Industrial policy and development

Includes bibliography

O ensino de evolução biológica no nível médio: investigando concepções de professores de biologia

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Relação entre gênero e orientação sexual a partir da perspectiva evolucionista

Este estudo trata da relação entre gênero e orientação sexual a partir da perspectiva interacionista da Psicologia Evolucionista e da análise de diferentes elementos da sexualidade humana. Procurou-se discutir a literatura existente sobre os conceitos de gênero e de orientação sexual, com base nos quatro porquês da Etologia. Propõe-se a existência de múltiplas origens para a orientação sexual, sendo uma delas relacionada aos padrões típicos de gênero e à identidade de gênero. Isso levaria à identificação com indivíduos do mesmo sexo ou do sexo oposto e, consequentemente, à atração pelo grupo diferente daquele com o qual se desenvolveu a identificação. Essa perspectiva integra pré-disposições biológicas à análise de influências culturais, compreendendo, como complementares, vertentes teóricas usualmente tidas como contraditórias.

Geoparks in Brazil-strategy of Geoconservation and Development

Within the framework of the potential of geopark development and the interest of the geological community in creating new areas for geoconservation in Brazil, the aim of this contribution is to show the importance of geoscience education as a strategy for both geoconservation and development, and for the success and maintenance of new geoparks. A historical and evolutionary approach to the theme reveals the current status of geoscience education in Brazil and offers a panorama of the challenges inherent in preparing for the creation of new geoconservation areas. Proposals that aim to promote geoconservation and sustainability in Brazil include projects that capitalize on geological heritage and its relationship with local communities, proposals that form partnerships between the government, universities, businesses, and non-governmental organizations for the development of education, and changes in the law specifically aimed at geoconservation. Improvement in the educational system, including Earth science education, is undoubtedly one of the best strategies to promote the preservation of our natural heritage, and a cultural change in education will certainly promote changes in other areas.

A multi-objective adaptive immune algorithm for multi-application NoC mapping

Current SoC design trends are characterized by the integration of larger amount of IPs targeting a wide range of application fields. Such multi-application systems are constrained by a set of requirements. In such scenario network-on-chips (NoC) are becoming more important as the on-chip communication structure. Designing an optimal NoC for satisfying the requirements of each individual application requires the specification of a large set of configuration parameters leading to a wide solution space. It has been shown that IP mapping is one of the most critical parameters in NoC design, strongly influencing the SoC performance. IP mapping has been solved for single application systems using single and multi-objective optimization algorithms. In this paper we propose the use of a multi-objective adaptive immune algorithm (M(2)AIA), an evolutionary approach to solve the multi-application NoC mapping problem. Latency and power consumption were adopted as the target multi-objective functions. To compare the efficiency of our approach, our results are compared with those of the genetic and branch and bound multi-objective mapping algorithms. We tested 11 well-known benchmarks, including random and real applications, and combines up to 8 applications at the same SoC. The experimental results showed that the M(2)AIA decreases in average the power consumption and the latency 27.3 and 42.1 % compared to the branch and bound approach and 29.3 and 36.1 % over the genetic approach.

Emergence of sensory selection mechanisms in Artificial Life simulations

Background The evolutionary advantages of selective attention are unclear. Since the study of selective attention began, it has been suggested that the nervous system only processes the most relevant stimuli because of its limited capacity [1]. An alternative proposal is that action planning requires the inhibition of irrelevant stimuli, which forces the nervous system to limit its processing [2]. An evolutionary approach might provide additional clues to clarify the role of selective attention. Methods We developed Artificial Life simulations wherein animals were repeatedly presented two objects, "left" and "right", each of which could be "food" or "non-food." The animals' neural networks (multilayer perceptrons) had two input nodes, one for each object, and two output nodes to determine if the animal ate each of the objects. The neural networks also had a variable number of hidden nodes, which determined whether or not it had enough capacity to process both stimuli (Table 1). The evolutionary relevance of the left and the right food objects could also vary depending on how much the animal's fitness was increased when ingesting them (Table 1). We compared sensory processing in animals with or without limited capacity, which evolved in simulations in which the objects had the same or different relevances. Table 1. Nine sets of simulations were performed, varying the values of food objects and the number of hidden nodes in the neural networks. The values of left and right food were swapped during the second half of the simulations. Non-food objects were always worth -3. The evolution of neural networks was simulated by a simple genetic algorithm. Fitness was a function of the number of food and non-food objects each animal ate and the chromosomes determined the node biases and synaptic weights. During each simulation, 10 populations of 20 individuals each evolved in parallel for 20,000 generations, then the relevance of food objects was swapped and the simulation was run again for another 20,000 generations. The neural networks were evaluated by their ability to identify the two objects correctly. The detectability (d') for the left and the right objects was calculated using Signal Detection Theory [3]. Results and conclusion When both stimuli were equally relevant, networks with two hidden nodes only processed one stimulus and ignored the other. With four or eight hidden nodes, they could correctly identify both stimuli. When the stimuli had different relevances, the d' for the most relevant stimulus was higher than the d' for the least relevant stimulus, even when the networks had four or eight hidden nodes. We conclude that selection mechanisms arose in our simulations depending not only on the size of the neuron networks but also on the stimuli's relevance for action.

Dissecting Arabidopsis Gß signal transduction on the protein surface.

The heterotrimeric G-protein complex provides signal amplification and target specificity. The Arabidopsis (Arabidopsis thaliana) G?-subunit of this complex (AGB1) interacts with and modulates the activity of target cytoplasmic proteins. This specificity resides in the structure of the interface between AGB1 and its targets. Important surface residues of AGB1, which were deduced from a comparative evolutionary approach, were mutated to dissect AGB1-dependent physiological functions. Analysis of the capacity of these mutants to complement well-established phenotypes of G?-null mutants revealed AGB1 residues critical for specific AGB1-mediated biological processes, including growth architecture, pathogen resistance, stomata-mediated leaf-air gas exchange, and possibly photosynthesis. These findings provide promising new avenues to direct the finely tuned engineering of crop yield and traits.

Modelagem e simulação de redes em chip sem fio.

O paradigma das redes em chip (NoCs) surgiu a fim de permitir alto grau de integração entre vários núcleos de sistemas em chip (SoCs), cuja comunicação é tradicionalmente baseada em barramentos. As NoCs são definidas como uma estrutura de switches e canais ponto a ponto que interconectam núcleos de propriedades intelectuais (IPs) de um SoC, provendo uma plataforma de comunicação entre os mesmos. As redes em chip sem fio (WiNoCs) são uma abordagem evolucionária do conceito de rede em chip (NoC), a qual possibilita a adoção dos mecanismos de roteamento das NoCs com o uso de tecnologias sem fio, propondo a otimização dos fluxos de tráfego, a redução de conectores e a atuação em conjunto com as NoCs tradicionais, reduzindo a carga nos barramentos. O uso do roteamento dinâmico dentro das redes em chip sem fio permite o desligamento seletivo de partes do hardware, o que reduz a energia consumida. Contudo, a escolha de onde empregar um link sem fio em uma NoC é uma tarefa complexa, dado que os nós são pontes de tráfego os quais não podem ser desligados sem potencialmente quebrar uma rota preestabelecida. Além de fornecer uma visão sobre as arquiteturas de NoCs e do estado da arte do paradigma emergente de WiNoC, este trabalho também propõe um método de avaliação baseado no já consolidado simulador ns-2, cujo objetivo é testar cenários híbridos de NoC e WiNoC. A partir desta abordagem é possível avaliar diferentes parâmetros das WiNoCs associados a aspectos de roteamento, aplicação e número de nós envolvidos em redes hierárquicas. Por meio da análise de tais simulações também é possível investigar qual estratégia de roteamento é mais recomendada para um determinado cenário de utilização, o que é relevante ao se escolher a disposição espacial dos nós em uma NoC. Os experimentos realizados são o estudo da dinâmica de funcionamento dos protocolos ad hoc de roteamento sem fio em uma topologia hierárquica de WiNoC, seguido da análise de tamanho da rede e dos padrões de tráfego na WiNoC.

Evaluating the performance of a EuroDivisia index using artificial intelligence techniques

We compare two methods in order to predict inflation rates in Europe. One method uses a standard back propagation neural network and the other uses an evolutionary approach, where the network weights and the network architecture is evolved. Results indicate that back propagation produces superior results. However, the evolving network still produces reasonable results with the advantage that the experimental set-up is minimal. Also of interest is the fact that the Divisia measure of money is superior as a predictive tool over simple sum.

Evaluating the performance of a EuroDivisia index using artificial intelligence techniques

This paper compares two methods to predict in°ation rates in Europe. One method uses a standard back propagation neural network and the other uses an evolutionary approach, where the network weights and the network architecture are evolved. Results indicate that back propagation produces superior results. However, the evolving network still produces reasonable results with the advantage that the experimental set-up is minimal. Also of interest is the fact that the Divisia measure of money is superior as a predictive tool over simple sum.

On Solving the Maximum Betweenness Problem Using Genetic Algorithms

In this paper a genetic algorithm (GA) is applied on Maximum Betweennes Problem (MBP). The maximum of the objective function is obtained by finding a permutation which satisfies a maximal number of betweenness constraints. Every permutation considered is genetically coded with an integer representation. Standard operators are used in the GA. Instances in the experimental results are randomly generated. For smaller dimensions, optimal solutions of MBP are obtained by total enumeration. For those instances, the GA reached all optimal solutions except one. The GA also obtained results for larger instances of up to 50 elements and 1000 triples. The running time of execution and finding optimal results is quite short.

Tourism in Albarracín and Region. Local Public Action and dynamics in recent key sustainable tourism development

Spanish tourist destinations in rural areas have been established over more than two decades of implementation of various public policy instruments (mainly tourism and rural development policies). These convey complementary objectives in theory but provoke distant results in practice. The intervention of these instruments produces in the region of Sierra de Albarracín (Teruel) two types of destination whose sustainability is committed: the historical urban site of Albarracín as a consolidated cultural tourism destination based on heritage and the Sierra as a generic and incipient destination of rural tourism. It is discussed how the deployment of the local public action causes a fragmented territory in two models of management and tourism development. Cooperation is presented as a key element for the necessary rethinking of tourism development in the region.

Molecular biology of prolactin and prolactin receptor in a marine teleost: the sea bream(Sparus aurata)

Tese de dout. em Biologia, especialidade de Biologia Molecular, Unidade de Ciências e Tecnologias dos Recursos Aquáticos, Univ. do Algarve

A simulation-based evolutionary multiobjective approach to manufacturing cell formation

The purpose of this paper is to propose a multiobjective optimization approach for solving the manufacturing cell formation problem, explicitly considering the performance of this said manufacturing system. Cells are formed so as to simultaneously minimize three conflicting objectives, namely, the level of the work-in-process, the intercell moves and the total machinery investment. A genetic algorithm performs a search in the design space, in order to approximate to the Pareto optimal set. The values of the objectives for each candidate solution in a population are assigned by running a discrete-event simulation, in which the model is automatically generated according to the number of machines and their distribution among cells implied by a particular solution. The potential of this approach is evaluated via its application to an illustrative example, and a case from the relevant literature. The obtained results are analyzed and reviewed. Therefore, it is concluded that this approach is capable of generating a set of alternative manufacturing cell configurations considering the optimization of multiple performance measures, greatly improving the decision making process involved in planning and designing cellular systems. (C) 2010 Elsevier Ltd. All rights reserved.

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.(...)