Morphology of polymer networks formed in the chiral and non chiral phases of an anti-ferroelectric liquid crystal

We introduced photo-polymer networks into the various liquid crystalline phases of the antiferroelectric liquid crystal AS612 and studied the effects of these networks by measuring the temperature dependence of the Bragg wavelengths selectively reflected. After polymerization, the decrease in Bragg wavelengths with respect to the original values is consistent with a shorter helical pitch due to polymer network shrinkage. Also, by removing the liquid crystalline material, we are able to image the residual polymer network using scanning electron microscopy and polarized light microscopy. The polymer strands are a few microns thick and the networks show both chiral and non-chiral features.

Exploiting thermally-reversible chemistry for controlling the crosslinking of polymer networks

High explosives are highly sensitive to accidental detonation by impact, fire, shrapnel and small arms fire. This sensitivity can be reduced by storing the energetic material within a rubbery polymer matrix and are known as plastic bonded explosives (PBX). The current procedure used to manufacture PBX involves mixing the energetic material with a hydroxy-functionalised aliphatic polymer. Upon the addition of an isocyanate crosslinker an immediate polymerisation occurs and thus the rapidly curing mixture must be used to fill the missile or shells, referred to as ‘stores’. This process can lead to poor distribution of the crosslinker resulting in the formation of an inhomogeneously crosslinked matrix and the formation of voids. One solution to this problem involves containing the crosslinker within polyurethane microcapsules that are uniformly dispersed in the explosive-polymer mixture. Upon the application of a stimulus the crosslinker can be released from the microcapsules and the formation of a uniformly crosslinked PBX achieved. Herein is reported the design and synthesis of polyurethane microcapsules that release isocyanate crosslinkers when desired using a thermal stimulus. This has been achieved by exploiting the thermally-reversible nature of oxime-urethane and Diels-Alder adducts that have been incorporated into the shell wall of the microcapsules. An alternative approach to controlling the polymerisation of PBX materials has also been achieved using thermally-reversible blocked isocyanates that regenerate the isocyanate crosslinker when exposed to heat.

MODELING THE EVOLUTION OF COMPLEX NETWORKS THROUGH THE PATH-STAR TRANSFORMATION AND OPTIMAL MULTIVARIATE METHODS

The topology of real-world complex networks, such as in transportation and communication, is always changing with time. Such changes can arise not only as a natural consequence of their growth, but also due to major modi. cations in their intrinsic organization. For instance, the network of transportation routes between cities and towns ( hence locations) of a given country undergo a major change with the progressive implementation of commercial air transportation. While the locations could be originally interconnected through highways ( paths, giving rise to geographical networks), transportation between those sites progressively shifted or was complemented by air transportation, with scale free characteristics. In the present work we introduce the path-star transformation ( in its uniform and preferential versions) as a means to model such network transformations where paths give rise to stars of connectivity. It is also shown, through optimal multivariate statistical methods (i.e. canonical projections and maximum likelihood classification) that while the US highways network adheres closely to a geographical network model, its path-star transformation yields a network whose topological properties closely resembles those of the respective airport transportation network.

Comparison of the interactomic networks of different species in terms of accessibility

Protein-protein interaction networks were investigated in terms of outward accessibility, which quantifies the effectiveness of each protein in accessing other proteins and is related to the internality of nodes. By comparing the accessibility between 144 ortholog proteins in yeast and the fruit fly, we found that the accessibility tends to be higher among proteins in the fly than in yeast. In addition, z-scores of the accessibility calculated for different species revealed that the protein networks of less evolved species tend to be more random than those of more evolved species. The accessibility was also used to identify the border of the yeast protein interaction network, which was found to be mainly composed of viable proteins.

On the efficiency of data representation on the modeling and characterization of complex networks

Specific choices about how to represent complex networks can have a substantial impact on the execution time required for the respective construction and analysis of those structures. In this work we report a comparison of the effects of representing complex networks statically by adjacency matrices or dynamically by adjacency lists. Three theoretical models of complex networks are considered: two types of Erdos-Renyi as well as the Barabasi-Albert model. We investigated the effect of the different representations with respect to the construction and measurement of several topological properties (i.e. degree, clustering coefficient, shortest path length, and betweenness centrality). We found that different forms of representation generally have a substantial effect on the execution time, with the sparse representation frequently resulting in remarkably superior performance. (C) 2011 Elsevier B.V. All rights reserved.

Artificial Neural Networks and the Study of the Psychoactivity of Cannabinoid Compounds

Cannabinoid compounds have widely been employed because of its medicinal and psychotropic properties. These compounds are isolated from Cannabis sativa (or marijuana) and are used in several medical treatments, such as glaucoma, nausea associated to chemotherapy, pain and many other situations. More recently, its use as appetite stimulant has been indicated in patients with cachexia or AIDS. In this work, the influence of several molecular descriptors on the psychoactivity of 50 cannabinoid compounds is analyzed aiming one obtain a model able to predict the psychoactivity of new cannabinoids. For this purpose, initially, the selection of descriptors was carried out using the Fisher`s weight, the correlation matrix among the calculated variables and principal component analysis. From these analyses, the following descriptors have been considered more relevant: E(LUMO) (energy of the lowest unoccupied molecular orbital), Log P (logarithm of the partition coefficient), VC4 (volume of the substituent at the C4 position) and LP1 (Lovasz-Pelikan index, a molecular branching index). To follow, two neural network models were used to construct a more adequate model for classifying new cannabinoid compounds. The first model employed was multi-layer perceptrons, with algorithm back-propagation, and the second model used was the Kohonen network. The results obtained from both networks were compared and showed that both techniques presented a high percentage of correctness to discriminate psychoactive and psychoinactive compounds. However, the Kohonen network was superior to multi-layer perceptrons.

A note on convergence of Peck-Shell and Green-Lin mechanisms in the Diamond-Dybvig model

We study the effects of population size in the Peck-Shell analysis of bank runs. We find that a contract featuring equal-treatment for almost all depositors of the same type approximates the optimum. Because the approximation also satisfies Green-Lin incentive constraints, when the planner discloses positions in the queue, welfare in these alternative specifications are sandwiched. Disclosure, however, it is not needed since our approximating contract is not subject to runs.

The role of media networks in compensating political biases: evidence from radio networks in Brazil

A central question in political economy is how to incentivize elected socials to allocate resources to those that need them the most. Research has shown that, while electoral incentives lead central governments to transfer fewer funds to non-aligned constituencies, media presence is instrumental in promoting a better allocation of resources. This study evaluates how these two phenomena interact by analyzing the role of media in compensating political biases. In particular, we analyze how media presence, connectivity and ownership affect the distribution of federal drought relief transfers to Brazilian municipalities. We find that municipalities that are not aligned with the federal government have a lower probability of receiving funds conditional on experiencing low precipitation. However, we show that the presence of radio stations compensates for this bias. This effect is driven by municipalities that have radio stations connected to a regional network rather than by the presence of local radio stations. In addition, the effect of network-connected radio stations increases with their network coverage. These findings suggests that the connection of a radio station to a network is important because it increases the salience of disasters, making it harder for the federal government to ignore non-allies. We show that our findings are not explained by the ownership and manipulation of media by politicians.

Business support networks for social businesses: a study of the Brazilian ecosystem

Negócios sociais, empresas autossuficientes com objetivos principalmente sociais estão a surgir e a mudar o cenário económico mundial. No Brasil, o campo de Empreendedorismo Social promete ajudar a resolver os vários problemas sociais do país, mas tal promessa depende do desenvolvimento de um ecossistema de suporte. No entanto, a pesquisa desenvolvida no tópico ainda é limitada, especialmente quando considerando pesquisa em contextos macro como estruturas de suporte ao negócio. O presente estudo explora o ecossistema de suporte aos negócios sociais no Brasil, oferecendo uma análise qualitativa preliminar da eficácia da rede de suporte existente para os negócios sociais, de acordo com as perceções de empreendedores sociais e prestadores de suporte. O estudo é desenvolvido baseando-se no modelo conceptual de Turrini et al. (2010) sobre os determinantes de eficácia de redes a fim de facilitar a captura de padrões. Desta forma, cada variável de eficácia de redes é desenvolvida no contexto da presente investigação e as principais conclusões relativas ao ecossistema de suporte para negócios sociais no Brasil são destacadas. Os resultados sugerem um rápido crescimento da disponibilidade de suporte para negócios sociais, mas indicam que estes serviços ainda são em número limitado e concentrados no Sudeste do país. Adicionalmente, os serviços de suporte são percecionados pelos empreendedores sociais como serviços de alta qualidade e embora se observe um sentimento generalizado de que a colaboração entre organizações de suporte tem sido importante para a construção do campo, os resultados indicam que um maior nível de interação e formalização entre prestadores de suporte levaria a maiores níveis de criação de sinergias e potenciaria a construção do ecossistema. Por último, é observado um sentimento generalizado de que o crescente nível de recursos financeiros, consciência pública e apoio do governo ao campo impactarão positivamente o desenvolvimento do ecossistema.

Windows of opportunities and knowledge networks: implications for the catch-up in developing countries

This document represents a doctoral thesis held under the Brazilian School of Public and Business Administration of Getulio Vargas Foundation (EBAPE/FGV), developed through the elaboration of three articles. The research that resulted in the articles is within the scope of the project entitled “Windows of opportunities and knowledge networks: implications for catch-up in developing countries”, funded by Support Programme for Research and Academic Production of Faculty (ProPesquisa) of Brazilian School of Public and Business Administration (EBAPE) of Getulio Vargas Foundation.

Stability and convergence analysis of a neural model applied in nonlinear systems optimization

A neural model for solving nonlinear optimization problems is presented in this paper. More specifically, a modified Hopfield network is developed and its internal parameters are computed using the valid-subspace technique. These parameters guarantee the convergence of the network to the equilibrium points that represent an optimal feasible solution. The network is shown to be completely stable and globally convergent to the solutions of nonlinear optimization problems. A study of the modified Hopfield model is also developed to analyze its stability and convergence. Simulation results are presented to validate the developed methodology.

Prediction via neural networks of the residual hydrogen peroxide used in photo-fenton processes for effluent treatment

This communication proposes the use of neural networks in the prediction of residual concentrations of hydrogen peroxide from the treatment of effluents through Advanced Oxidative Processes (AOP's), in particular, the photo-Fenton process. To verify the efficiency of the oxidative process, the Chemical Oxygen Demand (COD) parameter, the values of which may be modified by the presence of oxidizing agents such as residual hydrogen peroxide, is frequently taken in account. The analysis of the H2O2 interference was performed by spectrophotometry at 450 nm wavelength, via the monitoring of the reaction of ammonia with metavanadate. The results of the hydrogen peroxide residual concentration were modeled via a feedforward neural network, with the correlation coefficients between actual and predicted values above 0.96, indicating good prediction capacity.