Network optimization for enhanced resilience of urban heat island measurements

The urban heat island is a well-known phenomenon that impacts a wide variety of city operations. With greater availability of cheap meteorological sensors, it is possible to measure the spatial patterns of urban atmospheric characteristics with greater resolution. To develop robust and resilient networks, recognizing sensors may malfunction, it is important to know when measurement points are providing additional information and also the minimum number of sensors needed to provide spatial information for particular applications. Here we consider the example of temperature data, and the urban heat island, through analysis of a network of sensors in the Tokyo metropolitan area (Extended METROS). The effect of reducing observation points from an existing meteorological measurement network is considered, using random sampling and sampling with clustering. The results indicated the sampling with hierarchical clustering can yield similar temperature patterns with up to a 30% reduction in measurement sites in Tokyo. The methods presented have broader utility in evaluating the robustness and resilience of existing urban temperature networks and in how networks can be enhanced by new mobile and open data sources.

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.

Contagion in financial networks: a network theory and agent-based approaches to modeling the spread of risk in financial systems

Esta dissertação estuda a propagação de crises sobre o sistema financeiro. Mais especi- ficamente, busca-se desenvolver modelos que permitam simular como um determinado choque econômico atinge determinados agentes do sistema financeiro e apartir dele se propagam, transformando-se em um problema sistêmico. A dissertação é dividida em dois capítulos,além da introdução. O primeiro capítulo desenvolve um modelo de propa- gação de crises em fundos de investimento baseado em ciência das redes.Combinando dois modelos de propagação em redes financeiras, um simulando a propagação de perdas em redes bipartites de ativos e agentes financeiros e o outro simulando a propagação de perdas em uma rede de investimentos diretos em quotas de outros agentes, desenvolve-se um algoritmo para simular a propagação de perdas através de ambos os mecanismos e utiliza-se este algoritmo para simular uma crise no mercado brasileiro de fundos de investimento. No capítulo 2,desenvolve-se um modelo de simulação baseado em agentes, com agentes financeiros, para simular propagação de um choque que afeta o mercado de operações compromissadas.Criamos também um mercado artificial composto por bancos, hedge funds e fundos de curto prazo e simulamos a propagação de um choque de liquidez sobre um ativo de risco securitizando utilizado para colateralizar operações compromissadas dos bancos.

Identification of lubricant contamination by biodiesel using vibration analysis and neural network

Purpose - The purpose of this paper is to provide information on lubricant contamination by biodiesel using vibration and neural network.Design/methodology/approach - The possible contamination of lubricants is verified by analyzing the vibration and neural network of a bench test under determinated conditions.Findings - Results have shown that classical signal analysis methods could not reveal any correlation between the signal and the presence of contamination, or contamination grade. on other hand, the use of probabilistic neural network (PNN) was very successful in the identification and classification of contamination and its grade.Research limitations/implications - This study was done for some specific kinds of biodiesel. Other types of biodiesel could be analyzed.Practical implications Contamination information is presented in the vibration signal, even if it is not evident by classical vibration analysis. In addition, the use of PNN gives a relatively simple and easy-to-use detection tool with good confidence. The training process is fast, and allows implementation of an adaptive training algorithm.Originality/value - This research could be extended to an internal combustion engine in order to verify a possible contamination by biodiesel.

Improving the passive doppler geolocation system through extension of the data reception network

O objetivo deste trabalho e apresentar uma investigação preliminar da precisão nos resultados do sistema de localização geográfica de transmissores desenvolvido utilizando o software da rede brasileira de coleta de dados. Um conjunto de medidas de desvio Doppler de uma única passagem do satélite, considerando uma Plataforma de Coleta de Dados (PCD) e uma rede de estações de recepção terrestrês, e denominado uma rede de recepção de dados. Assim, a rede brasileira de coleta de dados com o uso de múltiplas estações de recepção permitira o incremento na quantidade de dados coletados com consequente melhora na precisão e na confiabilidade das localizações fornecidas. Consequentemente uma maior quantidade de localizações válidas e mais precisas. Os resultados e análises foram obtidos sob duas condições: na primeira foi considerada uma condição prática com dados reais e dados ideais simulados, para comparar os resultados considerando a mesma passagem do satélite, transmissor e duas estações de recepção conhecidas; na segunda foram consideradas as condições ideais simuladas a partir de medidas de um transmissor fixo, três estações de recepção e dois satélites. Os resultados utilizando a rede de recepção de dados foram bastante satisfatórios. O estudo realizado mostrou a importãncia da instalação de novas estações de recepção terrenas distribuídas no territorio nacional, para um aumento na quantidade de medidas e consequentemente uma maior quantidade de localizações válidas e mais precisas.

Brazilian network for the surveillance of maternal potentially life threatening morbidity and maternal near-miss and a multidimensional evaluation of their long term consequences

Background. It has been suggested that the study of women who survive life-threatening complications related to pregnancy (maternal near-miss cases) may represent a practical alternative to surveillance of maternal morbidity/mortality since the number of cases is higher and the woman herself is able to provide information on the difficulties she faced and the long-term repercussions of the event. These repercussions, which may include sexual dysfunction, postpartum depression and posttraumatic stress disorder, may persist for prolonged periods of time, affecting women's quality of life and resulting in adverse effects to them and their babies. Objective. The aims of the present study are to create a nationwide network of scientific cooperation to carry out surveillance and estimate the frequency of maternal near-miss cases, to perform a multicenter investigation into the quality of care for women with severe complications of pregnancy, and to carry out a multidimensional evaluation of these women up to six months. Methods/Design. This project has two components: a multicenter, cross-sectional study to be implemented in 27 referral obstetric units in different geographical regions of Brazil, and a concurrent cohort study of multidimensional analysis. Over 12 months, investigators will perform prospective surveillance to identify all maternal complications. The population of the cross-sectional component will consist of all women surviving potentially life-threatening conditions (severe maternal complications) or life-threatening conditions (the maternal near miss criteria) and maternal deaths according to the new WHO definition and criteria. Data analysis will be performed in case subgroups according to the moment of occurrence and determining cause. Frequencies of near-miss and other severe maternal morbidity and the association between organ dysfunction and maternal death will be estimated. A proportion of cases identified in the cross-sectional study will comprise the cohort of women for the multidimensional analysis. Various aspects of the lives of women surviving severe maternal complications will be evaluated 3 and 6 months after the event and compared to a group of women who suffered no severe complications in pregnancy. Previously validated questionnaires will be used in the interviews to assess reproductive function, posttraumatic stress, functional capacity, quality of life, sexual function, postpartum depression and infant development. © 2009 Cecatti et al.

Modernization and new services of the Brazilian active control network

The Brazilian Network for Continuous Monitoring of GNSS - RBMC is a national network of continuously operating reference GNSS stations. Since its establishment in December of 1996, it has been playing an essential role for the maintenance and user access of the fundamental geodetic frame in the country. In order to provide better services for RBMC, the Brazilian Institute of Geography and Statistics - IBGE and the National Institute of Colonization and Land Reform - INCRA are both partners involved in the National Geospatial Framework Project - PIGN. This paper provides an overview of the recent modernization phases the RBMC network has undergone highlighting its future steps. These steps involve the installation of new equipment, provide real time data from a group of core stations and compute real-time DGPS corrections, based on CDGPS (The real-time Canada-Wide DGPS Service) (The Real-Time Canada-Wide DGPS Service. http://www.cdgps.com/ 2009a). In addition to this, a post-mission Precise Point Positioning (PPP) service has been established based on the current Geodetic Survey Division of NRCan (CSRS-PPP) service. This service is operational since April 2009 and is in large use in the country. All activities mentioned before are based on a cooperation signed at the end of 2004 with the University of New Brunswick, supported by the Canadian International Development Agency and the Brazilian Cooperation Agency. The Geodetic Survey Division of NRCan is also participating in this modernization effort under the same project. This infrastructure of 66 GNSS stations, the real time, post processing services and the potentiality of providing Wide Area DGPS corrections in the future show that the RBMC system is comparable to those available in USA and Europe. © Springer-Verlag Berlin Heidelberg 2012.

Prediction of Oncogenic Interactions and Cancer-Related Signaling Networks Based on Network Topology

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

Decay of interspecific avian flock networks along a disturbance gradient in Amazonia

Our understanding of how anthropogenic habitat change shapes species interactions is in its infancy. This is in large part because analytical approaches such as network theory have only recently been applied to characterize complex community dynamics. Network models are a powerful tool for quantifying how ecological interactions are affected by habitat modification because they provide metrics that quantify community structure and function. Here, we examine how large-scale habitat alteration has affected ecological interactions among mixed-species flocking birds in Amazonian rainforest. These flocks provide a model system for investigating how habitat heterogeneity influences non-trophic interactions and the subsequent social structure of forest-dependent mixed-species bird flocks. We analyse 21 flock interaction networks throughout a mosaic of primary forest, fragments of varying sizes and secondary forest (SF) at the Biological Dynamics of Forest Fragments Project in central Amazonian Brazil. Habitat type had a strong effect on network structure at the levels of both species and flock. Frequency of associations among species, as summarized by weighted degree, declined with increasing levels of forest fragmentation and SF. At the flock level, clustering coefficients and overall attendance positively correlated with mean vegetation height, indicating a strong effect of habitat structure on flock cohesion and stability. Prior research has shown that trophic interactions are often resilient to large-scale changes in habitat structure because species are ecologically redundant. By contrast, our results suggest that behavioural interactions and the structure of non-trophic networks are highly sensitive to environmental change. Thus, a more nuanced, system-by-system approach may be needed when thinking about the resiliency of ecological networks.

Disentangling social networks from spatiotemporal dynamics: the temporal structure of a dolphin society

Social networks are static illustrations of dynamic societies, within which social interactions are constantly changing. Fundamental sources of variation include ranging behaviour and temporal demographic changes. Spatiotemporal dynamics can favour or limit opportunities for individuals to interact, and then a network may not essentially represent social processes. We examined whether a social network can embed such nonsocial effects in its topology, whereby emerging modules depict spatially or temporally segregated individuals. To this end, we applied a combination of spatial, temporal and demographic analyses to a long-term study of the association patterns of Guiana dolphins, Sotalia guianensis. We found that association patterns are organized into a modular social network. Space use was unlikely to reflect these modules, since dolphins' ranging behaviour clearly overlapped. However, a temporal demographic turnover, caused by the exit/entrance of individuals (most likely emigration/immigration), defined three modules of associations occurring at different times. Although this factor could mask real social processes, we identified the temporal scale that allowed us to account for these demographic effects. By looking within this turnover period (32 months), we assessed fission-fusion dynamics of the poorly known social organization of Guiana dolphins. We highlight that spatiotemporal dynamics can strongly influence the structure of social networks. Our findings show that hypothetical social units can emerge due to the temporal opportunities for individuals to interact. Therefore, a thorough search for a satisfactory spatiotemporal scale that removes such nonsocial noise is critical when analysing a social system. (C) 2012 The Association for the Study of Animal Behaviour. Published by Elsevier Ltd. All rights reserved.

Modeling the Emergence of Circadian Rhythms in a Clock Neuron Network

Circadian rhythms in pacemaker cells persist for weeks in constant darkness, while in other types of cells the molecular oscillations that underlie circadian rhythms damp rapidly under the same conditions. Although much progress has been made in understanding the biochemical and cellular basis of circadian rhythms, the mechanisms leading to damped or self-sustained oscillations remain largely unknown. There exist many mathematical models that reproduce the circadian rhythms in the case of a single cell of the Drosophila fly. However, not much is known about the mechanisms leading to coherent circadian oscillation in clock neuron networks. In this work we have implemented a model for a network of interacting clock neurons to describe the emergence (or damping) of circadian rhythms in Drosophila fly, in the absence of zeitgebers. Our model consists of an array of pacemakers that interact through the modulation of some parameters by a network feedback. The individual pacemakers are described by a well-known biochemical model for circadian oscillation, to which we have added degradation of PER protein by light and multiplicative noise. The network feedback is the PER protein level averaged over the whole network. In particular, we have investigated the effect of modulation of the parameters associated with (i) the control of net entrance of PER into the nucleus and (ii) the non-photic degradation of PER. Our results indicate that the modulation of PER entrance into the nucleus allows the synchronization of clock neurons, leading to coherent circadian oscillations under constant dark condition. On the other hand, the modulation of non-photic degradation cannot reset the phases of individual clocks subjected to intrinsic biochemical noise.

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

Describing and explaining the foreign expansion of network managing electronic business companies (NM-EBCs)

This study deals with the internationalization behavior of a new and specific type of e-business company, namely the network managing e-business company (NM-EBC). The business model of such e-business companies is based on providing a platform and applications for users to connect and interact, on gathering and channeling the inputs provided by the users, and on organizing and managing the cross-relationships of the various participants. Examples are online communities, matching platforms, and portals. Since NM-EBCs internationalize by replicating their business model in a foreign market and by building up and managing a network of users, who provide input themselves and interact with each other, they have to convince users in foreign markets to join the network and hence to adopt their platform. We draw upon Rogers’ Diffusion of Innovations Theory and Network Theory to explain the internationalization behavior of NM-EBCs. These two theories originate from neighboring disciplines and have not yet been used to explain the internationalization of firms. We combine both theories and formulate hypotheses about which strategies NM-EBCs may choose to expand abroad. To test the applicability of our theory and to gain rich data about the internationalization behavior of these firms, we carried out multiple case studies with internationally active Germany-based NM-EBCs.

Long-term immunologic response to antiretroviral therapy in low-income countries: a collaborative analysis of prospective studies

BACKGROUND: Few data are available on the long-term immunologic response to antiretroviral therapy (ART) in resource-limited settings, where ART is being rapidly scaled up using a public health approach, with a limited repertoire of drugs. OBJECTIVES: To describe immunologic response to ART among ART patients in a network of cohorts from sub-Saharan Africa, Latin America, and Asia. STUDY POPULATION/METHODS: Treatment-naive patients aged 15 and older from 27 treatment programs were eligible. Multilevel, linear mixed models were used to assess associations between predictor variables and CD4 cell count trajectories following ART initiation. RESULTS: Of 29 175 patients initiating ART, 8933 (31%) were excluded due to insufficient follow-up time and early lost to follow-up or death. The remaining 19 967 patients contributed 39 200 person-years on ART and 71 067 CD4 cell count measurements. The median baseline CD4 cell count was 114 cells/microl, with 35% having less than 100 cells/microl. Substantial intersite variation in baseline CD4 cell count was observed (range 61-181 cells/microl). Women had higher median baseline CD4 cell counts than men (121 vs. 104 cells/microl). The median CD4 cell count increased from 114 cells/microl at ART initiation to 230 [interquartile range (IQR) 144-338] at 6 months, 263 (IQR 175-376) at 1 year, 336 (IQR 224-472) at 2 years, 372 (IQR 242-537) at 3 years, 377 (IQR 221-561) at 4 years, and 395 (IQR 240-592) at 5 years. In multivariable models, baseline CD4 cell count was the most important determinant of subsequent CD4 cell count trajectories. CONCLUSION: These data demonstrate robust and sustained CD4 response to ART among patients remaining on therapy. Public health and programmatic interventions leading to earlier HIV diagnosis and initiation of ART could substantially improve patient outcomes in resource-limited settings.

Learning flexible sensori-motor mappings in a complex network

Given the complex structure of the brain, how can synaptic plasticity explain the learning and forgetting of associations when these are continuously changing? We address this question by studying different reinforcement learning rules in a multilayer network in order to reproduce monkey behavior in a visuomotor association task. Our model can only reproduce the learning performance of the monkey if the synaptic modifications depend on the pre- and postsynaptic activity, and if the intrinsic level of stochasticity is low. This favored learning rule is based on reward modulated Hebbian synaptic plasticity and shows the interesting feature that the learning performance does not substantially degrade when adding layers to the network, even for a complex problem.