Estimating state-transition probabilities for unobservable states using capture-recapture/resighting data

USGS Publications Warehouse

Kendall, W.L.; Nichols, J.D.

2002-01-01

Temporary emigration was identified some time ago as causing potential problems in capture-recapture studies, and in the last five years approaches have been developed for dealing with special cases of this general problem. Temporary emigration can be viewed more generally as involving transitions to and from an unobservable state, and frequently the state itself is one of biological interest (e.g., 'nonbreeder'). Development of models that permit estimation of relevant parameters in the presence of an unobservable state requires either extra information (e.g., as supplied by Pollock's robust design) or the following classes of model constraints: reducing the order of Markovian transition probabilities, imposing a degree of determinism on transition probabilities, removing state specificity of survival probabilities, and imposing temporal constancy of parameters. The objective of the work described in this paper is to investigate estimability of model parameters under a variety of models that include an unobservable state. Beginning with a very general model and no extra information, we used numerical methods to systematically investigate the use of ancillary information and constraints to yield models that are useful for estimation. The result is a catalog of models for which estimation is possible. An example analysis of sea turtle capture-recapture data under two different models showed similar point estimates but increased precision for the model that incorporated ancillary data (the robust design) when compared to the model with deterministic transitions only. This comparison and the results of our numerical investigation of model structures lead to design suggestions for capture-recapture studies in the presence of an unobservable state.

Transition probabilities of health states for workers in Malaysia using a Markov chain model

NASA Astrophysics Data System (ADS)

Samsuddin, Shamshimah; Ismail, Noriszura

2017-04-01

The aim of our study is to estimate the transition probabilities of health states for workers in Malaysia who contribute to the Employment Injury Scheme under the Social Security Organization Malaysia using the Markov chain model. Our study uses four states of health (active, temporary disability, permanent disability and death) based on the data collected from the longitudinal studies of workers in Malaysia for 5 years. The transition probabilities vary by health state, age and gender. The results show that men employees are more likely to have higher transition probabilities to any health state compared to women employees. The transition probabilities can be used to predict the future health of workers in terms of a function of current age, gender and health state.

Energy Landscape and Transition State of Protein-Protein Association

NASA Astrophysics Data System (ADS)

Alsallaq, Ramzi; Zhou, Huan-Xiang

2006-11-01

Formation of a stereospecific protein complex is favored by specific interactions between two proteins but disfavored by the loss of translational and rotational freedom. Echoing the protein folding process, we have previously proposed a transition state for protein-protein association. Here we clarify the specification of the transition state by working with two toy models for protein association. The models demonstrate that a sharp transition between the bound state with numerous short-range interactions but restricted translation and rotational freedom and the unbound state with at most a small number of interactions but expanded configurational freedom. This transition sets the outer boundary of the bound state as well as the transition state for association. The energy landscape is funnel-like, with the deep well of the bound state surrounded by a broad shallow basin. This formalism of protein-protein association is applied to four protein-protein complexes, and is found to give accurate predictions for the effects of charge mutations and ionic strength on the association rates.

Implementing autonomous clinical nurse specialist prescriptive authority: a competency-based transition model.

PubMed

Klein, Tracy Ann

2012-01-01

The purpose of this study was to identify and implement a competency-based regulatory model that transitions clinical nurse specialists (CNSs) to autonomous prescriptive authority pursuant to change in state law. Prescriptive authority for CNSs may be optional or restricted under current state law. Implementation of the APRN Consensus Model includes full prescriptive authority for all advanced practice registered nurses. Clinical nurse specialists face barriers to establishing their prescribing authority when laws or practice change. Identification of transition models will assist CNSs who need to add prescriptive authority to their scope of practice. Identification and implementation of a competency-based transition model for expansion of CNS prescriptive authority. By January 1, 2012, 9 CNSs in the state exemplar have completed a practicum and been granted full prescriptive authority including scheduled drug prescribing. No complaints or board actions resulted from the transition to autonomous prescribing. Transition to prescribing may be facilitated through competency-based outcomes including practicum hours as appropriate to the individual CNS nursing specialty. Outcomes from this model can be used to develop and further validate educational and credentialing policies to reduce barriers for CNSs requiring prescriptive authority in other states.

Effects of ignoring baseline on modeling transitions from intact cognition to dementia.

PubMed

Yu, Lei; Tyas, Suzanne L; Snowdon, David A; Kryscio, Richard J

2009-07-01

This paper evaluates the effect of ignoring baseline when modeling transitions from intact cognition to dementia with mild cognitive impairment (MCI) and global impairment (GI) as intervening cognitive states. Transitions among states are modeled by a discrete-time Markov chain having three transient (intact cognition, MCI, and GI) and two competing absorbing states (death and dementia). Transition probabilities depend on two covariates, age and the presence/absence of an apolipoprotein E-epsilon4 allele, through a multinomial logistic model with shared random effects. Results are illustrated with an application to the Nun Study, a cohort of 678 participants 75+ years of age at baseline and followed longitudinally with up to ten cognitive assessments per nun.

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.

Force transients and minimum cross-bridge models in muscular contraction

PubMed Central

Halvorson, Herbert R.

2010-01-01

Two- and three-state cross-bridge models are considered and examined with respect to their ability to predict three distinct phases of the force transients that occur in response to step change in muscle fiber length. Particular attention is paid to satisfying the Le Châtelier–Brown Principle. This analysis shows that the two-state model can account for phases 1 and 2 of a force transient, but is barely adequate to account for phase 3 (delayed force) unless a stretch results in a sudden increase in the number of cross-bridges in the detached state. The three-state model (A → B → C → A) makes it possible to account for all three phases if we assume that the A → B transition is fast (corresponding to phase 2), the B → C transition is of intermediate speed (corresponding to phase 3), and the C → A transition is slow; in such a scenario, states A and C can support or generate force (high force states) but state B cannot (detached, or low-force state). This model involves at least one ratchet mechanism. In this model, force can be generated by either of two transitions: B → A or B → C. To determine which of these is the major force-generating step that consumes ATP and transduces energy, we examine the effects of ATP, ADP, and phosphate (Pi) on force transients. In doing so, we demonstrate that the fast transition (phase 2) is associated with the nucleotide-binding step, and that the intermediate-speed transition (phase 3) is associated with the Pi-release step. To account for all the effects of ligands, it is necessary to expand the three-state model into a six-state model that includes three ligand-bound states. The slowest phase of a force transient (phase 4) cannot be explained by any of the models described unless an additional mechanism is introduced. Here we suggest a role of series compliance to account for this phase, and propose a model that correlates the slowest step of the cross-bridge cycle (transition C → A) to: phase 4 of step analysis, the rate constant ktr of the quick-release and restretch experiment, and the rate constant kact for force development time course following Ca2+ activation. PMID:18425593

Force transients and minimum cross-bridge models in muscular contraction.

PubMed

Kawai, Masataka; Halvorson, Herbert R

2007-01-01

Two- and three-state cross-bridge models are considered and examined with respect to their ability to predict three distinct phases of the force transients that occur in response to step change in muscle fiber length. Particular attention is paid to satisfying the Le Châtelier-Brown Principle. This analysis shows that the two-state model can account for phases 1 and 2 of a force transient, but is barely adequate to account for phase 3 (delayed force) unless a stretch results in a sudden increase in the number of cross-bridges in the detached state. The three-state model (A-->B-->C-->A) makes it possible to account for all three phases if we assume that the A-->B transition is fast (corresponding to phase 2), the B-->A transition is of intermediate speed (corresponding to phase 3), and the C-->A transition is slow; in such a scenario, states A and C can support or generate force (high force states) but state B cannot (detached, or low-force state). This model involves at least one ratchet mechanism. In this model, force can be generated by either of two transitions: B-->A or B-->C. To determine which of these is the major force-generating step that consumes ATP and transduces energy, we examine the effects of ATP, ADP, and phosphate (Pi) on force transients. In doing so, we demonstrate that the fast transition (phase 2) is associated with the nucleotide-binding step, and that the intermediate-speed transition (phase 3) is associated with the Pi-release step. To account for all the effects of ligands, it is necessary to expand the three-state model into a six-state model that includes three ligand-bound states. The slowest phase of a force transient (phase 4) cannot be explained by any of the models described unless an additional mechanism is introduced. Here we suggest a role of series compliance to account for this phase, and propose a model that correlates the slowest step of the cross-bridge cycle (transition C-->A) to: phase 4 of step analysis, the rate constant k(tr) of the quick-release and restretch experiment, and the rate constant k(act) for force development time course following Ca(2+) activation.

Remote sensing of rangeland biodiversity

USDA-ARS?s Scientific Manuscript database

Rangelands are managed based on state and transition models for an ecological site. Transitions to alternative ecological states are indicative of degrading rangelands. Three key variables may be remotely sensed to detect transitions between alternative states: amount of bare soil, presence of inva...

Land management in the American southwest: a state-and-transition approach to ecosystem complexity.

PubMed

Bestelmeyer, Brandon T; Herrick, Jeffrey E; Brown, Joel R; Trujillo, David A; Havstad, Kris M

2004-07-01

State-and-transition models are increasingly being used to guide rangeland management. These models provide a relatively simple, management-oriented way to classify land condition (state) and to describe the factors that might cause a shift to another state (a transition). There are many formulations of state-and-transition models in the literature. The version we endorse does not adhere to any particular generalities about ecosystem dynamics, but it includes consideration of several kinds of dynamics and management response to them. In contrast to previous uses of state-and-transition models, we propose that models can, at present, be most effectively used to specify and qualitatively compare the relative benefits and potential risks of different management actions (e.g., fire and grazing) and other factors (e.g., invasive species and climate change) on specified areas of land. High spatial and temporal variability and complex interactions preclude the meaningful use of general quantitative models. Forecasts can be made on a case-by-case basis by interpreting qualitative and quantitative indicators, historical data, and spatially structured monitoring data based on conceptual models. We illustrate how science- based conceptual models are created using several rangeland examples that vary in complexity. In doing so, we illustrate the implications of designating plant communities and states in models, accounting for varying scales of pattern in vegetation and soils, interpreting the presence of plant communities on different soils and dealing with our uncertainty about how those communities were assembled and how they will change in the future. We conclude with observations about how models have helped to improve management decision-making.

Lotka-Volterra competition models for sessile organisms.

PubMed

Spencer, Matthew; Tanner, Jason E

2008-04-01

Markov models are widely used to describe the dynamics of communities of sessile organisms, because they are easily fitted to field data and provide a rich set of analytical tools. In typical ecological applications, at any point in time, each point in space is in one of a finite set of states (e.g., species, empty space). The models aim to describe the probabilities of transitions between states. In most Markov models for communities, these transition probabilities are assumed to be independent of state abundances. This assumption is often suspected to be false and is rarely justified explicitly. Here, we start with simple assumptions about the interactions among sessile organisms and derive a model in which transition probabilities depend on the abundance of destination states. This model is formulated in continuous time and is equivalent to a Lotka-Volterra competition model. We fit this model and a variety of alternatives in which transition probabilities do not depend on state abundances to a long-term coral reef data set. The Lotka-Volterra model describes the data much better than all models we consider other than a saturated model (a model with a separate parameter for each transition at each time interval, which by definition fits the data perfectly). Our approach provides a basis for further development of stochastic models of sessile communities, and many of the methods we use are relevant to other types of community. We discuss possible extensions to spatially explicit models.

Effect of Zn2+ binding and enzyme active site on the transition state for RNA 2′-O-transphosphorylation interpreted through kinetic isotope effects

PubMed Central

Chen, Haoyuan; Piccirilli, Joseph A.; Harris, Michael E.; York, Darrin M.

2016-01-01

Divalent metal ions, due to their ability to stabilize high concentrations of negative charge, are important for RNA folding and catalysis. Detailed models derived from the structures and kinetics of enzymes and from computational simulations have been developed. However, in most cases the specific catalytic modes involving metal ions and their mechanistic roles and effects on transition state structures remains controversial. Valuable information about the nature of the transition state is provided by measurement of kinetic isotope effects (KIEs). However, KIEs reflect changes in all bond vibrational modes that differ between the ground state and transition state. QM calculations are therefore essential for developing structural models of the transition state and evaluating mechanistic alternatives. Herein, we present computational models for Zn2+ binding to RNA 2′O-transphosphorylation reaction models that aid in the interpretation of KIE experiments. Different Zn2+ binding modes produce distinct KIE signatures, and one binding mode involving two zinc ions is in close agreement with KIEs measured for non-enzymatic catalysis by Zn2+ aquo ions alone. Interestingly, the KIE signatures in this specific model are also very close to those in RNase A catalysis. These results allow a quantitative connection to be made between experimental KIE measurements and transition state structure and bonding, and provide insight into RNA 2′O-transphosphorylation reactions catalyzed by metal ions and enzymes. PMID:25812974

State-and-transition simulation models: a framework for forecasting landscape change

USGS Publications Warehouse

Daniel, Colin; Frid, Leonardo; Sleeter, Benjamin M.; Fortin, Marie-Josée

2016-01-01

SummaryA wide range of spatially explicit simulation models have been developed to forecast landscape dynamics, including models for projecting changes in both vegetation and land use. While these models have generally been developed as separate applications, each with a separate purpose and audience, they share many common features.We present a general framework, called a state-and-transition simulation model (STSM), which captures a number of these common features, accompanied by a software product, called ST-Sim, to build and run such models. The STSM method divides a landscape into a set of discrete spatial units and simulates the discrete state of each cell forward as a discrete-time-inhomogeneous stochastic process. The method differs from a spatially interacting Markov chain in several important ways, including the ability to add discrete counters such as age and time-since-transition as state variables, to specify one-step transition rates as either probabilities or target areas, and to represent multiple types of transitions between pairs of states.We demonstrate the STSM method using a model of land-use/land-cover (LULC) change for the state of Hawai'i, USA. Processes represented in this example include expansion/contraction of agricultural lands, urbanization, wildfire, shrub encroachment into grassland and harvest of tree plantations; the model also projects shifts in moisture zones due to climate change. Key model output includes projections of the future spatial and temporal distribution of LULC classes and moisture zones across the landscape over the next 50 years.State-and-transition simulation models can be applied to a wide range of landscapes, including questions of both land-use change and vegetation dynamics. Because the method is inherently stochastic, it is well suited for characterizing uncertainty in model projections. When combined with the ST-Sim software, STSMs offer a simple yet powerful means for developing a wide range of models of landscape dynamics.

Exact transition probabilities in a 6-state Landau–Zener system with path interference

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

Sinitsyn, Nikolai A.

2015-04-23

In this paper, we identify a nontrivial multistate Landau–Zener (LZ) model for which transition probabilities between any pair of diabatic states can be determined analytically and exactly. In the semiclassical picture, this model features the possibility of interference of different trajectories that connect the same initial and final states. Hence, transition probabilities are generally not described by the incoherent successive application of the LZ formula. Finally, we discuss reasons for integrability of this system and provide numerical tests of the suggested expression for the transition probability matrix.

Phase transitions and adiabatic preparation of a fractional Chern insulator in a boson cold-atom model

NASA Astrophysics Data System (ADS)

Motruk, Johannes; Pollmann, Frank

2017-10-01

We investigate the fate of hardcore bosons in a Harper-Hofstadter model which was experimentally realized by Aidelsburger et al. [Nat. Phys. 11, 162 (2015), 10.1038/nphys3171] at half-filling of the lowest band. We discuss the stability of an emergent fractional Chern insulator (FCI) state in a finite region of the phase diagram that is separated from a superfluid state by a first-order transition when tuning the band topology following the protocol used in the experiment. Since crossing a first-order transition is unfavorable for adiabatically preparing the FCI state, we extend the model to stabilize a featureless insulating state. The transition between this phase and the topological state proves to be continuous, providing a path in parameter space along which an FCI state could be adiabatically prepared. To further corroborate this statement, we perform time-dependent DMRG calculations which demonstrate that the FCI state may indeed be reached by adiabatically tuning a simple product state.

Effects of ignoring baseline on modeling transitions from intact cognition to dementia

PubMed Central

Yu, Lei; Tyas, Suzanne L.; Snowdon, David A.; Kryscio, Richard J.

2009-01-01

This paper evaluates the effect of ignoring baseline when modeling transitions from intact cognition to dementia with mild cognitive impairment (MCI) and global impairment (GI) as intervening cognitive states. Transitions among states are modeled by a discrete-time Markov chain having three transient (intact cognition, MCI, and GI) and two competing absorbing states (death and dementia). Transition probabilities depend on two covariates, age and the presence/absence of an apolipoprotein E-ε4 allele, through a multinomial logistic model with shared random effects. Results are illustrated with an application to the Nun Study, a cohort of 678 participants 75+ years of age at baseline and followed longitudinally with up to ten cognitive assessments per nun. PMID:20161282

Multistate modeling of habitat dynamics: Factors affecting Florida scrub transition probabilities

USGS Publications Warehouse

Breininger, D.R.; Nichols, J.D.; Duncan, B.W.; Stolen, Eric D.; Carter, G.M.; Hunt, D.K.; Drese, J.H.

2010-01-01

Many ecosystems are influenced by disturbances that create specific successional states and habitat structures that species need to persist. Estimating transition probabilities between habitat states and modeling the factors that influence such transitions have many applications for investigating and managing disturbance-prone ecosystems. We identify the correspondence between multistate capture-recapture models and Markov models of habitat dynamics. We exploit this correspondence by fitting and comparing competing models of different ecological covariates affecting habitat transition probabilities in Florida scrub and flatwoods, a habitat important to many unique plants and animals. We subdivided a large scrub and flatwoods ecosystem along central Florida's Atlantic coast into 10-ha grid cells, which approximated average territory size of the threatened Florida Scrub-Jay (Aphelocoma coerulescens), a management indicator species. We used 1.0-m resolution aerial imagery for 1994, 1999, and 2004 to classify grid cells into four habitat quality states that were directly related to Florida Scrub-Jay source-sink dynamics and management decision making. Results showed that static site features related to fire propagation (vegetation type, edges) and temporally varying disturbances (fires, mechanical cutting) best explained transition probabilities. Results indicated that much of the scrub and flatwoods ecosystem was resistant to moving from a degraded state to a desired state without mechanical cutting, an expensive restoration tool. We used habitat models parameterized with the estimated transition probabilities to investigate the consequences of alternative management scenarios on future habitat dynamics. We recommend this multistate modeling approach as being broadly applicable for studying ecosystem, land cover, or habitat dynamics. The approach provides maximum-likelihood estimates of transition parameters, including precision measures, and can be used to assess evidence among competing ecological models that describe system dynamics. ?? 2010 by the Ecological Society of America.

State-and-transition model archetypes: a global taxonomy of rangeland change

USDA-ARS?s Scientific Manuscript database

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...

Ashkin-Teller criticality and weak first-order behavior of the phase transition to a fourfold degenerate state in two-dimensional frustrated Ising antiferromagnets

NASA Astrophysics Data System (ADS)

Liu, R. M.; Zhuo, W. Z.; Chen, J.; Qin, M. H.; Zeng, M.; Lu, X. B.; Gao, X. S.; Liu, J.-M.

2017-07-01

We study the thermal phase transition of the fourfold degenerate phases (the plaquette and single-stripe states) in the two-dimensional frustrated Ising model on the Shastry-Sutherland lattice using Monte Carlo simulations. The critical Ashkin-Teller-like behavior is identified both in the plaquette phase region and the single-stripe phase region. The four-state Potts critical end points differentiating the continuous transitions from the first-order ones are estimated based on finite-size-scaling analyses. Furthermore, a similar behavior of the transition to the fourfold single-stripe phase is also observed in the anisotropic triangular Ising model. Thus, this work clearly demonstrates that the transitions to the fourfold degenerate states of two-dimensional Ising antiferromagnets exhibit similar transition behavior.

Forecasting client transitions in British Columbia's Long-Term Care Program.

PubMed Central

Lane, D; Uyeno, D; Stark, A; Gutman, G; McCashin, B

1987-01-01

This article presents a model for the annual transitions of clients through various home and facility placements in a long-term care program. The model, an application of Markov chain analysis, is developed, tested, and applied to over 9,000 clients (N = 9,483) in British Columbia's Long Term Care Program (LTC) over the period 1978-1983. Results show that the model gives accurate forecasts of the progress of groups of clients from state to state in the long-term care system from time of admission until eventual death. Statistical methods are used to test the modeling hypothesis that clients' year-over-year transitions occur in constant proportions from state to state within the long-term care system. Tests are carried out by examining actual year-over-year transitions of each year's new admission cohort (1978-1983). Various subsets of the available data are analyzed and, after accounting for clear differences among annual cohorts, the most acceptable model of the actual client transition data occurred when clients were separated into male and female groups, i.e., the transition behavior of each group is describable by a different Markov model. To validate the model, we develop model estimates for the numbers of existing clients in each state of the long-term care system for the period (1981-1983) for which actual data are available. When these estimates are compared with the actual data, total weighted absolute deviations do not exceed 10 percent of actuals. Finally, we use the properties of the Markov chain probability transition matrix and simulation methods to develop three-year forecasts with prediction intervals for the distribution of the existing total clients into each state of the system. The tests, forecasts, and Markov model supplemental information are contained in a mechanized procedure suitable for a microcomputer. The procedure provides a powerful, efficient tool for decision makers planning facilities and services in response to the needs of long-term care clients. PMID:3121537

Markov State Models of gene regulatory networks.

PubMed

Chu, Brian K; Tse, Margaret J; Sato, Royce R; Read, Elizabeth L

2017-02-06

Gene regulatory networks with dynamics characterized by multiple stable states underlie cell fate-decisions. Quantitative models that can link molecular-level knowledge of gene regulation to a global understanding of network dynamics have the potential to guide cell-reprogramming strategies. Networks are often modeled by the stochastic Chemical Master Equation, but methods for systematic identification of key properties of the global dynamics are currently lacking. The method identifies the number, phenotypes, and lifetimes of long-lived states for a set of common gene regulatory network models. Application of transition path theory to the constructed Markov State Model decomposes global dynamics into a set of dominant transition paths and associated relative probabilities for stochastic state-switching. In this proof-of-concept study, we found that the Markov State Model provides a general framework for analyzing and visualizing stochastic multistability and state-transitions in gene networks. Our results suggest that this framework-adopted from the field of atomistic Molecular Dynamics-can be a useful tool for quantitative Systems Biology at the network scale.

Experimental and computational analysis of the transition state for ribonuclease A-catalyzed RNA 2′-O-transphosphorylation

PubMed Central

Gu, Hong; Zhang, Shuming; Wong, Kin-Yiu; Radak, Brian K.; Dissanayake, Thakshila; Kellerman, Daniel L.; Dai, Qing; Miyagi, Masaru; Anderson, Vernon E.; York, Darrin M.; Piccirilli, Joseph A.; Harris, Michael E.

2013-01-01

Enzymes function by stabilizing reaction transition states; therefore, comparison of the transition states of enzymatic and nonenzymatic model reactions can provide insight into biological catalysis. Catalysis of RNA 2′-O-transphosphorylation by ribonuclease A is proposed to involve electrostatic stabilization and acid/base catalysis, although the structure of the rate-limiting transition state is uncertain. Here, we describe coordinated kinetic isotope effect (KIE) analyses, molecular dynamics simulations, and quantum mechanical calculations to model the transition state and mechanism of RNase A. Comparison of the 18O KIEs on the 2′O nucleophile, 5′O leaving group, and nonbridging phosphoryl oxygens for RNase A to values observed for hydronium- or hydroxide-catalyzed reactions indicate a late anionic transition state. Molecular dynamics simulations using an anionic phosphorane transition state mimic suggest that H-bonding by protonated His12 and Lys41 stabilizes the transition state by neutralizing the negative charge on the nonbridging phosphoryl oxygens. Quantum mechanical calculations consistent with the experimental KIEs indicate that expulsion of the 5′O remains an integral feature of the rate-limiting step both on and off the enzyme. Electrostatic interactions with positively charged amino acid site chains (His12/Lys41), together with proton transfer from His119, render departure of the 5′O less advanced compared with the solution reaction and stabilize charge buildup in the transition state. The ability to obtain a chemically detailed description of 2′-O-transphosphorylation transition states provides an opportunity to advance our understanding of biological catalysis significantly by determining how the catalytic modes and active site environments of phosphoryl transferases influence transition state structure. PMID:23878223

Mental models accurately predict emotion transitions.

PubMed

Thornton, Mark A; Tamir, Diana I

2017-06-06

Successful social interactions depend on people's ability to predict others' future actions and emotions. People possess many mechanisms for perceiving others' current emotional states, but how might they use this information to predict others' future states? We hypothesized that people might capitalize on an overlooked aspect of affective experience: current emotions predict future emotions. By attending to regularities in emotion transitions, perceivers might develop accurate mental models of others' emotional dynamics. People could then use these mental models of emotion transitions to predict others' future emotions from currently observable emotions. To test this hypothesis, studies 1-3 used data from three extant experience-sampling datasets to establish the actual rates of emotional transitions. We then collected three parallel datasets in which participants rated the transition likelihoods between the same set of emotions. Participants' ratings of emotion transitions predicted others' experienced transitional likelihoods with high accuracy. Study 4 demonstrated that four conceptual dimensions of mental state representation-valence, social impact, rationality, and human mind-inform participants' mental models. Study 5 used 2 million emotion reports on the Experience Project to replicate both of these findings: again people reported accurate models of emotion transitions, and these models were informed by the same four conceptual dimensions. Importantly, neither these conceptual dimensions nor holistic similarity could fully explain participants' accuracy, suggesting that their mental models contain accurate information about emotion dynamics above and beyond what might be predicted by static emotion knowledge alone.

Nonparametric model validations for hidden Markov models with applications in financial econometrics.

PubMed

Zhao, Zhibiao

2011-06-01

We address the nonparametric model validation problem for hidden Markov models with partially observable variables and hidden states. We achieve this goal by constructing a nonparametric simultaneous confidence envelope for transition density function of the observable variables and checking whether the parametric density estimate is contained within such an envelope. Our specification test procedure is motivated by a functional connection between the transition density of the observable variables and the Markov transition kernel of the hidden states. Our approach is applicable for continuous time diffusion models, stochastic volatility models, nonlinear time series models, and models with market microstructure noise.

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.

Neuronal network model of interictal and recurrent ictal activity

NASA Astrophysics Data System (ADS)

Lopes, M. A.; Lee, K.-E.; Goltsev, A. V.

2017-12-01

We propose a neuronal network model which undergoes a saddle node on an invariant circle bifurcation as the mechanism of the transition from the interictal to the ictal (seizure) state. In the vicinity of this transition, the model captures important dynamical features of both interictal and ictal states. We study the nature of interictal spikes and early warnings of the transition predicted by this model. We further demonstrate that recurrent seizures emerge due to the interaction between two networks.

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.

Phase diagram of quantum critical system via local convertibility of ground state

PubMed Central

Liu, Si-Yuan; Quan, Quan; Chen, Jin-Jun; Zhang, Yu-Ran; Yang, Wen-Li; Fan, Heng

2016-01-01

We investigate the relationship between two kinds of ground-state local convertibility and quantum phase transitions in XY model. The local operations and classical communications (LOCC) convertibility is examined by the majorization relations and the entanglement-assisted local operations and classical communications (ELOCC) via Rényi entropy interception. In the phase diagram of XY model, LOCC convertibility and ELOCC convertibility of ground-states are presented and compared. It is shown that different phases in the phase diagram of XY model can have different LOCC or ELOCC convertibility, which can be used to detect the quantum phase transition. This study will enlighten extensive studies of quantum phase transitions from the perspective of local convertibility, e.g., finite-temperature phase transitions and other quantum many-body models. PMID:27381284

CORRELATION OF THE GLASS TRANSITION TEMPERATURE OF PLASTICIZED PVC USING A LATTICE FLUID MODEL

EPA Science Inventory

A model has been developed to describe the composition dependence of the glass transition temperature (Tg) of polyvinyl chloride (PVC) + plasticizer mixtures. The model is based on Sanchez-Lacombe equation of state and the Gibbs-Di Marzio criterion, which states that th...

State and transition models: Theory, applications, and challenges. In: Briske, D.D. Rangeland Systems: Processes, Management and Challenges

USDA-ARS?s Scientific Manuscript database

State and transition models (STMs) are used for communicating about ecosystem change in rangelands and other ecosystems, especially the implications for management. The fundamental premise that rangelands can exhibit multiple states is now widely accepted. The current application of STMs for managem...

Transition State Gauche Effects Control the Torquoselectivities of the Electrocyclizations of Chiral 1-Azatrienes.

PubMed

Patel, Ashay; Vella, Joseph R; Ma, Zhi-Xiong; Hsung, R P; Houk, K N

2015-12-04

Hsung et al. have reported a series of torquoselective electrocyclizations of chiral 1-azahexa-1E,3Z,5E-trienes that yield functionalized dihydropyridines. To understand the origins of the torquoselectivities of these azaelectrocyclizations, we modeled these electrocyclic ring closures using the M06-2X density functional. A new stereochemical model that rationalizes the observed 1,2 stereoinduction emerges from these computations. This model is an improvement and generalization of the "inside-alkoxy" model used to rationalize stereoselectivities of the 1,3-dipolar cycloaddition of chiral allyl ethers and emphasizes a stabilizing hyperconjugative effect, which we have termed a transition state gauche effect. This stereoelectronic effect controls the conformational preferences at the electrocyclization transition states, and only in one of the allowed disrotatory electrocyclization transition states is the ideal stereoelectronic arrangement achieved without the introduction of a steric clash. Computational experiments confirm the role of this effect as a stereodeterminant since substrates with electropositive groups and electronegative groups have different conformational preferences at the transition state and undergo ring closure with divergent stereochemical outcomes. This predicted reversal of stereoselectivity for the ring closures of several silyl substituted azatrienes have been demonstrated experimentally.

Localization of soft modes at the depinning transition

NASA Astrophysics Data System (ADS)

Cao, Xiangyu; Bouzat, Sebastian; Kolton, Alejandro B.; Rosso, Alberto

2018-02-01

We characterize the soft modes of the dynamical matrix at the depinning transition, and compare the matrix with the properties of the Anderson model (and long-range generalizations). The density of states at the edge of the spectrum displays a universal linear tail, different from the Lifshitz tails. The eigenvectors are instead very similar in the two matrix ensembles. We focus on the ground state (soft mode), which represents the epicenter of avalanche instabilities. We expect it to be localized in all finite dimensions, and make a clear connection between its localization length and the Larkin length of the depinning model. In the fully connected model, we show that the weak-strong pinning transition coincides with a peculiar localization transition of the ground state.

Modeling the polydomain-monodomain transition of liquid crystal elastomers.

PubMed

Whitmer, Jonathan K; Roberts, Tyler F; Shekhar, Raj; Abbott, Nicholas L; de Pablo, Juan J

2013-02-01

We study the mechanism of the polydomain-monodomain transition in liquid crystalline elastomers at the molecular scale. A coarse-grained model is proposed in which mesogens are described as ellipsoidal particles. Molecular dynamics simulations are used to examine the transition from a polydomain state to a monodomain state in the presence of uniaxial strain. Our model demonstrates soft elasticity, similar to that exhibited by side-chain elastomers in the literature. By analyzing the growth dynamics of nematic domains during uniaxial extension, we provide direct evidence that at a molecular level the polydomain-monodomain transition proceeds through cluster rotation and domain growth.

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

PubMed

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

2011-01-01

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

State-transition diagrams for biologists.

PubMed

Bersini, Hugues; Klatzmann, David; Six, Adrien; Thomas-Vaslin, Véronique

2012-01-01

It is clearly in the tradition of biologists to conceptualize the dynamical evolution of biological systems in terms of state-transitions of biological objects. This paper is mainly concerned with (but obviously not limited too) the immunological branch of biology and shows how the adoption of UML (Unified Modeling Language) state-transition diagrams can ease the modeling, the understanding, the coding, the manipulation or the documentation of population-based immune software model generally defined as a set of ordinary differential equations (ODE), describing the evolution in time of populations of various biological objects. Moreover, that same UML adoption naturally entails a far from negligible representational economy since one graphical item of the diagram might have to be repeated in various places of the mathematical model. First, the main graphical elements of the UML state-transition diagram and how they can be mapped onto a corresponding ODE mathematical model are presented. Then, two already published immune models of thymocyte behavior and time evolution in the thymus, the first one originally conceived as an ODE population-based model whereas the second one as an agent-based one, are refactored and expressed in a state-transition form so as to make them much easier to understand and their respective code easier to access, to modify and run. As an illustrative proof, for any immunologist, it should be possible to understand faithfully enough what the two software models are supposed to reproduce and how they execute with no need to plunge into the Java or Fortran lines.

State-Transition Diagrams for Biologists

PubMed Central

Bersini, Hugues; Klatzmann, David; Six, Adrien; Thomas-Vaslin, Véronique

2012-01-01

It is clearly in the tradition of biologists to conceptualize the dynamical evolution of biological systems in terms of state-transitions of biological objects. This paper is mainly concerned with (but obviously not limited too) the immunological branch of biology and shows how the adoption of UML (Unified Modeling Language) state-transition diagrams can ease the modeling, the understanding, the coding, the manipulation or the documentation of population-based immune software model generally defined as a set of ordinary differential equations (ODE), describing the evolution in time of populations of various biological objects. Moreover, that same UML adoption naturally entails a far from negligible representational economy since one graphical item of the diagram might have to be repeated in various places of the mathematical model. First, the main graphical elements of the UML state-transition diagram and how they can be mapped onto a corresponding ODE mathematical model are presented. Then, two already published immune models of thymocyte behavior and time evolution in the thymus, the first one originally conceived as an ODE population-based model whereas the second one as an agent-based one, are refactored and expressed in a state-transition form so as to make them much easier to understand and their respective code easier to access, to modify and run. As an illustrative proof, for any immunologist, it should be possible to understand faithfully enough what the two software models are supposed to reproduce and how they execute with no need to plunge into the Java or Fortran lines. PMID:22844438

Nonparametric model validations for hidden Markov models with applications in financial econometrics

PubMed Central

Zhao, Zhibiao

2011-01-01

We address the nonparametric model validation problem for hidden Markov models with partially observable variables and hidden states. We achieve this goal by constructing a nonparametric simultaneous confidence envelope for transition density function of the observable variables and checking whether the parametric density estimate is contained within such an envelope. Our specification test procedure is motivated by a functional connection between the transition density of the observable variables and the Markov transition kernel of the hidden states. Our approach is applicable for continuous time diffusion models, stochastic volatility models, nonlinear time series models, and models with market microstructure noise. PMID:21750601

Mental models accurately predict emotion transitions

PubMed Central

Thornton, Mark A.; Tamir, Diana I.

2017-01-01

Successful social interactions depend on people’s ability to predict others’ future actions and emotions. People possess many mechanisms for perceiving others’ current emotional states, but how might they use this information to predict others’ future states? We hypothesized that people might capitalize on an overlooked aspect of affective experience: current emotions predict future emotions. By attending to regularities in emotion transitions, perceivers might develop accurate mental models of others’ emotional dynamics. People could then use these mental models of emotion transitions to predict others’ future emotions from currently observable emotions. To test this hypothesis, studies 1–3 used data from three extant experience-sampling datasets to establish the actual rates of emotional transitions. We then collected three parallel datasets in which participants rated the transition likelihoods between the same set of emotions. Participants’ ratings of emotion transitions predicted others’ experienced transitional likelihoods with high accuracy. Study 4 demonstrated that four conceptual dimensions of mental state representation—valence, social impact, rationality, and human mind—inform participants’ mental models. Study 5 used 2 million emotion reports on the Experience Project to replicate both of these findings: again people reported accurate models of emotion transitions, and these models were informed by the same four conceptual dimensions. Importantly, neither these conceptual dimensions nor holistic similarity could fully explain participants’ accuracy, suggesting that their mental models contain accurate information about emotion dynamics above and beyond what might be predicted by static emotion knowledge alone. PMID:28533373

Development of state and transition model assumptions used in National Forest Plan revision

Treesearch

Eric B. Henderson

2008-01-01

State and transition models are being utilized in forest management analysis processes to evaluate assumptions about disturbances and succession. These models assume valid information about seral class successional pathways and timing. The Forest Vegetation Simulator (FVS) was used to evaluate seral class succession assumptions for the Hiawatha National Forest in...

Nonequilibrium transitions in complex networks: A model of social interaction

NASA Astrophysics Data System (ADS)

Klemm, Konstantin; Eguíluz, Víctor M.; Toral, Raúl; San Miguel, Maxi

2003-02-01

We analyze the nonequilibrium order-disorder transition of Axelrod’s model of social interaction in several complex networks. In a small-world network, we find a transition between an ordered homogeneous state and a disordered state. The transition point is shifted by the degree of spatial disorder of the underlying network, the network disorder favoring ordered configurations. In random scale-free networks the transition is only observed for finite size systems, showing system size scaling, while in the thermodynamic limit only ordered configurations are always obtained. Thus, in the thermodynamic limit the transition disappears. However, in structured scale-free networks, the phase transition between an ordered and a disordered phase is restored.

Improving the effectiveness of ecological site descriptions: General state-and-transition models and the Ecosystem Dynamics Interpretive Tool (EDIT)

USDA-ARS?s Scientific Manuscript database

State-and-transition models (STMs) were conceived as a means to organize and communicate information about ecosystem changes and how to manage them. Information within STMs applies to ecological land classes, such as ecological sites, that possess similar vegetation states. The value of STMs for ran...

A Semi-analytical Model for Wind-fed Black Hole High-mass X-Ray Binaries: State Transition Triggered by Magnetic Fields from the Companion Star

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

Yaji, Kentaro; Yamada, Shinya; Masai, Kuniaki

We propose a mechanism of state transition in wind-fed black hole (BH) binaries (high-mass X-ray binaries) such as Cyg X-1 and LMC X-1. Modeling a line-driven stellar wind from the companion by two-dimensional hydrodynamical calculations, we investigate the processes of wind capture by, and accretion onto, the BH. We assume that the wind acceleration is terminated at the He ii ionization front because ions responsible for line-driven acceleration are ionized within the front, i.e., the He iii region. It is found that the mass accretion rate inferred from the luminosity is remarkably smaller than the capture rate. Considering the difference,more » we construct a model for the state transition based on the accretion flow being controlled by magnetorotational instability. The outer flow is torus-like, and plays an important role to trigger the transition. The model can explain why state transition does occur in Cyg X-1, while not in LMC X-1. Cyg X-1 exhibits a relatively low luminosity, and then the He ii ionization front is located and can move between the companion and BH, depending on its ionizing photon flux. On the other hand, LMC X-1 exhibits too high luminosity for the front to move considerably; the front is too close to the companion atmosphere. The model also predicts that each state of high-soft or low-hard would last fairly long because the luminosity depends weakly on the wind velocity. In the context of the model, the state transition is triggered by a fluctuation of the magnetic field when its amplitude becomes comparable to the field strength in the torus-like outer flow.« less

Indicators of ecosystem function identify alternate states in the sagebrush steppe.

PubMed

Kachergis, Emily; Rocca, Monique E; Fernandez-Gimenez, Maria E

2011-10-01

Models of ecosystem change that incorporate nonlinear dynamics and thresholds, such as state-and-transition models (STMs), are increasingly popular tools for land management decision-making. However, few models are based on systematic collection and documentation of ecological data, and of these, most rely solely on structural indicators (species composition) to identify states and transitions. As STMs are adopted as an assessment framework throughout the United States, finding effective and efficient ways to create data-driven models that integrate ecosystem function and structure is vital. This study aims to (1) evaluate the utility of functional indicators (indicators of rangeland health, IRH) as proxies for more difficult ecosystem function measurements and (2) create a data-driven STM for the sagebrush steppe of Colorado, USA, that incorporates both ecosystem structure and function. We sampled soils, plant communities, and IRH at 41 plots with similar clayey soils but different site histories to identify potential states and infer the effects of management practices and disturbances on transitions. We found that many IRH were correlated with quantitative measures of functional indicators, suggesting that the IRH can be used to approximate ecosystem function. In addition to a reference state that functions as expected for this soil type, we identified four biotically and functionally distinct potential states, consistent with the theoretical concept of alternate states. Three potential states were related to management practices (chemical and mechanical shrub treatments and seeding history) while one was related only to ecosystem processes (erosion). IRH and potential states were also related to environmental variation (slope, soil texture), suggesting that there are environmental factors within areas with similar soils that affect ecosystem dynamics and should be noted within STMs. Our approach generated an objective, data-driven model of ecosystem dynamics for rangeland management. Our findings suggest that the IRH approximate ecosystem processes and can distinguish between alternate states and communities and identify transitions when building data-driven STMs. Functional indicators are a simple, efficient way to create data-driven models that are consistent with alternate state theory. Managers can use them to improve current model-building methods and thus apply state-and-transition models more broadly for land management decision-making.

Accuracy of maximum likelihood estimates of a two-state model in single-molecule FRET

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

Gopich, Irina V.

2015-01-21

Photon sequences from single-molecule Förster resonance energy transfer (FRET) experiments can be analyzed using a maximum likelihood method. Parameters of the underlying kinetic model (FRET efficiencies of the states and transition rates between conformational states) are obtained by maximizing the appropriate likelihood function. In addition, the errors (uncertainties) of the extracted parameters can be obtained from the curvature of the likelihood function at the maximum. We study the standard deviations of the parameters of a two-state model obtained from photon sequences with recorded colors and arrival times. The standard deviations can be obtained analytically in a special case when themore » FRET efficiencies of the states are 0 and 1 and in the limiting cases of fast and slow conformational dynamics. These results are compared with the results of numerical simulations. The accuracy and, therefore, the ability to predict model parameters depend on how fast the transition rates are compared to the photon count rate. In the limit of slow transitions, the key parameters that determine the accuracy are the number of transitions between the states and the number of independent photon sequences. In the fast transition limit, the accuracy is determined by the small fraction of photons that are correlated with their neighbors. The relative standard deviation of the relaxation rate has a “chevron” shape as a function of the transition rate in the log-log scale. The location of the minimum of this function dramatically depends on how well the FRET efficiencies of the states are separated.« less

Accuracy of maximum likelihood estimates of a two-state model in single-molecule FRET

PubMed Central

Gopich, Irina V.

2015-01-01

Photon sequences from single-molecule Förster resonance energy transfer (FRET) experiments can be analyzed using a maximum likelihood method. Parameters of the underlying kinetic model (FRET efficiencies of the states and transition rates between conformational states) are obtained by maximizing the appropriate likelihood function. In addition, the errors (uncertainties) of the extracted parameters can be obtained from the curvature of the likelihood function at the maximum. We study the standard deviations of the parameters of a two-state model obtained from photon sequences with recorded colors and arrival times. The standard deviations can be obtained analytically in a special case when the FRET efficiencies of the states are 0 and 1 and in the limiting cases of fast and slow conformational dynamics. These results are compared with the results of numerical simulations. The accuracy and, therefore, the ability to predict model parameters depend on how fast the transition rates are compared to the photon count rate. In the limit of slow transitions, the key parameters that determine the accuracy are the number of transitions between the states and the number of independent photon sequences. In the fast transition limit, the accuracy is determined by the small fraction of photons that are correlated with their neighbors. The relative standard deviation of the relaxation rate has a “chevron” shape as a function of the transition rate in the log-log scale. The location of the minimum of this function dramatically depends on how well the FRET efficiencies of the states are separated. PMID:25612692

Exploring sensitivity of a multistate occupancy model to inform management decisions

USGS Publications Warehouse

Green, A.W.; Bailey, L.L.; Nichols, J.D.

2011-01-01

Dynamic occupancy models are often used to investigate questions regarding the processes that influence patch occupancy and are prominent in the fields of population and community ecology and conservation biology. Recently, multistate occupancy models have been developed to investigate dynamic systems involving more than one occupied state, including reproductive states, relative abundance states and joint habitat-occupancy states. Here we investigate the sensitivities of the equilibrium-state distribution of multistate occupancy models to changes in transition rates. We develop equilibrium occupancy expressions and their associated sensitivity metrics for dynamic multistate occupancy models. To illustrate our approach, we use two examples that represent common multistate occupancy systems. The first example involves a three-state dynamic model involving occupied states with and without successful reproduction (California spotted owl Strix occidentalis occidentalis), and the second involves a novel way of using a multistate occupancy approach to accommodate second-order Markov processes (wood frog Lithobates sylvatica breeding and metamorphosis). In many ways, multistate sensitivity metrics behave in similar ways as standard occupancy sensitivities. When equilibrium occupancy rates are low, sensitivity to parameters related to colonisation is high, while sensitivity to persistence parameters is greater when equilibrium occupancy rates are high. Sensitivities can also provide guidance for managers when estimates of transition probabilities are not available. Synthesis and applications. Multistate models provide practitioners a flexible framework to define multiple, distinct occupied states and the ability to choose which state, or combination of states, is most relevant to questions and decisions about their own systems. In addition to standard multistate occupancy models, we provide an example of how a second-order Markov process can be modified to fit a multistate framework. Assuming the system is near equilibrium, our sensitivity analyses illustrate how to investigate the sensitivity of the system-specific equilibrium state(s) to changes in transition rates. Because management will typically act on these transition rates, sensitivity analyses can provide valuable information about the potential influence of different actions and when it may be prudent to shift the focus of management among the various transition rates. ?? 2011 The Authors. Journal of Applied Ecology ?? 2011 British Ecological Society.

Approaches to incorporating climate change effects in state and transition simulation models of vegetation

Treesearch

Becky K. Kerns; Miles A. Hemstrom; David Conklin; Gabriel I. Yospin; Bart Johnson; Dominique Bachelet; Scott Bridgham

2012-01-01

Understanding landscape vegetation dynamics often involves the use of scientifically-based modeling tools that are capable of testing alternative management scenarios given complex ecological, management, and social conditions. State-and-transition simulation model (STSM) frameworks and software such as PATH and VDDT are commonly used tools that simulate how landscapes...

Phase separation and second-order phase transition in the phenomenological model for a Coulomb-frustrated two-dimensional system

NASA Astrophysics Data System (ADS)

Mamin, R. F.; Shaposhnikova, T. S.; Kabanov, V. V.

2018-03-01

We have considered the model of the phase transition of the second order for the Coulomb frustrated 2D charged system. The coupling of the order parameter with the charge was considered as the local temperature. We have found that in such a system, an appearance of the phase-separated state is possible. By numerical simulation, we have obtained different types ("stripes," "rings," "snakes") of phase-separated states and determined the parameter ranges for these states. Thus the system undergoes a series of phase transitions when the temperature decreases. First, the system moves from the homogeneous state with a zero order parameter to the phase-separated state with two phases in one of which the order parameter is zero and, in the other, it is nonzero (τ >0 ). Then a first-order transition occurs to another phase-separated state, in which both phases have different and nonzero values of the order parameter (for τ <0 ). Only a further decrease of temperature leads to a transition to a homogeneous ordered state.

Synaptic plasticity modulates autonomous transitions between waking and sleep states: Insights from a Morris-Lecar model

NASA Astrophysics Data System (ADS)

Ciszak, Marzena; Bellesi, Michele

2011-12-01

The transitions between waking and sleep states are characterized by considerable changes in neuronal firing. During waking, neurons fire tonically at irregular intervals and a desynchronized activity is observed at the electroencephalogram. This activity becomes synchronized with slow wave sleep onset when neurons start to oscillate between periods of firing (up-states) and periods of silence (down-states). Recently, it has been proposed that the connections between neurons undergo potentiation during waking, whereas they weaken during slow wave sleep. Here, we propose a dynamical model to describe basic features of the autonomous transitions between such states. We consider a network of coupled neurons in which the strength of the interactions is modulated by synaptic long term potentiation and depression, according to the spike time-dependent plasticity rule (STDP). The model shows that the enhancement of synaptic strength between neurons occurring in waking increases the propensity of the network to synchronize and, conversely, desynchronization appears when the strength of the connections become weaker. Both transitions appear spontaneously, but the transition from sleep to waking required a slight modification of the STDP rule with the introduction of a mechanism which becomes active during sleep and changes the proportion between potentiation and depression in accordance with biological data. At the neuron level, transitions from desynchronization to synchronization and vice versa can be described as a bifurcation between two different states, whose dynamical regime is modulated by synaptic strengths, thus suggesting that transition from a state to an another can be determined by quantitative differences between potentiation and depression.

Encapsulating model complexity and landscape-scale analyses of state-and-transition simulation models: an application of ecoinformatics and juniper encroachment in sagebrush steppe ecosystems

USGS Publications Warehouse

O'Donnell, Michael

2015-01-01

State-and-transition simulation modeling relies on knowledge of vegetation composition and structure (states) that describe community conditions, mechanistic feedbacks such as fire that can affect vegetation establishment, and ecological processes that drive community conditions as well as the transitions between these states. However, as the need for modeling larger and more complex landscapes increase, a more advanced awareness of computing resources becomes essential. The objectives of this study include identifying challenges of executing state-and-transition simulation models, identifying common bottlenecks of computing resources, developing a workflow and software that enable parallel processing of Monte Carlo simulations, and identifying the advantages and disadvantages of different computing resources. To address these objectives, this study used the ApexRMS® SyncroSim software and embarrassingly parallel tasks of Monte Carlo simulations on a single multicore computer and on distributed computing systems. The results demonstrated that state-and-transition simulation models scale best in distributed computing environments, such as high-throughput and high-performance computing, because these environments disseminate the workloads across many compute nodes, thereby supporting analysis of larger landscapes, higher spatial resolution vegetation products, and more complex models. Using a case study and five different computing environments, the top result (high-throughput computing versus serial computations) indicated an approximate 96.6% decrease of computing time. With a single, multicore compute node (bottom result), the computing time indicated an 81.8% decrease relative to using serial computations. These results provide insight into the tradeoffs of using different computing resources when research necessitates advanced integration of ecoinformatics incorporating large and complicated data inputs and models. - See more at: http://aimspress.com/aimses/ch/reader/view_abstract.aspx?file_no=Environ2015030&flag=1#sthash.p1XKDtF8.dpuf

Analysis of phase transitions in spin-crossover compounds by using atom - phonon coupling model

NASA Astrophysics Data System (ADS)

Gîndulescu, A.; Rotaru, A.; Linares, J.; Dimian, M.; Nasser, J.

2011-01-01

The spin - crossover compounds (SCO) have become of great interest recently due to their potential applications in memories, sensors, switches, and display devices. These materials are particularly interesting because upon application of heat, light, pressure or other physical stimulus, they feature a phase transition between a low-spin (LS) diamagnetic ground state and a high-spin (HS) paramagnetic state, accompanied in some cases by color change. The phase transition can be discontinuous (with hysteresis), in two steps or gradual. Our analysis is performed by using the atom - phonon coupling (APC) model which considers that neighboring molecules are connected through a spring characterized by an elastic constant depending on molecules electronic state. By associating a fictitious spin to each molecule that has -1 and +1 eigenvalues corresponding to LS and HS levels respectively, an Ising type model can be developed for the analysis of metastable states and phase transitions in spin-crossover compounds. This contribution is aimed at providing a review of our recent results in this area, as well as novel aspects related to SCO compounds behavior at low temperature. In the framework of the APC model, we will discuss about the existence of metastable and unstable states, phase transitions and hysteresis phenomena, as well as their dependence on sample size.

An algorithm for minimum-cost set-point ordering in a cryogenic wind tunnel

NASA Technical Reports Server (NTRS)

Tripp, J. S.

1981-01-01

An algorithm for minimum cost ordering of set points in a cryogenic wind tunnel is developed. The procedure generates a matrix of dynamic state transition costs, which is evaluated by means of a single-volume lumped model of the cryogenic wind tunnel and the use of some idealized minimum-costs, which is evaluated by means of a single-volume lumped model of the cryogenic wind tunnel and the use of some idealized minimum-cost state-transition control strategies. A branch and bound algorithm is employed to determine the least costly sequence of state transitions from the transition-cost matrix. Some numerical results based on data for the National Transonic Facility are presented which show a strong preference for state transitions that consume to coolant. Results also show that the choice of the terminal set point in an open odering can produce a wide variation in total cost.

Spin dependence of intra-ground-state-band E2 transitions in the SU(3) limit of the sdg interacting boson model

NASA Astrophysics Data System (ADS)

Long, G. L.; Ji, H. Y.

1998-04-01

B(E2, L+2-->L) transitions in the sdg interacting boson model SU(3) limit are studied with a general E2 transition operator. Analytical expressions are obtained using a group theoretic method. It is found that when using transition operators of the form (d†g~+g†d~)2 or (g†g~)2, the B(E2, L+2-->L) values in the ground-state band have an L(L+3) dependent term. As L increases, the B(E2) values can be larger than the rigid rotor model value. Application to 236,238U is discussed.

A Closed-Loop Model of Operator Visual Attention, Situation Awareness, and Performance Across Automation Mode Transitions.

PubMed

Johnson, Aaron W; Duda, Kevin R; Sheridan, Thomas B; Oman, Charles M

2017-03-01

This article describes a closed-loop, integrated human-vehicle model designed to help understand the underlying cognitive processes that influenced changes in subject visual attention, mental workload, and situation awareness across control mode transitions in a simulated human-in-the-loop lunar landing experiment. Control mode transitions from autopilot to manual flight may cause total attentional demands to exceed operator capacity. Attentional resources must be reallocated and reprioritized, which can increase the average uncertainty in the operator's estimates of low-priority system states. We define this increase in uncertainty as a reduction in situation awareness. We present a model built upon the optimal control model for state estimation, the crossover model for manual control, and the SEEV (salience, effort, expectancy, value) model for visual attention. We modify the SEEV attention executive to direct visual attention based, in part, on the uncertainty in the operator's estimates of system states. The model was validated using the simulated lunar landing experimental data, demonstrating an average difference in the percentage of attention ≤3.6% for all simulator instruments. The model's predictions of mental workload and situation awareness, measured by task performance and system state uncertainty, also mimicked the experimental data. Our model supports the hypothesis that visual attention is influenced by the uncertainty in system state estimates. Conceptualizing situation awareness around the metric of system state uncertainty is a valuable way for system designers to understand and predict how reallocations in the operator's visual attention during control mode transitions can produce reallocations in situation awareness of certain states.

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.

Applying Ecological Site Concepts and State-and-Transition Models to a Grazed Riparian Rangeland

USDA-ARS?s Scientific Manuscript database

Ecological site and state-and-transition models are useful tools for generating and testing hypotheses about drivers of vegetation composition in non-equilibrium systems, and have been widely implemented on rangelands. Compared to upland areas, little attention has been given to developing ecologica...

What can one learn from experiments about the elusive transition state?

PubMed Central

Chang, Iksoo; Cieplak, Marek; Banavar, Jayanth R.; Maritan, Amos

2004-01-01

We present the results of an exact analysis of a model energy landscape of a protein to clarify the idea of the transition state and the physical meaning of the φ values determined in protein engineering experiments. We benchmark our findings to various theoretical approaches proposed in the literature for the identification and characterization of the transition state. PMID:15295118

An atomic model for neutral and singly ionized uranium

NASA Technical Reports Server (NTRS)

Maceda, E. L.; Miley, G. H.

1979-01-01

A model for the atomic levels above ground state in neutral, U(0), and singly ionized, U(+), uranium is described based on identified atomic transitions. Some 168 states in U(0) and 95 in U(+) are found. A total of 1581 atomic transitions are used to complete this process. Also discussed are the atomic inverse lifetimes and line widths for the radiative transitions as well as the electron collisional cross sections.

Assessment of variations in control of asthma over time.

PubMed

Combescure, C; Chanez, P; Saint-Pierre, P; Daurès, J P; Proudhon, H; Godard, P

2003-08-01

Control and severity of asthma are two different but complementary concepts. The severity of asthma could influence the control over time. The aim of this study was to demonstrate this relationship. A total 365 patients with persistent asthma (severity) were enrolled and followed-up prospectively. Data were analysed using a continuous time homogeneous Markov model of the natural history of asthma. Control of asthma was defined according to three health states which were qualified: optimal, suboptimal and unacceptable control (states 1, 2 and 3). Transition forces (denoted lambda(ij) from state i to state j) and transition probabilities between control states were assessed and the results stratified by asthma severity were compared. Models were validated by comparing expected and observed numbers of patients in the different states. Transition probabilities stabilised between 100-250 days and more rapidly in patients with mild-to-moderate asthma. Patients with mild-to-moderate asthma in suboptimal or unacceptable control had a high probability of transition directly to optimal control. Patients with severe asthma had a tendency to remain in unacceptable control. A Markov model is a useful tool to model the control of asthma over time. Severity modified clearly the health states. It could be used to compare the performance of different approaches to asthma management.

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

USGS Publications Warehouse

Zweig, Christa L.; Kitchens, Wiley M.

2009-01-01

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

Information cascade on networks

NASA Astrophysics Data System (ADS)

Hisakado, Masato; Mori, Shintaro

2016-05-01

In this paper, we discuss a voting model by considering three different kinds of networks: a random graph, the Barabási-Albert (BA) model, and a fitness model. A voting model represents the way in which public perceptions are conveyed to voters. Our voting model is constructed by using two types of voters-herders and independents-and two candidates. Independents conduct voting based on their fundamental values; on the other hand, herders base their voting on the number of previous votes. Hence, herders vote for the majority candidates and obtain information relating to previous votes from their networks. We discuss the difference between the phases on which the networks depend. Two kinds of phase transitions, an information cascade transition and a super-normal transition, were identified. The first of these is a transition between a state in which most voters make the correct choices and a state in which most of them are wrong. The second is a transition of convergence speed. The information cascade transition prevails when herder effects are stronger than the super-normal transition. In the BA and fitness models, the critical point of the information cascade transition is the same as that of the random network model. However, the critical point of the super-normal transition disappears when these two models are used. In conclusion, the influence of networks is shown to only affect the convergence speed and not the information cascade transition. We are therefore able to conclude that the influence of hubs on voters' perceptions is limited.

Design of biomimetic catalysts by molecular imprinting in synthetic polymers: the role of transition state stabilization.

PubMed

Wulff, Günter; Liu, Junqiu

2012-02-21

The impressive efficiency and selectivity of biological catalysts has engendered a long-standing effort to understand the details of enzyme action. It is widely accepted that enzymes accelerate reactions through their steric and electronic complementarity to the reactants in the rate-determining transition states. Thus, tight binding to the transition state of a reactant (rather than to the corresponding substrate) lowers the activation energy of the reaction, providing strong catalytic activity. Debates concerning the fundamentals of enzyme catalysis continue, however, and non-natural enzyme mimics offer important additional insight in this area. Molecular structures that mimic enzymes through the design of a predetermined binding site that stabilizes the transition state of a desired reaction are invaluable in this regard. Catalytic antibodies, which can be quite active when raised against stable transition state analogues of the corresponding reaction, represent particularly successful examples. Recently, synthetic chemistry has begun to match nature's ability to produce antibody-like binding sites with high affinities for the transition state. Thus, synthetic, molecularly imprinted polymers have been engineered to provide enzyme-like specificity and activity, and they now represent a powerful tool for creating highly efficient catalysts. In this Account, we review recent efforts to develop enzyme models through the concept of transition state stabilization. In particular, models for carboxypeptidase A were prepared through the molecular imprinting of synthetic polymers. On the basis of successful experiments with phosphonic esters as templates to arrange amidinium groups in the active site, the method was further improved by combining the concept of transition state stabilization with the introduction of special catalytic moieties, such as metal ions in a defined orientation in the active site. In this way, the imprinted polymers were able to provide both an electrostatic stabilization for the transition state through the amidinium group as well as a synergism of transition state recognition and metal ion catalysis. The result was an excellent catalyst for carbonate hydrolysis. These enzyme mimics represent the most active catalysts ever prepared through the molecular imprinting strategy. Their catalytic activity, catalytic efficiency, and catalytic proficiency clearly surpass those of the corresponding catalytic antibodies. The active structures in natural enzymes evolve within soluble proteins, typically by the refining of the folding of one polypeptide chain. To incorporate these characteristics into synthetic polymers, we used the concept of transition state stabilization to develop soluble, nanosized carboxypeptidase A models using a new polymerization method we term the "post-dilution polymerization method". With this methodology, we were able to prepare soluble, highly cross-linked, single-molecule nanoparticles. These particles have controlled molecular weights (39 kDa, for example) and, on average, one catalytically active site per particle. Our strategies have made it possible to obtain efficient new enzyme models and further advance the structural and functional analogy with natural enzymes. Moreover, this bioinspired design based on molecular imprinting in synthetic polymers offers further support for the concept of transition state stabilization in catalysis.

Complex transitions between spike, burst or chaos synchronization states in coupled neurons with coexisting bursting patterns

NASA Astrophysics Data System (ADS)

Gu, Hua-Guang; Chen, Sheng-Gen; Li, Yu-Ye

2015-05-01

We investigated the synchronization dynamics of a coupled neuronal system composed of two identical Chay model neurons. The Chay model showed coexisting period-1 and period-2 bursting patterns as a parameter and initial values are varied. We simulated multiple periodic and chaotic bursting patterns with non-(NS), burst phase (BS), spike phase (SS), complete (CS), and lag synchronization states. When the coexisting behavior is near period-2 bursting, the transitions of synchronization states of the coupled system follows very complex transitions that begins with transitions between BS and SS, moves to transitions between CS and SS, and to CS. Most initial values lead to the CS state of period-2 bursting while only a few lead to the CS state of period-1 bursting. When the coexisting behavior is near period-1 bursting, the transitions begin with NS, move to transitions between SS and BS, to transitions between SS and CS, and then to CS. Most initial values lead to the CS state of period-1 bursting but a few lead to the CS state of period-2 bursting. The BS was identified as chaos synchronization. The patterns for NS and transitions between BS and SS are insensitive to initial values. The patterns for transitions between CS and SS and the CS state are sensitive to them. The number of spikes per burst of non-CS bursting increases with increasing coupling strength. These results not only reveal the initial value- and parameter-dependent synchronization transitions of coupled systems with coexisting behaviors, but also facilitate interpretation of various bursting patterns and synchronization transitions generated in the nervous system with weak coupling strength. Project supported by the National Natural Science Foundation of China (Grant Nos. 11372224 and 11402039) and the Fundamental Research Funds for Central Universities designated to Tongji University (Grant No. 1330219127).

Integrating Ecosystem Carbon Dynamics into State-and-Transition Simulation Models of Land Use/Land Cover Change

NASA Astrophysics Data System (ADS)

Sleeter, B. M.; Daniel, C.; Frid, L.; Fortin, M. J.

2016-12-01

State-and-transition simulation models (STSMs) provide a general approach for incorporating uncertainty into forecasts of landscape change. Using a Monte Carlo approach, STSMs generate spatially-explicit projections of the state of a landscape based upon probabilistic transitions defined between states. While STSMs are based on the basic principles of Markov chains, they have additional properties that make them applicable to a wide range of questions and types of landscapes. A current limitation of STSMs is that they are only able to track the fate of discrete state variables, such as land use/land cover (LULC) classes. There are some landscape modelling questions, however, for which continuous state variables - for example carbon biomass - are also required. Here we present a new approach for integrating continuous state variables into spatially-explicit STSMs. Specifically we allow any number of continuous state variables to be defined for each spatial cell in our simulations; the value of each continuous variable is then simulated forward in discrete time as a stochastic process based upon defined rates of change between variables. These rates can be defined as a function of the realized states and transitions of each cell in the STSM, thus providing a connection between the continuous variables and the dynamics of the landscape. We demonstrate this new approach by (1) developing a simple IPCC Tier 3 compliant model of ecosystem carbon biomass, where the continuous state variables are defined as terrestrial carbon biomass pools and the rates of change as carbon fluxes between pools, and (2) integrating this carbon model with an existing LULC change model for the state of Hawaii, USA.

A comparison between state-specific and linear-response formalisms for the calculation of vertical electronic transition energy in solution with the CCSD-PCM method.

PubMed

Caricato, Marco

2013-07-28

The calculation of vertical electronic transition energies of molecular systems in solution with accurate quantum mechanical methods requires the use of approximate and yet reliable models to describe the effect of the solvent on the electronic structure of the solute. The polarizable continuum model (PCM) of solvation represents a computationally efficient way to describe this effect, especially when combined with coupled cluster (CC) methods. Two formalisms are available to compute transition energies within the PCM framework: State-Specific (SS) and Linear-Response (LR). The former provides a more complete account of the solute-solvent polarization in the excited states, while the latter is computationally very efficient (i.e., comparable to gas phase) and transition properties are well defined. In this work, I review the theory for the two formalisms within CC theory with a focus on their computational requirements, and present the first implementation of the LR-PCM formalism with the coupled cluster singles and doubles method (CCSD). Transition energies computed with LR- and SS-CCSD-PCM are presented, as well as a comparison between solvation models in the LR approach. The numerical results show that the two formalisms provide different absolute values of transition energy, but similar relative solvatochromic shifts (from nonpolar to polar solvents). The LR formalism may then be used to explore the solvent effect on multiple states and evaluate transition probabilities, while the SS formalism may be used to refine the description of specific states and for the exploration of excited state potential energy surfaces of solvated systems.

Bifurcation analysis and dimension reduction of a predator-prey model for the L-H transition

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

Dam, Magnus; Brøns, Morten; Juul Rasmussen, Jens

2013-10-15

The L-H transition denotes a shift to an improved confinement state of a toroidal plasma in a fusion reactor. A model of the L-H transition is required to simulate the time dependence of tokamak discharges that include the L-H transition. A 3-ODE predator-prey type model of the L-H transition is investigated with bifurcation theory of dynamical systems. The analysis shows that the model contains three types of transitions: an oscillating transition, a sharp transition with hysteresis, and a smooth transition. The model is recognized as a slow-fast system. A reduced 2-ODE model consisting of the full model restricted to themore » flow on the critical manifold is found to contain all the same dynamics as the full model. This means that all the dynamics in the system is essentially 2-dimensional, and a minimal model of the L-H transition could be a 2-ODE model.« less

Exploring the Conformational Transitions of Biomolecular Systems Using a Simple Two-State Anisotropic Network Model

PubMed Central

Jo, Sunhwan; Bahar, Ivet; Roux, Benoît

2014-01-01

Biomolecular conformational transitions are essential to biological functions. Most experimental methods report on the long-lived functional states of biomolecules, but information about the transition pathways between these stable states is generally scarce. Such transitions involve short-lived conformational states that are difficult to detect experimentally. For this reason, computational methods are needed to produce plausible hypothetical transition pathways that can then be probed experimentally. Here we propose a simple and computationally efficient method, called ANMPathway, for constructing a physically reasonable pathway between two endpoints of a conformational transition. We adopt a coarse-grained representation of the protein and construct a two-state potential by combining two elastic network models (ENMs) representative of the experimental structures resolved for the endpoints. The two-state potential has a cusp hypersurface in the configuration space where the energies from both the ENMs are equal. We first search for the minimum energy structure on the cusp hypersurface and then treat it as the transition state. The continuous pathway is subsequently constructed by following the steepest descent energy minimization trajectories starting from the transition state on each side of the cusp hypersurface. Application to several systems of broad biological interest such as adenylate kinase, ATP-driven calcium pump SERCA, leucine transporter and glutamate transporter shows that ANMPathway yields results in good agreement with those from other similar methods and with data obtained from all-atom molecular dynamics simulations, in support of the utility of this simple and efficient approach. Notably the method provides experimentally testable predictions, including the formation of non-native contacts during the transition which we were able to detect in two of the systems we studied. An open-access web server has been created to deliver ANMPathway results. PMID:24699246

Characterization of Dynamical Phase Transitions in Quantum Jump Trajectories Beyond the Properties of the Stationary State

NASA Astrophysics Data System (ADS)

Lesanovsky, Igor; van Horssen, Merlijn; Guţă, Mădălin; Garrahan, Juan P.

2013-04-01

We describe how to characterize dynamical phase transitions in open quantum systems from a purely dynamical perspective, namely, through the statistical behavior of quantum jump trajectories. This approach goes beyond considering only properties of the steady state. While in small quantum systems dynamical transitions can only occur trivially at limiting values of the controlling parameters, in many-body systems they arise as collective phenomena and within this perspective they are reminiscent of thermodynamic phase transitions. We illustrate this in open models of increasing complexity: a three-level system, the micromaser, and a dissipative version of the quantum Ising model. In these examples dynamical transitions are accompanied by clear changes in static behavior. This is however not always the case, and, in general, dynamical phases need to be uncovered by observables which are strictly dynamical, e.g., dynamical counting fields. We demonstrate this via the example of a class of models of dissipative quantum glasses, whose dynamics can vary widely despite having identical (and trivial) stationary states.

Two-Dimensional Wetting Transition Modeling with the Potts Model

NASA Astrophysics Data System (ADS)

Lopes, Daisiane M.; Mombach, José C. M.

2017-12-01

A droplet of a liquid deposited on a surface structured in pillars may have two states of wetting: (1) Cassie-Baxter (CB), the liquid remains on top of the pillars, also known as heterogeneous wetting, or (2) Wenzel, the liquid fills completely the cavities of the surface, also known as homogeneous wetting. Studies show that between these two states, there is an energy barrier that, when overcome, results in the transition of states. The transition can be achieved by changes in geometry parameters of the surface, by vibrations of the surface or by evaporation of the liquid. In this paper, we present a comparison of two-dimensional simulations of the Cassie-Wenzel transition on pillar-structured surfaces using the cellular Potts model (CPM) with studies performed by Shahraz et al. In our work, we determine a transition diagram by varying the surface parameters such as the interpillar distance ( G) and the pillar height ( H). Our results were compared to those obtained by Shahraz et al. obtaining good agreement.

Characterization of dynamical phase transitions in quantum jump trajectories beyond the properties of the stationary state.

PubMed

Lesanovsky, Igor; van Horssen, Merlijn; Guţă, Mădălin; Garrahan, Juan P

2013-04-12

We describe how to characterize dynamical phase transitions in open quantum systems from a purely dynamical perspective, namely, through the statistical behavior of quantum jump trajectories. This approach goes beyond considering only properties of the steady state. While in small quantum systems dynamical transitions can only occur trivially at limiting values of the controlling parameters, in many-body systems they arise as collective phenomena and within this perspective they are reminiscent of thermodynamic phase transitions. We illustrate this in open models of increasing complexity: a three-level system, the micromaser, and a dissipative version of the quantum Ising model. In these examples dynamical transitions are accompanied by clear changes in static behavior. This is however not always the case, and, in general, dynamical phases need to be uncovered by observables which are strictly dynamical, e.g., dynamical counting fields. We demonstrate this via the example of a class of models of dissipative quantum glasses, whose dynamics can vary widely despite having identical (and trivial) stationary states.

Testing a Theoretical Model of Immigration Transition and Physical Activity.

PubMed

Chang, Sun Ju; Im, Eun-Ok

2015-01-01

The purposes of the study were to develop a theoretical model to explain the relationships between immigration transition and midlife women's physical activity and test the relationships among the major variables of the model. A theoretical model, which was developed based on transitions theory and the midlife women's attitudes toward physical activity theory, consists of 4 major variables, including length of stay in the United States, country of birth, level of acculturation, and midlife women's physical activity. To test the theoretical model, a secondary analysis with data from 127 Hispanic women and 123 non-Hispanic (NH) Asian women in a national Internet study was used. Among the major variables of the model, length of stay in the United States was negatively associated with physical activity in Hispanic women. Level of acculturation in NH Asian women was positively correlated with women's physical activity. Country of birth and level of acculturation were significant factors that influenced physical activity in both Hispanic and NH Asian women. The findings support the theoretical model that was developed to examine relationships between immigration transition and physical activity; it shows that immigration transition can play an essential role in influencing health behaviors of immigrant populations in the United States. The NH theoretical model can be widely used in nursing practice and research that focus on immigrant women and their health behaviors. Health care providers need to consider the influences of immigration transition to promote immigrant women's physical activity.

Conformational transition in signal transduction: metastable states and transition pathways in the activation of a signaling protein.

PubMed

Banerjee, Rahul; Yan, Honggao; Cukier, Robert I

2015-06-04

Signal transduction is of vital importance to the growth and adaptation of living organisms. The key to understand mechanisms of biological signal transduction is elucidation of the conformational dynamics of its signaling proteins, as the activation of a signaling protein is fundamentally a process of conformational transition from an inactive to an active state. A predominant form of signal transduction for bacterial sensing of environmental changes in the wild or inside their hosts is a variety of two-component systems, in which the conformational transition of a response regulator (RR) from an inactive to an active state initiates responses to the environmental changes. Here, RR activation has been investigated using RR468 as a model system by extensive unbiased all-atom molecular dynamics (MD) simulations in explicit solvent, starting from snapshots along a targeted MD trajectory that covers the conformational transition. Markov state modeling, transition path theory, and geometric analyses of the wealth of the MD data have provided a comprehensive description of the RR activation. It involves a network of metastable states, with one metastable state essentially the same as the inactive state and another very similar to the active state that are connected via a small set of intermediates. Five major pathways account for >75% of the fluxes of the conformational transition from the inactive to the active-like state. The thermodynamic stability of the states and the activation barriers between states are found, to identify rate-limiting steps. The conformal transition is initiated predominantly by movements of the β3α3 loop, followed by movements of the β4α4-loop and neighboring α4 helix region, and capped by additional movements of the β3α3 loop. A number of transient hydrophobic and hydrogen bond interactions are revealed, and they may be important for the conformational transition.

Developing ecological site and state-and-transition models for grazed riparian pastures at Tejon Ranch, California

Treesearch

Felix P. Ratcliff; James Bartolome; Michele Hammond; Sheri Spiegal; Michael White

2015-01-01

Ecological site descriptions and associated state-and-transition models are useful tools for understanding the variable effects of management and environment on range resources. Models for woody riparian sites have yet to be fully developed. At Tejon Ranch, in the southern San Joaquin Valley of California, we are using ecological site theory to investigate the role of...

Modeling the dynamic responses of riparian vegetation and salmon habitat in the Oregon Coast Range with state-and-transition models

Treesearch

Steven M. Wondzell; Agnieszka Przeszlowska; Dirk Pflugmacher; Miles A. Hemstrom; Peter A. Bisson

2012-01-01

Interactions between landuse and ecosystem change are complex, especially in riparian zones. To date, few models are available to project the influence of alternative landuse practices, natural disturbance and plant succession on the likely future conditions of riparian zones and aquatic habitats across large spatial extents. A state and transition approach was used to...

Performance and state-space analyses of systems using Petri nets

NASA Technical Reports Server (NTRS)

Watson, James Francis, III

1992-01-01

The goal of any modeling methodology is to develop a mathematical description of a system that is accurate in its representation and also permits analysis of structural and/or performance properties. Inherently, trade-offs exist between the level detail in the model and the ease with which analysis can be performed. Petri nets (PN's), a highly graphical modeling methodology for Discrete Event Dynamic Systems, permit representation of shared resources, finite capacities, conflict, synchronization, concurrency, and timing between state changes. By restricting the state transition time delays to the family of exponential density functions, Markov chain analysis of performance problems is possible. One major drawback of PN's is the tendency for the state-space to grow rapidly (exponential complexity) compared to increases in the PN constructs. It is the state space, or the Markov chain obtained from it, that is needed in the solution of many problems. The theory of state-space size estimation for PN's is introduced. The problem of state-space size estimation is defined, its complexities are examined, and estimation algorithms are developed. Both top-down and bottom-up approaches are pursued, and the advantages and disadvantages of each are described. Additionally, the author's research in non-exponential transition modeling for PN's is discussed. An algorithm for approximating non-exponential transitions is developed. Since only basic PN constructs are used in the approximation, theory already developed for PN's remains applicable. Comparison to results from entropy theory show the transition performance is close to the theoretic optimum. Inclusion of non-exponential transition approximations improves performance results at the expense of increased state-space size. The state-space size estimation theory provides insight and algorithms for evaluating this trade-off.

Local entanglement entropy of fermions as a marker of quantum phase transition in the one-dimensional Hubbard model

NASA Astrophysics Data System (ADS)

Cha, Min-Chul; Chung, Myung-Hoon

2018-05-01

We study quantum phase transition of interacting fermions by measuring the local entanglement entropy in the one-dimensional Hubbard model. The reduced density matrices for blocks of a few sites are constructed from the ground state wave function in infinite systems by adopting the matrix product state representation where time-evolving block decimations are performed to obtain the lowest energy states. The local entanglement entropy, constructed from the reduced density matrices, as a function of the chemical potential shows clear signatures of the Mott transition. The value of the central charge, numerically determined from the universal properties of the local entanglement entropy, confirms that the transition is caused by the suppression of the charge degrees of freedom.

Kinetic Analysis for Macrocyclizations Involving Anionic Template at the Transition State

PubMed Central

Martí-Centelles, Vicente; Burguete, M. Isabel; Luis, Santiago V.

2012-01-01

Several kinetic models for the macrocyclization of a C2 pseudopeptide with a dihalide through a SN2 reaction have been developed. These models not only focus on the kinetic analysis of the main macrocyclization reaction, but also consider the competitive oligomerization/polymerization processes yielding undesired oligomeric/polymeric byproducts. The effect of anions has also been included in the kinetic models, as they can act as catalytic templates in the transition state reducing and stabilizing the transition state. The corresponding differential equation systems for each kinetic model can be solved numerically. Through a comprehensive analysis of these results, it is possible to obtain a better understanding of the different parameters that are involved in the macrocyclization reaction mechanism and to develop strategies for the optimization of the desired processes. PMID:22666148

Early-warning signals for catastrophic soil degradation

NASA Astrophysics Data System (ADS)

Karssenberg, Derek

2010-05-01

Many earth systems have critical thresholds at which the system shifts abruptly from one state to another. Such critical transitions have been described, among others, for climate, vegetation, animal populations, and geomorphology. Predicting the timing of critical transitions before they are reached is of importance because of the large impact on nature and society associated with the transition. However, it is notably difficult to predict the timing of a transition. This is because the state variables of the system show little change before the threshold is reached. As a result, the precision of field observations is often too low to provide predictions of the timing of a transition. A possible solution is the use of spatio-temporal patterns in state variables as leading indicators of a transition. It is becoming clear that the critically slowing down of a system causes spatio-temporal autocorrelation and variance to increase before the transition. Thus, spatio-temporal patterns are important candidates for early-warning signals. In this research we will show that these early-warning signals also exist in geomorphological systems. We consider a modelled vegetation-soil system under a gradually increasing grazing pressure causing an abrupt shift towards extensive soil degradation. It is shown that changes in spatio-temporal patterns occur well ahead of this catastrophic transition. A distributed model describing the coupled processes of vegetation growth and geomorphological denudation is adapted. The model uses well-studied simple process representations for vegetation and geomorphology. A logistic growth model calculates vegetation cover as a function of grazing pressure and vegetation growth rate. Evolution of the soil thickness is modelled by soil creep and wash processes, as a function of net rain reaching the surface. The vegetation and soil system are coupled by 1) decreasing vegetation growth with decreasing soil thickness and 2) increasing soil wash with decreasing vegetation cover. The model describes a critical, catastrophic transition of an underexploited system with low grazing pressure towards an overexploited system. The underexploited state has high vegetation cover and well developed soils, while the overexploited state has low vegetation cover and largely degraded soils. We first show why spatio-temporal patterns in vegetation cover, morphology, erosion rate, and sediment load should be expected to change well before the critical transition towards the overexploited state. Subsequently, spatio-temporal patterns are quantified by calculating statistics, in particular first order statistics and autocorrelation in space and time. It is shown that these statistics gradually change before the transition is reached. This indicates that the statistics may serve as early-warning signals in real-world applications. We also discuss the potential use of remote sensing to predict the critical transition in real-world landscapes.

M1 transitions between low-lying states in the sdg-IBM-2

NASA Astrophysics Data System (ADS)

Casperson, Robert; Werner, Volker

2006-10-01

The interplay between collective and single-particle degrees of freedom for nuclei in the A=90 region have recently been under investigation. In Molybdenum and Ruthenium nuclei, collective symmetric and mixed-symmetric structures have been identified, while in Zirconium, underlying shell-structure plays an enhanced role. Collective symmetric structures appear when protons and neutrons are in phase, whereas mixed-symmetric structures occur when they are not. The one-phonon 2^+ mixed-symmetric state was identified from strong M1 transitions to the 2^+1 state. Similar transitions were observed between higher-spin states, and are predicted by the shell model. These phenomena will be investigated within the sdg Interacting Boson Model 2 in order to obtain a better understanding about the structure of the states involved, and results from first model calculations will be presented. Work supported by US DOE under grant number DE-FG02-91ER-40609.

Markov-chain model of classified atomistic transition states for discrete kinetic Monte Carlo simulations.

PubMed

Numazawa, Satoshi; Smith, Roger

2011-10-01

Classical harmonic transition state theory is considered and applied in discrete lattice cells with hierarchical transition levels. The scheme is then used to determine transitions that can be applied in a lattice-based kinetic Monte Carlo (KMC) atomistic simulation model. The model results in an effective reduction of KMC simulation steps by utilizing a classification scheme of transition levels for thermally activated atomistic diffusion processes. Thermally activated atomistic movements are considered as local transition events constrained in potential energy wells over certain local time periods. These processes are represented by Markov chains of multidimensional Boolean valued functions in three-dimensional lattice space. The events inhibited by the barriers under a certain level are regarded as thermal fluctuations of the canonical ensemble and accepted freely. Consequently, the fluctuating system evolution process is implemented as a Markov chain of equivalence class objects. It is shown that the process can be characterized by the acceptance of metastable local transitions. The method is applied to a problem of Au and Ag cluster growth on a rippled surface. The simulation predicts the existence of a morphology-dependent transition time limit from a local metastable to stable state for subsequent cluster growth by accretion. Excellent agreement with observed experimental results is obtained.

Transitions between strongly correlated and random steady-states for catalytic CO-oxidation on surfaces at high-pressure

DOE PAGES

Liu, Da -Jiang; Evans, James W.

2015-04-02

We explore simple lattice-gas reaction models for CO-oxidation on 1D and 2D periodic arrays of surface adsorption sites. The models are motivated by studies of CO-oxidation on RuO 2(110) at high-pressures. Although adspecies interactions are neglected, the effective absence of adspecies diffusion results in kinetically-induced spatial correlations. A transition occurs from a random mainly CO-populated steady-state at high CO-partial pressure p CO, to a strongly-correlated near-O-covered steady-state for low p CO as noted. In addition, we identify a second transition to a random near-O-covered steady-state at very low p CO.

Relativistic Coulomb excitation of 88Kr

NASA Astrophysics Data System (ADS)

Moschner, K.; Blazhev, A.; Jolie, J.; Warr, N.; Boutachkov, P.; Bednarczyk, P.; Sieja, K.; Algora, A.; Ameil, F.; Bentley, M. A.; Brambilla, S.; Braun, N.; Camera, F.; Cederkäll, J.; Corsi, A.; Danchev, M.; DiJulio, D.; Fahlander, C.; Gerl, J.; Giaz, A.; Golubev, P.; Górska, M.; Grebosz, J.; Habermann, T.; Hackstein, M.; Hoischen, R.; Kojouharov, I.; Kurz, N.; Mǎrginean, N.; Merchán, E.; Möller, T.; Naqvi, F.; Nara Singh, B. S.; Nociforo, C.; Pietralla, N.; Pietri, S.; Podolyák, Zs.; Prochazka, A.; Reese, M.; Reiter, P.; Rudigier, M.; Rudolph, D.; Sava, T.; Schaffner, H.; Scruton, L.; Taprogge, J.; Thomas, T.; Weick, H.; Wendt, A.; Wieland, O.; Wollersheim, H.-J.

2016-11-01

To investigate the systematics of mixed-symmetry states in N =52 isotones, a relativistic Coulomb excitation experiment was performed during the PreSPEC campaign at the GSI Helmholtzzentrum für Schwerionenforschung to determine E 2 transition strengths to 2+ states of the radioactive nucleus 88Kr. Absolute transition rates could be measured towards the first and third 2+ states. For the latter a mixed-symmetry character is suggested on the basis of the indication for a strong M 1 transition to the fully symmetric 21+ state, extending the knowledge of the N =52 isotones below Z =40 . A comparison with the proton-neutron interacting boson model and shell-model predictions is made and supports the assignment.

Characterizing longitudinal health state transitions among heroin, cocaine, and methamphetamine users

PubMed Central

Nosyk, B; Li, L; Evans, E; Huang, D; Min, J; Kerr, T; Brecht, ML; Hser, YI

2014-01-01

Aims Characterize longitudinal patterns of drug use careers and identify determinants of drug use frequency across cohorts of primary heroin, methamphetamine (MA) and cocaine users. Design Pooled analysis of prospective cohort studies. Settings Illicit drug users recruited from community, criminal justice and drug treatment settings in California, USA. Participants We used longitudinal data on from five observational cohort studies featuring primary users of heroin (N=629), cocaine (N=694) and methamphetamine (N=474). The mean duration of follow-up was 20.9 years. Measurements Monthly longitudinal data was arranged according to five health states (incarceration, drug treatment, abstinence, non-daily and daily use). We fitted proportional hazards (PH) frailty models to determine independent differences in successive episode durations. We then executed multi-state Markov (MSM) models to estimate probabilities of transitioning between health states, and the determinants of these transitions. Findings Across primary drug use types, PH frailty models demonstrated durations of daily use diminished in successive episodes over time. MSM models revealed primary stimulant users had more erratic longitudinal patterns of drug use, transitioning more rapidly between periods of treatment, abstinence, non-daily and daily use. MA users exhibited relatively longer durations of high-frequency use. Criminal engagement had a destabilizing effect on health state durations across drug types. Longer incarceration histories were associated with delayed transitions towards cessation. Conclusions PH frailty and MSM modeling techniques provided complementary information on longitudinal patterns of drug abuse. This information can inform clinical practice and policy, and otherwise be used in health economic simulation models, designed to inform resource allocation decisions. PMID:24837584

A hidden Markov model approach to neuron firing patterns.

PubMed

Camproux, A C; Saunier, F; Chouvet, G; Thalabard, J C; Thomas, G

1996-11-01

Analysis and characterization of neuronal discharge patterns are of interest to neurophysiologists and neuropharmacologists. In this paper we present a hidden Markov model approach to modeling single neuron electrical activity. Basically the model assumes that each interspike interval corresponds to one of several possible states of the neuron. Fitting the model to experimental series of interspike intervals by maximum likelihood allows estimation of the number of possible underlying neuron states, the probability density functions of interspike intervals corresponding to each state, and the transition probabilities between states. We present an application to the analysis of recordings of a locus coeruleus neuron under three pharmacological conditions. The model distinguishes two states during halothane anesthesia and during recovery from halothane anesthesia, and four states after administration of clonidine. The transition probabilities yield additional insights into the mechanisms of neuron firing.

Characteristics of the Mott transition and electronic states of high-temperature cuprate superconductors from the perspective of the Hubbard model

NASA Astrophysics Data System (ADS)

Kohno, Masanori

2018-04-01

A fundamental issue of the Mott transition is how electrons behaving as single particles carrying spin and charge in a metal change into those exhibiting separated spin and charge excitations (low-energy spin excitation and high-energy charge excitation) in a Mott insulator. This issue has attracted considerable attention particularly in relation to high-temperature cuprate superconductors, which exhibit electronic states near the Mott transition that are difficult to explain in conventional pictures. Here, from a new viewpoint of the Mott transition based on analyses of the Hubbard model, we review anomalous features observed in high-temperature cuprate superconductors near the Mott transition.

Ground-state ordering of the J1-J2 model on the simple cubic and body-centered cubic lattices

NASA Astrophysics Data System (ADS)

Farnell, D. J. J.; Götze, O.; Richter, J.

2016-06-01

The J1-J2 Heisenberg model is a "canonical" model in the field of quantum magnetism in order to study the interplay between frustration and quantum fluctuations as well as quantum phase transitions driven by frustration. Here we apply the coupled cluster method (CCM) to study the spin-half J1-J2 model with antiferromagnetic nearest-neighbor bonds J1>0 and next-nearest-neighbor bonds J2>0 for the simple cubic (sc) and body-centered cubic (bcc) lattices. In particular, we wish to study the ground-state ordering of these systems as a function of the frustration parameter p =z2J2/z1J1 , where z1 (z2) is the number of nearest (next-nearest) neighbors. We wish to determine the positions of the phase transitions using the CCM and we aim to resolve the nature of the phase transition points. We consider the ground-state energy, order parameters, spin-spin correlation functions, as well as the spin stiffness in order to determine the ground-state phase diagrams of these models. We find a direct first-order phase transition at a value of p =0.528 from a state of nearest-neighbor Néel order to next-nearest-neighbor Néel order for the bcc lattice. For the sc lattice the situation is more subtle. CCM results for the energy, the order parameter, the spin-spin correlation functions, and the spin stiffness indicate that there is no direct first-order transition between ground-state phases with magnetic long-range order, rather it is more likely that two phases with antiferromagnetic long range are separated by a narrow region of a spin-liquid-like quantum phase around p =0.55 . Thus the strong frustration present in the J1-J2 Heisenberg model on the sc lattice may open a window for an unconventional quantum ground state in this three-dimensional spin model.

Levitation of current carrying states in the lattice model for the integer quantum Hall effect.

PubMed

Koschny, T; Potempa, H; Schweitzer, L

2001-04-23

The disorder driven quantum Hall to insulator transition is investigated for a two-dimensional lattice model. The Hall conductivity and the localization length are calculated numerically near the transition. For uncorrelated and weakly correlated disorder potentials the current carrying states are annihilated by the negative Chern states originating from the band center. In the presence of correlated disorder potentials with correlation length larger than approximately half the lattice constant the floating up of the critical states in energy without merging is observed. This behavior is similar to the levitation scenario proposed for the continuum model.

E1 transitions from octupole vibration states

NASA Astrophysics Data System (ADS)

Cottle, P. D.

1993-04-01

Electric dipole moments are extracted from data for E1 transitions deexciting octupole vibration states in nineteen nuclei. The moments are then compared to values calculated using the droplet model prescription of Dorso, Myers, and Swiatecki. It is found that the E1 moments in quadrupole deformed nuclei can be reproduced with the droplet model using the same model parameters that reproduce atomic masses and fission barriers. This result supports the suggestion of Butler and Nazarewicz that single particle effects are usually much smaller than macroscopic effects in E1 transitions associated with octupole vibrations in reflection symmetric deformed nuclei.

The reduced transition probabilities for excited states of rare-earths and actinide even-even nuclei

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

Ghumman, S. S.

The theoretical B(E2) ratios have been calculated on DF, DR and Krutov models. A simple method based on the work of Arima and Iachello is used to calculate the reduced transition probabilities within SU(3) limit of IBA-I framework. The reduced E2 transition probabilities from second excited states of rare-earths and actinide even–even nuclei calculated from experimental energies and intensities from recent data, have been found to compare better with those calculated on the Krutov model and the SU(3) limit of IBA than the DR and DF models.

Capture-recapture studies for multiple strata including non-markovian transitions

USGS Publications Warehouse

Brownie, C.; Hines, J.E.; Nichols, J.D.; Pollock, K.H.; Hestbeck, J.B.

1993-01-01

We consider capture-recapture studies where release and recapture data are available from each of a number of strata on every capture occasion. Strata may, for example, be geographic locations or physiological states. Movement of animals among strata occurs with unknown probabilities, and estimation of these unknown transition probabilities is the objective. We describe a computer routine for carrying out the analysis under a model that assumes Markovian transitions and under reduced parameter versions of this model. We also introduce models that relax the Markovian assumption and allow 'memory' to operate (i.e., allow dependence of the transition probabilities on the previous state). For these models, we sugg st an analysis based on a conditional likelihood approach. Methods are illustrated with data from a large study on Canada geese (Branta canadensis) banded in three geographic regions. The assumption of Markovian transitions is rejected convincingly for these data, emphasizing the importance of the more general models that allow memory.

Forecasting timber, biomass, and tree carbon pools with the output of state and transition models

Treesearch

Xiaoping Zhou; Miles A. Hemstrom

2012-01-01

The Integrated Landscape Assessment Project (ILAP) uses spatial vegetation data and state and transition models (STM) to forecast future vegetation conditions and the interacting effects of natural disturbances and management activities. Results from ILAP will help land managers, planners, and policymakers evaluate management strategies that reduce fire risk, improve...

The role of data and inference in the development and application of ecological site concepts and state-and-transition models

USDA-ARS?s Scientific Manuscript database

Information embodied in ecological site descriptions and their state-and-transition models is crucial to effective land management, and as such is needed now. There is not time (or money) to employ a traditional research-based approach (i.e., inductive/deductive, hypothesis driven inference) to addr...

Markov Transition Model to Dementia with Death as a Competing Event.

PubMed

Wei, Shaoceng; Xu, Liou; Kryscio, Richard J

2014-12-01

This study evaluates the effect of death as a competing event to the development of dementia in a longitudinal study of the cognitive status of elderly subjects. A multi-state Markov model with three transient states: intact cognition, mild cognitive impairment (M.C.I.) and global impairment (G.I.) and one absorbing state: dementia is used to model the cognitive panel data; transitions among states depend on four covariates age, education, prior state (intact cognition, or M.C.I., or G.I.) and the presence/absence of an apolipoprotein E-4 allele (APOE4). A Weibull model and a Cox proportional hazards (Cox PH) model are used to fit the survival from death based on age at entry and the APOE4 status. A shared random effect correlates this survival time with the transition model. Simulation studies determine the sensitivity of the maximum likelihood estimates to the violations of the Weibull and Cox PH model assumptions. Results are illustrated with an application to the Nun Study, a longitudinal cohort of 672 participants 75+ years of age at baseline and followed longitudinally with up to ten cognitive assessments per nun.

Markov Transition Model to Dementia with Death as a Competing Event

PubMed Central

Wei, Shaoceng; Xu, Liou; Kryscio, Richard J.

2014-01-01

This study evaluates the effect of death as a competing event to the development of dementia in a longitudinal study of the cognitive status of elderly subjects. A multi-state Markov model with three transient states: intact cognition, mild cognitive impairment (M.C.I.) and global impairment (G.I.) and one absorbing state: dementia is used to model the cognitive panel data; transitions among states depend on four covariates age, education, prior state (intact cognition, or M.C.I., or G.I.) and the presence/absence of an apolipoprotein E-4 allele (APOE4). A Weibull model and a Cox proportional hazards (Cox PH) model are used to fit the survival from death based on age at entry and the APOE4 status. A shared random effect correlates this survival time with the transition model. Simulation studies determine the sensitivity of the maximum likelihood estimates to the violations of the Weibull and Cox PH model assumptions. Results are illustrated with an application to the Nun Study, a longitudinal cohort of 672 participants 75+ years of age at baseline and followed longitudinally with up to ten cognitive assessments per nun. PMID:25110380

Theoretical analysis of Lumry-Eyring models in differential scanning calorimetry

PubMed Central

Sanchez-Ruiz, Jose M.

1992-01-01

A theoretical analysis of several protein denaturation models (Lumry-Eyring models) that include a rate-limited step leading to an irreversibly denatured state of the protein (the final state) has been carried out. The differential scanning calorimetry transitions predicted for these models can be broadly classified into four groups: situations A, B, C, and C′. (A) The transition is calorimetrically irreversible but the rate-limited, irreversible step takes place with significant rate only at temperatures slightly above those corresponding to the transition. Equilibrium thermodynamics analysis is permissible. (B) The transition is distorted by the occurrence of the rate-limited step; nevertheless, it contains thermodynamic information about the reversible unfolding of the protein, which could be obtained upon the appropriate data treatment. (C) The heat absorption is entirely determined by the kinetics of formation of the final state and no thermodynamic information can be extracted from the calorimetric transition; the rate-determining step is the irreversible process itself. (C′) same as C, but, in this case, the rate-determining step is a previous step in the unfolding pathway. It is shown that ligand and protein concentration effects on transitions corresponding to situation C (strongly rate-limited transitions) are similar to those predicted by equilibrium thermodynamics for simple reversible unfolding models. It has been widely held in recent literature that experimentally observed ligand and protein concentration effects support the applicability of equilibrium thermodynamics to irreversible protein denaturation. The theoretical analysis reported here disfavors this claim. PMID:19431826

Simple model for vibration-translation exchange at high temperatures: effects of multiquantum transitions on the relaxation of a N2 gas flow behind a shock.

PubMed

Aliat, A; Vedula, P; Josyula, E

2011-02-01

In this paper a simple model is proposed for computation of rate coefficients related to vibration-translation transitions based on the forced harmonic oscillator theory. This model, which is developed by considering a quadrature method, provides rate coefficients that are in very good agreement with those found in the literature for the high temperature regime (≳10,000 K). This model is implemented to study a one-dimensional nonequilibrium inviscid N(2) flow behind a plane shock by considering a state-to-state approach. While the effects of ionization and chemical reactions are neglected in our study, our results show that multiquantum transitions have a great influence on the relaxation of the macroscopic parameters of the gas flow behind the shock, especially on vibrational distributions of high levels. All vibrational states are influenced by multiquantum processes, but the effective number of transitions decreases inversely according to the vibrational quantum number. For the initial conditions considered in this study, excited electronic states are found to be weakly populated and can be neglected in modeling. Moreover, the computing time is considerably reduced with the model described in this paper compared to others found in the literature. ©2011 American Physical Society

Semi-Markov models for interval censored transient cognitive states with back transitions and a competing risk

PubMed Central

Wei, Shaoceng; Kryscio, Richard J.

2015-01-01

Continuous-time multi-state stochastic processes are useful for modeling the flow of subjects from intact cognition to dementia with mild cognitive impairment and global impairment as intervening transient, cognitive states and death as a competing risk (Figure 1). Each subject's cognition is assessed periodically resulting in interval censoring for the cognitive states while death without dementia is not interval censored. Since back transitions among the transient states are possible, Markov chains are often applied to this type of panel data. In this manuscript we apply a Semi-Markov process in which we assume that the waiting times are Weibull distributed except for transitions from the baseline state, which are exponentially distributed and in which we assume no additional changes in cognition occur between two assessments. We implement a quasi-Monte Carlo (QMC) method to calculate the higher order integration needed for likelihood estimation. We apply our model to a real dataset, the Nun Study, a cohort of 461 participants. PMID:24821001

Semi-Markov models for interval censored transient cognitive states with back transitions and a competing risk.

PubMed

Wei, Shaoceng; Kryscio, Richard J

2016-12-01

Continuous-time multi-state stochastic processes are useful for modeling the flow of subjects from intact cognition to dementia with mild cognitive impairment and global impairment as intervening transient cognitive states and death as a competing risk. Each subject's cognition is assessed periodically resulting in interval censoring for the cognitive states while death without dementia is not interval censored. Since back transitions among the transient states are possible, Markov chains are often applied to this type of panel data. In this manuscript, we apply a semi-Markov process in which we assume that the waiting times are Weibull distributed except for transitions from the baseline state, which are exponentially distributed and in which we assume no additional changes in cognition occur between two assessments. We implement a quasi-Monte Carlo (QMC) method to calculate the higher order integration needed for likelihood estimation. We apply our model to a real dataset, the Nun Study, a cohort of 461 participants. © The Author(s) 2014.

Adaptive particle filter for robust visual tracking

NASA Astrophysics Data System (ADS)

Dai, Jianghua; Yu, Shengsheng; Sun, Weiping; Chen, Xiaoping; Xiang, Jinhai

2009-10-01

Object tracking plays a key role in the field of computer vision. Particle filter has been widely used for visual tracking under nonlinear and/or non-Gaussian circumstances. In particle filter, the state transition model for predicting the next location of tracked object assumes the object motion is invariable, which cannot well approximate the varying dynamics of the motion changes. In addition, the state estimate calculated by the mean of all the weighted particles is coarse or inaccurate due to various noise disturbances. Both these two factors may degrade tracking performance greatly. In this work, an adaptive particle filter (APF) with a velocity-updating based transition model (VTM) and an adaptive state estimate approach (ASEA) is proposed to improve object tracking. In APF, the motion velocity embedded into the state transition model is updated continuously by a recursive equation, and the state estimate is obtained adaptively according to the state posterior distribution. The experiment results show that the APF can increase the tracking accuracy and efficiency in complex environments.

Advanced network planning for bus rapid transit : the "Quickway" model as a modal alternative to "Light Rail Lite"

DOT National Transportation Integrated Search

2008-02-01

Transit planning in the United States has tended toward viewing BRT as an analogue to light rail transit, with similar operating patterns. This model, referred to as Light Rail Lite, is compared to international best practices, which have often...

A nonstationary Markov transition model for computing the relative risk of dementia before death

PubMed Central

Yu, Lei; Griffith, William S.; Tyas, Suzanne L.; Snowdon, David A.; Kryscio, Richard J.

2010-01-01

This paper investigates the long-term behavior of the k-step transition probability matrix for a nonstationary discrete time Markov chain in the context of modeling transitions from intact cognition to dementia with mild cognitive impairment (MCI) and global impairment (GI) as intervening cognitive states. The authors derive formulas for the following absorption statistics: (1) the relative risk of absorption between competing absorbing states, and (2) the mean and variance of the number of visits among the transient states before absorption. Since absorption is not guaranteed, sufficient conditions are discussed to ensure that the substochastic matrix associated with transitions among transient states converges to zero in limit. Results are illustrated with an application to the Nun Study, a cohort of 678 participants, 75 to 107 years of age, followed longitudinally with up to ten cognitive assessments over a fifteen-year period. PMID:20087848

Simplification of Markov chains with infinite state space and the mathematical theory of random gene expression bursts.

PubMed

Jia, Chen

2017-09-01

Here we develop an effective approach to simplify two-time-scale Markov chains with infinite state spaces by removal of states with fast leaving rates, which improves the simplification method of finite Markov chains. We introduce the concept of fast transition paths and show that the effective transitions of the reduced chain can be represented as the superposition of the direct transitions and the indirect transitions via all the fast transition paths. Furthermore, we apply our simplification approach to the standard Markov model of single-cell stochastic gene expression and provide a mathematical theory of random gene expression bursts. We give the precise mathematical conditions for the bursting kinetics of both mRNAs and proteins. It turns out that random bursts exactly correspond to the fast transition paths of the Markov model. This helps us gain a better understanding of the physics behind the bursting kinetics as an emergent behavior from the fundamental multiscale biochemical reaction kinetics of stochastic gene expression.

Simplification of Markov chains with infinite state space and the mathematical theory of random gene expression bursts

NASA Astrophysics Data System (ADS)

Jia, Chen

2017-09-01

Here we develop an effective approach to simplify two-time-scale Markov chains with infinite state spaces by removal of states with fast leaving rates, which improves the simplification method of finite Markov chains. We introduce the concept of fast transition paths and show that the effective transitions of the reduced chain can be represented as the superposition of the direct transitions and the indirect transitions via all the fast transition paths. Furthermore, we apply our simplification approach to the standard Markov model of single-cell stochastic gene expression and provide a mathematical theory of random gene expression bursts. We give the precise mathematical conditions for the bursting kinetics of both mRNAs and proteins. It turns out that random bursts exactly correspond to the fast transition paths of the Markov model. This helps us gain a better understanding of the physics behind the bursting kinetics as an emergent behavior from the fundamental multiscale biochemical reaction kinetics of stochastic gene expression.

Jet-cooled laser-induced fluorescence spectroscopy of cyclohexoxy: rotational and fine structure of molecules in nearly degenerate electronic States.

PubMed

Liu, Jinjun; Miller, Terry A

2014-12-26

The rotational structure of the previously observed B̃(2)A' ← X̃(2)A″ and B̃(2)A' ← Ã(2)A' laser-induced fluorescence spectra of jet-cooled cyclohexoxy radical (c-C6H11O) [ Zu, L.; Liu, J.; Tarczay, G.; Dupré, P; Miller, T. A. Jet-cooled laser spectroscopy of the cyclohexoxy radical. J. Chem. Phys. 2004 , 120 , 10579 ] has been analyzed and simulated using a spectroscopic model that includes the coupling between the nearly degenerate X̃ and à states separated by ΔE. The rotational and fine structure of these two states is reproduced by a 2-fold model using one set of molecular constants including rotational constants, spin-rotation constants (ε's), the Coriolis constant (Aζt), the quenched spin-orbit constant (aζed), and the vibronic energy separation between the two states (ΔE0). The energy level structure of both states can also be reproduced using an isolated-state asymmetric top model with rotational constants and effective spin-rotation constants (ε's) and without involving Coriolis and spin-orbit constants. However, the spin-orbit interaction introduces transitions that have no intensity using the isolated-state model but appear in the observed spectra. The line intensities are well simulated using the 2-fold model with an out-of-plane (b-) transition dipole moment for the B̃ ← X̃ transitions and in-plane (a and c) transition dipole moment for the B̃ ← à transitions, requiring the symmetry for the X̃ (Ã) state to be A″ (A'), which is consistent with a previous determination and opposite to that of isopropoxy, the smallest secondary alkoxy radical. The experimentally determined Ã-X̃ separation and the energy level ordering of these two states with different (A' and A″) symmetries are consistent with quantum chemical calculations. The 2-fold model also enables the independent determination of the two contributions to the Ã-X̃ separation: the relativistic spin-orbit interaction (magnetic effect) and the nonrelativistic vibronic separation between the lowest vibrational energy levels of these two states due to both electrostatic interaction (Coulombic effect) and difference in zero-point energies (kinetic effect).

Applying threshold concepts to conservation management of dryland ecosystems: Case studies on the Colorado Plateau

USGS Publications Warehouse

Bowker, Matthew A.; Miller, Mark E.; Garman, Steven L.; Belote, Travis; Guntenspergen, Glenn R.

2014-01-01

Ecosystems may occupy functionally distinct alternative states, some of which are more or less desirable from a management standpoint. Transitions from state to state are usually associated with a particular trigger or sequence of triggers, such as the addition or subtraction of a disturbance. Transitions are often not linear, rather it is common to see an abrupt transition come about even though the trigger increases only incrementally; these are examples of threshold behaviors. An ideal monitoring program, such as the National Park Service’s Inventory and Monitoring Program, would quantify triggers, and be able to inform managers when measurements of a trigger are approaching a threshold so that management action can avoid an unwanted state transition. Unfortunately, both triggers and the threshold points at which state transitions occur are generally only partially known. Using case studies, we advance a general procedure to help identify triggers and estimate where threshold dynamics may occur. Our procedure is as follows: (1) Operationally define the ecosystem type being considered; we suggest that the ecological site concept of the Natural Resource Conservation Service is a useful system, (2) Using all available a priori knowledge to develop a state-and-transition model (STM), which defines possible ecosystem states, plausible transitions among them and likely triggers, (3) Validate the STM by verifying the existence of its states to the greatest degree possible, (4) Use the STM model to identify transitions and triggers likely to be detectable by a monitoring program, and estimate to the greatest degree possible the value of a measurable indicator of a trigger at the point that a state transition is imminent (tipping point), and values that may indicate when management intervention should be considered (assessment points). We illustrate two different methods for attaining these goals using a data-rich case study in Canyonlands National Park, and a data-poor case study in Wupatki National Monument. In the data-rich case, STMs are validated and revised, and tipping and assessment points are estimated using statistical analysis of data. In the data-poor case, we develop an iterative expert opinion survey approach to validate the degree of confidence in an STM, revise the model, identify lack of confidence in specific model components, and create reasonable first approximations of tipping and assessment points, which can later be refined when more data are available. Our goal should be to develop the best set of models possible given the level of information available to support decisions, which is often not much. The approach presented here offers a flexible means of achieving this goal, and determining specific research areas in need of study.

A model of the normal and null states of pulsars

NASA Astrophysics Data System (ADS)

Jones, P. B.

1981-12-01

A solvable three-dimensional polar cap model of pair creation and charged particle acceleration has been derived. There are no free parameters of significance apart from the polar surface magnetic flux density. The parameter determining the acceleration potential difference has been obtained by calculation of elementary nuclear and electromagnetic processes. Solutions of the model exist for both normal and null states of a pulsar, and the instability in the normal state leading to the normal to null transition has been identified. The predicted necessary condition for the transition is entirely consistent with observation.

A model of the normal and null states of pulsars

NASA Astrophysics Data System (ADS)

Jones, P. B.

A solvable three dimensional polar cap model of pair creation and charged particle acceleration is derived. There are no free parameters of significance apart from the polar surface magnetic flux density. The parameter CO determining the acceleration potential difference was obtained by calculation of elementary nuclear and electromagnetic processes. Solutions of the model exist for both normal and null states of a pulsar, and the instability in the normal state leading to the normal to null transition is identified. The predicted necessary condition for the transition is entirely consistent with observation.

Probing the free energy landscape of the FBP28WW domain using multiple techniques.

PubMed

Periole, Xavier; Allen, Lucy R; Tamiola, Kamil; Mark, Alan E; Paci, Emanuele

2009-05-01

The free-energy landscape of a small protein, the FBP 28 WW domain, has been explored using molecular dynamics (MD) simulations with alternative descriptions of the molecule. The molecular models used range from coarse-grained to all-atom with either an implicit or explicit treatment of the solvent. Sampling of conformation space was performed using both conventional and temperature-replica exchange MD simulations. Experimental chemical shifts and NOEs were used to validate the simulations, and experimental phi values both for validation and as restraints. This combination of different approaches has provided insight into the free energy landscape and barriers encountered by the protein during folding and enabled the characterization of native, denatured and transition states which are compatible with the available experimental data. All the molecular models used stabilize well defined native and denatured basins; however, the degree of agreement with the available experimental data varies. While the most detailed, explicit solvent model predicts the data reasonably accurately, it does not fold despite a simulation time 10 times that of the experimental folding time. The less detailed models performed poorly relative to the explicit solvent model: an implicit solvent model stabilizes a ground state which differs from the experimental native state, and a structure-based model underestimates the size of the barrier between the two states. The use of experimental phi values both as restraints, and to extract structures from unfolding simulations, result in conformations which, although not necessarily true transition states, appear to share the geometrical characteristics of transition state structures. In addition to characterizing the native, transition and denatured states of this particular system in this work, the advantages and limitations of using varying levels of representation are discussed. 2008 Wiley Periodicals, Inc.

A hidden Markov model approach to neuron firing patterns.

PubMed Central

Camproux, A C; Saunier, F; Chouvet, G; Thalabard, J C; Thomas, G

1996-01-01

Analysis and characterization of neuronal discharge patterns are of interest to neurophysiologists and neuropharmacologists. In this paper we present a hidden Markov model approach to modeling single neuron electrical activity. Basically the model assumes that each interspike interval corresponds to one of several possible states of the neuron. Fitting the model to experimental series of interspike intervals by maximum likelihood allows estimation of the number of possible underlying neuron states, the probability density functions of interspike intervals corresponding to each state, and the transition probabilities between states. We present an application to the analysis of recordings of a locus coeruleus neuron under three pharmacological conditions. The model distinguishes two states during halothane anesthesia and during recovery from halothane anesthesia, and four states after administration of clonidine. The transition probabilities yield additional insights into the mechanisms of neuron firing. Images FIGURE 3 PMID:8913581

Radiative transition of hydrogen-like ions in quantum plasma

NASA Astrophysics Data System (ADS)

Hu, Hongwei; Chen, Zhanbin; Chen, Wencong

2016-12-01

At fusion plasma electron temperature and number density regimes of 1 × 103-1 × 107 K and 1 × 1028-1 × 1031/m3, respectively, the excited states and radiative transition of hydrogen-like ions in fusion plasmas are studied. The results show that quantum plasma model is more suitable to describe the fusion plasma than the Debye screening model. Relativistic correction to bound-state energies of the low-Z hydrogen-like ions is so small that it can be ignored. The transition probability decreases with plasma density, but the transition probabilities have the same order of magnitude in the same number density regime.

Elastic Model Transitions: A Hybrid Approach Utilizing Quadratic Inequality Constrained Least Squares (LSQI) and Direct Shape Mapping (DSM)

NASA Technical Reports Server (NTRS)

Hannan, Mike R.; Jurenko, Robert J.; Bush, Jason; Ottander, John

2014-01-01

A method for transitioning linear time invariant (LTI) models in time varying simulation is proposed that utilizes a hybrid approach for determining physical displacements by augmenting the original quadratically constrained least squares (LSQI) algorithm with Direct Shape Mapping (DSM) and modifying the energy constraints. The approach presented is applicable to simulation of the elastic behavior of launch vehicles and other structures that utilize discrete LTI finite element model (FEM) derived mode sets (eigenvalues and eigenvectors) that are propagated throughout time. The time invariant nature of the elastic data presents a problem of how to properly transition elastic states from the prior to the new model while preserving motion across the transition and ensuring there is no truncation or excitation of the system. A previous approach utilizes a LSQI algorithm with an energy constraint to effect smooth transitions between eigenvector sets with no requirement that the models be of similar dimension or have any correlation. This approach assumes energy is conserved across the transition, which results in significant non-physical transients due to changing quasi-steady state energy between mode sets, a phenomenon seen when utilizing a truncated mode set. The computational burden of simulating a full mode set is significant so a subset of modes is often selected to reduce run time. As a result of this truncation, energy between mode sets may not be constant and solutions across transitions could produce non-physical transients. In an effort to abate these transients an improved methodology was developed based on the aforementioned approach, but this new approach can handle significant changes in energy across mode set transitions. It is proposed that physical velocities due to elastic behavior be solved for using the LSQI algorithm, but solve for displacements using a two-step process that independently addresses the quasi-steady-state and non-steady-state contributions to the elastic displacement. For structures subject to large external forces, such as thrust or atmospheric drag, it is imperative to capture these forces when solving for elastic displacement. To simplify the mathematical formulation, assumptions are made regarding mass matrix normalization, constant external forcing, and constant viscous damping. These simplifications allow for direct solutions to the quasi-steady-state displacements through a process titled Direct Shape Mapping. DSM solves for the displacements using the eigenvalues of the elastic modes and the external forcing and returns a set of elastic displacements dictated by the eigenvectors of the post-transition mode set. For the non-steady-state contributions to displacement we formulate a LSQI problem that is constrained by energy of the non-steady state terms. The contributions from the quasi-steady-state and non-steady state solutions are then combined to obtain the physical displacements associated with the new set of eigenvectors. Results for the LSQI-DSM approach show significant reduction/complete removal of transients across mode set transitions while maintaining elastic motion from the prior state. For time propagation applications employing discrete elastic models that need to be transitioned in time and where running with full a full mode set is not feasible, the method developed offers a practical solution to simulating vehicle elasticity.

Integrating continuous stocks and flows into state-and-transition simulation models of landscape change

USGS Publications Warehouse

Daniel, Colin J.; Sleeter, Benjamin M.; Frid, Leonardo; Fortin, Marie-Josée

2018-01-01

State-and-transition simulation models (STSMs) provide a general framework for forecasting landscape dynamics, including projections of both vegetation and land-use/land-cover (LULC) change. The STSM method divides a landscape into spatially-referenced cells and then simulates the state of each cell forward in time, as a discrete-time stochastic process using a Monte Carlo approach, in response to any number of possible transitions. A current limitation of the STSM method, however, is that all of the state variables must be discrete.Here we present a new approach for extending a STSM, in order to account for continuous state variables, called a state-and-transition simulation model with stocks and flows (STSM-SF). The STSM-SF method allows for any number of continuous stocks to be defined for every spatial cell in the STSM, along with a suite of continuous flows specifying the rates at which stock levels change over time. The change in the level of each stock is then simulated forward in time, for each spatial cell, as a discrete-time stochastic process. The method differs from the traditional systems dynamics approach to stock-flow modelling in that the stocks and flows can be spatially-explicit, and the flows can be expressed as a function of the STSM states and transitions.We demonstrate the STSM-SF method by integrating a spatially-explicit carbon (C) budget model with a STSM of LULC change for the state of Hawai'i, USA. In this example, continuous stocks are pools of terrestrial C, while the flows are the possible fluxes of C between these pools. Importantly, several of these C fluxes are triggered by corresponding LULC transitions in the STSM. Model outputs include changes in the spatial and temporal distribution of C pools and fluxes across the landscape in response to projected future changes in LULC over the next 50 years.The new STSM-SF method allows both discrete and continuous state variables to be integrated into a STSM, including interactions between them. With the addition of stocks and flows, STSMs provide a conceptually simple yet powerful approach for characterizing uncertainties in projections of a wide range of questions regarding landscape change.

Dynamical modeling and analysis of large cellular regulatory networks

NASA Astrophysics Data System (ADS)

Bérenguier, D.; Chaouiya, C.; Monteiro, P. T.; Naldi, A.; Remy, E.; Thieffry, D.; Tichit, L.

2013-06-01

The dynamical analysis of large biological regulatory networks requires the development of scalable methods for mathematical modeling. Following the approach initially introduced by Thomas, we formalize the interactions between the components of a network in terms of discrete variables, functions, and parameters. Model simulations result in directed graphs, called state transition graphs. We are particularly interested in reachability properties and asymptotic behaviors, which correspond to terminal strongly connected components (or "attractors") in the state transition graph. A well-known problem is the exponential increase of the size of state transition graphs with the number of network components, in particular when using the biologically realistic asynchronous updating assumption. To address this problem, we have developed several complementary methods enabling the analysis of the behavior of large and complex logical models: (i) the definition of transition priority classes to simplify the dynamics; (ii) a model reduction method preserving essential dynamical properties, (iii) a novel algorithm to compact state transition graphs and directly generate compressed representations, emphasizing relevant transient and asymptotic dynamical properties. The power of an approach combining these different methods is demonstrated by applying them to a recent multilevel logical model for the network controlling CD4+ T helper cell response to antigen presentation and to a dozen cytokines. This model accounts for the differentiation of canonical Th1 and Th2 lymphocytes, as well as of inflammatory Th17 and regulatory T cells, along with many hybrid subtypes. All these methods have been implemented into the software GINsim, which enables the definition, the analysis, and the simulation of logical regulatory graphs.

Convergence of Transition Probability Matrix in CLVMarkov Models

NASA Astrophysics Data System (ADS)

Permana, D.; Pasaribu, U. S.; Indratno, S. W.; Suprayogi, S.

2018-04-01

A transition probability matrix is an arrangement of transition probability from one states to another in a Markov chain model (MCM). One of interesting study on the MCM is its behavior for a long time in the future. The behavior is derived from one property of transition probabilty matrix for n steps. This term is called the convergence of the n-step transition matrix for n move to infinity. Mathematically, the convergence of the transition probability matrix is finding the limit of the transition matrix which is powered by n where n moves to infinity. The convergence form of the transition probability matrix is very interesting as it will bring the matrix to its stationary form. This form is useful for predicting the probability of transitions between states in the future. The method usually used to find the convergence of transition probability matrix is through the process of limiting the distribution. In this paper, the convergence of the transition probability matrix is searched using a simple concept of linear algebra that is by diagonalizing the matrix.This method has a higher level of complexity because it has to perform the process of diagonalization in its matrix. But this way has the advantage of obtaining a common form of power n of the transition probability matrix. This form is useful to see transition matrix before stationary. For example cases are taken from CLV model using MCM called Model of CLV-Markov. There are several models taken by its transition probability matrix to find its convergence form. The result is that the convergence of the matrix of transition probability through diagonalization has similarity with convergence with commonly used distribution of probability limiting method.

Grassland-shrubland state transitions in arid rangelands: Competition matters

USDA-ARS?s Scientific Manuscript database

Background: State transition from grassland to shrubland is synonymous with desertification in many arid rangeland systems. Traditional desertification models emphasize abiotic feedbacks that modify the physical environment in ways that promote shrub proliferation and impede grass survival. Inherent...

Use of state-and-transition simulation modeling in National Forest planning in the Pacific Northwest, U.S.A

Treesearch

Ayn J. Shlisky; Don Vandendriesche

2012-01-01

Effective national forest planning depends on scientifically sound analyses of land management alternatives relative to desired future conditions and environmental effects. The USDA Forest Service Pacific Northwest Region is currently using state-and-transition simulation models (STMs) to simulate changes in forest composition and structure for the revisions of five...

Fire rehabilitation decisions at landscape scales: utilizing state-and-transition models developed through disturbance response grouping of ecological sites

USDA-ARS?s Scientific Manuscript database

Recognizing the utility of ecological sites and the associated state-and-transition model (STM) for decision support, the Bureau of Land Management in Nevada partnered with Nevada NRCS and the University of Nevada, Reno (UNR) in 2009 with the goal of creating a team that could (1) expedite developme...

Reentrant topological phase transition in a bridging model between Kitaev and Haldane chains

NASA Astrophysics Data System (ADS)

Sugimoto, Takanori; Ohtsu, Mitsuyoshi; Tohyama, Takami

2017-12-01

We present a reentrant phase transition in a bridging model between two different topological models: Kitaev and Haldane chains. This model is activated by introducing a bond alternation into the Kitaev chain [A. Y. Kitaev, Phys. Usp. 44, 131 (2001), 10.1070/1063-7869/44/10S/S29]. Without the bond alternation, the finite pairing potential induces a topological state defined by the zero-energy Majorana edge mode, while finite bond alternation without the pairing potential makes a different topological state similar to the Haldane state, which is defined by the local Berry phase in the bulk. The topologically ordered state corresponds to the Su-Schrieffer-Heeger state, which is classified as the same symmetry class. We thus find a phase transition between the two topological phases with a reentrant phenomenon, and extend the phase diagram in the plane of the pairing potential and the bond alternation by using three techniques: recursive equation, fidelity, and Pfaffian. In addition, we find that the phase transition is characterized by both the change of the position of Majorana zero-energy modes from one edge to the other edge and the emergence of a string order in the bulk, and that the reentrance is based on a sublattice U(1) rotation. Consequently, our paper and model not only open a direct way to discuss the bulk and edge topologies but demonstrate an example of the reentrant topologies.

Using Markov Chains to predict the natural progression of diabetic retinopathy.

PubMed

Srikanth, Priyanka

2015-01-01

To study the natural progression of diabetic retinopathy in patients with type 2 diabetes. This was an observational study of 153 cases with type 2 diabetes from 2010 to 2013. The state of patient was noted at end of each year and transition matrices were developed to model movement between years. Patients who progressed to severe non-proliferative diabetic retinopathy (NPDR) were treated. Markov Chains and Chi-square test were used for statistical analysis. We modelled the transition of 153 patients from NPDR to blindness on an annual basis. At the end of year 3, we compared results from the Markov model versus actual data. The results from Chi-square test confirmed that there was statistically no significant difference (P=0.70) which provided assurance that the model was robust to estimate mean sojourn times. The key finding was that a patient entering the system in mild NPDR state is expected to stay in that state for 5y followed by 1.07y in moderate NPDR, be in the severe NPDR state for 1.33y before moving into PDR for roughly 8y. It is therefore expected that such a patient entering the model in a state of mild NPDR will enter blindness after 15.29y. Patients stay for long time periods in mild NPDR before transitioning into moderate NPDR. However, they move rapidly from moderate NPDR to proliferative diabetic retinopathy (PDR) and stay in that state for long periods before transitioning into blindness.

Transitions between multiple equilibria of paleo climate: a glimpse in to the dynamics of abrupt climate change

NASA Astrophysics Data System (ADS)

Ferreira, David; Marshall, John; Ito, Takamitsu; McGee, David; Moreno-Chamarro, Eduardo

2017-04-01

The dynamics regulating large climatic transitions such as glacial-interglacial cycles or DO events remains a puzzle. Forcings behind these transitions are not robustly identified and potential candidates (e.g. Milankovitch cycles, freshwater perturbations) often appear too weak to explain such dramatic transitions. A potential solution to this long-standing puzzle is that Earth's climate is endowed with multiple equilibrium states of global extent. Such states are commonly found in low-order or conceptual climate models, but it is unclear whether a system as complex as Earth's climate can sustain multiple equilibrium states. Here we report that multiple equilibrium states of the climate system are also possible in a complex, fully dynamical coupled ocean-atmosphere-sea ice GCM with idealized Earth-like geometry, resolved weather systems and a hydrological cycle. In our model, two equilibrium states coexist for the same parameters and external forcings: a Warm climate with a small Northern hemisphere sea ice cap and a large southern one and a Cold climate with large ice caps at both poles. The dynamical states of the Warm and Cold solutions exhibit striking similarities with our present-day climate and the climate of the Last Glacial Maximum, respectively. A carbon cycle model driven by the two dynamical states produces an atmospheric pCO2 draw-down of about 110 pm between the Warm and Cold states, close to Glacial-Interglacial differences found in ice cores. Mechanism controlling the existence of the multiple states and changes in the atmospheric CO2 will be briefly presented. Finally we willdescribe transition experiments from the Cold to the Warm state, focusing on the lead-lags in the system, notably between the Northern and Southern Hemispheres climates.

Model of an Injection Semiconductor Quantum-Dot Laser

NASA Astrophysics Data System (ADS)

Koryukin, I. V.

2018-05-01

We propose an asymmetric electron-hole model of an injection semiconductor quantum-dot laser, which correctly allows for relaxation at transitions between the electron and hole levels. Steady-state solutions of the proposed model, conditions for the simultaneous operation at transitions between the ground and first excited state levels, and relaxation oscillations in the two-wave lasing regime are studied. It is shown that the model can be simplified when the relaxation between hole levels is much faster than the relaxation between electron levels.

Axelrod models of social influence with cultural repulsion

NASA Astrophysics Data System (ADS)

Radillo-Díaz, Alejandro; Pérez, Luis A.; Del Castillo-Mussot, Marcelo

2009-12-01

Since both attractive and repulsive effects among agents are important in social systems, we present simulations of two models based on Axelrod’s homogenization mechanism that includes repulsion. These models are the repulsive model, where all individuals can repel, and the partially repulsive model where only a fraction of repelling agents are considered. In these two models, attractive dynamics is implemented for agents with the ability to repel each other only if the number of features shared by them is greater than a threshold parameter. Otherwise, repelling dynamics is used. In the repulsive model, the transition from a monocultural state to a fragmented one often occurs abruptly from one cultural-variability value to the next one and a second transition emerges. For the partially repulsive model, there are also two different transitions present: the initial one being as abrupt as the one found for the repulsive model, whereas the second one follows a less abrupt behavior and resembles that of the original Axelrod model. However, the second transition for this model occurrs from a partially fragmented state and not from a monocultural one.

Coupled channels description of the α-decay fine structure

NASA Astrophysics Data System (ADS)

Delion, D. S.; Ren, Zhongzhou; Dumitrescu, A.; Ni, Dongdong

2018-05-01

We review the coupled channels approach of α transitions to excited states. The α-decaying states are identified as narrow outgoing Gamow resonances in an α-daughter potential. The real part of the eigenvalue corresponds to the Q-value, while the imaginary part determines the half of the total α-decay width. We first review the calculations describing transitions to rotational states treated by the rigid rotator model, in even–even, odd-mass and odd–odd nuclei. It is found that the semiclassical method overestimates the branching ratios to excited 4+ for some even–even α-emitters and fails in explaining the unexpected inversion of branching ratios of some odd-mass nuclei, while the coupled-channels results show good agreement with the experimental data. Then, we review the coupled channels method for α-transitions to 2+ vibrational and transitional states. We present the results of the Coherent State Model that describes in a unified way the spectra of vibrational, transitional and rotational nuclei. We evidence general features of the α-decay fine structure, namely the linear dependence between α-intensities and excitation energy, the linear correlation between the strength of the α-core interaction and spectroscopic factor, and the inverse correlation between the nuclear collectivity, given by electromagnetic transitions, and α-clustering.

Threshold of coexistence and critical behavior of a predator-prey stochastic model in a fractal landscape

NASA Astrophysics Data System (ADS)

Argolo, C.; Barros, P.; Tomé, T.; Arashiro, E.; Gleria, Iram; Lyra, M. L.

2016-08-01

We investigate a stochastic lattice model describing a predator-prey system in a fractal scale-free landscape, mimicked by the fractal Sierpinski carpet. We determine the threshold of species coexistence, that is, the critical phase boundary related to the transition between an active state, where both species coexist and an absorbing state where one of the species is extinct. We show that the predators must live longer in order to persist in a fractal habitat. We further performed a finite-size scaling analysis in the vicinity of the absorbing-state phase transition to compute a set of stationary and dynamical critical exponents. Our results indicate that the transition belongs to the directed percolation universality class exhibited by the usual contact process model on the same fractal landscape.

Coupled Flip-Flop Model for REM Sleep Regulation in the Rat

PubMed Central

Dunmyre, Justin R.; Mashour, George A.; Booth, Victoria

2014-01-01

Recent experimental studies investigating the neuronal regulation of rapid eye movement (REM) sleep have identified mutually inhibitory synaptic projections among REM sleep-promoting (REM-on) and REM sleep-inhibiting (REM-off) neuronal populations that act to maintain the REM sleep state and control its onset and offset. The control mechanism of mutually inhibitory synaptic interactions mirrors the proposed flip-flop switch for sleep-wake regulation consisting of mutually inhibitory synaptic projections between wake- and sleep-promoting neuronal populations. While a number of synaptic projections have been identified between these REM-on/REM-off populations and wake/sleep-promoting populations, the specific interactions that govern behavioral state transitions have not been completely determined. Using a minimal mathematical model, we investigated behavioral state transition dynamics dictated by a system of coupled flip-flops, one to control transitions between wake and sleep states, and another to control transitions into and out of REM sleep. The model describes the neurotransmitter-mediated inhibitory interactions between a wake- and sleep-promoting population, and between a REM-on and REM-off population. We proposed interactions between the wake/sleep and REM-on/REM-off flip-flops to replicate the behavioral state statistics and probabilities of behavioral state transitions measured from experimental recordings of rat sleep under ad libitum conditions and after 24 h of REM sleep deprivation. Reliable transitions from REM sleep to wake, as dictated by the data, indicated the necessity of an excitatory projection from the REM-on population to the wake-promoting population. To replicate the increase in REM-wake-REM transitions observed after 24 h REM sleep deprivation required that this excitatory projection promote transient activation of the wake-promoting population. Obtaining the reliable wake-nonREM sleep transitions observed in the data required that activity of the wake-promoting population modulated the interaction between the REM-on and REM-off populations. This analysis suggests neuronal processes to be targeted in further experimental studies of the regulatory mechanisms of REM sleep. PMID:24722577

Coupled flip-flop model for REM sleep regulation in the rat.

PubMed

Dunmyre, Justin R; Mashour, George A; Booth, Victoria

2014-01-01

Recent experimental studies investigating the neuronal regulation of rapid eye movement (REM) sleep have identified mutually inhibitory synaptic projections among REM sleep-promoting (REM-on) and REM sleep-inhibiting (REM-off) neuronal populations that act to maintain the REM sleep state and control its onset and offset. The control mechanism of mutually inhibitory synaptic interactions mirrors the proposed flip-flop switch for sleep-wake regulation consisting of mutually inhibitory synaptic projections between wake- and sleep-promoting neuronal populations. While a number of synaptic projections have been identified between these REM-on/REM-off populations and wake/sleep-promoting populations, the specific interactions that govern behavioral state transitions have not been completely determined. Using a minimal mathematical model, we investigated behavioral state transition dynamics dictated by a system of coupled flip-flops, one to control transitions between wake and sleep states, and another to control transitions into and out of REM sleep. The model describes the neurotransmitter-mediated inhibitory interactions between a wake- and sleep-promoting population, and between a REM-on and REM-off population. We proposed interactions between the wake/sleep and REM-on/REM-off flip-flops to replicate the behavioral state statistics and probabilities of behavioral state transitions measured from experimental recordings of rat sleep under ad libitum conditions and after 24 h of REM sleep deprivation. Reliable transitions from REM sleep to wake, as dictated by the data, indicated the necessity of an excitatory projection from the REM-on population to the wake-promoting population. To replicate the increase in REM-wake-REM transitions observed after 24 h REM sleep deprivation required that this excitatory projection promote transient activation of the wake-promoting population. Obtaining the reliable wake-nonREM sleep transitions observed in the data required that activity of the wake-promoting population modulated the interaction between the REM-on and REM-off populations. This analysis suggests neuronal processes to be targeted in further experimental studies of the regulatory mechanisms of REM sleep.

Analysis of a semiclassical model for rotational transition probabilities. [in highly nonequilibrium flow of diatomic molecules

NASA Technical Reports Server (NTRS)

Deiwert, G. S.; Yoshikawa, K. K.

1975-01-01

A semiclassical model proposed by Pearson and Hansen (1974) for computing collision-induced transition probabilities in diatomic molecules is tested by the direct-simulation Monte Carlo method. Specifically, this model is described by point centers of repulsion for collision dynamics, and the resulting classical trajectories are used in conjunction with the Schroedinger equation for a rigid-rotator harmonic oscillator to compute the rotational energy transition probabilities necessary to evaluate the rotation-translation exchange phenomena. It is assumed that a single, average energy spacing exists between the initial state and possible final states for a given collision.

A stochastic estimation procedure for intermittently-observed semi-Markov multistate models with back transitions.

PubMed

Aralis, Hilary; Brookmeyer, Ron

2017-01-01

Multistate models provide an important method for analyzing a wide range of life history processes including disease progression and patient recovery following medical intervention. Panel data consisting of the states occupied by an individual at a series of discrete time points are often used to estimate transition intensities of the underlying continuous-time process. When transition intensities depend on the time elapsed in the current state and back transitions between states are possible, this intermittent observation process presents difficulties in estimation due to intractability of the likelihood function. In this manuscript, we present an iterative stochastic expectation-maximization algorithm that relies on a simulation-based approximation to the likelihood function and implement this algorithm using rejection sampling. In a simulation study, we demonstrate the feasibility and performance of the proposed procedure. We then demonstrate application of the algorithm to a study of dementia, the Nun Study, consisting of intermittently-observed elderly subjects in one of four possible states corresponding to intact cognition, impaired cognition, dementia, and death. We show that the proposed stochastic expectation-maximization algorithm substantially reduces bias in model parameter estimates compared to an alternative approach used in the literature, minimal path estimation. We conclude that in estimating intermittently observed semi-Markov models, the proposed approach is a computationally feasible and accurate estimation procedure that leads to substantial improvements in back transition estimates.

Identification of ground-state spin ordering in antiferromagnetic transition metal oxides using the Ising model and a genetic algorithm

PubMed Central

Lee, Kyuhyun; Youn, Yong; Han, Seungwu

2017-01-01

Abstract We identify ground-state collinear spin ordering in various antiferromagnetic transition metal oxides by constructing the Ising model from first-principles results and applying a genetic algorithm to find its minimum energy state. The present method can correctly reproduce the ground state of well-known antiferromagnetic oxides such as NiO, Fe2O3, Cr2O3 and MnO2. Furthermore, we identify the ground-state spin ordering in more complicated materials such as Mn3O4 and CoCr2O4. PMID:28458746

Effects of land use change on soil carbon cycling in the conterminous United States from 1900 to 2050

Treesearch

Peter B. Woodbury; Linda S. Heath; James E. Smith

2007-01-01

We developed matrices representing historical area transitions between forest and other land uses. We projected future transitions on the basis of historical transitions and econometric model results. These matrices were used to drive a model of changes in soil and forest floor carbon stocks. Our model predicted net carbon emission from 1900 until 1982, then...

Dynamics of embryonic stem cell differentiation inferred from single-cell transcriptomics show a series of transitions through discrete cell states

PubMed Central

Jang, Sumin; Choubey, Sandeep; Furchtgott, Leon; Zou, Ling-Nan; Doyle, Adele; Menon, Vilas; Loew, Ethan B; Krostag, Anne-Rachel; Martinez, Refugio A; Madisen, Linda; Levi, Boaz P; Ramanathan, Sharad

2017-01-01

The complexity of gene regulatory networks that lead multipotent cells to acquire different cell fates makes a quantitative understanding of differentiation challenging. Using a statistical framework to analyze single-cell transcriptomics data, we infer the gene expression dynamics of early mouse embryonic stem (mES) cell differentiation, uncovering discrete transitions across nine cell states. We validate the predicted transitions across discrete states using flow cytometry. Moreover, using live-cell microscopy, we show that individual cells undergo abrupt transitions from a naïve to primed pluripotent state. Using the inferred discrete cell states to build a probabilistic model for the underlying gene regulatory network, we further predict and experimentally verify that these states have unique response to perturbations, thus defining them functionally. Our study provides a framework to infer the dynamics of differentiation from single cell transcriptomics data and to build predictive models of the gene regulatory networks that drive the sequence of cell fate decisions during development. DOI: http://dx.doi.org/10.7554/eLife.20487.001 PMID:28296635

Grassland-shrubland state transitions in arid lands: Competition matters

USDA-ARS?s Scientific Manuscript database

Background/Question/Methods: State transition from grassland to shrubland is synonymous with desertification in many dryland systems. The classic desertification model emphasizes abiotic feedbacks that modify the physical environment in ways that promote shrub proliferation and impede grass survival...

A single Markov-type kinetic model accounting for the macroscopic currents of all human voltage-gated sodium channel isoforms.

PubMed

Balbi, Pietro; Massobrio, Paolo; Hellgren Kotaleski, Jeanette

2017-09-01

Modelling ionic channels represents a fundamental step towards developing biologically detailed neuron models. Until recently, the voltage-gated ion channels have been mainly modelled according to the formalism introduced by the seminal works of Hodgkin and Huxley (HH). However, following the continuing achievements in the biophysical and molecular comprehension of these pore-forming transmembrane proteins, the HH formalism turned out to carry limitations and inconsistencies in reproducing the ion-channels electrophysiological behaviour. At the same time, Markov-type kinetic models have been increasingly proven to successfully replicate both the electrophysiological and biophysical features of different ion channels. However, in order to model even the finest non-conducting molecular conformational change, they are often equipped with a considerable number of states and related transitions, which make them computationally heavy and less suitable for implementation in conductance-based neurons and large networks of those. In this purely modelling study we develop a Markov-type kinetic model for all human voltage-gated sodium channels (VGSCs). The model framework is detailed, unifying (i.e., it accounts for all ion-channel isoforms) and computationally efficient (i.e. with a minimal set of states and transitions). The electrophysiological data to be modelled are gathered from previously published studies on whole-cell patch-clamp experiments in mammalian cell lines heterologously expressing the human VGSC subtypes (from NaV1.1 to NaV1.9). By adopting a minimum sequence of states, and using the same state diagram for all the distinct isoforms, the model ensures the lightest computational load when used in neuron models and neural networks of increasing complexity. The transitions between the states are described by original ordinary differential equations, which represent the rate of the state transitions as a function of voltage (i.e., membrane potential). The kinetic model, developed in the NEURON simulation environment, appears to be the simplest and most parsimonious way for a detailed phenomenological description of the human VGSCs electrophysiological behaviour.

Description of strong M1 transitions between 4^+ states at N=52 within the sdg-IBM-2

NASA Astrophysics Data System (ADS)

Casperson, R. J.; Werner, V.; Heinze, S.

2009-10-01

The interplay between collective and single-particle degrees of freedom for nuclei near the N=50 shell closure have recently been under investigation. In Molybdenum and Ruthenium nuclei, collective symmetric and mixed-symmetric structures have been identified, while in Zirconium, underlying shell-structure plays an enhanced role. The one-phonon 2^+ mixed-symmetry state was identified from its strong M1 transition to the 2^+1 state. Similar transitions were observed between 4^+ states in ^94Mo and ^92Zr, and shell model calculations indicate that hexadecapole excitations play a role. These phenomena will be investigated within the sdg-Interacting Boson Model-2 in order to gain a better understanding about the structure of the states involved, and to which extent the hexadecapole degree of freedom is important at relatively low energies. First calculations within this model, using an F-spin conserving Hamiltonian to disentangle symmetric and mixed- symmetric structures, will be presented and compared to data.

Laser Induced Optical Pumping Measurements of Cross Sections for Fine and Hyperfine Structure Transitions in Sodium Induced by Collisions with Helium Argon Atoms

NASA Technical Reports Server (NTRS)

Dobson, Chris C.; Sung, C. C.

1998-01-01

Optical pumping of the ground states of sodium can radically alter the shape of the laser induced fluorescence excitation spectrum, complicating measurements of temperature, pressure, etc., which are based on these spectra. Modeling of the fluorescence using rate equations for the eight hyperfine states of the sodium D manifolds can be used to quantify the contribution to the ground state pumping of transitions among the hyperfine excited states induced by collisions with buffer gas atoms. This model is used here to determine, from the shape of experimental spectra, cross sections for (Delta)F transitions of the P(sub 3/2) state induced by collisions with helium and argon atoms, for a range of values assumed for the P(sub 1/2), (Delta)F cross sections. The hyperfine cross sections measured using this method, which is thought to be novel, are compared with cross sections for transitions involving polarized magnetic substates, m(sub F), measured previously using polarization sensitive absorption. Also, fine structure transition ((Delta)J) cross sections were measured in the pumped vapor, giving agreement with previous measurements made in the absence of pumping.

Laser-Induced Optical Pumping Measurements of Cross Section for Fine- and Hyperfine-Structure Transitions in Sodium Induced by Collisions with Helium and Argon Atoms

NASA Technical Reports Server (NTRS)

Dobson, Chris C.; Sung, C. C.

1999-01-01

Optical pumping of the ground states of sodium can radically alter the shape of the laser-induced fluorescence excitation spectrum, complicating measurements of temperature, pressure, etc., which are based on these spectra. Modeling of the fluorescence using rate equations for the eight hyperfine states of the sodium D manifolds can be used to quantify the contribution to the ground state pumping of transitions among the hyperfine excited states induced by collisions with buffer gas atoms. This model is used here to determine, from the shape of experimental spectra, cross sections lor DELTA.F transitions of the P(sub 3/2) state induced by collisions with helium and argon atoms, for a range of values assumed for the P(sub 1/2), DELTA.F cross sections. The hyperfine cross sections measured using this method, which to our knowledge is novel, are compared with cross sections for transitions involving polarized magnetic substates m(sub F) measured previously using polarization sensitive absorption. Also, fine-structure transition cross sections were measured in the pumped vapor, giving agreement with previous measurements made in the absence of pumping.

Transitions across cognitive states and death among older adults in relation to education: A multistate survival model using data from six longitudinal studies.

PubMed

Robitaille, Annie; van den Hout, Ardo; Machado, Robson J M; Bennett, David A; Čukić, Iva; Deary, Ian J; Hofer, Scott M; Hoogendijk, Emiel O; Huisman, Martijn; Johansson, Boo; Koval, Andriy V; van der Noordt, Maaike; Piccinin, Andrea M; Rijnhart, Judith J M; Singh-Manoux, Archana; Skoog, Johan; Skoog, Ingmar; Starr, John; Vermunt, Lisa; Clouston, Sean; Muniz Terrera, Graciela

2018-04-01

This study examines the role of educational attainment, an indicator of cognitive reserve, on transitions in later life between cognitive states (normal Mini-Mental State Examination (MMSE), mild MMSE impairment, and severe MMSE impairment) and death. Analysis of six international longitudinal studies was performed using a coordinated approach. Multistate survival models were used to estimate the transition patterns via different cognitive states. Life expectancies were estimated. Across most studies, a higher level of education was associated with a lower risk of transitioning from normal MMSE to mild MMSE impairment but was not associated with other transitions. Those with higher levels of education and socioeconomic status had longer nonimpaired life expectancies. This study highlights the importance of education in later life and that early life experiences can delay later compromised cognitive health. This study also demonstrates the feasibility and benefit in conducting coordinated analysis across multiple studies to validate findings. Copyright © 2017 the Alzheimer's Association. Published by Elsevier Inc. All rights reserved.

Transition from complete synchronization to spatio-temporal chaos in coupled chaotic systems with nonhyperbolic and hyperbolic attractors

NASA Astrophysics Data System (ADS)

Rybalova, Elena; Semenova, Nadezhda; Strelkova, Galina; Anishchenko, Vadim

2017-06-01

We study the transition from coherence (complete synchronization) to incoherence (spatio-temporal chaos) in ensembles of nonlocally coupled chaotic maps with nonhyperbolic and hyperbolic attractors. As basic models of a partial element we use the Henon map and the Lozi map. We show that the transition to incoherence in a ring of coupled Henon maps occurs through the appearance of phase and amplitude chimera states. An ensemble of coupled Lozi maps demonstrates the coherence-incoherence transition via solitary states and no chimera states are observed in this case.

Magnetoelectric Effect in a Spin-State Transition System

NASA Astrophysics Data System (ADS)

Naka, Makoto; Mizoguchi, Eriko; Nasu, Joji; Ishihara, Sumio

2018-06-01

Magnetic, dielectric, and magnetoelectric properties in a spin-state transition system are examined, motivated by the recent discovery of multiferroic behavior in a cobalt oxide. We construct an effective model Hamiltonian on the basis of the two-orbital Hubbard model, in which the spin-state degrees of freedom in magnetic ions couple with ferroelectric-type lattice distortions. A phase transition occurs from the high-temperature low-spin phase to the low-temperature high-spin ferroelectric phase with an accompanying increase in spin entropy. The calculated results are consistent with the experimental pressure-temperature phase diagram. We predict the magnetic-field induced electric polarization in the low-spin paraelectric phase near the ferroelectric phase boundary.

Chapter 5: Application of state-and-transition models to evaluate wildlife habitat

Treesearch

Anita T. Morzillo; Pamela Comeleo; Blair Csuti; Stephanie Lee

2014-01-01

Wildlife habitat analysis often is a central focus of natural resources management and policy. State-and-transition models (STMs) allow for simulation of landscape level ecological processes, and for managers to test “what if” scenarios of how those processes may affect wildlife habitat. This chapter describes the methods used to link STM output to wildlife habitat to...

Chapter 3: Simulating fire hazard across landscapes through time: integrating state-and-transition models with the Fuel Characteristic Classification System

Treesearch

Jessica E. Halofsky; Stephanie K. Hart; Miles A. Hemstrom; Joshua S. Halofsky; Morris C. Johnson

2014-01-01

Information on the effects of management activities such as fuel reduction treatments and of processes such as vegetation growth and disturbance on fire hazard can help land managers prioritize treatments across a landscape to best meet management goals. State-and-transition models (STMs) allow landscape-scale simulations that incorporate effects of succession,...

Analysis of the E2 transitions for /sup 3/H-/alpha/ cluster states of /sup 7/Li by the resonating group method

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

Xu Pu; Zhao Xuan; Zeng Fanan

1989-07-01

It is suggested that the ground state and the 1st, 2nd, and 3rd excited states of /sup 7/Li are /sup 3/H-/alpha/ cluster-structure states. Using the resonating group method (RGM), the eigenvalues and eigenfunctions of these states as well as the reduced E2 transition probabilities between these states are calculated and are consistent with the experimental values. The results show that the RGM is much better than the harmonic oscillator model used by Bernheim /ital et/ /ital al/. in predicting the E2 transition rates.

Structure of low-lying states of {sup 10,11}C from proton elastic and inelastic scattering

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

Jouanne, C.; Lapoux, V.; Auger, F.

2005-07-01

To probe the ground state and transition densities, elastic and inelastic scattering on a proton target were measured in inverse kinematics for the unstable {sup 10}C and {sup 11}C nuclei at 45.3 and 40.6 MeV/nucleon, respectively. The detection of the recoil proton was performed by the MUST telescope array, in coincidence with a wall of scintillators for the quasiprojectile. The differential cross sections for elastic and inelastic scattering to the first excited states are compared to the optical model calculations performed within the framework of the microscopic nucleon-nucleus Jeukenne-Lejeune-Mahaux potential. Elastic scattering is sensitive to the matter-root-mean square radius foundmore » to be 2.42{+-}0.1 and 2.33{+-}0.1 fm, for {sup 10,11}C, respectively. The transition densities from cluster and mean-field models are tested, and the cluster model predicts the correct order of magnitude of cross sections for the transitions of both isotopes. Using the Bohr-Mottelson prescription, a profile for the {sup 10}C transition density from the 0{sup +} ground to the 2{sub 1}{sup +} state is deduced from the data. The corresponding neutron transition matrix element is extracted: M{sub n}=5.51{+-}1.09 fm{sup 2}.« less

Kinetics of First-Row Transition Metal Cations (V+, Fe+, Co+) with OCS at Thermal Energies.

PubMed

Sweeny, Brendan C; Ard, Shaun G; Shuman, Nicholas S; Viggiano, Albert A

2018-05-03

The temperature-dependent kinetics for reactions of V + , Fe + , and Co + with OCS are measured using a selected ion flow tube apparatus heated to 300-600 K. All three reactions proceed solely by C-S activation at thermal energies, resulting in metal sulfide cation formation. Previously calculated reaction pathways were employed to inform statistical modeling of these reactions for comparison to the data. As surmised previously, all three reactions at thermal energies require spin crossing, with the Fe + reaction crossing once circumventing a prohibitive transition state, before crossing again to form ground state products. The Fe + and Co + reaction efficiencies increase with energy. For the Co + reaction, and to a lesser extent the Fe + reaction, the apparent activation energies are less than the reaction endothermicities, possibly indicating increasing diabatic behavior of the spin crossings with energy. The V + reaction was well modeled assuming an entirely adiabatic spin crossing, such that the resultant avoided crossing behaves similarly to a tight transition state. The subsequent reaction of VS + with OCS producing VS 2 + is also investigated; the rate-limiting transition state energy derived from statistical modeling is poorly reproduced by quantum calculations using a variety of methods, highlighting the large (1-2 eV) uncertainty in calculated energetics of transition-metal containing species.

Typology of State Types: Persistence and Transition

DTIC Science & Technology

2015-04-28

is the lack of positive transition among the weakest states. Our findings are derived from a minimalist construct of a refined time series dataset...states based on a „ minimalist ‟ construct of the Country Indicators for Foreign Policy (CIFP) fragile states project and its core structural...begin with the rationale for developing a minimalist construct of a state typology model (STM), similar to the approach taken by Gravingholt, Ziaja

Abnormal sleep/wake dynamics in orexin knockout mice.

PubMed

Diniz Behn, Cecilia G; Klerman, Elizabeth B; Mochizuki, Takatoshi; Lin, Shih-Chieh; Scammell, Thomas E

2010-03-01

Narcolepsy with cataplexy is caused by a loss of orexin (hypocretin) signaling, but the physiologic mechanisms that result in poor maintenance of wakefulness and fragmented sleep remain unknown. Conventional scoring of sleep cannot reveal much about the process of transitioning between states or the variations within states. We developed an EEG spectral analysis technique to determine whether the state instability in a mouse model of narcolepsy reflects abnormal sleep or wake states, faster movements between states, or abnormal transitions between states. We analyzed sleep recordings in orexin knockout (OXKO) mice and wild type (WT) littermates using a state space analysis technique. This non-categorical approach allows quantitative and unbiased examination of sleep/wake states and state transitions. OXKO mice spent less time in deep, delta-rich NREM sleep and in active, theta-rich wake and instead spent more time near the transition zones between states. In addition, while in the midst of what should be stable wake, OXKO mice initiated rapid changes into NREM sleep with high velocities normally seen only in transition regions. Consequently, state transitions were much more frequent and rapid even though the EEG progressions during state transitions were normal. State space analysis enables visualization of the boundaries between sleep and wake and shows that narcoleptic mice have less distinct and more labile states of sleep and wakefulness. These observations provide new perspectives on the abnormal state dynamics resulting from disrupted orexin signaling and highlight the usefulness of state space analysis in understanding narcolepsy and other sleep disorders.

Best Practices for Leading a Transition to Standards-Based Grading in Secondary Schools

ERIC Educational Resources Information Center

Carter, Alexander B.

2016-01-01

Educational policy researchers have concluded that if U.S. schools transition from the traditional model of grading and reporting to a uniform standards-based grading and reporting model, students would benefit academically. However, very few middle and high schools in the United States have made the transition to standards-based grading. This…

Automated Transition State Search and Its Application to Diverse Types of Organic Reactions.

PubMed

Jacobson, Leif D; Bochevarov, Art D; Watson, Mark A; Hughes, Thomas F; Rinaldo, David; Ehrlich, Stephan; Steinbrecher, Thomas B; Vaitheeswaran, S; Philipp, Dean M; Halls, Mathew D; Friesner, Richard A

2017-11-14

Transition state search is at the center of multiple types of computational chemical predictions related to mechanistic investigations, reactivity and regioselectivity predictions, and catalyst design. The process of finding transition states in practice is, however, a laborious multistep operation that requires significant user involvement. Here, we report a highly automated workflow designed to locate transition states for a given elementary reaction with minimal setup overhead. The only essential inputs required from the user are the structures of the separated reactants and products. The seamless workflow combining computational technologies from the fields of cheminformatics, molecular mechanics, and quantum chemistry automatically finds the most probable correspondence between the atoms in the reactants and the products, generates a transition state guess, launches a transition state search through a combined approach involving the relaxing string method and the quadratic synchronous transit, and finally validates the transition state via the analysis of the reactive chemical bonds and imaginary vibrational frequencies as well as by the intrinsic reaction coordinate method. Our approach does not target any specific reaction type, nor does it depend on training data; instead, it is meant to be of general applicability for a wide variety of reaction types. The workflow is highly flexible, permitting modifications such as a choice of accuracy, level of theory, basis set, or solvation treatment. Successfully located transition states can be used for setting up transition state guesses in related reactions, saving computational time and increasing the probability of success. The utility and performance of the method are demonstrated in applications to transition state searches in reactions typical for organic chemistry, medicinal chemistry, and homogeneous catalysis research. In particular, applications of our code to Michael additions, hydrogen abstractions, Diels-Alder cycloadditions, carbene insertions, and an enzyme reaction model involving a molybdenum complex are shown and discussed.

Methods used to parameterize the spatially-explicit components of a state-and-transition simulation model

USGS Publications Warehouse

Sleeter, Rachel; Acevedo, William; Soulard, Christopher E.; Sleeter, Benjamin M.

2015-01-01

Spatially-explicit state-and-transition simulation models of land use and land cover (LULC) increase our ability to assess regional landscape characteristics and associated carbon dynamics across multiple scenarios. By characterizing appropriate spatial attributes such as forest age and land-use distribution, a state-and-transition model can more effectively simulate the pattern and spread of LULC changes. This manuscript describes the methods and input parameters of the Land Use and Carbon Scenario Simulator (LUCAS), a customized state-and-transition simulation model utilized to assess the relative impacts of LULC on carbon stocks for the conterminous U.S. The methods and input parameters are spatially explicit and describe initial conditions (strata, state classes and forest age), spatial multipliers, and carbon stock density. Initial conditions were derived from harmonization of multi-temporal data characterizing changes in land use as well as land cover. Harmonization combines numerous national-level datasets through a cell-based data fusion process to generate maps of primary LULC categories. Forest age was parameterized using data from the North American Carbon Program and spatially-explicit maps showing the locations of past disturbances (i.e. wildfire and harvest). Spatial multipliers were developed to spatially constrain the location of future LULC transitions. Based on distance-decay theory, maps were generated to guide the placement of changes related to forest harvest, agricultural intensification/extensification, and urbanization. We analyze the spatially-explicit input parameters with a sensitivity analysis, by showing how LUCAS responds to variations in the model input. This manuscript uses Mediterranean California as a regional subset to highlight local to regional aspects of land change, which demonstrates the utility of LUCAS at many scales and applications.

Ising tricriticality in the extended Hubbard model with bond dimerization

NASA Astrophysics Data System (ADS)

Fehske, Holger; Ejima, Satoshi; Lange, Florian; Essler, Fabian H. L.

We explore the quantum phase transition between Peierls and charge-density-wave insulating states in the one-dimensional, half-filled, extended Hubbard model with explicit bond dimerization. We show that the critical line of the continuous Ising transition terminates at a tricritical point, belonging to the universality class of the tricritical Ising model with central charge c=7/10. Above this point, the quantum phase transition becomes first order. Employing a numerical matrix-product-state based (infinite) density-matrix renormalization group method we determine the ground-state phase diagram, the spin and two-particle charge excitations gaps, and the entanglement properties of the model with high precision. Performing a bosonization analysis we can derive a field description of the transition region in terms of a triple sine-Gordon model. This allows us to derive field theory predictions for the power-law (exponential) decay of the density-density (spin-spin) and bond-order-wave correlation functions, which are found to be in excellent agreement with our numerical results. This work was supported by Deutsche Forschungsgemeinschaft (Germany), SFB 652, project B5, and by the EPSRC under Grant No. EP/N01930X/1 (FHLE).

Correlation and nonlocality measures as indicators of quantum phase transitions in several critical systems

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

Altintas, Ferdi, E-mail: ferdialtintas@ibu.edu.tr; Eryigit, Resul, E-mail: resul@ibu.edu.tr

2012-12-15

We have investigated the quantum phase transitions in the ground states of several critical systems, including transverse field Ising and XY models as well as XY with multiple spin interactions, XXZ and the collective system Lipkin-Meshkov-Glick models, by using different quantumness measures, such as entanglement of formation, quantum discord, as well as its classical counterpart, measurement-induced disturbance and the Clauser-Horne-Shimony-Holt-Bell function. Measurement-induced disturbance is found to detect the first and second order phase transitions present in these critical systems, while, surprisingly, it is found to fail to signal the infinite-order phase transition present in the XXZ model. Remarkably, the Clauser-Horne-Shimony-Holt-Bellmore » function is found to detect all the phase transitions, even when quantum and classical correlations are zero for the relevant ground state. - Highlights: Black-Right-Pointing-Pointer The ability of correlation measures to detect quantum phase transitions has been studied. Black-Right-Pointing-Pointer Measurement induced disturbance fails to detect the infinite order phase transition. Black-Right-Pointing-Pointer CHSH-Bell function detects all phase transitions even when the bipartite density matrix is uncorrelated.« less

CellTrans: An R Package to Quantify Stochastic Cell State Transitions.

PubMed

Buder, Thomas; Deutsch, Andreas; Seifert, Michael; Voss-Böhme, Anja

2017-01-01

Many normal and cancerous cell lines exhibit a stable composition of cells in distinct states which can, e.g., be defined on the basis of cell surface markers. There is evidence that such an equilibrium is associated with stochastic transitions between distinct states. Quantifying these transitions has the potential to better understand cell lineage compositions. We introduce CellTrans, an R package to quantify stochastic cell state transitions from cell state proportion data from fluorescence-activated cell sorting and flow cytometry experiments. The R package is based on a mathematical model in which cell state alterations occur due to stochastic transitions between distinct cell states whose rates only depend on the current state of a cell. CellTrans is an automated tool for estimating the underlying transition probabilities from appropriately prepared data. We point out potential analytical challenges in the quantification of these cell transitions and explain how CellTrans handles them. The applicability of CellTrans is demonstrated on publicly available data on the evolution of cell state compositions in cancer cell lines. We show that CellTrans can be used to (1) infer the transition probabilities between different cell states, (2) predict cell line compositions at a certain time, (3) predict equilibrium cell state compositions, and (4) estimate the time needed to reach this equilibrium. We provide an implementation of CellTrans in R, freely available via GitHub (https://github.com/tbuder/CellTrans).

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

USGS Publications Warehouse

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

2014-01-01

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

Enhancing pairwise state-transition weights: A new weighting scheme in simulated tempering that can minimize transition time between a pair of conformational states

NASA Astrophysics Data System (ADS)

Qiao, Qin; Zhang, Hou-Dao; Huang, Xuhui

2016-04-01

Simulated tempering (ST) is a widely used enhancing sampling method for Molecular Dynamics simulations. As one expanded ensemble method, ST is a combination of canonical ensembles at different temperatures and the acceptance probability of cross-temperature transitions is determined by both the temperature difference and the weights of each temperature. One popular way to obtain the weights is to adopt the free energy of each canonical ensemble, which achieves uniform sampling among temperature space. However, this uniform distribution in temperature space may not be optimal since high temperatures do not always speed up the conformational transitions of interest, as anti-Arrhenius kinetics are prevalent in protein and RNA folding. Here, we propose a new method: Enhancing Pairwise State-transition Weights (EPSW), to obtain the optimal weights by minimizing the round-trip time for transitions among different metastable states at the temperature of interest in ST. The novelty of the EPSW algorithm lies in explicitly considering the kinetics of conformation transitions when optimizing the weights of different temperatures. We further demonstrate the power of EPSW in three different systems: a simple two-temperature model, a two-dimensional model for protein folding with anti-Arrhenius kinetics, and the alanine dipeptide. The results from these three systems showed that the new algorithm can substantially accelerate the transitions between conformational states of interest in the ST expanded ensemble and further facilitate the convergence of thermodynamics compared to the widely used free energy weights. We anticipate that this algorithm is particularly useful for studying functional conformational changes of biological systems where the initial and final states are often known from structural biology experiments.

Enhancing pairwise state-transition weights: A new weighting scheme in simulated tempering that can minimize transition time between a pair of conformational states

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

Qiao, Qin, E-mail: qqiao@ust.hk; Zhang, Hou-Dao; Huang, Xuhui, E-mail: xuhuihuang@ust.hk

2016-04-21

Simulated tempering (ST) is a widely used enhancing sampling method for Molecular Dynamics simulations. As one expanded ensemble method, ST is a combination of canonical ensembles at different temperatures and the acceptance probability of cross-temperature transitions is determined by both the temperature difference and the weights of each temperature. One popular way to obtain the weights is to adopt the free energy of each canonical ensemble, which achieves uniform sampling among temperature space. However, this uniform distribution in temperature space may not be optimal since high temperatures do not always speed up the conformational transitions of interest, as anti-Arrhenius kineticsmore » are prevalent in protein and RNA folding. Here, we propose a new method: Enhancing Pairwise State-transition Weights (EPSW), to obtain the optimal weights by minimizing the round-trip time for transitions among different metastable states at the temperature of interest in ST. The novelty of the EPSW algorithm lies in explicitly considering the kinetics of conformation transitions when optimizing the weights of different temperatures. We further demonstrate the power of EPSW in three different systems: a simple two-temperature model, a two-dimensional model for protein folding with anti-Arrhenius kinetics, and the alanine dipeptide. The results from these three systems showed that the new algorithm can substantially accelerate the transitions between conformational states of interest in the ST expanded ensemble and further facilitate the convergence of thermodynamics compared to the widely used free energy weights. We anticipate that this algorithm is particularly useful for studying functional conformational changes of biological systems where the initial and final states are often known from structural biology experiments.« less

Optimal trajectories of brain state transitions

PubMed Central

Gu, Shi; Betzel, Richard F.; Mattar, Marcelo G.; Cieslak, Matthew; Delio, Philip R.; Grafton, Scott T.; Pasqualetti, Fabio; Bassett, Danielle S.

2017-01-01

The complexity of neural dynamics stems in part from the complexity of the underlying anatomy. Yet how white matter structure constrains how the brain transitions from one cognitive state to another remains unknown. Here we address this question by drawing on recent advances in network control theory to model the underlying mechanisms of brain state transitions as elicited by the collective control of region sets. We find that previously identified attention and executive control systems are poised to affect a broad array of state transitions that cannot easily be classified by traditional engineering-based notions of control. This theoretical versatility comes with a vulnerability to injury. In patients with mild traumatic brain injury, we observe a loss of specificity in putative control processes, suggesting greater susceptibility to neurophysiological noise. These results offer fundamental insights into the mechanisms driving brain state transitions in healthy cognition and their alteration following injury. PMID:28088484

Transition V & VI in Alabama: A Profile of Commitment. State Conference Proceedings.

ERIC Educational Resources Information Center

Browning, Philip; Rabren, Karen

This publication provides information on the Alabama Transition Initiative for students with disabilities, including papers presented at two statewide transition conferences. Conference papers include: (1) "Pell City School System's Community Transition Team Model" (Deloris Frasier); (2) "Alabama's MH/MR Service Coordinators in…

Using Markov Chains to predict the natural progression of diabetic retinopathy

PubMed Central

Srikanth, Priyanka

2015-01-01

AIM To study the natural progression of diabetic retinopathy in patients with type 2 diabetes. METHODS This was an observational study of 153 cases with type 2 diabetes from 2010 to 2013. The state of patient was noted at end of each year and transition matrices were developed to model movement between years. Patients who progressed to severe non-proliferative diabetic retinopathy (NPDR) were treated. Markov Chains and Chi-square test were used for statistical analysis. RESULTS We modelled the transition of 153 patients from NPDR to blindness on an annual basis. At the end of year 3, we compared results from the Markov model versus actual data. The results from Chi-square test confirmed that there was statistically no significant difference (P=0.70) which provided assurance that the model was robust to estimate mean sojourn times. The key finding was that a patient entering the system in mild NPDR state is expected to stay in that state for 5y followed by 1.07y in moderate NPDR, be in the severe NPDR state for 1.33y before moving into PDR for roughly 8y. It is therefore expected that such a patient entering the model in a state of mild NPDR will enter blindness after 15.29y. CONCLUSION Patients stay for long time periods in mild NPDR before transitioning into moderate NPDR. However, they move rapidly from moderate NPDR to proliferative diabetic retinopathy (PDR) and stay in that state for long periods before transitioning into blindness. PMID:25709923

A Stochastic Dynamic Programming Model With Fuzzy Storage States Applied to Reservoir Operation Optimization

NASA Astrophysics Data System (ADS)

Mousavi, Seyed Jamshid; Mahdizadeh, Kourosh; Afshar, Abbas

2004-08-01

Application of stochastic dynamic programming (SDP) models to reservoir optimization calls for state variables discretization. As an important variable discretization of reservoir storage volume has a pronounced effect on the computational efforts. The error caused by storage volume discretization is examined by considering it as a fuzzy state variable. In this approach, the point-to-point transitions between storage volumes at the beginning and end of each period are replaced by transitions between storage intervals. This is achieved by using fuzzy arithmetic operations with fuzzy numbers. In this approach, instead of aggregating single-valued crisp numbers, the membership functions of fuzzy numbers are combined. Running a simulated model with optimal release policies derived from fuzzy and non-fuzzy SDP models shows that a fuzzy SDP with a coarse discretization scheme performs as well as a classical SDP having much finer discretized space. It is believed that this advantage in the fuzzy SDP model is due to the smooth transitions between storage intervals which benefit from soft boundaries.

Sensitivity of peptide conformational dynamics on clustering of a classical molecular dynamics trajectory

NASA Astrophysics Data System (ADS)

Jensen, Christian H.; Nerukh, Dmitry; Glen, Robert C.

2008-03-01

We investigate the sensitivity of a Markov model with states and transition probabilities obtained from clustering a molecular dynamics trajectory. We have examined a 500ns molecular dynamics trajectory of the peptide valine-proline-alanine-leucine in explicit water. The sensitivity is quantified by varying the boundaries of the clusters and investigating the resulting variation in transition probabilities and the average transition time between states. In this way, we represent the effect of clustering using different clustering algorithms. It is found that in terms of the investigated quantities, the peptide dynamics described by the Markov model is sensitive to the clustering; in particular, the average transition times are found to vary up to 46%. Moreover, inclusion of nonphysical sparsely populated clusters can lead to serious errors of up to 814%. In the investigation, the time step used in the transition matrix is determined by the minimum time scale on which the system behaves approximately Markovian. This time step is found to be about 100ps. It is concluded that the description of peptide dynamics with transition matrices should be performed with care, and that using standard clustering algorithms to obtain states and transition probabilities may not always produce reliable results.

Continuous and discontinuous transitions to synchronization.

PubMed

Wang, Chaoqing; Garnier, Nicolas B

2016-11-01

We describe how the transition to synchronization in a system of globally coupled Stuart-Landau oscillators changes from continuous to discontinuous when the nature of the coupling is moved from diffusive to reactive. We explain this drastic qualitative change as resulting from the co-existence of a particular synchronized macrostate together with the trivial incoherent macrostate, in a range of parameter values for which the latter is linearly stable. In contrast to the paradigmatic Kuramoto model, this particular state observed at the synchronization transition contains a finite, non-vanishing number of synchronized oscillators, which results in a discontinuous transition. We consider successively two situations where either a fully synchronized state or a partially synchronized state exists at the transition. Thermodynamic limit and finite size effects are briefly discussed, as well as connections with recently observed discontinuous transitions.

Downscaling global land-use/land-cover projections for use in region-level state-and-transition simulation modeling

USGS Publications Warehouse

Sherba, Jason T.; Sleeter, Benjamin M.; Davis, Adam W.; Parker, Owen P.

2015-01-01

Global land-use/land-cover (LULC) change projections and historical datasets are typically available at coarse grid resolutions and are often incompatible with modeling applications at local to regional scales. The difficulty of downscaling and reapportioning global gridded LULC change projections to regional boundaries is a barrier to the use of these datasets in a state-and-transition simulation model (STSM) framework. Here we compare three downscaling techniques to transform gridded LULC transitions into spatial scales and thematic LULC classes appropriate for use in a regional STSM. For each downscaling approach, Intergovernmental Panel on Climate Change (IPCC) Representative Concentration Pathway (RCP) LULC projections, at the 0.5 × 0.5 cell resolution, were downscaled to seven Level III ecoregions in the Pacific Northwest, United States. RCP transition values at each cell were downscaled based on the proportional distribution between ecoregions of (1) cell area, (2) land-cover composition derived from remotely-sensed imagery, and (3) historic LULC transition values from a LULC history database. Resulting downscaled LULC transition values were aggregated according to their bounding ecoregion and “cross-walked” to relevant LULC classes. Ecoregion-level LULC transition values were applied in a STSM projecting LULC change between 2005 and 2100. While each downscaling methods had advantages and disadvantages, downscaling using the historical land-use history dataset consistently apportioned RCP LULC transitions in agreement with historical observations. Regardless of the downscaling method, some LULC projections remain improbable and require further investigation.

Ground-state fidelity and bipartite entanglement in the Bose-Hubbard model.

PubMed

Buonsante, P; Vezzani, A

2007-03-16

We analyze the quantum phase transition in the Bose-Hubbard model borrowing two tools from quantum-information theory, i.e., the ground-state fidelity and entanglement measures. We consider systems at unitary filling comprising up to 50 sites and show for the first time that a finite-size scaling analysis of these quantities provides excellent estimates for the quantum critical point. We conclude that fidelity is particularly suited for revealing a quantum phase transition and pinning down the critical point thereof, while the success of entanglement measures depends on the mechanisms governing the transition.

Estimation of Survival Probabilities for Use in Cost-effectiveness Analyses: A Comparison of a Multi-state Modeling Survival Analysis Approach with Partitioned Survival and Markov Decision-Analytic Modeling

PubMed Central

Williams, Claire; Lewsey, James D.; Mackay, Daniel F.; Briggs, Andrew H.

2016-01-01

Modeling of clinical-effectiveness in a cost-effectiveness analysis typically involves some form of partitioned survival or Markov decision-analytic modeling. The health states progression-free, progression and death and the transitions between them are frequently of interest. With partitioned survival, progression is not modeled directly as a state; instead, time in that state is derived from the difference in area between the overall survival and the progression-free survival curves. With Markov decision-analytic modeling, a priori assumptions are often made with regard to the transitions rather than using the individual patient data directly to model them. This article compares a multi-state modeling survival regression approach to these two common methods. As a case study, we use a trial comparing rituximab in combination with fludarabine and cyclophosphamide v. fludarabine and cyclophosphamide alone for the first-line treatment of chronic lymphocytic leukemia. We calculated mean Life Years and QALYs that involved extrapolation of survival outcomes in the trial. We adapted an existing multi-state modeling approach to incorporate parametric distributions for transition hazards, to allow extrapolation. The comparison showed that, due to the different assumptions used in the different approaches, a discrepancy in results was evident. The partitioned survival and Markov decision-analytic modeling deemed the treatment cost-effective with ICERs of just over £16,000 and £13,000, respectively. However, the results with the multi-state modeling were less conclusive, with an ICER of just over £29,000. This work has illustrated that it is imperative to check whether assumptions are realistic, as different model choices can influence clinical and cost-effectiveness results. PMID:27698003

Estimation of Survival Probabilities for Use in Cost-effectiveness Analyses: A Comparison of a Multi-state Modeling Survival Analysis Approach with Partitioned Survival and Markov Decision-Analytic Modeling.

PubMed

Williams, Claire; Lewsey, James D; Mackay, Daniel F; Briggs, Andrew H

2017-05-01

Modeling of clinical-effectiveness in a cost-effectiveness analysis typically involves some form of partitioned survival or Markov decision-analytic modeling. The health states progression-free, progression and death and the transitions between them are frequently of interest. With partitioned survival, progression is not modeled directly as a state; instead, time in that state is derived from the difference in area between the overall survival and the progression-free survival curves. With Markov decision-analytic modeling, a priori assumptions are often made with regard to the transitions rather than using the individual patient data directly to model them. This article compares a multi-state modeling survival regression approach to these two common methods. As a case study, we use a trial comparing rituximab in combination with fludarabine and cyclophosphamide v. fludarabine and cyclophosphamide alone for the first-line treatment of chronic lymphocytic leukemia. We calculated mean Life Years and QALYs that involved extrapolation of survival outcomes in the trial. We adapted an existing multi-state modeling approach to incorporate parametric distributions for transition hazards, to allow extrapolation. The comparison showed that, due to the different assumptions used in the different approaches, a discrepancy in results was evident. The partitioned survival and Markov decision-analytic modeling deemed the treatment cost-effective with ICERs of just over £16,000 and £13,000, respectively. However, the results with the multi-state modeling were less conclusive, with an ICER of just over £29,000. This work has illustrated that it is imperative to check whether assumptions are realistic, as different model choices can influence clinical and cost-effectiveness results.

Identifying and correcting non-Markov states in peptide conformational dynamics

NASA Astrophysics Data System (ADS)

Nerukh, Dmitry; Jensen, Christian H.; Glen, Robert C.

2010-02-01

Conformational transitions in proteins define their biological activity and can be investigated in detail using the Markov state model. The fundamental assumption on the transitions between the states, their Markov property, is critical in this framework. We test this assumption by analyzing the transitions obtained directly from the dynamics of a molecular dynamics simulated peptide valine-proline-alanine-leucine and states defined phenomenologically using clustering in dihedral space. We find that the transitions are Markovian at the time scale of ≈50 ps and longer. However, at the time scale of 30-40 ps the dynamics loses its Markov property. Our methodology reveals the mechanism that leads to non-Markov behavior. It also provides a way of regrouping the conformations into new states that now possess the required Markov property of their dynamics.

Transitions to Synchrony in Coupled Bursting Neurons

NASA Astrophysics Data System (ADS)

Dhamala, Mukeshwar; Jirsa, Viktor K.; Ding, Mingzhou

2004-01-01

Certain cells in the brain, for example, thalamic neurons during sleep, show spike-burst activity. We study such spike-burst neural activity and the transitions to a synchronized state using a model of coupled bursting neurons. In an electrically coupled network, we show that the increase of coupling strength increases incoherence first and then induces two different transitions to synchronized states, one associated with bursts and the other with spikes. These sequential transitions to synchronized states are determined by the zero crossings of the maximum transverse Lyapunov exponents. These results suggest that synchronization of spike-burst activity is a multi-time-scale phenomenon and burst synchrony is a precursor to spike synchrony.

Nonequilibrium phase transition in a self-activated biological network.

PubMed

Berry, Hugues

2003-03-01

We present a lattice model for a two-dimensional network of self-activated biological structures with a diffusive activating agent. The model retains basic and simple properties shared by biological systems at various observation scales, so that the structures can consist of individuals, tissues, cells, or enzymes. Upon activation, a structure emits a new mobile activator and remains in a transient refractory state before it can be activated again. Varying the activation probability, the system undergoes a nonequilibrium second-order phase transition from an active state, where activators are present, to an absorbing, activator-free state, where each structure remains in the deactivated state. We study the phase transition using Monte Carlo simulations and evaluate the critical exponents. As they do not seem to correspond to known values, the results suggest the possibility of a separate universality class.

MHD Simulation for Investigating the Dynamic State Transition Responsible for a Solar Eruption in Active Region 12158

NASA Astrophysics Data System (ADS)

Lee, Hwanhee; Magara, Tetsuya

2018-06-01

We present a magnetohydrodynamic model of solar eruption based on the dynamic state transition from the quasi-static state to the eruptive state of an active region (AR) magnetic field. For the quasi-static state before an eruption, we consider the existence of a slow solar wind originating from an AR, which may continuously make the AR magnetic field deviate from mechanical equilibrium. In this model, we perform a three-dimensional magnetohydrodynamic simulation of AR 12158 producing a coronal mass ejection, where the initial magnetic structure of the simulation is given by a nonlinear force-free field derived from an observed photospheric vector magnetic field. We then apply a pressure-driven outflow to the upper part of the magnetic structure to achieve a quasi-static pre-eruptive state. The simulation shows that the eruptive process observed in this AR may be caused by the dynamic state transition of an AR magnetic field, which is essentially different from the destabilization of a static magnetic field. The dynamic state transition is determined from the shape evolution of the magnetic field line according to the κH-mechanism. This work demonstrates how the mechanism works to produce a solar eruption in the dynamic solar corona governed by the gravitational field and the continuous outflows of solar wind.

Rates of transition between amyloid and neurodegeneration biomarker states and to dementia among non-demented individuals: a population-based cohort study

PubMed Central

Jack, Clifford R.; Therneau, Terry M.; Wiste, Heather J.; Weigand, Stephen D.; Knopman, David S.; Lowe, Val J.; Mielke, Michelle M.; Vemuri, Prashanthi; Roberts, Rosebud O.; Machulda, Mary M.; Senjem, Matthew L.; Gunter, Jeffrey L.; Rocca, Walter A.; Petersen, Ronald C.

2016-01-01

Summary Background We previously observed in a cross-sectional analysis that frequencies of amyloid and neurodegeneration biomarker states varied greatly by age among cognitively non-impaired participants, suggesting dynamic within-person processes. Our objective in this longitudinal study was to estimate rates of transitioning from a less- to a more-abnormal biomarker state by age among non-demented individuals, as well as rates of transitioning to dementia by biomarker state. Methods All participants (n=4049) were non-demented at baseline. A subset of 1541 underwent multi-modality imaging. Amyloid PET was used to classify individuals as amyloid positive (A+) or negative (A−). FDG PET and MRI were used to classify individuals as neurodegeneration positive (N+) or negative (N−). All observations from the 4049 individuals were used in a multi-state model to estimate four different age-specific biomarker state transition rates among non-demented individuals: A−N− to A+N−; A−N− to A−N+ (suspected non-Alzheimer pathology, SNAP); A+N− to A+N+; A−N+ (SNAP) to A+N+. We also estimated two age-specific rates to dementia: A+N+ to dementia; and A−N+ (SNAP) to dementia. Using these state-to-state transition rates, we estimated biomarker state frequencies by age. Findings All transition rates were low at age 50 and (with one exception) were well-characterized by an exponential increase with age. The rates per 100-person years at ages 65 versus 85 were 1.6 versus 17.2 for A−N− to A−N+, 6.1 versus 20.8 for A+N− to A+N+, 2.6 versus 13.2 for A−N+ to A+N+, 0.8 versus 7.0 for A+N+ to dementia, and 0.6 versus 1.7 for A−N+ to dementia. The one exception to an exponential increase with age was the transition rate from A−N− to A+N− which increased from 4.0 transitions per 100 person-years at age 65 to approximately 7 transitions per 100 person-years in the 70s and then plateaued beyond that age. Estimated biomarker frequencies by age from the multistate model were similar to cross-sectional biomarker frequencies. Interpretation Dynamic state-to-state transition rates illustrate important measurable aspects of the changing biology underlying brain aging. The biomarker states we describe relate to both AD and non-AD processes. Our transition rates suggest that brain aging can be conceptualized as a nearly inevitable acceleration toward worse biomarker and clinical states. The one exception was that transition to amyloidosis without neurodegeneration was most dynamic from age 60 to 70 and then plateaued beyond that age. We found that simple transition rates can explain complex, highly interdependent biomarker state frequencies in our sample. PMID:26597325

Ab initio-informed maximum entropy modeling of rovibrational relaxation and state-specific dissociation with application to the O2 + O system

NASA Astrophysics Data System (ADS)

Kulakhmetov, Marat; Gallis, Michael; Alexeenko, Alina

2016-05-01

Quasi-classical trajectory (QCT) calculations are used to study state-specific ro-vibrational energy exchange and dissociation in the O2 + O system. Atom-diatom collisions with energy between 0.1 and 20 eV are calculated with a double many body expansion potential energy surface by Varandas and Pais [Mol. Phys. 65, 843 (1988)]. Inelastic collisions favor mono-quantum vibrational transitions at translational energies above 1.3 eV although multi-quantum transitions are also important. Post-collision vibrational favoring decreases first exponentially and then linearly as Δv increases. Vibrationally elastic collisions (Δv = 0) favor small ΔJ transitions while vibrationally inelastic collisions have equilibrium post-collision rotational distributions. Dissociation exhibits both vibrational and rotational favoring. New vibrational-translational (VT), vibrational-rotational-translational (VRT) energy exchange, and dissociation models are developed based on QCT observations and maximum entropy considerations. Full set of parameters for state-to-state modeling of oxygen is presented. The VT energy exchange model describes 22 000 state-to-state vibrational cross sections using 11 parameters and reproduces vibrational relaxation rates within 30% in the 2500-20 000 K temperature range. The VRT model captures 80 × 106 state-to-state ro-vibrational cross sections using 19 parameters and reproduces vibrational relaxation rates within 60% in the 5000-15 000 K temperature range. The developed dissociation model reproduces state-specific and equilibrium dissociation rates within 25% using just 48 parameters. The maximum entropy framework makes it feasible to upscale ab initio simulation to full nonequilibrium flow calculations.

Shape coexistence and evolution in 98Sr

NASA Astrophysics Data System (ADS)

Park, J.; Garnsworthy, A. B.; Krücken, R.; Andreoiu, C.; Ball, G. C.; Bender, P. C.; Chester, A.; Close, A.; Finlay, P.; Garrett, P. E.; Glister, J.; Hackman, G.; Hadinia, B.; Leach, K. G.; Rand, E. T.; Sjue, S.; Starosta, K.; Svensson, C. E.; Tardiff, E.

2016-01-01

Shape coexistence between the strongly deformed ground state and the weakly deformed 02+ state in 98Sr has been a major topic of interest due to the energy difference of 215 keV, which is the smallest in all even-even nuclei. The electric monopole transition strength ρ2(E 0 ) is an important quantity that can relate the deformation difference and the shape mixing between the two 0+ states, which are admixtures of the vibrational (S) and the rotational (D) states in a simple mixing model. In a β -decay spectroscopy experiment, the experimental ρ2(E 0 ) was measured. A value of 0.053(5) is consistent with the previous measurement and was combined with known electric quadrupole transition strengths B (E 2 ) in calculations of a two-state mixing model. Based on a systematic study on neighboring Kr, Zr, and Mo isotopes, the mixing of the 0+ and 2+ states in 98Sr was determined to be 8.6% and 1.3%, respectively, corresponding to deformation parameters βD=0.38 (1 ) and βS=-0.23 (2 ) . These parameters reproduce experimental transition strengths well except for the 41+→21+ transition, which suggests a smaller D-band deformation for J ≥4 .

Absorption spectra and optical transitions in InAs/GaAs self-assembled quantum dots

NASA Astrophysics Data System (ADS)

Cusack, M. A.; Briddon, P. R.; Jaros, M.

1997-08-01

We have applied the multiband effective mass/valence force field method to the calculation of optical transitions and absorption spectra in InAs/GaAs self-organized dots of different sizes. We have found that the apparently conflicting assignments of luminescence features to optical transitions in different experiments are in fact entirely compatible with each other. Whether the optical signature of a dot is constructed from transitions between states of the same quantum numbers, or via additional processes between the ground conduction state and a low-lying valence state depends on the aspect ratio of the quantum dot radius and height. The states involved can be predicted from a simple particle in a rigid rectangular box model.

Non-equilibrium phase transitions in a driven-dissipative system of interacting bosons

NASA Astrophysics Data System (ADS)

Young, Jeremy T.; Foss-Feig, Michael; Gorshkov, Alexey V.; Maghrebi, Mohammad F.

2017-04-01

Atomic, molecular, and optical systems provide unique opportunities to study simple models of driven-dissipative many-body quantum systems. Typically, one is interested in the resultant steady state, but the non-equilibrium nature of the physics involved presents several problems in understanding its behavior theoretically. Recently, it has been shown that in many of these models, it is possible to map the steady-state phase transitions onto classical equilibrium phase transitions. In the language of Keldysh field theory, this relation typically only becomes apparent after integrating out massive fields near the critical point, leaving behind a single massless field undergoing near-equilibrium dynamics. In this talk, we study a driven-dissipative XXZ bosonic model and discover critical points at which two fields become gapless. Each critical point separates three different possible phases: a uniform phase, an anti-ferromagnetic phase, and a limit cycle phase. Furthermore, a description in terms of an equilibrium phase transition does not seem possible, so the associated phase transitions appear to be inherently non-equilibrium.

A New Multiphase Equation of State for SiO 2

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

Maerzke, Katie A.; Gammel, J. Tinka

SiO 2 is found as α-quartz at ambient conditions. Under shock compression, it transforms into a much higher density stishovite-like phase around 20 GPa, then into a liquid phase above 100 GPa. The SESAME library contains older equations of state for α-quartz, polycrystalline quartz, and fused quartz. These equations of state model the material as a single phase; i.e., there is no high pressure phase transition. Somewhat more recently (in 1992), Jon Boettger published equations of state for α-quartz, coesite, and stishovite, along with a phase transition model to mix them. However, we do not have a multiphase EOS thatmore » captures the phase transitions in this material. Others are working on a high-accuracy model for very high pressure SiO 2, since liquid quartz is used as an impedance matching standard above 100 GPa; however, we are focused on the 10-50 GPa range. This intermediate pressure range is most relevant for modeling the decomposition products of silicone polymers such as Sylgard 184 and SX358.« less

Applications of neural networks to the studies of phase transitions of two-dimensional Potts models

NASA Astrophysics Data System (ADS)

Li, C.-D.; Tan, D.-R.; Jiang, F.-J.

2018-04-01

We study the phase transitions of two-dimensional (2D) Q-states Potts models on the square lattice, using the first principles Monte Carlo (MC) simulations as well as the techniques of neural networks (NN). We demonstrate that the ideas from NN can be adopted to study these considered phase transitions efficiently. In particular, even with a simple NN constructed in this investigation, we are able to obtain the relevant information of the nature of these phase transitions, namely whether they are first order or second order. Our results strengthen the potential applicability of machine learning in studying various states of matters. Subtlety of applying NN techniques to investigate many-body systems is briefly discussed as well.

Phase of the Wilson line at high temperature in the standard model

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

Korthals Altes, C.P.; Lee, K.; Pisarski, R.D.

1994-09-26

We compute the effective potential for the phase of the Wilson line at high temperature in the standard model to one-loop order. Besides the trivial vacua, there are metastable states in the direction of U(1) hypercharge. Assuming that the Universe starts out in such a metastable state at the Planck scale, it easily persists to the time of the electroweak phase transition, which then proceeds by an unusual mechanism. All remnants of the metastable state evaporate about the time of the QCD phase transition.

Signatures of the Mott transition in the antiferromagnetic state of the two-dimensional Hubbard model

DOE PAGES

Fratino, L.; Sémon, P.; Charlebois, M.; ...

2017-06-06

The properties of a phase with large correlation length can be strongly influenced by the underlying normal phase. Here, we illustrate this by studying the half-filled two-dimensional Hubbard model using cellular dynamical mean-field theory with continuous-time quantum Monte Carlo. Sharp crossovers in the mechanism that favors antiferromagnetic correlations and in the corresponding local density of states are observed. We found that these crossovers occur at values of the interaction strength U and temperature T that are controlled by the underlying normal-state Mott transition.

General three-state model with biased population replacement: Analytical solution and application to language dynamics

NASA Astrophysics Data System (ADS)

Colaiori, Francesca; Castellano, Claudio; Cuskley, Christine F.; Loreto, Vittorio; Pugliese, Martina; Tria, Francesca

2015-01-01

Empirical evidence shows that the rate of irregular usage of English verbs exhibits discontinuity as a function of their frequency: the most frequent verbs tend to be totally irregular. We aim to qualitatively understand the origin of this feature by studying simple agent-based models of language dynamics, where each agent adopts an inflectional state for a verb and may change it upon interaction with other agents. At the same time, agents are replaced at some rate by new agents adopting the regular form. In models with only two inflectional states (regular and irregular), we observe that either all verbs regularize irrespective of their frequency, or a continuous transition occurs between a low-frequency state, where the lemma becomes fully regular, and a high-frequency one, where both forms coexist. Introducing a third (mixed) state, wherein agents may use either form, we find that a third, qualitatively different behavior may emerge, namely, a discontinuous transition in frequency. We introduce and solve analytically a very general class of three-state models that allows us to fully understand these behaviors in a unified framework. Realistic sets of interaction rules, including the well-known naming game (NG) model, result in a discontinuous transition, in agreement with recent empirical findings. We also point out that the distinction between speaker and hearer in the interaction has no effect on the collective behavior. The results for the general three-state model, although discussed in terms of language dynamics, are widely applicable.

A multi-state model examining patterns of transitioning among states of engagement in care in HIV-positive individuals initiating combination antiretroviral therapy

PubMed Central

Gillis, Jennifer; Loutfy, Mona; Bayoumi, Ahmed M; Antoniou, Tony; Burchell, Ann N; Walmsley, Sharon; Cooper, Curtis; Klein, Marina B.; Machouf, Nima; Montaner, Julio SG; Rourke, Sean B.; Tsoukas, Christos; Hogg, Robert; Raboud, Janet

2016-01-01

Background Common measures of engagement in care fail to acknowledge that infrequent follow-up may occur either intentionally among patients with sustained virologic suppression or unintentionally among patients with poor clinical outcomes. Methods Five states of HIV care were defined within the Canadian Observational Cohort (CANOC) Collaboration following combination antiretroviral therapy (cART) initiation: (1) guidelines HIV care (suppressed viral load (VL) and CD4 >200 cells/mm3, no gaps in cART >3 months, no gaps in CD4 or VL measurement >6 months), (2) successful care with decreased frequency of follow-up (as above except no gaps in CD4 or VL measurement >12 months), (3) suboptimal care (unsuppressed VL, CD4<200 cells/mm3 on 2 consecutive visits, ≥1 gap in cART >3 months, or ≥1 gap in CD4 or VL measurement >12 months), (4) loss to follow-up (no contact for 18 months), and (5) death. Multi-state models were used to determine factors associated with transitioning among states. Results 7810 participants were included. Younger age, female gender, Indigenous ethnicity and people who have injected drugs (PWID) were associated with increased likelihoods of transitioning from guidelines to suboptimal care and decreased likelihoods of transitioning from suboptimal to guidelines care. One-fifth of individuals in successful, decreased follow-up after cART initiation (mean sojourn time 0.72 years) were in suboptimal care in subsequent years. Conclusions Using routinely collected data, we have developed a flexible framework that characterizes patient transitions among states of HIV clinical care. We have demonstrated that multi-state models provide a useful approach to supplement ‘cascade of care’ work. PMID:27851713

Metastable state en route to traveling-wave synchronization state

NASA Astrophysics Data System (ADS)

Park, Jinha; Kahng, B.

2018-02-01

The Kuramoto model with mixed signs of couplings is known to produce a traveling-wave synchronized state. Here, we consider an abrupt synchronization transition from the incoherent state to the traveling-wave state through a long-lasting metastable state with large fluctuations. Our explanation of the metastability is that the dynamic flow remains within a limited region of phase space and circulates through a few active states bounded by saddle and stable fixed points. This complex flow generates a long-lasting critical behavior, a signature of a hybrid phase transition. We show that the long-lasting period can be controlled by varying the density of inhibitory/excitatory interactions. We discuss a potential application of this transition behavior to the recovery process of human consciousness.

Exploring extensions to multi-state models with multiple unobservable states

USGS Publications Warehouse

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

2009-01-01

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

The paradox of Foxd3: how does it function in pluripotency and differentiation of embryonic stem cells?

PubMed

Plank-Bazinet, Jennifer L; Mundell, Nathan A

2016-01-01

Uncommitted cells of the early mammalian embryo transition through distinct stages of pluripotency, including establishment of ground state "naïve" pluripotency in the early epiblast, transition to a post-implantation "primed" state, and subsequent lineage commitment of the gastrulating epiblast. Previous transcriptional profiling of in vitro models to recapitulate early to late epiblast transition and differentiation suggest that distinct gene regulatory networks are likely to function in each of these states. While the mechanisms underlying transition between pluripotent states are poorly understood, the forkhead family transcription factor Foxd3 has emerged as a key regulatory factor. Foxd3 is required to maintain pluripotent cells of the murine epiblast and for survival, self-renewal and pluripotency of embryonic stem cells (ESCs). Two recent, simultaneous studies have shed light on how Foxd3 regulates gene expression in early cell fate transitions of progenitor cells. While the two publications shared some common findings, they also presented some conflicting results and suggest different models for the mechanisms underlying Foxd3 function. Here, we discuss the key similarities and differences between the publications, highlight data from the literature relevant to their findings, and hypothesize a potential mechanism of Foxd3 action.

Transition sum rules in the shell model

NASA Astrophysics Data System (ADS)

Lu, Yi; Johnson, Calvin W.

2018-03-01

An important characterization of electromagnetic and weak transitions in atomic nuclei are sum rules. We focus on the non-energy-weighted sum rule (NEWSR), or total strength, and the energy-weighted sum rule (EWSR); the ratio of the EWSR to the NEWSR is the centroid or average energy of transition strengths from an nuclear initial state to all allowed final states. These sum rules can be expressed as expectation values of operators, which in the case of the EWSR is a double commutator. While most prior applications of the double commutator have been to special cases, we derive general formulas for matrix elements of both operators in a shell model framework (occupation space), given the input matrix elements for the nuclear Hamiltonian and for the transition operator. With these new formulas, we easily evaluate centroids of transition strength functions, with no need to calculate daughter states. We apply this simple tool to a number of nuclides and demonstrate the sum rules follow smooth secular behavior as a function of initial energy, as well as compare the electric dipole (E 1 ) sum rule against the famous Thomas-Reiche-Kuhn version. We also find surprising systematic behaviors for ground-state electric quadrupole (E 2 ) centroids in the s d shell.

Transition state analysis of Trypanosoma cruzi uridine phosphorylase-catalyzed arsenolysis of uridine

PubMed Central

Silva, Rafael G.; Vetticatt, Mathew J.; Merino, Emilio F.; Cassera, Maria B.; Schramm, Vern L.

2011-01-01

Uridine phosphorylase catalyzes the reversible phosphorolysis of uridine and 2′-deoxyuridine to generate uracil and (2-deoxy)ribose 1-phosphate, an important step in the pyrimidine salvage pathway. The coding sequence annotated as a putative nucleoside phosphorylase in the Trypanosoma cruzi genome was overexpressed in Escherichia coli, purified to homogeneity, and shown to be a homodimeric uridine phosphorylase, with similar specificity for uridine and 2′-deoxyuridine, and undetectable activity towards thymidine and purine nucleosides. Competitive kinetic isotope effects (KIEs) were measured and corrected for a forward commitment factor using arsenate as the nucleophile. The intrinsic KIEs are: 1′-14C = 1.103, 1,3-15N2 = 1.034, 3-15N = 1.004, 1-15N = 1.030, 1′-3H = 1.132, 2′-2H = 1.086 and 5′-3H2 = 1.041 for this reaction. Density functional theory was employed to quantitatively interpret the KIEs in terms of transition state structure and geometry. Matching of experimental KIEs to proposed transition state structures suggests an almost synchronous, SN2-like transition state model, in which the ribosyl moiety possesses significant bond order to both nucleophile and leaving group. Natural bond orbital analysis allowed a comparison of the charge distribution pattern between the ground state and the transition state model. PMID:21599004

Describing a Strongly Correlated Model System with Density Functional Theory.

PubMed

Kong, Jing; Proynov, Emil; Yu, Jianguo; Pachter, Ruth

2017-07-06

The linear chain of hydrogen atoms, a basic prototype for the transition from a metal to Mott insulator, is studied with a recent density functional theory model functional for nondynamic and strong correlation. The computed cohesive energy curve for the transition agrees well with accurate literature results. The variation of the electronic structure in this transition is characterized with a density functional descriptor that yields the atomic population of effectively localized electrons. These new methods are also applied to the study of the Peierls dimerization of the stretched even-spaced Mott insulator to a chain of H 2 molecules, a different insulator. The transitions among the two insulating states and the metallic state of the hydrogen chain system are depicted in a semiquantitative phase diagram. Overall, we demonstrate the capability of studying strongly correlated materials with a mean-field model at the fundamental level, in contrast to the general pessimistic view on such a feasibility.

Nuclear Structure of the Closed Subshell Nucleus 90Zr Studied with the (n,n'(gamma)) Reaction

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

Garrett, P E; Younes, Y; Becker, J A

States in {sup 90}Zr have been observed with the (n,n{prime}{gamma}) reaction using both spallation and monoenergetic accelerator-produced neutrons. A scheme comprised of 81 levels and 157 transitions was constructed concentrating on levels below 5.6 MeV in excitation energy. Spins have been determined by considering data from all experimental studies performed for {sup 90}Zr. Lifetimes have been deduced using the Doppler-shift attenuation method for many of the states and transition rates have been obtained. A spherical shell-model interpretation in terms of particle-hole excitations assuming a {sup 88}Sr closed core is given. In some cases, enhancements in B(M1) and B(E2) values aremore » observed that cannot be explained by assuming simple particle-hole excitations. Shell-model calculations using an extended f pg-shell model space reproduce the spectrum of excited states very well, and the gross features of the B(M1) and B(E2) transition rates. Transition rates for individual levels show discrepancies between calculations and experimental values.« less

Non-monotonicity and divergent time scale in Axelrod model dynamics

NASA Astrophysics Data System (ADS)

Vazquez, F.; Redner, S.

2007-04-01

We study the evolution of the Axelrod model for cultural diversity, a prototypical non-equilibrium process that exhibits rich dynamics and a dynamic phase transition between diversity and an inactive state. We consider a simple version of the model in which each individual possesses two features that can assume q possibilities. Within a mean-field description in which each individual has just a few interaction partners, we find a phase transition at a critical value qc between an active, diverse state for q < qc and a frozen state. For q lesssim qc, the density of active links is non-monotonic in time and the asymptotic approach to the steady state is controlled by a time scale that diverges as (q-qc)-1/2.

Using hidden Markov models to align multiple sequences.

PubMed

Mount, David W

2009-07-01

A hidden Markov model (HMM) is a probabilistic model of a multiple sequence alignment (msa) of proteins. In the model, each column of symbols in the alignment is represented by a frequency distribution of the symbols (called a "state"), and insertions and deletions are represented by other states. One moves through the model along a particular path from state to state in a Markov chain (i.e., random choice of next move), trying to match a given sequence. The next matching symbol is chosen from each state, recording its probability (frequency) and also the probability of going to that state from a previous one (the transition probability). State and transition probabilities are multiplied to obtain a probability of the given sequence. The hidden nature of the HMM is due to the lack of information about the value of a specific state, which is instead represented by a probability distribution over all possible values. This article discusses the advantages and disadvantages of HMMs in msa and presents algorithms for calculating an HMM and the conditions for producing the best HMM.

Toward a theory of the general-anesthetic-induced phase transition of the cerebral cortex. I. A thermodynamics analogy

NASA Astrophysics Data System (ADS)

Steyn-Ross, Moira L.; Steyn-Ross, D. A.; Sleigh, J. W.; Wilcocks, Lara C.

2001-07-01

In a recent paper the authors developed a stochastic model for the response of the cerebral cortex to a general anesthetic agent. The model predicted that there would be an anesthetic-induced phase change at the point of transition into unconsciousness, manifested as a divergence in the electroencephalogram spectral power, and a change in spectral energy distribution from being relatively broadband in the conscious state to being strongly biased towards much lower frequencies in the unconscious state. Both predictions have been verified in recent clinical measurements. In the present paper we extend the model by calculating the equilibrium distribution function for the cortex, allowing us to establish a correspondence between the cortical phase transition and the more familiar thermodynamic phase transitions. This correspondence is achieved by first identifying a cortical free energy function, then by postulating that there exists an inverse relationship between an anesthetic effect and a quantity we define as cortical excitability, which plays a role analogous to temperature in thermodynamic phase transitions. We follow standard thermodynamic theory to compute a cortical entropy and a cortical ``heat capacity,'' and we investigate how these will vary with anesthetic concentration. The significant result is the prediction that the entropy will decrease discontinuously at the moment of induction into unconsciousness, concomitant with a release of ``latent heat'' which should manifest as a divergence in the analogous heat capacity. There is clear clinical evidence of heat capacity divergence in historical anesthetic-effect measurements performed in 1977 by Stullken et al. [Anesthesiology 46, 28 (1977)]. The discontinuous step change in cortical entropy suggests that the cortical phase transition is analogous to a first-order thermodynamic transition in which the comatose-quiescent state is strongly ordered, while the active cortical state is relatively disordered.

Relaxation dynamics of magnetization transitions in synthetic antiferromagnet with perpendicular anisotropy

NASA Astrophysics Data System (ADS)

Talantsev, A.; Lu, Y.; Fache, T.; Lavanant, M.; Hamadeh, A.; Aristov, A.; Koplak, O.; Morgunov, R.; Mangin, S.

2018-04-01

Two synthetic antiferromagnet bilayer systems with strong perpendicular anisotropy CoFeB/Ta/CoFeB and Pt/Co/Ir/Co/Pt have been grown using sputtering techniques. For both systems two types of magnetization transitions have been studied. The first one concerns transitions from a state where magnetizations of the two magnetic layers are parallel (P state) to a state where magnetizations of the two layers are aligned antiparallel (AP state). The second one concerns transitions between the two possible antiparallel alignments (AP+  to AP-). For both systems and both transitions after-effect measurements can be understood in the frame of nucleation—propagation model. Time derivative analysis of magnetic relaxation curves and mapping of the first order reversal curves at different temperature allowed us to demonstrate the presence of different pinning centers, which number can be controlled by magnetic field and temperature.

Towards a Model of Cold Denaturation of Proteins

NASA Astrophysics Data System (ADS)

Sanchez, Isaac

2010-10-01

Proteins/enzymes can undergo cold denaturation or cold deactivation. In the active or natured state, a protein exists in a unique folded/ordered state. In the deactivated (denatured) state, a protein unfolds and exists in a disordered expanded state. This protein folding/unfolding or order/disorder transition can be triggered by a temperature change. What seems paradoxical is that the active (ordered) state can be induced by heating, or equivalently, the disordered inactive state can be induced by cooling. This is equivalent to an Ising spin model passing from a disordered array of spins to an ordered array by increasing temperature! Hydrogels and their corresponding polyelectrolyte chains behave similarly, i.e., the swollen disordered state can be induced by cooling while the more ordered collapsed or globular state is induced by heating (an entropically driven phase transition). In a living cell at the physiological temperature of 37 C, activation and deactivation of proteins is triggered by local environmental changes in pH, salinity, etc. The important physics is that the denaturation temperature can be moved up or down relative to 37 C by these stimuli. Moving the transition temperature up can destabilize the active protein while moving it down leads to stabilization. An analytical polymer model will be described that exhibits cold denaturation behavior.

Population projections for AIDS using an actuarial model.

PubMed

Wilkie, A D

1989-09-05

This paper gives details of a model for forecasting AIDS, developed for actuarial purposes, but used also for population projections. The model is only appropriate for homosexual transmission, but it is age-specific, and it allows variation in the transition intensities by age, duration in certain states and calendar year. The differential equations controlling transitions between states are defined, the method of numerical solution is outlined, and the parameters used in five different Bases of projection are given in detail. Numerical results for the population of England and Wales are shown.

Gain control through divisive inhibition prevents abrupt transition to chaos in a neural mass model.

PubMed

Papasavvas, Christoforos A; Wang, Yujiang; Trevelyan, Andrew J; Kaiser, Marcus

2015-09-01

Experimental results suggest that there are two distinct mechanisms of inhibition in cortical neuronal networks: subtractive and divisive inhibition. They modulate the input-output function of their target neurons either by increasing the input that is needed to reach maximum output or by reducing the gain and the value of maximum output itself, respectively. However, the role of these mechanisms on the dynamics of the network is poorly understood. We introduce a novel population model and numerically investigate the influence of divisive inhibition on network dynamics. Specifically, we focus on the transitions from a state of regular oscillations to a state of chaotic dynamics via period-doubling bifurcations. The model with divisive inhibition exhibits a universal transition rate to chaos (Feigenbaum behavior). In contrast, in an equivalent model without divisive inhibition, transition rates to chaos are not bounded by the universal constant (non-Feigenbaum behavior). This non-Feigenbaum behavior, when only subtractive inhibition is present, is linked to the interaction of bifurcation curves in the parameter space. Indeed, searching the parameter space showed that such interactions are impossible when divisive inhibition is included. Therefore, divisive inhibition prevents non-Feigenbaum behavior and, consequently, any abrupt transition to chaos. The results suggest that the divisive inhibition in neuronal networks could play a crucial role in keeping the states of order and chaos well separated and in preventing the onset of pathological neural dynamics.

The properties of the anti-tumor model with coupling non-Gaussian noise and Gaussian colored noise

NASA Astrophysics Data System (ADS)

Guo, Qin; Sun, Zhongkui; Xu, Wei

2016-05-01

The anti-tumor model with correlation between multiplicative non-Gaussian noise and additive Gaussian-colored noise has been investigated in this paper. The behaviors of the stationary probability distribution demonstrate that the multiplicative non-Gaussian noise plays a dual role in the development of tumor and an appropriate additive Gaussian colored noise can lead to a minimum of the mean value of tumor cell population. The mean first passage time is calculated to quantify the effects of noises on the transition time of tumors between the stable states. An increase in both the non-Gaussian noise intensity and the departure from the Gaussian noise can accelerate the transition from the disease state to the healthy state. On the contrary, an increase in cross-correlated degree will slow down the transition. Moreover, the correlation time can enhance the stability of the disease state.

Parallel State Space Construction for a Model Checking Based on Maximality Semantics

NASA Astrophysics Data System (ADS)

El Abidine Bouneb, Zine; Saīdouni, Djamel Eddine

2009-03-01

The main limiting factor of the model checker integrated in the concurrency verification environment FOCOVE [1, 2], which use the maximality based labeled transition system (noted MLTS) as a true concurrency model[3, 4], is currently the amount of available physical memory. Many techniques have been developed to reduce the size of a state space. An interesting technique among them is the alpha equivalence reduction. Distributed memory execution environment offers yet another choice. The main contribution of the paper is to show that the parallel state space construction algorithm proposed in [5], which is based on interleaving semantics using LTS as semantic model, may be adapted easily to the distributed implementation of the alpha equivalence reduction for the maximality based labeled transition systems.

Exotic and excited-state radiative transitions in charmonium from lattice QCD

DOE PAGES

Dudek, Jozef J.; Edwards, Robert G.; Thomas, Christopher E.

2009-05-01

We compute, for the first time using lattice QCD methods, radiative transition rates involving excited charmonium states, states of high spin and exotics. Utilizing a large basis of interpolating fields we are able to project out various excited state contributions to three-point correlators computed on quenched anisotropic lattices. In the first lattice QCD calculation of the exoticmore » $$1^{-+}$$ $$\\eta_{c1}$$ radiative decay, we find a large partial width $$\\Gamma(\\eta_{c1} \\to J/\\psi \\gamma) \\sim 100 \\,\\mathrm{keV}$$. We find clear signals for electric dipole and magnetic quadrupole transition form factors in $$\\chi_{c2} \\to J/\\psi \\gamma$$, calculated for the first time in this framework, and study transitions involving excited $$\\psi$$ and $$\\chi_{c1,2}$$ states. We calculate hindered magnetic dipole transition widths without the sensitivity to assumptions made in model studies and find statistically significant signals, including a non-exotic vector hybrid candidate $Y_{\\mathrm{hyb?}} \\to \\et« less

Tension-dependent structural deformation alters single-molecule transition kinetics.

PubMed

Sudhanshu, B; Mihardja, S; Koslover, E F; Mehraeen, S; Bustamante, C; Spakowitz, A J

2011-02-01

We analyze the response of a single nucleosome to tension, which serves as a prototypical biophysical measurement where tension-dependent deformation alters transition kinetics. We develop a statistical-mechanics model of a nucleosome as a wormlike chain bound to a spool, incorporating fluctuations in the number of bases bound, the spool orientation, and the conformations of the unbound polymer segments. With the resulting free-energy surface, we perform dynamic simulations that permit a direct comparison with experiments. This simple approach demonstrates that the experimentally observed structural states at nonzero tension are a consequence of the tension and that these tension-induced states cease to exist at zero tension. The transitions between states exhibit substantial deformation of the unbound polymer segments. The associated deformation energy increases with tension; thus, the application of tension alters the kinetics due to tension-induced deformation of the transition states. This mechanism would arise in any system where the tether molecule is deformed in the transition state under the influence of tension.

Tension-dependent structural deformation alters single-molecule transition kinetics

PubMed Central

Sudhanshu, B.; Mihardja, S.; Koslover, E. F.; Mehraeen, S.; Bustamante, C.; Spakowitz, A. J.

2011-01-01

We analyze the response of a single nucleosome to tension, which serves as a prototypical biophysical measurement where tension-dependent deformation alters transition kinetics. We develop a statistical-mechanics model of a nucleosome as a wormlike chain bound to a spool, incorporating fluctuations in the number of bases bound, the spool orientation, and the conformations of the unbound polymer segments. With the resulting free-energy surface, we perform dynamic simulations that permit a direct comparison with experiments. This simple approach demonstrates that the experimentally observed structural states at nonzero tension are a consequence of the tension and that these tension-induced states cease to exist at zero tension. The transitions between states exhibit substantial deformation of the unbound polymer segments. The associated deformation energy increases with tension; thus, the application of tension alters the kinetics due to tension-induced deformation of the transition states. This mechanism would arise in any system where the tether molecule is deformed in the transition state under the influence of tension. PMID:21245354

Abnormal Sleep/Wake Dynamics in Orexin Knockout Mice

PubMed Central

Diniz Behn, Cecilia G.; Klerman, Elizabeth B.; Mochizuki, Takatoshi; Lin, Shih-Chieh; Scammell, Thomas E.

2010-01-01

Study Objectives: Narcolepsy with cataplexy is caused by a loss of orexin (hypocretin) signaling, but the physiologic mechanisms that result in poor maintenance of wakefulness and fragmented sleep remain unknown. Conventional scoring of sleep cannot reveal much about the process of transitioning between states or the variations within states. We developed an EEG spectral analysis technique to determine whether the state instability in a mouse model of narcolepsy reflects abnormal sleep or wake states, faster movements between states, or abnormal transitions between states. Design: We analyzed sleep recordings in orexin knockout (OXKO) mice and wild type (WT) littermates using a state space analysis technique. This non-categorical approach allows quantitative and unbiased examination of sleep/wake states and state transitions. Measurements and Results: OXKO mice spent less time in deep, delta-rich NREM sleep and in active, theta-rich wake and instead spent more time near the transition zones between states. In addition, while in the midst of what should be stable wake, OXKO mice initiated rapid changes into NREM sleep with high velocities normally seen only in transition regions. Consequently, state transitions were much more frequent and rapid even though the EEG progressions during state transitions were normal. Conclusions: State space analysis enables visualization of the boundaries between sleep and wake and shows that narcoleptic mice have less distinct and more labile states of sleep and wakefulness. These observations provide new perspectives on the abnormal state dynamics resulting from disrupted orexin signaling and highlight the usefulness of state space analysis in understanding narcolepsy and other sleep disorders. Citation: Diniz Behn CG; Klerman EB; Mochizuki T; Lin S; Scammell TE. Abnormal sleep/wake dynamics in orexin knockout mice. SLEEP 2010;33(3):297-306. PMID:20337187

Equilibrium and kinetics of DNA overstretching modeled with a quartic energy landscape.

PubMed

Argudo, David; Purohit, Prashant K

2014-11-04

It is well known that the dsDNA molecule undergoes a phase transition from B-DNA into an overstretched state at high forces. For some time, the structure of the overstretched state remained unknown and highly debated, but recent advances in experimental techniques have presented evidence of more than one possible phase (or even a mixed phase) depending on ionic conditions, temperature, and basepair sequence. Here, we present a theoretical model to study the overstretching transition with the possibility that the overstretched state is a mixture of two phases: a structure with portions of inner strand separation (melted or M-DNA), and an extended phase that retains the basepair structure (S-DNA). We model the double-stranded DNA as a chain composed of n segments of length l, where the transition is studied by means of a Landau quartic potential with statistical fluctuations. The length l is a measure of cooperativity of the transition and is key to characterizing the overstretched phase. By analyzing the different values of l corresponding to a wide spectrum of experiments, we find that for a range of temperatures and ionic conditions, the overstretched form is likely to be a mix of M-DNA and S-DNA. For a transition close to a pure S-DNA state, where the change in extension is close to 1.7 times the original B-DNA length, we find l ? 25 basepairs regardless of temperature and ionic concentration. Our model is fully analytical, yet it accurately reproduces the force-extension curves, as well as the transient kinetic behavior, seen in DNA overstretching experiments.

Family Structure States and Transitions: Associations with Children's Well-Being during Middle Childhood

ERIC Educational Resources Information Center

Magnuson, Katherine; Berger, Lawrence M.

2009-01-01

Using longitudinal data from the Maternal and Child Supplement of the National Longitudinal Survey of Youth (N = 3,862) and Hierarchical Linear Models, we estimated associations of family structure states and transitions with children's achievement and behavior trajectories during middle childhood. Results suggest that residing in a single-mother…

Charge states of ions, and mechanisms of charge ordering transitions

NASA Astrophysics Data System (ADS)

Pickett, Warren E.; Quan, Yundi; Pardo, Victor

2014-07-01

To gain insight into the mechanism of charge ordering transitions, which conventionally are pictured as a disproportionation of an ion M as 2Mn+→M(n+1)+ + M(n-1)+, we (1) review and reconsider the charge state (or oxidation number) picture itself, (2) introduce new results for the putative charge ordering compound AgNiO2 and the dual charge state insulator AgO, and (3) analyze the cationic occupations of the actual (not formal) charge, and work to reconcile the conundrums that arise. We establish that several of the clearest cases of charge ordering transitions involve no disproportion (no charge transfer between the cations, and hence no charge ordering), and that the experimental data used to support charge ordering can be accounted for within density functional-based calculations that contain no charge transfer between cations. We propose that the charge state picture retains meaning and importance, at least in many cases, if one focuses on Wannier functions rather than atomic orbitals. The challenge of modeling charge ordering transitions with model Hamiltonians isdiscussed.

Front propagation and effect of memory in stochastic desertification models with an absorbing state

NASA Astrophysics Data System (ADS)

Herman, Dor; Shnerb, Nadav M.

2017-08-01

Desertification in dryland ecosystems is considered to be a major environmental threat that may lead to devastating consequences. The concern increases when the system admits two alternative steady states and the transition is abrupt and irreversible (catastrophic shift). However, recent studies show that the inherent stochasticity of the birth-death process, when superimposed on the presence of an absorbing state, may lead to a continuous (second order) transition even if the deterministic dynamics supports a catastrophic transition. Following these works we present here a numerical study of a one-dimensional stochastic desertification model, where the deterministic predictions are confronted with the observed dynamics. Our results suggest that a stochastic spatial system allows for a propagating front only when its active phase invades the inactive (desert) one. In the extinction phase one observes transient front propagation followed by a global collapse. In the presence of a seed bank the vegetation state is shown to be more robust against demographic stochasticity, but the transition in that case still belongs to the directed percolation equivalence class.

Three-state Potts model on non-local directed small-world lattices

NASA Astrophysics Data System (ADS)

Ferraz, Carlos Handrey Araujo; Lima, José Luiz Sousa

2017-10-01

In this paper, we study the non-local directed Small-World (NLDSW) disorder effects in the three-state Potts model as a form to capture the essential features shared by real complex systems where non-locality effects play a important role in the behavior of these systems. Using Monte Carlo techniques and finite-size scaling analysis, we estimate the infinite lattice critical temperatures and the leading critical exponents in this model. In particular, we investigate the first- to second-order phase transition crossover when NLDSW links are inserted. A cluster-flip algorithm was used to reduce the critical slowing down effect in our simulations. We find that for a NLDSW disorder densities p

Remote sensing, geographical information systems, and spatial modeling for analyzing public transit services

NASA Astrophysics Data System (ADS)

Wu, Changshan

Public transit service is a promising transportation mode because of its potential to address urban sustainability. Current ridership of public transit, however, is very low in most urban regions, particularly those in the United States. This woeful transit ridership can be attributed to many factors, among which poor service quality is key. Given this, there is a need for transit planning and analysis to improve service quality. Traditionally, spatially aggregate data are utilized in transit analysis and planning. Examples include data associated with the census, zip codes, states, etc. Few studies, however, address the influences of spatially aggregate data on transit planning results. In this research, previous studies in transit planning that use spatially aggregate data are reviewed. Next, problems associated with the utilization of aggregate data, the so-called modifiable areal unit problem (MAUP), are detailed and the need for fine resolution data to support public transit planning is argued. Fine resolution data is generated using intelligent interpolation techniques with the help of remote sensing imagery. In particular, impervious surface fraction, an important socio-economic indicator, is estimated through a fully constrained linear spectral mixture model using Landsat Enhanced Thematic Mapper Plus (ETM+) data within the metropolitan area of Columbus, Ohio in the United States. Four endmembers, low albedo, high albedo, vegetation, and soil are selected to model heterogeneous urban land cover. Impervious surface fraction is estimated by analyzing low and high albedo endmembers. With the derived impervious surface fraction, three spatial interpolation methods, spatial regression, dasymetric mapping, and cokriging, are developed to interpolate detailed population density. Results suggest that cokriging applied to impervious surface is a better alternative for estimating fine resolution population density. With the derived fine resolution data, a multiple route maximal covering/shortest path (MRMCSP) model is proposed to address the tradeoff between public transit service quality and access coverage in an established bus-based transit system. Results show that it is possible to improve current transit service quality by eliminating redundant or underutilized service stops. This research illustrates that fine resolution data can be efficiently generated to support urban planning, management and analysis. Further, this detailed data may necessitate the development of new spatial optimization models for use in analysis.

Phase diagram of the ultrafast photoinduced insulator-metal transition in vanadium dioxide

NASA Astrophysics Data System (ADS)

Cocker, T. L.; Titova, L. V.; Fourmaux, S.; Holloway, G.; Bandulet, H.-C.; Brassard, D.; Kieffer, J.-C.; El Khakani, M. A.; Hegmann, F. A.

2012-04-01

We use time-resolved terahertz spectroscopy to probe the ultrafast dynamics of the insulator-metal phase transition induced by femtosecond laser pulses in a nanogranular vanadium dioxide (VO2) film. Based on the observed thresholds for characteristic transient terahertz dynamics, a phase diagram of critical pump fluence versus temperature for the insulator-metal phase transition in VO2 is established for the first time over a broad range of temperatures down to 17 K. We find that both Mott and Peierls mechanisms are present in the insulating state and that the photoinduced transition is nonthermal. We propose a critical-threshold model for the ultrafast photoinduced transition based on a critical density of electrons and a critical density of coherently excited phonons necessary for the structural transition to the metallic state. As a result, evidence is found at low temperatures for an intermediate metallic state wherein the Mott state is melted but the Peierls distortion remains intact, consistent with recent theoretical predictions. Finally, the observed terahertz conductivity dynamics above the photoinduced transition threshold reveal nucleation and growth of metallic nanodomains over picosecond time scales.

Hybrid Defect Phase Transition: Renormalization Group and Monte Carlo Analysis

NASA Astrophysics Data System (ADS)

Kaufman, Miron; Diep, H. T.

2010-03-01

For the q-state Potts model with 2 < q <= 4 on the square lattice with a defect line, the order parameter on the defect line jumps discontinuously from zero to a nonzero value while the defect energy varies continuously with the temperature at the critical temperature. Monte-Carlo simulations (H. T. Diep, M. Kaufman, Phys Rev E 2009) of the q-state Potts model on a square lattice with a line of defects verify the renormalization group prediction (M. Kaufman, R. B. Griffiths, Phys Rev B 1982) on the occurrence of the hybrid transition on the defect line. This is interesting since for those q values the bulk transition is continuous. This hybrid (continuous - discontinuous) defect transition is induced by the infinite range correlations at the bulk critical point.

Quantum phase transitions in a two-dimensional quantum XYX model: ground-state fidelity and entanglement.

PubMed

Li, Bo; Li, Sheng-Hao; Zhou, Huan-Qiang

2009-06-01

A systematic analysis is performed for quantum phase transitions in a two-dimensional anisotropic spin-1/2 antiferromagnetic XYX model in an external magnetic field. With the help of an innovative tensor network algorithm, we compute the fidelity per lattice site to demonstrate that the field-induced quantum phase transition is unambiguously characterized by a pinch point on the fidelity surface, marking a continuous phase transition. We also compute an entanglement estimator, defined as a ratio between the one-tangle and the sum of squared concurrences, to identify both the factorizing field and the critical point, resulting in a quantitative agreement with quantum Monte Carlo simulation. In addition, the local order parameter is "derived" from the tensor network representation of the system's ground-state wave functions.

Ab initio-informed maximum entropy modeling of rovibrational relaxation and state-specific dissociation with application to the O{sub 2} + O system

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

Kulakhmetov, Marat, E-mail: mkulakhm@purdue.edu; Alexeenko, Alina, E-mail: alexeenk@purdue.edu; Gallis, Michael, E-mail: magalli@sandia.gov

Quasi-classical trajectory (QCT) calculations are used to study state-specific ro-vibrational energy exchange and dissociation in the O{sub 2} + O system. Atom-diatom collisions with energy between 0.1 and 20 eV are calculated with a double many body expansion potential energy surface by Varandas and Pais [Mol. Phys. 65, 843 (1988)]. Inelastic collisions favor mono-quantum vibrational transitions at translational energies above 1.3 eV although multi-quantum transitions are also important. Post-collision vibrational favoring decreases first exponentially and then linearly as Δv increases. Vibrationally elastic collisions (Δv = 0) favor small ΔJ transitions while vibrationally inelastic collisions have equilibrium post-collision rotational distributions. Dissociationmore » exhibits both vibrational and rotational favoring. New vibrational-translational (VT), vibrational-rotational-translational (VRT) energy exchange, and dissociation models are developed based on QCT observations and maximum entropy considerations. Full set of parameters for state-to-state modeling of oxygen is presented. The VT energy exchange model describes 22 000 state-to-state vibrational cross sections using 11 parameters and reproduces vibrational relaxation rates within 30% in the 2500–20 000 K temperature range. The VRT model captures 80 × 10{sup 6} state-to-state ro-vibrational cross sections using 19 parameters and reproduces vibrational relaxation rates within 60% in the 5000–15 000 K temperature range. The developed dissociation model reproduces state-specific and equilibrium dissociation rates within 25% using just 48 parameters. The maximum entropy framework makes it feasible to upscale ab initio simulation to full nonequilibrium flow calculations.« less

Relatively slow stochastic gene-state switching in the presence of positive feedback significantly broadens the region of bimodality through stabilizing the uninduced phenotypic state.

PubMed

Ge, Hao; Wu, Pingping; Qian, Hong; Xie, Xiaoliang Sunney

2018-03-01

Within an isogenic population, even in the same extracellular environment, individual cells can exhibit various phenotypic states. The exact role of stochastic gene-state switching regulating the transition among these phenotypic states in a single cell is not fully understood, especially in the presence of positive feedback. Recent high-precision single-cell measurements showed that, at least in bacteria, switching in gene states is slow relative to the typical rates of active transcription and translation. Hence using the lac operon as an archetype, in such a region of operon-state switching, we present a fluctuating-rate model for this classical gene regulation module, incorporating the more realistic operon-state switching mechanism that was recently elucidated. We found that the positive feedback mechanism induces bistability (referred to as deterministic bistability), and that the parameter range for its occurrence is significantly broadened by stochastic operon-state switching. We further show that in the absence of positive feedback, operon-state switching must be extremely slow to trigger bistability by itself. However, in the presence of positive feedback, which stabilizes the induced state, the relatively slow operon-state switching kinetics within the physiological region are sufficient to stabilize the uninduced state, together generating a broadened parameter region of bistability (referred to as stochastic bistability). We illustrate the opposite phenotype-transition rate dependence upon the operon-state switching rates in the two types of bistability, with the aid of a recently proposed rate formula for fluctuating-rate models. The rate formula also predicts a maximal transition rate in the intermediate region of operon-state switching, which is validated by numerical simulations in our model. Overall, our findings suggest a biological function of transcriptional "variations" among genetically identical cells, for the emergence of bistability and transition between phenotypic states.

Controlling protein molecular dynamics: How to accelerate folding while preserving the native state

NASA Astrophysics Data System (ADS)

Jensen, Christian H.; Nerukh, Dmitry; Glen, Robert C.

2008-12-01

The dynamics of peptides and proteins generated by classical molecular dynamics (MD) is described by using a Markov model. The model is built by clustering the trajectory into conformational states and estimating transition probabilities between the states. Assuming that it is possible to influence the dynamics of the system by varying simulation parameters, we show how to use the Markov model to determine the parameter values that preserve the folded state of the protein and at the same time, reduce the folding time in the simulation. We investigate this by applying the method to two systems. The first system is an imaginary peptide described by given transition probabilities with a total folding time of 1μs. We find that only small changes in the transition probabilities are needed to accelerate (or decelerate) the folding. This implies that folding times for slowly folding peptides and proteins calculated using MD cannot be meaningfully compared to experimental results. The second system is a four residue peptide valine-proline-alanine-leucine in water. We control the dynamics of the transitions by varying the temperature and the atom masses. The simulation results show that it is possible to find the combinations of parameter values that accelerate the dynamics and at the same time preserve the native state of the peptide. A method for accelerating larger systems without performing simulations for the whole folding process is outlined.

Model of the synthesis of trisporic acid in Mucorales showing bistability.

PubMed

Werner, S; Schroeter, A; Schimek, C; Vlaic, S; Wöstemeyer, J; Schuster, S

2012-12-01

An important substance in the signalling between individuals of Mucor-like fungi is trisporic acid (TA). This compound, together with some of its precursors, serves as a pheromone in mating between (+)- and (-)-mating types. Moreover, intermediates of the TA pathway are exchanged between the two mating partners. Based on differential equations, mathematical models of the synthesis pathways of TA in the two mating types of an idealised Mucor-fungus are here presented. These models include the positive feedback of TA on its own synthesis. The authors compare three sub-models in view of bistability, robustness and the reversibility of transitions. The proposed modelling study showed that, in a system where intermediates are exchanged, a reversible transition between the two stable steady states occurs, whereas an exchange of the end product leads to an irreversible transition. The reversible transition is physiologically favoured, because the high-production state of TA must come to an end eventually. Moreover, the exchange of intermediates and TA is compared with the 3-way handshake widely used by computers linked in a network.

Electric Monopole Transition Strengths in the Stable Nickel Isotopes

NASA Astrophysics Data System (ADS)

Evitts, Lee John

A series of measurements of stable nickel isotopes were performed at the Australian National University in Canberra. Excited states in 58,60,62Ni were populated via inelastic scattering of proton beams delivered by the 14UD Pelletron accelerator. Multiple setups were used in order to determine the structure of low-lying states. The CAESAR array of Compton-suppressed HPGe detectors was used to measure the (E2/M1) mixing ratio of transitions from angular distributions of gamma rays. The Super-e spectrometer was used to measure conversion coefficients for a number of J to J transitions. The data obtained from both devices was combined with previously measured parent lifetimes and branching ratios to determine E0 transition strengths between J-pi transitions. The E0 transition strength for the second 0+ to first 0+ transitions in 60,62Ni have been measured for the first time through internal conversion electron detection. The experimental value of 132(+59,-70) for 62Ni agrees within 2 sigma of the previous result obtained from internal pair formation. However it is likely that the previous experimental results used an outdated theoretical model for internal pair formation emission. This work also represents the first measurements of E0 transition strengths between 2+ states in Ni isotopes. There is generally large E0 strength between the 2+ states, particularly in the second 2+ to first 2+ transition, however there is also a large uncertainty in the measurements owing to the difficulties involved in measuring conversion coefficients. In 62Ni, the E0 transition strength of 172(+62,-77) for the second 2+ to first 2+ transition gives further weight to the argument against the spherical vibrator model, as an E0 transition is forbidden if there is a change of only one phonon. The large measurement also indicates the presence of shape coexistence, complementing the recent experimental work carried out in the neutron-rich Ni isotopes.

Motility-Driven Glass and Jamming Transitions in Biological Tissues

NASA Astrophysics Data System (ADS)

Bi, Dapeng; Yang, Xingbo; Marchetti, M. Cristina; Manning, M. Lisa

2016-04-01

Cell motion inside dense tissues governs many biological processes, including embryonic development and cancer metastasis, and recent experiments suggest that these tissues exhibit collective glassy behavior. To make quantitative predictions about glass transitions in tissues, we study a self-propelled Voronoi model that simultaneously captures polarized cell motility and multibody cell-cell interactions in a confluent tissue, where there are no gaps between cells. We demonstrate that the model exhibits a jamming transition from a solidlike state to a fluidlike state that is controlled by three parameters: the single-cell motile speed, the persistence time of single-cell tracks, and a target shape index that characterizes the competition between cell-cell adhesion and cortical tension. In contrast to traditional particulate glasses, we are able to identify an experimentally accessible structural order parameter that specifies the entire jamming surface as a function of model parameters. We demonstrate that a continuum soft glassy rheology model precisely captures this transition in the limit of small persistence times and explain how it fails in the limit of large persistence times. These results provide a framework for understanding the collective solid-to-liquid transitions that have been observed in embryonic development and cancer progression, which may be associated with epithelial-to-mesenchymal transition in these tissues.

[Development of Markov models for economics evaluation of strategies on hepatitis B vaccination and population-based antiviral treatment in China].

PubMed

Yang, P C; Zhang, S X; Sun, P P; Cai, Y L; Lin, Y; Zou, Y H

2017-07-10

Objective: To construct the Markov models to reflect the reality of prevention and treatment interventions against hepatitis B virus (HBV) infection, simulate the natural history of HBV infection in different age groups and provide evidence for the economics evaluations of hepatitis B vaccination and population-based antiviral treatment in China. Methods: According to the theory and techniques of Markov chain, the Markov models of Chinese HBV epidemic were developed based on the national data and related literature both at home and abroad, including the settings of Markov model states, allowable transitions and initial and transition probabilities. The model construction, operation and verification were conducted by using software TreeAge Pro 2015. Results: Several types of Markov models were constructed to describe the disease progression of HBV infection in neonatal period, perinatal period or adulthood, the progression of chronic hepatitis B after antiviral therapy, hepatitis B prevention and control in adults, chronic hepatitis B antiviral treatment and the natural progression of chronic hepatitis B in general population. The model for the newborn was fundamental which included ten states, i.e . susceptiblity to HBV, HBsAg clearance, immune tolerance, immune clearance, low replication, HBeAg negative CHB, compensated cirrhosis, decompensated cirrhosis, hepatocellular carcinoma (HCC) and death. The susceptible state to HBV was excluded in the perinatal period model, and the immune tolerance state was excluded in the adulthood model. The model for general population only included two states, survive and death. Among the 5 types of models, there were 9 initial states assigned with initial probabilities, and 27 states for transition probabilities. The results of model verifications showed that the probability curves were basically consistent with the situation of HBV epidemic in China. Conclusion: The Markov models developed can be used in economics evaluation of hepatitis B vaccination and treatment for the elimination of HBV infection in China though the structures and parameters in the model have uncertainty with dynamic natures.

Hierarchical Freezing in a Lattice Model

NASA Astrophysics Data System (ADS)

Byington, Travis W.; Socolar, Joshua E. S.

2012-01-01

A certain two-dimensional lattice model with nearest and next-nearest neighbor interactions is known to have a limit-periodic ground state. We show that during a slow quench from the high temperature, disordered phase, the ground state emerges through an infinite sequence of phase transitions. We define appropriate order parameters and show that the transitions are related by renormalizations of the temperature scale. As the temperature is decreased, sublattices with increasingly large lattice constants become ordered. A rapid quench results in a glasslike state due to kinetic barriers created by simultaneous freezing on sublattices with different lattice constants.

Tendency to occupy a statistically dominant spatial state of the flow as a driving force for turbulent transition.

PubMed

Chekmarev, Sergei F

2013-03-01

The transition from laminar to turbulent fluid motion occurring at large Reynolds numbers is generally associated with the instability of the laminar flow. On the other hand, since the turbulent flow characteristically appears in the form of spatially localized structures (e.g., eddies) filling the flow field, a tendency to occupy such a structured state of the flow cannot be ruled out as a driving force for turbulent transition. To examine this possibility, we propose a simple analytical model that treats the flow as a collection of localized spatial structures, each of which consists of elementary cells in which the behavior of the particles (atoms or molecules) is uncorrelated. This allows us to introduce the Reynolds number, associating it with the ratio between the total phase volume for the system and that for the elementary cell. Using the principle of maximum entropy to calculate the most probable size distribution of the localized structures, we show that as the Reynolds number increases, the elementary cells group into the localized structures, which successfully explains turbulent transition and some other general properties of turbulent flows. An important feature of the present model is that a bridge between the spatial-statistical description of the flow and hydrodynamic equations is established. We show that the basic assumptions underlying the model, i.e., that the particles are indistinguishable and elementary volumes of phase space exist in which the state of the particles is uncertain, are involved in the derivation of the Navier-Stokes equation. Taking into account that the model captures essential features of turbulent flows, this suggests that the driving force for the turbulent transition is basically the same as in the present model, i.e., the tendency of the system to occupy a statistically dominant state plays a key role. The instability of the flow at high Reynolds numbers can then be a mechanism to initiate structural rearrangement of the flow to find this state.

Thickness-dependent phase transition in graphite under high magnetic field

NASA Astrophysics Data System (ADS)

Taen, Toshihiro; Uchida, Kazuhito; Osada, Toshihito

2018-03-01

Various electronic phases emerge when applying high magnetic fields in graphite. However, the origin of a semimetal-insulator transition at B ≃30 T is still not clear, while an exotic density-wave state is theoretically proposed. In order to identify the electronic state of the insulator phase, we investigate the phase transition in thin-film graphite samples that were fabricated on silicon substrate by a mechanical exfoliation method. The critical magnetic fields of the semimetal-insulator transition in thin-film graphite shift to higher magnetic fields, accompanied by a reduction in temperature dependence. These results can be qualitatively reproduced by a density-wave model by introducing a quantum size effect. Our findings establish the electronic state of the insulator phase as a density-wave state standing along the out-of-plane direction, and help determine the electronic states in other high-magnetic-field phases.

Bosonic Confinement and Coherence in Disordered Nanodiamond Arrays.

PubMed

Zhang, Gufei; Samuely, Tomas; Du, Hongchu; Xu, Zheng; Liu, Liwang; Onufriienko, Oleksandr; May, Paul W; Vanacken, Johan; Szabó, Pavol; Kačmarčík, Jozef; Yuan, Haifeng; Samuely, Peter; Dunin-Borkowski, Rafal E; Hofkens, Johan; Moshchalkov, Victor V

2017-11-28

In the presence of disorder, superconductivity exhibits short-range characteristics linked to localized Cooper pairs which are responsible for anomalous phase transitions and the emergence of quantum states such as the bosonic insulating state. Complementary to well-studied homogeneously disordered superconductors, superconductor-normal hybrid arrays provide tunable realizations of the degree of granular disorder for studying anomalous quantum phase transitions. Here, we investigate the superconductor-bosonic dirty metal transition in disordered nanodiamond arrays as a function of the dispersion of intergrain spacing, which ranges from angstroms to micrometers. By monitoring the evolved superconducting gaps and diminished coherence peaks in the single-quasiparticle density of states, we link the destruction of the superconducting state and the emergence of bosonic dirty metallic state to breaking of the global phase coherence and persistence of the localized Cooper pairs. The observed resistive bosonic phase transitions are well modeled using a series-parallel circuit in the framework of bosonic confinement and coherence.

Phase transition in a spatial Lotka-Volterra model

NASA Astrophysics Data System (ADS)

Szabó, György; Czárán, Tamás

2001-06-01

Spatial evolution is investigated in a simulated system of nine competing and mutating bacterium strains, which mimics the biochemical war among bacteria capable of producing two different bacteriocins (toxins) at most. Random sequential dynamics on a square lattice is governed by very symmetrical transition rules for neighborhood invasions of sensitive strains by killers, killers by resistants, and resistants by sensitives. The community of the nine possible toxicity/resistance types undergoes a critical phase transition as the uniform transmutation rates between the types decreases below a critical value Pc above that all the nine types of strains coexist with equal frequencies. Passing the critical mutation rate from above, the system collapses into one of three topologically identical (degenerated) states, each consisting of three strain types. Of the three possible final states each accrues with equal probability and all three maintain themselves in a self-organizing polydomain structure via cyclic invasions. Our Monte Carlo simulations support that this symmetry-breaking transition belongs to the universality class of the three-state Potts model.

Status in calculating electronic excited states in transition metal oxides from first principles.

PubMed

Bendavid, Leah Isseroff; Carter, Emily Ann

2014-01-01

Characterization of excitations in transition metal oxides is a crucial step in the development of these materials for photonic and optoelectronic applications. However, many transition metal oxides are considered to be strongly correlated materials, and their complex electronic structure is challenging to model with many established quantum mechanical techniques. We review state-of-the-art first-principles methods to calculate charged and neutral excited states in extended materials, and discuss their application to transition metal oxides. We briefly discuss developments in density functional theory (DFT) to calculate fundamental band gaps, and introduce time-dependent DFT, which can model neutral excitations. Charged excitations can be described within the framework of many-body perturbation theory based on Green's functions techniques, which predominantly employs the GW approximation to the self-energy to facilitate a feasible solution to the quasiparticle equations. We review the various implementations of the GW approximation and evaluate each approach in its calculation of fundamental band gaps of many transition metal oxides. We also briefly review the related Bethe-Salpeter equation (BSE), which introduces an electron-hole interaction between GW-derived quasiparticles to describe accurately neutral excitations. Embedded correlated wavefunction theory is another framework used to model localized neutral or charged excitations in extended materials. Here, the electronic structure of a small cluster is modeled within correlated wavefunction theory, while its coupling to its environment is represented by an embedding potential. We review a number of techniques to represent this background potential, including electrostatic representations and electron density-based methods, and evaluate their application to transition metal oxides.

Modeling the impact of roadway emissions in light wind, stable and transition conditions

EPA Science Inventory

This paper examines the processes that govern air pollution dispersion under light wind, stable and transition conditions by using a state-of-the-art dispersion model to interpret measurements from a tracer experiment conducted next to US highway 99 in Sacramento in 1981–1982 dur...

Phase transition in conservative diffusive contact processes

NASA Astrophysics Data System (ADS)

Fiore, Carlos E.; de Oliveira, Mário J.

2004-10-01

We determine the phase diagrams of conservative diffusive contact processes by means of numerical simulations. These models are versions of the ordinary diffusive single-creation, pair-creation, and triplet-creation contact processes in which the particle number is conserved. The transition between the frozen and active states was determined by studying the system in the subcritical regime, and the nature of the transition, whether continuous or first order, was determined by looking at the fractal dimension of the critical cluster. For the single-creation model the transition remains continuous for any diffusion rate. For pair- and triplet-creation models, however, the transition becomes first order for high enough diffusion rate. Our results indicate that in the limit of infinite diffusion rate the jump in density equals 2/3 for the pair-creation model and 5/6 for the triplet-creation model.

Magnetic dipole transitions of Bc and Bc* mesons in the relativistic independent quark model

NASA Astrophysics Data System (ADS)

Patnaik, Sonali; Dash, P. C.; Kar, Susmita; Patra, Sweta P.; Barik, N.

2017-12-01

We study M1-transitions involving mesons: Bc(1 s ), Bc*(1 s ), Bc(2 s ), Bc*(2 s ), Bc(3 s ), and Bc*(3 s ) in the relativistic independent quark (RIQ) model based on a flavor independent average potential in the scalar-vector harmonic form. The transition form factor for Bc*→Bcγ is found to have analytical continuation from spacelike to physical timelike region. Our predicted coupling constant gBc*Bc=0.34 GeV-1 and decay width Γ (Bc*→Bcγ )=23 eV agree with other model predictions. In view of possible observation of Bc and Bc* s-wave states at LHC and Z-factory and potential use of theoretical estimate on M1-transitions, we investigate the allowed as well as hindered transitions of orbitally excited Bc-meson states and predict their decay widths in overall agreement with other model predictions. We consider the typical case of Bc*(1 s )→Bc(1 s )γ , where our predicted decay width which is found quite sensitive to the mass difference between Bc* and Bc mesons may help in determining the mass of Bc* experimentally.

Activity of a social dynamics model

NASA Astrophysics Data System (ADS)

Reia, Sandro M.; Neves, Ubiraci P. C.

2015-10-01

Axelrod's model was proposed to study interactions between agents and the formation of cultural domains. It presents a transition from a monocultural to a multicultural steady state which has been studied in the literature by evaluation of the relative size of the largest cluster. In this article, we propose new measurements based on the concept of activity per agent to study the Axelrod's model on the square lattice. We show that the variance of system activity can be used to indicate the critical points of the transition. Furthermore the frequency distribution of the system activity is able to show a coexistence of phases typical of a first order phase transition. Finally, we verify a power law dependence between cluster activity and cluster size for multicultural steady state configurations at the critical point.

Modeling of turbulence and transition

NASA Technical Reports Server (NTRS)

Shih, Tsan-Hsing

1992-01-01

The first objective is to evaluate current two-equation and second order closure turbulence models using available direct numerical simulations and experiments, and to identify the models which represent the state of the art in turbulence modeling. The second objective is to study the near-wall behavior of turbulence, and to develop reliable models for an engineering calculation of turbulence and transition. The third objective is to develop a two-scale model for compressible turbulence.

Ancestral state reconstructions require biological evidence to test evolutionary hypotheses: A case study examining the evolution of reproductive mode in squamate reptiles.

PubMed

Griffith, Oliver W; Blackburn, Daniel G; Brandley, Matthew C; Van Dyke, James U; Whittington, Camilla M; Thompson, Michael B

2015-09-01

To understand evolutionary transformations it is necessary to identify the character states of extinct ancestors. Ancestral character state reconstruction is inherently difficult because it requires an accurate phylogeny, character state data, and a statistical model of transition rates and is fundamentally constrained by missing data such as extinct taxa. We argue that model based ancestral character state reconstruction should be used to generate hypotheses but should not be considered an analytical endpoint. Using the evolution of viviparity and reversals to oviparity in squamates as a case study, we show how anatomical, physiological, and ecological data can be used to evaluate hypotheses about evolutionary transitions. The evolution of squamate viviparity requires changes to the timing of reproductive events and the successive loss of features responsible for building an eggshell. A reversal to oviparity requires that those lost traits re-evolve. We argue that the re-evolution of oviparity is inherently more difficult than the reverse. We outline how the inviability of intermediate phenotypes might present physiological barriers to reversals from viviparity to oviparity. Finally, we show that ecological data supports an oviparous ancestral state for squamates and multiple transitions to viviparity. In summary, we conclude that the first squamates were oviparous, that frequent transitions to viviparity have occurred, and that reversals to oviparity in viviparous lineages either have not occurred or are exceedingly rare. As this evidence supports conclusions that differ from previous ancestral state reconstructions, our paper highlights the importance of incorporating biological evidence to evaluate model-generated hypotheses. © 2015 Wiley Periodicals, Inc.

Phase Transitions in a Model for Social Learning via the Internet

NASA Astrophysics Data System (ADS)

Bordogna, Clelia M.; Albano, Ezequiel V.

Based on the concepts of educational psychology, sociology and statistical physics, a mathematical model for a new type of social learning process that takes place when individuals interact via the Internet is proposed and studied. The noise of the interaction (misunderstandings, lack of well organized participative activities, etc.) dramatically restricts the number of individuals that can be efficiently in mutual contact and drives phase transitions between ``ordered states'' such as the achievements of the individuals are satisfactory and ``disordered states'' with negligible achievements.

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.

Prediction of hemoglobin in blood donors using a latent class mixed-effects transition model.

PubMed

Nasserinejad, Kazem; van Rosmalen, Joost; de Kort, Wim; Rizopoulos, Dimitris; Lesaffre, Emmanuel

2016-02-20

Blood donors experience a temporary reduction in their hemoglobin (Hb) value after donation. At each visit, the Hb value is measured, and a too low Hb value leads to a deferral for donation. Because of the recovery process after each donation as well as state dependence and unobserved heterogeneity, longitudinal data of Hb values of blood donors provide unique statistical challenges. To estimate the shape and duration of the recovery process and to predict future Hb values, we employed three models for the Hb value: (i) a mixed-effects models; (ii) a latent-class mixed-effects model; and (iii) a latent-class mixed-effects transition model. In each model, a flexible function was used to model the recovery process after donation. The latent classes identify groups of donors with fast or slow recovery times and donors whose recovery time increases with the number of donations. The transition effect accounts for possible state dependence in the observed data. All models were estimated in a Bayesian way, using data of new entrant donors from the Donor InSight study. Informative priors were used for parameters of the recovery process that were not identified using the observed data, based on results from the clinical literature. The results show that the latent-class mixed-effects transition model fits the data best, which illustrates the importance of modeling state dependence, unobserved heterogeneity, and the recovery process after donation. The estimated recovery time is much longer than the current minimum interval between donations, suggesting that an increase of this interval may be warranted. Copyright © 2015 John Wiley & Sons, Ltd.

Free energy and phase transition of the matrix model on a plane wave

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

Hadizadeh, Shirin; Ramadanovic, Bojan; Semenoff, Gordon W.

2005-03-15

It has recently been observed that the weakly coupled plane-wave matrix model has a density of states which grows exponentially at high energy. This implies that the model has a phase transition. The transition appears to be of first order. However, its exact nature is sensitive to interactions. In this paper, we analyze the effect of interactions by computing the relevant parts of the effective potential for the Polyakov loop operator in the finite temperature plane-wave matrix model to three-loop order. We show that the phase transition is indeed of first order. We also compute the correction to the Hagedornmore » temperature to order two loops.« less

Thermal-history dependent magnetoelastic transition in (Mn,Fe){sub 2}(P,Si)

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

Miao, X. F., E-mail: x.f.miao@tudelft.nl; Dijk, N. H. van; Brück, E.

The thermal-history dependence of the magnetoelastic transition in (Mn,Fe){sub 2}(P,Si) compounds has been investigated using high-resolution neutron diffraction. As-prepared samples display a large difference in paramagnetic-ferromagnetic (PM-FM) transition temperature compared to cycled samples. The initial metastable state transforms into a lower-energy stable state when the as-prepared sample crosses the PM-FM transition for the first time. This additional transformation is irreversible around the transition temperature and increases the energy barrier which needs to be overcome through the PM-FM transition. Consequently, the transition temperature on first cooling is found to be lower than on subsequent cycles characterizing the so-called “virgin effect.” High-temperaturemore » annealing can restore the cycled sample to the high-temperature metastable state, which leads to the recovery of the virgin effect. A model is proposed to interpret the formation and recovery of the virgin effect.« less

State-Chart Autocoder

NASA Technical Reports Server (NTRS)

Clark, Kenneth; Watney, Garth; Murray, Alexander; Benowitz, Edward

2007-01-01

A computer program translates Unified Modeling Language (UML) representations of state charts into source code in the C, C++, and Python computing languages. ( State charts signifies graphical descriptions of states and state transitions of a spacecraft or other complex system.) The UML representations constituting the input to this program are generated by using a UML-compliant graphical design program to draw the state charts. The generated source code is consistent with the "quantum programming" approach, which is so named because it involves discrete states and state transitions that have features in common with states and state transitions in quantum mechanics. Quantum programming enables efficient implementation of state charts, suitable for real-time embedded flight software. In addition to source code, the autocoder program generates a graphical-user-interface (GUI) program that, in turn, generates a display of state transitions in response to events triggered by the user. The GUI program is wrapped around, and can be used to exercise the state-chart behavior of, the generated source code. Once the expected state-chart behavior is confirmed, the generated source code can be augmented with a software interface to the rest of the software with which the source code is required to interact.

Transition sum rules in the shell model

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

Lu, Yi; Johnson, Calvin W.

An important characterization of electromagnetic and weak transitions in atomic nuclei are sum rules. We focus on the non-energy-weighted sum rule (NEWSR), or total strength, and the energy- weighted sum rule (EWSR); the ratio of the EWSR to the NEWSR is the centroid or average energy of transition strengths from an nuclear initial state to all allowed final states. These sum rules can be expressed as expectation values of operators, in the case of the EWSR a double commutator. While most prior applications of the double-commutator have been to special cases, we derive general formulas for matrix elements of bothmore » operators in a shell model framework (occupation space), given the input matrix elements for the nuclear Hamiltonian and for the transition operator. With these new formulas, we easily evaluate centroids of transition strength functions, with no need to calculate daughter states. We then apply this simple tool to a number of nuclides, and demonstrate the sum rules follow smooth secular behavior as a function of initial energy, as well as compare the electric dipole (E1) sum rule against the famous Thomas-Reiche-Kuhn version. We also find surprising systematic behaviors for ground state electric quadrupole (E2) centroids in the $sd$-shell.« less

Transition sum rules in the shell model

DOE PAGES

Lu, Yi; Johnson, Calvin W.

2018-03-29

An important characterization of electromagnetic and weak transitions in atomic nuclei are sum rules. We focus on the non-energy-weighted sum rule (NEWSR), or total strength, and the energy- weighted sum rule (EWSR); the ratio of the EWSR to the NEWSR is the centroid or average energy of transition strengths from an nuclear initial state to all allowed final states. These sum rules can be expressed as expectation values of operators, in the case of the EWSR a double commutator. While most prior applications of the double-commutator have been to special cases, we derive general formulas for matrix elements of bothmore » operators in a shell model framework (occupation space), given the input matrix elements for the nuclear Hamiltonian and for the transition operator. With these new formulas, we easily evaluate centroids of transition strength functions, with no need to calculate daughter states. We then apply this simple tool to a number of nuclides, and demonstrate the sum rules follow smooth secular behavior as a function of initial energy, as well as compare the electric dipole (E1) sum rule against the famous Thomas-Reiche-Kuhn version. We also find surprising systematic behaviors for ground state electric quadrupole (E2) centroids in the $sd$-shell.« less

The paradox of Foxd3: how does it function in pluripotency and differentiation of embryonic stem cells?

PubMed Central

Plank-Bazinet, Jennifer L.

2016-01-01

Uncommitted cells of the early mammalian embryo transition through distinct stages of pluripotency, including establishment of ground state “naïve” pluripotency in the early epiblast, transition to a post-implantation “primed” state, and subsequent lineage commitment of the gastrulating epiblast. Previous transcriptional profiling of in vitro models to recapitulate early to late epiblast transition and differentiation suggest that distinct gene regulatory networks are likely to function in each of these states. While the mechanisms underlying transition between pluripotent states are poorly understood, the forkhead family transcription factor Foxd3 has emerged as a key regulatory factor. Foxd3 is required to maintain pluripotent cells of the murine epiblast and for survival, self-renewal and pluripotency of embryonic stem cells (ESCs). Two recent, simultaneous studies have shed light on how Foxd3 regulates gene expression in early cell fate transitions of progenitor cells. While the two publications shared some common findings, they also presented some conflicting results and suggest different models for the mechanisms underlying Foxd3 function. Here, we discuss the key similarities and differences between the publications, highlight data from the literature relevant to their findings, and hypothesize a potential mechanism of Foxd3 action. PMID:27868055

Rupture and Adaptation: British Technical Expertise to the Singapore Polytechnic and the Transition to a Nation-State

ERIC Educational Resources Information Center

Seng, Loh Kah

2015-01-01

The Singapore Polytechnic underwent a period of both rupture and adaptation as British advisers worked with the post-colonial government to facilitate technical education reform and Singapore's transition to a nation-state. Established in 1958 and based on the metropolitan model, the Singapore Polytechnic constituted an imperial project for…

Modeling Temporal Behavior in Large Networks: A Dynamic Mixed-Membership Model

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

Rossi, R; Gallagher, B; Neville, J

Given a large time-evolving network, how can we model and characterize the temporal behaviors of individual nodes (and network states)? How can we model the behavioral transition patterns of nodes? We propose a temporal behavior model that captures the 'roles' of nodes in the graph and how they evolve over time. The proposed dynamic behavioral mixed-membership model (DBMM) is scalable, fully automatic (no user-defined parameters), non-parametric/data-driven (no specific functional form or parameterization), interpretable (identifies explainable patterns), and flexible (applicable to dynamic and streaming networks). Moreover, the interpretable behavioral roles are generalizable, computationally efficient, and natively supports attributes. We applied ourmore » model for (a) identifying patterns and trends of nodes and network states based on the temporal behavior, (b) predicting future structural changes, and (c) detecting unusual temporal behavior transitions. We use eight large real-world datasets from different time-evolving settings (dynamic and streaming). In particular, we model the evolving mixed-memberships and the corresponding behavioral transitions of Twitter, Facebook, IP-Traces, Email (University), Internet AS, Enron, Reality, and IMDB. The experiments demonstrate the scalability, flexibility, and effectiveness of our model for identifying interesting patterns, detecting unusual structural transitions, and predicting the future structural changes of the network and individual nodes.« less

Absorbing phase transitions in deterministic fixed-energy sandpile models

NASA Astrophysics Data System (ADS)

Park, Su-Chan

2018-03-01

We investigate the origin of the difference, which was noticed by Fey et al. [Phys. Rev. Lett. 104, 145703 (2010), 10.1103/PhysRevLett.104.145703], between the steady state density of an Abelian sandpile model (ASM) and the transition point of its corresponding deterministic fixed-energy sandpile model (DFES). Being deterministic, the configuration space of a DFES can be divided into two disjoint classes such that every configuration in one class should evolve into one of absorbing states, whereas no configurations in the other class can reach an absorbing state. Since the two classes are separated in terms of toppling dynamics, the system can be made to exhibit an absorbing phase transition (APT) at various points that depend on the initial probability distribution of the configurations. Furthermore, we show that in general the transition point also depends on whether an infinite-size limit is taken before or after the infinite-time limit. To demonstrate, we numerically study the two-dimensional DFES with Bak-Tang-Wiesenfeld toppling rule (BTW-FES). We confirm that there are indeed many thresholds. Nonetheless, the critical phenomena at various transition points are found to be universal. We furthermore discuss a microscopic absorbing phase transition, or a so-called spreading dynamics, of the BTW-FES, to find that the phase transition in this setting is related to the dynamical isotropic percolation process rather than self-organized criticality. In particular, we argue that choosing recurrent configurations of the corresponding ASM as an initial configuration does not allow for a nontrivial APT in the DFES.

Absorbing phase transitions in deterministic fixed-energy sandpile models.

PubMed

Park, Su-Chan

2018-03-01

We investigate the origin of the difference, which was noticed by Fey et al. [Phys. Rev. Lett. 104, 145703 (2010)PRLTAO0031-900710.1103/PhysRevLett.104.145703], between the steady state density of an Abelian sandpile model (ASM) and the transition point of its corresponding deterministic fixed-energy sandpile model (DFES). Being deterministic, the configuration space of a DFES can be divided into two disjoint classes such that every configuration in one class should evolve into one of absorbing states, whereas no configurations in the other class can reach an absorbing state. Since the two classes are separated in terms of toppling dynamics, the system can be made to exhibit an absorbing phase transition (APT) at various points that depend on the initial probability distribution of the configurations. Furthermore, we show that in general the transition point also depends on whether an infinite-size limit is taken before or after the infinite-time limit. To demonstrate, we numerically study the two-dimensional DFES with Bak-Tang-Wiesenfeld toppling rule (BTW-FES). We confirm that there are indeed many thresholds. Nonetheless, the critical phenomena at various transition points are found to be universal. We furthermore discuss a microscopic absorbing phase transition, or a so-called spreading dynamics, of the BTW-FES, to find that the phase transition in this setting is related to the dynamical isotropic percolation process rather than self-organized criticality. In particular, we argue that choosing recurrent configurations of the corresponding ASM as an initial configuration does not allow for a nontrivial APT in the DFES.

Safety performance of traffic phases and phase transitions in three phase traffic theory.

PubMed

Xu, Chengcheng; Liu, Pan; Wang, Wei; Li, Zhibin

2015-12-01

Crash risk prediction models were developed to link safety to various phases and phase transitions defined by the three phase traffic theory. Results of the Bayesian conditional logit analysis showed that different traffic states differed distinctly with respect to safety performance. The random-parameter logit approach was utilized to account for the heterogeneity caused by unobserved factors. The Bayesian inference approach based on the Markov Chain Monte Carlo (MCMC) method was used for the estimation of the random-parameter logit model. The proposed approach increased the prediction performance of the crash risk models as compared with the conventional logit model. The three phase traffic theory can help us better understand the mechanism of crash occurrences in various traffic states. The contributing factors to crash likelihood can be well explained by the mechanism of phase transitions. We further discovered that the free flow state can be divided into two sub-phases on the basis of safety performance, including a true free flow state in which the interactions between vehicles are minor, and a platooned traffic state in which bunched vehicles travel in successions. The results of this study suggest that a safety perspective can be added to the three phase traffic theory. The results also suggest that the heterogeneity between different traffic states should be considered when estimating the risks of crash occurrences on freeways. Copyright © 2015 Elsevier Ltd. All rights reserved.

Reconfiguration of a smart surface using heteroclinic connections

PubMed Central

McInnes, Colin R.; Xu, Ming

2017-01-01

A reconfigurable smart surface with multiple equilibria is presented, modelled using discrete point masses and linear springs with geometric nonlinearity. An energy-efficient reconfiguration scheme is then investigated to connect equal-energy unstable (but actively controlled) equilibria. In principle, zero net energy input is required to transition the surface between these unstable states, compared to transitions between stable equilibria across a potential barrier. These transitions between equal-energy unstable states, therefore, form heteroclinic connections in the phase space of the problem. Moreover, the smart surface model developed can be considered as a unit module for a range of applications, including modules which can aggregate together to form larger distributed smart surface systems. PMID:28265191

Magnetic states, correlation effects and metal-insulator transition in FCC lattice

NASA Astrophysics Data System (ADS)

Timirgazin, M. A.; Igoshev, P. A.; Arzhnikov, A. K.; Irkhin, V. Yu

2016-12-01

The ground-state magnetic phase diagram (including collinear and spiral states) of the single-band Hubbard model for the face-centered cubic lattice and related metal-insulator transition (MIT) are investigated within the slave-boson approach by Kotliar and Ruckenstein. The correlation-induced electron spectrum narrowing and a comparison with a generalized Hartree-Fock approximation allow one to estimate the strength of correlation effects. This, as well as the MIT scenario, depends dramatically on the ratio of the next-nearest and nearest electron hopping integrals {{t}\\prime}/t . In contrast with metallic state, possessing substantial band narrowing, insulator one is only weakly correlated. The magnetic (Slater) scenario of MIT is found to be superior over the Mott one. Unlike simple and body-centered cubic lattices, MIT is the first order transition (discontinuous) for most {{t}\\prime}/t . The insulator state is type-II or type-III antiferromagnet, and the metallic state is spin-spiral, collinear antiferromagnet or paramagnet depending on {{t}\\prime}/t . The picture of magnetic ordering is compared with that in the standard localized-electron (Heisenberg) model.

An Epidemiological Model of Transition and Postschool Outcomes

ERIC Educational Resources Information Center

Flexer, Robert W.; Daviso, Alfred W., III; Baer, Robert M.; Queen, Rachel McMahan; Meindl, Richard S.

2011-01-01

This longitudinal transition study was conducted in collaboration with teachers who interviewed students who graduated from 177 school districts in a Great Lakes state. Special education students were interviewed at exit and 1 year following graduation using a survey based on the National Longitudinal Transition Study. The data were analyzed using…

Electric Quadrupole E2- Transitions of 170-174 Yb Isotopes

NASA Astrophysics Data System (ADS)

Abu El Sheikh, Mohd Kh. M.; Okhunov, Abdurahim A.; Usmanov, Ph. N.; Hassan, Torla HJ

2017-12-01

The non-adiabatic effects which is manifested in the electric properties of low-lying states of even-even deformed nuclei are studied. A simple phenomenological model which takes into account the Coriolis mixing of {K}π ={0}n+,{2}n+ and {K}π ={1}ν + state bands. The Calculations for isotopes 170-174 Yb, are carried out. The reduced probability of electric quadrupole transitions from the states {0}ν + and {2}ν + - bands to the ground (gr) state band is calculated and non adiabatic effect is discussed. The ratio of E2- transitions RIK from {0}2+, {0}3+, {2}1+, and {2}2+ bands are calculated and compared with the experimental data.

Discontinuous non-equilibrium phase transition in a threshold Schloegl model for autocatalysis: Generic two-phase coexistence and metastability

DOE PAGES

Wang, Chi -Jen; Liu, Da -Jiang; Evans, James W.

2015-04-28

Threshold versions of Schloegl’s model on a lattice, which involve autocatalytic creation and spontaneous annihilation of particles, can provide a simple prototype for discontinuous non-equilibrium phase transitions. These models are equivalent to so-called threshold contact processes. A discontinuous transition between populated and vacuum states can occur selecting a threshold of N ≥ 2 for the minimum number, N, of neighboring particles enabling autocatalytic creation at an empty site. Fundamental open questions remain given the lack of a thermodynamic framework for analysis. For a square lattice with N = 2, we show that phase coexistence occurs not at a unique valuemore » but for a finite range of particle annihilation rate (the natural control parameter). This generic two-phase coexistence also persists when perturbing the model to allow spontaneous particle creation. Such behavior contrasts both the Gibbs phase rule for thermodynamic systems and also previous analysis for this model. We find metastability near the transition corresponding to a non-zero effective line tension, also contrasting previously suggested critical behavior. As a result, mean-field type analysis, extended to treat spatially heterogeneous states, further elucidates model behavior.« less

Discontinuous non-equilibrium phase transition in a threshold Schloegl model for autocatalysis: Generic two-phase coexistence and metastability

NASA Astrophysics Data System (ADS)

Wang, Chi-Jen; Liu, Da-Jiang; Evans, James W.

2015-04-01

Threshold versions of Schloegl's model on a lattice, which involve autocatalytic creation and spontaneous annihilation of particles, can provide a simple prototype for discontinuous non-equilibrium phase transitions. These models are equivalent to so-called threshold contact processes. A discontinuous transition between populated and vacuum states can occur selecting a threshold of N ≥ 2 for the minimum number, N, of neighboring particles enabling autocatalytic creation at an empty site. Fundamental open questions remain given the lack of a thermodynamic framework for analysis. For a square lattice with N = 2, we show that phase coexistence occurs not at a unique value but for a finite range of particle annihilation rate (the natural control parameter). This generic two-phase coexistence also persists when perturbing the model to allow spontaneous particle creation. Such behavior contrasts both the Gibbs phase rule for thermodynamic systems and also previous analysis for this model. We find metastability near the transition corresponding to a non-zero effective line tension, also contrasting previously suggested critical behavior. Mean-field type analysis, extended to treat spatially heterogeneous states, further elucidates model behavior.

Phased models for evaluating the performability of computing systems

NASA Technical Reports Server (NTRS)

Wu, L. T.; Meyer, J. F.

1979-01-01

A phase-by-phase modelling technique is introduced to evaluate a fault tolerant system's ability to execute different sets of computational tasks during different phases of the control process. Intraphase processes are allowed to differ from phase to phase. The probabilities of interphase state transitions are specified by interphase transition matrices. Based on constraints imposed on the intraphase and interphase transition probabilities, various iterative solution methods are developed for calculating system performability.

Simple Deterministically Constructed Recurrent Neural Networks

NASA Astrophysics Data System (ADS)

Rodan, Ali; Tiňo, Peter

A large number of models for time series processing, forecasting or modeling follows a state-space formulation. Models in the specific class of state-space approaches, referred to as Reservoir Computing, fix their state-transition function. The state space with the associated state transition structure forms a reservoir, which is supposed to be sufficiently complex so as to capture a large number of features of the input stream that can be potentially exploited by the reservoir-to-output readout mapping. The largely "black box" character of reservoirs prevents us from performing a deeper theoretical investigation of the dynamical properties of successful reservoirs. Reservoir construction is largely driven by a series of (more-or-less) ad-hoc randomized model building stages, with both the researchers and practitioners having to rely on a series of trials and errors. We show that a very simple deterministically constructed reservoir with simple cycle topology gives performances comparable to those of the Echo State Network (ESN) on a number of time series benchmarks. Moreover, we argue that the memory capacity of such a model can be made arbitrarily close to the proved theoretical limit.

Reveal, A General Reverse Engineering Algorithm for Inference of Genetic Network Architectures

NASA Technical Reports Server (NTRS)

Liang, Shoudan; Fuhrman, Stefanie; Somogyi, Roland

1998-01-01

Given the immanent gene expression mapping covering whole genomes during development, health and disease, we seek computational methods to maximize functional inference from such large data sets. Is it possible, in principle, to completely infer a complex regulatory network architecture from input/output patterns of its variables? We investigated this possibility using binary models of genetic networks. Trajectories, or state transition tables of Boolean nets, resemble time series of gene expression. By systematically analyzing the mutual information between input states and output states, one is able to infer the sets of input elements controlling each element or gene in the network. This process is unequivocal and exact for complete state transition tables. We implemented this REVerse Engineering ALgorithm (REVEAL) in a C program, and found the problem to be tractable within the conditions tested so far. For n = 50 (elements) and k = 3 (inputs per element), the analysis of incomplete state transition tables (100 state transition pairs out of a possible 10(exp 15)) reliably produced the original rule and wiring sets. While this study is limited to synchronous Boolean networks, the algorithm is generalizable to include multi-state models, essentially allowing direct application to realistic biological data sets. The ability to adequately solve the inverse problem may enable in-depth analysis of complex dynamic systems in biology and other fields.

Unfolding and melting of DNA (RNA) hairpins: the concept of structure-specific 2D dynamic landscapes.

PubMed

Lin, Milo M; Meinhold, Lars; Shorokhov, Dmitry; Zewail, Ahmed H

2008-08-07

A 2D free-energy landscape model is presented to describe the (un)folding transition of DNA/RNA hairpins, together with molecular dynamics simulations and experimental findings. The dependence of the (un)folding transition on the stem sequence and the loop length is shown in the enthalpic and entropic contributions to the free energy. Intermediate structures are well defined by the two coordinates of the landscape during (un)zipping. Both the free-energy landscape model and the extensive molecular dynamics simulations totaling over 10 mus predict the existence of temperature-dependent kinetic intermediate states during hairpin (un)zipping and provide the theoretical description of recent ultrafast temperature-jump studies which indicate that hairpin (un)zipping is, in general, not a two-state process. The model allows for lucid prediction of the collapsed state(s) in simple 2D space and we term it the kinetic intermediate structure (KIS) model.

Slicing AADL Specifications for Model Checking

NASA Technical Reports Server (NTRS)

Odenbrett, Maximilian; Nguyen, Viet Yen; Noll, Thomas

2010-01-01

To combat the state-space explosion problem in model checking larger systems, abstraction techniques can be employed. Here, methods that operate on the system specification before constructing its state space are preferable to those that try to minimize the resulting transition system as they generally reduce peak memory requirements. We sketch a slicing algorithm for system specifications written in (a variant of) the Architecture Analysis and Design Language (AADL). Given a specification and a property to be verified, it automatically removes those parts of the specification that are irrelevant for model checking the property, thus reducing the size of the corresponding transition system. The applicability and effectiveness of our approach is demonstrated by analyzing the state-space reduction for an example, employing a translator from AADL to Promela, the input language of the SPIN model checker.

Systems Biology Approach and Mathematical Modeling for Analyzing Phase-Space Switch During Epithelial-Mesenchymal Transition.

PubMed

Simeoni, Chiara; Dinicola, Simona; Cucina, Alessandra; Mascia, Corrado; Bizzarri, Mariano

2018-01-01

In this report, we aim at presenting a viable strategy for the study of Epithelial-Mesenchymal Transition (EMT) and its opposite Mesenchymal-Epithelial Transition (MET) by means of a Systems Biology approach combined with a suitable Mathematical Modeling analysis. Precisely, it is shown how the presence of a metastable state, that is identified at a mesoscopic level of description, is crucial for making possible the appearance of a phase transition mechanism in the framework of fast-slow dynamics for Ordinary Differential Equations (ODEs).

Microscopic interpretation of inelastic electron scattering from even Ni isotopes

NASA Astrophysics Data System (ADS)

Yokoyama, Atsushi; Ogawa, Kengo

1990-10-01

Transition charge densities of inelastic electron scattering for the excitation of 2+ and 4+ states in even-mass Ni isotopes are investigated in terms of the standard shell model of the (p3/2,p1/2,f5/2)n configurations. Effective transition operators pertinent to the model space are derived by considering particle-hole excitations up to 12ħω for C2 and 14ħω for C4 transitions within the framework of a first-order perturbation theory. It is shown that surface-peaked transition charge densities can be obtained for the first excited 2+ and 4+ states, being in agreement with experiment. Particle-hole excitations up to λħω, e.g., λ=2 for C2 transition, are most responsible for that feature. Higher ħω excitations appear relatively significant in the interior region of the nucleus: They enhance the peak around the surface, improving further agreement with experiment, but for C2 transition they tend to generate another peak inside the nucleus and thus seem to deteriorate agreement with experiment. Transition densities for the 0+g.s.-->2+2,3 and 0+g.s.-->4+2 transitions are also discussed.

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.

Numerical study of Potts models with aperiodic modulations: influence on first-order transitions

NASA Astrophysics Data System (ADS)

Branco, Nilton; Girardi, Daniel

2012-02-01

We perform a numerical study of Potts models on a rectangular lattice with aperiodic interactions along one spatial direction. The number of states q is such that the transition is a first-order one for the uniform model. The Wolff algorithm is employed, for many lattice sizes, allowing for a finite-size scaling analyses to be carried out. Three different self-dual aperiodic sequences are employed, such that the exact critical temperature is known: this leads to precise results for the exponents. We analyze models with q=6 and 15 and show that the Harris-Luck criterion, originally introduced in the study of continuous transitions, is obeyed also for first-order ones. The new universality class that emerges for relevant aperiodic modulations depends on the number of states of the Potts model, as obtained elsewhere for random disorder, and on the aperiodic sequence. We determine the occurrence of log-periodic behavior, as expected for models with aperiodic modulated interactions.

Stochastic Sznajd Model in Open Community

NASA Astrophysics Data System (ADS)

Emmert-Streib, Frank

We extend the Sznajd Model for opinion formation by introducing persuasion probabilities for opinions. Moreover, we couple the system to an environment which mimics the application of the opinion. This results in a feedback, representing single-state opinion transitions in opposite to the two-state opinion transitions for persuading other people. We call this model opinion formation in an open community (OFOC). It can be seen as a stochastic extension of the Sznajd model for an open community, because it allows for a special choice of parameters to recover the original Sznajd model. We demonstrate the effect of feedback in the OFOC model by applying it to a scenario in which, e.g., opinion B is worse then opinion A but easier explained to other people. Casually formulated we analyzed the question, how much better one has to be, in order to persuade other people, provided the opinion is worse. Our results reveal a linear relation between the transition probability for opinion B and the influence of the environment on B.

Memory-efficient RNA energy landscape exploration

PubMed Central

Mann, Martin; Kucharík, Marcel; Flamm, Christoph; Wolfinger, Michael T.

2014-01-01

Motivation: Energy landscapes provide a valuable means for studying the folding dynamics of short RNA molecules in detail by modeling all possible structures and their transitions. Higher abstraction levels based on a macro-state decomposition of the landscape enable the study of larger systems; however, they are still restricted by huge memory requirements of exact approaches. Results: We present a highly parallelizable local enumeration scheme that enables the computation of exact macro-state transition models with highly reduced memory requirements. The approach is evaluated on RNA secondary structure landscapes using a gradient basin definition for macro-states. Furthermore, we demonstrate the need for exact transition models by comparing two barrier-based approaches, and perform a detailed investigation of gradient basins in RNA energy landscapes. Availability and implementation: Source code is part of the C++ Energy Landscape Library available at http://www.bioinf.uni-freiburg.de/Software/. Contact: mmann@informatik.uni-freiburg.de Supplementary information: Supplementary data are available at Bioinformatics online. PMID:24833804

Gain control through divisive inhibition prevents abrupt transition to chaos in a neural mass model

PubMed Central

Papasavvas, Christoforos A.; Wang, Yujiang; Trevelyan, Andrew J.; Kaiser, Marcus

2016-01-01

Experimental results suggest that there are two distinct mechanisms of inhibition in cortical neuronal networks: subtractive and divisive inhibition. They modulate the input-output function of their target neurons either by increasing the input that is needed to reach maximum output or by reducing the gain and the value of maximum output itself, respectively. However, the role of these mechanisms on the dynamics of the network is poorly understood. We introduce a novel population model and numerically investigate the influence of divisive inhibition on network dynamics. Specifically, we focus on the transitions from a state of regular oscillations to a state of chaotic dynamics via period-doubling bifurcations. The model with divisive inhibition exhibits a universal transition rate to chaos (Feigenbaum behavior). In contrast, in an equivalent model without divisive inhibition, transition rates to chaos are not bounded by the universal constant (non-Feigenbaum behavior). This non-Feigenbaum behavior, when only subtractive inhibition is present, is linked to the interaction of bifurcation curves in the parameter space. Indeed, searching the parameter space showed that such interactions are impossible when divisive inhibition is included. Therefore, divisive inhibition prevents non-Feigenbaum behavior and, consequently, any abrupt transition to chaos. The results suggest that the divisive inhibition in neuronal networks could play a crucial role in keeping the states of order and chaos well separated and in preventing the onset of pathological neural dynamics. PMID:26465514

Elastic Model Transitions: a Hybrid Approach Utilizing Quadratic Inequality Constrained Least Squares (LSQI) and Direct Shape Mapping (DSM)

NASA Technical Reports Server (NTRS)

Jurenko, Robert J.; Bush, T. Jason; Ottander, John A.

2014-01-01

A method for transitioning linear time invariant (LTI) models in time varying simulation is proposed that utilizes both quadratically constrained least squares (LSQI) and Direct Shape Mapping (DSM) algorithms to determine physical displacements. This approach is applicable to the simulation of the elastic behavior of launch vehicles and other structures that utilize multiple LTI finite element model (FEM) derived mode sets that are propagated throughout time. The time invariant nature of the elastic data for discrete segments of the launch vehicle trajectory presents a problem of how to properly transition between models while preserving motion across the transition. In addition, energy may vary between flex models when using a truncated mode set. The LSQI-DSM algorithm can accommodate significant changes in energy between FEM models and carries elastic motion across FEM model transitions. Compared with previous approaches, the LSQI-DSM algorithm shows improvements ranging from a significant reduction to a complete removal of transients across FEM model transitions as well as maintaining elastic motion from the prior state.

High-resolution study of Gamow-Teller transitions in the 47Ti(3He,t)47V reaction

NASA Astrophysics Data System (ADS)

Ganioǧlu, E.; Fujita, H.; Fujita, Y.; Adachi, T.; Algora, A.; Csatlós, M.; Deaven, J. M.; Estevez-Aguado, E.; Guess, C. J.; Gulyás, J.; Hatanaka, K.; Hirota, K.; Honma, M.; Ishikawa, D.; Krasznahorkay, A.; Matsubara, H.; Meharchand, R.; Molina, F.; Okamura, H.; Ong, H. J.; Otsuka, T.; Perdikakis, G.; Rubio, B.; Scholl, C.; Shimbara, Y.; Susoy, G.; Suzuki, T.; Tamii, A.; Thies, J. H.; Zegers, R. G. T.; Zenihiro, J.

2013-01-01

Given the importance of Gamow-Teller (GT) transitions in nuclear structure and astrophysical nuclear processes, we have studied Tz=+3/2→+1/2, GT transitions starting from the 47Ti nucleus in the (3He,t) charge-exchange reaction at 0∘ and at an intermediate incident energy of 140 MeV/nucleon. The experiments were carried out at the Research Center for Nuclear Physics (RCNP), Osaka, using the high-resolution facility with a high-dispersion beam line and the Grand-Raiden spectrometer. With an energy resolution of 20 keV, individual GT transitions were observed and GT strength was derived for each state populated up to an excitation energy (Ex) of 12.5 MeV. The GT strength was widely distributed from low excitation energy up to 12.5 MeV, where we had to stop the analysis because of the high level density. The distribution of the GT strengths was compared with the results of shell model calculations using the GXPF1 interaction. The calculations could reproduce the experimental GT distributions well. The GT transitions from the ground state of 47Ti and the M1 transitions from the isobaric analog state in 47V to the same low-lying states in 47V are analogous. It was found that the ratios of GT transition strengths to the ground state, the 0.088-MeV state, and the 0.146-MeV state are similar to the ratios of the strengths of the analogous M1 transitions from the isobaric analog state (IAS) to these states. The measured distribution of the GT strengths was also compared with those starting from the Tz=+3/2 nucleus 41K to the Tz=+1/2 nucleus 41Ca.

State-and-transition models: Conceptual versus simulation perspectives, usefulness and breadth of use, and land management applications

USGS Publications Warehouse

Provencher, Louis; Frid, Leonardo; Czembor, Christina; Morisette, Jeffrey T.

2016-01-01

State-and-Transition Simulation Modeling (STSM) is a quantitative analysis method that can consolidate a wide array of resource management issues under a “what-if” scenario exercise. STSM can be seen as an ensemble of models, such as climate models, ecological models, and economic models that incorporate human dimensions and management options. This chapter presents STSM as a tool to help synthesize information on social–ecological systems and to investigate some of the management issues associated with exotic annual Bromus species, which have been described elsewhere in this book. Definitions, terminology, and perspectives on conceptual and computer-simulated stochastic state-and-transition models are given first, followed by a brief review of past STSM studies relevant to the management of Bromus species. A detailed case study illustrates the usefulness of STSM for land management. As a whole, this chapter is intended to demonstrate how STSM can help both managers and scientists: (a) determine efficient resource allocation for monitoring nonnative grasses; (b) evaluate sources of uncertainty in model simulation results involving expert opinion, and their consequences for management decisions; and (c) provide insight into the consequences of predicted local climate change effects on ecological systems invaded by exotic annual Bromus species.

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

USDA-ARS?s Scientific Manuscript database

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

High-spin level structure and Ground-state phase transition in the odd-mass 103-109Rh isotopes in the framework of exactly solvable sdg interacting boson-fermion model

NASA Astrophysics Data System (ADS)

Ghapanvari, M.; Ghorashi, A. H.; Ranjbar, Z.; Jafarizadeh, M. A.

2018-03-01

In this article, the negative-parity states in the odd-mass 103 - 109Rh isotopes in terms of the sd and sdg interacting-boson fermion models were studied. The transitional interacting boson-fermion model Hamiltonians in sd and sdg-IBFM versions based on affine SU (1 , 1) Lie Algebra were employed to describe the evolution from the spherical to deformed gamma unstable shapes along with the chain of Rh isotopes. In this method, sdg-IBFM Hamiltonian, which is a three level pairing Hamiltonian was determined easily via the exactly solvable method. Some observables of the shape phase transitions such as energy levels, the two neutron separation energies, signature splitting of the γ-vibrational band, the α-decay and double β--decay energies were calculated and examined for these isotopes. The present calculation correctly reproduces the spherical to gamma-soft phase transition in the Rh isotopes. Some comparisons were made with sd-IBFM.

[Altitude-belt zonality of wood vegetation within mountainous regions of the Sayan Mountains: a model of ecological second-order phase transitions ].

PubMed

Sukhovol'skiĭ, V G; Ovchinnikova, T M; Baboĭ, S D

2014-01-01

As a description of altitude-belt zonality of wood vegetation, a model of ecological second-order transitions is proposed. Objects of the study have been chosen to be forest cenoses of the northern slope of Kulumyss Ridge (the Sayan Mauntains), while the results are comprised by the altitude profiles of wood vegetation. An ecological phase transition can be considered as the transition of cenoses at different altitudes from the state of presence of certain tree species within the studied territory to the state of their absence. By analogy with the physical model of second-order, phase transitions the order parameter is introduced (i.e., the area portion occupied by a single tree species at the certain altitude) as well as the control variable (i.e., the altitude of the wood vegetation belt). As the formal relation between them, an analog of the Landau's equation for phase transitions in physical systems is obtained. It is shown that the model is in a good accordance with the empirical data. Thus, the model can be used for estimation of upper and lower boundaries of altitude belts for individual tree species (like birch, aspen, Siberian fir, Siberian pine) as well as the breadth of their ecological niches with regard to altitude. The model includes also the parameters that describe numerically the interactions between different species of wood vegetation. The approach versatility allows to simplify description and modeling of wood vegetation altitude zonality, and enables assessment of vegetation cenoses response to climatic changes.

Resolving the chicken-and-egg problem in VO2: a new paradigm for the Mott transition

NASA Astrophysics Data System (ADS)

Najera, Oscar; Civelli, Marcello; Dobrosavljevi, Vladimir; Rozenberg, Marcelo

We consider a minimal model to investigate the metal-insulator transition in VO2. We adopt a Hubbard model with two orbital per unit cell, which captures the competition between Mott and singlet-dimer localization. We solve the model within Dynamical Mean Field Theory, characterizing in detail the metal-insulator transition and finding new features in the electronic states. We compare our results with available experimental data obtaining good agreement in the relevant model parameter range. Crucially, we can account for puzzling optical conductivity data obtained within the hysteresis region, which we associate to a novel metallic state characterized by a split heavy quasiparticle band. Our results show that the thermal-driven insulator-to-metal transition in VO2 is entirely compatible with a Mott electronic mechanism, solving a long standing ''chicken-and-egg'' debate and calling for further research of ``Mottronics'' applications of this system. This work was partially supported by public Grants from the French National Research Agency (ANR), project LACUNES No ANR-13-BS04-0006-01, the NSF DMR-1005751 and DMR-1410132.

Estimating parameters of hidden Markov models based on marked individuals: use of robust design data

USGS Publications Warehouse

Kendall, William L.; White, Gary C.; Hines, James E.; Langtimm, Catherine A.; Yoshizaki, Jun

2012-01-01

Development and use of multistate mark-recapture models, which provide estimates of parameters of Markov processes in the face of imperfect detection, have become common over the last twenty years. Recently, estimating parameters of hidden Markov models, where the state of an individual can be uncertain even when it is detected, has received attention. Previous work has shown that ignoring state uncertainty biases estimates of survival and state transition probabilities, thereby reducing the power to detect effects. Efforts to adjust for state uncertainty have included special cases and a general framework for a single sample per period of interest. We provide a flexible framework for adjusting for state uncertainty in multistate models, while utilizing multiple sampling occasions per period of interest to increase precision and remove parameter redundancy. These models also produce direct estimates of state structure for each primary period, even for the case where there is just one sampling occasion. We apply our model to expected value data, and to data from a study of Florida manatees, to provide examples of the improvement in precision due to secondary capture occasions. We also provide user-friendly software to implement these models. This general framework could also be used by practitioners to consider constrained models of particular interest, or model the relationship between within-primary period parameters (e.g., state structure) and between-primary period parameters (e.g., state transition probabilities).

Evaluating early-warning indicators of critical transitions in natural aquatic ecosystems

USGS Publications Warehouse

Gsell, Alena Sonia; Scharfenberger, Ulrike; Ozkundakci, Deniz; Walters, Annika W.; Hansson, Lars-Anders; Janssen, Annette B. G.; Noges, Peeter; Reid, Philip; Schindler, Daniel; van Donk, Ellen; Dakos, Vasilis; Adrian, Rita

2016-01-01

Ecosystems can show sudden and persistent changes in state despite only incremental changes in drivers. Such critical transitions are difficult to predict, because the state of the system often shows little change before the transition. Early-warning indicators (EWIs) are hypothesized to signal the loss of system resilience and have been shown to precede critical transitions in theoretical models, paleo-climate time series, and in laboratory as well as whole lake experiments. The generalizability of EWIs for detecting critical transitions in empirical time series of natural aquatic ecosystems remains largely untested, however. Here we assessed four commonly used EWIs on long-term datasets of five freshwater ecosystems that have experienced sudden, persistent transitions and for which the relevant ecological mechanisms and drivers are well understood. These case studies were categorized by three mechanisms that can generate critical transitions between alternative states: competition, trophic cascade, and intraguild predation. Although EWIs could be detected in most of the case studies, agreement among the four indicators was low. In some cases, EWIs were detected considerably ahead of the transition. Nonetheless, our results show that at present, EWIs do not provide reliable and consistent signals of impending critical transitions despite using some of the best routinely monitored freshwater ecosystems. Our analysis strongly suggests that a priori knowledge of the underlying mechanisms driving ecosystem transitions is necessary to identify relevant state variables for successfully monitoring EWIs.

Evaluating early-warning indicators of critical transitions in natural aquatic ecosystems.

PubMed

Gsell, Alena Sonia; Scharfenberger, Ulrike; Özkundakci, Deniz; Walters, Annika; Hansson, Lars-Anders; Janssen, Annette B G; Nõges, Peeter; Reid, Philip C; Schindler, Daniel E; Van Donk, Ellen; Dakos, Vasilis; Adrian, Rita

2016-12-13

Ecosystems can show sudden and persistent changes in state despite only incremental changes in drivers. Such critical transitions are difficult to predict, because the state of the system often shows little change before the transition. Early-warning indicators (EWIs) are hypothesized to signal the loss of system resilience and have been shown to precede critical transitions in theoretical models, paleo-climate time series, and in laboratory as well as whole lake experiments. The generalizability of EWIs for detecting critical transitions in empirical time series of natural aquatic ecosystems remains largely untested, however. Here we assessed four commonly used EWIs on long-term datasets of five freshwater ecosystems that have experienced sudden, persistent transitions and for which the relevant ecological mechanisms and drivers are well understood. These case studies were categorized by three mechanisms that can generate critical transitions between alternative states: competition, trophic cascade, and intraguild predation. Although EWIs could be detected in most of the case studies, agreement among the four indicators was low. In some cases, EWIs were detected considerably ahead of the transition. Nonetheless, our results show that at present, EWIs do not provide reliable and consistent signals of impending critical transitions despite using some of the best routinely monitored freshwater ecosystems. Our analysis strongly suggests that a priori knowledge of the underlying mechanisms driving ecosystem transitions is necessary to identify relevant state variables for successfully monitoring EWIs.

Battery-Charge-State Model

NASA Technical Reports Server (NTRS)

Vivian, H. C.

1985-01-01

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

The End of Accretion: The X-Ray Binary/Millisecond Pulsar Transition Object PSR J1023+0038

NASA Astrophysics Data System (ADS)

Archibald, Anne

2015-04-01

Millisecond radio pulsars (MSRPs), those spinning hundreds of times per second, have long been understood to be old pulsars that have been spun up by the accretion of matter from a companion in a low-mass X-ray binary (LMXB) phase. Yet the details of this transformation, particularly the end of the accretion process and the birth of a radio pulsar, remain mysterious. I will describe the discovery and detailed study of the first object known to transition between MSRP and LMXB states, PSR J1023+0038. By dint of a multiwavelength campaign of observations in the RMSP state, we are able to measure all the key system parameters and show the existence of an X-ray shock close to the pulsar-facing side of the companion. Since the discovery of PSR J1023+0038, two more objects (XSS J12270-4859 and M28I) have been found to make the same transition, and the study of these transitioning objects has become an active field of research. Most interestingly, PSR J1023+0038 has transitioned back into an LMXB state, with an active accretion disk and a puzzling increase in gamma-ray flux. Our detailed picture of the system allows us to test models of accretion against the phenomena we observe in PSR J1023+0038, and in fact these observations challenge current models: in spite of the low luminosity of the system (and low inferred accretion rate) some material is penetrating the centrifugal barrier and falling on the neutron-star surface. Key evidence for explaining this puzzling behaviour will come when PSR J1023+0038 returns to an MSRP state and we are able to compare pulsar timing models from after the LMXB state with those we obtained in this work.

A stochastic hybrid systems based framework for modeling dependent failure processes

PubMed Central

Fan, Mengfei; Zeng, Zhiguo; Zio, Enrico; Kang, Rui; Chen, Ying

2017-01-01

In this paper, we develop a framework to model and analyze systems that are subject to dependent, competing degradation processes and random shocks. The degradation processes are described by stochastic differential equations, whereas transitions between the system discrete states are triggered by random shocks. The modeling is, then, based on Stochastic Hybrid Systems (SHS), whose state space is comprised of a continuous state determined by stochastic differential equations and a discrete state driven by stochastic transitions and reset maps. A set of differential equations are derived to characterize the conditional moments of the state variables. System reliability and its lower bounds are estimated from these conditional moments, using the First Order Second Moment (FOSM) method and Markov inequality, respectively. The developed framework is applied to model three dependent failure processes from literature and a comparison is made to Monte Carlo simulations. The results demonstrate that the developed framework is able to yield an accurate estimation of reliability with less computational costs compared to traditional Monte Carlo-based methods. PMID:28231313

A stochastic hybrid systems based framework for modeling dependent failure processes.

PubMed

Fan, Mengfei; Zeng, Zhiguo; Zio, Enrico; Kang, Rui; Chen, Ying

2017-01-01

In this paper, we develop a framework to model and analyze systems that are subject to dependent, competing degradation processes and random shocks. The degradation processes are described by stochastic differential equations, whereas transitions between the system discrete states are triggered by random shocks. The modeling is, then, based on Stochastic Hybrid Systems (SHS), whose state space is comprised of a continuous state determined by stochastic differential equations and a discrete state driven by stochastic transitions and reset maps. A set of differential equations are derived to characterize the conditional moments of the state variables. System reliability and its lower bounds are estimated from these conditional moments, using the First Order Second Moment (FOSM) method and Markov inequality, respectively. The developed framework is applied to model three dependent failure processes from literature and a comparison is made to Monte Carlo simulations. The results demonstrate that the developed framework is able to yield an accurate estimation of reliability with less computational costs compared to traditional Monte Carlo-based methods.

Solvable four-state Landau-Zener model of two interacting qubits with path interference

DOE PAGES

Sinitsyn, Nikolai A.

2015-11-30

In this paper, I identify a nontrivial four-state Landau-Zener model for which transition probabilities between any pair of diabatic states can be determined analytically and exactly. The model describes an experimentally accessible system of two interacting qubits, such as a localized state in a Dirac material with both valley and spin degrees of freedom or a singly charged quantum dot (QD) molecule with spin orbit coupling. Application of the linearly time-dependent magnetic field induces a sequence of quantum level crossings with possibility of interference of different trajectories in a semiclassical picture. I argue that this system satisfies the criteria ofmore » integrability in the multistate Landau-Zener theory, which allows one to derive explicit exact analytical expressions for the transition probability matrix. Finally, I also argue that this model is likely a special case of a larger class of solvable systems, and present a six-state generalization as an example.« less

Large bond-dimension time-evolution block decimation study of the XXZ quantum spin chains of S = 1/2 and 1

NASA Astrophysics Data System (ADS)

Choi, Hwan Bin; Lee, Ji-Woo

2017-09-01

We study quantum phase transitions of a XXZ spin model with spin S = 1/2 and 1 in one dimension. The XXZ spin chain is one of basic models in understanding various one-dimensional magnetic materials. To study this model, we construct infinite-lattice matrix product state (iMPS), which is a tensor product form for a one-dimensional many-body quantum wave function. By using timeevolution- block-decimation method (TEBD) on iMPS, we obtain the ground states of the XXZ model at zero temperature. This method is very delicate in calculating ground states so that we developed a reliable method of finding the ground state with the dimension of entanglement coefficients up to 300, which is beyond the previous works. By analyzing ground-state energies, half-chain entanglement entropies, and entanglement spectrum, we found the signatures of quantum phase transitions between ferromagnetic phase, XY phase, Haldane phase, and antiferromagnetic phase.

Dynamical phase transitions in generalized Kuramoto model with distributed Sakaguchi phase

NASA Astrophysics Data System (ADS)

Banerjee, Amitava

2017-11-01

In this numerical work, we have systematically studied the dynamical phase transitions in the Kuramoto-Sakaguchi model of synchronizing phase oscillators controlled by disorder in the Sakaguchi phases. We derive the numerical steady state phase diagrams for quenched and annealed kinds of disorder in the Sakaguchi parameters, using the conventional order parameter and other such statistical quantities as strength of incoherence and discontinuity measures. We have also considered the correlation profile of the local order parameter fluctuations in the various phases identified. The phase diagrams for quenched disorder are qualitatively much different from those in the global coupling regime. The order of various transitions is confirmed by a study of the distribution of the order parameter and its fourth order Binder’s cumulant across the transition for an ensemble of initial distribution of phases. For the annealed type of disorder, in contrast to the case with quenched disorder, the system is almost insensitive to the amount of disorder. We also elucidate the role of chimeralike states in the synchronizing transition of the system, and study the effect of disorder on these states. Finally, we seek justification of our results from simulations guided by the Ott-Antonsen ansatz.

Effect of Critical Displacement Parameter on Slip Regime at Subduction Fault

NASA Astrophysics Data System (ADS)

Muldashev, Iskander; Sobolev, Stephan

2016-04-01

It is widely accepted that for the simple fault models value of critical displacement parameter (Dc) in Ruina-Dietrich's rate-and-state friction law is responsible for the transition from stick-slip regime at low Dc to non-seismic creep regime at large Dc. However, neither the value of "transition" Dc parameter nor the character of the transition is known for the realistic subduction zone setting. Here we investigate effect of Dc on regime of slip at subduction faults for two setups, generic model similar to simple shear elastic slider under quasistatic loading and full subduction model with appropriate geometry, stress and temperature distribution similar to the setting at the site of the Great Chile Earthquake of 1960. In our modeling we use finite element numerical technique that employs non-linear elasto-visco-plastic rheology in the entire model domain with rate-and-state plasticity within the fault zone. The model generates spontaneous earthquake sequence. Adaptive time-step integration procedure varies time step from 40 seconds at instability (earthquake), and gradually increases it to 5 years during postseismic relaxation. The technique allows observing the effect of Dc on period, magnitude of earthquakes through the cycles. We demonstrate that our modeling results for the generic model are consistent with the previous theoretical and numeric modeling results. For the full subduction model we obtain transition from non-seismic creep to stick-slip regime at Dc about 20 cm. We will demonstrate and discuss the features of the transition regimes in both generic and realistic subduction models.

Collisional excitation of molecules in dense interstellar clouds

NASA Technical Reports Server (NTRS)

Green, S.

1985-01-01

State transitions which permit the identification of the molecular species in dense interstellar clouds are reviewed, along with the techniques used to calculate the transition energies, the database on known molecular transitions and the accuracy of the values. The transition energies cannot be measured directly and therefore must be modeled analytically. Scattering theory is used to determine the intermolecular forces on the basis of quantum mechanics. The nuclear motions can also be modeled with classical mechanics. Sample rate constants are provided for molecular systems known to inhabit dense interstellar clouds. The values serve as a database for interpreting microwave and RF astrophysical data on the transitions undergone by interstellar molecules.

Comparative Evaluation of Energy Measurement Models for Transit Systems

DOT National Transportation Integrated Search

1984-02-01

Recent advances in solid state control technology have led to chopper-controlled propulsion systems in urban rail transit applications. Such systems offer the potential for superior train performance through increased train propulsion efficiency and ...

Spectral properties near the Mott transition in the two-dimensional Hubbard model

NASA Astrophysics Data System (ADS)

Kohno, Masanori

2013-03-01

Single-particle excitations near the Mott transition in the two-dimensional (2D) Hubbard model are investigated by using cluster perturbation theory. The Mott transition is characterized by the loss of the spectral weight from the dispersing mode that leads continuously to the spin-wave excitation of the Mott insulator. The origins of the dominant modes of the 2D Hubbard model near the Mott transition can be traced back to those of the one-dimensional Hubbard model. Various anomalous spectral features observed in cuprate high-temperature superconductors, such as the pseudogap, Fermi arc, flat band, doping-induced states, hole pockets, and spinon-like and holon-like branches, as well as giant kink and waterfall in the dispersion relation, are explained in a unified manner as properties near the Mott transition in a 2D system.

Dynamics of gene expression with positive feedback to histone modifications at bivalent domains

NASA Astrophysics Data System (ADS)

Huang, Rongsheng; Lei, Jinzhi

2018-03-01

Experiments have shown that in embryonic stem cells, the promoters of many lineage-control genes contain “bivalent domains”, within which the nucleosomes possess both active (H3K4me3) and repressive (H3K27me3) marks. Such bivalent modifications play important roles in maintaining pluripotency in embryonic stem cells. Here, to investigate gene expression dynamics when there are regulations in bivalent histone modifications and random partition in cell divisions, we study how positive feedback to histone methylation/demethylation controls the transition dynamics of the histone modification patterns along with cell cycles. We constructed a computational model that includes dynamics of histone marks, three-stage chromatin state transitions, transcription and translation, feedbacks from protein product to enzymes to regulate the addition and removal of histone marks, and the inheritance of nucleosome state between cell cycles. The model reveals how dynamics of both nucleosome state transition and gene expression are dependent on the enzyme activities and feedback regulations. Results show that the combination of stochastic histone modification at each cell division and the deterministic feedback regulation work together to adjust the dynamics of chromatin state transition in stem cell regenerations.

Magnetic coupling at rare earth ferromagnet/transition metal ferromagnet interfaces: A comprehensive study of Gd/Ni.

PubMed

Higgs, T D C; Bonetti, S; Ohldag, H; Banerjee, N; Wang, X L; Rosenberg, A J; Cai, Z; Zhao, J H; Moler, K A; Robinson, J W A

2016-07-22

Thin film magnetic heterostructures with competing interfacial coupling and Zeeman energy provide a fertile ground to study phase transition between different equilibrium states as a function of external magnetic field and temperature. A rare-earth (RE)/transition metal (TM) ferromagnetic multilayer is a classic example where the magnetic state is determined by a competition between the Zeeman energy and antiferromagnetic interfacial exchange coupling energy. Technologically, such structures offer the possibility to engineer the macroscopic magnetic response by tuning the microscopic interactions between the layers. We have performed an exhaustive study of nickel/gadolinium as a model system for understanding RE/TM multilayers using the element-specific measurement technique x-ray magnetic circular dichroism, and determined the full magnetic state diagrams as a function of temperature and magnetic layer thickness. We compare our results to a modified Stoner-Wohlfarth-based model and provide evidence of a thickness-dependent transition to a magnetic fan state which is critical in understanding magnetoresistance effects in RE/TM systems. The results provide important insight for spintronics and superconducting spintronics where engineering tunable magnetic inhomogeneity is key for certain applications.

Magnetic coupling at rare earth ferromagnet/transition metal ferromagnet interfaces: A comprehensive study of Gd/Ni

DOE PAGES

Higgs, T. D. C.; Bonetti, S.; Ohldag, H.; ...

2016-07-22

Thin film magnetic heterostructures with competing interfacial coupling and Zeeman energy provide a fertile ground to study phase transition between different equilibrium states as a function of external magnetic field and temperature. A rare-earth (RE)/transition metal (TM) ferromagnetic multilayer is a classic example where the magnetic state is determined by a competition between the Zeeman energy and antiferromagnetic interfacial exchange coupling energy. Technologically, such structures offer the possibility to engineer the macroscopic magnetic response by tuning the microscopic interactions between the layers. We have performed an exhaustive study of nickel/gadolinium as a model system for understanding RE/TM multilayers using themore » element-specific measurement technique x-ray magnetic circular dichroism, and determined the full magnetic state diagrams as a function of temperature and magnetic layer thickness. We compare our results to a modified Stoner-Wohlfarth-based model and provide evidence of a thickness-dependent transition to a magnetic fan state which is critical in understanding magnetoresistance effects in RE/TM systems. In conclusion, the results provide important insight for spintronics and superconducting spintronics where engineering tunable magnetic inhomogeneity is key for certain applications.« less

Magnetic coupling at rare earth ferromagnet/transition metal ferromagnet interfaces: A comprehensive study of Gd/Ni

NASA Astrophysics Data System (ADS)

Higgs, T. D. C.; Bonetti, S.; Ohldag, H.; Banerjee, N.; Wang, X. L.; Rosenberg, A. J.; Cai, Z.; Zhao, J. H.; Moler, K. A.; Robinson, J. W. A.

2016-07-01

Thin film magnetic heterostructures with competing interfacial coupling and Zeeman energy provide a fertile ground to study phase transition between different equilibrium states as a function of external magnetic field and temperature. A rare-earth (RE)/transition metal (TM) ferromagnetic multilayer is a classic example where the magnetic state is determined by a competition between the Zeeman energy and antiferromagnetic interfacial exchange coupling energy. Technologically, such structures offer the possibility to engineer the macroscopic magnetic response by tuning the microscopic interactions between the layers. We have performed an exhaustive study of nickel/gadolinium as a model system for understanding RE/TM multilayers using the element-specific measurement technique x-ray magnetic circular dichroism, and determined the full magnetic state diagrams as a function of temperature and magnetic layer thickness. We compare our results to a modified Stoner-Wohlfarth-based model and provide evidence of a thickness-dependent transition to a magnetic fan state which is critical in understanding magnetoresistance effects in RE/TM systems. The results provide important insight for spintronics and superconducting spintronics where engineering tunable magnetic inhomogeneity is key for certain applications.

Estimation in a semi-Markov transformation model

PubMed Central

Dabrowska, Dorota M.

2012-01-01

Multi-state models provide a common tool for analysis of longitudinal failure time data. In biomedical applications, models of this kind are often used to describe evolution of a disease and assume that patient may move among a finite number of states representing different phases in the disease progression. Several authors developed extensions of the proportional hazard model for analysis of multi-state models in the presence of covariates. In this paper, we consider a general class of censored semi-Markov and modulated renewal processes and propose the use of transformation models for their analysis. Special cases include modulated renewal processes with interarrival times specified using transformation models, and semi-Markov processes with with one-step transition probabilities defined using copula-transformation models. We discuss estimation of finite and infinite dimensional parameters of the model, and develop an extension of the Gaussian multiplier method for setting confidence bands for transition probabilities. A transplant outcome data set from the Center for International Blood and Marrow Transplant Research is used for illustrative purposes. PMID:22740583

Reprogramming of Escherichia coli K-12 Metabolism during the Initial Phase of Transition from an Anaerobic to a Micro-Aerobic Environment

PubMed Central

Trotter, Eleanor W.; Rolfe, Matthew D.; Hounslow, Andrea M.; Craven, C. Jeremy; Williamson, Michael P.; Sanguinetti, Guido; Poole, Robert K.; Green, Jeffrey

2011-01-01

Background Many bacteria undergo transitions between environments with differing O2 availabilities as part of their natural lifestyles and during biotechnological processes. However, the dynamics of adaptation when bacteria experience changes in O2 availability are understudied. The model bacterium and facultative anaerobe Escherichia coli K-12 provides an ideal system for exploring this process. Methods and Findings Time-resolved transcript profiles of E. coli K-12 during the initial phase of transition from anaerobic to micro-aerobic conditions revealed a reprogramming of gene expression consistent with a switch from fermentative to respiratory metabolism. The changes in transcript abundance were matched by changes in the abundances of selected central metabolic proteins. A probabilistic state space model was used to infer the activities of two key regulators, FNR (O2 sensing) and PdhR (pyruvate sensing). The model implied that both regulators were rapidly inactivated during the transition from an anaerobic to a micro-aerobic environment. Analysis of the external metabolome and protein levels suggested that the cultures transit through different physiological states during the process of adaptation, characterized by the rapid inactivation of pyruvate formate-lyase (PFL), a slower induction of pyruvate dehydrogenase complex (PDHC) activity and transient excretion of pyruvate, consistent with the predicted inactivation of PdhR and FNR. Conclusion Perturbation of anaerobic steady-state cultures by introduction of a limited supply of O2 combined with time-resolved transcript, protein and metabolite profiling, and probabilistic modeling has revealed that pyruvate (sensed by PdhR) is a key metabolic signal in coordinating the reprogramming of E. coli K-12 gene expression by working alongside the O2 sensor FNR during transition from anaerobic to micro-aerobic conditions. PMID:21980479

Reprogramming of Escherichia coli K-12 metabolism during the initial phase of transition from an anaerobic to a micro-aerobic environment.

PubMed

Trotter, Eleanor W; Rolfe, Matthew D; Hounslow, Andrea M; Craven, C Jeremy; Williamson, Michael P; Sanguinetti, Guido; Poole, Robert K; Green, Jeffrey

2011-01-01

Many bacteria undergo transitions between environments with differing O₂ availabilities as part of their natural lifestyles and during biotechnological processes. However, the dynamics of adaptation when bacteria experience changes in O₂ availability are understudied. The model bacterium and facultative anaerobe Escherichia coli K-12 provides an ideal system for exploring this process. Time-resolved transcript profiles of E. coli K-12 during the initial phase of transition from anaerobic to micro-aerobic conditions revealed a reprogramming of gene expression consistent with a switch from fermentative to respiratory metabolism. The changes in transcript abundance were matched by changes in the abundances of selected central metabolic proteins. A probabilistic state space model was used to infer the activities of two key regulators, FNR (O₂ sensing) and PdhR (pyruvate sensing). The model implied that both regulators were rapidly inactivated during the transition from an anaerobic to a micro-aerobic environment. Analysis of the external metabolome and protein levels suggested that the cultures transit through different physiological states during the process of adaptation, characterized by the rapid inactivation of pyruvate formate-lyase (PFL), a slower induction of pyruvate dehydrogenase complex (PDHC) activity and transient excretion of pyruvate, consistent with the predicted inactivation of PdhR and FNR. Perturbation of anaerobic steady-state cultures by introduction of a limited supply of O₂ combined with time-resolved transcript, protein and metabolite profiling, and probabilistic modeling has revealed that pyruvate (sensed by PdhR) is a key metabolic signal in coordinating the reprogramming of E. coli K-12 gene expression by working alongside the O₂ sensor FNR during transition from anaerobic to micro-aerobic conditions.

Lifetime measurements of 17C excited states and three-body and continuum effects

DOE PAGES

Smalley, D.; Iwasaki, H.; Navratil, P.; ...

2015-12-18

We studied transition rates for the lowest 1/2 + and 5/2 + excited states of 17C through lifetime measurements with the GRETINA array using the recoil-distance method. The present measurements provide a model-independent determination of transition strengths giving the values of B(M1;1/2 + → 3/2 + g.s.) = 1.04 +0.03 –0.12 × 1 0–2μ 2 N and B(M1;5/2 + → 3/2 + g.s.) = 7.12 +1.27 –0.96 × 10 –2μ 2 N. The quenched M1 transition strength for the 1/2 + → 3/2 + g.s. transition, with respect to the 5/2 + → 3/ 2+ g.s. transition, has been confirmedmore » with greater precision. Furthermore, the current data are compared to importance-truncated no-core shell model calculations addressing effects due to continuum and three-body forces.« less

Efficient Transition Probability Computation for Continuous-Time Branching Processes via Compressed Sensing.

PubMed

Xu, Jason; Minin, Vladimir N

2015-07-01

Branching processes are a class of continuous-time Markov chains (CTMCs) with ubiquitous applications. A general difficulty in statistical inference under partially observed CTMC models arises in computing transition probabilities when the discrete state space is large or uncountable. Classical methods such as matrix exponentiation are infeasible for large or countably infinite state spaces, and sampling-based alternatives are computationally intensive, requiring integration over all possible hidden events. Recent work has successfully applied generating function techniques to computing transition probabilities for linear multi-type branching processes. While these techniques often require significantly fewer computations than matrix exponentiation, they also become prohibitive in applications with large populations. We propose a compressed sensing framework that significantly accelerates the generating function method, decreasing computational cost up to a logarithmic factor by only assuming the probability mass of transitions is sparse. We demonstrate accurate and efficient transition probability computations in branching process models for blood cell formation and evolution of self-replicating transposable elements in bacterial genomes.

Efficient Transition Probability Computation for Continuous-Time Branching Processes via Compressed Sensing

PubMed Central

Xu, Jason; Minin, Vladimir N.

2016-01-01

Branching processes are a class of continuous-time Markov chains (CTMCs) with ubiquitous applications. A general difficulty in statistical inference under partially observed CTMC models arises in computing transition probabilities when the discrete state space is large or uncountable. Classical methods such as matrix exponentiation are infeasible for large or countably infinite state spaces, and sampling-based alternatives are computationally intensive, requiring integration over all possible hidden events. Recent work has successfully applied generating function techniques to computing transition probabilities for linear multi-type branching processes. While these techniques often require significantly fewer computations than matrix exponentiation, they also become prohibitive in applications with large populations. We propose a compressed sensing framework that significantly accelerates the generating function method, decreasing computational cost up to a logarithmic factor by only assuming the probability mass of transitions is sparse. We demonstrate accurate and efficient transition probability computations in branching process models for blood cell formation and evolution of self-replicating transposable elements in bacterial genomes. PMID:26949377

Superfluid-insulator transitions of two-species bosons in an optical lattice

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

Isacsson, A.; Department of Physics, Yale University, P.O. Box 208120, New Haven, Connecticut 06520-8120; Cha, M.-C.

2005-11-01

We consider the two-species bosonic Hubbard model with variable interspecies interaction and hopping strength in the grand canonical ensemble with a common chemical potential. We analyze the superfluid-insulator (SI) transition for the relevant parameter regimes and compute the ground state phase diagram in the vicinity of odd filling Mott states. We find that the superfluid-insulator transition occurs with (a) simultaneous onset of superfluidity of both species or (b) coexistence of Mott insulating state of one species and superfluidity of the other or, in the case of unit filling (c) complete depopulation of one species. The superfluid-insulator transition can be firstmore » order in a large region of the phase diagram. We develop a variational mean-field method which takes into account the effect of second order quantum fluctuations on the superfluid-insulator transition and corroborate the mean-field phase diagram using a quantum Monte Carlo study.« less

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

Yu, Liang; Abild-Pedersen, Frank

On the basis of an extensive set of density functional theory calculations, it is shown that a simple scheme provides a fundamental understanding of variations in the transition state energies and structures of reaction intermediates on transition metal surfaces across the periodic table. The scheme is built on the bond order conservation principle and requires a limited set of input data, still achieving transition state energies as a function of simple descriptors with an error smaller than those of approaches based on linear fits to a set of calculated transition state energies. Here, we have applied this approach together withmore » linear scaling of adsorption energies to obtain the energetics of the NH 3 decomposition reaction on a series of stepped fcc(211) transition metal surfaces. Moreover, this information is used to establish a microkinetic model for the formation of N 2 and H 2, thus providing insight into the components of the reaction that determines the activity.« less

Contribution of the 2(1)Ag state to the third-order optical nonlinearity in a squaraine dye.

PubMed

Andrews, J H; Khaydarov, J D; Singer, K D

1994-07-01

We have measured the third-harmonic response, gamma, of a centrosymmetric squaraine dye (ISQ) in chloroform at a range of frequencies for which the third harmonic is above the strong, narrow peak in the dye's linear absorption spectrum but below the UV absorption band. By fitting the experimental dispersion of gamma using a four-level model, we determine the strength, location, and width of the lowest-lying two-photon transition. We find that the 2(1)Ag state appears just above the 1(1)Bu state in energy and that the 1(1)Bu-2(1)Ag transition moment is somewhat smaller than the transition moment between the ground state and the 1(1)Bu state but much larger than previously predicted for comparable squaraine dyes.

The use of spatio-temporal correlation to forecast critical transitions

NASA Astrophysics Data System (ADS)

Karssenberg, Derek; Bierkens, Marc F. P.

2010-05-01

Complex dynamical systems may have critical thresholds at which the system shifts abruptly from one state to another. Such critical transitions have been observed in systems ranging from the human body system to financial markets and the Earth system. Forecasting the timing of critical transitions before they are reached is of paramount importance because critical transitions are associated with a large shift in dynamical regime of the system under consideration. However, it is hard to forecast critical transitions, because the state of the system shows relatively little change before the threshold is reached. Recently, it was shown that increased spatio-temporal autocorrelation and variance can serve as alternative early warning signal for critical transitions. However, thus far these second order statistics have not been used for forecasting in a data assimilation framework. Here we show that the use of spatio-temporal autocorrelation and variance in the state of the system reduces the uncertainty in the predicted timing of critical transitions compared to classical approaches that use the value of the system state only. This is shown by assimilating observed spatio-temporal autocorrelation and variance into a dynamical system model using a Particle Filter. We adapt a well-studied distributed model of a logistically growing resource with a fixed grazing rate. The model describes the transition from an underexploited system with high resource biomass to overexploitation as grazing pressure crosses the critical threshold, which is a fold bifurcation. To represent limited prior information, we use a large variance in the prior probability distributions of model parameters and the system driver (grazing rate). First, we show that the rate of increase in spatio-temporal autocorrelation and variance prior to reaching the critical threshold is relatively consistent across the uncertainty range of the driver and parameter values used. This indicates that an increase in spatio-temporal autocorrelation and variance are consistent predictors of a critical transition, even under the condition of a poorly defined system. Second, we perform data assimilation experiments using an artificial exhaustive data set generated by one realization of the model. To mimic real-world sampling, an observational data set is created from this exhaustive data set. This is done by sampling on a regular spatio-temporal grid, supplemented by sampling locations at a short distance. Spatial and temporal autocorrelation in this observational data set is calculated for different spatial and temporal separation (lag) distances. To assign appropriate weights to observations (here, autocorrelation values and variance) in the Particle Filter, the covariance matrix of the error in these observations is required. This covariance matrix is estimated using Monte Carlo sampling, selecting a different random position of the sampling network relative to the exhaustive data set for each realization. At each update moment in the Particle Filter, observed autocorrelation values are assimilated into the model and the state of the model is updated. Using this approach, it is shown that the use of autocorrelation reduces the uncertainty in the forecasted timing of a critical transition compared to runs without data assimilation. The performance of the use of spatial autocorrelation versus temporal autocorrelation depends on the timing and number of observational data. This study is restricted to a single model only. However, it is becoming increasingly clear that spatio-temporal autocorrelation and variance can be used as early warning signals for a large number of systems. Thus, it is expected that spatio-temporal autocorrelation and variance are valuable in data assimilation frameworks in a large number of dynamical systems.

Preventive and Abortive Strategies for Stimulation Based Control of Epilepsy: A Computational Model Study.

PubMed

Koppert, Marc; Kalitzin, Stiliyan; Velis, Demetrios; Lopes Da Silva, Fernando; Viergever, Max A

2016-12-01

Epilepsy is a condition in which periods of ongoing normal EEG activity alternate with periods of oscillatory behavior characteristic of epileptic seizures. The dynamics of the transitions between the two states are still unclear. Computational models provide a powerful tool to explore the underlying mechanisms of such transitions, with the purpose of eventually finding therapeutic interventions for this debilitating condition. In this study, the possibility to postpone seizures elicited by a decrease of inhibition is investigated by using external stimulation in a realistic bistable neuronal model consisting of two interconnected neuronal populations representing pyramidal cells and interneurons. In the simulations, seizures are induced by slowly decreasing the conductivity of GABA[Formula: see text] synaptic channels over time. Since the model is bistable, the system will change state from the initial steady state (SS) to the limit cycle (LS) state because of internal noise, when the inhibition falls below a certain threshold. Several state-independent stimulations paradigms are simulated. Their effectiveness is analyzed for various stimulation frequencies and intensities in combination with periodic and random stimulation sequences. The distributions of the time to first seizure in the presence of stimulation are compared with the situation without stimulation. In addition, stimulation protocols targeted to specific subsystems are applied with the objective of counteracting the baseline shift due to decreased inhibition in the system. Furthermore, an analytical model is used to investigate the effects of random noise. The relation between the strength of random noise stimulation, the control parameter of the system and the transitions between steady state and limit cycle are investigated. The study shows that it is possible to postpone epileptic activity by targeted stimulation in a realistic neuronal model featuring bistability and that it is possible to stop seizures by random noise in an analytical model.

Experimental and theoretical study of the electronic spectrum of the BAr2 complex: Transition to the excited valence B(2s2p2 2D) state

NASA Astrophysics Data System (ADS)

Krumrine, Jennifer R.; Alexander, Millard H.; Yang, Xin; Dagdigian, Paul J.

2000-03-01

The 2s2p22D←2s22p 2P valence transition in the BAr2 cluster is investigated in a collaborative experimental and theoretical study. Laser fluorescence excitation spectra of a supersonic expansion of B atoms entrained in Ar at high source backing pressures display several features not assignable to the BAr complex. Resonance fluorescence is not observed, but instead emission from the lower 3s state. Size-selected fluorescence depletion spectra show that these features in the excitation spectrum are primarily due to the BAr2 complex. This electronic transition within BAr2 is modeled theoretically, similarly to our earlier study of the 3s←2p transition [M. H. Alexander et al., J. Chem. Phys. 106, 6320 (1997)]. The excited potential energy surfaces of the fivefold degenerate B(2s2p22D) state within the ternary complex are computed in a pairwise-additive model employing diatomic BAr potential energy curves which reproduce our previous experimental observations on the electronic states emanating from the B(2D)+Ar asymptote. The simulated absorption spectrum reproduces reasonably well the observed fluorescence depletion spectrum. The theoretical model lends insight into the energetics of the approach of B to multiple Ar atoms, and how the orientation of B p-orbitals governs the stability of the complex.

Transition State Analysis of Thymidine Hydrolysis by Human Thymidine Phosphorylase*

PubMed Central

Schwartz, Phillip A.; Vetticatt, Mathew; Schramm, Vern L.

2010-01-01

Human thymidine phosphorylase (hTP) is responsible for thymidine (dT) homeostasis and its action promotes angiogenesis. In the absence of phosphate, hTP catalyzes a slow hydrolytic depyrimidination of dT yielding thymine and 2-deoxyribose (dRib). Its transition state was characterized using multiple kinetic isotope effect (KIE) measurements. Isotopically enriched thymidines were synthesized enzymatically from glucose or (deoxy)ribose and intrinsic KIEs were used to interpret the transition state structure. KIEs from [1′-14C]-, [1-15N]-, [1′-3H]-, [2′R-3H]-, [2′S-3H]-, [4′-3H]-, [5′-3H]dTs provided values of 1.033 ± 0.002, 1.004 ± 0.002, 1.325 ± 0.003, 1.101 ± 0.004, 1.087 ± 0.005, 1.040 ± 0.003, and 1.033 ± 0.003, respectively. Transition state analysis revealed a stepwise mechanism with a 2-deoxyribocation formed early and a higher energetic barrier for nucleophilic attack of a water molecule on the high energy intermediate. An equilibrium exists between the deoxyribocation and reactants prior to the irreversible nucleophilic attack by water. The results establish activation of the thymine leaving group without requirement for phosphate. A transition state constrained to match the intrinsic KIEs was found using density functional theory. An active site histidine (His116) is implicated as the catalytic base for activation of the water nucleophile at the rate-limiting transition state. The distance between the water nucleophile and the anomeric carbon (rC-O) is predicted to be 2.3 Å at the transition state. The transition state model predicts that deoxyribose adopts a mild 3′-endo confirmation during nucleophilic capture. These results differ from the concerted bimolecular mechanism reported for the arsenolytic reaction PMID:20804144

Effects of Changes in Number of Medications and Drug Burden Index Exposure on Transitions Between Frailty States and Death: The Concord Health and Ageing in Men Project Cohort Study.

PubMed

Jamsen, Kris M; Bell, J Simon; Hilmer, Sarah N; Kirkpatrick, Carl M J; Ilomäki, Jenni; Le Couteur, David; Blyth, Fiona M; Handelsman, David J; Waite, Louise; Naganathan, Vasi; Cumming, Robert G; Gnjidic, Danijela

2016-01-01

To investigate the effects of number of medications and Drug Burden Index (DBI) on transitions between frailty stages and death in community-dwelling older men. Cohort study. Sydney, Australia. Community-dwelling men aged 70 and older (N=1,705). Self-reported questionnaires and clinic visits were conducted at baseline and 2 and 5 years. Frailty was assessed at all three waves according to the modified Fried frailty phenotype. The total number of regular prescription medications and DBI (a measure of exposure to sedative and anticholinergic medications) were calculated over the three waves. Data on mortality over 9 years were obtained. Multistate modeling was used to characterize the transitions across three frailty states (robust, prefrail, frail) and death. Each additional medication was associated with a 22% greater risk of transitioning from the robust state to death (adjusted 95% confidence interval (CI)=1.06-1.41). Every unit increase in DBI was associated with a 73% greater risk of transitioning from the robust state to the prefrail state (adjusted 95% CI=1.30-2.31) and a 2.75 times greater risk of transitioning from the robust state to death (adjusted 95% CI=1.60-4.75). There was no evidence of an adjusted association between total number of medications or DBI and the other transitions. Although the possibility of confounding by indication cannot be excluded, additional medications were associated with greater risk of mortality in robust community-dwelling older men. Greater DBI was also associated with greater risk of death and transitioning from the robust state to the prefrail state. © 2016, Copyright the Authors Journal compilation © 2016, The American Geriatrics Society.

Quantum transition state dynamics of the cyclooctatetraene unimolecular reaction on ab initio potential energy surfaces

NASA Astrophysics Data System (ADS)

Tokizaki, Chihiro; Yoshida, Takahiko; Takayanagi, Toshiyuki

2016-05-01

The cyclooctatetraene (COT) anion has a stable D4h structure that is similar to the transition state configurations of the neutral C-C bond-alternation (D4h ↔ D8h ↔ D4h) and ring-inversion (D2d ↔ D4h ↔ D2d) unimolecular reactions. The previously measured photodetachment spectrum of COT- revealed the reaction dynamics in the vicinity of the two transition states on the neutral potential energy surface. In this work, the photodetachment spectrum is calculated quantum mechanically on ab initio-level potential energy surfaces within a three degree-of-freedom reduced-dimensionality model. Very good agreement has been obtained between theory and experiment, providing reliable interpretations for the experimental spectrum. A detailed picture of the reactive molecular dynamics of the COT unimolecular reaction in the transition state region is also discussed.

Computational Work to Support FAP/SRW Variable-Speed Power-Turbine Development

NASA Technical Reports Server (NTRS)

Ameri, Ali A.

2012-01-01

The purpose of this report is to document the work done to enable a NASA CFD code to model the transition on a blade. The purpose of the present work is to down-select a transition model that would allow the flow simulation of a Variable-Speed Power-Turbine (VSPT) to be accurately performed. The modeling is to be ultimately performed to also account for the blade row interactions and effect on transition and therefore accurate accounting for losses. The present work is limited to steady flows. The low Reynolds number k-omega model of Wilcox and a modified version of same will be used for modeling of transition on experimentally measured blade pressure and heat transfer. It will be shown that the k-omega model and its modified variant fail to simulate the transition with any degree of accuracy. A case is therefore made for more accurate transition models. Three-equation models based on the work of Mayle on Laminar Kinetic Energy were explored and the Walters and Leylek model which was thought to be in a more mature state of development is introduced and implemented in the Glenn-HT code. Two-dimensional flat plate results and three-dimensional results for flow over turbine blades and the resulting heat transfer and its transitional behavior are reported. It is shown that the transition simulation is much improved over the baseline k-omega model.

Fast-timing lifetime measurements of excited states in Cu67

NASA Astrophysics Data System (ADS)

NiÅ£ǎ, C. R.; Bucurescu, D.; Mǎrginean, N.; Avrigeanu, M.; Bocchi, G.; Bottoni, S.; Bracco, A.; Bruce, A. M.; Cǎta-Danil, G.; Coló, G.; Deleanu, D.; Filipescu, D.; GhiÅ£ǎ, D. G.; Glodariu, T.; Leoni, S.; Mihai, C.; Mason, P. J. R.; Mǎrginean, R.; Negret, A.; Pantelicǎ, D.; Podolyak, Z.; Regan, P. H.; Sava, T.; Stroe, L.; Toma, S.; Ur, C. A.; Wilson, E.

2014-06-01

The half-lives of the 9/2+, 13/2+, and 15/2+ yrast states in the neutron-rich Cu67 nucleus were determined by using the in-beam fast-timing technique. The experimentally deduced E3 transition strength for the decay of the 9/2+ level to the 3/2- ground state indicates that the wave function of this level might contain a collective component arising from the coupling of the odd proton p3/2 with the 3- state in Ni66. Theoretical interpretations of the 9/2+ state are presented within the particle-vibration weak-coupling scheme involving the unpaired proton and the 3- state from Ni66 and within shell-model calculations with a Ni56 core using the jj44b residual interaction. The shell model also accounts reasonably well for the other measured electromagnetic transition probabilities.

Modeling of Shock Waves with Multiple Phase Transitions in Condensed Materials

NASA Astrophysics Data System (ADS)

Missonnier, Marc; Heuzé, Olivier

2006-07-01

When a shock wave crosses a solid material and subjects it to solid-solid or solid-liquid phase transition, related phenomena occur: shock splitting, and the corresponding released shock wave after reflection. Modelling of these phenomena raises physical and numerical issues. After shock loading, such materials can reach different kinds of states: single-phase states, binary-phase states, and triple points. The thermodynamic path can be studied and easily understood in the (V,E) or (V,S) planes. In the case of 3 phase tin (β,γ, and liquid) submitted to shock waves, seven states can occur: β,γ, liquid, β-γ, β-liquid, γ-liquid, and β-γ-liquid. After studying the thermodynamic properties with a complete 3-phase Equation of State, we show the existence of these seven states with a hydrodynamic simulation.

Quantum phase transitions between a class of symmetry protected topological states

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

Tsui, Lokman; Jiang, Hong -Chen; Lu, Yuan -Ming

2015-04-30

The subject of this paper is the phase transition between symmetry protected topological states (SPTs). We consider spatial dimension d and symmetry group G so that the cohomology group, H d+1(G,U(1)), contains at least one Z 2n or Z factor. We show that the phase transition between the trivial SPT and the root states that generate the Z 2n or Z groups can be induced on the boundary of a (d+1)-dimensional G x Z T 2-symmetric SPT by a Z T 2 symmetry breaking field. Moreover we show these boundary phase transitions can be “transplanted” to d dimensions and realizedmore » in lattice models as a function of a tuning parameter. The price one pays is for the critical value of the tuning parameter there is an extra non-local (duality-like) symmetry. In the case where the phase transition is continuous, our theory predicts the presence of unusual (sometimes fractionalized) excitations corresponding to delocalized boundary excitations of the non-trivial SPT on one side of the transition. This theory also predicts other phase transition scenarios including first order transition and transition via an intermediate symmetry breaking phase.« less

Density functional tight-binding and infrequent metadynamics can capture entropic effects in intramolecular hydrogen transfer reactions

NASA Astrophysics Data System (ADS)

Oliveira, Luiz F. L.; Fu, Christopher D.; Pfaendtner, Jim

2018-04-01

Infrequent metadynamics uses biased simulations to estimate the unbiased kinetics of a system, facilitating the calculation of rates and barriers. Here the method is applied to study intramolecular hydrogen transfer reactions involving peroxy radicals, a class of reactions that is challenging to model due to the entropic contributions of the formation of ring structures in the transition state. Using the self-consistent charge density-functional based tight-binding (DFTB) method, we applied infrequent metadynamics to the study of four intramolecular H-transfer reactions, demonstrating that the method can qualitatively reproduce these high entropic contributions, as observed in experiments and those predicted by transition state theory modeled by higher levels of theory. We also show that infrequent metadynamics and DFTB are successful in describing the relationship between transition state ring size and kinetic coefficients (e.g., activation energies and the pre-exponential factors).

Insights into the nature of DNA binding of AbrB-like transcription factors

PubMed Central

Sullivan, Daniel M.; Bobay, Benjamin G.; Kojetin, Douglas J.; Thompson, Richele J.; Rance, Mark; Strauch, Mark A.; Cavanagh, John

2008-01-01

Summary Understanding the DNA recognition and binding by the AbrB-like family of transcriptional regulators is of significant interest since these proteins enable bacteria to elicit the appropriate response to diverse environmental stimuli. Although these ‘transition-state regulator’ proteins have been well characterized at the genetic level, the general and specific mechanisms of DNA binding remain elusive. We present RDC-refined NMR solution structures and dynamic properties of the DNA-binding domains of three Bacillus subtilis transition-state regulators AbrB, Abh, and SpoVT. We combined previously investigated DNase I footprinting, DNA methylation, gel shift assays, mutagenic and NMR studies to generate a structural model of the complex between AbrBN55 and its cognate promoter, abrB8. These investigations have enabled us to generate the first model for the specific nature of the transition-state regulator-DNA interaction. PMID:19000822

Kinetics from Replica Exchange Molecular Dynamics Simulations.

PubMed

Stelzl, Lukas S; Hummer, Gerhard

2017-08-08

Transitions between metastable states govern many fundamental processes in physics, chemistry and biology, from nucleation events in phase transitions to the folding of proteins. The free energy surfaces underlying these processes can be obtained from simulations using enhanced sampling methods. However, their altered dynamics makes kinetic and mechanistic information difficult or impossible to extract. Here, we show that, with replica exchange molecular dynamics (REMD), one can not only sample equilibrium properties but also extract kinetic information. For systems that strictly obey first-order kinetics, the procedure to extract rates is rigorous. For actual molecular systems whose long-time dynamics are captured by kinetic rate models, accurate rate coefficients can be determined from the statistics of the transitions between the metastable states at each replica temperature. We demonstrate the practical applicability of the procedure by constructing master equation (Markov state) models of peptide and RNA folding from REMD simulations.

Structural model of the open–closed–inactivated cycle of prokaryotic voltage-gated sodium channels

PubMed Central

Bagnéris, Claire; Naylor, Claire E.; McCusker, Emily C.

2015-01-01

In excitable cells, the initiation of the action potential results from the opening of voltage-gated sodium channels. These channels undergo a series of conformational changes between open, closed, and inactivated states. Many models have been proposed for the structural transitions that result in these different functional states. Here, we compare the crystal structures of prokaryotic sodium channels captured in the different conformational forms and use them as the basis for examining molecular models for the activation, slow inactivation, and recovery processes. We compare structural similarities and differences in the pore domains, specifically in the transmembrane helices, the constrictions within the pore cavity, the activation gate at the cytoplasmic end of the last transmembrane helix, the C-terminal domain, and the selectivity filter. We discuss the observed differences in the context of previous models for opening, closing, and inactivation, and present a new structure-based model for the functional transitions. Our proposed prokaryotic channel activation mechanism is then compared with the activation transition in eukaryotic sodium channels. PMID:25512599

Quantum vertex model for reversible classical computing.

PubMed

Chamon, C; Mucciolo, E R; Ruckenstein, A E; Yang, Z-C

2017-05-12

Mappings of classical computation onto statistical mechanics models have led to remarkable successes in addressing some complex computational problems. However, such mappings display thermodynamic phase transitions that may prevent reaching solution even for easy problems known to be solvable in polynomial time. Here we map universal reversible classical computations onto a planar vertex model that exhibits no bulk classical thermodynamic phase transition, independent of the computational circuit. Within our approach the solution of the computation is encoded in the ground state of the vertex model and its complexity is reflected in the dynamics of the relaxation of the system to its ground state. We use thermal annealing with and without 'learning' to explore typical computational problems. We also construct a mapping of the vertex model into the Chimera architecture of the D-Wave machine, initiating an approach to reversible classical computation based on state-of-the-art implementations of quantum annealing.

Quantum vertex model for reversible classical computing

NASA Astrophysics Data System (ADS)

Chamon, C.; Mucciolo, E. R.; Ruckenstein, A. E.; Yang, Z.-C.

2017-05-01

Mappings of classical computation onto statistical mechanics models have led to remarkable successes in addressing some complex computational problems. However, such mappings display thermodynamic phase transitions that may prevent reaching solution even for easy problems known to be solvable in polynomial time. Here we map universal reversible classical computations onto a planar vertex model that exhibits no bulk classical thermodynamic phase transition, independent of the computational circuit. Within our approach the solution of the computation is encoded in the ground state of the vertex model and its complexity is reflected in the dynamics of the relaxation of the system to its ground state. We use thermal annealing with and without `learning' to explore typical computational problems. We also construct a mapping of the vertex model into the Chimera architecture of the D-Wave machine, initiating an approach to reversible classical computation based on state-of-the-art implementations of quantum annealing.

Fast-timing study of the l -forbidden 1 /2+→3 /2+ M 1 transition in 129Sn

NASA Astrophysics Data System (ADS)

Licǎ, R.; Mach, H.; Fraile, L. M.; Gargano, A.; Borge, M. J. G.; Mǎrginean, N.; Sotty, C. O.; Vedia, V.; Andreyev, A. N.; Benzoni, G.; Bomans, P.; Borcea, R.; Coraggio, L.; Costache, C.; De Witte, H.; Flavigny, F.; Fynbo, H.; Gaffney, L. P.; Greenlees, P. T.; Harkness-Brennan, L. J.; Huyse, M.; Ibáñez, P.; Judson, D. S.; Konki, J.; Korgul, A.; Kröll, T.; Kurcewicz, J.; Lalkovski, S.; Lazarus, I.; Lund, M. V.; Madurga, M.; Mǎrginean, R.; Marroquín, I.; Mihai, C.; Mihai, R. E.; Morales, A. I.; Nácher, E.; Negret, A.; Page, R. D.; Pakarinen, J.; Pascu, S.; Paziy, V.; Perea, A.; Pérez-Liva, M.; Picado, E.; Pucknell, V.; Rapisarda, E.; Rahkila, P.; Rotaru, F.; Swartz, J. A.; Tengblad, O.; Van Duppen, P.; Vidal, M.; Wadsworth, R.; Walters, W. B.; Warr, N.; IDS Collaboration

2016-04-01

The levels in 129Sn populated from the β- decay of 129In isomers were investigated at the ISOLDE facility of CERN using the newly commissioned ISOLDE Decay Station (IDS). The lowest 1 /2+ state and the 3 /2+ ground state in 129Sn are expected to have configurations dominated by the neutron s1 /2 (l =0 ) and d3 /2 (l =2 ) single-particle states, respectively. Consequently, these states should be connected by a somewhat slow l -forbidden M 1 transition. Using fast-timing spectroscopy we have measured the half-life of the 1 /2+ 315.3-keV state, T1 /2= 19(10) ps, which corresponds to a moderately fast M 1 transition. Shell-model calculations using the CD-Bonn effective interaction, with standard effective charges and g factors, predict a 4-ns half-life for this level. We can reconcile the shell-model calculations to the measured T1 /2 value by the renormalization of the M 1 effective operator for neutron holes.

Phase diagram of the chiral magnet Cr1 /3NbS2 in a magnetic field

NASA Astrophysics Data System (ADS)

Tsuruta, K.; Mito, M.; Deguchi, H.; Kishine, J.; Kousaka, Y.; Akimitsu, J.; Inoue, K.

2016-03-01

We construct the phase diagram of the chiral magnet Cr1 /3NbS2 in a dc magnetic field (Hdc) using ac magnetic susceptibility measurements. At Hdc=0 , the ac response at the transition from the helical magnetic (HM) state to the paramagnetic (PM) state consists of a giant third-order harmonic component (M3 ω) and a first-order harmonic component (M1 ω). By applying Hdc perpendicular to the c axis, the HM state is transformed to the chiral soliton lattice (CSL) state, which is a superlattice tuned by Hdc. The above giant M3 ω is markedly suppressed at small Hdc. The CSL state is found to consist of CSL-1, with dominant helical texture and a poor ferromagnetic array, and CSL-2, with a large ferromagnetic array. The transition between CSL-1 and the PM state causes a linear magnetic response, the dominant component of which is the in-phase M1 ω. With increasing temperature, CSL-2 is transformed into the forced ferromagnetic (FFM) state, and ultimately the PM state is reached. The transition between CSL-2 and the FFM state consists of a large M3 ω and large out-of-phase M1 ω as well as in-phase M1 ω. The transition between the FMM and PM states also yields a linear magnetic response, like the CSL-1-PM-state transition. Five typical magnetic dynamics in the transitions among the HM state, CSL-1, CSL-2, FFM state, and PM state were identified according to the equivalent dynamical motion equation of a nonlinear spring model.

Independent evaluation of the transit retrofit package safety applications : final report.

DOT National Transportation Integrated Search

2015-02-01

This report presents the methodology and results of the independent evaluation of retrofit safety packages installed on transit vehicles in the : Safety Pilot Model Deploymentpart of the United States Department of Transportations Intelligent T...

Phase Transitions of an Epidemic Spreading Model in Small-World Networks

NASA Astrophysics Data System (ADS)

Hua, Da-Yin; Gao, Ke

2011-06-01

We propose a modified susceptible-infected-refractory-susceptible (SIRS) model to investigate the global oscillations of the epidemic spreading in Watts—Strogatz (WS) small-world networks. It is found that when an individual immunity does not change or decays slowly in an immune period, the system can exhibit complex transition from an infecting stationary state to a large amplitude sustained oscillation or an absorbing state with no infection. When the immunity decays rapidly in the immune period, the transition to the global oscillation disappears and there is no oscillation. Furthermore, based on the spatio-temporal evolution patterns and the phase diagram, it is disclosed that a long immunity period takes an important role in the emergence of the global oscillation in small-world networks.

A landscape-scale assessment of plant communities, hydrologic processes, and state-and-transition theory in a western juniper dominated ecosystem

NASA Astrophysics Data System (ADS)

Petersen, Steven L.

Western juniper has rapidly expanded into sagebrush steppe communities in the Intermountain West during the past 120 years. This expansion has occurred across a wide range of soil types and topographic positions. These plant communities, however, are typically treated in current peer-reviewed literature generically. The focus of this research is to investigate watershed level response to Western juniper encroachment at multiple topographic positions. Data collected from plots used to measure vegetation, soil moisture, and infiltration rates show that intercanopy sites within encroached Western juniper communities generally exhibit a significant decrease in intercanopy plant density and cover, decreased infiltration rates, increased water sediment content, and lower soil moisture content. High-resolution remotely sensed imagery and Geographic Information Systems were used with these plot level measurements to characterize and model the landscape-scale response for both biotic and abiotic components of a Western juniper encroached ecosystem. These data and their analyses included an inventory of plant density, plant cover, bare ground, gap distance and cover, a plant community classification of intercanopy patches and juniper canopy cover, soil moisture estimation, solar insulation prediction, slope and aspect. From these data, models were built that accurately predicted shrub density and shrub cover throughout the watershed study area, differentiated by aspect. We propose a new model of process-based plant community dynamics associated with current state-and-transition theory. This model is developed from field measurements and spatially explicit information that characterize the relationship between the matrix mountain big sagebrush plant community and intercanopy plant community patterns occurring within a Western juniper dominated woodland at a landscape scale. Model parameters (states, transitions, and thresholds) are developed based on differences in shrub density and cover, steady-state infiltration rates, water sediment content, and percent bare ground in response to juniper competition and topographic position. Results from both analysis of variance and multivariate hierarchical cluster analysis indicate that states, transitions, and thresholds can be accurately predicted for intercanopy areas occurring within the study area. In theory, this model and the GIS-based layers produced from this research can be used together to predict states, transitions, and thresholds for any location within the extent of the study area. This is a valuable tool for assessing sites at risk and those that have exceeded the ability to self-repair.

Are rapid transitions between invasive and native species caused by alternative stable states, and does it matter?

PubMed

Hansen, Gretchen J A; Ives, Anthony R; Vander Zanden, M Jake; Carpenter, Stephen R

2013-10-01

Rapid transitions in ecosystem structure, or regime shifts, are a hallmark of alternative stable states (ASS). However, regime shifts can occur even when feedbacks are not strong enough to cause ASS. We investigated the potential for ASS to explain transitions between dominance of an invasive species, rusty crayfish (Orconectes rusticus), and native sunfishes (Lepomis spp.) in northern Wisconsin (USA) lakes. A rapid transition from Lepomis to rusty crayfish dominance occurred as rusty crayfish invaded Trout Lake, and the reverse transition resulted from an eight-year experimental removal of rusty crayfish from Sparkling Lake. We fit a stage-structured population model of species interactions to 31 years of time-series data from each lake. The model identified water level as an important driver, with drought conditions reducing rusty crayfish recruitment and allowing Lepomis dominance. The maximum-likelihood parameter estimates of the negative interaction between rusty crayfish and Lepomis led to ASS in the model, where each species was capable of excluding the other within a narrow range of environmental conditions. However, uncertainty in parameter estimates made it impossible to exclude the potential that rapid transitions were caused by a simpler threshold response lacking alternative equilibria. Simulated forward and backward transitions between species dominance occurred at different environmental conditions (i.e., hysteresis), even when the parameters used for simulation did not predict ASS as a result of slow species responses to environmental drivers. Thus, ASS are possible, but by no means certain, explanations for rapid transitions in this system, and our results highlight the difficulties associated with distinguishing ASS from other types of threshold responses. However, whether regime shifts are caused by ASS may be relatively unimportant in this system, as the range of conditions over which transitions occur is narrow, and under most conditions, the system is predicted to exist in only a single state.

Diffusion maps, clustering and fuzzy Markov modeling in peptide folding transitions

NASA Astrophysics Data System (ADS)

Nedialkova, Lilia V.; Amat, Miguel A.; Kevrekidis, Ioannis G.; Hummer, Gerhard

2014-09-01

Using the helix-coil transitions of alanine pentapeptide as an illustrative example, we demonstrate the use of diffusion maps in the analysis of molecular dynamics simulation trajectories. Diffusion maps and other nonlinear data-mining techniques provide powerful tools to visualize the distribution of structures in conformation space. The resulting low-dimensional representations help in partitioning conformation space, and in constructing Markov state models that capture the conformational dynamics. In an initial step, we use diffusion maps to reduce the dimensionality of the conformational dynamics of Ala5. The resulting pretreated data are then used in a clustering step. The identified clusters show excellent overlap with clusters obtained previously by using the backbone dihedral angles as input, with small—but nontrivial—differences reflecting torsional degrees of freedom ignored in the earlier approach. We then construct a Markov state model describing the conformational dynamics in terms of a discrete-time random walk between the clusters. We show that by combining fuzzy C-means clustering with a transition-based assignment of states, we can construct robust Markov state models. This state-assignment procedure suppresses short-time memory effects that result from the non-Markovianity of the dynamics projected onto the space of clusters. In a comparison with previous work, we demonstrate how manifold learning techniques may complement and enhance informed intuition commonly used to construct reduced descriptions of the dynamics in molecular conformation space.

Diffusion maps, clustering and fuzzy Markov modeling in peptide folding transitions

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

Nedialkova, Lilia V.; Amat, Miguel A.; Kevrekidis, Ioannis G., E-mail: yannis@princeton.edu, E-mail: gerhard.hummer@biophys.mpg.de

Using the helix-coil transitions of alanine pentapeptide as an illustrative example, we demonstrate the use of diffusion maps in the analysis of molecular dynamics simulation trajectories. Diffusion maps and other nonlinear data-mining techniques provide powerful tools to visualize the distribution of structures in conformation space. The resulting low-dimensional representations help in partitioning conformation space, and in constructing Markov state models that capture the conformational dynamics. In an initial step, we use diffusion maps to reduce the dimensionality of the conformational dynamics of Ala5. The resulting pretreated data are then used in a clustering step. The identified clusters show excellent overlapmore » with clusters obtained previously by using the backbone dihedral angles as input, with small—but nontrivial—differences reflecting torsional degrees of freedom ignored in the earlier approach. We then construct a Markov state model describing the conformational dynamics in terms of a discrete-time random walk between the clusters. We show that by combining fuzzy C-means clustering with a transition-based assignment of states, we can construct robust Markov state models. This state-assignment procedure suppresses short-time memory effects that result from the non-Markovianity of the dynamics projected onto the space of clusters. In a comparison with previous work, we demonstrate how manifold learning techniques may complement and enhance informed intuition commonly used to construct reduced descriptions of the dynamics in molecular conformation space.« less

Diffusion maps, clustering and fuzzy Markov modeling in peptide folding transitions

PubMed Central

Nedialkova, Lilia V.; Amat, Miguel A.; Kevrekidis, Ioannis G.; Hummer, Gerhard

2014-01-01

Using the helix-coil transitions of alanine pentapeptide as an illustrative example, we demonstrate the use of diffusion maps in the analysis of molecular dynamics simulation trajectories. Diffusion maps and other nonlinear data-mining techniques provide powerful tools to visualize the distribution of structures in conformation space. The resulting low-dimensional representations help in partitioning conformation space, and in constructing Markov state models that capture the conformational dynamics. In an initial step, we use diffusion maps to reduce the dimensionality of the conformational dynamics of Ala5. The resulting pretreated data are then used in a clustering step. The identified clusters show excellent overlap with clusters obtained previously by using the backbone dihedral angles as input, with small—but nontrivial—differences reflecting torsional degrees of freedom ignored in the earlier approach. We then construct a Markov state model describing the conformational dynamics in terms of a discrete-time random walk between the clusters. We show that by combining fuzzy C-means clustering with a transition-based assignment of states, we can construct robust Markov state models. This state-assignment procedure suppresses short-time memory effects that result from the non-Markovianity of the dynamics projected onto the space of clusters. In a comparison with previous work, we demonstrate how manifold learning techniques may complement and enhance informed intuition commonly used to construct reduced descriptions of the dynamics in molecular conformation space. PMID:25240340

Configurational entropy of polar glass formers and the effect of electric field on glass transition

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

Matyushov, Dmitry V., E-mail: dmitrym@asu.edu

2016-07-21

A model of low-temperature polar liquids is constructed that accounts for the configurational heat capacity, entropy, and the effect of a strong electric field on the glass transition. The model is based on the Padé-truncated perturbation expansions of the liquid state theory. Depending on parameters, it accommodates an ideal glass transition of vanishing configurational entropy and its avoidance, with a square-root divergent enumeration function at the point of its termination. A composite density-temperature parameter ρ{sup γ}/T, often used to represent combined pressure and temperature data, follows from the model. The theory is in good agreement with the experimental data formore » excess (over the crystal state) thermodynamics of molecular glass formers. We suggest that the Kauzmann entropy crisis might be a signature of vanishing configurational entropy of a subset of degrees of freedom, multipolar rotations in our model. This scenario has observable consequences: (i) a dynamical crossover of the relaxation time and (ii) the fragility index defined by the ratio of the excess heat capacity and excess entropy at the glass transition. The Kauzmann temperature of vanishing configurational entropy and the corresponding glass transition temperature shift upward when the electric field is applied. The temperature shift scales quadratically with the field strength.« less

Calculating ground water transit time of horizontal flow through leaky aquifers.

PubMed

Braunsfurth, Angelika C; Schneider, Wilfried

2008-01-01

The calculation of ground water transit times is one important factor in ground water protection. In this paper, we present an analytical solution for the transit time for a Dupuit-type flow system applicable to saturated flow through a horizontal leaky aquifer discharging to a downgradient fixed-head boundary under steady-state conditions. We investigate the influence of leakage when comparing the resulting travel times of our model based on head-dependent leakage with the commonly used model with no leakage and a simplified model with constant leakage. The results show significant differences in the position of the water divide and transit time, suggesting that leakage cannot be ignored.

Sensitivity to perturbations and quantum phase transitions.

PubMed

Wisniacki, D A; Roncaglia, A J

2013-05-01

The local density of states or its Fourier transform, usually called fidelity amplitude, are important measures of quantum irreversibility due to imperfect evolution. In this Rapid Communication we study both quantities in a paradigmatic many body system, the Dicke Hamiltonian, where a single-mode bosonic field interacts with an ensemble of N two-level atoms. This model exhibits a quantum phase transition in the thermodynamic limit, while for finite instances the system undergoes a transition from quasi-integrability to quantum chaotic. We show that the width of the local density of states clearly points out the imprints of the transition from integrability to chaos but no trace remains of the quantum phase transition. The connection with the decay of the fidelity amplitude is also established.

A resonance based model of biological evolution

NASA Astrophysics Data System (ADS)

Damasco, Achille; Giuliani, Alessandro

2017-04-01

We propose a coarse grained physical model of evolution. The proposed model 'at least in principle' is amenable of an experimental verification even if this looks as a conundrum: evolution is a unique historical process and the tape cannot be reversed and played again. Nevertheless, we can imagine a phenomenological scenario tailored upon state transitions in physical chemistry in which different agents of evolution play the role of the elements of a state transition like thermal noise or resonance effects. The abstract model we propose can be of help for sketching hypotheses and getting rid of some well-known features of natural history like the so-called Cambrian explosion. The possibility of an experimental proof of the model is discussed as well.

NSR&D FY15 Final Report. Modeling Mechanical, Thermal, and Chemical Effects of Impact

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

Long, Christopher Curtis; Ma, Xia; Zhang, Duan Zhong

2015-11-02

The main goal of this project is to develop a computer model that explains and predicts coupled mechanical, thermal and chemical responses of HE under impact and friction insults. The modeling effort is based on the LANL-developed CartaBlanca code, which is implemented with the dual domain material point (DDMP) method to calculate complex and coupled thermal, chemical and mechanical effects among fluids, solids and the transitions between the states. In FY 15, we have implemented the TEPLA material model for metal and performed preliminary can penetration simulation and begun to link with experiment. Currently, we are working on implementing amore » shock to detonation transition (SDT) model (SURF) and JWL equation of state.« less

Role of dimensionality in Axelrod's model for the dissemination of culture

NASA Astrophysics Data System (ADS)

Klemm, Konstantin; Eguíluz, Víctor M.; Toral, Raúl; Miguel, Maxi San

2003-09-01

We analyze a model of social interaction in one- and two-dimensional lattices for a moderate number of features. We introduce an order parameter as a function of the overlap between neighboring sites. In a one-dimensional chain, we observe that the dynamics is consistent with a second-order transition, where the order parameter changes continuously and the average domain diverges at the transition point. However, in a two-dimensional lattice the order parameter is discontinuous at the transition point characteristic of a first-order transition between an ordered and a disordered state.

GaAs-oxide interface states - A gigantic photoionization effect and its implications to the origin of these states

NASA Technical Reports Server (NTRS)

Lagowski, J.; Walukiewicz, W.; Kazior, T. E.; Gatos, H. C.; Siejka, J.

1981-01-01

Gigantic photoionization was discovered on GaAs-oxide interfaces leading to the discharge of deep surface states with rates exceeding 1000 times those of photoionization transitions to the conduction band. It exhibits a peak similar to acceptor-donor transitions and is explained as due to energy transfer from photo-excited donor-acceptor pairs to deep surface states. This new process indicates the presence of significant concentrations of shallow donor and acceptor levels not recognized in previous interface models.

Generation of Department of Defense Architecture Framework (DODAF) Models Using the Monterey Phoenix Behavior Modeling Approach

DTIC Science & Technology

2015-09-01

63 Figure 30. Order processing state diagram (after Fowler and Scott 1997). ......................64 x Figure 32. Four of...events, precedence and inclusion. Figure 30 shows an OV-6b for order processing states. 64 Figure 30. Order processing state diagram (after Fowler... Order Processing State Transition Starts at checking order Ends at order delivered

Generating probabilistic Boolean networks from a prescribed transition probability matrix.

PubMed

Ching, W-K; Chen, X; Tsing, N-K

2009-11-01

Probabilistic Boolean networks (PBNs) have received much attention in modeling genetic regulatory networks. A PBN can be regarded as a Markov chain process and is characterised by a transition probability matrix. In this study, the authors propose efficient algorithms for constructing a PBN when its transition probability matrix is given. The complexities of the algorithms are also analysed. This is an interesting inverse problem in network inference using steady-state data. The problem is important as most microarray data sets are assumed to be obtained from sampling the steady-state.

Improving the effectiveness of ecological site descriptions: General state-and-transition models and the Ecosystem Dynamics Interpretive Tool (EDIT)

USGS Publications Warehouse

Bestelmeyer, Brandon T.; Williamson, Jeb C.; Talbot, Curtis J.; Cates, Greg W.; Duniway, Michael C.; Brown, Joel R.

2016-01-01

State-and-transition models (STMs) are useful tools for management, but they can be difficult to use and have limited content.STMs created for groups of related ecological sites could simplify and improve their utility. The amount of information linked to models can be increased using tables that communicate management interpretations and important within-group variability.We created a new web-based information system (the Ecosystem Dynamics Interpretive Tool) to house STMs, associated tabular information, and other ecological site data and descriptors.Fewer, more informative, better organized, and easily accessible STMs should increase the accessibility of science information.

Superradiant phase transition with graphene embedded in one dimensional optical cavity

NASA Astrophysics Data System (ADS)

Li, Benliang; Liu, Tao; Hewak, Daniel W.; Wang, Qi Jie

2018-01-01

We theoretically investigate the cavity QED of graphene embedded in an optical cavity under perpendicular magnetic field. We consider the coupling of cyclotron transition and a multimode cavity described by a multimode Dicke model. This model exhibits a superradiant quantum phase transition, which we describe exactly in an effective Hamiltonian approach. The complete excitation spectrum in both the normal phase and superradiant phase regimes is given. In contrast to the single mode case, multimode coupling of cavity photon and cyclotron transition can greatly reduce the critical vacuum Rabi frequency required for quantum phase transition, and dramatically enhance the superradiant emission by fast modulating the Hamiltonian. Our work paves a way to experimental explorations of quantum phase transitions in solid state systems.

Solvable multistate model of Landau-Zener transitions in cavity QED

DOE PAGES

Sinitsyn, Nikolai; Li, Fuxiang

2016-06-29

We consider the model of a single optical cavity mode interacting with two-level systems (spins) driven by a linearly time-dependent field. When this field passes through values at which spin energy level splittings become comparable to spin coupling to the optical mode, a cascade of Landau-Zener (LZ) transitions leads to co-flips of spins in exchange for photons of the cavity. We derive exact transition probabilities between different diabatic states induced by such a sweep of the field.

Free-energy landscape of ion-channel voltage-sensor–domain activation

PubMed Central

Delemotte, Lucie; Kasimova, Marina A.; Klein, Michael L.; Tarek, Mounir; Carnevale, Vincenzo

2015-01-01

Voltage sensor domains (VSDs) are membrane-bound protein modules that confer voltage sensitivity to membrane proteins. VSDs sense changes in the transmembrane voltage and convert the electrical signal into a conformational change called activation. Activation involves a reorganization of the membrane protein charges that is detected experimentally as transient currents. These so-called gating currents have been investigated extensively within the theoretical framework of so-called discrete-state Markov models (DMMs), whereby activation is conceptualized as a series of transitions across a discrete set of states. Historically, the interpretation of DMM transition rates in terms of transition state theory has been instrumental in shaping our view of the activation process, whose free-energy profile is currently envisioned as composed of a few local minima separated by steep barriers. Here we use atomistic level modeling and well-tempered metadynamics to calculate the configurational free energy along a single transition from first principles. We show that this transition is intrinsically multidimensional and described by a rough free-energy landscape. Remarkably, a coarse-grained description of the system, based on the use of the gating charge as reaction coordinate, reveals a smooth profile with a single barrier, consistent with phenomenological models. Our results bridge the gap between microscopic and macroscopic descriptions of activation dynamics and show that choosing the gating charge as reaction coordinate masks the topological complexity of the network of microstates participating in the transition. Importantly, full characterization of the latter is a prerequisite to rationalize modulation of this process by lipids, toxins, drugs, and genetic mutations. PMID:25535341

Free-energy landscape of ion-channel voltage-sensor-domain activation.

PubMed

Delemotte, Lucie; Kasimova, Marina A; Klein, Michael L; Tarek, Mounir; Carnevale, Vincenzo

2015-01-06

Voltage sensor domains (VSDs) are membrane-bound protein modules that confer voltage sensitivity to membrane proteins. VSDs sense changes in the transmembrane voltage and convert the electrical signal into a conformational change called activation. Activation involves a reorganization of the membrane protein charges that is detected experimentally as transient currents. These so-called gating currents have been investigated extensively within the theoretical framework of so-called discrete-state Markov models (DMMs), whereby activation is conceptualized as a series of transitions across a discrete set of states. Historically, the interpretation of DMM transition rates in terms of transition state theory has been instrumental in shaping our view of the activation process, whose free-energy profile is currently envisioned as composed of a few local minima separated by steep barriers. Here we use atomistic level modeling and well-tempered metadynamics to calculate the configurational free energy along a single transition from first principles. We show that this transition is intrinsically multidimensional and described by a rough free-energy landscape. Remarkably, a coarse-grained description of the system, based on the use of the gating charge as reaction coordinate, reveals a smooth profile with a single barrier, consistent with phenomenological models. Our results bridge the gap between microscopic and macroscopic descriptions of activation dynamics and show that choosing the gating charge as reaction coordinate masks the topological complexity of the network of microstates participating in the transition. Importantly, full characterization of the latter is a prerequisite to rationalize modulation of this process by lipids, toxins, drugs, and genetic mutations.

Affective State Level Recognition in Naturalistic Facial and Vocal Expressions.

PubMed

Meng, Hongying; Bianchi-Berthouze, Nadia

2014-03-01

Naturalistic affective expressions change at a rate much slower than the typical rate at which video or audio is recorded. This increases the probability that consecutive recorded instants of expressions represent the same affective content. In this paper, we exploit such a relationship to improve the recognition performance of continuous naturalistic affective expressions. Using datasets of naturalistic affective expressions (AVEC 2011 audio and video dataset, PAINFUL video dataset) continuously labeled over time and over different dimensions, we analyze the transitions between levels of those dimensions (e.g., transitions in pain intensity level). We use an information theory approach to show that the transitions occur very slowly and hence suggest modeling them as first-order Markov models. The dimension levels are considered to be the hidden states in the Hidden Markov Model (HMM) framework. Their discrete transition and emission matrices are trained by using the labels provided with the training set. The recognition problem is converted into a best path-finding problem to obtain the best hidden states sequence in HMMs. This is a key difference from previous use of HMMs as classifiers. Modeling of the transitions between dimension levels is integrated in a multistage approach, where the first level performs a mapping between the affective expression features and a soft decision value (e.g., an affective dimension level), and further classification stages are modeled as HMMs that refine that mapping by taking into account the temporal relationships between the output decision labels. The experimental results for each of the unimodal datasets show overall performance to be significantly above that of a standard classification system that does not take into account temporal relationships. In particular, the results on the AVEC 2011 audio dataset outperform all other systems presented at the international competition.

The origin of life is a spatially localized stochastic transition

PubMed Central

2012-01-01

Background Life depends on biopolymer sequences as catalysts and as genetic material. A key step in the Origin of Life is the emergence of an autocatalytic system of biopolymers. Here we study computational models that address the way a living autocatalytic system could have emerged from a non-living chemical system, as envisaged in the RNA World hypothesis. Results We consider (i) a chemical reaction system describing RNA polymerization, and (ii) a simple model of catalytic replicators that we call the Two’s Company model. Both systems have two stable states: a non-living state, characterized by a slow spontaneous rate of RNA synthesis, and a living state, characterized by rapid autocatalytic RNA synthesis. The origin of life is a transition between these two stable states. The transition is driven by stochastic concentration fluctuations involving relatively small numbers of molecules in a localized region of space. These models are simulated on a two-dimensional lattice in which reactions occur locally on single sites and diffusion occurs by hopping of molecules to neighbouring sites. Conclusions If diffusion is very rapid, the system is well-mixed. The transition to life becomes increasingly difficult as the lattice size is increased because the concentration fluctuations that drive the transition become relatively smaller when larger numbers of molecules are involved. In contrast, when diffusion occurs at a finite rate, concentration fluctuations are local. The transition to life occurs in one local region and then spreads across the rest of the surface. The transition becomes easier with larger lattice sizes because there are more independent regions in which it could occur. The key observations that apply to our models and to the real world are that the origin of life is a rare stochastic event that is localized in one region of space due to the limited rate of diffusion of the molecules involved and that the subsequent spread across the surface is deterministic. It is likely that the time required for the deterministic spread is much shorter than the waiting time for the origin, in which case life evolves only once on a planet, and then rapidly occupies the whole surface. Reviewers Reviewed by Omer Markovitch (nominated by Doron Lancet), Claus Wilke, and Nobuto Takeuchi (nominated by Eugene Koonin). PMID:23176307

Characterization of Nonlinear Rate Dependent Response of Shape Memory Polymers

NASA Technical Reports Server (NTRS)

Volk, Brent; Lagoudas, Dimitris C.; Chen, Yi-Chao; Whitley, Karen S.

2007-01-01

Shape Memory Polymers (SMPs) are a class of polymers, which can undergo deformation in a flexible state at elevated temperatures, and when cooled below the glass transition temperature, while retaining their deformed shape, will enter and remain in a rigid state. Upon heating above the glass transition temperature, the shape memory polymer will return to its original, unaltered shape. SMPs have been reported to recover strains of over 400%. It is important to understand the stress and strain recovery behavior of SMPs to better develop constitutive models which predict material behavior. Initial modeling efforts did not account for large deformations beyond 25% strain. However, a model under current development is capable of describing large deformations of the material. This model considers the coexisting active (rubber) and frozen (glass) phases of the polymer, as well as the transitions between the material phases. The constitutive equations at the continuum level are established with internal state variables to describe the microstructural changes associated with the phase transitions. For small deformations, the model reduces to a linear model that agrees with those reported in the literature. Thermomechanical characterization is necessary for the development, calibration, and validation of a constitutive model. The experimental data reported in this paper will assist in model development by providing a better understanding of the stress and strain recovery behavior of the material. This paper presents the testing techniques used to characterize the thermomechanical material properties of a shape memory polymer (SMP) and also presents the resulting data. An innovative visual-photographic apparatus, known as a Vision Image Correlation (VIC) system was used to measure the strain. The details of this technique will also be presented in this paper. A series of tensile tests were performed on specimens such that strain levels of 10, 25, 50, and 100% were applied to the material while it was above its glass transition temperature. After deforming the material to a specified applied strain, the material was then cooled to below the glass transition temperature (Tg) while retaining the deformed shape. Finally, the specimen was heated again to above the transition temperature, and the resulting shape recovery profile was measured. Results show that strain recovery occurs at a nonlinear rate with respect to time. Results also indicate that the ratio of recoverable strain/applied strain increases as the applied strain increases.

Engineered Bi-Histidine Metal Chelation Sites Map the Structure of the Mechanical Unfolding Transition State of an Elastomeric Protein Domain GB1

PubMed Central

Shen, Tao; Cao, Yi; Zhuang, Shulin; Li, Hongbin

2012-01-01

Determining the structure of the transition state is critical for elucidating the mechanism behind how proteins fold and unfold. Due to its high free energy, however, the transition state generally cannot be trapped and studied directly using traditional structural biology methods. Thus, characterizing the structure of the transition state that occurs as proteins fold and unfold remains a major challenge. Here, we report a novel (to our knowledge) method that uses engineered bi-histidine (bi-His) metal-binding sites to directly map the structure of the mechanical unfolding transition state of proteins. This method is adapted from the traditional ψ-value analysis, which uses engineered bi-His metal chelation sites to probe chemical (un)folding transition-state structure. The ϕM2+U-value is defined as ΔΔG‡-N/ΔΔGU-N, which is the energetic effects of metal chelation by the bi-His site on the unfolding energy barrier (ΔG‡-N) relative to its thermodynamic stability (ΔGU-N) and can be used to obtain information about the transition state in the mutational site. As a proof of principle, we used the small protein GB1 as a model system and set out to map its mechanical unfolding transition-state structure. Using single-molecule atomic force microscopy and spectrofluorimetry, we directly quantified the effect of divalent metal ion binding on the mechanical unfolding free energy and thermodynamic stability of GB1, which allowed us to quantify ϕM2+U-values for different sites in GB1. Our results enabled us to map the structure of the mechanical unfolding transition state of GB1. Within GB1’s mechanical unfolding transition state, the interface between force-bearing β-strands 1 and 4 is largely disrupted, and the first β-hairpin is partially disordered while the second β-hairpin and the α-helix remain structured. Our results demonstrate the unique application of ψ-value analysis in elucidating the structure of the transition state that occurs during the mechanical unfolding process, offering a potentially powerful new method for investigating the design of novel elastomeric proteins. PMID:22947942

Engineered bi-histidine metal chelation sites map the structure of the mechanical unfolding transition state of an elastomeric protein domain GB1.

PubMed

Shen, Tao; Cao, Yi; Zhuang, Shulin; Li, Hongbin

2012-08-22

Determining the structure of the transition state is critical for elucidating the mechanism behind how proteins fold and unfold. Due to its high free energy, however, the transition state generally cannot be trapped and studied directly using traditional structural biology methods. Thus, characterizing the structure of the transition state that occurs as proteins fold and unfold remains a major challenge. Here, we report a novel (to our knowledge) method that uses engineered bi-histidine (bi-His) metal-binding sites to directly map the structure of the mechanical unfolding transition state of proteins. This method is adapted from the traditional ψ-value analysis, which uses engineered bi-His metal chelation sites to probe chemical (un)folding transition-state structure. The φ(M2+)(U)-value is defined as ΔΔG(‡-N)/ΔΔG(U-N), which is the energetic effects of metal chelation by the bi-His site on the unfolding energy barrier (ΔG(‡-N)) relative to its thermodynamic stability (ΔG(U-N)) and can be used to obtain information about the transition state in the mutational site. As a proof of principle, we used the small protein GB1 as a model system and set out to map its mechanical unfolding transition-state structure. Using single-molecule atomic force microscopy and spectrofluorimetry, we directly quantified the effect of divalent metal ion binding on the mechanical unfolding free energy and thermodynamic stability of GB1, which allowed us to quantify φ(M2+)(U)-values for different sites in GB1. Our results enabled us to map the structure of the mechanical unfolding transition state of GB1. Within GB1's mechanical unfolding transition state, the interface between force-bearing β-strands 1 and 4 is largely disrupted, and the first β-hairpin is partially disordered while the second β-hairpin and the α-helix remain structured. Our results demonstrate the unique application of ψ-value analysis in elucidating the structure of the transition state that occurs during the mechanical unfolding process, offering a potentially powerful new method for investigating the design of novel elastomeric proteins. Copyright © 2012 Biophysical Society. Published by Elsevier Inc. All rights reserved.

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

Sinitsyn, Nikolai A.

In this paper, I identify a nontrivial four-state Landau-Zener model for which transition probabilities between any pair of diabatic states can be determined analytically and exactly. The model describes an experimentally accessible system of two interacting qubits, such as a localized state in a Dirac material with both valley and spin degrees of freedom or a singly charged quantum dot (QD) molecule with spin orbit coupling. Application of the linearly time-dependent magnetic field induces a sequence of quantum level crossings with possibility of interference of different trajectories in a semiclassical picture. I argue that this system satisfies the criteria ofmore » integrability in the multistate Landau-Zener theory, which allows one to derive explicit exact analytical expressions for the transition probability matrix. Finally, I also argue that this model is likely a special case of a larger class of solvable systems, and present a six-state generalization as an example.« less

Geometric structure and information change in phase transitions

NASA Astrophysics Data System (ADS)

Kim, Eun-jin; Hollerbach, Rainer

2017-06-01

We propose a toy model for a cyclic order-disorder transition and introduce a geometric methodology to understand stochastic processes involved in transitions. Specifically, our model consists of a pair of forward and backward processes (FPs and BPs) for the emergence and disappearance of a structure in a stochastic environment. We calculate time-dependent probability density functions (PDFs) and the information length L , which is the total number of different states that a system undergoes during the transition. Time-dependent PDFs during transient relaxation exhibit strikingly different behavior in FPs and BPs. In particular, FPs driven by instability undergo the broadening of the PDF with a large increase in fluctuations before the transition to the ordered state accompanied by narrowing the PDF width. During this stage, we identify an interesting geodesic solution accompanied by the self-regulation between the growth and nonlinear damping where the time scale τ of information change is constant in time, independent of the strength of the stochastic noise. In comparison, BPs are mainly driven by the macroscopic motion due to the movement of the PDF peak. The total information length L between initial and final states is much larger in BPs than in FPs, increasing linearly with the deviation γ of a control parameter from the critical state in BPs while increasing logarithmically with γ in FPs. L scales as |lnD | and D-1 /2 in FPs and BPs, respectively, where D measures the strength of the stochastic forcing. These differing scalings with γ and D suggest a great utility of L in capturing different underlying processes, specifically, diffusion vs advection in phase transition by geometry. We discuss physical origins of these scalings and comment on implications of our results for bistable systems undergoing repeated order-disorder transitions (e.g., fitness).

Geometric structure and information change in phase transitions.

PubMed

Kim, Eun-Jin; Hollerbach, Rainer

2017-06-01

We propose a toy model for a cyclic order-disorder transition and introduce a geometric methodology to understand stochastic processes involved in transitions. Specifically, our model consists of a pair of forward and backward processes (FPs and BPs) for the emergence and disappearance of a structure in a stochastic environment. We calculate time-dependent probability density functions (PDFs) and the information length L, which is the total number of different states that a system undergoes during the transition. Time-dependent PDFs during transient relaxation exhibit strikingly different behavior in FPs and BPs. In particular, FPs driven by instability undergo the broadening of the PDF with a large increase in fluctuations before the transition to the ordered state accompanied by narrowing the PDF width. During this stage, we identify an interesting geodesic solution accompanied by the self-regulation between the growth and nonlinear damping where the time scale τ of information change is constant in time, independent of the strength of the stochastic noise. In comparison, BPs are mainly driven by the macroscopic motion due to the movement of the PDF peak. The total information length L between initial and final states is much larger in BPs than in FPs, increasing linearly with the deviation γ of a control parameter from the critical state in BPs while increasing logarithmically with γ in FPs. L scales as |lnD| and D^{-1/2} in FPs and BPs, respectively, where D measures the strength of the stochastic forcing. These differing scalings with γ and D suggest a great utility of L in capturing different underlying processes, specifically, diffusion vs advection in phase transition by geometry. We discuss physical origins of these scalings and comment on implications of our results for bistable systems undergoing repeated order-disorder transitions (e.g., fitness).

Specificity in transition state binding: the Pauling model revisited.

PubMed

Amyes, Tina L; Richard, John P

2013-03-26

Linus Pauling proposed that the large rate accelerations for enzymes are caused by the high specificity of the protein catalyst for binding the reaction transition state. The observation that stable analogues of the transition states for enzymatic reactions often act as tight-binding inhibitors provided early support for this simple and elegant proposal. We review experimental results that support the proposal that Pauling's model provides a satisfactory explanation for the rate accelerations for many heterolytic enzymatic reactions through high-energy reaction intermediates, such as proton transfer and decarboxylation. Specificity in transition state binding is obtained when the total intrinsic binding energy of the substrate is significantly larger than the binding energy observed at the Michaelis complex. The results of recent studies that aimed to characterize the specificity in binding of the enolate oxygen at the transition state for the 1,3-isomerization reaction catalyzed by ketosteroid isomerase are reviewed. Interactions between pig heart succinyl-coenzyme A:3-oxoacid coenzyme A transferase (SCOT) and the nonreacting portions of coenzyme A (CoA) are responsible for a rate increase of 3 × 10(12)-fold, which is close to the estimated total 5 × 10(13)-fold enzymatic rate acceleration. Studies that partition the interactions between SCOT and CoA into their contributing parts are reviewed. Interactions of the protein with the substrate phosphodianion group provide an ~12 kcal/mol stabilization of the transition state for the reactions catalyzed by triosephosphate isomerase, orotidine 5'-monophosphate decarboxylase, and α-glycerol phosphate dehydrogenase. The interactions of these enzymes with the substrate piece phosphite dianion provide a 6-8 kcal/mol stabilization of the transition state for reaction of the appropriate truncated substrate. Enzyme activation by phosphite dianion reflects the higher dianion affinity for binding to the enzyme-transition state complex compared with that of the free enzyme. Evidence is presented that supports a model in which the binding energy of the phosphite dianion piece, or the phosphodianion group of the whole substrate, is utilized to drive an enzyme conformational change from an inactive open form E(O) to an active closed form E(C), by closure of a phosphodianion gripper loop. Members of the enolase and haloalkanoic acid dehalogenase superfamilies use variable capping domains to interact with nonreacting portions of the substrate and sequester the substrate from interaction with bulk solvent. Interactions of this capping domain with the phenyl group of mandelate have been shown to activate mandelate racemase for catalysis of deprotonation of α-carbonyl carbon. We propose that an important function of these capping domains is to utilize the binding interactions with nonreacting portions of the substrate to activate the enzyme for catalysis.

Specificity in Transition State Binding: The Pauling Model Revisited

PubMed Central

Amyes, Tina L.; Richard, John P.

2013-01-01

Linus Pauling proposed that the large rate accelerations for enzymes are due to the high specificity of the protein catalyst for binding the reaction transition state. The observation that stable analogs of the transition states for enzymatic reactions often act as tight-binding binding inhibitors provided early support for this simple and elegant proposal. We review experimental results which support the proposal that Pauling’s model provides a satisfactory explanation for the rate accelerations for many heterolytic enzymatic reactions through high energy reaction intermediates, such as proton transfer and decarboxylation. Specificity in transition state binding is obtained when the total intrinsic binding energy of the substrate is significantly larger than the binding energy observed at the Michaelis complex. The results of recent studies to characterize the specificity in binding of the enolate oxygen at the transition state for the 1,3-isomerization reaction catalyzed by ketosteroid isomerase are reviewed. Interactions between pig heart succinyl-CoA:3-oxoacid coenzyme A transferase (SCOT) and the nonreacting portions of CoA are responsible for a rate increase of 3 × 1012-fold, which is close to the estimated total 5 × 1013-fold enzymatic rate acceleration. Studies that partition the interactions between SCOT and CoA into their contributing parts are reviewed. Interactions of the protein with the substrate phosphodianion group provide a ca. 12 kcal/mol stabilization of the transition state for the reactions catalyzed by triosephosphate isomerase, orotidine 5′-monophosphate decarboxylase and α-glycerol phosphate dehydrogenase. The interactions of these enzymes with the substrate piece phosphite dianion provide a 6 – 8 kcal/mol stabilization of the transition state for reaction of the appropriate truncated substrate. Enzyme activation by phosphite dianion reflects the higher dianion affinity for binding to the enzyme-transition state complex compared with the free enzyme. Evidence is presented that supports a model in which the binding energy of the phosphite dianion piece, or the phosphodianion group of the whole substrate, is utilized to drive an enzyme conformational change from an inactive open form EO to an active closed form EC, by closure of a phosphodianion gripper loop. Members of the enolase and haloalkanoic acid dehalogenase superfamilies use variable capping domains to interact with nonreacting portions of the substrate and sequester the substrate from interaction with bulk solvent. Interactions of this capping domain with the phenyl group of mandelate have been shown to activate mandelate racemase for catalysis of deprotonation of α-carbonyl carbon. We propose that an important function of these capping domains is to utilize the binding interactions with nonreacting portions of the substrate to activate the enzyme for catalysis. PMID:23327224

Connecting the Kuramoto Model and the Chimera State

NASA Astrophysics Data System (ADS)

Kotwal, Tejas; Jiang, Xin; Abrams, Daniel M.

2017-12-01

Since its discovery in 2002, the chimera state has frequently been described as a counterintuitive, puzzling phenomenon. The Kuramoto model, in contrast, has become a celebrated paradigm useful for understanding a range of phenomena related to phase transitions, synchronization, and network effects. Here we show that the chimera state can be understood as emerging naturally through a symmetry-breaking bifurcation from the Kuramoto model's partially synchronized state. Our analysis sheds light on recent observations of chimera states in laser arrays, chemical oscillators, and mechanical pendula.

Theoretical Study of Energy Levels and Transition Probabilities of Boron Atom

NASA Astrophysics Data System (ADS)

Tian Yi, Zhang; Neng Wu, Zheng

2009-08-01

Full Text PDF Though the electrons configuration for boron atom is simple and boron atom has long been of interest for many researchers, the theoretical studies for properties of BI are not systematic, there are only few results reported on energy levels of high excited states of boron, and transition measurements are generally restricted to transitions involving ground states and low excited states without considering fine structure effects, provided only multiplet results, values for transitions between high excited states are seldom performed. In this article, by using the scheme of the weakest bound electron potential model theory calculations for energy levels of five series are performed and with the same method we give the transition probabilities between excited states with considering fine structure effects. The comprehensive set of calculations attempted in this paper could be of some value to workers in the field because of the lack of published calculations for the BI systems. The perturbations coming from foreign perturbers are taken into account in studying the energy levels. Good agreement between our results and the accepted values taken from NIST has been obtained. We also reported some values of energy levels and transition probabilities not existing on the NIST data bases.

Critical behavior of the extended Hubbard model with bond dimerization

NASA Astrophysics Data System (ADS)

Ejima, Satoshi; Lange, Florian; Essler, Fabian H. L.; Fehske, Holger

2018-05-01

Exploiting the matrix-product-state based density-matrix renormalization group (DMRG) technique we study the one-dimensional extended (U-V) Hubbard model with explicit bond dimerization in the half-filled band sector. In particular we investigate the nature of the quantum phase transition, taking place with growing ratio V / U between the symmetry-protected-topological and charge-density-wave insulating states. The (weak-coupling) critical line of continuous Ising transitions with central charge c = 1 / 2 terminates at a tricritical point belonging to the universality class of the dilute Ising model with c = 7 / 10 . We demonstrate that our DMRG data perfectly match with (tricritical) Ising exponents, e.g., for the order parameter β = 1 / 8 (1/24) and correlation length ν = 1 (5/9). Beyond the tricritical Ising point, in the strong-coupling regime, the quantum phase transition becomes first order.

A stochastic Markov chain model to describe lung cancer growth and metastasis.

PubMed

Newton, Paul K; Mason, Jeremy; Bethel, Kelly; Bazhenova, Lyudmila A; Nieva, Jorge; Kuhn, Peter

2012-01-01

A stochastic Markov chain model for metastatic progression is developed for primary lung cancer based on a network construction of metastatic sites with dynamics modeled as an ensemble of random walkers on the network. We calculate a transition matrix, with entries (transition probabilities) interpreted as random variables, and use it to construct a circular bi-directional network of primary and metastatic locations based on postmortem tissue analysis of 3827 autopsies on untreated patients documenting all primary tumor locations and metastatic sites from this population. The resulting 50 potential metastatic sites are connected by directed edges with distributed weightings, where the site connections and weightings are obtained by calculating the entries of an ensemble of transition matrices so that the steady-state distribution obtained from the long-time limit of the Markov chain dynamical system corresponds to the ensemble metastatic distribution obtained from the autopsy data set. We condition our search for a transition matrix on an initial distribution of metastatic tumors obtained from the data set. Through an iterative numerical search procedure, we adjust the entries of a sequence of approximations until a transition matrix with the correct steady-state is found (up to a numerical threshold). Since this constrained linear optimization problem is underdetermined, we characterize the statistical variance of the ensemble of transition matrices calculated using the means and variances of their singular value distributions as a diagnostic tool. We interpret the ensemble averaged transition probabilities as (approximately) normally distributed random variables. The model allows us to simulate and quantify disease progression pathways and timescales of progression from the lung position to other sites and we highlight several key findings based on the model.

Resource pulses and mammalian dynamics: conceptual models for hummock grasslands and other Australian desert habitats.

PubMed

Letnic, M; Dickman, C R

2010-08-01

Resources are produced in pulses in many terrestrial environments, and have important effects on the population dynamics and assemblage structure of animals that consume them. Resource-pulsing is particularly dramatic in Australian desert environments owing to marked spatial and temporal variability in rainfall, and thus primary productivity. Here, we first review how Australia's desert mammals respond to fluctuations in resource production, and evaluate the merits of three currently accepted models (the ecological refuge, predator refuge and fire-mosaic models) as explanations of the observed dynamics. We then integrate elements of these models into a novel state-and-transition model and apply it to well-studied small mammal assemblages that inhabit the vast hummock grassland, or spinifex, landscapes of the continental inland. The model has four states that are defined by differences in species composition and abundance, and eight transitions or processes that prompt shifts from one state to another. Using this model as a template, we construct three further models to explain mammalian dynamics in cracking soil habitats of the Lake Eyre Basin, gibber plains of the Channel Country, and the chenopod shrublands of arid southern Australia. As non-equilibrium concepts that recognise the strongly intermittent nature of resource pulsing in arid Australia, state-and-transition models provide useful descriptors of both spatial and temporal patterns in mammal assemblages. The models should help managers to identify when and where to implement interventions to conserve native mammals, such as control burns, reduced grazing or predator management. The models also should improve understanding of the potential effects of future climate change on mammal assemblages in arid environments in general. We conclude by proposing several tests that could be used to refine the models and guide further research.

Structural transitions in vortex systems with anisotropic interactions

DOE PAGES

Olszewski, Maciej W.; Eskildsen, M. R.; Reichhardt, Charles; ...

2017-12-29

We introduce a model of vortices in type-II superconductors with a four-fold anisotropy in the vortex–vortex interaction potential. Using numerical simulations we show that the vortex lattice undergoes structural transitions as the anisotropy is increased, with a triangular lattice at low anisotropy, a rhombic intermediate state, and a square lattice for high anisotropy. In some cases we observe a multi-q state consisting of an Archimedean tiling that combines square and triangular local ordering. At very high anisotropy, domains of vortex chain states appear. We discuss how this model can be generalized to higher order anisotropy as well as its applicabilitymore » to other particle-based systems with anisotropic particle–particle interactions.« less

Spirometric variability in smokers: transitions in COPD diagnosis in a five-year longitudinal study.

PubMed

Sood, Akshay; Petersen, Hans; Qualls, Clifford; Meek, Paula M; Vazquez-Guillamet, Rodrigo; Celli, Bartolome R; Tesfaigzi, Yohannes

2016-11-10

Spirometrically-defined chronic obstructive pulmonary disease (COPD) is considered progressive but its natural history is inadequately studied. We hypothesized that spirometrically-defined COPD states could undergo beneficial transitions. Participants in the Lovelace Smokers' Cohort (n = 1553), primarily women, were longitudinally studied over 5 years. Spirometric states included normal postbronchodilator spirometry, COPD Stage I, Unclassified state, and COPD Stage II+, as defined by GOLD guidelines. Beneficial transitions included either a decrease in disease severity, including resolution of spirometric abnormality, or maintenance of non-diseased state. 'All smokers' (n = 1553) and subgroups with normal and abnormal spirometry at baseline (n = 956 and 597 respectively) were separately analyzed. Markov-like model of transition probabilities over an average follow-up period of 5 years were calculated. Among 'all smokers', COPD Stage I, Unclassified, and COPD Stage II+ states were associated with probabilities of 16, 39, and 22 % respectively for beneficial transitions, and of 16, 35, and 4 % respectively for resolution. Beneficial transitions were more common for new-onset disease than for pre-existing disease (p < 0.001). Beneficial transitions were less common among older smokers, men, or those with bronchial hyperresponsiveness but more common among Hispanics and smokers with excess weight. This observational study of ever smokers, shows that spirometrically-defined COPD states, may not be uniformly progressive and can improve or resolve over time. The implication of these findings is that the spirometric diagnosis of COPD can be unstable. Furthermore, COPD may have a pre-disease state when interventions might help reverse or change its natural history. NA.

Regional models of cooperation handbook

DOT National Transportation Integrated Search

2016-12-28

This handbook describes notable practices used by State departments of transportation (State DOTs), metropolitan planning organizations (MPOs), transit agencies, and other transportation planning partners which work across jurisdictions or traditiona...

Collective dynamics in heterogeneous networks of neuronal cellular automata

NASA Astrophysics Data System (ADS)

Manchanda, Kaustubh; Bose, Amitabha; Ramaswamy, Ramakrishna

2017-12-01

We examine the collective dynamics of heterogeneous random networks of model neuronal cellular automata. Each automaton has b active states, a single silent state and r - b - 1 refractory states, and can show 'spiking' or 'bursting' behavior, depending on the values of b. We show that phase transitions that occur in the dynamical activity can be related to phase transitions in the structure of Erdõs-Rényi graphs as a function of edge probability. Different forms of heterogeneity allow distinct structural phase transitions to become relevant. We also show that the dynamics on the network can be described by a semi-annealed process and, as a result, can be related to the Boolean Lyapunov exponent.

The origin of nulls mode changes and timing noise in pulsars

NASA Astrophysics Data System (ADS)

Jones, P. B.

A solvable polar cap model obtained previously has normal states which may be associated with radio emission and null states. The solutions cannot be time-independent; the neutron star surface temperature T and mean surface nuclear charge Z are both functions of time. The normal and null states, and the transitions between them, form closed cycles in the T-Z plane. Normal-null transitions can occur inside a fraction of the area on the neutron star surface intersected by open magnetic flux lines. The fraction increases with pulsar period and becomes unity when the pulsar nears extinction. Frequency noise, mode changes, and pulse nulls have a common explanation in the transitions.

The origin of nulls, mode changes and timing noise in pulsars

NASA Astrophysics Data System (ADS)

Jones, P. B.

1982-09-01

A solvable polar cap model obtained previously has normal states which may be associated with radio emission, and null states. The solutions cannot be time-independent; the neutron star surface temperature T and mean surface nuclear charge Z are both functions of time. The normal and null states and the transitions between them, form closed cycles in the T-Z plane. Normal-null transitions can occur inside a fraction of the area of the neutron star surface intersected by open magnetic flux lines. The fraction increases with pulsar period and becomes unity when the pulsar nears extinction. Frequency noise, mode changes and pulse nulls have a common explanation in the transitions.

Transition in coupled replicas may not imply a finite-temperature ideal glass transition in glass-forming systems.

PubMed

Garrahan, Juan P

2014-03-01

A key open question in the glass transition field is whether a finite temperature thermodynamic transition to the glass state exists or not. Recent simulations of coupled replicas in atomistic models have found signatures of a static transition as a function of replica coupling. This can be viewed as evidence of an associated thermodynamic glass transition in the uncoupled system. We demonstrate here that a different interpretation is possible. We consider the triangular plaquette model, an interacting spin system which displays (East model-like) glassy dynamics in the absence of any static transition. We show that when two replicas are coupled, there is a curve of equilibrium phase transitions, between phases of small and large overlap, in the temperature-coupling plane (located on the self-dual line of an exact temperature-coupling duality of the system) which ends at a critical point. Crucially, in the limit of vanishing coupling the finite temperature transition disappears, and the uncoupled system is in the disordered phase at all temperatures. We discuss an interpretation of atomistic simulations in light of this result.

Manpower Modeling in the Airborne Community of the United States Army.

DTIC Science & Technology

1984-09-01

Inventories for CMIF 51 . . . 103 27. Authorizations and Inventories for CMF 54 . . . 104 28. Authorizations and Inventories for CMF 55 . 105 29...81 ........ 144 C.24 Transition Matrix for CMF 84 ......... 145 10 .. - C.25 Transition Matrix for CMiF 91 .... 145 C. 26 Transition matrix for CNF...150 C. 30 Transition Matrix for CM1F 97 ....... . 151 C. 31 Transition Matrix for CMiF 98 .. . .152 I. I._IRODUCTION In the last two decades, with the

Transitions in Prognostic Awareness Among Terminally Ill Cancer Patients in Their Last 6 Months of Life Examined by Multi-State Markov Modeling.

PubMed

Hsiu Chen, Chen; Wen, Fur-Hsing; Hou, Ming-Mo; Hsieh, Chia-Hsun; Chou, Wen-Chi; Chen, Jen-Shi; Chang, Wen-Cheng; Tang, Siew Tzuh

2017-09-01

Developing accurate prognostic awareness, a cornerstone of preference-based end-of-life (EOL) care decision-making, is a dynamic process involving more prognostic-awareness states than knowing or not knowing. Understanding the transition probabilities and time spent in each prognostic-awareness state can help clinicians identify trigger points for facilitating transitions toward accurate prognostic awareness. We examined transition probabilities in distinct prognostic-awareness states between consecutive time points in 247 cancer patients' last 6 months and estimated the time spent in each state. Prognostic awareness was categorized into four states: (a) unknown and not wanting to know, state 1; (b) unknown but wanting to know, state 2; (c) inaccurate awareness, state 3; and (d) accurate awareness, state 4. Transitional probabilities were examined by multistate Markov modeling. Initially, 59.5% of patients had accurate prognostic awareness, whereas the probabilities of being in states 1-3 were 8.1%, 17.4%, and 15.0%, respectively. Patients' prognostic awareness generally remained unchanged (probabilities of remaining in the same state: 45.5%-92.9%). If prognostic awareness changed, it tended to shift toward higher prognostic-awareness states (probabilities of shifting to state 4 were 23.2%-36.6% for patients initially in states 1-3, followed by probabilities of shifting to state 3 for those in states 1 and 2 [9.8%-10.1%]). Patients were estimated to spend 1.29, 0.42, 0.68, and 3.61 months in states 1-4, respectively, in their last 6 months. Terminally ill cancer patients' prognostic awareness generally remained unchanged, with a tendency to become more aware of their prognosis. Health care professionals should facilitate patients' transitions toward accurate prognostic awareness in a timely manner to promote preference-based EOL decisions. Terminally ill Taiwanese cancer patients' prognostic awareness generally remained stable, with a tendency toward developing higher states of awareness. Health care professionals should appropriately assess patients' readiness for prognostic information and respect patients' reluctance to confront their poor prognosis if they are not ready to know, but sensitively coach them to cultivate their accurate prognostic awareness, provide desired and understandable prognostic information for those who are ready to know, and give direct and honest prognostic information to clarify any misunderstandings for those with inaccurate awareness, thus ensuring that they develop accurate and realistic prognostic knowledge in time to make end-of-life care decisions. © AlphaMed Press 2017.

Effect of particle size on the glass transition.

PubMed

Larsen, Ryan J; Zukoski, Charles F

2011-05-01

The glass transition temperature of a broad class of molecules is shown to depend on molecular size. This dependency results from the size dependence of the pair potential. A generalized equation of state is used to estimate how the volume fraction at the glass transition depends on the size of the molecule, for rigid molecule glass-formers. The model shows that at a given pressure and temperature there is a size-induced glass transition: For molecules larger than a critical size, the volume fraction required to support the effective pressure due to particle attractions is above that which characterizes the glassy state. This observation establishes the boundary between nanoparticles, which exist in liquid form only as dispersions in low molecular weight solvents and large molecules which form liquids that have viscosities below those characterized by the glassy state.

Modeling lake trophic state: a random forest approach

EPA Science Inventory

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

Singular unlocking transition in the Winfree model of coupled oscillators.

PubMed

Quinn, D Dane; Rand, Richard H; Strogatz, Steven H

2007-03-01

The Winfree model consists of a population of globally coupled phase oscillators with randomly distributed natural frequencies. As the coupling strength and the spread of natural frequencies are varied, the various stable states of the model can undergo bifurcations, nearly all of which have been characterized previously. The one exception is the unlocking transition, in which the frequency-locked state disappears abruptly as the spread of natural frequencies exceeds a critical width. Viewed as a function of the coupling strength, this critical width defines a bifurcation curve in parameter space. For the special case where the frequency distribution is uniform, earlier work had uncovered a puzzling singularity in this bifurcation curve. Here we seek to understand what causes the singularity. Using the Poincaré-Lindstedt method of perturbation theory, we analyze the locked state and its associated unlocking transition, first for an arbitrary distribution of natural frequencies, and then for discrete systems of N oscillators. We confirm that the bifurcation curve becomes singular for a continuum uniform distribution, yet find that it remains well behaved for any finite N , suggesting that the continuum limit is responsible for the singularity.

Mixed effect Poisson log-linear models for clinical and epidemiological sleep hypnogram data

PubMed Central

Swihart, Bruce J.; Caffo, Brian S.; Crainiceanu, Ciprian; Punjabi, Naresh M.

2013-01-01

Bayesian Poisson log-linear multilevel models scalable to epidemiological studies are proposed to investigate population variability in sleep state transition rates. Hierarchical random effects are used to account for pairings of subjects and repeated measures within those subjects, as comparing diseased to non-diseased subjects while minimizing bias is of importance. Essentially, non-parametric piecewise constant hazards are estimated and smoothed, allowing for time-varying covariates and segment of the night comparisons. The Bayesian Poisson regression is justified through a re-derivation of a classical algebraic likelihood equivalence of Poisson regression with a log(time) offset and survival regression assuming exponentially distributed survival times. Such re-derivation allows synthesis of two methods currently used to analyze sleep transition phenomena: stratified multi-state proportional hazards models and log-linear models with GEE for transition counts. An example data set from the Sleep Heart Health Study is analyzed. Supplementary material includes the analyzed data set as well as the code for a reproducible analysis. PMID:22241689

A School-to-Work Transition System for the United States. Workforce Skills Program.

ERIC Educational Resources Information Center

Tucker, Marc

The core features of the preindustrial model of school-to-work transition are needed now. An environment must be recreated in which young people see the vital connections among education, training, and work that were once so clear. The emerging consensus model has these features: combined formal schooling and structured on-the-job training leading…

Simultaneous modeling of habitat suitability, occupancy, and relative abundance: African elephants in Zimbabwe

USGS Publications Warehouse

Martin, Julien; Chamaille-Jammes, Simon; Nichols, James D.; Fritz, Herve; Hines, James E.; Fonnesbeck, Christopher J.; MacKenzie, Darryl I.; Bailey, Larissa L.

2010-01-01

The recent development of statistical models such as dynamic site occupancy models provides the opportunity to address fairly complex management and conservation problems with relatively simple models. However, surprisingly few empirical studies have simultaneously modeled habitat suitability and occupancy status of organisms over large landscapes for management purposes. Joint modeling of these components is particularly important in the context of management of wild populations, as it provides a more coherent framework to investigate the population dynamics of organisms in space and time for the application of management decision tools. We applied such an approach to the study of water hole use by African elephants in Hwange National Park, Zimbabwe. Here we show how such methodology may be implemented and derive estimates of annual transition probabilities among three dry-season states for water holes: (1) unsuitable state (dry water holes with no elephants); (2) suitable state (water hole with water) with low abundance of elephants; and (3) suitable state with high abundance of elephants. We found that annual rainfall and the number of neighboring water holes influenced the transition probabilities among these three states. Because of an increase in elephant densities in the park during the study period, we also found that transition probabilities from low abundance to high abundance states increased over time. The application of the joint habitat–occupancy models provides a coherent framework to examine how habitat suitability and factors that affect habitat suitability influence the distribution and abundance of organisms. We discuss how these simple models can further be used to apply structured decision-making tools in order to derive decisions that are optimal relative to specified management objectives. The modeling framework presented in this paper should be applicable to a wide range of existing data sets and should help to address important ecological, conservation, and management problems that deal with occupancy, relative abundance, and habitat suitability.

Variational Identification of Markovian Transition States

NASA Astrophysics Data System (ADS)

Martini, Linda; Kells, Adam; Covino, Roberto; Hummer, Gerhard; Buchete, Nicolae-Viorel; Rosta, Edina

2017-07-01

We present a method that enables the identification and analysis of conformational Markovian transition states from atomistic or coarse-grained molecular dynamics (MD) trajectories. Our algorithm is presented by using both analytical models and examples from MD simulations of the benchmark system helix-forming peptide Ala5 , and of larger, biomedically important systems: the 15-lipoxygenase-2 enzyme (15-LOX-2), the epidermal growth factor receptor (EGFR) protein, and the Mga2 fungal transcription factor. The analysis of 15-LOX-2 uses data generated exclusively from biased umbrella sampling simulations carried out at the hybrid ab initio density functional theory (DFT) quantum mechanics/molecular mechanics (QM/MM) level of theory. In all cases, our method automatically identifies the corresponding transition states and metastable conformations in a variationally optimal way, with the input of a set of relevant coordinates, by accurately reproducing the intrinsic slowest relaxation rate of each system. Our approach offers a general yet easy-to-implement analysis method that provides unique insight into the molecular mechanism and the rare but crucial (i.e., rate-limiting) transition states occurring along conformational transition paths in complex dynamical systems such as molecular trajectories.

Effects of Composite Pions on the Chiral Condensate within the PNJL Model at Finite Temperature

NASA Astrophysics Data System (ADS)

Blaschke, D.; Dubinin, A.; Ebert, D.; Friesen, A. V.

2018-05-01

We investigate the effect of composite pions on the behaviour of the chiral condensate at finite temperature within the Polyakov-loop improved NJL model. To this end we treat quark-antiquark correlations in the pion channel (bound states and scattering continuum) within a Beth-Uhlenbeck approach that uses medium-dependent phase shifts. A striking medium effect is the Mott transition which occurs when the binding energy vanishes and the discrete pion bound state merges the continuum. This transition is triggered by the lowering of the continuum edge due to the chiral restoration transition. This in turn also entails a modification of the Polyakov-loop so that the SU(3) center symmetry gets broken at finite temperature and dynamical quarks (and gluons) appear in the system, taking over the role of the dominant degrees of freedom from the pions. At low temperatures our model reproduces the chiral perturbation theory result for the chiral condensate while at high temperatures the PNJL model result is recovered. The new aspect of the current work is a consistent treatment of the chiral restoration transition region within the Beth-Uhlenbeck approach on the basis of mesonic phase shifts for the treatment of the correlations.

Testing the impact of morphological rate heterogeneity on ancestral state reconstruction of five floral traits in angiosperms.

PubMed

Reyes, Elisabeth; Nadot, Sophie; von Balthazar, Maria; Schönenberger, Jürg; Sauquet, Hervé

2018-06-21

Ancestral state reconstruction is an important tool to study morphological evolution and often involves estimating transition rates among character states. However, various factors, including taxonomic scale and sampling density, may impact transition rate estimation and indirectly also the probability of the state at a given node. Here, we test the influence of rate heterogeneity using maximum likelihood methods on five binary perianth characters, optimized on a phylogenetic tree of angiosperms including 1230 species sampled from all families. We compare the states reconstructed by an equal-rate (Mk1) and a two-rate model (Mk2) fitted either with a single set of rates for the whole tree or as a partitioned model, allowing for different rates on five partitions of the tree. We find strong signal for rate heterogeneity among the five subdivisions for all five characters, but little overall impact of the choice of model on reconstructed ancestral states, which indicates that most of our inferred ancestral states are the same whether heterogeneity is accounted for or not.

Bifurcation analysis and phase diagram of a spin-string model with buckled states.

PubMed

Ruiz-Garcia, M; Bonilla, L L; Prados, A

2017-12-01

We analyze a one-dimensional spin-string model, in which string oscillators are linearly coupled to their two nearest neighbors and to Ising spins representing internal degrees of freedom. String-spin coupling induces a long-range ferromagnetic interaction among spins that competes with a spin-spin antiferromagnetic coupling. As a consequence, the complex phase diagram of the system exhibits different flat rippled and buckled states, with first or second order transition lines between states. This complexity translates to the two-dimensional version of the model, whose numerical solution has been recently used to explain qualitatively the rippled to buckled transition observed in scanning tunneling microscopy experiments with suspended graphene sheets. Here we describe in detail the phase diagram of the simpler one-dimensional model and phase stability using bifurcation theory. This gives additional insight into the physical mechanisms underlying the different phases and the behavior observed in experiments.

Bifurcation analysis and phase diagram of a spin-string model with buckled states

NASA Astrophysics Data System (ADS)

Ruiz-Garcia, M.; Bonilla, L. L.; Prados, A.

2017-12-01

We analyze a one-dimensional spin-string model, in which string oscillators are linearly coupled to their two nearest neighbors and to Ising spins representing internal degrees of freedom. String-spin coupling induces a long-range ferromagnetic interaction among spins that competes with a spin-spin antiferromagnetic coupling. As a consequence, the complex phase diagram of the system exhibits different flat rippled and buckled states, with first or second order transition lines between states. This complexity translates to the two-dimensional version of the model, whose numerical solution has been recently used to explain qualitatively the rippled to buckled transition observed in scanning tunneling microscopy experiments with suspended graphene sheets. Here we describe in detail the phase diagram of the simpler one-dimensional model and phase stability using bifurcation theory. This gives additional insight into the physical mechanisms underlying the different phases and the behavior observed in experiments.

Metastability of the midgap level EL 2 in GaAs - Relationship with the As antisite defect

NASA Technical Reports Server (NTRS)

Skowronski, M.; Lagowski, J.; Gatos, H. C.

1985-01-01

It is found that the rate of the photoinduced transition of the GaAs midgap level EL 2 to its metastable state increases as its occupation increases. High-resolution optical spectra of this transition exhibit a sharp peak very similar to the no-phonon line of the intracenter absorption of the As antisite defect. These findings show that the transition to the metastable state is initiated from the ground state 1A1, and it is finalized via the excited state 1T2 of the neutral As antisite defect. They thus provide a new basis for the critical assessment of the EL 2 metastability models and further confirmation of the association of EL 2 with the isolated As antisite defect.

Transition probability spaces in loop quantum gravity

NASA Astrophysics Data System (ADS)

Guo, Xiao-Kan

2018-03-01

We study the (generalized) transition probability spaces, in the sense of Mielnik and Cantoni, for spacetime quantum states in loop quantum gravity. First, we show that loop quantum gravity admits the structures of transition probability spaces. This is exemplified by first checking such structures in covariant quantum mechanics and then identifying the transition probability spaces in spin foam models via a simplified version of general boundary formulation. The transition probability space thus defined gives a simple way to reconstruct the discrete analog of the Hilbert space of the canonical theory and the relevant quantum logical structures. Second, we show that the transition probability space and in particular the spin foam model are 2-categories. Then we discuss how to realize in spin foam models two proposals by Crane about the mathematical structures of quantum gravity, namely, the quantum topos and causal sites. We conclude that transition probability spaces provide us with an alternative framework to understand various foundational questions of loop quantum gravity.

Integrated Turbine-Based Combined Cycle Dynamic Simulation Model

NASA Technical Reports Server (NTRS)

Haid, Daniel A.; Gamble, Eric J.

2011-01-01

A Turbine-Based Combined Cycle (TBCC) dynamic simulation model has been developed to demonstrate all modes of operation, including mode transition, for a turbine-based combined cycle propulsion system. The High Mach Transient Engine Cycle Code (HiTECC) is a highly integrated tool comprised of modules for modeling each of the TBCC systems whose interactions and controllability affect the TBCC propulsion system thrust and operability during its modes of operation. By structuring the simulation modeling tools around the major TBCC functional modes of operation (Dry Turbojet, Afterburning Turbojet, Transition, and Dual Mode Scramjet) the TBCC mode transition and all necessary intermediate events over its entire mission may be developed, modeled, and validated. The reported work details the use of the completed model to simulate a TBCC propulsion system as it accelerates from Mach 2.5, through mode transition, to Mach 7. The completion of this model and its subsequent use to simulate TBCC mode transition significantly extends the state-of-the-art for all TBCC modes of operation by providing a numerical simulation of the systems, interactions, and transient responses affecting the ability of the propulsion system to transition from turbine-based to ramjet/scramjet-based propulsion while maintaining constant thrust.

The mechanism of the emergence of distinct overstretched DNA states

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

Zhu, You-Liang; Sun, Zhao-Yan, E-mail: zysun@ciac.ac.cn; Lu, Zhong-Yuan

Although multiple overstretched DNA states were identified in experiments, the mechanism of the emergence of distinct states is still unclear. Molecular dynamics simulation is an ideal tool to clarify the mechanism, but the force loading rates in stretching achieved by conventional all-atom DNA models are much faster, which essentially affect overstretching states. We employed a modified coarse-grained DNA model with an unprecedented low loading rate in simulations to study the overstretching transitions of end-opened double-stranded DNA. We observed two-strand peeling off for DNA with low stability and the S-DNA with high stability under tension. By introducing a melting-forbidden model whichmore » prevents base-pair breaking, we still observed the overstretching transition induced by the formation of S-DNA due to the change of dihedral angle. Hence, we confirmed that the competition between the two strain-softening manners, i.e., base-pair breaking and dihedral angle variation, results in the emergence of distinct overstretched DNA states.« less

Transition of multidiffusive states in a biased periodic potential

NASA Astrophysics Data System (ADS)

Zhang, Jia-Ming; Bao, Jing-Dong

2017-03-01

We study a frequency-dependent damping model of hyperdiffusion within the generalized Langevin equation. The model allows for the colored noise defined by its spectral density, assumed to be proportional to ωδ -1 at low frequencies with 0 <δ <1 (sub-Ohmic damping) or 1 <δ <2 (super-Ohmic damping), where the frequency-dependent damping is deduced from the noise by means of the fluctuation-dissipation theorem. It is shown that for super-Ohmic damping and certain parameters, the diffusive process of the particle in a titled periodic potential undergos sequentially four time regimes: thermalization, hyperdiffusion, collapse, and asymptotical restoration. For analyzing transition phenomenon of multidiffusive states, we demonstrate that the first exist time of the particle escaping from the locked state into the running state abides by an exponential distribution. The concept of an equivalent velocity trap is introduced in the present model; moreover, reformation of ballistic diffusive system is also considered as a marginal situation but does not exhibit the collapsed state of diffusion.

Saddle point localization of molecular wavefunctions.

PubMed

Mellau, Georg Ch; Kyuberis, Alexandra A; Polyansky, Oleg L; Zobov, Nikolai; Field, Robert W

2016-09-15

The quantum mechanical description of isomerization is based on bound eigenstates of the molecular potential energy surface. For the near-minimum regions there is a textbook-based relationship between the potential and eigenenergies. Here we show how the saddle point region that connects the two minima is encoded in the eigenstates of the model quartic potential and in the energy levels of the [H, C, N] potential energy surface. We model the spacing of the eigenenergies with the energy dependent classical oscillation frequency decreasing to zero at the saddle point. The eigenstates with the smallest spacing are localized at the saddle point. The analysis of the HCN ↔ HNC isomerization states shows that the eigenstates with small energy spacing relative to the effective (v1, v3, ℓ) bending potentials are highly localized in the bending coordinate at the transition state. These spectroscopically detectable states represent a chemical marker of the transition state in the eigenenergy spectrum. The method developed here provides a basis for modeling characteristic patterns in the eigenenergy spectrum of bound states.

Identification of the protein folding transition state from molecular dynamics trajectories

NASA Astrophysics Data System (ADS)

Muff, S.; Caflisch, A.

2009-03-01

The rate of protein folding is governed by the transition state so that a detailed characterization of its structure is essential for understanding the folding process. In vitro experiments have provided a coarse-grained description of the folding transition state ensemble (TSE) of small proteins. Atomistic details could be obtained by molecular dynamics (MD) simulations but it is not straightforward to extract the TSE directly from the MD trajectories, even for small peptides. Here, the structures in the TSE are isolated by the cut-based free-energy profile (cFEP) using the network whose nodes and links are configurations sampled by MD and direct transitions among them, respectively. The cFEP is a barrier-preserving projection that does not require arbitrarily chosen progress variables. First, a simple two-dimensional free-energy surface is used to illustrate the successful determination of the TSE by the cFEP approach and to explain the difficulty in defining boundary conditions of the Markov state model for an entropically stabilized free-energy minimum. The cFEP is then used to extract the TSE of a β-sheet peptide with a complex free-energy surface containing multiple basins and an entropic region. In contrast, Markov state models with boundary conditions defined by projected variables and conventional histogram-based free-energy profiles are not able to identify the TSE of the β-sheet peptide.

Detonation propagation in annular arcs of condensed phase explosives

NASA Astrophysics Data System (ADS)

Ioannou, Eleftherios; Schoch, Stefan; Nikiforakis, Nikolaos; Michael, Louisa

2017-11-01

We present a numerical study of detonation propagation in unconfined explosive charges shaped as an annular arc (rib). Steady detonation in a straight charge propagates at constant speed, but when it enters an annular section, it goes through a transition phase and eventually reaches a new steady state of constant angular velocity. This study examines the speed of the detonation wave along the annular charge during the transition phase and at steady state, as well as its dependence on the dimensions of the annulus. The system is modeled using a recently proposed diffuse-interface formulation which allows for the representation of a two-phase explosive and of an additional inert material. The explosive considered is the polymer-bonded TATB-based LX-17 and is modeled using two Jones-Wilkins-Lee (JWL) equations of state and the ignition and growth reaction rate law. Results show that steady state speeds are in good agreement with experiment. In the transition phase, the evolution of outer detonation speed deviates from the exponential bounded growth function suggested by previous studies. We propose a new description of the transition phase which consists of two regimes. The first regime is caused by local effects at the outer edge of the annulus and leads to a dependence of the outer detonation speed on the angular position along the arc. The second regime is induced by effects originating from the inner edge of the annular charge and leads to the deceleration of the outer detonation until steady state is reached. The study concludes with a parametric study where the dependence of the steady state and the transition phase on the dimensions of the annulus is investigated.

A Networks Approach to Modeling Enzymatic Reactions.

PubMed

Imhof, P

2016-01-01

Modeling enzymatic reactions is a demanding task due to the complexity of the system, the many degrees of freedom involved and the complex, chemical, and conformational transitions associated with the reaction. Consequently, enzymatic reactions are not determined by precisely one reaction pathway. Hence, it is beneficial to obtain a comprehensive picture of possible reaction paths and competing mechanisms. By combining individually generated intermediate states and chemical transition steps a network of such pathways can be constructed. Transition networks are a discretized representation of a potential energy landscape consisting of a multitude of reaction pathways connecting the end states of the reaction. The graph structure of the network allows an easy identification of the energetically most favorable pathways as well as a number of alternative routes. © 2016 Elsevier Inc. All rights reserved.

Characterizing Transitions Between Decadal States of the Tropical Pacific using State Space Reconstruction

NASA Astrophysics Data System (ADS)

Ramesh, N.; Cane, M. A.

2017-12-01

The complex coupled ocean-atmosphere system of the Tropical Pacific generates variability on timescales from intraseasonal to multidecadal. Pacific Decadal Variability (PDV) is among the key drivers of global climate, with effects on hydroclimate on several continents, marine ecosystems, and the rate of global mean surface temperature rise under anthropogenic greenhouse gas forcing. Predicting phase shifts in the PDV would therefore be highly useful. However, the small number of PDV phase shifts that have occurred in the observational record pose a substantial challenge to developing an understanding of the mechanisms that underlie decadal variability. In this study, we use a 100,000-year unforced simulation from an intermediate-complexity model of the Tropical Pacific region that has been shown to produce PDV comparable to that in the real world. We apply the Simplex Projection method to the NINO3 index from this model to reconstruct a shadow manifold that preserves the topology of the true attractor of this system. We find that the high- and low-variance phases of PDV emerge as a pair of regimes in a 3-dimensional state space, and that the transitions between decadal states lie in a highly predictable region of the attractor. We then use a random forest algorithm to develop a physical interpretation of the processes associated with these highly-predictable transitions. We find that transitions to low-variance states are most likely to occur approximately 2.5 years after an El Nino event, and that ocean-atmosphere variables in the southeastern Tropical Pacific play a crucial role in driving these transitions.

Integration of kinetic isotope effect analyses to elucidate ribonuclease mechanism.

PubMed

Harris, Michael E; Piccirilli, Joseph A; York, Darrin M

2015-11-01

The well-studied mechanism of ribonuclease A is believed to involve concerted general acid-base catalysis by two histidine residues, His12 and His119. The basic features of this mechanism are often cited to explain rate enhancement by both protein and RNA enzymes that catalyze RNA 2'-O-transphosphorylation. Recent kinetic isotope effect analyses and computational studies are providing a more chemically detailed description of the mechanism of RNase A and the rate limiting transition state. Overall, the results support an asynchronous mechanism for both solution and ribonuclease catalyzed reactions in which breakdown of a transient dianoinic phosphorane intermediate by 5'OP bond cleavage is rate limiting. Relative to non-enzymatic reactions catalyzed by specific base, a smaller KIE on the 5'O leaving group and a less negative βLG are observed for RNase A catalysis. Quantum mechanical calculations consistent with these data support a model in which electrostatic and H-bonding interactions with the non-bridging oxygens and proton transfer from His119 render departure of the 5'O less advanced and stabilize charge buildup in the transition state. Both experiment and computation indicate advanced 2'OP bond formation in the rate limiting transition state. However, this feature makes it difficult to resolve the chemical steps involved in 2'O activation. Thus, modeling the transition state for RNase A catalysis underscores those elements of its chemical mechanism that are well resolved, as well as highlighting those where ambiguity remains. This article is part of a Special Issue entitled: Enzyme Transition States from Theory and Experiment. Published by Elsevier B.V.

Markov chains for testing redundant software

NASA Technical Reports Server (NTRS)

White, Allan L.; Sjogren, Jon A.

1988-01-01

A preliminary design for a validation experiment has been developed that addresses several problems unique to assuring the extremely high quality of multiple-version programs in process-control software. The procedure uses Markov chains to model the error states of the multiple version programs. The programs are observed during simulated process-control testing, and estimates are obtained for the transition probabilities between the states of the Markov chain. The experimental Markov chain model is then expanded into a reliability model that takes into account the inertia of the system being controlled. The reliability of the multiple version software is computed from this reliability model at a given confidence level using confidence intervals obtained for the transition probabilities during the experiment. An example demonstrating the method is provided.

A Network of Conformational Transitions in the Apo Form of NDM-1 Enzyme Revealed by MD Simulation and a Markov State Model.

PubMed

Gao, Kaifu; Zhao, Yunjie

2017-04-13

New Delhi metallo-β-lactamase-1 (NDM-1) is a novel β-lactamase enzyme that confers enteric bacteria with nearly complete resistance to all β-lactam antibiotics, so it raises a formidable and global threat to human health. However, the binding mechanism between apo-NDM-1 and antibiotics as well as related conformational changes remains poorly understood, which largely hinders the overcoming of its antibiotic resistance. In our study, long-time conventional molecular dynamics simulation and Markov state models were applied to reveal both the dynamical and conformational landscape of apo-NDM-1: the MD simulation demonstrates that loop L3, which is responsible for antibiotic binding, is the most flexible and undergoes dramatic conformational changes; moreover, the Markov state model built from the simulation maps four metastable states including open, semiopen, and closed conformations of loop L3 as well as frequent transitions between the states. Our findings propose a possible conformational selection model for the binding mechanism between apo-NDM-1 and antibiotics, which facilitates the design of novel inhibitors and antibiotics.

Refining Markov state models for conformational dynamics using ensemble-averaged data and time-series trajectories

NASA Astrophysics Data System (ADS)

Matsunaga, Y.; Sugita, Y.

2018-06-01

A data-driven modeling scheme is proposed for conformational dynamics of biomolecules based on molecular dynamics (MD) simulations and experimental measurements. In this scheme, an initial Markov State Model (MSM) is constructed from MD simulation trajectories, and then, the MSM parameters are refined using experimental measurements through machine learning techniques. The second step can reduce the bias of MD simulation results due to inaccurate force-field parameters. Either time-series trajectories or ensemble-averaged data are available as a training data set in the scheme. Using a coarse-grained model of a dye-labeled polyproline-20, we compare the performance of machine learning estimations from the two types of training data sets. Machine learning from time-series data could provide the equilibrium populations of conformational states as well as their transition probabilities. It estimates hidden conformational states in more robust ways compared to that from ensemble-averaged data although there are limitations in estimating the transition probabilities between minor states. We discuss how to use the machine learning scheme for various experimental measurements including single-molecule time-series trajectories.

Bimolecular reaction dynamics from photoelectron spectroscopy of negative ions

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

Bradforth, Stephen Edmund

1992-11-01

The transition state region of a neutral bimolecular reaction may be experimentally investigated by photoelectron spectroscopy of an appropriate negative ion. The photoelectron spectrum provides information on the spectroscopy and dynamics of the short lived transition state and may be used to develop model potential energy surfaces that are semi-quantitative in this important region. The principles of bound {yields} bound negative ion photoelectron spectroscopy are illustrated by way of an example: a full analysis of the photoelectron bands of CN -, NCO - and NCS -. Transition state photoelectron spectra are presented for the following systems Br + HI, Clmore » + HI, F + HI, F + CH 30H,F + C 2H 5OH,F + OH and F + H 2. A time dependent framework for the simulation and interpretation of the bound → free transition state photoelectron spectra is subsequently developed and applied to the hydrogen transfer reactions Br + HI, F + OH → O( 3P, 1D) + HF and F + H 2. The theoretical approach for the simulations is a fully quantum-mechanical wave packet propagation on a collinear model reaction potential surface. The connection between the wavepacket time evolution and the photoelectron spectrum is given by the time autocorrelation function. For the benchmark F + H 2 system, comparisons with three-dimensional quantum calculations are made.« less

The mechanism of the converter domain rotation in the recovery stroke of myosin motor protein

PubMed Central

Baumketner, Andrij

2012-01-01

Upon ATP binding, myosin motor protein is found in two alternative conformations, pre-recovery state M* and post-recovery state M**. The transition from one state to the other, known as the recovery stroke, plays a key role in the myosin functional cycle. Despite much recent research, the microscopic details of this transition remain elusive. A critical step in the recovery stroke is the rotation of the converter domain from “up” position in pre-recovery state to “down” position in post-recovery state that leads to the swing of the lever arm attached to it. In this work, we demonstrate that the two rotational states of the converter domain are determined by the interactions within a small structural motif in the force-generating region of the protein that can be accurately modeled on computers using atomic representation and explicit solvent. Our simulations show that the transition between the two states is controlled by a small helix (SH1) located next to the relay helix and relay loop. A small translation in the position of SH1 away from the relay helix is seen to trigger the transition from “up” state to “down” state. The transition is driven by a cluster of hydrophobic residues I687, F487 and F506 that make significant contributions to the stability of both states. The proposed mechanism agrees well with the available structural and mutational studies. PMID:22855405

Modeling resting-state functional networks when the cortex falls asleep: local and global changes.

PubMed

Deco, Gustavo; Hagmann, Patric; Hudetz, Anthony G; Tononi, Giulio

2014-12-01

The transition from wakefulness to sleep represents the most conspicuous change in behavior and the level of consciousness occurring in the healthy brain. It is accompanied by similarly conspicuous changes in neural dynamics, traditionally exemplified by the change from "desynchronized" electroencephalogram activity in wake to globally synchronized slow wave activity of early sleep. However, unit and local field recordings indicate that the transition is more gradual than it might appear: On one hand, local slow waves already appear during wake; on the other hand, slow sleep waves are only rarely global. Studies with functional magnetic resonance imaging also reveal changes in resting-state functional connectivity (FC) between wake and slow wave sleep. However, it remains unclear how resting-state networks may change during this transition period. Here, we employ large-scale modeling of the human cortico-cortical anatomical connectivity to evaluate changes in resting-state FC when the model "falls asleep" due to the progressive decrease in arousal-promoting neuromodulation. When cholinergic neuromodulation is parametrically decreased, local slow waves appear, while the overall organization of resting-state networks does not change. Furthermore, we show that these local slow waves are structured macroscopically in networks that resemble the resting-state networks. In contrast, when the neuromodulator decrease further to very low levels, slow waves become global and resting-state networks merge into a single undifferentiated, broadly synchronized network. © The Author 2013. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Quality-by-Design (QbD): An integrated process analytical technology (PAT) approach for a dynamic pharmaceutical co-precipitation process characterization and process design space development.

PubMed

Wu, Huiquan; White, Maury; Khan, Mansoor A

2011-02-28

The aim of this work was to develop an integrated process analytical technology (PAT) approach for a dynamic pharmaceutical co-precipitation process characterization and design space development. A dynamic co-precipitation process by gradually introducing water to the ternary system of naproxen-Eudragit L100-alcohol was monitored at real-time in situ via Lasentec FBRM and PVM. 3D map of count-time-chord length revealed three distinguishable process stages: incubation, transition, and steady-state. The effects of high risk process variables (slurry temperature, stirring rate, and water addition rate) on both derived co-precipitation process rates and final chord-length-distribution were evaluated systematically using a 3(3) full factorial design. Critical process variables were identified via ANOVA for both transition and steady state. General linear models (GLM) were then used for parameter estimation for each critical variable. Clear trends about effects of each critical variable during transition and steady state were found by GLM and were interpreted using fundamental process principles and Nyvlt's transfer model. Neural network models were able to link process variables with response variables at transition and steady state with R(2) of 0.88-0.98. PVM images evidenced nucleation and crystal growth. Contour plots illustrated design space via critical process variables' ranges. It demonstrated the utility of integrated PAT approach for QbD development. Published by Elsevier B.V.

Modelling hard and soft states of Cygnus X-1 with propagating mass accretion rate fluctuations

NASA Astrophysics Data System (ADS)

Rapisarda, S.; Ingram, A.; van der Klis, M.

2017-12-01

We present a timing analysis of three Rossi X-ray Timing Explorer observations of the black hole binary Cygnus X-1 with the propagating mass accretion rate fluctuations model PROPFLUC. The model simultaneously predicts power spectra, time lags and coherence of the variability as a function of energy. The observations cover the soft and hard states of the source, and the transition between the two. We find good agreement between model predictions and data in the hard and soft states. Our analysis suggests that in the soft state the fluctuations propagate in an optically thin hot flow extending up to large radii above and below a stable optically thick disc. In the hard state, our results are consistent with a truncated disc geometry, where the hot flow extends radially inside the inner radius of the disc. In the transition from soft to hard state, the characteristics of the rapid variability are too complex to be successfully described with PROPFLUC. The surface density profile of the hot flow predicted by our model and the lack of quasi-periodic oscillations in the soft and hard states suggest that the spin of the black hole is aligned with the inner accretion disc and therefore probably with the rotational axis of the binary system.

Metal-insulator transitions

NASA Astrophysics Data System (ADS)

Imada, Masatoshi; Fujimori, Atsushi; Tokura, Yoshinori

1998-10-01

Metal-insulator transitions are accompanied by huge resistivity changes, even over tens of orders of magnitude, and are widely observed in condensed-matter systems. This article presents the observations and current understanding of the metal-insulator transition with a pedagogical introduction to the subject. Especially important are the transitions driven by correlation effects associated with the electron-electron interaction. The insulating phase caused by the correlation effects is categorized as the Mott Insulator. Near the transition point the metallic state shows fluctuations and orderings in the spin, charge, and orbital degrees of freedom. The properties of these metals are frequently quite different from those of ordinary metals, as measured by transport, optical, and magnetic probes. The review first describes theoretical approaches to the unusual metallic states and to the metal-insulator transition. The Fermi-liquid theory treats the correlations that can be adiabatically connected with the noninteracting picture. Strong-coupling models that do not require Fermi-liquid behavior have also been developed. Much work has also been done on the scaling theory of the transition. A central issue for this review is the evaluation of these approaches in simple theoretical systems such as the Hubbard model and t-J models. Another key issue is strong competition among various orderings as in the interplay of spin and orbital fluctuations. Experimentally, the unusual properties of the metallic state near the insulating transition have been most extensively studied in d-electron systems. In particular, there is revived interest in transition-metal oxides, motivated by the epoch-making findings of high-temperature superconductivity in cuprates and colossal magnetoresistance in manganites. The article reviews the rich phenomena of anomalous metallicity, taking as examples Ti, V, Cr, Mn, Fe, Co, Ni, Cu, and Ru compounds. The diverse phenomena include strong spin and orbital fluctuations, mass renormalization effects, incoherence of charge dynamics, and phase transitions under control of key parameters such as band filling, bandwidth, and dimensionality. These parameters are experimentally varied by doping, pressure, chemical composition, and magnetic fields. Much of the observed behavior can be described by the current theory. Open questions and future problems are also extracted from comparison between experimental results and theoretical achievements.

Power law versus exponential state transition dynamics: application to sleep-wake architecture.

PubMed

Chu-Shore, Jesse; Westover, M Brandon; Bianchi, Matt T

2010-12-02

Despite the common experience that interrupted sleep has a negative impact on waking function, the features of human sleep-wake architecture that best distinguish sleep continuity versus fragmentation remain elusive. In this regard, there is growing interest in characterizing sleep architecture using models of the temporal dynamics of sleep-wake stage transitions. In humans and other mammals, the state transitions defining sleep and wake bout durations have been described with exponential and power law models, respectively. However, sleep-wake stage distributions are often complex, and distinguishing between exponential and power law processes is not always straightforward. Although mono-exponential distributions are distinct from power law distributions, multi-exponential distributions may in fact resemble power laws by appearing linear on a log-log plot. To characterize the parameters that may allow these distributions to mimic one another, we systematically fitted multi-exponential-generated distributions with a power law model, and power law-generated distributions with multi-exponential models. We used the Kolmogorov-Smirnov method to investigate goodness of fit for the "incorrect" model over a range of parameters. The "zone of mimicry" of parameters that increased the risk of mistakenly accepting power law fitting resembled empiric time constants obtained in human sleep and wake bout distributions. Recognizing this uncertainty in model distinction impacts interpretation of transition dynamics (self-organizing versus probabilistic), and the generation of predictive models for clinical classification of normal and pathological sleep architecture.

Single-Column Model Simulations of Subtropical Marine Boundary-Layer Cloud Transitions Under Weakening Inversions

NASA Astrophysics Data System (ADS)

Neggers, R. A. J.; Ackerman, A. S.; Angevine, W. M.; Bazile, E.; Beau, I.; Blossey, P. N.; Boutle, I. A.; de Bruijn, C.; Cheng, A.; van der Dussen, J.; Fletcher, J.; Dal Gesso, S.; Jam, A.; Kawai, H.; Cheedela, S. K.; Larson, V. E.; Lefebvre, M.-P.; Lock, A. P.; Meyer, N. R.; de Roode, S. R.; de Rooy, W.; Sandu, I.; Xiao, H.; Xu, K.-M.

2017-10-01

Results are presented of the GASS/EUCLIPSE single-column model intercomparison study on the subtropical marine low-level cloud transition. A central goal is to establish the performance of state-of-the-art boundary-layer schemes for weather and climate models for this cloud regime, using large-eddy simulations of the same scenes as a reference. A novelty is that the comparison covers four different cases instead of one, in order to broaden the covered parameter space. Three cases are situated in the North-Eastern Pacific, while one reflects conditions in the North-Eastern Atlantic. A set of variables is considered that reflects key aspects of the transition process, making use of simple metrics to establish the model performance. Using this method, some longstanding problems in low-level cloud representation are identified. Considerable spread exists among models concerning the cloud amount, its vertical structure, and the associated impact on radiative transfer. The sign and amplitude of these biases differ somewhat per case, depending on how far the transition has progressed. After cloud breakup the ensemble median exhibits the well-known "too few too bright" problem. The boundary-layer deepening rate and its state of decoupling are both underestimated, while the representation of the thin capping cloud layer appears complicated by a lack of vertical resolution. Encouragingly, some models are successful in representing the full set of variables, in particular, the vertical structure and diurnal cycle of the cloud layer in transition. An intriguing result is that the median of the model ensemble performs best, inspiring a new approach in subgrid parameterization.

Order and disorder in coupled metronome systems

NASA Astrophysics Data System (ADS)

Boda, Sz.; Davidova, L.; Néda, Z.

2014-04-01

Metronomes placed on a smoothly rotating disk are used for exemplifying order-disorder type phase-transitions. The ordered phase corresponds to spontaneously synchronized beats, while the disordered state is when the metronomes swing in unsynchronized manner. Using a given metronome ensemble, we propose several methods for switching between ordered and disordered states. The system is studied by controlled experiments and a realistic model. The model reproduces the experimental results, and allows to study large ensembles with good statistics. Finite-size effects and the increased fluctuation in the vicinity of the phase-transition point are also successfully reproduced.

A Time Integration Algorithm Based on the State Transition Matrix for Structures with Time Varying and Nonlinear Properties

NASA Technical Reports Server (NTRS)

Bartels, Robert E.

2003-01-01

A variable order method of integrating the structural dynamics equations that is based on the state transition matrix has been developed. The method has been evaluated for linear time variant and nonlinear systems of equations. When the time variation of the system can be modeled exactly by a polynomial it produces nearly exact solutions for a wide range of time step sizes. Solutions of a model nonlinear dynamic response exhibiting chaotic behavior have been computed. Accuracy of the method has been demonstrated by comparison with solutions obtained by established methods.

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

Filippone, Michele; Dusuel, Sebastien; Vidal, Julien

We consider a set of fully connected spin models that display first- or second-order transitions and for which we compute the ground-state entanglement in the thermodynamical limit. We analyze several entanglement measures (concurrence, Renyi entropy, and negativity) and show that, in general, discontinuous transitions lead to a jump of these quantities at the transition point. Interestingly, we also find examples where this is not the case.

p-Adic solid-on-solid model on a Cayley tree

NASA Astrophysics Data System (ADS)

Khakimov, O. N.

2017-12-01

We consider a p-adic solid-on-solid ( SOS) model with a nearest-neighbor coupling, m+1 spins, and a coupling constant J ∈ Q p on a Cayley tree. We find conditions under which a phase transition does not occur in the model. We show that if p | m + 1 for some J, then a phase transition occurs. Moreover, we formulate a criterion for the boundedness of p-adic Gibbs measures for the ( m+1)- state SOS model.

Nonradiative Transitions in Media of Different Polarities and Their Modeling for 12'-Apo-β-Caroten-12'-Al and 8'-Apo-β-Caroten-8'-Al

NASA Astrophysics Data System (ADS)

Pavlovich, V. S.

2014-09-01

The theory of nonradiative transitions, based on the model of orientational broadening of electronic levels, is used to interpret known data on the effect of the polarity of the medium and temperature on the lifetime of the S 1( A {/g -}) state for 12'-apo-β-caroten-12'-al and 8'-apo-β-caroten-8'-al. The effect of promoting vibrations on the rate constant for nonradiative transitions is considered. The results make it possible to hypothesize that the internal electric field created by the environment strongly perturbs the pigment molecules. Consequently, in the excited S 1( A {/g -}) state, both pigments exist as different conformers I and II. Their structures differ by a 180° rotation of the cyclohexene ring relative to the polyene chain. Conformer II predominates in polar media, and is found in an intramolecular charge-transfer state S 1( A {/g -}/ ICT). In addition, as a result of fluctuations in the internal electric field, it can also be found in a charge-separated state S 1( A {/g -}/ CS).

Spin textures on general surfaces of the correlated topological insulator SmB6

NASA Astrophysics Data System (ADS)

Baruselli, Pier Paolo; Vojta, Matthias

2016-05-01

Employing the k .p expansion for a family of tight-binding models for SmB6, we analytically compute topological surface states on a generic (l m n ) surface. We show how the Dirac-cone spin structure depends on model ingredients and on the angle θ between the surface normal and the main crystal axes. We apply the general theory to (001), (110), (111), and (210) surfaces, for which we provide concrete predictions for the spin pattern of surface states which we also compare with tight-binding results. As shown in previous work, the spin pattern on a (001 ) surface can be related to the value of mirror Chern numbers, and we explore the possibility of topological phase transitions between states with different mirror Chern numbers and the associated change of the spin structure of surface states. Such transitions may be accessed by varying either the hybridization between conduction and f electrons or the crystal-field splitting of the low-energy f multiplets, and we compute corresponding phase diagrams. Experimentally, chemical doping is a promising route to realize such transitions.

Bond Order Conservation Strategies in Catalysis Applied to the NH 3 Decomposition Reaction

DOE PAGES

Yu, Liang; Abild-Pedersen, Frank

2016-12-14

On the basis of an extensive set of density functional theory calculations, it is shown that a simple scheme provides a fundamental understanding of variations in the transition state energies and structures of reaction intermediates on transition metal surfaces across the periodic table. The scheme is built on the bond order conservation principle and requires a limited set of input data, still achieving transition state energies as a function of simple descriptors with an error smaller than those of approaches based on linear fits to a set of calculated transition state energies. Here, we have applied this approach together withmore » linear scaling of adsorption energies to obtain the energetics of the NH 3 decomposition reaction on a series of stepped fcc(211) transition metal surfaces. Moreover, this information is used to establish a microkinetic model for the formation of N 2 and H 2, thus providing insight into the components of the reaction that determines the activity.« less

Identification of key residues for protein conformational transition using elastic network model.

PubMed

Su, Ji Guo; Xu, Xian Jin; Li, Chun Hua; Chen, Wei Zu; Wang, Cun Xin

2011-11-07

Proteins usually undergo conformational transitions between structurally disparate states to fulfill their functions. The large-scale allosteric conformational transitions are believed to involve some key residues that mediate the conformational movements between different regions of the protein. In the present work, a thermodynamic method based on the elastic network model is proposed to predict the key residues involved in protein conformational transitions. In our method, the key functional sites are identified as the residues whose perturbations largely influence the free energy difference between the protein states before and after transition. Two proteins, nucleotide binding domain of the heat shock protein 70 and human/rat DNA polymerase β, are used as case studies to identify the critical residues responsible for their open-closed conformational transitions. The results show that the functionally important residues mainly locate at the following regions for these two proteins: (1) the bridging point at the interface between the subdomains that control the opening and closure of the binding cleft; (2) the hinge region between different subdomains, which mediates the cooperative motions between the corresponding subdomains; and (3) the substrate binding sites. The similarity in the positions of the key residues for these two proteins may indicate a common mechanism in their conformational transitions.

Strongly correlated superconductivity and quantum criticality

NASA Astrophysics Data System (ADS)

Tremblay, A.-M. S.

Doped Mott insulators and doped charge-transfer insulators describe classes of materials that can exhibit unconventional superconducting ground states. Examples include the cuprates and the layered organic superconductors of the BEDT family. I present results obtained from plaquette cellular dynamical mean-field theory. Continuous-time quantum Monte Carlo evaluation of the hybridization expansion allows one to study the models in the large interaction limit where quasiparticles can disappear. The normal state which is unstable to the superconducting state exhibits a first-order transition between a pseudogap and a correlated metal phase. That transition is the finite-doping extension of the metal-insulator transition obtained at half-filling. This transition serves as an organizing principle for the normal and superconducting states of both cuprates and doped organic superconductors. In the less strongly correlated limit, these methods also describe the more conventional case where the superconducting dome surrounds an antiferromagnetic quantum critical point. Sponsored by NSERC RGPIN-2014-04584, CIFAR, Research Chair in the Theory of Quantum Materials.

Paramagnetic and glass transitions in sudoku

NASA Astrophysics Data System (ADS)

Williams, A.; Ackland, G. J.

2012-09-01

We study the statistical mechanics of a model glassy system based on sudoku, a familiar and popular mathematical puzzle. Sudoku puzzles provide a very rare example of a class of frustrated systems with a unique ground state without symmetry. Here, the puzzle is recast as a thermodynamic system where the number of violated rules defines the energy. We use Monte Carlo simulation to show that the “sudoku Hamiltonian” exhibits two transitions as a function of temperature, a paramagnetic, and a glass transition. Of these, the intermediate condensed phase is the only one that visits the ground state (i.e., it solves the puzzle, though this is not the purpose of the study). Both transitions are associated with an entropy change, paramagnetism measured from the dynamics of the Monte Carlo run, showing a peak in specific heat, while the residual glass entropy is determined by finding multiple instances of the glass by repeated annealing. There are relatively few such simple models for frustrated or glassy systems that exhibit both ordering and glass transitions; sudoku puzzles are unique for the ease with which they can be obtained, with the proof of the existence of a unique ground state via the satisfiability of all constraints. Simulations suggest that in the glass phase there is an increase in information entropy with lowering temperature. In fact, we have shown that sudoku puzzles have the type of rugged energy landscape with multiple minima that typifies glasses in many physical systems. This puzzling result is a manifestation of the paradox of the residual glass entropy. These readily available puzzles can now be used as solvable model Hamiltonian systems for studying the glass transition.

Two-component Gaussian core model: Strong-coupling limit, Bjerrum pairs, and gas-liquid phase transition.

PubMed

Frydel, Derek; Levin, Yan

2018-01-14

In the present work, we investigate a gas-liquid transition in a two-component Gaussian core model, where particles of the same species repel and those of different species attract. Unlike a similar transition in a one-component system with particles having attractive interactions at long separations and repulsive interactions at short separations, a transition in the two-component system is not driven solely by interactions but by a specific feature of the interactions, the correlations. This leads to extremely low critical temperature, as correlations are dominant in the strong-coupling limit. By carrying out various approximations based on standard liquid-state methods, we show that a gas-liquid transition of the two-component system poses a challenging theoretical problem.

Two-component Gaussian core model: Strong-coupling limit, Bjerrum pairs, and gas-liquid phase transition

NASA Astrophysics Data System (ADS)

Frydel, Derek; Levin, Yan

2018-01-01

In the present work, we investigate a gas-liquid transition in a two-component Gaussian core model, where particles of the same species repel and those of different species attract. Unlike a similar transition in a one-component system with particles having attractive interactions at long separations and repulsive interactions at short separations, a transition in the two-component system is not driven solely by interactions but by a specific feature of the interactions, the correlations. This leads to extremely low critical temperature, as correlations are dominant in the strong-coupling limit. By carrying out various approximations based on standard liquid-state methods, we show that a gas-liquid transition of the two-component system poses a challenging theoretical problem.

Van der Waals model for phase transitions in thermoresponsive surface films.

PubMed

McCoy, John D; Curro, John G

2009-05-21

Phase transitions in polymeric surface films are studied with a simple model based on the van der Waals equation of state. Each chain is modeled by a single bead attached to the surface by an entropic-Hooke's law spring. The surface coverage is controlled by adjusting the chemical potential, and the equilibrium density profile is calculated with density functional theory. The interesting feature of this model is the multivalued nature of the density profile seen at low temperature. This van der Waals loop behavior is resolved with a Maxwell construction between a high-density phase near the wall and a low-density phase in a "vertical" phase transition. Signatures of the phase transition in experimentally measurable quantities are then found. Numerical calculations are presented for isotherms of surface pressure, for the Poisson ratio, and for the swelling ratio.

Symbolic Computation of Strongly Connected Components Using Saturation

NASA Technical Reports Server (NTRS)

Zhao, Yang; Ciardo, Gianfranco

2010-01-01

Finding strongly connected components (SCCs) in the state-space of discrete-state models is a critical task in formal verification of LTL and fair CTL properties, but the potentially huge number of reachable states and SCCs constitutes a formidable challenge. This paper is concerned with computing the sets of states in SCCs or terminal SCCs of asynchronous systems. Because of its advantages in many applications, we employ saturation on two previously proposed approaches: the Xie-Beerel algorithm and transitive closure. First, saturation speeds up state-space exploration when computing each SCC in the Xie-Beerel algorithm. Then, our main contribution is a novel algorithm to compute the transitive closure using saturation. Experimental results indicate that our improved algorithms achieve a clear speedup over previous algorithms in some cases. With the help of the new transitive closure computation algorithm, up to 10(exp 150) SCCs can be explored within a few seconds.

Land use change effects on forest carbon cycling throughout the southern United States

Treesearch

Peter B. Woodbury; Linda S. Heath; James E. Smith

2006-01-01

We modeled the effects of afforestation and deforestation on carbon cycling in forest floor and soil from 1900 to 2050 throughout 13 states in the southern United States. The model uses historical data on gross (two-way) transitions between forest, pasture, plowed agriculture, and urban lands along with equations describing changes in carbon over many decades for each...

Understanding molecular motor walking along a microtubule: a themosensitive asymmetric Brownian motor driven by bubble formation.

PubMed

Arai, Noriyoshi; Yasuoka, Kenji; Koishi, Takahiro; Ebisuzaki, Toshikazu; Zeng, Xiao Cheng

2013-06-12

The "asymmetric Brownian ratchet model", a variation of Feynman's ratchet and pawl system, is invoked to understand the kinesin walking behavior along a microtubule. The model system, consisting of a motor and a rail, can exhibit two distinct binding states, namely, the random Brownian state and the asymmetric potential state. When the system is transformed back and forth between the two states, the motor can be driven to "walk" in one direction. Previously, we suggested a fundamental mechanism, that is, bubble formation in a nanosized channel surrounded by hydrophobic atoms, to explain the transition between the two states. In this study, we propose a more realistic and viable switching method in our computer simulation of molecular motor walking. Specifically, we propose a thermosensitive polymer model with which the transition between the two states can be controlled by temperature pulses. Based on this new motor system, the stepping size and stepping time of the motor can be recorded. Remarkably, the "walking" behavior observed in the newly proposed model resembles that of the realistic motor protein. The bubble formation based motor not only can be highly efficient but also offers new insights into the physical mechanism of realistic biomolecule motors.

Projected Statewide Impact of "Opportunity Culture" School Models

ERIC Educational Resources Information Center

Holly, Christen; Dean, Stephanie; Hassel, Emily Ayscue; Hassel, Bryan C.

2014-01-01

This brief estimates the impact of a statewide implementation of Opportunity Culture models, using North Carolina as an example. Impacts estimated include student learning outcomes, gross state product, teacher pay, and other career characteristics, and state income tax revenue. Estimates indicate the potential for a statewide transition to…

Ra isotopes in the sdg interacting-boson model with one f-boson

NASA Astrophysics Data System (ADS)

Naotaka, Yoshinaga; Takahiro, Mizusaki; Takaharu, Otsuka

1993-06-01

We study positive- and negative-parity states in Ra isotopes in terms of the proton-neutron sdg interacting-boson model with one f-boson. The present calculation correctly reproduces the spherical to deformed phase transition. Especially, we would like to stress the importance of the g-boson for reproducing the E1 transitions which are very strong in this region.

Transitional circuitry for studying the properties of DNA

NASA Astrophysics Data System (ADS)

Trubochkina, N.

2018-01-01

The article is devoted to a new view of the structure of DNA as an intellectual scheme possessing the properties of logic and memory. The theory of transient circuitry, developed by the author for optimal computer circuits, revealed an amazing structural similarity between mathematical models of transition silicon elements and logic and memory circuits of solid state transient circuitry and atomic models of parts of DNA.

Statistical thermodynamics of protein folding: Comparison of a mean-field theory with Monte Carlo simulations

NASA Astrophysics Data System (ADS)

Hao, Ming-Hong; Scheraga, Harold A.

1995-01-01

A comparative study of protein folding with an analytical theory and computer simulations, respectively, is reported. The theory is based on an improved mean-field formalism which, in addition to the usual mean-field approximations, takes into account the distributions of energies in the subsets of conformational states. Sequence-specific properties of proteins are parametrized in the theory by two sets of variables, one for the energetics of mean-field interactions and one for the distribution of energies. Simulations are carried out on model polypeptides with different sequences, with different chain lengths, and with different interaction potentials, ranging from strong biases towards certain local chain states (bond angles and torsional angles) to complete absence of local conformational preferences. Theoretical analysis of the simulation results for the model polypeptides reveals three different types of behavior in the folding transition from the statistical coiled state to the compact globular state; these include a cooperative two-state transition, a continuous folding, and a glasslike transition. It is found that, with the fitted theoretical parameters which are specific for each polypeptide under a different potential, the mean-field theory can describe the thermodynamic properties and folding behavior of the different polypeptides accurately. By comparing the theoretical descriptions with simulation results, we verify the basic assumptions of the theory and, thereby, obtain new insights about the folding transitions of proteins. It is found that the cooperativity of the first-order folding transition of the model polypeptides is determined mainly by long-range interactions, in particular the dipolar orientation; the local interactions (e.g., bond-angle and torsion-angle potentials) have only marginal effect on the cooperative characteristic of the folding, but have a large impact on the difference in energy between the folded lowest-energy structure and the unfolded conformations of a protein.

On the reversibility of transitions between closed and open cellular convection

DOE PAGES

Feingold, G.; Koren, I.; Yamaguchi, T.; ...

2015-07-08

The two-way transition between closed and open cellular convection is addressed in an idealized cloud-resolving modeling framework. A series of cloud-resolving simulations shows that the transition between closed and open cellular states is asymmetrical and characterized by a rapid ("runaway") transition from the closed- to the open-cell state but slower recovery to the closed-cell state. Given that precipitation initiates the closed–open cell transition and that the recovery requires a suppression of the precipitation, we apply an ad hoc time-varying drop concentration to initiate and suppress precipitation. We show that the asymmetry in the two-way transition occurs even for very rapidmore » drop concentration replenishment. The primary barrier to recovery is the loss in turbulence kinetic energy (TKE) associated with the loss in cloud water (and associated radiative cooling) and the vertical stratification of the boundary layer during the open-cell period. In transitioning from the open to the closed state, the system faces the task of replenishing cloud water fast enough to counter precipitation losses, such that it can generate radiative cooling and TKE. It is hampered by a stable layer below cloud base that has to be overcome before water vapor can be transported more efficiently into the cloud layer. Recovery to the closed-cell state is slower when radiative cooling is inefficient such as in the presence of free tropospheric clouds or after sunrise, when it is hampered by the absorption of shortwave radiation. Tests suggest that recovery to the closed-cell state is faster when the drizzle is smaller in amount and of shorter duration, i.e., when the precipitation causes less boundary layer stratification. Cloud-resolving model results on recovery rates are supported by simulations with a simple predator–prey dynamical system analogue. It is suggested that the observed closing of open cells by ship effluent likely occurs when aerosol intrusions are large, when contact comes prior to the heaviest drizzle in the early morning hours, and when the free troposphere is cloud free.« less

Analysis of the Rotational Structure of ˜{B}^2A' ← ˜{X}^2A' Transition of Isopropoxy Radical: Isolated State vs. Coupled States Model

NASA Astrophysics Data System (ADS)

Melnik, Dmitry G.; Miller, Terry A.; Liu, Jinjun

2013-06-01

Isopropoxy radicals are reactive intermediates in atmospheric and combustion chemistry. From the theoretical point of view, they represent an extreme case of ``isotopically'' substituted methoxy radicals with two methyl groups playing the role of heavy hydrogen isotopes. Previously the rotationally resolved spectra of ˜{B}^2A' ← ˜{X}^2A' electronic transition were successfully analyzed using a simple effective rotational Hamiltonian of the isolated ˜{X} and ˜{B} states. However, a number of the experimentally determined parameters appeared dramatically inconsistent with the quantum chemistry calculations and theoretical predictions based on the symmetry arguments. Recently, we analyzed these spectra using a coupled two state model, which explicitly includes interactions between the ground ˜{X}^2A' state and low-lying excited ˜{A}^2A^'' state. In this presentation we will discuss the results of this analysis and compare the parameters of both models and their physical significance. D. G. Melnik, T. A. Miller and J. Liu, TI15, 67^{th Molecular Spectroscopy Symposium}, Columbus, 2012

Detecting phase boundaries of quantum spin-1/2 XXZ ladder via bipartite and multipartite entanglement transitions

NASA Astrophysics Data System (ADS)

Singha Roy, Sudipto; Dhar, Himadri Shekhar; Rakshit, Debraj; Sen(De), Aditi; Sen, Ujjwal

2017-12-01

Phase transition in quantum many-body systems inevitably causes changes in certain physical properties which then serve as potential indicators of critical phenomena. Besides the traditional order parameters, characterization of quantum entanglement has proven to be a computationally efficient and successful method for detection of phase boundaries, especially in one-dimensional models. Here we determine the rich phase diagram of the ground states of a quantum spin-1/2 XXZ ladder by analyzing the variation of bipartite and multipartite entanglements. Our study characterizes the different ground state phases and notes the correspondence with known results, while highlighting the finer details that emerge from the behavior of ground state entanglement. Analysis of entanglement in the ground state provides a clearer picture of the complex ground state phase diagram of the system using only a moderate-size model.

Magnetic-flux-driven topological quantum phase transition and manipulation of perfect edge states in graphene tube.

PubMed

Lin, S; Zhang, G; Li, C; Song, Z

2016-08-24

We study the tight-binding model for a graphene tube with perimeter N threaded by a magnetic field. We show exactly that this model has different nontrivial topological phases as the flux changes. The winding number, as an indicator of topological quantum phase transition (QPT) fixes at N/3 if N/3 equals to its integer part [N/3], otherwise it jumps between [N/3] and [N/3] + 1 periodically as the flux varies a flux quantum. For an open tube with zigzag boundary condition, exact edge states are obtained. There exist two perfect midgap edge states, in which the particle is completely located at the boundary, even for a tube with finite length. The threading flux can be employed to control the quantum states: transferring the perfect edge state from one end to the other, or generating maximal entanglement between them.

A Guide to Transitions in Education and Training Systems.

DTIC Science & Technology

1980-06-01

possessing high power and force and somewhat approachable in his position. If A2 is critical to the success of the change, the best approach may be to have...transition model. In this section we will highlight the problems unique to the transition state and outline a coordinated approach for its management. As...Essential to the effective management of the transition period is: - Psychological acceptance of uncertainty on the part of key leaders; - Clear and

Facilitating a Major Staffing Transition in a State Psychiatric Hospital With Changes to Nursing Orientation.

PubMed

Birnbaum, Shira; Sperber-Weiss, Doreen; Dimitrios, Timothy; Eckel, Donald; Monroy-Miller, Cherry; Monroe, Janet J; Friedman, Ross; Ologbosele, Mathias; Epo, Grace; Sharpe, Debra; Zarski, Yongsuk

A large state psychiatric hospital experienced a state-mandated Reduction in Force that resulted in the abrupt loss and rapid turnover of more than 40% of its nursing and paraprofessional staff. The change exemplified current national trends toward downsizing and facility closure. This article describes revisions to the nursing orientation program that supported cost containment and fidelity to mission and clinical practices during the transition. An existing nursing orientation program was reconfigured in alignment with principles of rational instructional design and a core-competencies model of curriculum development, evidence-based practices that provided tactical clarity and commonality of purpose during a complex and emotionally charged transition period. Program redesign enabled efficiencies that facilitated the transition, with no evidence of associated negative effects. The process described here offers an example for hospitals facing similar workforce reorganization in an era of public sector downsizing.

Reduced probabilities for E2 transitions between excited collective states of triaxial even–even nuclei

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

Nadyrbekov, M. S., E-mail: nodirbekov@inp.uz; Bozarov, O. A.

Reduced probabilities for intra- and interband E2 transitions in excited collective states of even–even lanthanide and actinide nuclei are analyzed on the basis of a model that admits an arbitrary triaxiality. They are studied in detail in the energy spectra of {sup 154}Sm, {sup 156}Gd, {sup 158}Dy, {sup 162,164}Er, {sup 230,232}Th, and {sup 232,234,236,238}U even–even nuclei. Theoretical and experimental values of the reduced probabilities for the respective E2 transitions are compared. This comparison shows good agreement for all states, including high-spin ones. The ratios of the reduced probabilities for the E2 transitions in question are compared with results following frommore » the Alaga rules. These comparisons make it possible to assess the sensitivity of the probabilities being considered to the presence of quadrupole deformations.« less

Experiences of Nigerian Internationally Educated Nurses Transitioning to United States Health Care Settings.

PubMed

Iheduru-Anderson, Kechinyere C; Wahi, Monika M

2018-04-01

Successful transition to practice of internationally educated nurses (IENs) can critically affect quality of care. The aim of this study was to characterize the facilitators and barriers to transition of Nigerian IENs (NIENs) to the United States health care setting. Using a descriptive phenomenology approach, 6 NIENs were interviewed about their transitional experiences in the United States. Thematic methods were used for data analysis. The three major themes identified from the participants' stories were "fear/anger and disappointment" (FAD), "road/journey to success/overcoming challenges" (RJO), and "moving forward" (MF). The FAD theme predominated, including experiences of racism, bullying, and inequality. The RJO theme included resilience, and the MF theme encompassed personal growth. NIENs face personal and organizational barriers to adaptation, especially fear, anger and disappointment. Future research should seek to develop a model for optimal adaptation that focuses on improving both personal and organizational facilitators and decreasing barriers.

Anharmonic vibrations around a triaxial nuclear deformation “frozen” to γ = 30°

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

Buganu, Petrica, E-mail: buganu@theory.nipne.ro; Budaca, Radu

2015-12-07

The Davydov-Chaban Hamiltonian with a sextic oscillator potential for the variable β and γ fixed to 30° is exactly solved for the ground and β bands and approximately for the γ band. The model is called Z(4)-Sextic in connection with the already established Z(4) solution. The energy spectra, normalized to the energy of the first excited state, and several B(E2) transition probabilities, normalized to the B(E2) transition from the first excited state to the ground state, depend on a single parameter α. By varying α within a sufficiently large interval, a shape phase transition from an approximately spherical shape tomore » a deformed one is evidenced.« less

Equilibration and non-equilibrium steady states in PT-symmetric Toda lattice

NASA Astrophysics Data System (ADS)

Harter, Andrew; Joglekar, Yogesh; Saxena, Avadh

The Toda lattice is a classical discrete integrable model, describing a chain of particles that interact through an exponentially decaying, pairwise potential. It also supports soliton solutions. We consider the fate of this lattice in the presence of localized, spatially separated, balanced drag (loss) and drive (gain). Such systems with balanced gain and loss undergo a transition, the so called parity-time (PT) symmetry breaking transition, from a quasi-equilibrium state to a state that is far removed from equilibrium. We determine the threshold for such a transition in the presence of stochastic and deterministic driving, and study the robustness of our results in the presence of different boundary conditions. This work is supported by DMR-1054020.

Dynamic transitions in a model of the hypothalamic-pituitary-adrenal axis

NASA Astrophysics Data System (ADS)

Čupić, Željko; Marković, Vladimir M.; Maćešić, Stevan; Stanojević, Ana; Damjanović, Svetozar; Vukojević, Vladana; Kolar-Anić, Ljiljana

2016-03-01

Dynamic properties of a nonlinear five-dimensional stoichiometric model of the hypothalamic-pituitary-adrenal (HPA) axis were systematically investigated. Conditions under which qualitative transitions between dynamic states occur are determined by independently varying the rate constants of all reactions that constitute the model. Bifurcation types were further characterized using continuation algorithms and scale factor methods. Regions of bistability and transitions through supercritical Andronov-Hopf and saddle loop bifurcations were identified. Dynamic state analysis predicts that the HPA axis operates under basal (healthy) physiological conditions close to an Andronov-Hopf bifurcation. Dynamic properties of the stress-control axis have not been characterized experimentally, but modelling suggests that the proximity to a supercritical Andronov-Hopf bifurcation can give the HPA axis both, flexibility to respond to external stimuli and adjust to new conditions and stability, i.e., the capacity to return to the original dynamic state afterwards, which is essential for maintaining homeostasis. The analysis presented here reflects the properties of a low-dimensional model that succinctly describes neurochemical transformations underlying the HPA axis. However, the model accounts correctly for a number of experimentally observed properties of the stress-response axis. We therefore regard that the presented analysis is meaningful, showing how in silico investigations can be used to guide the experimentalists in understanding how the HPA axis activity changes under chronic disease and/or specific pharmacological manipulations.

Large scale shell model study of nuclear spectroscopy in nuclei around 132Sn

NASA Astrophysics Data System (ADS)

Lo Iudice, N.; Bianco, D.; Andreozzi, F.; Porrino, A.; Knapp, F.

2012-10-01

The properties of low-lying 2+ states in chains of nuclei in the proximity of the magic number N=82 are investigated within a new shell model approach exploiting an iterative algorithm alternative to Lanczos. The calculation yields levels and transition strengths in overall good agreement with experiments. The comparative analysis of the E2 and M1 transitions supports, in many cases, the scheme provided by the interacting boson model.

Order-disorder transitions in lattice gases with annealed reactive constraints

NASA Astrophysics Data System (ADS)

Dudka, Maxym; Bénichou, Olivier; Oshanin, Gleb

2018-04-01

We study equilibrium properties of catalytically-activated reactions taking place on a lattice of adsorption sites. The particles undergo continuous exchanges with a reservoir maintained at a constant chemical potential μ and react when they appear at the neighbouring sites, provided that some reactive conditions are fulfilled. We model the latter in two different ways: in the Model I some fraction p of the bonds connecting neighbouring sites possesses special catalytic properties such that any two As appearing on the sites connected by such a bond instantaneously react and desorb. In the Model II some fraction p of the adsorption sites possesses such properties and neighbouring particles react if at least one of them resides on a catalytic site. For the case of annealed disorder in the distribution of the catalyst, which is tantamount to the situation when the reaction may take place at any point on the lattice but happens with a finite probability p, we provide an exact solution for both models for the interior of an infinitely large Cayley tree—the so-called Bethe lattice. We show that both models exhibit a rich critical behaviour: for the annealed Model I it is characterised by a transition into an ordered state and a re-entrant transition into a disordered phase, which both are continuous. For the annealed Model II, which represents a rather exotic model of statistical mechanics in which interactions of any particle with its environment have a peculiar Boolean form, the transition to an ordered state is always continuous, while the re-entrant transition into the disordered phase may be either continuous or discontinuous, depending on the value of p.

Anomalous finite-size effect due to quasidegenerate phases in triangular antiferromagnets with long-range interactions and mapping to the generalized six-state clock model

NASA Astrophysics Data System (ADS)

Nishino, Masamichi; Miyashita, Seiji

2016-11-01

The effect of long-range (LR) interactions on frustrated-spin models is an interesting problem, which provides rich ordering processes. We study the effect of LR interactions on triangular Ising antiferromagnets with the next-nearest-neighbor ferromagnetic interaction (TIAFF). In the thermodynamic limit, the LRTIAFF model should reproduce the corresponding mean-field results, in which successive phase transitions occur among various phases, i.e., the disordered paramagnetic phase, so-called partially disordered phase, three-sublattice ferrimagnetic phase, and two-sublattice ferrimagnetic phase. In the present paper we focus on the magnetic susceptibility at the transition point between the two-sublattice ferrimagnetic and the disordered paramagnetic phases at relatively large ferromagnetic interactions. In the mean-field analysis, the magnetic susceptibility shows no divergence at the transition point. In contrast, a divergencelike enhancement of the susceptibility is observed in Monte Carlo simulations in finite-size systems. We investigate the origin of this difference and find that it is attributed to a virtual degeneracy of the free energies of the partially disordered and 2-FR phases. We also exploit a generalized six-state clock model with an LR interaction, which is a more general system with Z6 symmetry. We discuss the phase diagram of this model and find that it exhibits richer transition patterns and contains the physics of the LRTIAFF model.

Walk, Bicycle, and Transit Trips of Transit-Dependent and Choice Riders in the 2009 United States National Household Travel Survey.

PubMed

Lachapelle, Ugo

2015-08-01

Previous research has shown that public transit use may be associated with active transportation. Access to a car may influence active transportation of transit riders. Using the 2009 United States National Household Travel Survey (NHTS), transit users ≥ 16 years old (n = 25,550) were categorized according to driver status and number of cars and drivers in the household. This typology ranged from choice transit riders (ie, "fully motorized drivers") to transit-dependent riders (ie, "unmotorized nondriver"). Transit trips, walking trips, and bicycling trips of transit users are estimated in negative binomial models against the car availability typology. Sixteen percent of participants took transit in the past month; most (86%) lived in car-owning households. As income increased, car availability also increased. Transit user groups with lower car availability were generally more likely than fully motorized drivers to take more public transit, walking, and bicycle trips. Transit riders have varying levels of vehicle access; their use of combinations of alternative modes of transportation fluctuates accordingly. Transit-dependent individuals without cars or sharing cars used active transportation more frequently than car owners. Policies to reduce vehicle ownership in households may enable increases in the use of alternative modes of transportation for transit users, even when cars are still owned.

Projection of postgraduate students flow with a smoothing matrix transition diagram of Markov chain

NASA Astrophysics Data System (ADS)

Rahim, Rahela; Ibrahim, Haslinda; Adnan, Farah Adibah

2013-04-01

This paper presents a case study of modeling postgraduate students flow at the College of Art and Sciences, Universiti Utara Malaysia. First, full time postgraduate students and the semester they were in are identified. Then administrative data were used to estimate the transitions between these semesters for the year 2001-2005 periods. Markov chain model is developed to calculate the -5 and -10 years projection of postgraduate students flow at the college. The optimization question addressed in this study is 'Which transitions would sustain the desired structure in the dynamic situation such as trend towards graduation?' The smoothed transition probabilities are proposed to estimate the transition probabilities matrix of 16 × 16. The results shows that using smoothed transition probabilities, the projection number of postgraduate students enrolled in the respective semesters are closer to actual than using the conventional steady states transition probabilities.

Modeling temporal sequences of cognitive state changes based on a combination of EEG-engagement, EEG-workload, and heart rate metrics

PubMed Central

Stikic, Maja; Berka, Chris; Levendowski, Daniel J.; Rubio, Roberto F.; Tan, Veasna; Korszen, Stephanie; Barba, Douglas; Wurzer, David

2014-01-01

The objective of this study was to investigate the feasibility of physiological metrics such as ECG-derived heart rate and EEG-derived cognitive workload and engagement as potential predictors of performance on different training tasks. An unsupervised approach based on self-organizing neural network (NN) was utilized to model cognitive state changes over time. The feature vector comprised EEG-engagement, EEG-workload, and heart rate metrics, all self-normalized to account for individual differences. During the competitive training process, a linear topology was developed where the feature vectors similar to each other activated the same NN nodes. The NN model was trained and auto-validated on combat marksmanship training data from 51 participants that were required to make “deadly force decisions” in challenging combat scenarios. The trained NN model was cross validated using 10-fold cross-validation. It was also validated on a golf study in which additional 22 participants were asked to complete 10 sessions of 10 putts each. Temporal sequences of the activated nodes for both studies followed the same pattern of changes, demonstrating the generalization capabilities of the approach. Most node transition changes were local, but important events typically caused significant changes in the physiological metrics, as evidenced by larger state changes. This was investigated by calculating a transition score as the sum of subsequent state transitions between the activated NN nodes. Correlation analysis demonstrated statistically significant correlations between the transition scores and subjects' performances in both studies. This paper explored the hypothesis that temporal sequences of physiological changes comprise the discriminative patterns for performance prediction. These physiological markers could be utilized in future training improvement systems (e.g., through neurofeedback), and applied across a variety of training environments. PMID:25414629

Transit and lifespan in neutrophil production: implications for drug intervention.

PubMed

Câmara De Souza, Daniel; Craig, Morgan; Cassidy, Tyler; Li, Jun; Nekka, Fahima; Bélair, Jacques; Humphries, Antony R

2018-02-01

A comparison of the transit compartment ordinary differential equation modelling approach to distributed and discrete delay differential equation models is studied by focusing on Quartino's extension to the Friberg transit compartment model of myelosuppression, widely relied upon in the pharmaceutical sciences to predict the neutrophil response after chemotherapy, and on a QSP delay differential equation model of granulopoiesis. An extension to the Quartino model is provided by considering a general number of transit compartments and introducing an extra parameter that allows for the decoupling of the maturation time from the production rate of cells. An overview of the well established linear chain technique, used to reformulate transit compartment models with constant transit rates as distributed delay differential equations (DDEs), is then given. A state-dependent time rescaling of the Quartino model is performed to apply the linear chain technique and rewrite the Quartino model as a distributed DDE, yielding a discrete DDE model in a certain parameter limit. Next, stability and bifurcation analyses are undertaken in an effort to situate such studies in a mathematical pharmacology context. We show that both the original Friberg and the Quartino extension models incorrectly define the mean maturation time, essentially treating the proliferative pool as an additional maturation compartment. This misspecification can have far reaching consequences on the development of future models of myelosuppression in PK/PD.

Modeling the solid-liquid phase transition in saturated triglycerides

NASA Astrophysics Data System (ADS)

Pink, David A.; Hanna, Charles B.; Sandt, Christophe; MacDonald, Adam J.; MacEachern, Ronald; Corkery, Robert; Rousseau, Dérick

2010-02-01

We investigated theoretically two competing published scenarios for the melting transition of the triglyceride trilaurin (TL): those of (1) Corkery et al. [Langmuir 23, 7241 (2007)], in which the average state of each TL molecule in the liquid phase is a discotic "Y" conformer whose three chains are dynamically twisted, with an average angle of ˜120° between them, and those of (2) Cebula et al. [J. Am. Oil Chem. Soc. 69, 130 (1992)], in which the liquid-state conformation of the TL molecule in the liquid phase is a nematic h∗-conformer whose three chains are in a modified "chair" conformation. We developed two competing models for the two scenarios, in which TL molecules are in a nematic compact-chair (or "h") conformation, with extended, possibly all-trans, chains at low-temperatures, and in either a Y conformation or an h∗ conformation in the liquid state at temperatures higher than the phase-transition temperature, T∗=319 K. We defined an h-Y model as a realization of the proposal of Corkery et al. [Langmuir 23, 7241 (2007)], and explored its predictions by mapping it onto an Ising model in a temperature-dependent field, performing a mean-field approximation, and calculating the transition enthalpy ΔH. We found that the most plausible realization of the h-Y model, as applied to the solid-liquid phase transition in TL, and likely to all saturated triglycerides, gave a value of ΔH in reasonable agreement with the experiment. We then defined an alternative h-h∗ model as a realization of the proposal of Cebula et al. [J. Am. Oil Chem. Soc. 69, 130 (1992)], in which the liquid phase exhibits an average symmetry breaking similar to an h conformation, but with twisted chains, to see whether it could describe the TL phase transition. The h-h∗ model gave a value of ΔH that was too small by a factor of ˜3-4. We also predicted the temperature dependence of the 1132 cm-1 Raman band for both models, and performed measurements of the ratios of three TL Raman bands in the temperature range of -20 °C≤T ≤90 °C. The experimental results were in accord with the predictions of the h-Y model and support the proposal of Corkery et al. [Langmuir 23, 7241 (2007)] that the liquid state is made up of molecules that are each, on average, in a Y conformation. Finally, we carried out computer simulations of minimal-model TLs in the liquid phase, and concluded that although the individual TL molecules are, on average, Y conformers, long-range discotic order is unlikely to exist.

Teaching 1H NMR Spectrometry Using Computer Modeling.

ERIC Educational Resources Information Center

Habata, Yoichi; Akabori, Sadatoshi

2001-01-01

Molecular modeling by computer is used to display stereochemistry, molecular orbitals, structure of transition states, and progress of reactions. Describes new ideas for teaching 1H NMR spectroscopy using computer modeling. (Contains 12 references.) (ASK)

Behavioral transitions induced by speed and noise in animal aggregates

NASA Astrophysics Data System (ADS)

Cambui, Dorílson S.; Iliass, Tarras

2017-04-01

In this paper, we used a self-propelled particle model to study the transition between phases of collective behavior observed in animal aggregates. In these systems, transitions occur when individuals shift from one collective state to another. We investigated transitions induced by both the speed and the noise. Statistical quantities that characterize the phase transition driven by noise, such as order parameter, the Binder cumulant and the susceptibility were analyzed, and we used the finite-size scaling theory to estimate the critical exponent ratios β/ν and γ/ν.

Generic finite size scaling for discontinuous nonequilibrium phase transitions into absorbing states

NASA Astrophysics Data System (ADS)

de Oliveira, M. M.; da Luz, M. G. E.; Fiore, C. E.

2015-12-01

Based on quasistationary distribution ideas, a general finite size scaling theory is proposed for discontinuous nonequilibrium phase transitions into absorbing states. Analogously to the equilibrium case, we show that quantities such as response functions, cumulants, and equal area probability distributions all scale with the volume, thus allowing proper estimates for the thermodynamic limit. To illustrate these results, five very distinct lattice models displaying nonequilibrium transitions—to single and infinitely many absorbing states—are investigated. The innate difficulties in analyzing absorbing phase transitions are circumvented through quasistationary simulation methods. Our findings (allied to numerical studies in the literature) strongly point to a unifying discontinuous phase transition scaling behavior for equilibrium and this important class of nonequilibrium systems.

Superconductor-Insulator Transition in NbTiN Films

NASA Astrophysics Data System (ADS)

Burdastyh, M. V.; Postolova, S. V.; Baturina, T. I.; Proslier, T.; Vinokur, V. M.; Mironov, A. Yu.

2017-12-01

Experimental results indicating a direct disorder-induced superconductor-insulator transition in NbTiN thin films have been reported. It has been shown that an increase in the resistance per square in the normal state is accompanied by the suppression of the critical temperature of the superconducting transition T c according to the fermion mechanism of suppression of superconductivity by disorder. At the same time, the temperature of the Berezinskii-Kosterlitz-Thouless transition is completely suppressed at a nonzero critical temperature and, then, the ground state changes to insulating, which is characteristic of the boson model of suppression of superconductivity by disorder. It has been shown that the temperature dependences of the resistance of insulating films follow the Arrhenius activation law.

Improvement of driving safety in road traffic system

NASA Astrophysics Data System (ADS)

Li, Ke-Ping; Gao, Zi-You

2005-05-01

A road traffic system is a complex system in which humans participate directly. In this system, human factors play a very important role. In this paper, a kind of control signal is designated at a given site (i.e., signal point) of the road. Under the effect of the control signal, the drivers will decrease their velocities when their vehicles pass the signal point. Our aim is to transit the traffic flow states from disorder to order and then improve the traffic safety. We have tested this technique for the two-lane traffic model that is based on the deterministic Nagel-Schreckenberg (NaSch) traffic model. The simulation results indicate that the traffic flow states can be transited from disorder to order. Different order states can be observed in the system and these states are safer.

Reliability assessment of fiber optic communication lines depending on external factors and diagnostic errors

NASA Astrophysics Data System (ADS)

Bogachkov, I. V.; Lutchenko, S. S.

2018-05-01

The article deals with the method for the assessment of the fiber optic communication lines (FOCL) reliability taking into account the effect of the optical fiber tension, the temperature influence and the built-in diagnostic equipment errors of the first kind. The reliability is assessed in terms of the availability factor using the theory of Markov chains and probabilistic mathematical modeling. To obtain a mathematical model, the following steps are performed: the FOCL state is defined and validated; the state graph and system transitions are described; the system transition of states that occur at a certain point is specified; the real and the observed time of system presence in the considered states are identified. According to the permissible value of the availability factor, it is possible to determine the limiting frequency of FOCL maintenance.

Modeling habitat dynamics accounting for possible misclassification

USGS Publications Warehouse

Veran, Sophie; Kleiner, Kevin J.; Choquet, Remi; Collazo, Jaime; Nichols, James D.

2012-01-01

Land cover data are widely used in ecology as land cover change is a major component of changes affecting ecological systems. Landscape change estimates are characterized by classification errors. Researchers have used error matrices to adjust estimates of areal extent, but estimation of land cover change is more difficult and more challenging, with error in classification being confused with change. We modeled land cover dynamics for a discrete set of habitat states. The approach accounts for state uncertainty to produce unbiased estimates of habitat transition probabilities using ground information to inform error rates. We consider the case when true and observed habitat states are available for the same geographic unit (pixel) and when true and observed states are obtained at one level of resolution, but transition probabilities estimated at a different level of resolution (aggregations of pixels). Simulation results showed a strong bias when estimating transition probabilities if misclassification was not accounted for. Scaling-up does not necessarily decrease the bias and can even increase it. Analyses of land cover data in the Southeast region of the USA showed that land change patterns appeared distorted if misclassification was not accounted for: rate of habitat turnover was artificially increased and habitat composition appeared more homogeneous. Not properly accounting for land cover misclassification can produce misleading inferences about habitat state and dynamics and also misleading predictions about species distributions based on habitat. Our models that explicitly account for state uncertainty should be useful in obtaining more accurate inferences about change from data that include errors.

State transitions of GRS 1739-278 in the 2014 outburst

NASA Astrophysics Data System (ADS)

Wang, Sili; Kawai, Nobuyuki; Shidatsu, Megumi; Tachibana, Yutaro; Yoshii, Taketoshi; Sudo, Masayuki; Kubota, Aya

2018-05-01

We report on the X-ray spectral analysis and time evolution of GRS 1739-278 during its 2014 outburst, based on MAXI/GSC and Swift/XRT observations. Over the course of the outburst, a transition from the low/hard state to the high/soft state and then back to the low/hard state was seen. During the high/soft state, the innermost disk temperature mildly decreased, while the innermost radius estimated with the multi-color disk model remained constant at ˜18 (D/8.5 kpc)(cos i/cos 30°)-1/2 km, where D is the source distance and i is the inclination of observation. This small innermost radius of the accretion disk suggests that the central object is more likely to be a Kerr black hole rather than a Schwardzschild black hole. Applying a relativistic disk emission model to the high/soft state spectra, a mass upper limit of 18.3 M⊙ was obtained based on the inclination limit i < 60° for an assumed distance of 8.5 kpc. Using the empirical relation of the transition luminosity to the Eddington limit, the mass is constrained to 4.0-18.3 M⊙ for the same distance. The mass can be further constrained to be no larger than 9.5 M⊙ by adopting the constraints based on the fits to the NuSTAR spectra with relativistically blurred disk reflection models (Miller et al. 2015, ApJ, 799, L6).

Hysteresis, phase transitions, and dangerous transients in electrical power distribution systems

NASA Astrophysics Data System (ADS)

Duclut, Charlie; Backhaus, Scott; Chertkov, Michael

2013-06-01

The majority of dynamical studies in power systems focus on the high-voltage transmission grids where models consider large generators interacting with crude aggregations of individual small loads. However, new phenomena have been observed indicating that the spatial distribution of collective, nonlinear contribution of these small loads in the low-voltage distribution grid is crucial to the outcome of these dynamical transients. To elucidate the phenomenon, we study the dynamics of voltage and power flows in a spatially extended distribution feeder (circuit) connecting many asynchronous induction motors and discover that this relatively simple 1+1 (space+time) dimensional system exhibits a plethora of nontrivial spatiotemporal effects, some of which may be dangerous for power system stability. Long-range motor-motor interactions mediated by circuit voltage and electrical power flows result in coexistence and segregation of spatially extended phases defined by individual motor states, a “normal” state where the motors’ mechanical (rotation) frequency is slightly smaller than the nominal frequency of the basic ac flows and a “stalled” state where the mechanical frequency is small. Transitions between the two states can be initiated by a perturbation of the voltage or base frequency at the head of the distribution feeder. Such behavior is typical of first-order phase transitions in physics, and this 1+1 dimensional model shows many other properties of a first-order phase transition with the spatial distribution of the motors’ mechanical frequency playing the role of the order parameter. In particular, we observe (a) propagation of the phase-transition front with the constant speed (in very long feeders) and (b) hysteresis in transitions between the normal and stalled (or partially stalled) phases.

Relationship of Topology, Multiscale Phase Synchronization, and State Transitions in Human Brain Networks

PubMed Central

Kim, Minkyung; Kim, Seunghwan; Mashour, George A.; Lee, UnCheol

2017-01-01

How the brain reconstitutes consciousness and cognition after a major perturbation like general anesthesia is an important question with significant neuroscientific and clinical implications. Recent empirical studies in animals and humans suggest that the recovery of consciousness after anesthesia is not random but ordered. Emergence patterns have been classified as progressive and abrupt transitions from anesthesia to consciousness, with associated differences in duration and electroencephalogram (EEG) properties. We hypothesized that the progressive and abrupt emergence patterns from the unconscious state are associated with, respectively, continuous and discontinuous synchronization transitions in functional brain networks. The discontinuous transition is explainable with the concept of explosive synchronization, which has been studied almost exclusively in network science. We used the Kuramato model, a simple oscillatory network model, to simulate progressive and abrupt transitions in anatomical human brain networks acquired from diffusion tensor imaging (DTI) of 82 brain regions. To facilitate explosive synchronization, distinct frequencies for hub nodes with a large frequency disassortativity (i.e., higher frequency nodes linking with lower frequency nodes, or vice versa) were applied to the brain network. In this simulation study, we demonstrated that both progressive and abrupt transitions follow distinct synchronization processes at the individual node, cluster, and global network levels. The characteristic synchronization patterns of brain regions that are “progressive and earlier” or “abrupt but delayed” account for previously reported behavioral responses of gradual and abrupt emergence from the unconscious state. The characteristic network synchronization processes observed at different scales provide new insights into how regional brain functions are reconstituted during progressive and abrupt emergence from the unconscious state. This theoretical approach also offers a principled explanation of how the brain reconstitutes consciousness and cognitive functions after physiologic (sleep), pharmacologic (anesthesia), and pathologic (coma) perturbations. PMID:28713258

Relationship of Topology, Multiscale Phase Synchronization, and State Transitions in Human Brain Networks.

PubMed

Kim, Minkyung; Kim, Seunghwan; Mashour, George A; Lee, UnCheol

2017-01-01

How the brain reconstitutes consciousness and cognition after a major perturbation like general anesthesia is an important question with significant neuroscientific and clinical implications. Recent empirical studies in animals and humans suggest that the recovery of consciousness after anesthesia is not random but ordered. Emergence patterns have been classified as progressive and abrupt transitions from anesthesia to consciousness, with associated differences in duration and electroencephalogram (EEG) properties. We hypothesized that the progressive and abrupt emergence patterns from the unconscious state are associated with, respectively, continuous and discontinuous synchronization transitions in functional brain networks. The discontinuous transition is explainable with the concept of explosive synchronization, which has been studied almost exclusively in network science. We used the Kuramato model, a simple oscillatory network model, to simulate progressive and abrupt transitions in anatomical human brain networks acquired from diffusion tensor imaging (DTI) of 82 brain regions. To facilitate explosive synchronization, distinct frequencies for hub nodes with a large frequency disassortativity (i.e., higher frequency nodes linking with lower frequency nodes, or vice versa) were applied to the brain network. In this simulation study, we demonstrated that both progressive and abrupt transitions follow distinct synchronization processes at the individual node, cluster, and global network levels. The characteristic synchronization patterns of brain regions that are "progressive and earlier" or "abrupt but delayed" account for previously reported behavioral responses of gradual and abrupt emergence from the unconscious state. The characteristic network synchronization processes observed at different scales provide new insights into how regional brain functions are reconstituted during progressive and abrupt emergence from the unconscious state. This theoretical approach also offers a principled explanation of how the brain reconstitutes consciousness and cognitive functions after physiologic (sleep), pharmacologic (anesthesia), and pathologic (coma) perturbations.

Hysteresis, phase transitions, and dangerous transients in electrical power distribution systems.

PubMed

Duclut, Charlie; Backhaus, Scott; Chertkov, Michael

2013-06-01

The majority of dynamical studies in power systems focus on the high-voltage transmission grids where models consider large generators interacting with crude aggregations of individual small loads. However, new phenomena have been observed indicating that the spatial distribution of collective, nonlinear contribution of these small loads in the low-voltage distribution grid is crucial to the outcome of these dynamical transients. To elucidate the phenomenon, we study the dynamics of voltage and power flows in a spatially extended distribution feeder (circuit) connecting many asynchronous induction motors and discover that this relatively simple 1+1 (space+time) dimensional system exhibits a plethora of nontrivial spatiotemporal effects, some of which may be dangerous for power system stability. Long-range motor-motor interactions mediated by circuit voltage and electrical power flows result in coexistence and segregation of spatially extended phases defined by individual motor states, a "normal" state where the motors' mechanical (rotation) frequency is slightly smaller than the nominal frequency of the basic ac flows and a "stalled" state where the mechanical frequency is small. Transitions between the two states can be initiated by a perturbation of the voltage or base frequency at the head of the distribution feeder. Such behavior is typical of first-order phase transitions in physics, and this 1+1 dimensional model shows many other properties of a first-order phase transition with the spatial distribution of the motors' mechanical frequency playing the role of the order parameter. In particular, we observe (a) propagation of the phase-transition front with the constant speed (in very long feeders) and (b) hysteresis in transitions between the normal and stalled (or partially stalled) phases.

Study of anyon condensation and topological phase transitions from a Z4 topological phase using the projected entangled pair states approach

NASA Astrophysics Data System (ADS)

Iqbal, Mohsin; Duivenvoorden, Kasper; Schuch, Norbert

2018-05-01

We use projected entangled pair states (PEPS) to study topological quantum phase transitions. The local description of topological order in the PEPS formalism allows us to set up order parameters which measure condensation and deconfinement of anyons and serve as substitutes for conventional order parameters. We apply these order parameters, together with anyon-anyon correlation functions and some further probes, to characterize topological phases and phase transitions within a family of models based on a Z4 symmetry, which contains Z4 quantum double, toric code, double semion, and trivial phases. We find a diverse phase diagram which exhibits a variety of different phase transitions of both first and second order which we comprehensively characterize, including direct transitions between the toric code and the double semion phase.

On Mechanical Transitions in Biologically Motivated Soft Matter Systems

NASA Astrophysics Data System (ADS)

Fogle, Craig

The notion of phase transitions as a characterization of a change in physical properties pervades modern physics. Such abrupt and fundamental changes in the behavior of physical systems are evident in condensed matter system and also occur in nuclear and subatomic settings. While this concept is less prevalent in the field of biology, recent advances have pointed to its relevance in a number of settings. Recent studies have modeled both the cell cycle and cancer as phase transition in physical systems. In this dissertation we construct simplified models for two biological systems. As described by those models, both systems exhibit phase transitions. The first model is inspired by the shape transition in the nuclei of neutrophils during differentiation. During differentiation the nucleus transitions from spherical to a shape often described as "beads on a string." As a simplified model of this system, we investigate the spherical-to-wrinkled transition in an elastic core bounded to a fluid shell system. We find that this model exhibits a first-order phase transition, and the shape that minimizes the energy of the system scales as (micror3/kappa). . The second system studied is motivated by the dynamics of globular proteins. These proteins may undergoes conformational changes with large displacements relative to their size. Transitions between conformational states are not possible if the dynamics are governed strictly by linear elasticity. We construct a model consisting of an predominantly elastic region near the energetic minimum of the system and a non-linear softening of the system at a critical displacement. We find that this simple model displays very rich dynamics include a sharp dynamical phase transition and driving-force-dependent symmetry breaking.

Combination of Markov state models and kinetic networks for the analysis of molecular dynamics simulations of peptide folding.

PubMed

Radford, Isolde H; Fersht, Alan R; Settanni, Giovanni

2011-06-09

Atomistic molecular dynamics simulations of the TZ1 beta-hairpin peptide have been carried out using an implicit model for the solvent. The trajectories have been analyzed using a Markov state model defined on the projections along two significant observables and a kinetic network approach. The Markov state model allowed for an unbiased identification of the metastable states of the system, and provided the basis for commitment probability calculations performed on the kinetic network. The kinetic network analysis served to extract the main transition state for folding of the peptide and to validate the results from the Markov state analysis. The combination of the two techniques allowed for a consistent and concise characterization of the dynamics of the peptide. The slowest relaxation process identified is the exchange between variably folded and denatured species, and the second slowest process is the exchange between two different subsets of the denatured state which could not be otherwise identified by simple inspection of the projected trajectory. The third slowest process is the exchange between a fully native and a partially folded intermediate state characterized by a native turn with a proximal backbone H-bond, and frayed side-chain packing and termini. The transition state for the main folding reaction is similar to the intermediate state, although a more native like side-chain packing is observed.

Transition between Functional Regimes in an Integrate-And-Fire Network Model of the Thalamus

PubMed Central

Barardi, Alessandro; Mazzoni, Alberto

2016-01-01

The thalamus is a key brain element in the processing of sensory information. During the sleep and awake states, this brain area is characterized by the presence of two distinct dynamical regimes: in the sleep state activity is dominated by spindle oscillations (7 − 15 Hz) weakly affected by external stimuli, while in the awake state the activity is primarily driven by external stimuli. Here we develop a simple and computationally efficient model of the thalamus that exhibits two dynamical regimes with different information-processing capabilities, and study the transition between them. The network model includes glutamatergic thalamocortical (TC) relay neurons and GABAergic reticular (RE) neurons described by adaptive integrate-and-fire models in which spikes are induced by either depolarization or hyperpolarization rebound. We found a range of connectivity conditions under which the thalamic network composed by these neurons displays the two aforementioned dynamical regimes. Our results show that TC-RE loops generate spindle-like oscillations and that a minimum level of clustering (i.e. local connectivity density) in the RE-RE connections is necessary for the coexistence of the two regimes. We also observe that the transition between the two regimes occurs when the external excitatory input on TC neurons (mimicking sensory stimulation) is large enough to cause a significant fraction of them to switch from hyperpolarization-rebound-driven firing to depolarization-driven firing. Overall, our model gives a novel and clear description of the role that the two types of neurons and their connectivity play in the dynamical regimes observed in the thalamus, and in the transition between them. These results pave the way for the development of efficient models of the transmission of sensory information from periphery to cortex. PMID:27598260

Charge-patterning phase transition on a surface lattice of titratable sites adjacent to an electrolyte solution

NASA Astrophysics Data System (ADS)

Shore, Joel; Thurston, George

We discuss a model for a charge-patterning phase transition on a two-dimensional square lattice of titratable sites, here regarded as protonation sites, placed on a square lattice in a dielectric medium just below the planar interface between this medium and an aqueous salt solution. Within Debye-Huckel theory, the analytical form of the electrostatic repulsion between protonated sites exhibits an approximate inverse cubic power-law decrease beyond short distances. The problem can thus be mapped onto the two-dimensional antiferromagnetic Ising model with this longer-range interaction, which we study with Monte Carlo simulations. As we increase pH, the occupation probability of a site decreases from 1 at low pH to 0 at high pH. For sufficiently-strong interaction strengths, a phase transition occurs as the occupation probability of 1/2 is approached: the charges arrange themselves into a checkerboard pattern. This ordered phase persists over a range of pH until a transition occurs back to a disordered state. This state is the analogue of the Neel state in the antiferromagnetic Ising spin model. More complicated ordered phases are expected for sufficiently strong interactions (with occupation probabilities of 1/4 and 3/4) and if the lattice is triangular rather than square. This work was supported by NIH EY018249 (GMT).

Mechanical Metamaterials with Negative Compressibility Transitions

NASA Astrophysics Data System (ADS)

Motter, Adilson

2015-03-01

When tensioned, ordinary materials expand along the direction of the applied force. In this presentation, I will explore network concepts to design metamaterials exhibiting negative compressibility transitions, during which the material undergoes contraction when tensioned (or expansion when pressured). Such transitions, which are forbidden in thermodynamic equilibrium, are possible during the decay of metastable, super-strained states. I will introduce a statistical physics theory for negative compressibility transitions, derive a first-principles model to predict these transitions, and present a validation of the model using molecular dynamics simulations. Aside from its immediate mechanical implications, our theory points to a wealth of analogous inverted responses, such as inverted susceptibility or heat-capacity transitions, allowed when considering realistic scales. This research was done in collaboration with Zachary Nicolaou, and was supported by the National Science Foundation and the Alfred P. Sloan Foundation.

Dislocation dynamics modelling of the ductile-brittle-transition

NASA Astrophysics Data System (ADS)

Hennecke, Thomas; Hähner, Peter

2009-07-01

Many materials like silicon, tungsten or ferritic steels show a transition between high temperature ductile fracture with stable crack grow and high deformation energy absorption and low temperature brittle fracture in an unstable and low deformation mode, the ductile-brittle-transition. Especially in steels, the temperature transition is accompanied by a strong increase of the measured fracture toughness over a certain temperature range and strong scatter in the toughness data in this transition regime. The change in fracture modes is affected by dynamic interactions between dislocations and the inhomogeneous stress fields of notches and small cracks. In the present work a dislocation dynamics model for the ductile-brittle-transition is proposed, which takes those interactions into account. The model can explain an increase with temperature of apparent toughness in the quasi-brittle regime and different levels of scatter in the different temperature regimes. Furthermore it can predict changing failure sites in materials with heterogeneous microstructure. Based on the model, the effects of crack tip blunting, stress state, external strain rate and irradiation-induced changes in the plastic flow properties can be discussed.

Viewing brain processes as Critical State Transitions across levels of organization: Neural events in Cognition and Consciousness, and general principles.

PubMed

Werner, Gerhard

2009-04-01

In this theoretical and speculative essay, I propose that insights into certain aspects of neural system functions can be gained from viewing brain function in terms of the branch of Statistical Mechanics currently referred to as "Modern Critical Theory" [Stanley, H.E., 1987. Introduction to Phase Transitions and Critical Phenomena. Oxford University Press; Marro, J., Dickman, R., 1999. Nonequilibrium Phase Transitions in Lattice Models. Cambridge University Press, Cambridge, UK]. The application of this framework is here explored in two stages: in the first place, its principles are applied to state transitions in global brain dynamics, with benchmarks of Cognitive Neuroscience providing the relevant empirical reference points. The second stage generalizes to suggest in more detail how the same principles could also apply to the relation between other levels of the structural-functional hierarchy of the nervous system and between neural assemblies. In this view, state transitions resulting from the processing at one level are the input to the next, in the image of a 'bucket brigade', with the content of each bucket being passed on along the chain, after having undergone a state transition. The unique features of a process of this kind will be discussed and illustrated.

On the magnetic circular dichroism of benzene. A density-functional study

NASA Astrophysics Data System (ADS)

Kaminský, Jakub; Kříž, Jan; Bouř, Petr

2017-04-01

Spectroscopy of magnetic circular dichroism (MCD) provides enhanced information on molecular structure and a more reliable assignment of spectral bands than absorption alone. Theoretical modeling can significantly enhance the information obtained from experimental spectra. In the present study, the time dependent density functional theory is employed to model the lowest-energy benzene transitions, in particular to investigate the role of the Rydberg states and vibrational interference in spectral intensities. The effect of solvent is explored on model benzene-methane clusters. For the lowest-energy excitation, the vibrational sub-structure of absorption and MCD spectra is modeled within the harmonic approximation, providing a very good agreement with the experiment. The simulations demonstrate that the Rydberg states have a much stronger effect on the MCD intensities than on the absorption, and a very diffuse basis set must be used to obtain reliable results. The modeling also indicates that the Rydberg-like states and associated transitions may persist in solutions. Continuum-like solvent models are thus not suitable for their modeling; solvent-solute clusters appear to be more appropriate, providing they are large enough.

General methods for sensitivity analysis of equilibrium dynamics in patch occupancy models

USGS Publications Warehouse

Miller, David A.W.

2012-01-01

Sensitivity analysis is a useful tool for the study of ecological models that has many potential applications for patch occupancy modeling. Drawing from the rich foundation of existing methods for Markov chain models, I demonstrate new methods for sensitivity analysis of the equilibrium state dynamics of occupancy models. Estimates from three previous studies are used to illustrate the utility of the sensitivity calculations: a joint occupancy model for a prey species, its predators, and habitat used by both; occurrence dynamics from a well-known metapopulation study of three butterfly species; and Golden Eagle occupancy and reproductive dynamics. I show how to deal efficiently with multistate models and how to calculate sensitivities involving derived state variables and lower-level parameters. In addition, I extend methods to incorporate environmental variation by allowing for spatial and temporal variability in transition probabilities. The approach used here is concise and general and can fully account for environmental variability in transition parameters. The methods can be used to improve inferences in occupancy studies by quantifying the effects of underlying parameters, aiding prediction of future system states, and identifying priorities for sampling effort.

Cystic fibrosis: addressing the transition from pediatric to adult-oriented health care.

PubMed

Kreindler, James L; Miller, Victoria A

2013-12-11

Survival for patients with cystic fibrosis (CF) increased to nearly 40 years in 2012 from the early childhood years in the 1940s. Therefore, patients are living long enough to require transition from pediatric CF centers to adult CF centers. The goal of transition is for the young adult to be engaged in the adult health care system in ways that optimize health, maximize potential, and increase quality of life. A successful transition promotes autonomy and responsibility with respect to one's own health. Currently, there is an information gap in the literature with respect to psychological models that can help guide informed transition processes. In this review, we establish the framework in which transition exists in CF; we review some of the published literature from the last 20 years of experience with transition in CF centers around the world; and we discuss psychological models of pediatric illness that can help to explain the current state of transition to adult-oriented care from pediatric-oriented care and help to formulate new models of ascertaining readiness for transition. Finally, we look at our current knowledge gaps and opportunities for future research endeavors.

Computational Analysis of Stereospecificity in the Cope Rearrangement

ERIC Educational Resources Information Center

Glish, Laura; Hanks, Timothy W.

2007-01-01

The Cope rearrangement is a highly stereospecific, concerted reaction of considerable synthetic utility. Experimental product distributions from the reaction of disubstituted 1,5-hexadienes can be readily understood by computer modeling of the various possible transitions states. Semi-empirical methods give relative energies of transition states…

Causal Role of Thalamic Interneurons in Brain State Transitions: A Study Using a Neural Mass Model Implementing Synaptic Kinetics

PubMed Central

Bhattacharya, Basabdatta Sen; Bond, Thomas P.; O'Hare, Louise; Turner, Daniel; Durrant, Simon J.

2016-01-01

Experimental studies on the Lateral Geniculate Nucleus (LGN) of mammals and rodents show that the inhibitory interneurons (IN) receive around 47.1% of their afferents from the retinal spiking neurons, and constitute around 20–25% of the LGN cell population. However, there is a definite gap in knowledge about the role and impact of IN on thalamocortical dynamics in both experimental and model-based research. We use a neural mass computational model of the LGN with three neural populations viz. IN, thalamocortical relay (TCR), thalamic reticular nucleus (TRN), to study the causality of IN on LGN oscillations and state-transitions. The synaptic information transmission in the model is implemented with kinetic modeling, facilitating the linking of low-level cellular attributes with high-level population dynamics. The model is parameterized and tuned to simulate alpha (8–13 Hz) rhythm that is dominant in both Local Field Potential (LFP) of LGN and electroencephalogram (EEG) of visual cortex in an awake resting state with eyes closed. The results show that: First, the response of the TRN is suppressed in the presence of IN in the circuit; disconnecting the IN from the circuit effects a dramatic change in the model output, displaying high amplitude synchronous oscillations within the alpha band in both TCR and TRN. These observations conform to experimental reports implicating the IN as the primary inhibitory modulator of LGN dynamics in a cognitive state, and that reduced cognition is achieved by suppressing the TRN response. Second, the model validates steady state visually evoked potential response in humans corresponding to periodic input stimuli; however, when the IN is disconnected from the circuit, the output power spectra do not reflect the input frequency. This agrees with experimental reports underpinning the role of IN in efficient retino-geniculate information transmission. Third, a smooth transition from alpha to theta band is observed by progressive decrease of neurotransmitter concentrations in the synaptic clefts; however, the transition is abrupt with removal of the IN circuitry in the model. The results imply a role of IN toward maintaining homeostasis in the LGN by suppressing any instability that may arise due to anomalous synaptic attributes. PMID:27899890

Evolution of E 2 transition strength in deformed hafnium isotopes from new measurements on 172Hf,174Hf, and 176Hf

NASA Astrophysics Data System (ADS)

Rudigier, M.; Nomura, K.; Dannhoff, M.; Gerst, R.-B.; Jolie, J.; Saed-Samii, N.; Stegemann, S.; Régis, J.-M.; Robledo, L. M.; Rodríguez-Guzmán, R.; Blazhev, A.; Fransen, Ch.; Warr, N.; Zell, K. O.

2015-04-01

Background: The available data for E 2 transition strengths in the region between neutron-deficient hafnium and platinum isotopes are far from complete. More and precise data are needed to enhance the picture of structure evolution in this region and to test state-of-the-art nuclear models. In a simple model, the maximum collectivity is expected at the middle of the major shell. However, for actual nuclei, particularly in heavy-mass regions, which should be highly complex, this picture may no longer be the case, and one should use a more realistic nuclear-structure model. We address this point by studying the spectroscopy of Hf as a representative case. Purpose: We remeasure the 21+ half-lives of 172,174,176Hf, for which there is some disagreement in the literature. The main goal is to measure, for the first time, the half-lives of higher-lying states of the rotational band. The new results are compared to a theoretical calculation for absolute transition strengths. Method: The half-lives were measured using γ -γ and conversion-electron-γ delayed coincidences with the fast timing method. For the determination of half-lives in the picosecond region, the generalized centroid difference method was applied. For the theoretical calculation of the spectroscopic properties, the interacting boson model is employed, whose Hamiltonian is determined based on microscopic energy-density functional calculations. Results: The measured 21+ half-lives disagree with results from earlier γ -γ fast timing measurements, but are in agreement with data from Coulomb excitation experiments and other methods. Half-lives of the 41+ and 61+ states were measured, as well as a lower limit for the 81+ states. Conclusions: This work shows the importance of a mass-dependent effective boson charge in the interacting boson model for the description of E 2 transition rates in chains of nuclei. It encourages further studies of the microscopic origin of this mass dependence. New experimental values on transition rates in nuclei from neighboring isotopic chains could support these studies.

Transition States and transition state analogue interactions with enzymes.

PubMed

Schramm, Vern L

2015-04-21

Enzymatic transition states have lifetimes of a few femtoseconds (fs). Computational analysis of enzyme motions leading to transition state formation suggests that local catalytic site motions on the fs time scale provide the mechanism to locate transition states. An experimental test of protein fs motion and its relation to transition state formation can be provided by isotopically heavy proteins. Heavy enzymes have predictable mass-altered bond vibration states without altered electrostatic properties, according to the Born-Oppenheimer approximation. On-enzyme chemistry is slowed in most heavy proteins, consistent with altered protein bond frequencies slowing the search for the transition state. In other heavy enzymes, structural changes involved in reactant binding and release are also influenced. Slow protein motions associated with substrate binding and catalytic site preorganization are essential to allow the subsequent fs motions to locate the transition state and to facilitate the efficient release of products. In the catalytically competent geometry, local groups move in stochastic atomic motion on the fs time scale, within transition state-accessible conformations created by slower protein motions. The fs time scale for the transition state motions does not permit thermodynamic equilibrium between the transition state and stable enzyme states. Isotopically heavy enzymes provide a diagnostic tool for fast coupled protein motions to transition state formation and mass-dependent conformational changes. The binding of transition state analogue inhibitors is the opposite in catalytic time scale to formation of the transition state but is related by similar geometries of the enzyme-transition state and enzyme-inhibitor interactions. While enzymatic transition states have lifetimes as short as 10(-15) s, transition state analogues can bind tightly to enzymes with release rates greater than 10(3) s. Tight-binding transition state analogues stabilize the rare but evolved enzymatic geometry to form the transition state. Evolution to efficient catalysis optimized this geometry and its stabilization by a transition state mimic results in tight binding. Release rates of transition state analogues are orders of magnitude slower than product release in normal catalytic function. During catalysis, product release is facilitated by altered chemistry. Compared to the weak associations found in Michaelis complexes, transition state analogues involve strong interactions related to those in the transition state. Optimum binding of transition state analogues occurs when the complex retains the system motions intrinsic to transition state formation. Conserved dynamic motion retains the entropic components of inhibitor complexes, improving the thermodynamics of analogue binding.

Deformation of the proton emitter 113Cs from electromagnetic transition and proton-emission rates

NASA Astrophysics Data System (ADS)

Hodge, D.; Cullen, D. M.; Taylor, M. J.; Nara Singh, B. S.; Ferreira, L. S.; Maglione, E.; Smith, J. F.; Scholey, C.; Rahkila, P.; Grahn, T.; Braunroth, T.; Badran, H.; Capponi, L.; Girka, A.; Greenlees, P. T.; Julin, R.; Konki, J.; Mallaburn, M.; Nefodov, O.; O'Neill, G. G.; Pakarinen, J.; Papadakis, P.; Partanen, J.; Ruotsalainen, P.; Sandzelius, M.; Sarén, J.; Smolen, M.; Sorri, J.; Stolze, S.; Uusitalo, J.

2016-09-01

The lifetime of the (11 /2+ ) state in the band above the proton-emitting (3 /2+ ) state in 113Cs has been measured to be τ =24 (6 ) ps from a recoil-decay-tagged differential-plunger experiment. The measured lifetime was used to deduce the deformation of the states using wave functions from a nonadiabatic quasiparticle model to independently calculate both proton-emission and electromagnetic γ -ray transition rates as a function of deformation. The only quadrupole deformation, which was able to reproduce the experimental excitation energies of the states, the electromagnetic decay rate of the (11 /2+ ) state and the proton-emission rate of the (3 /2+ ) state, was found to be β2=0.22 (6 ) . This deformation is in agreement with the earlier proton emission studies which concluded that 113Cs was best described as a deformed proton emitter, however, it is now more firmly supported by the present measurement of the electromagnetic transition rate.

Modeling personnel turnover in the parametric organization

NASA Technical Reports Server (NTRS)

Dean, Edwin B.

1991-01-01

A model is developed for simulating the dynamics of a newly formed organization, credible during all phases of organizational development. The model development process is broken down into the activities of determining the tasks required for parametric cost analysis (PCA), determining the skills required for each PCA task, determining the skills available in the applicant marketplace, determining the structure of the model, implementing the model, and testing it. The model, parameterized by the likelihood of job function transition, has demonstrated by the capability to represent the transition of personnel across functional boundaries within a parametric organization using a linear dynamical system, and the ability to predict required staffing profiles to meet functional needs at the desired time. The model can be extended by revisions of the state and transition structure to provide refinements in functional definition for the parametric and extended organization.

Influence of molecular designs on polaronic and vibrational transitions in a conjugated push-pull copolymer

NASA Astrophysics Data System (ADS)

Cobet, Christoph; Gasiorowski, Jacek; Menon, Reghu; Hingerl, Kurt; Schlager, Stefanie; White, Matthew S.; Neugebauer, Helmut; Sariciftci, N. Serdar; Stadler, Philipp

2016-10-01

Electron-phonon interactions of free charge-carriers in doped pi-conjugated polymers are conceptually described by 1-dimensional (1D) delocalization. Thereby, polaronic transitions fit the 1D-Froehlich model in quasi-confined chains. However, recent developments in conjugated polymers have diversified the backbones to become elaborate heterocylcic macromolecules. Their complexity makes it difficult to investigate the electron-phonon coupling. In this work we resolve the electron-phonon interactions in the ground and doped state in a complex push-pull polymer. We focus on the polaronic transitions using in-situ spectroscopy to work out the differences between single-unit and push-pull systems to obtain the desired structural- electronic correlations in the doped state. We apply the classic 1D-Froehlich model to generate optical model fits. Interestingly, we find the 1D-approach in push-pull polarons in agreement to the model, pointing at the strong 1D-character and plain electronic structure of the push-pull structure. In contrast, polarons in the single-unit polymer emerge to a multi- dimensional problem difficult to resolve due to their anisotropy. Thus, we report an enhancement of the 1D-character by the push-pull concept in the doped state - an important view in light of the main purpose of push-pull polymers for photovoltaic devices.

Hidden Markov models reveal complexity in the diving behaviour of short-finned pilot whales

PubMed Central

Quick, Nicola J.; Isojunno, Saana; Sadykova, Dina; Bowers, Matthew; Nowacek, Douglas P.; Read, Andrew J.

2017-01-01

Diving behaviour of short-finned pilot whales is often described by two states; deep foraging and shallow, non-foraging dives. However, this simple classification system ignores much of the variation that occurs during subsurface periods. We used multi-state hidden Markov models (HMM) to characterize states of diving behaviour and the transitions between states in short-finned pilot whales. We used three parameters (number of buzzes, maximum dive depth and duration) measured in 259 dives by digital acoustic recording tags (DTAGs) deployed on 20 individual whales off Cape Hatteras, North Carolina, USA. The HMM identified a four-state model as the best descriptor of diving behaviour. The state-dependent distributions for the diving parameters showed variation between states, indicative of different diving behaviours. Transition probabilities were considerably higher for state persistence than state switching, indicating that dive types occurred in bouts. Our results indicate that subsurface behaviour in short-finned pilot whales is more complex than a simple dichotomy of deep and shallow diving states, and labelling all subsurface behaviour as deep dives or shallow dives discounts a significant amount of important variation. We discuss potential drivers of these patterns, including variation in foraging success, prey availability and selection, bathymetry, physiological constraints and socially mediated behaviour. PMID:28361954

Isospin symmetry of Tz =±3/2→±1/2 Gamow-Teller transitions in A=41 nuclei

NASA Astrophysics Data System (ADS)

Fujita, Y.; Shimbara, Y.; Adachi, T.; Berg, G. P.; Brown, B. A.; Fujita, H.; Hatanaka, K.; Kamiya, J.; Nakanishi, K.; Sakemi, Y.; Sasaki, S.; Shimizu, Y.; Tameshige, Y.; Uchida, M.; Wakasa, T.; Yosoi, M.

2004-11-01

Under the assumption that isospin T is a good quantum number, isobaric analog states and various analogous transitions are expected in isobars with mass number A . The strengths of Tz =±3/2→±1/2 analogous Gamow-Teller (GT) transitions and analogous M1 transitions within the A=41 isobar quartet are compared in detail. The Tz =+3/2→+1/2 GT transitions from the Jπ = 3/2+ ground state of 41K leading to excited Jπ = 1/2+ , 3/2+ , and 5/2+ states in 41Ca were measured using the ( 3He ,t) charge-exchange reaction. With a high energy resolution of 35 keV , many fragmented states were observed, and the GT strength distribution was determined up to 10 MeV excitation energy ( Ex ) . The main part of the strength was concentrated in the Ex =4 6 MeV region. A shell-model calculation could reproduce the concentration, but not so well details of the strength distribution. The obtained distribution was further compared with two results of 41Ti β decay studying the analogous Tz =-3/2→-1/2 GT strengths. They reported contradicting distributions. One-to-one correspondences of analogous transitions and analog states were assigned up to Ex =6 MeV in the comparison with one of these 41Ti β -decay results. Combining the spectroscopic information of the analog states in 41Ca and 41Sc , the most probable Jπ values were deduced for each pair of analog states. It was found that 5/2+ states carry the main part of the observed GT strength, while much less GT strength was carried by 1/2+ and 3/2+ states. The gross features of the GT strength distributions for each J were similar for the isospin analogous Tz =±3/2→±1/2 transitions, but the details were somewhat different. From the difference of the distributions, isospin-asymmetry matrix elements of ≈8 keV were deduced. The Coulomb displacement energy, which is sensitive to the configuration of states, showed a sudden increase of about 50 keV at the excitation energy of 3.8 MeV . The strengths of several M1 transitions to the IAS in 41Ca were compared with the strengths of analogous GT transitions. It was found that ratios of the M1 and GT transition strengths were similar, suggesting that the contributions of the ℓτ term in M1 transitions are small.

Swimming trajectories of a three-sphere microswimmer near a wall

NASA Astrophysics Data System (ADS)

Daddi-Moussa-Ider, Abdallah; Lisicki, Maciej; Hoell, Christian; Löwen, Hartmut

2018-04-01

The hydrodynamic flow field generated by self-propelled active particles and swimming microorganisms is strongly altered by the presence of nearby boundaries in a viscous flow. Using a simple model three-linked sphere swimmer, we show that the swimming trajectories near a no-slip wall reveal various scenarios of motion depending on the initial orientation and the distance separating the swimmer from the wall. We find that the swimmer can either be trapped by the wall, completely escape, or perform an oscillatory gliding motion at a constant mean height above the wall. Using a far-field approximation, we find that, at leading order, the wall-induced correction has a source-dipolar or quadrupolar flow structure where the translational and angular velocities of the swimmer decay as inverse third and fourth powers with distance from the wall, respectively. The resulting equations of motion for the trajectories and the relevant order parameters fully characterize the transition between the states and allow for an accurate description of the swimming behavior near a wall. We demonstrate that the transition between the trapping and oscillatory gliding states is first order discontinuous, whereas the transition between the trapping and escaping states is continuous, characterized by non-trivial scaling exponents of the order parameters. In order to model the circular motion of flagellated bacteria near solid interfaces, we further assume that the spheres can undergo rotational motion around the swimming axis. We show that the general three-dimensional motion can be mapped onto a quasi-two-dimensional representational model by an appropriate redefinition of the order parameters governing the transition between the swimming states.

Combining multistate capture-recapture data with tag recoveries to estimate demographic parameters

USGS Publications Warehouse

Kendall, W.L.; Conn, P.B.; Hines, J.E.

2006-01-01

Matrix population models that allow an animal to occupy more than one state over time are important tools for population and evolutionary ecologists. Definition of state can vary, including location for metapopulation models and breeding state for life history models. For populations whose members can be marked and subsequently re-encountered, multistate mark-recapture models are available to estimate the survival and transition probabilities needed to construct population models. Multistate models have proved extremely useful in this context, but they often require a substantial amount of data and restrict estimation of transition probabilities to those areas or states subjected to formal sampling effort. At the same time, for many species, there are considerable tag recovery data provided by the public that could be modeled in order to increase precision and to extend inference to a greater number of areas or states. Here we present a statistical model for combining multistate capture-recapture data (e.g., from a breeding ground study) with multistate tag recovery data (e.g., from wintering grounds). We use this method to analyze data from a study of Canada Geese (Branta canadensis) in the Atlantic Flyway of North America. Our analysis produced marginal improvement in precision, due to relatively few recoveries, but we demonstrate how precision could be further improved with increases in the probability that a retrieved tag is reported.

Stochastic resonance in a generalized Von Foerster population growth model

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

Lumi, N.; Mankin, R.

The stochastic dynamics of a population growth model, similar to the Von Foerster model for human population, is studied. The influence of fluctuating environment on the carrying capacity is modeled as a multiplicative dichotomous noise. It is established that an interplay between nonlinearity and environmental fluctuations can cause single unidirectional discontinuous transitions of the mean population size versus the noise amplitude, i.e., an increase of noise amplitude can induce a jump from a state with a moderate number of individuals to that with a very large number, while by decreasing the noise amplitude an opposite transition cannot be effected. Anmore » analytical expression of the mean escape time for such transitions is found. Particularly, it is shown that the mean transition time exhibits a strong minimum at intermediate values of noise correlation time, i.e., the phenomenon of stochastic resonance occurs. Applications of the results in ecology are also discussed.« less

From bedside to classroom: the nurse educator transition model.

PubMed

Schoening, Anne M

2013-01-01

The purpose of this qualitative study was to generate a theoretical model that describes the social process that occurs during the role transition from nurse to nurse educator. Recruitment and retention of qualified nurse educators is essential in order to remedy the current staff nurse and faculty shortage in the United States, yet nursing schools face many challenges in this area. This grounded theory study utilized purposive, theoretical sampling to identify 20 nurse educators teaching in baccalaureate nursing programs in the Midwest. The Nurse Educator Transition (NET) model was created from these data.This model identifies four phases in the role transition from nurse to nurse educator: a) the Anticipatory/Expectation Phase, b) the Disorientation Phase, c) the Information-Seeking Phase, and d) the Identity Formation Phase. Recommendations include integrating formal pedagogical education into nursing graduate programs and creating evidence-based orientation and mentoring programs for novice nurse faculty.

Eigenstate Phase Transitions

NASA Astrophysics Data System (ADS)

Zhao, Bo

Phase transitions are one of the most exciting physical phenomena ever discovered. The understanding of phase transitions has long been of interest. Recently eigenstate phase transitions have been discovered and studied; they are drastically different from traditional thermal phase transitions. In eigenstate phase transitions, a sharp change is exhibited in properties of the many-body eigenstates of the Hamiltonian of a quantum system, but not the thermal equilibrium properties of the same system. In this thesis, we study two different types of eigenstate phase transitions. The first is the eigenstate phase transition within the ferromagnetic phase of an infinite-range spin model. By studying the interplay of the eigenstate thermalization hypothesis and Ising symmetry breaking, we find two eigenstate phase transitions within the ferromagnetic phase: In the lowest-temperature phase the magnetization can macroscopically oscillate by quantum tunneling between up and down. The relaxation of the magnetization is always overdamped in the remainder of the ferromagnetic phase, which is further divided into phases where the system thermally activates itself over the barrier between the up and down states, and where it quantum tunnels. The second is the many-body localization phase transition. The eigenstates on one side of the transition obey the eigenstate thermalization hypothesis; the eigenstates on the other side are many-body localized, and thus thermal equilibrium need not be achieved for an initial state even after evolving for an arbitrary long time. We study this many-body localization phase transition in the strong disorder renormalization group framework. After setting up a set of coarse-graining rules for a general one dimensional chain, we get a simple "toy model'' and obtain an almost purely analytical solution to the infinite-randomness critical fixed point renormalization group equation. We also get an estimate of the correlation length critical exponent nu ≈ 2.5.

Quantum mechanical/molecular mechanical/continuum style solvation model: time-dependent density functional theory.

PubMed

Thellamurege, Nandun M; Cui, Fengchao; Li, Hui

2013-08-28

A combined quantum mechanical/molecular mechanical/continuum (QM/MMpol/C) style method is developed for time-dependent density functional theory (TDDFT, including long-range corrected TDDFT) method, induced dipole polarizable force field, and induced surface charge continuum model. Induced dipoles and induced charges are included in the TDDFT equations to solve for the transition energies, relaxed density, and transition density. Analytic gradient is derived and implemented for geometry optimization and molecular dynamics simulation. QM/MMpol/C style DFT and TDDFT methods are used to study the hydrogen bonding of the photoactive yellow protein chromopore in ground state and excited state.

Communication: spin-boson model with diagonal and off-diagonal coupling to two independent baths: ground-state phase transition in the deep sub-Ohmic regime.

PubMed

Zhao, Yang; Yao, Yao; Chernyak, Vladimir; Zhao, Yang

2014-04-28

We investigate a spin-boson model with two boson baths that are coupled to two perpendicular components of the spin by employing the density matrix renormalization group method with an optimized boson basis. It is revealed that in the deep sub-Ohmic regime there exists a novel second-order phase transition between two types of doubly degenerate states, which is reduced to one of the usual types for nonzero tunneling. In addition, it is found that expectation values of the spin components display jumps at the phase boundary in the absence of bias and tunneling.

The localized quantum vacuum field

NASA Astrophysics Data System (ADS)

Dragoman, D.

2008-03-01

A model for the localized quantum vacuum is proposed in which the zero-point energy (ZPE) of the quantum electromagnetic field originates in energy- and momentum-conserving transitions of material systems from their ground state to an unstable state with negative energy. These transitions are accompanied by emissions and re-absorptions of real photons, which generate a localized quantum vacuum in the neighborhood of material systems. The model could help resolve the cosmological paradox associated with the ZPE of electromagnetic fields, while reclaiming quantum effects associated with quantum vacuum such as the Casimir effect and the Lamb shift. It also offers a new insight into the Zitterbewegung of material particles.

Investigation of Infra-red and Nonequilibrium Air Radiation

NASA Technical Reports Server (NTRS)

Kruger, Charles H.; Laux, Christophe O.

1994-01-01

This report summarizes the results obtained during a research program on the infrared radiation of air plasmas conducted in the High Temperature Gasdynamics Laboratory at Stanford University. This program was intended to investigate the masking of infrared signatures by the air plasma formed behind the bow shock of high velocity missiles. Prior to this work, the radiative emission of air plasmas in the infrared had been the object of few experimental investigations, and although several infrared systems were already modeled in radiation codes such as NEQAIR, measurements were required to validate numerical predictions and indicate whether all transitions of importance were accounted for in the model. The program was further motivated by the fact that 9 excited states (A, B, C, D, B', F, H, and H') of NO radiate in the infrared, especially between 1 and 1.5 microns where at least 9 transitions involving can be observed. Because these IR transitions are relatively well separated from each other, excited NO states concentrations can be easily measured, thus providing essential information on excited-state chemistry for use in optical diagnostics or in electronic excitation model validation. Detailed comparisons between measured and simulated spectra are presented.

Synthetic quorum sensing in model microcapsule colonies

NASA Astrophysics Data System (ADS)

Shum, Henry; Balazs, Anna C.

2017-08-01

Biological quorum sensing refers to the ability of cells to gauge their population density and collectively initiate a new behavior once a critical density is reached. Designing synthetic materials systems that exhibit quorum sensing-like behavior could enable the fabrication of devices with both self-recognition and self-regulating functionality. Herein, we develop models for a colony of synthetic microcapsules that communicate by producing and releasing signaling molecules. Production of the chemicals is regulated by a biomimetic negative feedback loop, the “repressilator” network. Through theory and simulation, we show that the chemical behavior of such capsules is sensitive to both the density and number of capsules in the colony. For example, decreasing the spacing between a fixed number of capsules can trigger a transition in chemical activity from the steady, repressed state to large-amplitude oscillations in chemical production. Alternatively, for a fixed density, an increase in the number of capsules in the colony can also promote a transition into the oscillatory state. This configuration-dependent behavior of the capsule colony exemplifies quorum-sensing behavior. Using our theoretical model, we predict the transitions from the steady state to oscillatory behavior as a function of the colony size and capsule density.

Active-to-absorbing-state phase transition in an evolving population with mutation.

PubMed

Sarkar, Niladri

2015-10-01

We study the active to absorbing phase transition (AAPT) in a simple two-component model system for a species and its mutant. We uncover the nontrivial critical scaling behavior and weak dynamic scaling near the AAPT that shows the significance of mutation and highlights the connection of this model with the well-known directed percolation universality class. Our model should be a useful starting point to study how mutation may affect extinction or survival of a species.

Kinetic model of stimulated emission created by resonance pumping of aluminum laser-induced plasma

NASA Astrophysics Data System (ADS)

Gornushkin, I. B.; Kazakov, A. Ya.

2017-06-01

Stimulated emission observed experimentally in an aluminum laser induced plasma is modeled via a kinetic approach. The simulated emission at several cascade transitions is created by a pump laser guided through the plasma at several microseconds after its creation and tuned in resonance with the strong 3s23p-3s24s transition at 266 nm. A two-dimensional space-time collisional radiative plasma model explains the creation of the population inversion and lasing at wavelengths of 2100 n m and 396.1 nm. The population inversion for lasing at 2100 n m is created by depopulation of the ground 3s23p state and population of the 3s25s state via the absorption of the resonant radiation at 266 nm. The population inversion for lasing at 396.1 nm occurs during the laser pulse via the decay of the population of the pumped 3s25s state to the excited 3s24s state via cascade transitions driven optically and by collisions. In particular, efficient are the mixing transitions between neighboring states separated by small gaps on the order of k T at plasma temperatures of 5000-10 000 K. The model predicts that the population inversion and corresponding gain may reach high values even at very moderate pump energy of several μJ per pulse. The efficiency of lasing at 2100 n m and 396.1 nm is estimated to be ˜3% and 0.05%, correspondingly with respect to the pump laser intensity. The gain for lasing at 396.1 nm can reach as high as ˜40 cm-1. The polarization effect that the pump radiation at 266 nm imposes on the stimulated emission at 396.1 nm is discussed. The calculated results are favorably compared to experimental data.

An Expert System For Multispectral Threat Assessment And Response

NASA Astrophysics Data System (ADS)

Steinberg, Alan N.

1987-05-01

A concept has been defined for an automatic system to manage the self-defense of a combat aircraft. Distinctive new features of this concept include: a. the flexible prioritization of tasks and coordinated use of sensor, countermeasures, flight systems and weapons assets by means of an automated planning function; b. the integration of state-of-the-art data fusion algorithms with event prediction processing; c. the use of advanced Artificial Intelligence tools to emulate the decision processes of tactical EW experts. Threat Assessment functions (a) estimate threat identity, lethality and intent on the basis of multi-spectral sensor data, and (b) predict the time to critical events in threat engagements (e.g., target acquisition, tracking, weapon launch, impact). Response Management functions (a) select candidate responses to reported threat situations; (b) estimate the effects of candidate actions on survival; and (c) coordinate the assignment of sensors, weapons and countermeasures with the flight plan. The system employs Finite State Models to represent current engagements and to predict subsequent events. Each state in a model is associated with a set of observable features, allowing interpretation of sensor data and adaptive use of sensor assets. Defined conditions on state transitions allow prediction of times to critical future states and are used in planning self-defensive responses, which are designed either to impede a particular state transition or to force a transition to a lower threat state.

STATIC QUARK ANTI-QUARK FREE AND INTERNAL ENERGY IN 2-FLAVOR QCD AND BOUND STATES IN THE QGP.

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

ZANTOW, F.; KACZMAREK, O.

2005-07-25

We present results on heavy quark free energies in 2-flavour QCD. The temperature dependence of the interaction between static quark anti-quark pairs will be analyzed in terms of temperature dependent screening radii, which give a first estimate on the medium modification of (heavy quark) bound states in the quark gluon plasma. Comparing those radii to the (zero temperature) mean squared charge radii of chasmonium states indicates that the J/{Psi} may survive the phase transition as a bound state, while {chi}{sub c} and {Psi}{prime} are expected to show significant thermal modifications at temperatures close to the transition. Furthermore we will analyzemore » the relation between heavy quark free energies, entropy contributions and internal energy and discuss their relation to potential models used to analyze the melting of heavy quark bound states above the deconfinement temperature. Results of different groups and various potential models for bound states in the deconfined phase of QCD are compared.« less

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

Semenov, A. N.

We propose a new spin-glass model with no positional quenched disorder which is regarded as a coarse-grained model of a structural glass-former. The model is analyzed in the 1D case when the number N of states of a primary cell is large. For N → ∞, the model exhibits a sharp freezing transition of the thermodynamic origin. It is shown both analytically and numerically that the glass transition is accompanied by a significant growth of a static length scale ξ pointing to the structural (equilibrium) nature of dynamical slowdown effects in supercooled liquids.

Characterization of the low-temperature properties of a simplified protein model

NASA Astrophysics Data System (ADS)

Hagmann, Johannes-Geert; Nakagawa, Naoko; Peyrard, Michel

2014-01-01

Prompted by results that showed that a simple protein model, the frustrated Gō model, appears to exhibit a transition reminiscent of the protein dynamical transition, we examine the validity of this model to describe the low-temperature properties of proteins. First, we examine equilibrium fluctuations. We calculate its incoherent neutron-scattering structure factor and show that it can be well described by a theory using the one-phonon approximation. By performing an inherent structure analysis, we assess the transitions among energy states at low temperatures. Then, we examine nonequilibrium fluctuations after a sudden cooling of the protein. We investigate the violation of the fluctuation-dissipation theorem in order to analyze the protein glass transition. We find that the effective temperature of the quenched protein deviates from the temperature of the thermostat, however it relaxes towards the actual temperature with an Arrhenius behavior as the waiting time increases. These results of the equilibrium and nonequilibrium studies converge to the conclusion that the apparent dynamical transition of this coarse-grained model cannot be attributed to a glassy behavior.

V/STOL propulsion control analysis: Phase 2, task 5-9

NASA Technical Reports Server (NTRS)

1981-01-01

Typical V/STOL propulsion control requirements were derived for transition between vertical and horizontal flight using the General Electric RALS (Remote Augmented Lift System) concept. Steady-state operating requirements were defined for a typical Vertical-to-Horizontal transition and for a typical Horizontal-to-Vertical transition. Control mode requirements were established and multi-variable regulators developed for individual operating conditions. Proportional/Integral gain schedules were developed and were incorporated into a transition controller with capabilities for mode switching and manipulated variable reassignment. A non-linear component-level transient model of the engine was developed and utilized to provide a preliminary check-out of the controller logic. An inlet and nozzle effects model was developed for subsequent incorporation into the engine model and an aircraft model was developed for preliminary flight transition simulations. A condition monitoring development plan was developed and preliminary design requirements established. The Phase 1 long-range technology plan was refined and restructured toward the development of a real-time high fidelity transient model of a supersonic V/STOL propulsion system and controller for use in a piloted simulation program at NASA-Ames.

Toward the Darwinian transition: Switching between distributed and speciated states in a simple model of early life.

PubMed

Arnoldt, Hinrich; Strogatz, Steven H; Timme, Marc

2015-01-01

It has been hypothesized that in the era just before the last universal common ancestor emerged, life on earth was fundamentally collective. Ancient life forms shared their genetic material freely through massive horizontal gene transfer (HGT). At a certain point, however, life made a transition to the modern era of individuality and vertical descent. Here we present a minimal model for stochastic processes potentially contributing to this hypothesized "Darwinian transition." The model suggests that HGT-dominated dynamics may have been intermittently interrupted by selection-driven processes during which genotypes became fitter and decreased their inclination toward HGT. Stochastic switching in the population dynamics with three-point (hypernetwork) interactions may have destabilized the HGT-dominated collective state and essentially contributed to the emergence of vertical descent and the first well-defined species in early evolution. A systematic nonlinear analysis of the stochastic model dynamics covering key features of evolutionary processes (such as selection, mutation, drift and HGT) supports this view. Our findings thus suggest a viable direction out of early collective evolution, potentially enabling the start of individuality and vertical Darwinian evolution.

Cook-Levin Theorem Algorithmic-Reducibility/Completeness = Wilson Renormalization-(Semi)-Group Fixed-Points; ``Noise''-Induced Phase-Transitions (NITs) to Accelerate Algorithmics (``NIT-Picking'') REPLACING CRUTCHES!!!: Models: Turing-machine, finite-state-models, finite-automata

NASA Astrophysics Data System (ADS)

Young, Frederic; Siegel, Edward

Cook-Levin theorem theorem algorithmic computational-complexity(C-C) algorithmic-equivalence reducibility/completeness equivalence to renormalization-(semi)-group phase-transitions critical-phenomena statistical-physics universality-classes fixed-points, is exploited via Siegel FUZZYICS =CATEGORYICS = ANALOGYICS =PRAGMATYICS/CATEGORY-SEMANTICS ONTOLOGY COGNITION ANALYTICS-Aristotle ``square-of-opposition'' tabular list-format truth-table matrix analytics predicts and implements ''noise''-induced phase-transitions (NITs) to accelerate versus to decelerate Harel [Algorithmics (1987)]-Sipser[Intro.Thy. Computation(`97)] algorithmic C-C: ''NIT-picking''(!!!), to optimize optimization-problems optimally(OOPO). Versus iso-''noise'' power-spectrum quantitative-only amplitude/magnitude-only variation stochastic-resonance, ''NIT-picking'' is ''noise'' power-spectrum QUALitative-type variation via quantitative critical-exponents variation. Computer-''science''/SEANCE algorithmic C-C models: Turing-machine, finite-state-models, finite-automata,..., discrete-maths graph-theory equivalence to physics Feynman-diagrams are identified as early-days once-workable valid but limiting IMPEDING CRUTCHES(!!!), ONLY IMPEDE latter-days new-insights!!!