Science.gov

Sample records for state interindustry models

  1. 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…

  2. Economic effects of state park recreation in Pennsylvania

    Treesearch

    Charles H. Strauss; Bruce E. Lord

    1992-01-01

    The economic effects resulting from the use and operation of Pennsylvania's state park system were analyzed with an input-output model of the state's economy. Direct expenditures by park users and park operations were estimated at $263 million for the 1987 study year. Secondary effects, stemming from interindustry trade and recreation-related employment,...

  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. PROCEEDINGS OF SECOND INTERINDUSTRIAL OCEANOGRAPHIC SYMPOSIUM, DECEMBER 11, 1962, SANTA BARBARA, CALIFORNIA

    DTIC Science & Technology

    Contents: THE INTERINDUSTRIAL OCEANOGRAPHIC SYMPOSIA; AN UNTENDED DIGITAL DATA ACQUISITION SYSTEM; NUMERICAL WIND-WAVE FORECASTING; THE GENERAL ... MOTORS DEEP-SEA BUOY SYSTEM; ACOUSTIC SCATTERING MEASUREMENTS AS INDICATORS OF WATER IN HOMOGENEITIES; AN OCEANOGRAPHIC DATA AND COMMUNICATIONS SYSTEM

  5. The topology of inter-industry relations from the Portuguese national accounts

    NASA Astrophysics Data System (ADS)

    Araújo, Tanya; Faustino, Rui

    2017-08-01

    In last years, the Portuguese economy has gone through a severe adjustment process, affecting almost all industrial sectors, the building blocks of economic structures. Research on economic structural changes has made use of input/output tables to define networks of industrial relations. Here, these networks are induced from output tables of the Portuguese national accounting system, being each inter-industry relation defined by the output made by any two industries for the products that they both produce. The topological analysis of these networks allows to uncover a particular structure that comes out during the Portuguese adjustment program. The evolution of the industrial networks shows an important structural change in 2011-2014, confirming the usefulness of inducting similarity networks from output tables and the consequent promising power of the graph formulation for the analysis of inter-industry relations.

  6. The effects on earnings of interregional and interindustry migration.

    PubMed

    Nakosteen, R A; Zimmer, M A

    1982-08-01

    "The purpose of this study is to examine a model of the decision to migrate between regions and/or industries and its effect on earnings. The study is based on a large set of individual microdata taken from the [U.S.] Social Security Administration's One Percent Continuous Work History Sample." The data are for 1971 and 1973. "Results of estimation provide strong support for the hypothesis of self-selection among region and industry migrants. Additional empirical evidence supports the notion of comparative advantage in migrant earnings, implying that earnings distributions of individuals who made a particular combination of migration decisions may differ from those of the population as a whole."

  7. 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…

  8. 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…

  9. 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.

  10. 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.

  11. 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.

  12. Probability state modeling theory.

    PubMed

    Bagwell, C Bruce; Hunsberger, Benjamin C; Herbert, Donald J; Munson, Mark E; Hill, Beth L; Bray, Chris M; Preffer, Frederic I

    2015-07-01

    As the technology of cytometry matures, there is mounting pressure to address two major issues with data analyses. The first issue is to develop new analysis methods for high-dimensional data that can directly reveal and quantify important characteristics associated with complex cellular biology. The other issue is to replace subjective and inaccurate gating with automated methods that objectively define subpopulations and account for population overlap due to measurement uncertainty. Probability state modeling (PSM) is a technique that addresses both of these issues. The theory and important algorithms associated with PSM are presented along with simple examples and general strategies for autonomous analyses. PSM is leveraged to better understand B-cell ontogeny in bone marrow in a companion Cytometry Part B manuscript. Three short relevant videos are available in the online supporting information for both of these papers. PSM avoids the dimensionality barrier normally associated with high-dimensionality modeling by using broadened quantile functions instead of frequency functions to represent the modulation of cellular epitopes as cells differentiate. Since modeling programs ultimately minimize or maximize one or more objective functions, they are particularly amenable to automation and, therefore, represent a viable alternative to subjective and inaccurate gating approaches.

  13. 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.

  14. 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.

  15. 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)

  16. 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)

  17. 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.

  18. 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.

  19. 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...

  20. 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...

  1. 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).

  2. A dynamic simulation model for analyzing the importance of forest resources in Alaska.

    Treesearch

    Wilbur R. Maki; Douglas Olson; Con H. Schallau

    1985-01-01

    A dynamic simulation model has been adapted for use in Alaska. It provides a flexible tool for examining the economic consequences of alternative forest resource management policies. The model could be adapted for use elsewhere if an interindustry transaction table is available or can be developed. To demonstrate the model's usefulness, the contribution of the...

  3. 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…

  4. 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…

  5. 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

  6. State representations of ARMA-models

    NASA Astrophysics Data System (ADS)

    Lomadze, Vakhtang

    2010-10-01

    A state representation of an arbitrary ARMA-model is computed explicitly. It is shown then that every ARMA-model is homotopy equivalent to its state representation, and that two state models are homotopy equivalent if and only if they are similar.

  7. Ecological Implications of Steady State and Nonsteady State Bioaccumulation Models.

    PubMed

    McLeod, Anne M; Paterson, Gordon; Drouillard, Ken G; Haffner, G Douglas

    2016-10-18

    Accurate predictions on the bioaccumulation of persistent organic pollutants (POPs) are critical for hazard and ecosystem health assessments. Aquatic systems are influenced by multiple stressors including climate change and species invasions and it is important to be able to predict variability in POP concentrations in changing environments. Current steady state bioaccumulation models simplify POP bioaccumulation dynamics, assuming that pollutant uptake and elimination processes become balanced over an organism's lifespan. These models do not consider the complexity of dynamic variables such as temperature and growth rates which are known to have the potential to regulate bioaccumulation in aquatic organisms. We contrast a steady state (SS) bioaccumulation model with a dynamic nonsteady state (NSS) model and a no elimination (NE) model. We demonstrate that both the NSS and the NE models are superior at predicting both average concentrations as well as variation in POPs among individuals. This comparison demonstrates that temporal drivers, such as environmental fluctuations in temperature, growth dynamics, and modified food-web structure strongly determine contaminant concentrations and variability in a changing environment. These results support the recommendation of the future development of more dynamic, nonsteady state bioaccumulation models to predict hazard and risk assessments in the Anthropocene.

  8. Operationalizing resilience using state and transition models

    USDA-ARS?s Scientific Manuscript database

    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...

  9. The French Model of the Educator State.

    ERIC Educational Resources Information Center

    Lelievre, Claude

    2000-01-01

    The 19th-century emergence of a centralized, state-controlled school system helped stabilize government and legitimize a state model during a revolutionary period in French history. The centralized model assisted national integration goals by fabricating a symbolic public space. This ambitious political construction may be coming apart. (Contains…

  10. 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.

  11. 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.

  12. 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.

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

    PubMed

    Nichols, James D; Hines, A James E; Mackenzie, Darryl I; Seamans, Mark E; Gutiérrez, R J

    2007-06-01

    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 naïve estimates, indicating the importance of appropriately accounting for uncertainty in detection and state classification.

  14. 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.

  15. 2017 Regional, State, and Local Modelers' Workshop

    EPA Pesticide Factsheets

    The 2017 Regional, State, and Local (RSL) Modelers' Workshop is being held at the EPA's RTP, NC Campus on Monday, September 25th and Tuesday, September 26th, 2017.This page provides information on the agenda and registration for the RSL Modelers' Workshop.

  16. 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…

  17. 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…

  18. Simulations of the Domain State Model

    DTIC Science & Technology

    2003-01-01

    bulk of the antiferromagnet, the latter is diluted throughout its volume. Extensive Monte Carlo simulations of the model were performed in the past...that a corresponding theoretical model, the domain state model, investigated by Monte Carlo simulations shows a behavior very similar to the...discuss this in detail in the following. 15 RESULTS Monte Carlo methods are used with a heat-bath algorithm and single-spin flip dynamics [26] for the

  19. Schematic model for QCD. III. Hadronic states

    SciTech Connect

    Nunez, M.V.; Lerma, S.H.; Hess, P.O.; Jesgarz, S.; Civitarese, O.; Reboiro, M.

    2004-09-01

    The hadronic spectrum obtained in the framework of a QCD-inspired schematic model is presented. The model is the extension of a previous version, whose basic degrees of freedom are constituent quarks, antiquarks, and gluons. The interaction between quarks and gluons is a phenomenological interaction and its parameters are fixed from data. The classification of the states, in terms of quark and antiquark and gluon configurations is based on symmetry considerations, and it is independent of the chosen interaction. Following this procedure, nucleon and {delta} resonances are identified, as well as various penta- and hepta-quarks states. The lowest pentaquarks state is predicted at 1.5 GeV and it has negative parity, while the lowest hepta-quarks state has positive parity and its energy is of the order of 2.5 GeV.

  20. Metastable states in homogeneous Ising models

    SciTech Connect

    Achilles, M.; Bendisch, J.; von Trotha, H.

    1987-04-01

    Metastable states of homogeneous 2D and 3D Ising models are studied under free boundary conditions. The states are defined in terms of weak and strict local minima of the total interaction energy. The morphology of these minima is characterized locally and globally on square and cubic grids. Furthermore, in the 2D case, transition from any spin configuration that is not a strict minimum to a strict minimum is possible via non-energy-increasing single flips.

  1. Bound states in the Higgs model

    NASA Astrophysics Data System (ADS)

    di Leo, Leo; Darewych, Jurij W.

    1994-02-01

    We derive relativistic wave equations for the bound states of two Higgs bosons within the Higgs sector of the minimal standard model. The variational method and the Hamiltonian formalism of QFT are used to obtain the equations using a simple ||hh>+||hhh> Fock-space ansatz. We present approximate solutions of these equations for a range of Higgs boson masses, and explore the parameter space which corresponds to the existence of two-Higgs-boson bound states.

  2. Approximate Methods for State-Space Models.

    PubMed

    Koyama, Shinsuke; Pérez-Bolde, Lucia Castellanos; Shalizi, Cosma Rohilla; Kass, Robert E

    2010-03-01

    State-space models provide an important body of techniques for analyzing time-series, but their use requires estimating unobserved states. The optimal estimate of the state is its conditional expectation given the observation histories, and computing this expectation is hard when there are nonlinearities. Existing filtering methods, including sequential Monte Carlo, tend to be either inaccurate or slow. In this paper, we study a nonlinear filter for nonlinear/non-Gaussian state-space models, which uses Laplace's method, an asymptotic series expansion, to approximate the state's conditional mean and variance, together with a Gaussian conditional distribution. This Laplace-Gaussian filter (LGF) gives fast, recursive, deterministic state estimates, with an error which is set by the stochastic characteristics of the model and is, we show, stable over time. We illustrate the estimation ability of the LGF by applying it to the problem of neural decoding and compare it to sequential Monte Carlo both in simulations and with real data. We find that the LGF can deliver superior results in a small fraction of the computing time.

  3. 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.

  4. Building Markov state models with solvent dynamics.

    PubMed

    Gu, Chen; Chang, Huang-Wei; Maibaum, Lutz; Pande, Vijay S; Carlsson, Gunnar E; Guibas, Leonidas J

    2013-01-01

    Markov state models have been widely used to study conformational changes of biological macromolecules. These models are built from short timescale simulations and then propagated to extract long timescale dynamics. However, the solvent information in molecular simulations are often ignored in current methods, because of the large number of solvent molecules in a system and the indistinguishability of solvent molecules upon their exchange. We present a solvent signature that compactly summarizes the solvent distribution in the high-dimensional data, and then define a distance metric between different configurations using this signature. We next incorporate the solvent information into the construction of Markov state models and present a fast geometric clustering algorithm which combines both the solute-based and solvent-based distances. We have tested our method on several different molecular dynamical systems, including alanine dipeptide, carbon nanotube, and benzene rings. With the new solvent-based signatures, we are able to identify different solvent distributions near the solute. Furthermore, when the solute has a concave shape, we can also capture the water number inside the solute structure. Finally we have compared the performances of different Markov state models. The experiment results show that our approach improves the existing methods both in the computational running time and the metastability. In this paper we have initiated an study to build Markov state models for molecular dynamical systems with solvent degrees of freedom. The methods we described should also be broadly applicable to a wide range of biomolecular simulation analyses.

  5. Building Markov state models with solvent dynamics

    PubMed Central

    2013-01-01

    Background Markov state models have been widely used to study conformational changes of biological macromolecules. These models are built from short timescale simulations and then propagated to extract long timescale dynamics. However, the solvent information in molecular simulations are often ignored in current methods, because of the large number of solvent molecules in a system and the indistinguishability of solvent molecules upon their exchange. Methods We present a solvent signature that compactly summarizes the solvent distribution in the high-dimensional data, and then define a distance metric between different configurations using this signature. We next incorporate the solvent information into the construction of Markov state models and present a fast geometric clustering algorithm which combines both the solute-based and solvent-based distances. Results We have tested our method on several different molecular dynamical systems, including alanine dipeptide, carbon nanotube, and benzene rings. With the new solvent-based signatures, we are able to identify different solvent distributions near the solute. Furthermore, when the solute has a concave shape, we can also capture the water number inside the solute structure. Finally we have compared the performances of different Markov state models. The experiment results show that our approach improves the existing methods both in the computational running time and the metastability. Conclusions In this paper we have initiated an study to build Markov state models for molecular dynamical systems with solvent degrees of freedom. The methods we described should also be broadly applicable to a wide range of biomolecular simulation analyses. PMID:23368418

  6. Multi-state modeling of biomolecules.

    PubMed

    Stefan, Melanie I; Bartol, Thomas M; Sejnowski, Terrence J; Kennedy, Mary B

    2014-09-01

    Multi-state modeling of biomolecules refers to a series of techniques used to represent and compute the behavior of biological molecules or complexes that can adopt a large number of possible functional states. Biological signaling systems often rely on complexes of biological macromolecules that can undergo several functionally significant modifications that are mutually compatible. Thus, they can exist in a very large number of functionally different states. Modeling such multi-state systems poses two problems: the problem of how to describe and specify a multi-state system (the "specification problem") and the problem of how to use a computer to simulate the progress of the system over time (the "computation problem"). To address the specification problem, modelers have in recent years moved away from explicit specification of all possible states and towards rule-based formalisms that allow for implicit model specification, including the κ-calculus, BioNetGen, the Allosteric Network Compiler, and others. To tackle the computation problem, they have turned to particle-based methods that have in many cases proved more computationally efficient than population-based methods based on ordinary differential equations, partial differential equations, or the Gillespie stochastic simulation algorithm. Given current computing technology, particle-based methods are sometimes the only possible option. Particle-based simulators fall into two further categories: nonspatial simulators, such as StochSim, DYNSTOC, RuleMonkey, and the Network-Free Stochastic Simulator (NFSim), and spatial simulators, including Meredys, SRSim, and MCell. Modelers can thus choose from a variety of tools, the best choice depending on the particular problem. Development of faster and more powerful methods is ongoing, promising the ability to simulate ever more complex signaling processes in the future.

  7. Multi-state Modeling of Biomolecules

    PubMed Central

    Stefan, Melanie I.; Bartol, Thomas M.; Sejnowski, Terrence J.; Kennedy, Mary B.

    2014-01-01

    Multi-state modeling of biomolecules refers to a series of techniques used to represent and compute the behavior of biological molecules or complexes that can adopt a large number of possible functional states. Biological signaling systems often rely on complexes of biological macromolecules that can undergo several functionally significant modifications that are mutually compatible. Thus, they can exist in a very large number of functionally different states. Modeling such multi-state systems poses two problems: the problem of how to describe and specify a multi-state system (the “specification problem”) and the problem of how to use a computer to simulate the progress of the system over time (the “computation problem”). To address the specification problem, modelers have in recent years moved away from explicit specification of all possible states and towards rule-based formalisms that allow for implicit model specification, including the κ-calculus [1], BioNetGen [2]–[5], the Allosteric Network Compiler [6], and others [7], [8]. To tackle the computation problem, they have turned to particle-based methods that have in many cases proved more computationally efficient than population-based methods based on ordinary differential equations, partial differential equations, or the Gillespie stochastic simulation algorithm [9], [10]. Given current computing technology, particle-based methods are sometimes the only possible option. Particle-based simulators fall into two further categories: nonspatial simulators, such as StochSim [11], DYNSTOC [12], RuleMonkey [9], [13], and the Network-Free Stochastic Simulator (NFSim) [14], and spatial simulators, including Meredys [15], SRSim [16], [17], and MCell [18]–[20]. Modelers can thus choose from a variety of tools, the best choice depending on the particular problem. Development of faster and more powerful methods is ongoing, promising the ability to simulate ever more complex signaling processes in the future

  8. Steady-state models of photosynthesis.

    PubMed

    von Caemmerer, Susanne

    2013-09-01

    In the challenge to increase photosynthetic rate per leaf area mathematical models of photosynthesis can be used to help interpret gas exchange measurements made under different environmental conditions and predict underlying photosynthetic biochemistry. To do this successfully it is important to improve the modelling of temperature dependencies of CO₂ assimilation and gain better understanding of internal CO₂ diffusion limitations. Despite these shortcomings steady-state models of photosynthesis provide simple easy to use tools for thought experiments to explore photosynthetic pathway changes such as redirecting photorespiratory CO₂, inserting bicarbonate pumps into C₃ chloroplasts or inserting C₄ photosynthesis into rice. Here a number of models derived from the C₃ model by Farquhar, von Caemmerer and Berry are discussed and compared.

  9. Bound states in the Higgs model

    SciTech Connect

    Di Leo, L.; Darewych, J.W. )

    1994-02-01

    We derive relativistic wave equations for the bound states of two Higgs bosons within the Higgs sector of the minimal standard model. The variational method and the Hamiltonian formalism of QFT are used to obtain the equations using a simple [vert bar][ital hh][r angle]+[vert bar][ital hhh][r angle] Fock-space ansatz. We present approximate solutions of these equations for a range of Higgs boson masses, and explore the parameter space which corresponds to the existence of two-Higgs-boson bound states.

  10. 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.

  11. 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.

  12. A critical appraisal of Markov state models

    NASA Astrophysics Data System (ADS)

    Schütte, Ch.; Sarich, M.

    2015-09-01

    Markov State Modelling as a concept for a coarse grained description of the essential kinetics of a molecular system in equilibrium has gained a lot of attention recently. The last 10 years have seen an ever increasing publication activity on how to construct Markov State Models (MSMs) for very different molecular systems ranging from peptides to proteins, from RNA to DNA, and via molecular sensors to molecular aggregation. Simultaneously the accompanying theory behind MSM building and approximation quality has been developed well beyond the concepts and ideas used in practical applications. This article reviews the main theoretical results, provides links to crucial new developments, outlines the full power of MSM building today, and discusses the essential limitations still to overcome.

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

    PubMed

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

    2014-01-01

    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.

  14. Parameter and state estimator for state space models.

    PubMed

    Ding, Ruifeng; Zhuang, Linfan

    2014-01-01

    This paper proposes a parameter and state estimator for canonical state space systems from measured input-output data. The key is to solve the system state from the state equation and to substitute it into the output equation, eliminating the state variables, and the resulting equation contains only the system inputs and outputs, and to derive a least squares parameter identification algorithm. Furthermore, the system states are computed from the estimated parameters and the input-output data. Convergence analysis using the martingale convergence theorem indicates that the parameter estimates converge to their true values. Finally, an illustrative example is provided to show that the proposed algorithm is effective.

  15. 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

  16. Sequential state generation by model neural networks.

    PubMed Central

    Kleinfeld, D

    1986-01-01

    Sequential patterns of neural output activity form the basis of many biological processes, such as the cyclic pattern of outputs that control locomotion. I show how such sequences can be generated by a class of model neural networks that make defined sets of transitions between selected memory states. Sequence-generating networks depend upon the interplay between two sets of synaptic connections. One set acts to stabilize the network in its current memory state, while the second set, whose action is delayed in time, causes the network to make specified transitions between the memories. The dynamic properties of these networks are described in terms of motion along an energy surface. The performance of the networks, both with intact connections and with noisy or missing connections, is illustrated by numerical examples. In addition, I present a scheme for the recognition of externally generated sequences by these networks. PMID:3467316

  17. Markov state models based on milestoning

    NASA Astrophysics Data System (ADS)

    Schütte, Christof; Noé, Frank; Lu, Jianfeng; Sarich, Marco; Vanden-Eijnden, Eric

    2011-05-01

    Markov state models (MSMs) have become the tool of choice to analyze large amounts of molecular dynamics data by approximating them as a Markov jump process between suitably predefined states. Here we investigate "Core Set MSMs," a new type of MSMs that build on metastable core sets acting as milestones for tracing the rare event kinetics. We present a thorough analysis of Core Set MSMs based on the existing milestoning framework, Bayesian estimation methods and Transition Path Theory (TPT). We show that Core Set MSMs can be used to extract phenomenological rate constants between the metastable sets of the system and to approximate the evolution of certain key observables. The performance of Core Set MSMs in comparison to standard MSMs is analyzed and illustrated on a toy example and in the context of the torsion angle dynamics of alanine dipeptide.

  18. Model bridging chimera state and explosive synchronization.

    PubMed

    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.

  19. 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.

  20. 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.

  1. Granger causality for state-space models.

    PubMed

    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.

  2. 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.

  3. 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.

  4. A 2-categorical state sum model

    NASA Astrophysics Data System (ADS)

    Baratin, Aristide; Freidel, Laurent

    2015-01-01

    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. Markov state modeling of sliding friction.

    PubMed

    Pellegrini, F; Landes, François P; Laio, A; Prestipino, S; Tosatti, E

    2016-11-01

    Markov state modeling (MSM) has recently emerged as one of the key techniques for the discovery of collective variables and the analysis of rare events in molecular simulations. In particular in biochemistry this approach is successfully exploited to find the metastable states of complex systems and their evolution in thermal equilibrium, including rare events, such as a protein undergoing folding. The physics of sliding friction and its atomistic simulations under external forces constitute a nonequilibrium field where relevant variables are in principle unknown and where a proper theory describing violent and rare events such as stick slip is still lacking. Here we show that MSM can be extended to the study of nonequilibrium phenomena and in particular friction. The approach is benchmarked on the Frenkel-Kontorova model, used here as a test system whose properties are well established. We demonstrate that the method allows the least prejudiced identification of a minimal basis of natural microscopic variables necessary for the description of the forced dynamics of sliding, through their probabilistic evolution. The steps necessary for the application to realistic frictional systems are highlighted.

  6. Markov state modeling of sliding friction

    NASA Astrophysics Data System (ADS)

    Pellegrini, F.; Landes, François P.; Laio, A.; Prestipino, S.; Tosatti, E.

    2016-11-01

    Markov state modeling (MSM) has recently emerged as one of the key techniques for the discovery of collective variables and the analysis of rare events in molecular simulations. In particular in biochemistry this approach is successfully exploited to find the metastable states of complex systems and their evolution in thermal equilibrium, including rare events, such as a protein undergoing folding. The physics of sliding friction and its atomistic simulations under external forces constitute a nonequilibrium field where relevant variables are in principle unknown and where a proper theory describing violent and rare events such as stick slip is still lacking. Here we show that MSM can be extended to the study of nonequilibrium phenomena and in particular friction. The approach is benchmarked on the Frenkel-Kontorova model, used here as a test system whose properties are well established. We demonstrate that the method allows the least prejudiced identification of a minimal basis of natural microscopic variables necessary for the description of the forced dynamics of sliding, through their probabilistic evolution. The steps necessary for the application to realistic frictional systems are highlighted.

  7. 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.

  8. 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.

  9. 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.

  10. 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

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

    PubMed

    Roeva, Olympia; Pencheva, Tania

    2014-09-03

    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.

  12. 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. Copyright © 2013 John Wiley & Sons, Ltd.

  13. 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. Copyright © 2015 John Wiley & Sons, Ltd.

  14. Model developer`s appendix to the model documentation report: NEMS macroeconomic activity module

    SciTech Connect

    1994-07-15

    The NEMS Macroeconomic Activity Module (MAM) tested here was used to generate the Annual Energy Outlook 1994 (AEO94). MAM is a response surface model, not a structural model, composed of three submodules: the National Submodule, the Interindustry Submodule, and the Regional Submodule. Contents of this report are as follows: properties of the mathematical solution; NEMS MAM empirical basis; and scenario analysis. Scenario analysis covers: expectations for scenario analysis; historical world oil price scenario; AEO94 high world oil price scenario; AEO94 low world oil price scenario; and immediate increase world oil price scenario.

  15. 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…

  16. 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

  17. Valuation of financial models with non-linear state spaces

    NASA Astrophysics Data System (ADS)

    Webber, Nick

    2001-02-01

    A common assumption in valuation models for derivative securities is that the underlying state variables take values in a linear state space. We discuss numerical implementation issues in an interest rate model with a simple non-linear state space, formulating and comparing Monte Carlo, finite difference and lattice numerical solution methods. We conclude that, at least in low dimensional spaces, non-linear interest rate models may be viable.

  18. Finite State Machines and Modal Models in Ptolemy II

    DTIC Science & Technology

    2009-11-01

    Finite State Machines and Modal Models in Ptolemy II Edward A. Lee Electrical Engineering and Computer Sciences University of California at Berkeley...DATES COVERED 00-00-2009 to 00-00-2009 4. TITLE AND SUBTITLE Finite State Machines and Modal Models in Ptolemy II 5a. CONTRACT NUMBER 5b...describes the usage and semantics of finite-state machines (FSMs) and modal models in Ptolemy II. FSMs are actors whose behavior is described using a

  19. Viral kinetic modeling: state of the art

    DOE PAGES

    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

  20. 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.

  1. Viral kinetic modeling: state of the art.

    PubMed

    Canini, Laetitia; Perelson, Alan S

    2014-10-01

    Viral kinetic (VK) 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 VK 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, VK modeling has provided new insights into the understanding of the disease progression and the modes of action of several drugs. We expect that VK 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.

  2. Unified State Model theory and application in Astrodynamics

    NASA Astrophysics Data System (ADS)

    Vittaldev, V.; Mooij, E.; Naeije, M. C.

    2012-03-01

    The Unified State Model is a method for expressing orbits using a set of seven elements. The elements consist of a quaternion and three parameters based on the velocity hodograph. A complete derivation of the original model is given in addition to two proposed modifications. Both modifications reduce the number of state elements from seven to six by replacing the quaternion with either modified Rodrigues parameters or the Exponential Map. Numerical simulations comparing the original Unified State Model, the Unified State Model with modified Rodrigues parameters, and the Unified State Model with Exponential Map, with the traditional Cartesian coordinates have been carried out. The Unified State Model and its derivatives outperform the Cartesian coordinates for all orbit cases in terms of accuracy and computational speed, except for highly eccentric perturbed orbits. The performance of the Unified State Model is exceptionally better for the case of orbits with continuous low-thrust propulsion with CPU simulation time being an order of magnitude lower than for the simulation using Cartesian coordinates. This makes the Unified State Model an excellent state propagator for mission optimizations.

  3. Hyperon polarizabilities in the bound-state soliton model

    NASA Astrophysics Data System (ADS)

    Gobbi, Carlo; Schat, Carlos L.; Scoccola, Norberto N.

    1996-02-01

    A detailed calculation of electric and magnetic static polarizabilities of octet hyperons is presented in the framework of the bound-state soliton model. Both seagull and dispersive contributions are considered, and the results are compared with different model predictions.

  4. Multi-state modeling in ASSESS

    SciTech Connect

    Fortney, D.S.; Patenaude, C.J. ); Snell, M.K. ); Key, B. )

    1992-07-06

    The Analytic System and Software for Evaluating Safeguards and Security (ASSESS) is an integrated safeguards evaluation tool focusing on theft and diversion of special nuclear material (SNM) by insiders, outsiders, and collusion between insiders and outsiders. ASSESS features a common Facility Description module that allows for defining a facility's safeguards and security system simultaneously for both insiderand outsider threats. This Facility Description module supports defining safeguards during two states. The two states could represent day'' and night,'' or normal'' and emergency,'' or simply open'' and closed.'' A problem arises due to differences in the modi operandi of (and hence, evaluation approaches for) insider and outsider threats. This can lead to situations where it is impossible to simultaneously define states correctly to meet the needs of both the Insider and Outsider evaluation modules. We have developed and are currently implementing an approach to address this problem. This approach has requiredprogramming in four ASSESS modules. In this paper, we discuss the ASSESS state problem and give an overview of the solution, including the implementation in the Facility and Insider modules. A second paper discussing details of the implementation in the Outsider module is also being presented in this session.

  5. Testing the Testing: Validity of a State Growth Model

    ERIC Educational Resources Information Center

    Brown, Kim Trask

    2008-01-01

    Possible threats to the validity of North Carolina's accountability model used to predict academic growth were investigated in two ways: the state's regression equations were replicated but updated to utilize current testing data and not that from years past as in the state's current model; and the updated equations were expanded to include…

  6. 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...

  7. 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...

  8. Quantal density-functional theory of excited states: The state arbitrariness of the model noninteracting system

    SciTech Connect

    Slamet, Marlina; Singh, Ranbir; Sahni, Viraht; Massa, Lou

    2003-10-01

    The quantal density-functional theory (Q-DFT) of nondegenerate excited-states maps the pure state of the Schroedinger equation to one of noninteracting fermions such that the equivalent excited state density, energy, and ionization potential are obtained. The state of the model S system is arbitrary in that it may be in a ground or excited state. The potential energy of the model fermions differs as a function of this state. The contribution of correlations due to the Pauli exclusion principle and Coulomb repulsion to the potential and total energy of these fermions is independent of the state of the S system. The differences are solely a consequence of correlation-kinetic effects. Irrespective of the state of the S system, the highest occupied eigenvalue of the model fermions is the negative of the ionization potential. In this paper we demonstrate the state arbitrariness of the model system by application of Q-DFT to the first excited singlet state of the exactly solvable Hookean atom. We construct two model S systems: one in a singlet ground state (1s{sup 2}), and the other in a singlet first excited state (1s2s). In each case, the density and energy determined are equivalent to those of the excited state of the atom, with the highest occupied eigenvalues being the negative of the ionization potential. From these results we determine the corresponding Kohn-Sham density-functional theory (KS-DFT) 'exchange-correlation' potential energy for the two S systems. Further, based on the results of the model calculations, suggestions for the KS-DFT of excited states are made.

  9. 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.

  10. Residual discrete symmetry of the five-state clock model

    NASA Astrophysics Data System (ADS)

    Baek, Seung Ki; Mäkelä, Harri; Minnhagen, Petter; Kim, Beom Jun

    2013-07-01

    It is well known that the q-state clock model can exhibit a Kosterlitz-Thouless (KT) transition if q is equal to or greater than a certain threshold, which has been believed to be five. However, recent numerical studies indicate that helicity modulus does not vanish in the high-temperature phase of the five-state clock model as predicted by the KT scenario. By performing Monte Carlo calculations under the fluctuating twist boundary condition, we show that it is because the five-state clock model does not have the fully continuous U(1) symmetry even in the high-temperature phase while the six-state clock model does. We suggest that the upper transition of the five-state clock model is actually a weaker cousin of the KT transition so that it is q≥6 that exhibits the genuine KT behavior.

  11. The power to act: two model state statutes.

    PubMed

    Erickson, Deborah L; Gostin, Lawrence O; Street, Jerry; Mills, S Peter

    2002-01-01

    Enabling statutes for state and local public health agencies set forth their powers and duties and provide the legal basis for their work. Obsolescence, inconsistency, and inadequacy may render some public health laws ineffective or even counterproductive. Reforming state public health law can improve the legal infrastructure that supports public health systems in responding to bioterrorism and other public health threats. Two legal tools available to assist the process of establishing a strong legal foundation for public health practice are the Model State Emergency Health Powers Act, developed in 2001 by the Center for Law and the Public's Health, and the Model State Public Health Act, currently under development by the Turning Point Public Health Statute Modernization National Collaborative. These model acts can serve as guides for assessing current state public health law, and they provide example statutory language for use by those working to update their laws. That strong state public health law and model public health acts serve as resources for law reform is recognized by local health officials and state legislators as well as by state public health officials. Lessons learned from recent experiences with crafting and introducing legislation based on the Model State Emergency Health Powers Act can prove useful in the future to those working on public health law reform efforts in their states.

  12. From Taylor state to model-Z

    NASA Astrophysics Data System (ADS)

    Braginsky, Stanislav I.; Roberts, Paul H.

    This is a sequel to an earlier paper [Roberts, Geophys. Astrophys. Fluid Dynam. v. 49, p. 143 (1989)] in which one of us claimed, on the basis of two sequences of integrations of a particular intermediate model of the geodynamo, that, as the dynamo number increases, a smooth transition occurs from Taylor-like behavior to model-Z-type behavior. A more complete survey of parameter space for this model is presented here which tends to corroborate this conclusion. Also, the relationship provided by this model between the external dipole moment of the field and the heat flux from the core is examined. The asymptotic dependence of solutions in the large dynamo number limit is considered.

  13. 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.

  14. Modeling new XYZ states at JPAC

    SciTech Connect

    Pilloni, Alessandro

    2016-12-01

    The observation of the unexpected XYZP resonances has challenged the usual heavy quarkonium framework. One of the most studied exotic states, the X(3872), happens to be copiously produced in high-energy hadron collisions. We discuss how this large prompt production cross-section, together with the comparison with light nuclei production data, disfavors a loosely-bound molecule interpretation, and calls for a new interpretation for the exotic hadron resonances. We also present the research of the Joint Physics Analysis Center in Hadron Spectroscopy.

  15. 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.

  16. 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.

  17. Shell model states in the continuum

    NASA Astrophysics Data System (ADS)

    Shirokov, A. M.; Mazur, A. I.; Mazur, I. A.; Vary, J. P.

    2016-12-01

    We suggest a method for calculating scattering phase shifts and energies and widths of resonances which utilizes only eigenenergies obtained in variational calculations with oscillator basis and their dependence on oscillator basis spacing ℏ Ω . We make use of simple expressions for the S matrix at eigenstates of a finite (truncated) Hamiltonian matrix in the oscillator basis obtained in the HORSE (J -matrix) formalism of quantum scattering theory. The validity of the suggested approach is verified in calculations with model Woods-Saxon potentials and applied to calculations of n α resonances and nonresonant scattering using the no-core shell model.

  18. Ground state configurations in two-mode quantum Rabi models

    NASA Astrophysics Data System (ADS)

    Chilingaryan, Suren; Rodríguez-Lara, B. M.

    We study two models describing a single two-level system coupled to two boson field modes in either a parallel or orthogonal configuration. Both models may be feasible for experimental realization through Raman adiabatic driving in cavity QED. We study their ground state configurations; that is, we find the quantum precursors of the corresponding semi-classical phase transitions. We found that the ground state configurations of both models present the same critical coupling as the quantum Rabi model. Around this critical coupling, the ground state goes from the so-called normal configuration with no excitation, the qubit in the ground state and the fields in the quantum vacuum state, to a ground state with excitations, the qubit in a superposition of ground and excited state, while the fields are not in the vacuum anymore, for the first model. The second model shows a more complex ground state configuration landscape where we find the normal configuration mentioned above, two single-mode configurations, where just one of the fields and the qubit are excited, and a dual-mode configuration, where both fields and the qubit are excited. S A Chilingaryan acknowledges financial support from CONACYT.

  19. Wave Modelling - The State of the Art

    DTIC Science & Technology

    2007-09-27

    Heverlee, Belgium q Universitt) di Torino, Dipartimento di Fisica Generale, Via P. Giuria 1, 10125 Torino, Italy A. M. Obukhov Institute for Physics of... molecular processes. Van Duin and Janssen (1992) pointed out that this approach fails for low-frequency waves. Mixing length modelling assumes that

  20. Nonequilibrium steady states in a model for prebiotic evolution

    NASA Astrophysics Data System (ADS)

    Wynveen, A.; Fedorov, I.; Halley, J. W.

    2014-02-01

    Some statistical features of steady states of a Kauffman-like model for prebiotic evolution are reported from computational studies. We postulate that the interesting "lifelike" states will be characterized by a nonequilibrium distribution of species and a time variable species self-correlation function. Selecting only such states from the population of final states produced by the model yields the probability of the appearance of such states as a function of a parameter p of the model. p is defined as the probability that a possible reaction in the the artificial chemistry actually appears in the network of chemical reactions. Small p corresponds to sparse networks utilizing a small fraction of the available reactions. We find that the probability of the appearance of such lifelike states exhibits a maximum as a function of p: at large p, most final states are in chemical equilibrium and hence are excluded by our criterion. At very small p, the sparseness of the network makes the probability of formation of any nontrivial dynamic final state low, yielding a low probability of production of lifelike states in this limit as well. We also report results on the diversity of the lifelike states (as defined here) that are produced. Repeated starts of the model evolution with different random number seeds in a given reaction network lead to final lifelike states which have a greater than random likelihood of resembling one another. Thus a form of "convergence" is observed. On the other hand, in different reaction networks with the same p, lifelike final states are statistically uncorrelated. In summary, the main results are (1) there is an optimal p or "sparseness" for production of lifelike states in our model—neither very dense nor very sparse networks are optimal—and (2) for a given p or sparseness, the resulting lifelike states can be extremely different. We discuss some possible implications for studies of the origin of life.

  1. Monitoring alert and drowsy states by modeling EEG source nonstationarity

    NASA Astrophysics Data System (ADS)

    Hsu, Sheng-Hsiou; Jung, Tzyy-Ping

    2017-10-01

    Objective. As a human brain performs various cognitive functions within ever-changing environments, states of the brain characterized by recorded brain activities such as electroencephalogram (EEG) are inevitably nonstationary. The challenges of analyzing the nonstationary EEG signals include finding neurocognitive sources that underlie different brain states and using EEG data to quantitatively assess the state changes. Approach. This study hypothesizes that brain activities under different states, e.g. levels of alertness, can be modeled as distinct compositions of statistically independent sources using independent component analysis (ICA). This study presents a framework to quantitatively assess the EEG source nonstationarity and estimate levels of alertness. The framework was tested against EEG data collected from 10 subjects performing a sustained-attention task in a driving simulator. Main results. Empirical results illustrate that EEG signals under alert versus drowsy states, indexed by reaction speeds to driving challenges, can be characterized by distinct ICA models. By quantifying the goodness-of-fit of each ICA model to the EEG data using the model deviation index (MDI), we found that MDIs were significantly correlated with the reaction speeds (r  =  ‑0.390 with alertness models and r  =  0.449 with drowsiness models) and the opposite correlations indicated that the two models accounted for sources in the alert and drowsy states, respectively. Based on the observed source nonstationarity, this study also proposes an online framework using a subject-specific ICA model trained with an initial (alert) state to track the level of alertness. For classification of alert against drowsy states, the proposed online framework achieved an averaged area-under-curve of 0.745 and compared favorably with a classic power-based approach. Significance. This ICA-based framework provides a new way to study changes of brain states and can be applied to

  2. Monitoring alert and drowsy states by modeling EEG source nonstationarity.

    PubMed

    Hsu, Sheng-Hsiou; Jung, Tzyy-Ping

    2017-10-01

    As a human brain performs various cognitive functions within ever-changing environments, states of the brain characterized by recorded brain activities such as electroencephalogram (EEG) are inevitably nonstationary. The challenges of analyzing the nonstationary EEG signals include finding neurocognitive sources that underlie different brain states and using EEG data to quantitatively assess the state changes. This study hypothesizes that brain activities under different states, e.g. levels of alertness, can be modeled as distinct compositions of statistically independent sources using independent component analysis (ICA). This study presents a framework to quantitatively assess the EEG source nonstationarity and estimate levels of alertness. The framework was tested against EEG data collected from 10 subjects performing a sustained-attention task in a driving simulator. Empirical results illustrate that EEG signals under alert versus drowsy states, indexed by reaction speeds to driving challenges, can be characterized by distinct ICA models. By quantifying the goodness-of-fit of each ICA model to the EEG data using the model deviation index (MDI), we found that MDIs were significantly correlated with the reaction speeds (r  =  -0.390 with alertness models and r  =  0.449 with drowsiness models) and the opposite correlations indicated that the two models accounted for sources in the alert and drowsy states, respectively. Based on the observed source nonstationarity, this study also proposes an online framework using a subject-specific ICA model trained with an initial (alert) state to track the level of alertness. For classification of alert against drowsy states, the proposed online framework achieved an averaged area-under-curve of 0.745 and compared favorably with a classic power-based approach. This ICA-based framework provides a new way to study changes of brain states and can be applied to monitoring cognitive or mental states of human

  3. State reduction for semi-Markov reliability models

    NASA Technical Reports Server (NTRS)

    White, Allan L.; Palumbo, Daniel L.

    1990-01-01

    Trimming, a method of reducing the number of states in a semi-Markov reliability model, is described, and an error bound is derived. The error bound uses only three parameters from the semi-Markov model: (1) the maximum sum of rates for failure transitions leaving any state, (2) the maximum average holding time for a recovery-mode state, (3) and the operating time for the system. The error bound can be computed before any model generation takes places, which means the modeler can decide immediately whether the model can be trimmed. The trimming has a precise and simple description and thus can be easily included in a program that generates reliability models. The simplest version of the error bound for trimming is presented. More accurate versions can be obtained by requesting more information about the system being modeled.

  4. Identifiability of steady-state chemical kinetic models

    SciTech Connect

    Shvetsova-Shilovskaya, T.N.; Gorskii, V.G.

    1995-01-01

    The methodology for the local and global identifiability analysis of steady-state kinetic models of catalytic reactions is discussed. This methodology is based on the prior transformation of the model into the linear form so that the coefficients of the linear form are uniquely identifiable combinations of constants (observed parameters). Identifiability analysis is applied to several particular models.

  5. Elements of a Model State Education Agency Diffusion System.

    ERIC Educational Resources Information Center

    Mojkowski, Charles

    A study, presented to the National Dissemination Conference, provides a conceptualization of a model diffusion system as it might exist within a state education agency (SEA) and places this diffusion model within the context of the SEA's expanding role as an educational service. Five conclusions were reached regarding a model diffusion system.…

  6. Modeling Solid State Detonation and Reactive Materials

    DTIC Science & Technology

    2010-07-01

    observed in "ideal" explosives. How- ever the lead wave head is not a classical shock in the sense of ZND theory, but rather a subsonic compaction wave...case for the classical ZND model of detonation. For this discussion, we regard the SSD as a det- onation in reactive materials that nominally runs at...2.33 km/sec. If one assumes simply that the wave head is supersonic relative to the am- bient, fresh material as is the case for a classical ZND

  7. Relationship between mental states in depression: the assimilation model perspective.

    PubMed

    Osatuke, Katerine; Stiles, William B; Barkham, Michael; Hardy, Gillian E; Shapiro, David A

    2011-11-30

    Metacognitive theories describe relationships between mental-affective self-states, including the capacity of one self-state to reflect upon another self-state. The assimilation model is a metacognitive approach that understands self-states as made of traces of experiences at different levels of integration. Psychological problems are understood as impaired accessibility of certain self-states to the person's normal awareness. These states are distressing or otherwise subjectively problematic when they emerge. This exploratory study used the assimilation framework to describe mental states in 17 clients who participated in a clinical trial of cognitive-behavioral therapy for depression. Three clinically sophisticated raters examined transcripts of 1h-long psychotherapy session per client to construct qualitative descriptions of self-states and their relationship patterns in these depressed individuals. We then systematically compared and integrated these raters' descriptions of the clients' self-states. In each case, we found a conflict between two internally incompatible states: an interpersonally submissive state and an interpersonally dominant one, a pattern consistent with the model's theoretical description of depression.

  8. The electronic excited states of green fluorescent protein chromophore models

    NASA Astrophysics Data System (ADS)

    Olsen, Seth Carlton

    We explore the properties of quantum chemical approximations to the excited states of model chromophores of the green fluorescent protein of A. victoria. We calculate several low-lying states by several methods of quantum chemical calculation, including state-averaged complete active space SCF (CASSCF) methods, time dependent density functional theory (TDDFT), equation-of motion coupled cluster (EOM-CCSD) and multireference perturbation theory (MRPT). Amongst the low-lying states we identify the optically bright pipi* state of the molecules and examine its properties. We demonstrate that the state is dominated by a single configuration function. We calculate zero-time approximations to the resonance Raman spectrum of GFP chromophore models, and assign published spectra based upon these.

  9. Structured fusion lasso penalized multi-state models.

    PubMed

    Sennhenn-Reulen, Holger; Kneib, Thomas

    2016-11-10

    Multi-state models generalize survival or duration time analysis to the estimation of transition-specific hazard rate functions for multiple transitions. When each of the transition-specific risk functions is parametrized with several distinct covariate effect coefficients, this leads to a model of potentially high dimension. To decrease the parameter space dimensionality and to work out a clear image of the underlying multi-state model structure, one can either aim at setting some coefficients to zero or to make coefficients for the same covariate but two different transitions equal. The first issue can be approached by penalizing the absolute values of the covariate coefficients as in lasso regularization. If, instead, absolute differences between coefficients of the same covariate on different transitions are penalized, this leads to sparse competing risk relations within a multi-state model, that is, equality of covariate effect coefficients. In this paper, a new estimation approach providing sparse multi-state modelling by the aforementioned principles is established, based on the estimation of multi-state models and a simultaneous penalization of the L1 -norm of covariate coefficients and their differences in a structured way. The new multi-state modelling approach is illustrated on peritoneal dialysis study data and implemented in the R package penMSM. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

  10. 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.

  11. State and parameter estimation for canonic models of neural oscillators.

    PubMed

    Tyukin, Ivan; Steur, Erik; Nijmeijer, Henk; Fairhurst, David; Song, Inseon; Semyanov, Alexey; Van Leeuwen, Cees

    2010-06-01

    We consider the problem of how to recover the state and parameter values of typical model neurons, such as Hindmarsh-Rose, FitzHugh-Nagumo, Morris-Lecar, from in-vitro measurements of membrane potentials. In control theory, in terms of observer design, model neurons qualify as locally observable. However, unlike most models traditionally addressed in control theory, no parameter-independent diffeomorphism exists, such that the original model equations can be transformed into adaptive canonic observer form. For a large class of model neurons, however, state and parameter reconstruction is possible nevertheless. We propose a method which, subject to mild conditions on the richness of the measured signal, allows model parameters and state variables to be reconstructed up to an equivalence class.

  12. Solvable model for chimera states of coupled oscillators.

    PubMed

    Abrams, Daniel M; Mirollo, Rennie; Strogatz, Steven H; Wiley, Daniel A

    2008-08-22

    Networks of identical, symmetrically coupled oscillators can spontaneously split into synchronized and desynchronized subpopulations. Such chimera states were discovered in 2002, but are not well understood theoretically. Here we obtain the first exact results about the stability, dynamics, and bifurcations of chimera states by analyzing a minimal model consisting of two interacting populations of oscillators. Along with a completely synchronous state, the system displays stable chimeras, breathing chimeras, and saddle-node, Hopf, and homoclinic bifurcations of chimeras.

  13. q-state Potts model on the Apollonian network.

    PubMed

    Araújo, Nuno A M; Andrade, Roberto F S; Herrmann, Hans J

    2010-10-01

    The q-state Potts model is studied on the Apollonian network with Monte Carlo simulations and the transfer matrix method. The spontaneous magnetization, correlation length, entropy, and specific heat are analyzed as a function of temperature for different number of states, q. Different scaling functions in temperature and q are proposed. A quantitative agreement is found between results from both methods. No critical behavior is observed in the thermodynamic limit for any number of states.

  14. Ground state energy fluctuations in the nuclear shell model

    NASA Astrophysics Data System (ADS)

    Velázquez, Víctor; Hirsch, Jorge G.; Frank, Alejandro; Barea, José; Zuker, Andrés P.

    2005-05-01

    Statistical fluctuations of the nuclear ground state energies are estimated using shell model calculations in which particles in the valence shells interact through well-defined forces, and are coupled to an upper shell governed by random 2-body interactions. Induced ground-state energy fluctuations are found to be one order of magnitude smaller than those previously associated with chaotic components, in close agreement with independent perturbative estimates based on the spreading widths of excited states.

  15. The New York State Bird Conservation Area (BCA) Program: A Model for the United States

    Treesearch

    M. F. Burger; D. J. Adams; T. Post; L. Sommers; B. Swift

    2005-01-01

    The New York State Bird Conservation Area (BCA) Program, modeled after the National Audubon Society?s Important Bird Areas Program, is based on legislation signed by Governor Pataki in 1997. New York is the first state in the nation to enact such a program. The BCA Program seeks to provide a comprehensive, ecosystem approach to conserving birds and their habitats on...

  16. Eight Models for Explaining States' Total Spending for People with Developmental Disabilities in the United States.

    ERIC Educational Resources Information Center

    Campbell, Edward M.; Fortune, Jon; Heinlein, Ken B.

    This report investigated the financial expenditures of states for services for individuals with developmental disabilities and examined the factors that influenced the level of expenditure. Eight multiple-regression models are presented which explain 70 to 88 percent of the variation in states' total expenditures. In addition to the obvious…

  17. Finite State Models of Manned Systems: Validation, Simplification, and Extension.

    DTIC Science & Technology

    1979-11-01

    point is that the stage of development of theory influences the type of modelling excersize undertaken. One must be explicit in defining the purpose...firing state is entered whenever the trigger is depressed , but firing actually occurs only if the fire control network is in the fire enabled state

  18. Calibration of state and transition models with FVS

    Treesearch

    Melinda Moeur; Don Vandendriesche

    2010-01-01

    The Interagency Mapping and Assessment Project (IMAP), a partnership between federal and state agencies, is developing mid-scale vegetation data and state and transition models (STM) for comparing the likely outcomes of alternative management policies on forested landscapes across the Pacific Northwest Region. In an STM, acres within a forested ecosystem transition...

  19. 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.

  20. Modeling Per Capita State Health Expenditure Variation: State-Level Characteristics Matter

    PubMed Central

    Cuckler, Gigi; Sisko, Andrea

    2013-01-01

    Objective In this paper, we describe the methods underlying the econometric model developed by the Office of the Actuary in the Centers for Medicare & Medicaid Services, to explain differences in per capita total personal health care spending by state, as described in Cuckler, et al. (2011). Additionally, we discuss many alternative model specifications to provide additional insights for valid interpretation of the model. Data Source We study per capita personal health care spending as measured by the State Health Expenditures, by State of Residence for 1991–2009, produced by the Centers for Medicare & Medicaid Services’ Office of the Actuary. State-level demographic, health status, economic, and health economy characteristics were gathered from a variety of U.S. government sources, such as the Census Bureau, Bureau of Economic Analysis, the Centers for Disease Control, the American Hospital Association, and HealthLeaders-InterStudy. Principal Findings State-specific factors, such as income, health care capacity, and the share of elderly residents, are important factors in explaining the level of per capita personal health care spending variation among states over time. However, the slow-moving nature of health spending per capita and close relationships among state-level factors create inefficiencies in modeling this variation, likely resulting in incorrectly estimated standard errors. In addition, we find that both pooled and fixed effects models primarily capture cross-sectional variation rather than period-specific variation. PMID:24834363

  1. Parameter redundancy in discrete state-space and integrated models.

    PubMed

    Cole, Diana J; McCrea, Rachel S

    2016-09-01

    Discrete state-space models are used in ecology to describe the dynamics of wild animal populations, with parameters, such as the probability of survival, being of ecological interest. For a particular parametrization of a model it is not always clear which parameters can be estimated. This inability to estimate all parameters is known as parameter redundancy or a model is described as nonidentifiable. In this paper we develop methods that can be used to detect parameter redundancy in discrete state-space models. An exhaustive summary is a combination of parameters that fully specify a model. To use general methods for detecting parameter redundancy a suitable exhaustive summary is required. This paper proposes two methods for the derivation of an exhaustive summary for discrete state-space models using discrete analogues of methods for continuous state-space models. We also demonstrate that combining multiple data sets, through the use of an integrated population model, may result in a model in which all parameters are estimable, even though models fitted to the separate data sets may be parameter redundant. © 2016 The Author. Biometrical Journal published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  2. 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

  3. Improvement of simple models for state-to-state and multi-temperature reaction rate coefficients

    NASA Astrophysics Data System (ADS)

    Kustova, E. V.; Savelev, A. S.; Sharafutdinov, I. Z.

    2016-11-01

    We propose a simple and accurate model for state-specific dissociation rate coefficients based on the widely used Treanor-Marrone model. It takes into account the dependence of the parameter in the Treanor-Marrone model on temperature and vibrational level and can be used with arbitrary vibrational ladder. The model is validated by comparisons with state-specific dissociation rate coefficients of O2 and N2 obtained using molecular dynamics, and its good accuracy is demonstrated. Two-temperature dissociation rate coefficients are derived averaging the state-specific non-equilibrium factors with different vibrational distributions. The two-temperature rate coefficients are compared with those given by the empirical Park model and coefficients extracted from shock-tube measurements.

  4. Equations of state in a lattice Boltzmann model

    NASA Astrophysics Data System (ADS)

    Yuan, Peng; Schaefer, Laura

    2006-04-01

    In this paper we consider the incorporation of various equations of state into the single-component multiphase lattice Boltzmann model. Several cubic equations of state, including the van der Waals, Redlich-Kwong, and Peng-Robinson, as well as a noncubic equation of state (Carnahan-Starling), are incorporated into the lattice Boltzmann model. The details of phase separation in these nonideal single-component systems are presented by comparing the numerical simulation results in terms of density ratios, spurious currents, and temperature ranges. A comparison with a real fluid system, i.e., the properties of saturated water and steam, is also presented.

  5. Quantum Rabi model for N-state atoms.

    PubMed

    Albert, Victor V

    2012-05-04

    A tractable N-state Rabi Hamiltonian is introduced by extending the parity symmetry of the two-state model. The single-mode case provides a few-parameter description of a novel class of periodic systems, predicting that the ground state of certain four-state atom-cavity systems will undergo parity change at strong-coupling. A group-theoretical treatment provides physical insight into dynamics and a modified rotating wave approximation obtains accurate analytical energies. The dissipative case can be applied to study excitation energy transfer in molecular rings or chains.

  6. 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.

  7. Assessing model state and forecasts variation in hydrologic data assimilation

    NASA Astrophysics Data System (ADS)

    Samuel, Jos; Coulibaly, Paulin; Dumedah, Gift; Moradkhani, Hamid

    2014-05-01

    Data assimilation (DA) has been widely used in hydrological models to improve model state and subsequent streamflow estimates. However, for poor or non-existent state observations, the state estimation in hydrological DA can be problematic, leading to inaccurate streamflow updates. This study evaluates the soil moisture and flow variations and forecasts by assimilating streamflow and soil moisture. Three approaches of Ensemble Kalman Filter (EnKF) with dual state-parameter estimation are applied: (1) streamflow assimilation, (2) soil moistue assimilation, and (3) combined assimilation of soil moisture and streamflow. The assimilation approaches are evaluated using the Sacramento Soil Moisture Accounting (SAC-SMA) model in the Spencer Creek catchment in southern Ontario, Canada. The results show that there are significant differences in soil moisture variations and streamflow estimates when the three assimilation approaches were applied. In the streamflow assimilation, soil moisture states were markedly distorted, particularly soil moisture of lower soil layer; whereas, in the soil moisture assimilation, streamflow estimates are inaccurate. The combined assimilation of streamflow and soil moisture provides more accurate forecasts of both soil moisture and streamflow, particularly for shorter lead times. The combined approach has the flexibility to account for model adjustment through the time variation of parameters together with state variables when soil moisture and streamflow observations are integrated into the assimilation procedure. This evaluation is important for the application of DA methods to simultaneously estimate soil moisture states and watershed response and forecasts.

  8. Intermittent Bellerophon state in frequency-weighted Kuramoto model

    NASA Astrophysics Data System (ADS)

    Zhou, Wenchang; Zou, Yong; Zhou, Jie; Liu, Zonghua; Guan, Shuguang

    2016-12-01

    Recently, the Bellerophon state, which is a quantized, time dependent, clustering state, was revealed in globally coupled oscillators [Bi et al., Phys. Rev. Lett. 117, 204101 (2016)]. The most important characteristic is that in such a state, the oscillators split into multiple clusters. Within each cluster, the instantaneous frequencies of the oscillators are not the same, but their average frequencies lock to a constant. In this work, we further characterize an intermittent Bellerophon state in the frequency-weighted Kuramoto model with a biased Lorentzian frequency distribution. It is shown that the evolution of oscillators exhibits periodical intermittency, following a synchronous pattern of bursting in a short period and resting in a long period. This result suggests that the Bellerophon state might be generic in Kuramoto-like models regardless of different arrangements of natural frequencies.

  9. 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.; hide

    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.

  10. Thermodynamic state ensemble models of cis-regulation.

    PubMed

    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.

  11. 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.

  12. Equity Access Plans: A Regulatory and Educational State Response Model.

    ERIC Educational Resources Information Center

    DeLisle, James

    1984-01-01

    Introduces the basic notion of equity access plans as property-based solutions to the cash flow needs of elderly homeowners and then proposes a normative response model that states can adopt to help manage the risk exposures. The recommended model incorporates regulatory, information dissemination, and educational elements. (BH)

  13. 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…

  14. Ground states of the massless Derezinski-Gerard model

    SciTech Connect

    Ohkubo, Atsushi

    2009-11-15

    We consider the massless Derezinski-Gerard model introduced by Derezinski and Gerard in 1999. We give a sufficient condition for the existence of a ground state of the massless Derezinski-Gerard model without the assumption that the Hamiltonian of particles has compact resolvent.

  15. Kinematic Cosmology & a new ``Steady State'' Model of Continued Creation

    NASA Astrophysics Data System (ADS)

    Wegener, Mogens

    2006-03-01

    Only a new "steady state" model justifies the observations of fully mature galaxies at ever increasing distances. The basic idea behind the world model presented here, which is a synthesis of the cosmologies of Parmenides and Herakleitos, is that the invariant structure of the infinite contents of a universe in flux may be depicted as a finite hyperbolic pseudo-sphere.

  16. Maximizing the Divergence from a Hierarchical Model of Quantum States

    NASA Astrophysics Data System (ADS)

    Weis, Stephan; Knauf, Andreas; Ay, Nihat; Zhao, Ming-Jing

    2015-03-01

    We study many-party correlations quantified in terms of the Umegaki relative entropy (divergence) from a Gibbs family known as a hierarchical model. We derive these quantities from the maximum-entropy principle which was used earlier to define the closely related irreducible correlation. We point out the differences between quantum states and probability vectors which exist in hierarchical models, in the divergence from a hierarchical model and in local maximizers of this divergence. The differences are, respectively, missing factorization, discontinuity and reduction of uncertainty. We discuss global maximizers of the mutual information of separable qubit states.

  17. Evolution of states in a continuum migration model

    NASA Astrophysics Data System (ADS)

    Kondratiev, Yuri; Kozitsky, Yuri

    2017-03-01

    The Markov evolution of states of a continuum migration model is studied. The model describes an infinite system of entities placed in R^d in which the constituents appear (immigrate) with rate b(x) and disappear, also due to competition. For this model, we prove the existence of the evolution of states μ _0 mapsto μ _t such that the moments μ _t(N_Λ ^n) , nin N, of the number of entities in compact Λ subset R^d remain bounded for all t>0 . Under an additional condition, we prove that the density of entities and the second correlation function remain point-wise bounded globally in time.

  18. 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.

  19. Discrete state space modeling and control of nonlinear unknown systems.

    PubMed

    Savran, Aydogan

    2013-11-01

    A novel procedure for integrating neural networks (NNs) with conventional techniques is proposed to design industrial modeling and control systems for nonlinear unknown systems. In the proposed approach, a new recurrent NN with a special architecture is constructed to obtain discrete-time state-space representations of nonlinear dynamical systems. It is referred as the discrete state-space neural network (DSSNN). In the DSSNN, the outputs of the hidden layer neurons of the DSSNN represent the system's (pseudo) state. The inputs are fed to output neurons and the delayed outputs of the hidden layer neurons are fed to their inputs via adjustable weights. The discrete state space model of the actual system is directly obtained by training the DSSNN with the input-output data. A training procedure based on the back-propagation through time (BPTT) algorithm is developed. The Levenberg-Marquardt (LM) method with a trust region approach is used to update the DSSNN weights. Linear state space models enable to use well developed conventional analysis and design techniques. Thus, building a linear model of a system has primary importance in industrial applications. Thus, a suitable linearization procedure is proposed to derive the linear state space model from the nonlinear DSSNN representation. The controllability, observability and stability properties are examined. The state feedback controllers are designed with both the linear quadratic regulator (LQR) and the pole placement techniques. The regulator and servo control problems are both addressed. A full order observer is also designed to estimate the state variables. The performance of the proposed procedure is demonstrated by applying for both single-input single-output (SISO) and multiple-input multiple-output (MIMO) nonlinear control problems. © 2013 ISA. Published by Elsevier Ltd. All rights reserved.

  20. Action Generation Model Based on Changes in State Patterns

    NASA Astrophysics Data System (ADS)

    Gouko, Manabu; Tomi, Naoki; Nagano, Tomoaki; Ito, Koji

    In this paper, we propose a self-organized learning model that can generate behaviors for successfully performing various tasks. The model memorizes various relationships between changes in a state pattern and a motor command through learning. After the learning, the model can perform various tasks by generating the various behaviors automatically. We confirmed the performance of the model by applying it to a mobile robot simulation. The results indicate that suitable behaviors for all the tasks generated spontaneously. Additionally, we propose a sequential learning method which modifies the memorized various relationships while the model executes the task. And we confirmed the effectiveness of the sequential learning by the simulation.

  1. Prediction of magnetic substorms using a state space model

    NASA Astrophysics Data System (ADS)

    Unnikrishnan, K.

    2012-02-01

    Nonlinear dynamical models of the magnetosphere derived from observational time series data using phase space reconstruction techniques have yielded new advances in the understanding of its dynamics. Considering the solar wind-magnetosphere interaction to be a natural input-output system its dynamical features can be reconstructed on the storm time scale by using the method of time delay embedding. Here, fourteen magnetic storm intervals belonging to low/moderate and high solar activity periods are considered and a suitable state space model has designed by performing training and validation tests, for which dawn to dusk electric field (VBz) is chosen as the input, and the AL time series as the output. The percentage of the output variations that is reproduced by the model is termed as fit_model and a higher number of fit_model means a better model. The number of components m used in the state space model is varied from 1-9 and the best prediction is obtained when m=4. The fit_model values of time series used for validation are 67.96, 67.2, 72.44, and 70.89, with m=4. In the present study most of the storms considered are having Dstmax in between -100 and -300 nT, and they can be predicted well with this procedure. To reveal the prediction capability of the proposed state space model the 30 steps ahead outputs for the storm events are generated, which reasonably reproduce the observed values.

  2. Nonlinear regime-switching state-space (RSSS) models.

    PubMed

    Chow, Sy-Miin; Zhang, Guangjian

    2013-10-01

    Nonlinear dynamic factor analysis models extend standard linear dynamic factor analysis models by allowing time series processes to be nonlinear at the latent level (e.g., involving interaction between two latent processes). In practice, it is often of interest to identify the phases--namely, latent "regimes" or classes--during which a system is characterized by distinctly different dynamics. We propose a new class of models, termed nonlinear regime-switching state-space (RSSS) models, which subsumes regime-switching nonlinear dynamic factor analysis models as a special case. In nonlinear RSSS models, the change processes within regimes, represented using a state-space model, are allowed to be nonlinear. An estimation procedure obtained by combining the extended Kalman filter and the Kim filter is proposed as a way to estimate nonlinear RSSS models. We illustrate the utility of nonlinear RSSS models by fitting a nonlinear dynamic factor analysis model with regime-specific cross-regression parameters to a set of experience sampling affect data. The parallels between nonlinear RSSS models and other well-known discrete change models in the literature are discussed briefly.

  3. 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

  4. Excited-state quantum phase transition in the Rabi model

    NASA Astrophysics Data System (ADS)

    Puebla, Ricardo; Hwang, Myung-Joong; Plenio, Martin B.

    2016-08-01

    The Rabi model, a two-level atom coupled to a harmonic oscillator, can undergo a second-order quantum phase transition (QPT) [M.-J. Hwang et al., Phys. Rev. Lett. 115, 180404 (2015), 10.1103/PhysRevLett.115.180404]. Here we show that the Rabi QPT accompanies critical behavior in the higher-energy excited states, i.e., the excited-state QPT (ESQPT). We derive analytic expressions for the semiclassical density of states, which show a logarithmic divergence at a critical energy eigenvalue in the broken symmetry (superradiant) phase. Moreover, we find that the logarithmic singularities in the density of states lead to singularities in the relevant observables in the system such as photon number and atomic polarization. We corroborate our analytical semiclassical prediction of the ESQPT in the Rabi model with its numerically exact quantum mechanical solution.

  5. State resolved vibrational relaxation modeling for strongly nonequilibrium flows

    NASA Astrophysics Data System (ADS)

    Boyd, Iain D.; Josyula, Eswar

    2011-05-01

    Vibrational relaxation is an important physical process in hypersonic flows. Activation of the vibrational mode affects the fundamental thermodynamic properties and finite rate relaxation can reduce the degree of dissociation of a gas. Low fidelity models of vibrational activation employ a relaxation time to capture the process at a macroscopic level. High fidelity, state-resolved models have been developed for use in continuum gas dynamics simulations based on computational fluid dynamics (CFD). By comparison, such models are not as common for use with the direct simulation Monte Carlo (DSMC) method. In this study, a high fidelity, state-resolved vibrational relaxation model is developed for the DSMC technique. The model is based on the forced harmonic oscillator approach in which multi-quantum transitions may become dominant at high temperature. Results obtained for integrated rate coefficients from the DSMC model are consistent with the corresponding CFD model. Comparison of relaxation results obtained with the high-fidelity DSMC model shows significantly less excitation of upper vibrational levels in comparison to the standard, lower fidelity DSMC vibrational relaxation model. Application of the new DSMC model to a Mach 7 normal shock wave in carbon monoxide provides better agreement with experimental measurements than the standard DSMC relaxation model.

  6. 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.

  7. 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

  8. Impulses and Physiological States in Theoretical Models of Nerve Membrane

    PubMed Central

    FitzHugh, Richard

    1961-01-01

    Van der Pol's equation for a relaxation oscillator is generalized by the addition of terms to produce a pair of non-linear differential equations with either a stable singular point or a limit cycle. The resulting “BVP model” has two variables of state, representing excitability and refractoriness, and qualitatively resembles Bonhoeffer's theoretical model for the iron wire model of nerve. This BVP model serves as a simple representative of a class of excitable-oscillatory systems including the Hodgkin-Huxley (HH) model of the squid giant axon. The BVP phase plane can be divided into regions corresponding to the physiological states of nerve fiber (resting, active, refractory, enhanced, depressed, etc.) to form a “physiological state diagram,” with the help of which many physiological phenomena can be summarized. A properly chosen projection from the 4-dimensional HH phase space onto a plane produces a similar diagram which shows the underlying relationship between the two models. Impulse trains occur in the BVP and HH models for a range of constant applied currents which make the singular point representing the resting state unstable. PMID:19431309

  9. Ground states of the spin-1 Bose-Hubbard model.

    PubMed

    Katsura, Hosho; Tasaki, Hal

    2013-03-29

    We prove basic theorems about the ground states of the S=1 Bose-Hubbard model. The results are quite universal and depend only on the coefficient U2 of the spin-dependent interaction. We show that the ground state exhibits saturated ferromagnetism if U2<0, is spin-singlet if U2>0, and exhibits "SU(3)-ferromagnetism" if U2=0, and completely determine the degeneracy in each region.

  10. 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.

  11. 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

  12. 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.

  13. 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.

  14. Model Fractional Quantum Hall States and Jack Polynomials

    SciTech Connect

    Bernevig, B. Andrei; Haldane, F. D. M.

    2008-06-20

    We describe an occupation-number-like picture of fractional quantum Hall states in terms of polynomial wave functions characterized by a dominant occupation-number configuration. The bosonic variants of single-component Abelian and non-Abelian fractional quantum Hall states are modeled by Jack symmetric polynomials (Jacks), characterized by dominant occupation-number configurations satisfying a generalized Pauli principle. In a series of well-known quantum Hall states, including the Laughlin, Read-Moore, and Read-Rezayi, the Jack polynomials naturally implement a ''squeezing rule'' that constrains allowed configurations to be restricted to those obtained by squeezing the dominant configuration. The Jacks presented in this Letter describe new trial uniform states, but it is yet to be determined to which actual experimental fractional quantum Hall effect states they apply.

  15. 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

  16. 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

  17. 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.

  18. 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.

  19. Insights from simple models for surface states in nanostructures

    NASA Astrophysics Data System (ADS)

    Boykin, Timothy B.; Klimeck, Gerhard

    2017-03-01

    Surface passivation is of great technological importance due to the increasing miniaturisation of electronic devices. It has been known for many years that under certain conditions surface states can form; when they do so in a quantum well (QW) the result is an unbound (i.e., evanescent) state in the QW. Such surface states are generally undesirable, so a good physical understanding of them is important. A simple single-p-orbital valence band model is used with two types of surface passivation to examine surface states in a QW: (1) an energy upshift added to the terminal atoms; and (2) explicit passivation by an s-orbital on each end of the QW. These models show these unbound/evanescent QW states can occur in both models; that in them the wavefunction is bound to the terminal atoms; and that the existence of these states is connected to the effective valence-band offset between the terminal atoms and the bulk QW.

  20. Purely optical navigation with model-based state prediction

    NASA Astrophysics Data System (ADS)

    Sendobry, Alexander; Graber, Thorsten; Klingauf, Uwe

    2010-10-01

    State-of-the-art Inertial Navigation Systems (INS) based on Micro-Electro-Mechanical Systems (MEMS) have a lack of precision especially in GPS denied environments like urban canyons or in pure indoor missions. The proposed Optical Navigation System (ONS) provides bias free ego-motion estimates using triple redundant sensor information. In combination with a model based state prediction our system is able to estimate velocity, position and attitude of an arbitrary aircraft. Simulating a high performance flow-field estimator the algorithm can compete with conventional low-cost INS. By using measured velocities instead of accelerations the system states drift behavior is not as distinctive as for an INS.

  1. Modeling of the stress state of the thumb carpometacarpal joint

    NASA Astrophysics Data System (ADS)

    Anferov, G. M.; Goryacheva, I. G.; Lyubicheva, A. N.; Soldatenkov, I. A.; Su, Fong-Chin; Chang, Chih-Han

    2013-07-01

    The stress state of the carpometacarpal joint (CMJ)was studied in sound and pathologic states by methods of continuum mechanics. The CMJ geometric model was constructed according to the results of computer processing of the data of tomographic investigations in the extension position, which were obtained at Cheng Kung Medical University (Taiwan). The study of contact interactions in the CML region for a given geometry were performed numerically in the ABAQUS program code. The obtained numerical solutions of contact problems permit comparatively analyzing the stress distribution in the bone tissue for various thumb positions and study the stress state dependence on the bone tissue porosity (osteoporosis), which varies with human age.

  2. Steady States and Universal Conductance in a Quenched Luttinger Model

    NASA Astrophysics Data System (ADS)

    Langmann, Edwin; Lebowitz, Joel L.; Mastropietro, Vieri; Moosavi, Per

    2017-01-01

    We obtain exact analytical results for the evolution of a 1+1-dimensional Luttinger model prepared in a domain wall initial state, i.e., a state with different densities on its left and right sides. Such an initial state is modeled as the ground state of a translation invariant Luttinger Hamiltonian {H_{λ}} with short range non-local interaction and different chemical potentials to the left and right of the origin. The system evolves for time t > 0 via a Hamiltonian {H_{λ'}} which differs from {H_{λ}} by the strength of the interaction. Asymptotically in time, as {t to ∞}, after taking the thermodynamic limit, the system approaches a translation invariant steady state. This final steady state carries a current I and has an effective chemical potential difference {μ+ - μ-} between right- (+) and left- (-) moving fermions obtained from the two-point correlation function. Both I and {μ+ - μ-} depend on {λ} and {λ'}. Only for the case {λ = λ' = 0} does {μ+ - μ-} equal the difference in the initial left and right chemical potentials. Nevertheless, the Landauer conductance for the final state, {G = I/(μ+ - μ-)}, has a universal value equal to the conductance quantum {e^2/h} for the spinless case.

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

    USGS Publications Warehouse

    Bailey, L.L.; Kendall, W.L.; Church, D.R.; Thomson, David L.; Cooch, Evan G.; Conroy, Michael J.

    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

  4. Determining state-space models from sequential output data

    NASA Technical Reports Server (NTRS)

    Lin, Jiguan Gene

    1988-01-01

    This talk focuses on the determination of state-space models for large space systems using only the output data. The output data could be generated by the unknown or deliberate initial conditions of the space structure in question. We shall review some relevant fundamental work on the state-space modeling of sequential output data that is potentially applicable to large space structures. If formulated in terms of some generalized Markov parameters, this approach is in some sense similar to, but much simpler than, the Juang-Pappa Eigensystem Realization Algorithm (ERA) and the Ho-Kalman construction procedure.

  5. A Computationally Efficient State Space Approach to Estimating Multilevel Regression Models and Multilevel Confirmatory Factor Models.

    PubMed

    Gu, Fei; Preacher, Kristopher J; Wu, Wei; Yung, Yiu-Fai

    2014-01-01

    Although the state space approach for estimating multilevel regression models has been well established for decades in the time series literature, it does not receive much attention from educational and psychological researchers. In this article, we (a) introduce the state space approach for estimating multilevel regression models and (b) extend the state space approach for estimating multilevel factor models. A brief outline of the state space formulation is provided and then state space forms for univariate and multivariate multilevel regression models, and a multilevel confirmatory factor model, are illustrated. The utility of the state space approach is demonstrated with either a simulated or real example for each multilevel model. It is concluded that the results from the state space approach are essentially identical to those from specialized multilevel regression modeling and structural equation modeling software. More importantly, the state space approach offers researchers a computationally more efficient alternative to fit multilevel regression models with a large number of Level 1 units within each Level 2 unit or a large number of observations on each subject in a longitudinal study.

  6. Hindcasting to measure ice sheet model sensitivity to initial states

    NASA Astrophysics Data System (ADS)

    Aschwanden, A.; Aðalgeirsdóttir, G.; Khroulev, C.

    2013-07-01

    Validation is a critical component of model development, yet notoriously challenging in ice sheet modeling. Here we evaluate how an ice sheet system model responds to a given forcing. We show that hindcasting, i.e. forcing a model with known or closely estimated inputs for past events to see how well the output matches observations, is a viable method of assessing model performance. By simulating the recent past of Greenland, and comparing to observations of ice thickness, ice discharge, surface speeds, mass loss and surface elevation changes for validation, we find that the short term model response is strongly influenced by the initial state. We show that the thermal and dynamical states (i.e. the distribution of internal energy and momentum) can be misrepresented despite a good agreement with some observations, stressing the importance of using multiple observations. In particular we identify rates of change of spatially dense observations as preferred validation metrics. Hindcasting enables a qualitative assessment of model performance relative to observed rates of change. It thereby reduces the number of admissible initial states more rigorously than validation efforts that do not take advantage of observed rates of change.

  7. 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.

  8. STEADY-STATE MODEL OF SOLAR WIND ELECTRONS REVISITED

    SciTech Connect

    Yoon, Peter H.; Kim, Sunjung; Choe, G. S.

    2015-10-20

    In a recent paper, Kim et al. put forth a steady-state model for the solar wind electrons. The model assumed local equilibrium between the halo electrons, characterized by an intermediate energy range, and the whistler-range fluctuations. The basic wave–particle interaction is assumed to be the cyclotron resonance. Similarly, it was assumed that a dynamical steady state is established between the highly energetic superhalo electrons and high-frequency Langmuir fluctuations. Comparisons with the measured solar wind electron velocity distribution function (VDF) during quiet times were also made, and reasonable agreements were obtained. In such a model, however, only the steady-state solution for the Fokker–Planck type of electron particle kinetic equation was considered. The present paper complements the previous analysis by considering both the steady-state particle and wave kinetic equations. It is shown that the model halo and superhalo electron VDFs, as well as the assumed wave intensity spectra for the whistler and Langmuir fluctuations, approximately satisfy the quasi-linear wave kinetic equations in an approximate sense, thus further validating the local equilibrium model constructed in the paper by Kim et al.

  9. Equations of state for explosive detonation products: The PANDA model

    SciTech Connect

    Kerley, G.I.

    1994-05-01

    This paper discusses a thermochemical model for calculating equations of state (EOS) for the detonation products of explosives. This model, which was first presented at the Eighth Detonation Symposium, is available in the PANDA code and is referred to here as ``the Panda model``. The basic features of the PANDA model are as follows. (1) Statistical-mechanical theories are used to construct EOS tables for each of the chemical species that are to be allowed in the detonation products. (2) The ideal mixing model is used to compute the thermodynamic functions for a mixture of these species, and the composition of the system is determined from assumption of chemical equilibrium. (3) For hydrocode calculations, the detonation product EOS are used in tabular form, together with a reactive burn model that allows description of shock-induced initiation and growth or failure as well as ideal detonation wave propagation. This model has been implemented in the three-dimensional Eulerian code, CTH.

  10. State-to-state modeling of ultrashort laser-induced plasmas

    NASA Astrophysics Data System (ADS)

    Morel, Vincent; Bultel, Arnaud; Schneider, Ioan; Grisolia, Christian

    2017-01-01

    The question of the Local Thermodynamic Equilibrium (LTE) of laser-induced plasmas is crucial regarding the Laser-Induced Breakdown Spectroscopy (LIBS) technique. The most relevant way to assess theoretically the possible departure from LTE is to develop state-to-state models of the chemical species involved. The present paper illustrates such an elaboration in the case of aluminum and tungsten. Based on this state-to-state approach, the two collisional-radiative models CoRaM-Al and CoRaM-W are elaborated. They include elementary processes under electron and heavy particle impact in thermal non-equilibrium, spontaneous emission, radiative recombination and thermal Bremsstrahlung. These models are applied to the case of ultrashort laser-induced plasmas expanding in an argon gas at different pressure, for which a relevant collisional-radiative model is also elaborated to predict the propagation of the shock wave. The laser conditions are close to those used for a typical LIBS analysis under ultrashort regime. At high argon pressure (105 Pa), the relaxation of the plasma takes place according to a rather low departure from LTE, as revealed by the thorough examination of the Boltzmann plots derived from the state-to-state models. This relaxation occurs at temperature higher for aluminum than for tungsten, but close to 10,000 K from 200 ns. Conversely, at low pressure (10 Pa), the extinction of the plasma is observed at ∼ 500 ns, just after a phase corresponding to significant departure from equilibrium. These results support the idea of the choice of short gate delays close to the laser pulse for the LIBS characterization of tungsten matrices in tokamak-like conditions.

  11. 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

  12. Classical electromagnetic model of surface states in topological insulators

    NASA Astrophysics Data System (ADS)

    Lakhtakia, Akhlesh; Mackay, Tom G.

    2016-07-01

    A topological insulator is classically modeled as an isotropic material with a magnetoelectric pseudoscalar Ψ existing in its bulk while its surface is charge free and current free. An alternative model is obtained by setting Ψ≡0 and incorporating surface charge and current densities characterized by an admittance γ. Analysis of planewave reflection and refraction due to a topological-insulator half space reveals that the parameters Ψ and γ arise identically in the reflection and transmission coefficients, implying that the two classical models cannot be distinguished on the basis of any scattering scenario. However, as Ψ disappears from the Maxwell equations applicable to any region occupied by the topological insulator, and because surface states exist on topological insulators as protected conducting states, the alternative model must be chosen.

  13. Path Flow Estimation Using Time Varying Coefficient State Space Model

    NASA Astrophysics Data System (ADS)

    Jou, Yow-Jen; Lan, Chien-Lun

    2009-08-01

    The dynamic path flow information is very crucial in the field of transportation operation and management, i.e., dynamic traffic assignment, scheduling plan, and signal timing. Time-dependent path information, which is important in many aspects, is nearly impossible to be obtained. Consequently, researchers have been seeking estimation methods for deriving valuable path flow information from less expensive traffic data, primarily link traffic counts of surveillance systems. This investigation considers a path flow estimation problem involving the time varying coefficient state space model, Gibbs sampler, and Kalman filter. Numerical examples with part of a real network of the Taipei Mass Rapid Transit with real O-D matrices is demonstrated to address the accuracy of proposed model. Results of this study show that this time-varying coefficient state space model is very effective in the estimation of path flow compared to time-invariant model.

  14. Gamow-Teller states in relativistic nuclear models

    NASA Astrophysics Data System (ADS)

    Kurasawa, Haruki; Suzuki, Toshio; van Giai, Nguyen

    2003-12-01

    The Gamow-Teller (GT) states are investigated in relativistic models. The Landau-Migdal (LM) parameter is introduced in the Lagrangian as a contact term with the pseudovector coupling. In the relativistic model the total GT strength in the nucleon space is quenched by about 12% in nuclear matter and by about 6% in finite nuclei, compared with the Ikeda-Fujii-Fujita sum rule. The quenched amount is taken by nucleon-antinucleon excitations in the timelike region. Because of the quenching, the relativistic model requires a larger value of the LM parameter than nonrelativistic models in describing the GT excitation energy. On the other hand, the effect of the Pauli blocking terms is not important for the GT states.

  15. 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).

  16. Electronic structure and localized states in a model amorphous silicon

    NASA Astrophysics Data System (ADS)

    Allan, G.; Delerue, C.; Lannoo, M.

    1998-03-01

    The electronic structure of a model amorphous silicon (a-Si) represented by a supercell of 4096 silicon atoms [B.R. Djordjevic, M.F. Thorpe, and F. Wooten, Phys. Rev. B 52, 5685 (1995)] and of a model hydrogenated amorphous silicon (a-Si:H) that we have built from the a-Si model are calculated in the tight-binding approximation. The band edges near the gap are characterized by exponential tails of localized states induced mainly by the variations in bond angles. The spatial localization of the states is compared between a-Si and a-Si:H. Comparison with experiments suggests that the structural models give good descriptions of the amorphous materials.

  17. Staggered Flux State in Two-Dimensional Hubbard Models

    NASA Astrophysics Data System (ADS)

    Yokoyama, Hisatoshi; Tamura, Shun; Ogata, Masao

    2016-12-01

    The stability and other properties of a staggered flux (SF) state or a correlated d-density wave state are studied for the Hubbard (t-t'-U) model on extended square lattices, as a low-lying state that competes with the dx2 - y2-wave superconductivity (d-SC) and possibly causes the pseudogap phenomena in underdoped high-Tc cuprates and organic κ-BEDT-TTF salts. In calculations, a variational Monte Carlo method is used. In the trial wave function, a configuration-dependent phase factor, which is vital to treat a current-carrying state for a large U/t, is introduced in addition to ordinary correlation factors. Varying U/t, t'/t, and the doping rate (δ) systematically, we show that the SF state becomes more stable than the normal state (projected Fermi sea) for a strongly correlated (U/t ≳ 5) and underdoped (δ ≲ 0.16) area. The decrease in energy is sizable, particularly in the area where Mott physics prevails and the circular current (order parameter) is strongly suppressed. These features are consistent with those for the t-J model. The effect of the frustration t'/t plays a crucial role in preserving charge homogeneity and appropriately describing the behavior of hole- and electron-doped cuprates and κ-BEDT-TTF salts. We argue that the SF state does not coexist with d-SC and is not a "normal state" from which d-SC arises. We also show that a spin current (flux or nematic) state is never stabilized in the same regime.

  18. State Space Model for Autopilot Design of Aerospace Vehicles

    DTIC Science & Technology

    2007-03-01

    possibly for future application of non-linear analysis and synthesis techniques , particularly for autopilot design of aerospace vehicles executing high g...manoeuvres. This report also considers a locally linearised state space model that lends itself to better known linear techniques of the modern...control theory. A coupled multi-input multi-output (MIMO) model is derived suitable for both the application of the modern control techniques as well

  19. A 3-states magnetic model of binary decisions in sociophysics

    NASA Astrophysics Data System (ADS)

    Fernandez, Miguel A.; Korutcheva, Elka; de la Rubia, F. Javier

    2016-11-01

    We study a diluted Blume-Capel model of 3-states sites as an attempt to understand how some social processes as cooperation or organization happen. For this aim, we study the effect of the complex network topology on the equilibrium properties of the model, by focusing on three different substrates: random graph, Watts-Strogatz and Newman substrates. Our computer simulations are in good agreement with the corresponding analytical results.

  20. Multiple time scales in multi-state models.

    PubMed

    Iacobelli, Simona; Carstensen, Bendix

    2013-12-30

    In multi-state models, it has been the tradition to model all transition intensities on one time scale, usually the time since entry into the study ('clock-forward' approach). The effect of time since an intermediate event has been accommodated either by changing the time scale to time since entry to the new state ('clock-back' approach) or by including the time at entry to the new state as a covariate. In this paper, we argue that the choice of time scale for the various transitions in a multi-state model should be dealt with as an empirical question, as also the question of whether a single time scale is sufficient. We illustrate that these questions are best addressed by using parametric models for the transition rates, as opposed to the traditional Cox-model-based approaches. Specific advantages are that dependence of failure rates on multiple time scales can be made explicit and described in informative graphical displays. Using a single common time scale for all transitions greatly facilitates computations of probabilities of being in a particular state at a given time, because the machinery from the theory of Markov chains can be applied. However, a realistic model for transition rates is preferable, especially when the focus is not on prediction of final outcomes from start but on the analysis of instantaneous risk or on dynamic prediction. We illustrate the various approaches using a data set from stem cell transplant in leukemia and provide supplementary online material in R. Copyright © 2013 John Wiley & Sons, Ltd.

  1. Ising percolation in a three-state majority vote model

    NASA Astrophysics Data System (ADS)

    Balankin, Alexander S.; Martínez-Cruz, M. A.; Gayosso Martínez, Felipe; Mena, Baltasar; Tobon, Atalo; Patiño-Ortiz, Julián; Patiño-Ortiz, Miguel; Samayoa, Didier

    2017-02-01

    In this Letter, we introduce a three-state majority vote model in which each voter adopts a state of a majority of its active neighbors, if exist, but the voter becomes uncommitted if its active neighbors are in a tie, or all neighbors are the uncommitted. Numerical simulations were performed on square lattices of different linear size with periodic boundary conditions. Starting from a random distribution of active voters, the model leads to a stable non-consensus state in which three opinions coexist. We found that the "magnetization" of the non-consensus state and the concentration of uncommitted voters in it are governed by an initial composition of system and are independent of the lattice size. Furthermore, we found that a configuration of the stable non-consensus state undergoes a second order percolation transition at a critical concentration of voters holding the same opinion. Numerical simulations suggest that this transition belongs to the same universality class as the Ising percolation. These findings highlight the effect of an updating rule for a tie between voter neighbors on the critical behavior of models obeying the majority vote rule whenever a strict majority exists.

  2. 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.

  3. Markov state model of the two-state behaviour of water

    NASA Astrophysics Data System (ADS)

    Hamm, Peter

    2016-10-01

    With the help of a Markov State Model (MSM), two-state behaviour is resolved for two computer models of water in a temperature range from 255 K to room temperature (295 K). The method is first validated for ST2 water, for which the so far strongest evidence for a liquid-liquid phase transition exists. In that case, the results from the MSM can be cross-checked against the radial distribution function g5(r) of the 5th-closest water molecule around a given reference water molecule. The latter is a commonly used local order parameter, which exhibits a bimodal distribution just above the liquid-liquid critical point that represents the low-density form of the liquid (LDL) and the high density liquid. The correlation times and correlation lengths of the corresponding spatial domains are calculated and it is shown that they are connected via a simple diffusion model. Once the approach is established, TIP4P/2005 will be considered, which is the much more realistic representation of real water. The MSM can resolve two-state behavior also in that case, albeit with significantly smaller correlation times and lengths. The population of LDL-like water increases with decreasing temperature, thereby explaining the density maximum at 4 °C along the lines of the two-state model of water.

  4. A three-state model for the photophysics of adenine.

    PubMed

    Serrano-Andrés, Luis; Merchán, Manuela; Borin, Antonio Carlos

    2006-08-25

    An ab initio theoretical study at the CASPT2 level is reported on minimum energy reaction paths, state minima, transition states, reaction barriers, and conical intersections on the potential energy hypersurfaces of two tautomers of adenine: 9H- and 7H-adenine. The obtained results led to a complete interpretation of the photophysics of adenine and derivatives, both under jet-cooled conditions and in solution, within a three-state model. The ultrafast subpicosecond fluorescence decay measured in adenine is attributed to the low-lying conical intersection (gs/pipi* La)(CI), reached from the initially populated 1(pipi* La) state along a path which is found to be barrierless only in 9H-adenine, while for the 7H tautomer the presence of an intermediate plateau corresponding to an NH2-twisted conformation may explain the absence of ultrafast decay in 7-substituted compounds. A secondary picosecond decay is assigned to a path involving switches towards two other states, 1(pipi* Lb) and 1(npi*), ultimately leading to another conical intersection with the ground state, (gs/npi*), with a perpendicular disposition of the amino group. The topology of the hypersurfaces and the state properties explain the absence of secondary decay in 9-substituted adenines in water in terms of the higher position of the 1(npi*) state and also that the 1(pipi* Lb) state of 7H-adenine is responsible for the observed fluorescence in water. A detailed discussion comparing recent experimental and theoretical findings is given. As for other nucleobases, the predominant role of a pipi*-type state in the ultrafast deactivation of adenine is confirmed.

  5. 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)

  6. 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.

  7. 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.

  8. 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…

  9. Paraprofessionals in Career Services: The Florida State University Model.

    ERIC Educational Resources Information Center

    Lenz, Janet G.

    This report is designed to provide information on the model developed for the career advisor (CA) program at the Florida State University (FSU) Career Center. The program serves the dual role of providing career services to the students along with training the next generation of career services providers. Since the career advisors who work in the…

  10. Optimal Tree Increment Models for the Northeastern United States

    Treesearch

    Don C. Bragg

    2005-01-01

    I used the potential relative increment (PRI) methodology to develop optimal tree diameter growth models for the Northeastern United States. Thirty species from the Eastwide Forest Inventory Database yielded 69,676 individuals, which were then reduced to fast-growing subsets for PRI analysis. For instance, only 14 individuals from the greater than 6,300-tree eastern...

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

    USDA-ARS?s Scientific Manuscript database

    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...

  12. 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)

  13. 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…

  14. Entropy and equilibrium state of free market models

    NASA Astrophysics Data System (ADS)

    Iglesias, J. R.; de Almeida, R. M. C.

    2012-03-01

    Many recent models of trade dynamics use the simple idea of wealth exchanges among economic agents in order to obtain a stable or equilibrium distribution of wealth among the agents. In particular, a plain analogy compares the wealth in a society with the energy in a physical system, and the trade between agents to the energy exchange between molecules during collisions. In physical systems, the energy exchange among molecules leads to a state of equipartition of the energy and to an equilibrium situation where the entropy is a maximum. On the other hand, in a large class of exchange models, the system converges to a very unequal condensed state, where one or a few agents concentrate all the wealth of the society while the wide majority of agents shares zero or almost zero fraction of the wealth. So, in those economic systems a minimum entropy state is attained. We propose here an analytical model where we investigate the effects of a particular class of economic exchanges that minimize the entropy. By solving the model we discuss the conditions that can drive the system to a state of minimum entropy, as well as the mechanisms to recover a kind of equipartition of wealth.

  15. 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.

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

    USDA-ARS?s Scientific Manuscript database

    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...

  17. Dimensional reduction of Markov state models from renormalization group theory

    NASA Astrophysics Data System (ADS)

    Orioli, S.; Faccioli, P.

    2016-09-01

    Renormalization Group (RG) theory provides the theoretical framework to define rigorous effective theories, i.e., systematic low-resolution approximations of arbitrary microscopic models. Markov state models are shown to be rigorous effective theories for Molecular Dynamics (MD). Based on this fact, we use real space RG to vary the resolution of the stochastic model and define an algorithm for clustering microstates into macrostates. The result is a lower dimensional stochastic model which, by construction, provides the optimal coarse-grained Markovian representation of the system's relaxation kinetics. To illustrate and validate our theory, we analyze a number of test systems of increasing complexity, ranging from synthetic toy models to two realistic applications, built form all-atom MD simulations. The computational cost of computing the low-dimensional model remains affordable on a desktop computer even for thousands of microstates.

  18. Dimensional reduction of Markov state models from renormalization group theory.

    PubMed

    Orioli, S; Faccioli, P

    2016-09-28

    Renormalization Group (RG) theory provides the theoretical framework to define rigorous effective theories, i.e., systematic low-resolution approximations of arbitrary microscopic models. Markov state models are shown to be rigorous effective theories for Molecular Dynamics (MD). Based on this fact, we use real space RG to vary the resolution of the stochastic model and define an algorithm for clustering microstates into macrostates. The result is a lower dimensional stochastic model which, by construction, provides the optimal coarse-grained Markovian representation of the system's relaxation kinetics. To illustrate and validate our theory, we analyze a number of test systems of increasing complexity, ranging from synthetic toy models to two realistic applications, built form all-atom MD simulations. The computational cost of computing the low-dimensional model remains affordable on a desktop computer even for thousands of microstates.

  19. 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.

  20. Trait and state anxiety in animal models: Is there correlation?

    PubMed

    Goes, Tiago Costa; Antunes, Fabrício Dias; Teixeira-Silva, Flavia

    2009-02-06

    It is believed that subjects with high trait anxiety levels tend to present state anxiety reactions with greater intensity than individuals with low trait anxiety levels. In order to verify if this premise is valid for animal models of anxiety, the present work investigated the possible correlation between two behavioral tests: the elevated plus-maze, a classic model of state-anxiety, and the free-exploratory paradigm, which has been proposed as a model of trait anxiety. The behavior of 46 drug-naive, adult, Wistar, male rats was measured in these two models on two occasions, 1 week apart. Subsequently, the intraclass correlation coefficient (ICC) was calculated for the parameters "percentage of time in the novel side" (%TNS; free-exploratory paradigm), "percentage of time in the open arms" (%TOA; elevated plus-maze) and "percentage of entries into the open arms" (%EOA; elevated plus-maze). These parameters were also used to classify the animals into groups presenting high, medium or low levels of anxiety in both tests, so that the concordance between the models could be evaluated through the kappa test. The analysis resulted in low ICC (%TNSx%TOA: -0.127; %TNSx%EOA: 0.040) and low kappa index (%TNSx%TOA: -0.017; %TNSx%EOA: -0.044), suggesting a poor correspondence between the free-exploratory paradigm and the elevated plus-maze. In conclusion, the data presented here indicate that the premise of correlation between trait and state anxiety is not necessarily true for animal models of anxiety and, therefore, care must be exercised when using state anxiety models in order to determine animals' anxiety profile.

  1. A three-state model for the photophysics of guanine.

    PubMed

    Serrano-Andrés, Luis; Merchán, Manuela; Borin, Antonio Carlos

    2008-02-27

    The nonadiabatic photochemistry of the guanine molecule (2-amino-6-oxopurine) and some of its tautomers has been studied by means of the high-level theoretical ab initio quantum chemistry methods CASSCF and CASPT2. Accurate computations, based by the first time on minimum energy reaction paths, states minima, transition states, reaction barriers, and conical intersections on the potential energy hypersurfaces of the molecules lead to interpret the photochemistry of guanine and derivatives within a three-state model. As in the other purine DNA nucleobase, adenine, the ultrafast subpicosecond fluorescence decay measured in guanine is attributed to the barrierless character of the path leading from the initially populated 1(pi pi* L(a)) spectroscopic state of the molecule toward the low-lying methanamine-like conical intersection (gs/pi pi* L(a))CI. On the contrary, other tautomers are shown to have a reaction energy barrier along the main relaxation profile. A second, slower decay is attributed to a path involving switches toward two other states, 1(pi pi* L(b)) and, in particular, 1(n(O) pi*), ultimately leading to conical intersections with the ground state. A common framework for the ultrafast relaxation of the natural nucleobases is obtained in which the predominant role of a pi pi*-type state is confirmed.

  2. The two-state dimer receptor model: a general model for receptor dimers.

    PubMed

    Franco, Rafael; Casadó, Vicent; Mallol, Josefa; Ferrada, Carla; Ferré, Sergi; Fuxe, Kjell; Cortés, Antoni; Ciruela, Francisco; Lluis, Carmen; Canela, Enric I

    2006-06-01

    Nonlinear Scatchard plots are often found for agonist binding to G-protein-coupled receptors. Because there is clear evidence of receptor dimerization, these nonlinear Scatchard plots can reflect cooperativity on agonist binding to the two binding sites in the dimer. According to this, the "two-state dimer receptor model" has been recently derived. In this article, the performance of the model has been analyzed in fitting data of agonist binding to A(1) adenosine receptors, which are an example of receptor displaying concave downward Scatchard plots. Analysis of agonist/antagonist competition data for dopamine D(1) receptors using the two-state dimer receptor model has also been performed. Although fitting to the two-state dimer receptor model was similar to the fitting to the "two-independent-site receptor model", the former is simpler, and a discrimination test selects the two-state dimer receptor model as the best. This model was also very robust in fitting data of estrogen binding to the estrogen receptor, for which Scatchard plots are concave upward. On the one hand, the model would predict the already demonstrated existence of estrogen receptor dimers. On the other hand, the model would predict that concave upward Scatchard plots reflect positive cooperativity, which can be neither predicted nor explained by assuming the existence of two different affinity states. In summary, the two-state dimer receptor model is good for fitting data of binding to dimeric receptors displaying either linear, concave upward, or concave downward Scatchard plots.

  3. Expiratory model-based method to monitor ARDS disease state

    PubMed Central

    2013-01-01

    Introduction Model-based methods can be used to characterise patient-specific condition and response to mechanical ventilation (MV) during treatment for acute respiratory distress syndrome (ARDS). Conventional metrics of respiratory mechanics are based on inspiration only, neglecting data from the expiration cycle. However, it is hypothesised that expiratory data can be used to determine an alternative metric, offering another means to track patient condition and guide positive end expiratory pressure (PEEP) selection. Methods Three fully sedated, oleic acid induced ARDS piglets underwent three experimental phases. Phase 1 was a healthy state recruitment manoeuvre. Phase 2 was a progression from a healthy state to an oleic acid induced ARDS state. Phase 3 was an ARDS state recruitment manoeuvre. The expiratory time-constant model parameter was determined for every breathing cycle for each subject. Trends were compared to estimates of lung elastance determined by means of an end-inspiratory pause method and an integral-based method. All experimental procedures, protocols and the use of data in this study were reviewed and approved by the Ethics Committee of the University of Liege Medical Faculty. Results The overall median absolute percentage fitting error for the expiratory time-constant model across all three phases was less than 10 %; for each subject, indicating the capability of the model to capture the mechanics of breathing during expiration. Provided the respiratory resistance was constant, the model was able to adequately identify trends and fundamental changes in respiratory mechanics. Conclusion Overall, this is a proof of concept study that shows the potential of continuous monitoring of respiratory mechanics in clinical practice. Respiratory system mechanics vary with disease state development and in response to MV settings. Therefore, titrating PEEP to minimal elastance theoretically results in optimal PEEP selection. Trends matched clinical

  4. Edge Theories in Projected Entangled Pair State Models

    NASA Astrophysics Data System (ADS)

    Yang, S.; Lehman, L.; Poilblanc, D.; Van Acoleyen, K.; Verstraete, F.; Cirac, J. I.; Schuch, N.

    2014-01-01

    We analyze the low energy excitations of spin lattice systems in two dimensions at zero temperature within the framework of projected entangled pair state models. Perturbations in the bulk give rise to physical excitations located at the edge. We identify the corresponding degrees of freedom, give a procedure to derive the edge Hamiltonian, and illustrate that it can exhibit a rich phase diagram. For topological models, the edge Hamiltonian is constrained by the topological order in the bulk, which gives rise to one-dimensional edge models with unconventional properties; for instance, a topologically ordered bulk can protect a ferromagnetic Ising chain at the edge against spontaneous symmetry breaking.

  5. 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.

  6. Schematic model for nuclear molecules as doorway states for fusion

    SciTech Connect

    Hess, P.O. ); Pereyra, P. )

    1990-10-01

    An elementary simple model for nuclear molecules is used to describe the molecular spectrum of the {sup 12}C-{sup 12}C system. Through that model the molecular potential is determined. Without further parameters the total fusion cross section around and below the barrier is calculated with good results indicating a correlation between the molecular spectrum and fusion. It is concluded that nuclear molecules may possibly be the doorway states for fusion. The simplicity of the model used allows a deeper schematic insight of the mechanism of fusion.

  7. Quasi-stationary states in nonlocal stochastic growth models with infinitely many absorbing states

    NASA Astrophysics Data System (ADS)

    Jara, D. A. C.; Alcaraz, F. C.

    2017-04-01

    We study a two parameter (u, p) extension of the conformally invariant raise and peel model. The model also represents a nonlocal and biased-asymmetric exclusion process with local and nonlocal jumps of excluded volume particles in the lattice. The model exhibits an unusual and interesting critical phase where, in the bulk limit, there are an infinite number of absorbing states. In spite of these absorbing states the system stays, during a time that increases exponentially with the lattice size, in a critical quasi-stationary state. In this critical phase the critical exponents depend only on one of the parameters defining the model (u). The endpoint of this critical phase, where the system changes from an active to an inactive frozen phase, belongs to a distinct universality class. This new behavior, we believe, is due to the appearance of Jordan cells in the Hamiltonian describing the time evolution. The dimensions of these cells increase with the lattice size. In a special case (u  =  0) where the model has no adsorptions we are able to calculate analytically the time evolution of some observables. A polynomial time dependence is obtained thanks to the appearance of Jordan cells structures in the Hamiltonian.

  8. 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.

  9. 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.

  10. ASPEN modeling of the Tri-State indirect liquefaction process

    SciTech Connect

    Begovich, J.M.; Clinton, J.H.; Johnson, P.J.; Barker, R.E.

    1983-01-01

    The ASPEN process simulator has been used to model an indirect liquefaction flowsheet patterned after that of the Tri-State project. This flowsheet uses Lurgi moving-bed gasification with synthesis gas conversion to methanol followed by further processing to gasoline using the Mobil MTG process. Models developed in this study include the following: Lurgi gasifier, Texaco gasifier, synthesis gas cooling, Rectisol, methanol synthesis, methanol-to-gasoline, CO-shift, methanation, and naphtha hydrotreating. These models have been successfully developed in modular form so that they can be used to simulate a number of different flowsheets or process alternatives. Simulations of the Tri-State flowsheet have been made using two different coal feed rates and two types of feed coal. The overall simulation model was adjusted to match the Tri-State flowsheet values for methanol, LPG, isobutane, and gasoline. As a result of this adjustment, the MTG reactor yield structure necessary to match the flowsheet product rates was determined. The models were exercised at different flow rates and were unaffected by such changes, demonstrating their range of operability. The use of Illinois No. 6 coal, with its lower ash content, resulted in slightly higher production rates for each of the products as compared to use of the Kentucky coal.

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

    PubMed

    MacKenzie, Darryl I; Nichols, James D; Seamans, Mark E; Gutiérrez, R J

    2009-03-01

    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.

  12. Condensed ground states of frustrated Bose-Hubbard models

    SciTech Connect

    Moeller, G.; Cooper, N. R.

    2010-12-15

    We study theoretically the ground states of two-dimensional Bose-Hubbard models which are frustrated by gauge fields. Motivated by recent proposals for the implementation of optically induced gauge potentials, we focus on the situation in which the imposed gauge fields give rise to a pattern of staggered fluxes of magnitude {alpha} and alternating in sign along one of the principal axes. For {alpha}=1/2 this model is equivalent to the case of uniform flux per plaquette n{sub {phi}=}1/2, which, in the hard-core limit, realizes the 'fully frustrated' spin-1/2 XY model. We show that the mean-field ground states of this frustrated Bose-Hubbard model typically break translational symmetry. Given the presence of both a non-zero superfluid fraction and translational symmetry breaking, these phases are supersolid. We introduce a general numerical technique to detect broken symmetry condensates in exact diagonalization studies. Using this technique we show that, for all cases studied, the ground state of the Bose-Hubbard model with staggered flux {alpha} is condensed, and we obtain quantitative determinations of the condensate fraction. We discuss the experimental consequences of our results. In particular, we explain the meaning of gauge invariance in ultracold-atom systems subject to optically induced gauge potentials and show how the ability to imprint phase patterns prior to expansion can allow very useful additional information to be extracted from expansion images.

  13. Internal Composite Bound States in Deterministic Reaction Diffusion Models

    NASA Astrophysics Data System (ADS)

    Cooper, Fred; Ghoshal, Gourab; Pawling, Alec; Pérez-Mercader, Juan

    2013-07-01

    By identifying potential composite states that occur in the Sel’kov-Gray-Scott (GS) model, we show that it can be considered as an effective theory at large spatiotemporal scales, arising from a more fundamental theory (which treats these composite states as fundamental chemical species obeying the diffusion equation) relevant at shorter spatiotemporal scales. When simulations in the latter model are performed as a function of a parameter M=λ-1, the generated spatial patterns evolve at late times into those of the GS model at large M, implying that the composites follow their own unique dynamics at short scales. This separation of scales is an example of dynamical decoupling in reaction diffusion systems.

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

    PubMed

    Owerre, S A

    2016-11-02

    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.

  15. 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

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

    NASA Astrophysics Data System (ADS)

    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.

  17. 3-state Hamiltonians associated to solvable 33-vertex models

    NASA Astrophysics Data System (ADS)

    Crampé, N.; Frappat, L.; Ragoucy, E.; Vanicat, M.

    2016-09-01

    Using the nested coordinate Bethe ansatz, we study 3-state Hamiltonians with 33 non-vanishing entries, or 33-vertex models, where only one global charge with degenerate eigenvalues exists and each site possesses three internal degrees of freedom. In the context of Markovian processes, they correspond to diffusing particles with two possible internal states which may be exchanged during the diffusion (transmutation). The first step of the nested coordinate Bethe ansatz is performed providing the eigenvalues in terms of rapidities. We give the constraints ensuring the consistency of the computations. These rapidities also satisfy Bethe equations involving 4 × 4 R-matrices, solutions of the Yang-Baxter equation which implies new constraints on the models. We solve them allowing us to list all the solvable 33-vertex models.

  18. Inequivalent models of irreversible dimer filling: ``Transition state'' dependence

    NASA Astrophysics Data System (ADS)

    Nord, R. S.; Evans, J. W.

    1990-12-01

    Irreversible adsorption of diatomics on crystalline surfaces is sometimes modeled as random dimer filling of adjacent pairs of sites on a lattice. We note that this process can be implemented in two distinct ways: (i) randomly pick adjacent pairs of sites, jj', and fill jj' only if both are empty (horizontal transition state); or (ii) randomly pick a single site, j, and if j and at least one neighbor are empty, then fill j and a randomly chosen empty neighbor (vertical transition state). Here it is instructive to consider processes which also include competitive random monomer filling of single sites. We find that although saturation (partial) coverages differ little between the models for pure dimer filling, there is a significant difference for comparable monomer and dimer filling rates. We present exact results for saturation coverage behavior for a linear lattice, and estimates for a square lattice. Ramifications for simple models of CO oxidation on surfaces are indicated.

  19. 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.

  20. State Space Identification of Linear Deterministic Rainfall-Runoff Models

    NASA Astrophysics Data System (ADS)

    Ramos, José; Mallants, Dirk; Feyen, Jan

    1995-06-01

    Rainfall-runoff models of the black box type abound in the water resources literature (i.e., transfer function, autoregressive moving average (ARMA), ARMAX, state space, etc.). The corresponding system identification algorithms for such models are known to be numerically efficient and accurate, leading in most cases to good parsimonious representations of the rainfall-runoff process. Alternatively, every model in transfer function, ARMA, and ARMAX form has an equivalent state space representation. However, state space models do not necessarily have simple system identification algorithms, unless the system matrices are restricted to some canonical form. Furthermore, state space system identification algorithms that work with the rainfall/runoff data directly (i.e., covariance free), require initial conditions and are inherently iterative and nonlinear. In this paper we present a state space system identification theory which overcomes these limitations. One advantage of such a theory is that the corresponding algorithms are highly robust to additive noise in the data. They are referred to as "subspace algorithms" due to their ability to separate the signal subspace from the noise subspace. The main advantages of the subspace algorithms are the automatic structure identification (system order), geometrical insights (notions of angle between subspaces), and the fact that they rely on robust numerical procedures (singular value decomposition). In this paper, two algorithms are presented. The first one is a two-step procedure, where the impulse response (unit hydrograph ordinates for the single-input, single-output case) are computed from the input/output data by solving a constrained deconvolution problem. These impulse response ordinates are then used as inputs for identifying the system matrices by means of a Hankel-based realization algorithm. The second approach uses the data directly to identify the system matrices, bypassing the deconvolution step. The

  1. On the applicability of simplified state-to-state models of transport coefficients

    NASA Astrophysics Data System (ADS)

    Kustova, E.; Mekhonoshina, M.; Oblapenko, G.

    2017-10-01

    Thermal conductivity and bulk viscosity coefficients are studied in the state-to-state approximation to assess the importance of accounting for rovibrational coupling and increasing diameters of vibrationally excited molecules. Transport coefficients are computed in binary mixtures for a wide temperature range, and compared to those obtained for the rigid rotator model. It is shown that accounting for rovibrational coupling leads to a twofold decrease in the bulk viscosity coefficient and a 5-7% decrease in the thermal conductivity coefficient; accounting for variable diameters has no effect on the bulk viscosity, but leads to a larger decrease in the thermal conductivity.

  2. Natural State Models of the Geysers Geothermal System

    NASA Astrophysics Data System (ADS)

    Brikowski, T.; Norton, D.; Blackwell, D.

    2001-12-01

    Summarized in the following report are the results obtained in a project focused on natural state (pre-production) modeling of The Geysers geothermal system. The project was motivated by a need to better-understand the origin, current state, and future scenarios for The Geysers to allow better management of this unique energy resource. During the three-year course of the project nine reviewed papers were published, and six oral presentations made to communicate these results to the industrial and academic geothermal communities. Preprints of the papers are attached as appendices, and form the bulk of the material in this report.

  3. Clinical states model for biomarkers in bladder cancer

    PubMed Central

    Apolo, Andrea B; Milowsky, Matthew; Bajorin, Dean F.

    2013-01-01

    Bladder cancer is a significant health care problem in the United States, with a high recurrence rate, the need for expensive continuous surveillance, and limited treatment options for patients with advanced disease. Research has contributed to an understanding of the molecular pathways involved in the development and progression of bladder cancer, and that understanding has led to the discovery of potentially diagnostic, predictive, and prognostic biomarkers. In this review, a clinical states model of bladder cancer is introduced and integrated into a paradigm for biomarker development. Biomarkers are systematically incorporated with predefined endpoints to aid in clinical management. PMID:19792967

  4. 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.

  5. Ground states of the SU(N) Heisenberg model.

    PubMed

    Kawashima, Naoki; Tanabe, Yuta

    2007-02-02

    The SU(N) Heisenberg model with various single-row representations is investigated by quantum Monte Carlo simulations. While the zero-temperature phase boundary agrees qualitatively with the theoretical predictions based on the 1/N expansion, some unexpected features are also observed. For N> or =5 with the fundamental representation, for example, it is suggested that the ground states possess exact or approximate U(1) degeneracy. In addition, for the representation of Young tableau with more than one column, the ground state shows no valence-bond-solid order even at N greater than the threshold value.

  6. 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.

  7. Modeling the Dynamics of Disease States in Depression

    PubMed Central

    Demic, Selver; Cheng, Sen

    2014-01-01

    Major depressive disorder (MDD) is a common and costly disorder associated with considerable morbidity, disability, and risk for suicide. The disorder is clinically and etiologically heterogeneous. Despite intense research efforts, the response rates of antidepressant treatments are relatively low and the etiology and progression of MDD remain poorly understood. Here we use computational modeling to advance our understanding of MDD. First, we propose a systematic and comprehensive definition of disease states, which is based on a type of mathematical model called a finite-state machine. Second, we propose a dynamical systems model for the progression, or dynamics, of MDD. The model is abstract and combines several major factors (mechanisms) that influence the dynamics of MDD. We study under what conditions the model can account for the occurrence and recurrence of depressive episodes and how we can model the effects of antidepressant treatments and cognitive behavioral therapy within the same dynamical systems model through changing a small subset of parameters. Our computational modeling suggests several predictions about MDD. Patients who suffer from depression can be divided into two sub-populations: a high-risk sub-population that has a high risk of developing chronic depression and a low-risk sub-population, in which patients develop depression stochastically with low probability. The success of antidepressant treatment is stochastic, leading to widely different times-to-remission in otherwise identical patients. While the specific details of our model might be subjected to criticism and revisions, our approach shows the potential power of computationally modeling depression and the need for different type of quantitative data for understanding depression. PMID:25330102

  8. Cavitation modeling for steady-state CFD simulations

    NASA Astrophysics Data System (ADS)

    Hanimann, L.; Mangani, L.; Casartelli, E.; Widmer, M.

    2016-11-01

    Cavitation in hydraulic turbomachines is an important phenomenon to be considered for performance predictions. Correct analysis of the cavitation onset and its effect on the flow field while diminishing the pressure level need therefore to be investigated. Even if cavitation often appears as an unsteady phenomenon, the capability to compute it in a steady state formulation for the design and assessment phase in the product development process is very useful for the engineer. In the present paper the development and corresponding application of a steady state CFD solver is presented, based on the open source toolbox OpenFOAM®. In the first part a review of different cavitation models is presented. Adopting the mixture-type cavitation approach, various models are investigated and developed in a steady state CFD RANS solver. Particular attention is given to the coupling between cavitation and turbulence models as well as on the underlying numerical procedure, especially the integration in the pressure- correction step of pressure-based solvers, which plays an important role in the stability of the procedure. The performance of the proposed model is initially assessed on simple cases available in the open literature. In a second step results for different applications are presented, ranging from airfoils to pumps.

  9. A Bayesian model for estimating multi-state disease progression

    PubMed Central

    Shen, Shiwen; Han, Simon X.; Petousis, Panayiotis; Weiss, Robert E.; Meng, Frank; Bui, Alex A.T.; Hsu, William

    2017-01-01

    A growing number of individuals who are considered at high risk of cancer are now routinely undergoing population screening. However, noted harms such as radiation exposure, overdiagnosis, and overtreatment underscore the need for better temporal models that predict who should be screened and at what frequency. The mean sojourn time (MST), an average duration period when a tumor can be detected by imaging but with no observable clinical symptoms, is a critical variable for formulating screening policy. Estimation of MST has been long studied using continuous Markov model (CMM) with Maximum likelihood estimation (MLE). However, a lot of traditional methods assume no observation error of the imaging data, which is unlikely and can bias the estimation of the MST. In addition, the MLE may not be stably estimated when data is sparse. Addressing these shortcomings, we present a probabilistic modeling approach for periodic cancer screening data. We first model the cancer state transition using a three state CMM model, while simultaneously considering observation error. We then jointly estimate the MST and observation error within a Bayesian framework. We also consider the inclusion of covariates to estimate individualized rates of disease progression. Our approach is demonstrated on participants who underwent chest x-ray screening in the National Lung Screening Trial (NLST) and validated using posterior predictive p-values and Pearson’s chi-square test. Our model demonstrates more accurate and sensible estimates of MST in comparison to MLE. PMID:28038345

  10. A Bayesian model for estimating multi-state disease progression.

    PubMed

    Shen, Shiwen; Han, Simon X; Petousis, Panayiotis; Weiss, Robert E; Meng, Frank; Bui, Alex A T; Hsu, William

    2017-02-01

    A growing number of individuals who are considered at high risk of cancer are now routinely undergoing population screening. However, noted harms such as radiation exposure, overdiagnosis, and overtreatment underscore the need for better temporal models that predict who should be screened and at what frequency. The mean sojourn time (MST), an average duration period when a tumor can be detected by imaging but with no observable clinical symptoms, is a critical variable for formulating screening policy. Estimation of MST has been long studied using continuous Markov model (CMM) with Maximum likelihood estimation (MLE). However, a lot of traditional methods assume no observation error of the imaging data, which is unlikely and can bias the estimation of the MST. In addition, the MLE may not be stably estimated when data is sparse. Addressing these shortcomings, we present a probabilistic modeling approach for periodic cancer screening data. We first model the cancer state transition using a three state CMM model, while simultaneously considering observation error. We then jointly estimate the MST and observation error within a Bayesian framework. We also consider the inclusion of covariates to estimate individualized rates of disease progression. Our approach is demonstrated on participants who underwent chest x-ray screening in the National Lung Screening Trial (NLST) and validated using posterior predictive p-values and Pearson's chi-square test. Our model demonstrates more accurate and sensible estimates of MST in comparison to MLE. Copyright © 2016 Elsevier Ltd. All rights reserved.

  11. Modeling GPCR active state conformations: the β(2)-adrenergic receptor.

    PubMed

    Simpson, Lisa M; Wall, Ian D; Blaney, Frank E; Reynolds, Christopher A

    2011-05-01

    The recent publication of several G protein-coupled receptor (GPCR) structures has increased the information available for homology modeling inactive class A GPCRs. Moreover, the opsin crystal structure shows some active features. We have therefore combined information from these two sources to generate an extensively validated model of the active conformation of the β(2)-adrenergic receptor. Experimental information on fully active GPCRs from zinc binding studies, site-directed spin labeling, and other spectroscopic techniques has been used in molecular dynamics simulations. The observed conformational changes reside mainly in transmembrane helix 6 (TM6), with additional small but significant changes in TM5 and TM7. The active model has been validated by manual docking and is in agreement with a large amount of experimental work, including site-directed mutagenesis information. Virtual screening experiments show that the models are selective for β-adrenergic agonists over other GPCR ligands, for (R)- over (S)-β-hydroxy agonists and for β(2)-selective agonists over β(1)-selective agonists. The virtual screens reproduce interactions similar to those generated by manual docking. The C-terminal peptide from a model of the stimulatory G protein, readily docks into the active model in a similar manner to which the C-terminal peptide from transducin, docks into opsin, as shown in a recent opsin crystal structure. This GPCR-G protein model has been used to explain site-directed mutagenesis data on activation. The agreement with experiment suggests a robust model of an active state of the β(2)-adrenergic receptor has been produced. The methodology used here should be transferable to modeling the active state of other GPCRs. Copyright © 2011 Wiley-Liss, Inc.

  12. Predicting the Kinetics of RNA Oligonucleotides Using Markov State Models.

    PubMed

    Pinamonti, Giovanni; Zhao, Jianbo; Condon, David E; Paul, Fabian; Noè, Frank; Turner, Douglas H; Bussi, Giovanni

    2017-02-14

    Nowadays different experimental techniques, such as single molecule or relaxation experiments, can provide dynamic properties of biomolecular systems, but the amount of detail obtainable with these methods is often limited in terms of time or spatial resolution. Here we use state-of-the-art computational techniques, namely, atomistic molecular dynamics and Markov state models, to provide insight into the rapid dynamics of short RNA oligonucleotides, to elucidate the kinetics of stacking interactions. Analysis of multiple microsecond-long simulations indicates that the main relaxation modes of such molecules can consist of transitions between alternative folded states, rather than between random coils and native structures. After properly removing structures that are artificially stabilized by known inaccuracies of the current RNA AMBER force field, the kinetic properties predicted are consistent with the time scales of previously reported relaxation experiments.

  13. 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

  14. 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

  15. Ground State Energy of the Low Density Hubbard Model

    NASA Astrophysics Data System (ADS)

    Seiringer, Robert; Yin, Jun

    2008-06-01

    We derive a lower bound on the ground state energy of the Hubbard model for given value of the total spin. In combination with the upper bound derived previously by Giuliani (J. Math. Phys. 48:023302, [2007]), our result proves that in the low density limit the leading order correction compared to the ground state energy of a non-interacting lattice Fermi gas is given by 8 π a ϱ u ϱ d , where ϱ u( d) denotes the density of the spin-up (down) particles, and a is the scattering length of the contact interaction potential. This result extends previous work on the corresponding continuum model to the lattice case.

  16. Transient and steady state modelling of a coupled WECS

    NASA Astrophysics Data System (ADS)

    Nathan, G. K.; Tan, J. K.

    The paper presents a method for simulation of a wind turbine using a dc motor. The armature and field voltages of the dc motor are independently regulated to obtain torque-speed characteristics which correspond to those of a wind turbine at different wind speeds. The mass moment of inertia of the wind turbine is represented by adding a rotating mass to a parallel shaft which is positively coupled to the motor shaft. To verify the method of simulation, an American multiblade wind turbine is chosen, loaded by coupling to a centrifugal pump. Using the principle of conservation of energy and characteristics of both constituent units, two mathematical models are proposed: one for steady state operation and another for the transient state. The close comparison between the theoretical and the experimental results validates the proposed models and the method of simulation. The experimental method is described and the results of the experimental and theoretical investigation are presented.

  17. Latent State-Space Models for Neural Decoding

    PubMed Central

    Truccolo, Wilson

    2014-01-01

    Ensembles of single-neurons in motor cortex can show strong low-dimensional collective dynamics. In this study, we explore an approach where neural decoding is applied to estimated low-dimensional dynamics instead of to the full recorded neuronal population. A latent state-space model (SSM) approach is used to estimate the low-dimensional neural dynamics from the measured spiking activity in population of neurons. A second state-space model representation is then used to decode, via a Kalman filter, from the estimated low-dimensional dynamics. The latent SSM-based decoding approach is illustrated on neuronal activity recorded from primary motor cortex in a monkey performing naturalistic 3-D reach and grasp movements. Our analysis show that 3-D reach decoding performance based on estimated low-dimensional dynamics is comparable to the decoding performance based on the full recorded neuronal population. PMID:25570630

  18. Latent state-space models for neural decoding.

    PubMed

    Aghagolzadeh, Mehdi; Truccolo, Wilson

    2014-01-01

    Ensembles of single-neurons in motor cortex can show strong low-dimensional collective dynamics. In this study, we explore an approach where neural decoding is applied to estimated low-dimensional dynamics instead of to the full recorded neuronal population. A latent state-space model (SSM) approach is used to estimate the low-dimensional neural dynamics from the measured spiking activity in population of neurons. A second state-space model representation is then used to decode kinematics, via a Kalman filter, from the estimated low-dimensional dynamics. The latent SSM-based decoding approach is illustrated on neuronal activity recorded from primary motor cortex in a monkey performing naturalistic 3-D reach and grasp movements. Our analysis show that 3-D reach decoding performance based on estimated low-dimensional dynamics is comparable to the decoding performance based on the full recorded neuronal population.

  19. Approximating the XY model on a random graph with a q -state clock model

    NASA Astrophysics Data System (ADS)

    Lupo, Cosimo; Ricci-Tersenghi, Federico

    2017-02-01

    Numerical simulations of spin glass models with continuous variables set the problem of a reliable but efficient discretization of such variables. In particular, the main question is how fast physical observables computed in the discretized model converge toward the ones of the continuous model when the number of states of the discretized model increases. We answer this question for the XY model and its discretization, the q -state clock model, in the mean-field setting provided by random graphs. It is found that the convergence of physical observables is exponentially fast in the number q of states of the clock model, so allowing a very reliable approximation of the XY model by using a rather small number of states. Furthermore, such an exponential convergence is found to be independent from the disorder distribution used. Only at T =0 , the convergence is slightly slower (stretched exponential). Thanks to the analytical solution to the q -state clock model, we compute accurate phase diagrams in the temperature versus disorder strength plane. We find that, at zero temperature, spontaneous replica symmetry breaking takes place for any amount of disorder, even an infinitesimal one. We also study the one step of replica symmetry breaking (1RSB) solution in the low-temperature spin glass phase.

  20. A continuous switching model for piezoelectric state switching methods

    NASA Astrophysics Data System (ADS)

    Lopp, Garrett K.; Kauffman, Jeffrey L.

    2017-04-01

    Piezoelectric-based, semi-active vibration reduction approaches have been studied for over a decade due to their potential in controlling vibration over a large frequency range. Previous studies have relied on a discrete model when switching between the stiffness states of the system. In such a modeling approach, the energy dissipation of the stored potential energy and the transient dynamics, in general, are not well understood. In this paper, a switching model is presented using a variable capacitance in the attached shunt circuit. When the switch duration is small in comparison to the period of vibration, the vibration reduction performance approaches that of the discrete model with an instantaneous switch, whereas longer switch durations lead to less vibration reduction. An energy analysis is then performed that results in the appearance of an energy dissipation term due to the varying capacitance in the shunt circuit.

  1. Equation-of-state modeling of mixtures with ionic liquids.

    PubMed

    Tsioptsias, Costas; Tsivintzelis, Ioannis; Panayiotou, Costas

    2010-05-14

    A non-electrolyte equation-of-state model was used to describe the phase behavior of binary systems containing alkyl-methyimidazolium bis(trifluoromethyl-sulfonyl)imide ionic liquids. A methodology is suggested for modeling this phase behavior by using the Non-Random Hydrogen-Bonding (NRHB) model. According to this methodology, the scaling constants of the ionic liquid are calculated using limited available experimental data on liquid densities and Hansen's solubility parameters, while all electrostatic interactions (polar, hydrogen bonding and ionic) are treated as strong specific interactions. Using the aforementioned methodology, the model is applied to describe the vapor-liquid and the liquid-liquid equilibria in mixtures of ionic liquids with various polar or quadrupolar solvents at low and high pressures. In all cases, one temperature-independent binary interaction parameter was used. Accurate correlations were obtained for the majority of the systems, both, for vapor-liquid and liquid-liquid equilibria.

  2. Multivariate Markovian modeling of tuberculosis: forecast for the United States.

    PubMed Central

    Debanne, S. M.; Bielefeld, R. A.; Cauthen, G. M.; Daniel, T. M.; Rowland, D. Y.

    2000-01-01

    We have developed a computer-implemented, multivariate Markov chain model to project tuberculosis (TB) incidence in the United States from 1980 to 2010 in disaggregated demographic groups. Uncertainty in model parameters and in the projections is represented by fuzzy numbers. Projections are made under the assumption that current TB control measures will remain unchanged for the projection period. The projections of the model demonstrate an intermediate increase in national TB incidence (similar to that which actually occurred) followed by continuing decline. The rate of decline depends strongly on geographic, racial, and ethnic characteristics. The model predicts that the rate of decline in the number of cases among Hispanics will be slower than among white non-Hispanics and black non-Hispanics a prediction supported by the most recent data. PMID:10756148

  3. Spatial Bayesian hierarchical modelling of extreme sea states

    NASA Astrophysics Data System (ADS)

    Clancy, Colm; O'Sullivan, John; Sweeney, Conor; Dias, Frédéric; Parnell, Andrew C.

    2016-11-01

    A Bayesian hierarchical framework is used to model extreme sea states, incorporating a latent spatial process to more effectively capture the spatial variation of the extremes. The model is applied to a 34-year hindcast of significant wave height off the west coast of Ireland. The generalised Pareto distribution is fitted to declustered peaks over a threshold given by the 99.8th percentile of the data. Return levels of significant wave height are computed and compared against those from a model based on the commonly-used maximum likelihood inference method. The Bayesian spatial model produces smoother maps of return levels. Furthermore, this approach greatly reduces the uncertainty in the estimates, thus providing information on extremes which is more useful for practical applications.

  4. Self-Organizing Neural Network Models for State Anticipatory Systems

    NASA Astrophysics Data System (ADS)

    Pöllä, Matti; Honkela, Timo

    2006-06-01

    A vital mechanism of high-level natural cognitive systems is the anticipatory capability of making decisions based on predicted events in the future. While in some cases the performance of computational cognitive systems can be improved by modeling anticipatory behavior, it has been shown that for many cognitive tasks anticipation is mandatory. In this paper, we review the use of self-organizing artificial neural networks in constructing the state-space model of an anticipatory system. The biologically inspired self-organizing map (SOM) and its topologically dynamic variants such as the growing neural gas (GNG) are discussed using illustrative examples of their performance.

  5. Quark-model identification of baryon ground and resonant states

    SciTech Connect

    Melde, T.; Plessas, W.; Sengl, B.

    2008-06-01

    We present a new classification scheme of baryon ground states and resonances into SU(3) flavor multiplets. The scheme is worked out along a covariant formalism with relativistic constituent quark models and it relies on detailed investigations of the baryon spectra, the spin-flavor structure of the baryon eigenstates, the behavior of their probability density distributions as well as covariant predictions for mesonic decay widths. The results are found to be quite independent of the specific types of relativistic constituent quark models employed. It turns out that a consistent classification requires one to include also resonances that are presently reported from experiments with only two-star status.

  6. Compact stellar models obeying quadratic equation of state

    NASA Astrophysics Data System (ADS)

    Bhar, Piyali; Singh, Ksh. Newton; Pant, Neeraj

    2016-10-01

    In present paper we obtain a new model of compact star by considering quadratic equation of state for the matter distribution and assuming a physically reasonable choice for metric coefficient g_{rr}. The solution is singularity free and well behaved inside the stellar interior. Several features are described analytically as well as graphically. From our analysis we have shown that our model is compatible with the observational data of the compact stars. We have discussed a detail analysis of neutron star PSR J1614-2230 via different graphs after determining all the constant parameters from boundary conditions.

  7. 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.

  8. Symbolic Model Checking: An Approach to the State Explosion Problem

    DTIC Science & Technology

    1992-05-01

    checking, state explosion problem, symbolic model checking, binary decision dia- grams . cache consistency, cache coherence, protocol verification...similar to. and in other ways different from the problem of proving correctness of pro- grams . Digital systems are most similar to what Pnueli has charac...Temporal logic is powerful enough to define a semantics for pro- grams which captures not only the traditional before and after con- ditions of Floyd

  9. Ground state nonuniversality in the random-field Ising model

    SciTech Connect

    Duxbury, P. M.; Meinke, J. H.

    2001-09-01

    Two attractive and often used ideas, namely, universality and the concept of a zero-temperature fixed point, are violated in the infinite-range random-field Ising model. In the ground state we show that the exponents can depend continuously on the disorder and so are nonuniversal. However, we also show that at finite temperature the thermal order-parameter exponent 1/2 is restored so that temperature is a relevant variable. Broader implications of these results are discussed.

  10. Modeling Conflict between China and the United States

    DTIC Science & Technology

    2012-12-01

    States Army B.A., Saint Bonaventure University, 1997 M.A., University of Oklahoma , 2005 Submitted in partial fulfillment of the requirements for...based on stable territorial sovereignty and a large population. This leads to significant increases in national power for the challenger. As the...game is built from solid empirical evidence so as the strength and validity of the model increases, its analysis might lead to justifiable policy

  11. 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

  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 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.

  14. 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.

  15. State-space based modeling for imaging system identification

    NASA Astrophysics Data System (ADS)

    Kaur, Balvinder; Hixson, Jonathan G.

    2017-05-01

    State-space (SS) based modeling for imaging electro-optical (EO) systems representing various states facilitates a method for system estimation. Traditionally linear shift-invariant (LSI) systems are modeled using Fourier analysis (FA). However, models based on FA may not have a clear insight too the instability reasons, whereas SS based models with system poles and zeros have a clear insight to the system stability information. In this paper, we introduce three methods to estimate system parameters for LSI EO imaging systems using SS based modeling. These methods include batch processing version of least squares (LS) estimation, recursive version of LS estimation, and sliding window LS estimation. The accuracy of the developed methods was tested using input and output signals of simulated LSI systems. First, LSI systems with various system parameters (poles and zeros) were simulated, which were then used to generate output signals for a set of random input signals, with each input signal value representing the average of an image. Then, these input and output signals were used to estimate systems employing SS and FA based modeling. Further, the estimated systems were used to generate output signals for a new set of input signals. For any given input signal, output signals generated by both systems were compared for similarities and signal-to-noise ratio (SNR). Results show that SS based models generate output signals that have higher SNR values. In addition, developed methods were tested against the simulated data and results show promise for development of models for estimating more complicated systems (e.g., non-linear system).

  16. State-to-state modeling of non equilibrium low-temperature atomic plasmas

    NASA Astrophysics Data System (ADS)

    Bultel, Arnaud; Morel, Vincent; Annaloro, Julien; Druguet, Marie-Claude

    2017-03-01

    The most relevant approach leading to a thorough understanding of the behavior of non equilibrium atomic plasmas is to elaborate state-to-state models in which the mass conservation equation is applied directly to atoms or ions on their excited states. The present communication reports the elaboration of such models and the results obtained. Two situations close to each other are considered. First, the plasmas produced behind shock fronts obtained in ground test facilities (shock tubes) or during planetary atmospheric entries of spacecrafts are discussed. We focused our attention on the nitrogen case for which a complete implementation of the CoRaM-N2 collisional-radiative model has been performed in a steady one-dimensional computation code based on the Rankine-Hugoniot assumptions. Second, the plasmas produced by the interaction between an ultra short laser pulse and a tungsten sample are discussed in the framework of the elaboration of the Laser-Induced Breakdown Spectroscopy (LIBS) technique. In the present case, tungsten has been chosen in the purpose of validating an in situ experimental method able to provide the elemental composition of the divertor wall of a tokamak like WEST or ITER undergoing high energetic deuterium and tritium nuclei fluxes.

  17. A National Study of the Current Status of State School Counseling Models

    ERIC Educational Resources Information Center

    Martin, Ian; Carey, John; DeCoster, Karen

    2009-01-01

    A national survey was conducted using a structured interview to investigate the status of school counseling models in all 50 states and the District of Columbia. Findings determined that 17 states have established models, 24 states are progressing in model implementation, and 10 states are at a beginning stage of model development. Implications…

  18. The 2014 United States National Seismic Hazard Model

    USGS Publications Warehouse

    Petersen, Mark D.; Moschetti, Morgan P.; Powers, Peter; Mueller, Charles; Haller, Kathleen; Frankel, Arthur; Zeng, Yuehua; Rezaeian, Sanaz; Harmsen, Stephen; Boyd, Oliver; Field, Ned; Chen, Rui; Rukstales, Kenneth S.; Luco, Nicolas; Wheeler, Russell; Williams, Robert; Olsen, Anna H.

    2015-01-01

    New seismic hazard maps have been developed for the conterminous United States using the latest data, models, and methods available for assessing earthquake hazard. The hazard models incorporate new information on earthquake rupture behavior observed in recent earthquakes; fault studies that use both geologic and geodetic strain rate data; earthquake catalogs through 2012 that include new assessments of locations and magnitudes; earthquake adaptive smoothing models that more fully account for the spatial clustering of earthquakes; and 22 ground motion models, some of which consider more than double the shaking data applied previously. Alternative input models account for larger earthquakes, more complicated ruptures, and more varied ground shaking estimates than assumed in earlier models. The ground motions, for levels applied in building codes, differ from the previous version by less than ±10% over 60% of the country, but can differ by ±50% in localized areas. The models are incorporated in insurance rates, risk assessments, and as input into the U.S. building code provisions for earthquake ground shaking.

  19. 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.

  20. 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.

  1. Orbitally Excited States of Quarkonia in a Nonrelativistic Model

    NASA Astrophysics Data System (ADS)

    Bhaghyesh; Vijaya Kumar, K. B.; Ma, Yong-Liang

    Having succeeded in predicting the S wave spectra and decays of cbar {c} and bbar {b} mesons, Bhaghyesh, K. B. Vijaya Kumar and A. P. Monteiro, J. Phys. G: Nucl. Part. Phys. 38, 085001 (2011), in this article, we apply our nonrelativistic quark model to calculate the spectra and decays of the orbitally excited states (P- and D-waves) of heavy quarkonia. The full Qbar {Q} potential used in our model consists of a Hulthen potential and a confining linear potential. The spin hyperfine, spin-orbit and tensor interactions are introduced to obtain the masses of the P- and D-wave states. The three-dimensional harmonic oscillator wave function is employed as a trial wave function to obtain the mass spectra. The model parameters and the wave function that reproduce the mass spectra of cbar {c} and bbar {b} mesons are used to investigate their decay properties. The two-photon decay widths, two-gluon decay widths and E1 radiative decay widths are calculated. The obtained values are compared with the experimental results and those obtained from other theoretical models.

  2. Steady state analysis of Boolean molecular network models via model reduction and computational algebra

    PubMed Central

    2014-01-01

    Background A key problem in the analysis of mathematical models of molecular networks is the determination of their steady states. The present paper addresses this problem for Boolean network models, an increasingly popular modeling paradigm for networks lacking detailed kinetic information. For small models, the problem can be solved by exhaustive enumeration of all state transitions. But for larger models this is not feasible, since the size of the phase space grows exponentially with the dimension of the network. The dimension of published models is growing to over 100, so that efficient methods for steady state determination are essential. Several methods have been proposed for large networks, some of them heuristic. While these methods represent a substantial improvement in scalability over exhaustive enumeration, the problem for large networks is still unsolved in general. Results This paper presents an algorithm that consists of two main parts. The first is a graph theoretic reduction of the wiring diagram of the network, while preserving all information about steady states. The second part formulates the determination of all steady states of a Boolean network as a problem of finding all solutions to a system of polynomial equations over the finite number system with two elements. This problem can be solved with existing computer algebra software. This algorithm compares favorably with several existing algorithms for steady state determination. One advantage is that it is not heuristic or reliant on sampling, but rather determines algorithmically and exactly all steady states of a Boolean network. The code for the algorithm, as well as the test suite of benchmark networks, is available upon request from the corresponding author. Conclusions The algorithm presented in this paper reliably determines all steady states of sparse Boolean networks with up to 1000 nodes. The algorithm is effective at analyzing virtually all published models even those of moderate

  3. Steady state analysis of Boolean molecular network models via model reduction and computational algebra.

    PubMed

    Veliz-Cuba, Alan; Aguilar, Boris; Hinkelmann, Franziska; Laubenbacher, Reinhard

    2014-06-26

    A key problem in the analysis of mathematical models of molecular networks is the determination of their steady states. The present paper addresses this problem for Boolean network models, an increasingly popular modeling paradigm for networks lacking detailed kinetic information. For small models, the problem can be solved by exhaustive enumeration of all state transitions. But for larger models this is not feasible, since the size of the phase space grows exponentially with the dimension of the network. The dimension of published models is growing to over 100, so that efficient methods for steady state determination are essential. Several methods have been proposed for large networks, some of them heuristic. While these methods represent a substantial improvement in scalability over exhaustive enumeration, the problem for large networks is still unsolved in general. This paper presents an algorithm that consists of two main parts. The first is a graph theoretic reduction of the wiring diagram of the network, while preserving all information about steady states. The second part formulates the determination of all steady states of a Boolean network as a problem of finding all solutions to a system of polynomial equations over the finite number system with two elements. This problem can be solved with existing computer algebra software. This algorithm compares favorably with several existing algorithms for steady state determination. One advantage is that it is not heuristic or reliant on sampling, but rather determines algorithmically and exactly all steady states of a Boolean network. The code for the algorithm, as well as the test suite of benchmark networks, is available upon request from the corresponding author. The algorithm presented in this paper reliably determines all steady states of sparse Boolean networks with up to 1000 nodes. The algorithm is effective at analyzing virtually all published models even those of moderate connectivity. The problem for

  4. Remaining lifetime modeling using State-of-Health estimation

    NASA Astrophysics Data System (ADS)

    Beganovic, Nejra; Söffker, Dirk

    2017-08-01

    Technical systems and system's components undergo gradual degradation over time. Continuous degradation occurred in system is reflected in decreased system's reliability and unavoidably lead to a system failure. Therefore, continuous evaluation of State-of-Health (SoH) is inevitable to provide at least predefined lifetime of the system defined by manufacturer, or even better, to extend the lifetime given by manufacturer. However, precondition for lifetime extension is accurate estimation of SoH as well as the estimation and prediction of Remaining Useful Lifetime (RUL). For this purpose, lifetime models describing the relation between system/component degradation and consumed lifetime have to be established. In this contribution modeling and selection of suitable lifetime models from database based on current SoH conditions are discussed. Main contribution of this paper is the development of new modeling strategies capable to describe complex relations between measurable system variables, related system degradation, and RUL. Two approaches with accompanying advantages and disadvantages are introduced and compared. Both approaches are capable to model stochastic aging processes of a system by simultaneous adaption of RUL models to current SoH. The first approach requires a priori knowledge about aging processes in the system and accurate estimation of SoH. An estimation of SoH here is conditioned by tracking actual accumulated damage into the system, so that particular model parameters are defined according to a priori known assumptions about system's aging. Prediction accuracy in this case is highly dependent on accurate estimation of SoH but includes high number of degrees of freedom. The second approach in this contribution does not require a priori knowledge about system's aging as particular model parameters are defined in accordance to multi-objective optimization procedure. Prediction accuracy of this model does not highly depend on estimated SoH. This model

  5. 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.

  6. Two-State Model of Allostery With Force

    NASA Astrophysics Data System (ADS)

    Pereverzev, Yuriy; Prezhdo, Oleg; Sokurenko, Evgeni

    2010-03-01

    We propose an allosteric model that describes force-induced changes in lifetimes of biological receptor-ligand bonds. Transitions between the two conformations of the allosteric site with applied force lead to changes in the receptor conformation. The ligand bound to the receptor fluctuates between two different potentials formed by the two conformations. The effect of the force on the receptor-ligand interaction potential is described by the Bell mechanism. The probability of detecting the ligand in the bound state is found to depend on two relaxation times of the ligand and allosteric sites. An analytic expression for the bond lifetime is derived as a function force. The model is used to explain the anomalous force and time dependences of integrin-fibronectin bond lifetimes measured by atomic force microscopy (Kong, F. et al J. Cell Biol., 2009, 185, 1275-1284). The analytic expression and model parameters describe very well all anomalous dependences identified in the experiments.

  7. 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.

  8. 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.

  9. A microscopic model of rate and state friction evolution

    NASA Astrophysics Data System (ADS)

    Li, Tianyi; Rubin, Allan M.

    2017-08-01

    Whether rate- and state-dependent friction evolution is primarily slip dependent or time dependent is not well resolved. Although slide-hold-slide experiments are traditionally interpreted as supporting the aging law, implying time-dependent evolution, recent studies show that this evidence is equivocal. In contrast, the slip law yields extremely good fits to velocity step experiments, although a clear physical picture for slip-dependent friction evolution is lacking. We propose a new microscopic model for rate and state friction evolution in which each asperity has a heterogeneous strength, with individual portions recording the velocity at which they became part of the contact. Assuming an exponential distribution of asperity sizes on the surface, the model produces results essentially similar to the slip law, yielding very good fits to velocity step experiments but not improving much the fits to slide-hold-slide experiments. A numerical kernel for the model is developed, and an analytical expression is obtained for perfect velocity steps, which differs from the slip law expression by a slow-decaying factor. By changing the quantity that determines the intrinsic strength, we use the same model structure to investigate aging-law-like time-dependent evolution. Assuming strength to increase logarithmically with contact age, for two different definitions of age we obtain results for velocity step increases significantly different from the aging law. Interestingly, a solution very close to the aging law is obtained if we apply a third definition of age that we consider to be nonphysical. This suggests that under the current aging law, the state variable is not synonymous with contact age.

  10. 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

  11. 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.

  12. 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.

  13. Research on Turbofan Engine Model above Idle State Based on NARX Modeling Approach

    NASA Astrophysics Data System (ADS)

    Yu, Bing; Shu, Wenjun

    2017-03-01

    The nonlinear model for turbofan engine above idle state based on NARX is studied. Above all, the data sets for the JT9D engine from existing model are obtained via simulation. Then, a nonlinear modeling scheme based on NARX is proposed and several models with different parameters are built according to the former data sets. Finally, the simulations have been taken to verify the precise and dynamic performance the models, the results show that the NARX model can well reflect the dynamics characteristic of the turbofan engine with high accuracy.

  14. Nonlinear system modeling with random matrices: echo state networks revisited.

    PubMed

    Zhang, Bai; Miller, David J; Wang, Yue

    2012-01-01

    Echo state networks (ESNs) are a novel form of recurrent neural networks (RNNs) that provide an efficient and powerful computational model approximating nonlinear dynamical systems. A unique feature of an ESN is that a large number of neurons (the "reservoir") are used, whose synaptic connections are generated randomly, with only the connections from the reservoir to the output modified by learning. Why a large randomly generated fixed RNN gives such excellent performance in approximating nonlinear systems is still not well understood. In this brief, we apply random matrix theory to examine the properties of random reservoirs in ESNs under different topologies (sparse or fully connected) and connection weights (Bernoulli or Gaussian). We quantify the asymptotic gap between the scaling factor bounds for the necessary and sufficient conditions previously proposed for the echo state property. We then show that the state transition mapping is contractive with high probability when only the necessary condition is satisfied, which corroborates and thus analytically explains the observation that in practice one obtains echo states when the spectral radius of the reservoir weight matrix is smaller than 1.

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

    NASA Astrophysics Data System (ADS)

    Giuliani, Alessandro; Seiringer, Robert

    2016-11-01

    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 > 2 d 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.

  16. Modeling of shock-induced solid state chemistry

    NASA Astrophysics Data System (ADS)

    Horie, Y.; Kipp, M. E.

    1987-06-01

    This report, a sequel to Sandia Report 86-0922 entitled, Shock-Induced Solid State Chemistry: Theoretical Background, by Y. Horie, describes models of chemical reactions in inorganic powder mixtures under high pressure shock wave loading. In the present work, two mathematical models, one homogeneous and the other heterogeneous, were formulated based mostly upon existing results of observations on post-shock samples of Al-Ni, Al-Ti, and ZnO-Fe2O3 mixtures. Two basic mechanisms were isolated for the development of the initial models: (1) the creation of a nonequilibrium mixture by dynamic mass mixing, and (2) ensuing chemical reactions. The homogeneous model was evaluated under shock conditions using the one dimensional wave propagation code WONDY-V. We found that results of recent measurements can be rationalized by the model. The model also suggested requisite conditions for the thermal excursion of localized reactions: a localized initial peak temperature of 1000K to 2000K and reaction time constants of 1 microsec or less. Evidence that reactions occurred while the sample was under shock loading may also be rationalized by observations of post-shock samples.

  17. A state-based model of prevention: Indiana's example.

    PubMed

    Agley, Jon; Gassman, Ruth

    2008-04-01

    Public health officials in the United States have battled alcohol, tobacco, and other drug (ATOD) use among adolescents for the past few decades, but only in 2002 did they begin to see a decline in rates of use. ATOD use and abuse are associated with numerous problems, including criminal behavior and increased adolescent morbidity and mortality rates. Researchers have sought to identify best-practice procedures for ATOD prevention; the state of Indiana has a strong ATOD prevention system in place that has the potential to serve as a model for other U.S. localities because of its best-practice approach to public health services. This article outlines the activities of the Indiana Prevention Resource Center to provide an example to strengthen public health professionals' ability to prevent ATOD use and abuse and to provide for a healthy adolescent population.

  18. Variational study of bound states in the Higgs model

    NASA Astrophysics Data System (ADS)

    Siringo, Fabio

    2000-12-01

    The possible existence of Higgs-boson-Higgs-boson bound states in the Higgs sector of the standard model is explored using the \\|hh>+\\|hhh> variational ansatz of Di Leo and Darewych. The resulting integral equations can be decoupled exactly, yielding a one-dimensional integral equation, solved numerically. We thereby avoid the extra approximations employed by Di Leo and Darewych, and we find a qualitatively different mass renormalization. Within the conventional scenario, where a not-too-large cutoff is invoked to avoid ``triviality,'' we find, as usual, an upper bound on the Higgs boson mass. Bound-state solutions are only found in the very strong coupling regime, but at the same time a relatively small physical mass is required as a consequence of renormalization.

  19. 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.

  20. Equivalence and Differences between Structural Equation Modeling and State-Space Modeling Techniques

    ERIC Educational Resources Information Center

    Chow, Sy-Miin; Ho, Moon-ho R.; Hamaker, Ellen L.; Dolan, Conor V.

    2010-01-01

    State-space modeling techniques have been compared to structural equation modeling (SEM) techniques in various contexts but their unique strengths have often been overshadowed by their similarities to SEM. In this article, we provide a comprehensive discussion of these 2 approaches' similarities and differences through analytic comparisons and…

  1. Equivalence and Differences between Structural Equation Modeling and State-Space Modeling Techniques

    ERIC Educational Resources Information Center

    Chow, Sy-Miin; Ho, Moon-ho R.; Hamaker, Ellen L.; Dolan, Conor V.

    2010-01-01

    State-space modeling techniques have been compared to structural equation modeling (SEM) techniques in various contexts but their unique strengths have often been overshadowed by their similarities to SEM. In this article, we provide a comprehensive discussion of these 2 approaches' similarities and differences through analytic comparisons and…

  2. 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

  3. Modeling Clinical States and Metabolic Rhythms in Bioarcheology.

    PubMed

    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.

  4. New models for fast steady state magnetic reconnection

    NASA Technical Reports Server (NTRS)

    Priest, E. R.; Forbes, T. G.

    1986-01-01

    A new unified family of models for incompressible, steady-state magnetic reconnection in a finite region is presented. The models are obtained by expanding in powers of the Alfven Mach number and may be used to elucidate some of the puzzling properties of numerical experiments on reconnection which are not present in the classical models. The conditions imposed on the inflow boundary of the finite region determine which member of the family occurs. Petscheklien and Sonnerup like solutions are particular members. The Sonneruplike regime is a special case of a weak slow mode expansion in the inflow region, and it separates two classes of members with reversed currents. The Petscheklike regime is a singular case of a weak fast mode expansion, and it separates the hybrid regime from a regime of slow mode compressions. Care should be taken in deciding which type of reconnection is operating in a numerical experiment. Indeed, no experiment to date has used boundary conditions appropriate for demonstrating steady state Petschek reconnection.

  5. 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

  6. Modeling on the Steady State of Thwaites Glacier

    NASA Astrophysics Data System (ADS)

    Yu, H.; Rignot, E. J.; Morlighem, M.; Seroussi, H.

    2013-12-01

    Thwaites Glacier (TWG) is the second largest ice stream in West Antarctica in terms of ice discharge, and the broadest ice stream in Antarctica (120 km wide). Observations and theory suggest that its configuration is inherently unstable in a warming climate. Satellite observations have revealed grounding line retreat, ice thinning, ice stream broadening and in more recent years ice flow acceleration. The most important part of the glacier evolution involves its grounding line dynamics and the impact of ice-ocean interactions. In a region between the grounding line and the limit of the flexure zone, some 10 km downstream, however, the glacier is not in hydrostatic equilibrium. Proper treatment of the grounding line dynamics requires full Stokes solution. Here, we model the grounding line of TWG in 2D, full Stokes, with the goal to examine whether the glacier is in a steady state configuration or not. The model treats ice sheet and ice shelf as two fluids coupled through the ice mass flux (Nowicki, 2008). Water stress is used as a constraint on the ice shelf instead of hydrostatic equilibrium. We use radar interferometry (InSAR) measurements of ice velocity and grounding line position through time, Bedmap2 and IceBridge thickness, and surface mass balance from RACMO to constrain the model. The results are used to conclude on the state of dynamic balance of the glacier. This work is funded by NASA Cryospheric Science Program.

  7. K¯ nuclear bound states in a dynamical model

    NASA Astrophysics Data System (ADS)

    Mareš, J.; Friedman, E.; Gal, A.

    2006-05-01

    A comprehensive data base of K-atom level shifts and widths is re-analyzed in order to study the density dependence of the K¯-nuclear optical potential. Significant departure from a tρ form is found only for ρ(r)/ρ ≲ 0.2 and extrapolation to nuclear-matter density ρ yields an attractive potential, about 170 MeV deep. Partial restoration of chiral symmetry compatible with pionic atoms and low-energy pion-nuclear data plays no role at the relevant low-density regime, but this effect is not ruled out at densities of order ρ and beyond. K¯-nuclear bound states are generated across the periodic table self consistently, using a relativistic mean-field model Lagrangian which couples the K¯ to the scalar and vector meson fields mediating the nuclear interactions. The reduced phase space available for K¯ absorption from these bound states is taken into account by adding an energy-dependent imaginary term which underlies the corresponding K¯-nuclear level widths, with a strength required by fits to the atomic data. Substantial polarization of the core nucleus is found for light nuclei, and the binding energies and widths calculated in this dynamical model differ appreciably from those calculated for a static nucleus. A wide range of binding energies is spanned by varying the K¯ couplings to the meson fields. Our calculations provide a lower limit of Γ=50±10 MeV on the width of nuclear bound states for K¯-binding energy in the range B˜100-200 MeV. Comments are made on the interpretation of the FINUDA experiment at DAΦNE which claimed evidence for deeply bound Kpp states in light nuclei.

  8. 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.

  9. 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

  10. Biomedical events extraction using the hidden vector state model.

    PubMed

    Zhou, Deyu; He, Yulan

    2011-11-01

    Biomedical events extraction concerns about events describing changes on the state of bio-molecules from literature. Comparing to the protein-protein interactions (PPIs) extraction task which often only involves the extraction of binary relations between two proteins, biomedical events extraction is much harder since it needs to deal with complex events consisting of embedded or hierarchical relations among proteins, events, and their textual triggers. In this paper, we propose an information extraction system based on the hidden vector state (HVS) model, called HVS-BioEvent, for biomedical events extraction, and investigate its capability in extracting complex events. HVS has been previously employed for extracting PPIs. In HVS-BioEvent, we propose an automated way to generate abstract annotations for HVS training and further propose novel machine learning approaches for event trigger words identification, and for biomedical events extraction from the HVS parse results. Our proposed system achieves an F-score of 49.57% on the corpus used in the BioNLP'09 shared task, which is only 2.38% lower than the best performing system by UTurku in the BioNLP'09 shared task. Nevertheless, HVS-BioEvent outperforms UTurku's system on complex events extraction with 36.57% vs. 30.52% being achieved for extracting regulation events, and 40.61% vs. 38.99% for negative regulation events. The results suggest that the HVS model with the hierarchical hidden state structure is indeed more suitable for complex event extraction since it could naturally model embedded structural context in sentences. Copyright © 2011 Elsevier B.V. All rights reserved.

  11. Traffic model with an absorbing-state phase transition.

    PubMed

    Iannini, M L L; Dickman, Ronald

    2017-02-01

    We consider a modified Nagel-Schreckenberg (NS) model in which drivers do not decelerate if their speed is smaller than the headway (number of empty sites to the car ahead). (In the original NS model, such a reduction in speed occurs with probability p, independent of the headway, as long as the current speed is greater than zero.) In the modified model the free-flow state (with all vehicles traveling at the maximum speed, v_{max}) is absorbing for densities ρ smaller than a critical value ρ_{c}=1/(v_{max}+2). The phase diagram in the ρ-p plane is reentrant: for densities in the range ρ_{c,<}<ρ<ρ_{c}, both small and large values of p favor free flow, while for intermediate values, a nonzero fraction of vehicles have speeds model. Our results suggest an unexpected connection between traffic models and stochastic sandpiles.

  12. MODELING THE HARD STATES OF THREE BLACK HOLE CANDIDATES

    SciTech Connect

    Zhang Hui; Yuan Feng; Chaty, Sylvain

    2010-07-10

    Simultaneous multiwavelength observations were recently performed for three black hole candidates-SWIFT J1753.5-0127, GRO J1655-40, and XTE J1720-318. In this paper, we test the accretion-jet model originally proposed for XTE J1118+480 by investigating the hard state of these three sources using this model. The accretion flow in the model is composed of an inner hot accretion flow and an outer truncated thin disk. We find that the model satisfactorily explains the spectrum ranging from radio to X-rays, with the radio and X-ray spectra dominated by the synchrotron and thermal Comptonization emissions in the jet and the hot accretion flow, respectively, with the infrared and optical being the sum of the emissions from the jet, hot accretion flow, and the truncated thin disk. Similar to the case of XTE J1118+480, the model can also explain, although only qualitatively in some cases, the observed timing features including quasi-periodic oscillation, and positive and negative time lags between the optical and X-ray emissions detected in SWIFT J1753.5-0127. The origin of the ejection events detected in XTE J1720-318 is also briefly discussed.

  13. Traffic model with an absorbing-state phase transition

    NASA Astrophysics Data System (ADS)

    Iannini, M. L. L.; Dickman, Ronald

    2017-02-01

    We consider a modified Nagel-Schreckenberg (NS) model in which drivers do not decelerate if their speed is smaller than the headway (number of empty sites to the car ahead). (In the original NS model, such a reduction in speed occurs with probability p , independent of the headway, as long as the current speed is greater than zero.) In the modified model the free-flow state (with all vehicles traveling at the maximum speed, vmax) is absorbing for densities ρ smaller than a critical value ρc=1 /(vmax+2 ) . The phase diagram in the ρ -p plane is reentrant: for densities in the range ρc ,<<ρ <ρc , both small and large values of p favor free flow, while for intermediate values, a nonzero fraction of vehicles have speeds model. Our results suggest an unexpected connection between traffic models and stochastic sandpiles.

  14. An unsteady state retention model for fluid desorption from sorbents.

    PubMed

    Bazargan, Alireza; Sadeghi, Hamed; Garcia-Mayoral, Ricardo; McKay, Gordon

    2015-07-15

    New studies regarding the sorption of fluids by solids are published every day. In performance testing, after the sorbent has reached saturation, it is usually removed from the sorbate bath and allowed to drain. The loss of liquid from the sorbents with time is of prime importance in the real-world application of sorbents, such as in oil spill response. However, there is currently no equation used for modeling the unsteady state loss of the liquid from the dripping sorbent. Here, an analytical model has been provided for modeling the dynamic loss of liquid from the sorbent in dripping experiments. Data from more than 60 sorbent-sorbate systems has been used to validate the model. The proposed model shows excellent agreement with experimental results and is expressed as: U(t)=U(L)e(-Kt)+U(e) In which U(t) (kg/kg) is the uptake capacity of the sorbent at any time t (s) during dripping, U(L) (kg/kg) is the uptake capacity lost due to dripping, and U(e) (kg/kg) is the equilibrium uptake capacity reached after prolonged dripping. K (1/s) is defined as the Kamaan coefficient and controls the curvature of the retention profile. Kamaan ([symbol: see text] IPA phonetics: kæmɒn) is an Iranian (Farsi/Persian) word meaning "arc" or "curve" and hence the letter K has been designated.

  15. 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.

  16. A model independent description of the deutron asymptotic D state

    NASA Astrophysics Data System (ADS)

    Ericson, T. E. O.; Rosa-Clot, M.

    1982-04-01

    The asymptotic deutron D state is shown to result nearly model-independently from iterated OPEP yielding a predicted value η = (0.02633 ± 0.00035). Alternatively the result leads to a determination of the πN coupling constant [ f2 = (0.0792 ± 0.0012 )]. Attention is drawn to the implications for the size of quark bags. Analogous considerations of the deutron quadrupole moment permit the first direct determination of its non-potential part from experiment ΔQ = (0.005 ± 0.004) fm 2.

  17. 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.

  18. The ground state of the Frenkel-Kontorova model

    NASA Astrophysics Data System (ADS)

    Babushkin, A. Yu.; Abkaryan, A. K.; Dobronets, B. S.; Krasikov, V. S.; Filonov, A. N.

    2016-09-01

    The continual approximation of the ground state of the discrete Frenkel-Kontorova model is tested using a symmetric algorithm of numerical simulation. A "kaleidoscope effect" is found, which means that the curves representing the dependences of the relative extension of an N-atom chain vary periodically with increasing N. Stairs of structural transitions for N ≫ 1 are analyzed by the channel selection method with the approximation N = ∞. Images of commensurable and incommensurable structures are constructed. The commensurable-incommensurable phase transitions are stepwise.

  19. 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

  20. 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

  1. 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.

  2. Models of the spin state of the comet Halley nucleus

    NASA Technical Reports Server (NTRS)

    Julian, William H.

    1990-01-01

    Eight rotation precession models of the comet Halley nucleus have been proposed by eight authors. The eight models were evaluated in relation to the constraints imposed by: (1) the observed long axis directions at the Vega 1, Vega 2, and Giotto encounters; (2) the ground based emission periods harmonically related to 7.4 days; (3) the need for a two day spin period in the analysis of the jet morphology; (4) the Smith et al. constraint on the net long axis roll between Vega 2 and Giotto; (5) the resistance of the spin state of the nucleus to change due to the torque from the jets; and (6) the 7.4 day repetition of the spatial orientation of the nucleus. The eight constraints are briefly described.

  3. 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.

  4. String Models for the Heavy Quark-Antiquark Bound States.

    NASA Astrophysics Data System (ADS)

    Tse, Sze-Man

    1988-12-01

    The heavy quark-antiquark bound state is examined in the phenomenological string models. Specifically, the Nambu-Goto model and the Polyakov's smooth string model are studied in the large-D limit, D being the number of transverse space-time dimensions. The static potential V(R) is extracted in both models in the large-D limit. In the former case, this amounts to the usual saddle point calculation. In the latter case, the renormalized, physical string tension is expressed in terms of the bare string tension and the extrinsic curvature coupling. A systematic loop expansion of V(R) is developed and carried out explicitly to one loop order, with the two loops result presented without detail. For large separations R, the potential is linear in R with corrections of order 1/R. The coefficient of the 1/R Luscher term has the universal value -piD/24 to any finite order in the loop expansion. For very small separations R, the potential V(R) is also proportional to 1/R with a coefficient twice that of Luscher's term. The corrections are logarithmically small. Polyakov's smooth string model is extended to the finite temperature situation. The temperature dependence of the string tension is investigated in the large-D limit. The effective string tension is calculated to the second order in the loop expansion. At low temperature, it differs from that of the Nambu-Goto model only by terms that fall exponentially with inverse temperature. Comparison of the potential V(R) in the smooth string model with lattice gauge calculation and hadron spectroscopy data yields a consistent result.

  5. 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…

  6. 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…

  7. 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.

  8. Vibrational exciton mediated quantum state transfer: Simple model

    NASA Astrophysics Data System (ADS)

    Pouthier, Vincent

    2012-06-01

    A communication protocol is proposed in which quantum state transfer is mediated by a vibrational exciton. We consider two distant molecular groups grafted on the sides of a one-dimensional lattice. These groups behave as two quantum computers where the information in encoded and received. The lattice plays the role of a communication channel along which the exciton propagates and interacts with a phonon bath. Special attention is paid to describing the system involving an exciton dressed by a single phonon mode. The Hamiltonian is thus solved exactly so that the relevance of the perturbation theory is checked. Within the nonadiabatic weak-coupling limit, it is shown that the system supports three quasidegenerate states that define the relevant paths followed by the exciton to tunnel between the computers. When the model parameters are judiciously chosen, constructive interferences take place between these paths. Phonon-induced decoherence is minimized and a high-fidelity quantum state transfer occurs over a broad temperature range.

  9. Variational state specific solvent models for excited states from time dependent self-consistent field methods

    NASA Astrophysics Data System (ADS)

    Bjorgaard, Josiah; Velizhanin, Kirill; Tretiak, Sergei

    2015-03-01

    The effect of a dielectric environment on a molecule can be profound, causing changes in nuclear configuration and electronic structure. Quantum chemical simulation of a solute-solvent system can be prohibitively expensive due to the large number of degrees of freedom attributed to the solvent. To remedy this, the solvent can be treated as a dielectric cavity. Mutual polarization of the solute and solvent must be considered for accurate treatment of an optically excited state (ES) with a state-specific solvent model (SSM). In vacuum, time dependent self-consistent field (TD-SCF) methods (e,g, TD-HF, TD-DFT) give variational excitation energies. With the well known Z-vector equation, a variational ES energy is used to explore the ES potential energy surface (PES) with analytical gradients. Modification of the standard TD-SCF eigensystem to accommodate a SSM creates a nonlinear TD-SCF equation with non-variational excitation energies. This prevents analytical gradients from being formulated so that the ES PES cannot be explored. Here, we show how a variational formulation of existing SSMs can be derived from a Lagrangian formalism and give numerical results for the variability of calculated quantities. Model dynamics using SSMs are showcased.

  10. Numerical study of persistence in models with absorbing states

    NASA Astrophysics Data System (ADS)

    Albano, Ezequiel V.; Muñoz, Miguel A.

    2001-03-01

    Extensive Monte Carlo simulations are performed in order to evaluate both the local (θl) and global (θg) persistence exponents in the Ziff-Gulari-Barshad (ZGB) [Phys. Rev. Lett. 56, 2553 (1986)] irreversible reaction model. At the second-order irreversible phase transition (IPT) we find that both the local and the global persistence exhibit power-law behavior with a crossover between two different time regimes. On the other hand, at the ZGB first-order IPT, active sites are short lived and the persistence decays more abruptly; it is not clear whether it shows power-law behavior or not. In order to analyze universality issues, we have also studied another model with absorbing states, the contact process, and evaluated the local persistence exponent in dimensions from 1 to 4. A striking apparent superuniversality is reported: the local persistence exponent seems to coincide in both one- and two-dimensional systems. Some other aspects of persistence in systems with absorbing states are also analyzed.

  11. Numerical study of persistence in models with absorbing states.

    PubMed

    Albano, E V; Muñoz, M A

    2001-03-01

    Extensive Monte Carlo simulations are performed in order to evaluate both the local (straight theta(l)) and global (straight theta(g)) persistence exponents in the Ziff-Gulari-Barshad (ZGB) [Phys. Rev. Lett. 56, 2553 (1986)] irreversible reaction model. At the second-order irreversible phase transition (IPT) we find that both the local and the global persistence exhibit power-law behavior with a crossover between two different time regimes. On the other hand, at the ZGB first-order IPT, active sites are short lived and the persistence decays more abruptly; it is not clear whether it shows power-law behavior or not. In order to analyze universality issues, we have also studied another model with absorbing states, the contact process, and evaluated the local persistence exponent in dimensions from 1 to 4. A striking apparent superuniversality is reported: the local persistence exponent seems to coincide in both one- and two-dimensional systems. Some other aspects of persistence in systems with absorbing states are also analyzed.

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

    PubMed

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

    2010-06-07

    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.

  13. 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

  14. 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.

  15. 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.

  16. Dynamic causal models of steady-state responses

    PubMed Central

    Moran, R.J.; Stephan, K.E.; Seidenbecher, T.; Pape, H.-C.; Dolan, R.J.; Friston, K.J.

    2009-01-01

    In this paper, we describe a dynamic causal model (DCM) of steady-state responses in electrophysiological data that are summarised in terms of their cross-spectral density. These spectral data-features are generated by a biologically plausible, neural-mass model of coupled electromagnetic sources; where each source comprises three sub-populations. Under linearity and stationarity assumptions, the model's biophysical parameters (e.g., post-synaptic receptor density and time constants) prescribe the cross-spectral density of responses measured directly (e.g., local field potentials) or indirectly through some lead-field (e.g., electroencephalographic and magnetoencephalographic data). Inversion of the ensuing DCM provides conditional probabilities on the synaptic parameters of intrinsic and extrinsic connections in the underlying neuronal network. This means we can make inferences about synaptic physiology, as well as changes induced by pharmacological or behavioural manipulations, using the cross-spectral density of invasive or non-invasive electrophysiological recordings. In this paper, we focus on the form of the model, its inversion and validation using synthetic and real data. We conclude with an illustrative application to multi-channel local field potential data acquired during a learning experiment in mice. PMID:19000769

  17. 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

  18. Benchmarking spin-state chemistry in starless core models

    NASA Astrophysics Data System (ADS)

    Sipilä, O.; Caselli, P.; Harju, J.

    2015-06-01

    Aims: We aim to present simulated chemical abundance profiles for a variety of important species, giving special attention to spin-state chemistry, in order to provide reference results to which present and future models can be compared. Methods: We employ gas-phase and gas-grain models to investigate chemical abundances in physical conditions that correspond to starless cores. To this end, we have developed new chemical reaction sets for both gas-phase and grain-surface chemistry, including the deuterated forms of species with up to six atoms and the spin-state chemistry of light ions and of the species involved in the ammonia and water formation networks. The physical model is kept simple to facilitate straightforward benchmarking of other models against the results of this paper. Results: We find that the ortho/para ratios of ammonia and water are similar in both gas-phase and gas-grain models, particularly at late times, implying that the ratios are determined by gas-phase processes. Furthermore, the ratios do not exhibit any strong dependence on core density. We derive late-time ortho/para ratios of ~0.5 for ammonia and ~1.6 for water. We find that including or excluding deuterium in the calculations has little effect on the abundances of non-deuterated species and on the ortho/para ratios of ammonia and water, especially in gas-phase models where deuteration is naturally hindered by the presence of abundant heavy elements. Although we study a rather narrow temperature range (10-20 K), we find strong temperature dependence in, e.g., deuteration and nitrogen chemistry. For example, the depletion timescale of ammonia is significantly reduced when the temperature is increased from 10 to 20 K; this is because the increase in temperature translates into increased accretion rates, while the very high binding energy of ammonia prevents it from being desorbed at 20 K. Appendices are available in electronic form at http://www.aanda.org

  19. 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…

  20. Specificity in transition state binding: the Pauling model revisited.

    PubMed

    Amyes, Tina L; Richard, John P

    2013-03-26

    Linus Pauling proposed that the large rate accelerations for enzymes are caused by the high specificity of the protein catalyst for binding the reaction transition state. The observation that stable analogues of the transition states for enzymatic reactions often act as tight-binding inhibitors provided early support for this simple and elegant proposal. We review experimental results that 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 that aimed 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-coenzyme A:3-oxoacid coenzyme A transferase (SCOT) and the nonreacting portions of coenzyme A (CoA) are responsible for a rate increase of 3 × 10(12)-fold, which is close to the estimated total 5 × 10(13)-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 an ~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

  1. Mixture of a seismicity model based on the rate-and-state friction and ETAS model

    NASA Astrophysics Data System (ADS)

    Iwata, T.

    2015-12-01

    Currently the ETAS model [Ogata, 1988, JASA] is considered to be a standard model of seismicity. However, because the ETAS model is a purely statistical one, the physics-based seismicity model derived from the rate-and-state friction (hereafter referred to as Dieterich model) [Dieterich, 1994, JGR] is frequently examined. However, the original version of the Dieterich model has several problems in the application to real earthquake sequences and therefore modifications have been conducted in previous studies. Iwata [2015, Pageoph] is one of such studies and shows that the Dieterich model is significantly improved as a result of the inclusion of the effect of secondary aftershocks (i.e., aftershocks caused by previous aftershocks). However, still the performance of the ETAS model is superior to that of the improved Dieterich model. For further improvement, the mixture of the Dieterich and ETAS models is examined in this study. To achieve the mixture, the seismicity rate is represented as a sum of the ETAS and Dieterich models of which weights are given as k and 1-k, respectively. This mixture model is applied to the aftershock sequences of the 1995 Kobe and 2004 Mid-Niigata sequences which have been analyzed in Iwata [2015]. Additionally, the sequence of the Matsushiro earthquake swarm in central Japan 1965-1970 is also analyzed. The value of k and parameters of the ETAS and Dieterich models are estimated by means of the maximum likelihood method, and the model performances are assessed on the basis of AIC. For the two aftershock sequences, the AIC values of the ETAS model are around 3-9 smaller (i.e., better) than those of the mixture model. On the contrary, for the Matsushiro swarm, the AIC value of the mixture model is 5.8 smaller than that of the ETAS model, indicating that the mixture of the two models results in significant improvement of the seismicity model.

  2. Model State Policy, Legislation and State Plan Toward the Education of Gifted and Talented Students: A Handbook for State and Local Districts.

    ERIC Educational Resources Information Center

    Grossi, John A.

    Intended for legislators, educators, and advocates, the document presents a model policy statement, statute, and state plan regarding the education of gifted and talented students. The models were based upon analysis of existing state policies, legislation, and plans. Preliminary discussion focuses on issues of mandation, administrative…

  3. Efficient estimation of thermodynamic state incorporating Bayesian model order selection

    NASA Astrophysics Data System (ADS)

    Lanterman, Aaron D.; Cooper, Matthew L.; Miller, Michael I.

    1999-08-01

    The recognition of targets in infrared scenes is complicated by the wide variety of appearances associated with different thermodynamic states. We represent the variability in the thermodynamic signatures of targets via an expansion in terms of 'eigentanks' derived from a principal component analysis performed over the target's surface. Employing a Poisson sensor likelihood, or equivalently a likelihood based on Csiszar's I-divergence, a natural discrepancy measure for nonnegative images, yields a coupled set of nonlinear equations which must be solved to computed maximum a posteriori estimates of the thermodynamic expansion coefficients. We propose a weighted least-squares approximation to the Poisson loglikelihood for which the MAP estimates are solutions of linear equations. Bayesian model order estimation techniques are employed to choose the number of coefficients; this prevents target models with numerous eigentanks in their representation from having an unfair advantage over simple target models. The Bayesian integral is approximated by Schwarz's application of Laplace's method of integration; this technique is closely related to Rissanen's minimum description length and Wallace's minimum message length criteria. Our implementation of these techniques on Silicon Graphics computers exploits the flexible nature of their rendering engines. The implementation is illustrated in estimating the orientation of a tank and the optimum number of representative eigentanks for real data provided by the U.S. Army Night Vision and Electronic Sensors Directorate.

  4. Forecasting seasonal influenza with a state-space SIR model.

    PubMed

    Osthus, Dave; Hickmann, Kyle S; Caragea, Petruţa C; Higdon, Dave; Del Valle, Sara Y

    2017-03-01

    Seasonal influenza is a serious public health and societal problem due to its consequences resulting from absenteeism, hospitalizations, and deaths. The overall burden of influenza is captured by the Centers for Disease Control and Prevention's influenza-like illness network, which provides invaluable information about the current incidence. This information is used to provide decision support regarding prevention and response efforts. Despite the relatively rich surveillance data and the recurrent nature of seasonal influenza, forecasting the timing and intensity of seasonal influenza in the U.S. remains challenging because the form of the disease transmission process is uncertain, the disease dynamics are only partially observed, and the public health observations are noisy. Fitting a probabilistic state-space model motivated by a deterministic mathematical model [a susceptible-infectious-recovered (SIR) model] is a promising approach for forecasting seasonal influenza while simultaneously accounting for multiple sources of uncertainty. A significant finding of this work is the importance of thoughtfully specifying the prior, as results critically depend on its specification. Our conditionally specified prior allows us to exploit known relationships between latent SIR initial conditions and parameters and functions of surveillance data. We demonstrate advantages of our approach relative to alternatives via a forecasting comparison using several forecast accuracy metrics.

  5. Modified Navier-Stokes model for nonequilibrium stationary states

    NASA Astrophysics Data System (ADS)

    Garcia-Colin, L. S.; Velasco, R. M.

    1982-10-01

    A hydrodynamic model is developed in order to study the features of the behavior of a fluid which is brought to a stationary state by the action of an external gradient in the cases of the action of a thermal gradient and of a constant shear rate. An examination of the sound absorption of the fluid shows that the Stokes-Kirchhoff formula is modified by the presence of the gradients, which suggests an experimental verification of the model which is independent of the magnitude of the real wave vector. In addition, the light scattering of the fluid is examined by computing the Brillouin-Rayleigh spectra which yields in both cases the same shift in the Brillouin peaks previously predicted. However, a small change in the intensity of the peaks due to the modification of the sound-absorption coefficient is predicted by this model. Calculations show a shift of the Rayleigh peak arising from the entropy flow in the case of the thermal gradient and an entropy-production term in the case of the constant rate of shear, while in both cases the order of magnitude of this correction in terms of the wave vector is the same as the terms responsible for the shift in the Brillouin peaks.

  6. Simulating generic spin-boson models with matrix product states

    NASA Astrophysics Data System (ADS)

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

    2016-11-01

    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. We present a general numerical framework for treating the out-of-equilibrium dynamics of such models based on matrix product states. Our approach applies for generic spin-boson systems: it treats any spatial and operator dependence of the two-body spin-boson coupling and places no restrictions on relative energy scales. We show that the full counting statistics of collective spin measurements and infidelity of quantum simulation due to spin-boson entanglement, both of which are difficult to obtain by other techniques, are readily calculable in our approach. We benchmark our method using a recently developed exact solution for a particular spin-boson coupling relevant to trapped ion quantum simulators. Finally, we show how decoherence can be incorporated within our framework using the method of quantum trajectories, and study the dynamics of an open-system spin-boson model with spatially nonuniform spin-boson coupling relevant for trapped atomic ion crystals in the presence of molecular ion impurities.

  7. 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.

  8. 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.

  9. Chronic care model implementation in the California State Prison System.

    PubMed

    Ha, Betsy Chang; Robinson, Greg

    2011-04-01

    The chronic care model (CCM) deployed through a learning collaborative strategy, such as the Institute for Healthcare Improvement's Breakthrough Series (BTS), is a widely adopted approach to improve care that has guided clinical quality initiatives nationally and internationally. The BTS collaborative approach has been used to improve chronic conditions at national and state levels and in single health care delivery systems but not in correctional health care. Combining the CCM with a learning collaborative strategy in prison health care is a new frontier. This article describes the adoption of the CCM using a learning collaborative approach in the California prison system under the mandate of a federal receivership and elucidates some barriers to implementation. Results from the first phase of a pilot study were positive in terms of benefit/ cost analysis and suggest financial and political viability to continue the program.

  10. Modeling steady-state methanogenic degradation of phenols in groundwater

    USGS Publications Warehouse

    Bekins, Barbara A.; Godsy, E. Michael; Goerlitz, Donald F.

    1993-01-01

    Field and microcosm observations of methanogenic phenolic compound degradation indicate that Monod kinetics governs the substrate disappearance but overestimates the observed biomass. In this paper we present modeling results from an ongoing multidisciplinary study of methanogenic biodegradation of phenolic compounds in a sand and gravel aquifer contaminated by chemicals and wastes used in wood treatment. Field disappearance rates of four phenols match those determined in batch microcosm studies previously performed by E.M. Godsy and coworkers. The degradation process appears to be at steady-state because even after a sustained influx over several decades, the contaminants still are disappearing in transport downgradient. The existence of a steady-state degradation profile of each substrate together with a low biomass density in the aquifer indicate that the bacteria population is exhibiting no net growth. This may be due to the oligotrophic nature of the biomass population in which utilization and growth are approximately independent of concentration for most of the concentration range. Thus a constant growth rate should exist over much of the contaminated area which may in turn be balanced by an unusually high decay or maintenance rate due to hostile conditions or predation.

  11. 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.

  12. Sensitivity of Material Response Calculations to the Equation of State Model

    DTIC Science & Technology

    equation of state model. Three equation of state models, all...sources. The sensitivity of the calculated material response to the choice of equation of state model is characterized in terms of the generated impulse...and the peak propagating stress at the time the radiation source is cut off. For the calculations presented in this report, the three equation of state models are in fairly good

  13. 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

  14. Mathematical Models of Cochlear Nucleus Onset Neurons: II. Model with Dynamic Spike-Blocking State

    PubMed Central

    KALLURI, SRIDHAR; DELGUTTE, BERTRAND

    2008-01-01

    Onset (On) neurons in the cochlear nucleus (CN), characterized by their prominent response to the onset followed by little or no response to the steady-state of sustained stimuli, have a remarkable ability to entrain (firing 1 spike per cycle of a periodic stimulus) to low-frequency tones up to 1000 Hz. In this article, we present a point-neuron model with independent, excitatory auditory-nerve (AN) inputs that accounts for the ability of On neurons to both produce onset responses for high-frequency tone bursts and entrain to a wide range of low-frequency tones. With a fixed-duration spike-blocking state after a spike (an absolute refractory period), the model produces entrainment to a broad range of low-frequency tones and an On response with short interspike intervals (chopping) for high-frequency tone bursts. To produce On response patterns with no chopping, we introduce a novel, more complex, active membrane model in which the spike-blocking state is maintained until the instantaneous membrane voltage falls below a transition voltage. During the sustained depolarization for a high-frequency tone burst, the new model does not chop because it enters a spike-blocking state after the first spike and fails to leave this state until the membrane voltage returns toward rest at the end of the stimulus. The model entrains to low-frequency tones because the membrane voltage falls below the transition voltage on every cycle when the AN inputs are phase-locked. With the complex membrane model, On response patterns having moderate steady-state activity for high-frequency tone bursts (On-L) are distinguished from those having no steady-state activity (On-I) by requiring fewer AN inputs. Voltage-gated ion channels found in On-responding neurons of the CN may underlie the hypothesized dynamic spike-blocking state. These results provide a mechanistic rationale for distinguishing between the different physiological classes of CN On neurons. PMID:12435926

  15. Emerging Governance in State-Level Higher Education: Competing Pressures and Models

    ERIC Educational Resources Information Center

    Mortensen, Brad Leon

    2009-01-01

    This dissertation study considered reforms in state-level higher education governance in the United States. Many researchers have suggested the emergence of market-oriented models in higher education governance. This study explored the existence of market-oriented models as well as other reform models in two western states, Utah and Washington. …

  16. 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

  17. 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.

  18. 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.

  19. 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

  20. Seasonal rainfall predictions over the southeast United States using the Florida State University nested regional spectral model

    NASA Astrophysics Data System (ADS)

    Cocke, Steven; Larow, T. E.; Shin, D. W.

    2007-02-01

    Seasonal rainfall predictions over the southeast United States using the recently developed Florida State University (FSU) nested regional spectral model are presented. The regional model is nested within the FSU coupled model, which includes a version of the Max Plank Institute Hamburg Ocean Primitive Equation model. The southeast U.S. winter has a rather strong climatic signal due to teleconnections with tropical Pacific sea surface temperatures and thus provides a good test case scenario for a modeling study. Simulations were done for 12 boreal winter seasons, from 1986 to 1997. Both the regional and global models captured the basic large-scale patterns of precipitation reasonably well when compared to observed station data. The regional model was able to predict the anomaly pattern somewhat better than the global model. The regional model was particularly more skillful at predicting the frequency of significant rainfall events, in part because of the ability to produce heavier rainfall events.

  1. Modelling the unsteady growth state population balance for a nonlinear growth model in an MSMPR crystallizer

    SciTech Connect

    Carver, C.; Chipman, N.A.; Carleson, T.E.

    1994-03-01

    The precipitation of zirconium and other metal species as hydroxides (hydrous oxides) from simulated nuclear waste process solutions has been investigated as a potential method to reduce radioactive waste volumes. The reaction of ammonium hexaflourozirconate was used to simulate these waste streams. Studies were conducted to investigate the unsteady state response of crystallization in mixed suspension, mixed product removal (MSMPR) crystallizer. Size distributions below 40 {mu}m from laboratory batch and MSMPR data indicate size-dependent growth may be occurring because they may fit the Abegg, Stevens and Larson (ASL) model. However, these distributions also may fit a transient growth model based on the Method of Lines numerical solution to the unsteady state population balance equation. The development of the Method of Lines solution as well as experimental agreement with both models were studied.

  2. 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.

  3. Transitions in state public health law: comparative analysis of state public health law reform following the Turning Point Model State Public Health Act.

    PubMed

    Meier, Benjamin Mason; Hodge, James G; Gebbie, Kristine M

    2009-03-01

    Given the public health importance of law modernization, we undertook a comparative analysis of policy efforts in 4 states (Alaska, South Carolina, Wisconsin, and Nebraska) that have considered public health law reform based on the Turning Point Model State Public Health Act. Through national legislative tracking and state case studies, we investigated how the Turning Point Act's model legal language has been considered for incorporation into state law and analyzed key facilitating and inhibiting factors for public health law reform. Our findings provide the practice community with a research base to facilitate further law reform and inform future scholarship on the role of law as a determinant of the public's health.

  4. Adaptive Mixture Modelling Metropolis Methods for Bayesian Analysis of Non-linear State-Space Models.

    PubMed

    Niemi, Jarad; West, Mike

    2010-06-01

    We describe a strategy for Markov chain Monte Carlo analysis of non-linear, non-Gaussian state-space models involving batch analysis for inference on dynamic, latent state variables and fixed model parameters. The key innovation is a Metropolis-Hastings method for the time series of state variables based on sequential approximation of filtering and smoothing densities using normal mixtures. These mixtures are propagated through the non-linearities using an accurate, local mixture approximation method, and we use a regenerating procedure to deal with potential degeneracy of mixture components. This provides accurate, direct approximations to sequential filtering and retrospective smoothing distributions, and hence a useful construction of global Metropolis proposal distributions for simulation of posteriors for the set of states. This analysis is embedded within a Gibbs sampler to include uncertain fixed parameters. We give an example motivated by an application in systems biology. Supplemental materials provide an example based on a stochastic volatility model as well as MATLAB code.

  5. 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-

  6. 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.

  7. Quantal Density Functional Theory (Q-DFT) of Excited States: The State Arbitrariness of the Model Noninteracting Fermion System

    NASA Astrophysics Data System (ADS)

    Slamet, Marlina; Singh, Ranbir; Sahni, Viraht

    2003-03-01

    Within Q-DFT(V. Sahni, L. Massa, R.Singh, and M. Slamet, Phys. Rev. Lett. 87), 113002(2001)., the system of electrons in a nondegenerate excited state as described by the schrödinger equation, is transformed to one of noninteracting fermions such that the equivalent excited state density, energy, and ionization potential are obtained. The state of the model fermion system is arbitrary in that it may be in a ground or excited state. (The correaponding local effective potential energies differ, their difference being solely due to Correlation-Kinetic effects.) In either case, the highest occupied eigenvalue is the negative of the ionization potential. We demonstrate the state arbitrariness of the model system by application of Q-DFT to the first excited singlet state of the exactly solvable Hooke's atom. We construct two model systems: one in a singlet ground state (textstyle1s^2), and the other in a singlet first excited state (1s2s). The density and energy obtained from each model are the same as that of the interacting system, with the highest occupied eigenvalue in each case being the negative of the ionization potential.

  8. 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.

  9. 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...

  10. 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…

  11. 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...

  12. Modeling of Cancer Stem Cell State Transitions Predicts Therapeutic Response

    PubMed Central

    Sehl, Mary E.; Shimada, Miki; Landeros, Alfonso; Lange, Kenneth; Wicha, Max S.

    2015-01-01

    Cancer stem cells (CSCs) possess capacity to both self-renew and generate all cells within a tumor, and are thought to drive tumor recurrence. Targeting the stem cell niche to eradicate CSCs represents an important area of therapeutic development. The complex nature of many interacting elements of the stem cell niche, including both intracellular signals and microenvironmental growth factors and cytokines, creates a challenge in choosing which elements to target, alone or in combination. Stochastic stimulation techniques allow for the careful study of complex systems in biology and medicine and are ideal for the investigation of strategies aimed at CSC eradication. We present a mathematical model of the breast cancer stem cell (BCSC) niche to predict population dynamics during carcinogenesis and in response to treatment. Using data from cell line and mouse xenograft experiments, we estimate rates of interconversion between mesenchymal and epithelial states in BCSCs and find that EMT/MET transitions occur frequently. We examine bulk tumor growth dynamics in response to alterations in the rate of symmetric self-renewal of BCSCs and find that small changes in BCSC behavior can give rise to the Gompertzian growth pattern observed in breast tumors. Finally, we examine stochastic reaction kinetic simulations in which elements of the breast cancer stem cell niche are inhibited individually and in combination. We find that slowing self-renewal and disrupting the positive feedback loop between IL-6, Stat3 activation, and NF-κB signaling by simultaneous inhibition of IL-6 and HER2 is the most effective combination to eliminate both mesenchymal and epithelial populations of BCSCs. Predictions from our model and simulations show excellent agreement with experimental data showing the efficacy of combined HER2 and Il-6 blockade in reducing BCSC populations. Our findings will be directly examined in a planned clinical trial of combined HER2 and IL-6 targeted therapy in HER2

  13. 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.

  14. Models of steady state cooling flows in elliptical galaxies

    NASA Technical Reports Server (NTRS)

    Vedder, Peter W.; Trester, Jeffrey J.; Canizares, Claude R.

    1988-01-01

    A comprehensive set of steady state models for spherically symmetric cooling flows in early-type galaxies is presented. It is found that a reduction of the supernova (SN) rate in ellipticals produces a decrease in the X-ray luminosity of galactic cooling flows and a steepening of the surface brightness profile. The mean X-ray temperature of the cooling flow is not affected noticeably by a change in the SN rate. The external pressure around a galaxy does not markedly change the luminosity of the gas within the galaxy but does change the mean temperature of the gas. The presence of a dark matter halo in a galaxy only changes the mean X-ray temperature slightly. The addition of a distribution of mass sinks which remove material from the general accretion flow reduces L(X) very slightly, flattens the surface brightness profile, and reduces the central surface brightness level to values close to those actually observed. A reduction in the stellar mass-loss rate only slightly reduces the X-ray luminosity of the cooling flow and flattens the surface brightness by a small amount.

  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. Boosting the power factor with resonant states: A model study

    NASA Astrophysics Data System (ADS)

    Thébaud, S.; Adessi, Ch.; Pailhès, S.; Bouzerar, G.

    2017-08-01

    A particularly promising pathway to enhance the efficiency of thermoelectric materials lies in the use of resonant states, as suggested by experimentalists and theorists alike. In this paper, we go over the mechanisms used in the literature to explain how resonant levels affect the thermoelectric properties, and we suggest that the effects of hybridization are crucial yet ill understood. In order to get a good grasp of the physical picture and to draw guidelines for thermoelectric enhancement, we use a tight-binding model containing a conduction band hybridized with a flat band. We find that the conductivity is suppressed in a wide energy range near the resonance, but that the Seebeck coefficient can be boosted for strong enough hybridization, thus allowing for a significant increase of the power factor. The Seebeck coefficient can also display a sign change as the Fermi level crosses the resonance. Our results suggest that in order to boost the power factor, the hybridization strength must not be too low, the resonant level must not be too close to the conduction (or valence) band edge, and the Fermi level must be located around, but not inside, the resonant peak.

  17. Girsanov reweighting for path ensembles and Markov state models

    NASA Astrophysics Data System (ADS)

    Donati, L.; Hartmann, C.; Keller, B. G.

    2017-06-01

    The sensitivity of molecular dynamics on changes in the potential energy function plays an important role in understanding the dynamics and function of complex molecules. We present a method to obtain path ensemble averages of a perturbed dynamics from a set of paths generated by a reference dynamics. It is based on the concept of path probability measure and the Girsanov theorem, a result from stochastic analysis to estimate a change of measure of a path ensemble. Since Markov state models (MSMs) of the molecular dynamics can be formulated as a combined phase-space and path ensemble average, the method can be extended to reweight MSMs by combining it with a reweighting of the Boltzmann distribution. We demonstrate how to efficiently implement the Girsanov reweighting in a molecular dynamics simulation program by calculating parts of the reweighting factor "on the fly" during the simulation, and we benchmark the method on test systems ranging from a two-dimensional diffusion process and an artificial many-body system to alanine dipeptide and valine dipeptide in implicit and explicit water. The method can be used to study the sensitivity of molecular dynamics on external perturbations as well as to reweight trajectories generated by enhanced sampling schemes to the original dynamics.

  18. 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.

  19. Modeling asymmetric cavity collapse with plasma equations of state.

    PubMed

    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.

  20. 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

  1. 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

  2. Modeling effective FRW cosmologies with perfect fluids from states of the hybrid quantum Gowdy model

    NASA Astrophysics Data System (ADS)

    Elizaga Navascués, Beatriz; Martín-Benito, Mercedes; Mena Marugán, Guillermo A.

    2015-01-01

    We employ recently developed approximation methods in the hybrid quantization of the Gowdy T3 model with linear polarization and a massless scalar field to obtain physically interesting solutions of this inhomogeneous cosmology. More specifically, we propose some particular approximate solutions of the quantum Gowdy model constructed in such a way that, for the Hamiltonian constraint, they effectively behave as those corresponding to a flat homogeneous and isotropic universe filled with a perfect fluid, even though these quantum states are far from being homogeneous and isotropic. We analyze how one can get different perfect fluid effective behaviors, including the cases of dust, radiation, and a cosmological constant.

  3. 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.

  4. Counting metastable states in a kinetically constrained model using a patch repetition analysis.

    PubMed

    Jack, Robert L

    2013-12-01

    We analyze metastable states in the East model, using a recently proposed patch repetition analysis based on time-averaged density profiles. The results reveal a hierarchy of states of varying lifetimes, consistent with previous studies in which the metastable states were identified and used to explain the glassy dynamics of the model. We establish a mapping between these states and configurations of systems of hard rods, which allows us to analyze both typical and atypical metastable states. We discuss connections between the complexity of metastable states and large-deviation functions of dynamical quantities, both in the context of the East model and more generally in glassy systems.

  5. Final state-selected spectra in unimolecular reactions: A transition-state-based random matrix model for overlapping resonances

    SciTech Connect

    Peskin, U.; Miller, W.H.; Reisler, H.

    1995-06-08

    Final state-selected spectra in unimolecular decomposition are obtained by a random matrix version of Feshbach`s optical model. The number of final states which are independently coupled to the molecular quasibound states is identified with the number of states at the dividing surface of transition state theory (TST). The coupling of the transition state to the molecular complex is modeled via a universal random matrix effective Hamiltonian which is characterized by its resonance eigenstates and provides the correct average unimolecular decay rate. The transition from nonoverlapping resonances which are associated with isolated Lorentzian spectral peaks, to overlapping resonances, associated with more complex spectra, is characterized in terms of deviations from a {chi}{sup 2}-like distribution of the resonance widths and the approach to a random phase-distribution of the resonance scattering amplitudes. The evolution of the system from a tight transition state to reaction products is treated explicitly as a scattering process where specific dynamics can be incorporated. Comparisons with recently measured final state-selected spectra and rotational distributions for the unimolecular reaction of NO{sub 2} show that the present model provides a useful new approach for understanding and interpreting experimental results which are dominated by overlapping resonances.

  6. Degenerate ground states and multiple bifurcations in a two-dimensional q-state quantum Potts model.

    PubMed

    Dai, Yan-Wei; Cho, Sam Young; Batchelor, Murray T; Zhou, Huan-Qiang

    2014-06-01

    We numerically investigate the two-dimensional q-state quantum Potts model on the infinite square lattice by using the infinite projected entangled-pair state (iPEPS) algorithm. We show that the quantum fidelity, defined as an overlap measurement between an arbitrary reference state and the iPEPS ground state of the system, can detect q-fold degenerate ground states for the Z_{q} broken-symmetry phase. Accordingly, a multiple bifurcation of the quantum ground-state fidelity is shown to occur as the transverse magnetic field varies from the symmetry phase to the broken-symmetry phase, which means that a multiple-bifurcation point corresponds to a critical point. A (dis)continuous behavior of quantum fidelity at phase transition points characterizes a (dis)continuous phase transition. Similar to the characteristic behavior of the quantum fidelity, the magnetizations, as order parameters, obtained from the degenerate ground states exhibit multiple bifurcation at critical points. Each order parameter is also explicitly demonstrated to transform under the Z_{q} subgroup of the symmetry group of the Hamiltonian. We find that the q-state quantum Potts model on the square lattice undergoes a discontinuous (first-order) phase transition for q=3 and q=4 and a continuous phase transition for q=2 (the two-dimensional quantum transverse Ising model).

  7. Rate heterogeneity across Squamata, misleading ancestral state reconstruction and the importance of proper null model specification.

    PubMed

    Harrington, S; Reeder, T W

    2017-02-01

    The binary-state speciation and extinction (BiSSE) model has been used in many instances to identify state-dependent diversification and reconstruct ancestral states. However, recent studies have shown that the standard procedure of comparing the fit of the BiSSE model to constant-rate birth-death models often inappropriately favours the BiSSE model when diversification rates vary in a state-independent fashion. The newly developed HiSSE model enables researchers to identify state-dependent diversification rates while accounting for state-independent diversification at the same time. The HiSSE model also allows researchers to test state-dependent models against appropriate state-independent null models that have the same number of parameters as the state-dependent models being tested. We reanalyse two data sets that originally used BiSSE to reconstruct ancestral states within squamate reptiles and reached surprising conclusions regarding the evolution of toepads within Gekkota and viviparity across Squamata. We used this new method to demonstrate that there are many shifts in diversification rates across squamates. We then fit various HiSSE submodels and null models to the state and phylogenetic data and reconstructed states under these models. We found that there is no single, consistent signal for state-dependent diversification associated with toepads in gekkotans or viviparity across all squamates. Our reconstructions show limited support for the recently proposed hypotheses that toepads evolved multiple times independently in Gekkota and that transitions from viviparity to oviparity are common in Squamata. Our results highlight the importance of considering an adequate pool of models and null models when estimating diversification rate parameters and reconstructing ancestral states. © 2016 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2016 European Society For Evolutionary Biology.

  8. A Manifold of Pure Gibbs States of the Ising Model on the Lobachevsky Plane

    NASA Astrophysics Data System (ADS)

    Gandolfo, Daniel; Ruiz, Jean; Shlosman, Senya

    2015-02-01

    In this paper we construct many `new' Gibbs states of the Ising model on the Lobachevsky plane, the millefeuilles. Unlike the usual states on the integer lattices, our foliated states have infinitely many interfaces. The interfaces are rigid and fill the Lobachevsky plane with positive density. We also construct analogous states on the Cayley trees.

  9. 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.

  10. Horizon state, Hawking radiation, and boundary Liouville model.

    PubMed

    Solodukhin, Sergey N

    2004-02-13

    We demonstrate that the near-horizon physics, the Hawking radiation, and the reflection off the radial potential barrier can be understood entirely within a conformal field theory picture in terms of one- and two-point functions in the boundary Liouville theory. An important element in this demonstration is the notion of horizon state, the Hawking radiation being interpreted as a result of the transition of horizon state to the ordinary states propagating outside the black hole horizon.

  11. 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.

  12. Typical Unpreparability of Quantum States with Quantum Circuit Model

    NASA Astrophysics Data System (ADS)

    Luo, Mingxing

    2014-04-01

    The quantum entanglement is an interesting resource in quantum information processing, especially in measurement-based quantum computing. However, most quantum states may be too entangled to be prepared efficiently in terms of quantum circuit theory, in that high values of the geometric measure of entanglement preclude states from holding a polynomial quantum preparation circuit. We prove that this phenomenon experiences occurs in a dramatic majority of all states using a novel circuit tree-state correspondence. This work highlights new aspects of the roles both entanglement and quantum circuit theory play for quantum information processing.

  13. A model of cerebellar computations for dynamical state estimation.

    PubMed

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

    2001-11-01

    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.

  14. 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.

  15. Algorithmic Construction of Local Hidden Variable Models for Entangled Quantum States.

    PubMed

    Hirsch, Flavien; Quintino, Marco Túlio; Vértesi, Tamás; Pusey, Matthew F; Brunner, Nicolas

    2016-11-04

    Constructing local hidden variable (LHV) models for entangled quantum states is a fundamental problem, with implications for the foundations of quantum theory and for quantum information processing. It is, however, a challenging problem, as the model should reproduce quantum predictions for all possible local measurements. Here we present a simple method for building LHV models, applicable to any entangled state and considering continuous sets of measurements. This leads to a sequence of tests which, in the limit, fully captures the set of quantum states admitting a LHV model. Similar methods are developed for local hidden state models. We illustrate the practical relevance of these methods with several examples.

  16. Algorithmic Construction of Local Hidden Variable Models for Entangled Quantum States

    NASA Astrophysics Data System (ADS)

    Hirsch, Flavien; Quintino, Marco Túlio; Vértesi, Tamás; Pusey, Matthew F.; Brunner, Nicolas

    2016-11-01

    Constructing local hidden variable (LHV) models for entangled quantum states is a fundamental problem, with implications for the foundations of quantum theory and for quantum information processing. It is, however, a challenging problem, as the model should reproduce quantum predictions for all possible local measurements. Here we present a simple method for building LHV models, applicable to any entangled state and considering continuous sets of measurements. This leads to a sequence of tests which, in the limit, fully captures the set of quantum states admitting a LHV model. Similar methods are developed for local hidden state models. We illustrate the practical relevance of these methods with several examples.

  17. 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.

  18. 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

    2016-05-25

    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.

  19. 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.

  20. The Noble-Abel Equation of State: Thermodynamic Derivations for Ballistics Modelling

    DTIC Science & Technology

    2005-11-01

    equation of state for propellant gases at the high densities and temperatures experienced in guns. Most computational fluid dynamics-based ballistics models, however, require additional thermodynamic functions which...derived from the equation of state . This note presents

  1. Maximizing State Lottery Dollars for Public Education: An Analysis of Current State Lottery Models

    ERIC Educational Resources Information Center

    Brady, Kevin P.; Pijanowski, John C.

    2007-01-01

    Today, it is increasingly difficult for states to adequately satisfy the demand for well-funded and quality public services, such as K-12 education by relying exclusively on traditional, broad-based taxes for fiscal support. State sponsored lotteries are an increasingly popular, non-traditional revenue stream for public education. There is in many…

  2. The Experience of One State Agency with the State Consultant Model.

    ERIC Educational Resources Information Center

    Katagiri, George

    The Research and Development Exchange (RDx) is a network of regional educational laboratories and university-based research and development centers working to support state and local school improvement efforts. Primary recipients of the services of all regional exchanges are dissemination specialists in state education agencies. The Northwest…

  3. Modeling States' Enactment of High School Exit Examination Policies

    ERIC Educational Resources Information Center

    Warren, John Robert; Kulick, Rachael B.

    2007-01-01

    We present five frameworks for explaining which U.S. states adopted high school exit examination policies at particular points in time. The frameworks correspond to issues of academic achievement, education spending, economic conditions, racial/ethnic heterogeneity and policy diffusion. Using event history techniques we find that states with…

  4. Modeling States' Enactment of High School Exit Examination Policies

    ERIC Educational Resources Information Center

    Warren, John Robert; Kulick, Rachael B.

    2007-01-01

    We present five frameworks for explaining which U.S. states adopted high school exit examination policies at particular points in time. The frameworks correspond to issues of academic achievement, education spending, economic conditions, racial/ethnic heterogeneity and policy diffusion. Using event history techniques we find that states with…

  5. 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.

  6. 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. 33 refs., 9 figs.

  7. A Linear Programming Model to Optimize Various Objective Functions of a Foundation Type State Support Program.

    ERIC Educational Resources Information Center

    Matzke, Orville R.

    The purpose of this study was to formulate a linear programming model to simulate a foundation type support program and to apply this model to a state support program for the public elementary and secondary school districts in the State of Iowa. The model was successful in producing optimal solutions to five objective functions proposed for…

  8. 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.

  9. Steady-state existence of passive vector fields under the Kraichnan model.

    PubMed

    Arponen, Heikki

    2010-03-01

    The steady-state existence problem for Kraichnan advected passive vector models is considered for isotropic and anisotropic initial values in arbitrary dimension. The models include the magnetohydrodynamic (MHD) equations, linear pressure model, and linearized Navier-Stokes (LNS) equations. In addition to reproducing the previously known results for the MHD model, we obtain the values of the Kraichnan model roughness parameter xi for which the LNS steady state exists.

  10. Four states magnetic dots: a design selection by micromagnetic modeling

    NASA Astrophysics Data System (ADS)

    Louis, D.; Hauet, T.; Petit-Watelot, S.; Lacour, D.; Hehn, M.; Montaigne, F.

    2016-10-01

    In a context where sub-micrometric magnetic dots are foreseen to play an active role in various new breeds of electronics components such as magnetic memories, magnetic logics or bio-sensors, the use of micromagnetic simulations to optimize their shapes and spatial arrangement with respect to a chosen application has become unavoidable. Prior realizing experimentally magnetic dots presenting four stable magnetic states (4SMS), we performed a micromagnetic study to select a design providing not only four equivalent magnetic states in a single dot but also exhibiting mostly uniform magnetic states.

  11. 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.

  12. Insights on the role of accurate state estimation in coupled model parameter estimation by a conceptual climate model study

    NASA Astrophysics Data System (ADS)

    Yu, Xiaolin; Zhang, Shaoqing; Lin, Xiaopei; Li, Mingkui

    2017-03-01

    The uncertainties in values of coupled model parameters are an important source of model bias that causes model climate drift. The values can be calibrated by a parameter estimation procedure that projects observational information onto model parameters. The signal-to-noise ratio of error covariance between the model state and the parameter being estimated directly determines whether the parameter estimation succeeds or not. With a conceptual climate model that couples the stochastic atmosphere and slow-varying ocean, this study examines the sensitivity of state-parameter covariance on the accuracy of estimated model states in different model components of a coupled system. Due to the interaction of multiple timescales, the fast-varying atmosphere with a chaotic nature is the major source of the inaccuracy of estimated state-parameter covariance. Thus, enhancing the estimation accuracy of atmospheric states is very important for the success of coupled model parameter estimation, especially for the parameters in the air-sea interaction processes. The impact of chaotic-to-periodic ratio in state variability on parameter estimation is also discussed. This simple model study provides a guideline when real observations are used to optimize model parameters in a coupled general circulation model for improving climate analysis and predictions.

  13. 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.

  14. Health monitoring of bridgelike structures using state variable models

    NASA Astrophysics Data System (ADS)

    Valentin-Sivico, Javier; Rao, Vittal S.; Koval, Leslie R.

    1997-05-01

    A global damage detection method for civil engineering structures is proposed. This method provides the capability of determining the reduction in both stiffness and damping parameters of the structural elements. The proposed method uses the state-space representation of the structural dynamics to make the diagnosis of structural integrity. Given that the state-space representation of any system is not unique, the damage detection procedure is developed for the physical coordinates of the state-space representation. A transformation matrix to get any arbitrary state-space representation into the physical coordinates is also utilized. The feasibility of the proposed method is verified on a numerical example as well as on a simulated three-bar truss structure with 3 degrees of freedom.

  15. Electronic State Decomposition of Energetic Materials and Model Systems

    DTIC Science & Technology

    2010-11-17

    tetrazine1,4-dioxde ( DATO ), is investigated. Although these molecules are based on N -oxides of a tetrazine aromatic heterocyclic ring, their...nitramines, furazan, tetrazines, tetrazine-N oxides, terazoles, PETN, RDX,HMX,CL-20,DAATO,ACTO, DATO ,conical intersections Elliot R Bernstein Colorado State...Tetrazine-N-Oxide Based High Nitrogen Content Energetic Materials from Excited Electronic States," J. Chem. Phys. 131, 194304 (2009). A

  16. Analyzing Tabular Requirements Specifications Using Infinite State Model Checking

    DTIC Science & Technology

    2006-01-01

    two-state properties that hold in every reachable transition. Property Checking with Salsa . The SCR property checker Salsa [5] may be used to check...SCR specifications for Dis- jointness and Coverage and for satisfaction of state and tran- sition invariants. Salsa can check the validity of formulas...TAME and Salsa . 3. Action Language Verifier Action Language is a specification language for reactive software systems. The Action Language Verifier

  17. Photonic states mixing beyond the plasmon hybridization model

    SciTech Connect

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

    2016-07-28

    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.

  18. 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.

  19. 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 =…

  20. 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.

  1. 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.

  2. 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.

  3. 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)

  4. Helping Students Become Better Mathematical Modelers: Pseudosteady-State Approximations.

    ERIC Educational Resources Information Center

    Bunge, Annette L.; Miller, Ronald L.

    1997-01-01

    Undergraduate and graduate students are often confused about several aspects of modeling physical systems. Describes an approach to address these issues using a single physical transport problem that can be analyzed with multiple mathematical models. (DKM)

  5. Helping Students Become Better Mathematical Modelers: Pseudosteady-State Approximations.

    ERIC Educational Resources Information Center

    Bunge, Annette L.; Miller, Ronald L.

    1997-01-01

    Undergraduate and graduate students are often confused about several aspects of modeling physical systems. Describes an approach to address these issues using a single physical transport problem that can be analyzed with multiple mathematical models. (DKM)

  6. 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)

  7. 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.

  8. Validating HRSA's nurse supply and demand models: a state-level perspective.

    PubMed

    Nooney, Jennifer G; Lacey, Linda M

    2007-01-01

    In addition to federal initiatives, solutions to the nursing shortage must also be devised at the state level. Understanding the timing and severity of the nursing shortage in a particular state is paramount to devising appropriate solutions In 2005, the Health Resources and Services Administration released new versions of the Nurse Supply Model and Nurse Demand Model designed to project the supply of RNs and demand for RNs, LPNs, and nurse aides in the United States through the year 2020. The process used by two state-level analysts to project nurse supply and demand in North Carolina using the HRSA models is described. The authors conclude that the models work well for state-level forecasting but that users should carefully assess the default data provided with the model against independent data sources specific to their states.

  9. Modular transformer state model for the simulation of high frequency spacecraft power systems

    NASA Astrophysics Data System (ADS)

    Evans, Bruce W.; Grigsby, L. L.; Nelms, R. M.

    A high frequency, lumped parameter model of a power transformer is presented. The model is used to derive a third-order state variable description of the device that is coupled to state variable models of the other power system components. Based on the state model, a digital simulation is conducted using the state transition matrix. The technique is used to simulate a high frequency spacecraft power system which includes a series resonant converter, transformer, transmission line, and resistive-inductive load. Each individual device is modeled as a two-port modular subnetwork with port voltages used as the independent variables. A state variable mathematical description of each device is formulated and numerically simulated using the state transition matrix. The results of the simulation are compared to results from EMTP, a program widely used by the power industry to predict transients.

  10. Jump Markov models and transition state theory: the quasi-stationary distribution approach.

    PubMed

    Di Gesù, Giacomo; Lelièvre, Tony; Le Peutrec, Dorian; Nectoux, Boris

    2016-12-22

    We are interested in the connection between a metastable continuous state space Markov process (satisfying e.g. the Langevin or overdamped Langevin equation) and a jump Markov process in a discrete state space. More precisely, we use the notion of quasi-stationary distribution within a metastable state for the continuous state space Markov process to parametrize the exit event from the state. This approach is useful to analyze and justify methods which use the jump Markov process underlying a metastable dynamics as a support to efficiently sample the state-to-state dynamics (accelerated dynamics techniques). Moreover, it is possible by this approach to quantify the error on the exit event when the parametrization of the jump Markov model is based on the Eyring-Kramers formula. This therefore provides a mathematical framework to justify the use of transition state theory and the Eyring-Kramers formula to build kinetic Monte Carlo or Markov state models.

  11. 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.

  12. 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.

  13. Nonexistence of nonconstant steady-state solutions in a triangular cross-diffusion model

    NASA Astrophysics Data System (ADS)

    Lou, Yuan; Tao, Youshan; Winkler, Michael

    2017-05-01

    In this paper we study the Shigesada-Kawasaki-Teramoto model for two competing species with triangular cross-diffusion. We determine explicit parameter ranges within which the model exclusively possesses constant steady state solutions.

  14. Forest ingrowth prediction model for the Northeastern United States

    Treesearch

    Linda S. Gribko

    1997-01-01

    In the last 20 years, there has been a revival of interest in the use of uneven-aged forest management techniques in the production of timber and forest amenity values. Uneven-aged management is coming into renewed favor especially among non-industrial private landowners in the northeastern United States. The practice allows periodic timber removals on relatively small...

  15. 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…

  16. 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…

  17. Quantization of closed mini-superspace models as bound states

    NASA Astrophysics Data System (ADS)

    Kung, J. H.

    1995-01-01

    The Wheeler-DeWitt equation is applied to closedk>0 Friedmann-Robertson-Walker metric with various combination of cosmological constant and matter (e.g., radiation or pressureless gas). It is shown that if the universe ends in the matter dominated era (e.g., radiation or pressureless gas) with zero cosmological constant, then the resulting Wheeler-DeWitt equation describes a bound state problem. As solutions of a nondegenerate bound state system, the eigen-wave functions are real (Hartle-Hawking). Furthermore, as a bound state problem, there exists a quantization condition that relates the curvature of the three space with the various energy densities of the universe. If we assume that our universe is closed, then the quantum number of our universe isN˜(Gk)-1˜10122. The largeness of this quantum number is naturally explained by an early inflationary phase which resulted in a flat universe we observe today. It is also shown that if there is a cosmological constant Λ>0 in our universe that persists for all time, then the resulting Wheeler-DeWitt equation describes a non-bound state system, regardless of the magnitude of the cosmological constant. As a consequence, the wave functions are in general complex (Vilenkin).

  18. 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…

  19. 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…

  20. A spline model of climate for the Western United States

    Treesearch

    Gerald E. Rehfeldt

    2006-01-01

    Monthly climate data of average, minimum, and maximum temperature and precipitation normalized for the period 1961 through 1990 were accumulated from approximately 3,000 weather stations in the Western United States and Southwestern Canada. About two-thirds of these observations were available from the weather services of the two countries while the remaining third...

  1. 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

  2. A generalized system of models forecasting Central States tree growth.

    Treesearch

    Stephen R. Shifley

    1987-01-01

    Describes the development and testing of a system of individual tree-based growth projection models applicable to species in Indiana, Missouri, and Ohio. Annual tree basal area growth is estimated as a function of tree size, crown ratio, stand density, and site index. Models are compatible with the STEMS and TWIGS Projection System.

  3. Realization of State-Space Models for Wave Propagation Simulations

    DTIC Science & Technology

    2012-01-01

    turquoise ). 13 Verification and Performance of Superstable Model The second FDTD analysis was to verify that a simulation using the...another, so that the turquoise and red lines are all that are visible). The implication is that model-order reduction can serve a useful purpose when

  4. State of the art hydraulic turbine model test

    NASA Astrophysics Data System (ADS)

    Fabre, Violaine; Duparchy, Alexandre; Andre, Francois; Larroze, Pierre-Yves

    2016-11-01

    Model tests are essential in hydraulic turbine development and related fields. The methods and technologies used to perform these tests show constant progress and provide access to further information. In addition, due to its contractual nature, the test demand evolves continuously in terms of quantity and accuracy. Keeping in mind that the principal aim of model testing is the transposition of the model measurements to the real machine, the measurements should be performed accurately, and a critical analysis of the model test results is required to distinguish the transposable hydraulic phenomena from the test rig interactions. Although the resonances’ effects are known and described in the IEC standard, their identification is difficult. Leaning on a strong experience of model testing, we will illustrate with a few examples of how to identify the potential problems induced by the test rig. This paper contains some of our best practices to obtain the most accurate, relevant, and independent test-rig measurements.

  5. [Research on monitoring mechanical wear state based on oil spectrum multi-dimensional time series model].

    PubMed

    Xu, Chao; Zhang, Pei-lin; Ren, Guo-quan; Li, Bing; Yang, Ning

    2010-11-01

    A new method using oil atomic spectrometric analysis technology to monitor the mechanical wear state was proposed. Multi-dimensional time series model of oil atomic spectrometric data of running-in period was treated as the standard model. Residues remained after new data were processed by the standard model. The residues variance matrix was selected as the features of the corresponding wear state. Then, high dimensional feature vectors were reduced through the principal component analysis and the first three principal components were extracted to represent the wear state. Euclidean distance was computed for feature vectors to classify the testing samples. Thus, the mechanical wear state was identified correctly. The wear state of a specified track vehicle engine was effectively identified, which verified the validity of the proposed method. Experimental results showed that introducing the multi-dimensional time series model to oil spectrometric analysis can fuse the spectrum data and improve the accuracy of monitoring mechanical wear state.

  6. Vive la Difference: What It Means for State Boards to Embrace Two Models for Public Education

    ERIC Educational Resources Information Center

    Smarick, Andy

    2017-01-01

    The charter school model differs fundamentally from the district-based model of public education delivery that is still dominant in every state. Instead of creating government bodies that directly operate all of an area's public schools, the state approves entities that authorize and oversee schools run by nonprofit organizations. In this article,…

  7. Surface states of a system of Dirac fermions: A minimal model

    SciTech Connect

    Volkov, V. A. Enaldiev, V. V.

    2016-03-15

    A brief survey is given of theoretical works on surface states (SSs) in Dirac materials. Within the formalism of envelope wave functions and boundary conditions for these functions, a minimal model is formulated that analytically describes surface and edge states of various (topological and nontopological) types in several systems with Dirac fermions (DFs). The applicability conditions of this model are discussed.

  8. A review of Bayesian state-space modelling of capture-recapture-recovery data.

    PubMed

    King, Ruth

    2012-04-06

    Traditionally, state-space models are fitted to data where there is uncertainty in the observation or measurement of the system. State-space models are partitioned into an underlying system process describing the transitions of the true states of the system over time and the observation process linking the observations of the system to the true states. Open population capture-recapture-recovery data can be modelled in this framework by regarding the system process as the state of each individual observed within the study in terms of being alive or dead, and the observation process the recapture and/or recovery process. The traditional observation error of a state-space model is incorporated via the recapture/recovery probabilities being less than unity. The models can be fitted using a Bayesian data augmentation approach and in standard BUGS packages. Applying this state-space framework to such data permits additional complexities including individual heterogeneity to be fitted to the data at very little additional programming effort. We consider the efficiency of the state-space model fitting approach by considering a random effects model for capture-recapture data relating to dippers and compare different Bayesian model-fitting algorithms within WinBUGS.

  9. A review of Bayesian state-space modelling of capture–recapture–recovery data

    PubMed Central

    King, Ruth

    2012-01-01

    Traditionally, state-space models are fitted to data where there is uncertainty in the observation or measurement of the system. State-space models are partitioned into an underlying system process describing the transitions of the true states of the system over time and the observation process linking the observations of the system to the true states. Open population capture–recapture–recovery data can be modelled in this framework by regarding the system process as the state of each individual observed within the study in terms of being alive or dead, and the observation process the recapture and/or recovery process. The traditional observation error of a state-space model is incorporated via the recapture/recovery probabilities being less than unity. The models can be fitted using a Bayesian data augmentation approach and in standard BUGS packages. Applying this state-space framework to such data permits additional complexities including individual heterogeneity to be fitted to the data at very little additional programming effort. We consider the efficiency of the state-space model fitting approach by considering a random effects model for capture–recapture data relating to dippers and compare different Bayesian model-fitting algorithms within WinBUGS. PMID:23565333

  10. The Total Quality Management Model Department of Personnel State of Colorado,

    DTIC Science & Technology

    A panel of three members will present the Total Quality Management model recently designed for the Department of Personnel, State of Colorado. This model was selected to increase work quality and productivity of the Department and to exemplify Governor Romer’s commitment to quality work within state government.

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

    USDA-ARS?s Scientific Manuscript database

    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...

  12. The State Role in Financing Community Colleges: A Model for Improvement.

    ERIC Educational Resources Information Center

    Taylor, Terry

    1985-01-01

    Explores trends in the state role in community college funding and college responses to those trends, underscoring the need for an improved funding formula model. Identifies specific goals and components of such a model, covering areas including governance, budgeting standards, tuition pricing, community education, and state and institutional…

  13. Predicting landscape vegetation dynamics using state-and-transition simulation models

    Treesearch

    Colin J. Daniel; Leonardo. Frid

    2012-01-01

    This paper outlines how state-and-transition simulation models (STSMs) can be used to project changes in vegetation over time across a landscape. STSMs are stochastic, empirical simulation models that use an adapted Markov chain approach to predict how vegetation will transition between states over time, typically in response to interactions between succession,...

  14. 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.

  15. General Method for Constructing Local Hidden Variable Models for Entangled Quantum States

    NASA Astrophysics Data System (ADS)

    Cavalcanti, D.; Guerini, L.; Rabelo, R.; Skrzypczyk, P.

    2016-11-01

    Entanglement allows for the nonlocality of quantum theory, which is the resource behind device-independent quantum information protocols. However, not all entangled quantum states display nonlocality. A central question is to determine the precise relation between entanglement and nonlocality. Here we present the first general test to decide whether a quantum state is local, and show that the test can be implemented by semidefinite programing. This method can be applied to any given state and for the construction of new examples of states with local hidden variable models for both projective and general measurements. As applications, we provide a lower-bound estimate of the fraction of two-qubit local entangled states and present new explicit examples of such states, including those that arise from physical noise models, Bell-diagonal states, and noisy Greenberger-Horne-Zeilinger and W states.

  16. State-Space Modeling, System Identification and Control of a 4th Order Rotational Mechanical System

    DTIC Science & Technology

    2009-12-01

    SYSTEM IDENTIFICATION AND CONTROL OF A 4th ORDER ROTATIONAL MECHANICAL SYSTEM by Jeremiah P. Anderson December 2009 Thesis Advisor...DATES COVERED Master’s Thesis 4. TITLE AND SUBTITLE State-space Modeling, System Identification and Control of a 4th Order Rotational Mechanical...Educational Control Products is modeled from first principles and represented in state-space form. Identification of the state-space parameters was

  17. Current animal models of hemophilia: the state of the art.

    PubMed

    Yen, Ching-Tzu; Fan, Meng-Ni; Yang, Yung-Li; Chou, Sheng-Chieh; Yu, I-Shing; Lin, Shu-Wha

    2016-01-01

    Hemophilia is the most well-known hereditary bleeding disorder, with an incidence of one in every 5000 to 30,000 males worldwide. The disease is treated by infusion of protein products on demand and as prophylaxis. Although these therapies have been very successful, some challenging and unresolved tasks remain, such as reducing bleeding rates, presence of target joints and/or established joint damage, eliminating the development of inhibitors, and increasing the success rate of immune-tolerance induction (ITI). Many preclinical trials are carried out on animal models for hemophilia generated by the hemophilia research community, which in turn enable prospective clinical trials aiming to tackle these challenges. Suitable animal models are needed for greater advances in treating hemophilia, such as the development of better models for evaluation of the efficacy and safety of long-acting products, more powerful gene therapy vectors than are currently available, and successful ITI strategies. Mice, dogs, and pigs are the most commonly used animal models for hemophilia. With the advent of the nuclease method for genome editing, namely the CRISPR/Cas9 system, it is now possible to create animal models for hemophilia other than mice in a short period of time. This review presents currently available animal models for hemophilia, and discusses the importance of animal models for the development of better treatment options for hemophilia.

  18. 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

  19. Feature Detection for Model Assessment in State Estimation

    DTIC Science & Technology

    1991-10-15

    Gong Combat Control Systems Department S. C. Nardone University of Massachusetts Dartmouth DTICS ELECTE JUL 141992 DlNA Naval Underwater Systems...Assessment in State Estimation .AUTHOR(S) D. J. Ferkinhoff S. C. Nardone * J. G. Baylog K. F. Gong 7. PERFORLMING ORGANIZATION NAME(S) AND ADORESS(ES...VA 22203 11. SUPPLEMENTARY NOTES *S. C. Nardone is affiliated with the University of Massachusetts Dartmouth, North Dartmouth, MA 02747. 12

  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. Uncertainty in a Markov state model with missing states and rates: Application to a room temperature kinetic model obtained using high temperature molecular dynamics

    NASA Astrophysics Data System (ADS)

    Chatterjee, Abhijit; Bhattacharya, Swati

    2015-09-01

    Several studies in the past have generated Markov State Models (MSMs), i.e., kinetic models, of biomolecular systems by post-analyzing long standard molecular dynamics (MD) calculations at the temperature of interest and focusing on the maximally ergodic subset of states. Questions related to goodness of these models, namely, importance of the missing states and kinetic pathways, and the time for which the kinetic model is valid, are generally left unanswered. We show that similar questions arise when we generate a room-temperature MSM (denoted MSM-A) for solvated alanine dipeptide using state-constrained MD calculations at higher temperatures and Arrhenius relation — the main advantage of such a procedure being a speed-up of several thousand times over standard MD-based MSM building procedures. Bounds for rate constants calculated using probability theory from state-constrained MD at room temperature help validate MSM-A. However, bounds for pathways possibly missing in MSM-A show that alternate kinetic models exist that produce the same dynamical behaviour at short time scales as MSM-A but diverge later. Even in the worst case scenario, MSM-A is found to be valid longer than the time required to generate it. Concepts introduced here can be straightforwardly extended to other MSM building techniques.

  2. Uncertainty in a Markov state model with missing states and rates: Application to a room temperature kinetic model obtained using high temperature molecular dynamics.

    PubMed

    Chatterjee, Abhijit; Bhattacharya, Swati

    2015-09-21

    Several studies in the past have generated Markov State Models (MSMs), i.e., kinetic models, of biomolecular systems by post-analyzing long standard molecular dynamics (MD) calculations at the temperature of interest and focusing on the maximally ergodic subset of states. Questions related to goodness of these models, namely, importance of the missing states and kinetic pathways, and the time for which the kinetic model is valid, are generally left unanswered. We show that similar questions arise when we generate a room-temperature MSM (denoted MSM-A) for solvated alanine dipeptide using state-constrained MD calculations at higher temperatures and Arrhenius relation — the main advantage of such a procedure being a speed-up of several thousand times over standard MD-based MSM building procedures. Bounds for rate constants calculated using probability theory from state-constrained MD at room temperature help validate MSM-A. However, bounds for pathways possibly missing in MSM-A show that alternate kinetic models exist that produce the same dynamical behaviour at short time scales as MSM-A but diverge later. Even in the worst case scenario, MSM-A is found to be valid longer than the time required to generate it. Concepts introduced here can be straightforwardly extended to other MSM building techniques.

  3. 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.

  4. Flow behavior and applicability of models for different hemodynamic states.

    PubMed

    Cymberknop, L; Pessana, F; Armentano, R; Legnani, W; Furfaro, A

    2010-01-01

    Arterial behavior analysis requires an accurate and dynamic knowledge of the stimuli and reactions involved. Belonging parameters quantification is performed by a data acquisition process and the application of existing models. However, it turns essentially to analyze the adjustment degree of the aforementioned models in terms of the arterial tree. Blood flow behavior as well as wall shear rate and the arterial compliance are anatomic location dependent. The main objective of the present work is to analyze the existing functional relationships between arterial wall and blood flow, in a particular place (brachial artery), in order to asses the specific model applicability, in cases such Poiseuille or Womersley models. In addition, due to the characteristic of the study, gender differential dynamic responses will be evaluated.

  5. Using Strategic Planning in Marketing Education. A State Model.

    ERIC Educational Resources Information Center

    James, Richard F.

    1995-01-01

    Describes the strategic planning process used in Wisconsin to keep marketing education programs viable. Includes information about the framework, the model, and needs assessment. Stresses the importance of evaluation and implementation. (JOW)

  6. Modeling and Calculator Tools for State and Local Transportation Resources

    EPA Pesticide Factsheets

    Air quality models, calculators, guidance and strategies are offered for estimating and projecting vehicle air pollution, including ozone or smog-forming pollutants, particulate matter and other emissions that pose public health and air quality concerns.

  7. 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.

  8. 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.

  9. Current State of the Art Historic Building Information Modelling

    NASA Astrophysics Data System (ADS)

    Dore, C.; Murphy, M.

    2017-08-01

    In an extensive review of existing literature a number of observations were made in relation to the current approaches for recording and modelling existing buildings and environments: Data collection and pre-processing techniques are becoming increasingly automated to allow for near real-time data capture and fast processing of this data for later modelling applications. Current BIM software is almost completely focused on new buildings and has very limited tools and pre-defined libraries for modelling existing and historic buildings. The development of reusable parametric library objects for existing and historic buildings supports modelling with high levels of detail while decreasing the modelling time. Mapping these parametric objects to survey data, however, is still a time-consuming task that requires further research. Promising developments have been made towards automatic object recognition and feature extraction from point clouds for as-built BIM. However, results are currently limited to simple and planar features. Further work is required for automatic accurate and reliable reconstruction of complex geometries from point cloud data. Procedural modelling can provide an automated solution for generating 3D geometries but lacks the detail and accuracy required for most as-built applications in AEC and heritage fields.

  10. A Markov state modeling analysis of sliding dynamics of a 2D model

    NASA Astrophysics Data System (ADS)

    Teruzzi, M.; Pellegrini, F.; Laio, A.; Tosatti, E.

    2017-10-01

    Non-equilibrium Markov State Modeling (MSM) has recently been proposed by Pellegrini et al. [Phys. Rev. E 94, 053001 (2016)] as a possible route to construct a physical theory of sliding friction from a long steady state atomistic simulation: the approach builds a small set of collective variables, which obey a transition-matrix-based equation of motion, faithfully describing the slow motions of the system. A crucial question is whether this approach can be extended from the original 1D small size demo to larger and more realistic size systems, without an inordinate increase of the number and complexity of the collective variables. Here we present a direct application of the MSM scheme to the sliding of an island made of over 1000 harmonically bound particles over a 2D periodic potential. Based on a totally unprejudiced phase space metric and without requiring any special doctoring, we find that here too the scheme allows extracting a very small number of slow variables, necessary and sufficient to describe the dynamics of island sliding.

  11. 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.

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

    PubMed Central

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

    2017-01-01

    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

  13. 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.

  14. Mouse models of ciliopathies: the state of the art

    PubMed Central

    Norris, Dominic P.; Grimes, Daniel T.

    2012-01-01

    The ciliopathies are an apparently disparate group of human diseases that all result from defects in the formation and/or function of cilia. They include disorders such as Meckel-Grüber syndrome (MKS), Joubert syndrome (JBTS), Bardet-Biedl syndrome (BBS) and Alström syndrome (ALS). Reflecting the manifold requirements for cilia in signalling, sensation and motility, different ciliopathies exhibit common elements. The mouse has been used widely as a model organism for the study of ciliopathies. Although many mutant alleles have proved lethal, continued investigations have led to the development of better models. Here, we review current mouse models of a core set of ciliopathies, their utility and future prospects. PMID:22566558

  15. 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.

  16. Mouse models of ciliopathies: the state of the art.

    PubMed

    Norris, Dominic P; Grimes, Daniel T

    2012-05-01

    The ciliopathies are an apparently disparate group of human diseases that all result from defects in the formation and/or function of cilia. They include disorders such as Meckel-Grüber syndrome (MKS), Joubert syndrome (JBTS), Bardet-Biedl syndrome (BBS) and Alström syndrome (ALS). Reflecting the manifold requirements for cilia in signalling, sensation and motility, different ciliopathies exhibit common elements. The mouse has been used widely as a model organism for the study of ciliopathies. Although many mutant alleles have proved lethal, continued investigations have led to the development of better models. Here, we review current mouse models of a core set of ciliopathies, their utility and future prospects.

  17. 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.

  18. Exact dissipation model for arbitrary photonic Fock state transport in waveguide QED systems.

    PubMed

    Chen, Zihao; Zhou, Yao; Shen, Jung-Tsung

    2017-02-15

    We present an exact dissipation model for correlated photon transport in waveguide QED systems. This model rigorously incorporates the infinitely many degrees of freedom of the full three-dimensional photonic scattering channels in the non-excitable ambient environment. We show that the photon leakages to the scattering channels can be accounted for by a reduced Hamiltonian and a restricted eigen-state, with a resultant atomic dissipation. This model is valid for arbitrary photonic Fock and coherent states.

  19. 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.

  20. An Enhanced Steady-State Constitutive Model for Semi-solid Forming of Al7075 Based on Cross Model

    NASA Astrophysics Data System (ADS)

    Meshkabadi, Ramin; Pouyafar, Vahid; Javdani, Akbar; Faraji, Ghader

    2017-09-01

    The parameters of the Cross model were determined in a wide range of shear rates close to industrial conditions using rapid compression tests and backward extrusion experiments. The Cross model fitted well with experimental results at low shear rates, but it almost broke down at high shear rates. In this paper, a new steady-state model was proposed for semi-solid forming of Al7075 considering the effects of the yield stress, entrapped liquid, and shear rate using the Cross model. The yield stress of the alloy was estimated in the semi-solid state by extrapolating the viscosity at the least applicable shear rates. The results showed that the new model eliminated the Cross model's deviations, and it can be used for accurate prediction of the steady-state flow behavior of the semi-solid alloy in a wide range of shear rates.

  1. An Enhanced Steady-State Constitutive Model for Semi-solid Forming of Al7075 Based on Cross Model

    NASA Astrophysics Data System (ADS)

    Meshkabadi, Ramin; Pouyafar, Vahid; Javdani, Akbar; Faraji, Ghader

    2017-07-01

    The parameters of the Cross model were determined in a wide range of shear rates close to industrial conditions using rapid compression tests and backward extrusion experiments. The Cross model fitted well with experimental results at low shear rates, but it almost broke down at high shear rates. In this paper, a new steady-state model was proposed for semi-solid forming of Al7075 considering the effects of the yield stress, entrapped liquid, and shear rate using the Cross model. The yield stress of the alloy was estimated in the semi-solid state by extrapolating the viscosity at the least applicable shear rates. The results showed that the new model eliminated the Cross model's deviations, and it can be used for accurate prediction of the steady-state flow behavior of the semi-solid alloy in a wide range of shear rates.

  2. 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

  3. 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.

  4. Triplet States of Thioflavin T in Fluorescent Molecular Rotor Model

    NASA Astrophysics Data System (ADS)

    Kuz‧mitskii, V. A.; Stepuro, V. I.

    2017-01-01

    Quantum-chemical INDO/S calculations of Thiofl avin T have been carried out taking account of variation of the angle φ between the planes of the benzothiazole (BTZ) and dimethylaniline (DMA) rings. It was found that when the angle φ changes from 40° to 90° the energy of the triplet state increases by 4000 cm-1, whereas the energy of the singlet state S 1 decreases by 1900 cm-1 and reaches a minimum. The function {E}_{T_1}(φ) has a minimum at φ = 30°, which is 300 cm-1 less than at φ = 40°. The calculated T 1 S 0 interval at φ = 30-40° amounts to 15,600-16,000 cm-1, which agrees well with the phosphorescence data (17,100-17,400 cm-1). For φ = 80-90° the T 1, T 2 , and T 3 levels ( T 1 and T 2 are lower than S 1 ) are close to the S 1 level. The S 1 and T 3 levels intersect at φ 85°, and at φ = 90° the interval Δ {E}_{S_1{T}_3} amounts to only 100 cm-1 due to the small value of the exchange integral corresponding to electron transfer DMA → BTZ.

  5. A Self-Organizing Incremental Spatiotemporal Associative Memory Networks Model for Problems with Hidden State

    PubMed Central

    2016-01-01

    Identifying the hidden state is important for solving problems with hidden state. We prove any deterministic partially observable Markov decision processes (POMDP) can be represented by a minimal, looping hidden state transition model and propose a heuristic state transition model constructing algorithm. A new spatiotemporal associative memory network (STAMN) is proposed to realize the minimal, looping hidden state transition model. STAMN utilizes the neuroactivity decay to realize the short-term memory, connection weights between different nodes to represent long-term memory, presynaptic potentials, and synchronized activation mechanism to complete identifying and recalling simultaneously. Finally, we give the empirical illustrations of the STAMN and compare the performance of the STAMN model with that of other methods. PMID:27891146

  6. A generalized ingrowth model for the northeastern United States

    Treesearch

    Linda S. Gribko; Donald E. Hilt; Mary Ann Fajvan

    1995-01-01

    Ingrowth, the number of trees that periodically grow into the smallest inventoried diameter class, has long been recognized as a basic element of multicohort or, uneven-aged, stand development. However, very little information is available to aid forest managers in the estimation of ingrowth. The purpose of this study was to develop a generalized ingrowth model for the...

  7. On the stability of steady states in a granuloma model

    NASA Astrophysics Data System (ADS)

    Friedman, Avner; Lam, King-Yeung

    We consider a free boundary problem for a system of two semilinear parabolic equations. The system represents a simple model of granuloma, a collection of immune cells and bacteria filling a 3-dimensional domain Ω(t) which varies in time. We prove the existence of stationary spherical solutions and study their linear asymptotic stability as time increases to infinity.

  8. Washington State Nursing Home Administrator Model Curriculum. Final Report.

    ERIC Educational Resources Information Center

    Cowan, Florence Kelly

    The course outlines presented in this final report comprise a proposed Fort Steilacoom Community College curriculum to be used as a statewide model two-year associate degree curriculum for nursing home administrators. The eight courses described are introduction to nursing, home administration, financial management of nursing homes, nursing home…

  9. Mathematical Modeling, Sense Making, and the Common Core State Standards

    ERIC Educational Resources Information Center

    Schoenfeld, Alan H.

    2013-01-01

    On October 14, 2013 the Mathematics Education Department at Teachers College hosted a full-day conference focused on the Common Core Standards Mathematical Modeling requirements to be implemented in September 2014 and in honor of Professor Henry Pollak's 25 years of service to the school. This article is adapted from my talk at this conference…

  10. 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…

  11. Mathematical Modeling, Sense Making, and the Common Core State Standards

    ERIC Educational Resources Information Center

    Schoenfeld, Alan H.

    2013-01-01

    On October 14, 2013 the Mathematics Education Department at Teachers College hosted a full-day conference focused on the Common Core Standards Mathematical Modeling requirements to be implemented in September 2014 and in honor of Professor Henry Pollak's 25 years of service to the school. This article is adapted from my talk at this conference…

  12. 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.

  13. 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…

  14. Prevalence of Prostate Cancer Clinical States and Mortality in the United States: Estimates Using a Dynamic Progression Model

    PubMed Central

    Scher, Howard I.; Solo, Kirk; Valant, Jason; Todd, Mary B.; Mehra, Maneesha

    2015-01-01

    Objective To identify patient populations most in need of treatment across the prostate cancer disease continuum, we developed a novel dynamic transition model based on risk of disease progression and mortality. Design and Outcome Measurements We modeled the flow of patient populations through eight prostate cancer clinical states (PCCS) that are characterized by the status of the primary tumor, presence of metastases, prior and current treatment, and testosterone levels. Simulations used published US incidence rates for each year from 1990. Progression and mortality rates were derived from published clinical trials, meta-analyses, and observational studies. Model outputs included the incidence, prevalence, and mortality for each PCCS. The impact of novel treatments was modeled in three distinct scenarios: metastatic castration-resistant prostate cancer (mCRPC), non-metastatic CRPC (nmCRPC), or both. Results and Limitations The model estimated the prevalence of prostate cancer as 2,219,280 in the US in 2009 and 3,072,480 in 2020, and incidence of mCRPC as 36,100 and 42,970, respectively. All-cause mortality in prostate cancer was estimated at 168,290 in 2009 and 219,360 in 2020, with 20.5% and 19.5% of these deaths, respectively, occurring in men with mCRPC. The majority (86%) of incidence flow into mCRPC states was from the nmCRPC clinical state. In the scenario with novel interventions for nmCRPC states, the progression to mCRPC is reduced, thus decreasing mCRPC incidence by 12% in 2020, with a sustained decline in mCRPC mortality. A limitation of the model is that it does not estimate prostate cancer—specific mortality. Conclusion The model informs clinical trial design for prostate cancer by quantifying outcomes in PCCS, and demonstrates the impact of an effective therapy applied in an earlier clinical state of nmCRPC on the incidence of mCRPC morbidity and subsequent mortality. PMID:26460686

  15. FE models of stress-strain states in vascular smooth muscle cell.

    PubMed

    Bursa, Jiri; Lebis, Radek; Janicek, Premysl

    2006-01-01

    The paper deals with problems related to computational modelling of stress-strain states in vascular smooth muscle cells (SMCs). First, motivation for stress-strain analysis of SMCs is presented. Problems of their structure, geometry, constitutive models and initial (stress-free) state are analyzed on the basis of anatomical, histological and physiological knowledge. Various types of computational FE models of SMCs are presented; their constitutive models are identified on the basis of published mechanical tests carried out with SMCs cultured in vitro. Results of two models are presented; the former is a homogeneous model of the cell tension test with hyperelastic constitutive relations of the cell material. The latter model is more complex, it comprehends cortical and deep cytoskeleton, modelled as a tensegrity structure, and homogeneous linear elastic nucleus and remaining cytoplasm; it is used in computational modelling of indentation test. Perspectives, assumptions and limitations of computational modelling of SMCs under physiological load are discussed.

  16. An Ab Initio Exciton Model Including Charge-Transfer Excited States

    DOE PAGES

    Li, Xin; Parrish, Robert M.; Liu, Fang; ...

    2017-06-15

    Here, the Frenkel exciton model is a useful tool for theoretical studies of multichromophore systems. We recently showed that the exciton model could be used to coarse-grain electronic structure in multichromophoric systems, focusing on singly excited exciton states. However, our previous implementation excluded charge-transfer excited states, which can play an important role in light-harvesting systems and near-infrared optoelectronic materials. Recent studies have also emphasized the significance of charge-transfer in singlet fission, which mediates the coupling between the locally excited states and the multiexcitonic states. In this work, we report on an ab initio exciton model that incorporates charge-transfer excited statesmore » and demonstrate that the model provides correct charge-transfer excitation energies and asymptotic behavior. Comparison with TDDFT and EOM-CC2 calculations shows that our exciton model is robust with respect to system size, screening parameter, and different density functionals. Inclusion of charge-transfer excited states makes the exciton model more useful for studies of singly excited states and provides a starting point for future construction of a model that also includes double-exciton states.« less

  17. 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.

  18. A Review of Equation of State Models, Chemical Equilibrium Calculations and CERV Code Requirements for SHS Detonation Modelling

    DTIC Science & Technology

    2009-10-01

    Beattie - Bridgeman Virial expansion The above equations are suitable for moderate pressures and are usually based on either empirical constants...CR 2010-013 October 2009 A Review of Equation of State Models, Chemical Equilibrium Calculations and CERV Code Requirements for SHS Detonation...Defence R&D Canada. A Review of Equation of State Models, Chemical Equilibrium Calculations and CERV Code Requirements for SHS Detonation

  19. 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.

  20. Ground-state energy of the q-state Potts model: The minimum modularity.

    PubMed

    Lee, J S; Hwang, S; Yeo, J; Kim, D; Kahng, B

    2014-11-01

    A wide range of interacting systems can be described by complex networks. A common feature of such networks is that they consist of several communities or modules, the degree of which may quantified as the modularity. However, even a random uncorrelated network, which has no obvious modular structure, has a finite modularity due to the quenched disorder. For this reason, the modularity of a given network is meaningful only when it is compared with that of a randomized network with the same degree distribution. In this context, it is important to calculate the modularity of a random uncorrelated network with an arbitrary degree distribution. The modularity of a random network has been calculated [Reichardt and Bornholdt, Phys. Rev. E 76, 015102 (2007)PLEEE81539-375510.1103/PhysRevE.76.015102]; however, this was limited to the case whereby the network was assumed to have only two communities, and it is evident that the modularity should be calculated in general with q(≥2) communities. Here we calculate the modularity for q communities by evaluating the ground-state energy of the q-state Potts Hamiltonian, based on replica symmetric solutions assuming that the mean degree is large. We found that the modularity is proportional to 〈sqrt[k]〉/〈k〉 regardless of q and that only the coefficient depends on q. In particular, when the degree distribution follows a power law, the modularity is proportional to 〈k〉^{-1/2}. Our analytical results are confirmed by comparison with numerical simulations. Therefore, our results can be used as reference values for real-world networks.

  1. Structural models and surface equation of state for pulmonary surfactant monolayers.

    PubMed

    Zeng, Zuoxiang; Li, Dan; Xue, Weilan; Sun, Li

    2007-12-01

    A simple surface equation of state is proposed to describe pi-A isotherms of pulmonary surfactant monolayers. The monolayer is considered as undergoing three characteristic states during the compression: the disordered liquid-expanded (LE) state, the ordered liquid-condensed (LC) state and the collapse state. Structural models of pure protein (SP-B and SP-C) monolayer are proposed to interpret the behavior characteristics of monolayer in the states. The area, ALC, is defined as an instantaneous LC-state area when the monolayer is under the complete LC state. The area, At, is defined as a transition area from the ordered LC state to the collapse state. And the collapse pressure, pi(max), is defined as the maximum surface pressure that the monolayer can bear before collapse. The ideal equation of state is revised by ALC, At and pi(max), and a new equation of state is obtained, which is applicable for pure components of pulmonary surfactant. The theoretical pi-A isotherms described by the equation of state are compared with the experimental ones for SP-B, SP-C, DPPC and DPPG, and good agreements are obtained. The equation of state is generalized to protein-lipid binary mixtures by introducing mixing rules. The predicted pi-A isotherms agree with the experimental ones for various pulmonary surfactant components and the average deviation is about 9.2%.

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. Mathematical modeling of living cell metabolism using the method of steady-state stoichiometric flux balance.

    PubMed

    Drozdov-Tikhomirov, L N; Scurida, G I; Davidov, A V; Alexandrov, A A; Zvyagilskaya, R A

    2006-08-01

    This approach uses a set of algebraic linear equations for reaction rates (the method of steady-state stoichiometric flux balance) to model the purposeful metabolism of the living self-reproducing biochemical system (i.e. cell), which persists in steady-state growth. Linear programming (SIMPLEX method) is used to derive the solution for the model equations set (determining reaction rates which provide flux balance at given conditions). Here, we demonstrate the approach through the mathematical modeling of steady-state metabolism in Saccharomyces cerevisiae mitochondria.

  10. Wang-Landau algorithm for continuous models and joint density of states.

    PubMed

    Zhou, Chenggang; Schulthess, T C; Torbrügge, Stefan; Landau, D P

    2006-03-31

    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.

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

    NASA Astrophysics Data System (ADS)

    Zhou, Chenggang; Schulthess, T. C.; Torbrügge, Stefan; Landau, D. P.

    2006-03-01

    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.

  12. A multi-attribute model of prostate cancer patient's preferences for health states.

    PubMed

    Chapman, G B; Elstein, A S; Kuzel, T M; Nadler, R B; Sharifi, R; Bennett, C L

    1999-05-01

    Multi-attribute utility theory (MAUT) provides a way to model decisions involving trade-offs among different aspects or goals of a problem. We used MAUT to model prostate cancer patients' preferences for their own health state and we compared this model to patients' global judgments of health state utility. 57 patients with prostate cancer (mean age = 70) at two Chicago Veterans Administration health clinics were asked to evaluate health states described in terms of five health attributes affected by prostate cancer: pain, mood, sexual function, bladder and bowel function, and fatigue and energy. Each attribute had three levels that were used to form three clinically realistic health state descriptions (A = high, B = moderate, C = low). A fourth personalized health description (P) matched the patient's current health. We first measured patients' preferences using time trade-off (TTO) judgments for the three health states (A, B, and C) and for their own current health state (P). The TTO for the patient's own health state (P) was standardized by comparing it to TTO judgments for states A and C. We next constructed a multi-attribute model using the relative importance of the five attributes. The MAU scores were moderately correlated with the TTO preference judgments for the personalized state (Pearson r = 0.38, N = 57, p < 0.01). Thus, patients' preference judgments are moderately consistent and systematic. MAUT appears to be a potentially feasible method for evaluating preferences of prostate cancer patients and may prove helpful in assisting with patient decision making.

  13. State Growth Models for School Accountability: Progress on Development and Reporting Measures of Student Growth

    ERIC Educational Resources Information Center

    Blank, Rolf K.

    2010-01-01

    The Council of Chief State School Officers (CCSSO) is working to respond to increased interest in the use of growth models for school accountability. Growth models are based on tracking change in individual student achievement scores over multiple years. While growth models have been used for decades in academic research and program evaluation, a…

  14. Number-conserving interacting fermion models with exact topological superconducting ground states

    NASA Astrophysics Data System (ADS)

    Wang, Zhiyuan; Xu, Youjiang; Pu, Han; Hazzard, Kaden R. A.

    2017-09-01

    We present a method to construct number-conserving Hamiltonians whose ground states exactly reproduce an arbitrarily chosen BCS-type mean-field state. Such parent Hamiltonians can be constructed not only for the usual s -wave BCS state, but also for more exotic states of this form, including the ground states of Kitaev wires and two-dimensional topological superconductors. This method leads to infinite families of locally interacting fermion models with exact topological superconducting ground states. After explaining the general technique, we apply this method to construct two specific classes of models. The first one is a one-dimensional double wire lattice model with Majorana-like degenerate ground states. The second one is a two-dimensional px+i py superconducting model, where we also obtain analytic expressions for topologically degenerate ground states in the presence of vortices. Our models may provide a deeper conceptual understanding of how Majorana zero modes could emerge in condensed matter systems, as well as inspire novel routes to realize them in experiment.

  15. States versus Rewards: Dissociable neural prediction error signals underlying model-based and model-free reinforcement learning

    PubMed Central

    Gläscher, Jan; Daw, Nathaniel; Dayan, Peter; O’Doherty, John P.

    2010-01-01

    Reinforcement learning (RL) uses sequential experience with situations (“states”) and outcomes to assess actions. Whereas model-free RL uses this experience directly, in the form of a reward prediction error (RPE), model-based RL uses it indirectly, building a model of the state transition and outcome structure of the environment, and evaluating actions by searching this model. A state prediction error (SPE) plays a central role, reporting discrepancies between the current model and the observed state transitions. Using functional magnetic resonance imaging in humans solving a probabilistic Markov decision task we found the neural signature of an SPE in the intraparietal sulcus and lateral prefrontal cortex, in addition to the previously well-characterized RPE in the ventral striatum. This finding supports the existence of two unique forms of learning signal in humans, which may form the basis of distinct computational strategies for guiding behavior. PMID:20510862

  16. Modeling crisis decision-making for children in state custody.

    PubMed

    He, Xiaoxing Z; Lyons, John S; Heinemann, Allen W

    2004-01-01

    We studied 1492 children in state custody over a 6-month period to investigate the relationship between children's hospital admissions and the crisis workers' clinical assessment. A 27-item standardized decision-support tool [the Childhood Severity of Psychiatric Illness (CSPI)] was used to evaluate the symptoms, risk factors, functioning, comorbidity, and system characteristics. The CSPI has been shown to have a reliability range from 0.70 to 0.80 using intraclass correlations. Logistic regression was used to calculate age-adjusted odds ratios (AOR) of hospitalization, their 95% confidence intervals, and corresponding P values. The results showed that risk factors, symptoms, functioning, comorbidities, and system characteristics were all associated with hospital admissions. Children with a recent suicide attempt, severe danger to others, or history of running away from home/treatment settings were more likely to be hospitalized (respective AOR=12.7, P<.0001; AOR=32.3, P<.0001; AOR=3.0, P=.001). In addition, hospitalization was inversely associated with caregiver knowledge of children (AOR=0.2, P=.01) and multisystem needs (AOR=0.3, P=.04). The decision to hospitalize children psychiatrically appears to be complex. As predicted, risk behaviors and severe symptoms were independent predictors of children's hospital admissions. Interestingly, the capacity of the caregiver and the children's involvement in multiple systems also predict children's hospital admissions.

  17. Proper modelling of ligand binding requires an ensemble of bound and unbound states.

    PubMed

    Pearce, Nicholas M; Krojer, Tobias; von Delft, Frank

    2017-03-01

    Although noncovalent binding by small molecules cannot be assumed a priori to be stoichiometric in the crystal lattice, occupancy refinement of ligands is often avoided by convention. Occupancies tend to be set to unity, requiring the occupancy error to be modelled by the B factors, and residual weak density around the ligand is necessarily attributed to `disorder'. Where occupancy refinement is performed, the complementary, superposed unbound state is rarely modelled. Here, it is shown that superior accuracy is achieved by modelling the ligand as partially occupied and superposed on a ligand-free `ground-state' model. Explicit incorporation of this model of the crystal, obtained from a reference data set, allows constrained occupancy refinement with minimal fear of overfitting. Better representation of the crystal also leads to more meaningful refined atomic parameters such as the B factor, allowing more insight into dynamics in the crystal. An outline of an approach for algorithmically generating ensemble models of crystals is presented, assuming that data sets representing the ground state are available. The applicability of various electron-density metrics to the validation of the resulting models is assessed, and it is concluded that ensemble models consistently score better than the corresponding single-state models. Furthermore, it appears that ignoring the superposed ground state becomes the dominant source of model error, locally, once the overall model is accurate enough; modelling the local ground state properly is then more meaningful than correcting all remaining model errors globally, especially for low-occupancy ligands. Implications for the simultaneous refinement of B factors and occupancies, and for future evaluation of the limits of the approach, in particular its behaviour at lower data resolution, are discussed.

  18. Predicting intervention onset in the ICU with switching state space models.

    PubMed

    Ghassemi, Marzyeh; Wu, Mike; Hughes, Michael C; Szolovits, Peter; Doshi-Velez, Finale

    2017-01-01

    The impact of many intensive care unit interventions has not been fully quantified, especially in heterogeneous patient populations. We train unsupervised switching state autoregressive models on vital signs from the public MIMIC-III database to capture patient movement between physiological states. We compare our learned states to static demographics and raw vital signs in the prediction of five ICU treatments: ventilation, vasopressor administra tion, and three transfusions. We show that our learned states, when combined with demographics and raw vital signs, improve prediction for most interventions even 4 or 8 hours ahead of onset. Our results are competitive with existing work while using a substantially larger and more diverse cohort of 36,050 patients. While custom classifiers can only target a specific clinical event, our model learns physiological states which can help with many interventions. Our robust patient state representations provide a path towards evidence-driven administration of clinical interventions.

  19. State innovation models: early experiences and challenges of an initiative to advance broad health system reform.

    PubMed

    Silow-Carroll, Sharon; Lamphere, JoAnn

    2013-09-01

    The Centers for Medicare and Medicaid Services and states are partnering to transform health care systems by creating and testing new models of care delivery and payment. Interviews with officials from states participating in the State Innovation Models (SIM) Initiative reveal that the readiness of providers and payers to adopt innovations var­ies, requiring different starting points, goals, and strategies. So far, effective strategies appear to include: building on past reform efforts; redesigning health information technol­ogy to provide reliable, targeted data on care costs and quality; and using standard perfor­mance measures and financial incentives to spur alignment of providers' and payers' goals. State governments also have policy levers to encourage efficient deployment of a diverse health care workforce. As federal officials review states' innovation plans, set timetables, and provide technical assistance, they can also take steps to accommodate the budgetary, political, and time constraints that states are facing.

  20. On observation distributions for state space models of population survey data.

    PubMed

    Knape, Jonas; Jonzén, Niclas; Sköld, Martin

    2011-11-01

    1. State space models are starting to replace more simple time series models in analyses of temporal dynamics of populations that are not perfectly censused. By simultaneously modelling both the dynamics and the observations, consistent estimates of population dynamical parameters may be obtained. For many data sets, the distribution of observation errors is unknown and error models typically chosen in an ad-hoc manner. 2. To investigate the influence of the choice of observation error on inferences, we analyse the dynamics of a replicated time series of red kangaroo surveys using a state space model with linear state dynamics. Surveys were performed through aerial counts and Poisson, overdispersed Poisson, normal and log-normal distributions may all be adequate for modelling observation errors for the data. We fit each of these to the data and compare them using AIC. 3. The state space models were fitted with maximum likelihood methods using a recent importance sampling technique that relies on the Kalman filter. The method relaxes the assumption of Gaussian observation errors required by the basic Kalman filter. Matlab code for fitting linear state space models with Poisson observations is provided. 4. The ability of AIC to identify the correct observation model was investigated in a small simulation study. For the parameter values used in the study, without replicated observations, the correct observation distribution could sometimes be identified but model selection was prone to misclassification. On the other hand, when observations were replicated, the correct distribution could typically be identified. 5. Our results illustrate that inferences may differ markedly depending on the observation distributions used, suggesting that choosing an adequate observation model can be critical. Model selection and simulations show that for the models and parameter values in this study, a suitable observation model can typically be identified if observations are