A Multidimensional scaling perspective of Rostow's forecasts with the Track-record (1960s-2011) of "pioneers" and "latecomers"

Proceedings of the 12th Conference on Dynamical Systems -Theory and Applications

Multidimensional Scaling Analysis of Stock Market Indexes

This paper applies multidimensional scaling techniques and Fourier transform for visualizing possible time-varying correlations between 25 stock market values. The method is useful for observing clusters of stock markets with similar behavior.

Fractional Dynamics Representation in the Pseudo Phase Plane

Proceedings of the 10th Conference on Dynamical Systems Theory and Applications

Application of Fractional Calculus in Mechatronics

Fractional Calculus (FC) goes back to the beginning of the theory of differential calculus. Nevertheless, the application of FC just emerged in the last two decades. In the field of dynamical systems theory some work has been carried out but the proposed models and algorithms are still in a preliminary stage of establishment. Having these ideas in mind, the paper discusses a FC perspective in the study of the dynamics and control of mechanical systems.

Dinâmica simbólica e ferradura de Smale

Descrevemos a “ferradura de Smale”, um sistema dinâmico bem conhecido que apresenta um conjunto de propriedades muito importantes em Sistemas Dinâmicos. O estudo da dinâmica da “ferradura de Smale” permitenos entender a importância do conceito de dinâmica simbólica.

Fractional Dynamics in Forest Fires

Every year forest fires consume large areas, being a major concern in many countries like Australia, United States and Mediterranean Basin European Countries (e.g., Portugal, Spain, Italy and Greece). Understanding patterns of such events, in terms of size and spatiotemporal distributions, may help to take measures beforehand in view of possible hazards and decide strategies of fire prevention, detection and suppression. Traditional statistical tools have been used to study forest fires. Nevertheless, those tools might not be able to capture the main features of fires complex dynamics and to model fire behaviour [1]. Forest fires size-frequency distributions unveil long range correlations and long memory characteristics, which are typical of fractional order systems [2]. Those complex correlations are characterized by self-similarity and absence of characteristic length-scale, meaning that forest fires exhibit power-law (PL) behaviour. Forest fires have also been proved to exhibit time-clustering phenomena, with timescales of the order of few days [3]. In this paper, we study forest fires in the perspective of dynamical systems and fractional calculus (FC). Public domain forest fires catalogues, containing data of events occurred in Portugal, in the period 1980 up to 2011, are considered. The data is analysed in an annual basis, modelling the occurrences as sequences of Dirac impulses. The frequency spectra of such signals are determined using Fourier transforms, and approximated through PL trendlines. The PL parameters are then used to unveil the fractional-order dynamics characteristics of the data. To complement the analysis, correlation indices are used to compare and find possible relationships among the data. It is shown that the used approach can be useful to expose hidden patterns not captured by traditional tools.

Towards a Mobile Three-dimensional Modelling System for Underground Structures

Robotica 2012: 12th International Conference on Autonomous Robot Systems and Competitions April 11, 2012, Guimarães, Portugal

Combining sparse and dense methods in 6D Visual Odometry

13th International Conference on Autonomous Robot Systems (Robotica), 2013, Lisboa

Multi-robot cooperative stereo for outdoor scenarios

13th International Conference on Autonomous Robot Systems (Robotica), 2013

Da 'portugalidade' à lusofonia

Tese de Doutoramento em Ciências da Comunicação (Especialidade em Teoria da Cultura)

Homogenization of scalar field cosmologies

We summarise recent results about the evolution of linear density perturbations in scalar field cosmologies with an exponential potential. We use covariant and gauge invariant perturbation variables and a dynamical systems' approach. We establish under what conditions do the perturbations decay to the future in agreement with the cosmic no-hair conjecture.

Influência do clima afectivo induzido pelo treinador no comportamento táctico e estado afectivo dos jogadores

O presente estudo tem como objectivo perceber como o clima afectivo (positivo ou negativo) induzido pelo treinador influencia o comportamento táctico e o estado afectivo percepcionado pelos jogadores de futebol Sub-15 do Campeonato Distrital da Associação de Futebol de Lisboa. Seleccionaram-se três equipas que constituíram os três grupos do estudo: grupo de afectividade positiva (GAP), grupo de afectividade negativa (GAN) e o grupo controlo (GC). Após um pré-teste, à excepção do GC, com manifestação de afectividade neutra pelo treinador, os grupos experimentais foram submetidos a situações de afectividade positiva e negativa, durante três sessões de treino. Após este período de intervenção, realizou-se um pós-teste. Avaliou-se afectos percepcionados pelos jogadores, através da escala PANAS e o comportamento táctico, através da largura de jogo da equipa, com base na recolha de dados posicionais, verificando-se a regularidade da largura de jogo através da entropia amostral (SampEn). Foram encontradas diferenças significativas na regularidade do comportamento no GAN ̅ e ̅ mas não se encontraram diferenças nos afectos percepcionados pelos jogadores em nenhum dos grupos. Encontrou-se igualmente uma tendência positiva na largura da equipa no GAP. Os resultados sugerem que o clima afectivo do treinador apresenta-se como um constrangimento ambiental que influência o comportamento táctico dos jogadores. O clima afectivo positivo estabeleceu um aumento da largura da equipa, mostrando-se viável à procura de comportamentos adaptativos para a consecução de objectivos estabelecidos.

Detection of Babesia bigemina infection: use of a DNA probe - a review

The development of a repetitive DNA probe for Babesia bigemina was reviewed. The original plasmid (p(Bbi)16) contained an insert of B. bigemina DNA of approximately 6.3 kb. This probe has been evaluated for specificityand analytical sensitivity by dot hybridization with isolates from Mexico, the Caribbean region and Kenya. A partial restriction map has been constructed and insert fragments have been subcloned and utilized as specific DNA probes. A comparison of 32P labelled and non-radioactive DNA probes was presented. Non-radioctive detection systems that have been used include digoxigenin dUTP incorporation, and detection by colorimetric substrate methods. Derivatives from the original DNA probe have been utilized to detect B. bigemina infection in a) experimentally inoculated cattle, b) field exposed cattle, c) infected Boophilus microplus ticks, and d) the development of a PCR amplification system.

A decision-making Fokker-Planck model in computational neuroscience

Minimal models for the explanation of decision-making in computational neuroscience are based on the analysis of the evolution for the average firing rates of two interacting neuron populations. While these models typically lead to multi-stable scenario for the basic derived dynamical systems, noise is an important feature of the model taking into account finite-size effects and robustness of the decisions. These stochastic dynamical systems can be analyzed by studying carefully their associated Fokker-Planck partial differential equation. In particular, we discuss the existence, positivity and uniqueness for the solution of the stationary equation, as well as for the time evolving problem. Moreover, we prove convergence of the solution to the the stationary state representing the probability distribution of finding the neuron families in each of the decision states characterized by their average firing rates. Finally, we propose a numerical scheme allowing for simulations performed on the Fokker-Planck equation which are in agreement with those obtained recently by a moment method applied to the stochastic differential system. Our approach leads to a more detailed analytical and numerical study of this decision-making model in computational neuroscience.

Dynamic simulation of regulatory networks using SQUAD.

BACKGROUND: The ambition of most molecular biologists is the understanding of the intricate network of molecular interactions that control biological systems. As scientists uncover the components and the connectivity of these networks, it becomes possible to study their dynamical behavior as a whole and discover what is the specific role of each of their components. Since the behavior of a network is by no means intuitive, it becomes necessary to use computational models to understand its behavior and to be able to make predictions about it. Unfortunately, most current computational models describe small networks due to the scarcity of kinetic data available. To overcome this problem, we previously published a methodology to convert a signaling network into a dynamical system, even in the total absence of kinetic information. In this paper we present a software implementation of such methodology. RESULTS: We developed SQUAD, a software for the dynamic simulation of signaling networks using the standardized qualitative dynamical systems approach. SQUAD converts the network into a discrete dynamical system, and it uses a binary decision diagram algorithm to identify all the steady states of the system. Then, the software creates a continuous dynamical system and localizes its steady states which are located near the steady states of the discrete system. The software permits to make simulations on the continuous system, allowing for the modification of several parameters. Importantly, SQUAD includes a framework for perturbing networks in a manner similar to what is performed in experimental laboratory protocols, for example by activating receptors or knocking out molecular components. Using this software we have been able to successfully reproduce the behavior of the regulatory network implicated in T-helper cell differentiation. CONCLUSION: The simulation of regulatory networks aims at predicting the behavior of a whole system when subject to stimuli, such as drugs, or determine the role of specific components within the network. The predictions can then be used to interpret and/or drive laboratory experiments. SQUAD provides a user-friendly graphical interface, accessible to both computational and experimental biologists for the fast qualitative simulation of large regulatory networks for which kinetic data is not necessarily available.