Formation and maintenance of complex systems

A complex system is often identified by the absence of a characteristic length, e.g. as in a fractal. A very large system subject to a fragmentation and/or aggregation dynamics passes through such complex configurations. We study statistically creation and maintenance of such configurations in space dimensions d = 1 to 5 and find that they are easily created (maintained) for small (large) d. An intermediate d such as d = 3 seems to be ideal for the creation and maintenance of complex systems. This has consequences in a statistical description of the universe.

The gradually truncated Lévy flight: Stochastic process for complex systems

Power-law distributions, i.e. Levy flights have been observed in various economical, biological, and physical systems in high-frequency regime. These distributions can be successfully explained via gradually truncated Levy flight (GTLF). In general, these systems converge to a Gaussian distribution in the low-frequency regime. In the present work, we develop a model for the physical basis for the cut-off length in GTLF and its variation with respect to the time interval between successive observations. We observe that GTLF automatically approach a Gaussian distribution in the low-frequency regime. We applied the present method to analyze time series in some physical and financial systems. The agreement between the experimental results and theoretical curves is excellent. The present method can be applied to analyze time series in a variety of fields, which in turn provide a basis for the development of further microscopic models for the system. © 2000 Elsevier Science B.V. All rights reserved.

Statistics and kinetics of single-molecule electron transfer dynamics in complex environments: A simulation model study

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

A new approach for determining stability constants of metal ion complexes in aquatic systems based on flow injection-ion exchange-flame atomic absorption spectrometry coupling

A method based an ion exchange(IE)-atomic absorption spectrometry(AAS) coupled by flow techniques, allowing the determination of formation constants of, at least, the first species of complex systems, in aqueous solution, was developed.The IE-AAS coupling reduces significantly the number of experimental steps in comparison with IE batch methods, resulting in an important increase in analytical rate. The method is simple both from experimental and computational points of view, making possible its utilization by workers without special expertise in the field of complex equilibria in solution. on the other hand, taking into account mainly the amount of hollow cathode lamps available to date, the developed procedure may be applied, within certain limitations, to the study of many systems whose features prevent the use of traditional approaches.

Nested liana-tree network in three distinct neotropical vegetation formations

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Structural FRF acquisition via electric impedance measurement applied to damage location

Continuing development of new materials makes systems lighter and stronger permitting more complex systems to provide more functionality and flexibility that demands a more effective evaluation of their structural health. Smart material technology has become an area of increasing interest in this field. The combination of smart materials and artificial neural networks can be used as an excellent tool for pattern recognition, turning their application adequate for monitoring and fault classification of equipment and structures. In order to identify the fault, the neural network must be trained using a set of solutions to its corresponding forward Variational problem. After the training process, the net can successfully solve the inverse variational problem in the context of monitoring and fault detection because of their pattern recognition and interpolation capabilities. The use of structural frequency response function is a fundamental portion of structural dynamic analysis, and it can be extracted from measured electric impedance through the electromechanical interaction of a piezoceramic and a structure. In this paper we use the FRF obtained by a mathematical model (FEM) in order to generate the training data for the neural networks, and the identification of damage can be done by measuring electric impedance, since suitable data normalization correlates FRF and electrical impedance.

Unidade e multiplicidade do tempo: uma abordagem transdisciplinar

Procurou-se, neste trabalho, pensar o tempo no contexto das ciências da saúde, no qual se entrelaçam aspectos físicos, biológicos, psicológicos e sociológicos. Enquanto em nossa percepção do mundo e de nós mesmos o tempo se apresenta sob muitas facetas, na física clássica, conforme o modelo newtoniano, assumia-se a existência de um tempo absoluto, unilinear, homogêneo e independente do observador. Com a teoria da relatividade e o estudo dos sistemas complexos, um novo conceito de tempo apresenta-se na física: o tempo fractal, o qual possibilita maior compatibilidade com as abordagens psicológicas e sociológicas. Nesta perspectiva, a experiência de vida de uma pessoa, e seus respectivos processos de construção da saúde, envolveria uma multiplicidade de tempos, que coexistem e se organizam segundo um padrão coerente de auto-similaridade. Uma quebra desse padrão estaria correlacionada com a ocorrência da doença. Sugere-se que uma abordagem mais adequada do adoecimento deveria levar em conta, como referência para o profissional de saúde, o conceito de tempo fractal, possibilitando maior sintonia do paciente com a complexidade da natureza e, por conseguinte, consigo mesmo.

In silico network topology-based prediction of gene essentiality

The identification of genes essential for survival is important for the understanding of the minimal requirements for cellular life and for drug design. As experimental studies with the purpose of building a catalog of essential genes for a given organism are time-consuming and laborious, a computational approach which could predict gene essentiality with high accuracy would be of great value. We present here a novel computational approach, called NTPGE (Network Topology-based Prediction of Gene Essentiality), that relies on the network topology features of a gene to estimate its essentiality. The first step of NTPGE is to construct the integrated molecular network for a given organism comprising protein physical, metabolic and transcriptional regulation interactions. The second step consists in training a decision-tree-based machine-learning algorithm on known essential and non-essential genes of the organism of interest, considering as learning attributes the network topology information for each of these genes. Finally, the decision-tree classifier generated is applied to the set of genes of this organism to estimate essentiality for each gene. We applied the NTPGE approach for discovering the essential genes in Escherichia coli and then assessed its performance. (C) 2007 Elsevier B.V. All rights reserved.

Determinação de parâmetros físico-químicos com um sensor potenciométrico sensível ao íon p-aminobenzoato

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Construção e aplicação físico-química de um eletrodo de segunda espécie, sensível ao íon oxalato, em meio aquoso

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Product development process: Using real options for assessments and to support the decision-making at decision gates

Enterprises need continuous product development activities to remain competitive in the marketplace. Their product development process (PDP) must manage stakeholders' needs - technical, financial, legal, and environmental aspects, customer requirements, Corporate strategy, etc. -, being a multidisciplinary and strategic issue. An approach to use real option to support the decision-making process at PDP phases in taken. The real option valuation method is often presented as an alternative to the conventional net present value (NPV) approach. It is based on the same principals of financial options: the right to buy or sell financial values (mostly stocks) at a predetermined price, with no obligation to do so. In PDP, a multi-period approach that takes into account the flexibility of, for instance, being able to postpone prototyping and design decisions, waiting for more information about technologies, customer acceptance, funding, etc. In the present article, the state of the art of real options theory is prospected and a model to use the real options in PDP is proposed, so that financial aspects can be properly considered at each project phase of the product development. Conclusion is that such model can provide more robustness to the decisions processes within PDP.

Long term economic relationships from cointegration maps

We employ the Bayesian framework to define a cointegration measure aimed to represent long term relationships between time series. For visualization of these relationships we introduce a dissimilarity matrix and a map based on the sorting points into neighborhoods (SPIN) technique, which has been previously used to analyze large data sets from DNA arrays. We exemplify the technique in three data sets: US interest rates (USIR), monthly inflation rates and gross domestic product (GDP) growth rates. (c) 2007 Elsevier B.V. All rights reserved.

Power-law distribution in a learning process: competition, learning and natural selection

In the present work, we propose a model for the statistical distribution of people versus number of steps acquired by them in a learning process, based on competition, learning and natural selection. We consider that learning ability is normally distributed. We found that the number of people versus step acquired by them in a learning process is given through a power law. As competition, learning and selection is also at the core of all economical and social systems, we consider that power-law scaling is a quantitative description of this process in social systems. This gives an alternative thinking in holistic properties of complex systems. (C) 2004 Elsevier B.V. All rights reserved.

Tsallis statistics and gradually truncated Levy flight - distribution of an economical index

Tsallis postulated a generalized form for entropy and give rise to a new statistics now known as Tsallis statistics. In the present work, we compare the Tsallis statistics with the gradually truncated Levy flight, and discuss the distribution of an economical index-the Standard and Poor's 500-using the values of standard deviation as calculated by our model. We find that both statistics give almost the same distribution. Thus we feel that gradual truncation of Levy distribution, after certain critical step size for describing complex systems, is a requirement of generalized thermodynamics or similar. The gradually truncated Levy flight is based on physical considerations and bring a better physical picture of the dynamics of the whole system. Tsallis statistics gives a theoretical support. Both statistics together can be utilized for the development of a more exact portfolio theory or to understand better the complexities in human and financial behaviors. A comparison of both statistics is made. (C) 2002 Published by Elsevier B.V. B.V.

Size limiting in Tsallis statistics

Power law scaling is observed in many physical, biological and socio-economical complex systems and is now considered an important property of these systems. In general, power law exists in the central part of the distribution. It has deviations from power law for very small and very large variable sizes. Tsallis, through non-extensive thermodynamics, explained power law distribution in many cases including deviation from the power law. In case of very large steps, the used the heuristic crossover approach. In the present we present an alternative model in which we consider that the entropy factor 9 decreases with variable size due to the softening of long range interactions or memory. We apply this model for distribution of citation index of scientists and examination scores and are able to explain the distribution for entire variable range. In the present model, we can have very sharp cut-off without interfering with power law in its central part as observed in many cases. (C) 2008 Elsevier B.V. All rights reserved.