The Missing Part of Seed Dispersal Networks: Structure and Robustness of Bat-Fruit Interactions

Mutualistic networks are crucial to the maintenance of ecosystem services. Unfortunately, what we know about seed dispersal networks is based only on bird-fruit interactions. Therefore, we aimed at filling part of this gap by investigating bat-fruit networks. It is known from population studies that: (i) some bat species depend more on fruits than others, and (ii) that some specialized frugivorous bats prefer particular plant genera. We tested whether those preferences affected the structure and robustness of the whole network and the functional roles of species. Nine bat-fruit datasets from the literature were analyzed and all networks showed lower complementary specialization (H(2)' = 0.3760.10, mean 6 SD) and similar nestedness (NODF = 0.5660.12) than pollination networks. All networks were modular (M=0.32 +/- 0.07), and had on average four cohesive subgroups (modules) of tightly connected bats and plants. The composition of those modules followed the genus-genus associations observed at population level (Artibeus-Ficus, Carollia-Piper, and Sturnira-Solanum), although a few of those plant genera were dispersed also by other bats. Bat-fruit networks showed high robustness to simulated cumulative removals of both bats (R = 0.55 +/- 0.10) and plants (R = 0.68 +/- 0.09). Primary frugivores interacted with a larger proportion of the plants available and also occupied more central positions; furthermore, their extinction caused larger changes in network structure. We conclude that bat-fruit networks are highly cohesive and robust mutualistic systems, in which redundancy is high within modules, although modules are complementary to each other. Dietary specialization seems to be an important structuring factor that affects the topology, the guild structure and functional roles in bat-fruit networks.

Impact of Manaus City on the Amazon Green Ocean atmosphere: ozone production, precursor sensitivity and aerosol load

As a contribution to the Large-Scale Biosphere-Atmosphere Experiment in Amazonia - Cooperative LBA Airborne Regional Experiment (LBA-CLAIRE-2001) field campaign in the heart of the Amazon Basin, we analyzed the temporal and spatial dynamics of the urban plume of Manaus City during the wet-to-dry season transition period in July 2001. During the flights, we performed vertical stacks of crosswind transects in the urban outflow downwind of Manaus City, measuring a comprehensive set of trace constituents including O(3), NO, NO(2), CO, VOC, CO(2), and H(2)O. Aerosol loads were characterized by concentrations of total aerosol number (CN) and cloud condensation nuclei (CCN), and by light scattering properties. Measurements over pristine rainforest areas during the campaign showed low levels of pollution from biomass burning or industrial emissions, representative of wet season background conditions. The urban plume of Manaus City was found to be joined by plumes from power plants south of the city, all showing evidence of very strong photochemical ozone formation. One episode is discussed in detail, where a threefold increase in ozone mixing ratios within the atmospheric boundary layer occurred within a 100 km travel distance downwind of Manaus. Observation-based estimates of the ozone production rates in the plume reached 15 ppb h(-1). Within the plume core, aerosol concentrations were strongly enhanced, with Delta CN/Delta CO ratios about one order of magnitude higher than observed in Amazon biomass burning plumes. Delta CN/Delta CO ratios tended to decrease with increasing transport time, indicative of a significant reduction in particle number by coagulation, and without substantial new particle nucleation occurring within the time/space observed. While in the background atmosphere a large fraction of the total particle number served as CCN (about 60-80% at 0.6% supersaturation), the CCN/CN ratios within the plume indicated that only a small fraction (16 +/- 12 %) of the plume particles were CCN. The fresh plume aerosols showed relatively weak light scattering efficiency. The CO-normalized CCN concentrations and light scattering coefficients increased with plume age in most cases, suggesting particle growth by condensation of soluble organic or inorganic species. We used a Single Column Chemistry and Transport Model (SCM) to infer the urban pollution emission fluxes of Manaus City, implying observed mixing ratios of CO, NO(x) and VOC. The model can reproduce the temporal/spatial distribution of ozone enhancements in the Manaus plume, both with and without accounting for the distinct (high NO(x)) contribution by the power plants; this way examining the sensitivity of ozone production to changes in the emission rates of NO(x). The VOC reactivity in the Manaus region was dominated by a high burden of biogenic isoprene from the background rainforest atmosphere, and therefore NO(x) control is assumed to be the most effective ozone abatement strategy. Both observations and models show that the agglomeration of NO(x) emission sources, like power plants, in a well-arranged area can decrease the ozone production efficiency in the near field of the urban populated cores. But on the other hand remote areas downwind of the city then bear the brunt, being exposed to increased ozone production and N-deposition. The simulated maximum stomatal ozone uptake fluxes were 4 nmol m(-2) s(-1) close to Manaus, and decreased only to about 2 nmol m(-2) s(-1) within a travel distance >1500 km downwind from Manaus, clearly exceeding the critical threshold level for broadleaf trees. Likewise, the simulated N deposition close to Manaus was similar to 70 kg N ha(-1) a(-1) decreasing only to about 30 kg N ha(-1) a(-1) after three days of simulation.

Gene Expression Complex Networks: Synthesis, Identification, and Analysis

Thanks to recent advances in molecular biology, allied to an ever increasing amount of experimental data, the functional state of thousands of genes can now be extracted simultaneously by using methods such as cDNA microarrays and RNA-Seq. Particularly important related investigations are the modeling and identification of gene regulatory networks from expression data sets. Such a knowledge is fundamental for many applications, such as disease treatment, therapeutic intervention strategies and drugs design, as well as for planning high-throughput new experiments. Methods have been developed for gene networks modeling and identification from expression profiles. However, an important open problem regards how to validate such approaches and its results. This work presents an objective approach for validation of gene network modeling and identification which comprises the following three main aspects: (1) Artificial Gene Networks (AGNs) model generation through theoretical models of complex networks, which is used to simulate temporal expression data; (2) a computational method for gene network identification from the simulated data, which is founded on a feature selection approach where a target gene is fixed and the expression profile is observed for all other genes in order to identify a relevant subset of predictors; and (3) validation of the identified AGN-based network through comparison with the original network. The proposed framework allows several types of AGNs to be generated and used in order to simulate temporal expression data. The results of the network identification method can then be compared to the original network in order to estimate its properties and accuracy. Some of the most important theoretical models of complex networks have been assessed: the uniformly-random Erdos-Renyi (ER), the small-world Watts-Strogatz (WS), the scale-free Barabasi-Albert (BA), and geographical networks (GG). The experimental results indicate that the inference method was sensitive to average degree k variation, decreasing its network recovery rate with the increase of k. The signal size was important for the inference method to get better accuracy in the network identification rate, presenting very good results with small expression profiles. However, the adopted inference method was not sensible to recognize distinct structures of interaction among genes, presenting a similar behavior when applied to different network topologies. In summary, the proposed framework, though simple, was adequate for the validation of the inferred networks by identifying some properties of the evaluated method, which can be extended to other inference methods.

The impact of the subtropical South Atlantic SST on South American precipitation

The Community Climate Model (CCM3) from the National Center for Atmospheric Research (NCAR) is used to investigate the effect of the South Atlantic sea surface temperature (SST) anomalies on interannual to decadal variability of South American precipitation. Two ensembles composed of multidecadal simulations forced with monthly SST data from the Hadley Centre for the period 1949 to 2001 are analysed. A statistical treatment based on signal-to-noise ratio and Empirical Orthogonal Functions (EOF) is applied to the ensembles in order to reduce the internal variability among the integrations. The ensemble treatment shows a spatial and temporal dependence of reproducibility. High degree of reproducibility is found in the tropics while the extratropics is apparently less reproducible. Austral autumn (MAM) and spring (SON) precipitation appears to be more reproducible over the South America-South Atlantic region than the summer (DJF) and winter (JJA) rainfall. While the Inter-tropical Convergence Zone (ITCZ) region is dominated by external variance, the South Atlantic Convergence Zone (SACZ) over South America is predominantly determined by internal variance, which makes it a difficult phenomenon to predict. Alternatively, the SACZ over western South Atlantic appears to be more sensitive to the subtropical SST anomalies than over the continent. An attempt is made to separate the atmospheric response forced by the South Atlantic SST anomalies from that associated with the El Nino - Southern Oscillation (ENSO). Results show that both the South Atlantic and Pacific SSTs modulate the intensity and position of the SACZ during DJF. Particularly, the subtropical South Atlantic SSTs are more important than ENSO in determining the position of the SACZ over the southeast Brazilian coast during DJF. On the other hand, the ENSO signal seems to influence the intensity of the SACZ not only in DJF but especially its oceanic branch during MAM. Both local and remote influences, however, are confounded by the large internal variance in the region. During MAM and JJA, the South Atlantic SST anomalies affect the magnitude and the meridional displacement of the ITCZ. In JJA, the ENSO has relatively little influence on the interannual variability of the simulated rainfall. During SON, however, the ENSO seems to counteract the effect of the subtropical South Atlantic SST variations on convection over South America.

Simulation of sugarcane residue decomposition and aboveground growth

Due to the worldwide increase in demand for biofuels, the area cultivated with sugarcane is expected to increase. For environmental and economic reasons, an increasing proportion of the areas are being harvested without burning, leaving the residues on the soil surface. This periodical input of residues affects soil physical, chemical and biological properties, as well as plant growth and nutrition. Modeling can be a useful tool in the study of the complex interactions between the climate, residue quality, and the biological factors controlling plant growth and residue decomposition. The approach taken in this work was to parameterize the CENTURY model for the sugarcane crop, to simulate the temporal dynamics of aboveground phytomass and litter decomposition, and to validate the model through field experiment data. When studying aboveground growth, burned and unburned harvest systems were compared, as well as the effect of mineral fertilizer and organic residue applications. The simulations were performed with data from experiments with different durations, from 12 months to 60 years, in Goiana, TimbaA(0)ba and Pradpolis, Brazil; Harwood, Mackay and Tully, Australia; and Mount Edgecombe, South Africa. The differentiation of two pools in the litter, with different decomposition rates, was found to be a relevant factor in the simulations made. Originally, the model had a basically unlimited layer of mulch directly available for decomposition, 5,000 g m(-2). Through a parameter optimization process, the thickness of the mulch layer closer to the soil, more vulnerable to decomposition, was set as 110 g m(-2). By changing the layer of mulch at any given time available for decomposition, the sugarcane residues decomposition simulations where close to measured values (R (2) = 0.93), contributing to making the CENTURY model a tool for the study of sugarcane litter decomposition patterns. The CENTURY model accurately simulated aboveground carbon stalk values (R (2) = 0.76), considering burned and unburned harvest systems, plots with and without nitrogen fertilizer and organic amendment applications, in different climates and soil conditions.

Multifractality in the random parameter model for multivariate time series

The Random Parameter model was proposed to explain the structure of the covariance matrix in problems where most, but not all, of the eigenvalues of the covariance matrix can be explained by Random Matrix Theory. In this article, we explore the scaling properties of the model, as observed in the multifractal structure of the simulated time series. We use the Wavelet Transform Modulus Maxima technique to obtain the multifractal spectrum dependence with the parameters of the model. The model shows a scaling structure compatible with the stylized facts for a reasonable choice of the parameter values. (C) 2009 Elsevier B.V. All rights reserved.

Effect of performance level on pacing strategy during a 10-km running race

The aim of this study was to examine the influence of the performance level of athletes on pacing strategy during a simulated 10-km running race, and the relationship between physiological variables and pacing strategy. Twenty-four male runners performed an incremental exercise test on a treadmill, three 6-min bouts of running at 9, 12 and 15 km h(-1), and a self-paced, 10-km running performance trial; at least 48 h separated each test. Based on 10-km running performance, subjects were divided into terziles, with the lower terzile designated the low-performing (LP) and the upper terzile designated the high-performing (HP) group. For the HP group, the velocity peaked at 18.8 +/- A 1.4 km h(-1) in the first 400 m and was higher than the average race velocity (P < 0.05). The velocity then decreased gradually until 2,000 m (P < 0.05), remaining constant until 9,600 m, when it increased again (P < 0.05). The LP group ran the first 400 m at a significantly lower velocity than the HP group (15.6 +/- A 1.6 km h(-1); P > 0.05) and this initial velocity was not different from LP average racing velocity (14.5 +/- A 0.7 km h(-1)). The velocity then decreased non-significantly until 9,600 m (P > 0.05), followed by an increase at the end (P < 0.05). The peak treadmill running velocity (PV), running economy (RE), lactate threshold (LT) and net blood lactate accumulation at 15 km h(-1) were significantly correlated with the start, middle, last and average velocities during the 10-km race. These results demonstrate that high and low performance runners adopt different pacing strategies during a 10-km race. Furthermore, it appears that important determinants of the chosen pacing strategy include PV, LT and RE.

Digital frequency relaying based on the modified least mean square method

This research presents a method for frequency estimation in power systems using an adaptive filter based on the Least Mean Square Algorithm (LMS). In order to analyze a power system, three-phase voltages were converted into a complex signal applying the alpha beta-transform and the results were used in an adaptive filtering algorithm. Although the use of the complex LMS algorithm is described in the literature, this paper deals with some practical aspects of the algorithm implementation. In order to reduce computing time, a coefficient generator was implemented. For the algorithm validation, a computing simulation of a power system was carried Out using the ATP software. Many different situations were Simulated for the performance analysis of the proposed methodology. The results were compared to a commercial relay for validation, showing the advantages of the new method. (C) 2009 Elsevier Ltd. All rights reserved.

Power quality analysis applying a hybrid methodology with wavelet transforms and neural networks

A hybrid system to automatically detect, locate and classify disturbances affecting power quality in an electrical power system is presented in this paper. The disturbances characterized are events from an actual power distribution system simulated by the ATP (Alternative Transients Program) software. The hybrid approach introduced consists of two stages. In the first stage, the wavelet transform (WT) is used to detect disturbances in the system and to locate the time of their occurrence. When such an event is flagged, the second stage is triggered and various artificial neural networks (ANNs) are applied to classify the data measured during the disturbance(s). A computational logic using WTs and ANNs together with a graphical user interface (GU) between the algorithm and its end user is then implemented. The results obtained so far are promising and suggest that this approach could lead to a useful application in an actual distribution system. (C) 2009 Elsevier Ltd. All rights reserved.

Assessment of the Performance of Acoustic and Mass Balance Methods for Leak Detection in Pipelines for Transporting Liquids

On-line leak detection is a main concern for the safe operation of pipelines. Acoustic and mass balance are the most important and extensively applied technologies in field problems. The objective of this work is to compare these leak detection methods with respect to a given reference situation, i.e., the same pipeline and monitoring signals acquired at the inlet and outlet ends. Experimental tests were conducted in a 749 m long laboratory pipeline transporting water as the working fluid. The instrumentation included pressure transducers and electromagnetic flowmeters. Leaks were simulated by opening solenoid valves placed at known positions and previously calibrated to produce known average leak flow rates. Results have clearly shown the limitations and advantages of each method. It is also quite clear that acoustics and mass balance technologies are, in fact, complementary. In general, an acoustic leak detection system sends out an alarm more rapidly and locates the leak more precisely, provided that the rupture of the pipeline occurs abruptly enough. On the other hand, a mass balance leak detection method is capable of quantifying the leak flow rate very accurately and of detecting progressive leaks.

A hybrid Particle Swarm Optimization - Simplex algorithm (PSOS) for structural damage identification

This study proposes a new PSOS-model based damage identification procedure using frequency domain data. The formulation of the objective function for the minimization problem is based on the Frequency Response Functions (FRFs) of the system. A novel strategy for the control of the Particle Swarm Optimization (PSO) parameters based on the Nelder-Mead algorithm (Simplex method) is presented; consequently, the convergence of the PSOS becomes independent of the heuristic constants and its stability and confidence are enhanced. The formulated hybrid method performs better in different benchmark functions than the Simulated Annealing (SA) and the basic PSO (PSO(b)). Two damage identification problems, taking into consideration the effects of noisy and incomplete data, were studied: first, a 10-bar truss and second, a cracked free-free beam, both modeled with finite elements. In these cases, the damage location and extent were successfully determined. Finally, a non-linear oscillator (Duffing oscillator) was identified by PSOS providing good results. (C) 2009 Elsevier Ltd. All rights reserved

Dimension stone for building facades: methodology for structural design

The importance of a careful selection of rocks used in building facade cladding is highlighted. A simple and viable methodology for the structural detailing of dimension stones and the verification of the global performance is presented based on a Strap software simulation. The results obtained proved the applicability of the proposed structural dimensioning methodology which represents an excellent simple tool for dimensioning rock slabs used for building facade cladding. The Strap software satisfactorily simulated the structural conditions of the stone slabs under the studied conditions, allowing the determination of alternative slab dimensions and the verification of the cladding strength at the support.

Reducing Urban Transport Energy Dependence: A New Urban Development Framework and GIS-Based Tool

High urban transport energy consumption is directly influenced by transport energy dependence. Dramatic reductions in urban transport energy dependence or consumption are not yet being widely observed despite the variety of urban planning tools currently available. A new urban development framework is presented to tackle this issue that makes use of a recently developed and successfully trialed GIS-based tool, the Transport Energy Specification (TES). The TES was simulated on a neighborhood in Sao Carlos, Brazil. In the simulation, energy dependence was reduced by a factor of 8 through activity location or infrastructure modifications to the built environment.

Hybrid Algorithms for Routing and Assignment Wavelengths in Optical Networks

This paper presents a strategy for the solution of the WDM optical networks planning. Specifically, the problem of Routing and Wavelength Allocation (RWA) in order to minimize the amount of wavelengths used. In this case, the problem is known as the Min-RWA. Two meta-heuristics (Tabu Search and Simulated Annealing) are applied to take solutions of good quality and high performance. The key point is the degradation of the maximum load on the virtual links in favor of minimization of number of wavelengths used; the objective is to find a good compromise between the metrics of virtual topology (load in Gb/s) and of the physical topology (quantity of wavelengths). The simulations suggest good results when compared to some existing in the literature.

A Study of Influence of Configurations of the Windings on the Performance of Single Phase Induction Motor with Capacitor Start

The single phase induction motors needs two stator windings to produce rotating magnetic field : one main winding and the other auxiliary winding. The aim of the auxiliary winding is to create the rotating electromagnetic field when the machine is started-up and is afterwards turned off, generally through the centrifugal switch coupled together with the shaft of the machine rotor. The main purpose of this document is to evaluate the influence that the two windings have on the external characteristics of the single phase induction motor. For this purpose, two different kinds of windings were carried out and simulated, with the proposal to obtain some benefits. The main winding and the auxiliary winding were prepared and mounted on a prototype. The simulation was done via software based FEM, to make the extraction and results analysis possible. This results are shown at the end this document.