The advance of cloud computing

The “Implementation of the National Data Centre” project, Augusto Espín, Deputy Minister of Telecommunications and Information Society, Ecuador .-- Cloud computing and public policy in Brazil, Rafael Henrique Rodrigues Moreira, Ministry of Science, Technology and Innovation, Brazil .-- “The cloud is being taken up more quickly in Latin America than in the rest of the world”, interview to Lalo Steinmann, Microsoft .-- The impact of education and research networks on the development of cloud computing Eduardo Vera, University of Chile .-- “The cloud helps to narrow divides by providing access to technology resources that used to be unaffordable”, interview to Luis Urzúa, Movistar Chile .-- “Cloud computing will be a strategic sector of the economy in the coming years”, interview to Jean-Bernard Gramunt, France’s digital strategy .-- “If take-up in Latin America is as strong as predicted, it will be a good opportunity to create and export technology”, interview to Flavio Junqueira, Yahoo! Labs.

Global integration, disarticulation and competitiveness in Mexico’s electromechanical sector: A structural analysis

This article analyses the dual functioning of the Mexican electromechanical sector between 1994 and 2008, as distinct from other globalized activities. An estimation of labour productivity in 52 industrial classes finds that structural heterogeneity increased particularly in the 1994-2001 subperiod, alongside technical and organizational improvements that were increasingly concentrated in a small number of subsidiary companies of transnational automotive-assembly enterprises. The application of a shift-share technique also revealed the absence of any significant structural change. Lastly, an extension of the methodology to evaluate competitiveness —developed by the Economic Commission for Latin America and the Caribbean (eclac)— and its application to a second database that reclassifies 1,345 foreign trade products, makes it possible to contrast these changes with the dynamism of the global production networks in which the leading firms of the sector in Mexico are engaged.

The tourism sector and the global economic crisis: development implicatins for the Caribbean

Over the past two years the global economy has experienced substantial economic turmoil, resulting in severe economic contraction. While there has been a recent return to growth, this situation has impacted all economic sectors worldwide. In the highly tourism-dependent region of the Caribbean, the impact of the global economic crisis has been most notable on the tourism sector, which, from the early 1990s, became the key driver of economic growth for the region. The eventual emergence of this sector reflects an economic development history which was previously underpinned by the export of agricultural commodities, and subsequently by the adoption of the import substitution industrialization model as promulgated by Arthur Lewis. This was further stimulated by spectacular economic contraction in Caribbean economies during the 1980s as a result of changes in the global terms of trade for commodities, generally low levels of competitiveness for manufactured goods, as well as weak institutional and governance frameworks. Ultimately, many economies began to reflect fiscal and balance of payments constraints. By the end of the 1990s, too, evidence of declining competitiveness even in the tourism sector began to become apparent particularly when evaluated under the framework of the Butler Tourism Area Life- Cycle (TALC) model. The recent economic crisis, therefore, provides an opportunity to reflect on the overall approach to economic development in the Caribbean, and to assess the implications of the region’s response to the crisis. This analysis makes the case for the future development of the sector to be based on two broad strategies. The first is to deepen the integration of the tourism sector into the broader economy through the diversification of the regional tourism product, as well as the enhancement of linkages with other sectors, while the second is to expand the tourism sector into a total service economy through the introduction of new services. Considering linkages, the development of clusters and value chains to support the tourism sector is identified with respect to agriculture and food, handicraft, and furnishings. Among the new services identified are education, wellness, yachting and boating, financial services, and information and communications technologies (ICT). This overall strategy is deemed to be better suited to the macroeconomic realities of the Caribbean, where high labour costs and other structural rigidities require a high-valued specialty tourism product in order to sustain the sector’s global competitiveness.

Cryotolerance and global gene-expression patterns of Bos taurus indicus and Bos taurus taurus in vitro- and in vivo-produced blastocysts

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

Typology of companies networks for competitive assessment: an application in higher education institutions

Taking into account the changes in the market scenario by virtue of globalization, Institutes of Higher Education (IES) as well as other organizations seek their competitive stability. For that reason, it is up to organizations to adopt innovative models of management for their operations aimed at improving results. Company networks consist of a model that is perfect for uniting efforts through cooperation among partners in a given business, which can involve ties of different natures. This paper shows the development and the application of an auxiliary technique to analyze the intensity, nature and importance of internal and external relations in the formation of results for a company network. For such, a multiple case study was conducted at two IES in the State of São Paulo and their networks of partners and employees in order to observe their specificities and organizational strategies. The study demonstrated the existence of specific performance criteria (pillars) for each IES and its network, resulting from its competitive reality. It reveals evidence that the education pillar is strengthened in both cases, and the research pillar is growing, although it is the weakest. The outreach pillar is the most robust in the public IES and the financial sustainability pillar is relevant for the private IES, and it was only detected in this IES.

The application of neural networks to the analysis of dissolved gases in insulating oil used in transformers

The state of insulating oils used in transformers is determined through the accomplishment of physical-chemical tests, which determine the state of the oil, as well as the chromatography test, which determines possible faults in the equipment. This article concentrate on determining, from a new methodology, a relationship among the variation of the indices obtained from the physical-chemical tests with those indices supplied by the chromatography tests.The determination of the relationship among the tests is accomplished through the application of neural networks. From the data obtained by physical-chemical tests, the network is capable to determine the relationship among the concentration of the main gases present in a certain sample, which were detected by the chromatography tests.More specifically, the proposed approach uses neural networks of perceptron type constituted of multiple layers. After the process of network training, it is possible to determine the existent relationship between the physical-chemical tests and the amount of gases present in the insulating oil.

Strategic feed formulation for relation of electrolytes to promote performance and prevent heat stress in broilers

An experiment was conducted to evaluate the impact in relation of dietary electrolytes, based on changes in the balance Na+K-Cl (DEB) and the ratio (K+Cl)/Na (DER) on the performance and survival of broilers subjected to acute heat stress. A total of 1575 male broiler chicks from 1 to 46 d of age were allocated in a 5x3 factorial arrangement in a completely randomized design, totaling of 15 treatments with 3 replicates of 35 birds each. The treatments consisted of 5 diets with electrolyte balances, arising from combinations DEB/DER (150/3, 250/2, 250/3, 250/4 and 350/3), associated with different times of application or not of the acute heat stress on birds at 25 and 36 d old. All diets were cornsoybean meal based and formulated to meet or exceed NRC requirements. Chicks had ad libitum access to feed and water in floor pens with wood shavings as litter. It was possible to verify that a DEB of 250 mEq/kg and a DER very close to the 3:1 providing a more nutritionally adequate diet. There was, however, the impossibility of obtaining a more suitable electrolyte ratio for a very low DEB (150 mEq/kg) or very high (350 mEq/kg) and also, to a very narrow DER (2:1) or very wide (4:1), due to an unfavorable performance and survival rate of birds in these conditions electrolytes adjustments of K, Na and Cl. There was clear indication, with significant difference (P < 0.05), that the DER has the potential to improve the performance of broilers, since simultaneous adjustment made in DEB, even in conditions of acute stress. The results of performance and survival rate of this study also indicate clearly that DER could not replace the DEB, and vice versa, in practical diets for broilers. Therefore, it can be affirmed that the strategic formulation of the correct electrolyte balance for DEB and DER enhances the performance and is able to prevent the effect of heat stress in broiler chickens, leading to better performance and survival.

Discriminating Different Classes of Biological Networks by Analyzing the Graphs Spectra Distribution

The brain's structural and functional systems, protein-protein interaction, and gene networks are examples of biological systems that share some features of complex networks, such as highly connected nodes, modularity, and small-world topology. Recent studies indicate that some pathologies present topological network alterations relative to norms seen in the general population. Therefore, methods to discriminate the processes that generate the different classes of networks (e. g., normal and disease) might be crucial for the diagnosis, prognosis, and treatment of the disease. It is known that several topological properties of a network (graph) can be described by the distribution of the spectrum of its adjacency matrix. Moreover, large networks generated by the same random process have the same spectrum distribution, allowing us to use it as a "fingerprint". Based on this relationship, we introduce and propose the entropy of a graph spectrum to measure the "uncertainty" of a random graph and the Kullback-Leibler and Jensen-Shannon divergences between graph spectra to compare networks. We also introduce general methods for model selection and network model parameter estimation, as well as a statistical procedure to test the nullity of divergence between two classes of complex networks. Finally, we demonstrate the usefulness of the proposed methods by applying them to (1) protein-protein interaction networks of different species and (2) on networks derived from children diagnosed with Attention Deficit Hyperactivity Disorder (ADHD) and typically developing children. We conclude that scale-free networks best describe all the protein-protein interactions. Also, we show that our proposed measures succeeded in the identification of topological changes in the network while other commonly used measures (number of edges, clustering coefficient, average path length) failed.

Muscarinic and Nicotinic Modulation of Thalamo-Prefrontal Cortex Synaptic Pasticity In Vivo

The mediodorsal nucleus of the thalamus (MD) is a rich source of afferents to the medial prefrontal cortex (mPFC). Dysfunctions in the thalamo-prefrontal connections can impair networks implicated in working memory, some of which are affected in Alzheimer disease and schizophrenia. Considering the importance of the cholinergic system to cortical functioning, our study aimed to investigate the effects of global cholinergic activation of the brain on MD-mPFC synaptic plasticity by measuring the dynamics of long-term potentiation (LTP) and depression (LTD) in vivo. Therefore, rats received intraventricular injections either of the muscarinic agonist pilocarpine (PILO; 40 nmol/mu L), the nicotinic agonist nicotine (NIC; 320 nmol/mu L), or vehicle. The injections were administered prior to either thalamic high-frequency (HFS) or low-frequency stimulation (LFS). Test pulses were applied to MD for 30 min during baseline and 240 min after HFS or LFS, while field postsynaptic potentials were recorded in the mPFC. The transient oscillatory effects of PILO and NIC were monitored through recording of thalamic and cortical local field potentials. Our results show that HFS did not affect mPFC responses in vehicle-injected rats, but induced a delayed-onset LTP with distinct effects when applied following PILO or NIC. Conversely, LFS induced a stable LTD in control subjects, but was unable to induce LTD when applied after PILO or NIC. Taken together, our findings show distinct modulatory effects of each cholinergic brain activation on MD-mPFC plasticity following HFS and LFS. The LTP-inducing action and long-lasting suppression of cortical LTD induced by PILO and NIC might implicate differential modulation of thalamo-prefrontal functions under low and high input drive.

ACTIVE NETWORKS THAT MAXIMIZE THE AMOUNT OF INFORMATION TRANSMISSION

This work clarifies the relationship between network circuit (topology) and behavior (information transmission and synchronization) in active networks, e. g. neural networks. As an application, we show how to determine a network topology that is optimal for information transmission. By optimal, we mean that the network is able to transmit a large amount of information, it possesses a large number of communication channels, and it is 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.

Local Structure of Hydrogen-Bonded Liquids

Ordinary yet unique, water is the substance on which life is based. Water seems, at first sight, to be a very simple molecule, consisting of two hydrogen atoms attached to one oxygen. Its small size belies the complexity of its action and its numerous anomalies, central to a broad class of important phenomena, ranging from global current circulation, terrestrial water and CO2 cycles to corrosion and wetting. The explanation of this complex behavior comes from water's unique ability to form extensive three-dimensional networks of hydrogen-bonds, whose nature and structures, in spite of a great deal of efforts involving a plethora of experimental and theoretical techniques, still lacks a complete scientific understanding. This thesis is devoted to the study of the local structure of hydrogen-bonded liquids, with a particular emphasis on water, taking advantage of a combination of core-level spectroscopies and density functional theory spectra calculations. X-ray absorption, in particular, is found to be sensitive to the local hydrogen-bond environment, thus offering a very promising tool for spectroscopic identification of specific structural configurations in water, alcohols and aqueous solutions. More specifically, the characteristic spectroscopic signature of the broken hydrogen-bond at the hydrogen side is used to analyze the structure of bulk water, leading to the finding that most molecules are arranged in two hydrogen-bond configurations, in contrast to the picture provided by molecular dynamics simulations. At the liquid-vapor interface, an interplay of surface sensitive measurements and theoretical calculations enables us to distinguish a new interfacial species in equilibrium with the gas. In a similar approach the cluster form of the excess proton in highly concentrated acid solutions and the different coordination of methanol at the vacuum interface and in the bulk can also be clearly identified. Finally the ability of core-level spectroscopies, aided by sophisticated density functional theory calculations, to directly probe the valence electronic structure of a system is used to observe the nature of the interaction between water molecules and solvated ions in solution. Water around transition metal ions is found to interact with the solute via orbital mixing with the metal d-orbitals. The hydrogen-bond between water molecules is explained in terms of electrostatic interactions enhanced by charge rehybridization in which charge transfer between connecting molecules is shown to be fundamental.

Management and routing algorithms for ad-hoc and sensor networks

Large scale wireless adhoc networks of computers, sensors, PDAs etc. (i.e. nodes) are revolutionizing connectivity and leading to a paradigm shift from centralized systems to highly distributed and dynamic environments. An example of adhoc networks are sensor networks, which are usually composed by small units able to sense and transmit to a sink elementary data which are successively processed by an external machine. Recent improvements in the memory and computational power of sensors, together with the reduction of energy consumptions, are rapidly changing the potential of such systems, moving the attention towards datacentric sensor networks. A plethora of routing and data management algorithms have been proposed for the network path discovery ranging from broadcasting/floodingbased approaches to those using global positioning systems (GPS). We studied WGrid, a novel decentralized infrastructure that organizes wireless devices in an adhoc manner, where each node has one or more virtual coordinates through which both message routing and data management occur without reliance on either flooding/broadcasting operations or GPS. The resulting adhoc network does not suffer from the deadend problem, which happens in geographicbased routing when a node is unable to locate a neighbor closer to the destination than itself. WGrid allow multidimensional data management capability since nodes' virtual coordinates can act as a distributed database without needing neither special implementation or reorganization. Any kind of data (both single and multidimensional) can be distributed, stored and managed. We will show how a location service can be easily implemented so that any search is reduced to a simple query, like for any other data type. WGrid has then been extended by adopting a replication methodology. We called the resulting algorithm WRGrid. Just like WGrid, WRGrid acts as a distributed database without needing neither special implementation nor reorganization and any kind of data can be distributed, stored and managed. We have evaluated the benefits of replication on data management, finding out, from experimental results, that it can halve the average number of hops in the network. The direct consequence of this fact are a significant improvement on energy consumption and a workload balancing among sensors (number of messages routed by each node). Finally, thanks to the replications, whose number can be arbitrarily chosen, the resulting sensor network can face sensors disconnections/connections, due to failures of sensors, without data loss. Another extension to {WGrid} is {W*Grid} which extends it by strongly improving network recovery performance from link and/or device failures that may happen due to crashes or battery exhaustion of devices or to temporary obstacles. W*Grid guarantees, by construction, at least two disjoint paths between each couple of nodes. This implies that the recovery in W*Grid occurs without broadcasting transmissions and guaranteeing robustness while drastically reducing the energy consumption. An extensive number of simulations shows the efficiency, robustness and traffic road of resulting networks under several scenarios of device density and of number of coordinates. Performance analysis have been compared to existent algorithms in order to validate the results.

Identification and characterization of the sRNA network in Neisseria meningitidis

Bacterial small regulatory RNAs (sRNAs) are posttranscriptional regulators involved in stress responses. These short non-coding transcripts are synthesised in response to a signal, and control gene expression of their regulons by modulating the translation or stability of the target mRNAs, often in concert with the RNA chaperone Hfq. Characterization of a Hfq knock out mutant in Neisseria meningitidis revealed that it has a pleiotropic phenotype, suggesting a major role for Hfq in adaptation to stresses and virulence and the presence of Hfq-dependent sRNA activity. Global gene expression analysis of regulated transcripts in the Hfq mutant revealed the presence of a regulated sRNA, incorrectly annotated as an open reading frame, which we renamed AniS. The synthesis of this novel sRNA is anaerobically induced through activation of its promoter by the FNR global regulator and through global gene expression analyses we identified at least two predicted mRNA targets of AniS. We also performed a detailed molecular analysis of the action of the sRNA NrrF,. We demonstrated that NrrF regulates succinate dehydrogenase by forming a duplex with a region of complementarity within the sdhDA region of the succinate dehydrogenase transcript, and Hfq enhances the binding of this sRNA to the identified target in the sdhCDAB mRNA; this is likely to result in rapid turnover of the transcript in vivo. In addition, in order to globally investigate other possible sRNAs of N. meningitdis we Deep-sequenced the transcriptome of this bacterium under both standard in vitro and iron-depleted conditions. This analysis revealed genes that were actively transcribed under the two conditions. We focused our attention on the transcribed non-coding regions of the genome and, along with 5’ and 3’ untranslated regions, 19 novel candidate sRNAs were identified. Further studies will be focused on the identification of the regulatory networks of these sRNAs, and their targets.

Constraining global methane emissions and uptake by ecosystems

Natural methane (CH4) emissions from wet ecosystems are an important part of today's global CH4 budget. Climate affects the exchange of CH4 between ecosystems and the atmosphere by influencing CH4 production, oxidation, and transport in the soil. The net CH4 exchange depends on ecosystem hydrology, soil and vegetation characteristics. Here, the LPJ-WHyMe global dynamical vegetation model is used to simulate global net CH4 emissions for different ecosystems: northern peatlands (45°–90° N), naturally inundated wetlands (60° S–45° N), rice agriculture and wet mineral soils. Mineral soils are a potential CH4 sink, but can also be a source with the direction of the net exchange depending on soil moisture content. The geographical and seasonal distributions are evaluated against multi-dimensional atmospheric inversions for 2003–2005, using two independent four-dimensional variational assimilation systems. The atmospheric inversions are constrained by the atmospheric CH4 observations of the SCIAMACHY satellite instrument and global surface networks. Compared to LPJ-WHyMe the inversions result in a~significant reduction in the emissions from northern peatlands and suggest that LPJ-WHyMe maximum annual emissions peak about one month late. The inversions do not put strong constraints on the division of sources between inundated wetlands and wet mineral soils in the tropics. Based on the inversion results we diagnose model parameters in LPJ-WHyMe and simulate the surface exchange of CH4 over the period 1990–2008. Over the whole period we infer an increase of global ecosystem CH4 emissions of +1.11 Tg CH4 yr−1, not considering potential additional changes in wetland extent. The increase in simulated CH4 emissions is attributed to enhanced soil respiration resulting from the observed rise in land temperature and in atmospheric carbon dioxide that were used as input. The long-term decline of the atmospheric CH4 growth rate from 1990 to 2006 cannot be fully explained with the simulated ecosystem emissions. However, these emissions show an increasing trend of +3.62 Tg CH4 yr−1 over 2005–2008 which can partly explain the renewed increase in atmospheric CH4 concentration during recent years.