nonlinear Kerr-like medium. Since the medium is modelled as an f-oscillator, it is possible to consider the field f-coherent states (nonlinear coherent states) and their evolution.

  15. Density of states of the XY model: An energy landscape approach

    NASA Astrophysics Data System (ADS)

    Nardini, Cesare; Nerattini, Rachele; Casetti, Lapo

    2015-02-01

    Among the stationary configurations of the Hamiltonian of a classical O(n) lattice spin model, a class can be identified which is in one-to-one correspondence with all the configurations of an Ising model defined on the same lattice and with the same interactions. Starting from this observation it has been recently proposed that the microcanonical density of states of an O(n) model could be written in terms of the density of states of the corresponding Ising model. Later, it has been shown that a relation of this kind holds exactly for two solvable models, the mean-field and the one-dimensional XY model, respectively. We apply the same strategy to derive explicit, albeit approximate, expressions for the density of states of the two-dimensional XY model with nearest-neighbor interactions on a square lattice. The caloric curve and the specific heat as a function of the energy density are calculated and compared against simulation data, yielding a good agreement over the entire energy density range.

  16. Generalized Facilitated Diffusion Model for DNA-Binding Proteins with Search and Recognition States

    PubMed Central

    Bauer, Maximilian; Metzler, Ralf

    2012-01-01

    Transcription factors (TFs) such as the lac repressor find their target sequence on DNA at remarkably high rates. In the established Berg-von Hippel model for this search process, the TF alternates between three-dimensional diffusion in the bulk solution and one-dimensional sliding along the DNA chain. To overcome the so-called speed-stability paradox, in similar models the TF was considered as being present in two conformations (search state and recognition state) between which it switches stochastically. Combining both the facilitated diffusion model and alternating states, we obtain a generalized model. We explicitly treat bulk excursions for rodlike chains arranged in parallel and consider a simplified model for coiled DNA. Compared to previously considered facilitated diffusion models, corresponding to limiting cases of our generalized model, we surprisingly find a reduced target search rate. Moreover, at optimal conditions there is no longer an equipartition between the time spent by the protein on and off the DNA chain. PMID:22677385

  17. An initial state perturbation experiment with the GISS model. [random error effects on numerical weather prediction models

    NASA Technical Reports Server (NTRS)

    Spar, J.; Notario, J. J.; Quirk, W. J.

    1978-01-01

    Monthly mean global forecasts for January 1975 have been computed with the Goddard Institute for Space Studies model from four slightly different sets of initial conditions - a 'control' state and three random perturbations thereof - to simulate the effects of initial state uncertainty on forecast quality. Differences among the forecasts are examined in terms of energetics, synoptic patterns and forecast statistics. The 'noise level' of the model predictions is depicted on global maps of standard deviations of sea level pressures, 500 mb heights and 850 mb temperatures for the set of four forecasts. Initial small-scale random errors do not appear to result in any major degradation of the large-scale monthly mean forecast beyond that generated by the model itself, nor do they appear to represent the major source of large-scale forecast error.

  18. Evaluation of the Outcome-Present State Test Model as a way to teach clinical reasoning.

    PubMed

    Bartlett, Robin; Bland, Ann; Rossen, Eileen; Kautz, Donald; Benfield, Susan; Carnevale, Teresa

    2008-08-01

    The Outcome-Present State Test (OPT) Model of Clinical Reasoning is a nursing process model designed to help students develop clinical reasoning skills. Although many nurse educators are using the OPT model as a teaching strategy, few are formally evaluating its use as a method. We used the OPT model as a teaching tool in an undergraduate psychiatric and mental health clinical nursing course and evaluated how quickly students became adept at using it. Most students mastered the use of the model; 29 of 43 students achieved the criterion score (a score greater than 65 on 3 or more models completed over 4 weeks). Not only did the students gain clinical reasoning skills, but they also used and learned more about the North American Nursing Diagnosis Association, Nursing Interventions Classification, and Nursing Outcomes Classification languages. Recommendations for future use of the model include adding client strengths and increasing focus on the quality of students' responses. PMID:18751647

  19. Steady-state model for estimating gas production from underground coal gasification

    SciTech Connect

    Greg Perkins; Veena Sahajwalla

    2008-11-15

    A pseudo-one-dimensional channel model has been developed to estimate gas production from underground coal gasification. The model incorporates a zero-dimensional steady-state cavity growth submodel and models mass transfer from the bulk gas to the coal wall using a correlation for natural convection. Simulations with the model reveal that the gas calorific value is sensitive to coal reactivity and the exposed reactive surface area per unit volume in the channel. A comparison of model results with several small-scale field trials conducted at Centralia in the U.S.A. show that the model can make good predictions of the gas production and composition under a range of different operating conditions, including operation with air and steam/oxygen mixtures. Further work is required to determine whether the model formulation is also suitable for simulating large-scale underground coal gasification field trials.

  20. Experiments and modeling of freshwater lenses in layered aquifers: Steady state interface geometry

    NASA Astrophysics Data System (ADS)

    Dose, Eduardo J.; Stoeckl, Leonard; Houben, Georg J.; Vacher, H. L.; Vassolo, Sara; Dietrich, Jörg; Himmelsbach, Thomas

    2014-02-01

    The interface geometry of freshwater lenses in layered aquifers was investigated by physical 2D laboratory experiments. The resulting steady-state geometries of the lenses were compared to existing analytical expressions from Dupuit-Ghyben-Herzberg (DGH) analysis of strip-island lenses for various cases of heterogeneity. Despite the vertical exaggeration of the physical models, which would seem to vitiate the assumption of vertical equipotentials, the fits with the DGH models were generally satisfactory. Observed deviations between the analytical and physical models can be attributed mainly to outflow zones along the shore line, which are not considered in the analytical models. As unconfined natural lenses have small outflow zones compared to their overall dimensions, and flow is mostly horizontal, the DGH analytical models should perform even better at full scale. Numerical models that do consider the outflow face generally gave a good fit to the physical models.

  1. Inference and Decoding of Motor Cortex Low-Dimensional Dynamics via Latent State-Space Models.

    PubMed

    Aghagolzadeh, Mehdi; Truccolo, Wilson

    2016-02-01

    Motor cortex neuronal ensemble spiking activity exhibits strong low-dimensional collective dynamics (i.e., coordinated modes of activity) during behavior. Here, we demonstrate that these low-dimensional dynamics, revealed by unsupervised latent state-space models, can provide as accurate or better reconstruction of movement kinematics as direct decoding from the entire recorded ensemble. Ensembles of single neurons were recorded with triple microelectrode arrays (MEAs) implanted in ventral and dorsal premotor (PMv, PMd) and primary motor (M1) cortices while nonhuman primates performed 3-D reach-to-grasp actions. Low-dimensional dynamics were estimated via various types of latent state-space models including, for example, Poisson linear dynamic system (PLDS) models. Decoding from low-dimensional dynamics was implemented via point process and Kalman filters coupled in series. We also examined decoding based on a predictive subsampling of the recorded population. In this case, a supervised greedy procedure selected neuronal subsets that optimized decoding performance. When comparing decoding based on predictive subsampling and latent state-space models, the size of the neuronal subset was set to the same number of latent state dimensions. Overall, our findings suggest that information about naturalistic reach kinematics present in the recorded population is preserved in the inferred low-dimensional motor cortex dynamics. Furthermore, decoding based on unsupervised PLDS models may also outperform previous approaches based on direct decoding from the recorded population or on predictive subsampling. PMID:26336135

  2. An improved state-parameter analysis of ecosystem models using data assimilation

    USGS Publications Warehouse

    Chen, M.; Liu, S.; Tieszen, L.L.; Hollinger, D.Y.

    2008-01-01

    Much of the effort spent in developing data assimilation methods for carbon dynamics analysis has focused on estimating optimal values for either model parameters or state variables. The main weakness of estimating parameter values alone (i.e., without considering state variables) is that all errors from input, output, and model structure are attributed to model parameter uncertainties. On the other hand, the accuracy of estimating state variables may be lowered if the temporal evolution of parameter values is not incorporated. This research develops a smoothed ensemble Kalman filter (SEnKF) by combining ensemble Kalman filter with kernel smoothing technique. SEnKF has following characteristics: (1) to estimate simultaneously the model states and parameters through concatenating unknown parameters and state variables into a joint state vector; (2) to mitigate dramatic, sudden changes of parameter values in parameter sampling and parameter evolution process, and control narrowing of parameter variance which results in filter divergence through adjusting smoothing factor in kernel smoothing algorithm; (3) to assimilate recursively data into the model and thus detect possible time variation of parameters; and (4) to address properly various sources of uncertainties stemming from input, output and parameter uncertainties. The SEnKF is tested by assimilating observed fluxes of carbon dioxide and environmental driving factor data from an AmeriFlux forest station located near Howland, Maine, USA, into a partition eddy flux model. Our analysis demonstrates that model parameters, such as light use efficiency, respiration coefficients, minimum and optimum temperatures for photosynthetic activity, and others, are highly constrained by eddy flux data at daily-to-seasonal time scales. The SEnKF stabilizes parameter values quickly regardless of the initial values of the parameters. Potential ecosystem light use efficiency demonstrates a strong seasonality. Results show that the

  3. Constraints of artificial neural networks for rainfall-runoff modelling: trade-offs in hydrological state representation and model evaluation

    NASA Astrophysics Data System (ADS)

    de Vos, N. J.; Rientjes, T. H. M.

    2005-02-01

    The application of Artificial Neural Networks (ANNs) on rainfall-runoff modelling needs to be researched more extensively in order to appreciate and fulfil the potential of this modelling approach. This paper reports on the application of multi-layer feedforward ANNs for rainfall-runoff modelling in the Geer catchment (Belgium) using both daily and hourly data. The good daily forecast results indicate that ANNs can be considered alternatives for traditional rainfall-runoff modelling approaches. However, investigation of the forecasts based on hourly data reveal a constraint that has hitherto been neglected by hydrologists. A timing error occurs due to a dominating autoregressive component that is introduced by using previous runoff values as ANN model input. The reason for the popular practice of using these previous runoff data is that this information indirectly represents the hydrological state of the catchment. Two possible solutions to this timing problem are discussed. Firstly, several alternatives for representation of the hydrological state are presented: moving averages over the previous discharge and over the previous rainfall, and the output of the simple GR4J model component for soil moisture. A combination of these various hydrological state representators produces good results in terms of timing, but the overall goodness of fit is not as good as the simulations with previous runoff data. Secondly, the use of a combination of multiple measures of model performance during ANN training is suggested, since not all differences between modelled and observed hydrograph characteristics such as timing, volume, and absolute values can be adequately expressed by a single performance measure. The possible undervaluation of timing errors by the commonly-used squared-error-based functions is a clear example of this inability.

  4. Estuarine ocean exchange in a North Pacific estuary: Comparison of steady state and dynamic models

    NASA Astrophysics Data System (ADS)

    Frick, Walter E.; Khangaonkar, Tarang; Sigleo, Anne C.; Yang, Zhaoqing

    2007-08-01

    Nutrient levels in coastal waters must be accurately assessed to determine the nutrient effects of increasing populations on coastal ecosystems. To accomplish this goal, in-field data with sufficient temporal resolution are required to define nutrient sources and sinks, and to ultimately calculate nutrient budgets. Models then are required for the interpretation and analysis of data sets. To quantify the coastal ocean nitrogen input to Yaquina Bay, Oregon, nitrate concentrations were measured by a moored sensor hourly for one month during summer upwelling some distance outside the estuary entrance jetties. The time series results then were interpreted using a steady state model (Visual Plumes' PDSW) and a hydrodynamic model, the Finite Volume Coastal Ocean Model (FVCOM). The physical scales of many stream and river plumes often lie between the scales for outfall mixing zone plume models, such as those found in EPA's Visual Plumes, and larger-sized grid scales for regional circulation models like FVCOM. A potential advantage of relatively simple, steady state plume models is that they use entrainment terms to close the plume equations, theory that has proven useful in simulating turbulent plume discharges from various sources, some approaching the dimensions of rivers. Important advantages of models like FVCOM are that they are dynamic and include the effects of the Earth's rotation. The results showed that the steady-state plume model simulates observed velocity and concentration data fairly well during periods of strong discharge velocity and weak ambient coastal currents. FVCOM was judged to give better estimates under all other ambient current conditions, although the data from the mooring cannot be used to prove this assertion as stronger currents would deflect the plume away from the mooring. Nevertheless, plume models may be useful in establishing boundary and initial conditions for hydrodynamic models.

  5. Minimal moment equations for stochastic models of biochemical reaction networks with partially finite state space.

    PubMed

    Ruess, Jakob

    2015-12-28

    Many stochastic models of biochemical reaction networks contain some chemical species for which the number of molecules that are present in the system can only be finite (for instance due to conservation laws), but also other species that can be present in arbitrarily large amounts. The prime example of such networks are models of gene expression, which typically contain a small and finite number of possible states for the promoter but an infinite number of possible states for the amount of mRNA and protein. One of the main approaches to analyze such models is through the use of equations for the time evolution of moments of the chemical species. Recently, a new approach based on conditional moments of the species with infinite state space given all the different possible states of the finite species has been proposed. It was argued that this approach allows one to capture more details about the full underlying probability distribution with a smaller number of equations. Here, I show that the result that less moments provide more information can only stem from an unnecessarily complicated description of the system in the classical formulation. The foundation of this argument will be the derivation of moment equations that describe the complete probability distribution over the finite state space but only low-order moments over the infinite state space. I will show that the number of equations that is needed is always less than what was previously claimed and always less than the number of conditional moment equations up to the same order. To support these arguments, a symbolic algorithm is provided that can be used to derive minimal systems of unconditional moment equations for models with partially finite state space. PMID:26723647

  6. Minimal moment equations for stochastic models of biochemical reaction networks with partially finite state space

    NASA Astrophysics Data System (ADS)

    Ruess, Jakob

    2015-12-01

    Many stochastic models of biochemical reaction networks contain some chemical species for which the number of molecules that are present in the system can only be finite (for instance due to conservation laws), but also other species that can be present in arbitrarily large amounts. The prime example of such networks are models of gene expression, which typically contain a small and finite number of possible states for the promoter but an infinite number of possible states for the amount of mRNA and protein. One of the main approaches to analyze such models is through the use of equations for the time evolution of moments of the chemical species. Recently, a new approach based on conditional moments of the species with infinite state space given all the different possible states of the finite species has been proposed. It was argued that this approach allows one to capture more details about the full underlying probability distribution with a smaller number of equations. Here, I show that the result that less moments provide more information can only stem from an unnecessarily complicated description of the system in the classical formulation. The foundation of this argument will be the derivation of moment equations that describe the complete probability distribution over the finite state space but only low-order moments over the infinite state space. I will show that the number of equations that is needed is always less than what was previously claimed and always less than the number of conditional moment equations up to the same order. To support these arguments, a symbolic algorithm is provided that can be used to derive minimal systems of unconditional moment equations for models with partially finite state space.

  7. Adaptive Input Reconstruction with Application to Model Refinement, State Estimation, and Adaptive Control

    NASA Astrophysics Data System (ADS)

    D'Amato, Anthony M.

    Input reconstruction is the process of using the output of a system to estimate its input. In some cases, input reconstruction can be accomplished by determining the output of the inverse of a model of the system whose input is the output of the original system. Inversion, however, requires an exact and fully known analytical model, and is limited by instabilities arising from nonminimum-phase zeros. The main contribution of this work is a novel technique for input reconstruction that does not require model inversion. This technique is based on a retrospective cost, which requires a limited number of Markov parameters. Retrospective cost input reconstruction (RCIR) does not require knowledge of nonminimum-phase zero locations or an analytical model of the system. RCIR provides a technique that can be used for model refinement, state estimation, and adaptive control. In the model refinement application, data are used to refine or improve a model of a system. It is assumed that the difference between the model output and the data is due to an unmodeled subsystem whose interconnection with the modeled system is inaccessible, that is, the interconnection signals cannot be measured and thus standard system identification techniques cannot be used. Using input reconstruction, these inaccessible signals can be estimated, and the inaccessible subsystem can be fitted. We demonstrate input reconstruction in a model refinement framework by identifying unknown physics in a space weather model and by estimating an unknown film growth in a lithium ion battery. The same technique can be used to obtain estimates of states that cannot be directly measured. Adaptive control can be formulated as a model-refinement problem, where the unknown subsystem is the idealized controller that minimizes a measured performance variable. Minimal modeling input reconstruction for adaptive control is useful for applications where modeling information may be difficult to obtain. We demonstrate

  8. Hurricane Loss Estimation Models: Opportunities for Improving the State of the Art.

    NASA Astrophysics Data System (ADS)

    Watson, Charles C., Jr.; Johnson, Mark E.

    2004-11-01

    The results of hurricane loss models are used regularly for multibillion dollar decisions in the insurance and financial services industries. These models are proprietary, and this “black box” nature hinders analysis. The proprietary models produce a wide range of results, often producing loss costs that differ by a ratio of three to one or more. In a study for the state of North Carolina, 324 combinations of loss models were analyzed, based on a combination of nine wind models, four surface friction models, and nine damage models drawn from the published literature in insurance, engineering, and meteorology. These combinations were tested against reported losses from Hurricanes Hugo and Andrew as reported by a major insurance company, as well as storm total losses for additional storms. Annual loss costs were then computed using these 324 combinations of models for both North Carolina and Florida, and compared with publicly available proprietary model results in Florida. The wide range of resulting loss costs for open, scientifically defensible models that perform well against observed losses mirrors the wide range of loss costs computed by the proprietary models currently in use. This outcome may be discouraging for governmental and corporate decision makers relying on this data for policy and investment guidance (due to the high variability across model results), but it also provides guidance for the efforts of future investigations to improve loss models. Although hurricane loss models are true multidisciplinary efforts, involving meteorology, engineering, statistics, and actuarial sciences, the field of meteorology offers the most promising opportunities for improvement of the state of the art.

  9. H2-optimal control with generalized state-space models for use in control-structure optimization

    NASA Technical Reports Server (NTRS)

    Wette, Matt

    1991-01-01

    Several advances are provided solving combined control-structure optimization problems. The author has extended solutions from H2 optimal control theory to the use of generalized state space models. The generalized state space models preserve the sparsity inherent in finite element models and hence provide some promise for handling very large problems. Also, expressions for the gradient of the optimal control cost are derived which use the generalized state space models.

  10. Ising spin network states for loop quantum gravity: a toy model for phase transitions

    NASA Astrophysics Data System (ADS)

    Feller, Alexandre; Livine, Etera R.

    2016-03-01

    Non-perturbative approaches to quantum gravity call for a deep understanding of the emergence of geometry and locality from the quantum state of the gravitational field. Without background geometry, the notion of distance should emerge entirely from the correlations between the gravity fluctuations. In the context of loop quantum gravity, quantum states of geometry are defined as spin networks. These are graphs decorated with spin and intertwiners, which represent quantized excitations of areas and volumes of the space geometry. Here, we develop the condensed-matter point of view on extracting the physical and geometrical information from spin network states: we introduce new Ising spin network states, both in 2d on a square lattice and in 3d on a hexagonal lattice, whose correlations map onto the usual Ising model in statistical physics. We construct these states from the basic holonomy operators of loop gravity and derive a set of local Hamiltonian constraints that entirely characterize our states. We discuss their phase diagram and show how the distance can be reconstructed from the correlations in the various phases. Finally, we propose generalizations of these Ising states, which open the perspective to study the coarse-graining and dynamics of spin network states using well-known condensed-matter techniques and results.

  11. GENERAL: Stochastic Four-State Mechanochemical Model of F1-ATPase

    NASA Astrophysics Data System (ADS)

    Wu, Wei-Xia; Zhan, Yong; Zhao, Tong-Jun; Han, Ying-Rong; Chen, Ya-Fei

    2010-10-01

    F1-ATPase, a part of ATP synthase, can synthesize and hydrolyze ATP moleculars in which the central γ-subunit rotates inside the α3 β3cylinder. A stochastic four-state mechanochemical coupling model of F1-ATPase is studied with the aid of the master equation. In this model, the ATP hydrolysis and synthesis are dependent on ATP, ADP, and Pi concentrations. The effects of ATP concentration, ADP concentration, and the external torque on the occupation probability of binding-state, the rotation rate and the diffusion coefficient of F1-ATPase are investigated. Moreover, the results from this model are compared with experiments. The mechanochemical mechanism F1-ATPase is qualitatively explained by the model.

  12. Validating SESAME Equations of State for Use in Hydrocode Models of Small Solar System Bodies

    NASA Astrophysics Data System (ADS)

    Catherine, Plesko; Ferguson, Jim; Gisler, Galen R.; Weaver, Robert P.

    2014-11-01

    Hydrodynamic models of small solar system body impacts, collisions, and hazard mitigation require material-specific equations of state (EOS's) in order to close the system of equations that comprise the model and accurately predict the response of such objects to shocks and other hydrodynamic phenomena. Current models approximate meteoritic and cometary materials using Earth-analogue EOS's, e.g., quartz, dunite, hydrated tuff, water ice, and numerical convolutions of analog EOS's. Earth-analogues are used because the formulation of a comprehensive equation of state requires a large amount of experimental data that is destructive to the often rare samples. Analogue EOS's can, however, perform very differently from the original material under shock loading. Some experimental data has become available over time for various meteorite types. Here we compare the available shock data for meteoritic materials to analogue EOS's available in the public Los Alamos National Laboratory SESAME EOS database to explore the applicability and limitations of these models.

  13. A diabatic state model for double proton transfer in hydrogen bonded complexes

    SciTech Connect

    McKenzie, Ross H.

    2014-09-14

    Four diabatic states are used to construct a simple model for double proton transfer in hydrogen bonded complexes. Key parameters in the model are the proton donor-acceptor separation R and the ratio, D{sub 1}/D{sub 2}, between the proton affinity of a donor with one and two protons. Depending on the values of these two parameters the model describes four qualitatively different ground state potential energy surfaces, having zero, one, two, or four saddle points. Only for the latter are there four stable tautomers. In the limit D{sub 2} = D{sub 1} the model reduces to two decoupled hydrogen bonds. As R decreases a transition can occur from a synchronous concerted to an asynchronous concerted to a sequential mechanism for double proton transfer.

  14. Charge-state-dependent energy loss of slow ions. II. Statistical atom model

    NASA Astrophysics Data System (ADS)

    Wilhelm, Richard A.; Möller, Wolfhard

    2016-05-01

    A model for charge-dependent energy loss of slow ions is developed based on the Thomas-Fermi statistical model of atoms. Using a modified electrostatic potential which takes the ionic charge into account, nuclear and electronic energy transfers are calculated, the latter by an extension of the Firsov model. To evaluate the importance of multiple collisions even in nanometer-thick target materials we use the charge-state-dependent potentials in a Monte Carlo simulation in the binary collision approximation and compare the results to experiment. The Monte Carlo results reproduce the incident charge-state dependence of measured data well [see R. A. Wilhelm et al., Phys. Rev. A 93, 052708 (2016), 10.1103/PhysRevA.93.052708], even though the experimentally observed charge exchange dependence is not included in the model.

  15. Spectral Reflectance Features in Crop State and Yield Models Considering Soil and Anthropogenic Impacts

    NASA Astrophysics Data System (ADS)

    Kancheva, R.; Borisova, D.

    Agricultural models for estimating plant processes and growth require explicit information of soil, vegetation, climate, etc. Remote sensing is a tool that can be used to measure vegetation parameters for input into these models. Especially valuable are temporal data about crop state and crop development under different conditions. This paper is devoted to spectral-biophysical modeling of agricultural plants considering crop ontogenesis and dependency on soil properties (organic matter, pH-factor, nutrient accessibility) and anthropogenic impacts (fertilization, contamination). Ground-based VIS and NIR measurements have been performed to establish and statistically validate empirical relationships between crop reflectance and agronomic parameters taking into account the specific growing conditions. These relationships provide crop state assessment over the growing season. The estimated from spectral data bioparameters have been used in yield-predicting models linking crop production with plant agronomic variables. The results have been compared to the approach of using reflectance temporal behavior for yield assessment.

  16. The Western States Water Mission: A Hyper-Resolution Hydrological Modeling and Data Integration Platform

    NASA Astrophysics Data System (ADS)

    Famiglietti, James; Basilio, Ralph; Trangsrud, Amy; Andreadis, Kostas; Cricthon, Dan; David, Cedric; Farr, Thomas; Malhotra, Shan; Neff, Kirstin; Reager, John

    2016-04-01

    Hydrological remote sensing has advanced significantly over the last decade, and will continue to grow with number of recent and near-future launched. Arguably, a platform for synthesizing remote observations is an important step towards improved modeling, understanding and prediction of terrestrial hydrology. In this presentation we describe the new NASA Western States Water Mission, a high-resolution, catchment-based modeling and data assimilation platform implemented for the western United States. Model structure will be described, as well as early results that include assimilation of satellite snow observations. A key feature of model development has been its treatment as a 'flight project' which enables leveraging of important NASA systems engineering and project management expertise.

  17. Anatomy of an Error: A Bidirectional State Model of Task Engagement/Disengagement and Attention-Related Errors

    ERIC Educational Resources Information Center

    Cheyne, J. Allan; Solman, Grayden J. F.; Carriere, Jonathan S. A.; Smilek, Daniel

    2009-01-01

    We present arguments and evidence for a three-state attentional model of task engagement/disengagement. The model postulates three states of mind-wandering: occurrent task inattention, generic task inattention, and response disengagement. We hypothesize that all three states are both causes and consequences of task performance outcomes and apply…

  18. An equivalent layer magnetization model for the United States derived from MAGSAT data

    NASA Technical Reports Server (NTRS)

    Mayhew, M. A.; Galliher, S. C. (Principal Investigator)

    1982-01-01

    Long wavelength anomalies in the total magnetic field measured field measured by MAGSAT over the United States and adjacent areas are inverted to an equivalent layer crustal magnetization distribution. The model is based on an equal area dipole grid at the Earth's surface. Model resolution having physical significance, is about 220 km for MAGSAT data in the elevation range 300-500 km. The magnetization contours correlate well with large-scale tectonic provinces.

  19. Reduced model of the evolution of the polarization states in wavelength-division-multiplexed channels

    SciTech Connect

    Wang, D.; Menyuk, C.R.

    1998-11-01

    We have developed a reduced model of the evolution of the polarization states of the channels in a wavelength-division-multiplexed system that follows only the Stokes parameters for each channel. We apply this model to demonstrating that the expected repolarization of polarization-scrambled signals is small. We verify our results by comparing them with numerical simulations with realistic parameters. {copyright} {ital 1998} {ital Optical Society of America}

  20. Modeling Winter Rainfall in Northwest India using a Hidden Markov Model: Understanding Occurrence of Different States and their Dynamical Connections

    NASA Astrophysics Data System (ADS)

    Pal, I.; Robertson, A. W.; Lall, U.; Cane, M. A.

    2013-12-01

    A multiscale-modeling framework for daily rainfall is considered and diagnostic results are presented for an application to the winter season in Northwest India. The daily rainfall process is considered to follow a Hidden Markov Model (HMM), with the hidden states assumed to be an unknown random function of slowly varying climatic modulation of the winter jet stream and moisture transport dynamics. The data used are from 14 stations over the Satluj River basin in northwest India in winter (Dec-Jan-Feb-Mar). The period considered is 1977/78-2005/06. The HMM identifies four discrete weather states, which are used to describe daily rainfall variability over the study region. The first hidden state has low rainfall occurrence and intensity, the second has modest occurrence and low intensity, the third has high occurrence but low to modest intensity and the fourth has high frequency and intensity of daily rainfall. Each state was found to be associated with a distinct atmospheric circulation pattern, with States 3 and 4 characterized by a zonally oriented wave train extending across Eurasia between 20N-40N, identified with ';Western Disturbances'. State 1, by contrast, is characterized by a lack of synoptic wave activity. The occurrence of State 4 is strongly conditioned by the El Nino and Indian Ocean Dipole (IOD) phenomena in winter, which is demonstrated using large-scale correlation maps based on mean sea level pressure (MSLP) and sea surface temperature (SST). This suggests that there is a tendency of higher frequency of the wet days and intense Western Disturbances in winter during El Nino and positive IOD years. These findings, derived from daily rainfall station records, help clarify the sequence of Northern Hemisphere mid-latitude storms bringing winter rainfall over Northwest India, and their association with potentially predictable low frequency modes on seasonal time scales and longer.

  1. A new method of modeling and state of charge estimation of the battery

    NASA Astrophysics Data System (ADS)

    Liu, Congzhi; Liu, Weiqun; Wang, Lingyan; Hu, Guangdi; Ma, Luping; Ren, Bingyu

    2016-07-01

    Accurately estimating the State of Charge (SOC) of the battery is the basis of Battery Management System (BMS). This paper has introduced a new modeling and state estimation method for the lithium battery system, which utilizes the fractional order theories. Firstly, a fractional order model based on the PNGV (Partnership for a New Generation of Vehicle) model is proposed after analyzing the impedance characteristics of the lithium battery and compared with the integer order model. With the observability of the discrete non-linear model of the battery confirmed, the method of the state observer based on the extended fractional Kalman filter (EFKF) and the least square identification method of battery parameters are studied. Then, it has been applied successfully to estimate the battery SOC using the measured battery current and voltage. Finally, a standard HPPC (Hybrid Pulse Power Characteristic) test is used for parameter identification and several experimental validations are investigated on a ternary manganese-nickel-cobalt lithium battery pack with a nominal capacity of 24 Ah which consists of ten Sony commercial cells (US18650GR G7) in parallels. The results demonstrate the effectiveness of the fractional order model and the estimation method.

  2. Steady-state and dynamic models for particle engulfment during solidification

    NASA Astrophysics Data System (ADS)

    Tao, Yutao; Yeckel, Andrew; Derby, Jeffrey J.

    2016-06-01

    Steady-state and dynamic models are developed to study the physical mechanisms that determine the pushing or engulfment of a solid particle at a moving solid-liquid interface. The mathematical model formulation rigorously accounts for energy and momentum conservation, while faithfully representing the interfacial phenomena affecting solidification phase change and particle motion. A numerical solution approach is developed using the Galerkin finite element method and elliptic mesh generation in an arbitrary Lagrangian-Eulerian implementation, thus allowing for a rigorous representation of forces and dynamics previously inaccessible by approaches using analytical approximations. We demonstrate that this model accurately computes the solidification interface shape while simultaneously resolving thin fluid layers around the particle that arise from premelting during particle engulfment. We reinterpret the significance of premelting via the definition an unambiguous critical velocity for engulfment from steady-state analysis and bifurcation theory. We also explore the complicated transient behaviors that underlie the steady states of this system and posit the significance of dynamical behavior on engulfment events for many systems. We critically examine the onset of engulfment by comparing our computational predictions to those obtained using the analytical model of Rempel and Worster [29]. We assert that, while the accurate calculation of van der Waals repulsive forces remains an open issue, the computational model developed here provides a clear benefit over prior models for computing particle drag forces and other phenomena needed for the faithful simulation of particle engulfment.

  3. Computing the modal mass from the state space model in combined experimental-operational modal analysis

    NASA Astrophysics Data System (ADS)

    Cara, Javier

    2016-05-01

    Modal parameters comprise natural frequencies, damping ratios, modal vectors and modal masses. In a theoretic framework, these parameters are the basis for the solution of vibration problems using the theory of modal superposition. In practice, they can be computed from input-output vibration data: the usual procedure is to estimate a mathematical model from the data and then to compute the modal parameters from the estimated model. The most popular models for input-output data are based on the frequency response function, but in recent years the state space model in the time domain has become popular among researchers and practitioners of modal analysis with experimental data. In this work, the equations to compute the modal parameters from the state space model when input and output data are available (like in combined experimental-operational modal analysis) are derived in detail using invariants of the state space model: the equations needed to compute natural frequencies, damping ratios and modal vectors are well known in the operational modal analysis framework, but the equation needed to compute the modal masses has not generated much interest in technical literature. These equations are applied to both a numerical simulation and an experimental study in the last part of the work.

  4. Open boundaries in a cellular automaton model for traffic flow with metastable states

    NASA Astrophysics Data System (ADS)

    Barlovic, Robert; Huisinga, Torsten; Schadschneider, Andreas; Schreckenberg, Michael

    2002-10-01

    The effects of open boundaries in the velocity-dependent randomization (VDR) model, a modified version of the well-known Nagel-Schreckenberg (NaSch) cellular automaton model for traffic flow, are investigated. In contrast to the NaSch model, the VDR model exhibits metastable states and phase separation in a certain density regime. A proper insertion strategy allows us to investigate the whole spectrum of possible system states and the structure of the phase diagram by Monte Carlo simulations. We observe an interesting microscopic structure of the jammed phases, which is different from the one of the NaSch model. For finite systems, the existence of high flow states in a certain parameter regime leads to a special structure of the fundamental diagram measured in the open system. Apart from that, the results are in agreement with an extremal principle for the flow, which has been introduced for models with a unique flow-density relation. Finally, we discuss the application of our findings for a systematic flow optimization. Here some surprising results are obtained, e.g., a restriction of the inflow can lead to an improvement of the total flow through a bottleneck.

  5. On the Finiteness of Collisions and Phase-Locked States for the Kuramoto Model

    NASA Astrophysics Data System (ADS)

    Ha, Seung-Yeal; Kim, Hwa Kil; Ryoo, Sang Woo

    2016-04-01

    Synchronization phenomenon is ubiquitous in our complex systems, and many phenomenological models have been proposed and studied analytically and numerically. Among them, the Kuramoto model serves as a prototype model for the phase synchronization of weakly coupled oscillators. In this paper, we study the finiteness of collisions (crossings) among Kuramoto oscillators in the relaxation process toward the phase-locked states and the total number of phase-locked states with positive (Kuramoto) order parameters. For identical oscillators, it is well known that collisions between distinct oscillators cannot occur in finite-time, and we show that there are only a finite number of phase-locked states with positive order parameters. However, for non-identical oscillators, oscillators with different natural frequencies can cross each other in their relaxation process, and estimating the total number of phase-locked states is a nontrivial matter. We show that, for the non-identical case, asymptotic phase-locking is equivalent to the finiteness of collisions, and the total number of phase-locked states with positive order parameters is bounded above by 2^N , where N is the number of oscillators.

  6. The k-sample problem in a multi-state model and testing transition probability matrices.

    PubMed

    Tattar, Prabhanjan N; Vaman, H J

    2014-07-01

    The choice of multi-state models is natural in analysis of survival data, e.g., when the subjects in a study pass through different states like 'healthy', 'in a state of remission', 'relapse' or 'dead' in a health related quality of life study. Competing risks is another common instance of the use of multi-state models. Statistical inference for such event history data can be carried out by assuming a stochastic process model. Under such a setting, comparison of the event history data generated by two different treatments calls for testing equality of the corresponding transition probability matrices. The present paper proposes solution to this class of problems by assuming a non-homogeneous Markov process to describe the transitions among the health states. A class of test statistics are derived for comparison of [Formula: see text] treatments by using a 'weight process'. This class, in particular, yields generalisations of the log-rank, Gehan, Peto-Peto and Harrington-Fleming tests. For an intrinsic comparison of the treatments, the 'leave-one-out' jackknife method is employed for identifying influential observations. The proposed methods are then used to develop the Kolmogorov-Smirnov type supremum tests corresponding to the various extended tests. To demonstrate the usefulness of the test procedures developed, a simulation study was carried out and an application to the Trial V data provided by International Breast Cancer Study Group is discussed. PMID:23722306

  7. On the Finiteness of Collisions and Phase-Locked States for the Kuramoto Model

    NASA Astrophysics Data System (ADS)

    Ha, Seung-Yeal; Kim, Hwa Kil; Ryoo, Sang Woo

    2016-06-01

    Synchronization phenomenon is ubiquitous in our complex systems, and many phenomenological models have been proposed and studied analytically and numerically. Among them, the Kuramoto model serves as a prototype model for the phase synchronization of weakly coupled oscillators. In this paper, we study the finiteness of collisions (crossings) among Kuramoto oscillators in the relaxation process toward the phase-locked states and the total number of phase-locked states with positive (Kuramoto) order parameters. For identical oscillators, it is well known that collisions between distinct oscillators cannot occur in finite-time, and we show that there are only a finite number of phase-locked states with positive order parameters. However, for non-identical oscillators, oscillators with different natural frequencies can cross each other in their relaxation process, and estimating the total number of phase-locked states is a nontrivial matter. We show that, for the non-identical case, asymptotic phase-locking is equivalent to the finiteness of collisions, and the total number of phase-locked states with positive order parameters is bounded above by 2^N, where N is the number of oscillators.

  8. Shell-model description of the charge form factor and the first excited state in /sup 4/He

    SciTech Connect

    Bevelacqua, J.J.

    1982-09-01

    A /sup 4/He shell-model formalism, including two- and three-body forces, is used to calculate ground and first excited state properties. Inclusion of the three-body force improves the calculated ground state rms radius, ground state form factor, and position of the /sup 4/He first excited state.

  9. Classification of Multiple Seizure-Like States in Three Different Rodent Models of Epileptogenesis.

    PubMed

    Guirgis, Mirna; Serletis, Demitre; Zhang, Jane; Florez, Carlos; Dian, Joshua A; Carlen, Peter L; Bardakjian, Berj L

    2014-01-01

    Epilepsy is a dynamical disease and its effects are evident in over fifty million people worldwide. This study focused on objective classification of the multiple states involved in the brain's epileptiform activity. Four datasets from three different rodent hippocampal preparations were explored, wherein seizure-like-events (SLE) were induced by the perfusion of a low - Mg(2+) /high-K(+) solution or 4-Aminopyridine. Local field potentials were recorded from CA3 pyramidal neurons and interneurons and modeled as Markov processes. Specifically, hidden Markov models (HMM) were used to determine the nature of the states present. Properties of the Hilbert transform were used to construct the feature spaces for HMM training. By sequentially applying the HMM training algorithm, multiple states were identified both in episodes of SLE and nonSLE activity. Specifically, preSLE and postSLE states were differentiated and multiple inner SLE states were identified. This was accomplished using features extracted from the lower frequencies (1-4 Hz, 4-8 Hz) alongside those of both the low- (40-100 Hz) and high-gamma (100-200 Hz) of the recorded electrical activity. The learning paradigm of this HMM-based system eliminates the inherent bias associated with other learning algorithms that depend on predetermined state segmentation and renders it an appropriate candidate for SLE classification. PMID:23771347

  10. Automatic detection of volcano-seismic events by modeling state and event duration in hidden Markov models

    NASA Astrophysics Data System (ADS)

    Bhatti, Sohail Masood; Khan, Muhammad Salman; Wuth, Jorge; Huenupan, Fernando; Curilem, Millaray; Franco, Luis; Yoma, Nestor Becerra

    2016-09-01

    In this paper we propose an automatic volcano event detection system based on Hidden Markov Model (HMM) with state and event duration models. Since different volcanic events have different durations, therefore the state and whole event durations learnt from the training data are enforced on the corresponding state and event duration models within the HMM. Seismic signals from the Llaima volcano are used to train the system. Two types of events are employed in this study, Long Period (LP) and Volcano-Tectonic (VT). Experiments show that the standard HMMs can detect the volcano events with high accuracy but generates false positives. The results presented in this paper show that the incorporation of duration modeling can lead to reductions in false positive rate in event detection as high as 31% with a true positive accuracy equal to 94%. Further evaluation of the false positives indicate that the false alarms generated by the system were mostly potential events based on the signal-to-noise ratio criteria recommended by a volcano expert.

  11. Accurate state estimation from uncertain data and models: an application of data assimilation to mathematical models of human brain tumors

    PubMed Central

    2011-01-01

    Background Data assimilation refers to methods for updating the state vector (initial condition) of a complex spatiotemporal model (such as a numerical weather model) by combining new observations with one or more prior forecasts. We consider the potential feasibility of this approach for making short-term (60-day) forecasts of the growth and spread of a malignant brain cancer (glioblastoma multiforme) in individual patient cases, where the observations are synthetic magnetic resonance images of a hypothetical tumor. Results We apply a modern state estimation algorithm (the Local Ensemble Transform Kalman Filter), previously developed for numerical weather prediction, to two different mathematical models of glioblastoma, taking into account likely errors in model parameters and measurement uncertainties in magnetic resonance imaging. The filter can accurately shadow the growth of a representative synthetic tumor for 360 days (six 60-day forecast/update cycles) in the presence of a moderate degree of systematic model error and measurement noise. Conclusions The mathematical methodology described here may prove useful for other modeling efforts in biology and oncology. An accurate forecast system for glioblastoma may prove useful in clinical settings for treatment planning and patient counseling. Reviewers This article was reviewed by Anthony Almudevar, Tomas Radivoyevitch, and Kristin Swanson (nominated by Georg Luebeck). PMID:22185645

  12. Persistent Cold States of the Tropical Pacific Ocean in an Intermediate Coupled Model and a General Circulation Model

    NASA Astrophysics Data System (ADS)

    Ramesh, N.; Cane, M. A.; Seager, R.

    2014-12-01

    The tropical Pacific Ocean has persistently cool sea surface temperature (SST) anomalies that last several years to a decade, with either no El Niño events or very few weak El Niño events. These have been shown to cause large-scale droughts in the extratropics[i], including the major North American droughts such as the 1930s Dust Bowl, and may also be responsible for modulating the global mean surface temperature[ii]. Here we show that two models with different levels of complexity - the Zebiak-Cane model and the Geophysical Fluid Dynamics Laboratory Coupled Model version 2.1 - are able to produce such periods in a realistic manner. We then test the predictability of these periods in the Zebiak-Cane model using an ensemble of experiments with perturbed initial states. Our results show that the cool mean state is modestly predictable, while the lack of El Niño events during these cool periods is not. These results have implications for our understanding of the origins of such persistent cool states and the possibility of improving predictions of large-scale droughts. Further, we apply this method of using an ensemble of model simulations with perturbed initial states to make retrospective forecasts and to forecast the mean state of the tropical Pacific Ocean for the upcoming decade. Our results suggest, albeit with low confidence, that the current cool mean state will persist. This could imply the continuation of the drier than normal conditions that have, in general, afflicted southwest North America since the 1997/98 El Niño, as well as the current pause in global warming. [i] C. Herweijer and R. Seager, "The global footprint of persistent extra-tropical drought in the instrumental era," International Journal of Climatology, vol. 28, pp. 1761-1774, 2008. [ii] G. A. Meehl, J. M. Arblaster, J. T. Fasullo, A. Hu and K. E. Trenberth, "Model-based evidence of deep-ocean heat uptake during surface-temperature hiatus periods," Nature Climate Change, vol. 1, pp. 360

  13. Comparison of Four Different Energy Balance Models for Estimating Evapotranspiration in the Midwest United States

    NASA Astrophysics Data System (ADS)

    Singh, R. K.; Senay, G. B.; Verdin, J. P.

    2015-12-01

    Availability of no-cost satellite images helped in development and utilization of remotely sensed images for water use estimation. Remotely sensed images are increasingly used for estimating evapotranspiration (ET) at different temporal and spatial scales. However, selecting any particular model from a plethora of energy balance models for estimating ET is challenging as each different model has its strengths and limitations. We compared four commonly used ET models, namely, Mapping EvapoTranspiration at high Resolution with Internalized Calibration (METRIC) model, Surface Energy Balance Algorithm for Land (SEBAL) model, Surface Energy Balance System (SEBS) model, and Operational Simplified Surface Energy Balance (SSEBop) model using Landsat images for estimating ET in the Midwest United States. We validated our model results using three AmeriFlux cropland sites at Mead, Nebraska. Our results showed that the METRIC and the SSEBop model worked very well at these sites with a root mean square error (RMSE) of less than 1 mm/day and an R2 of 0.96 (N=24). The mean bias error (MBE) was less than 10% for both the METRIC and the SSEBop models. In contrast, the SEBAL and the SEBS models have relatively higher RMSE (> 1.7 mm/day) and MBE (> 27%). However, all four models captured the spatial and temporal variation of ET reasonably well (R2 > 0.80). We found that the model simplification of the SSEBop for operational capability was not at the expense of model accuracy. Since the SSEBop model is relatively less data intensive and independent of user/automatic selection of anchor (hot/dry and cold/wet) pixels, it is more user friendly and operationally efficient. The SSEBop model can be reliably used for estimating water use using Landsat and MODIS images at daily, weekly, monthly, or annual time scale even in data scarce regions for sustainable use of limited water resources.

  14. Vortex dynamics in a three-state model under cyclic dominance.

    PubMed

    Szabó, G; Santos, M A; Mendes, J F

    1999-10-01

    The evolution of domain structure is investigated in a two-dimensional voter model with three states under cyclic dominance. The study focus on the dynamics of vortices, defined by the points where the three states (domains) meet. We can distinguish vortices and antivortices which walk randomly and annihilate each other. The domain wall motion can create vortex-antivortex pairs at a rate that is increased by the spiral formation due to cyclic dominance. This mechanism is contrasted with a branching annihilating random walk (BARW) in a particle-antiparticle system with density-dependent pair creation rate. Numerical estimates for the critical indices of the vortex density [beta=0.29(4)] and of its fluctuation [gamma=0.34(6)] improve an earlier Monte Carlo study [K. Tainaka and Y. Itoh, Europhys. Lett. 15, 399 (1991)] of the three-state cyclic model in two dimensions. PMID:11970211

  15. String states, loops and effective actions in noncommutative field theory and matrix models

    NASA Astrophysics Data System (ADS)

    Steinacker, Harold C.

    2016-09-01

    Refining previous work by Iso, Kawai and Kitazawa, we discuss bi-local string states as a tool for loop computations in noncommutative field theory and matrix models. Defined in terms of coherent states, they exhibit the stringy features of noncommutative field theory. This leads to a closed form for the 1-loop effective action in position space, capturing the long-range non-local UV/IR mixing for scalar fields. The formalism applies to generic fuzzy spaces. The non-locality is tamed in the maximally supersymmetric IKKT or IIB model, where it gives rise to supergravity. The linearized supergravity interactions are obtained directly in position space at one loop using string states on generic noncommutative branes.

  16. Periodic one-dimensional hopping model with transitions between nonadjacent states.

    PubMed

    Zhang, Yunxin

    2011-09-01

    A one-dimensional hopping model is useful for describing the motion of microscopic particles in a thermal noise environment. Recent experiments on the new generation of light-driven rotary molecular motors found that a motor in state i can jump forward to state i+1 or i+2 or backward to state i-1 or i-2 directly. In this paper, inspired by these experiments, such a modified periodic one-dimensional hopping model with arbitrary period N is studied theoretically. The mean velocity, effective diffusion constant, and mean dwell time in one single mechanochemical cycle are obtained. The corresponding results are illustrated and verified by being applied to the synthetic rotary molecular motors. PMID:22060325

  17. A two-state hysteresis model from high-dimensional friction.

    PubMed

    Biswas, Saurabh; Chatterjee, Anindya

    2015-07-01

    In prior work (Biswas & Chatterjee 2014 Proc. R. Soc. A 470, 20130817 (doi:10.1098/rspa.2013.0817)), we developed a six-state hysteresis model from a high-dimensional frictional system. Here, we use a more intuitively appealing frictional system that resembles one studied earlier by Iwan. The basis functions now have simple analytical description. The number of states required decreases further, from six to the theoretical minimum of two. The number of fitted parameters is reduced by an order of magnitude, to just six. An explicit and faster numerical solution method is developed. Parameter fitting to match different specified hysteresis loops is demonstrated. In summary, a new two-state model of hysteresis is presented that is ready for practical implementation. Essential Matlab code is provided. PMID:26587279

  18. Ordered vs. disordered states of the random-field model in three dimensions

    NASA Astrophysics Data System (ADS)

    Garanin, Dmitry A.; Chudnovsky, Eugene M.

    2015-04-01

    We report numerical investigation of the glassy behavior of random-field exchange models in three dimensions. Correlation of energy with the magnetization for different numbers of spin components has been studied. There is a profound difference between the models with two and three spin components with respect to the stability of the magnetized state due to the different kinds of singularities: vortex loops and hedgehogs, respectively. Memory effects pertinent to such states have been investigated. Insight into the mechanism of the large-scale disordering is provided by numerically implementing the Imry-Ma argument in which the spins follow the random field averaged over correlated volumes. Thermal stability of the magnetized states is investigated by the Monte Carlo method.

  19. Instanton effects in lattice models of bosonic symmetry-protected topological states

    NASA Astrophysics Data System (ADS)

    Santos, Luiz H.; Fradkin, Eduardo

    2016-04-01

    Bosonic symmetry-protected topological (SPT) states are gapped disordered phases of matter possessing symmetry-preserving boundary excitations. It has been proposed that, at long wavelengths, the universal properties of an SPT system are captured by an effective nonlinear sigma model field theory in the presence of a quantized topological θ term. By studying lattice models of bosonic SPT states, we are able to identify, in their Euclidean path integral formulation, (discrete) Berry phases that hold relevant physical information on the nature of the SPT ground states. These discrete Berry phases are given intuitive physical interpretation in terms of instanton effects that capture the presence of a θ term on the microscopic scale.

  20. A two-state hysteresis model from high-dimensional friction

    PubMed Central

    Biswas, Saurabh; Chatterjee, Anindya

    2015-01-01

    In prior work (Biswas & Chatterjee 2014 Proc. R. Soc. A 470, 20130817 (doi:10.1098/rspa.2013.0817)), we developed a six-state hysteresis model from a high-dimensional frictional system. Here, we use a more intuitively appealing frictional system that resembles one studied earlier by Iwan. The basis functions now have simple analytical description. The number of states required decreases further, from six to the theoretical minimum of two. The number of fitted parameters is reduced by an order of magnitude, to just six. An explicit and faster numerical solution method is developed. Parameter fitting to match different specified hysteresis loops is demonstrated. In summary, a new two-state model of hysteresis is presented that is ready for practical implementation. Essential Matlab code is provided. PMID:26587279