932 resultados para physical layer network coding


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Context. The subject of asteroids in cometary orbits (ACOs) has been of growing interest lately. These objects have the orbital characteristics typical of comets, but are asteroidal in appearance, i.e., show no signs of a coma at any part of their orbits. At least a fraction of these objects are thought to be comets that have either exhausted all their volatile content or developed a refractory crust that prevents sublimation. In particular, the asteroid ( 5201) Ferraz-Mello has, since its discovery, been suspected to be an extinct Jupiter family comet due to the peculiar nature of its orbit. Aims. The aim of this work is to put constraints on the possible origin of ( 5201) Ferraz-Mello by means of spectroscopic characterization and a study of the dynamics of this asteroid. Methods. We used the SOAR Optical Imager (SOI) to obtain observations of ( 5201) Ferraz-Mello using four SDSS filters. These observations were compared to asteroids listed in the Sloan Moving objects catalog and also to photometry of cometary nuclei, Centaurs, and TNOs. The orbital evolution of ( 5201) Ferraz-Mello and of a sample of asteroids and comets that are close to that object in the a - e plane were simulated using a pure N-body code for 4 000 years forward and 4 000 years backward in time. Results. The reflectance spectrum obtained from its colors in the SDSS system is unusual, with a steep spectral gradient that is comparable to TNOs and Centaurs, but with an increase in the reflectance in the g band that is not common in those populations. A similar behavior is seen in cometary nuclei that were observed in the presence of a faint dust coma. The dynamical results confirm the very chaotic evolution found previously and its dynamical similarity to the chaotic evolution of some comets. The asteroid is situated in the very stochastic layer at the border of the 2/1 resonance, and it has a very short Lyapunov time ( 30 - 40) years. Together, the spectral characteristcs and the dynamical evolution suggest that ( 5201) Ferraz-Mello is a dormant or extinct comet.

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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.

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We propose a natural way to create quantum-confined regions in graphene in a system that allows large-scale device integration. We show, using first-principles calculations, that a single graphene layer on a trenched region of [000 (1) over bar] SiC mimics (i) the energy bands around the Fermi level and (ii) the magnetic properties of free-standing graphene nanoribbons. Depending on the trench direction, either zigzag or armchair nanoribbons are mimicked. This behavior occurs because a single graphene layer over a SiC surface loses the graphenelike properties, which are restored solely over the trenches, providing in this way a confined strip region.

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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.

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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.

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The concept of constitutional dynamic chemistry (CDC) based on the control of non-covalent interactions in supramolecular structures is promising for having a large impact on nanoscience and nanotechnology if adequate nanoscale manipulation methods are used. In this study, we demonstrate that the layer-by-layer (LbL) technique may be used to produce electroactive electrodes with ITO coated by tetrasulfonated nickel phthalocyanine (NiTsPc) alternated with poly(allylamine hydrochloride) (PAH) incorporating gold nanoparticles (AuNP), in which synergy has been achieved in the interaction between the nanoparticles and NiTsPc. The catalytic activity toward hydrogen peroxide (H(2)O(2)) in multilayer films was investigated using cyclic voltammetry, where oxidation of H(2)O(2) led to increased currents in the PAH-AuNP/NiTsPc films for the electrochemical processes associated with the phthalocyanine ring and nickel at 0.52 and 0.81 V vs. SCE, respectively, while for PAH/NiTsPc films (without AuNP) only the first redox process was affected. In control experiments we found out that the catalytic activity was not solely due to the presence of AuNP, but rather to the nanoparticles inducing NiTsPc supramolecular structures that favored access to their redox sites, thus yielding strong charge transfer. The combined effects of NiTsPc and AuNP, which could only be observed in nanostructured LbL films, point to another avenue to pursue within the CDC paradigm.

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Layer-by-layer (LBL) assembly was used to combine crystalline rod-like nanoparticles obtained from a vegetable source, cellulose nanowhiskers (CNWs), with collagen, the main component of skin and connective tissue found exclusively in animals. The film growth of the multilayered collagen/CNW was monitored by UV-Vis spectroscopy and ellipsometry measurements, whereas the film morphology and surface roughness were characterized by SEM and AFM. UV-Vis spectra showed the deposition of the same amount of collagen, 5 mg m(-2), in each dipping cycle. Ellipsometry data showed an increment in thickness with the number of layers, and the average thickness of each bilayer was found to be 8.6 nm. The multilayered bio-based nanocomposites were formed by single layers of densely packed CNWs adsorbed on top of each thin collagen layer where the hydrogen bonding between collagen amide groups and OH groups of the CNWs plays a mandatory role in the build-up of the thin films. The approach used in this work represents a potential strategy to mimic the characteristics of natural extracellular matrix (ECM) which can be used for applications in the biomedical field.

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Outgassing of carbon dioxide (CO(2)) from rivers and streams to the atmosphere is a major loss term in the coupled terrestrial-aquatic carbon cycle of major low-gradient river systems (the term ""river system"" encompasses the rivers and streams of all sizes that compose the drainage network in a river basin). However, the magnitude and controls on this important carbon flux are not well quantified. We measured carbon dioxide flux rates (F(CO2)), gas transfer velocity (k), and partial pressures (p(CO2)) in rivers and streams of the Amazon and Mekong river systems in South America and Southeast Asia, respectively. F(CO2) and k values were significantly higher in small rivers and streams (channels <100 m wide) than in large rivers (channels >100 m wide). Small rivers and streams also had substantially higher variability in k values than large rivers. Observed F(CO2) and k values suggest that previous estimates of basinwide CO(2) evasion from tropical rivers and wetlands have been conservative and are likely to be revised upward substantially in the future. Data from the present study combined with data compiled from the literature collectively suggest that the physical control of gas exchange velocities and fluxes in low-gradient river systems makes a transition from the dominance of wind control at the largest spatial scales (in estuaries and river mainstems) toward increasing importance of water current velocity and depth at progressively smaller channel dimensions upstream. These results highlight the importance of incorporating scale-appropriate k values into basinwide models of whole ecosystem carbon balance.

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This study has as objective identifies the necessary competences to the physical education teachers of the basic education, in the teachers` of the public network of teaching of the Sao Paulo state perspective, licentiates and exits of the Physical Education School and Sport of the Sao Paulo University starting from 1995. It is a qualitative research, of nature no experimental, consisting of two studies (diagnostic and deepening). As instruments, questionnaire and semi-structured interview were used. It happened what the teachers judge importantly mobilize determined knowledges placed in a hierarchy or associated during the teaching practice, such as: knowledges pedagogic-educational, technical knowledges and cultural luggage, inserted in the current context and considering the cultural, social, political, economical and education transformations occurred along the history. There was shown up in this study the relevance of the formation continued for the teachers of Physical Education, who found her essential and basic added to the initial formation.

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There are several ways to attempt to model a building and its heat gains from external sources as well as internal ones in order to evaluate a proper operation, audit retrofit actions, and forecast energy consumption. Different techniques, varying from simple regression to models that are based on physical principles, can be used for simulation. A frequent hypothesis for all these models is that the input variables should be based on realistic data when they are available, otherwise the evaluation of energy consumption might be highly under or over estimated. In this paper, a comparison is made between a simple model based on artificial neural network (ANN) and a model that is based on physical principles (EnergyPlus) as an auditing and predicting tool in order to forecast building energy consumption. The Administration Building of the University of Sao Paulo is used as a case study. The building energy consumption profiles are collected as well as the campus meteorological data. Results show that both models are suitable for energy consumption forecast. Additionally, a parametric analysis is carried out for the considered building on EnergyPlus in order to evaluate the influence of several parameters such as the building profile occupation and weather data on such forecasting. (C) 2008 Elsevier B.V. All rights reserved.

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A hydraulic jump is characterised by strong energy dissipation and air entrainment. In the present study, new air-water flow measurements were performed in hydraulic jumps with partially-developed flow conditions in relatively large-size facilities with phase-detection probes. The experiments were conducted with identical Froude numbers, but a range of Reynolds numbers and relative channel widths. The results showed drastic scale effects at small Reynolds numbers in terms of void fraction and bubble count rate distributions. The void fraction distributions implied comparatively greater detrainment at low Reynolds numbers leading to a lesser overall aeration of the jump roller, while dimensionless bubble count rates were drastically lower especially in the mixing layer. The experimental results suggested also that the relative channel width had little effect on the air-water flow properties for identical inflow Froude and Reynolds numbers.

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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.

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Hypoeutectic AI-Si alloys represent the most widely used alloy system for cast aluminium applications. This system has a unique behaviour with respect to grain formation where an increase in silicon content results in a transition to larger grain sizes after a minimum at an intermediate concentration. As a result of the already large solute content, grain refinement by solute additions is inefficient and nucleant particles from the common aluminium grain refiners are not as effective as in wrought alloys. However, casting conditions, such as a low pouring temperature, that promote the formation of wall crystals tie. crystals nucleated in the thermally undercooled layer at or next to mould walls) are very effective in yielding a small grain size. This paper presents results of an investigation of the effect of low superheat and mould preheat temperature on grain size. It was found that pouring temperature controls the effectiveness of the wall mechanism while mould preheat has little effect until high preheat temperatures at which a large increase in grain size occurs. The observed changes in grain size are explained in terms of the balance between nucleation rate and survival rate of crystal nuclei resulting from changes in superheat and mould temperature.

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A multilayer organic film containing poly(acrylic acid) and chitosan was fabricated on a metallic support by means of the layer-by-layer technique. This film was used as a template for calcium carbonate crystallization and presents two possible binding sites where the nucleation may be initiated, either calcium ions acting as counterions of the polyelectrolyte or those trapped in the template gel network formed by the polyelectrolyte chains. Calcium carbonate formation was carried out by carbon dioxide diffusion, where CO, was generated from ammonium carbonate decomposition. The CaCO3 nanocrystals obtained, formed a dense, homogeneous, and continuous film. Vaterite and calcite CaCO3 crystalline forms were detected. (c) 2007 Elsevier B.V All rights reserved.

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The problem of the negative values of the interaction parameter in the equation of Frumkin has been analyzed with respect to the adsorption of nonionic molecules on energetically homogeneous surface. For this purpose, the adsorption states of a homologue series of ethoxylated nonionic surfactants on air/water interface have been determined using four different models and literature data (surface tension isotherms). The results obtained with the Frumkin adsorption isotherm imply repulsion between the adsorbed species (corresponding to negative values of the interaction parameter), while the classical lattice theory for energetically homogeneous surface (e.g., water/air) admits attraction alone. It appears that this serious contradiction can be overcome by assuming heterogeneity in the adsorption layer, that is, effects of partial condensation (formation of aggregates) on the surface. Such a phenomenon is suggested in the Fainerman-Lucassen-Reynders-Miller (FLM) 'Aggregation model'. Despite the limitations of the latter model (e.g., monodispersity of the aggregates), we have been able to estimate the sign and the order of magnitude of Frumkin's interaction parameter and the range of the aggregation numbers of the surface species. (C) 2004 Elsevier B.V All rights reserved.