Local Computation in Credal Networks

The goal of this contribution is to discuss local computation in credal networks — graphical models that can represent imprecise and indeterminate probability values. We analyze the inference problem in credal networks, discuss how inference algorithms can benefit from local computation, and suggest that local computation can be particularly important in approximate inference algorithms.

Evolutionary diversification in Central Brazil: where Amazonia and Cerrado meet

Apesar da fauna de mamíferos Neotropicais ser uma das mais ricas do mundo, o nosso conhecimento sobre os limites de espécies, distribuições geográficas e relações filogenéticas está ainda agora no seu início. As áreas de transição entre os dois maiores biomas da América do Sul, o Cerrado e a Amazónia, são ainda menos conhecidas. Até ao momento, escassos estudos focaram os pequenos mamíferos destas áreas. Destes estudos, apenas dois apresentam dados taxonómicos e de distribuição geográfica de uma lista de espécies reduzida e, nenhum é focado nos processos evolutivos que conduziram à diversidade destas áreas. O presente trabalho tem como objectivo aumentar o conhecimento básico sobre a diversidade do médio Rio Araguaia, na região central do Brasil, através da amostragem e análise de espécies de pequenos mamíferos, integrando um intenso trabalho de campo, de laboratório e de museu. Desta forma, um total de 22 espécies é registado para o médio Araguaia. De entre estas espécies, descreve-se uma espécie nova de Rhipidomys, regista-se uma espécie não descrita de Thrichomys e uma potencial nova forma de Oligoryzomys, e também se apresenta uma diagnose emendada do obscuro Oecomys cleberi. Para cada espécie, são também descritas as suas características morfológicas e resumem-se os seus aspectos de distribuição geográfica e história natural. Para os quatro géneros acima referidos, são apresentadas as análises filogenéticas que permitem a identificação das espécies. Adicionalmente, os princípios da filogeografia são aplicados para estudar os padrões da distribuição geográfica da diversidade genética de três roedores sigmodontíneos e seis marsupiais didelphídeos. Os resultados obtidos demonstram que o Rio Araguaia forma uma barreira geográfica para espécies especialistas em florestas não-alagáveis; por outro lado, espécies generalistas apresentam partilha de haplótipos em ambas as margens do rio. Argumentamos também que os refúgios florestais e os gradientes poderão ter tido um papel importante para moldar a estrutura genética de populações de pequenos mamíferos no Brasil central. Em suma, os resultados apresentados corroboram a proposição de que a diversidade Neotropical não poderá ser explicada através de um único modelo de especiação e que estes não são mutuamente exclusivos. O entendimento integral dos processos ecológicos e históricos que deram origem à fauna Neotropical, assim como a continuidade de estudos sistemáticos, depende da realização de novas amostragens e consequente enriquecimento dos museus com colecções apropriadas.

Synthesis in the human evolutionary behavioural sciences

Over the last three decades, the application of evolutionary theory to the human sciences has shown remarkable growth. This growth has also been characterised by a ‘splitting’ process, with the emergence of distinct sub-disciplines, most notably: Human Behavioural Ecology (HBE), Evolutionary Psychology (EP) and studies of Cultural Evolution (CE). Multiple applications of evolutionary ideas to the human sciences are undoubtedly a good thing, demonstrating the usefulness of this approach to human affairs. However, this fracture has been associated with considerable tension, a lack of integration, and sometimes outright conflict between researchers. In recent years however, there have been clear signs of hope that a synthesis of the human evolutionary behavioural sciences is underway. Here, we briefly review the history of the debate, both its theoretical and practical causes; then provide evidence that the field is currently becoming more integrated, as the traditional boundaries between sub-disciplines become blurred. This article constitutes the first paper under the new editorship of the Journal of Evolutionary Psychology, which aims to further this integration by explicitly providing a forum for integrated work.

Fuzzy model identification by evolutionary, gradient based and memtic algorithms

One of the crucial problems of fuzzy rule modeling is how to find an optimal or at least a quasi-optimal rule base fro a certain system. In most applications there is no human expert available, or, the result of a human expert's decision is too much subjective and is not reproducible, thus some automatic method to determine the fuzzy rule base must be deployed.

Design of neuro-fuzzy models by evolutionary and gradient-based algorithms

All systems found in nature exhibit, with different degrees, a nonlinear behavior. To emulate this behavior, classical systems identification techniques use, typically, linear models, for mathematical simplicity. Models inspired by biological principles (artificial neural networks) and linguistically motivated (fuzzy systems), due to their universal approximation property, are becoming alternatives to classical mathematical models. In systems identification, the design of this type of models is an iterative process, requiring, among other steps, the need to identify the model structure, as well as the estimation of the model parameters. This thesis addresses the applicability of gradient-basis algorithms for the parameter estimation phase, and the use of evolutionary algorithms for model structure selection, for the design of neuro-fuzzy systems, i.e., models that offer the transparency property found in fuzzy systems, but use, for their design, algorithms introduced in the context of neural networks. A new methodology, based on the minimization of the integral of the error, and exploiting the parameter separability property typically found in neuro-fuzzy systems, is proposed for parameter estimation. A recent evolutionary technique (bacterial algorithms), based on the natural phenomenon of microbial evolution, is combined with genetic programming, and the resulting algorithm, bacterial programming, advocated for structure determination. Different versions of this evolutionary technique are combined with gradient-based algorithms, solving problems found in fuzzy and neuro-fuzzy design, namely incorporation of a-priori knowledge, gradient algorithms initialization and model complexity reduction.

Cloning of the Bone Gla Protein gene from the teleost fish Sparus aurata (gilthead seabream). Molecular organization, developmental appearance and evolutionary implications

Tese de Doutoramento, Biologia Molecular, Faculdade de Ciências do Mar e do Ambiente, Universidade do Algarve, 2001

LMP based bid formation for virtual power players operating in smart grids

Power system organization has gone through huge changes in the recent years. Significant increase in distributed generation (DG) and operation in the scope of liberalized markets are two relevant driving forces for these changes. More recently, the smart grid (SG) concept gained increased importance, and is being seen as a paradigm able to support power system requirements for the future. This paper proposes a computational architecture to support day-ahead Virtual Power Player (VPP) bid formation in the smart grid context. This architecture includes a forecasting module, a resource optimization and Locational Marginal Price (LMP) computation module, and a bid formation module. Due to the involved problems characteristics, the implementation of this architecture requires the use of Artificial Intelligence (AI) techniques. Artificial Neural Networks (ANN) are used for resource and load forecasting and Evolutionary Particle Swarm Optimization (EPSO) is used for energy resource scheduling. The paper presents a case study that considers a 33 bus distribution network that includes 67 distributed generators, 32 loads and 9 storage units.

Evolutionary trajectory optimization for redundant robots

The trajectory planning of redundant robots is an important area of research and efficient optimization algorithms have been investigated in the last years. This paper presents a new technique that combines the closed-loop pseudoinverse method with genetic algorithms. In this case the trajectory planning is formulated as an optimization problem with constraints.

An evolutionary approach for the motion planning of redundant and hyper-redundant manipulators

The trajectory planning of redundant robots is an important area of research and efficient optimization algorithms are needed. The pseudoinverse control is not repeatable, causing drift in joint space which is undesirable for physical control. This paper presents a new technique that combines the closed-loop pseudoinverse method with genetic algorithms, leading to an optimization criterion for repeatable control of redundant manipulators, and avoiding the joint angle drift problem. Computer simulations performed based on redundant and hyper-redundant planar manipulators show that, when the end-effector traces a closed path in the workspace, the robot returns to its initial configuration. The solution is repeatable for a workspace with and without obstacles in the sense that, after executing several cycles, the initial and final states of the manipulator are very close.

On the numerical computation of the Mittag-Leffler function

Recently simple limiting functions establishing upper and lower bounds on the Mittag-Leffler function were found. This paper follows those expressions to design an efficient algorithm for the approximate calculation of expressions usual in fractional-order control systems. The numerical experiments demonstrate the superior efficiency of the proposed method.

On the numerical computation of the Mittag-Leffler function

Recently simple limiting functions establishing upper and lower bounds on the Mittag-Leffler function were found. This paper follows those expressions to design an efficient algorithm for the approximate calculation of expressions usual in fractional-order control systems. The numerical experiments demonstrate the superior efficiency of the proposed method.

Spatial neighborhood matrix computation: Inverse distance weighted versus binary contiguity

Paper presented at Geo-Spatial Crossroad GI_Forum, Salzburg, Austria.

An integrated approach to Physcomitrella patens transcriptomics reveals importantclues of the evolutionary development of plant organs and sexual reproduction

Land plant evolution required the generation of a new body plan that could resist the harsher and fluctuating environmental conditions found outside of aquatic environments. Unraveling the genetic basis of plant developmental innovations is not only revealing in terms of an evolutionary point of view, but it is also important for understanding the emergence of agronomically important traits. Comparative genetic studies between basal and modern land plants, both at the genome and trancriptome levels, can help in the generation of hypotheses related to the genetic basis of plant evolutionary development.(...)

Evolutionary dynamics of Chlamydia trachomatis genome and identification of molecular patterns of hypothetical protein coding genes

The obligate intracellular bacterium Chlamydia trachomatis is a human pathogen of major public health significance. Strains can be classified into 15 main serovars (A to L3) that preferentially cause ocular infections (A-C), genital infections (D-K) or lymphogranuloma venereum (LGV) (L1-L3), but the molecular basis behind their distinct tropism, ecological success and pathogenicity is not welldefined. Most chlamydial research demands culture in eukaryotic cell lines, but it is not known if stains become laboratory adapted. By essentially using genomics and transcriptomics, we aimed to investigate the evolutionary patterns underlying the adaptation of C. trachomatis to the different human tissues, given emphasis to the identification of molecular patterns of genes encoding hypothetical proteins, and to understand the adaptive process behind the C. trachomatis in vivo to in vitro transition. Our results highlight a positive selection-driven evolution of C. trachomatis towards nichespecific adaptation, essentially targeting host-interacting proteins, namely effectors and inclusion membrane proteins, where some of them also displayed niche-specific expression patterns. We also identified potential "ocular-specific" pseudogenes, and pointed out the major gene targets of adaptive mutations associated with LGV infections. We further observed that the in vivo-derived genetic makeup of C. trachomatis is not significantly compromised by its long-term laboratory propagation. In opposition, its introduction in vitro has the potential to affect the phenotype, likely yielding virulence attenuation. In fact, we observed a "genital-specific" rampant inactivation of the virulence gene CT135, which may impact the interpretation of data derived from studies requiring culture. Globally, the findings presented in this Ph.D. thesis contribute for the understanding of C.trachomatis adaptive evolution and provides new insights into the biological role of C. trachomatishypothetical proteins. They also launch research questions for future functional studies aiming toclarify the determinants of tissue tropism, virulence or pathogenic dissimilarities among C. trachomatisstrains.

Nutritional plasticity and evolutionary divergence in the Drosophila ovary

The environment can modify developmental trajectories and generate a range of distinct phenotypes without altering an organism’s genome, a widespread phenomenon called developmental plasticity. The past decades have seen a resurgent interest in understanding how developmental plasticity contributes to evolutionary processes, as it can produce phenotypic variation among individuals and facilitate diversification among populations that inhabit distinct ecological niches. To better understand the importance of plastic responses for evolutionary change, we need to explore how the environment alters development to produce phenotypic variation and then compare this to how genetic variation influences these same developmental processes.(...)