MATERIALS EDUCATION AND INNOVATION: GLOBALIZATION OPENS NEW FRONTIERS, OPPORTUNITIES AND CHALLENGES

In this paper we consider evolutionary pressures that will influence materials education and its role in the present scenario of Globalization: Challenges, Opportunities and needs. The main evolutionary pressures are related to some major control variables: increase of global population, new emerging technologies such as nanotechnology, alternative energies related to climate change, multimedia convergence in global communications, health, hunger, economic asymmetries and violence. Of course, many other factors could be identified, but this paper considers these as an adequate minimum basis for strategic considerations related to current materials education planning for the 21st century. In conclusion, we propose an International Network Program for Materials Education Strategy, thinking globally but acting regionally.

Innovation and entrepreneurship in scientific research

This research wants to lay emphasis on topics that historicize and rescue concepts, in addition, shows the relation between innovation and socioeconomic development resulted; reviews the legal framework to stimulate new innovation into Brazilian society; considers the definition and the entrepreneur university's new paradigm; and finally, this research highlights the importance of teaching entrepreneur at universities, with straight society benefits. The results suggests that innovation is directly enrolled with a successful development of certain society, as well, is actually the biggest business competitive differential into corporative universe. In one way of getting results of social advancement to inform entrepreneur research practice, it appears that entrepreneurs concepts, necessarily, must be incorporated into the array of Science/Technology/Innovation for the effective development of supported formula. This article develops a thought about actual scientific researches paradigm, the way that is built on today, and if it's sufficient to effectively get the results that society expects from main bodies to create human resource and researches, especially those with innovation aspects, at Brazilian economic improvement.

Atenção domiciliar como mudança do modelo tecnoassistencial

OBJETIVO: Analisar práticas de atenção domiciliar de serviços ambulatoriais e hospitalares e sua constituição como rede substitutiva de cuidado em saúde. PROCEDIMENTOS METODOLÓGICOS: Estudo qualitativo que analisou, com base na metodologia de caso traçador, quatro serviços ambulatoriais de atenção domiciliar da Secretaria Municipal de Saúde e um serviço de um hospital filantrópico do município de Belo Horizonte, MG, entre 2005 e 2007. Foram realizadas entrevistas com gestores e equipes dos serviços de atenção domiciliar, análise de documentos e acompanhamento de casos com entrevistas a pacientes e cuidadores. A análise foi orientada pelas categorias analíticas integração da atenção domiciliar na rede de saúde e modelo tecnoassistencial. ANÁLISE DOS RESULTADOS: A implantação da atenção domiciliar foi precedida por decisão político-institucional tanto com orientação racionalizadora, buscando a diminuição de custos, quanto com vistas à reordenação tecnoassistencial das redes de cuidados. Essas duas orientações encontram-se em disputa e constituem dificuldades para conciliação dos interesses dos diversos atores envolvidos na rede e na criação de espaços compartilhados de gestão. Pôde-se identificar a inovação tecnológica e a autonomia das famílias na implementação dos projetos de cuidado. As equipes mostraram-se coesas, construindo no cotidiano do trabalho novas formas de integrar os diferentes olhares para transformação das práticas em saúde. Foram observados desafios na proposta de integrar os diferentes serviços de caráter substitutivo do cuidado ao limitar a capacidade da atenção domiciliar de mudar o modelo tecnoassistencial. CONCLUSÕES: A atenção domiciliar possui potencial para constituição de uma rede substitutiva ao produzir novos modos de cuidar que atravessam os projetos dos usuários, dos familiares, da rede social e dos trabalhadores da atenção domiciliar. A atenção domiciliar como modalidade substitutiva de atenção à saúde requer sustentabilidade política, conceitual e operacional, bem como reconhecimento dos novos arranjos e articulação das propostas em curso.

Mobility and social network effects on extremist opinions

Understanding the emergence of extreme opinions and in what kind of environment they might become less extreme is a central theme in our modern globalized society. A model combining continuous opinions and observed discrete actions (CODA) capable of addressing the important issue of measuring how extreme opinions might be has been recently proposed. In this paper I show extreme opinions to arise in a ubiquitous manner in the CODA model for a multitude of social network structures. Depending on network details reducing extremism seems to be possible. However, a large number of agents with extreme opinions is always observed. A significant decrease in the number of extremists can be observed by allowing agents to change their positions in the network.

Influence of the technological innovation degree on knowledge creation: Evidence from a Brazilian firm

The aim of this paper is to analyze the process of knowledge creation when developing high technology products in projects having various innovation degrees. The main contribution to the literature is the systematization of an approach to analyze knowledge creation during the product innovation process. Three innovation projects developed by a company specialized in industrial automation systems were investigated using case studies. The knowledge creation processes, which took place in these three projects, were analyzed comparatively. As a distinctive result of this paper, the main features of the knowledge creation processes influenced by a degree of technological innovation are identified.

Anticipation of pain enhances the nociceptive transmission and functional connectivity within pain network in rats

Background: Expectation is a very potent pain modulator in both humans and animals. There is evidence that pain transmission neurons are modulated by expectation preceding painful stimuli. Nonetheless, few studies have examined the influence of pain expectation on the pain-related neuronal activity and the functional connectivity within the central nociceptive network. Results: This study used a tone-laser conditioning paradigm to establish the pain expectation in rats, and simultaneously recorded the anterior cingulate cortex (ACC), the medial dorsal thalamus (MD), and the primary somatosensory cortex (SI) to investigate the effect of pain expectation on laser-induced neuronal responses. Cross-correlation and partial directed coherence analysis were used to determine the functional interactions within and between the recorded areas during nociceptive transmission. The results showed that under anticipation condition, the neuronal activity to the auditory cue was significantly increased in the ACC area, whereas those to actual noxious stimuli were enhanced in all the recorded areas. Furthermore, neuronal correlations within and between these areas were significantly increased under conditions of expectation compared to those under non-expectation conditions, indicating an enhanced synchronization of neural activity within the pain network. In addition, information flow from the medial (ACC and MD) to the lateral (SI cortex) pain pathway increased, suggesting that the emotion-related neural circuits may modulate the neuronal activity in the somatosensory pathway during nociceptive transmission. Conclusion: These results demonstrate that the nociceptive processing in both medial and lateral pain systems is modulated by the expectation of pain.

Border figure detection using a phase oscillator network with dynamical coupling

Oscillator networks have been developed in order to perform specific tasks related to image processing. Here we analytically investigate the existence of synchronism in a pair of phase oscillators that are short-range dynamically coupled. Then, we use these analytical results to design a network able of detecting border of black-and-white figures. Each unit composing this network is a pair of such phase oscillators and is assigned to a pixel in the image. The couplings among the units forming the network are also dynamical. Border detection emerges from the network activity.

AtPIN: Arabidopsis thaliana Protein Interaction Network

Background: Protein-protein interactions (PPIs) constitute one of the most crucial conditions to sustain life in living organisms. To study PPI in Arabidopsis thaliana we have developed AtPIN, a database and web interface for searching and building interaction networks based on publicly available protein-protein interaction datasets. Description: All interactions were divided into experimentally demonstrated or predicted. The PPIs in the AtPIN database present a cellular compartment classification (C(3)) which divides the PPI into 4 classes according to its interaction evidence and subcellular localization. It has been shown in the literature that a pair of genuine interacting proteins are generally expected to have a common cellular role and proteins that have common interaction partners have a high chance of sharing a common function. In AtPIN, due to its integrative profile, the reliability index for a reported PPI can be postulated in terms of the proportion of interaction partners that two proteins have in common. For this, we implement the Functional Similarity Weight (FSW) calculation for all first level interactions present in AtPIN database. In order to identify target proteins of cytosolic glutamyl-tRNA synthetase (Cyt-gluRS) (AT5G26710) we combined two approaches, AtPIN search and yeast two-hybrid screening. Interestingly, the proteins glutamine synthetase (AT5G35630), a disease resistance protein (AT3G50950) and a zinc finger protein (AT5G24930), which has been predicted as target proteins for Cyt-gluRS by AtPIN, were also detected in the experimental screening. Conclusions: AtPIN is a friendly and easy-to-use tool that aggregates information on Arabidopsis thaliana PPIs, ontology, and sub-cellular localization, and might be a useful and reliable strategy to map protein-protein interactions in Arabidopsis. AtPIN can be accessed at http://bioinfo.esalq.usp.br/atpin.

Particle competition for complex network community detection

In many real situations, randomness is considered to be uncertainty or even confusion which impedes human beings from making a correct decision. Here we study the combined role of randomness and determinism in particle dynamics for complex network community detection. In the proposed model, particles walk in the network and compete with each other in such a way that each of them tries to possess as many nodes as possible. Moreover, we introduce a rule to adjust the level of randomness of particle walking in the network, and we have found that a portion of randomness can largely improve the community detection rate. Computer simulations show that the model has good community detection performance and at the same time presents low computational complexity. (C) 2008 American Institute of Physics.

Generalized connectivity between any two nodes in a complex network

This article focuses on the identification of the number of paths with different lengths between pairs of nodes in complex networks and how these paths can be used for characterization of topological properties of theoretical and real-world complex networks. This analysis revealed that the number of paths can provide a better discrimination of network models than traditional network measurements. In addition, the analysis of real-world networks suggests that the long-range connectivity tends to be limited in these networks and may be strongly related to network growth and organization.

Finding Quasi-Optimal Network Topologies for Information Transmission in Active Networks

This work clarifies the relation between network circuit (topology) and behaviour (information transmission and synchronization) in active networks, e.g. neural networks. As an application, we show how one can find network topologies that are able to transmit a large amount of information, possess a large number of communication channels, and are robust under large variations of the network coupling configuration. This theoretical approach is general and does not depend on the particular dynamic of the elements forming the network, since the network topology can be determined by finding a Laplacian matrix (the matrix that describes the connections and the coupling strengths among the elements) whose eigenvalues satisfy some special conditions. To illustrate our ideas and theoretical approaches, we use neural networks of electrically connected chaotic Hindmarsh-Rose neurons.

Network of recurrent events for the Olami-Feder-Christensen model

We numerically study the dynamics of a discrete spring-block model introduced by Olami, Feder, and Christensen (OFC) to mimic earthquakes and investigate to what extent this simple model is able to reproduce the observed spatiotemporal clustering of seismicity. Following a recently proposed method to characterize such clustering by networks of recurrent events [J. Davidsen, P. Grassberger, and M. Paczuski, Geophys. Res. Lett. 33, L11304 (2006)], we find that for synthetic catalogs generated by the OFC model these networks have many nontrivial statistical properties. This includes characteristic degree distributions, very similar to what has been observed for real seismicity. There are, however, also significant differences between the OFC model and earthquake catalogs, indicating that this simple model is insufficient to account for certain aspects of the spatiotemporal clustering of seismicity.

Automatic Network Fingerprinting through Single-Node Motifs

Complex networks have been characterised by their specific connectivity patterns (network motifs), but their building blocks can also be identified and described by node-motifs-a combination of local network features. One technique to identify single node-motifs has been presented by Costa et al. (L. D. F. Costa, F. A. Rodrigues, C. C. Hilgetag, and M. Kaiser, Europhys. Lett., 87, 1, 2009). Here, we first suggest improvements to the method including how its parameters can be determined automatically. Such automatic routines make high-throughput studies of many networks feasible. Second, the new routines are validated in different network-series. Third, we provide an example of how the method can be used to analyse network time-series. In conclusion, we provide a robust method for systematically discovering and classifying characteristic nodes of a network. In contrast to classical motif analysis, our approach can identify individual components (here: nodes) that are specific to a network. Such special nodes, as hubs before, might be found to play critical roles in real-world networks.

Haplotype distribution of five nuclear genes based on network genealogies and Bayesian inference indicates that Trypanosoma cruzi hybrid strains are polyphyletic

Chagas disease is still a major public health problem in Latin America. Its causative agent, Trypanosoma cruzi, can be typed into three major groups, T. cruzi I, T. cruzi II and hybrids. These groups each have specific genetic characteristics and epidemiological distributions. Several highly virulent strains are found in the hybrid group; their origin is still a matter of debate. The null hypothesis is that the hybrids are of polyphyletic origin, evolving independently from various hybridization events. The alternative hypothesis is that all extant hybrid strains originated from a single hybridization event. We sequenced both alleles of genes encoding EF-1 alpha, actin and SSU rDNA of 26 T. cruzi strains and DHFR-TS and TR of 12 strains. This information was used for network genealogy analysis and Bayesian phylogenies. We found T. cruzi I and T. cruzi II to be monophyletic and that all hybrids had different combinations of T. cruzi I and T. cruzi II haplotypes plus hybrid-specific haplotypes. Bootstrap values (networks) and posterior probabilities (Bayesian phylogenies) of clades supporting the monophyly of hybrids were far below the 95% confidence interval, indicating that the hybrid group is polyphyletic. We hypothesize that T. cruzi I and T. cruzi II are two different species and that the hybrids are extant representatives of independent events of genome hybridization, which sporadically have sufficient fitness to impact on the epidemiology of Chagas disease.

An opinion dynamics model for the diffusion of innovations

We study the dynamics of the adoption of new products by agents with continuous opinions and discrete actions (CODA). The model is such that the refusal in adopting a new idea or product is increasingly weighted by neighbor agents as evidence against the product. Under these rules, we study the distribution of adoption times and the final proportion of adopters in the population. We compare the cases where initial adopters are clustered to the case where they are randomly scattered around the social network and investigate small world effects on the final proportion of adopters. The model predicts a fat tailed distribution for late adopters which is verified by empirical data. (C) 2009 Elsevier B.V. All rights reserved.