Optimized network structure for full-synchronization

A network of Kuramoto oscillators with different natural frequencies is optimized for enhanced synchronizability. All node inputs are normalized by the node connectivity and some important properties of the network Structure are determined in this case: (i) optimized networks present a strong anti-correlation between natural frequencies of adjacent nodes: (ii) this anti-correlation should be as high as possible since the average path length between nodes is maintained as small as in random networks: and (iii) high anti-correlation is obtained without any relation between nodes natural frequencies and the degree of connectivity. We also propose a network construction model with which it is shown that high anti-correlation and small average paths may be achieved by randomly rewiring a fraction of the links of a totally anti-correlated network, and that these networks present optimal synchronization properties. (C) 2008 Elsevier B.V. All rights reserved.

On the basic reproduction number and the topological properties of the contact network: An epidemiological study in mainly locally connected cellular automata

We study the spreading of contagious diseases in a population of constant size using susceptible-infective-recovered (SIR) models described in terms of ordinary differential equations (ODEs) and probabilistic cellular automata (PCA). In the PCA model, each individual (represented by a cell in the lattice) is mainly locally connected to others. We investigate how the topological properties of the random network representing contacts among individuals influence the transient behavior and the permanent regime of the epidemiological system described by ODE and PCA. Our main conclusions are: (1) the basic reproduction number (commonly called R(0)) related to a disease propagation in a population cannot be uniquely determined from some features of transient behavior of the infective group; (2) R(0) cannot be associated to a unique combination of clustering coefficient and average shortest path length characterizing the contact network. We discuss how these results can embarrass the specification of control strategies for combating disease propagations. (C) 2009 Elsevier B.V. All rights reserved.

Reachability of the synchronous state in a mutually connected PLL network

Second-order phase locked loops (PLLs) are devices that are able to provide synchronization between the nodes in a network even under severe quality restrictions in the signal propagation. Consequently, they are widely used in telecommunication and control. Conventional master-slave (M-S) clock-distribution systems are being, replaced by mutually connected (MC) ones due to their good potential to be used in new types of application such as wireless sensor networks, distributed computation and communication systems. Here, by using an analytical reasoning, a nonlinear algebraic system of equations is proposed to establish the existence conditions for the synchronous state in an MC PLL network. Numerical experiments confirm the analytical results and provide ideas about how the network parameters affect the reachability of the synchronous state. The phase-difference oscillation amplitudes are related to the node parameters helping to design PLL neural networks. Furthermore, estimation of the acquisition time depending on the node parameters allows the performance evaluation of time distribution systems and neural networks based on phase-locked techniques. (c) 2008 Elsevier GmbH. All rights reserved.

Synaptic compensation on Hopfield network: implications for memory rehabilitation

The discrete-time neural network proposed by Hopfield can be used for storing and recognizing binary patterns. Here, we investigate how the performance of this network on pattern recognition task is altered when neurons are removed and the weights of the synapses corresponding to these deleted neurons are divided among the remaining synapses. Five distinct ways of distributing such weights are evaluated. We speculate how this numerical work about synaptic compensation may help to guide experimental studies on memory rehabilitation interventions.

Brazilian Network of Food Data Systems and LATINFOODS Regional Technical Compilation Committee: Food composition activities (2006-2009)

The Brazilian Network of Food Data Systems (BRASILFOODS) has been keeping the Brazilian Food Composition Database-USP (TBCA-USP) (http://www.fcf.usp.br/tabela) since 1998. Besides the constant compilation, analysis and update work in the database, the network tries to innovate through the introduction of food information that may contribute to decrease the risk for non-transmissible chronic diseases, such as the profile of carbohydrates and flavonoids in foods. In 2008, data on carbohydrates, individually analyzed, of 112 foods, and 41 data related to the glycemic response produced by foods widely consumed in the country were included in the TBCA-USP. Data (773) about the different flavonoid subclasses of 197 Brazilian foods were compiled and the quality of each data was evaluated according to the USDAs data quality evaluation system. In 2007, BRASILFOODS/USP and INFOODS/FAO organized the 7th International Food Data Conference ""Food Composition and Biodiversity"". This conference was a unique opportunity for interaction between renowned researchers and participants from several countries and it allowed the discussion of aspects that may improve the food composition area. During the period, the LATINFOODS Regional Technical Compilation Committee and BRASILFOODS disseminated to Latin America the Form and Manual for Data Compilation, version 2009, ministered a Food Composition Data Compilation course and developed many activities related to data production and compilation. (C) 2010 Elsevier Inc. All rights reserved.

Intellectuals in a Network A New Generation Faces the Challenges of Development

Brazilian social thought draws on the inspiration of past masters the common denominator of whose work is probably a deep humanism. Confronting the challenges of a fluid, ever-changing reality is now a matter of survival. The idea of climate change has made the environment, long relegated to second place, a matter of much wider interest and concern. The other great problem is poverty, and here, while there have been undeniable advances, much remains to be done. The main challenge is producing forms of social organization that will allow ordinary citizens to have an impact on what really matters. Developing policy in these areas has engaged the efforts of a wide range of experts from a variety of fields. Whereas university-educated intellectuals once formed an intelligentsia, today they are engaged in practical politics and much more often function as agents who link social actors together than as mere elaborators of theories.

Research Quality, Publications and Impact in Hydraulic Engineering into the 21st Century. Publish or Perish, Commercial versus Open Access, Internet versus Libraries

One of the main objectives of the first International Junior Researcher and Engineer Workshop on Hydraulic Structures is to provide an opportunity for young researchers and engineers to present their research. But a research project is only completed when it has been published and shared with the community. Referees and peer experts play an important role to control the research quality. While some new electronic tools provide further means to disseminate some research information, the quality and impact of the works remain linked with some thorough expert-review process and the publications in international scientific journals and books. Importantly unethical publishing standards are not acceptable and cheating is despicable.

Spectral properties of the tandem Jackson network, seen as a quasi-birth-and-death process

Quasi-birth-and-death (QBD) processes with infinite ���phase spaces��� can exhibit unusual and interesting behavior. One of the simplest examples of such a process is the two-node tandem Jackson network, with the ���phase��� giving the state of the first queue and the ���level��� giving the state of the second queue. In this paper, we undertake an extensive analysis of the properties of this QBD. In particular, we investigate the spectral properties of Neuts���s R-matrix and show that the decay rate of the stationary distribution of the ���level��� process is not always equal to the convergence norm of R. In fact, we show that we can obtain any decay rate from a certain range by controlling only the transition structure at level zero, which is independent of R. We also consider the sequence of tandem queues that is constructed by restricting the waiting room of the first queue to some finite capacity, and then allowing this capacity to increase to infinity. We show that the decay rates for the finite truncations converge to a value, which is not necessarily the decay rate in the infinite waiting room case. Finally, we show that the probability that the process hits level n before level 0 given that it starts in level 1 decays at a rate which is not necessarily the same as the decay rate for the stationary distribution.

Development and evaluation of neural network freeway incident detection models using field data

This paper discusses a multi-layer feedforward (MLF) neural network incident detection model that was developed and evaluated using field data. In contrast to published neural network incident detection models which relied on simulated or limited field data for model development and testing, the model described in this paper was trained and tested on a real-world data set of 100 incidents. The model uses speed, flow and occupancy data measured at dual stations, averaged across all lanes and only from time interval t. The off-line performance of the model is reported under both incident and non-incident conditions. The incident detection performance of the model is reported based on a validation-test data set of 40 incidents that were independent of the 60 incidents used for training. The false alarm rates of the model are evaluated based on non-incident data that were collected from a freeway section which was video-taped for a period of 33 days. A comparative evaluation between the neural network model and the incident detection model in operation on Melbourne's freeways is also presented. The results of the comparative performance evaluation clearly demonstrate the substantial improvement in incident detection performance obtained by the neural network model. The paper also presents additional results that demonstrate how improvements in model performance can be achieved using variable decision thresholds. Finally, the model's fault-tolerance under conditions of corrupt or missing data is investigated and the impact of loop detector failure/malfunction on the performance of the trained model is evaluated and discussed. The results presented in this paper provide a comprehensive evaluation of the developed model and confirm that neural network models can provide fast and reliable incident detection on freeways. (C) 1997 Elsevier Science Ltd. All rights reserved.

Capillary network models for transport in packed beds: Considerations of pore aspect ratio

The conventional analysis for the estimation of the tortuosity factor for transport in porous media is modified here to account for the effect of pore aspect ratio. Structural models of the porous medium are also constructed for calculating the aspect ratio as a function of porosity. Comparison of the model predictions with the extensive data of Currie (1960) for the effective diffusivity of hydrogen in packed beds shows good agreement with a network model of randomly oriented intersecting pores for porosities upto about 50 percent, which is the region of practical interest. The predictions based on this network model are also found to be in better agreement with the data of Currie than earlier expressions developed for unconsolidated and grainy media.

Prediction of MHC class II-binding peptides using an evolutionary algorithm and artificial neural network

Motivation: Prediction methods for identifying binding peptides could minimize the number of peptides required to be synthesized and assayed, and thereby facilitate the identification of potential T-cell epitopes. We developed a bioinformatic method for the prediction of peptide binding to MHC class II molecules. Results: Experimental binding data and expert knowledge of anchor positions and binding motifs were combined with an evolutionary algorithm (EA) and an artificial neural network (ANN): binding data extraction --> peptide alignment --> ANN training and classification. This method, termed PERUN, was implemented for the prediction of peptides that bind to HLA-DR4(B1*0401). The respective positive predictive values of PERUN predictions of high-, moderate-, low- and zero-affinity binder-a were assessed as 0.8, 0.7, 0.5 and 0.8 by cross-validation, and 1.0, 0.8, 0.3 and 0.7 by experimental binding. This illustrates the synergy between experimentation and computer modeling, and its application to the identification of potential immunotheraaeutic peptides.

Modeling the fluid-flow-induced stress and collapse in a dendritic network

An analytical approach to the stress development in the coherent dendritic network during solidification is proposed. Under the assumption that stresses are developed in the network as a result of the friction resisting shrinkage-induced interdendritic fluid flow, the model predicts the stresses in the solid. The calculations reflect the expected effects of postponed dendrite coherency, slower solidification conditions, and variations of eutectic volume fraction and shrinkage. Comparing the calculated stresses to the measured shear strength of equiaxed mushy zones shows that it is possible for the stresses to exceed the strength, thereby resulting in reorientation or collapse of the dendritic network.

Encoding combinatorial libraries: A novel application of fluorescent silica colloids

A major challenge associated with using large chemical libraries synthesized on microscopic solid support beads is the rapid discrimination of individual compounds in these libraries. This challenge can be overcome by encoding the beads with 1 mum silica colloidal particles (reporters) that contain specific and identifiable combinations of fluorescent byes. The colored bar code generated on support beads during combinatorial library synthesis can be easily, rapidly, and inexpensively decoded through the use of fluorescence microscopy. All reporters are precoated with polyelectrolytes [poly(acrylic acid), PAA, poly(sodium 4-styrenesulfonate PSSS, polyethylenimine, PEI, and/or poly(diallyldimethylammonium chloride), PDADMAC] with the aim of enhancing surface charge, promoting electrostatic attraction to the bead, and facilitating polymer bridging between the bead and reporter for permanent adhesion. As shown in this article, reporters coated with polyelectrolytes clearly outperform uncoated reporters with regard to quantity of attached reporters per bead (54 +/- 23 in 2500 mum(2) area for PEI/PAA coated and 11 +/- 6 for uncoated reporters) and minimization of cross-contamination (1 red reporter in 2500 mum(2) area of green-labeled bead for PEI/PAA coated and 26 +/- 15 red reporters on green-labeled beads for uncoated reporters after 10 days). Examination of various polyelectrolyte systems shows that the magnitude of the xi -potential of polyelectrolyte-coated reporters (-64 mV for PDADMAC/PSSS and -42 mV for PEI/PAA-coated reporters) has no correlation with the number of reporters that adhere to the solid support beads (21 +/- 16 in 2500 mum(2) area for PDADMAC/PSSS and 54 +/- 23 for PEI/PAA-coated reporters). The contribution of polymer bridging to the adhesion has a far greater influence than electrostatic attraction and is demonstrated by modification of the polyelectrolyte multilayers using gamma irradiation of precoated reporters either in aqueous solution or in polyelectrolyte solution.