high consequence networked: Topics by Science.gov

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Unraveling the disease consequences and mechanisms of modular structure in animal social networks

PubMed Central

Leu, Stephan T.; Cross, Paul C.; Hudson, Peter J.; Bansal, Shweta

2017-01-01

Disease risk is a potential cost of group living. Although modular organization is thought to reduce this cost in animal societies, empirical evidence toward this hypothesis has been conflicting. We analyzed empirical social networks from 43 animal species to motivate our study of the epidemiological consequences of modular structure in animal societies. From these empirical studies, we identified the features of interaction patterns associated with network modularity and developed a theoretical network model to investigate when and how subdivisions in social networks influence disease dynamics. Contrary to prior work, we found that disease risk is largely unaffected by modular structure, although social networks beyond a modular threshold experience smaller disease burden and longer disease duration. Our results illustrate that the lowering of disease burden in highly modular social networks is driven by two mechanisms of modular organization: network fragmentation and subgroup cohesion. Highly fragmented social networks with cohesive subgroups are able to structurally trap infections within a few subgroups and also cause a structural delay to the spread of disease outbreaks. Finally, we show that network models incorporating modular structure are necessary only when prior knowledge suggests that interactions within the population are highly subdivided. Otherwise, null networks based on basic knowledge about group size and local contact heterogeneity may be sufficient when data-limited estimates of epidemic consequences are necessary. Overall, our work does not support the hypothesis that modular structure universally mitigates the disease impact of group living. PMID:28373567
Unraveling the disease consequences and mechanisms of modular structure in animal social networks

USGS Publications Warehouse

Sah, Pratha; Leu, Stephan T.; Cross, Paul C.; Hudson, Peter J.; Bansal, Shweta

2017-01-01

Disease risk is a potential cost of group living. Although modular organization is thought to reduce this cost in animal societies, empirical evidence toward this hypothesis has been conflicting. We analyzed empirical social networks from 43 animal species to motivate our study of the epidemiological consequences of modular structure in animal societies. From these empirical studies, we identified the features of interaction patterns associated with network modularity and developed a theoretical network model to investigate when and how subdivisions in social networks influence disease dynamics. Contrary to prior work, we found that disease risk is largely unaffected by modular structure, although social networks beyond a modular threshold experience smaller disease burden and longer disease duration. Our results illustrate that the lowering of disease burden in highly modular social networks is driven by two mechanisms of modular organization: network fragmentation and subgroup cohesion. Highly fragmented social networks with cohesive subgroups are able to structurally trap infections within a few subgroups and also cause a structural delay to the spread of disease outbreaks. Finally, we show that network models incorporating modular structure are necessary only when prior knowledge suggests that interactions within the population are highly subdivided. Otherwise, null networks based on basic knowledge about group size and local contact heterogeneity may be sufficient when data-limited estimates of epidemic consequences are necessary. Overall, our work does not support the hypothesis that modular structure universally mitigates the disease impact of group living.
Unraveling the disease consequences and mechanisms of modular structure in animal social networks.

PubMed

Sah, Pratha; Leu, Stephan T; Cross, Paul C; Hudson, Peter J; Bansal, Shweta

2017-04-18

Disease risk is a potential cost of group living. Although modular organization is thought to reduce this cost in animal societies, empirical evidence toward this hypothesis has been conflicting. We analyzed empirical social networks from 43 animal species to motivate our study of the epidemiological consequences of modular structure in animal societies. From these empirical studies, we identified the features of interaction patterns associated with network modularity and developed a theoretical network model to investigate when and how subdivisions in social networks influence disease dynamics. Contrary to prior work, we found that disease risk is largely unaffected by modular structure, although social networks beyond a modular threshold experience smaller disease burden and longer disease duration. Our results illustrate that the lowering of disease burden in highly modular social networks is driven by two mechanisms of modular organization: network fragmentation and subgroup cohesion. Highly fragmented social networks with cohesive subgroups are able to structurally trap infections within a few subgroups and also cause a structural delay to the spread of disease outbreaks. Finally, we show that network models incorporating modular structure are necessary only when prior knowledge suggests that interactions within the population are highly subdivided. Otherwise, null networks based on basic knowledge about group size and local contact heterogeneity may be sufficient when data-limited estimates of epidemic consequences are necessary. Overall, our work does not support the hypothesis that modular structure universally mitigates the disease impact of group living.
Formulation and Optimization of Robust Sensor Placement Problems for Drinking Water Contamination Warning Systems

DOE PAGES

Watson, Jean-Paul; Murray, Regan; Hart, William E.

2009-11-13

We report that the sensor placement problem in contamination warning system design for municipal water distribution networks involves maximizing the protection level afforded by limited numbers of sensors, typically quantified as the expected impact of a contamination event; the issue of how to mitigate against high-consequence events is either handled implicitly or ignored entirely. Consequently, expected-case sensor placements run the risk of failing to protect against high-consequence 9/11-style attacks. In contrast, robust sensor placements address this concern by focusing strictly on high-consequence events and placing sensors to minimize the impact of these events. We introduce several robust variations of themore » sensor placement problem, distinguished by how they quantify the potential damage due to high-consequence events. We explore the nature of robust versus expected-case sensor placements on three real-world large-scale distribution networks. We find that robust sensor placements can yield large reductions in the number and magnitude of high-consequence events, with only modest increases in expected impact. Finally, the ability to trade-off between robust and expected-case impacts is a key unexplored dimension in contamination warning system design.« less
Hardware Neural Network for a Visual Inspection System

NASA Astrophysics Data System (ADS)

Chun, Seungwoo; Hayakawa, Yoshihiro; Nakajima, Koji

The visual inspection of defects in products is heavily dependent on human experience and instinct. In this situation, it is difficult to reduce the production costs and to shorten the inspection time and hence the total process time. Consequently people involved in this area desire an automatic inspection system. In this paper, we propose a hardware neural network, which is expected to provide high-speed operation for automatic inspection of products. Since neural networks can learn, this is a suitable method for self-adjustment of criteria for classification. To achieve high-speed operation, we use parallel and pipelining techniques. Furthermore, we use a piecewise linear function instead of a conventional activation function in order to save hardware resources. Consequently, our proposed hardware neural network achieved 6GCPS and 2GCUPS, which in our test sample proved to be sufficiently fast.
Trophic level, successional age and trait matching determine specialization of deadwood-based interaction networks of saproxylic beetles

PubMed Central

Gossner, Martin M.; Grass, Ingo; Arnstadt, Tobias; Hofrichter, Martin; Floren, Andreas; Linsenmair, Karl Eduard; Weisser, Wolfgang W.; Steffan-Dewenter, Ingolf

2017-01-01

The specialization of ecological networks provides important insights into possible consequences of biodiversity loss for ecosystem functioning. However, mostly mutualistic and antagonistic interactions of living organisms have been studied, whereas detritivore networks and their successional changes are largely unexplored. We studied the interactions of saproxylic (deadwood-dependent) beetles with their dead host trees. In a large-scale experiment, 764 logs of 13 tree species were exposed to analyse network structure of three trophic groups of saproxylic beetles over 3 successional years. We found remarkably high specialization of deadwood-feeding xylophages and lower specialization of fungivorous and predatory species. During deadwood succession, community composition, network specialization and network robustness changed differently for the functional groups. To reveal potential drivers of network specialization, we linked species' functional traits to their network roles, and tested for trait matching between plant (i.e. chemical compounds) and beetle (i.e. body size) traits. We found that both plant and animal traits are major drivers of species specialization, and that trait matching can be more important in explaining interactions than neutral processes reflecting species abundance distributions. High network specialization in the early successional stage and decreasing network robustness during succession indicate vulnerability of detritivore networks to reduced tree species diversity and beetle extinctions, with unknown consequences for wood decomposition and nutrient cycling. PMID:28469020
Inequality and visibility of wealth in experimental social networks.

PubMed

Nishi, Akihiro; Shirado, Hirokazu; Rand, David G; Christakis, Nicholas A

2015-10-15

Humans prefer relatively equal distributions of resources, yet societies have varying degrees of economic inequality. To investigate some of the possible determinants and consequences of inequality, here we perform experiments involving a networked public goods game in which subjects interact and gain or lose wealth. Subjects (n = 1,462) were randomly assigned to have higher or lower initial endowments, and were embedded within social networks with three levels of economic inequality (Gini coefficient = 0.0, 0.2, and 0.4). In addition, we manipulated the visibility of the wealth of network neighbours. We show that wealth visibility facilitates the downstream consequences of initial inequality-in initially more unequal situations, wealth visibility leads to greater inequality than when wealth is invisible. This result reflects a heterogeneous response to visibility in richer versus poorer subjects. We also find that making wealth visible has adverse welfare consequences, yielding lower levels of overall cooperation, inter-connectedness, and wealth. High initial levels of economic inequality alone, however, have relatively few deleterious welfare effects.
Professional Networking: A New Strategy for Improving Administrative Competence.

ERIC Educational Resources Information Center

Murphy, Peter J.

1985-01-01

A trend toward establishment of professional networks and exchanges among administrators in all kinds of educational institutions for the purpose of professional development and information exchange is emerging around the world. Although costs are high and benefits often difficult to measure, the consequences may be far-reaching. (MSE)
Optimal Scheduling for Underwater Communications in Multiple-User Scenarios

DTIC Science & Technology

2015-09-30

term goals of this project is to analyze and propose energy-efficient communication techniques for underwater acoustic sensor networks . These...investigate the possibility that these underwater acoustic networks disrupt the behavior of surrounding species of marine mammals. As a consequence of... underwater VHF acoustics , high data rate/short range acoustic communications and networking , and acoustic sensing in the VHF regime. WORK COMPLETED We
A Heuristic Decision Making Model to Mitigate Adverse Consequences in a Network Centric Warfare/Sense and Respond System

DTIC Science & Technology

2005-05-01

made. 4. Do military decision makers identify / analyze adverse consequences presently? Few do based on this research and most don’t do it effectively ...A HEURISTIC DECISION MAKING MODEL TO MITIGATE ADVERSE CONSEQUENCES IN A NETWORK CENTRIC WARFARE / SENSE AND RESPOND SYSTEM...ENS/05-01 A HEURISTIC DECISION MAKING MODEL TO MITIGATE ADVERSE CONSEQUENCES IN A NETWORK CENTRIC WARFARE / SENSE AND RESPOND SYSTEM
The perceived causal structures of smoking: Smoker and non-smoker comparisons

PubMed Central

Lydon, David M; Howard, Matthew C; Wilson, Stephen J; Geier, Charles F

2015-01-01

Despite the detrimental impact of smoking on health, its prevalence remains high. Empirical research has provided insight into the many causes and effects of smoking, yet lay perceptions of smoking remain relatively understudied. The current study used a form of network analysis to gain insight into the causal attributions for smoking of both smoking and non-smoking college students. The analyses resulted in highly endorsed, complex network diagrams that conveyed the perceived causal structures of smoking. Differences in smoker and non-smoker networks emerged with smokers attributing less negative consequences to smoking behaviors. Implications for intervention are discussed. PMID:25690755
Highly dynamic animal contact network and implications on disease transmission

PubMed Central

Chen, Shi; White, Brad J.; Sanderson, Michael W.; Amrine, David E.; Ilany, Amiyaal; Lanzas, Cristina

2014-01-01

Contact patterns among hosts are considered as one of the most critical factors contributing to unequal pathogen transmission. Consequently, networks have been widely applied in infectious disease modeling. However most studies assume static network structure due to lack of accurate observation and appropriate analytic tools. In this study we used high temporal and spatial resolution animal position data to construct a high-resolution contact network relevant to infectious disease transmission. The animal contact network aggregated at hourly level was highly variable and dynamic within and between days, for both network structure (network degree distribution) and individual rank of degree distribution in the network (degree order). We integrated network degree distribution and degree order heterogeneities with a commonly used contact-based, directly transmitted disease model to quantify the effect of these two sources of heterogeneity on the infectious disease dynamics. Four conditions were simulated based on the combination of these two heterogeneities. Simulation results indicated that disease dynamics and individual contribution to new infections varied substantially among these four conditions under both parameter settings. Changes in the contact network had a greater effect on disease dynamics for pathogens with smaller basic reproduction number (i.e. R0 < 2). PMID:24667241
Wavelets and Elman Neural Networks for monitoring environmental variables

NASA Astrophysics Data System (ADS)

Ciarlini, Patrizia; Maniscalco, Umberto

2008-11-01

An application in cultural heritage is introduced. Wavelet decomposition and Neural Networks like virtual sensors are jointly used to simulate physical and chemical measurements in specific locations of a monument. Virtual sensors, suitably trained and tested, can substitute real sensors in monitoring the monument surface quality, while the real ones should be installed for a long time and at high costs. The application of the wavelet decomposition to the environmental data series allows getting the treatment of underlying temporal structure at low frequencies. Consequently a separate training of suitable Elman Neural Networks for high/low components can be performed, thus improving the networks convergence in learning time and measurement accuracy in working time.
Power laws and fragility in flow networks.

PubMed

Shore, Jesse; Chu, Catherine J; Bianchi, Matt T

2013-01-01

What makes economic and ecological networks so unlike other highly skewed networks in their tendency toward turbulence and collapse? Here, we explore the consequences of a defining feature of these networks: their nodes are tied together by flow. We show that flow networks tend to the power law degree distribution (PLDD) due to a self-reinforcing process involving position within the global network structure, and thus present the first random graph model for PLDDs that does not depend on a rich-get-richer function of nodal degree. We also show that in contrast to non-flow networks, PLDD flow networks are dramatically more vulnerable to catastrophic failure than non-PLDD flow networks, a finding with potential explanatory power in our age of resource- and financial-interdependence and turbulence.
Recent advancements towards green optical networks

NASA Astrophysics Data System (ADS)

Davidson, Alan; Glesk, Ivan; Buis, Adrianus; Wang, Junjia; Chen, Lawrence

2014-12-01

Recent years have seen a rapid growth in demand for ultra high speed data transmission with end users expecting fast, high bandwidth network access. With this rapid growth in demand, data centres are under pressure to provide ever increasing data rates through their networks and at the same time improve the quality of data handling in terms of reduced latency, increased scalability and improved channel speed for users. However as data rates increase, present technology based on well-established CMOS technology is becoming increasingly difficult to scale and consequently data networks are struggling to satisfy current network demand. In this paper the interrelated issues of electronic scalability, power consumption, limited copper interconnect bandwidth and the limited speed of CMOS electronics will be explored alongside the tremendous bandwidth potential of optical fibre based photonic networks. Some applications of photonics to help alleviate the speed and latency in data networks will be discussed.
Community-level demographic consequences of urbanization: an ecological network approach.

PubMed

Rodewald, Amanda D; Rohr, Rudolf P; Fortuna, Miguel A; Bascompte, Jordi

2014-11-01

Ecological networks are known to influence ecosystem attributes, but we poorly understand how interspecific network structure affect population demography of multiple species, particularly for vertebrates. Establishing the link between network structure and demography is at the crux of being able to use networks to understand population dynamics and to inform conservation. We addressed the critical but unanswered question, does network structure explain demographic consequences of urbanization? We studied 141 ecological networks representing interactions between plants and nesting birds in forests across an urbanization gradient in Ohio, USA, from 2001 to 2011. Nest predators were identified by video-recording nests and surveyed from 2004 to 2011. As landscapes urbanized, bird-plant networks were more nested, less compartmentalized and dominated by strong interactions between a few species (i.e. low evenness). Evenness of interaction strengths promoted avian nest survival, and evenness explained demography better than urbanization, level of invasion, numbers of predators or other qualitative network metrics. Highly uneven networks had approximately half the nesting success as the most even networks. Thus, nest survival reflected how urbanization altered species interactions, particularly with respect to how nest placement affected search efficiency of predators. The demographic effects of urbanization were not direct, but were filtered through bird-plant networks. This study illustrates how network structure can influence demography at the community level and further, that knowledge of species interactions and a network approach may be requisite to understanding demographic responses to environmental change. © 2014 The Authors. Journal of Animal Ecology © 2014 British Ecological Society.
Accelerated intoxication of GABAergic synapses by botulinum neurotoxin A disinhibits stem cell-derived neuron networks prior to network silencing

PubMed Central

Beske, Phillip H.; Scheeler, Stephen M.; Adler, Michael; McNutt, Patrick M.

2015-01-01

Botulinum neurotoxins (BoNTs) are extremely potent toxins that specifically cleave SNARE proteins in peripheral synapses, preventing neurotransmitter release. Neuronal responses to BoNT intoxication are traditionally studied by quantifying SNARE protein cleavage in vitro or monitoring physiological paralysis in vivo. Consequently, the dynamic effects of intoxication on synaptic behaviors are not well-understood. We have reported that mouse embryonic stem cell-derived neurons (ESNs) are highly sensitive to BoNT based on molecular readouts of intoxication. Here we study the time-dependent changes in synapse- and network-level behaviors following addition of BoNT/A to spontaneously active networks of glutamatergic and GABAergic ESNs. Whole-cell patch-clamp recordings indicated that BoNT/A rapidly blocked synaptic neurotransmission, confirming that ESNs replicate the functional pathophysiology responsible for clinical botulism. Quantitation of spontaneous neurotransmission in pharmacologically isolated synapses revealed accelerated silencing of GABAergic synapses compared to glutamatergic synapses, which was consistent with the selective accumulation of cleaved SNAP-25 at GAD1+ pre-synaptic terminals at early timepoints. Different latencies of intoxication resulted in complex network responses to BoNT/A addition, involving rapid disinhibition of stochastic firing followed by network silencing. Synaptic activity was found to be highly sensitive to SNAP-25 cleavage, reflecting the functional consequences of the localized cleavage of the small subpopulation of SNAP-25 that is engaged in neurotransmitter release in the nerve terminal. Collectively these findings illustrate that use of synaptic function assays in networked neurons cultures offers a novel and highly sensitive approach for mechanistic studies of toxin:neuron interactions and synaptic responses to BoNT. PMID:25954159
Land use change in the last century in the Veneto floodplain: effects on network drainage density, water storage, and related consequences on flood risk

NASA Astrophysics Data System (ADS)

Prosdocimi, Massimo; Sofia, Giulia; Dalla Fontana, Giancarlo; Tarolli, Paolo

2013-04-01

In a high-density populated country such as Italy, the anthropic pressure plays a fundamental role in the alteration and the modification of the landscape. Among the most evident anthropic alterations, the most important are the urbanization processes that have been occurring since the end of the second world war. Agricultural activities, housing and other land uses have shifted due to the progressive spreading of urban areas. These modifications affect the hydrologic regimes, but municipalities often are not aware of the real impact of land cover changes on such processes and, consequently, an increase of the elements at risk of flooding is generally registered. The main objective of this work is to evaluate the impact of land cover changes in the Veneto region (north-east Italy), from 1954 to 2006, on the minor drainage network system and on its capacity to attenuate the direct runoff. The major flood event occurred between October and November 2010. The study is a typical agrarian landscape and it has been chosen considering its involvement inthe major flood of 2010 and considering also the availability of high-resolution topographic data (LiDAR-derived DTMs) and historical aerial photographs. Aerial photographs dated back to 1954 and 1981, in particular, have been used either to classify the land cover in five categories according to the first level of the CORINE land cover classification and to identify the minor drainage network. A semi-automatic approach based on the high-resolution DTM (Cazorzi et al., 2012), was also considered to identify the minor drainage network and estimate its water storage capacity. The results underline how land cover variation over the last 50 years has strongly increased the propension of the soil to produce direct runoff (increase of the Curve Number value) and it has also reduced the extent of the minor network system. As a consequence, the capacity of the agrarian minor network to attenuate and laminate a flood event is decreased as well. These analysis can be considered useful tools for a suitable land use planning in flood prone areas. References Cazorzi, F., Dalla Fontana, G., De Luca, A., Sofia, G., Tarolli, P. (2012). Drainage network detection and assessment of network storage capacity in agrarian landscape, Hydrological Processes, ISSN: 0885-6087, doi:10.1002/hyp.9224
Consequences of plant invasions on compartmentalization and species’ roles in plant–pollinator networks

PubMed Central

Albrecht, Matthias; Padrón, Benigno; Bartomeus, Ignasi; Traveset, Anna

2014-01-01

Compartmentalization—the organization of ecological interaction networks into subsets of species that do not interact with other subsets (true compartments) or interact more frequently among themselves than with other species (modules)—has been identified as a key property for the functioning, stability and evolution of ecological communities. Invasions by entomophilous invasive plants may profoundly alter the way interaction networks are compartmentalized. We analysed a comprehensive dataset of 40 paired plant–pollinator networks (invaded versus uninvaded) to test this hypothesis. We show that invasive plants have higher generalization levels with respect to their pollinators than natives. The consequences for network topology are that—rather than displacing native species from the network—plant invaders attracting pollinators into invaded modules tend to play new important topological roles (i.e. network hubs, module hubs and connectors) and cause role shifts in native species, creating larger modules that are more connected among each other. While the number of true compartments was lower in invaded compared with uninvaded networks, the effect of invasion on modularity was contingent on the study system. Interestingly, the generalization level of the invasive plants partially explains this pattern, with more generalized invaders contributing to a lower modularity. Our findings indicate that the altered interaction structure of invaded networks makes them more robust against simulated random secondary species extinctions, but more vulnerable when the typically highly connected invasive plants go extinct first. The consequences and pathways by which biological invasions alter the interaction structure of plant–pollinator communities highlighted in this study may have important dynamical and functional implications, for example, by influencing multi-species reciprocal selection regimes and coevolutionary processes. PMID:24943368
How the initial level of visibility and limited resource affect the evolution of cooperation

NASA Astrophysics Data System (ADS)

Han, Dun; Li, Dandan; Sun, Mei

2016-06-01

This work sheds important light on how the initial level of visibility and limited resource might affect the evolution of the players’ strategies under different network structure. We perform the prisoner’s dilemma game in the lattice network and the scale-free network, the simulation results indicate that the average density of death in lattice network decreases with the increases of the initial proportion of visibility. However, the contrary phenomenon is observed in the scale-free network. Further results reflect that the individuals’ payoff in lattice network is significantly larger than the one in the scale-free network. In the lattice network, the visibility individuals could earn much more than the invisibility one. However, the difference is not apparent in the scale-free network. We also find that a high Successful-Defection-Payoff (SDB) and a rich natural environment have relatively larger deleterious cooperation effects. A high SDB is beneficial to raising the level of visibility in the heterogeneous network, however, that has adverse visibility consequences in homogeneous network. Our result reveals that players are more likely to cooperate voluntarily under homogeneous network structure.

Risk analysis of urban gas pipeline network based on improved bow-tie model

NASA Astrophysics Data System (ADS)

Hao, M. J.; You, Q. J.; Yue, Z.

2017-11-01

Gas pipeline network is a major hazard source in urban areas. In the event of an accident, there could be grave consequences. In order to understand more clearly the causes and consequences of gas pipeline network accidents, and to develop prevention and mitigation measures, the author puts forward the application of improved bow-tie model to analyze risks of urban gas pipeline network. The improved bow-tie model analyzes accident causes from four aspects: human, materials, environment and management; it also analyzes the consequences from four aspects: casualty, property loss, environment and society. Then it quantifies the causes and consequences. Risk identification, risk analysis, risk assessment, risk control, and risk management will be clearly shown in the model figures. Then it can suggest prevention and mitigation measures accordingly to help reduce accident rate of gas pipeline network. The results show that the whole process of an accident can be visually investigated using the bow-tie model. It can also provide reasons for and predict consequences of an unfortunate event. It is of great significance in order to analyze leakage failure of gas pipeline network.
Do People Know I’m Poz?: Factors Associated with Knowledge of Serostatus among HIV-positive African Americans’ Social Network Members

PubMed Central

Hoover, Matthew A.; Green, Harold D.; Bogart, Laura M.; Wagner, Glenn J.; Mutchler, Matt G.; Galvan, Frank H.; McDavitt, Bryce

2015-01-01

We examined how functional social support, HIV-related discrimination, internalized HIV stigma, and social network structure and composition were cross-sectionally associated with network members’ knowledge of respondents’ serostatus among 244 HIV-positive African Americans in Los Angeles. Results of a generalized hierarchical linear model indicated people in respondents’ networks who were highly trusted, well-known to others (high degree centrality), HIV-positive, or sex partners were more likely to know respondents’ HIV serostatus; African American network members were less likely to know respondents’ serostatus, as were drug-using partners. Greater internalized stigma among respondents living with HIV was associated with less knowledge of their seropositivity within their social network whereas greater respondent-level HIV discrimination was associated with more knowledge of seropositivity within the network. Additional research is needed to understand the causal mechanisms and mediating processes associated with serostatus disclosure as well as the long-term consequences of disclosure and network members’ knowledge of respondents’ serostatus. PMID:25903505
Do People Know I'm Poz?: Factors Associated with Knowledge of Serostatus Among HIV-Positive African Americans' Social Network Members.

PubMed

Hoover, Matthew A; Green, Harold D; Bogart, Laura M; Wagner, Glenn J; Mutchler, Matt G; Galvan, Frank H; McDavitt, Bryce

2016-01-01

We examined how functional social support, HIV-related discrimination, internalized HIV stigma, and social network structure and composition were cross-sectionally associated with network members' knowledge of respondents' serostatus among 244 HIV-positive African Americans in Los Angeles. Results of a generalized hierarchical linear model indicated people in respondents' networks who were highly trusted, well-known to others (high degree centrality), HIV-positive, or sex partners were more likely to know respondents' HIV serostatus; African American network members were less likely to know respondents' serostatus, as were drug-using partners. Greater internalized stigma among respondents living with HIV was associated with less knowledge of their seropositivity within their social network whereas greater respondent-level HIV discrimination was associated with more knowledge of seropositivity within the network. Additional research is needed to understand the causal mechanisms and mediating processes associated with serostatus disclosure as well as the long-term consequences of disclosure and network members' knowledge of respondents' serostatus.
A user exposure based approach for non-structural road network vulnerability analysis

PubMed Central

Jin, Lei; Wang, Haizhong; Yu, Le; Liu, Lin

2017-01-01

Aiming at the dense urban road network vulnerability without structural negative consequences, this paper proposes a novel non-structural road network vulnerability analysis framework. Three aspects of the framework are mainly described: (i) the rationality of non-structural road network vulnerability, (ii) the metrics for negative consequences accounting for variant road conditions, and (iii) the introduction of a new vulnerability index based on user exposure. Based on the proposed methodology, a case study in the Sioux Falls network which was usually threatened by regular heavy snow during wintertime is detailedly discussed. The vulnerability ranking of links of Sioux Falls network with respect to heavy snow scenario is identified. As a result of non-structural consequences accompanied by conceivable degeneration of network, there are significant increases in generalized travel time costs which are measurements for “emotionally hurt” of topological road network. PMID:29176832
Altered Whole-Brain and Network-Based Functional Connectivity in Parkinson's Disease.

PubMed

de Schipper, Laura J; Hafkemeijer, Anne; van der Grond, Jeroen; Marinus, Johan; Henselmans, Johanna M L; van Hilten, Jacobus J

2018-01-01

Background: Functional imaging methods, such as resting-state functional magnetic resonance imaging, reflect changes in neural connectivity and may help to assess the widespread consequences of disease-specific network changes in Parkinson's disease. In this study we used a relatively new graph analysis approach in functional imaging: eigenvector centrality mapping. This model-free method, applied to all voxels in the brain, identifies prominent regions in the brain network hierarchy and detects localized differences between patient populations. In other neurological disorders, eigenvector centrality mapping has been linked to changes in functional connectivity in certain nodes of brain networks. Objectives: Examining changes in functional brain connectivity architecture on a whole brain and network level in patients with Parkinson's disease. Methods: Whole brain resting-state functional architecture was studied with a recently introduced graph analysis approach (eigenvector centrality mapping). Functional connectivity was further investigated in relation to eight known resting-state networks. Cross-sectional analyses included group comparison of functional connectivity measures of Parkinson's disease patients ( n = 107) with control subjects ( n = 58) and correlations with clinical data, including motor and cognitive impairment and a composite measure of predominantly non-dopaminergic symptoms. Results: Eigenvector centrality mapping revealed that frontoparietal regions were more prominent in the whole-brain network function in patients compared to control subjects, while frontal and occipital brain areas were less prominent in patients. Using standard resting-state networks, we found predominantly increased functional connectivity, namely within sensorimotor system and visual networks in patients. Regional group differences in functional connectivity of both techniques between patients and control subjects partly overlapped for highly connected posterior brain regions, in particular in the posterior cingulate cortex and precuneus. Clinico-functional imaging relations were not found. Conclusions: Changes on the level of functional brain connectivity architecture might provide a different perspective of pathological consequences of Parkinson's disease. The involvement of specific, highly connected (hub) brain regions may influence whole brain functional network architecture in Parkinson's disease.
Assessing Middle School Students' Knowledge of Conduct and Consequences and Their Behaviors regarding the Use of Social Networking Sites

ERIC Educational Resources Information Center

Kite, Stacey L.; Gable, Robert; Filippelli, Lawrence

2010-01-01

Cyberbullying and threats of Internet predators, not to mention the enduring consequences of postings, may lead to dangerous, unspeakable consequences. Cyberbullying and threats of Internet predators through social networking sites and instant messaging programs are initiating numerous problems for parents, school administrators, and law…
Robust Learning of High-dimensional Biological Networks with Bayesian Networks

NASA Astrophysics Data System (ADS)

Nägele, Andreas; Dejori, Mathäus; Stetter, Martin

Structure learning of Bayesian networks applied to gene expression data has become a potentially useful method to estimate interactions between genes. However, the NP-hardness of Bayesian network structure learning renders the reconstruction of the full genetic network with thousands of genes unfeasible. Consequently, the maximal network size is usually restricted dramatically to a small set of genes (corresponding with variables in the Bayesian network). Although this feature reduction step makes structure learning computationally tractable, on the downside, the learned structure might be adversely affected due to the introduction of missing genes. Additionally, gene expression data are usually very sparse with respect to the number of samples, i.e., the number of genes is much greater than the number of different observations. Given these problems, learning robust network features from microarray data is a challenging task. This chapter presents several approaches tackling the robustness issue in order to obtain a more reliable estimation of learned network features.
Benefits of a European project on diagnostics of highly pathogenic agents and assessment of potential "dual use" issues.

PubMed

Grunow, Roland; Ippolito, G; Jacob, D; Sauer, U; Rohleder, A; Di Caro, A; Iacovino, R

2014-01-01

Quality assurance exercises and networking on the detection of highly infectious pathogens (QUANDHIP) is a joint action initiative set up in 2011 that has successfully unified the primary objectives of the European Network on Highly Pathogenic Bacteria (ENHPB) and of P4-laboratories (ENP4-Lab) both of which aimed to improve the efficiency, effectiveness, and response capabilities of laboratories directed at protecting the health of European citizens against high consequence bacteria and viruses of significant public health concern. Both networks have established a common collaborative consortium of 37 nationally and internationally recognized institutions with laboratory facilities from 22 European countries. The specific objectives and achievements include the initiation and establishment of a recognized and acceptable quality assurance scheme, including practical external quality assurance exercises, comprising living agents, that aims to improve laboratory performance, accuracy, and detection capabilities in support of patient management and public health responses; recognized training schemes for diagnostics and handling of highly pathogenic agents; international repositories comprising highly pathogenic bacteria and viruses for the development of standardized reference material; a standardized and transparent Biosafety and Biosecurity strategy protecting healthcare personnel and the community in dealing with high consequence pathogens; the design and organization of response capabilities dealing with cross-border events with highly infectious pathogens including the consideration of diagnostic capabilities of individual European laboratories. The project tackled several sensitive issues regarding Biosafety, Biosecurity and "dual use" concerns. The article will give an overview of the project outcomes and discuss the assessment of potential "dual use" issues.
Benefits of a European Project on Diagnostics of Highly Pathogenic Agents and Assessment of Potential “Dual Use” Issues

PubMed Central

Grunow, Roland; Ippolito, G.; Jacob, D.; Sauer, U.; Rohleder, A.; Di Caro, A.; Iacovino, R.

2014-01-01

Quality assurance exercises and networking on the detection of highly infectious pathogens (QUANDHIP) is a joint action initiative set up in 2011 that has successfully unified the primary objectives of the European Network on Highly Pathogenic Bacteria (ENHPB) and of P4-laboratories (ENP4-Lab) both of which aimed to improve the efficiency, effectiveness, and response capabilities of laboratories directed at protecting the health of European citizens against high consequence bacteria and viruses of significant public health concern. Both networks have established a common collaborative consortium of 37 nationally and internationally recognized institutions with laboratory facilities from 22 European countries. The specific objectives and achievements include the initiation and establishment of a recognized and acceptable quality assurance scheme, including practical external quality assurance exercises, comprising living agents, that aims to improve laboratory performance, accuracy, and detection capabilities in support of patient management and public health responses; recognized training schemes for diagnostics and handling of highly pathogenic agents; international repositories comprising highly pathogenic bacteria and viruses for the development of standardized reference material; a standardized and transparent Biosafety and Biosecurity strategy protecting healthcare personnel and the community in dealing with high consequence pathogens; the design and organization of response capabilities dealing with cross-border events with highly infectious pathogens including the consideration of diagnostic capabilities of individual European laboratories. The project tackled several sensitive issues regarding Biosafety, Biosecurity and “dual use” concerns. The article will give an overview of the project outcomes and discuss the assessment of potential “dual use” issues. PMID:25426479
Experiments on neural network architectures for fuzzy logic

NASA Technical Reports Server (NTRS)

Keller, James M.

1991-01-01

The use of fuzzy logic to model and manage uncertainty in a rule-based system places high computational demands on an inference engine. In an earlier paper, the authors introduced a trainable neural network structure for fuzzy logic. These networks can learn and extrapolate complex relationships between possibility distributions for the antecedents and consequents in the rules. Here, the power of these networks is further explored. The insensitivity of the output to noisy input distributions (which are likely if the clauses are generated from real data) is demonstrated as well as the ability of the networks to internalize multiple conjunctive clause and disjunctive clause rules. Since different rules with the same variables can be encoded in a single network, this approach to fuzzy logic inference provides a natural mechanism for rule conflict resolution.
Conducting-insulating transition in adiabatic memristive networks

NASA Astrophysics Data System (ADS)

Sheldon, Forrest C.; Di Ventra, Massimiliano

2017-01-01

The development of neuromorphic systems based on memristive elements—resistors with memory—requires a fundamental understanding of their collective dynamics when organized in networks. Here, we study an experimentally inspired model of two-dimensional disordered memristive networks subject to a slowly ramped voltage and show that they undergo a discontinuous transition in the conductivity for sufficiently high values of memory, as quantified by the memristive ON-OFF ratio. We investigate the consequences of this transition for the memristive current-voltage characteristics both through simulation and theory, and demonstrate the role of current-voltage duality in relating forward and reverse switching processes. Our work sheds considerable light on the statistical properties of memristive networks that are presently studied both for unconventional computing and as models of neural networks.
Interaction rewiring and the rapid turnover of plant-pollinator networks.

PubMed

CaraDonna, Paul J; Petry, William K; Brennan, Ross M; Cunningham, James L; Bronstein, Judith L; Waser, Nickolas M; Sanders, Nathan J

2017-03-01

Whether species interactions are static or change over time has wide-reaching ecological and evolutionary consequences. However, species interaction networks are typically constructed from temporally aggregated interaction data, thereby implicitly assuming that interactions are fixed. This approach has advanced our understanding of communities, but it obscures the timescale at which interactions form (or dissolve) and the drivers and consequences of such dynamics. We address this knowledge gap by quantifying the within-season turnover of plant-pollinator interactions from weekly censuses across 3 years in a subalpine ecosystem. Week-to-week turnover of interactions (1) was high, (2) followed a consistent seasonal progression in all years of study and (3) was dominated by interaction rewiring (the reassembly of interactions among species). Simulation models revealed that species' phenologies and relative abundances constrained both total interaction turnover and rewiring. Our findings reveal the diversity of species interactions that may be missed when the temporal dynamics of networks are ignored. © 2017 John Wiley & Sons Ltd/CNRS.
Link state relationships under incident conditions : using a CTM-based linear programming dynamic traffic assignment model.

DOT National Transportation Integrated Search

2010-03-01

Urban transportation networks, consisting of numerous links and nodes, experience traffic incidents such as accidents and road : maintenance work. A typical consequence of incidents is congestion which results in long queues and causes high travel ti...
Link State Relationships Under Incident Conditions: Using a CTM-Based Linear Programming Dynamic Traffic Assignment Model

DOT National Transportation Integrated Search

2010-03-01

Urban transportation networks, consisting of numerous links and nodes, experience traffic incidents such as accidents and road maintenance work. A typical consequence of incidents is congestion which results in long queues and causes high travel time...
Quasirandom geometric networks from low-discrepancy sequences

NASA Astrophysics Data System (ADS)

Estrada, Ernesto

2017-08-01

We define quasirandom geometric networks using low-discrepancy sequences, such as Halton, Sobol, and Niederreiter. The networks are built in d dimensions by considering the d -tuples of digits generated by these sequences as the coordinates of the vertices of the networks in a d -dimensional Id unit hypercube. Then, two vertices are connected by an edge if they are at a distance smaller than a connection radius. We investigate computationally 11 network-theoretic properties of two-dimensional quasirandom networks and compare them with analogous random geometric networks. We also study their degree distribution and their spectral density distributions. We conclude from this intensive computational study that in terms of the uniformity of the distribution of the vertices in the unit square, the quasirandom networks look more random than the random geometric networks. We include an analysis of potential strategies for generating higher-dimensional quasirandom networks, where it is know that some of the low-discrepancy sequences are highly correlated. In this respect, we conclude that up to dimension 20, the use of scrambling, skipping and leaping strategies generate quasirandom networks with the desired properties of uniformity. Finally, we consider a diffusive process taking place on the nodes and edges of the quasirandom and random geometric graphs. We show that the diffusion time is shorter in the quasirandom graphs as a consequence of their larger structural homogeneity. In the random geometric graphs the diffusion produces clusters of concentration that make the process more slow. Such clusters are a direct consequence of the heterogeneous and irregular distribution of the nodes in the unit square in which the generation of random geometric graphs is based on.
Exploring Vietnamese co-authorship patterns in social sciences with basic network measures of 2008-2017 Scopus data.

PubMed

Ho, Tung Manh; Nguyen, Ha Viet; Vuong, Thu-Trang; Dam, Quang-Minh; Pham, Hiep-Hung; Vuong, Quan-Hoang

2017-01-01

Background: Collaboration is a common occurrence among Vietnamese scientists; however, insights into Vietnamese scientific collaborations have been scarce. On the other hand, the application of social network analysis in studying science collaboration has gained much attention all over the world. The technique could be employed to explore Vietnam's scientific community. Methods: This paper employs network theory to explore characteristics of a network of 412 Vietnamese social scientists whose papers can be found indexed in the Scopus database. Two basic network measures, density and clustering coefficient, were taken, and the entire network was studied in comparison with two of its largest components. Results: The networks connections are very sparse, with a density of only 0.47%, while the clustering coefficient is very high (58.64%). This suggests an inefficient dissemination of information, knowledge, and expertise in the network. Secondly, the disparity in levels of connection among individuals indicates that the network would easily fall apart if a few highly-connected nodes are removed. Finally, the two largest components of the network were found to differ from the entire networks in terms of measures and were both led by the most productive and well-connected researchers. Conclusions: High clustering and low density seems to be tied to inefficient dissemination of expertise among Vietnamese social scientists, and consequently low scientific output. Also low in robustness, the network shows the potential of an intellectual elite composed of well-connected, productive, and socially significant individuals.
Exploring Vietnamese co-authorship patterns in social sciences with basic network measures of 2008-2017 Scopus data

PubMed Central

Ho, Tung Manh; Nguyen, Ha Viet; Vuong, Thu-Trang; Dam, Quang-Minh; Pham, Hiep-Hung; Vuong, Quan-Hoang

2017-01-01

Background: Collaboration is a common occurrence among Vietnamese scientists; however, insights into Vietnamese scientific collaborations have been scarce. On the other hand, the application of social network analysis in studying science collaboration has gained much attention all over the world. The technique could be employed to explore Vietnam’s scientific community. Methods: This paper employs network theory to explore characteristics of a network of 412 Vietnamese social scientists whose papers can be found indexed in the Scopus database. Two basic network measures, density and clustering coefficient, were taken, and the entire network was studied in comparison with two of its largest components. Results: The networks connections are very sparse, with a density of only 0.47%, while the clustering coefficient is very high (58.64%). This suggests an inefficient dissemination of information, knowledge, and expertise in the network. Secondly, the disparity in levels of connection among individuals indicates that the network would easily fall apart if a few highly-connected nodes are removed. Finally, the two largest components of the network were found to differ from the entire networks in terms of measures and were both led by the most productive and well-connected researchers. Conclusions: High clustering and low density seems to be tied to inefficient dissemination of expertise among Vietnamese social scientists, and consequently low scientific output. Also low in robustness, the network shows the potential of an intellectual elite composed of well-connected, productive, and socially significant individuals. PMID:28928958
Maritime Transportation Risk Assessment of Tianjin Port with Bayesian Belief Networks.

PubMed

Zhang, Jinfen; Teixeira, Ângelo P; Guedes Soares, C; Yan, Xinping; Liu, Kezhong

2016-06-01

This article develops a Bayesian belief network model for the prediction of accident consequences in the Tianjin port. The study starts with a statistical analysis of historical accident data of six years from 2008 to 2013. Then a Bayesian belief network is constructed to express the dependencies between the indicator variables and accident consequences. The statistics and expert knowledge are synthesized in the Bayesian belief network model to obtain the probability distribution of the consequences. By a sensitivity analysis, several indicator variables that have influence on the consequences are identified, including navigational area, ship type and time of the day. The results indicate that the consequences are most sensitive to the position where the accidents occurred, followed by time of day and ship length. The results also reflect that the navigational risk of the Tianjin port is at the acceptable level, despite that there is more room of improvement. These results can be used by the Maritime Safety Administration to take effective measures to enhance maritime safety in the Tianjin port. © 2016 Society for Risk Analysis.
Resource constrained flux balance analysis predicts selective pressure on the global structure of metabolic networks.

PubMed

Abedpour, Nima; Kollmann, Markus

2015-11-23

A universal feature of metabolic networks is their hourglass or bow-tie structure on cellular level. This architecture reflects the conversion of multiple input nutrients into multiple biomass components via a small set of precursor metabolites. However, it is yet unclear to what extent this structural feature is the result of natural selection. We extend flux balance analysis to account for limited cellular resources. Using this model, optimal structure of metabolic networks can be calculated for different environmental conditions. We observe a significant structural reshaping of metabolic networks for a toy-network and E. coli core metabolism if we increase the share of invested resources for switching between different nutrient conditions. Here, hub nodes emerge and the optimal network structure becomes bow-tie-like as a consequence of limited cellular resource constraint. We confirm this theoretical finding by comparing the reconstructed metabolic networks of bacterial species with respect to their lifestyle. We show that bow-tie structure can give a system-level fitness advantage to organisms that live in highly competitive and fluctuating environments. Here, limitation of cellular resources can lead to an efficiency-flexibility tradeoff where it pays off for the organism to shorten catabolic pathways if they are frequently activated and deactivated. As a consequence, generalists that shuttle between diverse environmental conditions should have a more predominant bow-tie structure than specialists that visit just a few isomorphic habitats during their life cycle.
Evolution of cosmic string networks

NASA Technical Reports Server (NTRS)

Albrecht, Andreas; Turok, Neil

1989-01-01

A discussion of the evolution and observable consequences of a network of cosmic strings is given. A simple model for the evolution of the string network is presented, and related to the statistical mechanics of string networks. The model predicts the long string density throughout the history of the universe from a single parameter, which researchers calculate in radiation era simulations. The statistical mechanics arguments indicate a particular thermal form for the spectrum of loops chopped off the network. Detailed numerical simulations of string networks in expanding backgrounds are performed to test the model. Consequences for large scale structure, the microwave and gravity wave backgrounds, nucleosynthesis and gravitational lensing are calculated.

Research Note: The consequences of different methods for handling missing network data in Stochastic Actor Based Models

PubMed Central

Hipp, John R.; Wang, Cheng; Butts, Carter T.; Jose, Rupa; Lakon, Cynthia M.

2015-01-01

Although stochastic actor based models (e.g., as implemented in the SIENA software program) are growing in popularity as a technique for estimating longitudinal network data, a relatively understudied issue is the consequence of missing network data for longitudinal analysis. We explore this issue in our research note by utilizing data from four schools in an existing dataset (the AddHealth dataset) over three time points, assessing the substantive consequences of using four different strategies for addressing missing network data. The results indicate that whereas some measures in such models are estimated relatively robustly regardless of the strategy chosen for addressing missing network data, some of the substantive conclusions will differ based on the missing data strategy chosen. These results have important implications for this burgeoning applied research area, implying that researchers should more carefully consider how they address missing data when estimating such models. PMID:25745276
Research Note: The consequences of different methods for handling missing network data in Stochastic Actor Based Models.

PubMed

Hipp, John R; Wang, Cheng; Butts, Carter T; Jose, Rupa; Lakon, Cynthia M

2015-05-01

Although stochastic actor based models (e.g., as implemented in the SIENA software program) are growing in popularity as a technique for estimating longitudinal network data, a relatively understudied issue is the consequence of missing network data for longitudinal analysis. We explore this issue in our research note by utilizing data from four schools in an existing dataset (the AddHealth dataset) over three time points, assessing the substantive consequences of using four different strategies for addressing missing network data. The results indicate that whereas some measures in such models are estimated relatively robustly regardless of the strategy chosen for addressing missing network data, some of the substantive conclusions will differ based on the missing data strategy chosen. These results have important implications for this burgeoning applied research area, implying that researchers should more carefully consider how they address missing data when estimating such models.
Automated identification of functional dynamic networks from X-ray crystallography

PubMed Central

van den Bedem, Henry; Bhabha, Gira; Yang, Kun; Wright, Peter E.; Fraser, James S.

2013-01-01

Protein function often depends on the exchange between conformational substates. Allosteric ligand binding or distal mutations can stabilize specific active site conformations and consequently alter protein function. In addition to comparing independently determined X-ray crystal structures, alternative conformations observed at low levels of electron density have the potential to provide mechanistic insights into conformational dynamics. Here, we report a new multi-conformer contact network algorithm (CONTACT) that identifies networks of conformationally heterogeneous residues directly from high-resolution X-ray crystallography data. Contact networks in Escherichia coli dihydrofolate reductase (ecDHFR) predict the long-range pattern of NMR chemical shift perturbations of an allosteric mutation. A comparison of contact networks in wild type and mutant ecDHFR suggests how mutations that alter optimized networks of coordinated motions can impair catalytic function. Thus, CONTACT-guided mutagenesis will allow the structure-dynamics-function relationship to be exploited in protein engineering and design. PMID:23913260
Self-configuration and self-optimization process in heterogeneous wireless networks.

PubMed

Guardalben, Lucas; Villalba, Luis Javier García; Buiati, Fábio; Sobral, João Bosco Mangueira; Camponogara, Eduardo

2011-01-01

Self-organization in Wireless Mesh Networks (WMN) is an emergent research area, which is becoming important due to the increasing number of nodes in a network. Consequently, the manual configuration of nodes is either impossible or highly costly. So it is desirable for the nodes to be able to configure themselves. In this paper, we propose an alternative architecture for self-organization of WMN based on Optimized Link State Routing Protocol (OLSR) and the ad hoc on demand distance vector (AODV) routing protocols as well as using the technology of software agents. We argue that the proposed self-optimization and self-configuration modules increase the throughput of network, reduces delay transmission and network load, decreases the traffic of HELLO messages according to network's scalability. By simulation analysis, we conclude that the self-optimization and self-configuration mechanisms can significantly improve the performance of OLSR and AODV protocols in comparison to the baseline protocols analyzed.
The Strength of the Strongest Ties in Collaborative Problem Solving

NASA Astrophysics Data System (ADS)

de Montjoye, Yves-Alexandre; Stopczynski, Arkadiusz; Shmueli, Erez; Pentland, Alex; Lehmann, Sune

2014-06-01

Complex problem solving in science, engineering, and business has become a highly collaborative endeavor. Teams of scientists or engineers collaborate on projects using their social networks to gather new ideas and feedback. Here we bridge the literature on team performance and information networks by studying teams' problem solving abilities as a function of both their within-team networks and their members' extended networks. We show that, while an assigned team's performance is strongly correlated with its networks of expressive and instrumental ties, only the strongest ties in both networks have an effect on performance. Both networks of strong ties explain more of the variance than other factors, such as measured or self-evaluated technical competencies, or the personalities of the team members. In fact, the inclusion of the network of strong ties renders these factors non-significant in the statistical analysis. Our results have consequences for the organization of teams of scientists, engineers, and other knowledge workers tackling today's most complex problems.
The strength of the strongest ties in collaborative problem solving.

PubMed

de Montjoye, Yves-Alexandre; Stopczynski, Arkadiusz; Shmueli, Erez; Pentland, Alex; Lehmann, Sune

2014-06-20

Complex problem solving in science, engineering, and business has become a highly collaborative endeavor. Teams of scientists or engineers collaborate on projects using their social networks to gather new ideas and feedback. Here we bridge the literature on team performance and information networks by studying teams' problem solving abilities as a function of both their within-team networks and their members' extended networks. We show that, while an assigned team's performance is strongly correlated with its networks of expressive and instrumental ties, only the strongest ties in both networks have an effect on performance. Both networks of strong ties explain more of the variance than other factors, such as measured or self-evaluated technical competencies, or the personalities of the team members. In fact, the inclusion of the network of strong ties renders these factors non-significant in the statistical analysis. Our results have consequences for the organization of teams of scientists, engineers, and other knowledge workers tackling today's most complex problems.
Disturbed temporal dynamics of brain synchronization in vision loss.

PubMed

Bola, Michał; Gall, Carolin; Sabel, Bernhard A

2015-06-01

Damage along the visual pathway prevents bottom-up visual input from reaching further processing stages and consequently leads to loss of vision. But perception is not a simple bottom-up process - rather it emerges from activity of widespread cortical networks which coordinate visual processing in space and time. Here we set out to study how vision loss affects activity of brain visual networks and how networks' activity is related to perception. Specifically, we focused on studying temporal patterns of brain activity. To this end, resting-state eyes-closed EEG was recorded from partially blind patients suffering from chronic retina and/or optic-nerve damage (n = 19) and healthy controls (n = 13). Amplitude (power) of oscillatory activity and phase locking value (PLV) were used as measures of local and distant synchronization, respectively. Synchronization time series were created for the low- (7-9 Hz) and high-alpha band (11-13 Hz) and analyzed with three measures of temporal patterns: (i) length of synchronized-/desynchronized-periods, (ii) Higuchi Fractal Dimension (HFD), and (iii) Detrended Fluctuation Analysis (DFA). We revealed that patients exhibit less complex, more random and noise-like temporal dynamics of high-alpha band activity. More random temporal patterns were associated with worse performance in static (r = -.54, p = .017) and kinetic perimetry (r = .47, p = .041). We conclude that disturbed temporal patterns of neural synchronization in vision loss patients indicate disrupted communication within brain visual networks caused by prolonged deafferentation. We propose that because the state of brain networks is essential for normal perception, impaired brain synchronization in patients with vision loss might aggravate the functional consequences of reduced visual input. Copyright © 2015 Elsevier Ltd. All rights reserved.
Geography of invasion in mountain streams: consequences of headwater lake fish introductions

Treesearch

Susan B. Adams; Christopher A. Frissell; Bruce E. Rieman

2001-01-01

The introduction of fish into high-elevation lakes can provide a geographic and demographic boost to their invasion of stream networks, thereby further endangering the native stream fauna. Increasingly, remaining populations of native salmonids are concentrated in fragmented headwater refugia that are protected by physical or biological barriers from introduced fishes...
The structure and resilience of financial market networks

NASA Astrophysics Data System (ADS)

Kauê Dal'Maso Peron, Thomas; da Fontoura Costa, Luciano; Rodrigues, Francisco A.

2012-03-01

Financial markets can be viewed as a highly complex evolving system that is very sensitive to economic instabilities. The complex organization of the market can be represented in a suitable fashion in terms of complex networks, which can be constructed from stock prices such that each pair of stocks is connected by a weighted edge that encodes the distance between them. In this work, we propose an approach to analyze the topological and dynamic evolution of financial networks based on the stock correlation matrices. An entropy-related measurement is adopted to quantify the robustness of the evolving financial market organization. It is verified that the network topological organization suffers strong variation during financial instabilities and the networks in such periods become less robust. A statistical robust regression model is proposed to quantity the relationship between the network structure and resilience. The obtained coefficients of such model indicate that the average shortest path length is the measurement most related to network resilience coefficient. This result indicates that a collective behavior is observed between stocks during financial crisis. More specifically, stocks tend to synchronize their price evolution, leading to a high correlation between pair of stock prices, which contributes to the increase in distance between them and, consequently, decrease the network resilience.
A graph-theory framework for evaluating landscape connectivity and conservation planning.

PubMed

Minor, Emily S; Urban, Dean L

2008-04-01

Connectivity of habitat patches is thought to be important for movement of genes, individuals, populations, and species over multiple temporal and spatial scales. We used graph theory to characterize multiple aspects of landscape connectivity in a habitat network in the North Carolina Piedmont (U.S.A). We compared this landscape with simulated networks with known topology, resistance to disturbance, and rate of movement. We introduced graph measures such as compartmentalization and clustering, which can be used to identify locations on the landscape that may be especially resilient to human development or areas that may be most suitable for conservation. Our analyses indicated that for songbirds the Piedmont habitat network was well connected. Furthermore, the habitat network had commonalities with planar networks, which exhibit slow movement, and scale-free networks, which are resistant to random disturbances. These results suggest that connectivity in the habitat network was high enough to prevent the negative consequences of isolation but not so high as to allow rapid spread of disease. Our graph-theory framework provided insight into regional and emergent global network properties in an intuitive and visual way and allowed us to make inferences about rates and paths of species movements and vulnerability to disturbance. This approach can be applied easily to assessing habitat connectivity in any fragmented or patchy landscape.
Fitness consequences of spousal relatedness in 46 small-scale societies.

PubMed

Bailey, Drew H; Hill, Kim R; Walker, Robert S

2014-05-01

Social norms that regulate reproductive and marital decisions generate impressive cross-cultural variation in the prevalence of kin marriages. In some societies, marriages among kin are the norm and this inbreeding creates intensive kinship networks concentrated within communities. In others, especially forager societies, most marriages are between more genealogically and geographically distant individuals, which generates a larger number of kin and affines of lesser relatedness in more extensive kinship networks spread out over multiple communities. Here, we investigate the fitness consequence of kin marriages across a sample of 46 small-scale societies (12,439 marriages). Results show that some non-forager societies (including horticulturalists, agriculturalists and pastoralists), but not foragers, have intensive kinship societies where fitness outcomes (measured as the number of surviving children in genealogies) peak at commonly high levels of spousal relatedness. By contrast, the extensive kinship systems of foragers have worse fitness outcomes at high levels of spousal relatedness. Overall, societies with greater levels of inbreeding showed a more positive relationship between fitness and spousal relatedness. © 2014 The Author(s) Published by the Royal Society. All rights reserved.
Variability of community interaction networks in marine reserves and adjacent exploited areas

USGS Publications Warehouse

Montano-Moctezuma, G.; Li, H.W.; Rossignol, P.A.

2008-01-01

Regional and small-scale local oceanographic conditions can lead to high variability in community structure even among similar habitats. Communities with identical species composition can depict distinct networks due to different levels of disturbance as well as physical and biological processes. In this study we reconstruct community networks in four different areas off the Oregon Coast by matching simulated communities with observed dynamics. We compared reserves with harvested areas. Simulations suggested that different community networks, but with the same species composition, can represent each study site. Differences were found in predator-prey interactions as well as non-predatory interactions between community members. In addition, each site can be represented as a set of models, creating alternative stages among sites. The set of alternative models that characterize each study area depicts a sequence of functional responses where each specific model or interaction structure creates different species composition patterns. Different management practices, either in the past or of the present, may lead to alternative communities. Our findings suggest that management strategies should be analyzed at a community level that considers the possible consequences of shifting from one community scenario to another. This analysis provides a novel conceptual framework to assess the consequences of different management options for ecological communities. ?? 2008 Elsevier B.V. All rights reserved.
Brain connectivity aberrations in anabolic-androgenic steroid users.

PubMed

Westlye, Lars T; Kaufmann, Tobias; Alnæs, Dag; Hullstein, Ingunn R; Bjørnebekk, Astrid

2017-01-01

Sustained anabolic-androgenic steroid (AAS) use has adverse behavioral consequences, including aggression, violence and impulsivity. Candidate mechanisms include disruptions of brain networks with high concentrations of androgen receptors and critically involved in emotional and cognitive regulation. Here, we tested the effects of AAS on resting-state functional brain connectivity in the largest sample of AAS-users to date. We collected resting-state functional magnetic resonance imaging (fMRI) data from 151 males engaged in heavy resistance strength training. 50 users tested positive for AAS based on the testosterone to epitestosterone (T/E) ratio and doping substances in urine. 16 previous users and 59 controls tested negative. We estimated brain network nodes and their time-series using ICA and dual regression and defined connectivity matrices as the between-node partial correlations. In line with the emotional and behavioral consequences of AAS, current users exhibited reduced functional connectivity between key nodes involved in emotional and cognitive regulation, in particular reduced connectivity between the amygdala and default-mode network (DMN) and between the dorsal attention network (DAN) and a frontal node encompassing the superior and inferior frontal gyri (SFG/IFG) and the anterior cingulate cortex (ACC), with further reductions as a function of dependency, lifetime exposure, and cycle state (on/off).
Literature Review on Modeling Cyber Networks and Evaluating Cyber Risks.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kelic, Andjelka; Campbell, Philip L

The National Infrastructure Simulations and Analysis Center (NISAC) conducted a literature review on modeling cyber networks and evaluating cyber risks. The literature review explores where modeling is used in the cyber regime and ways that consequence and risk are evaluated. The relevant literature clusters in three different spaces: network security, cyber-physical, and mission assurance. In all approaches, some form of modeling is utilized at varying levels of detail, while the ability to understand consequence varies, as do interpretations of risk. This document summarizes the different literature viewpoints and explores their applicability to securing enterprise networks.
Network Access Control List Situation Awareness

ERIC Educational Resources Information Center

Reifers, Andrew

2010-01-01

Network security is a large and complex problem being addressed by multiple communities. Nevertheless, current theories in networking security appear to overestimate network administrators' ability to understand network access control lists (NACLs), providing few context specific user analyses. Consequently, the current research generally seems to…
Diverse types of genetic variation converge on functional gene networks involved in schizophrenia.

PubMed

Gilman, Sarah R; Chang, Jonathan; Xu, Bin; Bawa, Tejdeep S; Gogos, Joseph A; Karayiorgou, Maria; Vitkup, Dennis

2012-12-01

Despite the successful identification of several relevant genomic loci, the underlying molecular mechanisms of schizophrenia remain largely unclear. We developed a computational approach (NETBAG+) that allows an integrated analysis of diverse disease-related genetic data using a unified statistical framework. The application of this approach to schizophrenia-associated genetic variations, obtained using unbiased whole-genome methods, allowed us to identify several cohesive gene networks related to axon guidance, neuronal cell mobility, synaptic function and chromosomal remodeling. The genes forming the networks are highly expressed in the brain, with higher brain expression during prenatal development. The identified networks are functionally related to genes previously implicated in schizophrenia, autism and intellectual disability. A comparative analysis of copy number variants associated with autism and schizophrenia suggests that although the molecular networks implicated in these distinct disorders may be related, the mutations associated with each disease are likely to lead, at least on average, to different functional consequences.
Self-Configuration and Self-Optimization Process in Heterogeneous Wireless Networks

PubMed Central

Guardalben, Lucas; Villalba, Luis Javier García; Buiati, Fábio; Sobral, João Bosco Mangueira; Camponogara, Eduardo

2011-01-01

Self-organization in Wireless Mesh Networks (WMN) is an emergent research area, which is becoming important due to the increasing number of nodes in a network. Consequently, the manual configuration of nodes is either impossible or highly costly. So it is desirable for the nodes to be able to configure themselves. In this paper, we propose an alternative architecture for self-organization of WMN based on Optimized Link State Routing Protocol (OLSR) and the ad hoc on demand distance vector (AODV) routing protocols as well as using the technology of software agents. We argue that the proposed self-optimization and self-configuration modules increase the throughput of network, reduces delay transmission and network load, decreases the traffic of HELLO messages according to network’s scalability. By simulation analysis, we conclude that the self-optimization and self-configuration mechanisms can significantly improve the performance of OLSR and AODV protocols in comparison to the baseline protocols analyzed. PMID:22346584
The relationship between default mode network connectivity and social functioning in individuals at familial high-risk for schizophrenia.

PubMed

Dodell-Feder, David; Delisi, Lynn E; Hooker, Christine I

2014-06-01

Unaffected first-degree relatives of individuals with schizophrenia (i.e., those at familial high-risk [FHR]), demonstrate social dysfunction qualitatively similar though less severe than that of their affected relatives. These social difficulties may be the consequence of genetically conferred disruption to aspects of the default mode network (DMN), such as the dMPFC subsystem, which overlaps with the network of brain regions recruited during social cognitive processes. In the present study, we investigate this possibility, testing DMN connectivity and its relationship to social functioning in FHR using resting-state fMRI. Twenty FHR individuals and 17 controls underwent fMRI during a resting-state scan. Hypothesis-driven functional connectivity analyses examined ROI-to-ROI correlations between the DMN's hubs, and regions of the dMPFC subsystem and MTL subsystem. Connectivity values were examined in relationship to a measure of social functioning and empathy/perspective-taking. Results demonstrate that FHR exhibit reduced connectivity specifically within the dMPFC subsystem of the DMN. Certain ROI-to-ROI correlations predicted aspects of social functioning and empathy/perspective-taking across all participants. Together, the data indicate that disruption to the dMPFC subsystem of the DMN may be associated with familial risk for schizophrenia, and that these intrinsic connections may carry measurable consequences for social functioning. Copyright © 2014 Elsevier B.V. All rights reserved.
The relationship between default mode network connectivity and social functioning in individuals at familial high-risk for schizophrenia

PubMed Central

Dodell-Feder, David; DeLisi, Lynn E.; Hooker, Christine I.

2014-01-01

Unaffected first-degree relatives of individuals with schizophrenia (i.e., those at familial high-risk [FHR]), demonstrate social dysfunction qualitatively similar though less severe than that of their affected relatives. These social difficulties may be the consequence of genetically conferred disruption to aspects of the default mode network (DMN), such as the dMPFC subsystem, which overlaps with the network of brain regions recruited during social cognitive processes. In the present study, we investigate this possibility, testing DMN connectivity and its relationship to social functioning in FHR using resting-state fMRI. Twenty FHR individuals and 17 controls underwent fMRI during a resting-state scan. Hypothesis-driven functional connectivity analyses examined ROI-to-ROI correlations between the DMN’s hubs, and regions of the dMPFC subsystem and MTL subsystem. Connectivity values were examined in relationship to a measure of social functioning and empathy/perspective-taking. Results demonstrate that FHR exhibit reduced connectivity specifically within the dMPFC subsystem of the DMN. Certain ROI-to-ROI correlations predicted aspects of social functioning and empathy/perspective-taking across all participants. Together, the data indicate that disruption to the dMPFC subsystem of the DMN may be associated with familial risk for schizophrenia, and that these intrinsic connections may carry measurable consequences for social functioning. PMID:24768131
An Outline of Data Aggregation Security in Heterogeneous Wireless Sensor Networks.

PubMed

Boubiche, Sabrina; Boubiche, Djallel Eddine; Bilami, Azzedine; Toral-Cruz, Homero

2016-04-12

Data aggregation processes aim to reduce the amount of exchanged data in wireless sensor networks and consequently minimize the packet overhead and optimize energy efficiency. Securing the data aggregation process is a real challenge since the aggregation nodes must access the relayed data to apply the aggregation functions. The data aggregation security problem has been widely addressed in classical homogeneous wireless sensor networks, however, most of the proposed security protocols cannot guarantee a high level of security since the sensor node resources are limited. Heterogeneous wireless sensor networks have recently emerged as a new wireless sensor network category which expands the sensor nodes' resources and capabilities. These new kinds of WSNs have opened new research opportunities where security represents a most attractive area. Indeed, robust and high security level algorithms can be used to secure the data aggregation at the heterogeneous aggregation nodes which is impossible in classical homogeneous WSNs. Contrary to the homogeneous sensor networks, the data aggregation security problem is still not sufficiently covered and the proposed data aggregation security protocols are numberless. To address this recent research area, this paper describes the data aggregation security problem in heterogeneous wireless sensor networks and surveys a few proposed security protocols. A classification and evaluation of the existing protocols is also introduced based on the adopted data aggregation security approach.

Leveraging percolation theory to single out influential spreaders in networks

NASA Astrophysics Data System (ADS)

Radicchi, Filippo; Castellano, Claudio

2016-06-01

Among the consequences of the disordered interaction topology underlying many social, technological, and biological systems, a particularly important one is that some nodes, just because of their position in the network, may have a disproportionate effect on dynamical processes mediated by the complex interaction pattern. For example, the early adoption of a commercial product by an opinion leader in a social network may change its fate or just a few superspreaders may determine the virality of a meme in social media. Despite many recent efforts, the formulation of an accurate method to optimally identify influential nodes in complex network topologies remains an unsolved challenge. Here, we present the exact solution of the problem for the specific, but highly relevant, case of the susceptible-infected-removed (SIR) model for epidemic spreading at criticality. By exploiting the mapping between bond percolation and the static properties of the SIR model, we prove that the recently introduced nonbacktracking centrality is the optimal criterion for the identification of influential spreaders in locally tree-like networks at criticality. By means of simulations on synthetic networks and on a very extensive set of real-world networks, we show that the nonbacktracking centrality is a highly reliable metric to identify top influential spreaders also in generic graphs not embedded in space and for noncritical spreading.
Modelling dendritic ecological networks in space: An integrated network perspective

Treesearch

Erin E. Peterson; Jay M. Ver Hoef; Dan J. Isaak; Jeffrey A. Falke; Marie-Josee Fortin; Chris E. Jordan; Kristina McNyset; Pascal Monestiez; Aaron S. Ruesch; Aritra Sengupta; Nicholas Som; E. Ashley Steel; David M. Theobald; Christian E. Torgersen; Seth J. Wenger

2013-01-01

Dendritic ecological networks (DENs) are a unique form of ecological networks that exhibit a dendritic network topology (e.g. stream and cave networks or plant architecture). DENs have a dual spatial representation; as points within the network and as points in geographical space. Consequently, some analytical methods used to quantify relationships in other types of...
Experimental evidence for the effect of habitat loss on the dynamics of migratory networks.

PubMed

Betini, Gustavo S; Fitzpatrick, Mark J; Norris, D Ryan

2015-06-01

Migratory animals present a unique challenge for understanding the consequences of habitat loss on population dynamics because individuals are typically distributed over a series of interconnected breeding and non-breeding sites (termed migratory network). Using replicated breeding and non-breeding populations of Drosophila melanogaster and a mathematical model, we investigated three hypotheses to explain how habitat loss influenced the dynamics of populations in networks with different degrees of connectivity between breeding and non-breeding seasons. We found that habitat loss increased the degree of connectivity in the network and influenced population size at sites that were not directly connected to the site where habitat loss occurred. However, connected networks only buffered global population declines at high levels of habitat loss. Our results demonstrate why knowledge of the patterns of connectivity across a species range is critical for predicting the effects of environmental change and provide empirical evidence for why connected migratory networks are commonly found in nature. © 2015 John Wiley & Sons Ltd/CNRS.
Cascading Failures and Recovery in Networks of Networks

NASA Astrophysics Data System (ADS)

Havlin, Shlomo

Network science have been focused on the properties of a single isolated network that does not interact or depends on other networks. In reality, many real-networks, such as power grids, transportation and communication infrastructures interact and depend on other networks. I will present a framework for studying the vulnerability and the recovery of networks of interdependent networks. In interdependent networks, when nodes in one network fail, they cause dependent nodes in other networks to also fail. This is also the case when some nodes like certain locations play a role in two networks -multiplex. This may happen recursively and can lead to a cascade of failures and to a sudden fragmentation of the system. I will present analytical solutions for the critical threshold and the giant component of a network of n interdependent networks. I will show, that the general theory has many novel features that are not present in the classical network theory. When recovery of components is possible global spontaneous recovery of the networks and hysteresis phenomena occur and the theory suggests an optimal repairing strategy of system of systems. I will also show that interdependent networks embedded in space are significantly more vulnerable compared to non embedded networks. In particular, small localized attacks may lead to cascading failures and catastrophic consequences.Thus, analyzing data of real network of networks is highly required to understand the system vulnerability. DTRA, ONR, Israel Science Foundation.
A model for simulating adaptive, dynamic flows on networks: Application to petroleum infrastructure

DOE PAGES

Corbet, Thomas F.; Beyeler, Walt; Wilson, Michael L.; ...

2017-10-03

Simulation models can greatly improve decisions meant to control the consequences of disruptions to critical infrastructures. We describe a dynamic flow model on networks purposed to inform analyses by those concerned about consequences of disruptions to infrastructures and to help policy makers design robust mitigations. We conceptualize the adaptive responses of infrastructure networks to perturbations as market transactions and business decisions of operators. We approximate commodity flows in these networks by a diffusion equation, with nonlinearities introduced to model capacity limits. To illustrate the behavior and scalability of the model, we show its application first on two simple networks, thenmore » on petroleum infrastructure in the United States, where we analyze the effects of a hypothesized earthquake.« less
A model for simulating adaptive, dynamic flows on networks: Application to petroleum infrastructure

DOE Office of Scientific and Technical Information (OSTI.GOV)

Corbet, Thomas F.; Beyeler, Walt; Wilson, Michael L.

Simulation models can greatly improve decisions meant to control the consequences of disruptions to critical infrastructures. We describe a dynamic flow model on networks purposed to inform analyses by those concerned about consequences of disruptions to infrastructures and to help policy makers design robust mitigations. We conceptualize the adaptive responses of infrastructure networks to perturbations as market transactions and business decisions of operators. We approximate commodity flows in these networks by a diffusion equation, with nonlinearities introduced to model capacity limits. To illustrate the behavior and scalability of the model, we show its application first on two simple networks, thenmore » on petroleum infrastructure in the United States, where we analyze the effects of a hypothesized earthquake.« less
Characterization and management of electrical noise in the new Australian military HF communication network

NASA Astrophysics Data System (ADS)

Vyden, Bruce

2000-03-01

The Australian Defense Force's (ADF's) High Frequency (HF) communication network is soon to be replaced by a modernized system. Characterization of electrical noise at the receiver sites proposed for the new system is crucial to its performance. Consequently receiver site noise will be measured under the HF Modernization implementation contract that was awarded to Boeing Australia Ltd. Unfortunately the utility of the noise measurements is constrained by the uncertainties of both the ionosphere and atmosphere. This paper discusses some of the issues related to the methodology for measuring the noise and exposes some unresolved issues.
Pressure effects on collective density fluctuations in water and protein solutions

PubMed Central

Russo, Daniela; Laloni, Alessio; Filabozzi, Alessandra; Heyden, Matthias

2017-01-01

Neutron Brillouin scattering and molecular dynamics simulations have been used to investigate protein hydration water density fluctuations as a function of pressure. Our results show significant differences between the pressure and density dependence of collective dynamics in bulk water and in concentrated protein solutions. Pressure-induced changes in the tetrahedral order of the water HB network have direct consequences for the high-frequency sound velocity and damping coefficients, which we find to be a sensitive probe for changes in the HB network structure as well as the wetting of biomolecular surfaces. PMID:29073065
Constraints and entropy in a model of network evolution

NASA Astrophysics Data System (ADS)

Tee, Philip; Wakeman, Ian; Parisis, George; Dawes, Jonathan; Kiss, István Z.

2017-11-01

Barabási-Albert's "Scale Free" model is the starting point for much of the accepted theory of the evolution of real world communication networks. Careful comparison of the theory with a wide range of real world networks, however, indicates that the model is in some cases, only a rough approximation to the dynamical evolution of real networks. In particular, the exponent γ of the power law distribution of degree is predicted by the model to be exactly 3, whereas in a number of real world networks it has values between 1.2 and 2.9. In addition, the degree distributions of real networks exhibit cut offs at high node degree, which indicates the existence of maximal node degrees for these networks. In this paper we propose a simple extension to the "Scale Free" model, which offers better agreement with the experimental data. This improvement is satisfying, but the model still does not explain why the attachment probabilities should favor high degree nodes, or indeed how constraints arrive in non-physical networks. Using recent advances in the analysis of the entropy of graphs at the node level we propose a first principles derivation for the "Scale Free" and "constraints" model from thermodynamic principles, and demonstrate that both preferential attachment and constraints could arise as a natural consequence of the second law of thermodynamics.
Energy recovery from waste incineration: assessing the importance of district heating networks.

PubMed

Fruergaard, T; Christensen, T H; Astrup, T

2010-07-01

Municipal solid waste incineration contributes with 20% of the heat supplied to the more than 400 district heating networks in Denmark. In evaluation of the environmental consequences of this heat production, the typical approach has been to assume that other (fossil) fuels could be saved on a 1:1 basis (e.g. 1GJ of waste heat delivered substitutes for 1GJ of coal-based heat). This paper investigates consequences of waste-based heat substitution in two specific Danish district heating networks and the energy-associated interactions between the plants connected to these networks. Despite almost equal electricity and heat efficiencies at the waste incinerators connected to the two district heating networks, the energy and CO(2) accounts showed significantly different results: waste incineration in one network caused a CO(2) saving of 48 kg CO(2)/GJ energy input while in the other network a load of 43 kg CO(2)/GJ. This was caused mainly by differences in operation mode and fuel types of the other heat producing plants attached to the networks. The paper clearly indicates that simple evaluations of waste-to-energy efficiencies at the incinerator are insufficient for assessing the consequences of heat substitution in district heating network systems. The paper also shows that using national averages for heat substitution will not provide a correct answer: local conditions need to be addressed thoroughly otherwise we may fail to assess correctly the heat recovery from waste incineration. Copyright (c) 2010 Elsevier Ltd. All rights reserved.
Tough stimuli-responsive supramolecular hydrogels with hydrogen-bonding network junctions.

PubMed

Guo, Mingyu; Pitet, Louis M; Wyss, Hans M; Vos, Matthijn; Dankers, Patricia Y W; Meijer, E W

2014-05-14

Hydrogels were prepared with physical cross-links comprising 2-ureido-4[1H]-pyrimidinone (UPy) hydrogen-bonding units within the backbone of segmented amphiphilic macromolecules having hydrophilic poly(ethylene glycol) (PEG). The bulk materials adopt nanoscopic physical cross-links composed of UPy-UPy dimers embedded in segregated hydrophobic domains dispersed within the PEG matrix as comfirmed by cryo-electron microscopy. The amphiphilic network was swollen with high weight fractions of water (w(H2O) ≈ 0.8) owing to the high PEG weight fraction within the pristine polymers (w(PEG) ≈ 0.9). Two different PEG chain lengths were investigated and illustrate the corresponding consequences of cross-link density on mechanical properties. The resulting hydrogels exhibited high strength and resilience upon deformation, consistent with a microphase separated network, in which the UPy-UPy interactions were adequately shielded within hydrophobic nanoscale pockets that maintain the network despite extensive water content. The cumulative result is a series of tough hydrogels with tunable mechanical properties and tractable synthetic preparation and processing. Furthermore, the melting transition of PEG in the dry polymer was shown to be an effective stimulus for shape memory behavior.
Why is social network drinking associated with college students' alcohol use? Focus on psychological mediators.

PubMed

Reid, Allecia E; Carey, Kate B

2018-06-01

Level of drinking in the social network is strongly associated with college students' alcohol use. However, mechanisms through which networks are associated with personal drinking have been underexplored thus far. The present study examined theoretically derived constructs-sociability outcome expectancies, attitudes toward heavy drinking, self-efficacy for use of protective strategies, and descriptive norms-as potential mediators of the association between egocentric social network drinking and personal consumption. College students (N = 274) self-reported their social network's level of alcohol consumption, all mediators, drinks per week, and consequences at both baseline (Time 1) and a 1-month follow-up (Time 2). Autoregressive mediation models focused on the longitudinal associations between Time 1 network drinking and the Time 2 mediators and between the Time 1 mediators and the Time 2 outcomes. Consistent with hypotheses, Time 1 social network drinking was significantly associated with Time 2 drinks per week and consequences. Only attitudes significantly mediated social network associations with drinks per week and consequences, though the proportion of the total effects accounted for by attitudes was small. After accounting for the stability of constructs over time, social network drinking was generally un- or weakly related to sociability expectancies, self-efficacy, and descriptive norms. Results support reducing attitudes toward heavy drinking as a potential avenue for mitigating network effects, but also highlight the need to evaluate additional potential mechanisms of network effects. Intervention efforts that aim to address the social network have the potential to substantially reduce alcohol consumption, thereby enhancing the overall efficacy of alcohol risk-reduction interventions. (PsycINFO Database Record (c) 2018 APA, all rights reserved).
Undermining and Strengthening Social Networks through Network Modification

PubMed Central

Mellon, Jonathan; Yoder, Jordan; Evans, Daniel

2016-01-01

Social networks have well documented effects at the individual and aggregate level. Consequently it is often useful to understand how an attempt to influence a network will change its structure and consequently achieve other goals. We develop a framework for network modification that allows for arbitrary objective functions, types of modification (e.g. edge weight addition, edge weight removal, node removal, and covariate value change), and recovery mechanisms (i.e. how a network responds to interventions). The framework outlined in this paper helps both to situate the existing work on network interventions but also opens up many new possibilities for intervening in networks. In particular use two case studies to highlight the potential impact of empirically calibrating the objective function and network recovery mechanisms as well as showing how interventions beyond node removal can be optimised. First, we simulate an optimal removal of nodes from the Noordin terrorist network in order to reduce the expected number of attacks (based on empirically predicting the terrorist collaboration network from multiple types of network ties). Second, we simulate optimally strengthening ties within entrepreneurial ecosystems in six developing countries. In both cases we estimate ERGM models to simulate how a network will endogenously evolve after intervention. PMID:27703198
Undermining and Strengthening Social Networks through Network Modification.

PubMed

Mellon, Jonathan; Yoder, Jordan; Evans, Daniel

2016-10-05

Social networks have well documented effects at the individual and aggregate level. Consequently it is often useful to understand how an attempt to influence a network will change its structure and consequently achieve other goals. We develop a framework for network modification that allows for arbitrary objective functions, types of modification (e.g. edge weight addition, edge weight removal, node removal, and covariate value change), and recovery mechanisms (i.e. how a network responds to interventions). The framework outlined in this paper helps both to situate the existing work on network interventions but also opens up many new possibilities for intervening in networks. In particular use two case studies to highlight the potential impact of empirically calibrating the objective function and network recovery mechanisms as well as showing how interventions beyond node removal can be optimised. First, we simulate an optimal removal of nodes from the Noordin terrorist network in order to reduce the expected number of attacks (based on empirically predicting the terrorist collaboration network from multiple types of network ties). Second, we simulate optimally strengthening ties within entrepreneurial ecosystems in six developing countries. In both cases we estimate ERGM models to simulate how a network will endogenously evolve after intervention.
Undermining and Strengthening Social Networks through Network Modification

NASA Astrophysics Data System (ADS)

Mellon, Jonathan; Yoder, Jordan; Evans, Daniel

2016-10-01

Social networks have well documented effects at the individual and aggregate level. Consequently it is often useful to understand how an attempt to influence a network will change its structure and consequently achieve other goals. We develop a framework for network modification that allows for arbitrary objective functions, types of modification (e.g. edge weight addition, edge weight removal, node removal, and covariate value change), and recovery mechanisms (i.e. how a network responds to interventions). The framework outlined in this paper helps both to situate the existing work on network interventions but also opens up many new possibilities for intervening in networks. In particular use two case studies to highlight the potential impact of empirically calibrating the objective function and network recovery mechanisms as well as showing how interventions beyond node removal can be optimised. First, we simulate an optimal removal of nodes from the Noordin terrorist network in order to reduce the expected number of attacks (based on empirically predicting the terrorist collaboration network from multiple types of network ties). Second, we simulate optimally strengthening ties within entrepreneurial ecosystems in six developing countries. In both cases we estimate ERGM models to simulate how a network will endogenously evolve after intervention.
Privacy Issues of a National Research and Education Network.

ERIC Educational Resources Information Center

Katz, James E.; Graveman, Richard F.

1991-01-01

Discussion of the right to privacy of communications focuses on privacy expectations within a National Research and Education Network (NREN). Highlights include privacy needs in scientific and education communications; academic and research networks; network security and privacy concerns; protection strategies; and consequences of privacy…
The evolution of cost-efficiency in neural networks during recovery from traumatic brain injury.

PubMed

Roy, Arnab; Bernier, Rachel A; Wang, Jianli; Benson, Monica; French, Jerry J; Good, David C; Hillary, Frank G

2017-01-01

A somewhat perplexing finding in the systems neuroscience has been the observation that physical injury to neural systems may result in enhanced functional connectivity (i.e., hyperconnectivity) relative to the typical network response. The consequences of local or global enhancement of functional connectivity remain uncertain and this is particularly true for the overall metabolic cost of the network. We examine the hyperconnectivity hypothesis in a sample of 14 individuals with TBI with data collected at approximately 3, 6, and 12 months following moderate and severe TBI. As anticipated, individuals with TBI showed increased network strength and cost early after injury, but by one-year post injury hyperconnectivity was more circumscribed to frontal DMN and temporal-parietal attentional control regions. Cost in these subregions was a significant predictor of cognitive performance. Cost-efficiency analysis in the Power 264 data parcellation suggested that at 6 months post injury the network requires higher cost connections to achieve high efficiency as compared to the network 12 months post injury. These results demonstrate that networks self-organize to re-establish connectivity while balancing cost-efficiency trade-offs.
The evolution of cost-efficiency in neural networks during recovery from traumatic brain injury

PubMed Central

Roy, Arnab; Bernier, Rachel A.; Wang, Jianli; Benson, Monica; French, Jerry J.; Good, David C.; Hillary, Frank G.

2017-01-01

A somewhat perplexing finding in the systems neuroscience has been the observation that physical injury to neural systems may result in enhanced functional connectivity (i.e., hyperconnectivity) relative to the typical network response. The consequences of local or global enhancement of functional connectivity remain uncertain and this is particularly true for the overall metabolic cost of the network. We examine the hyperconnectivity hypothesis in a sample of 14 individuals with TBI with data collected at approximately 3, 6, and 12 months following moderate and severe TBI. As anticipated, individuals with TBI showed increased network strength and cost early after injury, but by one-year post injury hyperconnectivity was more circumscribed to frontal DMN and temporal-parietal attentional control regions. Cost in these subregions was a significant predictor of cognitive performance. Cost-efficiency analysis in the Power 264 data parcellation suggested that at 6 months post injury the network requires higher cost connections to achieve high efficiency as compared to the network 12 months post injury. These results demonstrate that networks self-organize to re-establish connectivity while balancing cost-efficiency trade-offs. PMID:28422992
To cut or not to cut? Assessing the modular structure of brain networks.

PubMed

Chang, Yu-Teng; Pantazis, Dimitrios; Leahy, Richard M

2014-05-01

A wealth of methods has been developed to identify natural divisions of brain networks into groups or modules, with one of the most prominent being modularity. Compared with the popularity of methods to detect community structure, only a few methods exist to statistically control for spurious modules, relying almost exclusively on resampling techniques. It is well known that even random networks can exhibit high modularity because of incidental concentration of edges, even though they have no underlying organizational structure. Consequently, interpretation of community structure is confounded by the lack of principled and computationally tractable approaches to statistically control for spurious modules. In this paper we show that the modularity of random networks follows a transformed version of the Tracy-Widom distribution, providing for the first time a link between module detection and random matrix theory. We compute parametric formulas for the distribution of modularity for random networks as a function of network size and edge variance, and show that we can efficiently control for false positives in brain and other real-world networks. Copyright © 2014 Elsevier Inc. All rights reserved.
Highly viscous antibody solutions are a consequence of network formation caused by domain-domain electrostatic complementarities: insights from coarse-grained simulations.

PubMed

Buck, Patrick M; Chaudhri, Anuj; Kumar, Sandeep; Singh, Satish K

2015-01-05

Therapeutic monoclonal antibody (mAb) candidates that form highly viscous solutions at concentrations above 100 mg/mL can lead to challenges in bioprocessing, formulation development, and subcutaneous drug delivery. Earlier studies of mAbs with concentration-dependent high viscosity have indicated that mAbs with negatively charged Fv regions have a dipole-like quality that increases the likelihood of reversible self-association. This suggests that weak electrostatic intermolecular interactions can form transient antibody networks that participate in resistance to solution deformation under shear stress. Here this hypothesis is explored by parametrizing a coarse-grained (CG) model of an antibody using the domain charges from four different mAbs that have had their concentration-dependent viscosity behaviors previously determined. Multicopy molecular dynamics simulations were performed for these four CG mAbs at several concentrations to understand the effect of surface charge on mass diffusivity, pairwise interactions, and electrostatic network formation. Diffusion coefficients computed from simulations were in qualitative agreement with experimentally determined viscosities for all four mAbs. Contact analysis revealed an overall greater number of pairwise interactions for the two mAbs in this study with high concentration viscosity issues. Further, using equilibrated solution trajectories, the two mAbs with high concentration viscosity issues quantitatively formed more features of an electrostatic network than the other mAbs. The change in the number of these network features as a function of concentration is related to the number of pairwise interactions formed by electrostatic complementarities between antibody domains. Thus, transient antibody network formation caused by domain-domain electrostatic complementarities is the most probable origin of high concentration viscosity for mAbs in this study.

Building Social Support Systems through a Babysitting Exchange Program.

ERIC Educational Resources Information Center

Douglas, Jeanne A.; Jason, Leonard A.

A babysitting exchange program was created for a group of women in order to build a social support network and to provide a test of the buffer hypothesis (i.e., the idea that social support may shield an individual from the negative physical and mental consequences of stress, particularly when stress is at high levels). The sample consisted of 30…
Predictive functional control for active queue management in congested TCP/IP networks.

PubMed

Bigdeli, N; Haeri, M

2009-01-01

Predictive functional control (PFC) as a new active queue management (AQM) method in dynamic TCP networks supporting explicit congestion notification (ECN) is proposed. The ability of the controller in handling system delay along with its simplicity and low computational load makes PFC a privileged AQM method in the high speed networks. Besides, considering the disturbance term (which represents model/process mismatches, external disturbances, and existing noise) in the control formulation adds some level of robustness into the PFC-AQM controller. This is an important and desired property in the control of dynamically-varying computer networks. In this paper, the controller is designed based on a small signal linearized fluid-flow model of the TCP/AQM networks. Then, closed-loop transfer function representation of the system is derived to analyze the robustness with respect to the network and controller parameters. The analytical as well as the packet-level ns-2 simulation results show the out-performance of the developed controller for both queue regulation and resource utilization. Fast response, low queue fluctuations (and consequently low delay jitter), high link utilization, good disturbance rejection, scalability, and low packet marking probability are other features of the developed method with respect to other well-known AQM methods such as RED, PI, and REM which are also simulated for comparison.
An Optimal Balance between Efficiency and Safety of Urban Drainage Networks

NASA Astrophysics Data System (ADS)

Seo, Y.

2014-12-01

Urban drainage networks have been developed to promote the efficiency of a system in terms of drainage time so far. Typically, a drainage system is designed to drain water from developed areas promptly as much as possible during floods. In this regard, an artificial drainage system have been considered to be more efficient compared to river networks in nature. This study examined artificial drainage networks and the results indicate they can be less efficient in terms of network configuration compared with river networks, which is counter-intuitive. The case study of 20 catchments in Seoul, South Korea shows that they have wide range of efficiency in terms of network configuration and consequently, drainage time. This study also demonstrates that efficient drainage networks are more sensitive to spatial and temporal rainfall variation such as rainstorm movement. Peak flows increase more than two times greater in effective drainage networks compared with inefficient and highly sinuous drainage networks. Combining these results, this study implies that the layout of a drainage network is an important factor in terms of efficient drainage and also safety in urban catchments. Design of an optimal layout of the drainage network can be an alternative non-structural measures that mitigate potential risks and it is crucial for the sustainability of urban environments.
The LAAS network observation for studying time correlations in extensive air showers

NASA Astrophysics Data System (ADS)

Ochi, Nobuaki; Iyono, A.; Kimura, Hitoomi; Konishi, Takeharu; Nakamura, Toru; Nakatsuka, Takao; Ohara, Soji; Ohmori, Nobuharu; Saito, Katsuhiko; Takahashi, Nobusuke; Tsuji, Shuhei; Wada, Tomonori; Yamamoto, Isao; Yamashita, Yoshihiko; Yanagimoto, Yukio

2003-02-01

The Large Area Air Shower (LAAS) group has been performing a network observation of extensive air showers (EAS) since 1996 in Japan. Ten compact EAS arrays are operating simultaneously at distant stations (up to ≍1000 km) and detecting EAS with mean energy of ≍1015 eV. Each station has 4--12 scintillation counters and a Global Positioning System (GPS), which provides time stamps of EAS triggers with an accuracy of 1μs. As a consequence of the comparable time stamps, uniformly-adjusted detectors and a standardized data format among all stations, we can treat the independent observations as a gigantic EAS detector system as a whole. The primary purpose of the network observation is to study large-scale correlations in ultra-high-energy cosmic rays. On the other hand, three nearby stations within 1~km distance at Okayama area have a possibility to detect extremely-high-energy EAS (≍1019 eV) as coincident triggers of the three stations. The present status of the network and some results from computer simulations are reported here.
Managing Network Partitions in Structured P2P Networks

NASA Astrophysics Data System (ADS)

Shafaat, Tallat M.; Ghodsi, Ali; Haridi, Seif

Structured overlay networks form a major class of peer-to-peer systems, which are touted for their abilities to scale, tolerate failures, and self-manage. Any long-lived Internet-scale distributed system is destined to face network partitions. Consequently, the problem of network partitions and mergers is highly related to fault-tolerance and self-management in large-scale systems. This makes it a crucial requirement for building any structured peer-to-peer systems to be resilient to network partitions. Although the problem of network partitions and mergers is highly related to fault-tolerance and self-management in large-scale systems, it has hardly been studied in the context of structured peer-to-peer systems. Structured overlays have mainly been studied under churn (frequent joins/failures), which as a side effect solves the problem of network partitions, as it is similar to massive node failures. Yet, the crucial aspect of network mergers has been ignored. In fact, it has been claimed that ring-based structured overlay networks, which constitute the majority of the structured overlays, are intrinsically ill-suited for merging rings. In this chapter, we motivate the problem of network partitions and mergers in structured overlays. We discuss how a structured overlay can automatically detect a network partition and merger. We present an algorithm for merging multiple similar ring-based overlays when the underlying network merges. We examine the solution in dynamic conditions, showing how our solution is resilient to churn during the merger, something widely believed to be difficult or impossible. We evaluate the algorithm for various scenarios and show that even when falsely detecting a merger, the algorithm quickly terminates and does not clutter the network with many messages. The algorithm is flexible as the tradeoff between message complexity and time complexity can be adjusted by a parameter.
Spatiotemporal dynamics of surface water networks across a global biodiversity hotspot—implications for conservation

NASA Astrophysics Data System (ADS)

Tulbure, Mirela G.; Kininmonth, Stuart; Broich, Mark

2014-11-01

The concept of habitat networks represents an important tool for landscape conservation and management at regional scales. Previous studies simulated degradation of temporally fixed networks but few quantified the change in network connectivity from disintegration of key features that undergo naturally occurring spatiotemporal dynamics. This is particularly of concern for aquatic systems, which typically show high natural spatiotemporal variability. Here we focused on the Swan Coastal Plain, a bioregion that encompasses a global biodiversity hotspot in Australia with over 1500 water bodies of high biodiversity. Using graph theory, we conducted a temporal analysis of water body connectivity over 13 years of variable climate. We derived large networks of surface water bodies using Landsat data (1999-2011). We generated an ensemble of 278 potential networks at three dispersal distances approximating the maximum dispersal distance of different water dependent organisms. We assessed network connectivity through several network topology metrics and quantified the resilience of the network topology during wet and dry phases. We identified ‘stepping stone’ water bodies across time and compared our networks with theoretical network models with known properties. Results showed a highly dynamic seasonal pattern of variability in network topology metrics. A decline in connectivity over the 13 years was noted with potential negative consequences for species with limited dispersal capacity. The networks described here resemble theoretical scale-free models, also known as ‘rich get richer’ algorithm. The ‘stepping stone’ water bodies are located in the area around the Peel-Harvey Estuary, a Ramsar listed site, and some are located in a national park. Our results describe a powerful approach that can be implemented when assessing the connectivity for a particular organism with known dispersal distance. The approach of identifying the surface water bodies that act as ‘stepping stone’ over time may help prioritize surface water bodies that are essential for maintaining regional scale connectivity.
Simultaneous entanglement swapping of multiple orbital angular momentum states of light.

PubMed

Zhang, Yingwen; Agnew, Megan; Roger, Thomas; Roux, Filippus S; Konrad, Thomas; Faccio, Daniele; Leach, Jonathan; Forbes, Andrew

2017-09-21

High-bit-rate long-distance quantum communication is a proposed technology for future communication networks and relies on high-dimensional quantum entanglement as a core resource. While it is known that spatial modes of light provide an avenue for high-dimensional entanglement, the ability to transport such quantum states robustly over long distances remains challenging. To overcome this, entanglement swapping may be used to generate remote quantum correlations between particles that have not interacted; this is the core ingredient of a quantum repeater, akin to repeaters in optical fibre networks. Here we demonstrate entanglement swapping of multiple orbital angular momentum states of light. Our approach does not distinguish between different anti-symmetric states, and thus entanglement swapping occurs for several thousand pairs of spatial light modes simultaneously. This work represents the first step towards a quantum network for high-dimensional entangled states and provides a test bed for fundamental tests of quantum science.Entanglement swapping in high dimensions requires large numbers of entangled photons and consequently suffers from low photon flux. Here the authors demonstrate entanglement swapping of multiple spatial modes of light simultaneously, without the need for increasing the photon numbers with dimension.
Unravelling daily human mobility motifs

PubMed Central

Schneider, Christian M.; Belik, Vitaly; Couronné, Thomas; Smoreda, Zbigniew; González, Marta C.

2013-01-01

Human mobility is differentiated by time scales. While the mechanism for long time scales has been studied, the underlying mechanism on the daily scale is still unrevealed. Here, we uncover the mechanism responsible for the daily mobility patterns by analysing the temporal and spatial trajectories of thousands of persons as individual networks. Using the concept of motifs from network theory, we find only 17 unique networks are present in daily mobility and they follow simple rules. These networks, called here motifs, are sufficient to capture up to 90 per cent of the population in surveys and mobile phone datasets for different countries. Each individual exhibits a characteristic motif, which seems to be stable over several months. Consequently, daily human mobility can be reproduced by an analytically tractable framework for Markov chains by modelling periods of high-frequency trips followed by periods of lower activity as the key ingredient. PMID:23658117
An Outline of Data Aggregation Security in Heterogeneous Wireless Sensor Networks

PubMed Central

Boubiche, Sabrina; Boubiche, Djallel Eddine; Bilami, Azzedine; Toral-Cruz, Homero

2016-01-01

Data aggregation processes aim to reduce the amount of exchanged data in wireless sensor networks and consequently minimize the packet overhead and optimize energy efficiency. Securing the data aggregation process is a real challenge since the aggregation nodes must access the relayed data to apply the aggregation functions. The data aggregation security problem has been widely addressed in classical homogeneous wireless sensor networks, however, most of the proposed security protocols cannot guarantee a high level of security since the sensor node resources are limited. Heterogeneous wireless sensor networks have recently emerged as a new wireless sensor network category which expands the sensor nodes’ resources and capabilities. These new kinds of WSNs have opened new research opportunities where security represents a most attractive area. Indeed, robust and high security level algorithms can be used to secure the data aggregation at the heterogeneous aggregation nodes which is impossible in classical homogeneous WSNs. Contrary to the homogeneous sensor networks, the data aggregation security problem is still not sufficiently covered and the proposed data aggregation security protocols are numberless. To address this recent research area, this paper describes the data aggregation security problem in heterogeneous wireless sensor networks and surveys a few proposed security protocols. A classification and evaluation of the existing protocols is also introduced based on the adopted data aggregation security approach. PMID:27077866
Security Shift in Future Network Architectures

DTIC Science & Technology

2010-11-01

RTO-MP-IST-091 2 - 1 Security Shift in Future Network Architectures Tim Hartog, M.Sc Information Security Dept. TNO Information and...current practice military communication infrastructures are deployed as stand-alone networked information systems. Network -Enabled Capabilities (NEC) and...information architects and security specialists about the separation of network and information security, the consequences of this shift and our view
Intervality and coherence in complex networks

NASA Astrophysics Data System (ADS)

Domínguez-García, Virginia; Johnson, Samuel; Muñoz, Miguel A.

2016-06-01

Food webs—networks of predators and prey—have long been known to exhibit "intervality": species can generally be ordered along a single axis in such a way that the prey of any given predator tend to lie on unbroken compact intervals. Although the meaning of this axis—usually identified with a "niche" dimension—has remained a mystery, it is assumed to lie at the basis of the highly non-trivial structure of food webs. With this in mind, most trophic network modelling has for decades been based on assigning species a niche value by hand. However, we argue here that intervality should not be considered the cause but rather a consequence of food-web structure. First, analysing a set of 46 empirical food webs, we find that they also exhibit predator intervality: the predators of any given species are as likely to be contiguous as the prey are, but in a different ordering. Furthermore, this property is not exclusive of trophic networks: several networks of genes, neurons, metabolites, cellular machines, airports, and words are found to be approximately as interval as food webs. We go on to show that a simple model of food-web assembly which does not make use of a niche axis can nevertheless generate significant intervality. Therefore, the niche dimension (in the sense used for food-web modelling) could in fact be the consequence of other, more fundamental structural traits. We conclude that a new approach to food-web modelling is required for a deeper understanding of ecosystem assembly, structure, and function, and propose that certain topological features thought to be specific of food webs are in fact common to many complex networks.
Networks: A Route to Improving Performance in Manufacturing SMEs

ERIC Educational Resources Information Center

Coleman, J.

2003-01-01

Perceived as important contributors to economic growth, network and cluster groups are currently receiving much attention. The same may be said of SMEs. But practical and theoretical perspectives indicate that SMEs, and particularly the owner-managers, place little value on networks and have only limited networking resources. Consequently, they do…
Hacking the Cell: Network Intrusion and Exploitation by Adenovirus E1A.

PubMed

King, Cason R; Zhang, Ali; Tessier, Tanner M; Gameiro, Steven F; Mymryk, Joe S

2018-05-01

As obligate intracellular parasites, viruses are dependent on their infected hosts for survival. Consequently, viruses are under enormous selective pressure to utilize available cellular components and processes to their own advantage. As most, if not all, cellular activities are regulated at some level via protein interactions, host protein interaction networks are particularly vulnerable to viral exploitation. Indeed, viral proteins frequently target highly connected "hub" proteins to "hack" the cellular network, defining the molecular basis for viral control over the host. This widespread and successful strategy of network intrusion and exploitation has evolved convergently among numerous genetically distinct viruses as a result of the endless evolutionary arms race between pathogens and hosts. Here we examine the means by which a particularly well-connected viral hub protein, human adenovirus E1A, compromises and exploits the vulnerabilities of eukaryotic protein interaction networks. Importantly, these interactions identify critical regulatory hubs in the human proteome and help define the molecular basis of their function. Copyright © 2018 King et al.
Hacking the Cell: Network Intrusion and Exploitation by Adenovirus E1A

PubMed Central

King, Cason R.; Zhang, Ali; Tessier, Tanner M.; Gameiro, Steven F.

2018-01-01

ABSTRACT As obligate intracellular parasites, viruses are dependent on their infected hosts for survival. Consequently, viruses are under enormous selective pressure to utilize available cellular components and processes to their own advantage. As most, if not all, cellular activities are regulated at some level via protein interactions, host protein interaction networks are particularly vulnerable to viral exploitation. Indeed, viral proteins frequently target highly connected “hub” proteins to “hack” the cellular network, defining the molecular basis for viral control over the host. This widespread and successful strategy of network intrusion and exploitation has evolved convergently among numerous genetically distinct viruses as a result of the endless evolutionary arms race between pathogens and hosts. Here we examine the means by which a particularly well-connected viral hub protein, human adenovirus E1A, compromises and exploits the vulnerabilities of eukaryotic protein interaction networks. Importantly, these interactions identify critical regulatory hubs in the human proteome and help define the molecular basis of their function. PMID:29717008
Building gene co-expression networks using transcriptomics data for systems biology investigations: Comparison of methods using microarray data

PubMed Central

Kadarmideen, Haja N; Watson-haigh, Nathan S

2012-01-01

Gene co-expression networks (GCN), built using high-throughput gene expression data are fundamental aspects of systems biology. The main aims of this study were to compare two popular approaches to building and analysing GCN. We use real ovine microarray transcriptomics datasets representing four different treatments with Metyrapone, an inhibitor of cortisol biosynthesis. We conducted several microarray quality control checks before applying GCN methods to filtered datasets. Then we compared the outputs of two methods using connectivity as a criterion, as it measures how well a node (gene) is connected within a network. The two GCN construction methods used were, Weighted Gene Co-expression Network Analysis (WGCNA) and Partial Correlation and Information Theory (PCIT) methods. Nodes were ranked based on their connectivity measures in each of the four different networks created by WGCNA and PCIT and node ranks in two methods were compared to identify those nodes which are highly differentially ranked (HDR). A total of 1,017 HDR nodes were identified across one or more of four networks. We investigated HDR nodes by gene enrichment analyses in relation to their biological relevance to phenotypes. We observed that, in contrast to WGCNA method, PCIT algorithm removes many of the edges of the most highly interconnected nodes. Removal of edges of most highly connected nodes or hub genes will have consequences for downstream analyses and biological interpretations. In general, for large GCN construction (with > 20000 genes) access to large computer clusters, particularly those with larger amounts of shared memory is recommended. PMID:23144540
Ecological consequences of colony structure in dynamic ant nest networks.

PubMed

Ellis, Samuel; Franks, Daniel W; Robinson, Elva J H

2017-02-01

Access to resources depends on an individual's position within the environment. This is particularly important to animals that invest heavily in nest construction, such as social insects. Many ant species have a polydomous nesting strategy: a single colony inhabits several spatially separated nests, often exchanging resources between the nests. Different nests in a polydomous colony potentially have differential access to resources, but the ecological consequences of this are unclear. In this study, we investigate how nest survival and budding in polydomous wood ant ( Formica lugubris ) colonies are affected by being part of a multi-nest system. Using field data and novel analytical approaches combining survival models with dynamic network analysis, we show that the survival and budding of nests within a polydomous colony are affected by their position in the nest network structure. Specifically, we find that the flow of resources through a nest, which is based on its position within the wider nest network, determines a nest's likelihood of surviving and of founding new nests. Our results highlight how apparently disparate entities in a biological system can be integrated into a functional ecological unit. We also demonstrate how position within a dynamic network structure can have important ecological consequences.
Light scattering optimization of chitin random network in ultrawhite beetle scales

NASA Astrophysics Data System (ADS)

Utel, Francesco; Cortese, Lorenzo; Pattelli, Lorenzo; Burresi, Matteo; Vignolini, Silvia; Wiersma, Diederik

2017-09-01

Among the natural white colored photonics structures, a bio-system has become of great interest in the field of disordered optical media: the scale of the white beetle Chyphochilus. Despite its low thickness, on average 7 μm, and low refractive index, this beetle exhibits extreme high brightness and unique whiteness. These properties arise from the interaction of light with a complex network of chitin nano filaments embedded in the interior of the scales. As it's been recently claimed, this could be a consequence of the peculiar morphology of the filaments network that, by means of high filling fraction (0.61) and structural anisotropy, optimizes the multiple scattering of light. We therefore performed a numerical analysis on the structural properties of the chitin network in order to understand their role in the enhancement of the scale scattering intensity. Modeling the filaments as interconnected rod shaped scattering centers, we numerically generated the spatial coordinates of the network components. Controlling the quantities that are claimed to play a fundamental role in the brightness and whiteness properties of the investigated system (filling fraction and average rods orientation, i.e. the anisotropy of the ensemble of scattering centers), we obtained a set of customized random networks. FDTD simulations of light transport have been performed on these systems, observing high reflectance for all the visible frequencies and proving the implemented algorithm to numerically generate the structures is suitable to investigate the dependence of reflectance by anisotropy.
Brain network disturbance related to posttraumatic stress and traumatic brain injury in veterans.

PubMed

Spielberg, Jeffrey M; McGlinchey, Regina E; Milberg, William P; Salat, David H

2015-08-01

Understanding the neural causes and consequences of posttraumatic stress disorder (PTSD) and mild traumatic brain injury (mTBI) is a high research priority, given the high rates of associated disability and suicide. Despite remarkable progress in elucidating the brain mechanisms of PTSD and mTBI, a comprehensive understanding of these conditions at the level of brain networks has yet to be achieved. The present study sought to identify functional brain networks and topological properties (measures of network organization and function) related to current PTSD severity and mTBI. Graph theoretic tools were used to analyze resting-state functional magnetic resonance imaging data from 208 veterans of Operation Enduring Freedom, Operation Iraqi Freedom, and Operation New Dawn, all of whom had experienced a traumatic event qualifying for PTSD criterion A. Analyses identified brain networks and topological network properties linked to current PTSD symptom severity, mTBI, and the interaction between PTSD and mTBI. Two brain networks were identified in which weaker connectivity was linked to higher PTSD re-experiencing symptoms, one of which was present only in veterans with comorbid mTBI. Re-experiencing was also linked to worse functional segregation (necessary for specialized processing) and diminished influence of key regions on the network, including the hippocampus. Findings of this study demonstrate that PTSD re-experiencing symptoms are linked to weakened connectivity in a network involved in providing contextual information. A similar relationship was found in a separate network typically engaged in the gating of working memory, but only in veterans with mTBI. Published by Elsevier Inc.
Hierarchical organization of brain functional networks during visual tasks.

PubMed

Zhuo, Zhao; Cai, Shi-Min; Fu, Zhong-Qian; Zhang, Jie

2011-09-01

The functional network of the brain is known to demonstrate modular structure over different hierarchical scales. In this paper, we systematically investigated the hierarchical modular organizations of the brain functional networks that are derived from the extent of phase synchronization among high-resolution EEG time series during a visual task. In particular, we compare the modular structure of the functional network from EEG channels with that of the anatomical parcellation of the brain cortex. Our results show that the modular architectures of brain functional networks correspond well to those from the anatomical structures over different levels of hierarchy. Most importantly, we find that the consistency between the modular structures of the functional network and the anatomical network becomes more pronounced in terms of vision, sensory, vision-temporal, motor cortices during the visual task, which implies that the strong modularity in these areas forms the functional basis for the visual task. The structure-function relationship further reveals that the phase synchronization of EEG time series in the same anatomical group is much stronger than that of EEG time series from different anatomical groups during the task and that the hierarchical organization of functional brain network may be a consequence of functional segmentation of the brain cortex.
Enhancing response coordination through the assessment of response network structural dynamics.

PubMed

Abbasi, Alireza; Sadeghi-Niaraki, Abolghasem; Jalili, Mahdi; Choi, Soo-Mi

2018-01-01

Preparing for intensifying threats of emergencies in unexpected, dangerous, and serious natural or man-made events, and consequent management of the situation, is highly demanding in terms of coordinating the personnel and resources to support human lives and the environment. This necessitates prompt action to manage the uncertainties and risks imposed by such extreme events, which requires collaborative operation among different stakeholders (i.e., the personnel from both the state and local communities). This research aims to find a way to enhance the coordination of multi-organizational response operations. To do so, this manuscript investigates the role of participants in the formed coordination response network and also the emergence and temporal dynamics of the network. By analyzing an inter-personal response coordination operation to an extreme bushfire event, the networks' and participants' structural change is evaluated during the evolution of the operation network over four time durations. The results reveal that the coordination response network becomes more decentralized over time due to the high volume of communication required to exchange information. New emerging communication structures often do not fit the developed plans, which stress the need for coordination by feedback in addition to by plan. In addition, we find that the participant's brokering role in the response operation network identifies a formal and informal coordination role. This is useful for comparison of network structures to examine whether what really happens during response operations complies with the initial policy.

The 2014-2015 warming anomaly in the Southern California Current System observed by underwater gliders

NASA Astrophysics Data System (ADS)

Zaba, Katherine D.; Rudnick, Daniel L.

2016-02-01

Large-scale patterns of positive temperature anomalies persisted throughout the surface waters of the North Pacific Ocean during 2014-2015. In the Southern California Current System, measurements by our sustained network of underwater gliders reveal the coastal effects of the recent warming. Regional upper ocean temperature anomalies were greatest since the initiation of the glider network in 2006. Additional observed physical anomalies included a depressed thermocline, high stratification, and freshening; induced biological consequences included changes in the vertical distribution of chlorophyll fluorescence. Contemporaneous surface heat flux and wind strength perturbations suggest that local anomalous atmospheric forcing caused the unusual oceanic conditions.
Critical tipping point distinguishing two types of transitions in modular network structures

NASA Astrophysics Data System (ADS)

Shai, Saray; Kenett, Dror Y.; Kenett, Yoed N.; Faust, Miriam; Dobson, Simon; Havlin, Shlomo

2015-12-01

Modularity is a key organizing principle in real-world large-scale complex networks. The relatively sparse interactions between modules are critical to the functionality of the system and are often the first to fail. We model such failures as site percolation targeting interconnected nodes, those connecting between modules. We find, using percolation theory and simulations, that they lead to a "tipping point" between two distinct regimes. In one regime, removal of interconnected nodes fragments the modules internally and causes the system to collapse. In contrast, in the other regime, while only attacking a small fraction of nodes, the modules remain but become disconnected, breaking the entire system. We show that networks with broader degree distribution might be highly vulnerable to such attacks since only few nodes are needed to interconnect the modules, consequently putting the entire system at high risk. Our model has the potential to shed light on many real-world phenomena, and we briefly consider its implications on recent advances in the understanding of several neurocognitive processes and diseases.
Network structure and functional properties of transparent hydrogel sanxan produced by Sphingomonas sanxanigenens NX02.

PubMed

Wu, Mengmeng; Shi, Zhong; Huang, Haidong; Qu, Jianmei; Dai, Xiaohui; Tian, Xuefeng; Wei, Weiying; Li, Guoqiang; Ma, Ting

2017-11-15

The micro-network structure and functional properties of sanxan, a novel polysaccharide produced by Sphingomonas sanxanigenens NX02, were investigated. Transparent hydrogel sanxan was a high acyl polymer containing 8.96% acetyl and 4.75% glyceroyl. The micro-network structure of sanxan was mainly cyclic configurations composed of side-by-side intermolecular associations, with many rounded nodes found. Sanxan exhibited predominant gelation behavior at concentrations above 0.1%, which was enhanced by adding cations, especially Ca 2+ . The gel strength of sanxan was much higher than that of low acyl gellan, but slightly lower than that of high acyl gellan. Furthermore, the conformation transition temperature was increased in the presence of added cations. Moreover, sanxan showed excellent emulsifying and emulsion stabilizing properties. Consequently, such excellent functional properties make sanxan a good candidate as a gelling, stabilizing, emulsifying, or suspending agent in food and cosmetics industries, and in medical and pharmaceutical usage. Copyright © 2017 Elsevier Ltd. All rights reserved.
Networks and Collaboration in Spanish Education Policy

ERIC Educational Resources Information Center

Azorín, Cecilia M.; Muijs, Daniel

2017-01-01

Background: Networks play an important role in today's societies. As a consequence, changes are apparent in the political, economic, cultural, educational and social agendas. Purpose: The main goal of this article is to map the situation of school networks in Spain. The research questions are focused on what forms collaboration and networking take…
Photon-trapping micro/nanostructures for high linearity in ultra-fast photodiodes

NASA Astrophysics Data System (ADS)

Cansizoglu, Hilal; Gao, Yang; Perez, Cesar Bartolo; Ghandiparsi, Soroush; Ponizovskaya Devine, Ekaterina; Cansizoglu, Mehmet F.; Yamada, Toshishige; Elrefaie, Aly F.; Wang, Shih-Yuan; Islam, M. Saif

2017-08-01

Photodetectors (PDs) in datacom and computer networks where the link length is up to 300 m, need to handle higher than typical input power used in other communication links. Also, to reduce power consumption due to equalization at high speed (>25Gb/s), the datacom links will use PAM-4 signaling instead of NRZ with stringent receiver linearity requirements. Si PDs with photon-trapping micro/nanostructures are shown to have high linearity in output current verses input optical power. Though there is less silicon material due to the holes, the micro-/nanostructured holes collectively reradiate the light to an in-plane direction of the PD surface and can avoid current crowding in the PD. Consequently, the photocurrent per unit volume remains at a low level contributing to high linearity in the photocurrent. We present the effect of design and lattice patterns of micro/nanostructures on the linearity of ultra-fast silicon PDs designed for high speed multi gigabit data networks.
Negative consequences from heavy social networking in adolescents: The mediating role of fear of missing out.

PubMed

Oberst, Ursula; Wegmann, Elisa; Stodt, Benjamin; Brand, Matthias; Chamarro, Andrés

2017-02-01

Social networking sites (SNS) are especially attractive for adolescents, but it has also been shown that these users can suffer from negative psychological consequences when using these sites excessively. We analyze the role of fear of missing out (FOMO) and intensity of SNS use for explaining the link between psychopathological symptoms and negative consequences of SNS use via mobile devices. In an online survey, 1468 Spanish-speaking Latin-American social media users between 16 and 18 years old completed the Hospital Anxiety and Depression Scale (HADS), the Social Networking Intensity scale (SNI), the FOMO scale (FOMOs), and a questionnaire on negative consequences of using SNS via mobile device (CERM). Using structural equation modeling, it was found that both FOMO and SNI mediate the link between psychopathology and CERM, but by different mechanisms. Additionally, for girls, feeling depressed seems to trigger higher SNS involvement. For boys, anxiety triggers higher SNS involvement. Copyright © 2016 The Foundation for Professionals in Services for Adolescents. Published by Elsevier Ltd. All rights reserved.
Slow, bursty dynamics as a consequence of quenched network topologies

NASA Astrophysics Data System (ADS)

Ådor, Géza

2014-04-01

Bursty dynamics of agents is shown to appear at criticality or in extended Griffiths phases, even in case of Poisson processes. I provide numerical evidence for a power-law type of intercommunication time distributions by simulating the contact process and the susceptible-infected-susceptible model. This observation suggests that in the case of nonstationary bursty systems, the observed non-Poissonian behavior can emerge as a consequence of an underlying hidden Poissonian network process, which is either critical or exhibits strong rare-region effects. On the contrary, in time-varying networks, rare-region effects do not cause deviation from the mean-field behavior, and heterogeneity-induced burstyness is absent.
Slow, bursty dynamics as a consequence of quenched network topologies.

PubMed

Ódor, Géza

2014-04-01

Bursty dynamics of agents is shown to appear at criticality or in extended Griffiths phases, even in case of Poisson processes. I provide numerical evidence for a power-law type of intercommunication time distributions by simulating the contact process and the susceptible-infected-susceptible model. This observation suggests that in the case of nonstationary bursty systems, the observed non-Poissonian behavior can emerge as a consequence of an underlying hidden Poissonian network process, which is either critical or exhibits strong rare-region effects. On the contrary, in time-varying networks, rare-region effects do not cause deviation from the mean-field behavior, and heterogeneity-induced burstyness is absent.
How Network Properties Affect One's Ability to Obtain Benefits: A Network Simulation

ERIC Educational Resources Information Center

Trefalt, Špela

2014-01-01

Networks and the social capital that they carry enable people to get things done, to prosper in their careers, and to feel supported. To develop an effective network, one needs to know more than how to make connections with strangers at a reception; understanding the consequences of network properties on one's ability to obtain benefits is…
A Network Analysis Perspective to Implementation: The Example of Health Links to Promote Coordinated Care.

PubMed

Yousefi Nooraie, Reza; Khan, Sobia; Gutberg, Jennifer; Baker, G Ross

2018-01-01

Although implementation models broadly recognize the importance of social relationships, our knowledge about applying social network analysis (SNA) to formative, process, and outcome evaluations of health system interventions is limited. We explored applications of adopting an SNA lens to inform implementation planning, engagement and execution, and evaluation. We used Health Links, a province-wide program in Canada aiming to improve care coordination among multiple providers of high-needs patients, as an example of a health system intervention. At the planning phase, an SNA can depict the structure, network influencers, and composition of clusters at various levels. It can inform the engagement and execution by identifying potential targets (e.g., opinion leaders) and by revealing structural gaps and clusters. It can also be used to assess the outcomes of the intervention, such as its success in increasing network connectivity; changing the position of certain actors; and bridging across specialties, organizations, and sectors. We provided an overview of how an SNA lens can shed light on the complexity of implementation along the entire implementation pathway, by revealing the relational barriers and facilitators, the application of network-informed and network-altering interventions, and testing hypotheses on network consequences of the implementation.
Control of epidemics on complex networks: Effectiveness of delayed isolation

NASA Astrophysics Data System (ADS)

Pereira, Tiago; Young, Lai-Sang

2015-08-01

We study isolation as a means to control epidemic outbreaks in complex networks, focusing on the consequences of delays in isolating infected nodes. Our analysis uncovers a tipping point: if infected nodes are isolated before a critical day dc, the disease is effectively controlled, whereas for longer delays the number of infected nodes climbs steeply. We show that dc can be estimated explicitly in terms of network properties and disease parameters, connecting lowered values of dc explicitly to heterogeneity in degree distribution. Our results reveal also that initial delays in the implementation of isolation protocols can have catastrophic consequences in heterogeneous networks. As our study is carried out in a general framework, it has the potential to offer insight and suggest proactive strategies for containing outbreaks of a range of serious infectious diseases.
Enhancing response coordination through the assessment of response network structural dynamics

PubMed Central

Jalili, Mahdi; Choi, Soo-Mi

2018-01-01

Preparing for intensifying threats of emergencies in unexpected, dangerous, and serious natural or man-made events, and consequent management of the situation, is highly demanding in terms of coordinating the personnel and resources to support human lives and the environment. This necessitates prompt action to manage the uncertainties and risks imposed by such extreme events, which requires collaborative operation among different stakeholders (i.e., the personnel from both the state and local communities). This research aims to find a way to enhance the coordination of multi-organizational response operations. To do so, this manuscript investigates the role of participants in the formed coordination response network and also the emergence and temporal dynamics of the network. By analyzing an inter-personal response coordination operation to an extreme bushfire event, the networks’ and participants’ structural change is evaluated during the evolution of the operation network over four time durations. The results reveal that the coordination response network becomes more decentralized over time due to the high volume of communication required to exchange information. New emerging communication structures often do not fit the developed plans, which stress the need for coordination by feedback in addition to by plan. In addition, we find that the participant’s brokering role in the response operation network identifies a formal and informal coordination role. This is useful for comparison of network structures to examine whether what really happens during response operations complies with the initial policy. PMID:29447192
Recovery plan for laurel wilt on redbay and other forest species caused by Raffaelea lauricola and disseminated by Xyleborus glabratus

Treesearch

M. A. Hughes; J.A. Smith; R. C. Ploetz; P. E. Kendra; Albert (Bud) Mayfield; James Hanula; J. Hulcr; L.L. Stelinski; S. Cameron; J. J. Riggins; D. Carrillo; R. Rabaglia; J. Eickwort

2015-01-01

This recovery plan is one of several disease-specific documents produced as part of the National Plant Disease Recovery System (NPDRS) called for in Homeland Security Presidential Directive Number 9 (HSPD-9). The purpose of the NPDRS is to insure that the tools, infrastructure, communication networks, and capacity required to mitigate the impact of high-consequence...
Self-Learning Power Control in Wireless Sensor Networks.

PubMed

Chincoli, Michele; Liotta, Antonio

2018-01-27

Current trends in interconnecting myriad smart objects to monetize on Internet of Things applications have led to high-density communications in wireless sensor networks. This aggravates the already over-congested unlicensed radio bands, calling for new mechanisms to improve spectrum management and energy efficiency, such as transmission power control. Existing protocols are based on simplistic heuristics that often approach interference problems (i.e., packet loss, delay and energy waste) by increasing power, leading to detrimental results. The scope of this work is to investigate how machine learning may be used to bring wireless nodes to the lowest possible transmission power level and, in turn, to respect the quality requirements of the overall network. Lowering transmission power has benefits in terms of both energy consumption and interference. We propose a protocol of transmission power control through a reinforcement learning process that we have set in a multi-agent system. The agents are independent learners using the same exploration strategy and reward structure, leading to an overall cooperative network. The simulation results show that the system converges to an equilibrium where each node transmits at the minimum power while respecting high packet reception ratio constraints. Consequently, the system benefits from low energy consumption and packet delay.
Self-Learning Power Control in Wireless Sensor Networks

PubMed Central

Liotta, Antonio

2018-01-01

Current trends in interconnecting myriad smart objects to monetize on Internet of Things applications have led to high-density communications in wireless sensor networks. This aggravates the already over-congested unlicensed radio bands, calling for new mechanisms to improve spectrum management and energy efficiency, such as transmission power control. Existing protocols are based on simplistic heuristics that often approach interference problems (i.e., packet loss, delay and energy waste) by increasing power, leading to detrimental results. The scope of this work is to investigate how machine learning may be used to bring wireless nodes to the lowest possible transmission power level and, in turn, to respect the quality requirements of the overall network. Lowering transmission power has benefits in terms of both energy consumption and interference. We propose a protocol of transmission power control through a reinforcement learning process that we have set in a multi-agent system. The agents are independent learners using the same exploration strategy and reward structure, leading to an overall cooperative network. The simulation results show that the system converges to an equilibrium where each node transmits at the minimum power while respecting high packet reception ratio constraints. Consequently, the system benefits from low energy consumption and packet delay. PMID:29382072
How Travel Demand Affects Detection of Non-Recurrent Traffic Congestion on Urban Road Networks

NASA Astrophysics Data System (ADS)

Anbaroglu, B.; Heydecker, B.; Cheng, T.

2016-06-01

Occurrence of non-recurrent traffic congestion hinders the economic activity of a city, as travellers could miss appointments or be late for work or important meetings. Similarly, for shippers, unexpected delays may disrupt just-in-time delivery and manufacturing processes, which could lose them payment. Consequently, research on non-recurrent congestion detection on urban road networks has recently gained attention. By analysing large amounts of traffic data collected on a daily basis, traffic operation centres can improve their methods to detect non-recurrent congestion rapidly and then revise their existing plans to mitigate its effects. Space-time clusters of high link journey time estimates correspond to non-recurrent congestion events. Existing research, however, has not considered the effect of travel demand on the effectiveness of non-recurrent congestion detection methods. Therefore, this paper investigates how travel demand affects detection of non-recurrent traffic congestion detection on urban road networks. Travel demand has been classified into three categories as low, normal and high. The experiments are carried out on London's urban road network, and the results demonstrate the necessity to adjust the relative importance of the component evaluation criteria depending on the travel demand level.
Persistence of social signatures in human communication.

PubMed

Saramäki, Jari; Leicht, E A; López, Eduardo; Roberts, Sam G B; Reed-Tsochas, Felix; Dunbar, Robin I M

2014-01-21

The social network maintained by a focal individual, or ego, is intrinsically dynamic and typically exhibits some turnover in membership over time as personal circumstances change. However, the consequences of such changes on the distribution of an ego's network ties are not well understood. Here we use a unique 18-mo dataset that combines mobile phone calls and survey data to track changes in the ego networks and communication patterns of students making the transition from school to university or work. Our analysis reveals that individuals display a distinctive and robust social signature, captured by how interactions are distributed across different alters. Notably, for a given ego, these social signatures tend to persist over time, despite considerable turnover in the identity of alters in the ego network. Thus, as new network members are added, some old network members either are replaced or receive fewer calls, preserving the overall distribution of calls across network members. This is likely to reflect the consequences of finite resources such as the time available for communication, the cognitive and emotional effort required to sustain close relationships, and the ability to make emotional investments.
Persistence of social signatures in human communication

PubMed Central

Saramäki, Jari; Leicht, E. A.; López, Eduardo; Roberts, Sam G. B.; Reed-Tsochas, Felix; Dunbar, Robin I. M.

2014-01-01

The social network maintained by a focal individual, or ego, is intrinsically dynamic and typically exhibits some turnover in membership over time as personal circumstances change. However, the consequences of such changes on the distribution of an ego’s network ties are not well understood. Here we use a unique 18-mo dataset that combines mobile phone calls and survey data to track changes in the ego networks and communication patterns of students making the transition from school to university or work. Our analysis reveals that individuals display a distinctive and robust social signature, captured by how interactions are distributed across different alters. Notably, for a given ego, these social signatures tend to persist over time, despite considerable turnover in the identity of alters in the ego network. Thus, as new network members are added, some old network members either are replaced or receive fewer calls, preserving the overall distribution of calls across network members. This is likely to reflect the consequences of finite resources such as the time available for communication, the cognitive and emotional effort required to sustain close relationships, and the ability to make emotional investments. PMID:24395777
The enhancement of security in healthcare information systems.

PubMed

Liu, Chia-Hui; Chung, Yu-Fang; Chen, Tzer-Shyong; Wang, Sheng-De

2012-06-01

With the progress and the development of information technology, the internal data in medical organizations have become computerized and are further established the medical information system. Moreover, the use of the Internet enhances the information communication as well as affects the development of the medical information system that a lot of medical information is transmitted with the Internet. Since there is a network within another network, when all networks are connected together, they will form the "Internet". For this reason, the Internet is considered as a high-risk and public environment which is easily destroyed and invaded so that a relevant protection is acquired. Besides, the data in the medical network system are confidential that it is necessary to protect the personal privacy, such as electronic patient records, medical confidential information, and authorization-controlled data in the hospital. As a consequence, a medical network system is considered as a network requiring high security that excellent protections and managerial strategies are inevitable to prevent illegal events and external attacks from happening. This study proposes secure medical managerial strategies being applied to the network environment of the medical organization information system so as to avoid the external or internal information security events, allow the medical system to work smoothly and safely that not only benefits the patients, but also allows the doctors to use it more conveniently, and further promote the overall medical quality. The objectives could be achieved by preventing from illegal invasion or medical information being stolen, protecting the completeness and security of medical information, avoiding the managerial mistakes of the internal information system in medical organizations, and providing the highly-reliable medical information system.
Bismaleimide and cyanate ester based sequential interpenetrating polymer networks for high temperature application

NASA Astrophysics Data System (ADS)

Geng, Xing

2005-07-01

A research area of high activity in connection with aerospace engineering has been the development of polymer thermosetting resins that can withstand temperature as high as 300°C while maintaining adequate toughness and providing ease of processing to enable low temperature and low cost composite fabrication methods. In order to meet such requirements, sequential interpenetrating polymer networks (IPNs) based on bismaleimide (BMI) and cyanate ester (CE) monomers were investigated. In these systems, a polycyanurate network is first formed in the presence of BMI and appropriate reactive diluent monomers and, in a second step, a network based on the BMI is created in the presence of a fully formed polycyanurate network. The materials developed can be processed at relatively low temperature (<150°C) and with the aid of electron beam (EB) curing. Of major importance to the success of this work was the identification of a reactive diluent that improves ease of processing and has tailored reactivity to allow for the controlled synthesis of CE-BMI sequential IPNs. Based on solubility and reactivity of a number of reactive diluents, N-acryloylmorpholine (AMP) was selected as a co-monomer for BMI copolymerization. A donor-acceptor reaction mechanism was suggested to explain the relative reactivity of a variety of reactive diluents towards maleimide functionality. The optimum processing parameters for the formation of the first network were determined through the study of metal catalyzed cure and hydrolysis of cyanate esters, whereas the reaction behavior for second network formation in terms of the influence of EB dose rate and temperature was elucidated through an in-situ kinetics study of maleimide and AMP copolymerization. Structure-property relationships were developed which allowed for the design of improved resin systems. In particular, an appropriate network coupler possessing cyanate ester and maleimide functionality was synthesized to link the polycyanurate first network to the BMI/AMP second network and thus form linked sequential IPNs (LIPNs). Consequently, Tg as high as 370°C was achieved and a fracture toughness of 120 J/m2 was obtained for resin systems that possess adequately low viscosity for processing using liquid molding techniques at low temperature.

Optimal Scheduling for Underwater Communications in Multiple-user Scenarios

DTIC Science & Technology

2014-09-30

underwater acoustic sensor networks . These techniques aim at consuming as less energy as... underwater acoustic networks disrupt the behavior of surrounding species of marine mammals. As a consequence of these two studies, we aim at developing...Markov models of incremental redundancy hybrid ARQ over underwater acoustic channels. Elsevier Journal on Ad-hoc Networks (Special Issue on Underwater Communications and Networks ), 2014. 4
Design of optimal nonlinear network controllers for Alzheimer's disease.

PubMed

Sanchez-Rodriguez, Lazaro M; Iturria-Medina, Yasser; Baines, Erica A; Mallo, Sabela C; Dousty, Mehdy; Sotero, Roberto C

2018-05-01

Brain stimulation can modulate the activity of neural circuits impaired by Alzheimer's disease (AD), having promising clinical benefit. However, all individuals with the same condition currently receive identical brain stimulation, with limited theoretical basis for this generic approach. In this study, we introduce a control theory framework for obtaining exogenous signals that revert pathological electroencephalographic activity in AD at a minimal energetic cost, while reflecting patients' biological variability. We used anatomical networks obtained from diffusion magnetic resonance images acquired by the Alzheimer's Disease Neuroimaging Initiative (ADNI) as mediators for the interaction between Duffing oscillators. The nonlinear nature of the brain dynamics is preserved, given that we extend the so-called state-dependent Riccati equation control to reflect the stimulation objective in the high-dimensional neural system. By considering nonlinearities in our model, we identified regions for which control inputs fail to correct abnormal activity. There are changes to the way stimulated regions are ranked in terms of the energetic cost of controlling the entire network, from a linear to a nonlinear approach. We also found that limbic system and basal ganglia structures constitute the top target locations for stimulation in AD. Patients with highly integrated anatomical networks-namely, networks having low average shortest path length, high global efficiency-are the most suitable candidates for the propagation of stimuli and consequent success on the control task. Other diseases associated with alterations in brain dynamics and the self-control mechanisms of the brain can be addressed through our framework.
Influence of Network Model Detail on Estimated Health Effects of Drinking Water Contamination Events

DOE Office of Scientific and Technical Information (OSTI.GOV)

Davis, Michael J.; Janke, Robert

Network model detail can influence the accuracy of results from analyses of water distribution systems. Some previous work has shown the limitations of skeletonized network models when considering water quality and hydraulic effects. Loss of model detail is potentially less important for aggregated effects such as the systemwide health effects associated with a contamination event, but has received limited attention. The influence of model detail on such effects is examined here by comparing results obtained for contamination events using three large network models and several skeletonized versions of the models. Loss of model detail decreases the accuracy of estimated aggregatedmore » adverse effects related to contamination events. It has the potential to have a large negative influence on the results of consequence assessments and the design of contamination warning systems. But, the adverse influence on analysis results can be minimized by restricting attention to high percentile effects (i.e., 95th percentile or higher).« less
Influence of Network Model Detail on Estimated Health Effects of Drinking Water Contamination Events

DOE Office of Scientific and Technical Information (OSTI.GOV)

Davis, Michael J.; Janke, Robert

Network model detail can influence the accuracy of results from analyses of water distribution systems. Previous work has shown the limitations of skeletonized network models when considering water quality and hydraulic effects. Loss of model detail is potentially less important for aggregated effects such as the systemwide health effects associated with a contamination event, but has received limited attention. The influence of model detail on such effects is examined here by comparing results obtained for contamination events using three large network models and several skeletonized versions of the models. Loss of model detail decreases the accuracy of estimated aggregated adversemore » effects related to contamination events. It has the potential to have a large negative influence on the results of consequence assessments and the design of contamination warning systems. However, the adverse influence on analysis results can be minimized by restricting attention to high percentile effects (i.e., 95th percentile or higher).« less
Synchronous neural networks of nonlinear threshold elements with hysteresis.

PubMed

Wang, L; Ross, J

1990-02-01

We use Hoffmann's suggestion [Hoffmann, G. W. (1986) J. Theor. Biol. 122, 33-67] of hysteresis in a single neuron level and determine its consequences in a synchronous network made of such neurons. We show that the overall retrieval ability in the presence of noise and the memory capacity of the network in the present model are better than in conventional models without such hysteresis. Second-order interaction further improves the retrieval ability of the network and causes hysteresis in the retrieval-noise curve for any arbitrary width of the bistable region. The convergence rate is increased by the hysteresis at high noise levels but is reduced by the hysteresis at low noise levels. Explicit formulae are given for calculations of average final convergence and noise threshold as functions of the width of the bistable region. There is neurophysiological evidence for hysteresis in single neurons, and we propose optical implementations of the present model by using ZnSe interference filters to test the predictions of the theory.
Influence of Network Model Detail on Estimated Health Effects of Drinking Water Contamination Events

DOE PAGES

Davis, Michael J.; Janke, Robert

2015-01-01

Network model detail can influence the accuracy of results from analyses of water distribution systems. Some previous work has shown the limitations of skeletonized network models when considering water quality and hydraulic effects. Loss of model detail is potentially less important for aggregated effects such as the systemwide health effects associated with a contamination event, but has received limited attention. The influence of model detail on such effects is examined here by comparing results obtained for contamination events using three large network models and several skeletonized versions of the models. Loss of model detail decreases the accuracy of estimated aggregatedmore » adverse effects related to contamination events. It has the potential to have a large negative influence on the results of consequence assessments and the design of contamination warning systems. But, the adverse influence on analysis results can be minimized by restricting attention to high percentile effects (i.e., 95th percentile or higher).« less
Avian influenza H5N1 viral and bird migration networks in Asia

USGS Publications Warehouse

Tian, Huaivu; Zhou, Sen; Dong, Lu; Van Boeckel, Thomas P.; Cui, Yujun; Newman, Scott H.; Takekawa, John Y.; Prosser, Diann J.; Xiao, Xiangming; Wu, Yarong; Cazelles, Bernard; Huang, Shanqian; Yang, Ruifu; Grenfell, Bryan T.; Xu, Bing

2015-01-01

The spatial spread of the highly pathogenic avian influenza virus H5N1 and its long-term persistence in Asia have resulted in avian influenza panzootics and enormous economic losses in the poultry sector. However, an understanding of the regional long-distance transmission and seasonal patterns of the virus is still lacking. In this study, we present a phylogeographic approach to reconstruct the viral migration network. We show that within each wild fowl migratory flyway, the timing of H5N1 outbreaks and viral migrations are closely associated, but little viral transmission was observed between the flyways. The bird migration network is shown to better reflect the observed viral gene sequence data than other networks and contributes to seasonal H5N1 epidemics in local regions and its large-scale transmission along flyways. These findings have potentially far-reaching consequences, improving our understanding of how bird migration drives the periodic reemergence of H5N1 in Asia.
Avian influenza H5N1 viral and bird migration networks in Asia

PubMed Central

Tian, Huaiyu; Zhou, Sen; Dong, Lu; Van Boeckel, Thomas P.; Cui, Yujun; Newman, Scott H.; Takekawa, John Y.; Prosser, Diann J.; Xiao, Xiangming; Wu, Yarong; Cazelles, Bernard; Huang, Shanqian; Yang, Ruifu; Grenfell, Bryan T.; Xu, Bing

2015-01-01

The spatial spread of the highly pathogenic avian influenza virus H5N1 and its long-term persistence in Asia have resulted in avian influenza panzootics and enormous economic losses in the poultry sector. However, an understanding of the regional long-distance transmission and seasonal patterns of the virus is still lacking. In this study, we present a phylogeographic approach to reconstruct the viral migration network. We show that within each wild fowl migratory flyway, the timing of H5N1 outbreaks and viral migrations are closely associated, but little viral transmission was observed between the flyways. The bird migration network is shown to better reflect the observed viral gene sequence data than other networks and contributes to seasonal H5N1 epidemics in local regions and its large-scale transmission along flyways. These findings have potentially far-reaching consequences, improving our understanding of how bird migration drives the periodic reemergence of H5N1 in Asia. PMID:25535385
Design of nodes for embedded and ultra low-power wireless sensor networks

NASA Astrophysics Data System (ADS)

Xu, Jun; You, Bo; Cui, Juan; Ma, Jing; Li, Xin

2008-10-01

Sensor network integrates sensor technology, MEMS (Micro-Electro-Mechanical system) technology, embedded computing, wireless communication technology and distributed information management technology. It is of great value to use it where human is quite difficult to reach. Power consumption and size are the most important consideration when nodes are designed for distributed WSN (wireless sensor networks). Consequently, it is of great importance to decrease the size of a node, reduce its power consumption and extend its life in network. WSN nodes have been designed using JN5121-Z01-M01 module produced by jennic company and IEEE 802.15.4/ZigBee technology. Its new features include support for CPU sleep modes and a long-term ultra low power sleep mode for the entire node. In low power configuration the node resembles existing small low power nodes. An embedded temperature sensor node has been developed to verify and explore our architecture. The experiment results indicate that the WSN has the characteristic of high reliability, good stability and ultra low power consumption.
Efficient implementation of neural network deinterlacing

NASA Astrophysics Data System (ADS)

Seo, Guiwon; Choi, Hyunsoo; Lee, Chulhee

2009-02-01

Interlaced scanning has been widely used in most broadcasting systems. However, there are some undesirable artifacts such as jagged patterns, flickering, and line twitters. Moreover, most recent TV monitors utilize flat panel display technologies such as LCD or PDP monitors and these monitors require progressive formats. Consequently, the conversion of interlaced video into progressive video is required in many applications and a number of deinterlacing methods have been proposed. Recently deinterlacing methods based on neural network have been proposed with good results. On the other hand, with high resolution video contents such as HDTV, the amount of video data to be processed is very large. As a result, the processing time and hardware complexity become an important issue. In this paper, we propose an efficient implementation of neural network deinterlacing using polynomial approximation of the sigmoid function. Experimental results show that these approximations provide equivalent performance with a considerable reduction of complexity. This implementation of neural network deinterlacing can be efficiently incorporated in HW implementation.
Who gets evicted? Assessing individual, neighborhood, and network factors.

PubMed

Desmond, Matthew; Gershenson, Carl

2017-02-01

The prevalence and consequences of eviction have transformed the lived experience of urban poverty in America, yet little is known about why some families avoid eviction while others do not. Applying discrete hazard models to a unique dataset of renters, this study empirically evaluates individual, neighborhood, and social network characteristics that explain disparities in displacement from housing. Family size, job loss, neighborhood crime and eviction rates, and network disadvantage are identified as significant and robust predictors of eviction, net of missed rental payments and other relevant factors. This study advances urban sociology and inequality research and informs policy interventions designed to prevent eviction and stem its consequences. Copyright © 2016 Elsevier Inc. All rights reserved.
Comparison study on qualitative and quantitative risk assessment methods for urban natural gas pipeline network.

PubMed

Han, Z Y; Weng, W G

2011-05-15

In this paper, a qualitative and a quantitative risk assessment methods for urban natural gas pipeline network are proposed. The qualitative method is comprised of an index system, which includes a causation index, an inherent risk index, a consequence index and their corresponding weights. The quantitative method consists of a probability assessment, a consequences analysis and a risk evaluation. The outcome of the qualitative method is a qualitative risk value, and for quantitative method the outcomes are individual risk and social risk. In comparison with previous research, the qualitative method proposed in this paper is particularly suitable for urban natural gas pipeline network, and the quantitative method takes different consequences of accidents into consideration, such as toxic gas diffusion, jet flame, fire ball combustion and UVCE. Two sample urban natural gas pipeline networks are used to demonstrate these two methods. It is indicated that both of the two methods can be applied to practical application, and the choice of the methods depends on the actual basic data of the gas pipelines and the precision requirements of risk assessment. Crown Copyright © 2011. Published by Elsevier B.V. All rights reserved.
Popularity versus similarity in growing networks.

PubMed

Papadopoulos, Fragkiskos; Kitsak, Maksim; Serrano, M Ángeles; Boguñá, Marián; Krioukov, Dmitri

2012-09-27

The principle that 'popularity is attractive' underlies preferential attachment, which is a common explanation for the emergence of scaling in growing networks. If new connections are made preferentially to more popular nodes, then the resulting distribution of the number of connections possessed by nodes follows power laws, as observed in many real networks. Preferential attachment has been directly validated for some real networks (including the Internet), and can be a consequence of different underlying processes based on node fitness, ranking, optimization, random walks or duplication. Here we show that popularity is just one dimension of attractiveness; another dimension is similarity. We develop a framework in which new connections optimize certain trade-offs between popularity and similarity, instead of simply preferring popular nodes. The framework has a geometric interpretation in which popularity preference emerges from local optimization. As opposed to preferential attachment, our optimization framework accurately describes the large-scale evolution of technological (the Internet), social (trust relationships between people) and biological (Escherichia coli metabolic) networks, predicting the probability of new links with high precision. The framework that we have developed can thus be used for predicting new links in evolving networks, and provides a different perspective on preferential attachment as an emergent phenomenon.
Using networks to detect regime changes in aquatic communities across nutrient gradients

NASA Astrophysics Data System (ADS)

Taranu, Z. E.

2015-12-01

Networks capture links or interactions between organisms within ecological webs. When an environmental stress occurs, rapid changes in ecosystem state are expected in food webs with highly connected networks and functionally redundant species. These networks can dissipate local disturbances quickly and provide resistance to change at first until a threshold is reached, at which point, a critical transition occurs (nodes shift in synchrony). In contrast, in low connectivity (modular) heterogeneous networks, the response in ecosystem state to an environmental stressor is gradual. Given that these ecosystem-level shifts can be difficult to predict, hard to reverse and can have undesirable consequences, there is considerable interest in identifying what type of response (gradual vs. hysteresis) is most likely in nature. In this work, we thus aimed to test for the support for a bifurcated response in aquatic ecosystem across a landscape of human impact and track which of the above scenarios was most common. More specifically, using the US EPA National Lake Assessment water quality dataset (2007 sampling), we quantified differences in food-web structures across a spatial gradient of human impact (eutrophication). Preliminary results indicate that certain network properties vary nonlinearly with respect to nutrient enrichment.
Quantitative analysis of factors that affect oil pipeline network accident based on Bayesian networks: A case study in China

NASA Astrophysics Data System (ADS)

Zhang, Chao; Qin, Ting Xin; Huang, Shuai; Wu, Jian Song; Meng, Xin Yan

2018-06-01

Some factors can affect the consequences of oil pipeline accident and their effects should be analyzed to improve emergency preparation and emergency response. Although there are some qualitative analysis models of risk factors' effects, the quantitative analysis model still should be researched. In this study, we introduce a Bayesian network (BN) model of risk factors' effects analysis in an oil pipeline accident case that happened in China. The incident evolution diagram is built to identify the risk factors. And the BN model is built based on the deployment rule for factor nodes in BN and the expert knowledge by Dempster-Shafer evidence theory. Then the probabilities of incident consequences and risk factors' effects can be calculated. The most likely consequences given by this model are consilient with the case. Meanwhile, the quantitative estimations of risk factors' effects may provide a theoretical basis to take optimal risk treatment measures for oil pipeline management, which can be used in emergency preparation and emergency response.
Aggregated channels network for real-time pedestrian detection

NASA Astrophysics Data System (ADS)

Ghorban, Farzin; Marín, Javier; Su, Yu; Colombo, Alessandro; Kummert, Anton

2018-04-01

Convolutional neural networks (CNNs) have demonstrated their superiority in numerous computer vision tasks, yet their computational cost results prohibitive for many real-time applications such as pedestrian detection which is usually performed on low-consumption hardware. In order to alleviate this drawback, most strategies focus on using a two-stage cascade approach. Essentially, in the first stage a fast method generates a significant but reduced amount of high quality proposals that later, in the second stage, are evaluated by the CNN. In this work, we propose a novel detection pipeline that further benefits from the two-stage cascade strategy. More concretely, the enriched and subsequently compressed features used in the first stage are reused as the CNN input. As a consequence, a simpler network architecture, adapted for such small input sizes, allows to achieve real-time performance and obtain results close to the state-of-the-art while running significantly faster without the use of GPU. In particular, considering that the proposed pipeline runs in frame rate, the achieved performance is highly competitive. We furthermore demonstrate that the proposed pipeline on itself can serve as an effective proposal generator.
A Novel Experimental and Analytical Approach to the Multimodal Neural Decoding of Intent During Social Interaction in Freely-behaving Human Infants.

PubMed

Cruz-Garza, Jesus G; Hernandez, Zachery R; Tse, Teresa; Caducoy, Eunice; Abibullaev, Berdakh; Contreras-Vidal, Jose L

2015-10-04

Understanding typical and atypical development remains one of the fundamental questions in developmental human neuroscience. Traditionally, experimental paradigms and analysis tools have been limited to constrained laboratory tasks and contexts due to technical limitations imposed by the available set of measuring and analysis techniques and the age of the subjects. These limitations severely limit the study of developmental neural dynamics and associated neural networks engaged in cognition, perception and action in infants performing "in action and in context". This protocol presents a novel approach to study infants and young children as they freely organize their own behavior, and its consequences in a complex, partly unpredictable and highly dynamic environment. The proposed methodology integrates synchronized high-density active scalp electroencephalography (EEG), inertial measurement units (IMUs), video recording and behavioral analysis to capture brain activity and movement non-invasively in freely-behaving infants. This setup allows for the study of neural network dynamics in the developing brain, in action and context, as these networks are recruited during goal-oriented, exploration and social interaction tasks.
Lag threads organize the brain’s intrinsic activity

PubMed Central

Mitra, Anish; Snyder, Abraham Z.; Blazey, Tyler; Raichle, Marcus E.

2015-01-01

It has been widely reported that intrinsic brain activity, in a variety of animals including humans, is spatiotemporally structured. Specifically, propagated slow activity has been repeatedly demonstrated in animals. In human resting-state fMRI, spontaneous activity has been understood predominantly in terms of zero-lag temporal synchrony within widely distributed functional systems (resting-state networks). Here, we use resting-state fMRI from 1,376 normal, young adults to demonstrate that multiple, highly reproducible, temporal sequences of propagated activity, which we term “lag threads,” are present in the brain. Moreover, this propagated activity is largely unidirectional within conventionally understood resting-state networks. Modeling experiments show that resting-state networks naturally emerge as a consequence of shared patterns of propagation. An implication of these results is that common physiologic mechanisms may underlie spontaneous activity as imaged with fMRI in humans and slowly propagated activity as studied in animals. PMID:25825720
Persistent Social Networks: Civil War Veterans Who Fought Together Co-Locate in Later Life.

PubMed

Costa, Dora L; Kahn, Matthew E; Roudiez, Christopher; Wilson, Sven

2018-05-01

We demonstrate the long reach of early social ties in the location decision of individuals and in their older age mortality risk using data on Union Army veterans of the US Civil War (1861-5). We estimate discrete choice migration models to quantify the trade-offs across locations faced by veterans. Veterans were more likely to move to a neighborhood or county where men from their same war company lived and were more likely to move to such areas than to areas where other veterans were located. Veterans also were less likely to move far from their origin and avoided urban immigrant areas and high mortality risk areas. They also avoided areas that opposed the Civil War. This co-location evidence highlights the existence of persistent social networks. Such social networks had long-term consequences: veterans living close to war-time comrades had a 6% lower probability of dying.
Disaster management and mitigation: the telecommunications infrastructure.

PubMed

Patricelli, Frédéric; Beakley, James E; Carnevale, Angelo; Tarabochia, Marcello; von Lubitz, Dag K J E

2009-03-01

Among the most typical consequences of disasters is the near or complete collapse of terrestrial telecommunications infrastructures (especially the distribution network--the 'last mile') and their concomitant unavailability to the rescuers and the higher echelons of mitigation teams. Even when such damage does not take place, the communications overload/congestion resulting from significantly elevated traffic generated by affected residents can be highly disturbing. The paper proposes innovative remedies to the telecommunications difficulties in disaster struck regions. The offered solutions are network-centric operations-cap able, and can be employed in management of disasters of any magnitude (local to national or international). Their implementation provide ground rescue teams (such as law enforcement, firemen, healthcare personnel, civilian authorities) with tactical connectivity among themselves, and, through the Next Generation Network backbone, ensure the essential bidirectional free flow of information and distribution of Actionable Knowledge among ground units, command/control centres, and civilian and military agencies participating in the rescue effort.

Understanding transit ridership demand for a multi-destination, multimodal transit network in an American metropolitan area : lessons for increasing choice ridership while maintaining transit dependent ridership.

DOT National Transportation Integrated Search

2012-01-01

This study examines the factors underlying transit demand in the multi-destination, integrated bus and rail transit network for Atlanta, Georgia. Atlanta provides an opportunity to explore the consequences of a multi-destination transit network for b...
The Practices of Student Network as Cooperative Learning in Ethiopia

ERIC Educational Resources Information Center

Reda, Weldemariam Nigusse; Hagos, Girmay Tsegay

2015-01-01

Student network is a teaching strategy introduced as cooperative learning to all educational levels above the upper primary schools (grade 5 and above) in Ethiopia. The study was, therefore, aimed at investigating to what extent the student network in Ethiopia is actually practiced in line with the principles of cooperative learning. Consequently,…
A Revolution in Regional Networking: Linking the Knowledge. AIR 1995 Annual Forum Paper.

ERIC Educational Resources Information Center

Rosmalen, C. M. van

Regional networking and knowledge transfer are considered with a focus on partnerships between business and higher education institutions, conditions for successful strategic allegiances, and the consequences of networking for the higher education mission. The experiences of Utrecht University (the Netherlands) are used to illustrate how a higher…
Class Size, School Size and the Size of the School Network

ERIC Educational Resources Information Center

Coupé, Tom; Olefir, Anna; Alonso, Juan Diego

2016-01-01

In many transition countries, including Ukraine, decreases in population and fertility have led to substantial falls in the number of school-aged children. As a consequence, these countries now have school networks that consist of many small schools, leading many countries to consider reorganizing their networks by closing smaller schools and…
Experimental resource pulses influence social-network dynamics and the potential for information flow in tool-using crows

PubMed Central

St Clair, James J. H.; Burns, Zackory T.; Bettaney, Elaine M.; Morrissey, Michael B.; Otis, Brian; Ryder, Thomas B.; Fleischer, Robert C.; James, Richard; Rutz, Christian

2015-01-01

Social-network dynamics have profound consequences for biological processes such as information flow, but are notoriously difficult to measure in the wild. We used novel transceiver technology to chart association patterns across 19 days in a wild population of the New Caledonian crow—a tool-using species that may socially learn, and culturally accumulate, tool-related information. To examine the causes and consequences of changing network topology, we manipulated the environmental availability of the crows' preferred tool-extracted prey, and simulated, in silico, the diffusion of information across field-recorded time-ordered networks. Here we show that network structure responds quickly to environmental change and that novel information can potentially spread rapidly within multi-family communities, especially when tool-use opportunities are plentiful. At the same time, we report surprisingly limited social contact between neighbouring crow communities. Such scale dependence in information-flow dynamics is likely to influence the evolution and maintenance of material cultures. PMID:26529116
Optimizing the process of recovery after road network break-up

NASA Astrophysics Data System (ADS)

Bíl, Michal; Vodák, Rostislav; Křivánková, Zuzana

2016-04-01

A functioning road network provides accessibility to municipalities, important services and facilities. This basic role of the network can be disrupted by natural disasters which usually affect large areas and cause temporal blockages or even destruction of many roads at the same time. This often leads to road network break-up, when a number of disconnected parts emerge. These parts are often of varying importance to society. Some of them may contain large cities or important facilities such as hospitals. This should be reflected during reconnection works when the most important parts of the network should be reconnected among the first in order to reduce the impact of the event. Decision makers and crisis managers, however, do still not have any dynamic tool which might help them with prioritizing the necessary steps. In our presentation we introduce an algorithm and examples of suitable loss functions which enable us to rapidly identify isolated parts of the network, evaluate them and consequently establish an optimal ranked sequence of interrupted links which have to be repaired to reduce the consequences of the disasters.
Indirect economic impact of landslide hazards by disruption to national road transportation networks; Scotland, United Kingdom.

NASA Astrophysics Data System (ADS)

Postance, Benjamin; Hillier, John; Dijkstra, Tom; Dixon, Neil

2016-04-01

The failure of engineered or natural slopes which support or are adjacent to transportation systems often inflicts costly direct physical damage and indirect system disruption. The consequences and severity of indirect impacts vary according to which links, nodes or network facilities are physically disrupted. Moreover, it is often the case that multiple slope failure disruptions are triggered simultaneously following prolonged or intense precipitation events due to a degree of local homogeneity of slope characteristics and materials. This study investigates the application of national commuter statistics and network agent simulation to evaluate indirect impacts of landslide events disrupting the Scottish trunk road transportation network (UK). Previous studies often employ shortest pathway analysis whereas agent simulation has received relatively little attention. British Geological Survey GeoSure landslide susceptibility data is used to select 35 susceptible trunk road segments by means of neighbouring total area at risk. For each of the candidate 35 segments the network and zonal variation in travel time is calculated for a single day of disruption, economic impact is approximated using established governmental and industry transport planning and appraisal values. The results highlight that a number of trunk road segments incur indirect economic losses in the order of tens of thousands of pounds for each day of closure. Calculated losses at the A83 Rest and Be Thankful are 50% greater than previous estimates at £75 thousand per day of closure. Also highlighted are events in which economic impact is relatively minor, yet concentrating on particular communities that can become substantially isolated as a consequence of a single event. The findings of this study are of interest and support wider investigations exploring cost considerations for decision makers and mitigation strategies, in addition to identifying network topological and demand indicators conducive to high indirect economic cost events.
Effect of Heterogeneity on Decorrelation Mechanisms in Spiking Neural Networks: A Neuromorphic-Hardware Study

NASA Astrophysics Data System (ADS)

Pfeil, Thomas; Jordan, Jakob; Tetzlaff, Tom; Grübl, Andreas; Schemmel, Johannes; Diesmann, Markus; Meier, Karlheinz

2016-04-01

High-level brain function, such as memory, classification, or reasoning, can be realized by means of recurrent networks of simplified model neurons. Analog neuromorphic hardware constitutes a fast and energy-efficient substrate for the implementation of such neural computing architectures in technical applications and neuroscientific research. The functional performance of neural networks is often critically dependent on the level of correlations in the neural activity. In finite networks, correlations are typically inevitable due to shared presynaptic input. Recent theoretical studies have shown that inhibitory feedback, abundant in biological neural networks, can actively suppress these shared-input correlations and thereby enable neurons to fire nearly independently. For networks of spiking neurons, the decorrelating effect of inhibitory feedback has so far been explicitly demonstrated only for homogeneous networks of neurons with linear subthreshold dynamics. Theory, however, suggests that the effect is a general phenomenon, present in any system with sufficient inhibitory feedback, irrespective of the details of the network structure or the neuronal and synaptic properties. Here, we investigate the effect of network heterogeneity on correlations in sparse, random networks of inhibitory neurons with nonlinear, conductance-based synapses. Emulations of these networks on the analog neuromorphic-hardware system Spikey allow us to test the efficiency of decorrelation by inhibitory feedback in the presence of hardware-specific heterogeneities. The configurability of the hardware substrate enables us to modulate the extent of heterogeneity in a systematic manner. We selectively study the effects of shared input and recurrent connections on correlations in membrane potentials and spike trains. Our results confirm that shared-input correlations are actively suppressed by inhibitory feedback also in highly heterogeneous networks exhibiting broad, heavy-tailed firing-rate distributions. In line with former studies, cell heterogeneities reduce shared-input correlations. Overall, however, correlations in the recurrent system can increase with the level of heterogeneity as a consequence of diminished effective negative feedback.
Using Bayesian Network as a tool for coastal storm flood impact prediction at Varna Bay (Bulgaria, Western Black Sea)

NASA Astrophysics Data System (ADS)

Valchev, Nikolay; Eftimova, Petya; Andreeva, Nataliya; Prodanov, Bogdan

2017-04-01

Coastal zone is among the fastest evolving areas worldwide. Ever increasing population inhabiting coastal settlements develops often conflicting economic and societal activities. The existing imbalance between the expansion of these activities, on one hand, and the potential to accommodate them in a sustainable manner, on the other, becomes a critical problem. Concurrently, coasts are affected by various hydro-meteorological phenomena such as storm surges, heavy seas, strong winds and flash floods, which intensities and occurrence frequency is likely to increase due to the climate change. This implies elaboration of tools capable of quick prediction of impact of those phenomena on the coast and providing solutions in terms of disaster risk reduction measures. One such tool is Bayesian network. Proposed paper describes the set-up of such network for Varna Bay (Bulgaria, Western Black Sea). It relates near-shore storm conditions to their onshore flood potential and ultimately to relevant impact as relative damage on coastal and manmade environment. Methodology for set-up and training of the Bayesian network was developed within RISC-KIT project (Resilience-Increasing Strategies for Coasts - toolKIT). Proposed BN reflects the interaction between boundary conditions, receptors, hazard, and consequences. Storm boundary conditions - maximum significant wave height and peak surge level, were determined on the basis of their historical and projected occurrence. The only hazard considered in this study is flooding characterized by maximum inundation depth. BN was trained with synthetic events created by combining estimated boundary conditions. Flood impact was modeled with the process-based morphodynamical model XBeach. Restaurants, sport and leisure facilities, administrative buildings, and car parks were introduced in the network as receptors. Consequences (impact) are estimated in terms of relative damage caused by given inundation depth. National depth-damage (susceptibility) curves were used to define the percentage of damage ranked as low, moderate, high and very high. Besides previously described components, BN includes also two hazard influencing disaster risk reduction (DRR) measures: re-enforced embankment of Varna Port wall and beach nourishment. As a result of training process the network is able to evaluate spatially varying hazards and damages for specific storm conditions. Moreover, it is able to predict where on the site the highest impact would occur and to quantify the mitigation capacity of proposed DRR measures. For example, it is estimated that storm impact would be considerably reduced in present conditions but vulnerability would be still high in climate change perspective.
An improved least cost routing approach for WDM optical network without wavelength converters

NASA Astrophysics Data System (ADS)

Bonani, Luiz H.; Forghani-elahabad, Majid

2016-12-01

Routing and wavelength assignment (RWA) problem has been an attractive problem in optical networks, and consequently several algorithms have been proposed in the literature to solve this problem. The most known techniques for the dynamic routing subproblem are fixed routing, fixed-alternate routing, and adaptive routing methods. The first one leads to a high blocking probability (BP) and the last one includes a high computational complexity and requires immense backing from the control and management protocols. The second one suggests a trade-off between performance and complexity, and hence we consider it to improve in our work. In fact, considering the RWA problem in a wavelength routed optical network with no wavelength converter, an improved technique is proposed for the routing subproblem in order to decrease the BP of the network. Based on fixed-alternate approach, the first k shortest paths (SPs) between each node pair is determined. We then rearrange the SPs according to a newly defined cost for the links and paths. Upon arriving a connection request, the sorted paths are consecutively checked for an available wavelength according to the most-used technique. We implement our proposed algorithm and the least-hop fixed-alternate algorithm to show how the rearrangement of SPs contributes to a lower BP in the network. The numerical results demonstrate the efficiency of our proposed algorithm in comparison with the others, considering different number of available wavelengths.
Differential Effects of Left and Right Prefrontal High-Frequency Repetitive Transcranial Magnetic Stimulation on Resting-State Functional Magnetic Resonance Imaging in Healthy Individuals.

PubMed

Schluter, Renée S; Jansen, Jochem M; van Holst, Ruth J; van den Brink, Wim; Goudriaan, Anna E

2018-03-01

High-frequency repetitive transcranial magnetic stimulation (HF-rTMS) has gained great interest in multiple clinical and research fields and is believed to accomplish its effect by influencing neuronal networks. The dorsolateral prefrontal cortex (dlPFC) is frequently chosen as the cortical target for HF-rTMS. However, very little is known about the differential effect of HF-rTMS over the left and right dlPFC on intrinsic functional connectivity networks in patients or in healthy individuals. The current study assessed the differential effects of left or right HF-rTMS (corrected for sham) on intrinsic independent component analysis (ICA)-defined functional connectivity networks in a sample of 45 healthy individuals. All subjects had a first scanning session in which baseline functional connectivity was assessed. During the second session, individuals received one session of left, right, or sham dlPFC HF-rTMS (60 5-sec trains of 10 Hz at 110% motor threshold). The sham condition was used to correct for time and placebo effects. ICAs were performed to assess baseline differences and stimulation effects on within- and between-network functional connectivity. Stimulation of the left dlPFC resulted in decreased functional connectivity in the salience network, whereas right dlPFC stimulation resulted in increased functional connectivity within this network. No differences between left or right dlPFC stimulation were found in between-network connectivity. These results suggest that left and right HF-rTMS may have differential effects, and more research is needed on the clinical consequences.
Experimental manipulation of avian social structure reveals segregation is carried over across contexts

PubMed Central

Firth, Josh A.; Sheldon, Ben C.

2015-01-01

Our current understanding of animal social networks is largely based on observations or experiments that do not directly manipulate associations between individuals. Consequently, evidence relating to the causal processes underlying such networks is limited. By imposing specified rules controlling individual access to feeding stations, we directly manipulated the foraging social network of a wild bird community, thus demonstrating how external factors can shape social structure. We show that experimentally imposed constraints were carried over into patterns of association at unrestricted, ephemeral food patches, as well as at nesting sites during breeding territory prospecting. Hence, different social contexts can be causally linked, and constraints at one level may have consequences that extend into other aspects of sociality. Finally, the imposed assortment was lost following the cessation of the experimental manipulation, indicating the potential for previously perturbed social networks of wild animals to recover from segregation driven by external constraints. PMID:25652839
ADVANCED SURVEILLANCE OF ENVIROMENTAL RADIATION IN AUTOMATIC NETWORKS.

PubMed

Benito, G; Sáez, J C; Blázquez, J B; Quiñones, J

2018-06-01

The objective of this study is the verification of the operation of a radiation monitoring network conformed by several sensors. The malfunction of a surveillance network has security and economic consequences, which derive from its maintenance and could be avoided with an early detection. The proposed method is based on a kind of multivariate distance, and the verification for the methodology has been tested at CIEMAT's local radiological early warning network.
Exploring the future with anticipatory networks

NASA Astrophysics Data System (ADS)

Skulimowski, A. M. J.

2013-01-01

This paper presents a theory of anticipatory networks that originates from anticipatory models of consequences in multicriteria decision problems. When making a decision, the decision maker takes into account the anticipated outcomes of each future decision problem linked by the causal relations with the present one. In a network of linked decision problems, the causal relations are defined between time-ordered nodes. The scenarios of future consequences of each decision are modeled by multiple vertices starting from an appropriate node. The network is supplemented by one or more relations of anticipation, or future feedback, which describe a situation where decision makers take into account the anticipated results of some future optimization problems while making their choice. So arises a multigraph of decision problems linked causally and by one or more anticipation relation, termed here the anticipatory network. We will present the properties of anticipatory networks and propose a method of reducing, transforming and using them to solve current decision problems. Furthermore, it will be shown that most anticipatory networks can be regarded as superanticipatory systems, i.e. systems that are anticipatory in the Rosen sense and contain a future model of at least one other anticipatory system. The anticipatory networks can also be applied to filter the set of future scenarios in a foresight exercise.
Modeling of workflow-engaged networks on radiology transfers across a metro network.

PubMed

Camorlinga, Sergio; Schofield, Bruce

2006-04-01

Radiology metro networks bear the challenging proposition of interconnecting several hospitals in a region to provide a comprehensive diagnostic imaging service. Consequences of a poorly designed and implemented metro network could cause delays or no access at all when health care providers try to retrieve medical cases across the network. This could translate into limited diagnostic services to patients, resulting in negative impacts to the patients' medical treatment. A workflow-engaged network (WEN) is a new network paradigm. A WEN appreciates radiology workflows and priorities in using the network. A WEN greatly improves the network performance by guaranteeing that critical image transfers experience minimal delay. It adjusts network settings to ensure the application's requirements are met. This means that high-priority image transfers will have guaranteed and known delay times, whereas lower-priority traffic will have increased delays. This paper introduces a modeling to understand the benefits that WEN brings to a radiology metro network. The modeling uses actual data patterns and flows found in a hospital metro region. The workflows considered are based on the Integrating the Healthcare Enterprise profiles. This modeling has been applied to metropolitan workflows of a health region. The modeling helps identify the kind of metro network that supports data patterns and flows in a metro area. The results of the modeling show that a 155-Mb/s metropolitan area network (MAN) with WEN operates virtually equal to a normal 622-Mb/s MAN without WEN, with potential cost savings for leased line services measured in the millions of dollars per year.
Characterizing the evolution of climate networks

NASA Astrophysics Data System (ADS)

Tupikina, L.; Rehfeld, K.; Molkenthin, N.; Stolbova, V.; Marwan, N.; Kurths, J.

2014-06-01

Complex network theory has been successfully applied to understand the structural and functional topology of many dynamical systems from nature, society and technology. Many properties of these systems change over time, and, consequently, networks reconstructed from them will, too. However, although static and temporally changing networks have been studied extensively, methods to quantify their robustness as they evolve in time are lacking. In this paper we develop a theory to investigate how networks are changing within time based on the quantitative analysis of dissimilarities in the network structure. Our main result is the common component evolution function (CCEF) which characterizes network development over time. To test our approach we apply it to several model systems, Erdős-Rényi networks, analytically derived flow-based networks, and transient simulations from the START model for which we control the change of single parameters over time. Then we construct annual climate networks from NCEP/NCAR reanalysis data for the Asian monsoon domain for the time period of 1970-2011 CE and use the CCEF to characterize the temporal evolution in this region. While this real-world CCEF displays a high degree of network persistence over large time lags, there are distinct time periods when common links break down. This phasing of these events coincides with years of strong El Niño/Southern Oscillation phenomena, confirming previous studies. The proposed method can be applied for any type of evolving network where the link but not the node set is changing, and may be particularly useful to characterize nonstationary evolving systems using complex networks.
Battle of Narratives

DTIC Science & Technology

2012-06-01

18 De Nooy, Wouter, Andrej Mrvar , and Vladimir Batagelj , Exploratory Social Network Analysis with Pajek (New York: Cambridge University Press, 2005... Mrvar , and Vladimir Batagelj . Exploratory Social Network Analysis with Pajek. New York: Cambridge University Press, 2005. Democratic National...Review 54(1):33-48; Brian Uzzi. 1996 . "The Sources and Consequences of Embeddedness for the Economic Performance of Organizations: The Network Effect
Exploring the Excluded Galactic Cosmic Rays--those at the Lowest Energies.

NASA Astrophysics Data System (ADS)

Shapiro, Maurice M.

2001-04-01

The solar wind prevents the lowest- energy Galactic cosmic rays (GCR) from entering the heliosphere. Consequently, space probes have thus far been unable to sample them. We suggest that astrochemistry may provide a ``handle" on these particles. Clouds in the interstellar medium (ISM) are sites of chemical-reaction networks that produce various molecular species detectable by their radioastronomical signatures. Highly ionizing low-energy cosmic rays are thought to be the principal agents of molecule production in clouds. Some anomalous abundances, e.g., of deuterium molecules, have been detected. Could studies of the foregoing networks of reactions and their products yield clues to the fluxes and energy spectra of the lowest-energy GCR in the ISM? Other approaches to this problem are also cited.
Exploring the Galactic Cosmic Rays at the lowest energies

NASA Astrophysics Data System (ADS)

Shapiro, M. M.

2001-08-01

The solar wind prevents the lowest-energy Galactic cosmic rays (GCR) from entering the Heliosphere. Consequently, space probes have thus far been unable to sample them. We suggest that astrochemistry may provide a handle on these particles. Clouds in the interstellar medium (ISM) are sites of chemical-reaction networks that produce various molecular species detectable by their radioastronomical signatures. Highly ionizing low-energy cosmic rays are thought to be the principal agents of molecule production in clouds. Some anomalous abundances, e.g., of deuterium molecules, have been detected. Could studies of the foregoing networks of reactions and their products yield clues to the fluxes and energy spectra of the lowest-energy GCR in the ISM? Other approaches to this problem are also cited.
Family ties: the multilevel effects of households and kinship on the networks of individuals.

PubMed

Koster, Jeremy

2018-04-01

Among social mammals, humans uniquely organize themselves into communities of households that are centred around enduring, predominantly monogamous unions of men and women. As a consequence of this social organization, individuals maintain social relationships both within and across households, and potentially there is conflict among household members about which social ties to prioritize or de-emphasize. Extending the logic of structural balance theory, I predict that there will be considerable overlap in the social networks of individual household members, resulting in a pattern of group-level reciprocity. To test this prediction, I advance the Group-Structured Social Relations Model, a generalized linear mixed model that tests for group-level effects in the inter-household social networks of individuals. The empirical data stem from social support interviews conducted in a community of indigenous Nicaraguan horticulturalists, and model results show high group-level reciprocity among households. Although support networks are organized around kinship, covariates that test predictions of kin selection models do not receive strong support, potentially because most kin-directed altruism occurs within households, not between households. In addition, the models show that households with high genetic relatedness in part from children born to adulterous relationships are less likely to assist each other.

Genes under weaker stabilizing selection increase network evolvability and rapid regulatory adaptation to an environmental shift.

PubMed

Laarits, T; Bordalo, P; Lemos, B

2016-08-01

Regulatory networks play a central role in the modulation of gene expression, the control of cellular differentiation, and the emergence of complex phenotypes. Regulatory networks could constrain or facilitate evolutionary adaptation in gene expression levels. Here, we model the adaptation of regulatory networks and gene expression levels to a shift in the environment that alters the optimal expression level of a single gene. Our analyses show signatures of natural selection on regulatory networks that both constrain and facilitate rapid evolution of gene expression level towards new optima. The analyses are interpreted from the standpoint of neutral expectations and illustrate the challenge to making inferences about network adaptation. Furthermore, we examine the consequence of variable stabilizing selection across genes on the strength and direction of interactions in regulatory networks and in their subsequent adaptation. We observe that directional selection on a highly constrained gene previously under strong stabilizing selection was more efficient when the gene was embedded within a network of partners under relaxed stabilizing selection pressure. The observation leads to the expectation that evolutionarily resilient regulatory networks will contain optimal ratios of genes whose expression is under weak and strong stabilizing selection. Altogether, our results suggest that the variable strengths of stabilizing selection across genes within regulatory networks might itself contribute to the long-term adaptation of complex phenotypes. © 2016 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2016 European Society For Evolutionary Biology.
Landslide susceptibility and risk assessment: specificities for road networks

NASA Astrophysics Data System (ADS)

Pellicani, Roberta; Argentiero, Ilenia; Parisi, Alessandro; Spilotro, Giuseppe

2017-04-01

A regional-scale assessment of landslide susceptibility and risk along the main road corridors crossing the provincial territory of Matera (Basilicata Region, Southern Italy) was carried out. The entire provincial road network extends for about 1,320 km through a territory, of which represents the main connection infrastructure among thirty-one municipalities due to the lack of an efficient integrated transportation system through the whole regional territory. For this reason, the strategic importance of these roads consists in their uniqueness in connecting every urban center with the socio-economic surrounding context. These roads and their vehicular traffic are continuously exposed to instability processes (about the 40% of the total length is disrupted by landslides), characterized both by high intensity and low frequency and by low intensity and high frequency. This last typology, consisting in small shallow landslides, is particularly hazardous for the roads since it is widespread along the road network, its occurrence is connected to rainfalls and determines high vulnerability conditions for the road in terms of interruption of vehicular traffic. A GIS-based heuristic-bivariate statistical predictive model was performed to assess and map the landslide susceptibility in the study area, by using a polynomial function of eight predisposing factors, weighted according to their influence on the landslide phenomena, recognized and collected in an inventory. Susceptibility associated to small shallow phenomena was assessed by using a polynomial function of specific factors, such as slope angle and aspect, lithological outcrops, rainfalls, etc. In absence of detailed input data, the spatial distribution of landslide risk along the road corridors was assessed and mapped using a qualitative hazard-consequence matrix approach, by which risk is obtained by combining hazard categories with consequence classes pairwise in a two-dimensional table or matrix. Landslide hazard, which is a function of the return time, due to the lack of temporal data, was evaluated as a function of the landslide intensity (velocity and areal extent) and susceptibility. The direct consequences of instability on the roads were defined by combining exposure and vulnerability in a matrix. Exposure was evaluated in terms of amount of traffic, which was calculated along each road stretch, connecting two or more urban areas, as a function of the average of population of each centers. Vulnerability, which expresses the degree of damage, was assessed in function of the presence of criticalities along roads, which were ranked according to the severity of damages and type of performed reparation works. The consequences, combined with the hazard levels, allowed to assess the landslide risk, classified in low, medium and high levels. The risk map highlighted that about the 30% (392 km) of the examined road corridors is affected by high risk levels. The comparison between the risk map and the landslide inventory recognized along roads has also revealed that the 49.5% of landslides affects sections where the risk was evaluated high. The obtained risk classification of the roads represents a support for decision making and allows to identify the priorities for designing appropriate landslide mitigation plans.
“Guilt by Association” Is the Exception Rather Than the Rule in Gene Networks

PubMed Central

Gillis, Jesse; Pavlidis, Paul

2012-01-01

Gene networks are commonly interpreted as encoding functional information in their connections. An extensively validated principle called guilt by association states that genes which are associated or interacting are more likely to share function. Guilt by association provides the central top-down principle for analyzing gene networks in functional terms or assessing their quality in encoding functional information. In this work, we show that functional information within gene networks is typically concentrated in only a very few interactions whose properties cannot be reliably related to the rest of the network. In effect, the apparent encoding of function within networks has been largely driven by outliers whose behaviour cannot even be generalized to individual genes, let alone to the network at large. While experimentalist-driven analysis of interactions may use prior expert knowledge to focus on the small fraction of critically important data, large-scale computational analyses have typically assumed that high-performance cross-validation in a network is due to a generalizable encoding of function. Because we find that gene function is not systemically encoded in networks, but dependent on specific and critical interactions, we conclude it is necessary to focus on the details of how networks encode function and what information computational analyses use to extract functional meaning. We explore a number of consequences of this and find that network structure itself provides clues as to which connections are critical and that systemic properties, such as scale-free-like behaviour, do not map onto the functional connectivity within networks. PMID:22479173
Actin assembly factors regulate the gelation kinetics and architecture of F-actin networks.

PubMed

Falzone, Tobias T; Oakes, Patrick W; Sees, Jennifer; Kovar, David R; Gardel, Margaret L

2013-04-16

Dynamic regulation of the actin cytoskeleton is required for diverse cellular processes. Proteins regulating the assembly kinetics of the cytoskeletal biopolymer F-actin are known to impact the architecture of actin cytoskeletal networks in vivo, but the underlying mechanisms are not well understood. Here, we demonstrate that changes to actin assembly kinetics with physiologically relevant proteins profilin and formin (mDia1 and Cdc12) have dramatic consequences on the architecture and gelation kinetics of otherwise biochemically identical cross-linked F-actin networks. Reduced F-actin nucleation rates promote the formation of a sparse network of thick bundles, whereas increased nucleation rates result in a denser network of thinner bundles. Changes to F-actin elongation rates also have marked consequences. At low elongation rates, gelation ceases and a solution of rigid bundles is formed. By contrast, rapid filament elongation accelerates dynamic arrest and promotes gelation with minimal F-actin density. These results are consistent with a recently developed model of how kinetic constraints regulate network architecture and underscore how molecular control of polymer assembly is exploited to modulate cytoskeletal architecture and material properties. Copyright © 2013 Biophysical Society. Published by Elsevier Inc. All rights reserved.
Actin Assembly Factors Regulate the Gelation Kinetics and Architecture of F-actin Networks

PubMed Central

Falzone, Tobias T.; Oakes, Patrick W.; Sees, Jennifer; Kovar, David R.; Gardel, Margaret L.

2013-01-01

Dynamic regulation of the actin cytoskeleton is required for diverse cellular processes. Proteins regulating the assembly kinetics of the cytoskeletal biopolymer F-actin are known to impact the architecture of actin cytoskeletal networks in vivo, but the underlying mechanisms are not well understood. Here, we demonstrate that changes to actin assembly kinetics with physiologically relevant proteins profilin and formin (mDia1 and Cdc12) have dramatic consequences on the architecture and gelation kinetics of otherwise biochemically identical cross-linked F-actin networks. Reduced F-actin nucleation rates promote the formation of a sparse network of thick bundles, whereas increased nucleation rates result in a denser network of thinner bundles. Changes to F-actin elongation rates also have marked consequences. At low elongation rates, gelation ceases and a solution of rigid bundles is formed. By contrast, rapid filament elongation accelerates dynamic arrest and promotes gelation with minimal F-actin density. These results are consistent with a recently developed model of how kinetic constraints regulate network architecture and underscore how molecular control of polymer assembly is exploited to modulate cytoskeletal architecture and material properties. PMID:23601318
Combined neurostimulation and neuroimaging in cognitive neuroscience: past, present, and future.

PubMed

Bestmann, Sven; Feredoes, Eva

2013-08-01

Modern neurostimulation approaches in humans provide controlled inputs into the operations of cortical regions, with highly specific behavioral consequences. This enables causal structure-function inferences, and in combination with neuroimaging, has provided novel insights into the basic mechanisms of action of neurostimulation on distributed networks. For example, more recent work has established the capacity of transcranial magnetic stimulation (TMS) to probe causal interregional influences, and their interaction with cognitive state changes. Combinations of neurostimulation and neuroimaging now face the challenge of integrating the known physiological effects of neurostimulation with theoretical and biological models of cognition, for example, when theoretical stalemates between opposing cognitive theories need to be resolved. This will be driven by novel developments, including biologically informed computational network analyses for predicting the impact of neurostimulation on brain networks, as well as novel neuroimaging and neurostimulation techniques. Such future developments may offer an expanded set of tools with which to investigate structure-function relationships, and to formulate and reconceptualize testable hypotheses about complex neural network interactions and their causal roles in cognition. © 2013 New York Academy of Sciences.
Causes and consequences of habitat fragmentation in river networks.

PubMed

Fuller, Matthew R; Doyle, Martin W; Strayer, David L

2015-10-01

Increases in river fragmentation globally threaten freshwater biodiversity. Rivers are fragmented by many agents, both natural and anthropogenic. We review the distribution and frequency of these major agents, along with their effects on connectivity and habitat quality. Most fragmentation research has focused on terrestrial habitats, but theories and generalizations developed in terrestrial habitats do not always apply well to river networks. For example, terrestrial habitats are usually conceptualized as two-dimensional, whereas rivers often are conceptualized as one-dimensional or dendritic. In addition, river flow often leads to highly asymmetric effects of barriers on habitat and permeability. New approaches tailored to river networks can be applied to describe the network-wide effects of multiple barriers on both connectivity and habitat quality. The net effects of anthropogenic fragmentation on freshwater biodiversity are likely underestimated, because of time lags in effects and the difficulty of generating a single, simple signal of fragmentation that applies to all aquatic species. We conclude by presenting a decision tree for managing freshwater fragmentation, as well as some research horizons for evaluating fragmented riverscapes. © 2015 New York Academy of Sciences.
A graph-based system for network-vulnerability analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Swiler, L.P.; Phillips, C.

1998-06-01

This paper presents a graph-based approach to network vulnerability analysis. The method is flexible, allowing analysis of attacks from both outside and inside the network. It can analyze risks to a specific network asset, or examine the universe of possible consequences following a successful attack. The graph-based tool can identify the set of attack paths that have a high probability of success (or a low effort cost) for the attacker. The system could be used to test the effectiveness of making configuration changes, implementing an intrusion detection system, etc. The analysis system requires as input a database of common attacks,more » broken into atomic steps, specific network configuration and topology information, and an attacker profile. The attack information is matched with the network configuration information and an attacker profile to create a superset attack graph. Nodes identify a stage of attack, for example the class of machines the attacker has accessed and the user privilege level he or she has compromised. The arcs in the attack graph represent attacks or stages of attacks. By assigning probabilities of success on the arcs or costs representing level-of-effort for the attacker, various graph algorithms such as shortest-path algorithms can identify the attack paths with the highest probability of success.« less
Sleep: A synchrony of cell activity-driven small network states

PubMed Central

Krueger, James M.; Huang, Yanhua; Rector, David M.; Buysse, Daniel J.

2013-01-01

We posit a bottom-up sleep regulatory paradigm in which state changes are initiated within small networks as a consequence of local cell activity. Bottom-up regulatory mechanisms are prevalent throughout nature, occurring in vastly different systems and levels of organization. Synchronization of state without top-down regulation is a fundamental property of large collections of small semi-autonomous entities. We posit that such synchronization mechanisms are sufficient and necessary for whole organism sleep onset. Within brain we posit that small networks of highly interconnected neurons and glia, e.g. cortical columns, are semi-autonomous units oscillating between sleep-like and wake-like states. We review evidence showing that cells, small networks, and regional areas of brain share sleep-like properties with whole animal sleep. A testable hypothesis focused on how sleep is initiated within local networks is presented. We posit that the release of cell activity-dependent molecules, such as ATP and nitric oxide, into the extracellular space initiates state changes within the local networks where they are produced. We review mechanisms of ATP induction of sleep regulatory substances (SRS) and their actions on receptor trafficking. Finally, we provide an example of how such local metabolic and state changes provide mechanistic explanations for clinical conditions such as insomnia. PMID:23651209
Parameter space exploration within dynamic simulations of signaling networks.

PubMed

De Ambrosi, Cristina; Barla, Annalisa; Tortolina, Lorenzo; Castagnino, Nicoletta; Pesenti, Raffaele; Verri, Alessandro; Ballestrero, Alberto; Patrone, Franco; Parodi, Silvio

2013-02-01

We started offering an introduction to very basic aspects of molecular biology, for the reader coming from computer sciences, information technology, mathematics. Similarly we offered a minimum of information about pathways and networks in graph theory, for a reader coming from the bio-medical sector. At the crossover about the two different types of expertise, we offered some definition about Systems Biology. The core of the article deals with a Molecular Interaction Map (MIM), a network of biochemical interactions involved in a small signaling-network sub-region relevant in breast cancer. We explored robustness/sensitivity to random perturbations. It turns out that our MIM is a non-isomorphic directed graph. For non physiological directions of propagation of the signal the network is quite resistant to perturbations. The opposite happens for biologically significant directions of signal propagation. In these cases we can have no signal attenuation, and even signal amplification. Signal propagation along a given pathway is highly unidirectional, with the exception of signal-feedbacks, that again have a specific biological role and significance. In conclusion, even a relatively small network like our present MIM reveals the preponderance of specific biological functions over unspecific isomorphic behaviors. This is perhaps the consequence of hundreds of millions of years of biological evolution.
A Secure Multicast Framework in Large and High-Mobility Network Groups

NASA Astrophysics Data System (ADS)

Lee, Jung-San; Chang, Chin-Chen

With the widespread use of Internet applications such as Teleconference, Pay-TV, Collaborate tasks, and Message services, how to construct and distribute the group session key to all group members securely is becoming and more important. Instead of adopting the point-to-point packet delivery, these emerging applications are based upon the mechanism of multicast communication, which allows the group member to communicate with multi-party efficiently. There are two main issues in the mechanism of multicast communication: Key Distribution and Scalability. The first issue is how to distribute the group session key to all group members securely. The second one is how to maintain the high performance in large network groups. Group members in conventional multicast systems have to keep numerous secret keys in databases, which makes it very inconvenient for them. Furthermore, in case that a member joins or leaves the communication group, many involved participants have to change their own secret keys to preserve the forward secrecy and the backward secrecy. We consequently propose a novel version for providing secure multicast communication in large network groups. Our proposed framework not only preserves the forward secrecy and the backward secrecy but also possesses better performance than existing alternatives. Specifically, simulation results demonstrate that our scheme is suitable for high-mobility environments.
Modeling Belt-Servomechanism by Chebyshev Functional Recurrent Neuro-Fuzzy Network

NASA Astrophysics Data System (ADS)

Huang, Yuan-Ruey; Kang, Yuan; Chu, Ming-Hui; Chang, Yeon-Pun

A novel Chebyshev functional recurrent neuro-fuzzy (CFRNF) network is developed from a combination of the Takagi-Sugeno-Kang (TSK) fuzzy model and the Chebyshev recurrent neural network (CRNN). The CFRNF network can emulate the nonlinear dynamics of a servomechanism system. The system nonlinearity is addressed by enhancing the input dimensions of the consequent parts in the fuzzy rules due to functional expansion of a Chebyshev polynomial. The back propagation algorithm is used to adjust the parameters of the antecedent membership functions as well as those of consequent functions. To verify the performance of the proposed CFRNF, the experiment of the belt servomechanism is presented in this paper. Both of identification methods of adaptive neural fuzzy inference system (ANFIS) and recurrent neural network (RNN) are also studied for modeling of the belt servomechanism. The analysis and comparison results indicate that CFRNF makes identification of complex nonlinear dynamic systems easier. It is verified that the accuracy and convergence of the CFRNF are superior to those of ANFIS and RNN by the identification results of a belt servomechanism.
Structural connectivity allows for multi-threading during rest: the structure of the cortex leads to efficient alternation between resting state exploratory behavior and default mode processing.

PubMed

Senden, Mario; Goebel, Rainer; Deco, Gustavo

2012-05-01

Despite the absence of stimulation or task conditions the cortex exhibits highly structured spatio-temporal activity patterns. These patterns are known as resting state networks (RSNs) and emerge as low-frequency fluctuations (<0.1 Hz) observed in the fMRI signal of human subjects during rest. We are interested in the relationship between structural connectivity of the cortex and the fluctuations exhibited during resting conditions. We are especially interested in the effect of degree of connectivity on resting state dynamics as the default mode network (DMN) is highly connected. We find in experimental resting fMRI data that the DMN is the functional network that is most frequently active and for the longest time. In large-scale computational simulations of the cortex based on the corresponding underlying DTI/DSI based neuroanatomical connectivity matrix, we additionally find a strong correlation between the mean degree of functional networks and the proportion of time they are active. By artificially modifying different types of neuroanatomical connectivity matrices in the model, we were able to demonstrate that only models based on structural connectivity containing hubs give rise to this relationship. We conclude that, during rest, the cortex alternates efficiently between explorations of its externally oriented functional repertoire and internally oriented processing as a consequence of the DMN's high degree of connectivity. Copyright © 2012 Elsevier Inc. All rights reserved.
Interplay between cooperation-enhancing mechanisms in evolutionary games with tag-mediated interactions

NASA Astrophysics Data System (ADS)

Hadzibeganovic, Tarik; Stauffer, Dietrich; Han, Xiao-Pu

2018-04-01

Cooperation is fundamental for the long-term survival of biological, social, and technological networks. Previously, mechanisms for the enhancement of cooperation, such as network reciprocity, have largely been studied in isolation and with often inconclusive findings. Here, we present an evolutionary, multiagent-based, and spatially explicit computer model to specifically address the interactive interplay between such mechanisms. We systematically investigate the effects of phenotypic diversity, network structure, and rewards on cooperative behavior emerging in a population of reproducing artificial decision makers playing tag-mediated evolutionary games. Cooperative interactions are rewarded such that both the benefits of recipients and costs of donators are affected by the reward size. The reward size is determined by the number of cooperative acts occurring within a given reward time frame. Our computational experiments reveal that small reward frames promote unconditional cooperation in populations with both low and high diversity, whereas large reward frames lead to cycles of conditional and unconditional strategies at high but not at low diversity. Moreover, an interaction between rewards and spatial structure shows that relative to small reward frames, there is a strong difference between the frequency of conditional cooperators populating rewired versus non-rewired networks when the reward frame is large. Notably, in a less diverse population, the total number of defections is comparable across different network topologies, whereas in more diverse environments defections become more frequent in a regularly structured than in a rewired, small-world network of contacts. Acknowledging the importance of such interaction effects in social dilemmas will have inevitable consequences for the future design of cooperation-enhancing protocols in large-scale, distributed, and decentralized systems such as peer-to-peer networks.
Human astrocytic grid networks patterned in parylene-C inlayed SiO2 trenches.

PubMed

Jordan, M D; Raos, B J; Bunting, A S; Murray, A F; Graham, E S; Unsworth, C P

2016-10-01

Recent literature suggests that glia, and in particular astrocytes, should be studied as organised networks which communicate through gap junctions. Astrocytes, however, adhere to most surfaces and are highly mobile cells. In order to study, such organised networks effectively in vitro it is necessary to influence them to pattern to certain substrates whilst being repelled from others and to immobilise the astrocytes sufficiently such that they do not continue to migrate further whilst under study. In this article, we demonstrate for the first time how it is possible to facilitate the study of organised patterned human astrocytic networks using hNT astrocytes in a SiO2 trench grid network that is inlayed with the biocompatible material, parylene-C. We demonstrate how the immobilisation of astrocytes lies in the depth of the SiO2 trench, determining an optimum trench depth and that the optimum patterning of astrocytes is a consequence of the parylene-C inlay and the grid node spacing. We demonstrate high fidelity of the astrocytic networks and demonstrate that functionality of the hNT astrocytes through ATP evoked calcium signalling is also dependent on the grid node spacing. Finally, we demonstrate that the location of the nuclei on the grid nodes is also a function of the grid node spacing. The significance of this work, is to describe a suitable platform to facilitate the study of hNT astrocytes from the single cell level to the network level to improve knowledge and understanding of how communication links to spatial organisation at these higher order scales and trigger in vitro research further in this area with clinical applications in the area of epilepsy, stroke and focal cerebral ischemia. Copyright © 2016 Elsevier Ltd. All rights reserved.
Background Noise of the Aldeia da Serra Region (Portugal) from a temporary broad band network

NASA Astrophysics Data System (ADS)

Wachilala, Piedade; Borges, José; Caldeira, Bento; Bezzeghoud, Mourad

2017-04-01

In this study, we analyse seismic background noise to assess the effect of noise based on the detectability of a temporary network constituted by DOCTAR (Deep Ocean Test Array), who have been deployed in a period between 2011 and 2012 in Portugal mainland, and the Évora permanent seismic station. This network is constituted by 14 digital broadband stations (14 CMG-3ESP and one STS2 sensors) with a flat response between the 60 sec to 50 Hz, 24-bit and 120s to 60Hz respectively. The temporary network was operated in continuous recording mode (three-components) in a region located in the north of the region of Évora, within a radius of about 30 km around the village of Aldeia da Serra, region in which there is an important seismic activity in the context of Portugal mainland. We calculated power spectral densities of background noise for each station/component and compare them with high-noise model and low-noise model of Peterson (1993). We consider different for day and night local and for different periods of the year. Power spectral density estimates show moderate noise levels with all stations falling within the high and low bounds of Peterson (1993). Considering the results of the noise, we estimate the detection limit of each station and consequently the detectability of the network. From this information and taking in attention the events recorded during the period of DOCTAR operation we analyse the improvement promoted by this temporary network regarding the existent seismic networks to the local seismicity study. This work was partially supported by COMPETE 2020 program (POCI-01-0145-FEDER-007690 project). We acknowledge GFZ Potsdam for providing part of the data used in this study.
Effects of n-dominance and group composition on task efficiency in laboratory triads.

NASA Technical Reports Server (NTRS)

Lampkin, E. C.

1972-01-01

Task-oriented triads were formed into various homogeneous and heterogeneous combinations according to their scores on the n-dominance personality trait of the Edwards Personal Preference Schedule. Five group categories were used. The group task required a consensus decision on each trial. High cooperation and interdependence were reinforced by partially restricting the communication network. Results showed heterogeneous groups significantly better at organizing their group communication processes. They consequently performed the task more efficiently than homogeneous triads.
Application of WebGIS for traffic risk assessment

NASA Astrophysics Data System (ADS)

Voumard, Jérémie; Aye, Zar Chi; Derron, Marc-Henri; Jaboyedoff, Michel

2015-04-01

Roads and railways are threatened throughout the year by several natural hazards around the world, leading to the closing of transportation corridors, loss of access, deviation travels and potentially infrastructures damages and loss of human lives and also financial, social and economic consequences. Protection measures used to reduce the exposure to natural hazards are usually expensive and cannot be deployed on an entire transportation network. It is thus necessary to choose priority areas where protection measures need to be built. The aim of this study is to propose a friendly tool to evaluate and to understand issues and consequences of section closing and affected parts of a transportation network at small region scale. The proposed tool, currently in its design and building phase, will provide ways to simulate different closure scenarios and to analyze their consequences on transportation network; like deviating traffic on others roads and railways sections, additional time and distance travel or accessibility for emergency services like police, firefighters and ambulances. The tool is based on OpenGeo architecture, which is composed of open-source components. It integrates PostGIS for database, GeoServer and GeoWebCache for application servers and finally GeoExt and OpenLayers for user interface. Users will be able to attribute quantitative (like roads and railway type and closure consequences) and qualitative (like section unavailability duration, season, etc.) data to the different roads and railways sections based on their user rights. They will also be able to evaluate different track closures consequences in terms of different scenarios. Once finalized, the goal of this project including natural hazards, traffic and geomatic thematic is to propose a decision support tool for public authorities firstly and for specialists secondly so that they can evaluate easily and accurately as much as possible to highlight the weakpoints of the transportation network in the case track closures due to natural hazards.
A Preliminary Investigation of the E-Beam Induced Polymerization of Maleimide and Norbornene End-capped Polyimides

NASA Technical Reports Server (NTRS)

Palmese, Giuseppe R.; Meador, Michael A. (Technical Monitor)

2005-01-01

A research area of high activity in connection with aerospace engineering has been the development of polymer thermosetting resins that can resist temperature as high as 300 C while maintaining adequate toughness, and providing ease of processing to enable low temperature and low cost composite fabrication methods. In order to meet such requirements, sequential interpenetrating polymer networks (IPNs) based on bismaleimide (BMI) and cyanate ester (CE) monomers were investigated. In these systems, a polycyanurate network is first formed in the presence of BMI and appropriate reactive diluent monomers and in a second step, a network based on the BMI is created in the presence of a fully formed polycyanurate network. The materials developed can be processed at relatively low temperature (less than 150 C) and with the aid of electron beam (EB) curing. Of major importance to the success of this work was the identification of a reactive diluent that improves ease of processing and has tailored reactivity to allow for the controlled synthesis of CE-BMI sequential IPNs. Based on solubility and reactivity of a number of reactive diluents, N-acryloylmorpholine (AMP) was selected as a comonomer for BMI copolymerization. A donor-acceptoreaction mechanism was suggested to explain the relative reactivity of a variety of reactive diluents towards maleimide functionality. The optimum processing parameters for the formation of the first network were determined through the study of metal catalyzed cure and hydrolysis of cyanate esters, whereas the reaction behavior for second network formation in terms of the influence of EB dose rate and temperature was elucidated through an in-situ kinetics study of maleimide and AMP copolymerization. Structure-property relationships were developed which allowed for the design of improved resin systems. In particular, appropriate network coupler possessing cyanate ester and maleimide functionality was synthesized to link the polycyanurate first network to the BMI/AMP second network and thus form linked sequential IPNs (LIPNs). Consequently, Tg as high as 370 C was achieved and a fracture toughness of 120 Joules per square meters was obtained for resin systems that possess adequately low viscosity for processing using liquid molding techniques at low temperature.
Network Experiences from a Cross-Sector Biosafety Level-3 Laboratory Collaboration: A Swedish Forum for Biopreparedness Diagnostics.

PubMed

Thelaus, Johanna; Lindberg, Anna; Thisted Lambertz, Susanne; Byström, Mona; Forsman, Mats; Lindmark, Hans; Knutsson, Rickard; Båverud, Viveca; Bråve, Andreas; Jureen, Pontus; Lundin Zumpe, Annelie; Melefors, Öjar

The Swedish Forum for Biopreparedness Diagnostics (FBD) is a network that fosters collaboration among the 4 agencies with responsibility for the laboratory diagnostics of high-consequence pathogens, covering animal health and feed safety, food safety, public health and biodefense, and security. The aim of the network is to strengthen capabilities and capacities for diagnostics at the national biosafety level-3 (BSL-3) laboratories to improve Sweden's biopreparedness, in line with recommendations from the EU and WHO. Since forming in 2007, the FBD network has contributed to the harmonization of diagnostic methods, equipment, quality assurance protocols, and biosafety practices among the national BSL-3 laboratories. Lessons learned from the network include: (1) conducting joint projects with activities such as method development and validation, ring trials, exercises, and audits has helped to build trust and improve communication among participating agencies; (2) rotating the presidency of the network steering committee has fostered trust and commitment from all agencies involved; and (3) planning for the implementation of project outcomes is important to maintain gained competencies in the agencies over time. Contacts have now been established with national agencies of the other Nordic countries, with an aim to expanding the collaboration, broadening the network, finding synergies in new areas, strengthening the ability to share resources, and consolidating long-term financing in the context of harmonized European biopreparedness.

Network Experiences from a Cross-Sector Biosafety Level-3 Laboratory Collaboration: A Swedish Forum for Biopreparedness Diagnostics

PubMed Central

Lindberg, Anna; Thisted Lambertz, Susanne; Byström, Mona; Forsman, Mats; Lindmark, Hans; Knutsson, Rickard; Båverud, Viveca; Bråve, Andreas; Jureen, Pontus; Lundin Zumpe, Annelie; Melefors, Öjar

2017-01-01

The Swedish Forum for Biopreparedness Diagnostics (FBD) is a network that fosters collaboration among the 4 agencies with responsibility for the laboratory diagnostics of high-consequence pathogens, covering animal health and feed safety, food safety, public health and biodefense, and security. The aim of the network is to strengthen capabilities and capacities for diagnostics at the national biosafety level-3 (BSL-3) laboratories to improve Sweden's biopreparedness, in line with recommendations from the EU and WHO. Since forming in 2007, the FBD network has contributed to the harmonization of diagnostic methods, equipment, quality assurance protocols, and biosafety practices among the national BSL-3 laboratories. Lessons learned from the network include: (1) conducting joint projects with activities such as method development and validation, ring trials, exercises, and audits has helped to build trust and improve communication among participating agencies; (2) rotating the presidency of the network steering committee has fostered trust and commitment from all agencies involved; and (3) planning for the implementation of project outcomes is important to maintain gained competencies in the agencies over time. Contacts have now been established with national agencies of the other Nordic countries, with an aim to expanding the collaboration, broadening the network, finding synergies in new areas, strengthening the ability to share resources, and consolidating long-term financing in the context of harmonized European biopreparedness. PMID:28805472
A Strategy Based on Protein-Protein Interface Motifs May Help in Identifying Drug Off-Targets

PubMed Central

Engin, H. Billur; Keskin, Ozlem; Nussinov, Ruth; Gursoy, Attila

2014-01-01

Networks are increasingly used to study the impact of drugs at the systems level. From the algorithmic standpoint, a drug can ‘attack’ nodes or edges of a protein-protein interaction network. In this work, we propose a new network strategy, “The Interface Attack”, based on protein-protein interfaces. Similar interface architectures can occur between unrelated proteins. Consequently, in principle, a drug that binds to one has a certain probability of binding others. The interface attack strategy simultaneously removes from the network all interactions that consist of similar interface motifs. This strategy is inspired by network pharmacology and allows inferring potential off-targets. We introduce a network model which we call “Protein Interface and Interaction Network (P2IN)”, which is the integration of protein-protein interface structures and protein interaction networks. This interface-based network organization clarifies which protein pairs have structurally similar interfaces, and which proteins may compete to bind the same surface region. We built the P2IN of p53 signaling network and performed network robustness analysis. We show that (1) ‘hitting’ frequent interfaces (a set of edges distributed around the network) might be as destructive as eleminating high degree proteins (hub nodes); (2) frequent interfaces are not always topologically critical elements in the network; and (3) interface attack may reveal functional changes in the system better than attack of single proteins. In the off-target detection case study, we found that drugs blocking the interface between CDK6 and CDKN2D may also affect the interaction between CDK4 and CDKN2D. PMID:22817115
A case of a large Chiari network mimicking a right atrial thrombus.

PubMed

Erdogan, Sevinc Bayer; Akansel, Serdar; Sargın, Murat; Mete, Muge Evren Tasdemir; Arslanhan, Gokhan; Aka, Serap Aykut

2017-01-01

The Chiari network is described as a reticulated network of fibers connected to the Eustachian valve identified as the embryological remnant of the right valve of the sinus venosus. It is an incidental finding without any significant pathophysiological consequences. However, the presence of the Chiari network in the right atrium obliges the physician to differentiate from other right atrial pathologies. We present a case of a large Chiari network mimicking a right atrial thrombus with incidental finding in a 76-year-old man undergoing coronary artery bypass surgery.
Network cosmology.

PubMed

Krioukov, Dmitri; Kitsak, Maksim; Sinkovits, Robert S; Rideout, David; Meyer, David; Boguñá, Marián

2012-01-01

Prediction and control of the dynamics of complex networks is a central problem in network science. Structural and dynamical similarities of different real networks suggest that some universal laws might accurately describe the dynamics of these networks, albeit the nature and common origin of such laws remain elusive. Here we show that the causal network representing the large-scale structure of spacetime in our accelerating universe is a power-law graph with strong clustering, similar to many complex networks such as the Internet, social, or biological networks. We prove that this structural similarity is a consequence of the asymptotic equivalence between the large-scale growth dynamics of complex networks and causal networks. This equivalence suggests that unexpectedly similar laws govern the dynamics of complex networks and spacetime in the universe, with implications to network science and cosmology.
Network Cosmology

PubMed Central

Krioukov, Dmitri; Kitsak, Maksim; Sinkovits, Robert S.; Rideout, David; Meyer, David; Boguñá, Marián

2012-01-01

Prediction and control of the dynamics of complex networks is a central problem in network science. Structural and dynamical similarities of different real networks suggest that some universal laws might accurately describe the dynamics of these networks, albeit the nature and common origin of such laws remain elusive. Here we show that the causal network representing the large-scale structure of spacetime in our accelerating universe is a power-law graph with strong clustering, similar to many complex networks such as the Internet, social, or biological networks. We prove that this structural similarity is a consequence of the asymptotic equivalence between the large-scale growth dynamics of complex networks and causal networks. This equivalence suggests that unexpectedly similar laws govern the dynamics of complex networks and spacetime in the universe, with implications to network science and cosmology. PMID:23162688
Television and Competition.

ERIC Educational Resources Information Center

Noll, Roger G.

The television industry is characterized by numerous imperfections in market competition. The spectrum allocation policy of the Federal Communications Commission (FCC) assures that there will be only three national television networks; consequently in nearly all markets these stations account for 75% to 100% of revenues. These networks in turn…
A conceptual model for site-level ecology of the giant gartersnake (Thamnophis gigas) in the Sacramento Valley, California

USGS Publications Warehouse

Halstead, Brian J.; Wylie, Glenn D.; Casazza, Michael L.; Hansen, Eric C.; Scherer, Rick D.; Patterson, Laura C.

2015-08-14

Bayesian networks further provide a clear visual display of the model that facilitates understanding among various stakeholders (Marcot and others, 2001; Uusitalo , 2007). Empirical data and expert judgment can be combined, as continuous or categorical variables, to update knowledge about the system (Marcot and others, 2001; Uusitalo , 2007). Importantly, Bayesian network models allow inference from causes to consequences, but also from consequences to causes, so that data can inform the states of nodes (values of different random variables) in either direction (Marcot and others, 2001; Uusitalo , 2007). Because they can incorporate both decision nodes that represent management actions and utility nodes that quantify the costs and benefits of outcomes, Bayesian networks are ideally suited to risk analysis and adaptive management (Nyberg and others, 2006; Howes and others, 2010). Thus, Bayesian network models are useful in situations where empirical data are not available, such as questions concerning the responses of giant gartersnakes to management.
Multi-period response management to contaminated water distribution networks: dynamic programming versus genetic algorithms

NASA Astrophysics Data System (ADS)

Bashi-Azghadi, Seyyed Nasser; Afshar, Abbas; Afshar, Mohammad Hadi

2018-03-01

Previous studies on consequence management assume that the selected response action including valve closure and/or hydrant opening remains unchanged during the entire management period. This study presents a new embedded simulation-optimization methodology for deriving time-varying operational response actions in which the network topology may change from one stage to another. Dynamic programming (DP) and genetic algorithm (GA) are used in order to minimize selected objective functions. Two networks of small and large sizes are used in order to illustrate the performance of the proposed modelling schemes if a time-dependent consequence management strategy is to be implemented. The results show that for a small number of decision variables even in large-scale networks, DP is superior in terms of accuracy and computer runtime. However, as the number of potential actions grows, DP loses its merit over the GA approach. This study clearly proves the priority of the proposed dynamic operation strategy over the commonly used static strategy.
Insect-Flower Interaction Network Structure Is Resilient to a Temporary Pulse of Floral Resources from Invasive Rhododendron ponticum

PubMed Central

Tiedeken, Erin Jo; Stout, Jane C.

2015-01-01

Invasive alien plants can compete with native plants for resources, and may ultimately decrease native plant diversity and/or abundance in invaded sites. This could have consequences for native mutualistic interactions, such as pollination. Although invasive plants often become highly connected in plant-pollinator interaction networks, in temperate climates they usually only flower for part of the season. Unless sufficient alternative plants flower outside this period, whole-season floral resources may be reduced by invasion. We hypothesized that the cessation of flowering of a dominant invasive plant would lead to dramatic, seasonal compositional changes in plant-pollinator communities, and subsequent changes in network structure. We investigated variation in floral resources, flower-visiting insect communities, and interaction networks during and after the flowering of invasive Rhododendron ponticum in four invaded Irish woodland sites. Floral resources decreased significantly after R. ponticum flowering, but the magnitude of the decrease varied among sites. Neither insect abundance nor richness varied between the two periods (during and after R. ponticum flowering), yet insect community composition was distinct, mostly due to a significant reduction in Bombus abundance after flowering. During flowering R. ponticum was frequently visited by Bombus; after flowering, these highly mobile pollinators presumably left to find alternative floral resources. Despite compositional changes, however, network structural properties remained stable after R. ponticum flowering ceased: generality increased, but quantitative connectance, interaction evenness, vulnerability, H’2 and network size did not change. This is likely because after R. ponticum flowering, two to three alternative plant species became prominent in networks and insects increased their diet breadth, as indicated by the increase in network-level generality. We conclude that network structure is robust to seasonal changes in floral abundance at sites invaded by alien, mass-flowering plant species, as long as alternative floral resources remain throughout the season to support the flower-visiting community. PMID:25764085
Food Web Designer: a flexible tool to visualize interaction networks.

PubMed

Sint, Daniela; Traugott, Michael

Species are embedded in complex networks of ecological interactions and assessing these networks provides a powerful approach to understand what the consequences of these interactions are for ecosystem functioning and services. This is mandatory to develop and evaluate strategies for the management and control of pests. Graphical representations of networks can help recognize patterns that might be overlooked otherwise. However, there is a lack of software which allows visualizing these complex interaction networks. Food Web Designer is a stand-alone, highly flexible and user friendly software tool to quantitatively visualize trophic and other types of bipartite and tripartite interaction networks. It is offered free of charge for use on Microsoft Windows platforms. Food Web Designer is easy to use without the need to learn a specific syntax due to its graphical user interface. Up to three (trophic) levels can be connected using links cascading from or pointing towards the taxa within each level to illustrate top-down and bottom-up connections. Link width/strength and abundance of taxa can be quantified, allowing generating fully quantitative networks. Network datasets can be imported, saved for later adjustment and the interaction webs can be exported as pictures for graphical display in different file formats. We show how Food Web Designer can be used to draw predator-prey and host-parasitoid food webs, demonstrating that this software is a simple and straightforward tool to graphically display interaction networks for assessing pest control or any other type of interaction in both managed and natural ecosystems from an ecological network perspective.
Hack's relation and optimal channel networks: The elongation of river basins as a consequence of energy minimization

NASA Astrophysics Data System (ADS)

Ijjasz-Vasquez, Ede J.; Bras, Rafael L.; Rodriguez-Iturbe, Ignacio

1993-08-01

As pointed by Hack (1957), river basins tend to become longer and narrower as their size increases. This work shows that this property may be partially regarded as the consequence of competition and minimization of energy expenditure in river basins.
The effect of a loss of model structural detail due to network skeletonization on contamination warning system design: case studies.

PubMed

Davis, Michael J; Janke, Robert

2018-01-04

The effect of limitations in the structural detail available in a network model on contamination warning system (CWS) design was examined in case studies using the original and skeletonized network models for two water distribution systems (WDSs). The skeletonized models were used as proxies for incomplete network models. CWS designs were developed by optimizing sensor placements for worst-case and mean-case contamination events. Designs developed using the skeletonized network models were transplanted into the original network model for evaluation. CWS performance was defined as the number of people who ingest more than some quantity of a contaminant in tap water before the CWS detects the presence of contamination. Lack of structural detail in a network model can result in CWS designs that (1) provide considerably less protection against worst-case contamination events than that obtained when a more complete network model is available and (2) yield substantial underestimates of the consequences associated with a contamination event. Nevertheless, CWSs developed using skeletonized network models can provide useful reductions in consequences for contaminants whose effects are not localized near the injection location. Mean-case designs can yield worst-case performances similar to those for worst-case designs when there is uncertainty in the network model. Improvements in network models for WDSs have the potential to yield significant improvements in CWS designs as well as more realistic evaluations of those designs. Although such improvements would be expected to yield improved CWS performance, the expected improvements in CWS performance have not been quantified previously. The results presented here should be useful to those responsible for the design or implementation of CWSs, particularly managers and engineers in water utilities, and encourage the development of improved network models.
The effect of a loss of model structural detail due to network skeletonization on contamination warning system design: case studies

NASA Astrophysics Data System (ADS)

Davis, Michael J.; Janke, Robert

2018-05-01

The effect of limitations in the structural detail available in a network model on contamination warning system (CWS) design was examined in case studies using the original and skeletonized network models for two water distribution systems (WDSs). The skeletonized models were used as proxies for incomplete network models. CWS designs were developed by optimizing sensor placements for worst-case and mean-case contamination events. Designs developed using the skeletonized network models were transplanted into the original network model for evaluation. CWS performance was defined as the number of people who ingest more than some quantity of a contaminant in tap water before the CWS detects the presence of contamination. Lack of structural detail in a network model can result in CWS designs that (1) provide considerably less protection against worst-case contamination events than that obtained when a more complete network model is available and (2) yield substantial underestimates of the consequences associated with a contamination event. Nevertheless, CWSs developed using skeletonized network models can provide useful reductions in consequences for contaminants whose effects are not localized near the injection location. Mean-case designs can yield worst-case performances similar to those for worst-case designs when there is uncertainty in the network model. Improvements in network models for WDSs have the potential to yield significant improvements in CWS designs as well as more realistic evaluations of those designs. Although such improvements would be expected to yield improved CWS performance, the expected improvements in CWS performance have not been quantified previously. The results presented here should be useful to those responsible for the design or implementation of CWSs, particularly managers and engineers in water utilities, and encourage the development of improved network models.
Differentiable cortical networks for inferences concerning people’s intentions versus physical causality

PubMed Central

Mason, Robert A.; Just, Marcel Adam

2010-01-01

Cortical activity associated with generating an inference was measured using fMRI. Participants read three-sentence passages that differed in whether or not an inference needed to be drawn to understand them. The inference was based on either a protagonist’s intention or a physical consequence of a character’s action. Activation was expected in Theory of Mind brain regions for the passages based on protagonists’ intentions but not for the physical consequence passages. The activation measured in the right temporo-parietal junction was greater in the intentional passages than in the consequence passages, consistent with predictions from a Theory of Mind perspective. In contrast, there was increased occipital activation in the physical inference passages. For both types of passage, the cortical activity related to the reading of the critical inference sentence demonstrated a recruitment of a common inference cortical network. This general inference-related activation appeared bilaterally in the language processing areas (the inferior frontal gyrus, the temporal gyrus, and the angular gyrus), as well as in the medial to superior frontal gyrus, which has been found to be active in Theory of Mind tasks. These findings are consistent with the hypothesis that component areas of the discourse processing network are recruited as needed based on the nature of the inference. A Protagonist monitoring and synthesis network is proposed as a more accurate account for Theory of Mind activation during narrative comprehension. PMID:21229617
Linking social and spatial networks to viral community phylogenetics reveals subtype-specific transmission dynamics in African lions.

PubMed

Fountain-Jones, Nicholas M; Packer, Craig; Troyer, Jennifer L; VanderWaal, Kimberly; Robinson, Stacie; Jacquot, Maude; Craft, Meggan E

2017-10-01

Heterogeneity within pathogen species can have important consequences for how pathogens transmit across landscapes; however, discerning different transmission routes is challenging. Here, we apply both phylodynamic and phylogenetic community ecology techniques to examine the consequences of pathogen heterogeneity on transmission by assessing subtype-specific transmission pathways in a social carnivore. We use comprehensive social and spatial network data to examine transmission pathways for three subtypes of feline immunodeficiency virus (FIV Ple ) in African lions (Panthera leo) at multiple scales in the Serengeti National Park, Tanzania. We used FIV Ple molecular data to examine the role of social organization and lion density in shaping transmission pathways and tested to what extent vertical (i.e., father- and/or mother-offspring relationships) or horizontal (between unrelated individuals) transmission underpinned these patterns for each subtype. Using the same data, we constructed subtype-specific FIV Ple co-occurrence networks and assessed what combination of social networks, spatial networks or co-infection best structured the FIV Ple network. While social organization (i.e., pride) was an important component of FIV Ple transmission pathways at all scales, we find that FIV Ple subtypes exhibited different transmission pathways at within- and between-pride scales. A combination of social and spatial networks, coupled with consideration of subtype co-infection, was likely to be important for FIV Ple transmission for the two major subtypes, but the relative contribution of each factor was strongly subtype-specific. Our study provides evidence that pathogen heterogeneity is important in understanding pathogen transmission, which could have consequences for how endemic pathogens are managed. Furthermore, we demonstrate that community phylogenetic ecology coupled with phylodynamic techniques can reveal insights into the differential evolutionary pressures acting on virus subtypes, which can manifest into landscape-level effects. © 2017 The Authors. Journal of Animal Ecology © 2017 British Ecological Society.
Network Framing of Pest Management Knowledge and Practice

ERIC Educational Resources Information Center

Moore, Keith M.

2008-01-01

Conventional technology transfer is based on the assumption that autonomous individuals independently make behavioral decisions. In contrast, Actor-Network Theory (ANT) suggests that people and technologies are interconnected in ways that reinforce and reproduce some types of knowledge and consequent behavioral practices, but not others. Research…
Troubling Consequences of Online Political Rumoring

ERIC Educational Resources Information Center

Garrett, R. Kelly

2011-01-01

Fear that the Internet promotes harmful political rumoring is merited but not for reasons originally anticipated. Although the network accelerates and widens rumor circulation, on the whole, it does not increase recipient credulity. E-mail, however, which fosters informal political communication within existing social networks, poses a unique…
The Complexity of Crime Network Data: A Case Study of Its Consequences for Crime Control and the Study of Networks

PubMed Central

Rostami, Amir; Mondani, Hernan

2015-01-01

The field of social network analysis has received increasing attention during the past decades and has been used to tackle a variety of research questions, from prevention of sexually transmitted diseases to humanitarian relief operations. In particular, social network analyses are becoming an important component in studies of criminal networks and in criminal intelligence analysis. At the same time, intelligence analyses and assessments have become a vital component of modern approaches in policing, with policy implications for crime prevention, especially in the fight against organized crime. In this study, we have a unique opportunity to examine one specific Swedish street gang with three different datasets. These datasets are the most common information sources in studies of criminal networks: intelligence, surveillance and co-offending data. We use the data sources to build networks, and compare them by computing distance, centrality, and clustering measures. This study shows the complexity factor by which different data sources about the same object of study have a fundamental impact on the results. The same individuals have different importance ranking depending on the dataset and measure. Consequently, the data source plays a vital role in grasping the complexity of the phenomenon under study. Researchers, policy makers, and practitioners should therefore pay greater attention to the biases affecting the sources of the analysis, and be cautious when drawing conclusions based on intelligence assessments and limited network data. This study contributes to strengthening social network analysis as a reliable tool for understanding and analyzing criminality and criminal networks. PMID:25775130
The complexity of crime network data: a case study of its consequences for crime control and the study of networks.

PubMed

Rostami, Amir; Mondani, Hernan

2015-01-01

The field of social network analysis has received increasing attention during the past decades and has been used to tackle a variety of research questions, from prevention of sexually transmitted diseases to humanitarian relief operations. In particular, social network analyses are becoming an important component in studies of criminal networks and in criminal intelligence analysis. At the same time, intelligence analyses and assessments have become a vital component of modern approaches in policing, with policy implications for crime prevention, especially in the fight against organized crime. In this study, we have a unique opportunity to examine one specific Swedish street gang with three different datasets. These datasets are the most common information sources in studies of criminal networks: intelligence, surveillance and co-offending data. We use the data sources to build networks, and compare them by computing distance, centrality, and clustering measures. This study shows the complexity factor by which different data sources about the same object of study have a fundamental impact on the results. The same individuals have different importance ranking depending on the dataset and measure. Consequently, the data source plays a vital role in grasping the complexity of the phenomenon under study. Researchers, policy makers, and practitioners should therefore pay greater attention to the biases affecting the sources of the analysis, and be cautious when drawing conclusions based on intelligence assessments and limited network data. This study contributes to strengthening social network analysis as a reliable tool for understanding and analyzing criminality and criminal networks.
How can we establish more successful knowledge networks in developing countries? Lessons learnt from knowledge networks in Iran.

PubMed

Yazdizadeh, Bahareh; Majdzadeh, Reza; Alami, Ali; Amrolalaei, Sima

2014-10-29

Formal knowledge networks are considered among the solutions for strengthening knowledge translation and one of the elements of innovative systems in developing and developed countries. In the year 2000, knowledge networks were established in Iran's health system to organize, lead, empower, and coordinate efforts made by health-related research centers in the country. Since the assessment of a knowledge network is one of the main requirements for its success, the current study was designed in two qualitative and quantitative sections to identify the strengths and weaknesses of the established knowledge networks and to assess their efficiency. In the qualitative section, semi-structured, in-depth interviews were held with network directors and secretaries. The interviews were analyzed through the framework approach. To analyze effectiveness, social network analysis approach was used. That is, by considering the networks' research council members as 'nodes', and the numbers of their joint articles--before and after the network establishments--as 'relations or ties', indices of density, clique, and centrality were calculated for each network. In the qualitative section, non-transparency of management, lack of goals, administrative problems were among the most prevalent issues observed. Currently, the most important challenges are the policies related to them and their management. In the quantitative section, we observed that density and clique indices had risen for some networks; however, the centrality index for the same networks was not as high. Consequently the attribution of density and clique indices to these networks was not possible. Therefore, consolidating and revising policies relevant to the networks and preparing a guide for establishing managing networks could prove helpful. To develop knowledge and technology in a country, networks need to solve the problems they face in management and governance. That is, the first step towards the realization of true knowledge networks in health system.

Information processing in echo state networks at the edge of chaos.

PubMed

Boedecker, Joschka; Obst, Oliver; Lizier, Joseph T; Mayer, N Michael; Asada, Minoru

2012-09-01

We investigate information processing in randomly connected recurrent neural networks. It has been shown previously that the computational capabilities of these networks are maximized when the recurrent layer is close to the border between a stable and an unstable dynamics regime, the so called edge of chaos. The reasons, however, for this maximized performance are not completely understood. We adopt an information-theoretical framework and are for the first time able to quantify the computational capabilities between elements of these networks directly as they undergo the phase transition to chaos. Specifically, we present evidence that both information transfer and storage in the recurrent layer are maximized close to this phase transition, providing an explanation for why guiding the recurrent layer toward the edge of chaos is computationally useful. As a consequence, our study suggests self-organized ways of improving performance in recurrent neural networks, driven by input data. Moreover, the networks we study share important features with biological systems such as feedback connections and online computation on input streams. A key example is the cerebral cortex, which was shown to also operate close to the edge of chaos. Consequently, the behavior of model systems as studied here is likely to shed light on reasons why biological systems are tuned into this specific regime.
Expanding the occupational health methodology: A concatenated artificial neural network approach to model the burnout process in Chinese nurses.

PubMed

Ladstätter, Felix; Garrosa, Eva; Moreno-Jiménez, Bernardo; Ponsoda, Vicente; Reales Aviles, José Manuel; Dai, Junming

2016-01-01

Artificial neural networks are sophisticated modelling and prediction tools capable of extracting complex, non-linear relationships between predictor (input) and predicted (output) variables. This study explores this capacity by modelling non-linearities in the hardiness-modulated burnout process with a neural network. Specifically, two multi-layer feed-forward artificial neural networks are concatenated in an attempt to model the composite non-linear burnout process. Sensitivity analysis, a Monte Carlo-based global simulation technique, is then utilised to examine the first-order effects of the predictor variables on the burnout sub-dimensions and consequences. Results show that (1) this concatenated artificial neural network approach is feasible to model the burnout process, (2) sensitivity analysis is a prolific method to study the relative importance of predictor variables and (3) the relationships among variables involved in the development of burnout and its consequences are to different degrees non-linear. Many relationships among variables (e.g., stressors and strains) are not linear, yet researchers use linear methods such as Pearson correlation or linear regression to analyse these relationships. Artificial neural network analysis is an innovative method to analyse non-linear relationships and in combination with sensitivity analysis superior to linear methods.
Is U.S. climatic diversity well represented within the existing federal protection network?

Treesearch

Enric Batllori; Carol Miller; Marc-Andre Parisien; Sean A. Parks; Max A. Moritz

2014-01-01

Establishing protection networks to ensure that biodiversity and associated ecosystem services persist under changing environments is a major challenge for conservation planning. The potential consequences of altered climates for the structure and function of ecosystems necessitates new and complementary approaches be incorporated into traditional conservation plans....
Environmental monitoring network for India

Treesearch

P.V. Sundareshwar; R. Murtugudde; G. Srinivasan; S. Singh; K.J. Ramesh; R. Ramesh; S.B. Verma; D. Agarwal; D. Baldocchi; C.K. Baru; K.K. Baruah; G.R. Chowdhury; V.K. Dadhwal; C.B.S. Dutt; J. Fuentes; Prabhat Gupta; W.W. Hardgrove; M. Howard; C.S. Jha; S. Lal; W.K. Michener; A.P. Mitra; J.T. Morris; R.R. Myneni; M. Naja; R. Nemani; R. Purvaja; S. Raha; S.K. Santhana Vanan; M. Sharma; A. Subramaniam; R. Sukumar; R.R. Twilley; P.R. Zimmerman

2007-01-01

Understanding the consequences of global environmental change and its mitigation will require an integrated global effort of comprehensive long-term data collection, synthesis, and action (1). The last decade has seen a dramatic global increase in the number of networked monitoring sites. For example, FLUXNET is a global collection of >300 micrometeorological...
Social Capital and Health in a Digital Society

ERIC Educational Resources Information Center

Sharif, Behjat A.

2007-01-01

Quality of life is directly influenced by the quality of social relationships. Social capital, a reflection of the cohesiveness of social networks, is considered a significant determinant of health outcomes. Among social beings, lack of quality social connections correlates with poor health consequences. Membership in social networks and social…
Envisioning, quantifying, and managing thermal regimes on river networks

Treesearch

E. Ashley Steel; Timothy J. Beechie; Christian E. Torgersen; Aimee H. Fullerton

2017-01-01

Water temperatures fluctuate in time and space, creating diverse thermal regimes on river networks. Temporal variability in these thermal landscapes has important biological and ecological consequences because of nonlinearities in physiological reactions; spatial diversity in thermal landscapes provides aquatic organisms with options to maximize growth and survival....
Social opinion dynamics is not chaotic

NASA Astrophysics Data System (ADS)

Lim, Chjan; Zhang, Weituo

2016-08-01

Motivated by the research on social opinion dynamics over large and dense networks, a general framework for verifying the monotonicity property of multi-agent dynamics is introduced. This allows a derivation of sociologically meaningful sufficient conditions for monotonicity that are tailor-made for social opinion dynamics, which typically have high nonlinearity. A direct consequence of monotonicity is that social opinion dynamics is nonchaotic. A key part of this framework is the definition of a partial order relation that is suitable for a large class of social opinion dynamics such as the generalized naming games. Comparisons are made to previous techniques to verify monotonicity. Using the results obtained, we extend many of the consequences of monotonicity to this class of social dynamics, including several corollaries on their asymptotic behavior, such as global convergence to consensus and tipping points of a minority fraction of zealots or leaders.
Anterior Cingulate Cortex Instigates Adaptive Switches in Choice by Integrating Immediate and Delayed Components of Value in Ventromedial Prefrontal Cortex

PubMed Central

Guitart-Masip, Marc; Kurth-Nelson, Zeb; Dolan, Raymond J.

2014-01-01

Actions can lead to an immediate reward or punishment and a complex set of delayed outcomes. Adaptive choice necessitates the brain track and integrate both of these potential consequences. Here, we designed a sequential task whereby the decision to exploit or forego an available offer was contingent on comparing immediate value and a state-dependent future cost of expending a limited resource. Crucially, the dynamics of the task demanded frequent switches in policy based on an online computation of changing delayed consequences. We found that human subjects choose on the basis of a near-optimal integration of immediate reward and delayed consequences, with the latter computed in a prefrontal network. Within this network, anterior cingulate cortex (ACC) was dynamically coupled to ventromedial prefrontal cortex (vmPFC) when adaptive switches in choice were required. Our results suggest a choice architecture whereby interactions between ACC and vmPFC underpin an integration of immediate and delayed components of value to support flexible policy switching that accommodates the potential delayed consequences of an action. PMID:24573291
Anterior cingulate cortex instigates adaptive switches in choice by integrating immediate and delayed components of value in ventromedial prefrontal cortex.

PubMed

Economides, Marcos; Guitart-Masip, Marc; Kurth-Nelson, Zeb; Dolan, Raymond J

2014-02-26

Actions can lead to an immediate reward or punishment and a complex set of delayed outcomes. Adaptive choice necessitates the brain track and integrate both of these potential consequences. Here, we designed a sequential task whereby the decision to exploit or forego an available offer was contingent on comparing immediate value and a state-dependent future cost of expending a limited resource. Crucially, the dynamics of the task demanded frequent switches in policy based on an online computation of changing delayed consequences. We found that human subjects choose on the basis of a near-optimal integration of immediate reward and delayed consequences, with the latter computed in a prefrontal network. Within this network, anterior cingulate cortex (ACC) was dynamically coupled to ventromedial prefrontal cortex (vmPFC) when adaptive switches in choice were required. Our results suggest a choice architecture whereby interactions between ACC and vmPFC underpin an integration of immediate and delayed components of value to support flexible policy switching that accommodates the potential delayed consequences of an action.
Network modules and hubs in plant-root fungal biomes

PubMed Central

Toju, Hirokazu; Yamamoto, Satoshi; Tanabe, Akifumi S.; Hayakawa, Takashi; Ishii, Hiroshi S.

2016-01-01

Terrestrial plants host phylogenetically and functionally diverse groups of below-ground microbes, whose community structure controls plant growth/survival in both natural and agricultural ecosystems. Therefore, understanding the processes by which whole root-associated microbiomes are organized is one of the major challenges in ecology and plant science. We here report that diverse root-associated fungi can form highly compartmentalized networks of coexistence within host roots and that the structure of the fungal symbiont communities can be partitioned into semi-discrete types even within a single host plant population. Illumina sequencing of root-associated fungi in a monodominant south beech forest revealed that the network representing symbiont–symbiont co-occurrence patterns was compartmentalized into clear modules, which consisted of diverse functional groups of mycorrhizal and endophytic fungi. Consequently, terminal roots of the plant were colonized by either of the two largest fungal species sets (represented by Oidiodendron or Cenococcum). Thus, species-rich root microbiomes can have alternative community structures, as recently shown in the relationships between human gut microbiome type (i.e. ‘enterotype’) and host individual health. This study also shows an analytical framework for pinpointing network hubs in symbiont–symbiont networks, leading to the working hypothesis that a small number of microbial species organize the overall root–microbiome dynamics. PMID:26962029
Silicon photonic Mach Zehnder modulators for next-generation short-reach optical communication networks

NASA Astrophysics Data System (ADS)

Lacava, C.; Liu, Z.; Thomson, D.; Ke, Li; Fedeli, J. M.; Richardson, D. J.; Reed, G. T.; Petropoulos, P.

2016-02-01

Communication traffic grows relentlessly in today's networks, and with ever more machines connected to the network, this trend is set to continue for the foreseeable future. It is widely accepted that increasingly faster communications are required at the point of the end users, and consequently optical transmission plays a progressively greater role even in short- and medium-reach networks. Silicon photonic technologies are becoming increasingly attractive for such networks, due to their potential for low cost, energetically efficient, high-speed optical components. A representative example is the silicon-based optical modulator, which has been actively studied. Researchers have demonstrated silicon modulators in different types of structures, such as ring resonators or slow light based devices. These approaches have shown remarkably good performance in terms of modulation efficiency, however their operation could be severely affected by temperature drifts or fabrication errors. Mach-Zehnder modulators (MZM), on the other hand, show good performance and resilience to different environmental conditions. In this paper we present a CMOS-compatible compact silicon MZM. We study the application of the modulator to short-reach interconnects by realizing data modulation using some relevant advanced modulation formats, such as 4-level Pulse Amplitude Modulation (PAM-4) and Discrete Multi-Tone (DMT) modulation and compare the performance of the different systems in transmission.
Intelligent model-based OPC

NASA Astrophysics Data System (ADS)

Huang, W. C.; Lai, C. M.; Luo, B.; Tsai, C. K.; Chih, M. H.; Lai, C. W.; Kuo, C. C.; Liu, R. G.; Lin, H. T.

2006-03-01

Optical proximity correction is the technique of pre-distorting mask layouts so that the printed patterns are as close to the desired shapes as possible. For model-based optical proximity correction, a lithographic model to predict the edge position (contour) of patterns on the wafer after lithographic processing is needed. Generally, segmentation of edges is performed prior to the correction. Pattern edges are dissected into several small segments with corresponding target points. During the correction, the edges are moved back and forth from the initial drawn position, assisted by the lithographic model, to finally settle on the proper positions. When the correction converges, the intensity predicted by the model in every target points hits the model-specific threshold value. Several iterations are required to achieve the convergence and the computation time increases with the increase of the required iterations. An artificial neural network is an information-processing paradigm inspired by biological nervous systems, such as how the brain processes information. It is composed of a large number of highly interconnected processing elements (neurons) working in unison to solve specific problems. A neural network can be a powerful data-modeling tool that is able to capture and represent complex input/output relationships. The network can accurately predict the behavior of a system via the learning procedure. A radial basis function network, a variant of artificial neural network, is an efficient function approximator. In this paper, a radial basis function network was used to build a mapping from the segment characteristics to the edge shift from the drawn position. This network can provide a good initial guess for each segment that OPC has carried out. The good initial guess reduces the required iterations. Consequently, cycle time can be shortened effectively. The optimization of the radial basis function network for this system was practiced by genetic algorithm, which is an artificially intelligent optimization method with a high probability to obtain global optimization. From preliminary results, the required iterations were reduced from 5 to 2 for a simple dumbbell-shape layout.
Online Social Networking and Addiction—A Review of the Psychological Literature

PubMed Central

Kuss, Daria J.; Griffiths, Mark D.

2011-01-01

Social Networking Sites (SNSs) are virtual communities where users can create individual public profiles, interact with real-life friends, and meet other people based on shared interests. They are seen as a ‘global consumer phenomenon’ with an exponential rise in usage within the last few years. Anecdotal case study evidence suggests that ‘addiction’ to social networks on the Internet may be a potential mental health problem for some users. However, the contemporary scientific literature addressing the addictive qualities of social networks on the Internet is scarce. Therefore, this literature review is intended to provide empirical and conceptual insight into the emerging phenomenon of addiction to SNSs by: (1) outlining SNS usage patterns, (2) examining motivations for SNS usage, (3) examining personalities of SNS users, (4) examining negative consequences of SNS usage, (5) exploring potential SNS addiction, and (6) exploring SNS addiction specificity and comorbidity. The findings indicate that SNSs are predominantly used for social purposes, mostly related to the maintenance of established offline networks. Moreover, extraverts appear to use social networking sites for social enhancement, whereas introverts use it for social compensation, each of which appears to be related to greater usage, as does low conscientiousness and high narcissism. Negative correlates of SNS usage include the decrease in real life social community participation and academic achievement, as well as relationship problems, each of which may be indicative of potential addiction. PMID:22016701
Stability and generalization in seed dispersal networks: a case study of frugivorous fish in Neotropical wetlands.

PubMed

Correa, Sandra Bibiana; Arujo, Joisiane K; Penha, Jerry; Nunes da Cunha, Catia; Bobier, Karen E; Anderson, Jill T

2016-08-31

When species within guilds perform similar ecological roles, functional redundancy can buffer ecosystems against species loss. Using data on the frequency of interactions between fish and fruit, we assessed whether co-occurring frugivores provide redundant seed dispersal services in three species-rich Neotropical wetlands. Our study revealed that frugivorous fishes have generalized diets; however, large-bodied fishes had greater seed dispersal breadth than small species, in some cases, providing seed dispersal services not achieved by smaller fish species. As overfishing disproportionately affects big fishes, the extirpation of these species could cause larger secondary extinctions of plant species than the loss of small specialist frugivores. To evaluate the consequences of frugivore specialization for network stability, we extracted data from 39 published seed dispersal networks of frugivorous birds, mammals and fish (our networks) across ecosystems. Our analysis of interaction frequencies revealed low frugivore specialization and lower nestedness than analyses based on binary data (presence-absence of interactions). In that case, ecosystems may be resilient to loss of any given frugivore. However, robustness to frugivore extinction declines with specialization, such that networks composed primarily of specialist frugivores are highly susceptible to the loss of generalists. In contrast with analyses of binary data, recently developed algorithms capable of modelling interaction strengths provide opportunities to enhance our understanding of complex ecological networks by accounting for heterogeneity of frugivore-fruit interactions. © 2016 The Author(s).
Stability and generalization in seed dispersal networks: a case study of frugivorous fish in Neotropical wetlands

PubMed Central

Arujo, Joisiane K.; Penha, Jerry; Nunes da Cunha, Catia

2016-01-01

When species within guilds perform similar ecological roles, functional redundancy can buffer ecosystems against species loss. Using data on the frequency of interactions between fish and fruit, we assessed whether co-occurring frugivores provide redundant seed dispersal services in three species-rich Neotropical wetlands. Our study revealed that frugivorous fishes have generalized diets; however, large-bodied fishes had greater seed dispersal breadth than small species, in some cases, providing seed dispersal services not achieved by smaller fish species. As overfishing disproportionately affects big fishes, the extirpation of these species could cause larger secondary extinctions of plant species than the loss of small specialist frugivores. To evaluate the consequences of frugivore specialization for network stability, we extracted data from 39 published seed dispersal networks of frugivorous birds, mammals and fish (our networks) across ecosystems. Our analysis of interaction frequencies revealed low frugivore specialization and lower nestedness than analyses based on binary data (presence–absence of interactions). In that case, ecosystems may be resilient to loss of any given frugivore. However, robustness to frugivore extinction declines with specialization, such that networks composed primarily of specialist frugivores are highly susceptible to the loss of generalists. In contrast with analyses of binary data, recently developed algorithms capable of modelling interaction strengths provide opportunities to enhance our understanding of complex ecological networks by accounting for heterogeneity of frugivore–fruit interactions. PMID:27581879
Inborn errors of metabolism and the human interactome: a systems medicine approach.

PubMed

Woidy, Mathias; Muntau, Ania C; Gersting, Søren W

2018-02-05

The group of inborn errors of metabolism (IEM) displays a marked heterogeneity and IEM can affect virtually all functions and organs of the human organism; however, IEM share that their associated proteins function in metabolism. Most proteins carry out cellular functions by interacting with other proteins, and thus are organized in biological networks. Therefore, diseases are rarely the consequence of single gene mutations but of the perturbations caused in the related cellular network. Systematic approaches that integrate multi-omics and database information into biological networks have successfully expanded our knowledge of complex disorders but network-based strategies have been rarely applied to study IEM. We analyzed IEM on a proteome scale and found that IEM-associated proteins are organized as a network of linked modules within the human interactome of protein interactions, the IEM interactome. Certain IEM disease groups formed self-contained disease modules, which were highly interlinked. On the other hand, we observed disease modules consisting of proteins from many different disease groups in the IEM interactome. Moreover, we explored the overlap between IEM and non-IEM disease genes and applied network medicine approaches to investigate shared biological pathways, clinical signs and symptoms, and links to drug targets. The provided resources may help to elucidate the molecular mechanisms underlying new IEM, to uncover the significance of disease-associated mutations, to identify new biomarkers, and to develop novel therapeutic strategies.
Online social networking and addiction--a review of the psychological literature.

PubMed

Kuss, Daria J; Griffiths, Mark D

2011-09-01

Social Networking Sites (SNSs) are virtual communities where users can create individual public profiles, interact with real-life friends, and meet other people based on shared interests. They are seen as a 'global consumer phenomenon' with an exponential rise in usage within the last few years. Anecdotal case study evidence suggests that 'addiction' to social networks on the Internet may be a potential mental health problem for some users. However, the contemporary scientific literature addressing the addictive qualities of social networks on the Internet is scarce. Therefore, this literature review is intended to provide empirical and conceptual insight into the emerging phenomenon of addiction to SNSs by: (1) outlining SNS usage patterns, (2) examining motivations for SNS usage, (3) examining personalities of SNS users, (4) examining negative consequences of SNS usage, (5) exploring potential SNS addiction, and (6) exploring SNS addiction specificity and comorbidity. The findings indicate that SNSs are predominantly used for social purposes, mostly related to the maintenance of established offline networks. Moreover, extraverts appear to use social networking sites for social enhancement, whereas introverts use it for social compensation, each of which appears to be related to greater usage, as does low conscientiousness and high narcissism. Negative correlates of SNS usage include the decrease in real life social community participation and academic achievement, as well as relationship problems, each of which may be indicative of potential addiction.
Many-objective Groundwater Monitoring Network Design Using Bias-Aware Ensemble Kalman Filtering and Evolutionary Optimization

NASA Astrophysics Data System (ADS)

Kollat, J. B.; Reed, P. M.

2009-12-01

This study contributes the ASSIST (Adaptive Strategies for Sampling in Space and Time) framework for improving long-term groundwater monitoring decisions across space and time while accounting for the influences of systematic model errors (or predictive bias). The ASSIST framework combines contaminant flow-and-transport modeling, bias-aware ensemble Kalman filtering (EnKF) and many-objective evolutionary optimization. Our goal in this work is to provide decision makers with a fuller understanding of the information tradeoffs they must confront when performing long-term groundwater monitoring network design. Our many-objective analysis considers up to 6 design objectives simultaneously and consequently synthesizes prior monitoring network design methodologies into a single, flexible framework. This study demonstrates the ASSIST framework using a tracer study conducted within a physical aquifer transport experimental tank located at the University of Vermont. The tank tracer experiment was extensively sampled to provide high resolution estimates of tracer plume behavior. The simulation component of the ASSIST framework consists of stochastic ensemble flow-and-transport predictions using ParFlow coupled with the Lagrangian SLIM transport model. The ParFlow and SLIM ensemble predictions are conditioned with tracer observations using a bias-aware EnKF. The EnKF allows decision makers to enhance plume transport predictions in space and time in the presence of uncertain and biased model predictions by conditioning them on uncertain measurement data. In this initial demonstration, the position and frequency of sampling were optimized to: (i) minimize monitoring cost, (ii) maximize information provided to the EnKF, (iii) minimize failure to detect the tracer, (iv) maximize the detection of tracer flux, (v) minimize error in quantifying tracer mass, and (vi) minimize error in quantifying the moment of the tracer plume. The results demonstrate that the many-objective problem formulation provides a tremendous amount of information for decision makers. Specifically our many-objective analysis highlights the limitations and potentially negative design consequences of traditional single and two-objective problem formulations. These consequences become apparent through visual exploration of high-dimensional tradeoffs and the identification of regions with interesting compromise solutions. The prediction characteristics of these compromise designs are explored in detail, as well as their implications for subsequent design decisions in both space and time.
Investigating the consequences of urban volcanism using a scenario approach I: Development and application of a hypothetical eruption in the Auckland Volcanic Field, New Zealand

NASA Astrophysics Data System (ADS)

Deligne, Natalia I.; Fitzgerald, Rebecca H.; Blake, Daniel M.; Davies, Alistair J.; Hayes, Josh L.; Stewart, Carol; Wilson, Grant; Wilson, Thomas M.; Castelino, Renella; Kennedy, Ben M.; Muspratt, Scott; Woods, Richard

2017-04-01

What happens when a city has a volcanic eruption within its boundaries? To explore the consequences of this rare but potentially catastrophic combination, we develop a detailed multi-hazard scenario of an Auckland Volcanic Field (AVF) eruption; the AVF underlies New Zealand's largest city, Auckland. We start with an existing AVF unrest scenario sequence and develop it through a month-long hypothetical eruption based on geologic investigations of the AVF and historic similar eruptions from around the world. We devise a credible eruption sequence and include all volcanic hazards that could occur in an AVF eruption. In consultation with Civil Defence and Emergency Management staff, we create a series of evacuation maps for before, during, and after the hypothetical eruption sequence. Our result is a versatile scenario with many possible applications, developed further in companion papers that explore eruption consequences on transportation and water networks. However, here we illustrate one application: evaluating the consequences of an eruption on electricity service provision. In a collaborative approach between scientists and electricity service providers, we evaluate the impact of the hypothetical eruption to electricity generation, transmission, and distribution infrastructure. We then evaluate how the impacted network functions, accounting for network adaptations (e.g., diverting power away from evacuated areas), site access, and restoration factors. We present a series of regional maps showing areas with full service, rolling outages, and no power as a result of the eruption. This illustrative example demonstrates how a detailed scenario can be used to further understand the ramifications of urban volcanism on local and regional populations, and highlights the importance of looking beyond damage to explore the consequences of volcanism.
A Stochastic Spiking Neural Network for Virtual Screening.

PubMed

Morro, A; Canals, V; Oliver, A; Alomar, M L; Galan-Prado, F; Ballester, P J; Rossello, J L

2018-04-01

Virtual screening (VS) has become a key computational tool in early drug design and screening performance is of high relevance due to the large volume of data that must be processed to identify molecules with the sought activity-related pattern. At the same time, the hardware implementations of spiking neural networks (SNNs) arise as an emerging computing technique that can be applied to parallelize processes that normally present a high cost in terms of computing time and power. Consequently, SNN represents an attractive alternative to perform time-consuming processing tasks, such as VS. In this brief, we present a smart stochastic spiking neural architecture that implements the ultrafast shape recognition (USR) algorithm achieving two order of magnitude of speed improvement with respect to USR software implementations. The neural system is implemented in hardware using field-programmable gate arrays allowing a highly parallelized USR implementation. The results show that, due to the high parallelization of the system, millions of compounds can be checked in reasonable times. From these results, we can state that the proposed architecture arises as a feasible methodology to efficiently enhance time-consuming data-mining processes such as 3-D molecular similarity search.

The microeconomics of residential photovoltaics: Tariffs, network operation and maintenance, and ancillary services in distribution-level electricity markets

DOE Office of Scientific and Technical Information (OSTI.GOV)

Boero, Riccardo; Backhaus, Scott N.; Edwards, Brian K.

Here, we develop a microeconomic model of a distribution-level electricity market that takes explicit account of residential photovoltaics (PV) adoption. The model allows us to study the consequences of most tariffs on PV adoption and the consequences of increased residential PV adoption under the assumption of economic sustainability for electric utilities. We also validated the model using U.S. data and extend it to consider different pricing schemes for operation and maintenance costs of the distribution network and for ancillary services. Results show that net metering promotes more environmental benefits and social welfare than other tariffs. But, if costs to operatemore » the distribution network increase, net metering will amplify the unequal distribution of surplus among households. In conclusion, maintaining the economic sustainability of electric utilities under net metering may become extremely difficult unless the uneven distribution of surplus is legitimated by environmental benefits.« less
Mitigation of the consequence of seismically induced damage on a utility water network by means of next generation SCADA

NASA Astrophysics Data System (ADS)

Robertson, Jamie; Shinozuka, Masanobu; Wu, Felix

2011-04-01

When a lifeline system such as a water delivery network is damaged due to a severe earthquake, it is critical to identify its location and extent of the damage in real time in order to minimize the potentially disastrous consequence such damage could otherwise entail. This paper demonstrates how the degree of such minimization can be estimated qualitatively by using the water delivery system of Irvine Water Ranch District (IRWD) as testbed, when it is subjected to magnitude 6.6 San Joaquin Hills Earthquake. In this demonstration, we consider two cases when the IRWD system is equipped or not equipped with a next generation SCADA which consists of a network of MEMS acceleration sensors densely populated and optimally located. These sensors are capable of identifying the location and extent of the damage as well as transmitting the data to the SCADA center for monitoring and control.
The microeconomics of residential photovoltaics: Tariffs, network operation and maintenance, and ancillary services in distribution-level electricity markets

DOE PAGES

Boero, Riccardo; Backhaus, Scott N.; Edwards, Brian K.

2016-11-12

Here, we develop a microeconomic model of a distribution-level electricity market that takes explicit account of residential photovoltaics (PV) adoption. The model allows us to study the consequences of most tariffs on PV adoption and the consequences of increased residential PV adoption under the assumption of economic sustainability for electric utilities. We also validated the model using U.S. data and extend it to consider different pricing schemes for operation and maintenance costs of the distribution network and for ancillary services. Results show that net metering promotes more environmental benefits and social welfare than other tariffs. But, if costs to operatemore » the distribution network increase, net metering will amplify the unequal distribution of surplus among households. In conclusion, maintaining the economic sustainability of electric utilities under net metering may become extremely difficult unless the uneven distribution of surplus is legitimated by environmental benefits.« less
Integrated modelling for the evaluation of infiltration effects.

PubMed

Schulz, N; Baur, R; Krebs, P

2005-01-01

The objective of the present study is the estimation of the potential benefits of sewer pipe rehabilitation for the performance of the drainage system and the wastewater treatment plant (WWTP) as well as for the receiving water quality. The relation of sewer system status and the infiltration rate is assessed based on statistical analysis of 470 km of CCTV (Closed Circuit Television) inspected sewers of the city of Dresden. The potential reduction of infiltration rates and the consequent performance improvements of the urban wastewater system are simulated as a function of rehabilitation activities in the network. The integrated model is applied to an artificial system with input from a real sewer network. In this paper, the general design of the integrated model and its data requirements are presented. For an exemplary study, the consequences of the simulations are discussed with respect to the prioritisation of rehabilitation activities in the network.
Evaluation of QoS supported in Network Mobility NEMO environments

NASA Astrophysics Data System (ADS)

Hussien, L. F.; Abdalla, A. H.; Habaebi, M. H.; Khalifa, O. O.; Hassan, W. H.

2013-12-01

Network mobility basic support (NEMO BS) protocol is an entire network, roaming as a unit which changes its point of attachment to the Internet and consequently its reachability in the network topology. NEMO BS doesn't provide QoS guarantees to its users same as traditional Internet IP and Mobile IPv6 as well. Typically, all the users will have same level of services without considering about their application requirements. This poses a problem to real-time applications that required QoS guarantees. To gain more effective control of the network, incorporated QoS is needed. Within QoS-enabled network the traffic flow can be distributed to various priorities. Also, the network bandwidth and resources can be allocated to different applications and users. Internet Engineering Task Force (IETF) working group has proposed several QoS solutions for static network such as IntServ, DiffServ and MPLS. These QoS solutions are designed in the context of a static environment (i.e. fixed hosts and networks). However, they are not fully adapted to mobile environments. They essentially demands to be extended and adjusted to meet up various challenges involved in mobile environments. With existing QoS mechanisms many proposals have been developed to provide QoS for individual mobile nodes (i.e. host mobility). In contrary, research based on the movement of the whole mobile network in IPv6 is still undertaking by the IETF working groups (i.e. network mobility). Few researches have been done in the area of providing QoS for roaming networks. Therefore, this paper aims to review and investigate (previous /and current) related works that have been developed to provide QoS in mobile network. Consequently, a new proposed scheme will be introduced to enhance QoS within NEMO environment, achieving by which seamless mobility to users of mobile network node (MNN).
Resonant UPS topologies for the emerging hybrid fiber-coaxial networks

NASA Astrophysics Data System (ADS)

Pinheiro, Humberto

Uninterruptible power supply (UPS) systems have been extensively applied to feed critical loads in many areas. Typical examples of critical loads include life-support equipment, computers and telecommunication systems. Although all UPS systems have a common purpose to provide continuous power-to critical loads, the emerging hybrid fiber-coaxial networks have created the need for specific types of UPS topologies. For example, galvanic isolation for the load and the battery, small size, high input power factor, and trapezoidal output voltage waveforms are among the required features of UPS topologies for hybrid fiber-coaxial networks. None of the conventional UPS topologies meet all these requirements. Consequently. this thesis is directed towards the design and analysis of UPS topologies for this new application. Novel UPS topologies are proposed and control techniques are developed to allow operation at high switching frequencies without penalizing the converter efficiency. By the use of resonant converters in the proposed UPS topologies. a high input power factor is achieved without requiring a dedicated power factor correction stage. In addition, a self-sustained oscillation control method is proposed to ensure soft switching under all operating conditions. A detailed analytical treatment of the resonant converters in the proposed UPS topologies is presented and design procedures illustrated. Simulation and experimental results are presented to validate the analyses and to demonstrate the feasibility of the proposed schemes.
Key role of coupling, delay, and noise in resting brain fluctuations

PubMed Central

Deco, Gustavo; Jirsa, Viktor; McIntosh, A. R.; Sporns, Olaf; Kötter, Rolf

2009-01-01

A growing body of neuroimaging research has documented that, in the absence of an explicit task, the brain shows temporally coherent activity. This so-called “resting state” activity or, more explicitly, the default-mode network, has been associated with daydreaming, free association, stream of consciousness, or inner rehearsal in humans, but similar patterns have also been found under anesthesia and in monkeys. Spatiotemporal activity patterns in the default-mode network are both complex and consistent, which raises the question whether they are the expression of an interesting cognitive architecture or the consequence of intrinsic network constraints. In numerical simulation, we studied the dynamics of a simplified cortical network using 38 noise-driven (Wilson–Cowan) oscillators, which in isolation remain just below their oscillatory threshold. Time delay coupling based on lengths and strengths of primate corticocortical pathways leads to the emergence of 2 sets of 40-Hz oscillators. The sets showed synchronization that was anticorrelated at <0.1 Hz across the sets in line with a wide range of recent experimental observations. Systematic variation of conduction velocity, coupling strength, and noise level indicate a high sensitivity of emerging synchrony as well as simulated blood flow blood oxygen level-dependent (BOLD) on the underlying parameter values. Optimal sensitivity was observed around conduction velocities of 1–2 m/s, with very weak coupling between oscillators. An additional finding was that the optimal noise level had a characteristic scale, indicating the presence of stochastic resonance, which allows the network dynamics to respond with high sensitivity to changes in diffuse feedback activity. PMID:19497858
Predictive Coding of Dynamical Variables in Balanced Spiking Networks

PubMed Central

Boerlin, Martin; Machens, Christian K.; Denève, Sophie

2013-01-01

Two observations about the cortex have puzzled neuroscientists for a long time. First, neural responses are highly variable. Second, the level of excitation and inhibition received by each neuron is tightly balanced at all times. Here, we demonstrate that both properties are necessary consequences of neural networks that represent information efficiently in their spikes. We illustrate this insight with spiking networks that represent dynamical variables. Our approach is based on two assumptions: We assume that information about dynamical variables can be read out linearly from neural spike trains, and we assume that neurons only fire a spike if that improves the representation of the dynamical variables. Based on these assumptions, we derive a network of leaky integrate-and-fire neurons that is able to implement arbitrary linear dynamical systems. We show that the membrane voltage of the neurons is equivalent to a prediction error about a common population-level signal. Among other things, our approach allows us to construct an integrator network of spiking neurons that is robust against many perturbations. Most importantly, neural variability in our networks cannot be equated to noise. Despite exhibiting the same single unit properties as widely used population code models (e.g. tuning curves, Poisson distributed spike trains), balanced networks are orders of magnitudes more reliable. Our approach suggests that spikes do matter when considering how the brain computes, and that the reliability of cortical representations could have been strongly underestimated. PMID:24244113
Rapid high-amplitude circumferential slow wave propagation during normal gastric pacemaking and dysrhythmias

PubMed Central

O'Grady, Gregory; Du, Peng; Paskaranandavadivel, Nira; Angeli, Timothy R.; Lammers, Wim JEP; Asirvatham, Samuel J.; Windsor, John A.; Farrugia, Gianrico; Pullan, Andrew J.; Cheng, Leo K.

2012-01-01

Background Gastric slow waves propagate aborally as rings of excitation. Circumferential propagation does not normally occur, except at the pacemaker region. We hypothesized that: i) the unexplained high-velocity, high-amplitude activity associated with the pacemaker region is a consequence of circumferential propagation; ii) rapid, high-amplitude circumferential propagation emerges during gastric dysrhythmias; iii) the driving network conductance might switch between ICC-MP and circular ICC-IM during circumferential propagation; iv) extracellular amplitudes and velocities are correlated. Methods An experimental-theoretical study was performed. HR gastric mapping was performed in pigs during normal activation, pacing and dysrhythmia. Activation profiles, velocities and amplitudes were quantified. ICC pathways were theoretically evaluated in a bidomain model. Extracellular potentials were modelled as a function of membrane potentials. Key Results High-velocity, high-amplitude activation was only recorded in the pacemaker region when circumferential conduction occurred. Circumferential propagation accompanied dysrhythmia in 8/8 experiments, was faster than longitudinal propagation (8.9 vs 6.9 mm/s; p=0.004), and of higher amplitude (739 vs 528 μV; p=0.007). Simulations predicted that ICC-MP could be the driving network during longitudinal propagation, whereas during ectopic pacemaking, ICC-IM could outpace and activate ICC-MP in the circumferential axis. Experimental and modeling data demonstrated a linear relationship between velocities and amplitudes (p<0.001). Conclusions & Inferences The high-velocity and high-amplitude profile of the normal pacemaker region is due to localized circumferential propagation. Rapid circumferential propagation also emerges during a range of gastric dysrhythmias, elevating extracellular amplitudes and organizing transverse wavefronts. One possible explanation for these findings is bidirectional coupling between ICC-MP and circular ICC-IM networks. PMID:22709238
Quantifying randomness in real networks

NASA Astrophysics Data System (ADS)

Orsini, Chiara; Dankulov, Marija M.; Colomer-de-Simón, Pol; Jamakovic, Almerima; Mahadevan, Priya; Vahdat, Amin; Bassler, Kevin E.; Toroczkai, Zoltán; Boguñá, Marián; Caldarelli, Guido; Fortunato, Santo; Krioukov, Dmitri

2015-10-01

Represented as graphs, real networks are intricate combinations of order and disorder. Fixing some of the structural properties of network models to their values observed in real networks, many other properties appear as statistical consequences of these fixed observables, plus randomness in other respects. Here we employ the dk-series, a complete set of basic characteristics of the network structure, to study the statistical dependencies between different network properties. We consider six real networks--the Internet, US airport network, human protein interactions, technosocial web of trust, English word network, and an fMRI map of the human brain--and find that many important local and global structural properties of these networks are closely reproduced by dk-random graphs whose degree distributions, degree correlations and clustering are as in the corresponding real network. We discuss important conceptual, methodological, and practical implications of this evaluation of network randomness, and release software to generate dk-random graphs.
Drivers potentially influencing host-bat fly interactions in anthropogenic neotropical landscapes at different spatial scales.

PubMed

Hernández-Martínez, Jacqueline; Morales-Malacara, Juan B; Alvarez-Añorve, Mariana Yolotl; Amador-Hernández, Sergio; Oyama, Ken; Avila-Cabadilla, Luis Daniel

2018-05-21

The anthropogenic modification of natural landscapes, and the consequent changes in the environmental conditions and resources availability at multiple spatial scales can affect complex species interactions involving key-stone species such as bat-parasite interactions. In this study, we aimed to identify the drivers potentially influencing host-bat fly interactions at different spatial scales (at the host, vegetation stand and landscape level), in a tropical anthropogenic landscape. For this purpose, we mist-netted phyllostomid and moormopid bats and collected the bat flies (streblids) parasitizing them in 10 sites representing secondary and old growth forest. In general, the variation in fly communities largely mirrored the variation in bat communities as a result of the high level of specialization characterizing host-bat fly interaction networks. Nevertheless, we observed that: (1) bats roosting dynamics can shape bat-streblid interactions, modulating parasite prevalence and the intensity of infestation; (2) a degraded matrix could favor crowding and consequently the exchange of ectoparasites among bat species, lessening the level of specialization of the interaction networks and promoting novel interactions; and (3) bat-fly interaction can also be shaped by the dilution effect, as a decrease in bat diversity could be associated with a potential increase in the dissemination and prevalence of streblids.
Passenger rail security, planning, and resilience: application of network, plume, and economic simulation models as decision support tools.

PubMed

Greenberg, Michael; Lioy, Paul; Ozbas, Birnur; Mantell, Nancy; Isukapalli, Sastry; Lahr, Michael; Altiok, Tayfur; Bober, Joseph; Lacy, Clifton; Lowrie, Karen; Mayer, Henry; Rovito, Jennifer

2013-11-01

We built three simulation models that can assist rail transit planners and operators to evaluate high and low probability rail-centered hazard events that could lead to serious consequences for rail-centered networks and their surrounding regions. Our key objective is to provide these models to users who, through planning with these models, can prevent events or more effectively react to them. The first of the three models is an industrial systems simulation tool that closely replicates rail passenger traffic flows between New York Penn Station and Trenton, New Jersey. Second, we built and used a line source plume model to trace chemical plumes released by a slow-moving freight train that could impact rail passengers, as well as people in surrounding areas. Third, we crafted an economic simulation model that estimates the regional economic consequences of a variety of rail-related hazard events through the year 2020. Each model can work independently of the others. However, used together they help provide a coherent story about what could happen and set the stage for planning that should make rail-centered transport systems more resistant and resilient to hazard events. We highlight the limitations and opportunities presented by using these models individually or in sequence. © 2013 Society for Risk Analysis.
Passenger Rail Security, Planning, and Resilience: Application of Network, Plume, and Economic Simulation Models as Decision Support Tools

PubMed Central

Greenberg, Michael; Lioy, Paul; Ozbas, Birnur; Mantell, Nancy; Isukapalli, Sastry; Lahr, Michael; Altiok, Tayfur; Bober, Joseph; Lacy, Clifton; Lowrie, Karen; Mayer, Henry; Rovito, Jennifer

2014-01-01

We built three simulation models that can assist rail transit planners and operators to evaluate high and low probability rail-centered hazard events that could lead to serious consequences for rail-centered networks and their surrounding regions. Our key objective is to provide these models to users who, through planning with these models, can prevent events or more effectively react to them. The first of the three models is an industrial systems simulation tool that closely replicates rail passenger traffic flows between New York Penn Station and Trenton, New Jersey. Second, we built and used a line source plume model to trace chemical plumes released by a slow-moving freight train that could impact rail passengers, as well as people in surrounding areas. Third, we crafted an economic simulation model that estimates the regional economic consequences of a variety of rail-related hazard events through the year 2020. Each model can work independently of the others. However, used together they help provide a coherent story about what could happen and set the stage for planning that should make rail-centered transport systems more resistant and resilient to hazard events. We highlight the limitations and opportunities presented by using these models individually or in sequence. PMID:23718133
Development of gridded solar radiation data over Belgium based on Meteosat and in-situ observations

NASA Astrophysics Data System (ADS)

Journée, Michel; Vanderveken, Gilles; Bertrand, Cédric

2013-04-01

Knowledge on solar resources is highly important for all forms of solar energy applications. With the recent development in solar-based technologies national meteorological services are faced with increasing demands for high-quality and reliable site-time specific solar resource information. Traditionally, solar radiation is observed by means of networks of meteorological stations. Costs for installation and maintenance of such networks are very high and national networks comprise only few stations. Consequently the availability of ground-based solar radiation measurements has proven to be spatially and temporally inadequate for many applications. To overcome such a limitation, a major effort has been undertaken at the Royal Meteorological Institute of Belgium (RMI) to provide the solar energy industry, the electricity sector, governments, and renewable energy organizations and institutions with the most suitable and accurate information on the solar radiation resources at the Earth's surface over the Belgian territory. Only space-based observations can deliver a global coverage of the solar irradiation impinging on horizontal surface at the ground level. Because only geostationary data allow to capture the diurnal cycle of the solar irradiance at the Earth's surface, a method that combines information from Meteosat Second Generation satellites and ground-measurement has been implemented at RMI to generate high resolution solar products over Belgium on an operational basis. Besides these new products, the annual and seasonal variability of solar energy resource was evaluated, solar radiation climate zones were defined and the recent trend in solar radiation was characterized.
The Widening Gulf between Genomics Data Generation and Consumption: A Practical Guide to Big Data Transfer Technology.

PubMed

Feltus, Frank A; Breen, Joseph R; Deng, Juan; Izard, Ryan S; Konger, Christopher A; Ligon, Walter B; Preuss, Don; Wang, Kuang-Ching

2015-01-01

In the last decade, high-throughput DNA sequencing has become a disruptive technology and pushed the life sciences into a distributed ecosystem of sequence data producers and consumers. Given the power of genomics and declining sequencing costs, biology is an emerging "Big Data" discipline that will soon enter the exabyte data range when all subdisciplines are combined. These datasets must be transferred across commercial and research networks in creative ways since sending data without thought can have serious consequences on data processing time frames. Thus, it is imperative that biologists, bioinformaticians, and information technology engineers recalibrate data processing paradigms to fit this emerging reality. This review attempts to provide a snapshot of Big Data transfer across networks, which is often overlooked by many biologists. Specifically, we discuss four key areas: 1) data transfer networks, protocols, and applications; 2) data transfer security including encryption, access, firewalls, and the Science DMZ; 3) data flow control with software-defined networking; and 4) data storage, staging, archiving and access. A primary intention of this article is to orient the biologist in key aspects of the data transfer process in order to frame their genomics-oriented needs to enterprise IT professionals.
Topological and statistical analyses of gene regulatory networks reveal unifying yet quantitatively different emergent properties.

PubMed

Ouma, Wilberforce Zachary; Pogacar, Katja; Grotewold, Erich

2018-04-01

Understanding complexity in physical, biological, social and information systems is predicated on describing interactions amongst different components. Advances in genomics are facilitating the high-throughput identification of molecular interactions, and graphs are emerging as indispensable tools in explaining how the connections in the network drive organismal phenotypic plasticity. Here, we describe the architectural organization and associated emergent topological properties of gene regulatory networks (GRNs) that describe protein-DNA interactions (PDIs) in several model eukaryotes. By analyzing GRN connectivity, our results show that the anticipated scale-free network architectures are characterized by organism-specific power law scaling exponents. These exponents are independent of the fraction of the GRN experimentally sampled, enabling prediction of properties of the complete GRN for an organism. We further demonstrate that the exponents describe inequalities in transcription factor (TF)-target gene recognition across GRNs. These observations have the important biological implication that they predict the existence of an intrinsic organism-specific trans and/or cis regulatory landscape that constrains GRN topologies. Consequently, architectural GRN organization drives not only phenotypic plasticity within a species, but is also likely implicated in species-specific phenotype.
A Drug-Sensitive Genetic Network Masks Fungi from the Immune System

PubMed Central

Wheeler, Robert T; Fink, Gerald R

2006-01-01

Fungal pathogens can be recognized by the immune system via their β-glucan, a potent proinflammatory molecule that is present at high levels but is predominantly buried beneath a mannoprotein coat and invisible to the host. To investigate the nature and significance of “masking” this molecule, we characterized the mechanism of masking and consequences of unmasking for immune recognition. We found that the underlying β-glucan in the cell wall of Candida albicans is unmasked by subinhibitory doses of the antifungal drug caspofungin, causing the exposed fungi to elicit a stronger immune response. Using a library of bakers' yeast (Saccharomyces cerevisiae) mutants, we uncovered a conserved genetic network that is required for concealing β-glucan from the immune system and limiting the host response. Perturbation of parts of this network in the pathogen C. albicans caused unmasking of its β-glucan, leading to increased β-glucan receptor-dependent elicitation of key proinflammatory cytokines from primary mouse macrophages. By creating an anti-inflammatory barrier to mask β-glucan, opportunistic fungi may promote commensal colonization and have an increased propensity for causing disease. Targeting the widely conserved gene network required for creating and maintaining this barrier may lead to novel broad-spectrum antimycotics. PMID:16652171
Multi-Agent Market Modeling of Foreign Exchange Rates

NASA Astrophysics Data System (ADS)

Zimmermann, Georg; Neuneier, Ralph; Grothmann, Ralph

A market mechanism is basically driven by a superposition of decisions of many agents optimizing their profit. The oeconomic price dynamic is a consequence of the cumulated excess demand/supply created on this micro level. The behavior analysis of a small number of agents is well understood through the game theory. In case of a large number of agents one may use the limiting case that an individual agent does not have an influence on the market, which allows the aggregation of agents by statistic methods. In contrast to this restriction, we can omit the assumption of an atomic market structure, if we model the market through a multi-agent approach. The contribution of the mathematical theory of neural networks to the market price formation is mostly seen on the econometric side: neural networks allow the fitting of high dimensional nonlinear dynamic models. Furthermore, in our opinion, there is a close relationship between economics and the modeling ability of neural networks because a neuron can be interpreted as a simple model of decision making. With this in mind, a neural network models the interaction of many decisions and, hence, can be interpreted as the price formation mechanism of a market.
The (in)adequacy of applicative use of quantum cryptography in wireless sensor networks

NASA Astrophysics Data System (ADS)

Turkanović, Muhamed; Hölbl, Marko

2014-10-01

Recently quantum computation and cryptography principles are exploited in the design of security systems for wireless sensor networks (WSNs), which are consequently named as quantum WSN. Quantum cryptography is presumably secure against any eavesdropper and thus labeled as providing unconditional security. This paper tries to analyze the aspect of the applicative use of quantum principles in WSN. The outcome of the analysis elaborates a summary about the inadequacy of applicative use of quantum cryptography in WSN and presents an overview of all possible applicative challenges and problems while designing quantum-based security systems for WSN. Since WSNs are highly complex frameworks, with many restrictions and constraints, every security system has to be fully compatible and worthwhile. The aim of the paper was to contribute a verdict about this topic, backed up by equitable facts.
Characterizing steady states of genome-scale metabolic networks in continuous cell cultures.

PubMed

Fernandez-de-Cossio-Diaz, Jorge; Leon, Kalet; Mulet, Roberto

2017-11-01

In the continuous mode of cell culture, a constant flow carrying fresh media replaces culture fluid, cells, nutrients and secreted metabolites. Here we present a model for continuous cell culture coupling intra-cellular metabolism to extracellular variables describing the state of the bioreactor, taking into account the growth capacity of the cell and the impact of toxic byproduct accumulation. We provide a method to determine the steady states of this system that is tractable for metabolic networks of arbitrary complexity. We demonstrate our approach in a toy model first, and then in a genome-scale metabolic network of the Chinese hamster ovary cell line, obtaining results that are in qualitative agreement with experimental observations. We derive a number of consequences from the model that are independent of parameter values. The ratio between cell density and dilution rate is an ideal control parameter to fix a steady state with desired metabolic properties. This conclusion is robust even in the presence of multi-stability, which is explained in our model by a negative feedback loop due to toxic byproduct accumulation. A complex landscape of steady states emerges from our simulations, including multiple metabolic switches, which also explain why cell-line and media benchmarks carried out in batch culture cannot be extrapolated to perfusion. On the other hand, we predict invariance laws between continuous cell cultures with different parameters. A practical consequence is that the chemostat is an ideal experimental model for large-scale high-density perfusion cultures, where the complex landscape of metabolic transitions is faithfully reproduced.

Characterizing steady states of genome-scale metabolic networks in continuous cell cultures

PubMed Central

Leon, Kalet; Mulet, Roberto

2017-01-01

In the continuous mode of cell culture, a constant flow carrying fresh media replaces culture fluid, cells, nutrients and secreted metabolites. Here we present a model for continuous cell culture coupling intra-cellular metabolism to extracellular variables describing the state of the bioreactor, taking into account the growth capacity of the cell and the impact of toxic byproduct accumulation. We provide a method to determine the steady states of this system that is tractable for metabolic networks of arbitrary complexity. We demonstrate our approach in a toy model first, and then in a genome-scale metabolic network of the Chinese hamster ovary cell line, obtaining results that are in qualitative agreement with experimental observations. We derive a number of consequences from the model that are independent of parameter values. The ratio between cell density and dilution rate is an ideal control parameter to fix a steady state with desired metabolic properties. This conclusion is robust even in the presence of multi-stability, which is explained in our model by a negative feedback loop due to toxic byproduct accumulation. A complex landscape of steady states emerges from our simulations, including multiple metabolic switches, which also explain why cell-line and media benchmarks carried out in batch culture cannot be extrapolated to perfusion. On the other hand, we predict invariance laws between continuous cell cultures with different parameters. A practical consequence is that the chemostat is an ideal experimental model for large-scale high-density perfusion cultures, where the complex landscape of metabolic transitions is faithfully reproduced. PMID:29131817
Spatial and Social Networks in Organizational Innovation

ERIC Educational Resources Information Center

Wineman, Jean D.; Kabo, Felichism W.; Davis, Gerald F.

2009-01-01

Research on the enabling factors of innovation has focused on either the social component of organizations or on the spatial dimensions involved in the innovation process. But no one has examined the aggregate consequences of the link from spatial layout, to social networks, to innovation. This project enriches our understanding of how innovation…
Effects of Aging and Adult-Onset Hearing Loss on Cortical Auditory Regions

PubMed Central

Cardin, Velia

2016-01-01

Hearing loss is a common feature in human aging. It has been argued that dysfunctions in central processing are important contributing factors to hearing loss during older age. Aging also has well documented consequences for neural structure and function, but it is not clear how these effects interact with those that arise as a consequence of hearing loss. This paper reviews the effects of aging and adult-onset hearing loss in the structure and function of cortical auditory regions. The evidence reviewed suggests that aging and hearing loss result in atrophy of cortical auditory regions and stronger engagement of networks involved in the detection of salient events, adaptive control and re-allocation of attention. These cortical mechanisms are engaged during listening in effortful conditions in normal hearing individuals. Therefore, as a consequence of aging and hearing loss, all listening becomes effortful and cognitive load is constantly high, reducing the amount of available cognitive resources. This constant effortful listening and reduced cognitive spare capacity could be what accelerates cognitive decline in older adults with hearing loss. PMID:27242405
Differentiable cortical networks for inferences concerning people's intentions versus physical causality.

PubMed

Mason, Robert A; Just, Marcel Adam

2011-02-01

Cortical activity associated with generating an inference was measured using fMRI. Participants read three-sentence passages that differed in whether or not an inference needed to be drawn to understand them. The inference was based on either a protagonist's intention or a physical consequence of a character's action. Activation was expected in Theory of Mind brain regions for the passages based on protagonists' intentions but not for the physical consequence passages. The activation measured in the right temporo-parietal junction was greater in the intentional passages than in the consequence passages, consistent with predictions from a Theory of Mind perspective. In contrast, there was increased occipital activation in the physical inference passages. For both types of passage, the cortical activity related to the reading of the critical inference sentence demonstrated a recruitment of a common inference cortical network. This general inference-related activation appeared bilaterally in the language processing areas (the inferior frontal gyrus, the temporal gyrus, and the angular gyrus), as well as in the medial to superior frontal gyrus, which has been found to be active in Theory of Mind tasks. These findings are consistent with the hypothesis that component areas of the discourse processing network are recruited as needed based on the nature of the inference. A Protagonist monitoring and synthesis network is proposed as a more accurate account for Theory of Mind activation during narrative comprehension. Copyright © 2010 Wiley-Liss, Inc.
Sustainability and collapse in a coevolutionary model of local resource stocks and behavioral patterns on a social network

NASA Astrophysics Data System (ADS)

Wiedermann, Marc; Donges, Jonathan F.; Heitzig, Jobst; Kurths, Jürgen

2014-05-01

When investigating the causes and consequences of global change, the collective behavior of human beings is considered as having a considerable impact on natural systems. In our work, we propose a conceptual coevolutionary model simulating the dynamics of local renewable resources in interaction with simplistic societal agents exploiting those resources. The society is represented by a social network on which social traits may be transmitted between agents. These traits themselves induce a certain rate of exploitation of the resource, leading either to its depletion or sustainable existence. Traits are exchanged probabilistically according to their instantaneous individual payoff, and hence this process depends on the status of the natural resource. At the same time agents may adaptively restructure their set of acquaintances. Connections with agents having a different trait may be broken while new connections with agents of the same trait are established. We investigate which choices of social parameters, like the frequency of social interaction, rationality and rate of social network adaptation, cause the system to end in a sustainable state and, hence, what can be done to avoid a collapse of the entire system. The importance and influence of the social network structure is analyzed by the variation of link-densities in the underlying network topology and shows significant influence on the expected outcome of the model. For a static network with no adaptation we find a robust phase transition between the two different regimes, sustainable and non-sustainable, which co-exist in parameter space. High connectivity within the social network, e.g., high link-densities, in combination with a fast rate of social learning lead to a likely collapse of the entire co-evolutionary system, whereas slow learning and small network connectivity very likely result in the sustainable existence of the natural resources. Collapse may be avoided by an intelligent rewiring, e.g. adaptation, of the social network that may also lead to the isolation of misbehaving parts of the society. Our results may suggest that with the current trend to faster imitation and ever increasing global network connectivity, societies are becoming more vulnerable to environmental collapse if they remain myopic at the same time.
Learning control of inverted pendulum system by neural network driven fuzzy reasoning: The learning function of NN-driven fuzzy reasoning under changes of reasoning environment

NASA Technical Reports Server (NTRS)

Hayashi, Isao; Nomura, Hiroyoshi; Wakami, Noboru

1991-01-01

Whereas conventional fuzzy reasonings are associated with tuning problems, which are lack of membership functions and inference rule designs, a neural network driven fuzzy reasoning (NDF) capable of determining membership functions by neural network is formulated. In the antecedent parts of the neural network driven fuzzy reasoning, the optimum membership function is determined by a neural network, while in the consequent parts, an amount of control for each rule is determined by other plural neural networks. By introducing an algorithm of neural network driven fuzzy reasoning, inference rules for making a pendulum stand up from its lowest suspended point are determined for verifying the usefulness of the algorithm.
Neonatal Brain Hemorrhage (NBH) of Prematurity: Translational Mechanisms of the Vascular-Neural Network

PubMed Central

Lekic, Tim; Klebe, Damon; Poblete, Roy; Krafft, Paul R.; Rolland, William B.; Tang, Jiping; Zhang, John H.

2015-01-01

Neonatal brain hemorrhage (NBH) of prematurity is an unfortunate consequence of preterm birth. Complications result in shunt dependence and long-term structural changes such as post-hemorrhagic hydrocephalus, periventricular leukomalacia, gliosis, and neurological dysfunction. Several animal models are available to study this condition, and many basic mechanisms, etiological factors, and outcome consequences, are becoming understood. NBH is an important clinical condition, of which treatment may potentially circumvent shunt complication, and improve functional recovery (cerebral palsy, and cognitive impairments). This review highlights key pathophysiological findings of the neonatal vascular-neural network in the context of molecular mechanisms targeting the post-hemorrhagic hydrocephalus affecting this vulnerable infant population. PMID:25620100
Discovering SIFIs in Interbank Communities

PubMed Central

Pecora, Nicolò; Rovira Kaltwasser, Pablo; Spelta, Alessandro

2016-01-01

This paper proposes a new methodology based on non-negative matrix factorization to detect communities and to identify central nodes in a network as well as within communities. The method is specifically designed for directed weighted networks and, consequently, it has been applied to the interbank network derived from the e-MID interbank market. In an interbank network indeed links are directed, representing flows of funds between lenders and borrowers. Besides distinguishing between Systemically Important Borrowers and Lenders, the technique complements the detection of systemically important banks, revealing the community structure of the network, that proxies the most plausible areas of contagion of institutions’ distress. PMID:28002445
Synchronization of heteroclinic circuits through learning in coupled neural networks

NASA Astrophysics Data System (ADS)

Selskii, Anton; Makarov, Valeri A.

2016-01-01

The synchronization of oscillatory activity in neural networks is usually implemented by coupling the state variables describing neuronal dynamics. Here we study another, but complementary mechanism based on a learning process with memory. A driver network, acting as a teacher, exhibits winner-less competition (WLC) dynamics, while a driven network, a learner, tunes its internal couplings according to the oscillations observed in the teacher. We show that under appropriate training the learner can "copy" the coupling structure and thus synchronize oscillations with the teacher. The replication of the WLC dynamics occurs for intermediate memory lengths only, consequently, the learner network exhibits a phenomenon of learning resonance.
High altitude environmental monitoring: the SHARE project and CEOP-HE

NASA Astrophysics Data System (ADS)

Tartari, G.

2009-04-01

Mountain areas above 2,500 m a.s.l. constitute about 25% of the Earth's surface and play a fundamental role in the global water balance, while influencing global climate and atmospheric circulation systems. Several millions, including lowlanders, are directly affected by the impacts of climate change on glaciers and water resource distribution. Mountains and high altitude plateaus are subject to the highest rate of temperature increase (e.g., Tibetan Plateau) and are recognized as particularly vulnerable to the effects of climate change. In spite of this, the number of permanent monitoring sites in the major environmental networks decreases with altitude. On a sample of two hundred high altitude automatic weather stations located above 2,500 m a.s.l., less than 20% are over 4,000 m, while there are only 24 stations in the world that could be considered "complete" high altitude observatories. Furthermore, entire mountain areas are left uncovered, creating significant data gaps which make reliable modelling and forecasting nearly impossible. In response to these problems, Ev-K2-CNR has developed the project SHARE (Stations at High Altitude for Research on the Environment) with the support of the Italian government and in collaboration with UNEP. This integrated environmental monitoring and research project aims to improve knowledge on the local, regional and global consequences of climate change in mountain regions and on the influence of high elevations on climate, atmospheric circulation and hydrology. SHARE today boasts a network of 13 permanent monitoring stations between 2,165 m and 8,000 m. Affiliated researchers have produced over 150 scientific publications in atmospheric sciences, meteorology and climate, glaciology, limnology and paleolimnology and geophysics. SHARE network data is also contributed to international programs (UNEP-ABC, WMO-GAW, WCRP-GEWEX-CEOP, NASA-AERONET, ILTER, EU-EUSAAR, EU-ACCENT). Within this context, the CEOP-High Elevations (CEOP-HE) element of regional focus was developed under the GEWEX CEOP programme to study multi-scale variability in water and energy cycles in high elevation areas, and to help improve observations, modelling and data management. Future plans include expansion of the SHARE network, addition of other key research areas including hydrology, and creation of mechanisms to favour exchange of data amongst high altitude networks. In coordination with other global research and monitoring projects (CliC, etc.), SHARE and CEOP-HE could provide a more organic and well-distributed interdisciplinary network, thus allowing governments and international agencies to better face impacts of climate change effects on energy and water budgets and elaborate appropriate adaptation strategies.
Impaired decision-making and brain shrinkage in alcoholism.

PubMed

Le Berre, A-P; Rauchs, G; La Joie, R; Mézenge, F; Boudehent, C; Vabret, F; Segobin, S; Viader, F; Allain, P; Eustache, F; Pitel, A-L; Beaunieux, H

2014-03-01

Alcohol-dependent individuals usually favor instant gratification of alcohol use and ignore its long-term negative consequences, reflecting impaired decision-making. According to the somatic marker hypothesis, decision-making abilities are subtended by an extended brain network. As chronic alcohol consumption is known to be associated with brain shrinkage in this network, the present study investigated relationships between brain shrinkage and decision-making impairments in alcohol-dependent individuals early in abstinence using voxel-based morphometry. Thirty patients performed the Iowa Gambling Task and underwent a magnetic resonance imaging investigation (1.5T). Decision-making performances and brain data were compared with those of age-matched healthy controls. In the alcoholic group, a multiple regression analysis was conducted with two predictors (gray matter [GM] volume and decision-making measure) and two covariates (number of withdrawals and duration of alcoholism). Compared with controls, alcoholics had impaired decision-making and widespread reduced gray matter volume, especially in regions involved in decision-making. The regression analysis revealed links between high GM volume in the ventromedial prefrontal cortex, dorsal anterior cingulate cortex and right hippocampal formation, and high decision-making scores (P<0.001, uncorrected). Decision-making deficits in alcoholism may result from impairment of both emotional and cognitive networks. Copyright © 2012 Elsevier Masson SAS. All rights reserved.
Efficient data replication for the delivery of high-quality video content over P2P VoD advertising networks

NASA Astrophysics Data System (ADS)

Ho, Chien-Peng; Yu, Jen-Yu; Lee, Suh-Yin

2011-12-01

Recent advances in modern television systems have had profound consequences for the scalability, stability, and quality of transmitted digital data signals. This is of particular significance for peer-to-peer (P2P) video-on-demand (VoD) related platforms, faced with an immediate and growing demand for reliable service delivery. In response to demands for high-quality video, the key objectives in the construction of the proposed framework were user satisfaction with perceived video quality and the effective utilization of available resources on P2P VoD networks. This study developed a peer-based promoter to support online advertising in P2P VoD networks based on an estimation of video distortion prior to the replication of data stream chunks. The proposed technology enables the recovery of lost video using replicated stream chunks in real time. Load balance is achieved by adjusting the replication level of each candidate group according to the degree-of-distortion, thereby enabling a significant reduction in server load and increased scalability in the P2P VoD system. This approach also promotes the use of advertising as an efficient tool for commercial promotion. Results indicate that the proposed system efficiently satisfies the given fault tolerances.
A Millimeter-Wave Cavity-Backed Suspended Substrate Stripline Antenna

NASA Technical Reports Server (NTRS)

Simons, Rainee N.

1999-01-01

Future generation satellite communication systems in near-Earth orbit will operate at frequencies in the higher mm-wave frequency bands. These satellite systems require low-profile, high gain, light weight and low cost antennas for communications to and from Earth as well as for inter-satellite links (ISL). At higher mm-wave frequencies, the conductor loss of conventional microstrip line is high and consequently the feed network loss of patch antenna arrays is also high. The high loss lowers the array efficiency, and in addition lowers the G/T ratio in a receiving array. Recently a radial line slot antenna array has been demonstrated to have high gain and efficiency at 60 GHz. In this paper, the design, fabrication and characterization of a V-Band (50-75 GHz), cavity backed, circular aperture antenna with suspended substrate stripline (SSS) feed is presented.
Social network influences on initiation and maintenance of reduced drinking among college students.

PubMed

Reid, Allecia E; Carey, Kate B; Merrill, Jennifer E; Carey, Michael P

2015-02-01

To determine whether (a) social networks influence the extent to which college students initiate and/or maintain reductions in drinking following an alcohol intervention and (b) students with riskier networks respond better to a counselor-delivered, vs. a computer-delivered, intervention. Mandated students (N = 316; 63% male) provided their perceptions of peer network members' drinking statuses (e.g., heavy drinker) and how accepting each friend would be if the participant reduced his or her drinking. Next, they were randomized to receive a brief motivational intervention (BMI) or Alcohol Edu for Sanctions (EDU). In latent growth models controlling for baseline levels on outcomes, influences of social networks on 2 phases of intervention response were examined: initiation of reductions in drinks per heaviest week, peak blood alcohol content (BAC), and consequences at 1 month (model intercepts) and maintenance of reductions between 1 and 12 months (model slopes). Peer drinking status predicted initiation of reductions in drinks per heaviest week and peak BAC; peer acceptability predicted initial reductions in consequences. Peer Acceptability × Condition interactions were significant or marginal for all outcomes in the maintenance phase. In networks with higher perceived acceptability of decreasing use, BMI and EDU exhibited similar growth rates. In less accepting networks, growth rates were significantly steeper among EDU than BMI participants. For consumption outcomes, lower perceived peer acceptability predicted steeper rates of growth in drinking among EDU but not BMI participants. Understanding how social networks influence behavior change and how interventions mitigate their influence is important for optimizing efficacy of alcohol interventions. (PsycINFO Database Record (c) 2015 APA, all rights reserved).
Bacterial chemoreceptors: high-performance signaling in networked arrays.

PubMed

Hazelbauer, Gerald L; Falke, Joseph J; Parkinson, John S

2008-01-01

Chemoreceptors are crucial components in the bacterial sensory systems that mediate chemotaxis. Chemotactic responses exhibit exquisite sensitivity, extensive dynamic range and precise adaptation. The mechanisms that mediate these high-performance functions involve not only actions of individual proteins but also interactions among clusters of components, localized in extensive patches of thousands of molecules. Recently, these patches have been imaged in native cells, important features of chemoreceptor structure and on-off switching have been identified, and new insights have been gained into the structural basis and functional consequences of higher order interactions among sensory components. These new data suggest multiple levels of molecular interactions, each of which contribute specific functional features and together create a sophisticated signaling device.
Bacterial chemoreceptors: high-performance signaling in networked arrays

PubMed Central

Hazelbauer, Gerald L.; Falke, Joseph J.; Parkinson, John S.

2010-01-01

Chemoreceptors are crucial components in the bacterial sensory systems that mediate chemotaxis. Chemotactic responses exhibit exquisite sensitivity, extensive dynamic range and precise adaptation. The mechanisms that mediate these high-performance functions involve not only actions of individual proteins but also interactions among clusters of components, localized in extensive patches of thousands of molecules. Recently, these patches have been imaged in native cells, important features of chemoreceptor structure and on–off switching have been identified, and new insights have been gained into the structural basis and functional consequences of higher order interactions among sensory components. These new data suggest multiple levels of molecular interactions, each of which contribute specific functional features and together create a sophisticated signaling device. PMID:18165013
A high-rate PCI-based telemetry processor system

NASA Astrophysics Data System (ADS)

Turri, R.

2002-07-01

The high performances reached by the Satellite on-board telemetry generation and transmission, as consequently, will impose the design of ground facilities with higher processing capabilities at low cost to allow a good diffusion of these ground station. The equipment normally used are based on complex, proprietary bus and computing architectures that prevent the systems from exploiting the continuous and rapid increasing in computing power available on market. The PCI bus systems now allow processing of high-rate data streams in a standard PC-system. At the same time the Windows NT operating system supports multitasking and symmetric multiprocessing, giving the capability to process high data rate signals. In addition, high-speed networking, 64 bit PCI-bus technologies and the increase in processor power and software, allow creating a system based on COTS products (which in future may be easily and inexpensively upgraded). In the frame of EUCLID RTP 9.8 project, a specific work element was dedicated to develop the architecture of a system able to acquire telemetry data of up to 600 Mbps. Laben S.p.A - a Finmeccanica Company -, entrusted of this work, has designed a PCI-based telemetry system making possible the communication between a satellite down-link and a wide area network at the required rate.
Poverty and fatalism: Impacts on the community dynamics and on hope in Brazilian residents.

PubMed

Cidade, Elívia Camurça; Moura, James Ferreira; Nepomuceno, Bárbara Barbosa; Ximenes, Verônica Morais; Sarriera, Jorge Castellá

2016-01-01

The aim of this study was to analyze the consequences of poverty on expressions of fatalism, hope, and sense of community of two Brazilian States: Ceará and Rio Grande do Sul. Seven-hundred and thirty-one people, divided in four groups (extreme poverty, poverty, median income, and adequate income) answered a questionnaire. The variables sense of community and hope were found to be predictors of fatalism. Individuals in situations of poverty and extreme poverty showed high indices of fatalism, pessimism, divinity control, and luck, and low indices of hope and sense of community. Individuals with adequate income have low levels of fatalism, pessimism, and divinity control. It is concluded that poverty has consequences on the life of those who experience it, and that attitudes of pessimism, hopelessness, and belief in luck as well as the weakening of community networks, articulate and support the maintenance of the status quo.
Convergent neuromodulation onto a network neuron can have divergent effects at the network level.

PubMed

Kintos, Nickolas; Nusbaum, Michael P; Nadim, Farzan

2016-04-01

Different neuromodulators often target the same ion channel. When such modulators act on different neuron types, this convergent action can enable a rhythmic network to produce distinct outputs. Less clear are the functional consequences when two neuromodulators influence the same ion channel in the same neuron. We examine the consequences of this seeming redundancy using a mathematical model of the crab gastric mill (chewing) network. This network is activated in vitro by the projection neuron MCN1, which elicits a half-center bursting oscillation between the reciprocally-inhibitory neurons LG and Int1. We focus on two neuropeptides which modulate this network, including a MCN1 neurotransmitter and the hormone crustacean cardioactive peptide (CCAP). Both activate the same voltage-gated current (I MI ) in the LG neuron. However, I MI-MCN1 , resulting from MCN1 released neuropeptide, has phasic dynamics in its maximal conductance due to LG presynaptic inhibition of MCN1, while I MI-CCAP retains the same maximal conductance in both phases of the gastric mill rhythm. Separation of time scales allows us to produce a 2D model from which phase plane analysis shows that, as in the biological system, I MI-MCN1 and I MI-CCAP primarily influence the durations of opposing phases of this rhythm. Furthermore, I MI-MCN1 influences the rhythmic output in a manner similar to the Int1-to-LG synapse, whereas I MI-CCAP has an influence similar to the LG-to-Int1 synapse. These results show that distinct neuromodulators which target the same voltage-gated ion channel in the same network neuron can nevertheless produce distinct effects at the network level, providing divergent neuromodulator actions on network activity.
Convergent neuromodulation onto a network neuron can have divergent effects at the network level

PubMed Central

Kintos, Nickolas; Nusbaum, Michael P.; Nadim, Farzan

2016-01-01

Different neuromodulators often target the same ion channel. When such modulators act on different neuron types, this convergent action can enable a rhythmic network to produce distinct outputs. Less clear are the functional consequences when two neuromodulators influence the same ion channel in the same neuron. We examine the consequences of this seeming redundancy using a mathematical model of the crab gastric mill (chewing) network. This network is activated in vitro by the projection neuron MCN1, which elicits a half-center bursting oscillation between the reciprocally-inhibitory neurons LG and Int1. We focus on two neuropeptides which modulate this network, including a MCN1 neurotransmitter and the hormone crustacean cardioactive peptide (CCAP). Both activate the same voltage-gated current (IMI) in the LG neuron. However, IMI-MCN1, resulting from MCN1 released neuropeptide, has phasic dynamics in its maximal conductance due to LG presynaptic inhibition of MCN1, while IMI-CCAP retains the same maximal conductance in both phases of the gastric mill rhythm. Separation of time scales allows us to produce a 2D model from which phase plane analysis shows that, as in the biological system, IMI-MCN1 and IMI-CCAP primarily influence the durations of opposing phases of this rhythm. Furthermore, IMI-MCN1 influences the rhythmic output in a manner similar to the Int1-to-LG synapse, whereas IMI-CCAP has an influence similar to the LG-to-Int1 synapse. These results show that distinct neuromodulators which target the same voltage-gated ion channel in the same network neuron can nevertheless produce distinct effects at the network level, providing divergent neuromodulator actions on network activity. PMID:26798029

Food choice patterns among frail older adults: The associations between social network, food choice values, and diet quality.

PubMed

Kim, Chang-O

2016-01-01

Social network type might affect an individual's food choice because these decisions are often made as a group rather than individually. In this study, the associations between social network type, food choice value, and diet quality in frail older adults with low socioeconomic status were investigated. For this cross-sectional study, 87 frail older adults were recruited from the National Home Healthcare Services in Seoul, South Korea. Social network types, food choice values, and diet quality were assessed using The Practitioner Assessment of Network Type Instrument, The Food Choice Questionnaire, and mean adequacy ratio, respectively. Results showed that frail older adults with close relationships with local family and/or friends and neighbors were less likely to follow their own preferences, such as taste, price, and beliefs regarding food health values. In contrast, frail older adults with a small social network and few community contacts were more likely to be influenced by their food choice values, such as price or healthiness of food. Frail older adults who tend to choose familiar foods were associated with low-quality dietary intake, while older adults who valued healthiness or use of natural ingredients were associated with a high-quality diet. The strength and direction of these associations were dependent on social network type of frail older adults. This study explored the hypothesis that food choice values are associated with a certain type of social network and consequently affect diet quality. While additional research needs to be conducted, community-based intervention intended to improve diet quality of frail older adults must carefully consider individual food choice values as well as social network types. Copyright © 2015 Elsevier Ltd. All rights reserved.
Empirical Bayes conditional independence graphs for regulatory network recovery.

PubMed

Mahdi, Rami; Madduri, Abishek S; Wang, Guoqing; Strulovici-Barel, Yael; Salit, Jacqueline; Hackett, Neil R; Crystal, Ronald G; Mezey, Jason G

2012-08-01

Computational inference methods that make use of graphical models to extract regulatory networks from gene expression data can have difficulty reconstructing dense regions of a network, a consequence of both computational complexity and unreliable parameter estimation when sample size is small. As a result, identification of hub genes is of special difficulty for these methods. We present a new algorithm, Empirical Light Mutual Min (ELMM), for large network reconstruction that has properties well suited for recovery of graphs with high-degree nodes. ELMM reconstructs the undirected graph of a regulatory network using empirical Bayes conditional independence testing with a heuristic relaxation of independence constraints in dense areas of the graph. This relaxation allows only one gene of a pair with a putative relation to be aware of the network connection, an approach that is aimed at easing multiple testing problems associated with recovering densely connected structures. Using in silico data, we show that ELMM has better performance than commonly used network inference algorithms including GeneNet, ARACNE, FOCI, GENIE3 and GLASSO. We also apply ELMM to reconstruct a network among 5492 genes expressed in human lung airway epithelium of healthy non-smokers, healthy smokers and individuals with chronic obstructive pulmonary disease assayed using microarrays. The analysis identifies dense sub-networks that are consistent with known regulatory relationships in the lung airway and also suggests novel hub regulatory relationships among a number of genes that play roles in oxidative stress and secretion. Software for running ELMM is made available at http://mezeylab.cb.bscb.cornell.edu/Software.aspx. ramimahdi@yahoo.com or jgm45@cornell.edu Supplementary data are available at Bioinformatics online.
Nonlinear dynamic systems identification using recurrent interval type-2 TSK fuzzy neural network - A novel structure.

PubMed

El-Nagar, Ahmad M

2018-01-01

In this study, a novel structure of a recurrent interval type-2 Takagi-Sugeno-Kang (TSK) fuzzy neural network (FNN) is introduced for nonlinear dynamic and time-varying systems identification. It combines the type-2 fuzzy sets (T2FSs) and a recurrent FNN to avoid the data uncertainties. The fuzzy firing strengths in the proposed structure are returned to the network input as internal variables. The interval type-2 fuzzy sets (IT2FSs) is used to describe the antecedent part for each rule while the consequent part is a TSK-type, which is a linear function of the internal variables and the external inputs with interval weights. All the type-2 fuzzy rules for the proposed RIT2TSKFNN are learned on-line based on structure and parameter learning, which are performed using the type-2 fuzzy clustering. The antecedent and consequent parameters of the proposed RIT2TSKFNN are updated based on the Lyapunov function to achieve network stability. The obtained results indicate that our proposed network has a small root mean square error (RMSE) and a small integral of square error (ISE) with a small number of rules and a small computation time compared with other type-2 FNNs. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.
The Antecedents, Objects, and Consequents of User Trust in Location-Based Social Networks

ERIC Educational Resources Information Center

Russo, Paul

2012-01-01

Online social networks provide rich opportunities to interact with friends and other online community members. At the same time, the addition of emerging location-sharing technologies--which broadcast a user's location online, including who they are with and what is happening nearby--is creating new dimensions to the types of interactions…
Logic-based models in systems biology: a predictive and parameter-free network analysis method†

PubMed Central

Wynn, Michelle L.; Consul, Nikita; Merajver, Sofia D.

2012-01-01

Highly complex molecular networks, which play fundamental roles in almost all cellular processes, are known to be dysregulated in a number of diseases, most notably in cancer. As a consequence, there is a critical need to develop practical methodologies for constructing and analysing molecular networks at a systems level. Mathematical models built with continuous differential equations are an ideal methodology because they can provide a detailed picture of a network’s dynamics. To be predictive, however, differential equation models require that numerous parameters be known a priori and this information is almost never available. An alternative dynamical approach is the use of discrete logic-based models that can provide a good approximation of the qualitative behaviour of a biochemical system without the burden of a large parameter space. Despite their advantages, there remains significant resistance to the use of logic-based models in biology. Here, we address some common concerns and provide a brief tutorial on the use of logic-based models, which we motivate with biological examples. PMID:23072820
Secrets and Misperceptions: The Creation of Self-Fulfilling Illusions

PubMed Central

Cowan, Sarah K.

2015-01-01

This study examines who hears what secrets, comparing two similar secrets-one that is highly stigmatized and one that is less so. Using a unique survey representative of American adults and intake forms from a medical clinic, I document marked differences in who hears these secrets. People who are sympathetic to the stigmatizing secret are more likely to hear of it than those who may react negatively. This is a consequence of people not just selectively disclosing their own secrets but selectively sharing others’ as well. As a result, people in the same social network will be exposed to and influenced by different information about those they know and hence experience that network differently. When people effectively exist in networks tailored by others not to offend, then the information they hear tends to be that of which they already approve. Were they to hear secrets they disapproved of, then their attitudes might change, but they are less likely to hear those secrets. As such, the patterns of secret hearing contribute to a stasis in public opinion. PMID:26082932
Frequency-selective augmenting responses by short-term synaptic depression in cat neocortex

PubMed Central

Houweling, Arthur R; Bazhenov, Maxim; Timofeev, Igor; Grenier, François; Steriade, Mircea; Sejnowski, Terrence J

2002-01-01

Thalamic stimulation at frequencies between 5 and 15 Hz elicits incremental or ‘augmenting’ cortical responses. Augmenting responses can also be evoked in cortical slices and isolated cortical slabs in vivo. Here we show that a realistic network model of cortical pyramidal cells and interneurones including short-term plasticity of inhibitory and excitatory synapses replicates the main features of augmenting responses as obtained in isolated slabs in vivo. Repetitive stimulation of synaptic inputs at frequencies around 10 Hz produced postsynaptic potentials that grew in size and carried an increasing number of action potentials resulting from the depression of inhibitory synaptic currents. Frequency selectivity was obtained through the relatively weak depression of inhibitory synapses at low frequencies, and strong depression of excitatory synapses together with activation of a calcium-activated potassium current at high frequencies. This network resonance is a consequence of short-term synaptic plasticity in a network of neurones without intrinsic resonances. These results suggest that short-term plasticity of cortical synapses could shape the dynamics of synchronized oscillations in the brain. PMID:12122156
Metapopulation dynamics and total biomass: Understanding the effects of diffusion in complex networks.

PubMed

Ruiz-Herrera, Alfonso

2018-05-01

In this study, I explored the impact of constructing a new dispersal route between two different patches in a metapopulation. My results indicated that its success/failure on the population abundance greatly depends on the patches directly involved and negligibly on the network topology. Specifically, constructing a dispersal route is highly recommended if it connects a source to a source that is close to becoming a sink or a sink that is close to becoming a source. This biological property is the basis for understanding the influence of the network topology on the population abundance. According to some thresholds discussed in this manuscript, I identified when a given route has a positive or negative effect on the population size. Consequently, as a simple rule of thumb, managers should look for metapopulations that have the maximum (resp. minimum) number paths with a positive (resp. negative) effect on the population abundance. As emphasized, the biological results of this paper do not depend on the model formulation. Copyright © 2018 Elsevier Inc. All rights reserved.
PlantNATsDB: a comprehensive database of plant natural antisense transcripts.

PubMed

Chen, Dijun; Yuan, Chunhui; Zhang, Jian; Zhang, Zhao; Bai, Lin; Meng, Yijun; Chen, Ling-Ling; Chen, Ming

2012-01-01

Natural antisense transcripts (NATs), as one type of regulatory RNAs, occur prevalently in plant genomes and play significant roles in physiological and pathological processes. Although their important biological functions have been reported widely, a comprehensive database is lacking up to now. Consequently, we constructed a plant NAT database (PlantNATsDB) involving approximately 2 million NAT pairs in 69 plant species. GO annotation and high-throughput small RNA sequencing data currently available were integrated to investigate the biological function of NATs. PlantNATsDB provides various user-friendly web interfaces to facilitate the presentation of NATs and an integrated, graphical network browser to display the complex networks formed by different NATs. Moreover, a 'Gene Set Analysis' module based on GO annotation was designed to dig out the statistical significantly overrepresented GO categories from the specific NAT network. PlantNATsDB is currently the most comprehensive resource of NATs in the plant kingdom, which can serve as a reference database to investigate the regulatory function of NATs. The PlantNATsDB is freely available at http://bis.zju.edu.cn/pnatdb/.
MicroRNA-mediated regulatory circuits: outlook and perspectives

NASA Astrophysics Data System (ADS)

Cora', Davide; Re, Angela; Caselle, Michele; Bussolino, Federico

2017-08-01

MicroRNAs have been found to be necessary for regulating genes implicated in almost all signaling pathways, and consequently their dysfunction influences many diseases, including cancer. Understanding of the complexity of the microRNA-mediated regulatory network has grown in terms of size, connectivity and dynamics with the development of computational and, more recently, experimental high-throughput approaches for microRNA target identification. Newly developed studies on recurrent microRNA-mediated circuits in regulatory networks, also known as network motifs, have substantially contributed to addressing this complexity, and therefore to helping understand the ways by which microRNAs achieve their regulatory role. This review provides a summarizing view of the state-of-the-art, and perspectives of research efforts on microRNA-mediated regulatory motifs. In this review, we discuss the topological properties characterizing different types of circuits, and the regulatory features theoretically enabled by such properties, with a special emphasis on examples of circuits typifying their biological significance in experimentally validated contexts. Finally, we will consider possible future developments, in particular regarding microRNA-mediated circuits involving long non-coding RNAs and epigenetic regulators.
Using robust Bayesian network to estimate the residuals of fluoroquinolone antibiotic in soil.

PubMed

Li, Xuewen; Xie, Yunfeng; Li, Lianfa; Yang, Xunfeng; Wang, Ning; Wang, Jinfeng

2015-11-01

Prediction of antibiotic pollution and its consequences is difficult, due to the uncertainties and complexities associated with multiple related factors. This article employed domain knowledge and spatial data to construct a Bayesian network (BN) model to assess fluoroquinolone antibiotic (FQs) pollution in the soil of an intensive vegetable cultivation area. The results show: (1) The relationships between FQs pollution and contributory factors: Three factors (cultivation methods, crop rotations, and chicken manure types) were consistently identified as predictors in the topological structures of three FQs, indicating their importance in FQs pollution; deduced with domain knowledge, the cultivation methods are determined by the crop rotations, which require different nutrients (derived from the manure) according to different plant biomass. (2) The performance of BN model: The integrative robust Bayesian network model achieved the highest detection probability (pd) of high-risk and receiver operating characteristic (ROC) area, since it incorporates domain knowledge and model uncertainty. Our encouraging findings have implications for the use of BN as a robust approach to assessment of FQs pollution and for informing decisions on appropriate remedial measures.
Model of mobile agents for sexual interactions networks

NASA Astrophysics Data System (ADS)

González, M. C.; Lind, P. G.; Herrmann, H. J.

2006-02-01

We present a novel model to simulate real social networks of complex interactions, based in a system of colliding particles (agents). The network is build by keeping track of the collisions and evolves in time with correlations which emerge due to the mobility of the agents. Therefore, statistical features are a consequence only of local collisions among its individual agents. Agent dynamics is realized by an event-driven algorithm of collisions where energy is gained as opposed to physical systems which have dissipation. The model reproduces empirical data from networks of sexual interactions, not previously obtained with other approaches.
Cross-modal and modality-specific expectancy effects between pain and disgust

PubMed Central

Sharvit, Gil; Vuilleumier, Patrik; Delplanque, Sylvain; Corradi-Dell’ Acqua, Corrado

2015-01-01

Pain sensitivity increases when a noxious stimulus is preceded by cues predicting higher intensity. However, it is unclear whether the modulation of nociception by expectancy is sensory-specific (“modality based”) or reflects the aversive-affective consequence of the upcoming event (“unpleasantness”), potentially common with other negative events. Here we compared expectancy effects for pain and disgust by using different, but equally unpleasant, nociceptive (thermal) and olfactory stimulations. Indeed both pain and disgust are aversive, associated with threat to the organism, and processed in partly overlapping brain networks. Participants saw cues predicting the unpleasantness (high/low) and the modality (pain/disgust) of upcoming thermal or olfactory stimulations, and rated the associated unpleasantness after stimuli delivery. Results showed that identical thermal stimuli were perceived as more unpleasant when preceded by cues threatening about high (as opposed to low) pain. A similar expectancy effect was found for olfactory disgust. Critically, cross-modal expectancy effects were observed on inconsistent trials when thermal stimuli were preceded by high-disgust cues or olfactory stimuli preceded by high-pain cues. However, these effects were stronger in consistent than inconsistent conditions. Taken together, our results suggest that expectation of an unpleasant event elicits representations of both its modality-specific properties and its aversive consequences. PMID:26631975
Personnel Recovery in Space

DTIC Science & Technology

2016-07-13

adequate security testing , and segment their networks and systems into separate defended enclaves. Finally, cyber defenders should posi- tion themselves...explicitly tied to following security practices, and there should be consequences for security failures that are regularly tested via a continuing testing ...program. Users should be routinely tested and probed, and those who do not perform well should face escalating consequences. For example, cyber
How to Avoid the Negative Consequences of Restructuring the Network of Rural Schools

ERIC Educational Resources Information Center

Suvorova, Galina

2004-01-01

Because of the destruction of the agricultural sector of Russia's economy, there is no demand for workers in the countryside, and, as a consequence, the able-bodied population is leaving the countryside and the birth rate has gone down drastically. These factors have resulted in the liquidation of kindergartens and small-enrollment schools and a…
Optimal percolation on multiplex networks.

PubMed

Osat, Saeed; Faqeeh, Ali; Radicchi, Filippo

2017-11-16

Optimal percolation is the problem of finding the minimal set of nodes whose removal from a network fragments the system into non-extensive disconnected clusters. The solution to this problem is important for strategies of immunization in disease spreading, and influence maximization in opinion dynamics. Optimal percolation has received considerable attention in the context of isolated networks. However, its generalization to multiplex networks has not yet been considered. Here we show that approximating the solution of the optimal percolation problem on a multiplex network with solutions valid for single-layer networks extracted from the multiplex may have serious consequences in the characterization of the true robustness of the system. We reach this conclusion by extending many of the methods for finding approximate solutions of the optimal percolation problem from single-layer to multiplex networks, and performing a systematic analysis on synthetic and real-world multiplex networks.
The neural representation of social networks.

PubMed

Weaverdyck, Miriam E; Parkinson, Carolyn

2018-05-24

The computational demands associated with navigating large, complexly bonded social groups are thought to have significantly shaped human brain evolution. Yet, research on social network representation and cognitive neuroscience have progressed largely independently. Thus, little is known about how the human brain encodes the structure of the social networks in which it is embedded. This review highlights recent work seeking to bridge this gap in understanding. While the majority of research linking social network analysis and neuroimaging has focused on relating neuroanatomy to social network size, researchers have begun to define the neural architecture that encodes social network structure, cognitive and behavioral consequences of encoding this information, and individual differences in how people represent the structure of their social world. Copyright © 2018 Elsevier Ltd. All rights reserved.
Social network extraction based on Web: 3. the integrated superficial method

NASA Astrophysics Data System (ADS)

Nasution, M. K. M.; Sitompul, O. S.; Noah, S. A.

2018-03-01

The Web as a source of information has become part of the social behavior information. Although, by involving only the limitation of information disclosed by search engines in the form of: hit counts, snippets, and URL addresses of web pages, the integrated extraction method produces a social network not only trusted but enriched. Unintegrated extraction methods may produce social networks without explanation, resulting in poor supplemental information, or resulting in a social network of durmise laden, consequently unrepresentative social structures. The integrated superficial method in addition to generating the core social network, also generates an expanded network so as to reach the scope of relation clues, or number of edges computationally almost similar to n(n - 1)/2 for n social actors.
eHealth services and Directive on Electronic Commerce 2000/31/EC.

PubMed

Van Gyseghem, Jean-Marc

2008-01-01

We often restrict the analysis of eHealth services to a concept of privacy. In this article, we'll demonstrate that other legislation can apply to those services as Directive 2000/31/EC on Ecommerce. By creating telematic networks or infrastructure, eHealth services are offering information services. But what are the consequences with such concept? What are the duties and rights for the actors of the network(s)? We'll try to answer to some questions, even if it won't be exhaustive.
Assessment of a Bayesian Belief Network-GIS framework as a practical tool to support marine planning.

PubMed

Stelzenmüller, V; Lee, J; Garnacho, E; Rogers, S I

2010-10-01

For the UK continental shelf we developed a Bayesian Belief Network-GIS framework to visualise relationships between cumulative human pressures, sensitive marine landscapes and landscape vulnerability, to assess the consequences of potential marine planning objectives, and to map uncertainty-related changes in management measures. Results revealed that the spatial assessment of footprints and intensities of human activities had more influence on landscape vulnerabilities than the type of landscape sensitivity measure used. We addressed questions regarding consequences of potential planning targets, and necessary management measures with spatially-explicit assessment of their consequences. We conclude that the BN-GIS framework is a practical tool allowing for the visualisation of relationships, the spatial assessment of uncertainty related to spatial management scenarios, the engagement of different stakeholder views, and enables a quick update of new spatial data and relationships. Ultimately, such BN-GIS based tools can support the decision-making process used in adaptive marine management. Copyright © 2010 Elsevier Ltd. All rights reserved.

Industrial defect discrimination applying infrared imaging spectroscopy and artificial neural networks

NASA Astrophysics Data System (ADS)

Garcia-Allende, Pilar Beatriz; Conde, Olga M.; Madruga, Francisco J.; Cubillas, Ana M.; Lopez-Higuera, Jose M.

2008-03-01

A non-intrusive infrared sensor for the detection of spurious elements in an industrial raw material chain has been developed. The system is an extension to the whole near infrared range of the spectrum of a previously designed system based on the Vis-NIR range (400 - 1000 nm). It incorporates a hyperspectral imaging spectrograph able to register simultaneously the NIR reflected spectrum of the material under study along all the points of an image line. The working material has been different tobacco leaf blends mixed with typical spurious elements of this field such as plastics, cardboards, etc. Spurious elements are discriminated automatically by an artificial neural network able to perform the classification with a high degree of accuracy. Due to the high amount of information involved in the process, Principal Component Analysis is first applied to perform data redundancy removal. By means of the extension to the whole NIR range of the spectrum, from 1000 to 2400 nm, the characterization of the material under test is highly improved. The developed technique could be applied to the classification and discrimination of other materials, and, as a consequence of its non-contact operation it is particularly suitable for food quality control.
Randomizing Genome-Scale Metabolic Networks

PubMed Central

Samal, Areejit; Martin, Olivier C.

2011-01-01

Networks coming from protein-protein interactions, transcriptional regulation, signaling, or metabolism may appear to have “unusual” properties. To quantify this, it is appropriate to randomize the network and test the hypothesis that the network is not statistically different from expected in a motivated ensemble. However, when dealing with metabolic networks, the randomization of the network using edge exchange generates fictitious reactions that are biochemically meaningless. Here we provide several natural ensembles of randomized metabolic networks. A first constraint is to use valid biochemical reactions. Further constraints correspond to imposing appropriate functional constraints. We explain how to perform these randomizations with the help of Markov Chain Monte Carlo (MCMC) and show that they allow one to approach the properties of biological metabolic networks. The implication of the present work is that the observed global structural properties of real metabolic networks are likely to be the consequence of simple biochemical and functional constraints. PMID:21779409
Neuroplasticity in Human Alcoholism

PubMed Central

Fein, George; Cardenas, Valerie A.

2015-01-01

Alcoholism is characterized by a lack of control over excessive alcohol consumption despite significant negative consequences. This impulsive and compulsive behavior may be related to functional abnormalities within networks of brain regions responsible for how we make decisions. The abnormalities may result in strengthened networks related to appetitive drive—or the need to fulfill desires—and simultaneously weakened networks that exercise control over behaviors. Studies using functional magnetic resonance imaging (fMRI) in abstinent alcoholics suggest that abstinence is associated with changes in the tone of such networks, decreasing resting tone in appetitive drive networks, and increasing resting tone in inhibitory control networks to support continued abstinence. Identifying electroencephalographic (EEG) measures of resting tone in these networks initially identified using fMRI, and establishing in longitudinal studies that these abstinence-related changes in network tone are progressive would motivate treatment initiatives to facilitate these changes in network tone, thereby supporting successful ongoing abstinence. PMID:26259093
Social inheritance can explain the structure of animal social networks

PubMed Central

Ilany, Amiyaal; Akçay, Erol

2016-01-01

The social network structure of animal populations has major implications for survival, reproductive success, sexual selection and pathogen transmission of individuals. But as of yet, no general theory of social network structure exists that can explain the diversity of social networks observed in nature, and serve as a null model for detecting species and population-specific factors. Here we propose a simple and generally applicable model of social network structure. We consider the emergence of network structure as a result of social inheritance, in which newborns are likely to bond with maternal contacts, and via forming bonds randomly. We compare model output with data from several species, showing that it can generate networks with properties such as those observed in real social systems. Our model demonstrates that important observed properties of social networks, including heritability of network position or assortative associations, can be understood as consequences of social inheritance. PMID:27352101
Network-Cognizant Voltage Droop Control for Distribution Grids

DOE PAGES

Baker, Kyri; Bernstein, Andrey; Dall'Anese, Emiliano; ...

2017-08-07

Our paper examines distribution systems with a high integration of distributed energy resources (DERs) and addresses the design of local control methods for real-time voltage regulation. Particularly, the paper focuses on proportional control strategies where the active and reactive output-powers of DERs are adjusted in response to (and proportionally to) local changes in voltage levels. The design of the voltage-active power and voltage-reactive power characteristics leverages suitable linear approximation of the AC power-flow equations and is network-cognizant; that is, the coefficients of the controllers embed information on the location of the DERs and forecasted non-controllable loads/injections and, consequently, on themore » effect of DER power adjustments on the overall voltage profile. We pursued a robust approach to cope with uncertainty in the forecasted non-controllable loads/power injections. Stability of the proposed local controllers is analytically assessed and numerically corroborated.« less
Network-Cognizant Voltage Droop Control for Distribution Grids

DOE Office of Scientific and Technical Information (OSTI.GOV)

Baker, Kyri; Bernstein, Andrey; Dall'Anese, Emiliano

Our paper examines distribution systems with a high integration of distributed energy resources (DERs) and addresses the design of local control methods for real-time voltage regulation. Particularly, the paper focuses on proportional control strategies where the active and reactive output-powers of DERs are adjusted in response to (and proportionally to) local changes in voltage levels. The design of the voltage-active power and voltage-reactive power characteristics leverages suitable linear approximation of the AC power-flow equations and is network-cognizant; that is, the coefficients of the controllers embed information on the location of the DERs and forecasted non-controllable loads/injections and, consequently, on themore » effect of DER power adjustments on the overall voltage profile. We pursued a robust approach to cope with uncertainty in the forecasted non-controllable loads/power injections. Stability of the proposed local controllers is analytically assessed and numerically corroborated.« less
Autism biomarkers: challenges, pitfalls and possibilities.

PubMed

Anderson, George M

2015-04-01

Network perspectives, in their emphasis on components and their interactions, might afford the best approach to the complexities of the ASD realm. Categorical approaches are unlikely to be fruitful as one should not expect to find a single or even predominant underlying cause of autism behavior across individuals. It is possible that the complex, highly interactive, heterogeneous and individualistic nature of the autism realm is intractable in terms of identifying clinically useful biomarker tests. It is hopeful from an emergenic perspective that small corrective changes in a single component of a deleterious network/configuration might have large beneficial consequences on developmental trajectories and in later treatment. It is suggested that the relationship between ASD and intellectual disability might be fundamentally different in single-gene versus nonsyndromic ASD. It is strongly stated that available biomarker "tests" for autism/ASD will do more harm than good. Finally, the serotonin-melatonin-oxidative stress-placental intersection might be an especially fruitful area of biological investigation.
High-Frequency Network Oscillations in Cerebellar Cortex

PubMed Central

Middleton, Steven J.; Racca, Claudia; Cunningham, Mark O.; Traub, Roger D.; Monyer, Hannah; Knöpfel, Thomas; Schofield, Ian S.; Jenkins, Alistair; Whittington, Miles A.

2016-01-01

SUMMARY Both cerebellum and neocortex receive input from the somatosensory system. Interaction between these regions has been proposed to underpin the correct selection and execution of motor commands, but it is not clear how such interactions occur. In neocortex, inputs give rise to population rhythms, providing a spatiotemporal coding strategy for inputs and consequent outputs. Here, we show that similar patterns of rhythm generation occur in cerebellum during nicotinic receptor subtype activation. Both gamma oscillations (30–80 Hz) and very fast oscillations (VFOs, 80–160 Hz) were generated by intrinsic cerebellar cortical circuitry in the absence of functional glutamatergic connections. As in neocortex, gamma rhythms were dependent on GABAA receptor-mediated inhibition, whereas VFOs required only nonsynaptically connected intercellular networks. The ability of cerebellar cortex to generate population rhythms within the same frequency bands as neocortex suggests that they act as a common spatiotemporal code within which corticocerebellar dialog may occur. PMID:18549787
Achieving high strength and high ductility in metal matrix composites reinforced with a discontinuous three-dimensional graphene-like network.

PubMed

Zhang, Xiang; Shi, Chunsheng; Liu, Enzuo; He, Fang; Ma, Liying; Li, Qunying; Li, Jiajun; Bacsa, Wolfgang; Zhao, Naiqin; He, Chunnian

2017-08-24

Graphene or graphene-like nanosheets have been emerging as an attractive reinforcement for composites due to their unique mechanical and electrical properties as well as their fascinating two-dimensional structure. It is a great challenge to efficiently and homogeneously disperse them within a metal matrix for achieving metal matrix composites with excellent mechanical and physical performance. In this work, we have developed an innovative in situ processing strategy for the fabrication of metal matrix composites reinforced with a discontinuous 3D graphene-like network (3D GN). The processing route involves the in situ synthesis of the encapsulation structure of 3D GN powders tightly anchored with Cu nanoparticles (NPs) (3D GN@Cu) to ensure mixing at the molecular level between graphene-like nanosheets and metal, coating of Cu on the 3D GN@Cu (3D GN@Cu@Cu), and consolidation of the 3D GN@Cu@Cu powders. This process can produce GN/Cu composites on a large scale, in which the in situ synthesized 3D GN not only maintains the perfect 3D network structure within the composites, but also has robust interfacial bonding with the metal matrix. As a consequence, the as-obtained 3D GN/Cu composites exhibit exceptionally high strength and superior ductility (the uniform and total elongation to failure of the composite are even much higher than the unreinforced Cu matrix). To the best of our knowledge, this work is the first report validating that a discontinuous 3D graphene-like network can simultaneously remarkably enhance the strength and ductility of the metal matrix.
Spatial networks

NASA Astrophysics Data System (ADS)

Barthélemy, Marc

2011-02-01

Complex systems are very often organized under the form of networks where nodes and edges are embedded in space. Transportation and mobility networks, Internet, mobile phone networks, power grids, social and contact networks, and neural networks, are all examples where space is relevant and where topology alone does not contain all the information. Characterizing and understanding the structure and the evolution of spatial networks is thus crucial for many different fields, ranging from urbanism to epidemiology. An important consequence of space on networks is that there is a cost associated with the length of edges which in turn has dramatic effects on the topological structure of these networks. We will thoroughly explain the current state of our understanding of how the spatial constraints affect the structure and properties of these networks. We will review the most recent empirical observations and the most important models of spatial networks. We will also discuss various processes which take place on these spatial networks, such as phase transitions, random walks, synchronization, navigation, resilience, and disease spread.
Influence of the segmentation on the characterization of cerebral networks of structural damage for patients with disorders of consciousness

NASA Astrophysics Data System (ADS)

Martínez, Darwin; Mahalingam, Jamuna J.; Soddu, Andrea; Franco, Hugo; Lepore, Natasha; Laureys, Steven; Gómez, Francisco

2015-01-01

Disorders of consciousness (DOC) are a consequence of a variety of severe brain injuries. DOC commonly results in anatomical brain modifications, which can affect cortical and sub-cortical brain structures. Postmortem studies suggest that severity of brain damage correlates with level of impairment in DOC. In-vivo studies in neuroimaging mainly focus in alterations on single structures. Recent evidence suggests that rather than one, multiple brain regions can be simultaneously affected by this condition. In other words, DOC may be linked to an underlying cerebral network of structural damage. Recently, geometrical spatial relationships among key sub-cortical brain regions, such as left and right thalamus and brain stem, have been used for the characterization of this network. This approach is strongly supported on automatic segmentation processes, which aim to extract regions of interests without human intervention. Nevertheless, patients with DOC usually present massive structural brain changes. Therefore, segmentation methods may highly influence the characterization of the underlying cerebral network structure. In this work, we evaluate the level of characterization obtained by using the spatial relationships as descriptor of a sub-cortical cerebral network (left and right thalamus) in patients with DOC, when different segmentation approaches are used (FSL, Free-surfer and manual segmentation). Our results suggest that segmentation process may play a critical role for the construction of robust and reliable structural characterization of DOC conditions.
TexNet seismic network performance and reported seismicity in West Texas

NASA Astrophysics Data System (ADS)

Savvaidis, A.; Lomax, A.; Aiken, C.; Young, B.; Huang, D.; Hennings, P.

2017-12-01

In 2015, the Texas State Legislature began funding the Texas Seismological Network (TexNet). Since then, 22 new permanent broadband three-component seismic stations have been added to 17 existing stations operated by various networks [US, N4, IM]. These stations together with 4 auxiliary stations, i.e. long term deployments of 20 sec portable stations, were deployed to provide a baseline of Texas seismicity. As soon as the deployment of the new permanent stations took place in West Texas, TexNet was able to detect and characterize smaller magnitude events than was possible before, i.e. M < 2.5. As a consequence, additional portable stations were installed in the area in order to better map the current seismicity level. During the different stages of station deployment, we monitored the seismic network performance and its ability to detect earthquake activity. We found that a key limitation to the network performance is industrial noise in West Texas. For example, during daytime, phase picking and event detection rates are much lower than during nighttime at noisy sites. Regarding seismicity, the high density portable station deployment close to the earthquake activity minimizes hypocentral location uncertainties. In addition, we examined the effects of different crustal velocity models in the area of study on hypocentral location using the local network first arrivals. Considerable differences in location were obtained, which shows the importance of local networks and/or reliable crustal velocity models for West Texas. Given the levels of seismicity in West Texas, a plan to continuously monitor the study area is under development.
Semi-Supervised Multi-View Learning for Gene Network Reconstruction

PubMed Central

Ceci, Michelangelo; Pio, Gianvito; Kuzmanovski, Vladimir; Džeroski, Sašo

2015-01-01

The task of gene regulatory network reconstruction from high-throughput data is receiving increasing attention in recent years. As a consequence, many inference methods for solving this task have been proposed in the literature. It has been recently observed, however, that no single inference method performs optimally across all datasets. It has also been shown that the integration of predictions from multiple inference methods is more robust and shows high performance across diverse datasets. Inspired by this research, in this paper, we propose a machine learning solution which learns to combine predictions from multiple inference methods. While this approach adds additional complexity to the inference process, we expect it would also carry substantial benefits. These would come from the automatic adaptation to patterns on the outputs of individual inference methods, so that it is possible to identify regulatory interactions more reliably when these patterns occur. This article demonstrates the benefits (in terms of accuracy of the reconstructed networks) of the proposed method, which exploits an iterative, semi-supervised ensemble-based algorithm. The algorithm learns to combine the interactions predicted by many different inference methods in the multi-view learning setting. The empirical evaluation of the proposed algorithm on a prokaryotic model organism (E. coli) and on a eukaryotic model organism (S. cerevisiae) clearly shows improved performance over the state of the art methods. The results indicate that gene regulatory network reconstruction for the real datasets is more difficult for S. cerevisiae than for E. coli. The software, all the datasets used in the experiments and all the results are available for download at the following link: http://figshare.com/articles/Semi_supervised_Multi_View_Learning_for_Gene_Network_Reconstruction/1604827. PMID:26641091
Impact of symmetry breaking in networks of globally coupled oscillators

NASA Astrophysics Data System (ADS)

Premalatha, K.; Chandrasekar, V. K.; Senthilvelan, M.; Lakshmanan, M.

2015-05-01

We analyze the consequences of symmetry breaking in the coupling in a network of globally coupled identical Stuart-Landau oscillators. We observe that symmetry breaking leads to increased disorderliness in the dynamical behavior of oscillatory states and consequently results in a rich variety of dynamical states. Depending on the strength of the nonisochronicity parameter, we find various dynamical states such as amplitude chimera, amplitude cluster, frequency chimera, and frequency cluster states. In addition we also find disparate transition routes to recently observed chimera death states in the presence of symmetry breaking even with global coupling. We also analytically verify the chimera death region, which corroborates the numerical results. These results are compared with that of the symmetry-preserving case as well.
Deep brain stimulation mechanisms: beyond the concept of local functional inhibition.

PubMed

Deniau, Jean-Michel; Degos, Bertrand; Bosch, Clémentine; Maurice, Nicolas

2010-10-01

Deep brain electrical stimulation has become a recognized therapy in the treatment of a variety of motor disorders and has potentially promising applications in a wide range of neurological diseases including neuropsychiatry. Behavioural observation that electrical high-frequency stimulation of a given brain area induces an effect similar to a lesion suggested a mechanism of functional inhibition. In vitro and in vivo experiments as well as per operative recordings in patients have revealed a variety of effects involving local changes of neuronal excitability as well as widespread effects throughout the connected network resulting from activation of axons, including antidromic activation. Here we review current data regarding the local and network activity changes induced by high-frequency stimulation of the subthalamic nucleus and discuss this in the context of motor restoration in Parkinson's disease. Stressing the important functional consequences of axonal activation in deep brain stimulation mechanisms, we highlight the importance of developing anatomical knowledge concerning the fibre connections of the putative therapeutic targets. © 2010 The Authors. European Journal of Neuroscience © 2010 Federation of European Neuroscience Societies and Blackwell Publishing Ltd.
Indirect adaptive fuzzy wavelet neural network with self- recurrent consequent part for AC servo system.

PubMed

Hou, Runmin; Wang, Li; Gao, Qiang; Hou, Yuanglong; Wang, Chao

2017-09-01

This paper proposes a novel indirect adaptive fuzzy wavelet neural network (IAFWNN) to control the nonlinearity, wide variations in loads, time-variation and uncertain disturbance of the ac servo system. In the proposed approach, the self-recurrent wavelet neural network (SRWNN) is employed to construct an adaptive self-recurrent consequent part for each fuzzy rule of TSK fuzzy model. For the IAFWNN controller, the online learning algorithm is based on back propagation (BP) algorithm. Moreover, an improved particle swarm optimization (IPSO) is used to adapt the learning rate. The aid of an adaptive SRWNN identifier offers the real-time gradient information to the adaptive fuzzy wavelet neural controller to overcome the impact of parameter variations, load disturbances and other uncertainties effectively, and has a good dynamic. The asymptotical stability of the system is guaranteed by using the Lyapunov method. The result of the simulation and the prototype test prove that the proposed are effective and suitable. Copyright © 2017. Published by Elsevier Ltd.
Keeping the Vimentin Network under Control: Cell–Matrix Adhesion–associated Plectin 1f Affects Cell Shape and Polarity of Fibroblasts

PubMed Central

Burgstaller, Gerald; Gregor, Martin; Winter, Lilli

2010-01-01

Focal adhesions (FAs) located at the ends of actin/myosin-containing contractile stress fibers form tight connections between fibroblasts and their underlying extracellular matrix. We show here that mature FAs and their derivative fibronectin fibril-aligned fibrillar adhesions (FbAs) serve as docking sites for vimentin intermediate filaments (IFs) in a plectin isoform 1f (P1f)-dependent manner. Time-lapse video microscopy revealed that FA-associated P1f captures mobile vimentin filament precursors, which then serve as seeds for de novo IF network formation via end-to-end fusion with other mobile precursors. As a consequence of IF association, the turnover of FAs is reduced. P1f-mediated IF network formation at FbAs creates a resilient cage-like core structure that encases and positions the nucleus while being stably connected to the exterior of the cell. We show that the formation of this structure affects cell shape with consequences for cell polarization. PMID:20702585
Exploring the Genomic Roadmap and Molecular Phylogenetics Associated with MODY Cascades Using Computational Biology.

PubMed

Chakraborty, Chiranjib; Bandyopadhyay, Sanghamitra; Doss, C George Priya; Agoramoorthy, Govindasamy

2015-04-01

Maturity onset diabetes of the young (MODY) is a metabolic and genetic disorder. It is different from type 1 and type 2 diabetes with low occurrence level (1-2%) among all diabetes. This disorder is a consequence of β-cell dysfunction. Till date, 11 subtypes of MODY have been identified, and all of them can cause gene mutations. However, very little is known about the gene mapping, molecular phylogenetics, and co-expression among MODY genes and networking between cascades. This study has used latest servers and software such as VarioWatch, ClustalW, MUSCLE, G Blocks, Phylogeny.fr, iTOL, WebLogo, STRING, and KEGG PATHWAY to perform comprehensive analyses of gene mapping, multiple sequences alignment, molecular phylogenetics, protein-protein network design, co-expression analysis of MODY genes, and pathway development. The MODY genes are located in chromosomes-2, 7, 8, 9, 11, 12, 13, 17, and 20. Highly aligned block shows Pro, Gly, Leu, Arg, and Pro residues are highly aligned in the positions of 296, 386, 437, 455, 456 and 598, respectively. Alignment scores inform us that HNF1A and HNF1B proteins have shown high sequence similarity among MODY proteins. Protein-protein network design shows that HNF1A, HNF1B, HNF4A, NEUROD1, PDX1, PAX4, INS, and GCK are strongly connected, and the co-expression analyses between MODY genes also show distinct association between HNF1A and HNF4A genes. This study has used latest tools of bioinformatics to develop a rapid method to assess the evolutionary relationship, the network development, and the associations among eleven MODY genes and cascades. The prediction of sequence conservation, molecular phylogenetics, protein-protein network and the association between the MODY cascades enhances opportunities to get more insights into the less-known MODY disease.
Briefer assessment of social network drinking: A test of the Important People Instrument-5 (IP-5).

PubMed

Hallgren, Kevin A; Barnett, Nancy P

2016-12-01

The Important People instrument (IP; Longabaugh et al., 2010) is one of the most commonly used measures of social network drinking. Although its reliability and validity are well-supported, the length of the instrument may limit its use in many settings. The present study evaluated whether a briefer, 5-person version of the IP (IP-5) adequately reproduces scores from the full IP. College freshmen (N = 1,053) reported their own past-month drinking, alcohol-related consequences, and information about drinking in their close social networks at baseline and 1 year later. From this we derived network members' drinking frequency, percentage of drinkers, and percentage of heavy drinkers, assessed for up to 10 (full IP) or 5 (IP-5) network members. We first modeled the expected concordance between full-IP scores and scores from simulated shorter IP instruments by sampling smaller subsets of network members from full IP data. Then, using quasi-experimental methods, we administered the full IP and IP-5 and compared the 2 instruments' score distributions and concurrent and year-lagged associations with participants' alcohol consumption and consequences. Most of the full-IP variance was reproduced from simulated shorter versions of the IP (ICCs ≥ 0.80). The full IP and IP-5 yielded similar score distributions, concurrent associations with drinking (r = 0.22 to 0.52), and year-lagged associations with drinking. The IP-5 retains most of the information about social network drinking from the full IP. The shorter instrument may be useful in clinical and research settings that require frequent measure administration, yielding greater temporal resolution for monitoring social network drinking. (PsycINFO Database Record (c) 2017 APA, all rights reserved).
Understanding the Construction of Personal Learning Networks to Support Non-Formal Workplace Learning of Training Professionals

ERIC Educational Resources Information Center

Manning, Christin

2013-01-01

Workers in the 21st century workplace are faced with rapid and constant developments that place a heavy demand on them to continually learn beyond what the Human Resources and Training groups can meet. As a consequence, professionals must rely on non-formal learning approaches through the development of a personal learning network to keep…

SPECIAL PURPOSE IT DERAILED: UNINTENDED CONSEQUENCES OF UNIVERSAL IT LAWS AND POLICIES

DTIC Science & Technology

2017-10-26

Information Services Division ........................ 3 Figure 2: iNET Instrumentation Telemetry Ground Station...consolidate local Information Technology (IT) networks into an enterprise architecture to reduce costs and to increase security. Leadership coined this...IT network was established to link Air Force and contractor sites to seamlessly share program information . So when Air Force IT leadership tried to
Findings on Facebook in Higher Education: A Comparison of College Faculty and Student Uses and Perceptions of Social Networking Sites

ERIC Educational Resources Information Center

Roblyer, M. D.; McDaniel, Michelle; Webb, Marsena; Herman, James; Witty, James Vince

2010-01-01

Social Networking Sites (SNSs) such as Facebook are one of the latest examples of communications technologies that have been widely-adopted by students and, consequently, have the potential to become a valuable resource to support their educational communications and collaborations with faculty. However, faculty members have a track record of…
A Study of How Young Adults Leverage Multiple Profile Management Functionality in Managing Their Online Reputation on Social Networking Sites

ERIC Educational Resources Information Center

McCune, T. John

2017-01-01

With privacy settings on social networking sites (SNS) perceived as complex and difficult to use and maintain, young adults can be left vulnerable to others accessing and using their personal information. Consequences of not regulating the boundaries their information on SNS include the ability for current and future employers to make…
Network Stability Is a Balancing Act of Personality, Power, and Conflict Dynamics in Rhesus Macaque Societies

PubMed Central

McCowan, Brenda; Beisner, Brianne A.; Capitanio, John P.; Jackson, Megan E.; Cameron, Ashley N.; Seil, Shannon; Atwill, Edward R.; Fushing, Hsieh

2011-01-01

Stability in biological systems requires evolved mechanisms that promote robustness. Cohesive primate social groups represent one example of a stable biological system, which persist in spite of frequent conflict. Multiple sources of stability likely exist for any biological system and such robustness, or lack thereof, should be reflected and thus detectable in the group's network structure, and likely at multiple levels. Here we show how network structure and group stability are linked to the fundamental characteristics of the individual agents in groups and to the environmental and social contexts in which these individuals interact. Both internal factors (e.g., personality, sex) and external factors (e.g., rank dynamics, sex ratio) were considered from the level of the individual to that of the group to examine the effects of network structure on group stability in a nonhuman primate species. The results yielded three main findings. First, successful third-party intervention behavior is a mechanism of group stability in rhesus macaques in that successful interventions resulted in less wounding in social groups. Second, personality is the primary factor that determines which individuals perform the role of key intervener, via its effect on social power and dominance discrepancy. Finally, individuals with high social power are not only key interveners but also key players in grooming networks and receive reconciliations from a higher diversity of individuals. The results from this study provide sound evidence that individual and group characteristics such as personality and sex ratio influence network structures such as patterns of reconciliation, grooming and conflict intervention that are indicators of network robustness and consequent health and well-being in rhesus macaque societies. Utilizing this network approach has provided greater insight into how behavioral and social processes influence social stability in nonhuman primate groups. PMID:21857922
Network stability is a balancing act of personality, power, and conflict dynamics in rhesus macaque societies.

PubMed

McCowan, Brenda; Beisner, Brianne A; Capitanio, John P; Jackson, Megan E; Cameron, Ashley N; Seil, Shannon; Atwill, Edward R; Fushing, Hsieh

2011-01-01

Stability in biological systems requires evolved mechanisms that promote robustness. Cohesive primate social groups represent one example of a stable biological system, which persist in spite of frequent conflict. Multiple sources of stability likely exist for any biological system and such robustness, or lack thereof, should be reflected and thus detectable in the group's network structure, and likely at multiple levels. Here we show how network structure and group stability are linked to the fundamental characteristics of the individual agents in groups and to the environmental and social contexts in which these individuals interact. Both internal factors (e.g., personality, sex) and external factors (e.g., rank dynamics, sex ratio) were considered from the level of the individual to that of the group to examine the effects of network structure on group stability in a nonhuman primate species. The results yielded three main findings. First, successful third-party intervention behavior is a mechanism of group stability in rhesus macaques in that successful interventions resulted in less wounding in social groups. Second, personality is the primary factor that determines which individuals perform the role of key intervener, via its effect on social power and dominance discrepancy. Finally, individuals with high social power are not only key interveners but also key players in grooming networks and receive reconciliations from a higher diversity of individuals. The results from this study provide sound evidence that individual and group characteristics such as personality and sex ratio influence network structures such as patterns of reconciliation, grooming and conflict intervention that are indicators of network robustness and consequent health and well-being in rhesus macaque societies. Utilizing this network approach has provided greater insight into how behavioral and social processes influence social stability in nonhuman primate groups.
Participation and coordination in Dutch health care policy-making. A network analysis of the system of intermediate organizations in Dutch health care.

PubMed

Lamping, Antonie J; Raab, Jörg; Kenis, Patrick

2013-06-01

This study explores the system of intermediate organizations in Dutch health care as the crucial system to understand health care policy-making in the Netherlands. We argue that the Dutch health care system can be understood as a system consisting of distinct but inter-related policy domains. In this study, we analyze four such policy domains: Finances, quality of care, manpower planning and pharmaceuticals. With the help of network analytic techniques, we describe how this highly differentiated system of >200 intermediate organizations is structured and coordinated and what (policy) consequences can be observed with regard to its particular structure and coordination mechanisms. We further analyze the extent to which this system of intermediate organizations enables participation of stakeholders in policy-making using network visualization tools. The results indicate that coordination between the different policy domains within the health care sector takes place not as one would expect through governmental agencies, but through representative organizations such as the representative organizations of the (general) hospitals, the health care consumers and the employers' association. We further conclude that the system allows as well as denies a large number of potential participants access to the policy-making process. As a consequence, the representation of interests is not necessarily balanced, which in turn affects health care policy. We find that the interests of the Dutch health care consumers are well accommodated with the national umbrella organization NPCF in the lead. However, this is no safeguard for the overall community values of good health care since, for example, the interests of the public health sector are likely to be marginalized.
The development of computer networks: First results from a microeconomic model

NASA Astrophysics Data System (ADS)

Maier, Gunther; Kaufmann, Alexander

Computer networks like the Internet are gaining importance in social and economic life. The accelerating pace of the adoption of network technologies for business purposes is a rather recent phenomenon. Many applications are still in the early, sometimes even experimental, phase. Nevertheless, it seems to be certain that networks will change the socioeconomic structures we know today. This is the background for our special interest in the development of networks, in the role of spatial factors influencing the formation of networks, and consequences of networks on spatial structures, and in the role of externalities. This paper discusses a simple economic model - based on a microeconomic calculus - that incorporates the main factors that generate the growth of computer networks. The paper provides analytic results about the generation of computer networks. The paper discusses (1) under what conditions economic factors will initiate the process of network formation, (2) the relationship between individual and social evaluation, and (3) the efficiency of a network that is generated based on economic mechanisms.
Estimating the strength of bone using linear response

NASA Astrophysics Data System (ADS)

Gunaratne, Gemunu H.

2002-12-01

Accurate diagnostic tools are required for effective management of osteoporosis; one method to identify additional diagnostics is to search for observable consequences of bone loss. An analysis of a model system is used to show that weakening of a bone is accompanied by a reduction of the fraction of the bone that participates in load transmission. On the basis of this observation, it is argued that the ratio Γ of linear responses of a network to dc and high-frequency ac driving can be used as a surrogate for their strength. Protocols needed to obtain Γ for bone samples are discussed.
A Millimeter-wave Cavity-backed Suspended Substrate Stripline Antenna

NASA Technical Reports Server (NTRS)

Simons, Rainee N.

1999-01-01

Future generation satellite communication systems in near-Earth orbit will operate at frequencies in the higher mm-wave frequency hands. These satellite systems require low-profile, high gain, light weight and low cost antennas for communications to and from Earth as well as for inter-satellite links (ISL). At higher mm-wave frequencies, the conductor loss of conventional microstrip line is high and consequently the feed network loss of patch antenna arrays is also high. The high loss lowers the array efficiency and in addition lowers the G/T ratio in a receiving array. Recently a radial line slot antenna array has been demonstrated to have high gain and efficiency at 60 GHz. In this paper, the design, fabrication and characterization of a V-Band (50-75 GHz) 4 x 4 planar array of cavity backed circular aperture antennas with suspended substrate stripline (SSS) corporate feed is presented.
The Widening Gulf between Genomics Data Generation and Consumption: A Practical Guide to Big Data Transfer Technology

PubMed Central

Feltus, Frank A.; Breen, Joseph R.; Deng, Juan; Izard, Ryan S.; Konger, Christopher A.; Ligon, Walter B.; Preuss, Don; Wang, Kuang-Ching

2015-01-01

In the last decade, high-throughput DNA sequencing has become a disruptive technology and pushed the life sciences into a distributed ecosystem of sequence data producers and consumers. Given the power of genomics and declining sequencing costs, biology is an emerging “Big Data” discipline that will soon enter the exabyte data range when all subdisciplines are combined. These datasets must be transferred across commercial and research networks in creative ways since sending data without thought can have serious consequences on data processing time frames. Thus, it is imperative that biologists, bioinformaticians, and information technology engineers recalibrate data processing paradigms to fit this emerging reality. This review attempts to provide a snapshot of Big Data transfer across networks, which is often overlooked by many biologists. Specifically, we discuss four key areas: 1) data transfer networks, protocols, and applications; 2) data transfer security including encryption, access, firewalls, and the Science DMZ; 3) data flow control with software-defined networking; and 4) data storage, staging, archiving and access. A primary intention of this article is to orient the biologist in key aspects of the data transfer process in order to frame their genomics-oriented needs to enterprise IT professionals. PMID:26568680
A hydrogeomorphic river network model predicts where and why hyporheic exchange is important in large basins

USGS Publications Warehouse

Gomez-Velez, Jesus D.; Harvey, Judson

2014-01-01

Hyporheic exchange has been hypothesized to have basin-scale consequences; however, predictions throughout river networks are limited by available geomorphic and hydrogeologic data and by models that can analyze and aggregate hyporheic exchange flows across large spatial scales. We developed a parsimonious but physically based model of hyporheic flow for application in large river basins: Networks with EXchange and Subsurface Storage (NEXSS). We applied NEXSS across a broad range of geomorphic diversity in river reaches and synthetic river networks. NEXSS demonstrates that vertical exchange beneath submerged bed forms rather than lateral exchange through meanders dominates hyporheic fluxes and turnover rates along river corridors. Per kilometer, low-order streams have a biogeochemical potential at least 2 orders of magnitude larger than higher-order streams. However, when biogeochemical potential is examined per average length of each stream order, low- and high-order streams were often found to be comparable. As a result, the hyporheic zone's intrinsic potential for biogeochemical transformations is comparable across different stream orders, but the greater river miles and larger total streambed area of lower order streams result in the highest cumulative impact from low-order streams. Lateral exchange through meander banks may be important in some cases but generally only in large rivers.
A hydrogeomorphic river network model predicts where and why hyporheic exchange is important in large basins

NASA Astrophysics Data System (ADS)

Gomez-Velez, Jesus D.; Harvey, Judson W.

2014-09-01

Hyporheic exchange has been hypothesized to have basin-scale consequences; however, predictions throughout river networks are limited by available geomorphic and hydrogeologic data and by models that can analyze and aggregate hyporheic exchange flows across large spatial scales. We developed a parsimonious but physically based model of hyporheic flow for application in large river basins: Networks with EXchange and Subsurface Storage (NEXSS). We applied NEXSS across a broad range of geomorphic diversity in river reaches and synthetic river networks. NEXSS demonstrates that vertical exchange beneath submerged bed forms rather than lateral exchange through meanders dominates hyporheic fluxes and turnover rates along river corridors. Per kilometer, low-order streams have a biogeochemical potential at least 2 orders of magnitude larger than higher-order streams. However, when biogeochemical potential is examined per average length of each stream order, low- and high-order streams were often found to be comparable. As a result, the hyporheic zone's intrinsic potential for biogeochemical transformations is comparable across different stream orders, but the greater river miles and larger total streambed area of lower order streams result in the highest cumulative impact from low-order streams. Lateral exchange through meander banks may be important in some cases but generally only in large rivers.
A minimal titration model of the mammalian dynamical heat shock response

NASA Astrophysics Data System (ADS)

Sivéry, Aude; Courtade, Emmanuel; Thommen, Quentin

2016-12-01

Environmental stress, such as oxidative or heat stress, induces the activation of the heat shock response (HSR) and leads to an increase in the heat shock proteins (HSPs) level. These HSPs act as molecular chaperones to maintain cellular proteostasis. Controlled by highly intricate regulatory mechanisms, having stress-induced activation and feedback regulations with multiple partners, the HSR is still incompletely understood. In this context, we propose a minimal molecular model for the gene regulatory network of the HSR that reproduces quantitatively different heat shock experiments both on heat shock factor 1 (HSF1) and HSPs activities. This model, which is based on chemical kinetics laws, is kept with a low dimensionality without altering the biological interpretation of the model dynamics. This simplistic model highlights the titration of HSF1 by chaperones as the guiding line of the network. Moreover, by a steady states analysis of the network, three different temperature stress regimes appear: normal, acute, and chronic, where normal stress corresponds to pseudo thermal adaption. The protein triage that governs the fate of damaged proteins or the different stress regimes are consequences of the titration mechanism. The simplicity of the present model is of interest in order to study detailed modelling of cross regulation between the HSR and other major genetic networks like the cell cycle or the circadian clock.
Efficient priority queueing routing strategy on networks of mobile agents

NASA Astrophysics Data System (ADS)

Wu, Gan-Hua; Yang, Hui-Jie; Pan, Jia-Hui

2018-03-01

As a consequence of their practical implications for communications networks, traffic dynamics on complex networks have recently captivated researchers. Previous routing strategies for improving transport efficiency have paid little attention to the orders in which the packets should be forwarded, just simply used first-in-first-out queue discipline. Here, we apply a priority queuing discipline and propose a shortest-distance-first routing strategy on networks of mobile agents. Numerical experiments reveal that the proposed scheme remarkably improves both the network throughput and the packet arrival rate and reduces both the average traveling time and the rate of waiting time to traveling time. Moreover, we find that the network capacity increases with an increase in both the communication radius and the number of agents. Our work may be helpful for the design of routing strategies on networks of mobile agents.
Automated Wildfire Detection Through Artificial Neural Networks

NASA Technical Reports Server (NTRS)

Miller, Jerry; Borne, Kirk; Thomas, Brian; Huang, Zhenping; Chi, Yuechen

2005-01-01

Wildfires have a profound impact upon the biosphere and our society in general. They cause loss of life, destruction of personal property and natural resources and alter the chemistry of the atmosphere. In response to the concern over the consequences of wildland fire and to support the fire management community, the National Oceanic and Atmospheric Administration (NOAA), National Environmental Satellite, Data and Information Service (NESDIS) located in Camp Springs, Maryland gradually developed an operational system to routinely monitor wildland fire by satellite observations. The Hazard Mapping System, as it is known today, allows a team of trained fire analysts to examine and integrate, on a daily basis, remote sensing data from Geostationary Operational Environmental Satellite (GOES), Advanced Very High Resolution Radiometer (AVHRR) and Moderate Resolution Imaging Spectroradiometer (MODIS) satellite sensors and generate a 24 hour fire product for the conterminous United States. Although assisted by automated fire detection algorithms, N O M has not been able to eliminate the human element from their fire detection procedures. As a consequence, the manually intensive effort has prevented NOAA from transitioning to a global fire product as urged particularly by climate modelers. NASA at Goddard Space Flight Center in Greenbelt, Maryland is helping N O M more fully automate the Hazard Mapping System by training neural networks to mimic the decision-making process of the frre analyst team as well as the automated algorithms.
Representing Micro-Macro Linkages by Actor-Based Dynamic Network Models

PubMed Central

Snijders, Tom A.B.; Steglich, Christian E.G.

2014-01-01

Stochastic actor-based models for network dynamics have the primary aim of statistical inference about processes of network change, but may be regarded as a kind of agent-based models. Similar to many other agent-based models, they are based on local rules for actor behavior. Different from many other agent-based models, by including elements of generalized linear statistical models they aim to be realistic detailed representations of network dynamics in empirical data sets. Statistical parallels to micro-macro considerations can be found in the estimation of parameters determining local actor behavior from empirical data, and the assessment of goodness of fit from the correspondence with network-level descriptives. This article studies several network-level consequences of dynamic actor-based models applied to represent cross-sectional network data. Two examples illustrate how network-level characteristics can be obtained as emergent features implied by micro-specifications of actor-based models. PMID:25960578
Visibility Graph Based Time Series Analysis.

PubMed

Stephen, Mutua; Gu, Changgui; Yang, Huijie

2015-01-01

Network based time series analysis has made considerable achievements in the recent years. By mapping mono/multivariate time series into networks, one can investigate both it's microscopic and macroscopic behaviors. However, most proposed approaches lead to the construction of static networks consequently providing limited information on evolutionary behaviors. In the present paper we propose a method called visibility graph based time series analysis, in which series segments are mapped to visibility graphs as being descriptions of the corresponding states and the successively occurring states are linked. This procedure converts a time series to a temporal network and at the same time a network of networks. Findings from empirical records for stock markets in USA (S&P500 and Nasdaq) and artificial series generated by means of fractional Gaussian motions show that the method can provide us rich information benefiting short-term and long-term predictions. Theoretically, we propose a method to investigate time series from the viewpoint of network of networks.
Concordant Chemical Reaction Networks

PubMed Central

Shinar, Guy; Feinberg, Martin

2015-01-01

We describe a large class of chemical reaction networks, those endowed with a subtle structural property called concordance. We show that the class of concordant networks coincides precisely with the class of networks which, when taken with any weakly monotonic kinetics, invariably give rise to kinetic systems that are injective — a quality that, among other things, precludes the possibility of switch-like transitions between distinct positive steady states. We also provide persistence characteristics of concordant networks, instability implications of discordance, and consequences of stronger variants of concordance. Some of our results are in the spirit of recent ones by Banaji and Craciun, but here we do not require that every species suffer a degradation reaction. This is especially important in studying biochemical networks, for which it is rare to have all species degrade. PMID:22659063
Bluetooth Roaming for Sensor Network System in Clinical Environment.

PubMed

Kuroda, Tomohiro; Noma, Haruo; Takase, Kazuhiko; Sasaki, Shigeto; Takemura, Tadamasa

2015-01-01

A sensor network is key infrastructure for advancing a hospital information system (HIS). The authors proposed a method to provide roaming functionality for Bluetooth to realize a Bluetooth-based sensor network, which is suitable to connect clinical devices. The proposed method makes the average response time of a Bluetooth connection less than one second by making the master device repeat the inquiry process endlessly and modifies parameters of the inquiry process. The authors applied the developed sensor network for daily clinical activities in an university hospital, and confirmed the stabilitya and effectiveness of the sensor network. As Bluetooth becomes a quite common wireless interface for medical devices, the proposed protocol that realizes Bluetooth-based sensor network enables HIS to equip various clinical devices and, consequently, lets information and communication technologies advance clinical services.
Prediction-based association control scheme in dense femtocell networks.

PubMed

Sung, Nak Woon; Pham, Ngoc-Thai; Huynh, Thong; Hwang, Won-Joo; You, Ilsun; Choo, Kim-Kwang Raymond

2017-01-01

The deployment of large number of femtocell base stations allows us to extend the coverage and efficiently utilize resources in a low cost manner. However, the small cell size of femtocell networks can result in frequent handovers to the mobile user, and consequently throughput degradation. Thus, in this paper, we propose predictive association control schemes to improve the system's effective throughput. Our design focuses on reducing handover frequency without impacting on throughput. The proposed schemes determine handover decisions that contribute most to the network throughput and are proper for distributed implementations. The simulation results show significant gains compared with existing methods in terms of handover frequency and network throughput perspective.

Causal influence in neural systems: Reconciling mechanistic-reductionist and statistical perspectives. Comment on "Foundational perspectives on causality in large-scale brain networks" by M. Mannino & S.L. Bressler

NASA Astrophysics Data System (ADS)

Griffiths, John D.

2015-12-01

The modern understanding of the brain as a large, complex network of interacting elements is a natural consequence of the Neuron Doctrine [1,2] that has been bolstered in recent years by the tools and concepts of connectomics. In this abstracted, network-centric view, the essence of neural and cognitive function derives from the flows between network elements of activity and information - or, more generally, causal influence. The appropriate characterization of causality in neural systems, therefore, is a question at the very heart of systems neuroscience.
Controlling extreme events on complex networks

NASA Astrophysics Data System (ADS)

Chen, Yu-Zhong; Huang, Zi-Gang; Lai, Ying-Cheng

2014-08-01

Extreme events, a type of collective behavior in complex networked dynamical systems, often can have catastrophic consequences. To develop effective strategies to control extreme events is of fundamental importance and practical interest. Utilizing transportation dynamics on complex networks as a prototypical setting, we find that making the network ``mobile'' can effectively suppress extreme events. A striking, resonance-like phenomenon is uncovered, where an optimal degree of mobility exists for which the probability of extreme events is minimized. We derive an analytic theory to understand the mechanism of control at a detailed and quantitative level, and validate the theory numerically. Implications of our finding to current areas such as cybersecurity are discussed.
Examining Food Risk in the Large using a Complex, Networked System-of-sytems Approach

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ambrosiano, John; Newkirk, Ryan; Mc Donald, Mark P

2010-12-03

The food production infrastructure is a highly complex system of systems. Characterizing the risks of intentional contamination in multi-ingredient manufactured foods is extremely challenging because the risks depend on the vulnerabilities of food processing facilities and on the intricacies of the supply-distribution networks that link them. A pure engineering approach to modeling the system is impractical because of the overall system complexity and paucity of data. A methodology is needed to assess food contamination risk 'in the large', based on current, high-level information about manufacturing facilities, corrunodities and markets, that will indicate which food categories are most at risk ofmore » intentional contamination and warrant deeper analysis. The approach begins by decomposing the system for producing a multi-ingredient food into instances of two subsystem archetypes: (1) the relevant manufacturing and processing facilities, and (2) the networked corrunodity flows that link them to each other and consumers. Ingredient manufacturing subsystems are modeled as generic systems dynamics models with distributions of key parameters that span the configurations of real facilities. Networks representing the distribution systems are synthesized from general information about food corrunodities. This is done in a series of steps. First, probability networks representing the aggregated flows of food from manufacturers to wholesalers, retailers, other manufacturers, and direct consumers are inferred from high-level approximate information. This is followed by disaggregation of the general flows into flows connecting 'large' and 'small' categories of manufacturers, wholesalers, retailers, and consumers. Optimization methods are then used to determine the most likely network flows consistent with given data. Vulnerability can be assessed for a potential contamination point using a modified CARVER + Shock model. Once the facility and corrunodity flow models are instantiated, a risk consequence analysis can be performed by injecting contaminant at chosen points in the system and propagating the event through the overarching system to arrive at morbidity and mortality figures. A generic chocolate snack cake model, consisting of fluid milk, liquid eggs, and cocoa, is described as an intended proof of concept for multi-ingredient food systems. We aim for an eventual tool that can be used directly by policy makers and planners.« less
The assembly and disassembly of ecological networks.

PubMed

Bascompte, Jordi; Stouffer, Daniel B

2009-06-27

Global change has created a severe biodiversity crisis. Species are driven extinct at an increasing rate, and this has the potential to cause further coextinction cascades. The rate and shape of these coextinction cascades depend very much on the structure of the networks of interactions across species. Understanding network structure and how it relates to network disassembly, therefore, is a priority for system-level conservation biology. This process of network collapse may indeed be related to the process of network build-up, although very little is known about both processes and even less about their relationship. Here we review recent work that provides some preliminary answers to these questions. First, we focus on network assembly by emphasizing temporal processes at the species level, as well as the structural building blocks of complex ecological networks. Second, we focus on network disassembly as a consequence of species extinctions or habitat loss. We conclude by emphasizing some general rules of thumb that can help in building a comprehensive framework to understand the responses of ecological networks to global change.
White matter integrity in brain networks relevant to anxiety and depression: evidence from the human connectome project dataset.

PubMed

De Witte, Nele A J; Mueller, Sven C

2017-12-01

Anxiety and depression are associated with altered communication within global brain networks and between these networks and the amygdala. Functional connectivity studies demonstrate an effect of anxiety and depression on four critical brain networks involved in top-down attentional control (fronto-parietal network; FPN), salience detection and error monitoring (cingulo-opercular network; CON), bottom-up stimulus-driven attention (ventral attention network; VAN), and default mode (default mode network; DMN). However, structural evidence on the white matter (WM) connections within these networks and between these networks and the amygdala is lacking. The current study in a large healthy sample (n = 483) observed that higher trait anxiety-depression predicted lower WM integrity in the connections between amygdala and specific regions of the FPN, CON, VAN, and DMN. We discuss the possible consequences of these anatomical alterations for cognitive-affective functioning and underscore the need for further theory-driven research on individual differences in anxiety and depression on brain structure.
Advanced Optical Burst Switched Network Concepts

NASA Astrophysics Data System (ADS)

Nejabati, Reza; Aracil, Javier; Castoldi, Piero; de Leenheer, Marc; Simeonidou, Dimitra; Valcarenghi, Luca; Zervas, Georgios; Wu, Jian

In recent years, as the bandwidth and the speed of networks have increased significantly, a new generation of network-based applications using the concept of distributed computing and collaborative services is emerging (e.g., Grid computing applications). The use of the available fiber and DWDM infrastructure for these applications is a logical choice offering huge amounts of cheap bandwidth and ensuring global reach of computing resources [230]. Currently, there is a great deal of interest in deploying optical circuit (wavelength) switched network infrastructure for distributed computing applications that require long-lived wavelength paths and address the specific needs of a small number of well-known users. Typical users are particle physicists who, due to their international collaborations and experiments, generate enormous amounts of data (Petabytes per year). These users require a network infrastructures that can support processing and analysis of large datasets through globally distributed computing resources [230]. However, providing wavelength granularity bandwidth services is not an efficient and scalable solution for applications and services that address a wider base of user communities with different traffic profiles and connectivity requirements. Examples of such applications may be: scientific collaboration in smaller scale (e.g., bioinformatics, environmental research), distributed virtual laboratories (e.g., remote instrumentation), e-health, national security and defense, personalized learning environments and digital libraries, evolving broadband user services (i.e., high resolution home video editing, real-time rendering, high definition interactive TV). As a specific example, in e-health services and in particular mammography applications due to the size and quantity of images produced by remote mammography, stringent network requirements are necessary. Initial calculations have shown that for 100 patients to be screened remotely, the network would have to securely transport 1.2 GB of data every 30 s [230]. According to the above explanation it is clear that these types of applications need a new network infrastructure and transport technology that makes large amounts of bandwidth at subwavelength granularity, storage, computation, and visualization resources potentially available to a wide user base for specified time durations. As these types of collaborative and network-based applications evolve addressing a wide range and large number of users, it is infeasible to build dedicated networks for each application type or category. Consequently, there should be an adaptive network infrastructure able to support all application types, each with their own access, network, and resource usage patterns. This infrastructure should offer flexible and intelligent network elements and control mechanism able to deploy new applications quickly and efficiently.
On the Structure of Cortical Microcircuits Inferred from Small Sample Sizes.

PubMed

Vegué, Marina; Perin, Rodrigo; Roxin, Alex

2017-08-30

The structure in cortical microcircuits deviates from what would be expected in a purely random network, which has been seen as evidence of clustering. To address this issue, we sought to reproduce the nonrandom features of cortical circuits by considering several distinct classes of network topology, including clustered networks, networks with distance-dependent connectivity, and those with broad degree distributions. To our surprise, we found that all of these qualitatively distinct topologies could account equally well for all reported nonrandom features despite being easily distinguishable from one another at the network level. This apparent paradox was a consequence of estimating network properties given only small sample sizes. In other words, networks that differ markedly in their global structure can look quite similar locally. This makes inferring network structure from small sample sizes, a necessity given the technical difficulty inherent in simultaneous intracellular recordings, problematic. We found that a network statistic called the sample degree correlation (SDC) overcomes this difficulty. The SDC depends only on parameters that can be estimated reliably given small sample sizes and is an accurate fingerprint of every topological family. We applied the SDC criterion to data from rat visual and somatosensory cortex and discovered that the connectivity was not consistent with any of these main topological classes. However, we were able to fit the experimental data with a more general network class, of which all previous topologies were special cases. The resulting network topology could be interpreted as a combination of physical spatial dependence and nonspatial, hierarchical clustering. SIGNIFICANCE STATEMENT The connectivity of cortical microcircuits exhibits features that are inconsistent with a simple random network. Here, we show that several classes of network models can account for this nonrandom structure despite qualitative differences in their global properties. This apparent paradox is a consequence of the small numbers of simultaneously recorded neurons in experiment: when inferred via small sample sizes, many networks may be indistinguishable despite being globally distinct. We develop a connectivity measure that successfully classifies networks even when estimated locally with a few neurons at a time. We show that data from rat cortex is consistent with a network in which the likelihood of a connection between neurons depends on spatial distance and on nonspatial, asymmetric clustering. Copyright © 2017 the authors 0270-6474/17/378498-13$15.00/0.
Quantifying the Evolution of Melt Ponds in the Marginal Ice Zone Using High Resolution Optical Imagery and Neural Networks

NASA Astrophysics Data System (ADS)

Ortiz, M.; Pinales, J. C.; Graber, H. C.; Wilkinson, J.; Lund, B.

2016-02-01

Melt ponds on sea ice play a significant and complex role on the thermodynamics in the Marginal Ice Zone (MIZ). Ponding reduces the sea ice's ability to reflect sunlight, and in consequence, exacerbates the albedo positive feedback cycle. In order to understand how melt ponds work and their effect on the heat uptake of sea ice, we must quantify ponds through their seasonal evolution first. A semi-supervised neural network three-class learning scheme using a gradient descent with momentum and adaptive learning rate backpropagation function is applied to classify melt ponds/melt areas in the Beaufort Sea region. The network uses high resolution panchromatic satellite images from the MEDEA program, which are collocated with autonomous platform arrays from the Marginal Ice Zone Program, including ice mass-balance buoys, arctic weather stations and wave buoys. The goal of the study is to capture the spatial variation of melt onset and freeze-up of the ponds within the MIZ, and gather ponding statistics such as size and concentration. The innovation of this work comes from training the neural network as the melt ponds evolve over time; making the machine learning algorithm time-dependent, which has not been previously done. We will achieve this by analyzing the image histograms through quantification of the minima and maxima intensity changes as well as linking textural variation information of the imagery. We will compare the evolution of the melt ponds against several different array sites on the sea ice to explore if there are spatial differences among the separated platforms in the MIZ.
Microfluidic approaches for the fabrication of gradient crosslinked networks based on poly(ethylene glycol) and hyperbranched polymers for manipulation of cell interactions

PubMed Central

Pedron, S; Peinado, C; Bosch, P; Benton, J A; Anseth, K S

2011-01-01

High-throughput methods allow rapid examination of parameter space to characterize materials and develop new polymeric formulations for biomaterials applications. One limitation is the difficulty of preparing libraries and performing high-throughput screening with conventional instrumentation and sample preparation. Here, we describe the fabrication of substrate materials with controlled gradients in composition by a rapid method of micromixing followed by a photopolymerization reaction. Specifically, poly(ethylene glycol) dimethacrylate was copolymerized with a hyperbranched multimethacrylate (P1000MA or H30MA) in a gradient manner. The extent of methacrylate conversion and the final network composition were determined by near-infrared spectroscopy, and mechanical properties were measured by nanoindentation. A relationship was observed between the elastic modulus and network crosslinking density. Roughness and hydrophilicity were increased on surfaces with a higher concentration of P1000MA. These results likely relate to a phase segregation process of the hyperbranched macromer that occurs during the photopolymerization reaction. On the other hand, the decrease in the final conversion in H30MA polymerization reactions was attributed to the lower termination rate as a consequence of the softening of the network. Valvular interstitial cell attachment was evaluated on these gradient substrates as a demonstration of studying cell morphology as a function of the local substrate properties. Data revealed that the presence of P1000MA affects cell–material interaction with a higher number of adhered cells and more cell spreading on gradient regions with a higher content of the multifunctional crosslinker. PMID:21105168
Modeling carbachol-induced hippocampal network synchronization using hidden Markov models

NASA Astrophysics Data System (ADS)

Dragomir, Andrei; Akay, Yasemin M.; Akay, Metin

2010-10-01

In this work we studied the neural state transitions undergone by the hippocampal neural network using a hidden Markov model (HMM) framework. We first employed a measure based on the Lempel-Ziv (LZ) estimator to characterize the changes in the hippocampal oscillation patterns in terms of their complexity. These oscillations correspond to different modes of hippocampal network synchronization induced by the cholinergic agonist carbachol in the CA1 region of mice hippocampus. HMMs are then used to model the dynamics of the LZ-derived complexity signals as first-order Markov chains. Consequently, the signals corresponding to our oscillation recordings can be segmented into a sequence of statistically discriminated hidden states. The segmentation is used for detecting transitions in neural synchronization modes in data recorded from wild-type and triple transgenic mice models (3xTG) of Alzheimer's disease (AD). Our data suggest that transition from low-frequency (delta range) continuous oscillation mode into high-frequency (theta range) oscillation, exhibiting repeated burst-type patterns, occurs always through a mode resembling a mixture of the two patterns, continuous with burst. The relatively random patterns of oscillation during this mode may reflect the fact that the neuronal network undergoes re-organization. Further insight into the time durations of these modes (retrieved via the HMM segmentation of the LZ-derived signals) reveals that the mixed mode lasts significantly longer (p < 10-4) in 3xTG AD mice. These findings, coupled with the documented cholinergic neurotransmission deficits in the 3xTG mice model, may be highly relevant for the case of AD.
Percolation in insect nest networks: Evidence for optimal wiring

NASA Astrophysics Data System (ADS)

Valverde, Sergi; Corominas-Murtra, Bernat; Perna, Andrea; Kuntz, Pascale; Theraulaz, Guy; Solé, Ricard V.

2009-06-01

Optimization has been shown to be a driving force for the evolution of some biological structures, such as neural maps in the brain or transport networks. Here we show that insect networks also display characteristic traits of optimality. By using a graph representation of the chamber organization of termite nests and a disordered lattice model, it is found that these spatial nests are close to a percolation threshold. This suggests that termites build efficient systems of galleries spanning most of the nest volume at low cost. The evolutionary consequences are outlined.
Artificial Neural Networks Equivalent to Fuzzy Algebra T-Norm Conjunction Operators

NASA Astrophysics Data System (ADS)

Iliadis, L. S.; Spartalis, S. I.

2007-12-01

This paper describes the construction of three Artificial Neural Networks with fuzzy input and output, imitating the performance of fuzzy algebra conjunction operators. More specifically, it is applied over the results of a previous research effort that used T-Norms in order to produce a characteristic torrential risk index that unified the partial risk indices for the area of Xanthi. Each one of the three networks substitutes a T-Norm and consequently they can be used as equivalent operators. This means that ANN performing Fuzzy Algebra operations can be designed and developed.
The Impact of the Network Topology on the Viral Prevalence: A Node-Based Approach

PubMed Central

Yang, Lu-Xing; Draief, Moez; Yang, Xiaofan

2015-01-01

This paper addresses the impact of the structure of the viral propagation network on the viral prevalence. For that purpose, a new epidemic model of computer virus, known as the node-based SLBS model, is proposed. Our analysis shows that the maximum eigenvalue of the underlying network is a key factor determining the viral prevalence. Specifically, the value range of the maximum eigenvalue is partitioned into three subintervals: viruses tend to extinction very quickly or approach extinction or persist depending on into which subinterval the maximum eigenvalue of the propagation network falls. Consequently, computer virus can be contained by adjusting the propagation network so that its maximum eigenvalue falls into the desired subinterval. PMID:26222539
Prediction of PM10 grades in Seoul, Korea using a neural network model based on synoptic patterns

NASA Astrophysics Data System (ADS)

Hur, S. K.; Oh, H. R.; Ho, C. H.; Kim, J.; Song, C. K.; Chang, L. S.; Lee, J. B.

2016-12-01

As of November 2014, the Korean Ministry of Environment (KME) started forecasting the level of ambient particulate matter with diameters ≤ 10 μm (PM10) as four grades: low (PM10 ≤ 30 μg m-3), moderate (30 < PM10 ≤ 80 μg m-3), high (80 < PM10 ≤ 150 μg m-3), and very high (PM10 > 150 μg m-3). Due to short history of forecast, overall performance of the operational forecasting system and its hit rate for the four PM10 grades are difficult to evaluate. In attempt to provide a statistical reference for the current air quality forecasting system, we hindcasted the four PM10 grades for the cold seasons (October-March) of 2001-2014 in Seoul, Korea using a neural network model based on the synoptic patterns of meteorological fields such as geopotential height, air temperature, relative humidity, and wind. In the form of cosine similarity, the distinctive synoptic patterns for each PM10 grades are well quantified as predictors to train the neural network model. Using these fields as predictors and considering the PM10 concentration in Seoul from the day before prediction as an additional predictor, an overall hit rate of 69% was achieved; the hit rates for the low, moderate, high, and very high PM10 grades were 33%, 83%, 45%, and 33%, respectively. This study reveals that the synoptic patterns of meteorological fields are useful predictors for the identification of favorable conditions for each PM10 grade, and the associated transboundary transport and local accumulation of PM10 from the industrialized regions of China. Consequently, the assessments of predictability obtained from the neural network model in this study are reliable to use as a statistical reference for the current air quality forecasting system.
A Behavioral Taxonomy of Loneliness in Humans and Rhesus Monkeys (Macaca mulatta)

PubMed Central

Capitanio, John P.; Hawkley, Louise C.; Cole, Steven W.; Cacioppo, John T.

2014-01-01

Social relationships endow health and fitness benefits, but considerable variation exists in the extent to which individuals form and maintain salutary social relationships. The mental and physical health effects of social bonds are more strongly related to perceived isolation (loneliness) than to objective social network characteristics. We sought to develop an animal model to facilitate the experimental analysis of the development of, and the behavioral and biological consequences of, loneliness. In Study 1, using a population-based sample of older adults, we examined how loneliness was influenced both by social network size and by the extent to which individuals believed that their daily social interactions reflected their own choice. Results revealed three distinct clusters of individuals: (i) individuals with large networks who believed they had high choice were lowest in loneliness, (ii) individuals with small social networks who believed they had low choice were highest in loneliness, and (iii) the remaining two groups were intermediate and equivalent in loneliness. In Study 2, a similar three-group structure was identified in two separate samples of adult male rhesus monkeys (Macaca mulatta) living in large social groups: (i) those high in sociability who had complex social interaction with a broad range of social partners (putatively low in loneliness), (ii) those low in sociability who showed tentative interactions with certain classes of social partners (putatively high in loneliness), and (iii) those low in sociability who interacted overall at low levels with a broad range of social partners (putatively low or intermediate in loneliness). This taxonomy in monkeys was validated in subsequent experimental social probe studies. These results suggest that, in highly social nonhuman primate species, some animals may show a mismatch between social interest and social attainment that could serve as a useful animal model for experimental and mechanistic studies of loneliness. PMID:25354040
Structural, electronic, and vibrational properties of high-density amorphous silicon: a first-principles molecular-dynamics study.

PubMed

Morishita, Tetsuya

2009-05-21

We report a first-principles study of the structural, electronic, and dynamical properties of high-density amorphous (HDA) silicon, which was found to be formed by pressurizing low-density amorphous (LDA) silicon (a normal amorphous Si) [T. Morishita, Phys. Rev. Lett. 93, 055503 (2004); P. F. McMillan, M. Wilson, D. Daisenberger, and D. Machon, Nature Mater. 4, 680 (2005)]. Striking structural differences between HDA and LDA are revealed. The LDA structure holds a tetrahedral network, while the HDA structure contains a highly distorted tetrahedral network. The fifth neighboring atom in HDA tends to be located at an interstitial position of a distorted tetrahedron composed of the first four neighboring atoms. Consequently, the coordination number of HDA is calculated to be approximately 5 unlike that of LDA. The electronic density of state (EDOS) shows that HDA is metallic, which is consistent with a recent experimental measurement of the electronic resistance of HDA Si. We find from local EDOS that highly distorted tetrahedral configurations enhance the metallic nature of HDA. The vibrational density of state (VDOS) also reflects the structural differences between HDA and LDA. Some of the characteristic vibrational modes of LDA are dematerialized in HDA, indicating the degradation of covalent bonds. The overall profile of the VDOS for HDA is found to be an intermediate between that for LDA and liquid Si under pressure (high-density liquid Si).
Local structure of gallate proton conductors

NASA Astrophysics Data System (ADS)

Giannici, F.; Messana, D.; Longo, A.; Sciortino, L.; Martorana, A.

2009-11-01

Lanthanum barium gallate proton conductors are based on disconnected GaO4 groups. The insertion of hydroxyls in the LaBaGaO4 network proceeds through self-doping with Ba2+, consequent O2- vacancy formation to fulfill charge neutrality. With a structural investigation on self-doped LaBaGaO4 oxides using synchrotron XRD and EXAFS on the Ga K-edge, we find that: (a) the GaO4 tetrahedra retain their size throughout the whole series; (b) the GaO4 tetrahedra rotate as rigid bodies on hydration, leading to the formation of a network of shorter O-O configurations that are stabilized by hydrogen bonds; (c) contraction of the lattice occurs along the a unit cell axis, as a consequence of an overall structural rearrangement of the hydrated solid.
The fractal architecture of cytoplasmic organization: scaling, kinetics and emergence in metabolic networks.

PubMed

Aon, Miguel Antonio; O'Rourke, Brian; Cortassa, Sonia

2004-01-01

In this work, we highlight the links between fractals and scaling in cells and explore the kinetic consequences for biochemical reactions operating in fractal media. Based on the proposal that the cytoskeletal architecture is organized as a percolation lattice, with clusters emerging as fractal forms, the analysis of kinetics in percolation clusters is especially emphasized. A key consequence of this spatiotemporal cytoplasmic organization is that enzyme reactions following Michaelis-Menten or allosteric type kinetics exhibit higher rates in fractal media (for short times and at lower substrate concentrations) at the percolation threshold than in Euclidean media. As a result, considerably faster and higher amplification of enzymatic activity is obtained. Finally, we describe some of the properties bestowed by cytoskeletal organization and dynamics on metabolic networks.
Towards a TWSTFT network time transfer

NASA Astrophysics Data System (ADS)

Jiang, Z.

2008-12-01

TWSTFT (Two Way Satellite Time and Frequency Transfer, TW hereafter) is a major technique used in TAI (International Atomic Time) generation. More than two-thirds of TAI clocks and almost all the primary frequency standards are transferred using TW. Up to now, the only geometry in TAI time transfer is single-link. However, the TAI TW time transfer data are highly redundant. In general, for an N-point network, there are N(N - 1)/2 independently measured links. Among them, only N - 1 will be used. We then have (N2 - 3N + 2)/2 redundant links. As a function of N, the redundant measurements increase quickly (cf figure 1 and table 1). At present, for the European-American network N = 13, but only 12 out of a total of 78 measured links are used in TAI. For the Asia-Pacific regions, N = 8. Full use of the high redundancy is an effective way to improve TAI without new cost. The sum of three TW links that form a closed triangle is the triangle closure. Theoretically a closure is expected to be zero if there are no measurement errors, namely the triangle closure condition. A non-zero closure is a true error and an index of the time link quality. A redundant link sets a geometric constraint. There are (N2 - 3N + 2)/2 independent conditions in a network. In 2006, Jiang and Petit (Proc. EFTF 2006 pp 468-75) proposed a mathematical model to adjust the closures to zero by global network processing. In consequence, time transfer between any two points through any link(s) in the network gives exactly the same result with the same uncertainty. This is the so-called network time transfer. In this paper, the author introduces his recent works on completing the network model by adding the calibration, the uncertainty estimation and the quality assessment using GPS PPP (time transfer by precise point positioning (PPP hereafter)) (Kouba and Héroux 2001 GPS Solut. 5 12-28, Ray and Senior 2005 Metrologia 42 215-32, Orgiazzi et al 2005 Proc. IEEE FCS 2005 pp 337-45, Defraigne et al 2007 Proc. EFTF 2007 pp 909-13, Petit and Jiang 2008 Int. J. Navig. Obs. 2008 1-8). As an independent technique with higher short-term stability, PPP is then a good reference to evaluate the improvement in the network time transfer. The gain is at least 30%. The new method also gives a solution for the high redundancy in the TAI international TW time transfer network. The TAI software Tsoft is operational to perform the network time transfer.
High-speed laser communications in UAV scenarios

NASA Astrophysics Data System (ADS)

Griethe, Wolfgang; Gregory, Mark; Heine, Frank; Kämpfner, Hartmut

2011-05-01

Optical links, based on coherent homodyne detection and BPSK modulation with bidirectional data transmission of 5.6 Gbps over distances of about 5,000 km and BER of 10-8, have been sufficiently verified in space. The verification results show that this technology is suitable not only for space applications but also for applications in the troposphere. After a brief description of the Laser Communication Terminal (LCT) for space applications, the paper consequently discusses the future utilization of satellite-based optical data links for Beyond Line of Sight (BLOS) operations of High Altitude Long Endurance (HALE) Unmanned Aerial Vehicles (UAV). It is shown that the use of optical frequencies is the only logical consequence of an ever-increasing demand for bandwidth. In terms of Network Centric Warfare it is highly recommended that Unmanned Aircraft Systems (UAS) of the future should incorporate that technology which allows almost unlimited bandwidth. The advantages of optical communications especially for Intelligence, Surveillance and Reconnaissance (ISR) are underlined. Moreover, the preliminary design concept of an airborne laser communication terminal is described. Since optical bi-directional links have been tested between a LCT in space and a TESAT Optical Ground Station (OGS), preliminary analysis on tracking and BER performance and the impact of atmospheric disturbances on coherent links will be presented.

Microwave characterization of slotline on high resistivity silicon for antenna feed network

NASA Technical Reports Server (NTRS)

Simons, Rainee N.; Taub, Susan R.; Lee, Richard Q.; Young, Paul G.

1993-01-01

Conventional silicon wafers have low resistivity and consequently unacceptably high value of dielectric attenuation constant. Microwave circuits for phased array antenna systems fabricated on these wafers therefore have low efficiency. By choosing a silicon substrate with sufficiently high resistivity it is possible to make the dielectric attenuation constant of the interconnecting microwave transmission lines approach those of GaAs or InP. In order for this to be possible, the transmission lines must be characterized. In this presentation, the effective dielectric constant (epsilon sub eff) and attenuation constant (alpha) of a slotline on high resistivity (5000 to 10 000 ohm-cm) silicon wafer will be discussed. The epsilon sub eff and alpha are determined from the measured resonant frequencies and the corresponding insertion loss of a slotline ring resonator. The results for slotline will be compared with microstrip line and coplanar waveguide.
Co-expression network analysis of duplicate genes in maize (Zea mays L.) reveals no subgenome bias.

PubMed

Li, Lin; Briskine, Roman; Schaefer, Robert; Schnable, Patrick S; Myers, Chad L; Flagel, Lex E; Springer, Nathan M; Muehlbauer, Gary J

2016-11-04

Gene duplication is prevalent in many species and can result in coding and regulatory divergence. Gene duplications can be classified as whole genome duplication (WGD), tandem and inserted (non-syntenic). In maize, WGD resulted in the subgenomes maize1 and maize2, of which maize1 is considered the dominant subgenome. However, the landscape of co-expression network divergence of duplicate genes in maize is still largely uncharacterized. To address the consequence of gene duplication on co-expression network divergence, we developed a gene co-expression network from RNA-seq data derived from 64 different tissues/stages of the maize reference inbred-B73. WGD, tandem and inserted gene duplications exhibited distinct regulatory divergence. Inserted duplicate genes were more likely to be singletons in the co-expression networks, while WGD duplicate genes were likely to be co-expressed with other genes. Tandem duplicate genes were enriched in the co-expression pattern where co-expressed genes were nearly identical for the duplicates in the network. Older gene duplications exhibit more extensive co-expression variation than younger duplications. Overall, non-syntenic genes primarily from inserted duplications show more co-expression divergence. Also, such enlarged co-expression divergence is significantly related to duplication age. Moreover, subgenome dominance was not observed in the co-expression networks - maize1 and maize2 exhibit similar levels of intra subgenome correlations. Intriguingly, the level of inter subgenome co-expression was similar to the level of intra subgenome correlations, and genes from specific subgenomes were not likely to be the enriched in co-expression network modules and the hub genes were not predominantly from any specific subgenomes in maize. Our work provides a comprehensive analysis of maize co-expression network divergence for three different types of gene duplications and identifies potential relationships between duplication types, duplication ages and co-expression consequences.
Improving Societal Resilience Through Enhanced Reconnection Speed of Damaged Networks

NASA Astrophysics Data System (ADS)

Vodák, Rostislav; Bíl, Michal

2017-04-01

Road networks rank among the foundations of civilization. They enable people, services and goods to be transported to arbitrary places at any time. Its functioning can be impacted by various events, not only by natural hazards and their combinations. This can lead to the concurrent interruption of a number of roads and even cut-off parts of the network from vital services. The impact of these events can be reduced by various measures, but cannot be fully eliminated. We are aware of the fact that extreme events which result in road network break up will occur regardless of the ongoing process of hazard reduction using, for example, the improvement of the structural robustness of roads. The next problem is that many of the events are unpredictable and thus the needed costs of the improvement can easily spiral out of control. We therefore focus on the speed of the recovery process which can be optimized. This means that the time during which the damaged network is reconnected again will be as short as possible. The result of the optimization procedure is a sequence of road links which represent the routes of the repair units. The optimization process is, however, highly nontrivial because of the large number of possible routes for repair units. This prevents anyone from finding an optimal solution. We consequently introduce an approach based on the Ant Colony Optimization algorithm which is able to suggest an almost optimal solution under various constraints which can be established by the administrator of the network. We will also demonstrate its results and variability with several case examples.
Continuous time limits of the utterance selection model

NASA Astrophysics Data System (ADS)

Michaud, Jérôme

2017-02-01

In this paper we derive alternative continuous time limits of the utterance selection model (USM) for language change [G. J. Baxter et al., Phys. Rev. E 73, 046118 (2006), 10.1103/PhysRevE.73.046118]. This is motivated by the fact that the Fokker-Planck continuous time limit derived in the original version of the USM is only valid for a small range of parameters. We investigate the consequences of relaxing these constraints on parameters. Using the normal approximation of the multinomial approximation, we derive a continuous time limit of the USM in the form of a weak-noise stochastic differential equation. We argue that this weak noise, not captured by the Kramers-Moyal expansion, cannot be neglected. We then propose a coarse-graining procedure, which takes the form of a stochastic version of the heterogeneous mean field approximation. This approximation groups the behavior of nodes of the same degree, reducing the complexity of the problem. With the help of this approximation, we study in detail two simple families of networks: the regular networks and the star-shaped networks. The analysis reveals and quantifies a finite-size effect of the dynamics. If we increase the size of the network by keeping all the other parameters constant, we transition from a state where conventions emerge to a state where no convention emerges. Furthermore, we show that the degree of a node acts as a time scale. For heterogeneous networks such as star-shaped networks, the time scale difference can become very large, leading to a noisier behavior of highly connected nodes.
Structural and Functional Characterization of a Caenorhabditis elegans Genetic Interaction Network within Pathways

PubMed Central

Boucher, Benjamin; Lee, Anna Y.; Hallett, Michael; Jenna, Sarah

2016-01-01

A genetic interaction (GI) is defined when the mutation of one gene modifies the phenotypic expression associated with the mutation of a second gene. Genome-wide efforts to map GIs in yeast revealed structural and functional properties of a GI network. This provided insights into the mechanisms underlying the robustness of yeast to genetic and environmental insults, and also into the link existing between genotype and phenotype. While a significant conservation of GIs and GI network structure has been reported between distant yeast species, such a conservation is not clear between unicellular and multicellular organisms. Structural and functional characterization of a GI network in these latter organisms is consequently of high interest. In this study, we present an in-depth characterization of ~1.5K GIs in the nematode Caenorhabditis elegans. We identify and characterize six distinct classes of GIs by examining a wide-range of structural and functional properties of genes and network, including co-expression, phenotypical manifestations, relationship with protein-protein interaction dense subnetworks (PDS) and pathways, molecular and biological functions, gene essentiality and pleiotropy. Our study shows that GI classes link genes within pathways and display distinctive properties, specifically towards PDS. It suggests a model in which pathways are composed of PDS-centric and PDS-independent GIs coordinating molecular machines through two specific classes of GIs involving pleiotropic and non-pleiotropic connectors. Our study provides the first in-depth characterization of a GI network within pathways of a multicellular organism. It also suggests a model to understand better how GIs control system robustness and evolution. PMID:26871911
Cooperation and coexpression: How coexpression networks shift in response to multiple mutualists.

PubMed

Palakurty, Sathvik X; Stinchcombe, John R; Afkhami, Michelle E

2018-04-01

A mechanistic understanding of community ecology requires tackling the nonadditive effects of multispecies interactions, a challenge that necessitates integration of ecological and molecular complexity-namely moving beyond pairwise ecological interaction studies and the "gene at a time" approach to mechanism. Here, we investigate the consequences of multispecies mutualisms for the structure and function of genomewide differential coexpression networks for the first time, using the tractable and ecologically important interaction between legume Medicago truncatula, rhizobia and mycorrhizal fungi. First, we found that genes whose expression is affected nonadditively by multiple mutualists are more highly connected in gene networks than expected by chance and had 94% greater network centrality than genes showing additive effects, suggesting that nonadditive genes may be key players in the widespread transcriptomic responses to multispecies symbioses. Second, multispecies mutualisms substantially changed coexpression network structure of 18 modules of host plant genes and 22 modules of the fungal symbionts' genes, indicating that third-party mutualists can cause significant rewiring of plant and fungal molecular networks. Third, we found that 60% of the coexpressed gene sets that explained variation in plant performance had coexpression structures that were altered by interactive effects of rhizobia and fungi. Finally, an "across-symbiosis" approach identified sets of plant and mycorrhizal genes whose coexpression structure was unique to the multiple mutualist context and suggested coupled responses across the plant-mycorrhizal interaction to rhizobial mutualists. Taken together, these results show multispecies mutualisms have substantial effects on the molecular interactions in host plants, microbes and across symbiotic boundaries. © 2018 John Wiley & Sons Ltd.
Individual and Network Correlates of Antisocial Personality Disorder Among Rural Nonmedical Prescription Opioid Users.

PubMed

Smith, Rachel V; Young, April M; Mullins, Ursula L; Havens, Jennifer R

2017-04-01

Examination of the association of antisocial personality disorder (ASPD) with substance use and HIV risk behaviors within the social networks of rural people who use drugs. Interviewer-administered questionnaires were used to assess substance use, HIV risk behavior, and social network characteristics of drug users (n = 503) living in rural Appalachia. The MINI International Psychiatric Interview was used to determine whether participants met DSM-IV criteria for ASPD and Axis-I psychological comorbidities (eg, major depressive disorder, posttraumatic stress disorder, generalized anxiety disorder). Participants were also tested for herpes simplex 2, hepatitis C, and HIV. Multivariate generalized linear mixed modeling was used to determine the association between ASPD and risk behaviors, substance use, and social network characteristics. Approximately one-third (31%) of participants met DSM-IV criteria for ASPD. In multivariate analysis, distrust and conflict within an individual's social networks, as well as past 30-day use of heroin and crack, male gender, younger age, lesser education, heterosexual orientation, and comorbid MDD were associated with meeting diagnostic criteria for ASPD. Participants meeting criteria for ASPD were more likely to report recent heroin and crack use, which are far less common drugs of abuse in this population in which the predominant drug of abuse is prescription opioids. Greater discord within relationships was also identified among those with ASPD symptomatology. Given the elevated risk for blood-borne infection (eg, HIV) and other negative social and health consequences conferred by this high-risk subgroup, exploration of tailored network-based interventions with mental health assessment is recommended. © 2016 National Rural Health Association.
Characterization and Compensation of Network-Level Anomalies in Mixed-Signal Neuromorphic Modeling Platforms

PubMed Central

Petrovici, Mihai A.; Vogginger, Bernhard; Müller, Paul; Breitwieser, Oliver; Lundqvist, Mikael; Muller, Lyle; Ehrlich, Matthias; Destexhe, Alain; Lansner, Anders; Schüffny, René; Schemmel, Johannes; Meier, Karlheinz

2014-01-01

Advancing the size and complexity of neural network models leads to an ever increasing demand for computational resources for their simulation. Neuromorphic devices offer a number of advantages over conventional computing architectures, such as high emulation speed or low power consumption, but this usually comes at the price of reduced configurability and precision. In this article, we investigate the consequences of several such factors that are common to neuromorphic devices, more specifically limited hardware resources, limited parameter configurability and parameter variations due to fixed-pattern noise and trial-to-trial variability. Our final aim is to provide an array of methods for coping with such inevitable distortion mechanisms. As a platform for testing our proposed strategies, we use an executable system specification (ESS) of the BrainScaleS neuromorphic system, which has been designed as a universal emulation back-end for neuroscientific modeling. We address the most essential limitations of this device in detail and study their effects on three prototypical benchmark network models within a well-defined, systematic workflow. For each network model, we start by defining quantifiable functionality measures by which we then assess the effects of typical hardware-specific distortion mechanisms, both in idealized software simulations and on the ESS. For those effects that cause unacceptable deviations from the original network dynamics, we suggest generic compensation mechanisms and demonstrate their effectiveness. Both the suggested workflow and the investigated compensation mechanisms are largely back-end independent and do not require additional hardware configurability beyond the one required to emulate the benchmark networks in the first place. We hereby provide a generic methodological environment for configurable neuromorphic devices that are targeted at emulating large-scale, functional neural networks. PMID:25303102
Characterization and compensation of network-level anomalies in mixed-signal neuromorphic modeling platforms.

PubMed

Petrovici, Mihai A; Vogginger, Bernhard; Müller, Paul; Breitwieser, Oliver; Lundqvist, Mikael; Muller, Lyle; Ehrlich, Matthias; Destexhe, Alain; Lansner, Anders; Schüffny, René; Schemmel, Johannes; Meier, Karlheinz

2014-01-01

Advancing the size and complexity of neural network models leads to an ever increasing demand for computational resources for their simulation. Neuromorphic devices offer a number of advantages over conventional computing architectures, such as high emulation speed or low power consumption, but this usually comes at the price of reduced configurability and precision. In this article, we investigate the consequences of several such factors that are common to neuromorphic devices, more specifically limited hardware resources, limited parameter configurability and parameter variations due to fixed-pattern noise and trial-to-trial variability. Our final aim is to provide an array of methods for coping with such inevitable distortion mechanisms. As a platform for testing our proposed strategies, we use an executable system specification (ESS) of the BrainScaleS neuromorphic system, which has been designed as a universal emulation back-end for neuroscientific modeling. We address the most essential limitations of this device in detail and study their effects on three prototypical benchmark network models within a well-defined, systematic workflow. For each network model, we start by defining quantifiable functionality measures by which we then assess the effects of typical hardware-specific distortion mechanisms, both in idealized software simulations and on the ESS. For those effects that cause unacceptable deviations from the original network dynamics, we suggest generic compensation mechanisms and demonstrate their effectiveness. Both the suggested workflow and the investigated compensation mechanisms are largely back-end independent and do not require additional hardware configurability beyond the one required to emulate the benchmark networks in the first place. We hereby provide a generic methodological environment for configurable neuromorphic devices that are targeted at emulating large-scale, functional neural networks.
Trends in the economic consequences of marital and cohabitation dissolution in the United States.

PubMed

Tach, Laura M; Eads, Alicia

2015-04-01

Mothers in the United States use a combination of employment, public transfers, and private safety nets to cushion the economic losses of romantic union dissolution, but changes in maternal labor force participation, government transfer programs, and private social networks may have altered the economic impact of union dissolution over time. Using nationally representative panels from the Survey of Income and Program Participation (SIPP) from 1984 to 2007, we show that the economic consequences of divorce have declined since the 1980s owing to the growth in married women's earnings and their receipt of child support and income from personal networks. In contrast, the economic consequences of cohabitation dissolution were modest in the 1980s but have worsened over time. Cohabiting mothers' income losses associated with union dissolution now closely resemble those of divorced mothers. These trends imply that changes in marital stability have not contributed to rising income instability among families with children, but trends in the extent and economic costs of cohabitation have likely contributed to rising income instability for less-advantaged children.
Hierarchical structures based on self-assembling beta-hairpin peptides and their application as biomaterials and hybrid materials

NASA Astrophysics Data System (ADS)

Altunbas, Aysegul

Self-assembly represents a robust and powerful paradigm for the bottom-up construction of nanostructures. Self-assembled peptide hydrogels are emerging as promising routes to novel multifunctional materials. The 20 amino acid MAX1and MAX8 peptides self-assemble into a three dimensional network of entangled, branched fibrils rich in beta-sheet secondary structure with a high density of lysine groups exposed on the fibril-surfaces. These hydrogels form self-supporting structures that shear thin upon application of shear and then immediately recover to a solid hydrogel upon cessation of shear which facilitates the local delivery of the hydrogel into a site in vivo. Templated condensation of silica precursors on self-assembled nanoscale peptide fibrils with various surface functionalities can be used to mimic biosilicification. This template-defined approach towards biomineralization was utilized for the controlled fabrication of 3D hybrid nanostructures. We report a study on the structure-property relationship of self-assembled peptide hydrogels where mineralization of individual fibrils through sol-gel chemistry was achieved. The nanostructure and consequent mechanical characteristics of these hybrid networks can be modulated by changing the stoichiometric parameters of the sol-gel process. Construction of such organic-inorganic hybrid networks by sol-gel processing of self-assembled peptide hydrogels has improved mechanical properties and resulted in materials with ˜ 3 orders of magnitude higher stiffness. The physical characterization of the hybrid networks via electron microscopy and small angle scattering is detailed and correlated with changes in the network mechanical behavior. The resultant high fidelity templating process suggests that the peptide substrate can be used to template the coating of other functional inorganic materials. Self-assembling peptide hydrogels encapsulating an anti-tumorigenic drug, curcumin, have been prepared and demonstrated to be an effective vehicle for the localized delivery of curcumin over sustained periods of time in vitro. The curcumin-hydrogel is prepared in-situ where curcumin encapsulation within the hydrogel network is accomplished concurrently with peptide self-assembly. Physical characterization methods and in vitro biological studies were used to demonstrate the effectiveness of curcumin-loaded beta-hairpin hydrogels as injectable agents for localized curcumin delivery. Notably, rheological characterization of the curcumin loaded hydrogel before and after shear flow have indicated solid-like properties even at high curcumin payloads. In vitro experiments with a medulloblastoma cell line confirm that the encapsulation of the curcumin within the hydrogel does not have an adverse effect on its bioactivity. Most importantly, the rate of curcumin release and its consequent therapeutic efficacy can be conveniently modulated by changing the morphological characteristics of the peptide hydrogel network. Lastly, MAX8 hydrogel cytocompatibility and biocompatibility was assessed with the future aim of utilizing this hydrogel as a scaffold in liver regeneration studies in rats. MAX8 hydrogel cytotoxity was evaluated using MC3T3-E1 and MG63 cell lines. Encapsulation, syringe delivery and subsequent viability of MG63 cells in hydrogels was also assessed to study the feasibility of using hydrogel/cell constructs as minimally invasive cell delivery vehicles. Biocompatibility was evaluated by monitoring inflammatory response induced by the MAX8 hydrogel via a subcutaneous mice model. Biocompatibility of MAX8 hydrogels at sites other than the subcutaneous region was also investigated using a cylindrical punch resection model in rat liver. The preliminary biocompatibility studies provide an elemental understanding of MAX8 hydrogel behavior in vivo.
A novel Smart Routing Protocol for remote health monitoring in Medical Wireless Networks.

PubMed

Sundararajan, T V P; Sumithra, M G; Maheswar, R

2014-01-01

In a Medical Wireless Network (MWN), sensors constantly monitor patient's physiological condition and movement. Inter-MWN communications are set up between the Patient Server and one or more Centralized Coordinators. However, MWNs require protocols with little energy consumption and the self-organizing attribute perceived in ad-hoc networks. The proposed Smart Routing Protocol (SRP) selects only the nodes with a higher residual energy and lower traffic density for routing. This approach enhances cooperation among the nodes of a Mobile Ad Hoc Network. Consequently, SRP produces better results than the existing protocols, namely Conditional Min-Max Battery Cost Routing, Min-Max Battery Cost Routing and AdHoc On-demand Distance Vector in terms of network parameters. The performance of the erstwhile schemes for routing protocols is evaluated using the network simulator Qualnet v 4.5.
Architecture Design and Experimental Platform Demonstration of Optical Network based on OpenFlow Protocol

NASA Astrophysics Data System (ADS)

Xing, Fangyuan; Wang, Honghuan; Yin, Hongxi; Li, Ming; Luo, Shenzi; Wu, Chenguang

2016-02-01

With the extensive application of cloud computing and data centres, as well as the constantly emerging services, the big data with the burst characteristic has brought huge challenges to optical networks. Consequently, the software defined optical network (SDON) that combines optical networks with software defined network (SDN), has attracted much attention. In this paper, an OpenFlow-enabled optical node employed in optical cross-connect (OXC) and reconfigurable optical add/drop multiplexer (ROADM), is proposed. An open source OpenFlow controller is extended on routing strategies. In addition, the experiment platform based on OpenFlow protocol for software defined optical network, is designed. The feasibility and availability of the OpenFlow-enabled optical nodes and the extended OpenFlow controller are validated by the connectivity test, protection switching and load balancing experiments in this test platform.
Protein intrinsic disorder in plants.

PubMed

Pazos, Florencio; Pietrosemoli, Natalia; García-Martín, Juan A; Solano, Roberto

2013-09-12

To some extent contradicting the classical paradigm of the relationship between protein 3D structure and function, now it is clear that large portions of the proteomes, especially in higher organisms, lack a fixed structure and still perform very important functions. Proteins completely or partially unstructured in their native (functional) form are involved in key cellular processes underlain by complex networks of protein interactions. The intrinsic conformational flexibility of these disordered proteins allows them to bind multiple partners in transient interactions of high specificity and low affinity. In concordance, in plants this type of proteins has been found in processes requiring these complex and versatile interaction networks. These include transcription factor networks, where disordered proteins act as integrators of different signals or link different transcription factor subnetworks due to their ability to interact (in many cases simultaneously) with different partners. Similarly, they also serve as signal integrators in signaling cascades, such as those related to response to external stimuli. Disordered proteins have also been found in plants in many stress-response processes, acting as protein chaperones or protecting other cellular components and structures. In plants, it is especially important to have complex and versatile networks able to quickly and efficiently respond to changing environmental conditions since these organisms cannot escape and have no other choice than adapting to them. Consequently, protein disorder can play an especially important role in plants, providing them with a fast mechanism to obtain complex, interconnected and versatile molecular networks.
Protein intrinsic disorder in plants

PubMed Central

Pazos, Florencio; Pietrosemoli, Natalia; García-Martín, Juan A.; Solano, Roberto

2013-01-01

To some extent contradicting the classical paradigm of the relationship between protein 3D structure and function, now it is clear that large portions of the proteomes, especially in higher organisms, lack a fixed structure and still perform very important functions. Proteins completely or partially unstructured in their native (functional) form are involved in key cellular processes underlain by complex networks of protein interactions. The intrinsic conformational flexibility of these disordered proteins allows them to bind multiple partners in transient interactions of high specificity and low affinity. In concordance, in plants this type of proteins has been found in processes requiring these complex and versatile interaction networks. These include transcription factor networks, where disordered proteins act as integrators of different signals or link different transcription factor subnetworks due to their ability to interact (in many cases simultaneously) with different partners. Similarly, they also serve as signal integrators in signaling cascades, such as those related to response to external stimuli. Disordered proteins have also been found in plants in many stress-response processes, acting as protein chaperones or protecting other cellular components and structures. In plants, it is especially important to have complex and versatile networks able to quickly and efficiently respond to changing environmental conditions since these organisms cannot escape and have no other choice than adapting to them. Consequently, protein disorder can play an especially important role in plants, providing them with a fast mechanism to obtain complex, interconnected and versatile molecular networks. PMID:24062761
Variable synaptic strengths controls the firing rate distribution in feedforward neural networks.

PubMed

Ly, Cheng; Marsat, Gary

2018-02-01

Heterogeneity of firing rate statistics is known to have severe consequences on neural coding. Recent experimental recordings in weakly electric fish indicate that the distribution-width of superficial pyramidal cell firing rates (trial- and time-averaged) in the electrosensory lateral line lobe (ELL) depends on the stimulus, and also that network inputs can mediate changes in the firing rate distribution across the population. We previously developed theoretical methods to understand how two attributes (synaptic and intrinsic heterogeneity) interact and alter the firing rate distribution in a population of integrate-and-fire neurons with random recurrent coupling. Inspired by our experimental data, we extend these theoretical results to a delayed feedforward spiking network that qualitatively capture the changes of firing rate heterogeneity observed in in-vivo recordings. We demonstrate how heterogeneous neural attributes alter firing rate heterogeneity, accounting for the effect with various sensory stimuli. The model predicts how the strength of the effective network connectivity is related to intrinsic heterogeneity in such delayed feedforward networks: the strength of the feedforward input is positively correlated with excitability (threshold value for spiking) when firing rate heterogeneity is low and is negatively correlated with excitability with high firing rate heterogeneity. We also show how our theory can be used to predict effective neural architecture. We demonstrate that neural attributes do not interact in a simple manner but rather in a complex stimulus-dependent fashion to control neural heterogeneity and discuss how it can ultimately shape population codes.
Genome Scale Modeling in Systems Biology: Algorithms and Resources

PubMed Central

Najafi, Ali; Bidkhori, Gholamreza; Bozorgmehr, Joseph H.; Koch, Ina; Masoudi-Nejad, Ali

2014-01-01

In recent years, in silico studies and trial simulations have complemented experimental procedures. A model is a description of a system, and a system is any collection of interrelated objects; an object, moreover, is some elemental unit upon which observations can be made but whose internal structure either does not exist or is ignored. Therefore, any network analysis approach is critical for successful quantitative modeling of biological systems. This review highlights some of most popular and important modeling algorithms, tools, and emerging standards for representing, simulating and analyzing cellular networks in five sections. Also, we try to show these concepts by means of simple example and proper images and graphs. Overall, systems biology aims for a holistic description and understanding of biological processes by an integration of analytical experimental approaches along with synthetic computational models. In fact, biological networks have been developed as a platform for integrating information from high to low-throughput experiments for the analysis of biological systems. We provide an overview of all processes used in modeling and simulating biological networks in such a way that they can become easily understandable for researchers with both biological and mathematical backgrounds. Consequently, given the complexity of generated experimental data and cellular networks, it is no surprise that researchers have turned to computer simulation and the development of more theory-based approaches to augment and assist in the development of a fully quantitative understanding of cellular dynamics. PMID:24822031
Lattice based Kinetic Monte Carlo Simulations of a complex chemical reaction network

NASA Astrophysics Data System (ADS)

Danielson, Thomas; Savara, Aditya; Hin, Celine

Lattice Kinetic Monte Carlo (KMC) simulations offer a powerful alternative to using ordinary differential equations for the simulation of complex chemical reaction networks. Lattice KMC provides the ability to account for local spatial configurations of species in the reaction network, resulting in a more detailed description of the reaction pathway. In KMC simulations with a large number of reactions, the range of transition probabilities can span many orders of magnitude, creating subsets of processes that occur more frequently or more rarely. Consequently, processes that have a high probability of occurring may be selected repeatedly without actually progressing the system (i.e. the forward and reverse process for the same reaction). In order to avoid the repeated occurrence of fast frivolous processes, it is necessary to throttle the transition probabilities in such a way that avoids altering the overall selectivity. Likewise, as the reaction progresses, new frequently occurring species and reactions may be introduced, making a dynamic throttling algorithm a necessity. We present a dynamic steady-state detection scheme with the goal of accurately throttling rate constants in order to optimize the KMC run time without compromising the selectivity of the reaction network. The algorithm has been applied to a large catalytic chemical reaction network, specifically that of methanol oxidative dehydrogenation, as well as additional pathways on CeO2(111) resulting in formaldehyde, CO, methanol, CO2, H2 and H2O as gas products.
An implementation of a data-transmission pipelining algorithm on Imote2 platforms

NASA Astrophysics Data System (ADS)

Li, Xu; Dorvash, Siavash; Cheng, Liang; Pakzad, Shamim

2011-04-01

Over the past several years, wireless network systems and sensing technologies have been developed significantly. This has resulted in the broad application of wireless sensor networks (WSNs) in many engineering fields and in particular structural health monitoring (SHM). The movement of traditional SHM toward the new generation of SHM, which utilizes WSNs, relies on the advantages of this new approach such as relatively low costs, ease of implementation and the capability of onboard data processing and management. In the particular case of long span bridge monitoring, a WSN should be capable of transmitting commands and measurement data over long network geometry in a reliable manner. While using single-hop data transmission in such geometry requires a long radio range and consequently a high level of power supply, multi-hop communication may offer an effective and reliable way for data transmissions across the network. Using a multi-hop communication protocol, the network relays data from a remote node to the base station via intermediary nodes. We have proposed a data-transmission pipelining algorithm to enable an effective use of the available bandwidth and minimize the energy consumption and the delay performance by the multi-hop communication protocol. This paper focuses on the implementation aspect of the pipelining algorithm on Imote2 platforms for SHM applications, describes its interaction with underlying routing protocols, and presents the solutions to various implementation issues of the proposed pipelining algorithm. Finally, the performance of the algorithm is evaluated based on the results of an experimental implementation.
Stochasticity versus determinism: consequences for realistic gene regulatory network modelling and evolution.

PubMed

Jenkins, Dafyd J; Stekel, Dov J

2010-02-01

Gene regulation is one important mechanism in producing observed phenotypes and heterogeneity. Consequently, the study of gene regulatory network (GRN) architecture, function and evolution now forms a major part of modern biology. However, it is impossible to experimentally observe the evolution of GRNs on the timescales on which living species evolve. In silico evolution provides an approach to studying the long-term evolution of GRNs, but many models have either considered network architecture from non-adaptive evolution, or evolution to non-biological objectives. Here, we address a number of important modelling and biological questions about the evolution of GRNs to the realistic goal of biomass production. Can different commonly used simulation paradigms, in particular deterministic and stochastic Boolean networks, with and without basal gene expression, be used to compare adaptive with non-adaptive evolution of GRNs? Are these paradigms together with this goal sufficient to generate a range of solutions? Will the interaction between a biological goal and evolutionary dynamics produce trade-offs between growth and mutational robustness? We show that stochastic basal gene expression forces shrinkage of genomes due to energetic constraints and is a prerequisite for some solutions. In systems that are able to evolve rates of basal expression, two optima, one with and one without basal expression, are observed. Simulation paradigms without basal expression generate bloated networks with non-functional elements. Further, a range of functional solutions was observed under identical conditions only in stochastic networks. Moreover, there are trade-offs between efficiency and yield, indicating an inherent intertwining of fitness and evolutionary dynamics.

Connected vehicle freeway speed harmonization systems.

DOT National Transportation Integrated Search

2016-03-15

The capacity drop phenomenon, which reduces the maximum bottleneck discharge rate following the onset of congestion, is a critical restriction in transportation networks that causes additional traffic congestion. Consequently, preventing or reducing ...
Fuzzy knowledge base construction through belief networks based on Lukasiewicz logic

NASA Technical Reports Server (NTRS)

Lara-Rosano, Felipe

1992-01-01

In this paper, a procedure is proposed to build a fuzzy knowledge base founded on fuzzy belief networks and Lukasiewicz logic. Fuzzy procedures are developed to do the following: to assess the belief values of a consequent, in terms of the belief values of its logical antecedents and the belief value of the corresponding logical function; and to update belief values when new evidence is available.
The Academic and Social Life Styles of Students and Teachers of Higher Education Institutions in Bangladesh as Consequences of Using Social Network Sites

ERIC Educational Resources Information Center

Clement, Che Kum

2014-01-01

With the emergence of social network sites (SNS), students and teachers of higher education institutions all over the world have been making efforts to meet up with the demands of these information and communication technology (ICT) tools. This paper presents the findings of a study conducted at four private universities in Bangladesh with the aim…
Heparan Sulfates Support Pyramidal Cell Excitability, Synaptic Plasticity, and Context Discrimination

PubMed Central

Minge, Daniel; Senkov, Oleg; Kaushik, Rahul; Herde, Michel K.; Tikhobrazova, Olga; Wulff, Andreas B.; Mironov, Andrey; van Kuppevelt, Toin H.; Oosterhof, Arie; Kochlamazashvili, Gaga

2017-01-01

Abstract Heparan sulfate (HS) proteoglycans represent a major component of the extracellular matrix and are critical for brain development. However, their function in the mature brain remains to be characterized. Here, acute enzymatic digestion of HS side chains was used to uncover how HSs support hippocampal function in vitro and in vivo. We found that long-term potentiation (LTP) of synaptic transmission at CA3–CA1 Schaffer collateral synapses was impaired after removal of highly sulfated HSs with heparinase 1. This reduction was associated with decreased Ca2+ influx during LTP induction, which was the consequence of a reduced excitability of CA1 pyramidal neurons. At the subcellular level, heparinase treatment resulted in reorganization of the distal axon initial segment, as detected by a reduction in ankyrin G expression. In vivo, digestion of HSs impaired context discrimination in a fear conditioning paradigm and oscillatory network activity in the low theta band after fear conditioning. Thus, HSs maintain neuronal excitability and, as a consequence, support synaptic plasticity and learning. PMID:28119345
Future Directions in the Study of Early-Life Stress and Physical and Emotional Health: Implications of the Neuroimmune Network Hypothesis.

PubMed

Hostinar, Camelia E; Nusslock, Robin; Miller, Gregory E

2018-01-01

Early-life stress is associated with increased vulnerability to physical and emotional health problems across the lifespan. The recently developed neuroimmune network hypothesis proposes that one of the underlying mechanisms for these associations is that early-life stress amplifies bidirectional crosstalk between the brain and the immune system, contributing to several mental and physical health conditions that have inflammatory underpinnings, such as depression and coronary heart disease. Neuroimmune crosstalk is thought to perpetuate inflammation and neural alterations linked to early-life stress exposure, and also foster behaviors that can further compromise health, such as smoking, drug abuse and consumption of high-fat diets. The goal of the present review is to briefly summarize the neuroimmune network hypothesis and use it as a starting point for generating new questions about the role of early-life stress in establishing a dysregulated relationship between neural and immune signaling, with consequences for lifespan physical and emotional health. Specifically, we aim to discuss implications and future directions for theory and empirical research on early-life stress, as well as for interventions that may improve the health and well-being of children and adolescents living in adverse conditions.
A practical tool for monitoring the performance of measuring systems in a laboratory network: report of an ACB Working Group.

PubMed

Ayling, Pete; Hill, Robert; Jassam, Nuthar; Kallner, Anders; Khatami, Zahra

2017-11-01

Background A logical consequence of the introduction of robotics and high-capacity analysers has seen a consolidation to larger units. This requires new structures and quality systems to ensure that laboratories deliver consistent and comparable results. Methods A spreadsheet program was designed to accommodate results from up to 12 different instruments/laboratories and present IQC data, i.e. Levey-Jennings and Youden plots and comprehensive numerical tables of the performance of each item. Input of data was made possible by a 'data loader' by which IQC data from the individual instruments could be transferred to the spreadsheet program on line. Results A set of real data from laboratories is used to populate the data loader and the networking software program. Examples are present from the analysis of variance components, the Levey-Jennings and Youden plots. Conclusions This report presents a software package that allows the simultaneous management and detailed monitoring of the performance of up to 12 different instruments/laboratories in a fully interactive mode. The system allows a quality manager of networked laboratories to have a continuous updated overview of the performance. This software package has been made available at the ACB website.
The complexity of classical music networks

NASA Astrophysics Data System (ADS)

Rolla, Vitor; Kestenberg, Juliano; Velho, Luiz

2018-02-01

Previous works suggest that musical networks often present the scale-free and the small-world properties. From a musician's perspective, the most important aspect missing in those studies was harmony. In addition to that, the previous works made use of outdated statistical methods. Traditionally, least-squares linear regression is utilised to fit a power law to a given data set. However, according to Clauset et al. such a traditional method can produce inaccurate estimates for the power law exponent. In this paper, we present an analysis of musical networks which considers the existence of chords (an essential element of harmony). Here we show that only 52.5% of music in our database presents the scale-free property, while 62.5% of those pieces present the small-world property. Previous works argue that music is highly scale-free; consequently, it sounds appealing and coherent. In contrast, our results show that not all pieces of music present the scale-free and the small-world properties. In summary, this research is focused on the relationship between musical notes (Do, Re, Mi, Fa, Sol, La, Si, and their sharps) and accompaniment in classical music compositions. More information about this research project is available at https://eden.dei.uc.pt/~vitorgr/MS.html.
Development of a wireless sensor network for individual monitoring of panels in a photovoltaic plant.

PubMed

Prieto, Miguel J; Pernía, Alberto M; Nuño, Fernando; Díaz, Juan; Villegas, Pedro J

2014-01-30

With photovoltaic (PV) systems proliferating in the last few years due to the high prices of fossil fuels and pollution issues, among others, it is extremely important to monitor the efficiency of these plants and optimize the energy production process. This will also result in improvements related to the maintenance and security of the installation. In order to do so, the main parameters in the plant must be continuously monitored so that the appropriate actions can be carried out. This monitoring should not only be carried out at a global level, but also at panel-level, so that a better understanding of what is actually happening in the PV plant can be obtained. This paper presents a system based on a wireless sensor network (WSN) that includes all the components required for such monitoring as well as a power supply obtaining the energy required by the sensors from the photovoltaic panels. The system proposed succeeds in identifying all the nodes in the network and provides real-time monitoring while tracking efficiency, features, failures and weaknesses from a single cell up to the whole infrastructure. Thus, the decision-making process is simplified, which contributes to reducing failures, wastes and, consequently, costs.
Landscape changes as a factor affecting the course and consequences of extreme floods in the Otava river basin, Czech Republic.

PubMed

Langhammer, Jakub; Vilímek, Vít

2008-09-01

The paper presents the analysis of anthropogenical modifications of the landscape in relation to the course and consequences of floods. The research was conducted in the Otava river basin which represents the core zone of the extreme flood in August 2002 in Central Europe. The analysis was focused on the key indicators of landscape modification potentially affecting the runoff process - the long-term changes of land-use, changes of land cover structure, land drainage, historical shortening of the river network and the modifications of streams and floodplains. The information on intensity and spatial distribution of modifications was derived from different data sources--historical maps, available GIS data, remote sensing and field mapping. The results revealed a high level of spatial diversity of anthropogenical modifications in different parts of the river basin. The intensive modifications in most of indicators were concentrated in the lowland region of the river basin due to its agricultural use; however important changes were also recorded in the headwater region of the basin. The high spatial diversity of the modifications may result in their varying effect on the course and consequences of floods in different parts of the river basin. This effect is demonstrated by the cluster analysis based on the matrix of indicators of stream and floodplain modification, physiogeographical characteristics and geomorphological evidences of the flood in August 2002, derived from the individual thematic layers using GIS.
Prediction-based association control scheme in dense femtocell networks

PubMed Central

Pham, Ngoc-Thai; Huynh, Thong; Hwang, Won-Joo; You, Ilsun; Choo, Kim-Kwang Raymond

2017-01-01

The deployment of large number of femtocell base stations allows us to extend the coverage and efficiently utilize resources in a low cost manner. However, the small cell size of femtocell networks can result in frequent handovers to the mobile user, and consequently throughput degradation. Thus, in this paper, we propose predictive association control schemes to improve the system’s effective throughput. Our design focuses on reducing handover frequency without impacting on throughput. The proposed schemes determine handover decisions that contribute most to the network throughput and are proper for distributed implementations. The simulation results show significant gains compared with existing methods in terms of handover frequency and network throughput perspective. PMID:28328992
Network Medicine: A Network-based Approach to Human Disease

PubMed Central

Barabási, Albert-László; Gulbahce, Natali; Loscalzo, Joseph

2011-01-01

Given the functional interdependencies between the molecular components in a human cell, a disease is rarely a consequence of an abnormality in a single gene, but reflects the perturbations of the complex intracellular network. The emerging tools of network medicine offer a platform to explore systematically not only the molecular complexity of a particular disease, leading to the identification of disease modules and pathways, but also the molecular relationships between apparently distinct (patho)phenotypes. Advances in this direction are essential to identify new diseases genes, to uncover the biological significance of disease-associated mutations identified by genome-wide association studies and full genome sequencing, and to identify drug targets and biomarkers for complex diseases. PMID:21164525
From allosteric drugs to allo-network drugs: state of the art and trends of design, synthesis and computational methods.

PubMed

Csermely, Peter; Nussinov, Ruth; Szilágyi, András

2013-01-01

Allosteric drugs bind to sites which are usually less conserved evolutionarily as compared to orthosteric sites. As such, they can discriminate between closely related proteins, have fewer side effects, and a consequent lower concentration can convey a lesser likelihood of receptor desensitization. However, an allosteric mode of action may also make the results of preclinical and animal experiments less predictive. The sensitivity of the allosteric consequences to the environment further increases the importance of accounting for patient population diversity. Even subtle differences in protein sequence, in cellular metabolic states or in target tissues, can result in different outcomes. This mini-hot-topic issue of CTMC showcases some successes and challenges of allosteric drug development through the examples of seventransmembrane (GPCR), AMPA, NMDA and metabotropic glutamate receptors, as well as the morpheein model of allosterism involved in inherent metabolic errors. Finally, the development of allo-network drugs, which are allosteric drugs acting indirectly on the neighborhood of the pharmacological target in protein-protein interaction or signaling networks, is described.
On Internet Symmetry and its Impact on Society

NASA Astrophysics Data System (ADS)

Wolff, S. S.

2014-12-01

The end-to-end principle, enunciated by Clark and Saltzer in 1981 enabled an Internet implementation in which there was a symmetry among the network nodes in the sense that no node was architecturally distinguished. Each interface to the network had a unique and accessible address and could communicate on equal terms with any other interface or collection of interfaces. In this egalitarian implementation there was in consequence no architectural distinction between providers and consumers of content - any network node could play either role. As the Internet spread to university campuses, incoming students found 10 megabit Ethernet in the dorm - while their parents at home were still stuck with 56 kilobit dialup. In the two decades bisected by the millenium, this combination of speed and symmetry on campus and beyond led to a panoply of transformational Internet applications such as Internet video conferencing and billion dollar industries like Google, Yahoo!, and Facebook. This talk places early Internet history in a social context, elaborates on the social and economic outcomes, defines"middlebox friction", discusses its erosive consequences, and suggests a solution to restore symmetry to the Internet-at-large.
DOW-PR DOlphin and Whale Pods Routing Protocol for Underwater Wireless Sensor Networks (UWSNs).

PubMed

Wadud, Zahid; Ullah, Khadem; Hussain, Sajjad; Yang, Xiaodong; Qazi, Abdul Baseer

2018-05-12

Underwater Wireless Sensor Networks (UWSNs) have intrinsic challenges that include long propagation delays, high mobility of sensor nodes due to water currents, Doppler spread, delay variance, multipath, attenuation and geometric spreading. The existing Weighting Depth and Forwarding Area Division Depth Based Routing (WDFAD-DBR) protocol considers the weighting depth of the two hops in order to select the next Potential Forwarding Node (PFN). To improve the performance of WDFAD-DBR, we propose DOlphin and Whale Pod Routing protocol (DOW-PR). In this scheme, we divide the transmission range into a number of transmission power levels and at the same time select the next PFNs from forwarding and suppressed zones. In contrast to WDFAD-DBR, our scheme not only considers the packet upward advancement, but also takes into account the number of suppressed nodes and number of PFNs at the first and second hops. Consequently, reasonable energy reduction is observed while receiving and transmitting packets. Moreover, our scheme also considers the hops count of the PFNs from the sink. In the absence of PFNs, the proposed scheme will select the node from the suppressed region for broadcasting and thus ensures minimum loss of data. Besides this, we also propose another routing scheme (whale pod) in which multiple sinks are placed at water surface, but one sink is embedded inside the water and is physically connected with the surface sink through high bandwidth connection. Simulation results show that the proposed scheme has high Packet Delivery Ratio (PDR), low energy tax, reduced Accumulated Propagation Distance (APD) and increased the network lifetime.
Probability of conductive bond formation in a percolating network of nanowires with fusible tips

NASA Astrophysics Data System (ADS)

Rykaczewski, Konrad; Wang, Robert Y.

2018-03-01

Meeting the heat dissipation demands of microelectronic devices requires development of polymeric composites with high thermal conductivity. This property is drastically improved by percolation networks of metallic filler particles that have their particle-to-particle contact resistances reduced through thermal or electromagnetic fusing. However, composites with fused metallic fillers are electrically conductive, which prevents their application within the chip-board and the inter-chip gaps. Here, we propose that electrically insulating composites for these purposes can be achieved by the application of fusible metallic coatings to the tips of nanowires with thermally conductive but electrically insulating cores. We derive analytical models that relate the ratio of the coated and total nanowire lengths to the fraction of fused, and thus conductive, bonds within percolating networks of these structures. We consider two types of materials for these fusible coatings. First, we consider silver-like coatings, which form only conductive bonds when contacting the silver-like coating of another nanowire. Second, we consider liquid metal-like coatings, which form conductive bonds regardless of whether they contact a coated or an uncoated segment of another nanowire. These models were validated using Monte Carlo simulations, which also revealed that electrical short-circuiting is highly unlikely until most of the wire is coated. Furthermore, we demonstrate that switching the tip coating from silver- to liquid metal-like materials can double the fraction of conductive bonds. Consequently, this work provides motivation to develop scalable methods for fabrication of the hybrid liquid-coated nanowires, whose dispersion in a polymer matrix is predicted to yield highly thermally conductive but electrically insulating composites.
DOW-PR DOlphin and Whale Pods Routing Protocol for Underwater Wireless Sensor Networks (UWSNs)

PubMed Central

Wadud, Zahid; Ullah, Khadem; Hussain, Sajjad; Yang, Xiaodong; Qazi, Abdul Baseer

2018-01-01

Underwater Wireless Sensor Networks (UWSNs) have intrinsic challenges that include long propagation delays, high mobility of sensor nodes due to water currents, Doppler spread, delay variance, multipath, attenuation and geometric spreading. The existing Weighting Depth and Forwarding Area Division Depth Based Routing (WDFAD-DBR) protocol considers the weighting depth of the two hops in order to select the next Potential Forwarding Node (PFN). To improve the performance of WDFAD-DBR, we propose DOlphin and Whale Pod Routing protocol (DOW-PR). In this scheme, we divide the transmission range into a number of transmission power levels and at the same time select the next PFNs from forwarding and suppressed zones. In contrast to WDFAD-DBR, our scheme not only considers the packet upward advancement, but also takes into account the number of suppressed nodes and number of PFNs at the first and second hops. Consequently, reasonable energy reduction is observed while receiving and transmitting packets. Moreover, our scheme also considers the hops count of the PFNs from the sink. In the absence of PFNs, the proposed scheme will select the node from the suppressed region for broadcasting and thus ensures minimum loss of data. Besides this, we also propose another routing scheme (whale pod) in which multiple sinks are placed at water surface, but one sink is embedded inside the water and is physically connected with the surface sink through high bandwidth connection. Simulation results show that the proposed scheme has high Packet Delivery Ratio (PDR), low energy tax, reduced Accumulated Propagation Distance (APD) and increased the network lifetime. PMID:29757208
Using social knowledge networking technology to enable meaningful use of electronic health record technology in hospitals and health systems.

PubMed

Rangachari, Pavani

2014-12-01

Despite the federal policy momentum towards "meaningful use" of Electronic Health Records, the healthcare organizational literature remains replete with reports of unintended adverse consequences of implementing Electronic Health Records, including: increased work for clinicians, unfavorable workflow changes, and unexpected changes in communication patterns & practices. In addition to being costly and unsafe, these unintended adverse consequences may pose a formidable barrier to "meaningful use" of Electronic Health Records. Correspondingly, it is essential for hospital administrators to understand and detect the causes of unintended adverse consequences, to ensure successful implementation of Electronic Health Records. The longstanding Technology-in-Practice framework emphasizes the role of human agency in enacting structures of technology use or "technologies-in-practice." Given a set of unintended adverse consequences from health information technology implementation, this framework could help trace them back to specific actions (types of technology-in-practice) and institutional conditions (social structures). On the other hand, the more recent Knowledge-in-Practice framework helps understand how information and communication technologies ( e.g. , social knowledge networking systems) could be implemented alongside existing technology systems, to create new social structures, generate new knowledge-in-practice, and transform technology-in-practice. Therefore, integrating the two literature streams could serve the dual purpose of understanding and overcoming unintended adverse consequences of Electronic Health Record implementation. This paper seeks to: (1) review the theoretical literatures on technology use & implementation, and identify a framework for understanding & overcoming unintended adverse consequences of implementing Electronic Health Records; (2) outline a broad project proposal to test the applicability of the framework in enabling "meaningful use" of Electronic Health Records in a healthcare context; and (3) identify strategies for successful implementation of Electronic Health Records in hospitals & health systems, based on the literature review and application.
Pan-Eurasian experiment (PEEX) establishing a process towards high level Pan-Eurasian atmosphere-ecosystem observation networks

NASA Astrophysics Data System (ADS)

Lappalainen, Hanna K.; Petäjä, Tuukka; Zaytzeva, Nina; Viisanen, Yrjö; Kotlyakov, Vladimir; Kasimov, Nikolay; Bondur, Valery; Matvienko, Gennady; Zilitinkevich, Sergej; Kulmala, Markku

2014-05-01

Pan-Eurasian Experiment (PEEX) is a new multidisciplinary research approach aiming at resolving the major uncertainties in the Earth system science and global sustainability questions in the Arctic and boreal Pan-Eurasian regions (Kulmala et al. 2011). The main goal of PEEX Research agenda is to contribute to solving the scientific questions that are specifically important for the Pan-Eurasian region in the coming years, in particular the global climate change and its consequences to nature and human society. Pan Eurasian region represents one the Earth most extensive areas of boreal forest (taiga) and the largest natural wetlands, thus being a significant source area of trace gas emissions, biogenic aerosol particles, and source and sink area for the greenhouse gas (GHG) exchange in a global scale (Guenther et al. 1995, Timkovsky et al. 2010, Tunved et al. 2006, Glagolev et al. 2010). One of the first activities of the PEEX initiative is to establish a process towards high level Pan-Eurasian Observation Networks. Siberian region is currently lacking a coordinated, coherent ground based atmosphere-ecosystem measurement network, which would be crucial component for observing and predicting the effects of climate change in the Northern Pan- Eurasian region The vision of the Pan-Eurasion network will be based on a hierarchical SMEAR-type (Stations Measuring Atmosphere-Ecosystem Interactions) integrated land-atmosphere observation system (Hari et al. 2009). A suite of stations have been selected for the Preliminary Phase of PEEX Observation network. These Preliminary Phase stations includes the SMEAR-type stations in Finland (SMEAR-I-II-II-IV stations), in Estonia (SMEAR-Järviselja) and in China (SMEAR-Nanjing) and selected stations in Russia and ecosystem station network in China. PEEX observation network will fill in the current observational gap in the Siberian region and bring the Siberian observation setup into international context with the with standardized or comparable procedures. It will prove a basis for the long-term continuation of advanced measurements on aerosols, clouds, GHGs and trace gases in Northern Pan- Eurasian area to be operated by PEEX educated technical staff.
The significance of small streams

NASA Astrophysics Data System (ADS)

Wohl, Ellen

2017-09-01

Headwaters, defined here as first- and secondorder streams, make up 70%‒80% of the total channel length of river networks. These small streams exert a critical influence on downstream portions of the river network by: retaining or transmitting sediment and nutrients; providing habitat and refuge for diverse aquatic and riparian organisms; creating migration corridors; and governing connectivity at the watershed-scale. The upstream-most extent of the channel network and the longitudinal continuity and lateral extent of headwaters can be difficult to delineate, however, and people are less likely to recognize the importance of headwaters relative to other portions of a river network. Consequently, headwaters commonly lack the legal protections accorded to other portions of a river network and are more likely to be significantly altered or completely obliterated by land use.
Generalized priority-queue network dynamics: Impact of team and hierarchy

NASA Astrophysics Data System (ADS)

Cho, Won-Kuk; Min, Byungjoon; Goh, K.-I.; Kim, I.-M.

2010-06-01

We study the effect of team and hierarchy on the waiting-time dynamics of priority-queue networks. To this end, we introduce generalized priority-queue network models incorporating interaction rules based on team-execution and hierarchy in decision making, respectively. It is numerically found that the waiting-time distribution exhibits a power law for long waiting times in both cases, yet with different exponents depending on the team size and the position of queue nodes in the hierarchy, respectively. The observed power-law behaviors have in many cases a corresponding single or pairwise-interacting queue dynamics, suggesting that the pairwise interaction may constitute a major dynamic consequence in the priority-queue networks. It is also found that the reciprocity of influence is a relevant factor for the priority-queue network dynamics.

Non-criticality of interaction network over system's crises: A percolation analysis.

PubMed

Shirazi, Amir Hossein; Saberi, Abbas Ali; Hosseiny, Ali; Amirzadeh, Ehsan; Toranj Simin, Pourya

2017-11-20

Extraction of interaction networks from multi-variate time-series is one of the topics of broad interest in complex systems. Although this method has a wide range of applications, most of the previous analyses have focused on the pairwise relations. Here we establish the potential of such a method to elicit aggregated behavior of the system by making a connection with the concepts from percolation theory. We study the dynamical interaction networks of a financial market extracted from the correlation network of indices, and build a weighted network. In correspondence with the percolation model, we find that away from financial crises the interaction network behaves like a critical random network of Erdős-Rényi, while close to a financial crisis, our model deviates from the critical random network and behaves differently at different size scales. We perform further analysis to clarify that our observation is not a simple consequence of the growth in correlations over the crises.
Interaction Control to Synchronize Non-synchronizable Networks.

PubMed

Schröder, Malte; Chakraborty, Sagar; Witthaut, Dirk; Nagler, Jan; Timme, Marc

2016-11-17

Synchronization constitutes one of the most fundamental collective dynamics across networked systems and often underlies their function. Whether a system may synchronize depends on the internal unit dynamics as well as the topology and strength of their interactions. For chaotic units with certain interaction topologies synchronization might be impossible across all interaction strengths, meaning that these networks are non-synchronizable. Here we propose the concept of interaction control, generalizing transient uncoupling, to induce desired collective dynamics in complex networks and apply it to synchronize even such non-synchronizable systems. After highlighting that non-synchronizability prevails for a wide range of networks of arbitrary size, we explain how a simple binary control may localize interactions in state space and thereby synchronize networks. Intriguingly, localizing interactions by a fixed control scheme enables stable synchronization across all connected networks regardless of topological constraints. Interaction control may thus ease the design of desired collective dynamics even without knowledge of the networks' exact interaction topology and consequently have implications for biological and self-organizing technical systems.
Visibility Graph Based Time Series Analysis

PubMed Central

Stephen, Mutua; Gu, Changgui; Yang, Huijie

2015-01-01

Network based time series analysis has made considerable achievements in the recent years. By mapping mono/multivariate time series into networks, one can investigate both it’s microscopic and macroscopic behaviors. However, most proposed approaches lead to the construction of static networks consequently providing limited information on evolutionary behaviors. In the present paper we propose a method called visibility graph based time series analysis, in which series segments are mapped to visibility graphs as being descriptions of the corresponding states and the successively occurring states are linked. This procedure converts a time series to a temporal network and at the same time a network of networks. Findings from empirical records for stock markets in USA (S&P500 and Nasdaq) and artificial series generated by means of fractional Gaussian motions show that the method can provide us rich information benefiting short-term and long-term predictions. Theoretically, we propose a method to investigate time series from the viewpoint of network of networks. PMID:26571115
Controllability and observability of Boolean networks arising from biology

NASA Astrophysics Data System (ADS)

Li, Rui; Yang, Meng; Chu, Tianguang

2015-02-01

Boolean networks are currently receiving considerable attention as a computational scheme for system level analysis and modeling of biological systems. Studying control-related problems in Boolean networks may reveal new insights into the intrinsic control in complex biological systems and enable us to develop strategies for manipulating biological systems using exogenous inputs. This paper considers controllability and observability of Boolean biological networks. We propose a new approach, which draws from the rich theory of symbolic computation, to solve the problems. Consequently, simple necessary and sufficient conditions for reachability, controllability, and observability are obtained, and algorithmic tests for controllability and observability which are based on the Gröbner basis method are presented. As practical applications, we apply the proposed approach to several different biological systems, namely, the mammalian cell-cycle network, the T-cell activation network, the large granular lymphocyte survival signaling network, and the Drosophila segment polarity network, gaining novel insights into the control and/or monitoring of the specific biological systems.
Chaotic, informational and synchronous behaviour of multiplex networks

NASA Astrophysics Data System (ADS)

Baptista, M. S.; Szmoski, R. M.; Pereira, R. F.; Pinto, S. E. De Souza

2016-03-01

The understanding of the relationship between topology and behaviour in interconnected networks would allow to charac- terise and predict behaviour in many real complex networks since both are usually not simultaneously known. Most previous studies have focused on the relationship between topology and synchronisation. In this work, we provide analytical formulas that shows how topology drives complex behaviour: chaos, information, and weak or strong synchronisation; in multiplex net- works with constant Jacobian. We also study this relationship numerically in multiplex networks of Hindmarsh-Rose neurons. Whereas behaviour in the analytically tractable network is a direct but not trivial consequence of the spectra of eigenvalues of the Laplacian matrix, where behaviour may strongly depend on the break of symmetry in the topology of interconnections, in Hindmarsh-Rose neural networks the nonlinear nature of the chemical synapses breaks the elegant mathematical connec- tion between the spectra of eigenvalues of the Laplacian matrix and the behaviour of the network, creating networks whose behaviour strongly depends on the nature (chemical or electrical) of the inter synapses.
Potentially dangerous 24-hour rainfall in the Provadiyska vally system at the end of the 20th and early 21st Centuries

NASA Astrophysics Data System (ADS)

Vladev, Dimitar

2018-03-01

Extreme rainfalls are of paramount importance for the formation of river springs and, consequently, the occurrence of spills and floods. The article presents the results of a case study of the potentially dangerous 24-hour eruptions in the Provadiyska valley system from the end of the 20th and the beginning of the 21st century. Particular attention is paid to the morphometric parameters and the configuration of the river-valley supply network of the Provadiyska river. On this basis, there are defined areas in which there are favorable conditions for forming high river waves.
Atom probe tomography of lithium-doped network glasses.

PubMed

Greiwe, Gerd-Hendrik; Balogh, Zoltan; Schmitz, Guido

2014-06-01

Li-doped silicate and borate glasses are electronically insulating, but provide considerable ionic conductivity. Under measurement conditions of laser-assisted atom probe tomography, mobile Li ions are redistributed in response to high electric fields. In consequence, the direct interpretation of measured composition profiles is prevented. It is demonstrated that composition profiles are nevertheless well understood by a complex model taking into account the electronic structure of dielectric materials, ionic mobility and field screening. Quantitative data on band bending and field penetration during measurement are derived which are important in understanding laser-assisted atom probe tomography of dielectric materials. Copyright © 2014 Elsevier B.V. All rights reserved.
The cultural contagion of conflict

PubMed Central

Gelfand, Michele; Shteynberg, Garriy; Lee, Tiane; Lun, Janetta; Lyons, Sarah; Bell, Chris; Chiao, Joan Y.; Bruss, C. Bayan; Al Dabbagh, May; Aycan, Zeynep; Abdel-Latif, Abdel-Hamid; Dagher, Munqith; Khashan, Hilal; Soomro, Nazar

2012-01-01

Anecdotal evidence abounds that conflicts between two individuals can spread across networks to involve a multitude of others. We advance a cultural transmission model of intergroup conflict where conflict contagion is seen as a consequence of universal human traits (ingroup preference, outgroup hostility; i.e. parochial altruism) which give their strongest expression in particular cultural contexts. Qualitative interviews conducted in the Middle East, USA and Canada suggest that parochial altruism processes vary across cultural groups and are most likely to occur in collectivistic cultural contexts that have high ingroup loyalty. Implications for future neuroscience and computational research needed to understand the emergence of intergroup conflict are discussed. PMID:22271785
On Applicability of Network Coding Technique for 6LoWPAN-based Sensor Networks.

PubMed

Amanowicz, Marek; Krygier, Jaroslaw

2018-05-26

In this paper, the applicability of the network coding technique in 6LoWPAN-based sensor multihop networks is examined. The 6LoWPAN is one of the standards proposed for the Internet of Things architecture. Thus, we can expect the significant growth of traffic in such networks, which can lead to overload and decrease in the sensor network lifetime. The authors propose the inter-session network coding mechanism that can be implemented in resource-limited sensor motes. The solution reduces the overall traffic in the network, and in consequence, the energy consumption is decreased. Used procedures take into account deep header compressions of the native 6LoWPAN packets and the hop-by-hop changes of the header structure. Applied simplifications reduce signaling traffic that is typically occurring in network coding deployments, keeping the solution usefulness for the wireless sensor networks with limited resources. The authors validate the proposed procedures in terms of end-to-end packet delay, packet loss ratio, traffic in the air, total energy consumption, and network lifetime. The solution has been tested in a real wireless sensor network. The results confirm the efficiency of the proposed technique, mostly in delay-tolerant sensor networks.
The hydraulic capacity of deteriorating sewer systems.

PubMed

Pollert, J; Ugarelli, R; Saegrov, S; Schilling, W; Di Federico, V

2005-01-01

Sewer and wastewater systems suffer from insufficient capacity, construction flaws and pipe deterioration. Consequences are structural failures, local floods, surface erosion and pollution of receiving waters bodies. European cities spend in the order of five billion Euro per year for wastewater network rehabilitation. This amount is estimated to increase due to network ageing. The project CARE-S (Computer Aided RE-habilitation of Sewer Networks) deals with sewer and storm water networks. The final project goal is to develop integrated software, which provides the most cost-efficient system of maintenance, repair and rehabilitation of sewer networks. Decisions on investments in rehabilitation often have to be made with uncertain information about the structural condition and the hydraulic performance of a sewer system. Because of this, decision-making involves considerable risks. This paper presents the results of research focused on the study of hydraulic effects caused by failures due to temporal decline of sewer systems. Hydraulic simulations are usually carried out by running commercial models that apply, as input, default values of parameters that strongly influence results. Using CCTV inspections information as dataset to catalogue principal types of failures affecting pipes, a 3D model was used to evaluate their hydraulic consequences. The translation of failures effects in parameters values producing the same hydraulic conditions caused by failures was carried out through the comparison of laboratory experiences and 3D simulations results. Those parameters could be the input of 1D commercial models instead of the default values commonly inserted.
Instagram #instasad?: exploring associations among instagram use, depressive symptoms, negative social comparison, and strangers followed.

PubMed

Lup, Katerina; Trub, Leora; Rosenthal, Lisa

2015-05-01

As the use and influence of social networking continues to grow, researchers have begun to explore its consequences for psychological well-being. Some research suggests that Facebook use can have negative consequences for well-being. Instagram, a photo-sharing social network created in 2010, has particular characteristics that may make users susceptible to negative consequences. This study tested a theoretically grounded moderated meditation model of the association between Instagram use and depressive symptoms through the mechanism of negative social comparison, and moderation by amount of strangers one follows. One hundred and seventeen 18-29 year olds completed online questionnaires containing demographics, frequency of Instagram use, amount of strangers followed on Instagram, the Center for Epidemiological Resources Scale for Depression, and the Social Comparison Rating Scale. Instagram use was marginally positively associated with depressive symptoms, and positive social comparison was significantly negatively associated with depressive symptoms. Amount of strangers followed moderated the associations of Instagram use with social comparison (significantly) and depressive symptoms (marginally), and further significantly moderated the indirect association of Instagram use with depressive symptoms through social comparison. Findings generally suggest that more frequent Instagram use has negative associations for people who follow more strangers, but positive associations for people who follow fewer strangers, with social comparison and depressive symptoms. Implications of negative associations of social networking for people who follow strangers and the need for more research on Instagram use given its increasing popularity are explored.
Hyperbolic geometry of Kuramoto oscillator networks

NASA Astrophysics Data System (ADS)

Chen, Bolun; Engelbrecht, Jan R.; Mirollo, Renato

2017-09-01

Kuramoto oscillator networks have the special property that their trajectories are constrained to lie on the (at most) 3D orbits of the Möbius group acting on the state space T N (the N-fold torus). This result has been used to explain the existence of the N-3 constants of motion discovered by Watanabe and Strogatz for Kuramoto oscillator networks. In this work we investigate geometric consequences of this Möbius group action. The dynamics of Kuramoto phase models can be further reduced to 2D reduced group orbits, which have a natural geometry equivalent to the unit disk \
The need for theory to guide concussion research.

PubMed

Molfese, Dennis L

2015-01-01

Although research into concussion has greatly expanded over the past decade, progress in identifying the mechanisms and consequences of head injury and recovery are largely absent. Instead, data are accumulated without the guidance of a systematic theory to direct research questions or generate testable hypotheses. As part of this special issue on sports concussion, I advance a theory that emphasizes changes in spatial and temporal distributions of the brain's neural networks during normal learning and the disruptions of these networks following injury. Specific predictions are made regarding both the development of the network as well as its breakdown following injury.
Scientific networking to address the causes, timing, emplacement mechanisms, and consequences of the Messinian Salinity Crisis

NASA Astrophysics Data System (ADS)

Camerlenghi, Angelo; Lofi, Johanna; Aloisi, Vanni; Flecker, Rachel

2017-04-01

The origin of the Mediterranean salt giant is linked to an extraordinary event in the geological history of the Mediterranean region, commonly referred to as the Messinian Salinity Crisis (MSC). After 45 years of intense yet disunited research efforts, the international scientific community at large faces a unique opportunity to access the deep and marginal basins Messinian depositional successions in the Mediterranean through scientific drilling, namely through the Integrated Ocean Discovery Program (IODP) and the International Continental Drilling Program (ICDP). Scientific activity to promote scientific drilling offshore and onshore is in progress under the broad umbrella of the Uncovering a Salt Giant' IODP Multi-Platform Drilling proposal, that has generated the Deep-Sea Records of the Messinian Salinity Crisis (DREAM) site-specific pre-proposal for riserless drilling on Messinian marginal basins and the related ICDP-IODP amphibious initiative Investigating Miocene Mediterranean- Atlantic gateway exchange (IMMAGE). Scientific networking has begun to establish a broad cross-disciplinary research community embracing geology, geophysics, geochemistry, microbiology, and paleoclimatology. Formal networking activities represent an opportunity for the scientific community to share objectives, data, expertise and tools with industry since there is considerable interest in oil and gas exploration, and consequent hazards, targeting the Mediterranean's deep salt deposits. With the acronym MEDSALT, we have established two networks working in close cooperation: (1) COST Action CA15103 Uncovering the Mediterranean salt giant (MEDSALT) (https://medsalt.eu/) is a 4-year long network established in May 2016 comprising scientific institutions from 28 states. This COST Action will provide an opportunity to develop further our knowledge of salt rock formation addressing four overarching scientific questions: a) What are the causes, timing and emplacement mechanisms of the Mediterranean salt giant? b) What are the factors responsible for and the socio-economic consequences of early salt deformation and fluid flow across and out of the halite layer? c) Do salt giants promote the development of a phylogenetically diverse and exceptionally active deep biosphere? d) What are the mechanisms underlying the spectacular vertical motions inside basins and their margins? (2) ANR Project 'Uncovering the Mediterranean Salt Giant' (MEDSALT) aims at establishing networking action to prepare an Integrated Ocean Discovery Program (IODP) full proposal to drill the Mediterranean Salt Giant with the R/V JOIDES Resolution. This 18-month long network consists of a core group of 22 scientists from 10 countries working in close cooperation with the brother COST Action MEDSALT. These inter-sectorial and multinational cooperation networks comprise a critical mass of both experienced and early-career researchers from Europe and beyond. The goal will be achieved through capacity building, researchers' mobility, skills development, knowledge exchange and scientific networking.
A Few Large Roads or Many Small Ones? How to Accommodate Growth in Vehicle Numbers to Minimise Impacts on Wildlife

PubMed Central

Rhodes, Jonathan R.; Lunney, Daniel; Callaghan, John; McAlpine, Clive A.

2014-01-01

Roads and vehicular traffic are among the most pervasive of threats to biodiversity because they fragmenting habitat, increasing mortality and opening up new areas for the exploitation of natural resources. However, the number of vehicles on roads is increasing rapidly and this is likely to continue into the future, putting increased pressure on wildlife populations. Consequently, a major challenge is the planning of road networks to accommodate increased numbers of vehicles, while minimising impacts on wildlife. Nonetheless, we currently have few principles for guiding decisions on road network planning to reduce impacts on wildlife in real landscapes. We addressed this issue by developing an approach for quantifying the impact on wildlife mortality of two alternative mechanisms for accommodating growth in vehicle numbers: (1) increasing the number of roads, and (2) increasing traffic volumes on existing roads. We applied this approach to a koala (Phascolarctos cinereus) population in eastern Australia and quantified the relative impact of each strategy on mortality. We show that, in most cases, accommodating growth in traffic through increases in volumes on existing roads has a lower impact than building new roads. An exception is where the existing road network has very low road density, but very high traffic volumes on each road. These findings have important implications for how we design road networks to reduce their impacts on biodiversity. PMID:24646891
A few large roads or many small ones? How to accommodate growth in vehicle numbers to minimise impacts on wildlife.

PubMed

Rhodes, Jonathan R; Lunney, Daniel; Callaghan, John; McAlpine, Clive A

2014-01-01

Roads and vehicular traffic are among the most pervasive of threats to biodiversity because they fragmenting habitat, increasing mortality and opening up new areas for the exploitation of natural resources. However, the number of vehicles on roads is increasing rapidly and this is likely to continue into the future, putting increased pressure on wildlife populations. Consequently, a major challenge is the planning of road networks to accommodate increased numbers of vehicles, while minimising impacts on wildlife. Nonetheless, we currently have few principles for guiding decisions on road network planning to reduce impacts on wildlife in real landscapes. We addressed this issue by developing an approach for quantifying the impact on wildlife mortality of two alternative mechanisms for accommodating growth in vehicle numbers: (1) increasing the number of roads, and (2) increasing traffic volumes on existing roads. We applied this approach to a koala (Phascolarctos cinereus) population in eastern Australia and quantified the relative impact of each strategy on mortality. We show that, in most cases, accommodating growth in traffic through increases in volumes on existing roads has a lower impact than building new roads. An exception is where the existing road network has very low road density, but very high traffic volumes on each road. These findings have important implications for how we design road networks to reduce their impacts on biodiversity.
'Migrants from over there' or 'racial minority here'? Sexual networks and prevention practices among sub-Saharan African migrants in France.

PubMed

Marsicano, Elise; Lydié, Nathalie; Bajos, Nathalie

2013-01-01

Migrants from sub-Saharan Africa bear a disproportionate burden of HIV infection in Europe, with an increasing proportion of them acquiring HIV after migration. This transformation in the epidemic pattern has raised concerns about the sexual mixing and preventive behaviours of migrants. This paper aims at exploring how racial boundaries shape sexual networks and structure prevention practices among migrants from sub-Saharan Africa. Analyses are based on a French survey carried out among 1874 individuals born in sub-Saharan Africa, aged 18-49 and living in Paris and its surroundings. Our results provide evidence of the existence of African sexual networks, over and beyond those of national origin. The intra-African segregation of these sexual networks leads to sexual contacts between migrants from low- and high-HIV prevalence countries, which probably contribute to the development of the epidemic amongst these migrants. Moreover, racially-based perceptions of HIV-related risk seem to produce a specific attitude toward prevention practices as shown by higher rates of condom use among migrant women from sub-Saharan Africa with a partner born outside sub-Saharan Africa. As a consequence, community-based approaches to HIV prevention should take into account the identification of migrants from sub-Saharan Africa as a racial minority and not only focus on national borders.
Adding seismic broadband analysis to characterize Andean backarc seismicity in Argentina

NASA Astrophysics Data System (ADS)

Alvarado, P.; Giuliano, A.; Beck, S.; Zandt, G.

2007-05-01

Characterization of the highly seismically active Andean backarc is crucial for assessment of earthquake hazards in western Argentina. Moderate-to-large crustal earthquakes have caused several deaths, damage and drastic economic consequences in Argentinean history. We have studied the Andean backarc crust between 30°S and 36°S using seismic broadband data available from a previous ("the CHARGE") IRIS-PASSCAL experiment. We collected more than 12 terabytes of continuous seismic data from 22 broadband instruments deployed across Chile and Argentina during 1.5 years. Using free software we modeled full regional broadband waveforms and obtained seismic moment tensor inversions of crustal earthquakes testing for the best focal depth for each event. We also mapped differences in the Andean backarc crustal structure and found a clear correlation with different types of crustal seismicity (i.e. focal depths, focal mechanisms, magnitudes and frequencies of occurrence) and previously mapped terrane boundaries. We now plan to use the same methodology to study other regions in Argentina using near-real time broadband data available from the national seismic (INPRES) network and global seismic networks operating in the region. We will re-design the national seismic network to optimize short-period and broadband seismic station coverage for different network purposes. This work is an international effort that involves researchers and students from universities and national government agencies with the goal of providing more information about earthquake hazards in western Argentina.
Electron beam energy stabilization using a neural network hybrid controller at the Australian Synchrotron Linac.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Meier, E.; Morgan, M. J.; Biedron, S. G.

2009-01-01

This paper describes the implementation of a neural network hybrid controller for energy stabilization at the Australian Synchrotron Linac. The structure of the controller consists of a neural network (NNET) feed forward control, augmented by a conventional Proportional-Integral (PI) feedback controller to ensure stability of the system. The system is provided with past states of the machine in order to predict its future state, and therefore apply appropriate feed forward control. The NNET is able to cancel multiple frequency jitter in real-time. When it is not performing optimally due to jitter changes, the system can successfully be augmented by themore » PI controller to attenuate the remaining perturbations. With a view to control the energy and bunch length at the FERMI{at}Elettra Free Electron Laser (FEL), the present study considers a neural network hybrid feed forward-feedback type of control to rectify limitations related to feedback systems, such as poor response for high jitter frequencies or limited bandwidth, while ensuring robustness of control. The Australian Synchrotron Linac is equipped with a beam position monitor (BPM), that was provided by Sincrotrone Trieste from a former transport line thus allowing energy measurements and energy control experiments. The present study will consequently focus on correcting energy jitter induced by variations in klystron phase and voltage.« less
Low-haze, annealing-free, very long Ag nanowire synthesis and its application in a flexible transparent touch panel

NASA Astrophysics Data System (ADS)

Moon, Hyunjin; Won, Phillip; Lee, Jinhwan; Ko, Seung Hwan

2016-07-01

Since transparent conducting films based on silver nanowires (AgNWs) have shown higher transmittance and electrical conductivity compared to those of indium tin oxide (ITO) films, the electronics industry has recognized them as promising substitutes. However, due to the higher haze value of AgNW transparent conducting films compared to ITO films, the clarity is decreased when AgNW films are applied to optoelectronic devices. In this study, we develop a highly transparent, low-haze, very long AgNW percolation network. Moreover, we confirm that analyzed chemical roles can easily be applied to different AgNW synthesis methods, and that they have a direct impact on the nanowire shape. Consequently, the lengths of the wires are increased up to 200 μm and the diameters of the wires are decreased up to 45 nm. Using these results, we fabricate highly transparent (96%) conductors (100 Ω/sq) with low-haze (2%) without any annealing process. This electrode shows enhanced clarity compared to previous results due to the decreased diffusive transmittance and scattering. In addition, a flexible touchscreen using a AgNW network is demonstrated to show the performance of modified AgNWs.

Modeling first impressions from highly variable facial images.

PubMed

Vernon, Richard J W; Sutherland, Clare A M; Young, Andrew W; Hartley, Tom

2014-08-12

First impressions of social traits, such as trustworthiness or dominance, are reliably perceived in faces, and despite their questionable validity they can have considerable real-world consequences. We sought to uncover the information driving such judgments, using an attribute-based approach. Attributes (physical facial features) were objectively measured from feature positions and colors in a database of highly variable "ambient" face photographs, and then used as input for a neural network to model factor dimensions (approachability, youthful-attractiveness, and dominance) thought to underlie social attributions. A linear model based on this approach was able to account for 58% of the variance in raters' impressions of previously unseen faces, and factor-attribute correlations could be used to rank attributes by their importance to each factor. Reversing this process, neural networks were then used to predict facial attributes and corresponding image properties from specific combinations of factor scores. In this way, the factors driving social trait impressions could be visualized as a series of computer-generated cartoon face-like images, depicting how attributes change along each dimension. This study shows that despite enormous variation in ambient images of faces, a substantial proportion of the variance in first impressions can be accounted for through linear changes in objectively defined features.
On the of neural modeling of some dynamic parameters of earthquakes and fire safety in high-rise construction

NASA Astrophysics Data System (ADS)

Haritonova, Larisa

2018-03-01

The recent change in the correlation of the number of man-made and natural catastrophes is presented in the paper. Some recommendations are proposed to increase the firefighting efficiency in the high-rise buildings. The article analyzes the methodology of modeling seismic effects. The prospectivity of applying the neural modeling and artificial neural networks to analyze a such dynamic parameters of the earthquake foci as the value of dislocation (or the average rupture slip) is shown. The following two input signals were used: the power class and the number of earthquakes. The regression analysis has been carried out for the predicted results and the target outputs. The equations of the regression for the outputs and target are presented in the work as well as the correlation coefficients in training, validation, testing, and the total (All) for the network structure 2-5-5-1for the average rupture slip. The application of the results obtained in the article for the seismic design for the newly constructed buildings and structures and the given recommendations will provide the additional protection from fire and earthquake risks, reduction of their negative economic and environmental consequences.
Relating Topological Determinants of Complex Networks to Their Spectral Properties: Structural and Dynamical Effects

NASA Astrophysics Data System (ADS)

Castellano, Claudio; Pastor-Satorras, Romualdo

2017-10-01

The largest eigenvalue of a network's adjacency matrix and its associated principal eigenvector are key elements for determining the topological structure and the properties of dynamical processes mediated by it. We present a physically grounded expression relating the value of the largest eigenvalue of a given network to the largest eigenvalue of two network subgraphs, considered as isolated: the hub with its immediate neighbors and the densely connected set of nodes with maximum K -core index. We validate this formula by showing that it predicts, with good accuracy, the largest eigenvalue of a large set of synthetic and real-world topologies. We also present evidence of the consequences of these findings for broad classes of dynamics taking place on the networks. As a by-product, we reveal that the spectral properties of heterogeneous networks built according to the linear preferential attachment model are qualitatively different from those of their static counterparts.
The evolutionary and ecological consequences of animal social networks: emerging issues.

PubMed

Kurvers, Ralf H J M; Krause, Jens; Croft, Darren P; Wilson, Alexander D M; Wolf, Max

2014-06-01

The first generation of research on animal social networks was primarily aimed at introducing the concept of social networks to the fields of animal behaviour and behavioural ecology. More recently, a diverse body of evidence has shown that social fine structure matters on a broader scale than initially expected, affecting many key ecological and evolutionary processes. Here, we review this development. We discuss the effects of social network structure on evolutionary dynamics (genetic drift, fixation probabilities, and frequency-dependent selection) and social evolution (cooperation and between-individual behavioural differences). We discuss how social network structure can affect important coevolutionary processes (host-pathogen interactions and mutualisms) and population stability. We also discuss the potentially important, but poorly studied, role of social network structure on dispersal and invasion. Throughout, we highlight important areas for future research. Copyright © 2014 Elsevier Ltd. All rights reserved.
Altered Micro-RNA Degradation Promotes Tumor Heterogeneity: A Result from Boolean Network Modeling.

PubMed

Wu, Yunyi; Krueger, Gerhard R F; Wang, Guanyu

2016-02-01

Cancer heterogeneity may reflect differential dynamical outcomes of the regulatory network encompassing biomolecules at both transcriptional and post-transcriptional levels. In other words, differential gene-expression profiles may correspond to different stable steady states of a mathematical model for simulation of biomolecular networks. To test this hypothesis, we simplified a regulatory network that is important for soft-tissue sarcoma metastasis and heterogeneity, comprising of transcription factors, micro-RNAs, and signaling components of the NOTCH pathway. We then used a Boolean network model to simulate the dynamics of this network, and particularly investigated the consequences of differential miRNA degradation modes. We found that efficient miRNA degradation is crucial for sustaining a homogenous and healthy phenotype, while defective miRNA degradation may lead to multiple stable steady states and ultimately to carcinogenesis and heterogeneity. Copyright© 2016 International Institute of Anticancer Research (Dr. John G. Delinassios), All rights reserved.
Network analysis of physics discussion forums and links to course success

NASA Astrophysics Data System (ADS)

Traxler, Adrienne; Gavrin, Andrew; Lindell, Rebecca

2017-01-01

Large introductory science courses tend to isolate students, with negative consequences for long-term retention in college. Many active learning courses build collaboration and community among students as an explicit goal, and social network analysis has been used to track the development and beneficial effects of these collaborations. Here we supplement such work by conducting network analysis of online course discussion forums in two semesters of an introductory physics class. Online forums provide a tool for engaging students with each other outside of class, and offer new opportunities to commuter or non-traditional students with limited on-campus time. We look for correlations between position in the forum network (centrality) and final course grades. Preliminary investigation has shown weak correlations in the very dense full-semester network, so we will consider reduced ''backbone'' networks that highlight the most consistent links between students. Future work and implications for instruction will also be discussed.
Vulnerability of a killer whale social network to disease outbreaks

NASA Astrophysics Data System (ADS)

Guimarães, Paulo R., Jr.; de Menezes, Márcio Argollo; Baird, Robin W.; Lusseau, David; Guimarães, Paulo; Dos Reis, Sérgio F.

2007-10-01

Emerging infectious diseases are among the main threats to conservation of biological diversity. A crucial task facing epidemiologists is to predict the vulnerability of populations of endangered animals to disease outbreaks. In this context, the network structure of social interactions within animal populations may affect disease spreading. However, endangered animal populations are often small and to investigate the dynamics of small networks is a difficult task. Using network theory, we show that the social structure of an endangered population of mammal-eating killer whales is vulnerable to disease outbreaks. This feature was found to be a consequence of the combined effects of the topology and strength of social links among individuals. Our results uncover a serious challenge for conservation of the species and its ecosystem. In addition, this study shows that the network approach can be useful to study dynamical processes in very small networks.
Measuring the consequences of wildfires in a Bayesian network with vulnerability and exposure indicators

NASA Astrophysics Data System (ADS)

Papakosta, Panagiota; Botzler, Sebastian; Krug, Kai; Straub, Daniel

2013-04-01

Mediterranean climate type areas have always been experiencing fire events. However, population growth and expansion of urban centers into wildland areas during the 20th century (expansion of wildland-urban interface) has increased the threat to humans and their activities. Life and property losses, damage on infrastructure and crops, and forest degradation are some of the damages caused by wildfires. Although fires repeatedly occur along the Mediterranean basin, not all areas have experienced severe consequences. The extent of damage by wildfires is influenced by several factors, such as population density, vegetation type, topography, weather conditions and social preparedness [1]. Wildfire consequence estimation by means of vulnerability and exposure indicators is an essential part of wildfire risk analysis. Vulnerability indicators express the conditions that increase the susceptibility of a site to the impact of wildfires and exposure indicators describe the elements at risk [2],[3]. Appropriate indicators to measure wildfire vulnerability and exposure can vary with scale and site. The consequences can be classified into economic, social, environmental and safety, and they can be tangible (human life losses, buildings damaged) or intangible (damage of cultural heritage site). As a consequence, a variety of approaches exist and there is a lack of generalized unified easy-to-implement methodologies. In this study we present a methodology for measuring consequences of wildfires in a Mediterranean area in the mesoscale (1 km² spatial resolution). Vulnerability and exposure indicators covering all consequence levels are identified and their interrelations are stressed. Variables such as building materials, roofing type, and average building values are included in the economic vulnerability level. Safety exposure is expressed by population density, demographic structure, street density and distance to closest fire station. Environmental vulnerability of protected areas and rare species is also included. Presence of cultural heritage sites, power stations and power line network influence social exposure. The conceptual framework is demonstrated with a Bayesian Network (BN). The BN model incorporates empirical observation, physical models and expert knowledge; it can also explicitly account for uncertainty in the indicators. The proposed model is applied to the island of Cyprus. Maps support the demonstration of results. [1] Keeley, J.E.; Bond, W.J.; Bradstock, R.A.; Pausas, J.G.; Rundel, P.W. (2012): Fire in Mediterranean ecosystems: ecology, evolution and management. Cambridge University Press, New York, USA. [2] UN/ISDR (International Strategy for Disaster Reduction (2004): Living with Risk: A Global Review of Disaster Reduction Initiatives, Geneva, UN Publications. [3] Birkmann, J. (2006): Measuring vulnerability to natural hazards: towards disaster resilient societies. United Nations University Press, Tokyo, Japan.
Potential implications of Luria's work for the neuropsychology of epilepsy and epilepsy surgery: A perspective for re-examination.

PubMed

Patrikelis, Panayiotis; Lucci, Giuliana; Siatouni, Anna; Verentzioti, Anastasia; Alexoudi, Athanasia; Gatzonis, Stylianos

2017-07-01

The pioneeristic work of Alexander Romanovic Luria into the field of human neuropsychology offered eminent contributions to clinical praxis by providing theory guided methods and instruments for the study of higher cortical functions. However, lots of this knowledge corpus either remains untranslated and thus inaccessible, or in some cases selectively overlooked by academic authorities and consequently not passed to the future generations of experts. Although Luria was not exclusively devoted to the study of epilepsy, his theories and clinical approaches actually penetrate the whole neuropathology spectrum. His holistic and systemic approach to the brain sounds nowadays more than opportune and consistent with the network approach of the modern neuroimaging era. As to epilepsy, the logic underlying the Lurian approach (cognitive functions organized into complex functional systems with intra- and/or inter-hemispheric distribution, as opposed to the modularistic view of the brain) seems consistent with our current knowledge in epileptology with respect to epileptic networks, as well as the modern construct of the functional deficit zone. These contributions seem to be highly promising for the neuropsychology of epilepsy and epilepsy surgery, since they provide clinicians with valuable methods and theories to assist them in the localization -and lateralization- of cognitive deficits. Consequently they are of great applicability in the context of the preoperative neuropsychological monitoring of patients candidates for epilepsy surgery, where neuropsychologist are called upon to provide surgeons with anatomical data. Copyright © 2017 Elsevier Inc. All rights reserved.
Flux Balance Analysis of Cyanobacterial Metabolism: The Metabolic Network of Synechocystis sp. PCC 6803

PubMed Central

Knoop, Henning; Gründel, Marianne; Zilliges, Yvonne; Lehmann, Robert; Hoffmann, Sabrina; Lockau, Wolfgang; Steuer, Ralf

2013-01-01

Cyanobacteria are versatile unicellular phototrophic microorganisms that are highly abundant in many environments. Owing to their capability to utilize solar energy and atmospheric carbon dioxide for growth, cyanobacteria are increasingly recognized as a prolific resource for the synthesis of valuable chemicals and various biofuels. To fully harness the metabolic capabilities of cyanobacteria necessitates an in-depth understanding of the metabolic interconversions taking place during phototrophic growth, as provided by genome-scale reconstructions of microbial organisms. Here we present an extended reconstruction and analysis of the metabolic network of the unicellular cyanobacterium Synechocystis sp. PCC 6803. Building upon several recent reconstructions of cyanobacterial metabolism, unclear reaction steps are experimentally validated and the functional consequences of unknown or dissenting pathway topologies are discussed. The updated model integrates novel results with respect to the cyanobacterial TCA cycle, an alleged glyoxylate shunt, and the role of photorespiration in cellular growth. Going beyond conventional flux-balance analysis, we extend the computational analysis to diurnal light/dark cycles of cyanobacterial metabolism. PMID:23843751
Visualization and Analysis of MiRNA-Targets Interactions Networks.

PubMed

León, Luis E; Calligaris, Sebastián D

2017-01-01

MicroRNAs are a class of small, noncoding RNA molecules of 21-25 nucleotides in length that regulate the gene expression by base-pairing with the target mRNAs, mainly leading to down-regulation or repression of the target genes. MicroRNAs are involved in diverse regulatory pathways in normal and pathological conditions. In this context, it is highly important to identify the targets of specific microRNA in order to understand the mechanism of its regulation and consequently its involvement in disease. However, the microRNA target identification is experimentally laborious and time-consuming. The in silico prediction of microRNA targets is an extremely useful approach because you can identify potential mRNA targets, reduce the number of possibilities and then, validate a few microRNA-mRNA interactions in an in vitro experimental model. In this chapter, we describe, in a simple way, bioinformatics guidelines to use miRWalk database and Cytoscape software for analyzing microRNA-mRNA interactions through their visualization as a network.
A hybrid intelligent method for three-dimensional short-term prediction of dissolved oxygen content in aquaculture.

PubMed

Chen, Yingyi; Yu, Huihui; Cheng, Yanjun; Cheng, Qianqian; Li, Daoliang

2018-01-01

A precise predictive model is important for obtaining a clear understanding of the changes in dissolved oxygen content in crab ponds. Highly accurate interval forecasting of dissolved oxygen content is fundamental to reduce risk, and three-dimensional prediction can provide more accurate results and overall guidance. In this study, a hybrid three-dimensional (3D) dissolved oxygen content prediction model based on a radial basis function (RBF) neural network, K-means and subtractive clustering was developed and named the subtractive clustering (SC)-K-means-RBF model. In this modeling process, K-means and subtractive clustering methods were employed to enhance the hyperparameters required in the RBF neural network model. The comparison of the predicted results of different traditional models validated the effectiveness and accuracy of the proposed hybrid SC-K-means-RBF model for three-dimensional prediction of dissolved oxygen content. Consequently, the proposed model can effectively display the three-dimensional distribution of dissolved oxygen content and serve as a guide for feeding and future studies.
Front-end circuit for position sensitive silicon and vacuum tube photomultipliers with gain control and depth of interaction measurement

NASA Astrophysics Data System (ADS)

Herrero, Vicente; Colom, Ricardo; Gadea, Rafael; Lerche, Christoph W.; Cerdá, Joaquín; Sebastiá, Ángel; Benlloch, José M.

2007-06-01

Silicon Photomultipliers, though still under development for mass production, may be an alternative to traditional Vacuum Photomultipliers Tubes (VPMT). As a consequence, electronic front-ends initially designed for VPMT will need to be modified. In this simulation, an improved architecture is presented which is able to obtain impact position and depth of interaction of a gamma ray within a continuous scintillation crystal, using either kind of PM. A current sensitive preamplifier stage with individual gain adjustment interfaces the multi-anode PM outputs with a current division resistor network. The preamplifier stage allows to improve front-end processing delay and temporal resolution behavior as well as to increase impact position calculation resolution. Depth of interaction (DOI) is calculated from the width of the scintillation light distribution, which is related to the sum of voltages in resistor network input nodes. This operation is done by means of a high-speed current mode scheme.
Modeling the influence of information on the coevolution of contact networks and the dynamics of infectious diseases

NASA Astrophysics Data System (ADS)

Zhang, Haifeng; Small, Michael; Fu, Xinchu; Sun, Guiquan; Wang, Binghong

2012-09-01

Outbreaks of infectious diseases may awaken the awareness of individuals, consequently, they may adjust their contact patterns according to the perceived risk from disease. In this paper, we assume that individuals make decisions on breaking or recovering links according to the information of diseases spreading which they have acquired. They will reduce some links when diseases are prevalent and have high risks; otherwise, they will recover some original links when the diseases are controlled or present minimal risk. Under such an assumption, we study the effects of information of diseases on the contact patterns within the population and on the dynamics of epidemics. By extensive simulations and theoretical analysis, we find that, due to the time-delayed information of diseases, both the density of the disease and the topology of the network vary with time in a periodic form. Our results indicate that the quality of information available to individuals can have an important effect on the spreading of infectious diseases and implications for related problems.
From Network Analysis to Functional Metabolic Modeling of the Human Gut Microbiota.

PubMed

Bauer, Eugen; Thiele, Ines

2018-01-01

An important hallmark of the human gut microbiota is its species diversity and complexity. Various diseases have been associated with a decreased diversity leading to reduced metabolic functionalities. Common approaches to investigate the human microbiota include high-throughput sequencing with subsequent correlative analyses. However, to understand the ecology of the human gut microbiota and consequently design novel treatments for diseases, it is important to represent the different interactions between microbes with their associated metabolites. Computational systems biology approaches can give further mechanistic insights by constructing data- or knowledge-driven networks that represent microbe interactions. In this minireview, we will discuss current approaches in systems biology to analyze the human gut microbiota, with a particular focus on constraint-based modeling. We will discuss various community modeling techniques with their advantages and differences, as well as their application to predict the metabolic mechanisms of intestinal microbial communities. Finally, we will discuss future perspectives and current challenges of simulating realistic and comprehensive models of the human gut microbiota.
A closer look at the relationship between the default network, mind wandering, negative mood, and depression.

PubMed

Konjedi, Shaghayegh; Maleeh, Reza

2017-08-01

By a systematic analysis of the current literature on the neural correlates of mind wandering, that is, the default network (DN), and by shedding light on some determinative factors and conditions which affect the relationship between mind wandering and negative mood, we show that (1) mind wandering per se does not necessarily have a positive correlation with negative mood and, on the higher levels, depression. We propose that negative mood as a consequence of mind wandering generally depends on two determinative conditions, that is, whether mind wandering is with or without meta-awareness and whether mind wandering occurs during high or low vigilance states; (2) increased activity of the DN is not necessarily followed by an increase in unhappiness and depression. We argue that while in some kinds of meditation practices we witness an increase in the structure and in the activity of the DN, no increase in unhappiness and depression is observed.
An incoherent feedforward loop facilitates adaptive tuning of gene expression.

PubMed

Hong, Jungeui; Brandt, Nathan; Abdul-Rahman, Farah; Yang, Ally; Hughes, Tim; Gresham, David

2018-04-05

We studied adaptive evolution of gene expression using long-term experimental evolution of Saccharomyces cerevisiae in ammonium-limited chemostats. We found repeated selection for non-synonymous variation in the DNA binding domain of the transcriptional activator, GAT1, which functions with the repressor, DAL80 in an incoherent type-1 feedforward loop (I1-FFL) to control expression of the high affinity ammonium transporter gene, MEP2. Missense mutations in the DNA binding domain of GAT1 reduce its binding to the GATAA consensus sequence. However, we show experimentally, and using mathematical modeling, that decreases in GAT1 binding result in increased expression of MEP2 as a consequence of properties of I1-FFLs. Our results show that I1-FFLs, one of the most commonly occurring network motifs in transcriptional networks, can facilitate adaptive tuning of gene expression through modulation of transcription factor binding affinities. Our findings highlight the importance of gene regulatory architectures in the evolution of gene expression. © 2018, Hong et al.
Brain Network Analysis from High-Resolution EEG Signals

NASA Astrophysics Data System (ADS)

de Vico Fallani, Fabrizio; Babiloni, Fabio

Over the last decade, there has been a growing interest in the detection of the functional connectivity in the brain from different neuroelectromagnetic and hemodynamic signals recorded by several neuro-imaging devices such as the functional Magnetic Resonance Imaging (fMRI) scanner, electroencephalography (EEG) and magnetoencephalography (MEG) apparatus. Many methods have been proposed and discussed in the literature with the aim of estimating the functional relationships among different cerebral structures. However, the necessity of an objective comprehension of the network composed by the functional links of different brain regions is assuming an essential role in the Neuroscience. Consequently, there is a wide interest in the development and validation of mathematical tools that are appropriate to spot significant features that could describe concisely the structure of the estimated cerebral networks. The extraction of salient characteristics from brain connectivity patterns is an open challenging topic, since often the estimated cerebral networks have a relative large size and complex structure. Recently, it was realized that the functional connectivity networks estimated from actual brain-imaging technologies (MEG, fMRI and EEG) can be analyzed by means of the graph theory. Since a graph is a mathematical representation of a network, which is essentially reduced to nodes and connections between them, the use of a theoretical graph approach seems relevant and useful as firstly demonstrated on a set of anatomical brain networks. In those studies, the authors have employed two characteristic measures, the average shortest path L and the clustering index C, to extract respectively the global and local properties of the network structure. They have found that anatomical brain networks exhibit many local connections (i.e. a high C) and few random long distance connections (i.e. a low L). These values identify a particular model that interpolate between a regular lattice and a random structure. Such a model has been designated as "small-world" network in analogy with the concept of the small-world phenomenon observed more than 30 years ago in social systems. In a similar way, many types of functional brain networks have been analyzed according to this mathematical approach. In particular, several studies based on different imaging techniques (fMRI, MEG and EEG) have found that the estimated functional networks showed small-world characteristics. In the functional brain connectivity context, these properties have been demonstrated to reflect an optimal architecture for the information processing and propagation among the involved cerebral structures. However, the performance of cognitive and motor tasks as well as the presence of neural diseases has been demonstrated to affect such a small-world topology, as revealed by the significant changes of L and C. Moreover, some functional brain networks have been mostly found to be very unlike the random graphs in their degree-distribution, which gives information about the allocation of the functional links within the connectivity pattern. It was demonstrated that the degree distributions of these networks follow a power-law trend. For this reason those networks are called "scale-free". They still exhibit the small-world phenomenon but tend to contain few nodes that act as highly connected "hubs". Scale-free networks are known to show resistance to failure, facility of synchronization and fast signal processing. Hence, it would be important to see whether the scaling properties of the functional brain networks are altered under various pathologies or experimental tasks. The present Chapter proposes a theoretical graph approach in order to evaluate the functional connectivity patterns obtained from high-resolution EEG signals. In this way, the "Brain Network Analysis" (in analogy with the Social Network Analysis that has emerged as a key technique in modern sociology) represents an effective methodology improving the comprehension of the complex interactions in the brain.
Temporal changes in the structure of a plant-frugivore network are influenced by bird migration and fruit availability

PubMed Central

Andresen, Ellen; Díaz-Castelazo, Cecilia

2016-01-01

Background. Ecological communities are dynamic collections whose composition and structure change over time, making up complex interspecific interaction networks. Mutualistic plant–animal networks can be approached through complex network analysis; these networks are characterized by a nested structure consisting of a core of generalist species, which endows the network with stability and robustness against disturbance. Those mutualistic network structures can vary as a consequence of seasonal fluctuations and food availability, as well as the arrival of new species into the system that might disorder the mutualistic network structure (e.g., a decrease in nested pattern). However, there is no assessment on how the arrival of migratory species into seasonal tropical systems can modify such patterns. Emergent and fine structural temporal patterns are adressed here for the first time for plant-frugivorous bird networks in a highly seasonal tropical environment. Methods. In a plant-frugivorous bird community, we analyzed the temporal turnover of bird species comprising the network core and periphery of ten temporal interaction networks resulting from different bird migration periods. Additionally, we evaluated how fruit abundance and richness, as well as the arrival of migratory birds into the system, explained the temporal changes in network parameters such as network size, connectance, nestedness, specialization, interaction strength asymmetry and niche overlap. The analysis included data from 10 quantitative plant-frugivorous bird networks registered from November 2013 to November 2014. Results. We registered a total of 319 interactions between 42 plant species and 44 frugivorous bird species; only ten bird species were part of the network core. We witnessed a noteworthy turnover of the species comprising the network periphery during migration periods, as opposed to the network core, which did not show significant temporal changes in species composition. Our results revealed that migration and fruit richness explain the temporal variations in network size, connectance, nestedness and interaction strength asymmetry. On the other hand, fruit abundance only explained connectance and nestedness. Discussion. By means of a fine-resolution temporal analysis, we evidenced for the first time how temporal changes in the interaction network structure respond to the arrival of migratory species into the system and to fruit availability. Additionally, few migratory bird species are important links for structuring networks, while most of them were peripheral species. We showed the relevance of studying bird–plant interactions at fine temporal scales, considering changing scenarios of species composition with a quantitative network approach. PMID:27330852
Armored RNA as Virus Surrogate in a Real-Time Reverse Transcriptase PCR Assay Proficiency Panel

PubMed Central

Hietala, S. K.; Crossley, B. M.

2006-01-01

In recent years testing responsibilities for high-consequence pathogens have been expanded from national reference laboratories into networks of local and regional laboratories in order to support enhanced disease surveillance and to test for surge capacity. This movement of testing of select agents and high-consequence pathogens beyond reference laboratories introduces a critical need for standardized, noninfectious surrogates of disease agents for use as training and proficiency test samples. In this study, reverse transcription-PCR assay RNA targets were developed and packaged as armored RNA for use as a noninfectious, quantifiable synthetic substitute for four high-consequence animal pathogens: classical swine fever virus; foot-and-mouth disease virus; vesicular stomatitis virus, New Jersey serogroup; and vesicular stomatitis virus, Indiana serogroup. Armored RNA spiked into oral swab fluid specimens mimicked virus-positive clinical material through all stages of the reverse transcription-PCR testing process, including RNA recovery by four different commercial extraction procedures, reverse transcription, PCR amplification, and real-time detection at target concentrations consistent with the dynamic ranges of the existing real-time PCR assays. The armored RNA concentrations spiked into the oral swab fluid specimens were stable under storage conditions selected to approximate the extremes of time and temperature expected for shipping and handling of proficiency panel samples, including 24 h at 37°C and 2 weeks at temperatures ranging from ambient room temperature to −70°C. The analytic test performance, including the reproducibility over the dynamic range of the assays, indicates that armored RNA can provide a noninfectious, quantifiable, and stable virus surrogate for specific assay training and proficiency test purposes. PMID:16390950

Network reconstructions with partially available data

NASA Astrophysics Data System (ADS)

Zhang, Chaoyang; Chen, Yang; Hu, Gang

2017-06-01

Many practical systems in natural and social sciences can be described by dynamical networks. Day by day we have measured and accumulated huge amounts of data from these networks, which can be used by us to further our understanding of the world. The structures of the networks producing these data are often unknown. Consequently, understanding the structures of these networks from available data turns to be one of the central issues in interdisciplinary fields, which is called the network reconstruction problem. In this paper, we considered problems of network reconstructions using partially available data and some situations where data availabilities are not sufficient for conventional network reconstructions. Furthermore, we proposed to infer subnetwork with data of the subnetwork available only and other nodes of the entire network hidden; to depict group-group interactions in networks with averages of groups of node variables available; and to perform network reconstructions with known data of node variables only when networks are driven by both unknown internal fast-varying noises and unknown external slowly-varying signals. All these situations are expected to be common in practical systems and the methods and results may be useful for real world applications.
Emergence of chirality in hexagonally packed monolayers of hexapentyloxytriphenylene on Au(111): a joint experimental and theoretical study.

PubMed

Sleczkowski, Piotr; Katsonis, Nathalie; Kapitanchuk, Oleksiy; Marchenko, Alexandr; Mathevet, Fabrice; Croset, Bernard; Lacaze, Emmanuelle

2014-11-11

We investigate the expression of chirality in a monolayer formed spontaneously by 2,3,6,7,10,11-pentyloxytriphenylene (H5T) on Au(111). We resolve its interface morphology by combining scanning tunneling microscopy (STM) with theoretical calculations of intermolecular and interfacial interaction potentials. We observe two commensurate structures. While both of them belong to a hexagonal space group, analogical to the triangular symmetry of the molecule and the hexagonal symmetry of the substrate surface, they surprisingly reveal a 2D chiral character. The corresponding breaking of symmetry arises for two reasons. First it is due to the establishment of a large molecular density on the substrate, which leads to a rotation of the molecules with respect to the molecular network crystallographic axes to avoid steric repulsion between neighboring alkoxy chains. Second it is due to the molecule-substrate interactions, leading to commensurable large crystallographic cells associated with the large size of the molecule. As a consequence, molecular networks disoriented with respect to the high symmetry directions of the substrate are induced. The high simplicity of the intermolecular and molecule-substrate van der Waals interactions leading to these observations suggests a generic character for this kind of symmetry breaking. We demonstrate that, for similar molecular densities, only two kinds of molecular networks are stabilized by the molecule-substrate interactions. The most stable network favors the interfacial interactions between terminal alkoxy tails and Au(111). The metastable one favors a specific orientation of the triphenylene core with its symmetry axes collinear to the Au⟨110⟩. This specific orientation of the triphenylene cores with respect to Au(111) appears associated with an energy advantage larger by at least 0.26 eV with respect to the disoriented core.
The Cortical Network for Braille Writing in the Blind.

PubMed

Likova, Lora T; Tyler, Christopher W; Cacciamani, Laura; Mineff, Kristyo; Nicholas, Spero

2016-01-01

Fundamental forms of high-order cognition, such as reading and writing, are usually studied in the context of one modality - vision. People without sight, however, use the kinesthetic-based Braille writing, and haptic-based Braille reading. We asked whether the cognitive and motor control mechanisms underlying writing and reading are modality-specific or supramodal. While a number of previous functional Magnetic Resonance Imaging (fMRI) studies have investigated the brain network for Braille reading in the blind, such studies on Braille writing are lacking. Consequently, no comparative network analysis of Braille writing vs. reading exists. Here, we report the first study of Braille writing, and a comparison of the brain organization for Braille writing vs Braille reading. FMRI was conducted in a Siemens 3T Trio scanner. Our custom MRI-compatible drawing/writing lectern was further modified to provide for Braille reading and writing. Each of five paragraphs of novel Braille text describing objects, faces and navigation sequences was read, then reproduced twice by Braille writing from memory, then read a second time. During Braille reading, the haptic-sensing of the Braille letters strongly activated not only the early visual area V1 and V2, but some highly specialized areas, such as the classical visual grapheme area and the Exner motor grapheme area. Braille-writing-from-memory, engaged a significantly more extensive network in dorsal motor, somatosensory/kinesthetic, dorsal parietal and prefrontal cortex. However, in contrast to the largely extended V1 activation in drawing-from-memory in the blind after training (Likova, 2012), Braille writing from memory generated focal activation restricted to the most foveal part of V1, presumably reflecting topographically the focal demands of such a "pin-pricking" task.
The Cortical Network for Braille Writing in the Blind

PubMed Central

Likova, Lora T.; Tyler, Christopher W.; Cacciamani, Laura; Mineff, Kristyo; Nicholas, Spero

2017-01-01

Fundamental forms of high-order cognition, such as reading and writing, are usually studied in the context of one modality - vision. People without sight, however, use the kinesthetic-based Braille writing, and haptic-based Braille reading. We asked whether the cognitive and motor control mechanisms underlying writing and reading are modality-specific or supramodal. While a number of previous functional Magnetic Resonance Imaging (fMRI) studies have investigated the brain network for Braille reading in the blind, such studies on Braille writing are lacking. Consequently, no comparative network analysis of Braille writing vs. reading exists. Here, we report the first study of Braille writing, and a comparison of the brain organization for Braille writing vs Braille reading. FMRI was conducted in a Siemens 3T Trio scanner. Our custom MRI-compatible drawing/writing lectern was further modified to provide for Braille reading and writing. Each of five paragraphs of novel Braille text describing objects, faces and navigation sequences was read, then reproduced twice by Braille writing from memory, then read a second time. During Braille reading, the haptic-sensing of the Braille letters strongly activated not only the early visual area V1 and V2, but some highly specialized areas, such as the classical visual grapheme area and the Exner motor grapheme area. Braille-writing-from-memory, engaged a significantly more extensive network in dorsal motor, somatosensory/kinesthetic, dorsal parietal and prefrontal cortex. However, in contrast to the largely extended V1 activation in drawing-from-memory in the blind after training (Likova, 2012), Braille writing from memory generated focal activation restricted to the most foveal part of V1, presumably reflecting topographically the focal demands of such a “pin-pricking” task. PMID:28890944
Assembly of a Comprehensive Regulatory Network for the Mammalian Circadian Clock: A Bioinformatics Approach

PubMed Central

Lehmann, Robert; Abreu, Monica; Fuhr, Luise; Herzel, Hanspeter; Leser, Ulf; Relógio, Angela

2015-01-01

By regulating the timing of cellular processes, the circadian clock provides a way to adapt physiology and behaviour to the geophysical time. In mammals, a light-entrainable master clock located in the suprachiasmatic nucleus (SCN) controls peripheral clocks that are present in virtually every body cell. Defective circadian timing is associated with several pathologies such as cancer and metabolic and sleep disorders. To better understand the circadian regulation of cellular processes, we developed a bioinformatics pipeline encompassing the analysis of high-throughput data sets and the exploitation of published knowledge by text-mining. We identified 118 novel potential clock-regulated genes and integrated them into an existing high-quality circadian network, generating the to-date most comprehensive network of circadian regulated genes (NCRG). To validate particular elements in our network, we assessed publicly available ChIP-seq data for BMAL1, REV-ERBα/β and RORα/γ proteins and found strong evidence for circadian regulation of Elavl1, Nme1, Dhx6, Med1 and Rbbp7 all of which are involved in the regulation of tumourigenesis. Furthermore, we identified Ncl and Ddx6, as targets of RORγ and REV-ERBα, β, respectively. Most interestingly, these genes were also reported to be involved in miRNA regulation; in particular, NCL regulates several miRNAs, all involved in cancer aggressiveness. Thus, NCL represents a novel potential link via which the circadian clock, and specifically RORγ, regulates the expression of miRNAs, with particular consequences in breast cancer progression. Our findings bring us one step forward towards a mechanistic understanding of mammalian circadian regulation, and provide further evidence of the influence of circadian deregulation in cancer. PMID:25945798
The Dallas-Fort Worth (DFW) Urban Radar Network: Enhancing Resilience in the Presence of Floods, Tornadoes, Hail and High Winds

NASA Astrophysics Data System (ADS)

Chandra*, Chandrasekar V.; the full DFW Team

2015-04-01

Currently, the National Weather Service (NWS) Next Generation Weather Radar (NEXRAD) provides observations updated every five-six minutes across the United States. However, at the maximum NEXRAD operating range of 230 km, the 0.5 degree radar beam (lowest tilt) height is about 5.4 km above ground level (AGL) because of the effect of Earth curvature. Consequently, much of the lower atmosphere (1-3 km AGL) cannot be observed by the NEXRAD. To overcome the fundamental coverage limitations of today's weather surveillance radars, and improve the spatial and temporal resolution issues, at urban scale, the National Science Foundation Engineering Research Center (NSF-ERC) for Collaborative Adaptive Sensing of the Atmosphere (CASA) has embarked the development of Dallas-Fort worth (DFW) urban remote sensing network to conduct high-resolution sensing in the lower atmosphere for a metropolitan environment, communicate high resolution observations and nowcasting of severe weather including flash floods, hail storms and high wind events. Being one of the largest inland metropolitan areas in the U.S., the DFW Metroplex is home to over 6.5 million people by 2012 according to the North Central Texas Council of Governments (NCTCOG). It experiences a wide range of natural weather hazards, including urban flash flood, high wind, tornado, and hail, etc. Successful monitoring of the rapid changing meteorological conditions in such a region is necessary for emergency management and decision making. Therefore, it is an ideal location to investigate the impacts of hazardous weather phenomena, to enhance resilience in an urban setting and demonstrate the CASA concept in a densely populated urban environment. The DFW radar network consists of 8 dual-polarization X-band weather radars and standard NEXRAD S-band radar, covering the greater DFW metropolitan region. This paper will present high resolution observation of tornado, urban flood, hail storm and damaging wind event all within the city.
Persons with Epilepsy: Between Social Inclusion and Marginalisation

PubMed Central

Mlinar, Simona; Petek, Davorina; Cotič, Živa; Mencin Čeplak, Metka; Zaletel, Marjan

2016-01-01

Background. Epilepsy is a chronic neurological disorder that can lead to complex psychosocial consequences. Epilepsy can change the social status of persons with epilepsy (PWE) and has an effect on their social inclusion as well as their perception of social inclusion. This study aims to explore subjective experiences with social inclusion of PWE in Slovenia. Methods. This study takes a qualitative approach. Eleven semistructured interviews were conducted with eleven participants. Interviews were analysed using thematic analysis. Results. Epilepsy has physical, emotional, and social consequences. Physical consequences of epilepsy are mainly tiredness and exhaustion following an epileptic episode, frequently accompanied by headaches. Emotional consequences are different forms of fear. The main social consequence identified is a negative effect on PWE's social network, which leads to (self-)isolation and social distrust. Conclusion. PWE experience of social inclusion depends on various psychosocial factors and differs from person to person. The consequences of epilepsy are shown in PWE social contacts and their sense of social inclusion and autonomy. PMID:27212802
Persons with Epilepsy: Between Social Inclusion and Marginalisation.

PubMed

Mlinar, Simona; Petek, Davorina; Cotič, Živa; Mencin Čeplak, Metka; Zaletel, Marjan

2016-01-01

Epilepsy is a chronic neurological disorder that can lead to complex psychosocial consequences. Epilepsy can change the social status of persons with epilepsy (PWE) and has an effect on their social inclusion as well as their perception of social inclusion. This study aims to explore subjective experiences with social inclusion of PWE in Slovenia. This study takes a qualitative approach. Eleven semistructured interviews were conducted with eleven participants. Interviews were analysed using thematic analysis. Epilepsy has physical, emotional, and social consequences. Physical consequences of epilepsy are mainly tiredness and exhaustion following an epileptic episode, frequently accompanied by headaches. Emotional consequences are different forms of fear. The main social consequence identified is a negative effect on PWE's social network, which leads to (self-)isolation and social distrust. PWE experience of social inclusion depends on various psychosocial factors and differs from person to person. The consequences of epilepsy are shown in PWE social contacts and their sense of social inclusion and autonomy.
Intelligent self-organization methods for wireless ad hoc sensor networks based on limited resources

NASA Astrophysics Data System (ADS)

Hortos, William S.

2006-05-01

A wireless ad hoc sensor network (WSN) is a configuration for area surveillance that affords rapid, flexible deployment in arbitrary threat environments. There is no infrastructure support and sensor nodes communicate with each other only when they are in transmission range. To a greater degree than the terminals found in mobile ad hoc networks (MANETs) for communications, sensor nodes are resource-constrained, with limited computational processing, bandwidth, memory, and power, and are typically unattended once in operation. Consequently, the level of information exchange among nodes, to support any complex adaptive algorithms to establish network connectivity and optimize throughput, not only deplete those limited resources and creates high overhead in narrowband communications, but also increase network vulnerability to eavesdropping by malicious nodes. Cooperation among nodes, critical to the mission of sensor networks, can thus be disrupted by the inappropriate choice of the method for self-organization. Recent published contributions to the self-configuration of ad hoc sensor networks, e.g., self-organizing mapping and swarm intelligence techniques, have been based on the adaptive control of the cross-layer interactions found in MANET protocols to achieve one or more performance objectives: connectivity, intrusion resistance, power control, throughput, and delay. However, few studies have examined the performance of these algorithms when implemented with the limited resources of WSNs. In this paper, self-organization algorithms for the initiation, operation and maintenance of a network topology from a collection of wireless sensor nodes are proposed that improve the performance metrics significant to WSNs. The intelligent algorithm approach emphasizes low computational complexity, energy efficiency and robust adaptation to change, allowing distributed implementation with the actual limited resources of the cooperative nodes of the network. Extensions of the algorithms from flat topologies to two-tier hierarchies of sensor nodes are presented. Results from a few simulations of the proposed algorithms are compared to the published results of other approaches to sensor network self-organization in common scenarios. The estimated network lifetime and extent under static resource allocations are computed.
An approach to efficient mobility management in intelligent networks

NASA Technical Reports Server (NTRS)

Murthy, K. M. S.

1995-01-01

Providing personal communication systems supporting full mobility require intelligent networks for tracking mobile users and facilitating outgoing and incoming calls over different physical and network environments. In realizing the intelligent network functionalities, databases play a major role. Currently proposed network architectures envision using the SS7-based signaling network for linking these DB's and also for interconnecting DB's with switches. If the network has to support ubiquitous, seamless mobile services, then it has to support additionally mobile application parts, viz., mobile origination calls, mobile destination calls, mobile location updates and inter-switch handovers. These functions will generate significant amount of data and require them to be transferred between databases (HLR, VLR) and switches (MSC's) very efficiently. In the future, the users (fixed or mobile) may use and communicate with sophisticated CPE's (e.g. multimedia, multipoint and multisession calls) which may require complex signaling functions. This will generate volumness service handling data and require efficient transfer of these message between databases and switches. Consequently, the network providers would be able to add new services and capabilities to their networks incrementally, quickly and cost-effectively.
Consequences of screening in lung cancer: development and dimensionality of a questionnaire.

PubMed

Brodersen, John; Thorsen, Hanne; Kreiner, Svend

2010-08-01

The objective of this study was to extend the Consequences of Screening (COS) Questionnaire for use in a lung cancer screening by testing for comprehension, content coverage, dimensionality, and reliability. In interviews, the suitability, content coverage, and relevance of the COS were tested on participants in a lung cancer screening program. The results were thematically analyzed to identify the key consequences of abnormal and false-positive screening results. Item Response Theory and Classical Test Theory were used to analyze data. Dimensionality, objectivity, and reliability were established by item analysis, examining the fit between item responses and Rasch models. Eight themes specifically relevant for participants in lung cancer screening results were identified: "self-blame,"focus on symptoms,"stigmatization,"introvert,"harm of smoking,"impulsivity,"empathy," and "regretful of still smoking." Altogether, 26 new items for part I and 16 new items for part II were generated. These themes were confirmed to fit a partial-credit Rasch model measuring different constructs including several of the new items. In conclusion, the reliability and the dimensionality of a condition-specific measure with high content validity for persons having abnormal or false-positive lung cancer screening results have been demonstrated. This new questionnaire called Consequences of Screening in Lung Cancer (COS-LC) covers in two parts the psychosocial experience in lung cancer screening. Part I: "anxiety,"behavior,"dejection,"sleep,"self-blame,"focus on airway symptoms,"stigmatization,"introvert," and "harm of smoking." Part II: "calm/relax,"social network,"existential values,"impulsivity,"empathy," and "regretful of still smoking."
The consequences of fetal growth restriction on brain structure and neurodevelopmental outcome.

PubMed

Miller, Suzanne L; Huppi, Petra S; Mallard, Carina

2016-02-15

Fetal growth restriction (FGR) is a significant complication of pregnancy describing a fetus that does not grow to full potential due to pathological compromise. FGR affects 3-9% of pregnancies in high-income countries, and is a leading cause of perinatal mortality and morbidity. Placental insufficiency is the principal cause of FGR, resulting in chronic fetal hypoxia. This hypoxia induces a fetal adaptive response of cardiac output redistribution to favour vital organs, including the brain, and is in consequence called brain sparing. Despite this, it is now apparent that brain sparing does not ensure normal brain development in growth-restricted fetuses. In this review we have brought together available evidence from human and experimental animal studies to describe the complex changes in brain structure and function that occur as a consequence of FGR. In both humans and animals, neurodevelopmental outcomes are influenced by the timing of the onset of FGR, the severity of FGR, and gestational age at delivery. FGR is broadly associated with reduced total brain volume and altered cortical volume and structure, decreased total number of cells and myelination deficits. Brain connectivity is also impaired, evidenced by neuronal migration deficits, reduced dendritic processes, and less efficient networks with decreased long-range connections. Subsequent to these structural alterations, short- and long-term functional consequences have been described in school children who had FGR, most commonly including problems in motor skills, cognition, memory and neuropsychological dysfunctions. © 2015 The Authors. The Journal of Physiology © 2015 The Physiological Society.
An accurate nonlinear stochastic model for MEMS-based inertial sensor error with wavelet networks

NASA Astrophysics Data System (ADS)

El-Diasty, Mohammed; El-Rabbany, Ahmed; Pagiatakis, Spiros

2007-12-01

The integration of Global Positioning System (GPS) with Inertial Navigation System (INS) has been widely used in many applications for positioning and orientation purposes. Traditionally, random walk (RW), Gauss-Markov (GM), and autoregressive (AR) processes have been used to develop the stochastic model in classical Kalman filters. The main disadvantage of classical Kalman filter is the potentially unstable linearization of the nonlinear dynamic system. Consequently, a nonlinear stochastic model is not optimal in derivative-based filters due to the expected linearization error. With a derivativeless-based filter such as the unscented Kalman filter or the divided difference filter, the filtering process of a complicated highly nonlinear dynamic system is possible without linearization error. This paper develops a novel nonlinear stochastic model for inertial sensor error using a wavelet network (WN). A wavelet network is a highly nonlinear model, which has recently been introduced as a powerful tool for modelling and prediction. Static and kinematic data sets are collected using a MEMS-based IMU (DQI-100) to develop the stochastic model in the static mode and then implement it in the kinematic mode. The derivativeless-based filtering method using GM, AR, and the proposed WN-based processes are used to validate the new model. It is shown that the first-order WN-based nonlinear stochastic model gives superior positioning results to the first-order GM and AR models with an overall improvement of 30% when 30 and 60 seconds GPS outages are introduced.
Four-trophic level food webs reveal the cascading impacts of an invasive plant targeted for biocontrol.

PubMed

López-Núñez, Francisco A; Heleno, Ruben H; Ribeiro, Sérgio; Marchante, Hélia; Marchante, Elizabete

2017-03-01

Biological invasions are a major threat to biodiversity and as such understanding their impacts is a research priority. Ecological networks provide a valuable tool to explore such impacts at the community level, and can be particularly insightful for planning and monitoring biocontrol programmes, including the potential for their seldom evaluated indirect non-target effects. Acacia longifolia is among the worst invasive species in Portugal, and has been recently targeted for biocontrol by a highly specific gall-wasp. Here we use an ambitious replicated network approach to: (1) identify the mechanisms by which direct and indirect impacts of A. longifolia can cascade from plants to higher trophic levels, including gallers, their parasitoids and inquilines; (2) reveal the structure of the interaction networks between plants, gallers, parasitoids and inquilines before the biocontrol; and (3) explore the potential for indirect interactions among gallers, including those established with the biocontrol agent, via apparent competition. Over a 15-month period, we collected 31,737 galls from native plants and identified all emerging insects, quantifying the interactions between 219 plant-, 49 galler-, 65 parasitoid- and 87 inquiline-species-one of the largest ecological networks to date. No galls were found on any of the 16 alien plant species. Invasion by A. longifolia caused an alarming simplification of plant communities, with cascading effects to higher trophic levels, namely: a decline of overall gall biomass, and on the richness, abundance and biomass of galler insects, their parasitoids, and inquilines. Correspondingly, we detected a significant decline in the richness of interactions between plants and galls. The invasion tended to increase overall interaction evenness by promoting the local extinction of the native plants that sustained more gall species. However, highly idiosyncratic responses hindered the detection of further consistent changes in network topology. Predictions of indirect effects of the biocontrol on native gallers via apparent competition ranged from negligible to highly significant. Such scenarios are incredibly hard to predict, but even if there are risks of indirect effects it is critical to weigh them carefully against the consequences of inaction and invasive species spread. © 2016 by the Ecological Society of America.
Influence of different land surfaces on atmospheric conditions measured by a wireless sensor network

NASA Astrophysics Data System (ADS)

Lengfeld, Katharina; Ament, Felix

2010-05-01

Atmospheric conditions close to the surface, like temperature, wind speed and humidity, vary on small scales because of surface heterogeneities. Therefore, the traditional measuring approach of using a single, highly accurate station is of limited representativeness for a larger domain, because it is not able to determine these small scale variabilities. However, both the variability and the domain averages are important information for the development and validation of atmospheric models and soil-vegetation-atmosphere-transfer (SVAT) schemes. Due to progress in microelectronics it is possible to construct networks of comparably cheap meteorological stations with moderate accuracy. Such a network provides data in high spatial and temporal resolution. The EPFL Lausanne developed such a network called SensorScope, consisting of low cost autonomous stations. Each station observes air and surface temperature, humidity, wind direction and speed, incoming solar radiation, precipitations, soil moisture and soil temperature and sends the data via radio communication to a base station. This base station forwards the collected data via GSM/GPRS to a central server. Within the FLUXPAT project in August 2009 we deployed 15 stations as a twin transect near Jülich, Germany. One aim of this first experiment was to test the quality of the low cost sensors by comparing them to more accurate reference measurements. It turned out, that although the network is not highly accurate, the measurements are consistent. Consequently an analysis of the pattern of atmospheric conditions is feasible. For example, we detect a variability of ± 0.5K in the mean temperature at a distance of only 2.3 km. The transect covers different types of vegetation and a small river. Therefore, we analyzed the influence of different land surfaces and the distance to the river on meteorological conditions. On the one hand, some results meet our expectations, e.g. the relative humidity decreases with increasing distance to the river. But on the other hand we found unexpected anomalies in the air temperature, which will be discussed in detail by selected case studies.
High performance spectrograph for solar UV 250-400 band

NASA Astrophysics Data System (ADS)

Di Menno, I.; Rafanelli, C.; De Simone, S.; Di Menno, M.

2007-09-01

The solar electromagnetic radiation flux is one of the important factors to evaluate the energy balance of the planet. It is important in the studies on the properties of the atmosphere and its components as AOD, on the energy requirements for anthropogenic activities as agriculture, industry and so on. The ever-increasing interest about the effects on the biosphere as consequence of anthropogenic activities has contributed to develop further studies about the solar radiation and in particular the UV band, 280-320 nm. The consequence has been a growing of instrumental site and radiometric networks. Many decisions affecting on civil society are taken using the data of these nets and consequently it is very important to study the effect of the environmental factors on the instrument output. The classical electromechanical equipments have good sensibility and resolution but their handicap is the time of the measure, generally some minutes. In this time, the sun is moved and the clouds in the sky too. The new generation of spectrometer based on solid state technology avoid the long time measurements. The paper show a new radiograph (fast spectroradiometer) for solar UV band 250-400 nm. It is based on CCD array and optical fiber. The performance are compared with a Brewer spectrophotometer during a comparison campaign close to Rome, Italy.
Chiral bis(amino acid)- and bis(amino alcohol)-oxalamide gelators. Gelation properties, self-assembly motifs and chirality effects.

PubMed

Frkanec, Leo; Zinić, Mladen

2010-01-28

Bis(amino acid)- and bis(amino alcohol)oxalamide gelators represent the class of versatile gelators whose gelation ability is a consequence of strong and directional intermolecular hydrogen bonding provided by oxalamide units and lack of molecular symmetry due to the presence of two chiral centres. Bis(amino acid)oxalamides exhibit ambidextrous gelation properties, being capable to form gels with apolar and also highly polar solvent systems and tend to organise into bilayers or inverse bilayers in hydrogel or organic solvent gel assemblies, respectively. (1)H NMR and FTIR studies of gels revealed the importance of the equilibrium between the assembled network and smaller dissolved gelator assemblies. The organisation in gel assemblies deduced from spectroscopic structural studies are in certain cases closely related to organisations found in the crystal structures of selected gelators, confirming similar organisations in gel assemblies and in the solid state. The pure enantiomer/racemate gelation controversy is addressed and the evidence provided that rac-16 forms a stable toluene gel due to resolution into enantiomeric bilayers, which then interact giving gel fibres and a network of different morphology compared to its (S,S)-enantiomer gel. The TEM investigation of both gels confirmed distinctly different gel morphologies, which allowed the relationship between the stereochemical form of the gelator, the fibre and the network morphology and the network solvent immobilisation capacity to be proposed. Mixing of the constitutionally different bis(amino acid) and bis(amino alcohol)oxalamide gelators resulted in some cases in highly improved gelation efficiency denoted as synergic gelation effect (SGE), being highly dependent also on the stereochemistry of the component gelators. Examples of photo-induced gelation based on closely related bis(amino acid)-maleic acid amide and -fumaramide and stilbene derived oxalamides where gels form by irradiation of the solution of a non-gelling isomer and its photo-isomerisation into gelling isomer are provided, as well as examples of luminescent gels, gel-based fluoride sensors, LC-gels and nanoparticle-hydrogel composites.
Network Medicine: From Cellular Networks to the Human Diseasome

NASA Astrophysics Data System (ADS)

Barabasi, Albert-Laszlo

2014-03-01

Given the functional interdependencies between the molecular components in a human cell, a disease is rarely a consequence of an abnormality in a single gene, but reflects the perturbations of the complex intracellular network. The tools of network science offer a platform to explore systematically not only the molecular complexity of a particular disease, leading to the identification of disease modules and pathways, but also the molecular relationships between apparently distinct (patho)phenotypes. Advances in this direction not only enrich our understanding of complex systems, but are also essential to identify new disease genes, to uncover the biological significance of disease-associated mutations identified by genome-wide association studies and full genome sequencing, and to identify drug targets and biomarkers for complex diseases.
Enhancement of Beaconless Location-Based Routing with Signal Strength Assistance for Ad-Hoc Networks

NASA Astrophysics Data System (ADS)

Chen, Guowei; Itoh, Kenichi; Sato, Takuro

Routing in Ad-hoc networks is unreliable due to the mobility of the nodes. Location-based routing protocols, unlike other protocols which rely on flooding, excel in network scalability. Furthermore, new location-based routing protocols, like, e. g. BLR [1], IGF [2], & CBF [3] have been proposed, with the feature of not requiring beacons in MAC-layer, which improve more in terms of scalability. Such beaconless routing protocols can work efficiently in dense network areas. However, these protocols' algorithms have no ability to avoid from routing into sparse areas. In this article, historical signal strength has been added as a factor into the BLR algorithm, which avoids routing into sparse area, and consequently improves the global routing efficiency.
Hydrodynamically induced oscillations and traffic dynamics in 1D microfludic networks

NASA Astrophysics Data System (ADS)

Bartolo, Denis; Jeanneret, Raphael

2011-03-01

We report on the traffic dynamics of particles driven through a minimal microfluidic network. Even in the minimal network consisting in a single loop, the traffic dynamics has proven to yield complex temporal patterns, including periodic, multi-periodic or chaotic sequences. This complex dynamics arises from the strongly nonlinear hydrodynamic interactions between the particles, that takes place at a junction. To better understand the consequences of this nontrivial coupling, we combined theoretical, numerical and experimental efforts and solved the 3-body problem in a 1D loop network. This apparently simple dynamical system revealed a rich and unexpected dynamics, including coherent spontaneous oscillations along closed orbits. Striking similarities between Hamiltonian systems and this driven dissipative system will be explained.

Seasonal change of topology and resilience of ecological networks in wetlandscapes

NASA Astrophysics Data System (ADS)

Bin, Kim; Park, Jeryang

2017-04-01

Wetlands distributed in a landscape provide various ecosystem services including habitat for flora and fauna, hydrologic controls, and biogeochemical processes. Hydrologic regime of each wetland at a given landscape varies by hydro-climatic and geological conditions as well as the bathymetry, forming a certain pattern in the wetland area distribution and spatial organization. However, its large-scale pattern also changes over time as this wetland complex is subject to stochastic hydro-climatic forcing in various temporal scales. Consequently, temporal variation in the spatial structure of wetlands inevitably affects the dispersal ability of species depending on those wetlands as habitat. Here, we numerically show (1) the spatiotemporal variation of wetlandscapes by forcing seasonally changing stochastic rainfall and (2) the corresponding ecological networks which either deterministically or stochastically forming the dispersal ranges. We selected four vernal pool regions with distinct climate conditions in California. The results indicate that the spatial structure of wetlands in a landscape by measuring the wetland area frequency distribution changes by seasonal hydro-climatic condition but eventually recovers to the initial state. However, the corresponding ecological networks, which the structure and function change by the change of distances between wetlands, and measured by degree distribution and network efficiency, may not recover to the initial state especially in the regions with high seasonal dryness index. Moreover, we observed that the changes in both the spatial structure of wetlands in a landscape and the corresponding ecological networks exhibit hysteresis over seasons. Our analysis indicates that the hydrologic and ecological resilience of a wetlandcape may be low in a dry region with seasonal hydro-climatic forcing. Implications of these results for modelling ecological networks depending on hydrologic systems especially for conservation purposes are discussed.
Automatic Semantic Segmentation of Brain Gliomas from MRI Images Using a Deep Cascaded Neural Network.

PubMed

Cui, Shaoguo; Mao, Lei; Jiang, Jingfeng; Liu, Chang; Xiong, Shuyu

2018-01-01

Brain tumors can appear anywhere in the brain and have vastly different sizes and morphology. Additionally, these tumors are often diffused and poorly contrasted. Consequently, the segmentation of brain tumor and intratumor subregions using magnetic resonance imaging (MRI) data with minimal human interventions remains a challenging task. In this paper, we present a novel fully automatic segmentation method from MRI data containing in vivo brain gliomas. This approach can not only localize the entire tumor region but can also accurately segment the intratumor structure. The proposed work was based on a cascaded deep learning convolutional neural network consisting of two subnetworks: (1) a tumor localization network (TLN) and (2) an intratumor classification network (ITCN). The TLN, a fully convolutional network (FCN) in conjunction with the transfer learning technology, was used to first process MRI data. The goal of the first subnetwork was to define the tumor region from an MRI slice. Then, the ITCN was used to label the defined tumor region into multiple subregions. Particularly, ITCN exploited a convolutional neural network (CNN) with deeper architecture and smaller kernel. The proposed approach was validated on multimodal brain tumor segmentation (BRATS 2015) datasets, which contain 220 high-grade glioma (HGG) and 54 low-grade glioma (LGG) cases. Dice similarity coefficient (DSC), positive predictive value (PPV), and sensitivity were used as evaluation metrics. Our experimental results indicated that our method could obtain the promising segmentation results and had a faster segmentation speed. More specifically, the proposed method obtained comparable and overall better DSC values (0.89, 0.77, and 0.80) on the combined (HGG + LGG) testing set, as compared to other methods reported in the literature. Additionally, the proposed approach was able to complete a segmentation task at a rate of 1.54 seconds per slice.
Single-Neuron NMDA Receptor Phenotype Influences Neuronal Rewiring and Reintegration following Traumatic Injury

PubMed Central

Patel, Tapan P.; Ventre, Scott C.; Geddes-Klein, Donna; Singh, Pallab K.

2014-01-01

Alterations in the activity of neural circuits are a common consequence of traumatic brain injury (TBI), but the relationship between single-neuron properties and the aggregate network behavior is not well understood. We recently reported that the GluN2B-containing NMDA receptors (NMDARs) are key in mediating mechanical forces during TBI, and that TBI produces a complex change in the functional connectivity of neuronal networks. Here, we evaluated whether cell-to-cell heterogeneity in the connectivity and aggregate contribution of GluN2B receptors to [Ca2+]i before injury influenced the functional rewiring, spontaneous activity, and network plasticity following injury using primary rat cortical dissociated neurons. We found that the functional connectivity of a neuron to its neighbors, combined with the relative influx of calcium through distinct NMDAR subtypes, together contributed to the individual neuronal response to trauma. Specifically, individual neurons whose [Ca2+]i oscillations were largely due to GluN2B NMDAR activation lost many of their functional targets 1 h following injury. In comparison, neurons with large GluN2A contribution or neurons with high functional connectivity both independently protected against injury-induced loss in connectivity. Mechanistically, we found that traumatic injury resulted in increased uncorrelated network activity, an effect linked to reduction of the voltage-sensitive Mg2+ block of GluN2B-containing NMDARs. This uncorrelated activation of GluN2B subtypes after injury significantly limited the potential for network remodeling in response to a plasticity stimulus. Together, our data suggest that two single-cell characteristics, the aggregate contribution of NMDAR subtypes and the number of functional connections, influence network structure following traumatic injury. PMID:24647941
Revisiting Robustness and Evolvability: Evolution in Weighted Genotype Spaces

PubMed Central

Partha, Raghavendran; Raman, Karthik

2014-01-01

Robustness and evolvability are highly intertwined properties of biological systems. The relationship between these properties determines how biological systems are able to withstand mutations and show variation in response to them. Computational studies have explored the relationship between these two properties using neutral networks of RNA sequences (genotype) and their secondary structures (phenotype) as a model system. However, these studies have assumed every mutation to a sequence to be equally likely; the differences in the likelihood of the occurrence of various mutations, and the consequence of probabilistic nature of the mutations in such a system have previously been ignored. Associating probabilities to mutations essentially results in the weighting of genotype space. We here perform a comparative analysis of weighted and unweighted neutral networks of RNA sequences, and subsequently explore the relationship between robustness and evolvability. We show that assuming an equal likelihood for all mutations (as in an unweighted network), underestimates robustness and overestimates evolvability of a system. In spite of discarding this assumption, we observe that a negative correlation between sequence (genotype) robustness and sequence evolvability persists, and also that structure (phenotype) robustness promotes structure evolvability, as observed in earlier studies using unweighted networks. We also study the effects of base composition bias on robustness and evolvability. Particularly, we explore the association between robustness and evolvability in a sequence space that is AU-rich – sequences with an AU content of 80% or higher, compared to a normal (unbiased) sequence space. We find that evolvability of both sequences and structures in an AU-rich space is lesser compared to the normal space, and robustness higher. We also observe that AU-rich populations evolving on neutral networks of phenotypes, can access less phenotypic variation compared to normal populations evolving on neutral networks. PMID:25390641
Modeling Nitrogen Processing in Northeast US River Networks

NASA Astrophysics Data System (ADS)

Whittinghill, K. A.; Stewart, R.; Mineau, M.; Wollheim, W. M.; Lammers, R. B.

2013-12-01

Due to increased nitrogen (N) pollution from anthropogenic sources, the need for aquatic ecosystem services such as N removal has also increased. River networks provide a buffering mechanism that retains or removes anthropogenic N inputs. However, the effectiveness of N removal in rivers may decline with increased loading and, consequently, excess N is eventually delivered to estuaries. We used a spatially distributed river network N removal model developed within the Framework for Aquatic Modeling in the Earth System (FrAMES) to examine the geography of N removal capacity of Northeast river systems under various land use and climate conditions. FrAMES accounts for accumulation and routing of runoff, water temperatures, and serial biogeochemical processing using reactivity derived from the Lotic Intersite Nitrogen Experiment (LINX2). Nonpoint N loading is driven by empirical relationships with land cover developed from previous research in Northeast watersheds. Point source N loading from wastewater treatment plants is estimated as a function of the population served and the volume of water discharged. We tested model results using historical USGS discharge data and N data from historical grab samples and recently initiated continuous measurements from in-situ aquatic sensors. Model results for major Northeast watersheds illustrate hot spots of ecosystem service activity (i.e. N removal) using high-resolution maps and basin profiles. As expected, N loading increases with increasing suburban or agricultural land use area. Network scale N removal is highest during summer and autumn when discharge is low and river temperatures are high. N removal as the % of N loading increases with catchment size and decreases with increasing N loading, suburban land use, or agricultural land use. Catchments experiencing the highest network scale N removal generally have N inputs (both point and non-point sources) located in lower order streams. Model results can be used to better predict nutrient loading to the coastal ocean across a broad range of current and future climate variability.
Evolutionary rewiring of bacterial regulatory networks

PubMed Central

Taylor, Tiffany B.; Mulley, Geraldine; McGuffin, Liam J.; Johnson, Louise J.; Brockhurst, Michael A.; Arseneault, Tanya; Silby, Mark W.; Jackson, Robert W.

2015-01-01

Bacteria have evolved complex regulatory networks that enable integration of multiple intracellular and extracellular signals to coordinate responses to environmental changes. However, our knowledge of how regulatory systems function and evolve is still relatively limited. There is often extensive homology between components of different networks, due to past cycles of gene duplication, divergence, and horizontal gene transfer, raising the possibility of cross-talk or redundancy. Consequently, evolutionary resilience is built into gene networks - homology between regulators can potentially allow rapid rescue of lost regulatory function across distant regions of the genome. In our recent study [Taylor, et al. Science (2015), 347(6225)] we find that mutations that facilitate cross-talk between pathways can contribute to gene network evolution, but that such mutations come with severe pleiotropic costs. Arising from this work are a number of questions surrounding how this phenomenon occurs. PMID:28357301
Complex networks in the Euclidean space of communicability distances

NASA Astrophysics Data System (ADS)

Estrada, Ernesto

2012-06-01

We study the properties of complex networks embedded in a Euclidean space of communicability distances. The communicability distance between two nodes is defined as the difference between the weighted sum of walks self-returning to the nodes and the weighted sum of walks going from one node to the other. We give some indications that the communicability distance identifies the least crowded routes in networks where simultaneous submission of packages is taking place. We define an index Q based on communicability and shortest path distances, which allows reinterpreting the “small-world” phenomenon as the region of minimum Q in the Watts-Strogatz model. It also allows the classification and analysis of networks with different efficiency of spatial uses. Consequently, the communicability distance displays unique features for the analysis of complex networks in different scenarios.
Coupled biopolymer networks

NASA Astrophysics Data System (ADS)

Schwarz, J. M.; Zhang, Tao

2015-03-01

The actin cytoskeleton provides the cell with structural integrity and allows it to change shape to crawl along a surface, for example. The actin cytoskeleton can be modeled as a semiflexible biopolymer network that modifies its morphology in response to both external and internal stimuli. Just inside the inner nuclear membrane of a cell exists a network of filamentous lamin that presumably protects the heart of the cell nucleus--the DNA. Lamins are intermediate filaments that can also be modeled as semiflexible biopolymers. It turns out that the actin cytoskeletal biopolymer network and the lamin biopolymer network are coupled via a sequence of proteins that bridge the outer and inner nuclear membranes. We, therefore, probe the consequences of such a coupling via numerical simulations to understand the resulting deformations in the lamin network in response to perturbations in the cytoskeletal network. Such study could have implications for mechanical mechanisms of the regulation of transcription, since DNA--yet another semiflexible polymer--contains lamin-binding domains, and, thus, widen the field of epigenetics.
Protein-protein interaction networks (PPI) and complex diseases

PubMed Central

Safari-Alighiarloo, Nahid; Taghizadeh, Mohammad; Rezaei-Tavirani, Mostafa; Goliaei, Bahram

2014-01-01

The physical interaction of proteins which lead to compiling them into large densely connected networks is a noticeable subject to investigation. Protein interaction networks are useful because of making basic scientific abstraction and improving biological and biomedical applications. Based on principle roles of proteins in biological function, their interactions determine molecular and cellular mechanisms, which control healthy and diseased states in organisms. Therefore, such networks facilitate the understanding of pathogenic (and physiologic) mechanisms that trigger the onset and progression of diseases. Consequently, this knowledge can be translated into effective diagnostic and therapeutic strategies. Furthermore, the results of several studies have proved that the structure and dynamics of protein networks are disturbed in complex diseases such as cancer and autoimmune disorders. Based on such relationship, a novel paradigm is suggested in order to confirm that the protein interaction networks can be the target of therapy for treatment of complex multi-genic diseases rather than individual molecules with disrespect the network. PMID:25436094
Influence of reciprocal edges on degree distribution and degree correlations

NASA Astrophysics Data System (ADS)

Zlatić, Vinko; Štefančić, Hrvoje

2009-07-01

Reciprocal edges represent the lowest-order cycle possible to find in directed graphs without self-loops. Representing also a measure of feedback between vertices, it is interesting to understand how reciprocal edges influence other properties of complex networks. In this paper, we focus on the influence of reciprocal edges on vertex degree distribution and degree correlations. We show that there is a fundamental difference between properties observed on the static network compared to the properties of networks, which are obtained by simple evolution mechanism driven by reciprocity. We also present a way to statistically infer the portion of reciprocal edges, which can be explained as a consequence of feedback process on the static network. In the rest of the paper, the influence of reciprocal edges on a model of growing network is also presented. It is shown that our model of growing network nicely interpolates between Barabási-Albert (BA) model for undirected and the BA model for directed networks.
Interaction Control to Synchronize Non-synchronizable Networks

PubMed Central

Schröder, Malte; Chakraborty, Sagar; Witthaut, Dirk; Nagler, Jan; Timme, Marc

2016-01-01

Synchronization constitutes one of the most fundamental collective dynamics across networked systems and often underlies their function. Whether a system may synchronize depends on the internal unit dynamics as well as the topology and strength of their interactions. For chaotic units with certain interaction topologies synchronization might be impossible across all interaction strengths, meaning that these networks are non-synchronizable. Here we propose the concept of interaction control, generalizing transient uncoupling, to induce desired collective dynamics in complex networks and apply it to synchronize even such non-synchronizable systems. After highlighting that non-synchronizability prevails for a wide range of networks of arbitrary size, we explain how a simple binary control may localize interactions in state space and thereby synchronize networks. Intriguingly, localizing interactions by a fixed control scheme enables stable synchronization across all connected networks regardless of topological constraints. Interaction control may thus ease the design of desired collective dynamics even without knowledge of the networks’ exact interaction topology and consequently have implications for biological and self-organizing technical systems. PMID:27853266
Evolving phenotypic networks in silico.

PubMed

François, Paul

2014-11-01

Evolved gene networks are constrained by natural selection. Their structures and functions are consequently far from being random, as exemplified by the multiple instances of parallel/convergent evolution. One can thus ask if features of actual gene networks can be recovered from evolutionary first principles. I review a method for in silico evolution of small models of gene networks aiming at performing predefined biological functions. I summarize the current implementation of the algorithm, insisting on the construction of a proper "fitness" function. I illustrate the approach on three examples: biochemical adaptation, ligand discrimination and vertebrate segmentation (somitogenesis). While the structure of the evolved networks is variable, dynamics of our evolved networks are usually constrained and present many similar features to actual gene networks, including properties that were not explicitly selected for. In silico evolution can thus be used to predict biological behaviours without a detailed knowledge of the mapping between genotype and phenotype. Copyright © 2014 The Author. Published by Elsevier Ltd.. All rights reserved.
The effects of malicious nodes on performance of mobile ad hoc networks

NASA Astrophysics Data System (ADS)

Li, Fanzhi; Shi, Xiyu; Jassim, Sabah; Adams, Christopher

2006-05-01

Wireless ad hoc networking offers convenient infrastructureless communication over the shared wireless channel. However, the nature of ad hoc networks makes them vulnerable to security attacks. Unlike their wired counterpart, infrastructureless ad hoc networks do not have a clear line of defense, their topology is dynamically changing, and every mobile node can receive messages from its neighbors and can be contacted by all other nodes in its neighborhood. This poses a great danger to network security if some nodes behave in a malicious manner. The immediate concern about the security in this type of networks is how to protect the network and the individual mobile nodes against malicious act of rogue nodes from within the network. This paper is concerned with security aspects of wireless ad hoc networks. We shall present results of simulation experiments on ad hoc network's performance in the presence of malicious nodes. We shall investigate two types of attacks and the consequences will be simulated and quantified in terms of loss of packets and other factors. The results show that network performance, in terms of successful packet delivery ratios, significantly deteriorates when malicious nodes act according to the defined misbehaving characteristics.
Detecting Statistically Significant Communities of Triangle Motifs in Undirected Networks

DTIC Science & Technology

2015-03-16

moderately-sized networks. As a consequence, throughout this effort, a simulated annealing (SA) algorithm will be employed to effectively search the...then increment k by 1 and repeat the search to find z∗3. Once can continue to increment k until W < zδ, at which point the algorithm will stop and...collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources
Non-Markovian State-Dependent Networks in Critical Loading

DTIC Science & Technology

2013-01-23

networks, see Reiman [18]. The results on the heavy traffic asymptotics for state-dependent rates available in the literature are mostly confined to the case...diffusion, see, Mandelbaum, Massey, and Reiman [13], Pang, Talreja, and Whitt [15], and references therein. We do not consider those set-ups in this paper...and Reiman [7] and also Dupuis and Ishii [4]) yields the regularity of the Skorohod map and is a consequence of Assumption (A1). 6 Proposition 2.3. The
A Fully Distributed Approach to the Design of a KBIT/SEC VHF Packet Radio Network,

DTIC Science & Technology

1984-02-01

topological change and consequent out-modea routing data. Algorithm development has been aided by computer simulation using a finite state machine technique...development has been aided by computer simulation using a finite state machine technique to model a realistic network of up to fifty nodes. This is...use of computer based equipments in weapons systems and their associated sensors and command and control elements and the trend from voice to data
Envisioning, quantifying, and managing thermal regimes on river networks

USGS Publications Warehouse

Steel, E. Ashley; Beechie, Timothy J.; Torgersen, Christian E.; Fullerton, Aimee H.

2017-01-01

Water temperatures fluctuate in time and space, creating diverse thermal regimes on river networks. Temporal variability in these thermal landscapes has important biological and ecological consequences because of nonlinearities in physiological reactions; spatial diversity in thermal landscapes provides aquatic organisms with options to maximize growth and survival. However, human activities and climate change threaten to alter the dynamics of riverine thermal regimes. New data and tools can identify particular facets of the thermal landscape that describe ecological and management concerns and that are linked to human actions. The emerging complexity of thermal landscapes demands innovations in communication, opens the door to exciting research opportunities on the human impacts to and biological consequences of thermal variability, suggests improvements in monitoring programs to better capture empirical patterns, provides a framework for suites of actions to restore and protect the natural processes that drive thermal complexity, and indicates opportunities for better managing thermal landscapes.
Climate change poised to threaten hydrologic connectivity and endemic fishes in dryland streams

PubMed Central

Jaeger, Kristin L.; Olden, Julian D.; Pelland, Noel A.

2014-01-01

Protecting hydrologic connectivity of freshwater ecosystems is fundamental to ensuring species persistence, ecosystem integrity, and human well-being. More frequent and severe droughts associated with climate change are poised to significantly alter flow intermittence patterns and hydrologic connectivity in dryland streams of the American Southwest, with deleterious effects on highly endangered fishes. By integrating local-scale hydrologic modeling with emerging approaches in landscape ecology, we quantify fine-resolution, watershed-scale changes in habitat size, spacing, and connectance under forecasted climate change in the Verde River Basin, United States. Model simulations project annual zero-flow day frequency to increase by 27% by midcentury, with differential seasonal consequences on continuity (temporal continuity at discrete locations) and connectivity (spatial continuity within the network). A 17% increase in the frequency of stream drying events is expected throughout the network with associated increases in the duration of these events. Flowing portions of the river network will diminish between 8% and 20% in spring and early summer and become increasingly isolated by more frequent and longer stretches of dry channel fragments, thus limiting the opportunity for native fishes to access spawning habitats and seasonally available refuges. Model predictions suggest that midcentury and late century climate will reduce network-wide hydrologic connectivity for native fishes by 6–9% over the course of a year and up to 12–18% during spring spawning months. Our work quantifies climate-induced shifts in stream drying and connectivity across a large river network and demonstrates their implications for the persistence of a globally endemic fish fauna. PMID:25136090
SME 2.0: Roadmap towards Web 2.0-Based Open Innovation in SME-Networks - A Case Study Based Research Framework

NASA Astrophysics Data System (ADS)

Lindermann, Nadine; Valcárcel, Sylvia; Schaarschmidt, Mario; von Kortzfleisch, Harald

Small- and medium sized enterprises (SMEs) are of high social and economic importance since they represent 99% of European enterprises. With regard to their restricted resources, SMEs are facing a limited capacity for innovation to compete with new challenges in a complex and dynamic competitive environment. Given this context, SMEs need to increasingly cooperate to generate innovations on an extended resource base. Our research project focuses on the aspect of open innovation in SME-networks enabled by Web 2.0 applications and referring to innovative solutions of non-competitive daily life problems. Examples are industrial safety, work-life balance issues or pollution control. The project raises the question whether the use of Web 2.0 applications can foster the exchange of creativity and innovative ideas within a network of SMEs and hence catalyze new forms of innovation processes among its participants. Using Web 2.0 applications within SMEs implies consequently breaking down innovation processes to employees’ level and thus systematically opening up a heterogeneous and broader knowledge base to idea generation. In this paper we address first steps on a roadmap towards Web 2.0-based open innovation processes within SME-networks. It presents a general framework for interaction activities leading to open innovation and recommends a regional marketplace as a viable, trust-building driver for further collaborative activities. These findings are based on field research within a specific SME-network in Rhineland-Palatinate Germany, the “WirtschaftsForum Neuwied e.V.”, which consists of roughly 100 heterogeneous SMEs employing about 8,000 workers.
Climate change poised to threaten hydrologic connectivity and endemic fishes in dryland streams.

PubMed

Jaeger, Kristin L; Olden, Julian D; Pelland, Noel A

2014-09-23

Protecting hydrologic connectivity of freshwater ecosystems is fundamental to ensuring species persistence, ecosystem integrity, and human well-being. More frequent and severe droughts associated with climate change are poised to significantly alter flow intermittence patterns and hydrologic connectivity in dryland streams of the American Southwest, with deleterious effects on highly endangered fishes. By integrating local-scale hydrologic modeling with emerging approaches in landscape ecology, we quantify fine-resolution, watershed-scale changes in habitat size, spacing, and connectance under forecasted climate change in the Verde River Basin, United States. Model simulations project annual zero-flow day frequency to increase by 27% by midcentury, with differential seasonal consequences on continuity (temporal continuity at discrete locations) and connectivity (spatial continuity within the network). A 17% increase in the frequency of stream drying events is expected throughout the network with associated increases in the duration of these events. Flowing portions of the river network will diminish between 8% and 20% in spring and early summer and become increasingly isolated by more frequent and longer stretches of dry channel fragments, thus limiting the opportunity for native fishes to access spawning habitats and seasonally available refuges. Model predictions suggest that midcentury and late century climate will reduce network-wide hydrologic connectivity for native fishes by 6-9% over the course of a year and up to 12-18% during spring spawning months. Our work quantifies climate-induced shifts in stream drying and connectivity across a large river network and demonstrates their implications for the persistence of a globally endemic fish fauna.

Don’t Judge a (Face)Book by its Cover: A Critical Review of the Implications of Social Networking Sites

DTIC Science & Technology

2011-05-01

It is vital to emphasise the possible risks, reinforce the restrictions to use, and stress the consequences of a failure to comply. This should...and the most popular sites now have in excess of 300 million members. Although these sites are currently most popular with teenagers and young adults...any necessary restrictions to use, and stress the consequences associated with a failure to comply. Evidence also suggests that education is most
Health and demographic surveillance systems: contributing to an understanding of the dynamics in migration and health

PubMed Central

Gerritsen, Annette; Bocquier, Philippe; White, Michael; Mbacké, Cheikh; Alam, Nurul; Beguy, Donatien; Odhiambo, Frank; Sacoor, Charfudin; Phuc, Ho Dang; Punpuing, Sureeporn; Collinson, Mark A.

2013-01-01

Background Migration is difficult to measure because it is highly repeatable. Health and Demographic Surveillance Systems (HDSSs) provide a unique opportunity to study migration as multiple episodes of migration are captured over time. A conceptual framework is needed to show the public health implications of migration. Objective/design Research conducted in seven HDSS centres [International Network for the Demographic Evaluation of Populations and Their Health (INDEPTH) Network], published in a peer-reviewed volume in 2009, is summarised focussing on the age–sex profile of migrants, the relation between migration and livelihoods, and the impact of migration on health. This illustrates the conceptual structure of the implications of migration. The next phase is described, the Multi-centre Analysis of the Dynamics In Migration And Health (MADIMAH) project, consisting of workshops focussed on preparing data and conducting the analyses for comparative studies amongst HDSS centres in Africa and Asia. The focus here is on the (standardisation of) determinants of migration and the impact of migration on adult mortality. Results The findings in the volume showed a relatively regular age structure for migration among all HDSS centres. Furthermore, migration generally contributes to improved living conditions at the place of origin. However, there are potential negative consequences of migration on health. It was concluded that there is a need to compare results from multiple centres using uniform covariate definitions as well as longitudinal analysis techniques. This was the starting point for the on-going MADIMAH initiative, which has increased capacity at the participating HDSS centres to produce the required datasets and conduct the analyses. Conclusions HDSS centres brought together within INDEPTH Network have already provided strong evidence of the potential negative consequences of migration on health, which contrast with the beneficial impacts of migration on livelihoods. Future comparative evidence using standardised tools will help design policies for mitigating the negative effects, and enhancing the positive effects, of migration on health. PMID:23849188
Molecular systems biology of ErbB1 signaling: bridging the gap through multiscale modeling and high-performance computing.

PubMed

Shih, Andrew J; Purvis, Jeremy; Radhakrishnan, Ravi

2008-12-01

The complexity in intracellular signaling mechanisms relevant for the conquest of many diseases resides at different levels of organization with scales ranging from the subatomic realm relevant to catalytic functions of enzymes to the mesoscopic realm relevant to the cooperative association of molecular assemblies and membrane processes. Consequently, the challenge of representing and quantifying functional or dysfunctional modules within the networks remains due to the current limitations in our understanding of mesoscopic biology, i.e., how the components assemble into functional molecular ensembles. A multiscale approach is necessary to treat a hierarchy of interactions ranging from molecular (nm, ns) to signaling (microm, ms) length and time scales, which necessitates the development and application of specialized modeling tools. Complementary to multiscale experimentation (encompassing structural biology, mechanistic enzymology, cell biology, and single molecule studies) multiscale modeling offers a powerful and quantitative alternative for the study of functional intracellular signaling modules. Here, we describe the application of a multiscale approach to signaling mediated by the ErbB1 receptor which constitutes a network hub for the cell's proliferative, migratory, and survival programs. Through our multiscale model, we mechanistically describe how point-mutations in the ErbB1 receptor can profoundly alter signaling characteristics leading to the onset of oncogenic transformations. Specifically, we describe how the point mutations induce cascading fragility mechanisms at the molecular scale as well as at the scale of the signaling network to preferentially activate the survival factor Akt. We provide a quantitative explanation for how the hallmark of preferential Akt activation in cell-lines harboring the constitutively active mutant ErbB1 receptors causes these cell-lines to be addicted to ErbB1-mediated generation of survival signals. Consequently, inhibition of ErbB1 activity leads to a remarkable therapeutic response in the addicted cell lines.
Gene Expression in Brain and Liver Produced by Three Different Regimens of Alcohol Consumption in Mice: Comparison with Immune Activation

PubMed Central

Osterndorff-Kahanek, Elizabeth; Ponomarev, Igor; Blednov, Yuri A.; Harris, R. Adron

2013-01-01

Chronically available alcohol escalates drinking in mice and a single injection of the immune activator lipopolysaccharide can mimic this effect and result in a persistent increase in alcohol consumption. We hypothesized that chronic alcohol drinking and lipopolysaccharide injections will produce some similar molecular changes that play a role in regulation of alcohol intake. We investigated the molecular mechanisms of chronic alcohol consumption or lipopolysaccharide insult by gene expression profiling in prefrontal cortex and liver of C57BL/6J mice. We identified similar patterns of transcriptional changes among four groups of animals, three consuming alcohol (vs water) in different consumption tests and one injected with lipopolysaccharide (vs. vehicle). The three tests of alcohol consumption are the continuous chronic two bottle choice (Chronic), two bottle choice available every other day (Chronic Intermittent) and limited access to one bottle of ethanol (Drinking in the Dark). Gene expression changes were more numerous and marked in liver than in prefrontal cortex for the alcohol treatments and similar in the two tissues for lipopolysaccharide. Many of the changes were unique to each treatment, but there was significant overlap in prefrontal cortex for Chronic-Chronic Intermittent and for Chronic Intermittent-lipopolysaccharide and in liver all pairs showed overlap. In silico cell-type analysis indicated that lipopolysaccharide had strongest effects on brain microglia and liver Kupffer cells. Pathway analysis detected a prefrontal cortex-based dopamine-related (PPP1R1B, DRD1, DRD2, FOSB, PDNY) network that was highly over-represented in the Chronic Intermittent group, with several genes from the network being also regulated in the Chronic and lipopolysaccharide (but not Drinking in the Dark) groups. Liver showed a CYP and GST centered metabolic network shared in part by all four treatments. We demonstrate common consequences of chronic alcohol consumption and immune activation in both liver and brain and show distinct genomic consequences of different types of alcohol consumption. PMID:23555817
Assessing the Climate Resilience of Transport Infrastructure Investments in Tanzania

NASA Astrophysics Data System (ADS)

Hall, J. W.; Pant, R.; Koks, E.; Thacker, S.; Russell, T.

2017-12-01

Whilst there is an urgent need for infrastructure investment in developing countries, there is a risk that poorly planned and built infrastructure will introduce new vulnerabilities. As climate change increases the magnitudes and frequency of natural hazard events, incidence of disruptive infrastructure failures are likely to become more frequent. Therefore, it is important that infrastructure planning and investment is underpinned by climate risk assessment that can inform adaptation planning. Tanzania's rapid economic growth is placing considerable strain on the country's transportation infrastructure (roads, railways, shipping and aviation); especially at the port of Dar es Salaam and its linking transport corridors. A growing number of natural hazard events, in particular flooding, are impacting the reliability of this already over-used network. Here we report on new methodology to analyse vulnerabilities and risks due to failures of key locations in the intermodal transport network of Tanzania, including strategic connectivity to neighboring countries. To perform the national-scale risk analysis we will utilize a system-of-systems methodology. The main components of this general risk assessment, when applied to transportation systems, include: (1) Assembling data on: spatially coherent extreme hazards and intermodal transportation networks; (2) Intersecting hazards with transport network models to initiate failure conditions that trigger failure propagation across interdependent networks; (3) Quantifying failure outcomes in terms of social impacts (customers/passengers disrupted) and/or macroeconomic consequences (across multiple sectors); and (4) Simulating, testing and collecting multiple failure scenarios to perform an exhaustive risk assessment in terms of probabilities and consequences. The methodology is being used to pinpoint vulnerability and reduce climate risks to transport infrastructure investments.
Consistent individual differences in the social phenotypes of wild great tits, Parus major

PubMed Central

Aplin, L.M.; Firth, J.A.; Farine, D.R.; Voelkl, B.; Crates, R.A.; Culina, A.; Garroway, C.J.; Hinde, C.A.; Kidd, L.R.; Psorakis, I.; Milligan, N.D.; Radersma, R.; Verhelst, B.L.; Sheldon, B.C.

2015-01-01

Despite growing interest in animal social networks, surprisingly little is known about whether individuals are consistent in their social network characteristics. Networks are rarely repeatedly sampled; yet an assumption of individual consistency in social behaviour is often made when drawing conclusions about the consequences of social processes and structure. A characterization of such social phenotypes is therefore vital to understanding the significance of social network structure for individual fitness outcomes, and for understanding the evolution and ecology of individual variation in social behaviour more broadly. Here, we measured foraging associations over three winters in a large PIT-tagged population of great tits, and used a range of social network metrics to quantify individual variation in social behaviour. We then examined repeatability in social behaviour over both short (week to week) and long (year to year) timescales, and investigated variation in repeatability across age and sex classes. Social behaviours were significantly repeatable across all timescales, with the highest repeatability observed in group size choice and unweighted degree, a measure of gregariousness. By conducting randomizations to control for the spatial and temporal distribution of individuals, we further show that differences in social phenotypes were not solely explained by within-population variation in local densities, but also reflected fine-scale variation in social decision making. Our results provide rare evidence of stable social phenotypes in a wild population of animals. Such stable social phenotypes can be targets of selection and may have important fitness consequences, both for individuals and for their social-foraging associates. PMID:26512142
Pathway mapping and development of disease-specific biomarkers: protein-based network biomarkers

PubMed Central

Chen, Hao; Zhu, Zhitu; Zhu, Yichun; Wang, Jian; Mei, Yunqing; Cheng, Yunfeng

2015-01-01

It is known that a disease is rarely a consequence of an abnormality of a single gene, but reflects the interactions of various processes in a complex network. Annotated molecular networks offer new opportunities to understand diseases within a systems biology framework and provide an excellent substrate for network-based identification of biomarkers. The network biomarkers and dynamic network biomarkers (DNBs) represent new types of biomarkers with protein–protein or gene–gene interactions that can be monitored and evaluated at different stages and time-points during development of disease. Clinical bioinformatics as a new way to combine clinical measurements and signs with human tissue-generated bioinformatics is crucial to translate biomarkers into clinical application, validate the disease specificity, and understand the role of biomarkers in clinical settings. In this article, the recent advances and developments on network biomarkers and DNBs are comprehensively reviewed. How network biomarkers help a better understanding of molecular mechanism of diseases, the advantages and constraints of network biomarkers for clinical application, clinical bioinformatics as a bridge to the development of diseases-specific, stage-specific, severity-specific and therapy predictive biomarkers, and the potentials of network biomarkers are also discussed. PMID:25560835
Anticipatory Cognitive Systems: a Theoretical Model

NASA Astrophysics Data System (ADS)

Terenzi, Graziano

This paper deals with the problem of understanding anticipation in biological and cognitive systems. It is argued that a physical theory can be considered as biologically plausible only if it incorporates the ability to describe systems which exhibit anticipatory behaviors. The paper introduces a cognitive level description of anticipation and provides a simple theoretical characterization of anticipatory systems on this level. Specifically, a simple model of a formal anticipatory neuron and a model (i.e. the τ-mirror architecture) of an anticipatory neural network which is based on the former are introduced and discussed. The basic feature of this architecture is that a part of the network learns to represent the behavior of the other part over time, thus constructing an implicit model of its own functioning. As a consequence, the network is capable of self-representation; anticipation, on a oscopic level, is nothing but a consequence of anticipation on a microscopic level. Some learning algorithms are also discussed together with related experimental tasks and possible integrations. The outcome of the paper is a formal characterization of anticipation in cognitive systems which aims at being incorporated in a comprehensive and more general physical theory.
NKT Cell Networks in the Regulation of Tumor Immunity

PubMed Central

Robertson, Faith C.; Berzofsky, Jay A.; Terabe, Masaki

2014-01-01

CD1d-restricted natural killer T (NKT) cells lie at the interface between the innate and adaptive immune systems and are important mediators of immune responses and tumor immunosurveillance. These NKT cells uniquely recognize lipid antigens, and their rapid yet specific reactions influence both innate and adaptive immunity. In tumor immunity, two NKT subsets (type I and type II) have contrasting roles in which they not only cross-regulate one another, but also impact innate immune cell populations, including natural killer, dendritic, and myeloid lineage cells, as well as adaptive populations, especially CD8+ and CD4+ T cells. The extent to which NKT cells promote or suppress surrounding cells affects the host’s ability to prevent neoplasia and is consequently of great interest for therapeutic development. Data have shown the potential for therapeutic use of NKT cell agonists and synergy with immune response modifiers in both pre-clinical studies and preliminary clinical studies. However, there is room to improve treatment efficacy by further elucidating the biological mechanisms underlying NKT cell networks. Here, we discuss the progress made in understanding NKT cell networks, their consequent role in the regulation of tumor immunity, and the potential to exploit that knowledge in a clinical setting. PMID:25389427
Programming of the appetite-regulating neural network: a link between maternal overnutrition and the programming of obesity?

PubMed

Mühlhäusler, B S

2007-01-01

The concept of a functional foetal "appetite regulatory neural network" is a new and potentially critical one. There is a growing body of evidence showing that the nutritional environment to which the foetus is exposed during prenatal and perinatal development has long-term consequences for the function of the appetite-regulating neural network and therefore the way in which an individual regulates energy balance throughout later life. This is of particular importance in the context of evidence obtained from a wide range of epidemiological studies, which have shown that individuals exposed to an elevated nutrient supply before birth have an increased risk of becoming obese as children and adults. This review summarises the key pieces of experimental evidence, by our group and others, that have contributed to our current understanding of the programming of appetite, and highlights the important questions that are yet to be answered. It is clear that this area of research has the potential to generate, within the next few years, interventions that could begin to alleviate the adverse long-term consequences of being exposed to an elevated nutrient supply before birth.
Living in the branches: population dynamics and ecological processes in dendritic networks

USGS Publications Warehouse

Grant, E.H.C.; Lowe, W.H.; Fagan, W.F.

2007-01-01

Spatial structure regulates and modifies processes at several levels of ecological organization (e.g. individual/genetic, population and community) and is thus a key component of complex systems, where knowledge at a small scale can be insufficient for understanding system behaviour at a larger scale. Recent syntheses outline potential applications of network theory to ecological systems, but do not address the implications of physical structure for network dynamics. There is a specific need to examine how dendritic habitat structure, such as that found in stream, hedgerow and cave networks, influences ecological processes. Although dendritic networks are one type of ecological network, they are distinguished by two fundamental characteristics: (1) both the branches and the nodes serve as habitat, and (2) the specific spatial arrangement and hierarchical organization of these elements interacts with a species' movement behaviour to alter patterns of population distribution and abundance, and community interactions. Here, we summarize existing theory relating to ecological dynamics in dendritic networks, review empirical studies examining the population- and community-level consequences of these networks, and suggest future research integrating spatial pattern and processes in dendritic systems.
Matching-centrality decomposition and the forecasting of new links in networks.

PubMed

Rohr, Rudolf P; Naisbit, Russell E; Mazza, Christian; Bersier, Louis-Félix

2016-02-10

Networks play a prominent role in the study of complex systems of interacting entities in biology, sociology, and economics. Despite this diversity, we demonstrate here that a statistical model decomposing networks into matching and centrality components provides a comprehensive and unifying quantification of their architecture. The matching term quantifies the assortative structure in which node makes links with which other node, whereas the centrality term quantifies the number of links that nodes make. We show, for a diverse set of networks, that this decomposition can provide a tight fit to observed networks. Then we provide three applications. First, we show that the model allows very accurate prediction of missing links in partially known networks. Second, when node characteristics are known, we show how the matching-centrality decomposition can be related to this external information. Consequently, it offers us a simple and versatile tool to explore how node characteristics explain network architecture. Finally, we demonstrate the efficiency and flexibility of the model to forecast the links that a novel node would create if it were to join an existing network. © 2016 The Author(s).
Measures of node centrality in mobile social networks

NASA Astrophysics Data System (ADS)

Gao, Zhenxiang; Shi, Yan; Chen, Shanzhi

2015-02-01

Mobile social networks exploit human mobility and consequent device-to-device contact to opportunistically create data paths over time. While links in mobile social networks are time-varied and strongly impacted by human mobility, discovering influential nodes is one of the important issues for efficient information propagation in mobile social networks. Although traditional centrality definitions give metrics to identify the nodes with central positions in static binary networks, they cannot effectively identify the influential nodes for information propagation in mobile social networks. In this paper, we address the problems of discovering the influential nodes in mobile social networks. We first use the temporal evolution graph model which can more accurately capture the topology dynamics of the mobile social network over time. Based on the model, we explore human social relations and mobility patterns to redefine three common centrality metrics: degree centrality, closeness centrality and betweenness centrality. We then employ empirical traces to evaluate the benefits of the proposed centrality metrics, and discuss the predictability of nodes' global centrality ranking by nodes' local centrality ranking. Results demonstrate the efficiency of the proposed centrality metrics.
Matching–centrality decomposition and the forecasting of new links in networks

PubMed Central

Rohr, Rudolf P.; Naisbit, Russell E.; Mazza, Christian; Bersier, Louis-Félix

2016-01-01

Networks play a prominent role in the study of complex systems of interacting entities in biology, sociology, and economics. Despite this diversity, we demonstrate here that a statistical model decomposing networks into matching and centrality components provides a comprehensive and unifying quantification of their architecture. The matching term quantifies the assortative structure in which node makes links with which other node, whereas the centrality term quantifies the number of links that nodes make. We show, for a diverse set of networks, that this decomposition can provide a tight fit to observed networks. Then we provide three applications. First, we show that the model allows very accurate prediction of missing links in partially known networks. Second, when node characteristics are known, we show how the matching–centrality decomposition can be related to this external information. Consequently, it offers us a simple and versatile tool to explore how node characteristics explain network architecture. Finally, we demonstrate the efficiency and flexibility of the model to forecast the links that a novel node would create if it were to join an existing network. PMID:26842568
The Reverse Thermal Effect in Epoxy Resins and Moisture Absorption in Semi-Interpenetrating Polymer Networks.

NASA Astrophysics Data System (ADS)

El-Sa'Ad, Leila

1989-12-01

Available from UMI in association with The British Library. Requires signed TDF. Epoxy resins exhibit many desirable properties which make them ideal subjects for use as matrices of composite materials in many commercial, military and space applications. However, due to their high cross-link density they are often brittle. Epoxy resin networks have been modified by incorporating tough, ductile thermoplastics. Such systems are referred to as Semi-Interpenetrating Polymer Networks (Semi-IPN). Systematic modification to the thermoplastics backbone allowed the morphology of the blend to be controlled from a homogeneous one-phase structure to fully separated structures. The moisture absorption by composites in humid environments has been found to lead to a deterioration in the physical and mechanical properties of the matrix. Therefore, in order to utilize composites to their full potential, their response to hot/wet environments must be known. The aims of this investigation were two-fold. Firstly, to study the effect of varying the temperature of exposure at different stages in the absorption process on the water absorption behaviour of a TGDDM/DDS epoxy resin system. Secondly, to study water absorption characteristics, under isothermal conditions, of Semi-Interpenetrating Polymer Networks possessing different morphologies, and develop a theoretical model to evaluate the diffusion coefficients of the two-phase structures. The mathematical treatment used in this analysis was based on Fick's second law of diffusion. Tests were performed on specimens immersed in water at 10 ^circ, 40^circ and 70^circC, their absorption behaviour and swelling behaviour, as a consequence of water absorption, were investigated. The absorption results of the variable temperature absorption tests indicated a saturation dependence on the absorption behaviour. Specimens saturated at a high temperature will undergo further absorption when transferred to a lower temperature. This behaviour was termed the "reverse thermal effect". The swelling results suggested that it is more tightly bound water in the polymer which takes part in the reverse thermal effect. The absorption results for the Semi-Interpenetrating Polymer Networks suggested that the two key parameters which affected the moisture uptake were the morphology of the network and the percentage of epoxy resin in the system.
Investigation of trailing mass in Z-pinch implosions and comparison to experiment

NASA Astrophysics Data System (ADS)

Yu, Edmund

2007-11-01

Wire-array Z pinches represent efficient, high-power x-ray sources with application to inertial confinement fusion, high energy density plasmas, and laboratory astrophysics. The first stage of a wire-array Z pinch is described by a mass ablation phase, during which stationary wires cook off material, which is then accelerated radially inwards by the JxB force. The mass injection rate varies axially and azimuthally, so that once the ablation phase concludes, the subsequent implosion is highly 3D in nature. In particular, a network of trailing mass and current is left behind the imploding plasma sheath, which can significantly affect pinch performance. In this work we focus on the implosion phase, electing to model the mass ablation via a mass injection scheme. Such a scheme has a number of injection parameters, but this freedom also allows us to gain understanding into the nature of the trailing mass network. For instance, a new result illustrates the role of azimuthal correlation. For an implosion which is 100% azimuthally correlated (corresponding to an azimuthally symmetric 2D r-z problem), current is forced to flow on the imploding plasma sheath, resulting in strong Rayleigh-Taylor (RT) growth. If, however, the implosion is not azimuthally symmetric, the additional azimuthal degree of freedom opens up new conducting paths of lower magnetic energy through the trailing mass network, effectively reducing RT growth. Consequently the 3D implosion experiences lower RT growth than the 2D r-z equivalent, and actually results in a more shell-like implosion. A second major goal of this work is to constrain the injection parameters by comparison to a well-diagnosed experimental data set, in which array mass was varied. In collaboration with R. Lemke, M. Desjarlais, M. Cuneo, C. Jennings, D. Sinars, E. Waisman
Artificial light at night as a new threat to pollination.

PubMed

Knop, Eva; Zoller, Leana; Ryser, Remo; Gerpe, Christopher; Hörler, Maurin; Fontaine, Colin

2017-08-10

Pollinators are declining worldwide and this has raised concerns for a parallel decline in the essential pollination service they provide to both crops and wild plants. Anthropogenic drivers linked to this decline include habitat changes, intensive agriculture, pesticides, invasive alien species, spread of pathogens and climate change. Recently, the rapid global increase in artificial light at night has been proposed to be a new threat to terrestrial ecosystems; the consequences of this increase for ecosystem function are mostly unknown. Here we show that artificial light at night disrupts nocturnal pollination networks and has negative consequences for plant reproductive success. In artificially illuminated plant-pollinator communities, nocturnal visits to plants were reduced by 62% compared to dark areas. Notably, this resulted in an overall 13% reduction in fruit set of a focal plant even though the plant also received numerous visits by diurnal pollinators. Furthermore, by merging diurnal and nocturnal pollination sub-networks, we show that the structure of these combined networks tends to facilitate the spread of the negative consequences of disrupted nocturnal pollination to daytime pollinator communities. Our findings demonstrate that artificial light at night is a threat to pollination and that the negative effects of artificial light at night on nocturnal pollination are predicted to propagate to the diurnal community, thereby aggravating the decline of the diurnal community. We provide perspectives on the functioning of plant-pollinator communities, showing that nocturnal pollinators are not redundant to diurnal communities and increasing our understanding of the human-induced decline in pollinators and their ecosystem service.
Poor mental health, peer drinking norms, and alcohol risk in a social network of first-year college students.

PubMed

Kenney, Shannon R; DiGuiseppi, Graham T; Meisel, Matthew K; Balestrieri, Sara G; Barnett, Nancy P

2018-09-01

College students with anxiety and depressive symptomatology face escalated risk for alcohol-related negative consequences. While it is well-established that normative perceptions of proximal peers' drinking behaviors influence students' own drinking behaviors, it is not clear how mental health status impacts this association. In the current study, we examined cross-sectional relationships between anxiety and depressed mood, perceived drinking behaviors and attitudes of important peers, and past month alcohol consumption and related problems in a first-semester college student social network. Participants (N = 1254, 55% female, 47% non-Hispanic White) were first-year students residing on campus at a single university who completed a web-based survey assessing alcohol use, mental health, and social connections among first-year student peers. Network autocorrelation models were used to examine the independent and interactive associations between mental health and perceptions of close peers' drinking on drinking outcomes, controlling for important variables. Mental health interacted with perceptions to predict past-month drinking outcomes, such that higher anxiety and higher perceptions that peers drink heavily was associated with more drinks consumed and consequences, and higher depression and perceptions was associated with more drinks consumed, heavy drinking frequency, and consequences. Attitudes that peers approve of heavy drinking were associated with more drinks consumed and heavy drinking frequency among students with lower (vs. higher) depressed mood. This study provides strong evidence that perceiving that close peers drink heavily is particularly risk-enhancing for anxious and depressed college students, and offers implications about alcohol intervention targeted at these subgroups. Copyright © 2018 Elsevier Ltd. All rights reserved.
Impaired Tuning of Neural Ensembles and the Pathophysiology of Schizophrenia: A Translational and Computational Neuroscience Perspective.

PubMed

Krystal, John H; Anticevic, Alan; Yang, Genevieve J; Dragoi, George; Driesen, Naomi R; Wang, Xiao-Jing; Murray, John D

2017-05-15

The functional optimization of neural ensembles is central to human higher cognitive functions. When the functions through which neural activity is tuned fail to develop or break down, symptoms and cognitive impairments arise. This review considers ways in which disturbances in the balance of excitation and inhibition might develop and be expressed in cortical networks in association with schizophrenia. This presentation is framed within a developmental perspective that begins with disturbances in glutamate synaptic development in utero. It considers developmental correlates and consequences, including compensatory mechanisms that increase intrinsic excitability or reduce inhibitory tone. It also considers the possibility that these homeostatic increases in excitability have potential negative functional and structural consequences. These negative functional consequences of disinhibition may include reduced working memory-related cortical activity associated with the downslope of the "inverted-U" input-output curve, impaired spatial tuning of neural activity and impaired sparse coding of information, and deficits in the temporal tuning of neural activity and its implication for neural codes. The review concludes by considering the functional significance of noisy activity for neural network function. The presentation draws on computational neuroscience and pharmacologic and genetic studies in animals and humans, particularly those involving N-methyl-D-aspartate glutamate receptor antagonists, to illustrate principles of network regulation that give rise to features of neural dysfunction associated with schizophrenia. While this presentation focuses on schizophrenia, the general principles outlined in the review may have broad implications for considering disturbances in the regulation of neural ensembles in psychiatric disorders. Published by Elsevier Inc.
Efficient estimators for likelihood ratio sensitivity indices of complex stochastic dynamics.

PubMed

Arampatzis, Georgios; Katsoulakis, Markos A; Rey-Bellet, Luc

2016-03-14

We demonstrate that centered likelihood ratio estimators for the sensitivity indices of complex stochastic dynamics are highly efficient with low, constant in time variance and consequently they are suitable for sensitivity analysis in long-time and steady-state regimes. These estimators rely on a new covariance formulation of the likelihood ratio that includes as a submatrix a Fisher information matrix for stochastic dynamics and can also be used for fast screening of insensitive parameters and parameter combinations. The proposed methods are applicable to broad classes of stochastic dynamics such as chemical reaction networks, Langevin-type equations and stochastic models in finance, including systems with a high dimensional parameter space and/or disparate decorrelation times between different observables. Furthermore, they are simple to implement as a standard observable in any existing simulation algorithm without additional modifications.

Efficient estimators for likelihood ratio sensitivity indices of complex stochastic dynamics

NASA Astrophysics Data System (ADS)

Arampatzis, Georgios; Katsoulakis, Markos A.; Rey-Bellet, Luc

2016-03-01

We demonstrate that centered likelihood ratio estimators for the sensitivity indices of complex stochastic dynamics are highly efficient with low, constant in time variance and consequently they are suitable for sensitivity analysis in long-time and steady-state regimes. These estimators rely on a new covariance formulation of the likelihood ratio that includes as a submatrix a Fisher information matrix for stochastic dynamics and can also be used for fast screening of insensitive parameters and parameter combinations. The proposed methods are applicable to broad classes of stochastic dynamics such as chemical reaction networks, Langevin-type equations and stochastic models in finance, including systems with a high dimensional parameter space and/or disparate decorrelation times between different observables. Furthermore, they are simple to implement as a standard observable in any existing simulation algorithm without additional modifications.
Efficient estimators for likelihood ratio sensitivity indices of complex stochastic dynamics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Arampatzis, Georgios; Katsoulakis, Markos A.; Rey-Bellet, Luc

2016-03-14

We demonstrate that centered likelihood ratio estimators for the sensitivity indices of complex stochastic dynamics are highly efficient with low, constant in time variance and consequently they are suitable for sensitivity analysis in long-time and steady-state regimes. These estimators rely on a new covariance formulation of the likelihood ratio that includes as a submatrix a Fisher information matrix for stochastic dynamics and can also be used for fast screening of insensitive parameters and parameter combinations. The proposed methods are applicable to broad classes of stochastic dynamics such as chemical reaction networks, Langevin-type equations and stochastic models in finance, including systemsmore » with a high dimensional parameter space and/or disparate decorrelation times between different observables. Furthermore, they are simple to implement as a standard observable in any existing simulation algorithm without additional modifications.« less
Intermittent kangaroo mother care: a NICU protocol.

PubMed

Davanzo, Riccardo; Brovedani, Pierpaolo; Travan, Laura; Kennedy, Jacqueline; Crocetta, Anna; Sanesi, Cecilia; Strajn, Tamara; De Cunto, Angela

2013-08-01

The practice of kangaroo mother care (KMC) is steadily increasing in high-tech settings due to its proven benefits for both infants and parents. In spite of that, clear guidelines about how to implement this method of care are lacking, and as a consequence, some restrictions are applied in many neonatal intensive care units (NICUs), preventing its practice. Based on recommendations from the Expert Group of the International Network on Kangaroo Mother Care, we developed a hospital protocol in the neonatal unit of the Institute for Maternal and Child Health in Trieste, Italy, a level 3 unit, aimed to facilitate and promote KMC implementation in high-tech settings. Our guideline is therefore proposed, based both on current scientific literature and on practical considerations and experience. Future adjustments and improvements would be considered based on increasing clinical KMC use and further knowledge.
Architecture for interoperable software in biology.

PubMed

Bare, James Christopher; Baliga, Nitin S

2014-07-01

Understanding biological complexity demands a combination of high-throughput data and interdisciplinary skills. One way to bring to bear the necessary combination of data types and expertise is by encapsulating domain knowledge in software and composing that software to create a customized data analysis environment. To this end, simple flexible strategies are needed for interconnecting heterogeneous software tools and enabling data exchange between them. Drawing on our own work and that of others, we present several strategies for interoperability and their consequences, in particular, a set of simple data structures--list, matrix, network, table and tuple--that have proven sufficient to achieve a high degree of interoperability. We provide a few guidelines for the development of future software that will function as part of an interoperable community of software tools for biological data analysis and visualization. © The Author 2012. Published by Oxford University Press.
Transportation statistics annual report 1996 : transportation and the environment

DOT National Transportation Integrated Search

1996-01-01

This report is a summary of the state of the nation's transportation systems and the issues and consequences of maintaining such a diverse and complex network. All transportation modes -- air, highway, rail, water, and pipeline -- are examined throug...
Genomics and transcriptomics in drug discovery.

PubMed

Dopazo, Joaquin

2014-02-01

The popularization of genomic high-throughput technologies is causing a revolution in biomedical research and, particularly, is transforming the field of drug discovery. Systems biology offers a framework to understand the extensive human genetic heterogeneity revealed by genomic sequencing in the context of the network of functional, regulatory and physical protein-drug interactions. Thus, approaches to find biomarkers and therapeutic targets will have to take into account the complex system nature of the relationships of the proteins with the disease. Pharmaceutical companies will have to reorient their drug discovery strategies considering the human genetic heterogeneity. Consequently, modeling and computational data analysis will have an increasingly important role in drug discovery. Copyright © 2013 Elsevier Ltd. All rights reserved.
Can multilayer brain networks be a real step forward?. Comment on "Network science of biological systems at different scales: A review" by M. Gosak et al.

NASA Astrophysics Data System (ADS)

Buldú, Javier M.; Papo, David

2018-03-01

Over the last two decades Network Science has become one of the most active fields in science, whose growth has been supported by four fundamental pillars: statistical physics, nonlinear dynamics, graph theory and Big Data [1]. Initially concerned with analyzing the structure of networks, Network Science rapidly turned its attention, focused on the implications of network topology, on the dynamics of and processes unfolding on networked systems, greatly improving our understanding of diffusion, synchronization, epidemics and information transmission in complex systems [2]. The network approach typically considered complex systems as evolving in a vacuum; however real networks are generally not isolated systems, but are in continuous and evolving contact with other networks, with which they interact in multiple qualitative different and typically time-varying ways. These systems can then be represented as a collection of subsystems with connectivity layers, which are simply collapsed when considering the traditional monolayer representation. Surprisingly, such an "unpacking" of layers has proven to bear profound consequences on the structural and dynamical properties of networks, leading for instance to counter-intuitive synchronization phenomena, where maximization synchronization is achieved through strategies opposite of those maximizing synchronization in isolated networks [3].
Spatio-temporal propagation of cascading overload failures in spatially embedded networks

NASA Astrophysics Data System (ADS)

Zhao, Jichang; Li, Daqing; Sanhedrai, Hillel; Cohen, Reuven; Havlin, Shlomo

2016-01-01

Different from the direct contact in epidemics spread, overload failures propagate through hidden functional dependencies. Many studies focused on the critical conditions and catastrophic consequences of cascading failures. However, to understand the network vulnerability and mitigate the cascading overload failures, the knowledge of how the failures propagate in time and space is essential but still missing. Here we study the spatio-temporal propagation behaviour of cascading overload failures analytically and numerically on spatially embedded networks. The cascading overload failures are found to spread radially from the centre of the initial failure with an approximately constant velocity. The propagation velocity decreases with increasing tolerance, and can be well predicted by our theoretical framework with one single correction for all the tolerance values. This propagation velocity is found similar in various model networks and real network structures. Our findings may help to predict the dynamics of cascading overload failures in realistic systems.
A network perspective on the processes of empowered organizations.

PubMed

Neal, Zachary P

2014-06-01

Organizational empowerment is a multi-faceted concept that involves processes occurring both within and between organizations that facilitate achievement of their goals. This paper takes a closer look at three interorganizational processes that lead to empowered organizations: building alliances, getting the word out, and capturing others' attention. These processes are located within the broader nomological network of empowerment and organizational empowerment, and are linked to particular patterns of interorganizational relationships that facilitate organizations' ability to engage in them. A new network-based measure, γ-centrality, is introduced to capture the particular network structure associated with each process to be assessed. It is demonstrated first in a hypothetical organizational network, then applied to take a closer look at organizational empowerment in the context of a coordinating council composed of human service agencies. The paper concludes with a discussion of the implications of relationships between these processes, and the potential for unintended consequences in the empowerment of organizations.
A network property necessary for concentration robustness

NASA Astrophysics Data System (ADS)

Eloundou-Mbebi, Jeanne M. O.; Küken, Anika; Omranian, Nooshin; Kleessen, Sabrina; Neigenfind, Jost; Basler, Georg; Nikoloski, Zoran

2016-10-01

Maintenance of functionality of complex cellular networks and entire organisms exposed to environmental perturbations often depends on concentration robustness of the underlying components. Yet, the reasons and consequences of concentration robustness in large-scale cellular networks remain largely unknown. Here, we derive a necessary condition for concentration robustness based only on the structure of networks endowed with mass action kinetics. The structural condition can be used to design targeted experiments to study concentration robustness. We show that metabolites satisfying the necessary condition are present in metabolic networks from diverse species, suggesting prevalence of this property across kingdoms of life. We also demonstrate that our predictions about concentration robustness of energy-related metabolites are in line with experimental evidence from Escherichia coli. The necessary condition is applicable to mass action biological systems of arbitrary size, and will enable understanding the implications of concentration robustness in genetic engineering strategies and medical applications.
A Computer Model of Insect Traps in a Landscape

NASA Astrophysics Data System (ADS)

Manoukis, Nicholas C.; Hall, Brian; Geib, Scott M.

2014-11-01

Attractant-based trap networks are important elements of invasive insect detection, pest control, and basic research programs. We present a landscape-level, spatially explicit model of trap networks, focused on detection, that incorporates variable attractiveness of traps and a movement model for insect dispersion. We describe the model and validate its behavior using field trap data on networks targeting two species, Ceratitis capitata and Anoplophora glabripennis. Our model will assist efforts to optimize trap networks by 1) introducing an accessible and realistic mathematical characterization of the operation of a single trap that lends itself easily to parametrization via field experiments and 2) allowing direct quantification and comparison of sensitivity between trap networks. Results from the two case studies indicate that the relationship between number of traps and their spatial distribution and capture probability under the model is qualitatively dependent on the attractiveness of the traps, a result with important practical consequences.
Social influence and bullying behavior: intervention-based network dynamics of the fairplayer.manual bullying prevention program.

PubMed

Wölfer, Ralf; Scheithauer, Herbert

2014-01-01

Bullying is a social phenomenon and although preventive interventions consequently address social mechanisms, evaluations hardly consider the complexity of peer processes. Therefore, the present study analyzes the efficacy of the fairplayer.manual bullying prevention program from a social network perspective. Within a pretest-posttest control group design, longitudinal data were available from 328 middle-school students (MAge = 13.7 years; 51% girls), who provided information on bullying behavior and interaction patterns. The revealed network parameters were utilized to examine the network change (MANCOVA) and the network dynamics (SIENA). Across both forms of analyses, findings revealed the hypothesized intervention-based decrease of bullies' social influence. Hence the present bullying prevention program, as one example of programs that successfully addresses both individual skills and social mechanisms, demonstrates the desired effect of reducing contextual opportunities for the exhibition of bullying behavior. © 2014 Wiley Periodicals, Inc.
A network property necessary for concentration robustness.

PubMed

Eloundou-Mbebi, Jeanne M O; Küken, Anika; Omranian, Nooshin; Kleessen, Sabrina; Neigenfind, Jost; Basler, Georg; Nikoloski, Zoran

2016-10-19

Maintenance of functionality of complex cellular networks and entire organisms exposed to environmental perturbations often depends on concentration robustness of the underlying components. Yet, the reasons and consequences of concentration robustness in large-scale cellular networks remain largely unknown. Here, we derive a necessary condition for concentration robustness based only on the structure of networks endowed with mass action kinetics. The structural condition can be used to design targeted experiments to study concentration robustness. We show that metabolites satisfying the necessary condition are present in metabolic networks from diverse species, suggesting prevalence of this property across kingdoms of life. We also demonstrate that our predictions about concentration robustness of energy-related metabolites are in line with experimental evidence from Escherichia coli. The necessary condition is applicable to mass action biological systems of arbitrary size, and will enable understanding the implications of concentration robustness in genetic engineering strategies and medical applications.
A network property necessary for concentration robustness

PubMed Central

Eloundou-Mbebi, Jeanne M. O.; Küken, Anika; Omranian, Nooshin; Kleessen, Sabrina; Neigenfind, Jost; Basler, Georg; Nikoloski, Zoran

2016-01-01

Maintenance of functionality of complex cellular networks and entire organisms exposed to environmental perturbations often depends on concentration robustness of the underlying components. Yet, the reasons and consequences of concentration robustness in large-scale cellular networks remain largely unknown. Here, we derive a necessary condition for concentration robustness based only on the structure of networks endowed with mass action kinetics. The structural condition can be used to design targeted experiments to study concentration robustness. We show that metabolites satisfying the necessary condition are present in metabolic networks from diverse species, suggesting prevalence of this property across kingdoms of life. We also demonstrate that our predictions about concentration robustness of energy-related metabolites are in line with experimental evidence from Escherichia coli. The necessary condition is applicable to mass action biological systems of arbitrary size, and will enable understanding the implications of concentration robustness in genetic engineering strategies and medical applications. PMID:27759015
T-cell movement on the reticular network.

PubMed

Donovan, Graham M; Lythe, Grant

2012-02-21

The idea that the apparently random motion of T cells in lymph nodes is a result of movement on a reticular network (RN) has received support from dynamic imaging experiments and theoretical studies. We present a mathematical representation of the RN consisting of edges connecting vertices that are randomly distributed in three-dimensional space, and models of lymphocyte movement on such networks including constant speed motion along edges and Brownian motion, not in three-dimensions, but only along edges. The simplest model, in which a cell moves with a constant speed along edges, is consistent with mean-squared displacement proportional to time over intervals long enough to include several changes of direction. A non-random distribution of turning angles is one consequence of motion on a preformed network. Confining cell movement to a network does not, in itself, increase the frequency of cell-cell encounters. Copyright © 2011 Elsevier Ltd. All rights reserved.
Fuzzy Neural Network-Based Interacting Multiple Model for Multi-Node Target Tracking Algorithm

PubMed Central

Sun, Baoliang; Jiang, Chunlan; Li, Ming

2016-01-01

An interacting multiple model for multi-node target tracking algorithm was proposed based on a fuzzy neural network (FNN) to solve the multi-node target tracking problem of wireless sensor networks (WSNs). Measured error variance was adaptively adjusted during the multiple model interacting output stage using the difference between the theoretical and estimated values of the measured error covariance matrix. The FNN fusion system was established during multi-node fusion to integrate with the target state estimated data from different nodes and consequently obtain network target state estimation. The feasibility of the algorithm was verified based on a network of nine detection nodes. Experimental results indicated that the proposed algorithm could trace the maneuvering target effectively under sensor failure and unknown system measurement errors. The proposed algorithm exhibited great practicability in the multi-node target tracking of WSNs. PMID:27809271
A Hybrid Adaptive Routing Algorithm for Event-Driven Wireless Sensor Networks

PubMed Central

Figueiredo, Carlos M. S.; Nakamura, Eduardo F.; Loureiro, Antonio A. F.

2009-01-01

Routing is a basic function in wireless sensor networks (WSNs). For these networks, routing algorithms depend on the characteristics of the applications and, consequently, there is no self-contained algorithm suitable for every case. In some scenarios, the network behavior (traffic load) may vary a lot, such as an event-driven application, favoring different algorithms at different instants. This work presents a hybrid and adaptive algorithm for routing in WSNs, called Multi-MAF, that adapts its behavior autonomously in response to the variation of network conditions. In particular, the proposed algorithm applies both reactive and proactive strategies for routing infrastructure creation, and uses an event-detection estimation model to change between the strategies and save energy. To show the advantages of the proposed approach, it is evaluated through simulations. Comparisons with independent reactive and proactive algorithms show improvements on energy consumption. PMID:22423207
A hybrid adaptive routing algorithm for event-driven wireless sensor networks.

PubMed

Figueiredo, Carlos M S; Nakamura, Eduardo F; Loureiro, Antonio A F

2009-01-01

Routing is a basic function in wireless sensor networks (WSNs). For these networks, routing algorithms depend on the characteristics of the applications and, consequently, there is no self-contained algorithm suitable for every case. In some scenarios, the network behavior (traffic load) may vary a lot, such as an event-driven application, favoring different algorithms at different instants. This work presents a hybrid and adaptive algorithm for routing in WSNs, called Multi-MAF, that adapts its behavior autonomously in response to the variation of network conditions. In particular, the proposed algorithm applies both reactive and proactive strategies for routing infrastructure creation, and uses an event-detection estimation model to change between the strategies and save energy. To show the advantages of the proposed approach, it is evaluated through simulations. Comparisons with independent reactive and proactive algorithms show improvements on energy consumption.
Spatio-temporal propagation of cascading overload failures in spatially embedded networks

PubMed Central

Zhao, Jichang; Li, Daqing; Sanhedrai, Hillel; Cohen, Reuven; Havlin, Shlomo

2016-01-01

Different from the direct contact in epidemics spread, overload failures propagate through hidden functional dependencies. Many studies focused on the critical conditions and catastrophic consequences of cascading failures. However, to understand the network vulnerability and mitigate the cascading overload failures, the knowledge of how the failures propagate in time and space is essential but still missing. Here we study the spatio-temporal propagation behaviour of cascading overload failures analytically and numerically on spatially embedded networks. The cascading overload failures are found to spread radially from the centre of the initial failure with an approximately constant velocity. The propagation velocity decreases with increasing tolerance, and can be well predicted by our theoretical framework with one single correction for all the tolerance values. This propagation velocity is found similar in various model networks and real network structures. Our findings may help to predict the dynamics of cascading overload failures in realistic systems. PMID:26754065
Rural women and violence situation: access and accessibility limits to the healthcare network.

PubMed

Costa, Marta Cocco da; Silva, Ethel Bastos da; Soares, Joannie Dos Santos Fachinelli; Borth, Luana Cristina; Honnef, Fernanda

2017-07-13

To analyze the access and accessibility to the healthcare network of women dwelling in rural contexts undergoing violence situation, as seen from the professionals' speeches. A qualitative, exploratory, descriptive study with professionals from the healthcare network services about coping with violence in four municipalities in the northern region of Rio Grande do Sul. The information derived from interviews, which have been analyzed by thematic modality. (Lack of) information of women, distance, restricted access to transportation, dependence on the partner and (lack of) attention by professionals to welcome women undergoing violence situation and (non)-articulation of the network are factors that limit the access and, as a consequence, they result in the lack of confrontation of this problem. To bring closer the services which integrate the confrontation network of violence against women and to qualify professionals to welcome these situations are factors that can facilitate the access and adhesion of rural women to the services.

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