Predicting epidemic outbreak from individual features of the spreaders

Knowing which individuals can be more efficient in spreading a pathogen throughout a determinate environment is a fundamental question in disease control. Indeed, over recent years the spread of epidemic diseases and its relationship with the topology of the involved system have been a recurrent topic in complex network theory, taking into account both network models and real-world data. In this paper we explore possible correlations between the heterogeneous spread of an epidemic disease governed by the susceptible-infected-recovered (SIR) model, and several attributes of the originating vertices, considering Erdos-Renyi (ER), Barabasi-Albert (BA) and random geometric graphs (RGG), as well as a real case study, the US air transportation network, which comprises the 500 busiest airports in the US along with inter-connections. Initially, the heterogeneity of the spreading is achieved by considering the RGG networks, in which we analytically derive an expression for the distribution of the spreading rates among the established contacts, by assuming that such rates decay exponentially with the distance that separates the individuals. Such a distribution is also considered for the ER and BA models, where we observe topological effects on the correlations. In the case of the airport network, the spreading rates are empirically defined, assumed to be directly proportional to the seat availability. Among both the theoretical and real networks considered, we observe a high correlation between the total epidemic prevalence and the degree, as well as the strength and the accessibility of the epidemic sources. For attributes such as the betweenness centrality and the k-shell index, however, the correlation depends on the topology considered.

Efficient Forest Data Structure for Evolutionary Algorithms Applied to Network Design

The design of a network is a solution to several engineering and science problems. Several network design problems are known to be NP-hard, and population-based metaheuristics like evolutionary algorithms (EAs) have been largely investigated for such problems. Such optimization methods simultaneously generate a large number of potential solutions to investigate the search space in breadth and, consequently, to avoid local optima. Obtaining a potential solution usually involves the construction and maintenance of several spanning trees, or more generally, spanning forests. To efficiently explore the search space, special data structures have been developed to provide operations that manipulate a set of spanning trees (population). For a tree with n nodes, the most efficient data structures available in the literature require time O(n) to generate a new spanning tree that modifies an existing one and to store the new solution. We propose a new data structure, called node-depth-degree representation (NDDR), and we demonstrate that using this encoding, generating a new spanning forest requires average time O(root n). Experiments with an EA based on NDDR applied to large-scale instances of the degree-constrained minimum spanning tree problem have shown that the implementation adds small constants and lower order terms to the theoretical bound.

The participation of the nutritionist in Primary Health Care in a large urban center

Nutritionists are important professionals for ensuring the implementation of health promotion, treatment and rehabilitation. However, their participation in primary healthcare from a quantitative standpoint is limited. The city of Sao Paulo has experienced an uneven urbanization process triggering new problems of insecurity in terms of food and nutrition. This article analyzes the performance of the primary healthcare nutritionist in a large urban center. It is a quantitative study that used data from the Municipal Health Department, population data of Sao Paulo and a semi-structured questionnaire applied in individual interviews. All regions of the city are found to have fewer nutritionists than the recommendation of the Federal Council of Nutritionists. There are 123 nutritionists in the basic healthcare network and 51 in the Family Health Support Nuclei (FHSN) (57.3%). Each nutritionist from the FHSN accompanies 7.1 family health strategy teams on average. The age groups corresponding to children are less frequently seen by nutritionists. Comparing the activities, the transition from a model of primary health care focused on individual care to a model that prioritizes group care was observed.

Complex network classification using partially self-avoiding deterministic walks

Complex networks have attracted increasing interest from various fields of science. It has been demonstrated that each complex network model presents specific topological structures which characterize its connectivity and dynamics. Complex network classification relies on the use of representative measurements that describe topological structures. Although there are a large number of measurements, most of them are correlated. To overcome this limitation, this paper presents a new measurement for complex network classification based on partially self-avoiding walks. We validate the measurement on a data set composed by 40000 complex networks of four well-known models. Our results indicate that the proposed measurement improves correct classification of networks compared to the traditional ones. (C) 2012 American Institute of Physics. [http://dx.doi.org/10.1063/1.4737515]

Optimization of Large-Scale Hydrothermal System Operation

This paper presents the development of a mathematical model to optimize the management and operation of the Brazilian hydrothermal system. The system consists of a large set of individual hydropower plants and a set of aggregated thermal plants. The energy generated in the system is interconnected by a transmission network so it can be transmitted to centers of consumption throughout the country. The optimization model offered is capable of handling different types of constraints, such as interbasin water transfers, water supply for various purposes, and environmental requirements. Its overall objective is to produce energy to meet the country's demand at a minimum cost. Called HIDROTERM, the model integrates a database with basic hydrological and technical information to run the optimization model, and provides an interface to manage the input and output data. The optimization model uses the General Algebraic Modeling System (GAMS) package and can invoke different linear as well as nonlinear programming solvers. The optimization model was applied to the Brazilian hydrothermal system, one of the largest in the world. The system is divided into four subsystems with 127 active hydropower plants. Preliminary results under different scenarios of inflow, demand, and installed capacity demonstrate the efficiency and utility of the model. From this and other case studies in Brazil, the results indicate that the methodology developed is suitable to different applications, such as planning operation, capacity expansion, and operational rule studies, and trade-off analysis among multiple water users. DOI: 10.1061/(ASCE)WR.1943-5452.0000149. (C) 2012 American Society of Civil Engineers.

Aerial Rivers and Lakes: Looking at Large-Scale Moisture Transport and Its Relation to Amazonia and to Subtropical Rainfall in South America

This is an observational study of the large-scale moisture transport over South America, with some analyses on its relation to subtropical rainfall. The concept of aerial rivers is proposed as a framework: it is an analogy between the main pathways of moisture flow in the atmosphere and surface rivers. Opposite to surface rivers, aerial rivers gain (lose) water through evaporation (precipitation). The magnitude of the vertically integrated moisture transport is discharge, and precipitable water is like the mass of the liquid column-multiplied by an equivalent speed it gives discharge. Trade wind flow into Amazonia, and the north/northwesterly flow to the subtropics, east of the Andes, are aerial rivers. Aerial lakes are the sections of a moisture pathway where the flow slows down and broadens, because of diffluence, and becomes deeper, with higher precipitable water. This is the case over Amazonia, downstream of the trade wind confluence. In the dry season, moisture from the aerial lake is transported northeastward, but weaker flow over southern Amazonia heads southward toward the subtropics. Southern Amazonia appears as a source of moisture to this flow. Aerial river discharge to the subtropics is comparable to that of the Amazon River. The variations of the amount of moisture coming from Amazonia have an important effect over the variability of discharge. Correlations between the flow from Amazonia and subtropical rainfall are not strong. However, some months within the set of dry seasons observed showed a strong increase (decrease) occurring together with an important increase (decrease) in subtropical rainfall.

Fog- and cloud-induced aerosol modification observed by the Aerosol Robotic Network (AERONET)

Large fine mode-dominated aerosols (submicron radius) in size distributions retrieved from the Aerosol Robotic Network (AERONET) have been observed after fog or low-altitude cloud dissipation events. These column-integrated size distributions have been obtained at several sites in many regions of the world, typically after evaporation of low-altitude cloud such as stratocumulus or fog. Retrievals with cloud-processed aerosol are sometimes bimodal in the accumulation mode with the larger-size mode often similar to 0.4-0.5 mu m radius (volume distribution); the smaller mode, typically similar to 0.12 to similar to 0.20 mu m, may be interstitial aerosol that were not modified by incorporation in droplets and/or aerosol that are less hygroscopic in nature. Bimodal accumulation mode size distributions have often been observed from in situ measurements of aerosols that have interacted with clouds, and AERONET size distribution retrievals made after dissipation of cloud or fog are in good agreement with particle sizes measured by in situ techniques for cloud-processed aerosols. Aerosols of this type and large size range (in lower concentrations) may also be formed by cloud processing in partly cloudy conditions and may contribute to the "shoulder" of larger-size particles in the accumulation mode retrievals, especially in regions where sulfate and other soluble aerosol are a significant component of the total aerosol composition. Observed trends of increasing aerosol optical depth (AOD) as fine mode radius increased suggests higher AOD in the near-cloud environment and higher overall AOD than typically obtained from remote sensing owing to bias toward sampling at low cloud fraction.

Ground-level ozone prediction using a neural network model based on meteorological variables and applied to the metropolitan area of Sao Paulo

A neural network model to predict ozone concentration in the Sao Paulo Metropolitan Area was developed, based on average values of meteorological variables in the morning (8:00-12:00 hr) and afternoon (13:00-17: 00 hr) periods. Outputs are the maximum and average ozone concentrations in the afternoon (12:00-17:00 hr). The correlation coefficient between computed and measured values was 0.82 and 0.88 for the maximum and average ozone concentration, respectively. The model presented good performance as a prediction tool for the maximum ozone concentration. For prediction periods from 1 to 5 days 0 to 23% failures (95% confidence) were obtained.

LARGE-SCALE DISTRIBUTION OF ARRIVAL DIRECTIONS OF COSMIC RAYS DETECTED ABOVE 10(18) eV AT THE PIERRE AUGER OBSERVATORY

A thorough search for large-scale anisotropies in the distribution of arrival directions of cosmic rays detected above 10(18) eV at the Pierre Auger Observatory is presented. This search is performed as a function of both declination and right ascension in several energy ranges above 10(18) eV, and reported in terms of dipolar and quadrupolar coefficients. Within the systematic uncertainties, no significant deviation from isotropy is revealed. Assuming that any cosmic-ray anisotropy is dominated by dipole and quadrupole moments in this energy range, upper limits on their amplitudes are derived. These upper limits allow us to test the origin of cosmic rays above 10(18) eV from stationary Galactic sources densely distributed in the Galactic disk and predominantly emitting light particles in all directions.

Do charges to freight trucks and trains in the European Union reflect their social marginal costs? Application to the case of Spain

In the last few years, the European Union (EU) has become greatly concerned about the environmental costs of road transport in Europe as a result of the constant growth in the market share of trucks and the steady decline in the market share of railroads. In order to reverse this trend, the EU is promoting the implementation of additional charges for heavy goods vehicles (HGV) on the trunk roads of the EU countries. However, the EU policy is being criticised because it does not address the implementation of charges to internalise the external costs produced by automobiles and other transport modes such as railroad. In this paper, we first describe the evolution of the HGV charging policy in the EU, and then assess its practical implementation across different European countries. Second, and of greater significance, by using the case study of Spain, we evaluate to what extent the current fees on trucks and trains reflect their social marginal costs, and consequently lead to an allocative-efficient outcome. We found that for the average case in Spain the truck industry meets more of the marginal social cost produced by it than does the freight railroad industry. The reason for this lies in the large sums of money paid by truck companies in fuel taxes, and the subsidies that continue to be granted by the government to the railroads.

Modularity and evolutionary constraints in a baculovirus gene regulatory network

Abstract Background The structure of regulatory networks remains an open question in our understanding of complex biological systems. Interactions during complete viral life cycles present unique opportunities to understand how host-parasite network take shape and behave. The Anticarsia gemmatalis multiple nucleopolyhedrovirus (AgMNPV) is a large double-stranded DNA virus, whose genome may encode for 152 open reading frames (ORFs). Here we present the analysis of the ordered cascade of the AgMNPV gene expression. Results We observed an earlier onset of the expression than previously reported for other baculoviruses, especially for genes involved in DNA replication. Most ORFs were expressed at higher levels in a more permissive host cell line. Genes with more than one copy in the genome had distinct expression profiles, which could indicate the acquisition of new functionalities. The transcription gene regulatory network (GRN) for 149 ORFs had a modular topology comprising five communities of highly interconnected nodes that separated key genes that are functionally related on different communities, possibly maximizing redundancy and GRN robustness by compartmentalization of important functions. Core conserved functions showed expression synchronicity, distinct GRN features and significantly less genetic diversity, consistent with evolutionary constraints imposed in key elements of biological systems. This reduced genetic diversity also had a positive correlation with the importance of the gene in our estimated GRN, supporting a relationship between phylogenetic data of baculovirus genes and network features inferred from expression data. We also observed that gene arrangement in overlapping transcripts was conserved among related baculoviruses, suggesting a principle of genome organization. Conclusions Albeit with a reduced number of nodes (149), the AgMNPV GRN had a topology and key characteristics similar to those observed in complex cellular organisms, which indicates that modularity may be a general feature of biological gene regulatory networks.

What drives the seasonality of photosynthesis across the Amazon basin? A cross-site analysis of eddy flux tower measurements from the Brasil flux network

We investigated the seasonal patterns of Amazonian forest photosynthetic activity, and the effects thereon of variations in climate and land-use, by integrating data from a network of ground-based eddy flux towers in Brazil established as part of the ‘Large-Scale Biosphere Atmosphere Experiment in Amazonia’ project. We found that degree of water limitation, as indicated by the seasonality of the ratio of sensible to latent heat flux (Bowen ratio) predicts seasonal patterns of photosynthesis. In equatorial Amazonian forests (5◦ N–5◦ S), water limitation is absent, and photosynthetic fluxes (or gross ecosystem productivity, GEP) exhibit high or increasing levels of photosynthetic activity as the dry season progresses, likely a consequence of allocation to growth of new leaves. In contrast, forests along the southern flank of the Amazon, pastures converted from forest, and mixed forest-grass savanna, exhibit dry-season declines in GEP, consistent with increasing degrees of water limitation. Although previous work showed tropical ecosystem evapotranspiration (ET) is driven by incoming radiation, GEP observations reported here surprisingly show no or negative relationships with photosynthetically active radiation (PAR). Instead, GEP fluxes largely followed the phenology of canopy photosynthetic capacity (Pc), with only deviations from this primary pattern driven by variations in PAR. Estimates of leaf flush at three

Multi-objective evolutionary algorithm for single and multiple fault service restoration in large-scale distribution systems

Network reconfiguration for service restoration (SR) in distribution systems is a complex optimization problem. For large-scale distribution systems, it is computationally hard to find adequate SR plans in real time since the problem is combinatorial and non-linear, involving several constraints and objectives. Two Multi-Objective Evolutionary Algorithms that use Node-Depth Encoding (NDE) have proved able to efficiently generate adequate SR plans for large distribution systems: (i) one of them is the hybridization of the Non-Dominated Sorting Genetic Algorithm-II (NSGA-II) with NDE, named NSGA-N; (ii) the other is a Multi-Objective Evolutionary Algorithm based on subpopulation tables that uses NDE, named MEAN. Further challenges are faced now, i.e. the design of SR plans for larger systems as good as those for relatively smaller ones and for multiple faults as good as those for one fault (single fault). In order to tackle both challenges, this paper proposes a method that results from the combination of NSGA-N, MEAN and a new heuristic. Such a heuristic focuses on the application of NDE operators to alarming network zones according to technical constraints. The method generates similar quality SR plans in distribution systems of significantly different sizes (from 3860 to 30,880 buses). Moreover, the number of switching operations required to implement the SR plans generated by the proposed method increases in a moderate way with the number of faults.