Dynamics and coexistence in a system with intraguild mutualism

It is a tenet of ecological theory that two competing consumers cannot stably coexist on a single limiting resource in a homogeneous environment. Many mechanisms and processes have since been evoked and studied, empirically and theoretically, to explain species coexistence and the observed biological diversity. Facilitative interactions clearly have the potential to enhance coexistence. Yet, even though mutual facilitation between species of the same guild is widely documented empirically, the subject has received very little theoretical attention. Here, we study one form of intraguild mutualism in the simplest possibly community module of one resource and two consumers. We incorporate mutualism as enhanced consumption in the presence of the other consumers. We find that intraguild mutualism can (a) significantly enhance coexistence of consumers, (b) induce cyclic dynamics, and (c) give rise to a bi-stability (a 'joint' Allee effect) and potentially catastrophic collapse of both consumer species. © 2012 Elsevier B.V.

Dynamics of the Gulf of California (GC). A case study of the internal waves using synthetic aperture radar (SAR)

Calificación: Matrícula de Honor

Influence of local wind speed and direction on wind power dynamics - Application to offshore very short-term forecasting

Wind power time series usually show complex dynamics mainly due to non-linearities related to the wind physics and the power transformation process in wind farms. This article provides an approach to the incorporation of observed local variables (wind speed and direction) to model some of these effects by means of statistical models. To this end, a benchmarking between two different families of varying-coefficient models (regime-switching and conditional parametric models) is carried out. The case of the offshore wind farm of Horns Rev in Denmark has been considered. The analysis is focused on one-step ahead forecasting and a time series resolution of 10 min. It has been found that the local wind direction contributes to model some features of the prevailing winds, such as the impact of the wind direction on the wind variability, whereas the non-linearities related to the power transformation process can be introduced by considering the local wind speed. In both cases, conditional parametric models showed a better performance than the one achieved by the regime-switching strategy. The results attained reinforce the idea that each explanatory variable allows the modelling of different underlying effects in the dynamics of wind power time series.

Mantle dynamics and seismic tomography

Three-dimensional imaging of the Earth's interior, called seismic tomography, has achieved breakthrough advances in the last two decades, revealing fundamental geodynamical processes throughout the Earth's mantle and core. Convective circulation of the entire mantle is taking place, with subducted oceanic lithosphere sinking into the lower mantle, overcoming the resistance to penetration provided by the phase boundary near 650-km depth that separates the upper and lower mantle. The boundary layer at the base of the mantle has been revealed to have complex structure, involving local stratification, extensive structural anisotropy, and massive regions of partial melt. The Earth's high Rayleigh number convective regime now is recognized to be much more interesting and complex than suggested by textbook cartoons, and continued advances in seismic tomography, geodynamical modeling, and high-pressure–high-temperature mineral physics will be needed to fully quantify the complex dynamics of our planet's interior.

Description and training of neural network dynamics

Attractor properties of a popular discrete-time neural network model are illustrated through numerical simulations. The most complex dynamics is found to occur within particular ranges of parameters controlling the symmetry and magnitude of the weight matrix. A small network model is observed to produce fixed points, limit cycles, mode-locking, the Ruelle-Takens route to chaos, and the period-doubling route to chaos. Training algorithms for tuning this dynamical behaviour are discussed. Training can be an easy or difficult task, depending whether the problem requires the use of temporal information distributed over long time intervals. Such problems require training algorithms which can handle hidden nodes. The most prominent of these algorithms, back propagation through time, solves the temporal credit assignment problem in a way which can work only if the relevant information is distributed locally in time. The Moving Targets algorithm works for the more general case, but is computationally intensive, and prone to local minima.

Chaotic Patterns in Aeroelastic Signals

This work presents the analysis of nonlinear aeroelastic time series from wing vibrations due to airflow separation during wind tunnel experiments. Surrogate data method is used to justify the application of nonlinear time series analysis to the aeroelastic system, after rejecting the chance for nonstationarity. The singular value decomposition (SVD) approach is used to reconstruct the state space, reducing noise from the aeroelastic time series. Direct analysis of reconstructed trajectories in the state space and the determination of Poincare sections have been employed to investigate complex dynamics and chaotic patterns. With the reconstructed state spaces, qualitative analyses may be done, and the attractors evolutions with parametric variation are presented. Overall results reveal complex system dynamics associated with highly separated flow effects together with nonlinear coupling between aeroelastic modes. Bifurcations to the nonlinear aeroelastic system are observed for two investigations, that is, considering oscillations-induced aeroelastic evolutions with varying freestream speed, and aeroelastic evolutions at constant freestream speed and varying oscillations. Finally, Lyapunov exponent calculation is proceeded in order to infer on chaotic behavior. Poincare mappings also suggest bifurcations and chaos, reinforced by the attainment of maximum positive Lyapunov exponents. Copyright (C) 2009 F. D. Marques and R. M. G. Vasconcellos.

Modeling ex vivo hematopoiesis using chemical engineering metaphors

Ex vivo hematopoiesis is increasingly used for clinical applications. Models of ex vivo hematopoiesis are required to better understand the complex dynamics and to optimize hematopoietic culture processes. A general mathematical modeling framework is developed which uses traditional chemical engineering metaphors to describe the complex hematopoietic dynamics. Tanks and tubular reactors are used to describe the (pseudo-) stochastic and deterministic elements of hematopoiesis, respectively. Cells at any point in the differentiation process can belong to either an immobilized, inert phase (quiescent cells) or a mobile, active phase (cycling cells). The model describes five processes: (1) flow (differentiation), (2) autocatalytic formation (growth),(3) degradation (death), (4) phase transition from immobilized to mobile phase (quiescent to cycling transition), and (5) phase transition from mobile to immobilized phase (cycling to quiescent transition). The modeling framework is illustrated with an example concerning the effect of TGF-beta 1 on erythropoiesis. (C) 1998 Published by Elsevier Science Ltd. All rights reserved.

Nitrogen fertilizer (15N) leaching in a central pivot fertigated coffee crop

Nitrogen has a complex dynamics in the soil-plant-atmosphere system. N fertilizers are subject to chemical and microbial transformations in soils that can result in significant losses. Considering the cost of fertilizers, the adoption of good management practices like fertigation could improve the N use efficiency by crops. Water balances (WB) were applied to evaluate fertilizer N leaching using 15N labeled urea in west Bahia, Brazil. Three scenarios (2008/2009) were established: i) rainfall + irrigation the full year, ii) rainfall only; and iii) rainfall + irrigation only in the dry season. The water excess was considered equal to the deep drainage for the very flat area (runoff = 0) with a water table located several meters below soil surface (capillary rise = 0). The control volume for water balance calculations was the 0 - 1 m soil layer, considering that it involves the active root system. The water drained below 1 m was used to estimate fertilizer N leaching losses. WB calculations used the mathematic model of Penman-Monteith for evapotranspiration, considering the crop coefficient equal to unity. The high N application rate associated to the high rainfall plus irrigation was found to be the main cause for leaching, which values were 14.7 and 104.5 kg ha-1 for the rates 400 and 800 kg ha-1 of N, corresponding to 3.7 and 13.1 % of the applied fertilizer, respectively.

Checklist cirúrgica: contributo para uma intervenção na área da segurança do doente

Mestrado em Intervenção Sócio-Organizacional na Saúde - Área de especuialização: Políticas de administração e gestão de serviços de saúde.

DYNAMOD – A dynamic agent based modelling framework for digital businesses

Digital Businesses have become a major driver for economic growth and have seen an explosion of new startups. At the same time, it also includes mature enterprises that have become global giants in a relatively short period of time. Digital Businesses have unique characteristics that make the running and management of a Digital Business much different from traditional offline businesses. Digital businesses respond to online users who are highly interconnected and networked. This enables a rapid flow of word of mouth, at a pace far greater than ever envisioned when dealing with traditional products and services. The relatively low cost of incremental user addition has led to a variety of innovation in pricing of digital products, including various forms of free and freemium pricing models. This thesis explores the unique characteristics and complexities of Digital Businesses and its implications on the design of Digital Business Models and Revenue Models. The thesis proposes an Agent Based Modeling Framework that can be used to develop Simulation Models that simulate the complex dynamics of Digital Businesses and the user interactions between users of a digital product. Such Simulation models can be used for a variety of purposes such as simple forecasting, analysing the impact of market disturbances, analysing the impact of changes in pricing models and optimising the pricing for maximum revenue generation or a balance between growth in usage and revenue generation. These models can be developed for a mature enterprise with a large historical record of user growth rate as well as for early stage enterprises without much historical data. Through three case studies, the thesis demonstrates the applicability of the Framework and its potential applications.

Asynchronous growth and competition in a two-sex age-structured population model

Asynchronous exponential growth has been extensively studied in population dynamics. In this paper we find out the asymptotic behaviour in a non-linear age-dependent model which takes into account sexual reproduction interactions. The main feature of our model is that the non-linear process converges to a linear one as the solution becomes large, so that the population undergoes asynchronous growth. The steady states analysis and the corresponding stability analysis are completely made and are summarized in a bifurcation diagram according to the parameter R0. Furthermore the effect of intraspecific competition is taken into account, leading to complex dynamics around steady states.

Bubbly collateral and economic activity

This paper develops a model of the bubbly economy and uses it to study the effects of bailoutpolicies. In the bubbly economy, weak enforcement institutions do not allow firms to pledge futurerevenues to their creditors. As a result, "fundamental" collateral is scarce and this impairs the intermediationprocess that transforms savings into capital. To overcome this shortage of "fundamental"collateral, the bubbly economy creates "bubbly" collateral. This additional collateral supports anintricate array of intra- and inter-generational transfers that allow savings to be transformed intocapital and bubbles. Swings in investor sentiment lead to fluctuations in the amount of bubblycollateral, giving rise to bubbly business cycles with very rich and complex dynamics.Bailout policies can affect these dynamics in a variety of ways. Expected bailouts provideadditional collateral and expand investment and the capital stock. Realized bailouts reduce thesupply of funds and contract investment and the capital stock. Thus, bailout policies tend to fosterinvestment and growth in normal times, but to depress investment and growth during crisis periods.We show how to design bailout policies that maximize various policy objectives.

A protein interaction atlas for the nuclear receptors: properties and quality of a hub-based dimerisation network.

BACKGROUND: The nuclear receptors are a large family of eukaryotic transcription factors that constitute major pharmacological targets. They exert their combinatorial control through homotypic heterodimerisation. Elucidation of this dimerisation network is vital in order to understand the complex dynamics and potential cross-talk involved. RESULTS: Phylogeny, protein-protein interactions, protein-DNA interactions and gene expression data have been integrated to provide a comprehensive and up-to-date description of the topology and properties of the nuclear receptor interaction network in humans. We discriminate between DNA-binding and non-DNA-binding dimers, and provide a comprehensive interaction map, that identifies potential cross-talk between the various pathways of nuclear receptors. CONCLUSION: We infer that the topology of this network is hub-based, and much more connected than previously thought. The hub-based topology of the network and the wide tissue expression pattern of NRs create a highly competitive environment for the common heterodimerising partners. Furthermore, a significant number of negative feedback loops is present, with the hub protein SHP [NR0B2] playing a major role. We also compare the evolution, topology and properties of the nuclear receptor network with the hub-based dimerisation network of the bHLH transcription factors in order to identify both unique themes and ubiquitous properties in gene regulation. In terms of methodology, we conclude that such a comprehensive picture can only be assembled by semi-automated text-mining, manual curation and integration of data from various sources.

Extreme times for volatility processes

Extreme times techniques, generally applied to nonequilibrium statistical mechanical processes, are also useful for a better understanding of financial markets. We present a detailed study on the mean first-passage time for the volatility of return time series. The empirical results extracted from daily data of major indices seem to follow the same law regardless of the kind of index thus suggesting an universal pattern. The empirical mean first-passage time to a certain level L is fairly different from that of the Wiener process showing a dissimilar behavior depending on whether L is higher or lower than the average volatility. All of this indicates a more complex dynamics in which a reverting force drives volatility toward its mean value. We thus present the mean first-passage time expressions of the most common stochastic volatility models whose approach is comparable to the random diffusion description. We discuss asymptotic approximations of these models and confront them to empirical results with a good agreement with the exponential Ornstein-Uhlenbeck model.

Generation and nonlinear evolution of shore-oblique/transverse sand bars

The coupling between topography, waves and currents in the surf zone may selforganize to produce the formation of shore-transverse or shore-oblique sand bars on an otherwise alongshore uniform beach. In the absence of shore-parallel bars, this has been shown by previous studies of linear stability analysis, but is now extended to the finite-amplitude regime. To this end, a nonlinear model coupling wave transformation and breaking, a shallow-water equations solver, sediment transport and bed updating is developed. The sediment flux consists of a stirring factor multiplied by the depthaveraged current plus a downslope correction. It is found that the cross-shore profile of the ratio of stirring factor to water depth together with the wave incidence angle primarily determine the shape and the type of bars, either transverse or oblique to the shore. In the latter case, they can open an acute angle against the current (upcurrent oriented) or with the current (down-current oriented). At the initial stages of development, both the intensity of the instability which is responsible for the formation of the bars and the damping due to downslope transport grow at a similar rate with bar amplitude, the former being somewhat stronger. As bars keep on growing, their finite-amplitude shape either enhances downslope transport or weakens the instability mechanism so that an equilibrium between both opposing tendencies occurs, leading to a final saturated amplitude. The overall shape of the saturated bars in plan view is similar to that of the small-amplitude ones. However, the final spacings may be up to a factor of 2 larger and final celerities can also be about a factor of 2 smaller or larger. In the case of alongshore migrating bars, the asymmetry of the longshore sections, the lee being steeper than the stoss, is well reproduced. Complex dynamics with merging and splitting of individual bars sometimes occur. Finally, in the case of shore-normal incidence the rip currents in the troughs between the bars are jet-like while the onshore return flow is wider and weaker as is observed in nature.