Dynamic analysis of hybrid energy systems under flexible operation and variable renewable generation – Part II: Dynamic cost analysis

International Nuclear Information System (INIS)

Garcia, Humberto E.; Mohanty, Amit; Lin, Wen-Chiao; Cherry, Robert S.

2013-01-01

Dynamic analysis of HES (hybrid energy systems) under flexible operation and variable renewable generation is considered in this two-part communication to better understand various challenges and opportunities associated with the high system variability arising from the integration of renewable energy into the power grid. Advanced HES solutions are investigated in which multiple forms of energy commodities, such as electricity and chemical products, may be exchanged. In particular, a comparative dynamic cost analysis is conducted in this part two of the communication to determine best HES options. The cost function includes a set of metrics for computing fixed costs, such as fixed operations and maintenance and overnight capital costs, and also variable operational costs, such as cost of operational variability, variable operations and maintenance cost, and cost of environmental impact, together with revenues. Assuming natural gas, coal, and nuclear as primary heat sources, preliminary results identify the level of renewable penetration at which a given advanced HES option (e.g., a nuclear hybrid) becomes increasingly more economical than a traditional electricity-only generation solution. Conditions are also revealed under which carbon resources may be better utilized as carbon sources for chemical production rather than as combustion material for electricity generation. - Highlights: ► Dynamic analysis of HES to investigate challenges related to renewable penetration. ► Evaluation of dynamic synergies among HES constituents on system performance. ► Comparison of traditional versus advanced HES candidates. ► Dynamic cost analysis of HES candidates to investigate their economic viability. ► Identification of conditions under which an energy commodity may be best utilized

Network structure shapes spontaneous functional connectivity dynamics.

Science.gov (United States)

Shen, Kelly; Hutchison, R Matthew; Bezgin, Gleb; Everling, Stefan; McIntosh, Anthony R

2015-04-08

The structural organization of the brain constrains the range of interactions between different regions and shapes ongoing information processing. Therefore, it is expected that large-scale dynamic functional connectivity (FC) patterns, a surrogate measure of coordination between brain regions, will be closely tied to the fiber pathways that form the underlying structural network. Here, we empirically examined the influence of network structure on FC dynamics by comparing resting-state FC (rsFC) obtained using BOLD-fMRI in macaques (Macaca fascicularis) to structural connectivity derived from macaque axonal tract tracing studies. Consistent with predictions from simulation studies, the correspondence between rsFC and structural connectivity increased as the sample duration increased. Regions with reciprocal structural connections showed the most stable rsFC across time. The data suggest that the transient nature of FC is in part dependent on direct underlying structural connections, but also that dynamic coordination can occur via polysynaptic pathways. Temporal stability was found to be dependent on structural topology, with functional connections within the rich-club core exhibiting the greatest stability over time. We discuss these findings in light of highly variable functional hubs. The results further elucidate how large-scale dynamic functional coordination exists within a fixed structural architecture. Copyright © 2015 the authors 0270-6474/15/355579-10$15.00/0.

Complexity analyses show two distinct types of nonlinear dynamics in short heart period variability recordings

Science.gov (United States)

Porta, Alberto; Bari, Vlasta; Marchi, Andrea; De Maria, Beatrice; Cysarz, Dirk; Van Leeuwen, Peter; Takahashi, Anielle C. M.; Catai, Aparecida M.; Gnecchi-Ruscone, Tomaso

2015-01-01

Two diverse complexity metrics quantifying time irreversibility and local prediction, in connection with a surrogate data approach, were utilized to detect nonlinear dynamics in short heart period (HP) variability series recorded in fetuses, as a function of the gestational period, and in healthy humans, as a function of the magnitude of the orthostatic challenge. The metrics indicated the presence of two distinct types of nonlinear HP dynamics characterized by diverse ranges of time scales. These findings stress the need to render more specific the analysis of nonlinear components of HP dynamics by accounting for different temporal scales. PMID:25806002

Nonlinear dynamical modes of climate variability: from curves to manifolds

Science.gov (United States)

Gavrilov, Andrey; Mukhin, Dmitry; Loskutov, Evgeny; Feigin, Alexander

2016-04-01

The necessity of efficient dimensionality reduction methods capturing dynamical properties of the system from observed data is evident. Recent study shows that nonlinear dynamical mode (NDM) expansion is able to solve this problem and provide adequate phase variables in climate data analysis [1]. A single NDM is logical extension of linear spatio-temporal structure (like empirical orthogonal function pattern): it is constructed as nonlinear transformation of hidden scalar time series to the space of observed variables, i. e. projection of observed dataset onto a nonlinear curve. Both the hidden time series and the parameters of the curve are learned simultaneously using Bayesian approach. The only prior information about the hidden signal is the assumption of its smoothness. The optimal nonlinearity degree and smoothness are found using Bayesian evidence technique. In this work we do further extension and look for vector hidden signals instead of scalar with the same smoothness restriction. As a result we resolve multidimensional manifolds instead of sum of curves. The dimension of the hidden manifold is optimized using also Bayesian evidence. The efficiency of the extension is demonstrated on model examples. Results of application to climate data are demonstrated and discussed. The study is supported by Government of Russian Federation (agreement #14.Z50.31.0033 with the Institute of Applied Physics of RAS). 1. Mukhin, D., Gavrilov, A., Feigin, A., Loskutov, E., & Kurths, J. (2015). Principal nonlinear dynamical modes of climate variability. Scientific Reports, 5, 15510. http://doi.org/10.1038/srep15510

Spectral Data Captures Important Variability Between and Among Species and Functional Types

Science.gov (United States)

Townsend, P. A.; Serbin, S. P.; Kingdon, C.; Singh, A.; Couture, J. J.; Gamon, J. A.

2013-12-01

Narrowband spectral data in the visible, near and shortwave infrared (400-2500 nm) are being used increasingly in plant ecology to characterize the biochemical, physiological and water status of vegetation, as well as community composition. In particular, spectroscopic data have recently received considerable attention for their capacity to discriminate plants according to functional properties or 'optical types.' Such measurements can be acquired from airborne/satellite remote sensing imagery or field spectrometers and are commonly used to directly estimate or infer properties important to photosynthesis, carbon and water fluxes, nutrient dynamics, phenology, and disturbance. Spectral data therefore represent proxies for measurements that are otherwise time consuming or expensive to make, and - more importantly - provide the opportunity to characterize the spatial and temporal variability of taxonomic or functional groups. We have found that spectral variation within species and functional types can in fact exceed the variation between types. As such, we recommend that the traditional quantification of characteristics defining species and/or functional types must be modified to include the range of variability in those properties. We provide four examples of the importance of spectral data for describing within-species/functional type variation. First, within temperate forests, the spectral properties of foliage vary considerably with canopy position. This variability is strongly related to differences in specific leaf area between shade- and sun-lit leaves, and the resulting differences among leaves in strategies for light harvesting, photosynthesis, and leaf longevity. These results point to the need to better characterize leaf optical properties throughout a canopy, rather than basing the characterization of ecosystem functioning on only the sunlit portion of the canopy crown. Second, we show considerable differences in optical properties of foliage from

Locally optimal control under unknown dynamics with learnt cost function: application to industrial robot positioning

Science.gov (United States)

Guérin, Joris; Gibaru, Olivier; Thiery, Stéphane; Nyiri, Eric

2017-01-01

Recent methods of Reinforcement Learning have enabled to solve difficult, high dimensional, robotic tasks under unknown dynamics using iterative Linear Quadratic Gaussian control theory. These algorithms are based on building a local time-varying linear model of the dynamics from data gathered through interaction with the environment. In such tasks, the cost function is often expressed directly in terms of the state and control variables so that it can be locally quadratized to run the algorithm. If the cost is expressed in terms of other variables, a model is required to compute the cost function from the variables manipulated. We propose a method to learn the cost function directly from the data, in the same way as for the dynamics. This way, the cost function can be defined in terms of any measurable quantity and thus can be chosen more appropriately for the task to be carried out. With our method, any sensor information can be used to design the cost function. We demonstrate the efficiency of this method through simulating, with the V-REP software, the learning of a Cartesian positioning task on several industrial robots with different characteristics. The robots are controlled in joint space and no model is provided a priori. Our results are compared with another model free technique, consisting in writing the cost function as a state variable.

Bounds of Double Integral Dynamic Inequalities in Two Independent Variables on Time Scales

Directory of Open Access Journals (Sweden)

S. H. Saker

2011-01-01

Full Text Available Our aim in this paper is to establish some explicit bounds of the unknown function in a certain class of nonlinear dynamic inequalities in two independent variables on time scales which are unbounded above. These on the one hand generalize and on the other hand furnish a handy tool for the study of qualitative as well as quantitative properties of solutions of partial dynamic equations on time scales. Some examples are considered to demonstrate the applications of the results.

Linear dynamical modes as new variables for data-driven ENSO forecast

Science.gov (United States)

Gavrilov, Andrey; Seleznev, Aleksei; Mukhin, Dmitry; Loskutov, Evgeny; Feigin, Alexander; Kurths, Juergen

2018-05-01

A new data-driven model for analysis and prediction of spatially distributed time series is proposed. The model is based on a linear dynamical mode (LDM) decomposition of the observed data which is derived from a recently developed nonlinear dimensionality reduction approach. The key point of this approach is its ability to take into account simple dynamical properties of the observed system by means of revealing the system's dominant time scales. The LDMs are used as new variables for empirical construction of a nonlinear stochastic evolution operator. The method is applied to the sea surface temperature anomaly field in the tropical belt where the El Nino Southern Oscillation (ENSO) is the main mode of variability. The advantage of LDMs versus traditionally used empirical orthogonal function decomposition is demonstrated for this data. Specifically, it is shown that the new model has a competitive ENSO forecast skill in comparison with the other existing ENSO models.

Dynamically variable spot size laser system

Science.gov (United States)

Gradl, Paul R. (Inventor); Hurst, John F. (Inventor); Middleton, James R. (Inventor)

2012-01-01

A Dynamically Variable Spot Size (DVSS) laser system for bonding metal components includes an elongated housing containing a light entry aperture coupled to a laser beam transmission cable and a light exit aperture. A plurality of lenses contained within the housing focus a laser beam from the light entry aperture through the light exit aperture. The lenses may be dynamically adjusted to vary the spot size of the laser. A plurality of interoperable safety devices, including a manually depressible interlock switch, an internal proximity sensor, a remotely operated potentiometer, a remotely activated toggle and a power supply interlock, prevent activation of the laser and DVSS laser system if each safety device does not provide a closed circuit. The remotely operated potentiometer also provides continuous variability in laser energy output.

Suppression of chaos at slow variables by rapidly mixing fast dynamics

Science.gov (United States)

Abramov, R.

2012-04-01

One of the key questions about chaotic multiscale systems is how the fast dynamics affects chaos at the slow variables, and, therefore, impacts uncertainty and predictability of the slow dynamics. Here we demonstrate that the linear slow-fast coupling with the total energy conservation property promotes the suppression of chaos at the slow variables through the rapid mixing at the fast variables, both theoretically and through numerical simulations. A suitable mathematical framework is developed, connecting the slow dynamics on the tangent subspaces to the infinite-time linear response of the mean state to a constant external forcing at the fast variables. Additionally, it is shown that the uncoupled dynamics for the slow variables may remain chaotic while the complete multiscale system loses chaos and becomes completely predictable at the slow variables through increasing chaos and turbulence at the fast variables. This result contradicts the common sense intuition, where, naturally, one would think that coupling a slow weakly chaotic system with another much faster and much stronger mixing system would result in general increase of chaos at the slow variables.

Phase space dynamics and collective variable fluctuations

International Nuclear Information System (INIS)

Benhassine, B.; Farine, M.; Idier, D.; Remaud, B.; Sebille, F.; Schuck, P.

1995-01-01

A dynamical study of collective variable fluctuations in heavy ion reactions is performed within the framework of the Boltzmann-Langevin theory. A general method to extract dispersions on collective variables from numerical simulations based on test particles models is presented and its validity is checked by comparison with analytical equilibrium results. (authors)

Phase space dynamics and collective variable fluctuations

Energy Technology Data Exchange (ETDEWEB)

Benhassine, B.; Farine, M.; Idier, D.; Remaud, B.; Sebille, F. [Laboratoire de Physique Nucleaire de Nantes, 44 (France); Schuck, P. [Institut des Sciences Nucleaires, 38 - Grenoble (France)

1995-12-31

A dynamical study of collective variable fluctuations in heavy ion reactions is performed within the framework of the Boltzmann-Langevin theory. A general method to extract dispersions on collective variables from numerical simulations based on test particles models is presented and its validity is checked by comparison with analytical equilibrium results. (authors) 10 refs.

Convex trace functions of several variables

DEFF Research Database (Denmark)

Hansen, Frank

2002-01-01

We prove that the function (x1,...,xk)¿Tr(f(x1,...,xk)), defined on k-tuples of symmetric matrices of order (n1,...,nk) in the domain of f, is convex for any convex function f of k variables. The matrix f(x1,...,xk) is defined by the functional calculus for functions of several variables, and it ...

Estimating variability in functional images using a synthetic resampling approach

International Nuclear Information System (INIS)

Maitra, R.; O'Sullivan, F.

1996-01-01

Functional imaging of biologic parameters like in vivo tissue metabolism is made possible by Positron Emission Tomography (PET). Many techniques, such as mixture analysis, have been suggested for extracting such images from dynamic sequences of reconstructed PET scans. Methods for assessing the variability in these functional images are of scientific interest. The nonlinearity of the methods used in the mixture analysis approach makes analytic formulae for estimating variability intractable. The usual resampling approach is infeasible because of the prohibitive computational effort in simulating a number of sinogram. datasets, applying image reconstruction, and generating parametric images for each replication. Here we introduce an approach that approximates the distribution of the reconstructed PET images by a Gaussian random field and generates synthetic realizations in the imaging domain. This eliminates the reconstruction steps in generating each simulated functional image and is therefore practical. Results of experiments done to evaluate the approach on a model one-dimensional problem are very encouraging. Post-processing of the estimated variances is seen to improve the accuracy of the estimation method. Mixture analysis is used to estimate functional images; however, the suggested approach is general enough to extend to other parametric imaging methods

Enhanced temporal variability of amygdala-frontal functional connectivity in patients with schizophrenia.

Science.gov (United States)

Yue, Jing-Li; Li, Peng; Shi, Le; Lin, Xiao; Sun, Hong-Qiang; Lu, Lin

2018-01-01

The "dysconnectivity hypothesis" was proposed 20 years ago. It characterized schizophrenia as a disorder with dysfunctional connectivity across a large range of distributed brain areas. Resting-state functional magnetic resonance imaging (rsfMRI) data have supported this theory. Previous studies revealed that the amygdala might be responsible for the emotion regulation-related symptoms of schizophrenia. However, conventional methods oversimplified brain activities by assuming that it remained static throughout the entire scan duration, which may explain why inconsistent results have been reported for the same brain region. An emerging technique is sliding time window analysis, which is used to describe functional connectivity based on the temporal variability of regions of interest (e.g., amygdala) in patients with schizophrenia. Conventional analysis of the static functional connectivity between the amygdala and whole brain was also conducted. Static functional connectivity between the amygdala and orbitofrontal region was impaired in patients with schizophrenia. The variability of connectivity between the amygdala and medial prefrontal cortex was enhanced (i.e., greater dynamics) in patients with schizophrenia. A negative relationship was found between the variability of connectivity and information processing efficiency. A positive correlation was found between the variability of connectivity and symptom severity. The findings suggest that schizophrenia was related to abnormal patterns of fluctuating communication among brain areas that are involved in emotion regulations. Unveiling the temporal properties of functional connectivity could disentangle the inconsistent results of previous functional connectivity studies.

Chronnectome fingerprinting: Identifying individuals and predicting higher cognitive functions using dynamic brain connectivity patterns.

Science.gov (United States)

Liu, Jin; Liao, Xuhong; Xia, Mingrui; He, Yong

2018-02-01

The human brain is a large, interacting dynamic network, and its architecture of coupling among brain regions varies across time (termed the "chronnectome"). However, very little is known about whether and how the dynamic properties of the chronnectome can characterize individual uniqueness, such as identifying individuals as a "fingerprint" of the brain. Here, we employed multiband resting-state functional magnetic resonance imaging data from the Human Connectome Project (N = 105) and a sliding time-window dynamic network analysis approach to systematically examine individual time-varying properties of the chronnectome. We revealed stable and remarkable individual variability in three dynamic characteristics of brain connectivity (i.e., strength, stability, and variability), which was mainly distributed in three higher order cognitive systems (i.e., default mode, dorsal attention, and fronto-parietal) and in two primary systems (i.e., visual and sensorimotor). Intriguingly, the spatial patterns of these dynamic characteristics of brain connectivity could successfully identify individuals with high accuracy and could further significantly predict individual higher cognitive performance (e.g., fluid intelligence and executive function), which was primarily contributed by the higher order cognitive systems. Together, our findings highlight that the chronnectome captures inherent functional dynamics of individual brain networks and provides implications for individualized characterization of health and disease. © 2017 Wiley Periodicals, Inc.

Static, dynamic balance and functional performance in subjects with and without plantar fasciitis

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Geiseane Aguiar Gonçalves

Full Text Available Abstract Introduction: Plantar fasciitis (PF is characterized by non-inflammatory degeneration and pain under the heel, and is one of the most common foot complaints. The compensations and adjustments made to decrease the discomfort caused by the disease are clinical findings and can be a factor that contributes to impaired balance and decreased functional performance. Objective: To compare functional performance as well as static and dynamic balance among subjects with and without PF. Methods: The sample consisted of 124 subjects of both sexes aged 20-60 years. Participants were divided into two groups: a bilateral PF group (PFG; n = 62 and a control group (CG, n = 62. The following outcomes were analyzed: static and dynamic balance (using functional tests and functional performance (using a questionnaire. We used Student’s t test for independent samples to compare variables between the groups. The alpha error was set at 0.05. Results: Subjects with PF showed greater impairment in their overall dynamic balance performance (p < 0.001 than the control group, except for left posteromedial movement (p = 0.19. The CG showed showed better functional performance (p < 0.001 than the PF group. There was no difference between groups for the variable static balance on stable (p = 0.160 and unstable surfaces (p = 0.085. Conclusion: Subjects with PF displayed smaller reach distances in the overall Star Excursion Balance Test (SEBT, demonstrating a deficit in dynamic balance and functional performance when compared with healthy subjects.

Functional coordination of muscles underlying changes in behavioural dynamics.

Science.gov (United States)

Vernooij, Carlijn A; Rao, Guillaume; Perdikis, Dionysios; Huys, Raoul; Jirsa, Viktor K; Temprado, Jean-Jacques

2016-06-10

The dynamical systems approach addresses Bernstein's degrees of freedom problem by assuming that the neuro-musculo-skeletal system transiently assembles and dismantles its components into functional units (or synergies) to meet task demands. Strikingly, little is known from a dynamical point of view about the functioning of the muscular sub-system in this process. To investigate the interaction between the dynamical organisation at muscular and behavioural levels, we searched for specific signatures of a phase transition in muscular coordination when a transition is displayed at the behavioural level. Our results provide evidence that, during Fitts' task when behaviour switches to a different dynamical regime, muscular activation displays typical signatures of a phase transition; a reorganisation in muscular coordination patterns accompanied by a peak in the variability of muscle activation. This suggests that consistent changes occur in coordination processes across the different levels of description (i.e., behaviour and muscles). Specifically, in Fitts' task, target size acts as a control parameter that induces a destabilisation and a reorganisation of coordination patterns at different levels of the neuro-musculo-skeletal system.

Predictive coding of dynamical variables in balanced spiking networks.

Science.gov (United States)

Boerlin, Martin; Machens, Christian K; Denève, Sophie

2013-01-01

Two observations about the cortex have puzzled neuroscientists for a long time. First, neural responses are highly variable. Second, the level of excitation and inhibition received by each neuron is tightly balanced at all times. Here, we demonstrate that both properties are necessary consequences of neural networks that represent information efficiently in their spikes. We illustrate this insight with spiking networks that represent dynamical variables. Our approach is based on two assumptions: We assume that information about dynamical variables can be read out linearly from neural spike trains, and we assume that neurons only fire a spike if that improves the representation of the dynamical variables. Based on these assumptions, we derive a network of leaky integrate-and-fire neurons that is able to implement arbitrary linear dynamical systems. We show that the membrane voltage of the neurons is equivalent to a prediction error about a common population-level signal. Among other things, our approach allows us to construct an integrator network of spiking neurons that is robust against many perturbations. Most importantly, neural variability in our networks cannot be equated to noise. Despite exhibiting the same single unit properties as widely used population code models (e.g. tuning curves, Poisson distributed spike trains), balanced networks are orders of magnitudes more reliable. Our approach suggests that spikes do matter when considering how the brain computes, and that the reliability of cortical representations could have been strongly underestimated.

Evolution of compact stars and dark dynamical variables

Energy Technology Data Exchange (ETDEWEB)

Bhatti, M.Z.; Yousaf, Z. [University of the Punjab, Department of Mathematics, Lahore (Pakistan); Ilyas, M. [University of the Punjab, Centre for High Energy Physics, Lahore (Pakistan)

2017-10-15

This work aims to explore the dark dynamical effects of the f(R, T) modified gravity theory on the dynamics of a compact celestial star. We have taken the interior geometry of a spherical star which is filled with an imperfect fluid distribution. The modified field equations are explored by taking a particular form of the f(R, T) model, i.e. f(R, T) = f{sub 1}(R) + f{sub 2}(R)f{sub 3}(T). These equations are utilized to formulate the well-known structure scalars under the dark dynamical effects of this higher-order gravity theory. Also, with the help of these scalar variables, the evolution equations for expansion and shear are formulated. The whole analysis is made under the condition of a constant R and T. We found a crucial significance of dark source terms and dynamical variables on the evolution and density inhomogeneity of compact objects. (orig.)

Can time be a discrete dynamical variable

International Nuclear Information System (INIS)

Lee, T.D.

1983-01-01

The possibility that time can be regarded as a discrete dynamical variable is examined through all phases of mechanics: from classical mechanics to nonrelativistic quantum mechanics, and to relativistic quantum field theories. (orig.)

The Possibility Using the Power Production Function of Complex Variable for Economic Forecasting

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Sergey Gennadyevich Svetunkov

2016-09-01

Full Text Available The possibility of dynamic analysis and forecasting production results using the power production functions of complex variables with real coefficients is considered. This model expands the arsenal of instrumental methods and allows multivariate production forecasts which are unattainable by other methods of real variables as the functions of complex variables simulate the production differently in comparison with the models of real variables. The values of coefficients of the power production functions of complex variables can be calculated for each statistical observation. This allows to consider the change of the coefficients over time, to analyze this trend and predict the values of the coefficients for a given term, thereby to predict the form of the production function, which forecasts the operating results. Thus, the model of the production function with variable coefficients is introduced into the scientific circulation. With this model, the inverse problem of forecasting might be solved, such as the determination of the necessary quantities of labor and capital to achieve the desired operational results. The study is based on the principles of the modern methodology of complex-valued economy, one of its sections is the complex-valued patterns of production functions. In the article, the possibility of economic forecasting is tested on the example of the UK economy. The results of this prediction are compared with the forecasts obtained by other methods, which have led to the conclusion about the effectiveness of the proposed approach and the method of forecasting at the macro levels of production systems. A complex-valued power model of the production function is recommended for the multivariate prediction of sustainable production systems — the global economy, the economies of individual countries, major industries and regions.

Dynamics and spatio-temporal variability of environmental factors in Eastern Australia using functional principal component analysis

Science.gov (United States)

Szabo, J.K.; Fedriani, E.M.; Segovia-Gonzalez, M. M.; Astheimer, L.B.; Hooper, M.J.

2010-01-01

This paper introduces a new technique in ecology to analyze spatial and temporal variability in environmental variables. By using simple statistics, we explore the relations between abiotic and biotic variables that influence animal distributions. However, spatial and temporal variability in rainfall, a key variable in ecological studies, can cause difficulties to any basic model including time evolution. The study was of a landscape scale (three million square kilometers in eastern Australia), mainly over the period of 19982004. We simultaneously considered qualitative spatial (soil and habitat types) and quantitative temporal (rainfall) variables in a Geographical Information System environment. In addition to some techniques commonly used in ecology, we applied a new method, Functional Principal Component Analysis, which proved to be very suitable for this case, as it explained more than 97% of the total variance of the rainfall data, providing us with substitute variables that are easier to manage and are even able to explain rainfall patterns. The main variable came from a habitat classification that showed strong correlations with rainfall values and soil types. ?? 2010 World Scientific Publishing Company.

The transfer function model for dynamic response of wet cooling coils

International Nuclear Information System (INIS)

Yao Ye; Liu Shiqing

2008-01-01

This paper mainly concerned about the dynamic response model of wet cooling coils that is developed by the Laplace transform method. The theoretic equations are firstly established based on the theory of energy conservation. Then, the transfer functions on the transient responses of wet cooling coils have been deduced using the method of Laplace transform. The transfer functions reveal the dynamic relationships between the inlet variables and the outlet ones of the cooling coils. Partial-fraction method and Newton-Raphson method are both used in the inversion of the transfer functions from the s-domain to τ-domain. To make the dynamic model of wet cooling coils more adaptive, RBFNN method is employed to determine the coefficients of heat and mass transfer. Experiments have been done and manifested that the coefficients of heat and mass transfer by RBFNN will be of great value to the validity of the transient response model of wet cooling coils in this study

Analytic functions of several complex variables

CERN Document Server

Gunning, Robert C

2009-01-01

The theory of analytic functions of several complex variables enjoyed a period of remarkable development in the middle part of the twentieth century. After initial successes by Poincaré and others in the late 19th and early 20th centuries, the theory encountered obstacles that prevented it from growing quickly into an analogue of the theory for functions of one complex variable. Beginning in the 1930s, initially through the work of Oka, then H. Cartan, and continuing with the work of Grauert, Remmert, and others, new tools were introduced into the theory of several complex variables that resol

Dynamic interactions between hydrogeological and exposure parameters in daily dose prediction under uncertainty and temporal variability

Energy Technology Data Exchange (ETDEWEB)

Kumar, Vikas, E-mail: vikas.kumar@urv.cat [Department of Chemical Engineering, Rovira i Virgili University, Tarragona 43007 (Spain); Barros, Felipe P.J. de [Sonny Astani Department of Civil and Environmental Engineering, University of Southern California, Los Angeles 90089, CA (United States); Schuhmacher, Marta [Department of Chemical Engineering, Rovira i Virgili University, Tarragona 43007 (Spain); Fernàndez-Garcia, Daniel; Sanchez-Vila, Xavier [Hydrogeology Group, Department of Geotechnical Engineering and Geosciences, University Politècnica de Catalunya-BarcelonaTech, Barcelona 08034 (Spain)

2013-12-15

Highlights: • Dynamic parametric interaction in daily dose prediction under uncertainty. • Importance of temporal dynamics associated with the dose. • Different dose experienced by different population cohorts as a function of time. • Relevance of uncertainty reduction in the input parameters shows temporal dynamism. -- Abstract: We study the time dependent interaction between hydrogeological and exposure parameters in daily dose predictions due to exposure of humans to groundwater contamination. Dose predictions are treated stochastically to account for an incomplete hydrogeological and geochemical field characterization, and an incomplete knowledge of the physiological response. We used a nested Monte Carlo framework to account for uncertainty and variability arising from both hydrogeological and exposure variables. Our interest is in the temporal dynamics of the total dose and their effects on parametric uncertainty reduction. We illustrate the approach to a HCH (lindane) pollution problem at the Ebro River, Spain. The temporal distribution of lindane in the river water can have a strong impact in the evaluation of risk. The total dose displays a non-linear effect on different population cohorts, indicating the need to account for population variability. We then expand the concept of Comparative Information Yield Curves developed earlier (see de Barros et al. [29]) to evaluate parametric uncertainty reduction under temporally variable exposure dose. Results show that the importance of parametric uncertainty reduction varies according to the temporal dynamics of the lindane plume. The approach could be used for any chemical to aid decision makers to better allocate resources towards reducing uncertainty.

Functional asynchronous networks: Factorization of dynamics and function

Directory of Open Access Journals (Sweden)

Bick Christian

2016-01-01

Full Text Available In this note we describe the theory of functional asynchronous networks and one of the main results, the Modularization of Dynamics Theorem, which for a large class of functional asynchronous networks gives a factorization of dynamics in terms of constituent subnetworks. For these networks we can give a complete description of the network function in terms of the function of the events comprising the network and thereby answer a question originally raised by Alon in the context of biological networks.

Chaos, dynamical structure and climate variability

Energy Technology Data Exchange (ETDEWEB)

Stewart, H.B. [Brookhaven National Lab., Upton, NY (United States). Dept. of Applied Science

1995-09-01

Deterministic chaos in dynamical systems offers a new paradigm for understanding irregular fluctuations. Techniques for identifying deterministic chaos from observed data, without recourse to mathematical models, are being developed. Powerful methods exist for reconstructing multidimensional phase space from an observed time series of a single scalar variable; these methods are invaluable when only a single scalar record of the dynamics is available. However, in some applications multiple concurrent time series may be available for consideration as phase space coordinates. Here the authors propose some basic analytical tools for such multichannel time series data, and illustrate them by applications to a simple synthetic model of chaos, to a low-order model of atmospheric circulation, and to two high-resolution paleoclimate proxy data series. The atmospheric circulation model, originally proposed by Lorenz, has 27 principal unknowns; they establish that the chaotic attractor can be embedded in a subspace of eight dimensions by exhibiting a specific subset of eight unknowns which pass multichannel tests for false nearest neighbors. They also show that one of the principal unknowns in the 27-variable model--the global mean sea surface temperature--is of no discernible usefulness in making short-term forecasts.

Bilingualism and age are continuous variables that influence executive function.

Science.gov (United States)

Incera, Sara; McLennan, Conor T

2018-05-01

We analyzed the effects of bilingualism and age on executive function. We examined these variables along a continuum, as opposed to dichotomizing them. We investigated the impact that bilingualism and age have on two measures of executive control (Stroop and Flanker). The mouse-tracking paradigm allowed us to examine the continuous dynamics of the responses as participants completed each trial. First, we found that the Stroop effect was reduced with younger age and higher levels of bilingualism; however, no Bilingualism by Age interaction emerged. Second, after controlling for baseline, the Flanker effect was not influenced by bilingualism or age. These results support the notion that bilingualism is one way of enhancing some aspects of executive function - specifically those related to the Stroop task - across the adult life span. In sum, different levels of bilingualism, and different ages, result in varying degrees of executive function as measured by the Stroop task.

Dynamic simulation of variable capacity refrigeration systems under abnormal conditions

International Nuclear Information System (INIS)

Liang Nan; Shao Shuangquan; Tian Changqing; Yan Yuying

2010-01-01

There are often abnormal working conditions at evaporator outlet of a refrigeration system, such as two-phase state in transient process, and it is essential to investigate such transient behaviours for system design and control strategy. In this paper, a dynamic lumped parameter model is developed to simulate the transient behaviours of refrigeration system with variable capacity in both normal and abnormal working conditions. The appropriate discriminant method is adopted to switch the normal and abnormal conditions smoothly and to eliminate the simulated data oscillation. In order to verify the dynamic model, we built a test system with variable frequency compressor, water-cooling condenser, evaporator and electronic expansion valve. Calculated values from the mathematical model show reasonable agreement with the experimental data. The simulation results show that the transient behaviours of the variable capacity refrigeration system in the abnormal working conditions can be calculated reliably with the dynamic model when the compressor rotary speed or the opening of electronic expansion valve changes abruptly.

Dynamics and computation in functional shifts

Science.gov (United States)

Namikawa, Jun; Hashimoto, Takashi

2004-07-01

We introduce a new type of shift dynamics as an extended model of symbolic dynamics, and investigate the characteristics of shift spaces from the viewpoints of both dynamics and computation. This shift dynamics is called a functional shift, which is defined by a set of bi-infinite sequences of some functions on a set of symbols. To analyse the complexity of functional shifts, we measure them in terms of topological entropy, and locate their languages in the Chomsky hierarchy. Through this study, we argue that considering functional shifts from the viewpoints of both dynamics and computation gives us opposite results about the complexity of systems. We also describe a new class of shift spaces whose languages are not recursively enumerable.

Nonlinear Dynamical Modes as a Basis for Short-Term Forecast of Climate Variability

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Feigin, A. M.; Mukhin, D.; Gavrilov, A.; Seleznev, A.; Loskutov, E.

2017-12-01

We study abilities of data-driven stochastic models constructed by nonlinear dynamical decomposition of spatially distributed data to quantitative (short-term) forecast of climate characteristics. We compare two data processing techniques: (i) widely used empirical orthogonal function approach, and (ii) nonlinear dynamical modes (NDMs) framework [1,2]. We also make comparison of two kinds of the prognostic models: (i) traditional autoregression (linear) model and (ii) model in the form of random ("stochastic") nonlinear dynamical system [3]. We apply all combinations of the above-mentioned data mining techniques and kinds of models to short-term forecasts of climate indices based on sea surface temperature (SST) data. We use NOAA_ERSST_V4 dataset (monthly SST with space resolution 20 × 20) covering the tropical belt and starting from the year 1960. We demonstrate that NDM-based nonlinear model shows better prediction skill versus EOF-based linear and nonlinear models. Finally we discuss capability of NDM-based nonlinear model for long-term (decadal) prediction of climate variability. [1] D. Mukhin, A. Gavrilov, E. Loskutov , A.Feigin, J.Kurths, 2015: Principal nonlinear dynamical modes of climate variability, Scientific Reports, rep. 5, 15510; doi: 10.1038/srep15510. [2] Gavrilov, A., Mukhin, D., Loskutov, E., Volodin, E., Feigin, A., & Kurths, J., 2016: Method for reconstructing nonlinear modes with adaptive structure from multidimensional data. Chaos: An Interdisciplinary Journal of Nonlinear Science, 26(12), 123101. [3] Ya. Molkov, D. Mukhin, E. Loskutov, A. Feigin, 2012: Random dynamical models from time series. Phys. Rev. E, Vol. 85, n.3.

Construction of a fuel demand function portraying inter-fuel substitution, a system dynamics approach

International Nuclear Information System (INIS)

Abada, Ibrahim; Briat, Vincent; Massol, Olivier

2011-04-01

Most of the recent numerical market equilibrium models of natural gas markets use imperfect competition assumptions. These models are typically embedded with an oversimplified representation of the demand side, usually a single-variable affine function, that does not capture any dynamic adjustment to past prices. To remedy this, we report an effort to construct an enhanced functional specification using the system dynamics-based model of Moxnes (1987, 1990). Thanks to a vintage representation of capital stock, this putty-clay model captures the effect of both past and current energy prices on fuel consumption. Using a re-calibrated version of this model, we first confirm the pertinence of this modeling framework to represent inter-fuel substitutions at different fuel prices in the industrial sector. Building on these findings, a dynamic functional specification of the demand function for natural gas is then proposed and calibrated. (authors)

Bayesian Inference for Functional Dynamics Exploring in fMRI Data

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Xuan Guo

2016-01-01

Full Text Available This paper aims to review state-of-the-art Bayesian-inference-based methods applied to functional magnetic resonance imaging (fMRI data. Particularly, we focus on one specific long-standing challenge in the computational modeling of fMRI datasets: how to effectively explore typical functional interactions from fMRI time series and the corresponding boundaries of temporal segments. Bayesian inference is a method of statistical inference which has been shown to be a powerful tool to encode dependence relationships among the variables with uncertainty. Here we provide an introduction to a group of Bayesian-inference-based methods for fMRI data analysis, which were designed to detect magnitude or functional connectivity change points and to infer their functional interaction patterns based on corresponding temporal boundaries. We also provide a comparison of three popular Bayesian models, that is, Bayesian Magnitude Change Point Model (BMCPM, Bayesian Connectivity Change Point Model (BCCPM, and Dynamic Bayesian Variable Partition Model (DBVPM, and give a summary of their applications. We envision that more delicate Bayesian inference models will be emerging and play increasingly important roles in modeling brain functions in the years to come.

Dynamical zeta functions and dynamical determinants for hyperbolic maps a functional approach

CERN Document Server

Baladi, Viviane

2018-01-01

The spectra of transfer operators associated to dynamical systems, when acting on suitable Banach spaces, contain key information about the ergodic properties of the systems. Focusing on expanding and hyperbolic maps, this book gives a self-contained account on the relation between zeroes of dynamical determinants, poles of dynamical zeta functions, and the discrete spectra of the transfer operators. In the hyperbolic case, the first key step consists in constructing a suitable Banach space of anisotropic distributions. The first part of the book is devoted to the easier case of expanding endomorphisms, showing how the (isotropic) function spaces relevant there can be studied via Paley–Littlewood decompositions, and allowing easier access to the construction of the anisotropic spaces which is performed in the second part. This is the first book describing the use of anisotropic spaces in dynamics. Aimed at researchers and graduate students, it presents results and techniques developed since the beginning of...

High taxonomic variability despite stable functional structure across microbial communities.

Science.gov (United States)

Louca, Stilianos; Jacques, Saulo M S; Pires, Aliny P F; Leal, Juliana S; Srivastava, Diane S; Parfrey, Laura Wegener; Farjalla, Vinicius F; Doebeli, Michael

2016-12-05

Understanding the processes that are driving variation of natural microbial communities across space or time is a major challenge for ecologists. Environmental conditions strongly shape the metabolic function of microbial communities; however, other processes such as biotic interactions, random demographic drift or dispersal limitation may also influence community dynamics. The relative importance of these processes and their effects on community function remain largely unknown. To address this uncertainty, here we examined bacterial and archaeal communities in replicate 'miniature' aquatic ecosystems contained within the foliage of wild bromeliads. We used marker gene sequencing to infer the taxonomic composition within nine metabolic functional groups, and shotgun environmental DNA sequencing to estimate the relative abundances of these groups. We found that all of the bromeliads exhibited remarkably similar functional community structures, but that the taxonomic composition within individual functional groups was highly variable. Furthermore, using statistical analyses, we found that non-neutral processes, including environmental filtering and potentially biotic interactions, at least partly shaped the composition within functional groups and were more important than spatial dispersal limitation and demographic drift. Hence both the functional structure and taxonomic composition within functional groups of natural microbial communities may be shaped by non-neutral and roughly separate processes.

Dynamics calculation with variable mass of mountain self-propelled chassis

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R.M. Makharoblidze

2016-12-01

Full Text Available Many technological processes in the field of agricultural production mechanization, such as a grain crop, planting root-tuber fruits, fertilizing, spraying and dusting, pressing feed materials, harvesting of various cultures, etc. are performed by the machine-tractor units with variable mass of links or processed media and materials. In recent years, are also developing the systems of automatic control, adjusting and control of technological processes and working members in agriculture production. Is studied the dynamics of transition processes of mountain self-propelled chassis with variable mass at real change disconnect or joining masses that is most often used in the function of movement (m(t = ctm(t = ct. Are derived the formulas of change of velocity of movement on displacement of unit and is defined the dependence of this velocity on the tractor and technological machine performance, with taking into account the gradual increase or removing of agricultural materials masses. According to the equation is possible to define a linear movement of machine-tractor unit. According to the obtained expressions we can define the basic operating parameters of machine-tractor unit with variable mass. The results of research would be applied at definition of characteristics of units, at development of new agricultural tractors.

Using transfer functions to quantify El Niño Southern Oscillation dynamics in data and models.

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MacMartin, Douglas G; Tziperman, Eli

2014-09-08

Transfer function tools commonly used in engineering control analysis can be used to better understand the dynamics of El Niño Southern Oscillation (ENSO), compare data with models and identify systematic model errors. The transfer function describes the frequency-dependent input-output relationship between any pair of causally related variables, and can be estimated from time series. This can be used first to assess whether the underlying relationship is or is not frequency dependent, and if so, to diagnose the underlying differential equations that relate the variables, and hence describe the dynamics of individual subsystem processes relevant to ENSO. Estimating process parameters allows the identification of compensating model errors that may lead to a seemingly realistic simulation in spite of incorrect model physics. This tool is applied here to the TAO array ocean data, the GFDL-CM2.1 and CCSM4 general circulation models, and to the Cane-Zebiak ENSO model. The delayed oscillator description is used to motivate a few relevant processes involved in the dynamics, although any other ENSO mechanism could be used instead. We identify several differences in the processes between the models and data that may be useful for model improvement. The transfer function methodology is also useful in understanding the dynamics and evaluating models of other climate processes.

Suppression of chaos at slow variables by rapidly mixing fast dynamics through linear energy-preserving coupling

Science.gov (United States)

Abramov, R. V.

2011-12-01

Chaotic multiscale dynamical systems are common in many areas of science, one of the examples being the interaction of the low-frequency dynamics in the atmosphere with the fast turbulent weather dynamics. One of the key questions about chaotic multiscale systems is how the fast dynamics affects chaos at the slow variables, and, therefore, impacts uncertainty and predictability of the slow dynamics. Here we demonstrate that the linear slow-fast coupling with the total energy conservation property promotes the suppression of chaos at the slow variables through the rapid mixing at the fast variables, both theoretically and through numerical simulations. A suitable mathematical framework is developed, connecting the slow dynamics on the tangent subspaces to the infinite-time linear response of the mean state to a constant external forcing at the fast variables. Additionally, it is shown that the uncoupled dynamics for the slow variables may remain chaotic while the complete multiscale system loses chaos and becomes completely predictable at the slow variables through increasing chaos and turbulence at the fast variables. This result contradicts the common sense intuition, where, naturally, one would think that coupling a slow weakly chaotic system with another much faster and much stronger chaotic system would result in general increase of chaos at the slow variables.

Three-Dimensional Dynamic Topology Optimization with Frequency Constraints Using Composite Exponential Function and ICM Method

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Hongling Ye

2015-01-01

Full Text Available The dynamic topology optimization of three-dimensional continuum structures subject to frequency constraints is investigated using Independent Continuous Mapping (ICM design variable fields. The composite exponential function (CEF is selected to be a filter function which recognizes the design variables and to implement the changing process of design variables from “discrete” to “continuous” and back to “discrete.” Explicit formulations of frequency constraints are given based on filter functions, first-order Taylor series expansion. And an improved optimal model is formulated using CEF and the explicit frequency constraints. Dual sequential quadratic programming (DSQP algorithm is used to solve the optimal model. The program is developed on the platform of MSC Patran & Nastran. Finally, numerical examples are given to demonstrate the validity and applicability of the proposed method.

Dynamic modeling of fixed-bed adsorption of flue gas using a variable mass transfer model

International Nuclear Information System (INIS)

Park, Jehun; Lee, Jae W.

2016-01-01

This study introduces a dynamic mass transfer model for the fixed-bed adsorption of a flue gas. The derivation of the variable mass transfer coefficient is based on pore diffusion theory and it is a function of effective porosity, temperature, and pressure as well as the adsorbate composition. Adsorption experiments were done at four different pressures (1.8, 5, 10 and 20 bars) and three different temperatures (30, 50 and 70 .deg. C) with zeolite 13X as the adsorbent. To explain the equilibrium adsorption capacity, the Langmuir-Freundlich isotherm model was adopted, and the parameters of the isotherm equation were fitted to the experimental data for a wide range of pressures and temperatures. Then, dynamic simulations were performed using the system equations for material and energy balance with the equilibrium adsorption isotherm data. The optimal mass transfer and heat transfer coefficients were determined after iterative calculations. As a result, the dynamic variable mass transfer model can estimate the adsorption rate for a wide range of concentrations and precisely simulate the fixed-bed adsorption process of a flue gas mixture of carbon dioxide and nitrogen.

Dynamical invariants for variable quadratic Hamiltonians

International Nuclear Information System (INIS)

Suslov, Sergei K

2010-01-01

We consider linear and quadratic integrals of motion for general variable quadratic Hamiltonians. Fundamental relations between the eigenvalue problem for linear dynamical invariants and solutions of the corresponding Cauchy initial value problem for the time-dependent Schroedinger equation are emphasized. An eigenfunction expansion of the solution of the initial value problem is also found. A nonlinear superposition principle for generalized Ermakov systems is established as a result of decomposition of the general quadratic invariant in terms of the linear ones.

Functional network macroscopes for probing past and present Earth system dynamics (Invited)

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Donges, J. F.

2013-12-01

The Earth, as viewed from a physicist's perspective, is a dynamical system of great complexity. Functional complex networks are inferred from observational data and model runs or constructed on the basis of theoretical considerations. Representing statistical interdependencies or causal interactions between objects (e.g., Earth system subdomains, processes, or local field variables), functional complex networks are conceptually well-suited for naturally addressing some of the fundamental questions of Earth system analysis concerning, among others, major dynamical patterns, teleconnections, and feedback loops in the planetary machinery, as well as critical elements such as thresholds, bottlenecks, and switches. The first part of this talk concerns complex network theory and network-based time series analysis. Regarding complex network theory, the novel contributions include consistent frameworks for analyzing the topology of (i) general networks of interacting networks and (ii) networks with vertices of heterogeneously distributed weights, as well as (iii) an analytical theory for describing spatial networks. In the realm of time series analysis, (i) recurrence network analysis is put forward as a theoretically founded, nonlinear technique for the study of single, but possibly multivariate time series. (ii) Coupled climate networks are introduced as an exploratory tool of data analysis for quantitatively characterizing the intricate statistical interdependency structure within and between several fields of time series. The second part presents applications for detecting dynamical transitions (tipping points) in time series and studying bottlenecks in the atmosphere's general circulation structure. The analysis of paleoclimate data reveals a possible influence of large-scale shifts in Plio-Pleistocene African climate variability on events in human evolution. This presentation summarizes the contents of the dissertation titled "Functional network macroscopes for

A Quasi-Dynamic Optimal Control Strategy for Non-Linear Multivariable Processes Based upon Non-Quadratic Objective Functions

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Jens G. Balchen

1984-10-01

Full Text Available The problem of systematic derivation of a quasi-dynamic optimal control strategy for a non-linear dynamic process based upon a non-quadratic objective function is investigated. The wellknown LQG-control algorithm does not lead to an optimal solution when the process disturbances have non-zero mean. The relationships between the proposed control algorithm and LQG-control are presented. The problem of how to constrain process variables by means of 'penalty' - terms in the objective function is dealt with separately.

LOCAL ENTROPY FUNCTION OF DYNAMICAL SYSTEM

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İsmail TOK

2013-05-01

Full Text Available In this work, we first,define the entropy function of the topological dynamical system and investigate basic properties of this function without going into details. Let (X,A,T be a probability measure space and consider P = { pl5p2,...,pn} a finite measurable partition of all sub-sets of topological dynamical system (X,T.Then,the quantity H (P = ^ zpt is called the i=1 entropy function of finite measurable partition P.Where f-1 log t if 0 0.If diam(P < s,then the quantity L^ (T = h^ (T - h^ (T,P is called a local entropy function of topological dynamical system (X,T . In conclusion, Let (X,T and (Y,S be two topological dynamical system. If TxS is a transformation defined on the product space (XxY,TxS with (TxS(x , y = (Tx,Sy for all (x,y X x Y.Then L ^^ (TxS = L^d(T + L (S .and, we prove some fundamental properties of this function.

Neuromorphic Implementation of Attractor Dynamics in a Two-Variable Winner-Take-All Circuit with NMDARs: A Simulation Study.

Science.gov (United States)

You, Hongzhi; Wang, Da-Hui

2017-01-01

Neural networks configured with winner-take-all (WTA) competition and N-methyl-D-aspartate receptor (NMDAR)-mediated synaptic dynamics are endowed with various dynamic characteristics of attractors underlying many cognitive functions. This paper presents a novel method for neuromorphic implementation of a two-variable WTA circuit with NMDARs aimed at implementing decision-making, working memory and hysteresis in visual perceptions. The method proposed is a dynamical system approach of circuit synthesis based on a biophysically plausible WTA model. Notably, slow and non-linear temporal dynamics of NMDAR-mediated synapses was generated. Circuit simulations in Cadence reproduced ramping neural activities observed in electrophysiological recordings in experiments of decision-making, the sustained activities observed in the prefrontal cortex during working memory, and classical hysteresis behavior during visual discrimination tasks. Furthermore, theoretical analysis of the dynamical system approach illuminated the underlying mechanisms of decision-making, memory capacity and hysteresis loops. The consistence between the circuit simulations and theoretical analysis demonstrated that the WTA circuit with NMDARs was able to capture the attractor dynamics underlying these cognitive functions. Their physical implementations as elementary modules are promising for assembly into integrated neuromorphic cognitive systems.

Chaos Synchronization Using Adaptive Dynamic Neural Network Controller with Variable Learning Rates

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Chih-Hong Kao

2011-01-01

Full Text Available This paper addresses the synchronization of chaotic gyros with unknown parameters and external disturbance via an adaptive dynamic neural network control (ADNNC system. The proposed ADNNC system is composed of a neural controller and a smooth compensator. The neural controller uses a dynamic RBF (DRBF network to online approximate an ideal controller. The DRBF network can create new hidden neurons online if the input data falls outside the hidden layer and prune the insignificant hidden neurons online if the hidden neuron is inappropriate. The smooth compensator is designed to compensate for the approximation error between the neural controller and the ideal controller. Moreover, the variable learning rates of the parameter adaptation laws are derived based on a discrete-type Lyapunov function to speed up the convergence rate of the tracking error. Finally, the simulation results which verified the chaotic behavior of two nonlinear identical chaotic gyros can be synchronized using the proposed ADNNC scheme.

Chaotic Dynamical State Variables Selection Procedure Based Image Encryption Scheme

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Zia Bashir

2017-12-01

Full Text Available Nowadays, in the modern digital era, the use of computer technologies such as smartphones, tablets and the Internet, as well as the enormous quantity of confidential information being converted into digital form have resulted in raised security issues. This, in turn, has led to rapid developments in cryptography, due to the imminent need for system security. Low-dimensional chaotic systems have low complexity and key space, yet they achieve high encryption speed. An image encryption scheme is proposed that, without compromising the security, uses reasonable resources. We introduced a chaotic dynamic state variables selection procedure (CDSVSP to use all state variables of a hyper-chaotic four-dimensional dynamical system. As a result, less iterations of the dynamical system are required, and resources are saved, thus making the algorithm fast and suitable for practical use. The simulation results of security and other miscellaneous tests demonstrate that the suggested algorithm excels at robustness, security and high speed encryption.

Cartesian integration of Grassmann variables over invariant functions

Energy Technology Data Exchange (ETDEWEB)

Kieburg, Mario; Kohler, Heiner; Guhr, Thomas [Universitaet Duisburg-Essen, Duisburg (Germany)

2009-07-01

Supersymmetry plays an important role in field theory as well as in random matrix theory and mesoscopic physics. Anticommuting variables are the fundamental objects of supersymmetry. The integration over these variables is equivalent to the derivative. Recently[arxiv:0809.2674v1[math-ph] (2008)], we constructed a differential operator which only acts on the ordinary part of the superspace consisting of ordinary and anticommuting variables. This operator is equivalent to the integration over all anticommuting variables of an invariant function. We present this operator and its applications for functions which are rotation invariant under the supergroups U(k{sub 1}/k{sub 2}) and UOSp(k{sub 1}/k{sub 2}).

Adaptive Synchronization of Fractional Order Complex-Variable Dynamical Networks via Pinning Control

Science.gov (United States)

Ding, Da-Wei; Yan, Jie; Wang, Nian; Liang, Dong

2017-09-01

In this paper, the synchronization of fractional order complex-variable dynamical networks is studied using an adaptive pinning control strategy based on close center degree. Some effective criteria for global synchronization of fractional order complex-variable dynamical networks are derived based on the Lyapunov stability theory. From the theoretical analysis, one concludes that under appropriate conditions, the complex-variable dynamical networks can realize the global synchronization by using the proper adaptive pinning control method. Meanwhile, we succeed in solving the problem about how much coupling strength should be applied to ensure the synchronization of the fractional order complex networks. Therefore, compared with the existing results, the synchronization method in this paper is more general and convenient. This result extends the synchronization condition of the real-variable dynamical networks to the complex-valued field, which makes our research more practical. Finally, two simulation examples show that the derived theoretical results are valid and the proposed adaptive pinning method is effective. Supported by National Natural Science Foundation of China under Grant No. 61201227, National Natural Science Foundation of China Guangdong Joint Fund under Grant No. U1201255, the Natural Science Foundation of Anhui Province under Grant No. 1208085MF93, 211 Innovation Team of Anhui University under Grant Nos. KJTD007A and KJTD001B, and also supported by Chinese Scholarship Council

Short- and long-term variations in non-linear dynamics of heart rate variability

DEFF Research Database (Denmark)

Kanters, J K; Højgaard, M V; Agner, E

1996-01-01

OBJECTIVES: The purpose of the study was to investigate the short- and long-term variations in the non-linear dynamics of heart rate variability, and to determine the relationships between conventional time and frequency domain methods and the newer non-linear methods of characterizing heart rate...... rate and describes mainly linear correlations. Non-linear predictability is correlated with heart rate variability measured as the standard deviation of the R-R intervals and the respiratory activity expressed as power of the high-frequency band. The dynamics of heart rate variability changes suddenly...

Alternating Dynamics of Segregation and Integration in Human EEG Functional Networks During Working-memory Task.

Science.gov (United States)

Zippo, Antonio G; Della Rosa, Pasquale A; Castiglioni, Isabella; Biella, Gabriele E M

2018-02-10

Brain functional networks show high variability in short time windows but mechanisms governing these transient dynamics remain unknown. In this work, we studied the temporal evolution of functional brain networks involved in a working memory (WM) task while recording high-density electroencephalography (EEG) in human normal subjects. We found that functional brain networks showed an initial phase characterized by an increase of the functional segregation index followed by a second phase where the functional segregation faded after the prevailing the functional integration. Notably, wrong trials were associated with different or disrupted sequences of the segregation-integration profiles and measures of network centrality and modularity were able to identify crucial aspects of the oscillatory network dynamics. Additionally, computational investigations further supported the experimental results. The brain functional organization may respond to the information processing demand of a WM task following a 2-step atomic scheme wherein segregation and integration alternately dominate the functional configurations. Copyright © 2017 The Author(s). Published by Elsevier Ltd.. All rights reserved.

Partitioning inter annual variability in net ecosystem exchange between climatic variability and functional change

International Nuclear Information System (INIS)

Hui, D.; Luo, Y.; Katul, G.

2003-01-01

Inter annual variability in net ecosystem exchange of carbon is investigated using a homogeneity-of-slopes model to identify the function change contributing to inter annual variability, net ecosystem carbon exchange, and night-time ecosystem respiration. Results of employing this statistical approach to a data set collected at the Duke Forest AmeriFlux site from August 1997 to December 2001 are discussed. The results demonstrate that it is feasible to partition the variation in ecosystem carbon fluxes into direct effects of seasonal and inter annual climatic variability and functional change. 51 refs., 4 tabs., 5 figs

Comparison of the Internal Dynamics of Metalloproteases Provides New Insights on Their Function and Evolution.

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Henrique F Carvalho

Full Text Available Metalloproteases have evolved in a vast number of biological systems, being one of the most diverse types of proteases and presenting a wide range of folds and catalytic metal ions. Given the increasing understanding of protein internal dynamics and its role in enzyme function, we are interested in assessing how the structural heterogeneity of metalloproteases translates into their dynamics. Therefore, the dynamical profile of the clan MA type protein thermolysin, derived from an Elastic Network Model of protein structure, was evaluated against those obtained from a set of experimental structures and molecular dynamics simulation trajectories. A close correspondence was obtained between modes derived from the coarse-grained model and the subspace of functionally-relevant motions observed experimentally, the later being shown to be encoded in the internal dynamics of the protein. This prompted the use of dynamics-based comparison methods that employ such coarse-grained models in a representative set of clan members, allowing for its quantitative description in terms of structural and dynamical variability. Although members show structural similarity, they nonetheless present distinct dynamical profiles, with no apparent correlation between structural and dynamical relatedness. However, previously unnoticed dynamical similarity was found between the relevant members Carboxypeptidase Pfu, Leishmanolysin, and Botulinum Neurotoxin Type A, despite sharing no structural similarity. Inspection of the respective alignments shows that dynamical similarity has a functional basis, namely the need for maintaining proper intermolecular interactions with the respective substrates. These results suggest that distinct selective pressure mechanisms act on metalloproteases at structural and dynamical levels through the course of their evolution. This work shows how new insights on metalloprotease function and evolution can be assessed with comparison schemes that

Dynamic radial distribution function from inelastic neutron scattering

International Nuclear Information System (INIS)

McQueeney, R.J.

1998-01-01

A real-space, local dynamic structure function g(r,ω) is defined from the dynamic structure function S(Q,ω), which can be measured using inelastic neutron scattering. At any particular frequency ω, S(Q,ω) contains Q-dependent intensity oscillations which reflect the spatial distribution and relative displacement directions for the atoms vibrating at that frequency. Information about local and dynamic atomic correlations is obtained from the Fourier transform of these oscillations g(r,ω) at the particular frequency. g(r,ω) can be formulated such that the elastic and frequency-summed limits correspond to the average and instantaneous radial distribution function, respectively, and is thus called the dynamic radial distribution function. As an example, the dynamic radial distribution function is calculated for fcc nickel in a model which considers only the harmonic atomic displacements due to phonons. The results of these calculations demonstrate that the magnitude of the atomic correlations can be quantified and g(r,ω) is a well-defined correlation function. This leads to a simple prescription for investigating local lattice dynamics. copyright 1998 The American Physical Society

Biodiversity and ecosystem functioning in dynamic landscapes

Science.gov (United States)

Brose, Ulrich; Hillebrand, Helmut

2016-01-01

The relationship between biodiversity and ecosystem functioning (BEF) and its consequence for ecosystem services has predominantly been studied by controlled, short-term and small-scale experiments under standardized environmental conditions and constant community compositions. However, changes in biodiversity occur in real-world ecosystems with varying environments and a dynamic community composition. In this theme issue, we present novel research on BEF in such dynamic communities. The contributions are organized in three sections on BEF relationships in (i) multi-trophic diversity, (ii) non-equilibrium biodiversity under disturbance and varying environmental conditions, and (iii) large spatial and long temporal scales. The first section shows that multi-trophic BEF relationships often appear idiosyncratic, while accounting for species traits enables a predictive understanding. Future BEF research on complex communities needs to include ecological theory that is based on first principles of species-averaged body masses, stoichiometry and effects of environmental conditions such as temperature. The second section illustrates that disturbance and varying environments have direct as well as indirect (via changes in species richness, community composition and species' traits) effects on BEF relationships. Fluctuations in biodiversity (species richness, community composition and also trait dominance within species) can severely modify BEF relationships. The third section demonstrates that BEF at larger spatial scales is driven by different variables. While species richness per se and community biomass are most important, species identity effects and community composition are less important than at small scales. Across long temporal scales, mass extinctions represent severe changes in biodiversity with mixed effects on ecosystem functions. Together, the contributions of this theme issue identify new research frontiers and answer some open questions on BEF relationships

Characterizing phenological vegetation dynamics amidst extreme climate variability in Australia with MODIS VI data

Science.gov (United States)

Broich, M.; Huete, A. R.; Xuanlon, M.; Davies, K.; Restrepo-Coupe, N.; Ratana, P.

2012-12-01

Australia's climate is extremely variable with inter-annual rainfall at any given site varying by 5- or 6-fold or more, across the continent. In addition to such inter-annual variability, there can be significant intra-annual variability, especially in monsoonal Australia (e.g. the wet tropical savannas) and Mediterranean climates in SW Australia where prolonged dry seasons occur each year. This presents unique challenges to the characterization of seasonal dynamics with satellite datasets. In contrast to annual reoccurring temperature-driven phenology of northern hemisphere mid-latitudes, vegetation dynamics of the vast and dry Australian interior are poorly quantified by existing remote sensing products. For example, in the current global-based MODIS phenology product, central Australia is covered by ~30% fill values for any given year. Two challenges are specific to Australian landscapes: first, the difficulty of characterizing seasonality of rainfall-driven ecosystems in interior Australia where duration and magnitude of green-up and brown down cycles show high inter annual variability; second, modeling two phenologic layers, the trees and the grass in savannas were the trees are evergreen but the herbaceous understory varies with rainfall. Savannas cover >50% of Australia. Australia's vegetation and climate are different from other continents. A MODIS phenology product capable of characterizing vegetation dynamics across the continent is being developed in this research as part of the AusCover national expert network aiming to provide Australian biophysical remote sensing data time-series and continental-scale map products. These products aim to support the Terrestrial Ecosystem Research Network (TERN) serving ecosystem research in Australia. The MODIS land surface product for Australia first searches the entire time series of each Climate Modeling Grid pixel for low-high-low extreme point sequences. A double logistic function is then fit to each of these

Biologic variability and correlation of platelet function testing in healthy dogs.

Science.gov (United States)

Blois, Shauna L; Lang, Sean T; Wood, R Darren; Monteith, Gabrielle

2015-12-01

Platelet function tests are influenced by biologic variability, including inter-individual (CVG ) and intra-individual (CVI ), as well as analytic (CVA ) variability. Variability in canine platelet function testing is unknown, but if excessive, would make it difficult to interpret serial results. Additionally, the correlation between platelet function tests is poor in people, but not well described in dogs. The aims were to: (1) identify the effect of variation in preanalytic factors (venipuncture, elapsed time until analysis) on platelet function tests; (2) calculate analytic and biologic variability of adenosine diphosphate (ADP) and arachidonic acid (AA)-induced thromboelastograph platelet mapping (TEG-PM), ADP-, AA-, and collagen-induced whole blood platelet aggregometry (WBA), and collagen/ADP and collagen/epinephrine platelet function analysis (PFA-CADP, PFA-CEPI); and (3) determine the correlation between these variables. In this prospective observational trial, platelet function was measured once every 7 days, for 4 consecutive weeks, in 9 healthy dogs. In addition, CBC, TEG-PM, WBA, and PFA were performed. Overall coefficients of variability ranged from 13.3% to 87.8% for the platelet function tests. Biologic variability was highest for AA-induced maximum amplitude generated during TEG-PM (MAAA; CVG = 95.3%, CVI = 60.8%). Use of population-based reference intervals (RI) was determined appropriate only for PFA-CADP (index of individuality = 10.7). There was poor correlation between most platelet function tests. Use of population-based RI appears inappropriate for most platelet function tests, and tests poorly correlate with one another. Future studies on biologic variability and correlation of platelet function tests should be performed in dogs with platelet dysfunction and those treated with antiplatelet therapy. © 2015 American Society for Veterinary Clinical Pathology.

Non-Markovian dynamics, decoherence and entanglement in dissipative quantum systems with applications to quantum information theory of continuous variable systems

International Nuclear Information System (INIS)

Hoerhammer, C.

2007-01-01

In this thesis, non-Markovian dynamics, decoherence and entanglement in dissipative quantum systems are studied. In particular, applications to quantum information theory of continuous variable systems are considered. The non-Markovian dynamics are described by the Hu-Paz-Zhang master equation of quantum Brownian motion. In this context the focus is on non-Markovian effects on decoherence and separability time scales of various single- mode and two-mode continuous variable states. It is verified that moderate non-Markovian influences slow down the decay of interference fringes and quantum correlations, while strong non-Markovian effects resulting from an out-of-resonance bath can even accelerate the loss of coherence, compared to predictions of Markovian approximations. Qualitatively different scenarios including exponential, Gaussian or algebraic decay of the decoherence function are analyzed. It is shown that partial recurrence of coherence can occur in case of non-Lindblad-type dynamics. The time evolution of quantum correlations of entangled two-mode continuous variable states is examined in single-reservoir and two-reservoir models, representing noisy correlated or uncorrelated non-Markovian quantum channels. For this purpose the model of quantum Brownian motion is extended. Various separability criteria for Gaussian and non-Gaussian continuous variable systems are applied. In both types of reservoir models moderate non-Markovian effects prolong the separability time scales. However, in these models the properties of the stationary state may differ. In the two-reservoir model the initial entanglement is completely lost and both modes are finally uncorrelated. In a common reservoir both modes interact indirectly via the coupling to the same bath variables. Therefore, new quantum correlations may emerge between the two modes. Below a critical bath temperature entanglement is preserved even in the steady state. A separability criterion is derived, which depends

Clinical applications of dynamic functional musculoskeletal ultrasound

Directory of Open Access Journals (Sweden)

Petscavage-Thomas J

2014-02-01

Full Text Available Jonelle Petscavage-Thomas Department of Radiology, Penn State Hershey Medical Center, Hershey, PA, USA Abstract: There is an increasing trend in medicine to utilize ultrasound for diagnosis of musculoskeletal pathology. Although magnetic resonance imaging provides excellent spatial resolution of musculoskeletal structures in multiple imaging planes and is generally the cross-sectional modality of choice, it does not provide dynamic functional assessment of muscles, tendons, and ligaments. Dynamic maneuvers with ultrasound provide functional data and have been shown to be accurate for diagnosis. Ultrasound is also less expensive, portable, and more readily available. This article will review the common snapping, impingement, and friction syndromes imaged with dynamic ultrasound. It will also discuss future areas of research, including musculoskeletal sonoelastography. Keywords: snapping, dynamic, ultrasound, functional, musculoskeletal

Antipersistent dynamics in short time scale variability of self-potential signals

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M. Ragosta

2000-06-01

Full Text Available Time scale properties of self-potential signals are investigated through the analysis of the second order structure function (variogram, a powerful tool to investigate the spatial and temporal variability of observational data. In this work we analyse two sequences of self-potential values measured by means of a geophysical monitoring array located in a seismically active area of Southern Italy. The range of scales investigated goes from a few minutes to several days. It is shown that signal fluctuations are characterised by two time scale ranges in which self-potential variability appears to follow slightly different dynamical behaviours. Results point to the presence of fractal, non stationary features expressing a long term correlation with scaling coefficients which are the clue of stabilising mechanisms. In the scale ranges in which the series show scale invariant behaviour, self-potentials evolve like fractional Brownian motions with anticorrelated increments typical of processes regulated by negative feedback mechanisms (antipersistence. On scales below about 6 h the strength of such an antipersistence appears to be slightly greater than that observed on larger time scales where the fluctuations are less efficiently stabilised.

AeroPropulsoServoElasticity: Dynamic Modeling of the Variable Cycle Propulsion System

Science.gov (United States)

Kopasakis, George

2012-01-01

This presentation was made at the 2012 Fundamental Aeronautics Program Technical Conference and it covers research work for the Dynamic Modeling of the Variable cycle Propulsion System that was done under the Supersonics Project, in the area of AeroPropulsoServoElasticity. The presentation covers the objective for the propulsion system dynamic modeling work, followed by the work that has been done so far to model the variable Cycle Engine, modeling of the inlet, the nozzle, the modeling that has been done to model the affects of flow distortion, and finally presenting some concluding remarks and future plans.

High population variability and source-sink dynamics in a solitary bee species.

Science.gov (United States)

Franzén, Markus; Nilsson, Sven G

2013-06-01

Although solitary bees are considered to play key roles in ecosystem functions, surprisingly few studies have explored their population dynamics. We investigated the population dynamics of a rare, declining, solitary bee (Andrena humilis) in a landscape of 80 km2 in southern Sweden from 2003 to 2011. Only one population was persistent throughout all years studied; most likely this population supplied the surrounding landscape with 11 smaller, temporary local populations. Despite stable pollen availability, the size of the persistent population fluctuated dramatically in a two-year cycle over the nine years, with 490-1230 nests in odd-numbered years and 21-48 nests in even-numbered years. These fluctuations were not significantly related to climatic variables or pollen availability. Nineteen colonization and 14 extinction events were recorded. Occupancy decreased with distance from the persistent population and increased with increasing resource (pollen) availability. There were significant positive correlations between the size of the persistent population and patch occupancy and colonization. Colonizations were generally more common in patches closer to the persistent population, whereas extinctions were independent of distance from the persistent population. Our results highlight the complex population dynamics that exist for this solitary bee species, which could be due to source-sink dynamics, a prolonged diapause, or can represent a bet-hedging strategy to avoid natural enemies and survive in small habitat patches. If large fluctuations in solitary bee populations prove to be widespread, it will have important implications for interpreting ecological relationships, bee conservation, and pollination.

Function theory of several complex variables

CERN Document Server

Krantz, Steven G

2001-01-01

The theory of several complex variables can be studied from several different perspectives. In this book, Steven Krantz approaches the subject from the point of view of a classical analyst, emphasizing its function-theoretic aspects. He has taken particular care to write the book with the student in mind, with uniformly extensive and helpful explanations, numerous examples, and plentiful exercises of varying difficulty. In the spirit of a student-oriented text, Krantz begins with an introduction to the subject, including an insightful comparison of analysis of several complex variables with th

Functional integral approach to classical statistical dynamics

International Nuclear Information System (INIS)

Jensen, R.V.

1980-04-01

A functional integral method is developed for the statistical solution of nonlinear stochastic differential equations which arise in classical dynamics. The functional integral approach provides a very natural and elegant derivation of the statistical dynamical equations that have been derived using the operator formalism of Martin, Siggia, and Rose

Temporal variability in phosphorus transfers: classifying concentration–discharge event dynamics

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P. Haygarth

2004-01-01

Full Text Available The importance of temporal variability in relationships between phosphorus (P concentration (Cp and discharge (Q is linked to a simple means of classifying the circumstances of Cp–Q relationships in terms of functional types of response. New experimental data at the upstream interface of grassland soil and catchment systems at a range of scales (lysimeters to headwaters in England and Australia are used to demonstrate the potential of such an approach. Three types of event are defined as Types 1–3, depending on whether the relative change in Q exceeds the relative change in Cp (Type 1, whether Cp and Q are positively inter-related (Type 2 and whether Cp varies yet Q is unchanged (Type 3. The classification helps to characterise circumstances that can be explained mechanistically in relation to (i the scale of the study (with a tendency towards Type 1 in small scale lysimeters, (ii the form of P with a tendency for Type 1 for soluble (i.e., p–Q relationships that can be developed further to contribute to future models of P transfer and delivery from slope to stream. Studies that evaluate the temporal dynamics of the transfer of P are currently grossly under-represented in comparison with models based on static/spatial factors. Keywords: phosphorus, concentration, discharge, lysimeters, temporal dynamics, overland flow

Fractal diffusion coefficient from dynamical zeta functions

Energy Technology Data Exchange (ETDEWEB)

Cristadoro, Giampaolo [Max Planck Institute for the Physics of Complex Systems, Noethnitzer Str. 38, D 01187 Dresden (Germany)

2006-03-10

Dynamical zeta functions provide a powerful method to analyse low-dimensional dynamical systems when the underlying symbolic dynamics is under control. On the other hand, even simple one-dimensional maps can show an intricate structure of the grammar rules that may lead to a non-smooth dependence of global observables on parameters changes. A paradigmatic example is the fractal diffusion coefficient arising in a simple piecewise linear one-dimensional map of the real line. Using the Baladi-Ruelle generalization of the Milnor-Thurnston kneading determinant, we provide the exact dynamical zeta function for such a map and compute the diffusion coefficient from its smallest zero. (letter to the editor)

Fractal diffusion coefficient from dynamical zeta functions

International Nuclear Information System (INIS)

Cristadoro, Giampaolo

2006-01-01

Dynamical zeta functions provide a powerful method to analyse low-dimensional dynamical systems when the underlying symbolic dynamics is under control. On the other hand, even simple one-dimensional maps can show an intricate structure of the grammar rules that may lead to a non-smooth dependence of global observables on parameters changes. A paradigmatic example is the fractal diffusion coefficient arising in a simple piecewise linear one-dimensional map of the real line. Using the Baladi-Ruelle generalization of the Milnor-Thurnston kneading determinant, we provide the exact dynamical zeta function for such a map and compute the diffusion coefficient from its smallest zero. (letter to the editor)

Interpreting and Utilising Intersubject Variability in Brain Function.

Science.gov (United States)

Seghier, Mohamed L; Price, Cathy J

2018-03-30

We consider between-subject variance in brain function as data rather than noise. We describe variability as a natural output of a noisy plastic system (the brain) where each subject embodies a particular parameterisation of that system. In this context, variability becomes an opportunity to: (i) better characterise typical versus atypical brain functions; (ii) reveal the different cognitive strategies and processing networks that can sustain similar tasks; and (iii) predict recovery capacity after brain damage by taking into account both damaged and spared processing pathways. This has many ramifications for understanding individual learning preferences and explaining the wide differences in human abilities and disabilities. Understanding variability boosts the translational potential of neuroimaging findings, in particular in clinical and educational neuroscience. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

A cumulant functional for static and dynamic correlation

International Nuclear Information System (INIS)

Hollett, Joshua W.; Hosseini, Hessam; Menzies, Cameron

2016-01-01

A functional for the cumulant energy is introduced. The functional is composed of a pair-correction and static and dynamic correlation energy components. The pair-correction and static correlation energies are functionals of the natural orbitals and the occupancy transferred between near-degenerate orbital pairs, rather than the orbital occupancies themselves. The dynamic correlation energy is a functional of the statically correlated on-top two-electron density. The on-top density functional used in this study is the well-known Colle-Salvetti functional. Using the cc-pVTZ basis set, the functional effectively models the bond dissociation of H 2 , LiH, and N 2 with equilibrium bond lengths and dissociation energies comparable to those provided by multireference second-order perturbation theory. The performance of the cumulant functional is less impressive for HF and F 2 , mainly due to an underestimation of the dynamic correlation energy by the Colle-Salvetti functional.

The dynamic adjoint as a Green’s function

International Nuclear Information System (INIS)

Pázsit, I.; Dykin, V.

2015-01-01

Highlight: • The relationship between the direct Green’s function and the dynamic adjoint function is discussed in two-group theory. • It is shown that the elements of the direct Greens’ function matrix are identical to those of the transpose of the adjoint Green’s function matrix, with an interchange of arguments. • It is also remarked how the dynamic adjoint function of van Dam can be given in terms of the direct Green’s function matrix. - Abstract: The concept of the dynamic adjoint was introduced by Hugo van Dam for calculating the in-core neutron noise in boiling water reactors in the mid-70’s. This successful approach found numerous applications for calculating the neutron noise in both PWRs and BWRs since then. Although the advantages and disadvantages of using the direct (forward) or the adjoint (backward) approach for the calculation of the neutron noise were analysed in a number of publications, the direct relationship between the forward Green’s function and the dynamic adjoint has not been discussed. On the other hand, in particle transport theory the relationship between the direct and adjoint Green’s function has been discussed in detail, in which Mike Williams has had many seminal contributions. In this note we analyse the relationship between the direct Green’s function and the dynamic adjoint in the spirit of Mike’s work in neutron transport and radiation damage theory. The paper is closed with some personal remarks and reminiscences.

Heuristic techniques for the analysis of variability as a dynamic aspect of change

NARCIS (Netherlands)

Van Dijk, M.W.G.; Van Geert, P.

Due to the influence of dynamic systems and microgenetic perspectives, variability is nowadays often seen as an important phenomenon that helps us understand the underlying mechanisms of development. This paper aims at demonstrating several simple techniques that can be used to analyse variability

Blood Pressure Variability and Cognitive Function Among Older African Americans: Introducing a New Blood Pressure Variability Measure.

Science.gov (United States)

Tsang, Siny; Sperling, Scott A; Park, Moon Ho; Helenius, Ira M; Williams, Ishan C; Manning, Carol

2017-09-01

Although blood pressure (BP) variability has been reported to be associated with cognitive impairment, whether this relationship affects African Americans has been unclear. We sought correlations between systolic and diastolic BP variability and cognitive function in community-dwelling older African Americans, and introduced a new BP variability measure that can be applied to BP data collected in clinical practice. We assessed cognitive function in 94 cognitively normal older African Americans using the Mini-Mental State Examination (MMSE) and the Computer Assessment of Mild Cognitive Impairment (CAMCI). We used BP measurements taken at the patients' three most recent primary care clinic visits to generate three traditional BP variability indices, range, standard deviation, and coefficient of variation, plus a new index, random slope, which accounts for unequal BP measurement intervals within and across patients. MMSE scores did not correlate with any of the BP variability indices. Patients with greater diastolic BP variability were less accurate on the CAMCI verbal memory and incidental memory tasks. Results were similar across the four BP variability indices. In a sample of cognitively intact older African American adults, BP variability did not correlate with global cognitive function, as measured by the MMSE. However, higher diastolic BP variability correlated with poorer verbal and incidental memory. By accounting for differences in BP measurement intervals, our new BP variability index may help alert primary care physicians to patients at particular risk for cognitive decline.

On the growth estimates of entire functions of double complex variables

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Sanjib Datta

2017-08-01

Full Text Available Recently Datta et al. (2016 introduced the idea of relative type and relative weak type of entire functions of two complex variables with respect to another entire function of two complex variables and prove some related growth properties of it. In this paper, further we study some growth properties of entire functions of two complex variables on the basis of their relative types and relative weak types as introduced by Datta et al (2016.

Robust transient dynamics and brain functions

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Mikhail I Rabinovich

2011-06-01

Full Text Available In the last few decades several concepts of Dynamical Systems Theory (DST have guided psychologists, cognitive scientists, and neuroscientists to rethink about sensory motor behavior and embodied cognition. A critical step in the progress of DST application to the brain (supported by modern methods of brain imaging and multi-electrode recording techniques has been the transfer of its initial success in motor behavior to mental function, i.e., perception, emotion, and cognition. Open questions from research in genetics, ecology, brain sciences, etc. have changed DST itself and lead to the discovery of a new dynamical phenomenon, i.e., reproducible and robust transients that are at the same time sensitive to informational signals. The goal of this review is to describe a new mathematical framework -heteroclinic sequential dynamics- to understand self-organized activity in the brain that can explain certain aspects of robust itinerant behavior. Specifically, we discuss a hierarchy of coarse-grain models of mental dynamics in the form of kinetic equations of modes. These modes compete for resources at three levels: (i within the same modality, (ii among different modalities from the same family (like perception, and (iii among modalities from different families (like emotion and cognition. The analysis of the conditions for robustness, i.e., the structural stability of transient (sequential dynamics, give us the possibility to explain phenomena like the finite capacity of our sequential working memory -a vital cognitive function-, and to find specific dynamical signatures -different kinds of instabilities- of several brain functions and mental diseases.

Pulmonary dynamics and functional imaging with krypton-81m as related to generator delivery characteristics

International Nuclear Information System (INIS)

Kaplan, E.

1985-01-01

Krypton-81m supplied from a generator by continuous elution with air is used with a gamma-camera computer system to produce a sequence of images from multiple breaths, which reconstructed the time-activity images of the breathing human lung. Functional images are produced by subsequent derivation to show specific variables of the dynamic sequences. The dynamic, quantitative, and regional aspects of the respiratory cycle are thus made available in a single study. The need for the delivery of a constant ratio of /sub 81m/Kr to air is required to accurately produce these various studies

Dynamical Functional Theory for Compressed Sensing

DEFF Research Database (Denmark)

Cakmak, Burak; Opper, Manfred; Winther, Ole

2017-01-01

the Thouless-Anderson-Palmer (TAP) equations corresponding to the ensemble. Using a dynamical functional approach we are able to derive an effective stochastic process for the marginal statistics of a single component of the dynamics. This allows us to design memory terms in the algorithm in such a way...

Power functional theory for the dynamic test particle limit

International Nuclear Information System (INIS)

Brader, Joseph M; Schmidt, Matthias

2015-01-01

For classical Brownian systems both in and out of equilibrium we extend the power functional formalism of Schmidt and Brader (2013 J. Chem. Phys. 138 214101) to mixtures of different types of particles. We apply the framework to develop an exact dynamical test particle theory for the self and distinct parts of the van Hove function, which characterize tagged and collective particle motion. The memory functions that induce non-Markovian dynamics are related to functional derivatives of the excess (over ideal) free power dissipation functional. The method offers an alternative to the recently found nonequilibrium Ornstein–Zernike relation for dynamic pair correlation functions. (paper)

KEELE, Minimization of Nonlinear Function with Linear Constraints, Variable Metric Method

International Nuclear Information System (INIS)

Westley, G.W.

1975-01-01

1 - Description of problem or function: KEELE is a linearly constrained nonlinear programming algorithm for locating a local minimum of a function of n variables with the variables subject to linear equality and/or inequality constraints. 2 - Method of solution: A variable metric procedure is used where the direction of search at each iteration is obtained by multiplying the negative of the gradient vector by a positive definite matrix which approximates the inverse of the matrix of second partial derivatives associated with the function. 3 - Restrictions on the complexity of the problem: Array dimensions limit the number of variables to 20 and the number of constraints to 50. These can be changed by the user

Bayesian estimation of dynamic matching function for U-V analysis in Japan

Science.gov (United States)

Kyo, Koki; Noda, Hideo; Kitagawa, Genshiro

2012-05-01

In this paper we propose a Bayesian method for analyzing unemployment dynamics. We derive a Beveridge curve for unemployment and vacancy (U-V) analysis from a Bayesian model based on a labor market matching function. In our framework, the efficiency of matching and the elasticities of new hiring with respect to unemployment and vacancy are regarded as time varying parameters. To construct a flexible model and obtain reasonable estimates in an underdetermined estimation problem, we treat the time varying parameters as random variables and introduce smoothness priors. The model is then described in a state space representation, enabling the parameter estimation to be carried out using Kalman filter and fixed interval smoothing. In such a representation, dynamic features of the cyclic unemployment rate and the structural-frictional unemployment rate can be accurately captured.

Moessbauer radiation dynamical diffraction in crystals being subjected to the action of external variable fields

International Nuclear Information System (INIS)

Baryshevskii, V.G.; Skadorov, V.V.

1986-01-01

A dynamical theory is developed of the Moessbauer radiation diffraction by crystals being subjected to an variable external field action. Equations describing the dynamical diffraction by nonstationary crystals are obtained. It is shown that the resonant interaction between Moessbauer radiation and shift field induced in the crystal by a variable external field giving rise to an effective conversion of the incident wave into a wave with changed frequency. (author)

Dynamic response function and large-amplitude dissipative collective motion

International Nuclear Information System (INIS)

Wu Xizhen; Zhuo Yizhong; Li Zhuxia; Sakata, Fumihiko.

1993-05-01

Aiming at exploring microscopic dynamics responsible for the dissipative large-amplitude collective motion, the dynamic response and correlation functions are introduced within the general theory of nuclear coupled-master equations. The theory is based on the microscopic theory of nuclear collective dynamics which has been developed within the time-dependent Hartree-Fock (TDHF) theory for disclosing complex structure of the TDHF-manifold. A systematic numerical method for calculating the dynamic response and correlation functions is proposed. By performing numerical calculation for a simple model Hamiltonian, it is pointed out that the dynamic response function gives an important information in understanding the large-amplitude dissipative collective motion which is described by an ensemble of trajectories within the TDHF-manifold. (author)

Approximation of functions in two variables by some linear positive operators

Directory of Open Access Journals (Sweden)

Mariola Skorupka

1995-12-01

Full Text Available We introduce some linear positive operators of the Szasz-Mirakjan type in the weighted spaces of continuous functions in two variables. We study the degree of the approximation of functions by these operators. The similar results for functions in one variable are given in [5]. Some operators of the Szasz-Mirakjan type are examined also in [3], [4].

Putting the “dynamic” back into dynamic functional connectivity

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Stewart Heitmann

2018-06-01

Full Text Available The study of fluctuations in time-resolved functional connectivity is a topic of substantial current interest. As the term “dynamic functional connectivity” implies, such fluctuations are believed to arise from dynamics in the neuronal systems generating these signals. While considerable activity currently attends to methodological and statistical issues regarding dynamic functional connectivity, less attention has been paid toward its candidate causes. Here, we review candidate scenarios for dynamic (functional connectivity that arise in dynamical systems with two or more subsystems; generalized synchronization, itinerancy (a form of metastability, and multistability. Each of these scenarios arises under different configurations of local dynamics and intersystem coupling: We show how they generate time series data with nonlinear and/or nonstationary multivariate statistics. The key issue is that time series generated by coupled nonlinear systems contain a richer temporal structure than matched multivariate (linear stochastic processes. In turn, this temporal structure yields many of the phenomena proposed as important to large-scale communication and computation in the brain, such as phase-amplitude coupling, complexity, and flexibility. The code for simulating these dynamics is available in a freeware software platform, the Brain Dynamics Toolbox. The study of network fluctuations in time-resolved functional connectivity is a topic of substantial current interest. However, the topic remains hotly disputed, with both positive and negative reports. A number of fundamental issues remain disputed, including statistical benchmarks and putative causes of nonstationarities. Dynamic models of large-scale brain activity can play a key role in this field by proposing the types of instabilities and dynamics that may be present. The purpose of the present paper is to employ simple dynamic models to illustrate the basic processes (“primitives” that

A study of the HEB longitudinal dynamics

International Nuclear Information System (INIS)

Larson, D.J.

1993-12-01

A study of the High Energy Booster (HEB) longitudinal dynamics is presented. Full derivations of ramp dependent longitudinal variables are given. The formulas assume that the input magnetic field and beam longitudinal emittance are known as a function of time, and that either the rf voltage or the rf bucket area are known as a function of time. Once these three inputs are specified, the formulas can be used to calculate values for all other longitudinal dynamics variables. The formulas have been incorporated into a single computer code named ELVIRA: Evaluation of Longitudinal Variables in Relativistic Accelerators. The ELVIRA code is documented here in detail. The ELVIRA code is used under two initial longitudinal emittance assumptions to plot ramp functions for the longitudinal dynamics design of the HEB as of May 5, 1992

Real analysis series, functions of several variables, and applications

CERN Document Server

Laczkovich, Miklós

2017-01-01

This book develops the theory of multivariable analysis, building on the single variable foundations established in the companion volume, Real Analysis: Foundations and Functions of One Variable. Together, these volumes form the first English edition of the popular Hungarian original, Valós Analízis I & II, based on courses taught by the authors at Eötvös Loránd University, Hungary, for more than 30 years. Numerous exercises are included throughout, offering ample opportunities to master topics by progressing from routine to difficult problems. Hints or solutions to many of the more challenging exercises make this book ideal for independent study, or further reading. Intended as a sequel to a course in single variable analysis, this book builds upon and expands these ideas into higher dimensions. The modular organization makes this text adaptable for either a semester or year-long introductory course. Topics include: differentiation and integration of functions of several variables; infinite numerica...

The impact of land use change and hydroclimatic variability on landscape connectivity dynamics across surface water networks at subcontinental scale

Science.gov (United States)

Tulbure, M. G.; Bishop-Taylor, R.; Broich, M.

2017-12-01

Land use (LU) change and hydroclimatic variability affect spatiotemporal landscape connectivity dynamics, important for species movement and dispersal. Despite the fact that LU change can strongly influence dispersal potential over time, prior research has only focused on the impacts of dynamic changes in the distribution of potential habitats. We used 8 time-steps of historical LU together with a Landsat-derived time-series of surface water habitat dynamics (1986-2011) over the Murray-Darling Basin (MDB), a region with extreme hydroclimatic variability, impacted by LU changes. To assess how changing LU and hydroclimatic variability affect landscape connectivity across time, we compared 4 scenarios, namely one where both climate and LU are dynamic over time, one where climate is kept steady (i.e. a median surface water extent layer), and two scenarios where LU is kept steady (i.e. resistance values associated with the most recent or the first LU layer). We used circuit theory to assign landscape features with `resistance' costs and graph theory network analysis, with surface water habitats as `nodes' connected by dispersal paths or `edges' Findings comparing a dry and an average season show high differences in number of nodes (14581 vs 21544) and resistance distances. The combined effect of LU change and landscape wetness was lower than expected, likely a function of the large, MDB-wide, aggregation scale. Spatially explicit analyses are expected to identify areas where the synergistic effect of LU change and landscape wetness greatly reduce or increase landscape connectivity, as well as areas where the two effects cancel each other out.

GrDHP: a general utility function representation for dual heuristic dynamic programming.

Science.gov (United States)

Ni, Zhen; He, Haibo; Zhao, Dongbin; Xu, Xin; Prokhorov, Danil V

2015-03-01

A general utility function representation is proposed to provide the required derivable and adjustable utility function for the dual heuristic dynamic programming (DHP) design. Goal representation DHP (GrDHP) is presented with a goal network being on top of the traditional DHP design. This goal network provides a general mapping between the system states and the derivatives of the utility function. With this proposed architecture, we can obtain the required derivatives of the utility function directly from the goal network. In addition, instead of a fixed predefined utility function in literature, we conduct an online learning process for the goal network so that the derivatives of the utility function can be adaptively tuned over time. We provide the control performance of both the proposed GrDHP and the traditional DHP approaches under the same environment and parameter settings. The statistical simulation results and the snapshot of the system variables are presented to demonstrate the improved learning and controlling performance. We also apply both approaches to a power system example to further demonstrate the control capabilities of the GrDHP approach.

Impact of sociodemographic variables on executive functions

OpenAIRE

Campanholo, Kenia Repiso; Boa, Izadora Nogueira Fonte; Hodroj, Flávia Cristina da Silva Araujo; Guerra, Glaucia Rosana Benute; Miotto, Eliane Correa; Lucia, Mara Cristina Souza de

2017-01-01

ABSTRACT Executive functions (EFs) regulate human behavior and allow individuals to interact and act in the world. EFs are sensitive to sociodemographic variables such as age, which promotes their decline, and to others that can exert a neuroprotective effect. Objective: To assess the predictive role of education, occupation and family income on decline in executive functions among a sample with a wide age range. Methods: A total of 925 participants aged 18-89 years with 1-28 years' education...

What Does Eye-Blink Rate Variability Dynamics Tell Us About Cognitive Performance?

Directory of Open Access Journals (Sweden)

Rafal Paprocki

2017-12-01

Full Text Available Cognitive performance is defined as the ability to utilize knowledge, attention, memory, and working memory. In this study, we briefly discuss various markers that have been proposed to predict cognitive performance. Next, we develop a novel approach to characterize cognitive performance by analyzing eye-blink rate variability dynamics. Our findings are based on a sample of 24 subjects. The subjects were given a 5-min resting period prior to a 10-min IQ test. During both stages, eye blinks were recorded from Fp1 and Fp2 electrodes. We found that scale exponents estimated for blink rate variability during rest were correlated with subjects' performance on the subsequent IQ test. This surprising phenomenon could be explained by the person to person variation in concentrations of dopamine in PFC and accumulation of GABA in the visual cortex, as both neurotransmitters play a key role in cognitive processes and affect blinking. This study demonstrates the possibility that blink rate variability dynamics at rest carry information about cognitive performance and can be employed in the assessment of cognitive abilities without taking a test.

A local dynamic correlation function from inelastic neutron scattering

International Nuclear Information System (INIS)

McQueeney, R.J.

1997-01-01

Information about local and dynamic atomic correlations can be obtained from inelastic neutron scattering measurements by Fourier transform of the Q-dependent intensity oscillations at a particular frequency. A local dynamic structure function, S(r,ω), is defined from the dynamic scattering function, S(Q,ω), such that the elastic and frequency-integrated limits correspond to the average and instantaneous pair-distribution functions, respectively. As an example, S(r,ω) is calculated for polycrystalline aluminum in a model where atomic motions are entirely due to harmonic phonons

The Extremism of Two Variable Function Based on the Positive Definite Property

Institute of Scientific and Technical Information of China (English)

Lü Bao-xian; LI Xiu-li

2004-01-01

In this paper we give out a sufficientand solution of quadratic function's maximum with theory of quadratic form and give out the definition of the positivedefinite property of the following homogeneous polynomials of degree 2n two variables function, based on the definite of localmaximum of two variables function.

Climate Variability Structures Plant Community Dynamics in Mediterranean Restored and Reference Tidal Wetlands

Directory of Open Access Journals (Sweden)

Dylan E. Chapple

2017-03-01

Full Text Available In Mediterranean regions and other areas with variable climates, interannual weather variability may impact ecosystem dynamics, and by extension ecological restoration projects. Conditions at reference sites, which are often used to evaluate restoration projects, may also be influenced by weather variability, confounding interpretations of restoration outcomes. To better understand the influence of weather variability on plant community dynamics, we explore change in a vegetation dataset collected between 1990 and 2005 at a historic tidal wetland reference site and a nearby tidal wetland restoration project initiated in 1976 in California’s San Francisco (SF Bay. To determine the factors influencing reference and restoration trajectories, we examine changes in plant community identity in relation to annual salinity levels in the SF Bay, annual rainfall, and tidal channel structure. Over the entire study period, both sites experienced significant directional change away from the 1990 community. Community change was accelerated following low salinity conditions that resulted from strong El Niño events in 1994–1995 and 1997–1998. Overall rates of change were greater at the restoration site and driven by a combination of dominant and sub-dominant species, whereas change at the reference site was driven by sub-dominant species. Sub-dominant species first appeared at the restoration site in 1996 and incrementally increased during each subsequent year, whereas sub-dominant species cover at the reference site peaked in 1999 and subsequently declined. Our results show that frequent, long-term monitoring is needed to adequately capture plant community dynamics in variable Mediterranean ecosystems and demonstrate the need for expanding restoration monitoring and timing restoration actions to match weather conditions.

Asymptotic functions of many variables and singular operations with Schwartz distributions

International Nuclear Information System (INIS)

Damyanov, B.P.

1987-11-01

A theory of the asymptotic functions for the case of many variables is presented. It is shown that the class F(R N ) of these generalized functions is closed in respect to the linear algebraic and analytic operations, multiplication as well as a set of linear and polynomial changes of the variables. The existence in F(R N ) of analogues (consistent with the linear operations) of the Schwartz distributions with point support is proved. In terms of these analogues, some formulae for singular products and changes of variables of the Dirac δ-function and its derivatives δ (i) (x), x is an element of R N , are given. (author). 14 refs

Environmental variability uncovers disruptive effects of species' interactions on population dynamics.

Science.gov (United States)

Gudmundson, Sara; Eklöf, Anna; Wennergren, Uno

2015-08-07

How species respond to changes in environmental variability has been shown for single species, but the question remains whether these results are transferable to species when incorporated in ecological communities. Here, we address this issue by analysing the same species exposed to a range of environmental variabilities when (i) isolated or (ii) embedded in a food web. We find that all species in food webs exposed to temporally uncorrelated environments (white noise) show the same type of dynamics as isolated species, whereas species in food webs exposed to positively autocorrelated environments (red noise) can respond completely differently compared with isolated species. This is owing to species following their equilibrium densities in a positively autocorrelated environment that in turn enables species-species interactions to come into play. Our results give new insights into species' response to environmental variation. They especially highlight the importance of considering both species' interactions and environmental autocorrelation when studying population dynamics in a fluctuating environment. © 2015 The Author(s).

Dynamical density functional theory for dense atomic liquids

International Nuclear Information System (INIS)

Archer, A J

2006-01-01

Starting from Newton's equations of motion, we derive a dynamical density functional theory (DDFT) applicable to atomic liquids. The theory has the feature that it requires as input the Helmholtz free energy functional from equilibrium density functional theory. This means that, given a reliable equilibrium free energy functional, the correct equilibrium fluid density profile is guaranteed. We show that when the isothermal compressibility is small, the DDFT generates the correct value for the speed of sound in a dense liquid. We also interpret the theory as a dynamical equation for a coarse grained fluid density and show that the theory can be used (making further approximations) to derive the standard mode coupling theory that is used to describe the glass transition. The present theory should provide a useful starting point for describing the dynamics of inhomogeneous atomic fluids

An agent-based model of cellular dynamics and circadian variability in human endotoxemia.

Directory of Open Access Journals (Sweden)

Tung T Nguyen

Full Text Available As cellular variability and circadian rhythmicity play critical roles in immune and inflammatory responses, we present in this study an agent-based model of human endotoxemia to examine the interplay between circadian controls, cellular variability and stochastic dynamics of inflammatory cytokines. The model is qualitatively validated by its ability to reproduce circadian dynamics of inflammatory mediators and critical inflammatory responses after endotoxin administration in vivo. Novel computational concepts are proposed to characterize the cellular variability and synchronization of inflammatory cytokines in a population of heterogeneous leukocytes. Our results suggest that there is a decrease in cell-to-cell variability of inflammatory cytokines while their synchronization is increased after endotoxin challenge. Model parameters that are responsible for IκB production stimulated by NFκB activation and for the production of anti-inflammatory cytokines have large impacts on system behaviors. Additionally, examining time-dependent systemic responses revealed that the system is least vulnerable to endotoxin in the early morning and most vulnerable around midnight. Although much remains to be explored, proposed computational concepts and the model we have pioneered will provide important insights for future investigations and extensions, especially for single-cell studies to discover how cellular variability contributes to clinical implications.

SOERP, Statistics and 2. Order Error Propagation for Function of Random Variables

International Nuclear Information System (INIS)

Cox, N. D.; Miller, C. F.

1985-01-01

1 - Description of problem or function: SOERP computes second-order error propagation equations for the first four moments of a function of independently distributed random variables. SOERP was written for a rigorous second-order error propagation of any function which may be expanded in a multivariable Taylor series, the input variables being independently distributed. The required input consists of numbers directly related to the partial derivatives of the function, evaluated at the nominal values of the input variables and the central moments of the input variables from the second through the eighth. 2 - Method of solution: The development of equations for computing the propagation of errors begins by expressing the function of random variables in a multivariable Taylor series expansion. The Taylor series expansion is then truncated, and statistical operations are applied to the series in order to obtain equations for the moments (about the origin) of the distribution of the computed value. If the Taylor series is truncated after powers of two, the procedure produces second-order error propagation equations. 3 - Restrictions on the complexity of the problem: The maximum number of component variables allowed is 30. The IBM version will only process one set of input data per run

Analysis of Uncertainty in Dynamic Processes Development of Banks Functioning

Directory of Open Access Journals (Sweden)

Aleksei V. Korovyakovskii

2013-01-01

Full Text Available The paper offers the approach to measure of uncertainty estimation in dynamic processes of banks functioning, using statistic data of different banking operations indicators. To calculate measure of uncertainty in dynamic processes of banks functioning the phase images of relevant sets of statistic data are considered. Besides, it is shown that the form of phase image of the studied sets of statistic data can act as a basis of measure of uncertainty estimation in dynamic processes of banks functioning. The set of analytical characteristics are offered to formalize the form of phase image definition of the studied sets of statistic data. It is shown that the offered analytical characteristics consider inequality of changes in values of the studied sets of statistic data, which is one of the ways of uncertainty display in dynamic processes development. The invariant estimates of measure of uncertainty in dynamic processes of banks functioning, considering significant changes in absolute values of the same indicators for different banks were obtained. The examples of calculation of measure of uncertainty in dynamic processes of concrete banks functioning were cited.

Coupling functions: Universal insights into dynamical interaction mechanisms

Science.gov (United States)

Stankovski, Tomislav; Pereira, Tiago; McClintock, Peter V. E.; Stefanovska, Aneta

2017-10-01

The dynamical systems found in nature are rarely isolated. Instead they interact and influence each other. The coupling functions that connect them contain detailed information about the functional mechanisms underlying the interactions and prescribe the physical rule specifying how an interaction occurs. A coherent and comprehensive review is presented encompassing the rapid progress made recently in the analysis, understanding, and applications of coupling functions. The basic concepts and characteristics of coupling functions are presented through demonstrative examples of different domains, revealing the mechanisms and emphasizing their multivariate nature. The theory of coupling functions is discussed through gradually increasing complexity from strong and weak interactions to globally coupled systems and networks. A variety of methods that have been developed for the detection and reconstruction of coupling functions from measured data is described. These methods are based on different statistical techniques for dynamical inference. Stemming from physics, such methods are being applied in diverse areas of science and technology, including chemistry, biology, physiology, neuroscience, social sciences, mechanics, and secure communications. This breadth of application illustrates the universality of coupling functions for studying the interaction mechanisms of coupled dynamical systems.

Comprehensive Modeling and Analysis of Rotorcraft Variable Speed Propulsion System With Coupled Engine/Transmission/Rotor Dynamics

Science.gov (United States)

DeSmidt, Hans A.; Smith, Edward C.; Bill, Robert C.; Wang, Kon-Well

2013-01-01

This project develops comprehensive modeling and simulation tools for analysis of variable rotor speed helicopter propulsion system dynamics. The Comprehensive Variable-Speed Rotorcraft Propulsion Modeling (CVSRPM) tool developed in this research is used to investigate coupled rotor/engine/fuel control/gearbox/shaft/clutch/flight control system dynamic interactions for several variable rotor speed mission scenarios. In this investigation, a prototypical two-speed Dual-Clutch Transmission (DCT) is proposed and designed to achieve 50 percent rotor speed variation. The comprehensive modeling tool developed in this study is utilized to analyze the two-speed shift response of both a conventional single rotor helicopter and a tiltrotor drive system. In the tiltrotor system, both a Parallel Shift Control (PSC) strategy and a Sequential Shift Control (SSC) strategy for constant and variable forward speed mission profiles are analyzed. Under the PSC strategy, selecting clutch shift-rate results in a design tradeoff between transient engine surge margins and clutch frictional power dissipation. In the case of SSC, clutch power dissipation is drastically reduced in exchange for the necessity to disengage one engine at a time which requires a multi-DCT drive system topology. In addition to comprehensive simulations, several sections are dedicated to detailed analysis of driveline subsystem components under variable speed operation. In particular an aeroelastic simulation of a stiff in-plane rotor using nonlinear quasi-steady blade element theory was conducted to investigate variable speed rotor dynamics. It was found that 2/rev and 4/rev flap and lag vibrations were significant during resonance crossings with 4/rev lagwise loads being directly transferred into drive-system torque disturbances. To capture the clutch engagement dynamics, a nonlinear stick-slip clutch torque model is developed. Also, a transient gas-turbine engine model based on first principles mean

An information theory framework for dynamic functional domain connectivity.

Science.gov (United States)

Vergara, Victor M; Miller, Robyn; Calhoun, Vince

2017-06-01

Dynamic functional network connectivity (dFNC) analyzes time evolution of coherent activity in the brain. In this technique dynamic changes are considered for the whole brain. This paper proposes an information theory framework to measure information flowing among subsets of functional networks call functional domains. Our method aims at estimating bits of information contained and shared among domains. The succession of dynamic functional states is estimated at the domain level. Information quantity is based on the probabilities of observing each dynamic state. Mutual information measurement is then obtained from probabilities across domains. Thus, we named this value the cross domain mutual information (CDMI). Strong CDMIs were observed in relation to the subcortical domain. Domains related to sensorial input, motor control and cerebellum form another CDMI cluster. Information flow among other domains was seldom found. Other methods of dynamic connectivity focus on whole brain dFNC matrices. In the current framework, information theory is applied to states estimated from pairs of multi-network functional domains. In this context, we apply information theory to measure information flow across functional domains. Identified CDMI clusters point to known information pathways in the basal ganglia and also among areas of sensorial input, patterns found in static functional connectivity. In contrast, CDMI across brain areas of higher level cognitive processing follow a different pattern that indicates scarce information sharing. These findings show that employing information theory to formally measured information flow through brain domains reveals additional features of functional connectivity. Copyright © 2017 Elsevier B.V. All rights reserved.

Stiffness Control of Variable Serial Elastic Actuators: Energy Efficiency through Exploitation of Natural Dynamics

Directory of Open Access Journals (Sweden)

Philipp Beckerle

2017-09-01

Full Text Available Variable elastic actuators are very promising for applications in physical human–robot interaction. Besides enabling human safety, such actuators can support energy efficiency, especially if the natural behavior of the system is exploited. In this paper, the power and energy consumption of variable stiffness actuators with serial elasticity is investigated analytically and experimentally. Besides the fundamental mechanics, the influence of friction and electrical losses is discussed. A simple but effective stiffness control method is used to exploit the corresponding knowledge of natural dynamics by tuning the system to antiresonance operation. Despite nonlinear friction effects and additional electrical dynamics, the consideration of the ideal mechanical dynamics is completely sufficient for stiffness control. Simulations and experiments show that this yields a distinct reduction in power and energy consumption, which underlines the suitability of the control strategy.

A Method for Analyzing the Dynamic Response of a Structural System with Variable Mass, Damping and Stiffness

Directory of Open Access Journals (Sweden)

Mike D.R. Zhang

2001-01-01

Full Text Available In this paper, a method for analyzing the dynamic response of a structural system with variable mass, damping and stiffness is first presented. The dynamic equations of the structural system with variable mass and stiffness are derived according to the whole working process of a bridge bucket unloader. At the end of the paper, an engineering numerical example is given.

A variational conformational dynamics approach to the selection of collective variables in metadynamics

Science.gov (United States)

McCarty, James; Parrinello, Michele

2017-11-01

In this paper, we combine two powerful computational techniques, well-tempered metadynamics and time-lagged independent component analysis. The aim is to develop a new tool for studying rare events and exploring complex free energy landscapes. Metadynamics is a well-established and widely used enhanced sampling method whose efficiency depends on an appropriate choice of collective variables. Often the initial choice is not optimal leading to slow convergence. However by analyzing the dynamics generated in one such run with a time-lagged independent component analysis and the techniques recently developed in the area of conformational dynamics, we obtain much more efficient collective variables that are also better capable of illuminating the physics of the system. We demonstrate the power of this approach in two paradigmatic examples.

Unsteady locomotion: integrating muscle function with whole body dynamics and neuromuscular control

Science.gov (United States)

Biewener, Andrew A.; Daley, Monica A.

2009-01-01

Summary By integrating studies of muscle function with analysis of whole body and limb dynamics, broader appreciation of neuromuscular function can be achieved. Ultimately, such studies need to address non-steady locomotor behaviors relevant to animals in their natural environments. When animals move slowly they likely rely on voluntary coordination of movement involving higher brain centers. However, when moving fast, their movements depend more strongly on responses controlled at more local levels. Our focus here is on control of fast-running locomotion. A key observation emerging from studies of steady level locomotion is that simple spring-mass dynamics, which help to economize energy expenditure, also apply to stabilization of unsteady running. Spring-mass dynamics apply to conditions that involve lateral impulsive perturbations, sudden changes in terrain height, and sudden changes in substrate stiffness or damping. Experimental investigation of unsteady locomotion is challenging, however, due to the variability inherent in such behaviors. Another emerging principle is that initial conditions associated with postural changes following a perturbation define different context-dependent stabilization responses. Distinct stabilization modes following a perturbation likely result from proximo-distal differences in limb muscle architecture, function and control strategy. Proximal muscles may be less sensitive to sudden perturbations and appear to operate, in such circumstances, under feed-forward control. In contrast, multiarticular distal muscles operate, via their tendons, to distribute energy among limb joints in a manner that also depends on the initial conditions of limb contact with the ground. Intrinsic properties of these distal muscle–tendon elements, in combination with limb and body dynamics, appear to provide rapid initial stabilizing mechanisms that are often consistent with spring-mass dynamics. These intrinsic mechanisms likely help to simplify the

Dynamic modelling and analysis of a wind turbine with variable speed

NARCIS (Netherlands)

Steinbuch, M.

1986-01-01

On behalf of the operation of the Dutch National Wind Farm, which is under construction now, a study is being performed on the control system design of variable speed wind turbines. To realize this a non-linear dynamic model of a wind turbine with synchronous generator and AC/ DC/AC conversion has

EVIDENCE FOR DYNAMICAL CHANGES IN A TRANSITIONAL PROTOPLANETARY DISK WITH MID-INFRARED VARIABILITY

International Nuclear Information System (INIS)

Muzerolle, James; Flaherty, Kevin; Balog, Zoltan; Smith, Paul S.; Rieke, George H.; Furlan, Elise; Allen, Lori; Muench, August; Calvet, Nuria; D'Alessio, Paola; Megeath, S. Thomas; Sherry, William H.

2009-01-01

We present multi-epoch Spitzer Space Telescope observations of the transitional disk LRLL 31 in the 2-3 Myr old star-forming region IC 348. Our measurements show remarkable mid-infrared variability on timescales as short as one week. The infrared continuum emission exhibits systematic wavelength-dependent changes that suggest corresponding dynamical changes in the inner disk structure and variable shadowing of outer disk material. We propose several possible sources for the structural changes, including a variable accretion rate or a stellar or planetary companion embedded in the disk. Our results indicate that variability studies in the infrared can provide important new constraints on protoplanetary disk behavior.

Kinetic and dynamic probability-density-function descriptions of disperse turbulent two-phase flows

Science.gov (United States)

Minier, Jean-Pierre; Profeta, Christophe

2015-11-01

This article analyzes the status of two classical one-particle probability density function (PDF) descriptions of the dynamics of discrete particles dispersed in turbulent flows. The first PDF formulation considers only the process made up by particle position and velocity Zp=(xp,Up) and is represented by its PDF p (t ;yp,Vp) which is the solution of a kinetic PDF equation obtained through a flux closure based on the Furutsu-Novikov theorem. The second PDF formulation includes fluid variables into the particle state vector, for example, the fluid velocity seen by particles Zp=(xp,Up,Us) , and, consequently, handles an extended PDF p (t ;yp,Vp,Vs) which is the solution of a dynamic PDF equation. For high-Reynolds-number fluid flows, a typical formulation of the latter category relies on a Langevin model for the trajectories of the fluid seen or, conversely, on a Fokker-Planck equation for the extended PDF. In the present work, a new derivation of the kinetic PDF equation is worked out and new physical expressions of the dispersion tensors entering the kinetic PDF equation are obtained by starting from the extended PDF and integrating over the fluid seen. This demonstrates that, under the same assumption of a Gaussian colored noise and irrespective of the specific stochastic model chosen for the fluid seen, the kinetic PDF description is the marginal of a dynamic PDF one. However, a detailed analysis reveals that kinetic PDF models of particle dynamics in turbulent flows described by statistical correlations constitute incomplete stand-alone PDF descriptions and, moreover, that present kinetic-PDF equations are mathematically ill posed. This is shown to be the consequence of the non-Markovian characteristic of the stochastic process retained to describe the system and the use of an external colored noise. Furthermore, developments bring out that well-posed PDF descriptions are essentially due to a proper choice of the variables selected to describe physical systems

Analogy between electromagnetic potentials and wave-like dynamic variables with connections to quantum theory

Science.gov (United States)

Yang, Chen

2018-05-01

The transitions from classical theories to quantum theories have attracted many interests. This paper demonstrates the analogy between the electromagnetic potentials and wave-like dynamic variables with their connections to quantum theory for audiences at advanced undergraduate level and above. In the first part, the counterpart relations in the classical electrodynamics (e.g. gauge transform and Lorenz condition) and classical mechanics (e.g. Legendre transform and free particle condition) are presented. These relations lead to similar governing equations of the field variables and dynamic variables. The Lorenz gauge, scalar potential and vector potential manifest a one-to-one similarity to the action, Hamiltonian and momentum, respectively. In the second part, the connections between the classical pictures of electromagnetic field and particle to quantum picture are presented. By characterising the states of electromagnetic field and particle via their (corresponding) variables, their evolution pictures manifest the same algebraic structure (isomorphic). Subsequently, pictures of the electromagnetic field and particle are compared to the quantum picture and their interconnections are given. A brief summary of the obtained results are presented at the end of the paper.

Halo control, beam matching, and new dynamical variables for beam distributions

International Nuclear Information System (INIS)

Lysenko, W.; Parsa, Z.

1997-01-01

We present the status of our work on physics models that relate release to the understanding and control of beam halo, which is a cause of particle loss in high power ion linear accelerators. We can minimize these particle losses, even in the presence of nonlinearities, by ensuring the beam is matched to high order. Our goal is to determine new dynamical variables that enable us to more directly solve for the evolution of the halo. We considered moments and several new variables, using a Lie-Poisson formulation whenever possible. Using symbolic techniques, we computed high-order matches and mode invariants (analogs of moment invariants) in the new variables. A promising new development developments is that of the variables we call weighted moments, which allow us to compute high-order nonlinear effects (like halos) while making use of well-developed existing results and computational techniques developed for studying first order effects. copyright 1997 American Institute of Physics

Targeted quantification of functional enzyme dynamics in environmental samples for microbially mediated biogeochemical processes: Targeted quantification of functional enzyme dynamics

Energy Technology Data Exchange (ETDEWEB)

Li, Minjing [School of Environmental Studies, China University of Geosciences, Wuhan 430074 People' s Republic of China; Gao, Yuqian [Pacific Northwest National Laboratory, Richland, WA 99354 USA; Qian, Wei-Jun [Pacific Northwest National Laboratory, Richland, WA 99354 USA; Shi, Liang [Pacific Northwest National Laboratory, Richland, WA 99354 USA; Liu, Yuanyuan [Pacific Northwest National Laboratory, Richland, WA 99354 USA; Nelson, William C. [Pacific Northwest National Laboratory, Richland, WA 99354 USA; Nicora, Carrie D. [Pacific Northwest National Laboratory, Richland, WA 99354 USA; Resch, Charles T. [Pacific Northwest National Laboratory, Richland, WA 99354 USA; Thompson, Christopher [Pacific Northwest National Laboratory, Richland, WA 99354 USA; Yan, Sen [School of Environmental Studies, China University of Geosciences, Wuhan 430074 People' s Republic of China; Fredrickson, James K. [Pacific Northwest National Laboratory, Richland, WA 99354 USA; Zachara, John M. [Pacific Northwest National Laboratory, Richland, WA 99354 USA; Liu, Chongxuan [Pacific Northwest National Laboratory, Richland, WA 99354 USA; School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen 518055 People' s Republic of China

2017-07-13

Microbially mediated biogeochemical processes are catalyzed by enzymes that control the transformation of carbon, nitrogen, and other elements in environment. The dynamic linkage between enzymes and biogeochemical species transformation has, however, rarely been investigated because of the lack of analytical approaches to efficiently and reliably quantify enzymes and their dynamics in soils and sediments. Herein, we developed a signature peptide-based technique for sensitively quantifying dissimilatory and assimilatory enzymes using nitrate-reducing enzymes in a hyporheic zone sediment as an example. Moreover, the measured changes in enzyme concentration were found to correlate with the nitrate reduction rate in a way different from that inferred from biogeochemical models based on biomass or functional genes as surrogates for functional enzymes. This phenomenon has important implications for understanding and modeling the dynamics of microbial community functions and biogeochemical processes in environments. Our results also demonstrate the importance of enzyme quantification for the identification and interrogation of those biogeochemical processes with low metabolite concentrations as a result of faster enzyme-catalyzed consumption of metabolites than their production. The dynamic enzyme behaviors provide a basis for the development of enzyme-based models to describe the relationship between the microbial community and biogeochemical processes.

Virtual continuity of the measurable functions of several variables, and Sobolev embedding theorems

OpenAIRE

Vershik, Anatoly; Zatitskiy, Pavel; Petrov, Fedor

2013-01-01

Classical Luzin's theorem states that the measurable function of one variable is "almost" continuous. This is not so anymore for functions of several variables. The search of right analogue of the Luzin theorem leads to a notion of virtually continuous functions of several variables. This probably new notion appears implicitly in the statements like embeddings theorems and traces theorems for Sobolev spaces. In fact, it reveals their nature as theorems about virtual continuity. This notion is...

Dynamic Variables Fail to Predict Fluid Responsiveness in an Animal Model With Pericardial Effusion.

Science.gov (United States)

Broch, Ole; Renner, Jochen; Meybohm, Patrick; Albrecht, Martin; Höcker, Jan; Haneya, Assad; Steinfath, Markus; Bein, Berthold; Gruenewald, Matthias

2016-10-01

The reliability of dynamic and volumetric variables of fluid responsiveness in the presence of pericardial effusion is still elusive. The aim of the present study was to investigate their predictive power in a porcine model with hemodynamic relevant pericardial effusion. A single-center animal investigation. Twelve German domestic pigs. Pigs were studied before and during pericardial effusion. Instrumentation included a pulmonary artery catheter and a transpulmonary thermodilution catheter in the femoral artery. Hemodynamic variables like cardiac output (COPAC) and stroke volume (SVPAC) derived from pulmonary artery catheter, global end-diastolic volume (GEDV), stroke volume variation (SVV), and pulse-pressure variation (PPV) were obtained. At baseline, SVV, PPV, GEDV, COPAC, and SVPAC reliably predicted fluid responsiveness (area under the curve 0.81 [p = 0.02], 0.82 [p = 0.02], 0.74 [p = 0.07], 0.74 [p = 0.07], 0.82 [p = 0.02]). After establishment of pericardial effusion the predictive power of dynamic variables was impaired and only COPAC and SVPAC and GEDV allowed significant prediction of fluid responsiveness (area under the curve 0.77 [p = 0.04], 0.76 [p = 0.05], 0.83 [p = 0.01]) with clinically relevant changes in threshold values. In this porcine model, hemodynamic relevant pericardial effusion abolished the ability of dynamic variables to predict fluid responsiveness. COPAC, SVPAC, and GEDV enabled prediction, but their threshold values were significantly changed. Copyright © 2016 Elsevier Inc. All rights reserved.

Dynamics of a pulsed continuous-variable quantum memory

DEFF Research Database (Denmark)

Dantan, Aurelien Romain; Cviklinski, Jean; Pinard, Michel

2006-01-01

We study the transfer dynamics of nonclassical fluctuations of light to the ground-state collective spin components of an atomic ensemble during a pulsed quantum memory sequence, and evaluate the relevant physical quantities to be measured in order to characterize such a quantum memory. We show...... in particular that the fluctuations stored into the atoms are emitted in temporal modes which are always different from those of the readout pulse, but which can nevertheless be retrieved efficiently using a suitable temporal mode-matching technique. We give a simple toy model—a cavity with variable...... transmission—that accounts for the behavior of the atomic quantum memory....

Capturing Dynamics of Biased Attention: Are New Attention Variability Measures the Way Forward?

Directory of Open Access Journals (Sweden)

Anne-Wil Kruijt

Full Text Available New indices, calculated on data from the widely used Dot Probe Task, were recently proposed to capture variability in biased attention allocation. We observed that it remains unclear which data pattern is meant to be indicative of dynamic bias and thus to be captured by these indices. Moreover, we hypothesized that the new indices are sensitive to SD differences at the response time (RT level in the absence of bias.Randomly generated datasets were analyzed to assess properties of the Attention Bias Variability (ABV and Trial Level Bias Score (TL-BS indices. Sensitivity to creating differences in 1 RT standard deviation, 2 mean RT, and 3 bias magnitude were assessed. In addition, two possible definitions of dynamic attention bias were explored by creating differences in 4 frequency of bias switching, and 5 bias magnitude in the presence of constant switching.ABV and TL-BS indices were found highly sensitive to increasing SD at the response time level, insensitive to increasing bias, linearly sensitive to increasing bias magnitude in the presence of bias switches, and non-linearly sensitive to increasing the frequency of bias switches. The ABV index was also found responsive to increasing mean response times in the absence of bias.Recently proposed DPT derived variability indices cannot uncouple measurement error from bias variability. Significant group differences may be observed even if there is no bias present in any individual dataset. This renders the new indices in their current form unfit for empirical purposes. Our discussion focuses on fostering debate and ideas for new research to validate the potentially very important notion of biased attention being dynamic.

Screening variability and change of soil moisture under wide-ranging climate conditions: Snow dynamics effects.

Science.gov (United States)

Verrot, Lucile; Destouni, Georgia

2015-01-01

Soil moisture influences and is influenced by water, climate, and ecosystem conditions, affecting associated ecosystem services in the landscape. This paper couples snow storage-melting dynamics with an analytical modeling approach to screening basin-scale, long-term soil moisture variability and change in a changing climate. This coupling enables assessment of both spatial differences and temporal changes across a wide range of hydro-climatic conditions. Model application is exemplified for two major Swedish hydrological basins, Norrström and Piteälven. These are located along a steep temperature gradient and have experienced different hydro-climatic changes over the time period of study, 1950-2009. Spatially, average intra-annual variability of soil moisture differs considerably between the basins due to their temperature-related differences in snow dynamics. With regard to temporal change, the long-term average state and intra-annual variability of soil moisture have not changed much, while inter-annual variability has changed considerably in response to hydro-climatic changes experienced so far in each basin.

Impact of sociodemographic variables on executive functions.

Science.gov (United States)

Campanholo, Kenia Repiso; Boa, Izadora Nogueira Fonte; Hodroj, Flávia Cristina da Silva Araujo; Guerra, Glaucia Rosana Benute; Miotto, Eliane Correa; de Lucia, Mara Cristina Souza

2017-01-01

Executive functions (EFs) regulate human behavior and allow individuals to interact and act in the world. EFs are sensitive to sociodemographic variables such as age, which promotes their decline, and to others that can exert a neuroprotective effect. To assess the predictive role of education, occupation and family income on decline in executive functions among a sample with a wide age range. A total of 925 participants aged 18-89 years with 1-28 years' education were submitted to assessment of executive functions using the Card Sorting Test (CST), Phonemic Verbal Fluency (FAS) Task and Semantic Verbal Fluency (SVF) Task. Data on income, occupation and educational level were collected for the sample. The data were analyzed using Linear Regression, as well as Pearson's and Spearman's Correlation. Age showed a significant negative correlation (p<0.001) with performance on the CST, FAS and SVF, whereas education, income and occupation were positively associated (p<0.001) with the tasks applied. After application of the multivariate linear regression model, a significant positive relationship with the FAS was maintained only for education (p<0.001) and income (p<0.001). The negative relationship of age (p<0.001) and positive relationship of both education (p<0.001) and income (p<0.001and p=0.003) were evident on the CST and SVF. Educational level and income positively influenced participants' results on executive function tests, attenuating expected decline for age. However, no relationship was found between occupation and the cognitive variables investigated.

Impact of sociodemographic variables on executive functions

Directory of Open Access Journals (Sweden)

Kenia Repiso Campanholo

Full Text Available ABSTRACT Executive functions (EFs regulate human behavior and allow individuals to interact and act in the world. EFs are sensitive to sociodemographic variables such as age, which promotes their decline, and to others that can exert a neuroprotective effect. Objective: To assess the predictive role of education, occupation and family income on decline in executive functions among a sample with a wide age range. Methods: A total of 925 participants aged 18-89 years with 1-28 years' education were submitted to assessment of executive functions using the Card Sorting Test (CST, Phonemic Verbal Fluency (FAS Task and Semantic Verbal Fluency (SVF Task. Data on income, occupation and educational level were collected for the sample. The data were analyzed using Linear Regression, as well as Pearson's and Spearman's Correlation. Results: Age showed a significant negative correlation (p<0.001 with performance on the CST, FAS and SVF, whereas education, income and occupation were positively associated (p<0.001 with the tasks applied. After application of the multivariate linear regression model, a significant positive relationship with the FAS was maintained only for education (p<0.001 and income (p<0.001. The negative relationship of age (p<0.001 and positive relationship of both education (p<0.001 and income (p<0.001 and p=0.003 were evident on the CST and SVF. Conclusion: Educational level and income positively influenced participants' results on executive function tests, attenuating expected decline for age. However, no relationship was found between occupation and the cognitive variables investigated.

Functions of a complex variable and some of their applications

CERN Document Server

Fuchs, B A; Sneddon, I N; Ulam, S

1961-01-01

Functions of a Complex Variable and Some of Their Applications, Volume 1, discusses the fundamental ideas of the theory of functions of a complex variable. The book is the result of a complete rewriting and revision of a translation of the second (1957) Russian edition. Numerous changes and additions have been made, both in the text and in the solutions of the Exercises. The book begins with a review of arithmetical operations with complex numbers. Separate chapters discuss the fundamentals of complex analysis; the concept of conformal transformations; the most important of the elementary fun

Suppression of chaos at slow variables by rapidly mixing fast dynamics through linear energy-preserving coupling

OpenAIRE

Abramov, Rafail V.

2011-01-01

Chaotic multiscale dynamical systems are common in many areas of science, one of the examples being the interaction of the low-frequency dynamics in the atmosphere with the fast turbulent weather dynamics. One of the key questions about chaotic multiscale systems is how the fast dynamics affects chaos at the slow variables, and, therefore, impacts uncertainty and predictability of the slow dynamics. Here we demonstrate that the linear slow-fast coupling with the total energy conservation prop...

Exploiting Fast-Variables to Understand Population Dynamics and Evolution

Science.gov (United States)

Constable, George W. A.; McKane, Alan J.

2017-11-01

We describe a continuous-time modelling framework for biological population dynamics that accounts for demographic noise. In the spirit of the methodology used by statistical physicists, transitions between the states of the system are caused by individual events while the dynamics are described in terms of the time-evolution of a probability density function. In general, the application of the diffusion approximation still leaves a description that is quite complex. However, in many biological applications one or more of the processes happen slowly relative to the system's other processes, and the dynamics can be approximated as occurring within a slow low-dimensional subspace. We review these time-scale separation arguments and analyse the more simple stochastic dynamics that result in a number of cases. We stress that it is important to retain the demographic noise derived in this way, and emphasise this point by showing that it can alter the direction of selection compared to the prediction made from an analysis of the corresponding deterministic model.

Influence of forced respiration on nonlinear dynamics in heart rate variability

DEFF Research Database (Denmark)

Kanters, J K; Højgaard, M V; Agner, E

1997-01-01

Although it is doubtful whether the normal sinus rhythm can be described as low-dimensional chaos, there is evidence for inherent nonlinear dynamics and determinism in time series of consecutive R-R intervals. However, the physiological origin for these nonlinearities is unknown. The aim...... with a metronome set to 12 min(-1). Nonlinear dynamics were measured as the correlation dimension and the nonlinear prediction error. Complexity expressed as correlation dimension was unchanged from normal respiration, 9.1 +/- 0.5, compared with forced respiration, 9.3 +/- 0.6. Also, nonlinear determinism...... expressed as the nonlinear prediction error did not differ between spontaneous respiration, 32.3 +/- 3.4 ms, and forced respiration, 31.9 +/- 5.7. It is concluded that the origin of the nonlinear dynamics in heart rate variability is not a nonlinear input from the respiration into the cardiovascular...

WKB wave function for many-variable systems

International Nuclear Information System (INIS)

Sakita, B.; Tzani, R.

1986-01-01

The WKB method is a non-perturbative semi-classical method in quantum mechanics. The method for a system of one degree of freedom is well known and described in standard textbooks. The method for a system with many degrees of freedom especially for quantum fields is more involved. There exist two methods: Feynman path integral and Schrodinger wave function. The Feynman path integral WKB method is essentially a stationary phase approximation for Feynman path integrals. The WKB Schrodinger wave function method is on the other hand an extension of the standard WKB to many-variable systems

Variable-structure approaches analysis, simulation, robust control and estimation of uncertain dynamic processes

CERN Document Server

Senkel, Luise

2016-01-01

This edited book aims at presenting current research activities in the field of robust variable-structure systems. The scope equally comprises highlighting novel methodological aspects as well as presenting the use of variable-structure techniques in industrial applications including their efficient implementation on hardware for real-time control. The target audience primarily comprises research experts in the field of control theory and nonlinear dynamics but the book may also be beneficial for graduate students.

Extracting neuronal functional network dynamics via adaptive Granger causality analysis.

Science.gov (United States)

Sheikhattar, Alireza; Miran, Sina; Liu, Ji; Fritz, Jonathan B; Shamma, Shihab A; Kanold, Patrick O; Babadi, Behtash

2018-04-24

Quantifying the functional relations between the nodes in a network based on local observations is a key challenge in studying complex systems. Most existing time series analysis techniques for this purpose provide static estimates of the network properties, pertain to stationary Gaussian data, or do not take into account the ubiquitous sparsity in the underlying functional networks. When applied to spike recordings from neuronal ensembles undergoing rapid task-dependent dynamics, they thus hinder a precise statistical characterization of the dynamic neuronal functional networks underlying adaptive behavior. We develop a dynamic estimation and inference paradigm for extracting functional neuronal network dynamics in the sense of Granger, by integrating techniques from adaptive filtering, compressed sensing, point process theory, and high-dimensional statistics. We demonstrate the utility of our proposed paradigm through theoretical analysis, algorithm development, and application to synthetic and real data. Application of our techniques to two-photon Ca 2+ imaging experiments from the mouse auditory cortex reveals unique features of the functional neuronal network structures underlying spontaneous activity at unprecedented spatiotemporal resolution. Our analysis of simultaneous recordings from the ferret auditory and prefrontal cortical areas suggests evidence for the role of rapid top-down and bottom-up functional dynamics across these areas involved in robust attentive behavior.

Platelet function, anthropometric and metabolic variables in Nigerian ...

African Journals Online (AJOL)

Platelet function, anthropometric and metabolic variables in Nigerian Type 2 Diabetic patients. ... (BSA) were assessed as indices of anthropometry, fasting blood sugar (FBS), plasma cholesterol and triglycerides (TAG) were determined using standard method and platelet aggregation test was done on the whole blood.

Variable Displacement Control of the Concrete Pumping System Based on Dynamic Programming

Directory of Open Access Journals (Sweden)

Ye Min

2017-01-01

Full Text Available To solve the problems of cylinder piston striking cylinder and the hydraulic shocking of the main pump, and causing energy waste problem, the method of variable displacement control of piston stroke was proposed. In order to achieve effective control of the piston stroke, variable displacement control model was established under the physical constraint condition of non-collision between piston and cylinder. And the control process was realized by Dynamic Programming(DP, the simulation and test results show that piston of concrete pumping system don’t strike cylinder and reduce the hydraulic shock of the main pump outlet, meanwhile improve the response speed of the cylinder and achieve energy-saving purposes under varying loads. This control model built in the integration design space of structure variable and control variable is of guiding significance for solving open-loop system’s engineering problems.

Dynamical variability in Saturn Equatorial Atmosphere

Science.gov (United States)

Sánchez-Lavega, A.; Pérez-Hoyos, S.; Hueso, R.; Rojas, J. F.; French, R. G.; Grupo Ciencias Planetarias Team

2003-05-01

Historical ground-based and recent HST observations show that Saturn's Equatorial Atmosphere is the region where the most intense large-scale dynamical variability took place at cloud level in the planet. Large-scale convective storms (nicknamed the ``Great White Spots") occurred in 1876, 1933 and 1990. The best studied case (the 1990 storm), produced a dramatic change in the cloud aspect in the years following the outburst of September 1990. Subsequently, a new large storm formed in 1994 and from 1996 to 2002 our HST observations showed periods of unusual cloud activity in the southern part of the Equator. This contrast with the aspect observed during the Voyager 1 and 2 encounters in 1980 and 1981 when the Equator was calm, except for some mid-scale plume-like features seen in 1981. Cloud-tracking of the features have revealed a dramatic slow down in the equatorial winds from maximum velocities of ˜ 475 m/s in 1980-1981 to ˜ 275 m/s during 1996-2002, as we have recently reported in Nature, Vol. 423, 623 (2003). We discuss the possibility that seasonal and ring-shadowing effects are involved in generating this activity and variability. Acknowledgements: This work was supported by the Spanish MCYT PNAYA 2000-0932. SPH acknowledges a PhD fellowship from the Spanish MECD and RH a post-doc fellowship from Gobierno Vasco. RGF was supported in part by NASA's Planetary Geology and Geophysics Program NAG5-10197 and STSCI Grant GO-08660.01A.

HYPERDIRE. HYPERgeometric functions DIfferential REduction. MATEMATICA based packages for differential reduction of generalized hypergeometric functions. FD and FS Horn-type hypergeometric functions of three variables

International Nuclear Information System (INIS)

Bytev, Vladimir V.; Kalmykov, Mikhail Yu.; Moch, Sven-Olaf; Hamburg Univ.

2013-12-01

HYPERDIRE is a project devoted to the creation of a set of Mathematica based programs for the differential reduction of hypergeometric functions. The current version includes two parts: the first one, FdFunction, for manipulations with Appell hypergeometric functions F D of r variables; and the second one, FsFunction, for manipulations with Lauricella-Saran hypergeometric functions F S of three variables. Both functions are related with one-loop Feynman diagrams.

Proton magnetic resonance imaging for assessment of lung function and respiratory dynamics

International Nuclear Information System (INIS)

Eichinger, Monika; Tetzlaff, Ralf; Puderbach, Michael; Woodhouse, Neil; Kauczor, H.-U.

2007-01-01

Since many pulmonary diseases present with a variable regional involvement, modalities for assessment of regional lung function gained increasing attention over the last years. Together with lung perfusion and gas exchange, ventilation, as a result of the interaction of the respiratory pump and the lungs, is an indispensable component of lung function. So far, this complex mechanism is still mainly assessed indirectly and globally. A differentiation between the individual determining factors of ventilation would be crucial for precise diagnostics and adequate treatment. By dynamic imaging of the respiratory pump, the mechanical components of ventilation can be assessed regionally. Amongst imaging modalities applicable to this topic, magnetic resonance imaging (MRI), as a tool not relying on ionising radiation, is the most attractive. Recent advances in MRI technology have made it possible to assess diaphragmatic and chest wall motion, static and dynamic lung volumes, as well as regional lung function. Even though existing studies show large heterogeneity in design and applied methods, it becomes evident that MRI is capable to visualise pulmonary function as well as diaphragmatic and thoracic wall movement, providing new insights into lung physiology. Partly contradictory results and conclusions are most likely caused by technical limitations, limited number of studies and small sample size. Existing studies mainly evaluate possible imaging techniques and concentrate on normal physiology. The few studies in patients with lung cancer and emphysema already give a promising outlook for these techniques from which an increasing impact on improved and quantitative disease characterization as well as better patient management can be expected

Structure and Dynamics of Hydroxyl-Functionalized Protic Ammonium Carboxylate Ionic Liquids.

Science.gov (United States)

Thummuru, Dhileep Nagi Reddy; Mallik, Bhabani S

2017-10-26

We performed classical molecular dynamics simulations to investigate the structure and dynamics of protic ionic liquids, 2-hydroxy ethylammonium acetate, ethylammonium hydroxyacetate, and 2-hydroxyethylammonium hydroxyacetate at ambient conditions. Structural properties such as density, radial distribution functions, spatial distribution functions, and structure factors have been calculated. Dynamic properties such as mean square displacements, as well as residence and hydrogen bond dynamics have also been calculated. Hydrogen bond lifetimes and residence times change with the addition of hydroxyl groups. We observe that when a hydroxyl group is present on the cation, dynamics become very slow and it forms a strong hydrogen bond with carboxylate oxygen atoms of the anion. The hydroxyl functionalized ILs show more dynamic diversity than structurally similar ILs.

A Particle Swarm Optimization Algorithm with Variable Random Functions and Mutation

Institute of Scientific and Technical Information of China (English)

ZHOU Xiao-Jun; YANG Chun-Hua; GUI Wei-Hua; DONG Tian-Xue

2014-01-01

The convergence analysis of the standard particle swarm optimization (PSO) has shown that the changing of random functions, personal best and group best has the potential to improve the performance of the PSO. In this paper, a novel strategy with variable random functions and polynomial mutation is introduced into the PSO, which is called particle swarm optimization algorithm with variable random functions and mutation (PSO-RM). Random functions are adjusted with the density of the population so as to manipulate the weight of cognition part and social part. Mutation is executed on both personal best particle and group best particle to explore new areas. Experiment results have demonstrated the effectiveness of the strategy.

Thomas-Fermi molecular dynamics

International Nuclear Information System (INIS)

Clerouin, J.; Pollock, E.L.; Zerah, G.

1992-01-01

A three-dimensional density-functional molecular-dynamics code is developed for the Thomas-Fermi density functional as a prototype for density functionals using only the density. Following Car and Parrinello [Phys. Rev. Lett. 55, 2471 (1985)], the electronic density is treated as a dynamical variable. The electronic densities are verified against a multi-ion Thomas-Fermi algorithm due to Parker [Phys. Rev. A 38, 2205 (1988)]. As an initial application, the effect of electronic polarization in enhancing ionic diffusion in strongly coupled plasmas is demonstrated

Dynamic Stiffness Transfer Function of an Electromechanical Actuator Using System Identification

Science.gov (United States)

Kim, Sang Hwa; Tahk, Min-Jea

2018-04-01

In the aeroelastic analysis of flight vehicles with electromechanical actuators (EMAs), an accurate prediction of flutter requires dynamic stiffness characteristics of the EMA. The dynamic stiffness transfer function of the EMA with brushless direct current (BLDC) motor can be obtained by conducting complicated mathematical calculations of control algorithms and mechanical/electrical nonlinearities using linearization techniques. Thus, system identification approaches using experimental data, as an alternative, have considerable advantages. However, the test setup for system identification is expensive and complex, and experimental procedures for data collection are time-consuming tasks. To obtain the dynamic stiffness transfer function, this paper proposes a linear system identification method that uses information obtained from a reliable dynamic stiffness model with a control algorithm and nonlinearities. The results of this study show that the system identification procedure is compact, and the transfer function is able to describe the dynamic stiffness characteristics of the EMA. In addition, to verify the validity of the system identification method, the simulation results of the dynamic stiffness transfer function and the dynamic stiffness model were compared with the experimental data for various external loads.

Molecular dynamics based enhanced sampling of collective variables with very large time steps

Science.gov (United States)

Chen, Pei-Yang; Tuckerman, Mark E.

2018-01-01

Enhanced sampling techniques that target a set of collective variables and that use molecular dynamics as the driving engine have seen widespread application in the computational molecular sciences as a means to explore the free-energy landscapes of complex systems. The use of molecular dynamics as the fundamental driver of the sampling requires the introduction of a time step whose magnitude is limited by the fastest motions in a system. While standard multiple time-stepping methods allow larger time steps to be employed for the slower and computationally more expensive forces, the maximum achievable increase in time step is limited by resonance phenomena, which inextricably couple fast and slow motions. Recently, we introduced deterministic and stochastic resonance-free multiple time step algorithms for molecular dynamics that solve this resonance problem and allow ten- to twenty-fold gains in the large time step compared to standard multiple time step algorithms [P. Minary et al., Phys. Rev. Lett. 93, 150201 (2004); B. Leimkuhler et al., Mol. Phys. 111, 3579-3594 (2013)]. These methods are based on the imposition of isokinetic constraints that couple the physical system to Nosé-Hoover chains or Nosé-Hoover Langevin schemes. In this paper, we show how to adapt these methods for collective variable-based enhanced sampling techniques, specifically adiabatic free-energy dynamics/temperature-accelerated molecular dynamics, unified free-energy dynamics, and by extension, metadynamics, thus allowing simulations employing these methods to employ similarly very large time steps. The combination of resonance-free multiple time step integrators with free-energy-based enhanced sampling significantly improves the efficiency of conformational exploration.

Contribution of LFP dynamics to single-neuron spiking variability in motor cortex during movement execution

Science.gov (United States)

Rule, Michael E.; Vargas-Irwin, Carlos; Donoghue, John P.; Truccolo, Wilson

2015-01-01

Understanding the sources of variability in single-neuron spiking responses is an important open problem for the theory of neural coding. This variability is thought to result primarily from spontaneous collective dynamics in neuronal networks. Here, we investigate how well collective dynamics reflected in motor cortex local field potentials (LFPs) can account for spiking variability during motor behavior. Neural activity was recorded via microelectrode arrays implanted in ventral and dorsal premotor and primary motor cortices of non-human primates performing naturalistic 3-D reaching and grasping actions. Point process models were used to quantify how well LFP features accounted for spiking variability not explained by the measured 3-D reach and grasp kinematics. LFP features included the instantaneous magnitude, phase and analytic-signal components of narrow band-pass filtered (δ,θ,α,β) LFPs, and analytic signal and amplitude envelope features in higher-frequency bands. Multiband LFP features predicted single-neuron spiking (1ms resolution) with substantial accuracy as assessed via ROC analysis. Notably, however, models including both LFP and kinematics features displayed marginal improvement over kinematics-only models. Furthermore, the small predictive information added by LFP features to kinematic models was redundant to information available in fast-timescale (spiking history. Overall, information in multiband LFP features, although predictive of single-neuron spiking during movement execution, was redundant to information available in movement parameters and spiking history. Our findings suggest that, during movement execution, collective dynamics reflected in motor cortex LFPs primarily relate to sensorimotor processes directly controlling movement output, adding little explanatory power to variability not accounted by movement parameters. PMID:26157365

Effects of climate variability and functional changes on carbon cycling in a temperate deciduous forest

Energy Technology Data Exchange (ETDEWEB)

Wu, Jian

2013-03-15

Temperate forests are globally important carbon (C) stocks and sinks. A decadal (1997-2009) trend of increasing C uptake has been observed in an intensively studied temperate deciduous forest, Soroe (Zealand, Denmark). This gave the impetus to investigate the factors controlling the C cycling and the fundamental processes at work in this type of ecosystem. The major objectives of this study were to (1) evaluate to what extent and at what temporal scales, direct climatic variability and functional changes (e.g. changes in the structure or physiological properties) regulate the interannual variability (IAV) in the ecosystem C balance; (2) provide a synthesis of the ecosystem C budget at this site and (3) investigate whether terrestrial ecosystem models can dynamically simulate the trend of increasing C uptake. Data driven analysis, semi-empirical and process-based modelling experiments were performed in a series of studies in order to provide a complete assessment of the carbon storage and allocation within the ecosystem and clarify the mechanisms responsible for the observed variability and trend in the ecosystem C fluxes. Combining all independently estimated ecosystem carbon budget (ECB) datasets and other calculated ECB components based on mass balance equations, a synthesis of the carbon cycling was performed. The results showed that this temperature deciduous forest was moderately productive with both high rates of gross primary production and ecosystem respiration. Approximately 62% of the gross assimilated carbon was respired by the living plants, while 21% was contributed to the soil as litter production, the latter balancing the total heterotrophic respiration. The remaining 17% was either stored in the plants (mainly as aboveground biomass) or removed from the system as wood production. In general, the ECB component datasets were consistent after the cross-checking. This, together with their characterized uncertainties, can be used in model data fusion

On Szasz-Mirakyan operators of functions of two variables

Directory of Open Access Journals (Sweden)

Lucyna Rempulska

1998-05-01

Full Text Available We consider Szasz-Mirakyan operators in polynomial and exponential weighted spaces of functions of two variables. We give Voronowskaya type theorem and theorem on convergence of certain sequences.

Dynamics of inequalities in geometric function theory

Directory of Open Access Journals (Sweden)

Reich Simeon

2001-01-01

Full Text Available A domain in the complex plane which is star-like with respect to a boundary point can be approximated by domains which are star-like with respect to interior points. This approximation process can be viewed dynamically as an evolution of the null points of the underlying holomorphic functions from the interior of the open unit disk towards a boundary point. We trace these dynamics analytically in terms of the Alexander–Nevanlinna and Robertson inequalities by using the framework of complex dynamical systems and hyperbolic monotonicity.

Asynchronous anti-noise hyper chaotic secure communication system based on dynamic delay and state variables switching

Energy Technology Data Exchange (ETDEWEB)

Liu, Hongjun [Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian 116024 (China); Weifang Vocational College, Weifang 261041 (China); Wang, Xingyuan, E-mail: wangxy@dlut.edu.cn [Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian 116024 (China); Zhu, Quanlong [Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian 116024 (China)

2011-07-18

This Letter designs an asynchronous hyper chaotic secure communication system, which possesses high stability against noise, using dynamic delay and state variables switching to ensure the high security. The relationship between the bit error ratio (BER) and the signal-to-noise ratio (SNR) is analyzed by simulation tests, the results show that the BER can be ensured to reach zero by proportionally adjusting the amplitudes of the state variables and the noise figure. The modules of the transmitter and receiver are implemented, and numerical simulations demonstrate the effectiveness of the system. -- Highlights: → Asynchronous anti-noise hyper chaotic secure communication system. → Dynamic delay and state switching to ensure the high security. → BER can reach zero by adjusting the amplitudes of state variables and noise figure.

Discrete two-sex models of population dynamics: On modelling the mating function

Science.gov (United States)

Bessa-Gomes, Carmen; Legendre, Stéphane; Clobert, Jean

2010-09-01

Although sexual reproduction has long been a central subject of theoretical ecology, until recently its consequences for population dynamics were largely overlooked. This is now changing, and many studies have addressed this issue, showing that when the mating system is taken into account, the population dynamics depends on the relative abundance of males and females, and is non-linear. Moreover, sexual reproduction increases the extinction risk, namely due to the Allee effect. Nevertheless, different studies have identified diverse potential consequences, depending on the choice of mating function. In this study, we investigate the consequences of three alternative mating functions that are frequently used in discrete population models: the minimum; the harmonic mean; and the modified harmonic mean. We consider their consequences at three levels: on the probability that females will breed; on the presence and intensity of the Allee effect; and on the extinction risk. When we consider the harmonic mean, the number of times the individuals of the least abundant sex mate exceeds their mating potential, which implies that with variable sex-ratios the potential reproductive rate is no longer under the modeller's control. Consequently, the female breeding probability exceeds 1 whenever the sex-ratio is male-biased, which constitutes an obvious problem. The use of the harmonic mean is thus only justified if we think that this parameter should be re-defined in order to represent the females' breeding rate and the fact that females may reproduce more than once per breeding season. This phenomenon buffers the Allee effect, and reduces the extinction risk. However, when we consider birth-pulse populations, such a phenomenon is implausible because the number of times females can reproduce per birth season is limited. In general, the minimum or modified harmonic mean mating functions seem to be more suitable for assessing the impact of mating systems on population dynamics.

Computational Fluid Dynamics Modeling of a Supersonic Nozzle and Integration into a Variable Cycle Engine Model

Science.gov (United States)

Connolly, Joseph W.; Friedlander, David; Kopasakis, George

2015-01-01

This paper covers the development of an integrated nonlinear dynamic simulation for a variable cycle turbofan engine and nozzle that can be integrated with an overall vehicle Aero-Propulso-Servo-Elastic (APSE) model. A previously developed variable cycle turbofan engine model is used for this study and is enhanced here to include variable guide vanes allowing for operation across the supersonic flight regime. The primary focus of this study is to improve the fidelity of the model's thrust response by replacing the simple choked flow equation convergent-divergent nozzle model with a MacCormack method based quasi-1D model. The dynamic response of the nozzle model using the MacCormack method is verified by comparing it against a model of the nozzle using the conservation element/solution element method. A methodology is also presented for the integration of the MacCormack nozzle model with the variable cycle engine.

Functional dynamics of cell surface membrane proteins.

Science.gov (United States)

Nishida, Noritaka; Osawa, Masanori; Takeuchi, Koh; Imai, Shunsuke; Stampoulis, Pavlos; Kofuku, Yutaka; Ueda, Takumi; Shimada, Ichio

2014-04-01

Cell surface receptors are integral membrane proteins that receive external stimuli, and transmit signals across plasma membranes. In the conventional view of receptor activation, ligand binding to the extracellular side of the receptor induces conformational changes, which convert the structure of the receptor into an active conformation. However, recent NMR studies of cell surface membrane proteins have revealed that their structures are more dynamic than previously envisioned, and they fluctuate between multiple conformations in an equilibrium on various timescales. In addition, NMR analyses, along with biochemical and cell biological experiments indicated that such dynamical properties are critical for the proper functions of the receptors. In this review, we will describe several NMR studies that revealed direct linkage between the structural dynamics and the functions of the cell surface membrane proteins, such as G-protein coupled receptors (GPCRs), ion channels, membrane transporters, and cell adhesion molecules. Copyright © 2013 Elsevier Inc. All rights reserved.

Fractal analysis of heart rate dynamics as a predictor of mortality in patients with depressed left ventricular function after acute myocardial infarction. TRACE Investigators. TRAndolapril Cardiac Evaluation

DEFF Research Database (Denmark)

Mäkikallio, T H; Høiber, S; Køber, L

1999-01-01

A number of new methods have been recently developed to quantify complex heart rate (HR) dynamics based on nonlinear and fractal analysis, but their value in risk stratification has not been evaluated. This study was designed to determine whether selected new dynamic analysis methods of HR...... variability predict mortality in patients with depressed left ventricular (LV) function after acute myocardial infarction (AMI). Traditional time- and frequency-domain HR variability indexes along with short-term fractal-like correlation properties of RR intervals (exponent alpha) and power-law scaling...

Students' Ways of Thinking about Two-Variable Functions and Rate of Change in Space

Science.gov (United States)

Weber, Eric David

2012-01-01

This dissertation describes an investigation of four students' ways of thinking about functions of two variables and rate of change of those two-variable functions. Most secondary, introductory algebra, pre-calculus, and first and second semester calculus courses do not require students to think about functions of more than one variable. Yet…

Geometric theory of functions of a complex variable

CERN Document Server

Goluzin, G M

1969-01-01

This book is based on lectures on geometric function theory given by the author at Leningrad State University. It studies univalent conformal mapping of simply and multiply connected domains, conformal mapping of multiply connected domains onto a disk, applications of conformal mapping to the study of interior and boundary properties of analytic functions, and general questions of a geometric nature dealing with analytic functions. The second Russian edition upon which this English translation is based differs from the first mainly in the expansion of two chapters and in the addition of a long survey of more recent developments. The book is intended for readers who are already familiar with the basics of the theory of functions of one complex variable.

Dynamic Functional Connectivity States Between the Dorsal and Ventral Sensorimotor Networks Revealed by Dynamic Conditional Correlation Analysis of Resting-State Functional Magnetic Resonance Imaging.

Science.gov (United States)

Syed, Maleeha F; Lindquist, Martin A; Pillai, Jay J; Agarwal, Shruti; Gujar, Sachin K; Choe, Ann S; Caffo, Brian; Sair, Haris I

2017-12-01

Functional connectivity in resting-state functional magnetic resonance imaging (rs-fMRI) has received substantial attention since the initial findings of Biswal et al. Traditional network correlation metrics assume that the functional connectivity in the brain remains stationary over time. However, recent studies have shown that robust temporal fluctuations of functional connectivity among as well as within functional networks exist, challenging this assumption. In this study, these dynamic correlation differences were investigated between the dorsal and ventral sensorimotor networks by applying the dynamic conditional correlation model to rs-fMRI data of 20 healthy subjects. k-Means clustering was used to determine an optimal number of discrete connectivity states (k = 10) of the sensorimotor system across all subjects. Our analysis confirms the existence of differences in dynamic correlation between the dorsal and ventral networks, with highest connectivity found within the ventral motor network.

Crossing the entropy barrier of dynamical zeta functions

International Nuclear Information System (INIS)

Aurich, R.; Bolte, J.; Matthies, C.; Sieber, M.; Steiner, F.

1992-01-01

Dynamical zeta functions are an important tool to quantize chaotic dynamical systems. The basic quantization rules require the computation of the zeta functions on the real energy axis, where the Euler product representations running over the classical periodic orbits usually do not converge due to the existence of the so-called entropy barrier determined by the topological entropy of the classical system. We shown that the convergence properties of the dynamical zeta functions rewritten as Dirichlet series are governed not only by the well-known topological and metric entropy, but depend crucially on subtle statistical properties of the Maslow indices and of the multiplicities of the periodic orbits that are measured by a new parameter for which we introduce the notion of a third entropy. If and only if the third entropy is nonvanishing, one can cross the entropy barrier; if it exceeds a certain value, one can even compute the zeta function in the physical region by means of a convergent Dirichlet series. A simple statistical model is presented which allows to compute the third entropy. Four examples of chaotic systems are studied in detail to test the model numerically. (orig.)

Crossing the entropy barrier of dynamical zeta functions

Energy Technology Data Exchange (ETDEWEB)

Aurich, R.; Bolte, J.; Matthies, C.; Sieber, M.; Steiner, F. (Hamburg Univ. (Germany). 2. Inst. fuer Theoretische Physik)

1992-01-01

Dynamical zeta functions are an important tool to quantize chaotic dynamical systems. The basic quantization rules require the computation of the zeta functions on the real energy axis, where the Euler product representations running over the classical periodic orbits usually do not converge due to the existence of the so-called entropy barrier determined by the topological entropy of the classical system. We shown that the convergence properties of the dynamical zeta functions rewritten as Dirichlet series are governed not only by the well-known topological and metric entropy, but depend crucially on subtle statistical properties of the Maslow indices and of the multiplicities of the periodic orbits that are measured by a new parameter for which we introduce the notion of a third entropy. If and only if the third entropy is nonvanishing, one can cross the entropy barrier; if it exceeds a certain value, one can even compute the zeta function in the physical region by means of a convergent Dirichlet series. A simple statistical model is presented which allows to compute the third entropy. Four examples of chaotic systems are studied in detail to test the model numerically. (orig.).

Function of dynamic models in systems biology: linking structure to behaviour.

Science.gov (United States)

Knüpfer, Christian; Beckstein, Clemens

2013-10-08

Dynamic models in Systems Biology are used in computational simulation experiments for addressing biological questions. The complexity of the modelled biological systems and the growing number and size of the models calls for computer support for modelling and simulation in Systems Biology. This computer support has to be based on formal representations of relevant knowledge fragments. In this paper we describe different functional aspects of dynamic models. This description is conceptually embedded in our "meaning facets" framework which systematises the interpretation of dynamic models in structural, functional and behavioural facets. Here we focus on how function links the structure and the behaviour of a model. Models play a specific role (teleological function) in the scientific process of finding explanations for dynamic phenomena. In order to fulfil this role a model has to be used in simulation experiments (pragmatical function). A simulation experiment always refers to a specific situation and a state of the model and the modelled system (conditional function). We claim that the function of dynamic models refers to both the simulation experiment executed by software (intrinsic function) and the biological experiment which produces the phenomena under investigation (extrinsic function). We use the presented conceptual framework for the function of dynamic models to review formal accounts for functional aspects of models in Systems Biology, such as checklists, ontologies, and formal languages. Furthermore, we identify missing formal accounts for some of the functional aspects. In order to fill one of these gaps we propose an ontology for the teleological function of models. We have thoroughly analysed the role and use of models in Systems Biology. The resulting conceptual framework for the function of models is an important first step towards a comprehensive formal representation of the functional knowledge involved in the modelling and simulation process

Effects of short-term variability of meteorological variables on soil temperature in permafrost regions

Science.gov (United States)

Beer, Christian; Porada, Philipp; Ekici, Altug; Brakebusch, Matthias

2018-03-01

Effects of the short-term temporal variability of meteorological variables on soil temperature in northern high-latitude regions have been investigated. For this, a process-oriented land surface model has been driven using an artificially manipulated climate dataset. Short-term climate variability mainly impacts snow depth, and the thermal diffusivity of lichens and bryophytes. These impacts of climate variability on insulating surface layers together substantially alter the heat exchange between atmosphere and soil. As a result, soil temperature is 0.1 to 0.8 °C higher when climate variability is reduced. Earth system models project warming of the Arctic region but also increasing variability of meteorological variables and more often extreme meteorological events. Therefore, our results show that projected future increases in permafrost temperature and active-layer thickness in response to climate change will be lower (i) when taking into account future changes in short-term variability of meteorological variables and (ii) when representing dynamic snow and lichen and bryophyte functions in land surface models.

Semigroups of transcendental entire functions and their dynamics

Indian Academy of Sciences (India)

DINESH KUMAR

Abstract. We investigate the dynamics of semigroups of transcendental entire func- tions using Fatou–Julia theory. Several results of the dynamics associated with iteration of a transcendental entire function have been extended to transcendental semigroups. We provide some condition for connectivity of the Julia set of the ...

Selfadjoint operators in spaces of functions of infinitely many variables

CERN Document Server

Berezanskiĭ, Yu M

1986-01-01

Questions in the spectral theory of selfadjoint and normal operators acting in spaces of functions of infinitely many variables are studied in this book, and, in particular, the theory of expansions in generalized eigenfunctions of such operators. Both individual operators and arbitrary commuting families of them are considered. A theory of generalized functions of infinitely many variables is constructed. The circle of questions presented has evolved in recent years, especially in connection with problems in quantum field theory. This book will be useful to mathematicians and physicists interested in the indicated questions, as well as to graduate students and students in advanced university courses.

Correlations between Sportsmen’s Morpho-Functional Measurements and Voice Acoustic Variables

Directory of Open Access Journals (Sweden)

Rexhepi Agron M.

2016-12-01

Full Text Available Purpose. Since human voice characteristics are specific to each individual, numerous anthropological studies have been oriented to find significant relationships between voice and morpho-functional features. The goal of this study was to identify the correlation between seven morpho-functional variables and six voice acoustic parameters in sportsmen. Methods. Following the protocols of the International Biological Program, seven morpho-functional variables and six voice acoustic parameters have been measured in 88 male professional athletes from Kosovo, aged 17-35 years, during the period of April-October 2013. The statistical analysis was accomplished through the SPSS program, version 20. The obtained data were analysed through descriptive parameters and with Spearman’s method of correlation analysis. Results. Spearman’s method of correlation showed significant negative correlations (R = -0.215 to -0.613; p = 0.05 between three voice acoustic variables of the fundamental frequency of the voice sample (Mean, Minimum, and Maximum Pitch and six morpho-functional measures (Body Height, Body Weight, Margaria-Kalamen Power Test, Sargent Jump Test, Pull-up Test, and VO2max.abs. Conclusions. The significant correlations imply that the people with higher stature have longer vocal cords and a lower voice. These results encourage investigations on predicting sportsmen’s functional abilities on the basis of their voice acoustic parameters.

Capturing the dynamics of response variability in the brain in ADHD

Directory of Open Access Journals (Sweden)

Janna van Belle

2015-01-01

Full Text Available ADHD is characterized by increased intra-individual variability in response times during the performance of cognitive tasks. However, little is known about developmental changes in intra-individual variability, and how these changes relate to cognitive performance. Twenty subjects with ADHD aged 7–24 years and 20 age-matched, typically developing controls participated in an fMRI-scan while they performed a go-no-go task. We fit an ex-Gaussian distribution on the response distribution to objectively separate extremely slow responses, related to lapses of attention, from variability on fast responses. We assessed developmental changes in these intra-individual variability measures, and investigated their relation to no-go performance. Results show that the ex-Gaussian measures were better predictors of no-go performance than traditional measures of reaction time. Furthermore, we found between-group differences in the change in ex-Gaussian parameters with age, and their relation to task performance: subjects with ADHD showed age-related decreases in their variability on fast responses (sigma, but not in lapses of attention (tau, whereas control subjects showed a decrease in both measures of variability. For control subjects, but not subjects with ADHD, this age-related reduction in variability was predictive of task performance. This group difference was reflected in neural activation: for typically developing subjects, the age-related decrease in intra-individual variability on fast responses (sigma predicted activity in the dorsal anterior cingulate gyrus (dACG, whereas for subjects with ADHD, activity in this region was related to improved no-go performance with age, but not to intra-individual variability. These data show that using more sophisticated measures of intra-individual variability allows the capturing of the dynamics of task performance and associated neural changes not permitted by more traditional measures.

The Mathematics of Psychotherapy: A Nonlinear Model of Change Dynamics.

Science.gov (United States)

Schiepek, Gunter; Aas, Benjamin; Viol, Kathrin

2016-07-01

Psychotherapy is a dynamic process produced by a complex system of interacting variables. Even though there are qualitative models of such systems the link between structure and function, between network and network dynamics is still missing. The aim of this study is to realize these links. The proposed model is composed of five state variables (P: problem severity, S: success and therapeutic progress, M: motivation to change, E: emotions, I: insight and new perspectives) interconnected by 16 functions. The shape of each function is modified by four parameters (a: capability to form a trustful working alliance, c: mentalization and emotion regulation, r: behavioral resources and skills, m: self-efficacy and reward expectation). Psychologically, the parameters play the role of competencies or traits, which translate into the concept of control parameters in synergetics. The qualitative model was transferred into five coupled, deterministic, nonlinear difference equations generating the dynamics of each variable as a function of other variables. The mathematical model is able to reproduce important features of psychotherapy processes. Examples of parameter-dependent bifurcation diagrams are given. Beyond the illustrated similarities between simulated and empirical dynamics, the model has to be further developed, systematically tested by simulated experiments, and compared to empirical data.

The functional variable method for solving the fractional Korteweg ...

Indian Academy of Sciences (India)

The physical and engineering processes have been modelled by means of fractional ... very important role in various fields such as economics, chemistry, notably control the- .... In §3, the functional variable method is applied for finding exact.

Global variables and the dynamics or relativistic nucleus-nucleus collisions

International Nuclear Information System (INIS)

Cugnon, J.; L'Hote, D.

1983-01-01

Various global variables providing a simple description of high multiplicity events are reviewed. Many of them are calculated in the framework of an intra-nuclear cascade model, which describes the collision process as a series of binary on-shell relativistic baryon-baryon collisions and which includes inelasticity through the production of δ-resonances. The calculations are first made for the Ar+KCl system at 0.8 GeV/A, with global variables including either all the nucleons or only the participant nucleons. The shape and the orientation of the ellipsoid of sphericity are particularly investigated. For both cases, on the average, the large axis of the ellipsoid is found to point in the beam direction. This result is discussed in comparison with hydrodynamics predictions and in relation with the mean free path. A kind of small 'bounce-off effect' is detected for intermediate impact parameters. The possibility of extracting the value of the impact parameter b from the value of a global variable is shown to depend upon the variation of this variable with b and upon the fluctuation of the global variable for a given impact parameter. A quality factor is defined to quantify this possibility. No current global variable seems to be more appropriate than the number of participant nucleons for the impact parameter selection. The physical origin of the fluctuations inside the intranuclear cascade model is discussed and the possibility of extracting useful information on the dynamics of the system from the fluctuations is pointed out. The energy dependence of our results is discussed. Some results of the calculations at 250 and 400 MeV/A are also presented for the same system Ar+KCl. (orig.)

Dynamic functional connectivity and individual differences in emotions during social stress.

Science.gov (United States)

Tobia, Michael J; Hayashi, Koby; Ballard, Grey; Gotlib, Ian H; Waugh, Christian E

2017-12-01

Exposure to acute stress induces multiple emotional responses, each with their own unique temporal dynamics. Dynamic functional connectivity (dFC) measures the temporal variability of network synchrony and captures individual differences in network neurodynamics. This study investigated the relationship between dFC and individual differences in emotions induced by an acute psychosocial stressor. Sixteen healthy adult women underwent fMRI scanning during a social evaluative threat (SET) task, and retrospectively completed questionnaires that assessed individual differences in subjectively experienced positive and negative emotions about stress and stress relief during the task. Group dFC was decomposed with parallel factor analysis (PARAFAC) into 10 components, each with a temporal signature, spatial network of functionally connected regions, and vector of participant loadings that captures individual differences in dFC. Participant loadings of two networks were positively correlated with stress-related emotions, indicating the existence of networks for positive and negative emotions. The emotion-related networks involved the ventromedial prefrontal cortex, cingulate cortex, anterior insula, and amygdala, among other distributed brain regions, and time signatures for these emotion-related networks were uncorrelated. These findings demonstrate that individual differences in stress-induced positive and negative emotions are each uniquely associated with large-scale brain networks, and suggest that dFC is a mechanism that generates individual differences in the emotional components of the stress response. Hum Brain Mapp 38:6185-6205, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Study on dynamic behavior of fusion reactor materials and their response to variable and complex irradiation environment

International Nuclear Information System (INIS)

Abe, K.; Kohyama, A.; Namba, C.; Wiffen, F.W.; Jones, R.H.

2001-01-01

A Japan-USA Program of irradiation experiments for fusion research, 'JUPITER', has been established as a 6 year program from 1995 to 2000. The goal is to study the dynamic behavior of fusion reactor materials and their response to variable and complex irradiation environment using fission reactors. The irradiation experiments in this program include low activation structural materials, functional ceramics and other innovative materials. The experimental data are analyzed by theoretical modeling and computer simulation to integrate the above effects. The irradiation capsules for in-situ measurement and varying temperature were developed successfully. It was found that insulating ceramics were worked up to 3 dpa. The property changes and related issues in low activation structural materials were summarized. (author)

Evaluating gambles using dynamics

Science.gov (United States)

Peters, O.; Gell-Mann, M.

2016-02-01

Gambles are random variables that model possible changes in wealth. Classic decision theory transforms money into utility through a utility function and defines the value of a gamble as the expectation value of utility changes. Utility functions aim to capture individual psychological characteristics, but their generality limits predictive power. Expectation value maximizers are defined as rational in economics, but expectation values are only meaningful in the presence of ensembles or in systems with ergodic properties, whereas decision-makers have no access to ensembles, and the variables representing wealth in the usual growth models do not have the relevant ergodic properties. Simultaneously addressing the shortcomings of utility and those of expectations, we propose to evaluate gambles by averaging wealth growth over time. No utility function is needed, but a dynamic must be specified to compute time averages. Linear and logarithmic "utility functions" appear as transformations that generate ergodic observables for purely additive and purely multiplicative dynamics, respectively. We highlight inconsistencies throughout the development of decision theory, whose correction clarifies that our perspective is legitimate. These invalidate a commonly cited argument for bounded utility functions.

Enhanced interannual precipitation variability increases plant functional diversity that in turn ameliorates negative impact on productivity.

Science.gov (United States)

Gherardi, Laureano A; Sala, Osvaldo E

2015-12-01

Although precipitation interannual variability is projected to increase due to climate change, effects of changes in precipitation variance have received considerable less attention than effects of changes in the mean state of climate. Interannual precipitation variability effects on functional diversity and its consequences for ecosystem functioning are assessed here using a 6-year rainfall manipulation experiment. Five precipitation treatments were switched annually resulting in increased levels of precipitation variability while maintaining average precipitation constant. Functional diversity showed a positive response to increased variability due to increased evenness. Dominant grasses decreased and rare plant functional types increased in abundance because grasses showed a hump-shaped response to precipitation with a maximum around modal precipitation, whereas rare species peaked at high precipitation values. Increased functional diversity ameliorated negative effects of precipitation variability on primary production. Rare species buffered the effect of precipitation variability on the variability in total productivity because their variance decreases with increasing precipitation variance. © 2015 John Wiley & Sons Ltd/CNRS.

Radionuclide renal dynamic and function study

International Nuclear Information System (INIS)

Guan Liang

1991-01-01

The radionuclide dynamic and function study, glomerular filtration rate (GFR) and effective renal plasma flow (ERPF) were reported in 14 cases of renal and ureteral calculi patients before and after extracorporeal shock wave lithotripsy (ESWL). In 12 cases with normal renal blood flow, within 3 months after ESWL, the GFR of shock and non-shock side decreased with different extent, while the individual ERPF had little change. In 5 cases followed up 1 year after ESWL, the individual GFR and ERPF were normal. In 2 cases of severe renal function insufficiency, there was no improvement in renal function in shock side, after 5 months and 1 year, the renal function was still at low level. Thereby it is considered that ESWL is not suitable for the renal calculi patients with severe renal function insufficiency

LINTAB, Linear Interpolable Tables from any Continuous Variable Function

International Nuclear Information System (INIS)

1988-01-01

1 - Description of program or function: LINTAB is designed to construct linearly interpolable tables from any function. The program will start from any function of a single continuous variable... FUNKY(X). By user input the function can be defined, (1) Over 1 to 100 X ranges. (2) Within each X range the function is defined by 0 to 50 constants. (3) At boundaries between X ranges the function may be continuous or discontinuous (depending on the constants used to define the function within each X range). 2 - Method of solution: LINTAB will construct a table of X and Y values where the tabulated (X,Y) pairs will be exactly equal to the function (Y=FUNKY(X)) and linear interpolation between the tabulated pairs will be within any user specified fractional uncertainty of the function for all values of X within the requested X range

Fish functional traits correlated with environmental variables in a temperate biodiversity hotspot.

Directory of Open Access Journals (Sweden)

Benjamin P Keck

Full Text Available The global biodiversity crisis has invigorated the search for generalized patterns in most disciplines within the natural sciences. Studies based on organismal functional traits attempt to broaden implications of results by identifying the response of functional traits, instead of taxonomic units, to environmental variables. Determining the functional trait responses enables more direct comparisons with, or predictions for, communities of different taxonomic composition. The North American freshwater fish fauna is both diverse and increasingly imperiled through human mediated disturbances, including climate change. The Tennessee River, USA, contains one of the most diverse assemblages of freshwater fish in North America and has more imperiled species than other rivers, but there has been no trait-based study of community structure in the system. We identified 211 localities in the upper Tennessee River that were sampled by the Tennessee Valley Authority between 2009 and 2011 and compiled fish functional traits for the observed species and environmental variables for each locality. Using fourth corner analysis, we identified significant correlations between many fish functional traits and environmental variables. Functional traits associated with an opportunistic life history strategy were correlated with localities subject to greater land use disturbance and less flow regulation, while functional traits associated with a periodic life history strategy were correlated with localities subject to regular disturbance and regulated flow. These are patterns observed at the continental scale, highlighting the generalizability of trait-based methods. Contrary to studies that found no community structure differences when considering riparian buffer zones, we found that fish functional traits were correlated with different environmental variables between analyses with buffer zones vs. entire catchment area land cover proportions. Using existing databases

Fish functional traits correlated with environmental variables in a temperate biodiversity hotspot.

Science.gov (United States)

Keck, Benjamin P; Marion, Zachary H; Martin, Derek J; Kaufman, Jason C; Harden, Carol P; Schwartz, John S; Strange, Richard J

2014-01-01

The global biodiversity crisis has invigorated the search for generalized patterns in most disciplines within the natural sciences. Studies based on organismal functional traits attempt to broaden implications of results by identifying the response of functional traits, instead of taxonomic units, to environmental variables. Determining the functional trait responses enables more direct comparisons with, or predictions for, communities of different taxonomic composition. The North American freshwater fish fauna is both diverse and increasingly imperiled through human mediated disturbances, including climate change. The Tennessee River, USA, contains one of the most diverse assemblages of freshwater fish in North America and has more imperiled species than other rivers, but there has been no trait-based study of community structure in the system. We identified 211 localities in the upper Tennessee River that were sampled by the Tennessee Valley Authority between 2009 and 2011 and compiled fish functional traits for the observed species and environmental variables for each locality. Using fourth corner analysis, we identified significant correlations between many fish functional traits and environmental variables. Functional traits associated with an opportunistic life history strategy were correlated with localities subject to greater land use disturbance and less flow regulation, while functional traits associated with a periodic life history strategy were correlated with localities subject to regular disturbance and regulated flow. These are patterns observed at the continental scale, highlighting the generalizability of trait-based methods. Contrary to studies that found no community structure differences when considering riparian buffer zones, we found that fish functional traits were correlated with different environmental variables between analyses with buffer zones vs. entire catchment area land cover proportions. Using existing databases and fourth corner

Dynamic Analysis of Money Demand Function: Case of Turkey*

OpenAIRE

doğru, bülent

2013-01-01

In this paper, the dynamic determinants of money demand function and the long-run and short-run relationships between money demand, income and nominal interest rates are examined in Turkey for the time period 1980-2012. In particular we estimate a dynamic specification of a log money demand function based on Keynesian liquidity preference theory to ascertain the relevant elasticity of money demand. The empirical results of the study show that in Turkey inflation, exchange rate and money deman...

Linking Activity and Function to Ecosystem Dynamics in a Coastal Bacterioplankton Community

Directory of Open Access Journals (Sweden)

Scott Michael Gifford

2014-04-01

Full Text Available For bacterial communities containing hundreds to thousands of distinct populations, connecting functional processes and environmental dynamics at high taxonomic resolution has remained challenging. Here we use the expression of ribosomal proteins (%RP as a proxy for in situ activity of 200 taxa within 20 metatranscriptomic samples in a coastal ocean time series encompassing both seasonal variability and diel dynamics. %RP patterns grouped the taxa into seven activity clusters with distinct profiles in functional gene expression and correlations with environmental gradients. Clusters 1-3 had their highest potential activity in the winter and fall, and included some of the most active taxa, while Clusters 4-7 had their highest potential activity in the spring and summer. Cluster 1 taxa were characterized by gene expression for motility and complex carbohydrate degradation (dominated by Gammaproteobacteria and Bacteroidetes, and Cluster 2 taxa by transcription of genes for amino acid and aromatic compound metabolism and aerobic anoxygenic phototrophy (Roseobacter. Other activity clusters were enriched in transcripts for proteorhodopsin and methylotrophy (Cluster 4; SAR11 and methylotrophs, photosynthesis and attachment (Clusters 5 and 7; Synechococcus, picoeukaryotes, Verucomicrobia, and Planctomycetes, and sulfur oxidation (Cluster 7; Gammaproteobacteria. The seasonal patterns in activity were overlain, and sometimes obscured, by large differences in %RP over shorter day-night timescales. Seventy-eight taxa, many of them heterotrophs, had a higher %RP activity index during the day than night, indicating strong diel activity at this coastal site. Emerging from these taxonomically- and time-resolved estimates of in situ microbial activity are predictions of specific ecological groupings of microbial taxa in a dynamic coastal environment.

Dynamical and biogeochemical control on the decadal variability of ocean carbon fluxes

Directory of Open Access Journals (Sweden)

R. Séférian

2013-04-01

Full Text Available Several recent observation-based studies suggest that ocean anthropogenic carbon uptake has slowed down due to the impact of anthropogenic forced climate change. However, it remains unclear whether detected changes over the recent time period can be attributed to anthropogenic climate change or rather to natural climate variability (internal plus naturally forced variability alone. One large uncertainty arises from the lack of knowledge on ocean carbon flux natural variability at the decadal time scales. To gain more insights into decadal time scales, we have examined the internal variability of ocean carbon fluxes in a 1000 yr long preindustrial simulation performed with the Earth System Model IPSL-CM5A-LR. Our analysis shows that ocean carbon fluxes exhibit low-frequency oscillations that emerge from their year-to-year variability in the North Atlantic, the North Pacific, and the Southern Ocean. In our model, a 20 yr mode of variability in the North Atlantic air-sea carbon flux is driven by sea surface temperature variability and accounts for ~40% of the interannual regional variance. The North Pacific and the Southern Ocean carbon fluxes are also characterised by decadal to multi-decadal modes of variability (10 to 50 yr that account for 20–40% of the interannual regional variance. These modes are driven by the vertical supply of dissolved inorganic carbon through the variability of Ekman-induced upwelling and deep-mixing events. Differences in drivers of regional modes of variability stem from the coupling between ocean dynamics variability and the ocean carbon distribution, which is set by large-scale secular ocean circulation.

Design and dynamic simulation of a fixed pitch 56 kW wind turbine drive train with a continuously variable transmission

Science.gov (United States)

Gallo, C.; Kasuba, R.; Pintz, A.; Spring, J.

1986-01-01

The dynamic analysis of a horizontal axis fixed pitch wind turbine generator (WTG) rated at 56 kW is discussed. A mechanical Continuously Variable Transmission (CVT) was incorporated in the drive train to provide variable speed operation capability. One goal of the dynamic analysis was to determine if variable speed operation, by means of a mechanical CVT, is capable of capturing the transient power in the WTG/wind environment. Another goal was to determine the extent of power regulation possible with CVT operation.

Alterations of Resting-State Static and Dynamic Functional Connectivity of the Dorsolateral Prefrontal Cortex in Subjects with Internet Gaming Disorder

Directory of Open Access Journals (Sweden)

Xu Han

2018-02-01

Full Text Available Internet gaming disorder (IGD, a major behavior disorder, has gained increasing attention. Recent studies indicate altered resting-state static functional connectivity (FC of the dorsolateral prefrontal cortex (DLPFC in subjects with IGD. Whereas static FC often provides information on functional changes in subjects with IGD, investigations of temporal changes in FC between the DLPFC and the other brain regions may shed light on the dynamic characteristics of brain function associated with IGD. Thirty subjects with IGD and 30 healthy controls (HCs matched for age, gender and education status were recruited. Using the bilateral DLPFC as seeds, static FC and dynamic FC maps were calculated and compared between groups. Correlations between alterations in static FC and dynamic FC and clinical variables were also investigated within the IGD group. The IGD group showed significantly lower static FC between the right DLPFC and the left rolandic operculum while higher static FC between the right DLPFC and the left pars triangularis when compared to HCs. The IGD group also had significantly decreased dynamic FC between the right DLPFC and the left insula, right putamen and left precentral gyrus, and increased dynamic FC in the left precuneus. Moreover, the dynamic FC between the right DLPFC and the left insula was negatively correlated with the severity of IGD. Dynamic FC can be used as a powerful supplement to static FC, helping us obtain a more comprehensive understanding of large-scale brain network activity in IGD and put forward new ideas for behavioral intervention therapy for it.

Influence of climate variability, fire and phosphorus limitation on vegetation structure and dynamics of the Amazon-Cerrado border

Science.gov (United States)

Ane Dionizio, Emily; Heil Costa, Marcos; de Almeida Castanho, Andrea D.; Ferreira Pires, Gabrielle; Schwantes Marimon, Beatriz; Hur Marimon-Junior, Ben; Lenza, Eddie; Martins Pimenta, Fernando; Yang, Xiaojuan; Jain, Atul K.

2018-02-01

Climate, fire and soil nutrient limitation are important elements that affect vegetation dynamics in areas of the forest-savanna transition. In this paper, we use the dynamic vegetation model INLAND to evaluate the influence of interannual climate variability, fire and phosphorus (P) limitation on Amazon-Cerrado transitional vegetation structure and dynamics. We assess how each environmental factor affects net primary production, leaf area index and aboveground biomass (AGB), and compare the AGB simulations to an observed AGB map. We used two climate data sets (monthly average climate for 1961-1990 and interannual climate variability for 1948-2008), two data sets of total soil P content (one based on regional field measurements and one based on global data), and the INLAND fire module. Our results show that the inclusion of interannual climate variability, P limitation and fire occurrence each contribute to simulating vegetation types that more closely match observations. These effects are spatially heterogeneous and synergistic. In terms of magnitude, the effect of fire is strongest and is the main driver of vegetation changes along the transition. Phosphorus limitation, in turn, has a stronger effect on transitional ecosystem dynamics than interannual climate variability does. Overall, INLAND typically simulates more than 80 % of the AGB variability in the transition zone. However, the AGB in many places is clearly not well simulated, indicating that important soil and physiological factors in the Amazon-Cerrado border region, such as lithology, water table depth, carbon allocation strategies and mortality rates, still need to be included in the model.

Correlations between respiratory and functional variables in heart failure

Directory of Open Access Journals (Sweden)

Fábio Cangeri Di Naso

2009-09-01

Full Text Available Background: Respiratory alterations can impact on the functional performance of patients with heart failure. Aim: To correlate maximum inspiratory muscular force and lung function variables with functional capacity in heart failure patients. Methods: A transversal study January-July 2007 with 42 chronic heart disease patients (28 males with no prior pulmonary illness. The patients were in New York Heart Association Functional Class I, II and III. The variables used were maximum inspiratory pressure, forced vital capacity and forced expiratory volume in the first second. Respiratory variables measured were distance covered in the six-minute walk test, NYHA functional class and the physical functioning domain of the Short Form-36 Quality of Life Questionnaire. Results: Maximum inspiratory pressure correlated with the six-minute walk test (r = 0.543 and p < 0.001, functional capacity (r = −0.566 and p < 0.001 and the physical functioning domain score of the Short Form-36 (r = 0.459 and p = 0.002. The same was true of forced vital capacity and the six-minute walk test (r = 0.501 and p = 0.001, functional capacity (r = −0.477 and p = 0.001 and Short Form-36 (r = 0.314 and p = 0.043 variables. Forced expiratory volume correlated with the distance covered in the six-minute walk test (r = 0.514 and p < 0.001 and functional capacity (r = −0.383 and p = 0.012. Conclusion: Lung function and inspiratory muscular force respiratory variables correlated with functional variables in patients with heart failure. Resumo: Fundamento: Alterações respiratórias podem influenciar o desempenho funcional em doentes com insuficiência cardíaca (IC. Objectivo: Correlacionar a força muscular inspiratória máxima (PImax e as variáveis da função pulmonar com a capacidade funcional em doentes com IC. Métodos: Estudo transversal

OCOPTR, Minimization of Nonlinear Function, Variable Metric Method, Derivative Calculation. DRVOCR, Minimization of Nonlinear Function, Variable Metric Method, Derivative Calculation

International Nuclear Information System (INIS)

Nazareth, J. L.

1979-01-01

1 - Description of problem or function: OCOPTR and DRVOCR are computer programs designed to find minima of non-linear differentiable functions f: R n →R with n dimensional domains. OCOPTR requires that the user only provide function values (i.e. it is a derivative-free routine). DRVOCR requires the user to supply both function and gradient information. 2 - Method of solution: OCOPTR and DRVOCR use the variable metric (or quasi-Newton) method of Davidon (1975). For OCOPTR, the derivatives are estimated by finite differences along a suitable set of linearly independent directions. For DRVOCR, the derivatives are user- supplied. Some features of the codes are the storage of the approximation to the inverse Hessian matrix in lower trapezoidal factored form and the use of an optimally-conditioned updating method. Linear equality constraints are permitted subject to the initial Hessian factor being chosen correctly. 3 - Restrictions on the complexity of the problem: The functions to which the routine is applied are assumed to be differentiable. The routine also requires (n 2 /2) + 0(n) storage locations where n is the problem dimension

Cumulant approach to dynamical correlation functions at finite temperatures

International Nuclear Information System (INIS)

Tran Minhtien.

1993-11-01

A new theoretical approach, based on the introduction of cumulants, to calculate thermodynamic averages and dynamical correlation functions at finite temperatures is developed. The method is formulated in Liouville instead of Hilbert space and can be applied to operators which do not require to satisfy fermion or boson commutation relations. The application of the partitioning and projection methods for the dynamical correlation functions is discussed. The present method can be applied to weakly as well as to strongly correlated systems. (author). 9 refs

MUSCLE WEAKNESS, FATIGUE, AND TORQUE VARIABILITY: EFFECTS OF AGE AND MOBILITY STATUS

Science.gov (United States)

KENT-BRAUN, JANE A.; CALLAHAN, DAMIEN M.; FAY, JESSICA L.; FOULIS, STEPHEN A.; BUONACCORSI, JOHN P.

2013-01-01

Introduction Whereas deficits in muscle function, particularly power production, develop in old age and are risk factors for mobility impairment, a complete understanding of muscle fatigue during dynamic contractions is lacking. We tested hypotheses related to torque-producing capacity, fatigue resistance, and variability of torque production during repeated maximal contractions in healthy older, mobility-impaired older, and young women. Methods Knee extensor fatigue (decline in torque) was measured during 4 min of dynamic contractions. Torque variability was characterized using a novel 4-component logistic regression model. Results Young women produced more torque at baseline and during the protocol than older women (P torque variability differed by group (P = 0.022) and was greater in older impaired compared with young women (P = 0.010). Conclusions These results suggest that increased torque variability may combine with baseline muscle weakness to limit function, particularly in older adults with mobility impairments. PMID:23674266

Early days in complex dynamics a history of complex dynamics in one variable during 1906-1942

CERN Document Server

Alexander, Daniel S; Rosa, Alessandro

2011-01-01

The theory of complex dynamics, whose roots lie in 19th-century studies of the iteration of complex function conducted by Kœnigs, Schröder, and others, flourished remarkably during the first half of the 20th century, when many of the central ideas and techniques of the subject developed. This book by Alexander, Iavernaro, and Rosa paints a robust picture of the field of complex dynamics between 1906 and 1942 through detailed discussions of the work of Fatou, Julia, Siegel, and several others. A recurrent theme of the authors' treatment is the center problem in complex dynamics. They present its complete history during this period and, in so doing, bring out analogies between complex dynamics and the study of differential equations, in particular, the problem of stability in Hamiltonian systems. Among these analogies are the use of iteration and problems involving small divisors which the authors examine in the work of Poincaré and others, linking them to complex dynamics, principally via the work of Samuel...

Social Dynamics Management and Functional Behavioral Assessment

Science.gov (United States)

Lee, David L.

2018-01-01

Managing social dynamics is a critical aspect of creating a positive learning environment in classrooms. In this paper three key interrelated ideas, reinforcement, function, and motivating operations, are discussed with relation to managing social behavior.

Cardiac parasympathetic outflow during dynamic exercise in humans estimated from power spectral analysis of P-P interval variability.

Science.gov (United States)

Takahashi, Makoto; Nakamoto, Tomoko; Matsukawa, Kanji; Ishii, Kei; Watanabe, Tae; Sekikawa, Kiyokazu; Hamada, Hironobu

2016-03-01

What is the central question of this study? Should we use the high-frequency (HF) component of P-P interval as an index of cardiac parasympathetic nerve activity during moderate exercise? What is the main finding and its importance? The HF component of P-P interval variability remained even at a heart rate of 120-140 beats min(-1) and was further reduced by atropine, indicating incomplete cardiac vagal withdrawal during moderate exercise. The HF component of R-R interval is invalid as an estimate of cardiac parasympathetic outflow during moderate exercise; instead, the HF component of P-P interval variability should be used. The high-frequency (HF) component of R-R interval variability has been widely used as an indirect estimate of cardiac parasympathetic (vagal) outflow to the sino-atrial node of the heart. However, we have recently found that the variability of the R-R interval becomes much smaller during dynamic exercise than that of the P-P interval above a heart rate (HR) of ∼100 beats min(-1). We hypothesized that cardiac parasympathetic outflow during dynamic exercise with a higher intensity may be better estimated using the HF component of P-P interval variability. To test this hypothesis, the HF components of both P-P and R-R interval variability were analysed using a Wavelet transform during dynamic exercise. Twelve subjects performed ergometer exercise to increase HR from the baseline of 69 ± 3 beats min(-1) to three different levels of 100, 120 and 140 beats min(-1). We also examined the effect of atropine sulfate on the HF components in eight of the 12 subjects during exercise at an HR of 140 beats min(-1) . The HF component of P-P interval variability was significantly greater than that of R-R interval variability during exercise, especially at the HRs of 120 and 140 beats min(-1). The HF component of P-P interval variability was more reduced by atropine than that of R-R interval variability. We conclude that cardiac parasympathetic outflow to the

Theory of quantum dynamics in fermionic environment: an influence functional approach

International Nuclear Information System (INIS)

Chen, Y.

1987-01-01

Quantum dynamics of a particle coupled to a fermionic environment is considered, with particular emphasis on the formulation of macroscopic quantum phenomena. The framework is based on a path integral formalism for the real-time density matrix. After integrating out of the fermion variables of the environment, they embed the whole environmental effects on the particle into the so-called influence functional in analogy to Feynman and Vernon's initial work. They then show that to the second order of the coupling constant, the exponent of the influence functional is in exact agreement with that due to a linear dissipative environment (boson bath). Having obtained this, they turn to a specific model in which the influence functional can be exactly evaluated in a long-term limit (long compared to the inverse of the cutoff frequency of the environmental spectrum). In this circumstance, they mainly address their attention to the quantum mechanical representation of the system-plus-environment from the known classical properties of the particle. It is shown that, in particular, the equivalence between the fermion bath and the boson bath is generally correct for a single-channel coupling provided they make a simple mapping between the nonlinear interaction functions of the baths. Finally, generalizations of the model to more complicated situations are discussed and significant applications and connections to certain practically interesting problems are mentioned

General framework for fluctuating dynamic density functional theory

Science.gov (United States)

Durán-Olivencia, Miguel A.; Yatsyshin, Peter; Goddard, Benjamin D.; Kalliadasis, Serafim

2017-12-01

We introduce a versatile bottom-up derivation of a formal theoretical framework to describe (passive) soft-matter systems out of equilibrium subject to fluctuations. We provide a unique connection between the constituent-particle dynamics of real systems and the time evolution equation of their measurable (coarse-grained) quantities, such as local density and velocity. The starting point is the full Hamiltonian description of a system of colloidal particles immersed in a fluid of identical bath particles. Then, we average out the bath via Zwanzig’s projection-operator techniques and obtain the stochastic Langevin equations governing the colloidal-particle dynamics. Introducing the appropriate definition of the local number and momentum density fields yields a generalisation of the Dean-Kawasaki (DK) model, which resembles the stochastic Navier-Stokes description of a fluid. Nevertheless, the DK equation still contains all the microscopic information and, for that reason, does not represent the dynamical law of observable quantities. We address this controversial feature of the DK description by carrying out a nonequilibrium ensemble average. Adopting a natural decomposition into local-equilibrium and nonequilibrium contribution, where the former is related to a generalised version of the canonical distribution, we finally obtain the fluctuating-hydrodynamic equation governing the time-evolution of the mesoscopic density and momentum fields. Along the way, we outline the connection between the ad hoc energy functional introduced in previous DK derivations and the free-energy functional from classical density-functional theory. The resultant equation has the structure of a dynamical density-functional theory (DDFT) with an additional fluctuating force coming from the random interactions with the bath. We show that our fluctuating DDFT formalism corresponds to a particular version of the fluctuating Navier-Stokes equations, originally derived by Landau and Lifshitz

Combining molecular dynamics with mesoscopic Green’s function reaction dynamics simulations

Energy Technology Data Exchange (ETDEWEB)

Vijaykumar, Adithya, E-mail: vijaykumar@amolf.nl [FOM Institute AMOLF, Science Park 104, 1098 XG Amsterdam (Netherlands); van ’t Hoff Institute for Molecular Sciences, University of Amsterdam, P.O. Box 94157, 1090 GD Amsterdam (Netherlands); Bolhuis, Peter G. [van ’t Hoff Institute for Molecular Sciences, University of Amsterdam, P.O. Box 94157, 1090 GD Amsterdam (Netherlands); Rein ten Wolde, Pieter, E-mail: p.t.wolde@amolf.nl [FOM Institute AMOLF, Science Park 104, 1098 XG Amsterdam (Netherlands)

2015-12-07

In many reaction-diffusion processes, ranging from biochemical networks, catalysis, to complex self-assembly, the spatial distribution of the reactants and the stochastic character of their interactions are crucial for the macroscopic behavior. The recently developed mesoscopic Green’s Function Reaction Dynamics (GFRD) method enables efficient simulation at the particle level provided the microscopic dynamics can be integrated out. Yet, many processes exhibit non-trivial microscopic dynamics that can qualitatively change the macroscopic behavior, calling for an atomistic, microscopic description. We propose a novel approach that combines GFRD for simulating the system at the mesoscopic scale where particles are far apart, with a microscopic technique such as Langevin dynamics or Molecular Dynamics (MD), for simulating the system at the microscopic scale where reactants are in close proximity. This scheme defines the regions where the particles are close together and simulated with high microscopic resolution and those where they are far apart and simulated with lower mesoscopic resolution, adaptively on the fly. The new multi-scale scheme, called MD-GFRD, is generic and can be used to efficiently simulate reaction-diffusion systems at the particle level.

Combining molecular dynamics with mesoscopic Green’s function reaction dynamics simulations

International Nuclear Information System (INIS)

Vijaykumar, Adithya; Bolhuis, Peter G.; Rein ten Wolde, Pieter

2015-01-01

In many reaction-diffusion processes, ranging from biochemical networks, catalysis, to complex self-assembly, the spatial distribution of the reactants and the stochastic character of their interactions are crucial for the macroscopic behavior. The recently developed mesoscopic Green’s Function Reaction Dynamics (GFRD) method enables efficient simulation at the particle level provided the microscopic dynamics can be integrated out. Yet, many processes exhibit non-trivial microscopic dynamics that can qualitatively change the macroscopic behavior, calling for an atomistic, microscopic description. We propose a novel approach that combines GFRD for simulating the system at the mesoscopic scale where particles are far apart, with a microscopic technique such as Langevin dynamics or Molecular Dynamics (MD), for simulating the system at the microscopic scale where reactants are in close proximity. This scheme defines the regions where the particles are close together and simulated with high microscopic resolution and those where they are far apart and simulated with lower mesoscopic resolution, adaptively on the fly. The new multi-scale scheme, called MD-GFRD, is generic and can be used to efficiently simulate reaction-diffusion systems at the particle level

Beat to beat variability in cardiovascular variables: noise or music?

Science.gov (United States)

Appel, M. L.; Berger, R. D.; Saul, J. P.; Smith, J. M.; Cohen, R. J.

1989-01-01

Cardiovascular variables such as heart rate, arterial blood pressure, stroke volume and the shape of electrocardiographic complexes all fluctuate on a beat to beat basis. These fluctuations have traditionally been ignored or, at best, treated as noise to be averaged out. The variability in cardiovascular signals reflects the homeodynamic interplay between perturbations to cardiovascular function and the dynamic response of the cardiovascular regulatory systems. Modern signal processing techniques provide a means of analyzing beat to beat fluctuations in cardiovascular signals, so as to permit a quantitative, noninvasive or minimally invasive method of assessing closed loop hemodynamic regulation and cardiac electrical stability. This method promises to provide a new approach to the clinical diagnosis and management of alterations in cardiovascular regulation and stability.

Dynamics in species composition of stream fish assemblages: environmental variability and nested subsets

Science.gov (United States)

Christopher M. Taylor; Melvin L. Warren

2001-01-01

Stream landscapes are highly variable in space and time and, like terrestrial landscapes, the resources they contain are patchily distributed. Organisms may disperse among patches to fulfill life-history requirements, but biotic and abiotic factors may limit patch or locality occupancy. Thus, the dynamics of immigration and extinction determine, in part, the local...

Predictive assessment of models for dynamic functional connectivity

DEFF Research Database (Denmark)

Nielsen, Søren Føns Vind; Schmidt, Mikkel Nørgaard; Madsen, Kristoffer Hougaard

2018-01-01

represent functional brain networks as a meta-stable process with a discrete number of states; however, there is a lack of consensus on how to perform model selection and learn the number of states, as well as a lack of understanding of how different modeling assumptions influence the estimated state......In neuroimaging, it has become evident that models of dynamic functional connectivity (dFC), which characterize how intrinsic brain organization changes over time, can provide a more detailed representation of brain function than traditional static analyses. Many dFC models in the literature...... dynamics. To address these issues, we consider a predictive likelihood approach to model assessment, where models are evaluated based on their predictive performance on held-out test data. Examining several prominent models of dFC (in their probabilistic formulations) we demonstrate our framework...

Generating relations of multi-variable Tricomi functions of two indices using Lie algebra representation

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Nader Ali Makboul Hassan

2014-01-01

Full Text Available This paper is an attempt to stress the usefulness of the multi-variable special functions. In this paper, we derive certain generating relations involving 2-indices 5-variables 5-parameters Tricomi functions (2I5V5PTF by using a Lie-algebraic method. Further, we derive certain new and known generating relations involving other forms of Tricomi and Bessel functions as applications.

Quantitative evaluation of the reticuloendothelial system function with dynamic MRI.

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Ting Liu

Full Text Available To evaluate the reticuloendothelial system (RES function by real-time imaging blood clearance as well as hepatic uptake of superparamagnetic iron oxide nanoparticle (SPIO using dynamic magnetic resonance imaging (MRI with two-compartment pharmacokinetic modeling.Kinetics of blood clearance and hepatic accumulation were recorded in young adult male 01b74 athymic nude mice by dynamic T2* weighted MRI after the injection of different doses of SPIO nanoparticles (0.5, 3 or 10 mg Fe/kg. Association parameter, Kin, dissociation parameter, Kout, and elimination constant, Ke, derived from dynamic data with two-compartment model, were used to describe active binding to Kupffer cells and extrahepatic clearance. The clodrosome and liposome were utilized to deplete macrophages and block the RES function to evaluate the capability of the kinetic parameters for investigation of macrophage function and density.The two-compartment model provided a good description for all data and showed a low sum squared residual for all mice (0.27±0.03. A lower Kin, a lower Kout and a lower Ke were found after clodrosome treatment, whereas a lower Kin, a higher Kout and a lower Ke were observed after liposome treatment in comparison to saline treatment (P<0.005.Dynamic SPIO-enhanced MR imaging with two-compartment modeling can provide information on RES function on both a cell number and receptor function level.

Dynamical signatures of isometric force control as a function of age, expertise, and task constraints.

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Vieluf, Solveig; Sleimen-Malkoun, Rita; Voelcker-Rehage, Claudia; Jirsa, Viktor; Reuter, Eva-Maria; Godde, Ben; Temprado, Jean-Jacques; Huys, Raoul

2017-07-01

From the conceptual and methodological framework of the dynamical systems approach, force control results from complex interactions of various subsystems yielding observable behavioral fluctuations, which comprise both deterministic (predictable) and stochastic (noise-like) dynamical components. Here, we investigated these components contributing to the observed variability in force control in groups of participants differing in age and expertise level. To this aim, young (18-25 yr) as well as late middle-aged (55-65 yr) novices and experts (precision mechanics) performed a force maintenance and a force modulation task. Results showed that whereas the amplitude of force variability did not differ across groups in the maintenance tasks, in the modulation task it was higher for late middle-aged novices than for experts and higher for both these groups than for young participants. Within both tasks and for all groups, stochastic fluctuations were lowest where the deterministic influence was smallest. However, although all groups showed similar dynamics underlying force control in the maintenance task, a group effect was found for deterministic and stochastic fluctuations in the modulation task. The latter findings imply that both components were involved in the observed group differences in the variability of force fluctuations in the modulation task. These findings suggest that between groups the general characteristics of the dynamics do not differ in either task and that force control is more affected by age than by expertise. However, expertise seems to counteract some of the age effects. NEW & NOTEWORTHY Stochastic and deterministic dynamical components contribute to force production. Dynamical signatures differ between force maintenance and cyclic force modulation tasks but hardly between age and expertise groups. Differences in both stochastic and deterministic components are associated with group differences in behavioral variability, and observed behavioral

Variable threshold algorithm for division of labor analyzed as a dynamical system.

Science.gov (United States)

Castillo-Cagigal, Manuel; Matallanas, Eduardo; Navarro, Iñaki; Caamaño-Martín, Estefanía; Monasterio-Huelin, Félix; Gutiérrez, Álvaro

2014-12-01

Division of labor is a widely studied aspect of colony behavior of social insects. Division of labor models indicate how individuals distribute themselves in order to perform different tasks simultaneously. However, models that study division of labor from a dynamical system point of view cannot be found in the literature. In this paper, we define a division of labor model as a discrete-time dynamical system, in order to study the equilibrium points and their properties related to convergence and stability. By making use of this analytical model, an adaptive algorithm based on division of labor can be designed to satisfy dynamic criteria. In this way, we have designed and tested an algorithm that varies the response thresholds in order to modify the dynamic behavior of the system. This behavior modification allows the system to adapt to specific environmental and collective situations, making the algorithm a good candidate for distributed control applications. The variable threshold algorithm is based on specialization mechanisms. It is able to achieve an asymptotically stable behavior of the system in different environments and independently of the number of individuals. The algorithm has been successfully tested under several initial conditions and number of individuals.

Stochastic methods for uncertainty treatment of functional variables in computer codes: application to safety studies

International Nuclear Information System (INIS)

Nanty, Simon

2015-01-01

This work relates to the framework of uncertainty quantification for numerical simulators, and more precisely studies two industrial applications linked to the safety studies of nuclear plants. These two applications have several common features. The first one is that the computer code inputs are functional and scalar variables, functional ones being dependent. The second feature is that the probability distribution of functional variables is known only through a sample of their realizations. The third feature, relative to only one of the two applications, is the high computational cost of the code, which limits the number of possible simulations. The main objective of this work was to propose a complete methodology for the uncertainty analysis of numerical simulators for the two considered cases. First, we have proposed a methodology to quantify the uncertainties of dependent functional random variables from a sample of their realizations. This methodology enables to both model the dependency between variables and their link to another variable, called co-variate, which could be, for instance, the output of the considered code. Then, we have developed an adaptation of a visualization tool for functional data, which enables to simultaneously visualize the uncertainties and features of dependent functional variables. Second, a method to perform the global sensitivity analysis of the codes used in the two studied cases has been proposed. In the case of a computationally demanding code, the direct use of quantitative global sensitivity analysis methods is intractable. To overcome this issue, the retained solution consists in building a surrogate model or meta model, a fast-running model approximating the computationally expensive code. An optimized uniform sampling strategy for scalar and functional variables has been developed to build a learning basis for the meta model. Finally, a new approximation approach for expensive codes with functional outputs has been

Abstraction of continuous dynamical systems utilizing lyapunov functions

DEFF Research Database (Denmark)

Sloth, Christoffer; Wisniewski, Rafael

2010-01-01

This paper considers the development of a method for abstracting continuous dynamical systems by timed automata. The method is based on partitioning the state space of dynamical systems with invariant sets, which form cells representing locations of the timed automata. To enable verification...... of the dynamical system based on the abstraction, conditions for obtaining sound, complete, and refinable abstractions are set up. It is proposed to partition the state space utilizing sub-level sets of Lyapunov functions, since they are positive invariant sets. The existence of sound abstractions for Morse......-Smale systems and complete and refinable abstractions for linear systems are shown....

LETTER TO THE EDITOR: Fractal diffusion coefficient from dynamical zeta functions

Science.gov (United States)

Cristadoro, Giampaolo

2006-03-01

Dynamical zeta functions provide a powerful method to analyse low-dimensional dynamical systems when the underlying symbolic dynamics is under control. On the other hand, even simple one-dimensional maps can show an intricate structure of the grammar rules that may lead to a non-smooth dependence of global observables on parameters changes. A paradigmatic example is the fractal diffusion coefficient arising in a simple piecewise linear one-dimensional map of the real line. Using the Baladi-Ruelle generalization of the Milnor-Thurnston kneading determinant, we provide the exact dynamical zeta function for such a map and compute the diffusion coefficient from its smallest zero.

Exponential and Logarithmic Functions

OpenAIRE

Todorova, Tamara

2010-01-01

Exponential functions find applications in economics in relation to growth and economic dynamics. In these fields, quite often the choice variable is time and economists are trying to determine the best timing for certain economic activities to take place. An exponential function is one in which the independent variable appears in the exponent. Very often that exponent is time. In highly mathematical courses, it is a truism that students learn by doing, not by reading. Tamara Todorova’s Pr...

Approaches for modeling within subject variability in pharmacometric count data analysis: dynamic inter-occasion variability and stochastic differential equations.

Science.gov (United States)

Deng, Chenhui; Plan, Elodie L; Karlsson, Mats O

2016-06-01

Parameter variation in pharmacometric analysis studies can be characterized as within subject parameter variability (WSV) in pharmacometric models. WSV has previously been successfully modeled using inter-occasion variability (IOV), but also stochastic differential equations (SDEs). In this study, two approaches, dynamic inter-occasion variability (dIOV) and adapted stochastic differential equations, were proposed to investigate WSV in pharmacometric count data analysis. These approaches were applied to published count models for seizure counts and Likert pain scores. Both approaches improved the model fits significantly. In addition, stochastic simulation and estimation were used to explore further the capability of the two approaches to diagnose and improve models where existing WSV is not recognized. The results of simulations confirmed the gain in introducing WSV as dIOV and SDEs when parameters vary randomly over time. Further, the approaches were also informative as diagnostics of model misspecification, when parameters changed systematically over time but this was not recognized in the structural model. The proposed approaches in this study offer strategies to characterize WSV and are not restricted to count data.

Application of dynamic model to predict some inside environment variables in a semi-solar greenhouse

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Behzad Mohammadi

2018-06-01

Full Text Available Greenhouses are one of the most effective cultivation methods with a yield per cultivated area up to 10 times more than free land cultivation but the use of fossil fuels in this production field is very high. The greenhouse environment is an uncertain nonlinear system which classical modeling methods have some problems to solve it. There are many control methods, such as adaptive, feedback and intelligent control and they require a precise model. Therefore, many modeling methods have been proposed for this purpose; including physical, transfer function and black-box modeling. The objective of this paper is to modeling and experimental validation of some inside environment variables in an innovative greenhouse structure (semi-solar greenhouse. For this propose, a semi-solar greenhouse was designed and constructed at the North-West of Iran in Azerbaijan Province (38°10′N and 46°18′E with elevation of 1364 m above the sea level. The main inside environment factors include inside air temperature (Ta and inside soil temperature (Ts were collected as the experimental data samples. The dynamic heat transfer model used to estimate the temperature in two different points of semi-solar greenhouse with initial values. The results showed that dynamic model can predict the inside temperatures in two different points (Ta and Ts with RMSE, MAPE and EF about 5.3 °C, 10.2% and 0.78% and 3.45 °C, 7.7% and 0.86%, respectively. Keywords: Semi-solar greenhouse, Dynamic model, Commercial greenhouse

Local dynamic stability and variability of gait are associated with fall history in elderly subjects

OpenAIRE

Toebes, M.J.P.; Hoozemans, M.J.M.; Furrer, R.; Dekker, J.; van Dieen, J.H.

2012-01-01

Gait parameters that can be measured with simple instrumentation may hold promise for identifying individuals at risk of falling. Increased variability of gait is associated with increased risk of falling, but research on additional parameters indicates that local dynamic stability (LDS) of gait may also be a predictor of fall risk. The objective of the present study was to assess the association between gait variability, LDS of gait and fall history in a large sample of elderly subjects.Subj...

Orthogonal functions, discrete variable representation, and generalized gauss quadratures

DEFF Research Database (Denmark)

Schneider, B. I.; Nygaard, Nicolai

2002-01-01

in the original representation. This has been exploited in bound-state, scattering, and time-dependent problems using the so-called, discrete variable representation (DVR). At the core of this approach is the mathematical three-term recursion relationship satisfied by the classical orthogonal functions...... functions, this is not the case. However, they may be computed in a stable numerical fashion, via the recursion. In essence, this is an application of the well-known Lanczos recursion approach. Once the recursion coefficients are known, it is possible to compute the points and weights of quadratures on...

Glucose variability negatively impacts long-term functional outcome in patients with traumatic brain injury.

Science.gov (United States)

Matsushima, Kazuhide; Peng, Monica; Velasco, Carlos; Schaefer, Eric; Diaz-Arrastia, Ramon; Frankel, Heidi

2012-04-01

Significant glycemic excursions (so-called glucose variability) affect the outcome of generic critically ill patients but has not been well studied in patients with traumatic brain injury (TBI). The purpose of this study was to evaluate the impact of glucose variability on long-term functional outcome of patients with TBI. A noncomputerized tight glucose control protocol was used in our intensivist model surgical intensive care unit. The relationship between the glucose variability and long-term (a median of 6 months after injury) functional outcome defined by extended Glasgow Outcome Scale (GOSE) was analyzed using ordinal logistic regression models. Glucose variability was defined by SD and percentage of excursion (POE) from the preset range glucose level. A total of 109 patients with TBI under tight glucose control had long-term GOSE evaluated. In univariable analysis, there was a significant association between lower GOSE score and higher mean glucose, higher SD, POE more than 60, POE 80 to 150, and single episode of glucose less than 60 mg/dL but not POE 80 to 110. After adjusting for possible confounding variables in multivariable ordinal logistic regression models, higher SD, POE more than 60, POE 80 to 150, and single episode of glucose less than 60 mg/dL were significantly associated with lower GOSE score. Glucose variability was significantly associated with poorer long-term functional outcome in patients with TBI as measured by the GOSE score. Well-designed protocols to minimize glucose variability may be key in improving long-term functional outcome. Copyright © 2012 Elsevier Inc. All rights reserved.

Temporal variability in phosphorus transfers: classifying concentration-discharge event dynamics

Science.gov (United States)

Haygarth, P.; Turner, B. L.; Fraser, A.; Jarvis, S.; Harrod, T.; Nash, D.; Halliwell, D.; Page, T.; Beven, K.

The importance of temporal variability in relationships between phosphorus (P) concentration (Cp) and discharge (Q) is linked to a simple means of classifying the circumstances of Cp-Q relationships in terms of functional types of response. New experimental data at the upstream interface of grassland soil and catchment systems at a range of scales (lysimeters to headwaters) in England and Australia are used to demonstrate the potential of such an approach. Three types of event are defined as Types 1-3, depending on whether the relative change in Q exceeds the relative change in Cp (Type 1), whether Cp and Q are positively inter-related (Type 2) and whether Cp varies yet Q is unchanged (Type 3). The classification helps to characterise circumstances that can be explained mechanistically in relation to (i) the scale of the study (with a tendency towards Type 1 in small scale lysimeters), (ii) the form of P with a tendency for Type 1 for soluble (i.e., <0.45 μm P forms) and (iii) the sources of P with Type 3 dominant where P availability overrides transport controls. This simple framework provides a basis for development of a more complex and quantitative classification of Cp-Q relationships that can be developed further to contribute to future models of P transfer and delivery from slope to stream. Studies that evaluate the temporal dynamics of the transfer of P are currently grossly under-represented in comparison with models based on static/spatial factors.

Multiscale simulations of anisotropic particles combining molecular dynamics and Green's function reaction dynamics

Science.gov (United States)

Vijaykumar, Adithya; Ouldridge, Thomas E.; ten Wolde, Pieter Rein; Bolhuis, Peter G.

2017-03-01

The modeling of complex reaction-diffusion processes in, for instance, cellular biochemical networks or self-assembling soft matter can be tremendously sped up by employing a multiscale algorithm which combines the mesoscopic Green's Function Reaction Dynamics (GFRD) method with explicit stochastic Brownian, Langevin, or deterministic molecular dynamics to treat reactants at the microscopic scale [A. Vijaykumar, P. G. Bolhuis, and P. R. ten Wolde, J. Chem. Phys. 143, 214102 (2015)]. Here we extend this multiscale MD-GFRD approach to include the orientational dynamics that is crucial to describe the anisotropic interactions often prevalent in biomolecular systems. We present the novel algorithm focusing on Brownian dynamics only, although the methodology is generic. We illustrate the novel algorithm using a simple patchy particle model. After validation of the algorithm, we discuss its performance. The rotational Brownian dynamics MD-GFRD multiscale method will open up the possibility for large scale simulations of protein signalling networks.

HYPERDIRE. HYPERgeometric functions DIfferential REduction. MATEMATICA based packages for differential reduction of generalized hypergeometric functions. F{sub D} and F{sub S} Horn-type hypergeometric functions of three variables

Energy Technology Data Exchange (ETDEWEB)

Bytev, Vladimir V. [Joint Inst. for Nuclear Research, Dubna (Russian Federation); Kalmykov, Mikhail Yu. [Deutsches Elektronen-Synchrotron (DESY), Zeuthen (Germany); Moch, Sven-Olaf [Deutsches Elektronen-Synchrotron (DESY), Zeuthen (Germany); Hamburg Univ. (Germany). 2. Inst. fuer Theoretische Physik

2013-12-15

HYPERDIRE is a project devoted to the creation of a set of Mathematica based programs for the differential reduction of hypergeometric functions. The current version includes two parts: the first one, FdFunction, for manipulations with Appell hypergeometric functions F{sub D} of r variables; and the second one, FsFunction, for manipulations with Lauricella-Saran hypergeometric functions F{sub S} of three variables. Both functions are related with one-loop Feynman diagrams.

Joint Chance-Constrained Dynamic Programming

Science.gov (United States)

Ono, Masahiro; Kuwata, Yoshiaki; Balaram, J. Bob

2012-01-01

This paper presents a novel dynamic programming algorithm with a joint chance constraint, which explicitly bounds the risk of failure in order to maintain the state within a specified feasible region. A joint chance constraint cannot be handled by existing constrained dynamic programming approaches since their application is limited to constraints in the same form as the cost function, that is, an expectation over a sum of one-stage costs. We overcome this challenge by reformulating the joint chance constraint into a constraint on an expectation over a sum of indicator functions, which can be incorporated into the cost function by dualizing the optimization problem. As a result, the primal variables can be optimized by a standard dynamic programming, while the dual variable is optimized by a root-finding algorithm that converges exponentially. Error bounds on the primal and dual objective values are rigorously derived. We demonstrate the algorithm on a path planning problem, as well as an optimal control problem for Mars entry, descent and landing. The simulations are conducted using a real terrain data of Mars, with four million discrete states at each time step.

Variability in dynamic properties of tantalum : spall, attenuation and load/unload.

Energy Technology Data Exchange (ETDEWEB)

Furnish, Michael David; Reinhart, William Dodd; Trott, Wayne Merle; Vogler, Tracy John; Chhabildas, Lalit Chandra

2005-07-01

A suite of impact experiments was conducted to assess spatial and shot-to-shot variability in dynamic properties of tantalum. Samples had a uniform refined {approx}20 micron grain structure with a strong axisymmetric [111] crystallographic texture. Two experiments performed with sapphire windows (stresses of approximately 7 and 12 GPa) clearly showed elastic-plastic loading and slightly hysteretic unloading behavior. An HEL amplitude of 2.8 GPa (corresponding to Y 1.5 GPa) was observed. Free-surface spall experiments showed clear wave attenuation and spallation phenomena. Here, loading stresses were {approx} 12.5 GPa and various ratios of impactor to target thicknesses were used. Spatial and shot-to-shot variability of the spall strength was {+-} 20%, and of the HEL, {+-} 10%. Experiments conducted with smaller diameter flyer plates clearly showed edge effects in the line and point VISAR records, indicating lateral release speeds of roughly 5 km/s.

State Anxiety and Nonlinear Dynamics of Heart Rate Variability in Students.

Science.gov (United States)

Dimitriev, Dimitriy A; Saperova, Elena V; Dimitriev, Aleksey D

2016-01-01

Clinical and experimental research studies have demonstrated that the emotional experience of anxiety impairs heart rate variability (HRV) in humans. The present study investigated whether changes in state anxiety (SA) can also modulate nonlinear dynamics of heart rate. A group of 96 students volunteered to participate in the study. For each student, two 5-minute recordings of beat intervals (RR) were performed: one during a rest period and one just before a university examination, which was assumed to be a real-life stressor. Nonlinear analysis of HRV was performed. The Spielberger's State-Trait Anxiety Inventory was used to assess the level of SA. Before adjusting for heart rate, a Wilcoxon matched pairs test showed significant decreases in Poincaré plot measures, entropy, largest Lyapunov exponent (LLE), and pointwise correlation dimension (PD2), and an increase in the short-term fractal-like scaling exponent of detrended fluctuation analysis (α1) during the exam session, compared with the rest period. A Pearson analysis indicated significant negative correlations between the dynamics of SA and Poincaré plot axes ratio (SD1/SD2), and between changes in SA and changes in entropy measures. A strong negative correlation was found between the dynamics of SA and LLE. A significant positive correlation was found between the dynamics of SA and α1. The decreases in Poincaré plot measures (SD1, complex correlation measure), entropy measures, and LLE were still significant after adjusting for heart rate. Corrected α1 was increased during the exam session. As before, the dynamics of adjusted LLE was significantly correlated with the dynamics of SA. The qualitative increase in SA during academic examination was related to the decrease in the complexity and size of the Poincaré plot through a reduction of both the interbeat interval and its variation.

State Anxiety and Nonlinear Dynamics of Heart Rate Variability in Students.

Directory of Open Access Journals (Sweden)

Dimitriy A Dimitriev

Full Text Available Clinical and experimental research studies have demonstrated that the emotional experience of anxiety impairs heart rate variability (HRV in humans. The present study investigated whether changes in state anxiety (SA can also modulate nonlinear dynamics of heart rate.A group of 96 students volunteered to participate in the study. For each student, two 5-minute recordings of beat intervals (RR were performed: one during a rest period and one just before a university examination, which was assumed to be a real-life stressor. Nonlinear analysis of HRV was performed. The Spielberger's State-Trait Anxiety Inventory was used to assess the level of SA.Before adjusting for heart rate, a Wilcoxon matched pairs test showed significant decreases in Poincaré plot measures, entropy, largest Lyapunov exponent (LLE, and pointwise correlation dimension (PD2, and an increase in the short-term fractal-like scaling exponent of detrended fluctuation analysis (α1 during the exam session, compared with the rest period. A Pearson analysis indicated significant negative correlations between the dynamics of SA and Poincaré plot axes ratio (SD1/SD2, and between changes in SA and changes in entropy measures. A strong negative correlation was found between the dynamics of SA and LLE. A significant positive correlation was found between the dynamics of SA and α1. The decreases in Poincaré plot measures (SD1, complex correlation measure, entropy measures, and LLE were still significant after adjusting for heart rate. Corrected α1 was increased during the exam session. As before, the dynamics of adjusted LLE was significantly correlated with the dynamics of SA.The qualitative increase in SA during academic examination was related to the decrease in the complexity and size of the Poincaré plot through a reduction of both the interbeat interval and its variation.

Totally Optimal Decision Trees for Monotone Boolean Functions with at Most Five Variables

KAUST Repository

Chikalov, Igor

2013-01-01

In this paper, we present the empirical results for relationships between time (depth) and space (number of nodes) complexity of decision trees computing monotone Boolean functions, with at most five variables. We use Dagger (a tool for optimization of decision trees and decision rules) to conduct experiments. We show that, for each monotone Boolean function with at most five variables, there exists a totally optimal decision tree which is optimal with respect to both depth and number of nodes.

Uncertain population dynamic and state variables of alfonsino (Beryx splendens Dinámica poblacional incierta y variables de estado en alfonsino (Beryx splendens

Directory of Open Access Journals (Sweden)

Rodrigo Wiff

2012-03-01

Full Text Available Alfonsino (Beryx splendens is a species associated with seamounts, with an important fishery in Juan Fernandez archipelago, Chile (33°40'S, 79°00'W. Since 2004, this resource has been managed by catch quotas estimated from stock assessment models. The alfonsino model involves high levels of uncertainty for several reasons including a lack of knowledge of aspects of the population dynamics and poorly informative time-series that feed the proposed evaluation models. This work evaluated three hypotheses regarding population dynamics and their influence on the main state variables (biomass, recruitment of the model using age-structured and dynamic biomass models. The hypotheses corresponded to de-recruitment of older individuals, non-linearity between standardized catch per unit effort, and population abundance as well as variations of the relative importance of length structures. According to the results, the depletion of the spawning biomass between 1998 and 2008 varied between 9 and 56%, depending on the combination of hypotheses used in the model. This indicates that state variables in alfonsino are not robust to the available information; rather, they depend strongly on the hypothesis of population dynamics. The discussion is focused on interpreting the causes of the changes in the state variables in light of a conceptual model for population dynamics in alfonsino and which pieces of information would be necessary to reduce the associated uncertainty.El alfonsino (Beryx splendens es una especie asociada a montes submarinos. En Chile sustenta una importante pesquería en el archipiélago de Juan Fernández (33°40'S, 79°00'W. Desde el año 2004, este recurso es administrado a través de cuotas anuales de capturas, las cuales son estimadas desde un modelo de evaluación de stock. La modelación de la población de alfonsino se caracteriza por una alta incertidumbre, debido a diversas fuentes, como son desconocimiento de aspectos de su din

Explicit symplectic algorithms based on generating functions for charged particle dynamics

Science.gov (United States)

Zhang, Ruili; Qin, Hong; Tang, Yifa; Liu, Jian; He, Yang; Xiao, Jianyuan

2016-07-01

Dynamics of a charged particle in the canonical coordinates is a Hamiltonian system, and the well-known symplectic algorithm has been regarded as the de facto method for numerical integration of Hamiltonian systems due to its long-term accuracy and fidelity. For long-term simulations with high efficiency, explicit symplectic algorithms are desirable. However, it is generally believed that explicit symplectic algorithms are only available for sum-separable Hamiltonians, and this restriction limits the application of explicit symplectic algorithms to charged particle dynamics. To overcome this difficulty, we combine the familiar sum-split method and a generating function method to construct second- and third-order explicit symplectic algorithms for dynamics of charged particle. The generating function method is designed to generate explicit symplectic algorithms for product-separable Hamiltonian with form of H (x ,p ) =pif (x ) or H (x ,p ) =xig (p ) . Applied to the simulations of charged particle dynamics, the explicit symplectic algorithms based on generating functions demonstrate superiorities in conservation and efficiency.

Effects of functional training on geometric indices of heart rate variability

Directory of Open Access Journals (Sweden)

Marianne P.C. de Rezende Barbosa

2016-06-01

Conclusion: Functional training had a beneficial impact on autonomic modulation, as characterized by increased parasympathetic activity and overall variability, thus highlighting the clinical usefulness of this type of training.

Hybrid Predictive Control for Dynamic Transport Problems

CERN Document Server

Núñez, Alfredo A; Cortés, Cristián E

2013-01-01

Hybrid Predictive Control for Dynamic Transport Problems develops methods for the design of predictive control strategies for nonlinear-dynamic hybrid discrete-/continuous-variable systems. The methodology is designed for real-time applications, particularly the study of dynamic transport systems. Operational and service policies are considered, as well as cost reduction. The control structure is based on a sound definition of the key variables and their evolution. A flexible objective function able to capture the predictive behaviour of the system variables is described. Coupled with efficient algorithms, mainly drawn from the area of computational intelligence, this is shown to optimize performance indices for real-time applications. The framework of the proposed predictive control methodology is generic and, being able to solve nonlinear mixed-integer optimization problems dynamically, is readily extendable to other industrial processes. The main topics of this book are: ●hybrid predictive control (HPC) ...

[Various methods of dynamic functional analysis in human sciences and economics].

Science.gov (United States)

Schiltz, J

2006-01-01

Including the temporal and developmental dimension into the measurement of human conduct is a fundamental concern for those who do research in natural surroundings. Observing an individual day after day may possibly give a more complete vision of how behavior works than measuring a group of individuals at a single time and analyzing the differences found among them. Unfortunately most of the tools allowing analyzing individual time series call for large numbers of repeated observations. Thus, practicable longitudinal research designs often do not involve either enough repeated measurements for traditional time series analyses nor either replicate enough individuals for traditional, large-sample analyses. Dynamic factor analysis is a rationale and procedure for both pooling relatively short time series information across limited numbers of participants and analyzing the pooled information for its dynamic, process-relevant elements. It is a merging of two important analytical tools - multivariate time series and the common factor model, from which it distinguishes itself mainly by the fact that in dynamic factor analysis, the values of the common factors can influence the values of the observed variables both concurrently and in delayed fashion. Dynamic factor analysis is actually a method which allows detecting structures in the time series as well as the relations between the series and the explanatory variables. We illustrate the different models used in psychology and social sciences, as well as in econometry and economics.

Piecewise linearisation of the first order loss function for families of arbitrarily distributed random variables

NARCIS (Netherlands)

Rossi, R.; Hendrix, E.M.T.

2014-01-01

We discuss the problem of computing optimal linearisation parameters for the first order loss function of a family of arbitrarily distributed random variable. We demonstrate that, in contrast to the problem in which parameters must be determined for the loss function of a single random variable,

Application of generalized function to dynamic analysis of elasto-plastic thick plates

International Nuclear Information System (INIS)

Zheng, D.; Weng, Z.

1987-01-01

The elasto-plastic dynamic analysis of thick plates is of great significance to the research and the design on an anti-seismic structure and an anti-explosive structure. In this paper, the derivative of δ-function is handled by using the generalized function. The dynamic influence coefficient of thick plates in deduced. A dynamic response of elasto-plastic thick plates its material has hardening behaviour considered, is analysed by using known elastic solutions. The general expressions for the dynamic response of elasto-plastic rectangular thick plates subjected arbitrary loads are given. Detailed computations are performed for the square plates of various height-span ratios. The results are compared with those obtained from the improved theory and the classical theory of plates. The modification of the classical deflection theory for plates is employed. The increment analysis is used for calculations. The yield function is considered as a function of inplane and transverse shear stresses. (orig./GL)

Analytic function theory of several variables elements of Oka’s coherence

CERN Document Server

Noguchi, Junjiro

2016-01-01

The purpose of this book is to present the classical analytic function theory of several variables as a standard subject in a course of mathematics after learning the elementary materials (sets, general topology, algebra, one complex variable). This includes the essential parts of Grauert–Remmert's two volumes, GL227(236) (Theory of Stein spaces) and GL265 (Coherent analytic sheaves) with a lowering of the level for novice graduate students (here, Grauert's direct image theorem is limited to the case of finite maps). The core of the theory is "Oka's Coherence", found and proved by Kiyoshi Oka. It is indispensable, not only in the study of complex analysis and complex geometry, but also in a large area of modern mathematics. In this book, just after an introductory chapter on holomorphic functions (Chap. 1), we prove Oka's First Coherence Theorem for holomorphic functions in Chap. 2. This defines a unique character of the book compared with other books on this subject, in which the notion of coherence appear...

Sharp Bounds by Probability-Generating Functions and Variable Drift

DEFF Research Database (Denmark)

Doerr, Benjamin; Fouz, Mahmoud; Witt, Carsten

2011-01-01

We introduce to the runtime analysis of evolutionary algorithms two powerful techniques: probability-generating functions and variable drift analysis. They are shown to provide a clean framework for proving sharp upper and lower bounds. As an application, we improve the results by Doerr et al....... (GECCO 2010) in several respects. First, the upper bound on the expected running time of the most successful quasirandom evolutionary algorithm for the OneMax function is improved from 1.28nln n to 0.982nlnn, which breaks the barrier of nln n posed by coupon-collector processes. Compared to the classical...

Intraindividual variability in physical and emotional functioning: comparison of adults with traumatic brain injuries and healthy adults.

Science.gov (United States)

Burton, Catherine L; Hultsch, David F; Strauss, Esther; Hunter, Michael A

2002-08-01

Recent research has shown that individuals with certain neurological conditions demonstrate greater intraindividual variability on cognitive tasks compared to healthy controls. The present study investigated intraindividual variability in the domains of physical functioning and affect/stress in three groups: adults with mild head injuries, adults with moderate/severe head injuries, and healthy adults. Participants were assessed on 10 occasions and results indicated that (a) individuals with head injuries demonstrated greater variability in dominant finger dexterity and right grip strength than the healthy controls; (b) increased variability tended to be associated with poorer performance/report both within and across tasks; and (c) increased variability on one task was associated with increased variability on other tasks. The findings suggest that increased variability in physical function, as well as cognitive function, represents an indicator of neurological compromise.

Heart rate variability biofeedback improves cardiorespiratory resting function during sleep.

Science.gov (United States)

Sakakibara, Masahito; Hayano, Junichiro; Oikawa, Leo O; Katsamanis, Maria; Lehrer, Paul

2013-12-01

The present study was designed to examine the effect of heart rate variability (HRV) biofeedback on the cardiorespiratory resting function during sleep in daily life. Forty-five healthy young adults were randomly assigned to one of three groups: HRV biofeedback, Autogenic Training(AT), and no-treatment control. Participants in the HRV biofeedback were instructed to use a handheld HRV biofeedback device before their habitual bedtime, those in the AT were asked to listen to an audiotaped instruction before bedtime,and those in the control were asked to engage in their habitual activity before bedtime. Pulse wave signal during sleep at their own residences was measured continuously with a wrist watch-type transdermal photoelectric sensor for three time points. Baseline data were collected on the first night of measurements, followed by two successive nights for HRV biofeedback, AT, or control. Cardiorespiratory resting function was assessed quantitatively as the amplitude of high frequency(HF) component of pulse rate variability, a surrogate measure of respiratory sinus arrhythmia. HF component increased during sleep in the HRV biofeedback group,although it remained unchanged in the AT and control groups. These results suggest that HRV biofeedback before sleep may improve cardiorespiratory resting function during sleep.

Local dynamic stability and variability of gait are associated with fall history in elderly subjects

NARCIS (Netherlands)

Toebes, M.J.P.; Hoozemans, M.J.M.; Furrer, R.; Dekker, J.; van Dieen, J.H.

2012-01-01

Gait parameters that can be measured with simple instrumentation may hold promise for identifying individuals at risk of falling. Increased variability of gait is associated with increased risk of falling, but research on additional parameters indicates that local dynamic stability (LDS) of gait may

Population dynamics under increasing environmental variability: implications of climate change for ecological network design criteria

NARCIS (Netherlands)

Verboom, J.; Schippers, P.; Cormont, A.; Sterk, M.; Vos, C.C.; Opdam, P.F.M.

2010-01-01

There is growing evidence that climate change causes an increase in variation in conditions for plant and animal populations. This increase in variation, e.g. amplified inter-annual variability in temperature and rainfall has population dynamical consequences because it raises the variation in vital

Non-commutative linear algebra and plurisubharmonic functions of quaternionic variables

OpenAIRE

Alesker, Semyon

2003-01-01

We recall known and establish new properties of the Dieudonn\\'e and Moore determinants of quaternionic matrices.Using these linear algebraic results we develop a basic theory of plurisubharmonic functions of quaternionic variables. Then we introduce and briefly discuss quaternionic Monge-Amp\\'ere equations.

Temporal dynamics of hot desert microbial communities reveal structural and functional responses to water input.

Science.gov (United States)

Armstrong, Alacia; Valverde, Angel; Ramond, Jean-Baptiste; Makhalanyane, Thulani P; Jansson, Janet K; Hopkins, David W; Aspray, Thomas J; Seely, Mary; Trindade, Marla I; Cowan, Don A

2016-09-29

The temporal dynamics of desert soil microbial communities are poorly understood. Given the implications for ecosystem functioning under a global change scenario, a better understanding of desert microbial community stability is crucial. Here, we sampled soils in the central Namib Desert on sixteen different occasions over a one-year period. Using Illumina-based amplicon sequencing of the 16S rRNA gene, we found that α-diversity (richness) was more variable at a given sampling date (spatial variability) than over the course of one year (temporal variability). Community composition remained essentially unchanged across the first 10 months, indicating that spatial sampling might be more important than temporal sampling when assessing β-diversity patterns in desert soils. However, a major shift in microbial community composition was found following a single precipitation event. This shift in composition was associated with a rapid increase in CO 2 respiration and productivity, supporting the view that desert soil microbial communities respond rapidly to re-wetting and that this response may be the result of both taxon-specific selection and changes in the availability or accessibility of organic substrates. Recovery to quasi pre-disturbance community composition was achieved within one month after rainfall.

Temporal dynamics of hot desert microbial communities reveal structural and functional responses to water input

Energy Technology Data Exchange (ETDEWEB)

Armstrong, Alacia; Valverde, Angel; Ramond, Jean-Baptiste; Makhalanyane, Thulani P.; Jansson, Janet K.; Hopkins, David W.; Aspray, Thomas J.; Seely, Mary; Trindade, Marla I.; Cowan, Don A.

2016-09-29

The temporal dynamics of desert soil microbial communities are poorly understood. Given the implications for ecosystem functioning under a global change scenario, a better understanding of desert microbial community stability is crucial. Here, we sampled soils in the central Namib Desert on sixteen different occasions over a one-year period. Using Illumina-based amplicon sequencing of the 16S rRNA gene, we found that α-diversity (richness) was more variable at a given sampling date (spatial variability) than over the course of one year (temporal variability). Community composition remained essentially unchanged across the first 10 months, indicating that spatial sampling might be more important than temporal sampling when assessing β-diversity patterns in desert soils. However, a major shift in microbial community composition was found following a single precipitation event. This shift in composition was associated with a rapid increase in CO2 respiration and productivity, supporting the view that desert soil microbial communities respond rapidly to re-wetting and that this response may be the result of both taxon-specific selection and changes in the availability or accessibility of organic substrates. Recovery to quasi pre-disturbance community composition was achieved within one month after rainfall.

Dynamical rescaling, the EMC effect and universality of hadron structure functions

International Nuclear Information System (INIS)

Close, F.E.

1984-04-01

Data are compared on the EMC effect, with the hypothesis that the quark confinement size increases in going from a free nucleon to a nucleus. In QCD a dynamical rescaling is predicted: Q 2 variation of the distribution function in a given target parallels the dependence on confinement size, R, at fixed Q 2 . Thus a dynamical scale invariance obtains when both R and Q 2 are varied, yielding the dynamical rescaling relation F 2 sup(A)(x, Q 2 ) = F 2 sup(N)(x, zetaQ 2 ) where zeta > 1 is predicted for any nucleus and is a function of the confinement size. Data on 12 nuclei agree with this, implying that confinement size is governed by nuclear density. The formalism is tested by relating the pion and nucleon structure functions. (author)

Quadrupole collective dynamics from energy density functionals: Collective Hamiltonian and the interacting boson model

International Nuclear Information System (INIS)

Nomura, K.; Vretenar, D.; Niksic, T.; Otsuka, T.; Shimizu, N.

2011-01-01

Microscopic energy density functionals have become a standard tool for nuclear structure calculations, providing an accurate global description of nuclear ground states and collective excitations. For spectroscopic applications, this framework has to be extended to account for collective correlations related to restoration of symmetries broken by the static mean field, and for fluctuations of collective variables. In this paper, we compare two approaches to five-dimensional quadrupole dynamics: the collective Hamiltonian for quadrupole vibrations and rotations and the interacting boson model (IBM). The two models are compared in a study of the evolution of nonaxial shapes in Pt isotopes. Starting from the binding energy surfaces of 192,194,196 Pt, calculated with a microscopic energy density functional, we analyze the resulting low-energy collective spectra obtained from the collective Hamiltonian, and the corresponding IBM Hamiltonian. The calculated excitation spectra and transition probabilities for the ground-state bands and the γ-vibration bands are compared to the corresponding sequences of experimental states.

Spatial-temporal-spectral EEG patterns of BOLD functional network connectivity dynamics

Science.gov (United States)

Lamoš, Martin; Mareček, Radek; Slavíček, Tomáš; Mikl, Michal; Rektor, Ivan; Jan, Jiří

2018-06-01

Objective. Growing interest in the examination of large-scale brain network functional connectivity dynamics is accompanied by an effort to find the electrophysiological correlates. The commonly used constraints applied to spatial and spectral domains during electroencephalogram (EEG) data analysis may leave part of the neural activity unrecognized. We propose an approach that blindly reveals multimodal EEG spectral patterns that are related to the dynamics of the BOLD functional network connectivity. Approach. The blind decomposition of EEG spectrogram by parallel factor analysis has been shown to be a useful technique for uncovering patterns of neural activity. The simultaneously acquired BOLD fMRI data were decomposed by independent component analysis. Dynamic functional connectivity was computed on the component’s time series using a sliding window correlation, and between-network connectivity states were then defined based on the values of the correlation coefficients. ANOVA tests were performed to assess the relationships between the dynamics of between-network connectivity states and the fluctuations of EEG spectral patterns. Main results. We found three patterns related to the dynamics of between-network connectivity states. The first pattern has dominant peaks in the alpha, beta, and gamma bands and is related to the dynamics between the auditory, sensorimotor, and attentional networks. The second pattern, with dominant peaks in the theta and low alpha bands, is related to the visual and default mode network. The third pattern, also with peaks in the theta and low alpha bands, is related to the auditory and frontal network. Significance. Our previous findings revealed a relationship between EEG spectral pattern fluctuations and the hemodynamics of large-scale brain networks. In this study, we suggest that the relationship also exists at the level of functional connectivity dynamics among large-scale brain networks when no standard spatial and spectral

Neural, electrophysiological and anatomical basis of brain-network variability and its characteristic changes in mental disorders.

Science.gov (United States)

Zhang, Jie; Cheng, Wei; Liu, Zhaowen; Zhang, Kai; Lei, Xu; Yao, Ye; Becker, Benjamin; Liu, Yicen; Kendrick, Keith M; Lu, Guangming; Feng, Jianfeng

2016-08-01

SEE MATTAR ET AL DOI101093/AWW151 FOR A SCIENTIFIC COMMENTARY ON THIS ARTICLE: Functional brain networks demonstrate significant temporal variability and dynamic reconfiguration even in the resting state. Currently, most studies investigate temporal variability of brain networks at the scale of single (micro) or whole-brain (macro) connectivity. However, the mechanism underlying time-varying properties remains unclear, as the coupling between brain network variability and neural activity is not readily apparent when analysed at either micro or macroscales. We propose an intermediate (meso) scale analysis and characterize temporal variability of the functional architecture associated with a particular region. This yields a topography of variability that reflects the whole-brain and, most importantly, creates an analytical framework to establish the fundamental relationship between variability of regional functional architecture and its neural activity or structural connectivity. We find that temporal variability reflects the dynamical reconfiguration of a brain region into distinct functional modules at different times and may be indicative of brain flexibility and adaptability. Primary and unimodal sensory-motor cortices demonstrate low temporal variability, while transmodal areas, including heteromodal association areas and limbic system, demonstrate the high variability. In particular, regions with highest variability such as hippocampus/parahippocampus, inferior and middle temporal gyrus, olfactory gyrus and caudate are all related to learning, suggesting that the temporal variability may indicate the level of brain adaptability. With simultaneously recorded electroencephalography/functional magnetic resonance imaging and functional magnetic resonance imaging/diffusion tensor imaging data, we also find that variability of regional functional architecture is modulated by local blood oxygen level-dependent activity and α-band oscillation, and is governed by the

Default Mode Dynamics for Global Functional Integration.

Science.gov (United States)

Vatansever, Deniz; Menon, David K; Manktelow, Anne E; Sahakian, Barbara J; Stamatakis, Emmanuel A

2015-11-18

The default mode network (DMN) has been traditionally assumed to hinder behavioral performance in externally focused, goal-directed paradigms and to provide no active contribution to human cognition. However, recent evidence suggests greater DMN activity in an array of tasks, especially those that involve self-referential and memory-based processing. Although data that robustly demonstrate a comprehensive functional role for DMN remains relatively scarce, the global workspace framework, which implicates the DMN in global information integration for conscious processing, can potentially provide an explanation for the broad range of higher-order paradigms that report DMN involvement. We used graph theoretical measures to assess the contribution of the DMN to global functional connectivity dynamics in 22 healthy volunteers during an fMRI-based n-back working-memory paradigm with parametric increases in difficulty. Our predominant finding is that brain modularity decreases with greater task demands, thus adapting a more global workspace configuration, in direct relation to increases in reaction times to correct responses. Flexible default mode regions dynamically switch community memberships and display significant changes in their nodal participation coefficient and strength, which may reflect the observed whole-brain changes in functional connectivity architecture. These findings have important implications for our understanding of healthy brain function, as they suggest a central role for the DMN in higher cognitive processing. The default mode network (DMN) has been shown to increase its activity during the absence of external stimulation, and hence was historically assumed to disengage during goal-directed tasks. Recent evidence, however, implicates the DMN in self-referential and memory-based processing. We provide robust evidence for this network's active contribution to working memory by revealing dynamic reconfiguration in its interactions with other networks

A functional-dynamic reflection on participatory processes in modeling projects.

Science.gov (United States)

Seidl, Roman

2015-12-01

The participation of nonscientists in modeling projects/studies is increasingly employed to fulfill different functions. However, it is not well investigated if and how explicitly these functions and the dynamics of a participatory process are reflected by modeling projects in particular. In this review study, I explore participatory modeling projects from a functional-dynamic process perspective. The main differences among projects relate to the functions of participation-most often, more than one per project can be identified, along with the degree of explicit reflection (i.e., awareness and anticipation) on the dynamic process perspective. Moreover, two main approaches are revealed: participatory modeling covering diverse approaches and companion modeling. It becomes apparent that the degree of reflection on the participatory process itself is not always explicit and perfectly visible in the descriptions of the modeling projects. Thus, the use of common protocols or templates is discussed to facilitate project planning, as well as the publication of project results. A generic template may help, not in providing details of a project or model development, but in explicitly reflecting on the participatory process. It can serve to systematize the particular project's approach to stakeholder collaboration, and thus quality management.

Applied systems theory as a means for studying the function and dynamics of living space used for agro-silviculture

Energy Technology Data Exchange (ETDEWEB)

Grossmann, W D; Schneider, T W

1980-09-01

Applied systems theories are sensitive tools for analysing the functions and dynamics of agrosilvicultural systems. Major interactions within and between agrosilvicultural systems and the natural and socio-economic environment are represented by corresponding interactions within a hierarchy of system models. A new meta-criteria analysis quantifies the variables of agrosilvicultural systems and produces indicators for assessing the stability or instability of the whole system complex. Two highly disaggregated models predict growth and yield and analyse structure and floristic variation of forest systems.

Variability of pulmonary function test in healthy children, asthmatic and with chronicle lung disease

International Nuclear Information System (INIS)

Rodriguez Martinez, Carlos; Sossa, Monica Patricia; Cortez, Eliana; Mallol, Javier

2004-01-01

Comparison of sequential pulmonary function tests in the same individual can be used to assess progression of a disease, response to therapy, or response to bronchial provocation. These types of comparisons require an understanding of the factors influencing the variability normally in repeat measurements of lung function. To avoid misleading conclusions about changes in serial measurements, the degree of variability of each test must be considered in their interpretation. The purpose of this study was to examine the degree of intrasubject variability for pulmonary function testing in healthy, asthmatic and children with chronic lung disease (CLD). The tests examined were spirometry, and body plethysmography determination of lung volumes. We studied 21 healthy children, 19 asthmatic patients and 19 children with CLD, testing were done on nine occasions, three times within a day, on three different days, over a period of two months. Short-term variability was defined as the coefficient of variation for the s ix measurements made on days 1 and 2, and the long-term variability as the CV of the nine measurements made on days 1, 2 and 3. Based on the CV measures, children with CLD had significantly more variability in all spirometric values compared with healthy and asthmatic children, except for PEF (P< 0.05) children with CLD had a significantly lower CV for TGV and FRC compared with the other two groups (p < 0.05). Asthmatic children had a significantly higher CV for RV and RV/TLC compared with healthy and children with CLD (p < 0.05). We propose a method to consider changes in pulmonary function tests as significant. The degree of variability and an estimate of the percent change for significance of spirometric and plethysmographic tests must be considered in the interpretation of data to avoid misleading conclusions. The variability of spirometric pulmonary function data in healthy subjects was smaller than that for patients with pulmonary disease, so larger

Association between Functional Variables and Heart Failure after Myocardial Infarction in Rats

Energy Technology Data Exchange (ETDEWEB)

Polegato, Bertha F.; Minicucci, Marcos F.; Azevedo, Paula S.; Gonçalves, Andréa F.; Lima, Aline F.; Martinez, Paula F.; Okoshi, Marina P.; Okoshi, Katashi; Paiva, Sergio A. R.; Zornoff, Leonardo A. M., E-mail: lzornoff@fmb.unesp.br [Faculdade de Medicina de Botucatu - Universidade Estadual Paulista ' Júlio de mesquita Filho' - UNESP Botucatu, SP (Brazil)

2016-02-15

Heart failure prediction after acute myocardial infarction may have important clinical implications. To analyze the functional echocardiographic variables associated with heart failure in an infarction model in rats. The animals were divided into two groups: control and infarction. Subsequently, the infarcted animals were divided into groups: with and without heart failure. The predictive values were assessed by logistic regression. The cutoff values predictive of heart failure were determined using ROC curves. Six months after surgery, 88 infarcted animals and 43 control animals were included in the study. Myocardial infarction increased left cavity diameters and the mass and wall thickness of the left ventricle. Additionally, myocardial infarction resulted in systolic and diastolic dysfunction, characterized by lower area variation fraction values, posterior wall shortening velocity, E-wave deceleration time, associated with higher values of E / A ratio and isovolumic relaxation time adjusted by heart rate. Among the infarcted animals, 54 (61%) developed heart failure. Rats with heart failure have higher left cavity mass index and diameter, associated with worsening of functional variables. The area variation fraction, the E/A ratio, E-wave deceleration time and isovolumic relaxation time adjusted by heart rate were functional variables predictors of heart failure. The cutoff values of functional variables associated with heart failure were: area variation fraction < 31.18%; E / A > 3.077; E-wave deceleration time < 42.11 and isovolumic relaxation time adjusted by heart rate < 69.08. In rats followed for 6 months after myocardial infarction, the area variation fraction, E/A ratio, E-wave deceleration time and isovolumic relaxation time adjusted by heart rate are predictors of heart failure onset.

Association between Functional Variables and Heart Failure after Myocardial Infarction in Rats

International Nuclear Information System (INIS)

Polegato, Bertha F.; Minicucci, Marcos F.; Azevedo, Paula S.; Gonçalves, Andréa F.; Lima, Aline F.; Martinez, Paula F.; Okoshi, Marina P.; Okoshi, Katashi; Paiva, Sergio A. R.; Zornoff, Leonardo A. M.

2016-01-01

Heart failure prediction after acute myocardial infarction may have important clinical implications. To analyze the functional echocardiographic variables associated with heart failure in an infarction model in rats. The animals were divided into two groups: control and infarction. Subsequently, the infarcted animals were divided into groups: with and without heart failure. The predictive values were assessed by logistic regression. The cutoff values predictive of heart failure were determined using ROC curves. Six months after surgery, 88 infarcted animals and 43 control animals were included in the study. Myocardial infarction increased left cavity diameters and the mass and wall thickness of the left ventricle. Additionally, myocardial infarction resulted in systolic and diastolic dysfunction, characterized by lower area variation fraction values, posterior wall shortening velocity, E-wave deceleration time, associated with higher values of E / A ratio and isovolumic relaxation time adjusted by heart rate. Among the infarcted animals, 54 (61%) developed heart failure. Rats with heart failure have higher left cavity mass index and diameter, associated with worsening of functional variables. The area variation fraction, the E/A ratio, E-wave deceleration time and isovolumic relaxation time adjusted by heart rate were functional variables predictors of heart failure. The cutoff values of functional variables associated with heart failure were: area variation fraction < 31.18%; E / A > 3.077; E-wave deceleration time < 42.11 and isovolumic relaxation time adjusted by heart rate < 69.08. In rats followed for 6 months after myocardial infarction, the area variation fraction, E/A ratio, E-wave deceleration time and isovolumic relaxation time adjusted by heart rate are predictors of heart failure onset

Multiscale simulations of anisotropic particles combining molecular dynamics and Green's function reaction dynamics

NARCIS (Netherlands)

Vijaykumar, A.; Ouldridge, T.E.; ten Wolde, P.R.; Bolhuis, P.G.

2017-01-01

The modeling of complex reaction-diffusion processes in, for instance, cellular biochemical networks or self-assembling soft matter can be tremendously sped up by employing a multiscale algorithm which combines the mesoscopic Green's Function Reaction Dynamics (GFRD) method with explicit stochastic

Dynamic Analysis of Fluid Power Drive-trains for Variable Speed Wind Turbines : A Parameter Study

NARCIS (Netherlands)

Jarquin Laguna, A.; Diepeveen, N.F.B.

2013-01-01

In the pursuit of making wind energy technology more economically attractive, the application of fluid power technology for the transmission of wind energy is being developed by several parties all over the world. This paper presents a dynamic model of a fluid power transmission for variable speed

Effects of a cognitive dual task on variability and local dynamic stability in sustained repetitive arm movements using principal component analysis: a pilot study.

Science.gov (United States)

Longo, Alessia; Federolf, Peter; Haid, Thomas; Meulenbroek, Ruud

2018-06-01

In many daily jobs, repetitive arm movements are performed for extended periods of time under continuous cognitive demands. Even highly monotonous tasks exhibit an inherent motor variability and subtle fluctuations in movement stability. Variability and stability are different aspects of system dynamics, whose magnitude may be further affected by a cognitive load. Thus, the aim of the study was to explore and compare the effects of a cognitive dual task on the variability and local dynamic stability in a repetitive bimanual task. Thirteen healthy volunteers performed the repetitive motor task with and without a concurrent cognitive task of counting aloud backwards in multiples of three. Upper-body 3D kinematics were collected and postural reconfigurations-the variability related to the volunteer's postural change-were determined through a principal component analysis-based procedure. Subsequently, the most salient component was selected for the analysis of (1) cycle-to-cycle spatial and temporal variability, and (2) local dynamic stability as reflected by the largest Lyapunov exponent. Finally, end-point variability was evaluated as a control measure. The dual cognitive task proved to increase the temporal variability and reduce the local dynamic stability, marginally decrease endpoint variability, and substantially lower the incidence of postural reconfigurations. Particularly, the latter effect is considered to be relevant for the prevention of work-related musculoskeletal disorders since reduced variability in sustained repetitive tasks might increase the risk of overuse injuries.

Robustness of MEK-ERK Dynamics and Origins of Cell-to-Cell Variability in MAPK Signaling

Directory of Open Access Journals (Sweden)

Sarah Filippi

2016-06-01

Full Text Available Cellular signaling processes can exhibit pronounced cell-to-cell variability in genetically identical cells. This affects how individual cells respond differentially to the same environmental stimulus. However, the origins of cell-to-cell variability in cellular signaling systems remain poorly understood. Here, we measure the dynamics of phosphorylated MEK and ERK across cell populations and quantify the levels of population heterogeneity over time using high-throughput image cytometry. We use a statistical modeling framework to show that extrinsic noise, particularly that from upstream MEK, is the dominant factor causing cell-to-cell variability in ERK phosphorylation, rather than stochasticity in the phosphorylation/dephosphorylation of ERK. We furthermore show that without extrinsic noise in the core module, variable (including noisy signals would be faithfully reproduced downstream, but the within-module extrinsic variability distorts these signals and leads to a drastic reduction in the mutual information between incoming signal and ERK activity.

Root structural and functional dynamics in terrestrial biosphere models--evaluation and recommendations.

Science.gov (United States)

Warren, Jeffrey M; Hanson, Paul J; Iversen, Colleen M; Kumar, Jitendra; Walker, Anthony P; Wullschleger, Stan D

2015-01-01

There is wide breadth of root function within ecosystems that should be considered when modeling the terrestrial biosphere. Root structure and function are closely associated with control of plant water and nutrient uptake from the soil, plant carbon (C) assimilation, partitioning and release to the soils, and control of biogeochemical cycles through interactions within the rhizosphere. Root function is extremely dynamic and dependent on internal plant signals, root traits and morphology, and the physical, chemical and biotic soil environment. While plant roots have significant structural and functional plasticity to changing environmental conditions, their dynamics are noticeably absent from the land component of process-based Earth system models used to simulate global biogeochemical cycling. Their dynamic representation in large-scale models should improve model veracity. Here, we describe current root inclusion in models across scales, ranging from mechanistic processes of single roots to parameterized root processes operating at the landscape scale. With this foundation we discuss how existing and future root functional knowledge, new data compilation efforts, and novel modeling platforms can be leveraged to enhance root functionality in large-scale terrestrial biosphere models by improving parameterization within models, and introducing new components such as dynamic root distribution and root functional traits linked to resource extraction. No claim to original US Government works. New Phytologist © 2014 New Phytologist Trust.

Dynamic sensorimotor planning during long-term sequence learning: the role of variability, response chunking and planning errors.

Science.gov (United States)

Verstynen, Timothy; Phillips, Jeff; Braun, Emily; Workman, Brett; Schunn, Christian; Schneider, Walter

2012-01-01

Many everyday skills are learned by binding otherwise independent actions into a unified sequence of responses across days or weeks of practice. Here we looked at how the dynamics of action planning and response binding change across such long timescales. Subjects (N = 23) were trained on a bimanual version of the serial reaction time task (32-item sequence) for two weeks (10 days total). Response times and accuracy both showed improvement with time, but appeared to be learned at different rates. Changes in response speed across training were associated with dynamic changes in response time variability, with faster learners expanding their variability during the early training days and then contracting response variability late in training. Using a novel measure of response chunking, we found that individual responses became temporally correlated across trials and asymptoted to set sizes of approximately 7 bound responses at the end of the first week of training. Finally, we used a state-space model of the response planning process to look at how predictive (i.e., response anticipation) and error-corrective (i.e., post-error slowing) processes correlated with learning rates for speed, accuracy and chunking. This analysis yielded non-monotonic association patterns between the state-space model parameters and learning rates, suggesting that different parts of the response planning process are relevant at different stages of long-term learning. These findings highlight the dynamic modulation of response speed, variability, accuracy and chunking as multiple movements become bound together into a larger set of responses during sequence learning.

Riemann zeta function from wave-packet dynamics

DEFF Research Database (Denmark)

Mack, R.; Dahl, Jens Peder; Moya-Cessa, H.

2010-01-01

We show that the time evolution of a thermal phase state of an anharmonic oscillator with logarithmic energy spectrum is intimately connected to the generalized Riemann zeta function zeta(s, a). Indeed, the autocorrelation function at a time t is determined by zeta (sigma + i tau, a), where sigma...... index of JWKB. We compare and contrast exact and approximate eigenvalues of purely logarithmic potentials. Moreover, we use a numerical method to find a potential which leads to exact logarithmic eigenvalues. We discuss possible realizations of Riemann zeta wave-packet dynamics using cold atoms...

Individual renal function study using dynamic computed tomography

International Nuclear Information System (INIS)

Fukuda, Yutaka; Kiya, Keiichi; Suzuki, Yoshiharu

1990-01-01

Dynamic CT scans of individual kindneys were obtained after an intravenous bolus injection of contrast agent. Time-density curves measured from the renal cortex, medulla and pelvis revealed the changes in density produced by the contrast agent reflecting the differential phase of renal function. Renal cortical density increased rapidly after bolus administration and then renal medullary and pelvic density increased continuously. In analyzing time-density curve, the cortico-medullary junction time, which is the time when the cortical and medullary curves cross was 57±8 seconds in patients with normal renal function. The cortico-medullary junction time was delayed in patient with decreased glomerular filtration rate. The cortico-pelvic junction time, which is the time when the cortical and pelvic curves cross was 104±33 seconds in patients with normal renal function. The cortico-pelvic junction time was delayed in patients with declined urinary concentrating capacity. In patients with unilateral renal agenesis and patients who were treated surgically by ureteral sprits, the relationship between individual renal functions and these junction times was examined. As a result of study there were inversely significant correlations between C-M junction time and unilateral GFR and between C-P junction time and urinary concentrating capacity. These studies indicate that dynamic CT scanning is an effective way that individual renal function can be monitored and evaluated. (author)

The dynamic mechanism of presenilin-function: Sensitive gate dynamics and loop unplugging control protein access

DEFF Research Database (Denmark)

Somavarapu, Arun Kumar; Kepp, Kasper Planeta

2016-01-01

There is no molecular explanation for the many presenilin 1 (PSEN1) mutations causing Alzheimer's disease, but both gain of function relating to amyloid production and loss of isolated PSEN1 function have been implied. We report here the first detailed dynamic all-atom model of mature PSEN1 from ...

Dynamics of heterogeneous oscillator ensembles in terms of collective variables

Science.gov (United States)

Pikovsky, Arkady; Rosenblum, Michael

2011-04-01

We consider general heterogeneous ensembles of phase oscillators, sine coupled to arbitrary external fields. Starting with the infinitely large ensembles, we extend the Watanabe-Strogatz theory, valid for identical oscillators, to cover the case of an arbitrary parameter distribution. The obtained equations yield the description of the ensemble dynamics in terms of collective variables and constants of motion. As a particular case of the general setup we consider hierarchically organized ensembles, consisting of a finite number of subpopulations, whereas the number of elements in a subpopulation can be both finite or infinite. Next, we link the Watanabe-Strogatz and Ott-Antonsen theories and demonstrate that the latter one corresponds to a particular choice of constants of motion. The approach is applied to the standard Kuramoto-Sakaguchi model, to its extension for the case of nonlinear coupling, and to the description of two interacting subpopulations, exhibiting a chimera state. With these examples we illustrate that, although the asymptotic dynamics can be found within the framework of the Ott-Antonsen theory, the transients depend on the constants of motion. The most dramatic effect is the dependence of the basins of attraction of different synchronous regimes on the initial configuration of phases.

Water Flow in Karst Aquifer Considering Dynamically Variable Saturation Conduit

Science.gov (United States)

Tan, Chaoqun; Hu, Bill X.

2017-04-01

The karst system is generally conceptualized as dual-porosity system, which is characterized by low conductivity and high storage continuum matrix and high conductivity and quick flow conduit networks. And so far, a common numerical model for simulating flow in karst aquifer is MODFLOW2005-CFP, which is released by USGS in 2008. However, the steady-state approach for conduit flow in CFP is physically impractical when simulating very dynamic hydraulics with variable saturation conduit. So, we adopt the method proposed by Reimann et al. (2011) to improve current model, in which Saint-Venant equations are used to model the flow in conduit. Considering the actual background that the conduit is very big and varies along flow path and the Dirichlet boundary varies with rainfall in our study area in Southwest China, we further investigate the influence of conduit diameter and outflow boundary on numerical model. And we also analyze the hydraulic process in multi-precipitation events. We find that the numerical model here corresponds well with CFP for saturated conduit, and it could depict the interaction between matrix and conduit during very dynamic hydraulics pretty well compare with CFP.

The functional variable method for finding exact solutions of some ...

Indian Academy of Sciences (India)

Abstract. In this paper, we implemented the functional variable method and the modified. Riemann–Liouville derivative for the exact solitary wave solutions and periodic wave solutions of the time-fractional Klein–Gordon equation, and the time-fractional Hirota–Satsuma coupled. KdV system. This method is extremely simple ...

Korean Conference on Several Complex Variables

CERN Document Server

Byun, Jisoo; Gaussier, Hervé; Hirachi, Kengo; Kim, Kang-Tae; Shcherbina, Nikolay

2015-01-01

This volume includes 28 chapters by authors who are leading researchers of the world describing many of the up-to-date aspects in the field of several complex variables (SCV). These contributions are based upon their presentations at the 10th Korean Conference on Several Complex Variables (KSCV10), held as a satellite conference to the International Congress of Mathematicians (ICM) 2014 in Seoul, Korea. SCV has been the term for multidimensional complex analysis, one of the central research areas in mathematics. Studies over time have revealed a variety of rich, intriguing, new knowledge in complex analysis and geometry of analytic spaces and holomorphic functions which were "hidden" in the case of complex dimension one. These new theories have significant intersections with algebraic geometry, differential geometry, partial differential equations, dynamics, functional analysis and operator theory, and sheaves and cohomology, as well as the traditional analysis of holomorphic functions in all dimensions. This...

HYPERDIRE HYPERgeometric functions DIfferential REduction. Mathematica-based packages for the differential reduction of generalized hypergeometric functions. Lauricella function FC of three variables

International Nuclear Information System (INIS)

Bytev, Vladimir V.; Kniehl, Bernd A.

2016-12-01

We present a further extension of the HYPERDIRE project, which is devoted to the creation of a set of Mathematica-based program packages for manipulations with Horn-type hypergeometric functions on the basis of differential equations. Specifically, we present the implementation of the differential reduction for the Lauricella function F C of three variables.

Platelet Function Tests: Preanalytical Variables, Clinical Utility, Advantages, and Disadvantages.

Science.gov (United States)

Hvas, Anne-Mette; Grove, Erik Lerkevang

2017-01-01

Platelet function tests are mainly used in the diagnostic work-up of platelet disorders. During the last decade, the additional use of platelet function tests to evaluate the effect of antiplatelet therapy has also emerged in an attempt to identify patients with an increased risk of arterial thrombosis. Furthermore, platelet function tests are increasingly used to measure residual effect of antiplatelet therapy prior to surgery with the aim of reducing the risk of bleeding. To a limited extend, platelet function tests are also used to evaluate hyperaggregability as a potential marker of a prothrombotic state outside the setting of antiplatelet therapy. This multifaceted use of platelet function tests and the development of simpler point-of-care tests with narrower application have increased the use of platelet function testing and also facilitated the use of platelet function tests outside the highly specialized laboratories. The present chapter describes the preanalytical variables, which should be taken into account when planning platelet function testing. Also, the most widely used platelet function tests are introduced, and their clinical utility and their relative advantages and disadvantages are discussed.

Thermal quantum time-correlation functions from classical-like dynamics

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Hele, Timothy J. H.

2017-07-01

Thermal quantum time-correlation functions are of fundamental importance in quantum dynamics, allowing experimentally measurable properties such as reaction rates, diffusion constants and vibrational spectra to be computed from first principles. Since the exact quantum solution scales exponentially with system size, there has been considerable effort in formulating reliable linear-scaling methods involving exact quantum statistics and approximate quantum dynamics modelled with classical-like trajectories. Here, we review recent progress in the field with the development of methods including centroid molecular dynamics , ring polymer molecular dynamics (RPMD) and thermostatted RPMD (TRPMD). We show how these methods have recently been obtained from 'Matsubara dynamics', a form of semiclassical dynamics which conserves the quantum Boltzmann distribution. We also apply the Matsubara formalism to reaction rate theory, rederiving t → 0+ quantum transition-state theory (QTST) and showing that Matsubara-TST, like RPMD-TST, is equivalent to QTST. We end by surveying areas for future progress.

Sampling intraspecific variability in leaf functional traits: Practical suggestions to maximize collected information.

Science.gov (United States)

Petruzzellis, Francesco; Palandrani, Chiara; Savi, Tadeja; Alberti, Roberto; Nardini, Andrea; Bacaro, Giovanni

2017-12-01

The choice of the best sampling strategy to capture mean values of functional traits for a species/population, while maintaining information about traits' variability and minimizing the sampling size and effort, is an open issue in functional trait ecology. Intraspecific variability (ITV) of functional traits strongly influences sampling size and effort. However, while adequate information is available about intraspecific variability between individuals (ITV BI ) and among populations (ITV POP ), relatively few studies have analyzed intraspecific variability within individuals (ITV WI ). Here, we provide an analysis of ITV WI of two foliar traits, namely specific leaf area (SLA) and osmotic potential (π), in a population of Quercus ilex L. We assessed the baseline ITV WI level of variation between the two traits and provided the minimum and optimal sampling size in order to take into account ITV WI , comparing sampling optimization outputs with those previously proposed in the literature. Different factors accounted for different amount of variance of the two traits. SLA variance was mostly spread within individuals (43.4% of the total variance), while π variance was mainly spread between individuals (43.2%). Strategies that did not account for all the canopy strata produced mean values not representative of the sampled population. The minimum size to adequately capture the studied functional traits corresponded to 5 leaves taken randomly from 5 individuals, while the most accurate and feasible sampling size was 4 leaves taken randomly from 10 individuals. We demonstrate that the spatial structure of the canopy could significantly affect traits variability. Moreover, different strategies for different traits could be implemented during sampling surveys. We partially confirm sampling sizes previously proposed in the recent literature and encourage future analysis involving different traits.

Proteins with Novel Structure, Function and Dynamics

Science.gov (United States)

Pohorille, Andrew

2014-01-01

Recently, a small enzyme that ligates two RNA fragments with the rate of 10(exp 6) above background was evolved in vitro (Seelig and Szostak, Nature 448:828-831, 2007). This enzyme does not resemble any contemporary protein (Chao et al., Nature Chem. Biol. 9:81-83, 2013). It consists of a dynamic, catalytic loop, a small, rigid core containing two zinc ions coordinated by neighboring amino acids, and two highly flexible tails that might be unimportant for protein function. In contrast to other proteins, this enzyme does not contain ordered secondary structure elements, such as alpha-helix or beta-sheet. The loop is kept together by just two interactions of a charged residue and a histidine with a zinc ion, which they coordinate on the opposite side of the loop. Such structure appears to be very fragile. Surprisingly, computer simulations indicate otherwise. As the coordinating, charged residue is mutated to alanine, another, nearby charged residue takes its place, thus keeping the structure nearly intact. If this residue is also substituted by alanine a salt bridge involving two other, charged residues on the opposite sides of the loop keeps the loop in place. These adjustments are facilitated by high flexibility of the protein. Computational predictions have been confirmed experimentally, as both mutants retain full activity and overall structure. These results challenge our notions about what is required for protein activity and about the relationship between protein dynamics, stability and robustness. We hypothesize that small, highly dynamic proteins could be both active and fault tolerant in ways that many other proteins are not, i.e. they can adjust to retain their structure and activity even if subjected to mutations in structurally critical regions. This opens the doors for designing proteins with novel functions, structures and dynamics that have not been yet considered.

Comparison Criteria for Nonlinear Functional Dynamic Equations of Higher Order

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Taher S. Hassan

2016-01-01

Full Text Available We will consider the higher order functional dynamic equations with mixed nonlinearities of the form xnt+∑j=0Npjtϕγjxφjt=0, on an above-unbounded time scale T, where n≥2, xi(t≔ri(tϕαixi-1Δ(t,  i=1,…,n-1,   with  x0=x,  ϕβ(u≔uβsgn⁡u, and α[i,j]≔αi⋯αj. The function φi:T→T is a rd-continuous function such that limt→∞φi(t=∞ for j=0,1,…,N. The results extend and improve some known results in the literature on higher order nonlinear dynamic equations.

Winter NH low-frequency variability in a hierarchy of low-order stochastic dynamical models of earth-atmosphere system

Science.gov (United States)

Zhao, Nan

2018-02-01

The origin of winter Northern Hemispheric low-frequency variability (hereafter, LFV) is regarded to be related to the coupled earth-atmosphere system characterized by the interaction of the jet stream with mid-latitude mountain ranges. On the other hand, observed LFV usually appears as transitions among multiple planetary-scale flow regimes of Northern Hemisphere like NAO + , AO +, AO - and NAO - . Moreover, the interaction between synoptic-scale eddies and the planetary-scale disturbance is also inevitable in the origin of LFV. These raise a question regarding how to incorporate all these aspects into just one framework to demonstrate (1) a planetary-scale dynamics of interaction of the jet stream with mid-latitude mountain ranges can really produce LFV, (2) such a dynamics can be responsible for the existence of above multiple flow regimes, and (3) the role of interaction with eddy is also clarified. For this purpose, a hierarchy of low-order stochastic dynamical models of the coupled earth-atmosphere system derived empirically from different timescale ranges of indices of Arctic Oscillation (AO), North Atlantic Oscillation (NAO), Pacific/North American (PNA), and length of day (LOD) and related probability density function (PDF) analysis are employed in this study. The results seem to suggest that the origin of LFV cannot be understood completely within the planetary-scale dynamics of the interaction of the jet stream with mid-latitude mountain ranges, because (1) the existence of multiple flow regimes such as NAO+, AO+, AO- and NAO- resulted from processes with timescales much longer than LFV itself, which may have underlying dynamics other than topography-jet stream interaction, and (2) we find LFV seems not necessarily to come directly from the planetary-scale dynamics of the interaction of the jet stream with mid-latitude mountain, although it can produce similar oscillatory behavior. The feedback/forcing of synoptic-scale eddies on the planetary

Constructing the reduced dynamical models of interannual climate variability from spatial-distributed time series

Science.gov (United States)

Mukhin, Dmitry; Gavrilov, Andrey; Loskutov, Evgeny; Feigin, Alexander

2016-04-01

We suggest a method for empirical forecast of climate dynamics basing on the reconstruction of reduced dynamical models in a form of random dynamical systems [1,2] derived from observational time series. The construction of proper embedding - the set of variables determining the phase space the model works in - is no doubt the most important step in such a modeling, but this task is non-trivial due to huge dimension of time series of typical climatic fields. Actually, an appropriate expansion of observational time series is needed yielding the number of principal components considered as phase variables, which are to be efficient for the construction of low-dimensional evolution operator. We emphasize two main features the reduced models should have for capturing the main dynamical properties of the system: (i) taking into account time-lagged teleconnections in the atmosphere-ocean system and (ii) reflecting the nonlinear nature of these teleconnections. In accordance to these principles, in this report we present the methodology which includes the combination of a new way for the construction of an embedding by the spatio-temporal data expansion and nonlinear model construction on the basis of artificial neural networks. The methodology is aplied to NCEP/NCAR reanalysis data including fields of sea level pressure, geopotential height, and wind speed, covering Northern Hemisphere. Its efficiency for the interannual forecast of various climate phenomena including ENSO, PDO, NAO and strong blocking event condition over the mid latitudes, is demonstrated. Also, we investigate the ability of the models to reproduce and predict the evolution of qualitative features of the dynamics, such as spectral peaks, critical transitions and statistics of extremes. This research was supported by the Government of the Russian Federation (Agreement No. 14.Z50.31.0033 with the Institute of Applied Physics RAS) [1] Y. I. Molkov, E. M. Loskutov, D. N. Mukhin, and A. M. Feigin, "Random

Phage exposure causes dynamic shifts in the expression states of specific phase-variable genes of Campylobacter jejuni

DEFF Research Database (Denmark)

Aidley, Jack; Holst Sørensen, Martine C.; Bayliss, Christopher D.

2017-01-01

Phase variation (PV) creates phenotypic heterogeneity at high frequencies and in a reversible manner. This phenomenon allows bacteria to adapt to a variety of different environments and selective pressures. In Campylobacter jejuni this reversible adaptive process is mediated by mutations in homop......Phase variation (PV) creates phenotypic heterogeneity at high frequencies and in a reversible manner. This phenomenon allows bacteria to adapt to a variety of different environments and selective pressures. In Campylobacter jejuni this reversible adaptive process is mediated by mutations...... in homopolymeric G/C tracts. Many C. jejuni-specific phages are dependent on phase-variable surface structures for successful infection. We previously identified the capsular polysaccharide (CPS) moiety, MeOPN-GalfNAc, as a receptor for phage F336 and showed that phase-variable expression of the transferase...... for this CPS modification, cj1421, and two other phase-variable CPS genes generated phage resistance in C. jejuni. Here we investigate the population dynamics of C. jejuni NCTC11168 when exposed to phage F336 in vitro using a newly described method - the 28-locus-CJ11168 PV analysis. Dynamic switching...

Dynamic chest radiography: flat-panel detector (FPD) based functional X-ray imaging.

Science.gov (United States)

Tanaka, Rie

2016-07-01

Dynamic chest radiography is a flat-panel detector (FPD)-based functional X-ray imaging, which is performed as an additional examination in chest radiography. The large field of view (FOV) of FPDs permits real-time observation of the entire lungs and simultaneous right-and-left evaluation of diaphragm kinetics. Most importantly, dynamic chest radiography provides pulmonary ventilation and circulation findings as slight changes in pixel value even without the use of contrast media; the interpretation is challenging and crucial for a better understanding of pulmonary function. The basic concept was proposed in the 1980s; however, it was not realized until the 2010s because of technical limitations. Dynamic FPDs and advanced digital image processing played a key role for clinical application of dynamic chest radiography. Pulmonary ventilation and circulation can be quantified and visualized for the diagnosis of pulmonary diseases. Dynamic chest radiography can be deployed as a simple and rapid means of functional imaging in both routine and emergency medicine. Here, we focus on the evaluation of pulmonary ventilation and circulation. This review article describes the basic mechanism of imaging findings according to pulmonary/circulation physiology, followed by imaging procedures, analysis method, and diagnostic performance of dynamic chest radiography.

Socio-functional dynamics of the mathematical contents

Directory of Open Access Journals (Sweden)

Isabel Alonso-Berenguer

2018-01-01

Full Text Available The article presents a model of the socio-functional dynamics of the mathematical contents that offers a novel theoretical-methodological basement for the development of the process of teaching-learning of the mathematical one. The investigation, of theoretical character, used the methods of analysis-synthesis, inductive-deductive and historical-logical to elaborate the one mentioned model that leaves of considering that the future professors have appropriated previously of the mathematical contents, foreseen in the curriculum, and they are, therefore, under conditions of understanding the potentialities of the same ones to facilitate the formation of socio-functional values.   

DEFINE: A Service-Oriented Dynamically Enabling Function Model

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Tan Wei-Yi

2017-01-01

In this paper, we introduce an innovative Dynamically Enable Function In Network Equipment (DEFINE to allow tenant get the network service quickly. First, DEFINE decouples an application into different functional components, and connects these function components in a reconfigurable method. Second, DEFINE provides a programmable interface to the third party, who can develop their own processing modules according to their own needs. To verify the effectiveness of this model, we set up an evaluating network with a FPGA-based OpenFlow switch prototype, and deployed several applications on it. Our results show that DEFINE has excellent flexibility and performance.

Functional clustering in hippocampal cultures: relating network structure and dynamics

International Nuclear Information System (INIS)

Feldt, S; Dzakpasu, R; Olariu, E; Żochowski, M; Wang, J X; Shtrahman, E

2010-01-01

In this work we investigate the relationship between gross anatomic structural network properties, neuronal dynamics and the resultant functional structure in dissociated rat hippocampal cultures. Specifically, we studied cultures as they developed under two conditions: the first supporting glial cell growth (high glial group), and the second one inhibiting it (low glial group). We then compared structural network properties and the spatio-temporal activity patterns of the neurons. Differences in dynamics between the two groups could be linked to the impact of the glial network on the neuronal network as the cultures developed. We also implemented a recently developed algorithm called the functional clustering algorithm (FCA) to obtain the resulting functional network structure. We show that this new algorithm is useful for capturing changes in functional network structure as the networks evolve over time. The FCA detects changes in functional structure that are consistent with expected dynamical differences due to the impact of the glial network. Cultures in the high glial group show an increase in global synchronization as the cultures age, while those in the low glial group remain locally synchronized. We additionally use the FCA to quantify the amount of synchronization present in the cultures and show that the total level of synchronization in the high glial group is stronger than in the low glial group. These results indicate an interdependence between the glial and neuronal networks present in dissociated cultures

Spatially heterogeneous dynamics investigated via a time-dependent four-point density correlation function

DEFF Research Database (Denmark)

Lacevic, N.; Starr, F. W.; Schrøder, Thomas

2003-01-01

correlation function g4(r,t) and corresponding "structure factor" S4(q,t) which measure the spatial correlations between the local liquid density at two points in space, each at two different times, and so are sensitive to dynamical heterogeneity. We study g4(r,t) and S4(q,t) via molecular dynamics......Relaxation in supercooled liquids above their glass transition and below the onset temperature of "slow" dynamics involves the correlated motion of neighboring particles. This correlated motion results in the appearance of spatially heterogeneous dynamics or "dynamical heterogeneity." Traditional...... two-point time-dependent density correlation functions, while providing information about the transient "caging" of particles on cooling, are unable to provide sufficiently detailed information about correlated motion and dynamical heterogeneity. Here, we study a four-point, time-dependent density...

Studies on variable swirl intake system for DI diesel engine using computational fluid dynamics

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Jebamani Rathnaraj David

2008-01-01

Full Text Available It is known that a helical port is more effective than a tangential port to attain the required swirl ratio with minimum sacrifice in the volumetric efficiency. The swirl port is designed for lesser swirl ratio to reduce emissions at higher speeds. But this condition increases the air fuel mixing time and particulate smoke emissions at lower speeds. Optimum swirl ratio is necessary according to the engine operating condition for optimum combustion and emission reduction. Hence the engine needs variable swirl to enhance the combustion in the cylinder according to its operating conditions, for example at partial load or low speed condition it requires stronger swirl, while the air quantity is more important than the swirl under very high speed or full load and maximum torque conditions. The swirl and charging quantity can easily trade off and can be controlled by the opening of the valve. Hence in this study the steady flow rig experiment is used to evaluate the swirl of a helical intake port design for different operating conditions. The variable swirl plate set up of the W06DTIE2 engine is used to experimentally study the swirl variation for different openings of the valve. The sliding of the swirl plate results in the variation of the area of inlet port entry. Therefore in this study a swirl optimized combustion system varying according to the operating conditions by a variable swirl plate mechanism is studied experimentally and compared with the computational fluid dynamics predictions. In this study the fluent computational fluid dynamics code has been used to evaluate the flow in the port-cylinder system of a DI diesel engine in a steady flow rig. The computational grid is generated directly from 3-D CAD data and in cylinder flow simulations, with inflow boundary conditions from experimental measurements, are made using the fluent computational fluid dynamics code. The results are in very good agreement with experimental results.

Dynamical zeta functions for piecewise monotone maps of the interval

CERN Document Server

Ruelle, David

2004-01-01

Consider a space M, a map f:M\\to M, and a function g:M \\to {\\mathbb C}. The formal power series \\zeta (z) = \\exp \\sum ^\\infty _{m=1} \\frac {z^m}{m} \\sum _{x \\in \\mathrm {Fix}\\,f^m} \\prod ^{m-1}_{k=0} g (f^kx) yields an example of a dynamical zeta function. Such functions have unexpected analytic properties and interesting relations to the theory of dynamical systems, statistical mechanics, and the spectral theory of certain operators (transfer operators). The first part of this monograph presents a general introduction to this subject. The second part is a detailed study of the zeta functions associated with piecewise monotone maps of the interval [0,1]. In particular, Ruelle gives a proof of a generalized form of the Baladi-Keller theorem relating the poles of \\zeta (z) and the eigenvalues of the transfer operator. He also proves a theorem expressing the largest eigenvalue of the transfer operator in terms of the ergodic properties of (M,f,g).

Multiscale simulations of patchy particle systems combining Molecular Dynamics, Path Sampling and Green's Function Reaction Dynamics

Science.gov (United States)

Bolhuis, Peter

Important reaction-diffusion processes, such as biochemical networks in living cells, or self-assembling soft matter, span many orders in length and time scales. In these systems, the reactants' spatial dynamics at mesoscopic length and time scales of microns and seconds is coupled to the reactions between the molecules at microscopic length and time scales of nanometers and milliseconds. This wide range of length and time scales makes these systems notoriously difficult to simulate. While mean-field rate equations cannot describe such processes, the mesoscopic Green's Function Reaction Dynamics (GFRD) method enables efficient simulation at the particle level provided the microscopic dynamics can be integrated out. Yet, many processes exhibit non-trivial microscopic dynamics that can qualitatively change the macroscopic behavior, calling for an atomistic, microscopic description. The recently developed multiscale Molecular Dynamics Green's Function Reaction Dynamics (MD-GFRD) approach combines GFRD for simulating the system at the mesocopic scale where particles are far apart, with microscopic Molecular (or Brownian) Dynamics, for simulating the system at the microscopic scale where reactants are in close proximity. The association and dissociation of particles are treated with rare event path sampling techniques. I will illustrate the efficiency of this method for patchy particle systems. Replacing the microscopic regime with a Markov State Model avoids the microscopic regime completely. The MSM is then pre-computed using advanced path-sampling techniques such as multistate transition interface sampling. I illustrate this approach on patchy particle systems that show multiple modes of binding. MD-GFRD is generic, and can be used to efficiently simulate reaction-diffusion systems at the particle level, including the orientational dynamics, opening up the possibility for large-scale simulations of e.g. protein signaling networks.

Dynamic prediction of cumulative incidence functions by direct binomial regression.

Science.gov (United States)

Grand, Mia K; de Witte, Theo J M; Putter, Hein

2018-03-25

In recent years there have been a series of advances in the field of dynamic prediction. Among those is the development of methods for dynamic prediction of the cumulative incidence function in a competing risk setting. These models enable the predictions to be updated as time progresses and more information becomes available, for example when a patient comes back for a follow-up visit after completing a year of treatment, the risk of death, and adverse events may have changed since treatment initiation. One approach to model the cumulative incidence function in competing risks is by direct binomial regression, where right censoring of the event times is handled by inverse probability of censoring weights. We extend the approach by combining it with landmarking to enable dynamic prediction of the cumulative incidence function. The proposed models are very flexible, as they allow the covariates to have complex time-varying effects, and we illustrate how to investigate possible time-varying structures using Wald tests. The models are fitted using generalized estimating equations. The method is applied to bone marrow transplant data and the performance is investigated in a simulation study. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

An optimal strategy for functional mapping of dynamic trait loci.

Science.gov (United States)

Jin, Tianbo; Li, Jiahan; Guo, Ying; Zhou, Xiaojing; Yang, Runqing; Wu, Rongling

2010-02-01

As an emerging powerful approach for mapping quantitative trait loci (QTLs) responsible for dynamic traits, functional mapping models the time-dependent mean vector with biologically meaningful equations and are likely to generate biologically relevant and interpretable results. Given the autocorrelation nature of a dynamic trait, functional mapping needs the implementation of the models for the structure of the covariance matrix. In this article, we have provided a comprehensive set of approaches for modelling the covariance structure and incorporated each of these approaches into the framework of functional mapping. The Bayesian information criterion (BIC) values are used as a model selection criterion to choose the optimal combination of the submodels for the mean vector and covariance structure. In an example for leaf age growth from a rice molecular genetic project, the best submodel combination was found between the Gaussian model for the correlation structure, power equation of order 1 for the variance and the power curve for the mean vector. Under this combination, several significant QTLs for leaf age growth trajectories were detected on different chromosomes. Our model can be well used to study the genetic architecture of dynamic traits of agricultural values.

Crossing safety barriers: influence of children's morphological and functional variables.

Science.gov (United States)

Cordovil, Rita; Vieira, Filomena; Barreiros, João

2012-05-01

Thirty-three children between 3 and 6 years of age were asked to climb four different types of safety barriers. Morphological and functional variables of the children, which were expected to influence climbing or passing through skills, were collected. The influence of those variables on children's success rate and time to cross was tested. No barrier offered a total restraining efficacy. The horizontal bars barrier was crossed by 97% of the children. In the group of children that succeeded in crossing the four barriers, mean time to cross the most difficult barrier was 15 s. Age was the best predictor for success in crossing most barriers but morphology and strength were important predictors of time to cross. The influence of anthropometric variables in time to cross was dependent upon the characteristics of the barrier. A good design of safety barriers should consider children's age, morphology and strength. Copyright © 2011 Elsevier Ltd and The Ergonomics Society. All rights reserved.

Natural Poisson structures of nonlinear plasma dynamics

International Nuclear Information System (INIS)

Kaufman, A.N.

1982-01-01

Hamiltonian field theories, for models of nonlinear plasma dynamics, require a Poisson bracket structure for functionals of the field variables. These are presented, applied, and derived for several sets of field variables: coherent waves, incoherent waves, particle distributions, and multifluid electrodynamics. Parametric coupling of waves and plasma yields concise expressions for ponderomotive effects (in kinetic and fluid models) and for induced scattering. (Auth.)

Natural Poisson structures of nonlinear plasma dynamics

International Nuclear Information System (INIS)

Kaufman, A.N.

1982-06-01

Hamiltonian field theories, for models of nonlinear plasma dynamics, require a Poisson bracket structure for functionals of the field variables. These are presented, applied, and derived for several sets of field variables: coherent waves, incoherent waves, particle distributions, and multifluid electrodynamics. Parametric coupling of waves and plasma yields concise expressions for ponderomotive effects (in kinetic and fluid models) and for induced scattering

A Nonlinear Mixed Effects Approach for Modeling the Cell-To-Cell Variability of Mig1 Dynamics in Yeast.

Directory of Open Access Journals (Sweden)

Joachim Almquist

Full Text Available The last decade has seen a rapid development of experimental techniques that allow data collection from individual cells. These techniques have enabled the discovery and characterization of variability within a population of genetically identical cells. Nonlinear mixed effects (NLME modeling is an established framework for studying variability between individuals in a population, frequently used in pharmacokinetics and pharmacodynamics, but its potential for studies of cell-to-cell variability in molecular cell biology is yet to be exploited. Here we take advantage of this novel application of NLME modeling to study cell-to-cell variability in the dynamic behavior of the yeast transcription repressor Mig1. In particular, we investigate a recently discovered phenomenon where Mig1 during a short and transient period exits the nucleus when cells experience a shift from high to intermediate levels of extracellular glucose. A phenomenological model based on ordinary differential equations describing the transient dynamics of nuclear Mig1 is introduced, and according to the NLME methodology the parameters of this model are in turn modeled by a multivariate probability distribution. Using time-lapse microscopy data from nearly 200 cells, we estimate this parameter distribution according to the approach of maximizing the population likelihood. Based on the estimated distribution, parameter values for individual cells are furthermore characterized and the resulting Mig1 dynamics are compared to the single cell times-series data. The proposed NLME framework is also compared to the intuitive but limited standard two-stage (STS approach. We demonstrate that the latter may overestimate variabilities by up to almost five fold. Finally, Monte Carlo simulations of the inferred population model are used to predict the distribution of key characteristics of the Mig1 transient response. We find that with decreasing levels of post-shift glucose, the transient

Soliton interactions and Bäcklund transformation for a (2+1)-dimensional variable-coefficient modified Kadomtsev-Petviashvili equation in fluid dynamics

Science.gov (United States)

Xiao, Zi-Jian; Tian, Bo; Sun, Yan

2018-01-01

In this paper, we investigate a (2+1)-dimensional variable-coefficient modified Kadomtsev-Petviashvili (mKP) equation in fluid dynamics. With the binary Bell-polynomial and an auxiliary function, bilinear forms for the equation are constructed. Based on the bilinear forms, multi-soliton solutions and Bell-polynomial-type Bäcklund transformation for such an equation are obtained through the symbolic computation. Soliton interactions are presented. Based on the graphic analysis, Parametric conditions for the existence of the shock waves, elevation solitons and depression solitons are given, and it is shown that under the condition of keeping the wave vectors invariable, the change of α(t) and β(t) can lead to the change of the solitonic velocities, but the shape of each soliton remains unchanged, where α(t) and β(t) are the variable coefficients in the equation. Oblique elastic interactions can exist between the (i) two shock waves, (ii) two elevation solitons, and (iii) elevation and depression solitons. However, oblique interactions between (i) shock waves and elevation solitons, (ii) shock waves and depression solitons are inelastic.

Challenges in microbial ecology: Building predictive understanding of community function and dynamics

DEFF Research Database (Denmark)

Widder, Stefanie; Allen, Rosalind J.; Pfeiffer, Thomas

2016-01-01

The importance of microbial communities (MCs) cannot be overstated. MCs underpin the biogeochemical cycles of the earth's soil, oceans and the atmosphere, and perform ecosystem functions that impact plants, animals and humans. Yet our ability to predict and manage the function of these highly...... complex, dynamically changing communities is limited. Building predictive models that link MC composition to function is a key emerging challenge in microbial ecology. Here, we argue that addressing this challenge requires close coordination of experimental data collection and method development...... is needed to achieve significant progress in our understanding of MC dynamics and function, and we make specific practical suggestions as to how this could be achieved....

A Variable Interval Rescheduling Strategy for Dynamic Flexible Job Shop Scheduling Problem by Improved Genetic Algorithm

Directory of Open Access Journals (Sweden)

Lei Wang

2017-01-01

Full Text Available In real-world manufacturing systems, production scheduling systems are often implemented under random or dynamic events like machine failure, unexpected processing times, stochastic arrival of the urgent orders, cancellation of the orders, and so on. These dynamic events will lead the initial scheduling scheme to be nonoptimal and/or infeasible. Hence, appropriate dynamic rescheduling approaches are needed to overcome the dynamic events. In this paper, we propose a dynamic rescheduling method based on variable interval rescheduling strategy (VIRS to deal with the dynamic flexible job shop scheduling problem considering machine failure, urgent job arrival, and job damage as disruptions. On the other hand, an improved genetic algorithm (GA is proposed for minimizing makespan. In our improved GA, a mix of random initialization population by combining initialization machine and initialization operation with random initialization is designed for generating high-quality initial population. In addition, the elitist strategy (ES and improved population diversity strategy (IPDS are used to avoid falling into the local optimal solution. Experimental results for static and several dynamic events in the FJSP show that our method is feasible and effective.

Soils in transition : dynamics and functioning of fungi

NARCIS (Netherlands)

Wal, Annemieke van der

2007-01-01

The focus of this thesis is on the dynamics and functions of saprotrophic soil fungi during conversion from an arable land into a natural ecosystem (heathland) and to asses their effects on soil ecosystem processes. Chapter 2 describes that fungal biomass in abandoned arable land is not increasing

Observer variability of lung function measurements in 2-6-yr-old children

DEFF Research Database (Denmark)

Klug, B; Nielsen, K G; Bisgaard, H

2000-01-01

by the interrupter technique measurements in young children are subject to influence by the observer, and the random variability between observers appears to be particularly great for respiratory resistance assessed by the interrupter technique. The authors suggest that the between-observer variability should......The aim of this study was to assess the within-observer and between-observer variability of lung function measurements in children aged 2-6 yrs. Two observers examined 22 asthmatic children independently according to a predefined protocol. Each observer obtained duplicate measurements...... observers. The ratio SDw between observers/mean SDw within observers was 0.94, 1.25, 1.35 and 2.86 for Xrs,5, Rrs,5, sRaw and Rint, respectively, indicating greater between-observer variability of the latter. The systematic difference between observers assessed by the difference between observer means...

Nonlinear Dynamic Models in Advanced Life Support

Science.gov (United States)

Jones, Harry

2002-01-01

To facilitate analysis, ALS systems are often assumed to be linear and time invariant, but they usually have important nonlinear and dynamic aspects. Nonlinear dynamic behavior can be caused by time varying inputs, changes in system parameters, nonlinear system functions, closed loop feedback delays, and limits on buffer storage or processing rates. Dynamic models are usually cataloged according to the number of state variables. The simplest dynamic models are linear, using only integration, multiplication, addition, and subtraction of the state variables. A general linear model with only two state variables can produce all the possible dynamic behavior of linear systems with many state variables, including stability, oscillation, or exponential growth and decay. Linear systems can be described using mathematical analysis. Nonlinear dynamics can be fully explored only by computer simulations of models. Unexpected behavior is produced by simple models having only two or three state variables with simple mathematical relations between them. Closed loop feedback delays are a major source of system instability. Exceeding limits on buffer storage or processing rates forces systems to change operating mode. Different equilibrium points may be reached from different initial conditions. Instead of one stable equilibrium point, the system may have several equilibrium points, oscillate at different frequencies, or even behave chaotically, depending on the system inputs and initial conditions. The frequency spectrum of an output oscillation may contain harmonics and the sums and differences of input frequencies, but it may also contain a stable limit cycle oscillation not related to input frequencies. We must investigate the nonlinear dynamic aspects of advanced life support systems to understand and counter undesirable behavior.

Dynamics with infinitely many derivatives: variable coefficient equations

International Nuclear Information System (INIS)

Barnaby, Neil; Kamran, Niky

2008-01-01

Infinite order differential equations have come to play an increasingly significant role in theoretical physics. Field theories with infinitely many derivatives are ubiquitous in string field theory and have attracted interest recently also from cosmologists. Crucial to any application is a firm understanding of the mathematical structure of infinite order partial differential equations. In our previous work we developed a formalism to study the initial value problem for linear infinite order equations with constant coefficients. Our approach relied on the use of a contour integral representation for the functions under consideration. In many applications, including the study of cosmological perturbations in nonlocal inflation, one must solve linearized partial differential equations about some time-dependent background. This typically leads to variable coefficient equations, in which case the contour integral methods employed previously become inappropriate. In this paper we develop the theory of a particular class of linear infinite order partial differential equations with variable coefficients. Our formalism is particularly well suited to the types of equations that arise in nonlocal cosmological perturbation theory. As an example to illustrate our formalism we compute the leading corrections to the scalar field perturbations in p-adic inflation and show explicitly that these are small on large scales.

A predictability study of Lorenz's 28-variable model as a dynamical system

Science.gov (United States)

Krishnamurthy, V.

1993-01-01

The dynamics of error growth in a two-layer nonlinear quasi-geostrophic model has been studied to gain an understanding of the mathematical theory of atmospheric predictability. The growth of random errors of varying initial magnitudes has been studied, and the relation between this classical approach and the concepts of the nonlinear dynamical systems theory has been explored. The local and global growths of random errors have been expressed partly in terms of the properties of an error ellipsoid and the Liapunov exponents determined by linear error dynamics. The local growth of small errors is initially governed by several modes of the evolving error ellipsoid but soon becomes dominated by the longest axis. The average global growth of small errors is exponential with a growth rate consistent with the largest Liapunov exponent. The duration of the exponential growth phase depends on the initial magnitude of the errors. The subsequent large errors undergo a nonlinear growth with a steadily decreasing growth rate and attain saturation that defines the limit of predictability. The degree of chaos and the largest Liapunov exponent show considerable variation with change in the forcing, which implies that the time variation in the external forcing can introduce variable character to the predictability.

A comprehensive approach to handle the dynamics of customer’s needs in Quality Function Deployment based on linguistic variables

Directory of Open Access Journals (Sweden)

Zohreh Bostaki

2014-04-01

Full Text Available In the contexture of a customer-driven goods or service design process, a well-timed update of customer’s requirements may not only serve as a necessity indicator to observe how things change over time, but also it incorporates the firms a better ground to interoperate different strategies to meet the future needs of its customer. This paper proposes a systematic methodology to deal with the customer needs’ dynamics, in terms of their relative weights, in the QFD. Compared with previous research, the contribution of this paper is fourfold. First, it applies some linguistic variables to get preferences of customers and experts to determine the relative importance of customer requirements (CRs and the relationships between customer requirements and engineering characteristics (ECs. Second, it proposes the implementation of a forecasting technique. Third, it describes more comprehensively on how future uncertainty in the weights of customer’s needs could be estimated and transmitted into the design attributes. Fourth, it proposes the implementation of a quantitative approach, which takes into account the decision maker’s attitude towards risk to optimize the QFD decision making analysis. Finally, a real-world application of QFD is provided to demonstrate the practical applicability of the proposed methodology.

A fast chaos-based image encryption scheme with a dynamic state variables selection mechanism

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Chen, Jun-xin; Zhu, Zhi-liang; Fu, Chong; Yu, Hai; Zhang, Li-bo

2015-03-01

In recent years, a variety of chaos-based image cryptosystems have been investigated to meet the increasing demand for real-time secure image transmission. Most of them are based on permutation-diffusion architecture, in which permutation and diffusion are two independent procedures with fixed control parameters. This property results in two flaws. (1) At least two chaotic state variables are required for encrypting one plain pixel, in permutation and diffusion stages respectively. Chaotic state variables produced with high computation complexity are not sufficiently used. (2) The key stream solely depends on the secret key, and hence the cryptosystem is vulnerable against known/chosen-plaintext attacks. In this paper, a fast chaos-based image encryption scheme with a dynamic state variables selection mechanism is proposed to enhance the security and promote the efficiency of chaos-based image cryptosystems. Experimental simulations and extensive cryptanalysis have been carried out and the results prove the superior security and high efficiency of the scheme.

Variability of the autoregulation index decreases after removing the effect of the very low frequency band

NARCIS (Netherlands)

Elting, J. W.; Maurits, N. M.; Aries, M. J. H.

Dynamic cerebral autoregulation (dCA) estimates show large between and within subject variability. Sources of variability include low coherence and influence of CO2 in the very low frequency (VLF) band, where dCA is active. This may lead to unreliable transfer function and autoregulation index (ARI)

Individual Differences in Dynamic Functional Brain Connectivity across the Human Lifespan.

Directory of Open Access Journals (Sweden)

Elizabeth N Davison

2016-11-01

Full Text Available Individual differences in brain functional networks may be related to complex personal identifiers, including health, age, and ability. Dynamic network theory has been used to identify properties of dynamic brain function from fMRI data, but the majority of analyses and findings remain at the level of the group. Here, we apply hypergraph analysis, a method from dynamic network theory, to quantify individual differences in brain functional dynamics. Using a summary metric derived from the hypergraph formalism-hypergraph cardinality-we investigate individual variations in two separate, complementary data sets. The first data set ("multi-task" consists of 77 individuals engaging in four consecutive cognitive tasks. We observe that hypergraph cardinality exhibits variation across individuals while remaining consistent within individuals between tasks; moreover, the analysis of one of the memory tasks revealed a marginally significant correspondence between hypergraph cardinality and age. This finding motivated a similar analysis of the second data set ("age-memory", in which 95 individuals, aged 18-75, performed a memory task with a similar structure to the multi-task memory task. With the increased age range in the age-memory data set, the correlation between hypergraph cardinality and age correspondence becomes significant. We discuss these results in the context of the well-known finding linking age with network structure, and suggest that hypergraph analysis should serve as a useful tool in furthering our understanding of the dynamic network structure of the brain.

Dynamics of the cosmological and Newton’s constant

International Nuclear Information System (INIS)

Smolin, Lee

2016-01-01

A modification of general relativity is presented in which Newton’s constant, G, and the cosmological constant, Λ, become a conjugate pair of dynamical variables. These are functions of a global time, hence the theory is presented in the framework of shape dynamics, which trades many-fingered time for a local scale invariance and an overall reparametrization of the global time. As a result, due to the fact that these global dynamical variables are canonically conjugate, the field equations are consistent. The theory predicts a relationship with no free parameters between the rates of change of Newton’s constant and the cosmological constant, in terms of the spatial average of the matter Lagrangian density. (paper)

Effects of climate variability and functional changes on carbon cycling in a temperate deciduous forest

DEFF Research Database (Denmark)

Wu, Jian

and the fundamental processes at work in this type of ecosystem. The major objectives of this study were to (1) evaluate to what extent and at what temporal scales, direct climatic variability and functional changes (e.g. changes in the structure or physiological properties) regulate the interannual variability (IAV....... In general, the ECB component datasets were consistent after the cross-checking. This, together with their characterized uncertainties, can be used in model data fusion studies. The sensitivity of the C fluxes to climatic variability was significantly higher at shorter than at longer time scales and changed...... seasonally. At the annual time scale, the IAV in net ecosystem exchange of CO2 (NEE) was mostly determined by changes in the ecosystem functional properties. This indicated that the processes controlling the function change need to be incorporated into the process-based ecosystem models. The process...

Extended Lagrangian Density Functional Tight-Binding Molecular Dynamics for Molecules and Solids

International Nuclear Information System (INIS)

Aradi, Balint; Frauenheim, Thomas

2015-01-01

A computationally fast quantum mechanical molecular dynamics scheme using an extended Lagrangian density functional tight-binding formulation has been developed and implemented in the DFTB+ electronic structure program package for simulations of solids and molecular systems. The scheme combines the computational speed of self-consistent density functional tight-binding theory with the efficiency and long-term accuracy of extended Lagrangian Born-Oppenheimer molecular dynamics. Furthermore, for systems without self-consistent charge instabilities, only a single diagonalization or construction of the single-particle density matrix is required in each time step. The molecular dynamics simulation scheme can also be applied to a broad range of problems in materials science, chemistry, and biology

Extended Lagrangian Density Functional Tight-Binding Molecular Dynamics for Molecules and Solids.

Science.gov (United States)

Aradi, Bálint; Niklasson, Anders M N; Frauenheim, Thomas

2015-07-14

A computationally fast quantum mechanical molecular dynamics scheme using an extended Lagrangian density functional tight-binding formulation has been developed and implemented in the DFTB+ electronic structure program package for simulations of solids and molecular systems. The scheme combines the computational speed of self-consistent density functional tight-binding theory with the efficiency and long-term accuracy of extended Lagrangian Born-Oppenheimer molecular dynamics. For systems without self-consistent charge instabilities, only a single diagonalization or construction of the single-particle density matrix is required in each time step. The molecular dynamics simulation scheme can be applied to a broad range of problems in materials science, chemistry, and biology.

q-Power function over q-commuting variables and deformed XXX, XXZ chains

International Nuclear Information System (INIS)

Khoroshkin, S.M.; Stolin, A.A.; Tolstoy, V.N.

2001-01-01

Certain functional identifies for the Gauss q-power function of a sum of q-commuting variables are found. Then these identifies are used to obtain two-parameter twists of the quantum affine algebra U q (sl 2 ) and of the Yangian Y(sl 2 ). The corresponding deformed trigonometric and rational quantum R matrices, which then are used in the computation of deformed XXX and XXZ Hamiltonians [ru

A phenomenological approach to modeling chemical dynamics in nonlinear and two-dimensional spectroscopy.

Science.gov (United States)

Ramasesha, Krupa; De Marco, Luigi; Horning, Andrew D; Mandal, Aritra; Tokmakoff, Andrei

2012-04-07

We present an approach for calculating nonlinear spectroscopic observables, which overcomes the approximations inherent to current phenomenological models without requiring the computational cost of performing molecular dynamics simulations. The trajectory mapping method uses the semi-classical approximation to linear and nonlinear response functions, and calculates spectra from trajectories of the system's transition frequencies and transition dipole moments. It rests on identifying dynamical variables important to the problem, treating the dynamics of these variables stochastically, and then generating correlated trajectories of spectroscopic quantities by mapping from the dynamical variables. This approach allows one to describe non-Gaussian dynamics, correlated dynamics between variables of the system, and nonlinear relationships between spectroscopic variables of the system and the bath such as non-Condon effects. We illustrate the approach by applying it to three examples that are often not adequately treated by existing analytical models--the non-Condon effect in the nonlinear infrared spectra of water, non-Gaussian dynamics inherent to strongly hydrogen bonded systems, and chemical exchange processes in barrier crossing reactions. The methods described are generally applicable to nonlinear spectroscopy throughout the optical, infrared and terahertz regions.

Painleve Analysis and Darboux Transformation for a Variable-Coefficient Boussinesq System in Fluid Dynamics with Symbolic Computation

International Nuclear Information System (INIS)

Li Hongzhe; Tian Bo; Li Lili; Zhang Haiqiang

2010-01-01

The new soliton solutions for the variable-coefficient Boussinesq system, whose applications are seen in fluid dynamics, are studied in this paper with symbolic computation. First, the Painleve analysis is used to investigate its integrability properties. For the identified case we give, the Lax pair of the system is found, and then the Darboux transformation is constructed. At last, some new soliton solutions are presented via the Darboux method. Those solutions might be of some value in fluid dynamics. (general)

What variables influence the ability of an AFO to improve function and when are they indicated?

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Malas, Bryan S

2011-05-01

Children with spina bifida often present with functional deficits of the lower limb associated with neurosegmental lesion levels and require orthotic management. The most used orthosis for children with spina bifida is the ankle-foot orthosis (AFO). The AFO improves ambulation and reduces energy cost while walking. Despite the apparent benefits of using an AFO, limited evidence documents the influence of factors predicting the ability of an AFO to improve function and when they are indicated. These variables include AFO design, footwear, AFO-footwear combination, and data acquisition. When these variables are not adequately considered in clinical decision-making, there is a risk the AFO will be abandoned prematurely or the patient's stability, function, and safety compromised. The purposes of this study are to (1) describe the functional deficits based on lesion levels; (2) identify and describe variables that influence the ability of an AFO to control deformities; and (3) describe what variables are indicated for the AFO to control knee flexion during stance, hyperpronation, and valgus stress at the knee. A selective literature review was undertaken searching MEDLINE and Cochrane databases using terms related to "orthosis" and "spina bifida." Based on previous studies and gait analysis data, suggestions can be made regarding material selection/geometric configuration, sagittal alignment, footplate length, and trim lines of an AFO for reducing knee flexion, hyperpronation, and valgus stress at the knee. Further research is required to determine what variables allow an AFO to improve function.

Predator-prey dynamics driven by feedback between functionally diverse trophic levels.

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Katrin Tirok

Full Text Available Neglecting the naturally existing functional diversity of communities and the resulting potential to respond to altered conditions may strongly reduce the realism and predictive power of ecological models. We therefore propose and study a predator-prey model that describes mutual feedback via species shifts in both predator and prey, using a dynamic trait approach. Species compositions of the two trophic levels were described by mean functional traits--prey edibility and predator food-selectivity--and functional diversities by the variances. Altered edibility triggered shifts in food-selectivity so that consumers continuously respond to the present prey composition, and vice versa. This trait-mediated feedback mechanism resulted in a complex dynamic behavior with ongoing oscillations in the mean trait values, reflecting continuous reorganization of the trophic levels. The feedback was only possible if sufficient functional diversity was present in both trophic levels. Functional diversity was internally maintained on the prey level as no niche existed in our system, which was ideal under any composition of the predator level due to the trade-offs between edibility, growth and carrying capacity. The predators were only subject to one trade-off between food-selectivity and grazing ability and in the absence of immigration, one predator type became abundant, i.e., functional diversity declined to zero. In the lack of functional diversity the system showed the same dynamics as conventional models of predator-prey interactions ignoring the potential for shifts in species composition. This way, our study identified the crucial role of trade-offs and their shape in physiological and ecological traits for preserving diversity.

Inferring the physical connectivity of complex networks from their functional dynamics

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Holm Liisa

2010-05-01

Full Text Available Abstract Background Biological networks, such as protein-protein interactions, metabolic, signalling, transcription-regulatory networks and neural synapses, are representations of large-scale dynamic systems. The relationship between the network structure and functions remains one of the central problems in current multidisciplinary research. Significant progress has been made toward understanding the implication of topological features for the network dynamics and functions, especially in biological networks. Given observations of a network system's behaviours or measurements of its functional dynamics, what can we conclude of the details of physical connectivity of the underlying structure? Results We modelled the network system by employing a scale-free network of coupled phase oscillators. Pairwise phase coherence (PPC was calculated for all the pairs of oscillators to present functional dynamics induced by the system. At the regime of global incoherence, we observed a Significant pairwise synchronization only between two nodes that are physically connected. Right after the onset of global synchronization, disconnected nodes begin to oscillate in a correlated fashion and the PPC of two nodes, either connected or disconnected, depends on their degrees. Based on the observation of PPCs, we built a weighted network of synchronization (WNS, an all-to-all functionally connected network where each link is weighted by the PPC of two oscillators at the ends of the link. In the regime of strong coupling, we observed a Significant similarity in the organization of WNSs induced by systems sharing the same substrate network but different configurations of initial phases and intrinsic frequencies of oscillators. We reconstruct physical network from the WNS by choosing the links whose weights are higher than a given threshold. We observed an optimal reconstruction just before the onset of global synchronization. Finally, we correlated the topology of the

Fractional dynamic calculus and fractional dynamic equations on time scales

CERN Document Server

Georgiev, Svetlin G

2018-01-01

Pedagogically organized, this monograph introduces fractional calculus and fractional dynamic equations on time scales in relation to mathematical physics applications and problems. Beginning with the definitions of forward and backward jump operators, the book builds from Stefan Hilger’s basic theories on time scales and examines recent developments within the field of fractional calculus and fractional equations. Useful tools are provided for solving differential and integral equations as well as various problems involving special functions of mathematical physics and their extensions and generalizations in one and more variables. Much discussion is devoted to Riemann-Liouville fractional dynamic equations and Caputo fractional dynamic equations.  Intended for use in the field and designed for students without an extensive mathematical background, this book is suitable for graduate courses and researchers looking for an introduction to fractional dynamic calculus and equations on time scales. .

A Tensor Statistical Model for Quantifying Dynamic Functional Connectivity.

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Zhu, Yingying; Zhu, Xiaofeng; Kim, Minjeong; Yan, Jin; Wu, Guorong

2017-06-01

Functional connectivity (FC) has been widely investigated in many imaging-based neuroscience and clinical studies. Since functional Magnetic Resonance Image (MRI) signal is just an indirect reflection of brain activity, it is difficult to accurately quantify the FC strength only based on signal correlation. To address this limitation, we propose a learning-based tensor model to derive high sensitivity and specificity connectome biomarkers at the individual level from resting-state fMRI images. First, we propose a learning-based approach to estimate the intrinsic functional connectivity. In addition to the low level region-to-region signal correlation, latent module-to-module connection is also estimated and used to provide high level heuristics for measuring connectivity strength. Furthermore, sparsity constraint is employed to automatically remove the spurious connections, thus alleviating the issue of searching for optimal threshold. Second, we integrate our learning-based approach with the sliding-window technique to further reveal the dynamics of functional connectivity. Specifically, we stack the functional connectivity matrix within each sliding window and form a 3D tensor where the third dimension denotes for time. Then we obtain dynamic functional connectivity (dFC) for each individual subject by simultaneously estimating the within-sliding-window functional connectivity and characterizing the across-sliding-window temporal dynamics. Third, in order to enhance the robustness of the connectome patterns extracted from dFC, we extend the individual-based 3D tensors to a population-based 4D tensor (with the fourth dimension stands for the training subjects) and learn the statistics of connectome patterns via 4D tensor analysis. Since our 4D tensor model jointly (1) optimizes dFC for each training subject and (2) captures the principle connectome patterns, our statistical model gains more statistical power of representing new subject than current state

A stochastic fractional dynamics model of space-time variability of rain

Science.gov (United States)

Kundu, Prasun K.; Travis, James E.

2013-09-01

varies in space and time in a highly irregular manner and is described naturally in terms of a stochastic process. A characteristic feature of rainfall statistics is that they depend strongly on the space-time scales over which rain data are averaged. A spectral model of precipitation has been developed based on a stochastic differential equation of fractional order for the point rain rate, which allows a concise description of the second moment statistics of rain at any prescribed space-time averaging scale. The model is thus capable of providing a unified description of the statistics of both radar and rain gauge data. The underlying dynamical equation can be expressed in terms of space-time derivatives of fractional orders that are adjusted together with other model parameters to fit the data. The form of the resulting spectrum gives the model adequate flexibility to capture the subtle interplay between the spatial and temporal scales of variability of rain but strongly constrains the predicted statistical behavior as a function of the averaging length and time scales. We test the model with radar and gauge data collected contemporaneously at the NASA TRMM ground validation sites located near Melbourne, Florida and on the Kwajalein Atoll, Marshall Islands in the tropical Pacific. We estimate the parameters by tuning them to fit the second moment statistics of radar data at the smaller spatiotemporal scales. The model predictions are then found to fit the second moment statistics of the gauge data reasonably well at these scales without any further adjustment.

Local dynamic stability and variability of gait are associated with fall history in elderly subjects.

Science.gov (United States)

Toebes, Marcel J P; Hoozemans, Marco J M; Furrer, Regula; Dekker, Joost; van Dieën, Jaap H

2012-07-01

Gait parameters that can be measured with simple instrumentation may hold promise for identifying individuals at risk of falling. Increased variability of gait is associated with increased risk of falling, but research on additional parameters indicates that local dynamic stability (LDS) of gait may also be a predictor of fall risk. The objective of the present study was to assess the association between gait variability, LDS of gait and fall history in a large sample of elderly subjects. Subjects were recruited and tested at a large national fair. One hundred and thirty four elderly, aged 50-75, who were able to walk without aids on a treadmill, agreed to participate. After subjects walked on a treadmill, LDS (higher values indicate more instability) and variability parameters were calculated from accelerometer signals (trunk worn). Fall history was obtained by self-report of falls in the past 12 months. Gait variability and short-term LDS were, individually and combined, positively associated with fall history. In conclusion, both increased gait variability and increased short-term LDS are possible risk factors for falling in the elderly. Copyright © 2012 Elsevier B.V. All rights reserved.

Dynamic Sensor Management Algorithm Based on Improved Efficacy Function

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TANG Shujuan

2016-01-01

Full Text Available A dynamic sensor management algorithm based on improved efficacy function is proposed to solve the multi-target and multi-sensory management problem. The tracking task precision requirements (TPR, target priority and sensor use cost were considered to establish the efficacy function by weighted sum the normalized value of the three factors. The dynamic sensor management algorithm was accomplished through control the diversities of the desired covariance matrix (DCM and the filtering covariance matrix (FCM. The DCM was preassigned in terms of TPR and the FCM was obtained by the centralized sequential Kalman filtering algorithm. The simulation results prove that the proposed method could meet the requirements of desired tracking precision and adjust sensor selection according to target priority and cost of sensor source usage. This makes sensor management scheme more reasonable and effective.

Differences in dynamic and static functional connectivity between young and elderly healthy adults

Energy Technology Data Exchange (ETDEWEB)

Park, Ji Eun; Jung, Seung Chai; Ryu, Kyeoung Hwa; Oh, Joo Young; Kim, Ho Sung; Choi, Choong-Gon; Kim, Sang Joon; Shim, Woo Hyun [University of Ulsan College of Medicine, Asan Medical Center, Department of Radiology and Research Institute of Radiology, Songpa-Gu, Seoul (Korea, Republic of)

2017-08-15

Brain connectivity is highly dynamic, but functional connectivity (FC) studies using resting-state functional magnetic resonance imaging (rs-fMRI) assume it to be static. This study assessed differences in dynamic FC between young healthy adults (YH) and elderly healthy adults (EH) compared to static FC. Using rs-fMRI data from 12 YH and 31 EH, FC was assessed in six functional regions (subcortical, auditory [AUD], sensorimotor [SM], visuospatial [VS], cognitive control [CC], and default mode network [DMN]). Static FC was calculated as Fisher's z-transformed correlation coefficient. The sliding time window correlation (window size 30 s, step size 3 s) was applied for dynamic FC, and the standard deviation across sliding windows was calculated. Differences in static and dynamic FC between EH and YH were calculated and compared by region. EH showed decreased static FC in the subcortical, CC, and DMN regions (FDR corrected p = 0.0013; 74 regions), with no regions showing static FC higher than that in YH. EH showed increased dynamic FC in the subcortical, CC, and DMN regions, whereas decreased dynamic FC in CC and DMN regions (p < 0.01). However, the regions showing differences between EH and YH did not overlap between static and dynamic FC. Dynamic FC exhibited differences from static FC in EH and YH, mainly in regions involved in cognitive control and the DMN. Altered dynamic FC demonstrated both qualitatively and quantitatively distinct patterns of transient brain activity and needs to be studied as an imaging biomarker in the aging process. (orig.)

Binary codes with impulse autocorrelation functions for dynamic experiments

International Nuclear Information System (INIS)

Corran, E.R.; Cummins, J.D.

1962-09-01

A series of binary codes exist which have autocorrelation functions approximating to an impulse function. Signals whose behaviour in time can be expressed by such codes have spectra which are 'whiter' over a limited bandwidth and for a finite time than signals from a white noise generator. These codes are used to determine system dynamic responses using the correlation technique. Programmes have been written to compute codes of arbitrary length and to compute 'cyclic' autocorrelation and cross-correlation functions. Complete listings of these programmes are given, and a code of 1019 bits is presented. (author)

Non-Random Variability in Functional Composition of Coral Reef Fish Communities along an Environmental Gradient.

Science.gov (United States)

Plass-Johnson, Jeremiah G; Taylor, Marc H; Husain, Aidah A A; Teichberg, Mirta C; Ferse, Sebastian C A

2016-01-01

Changes in the coral reef complex can affect predator-prey relationships, resource availability and niche utilisation in the associated fish community, which may be reflected in decreased stability of the functional traits present in a community. This is because particular traits may be favoured by a changing environment, or by habitat degradation. Furthermore, other traits can be selected against because degradation can relax the association between fishes and benthic habitat. We characterised six important ecological traits for fish species occurring at seven sites across a disturbed coral reef archipelago in Indonesia, where reefs have been exposed to eutrophication and destructive fishing practices for decades. Functional diversity was assessed using two complementary indices (FRic and RaoQ) and correlated to important environmental factors (live coral cover and rugosity, representing local reef health, and distance from shore, representing a cross-shelf environmental gradient). Indices were examined for both a change in their mean, as well as temporal (short-term; hours) and spatial (cross-shelf) variability, to assess whether fish-habitat association became relaxed along with habitat degradation. Furthermore, variability in individual traits was examined to identify the traits that are most affected by habitat change. Increases in the general reef health indicators, live coral cover and rugosity (correlated with distance from the mainland), were associated with decreases in the variability of functional diversity and with community-level changes in the abundance of several traits (notably home range size, maximum length, microalgae, detritus and small invertebrate feeding and reproductive turnover). A decrease in coral cover increased variability of RaoQ while rugosity and distance both inversely affected variability of FRic; however, averages for these indices did not reveal patterns associated with the environment. These results suggest that increased

Power maximization of variable-speed variable-pitch wind turbines using passive adaptive neural fault tolerant control

Science.gov (United States)

Habibi, Hamed; Rahimi Nohooji, Hamed; Howard, Ian

2017-09-01

Power maximization has always been a practical consideration in wind turbines. The question of how to address optimal power capture, especially when the system dynamics are nonlinear and the actuators are subject to unknown faults, is significant. This paper studies the control methodology for variable-speed variable-pitch wind turbines including the effects of uncertain nonlinear dynamics, system fault uncertainties, and unknown external disturbances. The nonlinear model of the wind turbine is presented, and the problem of maximizing extracted energy is formulated by designing the optimal desired states. With the known system, a model-based nonlinear controller is designed; then, to handle uncertainties, the unknown nonlinearities of the wind turbine are estimated by utilizing radial basis function neural networks. The adaptive neural fault tolerant control is designed passively to be robust on model uncertainties, disturbances including wind speed and model noises, and completely unknown actuator faults including generator torque and pitch actuator torque. The Lyapunov direct method is employed to prove that the closed-loop system is uniformly bounded. Simulation studies are performed to verify the effectiveness of the proposed method.

Relative effects of precipitation variability and warming on tallgrass prairie ecosystem function

Directory of Open Access Journals (Sweden)

P. A. Fay

2011-10-01

Full Text Available Precipitation and temperature drive many aspects of terrestrial ecosystem function. Climate change scenarios predict increasing precipitation variability and temperature, and long term experiments are required to evaluate the ecosystem consequences of interannual climate variation, increased growing season (intra-annual rainfall variability, and warming. We present results from an experiment applying increased growing season rainfall variability and year round warming in native tallgrass prairie. During ten years of study, total growing season rainfall varied 2-fold, and we found ~50–200% interannual variability in plant growth and aboveground net primary productivity (ANPP, leaf carbon assimilation (A_CO2, and soil CO₂ efflux (J_CO2 despite only ~40% variation in mean volumetric soil water content (0–15 cm, Θ₁₅. Interannual variation in soil moisture was thus amplified in most measures of ecosystem response. Differences between years in Θ₁₅ explained the greatest portion (14–52% of the variation in these processes. Experimentally increased intra-annual season rainfall variability doubled the amplitude of intra-annual soil moisture variation and reduced Θ₁₅ by 15%, causing most ecosystem processes to decrease 8–40% in some or all years with increased rainfall variability compared to ambient rainfall timing, suggesting reduced ecosystem rainfall use efficiency. Warming treatments increased soil temperature at 5 cm depth, particularly during spring, fall, and winter. Warming advanced canopy green up in spring, increased winter J_CO2, and reduced summer J_CO2 and forb ANPP, suggesting that the effects of warming differed in cooler versus warmer parts of the year. We conclude that (1 major ecosystem processes in this grassland may be substantially altered by predicted changes in

HYPERDIRE HYPERgeometric functions DIfferential REduction. Mathematica-based packages for the differential reduction of generalized hypergeometric functions. Lauricella function F{sub C} of three variables

Energy Technology Data Exchange (ETDEWEB)

Bytev, Vladimir V. [Hamburg Univ. (Germany). 2. Inst. fuer Theoretische Physik; Joint Institute for Nuclear Research, Dubna (Russian Federation); Kniehl, Bernd A. [Hamburg Univ. (Germany). 2. Inst. fuer Theoretische Physik

2016-12-15

We present a further extension of the HYPERDIRE project, which is devoted to the creation of a set of Mathematica-based program packages for manipulations with Horn-type hypergeometric functions on the basis of differential equations. Specifically, we present the implementation of the differential reduction for the Lauricella function F{sub C} of three variables.

Integrating factors and conservation theorems for Hamilton's canonical equations of motion of variable mass nonholonomic nonconservative dynamical systems

Institute of Scientific and Technical Information of China (English)

李仁杰; 乔永芬; 刘洋

2002-01-01

We present a general approach to the construction of conservation laws for variable mass nonholonomic noncon-servative systems. First, we give the definition of integrating factors, and we study in detail the necessary conditionsfor the existence of the conserved quantities. Then, we establish the conservation theorem and its inverse theorem forHamilton's canonical equations of motion of variable mass nonholonomic nonconservative dynamical systems. Finally,we give an example to illustrate the application of the results.

Spatial variability in intertidal macroalgal assemblages on the North Portuguese coast: consistence between species and functional group approaches

Science.gov (United States)

Veiga, P.; Rubal, M.; Vieira, R.; Arenas, F.; Sousa-Pinto, I.

2013-03-01

Natural assemblages are variable in space and time; therefore, quantification of their variability is imperative to identify relevant scales for investigating natural or anthropogenic processes shaping these assemblages. We studied the variability of intertidal macroalgal assemblages on the North Portuguese coast, considering three spatial scales (from metres to 10 s of kilometres) following a hierarchical design. We tested the hypotheses that (1) spatial pattern will be invariant at all the studied scales and (2) spatial variability of macroalgal assemblages obtained by using species will be consistent with that obtained using functional groups. This was done considering as univariate variables: total biomass and number of taxa as well as biomass of the most important species and functional groups and as multivariate variables the structure of macroalgal assemblages, both considering species and functional groups. Most of the univariate results confirmed the first hypothesis except for the total number of taxa and foliose macroalgae that showed significant variability at the scale of site and area, respectively. In contrast, when multivariate patterns were examined, the first hypothesis was rejected except at the scale of 10 s of kilometres. Both uni- and multivariate results indicated that variation was larger at the smallest scale, and thus, small-scale processes seem to have more effect on spatial variability patterns. Macroalgal assemblages, both considering species and functional groups as surrogate, showed consistent spatial patterns, and therefore, the second hypothesis was confirmed. Consequently, functional groups may be considered a reliable biological surrogate to study changes on macroalgal assemblages at least along the investigated Portuguese coastline.

Elements of mathematics functions of a real variable : elementary theory

CERN Document Server

Bourbaki, Nicolas

2004-01-01

This book is an English translation of the last French edition of Bourbaki’s Fonctions d'une Variable Réelle. The first chapter is devoted to derivatives, Taylor expansions, the finite increments theorem, convex functions. In the second chapter, primitives and integrals (on arbitrary intervals) are studied, as well as their dependence with respect to parameters. Classical functions (exponential, logarithmic, circular and inverse circular) are investigated in the third chapter. The fourth chapter gives a thorough treatment of differential equations (existence and unicity properties of solutions, approximate solutions, dependence on parameters) and of systems of linear differential equations. The local study of functions (comparison relations, asymptotic expansions) is treated in chapter V, with an appendix on Hardy fields. The theory of generalized Taylor expansions and the Euler-MacLaurin formula are presented in the sixth chapter, and applied in the last one to the study of the Gamma function on the real ...

Collective Variables in Apphed Linguistics Research

OpenAIRE

ヘンスリー, ジョール; HENSLEY, Joel

2011-01-01

This paper focuses on the key dynamic(al)systems theory concept of collective variables as it relates to developmental research in applied linguistics. Dynamic(al) systems theory is becoming prevalent in linguistic research and in the past two decades has jumped to the forefront of cutting edge in the field. One key concept in dynamic(al) systems theory is that of collective variables. In order to help properly orient this concept in the field of applied linguistics, this paper discusses the ...

Annual dynamics of daylight variability and contrast a simulation-based approach to quantifying visual effects in architecture

CERN Document Server

Rockcastle, Siobhan

2013-01-01

Daylight is a dynamic source of illumination in architectural space, creating diverse and ephemeral configurations of light and shadow within the built environment. Perceptual qualities of daylight, such as contrast and temporal variability, are essential to our understanding of both material and visual effects in architecture. Although spatial contrast and light variability are fundamental to the visual experience of architecture, architects still rely primarily on intuition to evaluate their designs because there are few metrics that address these factors. Through an analysis of contemporary

Task-related Functional Connectivity Dynamics in a Block-designed Visual Experiment

Directory of Open Access Journals (Sweden)

Xin eDi

2015-09-01

Full Text Available Studying task modulations of brain connectivity using functional magnetic resonance imaging (fMRI is critical to understand brain functions that support cognitive and affective processes. Existing methods such as psychophysiological interaction (PPI and dynamic causal modelling (DCM usually implicitly assume that the connectivity patterns are stable over a block-designed task with identical stimuli. However, this assumption lacks empirical verification on high-temporal resolution fMRI data with reliable data-driven analysis methods. The present study performed a detailed examination of dynamic changes of functional connectivity (FC in a simple block-designed visual checkerboard experiment with a sub-second sampling rate (TR = 0.645 s by estimating time-varying correlation coefficient (TVCC between BOLD responses of different brain regions. We observed reliable task-related FC changes (i.e., FCs were transiently decreased after task onset and went back to the baseline afterward among several visual regions of the bilateral middle occipital gyrus (MOG and the bilateral fusiform gyrus (FuG. Importantly, only the FCs between higher visual regions (MOG and lower visual regions (FuG exhibited such dynamic patterns. The results suggested that simply assuming a sustained FC during a task block may be insufficient to capture distinct task-related FC changes. The investigation of FC dynamics in tasks could improve our understanding of condition shifts and the coordination between different activated brain regions.

Collective variables method in relativistic theory

International Nuclear Information System (INIS)

Shurgaya, A.V.

1983-01-01

Classical theory of N-component field is considered. The method of collective variables accurately accounting for conservation laws proceeding from invariance theory under homogeneous Lorentz group is developed within the frames of generalized hamiltonian dynamics. Hyperboloids are invariant surfaces Under the homogeneous Lorentz group. Proceeding from this, field transformation is introduced, and the surface is parametrized so that generators of the homogeneous Lorentz group do not include components dependent on interaction and their effect on the field function is reduced to geometrical. The interaction is completely included in the expression for the energy-momentum vector of the system which is a dynamical value. Gauge is chosen where parameters of four-dimensional translations and their canonically-conjugated pulses are non-physical and thus phase space is determined by parameters of the homogeneous Lorentz group, field function and their canonically-conjugated pulses. So it is managed to accurately account for conservation laws proceeding from the requirement of lorentz-invariance

Anthropometric, cardiovascular and functional variables as indicators of health related physical fitness in university professors

Directory of Open Access Journals (Sweden)

Osvaldo Costa Moreira

Full Text Available AbstractObjective To verify the behavior of anthropometric, cardiovascular and functional variables as indicators of health-related physical fitness in university professors and perform a comparison of these variables between sexes.Materials and methods We conducted an observational epidemiological cross-sectional study in 145 professors (45.86 ± 9.7 years, 103 men (71.03%, which were evaluated by measuring heart rate (HR and systolic (SBP and diastolic (DBP pressure at rest, body weight, height, body mass index (BMI, body fat percentage (BF%, handgrip strength (HGS, flexibility and cardiorespiratory fitness (CRF. We proceeded to the descriptive analysis, Student t-test for comparison between sexes and multiple regression analysis to verify the association between the variables analyzed. It was adopted a significance level of p < 0.05.Results The sex affected all variables. Women had better levels of BMI, flexibility, SBP and DBP. The BF% and CRF were associated with SBP and BMI in both sexes.Conclusion The behavior of anthropometric, cardiovascular and functional variables indicated unsatisfactory values for flexibility, HGS and BMI, with the worst levels among men. Furthermore, the variables that showed better association with HRPF were BF% and CRF.

Dynamic Biological Functioning Important for Simulating and Stabilizing Ocean Biogeochemistry

Science.gov (United States)

Buchanan, P. J.; Matear, R. J.; Chase, Z.; Phipps, S. J.; Bindoff, N. L.

2018-04-01

The biogeochemistry of the ocean exerts a strong influence on the climate by modulating atmospheric greenhouse gases. In turn, ocean biogeochemistry depends on numerous physical and biological processes that change over space and time. Accurately simulating these processes is fundamental for accurately simulating the ocean's role within the climate. However, our simulation of these processes is often simplistic, despite a growing understanding of underlying biological dynamics. Here we explore how new parameterizations of biological processes affect simulated biogeochemical properties in a global ocean model. We combine 6 different physical realizations with 6 different biogeochemical parameterizations (36 unique ocean states). The biogeochemical parameterizations, all previously published, aim to more accurately represent the response of ocean biology to changing physical conditions. We make three major findings. First, oxygen, carbon, alkalinity, and phosphate fields are more sensitive to changes in the ocean's physical state. Only nitrate is more sensitive to changes in biological processes, and we suggest that assessment protocols for ocean biogeochemical models formally include the marine nitrogen cycle to assess their performance. Second, we show that dynamic variations in the production, remineralization, and stoichiometry of organic matter in response to changing environmental conditions benefit the simulation of ocean biogeochemistry. Third, dynamic biological functioning reduces the sensitivity of biogeochemical properties to physical change. Carbon and nitrogen inventories were 50% and 20% less sensitive to physical changes, respectively, in simulations that incorporated dynamic biological functioning. These results highlight the importance of a dynamic biology for ocean properties and climate.

Understanding Digital Learning from the Perspective of Systems Dynamics

Science.gov (United States)

Kok, Ayse

2009-01-01

The System Dynamics approach can be seen as a new way of understanding dynamical phenonema (natural, physical, biological, etc.) that occur in our daily lives taking into consideration not only single pairs of cause-effect variables, but the functioning of the system as a whole. This approach also provides the students with a new understanding in…

Variability of Neuronal Responses: Types and Functional Significance in Neuroplasticity and Neural Darwinism.

Science.gov (United States)

Chervyakov, Alexander V; Sinitsyn, Dmitry O; Piradov, Michael A

2016-01-01

HIGHLIGHTS We suggest classifying variability of neuronal responses as follows: false (associated with a lack of knowledge about the influential factors), "genuine harmful" (noise), "genuine neutral" (synonyms, repeats), and "genuine useful" (the basis of neuroplasticity and learning).The genuine neutral variability is considered in terms of the phenomenon of degeneracy.Of particular importance is the genuine useful variability that is considered as a potential basis for neuroplasticity and learning. This type of variability is considered in terms of the neural Darwinism theory. In many cases, neural signals detected under the same external experimental conditions significantly change from trial to trial. The variability phenomenon, which complicates extraction of reproducible results and is ignored in many studies by averaging, has attracted attention of researchers in recent years. In this paper, we classify possible types of variability based on its functional significance and describe features of each type. We describe the key adaptive significance of variability at the neural network level and the degeneracy phenomenon that may be important for learning processes in connection with the principle of neuronal group selection.

Chaotic behaviour of a pendulum with variable length

Energy Technology Data Exchange (ETDEWEB)

Bartuccelli, M; Christiansen, P L; Muto, V; Soerensen, M P; Pedersen, N F

1987-08-01

The Melnikov function for the prediction of Smale horseshoe chaos is applied to a driven damped pendulum with variable length. Depending on the parameters, it is shown that this dynamical system undertakes heteroclinic bifurcations which are the source of the unstable chaotic motion. The analytical results are illustrated by new numerical simulations. Furthermore, using the averaging theorem, the stability of the subharmonics is studied.

Livelihood profiling and sensitivity of livelihood strategies to land cover dynamics and agricultural variability

Science.gov (United States)

Berchoux, Tristan; Hutton, Craig; Watmough, Gary; Amoako Johnson, Fiifi; Atkinson, Peter

2017-04-01

With population increase and the urbanisation of rural areas, land scarcity is one of the biggest challenges now faced by communities in agrarian societies. At the household level, loss of land can be due to physical processes such as erosion, to social constraints such as inheritance, or to financial constraints such as loan reimbursement or the need of cash. For rural households, whose livelihoods are mainly based on agriculture, a decrease in the area of land cultivated can have significant consequences on their livelihood strategies, thus on their livelihood outcomes. However, it is still unclear how changes in cultivated area and agricultural productivity influence households' livelihood systems, including community capitals and households' livelihood strategies. This study aims to answer this gap by combining together earth observation from space, national census and participatory qualitative data into a community-wise analysis of the relationships between land cover dynamics, variability in agricultural production and livelihood activities. Its overarching aim is to investigate how land cover dynamics relates to changes in livelihood strategies and livelihood capitals. The study demonstrates that a change in land cover influences livelihood activities differently depending on the community capitals that households have access to. One significant aspect of integrating land dynamics with livelihood activities is its capacity to provide insights on the relationships between climate, agriculture, livelihood dynamics and rural development. More broadly, it gives policymakers new methods to characterise livelihood dynamics, thus to monitor some of the key Sustainable Development Goals: food security (SDG2), employment dynamics (SDG8), inequalities (SDG10) and sustainability of communities (SDG11).

Simulation of Protein Structure, Dynamics and Function in Organic Media

National Research Council Canada - National Science Library

Daggett, Valerie

1998-01-01

The overall goal of our ONR-sponsored research is to pursue realistic molecular modeling strudies pertinnent to the related properties of protein stability, dynamics, structure, function, and folding in aqueous solution...

Stochastic modeling and simulation of reaction-diffusion system with Hill function dynamics.

Science.gov (United States)

Chen, Minghan; Li, Fei; Wang, Shuo; Cao, Young

2017-03-14

Stochastic simulation of reaction-diffusion systems presents great challenges for spatiotemporal biological modeling and simulation. One widely used framework for stochastic simulation of reaction-diffusion systems is reaction diffusion master equation (RDME). Previous studies have discovered that for the RDME, when discretization size approaches zero, reaction time for bimolecular reactions in high dimensional domains tends to infinity. In this paper, we demonstrate that in the 1D domain, highly nonlinear reaction dynamics given by Hill function may also have dramatic change when discretization size is smaller than a critical value. Moreover, we discuss methods to avoid this problem: smoothing over space, fixed length smoothing over space and a hybrid method. Our analysis reveals that the switch-like Hill dynamics reduces to a linear function of discretization size when the discretization size is small enough. The three proposed methods could correctly (under certain precision) simulate Hill function dynamics in the microscopic RDME system.

Effects of a hydrotherapy programme on symbolic and complexity dynamics of heart rate variability and aerobic capacity in fibromyalgia patients.

Science.gov (United States)

Zamunér, Antonio Roberto; Andrade, Carolina P; Forti, Meire; Marchi, Andrea; Milan, Juliana; Avila, Mariana Arias; Catai, Aparecida Maria; Porta, Alberto; Silva, Ester

2015-01-01

To evaluate the effects of a hydrotherapy programme on aerobic capacity and linear and non-linear dynamics of heart rate variability (HRV) in women with fibromyalgia syndrome (FMS). 20 women with FMS and 20 healthy controls (HC) took part in the study. The FMS group was evaluated at baseline and after a 16-week hydrotherapy programme. All participants underwent cardiopulmonary exercise testing on a cycle ergometer and RR intervals recording in supine and standing positions. The HRV was analysed by linear and non-linear methods. The current level of pain, the tender points, the pressure pain threshold and the impact of FMS on quality of life were assessed. The FMS patients presented higher cardiac sympathetic modulation, lower vagal modulation and lower complexity of HRV in supine position than the HC. Only the HC decreased the complexity indices of HRV during orthostatic stimulus. After a 16-week hydrotherapy programme, the FMS patients increased aerobic capacity, decreased cardiac sympathetic modulation and increased vagal modulation and complexity dynamics of HRV in supine. The FMS patients also improved their cardiac autonomic adjustments to the orthostatic stimulus. Associations between improvements in non-linear dynamics of HRV and improvements in pain and in the impact of FMS on quality of life were found. A 16-week hydrotherapy programme proved to be effective in ameliorating symptoms, aerobic functional capacity and cardiac autonomic control in FMS patients. Improvements in the non-linear dynamics of HRV were related to improvements in pain and in the impact of FMS on quality of life.

Functional magnetic resonance imaging phase synchronization as a measure of dynamic functional connectivity.

Science.gov (United States)

Glerean, Enrico; Salmi, Juha; Lahnakoski, Juha M; Jääskeläinen, Iiro P; Sams, Mikko

2012-01-01

Functional brain activity and connectivity have been studied by calculating intersubject and seed-based correlations of hemodynamic data acquired with functional magnetic resonance imaging (fMRI). To inspect temporal dynamics, these correlation measures have been calculated over sliding time windows with necessary restrictions on the length of the temporal window that compromises the temporal resolution. Here, we show that it is possible to increase temporal resolution by using instantaneous phase synchronization (PS) as a measure of dynamic (time-varying) functional connectivity. We applied PS on an fMRI dataset obtained while 12 healthy volunteers watched a feature film. Narrow frequency band (0.04-0.07 Hz) was used in the PS analysis to avoid artifactual results. We defined three metrics for computing time-varying functional connectivity and time-varying intersubject reliability based on estimation of instantaneous PS across the subjects: (1) seed-based PS, (2) intersubject PS, and (3) intersubject seed-based PS. Our findings show that these PS-based metrics yield results consistent with both seed-based correlation and intersubject correlation methods when inspected over the whole time series, but provide an important advantage of maximal single-TR temporal resolution. These metrics can be applied both in studies with complex naturalistic stimuli (e.g., watching a movie or listening to music in the MRI scanner) and more controlled (e.g., event-related or blocked design) paradigms. A MATLAB toolbox FUNPSY ( http://becs.aalto.fi/bml/software.html ) is openly available for using these metrics in fMRI data analysis.

Dynamic analysis of elastic rubber tired car wheel breaking under variable normal load

Science.gov (United States)

Fedotov, A. I.; Zedgenizov, V. G.; Ovchinnikova, N. I.

2017-10-01

The purpose of the paper is to analyze the dynamics of the braking of the wheel under normal load variations. The paper uses a mathematical simulation method according to which the calculation model of an object as a mechanical system is associated with a dynamically equivalent schematic structure of the automatic control. Transfer function tool analyzing structural and technical characteristics of an object as well as force disturbances were used. It was proved that the analysis of dynamic characteristics of the wheel subjected to external force disturbances has to take into account amplitude and phase-frequency characteristics. Normal load variations impact car wheel braking subjected to disturbances. The closer slip to the critical point is, the higher the impact is. In the super-critical area, load variations cause fast wheel blocking.

Dynamic functional connectivity analysis reveals transient states of dysconnectivity in schizophrenia

Directory of Open Access Journals (Sweden)

E. Damaraju

2014-01-01

Full Text Available Schizophrenia is a psychotic disorder characterized by functional dysconnectivity or abnormal integration between distant brain regions. Recent functional imaging studies have implicated large-scale thalamo-cortical connectivity as being disrupted in patients. However, observed connectivity differences in schizophrenia have been inconsistent between studies, with reports of hyperconnectivity and hypoconnectivity between the same brain regions. Using resting state eyes-closed functional imaging and independent component analysis on a multi-site data that included 151 schizophrenia patients and 163 age- and gender matched healthy controls, we decomposed the functional brain data into 100 components and identified 47 as functionally relevant intrinsic connectivity networks. We subsequently evaluated group differences in functional network connectivity, both in a static sense, computed as the pairwise Pearson correlations between the full network time courses (5.4 minutes in length, and a dynamic sense, computed using sliding windows (44 s in length and k-means clustering to characterize five discrete functional connectivity states. Static connectivity analysis revealed that compared to healthy controls, patients show significantly stronger connectivity, i.e., hyperconnectivity, between the thalamus and sensory networks (auditory, motor and visual, as well as reduced connectivity (hypoconnectivity between sensory networks from all modalities. Dynamic analysis suggests that (1, on average, schizophrenia patients spend much less time than healthy controls in states typified by strong, large-scale connectivity, and (2, that abnormal connectivity patterns are more pronounced during these connectivity states. In particular, states exhibiting cortical–subcortical antagonism (anti-correlations and strong positive connectivity between sensory networks are those that show the group differences of thalamic hyperconnectivity and sensory hypoconnectivity

Adaptive functioning in pediatric epilepsy: contributions of seizure-related variables and parental anxiety.

Science.gov (United States)

Kerne, Valerie; Chapieski, Lynn

2015-02-01

Young people with epilepsy are less likely to achieve the level of independence attained by their peers. We examined the seizure-related variables that placed a group of 97 pediatric patients with intractable seizures at risk for poor adaptive functioning. Analyses evaluated both the direct effects of the medical variables and indirect effects that were mediated through increased parental anxiety about their child's epilepsy. Higher numbers of anticonvulsants, presence of seizures that secondarily generalize, longer duration of seizure disorder, and younger age at onset were all identified as risk factors for poor adaptive functioning. Depending on the specific behavioral domain of adaptive functioning, the effects were sometimes direct and sometimes indirect. Lower levels of parental education and positive family history of seizures were associated with higher levels of parental anxiety. Interventions that target parental anxiety about seizures may mitigate the deleterious effects of epilepsy on social development. Copyright © 2014 Elsevier Inc. All rights reserved.

Research of thermal dynamic characteristics for variable load single screw refrigeration compressor with different capacity control mechanism

International Nuclear Information System (INIS)

Wang, Zengli; Wang, Zhenbo; Wang, Jun; Jiang, Wenchun; Feng, Quanke

2017-01-01

Highlights: • Theoretical models of SSRC under part-load condition have been established. • The experiment of SSRC performance under part-load condition was conducted. • Thermal dynamic characteristic of SSRC under part-load condition was gained. • Economy and reliability of SSRC under part-load condition was analyzed. - Abstract: In the single screw refrigeration compressor (SSRC), the capacity control mechanism is normally employed to meet the actual required cooling capacity under different load conditions. In this paper, theoretical calculation models describing the working process of the SSRC with the single slide valve capacity control mechanism (SVCCM) and SSRC with the frequency conversion regulating mechanism (FCRM) are established to research the thermal dynamic characteristics for variable load SSRC under part-load conditions. Experimental investigation on a SSRC under part-load conditions is also carried out to verify the theoretical calculation models. By using these validated models, the thermodynamic performances and dynamic characteristics of the SSRC with different capacity control mechanism under part-load conditions have been analyzed and compared. Through the comparison, the economical efficiency and reliability of the SSRC with different capacity control mechanism were obtained. All of these works can provide the basis for the later optimization design for the variable load single screw refrigeration compressor.

Dynamic function MR of the cervical vertebral column

International Nuclear Information System (INIS)

Naegele, M.; Woell, B.; Reiser, M.; Koch, W.; Kaden, B.

1992-01-01

To obtain functional studies of the cervical spine, a device has been developed which allows MRI examinations to be carried out in five different degrees of flexion. T 1 and T 2 * weighted FFE sequences were used. Dynamic functional MRI was performed on 5 normals and 31 patients (5 disc herniation, 4 whiplash injuries, 6 spinal canal stenoses, 14 laminectomies and spinal fusions, 2 rheumatoid arthritis). The relationship of the spinal cord to the bony and ligamentous components in different degrees of flexion was particularly well shown in whiplash injury, spinal stenosis and postoperative situations. (orig.) [de

Dynamic behaviour of non-uniform Bernoulli-Euler beams subjected ...

African Journals Online (AJOL)

This paper investigates the dynamics behaviour of non-uniform Bernoulli-Euler beams subjected to concentrated loads ravelling at variable velocities. The solution technique is based on the Generalized Galerkin Method and the use of the generating function of the Bessel function type. The results show that, for all the ...

Orthogonal functions, discrete variable representation, and generalized gauss quadratures

DEFF Research Database (Denmark)

Schneider, B. I.; Nygaard, Nicolai

2002-01-01

in the original representation. This has been exploited in bound-state, scattering, and time-dependent problems using the so-called, discrete variable representation (DVR). At the core of this approach is the mathematical three-term recursion relationship satisfied by the classical orthogonal functions......, the distinction between spectral and grid approaches becomes blurred. In fact, the two approaches can be related by a similarity transformation. By the exploitation of this idea, calculations can be considerably simplified by removing the need to compute difficult matrix elements of the Hamiltonian...... functions, this is not the case. However, they may be computed in a stable numerical fashion, via the recursion. In essence, this is an application of the well-known Lanczos recursion approach. Once the recursion coefficients are known, it is possible to compute the points and weights of quadratures on...

Grid Compatibility of Variable Speed Wind Turbines with Directly Coupled Synchronous Generator and Hydro-Dynamically Controlled Gearbox

Energy Technology Data Exchange (ETDEWEB)

Mueller, H.; Poeller, M. [DIgSILENT GmbH, 72810 Gomaringen (Germany); Basteck, A.; Tilscher, M.; Pfister, J. [Voith Turbo GmbH and Co. KG, 74564 Crailsheim (Germany)

2006-07-01

This paper analyzes grid integration aspects of a new type of variable-speed wind turbine, the directly coupled synchronous generator with hydro-dynamically controlled gearbox. In contrast to existing wind generators using synchronous generators, the generator of this concept is directly connected to the AC grid, without the application of any power electronics converter. Variable speed operation of the turbine is mechanically achieved by a gear box with continuously controllable variable gear box ratio. For this purpose, a detailed dynamic model of a 2 MW wind turbine with a Voith WinDrive has been implemented using the modelling environment of the simulation software DIgSILENT PowerFactory. For investigating grid compatibility aspects of this new wind generator concept, a model of a 50 MW wind farm, with typical layout, based on 25 wind turbines of the 2 MW-class has been analyzed. This paper focuses on the compatibility of the new concept with existing connection standards, such as the E.ON grid code. Of special interest are typical stability phenomena of synchronous generators, such as transient and oscillatory stability as well as power quality issues like voltage flicker. The results of stability studies are presented and possible advantages of the new concept with special focus on offshore applications are discussed.

On Ostrowski Type Inequalities for Functions of Two Variables with Bounded Variation

Directory of Open Access Journals (Sweden)

Hüseyin Budak

2016-10-01

Full Text Available In this paper, we establish a new generalization of Ostrowski type inequalities for functions of two independent variables with bounded variation and apply it for qubature formulae. Some connections with the rectangle, the midpoint and Simpson's rule are also given.

Toward Capturing Momentary Changes of Heart Rate Variability by a Dynamic Analysis Method.

Directory of Open Access Journals (Sweden)

Haoshi Zhang

Full Text Available The analysis of heart rate variability (HRV has been performed on long-term electrocardiography (ECG recordings (12~24 hours and short-term recordings (2~5 minutes, which may not capture momentary change of HRV. In this study, we present a new method to analyze the momentary HRV (mHRV. The ECG recordings were segmented into a series of overlapped HRV analysis windows with a window length of 5 minutes and different time increments. The performance of the proposed method in delineating the dynamics of momentary HRV measurement was evaluated with four commonly used time courses of HRV measures on both synthetic time series and real ECG recordings from human subjects and dogs. Our results showed that a smaller time increment could capture more dynamical information on transient changes. Considering a too short increment such as 10 s would cause the indented time courses of the four measures, a 1-min time increment (4-min overlapping was suggested in the analysis of mHRV in the study. ECG recordings from human subjects and dogs were used to further assess the effectiveness of the proposed method. The pilot study demonstrated that the proposed analysis of mHRV could provide more accurate assessment of the dynamical changes in cardiac activity than the conventional measures of HRV (without time overlapping. The proposed method may provide an efficient means in delineating the dynamics of momentary HRV and it would be worthy performing more investigations.

Abnormal rich club organization and functional brain dynamics in schizophrenia.

Science.gov (United States)

van den Heuvel, Martijn P; Sporns, Olaf; Collin, Guusje; Scheewe, Thomas; Mandl, René C W; Cahn, Wiepke; Goñi, Joaquín; Hulshoff Pol, Hilleke E; Kahn, René S

2013-08-01

The human brain forms a large-scale structural network of regions and interregional pathways. Recent studies have reported the existence of a selective set of highly central and interconnected hub regions that may play a crucial role in the brain's integrative processes, together forming a central backbone for global brain communication. Abnormal brain connectivity may have a key role in the pathophysiology of schizophrenia. To examine the structure of the rich club in schizophrenia and its role in global functional brain dynamics. Structural diffusion tensor imaging and resting-state functional magnetic resonance imaging were performed in patients with schizophrenia and matched healthy controls. Department of Psychiatry, Rudolf Magnus Institute of Neuroscience, University Medical Center Utrecht, Utrecht, the Netherlands. Forty-eight patients and 45 healthy controls participated in the study. An independent replication data set of 41 patients and 51 healthy controls was included to replicate and validate significant findings. MAIN OUTCOME(S) AND MEASURES: Measures of rich club organization, connectivity density of rich club connections and connections linking peripheral regions to brain hubs, measures of global brain network efficiency, and measures of coupling between brain structure and functional dynamics. Rich club organization between high-degree hub nodes was significantly affected in patients, together with a reduced density of rich club connections predominantly comprising the white matter pathways that link the midline frontal, parietal, and insular hub regions. This reduction in rich club density was found to be associated with lower levels of global communication capacity, a relationship that was absent for other white matter pathways. In addition, patients had an increase in the strength of structural connectivity-functional connectivity coupling. Our findings provide novel biological evidence that schizophrenia is characterized by a selective

Connection between Dynamically Derived Initial Mass Function Normalization and Stellar Population Parameters

NARCIS (Netherlands)

McDermid, Richard M.; Cappellari, Michele; Alatalo, Katherine; Bayet, Estelle; Blitz, Leo; Bois, Maxime; Bournaud, Frédéric; Bureau, Martin; Crocker, Alison F.; Davies, Roger L.; Davis, Timothy A.; de Zeeuw, P. T.; Duc, Pierre-Alain; Emsellem, Eric; Khochfar, Sadegh; Krajnović, Davor; Kuntschner, Harald; Morganti, Raffaella; Naab, Thorsten; Oosterloo, Tom; Sarzi, Marc; Scott, Nicholas; Serra, Paolo; Weijmans, Anne-Marie; Young, Lisa M.

We report on empirical trends between the dynamically determined stellar initial mass function (IMF) and stellar population properties for a complete, volume-limited sample of 260 early-type galaxies from the ATLAS3D project. We study trends between our dynamically derived IMF normalization αdyn ≡

Shedding Light on Protein Folding, Structural and Functional Dynamics by Single Molecule Studies

Directory of Open Access Journals (Sweden)

Krutika Bavishi

2014-11-01

Full Text Available The advent of advanced single molecule measurements unveiled a great wealth of dynamic information revolutionizing our understanding of protein dynamics and behavior in ways unattainable by conventional bulk assays. Equipped with the ability to record distribution of behaviors rather than the mean property of a population, single molecule measurements offer observation and quantification of the abundance, lifetime and function of multiple protein states. They also permit the direct observation of the transient and rarely populated intermediates in the energy landscape that are typically averaged out in non-synchronized ensemble measurements. Single molecule studies have thus provided novel insights about how the dynamic sampling of the free energy landscape dictates all aspects of protein behavior; from its folding to function. Here we will survey some of the state of the art contributions in deciphering mechanisms that underlie protein folding, structural and functional dynamics by single molecule fluorescence microscopy techniques. We will discuss a few selected examples highlighting the power of the emerging techniques and finally discuss the future improvements and directions.

Principal States of Dynamic Functional Connectivity Reveal the Link Between Resting-State and Task-State Brain: An fMRI Study.

Science.gov (United States)

Cheng, Lin; Zhu, Yang; Sun, Junfeng; Deng, Lifu; He, Naying; Yang, Yang; Ling, Huawei; Ayaz, Hasan; Fu, Yi; Tong, Shanbao

2018-01-25

Task-related reorganization of functional connectivity (FC) has been widely investigated. Under classic static FC analysis, brain networks under task and rest have been demonstrated a general similarity. However, brain activity and cognitive process are believed to be dynamic and adaptive. Since static FC inherently ignores the distinct temporal patterns between rest and task, dynamic FC may be more a suitable technique to characterize the brain's dynamic and adaptive activities. In this study, we adopted [Formula: see text]-means clustering to investigate task-related spatiotemporal reorganization of dynamic brain networks and hypothesized that dynamic FC would be able to reveal the link between resting-state and task-state brain organization, including broadly similar spatial patterns but distinct temporal patterns. In order to test this hypothesis, this study examined the dynamic FC in default-mode network (DMN) and motor-related network (MN) using Blood-Oxygenation-Level-Dependent (BOLD)-fMRI data from 26 healthy subjects during rest (REST) and a hand closing-and-opening (HCO) task. Two principal FC states in REST and one principal FC state in HCO were identified. The first principal FC state in REST was found similar to that in HCO, which appeared to represent intrinsic network architecture and validated the broadly similar spatial patterns between REST and HCO. However, the second FC principal state in REST with much shorter "dwell time" implied the transient functional relationship between DMN and MN during REST. In addition, a more frequent shifting between two principal FC states indicated that brain network dynamically maintained a "default mode" in the motor system during REST, whereas the presence of a single principal FC state and reduced FC variability implied a more temporally stable connectivity during HCO, validating the distinct temporal patterns between REST and HCO. Our results further demonstrated that dynamic FC analysis could offer unique

Magnetic field induced dynamical chaos.

Science.gov (United States)

Ray, Somrita; Baura, Alendu; Bag, Bidhan Chandra

2013-12-01

In this article, we have studied the dynamics of a particle having charge in the presence of a magnetic field. The motion of the particle is confined in the x-y plane under a two dimensional nonlinear potential. We have shown that constant magnetic field induced dynamical chaos is possible even for a force which is derived from a simple potential. For a given strength of the magnetic field, initial position, and velocity of the particle, the dynamics may be regular, but it may become chaotic when the field is time dependent. Chaotic dynamics is very often if the field is time dependent. Origin of chaos has been explored using the Hamiltonian function of the dynamics in terms of action and angle variables. Applicability of the present study has been discussed with a few examples.

Variable-angle epifluorescence microscopy characterizes protein dynamics in the vicinity of plasma membrane in plant cells.

Science.gov (United States)

Chen, Tong; Ji, Dongchao; Tian, Shiping

2018-03-14

The assembly of protein complexes and compositional lipid patterning act together to endow cells with the plasticity required to maintain compositional heterogeneity with respect to individual proteins. Hence, the applications for imaging protein localization and dynamics require high accuracy, particularly at high spatio-temporal level. We provided experimental data for the applications of Variable-Angle Epifluorescence Microscopy (VAEM) in dissecting protein dynamics in plant cells. The VAEM-based co-localization analysis took penetration depth and incident angle into consideration. Besides direct overlap of dual-color fluorescence signals, the co-localization analysis was carried out quantitatively in combination with the methodology for calculating puncta distance and protein proximity index. Besides, simultaneous VAEM tracking of cytoskeletal dynamics provided more insights into coordinated responses of actin filaments and microtubules. Moreover, lateral motility of membrane proteins was analyzed by calculating diffusion coefficients and kymograph analysis, which represented an alternative method for examining protein motility. The present study presented experimental evidence on illustrating the use of VAEM in tracking and dissecting protein dynamics, dissecting endosomal dynamics, cell structure assembly along with membrane microdomain and protein motility in intact plant cells.

Phase Structure and Dynamics of QCD–A Functional Perspective

International Nuclear Information System (INIS)

Strodthoff, Nils

2017-01-01

The understanding of the phase structure and the fundamental properties of QCD matter from its microscopic description requires appropriate first-principle approaches. Here I review the progress towards a quantitative first-principle continuum approach within the framework of the Functional Renormalization group established by the fQCD collaboration. I focus on recent quantitative results for quenched QCD and Yang-Mills in the vacuum before addressing the calculation of dynamical quantities such as spectral functions and transport coefficients in this framework. (paper)

The Functional Segregation and Integration Model: Mixture Model Representations of Consistent and Variable Group-Level Connectivity in fMRI

DEFF Research Database (Denmark)

Churchill, Nathan William; Madsen, Kristoffer Hougaard; Mørup, Morten

2016-01-01

flexibility: they only estimate segregated structure and do not model interregional functional connectivity, nor do they account for network variability across voxels or between subjects. To address these issues, this letter develops the functional segregation and integration model (FSIM). This extension......The brain consists of specialized cortical regions that exchange information between each other, reflecting a combination of segregated (local) and integrated (distributed) processes that define brain function. Functional magnetic resonance imaging (fMRI) is widely used to characterize...... brain regions where network expression predicts subject age in the experimental data. Thus, the FSIM is effective at summarizing functional connectivity structure in group-level fMRI, with applications in modeling the relationships between network variability and behavioral/demographic variables....

How mechanical context and feedback jointly determine the use of mechanical variables in length perception by dynamic touch

NARCIS (Netherlands)

Menger, Rudmer; Withagen, Rob

Earlier studies have revealed that both mechanical context and feedback determine what mechanical invariant is used to perceive length by dynamic touch. In the present article, the authors examined how these two factors jointly constrain the informational variable that is relied upon. Participants

How mechanical context and feedback jointly determine the use of mechanical variables in length perception by dynamic touch

NARCIS (Netherlands)

Menger, Rudmer; Withagen, Rob

2009-01-01

Earlier studies have revealed that both mechanical context and feedback determine what mechanical invariant is used to perceive length by dynamic touch. In the present article, the authors examined how these two factors jointly constrain the informational variable that is relied upon. Participants

Dynamical principles in neuroscience

International Nuclear Information System (INIS)

Rabinovich, Mikhail I.; Varona, Pablo; Selverston, Allen I.; Abarbanel, Henry D. I.

2006-01-01

Dynamical modeling of neural systems and brain functions has a history of success over the last half century. This includes, for example, the explanation and prediction of some features of neural rhythmic behaviors. Many interesting dynamical models of learning and memory based on physiological experiments have been suggested over the last two decades. Dynamical models even of consciousness now exist. Usually these models and results are based on traditional approaches and paradigms of nonlinear dynamics including dynamical chaos. Neural systems are, however, an unusual subject for nonlinear dynamics for several reasons: (i) Even the simplest neural network, with only a few neurons and synaptic connections, has an enormous number of variables and control parameters. These make neural systems adaptive and flexible, and are critical to their biological function. (ii) In contrast to traditional physical systems described by well-known basic principles, first principles governing the dynamics of neural systems are unknown. (iii) Many different neural systems exhibit similar dynamics despite having different architectures and different levels of complexity. (iv) The network architecture and connection strengths are usually not known in detail and therefore the dynamical analysis must, in some sense, be probabilistic. (v) Since nervous systems are able to organize behavior based on sensory inputs, the dynamical modeling of these systems has to explain the transformation of temporal information into combinatorial or combinatorial-temporal codes, and vice versa, for memory and recognition. In this review these problems are discussed in the context of addressing the stimulating questions: What can neuroscience learn from nonlinear dynamics, and what can nonlinear dynamics learn from neuroscience?

Dynamical principles in neuroscience

Science.gov (United States)

Rabinovich, Mikhail I.; Varona, Pablo; Selverston, Allen I.; Abarbanel, Henry D. I.

2006-10-01

Dynamical modeling of neural systems and brain functions has a history of success over the last half century. This includes, for example, the explanation and prediction of some features of neural rhythmic behaviors. Many interesting dynamical models of learning and memory based on physiological experiments have been suggested over the last two decades. Dynamical models even of consciousness now exist. Usually these models and results are based on traditional approaches and paradigms of nonlinear dynamics including dynamical chaos. Neural systems are, however, an unusual subject for nonlinear dynamics for several reasons: (i) Even the simplest neural network, with only a few neurons and synaptic connections, has an enormous number of variables and control parameters. These make neural systems adaptive and flexible, and are critical to their biological function. (ii) In contrast to traditional physical systems described by well-known basic principles, first principles governing the dynamics of neural systems are unknown. (iii) Many different neural systems exhibit similar dynamics despite having different architectures and different levels of complexity. (iv) The network architecture and connection strengths are usually not known in detail and therefore the dynamical analysis must, in some sense, be probabilistic. (v) Since nervous systems are able to organize behavior based on sensory inputs, the dynamical modeling of these systems has to explain the transformation of temporal information into combinatorial or combinatorial-temporal codes, and vice versa, for memory and recognition. In this review these problems are discussed in the context of addressing the stimulating questions: What can neuroscience learn from nonlinear dynamics, and what can nonlinear dynamics learn from neuroscience?

Pod systems: an equivariant ordinary differential equation approach to dynamical systems on a spatial domain

International Nuclear Information System (INIS)

Elmhirst, Toby; Stewart, Ian; Doebeli, Michael

2008-01-01

We present a class of systems of ordinary differential equations (ODEs), which we call 'pod systems', that offers a new perspective on dynamical systems defined on a spatial domain. Such systems are typically studied as partial differential equations, but pod systems bring the analytic techniques of ODE theory to bear on the problems, and are thus able to study behaviours and bifurcations that are not easily accessible to the standard methods. In particular, pod systems are specifically designed to study spatial dynamical systems that exhibit multi-modal solutions. A pod system is essentially a linear combination of parametrized functions in which the coefficients and parameters are variables whose dynamics are specified by a system of ODEs. That is, pod systems are concerned with the dynamics of functions of the form Ψ(s, t) = y 1 (t) φ(s; x 1 (t)) + ··· + y N (t) φ(s; x N (t)), where s in R n is the spatial variable and φ: R n × R d → R. The parameters x i in R d and coefficients y i in R are dynamic variables which evolve according to some system of ODEs, x-dot i = G i (x, y) and y-dot i = H i (x, y), for i = 1, ..., N. The dynamics of Ψ in function space can then be studied through the dynamics of the x and y in finite dimensions. A vital feature of pod systems is that the ODEs that specify the dynamics of the x and y variables are not arbitrary; restrictions on G i and H i are required to guarantee that the dynamics of Ψ in function space are well defined (that is, that trajectories are unique). One important restriction is symmetry in the ODEs which arises because Ψ is invariant under permutations of the indices of the (x i , y i ) pairs. However, this is not the whole story, and the primary goal of this paper is to determine the necessary structure of the ODEs explicitly to guarantee that the dynamics of Ψ are well defined

Improvement of a new rotation function for molecular replacement by designing new scoring functions and dynamic correlation coefficient

Science.gov (United States)

Jiang, Fan; Ding, Wei

2010-10-01

A previously published new rotation function has been improved by using a dynamic correlation coefficient as well as two new scoring functions of relative entropy and mean-square-residues to make the rotation function more robust and independent of a specific set of weights for scoring and ranking. The previously described new rotation function calculates the rotation function of molecular replacement by matching the search model directly with the Patterson vector map. The signal-to-noise ratio for the correct match was increased by averaging all the matching peaks. Several matching scores were employed to evaluate the goodness of matching. These matching scores were then combined into a single total score by optimizing a set of weights using the linear regression method. It was found that there exists an optimal set of weights that can be applied to the global rotation search and the correct solution can be ranked in the top 100 or less. However, this set of optimal weights in general is dependent on the search models and the crystal structures with different space groups and cell parameters. In this work, we try to solve this problem by designing a dynamic correlation coefficient. It is shown that the dynamic correlation coefficient works for a variety of space groups and cell parameters in the global search of rotation function. We also introduce two new matching scores: relative entropy and mean-square-residues. Last but not least, we discussed a valid method for the optimization of the adjustable parameters for matching vectors.

Improvement of a new rotation function for molecular replacement by designing new scoring functions and dynamic correlation coefficient

International Nuclear Information System (INIS)

Fan, Jiang; Wei, Ding

2010-01-01

A previously published new rotation function has been improved by using a dynamic correlation coefficient as well as two new scoring functions of relative entropy and mean-square-residues to make the rotation function more robust and independent of a specific set of weights for scoring and ranking. The previously described new rotation function calculates the rotation function of molecular replacement by matching the search model directly with the Patterson vector map. The signal-to-noise ratio for the correct match was increased by averaging all the matching peaks. Several matching scores were employed to evaluate the goodness of matching. These matching scores were then combined into a single total score by optimizing a set of weights using the linear regression method. It was found that there exists an optimal set of weights that can be applied to the global rotation search and the correct solution can be ranked in the top 100 or less. However, this set of optimal weights in general is dependent on the search models and the crystal structures with different space groups and cell parameters. In this work, we try to solve this problem by designing a dynamic correlation coefficient. It is shown that the dynamic correlation coefficient works for a variety of space groups and cell parameters in the global search of rotation function. We also introduce two new matching scores: relative entropy and mean-square-residues. Last but not least, we discussed a valid method for the optimization of the adjustable parameters for matching vectors. (condensed matter: structure, thermal and mechanical properties)

Interdecadal variability of winter precipitation in Southeast China

OpenAIRE

Zhang, L.; Zhu, X.; Fraedrich, K.; Sielmann, F.; Zhi, X.

2014-01-01

Interdecadal variability of observed winter precipitation in Southeast China (1961–2010) is characterized by the first empirical orthogonal function of the three-monthly Standardized Precipitation Index (SPI) subjected to a 9-year running mean. For interdecadal time scales the dominating spatial modes represent monopole features involving the Arctic Oscillation (AO) and the sea surface temperature (SST) anomalies. Dynamic composite analysis (based on NCEP/NCAR reanalyzes) reveals the followin...

Variable separation solutions for the Nizhnik-Novikov-Veselov equation via the extended tanh-function method

International Nuclear Information System (INIS)

Zhang Jiefang; Dai Chaoqing; Zong Fengde

2007-01-01

In this paper, with the variable separation approach and based on the general reduction theory, we successfully generalize this extended tanh-function method to obtain new types of variable separation solutions for the following Nizhnik-Novikov-Veselov (NNV) equation. Among the solutions, two solutions are new types of variable separation solutions, while the last solution is similar to the solution given by Darboux transformation in Hu et al 2003 Chin. Phys. Lett. 20 1413

Composition operators on function spaces

CERN Document Server

Singh, RK

1993-01-01

This volume of the Mathematics Studies presents work done on composition operators during the last 25 years. Composition operators form a simple but interesting class of operators having interactions with different branches of mathematics and mathematical physics. After an introduction, the book deals with these operators on Lp-spaces. This study is useful in measurable dynamics, ergodic theory, classical mechanics and Markov process. The composition operators on functional Banach spaces (including Hardy spaces) are studied in chapter III. This chapter makes contact with the theory of analytic functions of complex variables. Chapter IV presents a study of these operators on locally convex spaces of continuous functions making contact with topological dynamics. In the last chapter of the book some applications of composition operators in isometries, ergodic theory and dynamical systems are presented. An interesting interplay of algebra, topology, and analysis is displayed. This comprehensive and up-to-date stu...

Extended q -Gaussian and q -exponential distributions from gamma random variables

Science.gov (United States)

Budini, Adrián A.

2015-05-01

The family of q -Gaussian and q -exponential probability densities fit the statistical behavior of diverse complex self-similar nonequilibrium systems. These distributions, independently of the underlying dynamics, can rigorously be obtained by maximizing Tsallis "nonextensive" entropy under appropriate constraints, as well as from superstatistical models. In this paper we provide an alternative and complementary scheme for deriving these objects. We show that q -Gaussian and q -exponential random variables can always be expressed as a function of two statistically independent gamma random variables with the same scale parameter. Their shape index determines the complexity q parameter. This result also allows us to define an extended family of asymmetric q -Gaussian and modified q -exponential densities, which reduce to the standard ones when the shape parameters are the same. Furthermore, we demonstrate that a simple change of variables always allows relating any of these distributions with a beta stochastic variable. The extended distributions are applied in the statistical description of different complex dynamics such as log-return signals in financial markets and motion of point defects in a fluid flow.

Population dynamics in variable environments

CERN Document Server

Tuljapurkar, Shripad

1990-01-01

Demography relates observable facts about individuals to the dynamics of populations. If the dynamics are linear and do not change over time, the classical theory of Lotka (1907) and Leslie (1945) is the central tool of demography. This book addresses the situation when the assumption of constancy is dropped. In many practical situations, a population will display unpredictable variation over time in its vital rates, which must then be described in statistical terms. Most of this book is concerned with the theory of populations which are subject to random temporal changes in their vital rates, although other kinds of variation (e. g. , cyclical) are also dealt with. The central questions are: how does temporal variation work its way into a population's future, and how does it affect our interpretation of a population's past. The results here are directed at demographers of humans and at popula­ tion biologists. The uneven mathematical level is dictated by the material, but the book should be accessible to re...

Optimizing Multireservoir System Operating Policies Using Exogenous Hydrologic Variables

Science.gov (United States)

Pina, Jasson; Tilmant, Amaury; Côté, Pascal

2017-11-01

Stochastic dual dynamic programming (SDDP) is one of the few available algorithms to optimize the operating policies of large-scale hydropower systems. This paper presents a variant, called SDDPX, in which exogenous hydrologic variables, such as snow water equivalent and/or sea surface temperature, are included in the state space vector together with the traditional (endogenous) variables, i.e., past inflows. A reoptimization procedure is also proposed in which SDDPX-derived benefit-to-go functions are employed within a simulation carried out over the historical record of both the endogenous and exogenous hydrologic variables. In SDDPX, release policies are now a function of storages, past inflows, and relevant exogenous variables that potentially capture more complex hydrological processes than those found in traditional SDDP formulations. To illustrate the potential gain associated with the use of exogenous variables when operating a multireservoir system, the 3,137 MW hydropower system of Rio Tinto (RT) located in the Saguenay-Lac-St-Jean River Basin in Quebec (Canada) is used as a case study. The performance of the system is assessed for various combinations of hydrologic state variables, ranging from the simple lag-one autoregressive model to more complex formulations involving past inflows, snow water equivalent, and winter precipitation.

Integrating factors and conservation theorems for Hamilton‘s canonical equations of motion of variable mass nonholonmic nonconservative dynamical systems

Institute of Scientific and Technical Information of China (English)

李仁杰; 刘洋; 等

2002-01-01

We present a general approach to the construction of conservation laws for variable mass noholonmic nonconservative systems.First,we give the definition of integrating factors,and we study in detail the necessary conditions for the existence of the conserved quantities,Then,we establish the conservatioin theorem and its inverse theorem for Hamilton's canonical equations of motion of variable mass nonholonomic nonocnservative dynamical systems.Finally,we give an example to illustrate the application of the results.

Dynamic density functional theory of solid tumor growth: Preliminary models

Directory of Open Access Journals (Sweden)

Arnaud Chauviere

2012-03-01

Full Text Available Cancer is a disease that can be seen as a complex system whose dynamics and growth result from nonlinear processes coupled across wide ranges of spatio-temporal scales. The current mathematical modeling literature addresses issues at various scales but the development of theoretical methodologies capable of bridging gaps across scales needs further study. We present a new theoretical framework based on Dynamic Density Functional Theory (DDFT extended, for the first time, to the dynamics of living tissues by accounting for cell density correlations, different cell types, phenotypes and cell birth/death processes, in order to provide a biophysically consistent description of processes across the scales. We present an application of this approach to tumor growth.

THE COVARIATION FUNCTION FOR SYMMETRIC &ALPHA;-STABLE RANDOM VARIABLES WITH FINITE FIRST MOMENTS

Directory of Open Access Journals (Sweden)

Dedi Rosadi

2012-05-01

Full Text Available In this paper, we discuss a generalized dependence measure which is designed to measure dependence of two symmetric α-stable random variables with finite mean(1<α<=2 and contains the covariance function as the special case (when α=2. Weshortly discuss some basic properties of the function and consider several methods to estimate the function and further investigate the numerical properties of the estimatorusing the simulated data. We show how to apply this function to measure dependence of some stock returns on the composite index LQ45 in Indonesia Stock Exchange.

Continuous-variable quantum teleportation in bosonic structured environments

Energy Technology Data Exchange (ETDEWEB)

He Guangqiang; Zhang Jingtao; Zhu Jun; Zeng Guihua [State Key Laboratory of Advanced Optical Communication Systems and Networks, Department of Electronic Engineering, Shanghai Jiaotong University, Shanghai 200240 (China)

2011-09-15

The effects of dynamics of continuous-variable entanglement under the various kinds of environments on quantum teleportation are quantitatively investigated. Only under assumption of the weak system-reservoir interaction, the evolution of teleportation fidelity is analytically derived and is numerically plotted in terms of environment parameters including reservoir temperature and its spectral density, without Markovian and rotating wave approximations. We find that the fidelity of teleportation is a monotonically decreasing function for Markovian interaction in Ohmic-like environments, while it oscillates for non-Markovian ones. According to the dynamical laws of teleportation, teleportation with better performances can be implemented by selecting the appropriate time.

A Multi-Point Method Considering the Maximum Power Point Tracking Dynamic Process for Aerodynamic Optimization of Variable-Speed Wind Turbine Blades

Directory of Open Access Journals (Sweden)

Zhiqiang Yang

2016-05-01

Full Text Available Due to the dynamic process of maximum power point tracking (MPPT caused by turbulence and large rotor inertia, variable-speed wind turbines (VSWTs cannot maintain the optimal tip speed ratio (TSR from cut-in wind speed up to the rated speed. Therefore, in order to increase the total captured wind energy, the existing aerodynamic design for VSWT blades, which only focuses on performance improvement at a single TSR, needs to be improved to a multi-point design. In this paper, based on a closed-loop system of VSWTs, including turbulent wind, rotor, drive train and MPPT controller, the distribution of operational TSR and its description based on inflow wind energy are investigated. Moreover, a multi-point method considering the MPPT dynamic process for the aerodynamic optimization of VSWT blades is proposed. In the proposed method, the distribution of operational TSR is obtained through a dynamic simulation of the closed-loop system under a specific turbulent wind, and accordingly the multiple design TSRs and the corresponding weighting coefficients in the objective function are determined. Finally, using the blade of a National Renewable Energy Laboratory (NREL 1.5 MW wind turbine as the baseline, the proposed method is compared with the conventional single-point optimization method using the commercial software Bladed. Simulation results verify the effectiveness of the proposed method.

Dynamical topology and statistical properties of spatiotemporal chaos.

Science.gov (United States)

Zhuang, Quntao; Gao, Xun; Ouyang, Qi; Wang, Hongli

2012-12-01

For spatiotemporal chaos described by partial differential equations, there are generally locations where the dynamical variable achieves its local extremum or where the time partial derivative of the variable vanishes instantaneously. To a large extent, the location and movement of these topologically special points determine the qualitative structure of the disordered states. We analyze numerically statistical properties of the topologically special points in one-dimensional spatiotemporal chaos. The probability distribution functions for the number of point, the lifespan, and the distance covered during their lifetime are obtained from numerical simulations. Mathematically, we establish a probabilistic model to describe the dynamics of these topologically special points. In spite of the different definitions in different spatiotemporal chaos, the dynamics of these special points can be described in a uniform approach.

Exploring protein dynamics space: the dynasome as the missing link between protein structure and function.

Directory of Open Access Journals (Sweden)

Ulf Hensen

Full Text Available Proteins are usually described and classified according to amino acid sequence, structure or function. Here, we develop a minimally biased scheme to compare and classify proteins according to their internal mobility patterns. This approach is based on the notion that proteins not only fold into recurring structural motifs but might also be carrying out only a limited set of recurring mobility motifs. The complete set of these patterns, which we tentatively call the dynasome, spans a multi-dimensional space with axes, the dynasome descriptors, characterizing different aspects of protein dynamics. The unique dynamic fingerprint of each protein is represented as a vector in the dynasome space. The difference between any two vectors, consequently, gives a reliable measure of the difference between the corresponding protein dynamics. We characterize the properties of the dynasome by comparing the dynamics fingerprints obtained from molecular dynamics simulations of 112 proteins but our approach is, in principle, not restricted to any specific source of data of protein dynamics. We conclude that: 1. the dynasome consists of a continuum of proteins, rather than well separated classes. 2. For the majority of proteins we observe strong correlations between structure and dynamics. 3. Proteins with similar function carry out similar dynamics, which suggests a new method to improve protein function annotation based on protein dynamics.

Functional Apparent Moduli (FAMs) as Predictors of Oral Implant Osseointegration Dynamics

OpenAIRE

Chang, Po-Chun; Seol, Yang-Jo; Kikuchi, Noboru; Goldstein, Steven A.; Giannobile, William V.

2010-01-01

At present, limited functional data exists regarding the application and use of biomechanical and imaging technologies for oral implant osseointegration assessment. The objective of this investigation was to determine the functional apparent moduli (FAMs) that could predict the dynamics of oral implant osseointegration. Using an in vivo dental implant osseous healing model, two FAMs, functional bone apparent modulus (FBAM) and composite tissue apparent modulus (FCAM), of the selected peri-imp...

Synchrony, compensatory dynamics, and the functional trait basis of phenological diversity in a tropical dry forest tree community: effects of rainfall seasonality

Science.gov (United States)

Lasky, Jesse R.; Uriarte, María; Muscarella, Robert

2016-11-01

Interspecific variation in phenology is a key axis of functional diversity, potentially mediating how communities respond to climate change. The diverse drivers of phenology act across multiple temporal scales. For example, abiotic constraints favor synchronous reproduction (positive covariance among species), while biotic interactions can favor synchrony or compensatory dynamics (negative covariance). We used wavelet analyses to examine phenology of community flower and seed production for 45 tree species across multiple temporal scales in a tropical dry forest in Puerto Rico with marked rainfall seasonality. We asked three questions: (1) do species exhibit synchronous or compensatory temporal dynamics in reproduction, (2) do interspecific differences in phenology reflect variable responses to rainfall, and (3) is interspecific variation in phenology and response to a major drought associated with functional traits that mediate responses to moisture? Community-level flowering was synchronized at seasonal scales (˜5-6 mo) and at short scales (˜1 mo, following rainfall). However, seed rain exhibited significant compensatory dynamics at intraseasonal scales (˜3 mo), suggesting interspecific variation in temporal niches. Species with large leaves (associated with sensitivity to water deficit) peaked in reproduction synchronously with the peak of seasonal rainfall (˜5 mo scale). By contrast, species with high wood specific gravity (associated with drought resistance) tended to flower in drier periods. Flowering of tall species and those with large leaves was most tightly linked to intraseasonal (˜2 mo scale) rainfall fluctuations. Although the 2015 drought dramatically reduced community-wide reproduction, functional traits were not associated with the magnitude of species-specific declines. Our results suggest opposing drivers of synchronous versus compensatory dynamics at different temporal scales. Phenology associations with functional traits indicated that

Antipersistent dynamics in short time scale variability of self-potential signals

OpenAIRE

Cuomo, V.; Lanfredi, M.; Lapenna, V.; Macchiato, M.; Ragosta, M.; Telesca, L.

2000-01-01

Time scale properties of self-potential signals are investigated through the analysis of the second order structure function (variogram), a powerful tool to investigate the spatial and temporal variability of observational data. In this work we analyse two sequences of self-potential values measured by means of a geophysical monitoring array located in a seismically active area of Southern Italy. The range of scales investigated goes from a few minutes to several days. It is shown that signal...

Resting heart rate, heart rate variability and functional decline in old age

DEFF Research Database (Denmark)

Ogliari, Giulia; Mahinrad, Simin; Stott, David J

2015-01-01

variability was defined as the standard deviation of normal-to-normal RR intervals (SDNN). Functional status in basic (ADL) and instrumental (IADL) activities of daily living was measured using Barthel and Lawton scales, at baseline and during follow-up. RESULTS: The mean age of the study population was 75...

Certain properties of some special functions of two variables and two indices

International Nuclear Information System (INIS)

Khan, Subuhi

2002-07-01

In this paper, we derive a result concerning eigenvector and eigenvalue for a quadratic combination of four operators defined on a Lie algebra of endomorphisms of a vector space. Further, using this result, we deduce certain properties of some special functions of two variables and two indices. (author)

Daily Physical Activity and Cognitive Function Variability in Older Adults.

Science.gov (United States)

Phillips, Christine B; Edwards, Jerri D; Andel, Ross; Kilpatrick, Marcus

2016-04-01

Physical activity (PA) is believed to preserve cognitive function in older adulthood, though little is known about these relationships within the context of daily life. The present microlongitudinal pilot study explored within- and between-person relationships between daily PA and cognitive function and also examined within-person effect sizes in a sample of community-dwelling older adults. Fifty-one healthy participants (mean age = 70.1 years) wore an accelerometer and completed a cognitive assessment battery for five days. There were no significant associations between cognitive task performance and participants' daily or average PA over the study period. Effect size estimates indicated that PA explained 0-24% of within-person variability in cognitive function, depending on cognitive task and PA dose. Results indicate that PA may have near-term cognitive effects and should be explored as a possible strategy to enhance older adults' ability to perform cognitively complex activities within the context of daily living.

Determination of a Two Variable Approximation Function with Application to the Fuel Combustion Charts

Directory of Open Access Journals (Sweden)

Irina-Carmen ANDREI

2017-09-01

Full Text Available Following the demands of the design and performance analysis in case of liquid fuel propelled rocket engines, as well as the trajectory optimization, the development of efficient codes, which frequently need to call the Fuel Combustion Charts, became an important matter. This paper presents an efficient solution to the issue; the author has developed an original approach to determine the non-linear approximation function of two variables: the chamber pressure and the nozzle exit pressure ratio. The numerical algorithm based on this two variable approximation function is more efficient due to its simplicity, capability to providing numerical accuracy and prospects for an increased convergence rate of the optimization codes.

Non-Markovian dynamics, decoherence and entanglement in dissipative quantum systems with applications to quantum information theory of continuous variable systems; Nicht-Markovsche Dynamik, Dekohaerenz und Verschraenkung in dissipativen Quantensystemen mit Anwendung in der Quanteninformationstheorie von Systemen kontinuierlicher Variablen

Energy Technology Data Exchange (ETDEWEB)

Hoerhammer, C.

2007-11-26

In this thesis, non-Markovian dynamics, decoherence and entanglement in dissipative quantum systems are studied. In particular, applications to quantum information theory of continuous variable systems are considered. The non-Markovian dynamics are described by the Hu-Paz-Zhang master equation of quantum Brownian motion. In this context the focus is on non-Markovian effects on decoherence and separability time scales of various single- mode and two-mode continuous variable states. It is verified that moderate non-Markovian influences slow down the decay of interference fringes and quantum correlations, while strong non-Markovian effects resulting from an out-of-resonance bath can even accelerate the loss of coherence, compared to predictions of Markovian approximations. Qualitatively different scenarios including exponential, Gaussian or algebraic decay of the decoherence function are analyzed. It is shown that partial recurrence of coherence can occur in case of non-Lindblad-type dynamics. The time evolution of quantum correlations of entangled two-mode continuous variable states is examined in single-reservoir and two-reservoir models, representing noisy correlated or uncorrelated non-Markovian quantum channels. For this purpose the model of quantum Brownian motion is extended. Various separability criteria for Gaussian and non-Gaussian continuous variable systems are applied. In both types of reservoir models moderate non-Markovian effects prolong the separability time scales. However, in these models the properties of the stationary state may differ. In the two-reservoir model the initial entanglement is completely lost and both modes are finally uncorrelated. In a common reservoir both modes interact indirectly via the coupling to the same bath variables. Therefore, new quantum correlations may emerge between the two modes. Below a critical bath temperature entanglement is preserved even in the steady state. A separability criterion is derived, which depends

Dynamic state estimation and prediction for real-time control and operation

NARCIS (Netherlands)

Nguyen, P.H.; Venayagamoorthy, G.K.; Kling, W.L.; Ribeiro, P.F.

2013-01-01

Real-time control and operation are crucial to deal with increasing complexity of modern power systems. To effectively enable those functions, it is required a Dynamic State Estimation (DSE) function to provide accurate network state variables at the right moment and predict their trends ahead. This

Dynamic Vehicle Routing Using an Improved Variable Neighborhood Search Algorithm

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Yingcheng Xu

2013-01-01

Full Text Available In order to effectively solve the dynamic vehicle routing problem with time windows, the mathematical model is established and an improved variable neighborhood search algorithm is proposed. In the algorithm, allocation customers and planning routes for the initial solution are completed by the clustering method. Hybrid operators of insert and exchange are used to achieve the shaking process, the later optimization process is presented to improve the solution space, and the best-improvement strategy is adopted, which make the algorithm can achieve a better balance in the solution quality and running time. The idea of simulated annealing is introduced to take control of the acceptance of new solutions, and the influences of arrival time, distribution of geographical location, and time window range on route selection are analyzed. In the experiment, the proposed algorithm is applied to solve the different sizes' problems of DVRP. Comparing to other algorithms on the results shows that the algorithm is effective and feasible.

Functional dynamic factor models with application to yield curve forecasting

KAUST Repository

Hays, Spencer; Shen, Haipeng; Huang, Jianhua Z.

2012-01-01

resulted in a trade-off between goodness of fit and consistency with economic theory. To address this, herein we propose a novel formulation which connects the dynamic factor model (DFM) framework with concepts from functional data analysis: a DFM

Effect of flow rate on environmental variables and phytoplankton dynamics: results from field enclosures

Science.gov (United States)

Zhang, Haiping; Chen, Ruihong; Li, Feipeng; Chen, Ling

2015-03-01

To investigate the effects of flow rate on phytoplankton dynamics and related environment variables, a set of enclosure experiments with different flow rates were conducted in an artificial lake. We monitored nutrients, temperature, dissolved oxygen, pH, conductivity, turbidity, chlorophyll- a and phytoplankton levels. The lower biomass in all flowing enclosures showed that flow rate significantly inhibited the growth of phytoplankton. A critical flow rate occurred near 0.06 m/s, which was the lowest relative inhibitory rate. Changes in flow conditions affected algal competition for light, resulting in a dramatic shift in phytoplankton composition, from blue-green algae in still waters to green algae in flowing conditions. These findings indicate that critical flow rate can be useful in developing methods to reduce algal bloom occurrence. However, flow rate significantly enhanced the inter-relationships among environmental variables, in particular by inducing higher water turbidity and vegetative reproduction of periphyton ( Spirogyra). These changes were accompanied by a decrease in underwater light intensity, which consequently inhibited the photosynthetic intensity of phytoplankton. These results warn that a universal critical flow rate might not exist, because the effect of flow rate on phytoplankton is interlinked with many other environmental variables.

The Functional Programming Language R and the Paradigm of Dynamic Scientific Programming

NARCIS (Netherlands)

Trancón y Widemann, B.; Bolz, C.F.; Grelck, C.; Loidl, H.-W.; Peña, R.

2013-01-01

R is an environment and functional programming language for statistical data analysis and visualization. Largely unknown to the functional programming community, it is popular and influential in many empirical sciences. Due to its integrated combination of dynamic and reflective scripting on one

Totally Optimal Decision Trees for Monotone Boolean Functions with at Most Five Variables

KAUST Repository

Chikalov, Igor; Hussain, Shahid; Moshkov, Mikhail

2013-01-01

In this paper, we present the empirical results for relationships between time (depth) and space (number of nodes) complexity of decision trees computing monotone Boolean functions, with at most five variables. We use Dagger (a tool for optimization

Mode coupling theory analysis of electrolyte solutions: Time dependent diffusion, intermediate scattering function, and ion solvation dynamics.

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Roy, Susmita; Yashonath, Subramanian; Bagchi, Biman

2015-03-28

A self-consistent mode coupling theory (MCT) with microscopic inputs of equilibrium pair correlation functions is developed to analyze electrolyte dynamics. We apply the theory to calculate concentration dependence of (i) time dependent ion diffusion, (ii) intermediate scattering function of the constituent ions, and (iii) ion solvation dynamics in electrolyte solution. Brownian dynamics with implicit water molecules and molecular dynamics method with explicit water are used to check the theoretical predictions. The time dependence of ionic self-diffusion coefficient and the corresponding intermediate scattering function evaluated from our MCT approach show quantitative agreement with early experimental and present Brownian dynamic simulation results. With increasing concentration, the dispersion of electrolyte friction is found to occur at increasingly higher frequency, due to the faster relaxation of the ion atmosphere. The wave number dependence of intermediate scattering function, F(k, t), exhibits markedly different relaxation dynamics at different length scales. At small wave numbers, we find the emergence of a step-like relaxation, indicating the presence of both fast and slow time scales in the system. Such behavior allows an intriguing analogy with temperature dependent relaxation dynamics of supercooled liquids. We find that solvation dynamics of a tagged ion exhibits a power law decay at long times-the decay can also be fitted to a stretched exponential form. The emergence of the power law in solvation dynamics has been tested by carrying out long Brownian dynamics simulations with varying ionic concentrations. The solvation time correlation and ion-ion intermediate scattering function indeed exhibit highly interesting, non-trivial dynamical behavior at intermediate to longer times that require further experimental and theoretical studies.

Dyadic variability in mother-adolescent interactions: developmental trajectories and associations with psychosocial functioning.

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Van der Giessen, Daniёlle; Branje, Susan J T; Frijns, Tom; Meeus, Wim H J

2013-01-01

Dyadic variability is considered to be a key mechanism in the development of mother-adolescent relationships, and low levels of dyadic flexibility are thought to be associated with behavior and relationship problems. The present observational study examined heterogeneity in the development of dyadic variability in mother-adolescent interactions and associations with psychosocial functioning. Dyadic variability refers to the range of emotional states during interactions of mother-adolescent dyads. During five annual home visits, 92 mother-adolescent dyads (M age T1 = 13; 65.2 % boys) were videotaped while discussing a conflict, and they completed several questionnaires on adolescents' aggressive behavior and adolescents' and mothers' perceived relationship quality. Two types of dyads were distinguished: low variability dyads (52 %) and high decreasing variability dyads (48 %). Over time, high decreasing variability dyads were characterized by a broader emotional repertoire than low variability dyads. Moreover, these two dyad types had distinct developmental patterns of psychosocial adjustment. Over time, high decreasing variability dyads showed lower levels of adolescents' aggressive behavior, and higher levels of perceived relationship quality than low variability dyads. These findings suggest that over time more dyadic variability is associated with less adjustment problems and a more constructive development of the mother-adolescent relationship. Adaptive interactions seem to be characterized by a wider range of emotional states and mothers should guide adolescents during interactions to express both positive and negative affect. Observing the dyadic variability during mother-adolescent interactions can help clinicians to distinguish adaptive from maladaptive mother-adolescent dyads.

Dynamic functional modules in co-expressed protein interaction networks of dilated cardiomyopathy

Directory of Open Access Journals (Sweden)

Oyang Yen-Jen

2010-10-01

Full Text Available Abstract Background Molecular networks represent the backbone of molecular activity within cells and provide opportunities for understanding the mechanism of diseases. While protein-protein interaction data constitute static network maps, integration of condition-specific co-expression information provides clues to the dynamic features of these networks. Dilated cardiomyopathy is a leading cause of heart failure. Although previous studies have identified putative biomarkers or therapeutic targets for heart failure, the underlying molecular mechanism of dilated cardiomyopathy remains unclear. Results We developed a network-based comparative analysis approach that integrates protein-protein interactions with gene expression profiles and biological function annotations to reveal dynamic functional modules under different biological states. We found that hub proteins in condition-specific co-expressed protein interaction networks tended to be differentially expressed between biological states. Applying this method to a cohort of heart failure patients, we identified two functional modules that significantly emerged from the interaction networks. The dynamics of these modules between normal and disease states further suggest a potential molecular model of dilated cardiomyopathy. Conclusions We propose a novel framework to analyze the interaction networks in different biological states. It successfully reveals network modules closely related to heart failure; more importantly, these network dynamics provide new insights into the cause of dilated cardiomyopathy. The revealed molecular modules might be used as potential drug targets and provide new directions for heart failure therapy.

Monte Carlo study of four-spinon dynamic structure function in antiferromagnetic Heisenberg model

International Nuclear Information System (INIS)

Si-Lakhal, B.; Abada, A.

2003-11-01

Using Monte Carlo integration methods, we describe the behavior of the exact four-s pinon dynamic structure function S 4 in the antiferromagnetic spin 1/2 Heisenberg quantum spin chain as a function of the neutron energy ω and momentum transfer k. We also determine the fourspinon continuum, the extent of the region in the (k, ω) plane outside which S 4 is identically zero. In each case, the behavior of S 4 is shown to be consistent with the four-spinon continuum and compared to the one of the exact two-spinon dynamic structure function S 2 . Overall shape similarity is noted. (author)

Combining protein sequence, structure, and dynamics: A novel approach for functional evolution analysis of PAS domain superfamily.

Science.gov (United States)

Dong, Zheng; Zhou, Hongyu; Tao, Peng

2018-02-01

PAS domains are widespread in archaea, bacteria, and eukaryota, and play important roles in various functions. In this study, we aim to explore functional evolutionary relationship among proteins in the PAS domain superfamily in view of the sequence-structure-dynamics-function relationship. We collected protein sequences and crystal structure data from RCSB Protein Data Bank of the PAS domain superfamily belonging to three biological functions (nucleotide binding, photoreceptor activity, and transferase activity). Protein sequences were aligned and then used to select sequence-conserved residues and build phylogenetic tree. Three-dimensional structure alignment was also applied to obtain structure-conserved residues. The protein dynamics were analyzed using elastic network model (ENM) and validated by molecular dynamics (MD) simulation. The result showed that the proteins with same function could be grouped by sequence similarity, and proteins in different functional groups displayed statistically significant difference in their vibrational patterns. Interestingly, in all three functional groups, conserved amino acid residues identified by sequence and structure conservation analysis generally have a lower fluctuation than other residues. In addition, the fluctuation of conserved residues in each biological function group was strongly correlated with the corresponding biological function. This research suggested a direct connection in which the protein sequences were related to various functions through structural dynamics. This is a new attempt to delineate functional evolution of proteins using the integrated information of sequence, structure, and dynamics. © 2017 The Protein Society.

Gradual plasticity alters population dynamics in variable environments: thermal acclimation in the green alga Chlamydomonas reinhartdii.

Science.gov (United States)

Kremer, Colin T; Fey, Samuel B; Arellano, Aldo A; Vasseur, David A

2018-01-10

Environmental variability is ubiquitous, but its effects on populations are not fully understood or predictable. Recent attention has focused on how rapid evolution can impact ecological dynamics via adaptive trait change. However, the impact of trait change arising from plastic responses has received less attention, and is often assumed to optimize performance and unfold on a separate, faster timescale than ecological dynamics. Challenging these assumptions, we propose that gradual plasticity is important for ecological dynamics, and present a study of the plastic responses of the freshwater green algae Chlamydomonas reinhardtii as it acclimates to temperature changes. First, we show that C. reinhardtii 's gradual acclimation responses can both enhance and suppress its performance after a perturbation, depending on its prior thermal history. Second, we demonstrate that where conventional approaches fail to predict the population dynamics of C. reinhardtii exposed to temperature fluctuations, a new model of gradual acclimation succeeds. Finally, using high-resolution data, we show that phytoplankton in lake ecosystems can experience thermal variation sufficient to make acclimation relevant. These results challenge prevailing assumptions about plasticity's interactions with ecological dynamics. Amidst the current emphasis on rapid evolution, it is critical that we also develop predictive methods accounting for plasticity. © 2018 The Author(s).

Proton structure functions in the dipole picture of BFKL dynamics

International Nuclear Information System (INIS)

Navelet, H.; Peschanski, R.; Wallon, S.; Royon, Ch.

1996-06-01

The proton structure functions are derived in the QCD dipole picture. Assuming k T and renormalization-group factorization, deep-inelastic proton scattering is related to deep-inelastic onium scattering. A three parameter fit of the 1994 H1 data in the low-x, moderate Q 2 range has been obtained. The dipole picture of BFKL dynamics is shown to provide a relevant model for quantitatively describing the proton structure functions at HERA. (author)

Fluctuation-Response Relation and modeling in systems with fast and slow dynamics

Directory of Open Access Journals (Sweden)

G. Lacorata

2007-10-01

Full Text Available We show how a general formulation of the Fluctuation-Response Relation is able to describe in detail the connection between response properties to external perturbations and spontaneous fluctuations in systems with fast and slow variables. The method is tested by using the 360-variable Lorenz-96 model, where slow and fast variables are coupled to one another with reciprocal feedback, and a simplified low dimensional system. In the Fluctuation-Response context, the influence of the fast dynamics on the slow dynamics relies in a non trivial behavior of a suitable quadratic response function. This has important consequences for the modeling of the slow dynamics in terms of a Langevin equation: beyond a certain intrinsic time interval even the optimal model can give just statistical prediction.

Age-related Multiscale Changes in Brain Signal Variability in Pre-task versus Post-task Resting-state EEG.

Science.gov (United States)

Wang, Hongye; McIntosh, Anthony R; Kovacevic, Natasa; Karachalios, Maria; Protzner, Andrea B

2016-07-01

Recent empirical work suggests that, during healthy aging, the variability of network dynamics changes during task performance. Such variability appears to reflect the spontaneous formation and dissolution of different functional networks. We sought to extend these observations into resting-state dynamics. We recorded EEG in young, middle-aged, and older adults during a "rest-task-rest" design and investigated if aging modifies the interaction between resting-state activity and external stimulus-induced activity. Using multiscale entropy as our measure of variability, we found that, with increasing age, resting-state dynamics shifts from distributed to more local neural processing, especially at posterior sources. In the young group, resting-state dynamics also changed from pre- to post-task, where fine-scale entropy increased in task-positive regions and coarse-scale entropy increased in the posterior cingulate, a key region associated with the default mode network. Lastly, pre- and post-task resting-state dynamics were linked to performance on the intervening task for all age groups, but this relationship became weaker with increasing age. Our results suggest that age-related changes in resting-state dynamics occur across different spatial and temporal scales and have consequences for information processing capacity.

Investigation of dynamic fracture behavior in functionally graded materials

International Nuclear Information System (INIS)

Yang, X B; Qin, Y P; Zhuang, Z; You, X C

2008-01-01

The fast running crack in functionally graded materials (FGMs) is investigated through numerical simulations under impact loading. Some fracture characterizations such as crack propagation and arrest are evaluated by the criterion of the crack tip opening angle. Based on the experimental results, the whole propagation process of the fast running crack is simulated by the finite element program. Thus, the dynamic fracture parameters can be obtained during the crack growing process. In this paper, the crack direction is assumed to be the graded direction of the materials, and the property gradation in FGMs is considered by varying the elastic modulus exponentially along the graded direction and keeping the mass density and Poisson's ratio constant. The influences of the non-homogeneity, the loading ratio and the crack propagation speed on the dynamic fracture response of FGMs are analyzed through the test and numerical analysis. Considering the potential application of FGMs in natural-gas transmission engineering, a functionally graded pipeline is designed to arrest the fast running crack for a short period in high pressure large diameter natural-gas pipelines

Evolutionary Fates and Dynamic Functionalization of Young Duplicate Genes in Arabidopsis Genomes.

Science.gov (United States)

Wang, Jun; Tao, Feng; Marowsky, Nicholas C; Fan, Chuanzhu

2016-09-01

Gene duplication is a primary means to generate genomic novelties, playing an essential role in speciation and adaptation. Particularly in plants, a high abundance of duplicate genes has been maintained for significantly long periods of evolutionary time. To address the manner in which young duplicate genes were derived primarily from small-scale gene duplication and preserved in plant genomes and to determine the underlying driving mechanisms, we generated transcriptomes to produce the expression profiles of five tissues in Arabidopsis thaliana and the closely related species Arabidopsis lyrata and Capsella rubella Based on the quantitative analysis metrics, we investigated the evolutionary processes of young duplicate genes in Arabidopsis. We determined that conservation, neofunctionalization, and specialization are three main evolutionary processes for Arabidopsis young duplicate genes. We explicitly demonstrated the dynamic functionalization of duplicate genes along the evolutionary time scale. Upon origination, duplicates tend to maintain their ancestral functions; but as they survive longer, they might be likely to develop distinct and novel functions. The temporal evolutionary processes and functionalization of plant duplicate genes are associated with their ancestral functions, dynamic DNA methylation levels, and histone modification abundances. Furthermore, duplicate genes tend to be initially expressed in pollen and then to gain more interaction partners over time. Altogether, our study provides novel insights into the dynamic retention processes of young duplicate genes in plant genomes. © 2016 American Society of Plant Biologists. All rights reserved.

Application of generalized function to dynamic analysis of thick plates

International Nuclear Information System (INIS)

Zheng, D.; Weng, Z.

1987-01-01

The structures with thick plates have been used extensively in national defence, mechanical engineering, chemical engineering, nuclear engineering, civil engineering, etc.. Various theories have been established to deal with the problems of elastic plates, which include the classical theory of thin plates, the improved theory of thick plates, three-dimensional elastical theory. In this paper, the derivative of δ-function is handled by using the generalized function. The dynamic analysis of thick plates subjected the concentrated load is presented. The improved Donnell's equation of thick plates is deduced and employed as the basic equation. The generalized coordinates are solved by using the method of MWR. The general expressions for the dynamic response of elastic thick plates subjected the concentrated load are given. The numerical results for rectangular plates are given herein. The results are compared with those obtained from the improved theory and the classical theory of plates. (orig./GL)

Dynamics of functional failures and recovery in complex road networks

Science.gov (United States)

Zhan, Xianyuan; Ukkusuri, Satish V.; Rao, P. Suresh C.

2017-11-01

We propose a new framework for modeling the evolution of functional failures and recoveries in complex networks, with traffic congestion on road networks as the case study. Differently from conventional approaches, we transform the evolution of functional states into an equivalent dynamic structural process: dual-vertex splitting and coalescing embedded within the original network structure. The proposed model successfully explains traffic congestion and recovery patterns at the city scale based on high-resolution data from two megacities. Numerical analysis shows that certain network structural attributes can amplify or suppress cascading functional failures. Our approach represents a new general framework to model functional failures and recoveries in flow-based networks and allows understanding of the interplay between structure and function for flow-induced failure propagation and recovery.

Prediction of spatially variable unsaturated hydraulic conductivity using scaled particle-size distribution functions

NARCIS (Netherlands)

Nasta, P.; Romano, N.; Assouline, S; Vrugt, J.A.; Hopmans, J.W.

2013-01-01

Simultaneous scaling of soil water retention and hydraulic conductivity functions provides an effective means to characterize the heterogeneity and spatial variability of soil hydraulic properties in a given study area. The statistical significance of this approach largely depends on the number of

Variability in negative emotions among individuals with chronic low back pain: relationships with pain and function.

Science.gov (United States)

Gerhart, James I; Burns, John W; Bruehl, Stephen; Smith, David A; Post, Kristina M; Porter, Laura S; Schuster, Erik; Buvanendran, Asokumar; Fras, Anne Marie; Keefe, Francis J

2017-11-13

Chronic pain is associated with elevated negative emotions, and resources needed to adaptively regulate these emotions can be depleted during prolonged pain. Studies of links between pain, function, and negative emotions in people with chronic pain, however, have focused almost exclusively on relationships among mean levels of these factors. Indexes that may reflect aspects of emotion regulation have typically not been analyzed. We propose that 1 index of emotion regulation is variability in emotion over time as opposed to average emotion over time. The sample was 105 people with chronic low back pain and 105 of their pain-free spouses. They completed electronic diary measures 5x/d for 14 consecutive days, producing 70 observations per person from which we derived estimates of within-subject variance in negative emotions. Location-scale models were used to simultaneously model predictors of both mean level and variance in patient negative emotions over time. Patients reported significantly more variability in negative emotions compared to their spouses. Patients who reported higher average levels of pain, pain interference, and downtime reported significantly higher levels of variability in negative emotions. Spouse-observed pain and pain behaviors were also associated with greater variability in patients' negative emotions. Test of the inverse associations between negative emotion level and variability in pain and function were significant but weaker in magnitude. These findings support the notion that chronic pain may erode negative emotion regulation resources, to the potential detriment of intra- and inter-personal function.

Quantifying Effects of Pharmacological Blockers of Cardiac Autonomous Control Using Variability Parameters.

Science.gov (United States)

Miyabara, Renata; Berg, Karsten; Kraemer, Jan F; Baltatu, Ovidiu C; Wessel, Niels; Campos, Luciana A

2017-01-01

Objective: The aim of this study was to identify the most sensitive heart rate and blood pressure variability (HRV and BPV) parameters from a given set of well-known methods for the quantification of cardiovascular autonomic function after several autonomic blockades. Methods: Cardiovascular sympathetic and parasympathetic functions were studied in freely moving rats following peripheral muscarinic (methylatropine), β1-adrenergic (metoprolol), muscarinic + β1-adrenergic, α1-adrenergic (prazosin), and ganglionic (hexamethonium) blockades. Time domain, frequency domain and symbolic dynamics measures for each of HRV and BPV were classified through paired Wilcoxon test for all autonomic drugs separately. In order to select those variables that have a high relevance to, and stable influence on our target measurements (HRV, BPV) we used Fisher's Method to combine the p -value of multiple tests. Results: This analysis led to the following best set of cardiovascular variability parameters: The mean normal beat-to-beat-interval/value (HRV/BPV: meanNN), the coefficient of variation (cvNN = standard deviation over meanNN) and the root mean square differences of successive (RMSSD) of the time domain analysis. In frequency domain analysis the very-low-frequency (VLF) component was selected. From symbolic dynamics Shannon entropy of the word distribution (FWSHANNON) as well as POLVAR3, the non-linear parameter to detect intermittently decreased variability, showed the best ability to discriminate between the different autonomic blockades. Conclusion: Throughout a complex comparative analysis of HRV and BPV measures altered by a set of autonomic drugs, we identified the most sensitive set of informative cardiovascular variability indexes able to pick up the modifications imposed by the autonomic challenges. These indexes may help to increase our understanding of cardiovascular sympathetic and parasympathetic functions in translational studies of experimental diseases.