In the mood: the dynamics of collective sentiments on Twitter

We study the relationship between the sentiment levels of Twitter users and the evolving network structure that the users created by @-mentioning each other. We use a large dataset of tweets to which we apply three sentiment scoring algorithms, including the open source SentiStrength program. Specifically we make three contributions. Firstly we find that people who have potentially the largest communication reach (according to a dynamic centrality measure) use sentiment differently than the average user: for example they use positive sentiment more often and negative sentiment less often. Secondly we find that when we follow structurally stable Twitter communities over a period of months, their sentiment levels are also stable, and sudden changes in community sentiment from one day to the next can in most cases be traced to external events affecting the community. Thirdly, based on our findings, we create and calibrate a simple agent-based model that is capable of reproducing measures of emotive response comparable to those obtained from our empirical dataset.

The role of predator overlap in the robustness and extinction of a four species predator-prey network

Predators and preys often form species networks with asymmetric patterns of interaction. We study the dynamics of a four species network consisting of two weakly connected predator-prey pairs. We focus our analysis on the effects of the cross interaction between the predator of the first pair and the prey of the second pair. This is an example where the predator overlap, which is the proportion of predators that a given prey shares with other preys, is not uniform across the network due to asymmetries in patterns of interaction. We explore the behavior of the system under different interaction strengths and study the dynamics of survival and extinction. In particular, we consider situations in which the four species have initial populations lower than their long-term equilibrium, simulating catastrophic situations in which their abundances are reduced due to human action or environmental change. We show that, under these reduced initial conditions, and depending on the strength of the cross interaction, the populations tend to oscillate before re-equilibrating, disturbing the community equilibrium and sometimes reaching values that are only a small fraction of the equilibrium population, potentially leading to their extinction. We predict that, contrary to one`s intuition, the most likely scenario is the extinction of the less predated preys. (C) 2010 Elsevier B.V. All rights reserved.

What makes a species central in a cleaning mutualism network?

Mutualisms often form networks of interacting species, characterized by the existence of a central core of species that potentially drive the ecology and the evolution of the whole community. Centrality measures allow quantification of how central or peripheral a species is within a network, thus informing about the role of each species in network organization, dynamics, and stability. In the present study we addressed the question whether the structural position of species in the network (i.e. their topological importance) relates to their ecological traits. We studied interactions between cleaner and client reef fishes to identify central and peripheral species within a mutualistic network, and investigated five ecological correlates. We used three measures to estimate the level of centrality of a species for distinct structural patterns, such as the number of interactions and the structural proximity to other species. Through the use of a principal component analysis (PCA) we observed that the centrality measures were highly correlated (92.5%) in the studied network, which indicates that the same species plays a similar role for the different structural patterns. Three cleaner and ten client species had positive values of centrality, which suggests that these species are modulating ecological and evolutionary dynamics within the network. Higher centralities were related to higher abundances and feeding habits for client fishes, but not for cleaners. The high correlation between centrality measures in the present study is likely related to the nested structure of the cleaning network. The cleaner species` set, by having central species that are not necessarily the most abundant ones, bears potentially more vulnerable points for network cohesiveness. Additionally, the present study generalizes previous findings for plant-animal mutualisms, as it shows that the structure of marine mutualisms is also related to a complex interplay between abundance and niche-related features.

Changes of a mutualistic network over time: reanalysis over a 10-year period

We analyzed the structure of a multispecific network or interacting ants and plants bearing extrafloral nectaries recorded in 1990 and again in 2000 in La Mancha, Veracruz, Mexico. We assessed the replicability of the number of interactions found among species and also whether there had been changes in the network structure associated with appearance of new ant and plant species during. that 10-year period. Our results show that the nested topology of the network was similar between sampling dates, group dissimilarity increased, mean number of interactions for ant species increased, the frequency distribution of standardized degrees reached higher values for plant species, more ant species and fewer plant species constituted the core of the more recent network, and the presence of new ant and plant species increased while their contribution to nestedness remained the same. Generalist species (i.e., those with the most links or interactions) appeared to maintain the stability of the network because the new species incorporated into the communities were linked to this core of generalists. Camponotus planatus was the most extreme generalist ant species (the one with the most links) in both networks, followed by four other ant species; but other species changed either their position along the continuum of generalists relative to specialists or their presence or absence within the network. Even though new species moved into the area during the decade between the surveys, the overall network structure remained unmodified.

Effects of roads, topography, and land use on forest cover dynamics in the Brazilian Atlantic Forest

Roads and topography can determine patterns of land use and distribution of forest cover, particularly in tropical regions. We evaluated how road density, land use, and topography affected forest fragmentation, deforestation and forest regrowth in a Brazilian Atlantic Forest region near the city of Sao Paulo. We mapped roads and land use/land cover for three years (1962, 1981 and 2000) from historical aerial photographs, and summarized the distribution of roads, land use/land cover and topography within a grid of 94 non-overlapping 100 ha squares. We used generalized least squares regression models for data analysis. Our models showed that forest fragmentation and deforestation depended on topography, land use and road density, whereas forest regrowth depended primarily on land use. However, the relationships between these variables and forest dynamics changed in the two studied periods; land use and slope were the strongest predictors from 1962 to 1981, and past (1962) road density and land use were the strongest predictors for the following period (1981-2000). Roads had the strongest relationship with deforestation and forest fragmentation when the expansions of agriculture and buildings were limited to already deforested areas, and when there was a rapid expansion of development, under influence of Sao Paulo city. Furthermore, the past(1962)road network was more important than the recent road network (1981) when explaining forest dynamics between 1981 and 2000, suggesting a long-term effect of roads. Roads are permanent scars on the landscape and facilitate deforestation and forest fragmentation due to increased accessibility and land valorization, which control land-use and land-cover dynamics. Topography directly affected deforestation, agriculture and road expansion, mainly between 1962 and 1981. Forest are thus in peril where there are more roads, and long-term conservation strategies should consider ways to mitigate roads as permanent landscape features and drivers facilitators of deforestation and forest fragmentation. (C) 2009 Elsevier B.V. All rights reserved.

SZNAJD MODEL AND PROPORTIONAL ELECTIONS: THE ROLE OF THE TOPOLOGY OF THE NETWORK

The Sznajd model (SM) has been employed with success in the last years to describe opinion propagation in a community. In particular, it has been claimed that its transient is able to reproduce some scale properties observed in data of proportional elections, in different countries, if the community structure (the network) is scale-free. In this work, we investigate the properties of the transient of a particular version of the SM, introduced by Bernardes and co-authors in 2002. We studied the behavior of the model in networks of different topologies through the time evolution of an order parameter known as interface density, and concluded that regular lattices with high dimensionality also leads to a power-law distribution of the number of candidates with v votes. Also, we show that the particular absorbing state achieved in the stationary state (or else, the winner candidate), is related to a particular feature of the model, that may not be realistic in all situations.

Percolation in a network with long-range connections: Implications for cytoskeletal structure and function

Cell shape, signaling, and integrity depend on cytoskeletal organization. In this study we describe the cytoskeleton as a simple network of filamentary proteins (links) anchored by complex protein structures (nodes). The structure of this network is regulated by a distance-dependent probability of link formation as P = p/d(s), where p regulates the network density and s controls how fast the probability for link formation decays with node distance (d). It was previously shown that the regulation of the link lengths is crucial for the mechanical behavior of the cells. Here we examined the ability of the two-dimensional network to percolate (i.e. to have end-to-end connectivity), and found that the percolation threshold depends strongly on s. The system undergoes a transition around s = 2. The percolation threshold of networks with s < 2 decreases with increasing system size L, while the percolation threshold for networks with s > 2 converges to a finite value. We speculate that s < 2 may represent a condition in which cells can accommodate deformation while still preserving their mechanical integrity. Additionally, we measured the length distribution of F-actin filaments from publicly available images of a variety of cell types. In agreement with model predictions, cells originating from more deformable tissues show longer F-actin cytoskeletal filaments. (C) 2008 Elsevier B.V. All rights reserved.

The web of connections between tourism companies: Structure and dynamics

Tourism destination networks are amongst the most complex dynamical systems, involving a myriad of human-made and natural resources. In this work we report a complex network-based systematic analysis of the Elba (Italy) tourism destination network, including the characterization of its structure in terms of several traditional measurements, the investigation of its modularity, as well as its comprehensive study in terms of the recently reported superedges approach. In particular, structural (the number of paths of distinct lengths between pairs of nodes, as well as the number of reachable companies) and dynamical features (transition probabilities and the inward/outward activations and accessibilities) are measured and analyzed, leading to a series of important findings related to the interactions between tourism companies. Among the several reported results, it is shown that the type and size of the Companies influence strongly their respective activations and accessibilities, while their geographical position does not seem to matter. It is also shown that the Elba tourism network is largely fragmented and heterogeneous, so that it could benefit from increased integration. (C) 2009 Elsevier B.V. All rights reserved.

Quasi-perfect state transfer in a bosonic dissipative network

In this paper we propose a scheme for quasi-perfect state transfer in a network of dissipative harmonic oscillators. We consider ideal sender and receiver oscillators connected by a chain of nonideal transmitter oscillators coupled by nearest-neighbour resonances. From the algebraic properties of the dynamical quantities describing the evolution of the network state, we derive a criterion, fixing the coupling strengths between all the oscillators, apart from their natural frequencies, enabling perfect state transfer in the particular case of ideal transmitter oscillators. Our criterion provides an easily manipulated formula enabling perfect state transfer in the special case where the network nonidealities are disregarded. We also extend such a criterion to dissipative networks where the fidelity of the transferred state decreases due to the loss mechanisms. To circumvent almost completely the adverse effect of decoherence, we propose a protocol to achieve quasi-perfect state transfer in nonideal networks. By adjusting the common frequency of the sender and the receiver oscillators to be out of resonance with that of the transmitters, we demonstrate that the sender`s state tunnels to the receiver oscillator by virtually exciting the nonideal transmitter chain. This virtual process makes negligible the decay rate associated with the transmitter line at the expense of delaying the time interval for the state transfer process. Apart from our analytical results, numerical computations are presented to illustrate our protocol.

Dynamic Changes in the Mental Rotation Network Revealed by Pattern Recognition Analysis of fMRI Data

We investigated the temporal dynamics and changes in connectivity in the mental rotation network through the application of spatio-temporal support vector machines (SVMs). The spatio-temporal SVM [Mourao-Miranda, J., Friston, K. J., et al. (2007). Dynamic discrimination analysis: A spatial-temporal SVM. Neuroimage, 36, 88-99] is a pattern recognition approach that is suitable for investigating dynamic changes in the brain network during a complex mental task. It does not require a model describing each component of the task and the precise shape of the BOLD impulse response. By defining a time window including a cognitive event, one can use spatio-temporal fMRI observations from two cognitive states to train the SVM. During the training, the SVM finds the discriminating pattern between the two states and produces a discriminating weight vector encompassing both voxels and time (i.e., spatio-temporal maps). We showed that by applying spatio-temporal SVM to an event-related mental rotation experiment, it is possible to discriminate between different degrees of angular disparity (0 degrees vs. 20 degrees, 0 degrees vs. 60 degrees, and 0 degrees vs. 100 degrees), and the discrimination accuracy is correlated with the difference in angular disparity between the conditions. For the comparison with highest accuracy (08 vs. 1008), we evaluated how the most discriminating areas (visual regions, parietal regions, supplementary, and premotor areas) change their behavior over time. The frontal premotor regions became highly discriminating earlier than the superior parietal cortex. There seems to be a parcellation of the parietal regions with an earlier discrimination of the inferior parietal lobe in the mental rotation in relation to the superior parietal. The SVM also identified a network of regions that had a decrease in BOLD responses during the 100 degrees condition in relation to the 0 degrees condition (posterior cingulate, frontal, and superior temporal gyrus). This network was also highly discriminating between the two conditions. In addition, we investigated changes in functional connectivity between the most discriminating areas identified by the spatio-temporal SVM. We observed an increase in functional connectivity between almost all areas activated during the 100 degrees condition (bilateral inferior and superior parietal lobe, bilateral premotor area, and SMA) but not between the areas that showed a decrease in BOLD response during the 100 degrees condition.

Non-destructive evaluation tool for monitoring and detection of structural damage by using neural network.

This work studies the capability of generalization of Neural Network using vibration based measurement data aiming at operating condition and health monitoring of mechanical systems. The procedure uses the backpropagation algorithm to classify the input patters of a system with different stiffness ratios. It has been investigated a large set of input data, containing various stiffness ratios as well as a reduced set containing only the extreme ones in order to study generalizing capability of the network. This allows to definition of Neural Networks capable to use a reduced set of data during the training phase. Once it is successfully trained, it could identify intermediate failure condition. Several conditions and intensities of damages have been studied by using numerical data. The Neural Network demonstrated a good capacity of generalization for all case. Finally, the proposal was tested with experimental data.

Podzolization as a deferralitization process: dynamics and chemistry of ground and surface waters in an Acrisol-Podzol sequence of the upper Amazon Basin

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

Structural health evaluation by optimization techinique and artificial neural network

This paper presents two different approaches to detect, locate, and characterize structural damage. Both techniques utilize electrical impedance in a first stage to locate the damaged area. In the second stage, to quantify the damage severity, one can use neural network, or optimization technique. The electrical impedance-based, which utilizes the electromechanical coupling property of piezoelectric materials, has shown engineering feasibility in a variety of practical field applications. Relying on high frequency structural excitations, this technique is very sensitive to minor structural changes in the near field of the piezoelectric sensors, and therefore, it is able to detect the damage in its early stage. Optimization approaches must be used for the case where a good condensed model is known, while neural network can be also used to estimate the nature of damage without prior knowledge of the model of the structure. The paper concludes with an experimental example in a welded cubic aluminum structure, in order to verify the performance of these two proposed methodologies.

Argentina: recent dynamics in the software and IT services industry

Includes bibliography.

Network for Cooperation in Integrated Water Resource Management for Sustainable Development in Latin America and the Caribbean N° 41

• Editorial remarks.-- Open discussion: Tariffs and subsidies: the current situation and trends in the region ; State-owned utilities and the flight from public law: challenges and trends ; Challenges and opportunities in access to water and sanitation in rural areas.-- Meetings: Proposals based on the Water and Environment Initiative consensuses.-- News of the Network: Peru’s Compensation Mechanisms for Ecosystem Services Act ; Ecuador’s Act on Water Resources and Water Use and Exploitation ; The environmental dynamics of groundwater in Mexico ; The Water Citizenship Programme in the province of Mendoza, Argentina.-- Internet and WWW News