Network structure of inter-industry flows
NASA Astrophysics Data System (ADS)
McNerney, James; Fath, Brian D.; Silverberg, Gerald
2013-12-01
We study the structure of inter-industry relationships using networks of money flows between industries in 45 national economies. We find these networks vary around a typical structure characterized by a Weibull link weight distribution, exponential industry size distribution, and a common community structure. The community structure is hierarchical, with the top level of the hierarchy comprising five industry communities: food industries, chemical industries, manufacturing industries, service industries, and extraction industries.
Fluctuation-dissipation theory of input-output interindustrial relations.
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.
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.
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…
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.
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.
The economic impact of the Department of Energy on the State of New Mexico Fiscal Year 1995
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.
The economic impact of the Department of Energy on the state of New Mexico fiscal year 1997
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.
The economic impact of the Department of Energy on the State of New Mexico Fiscal Year 1998
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.
Inventory of state energy models
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.
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.
Energy demand analytics using coupled technological and economic models
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...
State-induced technological change in the United States nuclear power industry 1947-1987
Bischak, G.A.
1988-01-01
The development of the nuclear power industry in the United States was the consequence of sustained state economic intervention to induce technological change and to promote the private development of civilian nuclear power. State planning, research and development funding, safety regulation and technology transfers from the military to private sector, are the principal instruments by which the state-induced technological change in nuclear power. This dissertation presents a historical and empirical analysis of the political and economic determinants of state-induced technical change. The first three chapters present an economic history showing that state research and regulatory policies determined the direction of technical change through regulation-induced innovations, while the competitive dynamics of the private-sector nuclear development determined the rate of technological change in the nuclear power industry. The next chapter presents an empirical study based on the results of a simultaneous multiple regression analysis of the inter-industry determinants of federal research intensity in the nuclear power industry and 25 other manufacturing and energy industries. A final chapter develops another two-equation simultaneous model to estimate the determinants of federal research intensity in the nuclear industry from 1961 to 1983.
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…
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
BHZ model edge states on Mobius strip
NASA Astrophysics Data System (ADS)
Mogni, Christopher; Vakaryuk, Victor; Tchernyshyov, Oleg
2014-03-01
We present analytical edge state solutions to the Bernevig-Hughes-Zhang (BHZ) model of a quantum spin hall topological insulator with Mobius geometry. The edge state solutions are obtained by solving the differential equations governing the BHZ model. The edge states satisfy both inverted periodic boundary conditions and single-valuedness boundary conditions. Furthermore, we develop a classification of boundary conditions compatible with the BHZ model insulator with Mobius geometry. We demonstrate that in the limit of large strip length that there exists a finite energy gap between the edge states. This energy gap does not exist for strips with periodic boundary conditions.
Operationalizing resilience using state and transition models
Technology Transfer Automated Retrieval System (TEKTRAN)
In management, restoration, and policy contexts, the notion of resilience can be confusing. Systematic development of conceptual models of ecological state change (state transition models; STMs) can help overcome semantic confusion and promote a mechanistic understanding of resilience. Drawing on ex...
Sandia Equation of State Model Library
2013-08-29
The software provides a general interface for querying thermodynamic states of material models along with implementation of both general and specific equation of state models. In particular, models are provided for the IAPWS-IF97 and IAPWS95 water standards as well as the associated water standards for viscosity, thermal conductivity, and surface tension. The interface supports implementation of models in a variety of independent variable spaces. Also, model support routines are included that allow for coupling ofmore » models and determination and representation of phase boundaries.« less
Sandia Equation of State Model Library
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.
Occupancy estimation and modeling with multiple states and state uncertainty
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.
Occupancy estimation and modeling with multiple states and state uncertainty.
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. PMID:17601132
Bound States in Boson Impurity Models
NASA Astrophysics Data System (ADS)
Shi, Tao; Wu, Ying-Hai; González-Tudela, A.; Cirac, J. I.
2016-04-01
The formation of bound states involving multiple particles underlies many interesting quantum physical phenomena, such as Efimov physics or superconductivity. In this work, we show the existence of an infinite number of such states for some boson impurity models. They describe free bosons coupled to an impurity and include some of the most representative models in quantum optics. We also propose a family of wave functions to describe the bound states and verify that it accurately characterizes all parameter regimes by comparing its predictions with exact numerical calculations for a one-dimensional tight-binding Hamiltonian. For that model, we also analyze the nature of the bound states by studying the scaling relations of physical quantities, such as the ground-state energy and localization length, and find a nonanalytical behavior as a function of the coupling strength. Finally, we discuss how to test our theoretical predictions in experimental platforms, such as photonic crystal structures and cold atoms in optical lattices.
A finite state model for meditation phenomena.
Waxman, J
1979-08-01
Various reports of brain wave synchrony during Transcendental Meditation have appeared in the literature and have been interpreted as indicating a heightened state of integration of brain function. We suggest that this observed synchrony rather than indicating a greater integration of brain function might be an artifact of parts of the brain acting like a finite state machine. The finite state model is developed, its properties derived and a test for the hypothesis is presented.
NASA Astrophysics Data System (ADS)
Goettle, R. J., IV; Hudson, E. A.
1980-06-01
The Gas Research Institute (GRI) needs to consider the economic impact of the various technologies whose research and development is supported by GRI funding. Three energy-economic models are useful for such a technology assessment. These models are: Energy Economic Modeling System, Energy Policy Model, and Time Stepped Energy System Optimization/Long Term Inter-Industry Transaction Model. These three models were used to help in the economic impact evaluation of various GRI research and development programs.
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.
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…
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.
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.
Optimized Markov state models for metastable systems
NASA Astrophysics Data System (ADS)
Guarnera, Enrico; Vanden-Eijnden, Eric
2016-07-01
A method is proposed to identify target states that optimize a metastability index amongst a set of trial states and use these target states as milestones (or core sets) to build Markov State Models (MSMs). If the optimized metastability index is small, this automatically guarantees the accuracy of the MSM, in the sense that the transitions between the target milestones is indeed approximately Markovian. The method is simple to implement and use, it does not require that the dynamics on the trial milestones be Markovian, and it also offers the possibility to partition the system's state-space by assigning every trial milestone to the target milestones it is most likely to visit next and to identify transition state regions. Here the method is tested on the Gly-Ala-Gly peptide, where it is shown to correctly identify the expected metastable states in the dihedral angle space of the molecule without a priori information about these states. It is also applied to analyze the folding landscape of the Beta3s mini-protein, where it is shown to identify the folded basin as a connecting hub between an helix-rich region, which is entropically stabilized, and a beta-rich region, which is energetically stabilized and acts as a kinetic trap.
Michigan State University's New Instructional Development Model.
ERIC Educational Resources Information Center
Gentry, Castelle G.; Sachs, Steven G.
Michigan State University developed a new instructional model which is a more comprehensive approach involving several instructional development consultants working with a group of faculty, a department, or an entire college. It involves specific agreements between clients and consultants before beginning the instructional development projects…
State-space models for multichannel detection
NASA Astrophysics Data System (ADS)
Roman, J. R.; Davis, D. W.
1993-07-01
In multichannel identification and detection (or model-based multichannel detection) problems the parameters of a model are identified from the observed channel process and the identified model is used to facilitate the detection of a signal in the observe process. A model-based multichannel detection algorithm was developed in the context of an innovations-based detection algorithm (IBDA) formulation for surveillance radar system applications. The state space model class was adopted to model the vector channel process because it is more general than the time series model class used in most analyses to date. An IBDA methodology was developed based on the canonical correlations algorithm which for state-space model identification offers performance advantages over alternative techniques. A computer simulation was developed to validate the methodology and the algorithm, and to carry out performance assessments. Simulation results indicate that the algorithm is capable of discriminating between the null hypothesis (clutter plus noise) and the alternative hypothesis (signal plus clutter plus noise). In summary, the applicability of the approach to radar system problems was established.
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.
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.
Input to state stability in reservoir models
NASA Astrophysics Data System (ADS)
Müller, Markus; Sierra, Carlos
2016-04-01
Models in ecology and biogeochemistry, in particular models of the global carbon cycle, can be generalized as systems of non-autonomous ordinary differential equations (ODEs). For many applications, it is important to determine the stability properties for this type of systems, but most methods available for autonomous systems are not necessarily applicable for the non-autonomous case. We discuss here stability notions for non-autonomous nonlinear models represented by systems of ODEs explicitly dependent on time and a time-varying input signal. We propose Input to State Stability (ISS) as candidate for the necessary generalization of the established analysis with respect to equilibria or invariant sets for autonomous systems, and show its usefulness by applying it to reservoir models typical for element cycling in ecosystem, e.g. in soil organic matter decomposition. We also show how ISS generalizes existent concepts formerly only available for Linear Time Invariant (LTI) and Linear Time Variant (LTV) systems to the nonlinear case.
Ground State Studies of Spin Glass Models.
NASA Astrophysics Data System (ADS)
Kolan, Amy Joanne
The ground state energy and degeneracy for a set of spin glass models, PQR models, has been studied in detail. For the pure frustration case, a subset of the general PQR case, we have studied the spacial distribution of frustrated plaquettes at T = 0. We investigated the "frustration -frustration" correlation function, which involved a series expansion analysis and a computer analysis, to examine a phase transition mechanism proposed by Schuster (1981). Schuster suggested that a pair of plaquettes is bound together above, and dissociated below a critical concentration of antiferromagnetic bonds. Our analysis, however, led us to conclude that there is no sharp "unbinding" of frustration pairs. We have developed an efficient algorithm to compute the ground state energy and degeneracy of sample PQR lattices and have studied the general PQR model numerically. Our algorithm is similar in essence to Morgenstern and Binder's (1980) transfer matrix approach used to calculate the partition function of a sample of spins in the pure frustration case. The algorithm involves computing times of order ALM 2('L), where L is the width of the lattice, M is the length, and A is a constant of proportionality. We have used the results of our analysis to investigate the possibility of a paramagnetic (<--->) spin glass phase transition in the PQR model at T = 0. Although scatter in our results for the ground state degeneracy/spin obscures evidence of a possible non-analyticity in this function, we do see evidence of a "break" in the curves for the ground state energy/spin. We have used this "break" to plot the phase transition line between the spin glass and paramagnetic regimes.
Challenges for models with composite states
NASA Astrophysics Data System (ADS)
Cline, James M.; Huang, Weicong; Moore, Guy D.
2016-09-01
Composite states of electrically charged and QCD-colored hyperquarks (HQs) in a confining SU (NHC) hypercolor gauge sector are a plausible extension of the standard model at the TeV scale and have been widely considered as an explanation for the tentative LHC diphoton excess. Additional new physics is required to avoid a stable charged hyperbaryon in such theories. We classify renormalizable models allowing the decay of this unwanted relic directly into standard model states, showing that they are significantly restricted if the new scalar states needed for UV completion are at the TeV scale. Alternatively, if hyperbaryon number is conserved, the charged relic can decay into a neutral hyperbaryon. Such theories are strongly constrained by direct detection, if the neutral constituent hyperquark carries color or weak isospin, and by LHC searches for leptoquarks if it is a color singlet. We show that the neutral hyperbaryon can have the observed relic abundance if the confinement scale and the hyperquark mass are above TeV scale, even in the absence of any hyperbaryon asymmetry.
Markov state models of biomolecular conformational dynamics
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
State energy modeling. Volume 1: An analysis of state energy modeling
NASA Astrophysics Data System (ADS)
Melcher, A. G.
1981-05-01
An inventory and analysis of state energy models were made. The inventory identified 69 models developed or used at the state government level. Most of these deal with energy demand and area mix as regards the sectors modeled and the fuel types included. Nearly all of these are econometric or econometric engineering end use models. Fewer models deal with energy supply, and several address both supply and demand. The most common types of models are econometric, engineering and use, linear programming, and input-output. Purposes of models include: forecasting; policy analysis; impact analysis; and scenario analysis. Uses include short term emergency management, long term strategic assessment, and specific applications in decisions on facility siting, utility capacity expansion and rate increases proposed legislation, and analysis of federal policy.
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.
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.
Model bridging chimera state and explosive synchronization.
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. PMID:27575120
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.
A 2-categorical state sum model
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.
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.
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.
Functional state modelling approach validation for yeast and bacteria cultivations
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
State-space models for optical imaging.
Myers, Kary L; Brockwell, Anthony E; Eddy, William F
2007-09-20
Measurement of stimulus-induced changes in activity in the brain is critical to the advancement of neuroscience. Scientists use a range of methods, including electrode implantation, surface (scalp) electrode placement, and optical imaging of intrinsic signals, to gather data capturing underlying signals of interest in the brain. These data are usually corrupted by artifacts, complicating interpretation of the signal; in the context of optical imaging, two primary sources of corruption are the heartbeat and respiration cycles. We introduce a new linear state-space framework that uses the Kalman filter to remove these artifacts from optical imaging data. The method relies on a likelihood-based analysis under the specification of a formal statistical model, and allows for corrections to the signal based on auxiliary measurements of quantities closely related to the sources of contamination, such as physiological processes. Furthermore, the likelihood-based modeling framework allows us to perform both goodness-of-fit testing and formal hypothesis testing on parameters of interest. Working with data collected by our collaborators, we demonstrate the method of data collection in an optical imaging study of a cat's brain.
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.
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.
State-space size considerations for disease-progression models.
Regnier, Eva D; Shechter, Steven M
2013-09-30
Markov models of disease progression are widely used to model transitions in patients' health state over time. Usually, patients' health status may be classified according to a set of ordered health states. Modelers lump together similar health states into a finite and usually small, number of health states that form the basis of a Markov chain disease-progression model. This increases the number of observations used to estimate each parameter in the transition probability matrix. However, lumping together observably distinct health states also obscures distinctions among them and may reduce the predictive power of the model. Moreover, as we demonstrate, precision in estimating the model parameters does not necessarily improve as the number of states in the model declines. This paper explores the tradeoff between lumping error introduced by grouping distinct health states and sampling error that arises when there are insufficient patient data to precisely estimate the transition probability matrix. PMID:23609629
State-space size considerations for disease-progression models.
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.
[State models (utopias) and sociology of medicine].
Vida, M
Social science was well developed at the end of the 18th century, but the theory or rather the methodology of sociology became a source of investigation only in the 19th century. The aspects of society were already studied in ancient times, though--since this term was not known--they thought of an omnipotent state as the only structure of human coexistence. Their judgement about the human community--what we call society today--were expressed inside the political science. In our times the investigation of sociology was primarily interested in what a real society should be, in contradiction to the philosophers of the ancient world, the Fathers of the Church in the Middle Ages and the modern natural-lawyers, who were discussing about an ideal constitutional form. They did not describe the veritable society and its occurrences, but showed a model of social conditions to their contemporaries, which had been imagined or contemplated suitable by them. Nowadays it has gradually been accepted in modern medicine that a substantial proportion in the etiology of certain diseases and the conditions of recovery have social origin. As social circumstances are natural elements of human beings, social existence impresses all functions of human body. The practical problems of prevention and therapy of diseases beside social relevances represent a special social aspect for medicine.
RNA fragment modeling with a nucleobase discrete-state model
NASA Astrophysics Data System (ADS)
Zhang, Jian; Bian, Yunqiang; Lin, Hui; Wang, Wei
2012-02-01
In this work we develop an approach for predicting the tertiary structures of RNA fragments by combining an RNA nucleobase discrete state (RNAnbds) model, a sequential Monte Carlo method, and a statistical potential. The RNAnbds model is designed for optimizing the configuration of nucleobases with respect to their preceding ones along the sequence and their spatial neighbors, in contrast to previous works that focus on RNA backbones. The tests of our approach with the fragments taken from a small RNA pseudoknot and a 23S ribosome RNA show that for short fragments (<10 nucleotides), the root mean square deviations (RMSDs) between the predicted and the experimental ones are generally smaller than 3 Å; for slightly longer fragments (10-15 nucleotides), most RMSDs are smaller than 4 Å. The comparison of our method with another physics-based predictor with a testing set containing nine loops shows that ours is superior in both accuracy and efficiency. Our approach is useful in facilitating RNA three-dimensional structure prediction as well as loop modeling. It also holds the promise of providing insight into the structural ensembles of RNA loops.
A Model for All-State Percussion Auditions.
ERIC Educational Resources Information Center
Alford, Emery E.
1985-01-01
Recommendations for student percussion auditions resulting from the Model All-State Percussion Audition Project are presented. It is hoped that state contest directors will consider their implementation. (RM)
Viral kinetic modeling: state of the art
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
Viral kinetic modeling: state of the art
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.
Viral kinetic modeling: state of the art.
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.
ERIC Educational Resources Information Center
Cole, David A.; Martin, Nina C.; Steiger, James H.
2005-01-01
The latent trait-state-error model (TSE) and the latent state-trait model with autoregression (LST-AR) represent creative structural equation methods for examining the longitudinal structure of psychological constructs. Application of these models has been somewhat limited by empirical or conceptual problems. In the present study, Monte Carlo…
Comparing State SAT Scores Using a Mixture Modeling Approach
ERIC Educational Resources Information Center
Kim, YoungKoung Rachel
2009-01-01
Presented at the national conference for AERA (American Educational Research Association) in April 2009. The large variability of SAT taker population across states makes state-by-state comparisons of the SAT scores challenging. Using a mixture modeling approach, therefore, the current study presents a method of identifying subpopulations in terms…
Development of Water Quality Modeling in the United States
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...
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…
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.
State of Modeling Symmetry in Hohlraums
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.
Nonequilibrium steady states in a model for prebiotic evolution.
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. PMID:25353526
Model abstraction results using state-space system identifications
NASA Astrophysics Data System (ADS)
Popken, Douglas A.
2000-06-01
In this paper we report on state-space system identification approaches to dynamic behavioral abstraction of military simulation models. Two stochastic simulation models were identified under a variety of scenarios. The `Attrition Simulation' is a model of two opposing forces with multiple weapon system types. The `Mission Simulation' is a model of a squadron of aircraft performing battlefield air interdiction. Four system identification techniques: Maximum Entropy, Compartmental Models, Canonical State-Space Models, and Hidden Markov Models (HMM), were applied to these simulation models. The system identification techniques were evaluated on how well their resulting abstractions replicated the distributions of the simulation states as well as the decision outputs. Encouraging results were achieved by the HMM technique applied to the Attrition Simulation--and by the Maximum Entropy technique applied to the Mission Simulation.
Minimal model for spoof acoustoelastic surface states
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.
Noninformative prior in the quantum statistical model of pure states
NASA Astrophysics Data System (ADS)
Tanaka, Fuyuhiko
2012-06-01
In the present paper, we consider a suitable definition of a noninformative prior on the quantum statistical model of pure states. While the full pure-states model is invariant under unitary rotation and admits the Haar measure, restricted models, which we often see in quantum channel estimation and quantum process tomography, have less symmetry and no compelling rationale for any choice. We adopt a game-theoretic approach that is applicable to classical Bayesian statistics and yields a noninformative prior for a general class of probability distributions. We define the quantum detection game and show that there exist noninformative priors for a general class of a pure-states model. Theoretically, it gives one of the ways that we represent ignorance on the given quantum system with partial information. Practically, our method proposes a default distribution on the model in order to use the Bayesian technique in the quantum-state tomography with a small sample.
Symmetry-breaking boundary states for WZW models
NASA Astrophysics Data System (ADS)
Blakeley, Daniel; Recknagel, Andreas
2009-01-01
Starting with the SU(2 WZW model, we construct boundary states that generically preserve only a parafermion times Virasoro subalgebra of the full affine Lie algebra symmetry of the bulk model. The boundary states come in families: intervals for generic k, quotients of SU(2) by discrete groups if k is a square. In that case, special members of the families can be viewed as superpositions of rotated Cardy branes. Using embeddings of SU(2) into higher groups, the new boundary states can be lifted to symmetry-breaking branes for other WZW models.
Skyrme models and nuclear matter equation of state
NASA Astrophysics Data System (ADS)
Adam, C.; Haberichter, M.; Wereszczynski, A.
2015-11-01
We investigate the role of pressure in a class of generalized Skyrme models. We introduce pressure as the trace of the spatial part of the energy-momentum tensor and show that it obeys the usual thermodynamical relation. Then, we compute analytically the mean-field equation of state in the high- and medium-pressure regimes by applying topological bounds on compact domains. The equation of state is further investigated numerically for the charge-one Skyrmions. We identify which term in a generalized Skyrme model is responsible for which part in the equation of state. Further, we compare our findings with the corresponding results in the Walecka model.
Oscillations and multiple steady states in active membrane transport models.
Vieira, F M; Bisch, P M
1994-01-01
The dynamic behavior of some non-linear extensions of the six-state alternating access model for active membrane transport is investigated. We use stoichio-metric network analysis to study the stability of steady states. The bifurcation analysis has been done through standard numerical methods. For the usual six-state model we have proved that there is only one steady state, which is globally asymptotically stable. When we added an autocatalytic step we found self-oscillations. For the competition between a monomer cycle and a dimer cycle, with steps of dimer formation, we have also found self-oscillations. We have also studied models involving the formation of a complex with other molecules. The addition of two steps for formation of a complex of the monomer with another molecule does not alter either the number or the stability of steady states of the basic six-state model. The model which combines the formation of a complex with an autocatalytic step shows both self-oscillations and multiple steady states. The results lead us to conclude that oscillations could be produced by active membrane transport systems if the transport cycle contains a sufficiently large number of steps (six in the present case) and is coupled to at least one autocatalytic reaction,. Oscillations are also predicted when the monomer cycle is coupled to a dimer cycle. In fact, the autocatalytic reaction can be seen as a simplification of the model involving competition between monomer and dimer cycles, which seems to be a more realistic description of biological systems. A self-regulation mechanism of the pumps, related to the multiple stationary states, is expected only for a combined effect of autocatalysis and formation of complexes with other molecules. Within the six-state model this model also leads to oscillation.
Metropolitan and state economic regions (MASTER) model - overview
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.
Solvable Model for Chimera States of Coupled Oscillators
NASA Astrophysics Data System (ADS)
Abrams, Daniel M.; Mirollo, Rennie; Strogatz, Steven H.; Wiley, Daniel A.
2008-08-01
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.
Solvable model for chimera states of coupled oscillators.
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.
Steady states in Leith's model of turbulence
NASA Astrophysics Data System (ADS)
Grebenev, V. N.; Griffin, A.; Medvedev, S. B.; Nazarenko, S. V.
2016-09-01
We present a comprehensive study and full classification of the stationary solutions in Leith’s model of turbulence with a generalised viscosity. Three typical types of boundary value problems are considered: Problems 1 and 2 with a finite positive value of the spectrum at the left (right) and zero at the right (left) boundaries of a wave number range, and Problem 3 with finite positive values of the spectrum at both boundaries. Settings of these problems and analysis of existence of their solutions are based on a phase-space analysis of orbits of the underlying dynamical system. One of the two fixed points of the underlying dynamical system is found to correspond to a ‘sharp front’ where the energy flux and the spectrum vanish at the same wave number. The other fixed point corresponds to the only exact power-law solution—the so-called dissipative scaling solution. The roles of the Kolmogorov, dissipative and thermodynamic scaling, as well as of sharp front solutions, are discussed.
Steady states in Leith's model of turbulence
NASA Astrophysics Data System (ADS)
Grebenev, V. N.; Griffin, A.; Medvedev, S. B.; Nazarenko, S. V.
2016-09-01
We present a comprehensive study and full classification of the stationary solutions in Leith’s model of turbulence with a generalised viscosity. Three typical types of boundary value problems are considered: Problems 1 and 2 with a finite positive value of the spectrum at the left (right) and zero at the right (left) boundaries of a wave number range, and Problem 3 with finite positive values of the spectrum at both boundaries. Settings of these problems and analysis of existence of their solutions are based on a phase–space analysis of orbits of the underlying dynamical system. One of the two fixed points of the underlying dynamical system is found to correspond to a ‘sharp front’ where the energy flux and the spectrum vanish at the same wave number. The other fixed point corresponds to the only exact power-law solution—the so-called dissipative scaling solution. The roles of the Kolmogorov, dissipative and thermodynamic scaling, as well as of sharp front solutions, are discussed.
Infinite Factorial Unbounded-State Hidden Markov Model.
Valera, Isabel; Ruiz, Francisco J R; Perez-Cruz, Fernando
2016-09-01
There are many scenarios in artificial intelligence, signal processing or medicine, in which a temporal sequence consists of several unknown overlapping independent causes, and we are interested in accurately recovering those canonical causes. Factorial hidden Markov models (FHMMs) present the versatility to provide a good fit to these scenarios. However, in some scenarios, the number of causes or the number of states of the FHMM cannot be known or limited a priori. In this paper, we propose an infinite factorial unbounded-state hidden Markov model (IFUHMM), in which the number of parallel hidden Markovmodels (HMMs) and states in each HMM are potentially unbounded. We rely on a Bayesian nonparametric (BNP) prior over integer-valued matrices, in which the columns represent the Markov chains, the rows the time indexes, and the integers the state for each chain and time instant. First, we extend the existent infinite factorial binary-state HMM to allow for any number of states. Then, we modify this model to allow for an unbounded number of states and derive an MCMC-based inference algorithm that properly deals with the trade-off between the unbounded number of states and chains. We illustrate the performance of our proposed models in the power disaggregation problem. PMID:26571511
Resilience-based application of state-and-transition models
Technology Transfer Automated Retrieval System (TEKTRAN)
We recommend that several conceptual modifications be incorporated into the state-and-transition model (STM) framework to: 1) explicitly link this framework to the concept of ecological resilience, 2) direct management attention away from thresholds and toward the maintenance of state resilience, an...
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…
Parameter redundancy in discrete state-space and integrated models.
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.
A comparison of weighted ensemble and Markov state model methodologies.
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.
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.
Coherent States for the Finite su(2)-OSCILLATOR Model
NASA Astrophysics Data System (ADS)
Vicent, Luis Edgar
A finite oscillator is a system that has a discrete and finite number of spatial positions and energy levels accessible. The su(2)-oscillator model takes the generators of the angular momentum su(2) algebra and, giving to each one a definite physical interpretation, provides a consistent mathematical description of a finite oscillator. This work searches an example of identification of generalized coherent states, within the collection of states and wavefunctions of the finite su(2) oscillator model.
Modeling Per Capita State Health Expenditure Variation: State-Level Characteristics Matter
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
Analysis and Modelling of the Steady-State and Dynamic-State Discharge in SMES System
NASA Astrophysics Data System (ADS)
Chen, Xiao Yuan; Jin, Jian Xun
The steady-state and dynamic-state discharge processes have been discussed to develop a superconducting magnetic energy storage (SMES) model in the paper. The SMES model allows the integrated analysis and optimization of the SMES devices, and their control systems, and can also serve as an independent storage module in the practical SMES application circuits, thus provide a method to link superconductivity technology to conventional power electronics in a SMES device.
Neural mass model-based tracking of anesthetic brain states.
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
Excited-state quantum phase transitions in Dicke superradiance models.
Brandes, Tobias
2013-09-01
We derive analytical results for various quantities related to the excited-state quantum phase transitions in a class of Dicke superradiance models in the semiclassical limit. Based on a calculation of a partition sum restricted to Dicke states, we discuss the singular behavior of the derivative of the density of states and find observables such as the mean (atomic) inversion and the boson (photon) number and its fluctuations at arbitrary energies. Criticality depends on energy and a parameter that quantifies the relative weight of rotating versus counterrotating terms, and we find a close analogy to the logarithmic and jump-type nonanalyticities known from the Lipkin-Meshkov-Glick model. PMID:24125239
Compact Two-State-Variable Second-Order Memristor Model.
Kim, Sungho; Kim, Hee-Dong; Choi, Sung-Jin
2016-06-01
A key requirement for using memristors in functional circuits is a predictive physical model to capture the resistive switching behavior, which shall be compact enough to be implemented using a circuit simulator. Although a number of memristor models have been developed, most of these models (i.e., first-order memristor models) have utilized only a one-state-variable. However, such simplification is not adequate for accurate modeling because multiple mechanisms are involved in resistive switching. Here, a two-state-variable based second-order memristor model is presented, which considers the axial drift of the charged vacancies in an applied electric field and the radial vacancy motion caused by the thermophoresis and diffusion. In particular, this model emulates the details of the intrinsic short-term dynamics, such as decay and temporal heat summation, and therefore, it accurately predicts the resistive switching characteristics for both DC and AC input signals. PMID:27152649
Compact Two-State-Variable Second-Order Memristor Model.
Kim, Sungho; Kim, Hee-Dong; Choi, Sung-Jin
2016-06-01
A key requirement for using memristors in functional circuits is a predictive physical model to capture the resistive switching behavior, which shall be compact enough to be implemented using a circuit simulator. Although a number of memristor models have been developed, most of these models (i.e., first-order memristor models) have utilized only a one-state-variable. However, such simplification is not adequate for accurate modeling because multiple mechanisms are involved in resistive switching. Here, a two-state-variable based second-order memristor model is presented, which considers the axial drift of the charged vacancies in an applied electric field and the radial vacancy motion caused by the thermophoresis and diffusion. In particular, this model emulates the details of the intrinsic short-term dynamics, such as decay and temporal heat summation, and therefore, it accurately predicts the resistive switching characteristics for both DC and AC input signals.
A nonlocal, ordinary, state-based plasticity model for peridynamics.
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.
Modeling solid-state transformations occurring in dissolution testing.
Laaksonen, Timo; Aaltonen, Jaakko
2013-04-15
Changes in the solid-state form can occur during dissolution testing of drugs. This can often complicate interpretation of results. Additionally, there can be several mechanisms through which such a change proceeds, e.g. solvent-mediated transformation or crystal growth within the drug material itself. Here, a mathematical model was constructed to study the dissolution testing of a material, which undergoes such changes. The model consisted of two processes: the recrystallization of the drug from a supersaturated liquid state caused by the dissolution of the more soluble solid form and the crystal growth of the stable solid form at the surface of the drug formulation. Comparison to experimental data on theophylline dissolution showed that the results obtained with the model matched real solid-state changes and that it was able to distinguish between cases where the transformation was controlled either by solvent-mediated crystallization or solid-state crystal growth. PMID:23506958
Ontology and modeling patterns for state-based behavior representation
NASA Technical Reports Server (NTRS)
Castet, Jean-Francois; Rozek, Matthew L.; Ingham, Michel D.; Rouquette, Nicolas F.; Chung, Seung H.; Kerzhner, Aleksandr A.; Donahue, Kenneth M.; Jenkins, J. Steven; Wagner, David A.; Dvorak, Daniel L.; Karban, Robert
2015-01-01
This paper provides an approach to capture state-based behavior of elements, that is, the specification of their state evolution in time, and the interactions amongst them. Elements can be components (e.g., sensors, actuators) or environments, and are characterized by state variables that vary with time. The behaviors of these elements, as well as interactions among them are represented through constraints on state variables. This paper discusses the concepts and relationships introduced in this behavior ontology, and the modeling patterns associated with it. Two example cases are provided to illustrate their usage, as well as to demonstrate the flexibility and scalability of the behavior ontology: a simple flashlight electrical model and a more complex spacecraft model involving instruments, power and data behaviors. Finally, an implementation in a SysML profile is provided.
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…
Periodic ground state for the charged massive Schwinger model
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.
Simulation of the 3-state Potts model with chemical potential
Mercado, Ydalia Delgado; Gattringer, Christof; Evertz, Hans Gerd
2011-05-23
The 3-state Potts model with chemical potential is mapped to a flux representation where the complex action problem is resolved. We perform a Monte Carlo simulation based on a worm algorithm to study the phase diagram of the model. Our results shed light on the role which center symmetry and its breaking play for the QCD phase diagram.
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.
Chan, H S
2000-09-01
A well-established experimental criterion for two-state thermodynamic cooperativity in protein folding is that the van't Hoff enthalpy DeltaH(vH) around the transition midpoint is equal, or very nearly so, to the calorimetric enthalpy DeltaH(cal) of the entire transition. This condition is satisfied by many small proteins. We use simple lattice models to provide a statistical mechanical framework to elucidate how this calorimetric two-state picture may be reconciled with the hierarchical multistate scenario emerging from recent hydrogen exchange experiments. We investigate the feasibility of using inverse Laplace transforms to recover the underlying density of states (i.e., enthalpy distribution) from calorimetric data. We find that the constraint imposed by DeltaH(vH)/DeltaH(cal) approximately 1 on densities of states of proteins is often more stringent than other "two-state" criteria proposed in recent theoretical studies. In conjunction with reasonable assumptions, the calorimetric two-state condition implies a narrow distribution of denatured-state enthalpies relative to the overall enthalpy difference between the native and the denatured conformations. This requirement does not always correlate with simple definitions of "sharpness" of a transition and has important ramifications for theoretical modeling. We find that protein models that assume capillarity cooperativity can exhibit overall calorimetric two-state-like behaviors. However, common heteropolymer models based on additive hydrophobic-like interactions, including highly specific two-dimensional Gō models, fail to produce proteinlike DeltaH(vH)/DeltaH(cal) approximately 1. A simple model is constructed to illustrate a proposed scenario in which physically plausible local and nonlocal cooperative terms, which mimic helical cooperativity and environment-dependent hydrogen bonding strength, can lead to thermodynamic behaviors closer to experiment. Our results suggest that proteinlike thermodynamic
Multiple time scales in multi-state models.
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. PMID:24027131
Multistage carcinogenesis modeling including cell cycle and DNA damage states
NASA Astrophysics Data System (ADS)
Hazelton, W.; Moolgavkar, S.
The multistage clonal expansion model of carcinogenesis is generalized to include cell cycle states and corresponding DNA damage states with imperfect repair for normal and initiated stem cells. Initiated cells may undergo transformation to a malignant state, eventually leading to cancer incidence or death. The model allows oxidative or radiation induced DNA damage, checkpoint delay, DNA repair, apoptosis, and transformation rates to depend on the cell cycle state or DNA damage state of normal and initiated cells. A probability generating function approach is used to represent the time dependent probability distribution for cells in all states. The continuous time coupled Markov system representing this joint distribution satisfies a partial differential equation (pde). Time dependent survival and hazard functions are found through numerical solution of the characteristic equations for the pde. Although the hazard and survival can be calculated numerically, number and size distributions of pre-malignant lesions from models that are developed will be approximated through simulation. We use the model to explore predictions for hazard and survival as parameters representing cell cycle regulation and arrest are modified. Modification of these parameters may influence rates for cell division, apoptosis and malignant transformation that are important in carcinogenesis. We also explore enhanced repair that may be important for low-dose hypersensitivity and adaptive response, and degradation of repair processes or loss of checkpoint control that may drive genetic instability.
Modeling state-dependent inactivation of membrane currents.
Marom, S; Abbott, L F
1994-01-01
Inactivation of many ion channels occurs through largely voltage-independent transitions to an inactivated state from the open state or from other states in the pathway leading to opening of the channel. Because this form of inactivation is state-dependent rather than voltage-dependent, it cannot be described by the standard Hodgkin-Huxley formalism used in virtually all modeling studies of neuronal behavior. Using two examples, cumulative inactivation of the Kv3 potassium channel and inactivation of the fast sodium channel, we extend the standard formalism for modeling macroscopic membrane currents to account for state-dependent inactivation. Our results provide an accurate description of cumulative inactivation of the Kv3 channel, new insight into inactivation of the sodium channel, and a general framework for modeling macroscopic currents when state-dependent processes are involved. In a model neuron, the macroscopic Kv3 current produces a novel short-term memory effect and firing delays similar to those seen in hippocampal neurons. Images FIGURE 5 PMID:7524708
Identifying state-dependent model error in numerical weather prediction
NASA Astrophysics Data System (ADS)
Moskaitis, J.; Hansen, J.; Toth, Z.; Zhu, Y.
2003-04-01
Model forecasts of complex systems such as the atmosphere lose predictive skill because of two different sources of error: initial conditions error and model error. While much study has been done to determine the nature and consequences of initial conditions error in operational forecast models, relatively little has been done to identify the source of model error and to quantify the effects of model error on forecasts. Here, we attempt to "disentangle" model error from initial conditions error by applying a diagnostic tool in a simple model framework to identify poor forecasts for which model error is likely responsible. The diagnostic is based on the premise that for a perfect ensemble forecast, verification should fall outside the range of ensemble forecast states only a small percentage of the time, according to the size of the ensemble. Identifying these outlier verifications and comparing the statistics of their occurrence to those of a perfect ensemble can tell us about the role of model error in a quantitative, state-dependent manner. The same diagnostic is applied to operational NWP models to quantify the role of model error in poor forecasts (see companion paper by Toth et al.). From these results, we can infer the atmospheric processes the model cannot adequately simulate.
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
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.
Animal Models of Psychosis: Current State and Future Directions
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
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.
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.
Equation of State of the Two-Dimensional Hubbard Model.
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.
Equation of State of the Two-Dimensional Hubbard Model.
Cocchi, Eugenio; Miller, Luke A; Drewes, Jan H; Koschorreck, Marco; Pertot, Daniel; Brennecke, Ferdinand; Köhl, Michael
2016-04-29
The subtle interplay between kinetic energy, interactions, and dimensionality challenges our comprehension of strongly correlated physics observed, for example, in the solid state. In this quest, the Hubbard model has emerged as a conceptually simple, yet rich model describing such physics. Here we present an experimental determination of the equation of state of the repulsive two-dimensional Hubbard model over a broad range of interactions 0≲U/t≲20 and temperatures, down to k_{B}T/t=0.63(2) using high-resolution imaging of ultracold fermionic atoms in optical lattices. We show density profiles, compressibilities, and double occupancies over the whole doping range, and, hence, our results constitute benchmarks for state-of-the-art theoretical approaches. PMID:27176527
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.
Multi-state succession in wetlands: a novel use of state and transition models
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
Multi-state succession in wetlands: a novel use of state and transition models.
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
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.
Steady States and Universal Conductance in a Quenched Luttinger Model
NASA Astrophysics Data System (ADS)
Langmann, Edwin; Lebowitz, Joel L.; Mastropietro, Vieri; Moosavi, Per
2016-05-01
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 &infty}; , 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.
Exploring extensions to multi-state models with multiple unobservable states
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
STEADY-STATE MODEL OF SOLAR WIND ELECTRONS REVISITED
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.
Equations of state for explosive detonation products: The PANDA model
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.
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.
State Dependence of Network Output: Modeling and Experiments
Nadim, Farzan; Brezina, Vladimir; Destexhe, Alain; Linster, Christiane
2008-01-01
Emerging experimental evidence suggests that both networks and their component neurons respond to similar inputs differently depending on the state of network activity. The network state is determined by the intrinsic dynamical structure of the network and may change as a function of neuromodulation, the balance or stochasticity of synaptic inputs to the network and the history of network activity. Much of the knowledge on state-dependent effects comes from comparisons of awake and sleep states of the mammalian brain. Yet, the mechanisms underlying these states are difficult to unravel. Several vertebrate and invertebrate studies have elucidated cellular and synaptic mechanisms of state-dependence resulting from neuromodulation, sensory input, and experience. Recent studies have combined modeling and experiments to examine the computational principles that emerge when network state is taken into account; these studies are highlighted in this article. We discuss these principles in a variety of systems (mammalian, crustacean, and mollusk) to demonstrate the unifying theme of state-dependence of network output. PMID:19005044
On rate-state and Coulomb failure models
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
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.
Testing Transition State Theory on Kac-Zwanzig Model
NASA Astrophysics Data System (ADS)
Ariel, G.; vanden-Eijnden, E.
2007-01-01
A variant of the Kac-Zwanzig model is used to test the prediction of transition state theory (TST) and variational transition state theory (VTST). The model describes the evolution of a distinguished particle moving in a double-well external potential and coupled to N free particles through linear springs. While the Kac-Zwanzig model is deterministic, under appropriate choice of the model parameters the evolution of the distinguished particle can be approximated by a two-state Markov chain whose transition rate constants can be computed exactly in suitable limit. Here, these transition rate constants are compared with the predictions of TST and VTST. It is shown that the application of TST with a naive (albeit natural) choice of dividing surface leads to the wrong prediction of the transition rate constants. This is due to crossings of the dividing surface that do not correspond to actual transition events. However, optimizing over the dividing surface within VTST allows one to eliminate completely these spurious crossings, and therefore derive the correct transition rate constants for the model. The reasons why VTST is successful in this model are discussed, which allows one to speculate on the reliability of VTST in more complicated systems.
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…
Spatially-explicit representation of state-and-transition models
Technology Transfer Automated Retrieval System (TEKTRAN)
The broad-scale assessment of natural resource conditions (e.g., rangeland health, restoration needs) requires knowledge of their spatial distribution. We argue that creating a database that links state-and-transition models (STMs) to spatial units is a valuable management tool for structuring groun...
Practical guidance for developing state-and-transition models
Technology Transfer Automated Retrieval System (TEKTRAN)
State-and-transition models (STMs) are synthetic descriptions of the dynamics of vegetation and surface soils occurring within specific ecological sites. STMs consist of a diagram and narratives that describe the dynamics and its causes. STMs are developed using a broad array of evidence including h...
Phase transitions for rotational states within an algebraic cluster model
NASA Astrophysics Data System (ADS)
López Moreno, E.; Morales Hernández, G. E.; Hess, P. O.; Yépez Martínez, H.
2016-07-01
The ground state and excited, rotational phase transitions are investigated within the Semimicroscopic Algebraic Cluster Model (SACM). The catastrophe theory is used to describe these phase transitions. Short introductions to the SACM and the catastrophe theory are given. We apply the formalism to the case of 16O+α→20Ne.
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.
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.
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)
Forward Models and State Estimation in Compensatory Eye Movements
Frens, Maarten A.; Donchin, Opher
2009-01-01
The compensatory eye movement (CEM) system maintains a stable retinal image, integrating information from different sensory modalities to compensate for head movements. Inspired by recent models of the physiology of limb movements, we suggest that CEM can be modeled as a control system with three essential building blocks: a forward model that predicts the effects of motor commands; a state estimator that integrates sensory feedback into this prediction; and, a feedback controller that translates a state estimate into motor commands. We propose a specific mapping of nuclei within the CEM system onto these control functions. Specifically, we suggest that the Flocculus is responsible for generating the forward model prediction and that the Vestibular Nuclei integrate sensory feedback to generate an estimate of current state. Finally, the brainstem motor nuclei – in the case of horizontal compensation this means the Abducens Nucleus and the Nucleus Prepositus Hypoglossi – implement a feedback controller, translating state into motor commands. While these efforts to understand the physiological control system as a feedback control system are in their infancy, there is the intriguing possibility that CEM and targeted voluntary movements use the same cerebellar circuitry in fundamentally different ways. PMID:19956563
NASA Astrophysics Data System (ADS)
Li, Xiangzhu; Paldus, Josef
2010-11-01
The concept of C-conditions, originally introduced in the framework of the multireference (MR), general-model-space (GMS), state-universal (SU), coupled-cluster (CC) approach with singles and doubles (GMS-SU-CCSD) to account for the internal amplitudes that vanish in the case of a complete model space, is applied to a state-selective or state-specific Mukherjee MR-CC method (MkCCSD). In contrast to the existing applications, the emphasis is on the description of excited states, particularly those belonging to the same symmetry species. The applicability of the C-conditions in all MR-SU-CC approaches is emphasized. Convergence problems encountered in the MkCCSD method when handling higher-lying states are pointed out. The performance of the GMS-SU-CCSD and MkCCSD methods is illustrated by considering low-lying vertical excitation energies of the ethylene molecule and para-benzyne diradical. A comparison with the equation-of-motion CCSD results, as well as with the available experimental data and recent multireference configuration interaction theoretical results, is also provided.
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.
Trait and state anxiety in animal models: Is there correlation?
Goes, Tiago Costa; Antunes, Fabrício Dias; Teixeira-Silva, Flavia
2009-02-01
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.
Open-state models of a potassium channel.
Biggin, Philip C; Sansom, Mark S P
2002-01-01
The structure of the bacterial potassium channel, KcsA, corresponds to the channel in a closed state. Two lines of evidence suggest that the channel must widen its intracellular mouth when in an open state: 1) internal block by a series of tetraalkylammonium ions and 2) spin labeling experiments. Thus it is known that the protein moves in this region, but it is unclear by how much and the mechanisms that are involved. To address this issue we have applied a novel approach to generate plausible open-state models of KcsA. The approach can be thought of as placing a balloon inside the channel and gradually inflating it. Only the protein sees the balloon, and so water is free to move in and out of the channel. The balloon is a van der Waals sphere whose parameters change by a small amount at each time step, an approach similar to methods used in free energy perturbation calculations. We show that positioning of this balloon at various positions along the pore axis generates similar open-state models, thus indicating that there may be a preferred pathway to an open state. We also show that the resulting structures from this process are conformationally unstable and need to undergo a relaxation process for up to 4 ns. We show that the channel can relax into a new state that has a larger pore radius at the region of the intracellular mouth. The resulting models may be useful in exploring models of the channel in the context of ion permeation and blocking agents. PMID:12324408
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.
The two-state dimer receptor model: a general model for receptor dimers.
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.
Energy modeling. Volume 2: Inventory and details of state energy models
NASA Astrophysics Data System (ADS)
Melcher, A. G.; Underwood, R. G.; Weber, J. C.; Gist, R. L.; Holman, R. P.; Donald, D. W.
1981-05-01
An inventory of energy models developed by or for state governments is presented, and certain models are discussed in depth. These models address a variety of purposes such as: supply or demand of energy or of certain types of energy; emergency management of energy; and energy economics. Ten models are described. The purpose, use, and history of the model is discussed, and information is given on the outputs, inputs, and mathematical structure of the model. The models include five models dealing with energy demand, one of which is econometric and four of which are econometric-engineering end-use models.
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.
Orbit sequential estimation using the unified state model
NASA Astrophysics Data System (ADS)
Neto, Ernesto Vieira
1994-02-01
The hodographic theory, developed first by Hamilton/Mobius in the middle of the nineteenth century and reintroduced by Altman in the 1960's, is presented in this work as the basis for the orbital unified state model in the orbit determination of artificial satellites. The full model defines the trajectory and attitude dynamics of an orbital spacecraft and enables efficient and rapid machine computation for mission analysis, orbit determination, and prediction. In this work, the orbital part of the model, together with the Kalman filter, is implemented for the orbit determination problem and the results are compared with conventional formulations.
Modeling species occurrence dynamics with multiple states and imperfect detection
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.
Dynamic models for problems of species occurrence with multiple states
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.
Modeling species occurrence dynamics with multiple states and imperfect detection.
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. PMID:19341151
Magnon edge states in the hardcore- Bose-Hubbard model.
Owerre, S A
2016-11-01
Quantum Monte Carlo (QMC) simulation has uncovered nonzero Berry curvature and bosonic edge states in the hardcore-Bose-Hubbard model on the gapped honeycomb lattice. The competition between the chemical potential and staggered onsite potential leads to an interesting quantum phase diagram comprising the superfluid phase, Mott insulator, and charge density wave insulator. In this paper, we present a semiclassical perspective of this system by mapping to a spin-1/2 quantum XY model. We give an explicit analytical origin of the quantum phase diagram, the Berry curvatures, and the edge states using semiclassical approximations. We find very good agreement between the semiclassical analyses and the QMC results. Our results show that the topological properties of the hardcore-Bose-Hubbard model are the same as those of magnon in the corresponding quantum spin system. Our results are applicable to systems of ultracold bosonic atoms trapped in honeycomb optical lattices. PMID:27603092
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.
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.
State-time spectrum of signal transduction logic models
NASA Astrophysics Data System (ADS)
MacNamara, Aidan; Terfve, Camille; Henriques, David; Peñalver Bernabé, Beatriz; Saez-Rodriguez, Julio
2012-08-01
Despite the current wealth of high-throughput data, our understanding of signal transduction is still incomplete. Mathematical modeling can be a tool to gain an insight into such processes. Detailed biochemical modeling provides deep understanding, but does not scale well above relatively a few proteins. In contrast, logic modeling can be used where the biochemical knowledge of the system is sparse and, because it is parameter free (or, at most, uses relatively a few parameters), it scales well to large networks that can be derived by manual curation or retrieved from public databases. Here, we present an overview of logic modeling formalisms in the context of training logic models to data, and specifically the different approaches to modeling qualitative to quantitative data (state) and dynamics (time) of signal transduction. We use a toy model of signal transduction to illustrate how different logic formalisms (Boolean, fuzzy logic and differential equations) treat state and time. Different formalisms allow for different features of the data to be captured, at the cost of extra requirements in terms of computational power and data quality and quantity. Through this demonstration, the assumptions behind each formalism are discussed, as well as their advantages and disadvantages and possible future developments.
Mathematical model for Dengue with three states of infection
NASA Astrophysics Data System (ADS)
Hincapie, Doracelly; Ospina, Juan
2012-06-01
A mathematical model for dengue with three states of infection is proposed and analyzed. The model consists in a system of differential equations. The three states of infection are respectively asymptomatic, partially asymptomatic and fully asymptomatic. The model is analyzed using computer algebra software, specifically Maple, and the corresponding basic reproductive number and the epidemic threshold are computed. The resulting basic reproductive number is an algebraic synthesis of all epidemic parameters and it makes clear the possible control measures. The microscopic structure of the epidemic parameters is established using the quantum theory of the interactions between the atoms and radiation. In such approximation, the human individual is represented by an atom and the mosquitoes are represented by radiation. The force of infection from the mosquitoes to the humans is considered as the transition probability from the fundamental state of atom to excited states. The combination of computer algebra software and quantum theory provides a very complete formula for the basic reproductive number and the possible control measures tending to stop the propagation of the disease. It is claimed that such result may be important in military medicine and the proposed method can be applied to other vector-borne diseases.
MODELING THE DEMAND FOR E85 IN THE UNITED STATES
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.
Modelling and simulation of large solid state laser systems
Simmons, W.W.; Warren, W.E.
1986-01-01
The role of numerical methods to simulate the several physical processes (e.g., diffraction, self-focusing, gain saturation) that are involved in coherent beam propagation through large laser systems is discussed. A comprehensive simulation code for modeling the pertinent physical phenomena observed in laser operations (growth of small-scale modulation, spatial filter, imaging, gain saturation and beam-induced damage) is described in some detail. Comparisons between code results and solid state laser output performance data are presented. Design and performance estimation of the large Nova laser system at LLNL are given. Finally, a global design rule for large, solid state laser systems is discussed.
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.
Simulated models of perturbed angular correlation (PAC) spectroscopy in a 4-state+S system
NASA Astrophysics Data System (ADS)
Hodges, Jeffery A.; Stufflebeam, Michael A.; Evenson, William E.; Matheson, P.; Zacate, M. O.
2007-10-01
Cerium oxide has a cubic crystal structure. A vacancy in CeO2 can be trapped by a probe atom and hop among equivalent 1st or 2nd neighbor sites of the probe, producing a fluctuating electric field gradient (EFG) at the probe nucleus. We have simulated the perturbed angular correlation (PAC) spectrum due to such a changing EFG (4-state model), as well as the case with an additional static background EFG (4-state+S). We have studied the effect of changing the defect hopping rates on the resulting spectrum and the inferred hyperfine parameters. We have analyzed these data to determine experimental conditions under which nonequilibrium initial probe distributions can be detected by PAC.
Evaluation of the Current State of Integrated Water Quality Modelling
NASA Astrophysics Data System (ADS)
Arhonditsis, G. B.; Wellen, C. C.; Ecological Modelling Laboratory
2010-12-01
Environmental policy and management implementation require robust methods for assessing the contribution of various point and non-point pollution sources to water quality problems as well as methods for estimating the expected and achieved compliance with the water quality goals. Water quality models have been widely used for creating the scientific basis for management decisions by providing a predictive link between restoration actions and ecosystem response. Modelling water quality and nutrient transport is challenging due a number of constraints associated with the input data and existing knowledge gaps related to the mathematical description of landscape and in-stream biogeochemical processes. While enormous effort has been invested to make watershed models process-based and spatially-distributed, there has not been a comprehensive meta-analysis of model credibility in watershed modelling literature. In this study, we evaluate the current state of integrated water quality modeling across the range of temporal and spatial scales typically utilized. We address several common modeling questions by providing a quantitative assessment of model performance and by assessing how model performance depends on model development. The data compiled represent a heterogeneous group of modeling studies, especially with respect to complexity, spatial and temporal scales and model development objectives. Beginning from 1992, the year when Beven and Binley published their seminal paper on uncertainty analysis in hydrological modelling, and ending in 2009, we selected over 150 papers fitting a number of criteria. These criteria involved publications that: (i) employed distributed or semi-distributed modelling approaches; (ii) provided predictions on flow and nutrient concentration state variables; and (iii) reported fit to measured data. Model performance was quantified with the Nash-Sutcliffe Efficiency, the relative error, and the coefficient of determination. Further, our
A Bayesian state-space formulation of dynamic occupancy models
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
Modeling of Material Removal by Solid State Heat Capacity Lasers
Boley, C D; Rubenchik, A M
2002-04-17
Pulsed lasers offer the capability of rapid material removal. Here we present simulations of steel coupon tests by two solid state heat capacity lasers built at LLNL. Operating at 1.05 pm, these deliver pulse energies of about 80 J at 10 Hz, and about 500 J at 20 Hz. Each is flashlamp-pumped. The first laser was tested at LLNL, while the second laser has been delivered to HELSTF, White Sands Missile Range. Liquid ejection appears to be an important removal mechanism. We have modeled these experiments via a time-dependent code called THALES, which describes heat transport, melting, vaporization, and the hydrodynamics of liquid, vapor, and air. It was previously used, in a less advanced form, to model drilling by copper vapor lasers [1] . It was also used to model vaporization in beam dumps for a high-power laser [2]. The basic model is in 1D, while the liquid hydrodynamics is handled in 2D.
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.
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.
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.
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.
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.
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.
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
Local hidden-variable models for entangled quantum states
NASA Astrophysics Data System (ADS)
Augusiak, R.; Demianowicz, M.; Acín, A.
2014-10-01
While entanglement and violation of Bell inequalities were initially thought to be equivalent quantum phenomena, we now have different examples of entangled states whose correlations can be described by local hidden-variable models and, therefore, do not violate any of the Bell inequalities. We provide an up-to-date overview of the existing literature regarding local hidden-variable models for entangled quantum states, in both the bipartite and multipartite cases, and discuss some of the most relevant open questions in this context. Our review covers twenty five years of this line of research, beginning with the seminal work by Werner (1989 Phys. Rev. A 40 8), which provided the first example of an entangled state with a local model. Werner's work, in turn, appeared twenty five years after the seminal work by Bell (1964 Physics 1 195), about the impossibility of recovering the predictions of quantum mechanics using a local hidden-variable theory. This article is part of a special issue of Journal of Physics A: Mathematical and Theoretical devoted to ‘50 years of Bell’s theorem’.
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…
BPS states in supersymmetric chiral models with higher derivative terms
NASA Astrophysics Data System (ADS)
Nitta, Muneto; Sasaki, Shin
2014-11-01
We study the higher derivative chiral models with four supercharges and Bogomol'nyi-Prasad-Sommerfield (BPS) states in these models. The off-shell Lagrangian generically includes higher powers of the auxiliary fields F , which causes distinct on-shell branches associated with the solutions to the auxiliary fields equation. We point out that the model admits a supersymmetric completion of arbitrary higher derivative bosonic models of a single complex scalar field, and an arbitrary scalar potential can be introduced even without superpotentials. As an example, we present a supersymmetric extension of the Faddeev-Skyrme model without four time derivatives, in contrast to the previously proposed supersymmetric Faddeev-Skyrme-like model containing four time derivatives. In general, higher derivative terms together with a superpotential result in deformed scalar potentials. We find that higher derivative corrections to 1 /2 BPS domain walls and 1 /2 BPS lumps are exactly canceled out, while the 1 /4 BPS lumps (as compact baby Skyrmions) depend on a characteristic feature of the higher derivative models. We also find a new 1 /4 BPS condition for domain wall junctions, which generically receives higher derivative corrections.
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.
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…
Predicting differences in gene regulatory systems by state space models.
Yamaguchi, Rui; Imoto, Seiya; Yamauchi, Mai; Nagasaki, Masao; Yoshida, Ryo; Shimamura, Teppei; Hatanaka, Yosuke; Ueno, Kazuko; Higuchi, Tomoyuki; Gotoh, Noriko; Miyano, Satoru
2008-01-01
We propose a statistical strategy to predict differentially regulated genes of case and control samples from time-course gene expression data by leveraging unpredictability of the expression patterns from the underlying regulatory system inferred by a state space model. The proposed method can screen out genes that show different patterns but generated by the same regulations in both samples, since these patterns can be predicted by the same model. Our strategy consists of three steps. Firstly, a gene regulatory system is inferred from the control data by a state space model. Then the obtained model for the underlying regulatory system of the control sample is used to predict the case data. Finally, by assessing the significance of the difference between case and predicted-case time-course data of each gene, we are able to detect the unpredictable genes that are the candidate as the key differences between the regulatory systems of case and control cells. We illustrate the whole process of the strategy by an actual example, where human small airway epithelial cell gene regulatory systems were generated from novel time courses of gene expressions following treatment with(case)/without(control) the drug gefitinib, an inhibitor for the epidermal growth factor receptor tyrosine kinase. Finally, in gefitinib response data we succeeded in finding unpredictable genes that are candidates of the specific targets of gefitinib. We also discussed differences in regulatory systems for the unpredictable genes. The proposed method would be a promising tool for identifying biomarkers and drug target genes.
Multiple endemic states in age-structured SIR epidemic models.
Franceschetti, Andrea; Pugliese, Andrea; Breda, Dmitri
2012-07-01
SIR age-structured models are very often used as a basic model of epidemic spread. Yet, their behaviour, under generic assumptions on contact rates between different age classes, is not completely known, and, in the most detailed analysis so far, Inaba (1990) was able to prove uniqueness of the endemic equilibrium only under a rather restrictive condition. Here, we show an example in the form of a 3x3 contact matrix in which multiple non-trivial steady states exist. This instance of non-uniqueness of positive equilibria differs from most existing ones for epidemic models, since it arises not from a backward transcritical bifurcation at the disease free equilibrium, but through two saddle-node bifurcations of the positive equilibrium. The dynamical behaviour of the model is analysed numerically around the range where multiple endemic equilibria exist; many other features are shown to occur, from coexistence of multiple attractive periodic solutions, some with extremely long period, to quasi-periodic and chaotic attractors. It is also shown that, if the contact rates are in the form of a 2x2 WAIFW matrix, uniqueness of non-trivial steady states always holds, so that 3 is the minimum dimension of the contact matrix to allow for multiple endemic equilibria.
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.
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
Finite state aeroelastic model for use in rotor design optimization
NASA Technical Reports Server (NTRS)
He, Chengjian; Peters, David A.
1993-01-01
In this article, a rotor aeroelastic model based on a newly developed finite state dynamic wake, coupled with blade finite element analysis, is described. The analysis is intended for application in rotor blade design optimization. A coupled simultaneous system of differential equations combining blade structural dynamics and aerodynamics is established in a formulation well-suited for design sensitivity computation. Each blade is assumed to be an elastic beam undergoing flap bending, lead-lag bending, elastic twist, and axial deflections. Aerodynamic loads are computed from unsteady blade element theory where the rotor three-dimensional unsteady wake is described by a generalized dynamic wake model. Correlation of results obtained from the analysis with flight test data is provided to assess model accuracy.
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.
Phenomenological model for transient deformation based on state variables
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.
Modeling individual effects in the Cormack-Jolly-Seber Model: A state-space formulation
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.
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.
Nonlinear State Estimation and Modeling of a Helicopter UAV
NASA Astrophysics Data System (ADS)
Barczyk, Martin
Experimentally-validated nonlinear flight control of a helicopter UAV has two necessary conditions: an estimate of the vehicle’s states from noisy multirate output measurements, and a nonlinear dynamics model with minimum complexity, physically controllable inputs and experimentally identified parameter values. This thesis addresses both these objectives for the Applied Nonlinear Controls Lab (ANCL)'s helicopter UAV project. A magnetometer-plus-GPS aided Inertial Navigation System (INS) for outdoor flight as well as an Attitude and Heading Reference System (AHRS) for indoor testing are designed, implemented and experimentally validated employing an Extended Kalman Filter (EKF), using a novel calibration technique for the magnetometer aiding sensor added to remove the limitations of an earlier GPS-only aiding design. Next the recently-developed nonlinear observer design methodology of invariant observers is adapted to the aided INS and AHRS examples, employing a rotation matrix representation for the state manifold to obtain designs amenable to global stability analysis, obtaining a direct nonlinear design for gains of the AHRS observer, modifying the previously-proposed Invariant EKF systematic method for computing gains, and culminating in simulation and experimental validation of the observers. Lastly a nonlinear control-oriented model of the helicopter UAV is derived from first principles, using a rigid-body dynamics formulation augmented with models of the on-board subsystems: main rotor forces and blade flapping dynamics, the Bell-Hiller system and flybar flapping dynamics, tail rotor forces, tail gyro unit, engine and rotor speed, servo operation, fuselage drag, and tail stabilizer forces. The parameter values in the resulting models are identified experimentally. Using these the model is further simplified to be tractable for model-based control design.
Modeling the human invader in the United States
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.
Specificity in Transition State Binding: The Pauling Model Revisited
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
Interacting boson model descriptions of high-spin states
Kuyucak, S.
1995-10-01
The I/N expansion technique for the interacting boson model (IBM) has recently been extended to higher orders using computer algebra. This allows, for the first time, a realistic description of high-spin states in the framework of the sdg-IBM. Systematic studies of moment of inertia show that the problems with its spin dependence are due to the energy surface being too rigid against rotations which can be remedied by including the d-boson energy in the Hamiltonian. The d-boson energy is also instrumental in resolving two other problems in the IBM first raised by Bohr and Mottelson, namely, energy scale mismatch in the ground and gamma bands, and the boson cutoff in B(E2) values. We apply the results to describe the high-spin states in rare-earth and actinide nuclei where the ground band has been followed up to spins L=30, and hence provide unique test cases for collective models. The same formalism can also be used in a phenomenological description of superdeformed states as will be demonstrated with examples in the Hg-Pb region.
Modeling biofiltration of VOC mixtures under steady-state conditions
Baltzis, B.C.; Wojdyla, S.M.; Zarook, S.M.
1997-06-01
Treatment of air streams contaminated with binary volatile organic compound (VOC) mixtures in classical biofilters under steady-state conditions of operation was described with a general mathematical model. The model accounts for potential kinetic interactions among the pollutants, effects of oxygen availability on biodegradation, and biomass diversification in the filter bed. While the effects of oxygen were always taken into account, two distinct cases were considered for the experimental model validation. The first involves kinetic interactions, but no biomass differentiation, used for describing data from biofiltration of benzene/toluene mixtures. The second case assumes that each pollutant is treated by a different type of biomass. Each biomass type is assumed to form separate patches of biofilm on the solid packing material, thus kinetic interference does not occur. This model was used for describing biofiltration of ethanol/butanol mixtures. Experiments were performed with classical biofilters packed with mixtures of peat moss and perlite (2:3, volume:volume). The model equations were solved through the use of computer codes based on the fourth-order Runge-Kutta technique for the gas-phase mass balances and the method of orthogonal collocation for the concentration profiles in the biofilms. Good agreement between model predictions and experimental data was found in almost all cases. Oxygen was found to be extremely important in the case of polar VOCs (ethanol/butanol).
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.
Periodic Striped Ground States in Ising Models with Competing Interactions
NASA Astrophysics Data System (ADS)
Giuliani, Alessandro; Seiringer, Robert
2016-06-01
We consider Ising models in two and three dimensions, with short range ferromagnetic and long range, power-law decaying, antiferromagnetic interactions. We let J be the ratio between the strength of the ferromagnetic to antiferromagnetic interactions. The competition between these two kinds of interactions induces the system to form domains of minus spins in a background of plus spins, or vice versa. If the decay exponent p of the long range interaction is larger than d + 1, with d the space dimension, this happens for all values of J smaller than a critical value J c (p), beyond which the ground state is homogeneous. In this paper, we give a characterization of the infinite volume ground states of the system, for p > 2d and J in a left neighborhood of J c (p). In particular, we prove that the quasi-one-dimensional states consisting of infinite stripes (d = 2) or slabs (d = 3), all of the same optimal width and orientation, and alternating magnetization, are infinite volume ground states. Our proof is based on localization bounds combined with reflection positivity.
Nonlinear system modeling with random matrices: echo state networks revisited.
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.
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…
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.
Modeling of efficient solid-state cooler on layered multiferroics.
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.
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
Modeling Clinical States and Metabolic Rhythms in Bioarcheology
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
Transitions between patterned states in vegetation models for semiarid ecosystems
NASA Astrophysics Data System (ADS)
Gowda, Karna; Riecke, Hermann; Silber, Mary
2014-02-01
A feature common to many models of vegetation pattern formation in semiarid ecosystems is a sequence of qualitatively different patterned states, "gaps → labyrinth → spots," that occurs as a parameter representing precipitation decreases. We explore the robustness of this "standard" sequence in the generic setting of a bifurcation problem on a hexagonal lattice, as well as in a particular reaction-diffusion model for vegetation pattern formation. Specifically, we consider a degeneracy of the bifurcation equations that creates a small bubble in parameter space in which stable small-amplitude patterned states may exist near two Turing bifurcations. Pattern transitions between these bifurcation points can then be analyzed in a weakly nonlinear framework. We find that a number of transition scenarios besides the standard sequence are generically possible, which calls into question the reliability of any particular pattern or sequence as a precursor to vegetation collapse. Additionally, we find that clues to the robustness of the standard sequence lie in the nonlinear details of a particular model.
Transitions between patterned states in vegetation models for semiarid ecosystems.
Gowda, Karna; Riecke, Hermann; Silber, Mary
2014-02-01
A feature common to many models of vegetation pattern formation in semiarid ecosystems is a sequence of qualitatively different patterned states, "gaps → labyrinth → spots," that occurs as a parameter representing precipitation decreases. We explore the robustness of this "standard" sequence in the generic setting of a bifurcation problem on a hexagonal lattice, as well as in a particular reaction-diffusion model for vegetation pattern formation. Specifically, we consider a degeneracy of the bifurcation equations that creates a small bubble in parameter space in which stable small-amplitude patterned states may exist near two Turing bifurcations. Pattern transitions between these bifurcation points can then be analyzed in a weakly nonlinear framework. We find that a number of transition scenarios besides the standard sequence are generically possible, which calls into question the reliability of any particular pattern or sequence as a precursor to vegetation collapse. Additionally, we find that clues to the robustness of the standard sequence lie in the nonlinear details of a particular model.
Regional Climate Model Projections for the State of Washington
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
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.
An unsteady state retention model for fluid desorption from sorbents.
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. PMID:25814100
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.
New equation of state model for hydrodynamic applications
Young, D.A.; Barbee, T.W. III; Rogers, F.J.
1997-07-01
Two new theoretical methods for computing the equation of state of hot, dense matter are discussed.The ab initio phonon theory gives a first-principles calculation of lattice frequencies, which can be used to compare theory and experiment for isothermal and shock compression of solids. The ACTEX dense plasma theory has been improved to allow it to be compared directly with ultrahigh pressure shock data on low-Z materials. The comparisons with experiment are good, suggesting that these models will be useful in generating global EOS tables for hydrodynamic simulations.
Linear modeling of steady-state behavioral dynamics.
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
Model-independent confirmation of the Z (4430 )- state
NASA Astrophysics Data System (ADS)
Aaij, R.; Adeva, B.; Adinolfi, M.; Affolder, A.; Ajaltouni, Z.; Albrecht, J.; Alessio, F.; Alexander, M.; Ali, S.; Alkhazov, G.; Alvarez Cartelle, P.; Alves, A. A.; Amato, S.; Amerio, S.; Amhis, Y.; An, L.; Anderlini, L.; Anderson, J.; Andreassen, R.; Andreotti, M.; Andrews, J. E.; Appleby, R. B.; Aquines Gutierrez, O.; Archilli, F.; Artamonov, A.; Artuso, M.; Aslanides, E.; Auriemma, G.; Baalouch, M.; Bachmann, S.; Back, J. J.; Badalov, A.; Balagura, V.; Baldini, W.; Barlow, R. J.; Barschel, C.; Barsuk, S.; Barter, W.; Batozskaya, V.; Bauer, Th.; Bay, A.; Beaucourt, L.; Beddow, J.; Bedeschi, F.; Bediaga, I.; Belogurov, S.; Belous, K.; Belyaev, I.; Ben-Haim, E.; Bencivenni, G.; Benson, S.; Benton, J.; Berezhnoy, A.; Bernet, R.; Bettler, M.-O.; van Beuzekom, M.; Bien, A.; Bifani, S.; Bird, T.; Bizzeti, A.; Bjørnstad, P. M.; Blake, T.; Blanc, F.; Blouw, J.; Blusk, S.; Bocci, V.; Bondar, A.; Bondar, N.; Bonivento, W.; Borghi, S.; Borgia, A.; Borsato, M.; Bowcock, T. J. V.; Bowen, E.; Bozzi, C.; Brambach, T.; van den Brand, J.; Bressieux, J.; Brett, D.; Britsch, M.; Britton, T.; Brodzicka, J.; Brook, N. H.; Brown, H.; Bursche, A.; Busetto, G.; Buytaert, J.; Cadeddu, S.; Calabrese, R.; Calvi, M.; Calvo Gomez, M.; Camboni, A.; Campana, P.; Campora Perez, D.; Carbone, A.; Carboni, G.; Cardinale, R.; Cardini, A.; Carranza-Mejia, H.; Carson, L.; Carvalho Akiba, K.; Casse, G.; Cassina, L.; Castillo Garcia, L.; Cattaneo, M.; Cauet, Ch.; Cenci, R.; Charles, M.; Charpentier, Ph.; Chen, S.; Cheung, S.-F.; Chiapolini, N.; Chrzaszcz, M.; Ciba, K.; Cid Vidal, X.; Ciezarek, G.; Clarke, P. E. L.; Clemencic, M.; Cliff, H. V.; Closier, J.; Coco, V.; Cogan, J.; Cogneras, E.; Collins, P.; Comerma-Montells, A.; Contu, A.; Cook, A.; Coombes, M.; Coquereau, S.; Corti, G.; Corvo, M.; Counts, I.; Couturier, B.; Cowan, G. A.; Craik, D. C.; Cruz Torres, M.; Cunliffe, S.; Currie, R.; D'Ambrosio, C.; Dalseno, J.; David, P.; David, P. N. Y.; Davis, A.; De Bruyn, K.; De Capua, S.; De Cian, M.; De Miranda, J. M.; De Paula, L.; De Silva, W.; De Simone, P.; Decamp, D.; Deckenhoff, M.; Del Buono, L.; Déléage, N.; Derkach, D.; Deschamps, O.; Dettori, F.; Di Canto, A.; Dijkstra, H.; Donleavy, S.; Dordei, F.; Dorigo, M.; Dosil Suárez, A.; Dossett, D.; Dovbnya, A.; Dujany, G.; Dupertuis, F.; Durante, P.; Dzhelyadin, R.; Dziurda, A.; Dzyuba, A.; Easo, S.; Egede, U.; Egorychev, V.; Eidelman, S.; Eisenhardt, S.; Eitschberger, U.; Ekelhof, R.; Eklund, L.; El Rifai, I.; Elsasser, Ch.; Ely, S.; Esen, S.; Evans, T.; Falabella, A.; Färber, C.; Farinelli, C.; Farley, N.; Farry, S.; Ferguson, D.; Fernandez Albor, V.; Ferreira Rodrigues, F.; Ferro-Luzzi, M.; Filippov, S.; Fiore, M.; Fiorini, M.; Firlej, M.; Fitzpatrick, C.; Fiutowski, T.; Fontana, M.; Fontanelli, F.; Forty, R.; Francisco, O.; Frank, M.; Frei, C.; Frosini, M.; Fu, J.; Furfaro, E.; Gallas Torreira, A.; Galli, D.; Gallorini, S.; Gambetta, S.; Gandelman, M.; Gandini, P.; Gao, Y.; Garofoli, J.; Garra Tico, J.; Garrido, L.; Gaspar, C.; Gauld, R.; Gavardi, L.; Gersabeck, E.; Gersabeck, M.; Gershon, T.; Ghez, Ph.; Gianelle, A.; Giani', S.; Gibson, V.; Giubega, L.; Gligorov, V. V.; Göbel, C.; Golubkov, D.; Golutvin, A.; Gomes, A.; Gordon, H.; Gotti, C.; Grabalosa Gándara, M.; Graciani Diaz, R.; Granado Cardoso, L. A.; Graugés, E.; Graziani, G.; Grecu, A.; Greening, E.; Gregson, S.; Griffith, P.; Grillo, L.; Grünberg, O.; Gui, B.; Gushchin, E.; Guz, Yu.; Gys, T.; Hadjivasiliou, C.; Haefeli, G.; Haen, C.; Haines, S. C.; Hall, S.; Hamilton, B.; Hampson, T.; Han, X.; Hansmann-Menzemer, S.; Harnew, N.; Harnew, S. T.; Harrison, J.; Hartmann, T.; He, J.; Head, T.; Heijne, V.; Hennessy, K.; Henrard, P.; Henry, L.; Hernando Morata, J. A.; van Herwijnen, E.; Heß, M.; Hicheur, A.; Hill, D.; Hoballah, M.; Hombach, C.; Hulsbergen, W.; Hunt, P.; Hussain, N.; Hutchcroft, D.; Hynds, D.; Idzik, M.; Ilten, P.; Jacobsson, R.; Jaeger, A.; Jalocha, J.; Jans, E.; Jaton, P.; Jawahery, A.; Jezabek, M.; Jing, F.; John, M.; Johnson, D.; Jones, C. R.; Joram, C.; Jost, B.; Jurik, N.; Kaballo, M.; Kandybei, S.; Kanso, W.; Karacson, M.; Karbach, T. M.; Kelsey, M.; Kenyon, I. R.; Ketel, T.; Khanji, B.; Khurewathanakul, C.; Klaver, S.; Kochebina, O.; Kolpin, M.; Komarov, I.; Koopman, R. F.; Koppenburg, P.; Korolev, M.; Kozlinskiy, A.; Kravchuk, L.; Kreplin, K.; Kreps, M.; Krocker, G.; Krokovny, P.; Kruse, F.; Kucharczyk, M.; Kudryavtsev, V.; Kurek, K.; Kvaratskheliya, T.; La Thi, V. N.; Lacarrere, D.; Lafferty, G.; Lai, A.; Lambert, D.; Lambert, R. W.; Lanciotti, E.; Lanfranchi, G.; Langenbruch, C.; Langhans, B.; Latham, T.; Lazzeroni, C.; Le Gac, R.; van Leerdam, J.; Lees, J.-P.; Lefèvre, R.; Leflat, A.; Lefrançois, J.; Leo, S.; Leroy, O.; Lesiak, T.; Leverington, B.; Li, Y.; Liles, M.; Lindner, R.; Linn, C.; Lionetto, F.; Liu, B.; Liu, G.; Lohn, S.; Longstaff, I.; Lopes, J. H.; Lopez-March, N.; Lowdon, P.; Lu, H.; Lucchesi, D.; Luo, H.; Lupato, A.; Luppi, E.; Lupton, O.; Machefert, F.; Machikhiliyan, I. V.; Maciuc, F.; Maev, O.; Malde, S.; Manca, G.; Mancinelli, G.; Manzali, M.; Maratas, J.; Marchand, J. F.; Marconi, U.; Marin Benito, C.; Marino, P.; Märki, R.; Marks, J.; Martellotti, G.; Martens, A.; Martín Sánchez, A.; Martinelli, M.; Martinez Santos, D.; Martinez Vidal, F.; Martins Tostes, D.; Massafferri, A.; Matev, R.; Mathe, Z.; Matteuzzi, C.; Mazurov, A.; McCann, M.; McCarthy, J.; McNab, A.; McNulty, R.; McSkelly, B.; Meadows, B.; Meier, F.; Meissner, M.; Merk, M.; Milanes, D. A.; Minard, M.-N.; Moggi, N.; Molina Rodriguez, J.; Monteil, S.; Moran, D.; Morandin, M.; Morawski, P.; Mordà, A.; Morello, M. J.; Moron, J.; Morris, A.-B.; Mountain, R.; Muheim, F.; Müller, K.; Muresan, R.; Mussini, M.; Muster, B.; Naik, P.; Nakada, T.; Nandakumar, R.; Nasteva, I.; Needham, M.; Neri, N.; Neubert, S.; Neufeld, N.; Neuner, M.; Nguyen, A. D.; Nguyen, T. D.; Nguyen-Mau, C.; Nicol, M.; Niess, V.; Niet, R.; Nikitin, N.; Nikodem, T.; Novoselov, A.; Oblakowska-Mucha, A.; Obraztsov, V.; Oggero, S.; Ogilvy, S.; Okhrimenko, O.; Oldeman, R.; Onderwater, G.; Orlandea, M.; Otalora Goicochea, J. M.; Owen, P.; Oyanguren, A.; Pal, B. K.; Palano, A.; Palombo, F.; Palutan, M.; Panman, J.; Papanestis, A.; Pappagallo, M.; Parkes, C.; Parkinson, C. J.; Passaleva, G.; Patel, G. D.; Patel, M.; Patrignani, C.; Pazos Alvarez, A.; Pearce, A.; Pellegrino, A.; Pepe Altarelli, M.; Perazzini, S.; Perez Trigo, E.; Perret, P.; Perrin-Terrin, M.; Pescatore, L.; Pesen, E.; Petridis, K.; Petrolini, A.; Picatoste Olloqui, E.; Pietrzyk, B.; Pilař, T.; Pinci, D.; Pistone, A.; Playfer, S.; Plo Casasus, M.; Polci, F.; Poluektov, A.; Polycarpo, E.; Popov, A.; Popov, D.; Popovici, B.; Potterat, C.; Powell, A.; Prisciandaro, J.; Pritchard, A.; Prouve, C.; Pugatch, V.; Puig Navarro, A.; Punzi, G.; Qian, W.; Rachwal, B.; Rademacker, J. H.; Rakotomiaramanana, B.; Rama, M.; Rangel, M. S.; Raniuk, I.; Rauschmayr, N.; Raven, G.; Reichert, S.; Reid, M. M.; dos Reis, A. C.; Ricciardi, S.; Richards, A.; Rihl, M.; Rinnert, K.; Rives Molina, V.; Roa Romero, D. A.; Robbe, P.; Rodrigues, A. B.; Rodrigues, E.; Rodriguez Perez, P.; Roiser, S.; Romanovsky, V.; Romero Vidal, A.; Rotondo, M.; Rouvinet, J.; Ruf, T.; Ruffini, F.; Ruiz, H.; Ruiz Valls, P.; Sabatino, G.; Saborido Silva, J. J.; Sagidova, N.; Sail, P.; Saitta, B.; Salustino Guimaraes, V.; Sanchez Mayordomo, C.; Sanmartin Sedes, B.; Santacesaria, R.; Santamarina Rios, C.; Santovetti, E.; Sapunov, M.; Sarti, A.; Satriano, C.; Satta, A.; Savrie, M.; Savrina, D.; Schiller, M.; Schindler, H.; Schlupp, M.; Schmelling, M.; Schmidt, B.; Schneider, O.; Schopper, A.; Schune, M.-H.; Schwemmer, R.; Sciascia, B.; Sciubba, A.; Seco, M.; Semennikov, A.; Senderowska, K.; Sepp, I.; Serra, N.; Serrano, J.; Sestini, L.; Seyfert, P.; Shapkin, M.; Shapoval, I.; Shcheglov, Y.; Shears, T.; Shekhtman, L.; Shevchenko, V.; Shires, A.; Silva Coutinho, R.; Simi, G.; Sirendi, M.; Skidmore, N.; Skwarnicki, T.; Smith, N. A.; Smith, E.; Smith, E.; Smith, J.; Smith, M.; Snoek, H.; Sokoloff, M. D.; Soler, F. J. P.; Soomro, F.; Souza, D.; Souza De Paula, B.; Spaan, B.; Sparkes, A.; Spinella, F.; Spradlin, P.; Stagni, F.; Stahl, S.; Steinkamp, O.; Stenyakin, O.; Stevenson, S.; Stoica, S.; Stone, S.; Storaci, B.; Stracka, S.; Straticiuc, M.; Straumann, U.; Stroili, R.; Subbiah, V. K.; Sun, L.; Sutcliffe, W.; Swientek, K.; Swientek, S.; Syropoulos, V.; Szczekowski, M.; Szczypka, P.; Szilard, D.; Szumlak, T.; T'Jampens, S.; Teklishyn, M.; Tellarini, G.; Teubert, F.; Thomas, C.; Thomas, E.; van Tilburg, J.; Tisserand, V.; Tobin, M.; Tolk, S.; Tomassetti, L.; Tonelli, D.; Topp-Joergensen, S.; Torr, N.; Tournefier, E.; Tourneur, S.; Tran, M. T.; Tresch, M.; Tsaregorodtsev, A.; Tsopelas, P.; Tuning, N.; Ubeda Garcia, M.; Ukleja, A.; Ustyuzhanin, A.; Uwer, U.; Vagnoni, V.; Valenti, G.; Vallier, A.; Vazquez Gomez, R.; Vazquez Regueiro, P.; Vázquez Sierra, C.; Vecchi, S.; Velthuis, J. J.; Veltri, M.; Veneziano, G.; Vesterinen, M.; Viaud, B.; Vieira, D.; Vieites Diaz, M.; Vilasis-Cardona, X.; Vollhardt, A.; Volyanskyy, D.; Voong, D.; Vorobyev, A.; Vorobyev, V.; Voß, C.; Voss, H.; de Vries, J. A.; Waldi, R.; Wallace, C.; Wallace, R.; Walsh, J.; Wandernoth, S.; Wang, J.; Ward, D. R.; Watson, N. K.; Websdale, D.; Whitehead, M.; Wicht, J.; Wiedner, D.; Wilkinson, G.; Williams, M. P.; Williams, M.; Wilson, F. F.; Wimberley, J.; Wishahi, J.; Wislicki, W.; Witek, M.; Wormser, G.; Wotton, S. A.; Wright, S.; Wu, S.; Wyllie, K.; Xie, Y.; Xing, Z.; Xu, Z.; Yang, Z.; Yuan, X.; Yushchenko, O.; Zangoli, M.; Zavertyaev, M.; Zhang, F.; Zhang, L.; Zhang, W. C.; Zhang, Y.; Zhelezov, A.; Zhokhov, A.; Zhong, L.; Zvyagin, A.; LHCb Collaboration
2015-12-01
The decay B0→ψ (2 S )K+π- is analyzed using 3 fb-1 of p p collision data collected with the LHCb detector. A model-independent description of the ψ (2 S )π mass spectrum is obtained, using as input the K π mass spectrum and angular distribution derived directly from data, without requiring a theoretical description of resonance shapes or their interference. The hypothesis that the ψ (2 S )π mass spectrum can be described in terms of K π reflections alone is rejected with more than 8 σ significance. This provides confirmation, in a model-independent way, of the need for an additional resonant component in the mass region of the Z (4430 )- exotic state.
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.
Modeling Dynamic Ductility: An Equation of State for Porous Metals
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.
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.
Solid state stability studies of model dipeptides: aspartame and aspartylphenylalanine.
Leung, S S; Grant, D J
1997-01-01
Some solid-state pharmaceutical properties and the solid-state thermal stability of the model dipeptides aspartame (APM) and aspartylphenylalanine (AP), have been investigated. Studies by differential scanning calorimetry (DSC), thermal gravimetric analysis (TGA), high-performance liquid chromatography, powder X-ray diffraction, and optical microscopy have shown that the dipeptides undergo solid state intramolecular aminolysis of the type, solid --> solid + gas. This reaction was observed for APM at 167-180 degrees C with the liberation of methanol and for AP at 186-202 degrees C with the liberation of water. The exclusive solid product of the degradation reaction of both dipeptides is the cyclic compound 3-(carboxymethyl)-6-benzyl-2,5-dioxopiperazine. The rates of the degradation reactions were monitored by isothermal TGA and by temperature-ramp DSC and were found to follow kinetics based on nucleation control with activation energies of about 266 kJ mol(-1) for APM and 234 kJ mol(-1) for AP.
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…
Integrated stoichiometric, thermodynamic and kinetic modelling of steady state metabolism.
Fleming, R M T; Thiele, I; Provan, G; Nasheuer, H P
2010-06-01
The quantitative analysis of biochemical reactions and metabolites is at frontier of biological sciences. The recent availability of high-throughput technology data sets in biology has paved the way for new modelling approaches at various levels of complexity including the metabolome of a cell or an organism. Understanding the metabolism of a single cell and multi-cell organism will provide the knowledge for the rational design of growth conditions to produce commercially valuable reagents in biotechnology. Here, we demonstrate how equations representing steady state mass conservation, energy conservation, the second law of thermodynamics, and reversible enzyme kinetics can be formulated as a single system of linear equalities and inequalities, in addition to linear equalities on exponential variables. Even though the feasible set is non-convex, the reformulation is exact and amenable to large-scale numerical analysis, a prerequisite for computationally feasible genome scale modelling. Integrating flux, concentration and kinetic variables in a unified constraint-based formulation is aimed at increasing the quantitative predictive capacity of flux balance analysis. Incorporation of experimental and theoretical bounds on thermodynamic and kinetic variables ensures that the predicted steady state fluxes are both thermodynamically and biochemically feasible. The resulting in silico predictions are tested against fluxomic data for central metabolism in Escherichia coli and compare favourably with in silico prediction by flux balance analysis.
Dislocation models of interseismic deformation in the western United States
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.
State-of-the-art Model M-2 Maintenance System
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.
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.
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
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
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.
Multiscale air quality modeling of the Northeastern United States
NASA Astrophysics Data System (ADS)
Kumar, Naresh; Russell, Armistead G.
The Urban and Regional Multiscale (URM) model has been used to study the ozone problem in the northeastern United States. The model was applied to a multiday ozone episode extending from 2 July 1988 to 8 July 1988. The URM model is particularly suitable for application to the Northeast as there is a dense network of urban centers along with large rural areas, and the model allows the use of variable grid sizes to effectively capture the pollutant dynamics while being computationally efficient. This study particularly concentrates on how spatial grid resolution affects results, particularly in the Northeast Corridor, a string of urban centers extending from Washington D.C. to Boston. Three different grid systems are employed in the model simulations to examine this issue. The most dynamic grid system uses grid sizes varying from 4.625 to 74 km, with the finest grids concentrated in the Northeast Corridor. The uniform grid system uses a uniform grid size of 18.5 km similar to that used in the regional oxidant model (ROM). The intermediate grid system uses grid sizes varying from 4.625 to 18.5 km. When finer grids are used over the urban areas, as in the intermediate and the most dynamic grid systems, the model predicted higher peak ozone concentrations with greater detail. Sensitivity calculations were performed to quantify the effect of various inputs on the predicted ozone. Effects of zeroing the initial conditions persisted until 7 July 1988. When using background levels of species concentrations as initial conditions, the effect lasted only for two days of simulation. Boundary conditions impacted the ozone concentrations near the boundary cells only. Emission inputs were the major factor in producing the large concentrations of ozone predicted in the Northeast Corridor. The URM model was also used to study ozone control strategy issues in the Northeast Corridor. A suite of simulations was performed where anthropogenic NO x and VOC emission levels were reducd
Estimation of HIV infection and incubation via state space models.
Tan, W Y; Ye, Z
2000-09-01
By using the state space model (Kalman filter model) of the HIV epidemic, in this paper we have developed a general Bayesian procedure to estimate simultaneously the HIV infection distribution, the HIV incubation distribution, the numbers of susceptible people, infective people and AIDS cases. The basic approach is to use the Gibbs sampling method combined with the weighted bootstrap method. We have applied this method to the San Francisco AIDS incidence data from January 1981 to December 1992. The results show clearly that both the probability density function of the HIV infection and the probability density function of the HIV incubation are curves with two peaks. The results of the HIV infection distribution are clearly consistent with the finding by Tan et al. [W.Y. Tan, S.C. Tang, S.R. Lee, Estimation of HIV seroconversion and effects of age in San Francisco homosexual populations, J. Appl. Stat. 25 (1998) 85]. The results of HIV incubation distribution seem to confirm the staged model used by Satten and Longini [G. Satten, I. Longini, Markov chain with measurement error: estimating the 'true' course of marker of the progression of human immunodeficiency virus disease, Appl. Stat. 45 (1996) 275]. PMID:10942785
Siebert, Uwe; Alagoz, Oguzhan; Bayoumi, Ahmed M; Jahn, Beate; Owens, Douglas K; Cohen, David J; Kuntz, Karen M
2012-01-01
State-transition modeling is an intuitive, flexible, and transparent approach of computer-based decision-analytic modeling including both Markov model cohort simulation and individual-based (first-order Monte Carlo) microsimulation. Conceptualizing a decision problem in terms of a set of (health) states and transitions among these states, state-transition modeling is one of the most widespread modeling techniques in clinical decision analysis, health technology assessment, and health-economic evaluation. State-transition models have been used in many different populations and diseases, and their applications range from personalized health care strategies to public health programs. Most frequently, state-transition models are used in the evaluation of risk factor interventions, screening, diagnostic procedures, treatment strategies, and disease management programs. The goal of this article was to provide consensus-based guidelines for the application of state-transition models in the context of health care. We structured the best practice recommendations in the following sections: choice of model type (cohort vs. individual-level model), model structure, model parameters, analysis, reporting, and communication. In each of these sections, we give a brief description, address the issues that are of particular relevance to the application of state-transition models, give specific examples from the literature, and provide best practice recommendations for state-transition modeling. These recommendations are directed both to modelers and to users of modeling results such as clinicians, clinical guideline developers, manufacturers, or policymakers. PMID:22999130
Langevin equation with fluctuating diffusivity: A two-state model.
Miyaguchi, Tomoshige; Akimoto, Takuma; Yamamoto, Eiji
2016-07-01
Recently, anomalous subdiffusion, aging, and scatter of the diffusion coefficient have been reported in many single-particle-tracking experiments, though the origins of these behaviors are still elusive. Here, as a model to describe such phenomena, we investigate a Langevin equation with diffusivity fluctuating between a fast and a slow state. Namely, the diffusivity follows a dichotomous stochastic process. We assume that the sojourn time distributions of these two states are given by power laws. It is shown that, for a nonequilibrium ensemble, the ensemble-averaged mean-square displacement (MSD) shows transient subdiffusion. In contrast, the time-averaged MSD shows normal diffusion, but an effective diffusion coefficient transiently shows aging behavior. The propagator is non-Gaussian for short time and converges to a Gaussian distribution in a long-time limit; this convergence to Gaussian is extremely slow for some parameter values. For equilibrium ensembles, both ensemble-averaged and time-averaged MSDs show only normal diffusion and thus we cannot detect any traces of the fluctuating diffusivity with these MSDs. Therefore, as an alternative approach to characterizing the fluctuating diffusivity, the relative standard deviation (RSD) of the time-averaged MSD is utilized and it is shown that the RSD exhibits slow relaxation as a signature of the long-time correlation in the fluctuating diffusivity. Furthermore, it is shown that the RSD is related to a non-Gaussian parameter of the propagator. To obtain these theoretical results, we develop a two-state renewal theory as an analytical tool. PMID:27575079
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.
Entanglement and Majorana edge states in the Kitaev model
NASA Astrophysics Data System (ADS)
Mandal, Saptarshi; Maiti, Moitri; Varma, Vipin Kerala
2016-07-01
We investigate the von Neumann entanglement entropy and Schmidt gap in the vortex-free ground state of the Kitaev model on the honeycomb lattice for square/rectangular and cylindrical subsystems. We find that, for both the subsystems, the free-fermionic contribution to the entanglement entropy SE exhibits signatures of the phase transitions between the gapless and gapped phases. However, within the gapless phase, we find that SE does not show an expected monotonic behavior as a function of the coupling Jz between the suitably defined one-dimensional chains for either geometry; moreover, the system generically reaches a point of minimum entanglement within the gapless phase before the entanglement saturates or increases again until the gapped phase is reached. This may be attributed to the onset of gapless modes in the bulk spectrum and the competition between the correlation functions along various bonds. In the gapped phase, on the other hand, SE always monotonically varies with Jz independent of the subregion size or shape. Finally, further confirming the Li-Haldane conjecture, we find that the Schmidt gap Δ defined from the entanglement spectrum also signals the topological transitions but only if there are corresponding zero-energy Majorana edge states that simultaneously appear or disappear across the transitions. We analytically corroborate some of our results on entanglement entropy, the Schmidt gap, and the bulk-edge correspondence using perturbation theory.
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.
A Planning Model for the Formulation of State and Local Career and Vocational Guidance Plans.
ERIC Educational Resources Information Center
West Virginia State Dept. of Education, Charleston. Bureau of Vocational, Technical, and Adult Education.
A planning model is presented which was used throughout the development of state and local and vocational guidance models and plans for West Virginia. The general planning model upon which the state model is based is also included. The planning model used is outlined in eighteen steps: (1) identify the problem; (2) decision makers awareness; (3)…
Natural State Model of the Nesjavellir Geothermal Field, Iceland
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.
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.
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
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-
Meier, Benjamin Mason; Gebbie, Kristine M.
2009-01-01
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. PMID:19150900
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.
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.
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.
Modeling lake trophic state: a random forest approach
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...
Modelling of free positron states in TiHx
NASA Astrophysics Data System (ADS)
Imas, O. N.; Karataeva, I. Yu.; Fedorov, K. B.
2016-08-01
Electron energy structure, positron spectrum and positron characteristics of α-Ti and α-TiH0.125 were calculated. Self-consistent calculations of the band structure were performed by the linear muffin-tin orbital method in the atomic sphere approximation. Modelling has been made on low content of hydrogen into α-Ti with expanded close-packed hexagonal cell inclusive 8 titanium atoms. Variation of sphere radiuses permitted to consider anisotropy and spherical symmetry of potential. Positron potential and positron wave function were calculated on a base of self-consistent electron density. Then positron probability of existence into TiHx lattice and lifetime were founded. Theoretical calculation indicated a satisfactory agreement of positron characteristics absolute values with the experimental data is achieved but the tendency of values with hydrogen defects increasing is not. The reason of divergence is discussed. On the basis of experimental data and theoretical calculations it was shown that different hydrogen atom states demonstrate the different influence in the lifetime spectra.
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.
Modeling asymmetric cavity collapse with plasma equations of state.
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. PMID:27300976
Bistability and State Transition of a Delay Differential Equation Model of Neutrophil Dynamics
NASA Astrophysics Data System (ADS)
Ma, Suqi; Zhu, Kaiyi; Lei, Jinzhi
This paper studies the existence of bistable states and control strategies to induce state transitions of a delay differential equation model of neutrophil dynamics. We seek the conditions that a stable steady state and an oscillatory state coexist in the neutrophil dynamical system. Physiologically, stable steady state represents the healthy state, while oscillatory state is usually associated with diseases such as cyclical neutropenia. We study the control strategies to induce the transitions from the disease state to the healthy state by introducing temporal perturbations to system parameters. This study is valuable in designing clinical protocols for the treatment of cyclical neutropenia.
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
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.
Quadractic Model of Thermodynamic States in SDF Explosions
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.
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.
Proton Therapy Expansion Under Current United States Reimbursement Models
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.
Steady state model for polymer light-emitting electrochemical cells
Smith, D.L.
1997-03-01
A model is presented for the steady state operation of polymer light-emitting electrochemical cells (LECs). An LEC consists of a luminescent and ionically conducting polymer, with an ionic salt added to provide ions necessary for p-type and n-type doping, sandwiched between two electrodes. Upon applying a sufficiently large voltage bias, the ions are spatially separated forming an electrical junction. Electrons injected from the n-type side of the junction recombine with holes injected from the p-type side of the junction emitting light. We first describe the LEC at zero bias in which electric fields may occur in charge double layers near the contacts but in which there is a charge neutral, field free region in the device center which has an equal density of anions and cations and essentially no electrons or holes. A threshold voltage for junction formation is found, which depends on the polymer energy gap, the dissociation free energy of the salt, and the added salt density. It is generally somewhat smaller than the polymer energy gap. Below threshold, an applied bias changes the electric fields in the double charge layers near the contacts but the device center remains field free and essentially no current flows. Above threshold, the ions become spatially separated, a junction forms, and current begins to flow. Part of the applied voltage, above threshold, falls in the contact region and is necessary to establish the junction by electrochemical doping and part of the applied voltage falls across the junction. We describe the structure of the junction, which is quite different from that of a conventional p-n junction, including the spatial profiles of the electrons, holes, and ions, and the electrostatic potential. We discuss the current-voltage and capacitance-voltage characteristics of the LECs and show how they depend on the material parameters. {copyright} {ital 1997 American Institute of Physics.}
Auger-Méthé, Marie; Field, Chris; Albertsen, Christoffer M; Derocher, Andrew E; Lewis, Mark A; Jonsen, Ian D; Mills Flemming, Joanna
2016-01-01
State-space models (SSMs) are increasingly used in ecology to model time-series such as animal movement paths and population dynamics. This type of hierarchical model is often structured to account for two levels of variability: biological stochasticity and measurement error. SSMs are flexible. They can model linear and nonlinear processes using a variety of statistical distributions. Recent ecological SSMs are often complex, with a large number of parameters to estimate. Through a simulation study, we show that even simple linear Gaussian SSMs can suffer from parameter- and state-estimation problems. We demonstrate that these problems occur primarily when measurement error is larger than biological stochasticity, the condition that often drives ecologists to use SSMs. Using an animal movement example, we show how these estimation problems can affect ecological inference. Biased parameter estimates of a SSM describing the movement of polar bears (Ursus maritimus) result in overestimating their energy expenditure. We suggest potential solutions, but show that it often remains difficult to estimate parameters. While SSMs are powerful tools, they can give misleading results and we urge ecologists to assess whether the parameters can be estimated accurately before drawing ecological conclusions from their results. PMID:27220686
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.
Conceptual geologic model and native state model of the Roosevelt Hot Springs hydrothermal system
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.
Conceptual geologic model and native state model of the Roosevelt Hot Springs hydrothermal system
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.
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…
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…
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…
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.
State-space reduction and equivalence class sampling for a molecular self-assembly model.
Packwood, Daniel M; Han, Patrick; Hitosugi, Taro
2016-07-01
Direct simulation of a model with a large state space will generate enormous volumes of data, much of which is not relevant to the questions under study. In this paper, we consider a molecular self-assembly model as a typical example of a large state-space model, and present a method for selectively retrieving 'target information' from this model. This method partitions the state space into equivalence classes, as identified by an appropriate equivalence relation. The set of equivalence classes H, which serves as a reduced state space, contains none of the superfluous information of the original model. After construction and characterization of a Markov chain with state space H, the target information is efficiently retrieved via Markov chain Monte Carlo sampling. This approach represents a new breed of simulation techniques which are highly optimized for studying molecular self-assembly and, moreover, serves as a valuable guideline for analysis of other large state-space models. PMID:27493765
State-space reduction and equivalence class sampling for a molecular self-assembly model
Han, Patrick; Hitosugi, Taro
2016-01-01
Direct simulation of a model with a large state space will generate enormous volumes of data, much of which is not relevant to the questions under study. In this paper, we consider a molecular self-assembly model as a typical example of a large state-space model, and present a method for selectively retrieving ‘target information’ from this model. This method partitions the state space into equivalence classes, as identified by an appropriate equivalence relation. The set of equivalence classes H, which serves as a reduced state space, contains none of the superfluous information of the original model. After construction and characterization of a Markov chain with state space H, the target information is efficiently retrieved via Markov chain Monte Carlo sampling. This approach represents a new breed of simulation techniques which are highly optimized for studying molecular self-assembly and, moreover, serves as a valuable guideline for analysis of other large state-space models. PMID:27493765
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.
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)
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)
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.
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.
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.
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.
State-Based Models for Light Curve Classification
NASA Astrophysics Data System (ADS)
Becker, A.
I discuss here the application of continuous time autoregressive models to the characterization of astrophysical variability. These types of models are general enough to represent many classes of variability, and descriptive enough to provide features for lightcurve classification. Importantly, the features of these models may be interpreted in terms of the power spectrum of the lightcurve, enabling constraints on characteristic timescales and periodicity. These models may be extended to include vector-valued inputs, raising the prospect of a fully general modeling and classification environment that uses multi-passband inputs to create a single phenomenological model. These types of spectral-temporal models are an important extension of extant techniques, and necessary in the upcoming eras of Gaia and LSST.
Relativistic three-boson bound-state model
Dulany, P.C.; Wallace, S.J.; Delfino, A.
1995-04-01
A three dimensional three-boson bound-state equation is derived from the four dimensional Bethe-Salpeter equation via an instant form of the quasipotential formalism. This provides a Schrodinger-like relativistic equation with a single, global Green`s function and relativistic dynamics. This equation is solved in momentum space for the lowest bound state without using partial wave decomposition. The lowest bound state is also calculated using the Schrodinger wavefunction. It is found that, using the Malfliet-Tjon V two particle interaction, perturbative calculations predict that the relativistic corrections decrease the binding energy by between 0.863 MeV to 1.461 MeV, while the actual corrections decrease the binding energy by between 0.014 MeV to 0.200 MeV.
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
Models of Distance Education for Developing Island States.
ERIC Educational Resources Information Center
Meacham, David; Zubair, Shafeea
The key to successful establishment of distance education in developing countries seems to be the initial choice of an appropriate model (a model that can be built upon the historical and cultural context, can survive in an environment of limited resources, and will be compatible with the views and ambitions of its political sponsors and clients).…
Quasiparticle-phonon model and quadrupole mixed-symmetry states of 96Ru
NASA Astrophysics Data System (ADS)
Stoyanov, Ch.; Pietralla, N.
2016-01-01
The structure of low-lying quadrupole states of 96Ru was calculated within the Quasiparticle-Phonon Model. It is shown that symmetric and mixed-symmetry properties manifest themselves via the structure of the excited states. The first 2+ state is collective and neutron and proton transition matrix elements Mn and Mp are in-phase, while the neutron and proton transition matrix elements Mn and Mp have opposite signs for the third 2+ state. This property of the third 2+ state leads to a large M1 transition between the first and third 2+ states. It is an unambigous demonstration of the mixed-symmetry nature of the third 2+ state. The structure of the first 1+ state is calculated. The state is a member of the two-phonon multiplet generated by the coupling of the [21+]QRPA and the [22+]QRPA states.
Current State of Animal (Mouse) Modeling in Melanoma Research
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
Current State of Animal (Mouse) Modeling in Melanoma Research.
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.
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.
Technology Transfer Automated Retrieval System (TEKTRAN)
State and transition models (STMs) are being developed for many areas in the United States and represent an important tool for assessing and managing public and private rangelands. Substantial resources have been invested in model development, yet minimal efforts have been made to evaluate the utili...
Description of superdeformed nuclear states in the interacting boson model
Liu, Y.; Zhao, E.; Liu, Y.; Song, J.; Liu, Y.; Sun, H.; Zhao, E.; Liu, Y.; Sun, H.
1997-09-01
We show in this paper that the superdeformed nuclear states can be described with a four parameter formula in the spirit of the perturbated SU(3) limit of the sdg IBM. The E2 transition {gamma}-ray energies, the dynamical moments of inertia of the lowest superdeformed (SD) bands in even-even Hg, Pb, Gd, and Dy isotopes, and the energy differences {Delta}E{sub {gamma}}{minus}{Delta}E{sub {gamma}}{sup ref} of the SD band 1 of {sup 194}Hg are calculated. The calculated results agree with experimental data well. This indicates that the SD states are governed by a rotational interaction plus a perturbation with SO{sub sdg}(5) symmetry. The perturbation causing the {Delta}I=4 bifurcation to emerge in the {Delta}I=2 superdeformed rotational band may then possess SO{sub sdg}(5) symmetry. {copyright} {ital 1997} {ital The American Physical Society}
Computer mentoring for school nurses: the New York State model.
Schoessler, S Z; Leever, J S
2000-12-01
As computer use in the school health office is becoming a necessity, learning and upgrading technology skills is a high priority for school nurses across the country. The New York State Association of School Nurses and the Statewide Advocacy for School Health Services conducted a needs assessment to determine school nurses' perceptions of information technology skill level and the use of technology in the school health office. From these data, they have collaboratively developed a computer-mentoring program to be used throughout New York State. This program pairs standardized computer training with the assignment of peer mentors to support novice computer users during the adoption of technology into New York's school health services.
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)
Modelling Subaqueous Debris Flows - A comparison of two state-of-the-art integrated models
NASA Astrophysics Data System (ADS)
Spinewine, Benoit; Sfouni-Grigoriadou, Mariangela; Ingarfield, Samuel
2015-04-01
With the gradual depletion of nearshore resources and technological advances in oil and gas production, developments are now often located beyond the continental shelf in environments susceptible to mass movement events. The risk to subsea infrastructure from these events is often quantified through: i) an assessment of potential unstable slope areas and ii) numerical modelling of the potential slide runout behaviour. This submission compares two different state-of-the-art depth-averaged numerical models for debris flow runout. These models both incorporate advanced rheology modelling and are capable of modelling slide behaviour over complex 3D bathymetry, but solve the governing equations in two drastically differing fashions - the first of which solves these equations within an Eulerian, Finite Volume framework, whilst the second solves the equations within a Lagrangian framework through a technique known as Smoothed Particle Hydrodynamics (SPH). The relationship between shear stress and shear strain rate is modelled using either the linear viscoplastic Bingham or non-linear viscoplastic Herschel-Bulkley model. These numerical models also have a facility for the modelling of soil strength degradation during runout as a consequence of remoulding, as well as through the entrainment of ambient fluid. The soil mass itself is modelled as a rigid plug layer with an internal shear strain rate of zero, overlying a sheared layer where the shear stress at the interface between these layers is equal to the yield stress of the soil. The velocity in the plug layer is constant throughout its depth, whilst in the sheared layer it gradually diminishes to zero. The Eurlerian model relies on an unstructured triangular mesh for the representation of the bathymetry. This is constructed using a generator which provides for local refinement in the area of anticipated runout and along steeper slopes or channelised areas. The equations are solved using a finite volume approach, using a
Empirical Geographic Modeling of Switchgrass Yields in the United States
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.
A model for steady-state HNF combustion
Louwers, J.; Gadiot, G.M.H.J.L.; Brewster, M.Q.; Son, S.F.
1997-09-01
A simple model for the combustion of solid monopropellants is presented. The condensed phase is treated by high activation energy asymptotics. The gas phase is treated by two limit cases: high activation energy, and low activation energy. This results in simplification of the gas phase energy equation, making an (approximate) analytical solution possible. The results of the model are compared with experimental results of Hydrazinium Nitroformate (HNF) combustion.
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.
Applicability of equations of state for modeling helium systems
NASA Astrophysics Data System (ADS)
Thomas, Rijo Jacob; Dutta, Rohan; Ghosh, Parthasarathi; Chowdhury, Kanchan
2012-07-01
Proper design of helium systems with large number of components and involved configurations such as helium liquefiers/refrigerators requires the use of tools like process simulators. The accuracy of the simulation results, to a great extent, depends on the accuracy of property data. For computation of thermodynamic properties of helium, the 32-parameter MBWR equation of state proposed by McCarty and Arp [1] is widely used. However, it is computationally involved, makes the simulation process more time-consuming and sometimes leads to computational difficulties such as numerical oscillations, divergence in solution especially, when the process operates over a wide thermodynamic region and is constituted of many components. Substituting MBWR EOS by simpler equations of state (EOS(s)) at selected thermodynamic planes, where the simpler EOS(s) have the similar accuracy as that of MBWR EOS may enhance ease of computation. In the present paper, the methodology to implement this concept has been elucidated with examples of steady state and dynamic simulation of helium liquefier/refrigerator based on Collins cycle. The above concept can be applied to thermodynamic analysis of other process cycles where computation of fluid property is involved.
State-transition modeling: a report of the ISPOR-SMDM Modeling Good Research Practices Task Force-3.
Siebert, Uwe; Alagoz, Oguzhan; Bayoumi, Ahmed M; Jahn, Beate; Owens, Douglas K; Cohen, David J; Kuntz, Karen M
2012-01-01
State-transition modeling (STM) is an intuitive, flexible, and transparent approach of computer-based decision-analytic modeling, including both Markov model cohort simulation as well as individual-based (first-order Monte Carlo) microsimulation. Conceptualizing a decision problem in terms of a set of (health) states and transitions among these states, STM is one of the most widespread modeling techniques in clinical decision analysis, health technology assessment, and health-economic evaluation. STMs have been used in many different populations and diseases, and their applications range from personalized health care strategies to public health programs. Most frequently, state-transition models are used in the evaluation of risk factor interventions, screening, diagnostic procedures, treatment strategies, and disease management programs. PMID:22990084
Local hidden variable models for entangled quantum States using finite shared randomness.
Bowles, Joseph; Hirsch, Flavien; Quintino, Marco Túlio; Brunner, Nicolas
2015-03-27
The statistics of local measurements performed on certain entangled states can be reproduced using a local hidden variable (LHV) model. While all known models make use of an infinite amount of shared randomness, we show that essentially all entangled states admitting a LHV model can be simulated with finite shared randomness. Our most economical model simulates noisy two-qubit Werner states using only log_{2}(12)≃3.58 bits of shared randomness. We also discuss the case of positive operator valued measures, and the simulation of nonlocal states with finite shared randomness and finite communication. Our work represents a first step towards quantifying the cost of LHV models for entangled quantum states.
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.
NASA Astrophysics Data System (ADS)
Jiménez, Andrea
2014-02-01
We study the unexpected asymptotic behavior of the degeneracy of the first few energy levels in the antiferromagnetic Ising model on triangulations of closed Riemann surfaces. There are strong mathematical and physical reasons to expect that the number of ground states (i.e., degeneracy) of the antiferromagnetic Ising model on the triangulations of a fixed closed Riemann surface is exponential in the number of vertices. In the set of plane triangulations, the degeneracy equals the number of perfect matchings of the geometric duals, and thus it is exponential by a recent result of Chudnovsky and Seymour. From the physics point of view, antiferromagnetic triangulations are geometrically frustrated systems, and in such systems exponential degeneracy is predicted. We present results that contradict these predictions. We prove that for each closed Riemann surface S of positive genus, there are sequences of triangulations of S with exactly one ground state. One possible explanation of this phenomenon is that exponential degeneracy would be found in the excited states with energy close to the ground state energy. However, as our second result, we show the existence of a sequence of triangulations of a closed Riemann surface of genus 10 with exactly one ground state such that the degeneracy of each of the 1st, 2nd, 3rd and 4th excited energy levels belongs to O( n), O( n 2), O( n 3) and O( n 4), respectively.
Regional Evacuation Modeling: A State of the Art Reviewing
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.
Steady-state Analysis Model for Advanced Fuelcycle Schemes
2006-05-12
The model was developed as a part of the study, "Advanced Fuel Cycles and Waste Management", which was performed during 20032005 by an ad-hoc expert group under the Nuclear Development Committee in the OECD/NEA. The model was designed for an efficient conduct of nuclear fuel cycle scheme cost analyses. It is simple, transparent and offers users the capability to track down the cost analysis results. All the fuel cycle schemes considered in the model aremore » represented in a graphic format and all values related to a fuel cycle step are shown in the graphic interface, i.e., there are no hidden values embedded in the calculations. All data on the fuel cycle schemes considered in the study including mass flows, waste generation, cost data, and other data such as activities, decay heat and neutron sources of spent fuel and highlevel waste along time are included in the model and can be displayed. The user can modify easily the values of mass flows and/or cost parameters and see the corresponding changes in the results. The model calculates: frontend fuel cycle mass flows such as requirements of enrichment and conversion services and natural uranium; mass of waste based on the waste generation parameters and the mass flow; and all costs. It performs Monte Carlo simulations with changing the values of all unit costs within their respective ranges (from lower to upper bounds).« less
Mouse models of ciliopathies: the state of the art
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
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.
The United States Geological Survey Science Data Lifecycle Model
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.
State of the art of sonic boom modeling.
Plotkin, Kenneth J
2002-01-01
Based on fundamental theory developed through the 1950s and 1960s, sonic boom modeling has evolved into practical tools. Over the past decade, there have been requirements for design tools for an advanced supersonic transport, and for tools for environmental assessment of various military and aerospace activities. This has resulted in a number of advances in the understanding of the physics of sonic booms, including shock wave rise times, propagation through turbulence, and blending sonic boom theory with modern computational fluid dynamics (CFD) aerodynamic design methods. This article reviews the early fundamental theory, recent advances in theory, and the application of these advances to practical models. PMID:11837958
State-space model with deep learning for functional dynamics estimation in resting-state fMRI.
Suk, Heung-Il; Wee, Chong-Yaw; Lee, Seong-Whan; Shen, Dinggang
2016-04-01
Studies on resting-state functional Magnetic Resonance Imaging (rs-fMRI) have shown that different brain regions still actively interact with each other while a subject is at rest, and such functional interaction is not stationary but changes over time. In terms of a large-scale brain network, in this paper, we focus on time-varying patterns of functional networks, i.e., functional dynamics, inherent in rs-fMRI, which is one of the emerging issues along with the network modelling. Specifically, we propose a novel methodological architecture that combines deep learning and state-space modelling, and apply it to rs-fMRI based Mild Cognitive Impairment (MCI) diagnosis. We first devise a Deep Auto-Encoder (DAE) to discover hierarchical non-linear functional relations among regions, by which we transform the regional features into an embedding space, whose bases are complex functional networks. Given the embedded functional features, we then use a Hidden Markov Model (HMM) to estimate dynamic characteristics of functional networks inherent in rs-fMRI via internal states, which are unobservable but can be inferred from observations statistically. By building a generative model with an HMM, we estimate the likelihood of the input features of rs-fMRI as belonging to the corresponding status, i.e., MCI or normal healthy control, based on which we identify the clinical label of a testing subject. In order to validate the effectiveness of the proposed method, we performed experiments on two different datasets and compared with state-of-the-art methods in the literature. We also analyzed the functional networks learned by DAE, estimated the functional connectivities by decoding hidden states in HMM, and investigated the estimated functional connectivities by means of a graph-theoretic approach. PMID:26774612
State-space model with deep learning for functional dynamics estimation in resting-state fMRI.
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.
NASA Astrophysics Data System (ADS)
Lee, Yongjin; Shin, Moon Sam; Kim, Hwayong
2008-12-01
In this study, a new crossover sine model (CSM) n was developed from a trigonometric model [M. E. Fisher, S. Zinn, and P. J. Upton, Phys. Rev. B 59, 14533 (1999)]. The trigonometric model is a parametric formulation model that is used to represent the thermodynamic variables near a critical point. Although there are other crossover models based on this trigonometric model, such as the CSM and the analytical sine model, which is an analytic formulation of the CSM, the new sine model (NSM) employs a different approach from these two models in terms of the connections between the parametric variables of the trigonometric model and thermodynamic variables. In order to test the performance of the NSM, the crossover lattice equation of state [M. S. Shin, Y. Lee, and H. Kim, J. Chem. Thermodyn. 40, 174 (2008)] was applied using the NSM for correlations of various pure fluids and fluid mixtures. The results showed that over a wide range of states, the crossover lattice fluid (xLF)/NSM yields the saturated properties of pure fluids and the phase behavior of binary mixtures more accurately than the original lattice equation of state. Moreover, a comparison with the crossover lattice equation of state using the CSM (xLF/CSM) showed that the new model presents good correlation results that are comparable to the xLF/CSM.
Lee, Yongjin; Shin, Moon Sam; Kim, Hwayong
2008-12-21
In this study, a new crossover sine model (CSM) n was developed from a trigonometric model [M. E. Fisher, S. Zinn, and P. J. Upton, Phys. Rev. B 59, 14533 (1999)]. The trigonometric model is a parametric formulation model that is used to represent the thermodynamic variables near a critical point. Although there are other crossover models based on this trigonometric model, such as the CSM and the analytical sine model, which is an analytic formulation of the CSM, the new sine model (NSM) employs a different approach from these two models in terms of the connections between the parametric variables of the trigonometric model and thermodynamic variables. In order to test the performance of the NSM, the crossover lattice equation of state [M. S. Shin, Y. Lee, and H. Kim, J. Chem. Thermodyn. 40, 174 (2008)] was applied using the NSM for correlations of various pure fluids and fluid mixtures. The results showed that over a wide range of states, the crossover lattice fluid (xLF)/NSM yields the saturated properties of pure fluids and the phase behavior of binary mixtures more accurately than the original lattice equation of state. Moreover, a comparison with the crossover lattice equation of state using the CSM (xLF/CSM) showed that the new model presents good correlation results that are comparable to the xLF/CSM.
A new state space model for the NASA/JPL 70-meter antenna servo controls
NASA Technical Reports Server (NTRS)
Hill, R. E.
1987-01-01
A control axis referenced model of the NASA/JPL 70-m antenna structure is combined with the dynamic equations of servo components to produce a comprehansive state variable (matrix) model of the coupled system. An interactive Fortran program for generating the linear system model and computing its salient parameters is described. Results are produced in a state variable, block diagram, and in factored transfer function forms to facilitate design and analysis by classical as well as modern control methods.
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…
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…
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.
Steady-State Analysis Model for Advanced Fuel Cycle Schemes.
2008-03-17
Version 00 SMAFS was developed as a part of the study, "Advanced Fuel Cycles and Waste Management", which was performed during 2003-2005 by an ad-hoc expert group under the Nuclear Development Committee in the OECD/NEA. The model was designed for an efficient conduct of nuclear fuel cycle scheme cost analyses. It is simple, transparent and offers users the capability to track down cost analysis results. All the fuel cycle schemes considered in the model aremore » represented in a graphic format and all values related to a fuel cycle step are shown in the graphic interface, i.e., there are no hidden values embedded in the calculations. All data on the fuel cycle schemes considered in the study including mass flows, waste generation, cost data, and other data such as activities, decay heat and neutron sources of spent fuel and high-level waste along time are included in the model and can be displayed. The user can easily modify values of mass flows and/or cost parameters and see corresponding changes in the results. The model calculates: front-end fuel cycle mass flows such as requirements of enrichment and conversion services and natural uranium; mass of waste based on the waste generation parameters and the mass flow; and all costs.« less
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
Phase coexistence in partially symmetric q-state models
NASA Astrophysics Data System (ADS)
Laanait, Lahoussine; Masaif, Noureddine; Ruiz, Jean
1993-08-01
We consider a lattice model whose spins may assume a finite number q of values. The interaction energy between two nearest-neighbor spins takes on the value J 1 + J 2 or J 2, depending on whether the two spins coincide or are different but coincide modulo q1, and it is zero otherwise. This model is a generalization of the Ashkin-Teller model and exhibits the multilayer wetting phenomenon, that is, wetting by one or two or three interfacial layers, depending on the number of phases in coexistence. While we plan to consider interface properties in such a case, here we study the phase diagram of the model. We show that for large values of q 1 and q/q 1, it exhibits, according the value of J 2/ J 1, either a unique first-order temperature-driven phase transition at some point β t where q ordered phases coexist with the disordered one, or two transition temperatures β{t/(1)} and β{t/(2)}, where q1 partially ordered phases coexist with the ordered ones (β{t/(1)}) or with the disordered one (β{t/(2)}), or for a particular value of J 2/ J 1 there is a unique transition temperature where all the previous phases coexist. Proofs are based on the Pirogov-Sinai theory: we perform a random cluster representation of the model (allowing us to consider noninteger values of q 1 and q/q 1) to which we adapt this theory.
The steady-state phase distribution of the motor switch complex model of Halobacterium salinarum.
del Rosario, Ricardo C H; Diener, Francine; Diener, Marc; Oesterhelt, Dieter
2009-12-01
Steady-state analysis is performed on the kinetic model for the switch complex of the flagellar motor of Halobacterium salinarum (Nutsch et al.). The existence and uniqueness of a positive steady-state of the system is established and it is demonstrated why the steady-state is centered around the competent phase, a state of the motor in which it is able to respond to light stimuli. It is also demonstrated why the steady-state shifts to the refractory phase when the steady-state value of the response regulator CheYP increases. This work is one aspect of modeling in systems biology wherein the mathematical properties of a model are established. PMID:19857501
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.
Sharp Contradiction for Local-Hidden-State Model in Quantum Steering.
Chen, Jing-Ling; Su, Hong-Yi; Xu, Zhen-Peng; Pati, Arun Kumar
2016-08-26
In quantum theory, no-go theorems are important as they rule out the existence of a particular physical model under consideration. For instance, the Greenberger-Horne-Zeilinger (GHZ) theorem serves as a no-go theorem for the nonexistence of local hidden variable models by presenting a full contradiction for the multipartite GHZ states. However, the elegant GHZ argument for Bell's nonlocality does not go through for bipartite Einstein-Podolsky-Rosen (EPR) state. Recent study on quantum nonlocality has shown that the more precise description of EPR's original scenario is "steering", i.e., the nonexistence of local hidden state models. Here, we present a simple GHZ-like contradiction for any bipartite pure entangled state, thus proving a no-go theorem for the nonexistence of local hidden state models in the EPR paradox. This also indicates that the very simple steering paradox presented here is indeed the closest form to the original spirit of the EPR paradox.
Evaluating an interprofessional disease state and medication management review model.
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.
Steady-state cracks in viscoelastic lattice models
Kessler, D.A.; Levine, H.
1999-05-01
We study the steady-state motion of mode III cracks propagating on a lattice exhibiting viscoelastic dynamics. The introduction of a Kelvin viscosity {eta} allows for a direct comparison between lattice results and continuum treatments. Utilizing both numerical and analytical (Wiener-Hopf) techniques, we explore this comparison as a function of the driving displacement {Delta} and the number of transverse rows {ital N}. At any {ital N}, the continuum theory misses the lattice-trapping phenomenon; this is well known, but the introduction of {eta} introduces some new twists. More importantly, for large {ital N} even at large {Delta}, the standard two-dimensional elastodynamics approach completely misses the {eta}-dependent velocity selection, as this selection disappears completely in the leading order naive continuum limit of the lattice problem. {copyright} {ital 1999} {ital The American Physical Society}
Interpolation of steady-state concentration data by inverse modeling.
Schwede, Ronnie L; Cirpka, Olaf A
2010-01-01
In most groundwater applications, measurements of concentration are limited in number and sparsely distributed within the domain of interest. Therefore, interpolation techniques are needed to obtain most likely values of concentration at locations where no measurements are available. For further processing, for example, in environmental risk analysis, interpolated values should be given with uncertainty bounds, so that a geostatistical framework is preferable. Linear interpolation of steady-state concentration measurements is problematic because the dependence of concentration on the primary uncertain material property, the hydraulic conductivity field, is highly nonlinear, suggesting that the statistical interrelationship between concentration values at different points is also nonlinear. We suggest interpolating steady-state concentration measurements by conditioning an ensemble of the underlying log-conductivity field on the available hydrological data in a conditional Monte Carlo approach. Flow and transport simulations for each conditional conductivity field must meet the measurements within their given uncertainty. The ensemble of transport simulations based on the conditional log-conductivity fields yields conditional statistical distributions of concentration at points between observation points. This method implicitly meets physical bounds of concentration values and non-Gaussianity of their statistical distributions and obeys the nonlinearity of the underlying processes. We validate our method by artificial test cases and compare the results to kriging estimates assuming different conditional statistical distributions of concentration. Assuming a beta distribution in kriging leads to estimates of concentration with zero probability of concentrations below zero or above the maximal possible value; however, the concentrations are not forced to meet the advection-dispersion equation.
Monthly Water Balance Model Portal for the United States
NASA Astrophysics Data System (ADS)
Hay, L.; Bock, A.; Markstrom, S. L.; McCabe, G. J., Jr.; Atkinson, D.
2014-12-01
The Monthly Water Balance Model (MWBM) portal delivers MWBM output generated for current and future climatic conditions for stream segments and hydrologic response units derived from the US Geological Survey's National Hydrologic Model Geospatial Fabric. The MWBM is a modular system that provides monthly estimates of components of the hydrologic cycle (e.g. streamflow, potential and actual evapotranspiration, snowpack, and storage) computed from mean monthly temperature, monthly total precipitation, latitude, and available soil water capacity. The MWBM portal can generate reports and graphics using simulations from more than 200 current and future climate scenarios at any location within the contiguous US. This presentation will introduce users to the MWBM portal and demonstrate how to access and download MWBM portal data.
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.
A NON-RADIAL OSCILLATION MODEL FOR PULSAR STATE SWITCHING
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.
Solid state convection models of lunar internal temperature
NASA Technical Reports Server (NTRS)
Schubert, G.; Young, R. E.; Cassen, P.
1975-01-01
Thermal models of the Moon were made which include cooling by subsolidus creep and consideration of the creep behavior of geologic material. Measurements from the Apollo program on seismic velocities, electrical conductivity of the Moon's interior, and heat flux at two locations were used in the calculations. Estimates of 1500 to 1600 K were calculated for the temperature, and one sextillion to ten sextillion sq cm/sec were calcualted for the viscosity of the deep lunar interior.
How ψ-epistemic models fail at explaining the indistinguishability of quantum states.
Branciard, Cyril
2014-07-11
We study the extent to which ψ-epistemic models for quantum measurement statistics-models where the quantum state does not have a real, ontic status-can explain the indistinguishability of nonorthogonal quantum states. This is done by comparing the overlap of any two quantum states with the overlap of the corresponding classical probability distributions over ontic states in a ψ-epistemic model. It is shown that in Hilbert spaces of dimension d≥4, the ratio between the classical and quantum overlaps in any ψ-epistemic model must be arbitrarily small for certain nonorthogonal states, suggesting that such models are arbitrarily bad at explaining the indistinguishability of quantum states. For dimensions d=3 and 4, we construct explicit states and measurements that can be used experimentally to put stringent bounds on the ratio of classical-to-quantum overlaps in ψ-epistemic models, allowing one in particular to rule out maximally ψ-epistemic models more efficiently than previously proposed.
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.
State Faith-Based Education in Israel: A Messianic-Nationalist Model of Interpretation
ERIC Educational Resources Information Center
Silberman-Keller, Diana
2005-01-01
This article analyzes the traces and configuration of three syntagmatic interpretation models in the educational text produced by Israel's state religious educational system: the "modus", the "hermetic" and the "gnostic" models, which together add up to a fourth, and unique one: "the messianic nationalist" model of interpretation. This…
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…
Wang-Landau Algorithm for Continuous Models and Joint Density of States
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.
Modeling enzymatic transition states by force field methods
NASA Astrophysics Data System (ADS)
Hansen, M. B.; Jensen, H. J. A.; Jensen, F.
The SEAM method, which models a transition structure as a minimum on the seam of two diabatic surfaces represented by force field functions, has been used to generate 20 transition structures for the decarboxylation of orotidine by the orotidine-5prime-monophosphate decarboxylase enzyme. The dependence of the TS geometry on the flexibility of the system has been probed by fixing layers of atoms around the active site and using increasingly larger nonbonded cutoffs. The variability over the 20 structures is found to decrease as the system is made more flexible. Relative energies have been calculated by various electronic structure methods, where part of the enzyme is represented by a force field description and the effects of the solvent are represented by a continuum model. The relative energies vary by several hundreds of kJ/mol between the transition structures, and tests showed that a large part of this variation is due to changes in the enzyme structure at distances more than 5 Å from the active site. There are significant differences between the results obtained by pure quantum methods and those from mixed quantum and molecular mechanics methods.
Kinks and bound states in the Gross-Neveu model
NASA Astrophysics Data System (ADS)
Feinberg, Joshua
1995-04-01
We investigate static space-dependent σ(x)=<ψ¯ψ> saddle point configurations in the two-dimensional Gross-Neveu model in the large N limit. We solve the saddle point condition for σ(x) explicitly by employing supersymmetric quantum mechanics and using simple properties of the diagonal resolvent of one-dimensional Schrödinger operators rather than inverse scattering techniques. The resulting solutions in the sector of unbroken supersymmetry are the Callan-Coleman-Gross-Zee kink configurations. We thus provide a direct and clean construction of these kinks. In the sector of broken supersymmetry we derive the DHN saddle point configurations. Our method of finding such nontrivial static configurations may be applied also in other two-dimensional field theories.
Astronomy across State Lines: A Collaborative Model for Astronomical Research
NASA Astrophysics Data System (ADS)
Johnson, Chelen H.; Barge, Jacqueline; Linahan, Marcella; York, Donald G.; Cante, David; Cook, Mary; Daw, Maeve; Donahoe, Katherine E.; Ford, Sydney; Haecker, Lille W.; Hibbs, Cecily A.; Hogan, Eleanor B.; Karos, Demetra N.; Kozikowski, Kendall G.; Martin, Taylor A.; Miranda, Fernando; Ng, Emily; Noel, Imany; O'Bryan, Sophie E.; Sharma, Vikrant; Zegeye, David
2015-01-01
Scientists do not work in isolation, nor should student scientists. In a collaborative effort, students from three high schools examined plates from the Sloan Digital Sky Survey (SDSS) to estimate the number of galaxies that contain evidence of a black hole. Working under the direction of Don York, former SDSS director, the three teachers used Google hangouts to discuss weekly progress. At their home institutions, students examined optical spectra from SDSS Data Release 10 to determine if a quasar could be discerned. Both Type I and Type II quasars can be seen in the SDSS data. Seven teams of students from different schools compared their findings and collaborated online to discuss potential discoveries. This project can serve as a model for high school teachers who want to facilitate their students participating in an authentic research project. The keys to a successful project are working with a mentor who can guide the group through difficult concepts and communicating frequently throughout the project.
Precessional States in a Laboratory Model of the Earth's Core
NASA Astrophysics Data System (ADS)
Triana, S. A.; Zimmerman, D.; Lathrop, D. P.
2010-12-01
A water-filled three-meter diameter spherical shell built as a model of the Earth's core shows evidence of precessionally induced flows. We identified the flow to be primarily the spin-over inertial wave mode, i.e., a uniform vorticity flow whose rotation axis is not aligned with the container's rotation axis. The mode's amplitude dependence on the Poincaré number is in qualitative agreement with Busse's laminar theory (JFM 33:739-751, 1968) while its phase differs significantly, perhaps due to topographic effects. At high rotation rates free shear layers concentrating most of the kinetic energy of the mode have been observed. Comparison with previous computational studies and implications for the Earth's core are discussed.
Precessional states in a laboratory model of the Earth's core
NASA Astrophysics Data System (ADS)
Triana, Santiago; Zimmerman, Daniel; Lathrop, Daniel
2010-11-01
A water-filled three-meter diameter spherical shell built as a model of the Earth's core shows evidence of precessionally induced flows. We identified the flow to be primarily the spin-over inertial wave mode, i.e., a uniform vorticity flow whose rotation axis is not aligned with the container's rotation axis. The mode's amplitude dependence on the Poincar'e number is in qualitative agreement with Busse's laminar theory (JFM 33:739-751, 1968) while its phase differs significantly, perhaps due to topographic effects. At high rotation rates free shear layers concentrating most of the kinetic energy of the mode have been observed. Comparison with previous computational studies and implications for the Earth's core are discussed.
Spatiotemporal modelling of ozone distribution in the State of California
NASA Astrophysics Data System (ADS)
Bogaert, P.; Christakos, G.; Jerrett, M.; Yu, H.-L.
This paper is concerned with the spatiotemporal mapping of monthly 8-h average ozone ( O3) concentrations over California during a 15-years period. The basic methodology of our analysis is based on the spatiotemporal random field (S/TRF) theory. We use a S/TRF decomposition model with a dominant seasonal O3 component that may change significantly from site to site. O3 seasonal patterns are estimated and separated from stochastic fluctuations. By means of Bayesian Maximum Entropy (BME) analysis, physically meaningful and sufficiently detailed space-time maps of the seasonal O3 patterns are generated across space and time. During the summer and winter months the seasonal O3 concentration maps exhibit clear and progressively changing geographical patterns over time, suggesting the existence of relationships in accordance with the typical physiographic and climatologic features of California. BME mapping accuracy can be superior to that of other techniques commonly used by EPA; its framework can rigorously assimilate useful data sources that were previously unaccounted for; the generated maps offer valuable assessments of the spatiotemporal O3 patterns that can be helpful in the identification of physical mechanisms and their interrelations, the design of human exposure and population health models, and in risk assessment. As they focus on the seasonal patterns, the maps are not contingent on short-time and locally prevalent weather conditions, which are of no interest in a global and non-forecasting framework. Moreover, the maps offer valuable insight about the space-time O3 concentration patterns and are, thus, helpful for disentangling the influence of explanatory factors or even for identifying some influential ones that could have been otherwise overlooked.
Modelling SF-6D health state preference data using a nonparametric Bayesian method.
Kharroubi, Samer A; Brazier, John E; Roberts, Jennifer; O'Hagan, Anthony
2007-05-01
This paper reports on the findings from applying a new approach to modelling health state valuation data. The approach applies a nonparametric model to estimate SF-6D health state utility values using Bayesian methods. The data set is the UK SF-6D valuation study where a sample of 249 states defined by the SF-6D (a derivative of the SF-36) was valued by a representative sample of the UK general population using standard gamble. The paper presents the results from applying the nonparametric model and comparing it to the original model estimated using a conventional parametric random effects model. The two models are compared theoretically and in terms of empirical performance. The paper discusses the implications of these results for future applications of the SF-6D and further work in this field. PMID:17069909
Two States Mapping Based Time Series Neural Network Model for Compensation Prediction Residual Error
NASA Astrophysics Data System (ADS)
Jung, Insung; Koo, Lockjo; Wang, Gi-Nam
2008-11-01
The objective of this paper was to design a model of human bio signal data prediction system for decreasing of prediction error using two states mapping based time series neural network BP (back-propagation) model. Normally, a lot of the industry has been applied neural network model by training them in a supervised manner with the error back-propagation algorithm for time series prediction systems. However, it still has got a residual error between real value and prediction result. Therefore, we designed two states of neural network model for compensation residual error which is possible to use in the prevention of sudden death and metabolic syndrome disease such as hypertension disease and obesity. We determined that most of the simulation cases were satisfied by the two states mapping based time series prediction model. In particular, small sample size of times series were more accurate than the standard MLP model.
Ground-state properties of linear-exchange quantum spin models
NASA Astrophysics Data System (ADS)
Danu, Bimla; Kumar, Brijesh; Pai, Ramesh V.
2012-10-01
We study a class of one-dimensional antiferromagnetic quantum spin-1/2 models using DMRG. The exchange interaction in these models decreases linearly with the separation between the spins, Jij = R - |i - j| for |i - j| < R, where R is a positive integer ⩾2. For |i - j| ⩾ R, the interaction is zero. It is known that all the odd-R models have the same exact dimer ground state as the Majumdar-Ghosh (MG) model. In fact, R = 3 is the MG model. However, for an even R, the exact ground state is not known in general, except for R = 2 (the integrable nearest-neighbor Heisenberg chain) and the asymptotic limit of R in which the MG dimer state emerges as the exact ground state. Therefore, we numerically study the ground-state properties of the finite even-R ≠ 2 models, particularly for R = 4, 6 and 8. We find that, unlike R = 2, the higher even-R models are spin-gapped, and exhibit robust dimer order of the MG type in the ground state. The spin-spin correlations decay rapidly to zero, albeit showing weak periodic revivals.
One size does not fit all: Adapting mark-recapture and occupancy models for state uncertainty
Kendall, W.L.; Thomson, David L.; Cooch, Evan G.; Conroy, Michael J.
2009-01-01
Multistate capture?recapture models continue to be employed with greater frequency to test hypotheses about metapopulation dynamics and life history, and more recently disease dynamics. In recent years efforts have begun to adjust these models for cases where there is uncertainty about an animal?s state upon capture. These efforts can be categorized into models that permit misclassification between two states to occur in either direction or one direction, where state is certain for a subset of individuals or is always uncertain, and where estimation is based on one sampling occasion per period of interest or multiple sampling occasions per period. State uncertainty also arises in modeling patch occupancy dynamics. I consider several case studies involving bird and marine mammal studies that illustrate how misclassified states can arise, and outline model structures for properly utilizing the data that are produced. In each case misclassification occurs in only one direction (thus there is a subset of individuals or patches where state is known with certainty), and there are multiple sampling occasions per period of interest. For the cases involving capture?recapture data I allude to a general model structure that could include each example as a special case. However, this collection of cases also illustrates how difficult it is to develop a model structure that can be directly useful for answering every ecological question of interest and account for every type of data from the field.
This state-of-the-science review was undertaken to identify fate and transport models and alternative modeling approaches that could be used to predict exposure to engineered nanomaterials (ENMs) released into the environment, specifically, for aquatic systems. The development of...
A quark model calculation of yy->pipi including final-state interactions
H.G. Blundell; S. Godfrey; G. Hay; Eric Swanson
2000-02-01
A quark model calculation of the processes yy->pi+pi- and yy->pipi is performed. At tree level, only charged pions couple to the initial state photons and neutral pions are not exceeded in the final state. However a small but significant cross section is observed. We demonstrate that this may be accounted for by a rotation in isospin space induced by final-state interactions.
Michael Swyer
2015-02-05
Matlab scripts/functions and data used to build Poly3D models and create permeability potential GIS layers for 1) Mount St Helen's, 2) Wind River Valley, and 3) Mount Baker geothermal prospect areas located in Washington state.
NASA Astrophysics Data System (ADS)
Nie, Lin-Fei; Teng, Zhi-Dong; Nieto, Juan J.; Jung, Il Hyo
2015-07-01
For reasons of preserving endangered languages, we propose, in this paper, a novel two-languages competitive model with bilingualism and interlinguistic similarity, where state-dependent impulsive control strategies are introduced. The novel control model includes two control threshold values, which are different from the previous state-dependent impulsive differential equations. By using qualitative analysis method, we obtain that the control model exhibits two stable positive order-1 periodic solutions under some general conditions. Moreover, numerical simulations clearly illustrate the main theoretical results and feasibility of state-dependent impulsive control strategies. Meanwhile numerical simulations also show that state-dependent impulsive control strategy can be applied to other general two-languages competitive model and obtain the desired result. The results indicate that the fractions of two competitive languages can be kept within a reasonable level under almost any circumstances. Theoretical basis for finding a new control measure to protect the endangered language is offered.
NASA Technical Reports Server (NTRS)
Canfield, Stephen
1999-01-01
This work will demonstrate the integration of sensor and system dynamic data and their appropriate models using an optimal filter to create a robust, adaptable, easily reconfigurable state (motion) estimation system. This state estimation system will clearly show the application of fundamental modeling and filtering techniques. These techniques are presented at a general, first principles level, that can easily be adapted to specific applications. An example of such an application is demonstrated through the development of an integrated GPS/INS navigation system. This system acquires both global position data and inertial body data, to provide optimal estimates of current position and attitude states. The optimal states are estimated using a Kalman filter. The state estimation system will include appropriate error models for the measurement hardware. The results of this work will lead to the development of a "black-box" state estimation system that supplies current motion information (position and attitude states) that can be used to carry out guidance and control strategies. This black-box state estimation system is developed independent of the vehicle dynamics and therefore is directly applicable to a variety of vehicles. Issues in system modeling and application of Kalman filtering techniques are investigated and presented. These issues include linearized models of equations of state, models of the measurement sensors, and appropriate application and parameter setting (tuning) of the Kalman filter. The general model and subsequent algorithm is developed in Matlab for numerical testing. The results of this system are demonstrated through application to data from the X-33 Michael's 9A8 mission and are presented in plots and simple animations.
Measuring up to the Model: A Ranking of State Charter School Laws. Seventh Edition
ERIC Educational Resources Information Center
Ziebarth, Todd
2016-01-01
This seventh edition of "Measuring up to the Model: A Ranking of State Charter School Laws" presents the latest activity in charter public school legislation across the country. Some highlights include: (1) significant activity regarding potential enabling legislation in several of the states without charter public school laws, (2)…
ERIC Educational Resources Information Center
Newton, Jill A.; Kasten, Sarah E.
2013-01-01
The release of the Common Core State Standards for Mathematics and their adoption across the United States calls for careful attention to the alignment between mathematics standards and assessments. This study investigates 2 models that measure alignment between standards and assessments, the Surveys of Enacted Curriculum (SEC) and the Webb…
An Experimental Model for Analyzing Strategies for Financing Higher Education in New York State.
ERIC Educational Resources Information Center
New York State Education Dept., Albany. Office of Postsecondary Research, Information Systems, and Institutional Aid.
Described is an experimental, quantitative model developed by the New York State Education Department to evaluate state-level financing strategies for higher education. It can be used to address a variety of questions and takes into account a host of direct and indirect relationships. It uses computer software and optimization algorithms developed…
State-and-transition models as guides for adaptive management: What are the needs?
Technology Transfer Automated Retrieval System (TEKTRAN)
State and transaction models (STMs) were conceived as a means to organize information about land potential and vegetation dynamics in rangelands to be used in their management. The basic idea is to describe the plant community states that can occur on a site and the causes of transitions between the...
Analyticity of quantum states in one-dimensional tight-binding model
NASA Astrophysics Data System (ADS)
Yamada, Hiroaki S.; Ikeda, Kensuke S.
2014-09-01
Analytical complexity of quantum wavefunction whose argument is extended into the complex plane provides an important information about the potentiality of manifesting complex quantum dynamics such as time-irreversibility, dissipation and so on. We examine Pade approximation and some complementary methods to investigate the complex-analytical properties of some quantum states such as impurity states, Anderson-localized states and localized states of Harper model. The impurity states can be characterized by simple poles of the Pade approximation, and the localized states of Anderson model and Harper model can be characterized by an accumulation of poles and zeros of the Pade approximated function along a critical border, which implies a natural boundary (NB). A complementary method based on shifting the expansion-center is used to confirm the existence of the NB numerically, and it is strongly suggested that the both Anderson-localized state and localized states of Harper model have NBs in the complex extension. Moreover, we discuss an interesting relationship between our research and the natural boundary problem of the potential function whose close connection to the localization problem was discovered quite recently by some mathematicians. In addition, we examine the usefulness of the Pade approximation for numerically predicting the existence of NB by means of two typical examples, lacunary power series and random power series.
ERIC Educational Resources Information Center
Nunez, Anne-Marie; Kim, Dongbin
2012-01-01
Latinos' college enrollment rates, particularly in four-year institutions, have not kept pace with their population growth in the United States. Using three-level hierarchical generalized linear modeling, this study analyzes data from the Educational Longitudinal Study (ELS) to examine the influence of high school and state contexts, in addition…
Digital soil mapping as a tool for quantifying state-and-transition models
Technology Transfer Automated Retrieval System (TEKTRAN)
Ecological sites and associated state-and-transition models (STMs) are rapidly becoming important land management tools in rangeland systems in the US and around the world. Descriptions of states and transitions are largely developed from expert knowledge and generally accepted species and community...
Modeling studies of the natural state of the Krafla geothermal field, Iceland
Bodvarsson, G.S.; Pruess, K.; Stefansson, V.; Eliasson, E.T.
1982-12-01
The modeling of the natural state of the Krafla system has yielded results that closely match all available field data, and agree with a conceptual model developed from geochemical observations. Furthermore, studies of the sensitivity of various parameters give valuable insight into the permeabilities of different reservoir zones, thermal conductivity of the caprock, rates and enthalpies of natural recharge and discharge, and various other important reservoir parameters. The model presented here is two-dimensional, and only considers a part of the old wellfield. In the future, we hope to develop a natural-state model for the entire Krafla system, taking into account the three-dimensional nature of fluid flows.
Generalized Treanor-Marrone model for state-specific dissociation rate coefficients
NASA Astrophysics Data System (ADS)
Kunova, O.; Kustova, E.; Savelev, A.
2016-08-01
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 its parameter 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. Non-equilibrium kinetics of O2/O and N2/N mixtures under heat bath conditions is studied; applying the optimized Treanor-Marrone model leads to more efficient dissociation and vibrational relaxation.
NASA Astrophysics Data System (ADS)
Raksincharoensak, Pongsathorn; Khaisongkram, Wathanyoo; Nagai, Masao; Shimosaka, Masamichi; Mori, Taketoshi; Sato, Tomomasa
2010-12-01
This paper describes the modelling of naturalistic driving behaviour in real-world traffic scenarios, based on driving data collected via an experimental automobile equipped with a continuous sensing drive recorder. This paper focuses on the longitudinal driving situations which are classified into five categories - car following, braking, free following, decelerating and stopping - and are referred to as driving states. Here, the model is assumed to be represented by a state flow diagram. Statistical machine learning of driver-vehicle-environment system model based on driving database is conducted by a discriminative modelling approach called boosting sequential labelling method.
Spatiotemporal modeling of internal states distribution for lithium-ion battery
NASA Astrophysics Data System (ADS)
Wang, Mingliang; Li, Han-Xiong
2016-01-01
Electrochemical properties of the battery are described in partial differential equations that are impossible to compute online. These internal states are spatially distributed and thus difficult to measure in the battery operation. A space-time separation method is applied to model the electrochemical properties of the battery with the help of the extended Kalman filter. The model is efficiently optimized by using LASSO adaptation method and can be updated through data-based learning. The analytical model derived is able to offer a fast estimation of internal states of the battery, and thus has potential to become a prediction model for battery management system.
State-and-transition prototype model of riparian vegetation downstream of Glen Canyon Dam, Arizona
Ralston, Barbara E.; Starfield, Anthony M.; Black, Ronald S.; Van Lonkhuyzen, Robert A.
2014-01-01
Facing an altered riparian plant community dominated by nonnative species, resource managers are increasingly interested in understanding how to manage and promote healthy riparian habitats in which native species dominate. For regulated rivers, managing flows is one tool resource managers consider to achieve these goals. Among many factors that can influence riparian community composition, hydrology is a primary forcing variable. Frame-based models, used successfully in grassland systems, provide an opportunity for stakeholders concerned with riparian systems to evaluate potential riparian vegetation responses to alternative flows. Frame-based, state-and-transition models of riparian vegetation for reattachment bars, separation bars, and the channel margin found on the Colorado River downstream of Glen Canyon Dam were constructed using information from the literature. Frame-based models can be simple spreadsheet models (created in Microsoft® Excel) or developed further with programming languages (for example, C-sharp). The models described here include seven community states and five dam operations that cause transitions between states. Each model divides operations into growing (April–September) and non-growing seasons (October–March) and incorporates upper and lower bar models, using stage elevation as a division. The inputs (operations) can be used by stakeholders to evaluate flows that may promote dynamic riparian vegetation states, or identify those flow options that may promote less desirable states (for example, Tamarisk [Tamarix sp.] temporarily flooded shrubland). This prototype model, although simple, can still elicit discussion about operational options and vegetation response.
Exponential H∞ synchronization and state estimation for chaotic systems via a unified model.
Liu, Meiqin; Zhang, Senlin; Fan, Zhen; Zheng, Shiyou; Sheng, Weihua
2013-07-01
In this paper, H∞ synchronization and state estimation problems are considered for different types of chaotic systems. A unified model consisting of a linear dynamic system and a bounded static nonlinear operator is employed to describe these chaotic systems, such as Hopfield neural networks, cellular neural networks, Chua's circuits, unified chaotic systems, Qi systems, chaotic recurrent multilayer perceptrons, etc. Based on the H∞ performance analysis of this unified model using the linear matrix inequality approach, novel state feedback controllers are established not only to guarantee exponentially stable synchronization between two unified models with different initial conditions but also to reduce the effect of external disturbance on the synchronization error to a minimal H∞ norm constraint. The state estimation problem is then studied for the same unified model, where the purpose is to design a state estimator to estimate its states through available output measurements so that the exponential stability of the estimation error dynamic systems is guaranteed and the influence of noise on the estimation error is limited to the lowest level. The parameters of these controllers and filters are obtained by solving the eigenvalue problem. Most chaotic systems can be transformed into this unified model, and H∞ synchronization controllers and state estimators for these systems are designed in a unified way. Three numerical examples are provided to show the usefulness of the proposed H∞ synchronization and state estimation conditions.
Operator functional state estimation based on EEG-data-driven fuzzy model.
Zhang, Jianhua; Yin, Zhong; Yang, Shaozeng; Wang, Rubin
2016-10-01
This paper proposed a max-min-entropy-based fuzzy partition method for fuzzy model based estimation of human operator functional state (OFS). The optimal number of fuzzy partitions for each I/O variable of fuzzy model is determined by using the entropy criterion. The fuzzy models were constructed by using Wang-Mendel method. The OFS estimation results showed the practical usefulness of the proposed fuzzy modeling approach. PMID:27668017
Operator functional state estimation based on EEG-data-driven fuzzy model.
Zhang, Jianhua; Yin, Zhong; Yang, Shaozeng; Wang, Rubin
2016-10-01
This paper proposed a max-min-entropy-based fuzzy partition method for fuzzy model based estimation of human operator functional state (OFS). The optimal number of fuzzy partitions for each I/O variable of fuzzy model is determined by using the entropy criterion. The fuzzy models were constructed by using Wang-Mendel method. The OFS estimation results showed the practical usefulness of the proposed fuzzy modeling approach.
2013-01-01
We investigate the nature of the S* excited state in carotenoids by performing a series of pump–probe experiments with sub-20 fs time resolution on spirilloxanthin in a polymethyl-methacrylate matrix varying the sample temperature. Following photoexcitation, we observe sub-200 fs internal conversion of the bright S2 state into the lower-lying S1 and S* states, which in turn relax to the ground state on a picosecond time scale. Upon cooling down the sample to 77 K, we observe a systematic decrease of the S*/S1 ratio. This result can be explained by assuming two thermally populated ground state isomers. The higher lying one generates the S* state, which can then be effectively frozen out by cooling. These findings are supported by quantum chemical modeling and provide strong evidence for the existence and importance of ground state isomers in the photophysics of carotenoids. PMID:23577754
Model of EF4-induced ribosomal state transitions and mRNA translocation
NASA Astrophysics Data System (ADS)
Xie, Ping
2014-08-01
EF4, a highly conserved protein present in bacteria, mitochondria and chloroplasts, can bind to both the posttranslocation and pretranslocation ribosomal complexes. When binding to the posttranslocation state, it catalyzes backward translocation to a pretranslocation state. When binding to the pretranslocation state, it catalyzes transition to another pretranslocation state that is similar and possibly identical to that resulting from the posttranslocation state bound by EF4, and competes with EF-G to regulate the elongation cycle. However, the molecular mechanism on how EF4 induces state transitions and mRNA translocation remains unclear. Here, we present both the model for state transitions induced by EF4 binding to the posttranslocation state and that by EF4 binding to the pretranslocation state, based on which we study the kinetics of EF4-induced state transitions and mRNA translocation, giving quantitative explanations of the available experimental data. Moreover, we present some predicted results on state transitions and mRNA translocation induced by EF4 binding to the pretranslocation state complexed with the mRNA containing a duplex region.
James, G. Andrew; Kelley, Mary E.; Craddock, R. Cameron; Holtzheimer, Paul E.; Dunlop, Boadie; Nemeroff, Charles; Mayberg, Helen S.; Hu, Xiaoping P.
2009-01-01
The extension of group-level connectivity methods to individual subjects remains a hurdle for statistical analyses of neuroimaging data. Previous group analyses of positron emission tomography data in clinically depressed patients, for example, have shown that resting-state connectivity prior to therapy predicts how patients eventually respond to pharmacological and cognitive-behavioral therapy. Such applications would be considerably more informative for clinical decision making if these connectivity methods could be extended into the individual subject domain. To test such an extension, 46 treatment-naïve depressed patients were enrolled in an fMRI study to model baseline resting-state functional connectivity. Resting-state fMRI scans were acquired and submitted to exploratory structural equation modeling (SEM) to derive the optimal group connectivity model. Jackknife and split sample tests confirm that group model was highly reproducible, and path weights were consistent across the best five group models. When this model was applied to data from individual subjects, 85% of patients fit the group model. Histogram analysis of individual subjects’ paths indicate that some paths are better representative of group membership. These results suggest that exploratory SEM is a viable technique for neuroimaging connectivity analyses of individual subjects’ resting-state fMRI data. PMID:19162206
Two-state model based on the block-localized wave function method
NASA Astrophysics Data System (ADS)
Mo, Yirong
2007-06-01
The block-localized wave function (BLW) method is a variant of ab initio valence bond method but retains the efficiency of molecular orbital methods. It can derive the wave function for a diabatic (resonance) state self-consistently and is available at the Hartree-Fock (HF) and density functional theory (DFT) levels. In this work we present a two-state model based on the BLW method. Although numerous empirical and semiempirical two-state models, such as the Marcus-Hush two-state model, have been proposed to describe a chemical reaction process, the advantage of this BLW-based two-state model is that no empirical parameter is required. Important quantities such as the electronic coupling energy, structural weights of two diabatic states, and excitation energy can be uniquely derived from the energies of two diabatic states and the adiabatic state at the same HF or DFT level. Two simple examples of formamide and thioformamide in the gas phase and aqueous solution were presented and discussed. The solvation of formamide and thioformamide was studied with the combined ab initio quantum mechanical and molecular mechanical Monte Carlo simulations, together with the BLW-DFT calculations and analyses. Due to the favorable solute-solvent electrostatic interaction, the contribution of the ionic resonance structure to the ground state of formamide and thioformamide significantly increases, and for thioformamide the ionic form is even more stable than the covalent form. Thus, thioformamide in aqueous solution is essentially ionic rather than covalent. Although our two-state model in general underestimates the electronic excitation energies, it can predict relative solvatochromic shifts well. For instance, the intense π →π* transition for formamide upon solvation undergoes a redshift of 0.3eV, compared with the experimental data (0.40-0.5eV).
Steady-state solutions of a diffusive energy-balance climate model and their stability
NASA Technical Reports Server (NTRS)
Ghil, M.
1975-01-01
A diffusive energy-balance climate model, governed by a nonlinear parabolic partial differential equation, was studied. Three positive steady-state solutions of this equation are found; they correspond to three possible climates of our planet: an interglacial (nearly identical to the present climate), a glacial, and a completely ice-covered earth. Models similar to the main one are considered, and the number of their steady states was determined. All the models have albedo continuously varying with latitude and temperature, and entirely diffusive horizontal heat transfer. The stability under small perturbations of the main model's climates was investigated. A stability criterion is derived, and its application shows that the present climate and the deep freeze are stable, whereas the model's glacial is unstable. The dependence was examined of the number of steady states and of their stability on the average solar radiation.
Charge state evolution in the solar wind. III. Model comparison with observations
Landi, E.; Oran, R.; Lepri, S. T.; Zurbuchen, T. H.; Fisk, L. A.; Van der Holst, B.
2014-08-01
We test three theoretical models of the fast solar wind with a set of remote sensing observations and in-situ measurements taken during the minimum of solar cycle 23. First, the model electron density and temperature are compared to SOHO/SUMER spectroscopic measurements. Second, the model electron density, temperature, and wind speed are used to predict the charge state evolution of the wind plasma from the source regions to the freeze-in point. Frozen-in charge states are compared with Ulysses/SWICS measurements at 1 AU, while charge states close to the Sun are combined with the CHIANTI spectral code to calculate the intensities of selected spectral lines, to be compared with SOHO/SUMER observations in the north polar coronal hole. We find that none of the theoretical models are able to completely reproduce all observations; namely, all of them underestimate the charge state distribution of the solar wind everywhere, although the levels of disagreement vary from model to model. We discuss possible causes of the disagreement, namely, uncertainties in the calculation of the charge state evolution and of line intensities, in the atomic data, and in the assumptions on the wind plasma conditions. Last, we discuss the scenario where the wind is accelerated from a region located in the solar corona rather than in the chromosphere as assumed in the three theoretical models, and find that a wind originating from the corona is in much closer agreement with observations.
Charge State Evolution in the Solar Wind. III. Model Comparison with Observations
NASA Astrophysics Data System (ADS)
Landi, E.; Oran, R.; Lepri, S. T.; Zurbuchen, T. H.; Fisk, L. A.; van der Holst, B.
2014-08-01
We test three theoretical models of the fast solar wind with a set of remote sensing observations and in-situ measurements taken during the minimum of solar cycle 23. First, the model electron density and temperature are compared to SOHO/SUMER spectroscopic measurements. Second, the model electron density, temperature, and wind speed are used to predict the charge state evolution of the wind plasma from the source regions to the freeze-in point. Frozen-in charge states are compared with Ulysses/SWICS measurements at 1 AU, while charge states close to the Sun are combined with the CHIANTI spectral code to calculate the intensities of selected spectral lines, to be compared with SOHO/SUMER observations in the north polar coronal hole. We find that none of the theoretical models are able to completely reproduce all observations; namely, all of them underestimate the charge state distribution of the solar wind everywhere, although the levels of disagreement vary from model to model. We discuss possible causes of the disagreement, namely, uncertainties in the calculation of the charge state evolution and of line intensities, in the atomic data, and in the assumptions on the wind plasma conditions. Last, we discuss the scenario where the wind is accelerated from a region located in the solar corona rather than in the chromosphere as assumed in the three theoretical models, and find that a wind originating from the corona is in much closer agreement with observations.
A one-step-ahead pseudo-DIC for comparison of Bayesian state-space models.
Millar, R B; McKechnie, S
2014-12-01
In the context of state-space modeling, conventional usage of the deviance information criterion (DIC) evaluates the ability of the model to predict an observation at time t given the underlying state at time t. Motivated by the failure of conventional DIC to clearly choose between competing multivariate nonlinear Bayesian state-space models for coho salmon population dynamics, and the computational challenge of alternatives, this work proposes a one-step-ahead DIC, DICp, where prediction is conditional on the state at the previous time point. Simulations revealed that DICp worked well for choosing between state-space models with different process or observation equations. In contrast, conventional DIC could be grossly misleading, with a strong preference for the wrong model. This can be explained by its failure to account for inflated estimates of process error arising from the model mis-specification. DICp is not based on a true conditional likelihood, but is shown to have interpretation as a pseudo-DIC in which the compensatory behavior of the inflated process errors is eliminated. It can be easily calculated using the DIC monitors within popular BUGS software when the process and observation equations are conjugate. The improved performance of DICp is demonstrated by application to the multi-stage modeling of coho salmon abundance in Lobster Creek, Oregon.
A one-step-ahead pseudo-DIC for comparison of Bayesian state-space models.
Millar, R B; McKechnie, S
2014-12-01
In the context of state-space modeling, conventional usage of the deviance information criterion (DIC) evaluates the ability of the model to predict an observation at time t given the underlying state at time t. Motivated by the failure of conventional DIC to clearly choose between competing multivariate nonlinear Bayesian state-space models for coho salmon population dynamics, and the computational challenge of alternatives, this work proposes a one-step-ahead DIC, DICp, where prediction is conditional on the state at the previous time point. Simulations revealed that DICp worked well for choosing between state-space models with different process or observation equations. In contrast, conventional DIC could be grossly misleading, with a strong preference for the wrong model. This can be explained by its failure to account for inflated estimates of process error arising from the model mis-specification. DICp is not based on a true conditional likelihood, but is shown to have interpretation as a pseudo-DIC in which the compensatory behavior of the inflated process errors is eliminated. It can be easily calculated using the DIC monitors within popular BUGS software when the process and observation equations are conjugate. The improved performance of DICp is demonstrated by application to the multi-stage modeling of coho salmon abundance in Lobster Creek, Oregon. PMID:25370730
The "intoxication state of consciousness": a model for alcohol and drug abuse.
Galanter, M
1976-06-01
The author describes a model of intoxicant use based on altered states of consciousness and reviews his own and others' research on marijuana to illustrate the utility of this model, which is derived from both introspective reports and observed data. The relationship of social behavior and cognitive functioning to the "intoxication state of consciousness" is discussed. This state of consciousness may have an adaptive value in engendering and stabilizing social cohesion. Possible treatment implications include cognitive labeling of cues that precipitate episodes of abuse, training for moderated drug use while patients are intoxicated, and providing abusers with altered consciousness through other means, such as meditation.
Leng, Guoyong; Huang, Maoyi; Tang, Qiuhong; Sacks, William J.; Lei, Huimin; Leung, Lai-Yung R.
2013-09-16
Previous studies on irrigation impacts on land surface fluxes/states were mainly conducted as sensitivity experiments, with limited analysis of uncertainties from the input data and model irrigation schemes used. In this study, we calibrated and evaluated the performance of irrigation water use simulated by the Community Land Model version 4 (CLM4) against observations from agriculture census. We investigated the impacts of irrigation on land surface fluxes and states over the conterminous United States (CONUS) and explored possible directions of improvement. Specifically, we found large uncertainty in the irrigation area data from two widely used sources and CLM4 tended to produce unrealistically large temporal variations of irrigation demand for applications at the water resources region scale over CONUS. At seasonal to interannual time scales, the effects of irrigation on surface energy partitioning appeared to be large and persistent, and more pronounced in dry than wet years. Even with model calibration to yield overall good agreement with the irrigation amounts from the National Agricultural Statistics Service (NASS), differences between the two irrigation area datasets still dominate the differences in the interannual variability of land surface response to irrigation. Our results suggest that irrigation amount simulated by CLM4 can be improved by (1) calibrating model parameter values to account for regional differences in irrigation demand and (2) accurate representation of the spatial distribution and intensity of irrigated areas.
Quantitative, steady-state properties of Catania's computational model of the operant reserve.
Berg, John P; McDowell, J J
2011-05-01
Catania (2005) found that a computational model of the operant reserve (Skinner, 1938) produced realistic behavior in initial, exploratory analyses. Although Catania's operant reserve computational model demonstrated potential to simulate varied behavioral phenomena, the model was not systematically tested. The current project replicated and extended the Catania model, clarified its capabilities through systematic testing, and determined the extent to which it produces behavior corresponding to matching theory. Significant departures from both classic and modern matching theory were found in behavior generated by the model across all conditions. The results suggest that a simple, dynamic operant model of the reflex reserve does not simulate realistic steady state behavior.
Quantitative, steady-state properties of Catania's computational model of the operant reserve.
Berg, John P; McDowell, J J
2011-05-01
Catania (2005) found that a computational model of the operant reserve (Skinner, 1938) produced realistic behavior in initial, exploratory analyses. Although Catania's operant reserve computational model demonstrated potential to simulate varied behavioral phenomena, the model was not systematically tested. The current project replicated and extended the Catania model, clarified its capabilities through systematic testing, and determined the extent to which it produces behavior corresponding to matching theory. Significant departures from both classic and modern matching theory were found in behavior generated by the model across all conditions. The results suggest that a simple, dynamic operant model of the reflex reserve does not simulate realistic steady state behavior. PMID:21238552
Density-dependent state-space model for population-abundance data with unequal time intervals.
Dennis, Brian; Ponciano, José Miguel
2014-08-01
The Gompertz state-space (GSS) model is a stochastic model for analyzing time-series observations of population abundances. The GSS model combines density dependence, environmental process noise, and observation error toward estimating quantities of interest in biological monitoring and population viability analysis. However, existing methods for estimating the model parameters apply only to population data with equal time intervals between observations. In the present paper, we extend the GSS model to data with unequal time intervals, by embedding it within a state-space version of the Ornstein-Uhlenbeck process, a continuous-time model of an equilibrating stochastic system. Maximum likelihood and restricted maximum likelihood calculations for the Ornstein-Uhlenbeck state-space model involve only numerical maximization of an explicit multivariate normal likelihood, and so the extension allows for easy bootstrapping, yielding confidence intervals for model parameters, statistical hypothesis testing of density dependence, and selection among sub-models using information criteria. Ecologists and managers previously drawn to models lacking density dependence or observation error because such models accommodated unequal time intervals (for example, due to missing data) now have an alternative analysis framework incorporating density dependence, process noise, and observation error.
An analysis of calibration curve models for solid-state heat-flow calorimeters
Hypes, P. A.; Bracken, D. S.; McCabe, G.
2001-01-01
Various calibration curve models for solid-state calorimeters are compared to determine which model best fits the calibration data. The calibration data are discussed. The criteria used to select the best model are explained. A conclusion regarding the best model for the calibration curve is presented. These results can also be used to evaluate the random and systematic error of a calorimetric measurement. A linear/quadratic model has been used for decades to fit the calibration curves for wheatstone bridge calorimeters. Excellent results have been obtained using this calibration curve model. The Multical software package uses this model for the calibration curve. The choice of this model is supported by 40 years [1] of calorimeter data. There is good empirical support for the linear/quadratic model. Calorimeter response is strongly linear. Calorimeter sensitivity is slightly lower at higher powers; the negative coefficient of the x{sup 2} term accounts for this. The solid-state calorimeter is operated using the Multical [2] software package. An investigation was undertaken to determine if the linear/quadratic model is the best model for the new sensor technology used in the solid-state calorimeter.
Turbulence Modeling Effects on the Prediction of Equilibrium States of Buoyant Shear Flows
NASA Technical Reports Server (NTRS)
Zhao, C. Y.; So, R. M. C.; Gatski, T. B.
2001-01-01
The effects of turbulence modeling on the prediction of equilibrium states of turbulent buoyant shear flows were investigated. The velocity field models used include a two-equation closure, a Reynolds-stress closure assuming two different pressure-strain models and three different dissipation rate tensor models. As for the thermal field closure models, two different pressure-scrambling models and nine different temperature variance dissipation rate, Epsilon(0) equations were considered. The emphasis of this paper is focused on the effects of the Epsilon(0)-equation, of the dissipation rate models, of the pressure-strain models and of the pressure-scrambling models on the prediction of the approach to equilibrium turbulence. Equilibrium turbulence is defined by the time rate (if change of the scaled Reynolds stress anisotropic tensor and heat flux vector becoming zero. These conditions lead to the equilibrium state parameters. Calculations show that the Epsilon(0)-equation has a significant effect on the prediction of the approach to equilibrium turbulence. For a particular Epsilon(0)-equation, all velocity closure models considered give an equilibrium state if anisotropic dissipation is accounted for in one form or another in the dissipation rate tensor or in the Epsilon(0)-equation. It is further found that the models considered for the pressure-strain tensor and the pressure-scrambling vector have little or no effect on the prediction of the approach to equilibrium turbulence.
Density dependent state space model for population abundance data with unequal time intervals
Dennis, Brian; Ponciano, José Miguel
2014-01-01
The Gompertz state-space (GSS) model is a stochastic model for analyzing time series observations of population abundances. The GSS model combines density dependence, environmental process noise, and observation error toward estimating quantities of interest in biological monitoring and population viability analysis. However, existing methods for estimating the model parameters apply only to population data with equal time intervals between observations. In the present paper, we extend the GSS model to data with unequal time intervals, by embedding it within a state-space version of the Ornstein-Uhlenbeck process, a continuous-time model of an equilibrating stochastic system. Maximum likelihood and restricted maximum likelihood calculations for the Ornstein-Uhlenbeck state-space model involve only numerical maximization of an explicit multivariate normal likelihood, and so the extension allows for easy bootstrapping, yielding confidence intervals for model parameters, statistical hypothesis testing of density dependence, and selection among sub-models using information criteria. Ecologists and managers previously drawn to models lacking density dependence or observation error because such models accommodated unequal time intervals (for example, due to missing data) now have an alternative analysis framework incorporating density dependence, process noise and observation error. PMID:25230459
Variational Monte Carlo study of magnetic states in the periodic Anderson model
NASA Astrophysics Data System (ADS)
Kubo, Katsunori
2015-03-01
We study the magnetic states of the periodic Anderson model with a finite Coulomb interaction between f electrons on a square lattice by applying variational Monte Carlo method. We consider Gutzwiller wavefunctions for the paramagnetic, antiferromagnetic, ferromagnetic, and charge density wave states. We find an antiferromagnetic phase around half-filling. There is a phase transition accompanying change in the Fermi-surface topology in this antiferromagnetic phase. We also study a case away from half-filling, and find a ferromagnetic state as the ground state there.
Modeling of the Equation of State for 0 < ρ/ρ0 < 1010
NASA Astrophysics Data System (ADS)
Prut, V. V.
2016-09-01
An approximation of the equation of state of matter in nonrelativistic and relativistic regions is considered. The cold component is determined in the limit v → 0 by the properties of an ideal homogeneous degenerate relativistic electron gas, and under normal conditions, by four experimental parameters: the specific volume, the binding energy, the bulk compression modulus, and the parameter -(∂lnB/∂lnv). Results are confirmed and illustrated by the experimental equation of state for iron in the region up to p ≈ 3 Mbar. A comparison of the model equation of state and the classical equation of state of an ideal homogeneous degenerate electron gas is given.
Recognition of human activity characteristics based on state transitions modeling technique
NASA Astrophysics Data System (ADS)
Elangovan, Vinayak; Shirkhodaie, Amir
2012-06-01
Human Activity Discovery & Recognition (HADR) is a complex, diverse and challenging task but yet an active area of ongoing research in the Department of Defense. By detecting, tracking, and characterizing cohesive Human interactional activity patterns, potential threats can be identified which can significantly improve situation awareness, particularly, in Persistent Surveillance Systems (PSS). Understanding the nature of such dynamic activities, inevitably involves interpretation of a collection of spatiotemporally correlated activities with respect to a known context. In this paper, we present a State Transition model for recognizing the characteristics of human activities with a link to a prior contextbased ontology. Modeling the state transitions between successive evidential events determines the activities' temperament. The proposed state transition model poses six categories of state transitions including: Human state transitions of Object handling, Visibility, Entity-entity relation, Human Postures, Human Kinematics and Distance to Target. The proposed state transition model generates semantic annotations describing the human interactional activities via a technique called Casual Event State Inference (CESI). The proposed approach uses a low cost kinect depth camera for indoor and normal optical camera for outdoor monitoring activities. Experimental results are presented here to demonstrate the effectiveness and efficiency of the proposed technique.
Sohl, Terry L.; Wimberly, Michael; Radeloff, Volker C.; Theobald, David M.; Sleeter, Benjamin M.
2016-01-01
A variety of land-use and land-cover (LULC) models operating at scales from local to global have been developed in recent years, including a number of models that provide spatially explicit, multi-class LULC projections for the conterminous United States. This diversity of modeling approaches raises the question: how consistent are their projections of future land use? We compared projections from six LULC modeling applications for the United States and assessed quantitative, spatial, and conceptual inconsistencies. Each set of projections provided multiple scenarios covering a period from roughly 2000 to 2050. Given the unique spatial, thematic, and temporal characteristics of each set of projections, individual projections were aggregated to a common set of basic, generalized LULC classes (i.e., cropland, pasture, forest, range, and urban) and summarized at the county level across the conterminous United States. We found very little agreement in projected future LULC trends and patterns among the different models. Variability among scenarios for a given model was generally lower than variability among different models, in terms of both trends in the amounts of basic LULC classes and their projected spatial patterns. Even when different models assessed the same purported scenario, model projections varied substantially. Projections of agricultural trends were often far above the maximum historical amounts, raising concerns about the realism of the projections. Comparisons among models were hindered by major discrepancies in categorical definitions, and suggest a need for standardization of historical LULC data sources. To capture a broader range of uncertainties, ensemble modeling approaches are also recommended. However, the vast inconsistencies among LULC models raise questions about the theoretical and conceptual underpinnings of current modeling approaches. Given the substantial effects that land-use change can have on ecological and societal processes, there
Digital modelling, ideal state reconstructor, and control for time-delay sampled-data systems
NASA Technical Reports Server (NTRS)
Tsai, J. S. H.; Chen, C. M.
1991-01-01
The cascaded discrete-time state-space representation of a cascaded continuous-time system with fractional input delays is established. Based on the time-delay digital modelling, a practically implementable ideal state reconstructor is also established such that system states are exactly reconstructed via the measurement histories of inputs and outputs without a state observer. By utilizing the blockpulse function approximation the digital modelling of cascaded continuous-time systems with fractional input delays can be carried out, and an artificial input design method is proposed to determine the state feedback gain. Thus the practically implementable digital control law can be established for digital control of time-delay sampled-data systems. An illustrative example is shown to demonstrate the effectiveness of the proposed method.
Kim, Jin Il; Song, Hyun-Seob; Sunkara, Sunil R; Lali, Arvind; Ramkrishna, Doraiswami
2012-01-01
We demonstrate strong experimental support for the cybernetic model based on maximizing carbon uptake rate in describing the microorganism's regulatory behavior by verifying exacting predictions of steady state multiplicity in a chemostat. Experiments with a feed mixture of glucose and pyruvate show multiple steady state behavior as predicted by the cybernetic model. When multiplicity occurs at a dilution (growth) rate, it results in hysteretic behavior following switches in dilution rate from above and below. This phenomenon is caused by transient paths leading to different steady states through dynamic maximization of the carbon uptake rate. Thus steady state multiplicity is a manifestation of the nonlinearity arising from cybernetic mechanisms rather than of the nonlinear kinetics. The predicted metabolic multiplicity would extend to intracellular states such as enzyme levels and fluxes to be verified in future experiments.
Ground-state energies of the nonlinear sigma model and the Heisenberg spin chains
NASA Technical Reports Server (NTRS)
Zhang, Shoucheng; Schulz, H. J.; Ziman, Timothy
1989-01-01
A theorem on the O(3) nonlinear sigma model with the topological theta term is proved, which states that the ground-state energy at theta = pi is always higher than the ground-state energy at theta = 0, for the same value of the coupling constant g. Provided that the nonlinear sigma model gives the correct description for the Heisenberg spin chains in the large-s limit, this theorem makes a definite prediction relating the ground-state energies of the half-integer and the integer spin chains. The ground-state energies obtained from the exact Bethe ansatz solution for the spin-1/2 chain and the numerical diagonalization on the spin-1, spin-3/2, and spin-2 chains support this prediction.
Irreversible transitions in the exchange-striction model of spin-glass state
NASA Astrophysics Data System (ADS)
Valkov, V. I.; Golovchan, A. V.
2014-08-01
Based on the assumption of a negative volume dependence of random exchange integrals, it is possible to switch to a compressible Sherrington-Kirkpatrick spin-glass model. Within the proposed model, temperature-pressure phase diagrams were calculated and pressure- and magnetic-field-induced first-order phase transitions from the initial paramagnetic and spin-glass states to the ferromagnetic state were predicted. It was shown that the application of pressure in the spin-glass state not only increases and shifts magnetic susceptibility, but also reduces the critical magnetic fields of irreversible induced phase transitions from the spin-glass to the ferromagnetic state. The obtained results are used to describe the spin-glass state in (Sm1-xGdx)0.55Sr0.45MnO3.
Colaiori, Francesca; Castellano, Claudio; Cuskley, Christine F; Loreto, Vittorio; Pugliese, Martina; Tria, Francesca
2015-01-01
Empirical evidence shows that the rate of irregular usage of English verbs exhibits discontinuity as a function of their frequency: the most frequent verbs tend to be totally irregular. We aim to qualitatively understand the origin of this feature by studying simple agent-based models of language dynamics, where each agent adopts an inflectional state for a verb and may change it upon interaction with other agents. At the same time, agents are replaced at some rate by new agents adopting the regular form. In models with only two inflectional states (regular and irregular), we observe that either all verbs regularize irrespective of their frequency, or a continuous transition occurs between a low-frequency state, where the lemma becomes fully regular, and a high-frequency one, where both forms coexist. Introducing a third (mixed) state, wherein agents may use either form, we find that a third, qualitatively different behavior may emerge, namely, a discontinuous transition in frequency. We introduce and solve analytically a very general class of three-state models that allows us to fully understand these behaviors in a unified framework. Realistic sets of interaction rules, including the well-known naming game (NG) model, result in a discontinuous transition, in agreement with recent empirical findings. We also point out that the distinction between speaker and hearer in the interaction has no effect on the collective behavior. The results for the general three-state model, although discussed in terms of language dynamics, are widely applicable.
Chimera states in a Hodgkin-Huxley model of thermally sensitive neurons.
Glaze, Tera A; Lewis, Scott; Bahar, Sonya
2016-08-01
Chimera states occur when identically coupled groups of nonlinear oscillators exhibit radically different dynamics, with one group exhibiting synchronized oscillations and the other desynchronized behavior. This dynamical phenomenon has recently been studied in computational models and demonstrated experimentally in mechanical, optical, and chemical systems. The theoretical basis of these states is currently under active investigation. Chimera behavior is of particular relevance in the context of neural synchronization, given the phenomenon of unihemispheric sleep and the recent observation of asymmetric sleep in human patients with sleep apnea. The similarity of neural chimera states to neural "bump" states, which have been suggested as a model for working memory and visual orientation tuning in the cortex, adds to their interest as objects of study. Chimera states have been demonstrated in the FitzHugh-Nagumo model of excitable cells and in the Hindmarsh-Rose neural model. Here, we demonstrate chimera states and chimera-like behaviors in a Hodgkin-Huxley-type model of thermally sensitive neurons both in a system with Abrams-Strogatz (mean field) coupling and in a system with Kuramoto (distance-dependent) coupling. We map the regions of parameter space for which chimera behavior occurs in each of the two coupling schemes.
Chimera states in a Hodgkin-Huxley model of thermally sensitive neurons
NASA Astrophysics Data System (ADS)
Glaze, Tera A.; Lewis, Scott; Bahar, Sonya
2016-08-01
Chimera states occur when identically coupled groups of nonlinear oscillators exhibit radically different dynamics, with one group exhibiting synchronized oscillations and the other desynchronized behavior. This dynamical phenomenon has recently been studied in computational models and demonstrated experimentally in mechanical, optical, and chemical systems. The theoretical basis of these states is currently under active investigation. Chimera behavior is of particular relevance in the context of neural synchronization, given the phenomenon of unihemispheric sleep and the recent observation of asymmetric sleep in human patients with sleep apnea. The similarity of neural chimera states to neural "bump" states, which have been suggested as a model for working memory and visual orientation tuning in the cortex, adds to their interest as objects of study. Chimera states have been demonstrated in the FitzHugh-Nagumo model of excitable cells and in the Hindmarsh-Rose neural model. Here, we demonstrate chimera states and chimera-like behaviors in a Hodgkin-Huxley-type model of thermally sensitive neurons both in a system with Abrams-Strogatz (mean field) coupling and in a system with Kuramoto (distance-dependent) coupling. We map the regions of parameter space for which chimera behavior occurs in each of the two coupling schemes.
Chimera states in a Hodgkin-Huxley model of thermally sensitive neurons.
Glaze, Tera A; Lewis, Scott; Bahar, Sonya
2016-08-01
Chimera states occur when identically coupled groups of nonlinear oscillators exhibit radically different dynamics, with one group exhibiting synchronized oscillations and the other desynchronized behavior. This dynamical phenomenon has recently been studied in computational models and demonstrated experimentally in mechanical, optical, and chemical systems. The theoretical basis of these states is currently under active investigation. Chimera behavior is of particular relevance in the context of neural synchronization, given the phenomenon of unihemispheric sleep and the recent observation of asymmetric sleep in human patients with sleep apnea. The similarity of neural chimera states to neural "bump" states, which have been suggested as a model for working memory and visual orientation tuning in the cortex, adds to their interest as objects of study. Chimera states have been demonstrated in the FitzHugh-Nagumo model of excitable cells and in the Hindmarsh-Rose neural model. Here, we demonstrate chimera states and chimera-like behaviors in a Hodgkin-Huxley-type model of thermally sensitive neurons both in a system with Abrams-Strogatz (mean field) coupling and in a system with Kuramoto (distance-dependent) coupling. We map the regions of parameter space for which chimera behavior occurs in each of the two coupling schemes. PMID:27586615
Neural evidence for a 3-state model of visual short-term memory.
Nee, Derek Evan; Jonides, John
2013-07-01
Recent research has suggested that short-term memory (STM) can be partitioned into three distinct states. By this model, a single item is held in the focus of attention making it available for immediate processing (focus of attention), a capacity-limited set of additional items is actively maintained for future processing (direct access region), and other recently presented information is passively active, but can nevertheless influence ongoing cognition (activated portion of long-term memory). While there is both behavioral and neural support for this 3-state model in verbal STM, it is unclear whether the model generalizes to non-verbal STM. Here, we tested a 3-state model of visual STM using fMRI. We found a triple dissociation of regions involved in the access of each hypothesized state. The inferior parietal cortex mediated access to the focus of attention, the medial temporal lobe (MTL) including the hippocampus mediated access to the direct access region, and the left ventrolateral prefrontal cortex (VLPFC) mediated access to the activated portion of long-term memory. Direct comparison with previously collected verbal STM data revealed overlapping neural activations involved in the access of each state across different forms of content suggesting that mechanisms of access are domain general. These data support a 3-state model of STM.
A multi-state model approach for prediction in chronic myeloid leukaemia.
Lauseker, Michael; Hasford, Joerg; Hoffmann, Verena S; Müller, Martin C; Hehlmann, Rüdiger; Pfirrmann, Markus
2015-06-01
Multi-state models support prediction in medicine. With different states of disease, chronic myeloid leukaemia (CML) is particularly suited for the application of multi-state models. In this article, we tried to find a model for CML that allows predicting the prevalence of three different states (initial state of disease, remission and progression) in dependence on treatment, adjusted for age, sex and risk score. Based on the German CML Study IV, one of the largest randomised studies in CML, the model was able to represent the known effects of age and risk score on the probabilities of remission and progression. Patients achieving a major molecular remission had a better chance of surviving without progression, but this effect was not significant. Comparing treatments, patient of the high-dose arm had the greatest chance to be in the state "remission" at 5 years but did not seem to have an advantage considering "progression". The proposed illness-death model can be useful for predicting the course of CML based on the patient's individual covariates (trial registration: this is an explorative analysis of ClinicalTrials.gov Identifier: NCT00055874). PMID:25465231
NASA Astrophysics Data System (ADS)
Colaiori, Francesca; Castellano, Claudio; Cuskley, Christine F.; Loreto, Vittorio; Pugliese, Martina; Tria, Francesca
2015-01-01
Empirical evidence shows that the rate of irregular usage of English verbs exhibits discontinuity as a function of their frequency: the most frequent verbs tend to be totally irregular. We aim to qualitatively understand the origin of this feature by studying simple agent-based models of language dynamics, where each agent adopts an inflectional state for a verb and may change it upon interaction with other agents. At the same time, agents are replaced at some rate by new agents adopting the regular form. In models with only two inflectional states (regular and irregular), we observe that either all verbs regularize irrespective of their frequency, or a continuous transition occurs between a low-frequency state, where the lemma becomes fully regular, and a high-frequency one, where both forms coexist. Introducing a third (mixed) state, wherein agents may use either form, we find that a third, qualitatively different behavior may emerge, namely, a discontinuous transition in frequency. We introduce and solve analytically a very general class of three-state models that allows us to fully understand these behaviors in a unified framework. Realistic sets of interaction rules, including the well-known naming game (NG) model, result in a discontinuous transition, in agreement with recent empirical findings. We also point out that the distinction between speaker and hearer in the interaction has no effect on the collective behavior. The results for the general three-state model, although discussed in terms of language dynamics, are widely applicable.
Multi-state relative survival modelling of colorectal cancer progression and mortality.
Gilard-Pioc, Séverine; Abrahamowicz, Michal; Mahboubi, Amel; Bouvier, Anne-Marie; Dejardin, Olivier; Huszti, Ella; Binquet, Christine; Quantin, Catherine
2015-06-01
Accurate identification of factors associated with progression of colorectal cancer remains a challenge. In particular, it is unclear which statistical methods are most suitable to separate the effects of putative prognostic factors on cancer progression vs cancer-specific and other cause mortality. To address these challenges, we analyzed 10 year follow-up data for patients who underwent curative surgery for colorectal cancer in 1985-2000. Separate analyses were performed in two French cancer registries. Results of three multivariable models were compared: Cox model with recurrence as a time-dependent variable, and two multi-state models, which separated prognostic factor effects on recurrence vs death, with or without recurrence. Conventional multi-state model analyzed all-cause mortality while new relative survival multi-state model focused on cancer-specific mortality. Among the 2517 and 2677 patients in the two registries, about 50% died without a recurrence, and 28% had a recurrence, of whom almost 90% died. In both multi-state models men had significantly increased risk of cancer recurrence in both registries (HR=0.79; 95% CI: 0.68-0.92 and HR=0.83; 95% CI: 0.71-0.96). However, the two multi-state models identified different prognostic factors for mortality without recurrence. In contrast to the conventional model, in the relative survival analyses gender had no independent association with cancer-specific mortality whereas patients diagnosed with stage III cancer had significantly higher risks in both registries (HR=1.67; 95% CI: 1.27-2.22 and HR=2.38; 95% CI: 1.29-3.27). In conclusion, relative survival multi-state model revealed that different factors may be associated with cancer recurrence vs cancer-specific mortality either after or without a recurrence.
A Model for Creating Engaged Land-Grant Universities: Penn State's Engagement Ladder Model
ERIC Educational Resources Information Center
Aronson, Keith R.; Webster, Nicole
2007-01-01
The original mission of the state and land-grant university was to engage with communities to solve problems and improve the quality of life for the citizenry. Today most state and land-grant universities have moved far away from their original mission and are struggling to become engaged with the communities they serve. In this case study, we…
User's instructions for the 41-node thermoregulatory model (steady state version)
NASA Technical Reports Server (NTRS)
Leonard, J. I.
1974-01-01
A user's guide for the steady-state thermoregulatory model is presented. The model was modified to provide conversational interaction on a remote terminal, greater flexibility for parameter estimation, increased efficiency of convergence, greater choice of output variable and more realistic equations for respiratory and skin diffusion water losses.
ERIC Educational Resources Information Center
Seadle, Michael
1998-01-01
Summarizes the elements of the Cornell-Yale digitization model and shows how Michigan State University (MSU) has expanded the model, focusing on a project to digitize the American Radicalism Collection of the MSU Libraries. Issues of selection, quality, integrity, longevity, and access are discussed. Sidebars present MSU digitizing procedures,…
State-and-transition model archetypes: a global taxonomy of rangeland change
Technology Transfer Automated Retrieval System (TEKTRAN)
State and transition models (STMs) synthesize science-based and local knowledge to formally represent the dynamics of rangeland and other ecosystems. Mental models or concepts of ecosystem dynamics implicitly underlie all management decisions in rangelands and thus how people influence rangeland sus...
A Process for Restructuring Service Delivery Models for Inclusion in New York State.
ERIC Educational Resources Information Center
Black, Jim; And Others
This paper describes a process for restructuring service-delivery models for inclusion in New York State schools. The process is based on several assumptions, some of which include: (1) Home-zone school placement or choice/magnet school options are the preferred placement for special education students; (2) inclusion models must restructure…
Mathematical modeling of a Ti:sapphire solid-state laser
NASA Technical Reports Server (NTRS)
Swetits, John J.
1987-01-01
The project initiated a study of a mathematical model of a tunable Ti:sapphire solid-state laser. A general mathematical model was developed for the purpose of identifying design parameters which will optimize the system, and serve as a useful predictor of the system's behavior.
The Sustainability of Comprehensive School Reform Models in Changing District and State Contexts
ERIC Educational Resources Information Center
Datnow, Amanda
2005-01-01
This article addresses the sustainability of comprehensive school reform (CSR) models in the face of turbulent district and state contexts. It draws on qualitative data gathered in a longitudinal case study of six CSR models implemented in 13 schools in one urban district. Why do reforms sustain in some schools and not in others? How do changing…
Massless ground state for a compact SU (2) matrix model in 4D
NASA Astrophysics Data System (ADS)
Boulton, Lyonell; Garcia del Moral, Maria Pilar; Restuccia, Alvaro
2015-09-01
We show the existence and uniqueness of a massless supersymmetric ground state wavefunction of a SU (2) matrix model in a bounded smooth domain with Dirichlet boundary conditions. This is a gauge system and we provide a new framework to analyze the quantum spectral properties of this class of supersymmetric matrix models subject to constraints which can be generalized for arbitrary number of colors.
Relativistic compact anisotropic charged stellar models with Chaplygin equation of state
NASA Astrophysics Data System (ADS)
Bhar, Piyali; Murad, Mohammad Hassan
2016-10-01
This paper presents a new model of static spherically symmetric relativistic charged stellar objects with locally anisotropic matter distribution together with the Chaplygin equation of state. The interior spacetime has been matched continuously to the exterior Reissner-Nordström geometry. Different physical properties of the stellar model have been investigated, analyzed, and presented graphically.
States-of-Mind Model: Cognitive Balance in the Treatment of Agoraphobia.
ERIC Educational Resources Information Center
Schwartz, Robert M.; Michelson, Larry
1987-01-01
Used states-of-mind model to track therapeutic changes in cognitive balance of 39 agoraphobics. Descriptive and statistical analyses from an outcome study of graduated exposure, relaxation training, and paradoxical intention supported the model. Agoraphobics evinced negative dialogue at pretreatment, positive dialogue at mid and posttreatment, and…
Exploring Solid-State Structure and Physical Properties: A Molecular and Crystal Model Exercise
ERIC Educational Resources Information Center
Bindel, Thomas H.
2008-01-01
A crystal model laboratory exercise is presented that allows students to examine relations among the microscopic-macroscopic-symbolic levels, using crystalline mineral samples and corresponding crystal models. Students explore the relationship between solid-state structure and crystal form. Other structure-property relationships are explored. The…
Technical Assistance Model for Long-Term Systems Change: Three State Examples
ERIC Educational Resources Information Center
Kasprzak, Christina; Hurth, Joicey; Lucas, Anne; Marshall, Jacqueline; Terrell, Adriane; Jones, Elizabeth
2010-01-01
The National Early Childhood Technical Assistance Center (NECTAC) Technical Assistance (TA) Model for Long-Term Systems Change (LTSC) is grounded in conceptual frameworks in the literature on systems change and systems thinking. The NECTAC conceptual framework uses a logic model approach to change developed specifically for states' infant and…
A non-local, ordinary-state-based viscoelasticity model for peridynamics.
Mitchell, John Anthony
2011-10-01
A non-local, ordinary-state-based, peridynamics viscoelasticity model is developed. In this model, viscous effects are added to deviatoric deformations and the bulk response remains elastic. The model uses internal state variables and is conceptually similar to linearized isotropic viscolelasticity in the local theory. The modulus state, which is used to form the Jacobian matrix in Newton-Raphson algorithms, is presented. The model is shown to satisfy the 2nd law of thermodynamics and is applicable to problems in solid continuum mechanics where fracture and rate effects are important; it inherits all the advantages for modeling fracture associated with peridynamics. By combining this work with the previously published ordinary-state-based plasticity model, the model may be amenable to viscoplasticity problems where plasticity and rate effects are simultaneously important. Also, the model may be extended to include viscous effects for spherical deformations as well. The later two extensions are not presented and may be the subject of further work.
Modeling Quality-Adjusted Life Expectancy Loss Resulting from Tobacco Use in the United States
ERIC Educational Resources Information Center
Kaplan, Robert M.; Anderson, John P.; Kaplan, Cameron M.
2007-01-01
Purpose: To describe the development of a model for estimating the effects of tobacco use upon Quality Adjusted Life Years (QALYs) and to estimate the impact of tobacco use on health outcomes for the United States (US) population using the model. Method: We obtained estimates of tobacco consumption from 6 years of the National Health Interview…
Longitudinal Stability of the Beck Depression Inventory II: A Latent Trait-State-Occasion Model
ERIC Educational Resources Information Center
Wu, Pei-Chen
2016-01-01
In a six-wave longitudinal study with two cohorts (660 adolescents and 630 young adults), this study investigated the longitudinal stability of the Beck Depression Inventory II (BDI-II) using the Trait-State-Occasion (TSO) model. The results revealed that the full TSO model was the best fitting representation of the depression measured by the…
Wasielewski, M.R.; Greenfield, S.R.; Svec, W.A.
1997-08-01
Results are presented on a photosynthetic model system that closely mimics the spin dynamics of triplet state formation found in photosynthetic reaction centers. This research will make it possible to design new models to probe the mechanism of the primary events of photosynthesis.
Multi-State Physics Models of Aging Passive Components in Probabilistic Risk Assessment
Unwin, Stephen D.; Lowry, Peter P.; Layton, Robert F.; Heasler, Patrick G.; Toloczko, Mychailo B.
2011-03-13
Multi-state Markov modeling has proved to be a promising approach to estimating the reliability of passive components - particularly metallic pipe components - in the context of probabilistic risk assessment (PRA). These models consider the progressive degradation of a component through a series of observable discrete states, such as detectable flaw, leak and rupture. Service data then generally provides the basis for estimating the state transition rates. Research in materials science is producing a growing understanding of the physical phenomena that govern the aging degradation of passive pipe components. As a result, there is an emerging opportunity to incorporate these insights into PRA. This paper describes research conducted under the Risk-Informed Safety Margin Characterization Pathway of the Department of Energy’s Light Water Reactor Sustainability Program. A state transition model is described that addresses aging behavior associated with stress corrosion cracking in ASME Class 1 dissimilar metal welds – a component type relevant to LOCA analysis. The state transition rate estimates are based on physics models of weld degradation rather than service data. The resultant model is found to be non-Markov in that the transition rates are time-inhomogeneous and stochastic. Numerical solutions to the model provide insight into the effect of aging on component reliability.
A five states survivability model for missions with ground-to-air threats
NASA Astrophysics Data System (ADS)
Erlandsson, Tina; Niklasson, Lars
2013-05-01
Fighter pilots are exposed to the risk of getting hit by enemy fire when flying missions with ground-to-air threats. A tactical support system including a survivability model could aid the pilot to assess and handle this risk. The survivability model presented here is a Markov model with five states; Undetected, Detected, Tracked, Engaged and Hit. The output from the model is the probabilities that the aircraft is in these states during the mission. The enemy's threat systems are represented with sensor and weapon areas and the transitions between the states depend on whether or not the aircraft is within any of these areas. Contrary to previous work, the model can capture the behaviors that the enemy's sensor systems communicate and that the risk of getting hit depends on the enemy's knowledge regarding the aircraft's kinematics. The paper includes a discussion regarding the interpretation of the states and the factors that influence the transitions between the states. Further developments are also identified for using the model to aid fighter pilots and operators of unmanned aerial vehicles with planning and evaluating missions as well as analyzing the situation during flight.
Modeling HUI 2 health state preference data using a nonparametric Bayesian method.
Kharroubi, Samer A; McCabe, Christopher
2008-01-01
This article reports the application of a recently described approach to modeling health state valuation data and the impact of the respondent characteristics on health state valuations. The approach applies a nonparametric model to estimate a Bayesian Health Utilities Index Mark 2 (HUI 2) health state valuation algorithm. The data set is the UK HUI 2 valuation study where a sample of 51 states defined by the HUI 2 was valued by a sample of the UK general population using standard gamble. The article reports the application of the nonparametric model and compares it to the original model estimated using a conventional parametric random effects model. Advantages of the nonparametric model are that it can be used to predict scores in populations with different distributions of characteristics than observed in the survey sample and that it allows for the impact of respondent characteristics to vary by health state. The results suggest an important age effect with sex, having some effect, but the remaining covariates having no discernable effect. The article discusses the implications of these results for future applications of the HUI 2 and further work in this field. PMID:18971313
A macro traffic flow model accounting for real-time traffic state
NASA Astrophysics Data System (ADS)
Tang, Tie-Qiao; Chen, Liang; Wu, Yong-Hong; Caccetta, Lou
2015-11-01
In this paper, we propose a traffic flow model to study the effects of the real-time traffic state on traffic flow. The numerical results show that the proposed model can describe oscillation in traffic and stop-and-go traffic, where the speed-density relationship is qualitatively accordant with the empirical data of the Weizikeng segment of the Badaling freeway in Beijing, which means that the proposed model can qualitatively reproduce some complex traffic phenomena associated with real-time traffic state.
NASA Astrophysics Data System (ADS)
Allis, Damian G.; Hakey, Patrick M.; Korter, Timothy M.
2008-10-01
The terahertz (THz, far-infrared) spectrum of 3,4-methylene-dioxymethamphetamine hydrochloride (Ecstasy) is simulated using solid-state density functional theory. While a previously reported isolated-molecule calculation is noteworthy for the precision of its solid-state THz reproduction, the solid-state calculation predicts that the isolated-molecule modes account for only half of the spectral features in the THz region, with the remaining structure arising from lattice vibrations that cannot be predicted without solid-state molecular modeling. The molecular origins of the internal mode contributions to the solid-state THz spectrum, as well as the proper consideration of the protonation state of the molecule, are also considered.
A TWO-STATE MIXED HIDDEN MARKOV MODEL FOR RISKY TEENAGE DRIVING BEHAVIOR
Jackson, John C.; Albert, Paul S.; Zhang, Zhiwei
2016-01-01
This paper proposes a joint model for longitudinal binary and count outcomes. We apply the model to a unique longitudinal study of teen driving where risky driving behavior and the occurrence of crashes or near crashes are measured prospectively over the first 18 months of licensure. Of scientific interest is relating the two processes and predicting crash and near crash outcomes. We propose a two-state mixed hidden Markov model whereby the hidden state characterizes the mean for the joint longitudinal crash/near crash outcomes and elevated g-force events which are a proxy for risky driving. Heterogeneity is introduced in both the conditional model for the count outcomes and the hidden process using a shared random effect. An estimation procedure is presented using the forward–backward algorithm along with adaptive Gaussian quadrature to perform numerical integration. The estimation procedure readily yields hidden state probabilities as well as providing for a broad class of predictors.
Hasharoni, K.; Levanon, H.; Greenfield, S.R.; Gosztola, D.J.; Svec, W.A.; Wasiclewski, M.R. |
1995-08-02
Supramolecular systems synthesized to model the photosynthetic reaction center (RC) are designed to mimic several key properties of the RC protein. Thus far, most RC models fulfill only a subset of these criteria, with very few reports employing time-resolved electron paramagnetic resonance spectroscopy (TREPR). We now report TREPR results on a photosynthetic model system (1) in a nematic liquid crystal (LC) that does not contain the natural pigments, yet closely mimics the spin dynamics of triplet state formation found only in photosynthetic RCs. The design of supermolecule 1 follows criteria established for promoting high quantum yield charge separation in glassy media. The observation of this triplet state in 1 by TREPR demonstrates that most of the electronic states found in the primary photochemistry of photosynthetic RCs can be mimicked successfully in synthetic models interacting with LCs. 12 refs., 3 figs.
Application of wheat yield model to United States and India. [Great Plains
NASA Technical Reports Server (NTRS)
Feyerherm, A. M. (Principal Investigator)
1977-01-01
The author has identified the following significant results. The wheat yield model was applied to the major wheat-growing areas of the US and India. In the US Great Plains, estimates from the winter and spring wheat models agreed closely with USDA-SRS values in years with the lowest yields, but underestimated in years with the highest yields. Application to the Eastern Plains and Northwest indicated the importance of cultural factors, as well as meteorological ones in the model. It also demonstrated that the model could be used, in conjunction with USDA-SRRS estimates, to estimate yield losses due to factors not included in the model, particularly diseases and freezes. A fixed crop calendar for India was built from a limited amount of available plot data from that country. Application of the yield model gave measurable evidence that yield variation from state to state was due to different mixes of levels of meteorological and cultural factors.
Arons, Alexander M M; Krabbe, Paul F M
2013-02-01
Interest is rising in measuring subjective health outcomes, such as treatment outcomes that are not directly quantifiable (functional disability, symptoms, complaints, side effects and health-related quality of life). Health economists in particular have applied probabilistic choice models in the area of health evaluation. They increasingly use discrete choice models based on random utility theory to derive values for healthcare goods or services. Recent attempts have been made to use discrete choice models as an alternative method to derive values for health states. In this article, various probabilistic choice models are described according to their underlying theory. A historical overview traces their development and applications in diverse fields. The discussion highlights some theoretical and technical aspects of the choice models and their similarity and dissimilarity. The objective of the article is to elucidate the position of each model and their applications for health-state valuation.
Detecting critical state before phase transition of complex systems by hidden Markov model
NASA Astrophysics Data System (ADS)
Liu, Rui; Chen, Pei; Li, Yongjun; Chen, Luonan
Identifying the critical state or pre-transition state just before the occurrence of a phase transition is a challenging task, because the state of the system may show little apparent change before this critical transition during the gradual parameter variations. Such dynamics of phase transition is generally composed of three stages, i.e., before-transition state, pre-transition state, and after-transition state, which can be considered as three different Markov processes. Thus, based on this dynamical feature, we present a novel computational method, i.e., hidden Markov model (HMM), to detect the switching point of the two Markov processes from the before-transition state (a stationary Markov process) to the pre-transition state (a time-varying Markov process), thereby identifying the pre-transition state or early-warning signals of the phase transition. To validate the effectiveness, we apply this method to detect the signals of the imminent phase transitions of complex systems based on the simulated datasets, and further identify the pre-transition states as well as their critical modules for three real datasets, i.e., the acute lung injury triggered by phosgene inhalation, MCF-7 human breast cancer caused by heregulin, and HCV-induced dysplasia and hepatocellular carcinoma.
Oscillations in Spurious States of the Associative Memory Model with Synaptic Depression
NASA Astrophysics Data System (ADS)
Murata, Shin; Otsubo, Yosuke; Nagata, Kenji; Okada, Masato
2014-12-01
The associative memory model is a typical neural network model that can store discretely distributed fixed-point attractors as memory patterns. When the network stores the memory patterns extensively, however, the model has other attractors besides the memory patterns. These attractors are called spurious memories. Both spurious states and memory states are in equilibrium, so there is little difference between their dynamics. Recent physiological experiments have shown that the short-term dynamic synapse called synaptic depression decreases its efficacy of transmission to postsynaptic neurons according to the activities of presynaptic neurons. Previous studies revealed that synaptic depression destabilizes the memory states when the number of memory patterns is finite. However, it is very difficult to study the dynamical properties of the spurious states if the number of memory patterns is proportional to the number of neurons. We investigate the effect of synaptic depression on spurious states by Monte Carlo simulation. The results demonstrate that synaptic depression does not affect the memory states but mainly destabilizes the spurious states and induces periodic oscillations.
Functional connectivity dynamics: modeling the switching behavior of the resting state.
Hansen, Enrique C A; Battaglia, Demian; Spiegler, Andreas; Deco, Gustavo; Jirsa, Viktor K
2015-01-15
Functional connectivity (FC) sheds light on the interactions between different brain regions. Besides basic research, it is clinically relevant for applications in Alzheimer's disease, schizophrenia, presurgical planning, epilepsy, and traumatic brain injury. Simulations of whole-brain mean-field computational models with realistic connectivity determined by tractography studies enable us to reproduce with accuracy aspects of average FC in the resting state. Most computational studies, however, did not address the prominent non-stationarity in resting state FC, which may result in large intra- and inter-subject variability and thus preclude an accurate individual predictability. Here we show that this non-stationarity reveals a rich structure, characterized by rapid transitions switching between a few discrete FC states. We also show that computational models optimized to fit time-averaged FC do not reproduce these spontaneous state transitions and, thus, are not qualitatively superior to simplified linear stochastic models, which account for the effects of structure alone. We then demonstrate that a slight enhancement of the non-linearity of the network nodes is sufficient to broaden the repertoire of possible network behaviors, leading to modes of fluctuations, reminiscent of some of the most frequently observed Resting State Networks. Because of the noise-driven exploration of this repertoire, the dynamics of FC qualitatively change now and display non-stationary switching similar to empirical resting state recordings (Functional Connectivity Dynamics (FCD)). Thus FCD bear promise to serve as a better biomarker of resting state neural activity and of its pathologic alterations. PMID:25462790
NASA Astrophysics Data System (ADS)
Aslan, Serdar; Taylan Cemgil, Ali; Akın, Ata
2016-08-01
Objective. In this paper, we aimed for the robust estimation of the parameters and states of the hemodynamic model by using blood oxygen level dependent signal. Approach. In the fMRI literature, there are only a few successful methods that are able to make a joint estimation of the states and parameters of the hemodynamic model. In this paper, we implemented a maximum likelihood based method called the particle smoother expectation maximization (PSEM) algorithm for the joint state and parameter estimation. Main results. Former sequential Monte Carlo methods were only reliable in the hemodynamic state estimates. They were claimed to outperform the local linearization (LL) filter and the extended Kalman filter (EKF). The PSEM algorithm is compared with the most successful method called square-root cubature Kalman smoother (SCKS) for both state and parameter estimation. SCKS was found to be better than the dynamic expectation maximization (DEM) algorithm, which was shown to be a better estimator than EKF, LL and particle filters. Significance. PSEM was more accurate than SCKS for both the state and the parameter estimation. Hence, PSEM seems to be the most accurate method for the system identification and state estimation for the hemodynamic model inversion literature. This paper do not compare its results with Tikhonov-regularized Newton—CKF (TNF-CKF), a recent robust method which works in filtering sense.
Robustness and state-space structure of Boolean gene regulatory models.
Willadsen, Kai; Wiles, Janet
2007-12-21
Robustness to perturbation is an important characteristic of genetic regulatory systems, but the relationship between robustness and model dynamics has not been clearly quantified. We propose a method for quantifying both robustness and dynamics in terms of state-space structures, for Boolean models of genetic regulatory systems. By investigating existing models of the Drosophila melanogaster segment polarity network and the Saccharomyces cerevisiae cell-cycle network, we show that the structure of attractor basins can yield insight into the underlying decision making required of the system, and also the way in which the system maximises its robustness. In particular, gene networks implementing decisions based on a few genes have simple state-space structures, and their attractors are robust by virtue of their simplicity. Gene networks with decisions that involve many interacting genes have correspondingly more complicated state-space structures, and robustness cannot be achieved through the structure of the attractor basins, but is achieved by larger attractor basins that dominate the state space. These different types of robustness are demonstrated by the two models: the D. melanogaster segment polarity network is robust due to simple attractor basins that implement decisions based on spatial signals; the S. cerevisiae cell-cycle network has a complicated state-space structure, and is robust only due to a giant attractor basin that dominates the state space.
Squeezed States, Uncertainty Relations and the Pauli Principle in Composite and Cosmological Models
NASA Technical Reports Server (NTRS)
Terazawa, Hidezumi
1996-01-01
The importance of not only uncertainty relations but also the Pauli exclusion principle is emphasized in discussing various 'squeezed states' existing in the universe. The contents of this paper include: (1) Introduction; (2) Nuclear Physics in the Quark-Shell Model; (3) Hadron Physics in the Standard Quark-Gluon Model; (4) Quark-Lepton-Gauge-Boson Physics in Composite Models; (5) Astrophysics and Space-Time Physics in Cosmological Models; and (6) Conclusion. Also, not only the possible breakdown of (or deviation from) uncertainty relations but also the superficial violation of the Pauli principle at short distances (or high energies) in composite (and string) models is discussed in some detail.
Rosenblatt, Marcus; Timmer, Jens; Kaschek, Daniel
2016-01-01
Ordinary differential equation models have become a wide-spread approach to analyze dynamical systems and understand underlying mechanisms. Model parameters are often unknown and have to be estimated from experimental data, e.g., by maximum-likelihood estimation. In particular, models of biological systems contain a large number of parameters. To reduce the dimensionality of the parameter space, steady-state information is incorporated in the parameter estimation process. For non-linear models, analytical steady-state calculation typically leads to higher-order polynomial equations for which no closed-form solutions can be obtained. This can be circumvented by solving the steady-state equations for kinetic parameters, which results in a linear equation system with comparatively simple solutions. At the same time multiplicity of steady-state solutions is avoided, which otherwise is problematic for optimization. When solved for kinetic parameters, however, steady-state constraints tend to become negative for particular model specifications, thus, generating new types of optimization problems. Here, we present an algorithm based on graph theory that derives non-negative, analytical steady-state expressions by stepwise removal of cyclic dependencies between dynamical variables. The algorithm avoids multiple steady-state solutions by construction. We show that our method is applicable to most common classes of biochemical reaction networks containing inhibition terms, mass-action and Hill-type kinetic equations. Comparing the performance of parameter estimation for different analytical and numerical methods of incorporating steady-state information, we show that our approach is especially well-tailored to guarantee a high success rate of optimization. PMID:27243005
Rosenblatt, Marcus; Timmer, Jens; Kaschek, Daniel
2016-01-01
Ordinary differential equation models have become a wide-spread approach to analyze dynamical systems and understand underlying mechanisms. Model parameters are often unknown and have to be estimated from experimental data, e.g., by maximum-likelihood estimation. In particular, models of biological systems contain a large number of parameters. To reduce the dimensionality of the parameter space, steady-state information is incorporated in the parameter estimation process. For non-linear models, analytical steady-state calculation typically leads to higher-order polynomial equations for which no closed-form solutions can be obtained. This can be circumvented by solving the steady-state equations for kinetic parameters, which results in a linear equation system with comparatively simple solutions. At the same time multiplicity of steady-state solutions is avoided, which otherwise is problematic for optimization. When solved for kinetic parameters, however, steady-state constraints tend to become negative for particular model specifications, thus, generating new types of optimization problems. Here, we present an algorithm based on graph theory that derives non-negative, analytical steady-state expressions by stepwise removal of cyclic dependencies between dynamical variables. The algorithm avoids multiple steady-state solutions by construction. We show that our method is applicable to most common classes of biochemical reaction networks containing inhibition terms, mass-action and Hill-type kinetic equations. Comparing the performance of parameter estimation for different analytical and numerical methods of incorporating steady-state information, we show that our approach is especially well-tailored to guarantee a high success rate of optimization. PMID:27243005
Rosenblatt, Marcus; Timmer, Jens; Kaschek, Daniel
2016-01-01
Ordinary differential equation models have become a wide-spread approach to analyze dynamical systems and understand underlying mechanisms. Model parameters are often unknown and have to be estimated from experimental data, e.g., by maximum-likelihood estimation. In particular, models of biological systems contain a large number of parameters. To reduce the dimensionality of the parameter space, steady-state information is incorporated in the parameter estimation process. For non-linear models, analytical steady-state calculation typically leads to higher-order polynomial equations for which no closed-form solutions can be obtained. This can be circumvented by solving the steady-state equations for kinetic parameters, which results in a linear equation system with comparatively simple solutions. At the same time multiplicity of steady-state solutions is avoided, which otherwise is problematic for optimization. When solved for kinetic parameters, however, steady-state constraints tend to become negative for particular model specifications, thus, generating new types of optimization problems. Here, we present an algorithm based on graph theory that derives non-negative, analytical steady-state expressions by stepwise removal of cyclic dependencies between dynamical variables. The algorithm avoids multiple steady-state solutions by construction. We show that our method is applicable to most common classes of biochemical reaction networks containing inhibition terms, mass-action and Hill-type kinetic equations. Comparing the performance of parameter estimation for different analytical and numerical methods of incorporating steady-state information, we show that our approach is especially well-tailored to guarantee a high success rate of optimization.
Multi-temperature state-dependent equivalent circuit discharge model for lithium-sulfur batteries
NASA Astrophysics Data System (ADS)
Propp, Karsten; Marinescu, Monica; Auger, Daniel J.; O'Neill, Laura; Fotouhi, Abbas; Somasundaram, Karthik; Offer, Gregory J.; Minton, Geraint; Longo, Stefano; Wild, Mark; Knap, Vaclav
2016-10-01
Lithium-sulfur (Li-S) batteries are described extensively in the literature, but existing computational models aimed at scientific understanding are too complex for use in applications such as battery management. Computationally simple models are vital for exploitation. This paper proposes a non-linear state-of-charge dependent Li-S equivalent circuit network (ECN) model for a Li-S cell under discharge. Li-S batteries are fundamentally different to Li-ion batteries, and require chemistry-specific models. A new Li-S model is obtained using a 'behavioural' interpretation of the ECN model; as Li-S exhibits a 'steep' open-circuit voltage (OCV) profile at high states-of-charge, identification methods are designed to take into account OCV changes during current pulses. The prediction-error minimization technique is used. The model is parameterized from laboratory experiments using a mixed-size current pulse profile at four temperatures from 10 °C to 50 °C, giving linearized ECN parameters for a range of states-of-charge, currents and temperatures. These are used to create a nonlinear polynomial-based battery model suitable for use in a battery management system. When the model is used to predict the behaviour of a validation data set representing an automotive NEDC driving cycle, the terminal voltage predictions are judged accurate with a root mean square error of 32 mV.
Down-state model of the voltage-sensing domain of a potassium channel.
Schow, Eric V; Freites, J Alfredo; Gogna, Karun; White, Stephen H; Tobias, Douglas J
2010-06-16
Voltage-sensing domains (VSDs) of voltage-gated potassium (Kv) channels undergo a series of conformational changes upon membrane depolarization, from a down state when the channel is at rest to an up state, all of which lead to the opening of the channel pore. The crystal structures reported to date reveal the pore in an open state and the VSDs in an up state. To gain insights into the structure of the down state, we used a set of experiment-based restraints to generate a model of the down state of the KvAP VSD using molecular-dynamics simulations of the VSD in a lipid bilayer in excess water. The equilibrated VSD configuration is consistent with the biotin-avidin accessibility and internal salt-bridge data used to generate it, and with additional biotin-avidin accessibility data. In the model, both the S3b and S4 segments are displaced approximately 10 A toward the intracellular side with respect to the up-state configuration, but they do not move as a rigid body. Arginine side chains that carry the majority of the gating charge also make large excursions between the up and down states. In both states, arginines interact with water and participate in salt bridges with acidic residues and lipid phosphate groups. An important feature that emerges from the down-state model is that the N-terminal half of the S4 segment adopts a 3(10)-helical conformation, which appears to be necessary to satisfy a complex salt-bridge network.
Current Pressure Transducer Application of Model-based Prognostics Using Steady State Conditions
NASA Technical Reports Server (NTRS)
Teubert, Christopher; Daigle, Matthew J.
2014-01-01
Prognostics is the process of predicting a system's future states, health degradation/wear, and remaining useful life (RUL). This information plays an important role in preventing failure, reducing downtime, scheduling maintenance, and improving system utility. Prognostics relies heavily on wear estimation. In some components, the sensors used to estimate wear may not be fast enough to capture brief transient states that are indicative of wear. For this reason it is beneficial to be capable of detecting and estimating the extent of component wear using steady-state measurements. This paper details a method for estimating component wear using steady-state measurements, describes how this is used to predict future states, and presents a case study of a current/pressure (I/P) Transducer. I/P Transducer nominal and off-nominal behaviors are characterized using a physics-based model, and validated against expected and observed component behavior. This model is used to map observed steady-state responses to corresponding fault parameter values in the form of a lookup table. This method was chosen because of its fast, efficient nature, and its ability to be applied to both linear and non-linear systems. Using measurements of the steady state output, and the lookup table, wear is estimated. A regression is used to estimate the wear propagation parameter and characterize the damage progression function, which are used to predict future states and the remaining useful life of the system.
Elenchezhiyan, M; Prakash, J
2015-09-01
In this work, state estimation schemes for non-linear hybrid dynamic systems subjected to stochastic state disturbances and random errors in measurements using interacting multiple-model (IMM) algorithms are formulated. In order to compute both discrete modes and continuous state estimates of a hybrid dynamic system either an IMM extended Kalman filter (IMM-EKF) or an IMM based derivative-free Kalman filters is proposed in this study. The efficacy of the proposed IMM based state estimation schemes is demonstrated by conducting Monte-Carlo simulation studies on the two-tank hybrid system and switched non-isothermal continuous stirred tank reactor system. Extensive simulation studies reveal that the proposed IMM based state estimation schemes are able to generate fairly accurate continuous state estimates and discrete modes. In the presence and absence of sensor bias, the simulation studies reveal that the proposed IMM unscented Kalman filter (IMM-UKF) based simultaneous state and parameter estimation scheme outperforms multiple-model UKF (MM-UKF) based simultaneous state and parameter estimation scheme.
Model Checking - My 27-Year Quest to Overcome the State Explosion Problem
NASA Technical Reports Server (NTRS)
Clarke, Ed
2009-01-01
Model Checking is an automatic verification technique for state-transition systems that are finite=state or that have finite-state abstractions. In the early 1980 s in a series of joint papers with my graduate students E.A. Emerson and A.P. Sistla, we proposed that Model Checking could be used for verifying concurrent systems and gave algorithms for this purpose. At roughly the same time, Joseph Sifakis and his student J.P. Queille at the University of Grenoble independently developed a similar technique. Model Checking has been used successfully to reason about computer hardware and communication protocols and is beginning to be used for verifying computer software. Specifications are written in temporal logic, which is particularly valuable for expressing concurrency properties. An intelligent, exhaustive search is used to determine if the specification is true or not. If the specification is not true, the Model Checker will produce a counterexample execution trace that shows why the specification does not hold. This feature is extremely useful for finding obscure errors in complex systems. The main disadvantage of Model Checking is the state-explosion problem, which can occur if the system under verification has many processes or complex data structures. Although the state-explosion problem is inevitable in worst case, over the past 27 years considerable progress has been made on the problem for certain classes of state-transition systems that occur often in practice. In this talk, I will describe what Model Checking is, how it works, and the main techniques that have been developed for combating the state explosion problem.
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
The Hofstadter model is one of the most celebrated models for the study of topological properties of matter and allows the study of the quantum Hall effect in a lattice system. Indeed, the Hofstadter Hamiltonian harbors the topological chiral edge states that are responsible for the quantized Hall conductivity. Here, we show that a lattice dimerization in the Hofstadter model opens an energy gap at half-filling. What is more, we demonstrate that even if the ensuing insulator has a Chern number equal to zero, concomitantly a doublet of edge states appear that are pinned to specific momenta. We show that the presence of these states can be understood from the topological properties of lower dimensional cuts of the system, using a mapping of the Hofstadter Hamiltonian to a collection of one-dimensional Aubry-André-Harper (AAH) models. A sub-set of AAH chains in this collection preserve inversion symmetry. This guarantees the presence of topologically protected doublets of end modes to which the edge states are pinned. To explicitly prove the robustness of the emerging edge states, we define and calculate the topological invariant that protects them, which turns out to be an integer invariant for inversion-symmetric AAH models.
Stable AMOC off-state in an eddy-resolving coupled climate model
NASA Astrophysics Data System (ADS)
Mecking, Jennifer; Drijfhout, Sybren; Jackson, Laura; Graham, Tim; Wood, Richard
2015-04-01
A collapse of the Atlantic Meridional Overturning Circulation (AMOC) despite being unlikely could have devastating impacts on the current climate. Shifts between on- and off-states of the AMOC have been associated with past abrupt climate change, supported by the bistability of the AMOC found in many ocean and climate models. However, as coupled climate models evolved in complexity a stable AMOC off-state no longer seemed supported. In this study a next-generation, eddy-resolving, climate model, HadGEM3 has an AMOC off-state that remains stable for the 260 year duration of the model integration. Ocean eddies modify the overall freshwater balance, allowing for stronger northward salt transport by the AMOC compared to non-eddy resolving models. As a result, the salinification of the subtropical North Atlantic, due to a southward shift of the intertropical rain belt, is balanced by reduced salt transport of the collapsed AMOC, stabilizing the off-state. Without ocean eddies, salinity biases in the Atlantic preclude the balance that stabilizes the off-state, unless flux-correction is applied.
An optimal state estimation model of sensory integration in human postural balance
NASA Astrophysics Data System (ADS)
Kuo, Arthur D.
2005-09-01
We propose a model for human postural balance, combining state feedback control with optimal state estimation. State estimation uses an internal model of body and sensor dynamics to process sensor information and determine body orientation. Three sensory modalities are modeled: joint proprioception, vestibular organs in the inner ear, and vision. These are mated with a two degree-of-freedom model of body dynamics in the sagittal plane. Linear quadratic optimal control is used to design state feedback and estimation gains. Nine free parameters define the control objective and the signal-to-noise ratios of the sensors. The model predicts statistical properties of human sway in terms of covariance of ankle and hip motion. These predictions are compared with normal human responses to alterations in sensory conditions. With a single parameter set, the model successfully reproduces the general nature of postural motion as a function of sensory environment. Parameter variations reveal that the model is highly robust under normal sensory conditions, but not when two or more sensors are inaccurate. This behavior is similar to that of normal human subjects. We propose that age-related sensory changes may be modeled with decreased signal-to-noise ratios, and compare the model's behavior with degraded sensors against experimental measurements from older adults. We also examine removal of the model's vestibular sense, which leads to instability similar to that observed in bilateral vestibular loss subjects. The model may be useful for predicting which sensors are most critical for balance, and how much they can deteriorate before posture becomes unstable.
NASA Astrophysics Data System (ADS)
Häme, Tuomas; Mutanen, Teemu; Rauste, Yrjö; Antropov, Oleg; Molinier, Matthieu; Quegan, Shaun; Kantzas, Euripides; Mäkelä, Annikki; Minunno, Francesco; Atli Benediktsson, Jon; Falco, Nicola; Arnason, Kolbeinn; Storvold, Rune; Haarpaintner, Jörg; Elsakov, Vladimir; Rasinmäki, Jussi
2015-04-01
The objective of project North State, funded by Framework Program 7 of the European Union, is to develop innovative data fusion methods that exploit the new generation of multi-source data from Sentinels and other satellites in an intelligent, self-learning framework. The remote sensing outputs are interfaced with state-of-the-art carbon and water flux models for monitoring the fluxes over boreal Europe to reduce current large uncertainties. This will provide a paradigm for the development of products for future Copernicus services. The models to be interfaced are a dynamic vegetation model and a light use efficiency model. We have identified four groups of variables that will be estimated with remote sensed data: land cover variables, forest characteristics, vegetation activity, and hydrological variables. The estimates will be used as model inputs and to validate the model outputs. The earth observation variables are computed as automatically as possible, with an objective to completely automatic estimation. North State has two sites for intensive studies in southern and northern Finland, respectively, one in Iceland and one in state Komi of Russia. Additionally, the model input variables will be estimated and models applied over European boreal and sub-arctic region from Ural Mountains to Iceland. The accuracy assessment of the earth observation variables will follow statistical sampling design. Model output predictions are compared to earth observation variables. Also flux tower measurements are applied in the model assessment. In the paper, results of hyperspectral, Sentinel-1, and Landsat data and their use in the models is presented. Also an example of a completely automatic land cover class prediction is reported.
Bayesian state space models for dynamic genetic network construction across multiple tissues.
Liang, Yulan; Kelemen, Arpad
2016-08-01
Construction of gene-gene interaction networks and potential pathways is a challenging and important problem in genomic research for complex diseases while estimating the dynamic changes of the temporal correlations and non-stationarity are the keys in this process. In this paper, we develop dynamic state space models with hierarchical Bayesian settings to tackle this challenge for inferring the dynamic profiles and genetic networks associated with disease treatments. We treat both the stochastic transition matrix and the observation matrix time-variant and include temporal correlation structures in the covariance matrix estimations in the multivariate Bayesian state space models. The unevenly spaced short time courses with unseen time points are treated as hidden state variables. Hierarchical Bayesian approaches with various prior and hyper-prior models with Monte Carlo Markov Chain and Gibbs sampling algorithms are used to estimate the model parameters and the hidden state variables. We apply the proposed Hierarchical Bayesian state space models to multiple tissues (liver, skeletal muscle, and kidney) Affymetrix time course data sets following corticosteroid (CS) drug administration. Both simulation and real data analysis results show that the genomic changes over time and gene-gene interaction in response to CS treatment can be well captured by the proposed models. The proposed dynamic Hierarchical Bayesian state space modeling approaches could be expanded and applied to other large scale genomic data, such as next generation sequence (NGS) combined with real time and time varying electronic health record (EHR) for more comprehensive and robust systematic and network based analysis in order to transform big biomedical data into predictions and diagnostics for precision medicine and personalized healthcare with better decision making and patient outcomes. PMID:27343475
Bayesian state space models for dynamic genetic network construction across multiple tissues.
Liang, Yulan; Kelemen, Arpad
2016-08-01
Construction of gene-gene interaction networks and potential pathways is a challenging and important problem in genomic research for complex diseases while estimating the dynamic changes of the temporal correlations and non-stationarity are the keys in this process. In this paper, we develop dynamic state space models with hierarchical Bayesian settings to tackle this challenge for inferring the dynamic profiles and genetic networks associated with disease treatments. We treat both the stochastic transition matrix and the observation matrix time-variant and include temporal correlation structures in the covariance matrix estimations in the multivariate Bayesian state space models. The unevenly spaced short time courses with unseen time points are treated as hidden state variables. Hierarchical Bayesian approaches with various prior and hyper-prior models with Monte Carlo Markov Chain and Gibbs sampling algorithms are used to estimate the model parameters and the hidden state variables. We apply the proposed Hierarchical Bayesian state space models to multiple tissues (liver, skeletal muscle, and kidney) Affymetrix time course data sets following corticosteroid (CS) drug administration. Both simulation and real data analysis results show that the genomic changes over time and gene-gene interaction in response to CS treatment can be well captured by the proposed models. The proposed dynamic Hierarchical Bayesian state space modeling approaches could be expanded and applied to other large scale genomic data, such as next generation sequence (NGS) combined with real time and time varying electronic health record (EHR) for more comprehensive and robust systematic and network based analysis in order to transform big biomedical data into predictions and diagnostics for precision medicine and personalized healthcare with better decision making and patient outcomes.
A state-based probabilistic model for tumor respiratory motion prediction
NASA Astrophysics Data System (ADS)
Kalet, Alan; Sandison, George; Wu, Huanmei; Schmitz, Ruth
2010-12-01
This work proposes a new probabilistic mathematical model for predicting tumor motion and position based on a finite state representation using the natural breathing states of exhale, inhale and end of exhale. Tumor motion was broken down into linear breathing states and sequences of states. Breathing state sequences and the observables representing those sequences were analyzed using a hidden Markov model (HMM) to predict the future sequences and new observables. Velocities and other parameters were clustered using a k-means clustering algorithm to associate each state with a set of observables such that a prediction of state also enables a prediction of tumor velocity. A time average model with predictions based on average past state lengths was also computed. State sequences which are known a priori to fit the data were fed into the HMM algorithm to set a theoretical limit of the predictive power of the model. The effectiveness of the presented probabilistic model has been evaluated for gated radiation therapy based on previously tracked tumor motion in four lung cancer patients. Positional prediction accuracy is compared with actual position in terms of the overall RMS errors. Various system delays, ranging from 33 to 1000 ms, were tested. Previous studies have shown duty cycles for latencies of 33 and 200 ms at around 90% and 80%, respectively, for linear, no prediction, Kalman filter and ANN methods as averaged over multiple patients. At 1000 ms, the previously reported duty cycles range from approximately 62% (ANN) down to 34% (no prediction). Average duty cycle for the HMM method was found to be 100% and 91 ± 3% for 33 and 200 ms latency and around 40% for 1000 ms latency in three out of four breathing motion traces. RMS errors were found to be lower than linear and no prediction methods at latencies of 1000 ms. The results show that for system latencies longer than 400 ms, the time average HMM prediction outperforms linear, no prediction, and the more
A heuristic finite-state model of the human driver in a car-following situation
NASA Technical Reports Server (NTRS)
Burnham, G. O.; Bekey, G. A.
1976-01-01
An approach to modeling human driver behavior in single-lane car following which is based on a finite-state decision structure is considered. The specific strategy at each point in the decision tree was obtained from observations of typical driver behavior. The synthesis of the decision logic is based on position and velocity thresholds and four states defined by regions in the phase plane. The performance of the resulting assumed intuitively logical model was compared with actual freeway data. The match of the model to the data was optimized by adapting the model parameters using a modified PARTAN algorithm. The results indicate that the heuristic model behavior matches actual car-following performance better during deceleration and constant velocity phases than during acceleration periods.
Einstein's steady-state theory: an abandoned model of the cosmos
NASA Astrophysics Data System (ADS)
O'Raifeartaigh, Cormac; McCann, Brendan; Nahm, Werner; Mitton, Simon
2014-09-01
We present a translation and analysis of an unpublished manuscript by Albert Einstein in which he attempted to construct a `steady-state' model of the universe. The manuscript, which appears to have been written in early 1931, demonstrates that Einstein once explored a cosmic model in which the mean density of matter in an expanding universe is maintained constant by the continuous formation of matter from empty space. This model is very different to previously known Einsteinian models of the cosmos (both static and dynamic) but anticipates the later steady-state cosmology of Hoyle, Bondi and Gold in some ways. We find that Einstein's steady-state model contains a fundamental flaw and suggest that it was abandoned for this reason. We also suggest that he declined to explore a more sophisticated version because he found such theories rather contrived. The manuscript is of historical interest because it reveals that Einstein debated between steady-state and evolving models of the cosmos decades before a similar debate took place in the cosmological community.
Adaptive behaviour and multiple equilibrium states in a predator-prey model.
Pimenov, Alexander; Kelly, Thomas C; Korobeinikov, Andrei; O'Callaghan, Michael J A; Rachinskii, Dmitrii
2015-05-01
There is evidence that multiple stable equilibrium states are possible in real-life ecological systems. Phenomenological mathematical models which exhibit such properties can be constructed rather straightforwardly. For instance, for a predator-prey system this result can be achieved through the use of non-monotonic functional response for the predator. However, while formal formulation of such a model is not a problem, the biological justification for such functional responses and models is usually inconclusive. In this note, we explore a conjecture that a multitude of equilibrium states can be caused by an adaptation of animal behaviour to changes of environmental conditions. In order to verify this hypothesis, we consider a simple predator-prey model, which is a straightforward extension of the classic Lotka-Volterra predator-prey model. In this model, we made an intuitively transparent assumption that the prey can change a mode of behaviour in response to the pressure of predation, choosing either "safe" of "risky" (or "business as usual") behaviour. In order to avoid a situation where one of the modes gives an absolute advantage, we introduce the concept of the "cost of a policy" into the model. A simple conceptual two-dimensional predator-prey model, which is minimal with this property, and is not relying on odd functional responses, higher dimensionality or behaviour change for the predator, exhibits two stable co-existing equilibrium states with basins of attraction separated by a separatrix of a saddle point.
Adaptive behaviour and multiple equilibrium states in a predator-prey model.
Pimenov, Alexander; Kelly, Thomas C; Korobeinikov, Andrei; O'Callaghan, Michael J A; Rachinskii, Dmitrii
2015-05-01
There is evidence that multiple stable equilibrium states are possible in real-life ecological systems. Phenomenological mathematical models which exhibit such properties can be constructed rather straightforwardly. For instance, for a predator-prey system this result can be achieved through the use of non-monotonic functional response for the predator. However, while formal formulation of such a model is not a problem, the biological justification for such functional responses and models is usually inconclusive. In this note, we explore a conjecture that a multitude of equilibrium states can be caused by an adaptation of animal behaviour to changes of environmental conditions. In order to verify this hypothesis, we consider a simple predator-prey model, which is a straightforward extension of the classic Lotka-Volterra predator-prey model. In this model, we made an intuitively transparent assumption that the prey can change a mode of behaviour in response to the pressure of predation, choosing either "safe" of "risky" (or "business as usual") behaviour. In order to avoid a situation where one of the modes gives an absolute advantage, we introduce the concept of the "cost of a policy" into the model. A simple conceptual two-dimensional predator-prey model, which is minimal with this property, and is not relying on odd functional responses, higher dimensionality or behaviour change for the predator, exhibits two stable co-existing equilibrium states with basins of attraction separated by a separatrix of a saddle point. PMID:25732186
Shell model study of T =0 states for 96Cd by the nucleon-pair approximation
NASA Astrophysics Data System (ADS)
Fu, G. J.; Cheng, Y. Y.; Zhao, Y. M.; Arima, A.
2016-08-01
In this paper we study the nucleon-pair approximation for T =0 states of 96Cd in the 1 p1 /21 p3 /20 f5 /20 g9 /2 shell with the JUN45 interaction. The lowest seniority scheme and the isoscalar spin-one pair approximation are not enough to describe the states. The isoscalar spin-aligned pair approximation is reasonably good for the yrast 2+, 4+, 6+, 12+, 14+, and 16+ states as pointed out previously. Not only the yrast positive-parity states but also nonyrast states and negative-parity states are well described by both the isovector pair approximation and the isoscalar pair approximation. We calculate overlaps between nucleon-pair basis states and shell-model wave functions. The largest overlaps and the corresponding nucleon-pair basis states are presented. We find that isovector spin-zero pairs, isovector spin-two pairs, and isoscalar spin-aligned pairs are the dominant building blocks in these states.
Lumped-state CRE Modeling of the Ionization Dynamics of O- and N-like Krypton
NASA Astrophysics Data System (ADS)
Whitney, K. G.; Dasgupta, A.; Thornhill, J. W.; Davis, J.
2007-11-01
An often used approximation employed to simplify the problem of modeling the L- and M-shell ionization dynamics of moderate to high atomic number plasmas is to lump the states within each nl multiplet of each ionization stage, and historically, this approximation has been applied assuming the multiplet substates are in LTE with respect to one another. In both Fe and W Z-pinch plasmas, this assumption has been shown to break down in ionization stages where the ground state has no multiplet structure ootnotetextK. G. Whitney, et. al., J. Phys. B, 40, 2747 (2007).. In this talk, we study the subpopulation dynamics in O- and N-like ionization stages where significant amounts of population can be stored in excited states and where ground states have multiplet structure. The non-LTE behavior of the following states is calculated: the ground states, the δn=0, and the 2p^33l or 2p^23l excited states of O-like and N-like Kr respectively, and used to determine the impact on lumped state excitation and ionization rates and on the MHD of Z-pinch Kr implosions. In particular, the reduction of the Einstein decay rates of the n=3 states as a function of ion density is calculated.
Control of spiral waves and turbulent states in a cardiac model by travelling-wave perturbations
NASA Astrophysics Data System (ADS)
Wang, Peng-Ye; Xie, Ping; Yin, Hua-Wei
2003-06-01
We propose a travelling-wave perturbation method to control the spatiotemporal dynamics in a cardiac model. It is numerically demonstrated that the method can successfully suppress the wave instability (alternans in action potential duration) in the one-dimensional case and convert spiral waves and turbulent states to the normal travelling wave states in the two-dimensional case. An experimental scheme is suggested which may provide a new design for a cardiac defibrillator.
Ground-state phase diagram of the one-dimensional half-filled extended Hubbard model
NASA Astrophysics Data System (ADS)
Tsuchiizu, M.; Furusaki, A.
2004-01-01
We revisit the ground-state phase diagram of the one-dimensional half-filled extended Hubbard model with on-site (U) and nearest-neighbor (V) repulsive interactions. In the first half of the paper, using the weak-coupling renormalization-group approach (g-ology) including second-order corrections to the coupling constants, we show that bond-charge-density-wave (BCDW) phase exists for U≈2V in between charge-density-wave (CDW) and spin-density-wave (SDW) phases. We find that the umklapp scattering of parallel-spin electrons disfavors the BCDW state and leads to a bicritical point where the CDW-BCDW and SDW-BCDW continuous-transition lines merge into the CDW-SDW first-order transition line. In the second half of the paper, we investigate the phase diagram of the extended Hubbard model with either additional staggered site potential Δ or bond alternation δ. Although the alternating site potential Δ strongly favors the CDW state (that is, a band insulator), the BCDW state is not destroyed completely and occupies a finite region in the phase diagram. Our result is a natural generalization of the work by Fabrizio, Gogolin, and Nersesyan [Phys. Rev. Lett. 83, 2014 (1999)], who predicted the existence of a spontaneously dimerized insulating state between a band insulator and a Mott insulator in the phase diagram of the ionic Hubbard model. The bond alternation δ destroys the SDW state and changes it into the BCDW state (or Peierls insulating state). As a result the phase diagram of the model with δ contains only a single critical line separating the Peierls insulator phase and the CDW phase. The addition of Δ or δ changes the universality class of the CDW-BCDW transition from the Gaussian transition into the Ising transition.
Non-equilibrium Steady States in Kac's Model Coupled to a Thermostat
NASA Astrophysics Data System (ADS)
Evans, Josephine
2016-09-01
This paper studies the existence, uniqueness and convergence to non-equilibrium steady states in Kac's model with an external coupling. We work in both Fourier distances and Wasserstein distances. Our methods work in the case where the external coupling is not a Maxwellian equilibrium. This provides an example of a non-equilibrium steady state. We also study the behaviour as the number of particles goes to infinity and show quantitative estimates on the convergence rate of the first marginal.
Theoretical model of an organic ferrimagnetic state for a bipartite lozenge chain
NASA Astrophysics Data System (ADS)
Duan, Y. F.; Yao, K. L.
2001-04-01
A model for one-dimensional bipartite lozenge chain is proposed. By unrestricted Hartree-Fock approximation, we find that the system should exhibit ferrimagnetic ordering for a half filled band. In the ground state, the energy levels of electrons will split off with respect to different spins and the electrons along the chain will form an antiferromagnetic spin-density wave. The ground state of the system will be more stable with increasing of the on-site Hubbard term.
Minimal state space realisation of continuous-time linear time-variant input-output models
NASA Astrophysics Data System (ADS)
Goos, J.; Pintelon, R.
2016-04-01
In the linear time-invariant (LTI) framework, the transformation from an input-output equation into state space representation is well understood. Several canonical forms exist that realise the same dynamic behaviour. If the coefficients become time-varying however, the LTI transformation no longer holds. We prove by induction that there exists a closed-form expression for the observability canonical state space model, using binomial coefficients.
A modified two-state empirical valence bond model for proton transport in aqueous solutions
Mabuchi, Takuya; Fukushima, Akinori; Tokumasu, Takashi
2015-07-07
A detailed analysis of the proton solvation structure and transport properties in aqueous solutions is performed using classical molecular dynamics simulations. A refined two-state empirical valence bond (aTS-EVB) method, which is based on the EVB model of Walbran and Kornyshev and the anharmonic water force field, is developed in order to describe efficiently excess proton transport via the Grotthuss mechanism. The new aTS-EVB model clearly satisfies the requirement for simpler and faster calculation, because of the simplicity of the two-state EVB algorithm, while providing a better description of diffusive dynamics of the excess proton and water in comparison with the previous two-state EVB models, which significantly improves agreement with the available experimental data. The results of activation energies for the excess proton and water calculated between 300 and 340 K (the temperature range used in this study) are also found to be in good agreement with the corresponding experimental data.
Measurement of the Equation of State of the Two-Dimensional Hubbard Model
NASA Astrophysics Data System (ADS)
Miller, Luke; Cocchi, Eugenio; Drewes, Jan; Koschorreck, Marco; Pertot, Daniel; Brennecke, Ferdinand; Koehl, Michael
2016-05-01
The subtle interplay between kinetic energy, interactions and dimensionality challenges our comprehension of strongly-correlated physics observed, for example, in the solid state. In this quest, the Hubbard model has emerged as a conceptually simple, yet rich model describing such physics. Here we present an experimental determination of the equation of state of the repulsive two-dimensional Hubbard model over a broad range of interactions, 0 <= U / t <= 20 , and temperatures, down to kB T / t = 0 . 63(2) using high-resolution imaging of ultracold fermionic atoms in optical lattices. We show density profiles, compressibilities and double occupancies over the whole doping range, and hence our results constitute benchmarks for state-of-the-art theoretical approaches.
Minimally Constrained Model of Self-Organized Helical States in Reversed-Field Pinches
NASA Astrophysics Data System (ADS)
Dennis, G. R.; Hudson, S. R.; Terranova, D.; Franz, P.; Dewar, R. L.; Hole, M. J.
2013-08-01
We show that the self-organized single-helical-axis (SHAx) and double-axis (DAx) states in reversed field pinches can be reproduced in a minimally constrained equilibrium model using only five parameters. This is a significant reduction on previous representations of the SHAx which have required an infinite number of constraints. The DAx state, which has a nontrivial topology, has not previously been reproduced using an equilibrium model that preserves this topological structure. We show that both states are a consequence of transport barrier formation in the plasma core, in agreement with experimental results. We take the limit of zero pressure in this work, although the model is also valid for finite pressure.
One-dimensional extended Hubbard model with spin-triplet pairing ground states
NASA Astrophysics Data System (ADS)
Tanaka, Akinori
2016-10-01
We show that the one-dimensional extended Hubbard model has saturated ferromagnetic ground states with the spin-triplet electron pair condensation in a certain range of parameters. The ground state wave functions with fixed electron numbers are explicitly obtained. We also construct two ground states in which both the spin-rotation and the gauge symmetries are broken, and show that these states are transferred from one to the other by applying the edge operators. The edge operators are reduced to the Majorana fermions in a special case. These symmetry breaking ground states are shown to be stabilized by a superconducting mean field Hamiltonian which is related to the Kitaev chain with the charge-charge interaction.
A generalised 17-state vibronic-coupling Hamiltonian model for ethylene
NASA Astrophysics Data System (ADS)
Jornet-Somoza, Joaquim; Lasorne, Benjamin; Robb, Michael A.; Meyer, Hans-Dieter; Lauvergnat, David; Gatti, Fabien
2012-08-01
In a previous work [B. Lasorne, M. A. Robb, H.-D. Meyer, and F. Gatti, "The electronic excited states of ethylene with large-amplitude deformations: A dynamical symmetry group investigation," Chem. Phys. 377, 30-45 (2010), 10.1016/j.chemphys.2010.08.011; B. Lasorne, M. A. Robb, H.-D. Meyer, and F. Gatti, Chem. Phys. 382, 132 (2011) (Erratum)], 10.1016/j.chemphys.2011.01.004, we investigated the electronic structure of ethylene (ethene, C2H4) in terms of 17 dominant configurations selected at the multiconfiguration self-consistent field level of theory. These were shown to be sufficient to recover most of the static electron correlation among the first valence and Rydberg states at all geometries. We also devised a strategy to build a 17-quasidiabatic-state matrix representation of the electronic Hamiltonian for curvilinear coordinates using dynamical symmetry. Here, we present fitted surfaces in the form of a generalised vibronic-coupling Hamiltonian model for two nuclear coordinates, CC bond stretching and torsion. Dynamic electron correlation is included into the electronic structure to improve the energetics of the Rydberg states at the multireference configuration interaction level of theory. The chemical interpretation of the adiabatic states of interest does not change qualitatively, which validates our choice of underlying quasidiabatic states in the model. The absorption spectrum is calculated with quantum dynamics and partially assigned. This first two-dimensional model shows a surprisingly good agreement with the experimental spectrum.
Majority rule has transition ratio 4 on Yule trees under a 2-state symmetric model.
Mossel, Elchanan; Steel, Mike
2014-11-01
Inferring the ancestral state at the root of a phylogenetic tree from states observed at the leaves is a problem arising in evolutionary biology. The simplest technique - majority rule - estimates the root state by the most frequently occurring state at the leaves. Alternative methods - such as maximum parsimony - explicitly take the tree structure into account. Since either method can outperform the other on particular trees, it is useful to consider the accuracy of the methods on trees generated under some evolutionary null model, such as a Yule pure-birth model. In this short note, we answer a recently posed question concerning the performance of majority rule on Yule trees under a symmetric 2-state Markovian substitution model of character state change. We show that majority rule is accurate precisely when the ratio of the birth (speciation) rate of the Yule process to the substitution rate exceeds the value 4. By contrast, maximum parsimony has been shown to be accurate only when this ratio is at least 6. Our proof relies on a second moment calculation, coupling, and a novel application of a reflection principle.
Entropy, chaos, and excited-state quantum phase transitions in the Dicke model.
Lóbez, C M; Relaño, A
2016-07-01
We study nonequilibrium processes in an isolated quantum system-the Dicke model-focusing on the role played by the transition from integrability to chaos and the presence of excited-state quantum phase transitions. We show that both diagonal and entanglement entropies are abruptly increased by the onset of chaos. Also, this increase ends in both cases just after the system crosses the critical energy of the excited-state quantum phase transition. The link between entropy production, the development of chaos, and the excited-state quantum phase transition is more clear for the entanglement entropy. PMID:27575109
Multiplicity of singular synchronous states in the Kuramoto model of coupled oscillators.
Komarov, Maxim; Pikovsky, Arkady
2013-11-15
We study the Kuramoto model of globally coupled oscillators with a biharmonic coupling function. We develop an analytic self-consistency approach to find stationary synchronous states in the thermodynamic limit and demonstrate that there is a huge multiplicity of such states, which differ microscopically in the distributions of locked phases. These synchronous regimes already exist prior to the linear instability transition of the fully asynchronous state. In the presence of white Gaussian noise, the multiplicity is lifted, but the dependence of the order parameters on coupling constants remains nontrivial.
Topological Invariants of Edge States for Periodic Two-Dimensional Models
NASA Astrophysics Data System (ADS)
Avila, Julio Cesar; Schulz-Baldes, Hermann; Villegas-Blas, Carlos
2013-06-01
Transfer matrix methods and intersection theory are used to calculate the bands of edge states for a wide class of periodic two-dimensional tight-binding models including a sublattice and spin degree of freedom. This allows to define topological invariants by considering the associated Bott-Maslov indices which can be easily calculated numerically. For time-reversal symmetric systems in the symplectic universality class this leads to a {Z}_2-invariant for the edge states. It is shown that the edge state invariants are related to Chern numbers of the bulk systems and also to (spin) edge currents, in the spirit of the theory of topological insulators.
Multi-state Markov model for disability: A case of Malaysia Social Security (SOCSO)
NASA Astrophysics Data System (ADS)
Samsuddin, Shamshimah; Ismail, Noriszura
2016-06-01
Studies of SOCSO's contributor outcomes like disability are usually restricted to a single outcome. In this respect, the study has focused on the approach of multi-state Markov model for estimating the transition probabilities among SOCSO's contributor in Malaysia between states: work, temporary disability, permanent disability and death at yearly intervals on age, gender, year and disability category; ignoring duration and past disability experience which is not consider of how or when someone arrived in that category. These outcomes represent different states which depend on health status among the workers.
NASA Astrophysics Data System (ADS)
Pal, Indrani; Robertson, Andrew W.; Lall, Upmanu; Cane, Mark A.
2015-02-01
A multiscale-modeling framework for daily rainfall is considered and diagnostic results are presented for an application to the winter season in Northwest India. The daily rainfall process is considered to follow a hidden Markov model (HMM), with the hidden states assumed to be an unknown random function of slowly varying climatic modulation of the winter jet stream and moisture transport dynamics. The data used are from 14 stations over Satluj River basin in winter (December-January-February-March). The period considered is 1977/78-2005/06. The HMM identifies four discrete weather states, which are used to describe daily rainfall variability over study region. Each state was found to be associated with a distinct atmospheric circulation pattern, with the driest and drier states, State 1 and 2 respectively, characterized by a lack of synoptic wave activity. In contrast, the wetter and wettest states, States 3 and 4 respectively, are characterized by a zonally oriented wave train extending across Eurasia between 20N and 40N, identified with `western disturbances' (WD). The occurrence of State 4 is strongly conditioned by the El Nino and Indian Ocean Dipole (IOD) phenomena in winter, which is demonstrated using large-scale correlation maps based on mean sea level pressure and sea surface temperature. This suggests that there is a tendency of higher frequency of the wet days and intense WD activities in winter during El Nino and positive IOD years. These findings, derived from daily rainfall station records, help clarify the sequence of Northern Hemisphere mid-latitude storms bringing winter rainfall over Northwest India, and their association with potentially predictable low frequency modes on seasonal time scales and longer.
Diffuse phosphorus models in the United States and europe: their usages, scales, and uncertainties.
Radcliffe, D E; Freer, Jim; Schoumans, Oscar
2009-01-01
Today there are many well-established computer models that are being used at different spatial and temporal scales to describe water, sediment, and P transport from diffuse sources. In this review, we describe how diffuse P models are commonly being used in the United States and Europe, the challenge presented by different temporal and spatial scales, and the uncertainty in model predictions. In the United States, for water bodies that do not meet water quality standards, a total maximum daily load (TMDL) of the pollutant of concern must be set that will restore water quality and a plan implemented to reduce the pollutant load to meet the TMDL. Models are used to estimate the current maximum daily and annual average load, to estimate the contribution from different nonpoint sources, and to develop scenarios for achieving the TMDL target. In Europe, the EC-Water Framework Directive is the driving force to improve water quality and models are playing a similar role to that in the United States, but the models being used are not the same. European models are more likely to take into account leaching of P and the identification of critical source areas. Scaling up to the watershed scale has led to overparameterized models that cannot be used to test hypotheses regarding nonpoint sources of P or transport processes using the monitoring data that is typically available. There is a need for more parsimonious models and monitoring data that takes advantage of the technological improvements that allow nearly continuous sampling for P and sediment. Tools for measuring model uncertainty must become an integral part of models and be readily available for model users.
Sharp Contradiction for Local-Hidden-State Model in Quantum Steering.
Chen, Jing-Ling; Su, Hong-Yi; Xu, Zhen-Peng; Pati, Arun Kumar
2016-01-01
In quantum theory, no-go theorems are important as they rule out the existence of a particular physical model under consideration. For instance, the Greenberger-Horne-Zeilinger (GHZ) theorem serves as a no-go theorem for the nonexistence of local hidden variable models by presenting a full contradiction for the multipartite GHZ states. However, the elegant GHZ argument for Bell's nonlocality does not go through for bipartite Einstein-Podolsky-Rosen (EPR) state. Recent study on quantum nonlocality has shown that the more precise description of EPR's original scenario is "steering", i.e., the nonexistence of local hidden state models. Here, we present a simple GHZ-like contradiction for any bipartite pure entangled state, thus proving a no-go theorem for the nonexistence of local hidden state models in the EPR paradox. This also indicates that the very simple steering paradox presented here is indeed the closest form to the original spirit of the EPR paradox. PMID:27562658
Sharp Contradiction for Local-Hidden-State Model in Quantum Steering
NASA Astrophysics Data System (ADS)
Chen, Jing-Ling; Su, Hong-Yi; Xu, Zhen-Peng; Pati, Arun Kumar
2016-08-01
In quantum theory, no-go theorems are important as they rule out the existence of a particular physical model under consideration. For instance, the Greenberger-Horne-Zeilinger (GHZ) theorem serves as a no-go theorem for the nonexistence of local hidden variable models by presenting a full contradiction for the multipartite GHZ states. However, the elegant GHZ argument for Bell’s nonlocality does not go through for bipartite Einstein-Podolsky-Rosen (EPR) state. Recent study on quantum nonlocality has shown that the more precise description of EPR’s original scenario is “steering”, i.e., the nonexistence of local hidden state models. Here, we present a simple GHZ-like contradiction for any bipartite pure entangled state, thus proving a no-go theorem for the nonexistence of local hidden state models in the EPR paradox. This also indicates that the very simple steering paradox presented here is indeed the closest form to the original spirit of the EPR paradox.
A Model for the Transient and Steady-State Mechanical Behavior of Contracting Muscle
Julian, F. J.; Sollins, K. R.; Sollins, M. R.
1974-01-01
A model was developed which can simulate both the transient and steady-state mechanical behavior of contracting skeletal striated muscle. Thick filament cross-bridges undergo cycles of attachment to and detachment from thin filament sites. Cross-bridges can attach only while in the first of two stable states. Force is then generated by a transition to the second state after which detachment can occur. Cross-bridges are assumed to be connected to the thin filaments by an elastic element whose extension or compression influences the rate constants for attachment, detachment, and changes between states. The model was programmed for a digital computer and attempts made to match both the transient and the steady-state responses of the model to that of real muscle in two basic types of experiment: force response to sudden change in length and length response to sudden reduction of load from Po. Values for rate constants and other parameters were chosen to try to match the model's output to results from real muscles, while at the same time trying to accommodate structural and biochemical information. PMID:4836669
Ground state of the Frenkel-Kontorova model with a transverse degree of freedom
NASA Astrophysics Data System (ADS)
Braun, O. M.; Peyrard, M.
1995-05-01
We study the ground state of a generalized Frenkel-Kontorova model with a transverse degree of freedom. The model describes a lattice of atoms with a fixed concentration, interacting by long-range repulsive forces, which is submitted to a two-dimensional substrate potential periodic (sinusoidal) in one direction and symmetric (parabolic) or asymmetric (Toda-like) in the transverse direction. When the magnitude of the interatomic repulsion increases, the ground state of the model undergoes a series of bifurcations. In particular, the first bifurcation leads to a zigzag ground state and results in drastic change of system properties, including a cusp in the average elastic constant. For incommensurate cases, the bifurcation can interplay with the Aubry transition from a pinned to a sliding state. A reentrant pinned state has, for instance, been found. The nature (continuous or discontinuous) of the next bifurcations depends on the symmetry of the substrate potential in the transverse direction. Finally, we discuss briefly the applicability of the model to describe conductivity of superionic conductors, surface diffusion, and crystal growth.
Steady-State Model of Solar Wind Electrons and Implications for Kappa Distribution
NASA Astrophysics Data System (ADS)
Kim, S.; Yoon, P. H.; Choe, G. S.
2015-12-01
The solar wind electrons are made of three or four distinct components, which are core Maxwellian background, isotropic halo, and super-halo (and sometimes, highly field-aligned strahl component which can be considered as a fourth element). A recent paper [Kim et al., ApJ, 806, 32 (2015)] puts forth a steady-state model for the solar wind electrons. The halo electrons are assumed to be in dynamical steady state with the whistler fluctuations, while the super-halo electrons maintain dynamical steady-state equilibrium with the Langmuir fluctuations, known as the quasi-thermal noise. However, the model was based upon the consideration of steady-state electron particle kinetic equation. The present paper completes the analysis by considering both the steady-state particle and wave kinetic equations. It is shown that the coupled equations enjoy two exact solutions, the Maxwellian and inverse power-law velocity distribution functions (VDFs). Kim et al. (2015) had modeled both halo and super-halo electrons by kappa VDFs. Since the kappa VDF matches the Maxwellian model for low energy and an inverse power-law for high-energy tail, the fact that exact solutions represent both aspects provides the plasma physical justification for the kappa VDF.
Sharp Contradiction for Local-Hidden-State Model in Quantum Steering
Chen, Jing-Ling; Su, Hong-Yi; Xu, Zhen-Peng; Pati, Arun Kumar
2016-01-01
In quantum theory, no-go theorems are important as they rule out the existence of a particular physical model under consideration. For instance, the Greenberger-Horne-Zeilinger (GHZ) theorem serves as a no-go theorem for the nonexistence of local hidden variable models by presenting a full contradiction for the multipartite GHZ states. However, the elegant GHZ argument for Bell’s nonlocality does not go through for bipartite Einstein-Podolsky-Rosen (EPR) state. Recent study on quantum nonlocality has shown that the more precise description of EPR’s original scenario is “steering”, i.e., the nonexistence of local hidden state models. Here, we present a simple GHZ-like contradiction for any bipartite pure entangled state, thus proving a no-go theorem for the nonexistence of local hidden state models in the EPR paradox. This also indicates that the very simple steering paradox presented here is indeed the closest form to the original spirit of the EPR paradox. PMID:27562658
A mathematical model of liver metabolism: from steady state to dynamic
NASA Astrophysics Data System (ADS)
Calvetti, D.; Kuceyeski, A.; Somersalo, E.
2008-07-01
The increase in Type 2 diabetes and other metabolic disorders has led to an intense focus on the areas of research related to metabolism. Because the liver is essential in regulating metabolite concentrations that maintain life, it is especially important to have good knowledge of the functions within this organ. In silico mathematical models that can adequately describe metabolite concentrations, flux and transport rates in the liver in vivo can be a useful predictive tool. Fully dynamic models, which contain expressions for Michaelis-Menten reaction kinetics can be utilized to investigate different metabolic states, for example exercise, fed or starved state. In this paper we describe a two compartment (blood and tissue) spatially lumped liver metabolism model. First, we use Bayesian Flux Balance Analysis (BFBA) to estimate the values of flux and transport rates at steady state, which agree closely with values from the literature. These values are then used to find a set of Michaelis-Menten parameters and initial concentrations which identify a dynamic model that can be used for exploring different metabolic states. In particular, we investigate the effect of doubling the concentration of lactate entering the system via the hepatic artery and portal vein. This change in lactate concentration forces the system to a new steady state, where glucose production is increased.
Relative stability of network states in Boolean network models of gene regulation in development.
Zhou, Joseph Xu; Samal, Areejit; d'Hérouël, Aymeric Fouquier; Price, Nathan D; Huang, Sui
2016-01-01
Progress in cell type reprogramming has revived the interest in Waddington's concept of the epigenetic landscape. Recently researchers developed the quasi-potential theory to represent the Waddington's landscape. The Quasi-potential U(x), derived from interactions in the gene regulatory network (GRN) of a cell, quantifies the relative stability of network states, which determine the effort required for state transitions in a multi-stable dynamical system. However, quasi-potential landscapes, originally developed for continuous systems, are not suitable for discrete-valued networks which are important tools to study complex systems. In this paper, we provide a framework to quantify the landscape for discrete Boolean networks (BNs). We apply our framework to study pancreas cell differentiation where an ensemble of BN models is considered based on the structure of a minimal GRN for pancreas development. We impose biologically motivated structural constraints (corresponding to specific type of Boolean functions) and dynamical constraints (corresponding to stable attractor states) to limit the space of BN models for pancreas development. In addition, we enforce a novel functional constraint corresponding to the relative ordering of attractor states in BN models to restrict the space of BN models to the biological relevant class. We find that BNs with canalyzing/sign-compatible Boolean functions best capture the dynamics of pancreas cell differentiation. This framework can also determine the genes' influence on cell state transitions, and thus can facilitate the rational design of cell reprogramming protocols.
Zhou, Jian; Troyanskaya, Olga G.
2016-01-01
Interpreting the functional state of chromatin from the combinatorial binding patterns of chromatin factors, that is, the chromatin codes, is crucial for decoding the epigenetic state of the cell. Here we present a systematic map of Drosophila chromatin states derived from data-driven probabilistic modelling of dependencies between chromatin factors. Our model not only recapitulates enhancer-like chromatin states as indicated by widely used enhancer marks but also divides these states into three functionally distinct groups, of which only one specific group possesses active enhancer activity. Moreover, we discover a strong association between one specific enhancer state and RNA Polymerase II pausing, linking transcription regulatory potential and chromatin organization. We also observe that with the exception of long-intron genes, chromatin state transition positions in transcriptionally active genes align with an absolute distance to their corresponding transcription start site, regardless of gene length. Using our method, we provide a resource that helps elucidate the functional and spatial organization of the chromatin code landscape. PMID:26841971
State-space models for bio-loggers: A methodological road map
NASA Astrophysics Data System (ADS)
Jonsen, I. D.; Basson, M.; Bestley, S.; Bravington, M. V.; Patterson, T. A.; Pedersen, M. W.; Thomson, R.; Thygesen, U. H.; Wotherspoon, S. J.
2013-04-01
Ecologists have an unprecedented array of bio-logging technologies available to conduct in situ studies of horizontal and vertical movement patterns of marine animals. These tracking data provide key information about foraging, migratory, and other behaviours that can be linked with bio-physical datasets to understand physiological and ecological influences on habitat selection. In most cases, however, the behavioural context is not directly observable and therefore, must be inferred. Animal movement data are complex in structure, entailing a need for stochastic analysis methods. The recent development of state-space modelling approaches for animal movement data provides statistical rigor for inferring hidden behavioural states, relating these states to bio-physical data, and ultimately for predicting the potential impacts of climate change. Despite the widespread utility, and current popularity, of state-space models for analysis of animal tracking data, these tools are not simple and require considerable care in their use. Here we develop a methodological "road map" for ecologists by reviewing currently available state-space implementations. We discuss appropriate use of state-space methods for location and/or behavioural state estimation from different tracking data types. Finally, we outline key areas where the methodology is advancing, and where it needs further development.
Building Energy Use Modeling at the U.S. State Level Under Climate Change
NASA Astrophysics Data System (ADS)
Zhou, Y.; Eom, J.; Clarke, L.; Kyle, P.
2012-12-01
Climate change plays an important role in building energy use for heating and cooling. As global building energy use accounts for as much as about 32% of global final energy consumption in 2005, the impact of climate change on greenhouse gas emissions may also be significant. As long-term socioeconomic transformation and energy service expansion show large spatial heterogeneity, advanced understanding of climate impact on building energy use at the sub-national level will offer useful insights into regional energy system planning. In this study, we have developed a detailed building energy model with U.S. 50-state representation, embedded in an integrated assessment framework (Global Change Assessment Model). The climate change impact on heating and cooling demand is measured through estimating heating and cooling degree days (HDD/CDDs) derived from MIT Integrated Global System Model (IGSM) climate data and linking the estimates to the building energy model. Having the model calibrated against historical data at the U.S. state level, we estimated the building energy use in the 21st century at the U.S. state level and analyzed its spatial pattern. We have found that the total building energy use (heating and cooling) in U.S. states is over- or under-estimated without having climate feedback taken into account, and that the difference with and without climate feedback at the state level varies from -25% to 25% in reference scenario and -15% to 10% in climate mitigation scenario. The result not only confirms earlier finding that global warming leads to increased cooling and decreased heating energy use, it also indicates that climate change has a different impact on total building energy use at national and state level, exhibiting large spatial heterogeneity across states (Figure 1). The scale impact in building energy use modeling emphasizes the importance of developing a building energy model that represents socioeconomic development, energy service expansion, and
Lagrangian particle modeling of air pollution transport in southwestern United States
Uliasz, M.; Stocker, R.A.; Pielke, R.A.
1994-12-31
Several modeling techniques of various complexity and accuracy are applied in a numerical modeling study of regional air pollution transport being performed within the Measurement Of Haze And Visual Effect (MOHAVE) project. The goal of this study is to assess the impact of the Mohave Power Project (MPP) and other potential sources of air pollution to specific Class I areas located in the desert southwest United States including the Grand Canyon National Park. The Colorado State University team is performing the daily meteorological and dispersion simulations for a year long study using a nonhydrostatic mesoscale meteorological model; the Regional Atmospheric Modeling System (RAMS) coupled with a Lagrangian particle dispersion (LPD) model. The modeling domain covers the southwestern United States with its extremely complex terrain. Two complementary dispersion modeling techniques: a traditional source-oriented approach and receptor-oriented approach are used to calculate concentration and influence function fields, respectively. All computations are performed on two IBM RISC-6000 workstations dedicated to the project. The goal of this paper is to present our design for daily dispersion simulations with an emphasis on influence function calculations using examples from the winter and summer intensive periods of the MOHAVE project.
NASA Technical Reports Server (NTRS)
Spar, J.; Notario, J. J.; Quirk, W. J.
1978-01-01
Monthly mean global forecasts for January 1975 have been computed with the Goddard Institute for Space Studies model from four slightly different sets of initial conditions - a 'control' state and three random perturbations thereof - to simulate the effects of initial state uncertainty on forecast quality. Differences among the forecasts are examined in terms of energetics, synoptic patterns and forecast statistics. The 'noise level' of the model predictions is depicted on global maps of standard deviations of sea level pressures, 500 mb heights and 850 mb temperatures for the set of four forecasts. Initial small-scale random errors do not appear to result in any major degradation of the large-scale monthly mean forecast beyond that generated by the model itself, nor do they appear to represent the major source of large-scale forecast error.
Ferrer, Loïc; Rondeau, Virginie; Dignam, James; Pickles, Tom; Jacqmin-Gadda, Hélène; Proust-Lima, Cécile
2016-09-30
Joint modelling of longitudinal and survival data is increasingly used in clinical trials on cancer. In prostate cancer for example, these models permit to account for the link between longitudinal measures of prostate-specific antigen (PSA) and time of clinical recurrence when studying the risk of relapse. In practice, multiple types of relapse may occur successively. Distinguishing these transitions between health states would allow to evaluate, for example, how PSA trajectory and classical covariates impact the risk of dying after a distant recurrence post-radiotherapy, or to predict the risk of one specific type of clinical recurrence post-radiotherapy, from the PSA history. In this context, we present a joint model for a longitudinal process and a multi-state process, which is divided into two sub-models: a linear mixed sub-model for longitudinal data and a multi-state sub-model with proportional hazards for transition times, both linked by a function of shared random effects. Parameters of this joint multi-state model are estimated within the maximum likelihood framework using an EM algorithm coupled with a quasi-Newton algorithm in case of slow convergence. It is implemented under R, by combining and extending mstate and JM packages. The estimation program is validated by simulations and applied on pooled data from two cohorts of men with localized prostate cancer. Thanks to the classical covariates available at baseline and the repeated PSA measurements, we are able to assess the biomarker's trajectory, define the risks of transitions between health states and quantify the impact of the PSA dynamics on each transition intensity. Copyright © 2016 John Wiley & Sons, Ltd.
Stable AMOC off state in an eddy-permitting coupled climate model
NASA Astrophysics Data System (ADS)
Mecking, J. V.; Drijfhout, S. S.; Jackson, L. C.; Graham, T.
2016-10-01
Shifts between on and off states of the Atlantic Meridional Overturning Circulation (AMOC) have been associated with past abrupt climate change, supported by the bistability of the AMOC found in many older, coarser resolution, ocean and climate models. However, as coupled climate models evolved in complexity a stable AMOC off state no longer seemed supported. Here we show that a current-generation, eddy-permitting climate model has an AMOC off state that remains stable for the 450-year duration of the model integration. Ocean eddies modify the overall freshwater balance, allowing for stronger northward salt transport by the AMOC compared with previous, non eddy-permitting models. As a result, the salinification of the subtropical North Atlantic, due to a southward shift of the intertropical rain belt, is counteracted by the reduced salt transport of the collapsed AMOC. The reduced salinification of the subtropical North Atlantic allows for an anomalous northward freshwater transport into the subpolar North Atlantic dominated by the gyre component. Combining the anomalous northward freshwater transport with the freshening due to reduced evaporation in this region helps stabilise the AMOC off state.
Stable AMOC off state in an eddy-permitting coupled climate model
NASA Astrophysics Data System (ADS)
Mecking, J. V.; Drijfhout, S. S.; Jackson, L. C.; Graham, T.
2016-01-01
Shifts between on and off states of the Atlantic Meridional Overturning Circulation (AMOC) have been associated with past abrupt climate change, supported by the bistability of the AMOC found in many older, coarser resolution, ocean and climate models. However, as coupled climate models evolved in complexity a stable AMOC off state no longer seemed supported. Here we show that a current-generation, eddy-permitting climate model has an AMOC off state that remains stable for the 450-year duration of the model integration. Ocean eddies modify the overall freshwater balance, allowing for stronger northward salt transport by the AMOC compared with previous, non eddy-permitting models. As a result, the salinification of the subtropical North Atlantic, due to a southward shift of the intertropical rain belt, is counteracted by the reduced salt transport of the collapsed AMOC. The reduced salinification of the subtropical North Atlantic allows for an anomalous northward freshwater transport into the subpolar North Atlantic dominated by the gyre component. Combining the anomalous northward freshwater transport with the freshening due to reduced evaporation in this region helps stabilise the AMOC off state.
Models for solid-state transport: messenger RNA movement from nucleus to cytoplasm.
Agutter, P S
1994-09-01
This paper explores the idea that mRNAs are transported between their transcription and processing sites in the nucleus, and their translation and degradation sites in the cytoplasm, by a 'solid-state' process. The underlying assumption is that negligible quantities of mRNA and of mRNA precursors are in solution in vivo. Therefore, mRNA transport cannot be considered as movement in the aqueous phase of the cell. The main lines of experimental evidence supporting this 'solid-state' concept are summarized and related controversies are outlined. Three possible models for a solid-state transport mechanism are discussed: a direct transfer model, with receptors organized analogously to the components of a multienzyme complex; a motor-driven model, analogous to synaptic vesicle transport in axons; and an assembly-driven model which assumes net movement along a fibril resulting from differential activities at the poles. Qualitative evaluation indicates that each of these models has characteristic advantages and disadvantages. The possibility that other nucleocytoplasmic transport processes might operate by solid-state mechanisms is briefly discussed.
An improved state-parameter analysis of ecosystem models using data assimilation
Chen, M.; Liu, S.; Tieszen, L.L.; Hollinger, D.Y.
2008-01-01
Much of the effort spent in developing data assimilation methods for carbon dynamics analysis has focused on estimating optimal values for either model parameters or state variables. The main weakness of estimating parameter values alone (i.e., without considering state variables) is that all errors from input, output, and model structure are attributed to model parameter uncertainties. On the other hand, the accuracy of estimating state variables may be lowered if the temporal evolution of parameter values is not incorporated. This research develops a smoothed ensemble Kalman filter (SEnKF) by combining ensemble Kalman filter with kernel smoothing technique. SEnKF has following characteristics: (1) to estimate simultaneously the model states and parameters through concatenating unknown parameters and state variables into a joint state vector; (2) to mitigate dramatic, sudden changes of parameter values in parameter sampling and parameter evolution process, and control narrowing of parameter variance which results in filter divergence through adjusting smoothing factor in kernel smoothing algorithm; (3) to assimilate recursively data into the model and thus detect possible time variation of parameters; and (4) to address properly various sources of uncertainties stemming from input, output and parameter uncertainties. The SEnKF is tested by assimilating observed fluxes of carbon dioxide and environmental driving factor data from an AmeriFlux forest station located near Howland, Maine, USA, into a partition eddy flux model. Our analysis demonstrates that model parameters, such as light use efficiency, respiration coefficients, minimum and optimum temperatures for photosynthetic activity, and others, are highly constrained by eddy flux data at daily-to-seasonal time scales. The SEnKF stabilizes parameter values quickly regardless of the initial values of the parameters. Potential ecosystem light use efficiency demonstrates a strong seasonality. Results show that the
Ruess, Jakob
2015-12-28
Many stochastic models of biochemical reaction networks contain some chemical species for which the number of molecules that are present in the system can only be finite (for instance due to conservation laws), but also other species that can be present in arbitrarily large amounts. The prime example of such networks are models of gene expression, which typically contain a small and finite number of possible states for the promoter but an infinite number of possible states for the amount of mRNA and protein. One of the main approaches to analyze such models is through the use of equations for the time evolution of moments of the chemical species. Recently, a new approach based on conditional moments of the species with infinite state space given all the different possible states of the finite species has been proposed. It was argued that this approach allows one to capture more details about the full underlying probability distribution with a smaller number of equations. Here, I show that the result that less moments provide more information can only stem from an unnecessarily complicated description of the system in the classical formulation. The foundation of this argument will be the derivation of moment equations that describe the complete probability distribution over the finite state space but only low-order moments over the infinite state space. I will show that the number of equations that is needed is always less than what was previously claimed and always less than the number of conditional moment equations up to the same order. To support these arguments, a symbolic algorithm is provided that can be used to derive minimal systems of unconditional moment equations for models with partially finite state space.
Analytical modeling of wetting states and simulation of drop shape on microstructured surfaces
NASA Astrophysics Data System (ADS)
Alen, Saif Khan; Farhat, Nazia; Rahman, Md. Ashiqur
2016-07-01
Understanding the relationship between surface roughness and wetting state is essential in designing microstructured surfaces with tunable wetting properties. In this work, an analytical model for predicting the wetting state on microgroove geometry is developed and applied to intrinsically hydrophilic brass surfaces with a wide range of groove geometry. To enhance the scope and applicability of the developed model, it is implemented on a number of other aluminum microgrooved surfaces. Before applying any surface minimization algorithm to obtain equilibrium droplet shape, the stable wetting state is determined by comparing the total surface energy of the liquid droplet in Cassie and Wenzel wetting state. It is found that hybridization of the microgrooved surface (PDMS coating on the groove base) reduces the critical microgroove dimensions for exhibiting a Cassie wetting state. The unusual spreading of water droplets, observed experimentally on certain microgrooved surfaces, is predicted more accurately when slightly inclined pillars (with a 7° inclination from vertical) instead of vertical wall are assumed. These results corroborate our earlier claim that the shape and the slope of the pillar edge are responsible for the unusual spreading exhibited by certain surfaces. Moreover, implementation of the experimentally obtained values of droplet elongation ratio in the numerical model further enhances the accuracy of the obtained results. The present mathematical model offers an excellent tool for predicting the wetting state of the rough hydrophilic surface using its roughness geometry, and the numerical approach of implementing inclined pillar and droplet elongation ratio can improve the accuracy of drop shape simulation while predicting the wetting states accurately.
NASA Astrophysics Data System (ADS)
Ruess, Jakob
2015-12-01
Many stochastic models of biochemical reaction networks contain some chemical species for which the number of molecules that are present in the system can only be finite (for instance due to conservation laws), but also other species that can be present in arbitrarily large amounts. The prime example of such networks are models of gene expression, which typically contain a small and finite number of possible states for the promoter but an infinite number of possible states for the amount of mRNA and protein. One of the main approaches to analyze such models is through the use of equations for the time evolution of moments of the chemical species. Recently, a new approach based on conditional moments of the species with infinite state space given all the different possible states of the finite species has been proposed. It was argued that this approach allows one to capture more details about the full underlying probability distribution with a smaller number of equations. Here, I show that the result that less moments provide more information can only stem from an unnecessarily complicated description of the system in the classical formulation. The foundation of this argument will be the derivation of moment equations that describe the complete probability distribution over the finite state space but only low-order moments over the infinite state space. I will show that the number of equations that is needed is always less than what was previously claimed and always less than the number of conditional moment equations up to the same order. To support these arguments, a symbolic algorithm is provided that can be used to derive minimal systems of unconditional moment equations for models with partially finite state space.
Ruess, Jakob
2015-12-28
Many stochastic models of biochemical reaction networks contain some chemical species for which the number of molecules that are present in the system can only be finite (for instance due to conservation laws), but also other species that can be present in arbitrarily large amounts. The prime example of such networks are models of gene expression, which typically contain a small and finite number of possible states for the promoter but an infinite number of possible states for the amount of mRNA and protein. One of the main approaches to analyze such models is through the use of equations for the time evolution of moments of the chemical species. Recently, a new approach based on conditional moments of the species with infinite state space given all the different possible states of the finite species has been proposed. It was argued that this approach allows one to capture more details about the full underlying probability distribution with a smaller number of equations. Here, I show that the result that less moments provide more information can only stem from an unnecessarily complicated description of the system in the classical formulation. The foundation of this argument will be the derivation of moment equations that describe the complete probability distribution over the finite state space but only low-order moments over the infinite state space. I will show that the number of equations that is needed is always less than what was previously claimed and always less than the number of conditional moment equations up to the same order. To support these arguments, a symbolic algorithm is provided that can be used to derive minimal systems of unconditional moment equations for models with partially finite state space. PMID:26723647
Zheng, Zhenzhen; Chou, Ching-Shan; Yi, Tau-Mu; Nie, Qing
2011-10-01
Cell polarization, in which substances previously uniformly distributed become asymmetric due to external or/and internal stimulation, is a fundamental process underlying cell mobility, cell division, and other polarized functions. The yeast cell S. cerevisiae has been a model system to study cell polarization. During mating, yeast cells sense shallow external spatial gradients and respond by creating steeper internal gradients of protein aligned with the external cue. The complex spatial dynamics during yeast mating polarization consists of positive feedback, degradation, global negative feedback control, and cooperative effects in protein synthesis. Understanding such complex regulations and interactions is critical to studying many important characteristics in cell polarization including signal amplification, tracking dynamic signals, and potential trade-off between achieving both objectives in a robust fashion. In this paper, we study some of these questions by analyzing several models with different spatial complexity: two compartments, three compartments, and continuum in space. The step-wise approach allows detailed characterization of properties of the steady state of the system, providing more insights for biological regulations during cell polarization. For cases without membrane diffusion, our study reveals that increasing the number of spatial compartments results in an increase in the number of steady-state solutions, in particular, the number of stable steady-state solutions, with the continuum models possessing infinitely many steady-state solutions. Through both analysis and simulations, we find that stronger positive feedback, reduced diffusion, and a shallower ligand gradient all result in more steady-state solutions, although most of these are not optimally aligned with the gradient. We explore in the different settings the relationship between the number of steady-state solutions and the extent and accuracy of the polarization. Taken together
NASA Astrophysics Data System (ADS)
D'Amato, Anthony M.
Input reconstruction is the process of using the output of a system to estimate its input. In some cases, input reconstruction can be accomplished by determining the output of the inverse of a model of the system whose input is the output of the original system. Inversion, however, requires an exact and fully known analytical model, and is limited by instabilities arising from nonminimum-phase zeros. The main contribution of this work is a novel technique for input reconstruction that does not require model inversion. This technique is based on a retrospective cost, which requires a limited number of Markov parameters. Retrospective cost input reconstruction (RCIR) does not require knowledge of nonminimum-phase zero locations or an analytical model of the system. RCIR provides a technique that can be used for model refinement, state estimation, and adaptive control. In the model refinement application, data are used to refine or improve a model of a system. It is assumed that the difference between the model output and the data is due to an unmodeled subsystem whose interconnection with the modeled system is inaccessible, that is, the interconnection signals cannot be measured and thus standard system identification techniques cannot be used. Using input reconstruction, these inaccessible signals can be estimated, and the inaccessible subsystem can be fitted. We demonstrate input reconstruction in a model refinement framework by identifying unknown physics in a space weather model and by estimating an unknown film growth in a lithium ion battery. The same technique can be used to obtain estimates of states that cannot be directly measured. Adaptive control can be formulated as a model-refinement problem, where the unknown subsystem is the idealized controller that minimizes a measured performance variable. Minimal modeling input reconstruction for adaptive control is useful for applications where modeling information may be difficult to obtain. We demonstrate
Hurricane Loss Estimation Models: Opportunities for Improving the State of the Art.
NASA Astrophysics Data System (ADS)
Watson, Charles C., Jr.; Johnson, Mark E.
2004-11-01
The results of hurricane loss models are used regularly for multibillion dollar decisions in the insurance and financial services industries. These models are proprietary, and this “black box” nature hinders analysis. The proprietary models produce a wide range of results, often producing loss costs that differ by a ratio of three to one or more. In a study for the state of North Carolina, 324 combinations of loss models were analyzed, based on a combination of nine wind models, four surface friction models, and nine damage models drawn from the published literature in insurance, engineering, and meteorology. These combinations were tested against reported losses from Hurricanes Hugo and Andrew as reported by a major insurance company, as well as storm total losses for additional storms. Annual loss costs were then computed using these 324 combinations of models for both North Carolina and Florida, and compared with publicly available proprietary model results in Florida. The wide range of resulting loss costs for open, scientifically defensible models that perform well against observed losses mirrors the wide range of loss costs computed by the proprietary models currently in use. This outcome may be discouraging for governmental and corporate decision makers relying on this data for policy and investment guidance (due to the high variability across model results), but it also provides guidance for the efforts of future investigations to improve loss models. Although hurricane loss models are true multidisciplinary efforts, involving meteorology, engineering, statistics, and actuarial sciences, the field of meteorology offers the most promising opportunities for improvement of the state of the art.
Ising spin network states for loop quantum gravity: a toy model for phase transitions
NASA Astrophysics Data System (ADS)
Feller, Alexandre; Livine, Etera R.
2016-03-01
Non-perturbative approaches to quantum gravity call for a deep understanding of the emergence of geometry and locality from the quantum state of the gravitational field. Without background geometry, the notion of distance should emerge entirely from the correlations between the gravity fluctuations. In the context of loop quantum gravity, quantum states of geometry are defined as spin networks. These are graphs decorated with spin and intertwiners, which represent quantized excitations of areas and volumes of the space geometry. Here, we develop the condensed-matter point of view on extracting the physical and geometrical information from spin network states: we introduce new Ising spin network states, both in 2d on a square lattice and in 3d on a hexagonal lattice, whose correlations map onto the usual Ising model in statistical physics. We construct these states from the basic holonomy operators of loop gravity and derive a set of local Hamiltonian constraints that entirely characterize our states. We discuss their phase diagram and show how the distance can be reconstructed from the correlations in the various phases. Finally, we propose generalizations of these Ising states, which open the perspective to study the coarse-graining and dynamics of spin network states using well-known condensed-matter techniques and results.
NASA Astrophysics Data System (ADS)
Famiglietti, James; Basilio, Ralph; Trangsrud, Amy; Andreadis, Kostas; Cricthon, Dan; David, Cedric; Farr, Thomas; Malhotra, Shan; Neff, Kirstin; Reager, John
2016-04-01
Hydrological remote sensing has advanced significantly over the last decade, and will continue to grow with number of recent and near-future launched. Arguably, a platform for synthesizing remote observations is an important step towards improved modeling, understanding and prediction of terrestrial hydrology. In this presentation we describe the new NASA Western States Water Mission, a high-resolution, catchment-based modeling and data assimilation platform implemented for the western United States. Model structure will be described, as well as early results that include assimilation of satellite snow observations. A key feature of model development has been its treatment as a 'flight project' which enables leveraging of important NASA systems engineering and project management expertise.
A diabatic state model for double proton transfer in hydrogen bonded complexes
McKenzie, Ross H.
2014-09-14
Four diabatic states are used to construct a simple model for double proton transfer in hydrogen bonded complexes. Key parameters in the model are the proton donor-acceptor separation R and the ratio, D{sub 1}/D{sub 2}, between the proton affinity of a donor with one and two protons. Depending on the values of these two parameters the model describes four qualitatively different ground state potential energy surfaces, having zero, one, two, or four saddle points. Only for the latter are there four stable tautomers. In the limit D{sub 2} = D{sub 1} the model reduces to two decoupled hydrogen bonds. As R decreases a transition can occur from a synchronous concerted to an asynchronous concerted to a sequential mechanism for double proton transfer.
A two-state Markov mixture model for a time series of epileptic seizure counts.
Albert, P S
1991-12-01
This paper discusses a model for a time series of epileptic seizure counts in which the mean of a Poisson distribution changes according to an underlying two-state Markov chain. The EM algorithm (Dempster, Laird, and Rubin, 1977, Journal of the Royal Statistical Society, Series B 39, 1-38) is used to compute maximum likelihood estimators for the parameters of this two-state mixture model and extensions are made allowing for nonstationarity. The model is illustrated using daily seizure counts for patients with intractable epilepsy and results are compared with a simple Poisson distribution and Poisson regressions. Some simulation results are also presented to demonstrate the feasibility of this model. PMID:1786324
Robust quasi-LPV control based on neural state-space models.
Bendtsen, J D; Trangbaek, K
2002-01-01
We derive a synthesis result for robust linear parameter varying (LPV) output feedback controllers for nonlinear systems modeled by neural state-space models. This result is achieved by writing the neural state-space model on a linear fractional transformation (LFT) form in a nonconservative way, separating the system description into a linear part and a nonlinear part. Linear parameter-varying control synthesis methods are then applied to design a nonlinear control law for this system. Since the model is assumed to have been identified from input-output measurement data only, it must be expected that there is some uncertainty on the identified nonlinearities. The control law is therefore made robust to noise perturbations. After formulating the controller synthesis as a set of linear matrix inequalities (LMIs) with added constraints, some implementation issues are addressed and a simulation example is presented.
A harmonic transition state theory model for defect initiation in crystals
NASA Astrophysics Data System (ADS)
Delph, T. J.; Cao, P.; Park, H. S.; Zimmerman, J. A.
2013-03-01
We outline here a model for the initiation of defects in crystals based upon harmonic transition state theory (hTST). This model combines a previously developed model for zero-temperature defect initiation with a multi-dimensional hTST model that is capable of accurately predicting the effects of temperature and loading rate upon defect initiation. The model has several features that set it apart from previous efforts along these lines, most notably a straightforward method of determining the energy barrier between adjacent equilibrium states that does not depend upon a priori information concerning the nature of the defect. We apply the model to two examples, triaxial stretching of a perfect fcc crystal and nanoindentation of a gold substrate. Very good agreement is found between the predictions of the model and independent molecular dynamics (MD) simulations. Among other things, the model predicts a strong dependence of the defect initiation behavior upon the loading parameter. A very attractive feature of this model is that it is valid for arbitrarily slow loading rates, in particular loading rates achievable in the laboratory, and suffers from none of the limitations in this regard inherent in MD simulations.
ERIC Educational Resources Information Center
Cheyne, J. Allan; Solman, Grayden J. F.; Carriere, Jonathan S. A.; Smilek, Daniel
2009-01-01
We present arguments and evidence for a three-state attentional model of task engagement/disengagement. The model postulates three states of mind-wandering: occurrent task inattention, generic task inattention, and response disengagement. We hypothesize that all three states are both causes and consequences of task performance outcomes and apply…
An equivalent layer magnetization model for the United States derived from MAGSAT data
NASA Technical Reports Server (NTRS)
Mayhew, M. A.; Galliher, S. C. (Principal Investigator)
1982-01-01
Long wavelength anomalies in the total magnetic field measured field measured by MAGSAT over the United States and adjacent areas are inverted to an equivalent layer crustal magnetization distribution. The model is based on an equal area dipole grid at the Earth's surface. Model resolution having physical significance, is about 220 km for MAGSAT data in the elevation range 300-500 km. The magnetization contours correlate well with large-scale tectonic provinces.
ERIC Educational Resources Information Center
Curry, Denis J.; Fischer, Norman M.
The trend toward greater state regulation of public higher education is discussed, along with alternative structures or models for state financing of public institutions. The situation in Washington State is briefly described as an illustration. It is proposed that interests of the state, college, and student can be enhanced by allowing colleges…
On the Finiteness of Collisions and Phase-Locked States for the Kuramoto Model
NASA Astrophysics Data System (ADS)
Ha, Seung-Yeal; Kim, Hwa Kil; Ryoo, Sang Woo
2016-06-01
Synchronization phenomenon is ubiquitous in our complex systems, and many phenomenological models have been proposed and studied analytically and numerically. Among them, the Kuramoto model serves as a prototype model for the phase synchronization of weakly coupled oscillators. In this paper, we study the finiteness of collisions (crossings) among Kuramoto oscillators in the relaxation process toward the phase-locked states and the total number of phase-locked states with positive (Kuramoto) order parameters. For identical oscillators, it is well known that collisions between distinct oscillators cannot occur in finite-time, and we show that there are only a finite number of phase-locked states with positive order parameters. However, for non-identical oscillators, oscillators with different natural frequencies can cross each other in their relaxation process, and estimating the total number of phase-locked states is a nontrivial matter. We show that, for the non-identical case, asymptotic phase-locking is equivalent to the finiteness of collisions, and the total number of phase-locked states with positive order parameters is bounded above by 2^N, where N is the number of oscillators.
NASA Astrophysics Data System (ADS)
Khan, Irfan; Costeux, Stephane; Adrian, David; Cristancho, Diego
2013-11-01
Due to environmental regulations carbon-dioxide (CO2) is increasingly being used to replace traditional blowing agents in thermoplastic foams. CO2 is dissolved in the polymer matrix under supercritical conditions. In order to predict the effect of process parameters on foam properties using numerical modeling, the P-V-T relationship of the blowing agents should accurately be represented at the supercritical state. Previous studies in the area of foam modeling have all used ideal gas equation of state to predict the behavior of the blowing agent. In this work the Peng-Robinson equation of state is being used to model the blowing agent during its diffusion into the growing bubble. The model is based on the popular ``Influence Volume Approach,'' which assumes a growing boundary layer with depleted blowing agent surrounds each bubble. Classical nucleation theory is used to predict the rate of nucleation of bubbles. By solving the mass balance, momentum balance and species conservation equations for each bubble, the model is capable of predicting average bubble size, bubble size distribution and bulk porosity. The effect of the improved model on the bubble growth and foam properties are discussed.
NASA Astrophysics Data System (ADS)
Cara, Javier
2016-05-01
Modal parameters comprise natural frequencies, damping ratios, modal vectors and modal masses. In a theoretic framework, these parameters are the basis for the solution of vibration problems using the theory of modal superposition. In practice, they can be computed from input-output vibration data: the usual procedure is to estimate a mathematical model from the data and then to compute the modal parameters from the estimated model. The most popular models for input-output data are based on the frequency response function, but in recent years the state space model in the time domain has become popular among researchers and practitioners of modal analysis with experimental data. In this work, the equations to compute the modal parameters from the state space model when input and output data are available (like in combined experimental-operational modal analysis) are derived in detail using invariants of the state space model: the equations needed to compute natural frequencies, damping ratios and modal vectors are well known in the operational modal analysis framework, but the equation needed to compute the modal masses has not generated much interest in technical literature. These equations are applied to both a numerical simulation and an experimental study in the last part of the work.
Steady-state and dynamic models for particle engulfment during solidification
NASA Astrophysics Data System (ADS)
Tao, Yutao; Yeckel, Andrew; Derby, Jeffrey J.
2016-06-01
Steady-state and dynamic models are developed to study the physical mechanisms that determine the pushing or engulfment of a solid particle at a moving solid-liquid interface. The mathematical model formulation rigorously accounts for energy and momentum conservation, while faithfully representing the interfacial phenomena affecting solidification phase change and particle motion. A numerical solution approach is developed using the Galerkin finite element method and elliptic mesh generation in an arbitrary Lagrangian-Eulerian implementation, thus allowing for a rigorous representation of forces and dynamics previously inaccessible by approaches using analytical approximations. We demonstrate that this model accurately computes the solidification interface shape while simultaneously resolving thin fluid layers around the particle that arise from premelting during particle engulfment. We reinterpret the significance of premelting via the definition an unambiguous critical velocity for engulfment from steady-state analysis and bifurcation theory. We also explore the complicated transient behaviors that underlie the steady states of this system and posit the significance of dynamical behavior on engulfment events for many systems. We critically examine the onset of engulfment by comparing our computational predictions to those obtained using the analytical model of Rempel and Worster [29]. We assert that, while the accurate calculation of van der Waals repulsive forces remains an open issue, the computational model developed here provides a clear benefit over prior models for computing particle drag forces and other phenomena needed for the faithful simulation of particle engulfment.
A new method of modeling and state of charge estimation of the battery
NASA Astrophysics Data System (ADS)
Liu, Congzhi; Liu, Weiqun; Wang, Lingyan; Hu, Guangdi; Ma, Luping; Ren, Bingyu
2016-07-01
Accurately estimating the State of Charge (SOC) of the battery is the basis of Battery Management System (BMS). This paper has introduced a new modeling and state estimation method for the lithium battery system, which utilizes the fractional order theories. Firstly, a fractional order model based on the PNGV (Partnership for a New Generation of Vehicle) model is proposed after analyzing the impedance characteristics of the lithium battery and compared with the integer order model. With the observability of the discrete non-linear model of the battery confirmed, the method of the state observer based on the extended fractional Kalman filter (EFKF) and the least square identification method of battery parameters are studied. Then, it has been applied successfully to estimate the battery SOC using the measured battery current and voltage. Finally, a standard HPPC (Hybrid Pulse Power Characteristic) test is used for parameter identification and several experimental validations are investigated on a ternary manganese-nickel-cobalt lithium battery pack with a nominal capacity of 24 Ah which consists of ten Sony commercial cells (US18650GR G7) in parallels. The results demonstrate the effectiveness of the fractional order model and the estimation method.
Bounds, Toni Herring; Bumpus, Jill L; Behringer, Bruce A
2011-07-01
East Tennessee State University (ETSU) was awarded a grant through an interagency agreement between the Centers for Disease Control and Prevention and the Appalachian Regional Commission to promote cancer control activities between state comprehensive cancer control (CCC) coalitions and local Appalachian communities. We invited representatives from CCC coalitions and Appalachian communities to a forum to develop a plan of action. The attendees recommended a minigrant model that uses a request for proposals (RFP) strategy to encourage CCC coalitions and Appalachian communities to collaboratively conduct forums and roundtables locally. They set criteria to guide the development of the RFPs and the agendas for the roundtables and forums that ensured new communication and collaboration between the CCC coalitions and the Appalachian communities. We established the roundtable agenda to focus on the presentation and discussion of state and local Appalachian community cancer risk, incidence, and death rates and introduction of state cancer plans. The forums had a more extensive agenda to present cancer data, describe state cancer plans, and describe successful cancer control programs in local Appalachian communities. This article describes the ETSU minigrant model that supports forums and roundtables and reports how this strategy improves cooperative partnerships between CCC coalitions and Appalachian communities in the local implementation of state cancer plans in Appalachia.
NASA Astrophysics Data System (ADS)
Bhatti, Sohail Masood; Khan, Muhammad Salman; Wuth, Jorge; Huenupan, Fernando; Curilem, Millaray; Franco, Luis; Yoma, Nestor Becerra
2016-09-01
In this paper we propose an automatic volcano event detection system based on Hidden Markov Model (HMM) with state and event duration models. Since different volcanic events have different durations, therefore the state and whole event durations learnt from the training data are enforced on the corresponding state and event duration models within the HMM. Seismic signals from the Llaima volcano are used to train the system. Two types of events are employed in this study, Long Period (LP) and Volcano-Tectonic (VT). Experiments show that the standard HMMs can detect the volcano events with high accuracy but generates false positives. The results presented in this paper show that the incorporation of duration modeling can lead to reductions in false positive rate in event detection as high as 31% with a true positive accuracy equal to 94%. Further evaluation of the false positives indicate that the false alarms generated by the system were mostly potential events based on the signal-to-noise ratio criteria recommended by a volcano expert.
Identifying an appropriate measurement modeling approach for the Mini-Mental State Examination.
Rubright, Jonathan D; Nandakumar, Ratna; Karlawish, Jason
2016-02-01
The Mini-Mental State Examination (MMSE) is a 30-item, dichotomously scored test of general cognition. A number of benefits could be gained by modeling the MMSE in an item response theory (IRT) framework, as opposed to the currently used classical additive approach. However, the test, which is built from groups of items related to separate cognitive subdomains, may violate a key assumption of IRT: local item independence. This study aimed to identify the most appropriate measurement model for the MMSE: a unidimensional IRT model, a testlet response theory model, or a bifactor model. Local dependence analysis using nationally representative data showed a meaningful violation of the local item independence assumption, indicating multidimensionality. In addition, the testlet and bifactor models displayed superior fit indices over a unidimensional IRT model. Statistical comparisons showed that the bifactor model fit MMSE respondent data significantly better than the other models considered. These results suggest that application of a traditional unidimensional IRT model is inappropriate in this context. Instead, a bifactor model is suggested for future modeling of MMSE data as it more accurately represents the multidimensional nature of the scale. (PsycINFO Database Record
NASA Astrophysics Data System (ADS)
Ramesh, N.; Cane, M. A.; Seager, R.
2014-12-01
The tropical Pacific Ocean has persistently cool sea surface temperature (SST) anomalies that last several years to a decade, with either no El Niño events or very few weak El Niño events. These have been shown to cause large-scale droughts in the extratropics[i], including the major North American droughts such as the 1930s Dust Bowl, and may also be responsible for modulating the global mean surface temperature[ii]. Here we show that two models with different levels of complexity - the Zebiak-Cane model and the Geophysical Fluid Dynamics Laboratory Coupled Model version 2.1 - are able to produce such periods in a realistic manner. We then test the predictability of these periods in the Zebiak-Cane model using an ensemble of experiments with perturbed initial states. Our results show that the cool mean state is modestly predictable, while the lack of El Niño events during these cool periods is not. These results have implications for our understanding of the origins of such persistent cool states and the possibility of improving predictions of large-scale droughts. Further, we apply this method of using an ensemble of model simulations with perturbed initial states to make retrospective forecasts and to forecast the mean state of the tropical Pacific Ocean for the upcoming decade. Our results suggest, albeit with low confidence, that the current cool mean state will persist. This could imply the continuation of the drier than normal conditions that have, in general, afflicted southwest North America since the 1997/98 El Niño, as well as the current pause in global warming. [i] C. Herweijer and R. Seager, "The global footprint of persistent extra-tropical drought in the instrumental era," International Journal of Climatology, vol. 28, pp. 1761-1774, 2008. [ii] G. A. Meehl, J. M. Arblaster, J. T. Fasullo, A. Hu and K. E. Trenberth, "Model-based evidence of deep-ocean heat uptake during surface-temperature hiatus periods," Nature Climate Change, vol. 1, pp. 360
A two-state hysteresis model from high-dimensional friction.
Biswas, Saurabh; Chatterjee, Anindya
2015-07-01
In prior work (Biswas & Chatterjee 2014 Proc. R. Soc. A 470, 20130817 (doi:10.1098/rspa.2013.0817)), we developed a six-state hysteresis model from a high-dimensional frictional system. Here, we use a more intuitively appealing frictional system that resembles one studied earlier by Iwan. The basis functions now have simple analytical description. The number of states required decreases further, from six to the theoretical minimum of two. The number of fitted parameters is reduced by an order of magnitude, to just six. An explicit and faster numerical solution method is developed. Parameter fitting to match different specified hysteresis loops is demonstrated. In summary, a new two-state model of hysteresis is presented that is ready for practical implementation. Essential Matlab code is provided. PMID:26587279
NASA Astrophysics Data System (ADS)
Liu, Guang-Hua; Tian, Guang-Shan
2012-08-01
The matrix product state (MPS) is utilized to investigate the ground state properties and quantum phase transitions (QPTs) of the dimerized antiferromagnetic Heisenberg (DAH) model. The ground state MPS wavefunctions determined by the infinite time-evolving block decimation (iTEBD) algorithm are shown to be very efficient descriptions of DAH model. In the thermodynamic limit, the quantum entanglement, the bond energy, and the nearest-neighbor correlations are calculated. It is revealed that the singular behavior of the bipartite entanglement can detect the QPTs directly. The critical point Jc2 = 1.0 is determined evidently, and the quantum phase transition is argued to belong to the second-order category. At the critical point, logarithmic divergent character of the block entanglement is observed, and the system can be described by a free bosonic field theory.
Widths of K¯-nuclear deeply bound states in a dynamical model
NASA Astrophysics Data System (ADS)
Mareš, J.; Friedman, E.; Gal, A.
2005-01-01
The relativistic mean field (RMF) model is applied to a system of nucleons and a Kbar meson, interacting via scalar and vector boson fields. The model incorporates the standard RMF phenomenology for bound nucleons and, for the Kbar meson, it relates to low-energy Kbar N and K- atom phenomenology. Deeply bound Kbar nuclear states are generated dynamically across the periodic table and are exhibited for 12C and 16O over a wide range of binding energies. Substantial polarization of the core nucleus is found for these light nuclei. Absorption modes are also included dynamically, considering explicitly both the resulting compressed nuclear density and the reduced phase space for Kbar absorption from deeply bound states. The behavior of the calculated width as function of the Kbar binding energy is studied in order to explore limits on the possible existence of narrow Kbar nuclear states.
A two-state hysteresis model from high-dimensional friction.
Biswas, Saurabh; Chatterjee, Anindya
2015-07-01
In prior work (Biswas & Chatterjee 2014 Proc. R. Soc. A 470, 20130817 (doi:10.1098/rspa.2013.0817)), we developed a six-state hysteresis model from a high-dimensional frictional system. Here, we use a more intuitively appealing frictional system that resembles one studied earlier by Iwan. The basis functions now have simple analytical description. The number of states required decreases further, from six to the theoretical minimum of two. The number of fitted parameters is reduced by an order of magnitude, to just six. An explicit and faster numerical solution method is developed. Parameter fitting to match different specified hysteresis loops is demonstrated. In summary, a new two-state model of hysteresis is presented that is ready for practical implementation. Essential Matlab code is provided.
Vortex dynamics in a three-state model under cyclic dominance.
Szabó, G; Santos, M A; Mendes, J F
1999-10-01
The evolution of domain structure is investigated in a two-dimensional voter model with three states under cyclic dominance. The study focus on the dynamics of vortices, defined by the points where the three states (domains) meet. We can distinguish vortices and antivortices which walk randomly and annihilate each other. The domain wall motion can create vortex-antivortex pairs at a rate that is increased by the spiral formation due to cyclic dominance. This mechanism is contrasted with a branching annihilating random walk (BARW) in a particle-antiparticle system with density-dependent pair creation rate. Numerical estimates for the critical indices of the vortex density [beta=0.29(4)] and of its fluctuation [gamma=0.34(6)] improve an earlier Monte Carlo study [K. Tainaka and Y. Itoh, Europhys. Lett. 15, 399 (1991)] of the three-state cyclic model in two dimensions.
String states, loops and effective actions in noncommutative field theory and matrix models
NASA Astrophysics Data System (ADS)
Steinacker, Harold C.
2016-09-01
Refining previous work by Iso, Kawai and Kitazawa, we discuss bi-local string states as a tool for loop computations in noncommutative field theory and matrix models. Defined in terms of coherent states, they exhibit the stringy features of noncommutative field theory. This leads to a closed form for the 1-loop effective action in position space, capturing the long-range non-local UV/IR mixing for scalar fields. The formalism applies to generic fuzzy spaces. The non-locality is tamed in the maximally supersymmetric IKKT or IIB model, where it gives rise to supergravity. The linearized supergravity interactions are obtained directly in position space at one loop using string states on generic noncommutative branes.
Vortex dynamics in a three-state model under cyclic dominance.
Szabó, G; Santos, M A; Mendes, J F
1999-10-01
The evolution of domain structure is investigated in a two-dimensional voter model with three states under cyclic dominance. The study focus on the dynamics of vortices, defined by the points where the three states (domains) meet. We can distinguish vortices and antivortices which walk randomly and annihilate each other. The domain wall motion can create vortex-antivortex pairs at a rate that is increased by the spiral formation due to cyclic dominance. This mechanism is contrasted with a branching annihilating random walk (BARW) in a particle-antiparticle system with density-dependent pair creation rate. Numerical estimates for the critical indices of the vortex density [beta=0.29(4)] and of its fluctuation [gamma=0.34(6)] improve an earlier Monte Carlo study [K. Tainaka and Y. Itoh, Europhys. Lett. 15, 399 (1991)] of the three-state cyclic model in two dimensions. PMID:11970211
Vortex dynamics in a three-state model under cyclic dominance
NASA Astrophysics Data System (ADS)
Szabó, György; Santos, M. A.; Mendes, J. F. F.
1999-10-01
The evolution of domain structure is investigated in a two-dimensional voter model with three states under cyclic dominance. The study focus on the dynamics of vortices, defined by the points where the three states (domains) meet. We can distinguish vortices and antivortices which walk randomly and annihilate each other. The domain wall motion can create vortex-antivortex pairs at a rate that is increased by the spiral formation due to cyclic dominance. This mechanism is contrasted with a branching annihilating random walk (BARW) in a particle-antiparticle system with density-dependent pair creation rate. Numerical estimates for the critical indices of the vortex density [β=0.29(4)] and of its fluctuation [γ=0.34(6)] improve an earlier Monte Carlo study [K. Tainaka and Y. Itoh, Europhys. Lett. 15, 399 (1991)] of the three-state cyclic model in two dimensions.
Instanton effects in lattice models of bosonic symmetry-protected topological states
NASA Astrophysics Data System (ADS)
Santos, Luiz H.; Fradkin, Eduardo
2016-04-01
Bosonic symmetry-protected topological (SPT) states are gapped disordered phases of matter possessing symmetry-preserving boundary excitations. It has been proposed that, at long wavelengths, the universal properties of an SPT system are captured by an effective nonlinear sigma model field theory in the presence of a quantized topological θ term. By studying lattice models of bosonic SPT states, we are able to identify, in their Euclidean path integral formulation, (discrete) Berry phases that hold relevant physical information on the nature of the SPT ground states. These discrete Berry phases are given intuitive physical interpretation in terms of instanton effects that capture the presence of a θ term on the microscopic scale.
NASA Astrophysics Data System (ADS)
Singh, R. K.; Senay, G. B.; Verdin, J. P.
2015-12-01
Availability of no-cost satellite images helped in development and utilization of remotely sensed images for water use estimation. Remotely sensed images are increasingly used for estimating evapotranspiration (ET) at different temporal and spatial scales. However, selecting any particular model from a plethora of energy balance models for estimating ET is challenging as each different model has its strengths and limitations. We compared four commonly used ET models, namely, Mapping EvapoTranspiration at high Resolution with Internalized Calibration (METRIC) model, Surface Energy Balance Algorithm for Land (SEBAL) model, Surface Energy Balance System (SEBS) model, and Operational Simplified Surface Energy Balance (SSEBop) model using Landsat images for estimating ET in the Midwest United States. We validated our model results using three AmeriFlux cropland sites at Mead, Nebraska. Our results showed that the METRIC and the SSEBop model worked very well at these sites with a root mean square error (RMSE) of less than 1 mm/day and an R2 of 0.96 (N=24). The mean bias error (MBE) was less than 10% for both the METRIC and the SSEBop models. In contrast, the SEBAL and the SEBS models have relatively higher RMSE (> 1.7 mm/day) and MBE (> 27%). However, all four models captured the spatial and temporal variation of ET reasonably well (R2 > 0.80). We found that the model simplification of the SSEBop for operational capability was not at the expense of model accuracy. Since the SSEBop model is relatively less data intensive and independent of user/automatic selection of anchor (hot/dry and cold/wet) pixels, it is more user friendly and operationally efficient. The SSEBop model can be reliably used for estimating water use using Landsat and MODIS images at daily, weekly, monthly, or annual time scale even in data scarce regions for sustainable use of limited water resources.
Testing Race-Neutral Admissions Models: Lessons from California State University-Long Beach
ERIC Educational Resources Information Center
Rendon, Laura I.; Novack, Vincent; Dowell, David
2005-01-01
This policy analysis article examines how California State University-Long Beach, an institution where upward of 22,000 student applied for roughly 3,400 freshman slots and where the transfer class had to be reduced because of mandatory enrollment reductions, tested race-neutral admissions models in accordance with Proposition 209, which prohibits…
ERIC Educational Resources Information Center
Senkevitch, Judith J.; Wolfram, Dietmar
1994-01-01
Provides an overview of the current state of networking technology in rural libraries and describes a model for educating rural librarians in accessing electronic networks. Topics discussed include information needs in rural libraries; telecommunications technology access in rural areas; and examples of services to enhance information access.…
An Expansion of the Trait-State-Occasion Model: Accounting for Shared Method Variance
ERIC Educational Resources Information Center
LaGrange, Beth; Cole, David A.
2008-01-01
This article examines 4 approaches for explaining shared method variance, each applied to a longitudinal trait-state-occasion (TSO) model. Many approaches have been developed to account for shared method variance in multitrait-multimethod (MTMM) data. Some of these MTMM approaches (correlated method, orthogonal method, correlated method minus one,…
Noé, Frank; Wu, Hao; Prinz, Jan-Hendrik; Plattner, Nuria
2013-11-14
Markov state models (MSMs) have been successful in computing metastable states, slow relaxation timescales and associated structural changes, and stationary or kinetic experimental observables of complex molecules from large amounts of molecular dynamics simulation data. However, MSMs approximate the true dynamics by assuming a Markov chain on a clusters discretization of the state space. This approximation is difficult to make for high-dimensional biomolecular systems, and the quality and reproducibility of MSMs has, therefore, been limited. Here, we discard the assumption that dynamics are Markovian on the discrete clusters. Instead, we only assume that the full phase-space molecular dynamics is Markovian, and a projection of this full dynamics is observed on the discrete states, leading to the concept of Projected Markov Models (PMMs). Robust estimation methods for PMMs are not yet available, but we derive a practically feasible approximation via Hidden Markov Models (HMMs). It is shown how various molecular observables of interest that are often computed from MSMs can be computed from HMMs/PMMs. The new framework is applicable to both, simulation and single-molecule experimental data. We demonstrate its versatility by applications to educative model systems, a 1 ms Anton MD simulation of the bovine pancreatic trypsin inhibitor protein, and an optical tweezer force probe trajectory of an RNA hairpin. PMID:24320261
NASA Astrophysics Data System (ADS)
Noé, Frank; Wu, Hao; Prinz, Jan-Hendrik; Plattner, Nuria
2013-11-01
Markov state models (MSMs) have been successful in computing metastable states, slow relaxation timescales and associated structural changes, and stationary or kinetic experimental observables of complex molecules from large amounts of molecular dynamics simulation data. However, MSMs approximate the true dynamics by assuming a Markov chain on a clusters discretization of the state space. This approximation is difficult to make for high-dimensional biomolecular systems, and the quality and reproducibility of MSMs has, therefore, been limited. Here, we discard the assumption that dynamics are Markovian on the discrete clusters. Instead, we only assume that the full phase-space molecular dynamics is Markovian, and a projection of this full dynamics is observed on the discrete states, leading to the concept of Projected Markov Models (PMMs). Robust estimation methods for PMMs are not yet available, but we derive a practically feasible approximation via Hidden Markov Models (HMMs). It is shown how various molecular observables of interest that are often computed from MSMs can be computed from HMMs/PMMs. The new framework is applicable to both, simulation and single-molecule experimental data. We demonstrate its versatility by applications to educative model systems, a 1 ms Anton MD simulation of the bovine pancreatic trypsin inhibitor protein, and an optical tweezer force probe trajectory of an RNA hairpin.
Data support for a state-and-transition model: What have we learned?
Technology Transfer Automated Retrieval System (TEKTRAN)
State-and-transition models (STMs) were conceived as a means to synthesize knowledge about alternative plant communities and the processes that lead to transitions among them for specific land areas. STMs that have been developed over the past decade have often been limited by 1) a lack of detail on...
EVALUATION OF THE STATE-OF-THE-ART CONTAMINATED SEDIMENT TRANSPORT AND FATE MODELING SYSTEM
Modeling approaches for evaluating the transport and fate of sediment and associated contaminants are briefly reviewed. The main emphasis is on: 1) the application of EFDC (Environmental Fluid Dynamics Code), the state-of-the-art contaminated sediment transport and fate public do...
NASA Astrophysics Data System (ADS)
Bezzi, Michele; Celada, Franco; Ruffo, Stefano; Seiden, Philip E.
1997-02-01
In this paper we extend the Celada-Seiden (CS) model of the humoral immune response to include infections virus and killer T cells (cellular response). The model represents molecules and cells with bitstrings. The response of the system to virus involves a competition between the ability of the virus to kill the host cells and the host's ability to eliminate the virus. We find two basins of attraction in the dynamics of this system, one is identified with disease and the other with the immune state. There is also an oscillating state that exists on the border of these two stable states. Fluctuations in the population of virus or antibody can end the oscillation and drive the system into one of the stable states. The introduction of mechanisms of cross-regulation between the two responses can bias the system towards one of them. We also study a mean field model, based on coupled maps, to investigate virus-like infections. This simple model reproduces the attractors for average populations observed in the cellular automaton. All the dynamical behavior connected to spatial extension is lost, as is the oscillating feature. Thus the mean field approximation introduced with coupled maps destroys oscillations.
Excited states of the Calogero-Sutherland model and singular vectors of the WN algebra
NASA Astrophysics Data System (ADS)
Awata, Hidetoshi; Matsuo, Yutaka; Odake, Satoru; Shiraishi, Jun'ichi
1995-02-01
Using the collective field method, we find a relation between the Jack symmetric polynomials, which describe the excited states of the Calogero-Sutherland model, and the singular vectors of the WN algebra. Based on this relation, we obtain their integral representations. We also give a direct algebraic method which leads to the same result, and integral representations of the skew-Jack polynomials.
Aristotelian-Inspired Model for Curtailing Academic Dishonesty in the United States
ERIC Educational Resources Information Center
Sanders, Maria A.
2012-01-01
This dissertation explores the growing epidemic of academic dishonesty in the United States in order to propose an Aristotelian-inspired model for developing moral character to curtail this epidemic. The task is laid out in four parts. Chapter one responds to the problem of "akrasia," adopting a modified version of Devin Henry's…
Exploration of ITER Steady-State Scenarios Using FASTRAN/IPS Integrated Transport Modeling
NASA Astrophysics Data System (ADS)
Murakami, M.; Park, J. M.; Batchelor, D. B.; Diem, S. J.; Elwasif, W. R.; Sontag, A. C.; DIII-D Team
2013-10-01
ITER steady-state (SS) scenarios are examined using an iterative steady-state (d / dt = 0) solution procedure using FASTRAN solver implemented in Integrated Plasma Simulator framework, self-consistently with heating and current drive (H&CD), MHD equilibrium, and transport models. The objective of the exercise is to understand the range of steady-state solutions using theory-based transport models with the ITER Day-1 H&CD and proposed upgrades (EC launcher modifications). ITER operation performances (fusion gain Q and noninductive fraction fNI and steady burn duration) are compared using different transport models (TGLF, GLF23, CDBM, MMM7.1) based on the edge profiles scaled from recent DIII-D ITER Steady State Demo discharges as well as from the existing pedestal models (EPED). Sensitivities of the operation spaces are studied using different density peaking and plasma current. Reducing Ip increases achievable fNI while peaking density increases Q but limited by MHD stability. Optimization of Day-1 H&CD mixes is discussed toward the ITER goal (Q = 5 and fNI = 1 for 3000 s). Work supported by the US Department of Energy under DE-AC05-00OR22725, and DE-FC02-04ER54698.