39 resultados para Complex dynamics

em CentAUR: Central Archive University of Reading - UK


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We study systems with periodically oscillating parameters that can give way to complex periodic or nonperiodic orbits. Performing the long time limit, we can define ergodic averages such as Lyapunov exponents, where a negative maximal Lyapunov exponent corresponds to a stable periodic orbit. By this, extremely complicated periodic orbits composed of contracting and expanding phases appear in a natural way. Employing the technique of ϵ-uncertain points, we find that values of the control parameters supporting such periodic motion are densely embedded in a set of values for which the motion is chaotic. When a tiny amount of noise is coupled to the system, dynamics with positive and with negative nontrivial Lyapunov exponents are indistinguishable. We discuss two physical systems, an oscillatory flow inside a duct and a dripping faucet with variable water supply, where such a mechanism seems to be responsible for a complicated alternation of laminar and turbulent phases.

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Anthropogenic pressure influences the two-way interactions between shallow aquifers and coastal lagoons. Aquifer overexploitation may lead to seawater intrusion, and aquifer recharge from rainfall plus irrigation may, in turn, increase the groundwater discharge into the lagoon. We analyse the evolution, since the 1950s up to the present, of the interactions between the Campo de Cartagena Quaternary aquifer and the Mar Menor coastal lagoon (SE Spain). This is a very heterogeneous and anisotropic detrital aquifer, where aquifer–lagoon interface has a very irregular geometry. Using electrical resistivity tomography, we clearly identified the freshwater–saltwater transition zone and detected areas affected by seawater intrusion. Severity of the intrusion was spatially variable and significantly related to the density of irrigation wells in 1950s–1960s, suggesting the role of groundwater overexploitation. We distinguish two different mechanisms by which water from the sea invades the land: (a) horizontal advance of the interface due to a wide exploitation area and (b) vertical rise (upconing) caused by local intensive pumping. In general, shallow parts of the geophysical profiles show higher electrical resistivity associated with freshwater mainly coming from irrigation return flows, with water resources mostly from deep confined aquifers and imported from Tagus river, 400 km north. This indicates a likely reversal of the former seawater intrusion process.

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This paper introduces new insights into the hydrochemical functioning of lowland river systems using field-based spectrophotometric and electrode technologies. The streamwater concentrations of nitrogen species and phosphorus fractions were measured at hourly intervals on a continuous basis at two contrasting sites on tributaries of the River Thames – one draining a rural catchment, the River Enborne, and one draining a more urban system, The Cut. The measurements complement those from an existing network of multi-parameter water quality sondes maintained across the Thames catchment and weekly monitoring based on grab samples. The results of the sub-daily monitoring show that streamwater phosphorus concentrations display highly complex dynamics under storm conditions dependent on the antecedent catchment wetness, and that diurnal phosphorus and nitrogen cycles occur under low flow conditions. The diurnal patterns highlight the dominance of sewage inputs in controlling the streamwater phosphorus and nitrogen concentrations at low flows, even at a distance of 7 km from the nearest sewage treatment works in the rural River Enborne. The time of sample collection is important when judging water quality against ecological thresholds or standards. An exhaustion of the supply of phosphorus from diffuse and multiple septic tank sources during storm events was evident and load estimation was not improved by sub-daily monitoring beyond that achieved by daily sampling because of the eventual reduction in the phosphorus mass entering the stream during events. The results highlight the utility of sub-daily water quality measurements and the discussion considers the practicalities and challenges of in situ, sub-daily monitoring.

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Despite many decades investigating scalp recordable 8–13-Hz (alpha) electroencephalographic activity, no consensus has yet emerged regarding its physiological origins nor its functional role in cognition. Here we outline a detailed, physiologically meaningful, theory for the genesis of this rhythm that may provide important clues to its functional role. In particular we find that electroencephalographically plausible model dynamics, obtained with physiological admissible parameterisations, reveals a cortex perched on the brink of stability, which when perturbed gives rise to a range of unanticipated complex dynamics that include 40-Hz (gamma) activity. Preliminary experimental evidence, involving the detection of weak nonlinearity in resting EEG using an extension of the well-known surrogate data method, suggests that nonlinear (deterministic) dynamics are more likely to be associated with weakly damped alpha activity. Thus rather than the “alpha rhythm” being an idling rhythm it may be more profitable to conceive it as a readiness rhythm.

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The ‘golden saying’ in early modern medicine was ‘Nature is the healer of disease’. This article uncovers the meaning and significance of this forgotten axiom by investigating perceptions of the agents and physiological processes of recovery from illness in England, c.1580-1720. Drawing on sources such as medical texts and diaries, it shows that doctors and laypeople attributed recovery to three agents – God, Nature, and the practitioner. While scholars are familiar with the roles of providence and medicine, the vital agency of Nature has been overlooked. In theory, the agents operated in a hierarchy: Nature was ‘God’s instrument’, and the physician, ‘Nature’s servant’; but in practice the power balance was more ambivalent. Nature was depicted both as a housewife who cooked and cleaned the humours, and as a warrior, who defeated the disease. Through exploring these complex dynamics, the article sheds fresh light on concepts of gender, disease, and bodies.

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Cybersecurity is a complex challenge that has emerged alongside the evolving global socio-technical environment of social networks that feature connectivity across time and space in ways unimaginable even a decade ago. This paper reports on the preliminary findings of a NATO funded project that investigates the nature of innovation in open collaborative communities and its implications for cyber security. In this paper, the authors describe the framing of relevant issues, the articulation of the research questions, and the derivation of a conceptual framework based on open collaborative innovation that has emerged from preliminary field research in Russia and the UK.

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This case study on the Sifnos island, Greece, assesses the main factors controlling vegetation succession following crop abandonment and describes the vegetation dynamics of maquis and phrygana formations in relation to alternative theories of secondary succession. Field survey data were collected and analysed at community as well as species level. The results show that vegetation succession on abandoned crop fields is determined by the combined effects of grazing intensity, soil and geological characteristics and time. The analysis determines the quantitative grazing thresholds that modify the successional pathway. Light grazing leads to dominance by maquis vegetation while overgrazing leads to phryganic vegetation. The proposed model shows that vegetation succession following crop abandonment is a complex multi-factor process where the final or the stable stage of the process is not predefined but depends on the factors affecting succession. An example of the use of succession models and disturbance thresholds as a policy assessment tool is presented by evaluating the likely vegetation impacts of the recent reform of the Common Agricultural Policy on Sifnos island over a 20-30-year time horizon. (c) 2006 Elsevier B.V. All rights reserved.

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Inferring the spatial expansion dynamics of invading species from molecular data is notoriously difficult due to the complexity of the processes involved. For these demographic scenarios, genetic data obtained from highly variable markers may be profitably combined with specific sampling schemes and information from other sources using a Bayesian approach. The geographic range of the introduced toad Bufo marinus is still expanding in eastern and northern Australia, in each case from isolates established around 1960. A large amount of demographic and historical information is available on both expansion areas. In each area, samples were collected along a transect representing populations of different ages and genotyped at 10 microsatellite loci. Five demographic models of expansion, differing in the dispersal pattern for migrants and founders and in the number of founders, were considered. Because the demographic history is complex, we used an approximate Bayesian method, based on a rejection-regression algorithm. to formally test the relative likelihoods of the five models of expansion and to infer demographic parameters. A stepwise migration-foundation model with founder events was statistically better supported than other four models in both expansion areas. Posterior distributions supported different dynamics of expansion in the studied areas. Populations in the eastern expansion area have a lower stable effective population size and have been founded by a smaller number of individuals than those in the northern expansion area. Once demographically stabilized, populations exchange a substantial number of effective migrants per generation in both expansion areas, and such exchanges are larger in northern than in eastern Australia. The effective number of migrants appears to be considerably lower than that of founders in both expansion areas. We found our inferences to be relatively robust to various assumptions on marker. demographic, and historical features. The method presented here is the only robust, model-based method available so far, which allows inferring complex population dynamics over a short time scale. It also provides the basis for investigating the interplay between population dynamics, drift, and selection in invasive species.

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Two Multifunctional photoactive complexes [Re(Cl)(CO)(3)-(MeDpe(+))(2)](2+) and [Re(MeDpe(+))(CO)(3)(bpy)](2+) (MeDpe(+) = N-methyl-4-[trans-2-(4-pyridyl)ethenyl]pyridinium, bpy = 2,2'-bipyridine) were synthesized. characterized. and their redox and photonic properties were investigated by cyclic voltammetry: ultraviolet-visible-infrared (UV/Vis/IR) spectroelectrochemistry, stationary UV/Vis and resonance Raman spectroscopy; photolysis; picosecond time-resolved absorption spectroscopy in the visible and infrared regions: and time-resolved resonance Raman spectroscopy. The first reduction step of either complex Occurs at about -1.1 V versus Fc/Fc(+) and is localized at MeDpe(+). Reduction alone does not induce a trans -> cis isomerization of MeDpe(+). [Re(Cl)(CO)(3)(MeDPe(+))(2)](2+) is photostable, while [Re(MeDpe(+))(CO)(3)(bpy)](2+) and free MeDpe(+) isomerize under near-UV irradiation. The lowest excited state of [Re(Cl)(CO)(3)(MeDPe(+))(2)](2+) has been identified as the Re(Cl)(CO)(3) -> MeDpe(+) (MLCT)-M-3 (MLCT = metal-to-ligand charge transfer), decaying directly to the ground state with lifetimes of approximate to 42 (73%) and approximate to 430ps (27%). Optical excitation of [Re(MeDpe(+))(CO)(3)(bpy)](2+) leads to population of Re(CO)(3) -> MeDpe(+) and Re(CO)(3) -> bpy (MLCT)-M-3 states, from which a MeDpe(+) localized intraligand 3 pi pi* excited state ((IL)-I-3) is populated with lifetimes of approximate to 0.6 and approximate to 10 ps, respectively. The 3IL state undergoes a approximate to 21 ps internal rotation, which eventually produces the cis isomer on a much longer timescale. The different excited-state behavior of the two complexes and the absence of thermodynamically favorable interligand electron transfer in excited [Re(MeDpe(+))(CO)(3)(bpy)](2+) reflect the fine energetic balance between excited states of different orbital origin, which can be tuned by subtle Structural variations. The complex [Re(MeDpe+)(CO)(3)(bpy)](2+) emerges as a prototypical, multifunctional species with complementary redox and photonic behavior.

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The development of eutrophication in river systems is poorly understood given the complex relationship between fixed plants, algae, hydrodynamics, water chemistry and solar radiation. However there is a pressing need to understand the relationship between the ecological status of rivers and the controlling environmental factors to help the reasoned implementation of the Water Framework Directive and Catchment Sensitive Farming in the UK. This research aims to create a dynamic, process-based, mathematical in-stream model to simulate the growth and competition of different vegetation types (macrophytes, phytoplankton and benthic algae) in rivers. The model, applied to the River Frome (Dorset, UK), captured well the seasonality of simulated vegetation types (suspended algae, macrophytes, epiphytes, sediment biofilm). Macrophyte results showed that local knowledge is important for explaining unusual changes in biomass. Fixed algae simulations indicated the need for the more detailed representation of various herbivorous grazer groups, however this would increase the model complexity, the number of model parameters and the required observation data to better define the model. The model results also highlighted that simulating only phytoplankton is insufficient in river systems, because the majority of the suspended algae have benthic origin in short retention time rivers. Therefore, there is a need for modelling tools that link the benthic and free-floating habitats.

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State-of-the-art computational methodologies are used to investigate the energetics and dynamics of photodissociated CO and NO in myoglobin (Mb···CO and Mb···NO). This includes the combination of molecular dynamics, ab initio MD, free energy sampling, and effective dynamics methods to compare the results with studies using X-ray crystallography and ultrafast spectroscopy metho ds. It is shown that modern simulation techniques along with careful description of the intermolecular interactions can give quantitative agreement with experiments on complex molecular systems. Based on this agreement predictions for as yet uncharacterized species can be made.

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We have performed atomistic molecular dynamics simulations of an anionic sodium dodecyl sulfate (SDS) micelle and a nonionic poly(ethylene oxide) (PEO) polymer in aqueous solution. The micelle consisted of 60 surfactant molecules, and the polymer chain lengths varied from 20 to 40 monomers. The force field parameters for PEO were adjusted by using 1,2-dimethoxymethane (DME) as a model compound and matching its hydration enthalpy and conformational behavior to experiment. Excellent agreement with previous experimental and simulation work was obtained through these modifications. The simulated scaling behavior of the PEO radius of gyration was also in close agreement with experimental results. The SDS-PEO simulations show that the polymer resides on the micelle surface and at the hydrocarbon-water interface, leading to a selective reduction in the hydrophobic contribution to the solvent-accessible surface area of the micelle. The association is mainly driven by hydrophobic interactions between the polymer and surfactant tails, while the interaction between the polymer and sulfate headgroups on the micelle surface is weak. The 40-monomer chain is mostly wrapped around the micelle, and nearly 90% of the monomers are adsorbed at low PEO concentration. Simulations were also performed with multiple 20-monomer chains, and gradual addition of polymer indicates that about 120 monomers are required to saturate the micelle surface. The stoichiometry of the resulting complex is in close agreement with experimental results, and the commonly accepted "beaded necklace" structure of the SDS-PEO complex is recovered by our simulations.

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A neural network enhanced proportional, integral and derivative (PID) controller is presented that combines the attributes of neural network learning with a generalized minimum-variance self-tuning control (STC) strategy. The neuro PID controller is structured with plant model identification and PID parameter tuning. The plants to be controlled are approximated by an equivalent model composed of a simple linear submodel to approximate plant dynamics around operating points, plus an error agent to accommodate the errors induced by linear submodel inaccuracy due to non-linearities and other complexities. A generalized recursive least-squares algorithm is used to identify the linear submodel, and a layered neural network is used to detect the error agent in which the weights are updated on the basis of the error between the plant output and the output from the linear submodel. The procedure for controller design is based on the equivalent model, and therefore the error agent is naturally functioned within the control law. In this way the controller can deal not only with a wide range of linear dynamic plants but also with those complex plants characterized by severe non-linearity, uncertainties and non-minimum phase behaviours. Two simulation studies are provided to demonstrate the effectiveness of the controller design procedure.

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Urban boundary layers (UBLs) can be highly complex due to the heterogeneous roughness and heating of the surface, particularly at night. Due to a general lack of observations, it is not clear whether canonical models of boundary layer mixing are appropriate in modelling air quality in urban areas. This paper reports Doppler lidar observations of turbulence profiles in the centre of London, UK, as part of the second REPARTEE campaign in autumn 2007. Lidar-measured standard deviation of vertical velocity averaged over 30 min intervals generally compared well with in situ sonic anemometer measurements at 190 m on the BT telecommunications Tower. During calm, nocturnal periods, the lidar underestimated turbulent mixing due mainly to limited sampling rate. Mixing height derived from the turbulence, and aerosol layer height from the backscatter profiles, showed similar diurnal cycles ranging from c. 300 to 800 m, increasing to c. 200 to 850 m under clear skies. The aerosol layer height was sometimes significantly different to the mixing height, particularly at night under clear skies. For convective and neutral cases, the scaled turbulence profiles resembled canonical results; this was less clear for the stable case. Lidar observations clearly showed enhanced mixing beneath stratocumulus clouds reaching down on occasion to approximately half daytime boundary layer depth. On one occasion the nocturnal turbulent structure was consistent with a nocturnal jet, suggesting a stable layer. Given the general agreement between observations and canonical turbulence profiles, mixing timescales were calculated for passive scalars released at street level to reach the BT Tower using existing models of turbulent mixing. It was estimated to take c. 10 min to diffuse up to 190 m, rising to between 20 and 50 min at night, depending on stability. Determination of mixing timescales is important when comparing to physico-chemical processes acting on pollutant species measured simultaneously at both the ground and at the BT Tower during the campaign. From the 3 week autumnal data-set there is evidence for occasional stable layers in central London, effectively decoupling surface emissions from air aloft.

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The dynamics of inter-regional communication within the brain during cognitive processing – referred to as functional connectivity – are investigated as a control feature for a brain computer interface. EMDPL is used to map phase synchronization levels between all channel pair combinations in the EEG. This results in complex networks of channel connectivity at all time–frequency locations. The mean clustering coefficient is then used as a descriptive feature encapsulating information about inter-channel connectivity. Hidden Markov models are applied to characterize and classify dynamics of the resulting complex networks. Highly accurate levels of classification are achieved when this technique is applied to classify EEG recorded during real and imagined single finger taps. These results are compared to traditional features used in the classification of a finger tap BCI demonstrating that functional connectivity dynamics provide additional information and improved BCI control accuracies.