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Objective Pre-eclampsia is a serious complication of pregnancy with high morbidity and mortality and an incidence of 3-5% in all pregnancies. Early prediction is still insufficient in clinical practice. Although most pre- eclamptic patients have pathological uterine perfusion in the second trimester, perfusion disturbance has a positive predictive accuracy (PPA) only of approximately 30%. Methods Non-invasive continuous blood pressure recordings were taken simultaneously via a finger cuff for 30 min. Time series of systolic as well as diastolic beat-to-beat pressure values were extracted to analyse heart rate and blood pressure variability and baroreflex sensitivity in 102 second- trimester pregnancies, to assess predictability for pre-eclampsia (n = 16). All women underwent Doppler investigations of the uterine arteries. Results We identified a combination of three variability and baroreflex parameters to best predict pre-eclampsia several weeks before clinical manifestation. The discriminant function of these three parameters classified patients with later pre-eclampsia with a sensitivity of 87.5%, a specificity of 83.7%, and a PPA of 50.0%. Combined with Doppler investigations of uterine arteries, PPA increased to 71.4%. Conclusions This technique of incorporating one-stop clinical assessment of uterine perfusion and variability parameters in the second trimester produces the most effective prediction of pre-eclampsia to date
In Allefeld & Kurths [2004], we introduced an approach to multivariate phase synchronization analysis in the form of a Synchronization Cluster Analysis (SCA). A statistical model of a synchronization cluster was described, and an abbreviated instruction on how to apply this model to empirical data was given, while an implementation of the corresponding algorithm was (and is) available from the authors. In this letter, the complete details on how the data analysis algorithm is to be derived from the model are filled in.
The separation of natural and anthropogenically caused climatic changes is an important task of contemporary climate research. For this purpose, a detailed knowledge of the natural variability of the climate during warm stages is a necessary prerequisite. Beside model simulations and historical documents, this knowledge is mostly derived from analyses of so-called climatic proxy data like tree rings or sediment as well as ice cores. In order to be able to appropriately interpret such sources of palaeoclimatic information, suitable approaches of statistical modelling as well as methods of time series analysis are necessary, which are applicable to short, noisy, and non-stationary uni- and multivariate data sets. Correlations between different climatic proxy data within one or more climatological archives contain significant information about the climatic change on longer time scales. Based on an appropriate statistical decomposition of such multivariate time series, one may estimate dimensions in terms of the number of significant, linear independent components of the considered data set. In the presented work, a corresponding approach is introduced, critically discussed, and extended with respect to the analysis of palaeoclimatic time series. Temporal variations of the resulting measures allow to derive information about climatic changes. For an example of trace element abundances and grain-size distributions obtained near the Cape Roberts (Eastern Antarctica), it is shown that the variability of the dimensions of the investigated data sets clearly correlates with the Oligocene/Miocene transition about 24 million years before present as well as regional deglaciation events. Grain-size distributions in sediments give information about the predominance of different transportation as well as deposition mechanisms. Finite mixture models may be used to approximate the corresponding distribution functions appropriately. In order to give a complete description of the statistical uncertainty of the parameter estimates in such models, the concept of asymptotic uncertainty distributions is introduced. The relationship with the mutual component overlap as well as with the information missing due to grouping and truncation of the measured data is discussed for a particular geological example. An analysis of a sequence of grain-size distributions obtained in Lake Baikal reveals that there are certain problems accompanying the application of finite mixture models, which cause an extended climatological interpretation of the results to fail. As an appropriate alternative, a linear principal component analysis is used to decompose the data set into suitable fractions whose temporal variability correlates well with the variations of the average solar insolation on millenial to multi-millenial time scales. The abundance of coarse-grained material is obviously related to the annual snow cover, whereas a significant fraction of fine-grained sediments is likely transported from the Taklamakan desert via dust storms in the spring season.
The emission dynamics of a mode-locked laser oscillator with a nonlinear mirror based on stimulated Brillouin scattering (SBS) has been investigated with regard to its spectrum and to its intensity distribution. The investigation was carried out experimentally as well as by numerical simulations. The laser yields trains of pulses with measured durations of 410 ps and energies of the single pulse of up to 2 mJ. Two theoretical models describing the complex emission dynamics of a mode-locked SBS-laser oscillator are introduced. The first model consists of spectrally resolved laser rate equations and thus describes the mode locking in the frequency domain by the superposition of the longitudinal resonator modes. The SBS-Q-switch is incorporated by a phenomenological description of the time dependent SBS reflectivity. Numerical simulations based on this model yield the evolution of a few 100 longitudinal laser modes and the corresponding intensity distribution during the course of a Q-switch pulse with 10-ps resolution. The influences of the different components on the spectrum and thus on the pulse duration will be discussed. The second model describes all occurring dynamics in the time domain providing easy access to the study of misalignment on the output dynamics. Results of numerical simulations of both models and measurement results are compared
We demonstrate, within the framework of the FitzHugh-Nagumo model, that a firing neuron can respond to a noisy driving in a nonreliable manner: the same Gaussian white noise acting on identical neurons evokes different patterns of spikes. The effect is characterized via calculations of the Lyapunov exponent and the event synchronization correlations. We construct a theory that explains the antireliability as a combined effect of a high sensitivity to noise of some stages of the dynamics and nonisochronicity of oscillations. Geometrically, the antireliability is described by a random noninvertible one-dimensional map
This Thesis was devoted to the study of the coupled system composed by El Niño/Southern Oscillation and the Annual Cycle. More precisely, the work was focused on two main problems: 1. How to separate both oscillations into an affordable model for understanding the behaviour of the whole system. 2. How to model the system in order to achieve a better understanding of the interaction, as well as to predict future states of the system. We focused our efforts in the Sea Surface Temperature equations, considering that atmospheric effects were secondary to the ocean dynamics. The results found may be summarised as follows: 1. Linear methods are not suitable for characterising the dimensionality of the sea surface temperature in the tropical Pacific Ocean. Therefore they do not help to separate the oscillations by themselves. Instead, nonlinear methods of dimensionality reduction are proven to be better in defining a lower limit for the dimensionality of the system as well as in explaining the statistical results in a more physical way [1]. In particular, Isomap, a nonlinear modification of Multidimensional Scaling methods, provides a physically appealing method of decomposing the data, as it substitutes the euclidean distances in the manifold by an approximation of the geodesic distances. We expect that this method could be successfully applied to other oscillatory extended systems and, in particular, to meteorological systems. 2. A three dimensional dynamical system could be modeled, using a backfitting algorithm, for describing the dynamics of the sea surface temperature in the tropical Pacific Ocean. We observed that, although there were few data points available, we could predict future behaviours of the coupled ENSO-Annual Cycle system with an accuracy of less than six months, although the constructed system presented several drawbacks: few data points to input in the backfitting algorithm, untrained model, lack of forcing with external data and simplification using a close system. Anyway, ensemble prediction techniques showed that the prediction skills of the three dimensional time series were as good as those found in much more complex models. This suggests that the climatological system in the tropics is mainly explained by ocean dynamics, while the atmosphere plays a secondary role in the physics of the process. Relevant predictions for short lead times can be made using a low dimensional system, despite its simplicity. The analysis of the SST data suggests that nonlinear interaction between the oscillations is small, and that noise plays a secondary role in the fundamental dynamics of the oscillations [2]. A global view of the work shows a general procedure to face modeling of climatological systems. First, we should find a suitable method of either linear or nonlinear dimensionality reduction. Then, low dimensional time series could be extracted out of the method applied. Finally, a low dimensional model could be found using a backfitting algorithm in order to predict future states of the system.
The averaged dynamics of various two-phase systems in a high-frequency vibration field is studied theoretically. The continuum approach is applied to describe such systems as solid particle suspensions, emulsions, bubbly fluids, when the volume concentration of the disperse phase is small and gravity is insignificant. The dynamics of the disperse system is considered by means of the method of averaging, when the fast pulsation and slow averaged motion can be treated separately. Two averaged models for both nondeformable and deformable particles, when the compressibility of the disperse phase becomes important, are obtained. A criterion when the compressibility of bubbles cannot be neglected is figured out. For both cases the developed models are applied to study the averaged dynamics of the disperse media in an infinite plane layer under the action of transversal vibration. (C) 2006 American Institute of Physics
Six Earth system models of intermediate complexity that are able to simulate interaction between atmosphere, ocean, and land surface, were forced with a scenario of land cover changes during the last millennium. In response to historical deforestation of about 18 million sq km, the models simulate a decrease in global mean annual temperature in the range of 0.13-0.25 degrees C. The rate of this cooling accelerated during the 19th century, reached a maximum in the first half of the 20th century, and declined at the end of the 20th century. This trend is explained by temporal and spatial dynamics of land cover changes, as the effect of deforestation on temperature is less pronounced for tropical than for temperate regions, and reforestation in the northern temperate areas during the second part of the 20th century partly offset the cooling trend. In most of the models, land cover changes lead to a decline in annual land evapotranspiration, while seasonal changes are rather equivocal because of spatial shifts in convergence zones. In the future, reforestation might be chosen as an option for the enhancement of terrestrial carbon sequestration. Our study indicates that biogeophysical mechanisms need to be accounted for in the assessment of land management options for climate change mitigation
We report that the performances of blue polymer electrophosphorescent devices are crucially depending on the choice of the electron transporting material incorporated into the emissive layer. Devices with 1,3-bis[(4-tert- butylphenyl)-1,3,4-oxidiazolyl]phenylene (OXD-7) doped at similar to 40 wt% into a poly(vinylcarbazole) matrix exhibited significantly higher efficiencies than those with 2-(4-biphenylyl)-5-(4-tert-butylphenyl)-1,3,4-oxadiazole (PBD), yielding maximum luminous and power efficiency values of 18.2 Cd/A and 8.8 lm/W, respectively. Time resolved photoluminescence measurements revealed a long lifetime phosphorescence component in layers with PBD, which we assign to significant triplet harvesting by this electron-transporting component. (c) 2006 American Institute of Physics
The velocity distribution of a granular gas is analyzed in terms of the Sonine polynomials expansion. We derive an analytical expression for the third Sonine coefficient a(3). In contrast to frequently used assumptions this coefficient is of the same order of magnitude as the second Sonine coefficient a(2). For small inelasticity the theoretical result is in good agreement with numerical simulations. The next-order Sonine coefficients a(4), a(5) and a(6) are determined numerically. While these coefficients are negligible for small dissipation, their magnitude grows rapidly with increasing inelasticity for 0 < epsilon less than or similar to 0.6. We conclude that this behavior of the Sonine coefficients manifests the breakdown of the Sonine polynomial expansion caused by the increasing impact of the overpopulated high-energy tail of the distribution function
Chaosphysik
(2006)
In view of the importance of charge storage in polymer electrets for electromechanical transducer applications, the aim of this work is to contribute to the understanding of the charge-retention mechanisms. Furthermore, we will try to explain how the long-term storage of charge carriers in polymeric electrets works and to identify the probable trap sites. Charge trapping and de-trapping processes were investigated in order to obtain evidence of the trap sites in polymeric electrets. The charge de-trapping behavior of two particular polymer electrets was studied by means of thermal and optical techniques. In order to obtain evidence of trapping or de-trapping, charge and dipole profiles in the thickness direction were also monitored. In this work, the study was performed on polyethylene terephthalate (PETP) and on cyclic-olefin copolymers (COCs). PETP is a photo-electret and contains a net dipole moment that is located in the carbonyl group (C = O). The electret behavior of PETP arises from both the dipole orientation and the charge storage. In contrast to PETP, COCs are not photo-electrets and do not exhibit a net dipole moment. The electret behavior of COCs arises from the storage of charges only. COC samples were doped with dyes in order to probe their internal electric field. COCs show shallow charge traps at 0.6 and 0.11 eV, characteristic for thermally activated processes. In addition, deep charge traps are present at 4 eV, characteristic for optically stimulated processes. PETP films exhibit a photo-current transient with a maximum that depends on the temperature with an activation energy of 0.106 eV. The pair thermalization length (rc) calculated from this activation energy for the photo-carrier generation in PETP was estimated to be approx. 4.5 nm. The generated photo-charge carriers can recombine, interact with the trapped charge, escape through the electrodes or occupy an empty trap. PETP possesses a small quasi-static pyroelectric coefficient (QPC): ~0.6 nC/(m²K) for unpoled samples, ~60 nC/(m²K) for poled samples and ~60 nC/(m²K) for unpoled samples under an electric bias (E ~10 V/µm). When stored charges generate an internal electric field of approx. 10 V/µm, they are able to induce a QPC comparable to that of the oriented dipoles. Moreover, we observe charge-dipole interaction. Since the raw data of the QPC-experiments on PETP samples is noisy, a numerical Fourier-filtering procedure was applied. Simulations show that the data analysis is reliable when the noise level is up to 3 times larger than the calculated pyroelectric current for the QPC. PETP films revealed shallow traps at approx. 0.36 eV during thermally-stimulated current measurements. These energy traps are associated with molecular dipole relaxations (C = O). On the other hand, photo-activated measurements yield deep charge traps at 4.1 and 5.2 eV. The observed wavelengths belong to the transitions in PETP that are analogous to the π - π* benzene transitions. The observed charge de-trapping selectivity in the photocharge decay indicates that the charge detrapping is from a direct photon-charge interaction. Additionally, the charge de-trapping can be facilitated by photo-exciton generation and the interaction of the photo-excitons with trapped charge carriers. These results indicate that the benzene rings (C6H4) and the dipolar groups (C = O) can stabilize and share an extra charge carrier in a chemical resonance. In this way, this charge could be de-trapped in connection with the photo-transitions of the benzene ring and with the dipole relaxations. The thermally-activated charge release shows a difference in the trap depth to its optical counterpart. This difference indicates that the trap levels depend on the de-trapping process and on the chemical nature of the trap site. That is, the processes of charge detrapping from shallow traps are related to secondary forces. The processes of charge de-trapping from deep traps are related to primary forces. Furthermore, the presence of deep trap levels causes the stability of the charge for long periods of time.
The concept of complementarity, originally defined for non-commuting observables of quantum systems with states of non-vanishing dispersion, is extended to classical dynamical systems with a partitioned phase space. Interpreting partitions in terms of ensembles of epistemic states (symbols) with corresponding classical observables, it is shown that such observables are complementary to each other with respect to particular partitions unless those partitions are generating. This explains why symbolic descriptions based on an ad hoc partition of an underlying phase space description should generally be expected to be incompatible. Related approaches with different background and different objectives are discussed
Uncertainty about the sensitivity of the climate system to changes in the Earth’s radiative balance constitutes a primary source of uncertainty for climate projections. Given the continuous increase in atmospheric greenhouse gas concentrations, constraining the uncertainty range in such type of sensitivity is of vital importance. A common measure for expressing this key characteristic for climate models is the climate sensitivity, defined as the simulated change in global-mean equilibrium temperature resulting from a doubling of atmospheric CO2 concentration. The broad range of climate sensitivity estimates (1.5-4.5°C as given in the last Assessment Report of the Intergovernmental Panel on Climate Change, 2001), inferred from comprehensive climate models, illustrates that the strength of simulated feedback mechanisms varies strongly among different models. The central goal of this thesis is to constrain uncertainty in climate sensitivity. For this objective we first generate a large ensemble of model simulations, covering different feedback strengths, and then request their consistency with present-day observational data and proxy-data from the Last Glacial Maximum (LGM). Our analyses are based on an ensemble of fully-coupled simulations, that were realized with a climate model of intermediate complexity (CLIMBER-2). These model versions cover a broad range of different climate sensitivities, ranging from 1.3 to 5.5°C, and have been generated by simultaneously perturbing a set of 11 model parameters. The analysis of the simulated model feedbacks reveals that the spread in climate sensitivity results from different realizations of the feedback strengths in water vapour, clouds, lapse rate and albedo. The calculated spread in the sum of all feedbacks spans almost the entire plausible range inferred from a sampling of more complex models. We show that the requirement for consistency between simulated pre-industrial climate and a set of seven global-mean data constraints represents a comparatively weak test for model sensitivity (the data constrain climate sensitivity to 1.3-4.9°C). Analyses of the simulated latitudinal profile and of the seasonal cycle suggest that additional present-day data constraints, based on these characteristics, do not further constrain uncertainty in climate sensitivity. The novel approach presented in this thesis consists in systematically combining a large set of LGM simulations with data information from reconstructed regional glacial cooling. Irrespective of uncertainties in model parameters and feedback strengths, the set of our model versions reveals a close link between the simulated warming due to a doubling of CO2, and the cooling obtained for the LGM. Based on this close relationship between past and future temperature evolution, we define a method (based on linear regression) that allows us to estimate robust 5-95% quantiles for climate sensitivity. We thus constrain the range of climate sensitivity to 1.3-3.5°C using proxy-data from the LGM at low and high latitudes. Uncertainties in glacial radiative forcing enlarge this estimate to 1.2-4.3°C, whereas the assumption of large structural uncertainties may increase the upper limit by an additional degree. Using proxy-based data constraints for tropical and Antarctic cooling we show that very different absolute temperature changes in high and low latitudes all yield very similar estimates of climate sensitivity. On the whole, this thesis highlights that LGM proxy-data information can offer an effective means of constraining the uncertainty range in climate sensitivity and thus underlines the potential of paleo-climatic data to reduce uncertainty in future climate projections.
We demonstrate that a multiple delayed feedback is a powerful tool to control coherence properties of autonomous self-sustained oscillators. We derive the equation for the phase dynamics in presence of noise and delay, and analyze it analytically. In Gaussian approximation a closed set of equations for the frequency and the diffusion constant is obtained. Solutions of these equations are in good agreement with direct numerical simulations.